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Dietary Restraint and Weight Change in College Women Participating in a Weight Gain Prevention Program

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Title:
Dietary Restraint and Weight Change in College Women Participating in a Weight Gain Prevention Program
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Hoover, Valerie J
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[Gainesville, Fla.]
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Degree:
Doctorate ( Ph.D.)
Degree Grantor:
University of Florida
Degree Disciplines:
Psychology
Clinical and Health Psychology
Committee Chair:
PERRI,MICHAEL G
Committee Co-Chair:
JANICKE,DAVID
Committee Members:
WAXENBERG,LORI B
MATHEWS,ANNE
Graduation Date:
8/9/2014

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Subjects / Keywords:
Binge eating ( jstor )
Calories ( jstor )
Eating disorders ( jstor )
Food ( jstor )
Obesity ( jstor )
Pretreatment ( jstor )
Weight control ( jstor )
Weight gain ( jstor )
Weight loss ( jstor )
Women ( jstor )
Clinical and Health Psychology -- Dissertations, Academic -- UF
obesity
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bibliography ( marcgt )
theses ( marcgt )
government publication (state, provincial, terriorial, dependent) ( marcgt )
born-digital ( sobekcm )
Electronic Thesis or Dissertation
Psychology thesis, Ph.D.

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Abstract:
Preventing expansion of the obesity epidemic is a key public health priority. One promising approach to weight gain prevention is to identify periods when individuals are at greatest risk for gaining weight (e.g., the first year of college) and then induce modest weight loss to buffer future weight gain. To ensure optimal outcomes, it is important to identify factors associated with poor treatment response so that programs can be appropriately tailored. Some research suggests that elevated dietary restraint is one such factor that may impede long-term weight management efforts. The current study examined the association between pretreatment dietary restraint and longer-term weight change in the context of a weight gain prevention program. Participants were 95 female college freshmen who were randomized to a five-week weight gain prevention intervention or wait-list control group. For the primary aim, the independent variable (dietary restraint) was assessed using the Three Factor Eating Questionnaire, Dietary Restraint subscale and the dependent variable was change in body weight during follow-up. Other outcome variables included disinhibition and hunger subscales, binge eating (Binge Eating Scale) and body shape, eating and weight concerns (Eating Disorders Examination Questionnaire). Measures were assessed at baseline, post-treatment and three-month follow-up. Regarding weight changes, main effects for time, group and time-by-group interactions were non-significant (ps > .05). Contrary to the primary hypothesis, pretreatment dietary restraint was unassociated with weight change during follow-up (p = .53). Bootstrap mediation revealed non-significant indirect effects of changes in binge eating and hunger on longer-term weight change. T-tests revealed that restrained and unrestrained eaters were not significantly different in their use of weight management strategies (ps > .05). The non-significant association between pretreatment dietary restraint and weight change is likely attributable to an obscuring of effects given the small weight changes or the possibility that the hypothesis is not supported. The literature is mixed on the role of dietary restraint in weight gain and obesity onset. Future studies should examine this association among free-living individuals, include a longer initial intervention, incorporate a maintenance period and utilize intention-to-treat methodology. ( en )
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In the series University of Florida Digital Collections.
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Includes vita.
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Includes bibliographical references.
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Description based on online resource; title from PDF title page.
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This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Thesis:
Thesis (Ph.D.)--University of Florida, 2014.
Local:
Adviser: PERRI,MICHAEL G.
Local:
Co-adviser: JANICKE,DAVID.
Electronic Access:
RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2015-08-31
Statement of Responsibility:
by Valerie J Hoover.

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Applicable rights reserved.
Embargo Date:
8/31/2015
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LD1780 2014 ( lcc )

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DIETARY RESTRAINT AND WEIGHT CHANGE IN COLLEGE WOMEN PARTICIPATING IN A WEIGHT GAIN PREVENTION PROGRAM By VALERIE J. HOOVER A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2014 1

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2014 Valerie J. Hoover 2

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To Nate – my partner in life – and to my parents, Leon and Carolyn, for their constant loving support 3

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ACKNOWLEDGEMENTS I would like to thank my mentor, Dr. Michael G. Perri, for his support and advisement throughout this process. I would also like to thank the members of my committee, Dr. David Janicke, Dr. Anne Mathews, and Dr. Lori Waxenberg, for their direction and assistance. I would also like to thank my colleagues in the UF Weight Management Program Lab, and in particular, Kathryn Ross Middleton, M.S., for her invaluable partnership on this project. This research was supported by grant R 18HL73326 from the National Heart, Lung, and Blood Institute and a PHHP Research Day grant from the College of Public Health and Health Professions, University of Florida. 4

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TABLE OF CONTENTS page ACKNOWLEDGEMENTS ............................................................................................... 4 LIST OF TABLES ............................................................................................................ 7 LIST OF FIGURES .......................................................................................................... 8 ABSTRACT ..................................................................................................................... 9 CHAPTER 1 INTRODUCTION .................................................................................................... 11 Obesity Epidemic .................................................................................................... 11 Weight Gain Prevention .......................................................................................... 12 Evidence for Weight Gain Prevention Programs .............................................. 13 Identification of Factors Associated with Poor LongTerm Outcomes .............. 14 Dietary Restraint ..................................................................................................... 15 Definition of Terms ........................................................................................... 15 Overview of Dietary Restraint Theory ............................................................... 15 Boundary Model of Eating Behavior ................................................................. 17 Disinhibition ...................................................................................................... 18 Negative mood states ................................................................................ 18 Abstinence violation and perceived deprivation ......................................... 20 Dietary Restraint and Weight Change in Community dwelling Adults .............. 20 Restraint and “Dieting” ..................................................................................... 21 Eating and Body related Psychopathology in College Females .............................. 22 Specific Aims and Hypotheses ............................................................................... 25 2 METHODS .............................................................................................................. 27 Participants ............................................................................................................. 27 Recruitment ............................................................................................................ 29 Intervention ............................................................................................................. 30 Measures ................................................................................................................ 32 Height and Weight ............................................................................................ 32 Dietary Restraint ............................................................................................... 33 Binge Eating ..................................................................................................... 34 Shape, Eating, and Weight Concerns .............................................................. 34 Caloric Intake ................................................................................................... 35 Weight Management Strategies ....................................................................... 35 Statistical Analyses ................................................................................................. 35 Primary Aim ...................................................................................................... 35 Secondary Aim ................................................................................................. 36 5

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Tertiary Aim ...................................................................................................... 36 Exploratory Aim ................................................................................................ 37 3 RESULTS ............................................................................................................... 39 Participants ............................................................................................................. 39 Attendance and Adherence .................................................................................... 41 Prim ary Aim ............................................................................................................ 41 Secondary Aim ....................................................................................................... 42 Tertiary Aim ............................................................................................................ 43 Exploratory Aims ..................................................................................................... 44 Analysis of Primary Aim among “Fall Only” ...................................................... 44 Analysis of Primary Aim among Overweight and Obese Participants .............. 45 Utilization of Weight Management Strategies ................................................... 45 Initial Weight Loss Success/Failure and Change in Eating Psychopathology .. 46 Flexible vs. Rigid Dietary Restraint ................................................................... 46 4 DISCUSSION ......................................................................................................... 55 Weight Change Following Intervention ................................................................... 55 Correlations between Baseline Measures ............................................................... 58 Primary Aim ............................................................................................................ 58 Secondary Aim ....................................................................................................... 59 Exploratory Aims ..................................................................................................... 61 Analysis of Primary Aim among “Fall Only” ...................................................... 61 Analysis of Primary Aim among Overweight and Obese Participants .............. 61 Utilization of Weight Management Strategies ................................................... 61 Initial Weight Loss Success/Failure and Change in Eating Psychopathology .. 62 Flexib le vs. Rigid Dietary Restraint ................................................................... 62 Limitations ............................................................................................................... 63 Strengths ................................................................................................................ 64 Future Directions .................................................................................................... 65 Conclusion .............................................................................................................. 66 APPENDIX A OUTLINE OF SESSIONS ....................................................................................... 67 B MEASURES ............................................................................................................ 68 LIST OF REFERENCES ............................................................................................... 88 BIOGRAPHICAL SKETCH ............................................................................................ 97 6

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LIST OF TABLES Table page 2 1 TFEQ R median split cut off scores .................................................................... 38 3 1 Baseline participant characteristics ................................................................... 48 3 2 Mean SD body weights for treatment and control groups ................................ 49 3 3 Baseline Pearson Correlations Between All Measures ....................................... 50 3 4 Regression Results for Primary Aim and Exploratory Aims 1 and 2 ................... 51 7

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LIST OF FIGURES Figure page 3 1 Participant flow diagram ..................................................................................... 52 3 2 Distribution of weight changes from post treatment to follow up ........................ 53 3 3 Model of proposed indirect effects of changes in binge eating and hunger on changes in weight ............................................................................................... 54 8

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Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy DIETARY RESTRAINT AND WEIGHT CHANGE IN COLLEGE WOMEN PARTICIPATING IN A WEIGHT GAIN PREVENTION PROGRAM By Valerie J. Hoover August 2014 Chair: Michael G. Perri Major: Clinical Psychology P reventing expansion of the obesity epidemic is a key public health priority. One promising approach to weight gain prevention is to identify periods when individuals are at greatest risk for gaining weight (e.g., the first year of college) and then induce modest weight loss to buffer future weight gain. To ensure optimal outcomes, it is important to identify factors associated with poor treatment response so that programs can be appropriately tailored. Some research suggests that elevated dietary restraint is one suc h factor that may impede longterm weight management efforts. The current study examined the association between pretreatment dietary restraint and longer term weight change in the context of a weight gain prevention program. Participants were 95 female college freshmen (mean SD Body Mass Index [BMI] = 26.8 6.4 kg/m2) who were randomized to a fiveweek weight gain prevention intervention or wait list control group. For the primary aim, the independent variable (dietary restraint) was assessed using the Three Factor Eating Questionnaire – Dietary Restraint subscale and the dependent variable was change in body weight during followup. Other outcome variables included disinhibition and hunger subscales, binge eating (Binge Eating Scale) and body shape, eat ing and weight concerns (Eating 9

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Disorders Examination Questionnaire). Measures were assessed at baseline, post treatment and threemonth follow up. Regarding weight changes, main effects for time, group and timeby group interactions were nonsignificant ( p s > .05). Contrary to the primary hypothesis, pretreatment dietary restraint was unassociated with weight change during follow up ( p = .53). Bootstrap mediation revealed nonsignificant indirect effects of changes in binge eating and hunger on longer t erm weight change. Ttests revealed that restrained and unrestrained eaters were not significantly different in their use of weight management strategies ( p s > .05). The nonsignificant association between pretreatment dietary restraint and weight change is likely attributable to an obscuring of effects given the small weight changes or the possibility that the hypothesis is not supported. The literature is mixed on the role of dietary restraint in weight gain and obesity onset. Future studies should exami ne this association among freeliving individuals, include a longer initial intervention, incorporate a maintenance period and utilize intention to treat methodology. 10

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CHAPTER 1 INTRODUCTION Obesity Epidemic Approximately 36% of adults in the United Stat es are currently obese ( National Center for Health Statistics, 2012) . Obese individuals are at increased risk for developing numerous physical health problems, including hypertension, hypercholesterolemia, type 2 diabetes, coronary heart disease, congestive heart failure, stroke and certain forms of cancer (Brown, Fujioka, Wilson, & Woodworth, 2009; Cecchini et al.; Noria & Grantcharov , 2013) . Not surprisingly given the impact on health, research has found that healthrelated quality of life decreases with increasing degree of obesity (Jia, 2005) . Furthermore, a recent study by Cawley and Meyehoefer (2012) concluded that medical costs for obese individuals are approximately 150% higher than for healthy weight individuals, which represents an increased economic burden for individuals and the healthcare system at large. A re cent review of lifestyle interventions for obesity revealed that these programs are successful in producing clinically meaningful initial weight losses of approximately 5 to 8%, although many individuals regain between a third to all of the lost weight wit hin the four years following treatment (Simpson, Shaw, & McNamara, 2011) . Environmental, behavioral and psychological factors all contribute to individuals’ varying degree of success with weight loss maintenance. Environmental influences impacting weight loss maintenance include such factors as social support and environment, access to healthy foods and availability and cost of physical activity resources. For example, studies have found that having an “exercise buddy” (i.e., social support) and access to physical activity equipment are 11

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associated with increased engagement in physical activity (Wendel Vos, Droomers, Kremers, Brug, & Van Lenthe, 2007) . Regarding dietary factors, obesity is associated with higher rates of food insecurity, particularly for women (Dinour, Bergen, & Yeh, 2007) . Behavioral and psychological factors also play a critical role in the quest for successful weight loss maintenance. One such factor is the erosion of adherence to behavioral weight management strategies that led to init ial weight loss success. Bouton (2011) provided a learning theory explanation for this and suggested that opportunities abound to associate unhealthy foods with environmental cues. He proposed that in order to change unhealthy eating behaviors, individual s must overwrite the former unhealthy learning with new healthy learning. However, he proposed that because many individuals’ environments remain fairly similar before and after behavior change, the new learning is fragile and highly susceptible to the inf luences of former learning. He suggested that it is a combination of unchanged environment, strong influence of former learning and fragility of new learning that largely accounts for why many individuals do not maintain their new healthy behaviors and subsequently regain lost weight. Weight Gain Prevention Research suggests that individuals gain an average of about .5 to .9 kg during adulthood (Garn et al., 1976; Lewis et al., 2000) . Furthermore, individuals tend to gain greater amounts of weight during j unctures in their lives when weight related environmental factors change considerably, such as the transition to the first year of college (Anderson, Shapiro, & Lundgren, 2003; Delinsky & Wilson, 2008) . For these 12

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reasons, an essential element of comprehens ively addressing the obesity epidemic is to prevent weight gain and the onset of obesity (Mitchell, Catenacci, Wyatt, & Hill, 2011) . An important intervention “window” for weight gain prevention is the freshman year of college. A recent metaanalysis by V ella Zarb and Elgar (2009) found that the average young adult student gains approximately 1.8 kg during this time. Weight gain prevention programs may help to prevent the adoption of unhealthy eating and physical activity behaviors and subsequent weight gain that frequently occurs during the first year of college, thereby helping to inhibit the onset of obesity in this population. Evidence for Weight Gain Prevention Programs The Pound of Prevention (POP) study by Forster, Jeffery, Schmid and Kramer (1988) was one of the first studies to look at preventing weight gain in adults. The study included 219 normal weight individuals randomized to either a 12month weight gain prevention group or a control group. The intervention included monthly newsletters on weight management topics, an optional 4week health education course and an optional financial incentive component. Results revealed that the intervention group lost significantly more weight (kg) than the control group (mean SE, intervention = 1.0 0. 3, control = 0.1 0.4, p = .03). However, when the results were examined by gender, it was found that the effect of the intervention was only significant among male participants (intervention = 2.1 1.7, control = 0.6 0.7, p < .01). The study di d not examine potential moderators of treatment effects. A followup study found that at three years after the start of treatment there were no significant differences between the intervention and control groups: mean SEM, 1.8 0.3 and 1.6 0.5, respec tively (Jeffery & French, 1999) . However, it was found that the intervention group reported greater utilization of weight management strategies 13

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(e.g., increased intake of fruits and vegetables, lower fat intake, awareness of portion sizes) than the contr ol group. Another randomized, controlled pilot study compared “small changes” and “large changes” in the context of an 8week weight gain prevention program (Gokee LaRose, Tate, Gorin, & Wing, 2010) . The study utilized a “weight buffering” approach to weight gain prevention, whereby the aim of both interventions was to produce initial weight loss to buffer against later weight gain. The 52 young adults who participated were mostly female (98%) with a mean SD age (years) of 25.6 4.7 and Body Mass Index (BMI; kg/m2) of 26.7 2.4. At the conclusion of the 8week intervention the “large changes” group lost significantly more weight (kg) than the “small changes” group (3.2 2.5 and 0.7 1.5, respectively, p < .001). This difference remained significant at 16week followup (3.5 3.1 and 1.5 1.8, respectively, p = .006). Perhaps of greatest importance is the fact that both intervention intensities produced a degree of weight loss and may be effective in preventing future weight gain. Identification of Factors Associated with Poor Long Term Outcomes Individuals vary with respect to psychological, behavioral, environmental and biological factors that directly and indirectly impact their degree of success in response to weight management intervention. In t he literature on standard behavioral treatment for obesity, certain factors have been associated with poorer outcomes, such as the presence of significant binge eating symptoms, Major Depressive Disorder, Attention Deficit Hyperactivity Disorder and great er frequency of past weight loss attempts (Altfas, 2002; Mauro, Taylor, Wharton, & Sharma, 2008; Simon et al., 2006; Vocks et al., 2010) . To maximize outcomes in weight gain prevention programs, it is important to identify factors that are predictive of poor longterm treatment response. By doing so, 14

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weight gain prevention interventions can then be appropriately tailored to address barriers to success. While it may seem counterintuitive, one such factor that may be predictive of poor response to intervention is a high degree of dietary restraint. Dietary Restraint Definition of Terms Dietary restraint refers to the degree to which individuals endeavor to restrict their caloric intake in order to keep both caloric intake and body weight at levels acceptable to the individual. Efforts to restrict caloric intake may take different forms, such as limiting highfat or highcarbohydrate foods, or even eliminating such foods from the diet. In contrast, the term disinhibition is conceptualized as the degree to w hich individuals do not restrict caloric intake, which may be in response to internal or external cues (e.g., breaking of personal dietary rules, negative mood states). Furthermore, disinhibition may refer to an acute state or a more persistent approach t o eating. Overview of Dietary Restraint Theory Restraint theory was first proposed by Peter Herman, Janet Polivy and Deborah Mack in 1975 (Herman & Mack, 1975; Herman & Polivy, 1975) . The theory was based on laboratory observations of the eating behavior of restrained and unrestrained eaters following highcalorie preloads. The researchers noted that restrained eaters ate more food following a highcalorie preload as compared to unrestrained eaters. The researchers termed this phenomenon counter regulat ory eating. The seminal study on restraint theory was conducted by Herman and Mack (1975) and examined the effect of a highcalorie preload on subsequent eating in 45 restrained and unrestrained female college students. The researchers hypothesized 15

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that restrained participants would consume more food ad libitum than unrestrained participants following the highcalorie preload. In line with their hypothesis, the researchers found that restrained eaters consumed significantly more food following the preload than after no preload. This same pattern was observed among both normal weight and obese participants. Research on counter regulation suggests that it is driven by an individual’s perception that the ingested food has led to breaking of the self imposed dietary rules, rather than the actual caloric content of the food. Polivy (1976) conducted a study examining the consumption of food ad libitum in 91 obese and normal weight male university students following random assignment to one of four conditions: high calorie preload/told high calorie, high calorie preload/told low calorie, low calorie preload/ told low calorie, and low calorie preload/told high calorie. Results revealed that highly restrained individuals who were told they had ingested a high calor ie preload ate significantly more food than those who were told they had ingested a low calorie preload. The opposite pattern was observed for low restrained individuals. There were no significant differences in the response pattern based on body weight or actual caloric content of the food. A similar pattern of results was found in a study using identical procedures with 60 female college students (Spencer & Fremouw, 1979) . Additional studies using similar methodologies also support the role of cognition in the counter regulatory effects observed among highly restrained individuals (Woody, Costanzo, Liefer, & Conger, 1981; Wooley, 1972) . 16

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Boundary Model of Eating Behavior The boundary model of eating behavior was originally proposed by Herman and Polivy (1984) and is helpful in further elucidating how the constructs of dietary restraint and counter regulation impact eating behavior. Herman and Polivy proposed that eating is r egulated by both physiological and psychological drives. The researchers identified what they termed the hunger boundary and the satiety boundary and proposed that among “normal eaters,” once these boundaries are crossed, eating behavior becomes largely directed by physiological drives to consume food (if the hunger boundary is crossed) or stop consuming food (if the satiety boundary is crossed). They also theorized that when “normal eaters” are within these boundaries, they are in the zone of biological indifference , where eating behavior is more heavily influenced by affective, cognitive and social factors. In their boundary model of eating behavior, Herman and Polivy also distinguished between “normal eaters” and highly restrained eaters. The researchers proposed that there is a greater distance between the hunger boundary (which can be visualized as existing on the left of a continuum of eating behavior) and satiety boundary (located on the right) among highly restrained eaters. They theorized that highly restrained eaters possess an additional boundary (i.e., the diet boundary ) . Herman and Polivy argued that the self imposed diet boundary is set between the hunger and satiety boundaries, and that when restrained eaters cross the diet boundary, they continue to eat until they reach the satiety boundary. Given that the satiety boundary is positioned farther to the right among restrained eaters (i.e., they need to consume a greater amount of food in order to reach the satiety boundary), this results in the consumption of larger amounts of food than would be consumed by normal eaters. The following section will review 17

