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Evaluation of Between-County Disparities in Premature Mortality Due to Stroke in the US

IMPORTANCE: Identifying the factors associated with premature stroke mortality and measuring between-county disparities may provide insight into how to reduce variations and achieve more equitable health outcomes. OBJECTIVE: To examine the between-county disparities in premature stroke mortality in...

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Autores principales: Song, Suhang, Ma, Gaoting, Trisolini, Michael G., Labresh, Kenneth A., Smith, Sidney C., Jin, Yinzi, Zheng, Zhi-Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8116984/
https://www.ncbi.nlm.nih.gov/pubmed/33978725
http://dx.doi.org/10.1001/jamanetworkopen.2021.4488
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author Song, Suhang
Ma, Gaoting
Trisolini, Michael G.
Labresh, Kenneth A.
Smith, Sidney C.
Jin, Yinzi
Zheng, Zhi-Jie
author_facet Song, Suhang
Ma, Gaoting
Trisolini, Michael G.
Labresh, Kenneth A.
Smith, Sidney C.
Jin, Yinzi
Zheng, Zhi-Jie
author_sort Song, Suhang
collection PubMed
description IMPORTANCE: Identifying the factors associated with premature stroke mortality and measuring between-county disparities may provide insight into how to reduce variations and achieve more equitable health outcomes. OBJECTIVE: To examine the between-county disparities in premature stroke mortality in the US, investigate county-level factors associated with mortality, and describe differences in mortality disparities by place of death and stroke subtype. DESIGN, SETTING, AND PARTICIPANTS: This retrospective cross-sectional study linked the mortality and demographic data of US counties from the Centers for Disease Control and Prevention WONDER database to county-level characteristics from multiple databases. The outcome measure was county-level age-adjusted stroke mortality among adults aged 25 to 64 years in 2637 US counties from 1999 to 2018. This study was conducted from April 1, 2019, to October 31, 2020. Generalized linear Poisson regressions were fitted to investigate 4 sets of factors associated with county-level mortality: demographic composition, socioeconomic status, health care and environmental features, and population health. The Theil index score was calculated to assess the mortality disparities. MAIN OUTCOMES AND MEASURES: Stroke mortality was measured as the number of deaths attributed to stroke in the data set. Out-of-stroke-unit death was defined as any death occurring in outpatient or emergency departments or at the pretransport location. Five stroke subtypes were included in the analysis. RESULTS: Although mortality did not change substantially from 1999 to 2018 (from 12.62 to 11.81 per 100 000 population), the proportion of deaths occurring out of the stroke unit increased from 23.56% (4328 of 18 369) to 34.57% (6978 of 20 188). A large percentage of stroke of an uncertain cause was reported, with most deaths (55.20%) occurring out of the stroke unit. In the county with the highest premature stroke mortality, the incidence was 20.78 times as high as that in the county with the lowest mortality (65.04 vs 3.13 deaths per 100 000 population). The highest between-county disparities were found for stroke of uncertain cause. For out-of-stroke-unit death, county-level mortality was largely associated with demographic composition (31.6%) and health care and environmental features (25.8%). For in-hospital death, 29.8% of county-level mortality was associated with population health and 28.7% was associated with demographic composition. CONCLUSIONS AND RELEVANCE: These findings suggest that strategies addressing specific factors that underlie the mortality disparities among US counties, especially for out-of-stroke-unit death and stroke of uncertain cause, may be useful when tailored to the county-level context before implementing interventions for the neediest counties.
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spelling pubmed-81169842021-05-14 Evaluation of Between-County Disparities in Premature Mortality Due to Stroke in the US Song, Suhang Ma, Gaoting Trisolini, Michael G. Labresh, Kenneth A. Smith, Sidney C. Jin, Yinzi Zheng, Zhi-Jie JAMA Netw Open Original Investigation IMPORTANCE: Identifying the factors associated with premature stroke mortality and measuring between-county disparities may provide insight into how to reduce variations and achieve more equitable health outcomes. OBJECTIVE: To examine the between-county disparities in premature stroke mortality in the US, investigate county-level factors associated with mortality, and describe differences in mortality disparities by place of death and stroke subtype. DESIGN, SETTING, AND PARTICIPANTS: This retrospective cross-sectional study linked the mortality and demographic data of US counties from the Centers for Disease Control and Prevention WONDER database to county-level characteristics from multiple databases. The outcome measure was county-level age-adjusted stroke mortality among adults aged 25 to 64 years in 2637 US counties from 1999 to 2018. This study was conducted from April 1, 2019, to October 31, 2020. Generalized linear Poisson regressions were fitted to investigate 4 sets of factors associated with county-level mortality: demographic composition, socioeconomic status, health care and environmental features, and population health. The Theil index score was calculated to assess the mortality disparities. MAIN OUTCOMES AND MEASURES: Stroke mortality was measured as the number of deaths attributed to stroke in the data set. Out-of-stroke-unit death was defined as any death occurring in outpatient or emergency departments or at the pretransport location. Five stroke subtypes were included in the analysis. RESULTS: Although mortality did not change substantially from 1999 to 2018 (from 12.62 to 11.81 per 100 000 population), the proportion of deaths occurring out of the stroke unit increased from 23.56% (4328 of 18 369) to 34.57% (6978 of 20 188). A large percentage of stroke of an uncertain cause was reported, with most deaths (55.20%) occurring out of the stroke unit. In the county with the highest premature stroke mortality, the incidence was 20.78 times as high as that in the county with the lowest mortality (65.04 vs 3.13 deaths per 100 000 population). The highest between-county disparities were found for stroke of uncertain cause. For out-of-stroke-unit death, county-level mortality was largely associated with demographic composition (31.6%) and health care and environmental features (25.8%). For in-hospital death, 29.8% of county-level mortality was associated with population health and 28.7% was associated with demographic composition. CONCLUSIONS AND RELEVANCE: These findings suggest that strategies addressing specific factors that underlie the mortality disparities among US counties, especially for out-of-stroke-unit death and stroke of uncertain cause, may be useful when tailored to the county-level context before implementing interventions for the neediest counties. American Medical Association 2021-05-12 /pmc/articles/PMC8116984/ /pubmed/33978725 http://dx.doi.org/10.1001/jamanetworkopen.2021.4488 Text en Copyright 2021 Song S et al. JAMA Network Open. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the CC-BY License.
spellingShingle Original Investigation
Song, Suhang
Ma, Gaoting
Trisolini, Michael G.
Labresh, Kenneth A.
Smith, Sidney C.
Jin, Yinzi
Zheng, Zhi-Jie
Evaluation of Between-County Disparities in Premature Mortality Due to Stroke in the US
title Evaluation of Between-County Disparities in Premature Mortality Due to Stroke in the US
title_full Evaluation of Between-County Disparities in Premature Mortality Due to Stroke in the US
title_fullStr Evaluation of Between-County Disparities in Premature Mortality Due to Stroke in the US
title_full_unstemmed Evaluation of Between-County Disparities in Premature Mortality Due to Stroke in the US
title_short Evaluation of Between-County Disparities in Premature Mortality Due to Stroke in the US
title_sort evaluation of between-county disparities in premature mortality due to stroke in the us
topic Original Investigation
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8116984/
https://www.ncbi.nlm.nih.gov/pubmed/33978725
http://dx.doi.org/10.1001/jamanetworkopen.2021.4488
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