<%BANNER%>

Divergent pathways: an analysis of racial differences in risk of retirement and work disability among African American a...

University of Florida Institutional Repository

PAGE 1

DIVERGENT PATHWAYS: AN ANALYSIS OF RACIAL DIFFERENCES IN RISK OF RETIREMENT AND WORK DISA BILITY AMONG AFRICAN AMERICAN AND WHITE WOMEN IN THE LABOR FORCE IN LATER MIDDLE-LIFE By TYSON H. BROWN A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS UNIVERSITY OF FLORIDA 2003

PAGE 2

Copyright 2003 by Tyson H. Brown

PAGE 3

ACKNOWLEDGMENTS I am especially thankful for my chair, Amy Pienta, for her endless support and expert guidance throughout my graduate training at the University of Florida. Many thanks go to my cochair, Chuck Peek, for his helpespecially in the early stages of my training. I am also very grateful for contributions from the other members of my committee, Tanya Koropeckyj-Cox and Bhramar Mukherjee. I also would like to acknowledge John Henretta, and express my gratitude for his helpful comments. These remarks would be incomplete without giving special thanks to Terry Mills for his consistent support during my undergraduate and graduate education at the University of Florida. iii

PAGE 4

TABLE OF CONTENTS page ACKNOWLEDGMENTS.................................................................................................iii LIST OF TABLES.............................................................................................................vi CHAPTER 1 INTRODUCTION........................................................................................................1 2 BACKGROUND..........................................................................................................3 Life Course Framework and Retirement Behavior.......................................................3 Race and Retirement Among Men...............................................................................3 Race, Health, and Disability.........................................................................................4 Race, Wealth, and Retirement Behavior.......................................................................5 Race, Family Characteristics, and Retirement Behavior..............................................6 Race, Work Characteristics, and Retirement Behavior................................................6 Race, Education, and Retirement Behavior..................................................................7 Research Hypotheses....................................................................................................7 3 RESEARCH DESIGN AND METHODS....................................................................9 Measurement of Labor Force Behavior........................................................................9 Measurement of Sociodemographic Characteristics..................................................10 Measurement of Health...............................................................................................11 Measurement of Family Circumstances.....................................................................11 Measurement of Midlife Work Characteristics..........................................................12 Measurement of Midlife Economic Well-Being........................................................13 Analytic Strategy........................................................................................................14 4 RESULTS...................................................................................................................15 Nested model strategy.................................................................................................18 Retirement behavior among African American and White women...........................19 Work disability among African American and White women...................................23 iv

PAGE 5

5 DISCUSSION.............................................................................................................28 LIST OF REFERENCES...................................................................................................34 BIOGRAPHICAL SKETCH.............................................................................................37 v

PAGE 6

LIST OF TABLES Table page 1. Descriptive Charcteristics of Women in the Labor Force at Baseline by Race.......16 2. Baseline Labor Force Status by Race.......................................................................17 3. Measures of Physical and Self-Rated Health by Baseline Labor Force Status........18 4. Risk Ratios from Proportional Hazard Models of Retirement.................................20 5. Risk Ratios from Proportional Hazard Models of Work Disability.........................24 vi

PAGE 7

Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Require m ents for the Degree of Ma s ter of Arts DIVERGENT PATHWAYS: AN ANALYSIS OF RACIAL DIFFERENCES IN RISK OF RETIREMENT AND WORK DISA BILITY AMONG AFRICAN AMERICAN AND WHITE WOMEN IN THE LABOR FORCE IN LATER MIDDLE-LIFE By Tyson H. Brown August 2003 Chair: Amy M. Pienta Cochair: Charles W. Peek Major Department: Sociology The purpose of the present is to explore the labor force exit patterns of African American and White women. Inattention has been give to racial disparities in the labor force exit behavior of African American a nd White women. Previous research on racial disparities in retirement behavior among men indicates that, compared to White men, African American men are more likely to exit the labor force via retirement or work disability. The present study uses five waves of panel data from the Health and Retirement study and the life course perspective to explore racial disparities in labor force exit behavior among women. Analyses suggest that African American women are disadvantaged relative to White women with respect to socioeconomic circumstances, family patterns, wealth, and health. Importantly, results from multivariate event history models indicate that, compared to White women, African American women are less likely to exit the labor force via retirement and are more likely to exit the labor force via vii

PAGE 8

work disability as a result of their lower levels of human capital, wealth, and health. Theoretical implications of the present study and policy relevance are also discussed. viii

PAGE 9

CHAPTER 1 INTRODUCTION The literature has shown evidence of race differences in retirement behavior. However, most of the research has overlooked women, with only a few exceptions. Researchers have found that African American women have more continuous patterns of work throughout the life course than White women (Belgrave, 1988), a finding opposite that found among men, which suggests that the race-retirement relationship may also vary by gender. This also underscores the need for further research on race differences in womens labor force exit pathways. The few studies that have explored race differences in womens retirement have used different cohorts and measurement strategies and have shown mixed results. For instance, Belgraves (1988) study of women born between 1917 and 1921, used cross-sectional data and labor force participation rates (LFPRs) to demonstrate that African American women have more continuous patterns of labor force participation throughout the life course. Pienta, Burr, and Mutchlers (1994) cross-sectional analysis of the 1920 to 1929 birth cohort, on the other hand, operationalized womens labor force participation as full-time work, part-time work, or not working. They found no significant race differences in womens labor force statuses. Although LFPRs have been the basis for much of the previous retirement research, LFPRs have masked important race differences that are revealed by further classifying individuals who have exited the labor force into disabled and nondisabled groups (Hayward, Friedman, and Chen, 1996). Distinguishing between retirees and the work disabled rather than relying solely on labor force participation rates may provide 1

PAGE 10

2 additional insight into the race-retirement relationship among women and thus imply different policy targets. Further, Hayward and colleagues (1996: S9) conclusion based on mens data that Retirement is more of a White experience than a Black experience, while the reverse is true with regard to disability (among men), underscore the importance of examining whether their findings hold true for women. The present study explores racial differences in womens labor force exit patterns, using retirement, work disability, attrition, and death as competing outcomes, with attention to the intervening effects of sociodemographic characteristics, work and family histories, health, and wealth. The present study aims to address two primary research questions: 1. Do African American and White women have different rates of retirement and work disability in late midlife? 2. Do racial differences in womens labor force exit behavior stem from racial differences in human capital, health, and work histories? Racial differences in education, economic resources, family patterns, and health over the life course are expected to contribute to divergent labor force exit pathways. Given African American womens higher labor market attachment throughout the life course (Belgrave, 1988; Brown and Pienta, 2002), lower rates of marriage, and fewer economic resources, relative to White women, African American women may be less likely to report exiting the labor force for retirement. Conversely, work disability rates may be higher among African American women, stemming from racial disparities in education and health.

PAGE 11

CHAPTER 2 BACKGROUND Life Course Framework and Retirement Behavior Much of the previous research on retirement has been based on the retirement behavior of White men. However, retirement models based on the retirement of White men may be inadequate for explaining the retirement behavior of women, ethnic minorities, and the chronically poor or ill (Burr, Massagli, Mutchler and Pienta, 1996; Gibson, 1987; Pienta, Burr and Mutchler, 1994). Historically, these populations have been disadvantaged in terms of education, career mobility, income, wealth, and health. Given well-documented race differences in education, health, wealth, work and family histories, a cumulative disadvantage framework may be useful for devising a model of race and labor force exit patterns among women. The cumulative disadvantage framework is an extension of the life course perspective that assets that social inequalities in later life are a result of the interaction of institutional arrangements and aggregated individual actions over time (Dannefer, 1991; ORand, 1996). Conceptually, the present study explores the possibility that race differences in labor force exit behavior may be a consequence of African American womens greater lifelong disadvantage with respect to education, work and family characteristics, wealth, and health. Race and Retirement Among Men Given the sparse research on womens retirement and race, much of our understanding of race differences in retirement come from studies of men. African American men have more discontinuous patterns of work history than White men 3

PAGE 12

4 throughout the life course (Welch, 1990). Older African American men are more likely than White men to be outside of the labor force (Bound, Schoenbaum, and Waidmann, 1995; Hayward et al., 1996). Also, African American men are more likely to delay entry into the labor force, more likely to have gaps in employment histories, and more likely to permanently withdraw from the labor force. Disability is a major contributor to older African American mens lower labor force participation rates (Hayward et al., 1996). Wray (1996) found that in addition to health, job characteristics such as pension coverage, retiree health insurance, and spousal retirement benefits were partially responsible for African Americans higher rates of disability. While there may be multiple plausible causes for racial differences in disability status (see Gibson, 1991; Parsons, 1980; Welch, 1990; Wilson, 1987), several studies have shown that health is a dominant and temporally proximate factor accounting for African American mens lower levels of labor force participation (Bound et al., 1995; Burr, Massagli, Mutchler, and Pienta, 1996; Hayward et al., 1996). Although previous research indicates that LFPRs may be more similar among African American and White women than they are among their male counterparts, African American womens poorer health, relative to White women, may place them at a greater risk of becoming work disabled. Race, Health, and Disability Health conditions are likely to provide additional insight into differences in the retirement behavior of women. African American women have poorer physical and self-rated health than White women. More specifically, compared to White women, African American women have a higher prevalence of diabetes, hypertension, heart disease, strokes, and functional loss (Blackwell, Collins, and Coles, 2002). A similar pattern emerges with respect to self-rated health, whereas 19% of White women between the

PAGE 13

5 ages of 45 and 74 rate their health as either fair or poor, 35% of their African American counterparts do so (National Academy on an Aging Society, 1999). Given African American womens poorer health, and the finding that men with poorer health are more likely to be work disabled (Bound et al., 1995; Hayward, Friedman, and Chen, 1996), African American women may face a higher risk of work disability than White women. On the other hand, Pienta and Browns (2001) study indicates that, for various reasons, health may have less of an impact on womens labor force participation than mens. An investigation of temporal antecedents of health disparities may provide a more complete understanding of the race-retirement relationship among women Race, Wealth, and Retirement Behavior Transitions into the retired status are also expected to vary by race and current socioeconomic position. Temporally proximate factors such as wealth are likely to intervene in the race-retirement behavior relationship. Previous research indicates that women with greater net worth are more likely to retire versus continue working (Brown and Pienta, 2002). Racial differences in wealth are great. While the median household net worth among Whites in 1990 was $44,408, African Americans median household net worth was $ 4,604 (Eller, 1994). Even more striking is the fact that the racial gap in wealth is widest at lower levels of income. Among individuals in the lowest quintile of income in the U.S., the net worth of whites is 10,000 times higher that that of blacks ($10,257 vs. $1) (Eller, 1994). Race differences in home ownership and home value contribute substantially to racial disparities in the distribution of wealth (Quadagno and Reid, 1996). In 1994, whereas 64% of Whites owned their homes, only 43.4% of African Americans owned their homes (U.S. Bureau of Census, 1996). And, whereas the average home equity value for Whites was $78,708 in 1992, African Americans average home

PAGE 14

6 equity value was $36,658 (Angel and Angel, 1996). These findings suggest that African American women may be forced either to remain in the labor force to maintain a continuing source of income, or to delay retirement in order to accumulate wealth for later consumption during the retirement years. Race, Family Characteristics, and Retirement Behavior Race differences in family circumstances are also expected to contribute to racial disparities in retirement. African American women are less likely than White women to be married, and among married women, African American women are less likely to have a retired spouse (Brown and Pienta, 2002). Thus, given that unmarried women and women with a spouse in the labor force a re less likely to be retired than married women with a retired spouse (Henretta and ORand, 1983; Henretta, ORand and Chan, 1993a; Henretta, ORand and Chan, 1993b), African American women should retire later. Earlier family circumstances also impact retirement behavior (Brown and Pienta, 2002). Family roles in early adulthood constitute initial pathways in the family life course that constrain later work-related roles (ORand, Henretta, and Krecker, 1992). Compared to White women of the 1931-1941 birth cohort, their African American counterparts are much more likely to have experienced either a non-marital first birth or post-marital single motherhood (Brown and Pienta, 2002). Therefore, we attended to the role of racial differences in early family histories in contributing to racial differences in work and family circumstances and ultimately retirement behavior of African American and White women. Race, Work Characteristics, and Retirement Behavior African American womens work histories may mediate the effects of their disadvantaged familial and economic circumstances on retirement. Compared to White

PAGE 15

7 women, African American women actually have more continuous patterns of labor force participation throughout the life course (Belgrave, 1988; Brown and Pienta, 2002). Moreover, African American women have comparable rates of pension coverage and pension wealth (Brown and Pienta, 2002). Among women workers, African Americans are more likely than Whites to be blue collar workers (Belgrave, 1988), who are more likely than white collar workers to retire (Brown and Pienta, 2002). Generally, African American womens work histories and the expected push and pull effects associated with such work circumstances indicate that African American women may be more likely than White women to retire. Thus, work characteristics may suppress racial disparities in retirement. Race, Education, and Retirement Behavior While the above text has focused on temporally proximate predictors of retirement behavior, the present studys cumulative disadvantage, life course framework points toward the utility of exploring the role of temporally distal life course conditions as determinants of more proximate circumstances and retirement behavior. Consequently, this study explored whether racial disparities in education may underlie racial disparities in health, and subsequent labor force exit pathways. Research Hypotheses The life course perspective and the literature related to racial disparities in retirement have been instrumental in developing several research hypotheses regarding the labor force patterns of African American and White women in the labor force in 1992: 1. Poorer health may be associated with higher risks of exiting the labor force via work disability

PAGE 16

8 2. African Americans may have higher risks of reporting an exit from the labor force via work disability as a result of their poorer health 3. African Americans may be less likely to report exiting the labor force via retirement as a consequence of their greater lifelong disadvantage in terms of education, family patterns, and economic resources.

PAGE 17

CHAPTER 3 RESEARCH DESIGN AND METHODS Data from waves 1 through 5 (1992 through 2000) of the Health and Retirement Study (HRS) are employed to investigate race differences in womens retirement. The HRS is a nationally representative panel study of Americans between the ages 51-61 in 1992, with oversamples of African Americans, Latinos and Floridians. Data were collected every two years via face-to-face (1992, and 1998) and telephone interviews (1994, 1996, and 2000), with response rates between 80 and 90 percent. The HRS is an ideal source for investigating retirement behavior because it has extensive measures of known correlates of retirement behavior such as sociodemographic factors, work and family histories, and measures of health and wealth. Initial analyses are restricted to African American (n=1018) and White (n=4134) women between the ages of 51-61 in 1992. Since the primary focus of this study is on labor force exit behavior, subsequent analyses are further restricted to women who are in the labor force at the beginning of each interval. Measurement of Labor Force Behavior At each wave respondents were asked the question: Are you working now, temporarily laid off, unemployed and looking for work, disabled and unable to work, retired, a homemaker, or what? Since the primary focus of this study is on labor force exits, women in the labor force are included in analyses until they experience either (1) retirement (ceasing work for pay and not work disabled or unemployed or laid-off), or (2) work disablement (ceasing work for pay as a result of a disability). The present study 9

PAGE 18

10 uses event history analysis, based on a total of 11,483 exposure intervals. Overall, there are 3,301 events, of which 2,762 are retirements, and 539 are exits due to a disability. Additional competing outcomes such as death and loss-to-follow-up where explored, but are not presented in this study. Retirement is becoming an increasingly ambiguous concept. Consequently, the retired and working states are not exact. Although the majority of the retired group self-identifies as retired, a relatively small proportion of the retired group includes respondents who stopped working and self-identified as a homemaker or other. Further, the working group includes women who recently ceased working for pay, yet self-identify as either temporarily laid off or actively looking for work. While these states are loosely defined, they capture important race differences in labor force exit behavior that are masked by relying solely on LFPRs (see Hayward et al., 1996). And although respondents may reenter the labor force after reporting an exit via retirement or work disability, most do not, and this initial exit is a definite disruption in the respondents work history that marks the beginning of the process leading to a permanent exit from the labor force (Hayward et al., 1996). Measurement of Sociodemographic Characteristics Race is a key analytic variable and is measured as a dummy variable (1= African American; 0= White). Older women are more likely to be outside of the labor force instead of being full-time workers (Pienta et al., 1994) and are more likely to stop working as a result of a work disability (Daly and Bound, 1996). Age (measured in years) at baseline is included in the multivariate analysis as a control variable to account for this age effect. A time-varying measure of age is also included in the hazard models in order to approximate aging over time. Respondents educational attainment (measured in years

PAGE 19

11 of formal education) is also included as a control variable because it is likely to influence an array of factors such as occupation, income, wealth, health (House and Williams, 2000), and subsequent labor force transitions. Measurement of Health Measures of physical health such as hypertension, stroke, heart disease, diabetes, chronic lung disease, psychological problems, arthritis, and cancer are included in the analyses. First, these were coded as dummy variables according to how the respondent answered the question, Has a doctor ever told you that you have (had a) [condition]. A summary measure of the total number of the above conditions ever diagnosed is included in the analyses. A measure of the respondents self-rated health is also included (1=excellent, 2=very good, 3=good, 4=fair, 5=poor Measurement of Family Circumstances Both present family circumstance and earlier social roles impact labor force behavior in later life (ORand et al., 1992). Previous research has shown that single parenthood experiences affect womens retirement behavior (Brown and Pienta, 2002). Women typically enter single parenthood via one of two pathways. First, women may become single mothers as a result of a nonmarital first birth (1= nonmarital first birth; 0= otherwise). Second, when women with children divorce or become widowed we measure post marital single parenthood (1= post marital single parent; 0= otherwise). Given single mothers relatively precarious economic circumstances, older women who have experienced single parenthood may need to continue working in order to amass sufficient savings for retirement. Further, racial disparities in rates of single parenthood may play a role in the race-retirement relationship.

PAGE 20

12 Current marital status is central to understanding labor force behavior, especially in later life. Unmarried women are economically disadvantaged compared to married women and thus may delay retirement in order to accumulate wealth for later consumption during the retirement years. Also, among married women, it is important to differentiate between women with spouses in the labor force and women with spouses not in the labor force because spouses tend to exit the labor force at around the same time as one another (Henretta and ORand, 1983; Henretta, ORand and Chan, 1993). Thus, 3 dummy variables are included to capture current marital status: (1) not married (divorced, widowed, and never married), (2) Married and spouse is in the labor force, and (3) Married and spouse is not in the labor force. Dependent children are also likely to impact labor force participation (Pienta et al., 1994) because children tend to place economic burdens on the household and thus women with a child under 21 may work longer in order to accrue sufficient savings for retirement and money needed to continue supporting a dependent child. Number of household residents may also influence household economic resources and labor force exit behavior. Measurement of Midlife Work Characteristics Wages 2 (average salary and or commission per week) are likely to influence labor force exit decisions. Workers with high wages may be less inclined to sacrifice the opportunity cost of forgoing a steady stream of income for retirement. As a proxy for labor market attachment, womens baseline self-report of their average number of hours worked per week and total years ever worked are included. Women with greater work hours and years worked over the life course may continue to have a stronger labor market attachment into later midlife. On the other hand, women with substantial labor force experience over the life course may have greater economic resources to draw on for

PAGE 21

13 retirement. Occupations stratify the labor force by allocating different resources, benefits and opportunities to workers. To account for this effect, occupations are divided into white collar, blue collar and service types of occupations. Further, a measure of the baseline jobs physical demands (1=all/almost of the time; 2=most of the time; 3=some of the time; 4=none/almost none of the time) is included because when comparing work and non-work alternatives, older workers may view high levels of physical demands as a hurdle to labor force participation, making non-work alternatives more attractive. Self-employment differs from employment in organizations in many respects (Carr, 1996), which are likely to lead to disparate labor force participation rates. Other work-related factors that are likely to influence labor force behaviors of retirementaged workers include: pension eligibility status (currently receiving or eligible to receive benefits; has pension coverage, but is not currently eligible; and no pension coverage), private pension wealth, and health insurance coverage. Self-reported pension wealth (measured as present value as of the interview year) is a summary of promised or received employer-provided pension benefits from as many as three current or prior jobs. Health insurance status is measured as: being uninsured; having employer-provided health insurance through ones own employer or a spouses employer; and having health insurance from another source (i.e. private health insurance, or government provided health insurance). Measurement of Midlife Economic Well-Being An individuals income and assets are key indicators of economic well-being. Much like the expected wage effect, we speculate that higher levels of household income provide incentives that are likely to encourage one to remain in the labor force. While income is expected to be inversely related to likelihood of retiring, a households total non-housing assets and net value of primary residence are likely to be positively

PAGE 22

14 associated with retirement. Individuals from households with lower levels of net worth are expected to be more likely than those with more economic wherewithal to remain in the labor force. The distributions of pension wealth, household income, total non-housing assets, net value of primary residence and net worth are skewed, therefore, these variables are transformed by the natural logarithm in the multivariate models 1 Analytic Strategy Descriptive statistics are presented for White and African American women (Table 1). Racial differences in descriptive characteristics are calculated using t-test (continuous variables) and chi-square (categorical variables) statistics. Baseline labor force status percentages are presented for (1) the full sample, and (2) by race (Table 2). Next, health profiles of women by baseline labor force status are presented in Table 3.Then, proportional hazard models of workers risk of becoming either retired (Table 4) or work disabled (Table 5) are estimated. A series of nested models are estimated in order to evaluate the direct and indirect effects of race and life course variables. Analysis of racial differences in attrition and death (not shown) indicated that among late middle-aged women in the labor force, African Americans have a higher risk of death than Whites, and similar rates of attrition. Analyses also check for the possibility of multicollinearity.

