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Neighborhood, Housing, and Women's Health Disparities

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PAGE 1

NEIGHBORHOOD, HOUS ING AND WOMENS HE ALTH DISPARITIES By DINAH PHILLIPS WELCH A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2006

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Copyright 2006 by Dinah Phillips Welch

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iii ACKNOWLEDGMENTS First and foremost, I want to acknowle dge my family, especially my husband, David, who has been an unwavering source of support throughout my doctoral education. In addition to providing emotional support, he has served as both a re search assistant and laboratory consultant. His advice during key ti me points in my research helped me to produce quality cortisol results. Dave, I am tr uly fortunate to have such a supportive and loving husband. I am grateful to my children who also supported me through this process with humor and love that I will always cherish. Th eir patience, understa nding and support kept me going through the tough times. Next, I want to thank Dr. Shawn Kneipp for her mentorship and guidance over the last four years. She has been a source of in spiration since our first meeting. Dr. Kneipps high standards are admirable and serve her st udents well in preparing them to be good nurse scientists. I thank her for taking the ti me to be a conscientious and caring mentor. I gratefully acknowledge my dissertati on committee Dr. Nabih Asal, Dr. Kristen Larsen, Dr. Ichan Huang, and Dr. Sandra Seymour for their expertise and advice throughout this process. Finally, I want to thank th e National Institutes of He alth, National Institute of Nursing Research and the Univer sity of Florida, College of Nursing for partial funding of this project.

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iv TABLE OF CONTENTS page ACKNOWLEDGMENTS.................................................................................................iii LIST OF TABLES............................................................................................................vii LIST OF FIGURES.........................................................................................................viii ABSRACT........................................................................................................................ .ix 1 INTRODUCTION........................................................................................................1 Background and Problem Statement............................................................................1 Theoretical Framework.................................................................................................4 Problem Statement........................................................................................................5 Purposes of the Study...................................................................................................5 Hypotheses....................................................................................................................6 Limitations....................................................................................................................6 Significance..................................................................................................................7 2 LITERATURE REVIEW.............................................................................................9 Socioeconomic Position and Health.............................................................................9 Socioeconomic Position and Chronic Disease Health Disparities......................14 SEP and Womens Health Disparities.................................................................15 Neighborhood SEP and Health...................................................................................17 Neighborhoods and Health.........................................................................................18 The Concept of Neighborhood............................................................................18 Neighborhood Disadvantage, Disorder and Health.............................................20 Neighborhood Social Cohesion and Health........................................................22 Neighborhood Aspects of Subsidized H ousing: Implications for Womens Health...............................................................................................................23 Housing and Health....................................................................................................25 Housing and Womens Health.............................................................................26 Housing Policy and Health..................................................................................27 What We Know and Gaps in Knowledge and Research.....................................31 SES and Chronic Stress: The Role of th e Hypothalamic-Pituitary-Adrenal (HPA) Axis in Chronic Disease..........................................................................................32 HPA Axis Physiology and its Role in Chronic Disease Development.......................34

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v Relationships Among Neighborhood Character istics, Housing, Chronic Stress, and Health...............................................................................................................37 Summary.....................................................................................................................38 3 METHODOLOGY.....................................................................................................40 Theoretical Framework...............................................................................................40 Research Design.........................................................................................................43 Population and Sample........................................................................................43 Setting..................................................................................................................46 Human Subjects Protection.................................................................................46 Inclusion and Exclusion Criteria.........................................................................46 Research Variables and Instruments...........................................................................48 Major Study Variables................................................................................................48 Neighborhood Characteristics....................................................................................49 Neighborhood Economic Disadvantage..............................................................49 Neighborhood Disorder.......................................................................................50 Neighborhood Stress: Crime Exposure...............................................................50 Neighborhood Social Cohesion...........................................................................51 Housing.......................................................................................................................52 Housing Satisfaction (Per ceived Housing Quality)....................................................52 Stress......................................................................................................................... ..52 Perceived Stress...................................................................................................53 Unfair Treatment and Discrimination.................................................................53 Chronic Stress......................................................................................................54 Psychological Distress................................................................................................55 Depression...........................................................................................................55 State-Trait Anxiety..............................................................................................55 General Health............................................................................................................56 Salivary Cortisol (SC).................................................................................................56 Individual Social Support...........................................................................................61 Study Protocol............................................................................................................61 Statistical Analyses.....................................................................................................63 Statistical Analysis Approach..............................................................................63 Specific Aim 1.....................................................................................................64 Issues of Multicollinearity...................................................................................65 Seemingly Unrelated Regression........................................................................66 Multi-level Analysis............................................................................................67 Specific Aim 2.....................................................................................................67 Specific Aim 3.....................................................................................................68 Missing Data........................................................................................................68 Handling Missing Cortisol Data..........................................................................69 Handling Missing Survey Data...........................................................................70 4 RESULTS...................................................................................................................73 Descriptive Results.....................................................................................................73

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vi Description of the Sample...................................................................................73 Neighborhood Characteristics of the Sample......................................................74 Stress, Psychological Distress, Heal th, and Salivary Cortisol Sample Characteristics..................................................................................................76 Specific Aim 1: Associations among Neighborhood Character istics, Stress, Psychological Distress, Hea lth and Salivary Cortisol......................................77 Bivariate Analyses of Neighborhood Ch aracteristics, Housing Satisfaction, Stress, Depression, State Anxiety, Health and Salivary Cortisol....................78 General Health, Neighborhood Characte ristics, Stress, and Psychological Distress.............................................................................................................79 Neighborhood and Individual Leve l Effects on State Anxiety...........................80 Depression, Neighborhood Char acteristics and Stress........................................81 Seemingly Unrelated Regression Anal ysis of Anxiety and Depression Regression Equations.......................................................................................83 Specific Aim 2: Differences in Ne ighborhood Characteristics by Housing Subsidy Type...................................................................................................87 Specific Aim 3: Differences in Stress Psychological Distress, Health and Salivary Cortisol by Housing Type..................................................................87 5 DISCUSSION AND RECOMMENDATIONS.........................................................90 Major Findings............................................................................................................90 Sample Characteristics........................................................................................91 Specific Aim 1: Relationships between Neighborhood Characteristics Stress, Psychological Distress, Hea lth and Salivary Cortisol......................................92 Neighborhood level hypotheses...................................................................92 Discussion Regarding Indi vidual Level Hypotheses...................................94 Discussion Regarding Neighborhood E ffects on Psychological Distress, Health and Salivary Cortisol.....................................................................98 Conclusions.........................................................................................................98 Specific Aims 2: Differences in Neighborhood Characteristics, Housing Satisfaction, by Housing Subsidy Type...........................................................99 Specific Aim 3: Differences in Stress, Psychological Distress, Health and SCAUCg by Housing Type................................................................................102 Study Limitations......................................................................................................103 Implications for Public Health Nursing Research and Practice................................104 APPENDIX CONSTRUCTS, CONCEPTS,AND OPERATIONAL MECHANISMS.......................107 LIST OF REFERENCES.................................................................................................110 BIOGRAPHICAL SKETCH...........................................................................................127

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vii LIST OF TABLES Table page 3-1 Skewness and Kurtosis for Study Variables............................................................64 3-2 Collinearity Diagnostics for Explanatory Variables................................................66 3-3 Example of Missing Cortisol Data for One Participant...........................................70 4-1 Sample Demographic Profile: (n=67)......................................................................74 4-2 Sample Description of Neighborhood Characteristics.............................................75 4-3 Stress, Psychological Distress, H ealth and Salivary Cortisol Scores.......................76 4-4 Salivary Cortisol Sc ores by Day and Time..............................................................76 4-5 Mean Psychological Distress and Genera l Health Scores Compared to National Norms.......................................................................................................................77 4-6 Correlations between Neighborhood Char acteristics, Housi ng Satisfaction, Psychological Distress, General He alth, and Salivary Cortisol...............................78 4-7 Bivariate Regression Re sults for General Health.....................................................79 4-8 Bivariate Regression Re sults for State Anxiety.......................................................80 4-10 Neighborhood, Psychosocial, and Indi vidual Effects on Depression (CES-D).......81 4-11 Regression Results for Neighborhood and Psychosocial Measures as Predictors of Depression............................................................................................................83 4-12 Seemingly Unrelated Regression Analys is of Anxiety and Depression Equations.84 4-13 Simple Regression SC-AUCg..............................................................................85 4-14 Multiple Regression of Individual Level Characteristics on SC-AUCg..................85 4-15 GEE Population Averaged Model of Effects of Neighborhood Characteristics, Stress and Psychological Dist ress on Salivary Cortisol...........................................86

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viii LIST OF FIGURES Figure page 3-1 Socio-biological Model............................................................................................42 4-1 Neighborhood Economic Disadvantage (NED) for all Participants........................75 4-2 Neighborhood Economic Disadvantage (NED) by Housing Subsidy Type............88

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ix Abstract of Dissertation Pres ented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy NEIGHBORHOOD, HOUS ING AND WOMENS HE ALTH DISPARITIES BY Dinah Phillips Welch August 2006 Chair: Shawn Kneipp Major Department: Nursing Humans do not exist in a vacuum; as such, health and illness do not occur entirely as the result of individual behaviors. People are intrinsi cally both social and physical beings and are therefore affected by myriad social factors. Lived experiences vary tremendously depending on the area one inhabi ts. The environment constitutes different contextual aspects that shape ones daily expe riences, the social and physical attributes of neighborhoods and housing areat the same tim eboth a product and mediator of larger social, economic, and political forces. Despite the numerous studies th at have established a clear relationship among neighborhood di sadvantage, housing, and health, the mechanisms by which neighborhoods and housing impact health remain unknown. Furthermore, a more thorough understandi ng of how Section 8 and public housing environments differ is critical, given that th e policy intent behind s ection 8 housing is to reduce pockets of poverty and its sequelae th at have been observe d in public housing.

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x The primary purposes of this study were to examine the relationships among neighborhood characteristics, perceived st ress, psychological distress, and salivary cortisol secretion among female heads of hous ehold with children of low socioeconomic position (SEP) and to determine the differen ces in neighborhood char acteristics, housing satisfaction, perceived stress, ps ychological distress, and saliva ry cortisol levels in low SEP female heads of hous eholds with children. Regression analyses indicate that nei ghborhood characteristics such as disorder, crime exposure and collective e fficacy are associated with increased levels of stress, psychological distress, and general health. However when individua l level factors are added to models, neighborhood characteristics no longer have an effect on depression, anxiety, health or salivary cortisol in this group of women. Mann-Whitney U tests showed a significant difference in neighbor hood economic disadvantage by housing type. Women living in section 8 housing units were located in more economically advantaged areas (z = -2.552, p<0.05) than women liv ing in public housing. There were no differences in neighborhood disorder, exposure to crime, nor collective efficacy. Future studies that replicate this one using a much larger random sa mple are needed to provide a better understanding of the impact of neighborhoods and housing on health.

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1 CHAPTER 1 INTRODUCTION This chapter introduces the backgrou nd, theoretical framework, and problem statement. The study purposes and associated hypotheses are stated. Limitations are acknowledged and the significance of the study is presented. Background and Problem Statement Women and children comprise the greatest proportion of people living in poverty in the United States (U. S.). As of 2004, the offi cial U. S. poverty rate was 12.7%, which is up from 12.5% in 2003 (U. S. Census Bur eau, 2005). In 2004, the poverty rate for families was 10.2% comprising almost 7.9 million families. Female-headed families suffer from poverty disproportionately, with 28.4% (nearly 4 million families) living in poverty compared to 5.5% of married-couple fa milies (3.2 million families) (Institute for Research on Poverty, 2005). Socioeconomic position (SEP) is defined as the social and economic factors that influence what position(s) individuals and gr oups hold within the structure of society (Lynch, 2000), and low SEP has repeatedly been associated with poor health outcomes. For example, the seminal Whitehall study of Britis h civil servants showed that a gradient in mortality runs across the social hierarc hy from the bottom employment grades to the top (Marmot, 2003; Marmot et al 1991). Disparities in health for chronic conditions are more pronounced among women than men, and a steeper gradient in disparate outcomes exists at the lower end of the economic stra ta than at the top (Lynch, 2000; Marmot and Wilkinson, 1999). Studies show, for example, that womens SEP is strongly and

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2 inversely related to cardiovascular dis ease (CVD) mortality (Wilkinson, 1996). Poor women are four to five times as likely to rate their health as fair or poor than women with higher incomes, and middle-aged women in the highest SEP group can expect to live 2.7 to 3.8 years longer than those in the lowest income group (Robert, 1998). Moreover, there is evidence that the SEP-related disparities of chronic diseases with some of the highest prevalence, morbidity, and mortality rates among women have actually widened over the past several years desp ite efforts to close the gap (Wilkinson, 1997). Housing costs account for the largest expend iture for most families and serve as an indicator of ones social and economic sta nding within society. Disparities in housing problems are suffered disproportionately in our society and parallel income-related health disparities. The broad term housing problems can be applied to a wide range of housing conditions considered to be sub-standard among develope d nations. As such, housing problems include conditions such as high co st burdens relative to income, overcrowding, poor conditions, and homelessness, among others. Currently, the U. S. is in the midst of an affordable-housing crisis. Affordable housing is defined as spending 30% or le ss of ones income on housing (Green and Malpezzi, 2003). However, few U. S. citizen s are able to pay such a small amount for housing and many are financially burdened by its high cost. In 2001, one third of the nation (95 million people) had housing problem s. Two-thirds of the people with housing problems are low-income as defined by federa l policy (household income at or less than 80% of the area median). And poignantly, 32% of the low income people with housing problems were children (Tre kson and Pelletiere, 2004).

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3 To put the scope of housing problems on more familiar terrain, the number of people that experience housing problems ex ceeds those who lack health insurance twofold (Joint Center for Housing Studies of Harvard University, 2004). In addition to unaffordable housing, crowding is on the rise and nearly 2 milli on households live in over-crowded units (Joint Center for Hous ing Studies of Harvard University, 2004). Nationally, 47% of renter households lived in unaffordable housing in 2003, which is a 2% increase from 2002. Studies are beginning to demonstrate that neighborhood and housing characteristics are independent determinants of health (Kington and Smith, 1997; Steptoe, Lundwall, and Cropley, 2000). An estimated 72% of all households receiving rental housing subsidiesincluding Section 8 (S8) and pub lic housing (PH)are headed by women, and many are concentrated in lower soci oeconomic areas (Adler and Ostrove, 1999) which have higher rates of chronic stress, anxiety, depression and CVD (Kington and Smith, 1997; Steptoe and Marmot, 2002). Increa singly, studies have shown that chronic stress is associated with the development of chronic illnesses such as insulin resistance, depression, and CVD (Berkman and Kawach i, 2000; Lundberg, 1999). As a result of these studies, researchers now hypothesize that arousal of the hypothalamic-pituitaryadrenal (HPA) axis through ch ronic exposure to stressors in the social and physical environment (e.g., neighborhood and housing-relate d stressors) results in wear and tear on physiological systems, contributing to the development of chronic diseases (Wilkinson, 1997) To further study this phenomenon, epidem iologists have begun employing multilevel analyses that include both aggregateand individual-level variables to examine

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4 determinants of SEP-related health disparit ies. An ecological-to-bi ological conceptual framework called for within public health and nursing parallels the conceptual and methodological approaches proposed in this study. Thus, this study examines whether neighborhood characteristics a nd health outcomes differ by housing subsidy type (i.e., section 8 and public housing) and whether neighborhood characteristics may contribute to SEP-related health disparities among women through chronic stress-physiological mechanisms. Theoretical Framework Nancy Kriegers ecosocial theory and Bru ce McEwens allostatic load model guide this research. Ecosocial theory seeks to expl ore the social biologi cal interface through which environmental factors affect health (Krieger and Davey-Smith, 2004) and calls for incorporating the use of th e concept embodiment in orde r to capture how social influences (e.g., housing and the built envir onment) become literally embodied into physiological characteristics that influence health. Allostatic load is based on the premise that physical and psychological stressors occur within a social and economic context, and that there is individual variation in the stre ss appraisal process as well as behavioral and emotional coping mechanisms to th e perceived stressor (McEwen, 1999). Combining these two theories into a soci o-biological model allows researchers to simultaneously explore social and biological variables advancing scientific knowledge as it relates to the understanding of the social-b iological interface th at may be mediating relationships among environments (i.e., ne ighborhoods), chronic stress, and health. Details on ecosocial theory and allostatic load, and their releva nce to this study are presented in Chapter. 3.

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5 Problem Statement Despite the numerous studies that have established a clear relationship among neighborhood disadvantage, housing, and health, the mechanisms by which neighborhoods impact health remain unknown. Sp ecific to the development of a research trajectory in this area, and adding to the body of knowledge regarding neighborhood effects on health, determining what neighbor hood and housing characteristics may most affect low SEP womens health risks mu st precede both targeted neighborhood/housing aggregate-level interventions and individual-level interventi ons within the highest risk neighborhoods. More research is needed that incorporates a socio-biological approach in order to determine the mechanisms by wh ich neighborhoods get under the skin and contribute to the developm ent of chronic disease. Purposes of the Study The specific aims of this study are as follows: 1. To determine the relationships among neighborhood characteristics, perceived stress, unfair treatment psychological distress, and salivary cortisol secretion among low SEP female heads of household with children; 2. To determine the differences in neighborhood characte ristics of two subsidy housing types, specifically s ection 8 and public housing, in which low SEP female heads of households with children live; and 3. To examine the differences in housin g satisfaction, perceived stress, unfair treatment psychological distress, and neuroendocrine regulation, specifically cortisol secretion, in low SEP female heads of households with children by housing subsidy type (i.e., section 8 and public housing).

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6 Hypotheses The following hypotheses are invest igated in this dissertation 1. Significantly higher levels of crime rates, neighborhood disorder, neighborhood stress, and neighborhood disadvantage will be positively associated with salivary cortisol. 2. Public housing sites will have sign ificantly more neighborhood disorder, greater levels of neighborhood disa dvantage, higher levels of neighborhood stress more perceived cr ime rates, higher objective crime rates, and lower levels of collective efficacy than S8 sites. 3. Women living in PH will experience significantly lower levels of housing satisfaction, have higher levels of pe rceived stress, psychological distress, and greater alterations in salivary cortisol secretion than women living in S8. Limitations This study has several limitations and ther efore the findings s hould be interpreted with caution. First, non-probability sampling limits the generalizability of this study to other populations. Using a random sample of neighborhoods and a random sample of participants from each neighborhood would im prove the generalizability at the population level and is vital to conduc ting epidemiological studies. Second, the small sample size may account for the lack of significant findings among neighborhood characteristics, psychological distress, health and salivary co rtisol. Third, the rese arch design could be strengthened by utilizing a l ongitudinal design that collects physiological measures over several years as opposed to the cross-sectiona l repeated measures design used in this study. Finally, most of the measures of neighborhood characteristics were based on perceptions of the study partic ipants. Using more objective m easures of crime rates and neighborhood disorder would prove useful in future studies. However, perceptions of ones environment are important factors to c onsider when investig ating behavioral and physiological responses to stressors. The effect of the social environment results from the

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7 fact that the brain and bo dy are constantly communicati ng via the autonomic nervous system and the endocrine and immune syst ems (McEwen, 2005) Thus, the regulation of stress-related mediators is de pendent upon how a potential stresso r is perceived as well as the individuals capacity to cope with that stressor. Significance Housing is an important social determin ant of health, and housing policy in the U.S. disproportionately affects women living in poverty. An increas ed understanding of relationships among neighborhood, housing, and hea lth has the potential to significantly improve individual and population health. The data from this study in accordance with other epidemiological studies in this ar ea indicate that neighborhood disorder and exposure to crime are important factors to consider regarding womens health. In line with both the Healt hy People 2010 (U. S. Departme nt of Health and Human Services, 2005) goals and the National Institut es of Nursing Research priorities, nursing has a commitment to reducing health dispar ities among disadvantaged groups through its scientific investigations. This research is consistent with both of these emphases within the public health arena and nursing. Moreover, there is an emerging interest in the relation between the built environment (i.e ., neighborhoods and housing) and health in the field of urban planning, Prof essionals from this field are partnering with public health practitioners and others to improve ne ighborhood conditions through multidisciplinary investigations that aim to improve the pub lics health by estab lishing healthy cities through more effective public policy (N orthridge, Sclar, and Biswas, 2003). Future research in womens health dispar ities must include examination of social and contextual factors that mediate SEP and health in order to develop population-based interventions (Fleury, Keller, and Murdaugh 2000). Specific to the development of a

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8 research trajectory in this area, and adding to the body of knowledge regarding neighborhood effects on health, determ ining what neighborhood and housing characteristics may most affect low SEP wome ns health risks must precede both targeted neighborhood/housing aggregate-level interven tions and individuallevel interventions within the highest risk neighborhoods. Furthermore, lacking in the literatu re is knowledge rega rding whether the experiences of women living in S8 housing differ from those in public housing, and how neighborhood characteristics associated with each of these programs affect health. Studies that discern whether home environm ent or neighborhood char acteristics of S8 housing differ from public housing in ways re levant to health are needed. A more thorough understanding of how S8 and public housing environments differ is critical, given that the policy intent behind S8 housing is to reduce the concentrated pockets of poverty and its sequelae that have been observed in public housing Knowledge gained from neighborhood, hous ing, and health research focusing on subsidized housing (i.e., public and section 8 housing) polic ies would provide valuable data from which to evaluate the impact of housing voucher and mobility programs on health. In addition, such knowledge can assist public health practitioners to secure financial resources for improving neighborhood conditions. The inclusion of bio-markers (such as cortisol, blood pressu re, and others) to test specif ic physiological mechanisms may provide more in-depth knowledge about physiological pathways that may be affected by social processes such as housing policies and neighborhood conditions and how they are embodied into physiological pr ocesses and thus produces illness (AcevedoGarcia et al 2004; Krieger and Davey-Smith, 2004).

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9 CHAPTER 2 LITERATURE REVIEW This chapter presents a literature review that concentrates on four major areas relevant to the study aims. The discussion be gins by presenting rele vant studies on the broad topic of the relationships among SEP and chronic disease health disparities, particularly as they relate to women. Then the discussion will become focused at the neighborhood level presenting study findi ngs that indicate how neighborhood characteristics contribute to chronic stress related health disparities. Nested within neighborhood are a variety of housing subsi dy types that may also impact health outcomes. This study focuses on federally subsidized Section 8 and public housing, therefore, a brief overview of subsidi zed housing policy, neig hborhood characteristics associated with subsidized housing, and a ssociations between housing and health are presented. Finally this review presents hypot hesized physiological mechanisms that may be affected when neighborhoods and housing serve as sources of chronic stress. This part of the discussion focuses on chronic stress effects on physiology, specifically the hypothalamic-pituitary-adrenal (HPA) axis and the development of chronic disease. Due to the extensive nature of the litera ture in the area of socioeconomic position and health, this section of the literature revi ew will focus on studies conducted in the United States and in England. Socioeconomic Position and Health In the past 20 years, research th at focuses on the relationship between socioeconomic position and health has grow n substantially. Some studies compare

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10 morbidity and mortality of different socio economic groups within individual countries, while others contrast health experiences across countries document the extent of inequalities, and explore possibl e explanations of differential health outcomes (Feinstein, 1993). Most studies of SEP and health ha ve focused on individual-level SEP (i.e., individual income, education, occupation), a nd the effects on broad health outcomes such as morbidity and mortality (Robert, 1998). In a review of the literature on SEP and health research published from 1970 to 1990, Feinstein reports findings from early seminal work and critiques the methodology of several studies conducted in the U. S. and England. For example, one study utilized two data sets the 1960 Matched Records St udy and the Chicago Area Study. The Chicago Area Study collected information on census tracts and will be discussed in the section on neighborhood SEP and health. The 1960 Matche d Records Study linked death certificates with census information on the educational attainment and house hold income for 340,000 individuals who died during May-August 1960 in the U. S. These findings show a strong inverse relationship among whites and nonwhites, females and males aged 25-64, between years of schooling and mortality in 1960. The difference in standardized mortality rates between the l east and best educated subgroups was at least 65% for each of the four classes (i.e., wh ite/non-white men and white/non -white females) (Feinstein, 1993). Furthermore, this study eluc idates the fact that the eff ects of education and income are largely independent of one another. Another important source of evidence supporting the SEP-health relationship comes from the Black Report which was published in 1980. In 1977 Sir Douglas Black and other researchers were a ppointed by the British Governme nt to assess the evidence

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11 on inequalities in health in the United Ki ngdom (U. K.). The Black Report assesses inequalities using a classi fication system of the Brit ish population in which the population is divided into six so cial classes including profes sional, intermediate, skilled nonmanual, skilled manual, partly skilled, and unskilled. Household status is determined by the occupation of the head of household (Feinstein, 1993). The findings from this study showed that in 1971, substantial mortality differentials existed in the U. K. and had in fact widened since 1930. In 1971, the mo rtality rate among men in the lowest occupational class (unskilled) was 9.88 per 1,000 as opposed to men in the highest class which was significantly lower at 3.98 per 1,000. The same trend was found among women as well. Women in the highest (i.e ., professional) occu pational class had a mortality rate of 2.15 per 1,000 while those in the lowest occu pational class had a mortality rate of 5.31 per 1,000 (Feinstein, 1993). There are several problematic methodological issues that have been identified in this area of research. First, the socioeconom ic indicators used in these early studies, particularly income, do not ade quately account for the possibili ty that poor health causes reduced income rather than low income resulting in poor health. In addition, many early studies use household income measures whic h for married households are generally the males income and therefore do not accura tely reflect the womans income or access to the household income. Thus, the income and health argument holds more validity when applied to men than when applied to women (Feinstein, 1993). Furthermore, these studies do not account for the impact of unpaid labor (i.e., household duties in addition to work) on womens health. Lastly, many resear chers in this area believe wealth as opposed to income to be the superior indicato r because the problem of reverse causality is

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12 less likely to affect household wealth, th an household income measures, primarily because household wealth accumulates over time and consequently is less affected by a single episode of illness (Berkman and Kawachi, 2000; Feinstein, 1993). After The Black Report was published an explosion of research in health inequalities followed. Much of the work expanded upon the approach used in The Black Report to include alternative datasets for more recent years. For example, Whitehead reviewed evidence from the 1979-83 decennial supplement that showed inequality in mortality rates across social clas ses was the same as, or slightly larger than before thus supporting evidence from the Black Report ev en after circumventing some of the methodological weaknesses in previous studi es (Feinstein, 1993). In a similar study, utilizing the same data, the researchers merg ed the social classes into two different groups manual and nonmanualand found si milar results that indicate a wide inequality in heart disease and lung cancer rates between the two groups (Marmot and McDowall, 1986). The more recent Whitehall I and II Studies of British civil servants conducted by Michael Marmot and colleagues provide further supporting evidence for the social inequality and health relationship (Willia ms and Collins, 1995). The Whitehall I Study examined mortality rates over 10 years among males aged 20-64. An inverse association between grade (level) of employment and mo rtality from coronary heart disease (CHD) and a range of other causes was observed. Me n in the lowest grade (i.e., messengers, doorkeepers, etc.) had three times the mortalit y rate than men in the highest grade (i.e., administrators) (Marmot, Shipley, and Rose, 1984). After controlling for standard risk factors such as hypertension, smoking, obesity, and physical inactivit y, the lowest grade

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13 worker still had a relative ri sk of 2.1 for CHD mortality co mpared to the highest grade worker (Marmot and Wilkinson, 1999). The Whitehall II study was designed to assess the effects of the social environment on health and the causes of soci al inequalities in health. More specifically, it investigates the role of stress on health and the extent to which stress might be involved in the social inequalities in health (Marmot, 2004). Th e study began in 1985 and included 10,308 male and female civil servants. Findings were c onsistent with the fi rst Whitehall study. Clear employment grade differences in health ri sk behaviors including smoking, diet, and exercise, economic and social circumstances and monotonous work characterized by low control and low satisfaction were present in both men and women (Marmot et al., 1991). Furthermore employment grade differences we re also associated with CHD (Marmot, Bosma, Hemingway, Brunner, and Stansfeld, 1997), metabolic syndrome and central obesity (Brunner, 2000). In addition to the well known Whiteha ll Studies described above, numerous studies, such as the Multiple Risk Fa ctor Intervention Trial, (Wilkinson, 1996) demonstrate that individual-lev el SEP disparities exist for many chronic diseases (Fleury, Keller, and Murdaugh, 2000; Kington and Sm ith, 1997; Marmot and Wilkinson, 1999). To date, much of the epidemiological rese arch in the area of individual-level SEP relationships to chronic disease has fo cused on CHD (Steptoe and Marmot, 2002). However, a consistent inverse relationship exists between SEP and multiple health indicators, such as CVD, diabetes, metabolic syndrome, arthritis, tuberculosis, chronic respiratory illness, malignant melanoma. (Adler and Ostrove, 1999), and lung and gastrointestinal cance rs (Feinstein, 1993).

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14 Socioeconomic Position and Chro nic Disease Health Disparities Socioeconomic position (SEP) has multiple dimensions that are associated with health. In virtually every dimension of me ntal and physical health, people in lowersocioeconomic groups have poorer health th an those in the middleor upper-income groups (Dalaker, 2001). Regardless of the SE P indicator used, (such as education, occupation, housing tenure, income), those w ho are worse off socioeconomically have worse health (Marmot and Wilkinson, 1999; Smith, Wentworth, Stamler, and Stamler, 1996). The gradient in morbidity and mortalit y by SEP for several chronic disease states has been documented for hundreds of years, observed consistently across studies, within and across countries and culture s, and persists and is actu ally increasing today (Lynch, 2000; Marmot and Wilkinson, 1999). For example, in a study that exam ined the extent of socioeconomic gradients in all-cause and cardiovascular disease (CVD) mortality among U. S. men and women aged 25-63 years fr om 1969 to 1998, the researchers found that area socioeconomic gradients in all cause and CVD mortality increased significantly over the last three decades (Singh and Siahpush, 2002). The researchers al so found that rates of all-cause and CVD morta lity among men in the lowest area socio-economic group were 42% and 30% greater in 1969-1970 and 73% and 79% greater in 1997-1998 respectively than those in the highest socioeconomic group. Women in the lowest area socioeconomic group had rates of all-cause and CVD mortality that were 29% and 49% greater in 1969-1970 and 53% and 94% greate r in 1997-1998 respectively than women in the highest area socioeconomic group. It is important to note, how ever, that health disparities are not observed solely at the ex treme ends of the socioeconomic spectrum. Morbidity and mortality risks increase along each incremental decrease in SEP (Wilkinson, 1996).

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15 The Matched Records Study conducted by K itagawa & Houser and published in 1975 as previously mentioned shows a pe rsistent inverse relationship between educational attainment and mortality from heart disease for both men and women and this relationship is stronger for both sexes ag ed 25 to 64 (Feinstein, 1993). However, the relationship between educational attainment and cancers is more complex. Cancers directly related to smoking such as lung cancer as well as, stomach, in testinal, and rectal cancers show a strong inverse relationship to education where other cancers (i.e., prostate and breast) do not (Feinstein, 1993). SEP and Womens Health Disparities Very little research has been conducted that specifically addresses womens SEP and health. Most research in the area of SEP and health has focused on middle-aged males or have included both males and fe males utilizing a cross-sectional descriptive methodology (Beebee-Dimmer, Lynch, Turrell, Lustgarten, Raghunathan, and Kaplan, 2004). One of the reasons that the relationshi p between womens SEP and health has not received much attention is because of the di fficulty in conceptualizing and measuring the class position of those w ithout direct labor market ties (McDonough, Walters, and Strohschein, 2002). Studies that have focused on womens health in relation to SEP have typically been limited to the quality of social roles, major institutionalized roles, and unequal distribution of resources while the socioec onomic dimensions of womens lives remain relatively unexplored (McD onough et al., 2002). Furthermore, a paucity of SEP and health related research has been conducte d among women residing in the United States (U. S.). Many of the studies reviewed on i ndividual-SEP and women s health originated in other industrialized co untries such as Canada (McDonough et al., 2002), Britain

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16 (Arber, 1997; Cooper, 2002; Martikainen, Lahelma, Marmot, Sekine, Nishi, and Kagamimori, 2004; Stafford, Bartley, Mitche ll, and Marmot, 2001) Spain (Artazcoz, Borrell, Benach, Cortes, and Rohlfs, 2004) a nd Finland and Japan (Martikainen et al., 2004). Despite the lack of research that focu ses specifically on womens SEP and health, studies in the U. S. have consistently s hown that women of lo wer SEP have a higher prevalence of diabetes (Centers for Disease C ontrol, 2000), report higher levels of social stress such as recent life events, major events, and death events (Turner and Avison, 2003), and have significantly poorer mental health (especially lone mothers with children) (Macran, Clarke, and Joshi, 1996). In addition, studies that have explored family demands, employment and health in women have found that among women workers of low educational level, family de mands showed a negative effect on health and health related behavior s (Artazcoz et al., 2004). As evidenced by this review, the relati onship between SEP and health is well known. What is missing from the literature is research on the mechanisms by which SEP affects womens health. While the precise m echanisms that mediate individual-level SEP and health are unknown, studies indicate it is not only access to material resources that are important, but that psychosoc ial factors contribute to health disparitie s, as well. For example, there is an interaction amon g high psychological demand/low control environments, an increased risk of psychologi cal strain, and physic al illness (Berkman and Kawachi, 2000; Lundberg, 1999; Marco, 200 0). Thus, in terms of individual-level measures of SEP, the pathways through wh ich SEP exerts its in fluence are not only through access to material resources (e.g., income or health care services), but may also

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17 operate via psychosocial mechanisms, as more fully described later in the literature review (see section on Hypothalamic-Pituitar y-Adrenal (HPA) axis Physiology and its Role in Chronic Disease Development). Furt hermore, the area in which one lives may also have a significant impact on health. As will be shown in the following sections, more research is being conducted that explores the relationship between neighborhoods and housing and their impact on health, which can account for some of the influence of SEP on health. Neighborhood SEP and Health In addition to research on individual-lev el SEP and health, epidemiologists are now exploring the SEP-health relationship from an aggregate level. Several studies have found residents of disadvantaged neighborhoods have worse self-reported health and more chronic health problems th an persons living in highe r SEP neighborhoods (Ross and Mirowsky, 2001). Studies are finding that neighborhood-level SEP indicators have a significant effect on health i ndependent of individual-leve l SEP (Bosma, Dike van de Mheen, Borsboom, and Mackenbach, 2001; R oy, Kerschbaum, and Steptoe, 2001). For example, in a study of 235 residents of 19 lower SEP neighborhoods, researchers found that neighborhood problems constitute sources of chronic stress that may increase the risk of poor health (Steptoe and Feldman, 2001). One of the problems in this area of resear ch is the diversity of indicators used to measure neighborhood level SEP. Some research ers have aggregated random samples of individual SEP indicators (i .e., income, education, and o ccupation to the neighborhood level) (Bosma et al., 2001). Others have us ed indicators such as percent unemployed, percent on public assistance, poverty rates, and percent households headed by females at the census tract level to determine th e neighborhood SEP level (Boardman, Finch,

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18 Ellison, Williams, and Jackson, 2001; Ross and Mirowsky, 2001). Krieger and colleagues found that among eight studies, four used differently categorized measures of neighborhood social class composition, education, poverty level, and unemployment rate, two used measures of average annual family income and two used da ta on median family income and educational level (Krieger et al. 2003). Despite the SEP measure used, the SEP-health disparities relationship persists above and beyond individual socioeconomic and behavioral factors and th erefore warrant further inves tigation (Steptoe and Feldman, 2001). Neighborhoods and Health The Concept of Neighborhood Neighborhood is a concept that has myriad definitions depending on the context in which it is used. A variety of criteria can be used to define neighborhood, including historical criteria, geographi cal criteria, residents pe rceptions, and administrative boundaries (Diez Roux, 2003). In addition, the si ze and definition of the geographic area may differ based on the outcome being studied. Neighborhood has been defined as a place wh ere people can easily walk over and interact with each other and as a social organization of people who reside within a geographical boundary (Galster, 2001). K earns and Parkinson (2001) describe neighborhood as existing at thr ee different levels. These in clude the home area (a 5-10 minute walk from ones home), locality, and urban district or re gion. The predominant function associated with each level of neighborhood is different. For example, the home area is where the psychosocial purposes of neighborhood is strongest with the main functions being, relaxation, connecting with others and fostering attachment and belonging. Localities or subdistricts (e.g., a public or section 8 housing complex)

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19 function as sites for residential activities a nd positioning oneself with in social networks. Regional aspects or the larger urban dist ricts of neighborhood (e.g., cities or towns) provide social and economic opportunities. Impor tantly, Kearns and Parkinson also note that at the second level of neighborhood (local ities), public or low-income housing can be subject to social exclusio n and discrimination imposed upon them by the larger urban district. The attributes comprising neighborhood are dynamic and are the result of past and current flows of households and resources in to and out of a defined geographic space (Kearns and Parkinson, 2001). For the purpose of this study, neighborhood will be defined according to Galsters (2001) defin ition that states, Neighborhood is the bundle of spatially based attributes associated with clusters of residences, sometimes in conjunction with other land uses (p. 2112). Th is definition accommodates the structural, class status, environmental, and social inter-active characteri stics of a neighborhood. Structural aspects include the type, state of repair, density, and lands caping of residential and non-residential buildings and the presence of sidewalks. Class status characteristics include income, occupation, and educationa l composition. The degree of noise pollution, land pollution, and the amount of litter are incl uded in the environmental characteristics of neighborhood. Finally, social-interactive ch aracteristics include local and family networks, degree of inter-household familiar ity, type and quality of interpersonal associations, participation in local organizati ons, and strength of in formal social control (Galster, 2001). Extant literature in this area of research has genera lly defined neighborhood using geographical or administrative boundaries. For example, studies conducted addressing

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20 neighborhood SEP and health outcomes typi cally identify neighborhood by census tract area (Boardman et al., 2001; Ross and Mirows ky, 2001) or combine census tracts into neighborhood clusters that ar e ecologically meaningful an d internally homogeneous (Sampson and Raudenbush, 1997). According to the U. S. Census Bureau, census tracts are small homogeneous areas in which similar population characterist ics, economic status and living conditions are found (T he Public Health Disparitie s Geocoding Project, 2004). As evidenced by this review, neighborhood can be defined in a variety of ways. Therefore, it is important to carefully consider the appropriate spatial scale in regards to the research questions and va riables to be studied (Macint yre, Ellaway, and Cummins, 2002). Neighborhood disadvantage is one example of a variable that is appropriately measured at the census tract level. On th e other hand, social networks may not be bounded by geographical boundaries and may eith er be much broader spatially or narrowly confined. Neighborhood Disadvantage, Disorder and Health Neighborhood disadvantage is a term used to describe socioeconomic position of a locality. Typically measured at the census tr act level, neighborhood di sadvantage is most frequently operationalized by developing an i ndex of various indicato rs such as family poverty, male unemployed, educational level, public assistance and female-headed households. Researchers have used percent poverty level, percent female heads of households, percent male unemployed, percen t on public assistance (Boardman et al., 2001; Sampson and Raudenbush, 1997), or prevalence of poverty and mother-only households, college educated residents a nd homeownership (Ross and Mirowsky, 2001). Economically disadvantaged neighbor hoods are characterized by high poverty rates. Subsidized and other lo w-income housing units are freque ntly concentrated in these

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21 high poverty areas. Neighborhood disadvantage has been positively related to higher levels of stress, lower social resources, and higher levels of anxiety and depression (Boardman et al., 2001). Studies show that neighborhood disadvantag e in the U. S. is associated with increased levels of anxiety and depression among adolescents (Aneshensel and Sucoff, 1996), discrimination in the workplace (Kirschenman and Neckerman, 1991), low birthweight (Buka, Brennan, Rich-Edwards, and Raudenbush, 2003; Pearl, Braveman and Abrams, 2001) and heart disease (Diez Roux, Merkin, Arnett, Chambless, Massing, Nieto, Sorlie, Szklo, Tyroler, and Watson, 2001; Sundquist, Malmstrom, and Johansson, 1999). Furthermore, people living in economi cally disadvantaged neighborhoods have reported more frequent experiences of unfair treatment (Schulz, Williams, Israel, Becker, Parker, Sherman, and Jackson, 2000), higher leve ls of substance abuse (Boardman et al., 2001), and higher levels of neighborhood disorder (Ross and Mirowsky, 2001). Neighborhood disorder is a concept that includes both the physical and social aspects of a neighborhood. Visible signs of physi cal disorder include hi gh levels of noise, dirtiness, abandoned and run-down buildi ngs. Vandalism and graffiti are common in these areas. Social disorder includes higher crime rates and signs such as fights and trouble among neighbors, the presence of peopl e hanging out on the streets, drinking and taking drugs (Ross and Mirowsky, 1999). Neighborhood disorder can be seen as a chronic stressor among urban communities that can potentially affect health in a variety of ways. For example, perceptions of higher neighborhood disorder have been linked to gr eater depressive symptoms after controlling for baseline depressive symptoms (Latki n and Curry, 2003). Ross and Mirowsky (2001)

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22 found that people living in disadvantaged ne ighborhoods with high levels of perceived disorder have higher levels of fear, report mo re chronic conditions and worse health and physical functioning. These studies do not include physiological biomarkers that would illuminate the mechanisms by which neighborhood stressors im pact mental and physical health. Fear stimulates the release of epinephrine and norepinephrine, followed by the release of cortisol (Ross and Mirowsky, 2001). Chronic release and exposure to these hormones have been associated with a variety of illnesses such as hypertension (HTN), hypercholesterolemia, atherosclerosis, and hyperglycemia (McEwen, 2000). Furthermore, little is known on how neighbor hood social cohesion and soci al networks may mediate the impact of neighborhood disadvantage and disorder on health. Neighborhood Social Cohesion and Health Social cohesion is a new construct in public health research believed to mediate the relationship between neighborhood SEP and healt h. It has been studied predominantly as an important neighborhood characteristic a nd has been clearly differentiated from individual social support in that it re presents trust among people with some geographically defined boundary where one lives. Kawachi and co lleagues (1997) found social cohesion explained 58% of the vari ance of all-cause ageand SEP-adjusted mortality, and for 15%-20% of the variance in other CVD mortality. Thus, the role of neighborhood social cohesion in modulating chronic stress-physio logical mechanisms believed to contribute to health dispar ities among women deserves further study. However, the concept of social cohesion is wrought with multiple and confusing definitions. Authors frequently define social capital and social cohesion in much the same way (Kawachi, Kennedy, and Prothrow-Stith, 1997). For example, Kawachi has used the

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23 same indicators of social capital to define and measure social cohesion in different studies (Kawachi, Kennedy, Gupta, and Prothr ow-Stith, 1999). Both social cohesion and social capital have been defined as the le vel of trust between c itizens of a community, norms of reciprocity and partic ipation in civic organizations that cooperate for mutual benefit (Kawachi, Kennedy, and Glass, 1999). Fo rrest and Kelly (2001) describe social cohesion as being about getting by and ge tting on at the more mundane level of everyday life (p. 2127). While social phenomenon within nei ghborhoods such as those represented by social cohesion are potentially relevant areas for intervention to improve health, nurse scholars (Drevdahl, Kneipp, Canales, and Do rcy, 2001) and others (Buka et al., 2003; O'Campo, 2003) have urged caution in a ssuming increasing social cohesion is a simplistic or complete remedy for reducing the health disparities observed to occur among neighborhoods with more or less co hesion. Nonetheless, when considering one (of several) contributing fact ors relevant for examining me chanisms underlying health disparities, the consistency and magnitude of associations observed to date deem it a worthwhile concept to inves tigate. For the purposes of this study a socially cohesive neighborhood is defined as th e extent of trust and soci al interaction within the neighborhood (Beauvais and Jenson, 2002; B uka et al., 2003; Sampson and Raudenbush, 1997). Neighborhood Aspects of Subsidized Housin g: Implications for Womens Health Nested within neighborhoods are a variety of housing types such as single-family and multi-family units, owned versus rental housing as well as subsidized housing. High poverty neighborhoods tend to have more low-in come subsidized rental housing units such as public and section 8 housing (Pendall 2000). Public housing (PH) consists of

