Centre de Sciences Humaines (CSH, UMIFRE n°20), a Network of Research Units of the National Centre for Scientific Research (CNRS) and the French Ministry of European and Foreign Affairs, New Delhi 110011, India.
Department of Public Health, Yerevan State Medical University, Yerevan 0025, Armenia.
Int J Environ Res Public Health. 2021 Oct 23;18(21):11153. doi: 10.3390/ijerph182111153.
Self-assessed health (SAH) is a widely used tool to estimate population health. However, the debate continues as to what exactly this ubiquitous measure of social science research means for policy conclusions. This study is aimed at understanding the tenability of the construct of SAH by simultaneously modelling SAH and clinical morbidity. Using data from 17 waves (2001-2017) of the Russian Longitudinal Monitoring Survey, which captures repeated response for SAH and frequently updates information on clinical morbidity, we operationalise a recursive semi-ordered probit model. Our approach allows for the estimation of the distributional effect of clinical morbidity on perceived health. This study establishes the superiority of inferences from the recursive model. We illustrated the model use for examining the endogeneity problem of perceived health for SAH, contributing to population health research and public policy development, in particular, towards the organisation of health systems.
自评健康（SAH）是一种广泛用于评估人口健康的工具。然而，对于这一在社会科学研究中无处不在的衡量标准对政策结论意味着什么，人们仍存在争议。本研究旨在通过同时构建 SAH 和临床发病模型来理解 SAH 的构建的可行性。我们使用了俄罗斯纵向监测调查（Russian Longitudinal Monitoring Survey）的 17 个波次（2001-2017 年）的数据，该调查捕获了 SAH 的重复响应，并经常更新临床发病的信息，我们采用了递归半有序概率模型。我们的方法允许对临床发病对感知健康的分布效应进行估计。本研究确立了递归模型推论的优越性。我们展示了该模型在检验 SAH 的感知健康的内生性问题方面的应用，这有助于人口健康研究和公共政策的制定，特别是在卫生系统的组织方面。
