0
We're unable to sign you in at this time. Please try again in a few minutes.
Retry
We were able to sign you in, but your subscription(s) could not be found. Please try again in a few minutes.
Retry
There may be a problem with your account. Please contact the AMA Service Center to resolve this issue.
Contact the AMA Service Center:
Telephone: 1 (800) 262-2350 or 1 (312) 670-7827  *   Email: subscriptions@jamanetwork.com
Error Message ......
Article |

Examination of Shared Risk and Protective Factors for Overweight and Disordered Eating Among Adolescents FREE

Jess Haines, PhD, MHSc, RD; Ken P. Kleinman, ScD; Sheryl L. Rifas-Shiman, MPH; Alison E. Field, ScD; S. Bryn Austin, ScD
[+] Author Affiliations

Author Affiliations: Obesity Prevention Program, Department of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care (Drs Haines and Kleinman and Ms Rifas-Shiman); Division of Adolescent/Young Adult Medicine, Department of Medicine, Children's Hospital Boston (Drs Field and Austin), and Channing Laboratory, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School (Drs Field and Austin); and Departments of Epidemiology (Dr Field) and Society, Human Development, and Health (Dr Austin), Harvard School of Public Health, Boston, Massachusetts.


Arch Pediatr Adolesc Med. 2010;164(4):336-343. doi:10.1001/archpediatrics.2010.19.
Text Size: A A A
Published online

Objective  To identify shared risk and protective factors for purging, binge eating, and overweight.

Design  Prospective cohort study.

Setting  Population-based questionnaires of children and adolescents residing across the United States.

Participants  Girls (n = 6022) and boys (n = 4518), aged 11 to 17 years in 1998, in the ongoing Growing Up Today Study.

Main Exposures  Putative risk and protective factors within the psychological, behavioral, and socioenvironmental domains.

Main Outcome Measures  Overweight, use of laxatives or purging (vomiting), and binge eating. Because of the low prevalence of purging, we did not examine shared factors for this behavior among boys.

Results  In 1998, a total of 219 girls (3.7%) and 30 boys (0.7%) reported purging behaviors, 426 girls (7.1%) and 90 boys (2.0%) reported binge eating, and 1019 girls (17.4%) and 1040 boys (24.6%) were overweight. From 1999 through 2001, 331 girls (7.8%) initiated purging behaviors, 503 girls (11.8%) and 132 boys (4.5%) initiated binge eating behaviors, and 424 girls (10.0%) and 382 boys (13.6%) became overweight. Concern for weight was directly associated with all 3 weight-related problems among boys and girls. Among girls, dieting, parental weight-related teasing, and family meal frequency had a shared effect on the weight-related problems examined.

Conclusions  Factors within the psychological, behavioral, and socioenvironmental domains may have a shared effect on purging, binge eating, and overweight. Further research is needed to determine if an intervention designed to address these shared risk and protective factors is effective in simultaneously reducing these weight-related problems.

Figures in this Article

Weight-related problems, including purging (vomiting), binge eating, and overweight or obesity (hereafter referred to as overweight), are prevalent among adolescents13 and have adverse consequences for health.48 Research suggesting that weight-related problems may co-occur in an individual, and that individuals may transition from one problem to another, has prompted researchers in the fields of eating disorders and obesity prevention to propose an integrated approach that addresses the spectrum of weight-related problems within a single intervention.913 However, limited knowledge about shared risk factors for these weight-related problems is a roadblock to developing interventions using this integrated approach.

Few studies have examined shared risk factors for weight-related problems. A study14 of more than 1000 adult twins found that having received parental comments about weight, as assessed retrospectively, was a shared risk factor for binge eating and purging. Possible differential recall of comments from parents is an important inferential limitation of this study. In addition, overweight was not examined. Previous analyses of the Growing Up Today Study (GUTS) have examined risk factors for binge eating and purging, but these analyses did not examine shared factors for purging, binge eating, and overweight.15

Neumark-Sztainer et al16 examined shared risk factors for overweight, binge eating, and weight control behaviors, including purging, among 2500 adolescents and found that, among girls, weight concern, weight-related teasing, and dieting predicted all 3 outcomes. Among boys, weight concern and weight control behaviors were associated with all 3 outcomes. Neumark-Sztainer et al examined the association between each risk factor and each weight-related problem in separate models. Thus, the relative contribution of these factors in relation to the others explored is unknown. Examining the relative contribution would help identify the most potent factors on which to intervene. In addition, the analyses of Neumark-Sztainer et al did not account for the correlation between these outcomes, possibly causing the standard error estimates of the effects to be too small, which can result in P values that overstate the significance of observed associations. Our study addresses limitations of previous research by modeling these weight-related outcomes jointly, allowing for appropriate estimation of P values and for assessing whether risk factors are associated differentially with purging, binge eating, and overweight.

We aimed to identify shared risk factors for overweight and disordered eating behaviors that could serve as targets for integrated interventions. To achieve this aim, we examined cross-sectional and prospective associations between a range of psychological, behavioral, and socioenvironmental factors and purging, binge eating, and overweight among a large sample of children and adolescents (aged 11-17 years). We hypothesized that factors within the psychological, socioenvironmental, and behavioral domains would jointly predict purging, binge eating, and overweight.

THEORETICAL MODEL

The putative risk factors of weight-related outcomes examined in this study are derived theoretically based on social cognitive theory (Figure).17,18 Many have been examined previously in etiologic studies of overweight or disordered eating.16,19

Place holder to copy figure label and caption
Figure.

