Institute for Hospital Management, School of Medicine, Tsinghua University, Beijing, China.
Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
Eur J Epidemiol. 2023 Jul;38(7):717-728. doi: 10.1007/s10654-023-01018-z. Epub 2023 Jun 6.
Population attributable risk (PAR%) reflects the preventable fraction of disease. However, PAR% estimates of cancer have shown large variation across populations, methods, data sources, and timing of measurements. Three statistical methods to estimate PAR% were identified from a systematic literature review: the Levin's formula, the comparative incidence rate method, and the comparative risk assessment method. We compared the variations in PAR% of postmenopausal breast cancer in the Nurses' Health Study to evaluate the influence by method choice, source of prevalence data, use of single vs repeated exposure measurements, and potential joint effects of obesity, alcohol, physical activity, fruit and vegetable intake. Across models of the three methods, the estimated PAR% using repeated measurements were higher than that using baseline measurement; overall PAR% for the baseline, simple update, and cumulative average models were 13.8%, 21.1%, 18.6% by Levin's formula; 13.7%, 28.0%, 31.2% by comparative risk assessment; and 17.4%, 25.2%, 29.3% by comparative incidence rate method. The estimated PAR% of the combination of multiple risk factors was higher than the product of the individual PAR%: 18.9% when assuming independence and 31.2% when considering the risk factors jointly. The three methods provided similar PAR% based on the same data source, timing of measurements, and target populations. However, sizable increases in the PAR% were observed for repeated measures over a single measure and for calculations based on achieving all recommendations jointly rather than individually.
人群归因风险（PAR%）反映了疾病的可预防部分。然而，癌症的 PAR%估计值在人群、方法、数据来源和测量时间上存在很大差异。从系统文献综述中确定了三种估计 PAR%的统计方法：莱文公式、比较发病率方法和比较风险评估方法。我们比较了护士健康研究中绝经后乳腺癌的 PAR%变化，以评估方法选择、患病率数据来源、使用单次或重复暴露测量以及肥胖、酒精、身体活动、水果和蔬菜摄入的潜在联合效应的影响。在三种方法的模型中，使用重复测量估计的 PAR%高于使用基线测量的 PAR%；莱文公式的基线、简单更新和累积平均模型的总体 PAR%分别为 13.8%、21.1%和 18.6%；比较风险评估的 PAR%分别为 13.7%、28.0%和 31.2%；比较发病率方法的 PAR%分别为 17.4%、25.2%和 29.3%。多个危险因素组合的估计 PAR%高于单个危险因素的乘积：假设独立性时为 18.9%，考虑危险因素联合时为 31.2%。基于相同的数据来源、测量时间和目标人群，三种方法提供了相似的 PAR%。然而，对于重复测量相对于单次测量以及基于联合实现所有建议而不是单独实现的计算，PAR%会显著增加。
