Coronary heart disease racial disparities among older adults in the U.S.: Systematic review, 2000-2024
Bibliographic record
Abstract
Background Coronary heart disease (CHD) remains a leading cause of morbidity and mortality among older U.S. adults, with significant racial and ethnic disparities in prevalence, treatment, and outcomes. This systematic review synthesizes evidence from 44 studies published between 2000 and 2024 to examine these disparities among adults aged ≥65, focusing on prevalence, access to care, treatment quality, outcomes, contributing factors, and effective interventions. Methods The review adhered to PRISMA 2020 guidelines. A comprehensive search was conducted across six databases: PubMed, Embase, Scopus, Web of Science, CINAHL, and the Cochrane Library. Studies were included if they examined racial/ethnic differences in CHD among U.S. adults aged ≥65. Two independent reviewers screened titles and abstracts, followed by full-text review, with disagreements resolved by a third reviewer. Inter-rater reliability was assessed using Cohen’s kappa (0.85 for title/abstract, 0.90 for full-text). Quality assessment used the Newcastle-Ottawa Scale (NOS; high quality ≥7 points, moderate 4–6 points, low ≤3 points) for observational studies and the Cochrane Risk of Bias tool for randomized trials. Due to heterogeneity, a narrative synthesis was conducted, with subgroup analyses for key outcomes. Results The 44 included studies revealed persistent disparities in CHD prevalence, access, treatment, and outcomes, particularly affecting Black, Hispanic, and American Indian/Alaska Native (AI/AN) older adults. Minority groups exhibited higher CHD prevalence and risk factors (e.g., hypertension, diabetes), lower access to guideline-directed therapies, and worse outcomes, including higher readmission and mortality rates. Structural racism, socioeconomic factors, and systemic biases were key drivers. Interventions like policy reforms, community-based programs, and telehealth showed promise in reducing disparities. Conclusions Despite progress in acute care, significant disparities persist in long-term CHD management among minority older adults. Addressing social determinants, improving access to equitable care, and implementing culturally competent interventions are essential for health equity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.045 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".