Putative socioenvironmental, behavioral, and psychological risk and protective factors for purging, binge eating, and overweight among adolescents.

Graphic Jump Location
STUDY POPULATION

GUTS is a prospective cohort study of adolescents residing throughout the United States. Participants are offspring of participants in the second Nurses' Health Study (NHS II). Participants in NHS II provided consent for their child to participate in GUTS. In 1996, we mailed GUTS participants an explanatory letter and a questionnaire. Returning the questionnaire constituted consent. The Human Subjects Committee at Brigham and Women's Hospital approved this study.

Details of initial recruitment are available elsewhere.20 The baseline 1996 sample included 8843 girls and 7696 boys ages 9 through 14 years. Participants were mailed follow-up questionnaires annually from 1997 through 2001 and biannually since 2003. For the present study, we explored cross-sectional associations between risk factors and purging, binge eating, and overweight in 1998 when participants were aged 11 through 17 years. We examined these associations in 1998 because all predictor variables of interest were assessed that year and most of the participants would have entered puberty by that time. Puberty has been shown to be associated with the development of weight-related problems.21 In our prospective analyses, we explored the association between factors assessed in 1998 and cumulative incidence of overweight, binge eating, and purging behaviors in 1999, 2000, and 2001. We selected these 3 years, which are the most proximal to the time the predictor variables were measured, to help reduce the noise from other factors that may influence these outcomes. In our cross-sectional (1998) analyses, we excluded 107 girls and 73 boys with medical conditions possibly interfering with growth, 1128 girls and 1417 boys missing data on all 3 outcome variables, and 1586 girls and 1688 boys missing any of the predictor variables of interest for 1998. Our final sample for our cross-sectional analyses was 6022 girls and 4518 boys. To identify development of weight-related problems subsequent to the predictors of interest, only participants who were not overweight and were not engaging in any of the relevant disordered eating behaviors in 1998 were eligible for the prospective analysis. Thus, we excluded 1597 girls and 1389 boys who reported purging or binge eating or who were overweight in 1998. We also excluded 163 girls and 219 boys missing data on all 3 outcome variables across the follow-up years. Our final sample for prospective analyses was 4262 girls and 2910 boys.

OUTCOME MEASURES
Purging

We assessed purging with the following validated questions2224: “During the past year, how often did you make yourself throw up to keep from gaining weight?” and “How often did you take laxatives to keep from gaining weight?” Response options ranged from “never” to “daily.” We defined purging as reporting vomiting or laxative use in the past year.

Binge Eating

We assessed binge eating with validated questions.22,23 Participants first reported the frequency during the past year of eating “so much food in a short period of time that you would be embarrassed if others saw you (binge eating or gorging).” Response options ranged from “never” to “more than once a week.” Respondents who reported any episodes of overeating were directed to a follow-up question asking whether “you felt out of control during these episodes, like you could not stop even if you wanted to”. We defined binge eating as having at least 1 episode of overeating in the past year and feeling out of control during the episode.

Overweight

Children and adolescents self-reported their height and weight. Previous studies2527 report high validity for self-reported heights and weights in adolescents. We classified children and adolescents as overweight or obese based on the International Obesity Task Force cutoff points,28 which are age- and sex-specific body mass index (calculated as weight in kilograms divided by height in meters squared) values for individuals younger than 18 years that correspond with a body mass index of 25 at 18 years of age. Thus, the International Obesity Task Force cutoff points provide comparability in assessing overweight in adolescents and adults.

PSYCHOLOGICAL AND BEHAVIORAL FACTORS
Weight Concern

We assessed weight concern using items from the McKnight Risk Factor Survey.29 Adolescent boys are more likely than girls to want to increase muscle tone rather than be thin;30 thus, to make the questions appropriate for boys, we replaced the questions on thinness with questions about the importance of not being fat in the surveys sent to male participants.

Dieting

We assessed dieting with the question, “During the past year, how often did you diet to lose weight or to keep from gaining weight?” Response options ranged from “never” to “always on a diet.” For these analyses, participants were considered dieters if they reported any dieting.

Fast-Food Intake

We assessed fast-food intake with the question, “How often do you eat fried foods away from home (like French fries)?” Response items ranged from “never/less than once per week” to “daily.” This item is moderately correlated with a question asking about the frequency of eating at a fast-food restaurant.31

Breakfast

We assessed frequency of breakfast with the question, “How many times each week (including weekdays and weekends) do you eat breakfast?” Response options ranged from “never or almost never” to “5 or more times per week.”

Physical Activity

We assessed mean hours of physical activity per week using the 18-item Youth/Adolescent Activity Questionnaire. This tool is based on the validated assessment tool developed for the NHS II questionnaire.32

Television Viewing

We assessed television (TV) viewing with the question, “How many hours per week do you spend watching TV?” Response options ranged from “never” to “31 or more hours per week.” Separate questions were asked for weekends and weekdays, and the values were summed and averaged to create the hours-per-day variable.

SOCIOENVIRONMENTAL FACTORS
Maternal Dieting

We assessed adolescent perception of maternal dieting with the question, “In the past year, how often has your mother tried to lose weight?” Response options ranged from “never” to “always.” For these analyses, mothers were considered dieters if their child reported any maternal dieting.33

Parental Weight-Related Teasing

We assessed parental weight-related teasing with the question, “In the past year, how often has your mother made a comment about your weight or eating that made you feel bad?” (a similar question was given with regard to the father). Response options ranged from “never” to “always.”

Peer Concern With Thinness

We assessed peer concern with the following questions: (1) “How often have your friends talked about wanting to lose weight?” (2) “How important has it been to your friends that they not be fat?” and (3) “How important has it been to your friends that you not be fat?” We used the mean score of these questions to create the peer influence variable.

