populationsattributabel

Populationsattributabel, typically referred to in epidemiology as the population attributable fraction (PAF) or population attributable risk, is a measure of how much of a disease burden in a population can be attributed to a specific exposure. It expresses the proportion or percentage of cases that could be prevented if the exposure were eliminated, assuming a causal relationship between exposure and disease.

The most common formulation uses the exposure prevalence in the population and the relative risk associated with the exposure. If Pe is the proportion of the population exposed and RR is the relative risk of the disease for the exposed versus the unexposed, the population attributable fraction is PAF = Pe × (RR − 1) / [Pe × (RR − 1) + 1]. An equivalent formulation uses incidence in the population: PAF = (It − Iu) / It, where It is the incidence in the total population and Iu is the incidence among the unexposed. For case-control studies where only odds ratios are available and the disease is rare, PAF can be approximated by PAF ≈ Pe × (OR − 1) / [Pe × (OR − 1) + 1].

Interpretation focuses on public health impact: a higher PAF indicates a larger portion of cases in the population could be prevented by removing or modifying the exposure, given causal assumptions. Example: with Pe = 0.3 and RR = 2, PAF ≈ 0.23, meaning about 23% of cases could be attributable to the exposure if eliminable.

Limitations include reliance on causality, sensitivity to exposure prevalence and misclassification, and the potential for multiple risk factors to interact in ways that complicate summing across exposures. PAFs are useful for prioritizing interventions and informing policy decisions.