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24 housing units owned and operated by the gove rnment and typically houses very lowincome families. PH residents pay rent based on income with a minimum of $25.00 to $50.00 up to 30% of their monthly income (less deductions allowed by regulations) (U. S. Department of Housing and Urban De velopment, 2003b). Section 8 housing is a voucher program in which recipients look fo r rental housing in the private market. Recipients of S8 contribute approximately 30% of their monthly income toward housing costs with S8 programs paying the remainde r of a defined payment standard (U. S. Department of Housing and Urban Developm ent, 2003a). Nationally, only 14.8% of S8 voucher recipients live in high poverty nei ghborhoods (Turner, P opkin, and Cunningham, 1999), however, while 53.6% of PH reside nts live in high po verty neighborhoods. In the United States, more than 5 milli on families are living in substandard housing (Bashir, 2002). Despite often-deplorable conditions, housing is often the highest expenditure for poor families. Increases in fa ir market rent (gross rent estimates for a specified area that include shelter cost a nd utilities except tele phones) are far exceeding increases in income, particularly among low-in come families. When families are forced to spend most of their income on housing, ot her important needs such as food, clothing, health care, and emotional stability suffer (Bashir, 2002). Approximately 4.8 million subsidized housi ng units are available in the U.S., with 2.4 million households participating in th e Section 8 program, 1.3 million households living in public housing units, and the rema ining 1.1 million units comprised of other types of housing assistance (U. S. Departme nt of Housing and Urban Development, 2002). Of all available subsidized units in the U.S., 96% are occupied. The occupied units are comprised of 58% minority households an d 70% female-headed households such as

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25 single-mother households and elderly women liv ing alone (U. S. Department of Housing and Urban Development, 1998). Housing and Health Decent, affordable housing not only impacts i ndividual and family health; it is also the building block of healthy neighborhoods, sh aping the quality of life in communities. Improved housing can lead to better outcomes for individuals and society at large. The relationship between housing and health has b een a long-standing issu e in the field of public health. As early as 1872 in a series of essays entitled The Housing Question, Freidrich Engels discussed the relationshi p between housing conditions and poor health. He argued that the conditions of the poor, working class ar eas in cities viewed as breeding grounds for epidemics could not be ignored without impunity. While the conditions creating the kind of infectious epid emics Engels addressed have been brought under control in todays industrialized countries and cities, the spatial concentration of socioeconomic groups is still observable (Dunn, 2000). Extant research on housing and health has b een mainly concentrated in four areas: 1) the disadvantage of individuals who are already in poor health in the housing market and their self-selection into substandard hous ing conditions, which may in turn account for any observed association between poor housi ng and poor health; 2) health status and access to health care for homeless persons; 3) pathological aspects of dwellings as the presumed cause of both physical and mental health outcomes, and 4) studies that specifically examine the stress es associated with unaffordab le and/or inadequate housing (Dunn, 2000). Regarding physical health, the literature provides evidence on associations among overcrowding, dampness and mold, indoor po llutants, infestations, and inadequate

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26 heating and infectious respiratory diseases, asthma, rhinitis, eczema, and heart disease (Marsh, Gordon, Heslop, and Pantazis, 2000). Ot her studies have shown relationships between stress, mental health, and housing. Fo r example, in a study on housing stressors, social supports and psychological distress, res earchers revealed that housing stressors are significantly associated with ps ychological distress and that living in substandard housing is an independent and added source of stress to the lives of people with lower incomes (Smith, Smith, Kearns, and Abbot 1993). Missing from the lite rature is research on the mechanisms by which housing affect s physical and mental health. Housing and Womens Health Inequalities in womens hea lth that parallel income inequalities are related to housing conditions in which women live. The negative effects of pove rty or near-poverty on health are often mediated or reinforced by substandard housing. In one case study, a single mother living in public housing describe d the physical manifestations and social consequences of substandard housing that sh e believed contributed to poor physical and mental health in women (Welch, 1997) Alt hough there are inherent limitations to singlecase studies, other studies with sample s of over 300 women living in public housing substantiate this finding (Edin and Lein, 1997; Rollins, Saris, and Johnston-Robledo, 2001; Wasylishyn and Johnson, 1998). Interviews of women living in public housing conducted by Rollins and colleagues (2001) highlighted problems such as structural damage and safety issues. Nicolas and Jean Baptiste (2001) used focus group sessions to learn about the experiences and perceptions of women who receive public assistance (including public housing subsid ies). Some of the major themes that emerged included feelings of shame and disrespect, an ins ecure future, and a sadness regarding lifes outcomes (Nicolas and JeanBaptiste, 2001). Similar themes were identified through

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27 interviews with 13 pregnant women livi ng in PH by McAllister and Boyle (1998), including discontent, struggli ng to make ends meet and loneliness. These three core themes depict the consequences of pove rty and living in low-income housing. The women in this study also viewed housing as sistance as degrading and stigmatizing, and notably, were much more concerned about th e violence in their neighborhood than they were about their current pregna ncy (McAllister and Boyle, 1998). These four studies provided excellent descriptions of the experiences and perceptions of living in pub lic housing. However, these st udies do not address whether the experiences of women living in S8 hous ing might differ from t hose in PH and how neighborhood characteristics a ffect health. Whether home environment or neighborhood characteristics of S8 housing differ from PH in ways relevant to health remain unknown. A more thorough understanding of how S8 and PH environments differ is critical, given that the policy intent behind S8 housing is to reduce the concentrat ed pockets of poverty and its consequences that ha ve been observed in PH. In addition, few studies have incorporated an approach that examines the physiological mechanisms by which neighborhoods and housing may impact health and either exacerbate or attenuate SEPrelated health disparities among women. Nurs e researchers, however, are essentially silent in this domain, even though public he alth nurses have an extensive history of addressing neighborhood-related co ncerns in relation to hea lth (Lundy and Janes, 2001). Housing Policy and Health Home ownership is the American dream. Vi ewed as part of the transition to adulthood, owning ones home is a common goal for many young men and women. Thus, the majority of housing assistance poli cies and programs have focused on homeownership. Unfortunately, due to a combin ation of factors such as the lack of

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28 affordable housing and an inadequate liv ing wage, many Americans are unable to become homeowners. Many low-income work ers, particularly single-women with children, are unable to own their own homes and must not only rent, but also rent utilizing federal housing subsidies. More over, minorities and poor women who must depend on housing subsidies to maintain shelte r are often stereotype d as lazy, ignorant, unkempt or destructive, and thus marginali zed, discriminated against and located apart from the main stream community and its higher level resources (Hays, 1995). Since the emergence of federal housing polic ies in the 1930s and the passage of the Wagner-Steagall Housing Act in 1937, low-income housing has been characterized by many factors leading to stigmatization and marginalization. By 1942, the United States Housing Authority (USHA) had built ove r 100,000 units in over 140 cities (Von Hoffman, 1996). The construction of public housing utilizing mini mal design elements reflective of the moderns style contributed to the distinctive yet ne gative image that came to be associated with public housing. Func tional yet austere looking designs and the placement of high density multi-family housing complexes in super-blocks also contributed to the distinctive image of public housing Therefor e, a sharp contrast to the types of residences detach ed single-family homes that most Americans occupied emerged that in time would stigma tize public housing (Von Hoffman, 1996). Further investigations of past housing policies reveal blat ant discriminatory language and practice. The 1934 Housing Act, focused on homeownership, guaranteeing loans for mortgages through government appr opriations. However the funds for these loans were restricted to the production of new and existing homes for a single owner.

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29 Tragically, during this time period, discri mination was prominent and many lenders practiced red lining, refusing to loan in certain areas of town based on race and ethnicity. Redlining was supported by the Federal Housing Administration (FHA). The FHA manuals used by lenders instructed them to avoid areas where disc ordant racial groups resided. In addition, the FHA encouraged deve lopers to establish deed restrictions prohibiting black owners and residents. Discrimination in the housing market became prevalent. Consequently, property values of minority neighborhoods plummeted, and neighborhood segregation by race and income was perpetuated (Orlebeke, 2000). Further alienation and marginalization of low-income and minority persons was inadvertently propelled by the design of ne w public housing units. Unfortunately, highrise buildings turned into PH disasters due to lack of funding for building design, basic amenities and maintenance, isolation and alienation from surrounding neighborhoods and the lack of public space (e.g., parks) (Orleb eke, 2000). Moreover, during the 1950s and 1960s inner city neighborhoods, now termed ghettos, continued to carry a negative stigma. Burdened with cycles of poverty, l ack of formal education, lack of economic stability, inadequate housing and a major reduc tion in federal funding, life in these areas become unsafe and unhealthy (Von Hoffman, 1996). Current trends in housing policy paint a bleak picture for housing subsidy programs. In 1971 members of Congress argue d that high cost, s hoddy construction, poor administration, failure to help low-inco me families and lack of planning on a metropolitan scale were only a few reasons for serious restructuring and reformation of housing subsidy policies and programs. In 1973, President Nixon called for a moratorium on subsidized housing production. Since then th e development of three different program

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30 types vouchers, block grants and tax cred itshave become the primary means of providing support for rental housing. In the early seventies, the Nixon admini stration introduced the Section 8 voucher program which gave the recipi ent the option of choosing a unit costing more than the FMR and paying the difference out of hi s/her own pocket (Hays, 1995). Voucher programs result in increased mobility of reci pients to better neighborhoods that are less socially and economically distressed with greater employment oppor tunities. One study showed that only 14.8 % of certificate and voucher recipients live in high-poverty neighborhoods (more than 30% poor), compared with 53.6 % of public housing residents (Newman and Schnare, 1997). Furthermore, they have lower rent burdens enabling them to use more of their inco me on food, clothing and hea lth care needs (Newman and Schnare, 1997). Debates regarding the best use of scar ce federal housing dollars often focus on arguments between housing production and rental assistance through voucher type programs. The original purpose of public housing programs was to provide housing for poor working families in urban inner city areas as a means of improving slums. However, several issues associated w ith public housing (such as, housing design, poor maintenance, residential segregation, and placement of lowincome housing in economically distressed areas) have contributed to so cial inequalities. The economic and racial segregation of poor families to the poorer less desirable areas of cities associated with federal housing policies and programs beginning in the 1930s unfortunately persis t to this day. The social inequalities associated with housing subsidy have significant implicat ions for the health of women and the neighborhoods where they live. Marginalization, discrimination,

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31 substandard housing, and housing located in disadvantaged neighborhoods may serve as chronic stressors that catalyze a cascade of ev ents that in time may lead to poor physical and mental health. What We Know and Gaps in Knowledge and Research While research in this area has found c onsistent associations between housing, poverty, and health, the pathways and mechanis ms by which the social aspects of these phenomena produce physiological alterati ons are not well known (Dunn, 2000). Few studies have incorporated an approach th at examines the physiological mechanisms by which neighborhoods and housing may impact hea lth and either exacer bate or attenuate SES-related health disparities among wome n. Lacking in the literature is knowledge regarding whether home environment or neighborhood characteri stics of various subsidized housing types differ and whether the experiences of wo men living in various subsidized housing types differ in ways relevant to hea lth. A more thorough understanding of how subsidized housing (S8 and PH) enviro nments differ is critical, given that the policy intent behind S8 housing is to reduce the concentrated pockets of poverty and its sequelae that have been observed in PH. Furthermore, very little research explores housing as a factor in the social production of health inequalities. Population health studies are needed that explore the relationships among hous ing, social capital, social cohesion, income/wealth inequalities and womens health from a life course perspective (Berkman and Kawachi, 2000; Dunn, 2000). Studies should address the social-biological interface, thus sorting out the mechanisms by which the social aspects of housing are embodied into physiological char acteristics that imp act health (AcevedoGarcia et al 2004).

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32 SES and Chronic Stress: The Role of th e Hypothalamic-Pituitary-Adrenal (HPA) Axis in Chronic Disease This section of the literature review high lights two areas: the first provides a brief overview of normal hypothalamic-pituitary-a drenal (HPA) axis function and its hypothesized role in chronic disease development and th e second reviews literature specific to changes in normal HPA axis f unction by SEP and chronic stress exposure. Human studies have establis hed relationships between psychosocial stressors and physiologic stress involving the HPA axis (Linden, Rutledge, and Con, 1998) Furthermore, there is increas ing evidence that characterist ics of lower socioeconomic environments are associated with excessi ve HPA activation (Seeman and McEwen, 1996) that may lead to the development of chr onic conditions that ha ve high morbidity and mortality rates (Rosmond and Bjorntorp, 2000) Responses of the HPA to stress allow organisms to achieve allostasis, the ability to obtain stability th rough change, which is required for survival (McEwen, 1998). McEw en and others (Seeman, Singer, Rowe, Horwitz, and McEwen, 1997) have proposed the cumulative effects of adapting to stressors (predominantly through pronounced HP A activation) may be quantifiable using the concept of allostatic lo ad as an index of wear and tear on the body over time. Accumulation of allostatic load is hypothesized to play a role in the pathogenesis of chronic diseases and is a useful concep t for considering the relationships among socioeconomic status, the psychosocial stresso rs of single-mothers, physiologic stress arousal patterns, and related disparities in health (McEwen, 1998). Animal studies have been particularly useful in determining ne uroendocrine pathways of the chronic stress and health relationship due to the ability to eliminate selection bias (Kneipp and Drevdahl, 2003). Nonhuman primat e studies indicate that domi nant social status in a

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33 stable environment is associated with less HPA activation (Sapolsky and Mott, 1987), higher HDL levels (Sapolsky, 1989), and less co ronary atherosclerosis in both males and females (Kaplan, Manuck, Clarkson, Lusso, a nd Taub, 1982). Reciprocally, animals that are socially subordinate, socia lly isolated, or in other so cially-stressful situations consistently demonstrate greater HPA ac tivity (Kalin and Carnes, 1984). In the immediate postpartum period, for example, Ba hr, and colleagues (Bahr, Pryce, Dobeli, and Martin, 1998) found female gorillas living under more stressful environments in captivity (e.g., being harassed by other adult and juvenile gorillas) had higher urine cortisol levels and less physical contact with their infants, suggesting the social environment affects parenting behavior and infant bonding via stress-related mechanisms. Several rat studies (Gelsema, Schoemaker, Ruzicka, and Copeland, 1994; Roy et al., 2001) support a relationship between chronica lly stressful environments, psychological distress, and CVD. The SEP of womens lives in relation to ch ronic stressors and disease outcomes has received little attention, even though there is incr easing evidence from human studies that chronic stress and HPA axis alteration indepe ndent of behavioral or lifestyle factors exists (Julius and Nesbitt, 1996). Other stud ies show that characteristics of lower SEP environments are associated with altered HPA activity believed to be involved in the development of chronic conditions that have, at the ecological level, been associated with lower SEP (e.g., CVD, DM, and asthma) (Bjorntorp, Holm, and Rosmond, 1999; Wamala, Lynch, and Kaplan, 2001). In a study of diurnal cortisol patterns in healthy mothers of toddlers, investigat ors found that individual differe nces in cortisol secretion

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34 patterns could be predicted from medical, demographic, contextual (home and work demands), and psychological variables (Adam and Gunnar, 2001). While many studies have consistently found chronic stress effects on cortisol patterns, others have not found a relationshi p (Smyth, Margit, Ockenfels, Gorin, Porter, Kerschbaum, Hellhammer, and Stone, 1997). On e reason for this may be that research done in this area has focused on two types of cortisol secretion in response to stressors: (1) those that are short-lived and occur imme diately in response to acute, laboratory stressors and (2) those that reflect changes in diurnal secretion patterns in response to chronic, or ongoing, stress exposures. Since th e specific aims of this research are to examine chronic stressors in relation to nei ghborhood context and healt h, the focus of this discussion will be on alterations in the HPA axis from chronic stress. HPA Axis Physiology and its Role in Chronic Disease Development A complex system, the HPA axis regulates the release of many different hormones. These hormones have either a stimulatory or inhibitory effect on many body functions. The following discussion focuses specifically on the release of the glucocorticoid, cortisol in response to stimulation of the HPA axis. When stimulated, the parvocellular neurons within the paraventricular nuclei of the hypothalamus release corticotropinreleasing hormone (CRH), AVP, and other fact ors. The portal system transports these factors to the anterior pituita ry, activates corticotrophs a nd stimulates the secretion of adrenocorticotropin hormone (ACTH). The syst emic blood system transports ACTH to the adrenal glands. The adrenal cortex then synthesizes and secr etes glucocorticoids (Campeau, Day, Helmreich, Kollack-Walk er, and Watson, 1998). Most importantly researchers hypothesize that exposures to stresso rs initiate this cascade of events and is one of the hypothesized mechanisms involved in mediating the SEP-health relationship.

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35 Glucocorticoids are known to have me tabolic, immunologic, anti-inflammatory, and growth inhibitory effect s on the body. They also influe nce levels of awareness and sleep patterns (McCance and Huether, 1998). However, the main function of glucocorticoids is to prom ote conditions that assist the body to adapt to adverse situations. Therefore, glucocorticoid recep tors are widely dispersed. The most potent glucocorticoid is cortisol. Co rtisol supports increased ener gy requirements during periods of stress by facilitating the m obilization of free fatty acids (FFA) found in adipose tissue in the form of triglycerides. The increase in FFA inhibits utilization of glucose in the peripheral tissues. Cortisol s timulates the release of gluc oneogenic enzymes, specifically phosphoenolpyruvate carboxykinase, which regulates the rate of gluconeogenesis. In addition, cortisol also functions to mobilize amino acids from proteins in skeletal muscle (Kacsoh, 2000). The main function of glucocorticoids is to promote conditions that assist the body systems to adapt to adverse situations. There is evidence to indicate changes in cortisol play a pivotal role in the development of diab etes and CVD. One function of cortisol is to support increased energy requirements duri ng periods of stress by facilitating the mobilization of FFA found in adipose tissue, which may contribute to the development of insulin resistance and, ultimately, Type 2 Diabetes Mellitus (Bjorntorp et al., 1999). Cortisol is perhaps most widely known fo r its immunosuppressive effects, and evidence now suggests inflammatory processes modulated by cortisol output may play a role in the development of atherosclerosis and CVD (Yudkin, Kumari, Hum phries, and MohamedAli, 2000).

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36 Normal cortisol has a diurnal rhythm with a peak occurring in the early morning and a nadir in the early evening. Under periods of stress, cortisol is released acutely to assist the body to adapt to its external and internal demands. Exposure to chronic stressors, however, results in a lterations in cortisol secretion that persist over time. It is this change in pattern of co rtisol secretion that has been most associated with SEP, chronic psychosocial distress, and the eventual development of sel ect chronic diseases (Lovallo and Thomas, 2000; Raber, 1998). Ch anges in HPA response and, specifically, the normal diurnal pattern of cortisol secr etion to stress, may result in pathological changes that lead to the deve lopment of select chronic diseases (McEwen, 1998; Raber, 1998). For example, Plat and coworker s describe how prolonged hypothalamic stimulation from a stressor might result in a bnormally high levels of cortisol secretion in the early evening. In addition they found that evening elevations in cortisol were associated with delayed hyperglycemic effect s, stimulation of lipolysis and increased concentrations of free fatty acids that have been associated with CVD (Plat, Leproult, L'Hermite-Baleriaux, Fery, Mockel, Polons ky, and Van Cauter, 1999). In another study, researchers found that a stress -related cortisol secretion pa ttern with a flattened curve depicting a loss of adaptability to stimuli was strongly correlated with elevated body mass index, waist-hip ratios, blood pressure, heart rate, tr iglycerides, total and lowdensity lipoproteins, insulin, glucose, and visceral fat mass (Bjorntorp et al., 1999). Therefore, they postulate that stress-relate d cortisol secretion along with an impaired regulation of the HPA axis, ar e connected to physiologic al terations associated with chronic disease development.

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37 Relationships Among Neighborhood Charact eristics, Housing, Chronic Stress, and Health Studies have demonstrated that neighborhood characteristics play a significant role in determining the type and intensity of daily stress experienced and therefore are important social determinants of health (Boardman et al., 2001; Wasylishyn and Johnson, 1998). Adjusted for individual-level SEP, liv ing in high poverty neighborhoods has been associated with increased daily stressors su ch as increased exposur e to drugs (Boardman et al., 2001) and violent cr ime (Sampson and Raudenbush, 1997) Studies indicate lowerincome women view the stress in their lives as major determinants of not only overall health status but also of other chronic diseases. For example, focus groups conducted by researchers with low-income African-Ameri can women to examine their awareness of and concern for CVD found they considered CVD to be associated with stress and low SEP (Behera, Winkleby, and Collins, 2001) Similarly another study found that lowincome women with mental health problems we re most interested in stress management strategies indicating that they view stress as an important aspect of psychological health (Alvidrez and Azocar, 1999). Additional qualitative studies with wo men living in low SES neighborhoods in Detroit highlighted that women linked st ressors directly re lated to neighborhood characteristics (Schulz, Parker, Israel, a nd Fisher, 2001). Furthermore, the cumulative effect of chronic stressors such as safe ty issues and unfair treatment was strongly associated with symptoms of depression, wh ile financial and family stress showed the strongest relationships with poorer self-repor ted health status (S chulz et al., 2001). A recent study conducted by Buka et. al (2003) examined neighborhood economic disadvantage, neighborhood support, and infant birth weight in 343 neighborhoods. They

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38 found neighborhood economic disadvantage al one accounted for 80.8% of the between neighborhood variance infant bi rth weight for African-American mothers and 76.3% for White mothers while controlli ng for individual risk factor s (including maternal age, education, smoking during pregnancy, and rece ipt of prenatal care). When neighborhood social support was added to the model, the addition of this explanatory variable to economic disadvantage accounted for 90.9% of the between neighborhood variance in infant birth weight for Whites. These results indicate that stressors produced as a consequence of living in economically disadvantaged neighborhoods ha ve significant implications for health, regardless of individual behavioral factors. What remains, unknown, however, is whether and how chronically stressful environments of low-income housing have physiological consequences that contribute to chroni c disease development, and whether the environments of PH and S8 differ in ways that are relevant for health (Buka et al., 2003). Summary As described in this literature review neighborhood-level characteristics have a significant effect on health above and beyond individual-level factors. Studies have shown that neighborhood-level factors can pr oduce environments that promote chronic stress and poor health. However, we do not have a clear understanding of the socialbiological interface that can provide eviden ce of the physiological mechanisms by which environments (i. e., neighborhoods) contribute to poor health and chronic illness. The study of social and biological va riables at the same time is intrinsically valuable because we are as humans, both social and biological (Brunner, 2000). More research is needed in order to understand what cons titutes an unhealthy environmen t and how it gets under the

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39 skin to produce illness (Taylor, Repetti, and Seeman, 1999). This study aims to contribute to this body of research by inve stigating social and biological variables simultaneously, by beginning to explain the social-biological processes by which neighborhoods and housing impact womens health disparities.

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40 CHAPTER 3 METHODOLOGY Theoretical Framework As stated in Chapter 1, this study is guided by a combination of an ecosocial paradigm and the allostatic load model. Togeth er, they allow for exploration of the social biological interface through which environm ental factors affect health. Kriegers ecosocial theory and McEwens allostatic load model guide the development of the conceptual framework used in this study (Krieger and Davey-Smith, 2004). Krieger and Davey-Smith (2004) call for incorporating th e concept embodiment in order to capture how social influences (i.e., housing and the bui lt environment) become literally embodied into physiological characteristics that infl uence health. The con cept of embodiment simultaneously embraces biologic and social processes while avoiding the trap of equating biologic with inna te and without assuming the so ma is governed exclusively by the psyche. In addition, as Krieger and Davey-Smith state, this new scholarship emphasizes how actualization and suppression of peoples agency, that is, their ability to act within their bodies, intim ately depends on socially stru ctured opportunities for, and threats to, their well-being (pg. 95). Thus keeping the con cept of embodiment in mind, the conceptual framework developed for this study draws from multiple disciplines such as public health, sociology, and medicine. The second theoretical model used to de rive the socio-biological conceptual framework is McEwens Allostatic Load model (McEwen, 1998). This model is based on the premise that physical and psychological st ressors occur within a social and economic

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41 context and that there is individual variati on in the stress appraisa l process as well as behavioral and emotional coping mechanisms to the perceived stressor (McEwen, 1999). McEwen describes four key propositions of his a llostatic load model. First, the brain is the integrative center for coordinating the behavioral and neur oendocrine responses (hormonal, autonomic) to challenges. Sec ond, there are considerable differences in coping with challenges based on interacting ge netic, developmental, and experiential factors that predisposes persons to react differently physiolo gically and behaviorally to events throughout life. Third, inherent w ithin the neuroendocrine and behavioral responses to challenge is the capacity to adapt (allostasis). However, while these physiological processes are protective in the shor t term, inefficiency or alterations in the ability of the neuroendocrine system to tu rn on and off responses leads to cumulative negative effects over time. Fourt h, allostasis has a price defi ned as allostatic load that reflects the cumulative negative effects or the wear and tear on bodily systems from being forced to constantly adapt to various psyc hosocial challenges and adverse environments (i.e., disadvantaged neighborhoods). Accumulation of allostatic load is hypothesized to play a role in the pathogenesis of select chronic diseases, such as insulin resistance, atherosclerosis, increased susceptibility to infections and memory loss (Bjornto rp, Holm, and Rosmond, 1999; McEwen, 1998; McEwen, 2000). Since this model addresses the fact that daily stressors occur within a social and economic context, it is a useful framework for considering the relationships among SEP, the psychosocial stressors of si ngle mothers, physio logic stress arousal patterns, and their noted disparities in h ealth (McEwen, 1999). As such, the impetus in this model is to move from the individual back to populations and consider the average

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42 properties of groups of individuals classified according to measures of SEP attending to not only the social and cultural factors th at influence health, but the potential physiological mediators found in these relatio nships. However, McEwens model lacks detail regarding the socio-economic aspects of neighborhood and health. Combining Kriegers ecosocial theory and McEwens allostatic load model enables the researcher to simultaneously explore social and biological variable s. This allows for advancing scientific knowledge as it relates to the understand ing of the social-biological interface that may be mediat ing relationships among envi ronments (i.e., neighborhoods), chronic stress, and health. Relationships am ong environment, social, psychological, and physiologic factors relevant to this study in relation to the Allostatic Load Model are illustrated in Figure 3-1. Key constructs and concepts and methods of operationalization are explained in the section on major study va riables below. The final outcome (CVD) is in grey because it was not explored in the present study. It is onl y an example of one possible outcome that could be explored using this framework. Figure 3-1: Socio-bi ological Model Neighborhood Housing Stress Psychological Distress Physiological Effects CVD Hypothesized Mechanisms Contri buting to Disease Development

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43 Research Design This study utilized a crosssectional design in which physiological measures were obtained six times a day for 2 days in a samp le of 84 women. Of th e 84 who participated, complete data were available for only 67 participants 23 from PH and 43 from S8 housing. The relationships among housing type neighborhood characteristics, stress, psychological distress and salivary cortisol are examined by specific aim 1. To meet specific aims 2 and 3, differences in neighbor hood characteristics, stress, psychological distress and salivary cortisol between women living in S8 and PH are explored. Population and Sample The population investigated in this study includes 18 to 45 year old women who are heads of households and have at least one child 18 yearsold or less living with them. This age group was selected because it is re presentative of the target population to be studied. Based on data from the department of Housing and Urban Development, almost two-thirds of those living in subsidized housing are between the ages of 18 and 62 (U. S. Department of Housing and Urban Devel opment, 1998). A subcategory of female children (as defined by NIH) those who are18 to 21 years of age and are mothers --, are included in this study. While considered by many as children, young (18to 21yearsold) mothers often live in disadvantaged neighborhoods and poor housing environments. Having the same adult responsibilities as any parent, they experience many daily stressors, associated with adult responsibilitie s in maintaining family safety and stability. The specific aims of this study are to ex amine the potential of chronic disease development as a result of cumulative stress a ssociated with adult family responsibilities and being female heads of households within a neighborhood context.

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44 The sample was selected based on their expos ure to either S8 or PH environments. Research participants were recruited from the area in cooperation with the Gainesville Housing Authority and S8 housing managers. In Gainesville, Florida and within a 10 mile perimeter of the city limits, there are 1,062 S8 housing slots. Approximately 400 people per year attend S8 housing orienta tion provided by the Gainesville Housing Authority. Ten to fifteen percent of people who move into S8 housing move from PH units (Dolder, C. personal communication, Ju ne 26, 2002). During a typical application process, of the 400 interested people, 150 applications are pro cessed and reviewed; approximately 5% to 10% are ab le to move into S8 housing. The sample was recruited by posting flyers at the local housing agencies, rental units participating in housi ng subsidy programs, the univers ity, health science center, local hospitals and primary care offices, social service agencies, and churches. In addition, the principal investig ator (PI) attended community meetings such as the Black on Black Crime Task Force, and tenan t/neighborhood associations in neighborhoods where the sample was located and informed them of the research and recruited interested persons. Addresses were obtained from th e Gainesville and Alachua County Housing Authority and letters were disseminated t o1500 section 8 and public housing addresses. Most of the public housing participants were recruited by going door to door. Sample size determination was based on a pow er analysis to ensure a power of 0.80 is achieved. A sample size of 49 subjects pe r housing type was needed to detect a difference of .40 in the outcome measures (i .e., salivary cortisol, chronic stress, and psychological distress). For multiple regres sion analyses a total of 107 women were needed. Power for this study was not achieve d due to an inadequate sample size.

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45 A total of 84 women participated in th is study. The original sample size of 107 women was not attained due to several i ssues. Despite compensa tion with a $30.00 gift certificate to Wal-mart, recr uitment of women living in public housing was difficult. Though data was not collected as to why wome n chose not to participate, based on their comments, fear of getting in trouble with the local housi ng authority is one possible reason many women did not participate in the study. Also, many of the women refused to collect saliva. Some were repulsed by the idea of collecting saliva, while others voiced concern about what would happen to it after th e study was over. Fear and mistrust despite efforts to assure women that their privacy and confidentiality would be maintained was believed to be a major factor in not achieving the desired samp le size. Also the study was limited to participants who lived within a 10-mile radius of Gainesville, thus limiting participants geographically. Of the 84 women who participated, 14 did not have usable cortisol data (defined as missing more that 2 time points in one day) These cases were deleted. Survey and cortisol data were imputed for the 70 participants remaining. Three participants failed to answer over 50% of the questions from one m easure leaving a final sample size of 67 women. It was decided a priori that if a partic ipant failed to answer more than 30% of the items in a measure, she would be excluded fr om data analysis. Up to 10% missing data on a measure may be considered small, while 40% missing data is considered to be high (Musil, Warner, Yobas, and Jones, 2002). Recommendations for handling missing data in nursing research are limited. Decisions regard ing the appropriate methods to deal with missing data are based on the pattern, level (s ubject or item) and amount of data that are missing (Kneipp and McIntosh, 2001; Patric ian, 2002). The robustness of certain

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46 imputation techniques is often dependent on extent and amount of missing data. Therefore, these factors shoul d be considered in order to minimize estimation error and response bias (Fox-Wasylyshyn and El-Masri, 2005). Imputation methods used in this study are described in detail later in this chapter. Setting The study was conducted in a naturalistic se tting (i.e., community of residence). The PI or her research assistant met with par ticipants in their homes or other settings as preferred by the participants. Human Subjects Protection Approval for this study was obtained from th e University of Florida Health Science Center Institutional Review Board prior to a ny subject recruitment or data collection. All subjects signed an informed consent form a nd were given a copy prior to enrollment in the study. Data collection took place in th e participants resi dential neighborhood. Confidentiality was maintained by use of a code for each subject. All files were kept in a locked file cabinet in the researchers office. Saliva samples were also coded and stored in a freezer in the college of nursing wet lab, wh ich is locked at all times and has limited access by select faculty, staff, and research assistants. Inclusion and Exclusion Criteria Inclusion criteria include: a) Living in public or section 8 housing for at least 1 month, b) Able to speak and read English, c) Between the ages of 18 and 45 years old, d) A mother who is head of the house hold with a child living in the same household who is 18 years old or less.

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47 Exclusion criteria include: a) Age greater than 45 years old, b) Diagnosis of an autoimmune disorder, c) Pregnant or breastfeeding, d) Taking antidepressant, anxiolytic or steroid-based medications. e) Working the night shift (from the hours of 11:00 pm to 7:00 am). The inclusion criteria were selected b ecause this study focuses on women living in section 8 and public housing units and how th ese areas may serve as stressor for women responsible for maintaining family safety a nd stability. Women living in an area for at least one month have had time to assess thei r neighborhood regarding crime, disorder and other characteristics. Women 18 years-old up to 45 years-old are repr esentative of most of those who live in subsidized housing as pr eviously described. Th e study was limited to participants who could read and speak English due to fina ncial constraints related to hiring a translator. These exclusion criteria were selected b ecause they are known to alter cortisol levels and may alter responses to stress, de pression and anxiety m easures. Studies have produced controversial results regarding differences in sa livary cortisol based on age group. Studies have demonstrated systematic differences are present in early morning salivary cortisol in which decr easing cortisol concentrations are positively correlated with age (Kirschbaum and Hellhammer, 1992). Th e lowest mean value of 11.6 nmol/l was found in the age group between 59 and 64 year s. The effect of pregnancy on salivary cortisol is controversial. Some studies have shown increases in salivary cortisol secretion while others have not (Kirschbaum and Hellhammer, 1992). In addition, the sample upper age limit of 45 years old will reduce confounding effects of menopause and chronic disease development on physiological measures.

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48 As previously described in the literature review, cortisol has a diurnal pattern with a peak 45 minutes to one hour after awaken ing and a nadir just before bedtime. Alterations in sleep quality a nd quanity and working the nigh t shift have been shown to affect the HPA axis and therefore alter cortis ol secretion patterns (Leproult, Copinschi, Buxton, and Van Cauter, 1997; Spiegel, Leproult, and Van Cauter, 1999). In addition to altering salivary cortisol levels, antidepressants and anti-anxiety agents may influence how a particpant responds to questions regard ing stress, depression and anxiety leading to underestimation and response bias. Theref ore persons taking antidepressant or anti-anxiety agen ts were exluded from the study. Research Variables and Instruments A demographic data sheet was used to co llect information such as age, marital status, race, household type, number and ages of children, individual income, education, and occupation, chronic diseases diagnoses, medication use, height, and weight. In addition information was obtained on current ad dress, living situa tion (i.e., living with others or others living with them), housing type, length of time in current dwelling, rent assistance per month, public assistance, rece ipt of food stamps and other sources of income via public assistance resources, such as child care and transportation. Additional data regarding smoking history, alcohol intake, and menstrual cycle phase and regularity were obtained, as well. Major Study Variables This section provides detailed information on the measures used in this study. A quick overview of each of the dependent and explanatory variables is provided in the table in the Appendix.

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49 Neighborhood Characteristics Neighborhood is defined according to Gals ters (2001) definition that states, Neighborhood is the bundle of sp atially based attributes asso ciated with clusters of residences, sometimes in conjunction with other land uses (p. 2112). This definition is broad and quite abstract. It includes several aspects of neighborhood such as the structural, class status, environmental, a nd social inter-active characteristics of neighborhood. For the purposes of this study, the te rm neighborhood characteristics include information on neighborhood economic disadvantage (measured at the census tract level), perceived neighborhood disorder, exposure to crime, and neighborhood cohesion. Each of these measures is described more fully below. Neighborhood Economic Disadvantage Neighborhood economic disadvantage was obtai ned using census tract level data from the 2000 census. Census tracts are de signed to be demogr aphically homogenous with stable boundaries over time and ge nerally contain between 3000 and 8000 resident (Boardman, et. al., 2001). Extensive research by Krieger and collea gues has shown that socioeconomic data obtained at the census tract level performs better at detecting economic gradients expected than measures at the county or state level (Krieger et al 2003). For the purposes of this study, neighbor hood economic disadvantage is an index measure of percent family poverty, percen t of female headed households, male unemployment rate, and percent of families r eceiving public assistance. The four values were summed to create the neighborhood disa dvantage measure in which higher numbers indicate greater disadvantage, with scores ranging from 0 to 12. This measure has been

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50 used in studies that investigated the re lationship between nei ghborhood disadvantage and health in adult samples mu ch like the sample in this study (Boardman et al., 2001; Sampson and Raudenbush, 1997). Prior rese arch by Sampson & Raudenbush (1997) demonstrated that these characteristics ar e highly interrelated and load on one single factor that can be describe d as neighborhood disadvantage ( = 0.97). Neighborhood Disorder The concept of perceived neighborhood diso rder includes both social and physical signs indicating a lack of or der in the neighborhood. Areas wi th high levels of disorder are characterized by deviance, noise, vandali sm, drug use, crime, trouble with neighbors and other incivilities (Ro ss and Mirowsky, 1999). This study measured perceived neighborhood disorder using an index that meas ures physical signs of disorder such as graffiti, vandalism, noise, and abandoned buildings, and social signs such as crime, people hanging out on the street, and people drinking or using drugs It also includes reverse-coded signs of neighborhood order such as safety, people taking care of their houses and apartments or watching out for each other. The perceived neighborhood disorder scale consists of 15 items on a four point Likert scale that ranges from order on the low end (15) to disorder on the high end (60) of the continuum. This scale has an alpha reliability of .915 (Ross and Mirowsky, 2001). Neighborhood Stress: Crime Exposure Neighborhood Stress is defined as exposure to a range of events and conditions in ones proximal environment that are capable of eliciting stressful emotions (e.g., fear, anger, depression) and that may exacerbate disease processes or undermine health (Ewart, 2002). The City Stress Index (CSI) wa s developed by Ewart ( 2002) and is used as a self-report measure to assess perceived ne ighborhood disorder and exposure to crime.

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51 The CSI is an 18-item measure with scores ranging from 18 to 72. Low scores indicate lower levels of neighborhood stressors. This measure can be completed by persons with an eighth grade reading-level. It has good va lidity and reliability with the neighborhood disorder and exposure to violence portions of the scale having a Ch ronbachs alpha of .88 and .85 respectively (Ewart, 2002). The recent development of the tool limits the data on use in other populations such as adults, but the reading level and use in urban dwelling adolescents make it a useful measure for this study. Permission to use this measure was obtained from Craig Ewart, a professor in the Center for Health and Behavior at Syracuse University (C. Ewart, personal communication, December 7, 2004). Neighborhood Social Cohesion Social cohesion refers to the level of tr ust, extent of conn ectedness and solidarity among groups in society (Kawachi and Berkman, 2000; Sampson and Raudenbush, 1997). For some, the neighborhood may become an extension of home for social purposes and becomes important in identity terms possibly leading to a high degree of interaction among community members (For rest and Kearns, 2001) Neighborhood social cohesion was measured using a using 5 conceptu ally related items that ask participants whether or not people in the neighborhood w illing to help others, get along with each other, share the same values, can be trusted, a nd whether or not they agreed they lived in a close-knit neighborhood (Sampson and Raude nbush, 1997). The items were scored on a 5-point Likert scale. Scores may range from 0 to 25 with higher scores indicating greater levels of cohesion. The reliability with which neighborhoods can be distinguished on neighborhood social cohesion ranges be tween 0.80 to 0.91 (Sampson and Raudenbush, 1997).

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52 Housing Nested within neighborhoods is the construct of housing. Without further definition, housing can refer to several diffe rent types of housing such as high or lowincome housing, public or section 8 (government subsidized housing), or rental versus owned housing. For use in this study, housing will be further defined as subsidized rental housing (public and section 8 housing). Housing Satisfaction (Perceived Housing Quality) Satisfaction with ones housing was m easured using one item from HUDs Customer Service and Satisfaction Survey (U. S. Department of Housing and Urban Development, 2003c). The Customer Service and Satisfaction Survey was developed in consultation with housing industry representati ves and public housing resident leadership groups. This survey consists of 20 items in addition to six optional demographic questions that were not used in this study. This survey is designed to be both an assessment of current resi dent opinions regarding their housing quality and a management tool to identify areas of con cern (U. S. Department of Housing and Urban Development, 2004). Housing satisfaction was determined by asking participants, How satisfied are you with your unit/home? Respons es to these questions are based on a 5point Likert Scale and ranged from, Does not apply, very dissatisfied, dissatisfied, satisfied to very satisfied. Higher scores are indicative of more satisfaction. This measure has not been used in research, thus, va lidity and reliability has not been reported. Stress The term stress has many definitions depending on the context in which it is used. Hans Selye, a pioneer in the development of stress theory, developed the concept of stress using a response-based orientation (Lyon, 2000) For some stress is good in that it

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53 produces excitement, anticipati on, and challenge; for others, the same stressor is bad, producing an undesirable state characterized by worry, frustration, chronic fatigue, and inability to cope (McEwen, 2005). Stress is defi ned in this study as an undesirable state based on ones perceptions of situations and events such as neighborhood crime and disorder, or unfair treatment which evokes ce rtain emotional, behavioral, and nonspecific physiologic responses. Perceived Stress Perceived Stress was measured using Cohe ns (1983) Perceived Stress Scale. This scale measures the degree to which situations in ones life are appraised as stressful. The Perceived Stress Scale is a widely used and accepted measure with good validity and reliability. Responses to these questions are based on a 5 point Likert scale asking participants to respond to th eir feelings and thoughts ove r the last month. It has good internal consistency with a Chronbachs al pha of .84 .86. Scores range from 0 to 56 with lower scores indicating less stress (Cohen, Kamarck, and Mermelstein, 1983). Unfair Treatment and Discrimination Unfair treatment was assessed using The Interpersonal Mistreatment Scale developed by Williams and colleagues (1997). Th ese items were developed to assess how often in their day-today lives persons expe rience a variety of forms of interpersonal mistreatment. The framework consisted of poor interpersonal treatment and made no reference to race, prejudice, or discrimina tion (Guyll, Matthews, and Bromberger, 2001; Williams, Yu, Jackson, and Anderson, 1997). Th e Interpersonal Mistreatment Scale consists of 10 items on a 4-point Likert scal e. Scores range from 10 to 40 with higher scores corresponding to more frequent experi ences of mistreatment. This measure has

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54 demonstrated good internal consistency with a Cronbachs alpha of .76 to .86 (Guyll et al., 2001; Williams et al., 1997). Chronic Stress Chronic stress, the cumulative load of minor, everyday stressors, can have longterm consequences (McEwen, 1998). The effect s of chronic stress may be exacerbated by unhealthy behaviors such as l ack of physical activity, high ca lorie, high fat diets, smoking and alcohol use. Chronic Stress was measured in this study using the Trier Inventory for the Assessment of Chronic Stress (TIC-S) (Sch lotz and Schulz, 2004). This measure is a comprehensive measure of chronic stress that comprises nine dimensions including work overload, social overload, ove rextended at work, lack of social recognition, work discontent, social tension, performance pressu re at work, performance pressure in social interactions, social isolation, and worry propensity. This measur e is included in this study in addition to the perceived stress scale becaus e in addition to being more comprehensive, it asks people to answer questions based on their experiences for the last 3 months. Stressors experienced for this amount of time have more of a chronic component than stress experienced for only one month. Fu rthermore, the TIC-S includes specific dimensions which allow researchers to pinpoint specific areas (work or social life) that may be considered stressful, unlike other m easure used in this study. Responses are based on a 5 point Likert scale. Th e TIC-S has demonstrated good in ternal consistency with a Cronbachs alpha of .76 to .91 and a split-hal f reliability of .79 to .89. Permission was obtained from William Schlotz a professor at the University of Trier, Department of Psychobiology in Johanniterufer Germany to us e the short version of the Trier Inventory for the Assessment of Chronic Stress (T ICS-S) (Schlotz and Schulz, 2004).

