Joseph J. Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin.
Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, Pennsylvania.
Am J Epidemiol. 2018 Jul 1;187(7):1424-1437. doi: 10.1093/aje/kwx363.
Risk factors can drive socioeconomic inequalities in cardiovascular disease (CVD) through differential exposure and differential vulnerability. In this paper, we show how econometric decomposition directly enables simultaneous, policy-oriented assessment of these 2 mechanisms. We specifically estimate contributions of neighborhood environment and proximal risk factors to socioeconomic inequality in CVD incidence via these mechanisms. We followed 5,608 participants in the Multi-Ethnic Study of Atherosclerosis (2000-2012) to their first CVD event (median length of follow-up, 12.2 years). We used a summary measure of baseline socioeconomic position (SEP). Covariates included baseline demographics, neighborhood characteristics, and psychosocial, behavioral, and biomedical risk factors. Using Poisson models, we decomposed the difference (inequality) in incidence rates between low- and high-SEP groups into contributions of 1) differences in covariate means (differential exposure) and 2) differences in CVD risk associated with covariates (differential vulnerability). Notwithstanding large uncertainty in neighborhood estimates, our analysis suggested that differential exposure to poorer neighborhood socioeconomic conditions, adverse social environment, diabetes, and hypertension accounted for most of the inequality. Psychosocial and behavioral contributions were negligible. Further, neighborhood SEP, female sex, and white race were more strongly associated with CVD among low-SEP (vs. high-SEP) participants. These differentials in vulnerability also accounted for nontrivial portions of the inequality and could have important implications for intervention.
风险因素可通过不同的暴露和脆弱性导致心血管疾病(CVD)的社会经济不平等。本文展示了如何通过计量经济学分解直接同时评估这两种机制。我们通过这些机制,具体估计了邻里环境和近端风险因素对 CVD 发病率的社会经济不平等的贡献。我们对动脉粥样硬化多民族研究(2000-2012 年)中的 5608 名参与者进行随访,直至他们首次发生 CVD 事件(中位随访时间为 12.2 年)。我们使用基线社会经济地位(SEP)的综合衡量标准。协变量包括基线人口统计学特征、邻里特征以及心理社会、行为和生物医学风险因素。我们使用泊松模型将低和高 SEP 组之间的发病率差异(不平等)分解为以下因素的贡献:1)协变量均值差异(差异暴露)和 2)与协变量相关的 CVD 风险差异(差异脆弱性)。尽管邻里环境估计存在很大的不确定性,但我们的分析表明,对较差的邻里社会经济条件、不利的社会环境、糖尿病和高血压的差异暴露解释了大部分不平等。心理社会和行为因素的贡献可以忽略不计。此外,在低 SEP(与高 SEP 相比)参与者中,邻里 SEP、女性和白种人种族与 CVD 的相关性更强。脆弱性的这些差异也导致了不平等的相当大的部分,这可能对干预具有重要意义。