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those factors that research has indicated may cause individuals to cross the diet boundary. Disinhibition Disinhibitors refer to those f actors that lead to a disruption in dietary control. Disinhibitors are believed to have the effect of causing restrained eaters to abandon their dietary rules and consume larger amounts and/or certain types of foods (e.g., high calorie or high fat foods) than they would consume when adhering to their dietary rules (Ruderman, 1986) . The two disinhibitors that are most frequently cited in the literature are negative mood states and the abstinence violation effect ( Herman & Polivy, 1975; Lowe & Levine, 2005; Markowitz, Butryn, & Lowe, 2008; Polivy & Herman, 1976) . The term disinhibition is often used as an analogue to the term binge eating (Wardle & Beinart, 1981) . The hallmark of Binge Eating Disorder is recurrently eating, in a brief period of time, signif icantly more food than most other people would eat in a similar situation ( American Psychiatric Association , 2013) . Additionally, individuals who engage in binge eating typically experience a perceived lack of control over their eating during binge episodes. They are also likely to experience feelings of guilt, embarrassment and disgust and may binge eat alone due to these feelings. Negative mood states Studies examining the disinhibitory effects of anxiety on eating behavior have typically used two primary modes of anxiety induction: induction of acute physical fear and induction of a more general dysphoria. Polivy, Herman and McFarlane (1994) noted that induction of a general dysphoria generally produces larger discrepancies in the amount of food consum ed than induction of physical fear. 18

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A study by Herman and Polivy (1975) examined the effects of an anxiety manipulation (electric shock) on food consumption in normal weight and obese restrained and unrestrained female college students. The anxiety manipul ation was effective ( p < .001) and there were no baseline differences in anxiety between restrained and unrestrained eaters. Results revealed that restrained eaters consumed significantly more food following anxiety induction ( p < .05). Another study on the impact of mood on food consumption in restrained eaters was conducted by Polivy et al. (1994) . The study included a sample of 94 female college students and examined the role of food palatability on amount of food consumed following high anxiety induction (extemporaneous speech) or low anxiety induction (tactile ratings of fabric). Results showed that restrained eaters in the high anxiety condition consumed significantly more palatable and unpalatable food, as compared to restrained eaters in the low anxiety condition ( p < .01). Among unrestrained eaters, there was a nonsignificant difference in the amount of food consumed between the high and low anxiety conditions ( p > .10). These results suggest that restrained eaters, but not unrestrained eaters , eat significantly more when anxious, regardless of food palatability. Heatherton and Baumeister (1991) hypothesized that individuals who overeat in response to negative emotional stimuli do so in order to escape from aversive awareness of their emotional state, which they termed escape theory. Specifically, the researchers proposed that these individuals shift the focus of their attention from higher order cognitive and emotional processes (e.g., depressive and anxious thoughts and feelings) to the immed iate stimulus environment by focusing on the act of food 19

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consumption. The authors hypothesized that since cognitive control of eating exists at higher levels of awareness, dietary control is relinquished when awareness shifts to lower order processes. Abstinence violation and perceived deprivation Another factor believed to impact disinhibition is the abstinence violation effect . This refers to the observed phenomenon wherein restrained individuals consume a type or amount of food that is prohibited ac cording to their self imposed dietary rules, and then subsequently eat other forbidden foods and/or large amounts of food. Markowitz et al. (2008) looked at how the abstinence violation effect relates to perceived deprivation in a population of 66 normal weight, noneating disordered female college freshmen. Results revealed a significant positive association between perceived deprivation and dietary restraint, concerns about dieting and weight gain during the first year of college. Lowe and Levine (2005) have highlighted that most restrained eaters do not maintain their body weights at levels low enough to trigger a biological drive to eat in order to return to a homeostatic body weight. Rather, they hypothesized that restrained individuals only feel deprived because they impose rules about the types and quantities of food they are able to eat. When restrained individuals inevitably break these rules, they fall prey to the abstinence violation effect and subsequently continue to eat previously forbidden foods, at times in large amounts. Dietary Restraint and Weight Change in Community dwelling Adults Several studies have found that high levels of dietary restraint are associated with weight gain among community dwelling adults. Drapeau et al. (2003) loo ked at the association between dietary restraint and weight change over a six year period among 20

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75 community dwelling men and women. Results indicated that women ( n = 45) classified at baseline as restrained eaters gained 4.9 kg ( SEM = 1.5 kg) over the six year study, as compared to unrestrained women who gained 0.5 kg ( SEM = 1.5) over the same time period, p < .05. The effect was nonsignificant among male participants ( p > .05). A prospective study conducted by Klesges, Isbell and Klesges (1992) looked at the association between dietary restraint and weight change among a community dwelling sample of 287 Caucasian women and men with a mean age of 35.7 years (SD = 4.5). Results showed that among women, the two significant predictors of weight change over the oneyear study period were baseline dietary restraint and baseline body weight. Specifically, higher restraint scores were associated with significantly greater weight gain over the study period ( p < .0001). In a cross sectional, community based study of 1,587 male and female monozygotic twins, Schur, Noonan, Polivy, Goldberg and Buchwald (2009) looked at the association between dietary restraint and self reported weight and BMI change over a 3year period. Results for the entire sample revealed that highly restrained eaters gained 3.1 kg (95% CI = 2.5 to 3.8) over the study period. In comparison, intermediate restrained eaters gained 2.2 kg (95% CI = 1.9 to 2.5) and low restrained eaters gained 1.3 kg (95% CI = .7 to 1.7). The differences in weight c hange between all three restraint categories were statistically significant ( p s < .01). Restraint and “Dieting” It has been suggested that dietary restraint and “dieting” are separate concepts and that dietary restraint impacts eating behavior in a differ ent manner than short term weight loss attempts, or “dieting” (Lowe, Whitlow, & Bellwoar, 1991) . In order to 21

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examine how dieting may impact eating behavior, Lowe (1994) placed restrained and unrestrained eaters on a twoday “diet” or “no diet.” Results from the study revealed that over the short term (i.e., two days) restrained dieters ate significantly less than restrained nondieters. The opposite pattern was found among unrestrained eaters (i.e., unrestrained dieters ate significantly more than unrestrained nondieters). Lowe interpreted these results to mean that in the short term, dieting increased restrained individuals’ motivation to restrict their eating. A significant criticism of this study is the short length of the externally imposed diet. While restrained individuals may be able to successfully restrict their food intake for brief periods of time, disinhibition and the counter regulatory effect may be observed over the longer term. In another study conducted by Lowe, Foster, Kerzhnerman, Swain and Wadden (2001) , 42 obese, restrained, non binge eaters were assigned for eight weeks to either a weekly weight loss group (“dieters” condition) or a group that focused on the potential pitfalls of dieting (“undieters” condition). At pretest, participants were randomly assigned to either a preload or no preload condition and then subjected to an ostensible taste test. Results revealed that among restrained eaters at both pretest and eight weeks post test, there were nonsignificant differences in the amount of food consumed between the preload and no preload conditions. A significant limitation of this study is that there was no maintenance period, and it is therefore unknown how “diet” participants would have performed once external supports (i.e., weight loss group) were removed. Eating and Body related Psychopathology in College Females The lifetime prevalence of Anorexia Nervosa, Bulimia Nervosa, and Binge Eating Disorder are 0.6%, 0.6%, and 2.8%, respectively, although the prevalence of t hese 22

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disorders and subthreshold eatingrelated cognitions and behaviors are higher among college females (Hudson, Hiripi, Pope, & Kessler, 2007; Keel, Heatherton, Dorer, Joiner, & Zalta, 2006; Striegel Moore et al., 2009; Taylor et al., 2006) . The peak age of onset of eating disorders among females is approximately 16 to 20 years of age (Striegel Moore et al., 2003) , or around the same time that college bound young adults leave home. In addition to developmental stage, the college social environment and a cademic stressors are believed to contribute to the high rates of eatingrelated psychopathology in this population (Berg, Frazier, & Sherr, 2009) . Given the susceptibility of this population to disordered eating thoughts and behaviors, it should be ensur ed that weight gain prevention interventions implemented with this population do not lead to a worsening of these concerns. A study conducted by Berg et al. ( 2009) examined the prevalence of eating disorders and eatingrelated psychopathology among a sam ple of 324 female university students. Results revealed that approximately 49% of women endorsed engaging in binge eating and/or compensatory behavior at least once per week. Another study by Taylor et al. (2006) found that among a sample of 480 college females, approximately 35 to 40% of participants endorsed difficulties with controlling their weight, reported that they view themselves as “too fat,” and/or reported a desire to be thinner. Importantly, eatingrelated psychopathology is associated with l ow self confidence, low self esteem, and feelings of shame (Fairburn et al., 1998) . Excessive shape and weight concerns have also been identified as major risk factors for the onset of full threshold eating disorders (Stice, 2002) . 23

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Taken together, these st udies suggest that there are high rates of subclinical eating disorder related behaviors and cognitions among college females. This pathology is associated with poor mental health indicators and puts the individual at increased risk for developing a full threshold eating disorder. While weight loss interventions have generally been found to be fairly free of adverse psychological effects in obese individuals (French, 1999; Klem, Wing, McGuire, Seagle, & Hill, 1997) the effects of weight loss intervention on eating and body related psychopathology among normal weight college females has not been examined. In summary, evidence from laboratory studies suggests that high levels of dietary restraint may be associated with a counter regulatory eating pattern, such that individuals with high levels of dietary restraint consume more food following exposure to various disinhibitors than individuals with low levels of dietary restraint. Studies of community dwelling adults also suggest that high levels of dietary restraint are associated with greater weight gain and earlier onset of obesity over the longterm. Regarding the connection between dieting and weight change, while some short term studies examining this association appear to suggest that there is no relation, these studies have either utilized an extremely brief induction or have not examined the effects of dieting beyond the initial intervention. For these reasons, the current study sought to examine how high levels of dietary restraint may be related to longer term weight change following an initial weight gain prevention intervention. The study also sought to examine how changes in binge eating and hunger may act as mediators between pretreatment levels of dietary restraint and longer term weight change. Finally, given that the current study population 24

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included female college freshmen, a demographic at risk for the development and/or exacerbation of eatingrelated cognitions and behaviors, the current study sought to examine how high pretreatment lev els of dietary restraint and initial weight changes may be related to longer term changes in eatingrelated psychopathology. Specific Aims and Hypotheses The primary aim of the current study was to examine how degree of dietary restraint is related to longer term weight change following participation in a brief weight gain prevention program. The primary hypothesis was that higher levels of dietary restraint at pretreatment would be associated with greater weight regain from post treatment to threemonth fo llowup. The second aim of the current study was to investigate the degree to which changes in binge eating and hunger may mediate the relation between degree of dietary restraint and longer term weight change. The secondary hypothesis was that increases in binge eating and hunger from post treatment to three month follow up would partially mediate the relation between degree of dietary restraint and weight change from post treatment to follow up, such that restrained individuals would evidence greater inc reases in binge eating, hunger and weight gain during the follow up period. The tertiary aim of the current study was to assess the association between dietary restraint and longer term changes in eating, body shape and weight concerns. The tertiary hypothesis was that individuals with higher levels of dietary restraint at pretreatment would exhibit significantly greater increases in eating, shape and weight concerns from post treatment to three month follow up. 25

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Finally, an exploratory aim of the current study was to examine potential differences in types of weight management strategies employed by restrained and unrestrained eats during the follow up period. 26

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CHAPTER 2 METHODS Participants Participants in the current study were 95 first year female undergraduate students from the University of Florida. An original sample size of 98 was decided on in order to provide a power of .80 (alpha = .05) for detecting a moderate effect size ( f =.25) in the difference of mean weight change from post treatment to follow up between restrained and unrestrained eaters. Effect size provides a standardized measure of the strength of the relation between two variables. Effect size conventions differ for d and f. Regarding d, effect size conventions are as follows: 0. 20 = small, 0.50 = moderate and 0.80 = large (Cohen, 1992). In comparison, effect size conventions for f are as follows: 0.10 = small, 0.25 = moderate and 0.40 = large (Cohen, 1992). No studies were identified that prospectively examined changes in body w eight following a weight loss intervention in individuals identified at pretreatment as restrained and unrestrained eaters. Similarly, no studies were identified that estimated differences in caloric intake following weight loss intervention in individuals identified at pretreatment as restrained and unrestrained eaters. Furthermore, it was not appropriate to base the power analysis on differences in weight regain between intervention and control groups following typical short term weight loss intervention, as doing so would have masked the potential subgroup differences in treatment response that are the focus of the current study. Given that there were no appropriate, currently existing data on which to base the power analysis for the current study, the m oderate effect size of f = .25 was selected. 27

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The current study was limited to female students for several reasons. First, research revealed that females present with higher levels of dietary restraint than males (Drapeau et al., 2003; Klesges et al., 1992) . If it was found that high levels of dietary restraint are associated with poorer weight loss outcomes, this finding would have greater implications for females. Second, prior research demonstrated that behavioral interventions involving physical activit y have different effects on males and females (Calfas et al., 2000; Donnelly et al., 2003) . Exclusionary criteria for the current study included the following: BMI < 22; eating disorder or a significantly eating disordered eating pattern; medical conditio n that affects weight; current medication that affects weight; serious infectious disease; pregnancy (or expressed intent to become pregnant during the following year); unwillingness to provide informed consent; or unwillingness to accept randomization int o the fall semester or spring semester groups. Only participants who completed both screening visits were eligible to be included in the study. The exclusionary criteria for the current study hold several implications. First, given that individuals with s ignificant eating disorder psychopathology were excluded from participation, findings from the current study may be inapplicable to such individuals. Additionally, measures of central tendency from the current study population (e.g., median dietary restraint score) could be lower than those derived from a sample of college females that include individuals with significant eating disorder symptomatology. Second, the current study included individuals who are normal weight, overweight, and obese. As such, the study findings will not be specific to obese individuals, which is the population of focus for the majority of studies examining patterns of weight regain. 28

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Recruitment To achieve the proposed sample size of 98, initial efforts focused on attempting to recruit 135 female undergraduate students (assuming a 15% dropout/withdrawal rate between recruitment and group start and a 15% attrition rate between group start and the end of the semester). All participants were recruited from the University of Florida. Recruitment methods included distribution of study flyers around campus and in residence halls; announcement at new student orientations, other university events, and in freshman classes; and ads on ResTV (closed circuit television station in residence halls) and in the Independent Florida Alligator (a student newspaper distributed throughout campus). Interested individuals were instructed to call a local telephone number to obtain more information about the study and, if interested, to be screened for initial eligibility criteria. Following the initial telephone screening, interested individuals were asked to meet inperson for Screening Visit 1. At this visit, potential participants were asked to read and a sign a consent form, after which the project director or a trained research assistant measured and recorded their height and weight. At Screening Visit 2, approximately one to two weeks later, participants were informed of their randomization. Importantly, between Screening Visits 1 and 2, participants were required to complete three online 24hour diet recalls and the study questionnaires. If these items were not completed by Screening Visit 2, individuals were not allowed to participate in the study. Two screening visits were required in order t o decrease attrition. Assessment of body weight and completion of study questionnaires were repeated five weeks later and again two months later at the end of the semester. 29

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Intervention The current study was conducted within the context of a freshman weight gain prevention study that randomized participants to either an immediate fiveweek weight loss intervention in the fall semester or a wait list control group that received the intervention in the spring semester. Given that both groups ultimately recei ved the weight loss intervention, the current study included all study participants in the analyses to maximize power. The weight gain prevention intervention consisted of a 5 week weight loss program focused on producing an initial weight loss of 1.4 – 2 .3 kg to buffer against future weight gain. The intervention focused on aiding individuals in reducing caloric intake and increasing physical activity, implementing self monitoring of caloric intake and body weight, and improving self regulatory skills ( see Appendix A for session outlines). Participants were taught self monitoring and self regulatory skills to help them achieve weight loss. They were also encouraged to explore resources for tracking daily caloric intake and physical activity (e.g., fitday.com, sparkpeople.com, thedailyplate.com). In addition to learning skills for managing weight, participants were also instructed on the Stoplight Diet as a means of increasing the quality of their nutritional intake and decreasing dietary fat intake. The Stoplight Diet helps individuals to improve diet quality by providing guidelines for increasing consumption of fruits, vegetables, and lean proteins (i.e., “Green” foods), limiting intake of highnutrient, highcalorie foods, such as whole grains and low fat dairy (i.e., “Yellow” foods), and limiting consumption of highfat, low nutrient, highsodium foods (i.e., “Red” foods). Participants were 30

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encouraged to maintain simplified food records, based on the Stoplight Diet, for the remainder of the program. The decision to have participants keep simplified food records instead of more detailed records was made for several reasons. First, given the importance of self monitoring for the successful longterm regulation of body weight, it was decided that some form of self monitoring was needed. However, this was also weighed against the significant effort and time burden required of more detailed food records. Specifically, the cost (significant effort and time associated with keeping detailed food records) would likely outweigh the perceived benefits, as many participants were likely attempting to lose fairly small amounts of weight. With regards to physical activity, participants were guided on increasing their daily activity levels to 30 minutes per day of m oderateintensity physical activity (e.g., brisk walking). For participants who were already at this level and for those who achieved this level during the intervention, this goal was increased to one hour per day of moderateintensity physical activity. This goal was based on research conducted by Jakicic and Otto (2005) who reported that one hour per day of moderateintensity physicial activity is associated with longterm weight maintenance among women. At the conclusion of the fiveweek intervention, participants were encouraged to continue to engage in daily self weighing and completion of self monitoring logs based on the Stoplight Diet. Participants were provided with extra sets of records and preaddressed campus mailers to return these records to t he study investigator. Additionally, participants were provided with a goal sheet that reiterates strategies associated with successful longterm weight maintenance, as well as action plans for 31

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when participants exceeded their “management” weight range (i. e., > 0.9 kg and > 2.3 kg above their pretreatment weight). Participants were encouraged to call or email their group leader if they experienced difficulty staying within their “management” weight range. Participants randomized to the control group received the identical intervention during the first five weeks of the spring semester. During the fall semester, the control group received no study intervention and their only contact with study staff related to the scheduling and attending of study assessments . Measures At baseline, individuals’ height and weight were measured and used to determine their BMI. As an eligibility requirement, individuals were also asked to complete questionnaires using the Survey Monkey data management system and to complete three online 24hour dietary recalls (Subar et al., 2007) on two nonconsecutive weekdays and one weekend day. The measures used in this study are described below and the full forms can be found in Appendix B. The forms in Appendix B contain the content but not the format of the forms as they appeared electronically via Survey Monkey. Survey Monkey allowed participants to complete the forms electronically while the data were stored on secure servers. All measures were administered at pretreatment (beginning of the semester), immediately following the intervention (post treatment), and at 3month follow up (end of the semester). Height and Weight Height was measured to the nearest .001 m with a digital stadiometer. Weight was measured to the nearest 0.1 kg usi ng a calibrated digital scale. Participants were weighed in light indoor clothing and without shoes. To ensure stability of weight 32

