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Life Trajectories, Biomedical Evidence, and Lessons for Policies

机译:终身轨迹,生物医学证据和政策的课程

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Here I compare two types of evidence that have recently emerged from the literature. This Commentary is a contribution to the Frontiers Research Topic on social disparities in ageing, and aims to draw attention to the novel connections that link social disparities, the biological capital of individuals and policy strategies. The biological capital (as defined in the paper), accrued since conception by individuals, in turn affects their social, cultural and economic capitals, and thus creates a positive feedback loop. In a large network funded by the European Commission, Lifepath, we have shown that the determinants of health inequalities start in early life and cumulate throughout the life-course. For example, exposure to adverse childhood experiences (ACEs) influences the likelihood of later in life health effects, including poor ageing. In this paper I compare two types of evidence that have recently emerged from the literature. One addresses the role of early vs late exposures to risk factors for ageing and mortality, including ACEs, using e.g. microsimulation models. The second type of evidence, provided in a recent document of the WHO European Regional Office, is based on the analysis of five broad determinants of health inequalities and eight different macroeconomic policies to tackle such inequalities. Six of the policies, if enacted, have the potential to reduce inequalities in the short term by increasing public expenditure on housing and community amenities, increasing expenditure on labour market policies, reducing income inequality, increasing social protection expenditure, reducing unemployment, and/or reducing out-of-pocket payments for health. Both of these lines of evidence suggest that there are ample opportunities for policy interventions. I also discuss the need for analytical methods to bridge the two types of analyses (biomedical and macroeconomic), i.e. fill the gap between analyses based on individual determinants of health inequalities and those based on societal determinants, to help create more effective policy-making. Also, I propose that before launching large projects to reduce health inequalities, well-designed experiments must be conducted to test their efficacy. These experiments, though, are challenging when addressing social policies, in consideration of ethical constraints and timescales.
机译:在这里,我比较了来自文献中最近出现的两种类型的证据。这项评论是对衰老的社会差异的前沿研究课题的贡献,旨在提请注意联系社会差异,个人和政策战略的生物资本的新建议。自体概念的生物资本(如本文所定义),又影响了他们的社会,文化和经济资本,从而产生了积极的反馈循环。在由欧盟委员会资助的大型网络中,我们已经表明,健康不平等的决定因素在早期生命中开始并在整个生命课程中累积。例如,暴露于不利的儿童经历(ACE)影响后期生命健康影响的可能性,包括糟糕的老化。在本文中,我比较了最近从文献中出现的两种类型的证据。一个解决患者早期暴露于危险因素的危险因素,包括ACE,使用例如ACE的危险因素。微观模型。第二种类型的证据,在WHO欧洲区域办事处的最近文件中提供,是基于对卫生不平等的五种广泛决定因素和八种不同的宏观经济政策分析,以解决此类不平等。六项政策(如果颁布),如果通过增加公共房屋和社区设施,增加劳动力市场政策的支出,减少收入不平等,增加社会保护支出,减少失业率,减少失业率和/或减少社会保护支出,减少失业率,减少社会保护支出,减少失业率,减少失业和/或降低收入不平等的支出,有可能降低短期内不平等。减少健康的港口支付。这两种证据都表明,政策干预有充足的机会。我还讨论了对两种类型的分析方法(生物医学和宏观经济)的分析方法,即填补基于健康不平等的单个决定因素与基于社会决定因素的分析之间的差距,以帮助创造更有效的政策制定。此外,我建议在推出大型项目以减少健康不等式之前,必须进行精心设计的实验以测试它们的疗效。但是,考虑到道德限制和时间尺度,这些实验在解决社会政策时挑战。

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