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55 Psychological Distress Psychological Distress is defi ned as a discomforting emotional state experienced by an individual in response to one or more st ressors or demands that is manifest by a change in baseline stable em otional state to one of a nxiety, depression, demotivation, irritability, aggressiveness, or self-dep reciation (Ridner, 2004). In this study, psychological distress was measured by us ing scales that measure depressive symptomology and state anxiety. In addition to serving as independent variables that influence the outcome variable health and salivary cortisol, these variables will also be dependent variables when addressing the impact of neighborhood stressors and mental health. Depression The Center for Epidemiological Studies of Depression Scale (CES-D) is a 20-item, self-report scale that measures depre ssive symptoms in the general population (Weissman, Sholomskas, Pottenger, Prussoff, and Locke, 1977). It includes six major symptom areas: (1) depressed mood; (2) guilt-worthlessness; (3) helplessness/hopelessness; (4) psychomotor reta rdation; (5) loss of appetite; (6) sleep disturbance. Responses are base d on a 4-point Likert scale. Va lidity and reliability of this scale has been supported in previous studies Internal consistency and reliability using Cronbachs alpha has ranged from 0.85 to 0.91 (McDowell & Newell, 1996). State-Trait Anxiety The Speilberger State-Trait Anxiety Invent ory for Adults Form Y (STAI Form Y1) was used to measure anxiety. The STAI ha s been used extensively in research and clinical practice. It comprises separate self -report scales for measuring state and trait anxiety. The state portion of the scales cons ists of 20 statements that evaluate how

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56 respondents feel at the moment they are completing the surv ey. The trait portion of the scale consists of 20 statements that asse ss how people generally feel (Spielberger, Gorsuch, Lushene, Vagg, and Jacobs, 1983). Re sponses are based on a 4-point Likert scale. This measure had demonstrated good in ternal consistency w ith a Cronbachs alpha of .86 to .95. General Health General Health was measured using one item from the SF-12v2TM survey form (Ware, Kosinski, and Keller, 1996). Particip ants were asked, In general would you say your health is poor, fair, good, very good, or excellent? Answers were based on a fourweek recall. Scores ranged from 1 to 5 resp ectively. These scores were transformed to a 0 to 100 scale and compared with national norms for women of the same age group (Ware, Kosinski, Turner-Bowker, and Gande k, 2002). Cronbachs alpha for the SF-12v2TM survey ranges from 0.73 0.77 in the genera l population of women ages 18 to 44 years old (Ware et al., 1996). Salivary Cortisol (SC) SC is a widely accepted method for meas uring physiological responses to acute laboratory induced stress and pe rceived chronic stress. It hi ghly correlates with serum (blood) and urine cortisol levels and offe rs stress-free, non-in vasive sampling, easy collection and storage (Kirschba um and Hellhammer, 1994). However, cortisol levels are affected by a variety of factors such as an acute stressor, smoking, drugs (such as steroidbased medications, contraceptives, anti-depres sants and anxiolytics), a high protein meal, lack of sleep and the luteal phase of the menstrual cycle (Kirschbaum and Hellhammer, 1992). These factors were controlled for in th e exclusion criteria and saliva collection protocol, or by incorporating them as covari ates in statistical models. Samples were

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57 analyzed using the HS-Cortisol High Sensitiv ity Salivary Cortisol Enzyme Immunoassay Kit. This kit requires minimal saliva volume (25 l), detects < 0.012 to 3.0 l of cortisol, has a serum-saliva correlation of r = .94, p <.0001 (Salimetrics, 2005). It was designed as a superior alternative to resolve pr oblems associated with serum-based radioimmunoassay and other salivary imm unoassays (Schwartz, Granger, Susman, Gunnar, and Laird, 1998). Participants provided 12 cortisol sample s consisting of 6 samples per day for 2 days. Specimens were collected over 2 days based on expert recommendations from the John D. and Catherine T. MacArthur Resear ch Network on Socioeconomic Status and Health. Though somewhat controversial, the more measurements in a day for a greater number of days (at least 3 to 4) allows for a more reliable measurement of trait daily concentration of cortisol (AUC). The advantage of using multiple days is that it helps to control the unreliability of one days da ta, which can underestimate the cortisol relationship to outcomes (S tewart and Seeman, 1999). A period of 2 days was decided upon for several reasons. First, prior research experience with a similar population suggested that data collection for a period of time longer than two days would be unrealistic. The day to day turmoil experienced by many in this population precludes prolonged daily data collection. Furthermore, daily data collection for 4 to 6 days places a significan t burden on the participants in addition to their daily routines and re sponsibilities. Finally, biol ogical specimen collection and analysis is costly. Material s and supplies for collection and analyses of biological specimens can be quite expensive, and partic ipants should be compensated appropriately

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58 for the time commitment and burden placed upon them as study participants. Therefore, financial constraints also prevented more frequent or prolonged data collection. Specimen collection was timed based on each participants time of awakening with the first sample to be collected upon awak ening (T1). The remaining 5 samples were collected at 30 minutes 1 hour, 4, 9, and 11 hour s after waking (T2-T6). This method of salivary cortisol collection is preferred since the time of cor tisol peak is not dependent upon the absolute time nor is it influenced by daylight; it is dependent on wake-up timing of each individual (Immuno-Biological Laborat ories, 2004; Stewart and Seeman, 2000). The total area under the curve (AUCg) w ith respect to ground as described by Pressner and colleagues (2003) was examined in terms of its relationship to the independent variables in this study. The formula used for the AUCg is derived from the trapezoid formula (Pressner, Kirschbaum, Meinlschmid, and Hellhammer, 2003). The formula used to calculate AUCg is presented below in Equation 3-1. Equation 3-1 AUCg = (SC2+SC1)/2*t1+(SC3+SC2)/2*t2+(SC4+SC3 )/2*t3+(SC5+SC4)/2*t4+(SC6+SC5)/2*t5 This AUCg calculation takes into account chan ge over time of each measurement and the distance of the measures from zero (the le vel at which the changes over time occur and results in a measure that is more related to total hormonal output (Pressner et al., 2003). Researchers at the MacArthur Research Ne twork on Socioeconomic Status and Health agree that AUC is the most widely accepted measure whereas diurnal rhythm, or diurnal pattern analysis is more contr oversial (Stewart and Seeman, 2000).

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59 However, AUCg is not without limitati ons. Though AUCg is a summarized index for repeated measures over time, it is not sens itive to fluctuations of repeated measures. For example, if two persons have completely di fferent patterns of cortisol levels relative to time, they may get the same AUCg. In a ddition, the AUCg approach does not take into account the correlations among repeated outcome measures within a specific person. Given these limitations, generalized estima ting equations (GEEs) will additionally be used to examine the relationships among the independent variables and salivary cortisol. GEEs provide a general framework for the analyses of c ontinuous, ordinal, polychotomous, dichotomous, and count-depende nt data, and relax several assumptions of traditional regression mode ls. GEEs represent an extens ion of the generalized linear model (GLMs) to accommodate correlated data. GLMs assume that the dependent variable can be expressed as a linear function of the inde pendent variables. It also assumes that the variance of the depende nt variables is a kno wn function of its expectation (thus allowing relaxation of the homoscedasticity assumption). Other assumptions of the GEE method include: (1) the number of clusters be relatively high (a rule of thumb is no fewer than 10, possibly more than 30, and (2) the observations in different clusters be indepe ndent, although within-cluster ob servations may correlate. Hence, GLMs do not require the specification of the form of the di stribution, but only the relationship between the outcome mean and the explanatory variables and between the mean and the variance (Ghisletta and Spini, 2004). GEE is a marginal (or population averaged ) as opposed to a cluster-specific (or subject-specific, conditional) method. Popul ation average models model the average response over the subpopulation that shares a common value of the predictors as a

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60 function of such predictors. P opulation average parameters re present the averaged effect of a unit change in the predictors for the whole population. The GEE approach specifies a working correlation matrix for the vector of repeated measures from each participant to account for the dependency among the repeated measures. The working correlation can be assumed to be the same for all partic ipants, reflecting aver age dependence among the repeated measures over participants. Several working correlation structures can also be specified, including independent, exchang eable, autoregressive, and unstructured correlation. The standard errors are derived from what is calle d the sandwich estimator of the covariance matrix of the regression coefficients. The main advantage of GEEs is that the calculation of the standard errors for the regression coeffici ents is robust even if the specifications of the correlation structure is incorrect or if th e strength of the correlation between repeated outcomes varies somewhat from person to person. Although the use of robust standard errors ensures that regression inferences are consiste nt regardless which correlation structure is chosen, however, ther e is no straightforward way in GEE models to truly determine the best correlation st ructure to use (Ghisletta and Spini, 2004). GEE is not without limitations. First the technique is asymptotic, hence requiring large total sample sizes for unbiased and cons istent estimation. Second, in applications to empirical data, sensitivity analyses of di fferent specifications of the intracluster correlation matrix are advised. Finally, GEE methodology assumes missing completely at random data, because GEEs do not specify the full conditional likelihood. However, GEEs do no yield a great deal of bias with missing at random data (Ghisletta and Spini, 2004).

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61 Given the limitations of AUCg and the advantages of GEE methods, GEE will also be used to examine the relations hips among neighborhood characteristics, psychological distress, stress, and salivary cortisol. Individual Social Support Individual social support is considered a covariate in this study. The amount and type of individual social suppor t one has may possibly offset the lack of support that may exist in the area in which one lives. Therefore, it is important to control for the amount of individual social support when examining th e effects of neighborhood social cohesion on health. Individual-level social support was measured in this study using the International Support Evaluation List General Populat ion Form (ISEL-GP) (Cohen, Mermelstein, Kamarck, and Hoberman, 1985). ISEL-GP consis ts of 40 items designed to assess the perceived availability of four separate functions of indivi dual social support (tangible, appraisal, self-esteem, and belonging). Respons es are measured on a 4-point Likert scale. In other studies Cronbachs alpha has been reported as 0.88 and 0.90 and test-retest reliability coefficients = 0.87 (Cohen et al., 1985). Study Protocol Participants were screened for inclusion in the study. For those who met inclusion and exclusion criteria and ag reed to participate, a time and place was agreed upon for the participant to meet with the PI. At this initial meeting, th e consent to participate in research was reviewed with the participant, who then signed the informed consent form approved by the Institutional Review Board Human Subjects Committee at the University of Florida. At this point, th e PI or research assistant cove red the requirements of the study in detail. The PI or research assistant left the Salivettes for saliva collection and the questionnaire and scheduled a time to pick up the saliva and completed questionnaire.

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62 To provide a sample, participants were given 12 tubes called Salivettes (The Sarstedt Group, 2003). Six tubes for each day of collection were provided in separate plastic bags. Saliva collection times were based on the time of awakening and were collected 30 minutes, 1, 4, 9, and 11 hours after waking. Participants were instructed to collect the first saliv a specimen (upon awakening) before rising and getting out of bed. Upright positions may significantly increase salivary cortisol concentrations (Hennig et al., 2000). They were also instructed to pl ace a cotton roll in th eir mouths, chew on it until it became saturated, and place it in the sa livette. Participants were instructed not to brush their teeth, smoke, eat, or drink anything at least tw o hours prior to collection because the factors have been shown to alter salivary cortisol concentrations (Kirschbaum, Read, and Hellhammer, 1992). They were also instructed to place the salivette tubes in the freezer at the end of each day. After being collected by the researcher or research assistant, samples we re centrifuged and stor ed frozen (-20 C). Before analysis samples were thawed and mu cins were precipitated from the specimens at 3000 rpm for 15 minutes. Cortisol was measured by using Expanded Range High Sensitivity Salivary Cortisol Enzyme Immunoa ssay Kit (Salimetrics, 2005). All analyses were conducted according to the manufacturers directions. Samples with greater than 30% coefficient of variation (CV) were re run. Interand intra-assay CV% was less than 15%. Inter-assay CV is based on the high and low controls of 28 plates. Intra-assay CV was based on eight high and eight low control duplicate samples. Participation in this study required a comm itment of completing a survey that took approximately 1 to 1.5 hours to complete a nd completing saliva collection for 2 days. Each saliva collection was estimated to take a maximum of 5 minutes which would entail

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63 an additional 1 hour of the participants time. Given the time burden placed on the participants, a $30.00 gift certificate to Walmart was given to each participant that completed data collection. A $30.00 gift certificate was used as opposed to cash so it would not be counted as income, placing the pa rticipants at risk for loosing food stamp supplements, housing subsidy or other fi nancial assistance through the Temporary Assistance for Needy Families program, if they were receiving these supports. Statistical Analyses Data were analyzed using Stata 9.0 statisti cal software. Two-tailed tests were used in all cases and an alpha level of .05 was se lected a priori to determine significance. Descriptive statistics were tabulated for all variables. Statistical Analysis Approach Before any analyses were conducted, th e primary outcome va riables (general health, state anxiety, depre ssion and SC-AUCg) were examined for normality. Skewness and kurtosis tests for normality were used to examine the distribution of all study variables (see table 3-1 below). General he alth was transformed to a 0 to 100 scale. General health and SC-AUCg were bot h positively skewed; therefore, log transformations were conducted based on the ladder of powers (Hamilton, 2006). Depression was also positively skewed, but was transformed using square root transformation. Choosing a transformation me thod for each outcome variable was based on analyses using ladder of powers. This test combines the ladder of powers with tests of normality (specifically the skewness/kurtosis te st in Stata) and reports whether the result is significantly non-normal (Hamilton, 2006). The transformation with the lowest Chi square and a normal distribution was chosen because most statistical procedures work best when applied to variables that follow a normal distribution.

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64 Table 3-1 Skewness and Kurtosis for Study Variables Neighborhood Characteristics Skewness Kurtosis Adj chi2 Prob>chi2 Neighborhood Economic Disadvant age 0.000 0.089 13.76 0.0010 Neighborhood Disorder 0.305 0.456 1.67 0.434 Neighborhood Stress 0.039 0.515 4.69 0.096 Neighborhood Social Cohesion 0.474 .669 0.71 0.6999 Individual-level Variables Housing Satisfaction 0.001 0.184 10.63 0.005 Unfair Treatment 0.212 0.210 3.26 0.195 Perceived Stress 0.780 0.527 0.49 0.784 Chronic Stress 0.732 0.629 0.35 0.8375 ISEL social support 0.501 .556 0.82 0.2413 Anxiety 0.130 0.510 2.84 0.6637 Depression 0.645 0.007 6.76 0.034 General Health 0.001 0.357 10.05 0.0066 Salivary Cortisol (SC) AUCg_ug/dl 0.000 0.001 26.33 0.0000 Specific Aim 1 The first aim of this study was to de termine the relationships among neighborhood characteristics, perceived stress, psychologi cal distress, and salivary cortisol levels among low SEP female heads of households with children living in either section 8 or public housing. More specificall y, this research sought to examine whether neighborhood characteristics had an independent effect on the outcome variables Bivariate correlation and multiple regressi on analyses were used to determine significant relationships among th e study variables. First simple regression analyses were conducted and nonsignificant explanatory vari ables were not added to subsequent models. Standard multiple regression analyses were utilized to determine associations between neighborhood characteristics, depres sion, anxiety, healt h, and SC-AUCg above and beyond individual level predictors. For all multiple regressions, assumptions were tested by examining normal probability plot s of residuals and scatter diagrams of

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65 residuals versus predicted residuals. No violations of normality, linearity, or homoscedasticity were detected. There was no evidence of influentia l outliers based on stem and leaf plots and studentized residuals. In addition, perceived st ress, chronic stress, anxiety and depression were examined for mu lticollinearity. Finally seemingly unrelated regression is used to compensate for crossequation error correlation between the anxiety and depression equations (Chen, E nder, Mitchell, and Wells, 2006). Issues of Multicollinearity Multicollinearity can occur in multiple regression analysis when independent variables are too highly intercorrelated (Polit, 1996) and is associated with unstable estimated regression coefficients (Cha tterjee, Hadi, and Pr ice, 2000). A thorough investigation of multicollinearity will involve examining the value of R2 that results from regressing each of the pred ictor variables against all the others. Table 3-2 shows collinearity diagnostics for all possible expl anatory variables. Th e relationship between explanatory variables, R2 j would be close to 1, and the variance inflation factor (VIF) would be large. Values of VIF greater th an 10 is indicative of collinearity problems (Chatterjee et al., 2000). To lerance defined as 1/VIF is used also used by many researchers to check on the degree of collinearity. A tolerance value lower than 0.1 means that the variable considered is a linear comb ination of other indepe ndent variables (Chen et al., 2006). In addition, a condition number a comm only used index of global instability greater than or equal to 10 is an indication of global instability. The condition index number for the variables not ed in table 3.2 is 4.66. No problems with collinearity were identified.

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66 Table 3-2 Collinearity Diagnostics for Explanatory Variables Variable VIF ToleranceR2 Condition Index Neighborhood Economic Disadvantage 1.13 0.885 0.11 1.0 Neighborhood Disorder 1.45 0.692 0.31 1.75 Neighborhood Stress 1.95 0.514 0.49 2.05 Neighborhood Social Cohesion 1.67 0.599 0.40 2.41 Unfair Treatment 1.51 0.663 0.34 2.65 Perceived Stress 1.67 .0598 0.40 2.78 Chronic Stress 2.27 0.440 0.56 3.22 Social Support 1.99 0.504 0.50 3.41 Depression 2.87 0.350 0.65 3.50 Anxiety 3.16 0.317 0.68 4.66 Seemingly Unrelated Regression Pairwise correlation of anxiety and depr ession revealed that these two measures had a strong correlation (r, 0.74; p-value < 0.001). Though problems with collinearity when these variables were used as explanator y variables were not revealed as mentioned above, it was suspected that when anxiety and depression were used as dependent variables in separate equations, the regres sion errors may be co rrelated. Correlation of errors in regression models may lead to unde restimation of the re gression coefficients (Chen, Ender, Mitchell, and Wells, 2005). Seemingly unrelated regression allows researchers to estimate both models simultaneously while accounting for the correlated errors at the same time, leading to more a ppropriate standard erro rs (Chen et al., 2005). Unlike traditional multivariate regression, seem ingly unrelated regression allows one to estimate equations that do not have the same set of predictors, allowing more flexibility in model estimation approaches. The estimates provided for the individual equations are the same as the ordinary least squares estimates A ChiSquare test is used to determine the overall fit of the model (Chen et al., 2005) Seemingly unrelated regression was used

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67 instead of multivariate regression because the explanatory variables differed for the two equations. Multi-level Analysis Typically, when data are nested as in this study persons nested within neighborhoods and the study is examining th e contextual effects of neighborhoods on individual health, multi-level analyses are warranted (Diez-Roux, 2000). Multi-level analysis allows researcher s to examine neighborhood-level variation in health among populations (Merlo, Chaix, Yang, Lynch, and Ra stam, 2005) and to test hypotheses about how variables measured at one level (neighbor hoods) affect relations occurring at another (individual) level (Raudenbush a nd Bryk, 2002). It is intuitive that people living in the same neighborhood or in neighborhoods with similar characteristics will have comparable health characteristics. Theref ore, when examining neighborhood contextual effects on individual health, va riation in neighborhood characte ristics is essential. Given the lack of variation in ne ighborhood economic disadvantage in this study (as determined in Aim 2), multi-level statistical an alyses could not be conducted. Specific Aim 2 The second aim of the study was to dete rmine the differences in neighborhood characteristics of two subsidized housing t ypes, specifically section 8 and public housing, in which low SEP female heads of households with children live. Assumptions for using t-tests include ra ndom sampling, a normal distribution, and homogeneity of variance. Skewness and kurtosis tests for normality as shown in Table 3.1 were used to examine the distribution of all outcome variables. Variance comparison tests for each of the neighborhood variables by housing subsidy type showed that the homogeneity of variance assumption was not violated. Neighborhood economic

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68 disadvantage was negatively skewed. Group comp arison t-tests were used to determine the differences in neighborhood disorder, neighborhood stress, and neighborhood social cohesion by housing type. The Mann-Whitney U -test, the non-parametric analogue of the t-test, (Polit, 1996) was used to ex amine differences neighborhood economic disadvantage by housing subsidy type. Specific Aim 3 The final aim of the study was to examin e the differences in housing satisfaction, perceived stress, psychological distress, and sa livary cortisol levels, in low SEP female heads of households with children by housing subsidy t ype (section 8 and public housing). Again, assumptions as noted in the previ ous section were analyzed for violation. General health, housing satisfaction, depr ession, and SC-AUCg were significantly skewed as shown in Table 3.1. SC-AUCg, general health and depression were transformed as previously described. Group co mparison t-tests were performed to detect differences in SC-AUCG, depr ession, perceived stress, chro nic stress, anxiety, social support, and health by housing subsidy t ype. Variance comparison tests showed no violations in homogeneity of varian ce by housing subsidy type. Mann-Whitney U tests were used to examine the differences in housing satisfaction by housing subsidy type because housing satisfaction was a one-item question measured on an ordinal scale and was not normally distributed. Missing Data Missing data were present in several st udy variables including salivary cortisol. Item non-response occurs when a participant does not respond to a question or questions on a survey, which is the case for the missing da ta in this study. Several methods to deal

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69 with missing data are available to research ers depending on the pattern of missing data including case mean substitution, sample and group mean substitution, hot-deck imputation, regression and multiple imputa tion (Fox-Wasylyshyn and El-Masri, 2005; Patrician, 2002). Case-wise single item imput ation using multinomial logistic regression analysis was used to impute data in this study. This method was chosen because it uses a respondents scores on non-missing values with in a scale or subscale to predict missing values. This approach takes into account that missing values may differ based on differences in individual ch aracteristics. The outcome va riables (item codes) were categorical with more than two categories; polytomous or multinomia l logistic regression was preformed to predict the missing value in a subscale. Regression imputation uses knowledge of the available data to predic t values of missing data. The underlying principle is that missing data items can be predicted by other items in the measure or subscale, the resulting regression equation can be used to predict missing values (Patrician, 2002). More specific information is provided regarding missing data patterns in the section Handli ng Missing Survey Data. Handling Missing Cortisol Data Of the 84 participants, 14 did not have usable cortisol data (defined as greater than 2 time points missing in one day). These cases were deleted and not used in data analyses. Of the 70 participants remaining, 49 had complete cortisol data on Day 1 and 46 on Day 2. For statistical analyses missing data at Days 1 and 2 T2 were replaced by the average values from the preceding and fo llowing samples. For example, from table 33 below, one participant was missing cortisol data on Day 1 T2 and T5, and on Day 2 T3. The average of T1 and T3 on Day 1 was used to replace the missi ng data point.(0.219 + 0.44)/2 = 0.66/2 = 0.33. Therefore, 0.33 was the value used to replace the missing data

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70 point for the Day1 at T2. Equation 3-2 provide s a formula for calculating the average for a T2 data point. Table 3-3: Example of Missing Cor tisol Data for One Participant Time of Day Day 1 Day 2 Replacement Value T1 Awakening 0.219 0.094 -T2 30 min after waking 0.225 0.33 T3 60 min after waking 0.44 0.44 T4 4 hr after waking .552 0.272 -T5 9 hr after waking 0.166 0.166 T6 11 hr after waking 0.199 0.122 -Equation 3.2: Formula for Calculated T2 SC for Days 1 and 2 T2 = T1 + T3/2 When data were missing at any time other than T2, the value from the same time point on the preceding or following day was taken. For example, from table 3-3 the participant was missing cortisol data on Day 2, T3 this missing data point was replaced with the value at the same time from the preceding da y (0.44).These techniques have been utilized in other studies (Odber, Cawood, and Bancroft 1998). After imputing SC data, a total of 70 participants were retained for data analysis. Handling Missing Survey Data Once cases were deleted due to missing co rtisol data, missing survey data was imputed. No more than 20% of the data we re missing from any study measure. Before imputing data, missing value patterns were determined by dummy coding missing data for each participant with 0 = no missing data and 1 = at least one missing data point. Study participants were grouped on whether or not missing data was present and twosample t-tests were performed on each study variable. Creating a missing data dummy code and computing t-test comparisons between respondents and non-respondents is

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71 often used to determine if non-responders differ on any of the items in the data set (Wasylyshyn and El-Masri, 2005). A significan t difference between respondents and nonrespondents indicates an association, and rule s out the possibility the data are missing completely at random (MCAR) (Wasylyshyn and El-Masri, 2005). Missing data points are said to be MCAR if the probability of missing data on one variable is not related to the value of that variab le or is not related to other vari ables in the data set (Patrician, 2002). Because the state anxiety was statisti cally significantly diffe rent (t= -1.99, df 70, p=0.05), and the individual social support sc ale approached significance, (t=-1.88, df, 61. p=0.06), data from this study were determined to be missing at random (MAR). MAR occurs when the probability of a missing data point in one variable is not related to the value of that variable (Patri cian, 2002). Each measure used in this study was divided into its appropriate subscales, if present, and multinomial regression analyses were performed for each item missing within a measure base d on items present within the subscale. Case-wise multinomial regression imputation was used to predict missing values. This method ascribes the respondents pred icted score based upon the items that are present within in the missing score subscale for that respondent. The primary advantage of this technique is that it acknowledges differences across cases (respondents) and maximizes any one respondents own data from items in a given subscale. Also, imputing item-level missing data retains the inter-subject variability across summed scores because the majority of information from each particip ant is retained with measurements and their subscales. Using single value regression to re place missing values is most useful when data are 10% 40% incomplete (Wasylyshyn and El-Masri, 2005).

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72 After data imputation for each study variable was complete, three additional participants had to be withdr awn from the study due to exce ssive missing data, leaving a final sample size of 67. In summary, after imputing missing data, 67 women were included in data analysis. Specific aim 1 was addressed by bivariate an alysis, standard multiple and multivariate regressions, and GEE. Specific Aims 2 and 3 are examined by using t-test and the MannWhitney U test depending on the type of variab le under study and whether the normality assumption was met.

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73 CHAPTER 4 RESULTS The first aim of this study was to examine the relationships among neighborhood characteristics, perceived stre ss, psychological distress, and salivary cortisol levels among low SEP female heads of households with children. The second aim was to examine the differences in neighborhood characteristics by housing subsidy type (i.e., public and section 8 housing). Finally, this study sought to determine if participants who lived in public versus section 8 housing differed in te rms of stress, psychological distress, general health and salivary cortisol levels. This chapter first presents descriptive resu lts, including means, standard deviations, and frequency data for each variable. The hypotheses posed in Chapter 1 are addressed using parametric and nonparametric tests. Descriptive Results Description of the Sample As described in Chapter 3, data analysis included a final sample size of 67 women. Most of the participants in th is study were black, single, ha d a high school education or less and one to two children. The mean age was 30 years old. Over half of the participants reported their main daily activity as either looking for work or keeping house and raising children. Mean gross income was $486.50/month. Sixty-four percent of the participants lived in section 8 housing and le ss than one-third were receivi ng direct financial assistance through the Temporary Assistance for Needy Families Program (TANF). Table 4-1 below provides a detailed description of the sample.

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74 Table 4-1: Sample Demographic Profile: (n=67) N % Mean (SD) Range Age --30.33 (8.31) 18-45 Income --486.50 (440.71) $0-$2,100 Race White Black Hispanic/Latino 12 54 1 17.91 80.60 1.49 --Marital Status Married Single Divorced/Separated 6 57 3 9.09 86.36 4.55 --Education Less than 9th grade Less than 12th grade High School Diploma General Education Diploma Some College/Training Associates Degree 4 21 9 10 16 5 6.15 32.31 13.85 15.38 24.62 7.69 --Number of Children 1-2 3-4 5-7 44 21 2 65.87 31.34 2.98 --Daily Activity Work Full-time Work Part-time School Full-time School Part-time Work and School Part time Unemployed Keep House/Raise Children 9 10 4 4 6 20 30 13.43 14.93 5.97 5.97 8.96 25.37 25.37 --Housing Type: Public Hosing Section 8 Housing 24 43 35.82 64.18 --TANF Assistance Yes No 23 44 29.03 70.97 --Neighborhood Characteristics of the Sample Two-thirds of the participants lived in neighborhoods with the greatest amount of economic disadvantage that were characterized by high rates of disorder, and exposure to crime. (See figure 4-1).

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75 1.4931.4931.493 16.42 13.43 2.985 62.69 0 20 40 60 Percent 0 3 6 9 12 NED Figure 4-1: Neighborhood Ec onomic Disadvantage (NED) for all Participants Over 50% of the participants scored above the mean on neighborhood disorder while 25% scored will over the mean of 37.15 on neighbor hood stress indicating that they perceived their neighborhoods as areas with high rates of and crime. In addition, these women also reported higher rates of social cohesion which is not surprising given that studies have shown that neighborhood social cohesion may buffer the effects of neighborhood disorder and stress (Ross and Jang, 2000). See Table 4.2 on the following page. Table 4-2: Sample Descripti on of Neighborhood Characteristics. Variables Mean (SD) Range Neighborhood Characteristics Neighborhood Economic Disadvantage 10.16 (.66) 1-12 Neighborhood Disorder 36.52 (.98) 16-55 Neighborhood Stress (Crime E xposure) 37.15 (.89) 18-72 Neighborhood Social Cohesion 13.31 (.86) 5-25

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76 Stress, Psychological Distress, Health, and Salivary Cortisol Sample Characteristics Table 4-3 provides mean scores and ranges fo r all individual level psychosocial and stress variables. Table 4-3: Stress, Psychological Distress, Health and Salivary Cortisol Scores Variables Mean (SD) Range Unfair Treatment 21.49 (.35) 10-36 Perceived Stress 28.64 (.87) 12-45 Chronic Stress 52.82 (.48) 0-105 Individual Social Support 70.46 (.76) 26-117 Depression 24.73 (.77) 2-47 State Anxiety 44.67 (.95) 20-70 General Health 37.21 (.69) 0-100 Salivary Cortisol (AUC) ug/dl 2.84 (.19) 0.227-10.71 Salivary cortisol levels vary based on th e time at which the sample is taken. The ranges of salivary cortisol in this sample of women are within th e ranges for healthy women of the same age group reported by ot her investigators (K irschbaum, Read, and Hellhammer, 1992). Table 4-4 provides mean scores and ranges for salivary cortisol measures by day and time. Table 4-4 Salivary Cortisol Scores by Day and Time Salivary Cortisol (ug/dl) by Day/Time Mean (SD) Range Day 1 Time 1 awakening 0.315 (.259) 0.02-1.25 Time 2 30 minutes after waking 0.328 (0.277) 0.02-1.27 Time 3 60 minutes after waking 0.261 (0.256) 0.016-1.48 Time 4 4 hours after waking 0.255 (0.241) 0.015-1.08 Time 5 9 hours after waking 0.195 (0.235) 0.015-1.17 Time 6 11 hours after waking 0.194 (0.227) 0.011-0.91 Day 2 Time 1 awakening 0.292 (0.275) 0.013-1.53 Time 2 30 minutes after waking 0.332 (0.32) 0.015-1.40 Time 3 60 minutes after waking 0.269 (0.237) 0.014-0.91 Time 4 4 hours after waking 0.223 (0.236) 0.017-1.10 Time 5 9 hours after waking 0.180-(0.201) 0.007-0.84 Time 6 11 hours after waking 0.136 (0.172) 0.017-0.83

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77 Overall, this sample of women reported highe r levels of anxiety and scored lower on general health compared to national norms (Spielberger, Gorsuch, Lushene, Vagg, and Jacobs, 1983; Ware, Kosinski, Turner-Bowke r, and Gandek, 2002; Weissman, Sholomskas, Pottenger, Prussoff, and Locke, 1977) indicat ing poorer health. (S ee Table 4-5). They scored well above the cut off of 16 on the CES-D, which indicates depressive symptoms are high enough to suggest clinical depression with a mean of 24.73. Table 4-5: Mean Psychologica l Distress and General Health Scores Compared to National Norms Sample Mean (SD) Norm for females of same age (SD) State Anxiety 44.67 ( 11.95) 35.20 ( 10.61) Depression 24.73 ( 11.77) >16 Suggests clinical depression General Health 37.21 ( 27.69 49.84* 52.11** 51.01*** ( 10.62) ( 9.86) ( 8.70) National norms for women 18-24 years old ** National norms for women 25-34 years old *** National norms for women 35-44 years old Specific Aim 1: Associations among Ne ighborhood Characteristics, Stress, Psychological Distress, Heal th and Salivary Cortisol The first aim of this study was to determine the relationships among neighborhood characteristics, perceived stre ss, psychological distress, and salivary cortisol levels among low SEP female heads of household with childr en 18 years old or less. It was hypothesized that higher rates of neighborhood disorder, exposure to crime, and neighborhood economic disadvantage, and elevated leve ls of stress would be positiv ely associated with depression, state anxiety, and salivary cortisol and nega tively associated with general health. More specifically, this research i nvestigated whether neighborhood ch aracteristics had an effect on any of the outcome when individual level factors (perceived stre ss, unfair treatment, chronic stress, and social support) were added to the model.

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78 Bivariate Analyses of Neighborhood Charac teristics, Housing Satisfaction, Stress, Depression, State Anxiety, He alth and Salivary Cortisol Based on bivariate correlations the hypot heses for specific aim 1 are partially supported. Neighborhood disorder (ND), ne ighborhood stress (NS), and neighborhood social cohesion (NSC) have significant weak to moderate positive associations with depression, chronic stress, and unfair trea tment. Only ND and NS were positively associated with perceived stress. NSC had a positive, but weak association with housing satisfaction and a weak negative correlation with chronic stre ss. Housing satisfaction also had a weak negative association with unfai r treatment. (See Table 4-6). Neighborhood economic disadvantage (NED) was not associated with any of the outcome variables in this study. The remainder of this section is orde red based on the outcome variable under study. First, predictors of general health are pres ented, followed by state a nxiety, depression and finally SC-AUCg. Table 4-6: Correlations between Neighborhood Characteristics, Housing Satisfaction, Psychological Distress, General He alth, and Salivary Cortisol NED a ND NS NSC Housing a Satisfaction Housing Satisfaction a -0.033 0.23 (0.06) -0.20 0.30* State Anxiety -0.12 0.22 (0.06) 0.37** -0.14 -0.11 Depression (sqrt) -0.17 0.29* 0.39** -0.24* -0.06 General Health (log) -0.07 -0.09 -0.04 .019 0.057 Unfair Treatment -0.19 0.41*** 0.35** -0.29* -0.25* Perceived Stress -0.14 0.26* 0.39** -0.19 -0.02 Chronic Stress -0.15 0.48*** 0.52*** -0.25* -0.04 Salivary Cortisol (SC) AUCg ug/dl (log ) 0.07 -0.09 -0.11 0.13 -0.08 Note: *p < 0.05 **p < 0.01 ***p<0.001; n = 67

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79 General Health, Neighborhood Characterist ics, Stress, and Psychological Distress As previously stated, general health was log transformed to obtain a normal distribution. Bivariate regre ssion analysis revealed that unfair treatment and smoking significantly impacted health in this sample of women. However, the magnitude of the effect of unfair treatment is quite small (adj. R2 = 0.05, F (1,65 = 4.37. p-value <0.05) accounting for only five percent of the vari ability in general health. Smoking (adj. R2 = 0.11, F (1, 65 = 8.85. p-value <0.01) accounted for 11% of the variation in health. As shown in table 4-7 below, none of the other va riables in this study ha d a significant effect on general health. Table 4-7: Bivariate Regressi on Results for General Health Variable B SE Adj R2 F 95% CI Neighborhood Characteristics Neighborhood Economic Disadvantage -0.006 0.021 0.001 0.08 -0.05 0.04 Neighborhood Disorder -0.003 0.007 0.02 0.25 -0.017 0.01 Neighborhood Stress -0.001 0.005 0.004 0.04 -0.010.008 Neighborhood Social Cohesion 0.013 0.008 0.001 2.34 -0.004 0.036 Individual Level Factors Perceived Stress (PSS) -0.013 0.008 0.03 2.90 -0.03 0.002 Chronic Stress (TCSI) -0.002 0.003 -0.01 0.45 -0.01 0.003 Unfair Treatment -0.178* 0.008 0.05 4.37 -0.35 0.001 State Anxiety -0.01 0.004 0.01 1.89 -0.01 0.002 Depression -0.007 0.005 0.02 2.18 -0.02 0.002 Individual Social Support (ISEL) 0.003 0.003 0.004 1.23 -0.002 0.008 Age -0.008 0.006 0.007 1.49 -0.02 0.005 Marital Status -0.13 0.15 0.01 0.73 -0.43 0.17 Number of children -0.01 0.05 -0.01 0.06 -0.1 0.08 Education 0.01 0.04 -0.01 0.08 -0.06 0.08 Monthly Income -0.00 0.00 -0.01 0.17 -0.0003 0.00 Smoking -0.40** 0.14 0.11 8.85 -0.68 -0.13 Note: *p < 0.05 **p < 0.01 ***p<0.001; df (1, 65); n = 67

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80 Multiple regression analysis of the effects of smoking and unfair treatment on health showed that both variables are signifi cant predictors of health (adj. R2 = 0.11, F (2, 64 = 6.76. p-value <0.01) (table not shown). Potent ial confounding variables considered were age, race, marital status, number of childre n living in the househol d, income, and smoking. None of these variables (other than smoking) were significantly associated with general health in bivariate regression analyses. Neighborhood and Individual Leve l Effects on State Anxiety Bivariate analyses (see Table 48) show that neighborhood stress (disorder plus exposure to crime) significantly affects state anxiety a ccounting for 13% of the variation (Adj. R2 0.13, F (1, 65) = 10.56, p-value 0.002). No other neig hborhood characteristics had an impact on state anxiety. Table: 4-8: Bivari ate Regression Results for State Anxiety Variable B SE Adj. R2 F 95% CI Neighborhood Characteristics Neighborhood Economic Disadvantage -0.67 0.55 0.023 1.50 -1.77 0.42 Neighborhood Disorder 0.33 0.18 0.036 3.43 -0.03-0.70 Neighborhood Stress 0.37** 0.11 0.13 10.56 0.14 0.61 Neighborhood Social Cohesion -0.26 0.23 0.004 1.29 -0.73 0.20 Individual Characteristics Unfair Treatment 0.38 0.23 0.03 2.78 -0.075 0.84 Perceived Stress (PSS) 1.01*** 0.18 0 .33 32.94 0.66 1.36 Chronic Stress (TCSI) 0.30*** 0.06 0.28 27.18 0.19 0.42 Individual Social Support -0.35*** 0.06 0.37 39.92 -0.47 -0.24 Age -0.04 0.18 -0.01 0.04 -0.40 0.32 Race 3.27 2.09 0.02 2.45 -0.90 7.45 Education -1.3 0.10 0.01 1.80 -3.27 0.64 Income -0.005 0.003 0.01 1.90 -0.01 0.002 Marital Status 4.6 4.02 0.005 1.30 -3.4 12.6 Number of children -1.7 1.25 0.01 1.85 -4.22 0.8 p <0.05, ** p <0.01, *** p<0.001: df 1, 65 n = 67 The final model for state anxiety included ne ighborhood stress, perceived stress, chronic stress and individual social s upport. Covariates considered we re, age, marital status, race,

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81 education, income, and number of children liv ing in the household. N one of these suspect covariates had a significant impact on state anxiety and were not included in the final model. Neighborhood stress, perceived stress, ch ronic stress and social support were added to the final model. Once individual level characteristics were added to the model, neighborhood stress no longer had an effect on st ate anxiety. Together perceived stress and social support accounted for almost 50% of the variation in state anxiety (Adj. R2 = 0.49, F (4, 62) = 17.12, p < 0.001). See Table 4-9 below Table 4-9 Effects of Neighborhood and Individu al Level Characteristics on State Anxiety Variable B SE 95% CI Neighborhood Characteristics Neighborhood Stress -0.13 0.11 -0.22 0.20 Individual Level Factors Perceived Stress (PSS) 0.60 ** 0.18 0.22 0.93 Chronic Stress (TCSI) 0.11 0.64 -0.01 0.24 Individual Social Support (ISEL) -0.21*** 0.63 -0.33 -0.08 Note: n = 67 F(4, 62) = 17.12 Adj. R2 = 0.49*** p <0.05, ** p <0.01, *** p<0.001: Depression, Neighborhood Ch aracteristics and Stress Bivariate analyses show that neighborhood disorder (Adj R2 0.07, F (1, 65) = 6.16, pvalue < 0.05), neighborhood stress (Adj. R2 0.14, F (1, 65) = 11.42, p-value < 0.01) and neighborhood social cohesion (Adj. R2 0.04, F (1, 65) = 4.04, p-value < 0.05) have mild effects on depression scores in th is group of women. See table 4-10. Individual factors such as perceived stress (Adj. R2 0.26, F (1,65) = 24.42, p-value < 0.001), chronic stress (Adj. R2 0.39, F (1,65) = 43.32, p-value < 0.001), unfair treatment (Adj. R2 0.14, F (1,65) = 11.92, p-value < 0.01), and i ndividual social support (Adj. R2 0.26, F (1,65) = 24.27, p-value < 0.001) also significantly impact depression. Due to the small sample size and the large number of variables, significant neighborhood and individual level variables in Table 4-11 were put into separate multiple regression

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82 models. Variables that continued to have a statistically significant effect on depression were put in the final model. Table 4-11 illustrates the first model and shows which neighborhood variables remain significant pred ictors of depression. When all neighborhood level variables were added to the model, only neighborhood stress remained significant (Adj. R2 0.13. F (3. 63) = 4.38, p value < 0.01). Theref ore, neighborhood stress was placed in the final model. Table 4-10: Neighborhood, Psychosocial, and Individual Effects on Depression (CES-D) Variable B SE Adj. R2 F 95% CI Neighborhood Characteristics Neighborhood Economic Disadvantage -0.08 0.06 0.01 1.89 -0.02 0.04 Neighborhood Disorder 0.05* 0.02 0.07 6.16 0.01 0.09 Neighborhood Stress 0.04** 0.01 0.14 11.42 0.02 0.07 Neighborhood Social Cohesion -0.05* 0.02 0.04 4.04 -0.1 -0.0003 Individual Level Factors Perceived Stress (PSS) 0.1*** 0.02 0.26 24.42 0.06 0.14 Chronic Stress (TCSI) 0.04*** 0.006 0.39 43.32 0.03 0.05 Unfair Treatment 0.08** 0.024 0.14 11.92 0.03 0.13 Individual Social Support (ISEL) -0.03*** 0.007 0.26 24.27 -0.05 -0.02 Age -0.02 0.02 0.005 0.69 -0.05 0.02 Marital Status 0.43 0.44 -0.001 0.94 -0.46 1.31 Number of children -0.20 0.14 0.015 2.00 -0.47 0.08 Race 0.11 0.24 -0.01 0.23 -0.36 0.58 Education -0.18 0.11 0.03 2.90 -0.40 0.03 Income -0.0007 0.0004 0.04 3.41 -0.002 000 Note n = 67 df (1, 65) p <0.05, ** p <0.01, *** p<0.001: The second model consists of significant in dividual level factors from Table 4-10 above. As shown in Table 4-11, only perceived and chronic stress (Adj. R2 0.47. F (4. 62) = 15.85, p value < 0.01) continue to be significant predictors a ccounting for almost 50% of the variation in depression. In the fi nal model neighborhood stress no longer has a significant effect on depression. For this sample of women, perceived and chronic stressors

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83 (Adj. R2 0.45, F (3. 63) = 18.85, p value < 0.001) ar e more important predictors of depression than neighborhood disorder and exposure to crime. Table 4-11: Regression Results for Neighborhood and Psychosocia l Measures as Predictors of Depression Variable B SE 95% CI Model 1 Neighborhood Level Factors n = 67, F (3, 63) = 4.38; Adj. R2 0.13** Neighborhood Disorder 0.006 0.25 [-0.45 0.06] Neighborhood Stress 0.45* 0.19 [ 0.07 0.83] Neighborhood Social Cohesion -0.03 0.03 [-0.09 0.02] Model 2 Individual Level Factors n = 67, F (4, 62) = 15.85; Adj. R2 0.47** Perceived Stress (PSS) 0.05* 0.02 [0.01 0.09] Chronic Stress (TCSI) 0.02** 0.007 [0.008 0.04] Unfair Treatment 0.25 0.02 [-0.02 0.07] Individual Social Support (ISEL) -0.01 0.007 [-0.02 0.003] Final Model Combined n = 67, F (3, 63) = 18.85; Adj. R2 0.45** Neighborhood Stress 0.01 0.15 [-0.29 0.31] Perceived Stress (PSS) 0.06** 0.02 [0.02 0.09] Chronic Stress (TCSI) 0.03*** 0.007 [0.02 0.04] p <0.05, ** p <0.01, *** p<0.001: Seemingly Unrelated Regression Analysis of Anxiety and Dep ression Regression Equations The correlation matrix of residuals for anxiety and depression was 0.52. BreuschPagan test of independence reve aled that the residuals from the two equations above are not independent (Chi Square 18.24, p-value < 0.001) Table 4-12 shows seemingly unrelated regression results for anxiety and depression regression models. Again, with individual level factors added to the model, neighborhood st ress is no longer a predictor of anxiety or depression. Both perceived stress and chroni c stress remain significant predictors of depression and anxiety. Social s upport is also a significant pred ictor of anxiety with lower levels of social support associat ed with higher levels of anxiety.

