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Estimating attributable fraction in partially ecologic case-control studies.

Författare

Summary, in English

Partially ecologic case-control studies combine group-level exposure data with individual-level data on disease status, group membership, and covariates. If the exposure measure is the exposure prevalence of various groups, the attributable fraction (AF; the estimated proportion of cases that are attributable to exposure) can be estimated by classifying all subjects in groups with exposure prevalence above zero as exposed. Such a threshold AF estimator ([AF]T) is unbiased in confounding-free situations if the threshold is 100% sensitive, but it might be imprecise. We propose an alternative AF estimator, [AF]L, for partially ecologic case-control studies under a linear model for the association between the exposure prevalence and the odds ratio. The proposed estimator can also be applied to situations in which covariate adjustment is necessary. [AF]T and [AF]L are compared with respect to precision and bias. [AF]L is also unbiased when the exposure prevalence is zero in the group(s) assessed as unexposed. Using [AF]L will consistently result in improved precision compared with [AF]T, although the results may not differ substantially. The 95% confidence intervals for both AF estimators show satisfactory coverage in bias-free exposure scenarios. Pronounced negative bias and decreased coverage result for both AF estimators even when small fractions (3-9%) of exposed subjects are included in the group assessed as unexposed.

Publiceringsår

2002

Språk

Engelska

Sidor

459-466

Publikation/Tidskrift/Serie

Epidemiology

Volym

13

Issue

4

Dokumenttyp

Artikel i tidskrift

Förlag

Wolters Kluwer

Ämne

  • Public Health, Global Health, Social Medicine and Epidemiology

Nyckelord

  • Bias (Epidemiology)
  • Case-Control Studies
  • Epidemiologic Methods
  • Occupational Exposure
  • Linear Models
  • Human
  • Odds Ratio
  • Sensitivity and Specificity

Status

Published

ISBN/ISSN/Övrigt

  • ISSN: 1531-5487