title: Biased Exposure-Health Effect Estimates from Selection in Cohort Studies: Are Environmental Studies at Particular Risk?
abstract: BACKGROUND
  The process of creating a cohort or cohort substudy may induce misleading exposure-health effect associations through collider stratification bias (i.e., selection bias) or bias due to conditioning on an intermediate. Studies of environmental risk factors may be at particular risk.
  
  
  OBJECTIVE
  We aimed to demonstrate how such biases of the exposure-health effect association arise and how one may mitigate them.
  
  
  METHODS
  We used directed acyclic graphs and the example of bone lead and mortality (all-cause, cardiovascular, and ischemic heart disease) among 835 white men in the Normative Aging Study (NAS) to illustrate potential bias related to recruitment into the NAS and the bone lead substudy. We then applied methods (adjustment, restriction, and inverse probability of attrition weighting) to mitigate these biases in analyses using Cox proportional hazards models to estimate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs).
  
  
  RESULTS
  Analyses adjusted for age at bone lead measurement, smoking, and education among all men found HRs (95% CI) for the highest versus lowest tertile of patella lead of 1.34 (0.90, 2.00), 1.46 (0.86, 2.48), and 2.01 (0.86, 4.68) for all-cause, cardiovascular, and ischemic heart disease mortality, respectively. After applying methods to mitigate the biases, the HR (95% CI) among the 637 men analyzed were 1.86 (1.12, 3.09), 2.47 (1.23, 4.96), and 5.20 (1.61, 16.8), respectively.
  
  
  CONCLUSIONS
  Careful attention to the underlying structure of the observed data is critical to identifying potential biases and methods to mitigate them. Understanding factors that influence initial study participation and study loss to follow-up is critical. Recruitment of population-based samples and enrolling participants at a younger age, before the potential onset of exposure-related health effects, can help reduce these potential pitfalls.
  
  
  BACKGROUND
  Weisskopf MG, Sparrow D, Hu H, Power MC. 2015. Biased exposure-health effect estimates from selection in cohort studies: are environmental studies at particular risk? Environ Health Perspect 123:1113-1122; http://dx.doi.org/10.1289/ehp.1408888.
authors.affiliation: Department of Epidemiology and Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
authors.forename: Marc G
authors.initials: MG
authors.lastname: Weisskopf
authors.forename: David
authors.initials: D
authors.lastname: Sparrow
authors.forename: Howard
authors.initials: H
authors.lastname: Hu
authors.forename: Melinda C
authors.initials: MC
authors.lastname: Power
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D015982:Bias; D001842:Bone and Bones / Q000737:chemistry*; D002318:Cardiovascular Diseases / Q000401:mortality; D015331:Cohort Studies; D004781:Environmental Exposure; D006801:Humans; D007854:Lead / Q000032:analysis*; D008297:Male; D009026:Mortality; D016016:Proportional Hazards Models
chemical_list: D007854:Lead