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84 Possible confounding variables included weight smoking, hours of slee p, and presence of an acute stressor, and menstrual cycle phase None of these factors were significantly associated with SC-AUCg. The only individua l level factors associated with SC-AUCg were unfair treatment (Adj. R2 0.13, F (1. 65) = 11.26, p value < 0.01) and weight (Adj. R2 0.04, F (1. 65) = 4.05, p value < 0.05). Table 4-12 Seemingly Unrelated Regressi on Analysis of Anxiety and Depression Equations Equation Obs. Parms. RMSE R2 Chi2 P CESD 67 3 0.95 0.47 60.12 0.000 State Anxiety 67 4 8.22 0.52 71.32 0.000 B SE Z p-value 95% CI Depression Equation Neighborhood Stress 0.002 0.14 0.08 0.94 [-0.27 0.30] Perceived Stress 0.06 0.02 2.98 0.003 [0.02 0.09] Chronic Stress 0.03 0.007 4.49 0.000 [0.17 0.044] Anxiety Equation Neighborhood Stress 0.0005 1.25 -0.10 0.92 [-2.59 2.34] Perceived Stress 0.62 0.17 3.64 0.000 [0.28 0.95] Chronic Stress 0.13 0.06 2.21 0.03 [-0.26 -0.06] Social Support -0.16 0.05 -3.08 0.002 [-0.26 -0.06] When these variables were added to a multiple regression model both remained significant predictors of salivary cortisol (Adj. R2 0.21, F (2. 62) = 9.32, p value < 0.001) and accounted for 20% of the variability in mean salivary cortisol over the day. See table 414. Contrary to the hypothesis th at unfair treatment (stress) would be positively associated with SC-AUCg, for each 0.04 point increase in unfair treatment SC-AUCg decreased by one unit (ug/dl). Given the limitations regarding the lack of sensitivity of SC-AUCg to differences in individual cortisol levels ove r time and the correlation of repeated salivary cortisol measures within each person as discussed in chapter 3, general estimating equations (GEE)

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85 were also used to examine the relationshi ps among neighborhood characteristics, stress, psychological distress and salivary cortisol. Table 4-13: Simple Regression SC-AUCg Variable SE Adj. R2 F 95% CI Neighborhood Characteristics Neighborhood Economic Disadvantage 0.02 0.03 -0.01 0.29 -0.05 0.08 Neighborhood Disorder -0.003 0.01 -0.014 0.09 -0.02 0.018 Neighborhood Stress -0.006 0.007 -0.003 0.82 -0.02 0.01 Neighborhood Social Cohesion 0.01 0.01 0.003 1.21 -0.01 0.05 Individual Characteristics Unfair Treatment -0.04** 0.012 0.13 11.26 -0.06 -0.02 Perceived Stress -0.022 0.12 0.04 3.48 -0.04 0.002 Chronic Stress -0.002 0.004 -0.010 0.35 -0.01 0.005 Individual Social Support 0.004 0.004 0.0002 1.01 -0.004 0.01 Depression -0.01 0.007 0.016 2.06 -0.02 0.004 Anxiety -0.011 0.007 0.027 2.80 -0.02 0.002 Weight -0.004* 0.002 0.04 9.32 -0.01 -0.00003 Birth Control 0.18 0.27 -0.009 0.44 -3.65 0.73 Menstrual Cycle Phase -0.09 0.12 -0.007 0.54 -0.33 0.15 Smoking -0.14 0.22 -0.01 0.41 -0.57 0.29 Sleep Hrs Day 1 Day 2 -0.17 0.04 0.04 0.05 -0.01 -0.003 0.19 0.76 -0.09 0.06 -0.5 0.13 Acute Stressor Day 1 Day 2 -0.06 0.19 0.19 0.25 -0.01 -0.006 0.11 0.59 -0.43 0.31 -0.31 0.70 Age 0.008 0.01 0.01 0.75 -0.01 0.03 p <0.05, ** p <0.01, *** p<0.001; df 1, 65 Table 4-14: Multiple Regression of Indi vidual Level Characteristics on SC-AUCg Variable B SE 95% CI Unfair Treatment -0.045*** 0.01 -0.07 -0.02 Weight -0.004* 0.002 -0.007 -0.0008 Note: n = 65 F(2, 62) = 9.32 Adj. R2 = 0.21*** p <0.05, ** p <0.01, *** p<0.001: As stated in chapter 3, in addition to us ing standard regression, GEE was used to examine the relationship between neighborhood ch aracteristics, stress, and psychological

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86 distress and repeated measures of saliva ry cortisol. Using GEE methodology, neighborhood characteristics do not have an effect on sa livary cortisol. In this sample of women, perceived stress and unfair treatment are negativ ely associated with salivary cortisol. As seen in the final model, the GEE approach yi elds more conservative results compared to standard multiple regression using AUCg. For each unit change in unfair treatment and perceived stress salivary cortisol decreases by 0.02 and 0.03 units respectively, after controlling for other potentia lly confounding psychosocial an d physiological stressors (p <0.05). See table 4-15. Table 4-15: GEE Population Averaged Model of Effects of Neighborho od Characteristics, Stress and Psychological Dist ress on Salivary Cortisol Variable B SE p 95% CI Neighborhood Characteristics Multiple Regression Number of observations = 804; number of groups = 67; Wald Chi2 = 7.02; p = 0.22 Neighborhood Economic Disadvantage -0.007 0.03 0.80 -0.066 0.50 Neighborhood Disorder 0.09 0.01 0.47 -0.016 0.03 Neighborhood Stress -0.01 0.008 0.18 -0.025 0.005 Neighborhood Social Cohesion 0.007 0.02 0.77 -0.040 0.053 Individual Level Characteristics Multiple Regression Number of observations = 804; number of groups = 67; Wald Chi2 = 16.42; p = 0.02 Unfair Treatment -0.031 0.013 0.02 -0.06 0.005 Perceived Stress -0.29 0.013 0.04 -0.05 0.002 Chronic Stress 0.005 0.005 0.27 -0.004 0.014 Individual Social Support 0.0001 0.005 0.98 -0.009 0.009 Depression 0.009 0.010 0.41 -0.012 0.009 Anxiety -0.007 0.011 0.53 -0.027 0.014 Final Model Controlling for Individual SES, physiological factors and health behaviors Number of observations =768; num ber of groups = 64; Wald Chi2 = 19.73; p = 0.01 Unfair Treatment -0.02 0.012 0.03 -0.05 -0.002 Perceived Stress -0.025 0.011 0.02 -0.05 -0.003 Monthly Income -0.0001 0.0002 0.64 -0.0004 0.0003 Weight -0.003 0.002 0.07 -0.006 0.0003 Menstrual Cycle Phase 0.06 0.11 0.60 -0.16 0.27 Smoking Packs per day -0.14 0.19 0.47 -0.52 0.24 Number of Children in household -0.029 0.063 0.65 -0.15 0.09

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87 Specific Aim 2: Differences in Neighborh ood Characteristics by Housing Subsidy Type The second aim of this study was to de termine the differences in neighborhood characteristics of two subsidized housing t ypes, specifically section 8 and public housing, in which low SEP female heads of households with children live. It was proposed that public housing sites would have significantly mo re neighborhood disorder, greater levels of neighborhood disadvantage, higher levels of neighborhood stress, higher reports of crime exposure, and lower levels of neighborhood so cial cohesion than section 8 housing sites. Group comparison T-test and Mann-Whitney U -test were used to test whether neighborhoods differed by housing subsidy type. Eighty percent of the women living in public housing lived in the most economically disadvantaged neighborhoods, while a little over one half of those living in section 8 housing lived in the poorest areas. Figure 4.2 illustrates the differe nces in neighborhood economic disadvantage by housing subsidy type. As shown in table 3-1, skewness and kurtosis tests for normality showed that NED is significantly skewed to the left. Therefore, the Mann-Whitney U test was used to test whether there were differences in NED by housing subsidy type. The hypotheses were partially supported. Women living in secti on 8 housing units were located in more economically advantaged areas (z = -2.552, p<0. 05) (table not shown). No differences in neighborhood disorder, exposure to crime, or collective efficacy by housing type were found in this sample of women. Specific Aim 3: Differences in Stress, Ps ychological Distress, Health and Salivary Cortisol by Housing Type The final aim of this study was to exam ine the differences in housing satisfaction, perceived stress, psychological distress, and sa livary cortisol levels, in low SEP female

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88 heads of households with child ren by housing type. It was pur ported that women living in public housing would experience significantly lower levels of housing satisfaction, have higher levels of perceived stre ss, psychological distress, and gr eater alterations in salivary cortisol secretion than wome n living in section 8 housing. Figure 4.2: Neighborhood Econom ic Disadvantage (NED) by Housing Subsidy Type The outcome variables were housing satisfa ction, perceived stress, chronic stress, state anxiety, depression and SC-AUCg. Hous ing satisfaction is an ordinal variable; therefore the Mann-Whitney test was used to examine differences in housing satisfaction by housing type. T-tests were used for all other variables. There were no differences in any of the outcome variables by housing subsidy type. The hypotheses for this specific aim were not supported. 2.326 2.326 20.93 18.6 4.651 51.16 4.167 8.333 4.167 83.33 0 50 100 0 5 10 15 0 5 10 15 Section 8 Public Housing Percent NEDGraphs by SQ_S8PH

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89 The hypotheses for specific aims one and two were partially supported. Study results did not support specific aim three. Th e women in this study have higher rates of state anxiety and depression, and lower levels of general health compared to national norms for the same age group. Neighborhood disorder and crime exposure were mildly to moderately associated with increased levels of perceived stress, unfair treatment, chronic stress, depression and anxiety. However, the neighborhood effects on depression and anxiety became statistically insignificant when perceived stress, unfair treatment, chronic stress and other individual level covariates were added to the mode l. The following chapter provides a detailed discussion on the study resu lts, discusses the limita tions of the study and implications for public health nursing research and practice.

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90 CHAPTER 5 DISCUSSION AND RECOMMENDATIONS This chapter presents major study find ings, addresses study limitations and discusses implications for publ ic health nursing research a nd practice. First, findings regarding sample characteristics are discusse d. Then major findings for each specific aim and associated hypotheses are presented. Next study limitations are acknowledged. Finally, implications for public health nur sing research and practice are discussed. Major Findings This study is unique in its design and atte mpts to examine the associations among housing type, neighborhood characteristics, stre ss, psychological distress, health, and the hypothalamic-pituitary-adrenal axis (HPA axis ), specifically salivary cortisol. Salivary cortisol samples were collected for two da ys in women living in section 8 or public housing while in their natural setting going about their daily routine. To date only one study has examined neighborhood characteristic s (neighborhood socioeco nomic status) in relation to the HPA axis, sp ecifically cortisol levels; however, that study examined cortisol as a response to an acute stressor, as opposed to basal levels in relation to chronic stress exposures. Kapuku, Trieber and Davis (2002) colleagues examined the association between neighborhood socioeconomic status (S ES), cardiovascular function, and plasma cortisol in response to laboratory-induced st ress in a sample of 24 black males 16 to 25 years old. They found that family SES was relate d to baseline serum cortisol level (partial r = .46, p<.05), but the correlation between neighborhood SES was not statistically significant (Kapuku, Treiber, and Davis, 2002). Other studies have examined individual-

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91 level factors such as perceived stress and burnout (Grossi et al., 2005; Zarkovic et al 2003), depression and an xiety (Takai et al 2004; Vedhara et al. 2003) and individuallevel SES (Cohen, Doyle, and Baum, 2006) in re lation to cortisol. However, the present study is the first to examine the associati ons between other neighborhood characteristics (disorder, crime, and social cohesion and neighborhood economic disadvantage) and salivary cortisol levels in a community setting. In addition, th is study sought to determine if any differences are present in neighbor hood characteristics, stress, psychological distress, and salivary cortis ol by housing subsidy type (section 8 and public housing). Sample Characteristics Consistent with national housing data (U S. Department of Housing and Urban Development, 1998), the majority of women is this study were Black, single female heads of households with one or two children and a high school diploma or GED as the maximum level of education. Their mean annual income was $5, 838.00 which is well below the 2006 poverty guidelines for two, th ree, and four persons households ($13,200, 16,660, and 20,000 respectively) (United States Department of Health and Human Services, 2006). Despite their low-income, less than 1/3 of the women in this study received financial assistance from the Tem porary Assistance for Needy Family programs. Information on food stamp assistance or involvement in the Women, Infants and Children program was not obtained. Other studies have show n that poor women experience more social stressors (McAlliste r and Boyle, 1998; Turner and Avison, 2003) and have poorer physical and mental health (Artazcoz, Borrell, Benach, Cortes, and Rohlfs, 2004; Macran, Clarke, and Joshi, 1996). The women in this study reported higher rates of state anxiet y and poorer general health than the national norms. Almost one -half of the sample (49.25%) scored well

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92 above the cut off of 16 (mean 24.73) on the CE S-D, suggestive of clinical depression. Other studies have also demonstrated that women living in subsid ized housing report poorer mental and physical health (Faut h, Leventhal, and Brooks-Gunn, 2004; Leventhal and Brooks-Gunn, 2003; Welch, 1997). Similar to these findings, Popkin and colleagues (2002) evaluated residents involved in the HOPE VI program, a major fe deral initiative to transform distressed public housing nationwide by demolishing dist ressed developments and replacing them with mixed-income housing. In the baseline report (status before moving), adult public housing residents reported higher rates of depression (60% higher than the national population average) and lower rates of overall health than the national average (29% of adults in public housing older than 50 years of age versus 30% for adults in the same age group nationally) (Popkin et al 2002). Specific Aim 1: Relationships between Neighborhood Characteristics Stress, Psychological Distress, Heal th and Salivary Cortisol Several hypotheses are associated with specific aim 1 and are divided into neighborhoodand individual-level factors. Th e final hypothesis relevant to specific aim 1 was that neighborhood characteristics woul d have an effect on depression, anxiety, general health and SC-AUCg above a nd beyond individual level stressors. Neighborhood level hypotheses Regarding neighborhood-level factors, it was posited that women living in neighborhoods with high levels of nei ghborhood economic disadvant age, disorder and crime would have higher levels of perceived stress, chronic stress, anxiety, depression SC-AUCg, and lower levels of general heal th. Higher levels of neighborhood social

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93 cohesion were hypothesized to be associated with lower levels of perceived stress, chronic stress, anxiety, depression, SC-AUCg and be tter general health. The hypotheses for specific aim one were pa rtially supported. Fi ndings reveal that neighborhood disorder and crime exposure are mildly to moderately correlated with increased levels of stress and psychological distress, but not genera l health, SC-AUCg, or repeated time-specific measures of salivary co rtisol. These findings are consistent with other studies investigating neighborhood eff ects on stress, psychol ogical distress, and health (Boardman, 2004; Boardman, Finc h, Ellison, Williams, and Jackson, 2001; McAllister and Boyle, 1998; Steptoe and Feldman, 2001). In the present study, neighborhood economic di sadvantage was not associated with stress, psychological distress, general health or SC-AUCg. Other studies investigating the relationships between neighborhood SES and health have revealed inc onsistent findings. Some studies have documented an associ ation between neighborhood SES and stress (Boardman et al., 2001; Schulz et al., 2000) and psychologica l distress and health (Ross and Mirowsky, 2001). In contrast, other studies have not found a signi ficant relationship between neighborhood SES, stress, psychol ogical distress and health (Henderson et al 2005; Kapuku et al., 2002). Inconsistencie s in the neighborhood effects and stress literature are likely due to different inde xes used to measure neighborhood effects on health as well as the use of different methods and instruments used to measure stress. More studies are needed using consistent neighborhood measures to better understand the contextual effects of neighborhoods on health. Neighborhood social cohesion was shown to have weak negative associations with depression, unfair treatment, and chronic stress, but not with anxiety and perceived stress

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94 as hypothesized. Furthermore, neighborhood so cial cohesion was not associated with general health or SC-AUCg in the present study. Ellaway, Macintyre and Kearns (2001) revealed similar findings in their study on pe rceptions of place and health in socially contrasting neighborhoods. They found that perceived neighborhood social cohesion was not significantly associated w ith general self-ass essed health, but there was a negative weak association (R2 -0.149, p <.05) with mental h ealth (Ellaway, Macintyre, and Kearns, 2001). However, other studies inve stigating the relations hip between social cohesion and health have found that social cohesion may serve as a buffer between perceived neighborhood disorder and health, especially physical functioning (Feldman and Steptoe, 2004; Ross and Jang, 2000). To date, no studies have examined the relationships among neighborhood disorder, crime exposure and social cohesion on salivary cortisol levels. Discussion Regarding Indi vidual Level Hypotheses It was hypothesized that perceived stress, ch ronic stress and unfair treatment would be positively associated with depressi on, anxiety and SC-AUCg; and negatively associated with general health. Individual so cial support would be ne gatively associated with perceived stress, chronic stress, de pression, anxiety and SC-AUCg and positively associated with general health. Perceived stress and individual social s upport accounted for almost half of the variation in stat e anxiety (Adj. R2 = 0.49, F (4, 62 p < 0.001). Where as perceived and chronic stress accounted for 45% of the va riation in depression scores (Adj. R2 0.45, F (3, 63) = 18.85, p-value < 0.01). These findings ar e consistent with numerous studies that have documented significant associations betw een perceived stress, chronic stress social

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95 support and psychological distress (anxiet y and depression) (Elliot, 2000; Ross, Reynolds, and Geis, 2000; Schulz et al 2006). This study did not find a significant a ssociation between SC-AUCg perceived stress, chronic stress, depression or anxiety using standard multiple regression methods. However when GEE was used perceived st ress and unfair treatment was negatively associated with mean salivary cortisol. Th ese findings are similar to others in the literature. However, inconsistencies in findings are common. For example, Takai and colleagues (2004) did not find a significant associa tion between basal salivary cortisol levels and State Trait Anxiety Inventory sc ores; where as other researchers have found significant relationships between stress, depression, anxiety and basal salivary cortisol levels (Polk, Cohen, Doyle, Skoner, and Kirschbaum, 2005; van Eck, Berkhof, Nicolson, and Sulon, 1996; Vedhara et al., 2003). Howeve r, these studies vary in their methodology which may influence their findings. For exam ple, Polk and colleagues (2005) obtained salivary cortisol samples in a hotel setting pr ior to viral exposure. In this setting, the change in normal routine as well as anticip atory stress regarding voluntary viral exposure may disrupt the normal cortisol levels in these participants. Vedhara et. al (2003) examined salivary cortisol using both AUC a nd rate of change in a sample of 54 women attending a diagnostic breast clinic with su spected breast disease. Again, examining salivary cortisol in this type of environment may result in biased results due to the increase in emotional distress due to the po ssibility of being diagnosed with a serious breast disorder. Some researchers have found that lower levels of cortisol have been associated with chronic stress, and depression (Burke, Fe rnald, Gertler, and Adler, 2005; Zarkovic et al.,

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96 2003), while others have demonstr ated that stress, anxiety, an d depression are associated with higher levels of salivary cortisol (van Eck et al., 1996). These inconsistencies may be the result of the variety of way and methods used to analyze salivary cortisol. Some researchers use morning cortisol levels or morning area under the cu rve, while other use multi-level analyses to estimate the average cor tisol levels over time (Burke et al., 2005; Kirschbaum and Hellhammer, 1994). In a ddition to differences in statistical methodology, the settings in which salivary cortisol is collected also differ. For example, Burke and colleagues (2005) examined saliva ry cortisol in response to an acute naturalistic stressor (unexpected arrival of a team of researchers at the participants homes) with saliva samples co llected upon arrival, then 25 an d 50 minutes after arrival. In contrast van Eck, Berkhof, Nicolson and Su lon (1996) examined salivary cortisol 10 times a day for five consecutive days in a sample of 87 men during their normal daily activities. In this type of st udy, researchers are able to get a better idea of cortisol levels and diurnal patterns in a natura listic setting. However, given the short length of time for which cortisol was evaluated, little can be said about the impact of chronic stress on alterations in salivary cortisol. More re search that incorporates comprehensive longitudinal designs, preferably over the lif e-course, are essential to understanding how chronic exposure to stressful stimuli affect co rtisol levels, which may in turn perpetuate chronic illnesses such as hypertension, cardi ovascular disease, and type 2 diabetes. This is the first study to document an a ssociation between unfair treatment (a chronic psychosocial stressor) a nd salivary cortisol (Adj. R2 = 0.13, p < 0.001). Higher scores on the interpersonal mistreatment scal e were significantly associated with lower mean salivary cortisol levels throughout the day using both standard multiple regression

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97 and GEE. This finding is surprising in that the direction of the relationship between unfair treatment and SC-AUCg is opposite of the hypothesized relationship. Only one study has examined unfair treatment as a factor that may alter physiological responses to stress. Guyll, Matthew, and Bromberger (2001) examined the cardiov ascular reactivity of 70 African Americans and 158 Caucasians in response to laboratory induced stressors. They found that after adjusting for covariates, attributing mi streatment to discrimination was positively related to baseline heart rate levels among African American participants [t(95) = 2.08, p<.05, (Madj=72.9vs68.7bpm; f2=0.046]. Also between-sub jects analyses of African Americans data s howed that participants w ho experienced discrimination exhibited greater average diasto lic blood pressure reactivity th an those who did not [t(94) = 2.25, p,.03 (Madj = 9.2 versus 5.5 mmHg; f2 = 0.054] (Guyll, Matthews, and Bromberger, 2001). To date no published studies have been found that examined unfair treatment or discrimination in re lation to salivary cortisol. The differences noted in associations be tween perceived stre ss, unfair treatment and salivary cortisol using AUCg versus repeat ed measures (GEE) may be due to the fact that GEE adjusts for correlations between re peated time-specific measures of salivary cortisol, but AUCg does not. The co rrelation adjustment in GEE tends to result in smaller standard errors in the coefficients of sta ndard regression models, leading to smaller pvalues (less statistical signifi cance). Inconsistencies in the literature along with the current debates regarding AUC methodology justify further detailed multi-level analyses of time dependent changes in salivary cortisol in relation to unfair treatment before making any conclusions regardi ng this finding. The time of day in relation to salivary cortisol levels along with AUC ( over the entire day) is an im portant factor in determining

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98 the relationship between salivary cortisol levels and chronic il lnesses. Different portions of the diurnal cortisol pattern may be more relevant to a certain illness than other parts of the cortisol cycle. For example, blunted morning cortisol response and morning AUC have been associated with chronic psychologi cal distress and depres sion (Burke et al., 2005; Zarkovic et al., 2003); wh ere as elevated evening co rtisol levels have been associated with cardiovascular disease (S tewart and Seeman, 2000). More research is needed to resolve thes e methodological issues. Discussion Regarding Neighborhood Effects on Psychological Distress, Health and Salivary Cortisol The final hypothesis regarding specific aim 1 was that neighborhood economic disadvantage, disorder, crime and social support would have an effect on psychological distress (anxiety and depression), salivary cortisol and general h ealth above and beyond individual level factor s. After controlling for individual level factors (perceived stress, chronic stress and individual social suppor t), neighborhood level factors no longer had an effect on depression, anxiety, health or SC-AUCg. Other studies have similarly found that the effects of advers e neighborhood characteristics on health are mediated by psychosocial and physiological processes (C attell, 2001; Hill, Ross, and Angel, 2005; Sampson, Morenoff, and Gannon-Rowley, 2002). Others studies, however, have found strong positive associations between pe rceived neighborhood characteristics and depressive symptoms that are not buffere d by individual social support (Latkin and Curry, 2003). Conclusions This study did not find an associa tion between any of the neighborhood characteristics examined and health, SCAUCg, or repeated, time-specific salivary

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99 cortisol levels. Neighborhood effects on mental and physical health reported elsewhere, however, tend to be small (Boardman, 2004; Feldman and Steptoe, 2004; Schulz et al., 2000). Given the small sample size in this study, it is possible that any significant neighborhood effects on the outcome measures were undetectable due to lack of power. However, the significant associations found in this study between neighborhood disorder, crime and social cohesion, and stress and psychological dist ress indicate that neighborhood characteristics infl uence perceptions of stress. These findings affirm the importance and necessity of including neighborhood level variables in future studies as important sources of individual stress, particularly in rela tion to an ecological model. The association between unfai r treatment and SC-AUCg and repeated time-specific salivary cortisol is unexpect ed and has the potential to add to the literature on psychosocial stressors and health via the HPA axis. More research is needed utilizing a longitudinal design to better understand the relationship between unfair treatment and salivary cortisol. Specific Aims 2: Differences in Neighborhood Characteristics, Housing Satisfaction, by Housing Subsidy Type It was hypothesized that women living in publ ic housing would have higher rates of neighborhood economic disadvantage and higher scores on perceived neighborhood disorder, neighborhood stress, and lower sc ores on perceived neighborhood social cohesion. The hypotheses for specific aim 2 we re partially supported. Though there is a significant difference in ne ighborhood economic disadvantage by housing subsidy type, there were no differences in neighborhood di sorder, exposure to crime, nor neighborhood social cohesion. The lack of significant differences in neighborhood disorder, crime exposure and neighborhood social cohesion by h ousing subsidy type may be explained by

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100 the fact that while located in areas with greater economic advant age, Section 8 housing units may still be located in areas with pockets of high crime rates and disorder. However, it should be noted that this study did not differentiate between the types of Section 8 households that par ticipated. Section 8 recipients in this study included those using project-based Section 8, certificates, and vouchers. In project-based Section 8, families live in specifically designated section 8 housing developments or units. The assistance is tied to the unit, not the family, thus mobility to more advantaged areas is limited (Employment Support Institute, 2006). As noted in Chapter 2, historic and recent trends for location of low-income housing uni ts are that they are more often than not located in more economically disadvantaged areas. Though being phased out, certificate programs remain in effect. The main difference between Section 8 certificate a nd voucher programs is th at the public housing authority or administering agency pays th e landlord the difference between 30% of the households adjusted income and the units re nt and that rent ca nnot exceed the U. S. Department of Housing and Urban Developmen t (HUD) established fair market rent for the area (U. S. Department of Housing and Urban Development, 2004). In the Section 8 voucher program, the family pays the differe nce between the actual rent charged by the landlord and the amount subsidized by the program. In other words, if they can afford to do so, the family may rent a unit that exceed s the HUD fair market rent for the area. Though detailed statistics were not kept on the different types of Sec tion 8 recipients in the present study, many of the participants li ved in project-based Section 8 units which may attenuate the differences between S ection 8 and public housing residents.

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101 There are weaknesses associated with the Section 8 voucher programs that may also impact the ability to differentiate be tween neighborhood characte ristics of public and Section 8 housing. Historically many suburban jurisdictions have used zoning and land use regulations to limit the development of multi-family rental housing in order to maintain their property tax base and ensure social homogeneity. Consequently, the stock of affordable rental housing te nds to be concentrated in ce ntral cities, older suburbs, and less affluent neighborhoods (Turner, 2003). Furthermore, while the housing voucher program has allowed recipients to live in lowerpoverty areas, racial disparities still exist in terms of residential mob ility and choice. Studies have shown that 25.2% of AfricanAmerican recipients and 27.9% of Hispanic s live in high-poverty neighborhoods (poverty rates over 30%), compared with only eight percent of whites (Dev ine, Gray, Rubin, and Taghavi, 2003). However, at least one study has show n a significant difference in voucher recipients and persons residing in public hous ing or receiving proj ect-based assistance. Leventhal and Brooks-Gunn (2003) focused on th e short term effect s of the Moving To Opportunity program (MTO), a randomized housing mobility experiment launched by HUD in 1994. They found that the experime ntal group (families who received Section 8 vouchers and special assistance to move onl y to neighborhoods with less than 10% poverty rates) had higher median incomes and reported significantly less physical and social disorder compared to control groups (families who continued to live in public housing or who receive projectbased Section 8 assistance). The section 8 voucher program is the fe deral governments major program for assisting very low-income households to affo rd housing in the private market. It also

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102 provides the most portability in terms of selecting into more advantaged neighborhoods. However many barriers remain that limit the success of the Secti on 8 voucher program to improve neighborhood quality for its recipien ts. Future research should focus on the differences between the voucher program and ot her types of housing assistance in terms of neighborhood characteristics, residentia l segregation, employment opportunities and the impact on health. Specific Aim 3: Differences in Stress, Ps ychological Distress, Health and SC-AUCg by Housing Type It was hypothesized that women living in public housing units would report significantly higher levels of stress, psychol ogical distress, have higher SC-AUCg levels and report poorer health than their counterparts in Section 8 housi ng. The data did not support the stated hypotheses fo r specific aim 3. There were no significant differences found in stress, psychological distress, healt h, or salivary cortisol by housing type. Given the fact that 50% of the wome n living in Section 8 units al so lived in neighborhoods with high levels of economic disadvantage, disorder and crime, it is possible that the women in this study experienced similar environmental stressors as women living in public housing. Only a few studies have asse ssed the differences in hea lth between public housing and section 8 voucher recipients. The MTO study demonstrated that households who moved to low-poverty neighborhoods (experimental gr oup) reported less me ntal distress than those who remained in high poverty areas (control group) (Leventhal and Brooks-Gunn, 2003). The HOPE VI resident tracking study revealed that persons returning to revitalized public housing units were less likely to report very good or excellent health than those moving to other areas, even after re stricting elderly adults from the analysis (Buron, Popkin, Levy, Harris, and Khadduri, 2002). Though neighborhood and mental

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103 health benefits have been documented regarding recent changes in low-income housing policy, more research is needed to unders tand the social processes and physiological mechanisms that contribute to disparate health outcomes amo ng low-income women. Study Limitations This study has several limitations. Theref ore, the findings should be interpreted with caution. First, non-probability sampling limits the generalizability of this study to other populations. Using a random sample of neighborhoods and a random sample of participants from each neighborhood would im prove the generalizability at the population level and is vital to conducting epidemiological studies. A larger sample of a variety of neighborhood environments is crucial to detecting neighborhood effects on health. Second, the small sample size may account for th e lack of significant findings between neighborhood characteristics, psychological di stress, health and salivary cortisol. Third, the research design could be stre ngthened by utilizing a longitudinal design that collects physiological meas ures over several years as oppo sed to the cross-sectional repeated measures design used in this study. Longitudinal designs, especially in the face of forced relocation due to public housing rev italization efforts, are crucial in determining the effects of these changes on the health and well-being of the mover as well as the recipient communities. Some important rese arch questions might be: what are the recipient community members perceptions of S8 voucher recipients and how do those perceptions change over time? How do those perceptions impact acceptance into the community and treatment of low-income housing residents? Fourth, most of the measures of neig hborhood characteristics were based on the perceptions of the study partic ipants. Using more objective m easures of crime rates and neighborhood disorder would prove useful in future studies. However, perceptions of

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104 ones environment are important factors to c onsider when investig ating behavioral and physiological responses to stressors. The effect of the social environment results from the fact that the brain and bo dy are constantly communicati ng via the autonomic nervous system and the endocrine and immune syst ems (McEwen, 2005). Thus, the regulation of stress-related mediators is de pendent upon how a potential stresso r is perceived as well as the individuals capacity to cope with that stressor. Fifth, given the natural hierar chical ordering of the data (individuals nested housing nested within neighborhoods), multi-level an alysis techniques in future studies are warranted in order to account for the contextual effect of neighborhoods on individual health outcomes. Implications for Public Health Nursing Research and Practice Public health nurses (PHNs) are in an extraordinary position to provide policy makers with accurate accounts of how substandard housing and disadvantaged neighborhoods affect the daily lives of women and their fam ilies. Keeping up to date on current policy trends involving housing, welf are, and neighborhood re vitalization is an important aspect of understand ing the communities served. In addition, PHNs as trusted members of the community are valuable resour ces for grass roots organizations and local community groups, which strive to improve neighborhood and housing conditions. In this venue, PHNs can educate and empower community members to advocate for themselves and their communities on important policy issues. Housing is an important social determin ant of health, and housing policy in the U.S. disproportionately affects women living in poverty. The negativ e effects of poverty or near-poverty on health are often mediated or reinfor ced by substandard housing. An

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105 increased understanding of relationships among neighborhood, housing, and health has the potential to significantly improve individual and population health. Despite the lack of significant findings in the presence of indivi dual level factors in this study, neighborhood economic disadvantage, disorder and exposure to crime remain important factors to consider regarding womens health. For example, this study found that the majority of low-income housi ng participants reside in economically disadvantaged areas characterized by high rate s of perceived disorder and crime, which has implications for future policy decisions regarding location of low-income housing units. In order to reduce pockets of poverty and high crime areas, understanding the current state of low-income housing in an area is crucial. However, further research with larger sample sizes are needed in order to better understa nd the contextual effects of neighborhoods and housing on community health Policies that prevent residential and income segregation and concentration of affo rdable housing units are crucial to reducing social inequalities and their related disparities in health. The women in this study reported high ra tes of unfair treatment, perceived and chronic stress. An examination of local housing and land use policies may identify institutional forms of discrimination leadi ng to important policy changes that could possibly improve womens health. In additi on, intervention studies that educate women who live in subsidized housing, as well as providers of social services, on how to constructively deal with stress and confr ont discriminatory behaviors in a positive manner may prove beneficial. More research in this area could highlight specific mechanisms by which low-income housing pa rticipants experience discriminatory treatment that may in turn result in higher levels of overall chronic stress.

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106 Knowledge gained from further ne ighborhood, housing, and health research focusing on low-income housing policies would provide valuable data from which to evaluate the impact of housing voucher a nd mobility programs on health. Increased awareness of these issues can possibly assist public health nurses, other public health practitioners, urban planners and local governments to secu re financial resources for improving neighborhood and housing conditions. Finally, the inclusion of bio-markers (e.g., cortisol and blood pressure) to te st specific mechanisms of housing or neighborhood effects on health over time ma y provide more in depth knowledge on the pathways by which social processes such as housing policies and neighborhood conditions are embodied into physiological processes and thus produce illness.

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107 APPENDIX CONSTRUCTS, CONCEPTS, AND OPERATIONAL MECHANISMS Major Explanatory Variables Construct Concept & Instruments` Psychometrics Neighborhood Characteristics 1. Neighborhood Economic Disadvantage An index of % family poverty, % male unemployed, % female head of household and % on public assistance at the census tr act level obtained from the 2000 Census Bureau website. 2. Neighborhood Disorder perceived neighborhood disorder scal e consists of 15 items on a four point Likert scal e that ranges from order on the low end (15) to disorder on the high end (60) of the continuum. 3. City Stress Index a self-report measure to assess perceived neighborhood disorder and exposure to violence. The CSI is an 18 item measure with scores ranging from 18 to 72. Low scores indicate lowe r levels of neighborhood stressors. 4. Neighborhood Social Cohesion Measures aggregate level trust with neighborhoods. (Sampson and Raudenbush, 1997) 5 items on a 5point Likert Scal e; range 0-25. 1.Chronbachs alpha = 0.97 (Sampson & Raudenbush, 1997). 2. Chronbachs alpha = 0.915, (Ross and Mirowsky, 1999, 2001). 3. Chronbachs alpha of .88 and .85 respectively (Ewart, 2002). 4. Chronbachs alpha ranges from 0.80 to 0.91 (Sampson, Raudenbush, and Earls, 1997).

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108 Major Explanatory Variables Continued Construct Concept & Instruments Psychometrics Housing Perceived Housing Quality Housing and Urban Development (HUD) Customer Service and Satisfaction Survey 26 item on a 5-point Likert scale that measures the degree to which individuals are satisfied with their current housing situation. Includes areas of overall satisfaction, maintenance and repair, communication with management, safety, services, and housing development appearance (U. S. Department of Housing and Urban Development, 2002). This instrument was developed in focus group settings with public housing residents by HUD. Chronbachs alpha has not been reported for this instrument. Stress 1. Perceived Stress The Perceived Stress Scale (PSS) Measures the degree to wh ich situations in ones life are appraised as stre ssful. A 14 item measure, the PSS scores range from 0 to 56 with lower scores indicating less stress 2. Trier Chronic Stress Inventory a 30-item comprehensive measure of chronic stress that comprises nine dimensions including work overload, social overloa d, overextended at work, lack of social recognition, work discontent, social tension performance pressure at work, performance pressure in social interac tions, social isolation, and worry propensity. 3. Unfair Treatment consists of 10 items. Scores range from 10 to 40 with higher scores corresponding to more fre quent experiences of mistreatment (Guyll, Matthews, and Bromberger, 2001; Williams, Yu, Jackson, and Anderson, 1997). 1. Test-retest: r=0.85 Cronbachs alpha = 0.84-0.86 in women. 2. Cronbachs alpha of .76 to .91 and a split-half reliability of .79 to .89. 3. Cronbachs alpha of .76 to .86.

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109 Major Outcome Variables Construct Concept & Instruments Psychometrics Psychological Distress 1. State/Trait Anxiety The Speilberger StateTrait Anxiety Inventory fo r Adults has been used extensively in research and clinical practice. The state portion of the scale consists of 20 statements that evaluate how respondents fell at the moment they are completing the survey. The trait portion of the scale c onsists of 20 statements that assess how people generally feel (Spielberger, Gorsuch, Lushene, Vagg, and Jacobs, 1983). 2. CES-D a 20-item self-report scale that measures depressive symptoms in the general population (Weissman, Sholomskas, Pottenger, Prussoff, and Locke, 1977). It includes six major symptom areas: (1) depressed mood; (2) guiltworthlessness; (3) helplessness/hopelessness; (4) psychomotor retardation; (5) loss of appetite; (6) sleep disturbance. 1. Cronbachs alpha of .86 to .95. 2. Cronbachs alpha has ranged from 0.85 to 0.91 (McDowell & Newell, 1996). General Health SF-12v2 Health Survey Only one item from this instrument is used to evaluate general health. Responses range from 0 to 5 (Ware, Kosinski, Turner-Bower, & Gandek, 2005). Chronbachs alpha ranges from 0.73 0.77 in women ages 18-44 years old. Physiological Effects Salivary Cortisol (SC) SC is a widely accepted method for measuring physiological responses to stress; highly correlates with serum (blood) and urine cortisol levels a nd offers stress-free, noninvasive sampling, easy collection and storage (Kirschbaum and Hellhammer, 1994). Samples will be analyzed using the Extended Range High Sensitivity Salivary Cortisol Enzyme Immunoassay Kit (Salimetrics, 2005). Requires minimal saliva volume (25 l), has a serumsaliva correlation of r =.94, p < .0001(Salimetrics, 2005; Schwartz, Granger, Susman, Gunnar, and Laird, 1998).

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110 LIST OF REFERENCES Acevedo-Garcia, D., Osypuk, T. L., Werbel, R. E., Meara, E. R., Cutler, D. M., & Berkman, L. F. (2004). Does housing mobility policy improve health? Housing Policy Debate, 15 (1), 49-98. Adam, E. K., & Gunnar, M. R. (2001). Re lationship functioning and home and work demands predict individual differences in diurnal cortisol patterns in women. Psychoneuroendocrinology, 26 189-208. Adler, N., & Ostrove, J. (1999). Socioeconom ic status and health: What we know and what we don't. Annals New York Academy of Sciences, 896 3-15. Alvidrez, J., & Azocar, F. ( 1999). Distressed women's clinic patients: Preferences for mental health treatments and perceived obstacles. General Hospital Psychiatry, 21 340-347. Aneshensel, C. S., & Sucoff, C. A. (1 996). The neighborhood cont ext of adolescent mental health. Journal of Health and Social Behavior, 37 (4), 293-310. Arber, S. (1997). Comparing in equalities in women's and me n's health: Britain in the 1990s. Social Science & Medicine, 44 (6), 773-787. Artazcoz, L. L., Borrell, C., Benach, J., Cortes, I., & Rohlfs, I. (2004). Women, family demands and health: The importance of employment status and socio-economic position. Social Science & Medicine, 59 (2), 263-274. Bahr, N. I., Pryce, C. R., Dobeli, M., & Martin, R. D. (1998). Evidence form urinary cortisol that maternal behavior is related to stress in gorillas. Physiology and Behavior, 64 (4), 429-437. Bashir, S. A. (2002). Home is where the harm is: Inadequate housing as a public health crisis. American Journal of Public Health, 92 (5), 733-738. Beauvais, C., & Jenson, J. (2002). Social cohesion: Updating the state of the research Ottawa: Canadian Policy Research Networks. Beebee-Dimmer, J., Lynch, J. W., Turrell G., Lustgarten, S., Raghunathan, T., & Kaplan, G. A. (2004). Childhood and adult socioeconomic conditions and 31 year mortality risk in women. American Journal of Epidemiology, 159 (5), 481-490.

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111 Behera, S. K., Winkleby, M. A., & Collins, R. (2001). Low awareness of cardiovascular disease risk among low-income African American women. American Journal of Health Promotion, 14 (5), 301-305. Berkman, L. F., & Kawachi, I. (eds.). (2000). Social epidemiology New York: Oxford University Press. Bjorntorp, P., Holm, G., & Rosmond, R. (1999) Hypothalamic arousal, insulin resistance and type 2 diabetes mellitus. Diabetic Medicine, 16 373-383. Boardman, J. D., Finch, B. K., Ellison, C. G ., Williams, D. R., & Jackson, J. S. (2001). Neighborhood disadvantage, stress, and drug use among adults. Journal of Health and Social Behavior, 42 151-165. Boardman, J. D. (2004). Stress and physic al health: The role of neighborhoods as mediating and moderating mechanisms. Social Science and Medicine, 58 24732483 Bosma, J., Dike van de Mheen, H., Bors boom, G. J., & Mackenbach, J. P. (2001). Neighborhood socioeconomic status and all-cause mortality. American Journal of Epidemiology, 153 (4), 363-371. Brunner, E. J. (2000). Toward a new social biology. In L. F. Berkman & I. Kawachi (Eds.), Social epidemiology (pp. 306-331). Oxford: Oxford University Press, Inc. Buka, S. L., Brennan, R. T., Rich-Edwar ds, J. W., & Raudenbush, S. W. (2003). Neighborhood support and the birthweight of urban infants. American Journal of Epidemiology, 157 (1), 1-8. Burke, H. M., Fernald, L. C., Gertler, P. J., & Adler, N. E. (2005). Depressive symptoms are associated with blunted cortisol st ress responses in very-low income women. Psychosomatic Medicine, 67 211-216. Buron, L., Popkin, S., Levy, D., Harris, L., & Kh adduri, J. (2002). The Hope VI resident tracking study: A snapshot of the current living situa tion of original residents from eight sites. Retrieved June 2006 from http://www.urban.org/UploadedPDF/410591_HOPEVI_ResTrack.pdf Campeau, S., Day, H. E., Helmreich, D. L., Kollack-Walker, S., & Watson, S. J. (1998). Principles of psychoneuroendocrinology. The Psychiatric Clinics of North America, 21 (2), 259-276. Cattell, V. (2001). Poor people, poor places, and poor health: Th e mediating role of social networks and social capital. Social Science & Medicine, 52 1501-1516.

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112 Centers for Disease Control. (2000). Socioeconomic status of women with diabetes: United states 2000. Morbidity and Mortality Weekly Report, 51 (107), 147-148. Chatterjee, S., Hadi, A. S., & Price, B. (2000). Regression analysis by example (3rd ed.). New York: John Wiley & Sons, Inc. Chen, X., Ender, P. B., Mitchell, M., & We lls, C. (2005). Regression with stata: UCLA Academic Technology Services Cohen, S., Doyle, W. J., & Baum, A. (2006). Socioeconomic status is associated with stress hormones. Psychosomatic Medicine, 68 414-420. Cohen, S., Kamarck, T., & Mermelstein, R. (198 3). A global measure of perceived stress. journal of Health and Social Behavior, 24 (4), 385-396. Cohen, S., Mermelstein, E., Kamarck, T., & Hoberman, H. M. (1985). Measuring the functional components of social support The Hague, Holland: Martinus Nijhoff. Cooper, H. (2002). Investigating socio-ec onomic explanations for gender and ethnic inequalities in health. Social Science & Medicine, 54 693-706. Dalaker, J. (2001). Poverty in the united states (No. Series P60-214). Washington, D. C.: U. S. Government Printing Office. Devine, D. J., Gray, R. W., Rubin, L., & Ta ghavi, L. B. (2003). Housing choice voucher location patterns: Implications for part icipants and neighbor hood welfare. Retrieved May 2006, from http://www.novoco.com/Researc h_Center/Location_Paper.pdf Diez-Roux, A. V. (2000). Multilevel anal ysis in public health research. Annual Reviews in Public Health, 21 171-192. Diez Roux, A. V. (2003). The examination of neighborhood effects on health: Conceptual and methodological issues related to the presence of multiple levels of organization. In I. Kawachi & L. F. Berkman (Eds.), Neighborhoods and health (pp. 45-64). Oxford: Oxford University Press. Diez Roux, A. V., Merkin, S. S., Arnett, D., Chambless, L., Massing, M., Nieto, J., et al. (2001). Neighborhood of residence and inci dence of coronary heart disease. New England Journal of Medicine, 345 (2), 99-106. Drevdahl, D., Kneipp, S., Canales, M. K., & Dorcy, K. S. (2001). Reinvesting in social justice: A capital idea fo r public health nursing? Advances in Nursing Science, 24 (9), 19-31.