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measurements, assessment visits occured early in the morning, and participants were instructed to fast for 12 hours before their visits (beginning the previous night) and to void their bowels prior to weighing. Dietary Restraint The Three Factor Eating Questionnaire – Cognitive Dietary Restraint subscale (TFEQ R) was used to assess dietary restraint (Stunkard, 1985). Scores for the TFEQ R range from 0 to 21, with lower scores indicating less restraint and higher scores indicating greater restraint. The TFEQ R has excellent internal consistency, with estimates ranging from .80 to .90 (Allison, Kalinsky, & Gorman, 1992; Laessle, Tuschl, Kotthaus, & Prike, 1989). The TFEQ R also possesses excellent test retest reliability over a 2w eek period, r = .91 (Allison et al., 1992). The measure was also found to have excellent convergent validity with the Dutch Eating Behavior Questionnaire ( r = .89), which is another frequently used measure to assess dietary restraint (Allison et al., 1992). Furthermore, unlike the Restraint Scale (another commonly used measure of dietary restraint), the TFEQ R has been found to be reliable and valid not only among individuals of normal weight, but also among overweight and obese individulas (Allison et al ., 1992; Ruderman, 1983; van Strien, Peter Herman, Engels, Larsen, & van Leeuwe, 2007). Regarding classification of participants as restrained or unrestrained eaters, no clinical cut offs currently exist for classifying individuals in this manner. The mos t frequently used method of classification involves determining the median dietary restraint score in a study population, then classifying individuals with scores above the median as restrained eaters and individuals with scores below the median as unrestr ained eaters (Boon, V ogelzang, & Jansen, 2000; Herman & Mack, 1975; Lowe & 33

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Timko, 2004; Morris, Goldsmith, Roll, & Smith, 2001). The current study utilized the same methodology in order to increase comparability between studies. However, it is important t o be able to contextualize the median score for the current study population. To this end, Table 2 1 presents the TFEQ R median score cut offs for nine other studies that have utilized this methodology. Binge Eating The Binge Eating Scale (BES) was used to assess the severity of binge eating (Gormally, Black, Daston, & Rardin, 1982). BES scores were treated as a continuous variable. A study conducted by Timmerman (1999) examined the measure’s concurrent validity by correlating BES scores with 28 day food records. BES scores were moderately correlated with both subjective binge days and binge episodes ( r = .39 and r = .40) and objective (i.e., > 1000 kcal in a 2hour period) binge days and binge episodes ( r = .32 and r = .30, respectively). Shape, Eati ng, and Weight Concerns Shape, eating, and weight concerns were meaured using the subscales from the Eating Disorder Examination – Questonnaire version (EDE Q). Items on the EDE Q were taken directly from corresponding EDE items and are scored using the s ame sevenpoint rating scale. The EDE Q has adequate to excellent concurrent validity with the EDE. Among non eatingdisordered females, estimates for the Shape concern subscale (EDE Q S) range from .78 to .80, and estimates for the Weight concern subscal e (EDEQ W) range from .77 to .79 (Fairburn & Baglin, 1994; Mond, Hay, Rodgers, Owen, & Beumont, 2004). The concurrent validity for the Eating concern subscale (EDE Q E) has been estimated to be .68 (Mond et al., 2004). The internal consistency of the thr 34

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from .78 to .93 (Luce & Crowther, 1999). The same study also found that twoweek test retest reliabilities of the three subscales are excellent, with r s ranging from .87 to .94. Caloric Intake Caloric intake was measured using the online Automated Self Administered Dietary Recall (ASA24) (Subar et al., 2007). The ASA 24 utilizes the USDA Food and Nutrient Database and the Baylor College of Medicine’s Food Intake Recording Software to enable respondants to select the food and drinks they consume using a “food pathway.” The pathway probes individuals for foods, portions, and betweenmeal snacks that may otherwise be easily forgotten. At each assessment point, participants were asked to com plete three dietary recalls: two on nonconsecutive weekdays and one on a weekend day. Weight Management Strategies The frequency of participants’ utilization of specific weight management strategies was assessed using the Weight Management Questionnaire ( WMQ). The WMQ was developed internally and there are no publisehd data on the measure’s validity or reliability. Examples of strategies that are assessed include frequenccy of self weighing, self monitoring of food intake and physical activity, meal planni ng and decreasing portion sizes. Statistical Analyses Primary Aim Missing data at threemonth follow up were imputed using multiple imputation (Rubin, 1976) . Analyses were conducted to examine potential betweengroup differences in pretreatment BMI and w eight change from pretreatment to post treatment. 35

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Any significant betweengroup differences would be included as covariates in the analyses. Linear regression was used to determine the effect of pretreatment dietary restraint (independent variable) on longer term weight change (dependent variable). If the effect was significant, a follow up multiple regression analysis was planned to explore potential differential effects related to when participants begin the intervention (i.e., fall versus spring semester). Secondary Aim Bootstrap mediation was used to determine the extent to which changes in binge eating and hunger from post treatment to follow up act as mediators between degree of pretreatment dietary restraint and weight change from post treatment to f ollowup. Bootstrapping is a nonparametric re sampling procedure for testing mediation. Benefits of bootstrapping mediation are that the procedure is robust to nonnormal sampling distributions, multiple mediators can be tested simultaneously, and the p robability of committing a Type 1 error is decreased by minimizing the number of inferential tests (Preacher & Hayes, 2004, 2008) . Tertiary Aim Three separate linear regressions , with Bonferroni adjustment for family wise error, were conducted to determine the effect of pretreatment dietary restraint (independent variable) on changes in shape, eating and weight concerns (dependent variables) from post treatment to threemonth follow up. It was also initially proposed that three additional linear regressions would be conducted to assess the potential associations between pretreatment dietary restraint and preto post treatment changes in shape, eating, or weight concerns. If significant associations were discovered, it was 36

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proposed that the change in the relevant variable (i.e., shape, eating and/or weight concern) would be included as a covariate in the analysis. Exploratory Aim It was also proposed that exploratory analyses would be conducted to examine potential differences in types of weight management strategies employed by restrained and unrestrained eaters from post treatment to threemonth follow up. To account for the large number of tests to be conducted, a more conservative alpha of < .01 was selected for determination of statistical significance. Additionally, it was proposed that five t tests would be conducted to examine potential differences between initial treatment “successes” and “failures” on changes in eatingrelated psychopathology, as assessed using the EDEQ subscales and total score. It was proposed that initial treatment success be operationally defined as weight treatment to post treatment, and that initial treatment failure be defined as either weight gain or weight loss of < 1 pound during the same time per iod. 37

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Table 21. TFEQ R median split cut off scores Reference (year) Population (n) Score Lowe & Kleifield (1988) female undergraduate college students (42) 10 Ridgway & Jeffrey (1998) female undergraduate college students (104) 10 Tepper, Choia, & Nayga (1997) community sample of adult men (137) 10 Bryant, Kiezebrink, King, & Blundell (2010) community sample of men and women (426) 9 Beiseigel & Nickols Richardson (2004) female undergraduate students (65) 9 Van Loan & Keim (2000) community sample of pre menopausal women (185) 9 Rutters, Nieuwenhuizen, Lemmens, & Westerterp Plantenga (2009) community sample of men and women (76) 9 Chambers & Yeomans (2011) female college students (736) 8 Goldfield & Legg (2006) female undergraduate college students (30) 7 38

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CHAPTER 3 RESULTS Participants A total of 364 individuals completed an initial phone screen for the current study. Of these individuals, 177 signed an informed consent form and attended an initial in person assessment visit. After completion of the initial in person assessment visit, a total of 95 individuals met all criteria to be included in the current study. Participants were recruited for the current study in two waves – the first in August/September 2010 and the second in August/September 2011. All 95 eligible participants were randomized to complete the intervention in either the fall or spring semester: 47 were randomized to the fall condition and 48 were randomized to the spring condition. Figure 31 displays participant flow throughout the course of the study. Baseline participant characteristics are presented in Table 31. Total n s for all measures were 95 except for the BES and EDE Q ( n s = 54), as these measures were included only for the second s tudy wave. At pretreatment the mean SD age (years) of participants was 18.5 0.3, mean body weight (kg) was 69.4 12.6, and mean BMI (kg/m2) was 26.8 6.4. Based on the WHO weight categories ( World Health Organization, 1995) , 41.1% (n=39) of participants were in the “normal weight” range (18.524.9), 46.3% (n=44) were in the “overweight” range (25.029.9), and 12.6% (n=12) were in the “obese” range (30 and higher). Using multiple imputation methodology (Rubin, 1976) , mean weight change (kg) for all st udy participants from pretreatment to post treatment was .05 39

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(SD range = 1.92 to 2.0). Mean weight change for all study participants from post treatment to 3month follow up was 0.24 (SD range = 2.0 to 2.2). Examination of mean weight changes in the treat ment versus control groups during the fall semester revealed that for the treatment group, the mean weight change (kg) was .02 (SD range = 1.9 to 2.0). In the same group, weight change from post treatment to follow up was 0.6 (SD range = 1.9 to 2.0). In the control group, initial weight change was 0.4 (SD range = 1.5 to 1.6) and weight change during the follow up period was 0.1 (SD range = 1.6 to 1.9). Table 32 presents the means and SDs for body weights in both groups at each assessment point. At pretreatment, participants’ mean SD dietary restraint score was 11. 49 4.29 and the median score was 12, which is somewhat higher than the median score in other studies of female college students (Beiseigel & Nickols Richardson, 2004; Chambers & Yeomans, 2011; Goldfield & Legg, 2006; Lowe & Kleifield, 1988; Ridgway & Jeffrey, 1998) . Baseline dietary restraint and baseline weight and BMI were not correlated (ps > .05). Table 33 presents correlations between all baseline measures and weight changes from preto post treatment and post treatment to follow up among all study participants. Regarding the racial and ethnic makeup of the study population, 58.9% ( n = 56) of participants self identified as “white nonHispanic,” 26.3% ( n = 25) as “black, nonHispanic, ” 25.3% ( n = 24) as Hispanic, 5.3% ( n = 5) as “Asian,” 3.2% ( n = 3) as multiple races, and 6.3% ( n = 6) chose to not respond. 40

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Attendance and Adherence For all study participants, the mean SD for attendance was 2.91 1.98 sessions, out of a possible tot al of five sessions. When makeup sessions were included in addition to attendance at regularly scheduled sessions, participants completed 3.26 2.05 sessions. A total of 73 participants attended at least 1 regularly scheduled session. Among these 73 par ticipants, the mean for attendance at regularly scheduled sessions was 3.78 1.34 sessions. When makeup sessions were added, attendance among this group averaged 4.23 1.17 sessions. Among this same subgroup, participants completed 15.2 10.8 daily f ood records, with a range of 0 to 33 records. Primary Aim In order to address the issue of missing data at post treatment and follow up, data were mult iply imputed using the multiple i mputation addon for IBM SPSS Statistics v.20 (Rubin, 1976) . A missin g values analysis revealed a nonmonotonic pattern of missing data and therefore fully conditional specification was used to create five imputed datasets ( IBM Corporation, 2011) . Examination of general linear model assumptions revealed that the data were distributed linearly and homoscedastically. However, there was evidence that the data for the dependent variable (i.e., weight change from post treatment to follow up) was leptokurtic, with standardized estimates of kurtosis ranging from 2.079 to 2.973 acr oss the original and five imputed datasets. A distribution from one of the multiply imputed datasets is presented in Figure 32 . While transformations can be used successfully to adjust for skew and negative kurtosis, no acceptable transformations currentl y exist to address the issue of 41

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leptokurtosis (Fink, 2009) . Leptokurtic distributions are indicative of limited variability and are commonly associated with difficulty in detecting an effect due to restriction of range. Next, bivariate correlations were c onducted to examine whether there were significant associations between pretreatment dietary restraint and the following variables: pretreatment BMI ( r = .087, p = .403, pooled) and weight change from pretreatment to post treatment ( r = .037, p = .728, pooled). As the correlations were not significant, these variables were not included as covariates in the below analysis. Finally, a linear regression was conducted with pretreatment dietary restraint as the independent variable and weight change from post t reatment to followup as the dependent variable. While pooled results are not available for linear regression ( IBM Corporation , 2011) , results from the analysis for the original and five imputed datasets all indicated a nonsignificant association between pretreatment dietary restraint and longer term weight change. Results are presented in Table 34. Based on the observed parameters, post hoc analysis revealed that a sample size of 705 participants would have been necessary to achieve statistical significa Secondary Aim Bootstrap mediation methodology (Preacher & Hayes, 2008) was utilized to examine the total and specific indirect effects of self reported changes in binge eating and hunger from post treatment to follow up on changes in weight from during the same time period (Fig. 33 ). Results from the analysis revealed that there was a nonsignificant total indirect effect of the proposed mediators on 42

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changes in weight from post treatment to follow up (95% bias corrected CI [ .0841, .0261]). Further examination revealed that the specific indirect effects of changes in binge eating (95% bias corrected CI [ .0889, .0122]) and changes in hunger (95% bias corrected CI [ .0120, .0535]) from post treatment to follow up were similarly non significant. Additionally, the total and specific indirect effects of self reported changes in b inge eating and hunger from pretreatment to post treatment on changes in weight during the same time period were also examined. Results revealed a nonsignificant total indirect effect of the proposed mediators on changes in weight from pretreatment to pos t treatment (95% bias corrected CI [ .0491, .0766]). Similarly, the specific indirect effects of changes in binge eating (95% bias corrected CI [ .0620, .0250]) and changes in hunger (95% bias corrected CI [ .0082, .0887]) were nonsignificant. Tertiary Aim Three separate linear regressions were conducted to determine the effect of pretreatment dietary restraint (independent variable) on changes in shape, eating and weight concerns (dependent variables) from post treatment to threemonth follow up. Addit ionally, three linear regressions were conducted to examine potential associations between pretreatment dietary restraint and preto post treatment changes in shape, eating, and weight concerns. Results from these analyses revealed that change in eating c oncerns from preto post treatment was associated with pretreatment dietary restraint ( p = .047). As such, this variable was included as a covariate in the analysis of the association 43

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between pretreatment dietary restraint and changes in eating concerns f rom post treatment to follow up. Results from the three linear regressions revealed nonsignificant associations between pretreatment dietary restraint and changes in shape, eating, and weight concerns prior to correction for family wise error ( p s = .308, .347, and .287, respectively). Exploratory Aims Two exploratory aims examined potential effects for the primary aim among specified subgroups. A third exploratory aim examined potential differences in utilization of weight management strategies between restrained and unrestrained eaters. A fourth exploratory aim compared initial treatment “successes” and “failures” on changes in eating disorder symptoms from preto post treatment. Analysis of Primary Aim among “Fall Only” The primary aim was reexamined using only data from individuals who received the intervention in the fall semester ( n = 45). As in the primary aim, bivariate correlations revealed that there were nonsignificant associations between pretreatment dietary restraint and pretreatment BM I ( r = .171, p = .250, pooled) and weight change from pretreatment to post treatment ( r = .016, p = .918, pooled). Therefore, these variables were not included as covariates in the analysis. As with results for the primary aim, while pooled results are not available for linear regression, results from the analysis for the original and five imputed datasets all indicated a nonsignificant relation between pretreatment 44

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dietary restraint and longer term weight change among participants randomized to the fal l condition. Results are presented in Table 34 . Additionally, this analysis was also conducted on a dataset that was specifically imputed for the treatment condition in the fall group only. Results from this analysis were similarly nonsignificant for baseline to post treatment and post treatment to follow up ( p s = .17 and .89, respectively). Analysis of Primary Aim among Overweight and Obese Participants The primary aim was also revisited among those individuals with BMIs in the overweight and obese cat n = 56). This approach was based on the rationale that individuals in the higher BMI categories may demonstrate greater variability in weight change outcomes, thereby increasing the likelihood of being able to observe an effect if one exists. Bivariate correlations revealed nonsignificant associations between pretreatment dietary restraint and pretreatment BMI (r = .084, p = .538, pooled) and weight change from pretreatment to post treatment ( r = .142, p = .305, pooled). Therefore, these variables were not included as covariates in the analysis. As seen in the results for the primary aim, while pooled results are not available for linear regression, results from the analysis for the original and five impu ted datasets all indicated a nonsignificant association between pretreatment dietary restraint and longer term weight change among overweight and obese participants. Results are presented in Table 34 . Utilization of Weight Management Strategies Two taile d t tests were conducted to examine whether restrained and unrestrained eaters differed significantly on their self reported utilization of 36 45

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weight management strategies. Individuals were classified as restrained or unrestrained based on a median split ( dietary restraint score at the May (final) assessment visit. Utilization of weight management strategies was also assessed at the May visit. Results revealed that unrestrained eaters reported keeping a daily fat gram goal for 2.29 days per month, as opposed to 1.44 days per month among restrained eaters ( t = 2.827, df = 31, p = .008), which was deemed significant at Initial Weight Loss Success/Failure and Change in Eating Psychopathology Two tailed t tests were conducted to explore potential differences between initial treatment “successes” and “failures” on changes in eatingrelated psychopathology from preto post treatment. For this “extreme groups” analysis, initial tr from pre to post treatment. Initial treatment failure was defined as an increase in weight during the same time period. Of the 95 total participants, 14 individuals lost at least 4 pounds and 39 participants gained weight during initial treatment. Results from six t tests revealed that initial treatment successes and failures did not differ significantly on self reported changes in dietary restraint, eating concern, shape concern, wei ght concern, total EDEQ score or binge eating from preto post treatment. Flexible vs. Rigid Dietary Restraint Participants’ scores on the TFEQ R were recalculated to produce “Flexible Control” and “Rigid Control” scores (Westenhoefer, Stunkard, & Pudel, 1999) . Participants’ mean SD Flexible Control score was 3.8 1.7 and Rigid Control 46

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score was 3.3 1.8. Four separate linear regressions were conducted to evaluate the relations between Flexible Control and Rigid Control on changes in weight from pre t o post treatment and post treatment to follow up. Results revealed nonsignificant effects of Flexible and Rigid Controls on preto post treatment weight change ( = .03, t = .25, p = .80 and = .05, t = .41, p = .69, respectively). Results further rev ealed nonsignificant effects of Flexible and Rigid Controls on weight change from post treatment to follow up ( = .09, t = .59, p = .56 and = .09, t = .67, p = .50, respectively). 47

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Table 31. Baseline participant characteristics Mean SD n Age (years) 18.5 0.3 95 Weight (kg) 69.4 12.6 95 Height (cm) 161.6 9.1 95 BMI (kg/m 2 ) 26.8 6.4 95 TFEQ Restraint 11.5 4.3 95 Disinhibition 6.8 3.5 95 Hunger 5.9 3.4 95 BES 8.0 6.4 54 EDEQ Restraint 1.8 1.2 54 Eating concern 1.0 1.1 54 Shape concern 2.9 1.6 54 Weight concern 3.2 1.5 54 Total score 2.2 1.1 54 Race n (%) White non Hispanic 56 (58.9) Black non Hispanic 25 (26.3) Asian 5 (5.3) Multiple races 3 (3.2) Declined to respond 6 (6.3) Ethnicity Hispanic 24 (25.3) Non hispanic 71 (74.7) Note. TFEQ = Three Factor Eating Questionnaire, BES = Binge Eating scale, EDEQ = Eating Disorder Examination Questionnaire 48

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Table 32. Mean SD body weights for treatment and control groups Treatment Control M SD a M SD a Baseline Weight 68.9 14.4 69.9 10.7 Post test Weight 68.9 14.4 14.7 70.3 11.1 11.2 Follow up Weight 69.5 14.3 14.6 70.3 11.4 11.6 Note. Within and between group differences were not significant at p < .05 a The range of SDs are provided for the five imputed datasets at post test and follow up, as pooled SDs are not available 49

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Table 33. Baseline Pearson Correlations Between All Measures Measure Weight TFEQ Restraint TFEQ Disinhibition TFEQ Hunger BES EDEQ Restraint EDEQ Eating EDEQ Shape EDEQ Weight EDEQ Total TFEQ Restraint Correlation .129 p value .212 n 95 TFEQ Disinhibition Correlation .025 .015 p value .811 .887 n 95 95 TFEQ Hunger Correlation .031 .392 b .458 b p value .765 .000 .000 n 95 95 95 BES Correlation .052 .117 .682 b .272 a p value .711 .407 .000 .049 n 53 53 53 53 EDEQ Restraint Correlation .048 .565 b .265 .143 .332 a p value .732 .000 .053 .303 .015 n 54 54 54 54 53 EDEQ Eating Correlation .303a .205 .499 b .218 .512 b .462 b p value .025 .137 .000 .113 .000 .000 n 54 54 54 54 53 54 EDEQ Shape Correlation .247 .126 .557 b .165 .690 b .410 a .656 b p value .071 .364 .000 .235 .000 .002 .000 n 54 54 54 54 53 54 54 EDEQ Weight Correlation .312a .171 .385 a .105 .614 b .372 a .478 b .841 b p value .021 .218 .004 .453 .000 .005 .000 .000 n 54 54 54 54 53 54 54 54 EDEQ Total Correlation .284 a .311 a .528 b .110 .673 b .666 b .776 b .920 b .862 b p value .037 .022 .000 .431 .000 .000 .000 .000 .000 n 54 54 54 54 53 54 54 54 54 Note. TFEQ = Three Factor Eating Questionnaire, BES = Binge Eating Scale, EDEQ = Eating Disorders Examination Questionnaire a Correlation is significant at p p

