Evidence map›Paper›PMID 38408898›Full record

ArticleBMC cardiovascular disorders2024

Social associations and cardiovascular mortality in the United States counties, 2016 to 2020.

Ashish Kumar, Kinza Iqbal, Mariam Shariff, Monil Majmundar, Ankur Kalra

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Article in BMC cardiovascular disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Ashish KumarDepartment of Internal Medicine, Cleveland Clinic Akron General, Akron, OH, USA.
Kinza IqbalDepartment of Internal Medicine, Dow Medical College, Dow University of Health Sciences, Karachi, Pakistan.
Mariam ShariffDepartment of Surgery, Mayo Clinic, Rochester, Minneapolis, USA.
Monil MajmundarDepartment of Cardiovascular Medicine, University of Kansas Medical Center, Kansas City, KS, USA.
Ankur KalraFranciscan Health, Lafayette, IN, USA. kalramd.ankur@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe positive aspects of social interaction on health have been described often, with considerably less attention to their negative aspect. This study aimed to assess the impact of social associations on cardiovascular mortality in the United States.

methodsThe Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) data sets from 2016 to 2020 were used to identify death records due to cardiovascular disease in the United States population aged 15 years and older. The social association rate defined as membership associations per 10,000 population, accessed from the 2020 County Health Rankings data was used as a surrogate for social participation. All United States counties were grouped into quartiles based on their social association rate; Q1 being the lowest quartile of social association, and Q4 the highest quartile. Age-adjusted mortality rate (AAMR) was calculated for each quartile. County health factor rankings for the state of Texas were used to adjust the AAMR for baseline comorbidities of county population, using Gaussian distribution linear regression.

resultsOverall, the AAMR was highest in the 4th social association rate quartile (306.73 [95% CI, 305.72-307.74]) and lowest in the 1st social association rate quartile (266.80 [95% CI, 266.41-267.20]). The mortality rates increased in a linear pattern from lowest to highest social association rate quartiles. After adjustment for the county health factor ranks of Texas, higher social association rate remained associated with a significantly higher AAMR (coefficient 15.84 [95% CI, 12.78-18.89]).

conclusionsOur study reported higher cardiovascular AAMR with higher social associations in the United States, with similar results after adjustment for County Health Rankings in the state of Texas.

Indexed as

Cardiovascular DiseasesCross-Sectional StudiesHumansUnited StatesCardiovascular mortalitySocial associationSocial support

Identifiers

PMID38408898
PMCPMC10898153

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