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113 Dunn, J. R. (2000). Housing and health inequa lities: Review and pr ospects for research. Housing Studies, 15 (3), 341-366. Edin, K., & Lein, L. (1997). Making ends meet: How singl e mothers survive welfare and low-wage work New York: Russell Sage Foundation. Ellaway, A., Macintyre, S., & Kearns, A. ( 2001). Perceptions of place and health in socially contrasting neighborhoods. Urban Studies, 38 (12), 2299-2316. Elliot, M. (2000). The stress process in neighborhood context. Health and Place, 6 287299. Employment Support Institute. (2006). Tenant-based and project-based vouchers and certificates overview. Retrieved May 2006, from http://www.workworld.org/wwwebhelp/ten ant_based_project_based_vouchers_ce rtificates.htm Ewart, C. K. (2002). Discovering how ur ban poverty and violence affect health: Development and validation of a neighborhood stress index. Health Psychology, 31 (3), 254-262. Fauth, R. C., Leventhal, T., & Brooks-Gunn, J. (2004). Short-term effects of moving from public housing in poor to middle-class neighborhoods on low-income, minority adults' outcomes. Social Science and Medicine, 59 2271-2284. Feinstein, J. S. (1993). The relationship be tween socioeconomic st atus and health: A review of the literature. The Milbank Quarterly, 71 (2), 279-322. Feldman, P. J., & Steptoe, A. (2004). Ho w neighborhoods and physical functioning are related: The roles of ne ighborhood socioeconomic stat us, perceived neighborhood strain, and individual he alth risk factors. Annals of Behavioral Medicine, 27 (2), 92-99. Fleury, J., Keller, C., & Murdaugh, C. (2000). So cial and contextual etiology of coronary heart disease in women. Journal of Women's Health & Gender-Based Medicine, 9 (9), 967-978. Forrest, R., & Kearns, A. (2001). Social c ohesion, social capita l and the neighborhood. Urban Studies, 38 (12), 2125-2143. Fox-Wasylyshyn, S., & El-Masri, M. M. ( 2005). Handling missing data in self-report measures. Research in Nursing & Health, 28 488-495. Galster, G. (2001). On the nature of neighborhood. Urban Studies, 38 (12), 2111-2124.

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114 Gelsema, A. J., Schoemaker, R. G., Ru zicka, M., & Copeland, N. E. (1994). Cardiovascular effects of social stre ss in borderline hypertensive rates. Journal of Hypertension, 12 (9), 1019-1029. Ghisletta, P., & Spini, D. (2004). An introdu ction to generalized estimating equations and an application to assess selectivity e ffects in a longitudinal study on very old individuals. journal of Educational and Behavioral Studies, 29 (4), 421-437. Green, R. K., & Malpezzi, S. (2003). A primer on u. S. Housing markets and housing policy Washington, DC: The Urban Institute Press. Grossi, G., Perski, A., Ekstedt, M., Johan sson, T., Lindstrom, M., & Holm, K. (2005). The morning salivary cortis ol response in burnout. Journal of Psychosomatic Research, 59 (2), 103-111. Guyll, M., Matthews, A., & Bromberger, J. T. (2001) Discrimination and unfair treatment: Relationship to cardiovascula r reactivity among African American and European American women. Health Psychology, 5 (315-325). Hamilton, L. C. (2006). Statistics with stata Duxbury: Thomson Brooks/Cole. Hays, R. A. (1995). The federal government and urban hous ing: Ideology and change in public policy (2nd ed.). Albany: State Univ ersity of New York Press. Henderson, C., Diez Roux, A. V., Jacobs Jr., D. R., Kieffe, C. I., West, D., & Williams, D. R. (2005). Neighborhood characterist ics, individual level socioeconomic factors, and depressive symptoms in young adults: The CARDIA study. Journal of Epidemiology and Community Health, 59 322-328. Hennig, J., Friebe, J., Ryl, I., Kramer, b., Bo ttcher, J., & Netter, P. (2000). Upright posture influences salivary cortisol. Psychoneuroendocrinology, 25 69-83. Hill, T. D., Ross, C. E., & Angel, R. J. (2005). Neighborhood disorder, psychophysiological distress and health. Journal of Health and Social Behavior, 46 170-186. Immuno-Biological Laboratori es. (2004). Saliva diagnostics Retrieved April 2006, from http://www.biovit.hr/ib l/saliva/intro_e.pdf Institute for Research on Poverty. (2005). Who was poor in 2004? Retrieved April 2006, from http://www.irp.wisc.edu/faqs/faq3.htm Joint Center for Housing Studies of Harvard University. (2004). The state of the nation's housing. Retrieved January 2005, from http://www.jchs.harvard.edu/ publications/markets/son2004.pdf

PAGE 125

115 Julius, S., & Nesbitt, S. (1996). Sympatheti c overactivity in hypertension: A moving target. American Journal of Hypertension, 9 113S-120S. Kacsoh, B. (2000). Endocrine physiology New York: McGraw-Hill. Kalin, N. H., & Carnes, M. (1984). Biological correlates of attachment bond disruption in humans and nonhuman primates. Progressive Neuropsychopharmacology and Biological Psychiatry, 8 (3), 459-469. Kaplan, J. R., Manuck, S. B., Clarkson, T. B., Lusso, F. M., & Taub, D. M. (1982). Social status, environment, and at herosclerosis in cynomolgus monkeys. Arteriosclerosis, 2 (5), 359-368. Kapuku, G. K., Treiber, F. A., & Davis, H. C. (2002). Relationships among socioeconomic status, stress induced cha nges in cortisol, and blood pressure in African American males. Annals of Behavioral Medicine, 24 (4), 320-325. Kawachi, I., & Berkman, L. F. (2000). Social cohesion, social capital and health. In I. Kawachi & L. F. Berkman (Eds.), Social epidemiology (pp. 174-190). Oxford: Oxford University Press. Kawachi, I., Kennedy, B. P., & Glass, R. (1999) Social capital and self-rated health: A contextual analysis. American Journal of Public Health, 89 (8), 1187-1193. Kawachi, I., Kennedy, B. P., Gupta, V., & Prothrow-Stith, D. (1999). Women's status and the health of women and men: A view from the states. Social Science and Medicine, 48 21-32. Kawachi, I., Kennedy, B. P., & Prothrow-S tith, D. (1997). Social capital, income equality, and mortality. American Journal of Public Health, 37 1491-1498. Kearns, A., & Parkinson, M. ( 2001). The significance of neighbourhood. Urban Studies, 38 (12), 2103-2110. Kington, R. S., & Smith, J. P. (1997). Soci oeconomic status and racial and ethnic differences in functional status a ssociated with chronic diseases. American Journal of Public Health, 87 (5), 805-811. Kirschbaum, C., & Hellhammer, D. H. ( 1992). Methodological aspects of salivary cortisol measurement. In C. Kirschbaum G. F. Read & D. Hellhammer (Eds.), Assessment of hormones and drugs in saliva in biobehavioral research (pp. 1932). Seattle: Hogrefe & Huber Publishers. Kirschbaum, C., & Hellhammer, D. H. (1994). Salivary cortisol in psychoneuroendocrine research: Recent developments and applications. Psychoneuroendocrinology, 19 (4), 313-333.

PAGE 126

116 Kirschbaum, C., Read, F. G., & He llhammer, D. H. (Eds.). (1992). Assessment of hormones and drugs in saliva in biobehavioral research Seattle: Hogrefe and Huber Publishers. Kirschenman, J., & Neckerman, K. (1991). We'd love to hire them but...The meaning of race for employers. In C. Jencks & P. Peterson (Eds.), The urban underclass (pp. 203-232). New York: Brookings. Kneipp, S., & Drevdahl, D. (2003). Problem s with parsimony in research on the socioeconomic determinants of health. Advances in Nursing Science, 26 (3), 162172. Kneipp, S. M., & McIntosh, M. (2001). Hand ling missing data in nur sing research with multiple imputation. Nursing Research, 50 (6), 384-389. Krieger, N., & Davey-Smith, G. (2004). "Bodies count," And body counts: Social epidemiology and embodying inequality. Epidemiologic Reviews, 26 92-103. Krieger, N., Zierler, S., Hoga n, J. W., Waterman, P., Chen, J ., Lemieux, K., et al. (2003). Geocoding and measurement of neighbor hood socioeconomic position: A u. S. Perspective. In I. Kawachi & L. F. Berkman (Eds.), Neighborhoods and health (pp. 147-178). Oxford: Oxford University Press. Latkin, C. A., & Curry, A. D. (2003). Stressful neighborhoods and depression: A prospective study of the imp act of neighborhood disorder. Journal of Health and Social Behavior, 44 34-44. Leproult, R., Copinschi, G., Buxton, O., & Van Cauter, E. (1997). Sleep loss results in an elevation of cortisol levels the next evening. Sleep, 20 (10), 865-870. Leventhal, T., & Brooks-Gunn, J. (2003). Moving to opportunity: An experimental study of neighborhood effects on mental health. American Journal of Public Health, 93 (9), 1576-1582. Linden, W., Rutledge, T., & Con, A. (1998). A case for the usefulness of laboratory social stressors. Annals of behavioral medicine. Annals of Behavioral Medicine, 20 (4), 310-316. Lovallo, W. R., & Thomas, T. L. (2000). Stress hormones in psychophysiological research: Emotional, behavioral, and cogni tive implications. In J. T. Cacioppo, L. G. Tassinary & G. G. Berntson (Eds.), Handbook of psychophysiology (2nd ed., pp. 342-350). Cambridge: Cambridge University Press. Lundberg, U. F., M. (1999). Stress and wo rkload of men and women in high-ranking positions. Journal of Occupational Health Psychology, 4 (2), 142-151.

PAGE 127

117 Lundy, K., & Janes, S. (2001). Community health nursing: Caring for the public's health. Boston: James & Bartlett Publishers. Lynch, J. K., G.,. (2000). Socioeconomic positio n. In L. F. K. Berkman, I., (eds.) (Ed.), Social epidemiology (pp. 391). New York: Oxford University Press. Lyon, B. L. (2000). Stress, coping a nd health. In V. H. Rice (Ed.), Handbook of stress, coping, and health: Implications for nursing research, theory, and practice (pp. 3-23). Thousand Oaks: Sage Publications, Inc. Macintyre, S., Ellaway, A., & Cummins, S. (2002). Place effects on health: How can we conceptualise, operationalise and measure them? Social Science & Medicine, 55 125-139. Macran, S., Clarke, L., & Joshi, H. (1996). Women's health: Dimensions and differentials. Social Science & Medicine, 42 (9), 1203-1216. Marco, C. A., Schwartz, J. E., Neale, J. M., Shiffman, S., & Cately, D. A.,. (2000). Impact of gender and having children in the household on ambulatory blood pressure in work and nonwork settings: A partial replication and new findings. Annals of Behavioral Medicine, 22 (2), 110-115. Marmot, M. (2003). Understanding social inequalities in health. Perspectives in Biology and Medicine, 46 S9-S23. Marmot, M. (2004). The stress and health st udy: Also known as the Whitehall II study. Retrieved June 2004, from http://www.ucl.ac.uk/epide miology/white/w2homepage.htm Marmot, M., & McDowall, M. (1986). Mortalit y decline and widening social inequalities. Lancet, 2 (8501), 274-276. Marmot, M., Shipley, M. J., & Rose, G. (1984). Inequalities in death: Specific explanations of a general pattern? Lancet, 1 1003-1006. Marmot, M., Smith, G. D., Stansfeld, S. A., Pa tel, C., North, F., Head, J., et al. (1991). Health inequalities among British ci vil servants: The Whitehall II study. Lancet, 337 1387-1393. Marmot, M., & Wilkinson, R. G. (Eds.). (1999). Social determinants of health Oxford: Oxford University Press. Marmot, M. G., Bosma, J., Hemingway, H., Brunner, E., & Stansfeld, S. (1997). Contributions of job control and other risk factors to social vari ations in coronary heart disease incidence. Lancet, 350 235-239.

PAGE 128

118 Marsh, A., Gordon, D., Heslop, P., & Pantaz is, C. (2000). Housing deprivation and health: A longitudinal analysis. Housing Studies, 15 (4), 411-428. Martikainen, P., Lahelma, E., Marmot, M., Sekine, M., Nishi, N., & Kagamimori, S. (2004). A comparison of socioeconomic di fferences in physical functioning and perceived health among male and female employees in Britain, Finland and Japan. Social Science & Medicine, 59 (6), 1287-1295. McAllister, L. E., & Boyle, J. S. (1998) Without money, means, or men: African American women receiving prenatal care in a housing project. Family and Community Health, 21 (3), 67-74. McCance, L., & Huether, S. (1998). Pathophysiology: The basis for disease in adults and children (3 ed.). St. Louis: Mosby. McDonough, P., Walters, V., & Strohschein, L. (2002). Chronic stress and the social patterning of women's health in Canada. Social Science & Medicine, 54 (5), 767782. McDowell, I., & Newell, C. (1996). Measuring health: A guide to rating scales and questionnaires (2nd ed.). New York: Oxford University Press. McEwen, B. (1998). Protective and dama ging effects of stress mediators. The New England Journal of Medicine, 338 (3), 171-179. McEwen, B. (1999). Stress, adaptation, and disease. Annals New York Academy of Sciences, 893 33-44. McEwen, B. (2000). The neurobiol ogy of stress: From serendip ity to clinical relevance. Brain Research, 886 172-189. McEwen, B. S. (2005). Stressed or st ressed out: What is the difference? Journal of Psychiatry and Neuroscience, 30 (5), 315-318. Merlo, J., Chaix, B., Yang, M., Lynch, J., & Rastam, L. (2005). A brief conceptual tutorial of multilevel analysis in soci al epidemiology: Linking the statistical concept of clustering to the idea of contextual phenomenon. Journal of Epidemiology and Community Health, 59 443-449. Musil, C. M., Warner, C. B., Yobas, P. K., & Jones, S. L. (2002). A comparison of imputation techniques for handling missing data. Western Journal of Nursing Research, 24 (7), 815-829. Newman, S. J., & Schnare, A. B. (1997). ...A nd a suitable living environment: The failure of housing programs to deliver on neighborhood quality. Housing Policy Debate, 8 (4), 703-741.

PAGE 129

119 Nicolas, G., & JeanBaptiste, V. (2001). Experiences of women on public assistance. Journal of Social Issues, 57 (2), 299-309. Northridge, M. E., Sclar, E. D., & Biswas, P. (2003). Sorting out the connections between the built environment and health: A c onceptual framework for navigating pathways and planni ng healthy cities. Journal of Urban Health: Bulletin of the New York Academy of Medicine, 80 (4), 556-568. O'Campo, P. (2003). Invited commentary: A dvancing theory and methods for multilevel models of residential neighborhoods and health. American Journal of Epidemiology, 157 (1), 9-13. Odber, J., Cawood, E. H., & Bancroft, J. ( 1998). Salivary cortisol in women with and without perimenstrual mood changes. Journal of Psychosomatic Research, 45 (6), 557-568. Orlebeke, C. J. (2000). The evolution of low-income housing policy, 1949 to 1999. Housing Policy Debate, 11 (2), 489-520. Patrician, A. (2002). Multiple imputation for missing data. Research in Nursing & Health, 25 (1), 76-84. Pearl, M., Braveman, P., & Abrams, B. (2001). The relationship of neighborhood socioeconomic characteristics to birthw eight among 5 ethnic groups in California. American Journal of Public Health, 91 (11), 1808-1814. Pendall, R. (2000). Why voucher and certificat e users live in di stressed neighborhoods. Housing Policy Debate, 11 (4), 881-910. Plat, L., Leproult, R., L'Hermite-Baleriaux, M ., Fery, F., Mockel, J., Polonsky, K., et al. (1999). Metabolic effects of short-term el evations of plasma cortisol are more pronounced in the evening than in the morning. The Journal of Clinical Endocrinology & Metabolism, 84 3082-3092. Polit, D. F. (1996). Data analysis and statistics for nursing research Stamford: Appleton & Lange. Polk, D. E., Cohen, S., Doyle, W. J., Skoner, D. P., & Kirschbaum, C. (2005). State and trait affect as predictors of salivary cortisol in health adults. Psychoneuroendocrinology, 30 261-272. Popkin, S. J., Levy, D. K., Harris, L. E., Co mey, J., Cunningham, M. K., Buron, L., et al. (2002). Hope VI panel study: Baseline report. Retrieved May 2004, from http://www.urban.org/UploadedPDF/410590_HOPEVI_PanelStudy.pdf

PAGE 130

120 Pressner, J. C., Kirschbaum, C., Meinlsch mid, G., & Hellhammer, D. H. (2003). Two formulas for computation of the area unde r the curve represent measures of total hormone concentration versus time-dependent change. Psychoneuroendocrinology, 28 916-931. The Public Health Disparities Geocoding Pr oject. (2004). Geocoding and monitoring us socioeconomic inequalities in health: An introduction to using area-based socioeconomic measures. The Public Health Disparities Geocoding Project Retrieved July 2004, from http://www.hsph.harvard.edu/thegeocodi ngproject/webpage/monograph/geocodin g.htm Raber, J. (1998). Detrimental effects of chronic hypothalamic-p ituitary-adrenal axis activation. From obesity to memory deficits. Molecular Neurobiology, 18 (1), 122. Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear mode ls: Applications and data analysis methods (2nd ed.). Thousand Oaks: Sage Publications. Ridner, S. H. (2004). Psychologica l distress: Concept analysis. Journal of Advanced Nursing, 45 (5), 536-545. Robert, S. A. (1998). Community-level soci oeconomic status effects on adult health. Journal of Health and Social Behavior, 39 18-37. Rollins, J. J., Saris, R. N., & Johnston-Robledo, I. (2001). Low-income women speak out about housing: A high stakes game of musical chairs. Journal of Social Issues, 57 (2), 277-298. Rosmond, R., & Bjorntorp, P. (2000). The hypothala mic-pituitary-adrena l axis activity as a predictor of cardiovascular diseas e, type 2 diabetes and stroke. Journal of Internal Medicine, 247 188-197. Ross, C. E., & Jang, S. J. (2000). Nei ghborhood disorder, fear, and mistrust: The buffering role of social ties with neighbors. American Journal of Community Psychiatry, 28 (4), 401-420. Ross, C. E., & Mirowsky, J. (1999). Disord er and decay: The concept and measurement of perceived neighborhood disorder. Urban Affairs, 34 (3), 412-432. Ross, C. E., & Mirowsky, J. (2001). Neighbor hood disadvantage, disorder and health. Journal of Health and Social Behavior, 42 258-276. Ross, C. E., Reynolds, J. R., & Geis, K. J. (2000). The contingent meaning of neighborhood stability for reside nt's psychological well-being. American Sociological Review, 65 581-597.

PAGE 131

121 Ross, C. E., & Mirowsky, J. (2001). Neighbor hood disadvantage, disorder and health. Journal of Health and Social Behavior, 42 258-276. Roy, M. P., Kerschbaum, C., & Steptoe, A. (2001). Psychological, cardiovascular, and metabolic correlates of individual differen ces in cortisol stress recovery in young men. Psychoneuroendocrinology, 26 375-391. Salimetrics. (2005, January 03, 2006). Expanded range high sensitivity salivary cortisol enzyme immunoassay kit. Retrieved April 2006, from http://www.salimetrics.com/ercortisolkitinsert.htm Sampson, R. J., Morenoff, J. D., & Gannon-Rowley, T. (2002). Assessing "Neighborhood effects": Social processe s and new directions in research. Annual Reviews of Sociology, 28 443-478. Sampson, R. J., & Raudenbush, S. W. ( 1997). Neighborhoods and violent crime: A multilevel study of collective efficacy. Science, 277 (5328), 918-922. Sapolsky, R. M. (1989). Hypercortisolism am ong socially subordinate wild baboons originates at the CNS level. Archives of General Psychiatry, 46 (11), 1047-1051. Sapolsky, R. M., & Mott, G. E. (1987). Social su bordinance in wild baboons is associated with suppressed high density lipoprotein-ch olesterol concentra tions: The possible role of chronic stress. Endocrinology, 121 1605-1610. The Sarstedt Group. (2003). Salivette A sta ndardized method for the collection of saliva Retrieved June 2006, from http://www.sarstedt.com/php/main.php?newlanguage=en Schlotz, W., & Schulz, P. (2004). The short version of the Trier inventory for the assessment of chronic stre ss (tic-s): Abstract with questionnaire and scale description Johanniterufer, Germany: University of Trier. Schulz, A., Parker, E., Israel, B., & Fisher T. (2001). Social c ontext, stressors and disparities in women's health. Journal of the American Medical Women's Association, 56 143-149. Schulz, A., Williams, D., Israel, B., Becker, A ., Parker, E., Sherman, A. J., et al. (2000). Unfair treatment, neighborhood effects, and mental health in the Detroit metropolitan area. J ournal of Health and Social Behavior, 41 314-332.

PAGE 132

122 Schulz, A. J., Israel, B. A., Zenk, S. N., Park er, E. A., Lichtenstein, R., Shellman-Weir, S., et al. (2006). Psychosocial stress and social support as mediators of relationships between income, length of residence and depressive symptoms among African American wome n on Detroits eastside. Social Science & Medicine, 62 510-522. Schwartz, E. B., Granger, D. A., Susman, E. J., Gunnar, M. R., & Laird, B. (1998). Assessing salivary cortisol in st udies of child development. Child Development, 69 1503-1513. Seeman, T. E., & McEwen, B. S. (1996). Impact of social environment characteristics on neuroendocrine regulation. Psychosomatic Medicine, 58 459-471. Seeman, T. E., Singer, B. H., Rowe, J. W., Horwitz, R. I., & McEwen, B. (1997). Price of adaptation--allostatic load a nd its health consequences. Archives of Internal Medicine, 157 (2259-2267). Singh, G. H., & Siahpush, M. (2002). Increa sing inequalities in all-cause and cardiovascular mortality among U.S. Adu lts aged 25-64 years by socioeconomic status, 1969-1998. International Journal of Epidemiology, 31 600-613. Smith, C. A., Smith, C. J., Kearns, R. A., & Abbot, M. W. (1993). Housing stressors, social support and psychological distress. Social Science & Medicine, 37 (5), 603612. Smith, G. D., Wentworth, D., D., N. J., Stamle r, R., & Stamler, J. (1996). Socioeconomic differentials in mortality risk among men screened for the multiple risk factor intervention trial: Ii: Black men. American Journal of Public Health, 86 (4), 497503. Smyth, J. M., Margit, C., Ockenfels, A. A., Gorin, D. C., Porter, L. C., Kerschbaum, D., et al. (1997). Individual differences in the diurnal cycle of cortisol. Psychoneuroendocrinology, 22 (2), 89-105. Spiegel, K., Leproult, R., & Van Cauter, E. ( 1999). Impact of sleep de pt on metabolic and endocrine function. The Lancet, 354 1435-1439. Spielberger, C. D., Gorsuch, R. L., Lushene, R., Vagg, P. R., & Jacobs, G. A. (1983). State-trait anxiety inventory for adults form y: Manual, test and scoring key review set Redwood: Mind Garden, Inc. Stafford, M., Bartley, M., Mitchell, R., & Marmot, M. (2001). Characteristics of individuals and characteristic s of areas: Investigating th eir influence on health in the Whitehall II study. Health & Place, 7 117-129.

PAGE 133

123 Steptoe, A., & Feldman, P. J. (2001). Ne ighborhood problems as sources of chronic stress: Development of a measure of neighborhood problems and associations with socioeconomic status and health. Annals of Behavioral Medicine, 23 (3), 177185. Steptoe, A., Lundwall, K., & Cropley, M. (2000). Gender, family structure and cardiovascular activity during the working day and evening. Social Science and Medicine, 50 531-539. Steptoe, A., & Marmot, M. (2002). The role of psychobiological pathways in socioeconomic inequalities in car diovascular disease risk. European Heart Journal, 23 13-15. Stewart, J., & Seeman, T. (2000). Salivary cortisol measurement. John D. and Catherine T. MacArthur Research Network on Socioeconomic Status and Health Retrieved October 2004, from http://www.macses.ucsf.edu/Research/Allo static/notebook/salivarycort.html#Sam ples Sundquist, J., Malmstrom, M., & Johansson, S. (1999). Cardiovascular risk factors and the neighbourhood environment: A multilevel analysis. International Journal of Epidemiology, 28 841-845. Takai, N., Yamaguchi, M., Aragaki, T., Eto, K., Uchihashi, K., & Nishikawa, Y. (2004). Effect of psychological stress on the sa livary cortisol and amylase levels in healthy young adults. Archives of Oral Biology, 49 963-968. Taylor, S. E., Repetti, R. L., & Seeman, T. E. (1999). What is an unhealthy environment and how does is get under the skin? In Kawachi I., Kennedy B. P. & W. R. G. (Eds.), The society and population health re ader: Income inequality and health. (pp. 351-378). New York: The New Press. Trekson, M., & Pelletiere, D. (2004). America' s neighbors: The affordable housing crisis and the people it affects. Retrieved January 2004, from http://www.nlihc.org/res earch/lalihd/neighbors.pdf Turner, R. J., & Avison, W. R. (2003). Status variations in stress exposure: Implications for the interpretation of research on r ace, socioeconomic status and gender. journal of Health and Social Behavior, 44 (December), 488-505. Turner, M. A., Popkin, S., & Cunningham, M. (1999). Section 8 mobility and neighborhood health: Emerging issues and policy challenges. Paper presented at the Section 8 Mobility and Ne ighborhood Health, Washington DC.

PAGE 134

124 Turner, M. A. (2003). Strengths and wea knesses of the housing voucher program. Retrieved July 2004, from http://www.urban.org/urlprint.cfm=?ID=8450 Turner, R. J., & Avison, W. R. (2003). Status variations in stress exposure: Implications for the interpretation of research on r ace, socioeconomic status and gender. journal of Health and Social Behavior, 44 (December), 488-505. U. S. Census Bureau. (2005, August 30). In come stable, poverty rate increases, percentage of Americans without health insurance unchanged. Retrieved April 2006, from http://www.census.gov/PressRelease/www/releases/archi ves/income_wealth/005647.html U. S. Department of Health and Huma n Services. (2005). Healthy people 2010. Retrieved April 2006, from http://www.healthypeople.gov/About/ U. S. Department of Health and Hu man Services. (2006). The 2006 HHS poverty guidelines. Retr ieved May 2006, from http://aspe.hhs.gove/poverty/06poverty.shtml U. S. Department of Housing and Urban De velopment. (1998). A picture of subsidized households: U. S. Retrieved May 2006, from http://www.huduser.org/datasets/a ssthsg/statedata98/index.html U. S. Department of Housing and Urban Development. (2002). HUD's public housing program. Retrieved July 2002, from http://www.hud.gov/renting/phprog.cfm U. S. Department of Housing and Urba n Development. (2003a). Housing choice vouchers fact sheet. Retrieved September 2003, from http://www.hud.gov:80/offices/pih/pr ograms/hcv/about/fact_sheet.cfm U. S. Department of Housing and Urban Development. (2003b). HUD's public housing program. Retrieved September 2003, from http://www.hud.gov:80/renting/phproj.cfm U. S. Department of Housing and Urban Deve lopment. (2003c). Public housing customer service and satisfaction survey: Scor ing methodology. Retrieved October 2004, from http://www.hud.gov/offices/reac/ pdf/pih_scoring_process.pdf U. S. Department of Housing and Urban Deve lopment. (2004). Section 8 rental certificate program. Retrieved May 2006, from http://www.hud.gov/progdesc/certifi8.cfm U. S. Department of Housing and Urban Development. (2004). HUD customer service and satisfaction survey. Retrieved October 2004, from http://www.hud.gov/offices/reac/p roducts/rass/rass_mission.cfm

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125 van Eck, M., Berkhof, H., Nicolson, N., & Su lon, J. (1996). The effects of perceived stress, traits, mood states and stressful daily events on salivary cortisol. Psychosomatic Medicine, 58 447-458. Vedhara, K., Miles, J., Bennett, P., Plummer, S., Tallon, D., Brooks, E., et al. (2003). An investigation into the relationship between salivary cortisol stress anxiety and depression. Biological Psychology, 62 89-96. Von Hoffman, A. (1996). High ambitions: The past and future of American low-income housing policy. Housing Policy Debate, 7 (3), 423-446. Wamala, S. P., Lynch, J., & Kaplan, G. A. (2001). Women's exposure to early and later life socioeconomic disadvan tage and coronary heart disease risk: The Stockholm female coronary risk study. International Journal of Epidemiology, 30 275-284. Ware, J. E., Kosinski, M., & Keller, S. D. (1996). A 12-item short form health survey: Construction of scales and prelimin ary tests of reliability and validity. Medical Care, 34 220-233. Ware, J. E., Kosinski, M., Turner-Bowker, D. M., & Gandek, B. (2002). How to score version 2 of the sf-12 health survey (w ith a supplement documenting version 1) Lincoln, RI: Quality Metric Incorporated. Wasylishyn, C., & Johnson, J. L. (1998). Li ving in a housing co-operative for low income-women: Issues of identit y, environment, and control. Social Science and Medicine, 47 (7), 973-981. Wasylyshyn, S. M., & El-Masri, M. M. ( 2005). Handling missing data in self-report measures. Research in Nursing & Health, 28 488-495. Weissman, M. M., Sholomskas, D., Pottenger, M., Prussoff, B. A., & Locke, B. Z. (1977). Assess depressive symptoms in fi ve psychiatric populations: A validation study. American Journal of Epidemiology, 106 (3), 203-214. Welch, K. (1997). Women's health and low-income housing. Journal of Nurse Midwifery, 42 (6), 521-526. Wilkinson, R. G. (1996). Unhealthy societies: The afflictions of inequality London: Routledge. Wilkinson, R. G. (1997). Comment: Income inequality and social cohesion. American Journal of Public Health, 87 (9), 1504-1506. Williams, D. R., & Collins, C. (1995). U.S. Socioeconomic and racial differences in health: Patterns and explanations. Annual Review of Sociology, 21 349-386.

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126 Williams, D. R., Yu, Y., Jackson, J. S., & A nderson, N. B. (1997). Racial differences in physical and mental health: Socio-econo mic status, stress, and discrimination. Journal of Health Psychology, 2 335-351. Yudkin, J. S., Kumari, M., Humphries, S. E., & Mohamed-Ali, V. (2000). Inflammation, obesity, stress and coronary heart di sease: Is interleukin-6 the link? Atherosclerosis, 148 209-214. Zarkovic, M., Stefanova, E., Ciric, J., Penezi c, Z., Kostic, V., Sumarac-Dumanovic, M., et al. (2003). Prolonged ps ychological stress suppresses cortisol secretion. Clinical Endocrinology, 59 811-816.

PAGE 137

127 BIOGRAPHICAL SKETCH Dinah Welch was born in Lumbert on, North Carolina. She received her associates degree in nursing in 1985 fr om Sandhills Community College. Upon completion of her degree, she worked as a re gistered nurse in emergency and intensive care settings focusing on cardiov ascular nursing practice. She received her Bachelor of Science and Master of Science in Nursing degree in 2002. After completing her masters degree in 2002, Dinah went remained in academia as a doctoral student in nursing. She also enrolled in the Masters of Public Health program focusing on epidemiology. During the course of her doctoral studies, Dinah work ed as a research assistant for Dr. Shawn Kneipp, and was awarded a National Institutes of Health, National Institute for Nursing Research Ruth L. Kirschstein Predoctoral Fe llowship. Dinah also worked as an adjunct clinical assistant professor working w ith undergraduate community health nursing students in the clinical setti ng. She graduated with her master s in public health in May 2006. During the four years of her doctoral studies, Dinah was mentored by Dr. Shawn Kneipp. As a predoctoral research fellow, research assistant, and adjunct clinical assistant professor, Dinah has had valuable experi ences in learning about how neighborhoods and housing impact womens health, grant writ ing, proposal development, participant recruitment, data management and analys is, presenting at national meetings, and publishing.

PAGE 138

128 Dinah has presented oral and poster presen tations at the American Public Health Associations annual meetings since 2003. At the 2005 American Public Health Association meeting, Dinahs poster presentation, Neighborhood Effects on Psychosocial Well-being in Women, won th e first place award for doctoral student community research project in the public health nursing section. She has published a manuscript in the journal Policy, Politics and Nursing Practice. Dinah will graduate in August 2006 with her Ph.D. in nursing and mi nor area in public policy. She plans to continue her work in the field of social ep idemiology as a nurse re searcher, educator and public health nurse clinician.


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Title: Neighborhood, Housing, and Women's Health Disparities
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Copyright Date: 2008

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Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
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NEIGHBORHOOD, HOUSING AND WOMEN' S HEALTH DISPARITIES


By

DINAH PHILLIPS WELCH













A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA


2006































Copyright 2006

by

Dinah Phillips Welch
















ACKNOWLEDGMENTS

First and foremost, I want to acknowledge my family, especially my husband,

David, who has been an unwavering source of support throughout my doctoral education.

In addition to providing emotional support, he has served as both a research assistant and

laboratory consultant. His advice during key time points in my research helped me to

produce quality cortisol results. Dave, I am truly fortunate to have such a supportive and

loving husband.

I am grateful to my children who also supported me through this process with

humor and love that I will always cherish. Their patience, understanding and support kept

me going through the tough times.

Next, I want to thank Dr. Shawn Kneipp for her mentorship and guidance over the

last four years. She has been a source of inspiration since our first meeting. Dr. Kneipp's

high standards are admirable and serve her students well in preparing them to be good

nurse scientists. I thank her for taking the time to be a conscientious and caring mentor.

I gratefully acknowledge my dissertation committee Dr. Nabih Asal, Dr. Kristen

Larsen, Dr. Ichan Huang, and Dr. Sandra Seymour for their expertise and advice

throughout this process.

Finally, I want to thank the National Institutes of Health, National Institute of

Nursing Research and the University of Florida, College of Nursing for partial funding of

this proj ect.




















TABLE OF CONTENTS


page

ACKNOWLEDGMENT S ................. ................. iii.._._. ....


LI ST OF T ABLE S ...._.._ ................ ................. vii...


LI ST OF FIGURE S ........._.._.. .......... ............... viii..


AB SRAC T ................. ................. ix.............


1 INTRODUCTION ................. ...............1.......... ......


Background and Problem Statement .............. ...............1.....
Theoretical Framework............... ...............4
Problem Statement ................. ...............5.................

Purposes of the Study .............. ...............5.....
Hypotheses............... ...............
Limitations ................. ...............6.................

Significance .............. ...............7.....

2 LITERATURE REVIEW ................. ...............9................


Socioeconomic Position and Health ................ ............... .... .. .. ....... ........ 9
Socioeconomic Position and Chronic Disease Health Disparities ......................14
SEP and Women' s Health Disparities ................. ...............15...............
Neighborhood SEP and Health ................. ...............17................
Neighborhoods and Health ................ ...............18........... ....
The Concept of Neighborhood ................. ................ .......... ............1
Neighborhood Disadvantage, Disorder and Health ................. ............. .......20
Neighborhood Social Cohesion and Health ............... .. ...... ..... ..........2
Neighborhood Aspects of Subsidized Housing: Implications for Women' s
Health ................. ...............23.................
Housing and Health ....................... ...............25
Housing and Women's Health............... ...............26.
Housing Policy and Health ................... .. ......... .. ...............27....
What We Know and Gaps in Knowledge and Research ................. .................3 1
SE S and C hroni c Stre ss: The Role of the Hyp othal amic-Pituitary -Adrenal (HPA)
Axi s in Chronic Di sease ................. ..... ........ ......... .... .........3
HPA Axis Physiology and its Role in Chronic Disease Development.......................34












Relationships Among Neighborhood Characteristics, Housing, Chronic Stress,
and H health .............. ...............37....
Summary .............._ ....._. ...............3 8...


3 METHODOLOGY .............. ...............40....


Theoretical Framework............... ...............4
Research Design ............... ...............43....
Population and Sample ..........._.._ ....._. ...............43...
Setting ..........._.... ............._ ...............46....
Human Subj ects Protection ............. .....__ ...._ ............4
Inclusion and Exclusion Criteria .............. ...............46....
Research Variables and Instruments................ ..............4

Maj or Study Variables ........._.___..... .___ ...............48....
Neighborhood Characteristics .............. ...............49...
Neighborhood Economic Disadvantage ....._.__._ ..... ... .__. .. ...._._.........49
Neighborhood Disorder ......__................. .........__ .......... 5
Neighborhood Stress: Crime Exposure .............. ...............50....
Neighborhood Social Cohesion............... ...............51
Housing .........._.... ... .. ....... ... ... ._. ........... .......5
Housing Satisfaction (Perceived Housing Quality) ....._.__._ ........___ ...............52
Stress.................. ...............5
P erceived Stre s s............... .. ......_ ...............53...
Unfair Treatment and Discrimination .............. ...............53....
Chroni c Stre s s........._... ...... ._ ._ ...............54..

Psychological Distress ........._.._ ..... .___ ...............55.....
Depression ........._... ......___ ...............55....
State-Trait Anxiety .............. ...............55....
General Health ........._.._ ..... .___ ...............56.....
Salivary Cortisol (SC)............... ...............56..
Individual Social Support ................. ...............61................
Study Protocol .............. ...............61....
Statistical Analyses ................. ........... ...............63.......
Statistical Analysis Approach............... ...............63
Specific Aim 1 .................. ...............64..
Issues of Multicollinearity ................. ......... ...............65......
Seemingly Unrelated Regression .............. ...............66....
M ulti-level Analysis .............. ...............67....
Specific Aim 2............... ...............67...
Specify c Aim 3 .............. ...............68....
M missing Data................ ...... ............6
Handling Missing Cortisol Data ................. ...............69................
Handling Missing Survey Data .............. ...............70....


4 RE SULT S .............. ...............73....


Descriptive Results ................. ...............73.......... .....











Description of the Sample .................. .. ......... ...............73. ....
Neighborhood Characteristics of the Sample.................... .. ......... ................74
Stress, Psychological Distress, Health, and Salivary Cortisol Sample
Characteri sti cs ............_. .... ..._ .... .. ..__ ..... .. ...........7
Specific Aim 1: Associations among Neighborhood Characteristics, Stress,
Psychological Distress, Health and Salivary Cortisol............._._.................. .77
Bivariate Analyses of Neighborhood Characteristics, Housing Satisfaction,
Stress, Depression, State Anxiety, Health and Salivary Cortisol ....................78
General Health, Neighborhood Characteristics, Stress, and Psychological
D i stores s................... ........ ._. .............. ........ ..........7
Neighborhood and Individual Level Effects on State Anxiety ...........................80
Depression, Neighborhood Characteristics and Stress ........._..... ..................81
Seemingly Unrelated Regression Analysis of Anxiety and Depression
Regression Equations ............... .. .... .. ....... .... ...... ..... ... ........8
Specific Aim 2: Differences in Neighborhood Characteristics by Housing
Subsidy Type .............. .. .. .. ... ...........................8
Specific Aim 3: Differences in Stress, Psychological Distress, Health and
Salivary Cortisol by Housing Type............... ...............87..

5 DISCUSSION AND RECOMMENDATIONS .............. ...............90....


M aj or Findings. ........... ......_ _. ...............90...
Sample Characteristics ................... ... .. .... .. .. ........9
Specific Aim 1: Relationships between Neighborhood Characteristics Stress,
Psychological Distress, Health and Salivary Cortisol ................. ................. 92
Neighborhood level hypotheses ................. .... ...............92
Discussion Regarding Individual Level Hypotheses .............. ..................94
Discussion Regarding Neighborhood Effects on Psychological Distress,
Health and Salivary Cortisol............... ...............98
Conclusions .............. ... .. ... .... .. .. .. .......9
Specific Aims 2: Differences in Neighborhood Characteristics, Housing
Satisfaction, by Housing Subsidy Type .................. .... .. .......... ..........._.......99
Specific Aim 3: Differences in Stress, Psychological Distress, Health and SC-
AUCg by Housing Type .............. ...............102....
Study Limitations. ................... ... ......... ... ......... .. .. ..........10
Implications for Public Health Nursing Research and Practice. ............... ... ............104

APPENDIX

CONSTRUCTS, CONCEPTS,AND OPERATIONAL MECHANISMS ................... ....107

LIST OF REFERENCES ................. ...............110................

BIOGRAPHICAL SKETCH ................. ...............127......... ......

















LIST OF TABLES


Table pg

3-1 Skewness and Kurtosis for Study Variables .............. ...............64....

3-2 Collinearity Diagnostics for Explanatory Variables .............. ....................6

3-3 Example of Missing Cortisol Data for One Participant ................. ............... .....70

4-1 Sample Demographic Profile: (n=67) .............. ...............74....

4-2 Sample Description of Neighborhood Characteristics ................. .....................75

4-3 Stress, Psychological Distress, Health and Salivary Cortisol Scores.......................76

4-4 Salivary Cortisol Scores by Day and Time .............. ...............76....

4-5 Mean Psychological Distress and General Health Scores Compared to National
Norms ................ ...............77.................

4-6 Correlations between Neighborhood Characteristics, Housing Satisfaction,
Psychological Distress, General Health, and Salivary Cortisol .............. ................78

4-7 Bivariate Regression Results for General Health ........................... ...............79

4-8 Bivariate Regression Results for State Anxiety .............. ...............80....

4-10 Neighborhood, Psychosocial, and Individual Effects on Depression (CES-D).......81

4-11 Regression Results for Neighborhood and Psychosocial Measures as Predictors
of Depres si on........._._.._...... .___ ...............83....

4-12 Seemingly Unrelated Regression Analysis of Anxiety and Depression Equations .84

4-13 Simple Regression SC-AUCg .............. ...............85....

4-14 Multiple Regression of Individual Level Characteristics on SC-AUCg .................. 85

4-15 GEE Population Averaged Model of Effects of Neighborhood Characteristics,
Stress and Psychological Distress on Salivary Cortisol .............. .....................8

















LIST OF FIGURES


Figure pg

3-1 Socio-biological M odel .............. ...............42....

4-1 Neighborhood Economic Disadvantage (NED) for all Participants ........................75

4-2 Neighborhood Economic Disadvantage (NED) by Housing Subsidy Type ............88
















Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy

NEIGHBORHOOD, HOUSING AND WOMEN' S HEALTH DISPARITIES

BY

Dinah Phillips Welch

August 2006

Chair: Shawn Kneipp
Major Department: Nursing

Humans do not exist in a vacuum; as such, health and illness do not occur entirely

as the result of individual behaviors. People are intrinsically both social and physical

beings and are therefore affected by myriad social factors. Lived experiences vary

tremendously depending on the area one inhabits. The environment constitutes different

contextual aspects that shape one's daily experiences, the social and physical attributes of

neighborhoods and housing are-at the same time-both a product and mediator of larger

social, economic, and political forces. Despite the numerous studies that have established

a clear relationship among neighborhood disadvantage, housing, and health, the

mechanisms by which neighborhoods and housing impact health remain unknown.

Furthermore, a more thorough understanding of how Section 8 and public housing

environments differ is critical, given that the policy intent behind section 8 housing is to

reduce pockets of poverty and its sequelae that have been observed in public housing.










The primary purposes of this study were to examine the relationships among

neighborhood characteristics, perceived stress, psychological distress, and salivary

cortisol secretion among female heads of household with children of low socioeconomic

position (SEP) and to determine the differences in neighborhood characteristics, housing

satisfaction, perceived stress, psychological distress, and salivary cortisol levels in low

SEP female heads of households with children.

Regression analyses indicate that neighborhood characteristics such as disorder,

crime exposure and collective efficacy are associated with increased levels of stress,

psychological distress, and general health. However when individual level factors are

added to models, neighborhood characteristics no longer have an effect on depression,

anxiety, health or salivary cortisol in this group of women. Mann-Whitney U tests

showed a significant difference in neighborhood economic disadvantage by housing type.

Women living in section 8 housing units were located in more economically advantaged

areas (z = -2.552, p<0.05) than women living in public housing. There were no

differences in neighborhood disorder, exposure to crime, nor collective efficacy. Future

studies that replicate this one using a much larger random sample are needed to provide a

better understanding of the impact of neighborhoods and housing on health.