Desire to Look Like Same-Sex Media Figure

We assessed desire to look like same-sex media figures with the question, “In the past year, how often have you tried to look like the girls or women you see on TV, in movies, or in magazines?” (a similar question was posed to boys). Response options ranged from “not at all” to “totally.”

Family Meal Frequency

We assessed family meal frequency with the question, “How often do you sit down with other members of your family to eat dinner or supper?” Response options ranged from “never” to “every day.”

Other Covariates

The age of the child/adolescent was used as a covariate. We calculated this age from the individual's birth date and the date each questionnaire was returned.

STATISTICAL ANALYSES

We used generalized estimating equations34,35 to jointly model the effects of the predictors on purging, binge eating, and overweight. These models assume that there is some correlation among the outcomes and adjust standard errors to account for this correlation. We first assessed whether different effects for each predictor were necessary. To do this, we included each predictor as a main effect plus interaction terms between outcome type (ie, purging, binge eating, overweight) and each predictor. Specifically, we included a row for each outcome for each participant. An indicator variable for outcome type is included in this row, as well as an interaction term between the indicator variable and each predictor. The test to examine whether different odds ratios (ORs) are required for each outcome is a 2-df test of whether that interaction is significant. If the interaction terms were statistically significant (P ≤ .05), we retained them in the model and showed the distinct ORs for each outcome associated with the predictor. If the interaction terms were not significant, we removed them from the model and presented the homogenous main effect of the predictor on the outcomes as a single OR, which applies to all of the outcomes. All analyses were stratified by sex and conducted using SAS statistical software, version 9.1 (SAS Institute, Cary, North Carolina).

We conducted sensitivity analyses for the cross-sectional and prospective analyses to examine how our decisions regarding inclusion and exclusion of participants may have influenced our results. We ran our models 2 different ways: (1) excluding any participants who had missing data on any outcome variable of interest and (2) including all participants in the models regardless of how many outcome variables of interest were missing. No substantive differences in results were found for the model options. We chose to use results from the second model, which kept all available data by including all participants in the models regardless of how many outcome variables of interest were missing.

PARTICIPANT CHARACTERISTICS

In 1998, a total of 219 girls (3.6%) and 30 boys (0.7%) reported purging and 426 girls (7.1%) and 90 boys (2.0%) reported binge eating (Table 1). In addition, 1019 girls (17.4%) and 1040 boys (24.6%) were overweight. Given the small number of boys reporting purging behaviors, we did not include purging in our examination of shared factors for boys. During the 3-year follow-up period, 331 girls (7.8%) initiated purging, whereas 503 girls (11.8%) and 132 boys (4.5%) initiated binge eating behaviors. In addition, 424 girls (10.0%) and 382 boys (13.6%) became overweight.

Table Graphic Jump LocationTable 1. Outcomes, Predictors, and Covariates of Growing Up Today Study Participants in 1998
CROSS-SECTIONAL RESULTS

Table 2 presents the cross-sectional multivariable adjusted ORs of purging (girls only), binge eating, and overweight associated with psychological, behavioral, and socioenvironmental factors among girls and boys. In instances when the effect estimates for a predictor were similar for all 3 outcomes (ie, the interaction term of outcome type and the predictor variable of interest was not significant), we present the single homogeneous main effect of the predictor variable on the outcomes. In instances when the effect estimates for a predictor were significantly different for the 3 outcomes (ie, the interaction term was significant), we present the individual effect of the predictor variable and each outcome.

Table Graphic Jump LocationTable 2. Cross-sectional Associations Between Psychological, Behavioral, and Socioenvironmental Factors and Weight-Related Outcomes in 1998 in Adolescent Girls and Boysa
Girls

Among girls, weight concern was directly associated with all 3 weight-related problems and the direction and magnitude of the effect were similar for all 3 outcomes (homogeneous effect OR, 2.45; 95% confidence interval [CI], 2.26-2.67). Of the 5 behavioral factors examined, only dieting was significantly associated with all 3 weight-related problems. The magnitude of the effect differed across the 3 outcomes, with dieting being most strongly associated with purging. Physical activity was significantly associated with purging and overweight; however, the direction of the effect differed; physical activity was directly associated with purging and inversely associated with overweight. Fast-food intake, breakfast, and TV viewing did not have a shared effect on the weight-related problems examined.

None of the socioenvironmental factors were significantly associated with all 3 weight-related problems. However, a number of socioenvironmental factors were associated with 2 of the 3 weight-related problems, suggesting a shared effect. Parental weight-related teasing was directly associated with binge eating and overweight. Family meal frequency was inversely associated with purging and binge eating. The desire to look like same-sex media figures and the importance of thinness to peers were also significantly associated with 2 of the weight-related problems; however, the direction of these associations differed across outcomes. The desire to look like same-sex media figures was directly associated with purging and inversely associated with overweight. The importance of thinness to peers was directly associated with binge eating and inversely associated with overweight. Maternal dieting did not have a shared effect on the weight-related problems examined.

Boys

Among boys, concern with weight was directly associated with binge eating and overweight; the magnitude of effect differed across the 2 outcomes, with weight concern being more strongly associated with overweight. Of the 5 behavioral factors examined, only TV viewing was significantly associated with binge eating and overweight. Television viewing was directly associated with both outcomes (homogeneous effect OR, 1.12; 95% CI, 1.06-1.18). Dieting, fast-food intake, breakfast, and physical activity did not have a shared effect on binge eating and overweight among boys.

