Steenland Kyle, Armstrong Ben
Rollins School of Public Health, Emory University, 1518 Clifton Road, Atlanta, GA 30322, USA.
Epidemiology. 2006 Sep;17(5):512-9. doi: 10.1097/01.ede.0000229155.05644.43.
There are a number of measures that quantify the public health burden due to specific risk factors for specific diseases. Although these measures are of importance for policymakers, epidemiologists do not often calculate them or may be unfamiliar with some of the issues involved when they do. The primary measure of interest is the attributable fraction (AF), representing the fraction of cases or deaths from a specific disease that would not have occurred in the absence of exposure to a specific risk factor either in the exposed population or the population as a whole. AFs can be multiplied by the total number of cases of a given disease to obtain a "body count"--the absolute number of preventable cases due to a specific risk factor. Two other measures of public health burden, used in conjunction with AFs, are attributable years-of-life-lost and attributable disability-adjusted life-years. We provide an overview of the AF and related measures and discuss some of the specific issues involved in calculating AFs. These issues include calculating the variance of AFs (such as Monte Carlo sensitivity methods), biases arising from some formulas for the AF, sources of data for calculating AFs, dependence of AFs on basic decisions about what exposure-disease associations are causal, and extrapolation from the source population to the target population.
有许多措施可量化特定疾病的特定风险因素所导致的公共卫生负担。尽管这些措施对政策制定者很重要，但流行病学家并不经常计算它们，或者在计算时可能不熟悉其中涉及的一些问题。主要关注的指标是归因分数（AF），它表示在没有接触特定风险因素的情况下，特定疾病在暴露人群或整个人口中不会发生的病例或死亡比例。归因分数可以乘以特定疾病的病例总数，以得出“具体数字”——即特定风险因素导致的可预防病例的绝对数量。与归因分数一起使用的另外两个公共卫生负担指标是归因寿命损失年数和归因伤残调整生命年数。我们概述了归因分数及相关指标，并讨论了计算归因分数时涉及的一些具体问题。这些问题包括计算归因分数的方差（如蒙特卡洛敏感性方法）、归因分数某些公式产生的偏差、计算归因分数的数据来源、归因分数对关于哪些暴露-疾病关联具有因果关系的基本决策的依赖性，以及从源人群到目标人群的外推。