PAGE 23

CHAPTER 4 RESULTS Table 1 presents descriptive characteristics for a sample of African American and White women in the labor force in 1992 and reveals important racial differences in life course circumstances, which may affect labor force exit behavior. Compared to White women, African American women are disadvantaged in terms of educational attainment and health, more likely to have been a single parent, less likely to be married or have a spouse in the labor force, more likely to work in a blue collar job, more likely to be uninsured, and have less household income and non-housing assets. Table 2 indicates that, overall, 63.3% of women were in the labor force at baseline; 27.9% were retired; and 8.8% of women were work disabled. Importantly, African American and White women appear to have similar rates of labor force participation. However, further classification of women who have exited the labor force reveals several important racial differences. Whereas African American women are much more likely than White women to report being work disabled (17.4% vs. 3.7%, p< .01), they are less likely to be retired (18.2% vs. 30.2%, p< .01). 15

PAGE 24

16 Table 1. Descriptive Characteristics of Women in the Labor Force at Baseline by Race White African American (n=2515) (n=635) Sociodemographic and Health Measures Age (mean) 55.5 55.4 *** Education (mean) 12.6 12.0 *** Self-Reported Health Status (mean) 2.2 2.8 *** # of Diagnosed Conditions (mean) 1.0 1.2 *** Arthritis (%) 36.8 36.7 Psychological Problems (%) 6.6 5.8 High Blood Pressure (%) 27.4 51.2 *** Diabetes (%) 5.5 12.6 *** Cancer (%) 7 4.6 *** Lung Disease (%) 4.8 3.8 ** Heart Problems (%) 6.4 7.1 Stroke (%) 1.0 1.9 *** Family Circumstances Marital Status Married w/ spouse in Labor Force (%) 51.9 28.5 *** Married w/ spouse out of Labor Force (%) 16.3 13.4 *** Unmarried (%) 31.8 58.1 *** Kid in HH LT 21 yrs old 15.9 21.9 *** # HH Residents 2.4 2.8 *** Nonmarital First Birth (%) 8.6 25.7 *** Post Marriage Single Parenthood (%) 30.4 40.2 *** Job Characteristics and Work History Wage/ Week (mean) $441.20 $369.14 *** Work Hours/ Week (mean) 37.0 35.9 ** Pension Wealth (median) $ 33,747.00 $ 42,288.00 ** Years Employed Over Life Course (Mean) 26.2 27.3 **

PAGE 25

17 Table 1 (continued). White African American (n=2515) (n=635) Occupation (%) White collar 29.6 20.3 *** Blue collar 19.4 30.8 *** Service sector 51.0 48.9 Self employed (%) 14.6 7.3 *** Pension Status (%) Covered by a pension 47.1 47.1 Eligible for Pension 11.2 13.1 No pension 41.7 39.8 Health Insurance Status (%) Employer health insurance 75.9 71.7 *** Other health insurance 10.0 10.3 No health insurance 14.1 18.0 *** Economic Well Being Net Value of Primary Res. (median) $50,000.00 $22,000.00 *** Non-Housing Assets (Median) $46,580.00 $6,000.00 *** HH Income (median) $39,000.00 $24,000.00 *** *p<.10; **p<.05; ***p<.01. Note T-test (continuous variables) and chi-square (categorical variables) statistics are used to compare descriptive statistics across the two samples. Table 2. Baseline Labor Force Status by Race Labor Force Status Total Whites (%) African Americans (%) ILF 63.3 63.0 64.4 Work-Disabled *** 8.8 3.7 17.4 Retired *** 27.9 30.3 18.2 *p<.05; **p<.01; ***p<.001 Results presented in Table 3 indicate that health profiles of women vary by baseline labor force status. Women in the labor force have the best health (e.g. they have the

PAGE 26

18 lowest prevalence of hypertension, diabetes, cancer, lung disease, heart problems, strokes, arthritis and psychological problems, and they have the highest self-rated health), followed by retired women. As expected, women who report being work disabled have the poorest health profiles. Since analyses of labor force exits will draw solely upon women in the labor force at baseline, it is worth noting the presence of a healthy-worker selection bias. Table 3. Measures of Physical and Self-Rated Health by Baseline Labor Force Status ILF Retired Work-Disabled # of Diagnosed Conditions (mean) a***, b***, c*** 1.0 1.3 2.6 Self-Rated Health (mean) a***, b***, c*** 2.3 2.7 4.3 High Blood Pressure (%) a***, b***, c*** 29.6 35.8 51.4 Diabetes (%) a***, b***, c*** 6.2 9.8 21.5 Cancer (%) a*, b***, c*** 6.5 7.2 12.0 Lung Disease (%) a**, b***, c*** 4.6 5.2 20.6 Heart Problems (%) a***, b***, c*** 6.1 8.6 30.2 Stroke (%) a***, b***, c*** 1.1 1.8 9.6 Arthritis (%) a***, b***, c*** 36.4 42.0 70.5 Psychological Problems (%) a***, b***, c*** 6.3 11.7 38.7 *p<.10; **p<.05; ***p<.01 a Denotes statistically significant different mean values between individuals ILF and Retired b Denotes statistically significant different mean values between individuals ILF and Work Disabled c Denotes statistically significant different mean values between work-disabled and retired individuals Nested model strategy Tables 4 and 5 present results from the multivariate proportional hazard models of the impact of race on rates of retirement or exiting the labor force due to a disability, respectively. Both tables employ a nested model strategy in order to explore how life course factors may intervene in the race-labor force behavior relationship. Model 1

PAGE 27

19 includes measures of race and age at baseline. Model 2 adds covariates to estimate the effects of time and education. Model 3, the base model, adds measures of baseline health in order to estimate the effects of physical and subjective health on labor force exit behavior, and to explore whether health intervenes in the race-labor force behavior exit relationship. Model 4 adds measures of work characteristics to the base model in order to explore the impact of work variables on retirement and their role in the race-retirement relationship. Model 5 adds measures of prior single parenthood experiences to the base model in order to explore whether earlier family circumstances impact subsequent labor force behaviors and their role in the race-retirement relationship. Single parenting and current family circumstances are added to the base model in order to explore the direct effects of family characteristics, as well as the direct and indirect effects of earlier single parenting circumstances and race on labor force exit behavior (Model 6). Next, economic measures are added to the base model (Model 7). Model 8 is the fully specified model. Retirement behavior among African American and White women Risk ratios of retirement presented in Table 4 indicate that African American are less likely than White women to retire (Models 1-4). As hypothesized, familial and economic factors over the life course intervene in the race-retirement relationship. For instance, controlling for prior single parenting circumstances (Model 5) and current family circumstances (Model 6) eliminates racial disparities in retirement. Similarly, once measures of economic security are included in the model, African American and White women appear to have similar rates of retirement (Model 7). Analyses presented in Table 4 reveal a number of other important predictors of retirement behavior. Whereas older women, self-employed women, and women with greater pension wealth, non-housing assets, or net value of primary residence are more

PAGE 28

Table 4. Risk Ratios from Proportional Hazard Models of Retirement 20 MODEL 1 MODEL 2 MODEL 3 MODEL 4 MODEL 5 MODEL 6 MODEL 7 MODEL 8 VARIABLES African American .89** .88** .87** .86** .90 1.04 1.01 1.09 Age 1.16*** .99 .99 .95*** .98 .98* .98 .94*** Time 1.18*** 1.18*** 1.23*** 1.18*** 1.18*** 1.18*** 1.23*** Education 1.0 1.0 .98** 1.0 .99 .98** .97*** Health Measures Number of Diagnosed Conditions 1.02 1.03 1.03 1.03 1.03 1.04* Self-Rated Health 1.02 1.04 1.02 1.03 1.04* 1.06** WORK CHARACTERISTICS Wage / Week 1.0 1.0 Hours / Week .99*** .99*** Log of Pension Wealth 1.02*** 1.02*** Years Worked Over Life Course .99*** .99*** Occupation Blue collar 1.11 1.12 Service 1.01 1.0 White Collar d d Self employed 1.27*** 1.19** Pension Status

PAGE 29

Table 4 (continued). MODEL 1 MODEL 2 MODEL 3 MODEL 4 MODEL 5 MODEL 6 MODEL 7 MODEL 8 Covered by pension 1.11** 1.12** Eligible for pension 1.22*** 1.23*** No pension d d Health Insurance Coverage s d d Uninsured .91 .99 Other Health insurance 1.0 1.04 Employer-provided d d FAMILY CIRCUMSTANCES Post Marital Single Parenthood .80*** .92* .95 Non-marital 1st Birth .91 .87** .89 Current Marital Statu Unmarried .74*** .74*** Married (Spouse in Labor Force) 1.17*** 1.05 Married (Spouse Not in Labor Force) Child under 21 .91 .89* Number of HH Residents .93*** .93*** ECONOMIC WELL-BEING Log of HH Income 1.01 .98 Log of Non-housing Assets 1.04*** 1.03*** 21

PAGE 30

Table 4 (continued). MODEL 1 MODEL 2 MODEL 3 MODEL 4 MODEL 5 MODEL 6 MODEL 7 MODEL 8 Log of Net Value of Primary Residence 1.02*** 1.01** Intercept 9.830 10.640 10.88 10.37 10.46 10.22 10.93 9.85 Model X2 -6718.62 -6542.44 -6541.03 -4964.09 -6525.19 -6480.21 -6505.34 -4910.81 D.F. 2 4 6 13 8 12 9 26 *p<.10; **p<.05; ***p<.01. d Denotes reference group 22

PAGE 31

23 likely to retire, women with greater work hours per week, greater work tenure over the life course, greater number of household residents, and ever single mothers are less likely to retire. Women who are eligible to receive their pension are more likely than women without a pension to retire. Controlling for current marital status indicates that compared to married women with a spouse in the labor force, unmarried women are less likely to retire, and married women with a spouse in the labor force are more likely to retire. Also, part of the single parent effect is mediated by current marital status. Diagnostic measures do not indicate severe multicollinearity in the models of retirement. Work disability among African American and White women Table 5 presents the relative risk ratios of exiting the labor force as a result of a work disability. As hypothesized, African American women have a significantly higher risk than White women of reporting an exit from the labor force due to a disability (RR=2.03, p< .01) (Model 1). Controlling for educational attainment (Model 2), results in a modest reduction in African Americans excess risk (RR= 1.74, p< .01). Adding baseline measures of health (Model 3) reveals several important findings: (1) women with a greater number of health conditions and poorer self-rated health are more likely to report exiting the labor force due to disability, (2) African American womens excess risk or work disability is substantially reduced (RR= 1.74, p< .01 to RR=1.28, p< .05), and (3) educations effect size is somewhat reduced (RR= .84, p< .01 to RR= .90, p< .01)--indicating that educations effect on rates of work disablement partially operate via health measures. These findings lend support to the notion that African American womens excess risk of work disability is partially a function of their poorer health, as well as the idea that racial disparities in educational attainment, in part, underlie racial differences in both health and labor force exit behavior in later life.

PAGE 32

Table 5. Risk Ratios from Proportional Hazard Models of Work Disability 24 MODEL 1 MODEL 2 MODEL 3 MODEL 4 MODEL 5 MODEL 6 MODEL 7 MODEL 8 VARIABLES African American 2.03*** 1.74*** 1.28** 1.44*** 1.21 1.16 1.06 1.28* Age .97** .90*** .89*** .84*** .89*** .89*** .89*** .84*** Time 1.06*** 1.06*** 1.13*** 1.06*** 1.06*** 1.06*** 1.13*** Education .84*** .90*** .93*** .90*** .99** .93*** .94*** Health Measures Number of Diagnosed Conditions, W1 1.18*** 1.19*** 1.16*** 1.15*** 1.15*** 1.14*** Self-Rated Health, W1 1.85*** 1.86*** 1.83*** 1.82*** 1.77*** 1.80*** WORK CHARACTERISTICS Wage / Week 1.0 .99 Hours / Week 1.01* 1.01** Log of Pension Wealth .98 .99 Years Worked Over Life Course .98*** .98*** Occupation Blue collar 1.08 1.10 Service .99 .99 White Collar d d Self employed .51*** .54** Pension Status Covered by pension 1.19 1.22

PAGE 33

Table 5 (continued). 25 MODEL 1 MODEL 2 MODEL 3 MODEL 4 MODEL 5 MODEL 6 MODEL 7 MODEL 8 Eligible for pension 1.45* 1.51** No pension d d d d Health Insurance Coverage Uninsured 1.28* 1.17 Other Health insurance 1.94*** 1.72*** Employer-provided d d FAMILY CIRCUMSTANCES Post Marital Single Parenthood 1.35*** 1.20* 1.20 Non-marital 1st Birth 1.23* 1.25* 1.17 Current Marital Status Unmarried .99 .68 ** Married (Spouse in Labor Force) .69*** .67*** Married (Spouse Not in Labor Force) Child under 21 1.25* 1.47*** Number of HH Residents .93* .90** ECONOMIC WELLBEING Log of HH Income .95*** .95 Log of Non-housing Assets .97*** .97** Log of Net Value of Primary Residence .98** .99

PAGE 34

Table 5 (continued). MODEL 1 MODEL 2 MODEL 3 MODEL 4 MODEL 5 MODEL 6 MODEL 7 MODEL 8 Intercept 1.14 1.09 .74 1.59 1.03 .55 .17 .70 Model X2 -1993.54 -1953.42 -1821.17 -1435.67 -1814.35 -1804.83 -1804.95 -1415.46 D.F. 2 4 6 13 8 12 9 26 *p<.10; **p<.05; ***p<.01. d Denotes reference group 26

PAGE 35

27 Racial disparities in family patterns and wealth also underlie racial disparities in rates of work disability. Once either measures of family circumstances (Model 6) or economic well being (Model 7) are controlled for, African American and White women appear to have similar rates of work disability. Importantly, measures of work, family, and economic circumstances impact rates of work disability. Women with more years of employment throughout the life course are less likely to become work disabled. Compared to married women with a spouse outside the labor force, married women with a spouse in the labor force have a lower risk of becoming work disabled. Also, self-employment, older age, and higher values of household income, non-housing assets and net value of primary residence are associated with lower risks of work disability. Diagnostic measures do not indicate severe multicollinearity in disability models.

PAGE 36

CHAPTER 5 DISCUSSION Much like previous research on labor force exit behavior, results from the presents study suggest that an array of life course factors are central to the distribution of older workers across the alternative destination statuses of retirement, and work disability (Hayward, Grady, Hardy, and Sommers, 1989; Szinovacz, DeViney, and Davey 2001). However, this study is among the first to utilize longitudinal data to demonstrate that race is an important predictor of labor force status and labor force exit behavior among women in late midlife. As hypothesized, among women in the labor force in late middle age, African Americans have lower rates of retirement and higher risks of work disability as a result of racial differences in circumstance throughout the life course. Results from proportional hazard models demonstrate that racial disparities in labor force exit behavior stem from racial differences in human capital, health, and wealth across the life course. In the case of retirement, racial differences in family and economic circumstance appear to underlie racial disparities. Compared to White women, African American women are more likely to have ever been single parents, be unmarried, have more household residents, and are less likely to be married to a spouse in the labor force--all of which are associated with lower rates of retirement. Once family characteristics are controlled for, African American and White women have similar rates of retirement. Household non-housing assets and net value of primary residence also intervene in the race-retirement relationship. Importantly, racial differences in these two measures are 28

PAGE 37

29 prominent, and African American and White women with equivalent levels of economic resources appear to have comparable rates of retirement. Racial disparities in rates of work disability are even more pronounced. Results suggest that African American women are approximately twice as likely as White women to exit the labor force via work disability. Both temporally distal and proximate factors intervene in the race-work disability relationship. For instance, racial differences in educational attainment account for a significant share of racial disparities in work disability. Also, more contemporaneous factors such as physical and self-rated health are, in part, a function of education, and account for a substantial portion of the race gap in rates of work disability. While some researchers have suggested that racial disparities in work disability are a consequence of economic incentives, lack of attractive employment, or social desirability, this studys findings suggest that African American womens disproportionately high rates of work disability are primarily a consequence of their poorer health. While health differences between the two groups account for a substantial portion of the race gap in work disability, residual racial disparities in work disability remain. One reason that the health disparities may not have completely accounted for the race gap in work disability may be due to under-reporting of health conditions among African American women. Compared to White women, African American women have far fewer economic resources, are more likely to be uninsured, and are less likely to have employer provided insurance. Consequently they are likely to receive infrequent and inadequate health care. African Americans lower rates of contact with health care providers may

PAGE 38

30 significantly mask unrecognized health problems, and thus understate the full effect of doctor-diagnosed conditions in the race-work disability relationship. Educational attainment was expected to play a key role in the race-work disability and race-retirement relationship. However, important historical structural arrangements may be muting the effect of education, most notably, racially segregated schools and institutional racism. Women in this sample were born between 1931 and 1941, and thus received separate and unequal education prior to the implementation civil rights legislation. Consequently, even among White and African American women with the same number of years of education, African American women likely received sub-par education. Furthermore, institutional racism resulted in fewer opportunities for these African American women, relative to White women, at a given level of education or skill. Clearly, racial differences in labor force exit patterns reflect socioeconomic and health disparities. Given the importance of understanding labor force exit behavior within the context of decisions and circumstances throughout the life course (Hayward et al., 1996; ORand et al., 1992; Szinovacz, DeViney, and Davey, 2001), the present study investigated racial differences across an array of factors. In addition to racial disparities in retirement behavior, education, and health, dramatic racial differences in work and family circumstances, and economic well being were observed for this cohort of women. African American women were disadvantaged, relative to White women, in many respects. For example, compared to White women, African American women have substantially higher rates of nonmarital first births and post marital spells of single parenthood, are more likely to be a blue collar workers, less likely to be self-employed or working in a white

PAGE 39

31 collar job, less likely to have employer-provided health insurance or a spouse in the labor force, more likely to be uninsured or unmarried, and have less household net worth and income. Pension wealth and total years worked represent two features that African American women actually fare better on than White women. This study extends upon Belgraves (1988) study in several key respects. First, the use of a nationally representative sample makes national inferences possible. Second, this study distinguishes between types of non-participation (e.g. retirement and disability), revealing striking racial disparities that would have been masked by relying on labor force participation rates. Third, rather than relying solely on cross-sectional data, this study uses longitudinal data to explore womens dynamic labor force exit patterns. Further, the present study includes measures of a wide array of life course circumstances, instead of relying solely on temporally proximate pull factors. Findings from the present study are suggestive of both similarities and differences in race-labor force exit behavior relationship among women and men. Among women, African Americans appear to have higher risks than Whites of exiting the labor force via work disability as a result their poorer health, a findings similar to that among men. In the case of retirement, however, whereas African American women have lower rates than White women, African American males have higher rates of retirement, relative to White men (Hayward et al., 1996). This is likely a result of greater racial similarities in labor force histories among women than men. The literature on womens retirement more generally, as well as race differences, may benefit from future studies that explore the impact of marital transitions and spousal labor force transitions on labor force exit behavior. Additionally, there is a dearth of work

PAGE 40

32 on womens risk of reentry into the labor force from alternate labor force statuses. Future research on retirement ought to consider exploring the inter-connectedness of transitions across multiple domains such as family, health, work, and economics (Szinovacz, DeViney, and Davey, 2001). It is worth noting that although analyses are based on data collected between 1992 and 2000, analyses do not explicitly focus on period effects. The United States experienced great economic and social changes during this time span. For example, the economic depression of the early 1990s preceded the sustained economic boom of the later 1990s. Welfare reform legislation was also passed during this time period (1996). While a myriad of macro-level factors may have influenced womens labor force exit behavior, the effects of such phenomena are difficult to isolate and are beyond the scope of this study. Findings from the present study are an important first step in documenting and understanding racial disparities in womens labor force exit behavior. Further, they highlight the importance of distinguishing between forms of non-participation--retirement and work disability, and lend support to the notion that racial differences in the labor force exit behavior among women in later midlife are a consequence of different circumstances throughout the life course. The subject matter of this paper is timely and important amid concerns over the increasing dependency ratio, as the United States deliberates revising the Social Security Retirement system, and as the labor force is becoming increasingly gray, brown, and female. Findings that health problems contribute to higher risks of labor force withdrawal via work disability support the notion that health affects worker productivity and

PAGE 41

33 consequently the demand for and supply of market labor services (Deleire and Manning, 2002). Thus, social and economic costs of health impairments exist. In view of that, preventative poverty and health policy initiatives that focus on improving population education and health, especially among vulnerable populations, may reduce involuntary labor force exits via work disability, and contribute to an increase in labor force participation and economic productivity. In light of the forecasted declining role of Social Security income in the well being of older Americans, policies that emphasize financial education including issues related to expected time-horizon, savings and investments, and future income and expenses may become increasingly critical for labor force optimization and the long-term financial security of older women.