CHAPTER 1
INTTRODUCTION

This chapter introduces the background, theoretical framework, and problem

statement. The study purposes and associated hypotheses are stated. Limitations are

acknowledged and the significance of the study is presented.

Background and Problem Statement

Women and children comprise the greatest proportion of people living in poverty in

the United States (U. S.). As of 2004, the official U. S. poverty rate was 12.7%, which is

up from 12.5% in 2003 (U. S. Census Bureau, 2005). In 2004, the poverty rate for

families was 10.2% comprising almost 7.9 million families. Female-headed families

suffer from poverty disproportionately, with 28.4% (nearly 4 million families) living in

poverty compared to 5.5% of married-couple families (3.2 million families) (Institute for

Research on Poverty, 2005).

Socioeconomic position (SEP) is defined as the social and economic factors that

influence what positions) individuals and groups hold within the structure of society"

(Lynch, 2000), and low SEP has repeatedly been associated with poor health outcomes.

For example, the seminal Whitehall study of British civil servants showed that a gradient

in mortality runs across the social hierarchy from the bottom employment grades to the

top (Marmot, 2003; Marmot et al., 1991). Disparities in health for chronic conditions are

more pronounced among women than men, and a steeper gradient in disparate outcomes

exists at the lower end of the economic strata than at the top (Lynch, 2000; Marmot and

Wilkinson, 1999). Studies show, for example, that women's SEP is strongly and









inversely related to cardiovascular disease (CVD) mortality (Wilkinson, 1996). Poor

women are four to five times as likely to rate their health as fair or poor than women with

higher incomes, and middle-aged women in the highest SEP group can expect to live 2.7

to 3.8 years longer than those in the lowest income group (Robert, 1998). Moreover, there

is evidence that the SEP-related disparities of chronic diseases with some of the highest

prevalence, morbidity, and mortality rates among women have actually widened over the

past several years despite efforts to close the gap (Wilkinson, 1997).

Housing costs account for the largest expenditure for most families and serve as an

indicator of one's social and economic standing within society. Disparities in housing

problems are suffered disproportionately in our society and parallel income-related health

disparities. The broad term housing problems can be applied to a wide range of housing

conditions considered to be sub-standard among developed nations. As such, housing

problems include conditions such as high cost burdens relative to income, overcrowding,

poor conditions, and homelessness, among others.

Currently, the U. S. is in the midst of an affordable-housing crisis. Affordable

housing is defined as spending 30% or less of one's income on housing (Green and

Malpezzi, 2003). However, few U. S. citizens are able to pay such a small amount for

housing and many are financially burdened by its high cost. In 2001, one third of the

nation (95 million people) had housing problems. Two-thirds of the people with housing

problems are low-income as defined by federal policy (household income at or less than

80% of the area median). And poignantly, 32% of the low income people with housing

problems were children (Trekson and Pelletiere, 2004).










To put the scope of housing problems on more familiar terrain, the number of

people that experience housing problems exceeds those who lack health insurance

twofold (Joint Center for Housing Studies of Harvard University, 2004). In addition to

unaffordable housing, crowding is on the rise, and nearly 2 million households live in

over-crowded units (Joint Center for Housing Studies of Harvard University, 2004).

Nationally, 47% of renter households lived in unaffordable housing in 2003, which is a

2% increase from 2002.

Studies are beginning to demonstrate that neighborhood and housing characteristics

are independent determinants of health (Kington and Smith, 1997; Steptoe, Lundwall,

and Cropley, 2000). An estimated 72% of all households receiving rental housing

sub sidies--including Section 8 (S 8) and public housing (PH)-are headed by women,

and many are concentrated in lower socioeconomic areas (Adler and Ostrove, 1999)

which have higher rates of chronic stress, anxiety, depression and CVD (Kington and

Smith, 1997; Steptoe and Marmot, 2002). Increasingly, studies have shown that chronic

stress is associated with the development of chronic illnesses such as insulin resistance,

depression, and CVD (Berkman and Kawachi, 2000; Lundberg, 1999). As a result of

these studies, researchers now hypothesize that arousal of the hypothalamic-pituitary-

adrenal (HPA) axis through chronic exposure to stressors in the social and physical

environment (e.g., neighborhood and housing-related stressors) results in "wear and tear"

on physiological systems, contributing to the development of chronic diseases

(Wilkinson, 1997)

To further study this phenomenon, epidemiologists have begun employing multi-

level analyses that include both aggregate- and individual-level variables to examine









determinants of SEP-related health disparities. An ecological-to-biological conceptual

framework called for within public health and nursing parallels the conceptual and

methodological approaches proposed in this study. Thus, this study examines whether

neighborhood characteristics and health outcomes differ by housing subsidy type (i.e.,

section 8 and public housing) and whether neighborhood characteristics may contribute

to SEP-related health di spariti es among women through chroni c stre ss-phy si logical

mechanisms.

Theoretical Framework

Nancy Krieger's ecosocial theory and Bruce McEwen' s allostatic load model guide

this research. Ecosocial theory seeks to explore the social biological interface through

which environmental factors affect health (Krieger and Davey-Smith, 2004) and calls for

incorporating the use of the concept "embodiment" in order to capture how social

influences (e.g., housing and the built environment) become literally embodied into

physiological characteristics that influence health. Allostatic load is based on the premise

that physical and psychological stressors occur within a social and economic context, and

that there is individual variation in the stress appraisal process as well as behavioral and

emotional coping mechanisms to the perceived stressor (McEwen, 1999).

Combining these two theories into a socio-biological model allows researchers to

simultaneously explore social and biological variables advancing scientific knowledge as

it relates to the understanding of the social-biological interface that may be mediating

relationships among environments (i.e., neighborhoods), chronic stress, and health.

Details on ecosocial theory and allostatic load, and their relevance to this study are

presented in Chapter. 3.









Problem Statement

Despite the numerous studies that have established a clear relationship among

neighborhood disadvantage, housing, and health, the mechanisms by which

neighborhoods impact health remain unknown. Specific to the development of a research

traj ectory in this area, and adding to the body of knowledge regarding neighborhood

effects on health, determining what neighborhood and housing characteristics may most

affect low SEP women's health risks must precede both targeted neighborhood/housing

aggregate-level interventions and individual-level interventions within the highest risk

neighborhoods. More research is needed that incorporates a socio-biological approach in

order to determine the mechanisms by which neighborhoods "get under the skin" and

contribute to the development of chronic disease.

Purposes of the Study

The specific aims of this study are as follows:

1. To determine the relationships among neighborhood characteristics,
perceived stress, unfair treatment psychological distress, and salivary
cortisol secretion among low SEP female heads of household with
children;

2. To determine the differences in neighborhood characteristics of two
subsidy housing types, specifically section 8 and public housing, in which
low SEP female heads of households with children live; and

3. To examine the differences in housing satisfaction, perceived stress, unfair
treatment psychological distress, and neuroendocrine regulation,
specifically cortisol secretion, in low SEP female heads of households
with children by housing subsidy type (i.e., section 8 and public housing).










Hypotheses

The following hypotheses are investigated in this dissertation

1. Significantly higher levels of crime rates, neighborhood disorder,
neighborhood stress, and neighborhood disadvantage will be positively
associated with salivary cortisol.

2. Public housing sites will have significantly more neighborhood disorder,
greater levels of neighborhood disadvantage, higher levels of
neighborhood stress more perceived crime rates, higher obj ective crime
rates, and lower levels of collective efficacy than S8 sites.

3. Women living in PH will experience significantly lower levels of housing
satisfaction, have higher levels of perceived stress, psychological distress,
and greater alterations in salivary cortisol secretion than women living in
S8.
Limitations

This study has several limitations and therefore the Eindings should be interpreted

with caution. First, non-probability sampling limits the generalizability of this study to

other populations. Using a random sample of neighborhoods and a random sample of

participants from each neighborhood would improve the generalizability at the population

level and is vital to conducting epidemiological studies. Second, the small sample size

may account for the lack of significant findings among neighborhood characteristics,

psychological distress, health and salivary cortisol. Third, the research design could be

strengthened by utilizing a longitudinal design that collects physiological measures over

several years as opposed to the cross-sectional repeated measures design used in this

study. Finally, most of the measures of neighborhood characteristics were based on

perceptions of the study participants. Using more obj ective measures of crime rates and

neighborhood disorder would prove useful in future studies. However, perceptions of

one's environment are important factors to consider when investigating behavioral and

physiological responses to stressors. The effect of the social environment results from the









fact that the brain and body are constantly communicating via the autonomic nervous

system and the endocrine and immune systems (McEwen, 2005) Thus, the regulation of

stress-related mediators is dependent upon how a potential stressor is perceived as well as

the individual's capacity to cope with that stressor.

Significance

Housing is an important social determinant of health, and housing policy in the

U.S. disproportionately affects women living in poverty. An increased understanding of

relationships among neighborhood, housing, and health has the potential to significantly

improve individual and population health. The data from this study in accordance with

other epidemiological studies in this area indicate that neighborhood disorder and

exposure to crime are important factors to consider regarding women's health.

In line with both the Healthy People 2010 (U. S. Department of Health and Human

Services, 2005) goals and the National Institutes of Nursing Research priorities, nursing

has a commitment to reducing health disparities among disadvantaged groups through its

scientific investigations. This research is consistent with both of these emphases within

the public health arena and nursing. Moreover, there is an emerging interest in the

relation between the built environment (i.e., neighborhoods and housing) and health in

the field of urban planning, Professionals from this field are partnering with public health

practitioners and others to improve neighborhood conditions through multidisciplinary

investigations that aim to improve the publics' health by establishing healthy cities

through more effective public policy (Northridge, Sclar, and Biswas, 2003).

Future research in women's health disparities must include examination of social

and contextual factors that mediate SEP and health in order to develop population-based

interventions (Fleury, Keller, and Murdaugh 2000). Specific to the development of a









research traj ectory in this area, and adding to the body of knowledge regarding

neighborhood effects on health, determining what neighborhood and housing

characteristics may most affect low SEP women's health risks must precede both targeted

neighborhood/housing aggregate-level interventions and individual-level interventions

within the highest risk neighborhoods.

Furthermore, lacking in the literature is knowledge regarding whether the

experiences of women living in S8 housing differ from those in public housing, and how

neighborhood characteristics associated with each of these programs affect health.

Studies that discern whether home environment or neighborhood characteristics of S8

housing differ from public housing in ways relevant to health are needed. A more

thorough understanding of how S8 and public housing environments differ is critical,

given that the policy intent behind S8 housing is to reduce the concentrated pockets of

poverty and its sequelae that have been observed in public housing

Knowledge gained from neighborhood, housing, and health research focusing on

subsidized housing (i.e., public and section 8 housing) policies would provide valuable

data from which to evaluate the impact of housing voucher and mobility programs on

health. In addition, such knowledge can assist public health practitioners to secure

financial resources for improving neighborhood conditions. The inclusion of bio-markers

(such as cortisol, blood pressure, and others) to test specific physiological mechanisms

may provide more in-depth knowledge about physiological pathways that may be

affected by social processes such as housing policies and neighborhood conditions and

how they are embodied into physiological processes and thus produces illness (Acevedo-

Garcia et al., 2004; Krieger and Davey-Smith, 2004).















CHAPTER 2
LITERATURE REVIEW

This chapter presents a literature review that concentrates on four maj or areas

relevant to the study aims. The discussion begins by presenting relevant studies on the

broad topic of the relationships among SEP and chronic disease health disparities,

particularly as they relate to women. Then the discussion will become focused at the

neighborhood level presenting study findings that indicate how neighborhood

characteristics contribute to chronic stress related health disparities. Nested within

neighborhood are a variety of housing subsidy types that may also impact health

outcomes. This study focuses on federally subsidized Section 8 and public housing,

therefore, a brief overview of subsidized housing policy, neighborhood characteristics

associated with subsidized housing, and associations between housing and health are

presented. Finally this review presents hypothesized physiological mechanisms that may

be affected when neighborhoods and housing serve as sources of chronic stress. This part

of the discussion focuses on chronic stress effects on physiology, specifically the hypo-

thalamic-pituitary-adrenal (HPA) axis and the development of chronic disease. Due to the

extensive nature of the literature in the area of socioeconomic position and health, this

section of the literature review will focus on studies conducted in the United States and in

England.

Socioeconomic Position and Health

In the past 20 years, research that focuses on the relationship between

socioeconomic position and health has grown substantially. Some studies compare









morbidity and mortality of different socioeconomic groups within individual countries,

while others contrast health experiences across countries, document the extent of

inequalities, and explore possible explanations of differential health outcomes (Feinstein,

1993). Most studies of SEP and health have focused on individual-level SEP (i.e.,

individual income, education, occupation), and the effects on broad health outcomes such

as morbidity and mortality (Robert, 1998).

In a review of the literature on SEP and health research published from 1970 to

1990, Feinstein reports findings from early seminal work and critiques the methodology

of several studies conducted in the U. S. and England. For example, one study utilized

two data sets the 1960 Matched Records Study and the Chicago Area Study. The Chicago

Area Study collected information on census tracts and will be discussed in the section on

neighborhood SEP and health. The 1960 Matched Records Study linked death certificates

with census information on the educational attainment and household income for 340,000

individuals who died during May-August 1960 in the U. S. These findings show a strong

inverse relationship among whites and non-whites, females and males aged 25-64,

between years of schooling and mortality in 1960. The difference in standardized

mortality rates between the least and best educated subgroups was at least 65% for each

of the four classes (i.e., white/non-white men and white/non-white females) (Feinstein,

1993). Furthermore, this study elucidates the fact that the effects of education and income

are largely independent of one another.

Another important source of evidence supporting the SEP-health relationship

comes from the Black Report which was published in 1980. In 1977 Sir Douglas Black

and other researchers were appointed by the British Government to assess the evidence









on inequalities in health in the United Kingdom (U. K.). The Black Report assesses

inequalities using a classification system of the British population in which the

population is divided into six social classes including professional, intermediate, skilled

nonmanual, skilled manual, partly skilled, and unskilled. Household status is determined

by the occupation of the head of household (Feinstein, 1993). The findings from this

study showed that in 1971, substantial mortality differentials existed in the U. K. and had

in fact widened since 1930. In 1971, the mortality rate among men in the lowest

occupational class (unskilled) was 9.88 per 1,000 as opposed to men in the highest class

which was significantly lower at 3.98 per 1,000. The same trend was found among

women as well. Women in the highest (i.e., professional) occupational class had a

mortality rate of 2. 15 per 1,000 while those in the lowest occupational class had a

mortality rate of 5.31 per 1,000 (Feinstein, 1993).

There are several problematic methodological issues that have been identified in

this area of research. First, the socioeconomic indicators used in these early studies,

particularly income, do not adequately account for the possibility that poor health causes

reduced income rather than low income resulting in poor health. In addition, many early

studies use household income measures which for married households -are generally

the male's income and therefore do not accurately reflect the woman's income or access

to the household income. Thus, the income and health argument holds more validity

when applied to men than when applied to women (Feinstein, 1993). Furthermore, these

studies do not account for the impact of unpaid labor (i.e., household duties in addition to

work) on women's health. Lastly, many researchers in this area believe wealth as

opposed to income to be the superior indicator because the problem of reverse causality is









less likely to affect household wealth, than household income measures, primarily

because household wealth accumulates over time and consequently is less affected by a

single episode of illness (Berkman and Kawachi, 2000; Feinstein, 1993).

After The Black Report was published an explosion of research in health

inequalities followed. Much of the work expanded upon the approach used in The Black

Report to include alternative datasets for more recent years. For example, Whitehead

reviewed evidence from the 1979-83 decennial supplement that showed inequality in

mortality rates across social classes was the same as, or slightly larger than before thus

supporting evidence from the Black Report even after circumventing some of the

methodological weaknesses in previous studies (Feinstein, 1993). In a similar study,

utilizing the same data, the researchers merged the social classes into two different

groups manual and nonmanual--and found similar results that indicate a wide

inequality in heart disease and lung cancer rates between the two groups (Marmot and

McDowall, 1986).

The more recent Whitehall I and II Studies of British civil servants conducted by

Michael Marmot and colleagues provide further supporting evidence for the social

inequality and health relationship (Williams and Collins, 1995). The Whitehall I Study

examined mortality rates over 10 years among males aged 20-64. An inverse association

between grade (level) of employment and mortality from coronary heart disease (CHD)

and a range of other causes was observed. Men in the lowest grade (i.e., messengers,

doorkeepers, etc.) had three times the mortality rate than men in the highest grade (i.e.,

administrators) (Marmot, Shipley, and Rose, 1984). After controlling for standard risk

factors such as hypertension, smoking, obesity, and physical inactivity, the lowest grade









worker still had a relative risk of 2.1 for CHD mortality compared to the highest grade

worker (Marmot and Wilkinson, 1999).

The Whitehall II study was designed to assess the effects of the social environment

on health and the causes of social inequalities in health. More specifically, it investigates

the role of stress on health and the extent to which stress might be involved in the social

inequalities in health (Marmot, 2004). The study began in 1985 and included 10,308 male

and female civil servants. Findings were consistent with the first Whitehall study. Clear

employment grade differences in health risk behaviors including smoking, diet, and

exercise, economic and social circumstances, and monotonous work characterized by low

control and low satisfaction were present in both men and women (Marmot et al., 1991).

Furthermore employment grade differences were also associated with CHD (Marmot,

Bosma, Hemingway, Brunner, and Stansfeld, 1997), metabolic syndrome and central

obesity (Brunner, 2000).

In addition to the well known Whitehall Studies described above, numerous

studies, such as the Multiple Risk Factor Intervention Trial, (Wilkinson, 1996)

demonstrate that individual-level SEP disparities exist for many chronic diseases (Fleury,

Keller, and Murdaugh, 2000; Kington and Smith, 1997; Marmot and Wilkinson, 1999).

To date, much of the epidemiological research in the area of individual-level SEP

relationships to chronic disease has focused on CHD (Steptoe and Marmot, 2002).

However, a consistent inverse relationship exists between SEP and multiple health

indicators, such as CVD, diabetes, metabolic syndrome, arthritis, tuberculosis, chronic

respiratory illness, malignant melanoma. (Adler and Ostrove, 1999), and lung and

gastrointestinal cancers (Feinstein, 1993).









Socioeconomic Position and Chronic Disease Health Disparities

Socioeconomic position (SEP) has multiple dimensions that are associated with

health. In virtually every dimension of mental and physical health, people in lower-

socioeconomic groups have poorer health than those in the middle- or upper-income

groups (Dalaker, 2001). Regardless of the SEP indicator used, (such as education,

occupation, housing tenure, income), those who are worse off socioeconomically have

worse health (Marmot and Wilkinson, 1999; Smith, Wentworth, Stamler, and Stamler,

1996). The gradient in morbidity and mortality by SEP for several chronic disease states

has been documented for hundreds of years, observed consistently across studies, within

and across countries and cultures, and persists and is actually increasing today (Lynch,

2000; Marmot and Wilkinson, 1999). For example, in a study that examined the extent of

socioeconomic gradients in all-cause and cardiovascular disease (CVD) mortality among

U. S. men and women aged 25-63 years from 1969 to 1998, the researchers found that

area socioeconomic gradients in all cause and CVD mortality increased significantly over

the last three decades (Singh and Siahpush, 2002). The researchers also found that rates

of all-cause and CVD mortality among men in the lowest area socio-economic group

were 42% and 30% greater in 1969-1970 and 73% and 79% greater in 1997-1998

respectively than those in the highest socioeconomic group. Women in the lowest area

socioeconomic group had rates of all-cause and CVD mortality that were 29% and 49%

greater in 1969-1970 and 53% and 94% greater in 1997-1998 respectively than women in

the highest area socioeconomic group. It is important to note, however, that health

disparities are not observed solely at the extreme ends of the socioeconomic spectrum.

Morbidity and mortality risks increase along each incremental decrease in SEP

(Wilkinson, 1996).









The Matched Records Study conducted by Kitagawa & Houser and published in

1975 as previously mentioned shows a persistent inverse relationship between

educational attainment and mortality from heart disease for both men and women and

this relationship is stronger for both sexes aged 25 to 64 (Feinstein, 1993). However, the

relationship between educational attainment and cancers is more complex. Cancers

directly related to smoking such as lung cancer, as well as, stomach, intestinal, and rectal

cancers show a strong inverse relationship to education where other cancers (i.e., prostate

and breast) do not (Feinstein, 1993).

SEP and Women's Health Disparities

Very little research has been conducted that specifically addresses women's SEP

and health. Most research in the area of SEP and health has focused on middle-aged

males or have included both males and females utilizing a cross-sectional descriptive

methodology (Beebee-Dimmer, Lynch, Turrell, Lustgarten, Raghunathan, and Kaplan,

2004). One of the reasons that the relationship between women' s SEP and health has not

received much attention is because of the difficulty in conceptualizing and measuring the

class position of those without direct labor market ties (McDonough, Walters, and

Strohschein, 2002).

Studies that have focused on women's health in relation to SEP have typically been

limited to the quality of social roles, maj or institutionalized roles, and unequal

distribution of resources while the socioeconomic dimensions of women' s lives remain

relatively unexplored (McDonough et al., 2002). Furthermore, a paucity of SEP and

health related research has been conducted among women residing in the United States

(U. S.). Many of the studies reviewed on individual-SEP and women' s health originated

in other industrialized countries such as Canada (McDonough et al., 2002), Britain










(Arber, 1997; Cooper, 2002; Martikainen, Lahelma, Marmot, Sekine, Nishi, and

Kagamimori, 2004; Stafford, Bartley, Mitchell, and Marmot, 2001) Spain (Artazcoz,

Borrell, Benach, Cortes, and Rohlfs, 2004) and Finland and Japan (Martikainen et al.,

2004).

Despite the lack of research that focuses specifically on women' s SEP and health,

studies in the U. S. have consistently shown that women of lower SEP have a higher

prevalence of diabetes (Centers for Disease Control, 2000), report higher levels of social

stress such as recent life events, maj or events, and death events (Turner and Avison,

2003), and have significantly poorer mental health (especially lone mothers with

children) (Macran, Clarke, and Joshi, 1996). In addition, studies that have explored

family demands, employment and health in women have found that among women

workers of low educational level, family demands showed a negative effect on health and

health related behaviors (Artazcoz et al., 2004).

As evidenced by this review, the relationship between SEP and health is well

known. What is missing from the literature is research on the mechanisms by which SEP

affects women's health. While the precise mechanisms that mediate individual-level SEP

and health are unknown, studies indicate it is not only access to material resources that

are important, but that psychosocial factors contribute to health disparities, as well. For

example, there is an interaction among high psychological demand/low control

environments, an increased risk of psychological strain, and physical illness (Berkman

and Kawachi, 2000; Lundberg, 1999; Marco, 2000). Thus, in terms of individual-level

measures of SEP, the pathways through which SEP exerts its influence are not only

through access to material resources (e.g., income or health care services), but may also










operate via psychosocial mechanisms, as more fully described later in the literature

review (see section on Hypothalamic-Pituitary-Adrenal (HPA) axis Physiology and its

Role in Chronic Disease Development). Furthermore, the area in which one lives may

also have a significant impact on health. As will be shown in the following sections, more

research is being conducted that explores the relationship between neighborhoods and

housing and their impact on health, which can account for some of the influence of SEP

on health.

Neighborhood SEP and Health

In addition to research on individual-level SEP and health, epidemiologists are now

exploring the SEP-health relationship from an aggregate level. Several studies have found

residents of disadvantaged neighborhoods have worse self-reported health and more

chronic health problems than persons living in higher SEP neighborhoods (Ross and

Mirowsky, 2001). Studies are finding that neighborhood-level SEP indicators have a

significant effect on health independent of individual-level SEP (Bosma, Dike van de

Mheen, Borsboom, and Mackenbach, 2001; Roy, Kerschbaum, and Steptoe, 2001). For

example, in a study of 23 5 residents of 19 lower SEP neighborhoods, researchers found

that neighborhood problems constitute sources of chronic stress that may increase the risk

of poor health (Steptoe and Feldman, 2001).

One of the problems in this area of research is the diversity of indicators used to

measure neighborhood level SEP. Some researchers have aggregated random samples of

individual SEP indicators (i.e., income, education, and occupation to the neighborhood

level) (Bosma et al., 2001). Others have used indicators such as percent unemployed,

percent on public assistance, poverty rates, and percent households headed by females at

the census tract level to determine the neighborhood SEP level (Boardman, Finch,









Ellison, Williams, and Jackson, 2001; Ross and Mirowsky, 2001). Krieger and colleagues

found that among eight studies, four used differently categorized measures of

neighborhood social class composition, education, poverty level, and unemployment rate,

two used measures of average annual family income and two used data on median family

income and educational level (Krieger et al. 2003). Despite the SEP measure used, the

SEP-health disparities relationship persists above and beyond individual socioeconomic

and behavioral factors and therefore warrant further investigation (Steptoe and Feldman,

2001).

Neighborhoods and Health

The Concept of Neighborhood

Neighborhood is a concept that has myriad definitions depending on the context in

which it is used. A variety of criteria can be used to define neighborhood, including

historical criteria, geographical criteria, resident's perceptions, and administrative

boundaries (Diez Roux, 2003). In addition, the size and definition of the geographic area

may differ based on the outcome being studied.

Neighborhood has been defined as a place where people can easily walk over and

interact with each other and as a social organization of people who reside within a

geographical boundary (Galster, 2001). Kearns and Parkinson (2001) describe

neighborhood as existing at three different levels. These include the home area (a 5-10

minute walk from one's home), locality, and urban district or region. The predominant

function associated with each level of neighborhood is different. For example, the home

area is where the psychosocial purposes of neighborhood is strongest with the main

functions being, relaxation, connecting with others and fostering attachment and

belonging. Localities or sub-districts (e.g., a public or section 8 housing complex)









function as sites for residential activities and positioning oneself within social networks.

Regional aspects or the larger urban districts of neighborhood (e.g., cities or towns)

provide social and economic opportunities. Importantly, Kearns and Parkinson also note

that at the second level of neighborhood (localities), public or low-income housing can be

subject to social exclusion and discrimination imposed upon them by the larger urban

district.

The attributes comprising neighborhood are dynamic and are the result of past and

current flows of households and resources into and out of a defined geographic space

(Kearns and Parkinson, 2001). For the purpose of this study, neighborhood will be

defined according to Galster's (2001) definition that states, "Neighborhood is the bundle

of spatially based attributes associated with clusters of residences, sometimes in

conjunction with other land uses" (p. 2112). This definition accommodates the structural,

class status, environmental, and social inter-active characteristics of a neighborhood.

Structural aspects include the type, state of repair, density, and landscaping of residential

and non-residential buildings and the presence of sidewalks. Class status characteristics

include income, occupation, and educational composition. The degree of noise pollution,

land pollution, and the amount of litter are included in the environmental characteristics

of neighborhood. Finally, social-interactive characteristics include local and family

networks, degree of inter-household familiarity, type and quality of interpersonal

associations, participation in local organizations, and strength of informal social control

(Galster, 2001).

Extant literature in this area of research has generally defined neighborhood using

geographical or administrative boundaries. For example, studies conducted addressing










neighborhood SEP and health outcomes typically identify neighborhood by census tract

area (Boardman et al., 2001; Ross and Mirowsky, 2001) or combine census tracts into

"neighborhood clusters" that are ecologically meaningful and internally homogeneous

(Sampson and Raudenbush, 1997). According to the U. S. Census Bureau, census tracts

are small homogeneous areas in which similar population characteristics, economic status

and living conditions are found (The Public Health Disparities Geocoding Proj ect, 2004).

As evidenced by this review, neighborhood can be defined in a variety of ways.

Therefore, it is important to carefully consider the appropriate spatial scale in regards to

the research questions and variables to be studied (Macintyre, Ellaway, and Cummins,

2002). Neighborhood disadvantage is one example of a variable that is appropriately

measured at the census tract level. On the other hand, social networks may not be

bounded by geographical boundaries and may either be much broader spatially or

narrowly confined.

Neighborhood Disadvantage, Disorder and Health

Neighborhood disadvantage is a term used to describe socioeconomic position of a

locality. Typically measured at the census tract level, neighborhood disadvantage is most

frequently operationalized by developing an index of various indicators such as family

poverty, male unemployed, educational level, public assistance and female-headed

households. Researchers have used percent poverty level, percent female heads of

households, percent male unemployed, percent on public assistance (Boardman et al.,

2001; Sampson and Raudenbush, 1997), or prevalence of poverty and mother-only

households, college educated residents and homeownership (Ross and Mirowsky, 2001).

Economically disadvantaged neighborhoods are characterized by high poverty

rates. Subsidized and other low-income housing units are frequently concentrated in these










high poverty areas. Neighborhood disadvantage has been positively related to higher

levels of stress, lower social resources, and higher levels of anxiety and depression

(Boardman et al., 2001).

Studies show that neighborhood disadvantage in the U. S. is associated with

increased levels of anxiety and depression among adolescents (Aneshensel and Sucoff,

1996), discrimination in the workplace (Kirschenman and Neckerman, 1991), low

birthweight (Buka, Brennan, Rich-Edwards, and Raudenbush, 2003; Pearl, Braveman and

Abrams, 2001) and heart disease (Diez Roux, Merkin, Arnett, Chambless, Massing,

Nieto, Sorlie, Szklo, Tyroler, and Watson, 2001; Sundquist, Malmstrom, and Johansson,

1999). Furthermore, people living in economically disadvantaged neighborhoods have

reported more frequent experiences of unfair treatment (Schulz, Williams, Israel, Becker,

Parker, Sherman, and Jackson, 2000), higher levels of substance abuse (Boardman et al.,

2001), and higher levels of neighborhood disorder (Ross and Mirowsky, 2001).

Neighborhood disorder is a concept that includes both the physical and social

aspects of a neighborhood. Visible signs of physical disorder include high levels of noise,

dirtiness, abandoned and run-down buildings. Vandalism and graffiti are common in

these areas. Social disorder includes higher crime rates and signs such as fights and

trouble among neighbors, the presence of people hanging out on the streets, drinking and

taking drugs (Ross and Mirowsky, 1999).

Neighborhood disorder can be seen as a chronic stressor among urban communities

that can potentially affect health in a variety of ways. For example, perceptions of higher

neighborhood disorder have been linked to greater depressive symptoms after controlling

for baseline depressive symptoms (Latkin and Curry, 2003). Ross and Mirowsky (2001)









found that people living in disadvantaged neighborhoods with high levels of perceived

disorder have higher levels of fear, report more chronic conditions and worse health and

physical functioning.

These studies do not include physiological biomarkers that would illuminate the

mechanisms by which neighborhood stressors impact mental and physical health. Fear

stimulates the release of epinephrine and norepinephrine, followed by the release of

cortisol (Ross and Mirowsky, 2001). Chronic release and exposure to these hormones

have been associated with a variety of illnesses such as hypertension (HTN),

hypercholesterolemia, atherosclerosis, and hyperglycemia (McEwen, 2000). Furthermore,

little is known on how neighborhood social cohesion and social networks may mediate

the impact of neighborhood disadvantage and disorder on health.

Neighborhood Social Cohesion and Health

Social cohesion is a new construct in public health research believed to mediate the

relationship between neighborhood SEP and health. It has been studied predominantly as

an important neighborhood characteristic and has been clearly differentiated from

individual social support in that it represents trust among people with some

geographically defined boundary where one lives. Kawachi and colleagues (1997) found

social cohesion explained 58% of the variance of all-cause age- and SEP-adjusted

mortality, and for 15%-20% of the variance in other CVD mortality. Thus, the role of

neighborhood social cohesion in modulating chronic stress-physiological mechanisms

believed to contribute to health disparities among women deserves further study.

However, the concept of social cohesion is wrought with multiple and confusing

definitions. Authors frequently define social capital and social cohesion in much the same

way (Kawachi, Kennedy, and Prothrow-Stith, 1997). For example, Kawachi has used the









same indicators of social capital to define and measure social cohesion in different

studies (Kawachi, Kennedy, Gupta, and Prothrow-Stith, 1999). Both social cohesion and

social capital have been defined as the level of trust between citizens of a community,

norms of reciprocity and participation in civic organizations that cooperate for mutual

benefit (Kawachi, Kennedy, and Glass, 1999). Forrest and Kelly (2001) describe social

cohesion as being "about getting by and getting on at the more mundane level of

everyday life" (p. 2127).

While social phenomenon within neighborhoods such as those represented by

social cohesion are potentially relevant areas for intervention to improve health, nurse

scholars (Drevdahl, Kneipp, Canales, and Dorcy, 2001) and others (Buka et al., 2003;

O'Campo, 2003) have urged caution in assuming increasing social cohesion is a

simplistic or complete remedy for reducing the health disparities observed to occur

among neighborhoods with 'more' or 'less' cohesion. Nonetheless, when considering one

(of several) contributing factors relevant for examining mechanisms underlying health

disparities, the consistency and magnitude of associations observed to date deem it a

worthwhile concept to investigate. For the purposes of this study a socially cohesive

neighborhood is defined as the extent of trust and social interaction within the

neighborhood (Beauvais and Jenson, 2002; Buka et al., 2003; Sampson and Raudenbush,

1997).

Neighborhood Aspects of Subsidized Housing: Implications for Women's Health

Nested within neighborhoods are a variety of housing types such as single-family

and multi-family units, owned versus rental housing as well as subsidized housing. High

poverty neighborhoods tend to have more low-income subsidized rental housing units

such as public and section 8 housing (Pendall, 2000). Public housing (PH) consists of









housing units owned and operated by the government and typically houses very low-

income families. PH residents pay rent based on income with a minimum of $25.00 to

$50.00 up to 30% of their monthly income (less deductions allowed by regulations) (U.

S. Department of Housing and Urban Development, 2003b). Section 8 housing is a

voucher program in which recipients look for rental housing in the private market.

Recipients of S8 contribute approximately 30% of their monthly income toward housing

costs with S8 programs paying the remainder of a defined payment standard (U. S.

Department of Housing and Urban Development, 2003a). Nationally, only 14.8% of S8

voucher recipients live in high poverty neighborhoods (Turner, Popkin, and Cunningham,

1999), however, while 53.6% of PH residents live in high poverty neighborhoods.

In the United States, more than 5 million families are living in substandard housing

(Bashir, 2002). Despite often-deplorable conditions, housing is often the highest

expenditure for poor families. Increases in fair market rent (gross rent estimates for a

specified area that include shelter cost and utilities except telephones) are far exceeding

increases in income, particularly among low-income families. When families are forced

to spend most of their income on housing, other important needs such as food, clothing,

health care, and emotional stability suffer (Bashir, 2002).

Approximately 4.8 million subsidized housing units are available in the U.S., with

2.4 million households participating in the Section 8 program, 1.3 million households

living in public housing units, and the remaining 1.1 million units comprised of other

types of housing assistance (U. S. Department of Housing and Urban Development,

2002). Of all available subsidized units in the U.S., 96% are occupied. The occupied units

are comprised of 58% minority households and 70% female-headed households such as









single-mother households and elderly women living alone (U. S. Department of Housing

and Urban Development, 1998).

Housing and Health

Decent, affordable housing not only impacts individual and family health; it is also

the building block of healthy neighborhoods, shaping the quality of life in communities.

Improved housing can lead to better outcomes for individuals and society at large. The

relationship between housing and health has been a long-standing issue in the field of

public health. As early as 1872 in a series of essays entitled "The Housing Question",

Freidrich Engels discussed the relationship between housing conditions and poor health.

He argued that the conditions of the poor, working class areas in cities viewed as

breeding grounds for epidemics could not be ignored without impunity. While the

conditions creating the kind of infectious epidemics Engels addressed have been brought

under control in today's industrialized countries and cities, the spatial concentration of

socioeconomic groups is still observable (Dunn, 2000).

Extant research on housing and health has been mainly concentrated in four areas:

1) the disadvantage of individuals who are already in poor health in the housing market

and their self-selection into substandard housing conditions, which may in turn account

for any observed association between poor housing and poor health; 2) health status and

access to health care for homeless persons; 3) pathological aspects of dwellings as the

presumed cause of both physical and mental health outcomes, and 4) studies that

specifically examine the stresses associated with unaffordable and/or inadequate housing

(Dunn, 2000).

Regarding physical health, the literature provides evidence on associations among

overcrowding, dampness and mold, indoor pollutants, infestations, and inadequate









heating and infectious respiratory diseases, asthma, rhinitis, eczema, and heart disease

(Marsh, Gordon, Heslop, and Pantazis, 2000). Other studies have shown relationships

between stress, mental health, and housing. For example, in a study on housing stressors,

social supports and psychological distress, researchers revealed that housing stressors are

significantly associated with psychological distress and that living in substandard housing

is an independent and added source of stress to the lives of people with lower incomes

(Smith, Smith, Kearns, and Abbot, 1993). Missing from the literature is research on the

mechanisms by which housing affects physical and mental health.

Housing and Women's Health

Inequalities in women's health that parallel income inequalities are related to

housing conditions in which women live. The negative effects of poverty or near-poverty

on health are often mediated or reinforced by substandard housing. In one case study, a

single mother living in public housing described the physical manifestations and social

consequences of substandard housing that she believed contributed to poor physical and

mental health in women (Welch, 1997) Although there are inherent limitations to single-

case studies, other studies with samples of over 300 women living in public housing

substantiate this finding (Edin and Lein, 1997; Rollins, Saris, and Johnston-Robledo,

2001; Wasylishyn and Johnson, 1998). Interviews of women living in public housing

conducted by Rollins and colleagues (2001) highlighted problems such as structural

damage and safety issues. Nicolas and JeanBaptiste (2001) used focus group sessions to

learn about the experiences and perceptions of women who receive public assistance

(including public housing subsidies). Some of the maj or themes that emerged included

feelings of shame and disrespect, an insecure future, and a sadness regarding life's

outcomes (Nicolas and JeanBaptiste, 2001). Similar themes were identified through









interviews with 13 pregnant women living in PH by McAllister and Boyle (1998),

including discontent, struggling to make ends meet and loneliness. These three core

themes depict the consequences of poverty and living in low-income housing. The

women in this study also viewed housing assistance as degrading and stigmatizing, and

notably, were much more concerned about the violence in their neighborhood than they

were about their current pregnancy (McAllister and Boyle, 1998).

These four studies provided excellent descriptions of the experiences and

perceptions of living in public housing. However, these studies do not address whether

the experiences of women living in S8 housing might differ from those in PH and how

neighborhood characteristics affect health. Whether home environment or neighborhood

characteristics of S8 housing differ from PH in ways relevant to health remain unknown.

A more thorough understanding of how S8 and PH environments differ is critical, given

that the policy intent behind S8 housing is to reduce the concentrated pockets of poverty

and its consequences that have been observed in PH. In addition, few studies have

incorporated an approach that examines the physiological mechanisms by which

neighborhoods and housing may impact health and either exacerbate or attenuate SEP-

related health disparities among women. Nurse researchers, however, are essentially

silent in this domain, even though public health nurses have an extensive history of

addressing neighborhood-related concerns in relation to health (Lundy and Janes, 2001).

Housing Policy and Health

Home ownership is the American dream. Viewed as part of the transition to

adulthood, owning one's home is a common goal for many young men and women. Thus,

the maj ority of housing assistance policies and programs have focused on

homeownership. Unfortunately, due to a combination of factors such as the lack of









affordable housing and an inadequate living wage, many Americans are unable to

become homeowners. Many low-income workers, particularly single-women with

children, are unable to own their own homes and must not only rent, but also rent

utilizing federal housing subsidies. Moreover, minorities and poor women who must

depend on housing subsidies to maintain shelter are often stereotyped as lazy, ignorant,

unkempt or destructive, and thus marginalized, discriminated against and located apart

from the main stream community and its higher level resources (Hays, 1995).

Since the emergence of federal housing policies in the 1930s and the passage of the

Wagner-Steagall Housing Act in 1937, low-income housing has been characterized by

many factors leading to stigmatization and marginalization. By 1942, the United States

Housing Authority (USHA) had built over 100,000 units in over 140 cities (Von

Hoffman, 1996). The construction of public housing utilizing minimal design elements

reflective of the moderns style contributed to the distinctive yet negative image that came

to be associated with public housing. Functional yet austere looking designs and the

placement of high density multi-family housing complexes in super-blocks also

contributed to the distinctive image of public housing Therefore, a sharp contrast to the

types of residences detached single-family homes that most Americans occupied

emerged that in time would stigmatize public housing (Von Hoffman, 1996).

Further investigations of past housing policies reveal blatant discriminatory

language and practice. The 1934 Housing Act, focused on homeownership, guaranteeing

loans for mortgages through government appropriations. However the funds for these

loans were restricted to the production of new and existing homes for a single owner.










Tragically, during this time period, discrimination was prominent and many lenders

practiced red lining, refusing to loan in certain areas of town based on race and ethnicity.

Redlining was supported by the Federal Housing Administration (FHA). The FHA

manuals used by lenders instructed them to avoid areas where discordant racial groups

resided. In addition, the FHA encouraged developers to establish deed restrictions

prohibiting black owners and residents. Discrimination in the housing market became

prevalent. Consequently, property values of minority neighborhoods plummeted, and

neighborhood segregation by race and income was perpetuated (Orlebeke, 2000).

Further alienation and marginalization of low-income and minority persons was

inadvertently propelled by the design of new public housing units. Unfortunately, high-

rise buildings turned into PH disasters due to lack of funding for building design, basic

amenities and maintenance, isolation and alienation from surrounding neighborhoods and

the lack of public space (e.g., parks) (Orlebeke, 2000). Moreover, during the 1950s and

1960s inner city neighborhoods, now termed ghettos, continued to carry a negative

stigma. Burdened with cycles of poverty, lack of formal education, lack of economic

stability, inadequate housing and a maj or reduction in federal funding, life in these areas

become unsafe and unhealthy (Von Hoffman, 1996).

Current trends in housing policy paint a bleak picture for housing subsidy

programs. In 1971 members of Congress argued that high cost, shoddy construction, poor

administration, failure to help low-income families and lack of planning on a

metropolitan scale were only a few reasons for serious restructuring and reformation of

housing subsidy policies and programs. In 1973, President Nixon called for a moratorium

on subsidized housing production. Since then the development of three different program










types vouchers, block grants and tax credits--have become the primary means of

providing support for rental housing.

In the early seventies, the Nixon administration introduced the Section 8 voucher

program which gave the recipient the option of choosing a unit costing more than the

FMR and paying the difference out of his/her own pocket (Hays, 1995). Voucher

programs result in increased mobility of recipients to better neighborhoods that are less

socially and economically distressed with greater employment opportunities. One study

showed that only 14.8 % of certificate and voucher recipients live in high-poverty

neighborhoods (more than 30% poor), compared with 53.6 % of public housing residents

(Newman and Schnare, 1997). Furthermore, they have lower rent burdens enabling them

to use more of their income on food, clothing and health care needs (Newman and

Schnare, 1997).

Debates regarding the best use of scarce federal housing dollars often focus on

arguments between housing production and rental assistance through voucher type

programs. The original purpose of public housing programs was to provide housing for

poor working families in urban inner city areas as a means of improving slums. However,

several issues associated with public housing (such as, housing design, poor maintenance,

residential segregation, and placement of low-income housing in economically distressed

areas) have contributed to social inequalities. The economic and racial segregation of

poor families to the poorer less desirable areas of cities associated with federal housing

policies and programs beginning in the 1930s unfortunately persist to this day. The social

inequalities associated with housing subsidy have significant implications for the health

of women and the neighborhoods where they live. Marginalization, discrimination,









substandard housing, and housing located in disadvantaged neighborhoods may serve as

chronic stressors that catalyze a cascade of events that in time may lead to poor physical

and mental health.

What We Know and Gaps in Knowledge and Research

While research in this area has found consistent associations between housing,

poverty, and health, the pathways and mechanisms by which the social aspects of these

phenomena produce physiological alterations are not well known (Dunn, 2000). Few

studies have incorporated an approach that examines the physiological mechanisms by

which neighborhoods and housing may impact health and either exacerbate or attenuate

SES-related health disparities among women. Lacking in the literature is knowledge

regarding whether home environment or neighborhood characteristics of various

subsidized housing types differ and whether the experiences of women living in various

subsidized housing types differ in ways relevant to health. A more thorough

understanding of how subsidized housing (S8 and PH) environments differ is critical,

given that the policy intent behind S8 housing is to reduce the concentrated pockets of

poverty and its sequelae that have been observed in PH. Furthermore, very little research

explores housing as a factor in the social production of health inequalities. Population

health studies are needed that explore the relationships among housing, social capital,

social cohesion, income/wealth inequalities and women's health from a life course

perspective (Berkman and Kawachi, 2000; Dunn, 2000). Studies should address the

social-biological interface, thus sorting out the mechanisms by which the social aspects

of housing are embodied into physiological characteristics that impact health (Acevedo-

Garcia et al., 2004).