Parental weight-related teasing was directly associated with binge eating and overweight (homogeneous effect OR, 1.31; 95% CI, 1.15-1.50). Importance of thinness to peers was significantly associated with binge eating and overweight; however, the direction of these associations differed across outcomes. Importance of thinness to peers was directly associated with binge eating and inversely associated with overweight. The desire to look like same-sex media figures was also directly associated with binge eating and inversely associated with overweight. Maternal dieting and family meal frequency did not have a shared effect on binge eating and overweight.

PROSPECTIVE RESULTS

Table 3 presents the prospective multivariable adjusted ORs of incident cases of purging (girls only), binge eating, and overweight status. These factors are associated with risk factors among girls and boys.

Table Graphic Jump LocationTable 3. Prospective Associations Between Psychological, Behavioral, and Socioenvironmental Factors Assessed in 1998 and Incident Weight-Related Outcomes in 1999-2001 in Adolescent Girls and Boysa
Girls

As in our cross-sectional analyses, concern with weight was directly associated with all 3 weight-related problems in our prospective analyses, and the direction and magnitude of the effect were similar for all 3 outcomes (homogeneous effect OR, 1.56; 95% CI, 1.42-1.71). Dieting was also directly associated with those 3 outcomes (homogeneous effect OR, 1.48; 95% CI, 1.25-1.74). Unlike our cross-sectional results, which found that physical activity was directly associated with purging and inversely associated with overweight, our prospective analyses showed that physical activity did not have a shared effect on the weight-related outcomes. Prospectively, fast-food intake, breakfast, and TV viewing did not have a shared effect on weight-related problems, similar to our cross-sectional findings.

As we found in our cross-sectional analyses, parental weight-related teasing was directly associated with binge eating and overweight but not purging prospectively. Also similar to our cross-sectional analyses, the desire to look like same-sex media figures was associated with more than 1 weight-related problem prospectively, but the direction of this effect differed across outcomes; it was directly associated with purging and inversely associated with overweight. Prospectively, family meal frequency was inversely associated with all 3 weight-related outcomes (homogeneous effect OR, 0.90; 95% CI, 0.83-0.98). Maternal dieting and the importance of thinness to peers did not have a shared effect on weight-related problems.

Boys

As we found in our cross-sectional analyses, concern with weight was directly associated with binge eating and overweight prospectively; the effect's magnitude differed across the 2 outcomes, with weight concern being more strongly associated with overweight. Unlike our cross-sectional results, which found that TV viewing was directly associated with binge eating and overweight prospectively, TV viewing did not have a shared effect on obesity and binge eating. Dieting, fast-food intake, breakfast, and physical activity also did not have a shared effect on binge eating and overweight among boys. Prospectively, none of the 5 socioenvironmental factors had a shared effect on binge eating and overweight among boys.

Using analytic methods that account for the correlation among the 3 weight-related outcomes, we examined shared risk factors of purging, binge eating, and overweight in a large cohort of adolescents. Identification of shared risk factors for these weight-related problems can inform development of interventions to promote maintenance of healthful weight and decrease risk of disordered eating.

We found that weight concern was the most robust shared risk factor for purging (girls only), binge eating, and overweight among boys and girls. Among girls, dieting was a shared risk factor for purging, binge eating, and overweight. Two socioenvironmental factors, weight-related teasing by parents and family meal frequency, had a shared effect on weight-related problems. Parental weight-related teasing was a risk factor for binge eating and overweight, and family meal frequency was a protective factor for all 3 weight-related outcomes. These findings are consistent with previous research showing that dieting36,37 and weight-related teasing38,39 are associated with increased risk of disordered eating and obesity and that family meals4043 may reduce adolescents' risk of engaging in disordered eating behaviors.

Our finding that girls who reported wanting to look like same-sex media figures were less likely to become overweight but were more likely to initiate purging behaviors underscores the importance of examining the influence of risk factors on a range of weight-related problems. By looking only at the influence of wanting to look like media figures on obesity risk, researchers and public health professionals may inadvertently promote an obesity prevention strategy (ie, emulating media figures) that could increase disordered eating risk among adolescents.44

Among boys, none of the behavioral or socioenvironmental factors were consistently associated with binge eating and overweight. Our results are consistent with the finding by Neumark-Sztainer et al16 that, compared with girls, substantially fewer risk factors had a shared effect on weight-related problems among boys. It is possible that our relatively null findings among boys may be because our measures of the behavioral or socioenvironmental factors do not adequately capture the experiences of boys. For example, we did not assess performance-related (vs appearance-related) pressures to achieve an ideal body weight, which may have a strong influence on weight-related problems among boys.45 Further research is needed to elucidate shared factors of weight-related problems among boys.

This study's strengths include prospective data collection, the breadth of theoretically driven risk factors examined, and the use of analytic methods that account for the correlation among the weight-related outcomes examined. This study also had limitations. Although study participants reside throughout the United States, our cohort is not a representative sample of US adolescents. Participants are children of registered nurses and the cohort is more than 90% white, which may reduce the generalizability of our findings. However, our findings are similar to those of Neumark-Sztainer et al,16 who examined shared risk factors in an ethnically and socioeconomically diverse population. Another limitation was the necessity of collecting data from adolescents by self-report questionnaires. All 3 self-report outcome measures have been previously validated,22,23,46 and the resulting measurement error should be random.

In conclusion, we found that weight concern was the most robust shared risk factor for overweight and disordered eating among adolescents. Among girls, we found that dieting, parental weight-related teasing, and family meal frequency had a shared effect on these weight-related problems. Interventions that aim to prevent multiple weight-related problems should test strategies that address these factors to determine whether such efforts can reduce the high prevalence of overweight and disordered eating behaviors among adolescents.

