Confounding

Objectives

• To define and discuss confounding

• To discuss methods of diagnosing confounding

• To define positive, negative and qualitative confounding

• To diagnose some data for confounding

Definition of Confounding

• A non-causal association between a given exposure and an outcome is observed as a result of the influence of a third variable (or group of variables) designated as confounding variable(s).

Rules of Confounding

• The confounding variable is:– Causally associated with the outcome– Non-causally or causally associated with

the exposure– Not an intermediate variable in the causal

pathway between exposure and outcome

Example• The association of alcohol related cirrhosis and TB

mortality• Which are predictors and confounders?

– Age– Race– Gender– SES– Homelessness– Nutrition– HIV status– Access to care– Resistant strain of TB– Adherence to TB medication

Predictor, Confounder or Outcome

• Cell phone, auto accident, young age• Vitamin A, diarrhea, childhood mortality• Hepatitis C, alcohol, mortality• Age, oral birth control, breast cancer

incidence• SES, race, cancer mortality• Gender, SES, heart attack attributable

mortality

Different strategies to assess confounding

• Examine crude and adjusted estimates of the association

• Stratification

Types of

• Positive – overestimation of the true strength of association

• Negative – underestimation of the true strength of association

• Qualitative – inverse in the direction of the association