ArticleCureus2024
Exploring the Factors Influencing Coronary Heart Disease Prevalence in the US Population: A Retrospective Observational Study.
Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Construction of diagnostic and prognostic models for premature coronary artery disease based on multiple machine algorithms.Frontiers in cardiovascular medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionCoronary heart disease (CHD) remains a significant global health concern and is characterized by inadequate blood supply to the myocardium due to the accumulation of plaque in the coronary arteries. Despite therapeutic advancements, prevalence disparities persist across various segments of the U.S. population, posing a significant challenge to healthcare systems. This study aims to find the prevalence disparities of CHD using Behavioral Risk Factor Surveillance System (BRFSS) data. METHODOLOGY: A retrospective observational study was done using the 2022 BRFSS dataset on January 17, 2024. The study examined the presence of CHD as the dependent variable and investigated various independent variables. Descriptive and logistic regression analyses were conducted using the BRFSS Web Enabled Analysis Tool (Centers for Disease Control and Prevention, Atlanta, GA). Data management and storage utilized Microsoft Excel, and graphical analysis employed GraphPad Prism, version 9.4.1 (GraphPad Software, Inc., San Diego, CA).
resultsIn demographics, respondents aged 65+ had higher CHD odds, while females exhibited lower risk than males. Hispanics had the lowest odds of CHD among all races. Socioeconomically, inability to work and retirees had higher CHD odds, as did income below $20,000 but ≥$15,000. Poor physical health increased CHD odds, as did having multiple healthcare providers. Medicare users had the highest CHD odds among insurance options.
conclusionsSignificant disparities in CHD prevalence were seen across demographic, socioeconomic, health status, and healthcare access dimensions in the United States, emphasizing the urgent need for targeted interventions to address these disparities and improve overall public health outcomes.
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Registered trials
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