title: Isolating the effect of major depression on obesity: role of selection bias.
abstract: BACKGROUND
  There is suggestive evidence that rates of major depression have risen markedly in the U.S. concurrent with the rise in obesity. The economic burden of depression, about USD100 billion annually, is under-estimated if depression has a positive causal impact on obesity. However, virtually the entire existing literature on the connection between the two conditions has examined merely whether they are significantly correlated, sometimes holding constant a limited set of demographic factors.
  
  
  OBJECTIVE
  This study assesses whether, and the extent to which, the positive association between the two conditions reflects a causal link from major depression to higher BMI and obesity.
  
  
  METHODS
  Individual-level data from three nationally-representative studies are utilized: (i) National Comorbidity Survey-Replication (N=3,229); (ii) National Longitudinal Survey of Youth-1979 (N=21,365); and (iii) Behavioral Risk Factor Surveillance System (N=2,858,973). Dependent variables include body mass index (BMI) and a dichotomous indicator for overweight or obese. We measure diagnosed major depression based on DSM-IV criteria and the CES Depression scale. While contemporaneous effects are considered, the study primarily focuses on the effects of past and lifetime depression to bypass reverse causality and further assess the role of non-random selection on unobservable factors. The effects of past and lifetime depression on obesity are estimated based on: (i) models that control for an extensive set of typically-unobserved factors, including parental history, family background, parental investments, risk-taking, and use of anti-depressants and other prescription medications; (ii) constrained selection models; and (iii) models controlling for family fixed effects.
  
  
  RESULTS
  There are expectedly no significant or substantial effects of current depression on BMI or overweight/obesity, given that BMI is a stock that changes relatively slowly over time. Results also do not support a causal interpretation among males. However, among females, estimates indicate that past or lifetime diagnosis of major depression raises the probability of being overweight or obese by about seven percentage points. Results also suggest that this effect appears to plausibly operate through shifts in food consumption and physical activity.
  
  
  CONCLUSIONS
  Unadjusted differences document a strong correlation between depression and obesity, both cross-sectionally and temporally. However, it remains unclear how much of this association is consistent with a causal link from depression to obesity and how much of it is being driven by non-random selection. We find evidence that past and lifetime depression raises the probability of being overweight or obese among females. We estimate that this higher risk of overweight and obesity among females could potentially add about 10% (or USD9.7 billion) to the estimated economic burden of depression.
  
  
  CONCLUSIONS
  Estimates from this study suggest that the rising trend in obesity partly underlies the reported increased prevalence of depression, at least among women. Public health interventions which reduce major depression among women could therefore also further promote public health by reducing overweight and obesity.
  
  
  CONCLUSIONS
  While this study points to some preliminary evidence that the effect of depression on obesity appears to operate through shifts in diet and physical activity, more research is required to inform the proximate and distant mediating pathways. Though this study focuses on gender differentials, differences based on race/ethnicity and educational status would further inform heterogeneous responses across individuals and population subgroups.
authors.affiliation: Bentley University and National Bureau of Economic Research, Department of Economics, Waltham, MA 02452, USA. ddave@bentley.edu
authors.forename: Dhaval M
authors.initials: DM
authors.lastname: Dave
authors.forename: Jennifer
authors.initials: J
authors.lastname: Tennant
authors.forename: Gregory
authors.initials: G
authors.lastname: Colman
mesh_terms: D000293:Adolescent; D000328:Adult; D015984:Causality; D015897:Comorbidity; D017281:Cost of Illness; D003430:Cross-Sectional Studies; D003866:Depressive Disorder / Q000191:economics* / Q000453:epidemiology* / Q000208:ethnology; D015340:Epidemiologic Research Design; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D017059:Models, Econometric; D009765:Obesity / Q000191:economics / Q000453:epidemiology* / Q000208:ethnology; D015995:Prevalence; D012307:Risk Factors; D015983:Selection Bias; D017678:Sex Distribution; D014481:United States / Q000453:epidemiology; D055815:Young Adult