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County-Level Life Expectancy Change: A Novel Metric for Monitoring Public Health
Life expectancy (LE) is a core measure of population health. Studies have confirmed the predictive importance of modifiable determinants on LE, but less is known about their association with LE change over time at the US county level. In addition, we explore the predictive association of LE change w...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9517827/ https://www.ncbi.nlm.nih.gov/pubmed/36078387 http://dx.doi.org/10.3390/ijerph191710672 |
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author | Chandran, Aruna Purbey, Ritika Leifheit, Kathryn M. Evans, Kirsten McGhie Baez, Jocelyn Velasquez Althoff, Keri N. |
author_facet | Chandran, Aruna Purbey, Ritika Leifheit, Kathryn M. Evans, Kirsten McGhie Baez, Jocelyn Velasquez Althoff, Keri N. |
author_sort | Chandran, Aruna |
collection | PubMed |
description | Life expectancy (LE) is a core measure of population health. Studies have confirmed the predictive importance of modifiable determinants on LE, but less is known about their association with LE change over time at the US county level. In addition, we explore the predictive association of LE change with COVID-19 mortality. We used a linear regression model to calculate county-level annual LE change from 2011 to 2016, and categorized LE change (≤−0.1 years change per year as decreasing, ≥0.1 years as increasing, otherwise no change). A multinomial regression model was used to determine the association between modifiable determinants of health indicators from the County Health Rankings and LE change. A Poisson regression model was used to evaluate the relationship between change in life expectancy and COVID-19 mortality through September 2021. Among 2943 counties, several modifiable determinants of health were significantly associated with odds of being in increasing LE or decreasing LE counties, including adult smoking, obesity, unemployment, and proportion of children in poverty. The presence of an increasing LE in 2011–2016, as compared to no change, was significantly associated with a 5% decrease in COVID-19 mortality between 2019 and 2021 (β = 0.953, 95% CI: 0.943, 0.963). We demonstrated that change in LE at the county level is a useful metric for tracking public health progress, measuring the impact of public health initiatives, and gauging preparedness and vulnerability for future public health emergencies. |
format | Online Article Text |
id | pubmed-9517827 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-95178272022-09-29 County-Level Life Expectancy Change: A Novel Metric for Monitoring Public Health Chandran, Aruna Purbey, Ritika Leifheit, Kathryn M. Evans, Kirsten McGhie Baez, Jocelyn Velasquez Althoff, Keri N. Int J Environ Res Public Health Article Life expectancy (LE) is a core measure of population health. Studies have confirmed the predictive importance of modifiable determinants on LE, but less is known about their association with LE change over time at the US county level. In addition, we explore the predictive association of LE change with COVID-19 mortality. We used a linear regression model to calculate county-level annual LE change from 2011 to 2016, and categorized LE change (≤−0.1 years change per year as decreasing, ≥0.1 years as increasing, otherwise no change). A multinomial regression model was used to determine the association between modifiable determinants of health indicators from the County Health Rankings and LE change. A Poisson regression model was used to evaluate the relationship between change in life expectancy and COVID-19 mortality through September 2021. Among 2943 counties, several modifiable determinants of health were significantly associated with odds of being in increasing LE or decreasing LE counties, including adult smoking, obesity, unemployment, and proportion of children in poverty. The presence of an increasing LE in 2011–2016, as compared to no change, was significantly associated with a 5% decrease in COVID-19 mortality between 2019 and 2021 (β = 0.953, 95% CI: 0.943, 0.963). We demonstrated that change in LE at the county level is a useful metric for tracking public health progress, measuring the impact of public health initiatives, and gauging preparedness and vulnerability for future public health emergencies. MDPI 2022-08-27 /pmc/articles/PMC9517827/ /pubmed/36078387 http://dx.doi.org/10.3390/ijerph191710672 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Chandran, Aruna Purbey, Ritika Leifheit, Kathryn M. Evans, Kirsten McGhie Baez, Jocelyn Velasquez Althoff, Keri N. County-Level Life Expectancy Change: A Novel Metric for Monitoring Public Health |
title | County-Level Life Expectancy Change: A Novel Metric for Monitoring Public Health |
title_full | County-Level Life Expectancy Change: A Novel Metric for Monitoring Public Health |
title_fullStr | County-Level Life Expectancy Change: A Novel Metric for Monitoring Public Health |
title_full_unstemmed | County-Level Life Expectancy Change: A Novel Metric for Monitoring Public Health |
title_short | County-Level Life Expectancy Change: A Novel Metric for Monitoring Public Health |
title_sort | county-level life expectancy change: a novel metric for monitoring public health |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9517827/ https://www.ncbi.nlm.nih.gov/pubmed/36078387 http://dx.doi.org/10.3390/ijerph191710672 |
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