Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill; Carolina Population Center, University of North Carolina, Chapel Hill; Social and Scientific Systems, Inc., Durham, NC.
Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill; Carolina Population Center, University of North Carolina, Chapel Hill.
Ann Epidemiol. 2019 Jan;29:1-7. doi: 10.1016/j.annepidem.2018.09.007. Epub 2018 Sep 29.
Identifying the exposures or interventions that exacerbate or ameliorate racial health disparities is one of the fundamental goals of social epidemiology. Introducing an interaction term between race and an exposure into a statistical model is commonly used in the epidemiologic literature to assess racial health disparities and the potential viability of a targeted health intervention. However, researchers may attribute too much authority to the interaction term and inadvertently ignore other salient information regarding the health disparity. In this article, we highlight empirical examples from the literature demonstrating limitations of overreliance on interaction terms in health disparities research; we further suggest approaches for moving beyond interaction terms when assessing these disparities. We promote a comprehensive framework of three guiding questions for disparity investigation, suggesting examination of the group-specific differences in (1) outcome prevalence, (2) exposure prevalence, and (3) effect size. Our framework allows for better assessment of meaningful differences in population health and the resulting implications for interventions, demonstrating that interaction terms alone do not provide sufficient means for determining how disparities arise. The widespread adoption of this more comprehensive approach has the potential to dramatically enhance understanding of the patterning of health and disease and the drivers of health disparities.
确定加剧或改善种族健康差异的暴露或干预措施是社会流行病学的基本目标之一。在流行病学文献中,引入种族与暴露之间的交互项通常用于评估种族健康差异和针对性健康干预的潜在可行性。然而,研究人员可能会过分信任交互项,并无意中忽略了有关健康差异的其他重要信息。在本文中,我们从文献中强调了一些实证例子,这些例子表明在健康差异研究中过度依赖交互项存在局限性;我们进一步提出了在评估这些差异时超越交互项的方法。我们提出了一个用于差异研究的三个指导问题的综合框架,建议检查(1)结局发生率、(2)暴露发生率和(3)效应大小方面的群体特异性差异。我们的框架允许更好地评估人群健康方面的有意义差异以及对干预措施的影响,表明仅交互项并不能提供确定差异产生方式的充分手段。这种更全面方法的广泛采用有可能极大地增强对健康和疾病模式以及健康差异驱动因素的理解。