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Table 34. Regression Results for Primary Aim and Exploratory Aims 1 and 2 Dataset B SE B p Primary Aim Original 0.037 0.059 .074 .005 .53 Pooled 0.017 0.052 --.74 Exploratory Aim 1 Original 0.065 0.075 .145 .021 .39 Pooled 0.039 0.067 --.55 Exploratory Aim 2 Original 0.073 0.084 .135 .018 .39 Pooled 0.060 0.072 --.41 Note. Pooled results for multiply imputed datasets are noted when available 51

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Figure 31 . Participant flow diagram Assessed for eligibility (n=177) Included in study (n=95) Excluded (n=82) Incomplete assessment (n=56) BMI <22 (n=13) Did not attend study visit (n=11) Possible disordered eating (n=2) Lost to follow up/unable to schedule (n=9) Included in analysis (n=95) Eligibility Allocation Followup Analysis 52

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Figure 32 . Distribution of weight changes from post treatment to follow up 53

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Figure 33 . Model of proposed indirect effects of changes in binge eating and hunger on changes in weight Change in B inge eating Change in Hunger (post treatment to follow up) Dietary Restraint (pretreatment) Change in Weight (post treatment to follow up) a c b 54

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CHAPTER 4 DISCUSSION Results from the current study revealed a nonsignificant association between pretreatment levels of dietary restraint and longer term weight change. These results remained consistent when the association was examined among the subgroup of participants receiving the intervention in the fall, as well as among the subgroup of participants who were overweight or obese. In accordance with these findings, results from the current study also revealed that restrained and unrestrained eaters did not differ significantly in their utilization of behavioral weight management strategies. Finally, changes in self reported binge eating and hunger were unrelated to changes in weight during the follow up period. The implications of these results, as well as plausible explanations for these findings, are discussed in the following section. Weight Change Following Intervention Research targeting weight gain prevention in young adults, particularly college freshmen, often faces certain challenges. A recent metaanalysis of weight gain prevention interventions with young adults (i.e., individuals 18 to 35 years of age) found that a notable proportion of studies had high dropout rates and did not utilize intentionto treat analyses (Hebden, Chey, & AllmanFarinelli, 2012) . This increases the risk that the study results were biased and that participants may appear to have been more successful in losing or maintaining weight than they actually were. While the current st udy had fairly good attendance, acceptable follow up rates and utilized intentionto treat methodology, a drawback of the current study is that participants’ weight did not change significantly in response to the intervention. There are several plausible e xplanations that may account for this. First, the study utilized a 55

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brief, five week intervention. The rationale for using a fiveweek intervention was that this length of time would minimize participant burden (and thereby minimize dropout and adherence issues), while still allowing sufficient time for participants to learn behavioral weight management strategies. However, research has shown that interventions of longer duration produce greater amounts of weight loss (Perri, 1989) . Additionally, some participants stated that initially it was difficult to carve out time in their schedules to attend the group sessions. However, they said that once they reserved this time in their schedules, it was not a major challenge to attend the sessions. Additional ly, many participants expressed that they wished the sessions continued throughout the semester, much like a regular class. For these reasons it is possible that a longer intervention would have been more effective in producing significant weight change and may actually have been feasible and acceptable to participants. The lack of significant weight change in the current study may also be understood through the framework of the Health Belief Model (Janz & Becker, 1984) . Briefly, as applied to weight gain prevention, the Health Belief Model assumes that individuals are most likely to make healthy weight related behavior changes when they perceive that 1) they are susceptible to gaining weight/becoming obese, 2) making healthy behavior changes would decrease their chances of gaining weight/becoming obese, 3) gaining weight/becoming obese would have severe consequences, 4) the barriers to making the healthy behavior changes are few and 5) they can successfully overcome the barriers to making the healthy behavi or changes. 56

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Several of these assumptions may not hold true among a young adult college population and may help to explain why participants in the current study did not achieve greater weight reductions. Regarding the first assumption, very young adults of ten possess a sense of invulnerability and a belief that negative outcomes are only likely to befall other people (Elkind, 1967) . This sense of invulnerability may lead young adults to feel that unhealthy weight related behaviors are unlikely to result in negative consequences (i.e., obesity and associated health problems) for them . This perceived lack of consequences may lead to decreased motivation to make healthy behavior changes. Related to this, many obesity related chronic health problems are commonl y associated with advanced age. Even if young adults recognize that they are susceptible to becoming obese and developing associated health problems, the perceived distal nature of these consequences may lead young adults to dismiss or defer the need to m ake healthy changes in the present. Lastly, the Health Belief Model holds that individuals are most likely to make positive changes if they perceive the barriers to be few and easily surmountable. Weight management is commonly viewed as a fairly difficul t endeavor with many obstacles (Ciao, Latner, & Durso, 2012) , e.g., perceived high cost of healthy food, making healthy choices while dining out, dealing with cravings, managing urges to engage in emotional eating and finding time to prepare healthy food and engage in physical activity. Given the many perceived challenges to successful weight management, combined with the academic, social and time management demands associated with college life, participants in the current study may have felt that they were unable to overcome the 57

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obstacles to managing their weight. This in turn may have decreased individuals’ motivation to persist in their attempts to make healthy changes. Correlations between Baseline Measures Analysis of correlations between baseline measures revealed that higher pretreatment body weight was significantly associated with greater eating and weight related concerns. However, pretreatment body weight was not associated with other domains of eatingrelated psychopathology, such as dietary r estraint, disinhibition, binge eating and concerns about body shape. These findings suggest that in this healthy female student population, individuals with higher body weights experience some degree of preoccupation with eating and weight concerns. Prim ary Aim The hypothesis that elevated pretreatment levels of dietary restraint would be associated with greater weight regain during follow up was not supported in this study. Contrary to the findings from the current study, laboratory based studies have found a consistent association between elevated dietary restraint and counter regulatory eating, where highly restrained individuals (as compared to low restrained individuals) actually consume greater amounts of food over the short term when faced with various disinhibitors ( Herman & Polivy, 1975; Markowitz et al., 2008; Polivy, 1976; Spencer & Fremouw, 1979) . While dietary restraint theory was originally grounded in results from laboratory based studies, other researchers began to test the theory outside of the artificial confines of the laboratory setting. This has led to the development of a literature on dietary restraint theory that, while still promising, is more mixed on the application to free living individuals. Results from longitudinal, observational studies predominantly 58

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suggest that individuals with higher levels of dietary restraint show greater increases in weight over time, as well as an earlier onset of obesity (Drapeau et al., 2003; Klesges et al., 1992; Stice, Cameron, Killen, Hayward, & Taylor, 1999) . In contrast to these findings, two br ief randomized clinical trials provide evidence contrary to restraint theory and suggest that with very short term “diets,” there is an association between higher levels dietary restraint and lower calor ic intake (Lowe, 1994; Lowe et al., 2001) . The results from the current study have several plausible explanations. First, it is possible that the limited variability in weight change outcomes (as discussed in the previous section) obscured an existing effect. This is a common, and currently irremediable, issue with study results in which the dependent variable forms a leptokurtic distribution (Fink, 2009) . Another related explanation is that, given the small changes in weight, the study may not have been s ufficiently powered to detect an effect. However, if the size of the study sample was increased and a statistically significant effect was then found, it may call into question the clinical significance of such an effect. Another possible explanation for the study results is that the hypothesis is not supported and dietary restraint is unrelated to longer term weight change following weight loss intervention in a female student population. Secondary Aim The utilization of bootstrap mediation allowed for t he examination of indirect effects on weight change, despite the lack of a significant main effect of dietary restraint on weight change during follow up (Preacher & Hayes, 2008) . Results from the analysis revealed nonsignificant indirect effects of changes in binge eating and hunger scores from post treatment to followup on changes in weight over the same time period. Similarly, results for the total and specific indirect effects of changes in binge eating and 59

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hunger scores from pretreatment to post tre atment on changes in weight during the same time period were also not significant. As with the primary aim, a possible explanation for this finding is that mean weight change for the study sample was very small, thereby potentially obscuring an existing effect. Also as with the primary aim, another possible explanation is that an effect does not exist. Tertiary Aim The peak age of onset of eating disorders is approximately 1620 years of age (Striegel Moore et al., 2003) . Additionally, the lifetime prevalence of full and subthreshold eating disorders is higher among females who attend college than in the general population (Striegel Moore et al., 2009; Taylor et al., 2006) . For these reasons, weight gain prevention programs with college females should be examined to determine the effects of intervention on subsequent body imagerelated concerns. In the current study, results from three separate linear regressions revealed that the level of self reported dietary restraint at pretreatment was related to increases in eatingrelated concerns, but not with body shape or weight concerns, from pretreatment to post treatment. However, dietary restraint at pretreatment was not associated with changes in shape, weight, or eating concerns from post treatment to follow up. These results, which are the first of their kind in the weight gain prevention literatur e, suggest that among college female freshmen (a group at elevated risk for the development of eating disorders), the degree of dietary restraint prior to entering a weight gain prevention program is unrelated to later changes in body shape, eating, and w eight concerns. 60

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Exploratory Aims Analysis of Primary Aim among “Fall Only” While a main effect of pretreatment dietary restraint on longer term weight change was not found, an exploratory analysis revisited the aim among the subset of individuals who rec eived the intervention in the fall semester. The rationale for this was that these individuals’ weight related behaviors had less opportunity to be affected by the college environment prior to initiation of the intervention. The results from the analysi s revealed that there was a nonsignificant effect among this subsample. These results suggest that timing of the intervention does not account for the lack of a relation between pretreatment dietary restraint and longer term weight change. Analysis of Pr imary Aim among Overweight and Obese Participants An exploratory aim was also conducted to reexamine the primary aim among a subset of individuals whose BMI scores fell in the “overweight” and “obese” ranges. The rationale was that this subgroup of indivi duals would experience more variability in weight change outcomes and that therefore there would be a greater likelihood of being able to detect an effect if one did indeed exist. Contrary to the hypothesis, results from the analysis revealed that there was a nonsignificant association between pretreatment dietary restraint and longer term weight change among the subset of overweight and obese individuals. Similar to the primary aim, these findings may be explained by the restriction of range in weight ch ange outcomes, or the possibility that an effect does not exist. Utilization of Weight Management Strategies Another exploratory aim was conducted to examine potential differences in the utilization of 36 weight management strategies between restrained and unrestrained 61

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eaters. Results revealed that restrained and unrestrained eaters differed significantly only on the frequency with which they kept a daily fat gram goal (1.58 vs. 2.29 days, respectively). While this finding was statistically significant, it is not clinically meaningful and the preponderance of evidence suggests that restrained and unrestrained eaters do not differ in their utilization of weight management strategies, which is in accordance with findings from the primary analysis. Initial Wei ght Loss Success/Failure and Change in Eating Psychopathology T test results revealed that initial weight loss success or failure was unrelated to self reported changes in eatingrelated psychopathology (i.e., binge eating, dietary restraint and eating, shape and weight concerns) from preto post treatment. These results suggest that in a female college freshmen population, favorable response to weight gain prevention intervention is not associated with a worsening of eating disorder symptoms. No other studies were identified that examined the relation of treatment response and changes in eatingrelated psychopathology. Flexible vs. Rigid Dietary Restraint Results from linear regression revealed that participants’ degree of Flexible Control and Rigid Control were unrelated to weight change from preto post treatment and post treatment to follow up. Prior research suggests that greater Flexible Control is associated with lower BMI and lower caloric intake for both males and females, and that greater Rigid Control is associated with higher BMI for both males and females, as well as with greater caloric intake for females (Westenhoefer et al., 1999) . Another randomized, controlled study by Teixeira et al. (2010) examined the potential moderating effects of Flex ible Control on weight change following intervention. Participants were 225 overweight and obese women (mean SD BMI = 31.3 4.1 62

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kg/m2 and age = 37.6 7.0 years) who were randomized to a 1year group weight management intervention or a health education control condition. At both 1year and 2year follow ups, increased Flexible Control was associated with statistically significant decreases in body weight ( r = .40, p < .001; r = .24, p < .01, respectively). In the current study, the nonsignificant relations of Flexible Control and Rigid Control with initial and longer term weight changes may be due to lack of an effect, or it may be attributable to the restricted range in weight changes outcomes. Limitations A limitation of the current study is the brevity of the intervention, particularly as it relates to the nonsignificant changes in weight and associated restriction of range issue. Specifically, if the intervention had been longer, it is possible that individuals would have experienced greater init ial decreases in weight. With greater initial decreases in weight there likely would have been more variability in weight change during the follow up period, which may have allowed for improved detection of existing effects. Related to this, given the sm all changes in weight, another limitation of the current study is that it may have been underpowered to detect an effect. However, if the size of the study sample was increased and an effect was found, the clinical relevance of any such effect may be brought into question. Another limitation is that for the secondary aim changes in binge eating and hunger were measured concurrently with changes in weight. It would have been more appropriate to assess the potential mediators at an interim point between post treatment and follow up. However, it was not feasible to do this in the current study as it would have presented too great an assessment burden on the study participants. Another 63

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limitation is that males, as well as women reporting significant eating dis order psychopathology, were excluded from participation. As such, the results may not generalize to these individuals. Strengths The current study has a number of strengths related to novelty, racial/ethnic diversity and analytic methodology. First, a si gnificant strength of the current study is that it is the first of its kind to examine the relation of dietary restraint to weight change during a maintenance period. While other studies have examined dietary restraint and food consumption in laboratory settings, as well as the association between dietary restraint and initial weight changes, the current study is the first to examine dietary restraint and longer term weight change following weight loss intervention. Second, the study population had a high degree of racial and ethnic diversity. More than a quarter of participants identified as “black, nonHispanic” and another quarter identified as Hispanic. This diversity in the study population makes the results more generalizable to the population at large. Another strength of the current study is that it utilized multiple imputation to address the issue of missing data. Other methods for handling missing data that are frequently used in research (e.g., baseline carried forward, last observation carried forward, listwise deletion of missing cases) have the effect of biasing the data and study results. The main benefit of using multiple imputation is that it infers sampling distributions and allows for the inclusion of all cases and data in the analysis. Finally, the current study utilized bootstrap mediation to analyze the secondary aim. The benefit of this approach is that, even though there was a nonsignificant association between pretreatment dietary restraint and weight change during follow up, 64

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it was still appropriate to examine the total and specific indirect effects of the proposed mediators on weight change. Future Directions It is wellaccepted that preventing the growth of the obesity epidemic is a key public health priority ( Department of Health and Human Services, 2010) . One approach to preventing weight gain is to identify points during which individuals are most likely to gain weight (e.g., freshmen year of college), and then aid them in losing a modest amount of weight to buffer agains t future weight gain. To ensure optimal outcomes, it is also important to identify factors that may be associated with poor treatment response, so that programs can be appropriately tailored to address these barriers. One such factor that may impede longterm success is a high degree of dietary restraint. Laboratory studies provide consistent evidence that elevated dietary restraint is associated with increased caloric consumption in the short term. Observational studies also support the claim that greater dietary restraint is predictive of weight gain over time. However, contrary to these findings, limited evidence from two randomized trials and the current prospective study suggest that there is either a neutral or beneficial effect of elevated dietary restraint on short and longer term weight changes. Given the importance of developing effective weight gain prevention interventions, combined with the current mixed evidence on the association between dietary restraint and short and longterm weight chang e, it remains worthwhile to further investigate the matter. In order to address the limitations in the literature and the current study, future studies should focus on testing restraint theory with freeliving individuals, incorporate a longer initial intervention, include a maintenance period and utilize intentionto treat methodology. 65

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Conclusion Results from this study do not provide support for restraint theory in the context of a weight gain prevention program with female college freshmen. There are several plausible explanations for the findings, including obscuring of existing effects due to limited variability in weight changes, the possibility that the study was underpowered, and the prospect that dietary restraint theory does not hold true in a prospective study with free living individuals. However, given that the literature contains mixed results, along with the importance of developing effective weight gain prevention programs, the current state of the evidence is not sufficient to discard rest raint theory and the potential it holds for understanding longer term response to weight gain prevention intervention. For this reason, it is remains worthwhile for future studies to attempt to further clarify the role of dietary restraint in weight gain prevention. 66

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APPENDIX A OUTLINE OF SESSIONS Session 1: Introduction to the Intervention & Self Monitoring What is weight maintenance? Impact of environment on weight Calories in vs. calories out: setting a calorie goal Introduction to self monitoring Session 2: Problem Solving & Taking Control of Eating Patterns What happens when your plans don't work out? Setting realistic goals Overcoming barriers Eating patterns & Eating regularly Session 3: Becoming Active & Understanding Fad Di ets Learn national recommendations for physical activity Find activity that's fun for you! What are fad diets? Are they effective? Session 4: Improving Nutrition & Body Image Introduction to the Stoplight Diet Media impact on body image: what is ideal? Improving body image! Session 5: Eating Out, Planning for Holidays & Special Events, & Long Term Success! Eating out without eating too much Controlling portion sizes Planning ahead for special events Strategies for long term success 67

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APPENDIX B MEASURES THREE FACTOR EATING QUESTIONNAIRE For questions 136, answer “TRUE” if you agree with the statement, or feel it is true as applied to you. Answer “FALSE” if you disagree with the statement, or feel that it is false as applie d to you. T RUE FALSE 1. When I smell a sizzling steak or see a juicy piece of meat, I find it very difficult to keep from eating, even if I have just finished a meal. 2. I usually eat too much at social occasions, like parties and picnics. 3. I am usually so hungry that I eat more than three times a day. 4. When I have eaten my quota of calories, I am usually good about not eating anymore. 5. Dieting is so hard for me because I just get too hungry. 6. I deliberately take small helpings as a means of controlling my weight. 7. Sometimes things just taste so good that I keep on eating even when I am no longer hungry. 8. Since I am often hungry, I sometimes wish that while I am eating, an expert would tell me that I have had enough or that I can have something more to eat. 9. When I feel anxious, I find myself eating. 10. Life is too short to worry about dieting. 68

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11. Since my weight goes up and down, I have gone on reducing diets more than once. 12. I often feel so hungry that I just have to eat something. 13. When I am with someone who is overeating, I usually overeat too. 14. I have a pretty good idea of the number of calories in common foods. 15. Sometimes when I start eating, I just can’t seem to stop. 16. It is not difficult for me to leave something on my plate. 17. At certain times of the day, I get hungry because I have gotten used to eating then. 18. While on a diet, if I eat food that is not allowed, I consciously eat less for a period of time to make up for it. 19. Being with someone who is eating often makes me hungry enough to eat also. 20. When I feel blue, I often overeat. 21. I enjoy eating too much to spoil it by counting calories or watching my weight. 22. When I see a real delicacy, I often get so hungry that I have to eat right away. 23. I often stop eating when I am not really full as a conscious means of limiting the amount that I eat. 24. I get so hungry that my stomach often seems like a bottomless pit. 25. My weight has hardly changed at all in the last ten years. 69

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26. I am always hungry so it is hard for me to stop eating before I finish the food on my plate. 27. When I feel lonely, I console myself by eating. 28. I consciously hold back at meals in order not to gain weight. 29. I sometimes get very hungry late in the evening or at night. 30. I eat anything I want, any time I want. 31. Without even thinking about it, I take a long time to eat. 32. I count calories as a conscious means of controlling my weight. 33. I do not eat some foods because they make me fat. 34. I am always hungry enough to eat at any time. 35. I pay a great deal of attention to changes in my figure. 36. While on a diet, if I eat a food that is not allowed, I often then splurge and eat other high calorie foods. Please answer the following questions by filling in the circle corresponding to the letter of the response that is appropriate to you. 37. How often are you dieting in a conscious effort to control your weight? \030 \030 \030 not at all slightly moderately very much 70

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39. How often do you feel hungry? \030 \030 \030 never rarely often always 41. How difficult would it be for you to stop eating halfway through dinner and not eat for the next four hours? \030 \030 \030 easy slightly difficult moderately difficult very difficult 42. How conscious are you of what you are eating? avoid “stocking up” on tempting foods?

