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Invited Commentary: Can Changes in the Distributions of and Associations Between Education and Income Bias Estimates of Temporal Trends in Health Disparities?

机译:邀请评论:教育和收入偏差的分布和关联是否可以估计健康差异的时间趋势?

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摘要

Chen et al (Am J Epidemiol 2012; xx:xxx—xxx) develop a simulation study for comparing various measures of socioeconomic health disparities when bias can arise from temporal changes in the bivariate distribution of education and income. In this commentary, I argue that, in relation to health, the “meaning” of education cannot be reduced to its socioeconomic value; improved health literacy, for instance, can result in important health benefits. Further, I suggest that unless there is a substantial prior understanding of the data generating mechanism, directed acyclic graph models should be avoided because causal relationships cannot be inferred from regression. An alternative is to resort to conditional independence graphs, which use only undirected edges. Finally, although the slope index of inequality (SII) can, in some specific cases, be seen to reduce bias in temporal comparisons of socioeconomic health disparities, it was not designed for causal inference. The SII simply describes the average change in the proportion in poor health when the population is ordered by socioeconomic status.
机译:Chen等人(Am J Epidemiol 2012; xx:xxx-xxx)开展了一项模拟研究,用于比较当教育和收入的二元分布的时间变化可能引起偏差时,对社会经济健康差异的各种衡量指标。在这篇评论中,我认为,就健康而言,教育的“含义”不能降低到其社会经济价值。例如,提高健康素养可以带来重要的健康益处。此外,我建议除非对数据生成机制有足够的先验了解,否则应避免使用有向无环图模型,因为无法从回归中推断出因果关系。一种替代方法是求助于条件独立图,该图仅使用无向边。最后,尽管在某些特定情况下,不平等的斜率指数(SII)可以减少社会经济健康差异的时间比较中的偏差,但它并非设计用于因果推理。 SII简单描述了按社会经济地位对人口进行排序时健康状况不佳的比例的平均变化。

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