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Life Trajectories, Biomedical Evidence, and Lessons for Policies

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 individua...

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Autor principal: Vineis, Paolo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7235276/
https://www.ncbi.nlm.nih.gov/pubmed/32478028
http://dx.doi.org/10.3389/fpubh.2020.00160
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author Vineis, Paolo
author_facet Vineis, Paolo
author_sort Vineis, Paolo
collection PubMed
description 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.
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spelling pubmed-72352762020-05-29 Life Trajectories, Biomedical Evidence, and Lessons for Policies Vineis, Paolo Front Public Health Public Health 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. Frontiers Media S.A. 2020-05-12 /pmc/articles/PMC7235276/ /pubmed/32478028 http://dx.doi.org/10.3389/fpubh.2020.00160 Text en Copyright © 2020 Vineis. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Vineis, Paolo
Life Trajectories, Biomedical Evidence, and Lessons for Policies
title Life Trajectories, Biomedical Evidence, and Lessons for Policies
title_full Life Trajectories, Biomedical Evidence, and Lessons for Policies
title_fullStr Life Trajectories, Biomedical Evidence, and Lessons for Policies
title_full_unstemmed Life Trajectories, Biomedical Evidence, and Lessons for Policies
title_short Life Trajectories, Biomedical Evidence, and Lessons for Policies
title_sort life trajectories, biomedical evidence, and lessons for policies
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7235276/
https://www.ncbi.nlm.nih.gov/pubmed/32478028
http://dx.doi.org/10.3389/fpubh.2020.00160
work_keys_str_mv AT vineispaolo lifetrajectoriesbiomedicalevidenceandlessonsforpolicies