Socioeconomic status and health in blacks and whites: The problem of residual confounding and the resiliency of race
Socioeconomic status and health in blacks and whites: The problem of residual confounding and the resiliency of race
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DOI：
10.1097/00001648-199710000-00002
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发表时间：
1997-11-01
期刊：
影响因子：
5.4
通讯作者：
McGee, DL
中科院分区：
文献类型：
--
作者：
Kaufman, JS;Cooper, RS;McGee, DL
大量的流行病学研究集中在种族/民族差异，特别是黑人和白人之间。由于健康终点和种族分类与社会经济地位相关，研究人员通常会调整社会经济指标。其目的通常是为了控制混杂因素，从而使群体具有可比性，并排除社会经济地位作为先天生理差异假设的替代解释。因此，对这些分析有效性的威胁是残余混杂的存在。我们在这个分析设计中确定了四个潜在的残余混杂源：社会经济地位变量的分类，社会经济指标的测量误差，使用汇总的社会经济地位指标，以及不相称的社会经济指标。使用模拟和文献中的例子，我们证明了残余混杂的影响是对数据的解释偏向于独立的种族/民族群体效应的结论。研究人员经常在控制社会经济地位的模型的基础上提到可能的“遗传”差异。我们认为，根据这一分析战略得出的这种结论一般是没有根据的。疾病的种族/民族差异是一个紧迫的公共卫生问题，但目前的方法并不经常提供一个推断的基础上，这种差异的病因学推定的生物学因素。
A large number of epidemiologic studies have focused on racial/ethnic differences, particularly between blacks and whites. Because health endpoints and racial categorizations are associated with socioeconomic status, investigators generally adjust for socioeconomic indicators. The intention is usually to control for confounding, thereby making groups comparable and excluding socioeconomic status as an alternative explanation to hypotheses of innate physiologic differences. A threat to the validity of these analyses is therefore the presence of residual confounding. We identify four potential sources of residual confounding in this analytical design: categorization of socioeconomic status variables, measurement error in socioeconomic indicators, use of aggregated socioeconomic status measures, and incommensurate socioeconomic indicators. Using simulations and examples from the literature, we demonstrate that the effect of residual confounding is to bias interpretation of data toward the conclusion of independent racial/ethnic group effects.Investigators often refer to possible ''genetic'' differences on the basis of models that control for socioeconomic status. We propose that such conclusions on the basis of this analytical strategy are generally unwarranted. Racial/ethnic differences in disease are a pressing public health concern, but the current approach does not often provide a basis for inference about putative biological factors in the etiology of this disparity.