title: Weight Loss and Coronary Heart Disease: Sensitivity Analysis for Unmeasured Confounding by Undiagnosed Disease.
abstract: BACKGROUND
  Evidence for the effect of weight loss on coronary heart disease (CHD) or mortality has been mixed. The effect estimates can be confounded due to undiagnosed diseases that may affect weight loss.
  
  
  METHODS
  We used data from the Nurses' Health Study to estimate the 26-year risk of CHD under several hypothetical weight loss strategies. We applied the parametric g-formula and implemented a novel sensitivity analysis for unmeasured confounding due to undiagnosed disease by imposing a lag time for the effect of weight loss on chronic disease. Several sensitivity analyses were conducted.
  
  
  RESULTS
  The estimated 26-year risk of CHD did not change under weight loss strategies using lag times from 0 to 18 years. For a 6-year lag time, the risk ratios of CHD for weight loss compared with no weight loss ranged from 1.00 (0.99, 1.02) to 1.02 (0.99, 1.05) for different degrees of weight loss with and without restricting the weight loss strategy to participants with no major chronic disease. Similarly, no protective effect of weight loss was estimated for mortality risk. In contrast, we estimated a protective effect of weight loss on risk of type 2 diabetes.
  
  
  CONCLUSIONS
  We estimated that maintaining or losing weight after becoming overweight or obese does not reduce the risk of CHD or death in this cohort of middle-age US women. Unmeasured confounding, measurement error, and model misspecification are possible explanations but these did not prevent us from estimating a beneficial effect of weight loss on diabetes.
authors.affiliation: From the aDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA; bDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA; cDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA; dDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA; eChanning Laboratory, Harvard Medical School and Brigham and Women's Hospital, Boston, MA; fDivision of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and gHarvard-MIT Division of Health Sciences and Technology, Cambridge, MA.
authors.forename: Goodarz
authors.initials: G
authors.lastname: Danaei
authors.forename: James M
authors.initials: JM
authors.lastname: Robins
authors.forename: Jessica G
authors.initials: JG
authors.lastname: Young
authors.forename: Frank B
authors.initials: FB
authors.lastname: Hu
authors.forename: JoAnn E
authors.initials: JE
authors.lastname: Manson
authors.forename: Miguel A
authors.initials: MA
authors.lastname: Hernán
mesh_terms: D000328:Adult; D015992:Body Mass Index; D003327:Coronary Disease / Q000453:epidemiology* / Q000401:mortality; D003924:Diabetes Mellitus, Type 2 / Q000453:epidemiology; D005260:Female; D006801:Humans; D008875:Middle Aged; D015233:Models, Statistical; D009765:Obesity / Q000453:epidemiology / Q000628:therapy*; D050177:Overweight / Q000453:epidemiology / Q000628:therapy; D012307:Risk Factors; D013223:Statistics as Topic; D015431:Weight Loss