Eide G E, Heuch I
Centre for Clinical Research, Haukeland Hospital, and Section for Medical Statistics, University of Bergen, Norway.
Stat Methods Med Res. 2001 Jun;10(3):159-93. doi: 10.1177/096228020101000302.
A general methodology for visualizing attributable fractions in epidemiology is described. The methodology applies to the multifactorial exposure situation and embraces various types of attributable fractions including adjusted, sequential and average attributable fractions. The concept of the scaled Venn diagram plays a central role, illustrating total disease risk and excess disease risk attributable to the exposures as areas in a unit square. This forms the ground for making simple pie charts of attributable fractions summing to 1 (or 100%). The potential applications extend from cohort and cross-sectional data to data from case-control studies. The methodology is illustrated by theoretical as well as empirical examples including the risk of motor fatalities attributable to driver's blood alcohol concentration and age, and the prevalence of chronic cough attributable to smoking habits, occupational exposure to dust or gas, and residence. A total of 40 figures illustrate the methodology.
本文描述了一种在流行病学中可视化归因分数的通用方法。该方法适用于多因素暴露情况，涵盖各种类型的归因分数，包括调整后的、序贯的和平均归因分数。缩放维恩图的概念起着核心作用，它将归因于暴露的总疾病风险和额外疾病风险表示为单位正方形中的面积。这为制作总和为1（或100%）的归因分数简单饼图奠定了基础。其潜在应用范围从队列数据和横断面数据扩展到病例对照研究的数据。通过理论和实证示例对该方法进行了说明，包括驾驶员血液酒精浓度和年龄导致的机动车死亡风险，以及吸烟习惯、职业性接触粉尘或气体和居住环境导致的慢性咳嗽患病率。共有40个图说明了该方法。
