Evidence map›Paper›PMID 40138291›Full record

ArticlePloS one2025

Ethnic variations in cardiovascular disease (CVD) risk factors and associations with prevalent CVD and CVD mortality in the United States.

Queenie Cheung, Sean Wharton, Andrea Josse, Jennifer L Kuk

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Queenie CheungSchool of Kinesiology and Health Science, York University, Toronto, Ontario, Canada.ORCID 0009-0003-0403-5577
Sean WhartonSchool of Kinesiology and Health Science, York University, Toronto, Ontario, Canada.
Andrea JosseSchool of Kinesiology and Health Science, York University, Toronto, Ontario, Canada.
Jennifer L KukSchool of Kinesiology and Health Science, York University, Toronto, Ontario, Canada.ORCID 0000-0002-3425-6149

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo explore the association between ethnicity and cardiovascular disease (CVD) risk factors, including physical inactivity, obesity, hypertension, type 2 diabetes (T2D), lack of health insurance and low family income in a nationally representative sample of U.S. adults. RESEARCH DESIGN AND

methodsAdults from the National Health and Nutrition Examination Survey (NHANES 2011-2020, n = 17,355) were classified as having CVD risk factors based on both self-reported and metabolic data. Ethnic differences in how these CVD risk factors relate to prevalent CVD and CVD mortality was examined in Whites, Blacks, Asians and Hispanics.

resultsCompared to Whites, significant disparities were noted in several CVD risk factors in ethnic minorities, such as lower PA, lower income, and more prevalent metabolic risk factors. Blacks and Hispanics commonly had higher prevalent CVD risk as compared to Whites even after adjusting for income and metabolic risk factors. Physical inactivity was most strongly associated with prevalent CVD and CVD mortality among Whites and Blacks. There were no ethnic differences in the inverse association between income and prevalent CVD risk, but Blacks with low income were associated with the greatest elevated CVD mortality. Hypertension and T2D were similarly related with prevalent CVD across ethnic groups, but Blacks and Hispanics with hypertension or T2D were at greater CVD mortality risk as compared to Whites.

conclusionOur study identified that socioeconomic and metabolic risk factors may relate differently to CVD outcomes among ethnic minority groups in the United States. Addressing these ethnic disparities in health warrants further investigation.

Indexed as

Cardiovascular DiseasesAdultAgedBlack or African AmericanDiabetes Mellitus, Type 2EthnicityFemaleHeart Disease Risk FactorsHispanic or LatinoHumansHypertensionMaleMiddle AgedNutrition SurveysObesityPrevalence

Identifiers

PMID40138291
PMCPMC11940680

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.