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46. How likely are you to consciously eat slowly in order to cut down on how much you eat? \030 \030 \030 almost never seldom at least once a week almost every day 48. How likely are you to consciously eat less than you want? \030 \030 \030 unlikely slightly likely moderately likely very likely 49. Do you go on eating binges even though you are not hungry? \030 \030 \030 never rarely sometimes at least once a week 50. To what extent does this statement describe your eating behavior? “I start dieting in the morning, but because of any number of things that happen during the day, by evening I have given up and eat what I want, promising myself to start dieting again tomorrow.” \030 \030 \030 not like me little like me pretty good description of me describes me perfectly 51. On a scale of 1 to 6, where 1 means no restraint in eating (eat whatever you want, whenever you want it) and 6 means total restraint (constantly limiting food intake and never “giving in”), what number would you give yourself? \030 \030 \030 \030 \030 1 2 3 4 5 6 72

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BES Below are groups of numbered statements. Read all of the statements in each group and fill in the bubble for the one that best describes the way you feel about problems you have controlling your eating behavior. 1. O I don’t feel self conscious about my weight or body size when I’m with others. O I feel concerned about how I look to others, but it normally does not make me feel disappointed with myself. O I do get self conscious about my appearance and weight, which makes me feel disappointed in myself . O I feel very self conscious about my weight, and frequently I feel intense shame and disgust with myself. I try to avoid social contacts because of my self consciousness. 2. O I don’t have any difficulty eating slowly in the proper manner. O Although I seem to “gobble down” foods, I don’t end up feeling stuffed because of eating too much. O At times, I tend to eat quickly and then I feel uncomfortable afterwards. O I have a habit of bolting down my food without really chewing it. When this happens I usually feel uncomfortably stuffed because I’ve eaten too much. 3. O I feel capable of controlling my eating urges when I want to. O I feel that I have failed to control my eating more than the average person. O I feel utterly helpless when it comes to feeling in control of my eating urges. O Because I feel so helpless about controlling my eating, I have become very desperate about trying to get in control. 4. O I don’t have the habit of eating when I’m bored. O I sometimes eat when I’m bored, but often I’m able to “get busy” and get my mind off food. O I have a regular habit of eating when I’m bored, but occasionally, I can use some other activity to get my mind off eating. O I have a strong habit of eating when I’m bored. Nothing seems to help me break the habit. 5. O I’m usually physically hungry when I eat something. O Occasionally, I eat something on impulse even though I really am not hungry. 73

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O I have the regular habit of eating food that I might not really enjoy, to satisfy a hungry feeling, even though physically I don’t need the food. O Even though I’m not physically hungry, I get a hungry feeling in my mouth that only seems to be satisfied when I eat a food, like a sandwich, that fills my mouth. Sometimes, when I eat the food to satisfy my mouth hunger, I then spit the food out so that I won’t gain weight. 6. O I don’t feel any guilt or self hate after I overeat. O After I overeat, I occasionally feel guilt or self hate. O Almost all the time I experience strong guilt or self hate after I overeat. 7. O I don’t lose total control of my eating when dieting, even after periods when I overeat. O Sometimes when I eat a “forbidden food” on a diet, I feel like I “blew it” and eat even more. O Frequently, I have t he habit of saying to myself, “I’ve blown it now, why not go all the way,” when I overeat on a diet. When that happens I eat even more. O I have a regular habit of starting strict diets for myself, but I break the diets by going on an eating binge. My life seems to be either a “feast” or a “famine.” 8. O I rarely eat so much food that I feel uncomfortably stuffed afterwards. O Usually about once a month, I eat such a large quantity of food, I end up feeling very stuffed. O I have regular times during the month when I eat large amounts of food, either at mealtime or at snacks. O I eat so much food that I regularly feel quite uncomfortable after eating and sometimes a bit nauseous. 9. O My level of calorie intake does not go up very high or down very low on a regular basis. O Sometimes after I overeat, I will try to reduce my caloric intake to almost nothing to compensate for the excess calories I’ve eaten. O I have a regular habit of overeating during the night. It seems that my routine is not to be hungry in morning, but to overeat in the evening. O In my adult years, I have had weeklong periods where I practically starve myself. This follows periods when I overeat. It seems I live a life of either “feast” or “famine.” 10. O I usually am able to stop eating when I want to. I know when “enough is enough.” O Every so often, I experience a compulsion to eat, which I can’t seem to control. 74

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O Frequently I experience strong urges to eat, which I seem unable to control, but at other times I can control my eating urges. O I feel incapable of controlling urges to eat. I have a fear of involuntarily not being able to stop eating. 11. O It is not difficult for me to stop eating when I feel full. O I usually can stop eating when I feel full, but occasionally I overeat, after which I feel uncomfortably stuffed. O It is difficult for me to stop eating once I start, and usually I feel uncomfortably stuffed after I eat. O Because it is difficult for me to stop eating when I want to, I sometimes have to induce vomiting to relieve my stuffed feeling. 12. O I seem to eat just a much when I’m with others (family, social gatherings) as when I’m by myself. O Sometimes when I’m with other people, I don’t eat as much as I want to eat because I’m self conscious about my eating. O Frequently, I eat only a small amount of food when others are present because I’m very embarrassed about my eating. O I feel so ashamed about overeating that I pick times to overeat when I know no one will see me. I feel like a “c loset eater.” 13. O I eat three meals a day with only an occasional betweenmeal snack. O I eat three meals a day, but I also normally snack between meals. O When I am snacking heavily, I get in the habit of skipping regular meals. O There are regular periods when I seem to be continually eating, with no planned meals. 14. O I don’t think much about trying to control unwanted eating urges. O At least some of the time, I feel my thoughts are preoccupied with trying to control my eating urges. O I feel that frequently I spend much time thinking about how much I ate, or about trying to not eat anymore. O It seems to me that most of my waking hours are preoccupied by either thoughts of eating or not eating. I feel like I’m constantly struggling not to eat. 15. O I don’t think about food a great deal. O I have strong cravings for food, but they last only for brief periods of time. O I have days when I can’t seem to think about anything else but food. 75

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O Most of my days seem to be preoccupied with thoughts about food; I feel like I live to eat. 16. O I usually know whether or not I’m physically hungry. I take the right portion of food to satisfy me. O Occasionally, I feel uncertain about knowing whether or not I’m physically hungry. At these times it’s hard to know how much food I should take to satisfy me. O Even though I might know how many calories I should eat, I don’t have any idea what is a “normal” amount of food for me. 76

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EATING HABITS QUESTIONNAIRE The following questio ns are concerned with the PAST FOUR WEEKS ONLY (28 days). Please read each question carefully and circle the appropriate number on the right. Please answer all the questions. On HOW MANY DAYS OUT OF THE PAST 28 DAYS No 1 5 6 12 1315 1622 2337 every days days days days days days day 1. Have you been consciously trying to restrict the amount of food you eat in order to influence your shape or weight 0 1 2 3 4 5 6 2. Have you gone for long periods of time (8 hours or more) without eating anything in order to influence your shape or weight? 0 1 2 3 4 5 6 3. H ave you attempted to avoid eating any foods which you like in order to influence yo ur shape or weight? 0 1 2 3 4 5 6 4. Have you attempted to follow definite rules regarding your eating in order to influence your shape or weight; for example, a calorie limit, a set amount of food, or rules about what or w hen you should eat? 0 1 2 3 4 5 6 5. Has thinking about food or its calorie content interfered significantly with your ability to concentrate on things you are interest in; for example, reading, watching TV, or following a conversation? 0 1 2 3 4 5 6 6. Have you had a definite fear that you might not be able to either resist or stop eating? 0 1 2 3 4 5 6 7. Have you experienced a sense of loss of control over eating? 0 1 2 3 4 5 6 8. Have you had any episodes of binge eating? 0 1 2 3 4 5 6 77

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No 1 5 6 12 1315 1622 2337 every days d ays days days days days day 9. Have you eaten in secret? (do not count binges) 0 1 2 3 4 5 6 10. Have you had a definite desire for your stomach to be flat? 0 1 2 3 4 5 6 11. Have you had a definite desire for your stomach to feel empty? 0 1 2 3 4 5 6 12. Has thinking about your shape or weight interfered with your ability to concentrate on things you are interested in; for example, reading, watching TV, or following a conversation? 0 1 2 3 4 5 6 13. Have you had a definite fear that you might gain weight or become fat? 0 1 2 3 4 5 6 14. Have you felt fat? 0 1 2 3 4 5 6 15. Have you had a strong desire to lose weight? 0 1 2 3 4 5 6 ________________________________________________________________ 16. On what proportion of the times that you have 0=None of the times eaten have you felt guilty because of your 1= A few of the times shape or weight? (Do not count binges) 2=Less than half the times 3= Half the times 4=More than half the times 5=Most of the time 6=Every time ________________________________________________________________ 17. Have there been times when you have eaten 0=NO what other people would regard as an unusually 1=YES large amount of food? Please circle. 18. How many such episodes have you had over the past four weeks? ______ 19. During how many of these episodes of overeating did you have a sense of having lost control? ______ ________________________________________________________________ 78

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20. Have you had other episodes of eating in which 0=NO you have had a sense of having lost control but 1=YES have not eaten an unusually large amount of food? (Please ci rcle) 21. How many such episodes have you had over the past four weeks? ______ ________________________________________________________________ 22. Have you made yourself sick (vomit) as a means 0=NO of controlling your shape or weight, or to counteract 1=YES the effects of eating? 23.On how many days out of the last 28 have you done this? ______ ________________________________________________________________ 24. Have you taken laxatives as a means of controlling 0=NO your shape or weight, or to counteract the effects 1=YES of eating? 25. ON how many days out of the last 28 have you done this? ______ ________________________________________________________________ 26. Have you taken diuretics (water tablets) as a 0=NO means of controllin g your shape or weight, or 1=YES to counteract the effects of eating? 27. On how may days out of the last 28 have you done this? ______ ________________________________________________________________ 28. Have you vigorously exercised as a means of 0=NO controlling your weight, altering your shape 1=YES or amount of fat, or burning off calories? 29. On how many days out of the last 28 have you done this? ______ ________________________________________________________________ 79

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OVER THE PAST FOUR WEEKS (28 DAYS) Not at all slightly moderately markedly 30. Has your weight influenced how you think about (judge) yourself as a person? 0 1 2 3 4 5 6 ________________________________________________________________ 31. Has your shape influenced how you think about (judge) yourself as a person? 0 1 2 3 4 5 6 ________________________________________________________________ 32. How much would it distress you if you had to weight yourself once a week for the next four weeks? 0 1 2 3 4 5 6 ________________________________________________________________ 33. How dissatisfied have you felt about your weight? 0 1 2 3 4 5 6 _________________________________ _______________________________ 34. How dissatisfied have you felt about your shape? 0 1 2 3 4 5 6 ________________________________________________________________ 35. How thin have you wanted to be? 0 1 2 3 4 5 6 ________________________________________________________________ 36. How concerned have you been about other people seeing you eat? (only circle 4,5, or 6, if you have av oided some occasions.) 0 1 2 3 4 5 6 ________________________________________________________________ Not at all slightly moderately markedly 37. How uncomfortable have you felt seeing your body; for example, in a mirror, in s hop window reflections, while undressing or taking a bath or shower? (Only circle 4,5 or 6, if you have avoided some occasions) 0 1 2 3 4 5 6 38. How uncomfortable have you felt about others seeing your body; for example, in communal changing rooms, when swimming or wearing tight clothes? (Only circle 4, 5 or 6, if you have avoided some occasions.) 0 1 2 3 4 5 6 ________________________________________________________________ 80

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Have the past four weeks been representative 1=NO of the past year? 2=YES If NO, how has the past year differed from the past four weeks? _________________________________ ___________________________ 81

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WEIGHT MANAGEMENT QUESTIONNAIRE PART I The following items describe strategies that some people use to manage their weight. Please indicate how often you CURRENTLY (over the past month) use these strategies, ranging from 028 days per month. HOW OFTEN IN THE PAST MONTH HAVE YOU (Please indicate number of days, 028) 1. Weighed yourself? _____days 2. Planned your meals ahead of time? _____days 3. Tried to slow down your pace of eating? _____days 4. Kept a food record of what you eat? _____days 5. Written down calories on a food record? _____days 6. Kept a goal for the amount of calories you eat per day? _____days 7. Kep t a goal for the amount of fruits and vegetables you eat per day? _____days 8. Kept a goal for the grams of fat you eat per day? _____days 9. Tried to increase your intake of whole grains/fiber? _____days 10. Tried to limit eating out at restaur ants? _____days 11. Eaten breakfast? _____days 82

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12. Worn a pedometer to calculate daily steps? _____days 13. Written down the number of minutes you’ve exercised? _____days 14. Tried to avoid doing other activities (e.g., watching TV) while eating? _____days 15. Used strategies to eat smaller portions? _____days 16. Chosen lower calorie options of particular foods? _____days 17. Tried to avoid eating late at night? _____days 18. Tried to avoid particular snack foods? _____days 83

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WEIGHT MANAGEMENT QUESTIONNAIRE PART II The following questions ask you to rate how often you have used these strategies SINCE THE PROJECT SEE GROUPS ENDED, ranging from 1 (never) to 7 (every day). 19. How often since the program ended have you weighed yourself? 1 2 3 4 5 6 Never Rarely Sometimes Often Most of the Time Every day (Several times/year) (Once per month) (3 4 times/month) (Several times/ week) 20. How often since the program ended have you planned your meals ahead of time? 1 2 3 4 5 6 Never Rarely Sometimes Often Most of the Time Every day (Several times/year) (Once per month) (3 4 times/month) (Several times/ week) 21. How often since the program ended have you tried to slow down your pace of eating? 1 2 3 4 5 6 Never Rarely Sometimes Often Most of the Time Every day (Several times/year) (Once per month) (3 4 times/month) (Several times/ week) 22. How often since the program ended have you kept a food record of what you eat? 1 2 3 4 5 6 Never Rarely Sometimes Often Most of the Time Every day (Several times/year) (Once per month) (3 4 times/month) (Several times/ week) 84

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23. How often since the program ended have you written down calories on a food record? 1 2 3 4 5 6 Never Rarely Sometimes Often Most of the Time Every day (Several times/year) (Once per month) (3 4 times/month) (Several times/ week) 24. How often since the program ended have you kept a goal for the amount of calories you eat per day? 1 2 3 4 5 6 Never Rarely Sometimes Often Most of the Time Every day (Several times/year) (Once per month) (3 4 times/month) (Several times/ week) 25. How often since the program ended have you kept a goal for the amount of fruits and vegetables you eat per day? 1 2 3 4 5 6 Never Rarely Sometimes Often Most of the Time Every day (Several times/year) (Once per month) (3 4 times/month) (Several times/ week) 26. How often since the program ended have you kept a goal for the grams of fat you eat per day? 1 2 3 4 5 6 Never Rarely Sometimes Often Most of the Time Every day (Several times/year) (Once per month) (3 4 times/month) (Several times/ week) 27. How often since the program ended have you tried to increase your intake of whole grains/fiber? 1 2 3 4 5 6 Never Rarely Sometimes Often Most of the Time Every day (Several times/year) (Once per month) (3 4 times/month) (Several times/ week) 85

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28. How often since the program ended have you tried to limit eating out at restaurants? 1 2 3 4 5 6 Never Rarely Sometimes Often Most of the Time Every day (Several times/year) (Once per month) (3 4 times/month) (Several times/ week) 29. How often since the program ended have you eaten breakfast? 1 2 3 4 5 6 Never Rarely Sometimes Often Most of the Time Every day (Several times/year) (Once per month) (3 4 times/month) (Several times/ week) 30. How often since the program ended have you worn a pedometer to calculate daily steps? 1 2 3 4 5 6 Never Rarely Sometimes Often Most of the Time Every day (Several times/year) (Once per month) (3 4 times/month) (Several times/ week) 31. How often since the program ended have you written down the number of minutes you’ve exercised? 1 2 3 4 5 6 Never Rarely Sometimes Often Most of the Time Every day (Several times/year) (Once per month) (3 4 times/month) (Several times/ week) 32. How often since the program ended have you tried to avoid doing other activities (e.g., reading, watching TV) while eating? 1 2 3 4 5 6 Never Rarely Sometimes Often Most of the Time Every day (Several times/year) (Once per month) (3 4 times/month) (Several times/ week) 86

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33. How often since the program ended have you used strategies to eat smaller portions? 1 2 3 4 5 6 Never Rarely Sometimes Often Most of the Time Every day (Several times/year) (Once per month) (3 4 times/month) (Several times/ week) 34. How often since the program ended have you chosen lower calorie options of particular foods? 1 2 3 4 5 6 Never Rarely Sometimes Often Most of the Time Every day (Several times/year) (Once per month) (3 4 times/month) (Several times/ week) 35. How often since the program ended have you tried to avoid eating late at night? 1 2 3 4 5 6 Never Rarely Sometimes Often Most of the Time Every day (Several times/year) (Once per month) (3 4 times/month) (Several times/ week) 36. How often since the program ended have you tried to avoid particular snack foods? 1 2 3 4 5 6 Never Rarely Sometimes Often Most of the Time Every day (Several times/year) (Once per month) (3 4 times/month) (Several times/ week) 87

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Hebden, L., Chey, T., & AllmanFarinelli, M. (2012). Lifestyle intervention for preventing weight gain in young adults: A systematic review and metaanalysis of RCTs. Obesity Reviews , 13(8), 692710. doi : 10.1111/j.1467789X.2012.00990.x Herman, C. P., & Mack, D. (1975). Restrained and unrestrained eating. Journal of Personality, 43(4), 647660. doi: 10.1111/j.14676494.1975.tb00727.x Herman, C. P., & Polivy, J. (1975). Anxiety, restraint, and eating behavior. Journal of Abnormal Psychology, 84(6), 666672. doi: 10.1037/0021843x.84.6.666 Herman, C. P., Polivy, J. (1984). A boundary model for regulation of eating. Psychiatric Annals, 13(12), 918927. http://www.psychiatricannalsonline.com/cmeInfo.asp Hudson, J. I., Hiripi, E., Pope Jr . , H. G. , & Kessler, R. C. (2007). The prevalence and correlates of eating disorders in t he National Comorbidity Survey r eplication. Biological Psychiatry, 61(3), 348 358. d oi : 10.1016/j.biopsych.2006.03.040 IBM Corporation. (2011). IBM SPSS Missing Values 20 . Chicago, IL: Author . Jakicic, J. M., & Otto, A. D. (2005). Physical activity considerations for the treatment and prevention of obesity. The American Journal of Clinical Nutrition, 82(1), 226S 229S. http://ajcn.nutrition.org/ Janz, N. K., & Becker, M. H. (198 4). The Health Belief Model: A decade l ater. Health Education & Behavior, 11(1), 1 47. doi: 10.1177/109019818401100101 Jeffery, R. W., & French, S. A. (1999). Pre venting weight gain in adults: The Pound of P revention study. Am erican Journal of Public Health, 89(5), 747751. doi: 10.2105/ajph.89.5.747 Jia, H. L., & Lubetkin, E. I. (2005). The impact of obesity on healthrelated quality of life in the general adult US population. Journal of Public Health, 27(2), 156– 164. doi: 10.1093/pubmed/fdi025 Keel, P. K., Heatherton, T. F., Dorer, D. J., Joiner, T. E., & Zalta, A. K. (2006). Point prev alence of Bulimia N ervosa in 1982, 1992, and 2002. Psychological Medicine, 36(1), 119127. doi: 10.1017/S0033291705006148 Klem, M., Wing, R., McGuire, M., Seagle, H., & Hill, J. (1997). A descriptive study of individuals successful at longterm maintenance of substantial weight loss. The American Journal of Clinical Nutrition, 66(2), 239246. http://ajcn.nutrition.org/ Klesges, R. C., Isbell, T. R., & Klesges, L. M. (1992). Relationship between dietary restraint, energy intake, physical activity, and body weight: A prospective analysis. Journal of Abnormal Psychology, 101(4), 668674. doi: 10.1037/0021843x.101.4.668 91