Correspondence: Jess Haines, PhD, MHSc, RD, Obesity Prevention Program, Department of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care, 133 Brookline Ave, Sixth Floor, Boston, MA 02215 (Jess_Haines@harvardpilgrim.org).

Accepted for Publication: November 30, 2009.

Author Contributions: Drs Field and Austin contributed equally to this study. Drs Haines and Field and Ms Rifas-Shiman had full access to all data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Haines, Kleinman, and Austin. Acquisition of data: Field and Austin. Analysis and interpretation of data: Haines, Kleinman, Rifas-Shiman, Field, and Austin. Drafting of the manuscript: Haines. Critical revision of the manuscript for important intellectual content: Haines, Kleinman, Rifas-Shiman, Field, and Austin. Statistical analysis: Kleinman and Rifas-Shiman. Obtained funding: Haines, Field, and Austin. Administrative, technical, and material support: Haines. Study supervision: Austin.

Financial Disclosure: None reported.

Funding/Support: This study was supported by grants DK46834, DK59570, and DK072117 from the National Institutes of Health; the Kellogg Company; and grant 200510MFE-154556-10955 from the Canadian Institutes of Health Research.

Ogden  CLCarroll  MDCurtin  LRMcDowell  MATabak  CJFlegal  KM Prevalence of overweight and obesity in the United States, 1999-2004. JAMA 2006;295 (13) 1549- 1555
PubMed Link to Article
Hoek  HW Incidence, prevalence and mortality of anorexia nervosa and other eating disorders. Curr Opin Psychiatry 2006;19 (4) 389- 394
PubMed Link to Article
Keel  PKHeatherton  TFDorer  DJJoiner  TEZalta  AK Point prevalence of bulimia nervosa in 1982, 1992, and 2002. Psychol Med 2006;36 (1) 119- 127
PubMed Link to Article
Johnson  JGCohen  PKasen  SBrook  JS Childhood adversities associated with risk for eating disorders or weight problems during adolescence or early adulthood. Am J Psychiatry 2002;159 (3) 394- 400
PubMed Link to Article
Strauss  CCSmith  KFrame  CForehand  R Personal and interpersonal characteristics associated with childhood obesity. J Pediatr Psychol 1985;10 (3) 337- 343
PubMed Link to Article
Fagot-Campagna  APettitt  DJEngelgau  MM  et al.  Type 2 diabetes among North American children and adolescents: an epidemiologic review and a public health perspective. J Pediatr 2000;136 (5) 664- 672
PubMed Link to Article
Herzog  DBKeller  MBSacks  NRYeh  CJLavori  PW Psychiatric comorbidity in treatment-seeking anorexics and bulimics. J Am Acad Child Adolesc Psychiatry 1992;31 (5) 810- 818
PubMed Link to Article
Zipfel  SLowe  BReas  DLDeter  HCHerzog  W Long-term prognosis in anorexia nervosa: lessons from a 21-year follow-up study. Lancet 2000;355 (9205) 721- 722
PubMed Link to Article
Neumark-Sztainer  D Obesity and eating disorder prevention: an integrated approach? Adolesc Med 2003;14 (1) 159- 173
PubMed
Irving  LMNeumark-Sztainer  D Integrating the prevention of eating disorders and obesity: feasible or futile? Prev Med 2002;34 (3) 299- 309
PubMed Link to Article
Smolak  LStriegel-Moore  RH Future directions in eating disorder and obesity research. Thompson  JKHandbook of Eating Disorders and Obesity. Hoboken, NJ John Wiley & Sons Inc2004;738- 754
Austin  SB Prevention research and eating disorders: theory and new directions. Psychol Med 2000;30 (6) 1249- 1262
PubMed Link to Article
Brownell  KDFairburn  CG Eating Disorders and Obesity: A Comprehensive Handbook.  New York, NY Guilford Press1995;
Wade  TDTreloar  SMartin  NG Shared and unique risk factors between lifetime purging and objective binge eating: a twin study. Psychol Med 2008;38 (10) 1455- 1464
PubMed Link to Article
Field  AEJavaras  KMAneja  P  et al.  Family, peer, and media predictors of becoming eating disordered. Arch Pediatr Adolesc Med 2008;162 (6) 574- 579
PubMed Link to Article
Neumark-Sztainer  DRWall  MMHaines  JIStory  MTSherwood  NEvan den Berg  PA Shared risk and protective factors for overweight and disordered eating in adolescents. Am J Prev Med 2007;33 (5) 359- 369
PubMed Link to Article
Bandura  A Social Learning Theory.  Englewood Cliffs, NJ Prentice Hall1977;
Bandura  A Social Foundations of Thought and Action: A Social Cognitive Theory.  Englewood Cliffs, NJ Prentice-Hall1986;
Haines  JNeumark-Sztainer  D Prevention of obesity and eating disorders: a consideration of shared risk factors. Health Educ Res 2006;21 (6) 770- 782
PubMed Link to Article
Gillman  MWRifas-Shiman  SLCamargo  CA  Jr  et al.  Risk of overweight among adolescents who were breastfed as infants. JAMA 2001;285 (19) 2461- 2467
PubMed Link to Article
Stice  E Risk and maintenance factors for eating pathology: a meta-analytic review. Psychol Bull 2002;128 (5) 825- 848
PubMed Link to Article
Field  AETaylor  CBCelio  AColditz  GA Comparison of self-report to interview assessment of bulimic behaviors among preadolescent and adolescent girls and boys. Int J Eat Disord 2004;35 (1) 86- 92
