Revisiting the Population Attributable Fraction

The population attributable fraction corresponds to the reduction of the outcome had individuals (counter-to-fact) not experienced the exposure scaled by the observed incidence. Estimators proposed by Levin and Miettinen implicitly assume the study population is a random sample of the target population, which is not always the case.

In our example, we estimate the reduction in AIDS or death among women diagnosed with HIV in the United States in 2008, had they not had a history of injection drug use. To transport risk estimates from 1164 women in the Women's Interagency HIV Study to the 11,282 women diagnosed with HIV in the United States in 2008, we use the inverse probability of treatment and the inverse odds of sampling weighting. We estimate the variance of the population attributable fraction with a nonparametric bootstrap and M-estimation using the sandwich variance estimator.

The population attributable fraction estimated in the observed sample was 0.21 (95% confidence interval: 0.13, 0.29). After transporting the population attributable fraction to the target population, it was 0.13 (95% confidence interval: 0.065, 0.19).

Defining the target population and identification conditions allows for a clearer interpretation of the population attributable fraction.