Davillas Apostolos, Jones Andrew M
Office of Health Economics (OHE), London, United Kingdom; Institute for Social and Economic Research, University of Essex, United Kingdom.
Department of Economics and Related Studies, University of York, United Kingdom; Centre for Health Economics, Monash University, Australia.
J Health Econ. 2020 Jan;69:102251. doi: 10.1016/j.jhealeco.2019.102251. Epub 2019 Dec 23.
We use a set of biomarkers to measure inequality of opportunity (IOp) in the risk of major chronic conditions in the UK. Applying a direct ex ante IOp approach, we find that inequalities in biomarkers attributed to circumstances account for a non-trivial part of the total variation. For example, observed circumstances account for 20 % of the total inequalities in our composite measure of multi-system health risk, allostatic load. We propose an extension to the decomposition of ex ante IOp to complement the mean-based approach, analysing the contribution of circumstances across the quantiles of the biomarker distributions. Shapley decompositions show that, for most of the biomarkers, the percentage contribution of socioeconomic circumstances (education and childhood socioeconomic status), relative to differences attributable to age and gender, increase towards the right tail of the biomarker distribution, where health risks are more pronounced.
我们使用一组生物标志物来衡量英国主要慢性病风险中的机会不平等（IOp）。应用一种直接的事前IOp方法，我们发现归因于环境因素的生物标志物不平等在总变异中占相当大的比例。例如，在我们的多系统健康风险综合指标——应激负荷中，观察到的环境因素占总不平等的20%。我们提出对事前IOp分解进行扩展，以补充基于均值的方法，分析环境因素在生物标志物分布分位数上的贡献。夏普利分解表明，对于大多数生物标志物而言，相对于年龄和性别导致的差异，社会经济环境因素（教育程度和童年社会经济地位）的贡献百分比朝着生物标志物分布的右尾增加，在右尾处健康风险更为明显。
