Collider Bias Is Only a Partial Explanation for the Obesity Paradox

Epidemiology. 2016 Jul;27(4):525-30. doi: 10.1097/EDE.0000000000000493.


Background: "Obesity paradox" refers to an association between obesity and reduced mortality (contrary to an expected increased mortality). A common explanation is collider stratification bias: unmeasured confounding induced by selection bias. Here, we test this supposition through a realistic generative model.

Methods: We quantify the collider stratification bias in a selected population using counterfactual causal analysis. We illustrate the bias for a range of scenarios, describing associations between exposure (obesity), outcome (mortality), mediator (in this example, diabetes) and an unmeasured confounder.

Results: Collider stratification leads to biased estimation of the causal effect of exposure on outcome. However, the bias is small relative to the causal relationships between the variables.

Conclusions: Collider bias can be a partial explanation of the obesity paradox, but unlikely to be the main explanation for a reverse direction of an association to a true causal relationship. Alternative explanations of the obesity paradox should be explored. See Video Abstract at

MeSH terms

  • Bias
  • Confounding Factors, Epidemiologic*
  • Humans
  • Logistic Models
  • Mortality*
  • Obesity / epidemiology*