SES and Chronic Stress: The Role of the Hypothalamic-Pituitary-Adrenal (HPA)
Axis in Chronic Disease

This section of the literature review highlights two areas: the first provides a brief

overvi ew of normal hyp othal ami c-pituitary -adrenal (HPA) axi s functi on and its

hypothesized role in chronic disease development and the second reviews literature

specific to changes in normal HPA axis function by SEP and chronic stress exposure.

Human studies have established relationships between psychosocial stressors and

physiologic stress involving the HPA axis (Linden, Rutledge, and Con, 1998)

Furthermore, there is increasing evidence that characteristics of lower socioeconomic

environments are associated with excessive HPA activation (Seeman and McEwen, 1996)

that may lead to the development of chronic conditions that have high morbidity and

mortality rates (Rosmond and Bj orntorp, 2000). Responses of the HPA to stress allow

organisms to achieve allostasis, the ability to obtain stability through change, which is

required for survival (McEwen, 1998). McEwen and others (Seeman, Singer, Rowe,

Horwitz, and McEwen, 1997) have proposed the cumulative effects of adapting to

stressors (predominantly through pronounced HPA activation) may be quantifiable using

the concept of allostatic load as an index of wear and tear on the body over time.

Accumulation of allostatic load is hypothesized to play a role in the pathogenesis of

chronic diseases and is a useful concept for considering the relationships among

socioeconomic status, the psychosocial stressors of single-mothers, physiologic stress

arousal patterns, and related disparities in health (McEwen, 1998). Animal studies have

been particularly useful in determining neuroendocrine pathways of the chronic stress

and health relationship due to the ability to eliminate selection bias (Kneipp and

Drevdahl, 2003). Nonhuman primate studies indicate that dominant social status in a









stable environment is associated with less HPA activation (Sapolsky and Mott, 1987),

higher HDL levels (Sapolsky, 1989), and less coronary atherosclerosis in both males and

females (Kaplan, Manuck, Clarkson, Lusso, and Taub, 1982). Reciprocally, animals that

are socially subordinate, socially isolated, or in other socially-stressful situations

consistently demonstrate greater HPA activity (Kalin and Cames, 1984). In the

immediate postpartum period, for example, Bahr, and colleagues (Bahr, Pryce, Dobeli,

and Martin, 1998) found female gorillas living under more stressful environments in

captivity (e.g., being harassed by other adult and juvenile gorillas) had higher urine

cortisol levels and less physical contact with their infants, suggesting the social

environment affects parenting behavior and infant bonding via stress-related mechanisms.

Several rat studies (Gelsema, Schoemaker, Ruzicka, and Copeland, 1994; Roy et al.,

2001) support a relationship between chronically stressful environments, psychological

distress, and CVD.

The SEP of women' s lives in relation to chronic stressors and disease outcomes has

received little attention, even though there is increasing evidence from human studies that

chronic stress and HPA axis alteration independent of behavioral or lifestyle factors

exists (Julius and Nesbitt, 1996). Other studies show that characteristics of lower SEP

environments are associated with altered HPA activity believed to be involved in the

development of chronic conditions that have, at the ecological level, been associated with

lower SEP (e.g., CVD, DM, and asthma) (Bjorntorp, Holm, and Rosmond, 1999;

Wamala, Lynch, and Kaplan, 2001). In a study of diumal cortisol patterns in healthy

mothers of toddlers, investigators found that individual differences in cortisol secretion










patterns could be predicted from medical, demographic, contextual (home and work

demands), and psychological variables (Adam and Gunnar, 2001).

While many studies have consistently found chronic stress effects on cortisol

patterns, others have not found a relationship (Smyth, Margit, Ockenfels, Gorin, Porter,

Kerschbaum, Hellhammer, and Stone, 1997). One reason for this may be that research

done in this area has focused on two types of cortisol secretion in response to stressors:

(1) those that are short-lived and occur immediately in response to acute, laboratory

stressors and (2) those that reflect changes in diurnal secretion patterns in response to

chronic, or ongoing, stress exposures. Since the specific aims of this research are to

examine chronic stressors in relation to neighborhood context and health, the focus of this

discussion will be on alterations in the HPA axis from chronic stress.

HPA Axis Physiology and its Role in Chronic Disease Development

A complex system, the HPA axis regulates the release of many different hormones.

These hormones have either a stimulatory or inhibitory effect on many body functions.

The following discussion focuses specifically on the release of the glucocorticoid,

cortisol in response to stimulation of the HPA axis. When stimulated, the parvocellular

neurons within the paraventricular nuclei of the hypothalamus release corticotropin-

releasing hormone (CRH), AVP, and other factors. The portal system transports these

factors to the anterior pituitary, activates corticotrophs and stimulates the secretion of

adrenocorticotropin hormone (ACTH). The systemic blood system transports ACTH to

the adrenal glands. The adrenal cortex then synthesizes and secretes glucocorticoids

(Campeau, Day, Helmreich, Kollack-Walker, and Watson, 1998). Most importantly

researchers hypothesize that exposures to stressors initiate this cascade of events and is

one of the hypothesized mechanisms involved in mediating the SEP-health relationship.









Glucocorticoids are known to have metabolic, immunologic, anti-inflammatory,

and growth inhibitory effects on the body. They also influence levels of awareness and

sleep patterns (McCance and Huether, 1998). However, the main function of

glucocorticoids is to promote conditions that assist the body to adapt to adverse

situations. Therefore, glucocorticoid receptors are widely dispersed. The most potent

glucocorticoid is cortisol. Cortisol supports increased energy requirements during periods

of stress by facilitating the mobilization of free fatty acids (FFA) found in adipose tissue

in the form of triglycerides. The increase in FFA inhibits utilization of glucose in the

peripheral tissues. Cortisol stimulates the release of gluconeogenic enzymes, specifically

phosphoenolpyruvate carboxykinase, which regulates the rate of gluconeogenesis. In

addition, cortisol also functions to mobilize amino acids from proteins in skeletal muscle

(Kacsoh, 2000).

The main function of glucocorticoids is to promote conditions that assist the body

systems to adapt to adverse situations. There is evidence to indicate changes in cortisol

play a pivotal role in the development of diabetes and CVD. One function of cortisol is to

support increased energy requirements during periods of stress by facilitating the

mobilization of FFA found in adipose tissue, which may contribute to the development of

insulin resistance and, ultimately, Type 2 Diabetes Mellitus (Bjorntorp et al., 1999).

Cortisol is perhaps most widely known for its immunosuppressive effects, and evidence

now suggests inflammatory processes modulated by cortisol output may play a role in the

development of atherosclerosis and CVD (Yudkin, Kumari, Humphries, and Mohamed-

Ali, 2000).









Normal cortisol has a diumal rhythm with a peak occurring in the early morning

and a nadir in the early evening. Under periods of stress, cortisol is released acutely to

assist the body to adapt to its external and internal demands. Exposure to chronic

stressors, however, results in alterations in cortisol secretion that persist over time. It is

this change in pattern of cortisol secretion that has been most associated with SEP,

chronic psychosocial distress, and the eventual development of select chronic diseases

(Lovallo and Thomas, 2000; Raber, 1998). Changes in HPA response and, specifically,

the normal diurnal pattern of cortisol secretion to stress, may result in pathological

changes that lead to the development of select chronic diseases (McEwen, 1998; Raber,

1998). For example, Plat and coworkers describe how prolonged hypothalamic

stimulation from a stressor might result in abnormally high levels of cortisol secretion in

the early evening. In addition they found that evening elevations in cortisol were

associated with delayed hyperglycemic effects, stimulation of lipolysis and increased

concentrations of free fatty acids that have been associated with CVD (Plat, Leproult,

L'Hermite-Baleriaux, Fery, Mockel, Polonsky, and Van Cauter, 1999). In another study,

researchers found that a stress-related cortisol secretion pattern with a flattened curve--

depicting a loss of adaptability to stimuli--was strongly correlated with elevated body

mass index, waist-hip ratios, blood pressure, heart rate, triglycerides, total and low-

density lipoproteins, insulin, glucose, and visceral fat mass (Bjorntorp et al., 1999).

Therefore, they postulate that stress-related cortisol secretion along with an impaired

regulation of the HPA axis, are connected to physiologic alterations associated with

chronic disease development.









Relationships Among Neighborhood Characteristics, Housing, Chronic Stress, and
Health

Studies have demonstrated that neighborhood characteristics play a significant role

in determining the type and intensity of daily stress experienced and therefore are

important social determinants of health (Boardman et al., 2001; Wasylishyn and Johnson,

1998). Adjusted for individual-level SEP, living in high poverty neighborhoods has been

associated with increased daily stressors such as increased exposure to drugs (Boardman

et al., 2001) and violent crime (Sampson and Raudenbush, 1997). Studies indicate lower-

income women view the stress in their lives as maj or determinants of not only overall

health status but also of other chronic diseases. For example, focus groups conducted by

researchers with low-income African-American women to examine their awareness of

and concern for CVD found they considered CVD to be associated with stress and low

SEP (Behera, Winkleby, and Collins, 2001). Similarly another study found that low-

income women with mental health problems were most interested in stress management

strategies indicating that they view stress as an important aspect of psychological health

(Alvidrez and Azocar, 1999).

Additional qualitative studies with women living in low SES neighborhoods in

Detroit highlighted that women linked stressors directly related to neighborhood

characteristics (Schulz, Parker, Israel, and Fisher, 2001). Furthermore, the cumulative

effect of chronic stressors such as safety issues and unfair treatment was strongly

associated with symptoms of depression, while financial and family stress showed the

strongest relationships with poorer self-reported health status (Schulz et al., 2001). A

recent study conducted by Buka et. al. (2003) examined neighborhood economic

disadvantage, neighborhood support, and infant birth weight in 343 neighborhoods. They









found neighborhood economic disadvantage alone accounted for 80.8% of the between

neighborhood variance infant birth weight for African-American mothers and 76.3% for

White mothers while controlling for individual risk factors (including maternal age,

education, smoking during pregnancy, and receipt of prenatal care). When neighborhood

social support was added to the model, the addition of this explanatory variable to

economic disadvantage accounted for 90.9% of the between neighborhood variance in

infant birth weight for Whites.

These results indicate that stressors produced as a consequence of living in

economically disadvantaged neighborhoods have significant implications for health,

regardless of individual behavioral factors. What remains, unknown, however, is whether

and how chronically stressful environments of low-income housing have physiological

consequences that contribute to chronic disease development, and whether the

environments of PH and S8 differ in ways that are relevant for health (Buka et al., 2003).

Summary


As described in this literature review, neighborhood-level characteristics have a

significant effect on health above and beyond individual-level factors. Studies have

shown that neighborhood-level factors can produce environments that promote chronic

stress and poor health. However, we do not have a clear understanding of the social-

biological interface that can provide evidence of the physiological mechanisms by which

environments (i. e., neighborhoods) contribute to poor health and chronic illness. The

study of social and biological variables at the same time is intrinsically valuable because

we are as humans, both social and biological (Brunner, 2000). More research is needed in

order to understand what constitutes an unhealthy environment and how it "gets under the









skin" to produce illness (Taylor, Repetti, and Seeman, 1999). This study aims to

contribute to this body of research by investigating social and biological variables

simultaneously, by beginning to explain the social-biological processes by which

neighborhoods and housing impact women's health disparities.















CHAPTER 3
METHODOLOGY

Theoretical Framework

As stated in Chapter 1, this study is guided by a combination of an ecosocial

paradigm and the allostatic load model. Together, they allow for exploration of the social

- biological interface through which environmental factors affect health. Krieger's

ecosocial theory and McEwen' s allostatic load model guide the development of the

conceptual framework used in this study (Krieger and Davey-Smith, 2004). Krieger and

Davey-Smith (2004) call for incorporating the concept "embodiment" in order to capture

how social influences (i.e., housing and the built environment) become literally embodied

into physiological characteristics that influence health. The concept of "embodiment"

simultaneously embraces biologic and social processes while avoiding the trap of

equating "biologic' with "innate" and without assuming the soma is governed exclusively

by the psyche. In addition, as Krieger and Davey-Smith state, "this new scholarship

emphasizes how actualization and suppression of people' s agency, that is, their ability to

act within their bodies, intimately depends on socially structured opportunities for, and

threats to, their well-being" (pg. 95). Thus keeping the concept of embodiment in mind,

the conceptual framework developed for this study draws from multiple disciplines such

as public health, sociology, and medicine.

The second theoretical model used to derive the socio-biological conceptual

framework is McEwen's Allostatic Load model (McEwen, 1998). This model is based on

the premise that physical and psychological stressors occur within a social and economic









context and that there is individual variation in the stress appraisal process as well as

behavioral and emotional coping mechanisms to the perceived stressor (McEwen, 1999).

McEwen describes four key propositions of his allostatic load model. First, the brain is

the integrative center for coordinating the behavioral and neuroendocrine responses

(hormonal, autonomic) to challenges. Second, there are considerable differences in

coping with challenges based on interacting genetic, developmental, and experiential

factors that predisposes persons to react differently physiologically and behaviorally to

events throughout life. Third, inherent within the neuroendocrine and behavioral

responses to challenge is the capacity to adapt (allostasis). However, while these

physiological processes are protective in the short term, inefficiency or alterations in the

ability of the neuroendocrine system to turn on and off responses leads to cumulative

negative effects over time. Fourth, allostasis has a price defined as allostatic load -that

reflects the cumulative negative effects or the wear and tear on bodily systems from being

forced to constantly adapt to various psychosocial challenges and adverse environments

(i.e., disadvantaged neighborhoods).

Accumulation of allostatic load is hypothesized to play a role in the pathogenesis of

select chronic diseases, such as insulin resistance, atherosclerosis, increased susceptibility

to infections and memory loss (Bjorntorp, Holm, and Rosmond, 1999; McEwen, 1998;

McEwen, 2000). Since this model addresses the fact that daily stressors occur within a

social and economic context, it is a useful framework for considering the relationships

among SEP, the psychosocial stressors of single mothers, physiologic stress arousal

patterns, and their noted disparities in health (McEwen, 1999). As such, the impetus in

this model is to move from the individual back to populations and consider the average










properties of groups of individuals classified according to measures of SEP attending to

not only the social and cultural factors that influence health, but the potential

physiological mediators found in these relationships. However, McEwen's model lacks

detail regarding the socio-economic aspects of neighborhood and health.

Combining Krieger' s ecosocial theory and McEwen' s allostatic load model enables

the researcher to simultaneously explore social and biological variables. This allows for

advancing scientific knowledge as it relates to the understanding of the social-biological

interface that may be mediating relationships among environments (i.e., neighborhoods),

chronic stress, and health. Relationships among environment, social, psychological, and

physiologic factors relevant to this study in relation to the Allostatic Load Model are

illustrated in Figure 3-1. Key constructs and concepts and methods of operationalization

are explained in the section on maj or study variables below. The final outcome (CVD) is

in grey because it was not explored in the present study. It is only an example of one

possible outcome that could be explored using this framework.

Figure 3-1: Socio-biological Model


Hypothesized Mechanisms Contributing to Disease Development









Research Design

This study utilized a cross-sectional design in which physiological measures were

obtained six times a day for 2 days in a sample of 84 women. Of the 84 who participated,

complete data were available for only 67 participants 23 from PH and 43 from S8

housing. The relationships among housing type, neighborhood characteristics, stress,

psychological distress and salivary cortisol are examined by specific aim 1. To meet

specific aims 2 and 3, differences in neighborhood characteristics, stress, psychological

distress and salivary cortisol between women living in S8 and PH are explored.

Population and Sample

The population investigated in this study includes 18 to 45 year old women who are

heads of households and have at least one child 18 years-old or less living with them.

This age group was selected because it is representative of the target population to be

studied. Based on data from the department of Housing and Urban Development, almost

two-thirds of those living in subsidized housing are between the ages of 18 and 62 (U. S.

Department of Housing and Urban Development, 1998). A subcategory of female

children (as defined by NIH) those who arel8 to 21 years of age and are mothers --, are

included in this study. While considered by many as children, young (18- to 21- years-

old) mothers often live in disadvantaged neighborhoods and poor housing environments.

Having the same adult responsibilities as any parent, they experience many daily

stressors, associated with adult responsibilities in maintaining family safety and stability.

The specific aims of this study are to examine the potential of chronic disease

development as a result of cumulative stress associated with adult family responsibilities

and being female heads of households within a neighborhood context.









The sample was selected based on their exposure to either S8 or PH environments.

Research participants were recruited from the area in cooperation with the Gainesville

Housing Authority and S8 housing managers. In Gainesville, Florida and within a 10

mile perimeter of the city limits, there are 1,062 S8 housing "slots". Approximately 400

people per year attend S8 housing orientation provided by the Gainesville Housing

Authority. Ten to fifteen percent of people who move into S8 housing move from PH

units (Dolder, C. personal communication, June 26, 2002). During a typical application

process, of the 400 interested people, 150 applications are processed and reviewed;

approximately 5% to 10% are able to move into S8 housing.

The sample was recruited by posting flyers at the local housing agencies, rental

units participating in housing subsidy programs, the university, health science center,

local hospitals and primary care offices, social service agencies, and churches. In

addition, the principal investigator (PI) attended community meetings such as the Black

on Black Crime Task Force, and tenant/neighborhood associations in neighborhoods

where the sample was located and informed them of the research and recruited interested

persons. Addresses were obtained from the Gainesville and Alachua County Housing

Authority and letters were disseminated tol500 section 8 and public housing addresses.

Most of the public housing participants were recruited by going door to door.

Sample size determination was based on a power analysis to ensure a power of 0.80

is achieved. A sample size of 49 subj ects per housing type was needed to detect a

difference of .40 in the outcome measures (i.e., salivary cortisol, chronic stress, and

psychological distress). For multiple regression analyses a total of 107 women were

needed. Power for this study was not achieved due to an inadequate sample size.









A total of 84 women participated in this study. The original sample size of 107

women was not attained due to several issues. Despite compensation with a $30.00 gift

certificate to Wal-mart, recruitment of women living in public housing was difficult.

Though data was not collected as to why women chose not to participate, based on their

comments, fear of getting in trouble with the local housing authority is one possible

reason many women did not participate in the study. Also, many of the women refused to

collect saliva. Some were repulsed by the idea of collecting saliva, while others voiced

concern about what would happen to it after the study was over. Fear and mistrust despite

efforts to assure women that their privacy and confidentiality would be maintained was

believed to be a maj or factor in not achieving the desired sample size. Also the study was

limited to participants who lived within a 10-mile radius of Gainesville, thus limiting

participants geographically.

Of the 84 women who participated, 14 did not have usable cortisol data (defined as

missing more that 2 time points in one day). These cases were deleted. Survey and

cortisol data were imputed for the 70 participants remaining. Three participants failed to

answer over 50% of the questions from one measure leaving a Einal sample size of 67

women. It was decided a priori that if a participant failed to answer more than 30% of the

items in a measure, she would be excluded from data analysis. Up to 10% missing data

on a measure may be considered small, while 40% missing data is considered to be high

(Musil, Warner, Yobas, and Jones, 2002). Recommendations for handling missing data in

nursing research are limited. Decisions regarding the appropriate methods to deal with

missing data are based on the pattern, level (subject or item) and amount of data that are

missing (Kneipp and McIntosh, 2001; Patrician, 2002). The robustness of certain










imputation techniques is often dependent on extent and amount of missing data.

Therefore, these factors should be considered in order to minimize estimation error and

response bias (Fox-Wasylyshyn and El-Masri, 2005). Imputation methods used in this

study are described in detail later in this chapter.

Setting

The study was conducted in a naturalistic setting (i.e., community of residence).

The PI or her research assistant met with participants in their homes or other settings as

preferred by the participants.

Human Subjects Protection

Approval for this study was obtained from the University of Florida Health Science

Center Institutional Review Board prior to any subj ect recruitment or data collection. All

subj ects signed an informed consent form and were given a copy prior to enrollment in

the study. Data collection took place in the participant's residential neighborhood.

Confidentiality was maintained by use of a code for each subject. All files were kept in a

locked file cabinet in the researcher' s office. Saliva samples were also coded and stored

in a freezer in the college of nursing wet lab, which is locked at all times and has limited

access by select faculty, staff, and research assistants.

Inclusion and Exclusion Criteria

Inclusion criteria include:

a) Living in public or section 8 housing for at least 1 month,
b) Able to speak and read English,
c) Between the ages of 18 and 45 years old,
d) A mother who is head of the household with a child living in the same
household who is 18 years old or less.









Exclusion criteria include:

a) Age greater than 45 years old,
b) Diagnosis of an autoimmune disorder,
c) Pregnant or breastfeeding,
d) Taking antidepressant, anxiolytic, or steroid-based medications.
e) Working the night shift (from the hours of 11:00 pm to 7:00 am).

The inclusion criteria were selected because this study focuses on women living in

section 8 and public housing units and how these areas may serve as stressor for women

responsible for maintaining family safety and stability. Women living in an area for at

least one month have had time to assess their neighborhood regarding crime, disorder and

other characteristics. Women 18 years-old up to 45 years-old are representative of most

of those who live in subsidized housing as previously described. The study was limited to

participants who could read and speak English due to financial constraints related to

hiring a translator.

These exclusion criteria were selected because they are known to alter cortisol

levels and may alter responses to stress, depression and anxiety measures. Studies have

produced controversial results regarding differences in salivary cortisol based on age

group. Studies have demonstrated systematic differences are present in early morning

salivary cortisol in which decreasing cortisol concentrations are positively correlated with

age (Kirschbaum and Hellhammer, 1992). The lowest mean value of 11.6 nmol/1 was

found in the age group between 59 and 64 years. The effect of pregnancy on salivary

cortisol is controversial. Some studies have shown increases in salivary cortisol secretion

while others have not (Kirschbaum and Hellhammer, 1992). In addition, the sample

upper age limit of 45 years old will reduce confounding effects of menopause and chronic

disease development on physiological measures.










As previously described in the literature review, cortisol has a diurnal pattern with

a peak 45 minutes to one hour after awakening and a nadir just before bedtime.

Alterations in sleep quality and quanity and working the night shift have been shown to

affect the HPA axis and therefore alter cortisol secretion patterns (Leproult, Copinschi,

Burton, and Van Cauter, 1997; Spiegel, Leproult, and Van Cauter, 1999).

In addition to altering salivary cortisol levels, antidepressants and anti-anxiety

agents may influence how a participant responds to questions regarding stress, depression

and anxiety leading to underestimation and response bias. Therefore persons taking anti-

depressant or anti-anxiety agents were excluded from the study.

Research Variables and Instruments

A demographic data sheet was used to collect information such as age, marital

status, race, household type, number and ages of children, individual income, education,

and occupation, chronic diseases diagnoses, medication use, height, and weight. In

addition information was obtained on current address, living situation (i.e., living with

others or others living with them), housing type, length of time in current dwelling, rent

assistance per month, public assistance, receipt of food stamps and other sources of

income via public assistance resources, such as child care and transportation. Additional

data regarding smoking history, alcohol intake, and menstrual cycle phase and regularity

were obtained, as well.

Major Study Variables

This section provides detailed information on the measures used in this study. A

quick overview of each of the dependent and explanatory variables is provided in the

table in the Appendix.










Neighborhood Characteristics

Neighborhood is defined according to Galster' s (2001) definition that states,

"Neighborhood is the bundle of spatially based attributes associated with clusters of

residences, sometimes in conjunction with other land uses" (p. 2112). This definition is

broad and quite abstract. It includes several aspects of neighborhood such as the

structural, class status, environmental, and social inter-active characteristics of

neighborhood.

For the purposes of this study, the term neighborhood characteristics include

information on neighborhood economic disadvantage (measured at the census tract level),

perceived neighborhood disorder, exposure to crime, and neighborhood cohesion. Each

of these measures is described more fully below.

Neighborhood Economic Disadvantage

Neighborhood economic disadvantage was obtained using census tract level data

from the 2000 census. Census tracts are designed to be demographically homogenous

with stable boundaries over time and generally contain between 3000 and 8000 resident

(Boardman, et. al., 2001). Extensive research by Krieger and colleagues has shown that

socioeconomic data obtained at the census tract level performs better at detecting

economic gradients expected than measures at the county or state level (Krieger et al.,

2003).

For the purposes of this study, neighborhood economic disadvantage is an index

measure of percent family poverty, percent of female headed households, male

unemployment rate, and percent of families receiving public assistance. The four values

were summed to create the neighborhood disadvantage measure in which higher numbers

indicate greater disadvantage, with scores ranging from 0 to 12. This measure has been









used in studies that investigated the relationship between neighborhood disadvantage and

health in adult samples much like the sample in this study (Boardman et al., 2001;

Sampson and Raudenbush, 1997). Prior research by Sampson & Raudenbush (1997)

demonstrated that these characteristics are highly interrelated and load on one single

factor that can be described as neighborhood disadvantage (a= 0.97).

Neighborhood Disorder

The concept of perceived neighborhood disorder includes both social and physical

signs indicating a lack of order in the neighborhood. Areas with high levels of disorder

are characterized by deviance, noise, vandalism, drug use, crime, trouble with neighbors

and other incivilities (Ross and Mirowsky, 1999). This study measured perceived

neighborhood disorder using an index that measures physical signs of disorder such as

graffiti, vandalism, noise, and abandoned buildings, and social signs such as crime,

people hanging out on the street, and people drinking or using drugs. It also includes

reverse-coded signs of neighborhood order such as safety, people taking care of their

houses and apartments or watching out for each other. The perceived neighborhood

disorder scale consists of 15 items on a four point Likert scale that ranges from order on

the low end (15) to disorder on the high end (60) of the continuum. This scale has an

alpha reliability of .915 (Ross and Mirowsky, 2001).

Neighborhood Stress: Crime Exposure

Neighborhood Stress is defined as exposure to a range of events and conditions in

one's proximal environment that are capable of eliciting stressful emotions (e.g., fear,

anger, depression) and that may exacerbate disease processes or undermine health

(Ewart, 2002). The City Stress Index (CSI) was developed by Ewart (2002) and is used as

a self-report measure to assess perceived neighborhood disorder and exposure to crime.









The CSI is an 18-item measure with scores ranging from 18 to 72. Low scores indicate

lower levels of neighborhood stressors. This measure can be completed by persons with

an eighth grade reading-level. It has good validity and reliability with the neighborhood

disorder and exposure to violence portions of the scale having a Chronbach' s alpha of .88

and .85 respectively (Ewart, 2002). The recent development of the tool limits the data on

use in other populations such as adults, but the reading level and use in urban dwelling

adolescents make it a useful measure for this study. Permission to use this measure was

obtained from Craig Ewart, a professor in the Center for Health and Behavior at Syracuse

University (C. Ewart, personal communication, December 7, 2004).

Neighborhood Social Cohesion

Social cohesion refers to the level of trust, extent of connectedness and solidarity

among groups in society (Kawachi and Berkman, 2000; Sampson and Raudenbush,

1997). For some, the neighborhood may become an extension of home for social

purposes and becomes important in identity terms possibly leading to a high degree of

interaction among community members (Forrest and Kearns, 2001). Neighborhood social

cohesion was measured using a using 5 conceptually related items that ask participants

whether or not people in the neighborhood willing to help others, get along with each

other, share the same values, can be trusted, and whether or not they agreed they lived in

a close-knit neighborhood (Sampson and Raudenbush, 1997). The items were scored on a

5-point Likert scale. Scores may range from 0 to 25 with higher scores indicating greater

levels of cohesion. The reliability with which neighborhoods can be distinguished on

neighborhood social cohesion ranges between 0.80 to 0.91 (Sampson and Raudenbush,

1997).









Housing

Nested within neighborhoods is the construct of housing. Without further

definition, housing can refer to several different types of housing such as high or low-

income housing, public or section 8 (government subsidized housing), or rental versus

owned housing. For use in this study, housing will be further defined as subsidized rental

housing (public and section 8 housing).

Housing Satisfaction (Perceived Housing Quality)

Satisfaction with one's housing was measured using one item from HIUD's

Customer Service and Satisfaction Survey (U. S. Department of Housing and Urban

Development, 2003c). The Customer Service and Satisfaction Survey was developed in

consultation with housing industry representatives and public housing resident leadership

groups. This survey consists of 20 items in addition to six optional demographic

questions that were not used in this study. This survey is designed to be both an

assessment of current resident opinions regarding their housing quality and a

management tool to identify areas of concern (U. S. Department of Housing and Urban

Development, 2004). Housing satisfaction was determined by asking participants, "How

satisfied are you with your unit/home?" Responses to these questions are based on a 5-

point Likert Scale and ranged from, "Does not apply, very dissatisfied, dissatisfied,

satisfied to very satisfied." Higher scores are indicative of more satisfaction. This

measure has not been used in research, thus, validity and reliability has not been reported.

Stress

The term stress has many definitions depending on the context in which it is used.

Hans Selye, a pioneer in the development of stress theory, developed the concept of stress

using a response-based orientation (Lyon, 2000). For some stress is good in that it










produces excitement, anticipation, and challenge; for others, the same stressor is bad,

producing an undesirable state characterized by worry, frustration, chronic fatigue, and

inability to cope (McEwen, 2005). Stress is defined in this study as an undesirable state

based on one's perceptions of situations and events such as neighborhood crime and

disorder, or unfair treatment which evokes certain emotional, behavioral, and nonspecific

physiologic responses.

Perceived Stress

Perceived Stress was measured using Cohen's (1983) Perceived Stress Scale. This

scale measures the degree to which situations in one's life are appraised as stressful. The

Perceived Stress Scale is a widely used and accepted measure with good validity and

reliability. Responses to these questions are based on a 5 point Likert scale asking

participants to respond to their feelings and thoughts over the last month. It has good

internal consistency with a Chronbach's alpha of .84 .86. Scores range from 0 to 56

with lower scores indicating less stress (Cohen, Kamarck, and Mermelstein, 1983).

Unfair Treatment and Discrimination

Unfair treatment was assessed using The Interpersonal Mistreatment Scale

developed by Williams and colleagues (1997). These items were developed to assess how

often in their day-to- day lives persons experience a variety of forms of interpersonal

mistreatment. The framework consisted of poor interpersonal treatment and made no

reference to race, prejudice, or discrimination (Guyll, Matthews, and Bromberger, 2001;

Williams, Yu, Jackson, and Anderson, 1997). The Interpersonal Mistreatment Scale

consists of 10 items on a 4-point Likert scale. Scores range from 10 to 40 with higher

scores corresponding to more frequent experiences of mistreatment. This measure has









demonstrated good internal consistency with a Cronbach's alpha of .76 to .86 (Guyll et

al., 2001; Williams et al., 1997).

Chronic Stress

Chronic stress, the cumulative load of minor, everyday stressors, can have long-

term consequences (McEwen, 1998). The effects of chronic stress may be exacerbated by

unhealthy behaviors such as lack of physical activity, high calorie, high fat diets, smoking

and alcohol use. Chronic Stress was measured in this study using the Trier Inventory for

the Assessment of Chronic Stress (TIC-S) (Schlotz and Schulz, 2004). This measure is a

comprehensive measure of chronic stress that comprises nine dimensions including work

overload, social overload, overextended at work, lack of social recognition, work

discontent, social tension, performance pressure at work, performance pressure in social

interactions, social isolation, and worry propensity. This measure is included in this study

in addition to the perceived stress scale because in addition to being more comprehensive,

it asks people to answer questions based on their experiences for the last 3 months.

Stressors experienced for this amount of time have more of a chronic component than

stress experienced for only one month. Furthermore, the TIC-S includes specific

dimensions which allow researchers to pinpoint specific areas (work or social life) that

may be considered stressful, unlike other measure used in this study. Responses are based

on a 5 point Likert scale. The TIC-S has demonstrated good internal consistency with a

Cronbach' s alpha of .76 to .91 and a split-half reliability of .79 to .89. Permission was

obtained from William Schlotz a professor at the University of Trier, Department of

Psychobiology in Johanniterufer Germany to use the short version of the Trier Inventory

for the Assessment of Chronic Stress (TICS-S) (Schlotz and Schulz, 2004).










Psychological Distress

Psychological Distress is defined as a discomforting emotional state experienced by

an individual in response to one or more stressors or demands that is manifest by a

change in baseline stable emotional state to one of anxiety, depression, demotivation,

irritability, aggressiveness, or self-depreciation (Ridner, 2004). In this study,

psychological distress was measured by using scales that measure depressive

symptomology and state anxiety. In addition to serving as independent variables that

influence the outcome variable health and salivary cortisol, these variables will also be

dependent variables when addressing the impact of neighborhood stressors and mental

health.

Depression

The Center for Epidemiological Studies of Depression Scale (CES-D) is a 20-item,

self-report scale that measures depressive symptoms in the general population

(Weissman, Sholomskas, Pottenger, Prussoff, and Locke, 1977). It includes six major

symptom areas: (1) depressed mood; (2) guilt-worthlessness; (3)

helplessness/hopelessness; (4) psychomotor retardation; (5) loss of appetite; (6) sleep

disturbance. Responses are based on a 4-point Likert scale. Validity and reliability of this

scale has been supported in previous studies Internal consistency and reliability using

Cronbach's alpha has ranged from 0.85 to 0.91 (McDowell & Newell, 1996).

State-Trait Anxiety

The Speilberger State-Trait Anxiety Inventory for Adults Form Y (STAI Form Y-

1) was used to measure anxiety. The STAI has been used extensively in research and

clinical practice. It comprises separate self-report scales for measuring state and trait

anxiety. The state portion of the scales consists of 20 statements that evaluate how










respondents feel at the moment they are completing the survey. The trait portion of the

scale consists of 20 statements that assess how people generally feel (Spielberger,

Gorsuch, Lushene, Vagg, and Jacobs, 1983). Responses are based on a 4-point Likert

scale. This measure had demonstrated good internal consistency with a Cronbach's alpha

of .86 to .95.

General Health

General Health was measured using one item from the SF-12v2TM SUTVey form

(Ware, Kosinski, and Keller, 1996). Participants were asked, "In general would you say

your health is poor, fair, good, very good, or excellent?" Answers were based on a four-

week recall. Scores ranged from 1 to 5 respectively. These scores were transformed to a 0

to 100 scale and compared with national norms for women of the same age group (Ware,

Kosinski, Turner-Bowker, and Gandek, 2002). Cronbach's alpha for the SF-12v2TM

survey ranges from 0.73 0.77 in the general population of women ages 18 to 44 years

old (Ware et al., 1996).

Salivary Cortisol (SC)

SC is a widely accepted method for measuring physiological responses to acute

laboratory induced stress and perceived chronic stress. It highly correlates with serum

(blood) and urine cortisol levels and offers stress-free, non-invasive sampling, easy

collection and storage (Kirschbaum and Hellhammer, 1994). However, cortisol levels are

affected by a variety of factors such as an acute stressor, smoking, drugs (such as steroid-

based medications, contraceptives, anti-depressants and anxiolytics), a high protein meal,

lack of sleep and the luteal phase of the menstrual cycle (Kirschbaum and Hellhammer,

1992). These factors were controlled for in the exclusion criteria and saliva collection

protocol, or by incorporating them as covariates in statistical models. Samples were










analyzed using the HS-Cortisol High Sensitivity Salivary Cortisol Enzyme Immunoassay

Kit. This kit requires minimal saliva volume (25 CIl), detects < 0.012 to 3.0 Cll of cortisol,

has a serum-saliva correlation of r = .94, p <.0001 (Salimetrics, 2005). It was designed as

a superior alternative to resolve problems associated with serum-based

radioimmunoassay and other salivary immunoassays (Schwartz, Granger, Susman,

Gunnar, and Laird, 1998).

Participants provided 12 cortisol samples consisting of 6 samples per day for 2

days. Specimens were collected over 2 days based on expert recommendations from the

John D. and Catherine T. MacArthur Research Network on Socioeconomic Status and

Health. Though somewhat controversial, the more measurements in a day for a greater

number of days (at least 3 to 4) allows for a more reliable measurement of "trait" daily

concentration of cortisol (AUC). The advantage of using multiple days is that it helps to

control the unreliability of one day's data, which can underestimate the cortisol

relationship to outcomes (Stewart and Seeman, 1999).

A period of 2 days was decided upon for several reasons. First, prior research

experience with a similar population suggested that data collection for a period of time

longer than two days would be unrealistic. The day to day turmoil experienced by many

in this population precludes prolonged daily data collection. Furthermore, daily data

collection for 4 to 6 days places a significant burden on the participants in addition to

their daily routines and responsibilities. Finally, biological specimen collection and

analysis is costly. Materials and supplies for collection and analyses of biological

specimens can be quite expensive, and participants should be compensated appropriately









for the time commitment and burden placed upon them as study participants. Therefore,

financial constraints also prevented more frequent or prolonged data collection.

Specimen collection was timed based on each participant' s time of awakening with

the first sample to be collected upon awakening (T1). The remaining 5 samples were

collected at 30 minutes I hour, 4, 9, and 11 hours after waking (T2-T6). This method of

salivary cortisol collection is preferred since the time of cortisol peak is not dependent

upon the absolute time nor is it influenced by daylight; it is dependent on wake-up timing

of each individual (Immuno-Biological Laboratories, 2004; Stewart and Seeman, 2000).

The total area under the curve (AUCg) with respect to ground as described by

Pressner and colleagues (2003) was examined in terms of its relationship to the

independent variables in this study. The formula used for the AUCg is derived from the

trapezoid formula (Pressner, Kirschbaum, Meinlschmid, and Hellhammer, 2003). The

formula used to calculate AUCg is presented below in Equation 3-1.

Equation 3-1


AUCg =
(SC2+SC 1)/2*tl+(SC3+SC2)/2*t2+(SC4+SC3)/2*t3+(SC5S4/*4(C+C)2t


This AUCg calculation takes into account change over time of each measurement and the

distance of the measures from zero (the level at which the changes over time occur and

results in a measure that is more related to total hormonal output (Pressner et al., 2003).

Researchers at the MacArthur Research Network on Socioeconomic Status and Health

agree that AUC is the most widely accepted measure whereas diurnal rhythm, or diurnal

'pattern' analysis is more controversial (Stewart and Seeman, 2000).









However, AUCg is not without limitations. Though AUCg is a summarized index

for repeated measures over time, it is not sensitive to fluctuations of repeated measures.

For example, if two persons have completely different patterns of cortisol levels relative

to time, they may get the same AUCg. In addition, the AUCg approach does not take into

account the correlations among repeated outcome measures within a specific person.

Given these limitations, generalized estimating equations (GEEs) will additionally be

used to examine the relationships among the independent variables and salivary cortisol.

GEEs provide a general framework for the analyses of continuous, ordinal,

polychotomous, dichotomous, and count-dependent data, and relax several assumptions

of traditional regression models. GEEs represent an extension of the generalized linear

model (GLMs) to accommodate correlated data. GLMs assume that the dependent

variable can be expressed as a linear function of the independent variables. It also

assumes that the variance of the dependent variables is a known function of its

expectation (thus allowing relaxation of the homoscedasticity assumption). Other

assumptions of the GEE method include: (1) the number of clusters be relatively high (a

rule of thumb is no fewer than 10, possibly more than 30, and (2) the observations in

different clusters be independent, although within-cluster observations may correlate.

Hence, GLMs do not require the specification of the form of the distribution, but only the

relationship between the outcome mean and the explanatory variables and between the

mean and the variance (Ghisletta and Spini, 2004).

GEE is a marginal (or population averaged) as opposed to a cluster-specific (or

subj ect-specifie, conditional) method. Population average models model the average

response over the subpopulation that shares a common value of the predictors as a









function of such predictors. Population average parameters represent the averaged effect

of a unit change in the predictors for the whole population. The GEE approach specifies a

working correlation matrix for the vector of repeated measures from each participant to

account for the dependency among the repeated measures. The working correlation can

be assumed to be the same for all participants, reflecting average dependence among the

repeated measures over participants. Several working correlation structures can also be

specified, including independent, exchangeable, autoregressive, and unstructured

correlation. The standard errors are derived from what is called the sandwich estimator of

the covariance matrix of the regression coefficients. The main advantage of GEEs is that

the calculation of the standard errors for the regression coefficients is robust even if the

specifications of the correlation structure is incorrect or if the strength of the correlation

between repeated outcomes varies somewhat from person to person. Although the use of

robust standard errors ensures that regression inferences are consistent regardless which

correlation structure is chosen, however, there is no straightforward way in GEE models

to truly determine the best correlation structure to use (Ghisletta and Spini, 2004).

GEE is not without limitations. First the technique is asymptotic, hence requiring

large total sample sizes for unbiased and consistent estimation. Second, in applications to

empirical data, sensitivity analyses of different specifications of the intracluster

correlation matrix are advised. Finally, GEE methodology assumes missing completely at

random data, because GEEs do not specify the full conditional likelihood. However,

GEEs do no yield a great deal of bias with missing at random data (Ghisletta and Spini,

2004).









Given the limitations of AUCg and the advantages of GEE methods, GEE will

also be used to examine the relationships among neighborhood characteristics,

psychological distress, stress, and salivary cortisol.

Individual Social Support

Individual social support is considered a covariate in this study. The amount and

type of individual social support one has may possibly offset the lack of support that may

exist in the area in which one lives. Therefore, it is important to control for the amount of

individual social support when examining the effects of neighborhood social cohesion on

health. Individual-level social support was measured in this study using the International

Support Evaluation List General Population Form (ISEL-GP) (Cohen, Mermelstein,

Kamarck, and Hoberman, 1985). ISEL-GP consists of 40 items designed to assess the

perceived availability of four separate functions of individual social support (tangible,

appraisal, self-esteem, and belonging). Responses are measured on a 4-point Likert scale.

In other studies Cronbach's alpha has been reported as 0.88 and 0.90 and test-retest

reliability coefficients = 0.87 (Cohen et al., 1985).

Study Protocol

Participants were screened for inclusion in the study. For those who met inclusion

and exclusion criteria and agreed to participate, a time and place was agreed upon for the

participant to meet with the PI. At this initial meeting, the consent to participate in

research was reviewed with the participant, who then signed the informed consent form

approved by the Institutional Review Board Human Subj ects Committee at the University

of Florida. At this point, the PI or research assistant covered the requirements of the study

in detail. The PI or research assistant left the Salivettes for saliva collection and the

questionnaire and scheduled a time to pick up the saliva and completed questionnaire.










To provide a sample, participants were given 12 tubes called Salivettes@ (The

Sarstedt Group, 2003). Six tubes for each day of collection were provided in separate

plastic bags. Saliva collection times were based on the time of awakening and were

collected 30 minutes, 1, 4, 9, and 11 hours after waking. Participants were instructed to

collect the first saliva specimen (upon awakening) before rising and getting out of bed.

Upright positions may significantly increase salivary cortisol concentrations (Hennig et

al., 2000). They were also instructed to place a cotton roll in their mouths, chew on it

until it became saturated, and place it in the salivette. Participants were instructed not to

brush their teeth, smoke, eat, or drink anything at least two hours prior to collection

because the factors have been shown to alter salivary cortisol concentrations

(Kirschbaum, Read, and Hellhammer, 1992). They were also instructed to place the

salivette tubes in the freezer at the end of each day. After being collected by the

researcher or research assistant, samples were centrifuged and stored frozen (-200 C).

Before analysis samples were thawed and mucins were precipitated from the specimens

at 3000 rpm for 15 minutes. Cortisol was measured by using Expanded Range High

Sensitivity Salivary Cortisol Enzyme Immunoassay Kit (Salimetrics, 2005). All analyses

were conducted according to the manufacturer' s directions. Samples with greater than

30% coefficient of variation (CV) were rerun. Inter- and intra-assay CV% was less than

15%. Inter-assay CV is based on the high and low controls of 28 plates. Intra-assay CV

was based on eight high and eight low control duplicate samples.

Participation in this study required a commitment of completing a survey that took

approximately 1 to 1.5 hours to complete and completing saliva collection for 2 days.

Each saliva collection was estimated to take a maximum of 5 minutes which would entail









an additional 1 hour of the participant' s time. Given the time burden placed on the

participants, a $30.00 gift certificate to Wal-mart was given to each participant that

completed data collection. A $30.00 gift certificate was used as opposed to cash so it

would not be counted as income, placing the participants at risk for loosing food stamp

supplements, housing subsidy or other Einancial assistance through the Temporary

Assistance for Needy Families program, if they were receiving these supports.