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Laessle, R. G., Tuschl, R. J., Kotthaus, B. C., & Prike, K. M. (1989). A comparison of the validity of three scales for the assessment of dietary restraint. Journal of Abnormal Psychology, 98(4), 504507. doi: 10.1037/0021843x.98.4.504 Lewis, C. E., Jacobs , D. R., McCreath, H., Kiefe, C. I., Schreiner, P. J., Smith, D. E., & Williams, O. D. (2000). Weight gain continues in the 1990s: 10year trends in weight and overweight from the CARDIA study. American Journal of Epidemiology, 151(12), 11721181. doi: 10. 1093/oxfordjournals.aje.a010167 Lowe, M. R. (1994). Putting restrained and unrestrained nondieters on short term diets: Effects on eating. Addictive Behaviors, 19(4), 349356. doi: 10.1016/03064603(94)900574 Lowe, M. R., Foster, G. D., Kerzhnerman, I., Swain, R. M., & Wadden, T. A. (2001). Restrictive dieting vs. "undieting": Effects on eating regulation in obese clinic attenders. Addictive Behaviors, 26(2), 253266. doi: 10.1016/S03064603(00)001064 Lowe, M. R., & Kleifield, E. I. (1988). Cognitive restraint, weight suppression, and the regulation of eating. Appetite, 10(3), 159168. doi: 10.1016/01956663(88)900098 Lowe, M. R., & Levine, A. S. (2005). Eating motives and the controversy over dieting: Eating less than needed versus less than w anted. Obesity Research, 13(5), 797806. doi: 10.1038/oby.2005.90 Lowe, M. R., & Timko, C. A. (2004). What a difference a diet makes: Towards an understanding of differences between restrained dieters and restrained nondieter s. Eating Behaviors, 5(3), 199208. doi: 10.1016/j.eatbeh.2004.01.006 Lowe, M. R., Whitlow, J. W., & Bellwoar, V. (1991). Eating regulation: The role of restraint, dieting, and weight. International Journal of Eating Disorders, 10(4), 461471. doi: 10.1002/1098108x(199107)10:4<461::aideat2260100411>3.0.co;2u Luce, K. H., & Crowther, J. H. (1999). The r eliability of the Eating Disorder Examination Self Report Questionnaire Version (EDE Q). International Journal of Eating Disorders, 25(3), 349351. doi : 10.1002/(SICI)1098108X(199904)25:3<349::AID EAT15>3.0.CO;2M Markowitz, J. T., Butryn, M. L., & Lowe, M. R. (2008). Perceived deprivation, restrained eating and susceptibility to weight gain. Appetite, 51(3), 720722. doi: 10.1016/j.appet.2008.03.017 92

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Preacher, K., & Hayes, A. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879891. doi: 10.3758/brm.40.3.879 Ridgway, P. S., & Jeffrey, D. B. (1998). A comparison of the Three factor Eating Questionnaire and the Restraint Scale and consideration of Lowe's Threefactor M odel. Addictive Behaviors, 23(1), 115118. doi: 10.1016/S03064603(97)000312 Rubin, D. B. (1976). Inference and missing data. Biometrika, 63(3), 581592. doi: 10.1093/biomet/63.3.581 Ruderman, A. J. (1983). The restraint scale: A psychometric investigation. Behaviour Research and Therapy, 21(3), 253258. doi: 10.1016/00057967(83)902073 Ruderman, A. J. (1986). Dietary restraint: A theoretical and empirical review. Psychological Bulletin, 99(2), 247 262. doi: 10.1037/00332909.99.2.247 Rutters, F., Nieuwe nhuizen, A. G., Lemmens, S. G. , Born, J. M., & Westerterp Plantenga, M. S. (2009). Hyperactivity of the HPA axis is related to dietary restraint in normal weight women. Physiology & Behavior, 96(2), 315319. doi: 10.1016/j.physbeh.2008.10.015 Schur, E., Noonan, C., Polivy, J., Goldberg, J., & Buchwal d, D. (2009). Genetic and environmental influences on restrained eating behavior. International Journal of Eating Disorders, 42(8), 765 772. doi: 10.1002/eat.20734 Simon, G. E., Von Korff, M., Saunders, K., Miglioretti, D. L., Crane, P. K., van Belle, G., & Kess ler, R. C. (2006). Association between obesity and psychiatric disorders in the US adult population. Arch ives of General Psychiatry, 63 (7), 824830. doi: 10.1001/archpsyc.63.7.824 Simpson, S. A., Shaw, C., & McNamara, R. (2011). What is the most ef fective way to maintain weight loss in adults? British Medical Journal, 28(343) , d8042. doi: 10.1136/bmj.d8042 Spencer, J. A., & Fremouw, W. J. (1979). Binge eating as a function of restraint and weight classification. Journal of Abnormal Psychology, 88(3), 262267. doi: 10.1037/0021843x.88.3.262 Stice, E. (2002). Risk and maintenance factors for eating pathology: A metaanalytic review. Psychological Bulletin, 128(5), 825848. doi: 10.1037/00332909.128.5.825 94

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Stice, E., Cameron, R. P., Killen, J. D., Hayward, C., & Taylor, C. B. (1999). Naturalistic weight reduction efforts prospectively predict growth in relative weight and onset of obesity among female adolescents. Journal of Consulting and Clinical Psychology, 67(6), 967974. doi: 10.1037/0022006x .67.6.967 Striegel Moore, R. H., Dohm, F. A., Kraemer, H. C., Taylor, C. B., Daniels, S., Crawford, P. B., & Schreiber, G. B. (2003). Eating disorders in w hite and black w omen. Am erican Journal of Psychiatry, 160 (7), 13261331. doi: 10.1176/appi.ajp.160.7.1326 Striegel Moore, R. H., Rosselli, F., Perrin, N., DeBar, L., Wilson, G. T., May, A., & Kraemer, H. C. (2009). Gender difference in the prevalence of eating disorder symptoms. International Journal of Eating Disorders, 42(5), 471474. doi: 10.1002/eat .20625 Stunkard, A. J. , & Messick, S. (1985). The Threefactor Eating Q uestionnaire to measure dietary restraint, disinhibition and hunger. Journal of Psychosomatic Research, 29(1), 71 83. doi: 10.1016/00223999(85)900108 Subar, A. F., Thompson, F. E., Potischman, N., Forsyth, B. H., Buday, R., Richards, D., . . . Ba ranowski, T. (2007). Formative research of a quick list for an automated self administered 24hour dietary r ecall. Journal of the American Dietetic Association, 107(6), 10021007. doi: 10.1016/j.jada.2007.03.007 Taylor, C. B., Bryson, S., Luce, K. H., Cunning, D., Doyle, A. C., Abascal, L. B., . . . Wilfle y, D. E. (2006). Prevention of eating disorders in at risk college age w omen. Arch ives of Gen eral Psychiatry, 63(8), 881888. doi: 10.1001/ archpsyc.63.8.881 Teixeira, P. J., Silva, M. N., Coutinho, S. R., Palmeira, A. L., Mata, J., Vieira, P. N., . . . Sardinha, L. B. (2010). Mediators of weight loss and weight loss maintenance in middle aged women. Obesity, 18(4), 725735. doi: 10.1038/oby.2009.281 Tepper, B. J., Choi, Y. S., & Nayga Jr . , R. M. (1997). Understanding food choice in adult men: Influence of nutrition knowledge, food beliefs and dietary restraint. Food Quality and Preference, 8(4), 307317. doi: 10.1016/S09503293(97)000141 Timmerman, G. M. (1999 ). Binge Eating Scale: Further assessment of validity and reliability . Journal of Applied Biobehavioral Research, 4(1), 1 12. doi: 10.1111/j.17519861.1999.tb00051.x Van Loan, M. D., & Keim, N. L. (2000). Influence of cognitive eating restraint on total body measurements of bone mineral density and bone mineral content in premenopausal women aged 18– 45 y: A crosssectional study. The American Journal of Clinical Nutrition, 72(3), 837843. http://ajcn.nutrition.org/ 95

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van Strien, T., Herman, C. P. , Engels, R. C. M. E., Larsen, J. K., & van Leeuwe, J. F. J. (2007). Construct validation of the Restraint Scale in normal weight and overweight females. Appetite, 49(1), 109121. doi: 10.1016/j.appet.2007.01.003 Vella Zarb, R. A., & Elgar, F. J. (2009). The “freshman 5”: A meta analysis of weight gain in the freshman year of college. Journal of American College Health, 58(2), 161166. doi: 10.1080/07448480903221392 Vocks, S., TuschenCaffier, B., Pietrowsky, R., Rustenbach, S. J., Kersting, A., & Herpertz, S. (2010). Metaanalysis of the effectiveness of psychological and pharmacological treatments for Binge Eating D isorder. International Journal of Eating Disorders, 43(3), 205 217. doi: 10.1002/eat.20696 Wardle, J., & Beinart, H. (1981). Binge eating: A theoretical review. British Journal of Clinical Psychology, 20 (2), 97 109. doi: 10.1111/j.20448260.1981.tb00503.x Wendel Vos, W., Droomers, M., Kremers, S., Brug, J ., & Van Lenthe, F. (2007). Potential environmental determinants of physical activity in adults: A systematic review. Obesity Reviews, 8 (5), 425440. doi: 10.1111/j.1467789X.2007.00370.x Westenhoefer, J., Stunkard, A. J., & Pudel, V. (1999). Validation of the flexible and rigid control dimensions of dietary restraint. International Journal of Eating Disorders, 26(1), 5364. doi: 10.1002/(sici)1098108x(199907)26:1<53::aideat7>3.0.co;2 n Woody, E. Z., Costanzo, P. R., Liefer, H., & Conger, J. (1981). The effects of taste and caloric perceptions on the eating behavior of restrained and unrestrained subjects. Cognitive Therapy and Research, 5(4), 381390. doi: 10.1007/bf01173690 Wooley, S. C. (1972). Physiologic versus cognitive factors in short term food regulation in the obese and nonobese. Psychosomatic Medicine, 34(1), 62 68. http://www.psychosomaticmedicine.org/ World Health Organization. (1995). Physical status: The use and interpretation of anthropometry (Technical Report Series No. 854). Geneva: Author. 96

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BIOGRAPHICAL SKETCH Valerie J. Hoover graduated from Temple University magna cum laude in 2004 with a Bachelor of Arts degree in p sychology. While at Temple University, Valerie volunteered as an undergraduate research assistant in the psychology research laboratory of Brian Marx, Ph.D., where she worked on a study examining the association between alcohol consumption and decisionmaking and judgment. From January 2005 through December 2006, Valerie worked as a research assistant at the University of Pennsylvania in Philadelphia, Pennsylvania under Robert F. Forman, Ph.D. In this capacity she worked on numerous research protocols, including studi es examining the development of a set of group therapy resources for substance abuse counselors, therapist feedback and performance interventions, and availability of controlled substances via the internet. From January 2007 through April 2008 Valerie work ed as a research coordinator at the Washington Center for Clinical Research in Washington, D.C. under Hope F. Ferdowsian, M.D., M.P.H. In this role Valerie played a key role in implementing a research study examining the effect of a low fat, plant based d iet on weight loss and glucose control within a worksite setting. In August 2008 Valerie began her doctorate in clinical psychology at the University of Florida (UF) under the mentorship of Michael G. Perri, Ph.D. During her work in Dr. Perri’s UF Weight Management Laboratory, Valerie served as a weight management group leader for three waves of the Rural Lifestyle Intervention Treatment Effectiveness Trial and assisted with multiple other aspects of study recruitment, assessment, and data collection. Val erie graduated with her Master of Science degree in p sychology in May 2010, with her thesis focusing on the relation between changes in 97

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weight loss expectations and longer term weight change following weight loss intervention. Valerie will fulfill her fina l doctoral requirements by completing her internship in clinical p sychology at Rush University Medical Center. Valerie’s research interests relate to improving behavior change methods (including in the area of weight management), as well as psychopatholog i cal aspects of eating behavior. 98



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Maritalstatusandbodyweight,weightperception,andweightmanagementamong U.S.adultsLoriA.Klos,JefferySobalDivisionofNutritionalSciences,CornellUniversity,Ithaca,NY,USAabstract articleinfoArticlehistory: Received13February2013 Receivedinrevisedform25June2013 Accepted15July2013 Availableonline22July2013 Keywords: Marriage Bodyweight Perceivedweight Desiredweight Weightmanagement BMIMarriedindividualsoftenhavehigherbodyweightsthanunmarriedindividuals,butitisunclearhowmarital rolesaffectbodyweight-relatedperceptions,desires,andbehaviors.Thisstudyanalyzedcross-sectionaldata for4,089adultmenand3,989adultwomenusingmultinomiallogisticregressiontoexamineassociations betweenmaritalstatus,perceivedbodyweight,desiredbodyweight,andweightmanagementapproach.Controllingfordemographicsandcurrentweight,marriedorcohabitingwomenanddivorcedorseparated womenmoreoftenperceivedthemselvesasoverweightanddesiredtoweighlessthanwomenwhohad nevermarried.Maritalstatuswasunrelatedtomen'sweightperceptionanddesiredweightchange.Marital statuswasalsogenerallyunrelatedtoweightmanagementapproach,exceptthatdivorcedorseparated womenweremorelikelytohaveintentionallylostweightwithinthepastyearcomparedtonevermarried women.Additionally,nevermarriedmenweremorelikelytobeattemptingtopreventweightgainthanmarried orcohabitingmenandwidowedmen.Overall,marriedandformerlymarriedwomenmoreoftenperceived themselvesasoverweightanddesiredalowerweight.Men'smaritalstatuswasgenerallyunassociatedwith weight-relatedperceptions,desires,andbehaviors.Women'sbutnotmen'smaritalrolesappeartoin uence theirperceivedanddesiredweight,suggestingthatweightmanagementinterventionsshouldbesensitiveto bothmaritalstatusandgenderdifferences. ©2013ElsevierLtd.Allrightsreserved.1.Introduction Bodyweightisahealthandappearanceissuewithimplicationsfor maritalrelationships.Prevalenceofoverweightandobesityremains highintheU.S.( Flegal,Carroll,Ogden,&Curtain,2010 ),andobeseindividualsarestigmatizedinmanysocialsituations,includingromantic relationshipsandmarriagemarkets( Puhl&Heuer,2009 ).Howan individualevaluatesandinterpretstheirbodyweightisin uenced byculturalvaluesaboutattractiveness,medicalde nitionsofhealthy weight,andsocialrelationships,withvariationsintheseevaluationsbetweengender,age,race/ethnicity,andclass.Romanticrelationshipsare especiallysalientindeterminingbodyweightideals( Tom,Chen,Liao,& Shao,2005 ),buttheserelationshipshavenotbeenwellexaminedin conjunctionwithweightperceptions,desires,andmanagement. Theprevalenceofoverweightandobesitydiffersbymaritalstatus formenandwomen( Schoenborn,2004;Sobal,Rauschenbach,& Frongillo,1992 ).Marriedmenaremostlikelytobeoverweightor obeseofallgenderandmaritalstatuscategories.Lessmaritalstatus variationexistsamongoverweightandobesewomen.However, unmarriedwomen,andtoalesserextentunmarriedmen,involvedin datingrelationshipshavelowerbodymassindex(BMI)valuesandare lesslikelytobeoverweightthanthosewhoareunmarriedbutnotin romanticrelationships( Sheets&Ajmere,2005;Wiederman&Hurst, 1998 ).Theseassociationsarelikelyduetotheimportanceofbodyweight inde ningattractiveness,especiallyforwomen( Sobal,Nicolopoulos,& Lee,1995 ).Thuspeopleseekingapartnerinthemarriagemarketmay strivetoattainormaintainanidealbodyweightinanefforttomaximize theircon denceorsocialcapital( Bove&Sobal,2011;Shilling,2003 ). Weight-relatedchangesassociatedwithrelationshiptransitionsalso provideevidencethatromanticrelationshipsarerelevanttotheexaminationofbodyweight.Enteringmarriageisassociatedwithweight gain,particularlyamongwomen( Dinour,Leung,Tripicchio,Khan,& Yeh,2012;Sobal,Rauschenbach,&Frongillo,2003 ).Marriedindividuals nolongerinthemarriagemarketmayexperiencelesspressuretoattain ormaintain  idealbodies Ž aftersecuringapartner,andarein uenced bymaritalactivitiespromotingweightgain,suchassharedmealsand dietarytemptations( Anderson,Marshall,&Lea,2004;Sobaletal., 2003 ),lesspersonaltimeforphysicalactivity( Nomaguchi&Bianchi, 2004 ),andchildbearingandchildrearing( Wolfe,Sobal,Olson,Frongillo, &Williamson,1997 ).Individualsinorre-enteringmarriagemarkets tendtoloseweightovertime( Sobaletal.,2003 ).Thissuggeststhatindividualsmayperceivetheirbodiesdi fferentlyandvaryintheirdesired weightscongruentwiththeirmaritalstatus,andthatdifferentweight EatingBehaviors14(2013)500 … 507 Correspondingauthorat:DepartmentofKinesiology,UniversityofWisconsinMilwaukee,455EnderisHall,Milwauke e,WI53201,USA.Tel.:+14142293162;fax:+1 4142292619. E-mailaddress: neighbol@uwm.edu (L.A.Klos). 1471-0153/$ … seefrontmatter©2013ElsevierLtd.Allrightsreserved. http://dx.doi.org/10.1016/j.eatbeh.2013.07.008 Contentslistsavailableat ScienceDirectEatingBehaviors

