Office of Epidemiology, Policy & Evaluation, Maternal and Child Health Bureau, Health Resources and Services Administration, Rockville, MD 20857, USA.
Ann Epidemiol. 2012 Oct;22(10):683-90. doi: 10.1016/j.annepidem.2012.06.105. Epub 2012 Aug 2.
A common epidemiologic objective is to evaluate the contribution of residential context to individual-level disparities by race or socioeconomic position.
We reviewed analytic strategies to account for the total (observed and unobserved factors) contribution of environmental context to health inequalities, including conventional fixed effects (FE) and hybrid FE implemented within a random effects (RE) or a marginal model.
To illustrate results and limitations of the various analytic approaches of accounting for the total contextual component of health disparities, we used data on births nested within neighborhoods as an applied example of evaluating neighborhood confounding of racial disparities in gestational age at birth, including both a continuous and a binary outcome.
Ordinary and RE models provided disparity estimates that can be substantially biased in the presence of neighborhood confounding. Both FE and hybrid FE models can account for cluster level confounding and provide disparity estimates unconfounded by neighborhood, with the latter having greater flexibility in allowing estimation of neighborhood-level effects and intercept/slope variability when implemented in a RE specification.
Given the range of models that can be implemented in a hybrid approach and the frequent goal of accounting for contextual confounding, this approach should be used more often.
一个常见的流行病学目标是通过种族或社会经济地位来评估居住环境对个体差异的贡献。
我们回顾了分析策略，以解释环境背景对健康不平等的总体（观察到的和未观察到的因素）贡献，包括传统的固定效应（FE）和混合 FE，它们在随机效应（RE）或边缘模型中实施。
为了说明各种分析方法在解释健康差异的总背景成分方面的结果和局限性，我们使用了嵌套在社区中的出生数据作为评估出生时胎龄种族差异的社区混杂的应用示例，包括连续和二分结果。
普通和 RE 模型提供的差异估计在存在社区混杂的情况下可能会有很大偏差。FE 和混合 FE 模型都可以解释簇级别的混杂，并提供不受社区混杂影响的差异估计，后者在 RE 规范中实施时具有更大的灵活性，可以估计社区层面的效果和截距/斜率变化。
鉴于可以在混合方法中实施的模型范围以及经常需要解释上下文混杂的目标，因此应该更频繁地使用这种方法。