PAGE 42

LIST OF REFERENCES Belgrave, Linda L., 1988. The Effects of Race Differences in Work History, Work Attitudes, Economic Resources, and Health on Womens Retirement. Research on Aging, 10 (3), 383-398. Blackwell, D.L., J.G. Collins, and R. Coles. 2002. Summary Health Statistics for U.S. Adults: National Health Interview Survey, 1997. National Center for Health Statistics. Vital Health Stat. 10:205. Bound, J., M. Schoenbaum, and T. Waidmann. 1995. Race and Educational Differences in Disability Status and Labor Force Attachment. Journal of Human Resources 30(5): S227-S267. Brown, T.H. and A.M. Pienta. 2002. The Impact of Divorce, Single Parenthood, and Work Characteristics on Labor Force Behavior Among Retirement-Aged Women. Poster presented at the Gerontological Association of America, Boston, MA. November 2002. Burr, Jeffrey. A., Michael P. Massagli, Jan E. Mutchler, and Amy M. Pienta. 1996. Labor Force Transitions Among Older African American and White Men." Social Forces 74: 963-982. Carr, Deborah. 1996. "Two Paths to Self-employment? Women's and Men's Self-employment in the United States, 1980." Work and Occupations. 23:26-53. Daly, Mary. and John Bound. 1996. "Worker Adaptation and Employer Accommodation Following the Onset of a Work-Limiting Health Impairment." Journal of Gerontology: Social Sciences 51(2): s53-s60. Dannefer, Dale. 1991. The Race is to the Swift: Images of Collective Aging. In G. M. Kenyon, J. E. Birren, and J. J. F. Schroots (Eds.), Metaphors of Aging in Science and the Humanities: 155-172. New York: Springer. Deleire, Thomas, and Willard Manning. In press. Labor Market Costs of Injury and Illness: Prevalence Matters. Health Economics. Eller, T.J. 1994. Household Wealth and Asset Ownership: 1991.Current Populatin Reports, Series P70-34, U.S. Government Printing Office, Washington, D.C. January, 1994. 34

PAGE 43

35 Gibson, Rose C. 1987. "Reconceptualizing Retirement for Black Americans." The Gerontologist 27 (6): 691-698. Gibson, Rose C. 1991. "The Subjective Retirement of Black Americans." Journal of Gerontology 46 (4): S204-209. Hayward, M.D., W.R. Grady M.A. Hardy, and D. Sommers. 1989. "Occupational Influences on Retirement, Disability and Death." Demography 26:393-409. Hayward, Mark D., Samantha Friedman, and Hsinmu Chen. 1996. "Race Inequities in Men's Retirement." Journal of Gerontology: Social Sciences 51B:S1-10. Henretta, John C. and Angela M. O'Rand. 1983. "Joint Retirement in the Dual Worker Family." Social Forces 62(2): 504-520. Henretta, John C., Angela M. O'Rand, and Christopher G. Chan. 1993a. "Joint Role Investments and Synchronization of Retirement: A Sequential Approach to Couples' Retirement Timing." Social Forces 71(4): 981-1000. Henretta, John C., Angela M. O'Rand, and Christopher G. Chan. 1993b. "Gender Differences in Employment After Spouses' Retirement." Research on Aging 15 (2):148-69. House, James, and David Williams. 2000. Understanding and Reducing Socioeconomic and Racial/Ethnic Disparities in Health. B.D. Swedley and S.L. Syme (Eds.). Promoting Health: Interventions from Social and Behavioral Research. National Academy Press Washington, D.C.:88-124. National Academy on an Aging Society. 1999. Chronic Conditions: Challenges for the 21 st Century: Chronic and Disabling Conditions, Number 1, November 1999. Washington DC. ORand, Angela. 1996. The Precious and the Precocious: Understanding Cumulative Disadvantage and Cumulative Advantage over the Life Course. The Gerontologist 36 (2): 230-238. ORand, Agela M., J.C. Henretta, and M.L. Krecker. 1992. Family Pathways to Retirement. M. Szinovacz (Ed.), Family Retirement: 81-98. New York: Sage. Parsons, D.O.1980. Racial Trends in Male Labor Force Participation. American Economic Review 70: 911-920. Pienta, Amy M., Jeffrey Burr, and Jan E. Mutchler. 1994. Womens Labor Force Participation in Later Life: The Effects of Early Work and Family Experiences. Journal of Gerontology 49: 231-239.

PAGE 44

36 Pienta, Amy M., and Tyson H. Brown. 2001. Labor Force Transitions Among Disabled Workers: An Examination of Gender Differences. Poster presented at the American Sociological Association, Anaheim, CA. August 2001. Quadagno, J., and Jennifer Reid. 1999. The Political Economy Perspective in Aging. V.L. Bengtson and K.W. Schaie (Eds.), Handbook of Theories of Aging: 344-358. New York: Springer Publishing Company. Szinovacz, M.E., DeViney, S., and Davey, A. 2001. Influences of Family Obligations and Relationships on Retirement: Variations by gender, race, and marital status. Journals of Gerontology: Social Sciences 56: S20-S27. U.S. Bureau of the Census. 1993. Statistical Abstract of the United States. Washington, D.C.: Government Printing Office. Welch, F. 1990. The Employment of Black Men. Journal of Labor Economics 8: S26-S74. Wilson, W. J. 1987. The Obligation to Work and the Availability of Jobs: A Dialogue Between Lawrence M. Mead and William Julius Wilson. Focus 10: 11-19. Wray, L.A. 1996. The Role of Ethnicity in the Disability and Work Experience of Preretirment-age Americans. The Gerontologist 36: 287-296.

PAGE 45

BIOGRAPHICAL SKETCH Prior to receiving his Master of Arts in sociology with a minor in statistics, Tyson Brown earned his Bachelor of Arts in sociology with minors in business administration and gerontology at the University of Florida. Concurrent to earning his Master of Arts degree, he was a research trainee at the Institute on Aging. After completing his masters degree, Tyson began his Ph.D. coursework at the University of North Carolina at Chapel Hill in the Department of Sociology and an NIA-funded research traineeship at the Carolina Population Center. 37