PubMed Link to Article
Brener  NDCollins  JLKann  LWarren  CWWilliams  BI Reliability of the Youth Risk Behavior Survey Questionnaire. Am J Epidemiol 1995;141 (6) 575- 580
PubMed
Kann  LWarren  CWHarris  WA  et al.  Youth Risk Behavior Surveillance—United States, 1995. MMWR CDC Surveill Summ 1996;45 (4) 1- 84
PubMed
Shannon  BSmiciklas-Wright  HWang  MQ Inaccuracies in self-reported weights and heights of a sample of sixth-grade children. J Am Diet Assoc 1991;91 (6) 675- 678
PubMed
Strauss  RS Comparison of measured and self-reported weight and height in a cross-sectional sample of young adolescents. Int J Obes Relat Metab Disord 1999;23 (8) 904- 908
PubMed Link to Article
Goodman  EHinden  BRKhandelwal  S Accuracy of teen and parental reports of obesity and body mass index. Pediatrics 2000;106 (1, pt 1) 52- 58
PubMed Link to Article
Cole  TJBellizzi  MCFlegal  KMDietz  WH Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ 2000;320 (7244) 1240- 1243
PubMed Link to Article
Shisslak  CMRenger  RSharpe  T  et al.  Development and evaluation of the McKnight Risk Factor Survey for assessing potential risk and protective factors for disordered eating in preadolescent and adolescent girls. Int J Eat Disord 1999;25 (2) 195- 214
PubMed Link to Article
McCabe  MPRicciardelli  LAFinemore  J The role of puberty, media and popularity with peers on strategies to increase weight, decrease weight and increase muscle tone among adolescent boys and girls. J Psychosom Res 2002;52 (3) 145- 153
PubMed Link to Article
Taveras  EMBerkey  CSRifas-Shiman  SL  et al.  Association of consumption of fried food away from home with body mass index and diet quality in older children and adolescents. Pediatrics 2005;116 (4) e518- e524http://www.ajcn.org/cgi/content/full/86/1/198. Accessed February 8, 2010
PubMed Link to Article
Wolf  AMHunter  DJColditz  GA  et al.  Reproducibility and validity of a self-administered physical activity questionnaire. Int J Epidemiol 1994;23 (5) 991- 999
PubMed Link to Article
Field  AEAustin  SBStriegel-Moore  R  et al.  Weight concerns and weight control behaviors of adolescents and their mothers. Arch Pediatr Adolesc Med 2005;159 (12) 1121- 1126
PubMed Link to Article
Zeger  SLLiang  KY Longitudinal data analysis for discrete and continuous outcomes. Biometrics 1986;42 (1) 121- 130
PubMed Link to Article
Liang  KZeger  S Longitudinal data analysis using generalized linear models. Biometrika 1986;73 (1) 13- 22
Link to Article
Neumark-Sztainer  DWall  MGuo  JStory  MHaines  JEisenberg  M Obesity, disordered eating, and eating disorders in a longitudinal study of adolescents: how do dieters fare 5 years later? J Am Diet Assoc 2006;106 (4) 559- 568
PubMed Link to Article
Stice  ECameron  RPKillen  JDHayward  CTaylor  CB Naturalistic weight-reduction efforts prospectively predict growth in relative weight and onset of obesity among female adolescents. J Consult Clin Psychol 1999;67 (6) 967- 974
PubMed Link to Article
Taylor  CBBryson  SCelio Doyle  AA  et al.  The adverse effect of negative comments about weight and shape from family and siblings on women at high risk for eating disorders. Pediatrics 2006;118 (2) 731- 738
PubMed Link to Article
Keery  HBoutelle  Kvan den Berg  PThompson  JK The impact of appearance-related teasing by family members. J Adolesc Health 2005;37 (2) 120- 127
PubMed Link to Article
Neumark-Sztainer  DEisenberg  MEFulkerson  JAStory  MLarson  NI Family meals and disordered eating in adolescents: longitudinal findings from project EAT. Arch Pediatr Adolesc Med 2008;162 (1) 17- 22
PubMed Link to Article
Ackard  DMNeumark-Sztainer  D Family mealtime while growing up: associations with symptoms of bulimia nervosa. Eat Disord 2001;9 (3) 239- 249
PubMed Link to Article
Sen  B Frequency of family dinner and adolescent body weight status: evidence from the national longitudinal survey of youth, 1997. Obesity (Silver Spring) 2006;14 (12) 2266- 2276
PubMed Link to Article
Veugelers  PJFitzgerald  AL Prevalence of and risk factors for childhood overweight and obesity. CMAJ 2005;173 (6) 607- 613
PubMed Link to Article
Taveras  EMRifas-Shiman  SLField  AEFrazier  ALColditz  GAGillman  MW The influence of wanting to look like media figures on adolescent physical activity. J Adolesc Health 2004;35 (1) 41- 50
PubMed Link to Article
Cafri  Gvan den Berg  PThompson  JK Pursuit of muscularity in adolescent boys: relations among biopsychosocial variables and clinical outcomes. J Clin Child Adolesc Psychol 2006;35 (2) 283- 291
PubMed Link to Article
Field  AEAneja  PRosner  B The validity of self-reported weight change among adolescents and young adults. Obesity (Silver Spring) 2007;15 (9) 2357- 2364
PubMed Link to Article

Figures

Place holder to copy figure label and caption
Figure.

