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Predicting later life health status and mortality using state-level socioeconomic characteristics in early life

Studies extending across multiple life stages promote an understanding of factors influencing health across the life span. Existing work has largely focused on individual-level rather than area-level early life determinants of health. In this study, we linked multiple data sets to examine whether ea...

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Detalles Bibliográficos
Autores principales: Hamad, Rita, Rehkopf, David H., Kuan, Kai Y., Cullen, Mark R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5047283/
https://www.ncbi.nlm.nih.gov/pubmed/27713921
http://dx.doi.org/10.1016/j.ssmph.2016.04.005
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author Hamad, Rita
Rehkopf, David H.
Kuan, Kai Y.
Cullen, Mark R.
author_facet Hamad, Rita
Rehkopf, David H.
Kuan, Kai Y.
Cullen, Mark R.
author_sort Hamad, Rita
collection PubMed
description Studies extending across multiple life stages promote an understanding of factors influencing health across the life span. Existing work has largely focused on individual-level rather than area-level early life determinants of health. In this study, we linked multiple data sets to examine whether early life state-level characteristics were predictive of health and mortality decades later. The sample included 143,755 U.S. employees, for whom work life claims and administrative data were linked with early life state-of-residence and mortality. We first created a “state health risk score” (SHRS) and “state mortality risk score” (SMRS) by modeling state-level contextual characteristics with health status and mortality in a randomly selected 30% of the sample (the “training set”). We then examined the association of these scores with objective health status and mortality in later life in the remaining 70% of the sample (the “test set”) using multivariate linear and Cox regressions, respectively. The association between the SHRS and adult health status was β=0.14 (95%CI: 0.084, 0.20), while the hazard ratio for the SMRS was 0.96 (95%CI: 0.93, 1.00). The association between the SHRS and health was not statistically significant in older age groups at a p-level of 0.05, and there was a statistically significantly different association for health status among movers compared to stayers. This study uses a life course perspective and supports the idea of “sensitive periods” in early life that have enduring impacts on health. It adds to the literature examining populations in the U.S. where large linked data sets are infrequently available.
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spelling pubmed-50472832017-12-01 Predicting later life health status and mortality using state-level socioeconomic characteristics in early life Hamad, Rita Rehkopf, David H. Kuan, Kai Y. Cullen, Mark R. SSM Popul Health Article Studies extending across multiple life stages promote an understanding of factors influencing health across the life span. Existing work has largely focused on individual-level rather than area-level early life determinants of health. In this study, we linked multiple data sets to examine whether early life state-level characteristics were predictive of health and mortality decades later. The sample included 143,755 U.S. employees, for whom work life claims and administrative data were linked with early life state-of-residence and mortality. We first created a “state health risk score” (SHRS) and “state mortality risk score” (SMRS) by modeling state-level contextual characteristics with health status and mortality in a randomly selected 30% of the sample (the “training set”). We then examined the association of these scores with objective health status and mortality in later life in the remaining 70% of the sample (the “test set”) using multivariate linear and Cox regressions, respectively. The association between the SHRS and adult health status was β=0.14 (95%CI: 0.084, 0.20), while the hazard ratio for the SMRS was 0.96 (95%CI: 0.93, 1.00). The association between the SHRS and health was not statistically significant in older age groups at a p-level of 0.05, and there was a statistically significantly different association for health status among movers compared to stayers. This study uses a life course perspective and supports the idea of “sensitive periods” in early life that have enduring impacts on health. It adds to the literature examining populations in the U.S. where large linked data sets are infrequently available. Elsevier 2016-04-30 /pmc/articles/PMC5047283/ /pubmed/27713921 http://dx.doi.org/10.1016/j.ssmph.2016.04.005 Text en © 2016 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Hamad, Rita
Rehkopf, David H.
Kuan, Kai Y.
Cullen, Mark R.
Predicting later life health status and mortality using state-level socioeconomic characteristics in early life
title Predicting later life health status and mortality using state-level socioeconomic characteristics in early life
title_full Predicting later life health status and mortality using state-level socioeconomic characteristics in early life
title_fullStr Predicting later life health status and mortality using state-level socioeconomic characteristics in early life
title_full_unstemmed Predicting later life health status and mortality using state-level socioeconomic characteristics in early life
title_short Predicting later life health status and mortality using state-level socioeconomic characteristics in early life
title_sort predicting later life health status and mortality using state-level socioeconomic characteristics in early life
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5047283/
https://www.ncbi.nlm.nih.gov/pubmed/27713921
http://dx.doi.org/10.1016/j.ssmph.2016.04.005
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