xml version 1.0 encoding UTF-8
REPORT xmlns http:www.fcla.edudlsmddaitss xmlns:xsi http:www.w3.org2001XMLSchema-instance xsi:schemaLocation http:www.fcla.edudlsmddaitssdaitssReport.xsd
INGEST IEID E20110109_AAAAZS INGEST_TIME 2011-01-10T03:14:53Z PACKAGE UFE0001240_00001
AGREEMENT_INFO ACCOUNT UF PROJECT UFDC
FILES
FILE SIZE 1053954 DFID F20110109_AADJTJ ORIGIN DEPOSITOR PATH brown_t_Page_39.tif GLOBAL false PRESERVATION BIT MESSAGE_DIGEST ALGORITHM MD5
e7e0a33c600eb79d9071ae40db91c9e8
SHA-1
4d7fcb3c280364e7d612bf2db9c219c87bd56491
54953 F20110109_AADJOM UFE0001240_00001.mets FULL
f394b582ac9ac36efaba6e66265f6aba
de124784cdce829f3422ea9b7b267ffe0023201c
23321 F20110109_AADJYG brown_t_Page_19thm.jpg
1b819016865158ab394fd23103435901
b49105caf8eeefa1aa440b2624a0a21962231926
F20110109_AADJTK brown_t_Page_40.tif
959c63ff8016a474beca9c5055f11fba
c6a521cfca334bfd7af478ab9caad0d128d079fa
83868 F20110109_AADJYH brown_t_Page_20.QC.jpg
7ed47eb4dbb86f44aa405effa410cbc4
fba618283cf30c01250f0f70e8415935ab0a5978
F20110109_AADJTL brown_t_Page_41.tif
5127ad08f8774b9290e2d5a348d9de8f
89afe880c8ec85cf6847b97458d56d2964d706a6
85371 F20110109_AADJYI brown_t_Page_21.QC.jpg
bac665b08861ac5dcef7436f571d4e21
7bc537e6e48e41c833be2e7c306d4999e873d993
F20110109_AADJTM brown_t_Page_42.tif
30d78d180596ad65490bd1f83a862f69
73d52f49abbe693df3f8e0d940a7300c56659686
70569 F20110109_AADJOP brown_t_Page_01.jpg
59ae2e7a3b8c136e35c0908f3fa01fa8
257dbe5045dba966b0f025686be22d0b7da04907
26090 F20110109_AADJYJ brown_t_Page_21thm.jpg
7b4905a14b0816d6c90c76f743daff73
7e119a1b98c34f7341fc0ac123f01c9dbde70a79
F20110109_AADJTN brown_t_Page_43.tif
e4c4e9a308d2abc8a47215e209fc651c
825497005c5f24b4aca6f2c90272f525e07cd307
14598 F20110109_AADJOQ brown_t_Page_02.jpg
3a6abc1f0c1514f525e660d73827e5fd
1e326cb5baa823de42ee9fc817b862325a7dde70
56974 F20110109_AADJYK brown_t_Page_22.QC.jpg
dbfe0e0f30a8f325a6e716a06647e862
4c7a1b611912dd489b06e086cf9d5a2dd993fc8a
F20110109_AADJTO brown_t_Page_44.tif
198ef58ae7fd2b2cea3123d5b169121d
da235e4f89026e4ee762771d94de26318c1d4a8f
245348 F20110109_AADJOR brown_t_Page_04.jpg
71e6cb83afd85a712db1caf070c2e421
baf286a1e82213dc0ea02f2d5ac4c6c0747b0f54
18603 F20110109_AADJYL brown_t_Page_22thm.jpg
028b2fb987c514b57f46acd1a5a48566
0a035cebd3c560ea17c5b32246a173c2539e43c1
F20110109_AADJTP brown_t_Page_45.tif
e6e79a5ba9caa028e64f6a0097770024
7adee8e0404b7b845851198fc25bd491c548ef4a
61308 F20110109_AADJOS brown_t_Page_05.jpg
54360465752446c32f851a9d3002828f
a9178ceb73128bb2ee00e70333e8e0297819b024
51050 F20110109_AADJYM brown_t_Page_23.QC.jpg
6a7f348a58adb216e6313039e45cdc15
194512eba5dacca25b02392cac484cdd423b9ca6
10387 F20110109_AADJTQ brown_t_Page_01.pro
1091c1b655fd5e412e386de276a49a39
cceb98cdad74d29e27725a53852e9abcf60fdaac
96967 F20110109_AADJOT brown_t_Page_06.jpg
193a7659a01f1e0fec494ac0ada749d4
f1ced7c77d62dfb5041c64f1fc46a1a9d4eb1ec9
15554 F20110109_AADJYN brown_t_Page_23thm.jpg
a194521e12d0df63bf59903ff6353350
04aeec6571e5e82a71fc2655f4a28654b9689697
1147 F20110109_AADJTR brown_t_Page_02.pro
a0e9b479ccbec5efeca78fcc68a37e6e
6ff9bf33aaf63e40dc8ff39a00418d0032a20447
178819 F20110109_AADJOU brown_t_Page_07.jpg
f5888f479ca8669a58561b6b98d6280a
803230fece94b6a418142cd555dc61cb5c347edf
49005 F20110109_AADJYO brown_t_Page_24.QC.jpg
5e1611eff5d2f872ec9152008796e815
fb8ebf584eda0a28c6b36c731b321e31486ee773
18168 F20110109_AADJTS brown_t_Page_03.pro
3d86b51d3391ab5a8452d1a28bf5e3b9
961311fce28b3d7c7b2a7afa77eb5e6dc75bd94a
28149 F20110109_AADJOV brown_t_Page_08.jpg
c1c4d33d7aa96e0c6fe726239b15da8d
3700f2edc3e2e851e9bf03a57e94654d36da31f3
54598 F20110109_AADJYP brown_t_Page_25.QC.jpg
f8bc78efd00bb6a5e376ff6c2773b08b
5616009764fc4818c5be5f258fb5a36c8c577638
67380 F20110109_AADJTT brown_t_Page_04.pro
c72bf10953295c54e414a13e229f6c48
f7efa080b301984b8ece17728eff6409fecbfbca
192326 F20110109_AADJOW brown_t_Page_09.jpg
ee2b8672805a032c1596f8447bef8258
a318bcc4faa0a9fe3a1b52a1b340b71bc866b8d6
17192 F20110109_AADJYQ brown_t_Page_25thm.jpg
72993cf0a58aa12caa5ed147e3e4bae0
58d48f752bd10ebdb9c2cc89b0b9f37bf235234c
9051 F20110109_AADJTU brown_t_Page_05.pro
109a5c7acce6427625aaf047faef1330
2ccea15892eaccc032dbfe14688a42d02a7dfb79
75581 F20110109_AADJYR brown_t_Page_26.QC.jpg
47815e9fc899d172130f4b7ebe3c1bf4
06e2fd0b5ad1aa8ae6815370dfdd4ded2d1feee0
14213 F20110109_AADJTV brown_t_Page_06.pro
4df2062e9087b8c484d689db70bba709
42b368a2430f331d03f8fe0d13c0d61577132b22
182612 F20110109_AADJOX brown_t_Page_10.jpg
576d3c8d55149e8b76ea7d2ba81a734f
10b3b7613167d9b89bdb66f03894860ee7ba4b04
83437 F20110109_AADJYS brown_t_Page_27.QC.jpg
a99d86f6e0505886cd50025d487f1b7a
8e1e9f9de8c4eff776e03642eb4b83b12d37eaf6
39102 F20110109_AADJTW brown_t_Page_07.pro
81d07d454b63b40a49f68bc2f7b9928c
3f2ea4cfab57dfcd7cae13483a5ccc60c009c347
180493 F20110109_AADJOY brown_t_Page_11.jpg
929b8268b4611e9e7122c9d1271183cd
977b84e95a4c26865e80e1ff263d3d6eaccba509
25455 F20110109_AADJYT brown_t_Page_27thm.jpg
c2c2c523ca26f4776149d14d5dcf6155
99ca29424fc6e28ace9c250c0bead1df45cc1bdb
4824 F20110109_AADJTX brown_t_Page_08.pro
8cf28e8061bd34059d3abac524670e64
1e8a0e58f465ad864f35075abed7266483325342
218999 F20110109_AADJOZ brown_t_Page_12.jpg
807fb53c9a8fa6cd706272bf7b929e44
10dd829b0b0fe377e773728435307bd2d0ed78e4
28261 F20110109_AADJYU brown_t_Page_28.QC.jpg
7d6a021d7c9916b3a2bea89b2e480ace
fd9d817b282f3fc66237d4f03e782bf88efb717d
45532 F20110109_AADJTY brown_t_Page_09.pro
d5536fa720c9aec730f2510346609f7d
51eebdc0551e0c92766ff54976386c028b882a3b
10460 F20110109_AADJYV brown_t_Page_28thm.jpg
4511224beaaffd09bad1078e8680b2b6
e8ec57c90737ade6d4f83ddee7d0e639a77f77bf
42784 F20110109_AADJTZ brown_t_Page_10.pro
4500dfb3bcbcfdc41f23e9d260e6ba2f
75aa803c2a2bf35cb6f561cab81bca42c6355b44
23294 F20110109_AADJYW brown_t_Page_29.QC.jpg
3d744e43d18ce4afb89f1b5d966d0d98
c5e699233c89019d3afa0cf394a2177ad2ed6bbb
116095 F20110109_AADJRA brown_t_Page_21.jp2
2f2e2e15be9ca7823d7634c470e26c55
8d0b2d218891c08b0a79da036a5e03a7fbf48201
8618 F20110109_AADJYX brown_t_Page_29thm.jpg
1338af86765fdc84d51f83f088717855
991d89b87937ea30b7ef755caa4d2f9ce4cbec3f
82694 F20110109_AADJRB brown_t_Page_22.jp2
00fe2ad0c9ed19501bef375fbfb23bf9
dd47bdace72c3dd8ec3aea314ea5704a6746fc9b
15818 F20110109_AADJYY brown_t_Page_30.QC.jpg
b54f2edde007145283368fb5b7f21cc6
39902302ddb7807c3620bfc1becbe5fa0c450ea8
69057 F20110109_AADJRC brown_t_Page_23.jp2
53e0ba1dd8921d57cb695d70260ea00d
bbf5138f71e269a750d7cfcc6c84588ae8007d07
2146 F20110109_AADJWA brown_t_Page_21.txt
12df63666dd085c6cd3457e405152fb2
79dc8daa61dcaac638ba01e1627b4348fc629c0a
6207 F20110109_AADJYZ brown_t_Page_30thm.jpg
80c6201cd1223129466717bfd0bb1f7f
644ca557497b7d60eae4256e807242e6871e5e7b
66862 F20110109_AADJRD brown_t_Page_24.jp2
e56401e62bf4d6abc5734c0a372cb88d
349b1dfcb90016f8748f93ecb9a84cdeb5b89e3b
1517 F20110109_AADJWB brown_t_Page_22.txt
8b247005ff88f472fcbb527fc6dffe1a
da7423d13c90b70719d3cf4007227074932c9a82
70846 F20110109_AADJRE brown_t_Page_25.jp2
2715898c051b9b432421b30799c572ca
d6433856899aecade37f5efc1f28c94c3ffa3112
1303 F20110109_AADJWC brown_t_Page_23.txt
275c21768ed4b51578c321cf8c560cff
66cf52adf09c60ce7cc186792a6b15ac05a9dfa0
104087 F20110109_AADJRF brown_t_Page_26.jp2
5a8aa6bbf74c737587a1e57b99dc176d
6e0a7a8405fe0ec532b1662ce8aee61690526286
1440 F20110109_AADJWD brown_t_Page_24.txt
967a6d65b0f8c831c98273c6164ca82d
a2215921cb8e9b80c82db5536a5ca806043141d2
116068 F20110109_AADJRG brown_t_Page_27.jp2
14d3330033ad7d90cb4637ca94f9f717
723eb06685194e7affe5e521e5040fdfd272c10a
2165 F20110109_AADJWE brown_t_Page_25.txt
d3f3b7ba69c07d629c807b5c4cd99d16
9b7bda93e99ffe0d6c6386a52ae8e3ef674f0384
46017 F20110109_AADJRH brown_t_Page_28.jp2
b2917756d7d799446db481a534a2315a
c2353a4f2ca0ee129a28445bacc246ddd40d695c
2180 F20110109_AADJWF brown_t_Page_26.txt
456f7d694cfa8770f3e0eb4836145561
0ee68a413e6f663fd837a186018a0c358a939782
39594 F20110109_AADJRI brown_t_Page_29.jp2
a5ecb28d94c6784dcfa210a193b80c6a
1b71d6b260657308771ff7494463c42bdcd187cc
2136 F20110109_AADJWG brown_t_Page_27.txt
74e9cba79f6bbde48a1e0517e1219273
2e34e38968dd4e37054e0f04683c8435e615dbac
24795 F20110109_AADJRJ brown_t_Page_30.jp2
ec35881549331791e08ee808c6fdcb26
e405824aa1bb7b8cc14b6c2ab65ab4a3242b50d7
1068 F20110109_AADJWH brown_t_Page_28.txt
deb6dcbed75b1e3e6eda074ee50de88e
15963dacd1fa1a9a9db19462f654b255eaf1d2d1
114134 F20110109_AADJRK brown_t_Page_31.jp2
505079292867c758d071e4238fe63b9b
2b9f178e6e1fd71387a757b307846d2ce2fe636c
2138 F20110109_AADJWI brown_t_Page_29.txt
1451af3546a8c904230137dc83c4e0b9
80fbaa150e9b7b8f92d7405c80dd1efaa6e87792
51092 F20110109_AADJRL brown_t_Page_32.jp2
e78356dc4e54c075640797f4745d3189
5fcac4d71e15ca95cb649d9e7ba4b75ab5a8ee27
712 F20110109_AADJWJ brown_t_Page_30.txt
4981f3614c7b2cc024e9bd8eb592d2ec
cc4131cf4e92852e0e869fa717fcf02cfeae78ed
40997 F20110109_AADJRM brown_t_Page_33.jp2
0ba27dd13e63cd42386b2afb27ae3cf8
c2097604a4626aa3a8dc1e31262daea642b8bf31
2142 F20110109_AADJWK brown_t_Page_31.txt
0902002dfca0faba752041f2e672620b
094b68cfccc7b3d0353d1ec7727f080a83ea8d6c
19865 F20110109_AADJRN brown_t_Page_34.jp2
f1d86aafeea6c5bdd2fa24d8121bccd9
2215a41580c3fb3a702487afd3265e3550e8825e
2102 F20110109_AADJWL brown_t_Page_32.txt
68fc9b5b76cafaad7096b6d9dd6cbe4e
9ee58c9693e266a7b7cea7a56d61fbad1a3e3de3
96175 F20110109_AADJRO brown_t_Page_36.jp2
60a3e23b7853006cd671556627f4c3e8
620aecbe918604cc7ce8f0b13c6b73983e29873f
2278 F20110109_AADJWM brown_t_Page_33.txt
986863305fb29d9d88b76797c79bb8ac
19dec66c4bbb6ded7ce02587347139ef87cfe4f3
104466 F20110109_AADJRP brown_t_Page_37.jp2
9be59856d13599c338c81999ef4b0f9a
7e022766aa378c3256d5a7b59523f925aeacc87d
554 F20110109_AADJWN brown_t_Page_34.txt
af70368c1d8600b1ef0fa905732cf287
b88a3b1a23d17181293ecb9c9ed8e914502de058
108888 F20110109_AADJRQ brown_t_Page_38.jp2
96eea25d1fa5b8d7ec8f108a2a9151e1
af516f3048e49c475f16099b73054d9162a2fccd
975 F20110109_AADJWO brown_t_Page_35.txt
e93cf73de579665d0daa102891573d41
5d866a7efc8d316cfd19b358cb16be9a3d91eb66
109159 F20110109_AADJRR brown_t_Page_39.jp2
dd69ed9e3b47c048b741ccacaac31822
2bc0772a4312596c22832e11b0eefbd00edae26d
2013 F20110109_AADJWP brown_t_Page_39.txt
1829bec3c3824206a6260e8856d95493
b04c85de3ec32a29a214edda4713a90f3d9fa8b4
104241 F20110109_AADJRS brown_t_Page_40.jp2
d8efcde09d9adef274a4cddf081de9ba
3236610aa6a3c0cd5274d269ad906b8104e6a896
1893 F20110109_AADJWQ brown_t_Page_40.txt
48b1757f9d6256560eea0db995d2923e
ab90d81f6a432ea38e90685ccbab8698362ecd64
50900 F20110109_AADJRT brown_t_Page_41.jp2
8f78fa6e3d3a7d3ace6726b0dd6d6ec3
6b05a7a5e8a96b67c602dd81c3e5adc9568ac9ed
883 F20110109_AADJWR brown_t_Page_41.txt
33ab123fbc522b58111c2506f6c828e4
243bc19df32182126fb9d498dbc4f12335297013
107697 F20110109_AADJRU brown_t_Page_42.jp2
d5f78becb4e3d13a2440b191213fdfea
e9c221d798f449850a9dd5b8270c0bca271c348d
2040 F20110109_AADJWS brown_t_Page_42.txt
6dd33e25d604a716a69ac04b657eca1f
1dbcb2a247a5aca2d08fb44dfdc8887da42703c1
122083 F20110109_AADJRV brown_t_Page_43.jp2
c611a14cc25e34de1883186203cc3b30
ec9052880a0c4d1994626c688474937df40ca7e8
2265 F20110109_AADJWT brown_t_Page_43.txt
03bf3cd22d29c959427d1f7820d971b3
a4bc59e32905c16e1810238f0408167bb9f669c2
68166 F20110109_AADJRW brown_t_Page_44.jp2
aa535e19743cbc8dbea44c6ad159e94b
a88a38c1155e26edba75a36c345f107c4bac8e5d
1235 F20110109_AADJWU brown_t_Page_44.txt
470012442480f91b364b0c9c258e1a1d
153bd7ee5bff6193989ea17c982d5b8e824e27a1
35922 F20110109_AADJRX brown_t_Page_45.jp2
5f26192ca4ea34dafd7ea82ef0ad6436
f3f4bf9b08a940af7e1daba040a6a6eeb7b09ea3
648 F20110109_AADJWV brown_t_Page_45.txt
1cb2bd6c30921827c1a4afb1a9f9224d
cb7024fd0f3bd70ac5696d482a97d6b38b67a2ba
F20110109_AADJRY brown_t_Page_01.tif
c263f6b0025fa16f435d9b8b43924d2a
758189a39748208556ed97c2886446f016ed91e1
7665 F20110109_AADJWW brown_t_Page_01thm.jpg
c03a5512187328ba06e81cd95f3a57dc
a81fa184fddeb87ce747e7b2217491f49e826058
222108 F20110109_AADJPA brown_t_Page_13.jpg
7c062fec2d27fd30307729f891cca1bc
c0702ab4f69ce204b81732c3ca5cf4b9f77e131a
F20110109_AADJRZ brown_t_Page_02.tif
52f3ee4e1999c9aeb751e784cf601b76
b50a94e28f48277f6f964ae76d96ba8ebc5c7b87
686852 F20110109_AADJWX brown_t.pdf
78dc312596bda4aac2ab8c18f682a358
2ae36246c5b683586d171e9feb99582ef71e3f25
205766 F20110109_AADJPB brown_t_Page_14.jpg
becd68aba913555dd2d6baf1f38fe83d
a6af4d7ddc3fb33a733cdb996db5386db0902145
70265 F20110109_AADJWY brown_t_Page_36.QC.jpg
0d910e82262d90eb5a5041714b2f2bc8
c3ad5efa90a16ef96fc43469571f03b206b370bc
192791 F20110109_AADJPC brown_t_Page_15.jpg
6c93b49ab708edce2c35c8f57c173c52
12053f011f115ec2a85965b441b8a40e6c1cd8bd
46313 F20110109_AADJPD brown_t_Page_16.jpg
ecd9d81636d656f51cd07b42f6907b21
c80d7f68dc68c10ea2ef181ca18cc78f99af2e26
42260 F20110109_AADJUA brown_t_Page_11.pro
46395723ec215166aef2e7e650f0ef43
1481078ef1ee7531bde547201e687c9540616d1e
23559 F20110109_AADJWZ brown_t_Page_01.QC.jpg
5c591502542dd00e4bbcf61af8e58d2e
5d0e6a5d4c9b601833a75e6fa05dc5b8243afc0a
187749 F20110109_AADJPE brown_t_Page_17.jpg
ef1c342755ad19c4cd345270f6f633ee
f8f18424348020c2ce42240a0f7cf5ca7a53d852
52220 F20110109_AADJUB brown_t_Page_12.pro
28c7295e0d2cb0f564eb95dd34a1db7b
b805367b8fbfc0b14548fc3364f7cf1ec7aaed81
215940 F20110109_AADJPF brown_t_Page_18.jpg
21726443fd67d0a1bc038ae631c6019f
8e0db4a02943a088946d43c662fdb03d0c7875ca
83593 F20110109_AADJZA brown_t_Page_31.QC.jpg
cbe00a59ff4f11e751a5da3083dd03c8
ae073354b580e6684883e48ca845960d2e7da80b
52900 F20110109_AADJUC brown_t_Page_13.pro
85147825f263168e81fb3a617ccdbb05
e6136214cb43aab7a7038d1d56f52e60790d4af9
194061 F20110109_AADJPG brown_t_Page_19.jpg
f114e8a67540baf3ea32399d30ccc70a
8ffbe3c29a6c061b029c8ee7800d08be27c6c2f8
25563 F20110109_AADJZB brown_t_Page_31thm.jpg
f2075ea87bae47e70dbaf6d361560ff1
fb8566b61192a1909c283a6564e50b3067c04411
49218 F20110109_AADJUD brown_t_Page_14.pro
a279a031e3127578e45bf48599acbd7c
e6d751aa7d9ee5401fd8668e6b7c5436fc4b34f2
218042 F20110109_AADJPH brown_t_Page_20.jpg
4bb9657fe3fccfcb94bf48e3d22f8191
a95910760287c96738512d4a43727afa7b3d0cc3
44441 F20110109_AADJUE brown_t_Page_15.pro
d82d6b081e927980f9fe71946b316d5d
f775129ce698fea1a35ade6847461c611b630bde
224146 F20110109_AADJPI brown_t_Page_21.jpg
625fcea7a340f049d43d14011acf5da6
da62233e872291b93e31863517d15c7c7e0b5806
25476 F20110109_AADJZC brown_t_Page_32.QC.jpg
2dda793d38a61e055ca24331e1ecc165
397f4662595df83c51d1937aa01ba9cd0c8ac592
9511 F20110109_AADJUF brown_t_Page_16.pro
550aeda343b5bdcb551b4265be5049f4
ee41d4765c73c3607f47e13eda4791a564459e83
158264 F20110109_AADJPJ brown_t_Page_22.jpg
a00373e490c4ae1473d3c64eb7b6845b
6de938a6c4365b240486558b59338982d8baf580
9890 F20110109_AADJZD brown_t_Page_32thm.jpg
f3f8e4e8d050e736763606743315df18
da60b8ae4c6acd12d5828c8f65e169f818ad09eb
43194 F20110109_AADJUG brown_t_Page_17.pro
a12851645498695c8f071cb82dce6f19
5360f21728ad5a00cd561e4ee878407a7ccbd8c0
133615 F20110109_AADJPK brown_t_Page_23.jpg
f1c6dda4067d3dfd20a27ef0b6b246f5
6dff67290db28912a38e49645a0d23cadfaa47ea
20751 F20110109_AADJZE brown_t_Page_33.QC.jpg
8411368587fc1430ae4f731138cab626
f1703172c092d8e9777c1f05495e73d766e9f872
52161 F20110109_AADJUH brown_t_Page_18.pro
f604885969b14c166bc117a068974d03
b45fa07148c027effea62ec3bb44598fb53595e3
129180 F20110109_AADJPL brown_t_Page_24.jpg
9bf4000171b378995f59870730afcdbd
74b81b7a2c3310146a46dbd0745c2baefd980690
8400 F20110109_AADJZF brown_t_Page_33thm.jpg
f0155f7d33e9c93411f63abcad6e5fba
8d28b6521b3e8f2d30da5596e98c740f96cf99ff
46415 F20110109_AADJUI brown_t_Page_19.pro
e3638de7d04c152a07dfe7a6d26466d1
ac217fe47a96d3aaae31d4517e27d83764247702
12108 F20110109_AADJZG brown_t_Page_34.QC.jpg
26e0b18f5978fcda73979dc696b042da
4a5f291ef5ac11bda7121f4846acf4528ac71536
52436 F20110109_AADJUJ brown_t_Page_20.pro
cff62b4cb5380160d289b0d42cce53ea
b2cd8af4c377c7cf6c335c46b3cac8aef0760246
142774 F20110109_AADJPM brown_t_Page_25.jpg
df29570f4fedda535339245191a6fef6
3711aae2acff9ef7648711532afbfc212dd58eb2
41801 F20110109_AADJZH brown_t_Page_35.QC.jpg
5711a841d8b10eaae1a0b73742bf5ce9
ce405eee8ff67c6ac1380c46e70c9a3871948d49
54368 F20110109_AADJUK brown_t_Page_21.pro
02dc9a99eba273eaed161f190227226b
1155c4293d8178d5b336d2787351171948239067
199127 F20110109_AADJPN brown_t_Page_26.jpg
e1bf234483136b6748768317a631d408
8787df966d73b0349d2aaea96a25dbdf453c9ef7
21365 F20110109_AADJZI brown_t_Page_36thm.jpg
78dc2bb408b0a793528759aad6e5b5ca
74b4cab86403aa92525f011b67a334d880fc21ea
37238 F20110109_AADJUL brown_t_Page_22.pro
1361c335810340acd043e6e754002f57
80b7ece8b39b7a1e36d46d42f3e87740fcc45419
224879 F20110109_AADJPO brown_t_Page_27.jpg
a542f9bc1f113cff634ddb76411409dd
2e1d36efeb250d3b28f0fb7b5698dc2116aa400d
74313 F20110109_AADJZJ brown_t_Page_37.QC.jpg
2a25462e7d994e8d1a858f4f562fe33f
1198b6f06ec6975c7856939d0cd3056e9b6fd738
28156 F20110109_AADJUM brown_t_Page_24.pro
f483a7351aaebef2ff0f08bbea9032b3
0d73e8124d75129bf9f6319ea2d58fd658a19f72
72472 F20110109_AADJPP brown_t_Page_28.jpg
562a9bdc8a1f187021cc6488c6e68c83
93f488d6876ad5972940962f582c7224a8fde2ad
79845 F20110109_AADJZK brown_t_Page_38.QC.jpg
f03d3ba9bf655ac08d64a6cc1c579f53
b579726e30de41c43b978911577f80b23356373e
40526 F20110109_AADJUN brown_t_Page_25.pro
ecf0858a78914df108202b1f53adbf31
1582239b3a6b1bda49d1e2777cb6c5676ae69be5
61506 F20110109_AADJPQ brown_t_Page_29.jpg
3bddd1d2d2007156caeeea4c66819d3a
bc64fe0720730ec7fcc490a3126f2578da3f26c7
24444 F20110109_AADJZL brown_t_Page_38thm.jpg
1b88d8998f37a8b81f012c692774669e
4355d18c169e4a462b1aeaff4c8a96fe7c996580
49735 F20110109_AADJUO brown_t_Page_26.pro
baa2af48893a3652952983173dbdcdcd
07bac8c666d10987c87a1dbf43ed8f023f6a12ce
34588 F20110109_AADJPR brown_t_Page_30.jpg
d6ba451b4f2f93c9ad6604a11d35036f
3bb17b4711d65c73227ce24cf84ad2958eff517e
79484 F20110109_AADJZM brown_t_Page_39.QC.jpg
6727de1bdb5026e6c2ccee8eeb310d0c
2d8d48be8d4f542fdc9ae65f8fc9a9fb1c3c4c0e
54127 F20110109_AADJUP brown_t_Page_27.pro
724aea6888036cb2fe0fcae42366ea3e
045bc3246004aabdd8ee8d91758f22ed57cce965
224023 F20110109_AADJPS brown_t_Page_31.jpg
50409b72c16ab2f71564e870fb7c38e6
5afba3dd1ba5ff3a1cc82e036709e1a3ab96b07e
25200 F20110109_AADJZN brown_t_Page_39thm.jpg
cc3a42ccaf64ea7db82f7e651abaac0d
61ec0f05022eb0758eec3707cb2f94c85591dc60
20572 F20110109_AADJUQ brown_t_Page_28.pro
19242f836a9314406b41d8b22aa402a5
e8a9d31336962e7aee331735ccab4119e8e5c118
62583 F20110109_AADJPT brown_t_Page_32.jpg
314ed621587b70f60d1d439773f9678a
95221e856a9a3b38c2bd84fb787a42426644e356
75575 F20110109_AADJZO brown_t_Page_40.QC.jpg
1f9d4b3c74b19356d4e9f83a9241755e
9de7e6d44e64a469f2728d14c2beca402a7e2083
37661 F20110109_AADJUR brown_t_Page_29.pro
a218cf7abd9becab4efbf066092f7bff
cc028de62539a4cc05a6f0dca63bfe623cb978c8
55493 F20110109_AADJPU brown_t_Page_33.jpg
39ae26e3a69e9348f3b8f0ef0f9d3f2f
52628266ceb7d80acf0d617a15a0a7b8d0136d45
24185 F20110109_AADJZP brown_t_Page_40thm.jpg
97e89a66638f139041ad5efd03a0f4b9
6a24a4d43b8a7936ef3a726551b59e589fcf417c
14403 F20110109_AADJUS brown_t_Page_30.pro
ef88e3b1e4990469a6ccb85c3259d859