Putative socioenvironmental, behavioral, and psychological risk and protective factors for purging, binge eating, and overweight among adolescents.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Outcomes, Predictors, and Covariates of Growing Up Today Study Participants in 1998
Table Graphic Jump LocationTable 2. Cross-sectional Associations Between Psychological, Behavioral, and Socioenvironmental Factors and Weight-Related Outcomes in 1998 in Adolescent Girls and Boysa
Table Graphic Jump LocationTable 3. Prospective Associations Between Psychological, Behavioral, and Socioenvironmental Factors Assessed in 1998 and Incident Weight-Related Outcomes in 1999-2001 in Adolescent Girls and Boysa

References

Ogden  CLCarroll  MDCurtin  LRMcDowell  MATabak  CJFlegal  KM Prevalence of overweight and obesity in the United States, 1999-2004. JAMA 2006;295 (13) 1549- 1555
PubMed Link to Article
Hoek  HW Incidence, prevalence and mortality of anorexia nervosa and other eating disorders. Curr Opin Psychiatry 2006;19 (4) 389- 394
PubMed Link to Article
Keel  PKHeatherton  TFDorer  DJJoiner  TEZalta  AK Point prevalence of bulimia nervosa in 1982, 1992, and 2002. Psychol Med 2006;36 (1) 119- 127
PubMed Link to Article
Johnson  JGCohen  PKasen  SBrook  JS Childhood adversities associated with risk for eating disorders or weight problems during adolescence or early adulthood. Am J Psychiatry 2002;159 (3) 394- 400
PubMed Link to Article
Strauss  CCSmith  KFrame  CForehand  R Personal and interpersonal characteristics associated with childhood obesity. J Pediatr Psychol 1985;10 (3) 337- 343
PubMed Link to Article
Fagot-Campagna  APettitt  DJEngelgau  MM  et al.  Type 2 diabetes among North American children and adolescents: an epidemiologic review and a public health perspective. J Pediatr 2000;136 (5) 664- 672
PubMed Link to Article
Herzog  DBKeller  MBSacks  NRYeh  CJLavori  PW Psychiatric comorbidity in treatment-seeking anorexics and bulimics. J Am Acad Child Adolesc Psychiatry 1992;31 (5) 810- 818
PubMed Link to Article
Zipfel  SLowe  BReas  DLDeter  HCHerzog  W Long-term prognosis in anorexia nervosa: lessons from a 21-year follow-up study. Lancet 2000;355 (9205) 721- 722
PubMed Link to Article
Neumark-Sztainer  D Obesity and eating disorder prevention: an integrated approach? Adolesc Med 2003;14 (1) 159- 173
PubMed
Irving  LMNeumark-Sztainer  D Integrating the prevention of eating disorders and obesity: feasible or futile? Prev Med 2002;34 (3) 299- 309
PubMed Link to Article
Smolak  LStriegel-Moore  RH Future directions in eating disorder and obesity research. Thompson  JKHandbook of Eating Disorders and Obesity. Hoboken, NJ John Wiley & Sons Inc2004;738- 754
Austin  SB Prevention research and eating disorders: theory and new directions. Psychol Med 2000;30 (6) 1249- 1262
PubMed Link to Article
Brownell  KDFairburn  CG Eating Disorders and Obesity: A Comprehensive Handbook.  New York, NY Guilford Press1995;
Wade  TDTreloar  SMartin  NG Shared and unique risk factors between lifetime purging and objective binge eating: a twin study. Psychol Med 2008;38 (10) 1455- 1464
PubMed Link to Article
Field  AEJavaras  KMAneja  P  et al.  Family, peer, and media predictors of becoming eating disordered. Arch Pediatr Adolesc Med 2008;162 (6) 574- 579
PubMed Link to Article
Neumark-Sztainer  DRWall  MMHaines  JIStory  MTSherwood  NEvan den Berg  PA Shared risk and protective factors for overweight and disordered eating in adolescents. Am J Prev Med 2007;33 (5) 359- 369
PubMed Link to Article
Bandura  A Social Learning Theory.  Englewood Cliffs, NJ Prentice Hall1977;
Bandura  A Social Foundations of Thought and Action: A Social Cognitive Theory.  Englewood Cliffs, NJ Prentice-Hall1986;
Haines  JNeumark-Sztainer  D Prevention of obesity and eating disorders: a consideration of shared risk factors. Health Educ Res 2006;21 (6) 770- 782
PubMed Link to Article
Gillman  MWRifas-Shiman  SLCamargo  CA  Jr  et al.  Risk of overweight among adolescents who were breastfed as infants. JAMA 2001;285 (19) 2461- 2467
PubMed Link to Article
Stice  E Risk and maintenance factors for eating pathology: a meta-analytic review. Psychol Bull 2002;128 (5) 825- 848
PubMed Link to Article
Field  AETaylor  CBCelio  AColditz  GA Comparison of self-report to interview assessment of bulimic behaviors among preadolescent and adolescent girls and boys. Int J Eat Disord 2004;35 (1) 86- 92
PubMed Link to Article
Brener  NDCollins  JLKann  LWarren  CWWilliams  BI Reliability of the Youth Risk Behavior Survey Questionnaire. Am J Epidemiol 1995;141 (6) 575- 580
PubMed
Kann  LWarren  CWHarris  WA  et al.  Youth Risk Behavior Surveillance—United States, 1995. MMWR CDC Surveill Summ 1996;45 (4) 1- 84
PubMed
Shannon  BSmiciklas-Wright  HWang  MQ Inaccuracies in self-reported weights and heights of a sample of sixth-grade children. J Am Diet Assoc 1991;91 (6) 675- 678
PubMed
Strauss  RS Comparison of measured and self-reported weight and height in a cross-sectional sample of young adolescents. Int J Obes Relat Metab Disord 1999;23 (8) 904- 908
PubMed Link to Article
