Klose Mark, Zivich Paul N, Cole Stephen R
From the Department of Epidemiology, Gillings School of Global Public Health, UNC Chapel Hill, Chapel Hill, NC.
Institute of Global Health and Infectious Diseases, UNC Chapel Hill, Chapel Hill, NC.
Epidemiology. 2025 Jul 1;36(4):482-486. doi: 10.1097/EDE.0000000000001867. Epub 2025 Apr 1.
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.
人群归因分数对应于若个体（反事实情况）未经历暴露时结局的降低幅度，该降低幅度以观察到的发病率进行衡量。莱文和米耶蒂宁提出的估计方法隐含地假设研究人群是目标人群的随机样本，但实际情况并非总是如此。
在我们的示例中，我们估计了2008年在美国被诊断为感染艾滋病毒的女性中，若她们没有注射吸毒史，艾滋病或死亡情况的减少幅度。为了将风险估计从女性机构间艾滋病毒研究中的1164名女性应用到2008年在美国被诊断为感染艾滋病毒的11282名女性中，我们使用治疗的逆概率和抽样权重的逆概率。我们使用非参数自助法和使用三明治方差估计器的M估计来估计人群归因分数的方差。
在观察到的样本中估计的人群归因分数为0.21（95%置信区间：0.13，0.29）。将人群归因分数应用到目标人群后，其为0.13（95%置信区间：0.065，0.19）。
定义目标人群和识别条件有助于更清晰地解释人群归因分数。