784257b3b112d3da466d03b0da6b4696cb438d88
29210 F20110109_AADJPV brown_t_Page_34.jpg
3513dfda0e190859287120ae78b05b2c
bf087c490a5f59d9e09c04d7318e009788b6d169
37146 F20110109_AADJZQ brown_t_Page_41.QC.jpg
c28d609a0fc1d9ec3704de66834555ee
f3c42bb1170c5c9e5a0e6fe3990c523559d23c52
54419 F20110109_AADJUT brown_t_Page_31.pro
38f1ee4f8ae8d0313b5fa0163e5affc5
1733061da526512a45aac474b21129e4f27c57d0
109364 F20110109_AADJPW brown_t_Page_35.jpg
13c7d1e71a7c9b73fcebb40b5fb01482
b370b31473a25a2c6133322d766bca0f3fb049b4
12608 F20110109_AADJZR brown_t_Page_41thm.jpg
48964f2e5c79c5b5fcbff0dc4c6a6571
0c4aac6cc3c9842e9ea3cc390c9b2fce92938ebc
40504 F20110109_AADJUU brown_t_Page_32.pro
972c0f57f0f22af9bea8b8d6a44226ba
b3469dbea1127f938c515682933edae69b3dc9b1
184229 F20110109_AADJPX brown_t_Page_36.jpg
1a7ab73e62dfa7b101cf2555d17394b7
83720d6242e4771f4e6df700711c3228b154e936
67969 F20110109_AADJZS brown_t_Page_42.QC.jpg
d8ebb6532599fee727c50828a55340e7
69a0c00c9ed1bdb792c717e08c573de03d4570fc
36422 F20110109_AADJUV brown_t_Page_33.pro
c62d66d96b7839c67e6bc559b058c5bc
9ece0f61ee0735ce98b2d1f2897ff047e345f233
21830 F20110109_AADJZT brown_t_Page_42thm.jpg
6a55d782ab0563a48f2ced02029f618a
5b30037c34752b7b3b1207dcf49560a6ede750a0
24434 F20110109_AADJUW brown_t_Page_35.pro
327159e52540565b935487303a64409d
03026e632484f2eba966725df460ac84cd790bed
203958 F20110109_AADJPY brown_t_Page_37.jpg
7cce1d898ab6a895388f91dc9ba3e2e1
455d2a975405258a0de51bb38471f307d95820e6
76933 F20110109_AADJZU brown_t_Page_43.QC.jpg
ef8d2b137492b832cce7d0b430e3c21c
7336392ff259f52baee68be1190584a208b2134a
44590 F20110109_AADJUX brown_t_Page_36.pro
d86affd400f3bd13c1de4d91ce284289
9b33fb83017f1985318426d5f0cdc0fc8d79232e
210952 F20110109_AADJPZ brown_t_Page_38.jpg
b6cec4a0b3a82e3e1094aa152aeae614
a9fe279edb3dd434de227df23eaff25fb774f451
47987 F20110109_AADJUY brown_t_Page_37.pro
8271baf86851f417360eaa8ac9038a3a
bc7c752cf2b403c9d5be4d0720bcd174aeaee140
24070 F20110109_AADJZV brown_t_Page_43thm.jpg
f9e4058677387ef4755eabbe9b481012
c5521005ffb430b6ec47392f7755c7354edb6840
F20110109_AADJSA brown_t_Page_03.tif
c7aa3b15eb066865105230cdf48ed247
d0f282f020662b52cddb61b615473e430d2c0fdf
50196 F20110109_AADJUZ brown_t_Page_38.pro
425848b404523751ec69d2a1aad08364
b6b2bd187db393be8db5b17780aac7d9b3763af3
46285 F20110109_AADJZW brown_t_Page_44.QC.jpg
155d52d1a889df1814aad272c2688b68
a9d361d81483e59aaecae9eacb579f573cfbee3b
25271604 F20110109_AADJSB brown_t_Page_04.tif
d34828702d23fd3eb9efc944f02b3d23
bc0c84f7eff2fb6aaf9b216f7fb1cdb42ebcf33e
28034 F20110109_AADJZX brown_t_Page_45.QC.jpg
70c5b1630b723fa34297eaf77e0db7f4
7b95178905fa711bb8f0ff0a6fed04e5bc401737
F20110109_AADJSC brown_t_Page_05.tif
d267116fe3ec33bd8b05519766cddb2b
e609f99418347dd4f10c4307c98ef558c2038595
9028 F20110109_AADJZY brown_t_Page_45thm.jpg
fb232106c01263de9fd8d8e860f08c80
eb01d1dd807f169171702f33252f7944343ee1eb
F20110109_AADJSD brown_t_Page_06.tif
75ace716bf738d6932216281d60e635a
83c67848f434e9aa05810a460090e06ce7fc1891
70516 F20110109_AADJXA UFE0001240_00001.xml
727abdbb41fcb77ae871aa44e3a1596f
e2c403517b69a3e6bc02c8ea849b71f8700b2f86
F20110109_AADJSE brown_t_Page_07.tif
c40203257ba8ed11e8e17ff4c40a9ec4
51068f7f8518be0bf1029074074a4058ddac3f92
5823 F20110109_AADJXB brown_t_Page_02.QC.jpg
d8099a3f6d5508ca6f12d0daf30ef434
e10b5e11fef1df297b1f04b6db016e014d04e3e5
F20110109_AADJSF brown_t_Page_08.tif
57407f86f5eb2327ddb09a489cd54ba7
cafe6008e2da868362fb26566701df41cbaa7435
3109 F20110109_AADJXC brown_t_Page_02thm.jpg
f7063520bd8b941c9c3a93a056b0eabd
cd3454a2852eff979b12864e6c1196ee0bd918f0
F20110109_AADJSG brown_t_Page_09.tif
da605040695e95d71fc0e18763d13efa
98bdae6b4f8082d8eacabaa2e7705f4496343f24
33871 F20110109_AADJXD brown_t_Page_03.QC.jpg
6da1e4102c0305a4aadfbbc2eac8b186
ef1c97094467adee46cc43e8794bc53f993846c4
F20110109_AADJSH brown_t_Page_10.tif
2d0e90f12269957e7f583b591594978b
2771674be976b6549e21eb7598821431f7d53eda
11296 F20110109_AADJXE brown_t_Page_03thm.jpg
ae371c48fae99448899c0e330eaa3cdb
23acf4f9aa6c5521449393188729a3708bbb026b
92124 F20110109_AADJXF brown_t_Page_04.QC.jpg
46892e1856cf109dcd80afd49519c5d9
e3b9b8dcb9e698994f1ec19d883a67020447fc42
F20110109_AADJSI brown_t_Page_11.tif
c610d732fb69290212ca515aff7b3426
f8310aee697b9ae3b2a8267d4c1b62f93713585e
46856 F20110109_AADJXG brown_t_Page_04thm.jpg
f7ee3de2ca08cb62d696370c0c3c9616
3d5c5c8644e1b04a2bb95c5311050a2a2e2f5ae4
F20110109_AADJSJ brown_t_Page_12.tif
9092d680032f002ab3010fd5a23fd49b
9a95deb096812e41852af43daff6f94f9130d8fb
35846 F20110109_AADJXH brown_t_Page_05.QC.jpg
b06f0c8d81ac67dd2013830abbf99e21
91b95e01536fb75d699278fcd00b29bb32afb045
F20110109_AADJSK brown_t_Page_13.tif
7ef463971b01d34e97a566b8f26e82ca
ab0624c576e38205f111fcc6308f8853cef664fe
29938 F20110109_AADJXI brown_t_Page_05thm.jpg
46c400c7342b59947df635e2f41d789a
7cab26028265680be90215abc5052ce3334a2d62
F20110109_AADJSL brown_t_Page_14.tif
b1b36487ebb33628a8d440b9fdde23f4
dcc720052ec198e8b7157dc48364b144bd98958b
52945 F20110109_AADJXJ brown_t_Page_06.QC.jpg
e42834ca6494ea05127f67255595c457
892d4501e778365fb74c8cc23d08f69aa3457a4e
F20110109_AADJSM brown_t_Page_15.tif
68b1b032931c217f1db6a618408f8ebb
1631f954e68e2b048ed2a98fe839f866c3a3f632
33799 F20110109_AADJXK brown_t_Page_06thm.jpg
70bd12cdadc0f97297476eeb1cb9a08e
6de5e2fd2124738bf06d922e409f3206081e92c5
F20110109_AADJSN brown_t_Page_16.tif
5dfe70f83bd0b7af6f8c9c2345154461
5f576d713b11cf194ecf1cdaf0a5eb97c29a4d39
11850 F20110109_AADJNR brown_t_Page_34.pro
cd2b212f715daff19eb4282b1bf8bb15
b020e12724ac713ec54265d1da29b2183fe4b1fa
61438 F20110109_AADJXL brown_t_Page_07.QC.jpg
da2b25cff5736ab0a2667fb54fb73c41
d4d82ac989bed44c180864b7859e1d8db9f93f06
F20110109_AADJSO brown_t_Page_17.tif
f1327dd9b3c2051fa24ba6995fe7b843
2ce717dcbca17cb70512fef29b30158e717e1bd4
55764 F20110109_AADJNS brown_t_Page_35.jp2
eee0017318556c0314cc33ab783f87a4
d42dea0a49ed41e7a2f994796c27bc6a4a9eaddf
19360 F20110109_AADJXM brown_t_Page_07thm.jpg
126b424fd0d842c02d2baece66246436
c06caba7a2a1f1e57dd48ea72a748915ef0b3533
F20110109_AADJSP brown_t_Page_18.tif
0ab814597128ef45772c3fd46f2158a0
9e1746c772512bf9fb036da59e1c8ef34db453eb
1976 F20110109_AADJNT brown_t_Page_38.txt
4c4afdcb6e55af84d48fece4ab41ca4a
1fe8dbb2f4d0af45132eae04bc9c8b8c37e773b3
12206 F20110109_AADJXN brown_t_Page_08.QC.jpg
345510be3fa8ef39f809e7e845cb0224
70294b697b490305a94f1367d1efdc26b2025852
F20110109_AADJSQ brown_t_Page_19.tif
e6428f15668ca2afe0f01a1cb6cdc1a1
0dea1847bdf1170fe0a12a95817da21c4b43c015
1838 F20110109_AADJNU brown_t_Page_36.txt
10a293d7cf13ace3a3e8699c4ae2f7bc
2afc98731c4dec7694e82ca9751f423b9e25ec91
4757 F20110109_AADJXO brown_t_Page_08thm.jpg
fbb5d5dc54902a496d16be70fb9b5667
8566e70edfadb1d20460e6d0c0ed52409c30de7a
F20110109_AADJSR brown_t_Page_20.tif
cd262d8ab809cc23b8cb8403b656a25a
9cff362e2541709c115e3301443ee00e3ded29b9
16424 F20110109_AADJNV brown_t_Page_24thm.jpg
7a30b22c8a58488433fb188c92aae196
a87ebdc9ad74cde50cf20d7a8af303275887d178
22467 F20110109_AADJXP brown_t_Page_09thm.jpg
6866a19bd40780a1896a9a5aaacbbd55
795bfa106be2a8498dfc0b9d9d339bd84b66eac6
F20110109_AADJSS brown_t_Page_21.tif
4c5536d47643e516b66bd0691c5d984d
2a0260774ca0cc3255d1990add2d34d7443f38d4
66770 F20110109_AADJXQ brown_t_Page_10.QC.jpg
430a9c21d2c63267ce2c3ae3d0fd2a3a
ab81ca48e47029feaf386adaf1714104c64610e0
F20110109_AADJST brown_t_Page_22.tif
70559ea2ab1d60023b21486e7d04ae90
277abdbcbba749fa062469f88462fd34b2bf13d3
114400 F20110109_AADJNW brown_t_Page_20.jp2
975124412bebbef501153898a8e49a50
9902e6e5b178918dada46df45da20c7870a27d93
21833 F20110109_AADJXR brown_t_Page_10thm.jpg
ffb2d1c43d15a5644e462bc24b0ef974
dea881d3be9498b6871e5e55e7c1f79266fdf0d3
F20110109_AADJSU brown_t_Page_23.tif
054191cf95500dc88e71992b1d918d88
01d76fd79c7bc435599fc21c8b32599ba48854ff
24854 F20110109_AADJNX brown_t_Page_14thm.jpg
7f371738b6957e030b9fb72afc62cc77
07aa57b7965adce6210120e39a0eed5a61389925
66525 F20110109_AADJXS brown_t_Page_11.QC.jpg
da494349073d60fecd4d191539b1746f
ad03da9c780e3175d93e76b9928089e2baa562e1
F20110109_AADJSV brown_t_Page_24.tif
828e20f5978acefd7c0c960aeb5e8c76
9042248559cf6eb2e872561e991255c68562415a
23316 F20110109_AADJNY brown_t_Page_26thm.jpg
3252446a892318d34ff6d565ccb84168
3ea69f298e54d1d12a2ca05ca0cab5f6a0c7ae8a
21286 F20110109_AADJXT brown_t_Page_11thm.jpg
f16be56179b8f5a5aff601ccdeaebb82
04d08a4f8c9adb60fc6247b0d66f3e2f3bb73b8e
F20110109_AADJSW brown_t_Page_25.tif
fc59192314f767b47c01aea3af2f1702
8be92c91ff31ff9ace32a737ffb26beb7824590d
F20110109_AADJNZ brown_t_Page_38.tif
a5f92be74c71672b63ecc3c78d6fdd8e
b3bf7a7d286515319c3679d834f921b7544a386f
83821 F20110109_AADJXU brown_t_Page_12.QC.jpg
6d29f53bf8eda5a53adcf747d8642dcd
87dcc957e54357b80af7efbb97918acd25150521
F20110109_AADJSX brown_t_Page_26.tif
799e15759f8869335c821c5c4162ac11
8f415b8322cb9f1224a093b7ba6f36fe4fc16cea
24930 F20110109_AADJXV brown_t_Page_12thm.jpg
0bc9856e2f4a64fbe3754057f50a3c00
aa5bfb3007f4c48d9dc80923c767a9913b5784d9
F20110109_AADJSY brown_t_Page_27.tif
f95a79c1b39fcd921661d1c36fe2f243
9222d00237d1e1463979d6a51a3c6e280a0feb29
82153 F20110109_AADJXW brown_t_Page_13.QC.jpg
57247a09170fbe96441d559a51599fb9
efc458aa83b2205d5929d50e112d18049ae7c71a
210947 F20110109_AADJQA brown_t_Page_39.jpg
d2b8cdc0988da2eb964f67044e531424
a379bbf2955ab2d82681e06714462af07cfc9867
1054428 F20110109_AADJSZ brown_t_Page_28.tif
2a31fa50541ef038bc58db835f5933d5
5c2e7d64571f19dff97b1fa912f8d8cb8c7ffe59
25804 F20110109_AADJXX brown_t_Page_13thm.jpg
6bfdf24121694f3ef17e0ca60c7e19d4
5f3e6256dd09b9eefc046794680841d74eb05371
201121 F20110109_AADJQB brown_t_Page_40.jpg
b96a30e464afddef90cc655b6a01ab7a
a0bcbf0aa75c265b427283e2508a2e1271407ade
79319 F20110109_AADJXY brown_t_Page_14.QC.jpg
bbf94166a5077bea2c6077a4de452d43
f6d19a6952f0ede7026fa6824783329747940253
99135 F20110109_AADJQC brown_t_Page_41.jpg
210902fcddc25a1a198b9a68654ea171
322326e09224ceb48727ad8926db54b4b7c8b968
50934 F20110109_AADJVA brown_t_Page_39.pro
0b0e091bf297a570f0a4d955a24d574e
75c0e72bef6ce337afd6876bd5c6b77971a8aea4
67945 F20110109_AADJXZ brown_t_Page_15.QC.jpg
b319cfd7de46553c6582e557d616a6b3
237fb32255590beea05e06638c9b383af07b9f23
206350 F20110109_AADJQD brown_t_Page_42.jpg
3a926668662557dedd4785a9acd5d74b
fa8d16b8319e004778c8ed6b0b1b76e7ba3202e3
47883 F20110109_AADJVB brown_t_Page_40.pro
dce3412fa2ee414625d7ce3108958335
8480e35485f292774632fae70cc1415a54a8f818
236697 F20110109_AADJQE brown_t_Page_43.jpg
16f3f235ae14947dd693d7bafed2f6f2
318c21cedfb46cde9928aaa628831bf11645600d
22235 F20110109_AADJVC brown_t_Page_41.pro
9d60a5ae8634f423a17df51f622e5aae
1658dea0a6c1f66f49ac6ba0fe334469f2826481
145129 F20110109_AADJQF brown_t_Page_44.jpg
4314bd02b0d44eb18b2511595af270e3
2f800e748c12b78268e6b045342acdbfd85a95c9
49823 F20110109_AADJVD brown_t_Page_42.pro
4903535022e4ea120879be9a67a8044f
851cedd3affb2473279481369377ff5f954b75ee
71421 F20110109_AADJQG brown_t_Page_45.jpg
2c4552687deace42a332d125d942ac36
157c427a3031b138312bc2f6c21426e96206af49
29601 F20110109_AADJQH brown_t_Page_01.jp2
c9a417e16d9ddead93b208a65c5bfbad
1111abba6bd44b68657c9c407ecbb243dd6af129
55690 F20110109_AADJVE brown_t_Page_43.pro
d6a4fd8c2099e5487984e01978e8524f
0ee3c263c6734a75f08ebf5770100b75e5226173
5482 F20110109_AADJQI brown_t_Page_02.jp2
66d35f288667cf68005a8d301f15a856
4bf0fad023d3d501602345252b6712d808393bae
30166 F20110109_AADJVF brown_t_Page_44.pro
b70192dd728818e9be9971c0b7473338
3f33c77ad8e98e1518fffc06b1b3a590a0998a28
43504 F20110109_AADJQJ brown_t_Page_03.jp2
4ce4c597321417e2930f71bfbc4b1f9a
8aace94613956050156d70d8470612fa511a49d4
541 F20110109_AADJVG brown_t_Page_01.txt
6f71abe3c64a4d613b51bf0950eeb6e3
6f263df5dcdd33324f5f8fb8e2344f9f38110190
1051959 F20110109_AADJQK brown_t_Page_04.jp2
6e70d481bdb618c0e352341f2ea6d108
82f9989983b40fee069abd4dbad957def4330da8
111 F20110109_AADJVH brown_t_Page_02.txt
5aa397defb1f3f5cc7e016d30a9109c5
6057d116401644498b94ab3ec1e0f5220a23eb2c
217713 F20110109_AADJQL brown_t_Page_05.jp2
ac8d12e72708b5f80642201a72c9b1b2
76d75b01d1b13805643e46459a6c59c8d0533c65
789 F20110109_AADJVI brown_t_Page_03.txt
ea8c6afa3750ed4e985b06c5964ff7bd
236df8213d4745e0159fc3540ecde6bba774ca64
552396 F20110109_AADJQM brown_t_Page_06.jp2
372d945bd9cbc8e14af44f582b0db378
600a3371472cfc5c6beee8abba8b993d12f5da79
2784 F20110109_AADJVJ brown_t_Page_04.txt
b4ff1ff2abb25113cc9aa3197f9f55fb
014cda9c1c5b4a876a4a0e43ce6408503d4cdfd9
86290 F20110109_AADJQN brown_t_Page_07.jp2
957709153e644440d5ed2805dcd5dda2
2da2c0d61bf4b76f87958df7c80ce42ee159ba72
506 F20110109_AADJVK brown_t_Page_05.txt
8ba60a7312dfe3a02a69bfe5a248ef1c
47d272a73b684d401de225d0311630a97aecb4f1
13317 F20110109_AADJQO brown_t_Page_08.jp2
c8e652bf33021376a10286dc0db56243
16c9a05c9266ed6e4051f551e1585c320a591447
646 F20110109_AADJVL brown_t_Page_06.txt
d41e17bb6cbfd381e5ad12057ee522b8
e4ace786ed306012d697ff55359e439100ac2c9c
99108 F20110109_AADJQP brown_t_Page_09.jp2
8826900c860ee7476b810b8b0caef8fc
b78ac91030779bf083f37b5eb0fbf3eb5b3897d0
1705 F20110109_AADJVM brown_t_Page_07.txt
8718cd8d364075c9fbbc23c05ca796ef
4f54300f5b576beac0e095da40ea1eecf577d49d
94785 F20110109_AADJQQ brown_t_Page_10.jp2
497b141056d2d6948beabbff2e52e537
6a13db0017e038dd49ad8b3ba20d67b71d471462
194 F20110109_AADJVN brown_t_Page_08.txt
e8a6b23cfbff24414d5076a7e7e89230
3cd6160cb986d717c4905d8e68f8f17c0eb01f02
93404 F20110109_AADJQR brown_t_Page_11.jp2
7d9cd58d4808f843fca320196e118d8f
4858fa1ff6be192a98b143af79a200166c50e8a7
1867 F20110109_AADJVO brown_t_Page_09.txt
4c69efae1bdfb444dec654a97bfe55b5
4e6f98c9451b190d3ef05f333ddcba4eda67ce2e
113223 F20110109_AADJQS brown_t_Page_12.jp2
97a4a8ac7507f16707643b3eec75b2f4
00367044b8fe6fc64c89e8b89c3454026dd6bf60
1717 F20110109_AADJVP brown_t_Page_10.txt
6e3aeb72462acea6c0225c2f08c2e3df
5e6090e846029663da6564f4f7954f02ae6a24cf
114840 F20110109_AADJQT brown_t_Page_13.jp2
bae5ed94f8eedcf8d1d27a380fd3f742
498608439354a4070c3bf9dc516e678ca9c5e646
1788 F20110109_AADJVQ brown_t_Page_11.txt
c8f38f56ec1643d72ca891e84d3d0eef
fb10ea48c5102f79777ccdc00d00e4a65ee9174b
107812 F20110109_AADJQU brown_t_Page_14.jp2
52f84e4e7a419d324103ad3d2f738a14
7b5932850207dfd391c650c04d869063fd2f4f1f
2071 F20110109_AADJVR brown_t_Page_12.txt
7ab54aa3b6565df8258d4de749ea3f86
f70656d16bbb969780643a1f7be1106eefe33a95
99013 F20110109_AADJQV brown_t_Page_15.jp2
a3bd54e7d21f996a375669892a674694
a90fa49d1c41de7050fc28aef457735f066bee9a
2091 F20110109_AADJVS brown_t_Page_13.txt
68e21f25703aa08f74ebc2e68f32046b
f4a657b028b357cfc61081e8ea5a23eaf0658cb8
22558 F20110109_AADJQW brown_t_Page_16.jp2
79d66b4ae415ed2c1f34400724edae86
713d2bb621507121e15a7b9a129f86a63fe1a726
1974 F20110109_AADJVT brown_t_Page_14.txt
957d0cd02eb2a93b4513c258cfbcedf7
5ab736cb336ce66d60a2d137bba1921293d42957
95356 F20110109_AADJQX brown_t_Page_17.jp2
7a42c32c697c48b45f9ad060609447a7
cb09d972dcfdddc7b7dd33ed072af0d0f8f81c33
1820 F20110109_AADJVU brown_t_Page_15.txt
f500662ff15a8638b4cd0b096e80286c
2d0520835906dae67dec36194d8ca54911646bf0
112078 F20110109_AADJQY brown_t_Page_18.jp2
815b7e9eb1d4734a839827f3d836202c
590f3b28fdc7006c9891d140a7fd94dfbcd1f6e9
438 F20110109_AADJVV brown_t_Page_16.txt
35f4f8916da5d0813599454dc4fad4fe
4118f2f30cc2d2127e4f76e42191d72e008a4f4d
1791 F20110109_AADJVW brown_t_Page_17.txt
d3d54f6eaf39f0085dd5a82a63f38010
f31170a90dd449b057f3e61c2cdaa8115527856c
71664 F20110109_AADJOA brown_t_Page_09.QC.jpg
5100e5dee0df9b4367a6b9a80b62e6a3
4e863f6d52e0b74f16b6c3602812af8ca77ee492
102934 F20110109_AADJQZ brown_t_Page_19.jp2
31ff39540ae551459527c78079c97abd
ca5eac40cf2e14999b5db12b6798033e240bb358
2062 F20110109_AADJVX brown_t_Page_18.txt
5aa31d8c6d4918ade01e9a695dfb43e2
a5af59b7ab51987821d59cf5db97889a86d29e2e
25547 F20110109_AADJOB brown_t_Page_20thm.jpg
210788421c2eda56bb7673aa67a18164
dbe6b282a08bf4198a3211fc98e18ace51350a55
1888 F20110109_AADJVY brown_t_Page_19.txt
878b9505199d1244309ea61e2039aab1
48a2b55d8af69c21c25d58f249cb6b89e163402f
13191 F20110109_AADJOC brown_t_Page_35thm.jpg
a6703cfbfd20d8cee8e077f3a6962e84
165e7247fba297cd6bb56e3e48e4f6c8800fcf78
F20110109_AADJTA brown_t_Page_29.tif
69a158167611a0ae753ce9e194131350
0e13f38ff9085eb0eb3ceade8082e547ea2a51fc
2076 F20110109_AADJVZ brown_t_Page_20.txt
eb7f1109e212af007c2e4c528a0ca381
0a0301c72a14c38228237e097792aa0ebd34472c
5861 F20110109_AADJOD brown_t_Page_34thm.jpg
76199f0d6d31ca579da5aec5890d82d1
3707f12d7f573c390ce950d5c89a624a4ee163a7
F20110109_AADJTB brown_t_Page_30.tif
dc5800377d823e13909d8e67d4373a72
7c4820cdd4d6c9f9afc12d0ba7bbf0bc3c11ba9f
83788 F20110109_AADJOE brown_t_Page_03.jpg
f8e0c524d4a587a2488ea1bd609cfce0
37a337b98aa590ae86e84348f5df4dfb92909964
23382 F20110109_AADJYA brown_t_Page_15thm.jpg
8ad6f65287a7c91f8dfc8cb2adb2eed8
68e06346518fd1afa73a0a9e912bde5e96d1ccc0
F20110109_AADJTC brown_t_Page_31.tif
0b9042dcdfb0335a19403cf166154c21
cb42ec60147b46fdfc52f6df4fdee4cfafdbccdc
30437 F20110109_AADJOF brown_t_Page_23.pro
756fdaedb9131527df1c88149c68d21e
e7727945ce645f3b66bc98011205c5b6e4af31b9
F20110109_AADJTD brown_t_Page_32.tif
44ef52b816bdab66bd146a123f2701ae
d0b879ea7226ef223ae2c1af536d3d76feadfd3e
1895 F20110109_AADJOG brown_t_Page_37.txt
5462e86159226983af23c58bf6aaecbd
1a2e7528e9730e45eb269065b1e684a0dd15dcad
F20110109_AADJTE brown_t_Page_33.tif
2704c0eb4daac8c9c0c24a183ccfc3fc
3edc0dfdba34e7175ac218ecb7d0d6236b2a9050
14250 F20110109_AADJOH brown_t_Page_44thm.jpg
71b3118bef1bbbf7f7da403389f3b759
d86b22df86c48b25131fe9f0ebcaf40274b93796
5905 F20110109_AADJYB brown_t_Page_16thm.jpg
1b2f003111989be3a0354756b71c743c
9dc879961cbea71e241be618b30f1637598fedec
F20110109_AADJTF brown_t_Page_34.tif
ce7340f164f7ae36fa74017d58271bfb
7615a83f51044a8658108e75c5e5084dff35145a
15564 F20110109_AADJOI brown_t_Page_16.QC.jpg
24edab58350d93e6d17864621900a31a
4d68541f894d94777dff5f2a007180fe4ed171b3
67445 F20110109_AADJYC brown_t_Page_17.QC.jpg
e019a0c8dc0e2f9e66394789c88564fb
2acc7bfa7080025d69f6f5abd1b1d6367d57b1ea
F20110109_AADJTG brown_t_Page_35.tif
199a51763600d3f4d3a2ae1ca0281dde
bfb096156c3a317133610fbb21b528c2bfb31af6
23763 F20110109_AADJOJ brown_t_Page_37thm.jpg
86ad9d86dc3c1ad65d63c037f651e207
3e4fddf597a1a62fac514fbe5385c262365147f4
21411 F20110109_AADJYD brown_t_Page_17thm.jpg
350c95b6e1a3dd95ed5a36a6cc0c64a6
fa807d3c866adc6da48281d43d42a136e8d99b17
F20110109_AADJTH brown_t_Page_36.tif
ee4c7e4e92b1ecd4e174e9fe23ce689f
59b4131e05b237232a70b87137691092777db4d3
82506 F20110109_AADJOK brown_t_Page_18.QC.jpg
01398baac6581be2664f2d021a50dbdd
d312deb655fdf1e7014f21ba988c325da75c462e
25935 F20110109_AADJYE brown_t_Page_18thm.jpg
466b0577edaef1b22dba0aa032b6c660
2c51e65f243cd5c5c983d29c64eb67a0324b883f
F20110109_AADJTI brown_t_Page_37.tif
ef5180a59f655c2b702d890ebec7b686
858dfeaeb1ccf600e148521987cb11846b60b0b2
15080 F20110109_AADJOL brown_t_Page_45.pro
ccdb490886e1ab5c02a24c13d879d9db
272d7e6fa38ab4893f5e5d0524b5992a929a2e52
75713 F20110109_AADJYF brown_t_Page_19.QC.jpg
b83159a088fb2d7c1da0a1bc05e59442
6b73de3f96efd4af2f6a7d751dd1b63d08596235