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managementstylesmayoccurbetweenepisodesofanindividual'smaritalstatus.Surprisinglyfewstudiesexamineassociationsbetweenmarital statusandbodyweightperceptions,desires,andbehaviors. Howanindividualinterpretsandevaluatestheirbodyweight statushasbeenrecognizedasanimportantdeterminantofweight management-relatedbehaviors(e.g., Lemon,Rosal,Zapka,Borg,& Andersen,2009;Powelletal.,2010 ).Inthecurrentsociocultural climatewhereleannessisidealized( Tiggemann,2011 )andexcess weightisstigmatized( Puhl&Heuer,2009 ),theperceptionofbeing overweightorobesehasbeenconsideredaproxyforbodyweight dissatisfaction.Severalpopulation-basedstudieshaveexamineda numberofdemographicandsocioeconomicfactors(e.g.,gender, socioeconomicstatus,race/ethnicity)associatedwithweightperception,misperception(perceivingone'sweightdiscordantfromobjective measuressuchasbodymassindex),andweightmanagementefforts. Afteradjustmentforinitialdifferencesinactualbodyweight,selfperceivedoverweightstatuswasmo relikelyamongwomen,Caucasians, andthosewithhigherincomeandeducation(e.g., Paeratakul,White, Williamson,Ryan,&Bray,2002 ).Weightmisperception(e.g.,anindividualwithaBMIintheoverweightrangewhoperceivestheirweight as  aboutright Ž )isprevalentintheU.S.( Chang&Christakis,2003; Kjærbye-Thygesen,Munk,Ottesen,&KrügerKjær,2004;Wardle& Johnson,2002 ).Thisisimportantinthecontextoftheobesityepidemic ( WorldHealthOrganization,1998 )becauseweightmisperceptionsalso in uencedesiretochange(ornotchange)weightandweightmanagementbehaviors( Anton,Perri,&Riley,2000;Duncanetal.,2011; Wardle&Johnson,2002 ).Forexample,examinationofdatafroma nationally-representativesampleofadultsfoundthatoverweight andobeseadultswhodidnotperceivetheirweightstatusasoverweightwerelesslikelytowanttoweighless,andwerelesslikelyto beattemptingweightloss( Duncanetal.,2011 ).Publicbeliefssuggest thatpeopleremainthintoattractmaritalpartners,butweightbecomes lessimportantoncewed( Tometal.,2005 ),althoughweightperceptions andweightmanagementbehaviorhaverarelybeenstudiedinrelationto maritalstatus. Ofstudiesexaminingweightperception-relatedconstructsin nationally-representativesamples,mostdidnotevaluatemarital statusasapossiblepredictorvariable,althoughsomeadjustedfor itinstatisticalmodels(e.g., Bennett&Wolin,2006 ). Changand Christakis(2003) foundthatwomen'smaritalstatus(married,previouslymarried,ornevermarried)wasunrelatedtotheirperceived weight,whilemarriedmenweremorelikelytoperceivetheirweight statusasheavierthanmenwhohadneverbeenmarried.Another studyfoundnorelationshipbetweenmaritalstatusandweight perception,althoughonlytworelationshipcategorieswereexamined:marriedandnotmarried( Chang&Christakis,2001 ).However, otherstudiesexaminingromanticrelationshipstatusandweight evaluationrevealedmixed ndings.Onestudyfoundthatmarried adultsperceivethemselvesasheavier,butstillconsiderachieving an  ideal Ž bodylessimportant,comparedtosingleindividuals( Tom etal.,2005 ).However,alargesurveyof ConsumerReports readersfound bodydissatisfactiontobeunrelatedtomaritalstatus( Friedman,Dixon, Brownell,Whisman,&Wil ey,1999 ).Theseinconsistentassociations mayberelatedtotherelationshipcategoriesresearchersexaminedin theiranalyses,andthewayinwhichresearchersoperationalizedthe evaluationofbodyweightandshape(e.g.,weightperception,bodydis-satisfaction,idealbodyimportance ).Somestudiesselectivelyfocused oncertainrelationshiptypeslikemarriedorunmarriedromanticcouples. Forexample,amongmarriedadults,womenweredissatis edwiththeir bodiesmorethantheirhusbandswere( Markey,Markey,&Birch,2004 ), consistentwith ndingsaboutgenderdifferencesinbodysatisfaction ( Feingold&M azzella,1998 ),butthestudydesigndidnotpermitcomparisontootherrelationshiptypes. Weightperceptionisacontributingfactorinthedesiretomodify bodyweightandintheengagementinbehavior(s)todoso.While anumberofstudieshavedescribedtheapproachestoweight managementusedbyadults(e.g., Lowryetal.,2000;Weiss,Galuska, KettelKhan,&Serdula,2006 ),maritalstatushasnotbeenthoroughly exploredasapossiblepredictorfordesiredorattemptedweightchange. InonestudyofU.S.adultstryingtoloseweight,maritalstatuswas unrelatedtothelikelihoodofusingrecommendedweight-lossstrategies(i.e.,eatingfewercaloriesandexercisingmore; Kruger,Galuska, Serdula,&Jones,2004 ).However,arecentin-depthanalysisofrecently marriedcouplesrevealsthatweightisasalienttopicwithinthecontext ofrelationships( Bove&Sobal,2011 ).Also,therelevanceofweightappearstochangewithchangesinmaritalstatus,andisimportantforunderstandinganindividual'sbehaviorsrelatedtoweight,diet,and exercise.Newlymarriedadultsdescribedarelaxationinweightconcern onceinvolvedincommittedrelationships,comparedtowhenthey soughtmaritalpartners,anddescribedsubsequentweightgaindueto areductioninactiveweightmanagementefforts(alongwithother changesassociatedwithcommensality,suchassharedmeals).These ndingsprovidesupportforacloserexaminationofmaritalstatusand weightmanagementinlargersamplesofadults. Thesefewstudiessuggestthattypesofmaritalrelationshipsmay in uenceweightevaluation,bodydissatisfaction,andweightmanagementbehavior.Adultassociationsbetweenromanticrelationshipsand weightperception,desiretochangebodyweight,andweightmanagementbehaviorsareunclear,particularlyacrossarangeofrelationship typesincludingnevermarried,livingwithapartner,married,separated, divorced,andwidowed.Weightperceptionsandweightchangedesires areimportantbecausetheypredictweightmanagementattempts(and thetypesofbehaviorsusedtochangeweight),evenafteraccounting forobjectiveweightstatus(e.g., Powelletal.,2010 ).Marriageand weightperceptions,desiredweight,andweightmanagementneed furtherstudytoprovideknowledgeforweightmanagementpolicies, programs,andclinicalworkthatconsiderromanticrelationship contexts. Theobjectiveofthiscross-sectionalstudywastoexamineassociationsbetweenmaritalstatusan dtheperceptionofbodyweight, desiredweightchange,andweightmanagementapproachina nationally-representativesampleofU.S.adultscontrollingforimportantsociodemographicvariab lessuchasage,race/ethnicity, andsocioeconomicstatus. 2.Method 2.1.Designandsample Thepresentstudyisasecondaryanalysisofthedatafromthe1999 … 2002NationalHealthandNutrition ExaminationSurvey(NHANES) „ a cross-sectional,nationally-representativesampleoftheU.S.civilian, non-institutionalizedpopulation.Dataarecollectedthroughmedical examinations,questionnaires,andinterviewsthatincludemeasurements ofheightandweight.AnextensivedescriptionofNHANEScanbefound elsewhere( NationalCenterforHealthStatistics,2012 ).Thisanalysis examineddatafrom10,291adultsaged20orolder. Forthisstudy,participantswereexcludedfromtheanalyticalsampleiftheirmaritalstatuswasunknown( n =441),iftheydidnotcompletethemedicalexamination( n =820),oriftheirheightandweight datawereunavailable( n =19).Similartootherresearchers'approach withthisdataset(e.g., Dorsey,Eberhardt,&Ogden,2009 ),weexcluded participantswhoself-classi edtheirraceorethnicityas  Otheror multiracial Ž ( n =256)duetorelativelylowrepresentationinthesample.Womenwhowerecurrentlypregnantorofundeterminedpregnancystatus( n =627)werealsoexcluded,aswerethosewithmissing valuesforotherstudy-relatedvariables( n =50),withtheexception ofeducationandincome.Missingvaluesforeducation( n =14)andincome( n =824)wereimputedusingexpectation … maximizationprocedures( Allison,2002 ).The nalanalyticalsample( n =8,078)was comprisedof4,089menand3,989women.501 L.A.Klos,J.Sobal/EatingBehaviors14(2013)500 – 507

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2.2.Measures 2.2.1.Maritalstatus Participantsself-reportedtheircurrentmaritalstatusasmarried, widowed,divorced,separated,nevermarried,orlivingwithapartner (cohabiting).Duetosmallsamplesizeswithinsomeresponsecategories,thoselivingwithapartner(217men,184women)werecombined withmarriedindividuals,andseparatedparticipants(112men,188 women)werecombinedwiththosewhoweredivorced. 2.2.2.Height,weight,andbodymassindex(BMI) Formostparticipantsinthedataset,theirheightandweightwere measuredbytrainedstaffduringamedicalexamination.Giventhe highcorrelationbetweenmeasuredandself-reportedheight( r =.93) andweight( r =.97)amongparticipantsinthissample,self-reported heightandweightwereused( n =335)whenmeasuredvalueswere notavailable.BMIwascalculatedbydividingrespondents'weight (kilograms)bytheirheight(meters),squared.BMIvalueswere constrainedto50kg/m2( n =51)toavoidtheunduein uenceof outliersattheupperendofthedistribution.UsingstandardBMI categories,respondentswereclassi edasunderweight( b 18.5kg/m2), normalweight(18.5 … 24.9kg/m2),overweight(25.0 … 29.9kg/m2),and obese( 30.0kg/m2)( WorldHealthOrganization,1998 ).Therelatively smallnumberofunderweightrespondents( n =144)werecombined withnormalweightrespondentstoforma  notoverweight Ž category ( b 25.0kg/m2)forsomeanalyses. 2.2.3.Weightperceptionanddesiredweightchange PriortobeingweighedduringtheNHANESmedicalexam,participantswereasked,  Doyouconsideryourselftobeoverweight,underweight,orabouttherightweight? Ž Desiredweightchangewas assessedbythequestion,  Wouldyouliketoweighmore,less,orstay aboutthesame? Ž 2.2.4.Weightmanagementapproach Participantswereclassi edintooneof veweightmanagementcategoriesbasedonboththeirbodyweighthistoryandtheirresponseto twoweightmanagement-relatedquestions.Participantswithacurrent bodyweighttenormorepoundslessthantheirweightoneyearago wereaskediftheweightlosswasintentional.Ifitwas,participants werede nedasthosewho intentionallylostweight ,otherwisethey werede nedasthosewho unintentionallylostweight .Participants withacurrentbodyweightwithin10lboftheirweightoneyearago wereasked,  Duringthepast12months,haveyoutriedtoloseweight? Ž Table1 Demographiccharacteristicsandweight-relatedvariablesbymaritalstatusamongmen. CharacteristicMaritalstatus TotalNMM/CD/SW ( n =4089)( n =690)( n =2797)( n =407)( n =195) p Age(years), M , SE 45.6(0.4)31.1(0.8)48.5(0.5)47.4(0.7)72.7(1.4) Race/ethnicity(%) White74.967.078.270.579.2 Black10.416.47.316.214.6 Hispanic14.616.614.513.36.2 Education(%) Lessthanhighschool21.621.121.326.439.3 Highschoolgraduate27.224.525.327.726.1 Somecollegeorgreater51.254.353.445.934.6 Annualfamilyincome(%) b $10,0007.515.63.912.710.5 $10,000 … 19,99915.519.011.518.435.9 $20,000 … 34,99919.722.817.925.825.1 $35,000 … 54,99920.818.423.720.321.2 $55,000 … 74,99913.910.415.611.45.2 $75,00022.613.827.411.42.2 BMI(kg/m2), M ( SE )27.8(0.1)26.6(0.3)28.3(0.2)27.1(0.5)27.4(0.4) BMICategory(%) Notoverweight31.645.926.140.935.3 Overweight41.131.644.337.241.8 Obese27.322.529.621.922.9 Perceivedweightstatus(%) Aboutright45.752.642.949.551.1 Overweight47.433.952.341.042.3 Underweight7.013.54.86.69.5 Desiredweightchange(%) Weighsame36.839.634.941.650.6 Weighmore10.021.66.711.54.9 Weighless53.238.858.546.944.4 Weightmanagementapproach(%) Notmanagingweight52.356.251.150.961.5 Preventingweightgain9.78.710.76.14.6 Attemptingweightloss22.118.023.124.616.5 Intentionallylostweight10.010.29.910.88.0 Unintentionallylostweight5.86.85.27.69.4 Note .Samplesizes( n s)areunweightedwhilepercentagesareweightedtore ectanationally-representativesample;NM=Nevermarried;M/C=Marriedorcohabiting;D/S= Divorcedorseparated;W=Widowed. DifferencesinmeansorpercentagesbymaritalstatuscategoriesweretestedusingANOVAandchi-squareanalyses,respectively. p b .05. p b .01. p b .001. 502 L.A.Klos,J.Sobal/EatingBehaviors14(2013)500 – 507

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and,  Duringthepast12months,haveyoudoneanythingtokeepfrom gainingweight? Ž Participantsanswering  yes Ž toeitherquestionwere classi edaccordinglyaseither attemptingweightloss or preventingweight gain ,respectively.Participantsresponding  no Ž tobothweightmanagementquestionswereconsideredtobe notmanagingweight . 2.2.5.Demographics Gender,age,race/ethnicity,education,annualfamilyincome,and smokingstatuswereobtainedthroughself-report.Participantsselfclassi edtheirrace/ethnicityasnon-HispanicWhite(White),nonHispanicBlack(Black),MexicanAmericanandotherHispanic(Hispanic), andOtherormultiracial.Duetolimitednumbersofparticipantsselfclassifyingtheirrace/ethnicityas  Otherormultiracial, Ž onlythe rst threecategoriesarereportedinthispaper.Highestlevelofeducation achievedwascategorizedaslessthanhighschool,highschoolgraduate (orequivalent),orsomecollegeorgreater.Annualfamilyincomewas reportedonaneleven-pointscal efrom$0to$4,999through$75,000 andabove,andre-codedintosixcategoriesfordescriptivepurposes. 2.3.Analysis NHANESusedcomplex,strati ed,multistage,probabilitysampling. Greaterdetailonthesamplingframesandsamplesectionprocedures aredescribedindetailelsewhere( NationalCenterforHealthStatistics, 2012 ).Four-yearsampleweightswereusedtoadjustforunequalprobabilityofselection,andweightswererecalculatedforthisanalytical samplesothetotalweighted n equaledthesamplesize.Variances werecorrectedforcomplexsamplingusingmaskedstrataandpseudo samplingunitsfromNHANES.SPSS(version14.0,Chicago,IL)andthe correspondingcomplexsamplesmodulewereusedforthisanalysis. Chi-squareandANOVAtestswereusedtoexaminedifferencesin demographicvariablesandBMIbymaritalstatus.ForANOVAteststo comparedifferencesinmeans(i.e.,ageandBMI),nevermarriedindividualswereconsideredthereferencecategory.Linearandmultinomial logisticregressionwasusedtoexaminemaritalstatusdifferencesin meanBMIandBMIclassi cation,respectively,adjustingforage,race/ ethnicity,education,andannualfamilyincome.Toexamineassociations betweenmaritalstatusandweightevaluationandweightmanagementrelatedvariables,multinomiallogi sticregressionanalyseswereusedto examineassociationsbetweenmarit alstatusand(1)perceivedweight status,(2)desiredweightchange,and(3)weightmanagementapproach. Regressionmodelsusedtoexamineassociationsbetweenmaritalstatus andweightevaluationandweightmanagement-relatedvariableswere adjustedfordemographicfactorsincludingage,race/ethnicity,andsocioeconomicstatusandBMI.Aspreviousstudiessuggestthatmenand womeninterpretandmanageweightdifferently,andalsoexperience Table2 Demographiccharacteristicsandweight-relatedvariablesbymaritalstatusamongwomen. CharacteristicMaritalstatus p TotalNMM/CD/SW ( n =3989)( n =566)( n =2165)( n =610)( n =648) Age(years), M , SE 47.7(0.5)32.2(0.9)46.6(0.4)48.4(0.6)72.9(0.6) Race/ethnicity(%) White74.257.180.363.278.6 Black11.722.67.219.211.8 Hispanic14.020.312.517.69.6 Education(%) Lessthanhighschool22.020.218.725.138.4 Highschoolgraduate26.020.226.126.532.4 Somecollegeorgreater51.959.755.248.429.3 Annualfamilyincome(%) b $10,00011.721.64.520.226.1 $10,000 … 19,99917.524.611.123.534.7 $20,000 … 34,99920.521.018.925.821.1 $35,000 … 54,99919.316.722.017.99.7 $55,000 … 74,99911.98.215.76.23.8 $75,00019.28.027.86.44.5 BMI(kg/m2), M ( SE )28.2(0.2)28.1(0.4)28.1(0.2)28.9(0.3)28.3(0.5) BMIcategory(%) Notoverweight38.144.239.530.432.7 Overweight27.922.727.431.532.9 Obese34.033.133.138.134.3 Perceivedweightstatus(%) Aboutright31.136.628.828.040.8 Overweight65.759.069.068.253.3 Underweight3.24.42.23.85.9 Desiredweightchange(%) Weighsame23.626.820.423.137.6 Weighmore3.05.02.22.65.4 Weighless73.468.277.474.457.1 Weightmanagementapproach(%) Notmanagingweight38.138.435.638.150.8 Preventingweightgain9.08.99.97.85.6 Attemptingweightloss36.433.440.434.321.8 Intentionallylostweight10.410.89.913.38.8 Unintentionallylostweight6.28.54.26.613.0 Note .Samplesizes( n s)areunweightedwhilepercentagesareweightedtore ectanationally-representativesample;NM=Nevermarried;aM/C=Marriedorcohabiting;D/S= Divorcedorseparated;W=Widowed. DifferencesinmeansorpercentagesbymaritalstatuscategoriesweretestedusingANOVAandchi-squareanalyses,respectively. p b .05. p b .01. p b .001. 503 L.A.Klos,J.Sobal/EatingBehaviors14(2013)500 – 507

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marriagedifferently( Kiecolt-Glaser&Newton,2001 ),allanalyseswere conductedseparatelybygender. 3.Results 3.1.Demographiccharacteristicsbymaritalstatus TheweighteddatamirrorsnationalpatternsofadultsintheU.S. withthemajorityofparticipantsbeingmiddle-aged,White,withat leastahighschooleducation. Tables1and2 presentthedemographic variablesbymaritalstatusformenandwomen,respectively.Nearly everydemographicvariableexaminedinthisstudyvariedsigni cantly acrossmaritalstatuscategoriesforbothmenandwomen.Marriedor previouslymarriedadultsweresigni cantlyolderthanthosewhohad nevermarried.Amongmarriedorcohabitingparticipants,themajority wasWhite(78%)andonly6%wereBlack.Attainmentofahighschool diploma(orequivalent)didnotvarybymaritalstatus,whilewidows weresomewhatlesslikelytohaveattendedcollegethanmembersof othermaritalgroups.Married/cohabitingadultsalsotendedtorepresentedmostfrequentlyinthehighestfamilyincomebracket,illustratingtheeconomicadvantageofmarriage/cohabitation. 3.2.Bodymassindexandmaritalstatus Therelationshipbetweenmaritalstatusandbodyweightvariedbetweenmenandwomen.Menwhoweremarried/cohabitinghadsignificantlyhigherBMIsthanmenwhohadnevermarried( Table1 ),andthis ndingremainedsigni cantafteradjustmentforage,race/ethnicity, education,andincome.ThemeanBMIofpreviouslymarriedmendid notdifferfromnevermarriedmen.Afteradjustmentfor demographicfactors,married/cohabitingmenweremorelikelytobe overweight( OR =1.78,95%CI:1.29 … 2.43)orobese( OR =1.73,95% CI:1.20 … 2.52)thannevermarriedmen.Previouslymarriedmendid notdifferfromnevermarriedmenwhenexaminingBMIcategorically. ThemeanBMIobservedinthissampleofwomendidnotvaryby maritalstatus( Table2 ),andthis ndingremainedconsistentafter adjustingfordemographicvariables.Women'smaritalstatuswas generallyunrelatedtotheirBMIwhenBMIwastreatedasacategorical variablewithoneexception:divorced/separatedwomenweremore likelytobeoverweightthannevermarriedwomen( OR =1.63,95% CI:1.14 … 2.32). 3.3.Weightperception Themajorityofmarriedorcohabitingmen( Table1 ),andthe majorityofwomeninallmaritalstatuscategories( Table2 ),perceived themselvesasoverweight.Abouthalfofnevermarried,divorced/ separated,andwidowedmenperceivedtheirweightstatusas  about right, Ž asdidabout29%to41%ofwomeninthissampledepending upontheirmaritalstatus.Fewindividualswithinanymaritalcategory consideredthemselvesunderweight.However,multivariateanalyses revealedthatmaritalstatuswasnotsigni cantlyrelatedtoweightperceptionamongmen( Table3 ),andwasonlymarginallysigni cant amongwomen,afteradjustingfordemographicfactorsandBMI ( Table4 ).Morespeci cally,comparedtonevermarriedwomen, married/cohabitinganddivorced/separatedwomenweremore likelytoconsiderthemselvesoverweightthanabouttheright weight.Maritalstatuswasunrel atedtowomen'sperceptionof beingunderweight. 3.4.Desiredweightchange Themajorityofnevermarriedandwidowedmendesiredtostay aboutthesamebodyweight,whilethemajorityofmarried/cohabitinganddivorced/separatedmenwantedtoweighless( Table1 ).Most womenacrossallmaritalstatuscategories,especiallymarriedwomen, desiredtoweighless.Menwhohadneverbeenmarriedmostfrequentlywantedtoweighmore,whilefewwomeninanymaritalcategory desiredweightgain.Amongmen,therelationshipsbetweenmarital statusandthedesireforadifferentbodyweightwerenotstatistically signi cantthemultivariatemodel,adjustingfordemographicvariables andBMI( Table3 ).Amongwomen,maritalstatuswasunrelatedtothe desiretoweighmore.However,married/cohabitingwomenand divorced/separatedwomenwerebothabout1.6timesmorelikely todesiretoweighlessthantostaythesameweight,comparedto womenwhohadnevermarried,controllingfordemographicsand currentBMI( Table4 ). Table3 Regressionanalysesexaminingmen'smaritalstatusasapredictorofweightperception, desiredweightchange,andweightmanagementapproach( n =4089). VariableMaritalstatusan % ORb95%CI Perceivedweightstatus Aboutright(Ref.)Nevermarried38452.6 …… Married130342.9 …… Widowed11251.1 …… Divorced21149.5 …… OverweightNevermarried22033.9Ref. … Married135052.31.29[0.89,1.86] Widowed6842.31.04[0.63,1.71] Divorced15441.01.47[0.89,2.42] UnderweightNevermarried8613.5Ref. … Married1444.80.99[0.55,1.75] Widowed156.61.03[0.36,2.90] Divorced429.51.16[0.46,2.90] Desiredweightchange Weighsame(Ref.)Nevermarried30139.6 …… Married113534.9 …… Widowed11050.6 …… Divorced18841.6 …… WeighmoreNevermarried13821.6Ref. … Married1796.70.83[0.53,1.32] Widowed124.90.87[0.32,2.38] Divorced4911.50.94[0.41,2.12] WeighlessNevermarried25138.8Ref. … Married148358.51.26[0.91,1.75] Widowed7344.40.94[0.52,1.71] Divorced17046.91.50[0.93,2.43] Weightmanagementapproach PreventingweightgainNevermarried588.7Ref. … Married 25510.7 0.65[0.44,.097] Widowed 84.6 0.25[0.12,0.56] Divorced236.10.59[0.29,1.21] IntentionallylostweightNevermarried6010.2Ref. … Married2629.90.65[0.41,1.04] Widowed148.00.50[0.22,1.15] Divorced4510.81.06[0.62,1.84] AttemptingweightlossNevermarried11918.0Ref. … Married59923.10.87[0.64.1.18] Widowed2916.50.64[0.35,1.20] Divorced8524.61.44[0.96,2.17] Notmanagingweight(Ref.)Nevermarried40456.2 …… Married149251.1 …… Widowed12361.5 …… Divorced21750.9 …… UnintentionallylostweightNevermarried496.8Ref. … Married1895.20.76[0.48,1.20] Widowed219.40.91[0.44,1.89] Divorced377.61.11[0.62,1.99] Note .Tofacilitatereadability,statisticallysigni cantassociations( p b .05)havebeen presentedinboldtext; OR =oddsratio;CI=con denceinterval;Ref=reference categoryforregressionanalyses.aMarriedcategoryalsoincludescohabitingindividuals;divorcedcategoryalsoincludes separatedindividuals;nevermarried(referencecategory).bOR sandcorresponding95%CI'srepresentresultsfromadjustedregressionmodels whichincludeBMI,age,education,income,andrace/ethnicityascovariates. 504 L.A.Klos,J.Sobal/EatingBehaviors14(2013)500 – 507

