Pilehvari Asal, You Wen, Lin Xu
Department of Public Health Sciences, University of Virginia, Charlottesville, USA.
Department of Economics, Virginia Tech, Blacksburg, USA.
Eur J Ageing. 2023 May 10;20(1):14. doi: 10.1007/s10433-023-00759-w.
While a large body of literature investigates the bidirectional relationship between retirement and health, few have analyzed the mechanism through which retirement affects health which will provide important policy instrument insights. Using three waves of National Social Life, Health, and Aging Project, we examine the mediating role of the social network in the relationship between retirement and health in USA. We address the endogeneity and reverse causality through panel instrumental fixed-effect methods. We apply both single and parallel mediation analyses to identify the potential mechanism by which social network characteristics mediate the impact of retirement on health. Findings reveal that retirement adversely affects physical and mental health outcomes, and a considerable portion of these effects are explained by social network changes post-retirement. Specifically, 58% of reduction in the probability of reporting good physical health and 4.5% of increment in chances of having depression symptoms post-retirement can be explained by shrinkage in the size of social network in retirees. Using parallel mediation identification to account for dependencies among social network features, we find that social network size induces 79.5% reduction in probability of reporting good physical health and 18.6% increase in probability of having depression in retirees as compared to non-retirees. Findings in this paper suggest that investing in social network of the elderly can buffer the adverse health effect of retirement and can be an effective policy target for promoting healthy aging.
虽然大量文献研究了退休与健康之间的双向关系,但很少有人分析退休影响健康的机制,而这将提供重要的政策工具见解。利用三轮全国社会生活、健康与老龄化项目,我们研究了社交网络在美国退休与健康关系中的中介作用。我们通过面板工具固定效应方法解决内生性和反向因果关系问题。我们应用单中介和并行中介分析来确定社交网络特征介导退休对健康影响的潜在机制。研究结果表明,退休对身心健康结果有不利影响,而这些影响中有相当一部分可以由退休后社交网络的变化来解释。具体而言,退休人员报告身体健康良好的概率降低58%以及出现抑郁症状几率增加4.5%可以由退休人员社交网络规模的缩小来解释。使用并行中介识别来考虑社交网络特征之间的依赖性,我们发现与未退休人员相比,社交网络规模使退休人员报告身体健康良好的概率降低79.5%,出现抑郁的概率增加18.6%。本文的研究结果表明,投资老年人的社交网络可以缓冲退休对健康的不利影响,并且可以成为促进健康老龄化的有效政策目标。