Permanent Link: http://ufdc.ufl.edu/UFE0001240/00001

Material Information

Title: Divergent pathways: an analysis of racial differences in risk of retirement and work disability among African American and white women in the labor force in later middle-life
Physical Description: Mixed Material
Creator: Brown, Tyson H. ( Author, Primary )
Publication Date: 2003
Copyright Date: 2003

Record Information

Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
System ID: UFE0001240:00001

Permanent Link: http://ufdc.ufl.edu/UFE0001240/00001

Material Information

Title: Divergent pathways: an analysis of racial differences in risk of retirement and work disability among African American and white women in the labor force in later middle-life
Physical Description: Mixed Material
Creator: Brown, Tyson H. ( Author, Primary )
Publication Date: 2003
Copyright Date: 2003

Record Information

Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
System ID: UFE0001240:00001


This item has the following downloads:


Full Text












DIVERGENT PATHWAYS: AN ANALYSIS OF RACIAL DIFFERENCES IN RISK
OF RETIREMENT AND WORK DISABILITY AMONG AFRICAN AMERICAN
AND WHITE WOMEN IN THE LABOR FORCE IN LATER MIDDLE-LIFE
















By

TYSON H. BROWN


A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF ARTS

UNIVERSITY OF FLORIDA


2003


































Copyright 2003

by

Tyson H. Brown















ACKNOWLEDGMENTS

I am especially thankful for my chair, Amy Pienta, for her endless support and

expert guidance throughout my graduate training at the University of Florida.

Many thanks go to my cochair, Chuck Peek, for his help-especially in the early

stages of my training. I am also very grateful for contributions from the other members of

my committee, Tanya Koropeckyj-Cox and Bhramar Mukherjee.

I also would like to acknowledge John Henretta, and express my gratitude for his

helpful comments.

These remarks would be incomplete without giving special thanks to Terry Mills

for his consistent support during my undergraduate and graduate education at the

University of Florida.
















TABLE OF CONTENTS

page

A C K N O W L E D G M E N T S ......... .................................................................................... iii

LIST OF TABLES ........... ................... .............. ....... ....... vi

CHAPTER

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

2 B A C K G R O U N D .................... .... ................................ ........ ........ .......... .. ....

Life Course Framework and Retirement Behavior.....................................................3
Race and R etirem ent A m ong M en ........................................ .......... ............... 3
R ace, H health, and D disability ............................................................................. 4
Race, Wealth, and Retirement Behavior............................................. ...............5
Race, Family Characteristics, and Retirement Behavior............................................6
Race, Work Characteristics, and Retirement Behavior ..............................................6
Race, Education, and R etirem ent Behavior....................................... .....................7
R research H ypotheses .................. ................................ ........ .......... .. ..

3 RESEARCH DESIGN AND METHODS .................... .......................................9

M easurement of Labor Force Behavior.............................................. .................. 9
Measurement of Sociodemographic Characteristics ...............................................10
M easurem ent of H health .................................................................. ...................... 11
M easurem ent of Fam ily Circum stances ........................ .. ................... .................11
Measurement of Midlife Work Characteristics ...................................... ..................12
Measurement of Midlife Economic Well-Being ................................... ................ 13
A n alytic Strategy ................................................................14

4 R E S U L T S ............. ..... ............ ................. ..................................................1 5

N ested m odel strategy......................................................... .. .. .... ........ ......18
Retirement behavior among African American and White women .........................19
Work disability among African American and White women............................. 23










5 DISCUSSION ........ .......... ...... ....... ......... .......................28

LIST O F R EFEREN CE S .............................. ......................................... ............... 34

B IO G R A PH IC A L SK E T C H ...................................................................... ..................37























































v
















LIST OF TABLES

Table pge

1. Descriptive Charcteristics of Women in the Labor Force at Baseline by Race .......16

2. Baseline Labor Force Status by Race............................................ ............... 17

3. Measures of Physical and Self-Rated Health by Baseline Labor Force Status........18

4. Risk Ratios from Proportional Hazard Models of Retirement..............................20

5. Risk Ratios from Proportional Hazard Models of Work Disability.........................24















Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Arts

DIVERGENT PATHWAYS: AN ANALYSIS OF RACIAL DIFFERENCES IN RISK
OF RETIREMENT AND WORK DISABILITY AMONG AFRICAN AMERICAN
AND WHITE WOMEN IN THE LABOR FORCE IN LATER MIDDLE-LIFE

By

Tyson H. Brown

August 2003

Chair: Amy M. Pienta
Cochair: Charles W. Peek
Major Department: Sociology

The purpose of the present is to explore the labor force exit patterns of African

American and White women. Inattention has been give to racial disparities in the labor

force exit behavior of African American and White women. Previous research on racial

disparities in retirement behavior among men indicates that, compared to White men,

African American men are more likely to exit the labor force via retirement or work

disability. The present study uses five waves of panel data from the Health and

Retirement study and the life course perspective to explore racial disparities in labor

force exit behavior among women. Analyses suggest that African American women are

disadvantaged relative to White women with respect to socioeconomic circumstances,

family patterns, wealth, and health. Importantly, results from multivariate event history

models indicate that, compared to White women, African American women are less

likely to exit the labor force via retirement and are more likely to exit the labor force via









work disability as a result of their lower levels of human capital, wealth, and health.

Theoretical implications of the present study and policy relevance are also discussed.














CHAPTER 1
INTRODUCTION

The literature has shown evidence of race differences in retirement behavior.

However, most of the research has overlooked women, with only a few exceptions.

Researchers have found that African American women have more continuous patterns of

work throughout the life course than White women (Belgrave, 1988), a finding opposite

that found among men, which suggests that the race-retirement relationship may also

vary by gender. This also underscores the need for further research on race differences in

women's labor force exit pathways. The few studies that have explored race differences

in women's retirement have used different cohorts and measurement strategies and have

shown mixed results. For instance, Belgrave's (1988) study of women born between 1917

and 1921, used cross-sectional data and labor force participation rates (LFPRs) to

demonstrate that African American women have more continuous patterns of labor force

participation throughout the life course. Pienta, Burr, and Mutchler's (1994) cross-

sectional analysis of the 1920 to 1929 birth cohort, on the other hand, operationalized

women's labor force participation as full-time work, part-time work, or not working.

They found no significant race differences in women's labor force statuses.

Although LFPRs have been the basis for much of the previous retirement

research, LFPRs have masked important race differences that are revealed by further

classifying individuals who have exited the labor force into disabled and nondisabled

groups (Hayward, Friedman, and Chen, 1996). Distinguishing between retirees and the

work disabled rather than relying solely on labor force participation rates may provide









additional insight into the race-retirement relationship among women and thus imply

different policy targets. Further, Hayward and colleagues' (1996: S9) conclusion based

on men's data that "Retirement is more of a White experience than a Black experience,

while the reverse is true with regard to disability (among men)," underscore the

importance of examining whether their findings hold true for women.

The present study explores racial differences in women's labor force exit patterns,

using retirement, work disability, attrition, and death as competing outcomes, with

attention to the intervening effects of sociodemographic characteristics, work and family

histories, health, and wealth. The present study aims to address two primary research

questions:

1. Do African American and White women have different rates of retirement and
work disability in late midlife?

2. Do racial differences in women's labor force exit behavior stem from racial
differences in human capital, health, and work histories?

Racial differences in education, economic resources, family patterns, and health over the

life course are expected to contribute to divergent labor force exit pathways. Given

African American women's higher labor market attachment throughout the life course

(Belgrave, 1988; Brown and Pienta, 2002), lower rates of marriage, and fewer economic

resources, relative to White women, African American women may be less likely to

report exiting the labor force for retirement. Conversely, work disability rates may be

higher among African American women, stemming from racial disparities in education

and health.














CHAPTER 2
BACKGROUND

Life Course Framework and Retirement Behavior

Much of the previous research on retirement has been based on the retirement

behavior of White men. However, retirement models based on the retirement of White

men may be inadequate for explaining the retirement behavior of women, ethnic

minorities, and the chronically poor or ill (Burr, Massagli, Mutchler and Pienta, 1996;

Gibson, 1987; Pienta, Burr and Mutchler, 1994). Historically, these populations have

been disadvantaged in terms of education, career mobility, income, wealth, and health.

Given well-documented race differences in education, health, wealth, work and family

histories, a cumulative disadvantage framework may be useful for devising a model of

race and labor force exit patterns among women. The cumulative disadvantage

framework is an extension of the life course perspective that assets that social inequalities

in later life are a result of the interaction of institutional arrangements and aggregated

individual actions over time (Dannefer, 1991; O'Rand, 1996). Conceptually, the present

study explores the possibility that race differences in labor force exit behavior may be a

consequence of African American women's greater lifelong disadvantage with respect to

education, work and family characteristics, wealth, and health.

Race and Retirement Among Men

Given the sparse research on women's retirement and race, much of our

understanding of race differences in retirement come from studies of men. African

American men have more discontinuous patterns of work history than White men









throughout the life course (Welch, 1990). Older African American men are more likely

than White men to be outside of the labor force (Bound, Schoenbaum, and Waidmann,

1995; Hayward et al., 1996). Also, African American men are more likely to delay entry

into the labor force, more likely to have gaps in employment histories, and more likely to

permanently withdraw from the labor force. Disability is a major contributor to older

African American men's lower labor force participation rates (Hayward et al., 1996).

Wray (1996) found that in addition to health, job characteristics such as pension

coverage, retiree health insurance, and spousal retirement benefits were partially

responsible for African American's higher rates of disability. While there may be

multiple plausible causes for racial differences in disability status (see Gibson, 1991;

Parsons, 1980; Welch, 1990; Wilson, 1987), several studies have shown that health is a

dominant and temporally proximate factor accounting for African American men's lower

levels of labor force participation (Bound et al., 1995; Burr, Massagli, Mutchler, and

Pienta, 1996; Hayward et al., 1996). Although previous research indicates that LFPRs

may be more similar among African American and White women than they are among

their male counterparts, African American women's poorer health, relative to White

women, may place them at a greater risk of becoming work disabled.

Race, Health, and Disability

Health conditions are likely to provide additional insight into differences in the

retirement behavior of women. African American women have poorer physical and self-

rated health than White women. More specifically, compared to White women, African

American women have a higher prevalence of diabetes, hypertension, heart disease,

strokes, and functional loss (Blackwell, Collins, and Coles, 2002). A similar pattern

emerges with respect to self-rated health, whereas 19% of White women between the









ages of 45 and 74 rate their health as either fair or poor, 35% of their African American

counterparts do so (National Academy on an Aging Society, 1999). Given African

American women's poorer health, and the finding that men with poorer health are more

likely to be work disabled (Bound et al., 1995; Hayward, Friedman, and Chen, 1996),

African American women may face a higher risk of work disability than White women.