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3.5.Weightmanagementapproach Mostmenwithineachmaritalstatuscategory,aswellasmany widowedwomen,reportednottakinganyactiontomodifytheirbody weight( Tables1and2 ,respectively).Fewmenandwomenwithin eachmaritalcategoryreportedsuccessfulweightlossof10lbormore inthepastyear.Similarproportionsofwomenwhowerenevermarried, married/cohabiting,anddivorced/separatedwereeitherattemptingto loseweightornottakingaction.Inmultivariatemodels,therewerefew signi cantassociationsbetweenmaritalstatusandweightmanagement amongmenandwomen.Menwhower emarried/cohabitatingwere lesslikelytobeattemptingtopreventweightgain(versusnottakingaction)comparedtonevermarriedmen ,adjustingfordemographicsand currentBMI( Table3 ).Divorced/separatedwomenweremorelikelyto haveintentionallylost10ormorepoundsinthepastyear(versusnot takingaction)comparedtowomen whohadnevermarried,adjusting fordemographicsandcurrentBMI( Table4 ). 4.Discussion Inthisnationally-representativesampleofadults,meninmarriedorcohabitingrelationshipshadhigherbodyweightsthan menwhohadnevermarried,controllingfordemographicsincluding age,race/ethnicity,andsocioeconomicstatus,consistentwithprevious research( Schoenborn,2004;Sobaletal.,1992 ).Womeninmaritalor cohabitingrelationshipsweresimilarinweighttowomenwhohad nevermarried,whiledivorcedorseparatedwomenweremorelikelyto beoverweight.Expandingthebodyofresearchrelatedtomaritalstatus andweightevaluation-relatedvariables,weobservedthatweightperception,desiredweightchange,andapproachtoweightmanagement variedsomewhatbymaritalstatus,althoughthesigni cantassociations wereobservedprimarilyamongwomenratherthanmen. Women'smaritalstatuswasassociatedwithbothweightperception anddesiredweightchange.Aboutthree-fourthsofwomenwhowere marriedorcohabiting,ordivorcedorseparated,viewedthemselvesas overweightanddesiredtoloseweight;atthesametime,thispattern ofweightperceptionanddesiredweightchangewassigni cantlyless commonamongwomenwhohadnevermarried.Formostwomen, pressuretonegativelyevaluatetheirbodyweightstatus(e.g.,overweightweightperception)ordesireforathinnerbodymaynotlessen aftermarriage.InWesternsocieties,bodyweightisanintegralcomponentofwomen'sattractivenessanddesirability( Jackson,2002;Rodin, Silberstein,&Streigel-Moore,1985 ),andwomenmaycontinuetoexperienceaneedtofocusonweight-relatedappearanceevenafterentering marriage.Desiringtoweighlessmaybemotivatedbydesirestosatisfy theirpartneraswellastomaintainaculturallyacceptableappearance inothersocialsituations,likewithfemalefriendsandinpublicsettings ( Paquette&Raine,2004 ).Anotherpossibilityisthatthechangesin one'sphysiqueassociatedwithchildbearing(whichismorecommon amongmarriedwomen; Wildsmith,StewardStreng,&Manlove,2011 ) maycontributetowomen'sbodydissatisfactionpostpartum( Heinburg &Guarda,2002 ),perhapscontributingtothegreaterperceptionof beingoverweightanddesiredweight lossamongmarriedandcohabiting women. Incontrasttothewomeninthissample,nosigni cantassociations wereobservedbetweenmen'smaritalstatusandtheirweightperceptionordesiredweightchangeafteradjustmentfordemographicand bodyweightdifferences.Thelackofrelationshipsbetweenthesevariablessuggeststhatbroadmaritalrolesmaynotbeasalientconsideration whenmenevaluatetheirweightstatus.Previousresearchsuggeststhat bodyweightisnotascentraltode ningaman'sdesirabilityasaromantic partnerasitisforwomen,somenmaynotconsidertheirrelationship statuswhenevaluatingtheirweightandweightmanagementapproach.Additionally,menofhigherbodyweightsdonotseemtoexperiencethesamedegreeofweightstigmatizationaswomeninthe contextofromanticrelationships.Forexample,theaverageBMIof non-datingwomenwassigni cantlyhigherthanthoseincasualor exclusiverelationships,whileBMIwasnotassociatedwithmen's datingstatus( Sheets&Ajmere,2005 ).Thissuggeststhattheremaybeasocialpenaltyforhigherbodyweightsamongwomenbutnot men.Amongdatingormarriedcouples,women's,butnotmen's, BMIwasassociatedwithworserelationshipfunctioning( Boyes& Latner,2009 ).Takentogether,perhapsmenevaluatetheirweight statussimilarlyirrespectiveoftheirpositiononthemarriagemarket astheymaynotgleanvalidationpertainingtotheirdesirability throughsecuringaromanticpartner,andtheymaybelesslikelyto experienceissuessecondarytoweightbiaswhenseekingapartner ormaintainingarelationship. Table4 Regressionanalysesexaminingwomen'smaritalstatusasapredictorofwomen'sweight perception,desiredweightchange,andweightmanagementapproach( n =3989). VariableMaritalstatusan % ORb95%CI Perceivedweightstatus Aboutright(Ref.)Nevermarried21036.6 …… Married64228.8 …… Widowed28340.8 …… Divorced19028.0 …… OverweightNevermarried33059.0Ref. … Married146769.01.66[1.15,2.40] Widowed32053.31.10[0.62,1.94] Divorced40068.21.61[1.13,2.28] UnderweightNevermarried264.4Ref. … Married562.20.84[0.41,1.73] Widowed455.90.91[0.36,2.30] Divorced203.81.10[0.51,2.39] Desiredweightchange Weighsame(Ref.)Nevermarried16726.8 …… Married48420.4 …… Widowed26637.6 …… Divorced16423.1 …… WeighmoreNevermarried355.0Ref. … Married622.20.80[0.38,1.71] Widowed455.40.68[0.27,1.67] Divorced162.60.60[0.26,1.39] WeighlessNevermarried36468.2Ref. … Married161977.41.66[1.10,2.50] Widowed33757.11.10[0.65,1.87] Divorced43074.41.60[1.04,2.46] Weightmanagementapproach PreventingweightgainNevermarried428.9Ref. … Married1899.9 …… Widowed335.6 …… Divorced377.8 …… IntentionallylostweightNevermarried5610.8Ref. … Married2049.90.99[0.60,1.67] Widowed538.81.47[0.72,3.03] Divorced 7913.3 1.63[1.01,2.45] AttemptingweightlossNevermarried18633.4Ref. … Married82840.41.33[0.94,1.87] Widowed12921.81.09[0.64,1.86] Divorced19834.31.32[0.88,1.97] Notmanagingweight(Ref.)Nevermarried24338.4 …… Married83635.6 …… Widowed34850.8 …… Divorced24838.1 …… UnintentionallylostweightNevermarried398.5Ref. … Married1084.20.71[0.38,1.32] Widowed8513.01.51[0.68,3.37] Divorced486.60.88[0.41,1.87] Note .Tofacilitatereadability,statisticallysigni cantassociations( p b .05)havebeen presentedinboldtext; OR =oddsratio;CI=con denceinterval;Ref=reference categoryforregressionanalyses.aMarriedcategoryalsoincludescohabitingindividuals;Divorcedcategoryalsoincludes separatedindividuals;Nevermarried(referencecategory).bOR sandcorresponding95%CI'srepresentresultsfromadjustedregressionmodels whichincludeBMI,age,education,income,andrace/ethnicityascovariates. 505 L.A.Klos,J.Sobal/EatingBehaviors14(2013)500 – 507

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Overall,therewereveryfewassociationsbetweenmaritalstatusand theweightmanagementapproachusedbytheadultsinthissample. Aboutonethirdofthewomeninthissamplewereattemptingtolose weight,andasimilarproportionreportednotmanagingtheirbody weight.Similartothemeninthisstudy,women'smaritalstatuswas generallyunrelatedtotheirapproachtoweightmanagementwith oneexception:divorcedorseparatedwomenweremorelikelythan nevermarriedwomentohaveintentionallylostweightwithinthe pastyear.Menemphasizeamate'sphysicalattractivenessmorethan womendo( Buss,1994 ),andpressureforwomentoattainormaintain anidealweightmaynotrelaxevenafteramaritalrelationshipissolidi ed,andperhapsintensifyuponmaritaldissolutionandsubsequent returntothemarriagemarket.Thismayleadmarriedandpreviously marriedwomentocontinuetoviewthemselvesasoverweightanddesireweightloss,butresultinquanti able(althoughself-reported) weightlossamongwomenwhomaybeseekinganewmaritalpartner possiblybecausewomenbelievethatweightlossraisesthelikelihood ofattractinganewromanticpartner( Cawley,Joyner,&Sobal,2006; Sobaletal.,2003 ). Interestingly,whileweight-relatedcommentsbyromanticpartners hasbeenreportedtobecommon( Sheets&Ajmere,2005 )andmaynegativelyin uencewomen'sbodyimage( Bove&Sobal,2011;Paquette& Raine,2004 ),itwasnotre ectedintheweightmanagementapproach usedbymarriedandcohabitingwomeninthissample.Broadersocioculturalpressuresonwomentoactivelymanagetheirweight,both withinarelationshipandoutsideofit,maysupersedeimpactsofpossibleweight-relatedcommentswithinrelationships,partiallyexplaining theoveralllackofdifferentiationinwomen'sweightmanagement approachesbymaritalstatus. Despitethe ndingthatoverhalfofthemensampledwereoverweightorobesewithineachmaritalclassi cation,themajorityreported nottakinganyactiontoloseweight,andtheproportionofmen attemptingtoloseweightdidnotdifferbymaritalstatus.However, marriedorcohabitatingmen,alongwithwidowedmen,werelesslikely tobeattemptingtopreventgainingweight(thannottakingaction)in comparisontonevermarriedmen.Toputitanotherway,nevermarried menweremorelikelytobeattemptingtopreventweightgainthan married/cohabitatingandwidowedmen afteradjustmentfordifferences indemographicsandbodyweight.Thehigherlikelihoodofattemptingto preventweightgainamongnevermarriedmenmayre ectsomeconcern relatedtobodyweightassociatedwithmaintainingorimprovingone's positioninthemarriagemarket.Becausemenoftengainweightupon entryintomarriage( Dinouretal.,2012;Sobaletal.,2003 ),whichis re ectedinthehigherprevalenceofoverweightandobesityamongmarriedorcohabitingmeninthissample,onepossibleexplanationforthisis thatwomenmaybemoreacceptingoft heirpartner'sweightgain,and men,onceinalong-termrelationship,may  giveup  tryingtomanage theirweight( Ziebland,Robertson,Jay,&Neil,2002 ).Lesssocialpressure maybeplacedonmeninarelationshiptoachieveormaintainaleaner, muscularphysique,combinedwithfewersocialconsequencesofhigher bodyweights,maypartiallyexplainthehigherprevalenceofoverweight andobesityamongmarriedmen( Schoenborn,2004;Sobaletal.,1992 ). Overall,these ndingssuggestthatadults,particularlywomen, withindifferenttypesofmaritalrelationshipsmayevaluatetheir bodyweightdifferently(particularlywhatitmeanstobenormal weightversusoverweight),butactionsrelatedtoweightmanagement arefairlysimilaracrossmaritalstatuscategories.However,thisstudy hassomelimitationsthatshouldbeconsideredwheninterpretingthe ndings. Relativelysmallsamplesizesledustocombinecohabitingandmarriedindividualsaswellasseparatedanddivorcedindividuals,masking potentialdifferencesbetweentheserelationshipcategories.Subjective well-beingofsomeoneundergoingthestressofseparatingfromapart-nermaybedifferentfromsomeonecompletingthedivorceprocess ( KampDush&Amato,2005 ),andperceptionandmanagementbody weightmayalsodiffer.MaritalstatusassessmentbyNHANESdidnot distinguishwhetherornotnevermarriedindividualswereactively seekingapartner,inthemarriagemarketbutnotattached,orinaromanticrelationship.Nevermarriedbutromanticallyinvolveddatingindividualsmayexperiencebodyweightdifferentlythanthosenever marriedandnotromanticallyinvolved.Whilemaritalstatusistypically analyzedasasetofcategoricalroles,maritalstatesaremorecomplex. Thedevelopmentanddissolutionofmaritalrelationshipsismoreofa continuumthananabrupttransitionbetweendifferentroles( Vaughan, 1986 ).Maritalstatusalsodoesnotascertainwhetherrespondentsare inheterosexualorhomosexualcouples,anddifferencesexistinbody imagebysexualorientation( Conner,Johnson,&Grogan,2004 ).Additionally,NHANESdidnotassessdimensionsofrelationshipquality(e.g.,satisfaction,romanticpartnersupport)whichhavepreviouslybeenshownto in uenceanindividual'sinterpretationoftheirbodyweightandshape (e.g., Boyes,Fletcher,&Latner,2007; Weller&Dziegielewski,2005 ). InferencesaboutNHANESbodyweight-relatedvariablesshouldbe madecautiously.Bodymassindexcategoriesaredelineatedbyhealth professionalsandmaynotcorrespondtosocialnormsaboutwhatindividualsconsider  attractive Ž or  healthy Ž weights.Also,itisunclear whatsocialcomparisontarget(s),likesocietalweightideals,healthprofessionalrecommendations,etc.,areusedwhenindividualsareasked howtheyperceivetheirbodyweight.Bodyimageandweightmanagementaredifferentiallyassociatedwiththechoiceofcomparisontarget ( Thompson,Heinberg,Altabe,&Tantleff-Dunn,1999 );assuch,comparisontargetsusedacrossthemaritalrelationshipspectrumneedtobe investigated.Additionally,NHANESdoesnotdirectlyassessweightsatisfaction.Althoughcomponentsofweightsatisfactioncanbecautiously inferredfromdesiredweightchangeandweightmanagementbehavior ( Neighbors&Sobal,2007 ),relationshipsbetweenmaritalstatusand weightsatisfactionrequirefurtherstudy.Finally,thelanguageusedin NHANEStocaptureinformationaboutbodysize-relatedperceptions, desires,andbehaviorfocusedonbodyweight.Itispossiblethat womenandmenmayresponddifferentlytoweight-relatedquestions comparedtothoseaboutmuscularity,tone,orshape.Futureworkin thisareashouldconsiderexploringtheinterrelationshipsbetweenmaritalstatus,gender,andbodyevaluationandmanagementbeyondbody weight. Whileparitywasnotincludedasacovariateinthisanalysis,previousstudieshavedemonstratedanassociationwithbetweenparity andwomen'sbodyweight( Wolfeetal.,1997 ),butnotweightperception( Kjærbye-Thygesenetal.,2004 ).Futureworkinthisareashould elucidatetheroleofchildbearingandchildrearingontheinterpretation ofbodyweightandshapewithinthecontextofromanticrelationships. Additionally,relativelysmallsamplesizesledustogroupindividuals intooneofthreeracial/ethniccategories(i.e.,White,Black,orHispanic), limitingthegeneralizabilityofthisstudytothosepopulations.Future studiesshouldmorefullyexploretheseissuesinmultipleracial/ethnic groupsusingmorediverseandlargersamples. Despitesomelimitations,thisstudyelucidatedassociationsbetween maritalstatusandvariablesrelatedtobodyimageandweightmanagementinanationally-representativesampleofUSadults.Onebroadsocialrole … maritalstatus … wassigni cantlyassociatedwithbodyweight perceptions,desiredweightchanges,andweightchangeefforts,particularlyamongwomen.Weightmanagementinterventionstargetingthe coupleasaunitmaybeef cacious( Burke,Giangiulio,Gillam,Beilin,& Houghton,2003 ),especiallyiftheypromotepositivehealthbehaviors forthebettermentofthecouple( Lewisetal.,2006 ).Futureworkin thisareashouldincludemorenuancedromanticrelationshipcategories (e.g.,casuallydating,exclusivelydating)andrelationshipcharacteristics (e.g.,satisfaction)whenexamininghowindividualsinterpretandmanagetheirbodyweightandshape.Givenconcernsaboutpromotinghealthyweightmanagementwhileavoidingharmtobodyimage,examiningthein uenceofmaritalrelationshipsonbodyimageandweight controloffersimportantinsightsabouthowmaritalstatusin uences theimportanceof,andengagementin,stepstakentomanagebody weight.506 L.A.Klos,J.Sobal/EatingBehaviors14(2013)500 – 507

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Roleoffundingsources Therewasnoexternalfundingsourceforthisstudy. Contributors Bothauthorsparticipatedindesigningthestudy,interpretingdata,andwritingthe manuscript,andLoriKlosconductedthedataanalysis. Con ictofinterest Theauthorsdeclarenocon ictsofinterestforthisstudy. Acknowledgments TheauthorsthanktheDivisionofNutritionalSciencesatCornellUniversityforprovidingsupportforthisproject.ReferencesAllison,P.D.(2002). Missingdata .ThousandOaks,CA:SagePublications. Anderson,A.S.,Marshall,D.W.,&Lea,E.J.(2004). Sharedlives „ Anopportunityfor obesityprevention? Appetite , 43 ,327 … 329. Anton,S.D.,Perri,M.G.,&Riley,J.R.(2000). Discrepancybetweenactualandidealbody images:Impactoneatingandexercisebehaviors. EatingBehaviors , 1 ,153 … 160. Bennett,G.G.,&Wolin,K.Y.(2006).Satis edorunaware?Racialdifferencesinperceived weightstatus. InternationalJournalofBehavioralNutritionandPhysicalActivity , 12 . http://dx.doi.org/10.1186/1479-5868-3-40 . Bove,C.F.,&Sobal,J.(2011). 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