Statistical Analyses

Data were analyzed using Stata 9.0 statistical software. Two-tailed tests were used

in all cases and an alpha level of .05 was selected a priori to determine significance.

Descriptive statistics were tabulated for all variables.

Statistical Analysis Approach

Before any analyses were conducted, the primary outcome variables (general

health, state anxiety, depression and SC-AUCg) were examined for normality. Skewness

and kurtosis tests for normality were used to examine the distribution of all study

variables (see table 3-1 below). General health was transformed to a 0 to 100 scale.

General health and SC-AUCg were both positively skewed; therefore, log

transformations were conducted based on the ladder of powers (Hamilton, 2006).

Depression was also positively skewed, but was transformed using square root

transformation. Choosing a transformation method for each outcome variable was based

on analyses using ladder of powers. This test combines the ladder of powers with tests of

normality specificallyy the skewness/kurtosis test in Stata) and reports whether the result

is significantly non-normal (Hamilton, 2006). The transformation with the lowest Chi

square and a normal distribution was chosen because most statistical procedures work

best when applied to variables that follow a normal distribution.










Table 3-1 Skewness and Kurtosis for Study Variables
Neighborhood Characteristics Skewness Kurtosis
Neighborhood Economic Disadvantage 0.000 0.089
Neighborhood Disorder 0.305 0.456
Neighborhood Stress 0.039 0.515
Neighborhood Social Cohesion 0.474 .669
Individual-level Variables
Housing Satisfaction 0.001 0.184
Unfair Treatment 0.212 0.210
Perceived Stress 0.780 0.527
Chronic Stress 0.732 0.629
ISEL social support 0.501 .556
Anxiety 0.130 0.510
Depression 0.645 0.007
General Health 0.001 0.357
Salivary Cortisol (SC) 0.000 0.001
AUCg~ug/dl


Adj chi2
13.76
1.67
4.69
0.71


10.63
3.26
0.49
0.35
0.82
2.84
6.76
10.05
26.33


PrOb>chi2
0.0010
0.434
0.096
0.6999


0.005
0.195
0.784
0.8375
0.2413
0.6637
0.034
0.0066
0.0000


Specific Aim 1

The first aim of this study was to determine the relationships among neighborhood

characteristics, perceived stress, psychological distress, and salivary cortisol levels

among low SEP female heads of households with children living in either section 8 or

public housing. More specifically, this research sought to examine whether neighborhood

characteristics had an independent effect on the outcome variables

Bivariate correlation and multiple regression analyses were used to determine

significant relationships among the study variables. First simple regression analyses were

conducted and nonsignificant explanatory variables were not added to subsequent

models. Standard multiple regression analyses were utilized to determine associations

between neighborhood characteristics, depression, anxiety, health, and SC-AUCg above

and beyond individual level predictors. For all multiple regressions, assumptions were

tested by examining normal probability plots of residuals and scatter diagrams of









residuals versus predicted residuals. No violations of normality, linearity, or

homoscedasticity were detected. There was no evidence of influential outliers based on

stem and leaf plots and studentized residuals. In addition, perceived stress, chronic stress,

anxiety and depression were examined for multicollinearity. Finally seemingly unrelated

regression is used to compensate for cross-equation error correlation between the anxiety

and depression equations (Chen, Ender, Mitchell, and Wells, 2006).

Issues of Multicollinearity

Multicollinearity can occur in multiple regression analysis when independent

variables are too highly intercorrelated (Polit, 1996) and is associated with unstable

estimated regression coefficients (Chatterj ee, Hadi, and Price, 2000). A thorough

investigation of multicollinearity will involve examining the value of R2 that results from

regressing each of the predictor variables against all the others. Table 3-2 shows

collinearity diagnostics for all possible explanatory variables. The relationship between

explanlatory variables, R would be closeC to 1, andC LI theIIC~ vaiance LLV inflation fato (VIF)

would be large. Values of VIF greater than 10 is indicative of collinearity problems

(Chatterj ee et al., 2000). Tolerance defined as 1/VIF is used also used by many

researchers to check on the degree of collinearity. A tolerance value lower than 0. 1 means

that the variable considered is a linear combination of other independent variables (Chen

et al., 2006). In addition, a condition number a commonly used index of global

instability greater than or equal to 10 is an indication of global instability. The

condition index number for the variables noted in table 3.2 is 4.66. No problems with

collinearity were identified.










Table 3-2 Collinearity Diagnostics for Explanatory Variables
Variable VIF Tolerance R2 COndition
Index
Neighborhood Economic Disadvantage 1.13 0.885 0.11 1.0
Neighborhood Disorder 1.45 0.692 0.31 1.75
Neighborhood Stress 1.95 0.514 0.49 2.05
Neighborhood Social Cohesion 1.67 0.599 0.40 2.41
Unfair Treatment 1.51 0.663 0.34 2.65
Perceived Stress 1.67 .0598 0.40 2.78
Chronic Stress 2.27 0.440 0.56 3.22
Social Support 1.99 0.504 0.50 3.41
Depression 2.87 0.350 0.65 3.50
Anxiety 3.16 0.317 0.68 4.66


Seemingly Unrelated Regression

Pairwise correlation of anxiety and depression revealed that these two measures

had a strong correlation (r, 0.74; p-value < 0.001). Though problems with collinearity

when these variables were used as explanatory variables were not revealed as mentioned

above, it was suspected that when anxiety and depression were used as dependent

variables in separate equations, the regression errors may be correlated. Correlation of

errors in regression models may lead to underestimation of the regression coefficients

(Chen, Ender, Mitchell, and Wells, 2005). Seemingly unrelated regression allows

researchers to estimate both models simultaneously while accounting for the correlated

errors at the same time, leading to more appropriate standard errors (Chen et al., 2005).

Unlike traditional multivariate regression, seemingly unrelated regression allows one to

estimate equations that do not have the same set of predictors, allowing more flexibility

in model estimation approaches. The estimates provided for the individual equations are

the same as the ordinary least squares estimates. A Chi- Square test is used to determine

the overall fit of the model (Chen et al., 2005). Seemingly unrelated regression was used









instead of multivariate regression because the explanatory variables differed for the two

equations.

Multi-level Analysis

Typically, when data are nested as in this study persons nested within

neighborhoods and the study is examining the contextual effects of neighborhoods on

individual health, multi-level analyses are warranted (Diez-Roux, 2000). Multi-level

analysis allows researchers to examine neighborhood-level variation in health among

populations (Merlo, Chaix, Yang, Lynch, and Rastam, 2005) and to test hypotheses about

how variables measured at one level (neighborhoods) affect relations occurring at another

(individual) level (Raudenbush and Bryk, 2002). It is intuitive that people living in the

same neighborhood or in neighborhoods with similar characteristics will have

comparable health characteristics. Therefore, when examining neighborhood contextual

effects on individual health, variation in neighborhood characteristics is essential. Given

the lack of variation in neighborhood economic disadvantage in this study (as determined

in Aim 2), multi-level statistical analyses could not be conducted.

Specific Aim 2

The second aim of the study was to determine the differences in neighborhood

characteristics of two subsidized housing types, specifically section 8 and public housing,

in which low SEP female heads of households with children live.

Assumptions for using t-tests include random sampling, a normal distribution, and

homogeneity of variance. Skewness and kurtosis tests for normality as shown in Table

3.1 were used to examine the distribution of all outcome variables. Variance comparison

tests for each of the neighborhood variables by housing subsidy type showed that the

homogeneity of variance assumption was not violated. Neighborhood economic









disadvantage was negatively skewed. Group comparison t-tests were used to determine

the differences in neighborhood disorder, neighborhood stress, and neighborhood social

cohesion by housing type. The Mann-Whitney U-test, the non-parametric analogue of the

t-test, (Polit, 1996) was used to examine differences neighborhood economic

disadvantage by housing subsidy type.

Specific Aim 3

The final aim of the study was to examine the differences in housing satisfaction,

perceived stress, psychological distress, and salivary cortisol levels, in low SEP female

heads of households with children by housing subsidy type (section 8 and public

housing).

Again, assumptions as noted in the previous section were analyzed for violation.

General health, housing satisfaction, depression, and SC-AUCg were significantly

skewed as shown in Table 3.1. SC-AUCg, general health and depression were

transformed as previously described. Group comparison t-tests were performed to detect

differences in SC-AUCG, depression, perceived stress, chronic stress, anxiety, social

support, and health by housing subsidy type. Variance comparison tests showed no

violations in homogeneity of variance by housing subsidy type. Mann-Whitney Utests

were used to examine the differences in housing satisfaction by housing subsidy type

because housing satisfaction was a one-item question measured on an ordinal scale and

was not normally distributed.

Missing Data

Missing data were present in several study variables including salivary cortisol.

Item non-response occurs when a participant does not respond to a question or questions

on a survey, which is the case for the missing data in this study. Several methods to deal









with missing data are available to researchers depending on the pattern of missing data

including case mean substitution, sample and group mean substitution, hot-deck

imputation, regression and multiple imputation (Fox-Wasylyshyn and El-Masri, 2005;

Patrician, 2002). Case-wise single item imputation using multinomial logistic regression

analysis was used to impute data in this study. This method was chosen because it uses a

respondent' s scores on non-missing values within a scale or subscale to predict missing

values. This approach takes into account that missing values may differ based on

differences in individual characteristics. The outcome variables (item codes) were

categorical with more than two categories; polytomous or multinomial logistic regression

was preformed to predict the missing value in a subscale. Regression imputation uses

knowledge of the available data to predict values of missing data. The underlying

principle is that missing data items can be predicted by other items in the measure or

subscale, the resulting regression equation can be used to predict missing values

(Patrician, 2002). More specific information is provided regarding missing data patterns

in the section Handling Missing Survey Data.

Handling Missing Cortisol Data

Of the 84 participants, 14 did not have usable cortisol data (defined as greater than

2 time points missing in one day). These cases were deleted and not used in data

analyses. Of the 70 participants remaining, 49 had complete cortisol data on Day 1 and

46 on Day 2. For statistical analyses missing data at Days 1 and 2 T2 were replaced by

the average values from the preceding and following samples. For example, from table 3-

3 below, one participant was missing cortisol data on Day 1 T2 and TS, and on Day 2 T3.

The average of T1 and T3 on Day 1 was used to replace the missing data point.(0.219 +

0.44)/2 = 0.66/2 = 0.33. Therefore, 0.33 was the value used to replace the missing data










point for the Day1 at T2. Equation 3-2 provides a formula for calculating the average for

a T2 data point.

Table 3-3: Example of Missing Cortisol Data for One Participant
Time of Day Day 1 Day 2 Replacement Value
T1 Awakening 0.219 0.094 --
T2 30 min after waking 0.225 0.33
T3 60 min after waking 0.44 0.44
T4 4 hr after waking .552 0.272 --
T5 9 hr after waking 0.166 0.166
T6 11 hr after waking 0.199 0.122 --


Equation 3.2: Formula for Calculated T2 SC for Days 1 and 2

T2 = T1 + T3/2

When data were missing at any time other than T2, the value from the same time point on

the preceding or following day was taken. For example, from table 3-3 the participant

was missing cortisol data on Day 2, T3 this missing data point was replaced with the

value at the same time from the preceding day (0.44).These techniques have been utilized

in other studies (Odber, Cawood, and Bancroft, 1998). After imputing SC data, a total of

70 participants were retained for data analysis.

Handling Missing Survey Data

Once cases were deleted due to missing cortisol data, missing survey data was

imputed. No more than 20% of the data were missing from any study measure. Before

imputing data, missing value patterns were determined by dummy coding missing data

for each participant with 0 = no missing data and 1 = at least one missing data point.

Study participants were grouped on whether or not missing data was present and two-

sample t-tests were performed on each study variable. Creating a missing data dummy

code and computing t-test comparisons between respondents and non-respondents is









often used to determine if non-responders differ on any of the items in the data set

(Wasylyshyn and El-Masri, 2005). A significant difference between respondents and non-

respondents indicates an association, and rules out the possibility the data are missing

completely at random (MCAR) (Wasylyshyn and El-Masri, 2005). Missing data points

are said to be MCAR if the probability of missing data on one variable is not related to

the value of that variable or is not related to other variables in the data set (Patrician,

2002). Because the state anxiety was statistically significantly different (t= -1.99, df 70,

p=0.05), and the individual social support scale approached significance, (t=-1.88, df, 61.

p=0.06), data from this study were determined to be missing at random (MAR). MAR

occurs when the probability of a missing data point in one variable is not related to the

value of that variable (Patrician, 2002). Each measure used in this study was divided into

its appropriate subscales, if present, and multinomial regression analyses were performed

for each item missing within a measure based on items present within the subscale.

Case-wise multinomial regression imputation was used to predict missing values.

This method ascribes the respondent' s predicted score based upon the items that are

present within in the missing score subscale for that respondent. The primary advantage

of this technique is that it acknowledges differences across cases (respondents) and

maximizes any one respondents own data from items in a given subscale. Also, imputing

item-level missing data retains the inter-subj ect variability across summed scores because

the maj ority of information from each participant is retained with measurements and their

sub scales. Using single value regression to replace missing values is most useful when

data are 10% 40% incomplete (Wasylyshyn and El-Masri, 2005).









After data imputation for each study variable was complete, three additional

participants had to be withdrawn from the study due to excessive missing data, leaving a

Einal sample size of 67.

In summary, after imputing missing data, 67 women were included in data analysis.

Specific aim 1 was addressed by bivariate analysis, standard multiple and multivariate

regressions, and GEE. Specific Aims 2 and 3 are examined by using t-test and the Mann-

Whitney Utest depending on the type of variable under study and whether the normality

assumption was met.















CHAPTER 4
RESULTS

The first aim of this study was to examine the relationships among neighborhood

characteristics, perceived stress, psychological distress, and salivary cortisol levels among

low SEP female heads of households with children. The second aim was to examine the

differences in neighborhood characteristics by housing subsidy type (i.e., public and

section 8 housing). Finally, this study sought to determine if participants who lived in

public versus section 8 housing differed in terms of stress, psychological distress, general

health and salivary cortisol levels.

This chapter first presents descriptive results, including means, standard deviations,

and frequency data for each variable. The hypotheses posed in Chapter 1 are addressed

using parametric and nonparametric tests.

Descriptive Results

Description of the Sample

As described in Chapter 3, data analysis included a final sample size of 67 women.

Most of the participants in this study were black, single, had a high school education or less

and one to two children. The mean age was 30 years old. Over half of the participants

reported their main daily activity as either looking for work or keeping house and raising

children. Mean gross income was $486.50/month. Sixty-four percent of the participants

lived in section 8 housing and less than one-third were receiving direct financial assistance

through the Temporary Assistance for Needy Families Program (TANF). Table 4-1 below

provides a detailed description of the sample.










Table 4-1: Sample Demographic Profile:
N
Age--
Income--
Race
White 12
Black 54
Hispanic/Latino 1
Marital Status
Married 6
Single 57
Divorced/Separated 3
Education
Less than 9th grade 4
Less than 12th grade 21
High School Diploma 9
General Education Diploma 10
Some College/Training 16
Associates Degree 5
Number of Children
1-2 44
3-4 21
5-7 2
Daily Activity
Work Full-time 9
Work Part-time 10
School Full-time 4
School Part-time 4
Work and School Part time 6
Unemployed 20
Keep House/Raise Children 30
Housing Type:
Public Hosing 24
Section 8 Housing 43
TANF Assistance
Yes 23
No 44


(n=67)
% Mean (SD)
-- 30.33 (8.31)
--486.50 (440.71)


Range
18-45
$0-$2.100


17.91
80.60
1.49

9.09
86.36
4.55

6.15
32.31
13.85
15.38
24.62
7.69

65.87
31.34
2.98

13.43
14.93
5.97
5.97
8.96
25.37
25.37

35.82
64.18

29.03
70.97


Neighborhood Characteristics of the Sample

Two-thirds of the participants lived in neighborhoods with the greatest amount of

economic disadvantage that were characterized by high rates of disorder, and exposure to


crime. (See figure 4-1).














62.69









N] 16.42


1.493 1.493 1.493

0 3 6 9 12
NED



Figure 4-1: Neighborhood Economic Disadvantage (NED) for all Participants


Over 50% of the participants scored above the mean on neighborhood disorder while 25%

scored will over the mean of 37. 15 on neighborhood stress indicating that they perceived

their neighborhoods as areas with high rates of and crime. In addition, these women also

reported higher rates of social cohesion which is not surprising given that studies have

shown that neighborhood social cohesion may buffer the effects of neighborhood disorder

and stress (Ross and Jang, 2000). See Table 4.2 on the following page.

Table 4-2: Sample Description of Neighborhood Characteristics.
Variables Mean (SD) Range
Neighborhood Characteristics
Neighborhood Economic Disadvantage 10.16 (12.66) 1-12
Neighborhood Disorder 36.52 (17.98) 16-55
Neighborhood Stress (Crime Exposure) 37.15 (11.89) 18-72
Neighborhood Social Cohesion 13.31 (13.86) 5-25










Stress, Psychological Distress, Health, and Salivary Cortisol Sample Characteristics

Table 4-3 provides mean scores and ranges for all individual level psychosocial and

stress variables.

Table 4-3: Stress, Psychological Distress, Health and Salivary Cortisol Scores


Variables


Mean (SD)
21.49 (16.35)
28.64 (16.87)
52.82 (+21.48)
70.46 (120.76)
24.73 (11.77)
44.67 (11.95)
37.21 (127.69)
2.84 (12.19)


Range
10-36
12-45
0-105
26-117
2-47
20-70
0-100
0.227-10.71


Unfair Treatment
Perceived Stress
Chronic Stress
Individual Social


Support


Depression
State Anxiety
General Health
Salivary Cortisol (AUC) ug/dl


Salivary cortisol levels vary based on the time at which the sample is taken. The

ranges of salivary cortisol in this sample of women are within the ranges for healthy

women of the same age group reported by other investigators (Kirschbaum, Read, and

Hellhammer, 1992). Table 4-4 provides mean scores and ranges for salivary cortisol

measures by day and time.


Table 4-4 Salivary Cortisol Scores by Day and Time
Salivary Cortisol (ug/dl) Mean (SD)
by Day/Time


Day 1







Day 2


Time 1
Time 2
Time 3
Time 4
Time 5
Time 6

Time 1
Time 2
Time 3
Time 4
Time 5
Time 6


awakening
30 minutes after waking
60 minutes after waking
4 hours after waking
9 hours after waking
11 hours after waking

awakening
30 minutes after waking
60 minutes after waking
4 hours after waking
9 hours after waking
11 hours after waking


0.315 (.259)
0.328 (0.277)
0.261 (0.256)
0.255 (0.241)
0.195 (0.235)
0.194 (0.227)

0.292 (0.275)
0.332 (0.32)
0.269 (0.237)
0.223 (0.236)
0.180-(0.201)
0.136 (0.172)


0.02-1.25
0.02-1.27
0.016-1.48
0.015-1.08
0.015-1.17
0.011-0.91

0.013-1.53
0.015-1.40
0.014-0.91
0.017-1.10
0.007-0.84
0.017-0.83


Range










Overall, this sample of women reported higher levels of anxiety and scored lower on

general health compared to national norms (Spielberger, Gorsuch, Lushene, Vagg, and

Jacobs, 1983; Ware, Kosinski, Turner-Bowker, and Gandek, 2002; Weissman, Sholomskas,

Pottenger, Prussoff, and Locke, 1977) indicating poorer health. (See Table 4-5). They

scored well above the cut off of 16 on the CES-D, which indicates depressive symptoms

are high enough to suggest clinical depression with a mean of 24.73.


Table 4-5: Mean Psychological Distress and General Health Scores Compared to National
Norms
Sample Mean Norm for females of same age
(SD) (SD)
State Anxiety 44.67 (a 11.95) 35.20 (a 10.61)
Depression 24.73 (a 11.77) >16 Suggests clinical depression
General Health 37.21 (a 27.69 49.84* 52.11** 51.01***
(a 10.62) (A 9.86) (A 8.70)
* National norms for women 18-24 years old
** National norms for women 25-34 years old
*** National norms for women 35-44 years old

Specific Aim 1: Associations among Neighborhood Characteristics, Stress,
Psychological Distress, Health and Salivary Cortisol

The first aim of this study was to determine the relationships among neighborhood

characteristics, perceived stress, psychological distress, and salivary cortisol levels among

low SEP female heads of household with children 18 years old or less. It was hypothesized

that higher rates of neighborhood disorder, exposure to crime, and neighborhood economic

disadvantage, and elevated levels of stress would be positively associated with depression,

state anxiety, and salivary cortisol and negatively associated with general health. More

specifically, this research investigated whether neighborhood characteristics had an effect

on any of the outcome when individual level factors (perceived stress, unfair treatment,

chronic stress, and social support) were added to the model.










Bivariate Analyses of Neighborhood Characteristics, Housing Satisfaction, Stress,
Depression, State Anxiety, Health and Salivary Cortisol

Based on bivariate correlations the hypotheses for specific aim 1 are partially

supported. Neighborhood disorder (ND), neighborhood stress (NS), and neighborhood

social cohesion (NSC) have significant weak to moderate positive associations with

depression, chronic stress, and unfair treatment. Only ND and NS were positively

associated with perceived stress. NSC had a positive, but weak association with housing

satisfaction and a weak negative correlation with chronic stress. Housing satisfaction also

had a weak negative association with unfair treatment. (See Table 4-6). Neighborhood

economic disadvantage (NED) was not associated with any of the outcome variables in this

study. The remainder of this section is ordered based on the outcome variable under study.

First, predictors of general health are presented, followed by state anxiety, depression and

finally SC-AUCg.

Table 4-6: Correlations between Neighborhood Characteristics, Housing Satisfaction,
Psychological Distress, General Health, and Salivary Cortisol

NEDa ND NS NSC Housing a
Satisfaction
Housing Satisfaction a -0.033 0.23 (0.06) -0.20 0.30*
State Anxiety -0.12 0.22 (0.06) 0.37** -0.14 -0.11
Depression (sqrt) -0.17 0.29* 0.39** -0.24* -0.06
General Health (log) -0.07 -0.09 -0.04 .019 0.057
Unfair Treatment -0.19 0.41*** 0.35** -0.29* -0.25*
Perceived Stress -0. 14 0.26* 0.39** -0. 19 -0.02
Chronic Stress -0.15 0.48*** 0.52*** -0.25* -0.04
Salivary Cortisol (SC)
AUCg ug/dl (log ) 0.07 -0.09 -0.11 0.13 -0.08

Note: *p< 0.05 **p <0.01 ***p<0.001; n =67




























































-0.40** 0.14 0.11


8.85 -0.68 -0.13


Note: *p < 0.05 **p < 0.01 ***p<0.001; df (1, 65); n = 67


General Health, Neighborhood Characteristics, Stress, and Psychological Distress

As previously stated, general health was log transformed to obtain a normal

distribution. Bivariate regression analysis revealed that unfair treatment and smoking

significantly impacted health in this sample of women. However, the magnitude of the

effect of unfair treatment is quite small (adj. R2 = 0.05, F (1,65 = 4.37. p-value <0.05)

accounting for only five percent of the variability in general health. Smoking (adj. R2

0. 11, F (1, 65 = 8.85. p-value <0.01) accounted for 1 1% of the variation in health. As

shown in table 4-7 below, none of the other variables in this study had a significant effect

on general health.


Results for General Health
B SE Adj R2 F
hborhood Characteristics
-0.006 0.021 0.001 0.08


Table 4-7: Bivariate Regression
Variable
Neig:


95% CI

-0.05 0.04

-0.017 0.01
-0.01- 0.008
-0.004 0.036


-0.03 0.002
-0.01 0.003
-0.35 0.001
-0.01 0.002
-0.02 0.002
-0.002 0.008

-0.02 0.005
-0.43 0. 17
-0.1 0.08
-0.06 0.08
-0.0003 0.00


0.25
0.04
2.34


-0.003
-0.001
0.013


Neighborhood Economic
Disadvantage
Neighborhood Disorder
Neighborhood Stress
Neighborhood Social
Cohesion

Perceived Stress (PSS)
Chronic Stress (TCSI)
Unfair Treatment
State Anxiety
Depression
Individual Social Support
(ISEL)
Age
Marital Status
Number of children
Education
Monthly Income
Smoking


Individual
-0.013
-0.002
-0.178*
-0.01
-0.007
0.003

-0.008
-0.13
-0.01
0.01
-0.00


0.007 0.02
0.005 0.004
0.008 0.001

Level Factors


0.008 0.03 2.90
0.003 -0.01 0.45
0.008 0.05 4.37
0.004 0.01 1.89
0.005 0.02 2.18
0.003 0.004 1.23

0.006 0.007 1.49
0.15 0.01 0.73
0.05 -0.01 0.06
0.04 -0.01 0.08
0.00 -0.01 0.17










Multiple regression analysis of the effects of smoking and unfair treatment on health

showed that both variables are significant predictors of health (adj. R2 = 0. 11, F (2, 64 =

6.76. p-value <0.01) (table not shown). Potential confounding variables considered were

age, race, marital status, number of children living in the household, income, and smoking.

None of these variables (other than smoking) were significantly associated with general

health in bivariate regression analyses.

Neighborhood and Individual Level Effects on State Anxiety

Bivariate analyses (see Table 4-8) show that neighborhood stress (disorder plus exposure to

crime) significantly affects state anxiety accounting for 13% of the variation (Adj. R2 0. 13,

F (1, 65) = 10.56, p-value 0.002). No other neighborhood characteristics had an impact on

state anxiety.

Table: 4-8: Bivariate Regression Results for State Anxiety


Variable


F 95% CI


:ighborhood Characteristics
-0.67 0.55 0.023

0.33 0.18 0.036
0.37** 0.11 0.13
-0.26 0.23 0.004
Individual Characteristics
0.38 0.23 0.03
1.01*** 0.18 0 .33
0.30*** 0.06 0.28
-0.35*** 0.06 0.37
-0.04 0.18 -0.01
3.27 2.09 0.02
-1.3 0.10 0.01
-0.005 0.003 0.01
4.6 4.02 0.005
-1.7 1.25 0.01
** p<0.001: df 1, 65 n = 67


Neighborhood Economic
Disadvantage
Neighborhood Disorder
Neighborhood Stress
Neighborhood Social Cohesion

Unfair Treatment
Perceived Stress (PSS)
Chronic Stress (TCSI)
Individual Social Support
Age
Race
Education
Income
Marital Status
Number of children
* p <0.05, ** p <0.01, *"


1.50

3.43
10.56
1.29

2.78
32.94
27.18
39.92
0.04
2.45
1.80
1.90
1.30
1.85


-1.77 0.42

-0.03-0.70
0.14 0.61
-0.73 0.20

-0.075 0.84
0.66 1.36
0.19 0.42
-0.47 -0.24
-0.40 0.32
-0.90 7.45
-3.27 0.64
-0.01 0.002
-3.4 12.6
-4.22 0.8


The Einal model for state anxiety included neighborhood stress, perceived stress, chronic

stress and individual social support. Covariates considered were, age, marital status, race,


B SE Adj. R2









education, income, and number of children living in the household. None of these suspect

covariates had a significant impact on state anxiety and were not included in the final

model. Neighborhood stress, perceived stress, chronic stress and social support were added

to the final model. Once individual level characteristics were added to the model,

neighborhood stress no longer had an effect on state anxiety. Together perceived stress and

social support accounted for almost 50% of the variation in state anxiety (Adj. R2 = 0.49, F

(4, 62) = 17.12, p < 0.001). See Table 4-9 below

Table 4-9 Effects of Neighborhood and Individual Level Characteristics on State Anxiety
Variable B SE 95% CI
Neighborhood Characteristics
Neighborhood Stress -0.13 0.11 -0.22 0.20
Individual Level Factors
Perceived Stress (PSS) 0.60 ** 0.18 0.22 0.93
Chronic Stress (TCSI) 0.11 0.64 -0.01 0.24
Individual Social Support (ISEL) -0.21*** 0.63 -0.33 --0.08
Note: n = 67 F(4, 62) = 17.12 Adj. R2 = 0.49***
* p <0.05, ** p <0.01, *** p<0.001:

Depression, Neighborhood Characteristics and Stress

Bivariate analyses show that neighborhood disorder (Adj R2 0.07, F (1, 65) = 6.16, p-

value < 0.05), neighborhood stress (Adj. R2 0. 14, F (1, 65) = 11.42, p-value < 0.01) and

neighborhood social cohesion (Adj. R2 0.04, F (1, 65) = 4.04, p-value < 0.05) have mild

effects on depression scores in this group of women. See table 4-10.

Individual factors such as perceived stress (Adj. R2 0.26, F (1,65) = 24.42, p-value <

0.001), chronic stress (Adj. R2 0.39, F (1,65) = 43.32, p-value < 0.001), unfair treatment

(Adj. R2 0. 14, F (1,65) = 11.92, p-value < 0.01), and individual social support (Adj. R2

0.26, F (1,65) = 24.27, p-value < 0.001) also significantly impact depression.

Due to the small sample size and the large number of variables, significant neighborhood

and individual level variables in Table 4-11 were put into separate multiple regression










models. Variables that continued to have a statistically significant effect on depression

were put in the final model. Table 4-11 illustrates the first model and shows which

neighborhood variables remain significant predictors of depression. When all neighborhood

level variables were added to the model, only neighborhood stress remained significant

(Adj. R2 0. 13. F (3. 63) = 4.3 8, p -value < 0.01). Therefore, neighborhood stress was placed

in the final model.

Table 4-10: Neighborhood, Psychosocial, and Individual Effects on Depression (CES-D)
Variable B SE Adj. R2 F 95% CI
Neighborhood Characteristics


Neighborhood Economic -0.08
Disadvantage
Neighborhood Disorder 0.05*
Neighborhood Stress 0.04**
Neighborhood Social -0.05*
Cohesion
Individual
Perceived Stress (PSS) 0.1***
Chronic Stress (TCSI) 0.04***
Unfair Treatment 0.08**
Individual Social Support -0.03***
(ISEL)
Age -0.02
Marital Status 0.43
Number of children -0.20
Race 0.11
Education -0.18
Income -0.0007
Note n = 67 df (1, 65)
* p <0.05, ** p <0.01, *** p<0.001:


0.06 0.01

0.02 0.07
0.01 0.14
0.02 0.04

Level Factors
0.02 0.26
0.006 0.39
0.024 0.14
0.007 0.26

0.02 0.005
0.44 -0.001
0.14 0.015
0.24 -0.01
0.11 0.03
0.0004 0.04


1.89

6.16
11.42
4.04


24.42
43.32
11.92
24.27

0.69
0.94
2.00
0.23
2.90
3.41


-0.02 0.04

0.01 0.09
0.02 0.07
-0.1 --0.0003


0.06 0. 14
0.03 0.05
0.03 0. 13
-0.05 --0.02

-0.05 0.02
-0.46 1.31
-0.47 0.08
-0.36 0.58
-0.40 0.03
-0.002 000


The second model consists of significant individual level factors from Table 4-10

above. As shown in Table 4-11, only perceived and chronic stress (Adj. R2 0.47. F (4. 62) =

15.85, p -value < 0.01) continue to be significant predictors accounting for almost 50% of

the variation in depression. In the final model neighborhood stress no longer has a

significant effect on depression. For this sample of women, perceived and chronic stressors










(Adj. R2 0.45, F (3. 63) = 18.85, p -value < 0.001) are more important predictors of

depression than neighborhood disorder and exposure to crime.

Table 4-11: Regression Results for Neighborhood and Psychosocial Measures as Predictors
of Depression
Variable B SE 95% CI
Model 1 Neighborhood Level Factors
n = 67, F (3, 63) = 4.3 8; Adj. R2 0. 13** '
Neighborhood Disorder 0.006 0.25 [-0.45 0.06]
Neighborhood Stress 0.45* 0.19 [ 0.07 0.83]
Neighborhood Social Cohesion -0.03 0.03 [-0.09 0.02]
Model 2 -Individual Level Factors
n = 67, F (4, 62) = 15.85; Adj. R2 0.47**
Perceived Stress (PSS) 0.05* 0.02 [0.01 0.09]
Chronic Stress (TCSI) 0.02** 0.007 [0.008 0.04]
Unfair Treatment 0.25 0.02 [-0.02 0.07]
Individual Social Support (ISEL) -0.01 0.007 [-0.02 0.003]
Final Model Combined
n = 67, F (3, 63) = 18.85; Adj. R2 0.45**
Neighborhood Stress 0.01 0.15 [-0.29 0.31]
Perceived Stress (PSS) 0.06** 0.02 [0.02, 0.09]
Chronic Stress (TCSI) 0.03*** 0.007 [0.02, 0.04]
* p <0.05, ** p <0.01, *** p<0.001:


Seemingly Unrelated Regression Analysis of Anxiety and Depression Regression
Equations

The correlation matrix of residuals for anxiety and depression was 0.52. Breusch-

Pagan test of independence revealed that the residuals from the two equations above are not

independent (Chi Square 18.24, p-value < 0.001). Table 4-12 shows seemingly unrelated

regression results for anxiety and depression regression models. Again, with individual

level factors added to the model, neighborhood stress is no longer a predictor of anxiety or

depression. Both perceived stress and chronic stress remain significant predictors of

depression and anxiety. Social support is also a significant predictor of anxiety with lower

levels of social support associated with higher levels of anxiety.









Possible confounding variables included weight, smoking, hours of sleep, and presence of

an acute stressor, and menstrual cycle phase. None of these factors were significantly

associated with SC-AUCg. The only individual level factors associated with SC-AUCg

were unfair treatment (Adj. R2 0. 13, F (1. 65) = 11.26, p value < 0.01) and weight (Adj.

R2 0.04, F (1. 65) = 4.05, p -value < 0.05).

Table 4-12 Seemingly Unrelated Regression Analysis of Anxiety and Depression
Equations
Equation Obs. Arms. RMSE R2 Chi2
CESD 67 3 0.95 0.47 60.12 0.000
State Anxiety 67 4 8.22 0.52 71.32 0.000
B SE Z p-value 95% CI
Depression Equation
Neighborhood Stress 0.002 0.14 0.08 0.94 [-0.27 0.30]
Perceived Stress 0.06 0.02 2.98 0.003 [0.02, 0.09]
Chronic Stress 0.03 0.007 4.49 0.000 [0.17 ,0.044]
Anxiety Equation
Neighborhood Stress 0.0005 1.25 -0.10 0.92 [-2.59 ,2.34]
Perceived Stress 0.62 0.17 3.64 0.000 [0.28 ,0.95]
Chronic Stress 0.13 0.06 2.21 0.03 [-0.26 ,-0.06]
Social Support -0.16 0.05 -3.08 0.002 [-0.26 -0.06]


When these variables were added to a multiple regression model both remained

significant predictors of salivary cortisol (Adj. R2 0.21, F (2. 62) = 9.32, p -value < 0.001)

and accounted for 20% of the variability in mean salivary cortisol over the day. See table 4-

14. Contrary to the hypothesis that unfair treatment (stress) would be positively associated

with SC-AUCg, for each 0.04 point increase in unfair treatment SC-AUCg decreased by

one unit (ug/dl).

Given the limitations regarding the lack of sensitivity of SC-AUCg to differences in

individual cortisol levels over time and the correlation of repeated salivary cortisol

measures within each person as discussed in chapter 3, general estimating equations (GEE)










were also used to examine the relationships among neighborhood characteristics, stress,

psychological distress and salivary cortisol.

Table 4-13: Simple Regression SC-AUCg
Variable B SE Adj. R2 F 95% CI


Neighborhood Characteristics
0.02 0.03 -0.01


Neighborhood Economic
Disadvantage
Neighborhood Disorder
Neighborhood Stress
Neighborhood Social
Cohesion

Unfair Treatment
Perceived Stress
Chronic Stress
Individual Social Support
Depression
Anxiety
Weight
Birth Control
Menstrual Cycle Phase
Smoking
Sleep Hrs
Day 1
Day 2
Acute Stressor


0.29 -0.05 0.08


-0.003
-0.006
0.01


0.01
0.007
0.01


-0.014
-0.003
0.003


0.09
0.82
1.21



11.26
3.48
0.35
1.01
2.06
2.80
9.32
0.44
0.54
0.41


-0.02 -
-0.02 -
-0.01

-0-

-0.06 -
-0.04
-0.01
-0.004
-0.02 -

-0.01 -
-3.65 -
-0.33 -
-0.57 -


0.018
0.01
0.05


Individual Characteristics


-0.04**
-0.022
-0.002
0.004
-0.01
-0.011
-0.004*
0.18
-0.09
-0.14


0.012
0.12
0.004
0.004
0.007
0.007
0.002
0.27
0.12
0.22


0.13
0.04
-0.010
0.0002
0.016
0.027
0.04
-0.009
-0.007
-0.01


-0.02
0.002
0.005
- 0.01
0.004
0.002
-0.00003
0.73
0.15
0.29


-0.17 0.04 -0.01 0.19 -0.09 0.06
0.04 0.05 -0.003 0.76 -0.5 0.13


Day 1
Day 2
Age
* p <0.05,


-0.06 0.19
0.19 0.25
0.008 0.01
*** p<0.001; df 1, 65


-0.01
-0.006
0.01


0.11
0.59
0.75


-0.43
-0.31
-0.01


0.31
0.70
0.03


** p <0.01,


Table 4-14: Multiple Regression of Individual Level Characteristics on SC-AUCg
Variable B SE 95% CI
Unfair Treatment -0.045*** 0.01 -0.07 -0.02
Weight -0.004* 0.002 -0.007 -0.0008
Note: n =65 F(2, 62) =9.32 Adj. R2 0.21***
* p <0.05, ** p <0.01, *** p<0.001:


As stated in chapter 3, in addition to using standard regression, GEE was used to

examine the relationship between neighborhood characteristics, stress, and psychological










distress and repeated measures of salivary cortisol. Using GEE methodology, neighborhood

characteristics do not have an effect on salivary cortisol. In this sample of women,

perceived stress and unfair treatment are negatively associated with salivary cortisol. As

seen in the final model, the GEE approach yields more conservative results compared to

standard multiple regression using AUCg. For each unit change in unfair treatment and

perceived stress salivary cortisol decreases by 0.02 and 0.03 units respectively, after

controlling for other potentially confounding psychosocial and physiological stressors (p

<0.05). See table 4-15.

Table 4-15: GEE Population Averaged Model of Effects of Neighborhood Characteristics,
Stress and Psychological Distress on Salivary Cortisol
Variable B SE p 95% CI
Neighborhood Characteristics Multiple Regression
Number of observations 804; number of groups 67; Wald Chi2 7. 02; p = 0. 22
Neighborhood Economic Disadvantage -0.007 0.03 0.80 -0.066 0.50
Neighborhood Disorder 0.09 0.01 0.47 -0.016 0.03
Neighborhood Stress -0.01 0.008 0.18 -0.025 0.005
Neighborhood Social Cohesion 0.007 0.02 0.77 -0.040 0.053
Individual Level Characteristics Multiple Regression
Number of observations = 804; number of groups = 67; Wald Chi2 1 6.42; p = 0. 02
Unfair Treatment -0.031 0.013 0.02 -0.06 0.005
Perceived Stress -0.29 0.013 0.04 -0.05 0.002
Chronic Stress 0.005 0.005 0.27 -0.004 0.014
Individual Social Support 0.0001 0.005 0.98 -0.009 0.009
Depression 0.009 0.010 0.41 -0.012 -0.009
Anxiety -0.007 0.011 0.53 -0.027 0.014
Final Model Controlling for Individual SES, physiological factors and health behaviors
Number of observations 768; number of groups = 64; Wald Chi2 1 9. 73; p 0. 01
Unfair Treatment -0.02 0.012 0.03 -0.05 -0.002
Perceived Stress -0.025 0.011 0.02 -0.05 -0.003
Monthly Income -0.0001 0.0002 0.64 -0.0004 0.0003
Weight -0.003 0.002 0.07 -0.006 0.0003
Menstrual Cycle Phase 0.06 0.11 0.60 -0.16 0.27
Smoking Packs per day -0.14 0.19 0.47 -0.52 0.24
Number of Children in household -0.029 0.063 0.65 -0.15 0.09









Specific Aim 2: Differences in Neighborhood Characteristics by Housing Subsidy
Type

The second aim of this study was to determine the differences in neighborhood

characteristics of two subsidized housing types, specifically section 8 and public housing,

in which low SEP female heads of households with children live. It was proposed that

public housing sites would have significantly more neighborhood disorder, greater levels of

neighborhood disadvantage, higher levels of neighborhood stress, higher reports of crime

exposure, and lower levels of neighborhood social cohesion than section 8 housing sites.

Group comparison T-test and Mann-Whitney U-test were used to test whether

neighborhoods differed by housing subsidy type.

Eighty percent of the women living in public housing lived in the most economically

disadvantaged neighborhoods, while a little over one half of those living in section 8

housing lived in the poorest areas. Figure 4.2 illustrates the differences in neighborhood

economic disadvantage by housing subsidy type.

As shown in table 3-1, skewness and kurtosis tests for normality showed that NED is

significantly skewed to the left. Therefore, the Mann-Whitney Utest was used to test

whether there were differences in NED by housing subsidy type. The hypotheses were

partially supported. Women living in section 8 housing units were located in more

economically advantaged areas (z = -2.552, p<0.05) (table not shown). No differences in

neighborhood disorder, exposure to crime, or collective efficacy by housing type were

found in this sample of women.

Specific Aim 3: Differences in Stress, Psychological Distress, Health and Salivary
Cortisol by Housing Type

The final aim of this study was to examine the differences in housing satisfaction,

perceived stress, psychological distress, and salivary cortisol levels, in low SEP female

















































10 15 0
NED


I II I


heads of households with children by housing type. It was purported that women living in


public housing would experience significantly lower levels of housing satisfaction, have


higher levels of perceived stress, psychological distress, and greater alterations in salivary


cortisol secretion than women living in section 8 housing.


Section 8


Public Housing


83 33


Percn
50-








2 3262 326

0 5

Graphs by SQ_S8PH


51 16


8 333


4 167


Figure 4.2: Neighborhood Economic Disadvantage (NED) by Housing Subsidy Type



The outcome variables were housing satisfaction, perceived stress, chronic stress,


state anxiety, depression and SC-AUCg. Housing satisfaction is an ordinal variable;


therefore the Mann-Whitney test was used to examine differences in housing satisfaction


by housing type. T-tests were used for all other variables. There were no differences in any


of the outcome variables by housing subsidy type. The hypotheses for this specific aim


were not supported.









The hypotheses for specific aims one and two were partially supported. Study

results did not support specific aim three. The women in this study have higher rates of

state anxiety and depression, and lower levels of general health compared to national norms

for the same age group. Neighborhood disorder and crime exposure were mildly to

moderately associated with increased levels of perceived stress, unfair treatment, chronic

stress, depression and anxiety. However, the neighborhood effects on depression and

anxiety became statistically insignificant when perceived stress, unfair treatment, chronic

stress and other individual level covariates were added to the model. The following chapter

provides a detailed discussion on the study results, discusses the limitations of the study

and implications for public health nursing research and practice.















CHAPTER 5
DISCUSSION AND RECOMMENDATIONS

This chapter presents maj or study findings, addresses study limitations and

discusses implications for public health nursing research and practice. First, findings

regarding sample characteristics are discussed. Then maj or Eindings for each specific aim

and associated hypotheses are presented. Next study limitations are acknowledged.

Finally, implications for public health nursing research and practice are discussed.

Major Findings

This study is unique in its design and attempts to examine the associations among

housing type, neighborhood characteristics, stress, psychological distress, health, and the

hypothalamic-pituitary-adrenal axis (HPA axis), specifically salivary cortisol. Salivary

cortisol samples were collected for two days in women living in section 8 or public

housing while in their natural setting going about their daily routine. To date only one

study has examined neighborhood characteristics (neighborhood socioeconomic status) in

relation to the HPA axis, specifically cortisol levels; however, that study examined

cortisol as a response to an acute stressor, as opposed to basal levels in relation to chronic

stress exposures. Kapuku, Trieber and Davis (2002) colleagues examined the association

between neighborhood socioeconomic status (SES), cardiovascular function, and plasma

cortisol in response to laboratory-induced stress in a sample of 24 black males 16 to 25

years old. They found that family SES was related to baseline serum cortisol level (partial

r = .46, p<.05), but the correlation between neighborhood SES was not statistically

significant (Kapuku, Treiber, and Davis, 2002). Other studies have examined individual-