On the other hand, Pienta and Brown's (2001) study indicates that, for various reasons,

health may have less of an impact on women's labor force participation than men's. An

investigation of temporal antecedents of health disparities may provide a more complete

understanding of the race-retirement relationship among women

Race, Wealth, and Retirement Behavior

Transitions into the "retired" status are also expected to vary by race and current

socioeconomic position. Temporally proximate factors such as wealth are likely to

intervene in the race-retirement behavior relationship. Previous research indicates that

women with greater net worth are more likely to retire versus continue working (Brown

and Pienta, 2002). Racial differences in wealth are great. While the median household net

worth among Whites in 1990 was $44,408, African American's median household net

worth was $ 4,604 (Eller, 1994). Even more striking is the fact that the racial gap in

wealth is widest at lower levels of income. Among individuals in the lowest quintile of

income in the U.S., the net worth of whites is 10,000 times higher that that of blacks

($10,257 vs. $1) (Eller, 1994). Race differences in home ownership and home value

contribute substantially to racial disparities in the distribution of wealth (Quadagno and

Reid, 1996). In 1994, whereas 64% of Whites owned their homes, only 43.4% of African

Americans owned their homes (U.S. Bureau of Census, 1996). And, whereas the average

home equity value for Whites was $78,708 in 1992, African American's average home









equity value was $36,658 (Angel and Angel, 1996). These findings suggest that African

American women may be forced either to remain in the labor force to maintain a

continuing source of income, or to delay retirement in order to accumulate wealth for

later consumption during the retirement years.

Race, Family Characteristics, and Retirement Behavior

Race differences in family circumstances are also expected to contribute to racial

disparities in retirement. African American women are less likely than White women to

be married, and among married women, African American women are less likely to have

a retired spouse (Brown and Pienta, 2002). Thus, given that unmarried women and

women with a spouse in the labor force a re less likely to be retired than married women

with a retired spouse (Henretta and O'Rand, 1983; Henretta, O'Rand and Chan, 1993a;

Henretta, O'Rand and Chan, 1993b), African American women should retire later. Earlier

family circumstances also impact retirement behavior (Brown and Pienta, 2002). Family

roles in early adulthood constitute initial pathways in the family life course that constrain

later work-related roles (O'Rand, Henretta, and Krecker, 1992). Compared to White

women of the 1931-1941 birth cohort, their African American counterparts are much

more likely to have experienced either a non-marital first birth or post-marital single

motherhood (Brown and Pienta, 2002). Therefore, we attended to the role of racial

differences in early family histories in contributing to racial differences in work and

family circumstances and ultimately retirement behavior of African American and White

women.

Race, Work Characteristics, and Retirement Behavior

African American women's work histories may mediate the effects of their

disadvantaged familial and economic circumstances on retirement. Compared to White









women, African American women actually have more continuous patterns of labor force

participation throughout the life course (Belgrave, 1988; Brown and Pienta, 2002).

Moreover, African American women have comparable rates of pension coverage and

pension wealth (Brown and Pienta, 2002). Among women workers, African Americans

are more likely than Whites to be blue collar workers (Belgrave, 1988), who are more

likely than white collar workers to retire (Brown and Pienta, 2002). Generally, African

American women's work histories and the expected push and pull effects associated with

such work circumstances indicate that African American women may be more likely than

White women to retire. Thus, work characteristics may suppress racial disparities in

retirement.

Race, Education, and Retirement Behavior

While the above text has focused on temporally proximate predictors of retirement

behavior, the present study's cumulative disadvantage, life course framework points

toward the utility of exploring the role of temporally distal life course conditions as

determinants of more proximate circumstances and retirement behavior. Consequently,

this study explored whether racial disparities in education may underlie racial disparities

in health, and subsequent labor force exit pathways.

Research Hypotheses

The life course perspective and the literature related to racial disparities in

retirement have been instrumental in developing several research hypotheses regarding

the labor force patterns of African American and White women in the labor force in

1992:

1. Poorer health may be associated with higher risks of exiting the labor force via
work disability






8


2. African Americans may have higher risks of reporting an exit from the labor force
via work disability as a result of their poorer health

3. African Americans may be less likely to report exiting the labor force via
retirement as a consequence of their greater lifelong disadvantage in terms of
education, family patterns, and economic resources.














CHAPTER 3
RESEARCH DESIGN AND METHODS

Data from waves 1 through 5 (1992 through 2000) of the Health and Retirement

Study (HRS) are employed to investigate race differences in women's retirement. The

HRS is a nationally representative panel study of Americans between the ages 51-61 in

1992, with oversamples of African Americans, Latinos and Floridians. Data were

collected every two years via face-to-face (1992, and 1998) and telephone interviews

(1994, 1996, and 2000), with response rates between 80 and 90 percent. The HRS is an

ideal source for investigating retirement behavior because it has extensive measures of

known correlates of retirement behavior such as sociodemographic factors, work and

family histories, and measures of health and wealth.

Initial analyses are restricted to African American (n=1018) and White (n=4134)

women between the ages of 51-61 in 1992. Since the primary focus of this study is on

labor force exit behavior, subsequent analyses are further restricted to women who are in

the labor force at the beginning of each interval.

Measurement of Labor Force Behavior

At each wave respondents were asked the question: "Are you working now,

temporarily laid off, unemployed and looking for work, disabled and unable to work,

retired, a homemaker, or what?" Since the primary focus of this study is on labor force

exits, women in the labor force are included in analyses until they experience either (1)

retirement (ceasing work for pay and not work disabled or unemployed or laid-off), or (2)

work disablement (ceasing work for pay as a result of a disability). The present study









uses event history analysis, based on a total of 11,483 "exposure intervals." Overall, there

are 3,301 events, of which 2,762 are retirements, and 539 are exits due to a disability.

Additional competing outcomes such as death and loss-to-follow-up where explored, but

are not presented in this study.

Retirement is becoming an increasingly ambiguous concept. Consequently, the

"retired" and "working" states are not exact. Although the majority of the "retired" group

self-identifies as retired, a relatively small proportion of the "retired" group includes

respondents who stopped working and self-identified as a "homemaker" or "other."

Further, the working group includes women who recently ceased working for pay, yet

self-identify as either temporarily laid off or actively looking for work. While these states

are loosely defined, they capture important race differences in labor force exit behavior

that are masked by relying solely on LFPRs (see Hayward et al., 1996). And although

respondents may reenter the labor force after reporting an exit via retirement or work

disability, most do not, and this initial exit is a definite disruption in the respondent's

work history that marks the beginning of the process leading to a permanent exit from the

labor force (Hayward et al., 1996).

Measurement of Sociodemographic Characteristics

Race is a key analytic variable and is measured as a dummy variable (1= African

American; 0= White). Older women are more likely to be outside of the labor force

instead of being full-time workers (Pienta et al., 1994) and are more likely to stop

working as a result of a work disability (Daly and Bound, 1996). Age (measured in years)

at baseline is included in the multivariate analysis as a control variable to account for this

age effect. A time-varying measure of age is also included in the hazard models in order

to approximate aging over time. Respondent's educational attainment (measured in years









of formal education) is also included as a control variable because it is likely to influence

an array of factors such as occupation, income, wealth, health (House and Williams,

2000), and subsequent labor force transitions.

Measurement of Health

Measures of physical health such as hypertension, stroke, heart disease, diabetes,

chronic lung disease, psychological problems, at thi itin, and cancer are included in the

analyses. First, these were coded as dummy variables according to how the respondent

answered the question, "Has a doctor ever told you that you have (had a) [condition]." A

summary measure of the total number of the above conditions ever diagnosed is included

in the analyses. A measure of the respondent's self-rated health is also included

(l=excellent, 2=very good, 3=good, 4=fair, 5=poor

Measurement of Family Circumstances

Both present family circumstance and earlier social roles impact labor force

behavior in later life (O'Rand et al., 1992). Previous research has shown that single

parenthood experiences affect women's retirement behavior (Brown and Pienta, 2002).

Women typically enter single parenthood via one of two pathways. First, women may

become single mothers as a result of a nonmaritalfirst birth (1= nonmarital first birth; 0=

otherwise). Second, when women with children divorce or become widowed we measure

post marital single parenthood (1= post marital single parent; 0= otherwise). Given

single mother's relatively precarious economic circumstances, older women who have

experienced single parenthood may need to continue working in order to amass sufficient

savings for retirement. Further, racial disparities in rates of single parenthood may play a

role in the race-retirement relationship.









Current marital status is central to understanding labor force behavior, especially in

later life. Unmarried women are economically disadvantaged compared to married

women and thus may delay retirement in order to accumulate wealth for later

consumption during the retirement years. Also, among married women, it is important to

differentiate between women with spouses in the labor force and women with spouses not

in the labor force because spouses tend to exit the labor force at around the same time as

one another (Henretta and O'Rand, 1983; Henretta, O'Rand and Chan, 1993). Thus, 3

dummy variables are included to capture current marital status: (1) not married

(divorced, widowed, and never married), (2) Married and spouse is in the labor force,

and (3) Married and spouse is not in the labor force. Dependent children are also likely

to impact labor force participation (Pienta et al., 1994) because children tend to place

economic burdens on the household and thus women with a child under 21 may work

longer in order to accrue sufficient savings for retirement and money needed to continue

supporting a dependent child. Number of household residents may also influence

household economic resources and labor force exit behavior.

Measurement of Midlife Work Characteristics

Wages2 (average salary and or commission per week) are likely to influence labor

force exit decisions. Workers with high wages may be less inclined to sacrifice the

opportunity cost of forgoing a steady stream of income for retirement. As a proxy for

labor market attachment, women's baseline self-report of their average number of hours

worked per week and total years ever worked are included. Women with greater work

hours and years worked over the life course may continue to have a stronger labor market

attachment into later midlife. On the other hand, women with substantial labor force

experience over the life course may have greater economic resources to draw on for









retirement. Occupations stratify the labor force by allocating different resources,

benefits and opportunities to workers. To account for this effect, occupations are divided

into white collar, blue collar and service types of occupations. Further, a measure of the

baseline job's physical demands (1=all/almost of the time; 2=most of the time; 3=some

of the time; 4=none/almost none of the time) is included because when comparing work

and non-work alternatives, older workers may view high levels of physical demands as a

hurdle to labor force participation, making non-work alternatives more attractive. Self-

employment differs from employment in organizations in many respects (Carr, 1996),

which are likely to lead to disparate labor force participation rates. Other work-related

factors that are likely to influence labor force behaviors of retirement- aged workers

include: pension eligibility status (currently receiving or eligible to receive benefits; has

pension coverage, but is not currently eligible; and no pension coverage), private pension

wealth, and health insurance coverage. Self-reported pension wealth (measured as

present value as of the interview year) is a summary of promised or received employer-

provided pension benefits from as many as three current or priorjobs. Health insurance

status is measured as: being uninsured; having employer-provided health insurance

through one's own employer or a spouse's employer; and having health insurance from

another source (i.e. private health insurance, or government provided health insurance).

Measurement of Midlife Economic Well-Being

An individual's income and assets are key indicators of economic well-being.

Much like the expected wage effect, we speculate that higher levels of household income

provide incentives that are likely to encourage one to remain in the labor force. While

income is expected to be inversely related to likelihood of retiring, a household's total

non-housing assets and net value of primary residence are likely to be positively









associated with retirement. Individuals from households with lower levels of net worth

are expected to be more likely than those with more economic wherewithal to remain in

the labor force. The distributions of pension wealth, household income, total non-housing

assets, net value of primary residence and net worth are skewed, therefore, these variables

are transformed by the natural logarithm in the multivariate models1.

Analytic Strategy

Descriptive statistics are presented for White and African American women (Table

1). Racial differences in descriptive characteristics are calculated using t-test (continuous

variables) and chi-square (categorical variables) statistics. Baseline labor force status

percentages are presented for (1) the full sample, and (2) by race (Table 2). Next, health

profiles of women by baseline labor force status are presented in Table 3.Then,

proportional hazard models of worker's risk of becoming either retired (Table 4) or work

disabled (Table 5) are estimated. A series of nested models are estimated in order to

evaluate the direct and indirect effects of race and life course variables. Analysis of racial

differences in attrition and death (not shown) indicated that among late middle-aged

women in the labor force, African Americans have a higher risk of death than Whites,

and similar rates of attrition. Analyses also check for the possibility of multicollinearity.














CHAPTER 4
RESULTS

Table 1 presents descriptive characteristics for a sample of African American and

White women in the labor force in 1992 and reveals important racial differences in life

course circumstances, which may affect labor force exit behavior. Compared to White

women, African American women are disadvantaged in terms of educational attainment

and health, more likely to have been a single parent, less likely to be married or have a

spouse in the labor force, more likely to work in a blue collar job, more likely to be

uninsured, and have less household income and non-housing assets.

Table 2 indicates that, overall, 63.3% of women were in the labor force at baseline;

27.9% were retired; and 8.8% of women were work disabled. Importantly, African

American and White women appear to have similar rates of labor force participation.

However, further classification of women who have exited the labor force reveals several

important racial differences. Whereas African American women are much more likely

than White women to report being work disabled (17.4% vs. 3.7%, p< .01), they are less

likely to be retired (18.2% vs. 30.2%, p< .01).










Table 1. Descriptive Characteristics of Women in the Labor Force at Baseline by Race
African
White American

(n=2515) (n=635)


Sociodemographic and Health Measures

Age (mean)

Education (mean)

Self-Reported Health Status (mean)

# of Diagnosed Conditions (mean)

Arthritis (%)

Psychological Problems (%)

High Blood Pressure (%)

Diabetes (%)

Cancer (%)

Lung Disease (%)

Heart Problems (%)

Stroke (%)

Family Circumstances

Marital Status

Married w/ spouse in Labor Force (%)

Married w/ spouse out of Labor Force (%)

Unmarried (%)

Kid in HH LT 21 yrs old

# HH Residents

Nonmarital First Birth (%)

Post Marriage Single Parenthood (%)

Job Characteristics and Work History

Wage/ Week (mean)

Work Hours/ Week (mean)

Pension Wealth (median)

Years Employed Over Life Course (Mean)


55.5

12.6

2.2

1.0

36.8

6.6

27.4

5.5

7

4.8

6.4

1.0




51.9

16.3

31.8
15.9

2.4

8.6

30.4


$441.20

37.0

$ 33,747.00

26.2


55.4

12.0

2.8

1.2

36.7

5.8

51.2

12.6

4.6

3.8

7.1

1.9




28.5

13.4

58.1
21.9

2.8

25.7

40.2


$369.14

35.9

$ 42,288.00

27.3









Table 1 (continued).
African
White American
(n=2515) (n=635)

Occupation (%)
White collar 29.6 20.3 ***
Blue collar 19.4 30.8 ***
Service sector 51.0 48.9
Self employed (%) 14.6 7.3 ***
Pension Status (%)
Covered by a pension 47.1 47.1
Eligible for Pension 11.2 13.1
No pension 41.7 39.8
Health Insurance Status (%)
Employer health insurance 75.9 71.7 ***
Other health insurance 10.0 10.3
No health insurance 14.1 18.0 ***
Economic Well Being
Net Value of Primary Res. (median) $50,000.00 $22,000.00 ***
Non-Housing Assets (Median) $46,580.00 $6,000.00 ***
HH Income (median) $39,000.00 $24,000.00 ***
*p<.10; **p<.05; ***p<.01.
Note T-test (continuous variables) and chi-square (categorical variables) statistics are
used to compare descriptive statistics across the two samples.

Table 2. Baseline Labor Force Status by Race

Labor Force Status Total Whites (%) African Americans (%)

ILF 63.3 63.0 64.4
Work-Disabled*** 8.8 3.7 17.4
Retired *** 27.9 30.3 18.2
*p<.05; **p<.01; ***p<.001

Results presented in Table 3 indicate that health profiles of women vary by baseline

labor force status. Women in the labor force have the best health (e.g. they have the









lowest prevalence of hypertension, diabetes, cancer, lung disease, heart problems,

strokes, arthritis and psychological problems, and they have the highest self-rated health),

followed by retired women. As expected, women who report being work disabled have

the poorest health profiles. Since analyses of labor force exits will draw solely upon

women in the labor force at baseline, it is worth noting the presence of a healthy-worker

selection bias.

Table 3. Measures of Physical and Self-Rated Health by Baseline Labor Force Status

ILF Retired Work-Disabled
# of Diagnosed Conditions (mean) a***, b***, c*** 1.0 1.3 2.6
Self-Rated Health (mean) a***, b***, c*** 2.3 2.7 4.3
High Blood Pressure (%) a***, b***, c*** 29.6 35.8 51.4
Diabetes (%) a***, b***, c*** 6.2 9.8 21.5
Cancer (%) a*, b***, c*** 6.5 7.2 12.0
Lung Disease (%) a**, b***, c*** 4.6 5.2 20.6
Heart Problems (%) a***, b***, c*** 6.1 8.6 30.2
Stroke (%) a***, b***, c*** 1.1 1.8 9.6
Arthritis (%) a***, b***, c*** 36.4 42.0 70.5
Psychological Problems (%) a***, b***, c*** 6.3 11.7 38.7
*p<.10; **p<.05; ***p<.01
a Denotes statistically significant different mean values between individuals ILF and
Retired
b Denotes statistically significant different mean values between individuals ILF and
Work Disabled
c Denotes statistically significant different mean values between work-disabled and
retired individuals

Nested model strategy

Tables 4 and 5 present results from the multivariate proportional hazard models of

the impact of race on rates of retirement or exiting the labor force due to a disability,

respectively. Both tables employ a nested model strategy in order to explore how life

course factors may intervene in the race-labor force behavior relationship. Model 1









includes measures of race and age at baseline. Model 2 adds covariates to estimate the

effects of time and education. Model 3, the base model, adds measures of baseline health

in order to estimate the effects of physical and subjective health on labor force exit

behavior, and to explore whether health intervenes in the race-labor force behavior exit

relationship. Model 4 adds measures of work characteristics to the base model in order to

explore the impact of work variables on retirement and their role in the race-retirement

relationship. Model 5 adds measures of prior single parenthood experiences to the base

model in order to explore whether earlier family circumstances impact subsequent labor

force behaviors and their role in the race-retirement relationship. Single parenting and

current family circumstances are added to the base model in order to explore the direct

effects of family characteristics, as well as the direct and indirect effects of earlier single

parenting circumstances and race on labor force exit behavior (Model 6). Next, economic

measures are added to the base model (Model 7). Model 8 is the fully specified model.

Retirement behavior among African American and White women

Risk ratios of retirement presented in Table 4 indicate that African American are

less likely than White women to retire (Models 1-4). As hypothesized, familial and

economic factors over the life course intervene in the race-retirement relationship. For

instance, controlling for prior single parenting circumstances (Model 5) and current

family circumstances (Model 6) eliminates racial disparities in retirement. Similarly, once

measures of economic security are included in the model, African American and White

women appear to have similar rates of retirement (Model 7).

Analyses presented in Table 4 reveal a number of other important predictors of

retirement behavior. Whereas older women, self-employed women, and women with

greater pension wealth, non-housing assets, or net value of primary residence are more















Table 4. Risk Ratios from Proportional Hazard Models of Retirement

MODEL 1 MODEL 2 MODEL 3 MODEL 4 MODEL 5 MODEL 6 MODEL 7 MODEL 8


VARIABLES

African American

Age

Time

Education

Health Measures

Number of Diagnosed Conditions

Self-Rated Health

WORK CHARACTERISTICS

Wage / Week

Hours / Week

Log of Pension Wealth

Years Worked Over Life Course

Occupation

Blue collar

Service

White Collar

Self employed

Pension Status


.89**

1.16***


.88**

.99

1.18***

1.0


.87**

.99

1.18***

1.0


.86**

.95***

1.23***

.98**



1.03

1.04



1.0

.99***

1.02***

.99***


.90

.98

1.18***

1.0



1.03

1.02


1.04

.98*

1.18***

.99



1.03

1.03


1.01

.98

1.18***

.98**



1.03

1.04*


d

1.27***


1.09

.94***

1.23***

.97***



1.04*

1.06**



1.0

.99***

1.02***

.99***


d

1.19**














Table 4 (continued).