Goodman  EHinden  BRKhandelwal  S Accuracy of teen and parental reports of obesity and body mass index. Pediatrics 2000;106 (1, pt 1) 52- 58
PubMed Link to Article
Cole  TJBellizzi  MCFlegal  KMDietz  WH Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ 2000;320 (7244) 1240- 1243
PubMed Link to Article
Shisslak  CMRenger  RSharpe  T  et al.  Development and evaluation of the McKnight Risk Factor Survey for assessing potential risk and protective factors for disordered eating in preadolescent and adolescent girls. Int J Eat Disord 1999;25 (2) 195- 214
PubMed Link to Article
McCabe  MPRicciardelli  LAFinemore  J The role of puberty, media and popularity with peers on strategies to increase weight, decrease weight and increase muscle tone among adolescent boys and girls. J Psychosom Res 2002;52 (3) 145- 153
PubMed Link to Article
Taveras  EMBerkey  CSRifas-Shiman  SL  et al.  Association of consumption of fried food away from home with body mass index and diet quality in older children and adolescents. Pediatrics 2005;116 (4) e518- e524http://www.ajcn.org/cgi/content/full/86/1/198. Accessed February 8, 2010
PubMed Link to Article
Wolf  AMHunter  DJColditz  GA  et al.  Reproducibility and validity of a self-administered physical activity questionnaire. Int J Epidemiol 1994;23 (5) 991- 999
PubMed Link to Article
Field  AEAustin  SBStriegel-Moore  R  et al.  Weight concerns and weight control behaviors of adolescents and their mothers. Arch Pediatr Adolesc Med 2005;159 (12) 1121- 1126
PubMed Link to Article
Zeger  SLLiang  KY Longitudinal data analysis for discrete and continuous outcomes. Biometrics 1986;42 (1) 121- 130
PubMed Link to Article
Liang  KZeger  S Longitudinal data analysis using generalized linear models. Biometrika 1986;73 (1) 13- 22
Link to Article
Neumark-Sztainer  DWall  MGuo  JStory  MHaines  JEisenberg  M Obesity, disordered eating, and eating disorders in a longitudinal study of adolescents: how do dieters fare 5 years later? J Am Diet Assoc 2006;106 (4) 559- 568
PubMed Link to Article
Stice  ECameron  RPKillen  JDHayward  CTaylor  CB Naturalistic weight-reduction efforts prospectively predict growth in relative weight and onset of obesity among female adolescents. J Consult Clin Psychol 1999;67 (6) 967- 974
PubMed Link to Article
Taylor  CBBryson  SCelio Doyle  AA  et al.  The adverse effect of negative comments about weight and shape from family and siblings on women at high risk for eating disorders. Pediatrics 2006;118 (2) 731- 738
PubMed Link to Article
Keery  HBoutelle  Kvan den Berg  PThompson  JK The impact of appearance-related teasing by family members. J Adolesc Health 2005;37 (2) 120- 127
PubMed Link to Article
Neumark-Sztainer  DEisenberg  MEFulkerson  JAStory  MLarson  NI Family meals and disordered eating in adolescents: longitudinal findings from project EAT. Arch Pediatr Adolesc Med 2008;162 (1) 17- 22
PubMed Link to Article
Ackard  DMNeumark-Sztainer  D Family mealtime while growing up: associations with symptoms of bulimia nervosa. Eat Disord 2001;9 (3) 239- 249
PubMed Link to Article
Sen  B Frequency of family dinner and adolescent body weight status: evidence from the national longitudinal survey of youth, 1997. Obesity (Silver Spring) 2006;14 (12) 2266- 2276
PubMed Link to Article
Veugelers  PJFitzgerald  AL Prevalence of and risk factors for childhood overweight and obesity. CMAJ 2005;173 (6) 607- 613
PubMed Link to Article
Taveras  EMRifas-Shiman  SLField  AEFrazier  ALColditz  GAGillman  MW The influence of wanting to look like media figures on adolescent physical activity. J Adolesc Health 2004;35 (1) 41- 50
PubMed Link to Article
Cafri  Gvan den Berg  PThompson  JK Pursuit of muscularity in adolescent boys: relations among biopsychosocial variables and clinical outcomes. J Clin Child Adolesc Psychol 2006;35 (2) 283- 291
PubMed Link to Article
Field  AEAneja  PRosner  B The validity of self-reported weight change among adolescents and young adults. Obesity (Silver Spring) 2007;15 (9) 2357- 2364
PubMed Link to Article

Correspondence

CME
Meets CME requirements for:
Browse CME for all U.S. States
Accreditation Information
The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
Note: You must get at least of the answers correct to pass this quiz.
You have not filled in all the answers to complete this quiz
The following questions were not answered:
Sorry, you have unsuccessfully completed this CME quiz with a score of
The following questions were not answered correctly:
Commitment to Change (optional):
Indicate what change(s) you will implement in your practice, if any, based on this CME course.
Your quiz results:
The filled radio buttons indicate your responses. The preferred responses are highlighted
For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
Indicate what changes(s) you will implement in your practice, if any, based on this CME course.
Submit a Comment

Multimedia

Some tools below are only available to our subscribers or users with an online account.

Web of Science® Times Cited: 36

Related Content

Customize your page view by dragging & repositioning the boxes below.

Articles Related By Topic
Related Collections
PubMed Articles