About: Life Trajectories, Biomedical Evidence, and Lessons for Policies

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Life Trajectories, Biomedical Evidence, and Lessons for Policies
Creator	Aaronson, William Bergman, Margo Olsen, Larry Vineis, Paolo
topic	covid:72ae56231629749d9cb7342aa51021f7d8d1ff22#this
Source	Medline; PMC
abstract	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 aging, 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 aging. 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 aging 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 labor 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.
has issue date	2020-05-12(xsd:dateTime)
bibo:doi	10.3389/fpubh.2020.00160
bibo:pmid	32478028
has license	cc-by
sha1sum (hex)	72ae56231629749d9cb7342aa51021f7d8d1ff22
schema:url	https://doi.org/10.3389/fpubh.2020.00160
resource representing a document's title	Life Trajectories, Biomedical Evidence, and Lessons for Policies
has PubMed Central identifier	PMC7235276
has PubMed identifier	32478028
schema:publication	Front Public Health
resource representing a document's body	covid:72ae56231629749d9cb7342aa51021f7d8d1ff22#body_text
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