MODEL 1 MODEL 2 MODEL 3 MODEL 4 MODEL 5 MODEL 6 MODEL 7 MODEL 8

Covered by pension 1.11** 1.12**

Eligible for pension 1.22*** 1.23***

No pension d d

Health Insurance Coverage

Uninsured .91 .99

Other Health insurance 1.0 1.04

Employer-provided d d

FAMILY CIRCUMSTANCES

Post Marital Single Parenthood .80*** .92* .95

Non-marital 1st Birth .91 .87** .89

Current Marital Status

Unmarried .74*** .74***

Married (Spouse in Labor Force) 1.17*** 1.05
Married (Spouse Not in Labor
Force) d d

Child under 21 .91 .89*

Number of HH Residents .93*** .93***

ECONOMIC WELL-BEING

Log of HH Income 1.01 .98

Log of Non-housing Assets 1.04*** 1.03***














Table 4 (continued).

MODEL 1 MODEL 2 MODEL 3 MODEL 4 MODEL 5 MODEL 6 MODEL 7 MODEL 8
Log of Net Value of Primary
Residence 1.02*** 1.01**

Intercept 9.830 10.640 10.88 10.37 10.46 10.22 10.93 9.85

Model X2 -6718.62 -6542.44 -6541.03 -4964.09 -6525.19 -6480.21 -6505.34 -4910.81

D.F. 2 4 6 13 8 12 9 26
*p<.10; **p<.05; ***p<.01.
d Denotes reference group









likely to retire, women with greater work hours per week, greater work tenure over the

life course, greater number of household residents, and ever single mothers are less likely

to retire. Women who are eligible to receive their pension are more likely than women

without a pension to retire. Controlling for current marital status indicates that compared

to married women with a spouse in the labor force, unmarried women are less likely to

retire, and married women with a spouse in the labor force are more likely to retire. Also,

part of the single parent effect is mediated by current marital status. Diagnostic measures

do not indicate severe multicollinearity in the models of retirement.

Work disability among African American and White women

Table 5 presents the relative risk ratios of exiting the labor force as a result of a

work disability. As hypothesized, African American women have a significantly higher

risk than White women of reporting an exit from the labor force due to a disability

(RR=2.03, p< .01) (Model 1). Controlling for educational attainment (Model 2), results in

a modest reduction in African American's excess risk (RR= 1.74, p< .01). Adding

baseline measures of health (Model 3) reveals several important findings: (1) women

with a greater number of health conditions and poorer self-rated health are more likely to

report exiting the labor force due to disability, (2) African American women's excess risk

or work disability is substantially reduced (RR= 1.74, p< .01 to RR=1.28, p< .05), and (3)

education's effect size is somewhat reduced (RR= .84, p< .01 to RR= .90, p< .01)--

indicating that education's effect on rates of work disablement partially operate via health

measures. These findings lend support to the notion that African American women's

excess risk of work disability is partially a function of their poorer health, as well as the

idea that racial disparities in educational attainment, in part, underlie racial differences in

both health and labor force exit behavior in later life.














Table 5. Risk Ratios from Proportional Hazard Models of Work Disability

MODEL 1 MODEL 2 MODEL 3 MODEL 4 MODEL 5 MODEL 6 MODEL 7 MODEL 8

VARIABLES
African American 2.03*** 1.74*** 1.28** 1.44*** 1.21 1.16 1.06 1.28*
Age .97** .90*** .89*** .84*** .89*** .89*** .89*** .84***
Time 1.06*** 1.06*** 1.13*** 1.06*** 1.06*** 1.06*** 1.13***
Education .84*** .90*** .93*** .90*** .99** .93*** .94***
Health Measures
Number of Diagnosed
Conditions, W1 1.18*** 1.19*** 1.16*** 1.15*** 1.15*** 1.14***
Self-Rated Health, W1 1.85*** 1.86*** 1.83*** 1.82*** 1.77*** 1.80***
WORK
CHARACTERISTICS
Wage/ Week 1.0 .99
Hours/ Week 1.01* 1.01**
Log of Pension Wealth .98 .99
Years Worked Over Life
Course .98*** .98***
Occupation
Blue collar 1.08 1.10
Service .99 .99
White Collar d d
Self employed .51*** .54**
Pension Status
Covered by pension 1.19 1.22














Table 5 (continued).

MODEL 1 MODEL 2 MODEL 3 MODEL 4 MODEL 5 MODEL 6 MODEL 7 MODEL 8


Eligible for pension 1.45* 1.51**
No pension d d
Health Insurance Coverage
Uninsured 1.28* 1.17
Other Health insurance 1.94*** 1.72***
Employer-provided d d
FAMILY
CIRCUMSTANCES
Post Marital Single
Parenthood 1.35*** 1.20* 1.20
Non-marital 1st Birth 1.23* 1.25* 1.17
Current Marital Status
.68
Unmarried .99 **
Married (Spouse in Labor
Force) .69*** .67***
Married (Spouse Not in
Labor Force) d d
Child under 21 1.25* 1.47***
Number of HH Residents .93* .90**
ECONOMIC WELL-
BEING
Log of HH Income .95*** .95
Log of Non-housing Assets .97*** .97**
Log of Net Value of Primary
Residence .98** .99














Table 5 (continued).

MODEL 1 MODEL 2 MODEL 3 MODEL 4 MODEL 5 MODEL 6 MODEL 7 MODEL 8

Intercept 1.14 1.09 .74 1.59 1.03 .55 .17 .70
Model X2 -1993.54 -1953.42 -1821.17 -1435.67 -1814.35 -1804.83 -1804.95 -1415.46
D.F. 2 4 6 13 8 12 9 26
*p<.10; **p<.05; ***p<.01.
d Denotes reference group









Racial disparities in family patterns and wealth also underlie racial disparities in

rates of work disability. Once either measures of family circumstances (Model 6) or

economic well being (Model 7) are controlled for, African American and White women

appear to have similar rates of work disability. Importantly, measures of work, family,

and economic circumstances impact rates of work disability. Women with more years of

employment throughout the life course are less likely to become work disabled.

Compared to married women with a spouse outside the labor force, married women with

a spouse in the labor force have a lower risk of becoming work disabled. Also, self-

employment, older age, and higher values of household income, non-housing assets and

net value of primary residence are associated with lower risks of work disability.

Diagnostic measures do not indicate severe multicollinearity in disability models.














CHAPTER 5
DISCUSSION

Much like previous research on labor force exit behavior, results from the presents

study suggest that an array of life course factors are central to the distribution of older

workers across the alternative destination statuses of retirement, and work disability

(Hayward, Grady, Hardy, and Sommers, 1989; Szinovacz, DeViney, and Davey 2001).

However, this study is among the first to utilize longitudinal data to demonstrate that race

is an important predictor of labor force status and labor force exit behavior among

women in late midlife. As hypothesized, among women in the labor force in late middle

age, African Americans have lower rates of retirement and higher risks of work disability

as a result of racial differences in circumstance throughout the life course.

Results from proportional hazard models demonstrate that racial disparities in labor

force exit behavior stem from racial differences in human capital, health, and wealth

across the life course. In the case of retirement, racial differences in family and economic

circumstance appear to underlie racial disparities. Compared to White women, African

American women are more likely to have ever been single parents, be unmarried, have

more household residents, and are less likely to be married to a spouse in the labor force--

all of which are associated with lower rates of retirement. Once family characteristics are

controlled for, African American and White women have similar rates of retirement.

Household non-housing assets and net value of primary residence also intervene in the

race-retirement relationship. Importantly, racial differences in these two measures are









prominent, and African American and White women with equivalent levels of economic

resources appear to have comparable rates of retirement.

Racial disparities in rates of work disability are even more pronounced. Results

suggest that African American women are approximately twice as likely as White women

to exit the labor force via work disability. Both temporally distal and proximate factors

intervene in the race-work disability relationship. For instance, racial differences in

educational attainment account for a significant share of racial disparities in work

disability. Also, more contemporaneous factors such as physical and self-rated health are,

in part, a function of education, and account for a substantial portion of the race gap in

rates of work disability. While some researchers have suggested that racial disparities in

work disability are a consequence of economic incentives, lack of attractive employment,

or social desirability, this study's findings suggest that African American women's

disproportionately high rates of work disability are primarily a consequence of their

poorer health.

While health differences between the two groups account for a substantial portion

of the race gap in work disability, residual racial disparities in work disability remain.

One reason that the health disparities may not have completely accounted for the race gap

in work disability may be due to under-reporting of health conditions among African

American women. Compared to White women, African American women have far fewer

economic resources, are more likely to be uninsured, and are less likely to have employer

provided insurance. Consequently they are likely to receive infrequent and inadequate

health care. African American's lower rates of contact with health care providers may









significantly mask unrecognized health problems, and thus understate the full effect of

doctor-diagnosed conditions in the race-work disability relationship.

Educational attainment was expected to play a key role in the race-work disability

and race-retirement relationship. However, important historical structural arrangements

may be muting the effect of education, most notably, racially segregated schools and

institutional racism. Women in this sample were born between 1931 and 1941, and thus

received 'separate and unequal' education prior to the implementation civil rights

legislation. Consequently, even among White and African American women with the

same number of years of education, African American women likely received sub-par

education. Furthermore, institutional racism resulted in fewer opportunities for these

African American women, relative to White women, at a given level of education or skill.

Clearly, racial differences in labor force exit patterns reflect socioeconomic and health

disparities.

Given the importance of understanding labor force exit behavior within the context

of decisions and circumstances throughout the life course (Hayward et al., 1996; O'Rand

et al., 1992; Szinovacz, DeViney, and Davey, 2001), the present study investigated racial

differences across an array of factors. In addition to racial disparities in retirement

behavior, education, and health, dramatic racial differences in work and family

circumstances, and economic well being were observed for this cohort of women. African

American women were disadvantaged, relative to White women, in many respects. For

example, compared to White women, African American women have substantially higher

rates of nonmarital first births and post marital spells of single parenthood, are more

likely to be a blue collar workers, less likely to be self-employed or working in a white









collar job, less likely to have employer-provided health insurance or a spouse in the labor

force, more likely to be uninsured or unmarried, and have less household net worth and

income. Pension wealth and total years worked represent two features that African

American women actually fare better on than White women.

This study extends upon Belgrave's (1988) study in several key respects. First, the

use of a nationally representative sample makes national inferences possible. Second, this

study distinguishes between types of non-participation (e.g. retirement and disability),

revealing striking racial disparities that would have been masked by relying on labor

force participation rates. Third, rather than relying solely on cross-sectional data, this

study uses longitudinal data to explore women's dynamic labor force exit patterns.

Further, the present study includes measures of a wide array of life course circumstances,

instead of relying solely on temporally proximate "pull" factors.

Findings from the present study are suggestive of both similarities and differences

in race-labor force exit behavior relationship among women and men. Among women,

African Americans appear to have higher risks than Whites of exiting the labor force via

work disability as a result their poorer health, a findings similar to that among men. In the

case of retirement, however, whereas African American women have lower rates than

White women, African American males have higher rates of retirement, relative to White

men (Hayward et al., 1996). This is likely a result of greater racial similarities in labor

force histories among women than men.

The literature on women's retirement more generally, as well as race differences,

may benefit from future studies that explore the impact of marital transitions and spousal

labor force transitions on labor force exit behavior. Additionally, there is a dearth of work









on women's risk of reentry into the labor force from alternate labor force statuses. Future

research on retirement ought to consider exploring the inter-connectedness of transitions

across multiple domains such as family, health, work, and economics (Szinovacz,

DeViney, and Davey, 2001).

It is worth noting that although analyses are based on data collected between 1992

and 2000, analyses do not explicitly focus on period effects. The United States

experienced great economic and social changes during this time span. For example, the

economic depression of the early 1990's preceded the sustained economic boom of the

later 1990's. Welfare reform legislation was also passed during this time period (1996).

While a myriad of macro-level factors may have influenced women's labor force exit

behavior, the effects of such phenomena are difficult to isolate and are beyond the scope

of this study.

Findings from the present study are an important first step in documenting and

understanding racial disparities in women's labor force exit behavior. Further, they

highlight the importance of distinguishing between forms of non-participation--retirement

and work disability, and lend support to the notion that racial differences in the labor

force exit behavior among women in later midlife are a consequence of different

circumstances throughout the life course.

The subject matter of this paper is timely and important amid concerns over the

increasing dependency ratio, as the United States deliberates revising the Social Security

Retirement system, and as the labor force is becoming increasingly gray, brown, and

female. Findings that health problems contribute to higher risks of labor force withdrawal

via work disability support the notion that health affects worker productivity and









consequently the demand for and supply of market labor services (Deleire and Manning,

2002). Thus, social and economic costs of health impairments exist. In view of that,

preventative poverty and health policy initiatives that focus on improving population

education and health, especially among vulnerable populations, may reduce involuntary

labor force exits via work disability, and contribute to an increase in labor force

participation and economic productivity. In light of the forecasted declining role of Social

Security income in the well being of older Americans, policies that emphasize financial

education including issues related to expected time-horizon, savings and investments, and

future income and expenses may become increasingly critical for labor force optimization

and the long-term financial security of older women.
















LIST OF REFERENCES


Belgrave, Linda L., 1988. "The Effects of Race Differences in Work History, Work
Attitudes, Economic Resources, and Health on Women's Retirement." Research on
Aging, 10 (3), 383-398.

Blackwell, D.L., J.G. Collins, and R. Coles. 2002. Summary Health Statistics for U.S.
Adults: National Health Interview Survey, 1997. National Center for Health
Statistics. Vital Health Stat. 10:205.

Bound, J., M. Schoenbaum, and T. Waidmann. 1995. "Race and Educational Differences
in Disability Status and Labor Force Attachment." Journal ofHuman Resources
30(5): S227-S267.

Brown, T.H. and A.M. Pienta. 2002. "The Impact of Divorce, Single Parenthood, and
Work Characteristics on Labor Force Behavior Among Retirement-Aged Women."
Poster presented at the Gerontological Association of America, Boston, MA.
November 2002.

Burr, Jeffrey. A., Michael P. Massagli, Jan E. Mutchler, and Amy M. Pienta. 1996.
"Labor Force Transitions Among Older African American and White Men." Social
Forces 74: 963-982.

Carr, Deborah. 1996. "Two Paths to Self-employment? Women's and Men's Self-
employment in the United States, 1980." Work and Occupations. 23:26-53.

Daly, Mary. and John Bound. 1996. "Worker Adaptation and Employer Accommodation
Following the Onset of a Work-Limiting Health Impairment." Journal of
Gerontology: Social Sciences 51(2): s53-s60.

Dannefer, Dale. 1991. "The Race is to the Swift: Images of Collective Aging. In G. M.
Kenyon, J. E. Birren, and J. J. F. Schroots (Eds.), Metaphors ofAging in Science
and the Humanities: 155-172. New York: Springer.

Deleire, Thomas, and Willard Manning. In press. "Labor Market Costs of Injury and
Illness: Prevalence Matters." Health Economics.

Eller, T.J. 1994. "Household Wealth and Asset Ownership: 1991."Current Populatin
Reports, Series P70-34, U.S. Government Printing Office, Washington, D.C.
January, 1994.









Gibson, Rose C. 1987. "Reconceptualizing Retirement for Black Americans." The
Gerontologist 27 (6): 691-698.

Gibson, Rose C. 1991. "The Subjective Retirement of Black Americans." Journal of
Gerontology 46 (4): S204-209.

Hayward, M.D., W.R. Grady M.A. Hardy, and D. Sommers. 1989. "Occupational
Influences on Retirement, Disability and Death." Demography 26:393-409.

Hayward, Mark D., Samantha Friedman, and Hsinmu Chen. 1996. "Race Inequities in
Men's Retirement." Journal of Gerontology: Social Sciences 51B:S 1-10.

Henretta, John C. and Angela M. O'Rand. 1983. "Joint Retirement in the Dual Worker
Family." SocialForces 62(2): 504-520.

Henretta, John C., Angela M. O'Rand, and Christopher G. Chan. 1993a. "Joint Role
Investments and Synchronization of Retirement: A Sequential Approach to
Couples' Retirement Timing." Social Forces 71(4): 981-1000.

Henretta, John C., Angela M. O'Rand, and Christopher G. Chan. 1993b. "Gender
Differences in Employment After Spouses' Retirement." Research on Aging 15
(2):148-69.

House, James, and David Williams. 2000. "Understanding and Reducing Socioeconomic
and Racial/Ethnic Disparities in Health." B.D. Swedley and S.L. Syme (Eds.).
Promoting Health: Interventions from Social and Behavioral Research. National
Academy Press Washington, D.C.:88-124.

National Academy on an Aging Society. 1999. Chronic Conditions: Challenges for the
21st Century: Chronic and Disabling Conditions, Number 1, November 1999.
Washington DC.

O'Rand, Angela. 1996. "The Precious and the Precocious: Understanding Cumulative
Disadvantage and Cumulative Advantage over the Life Course." The Gerontologist
36 (2): 230-238.

O'Rand, Agela M., J.C. Henretta, and M.L. Krecker. 1992. Family Pathways to
Retirement. M. Szinovacz (Ed.), Family Retirement: 81-98. New York: Sage.

Parsons, D.O.1980. "Racial Trends in Male Labor Force Participation." American
Economic Review 70: 911-920.

Pienta, Amy M., Jeffrey Burr, and Jan E. Mutchler. 1994. "Women's Labor Force
Participation in Later Life: The Effects of Early Work and Family Experiences."
Journal of Gerontology 49: 231-239.









Pienta, Amy M., and Tyson H. Brown. 2001. "Labor Force Transitions Among Disabled
Workers: An Examination of Gender Differences." Poster presented at the
American Sociological Association, Anaheim, CA. August 2001.

Quadagno, J., and Jennifer Reid. 1999. "The Political Economy Perspective in Aging."
V.L. Bengtson and K.W. Schaie (Eds.), Handbook of Theories ofAging: 344-358.
New York: Springer Publishing Company.

Szinovacz, M.E., DeViney, S., and Davey, A. 2001. "Influences of Family Obligations
and Relationships on Retirement: Variations by gender, race, and marital status."
Journals of Gerontology: Social Sciences 56: S20-S27.

U.S. Bureau of the Census. 1993. Statistical Abstract of the United States. Washington,
D.C.: Government Printing Office.

Welch, F. 1990. "The Employment of Black Men." Journal of Labor Economics 8: S26-
S74.

Wilson, W. J. 1987. "The Obligation to Work and the Availability of Jobs: A Dialogue
Between Lawrence M. Mead and William Julius Wilson." Focus 10: 11-19.

Wray, L.A. 1996. "The Role of Ethnicity in the Disability and Work Experience of
Preretirment-age Americans." The Gerontologist 36: 287-296.















BIOGRAPHICAL SKETCH

Prior to receiving his Master of Arts in sociology with a minor in statistics, Tyson

Brown earned his Bachelor of Arts in sociology with minors in business administration

and gerontology at the University of Florida. Concurrent to earning his Master of Arts

degree, he was a research trainee at the Institute on Aging. After completing his master's

degree, Tyson began his Ph.D. coursework at the University of North Carolina at Chapel

Hill in the Department of Sociology and an NIA-funded research traineeship at the

Carolina Population Center.