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Revisiting the Population Attributable Fraction.

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This summary is machine-generated.

This study adjusted population attributable fraction estimates for HIV-positive women in the US. It found that removing injection drug use history could reduce AIDS or death rates by 13% in the target population.

Keywords:
Epidemiologic methodsPopulation attributable fractionRandom errorVariance

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Public Health

Background:

  • Population attributable fraction (PAF) quantifies outcome reduction if exposure is removed.
  • Traditional PAF estimators assume random sampling, which may not hold.
  • This study addresses PAF estimation in target populations distinct from the study sample.

Purpose of the Study:

  • To estimate the reduction in AIDS or death among US women diagnosed with HIV in 2008, had they not had a history of injection drug use.
  • To transport risk estimates from a specific study sample to a broader target population.
  • To refine PAF interpretation by clearly defining target populations and identification conditions.

Main Methods:

  • Utilized inverse probability of treatment and inverse odds of sampling weighting to transport risk estimates.
  • Applied methods to data from the Women's Interagency HIV Study to a national HIV-diagnosed population.
  • Estimated PAF variance using nonparametric bootstrap and M-estimation with sandwich variance estimator.

Main Results:

  • The PAF estimated in the observed sample was 0.21 (95% CI: 0.13, 0.29).
  • After transporting to the target population, the PAF was estimated at 0.13 (95% CI: 0.065, 0.19).

Conclusions:

  • Clear definition of the target population is crucial for accurate PAF interpretation.
  • Methodology allows for valid risk estimation in target populations beyond the initial study sample.
  • Findings highlight the impact of injection drug use history on HIV outcomes.