Department of Epidemiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Japan.
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA.
Epidemiology. 2024 Jul 1;35(4):469-472. doi: 10.1097/EDE.0000000000001731. Epub 2024 Apr 12.
One of the common errors in the calculation of the population attributable fraction (PAF) is the use of an adjusted risk ratio in the Levin formula. In this article, we discuss the errors visually using wireframes by varying the standardized mortality ratio (SMR) and associational risk ratio (aRR) when the prevalence of exposure is fixed. When SMR >1 and SMR > aRR, the absolute bias is positive, and its magnitude increases as the difference between SMR and aRR increases. By contrast, when aRR > SMR > 1, the absolute bias is negative and its magnitude is relatively small. Moreover, when SMR > aRR, the relative bias is larger than one, whereas when SMR < aRR, the relative bias is smaller than one. Although the target population of the PAF is the total population, the target of causation of the PAF is not the total population but the exposed group.
人群归因分数（PAF）计算中的一个常见错误是在 Levin 公式中使用调整后的风险比。在本文中，我们通过改变固定暴露率时的标准化死亡率比（SMR）和关联风险比（aRR），使用线框图直观地讨论了这些错误。当 SMR>1 且 SMR>aRR 时，绝对偏差为正，且随着 SMR 与 aRR 之间的差异增大而增大。相比之下，当 aRR>SMR>1 时，绝对偏差为负，且幅度相对较小。此外，当 SMR>aRR 时，相对偏差大于 1，而当 SMR<aRR 时，相对偏差小于 1。尽管 PAF 的目标人群是总人口，但 PAF 的因果目标不是总人口，而是暴露人群。
