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Predicting mortality from 57 economic, behavioral, social, and psychological factors

Behavioral and social scientists have identified many nonbiological predictors of mortality. An important limitation of much of this research, however, is that risk factors are not studied in comparison with one another or from across different fields of research. It therefore remains unclear which...

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Autores principales: Puterman, Eli, Weiss, Jordan, Hives, Benjamin A., Gemmill, Alison, Karasek, Deborah, Mendes, Wendy Berry, Rehkopf, David H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7369318/
https://www.ncbi.nlm.nih.gov/pubmed/32571904
http://dx.doi.org/10.1073/pnas.1918455117
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author Puterman, Eli
Weiss, Jordan
Hives, Benjamin A.
Gemmill, Alison
Karasek, Deborah
Mendes, Wendy Berry
Rehkopf, David H.
author_facet Puterman, Eli
Weiss, Jordan
Hives, Benjamin A.
Gemmill, Alison
Karasek, Deborah
Mendes, Wendy Berry
Rehkopf, David H.
author_sort Puterman, Eli
collection PubMed
description Behavioral and social scientists have identified many nonbiological predictors of mortality. An important limitation of much of this research, however, is that risk factors are not studied in comparison with one another or from across different fields of research. It therefore remains unclear which factors should be prioritized for interventions and policy to reduce mortality risk. In the current investigation, we compare 57 factors within a multidisciplinary framework. These include (i) adverse socioeconomic and psychosocial experiences during childhood and (ii) socioeconomic conditions, (iii) health behaviors, (iv) social connections, (v) psychological characteristics, and (vi) adverse experiences during adulthood. The current prospective cohort investigation with 13,611 adults from 52 to 104 y of age (mean age 69.3 y) from the nationally representative Health and Retirement Study used weighted traditional (i.e., multivariate Cox regressions) and machine-learning (i.e., lasso, random forest analysis) statistical approaches to identify the leading predictors of mortality over 6 y of follow-up time. We demonstrate that, in addition to the well-established behavioral risk factors of smoking, alcohol abuse, and lack of physical activity, economic (e.g., recent financial difficulties, unemployment history), social (e.g., childhood adversity, divorce history), and psychological (e.g., negative affectivity) factors were also among the strongest predictors of mortality among older American adults. The strength of these predictors should be used to guide future transdisciplinary investigations and intervention studies across the fields of epidemiology, psychology, sociology, economics, and medicine to understand how changes in these factors alter individual mortality risk.
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spelling pubmed-73693182020-07-29 Predicting mortality from 57 economic, behavioral, social, and psychological factors Puterman, Eli Weiss, Jordan Hives, Benjamin A. Gemmill, Alison Karasek, Deborah Mendes, Wendy Berry Rehkopf, David H. Proc Natl Acad Sci U S A Social Sciences Behavioral and social scientists have identified many nonbiological predictors of mortality. An important limitation of much of this research, however, is that risk factors are not studied in comparison with one another or from across different fields of research. It therefore remains unclear which factors should be prioritized for interventions and policy to reduce mortality risk. In the current investigation, we compare 57 factors within a multidisciplinary framework. These include (i) adverse socioeconomic and psychosocial experiences during childhood and (ii) socioeconomic conditions, (iii) health behaviors, (iv) social connections, (v) psychological characteristics, and (vi) adverse experiences during adulthood. The current prospective cohort investigation with 13,611 adults from 52 to 104 y of age (mean age 69.3 y) from the nationally representative Health and Retirement Study used weighted traditional (i.e., multivariate Cox regressions) and machine-learning (i.e., lasso, random forest analysis) statistical approaches to identify the leading predictors of mortality over 6 y of follow-up time. We demonstrate that, in addition to the well-established behavioral risk factors of smoking, alcohol abuse, and lack of physical activity, economic (e.g., recent financial difficulties, unemployment history), social (e.g., childhood adversity, divorce history), and psychological (e.g., negative affectivity) factors were also among the strongest predictors of mortality among older American adults. The strength of these predictors should be used to guide future transdisciplinary investigations and intervention studies across the fields of epidemiology, psychology, sociology, economics, and medicine to understand how changes in these factors alter individual mortality risk. National Academy of Sciences 2020-07-14 2020-06-22 /pmc/articles/PMC7369318/ /pubmed/32571904 http://dx.doi.org/10.1073/pnas.1918455117 Text en Copyright © 2020 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/ https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Social Sciences
Puterman, Eli
Weiss, Jordan
Hives, Benjamin A.
Gemmill, Alison
Karasek, Deborah
Mendes, Wendy Berry
Rehkopf, David H.
Predicting mortality from 57 economic, behavioral, social, and psychological factors
title Predicting mortality from 57 economic, behavioral, social, and psychological factors
title_full Predicting mortality from 57 economic, behavioral, social, and psychological factors
title_fullStr Predicting mortality from 57 economic, behavioral, social, and psychological factors
title_full_unstemmed Predicting mortality from 57 economic, behavioral, social, and psychological factors
title_short Predicting mortality from 57 economic, behavioral, social, and psychological factors
title_sort predicting mortality from 57 economic, behavioral, social, and psychological factors
topic Social Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7369318/
https://www.ncbi.nlm.nih.gov/pubmed/32571904
http://dx.doi.org/10.1073/pnas.1918455117
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