Disparities in cardiovascular disease among Caribbean populations: a systematic literature review
Bibliographic record
Abstract
BACKGROUND: Cardiovascular diseases (CVD) are the predominant cause of death globally. The large health disparities in the distribution of the burden of disease seen in developed and developing countries are of growing concern. Central to this concern is the poor outcome which is seen disproportionately in socially disadvantaged groups and racial/ethnic minorities. The aim of the study was to conduct a systematic literature review to investigate the nature of cardiovascular disease health disparities among Afro-Caribbean origin populations and identify current knowledge gaps. METHODS: A systematic literature review including a detailed search strategy was developed to search MEDLINE and other research databases. Using an a priori protocol peer-reviewed publications and grey literature articles were retrieved and screened and relevant data extracted by two independent review authors. Thematic analysis was done according to CVD outcomes and measures of disparity including age, sex, ethnicity and socioeconomic status. RESULTS: The search retrieved 665 articles of which 22 met the inclusion criteria. Most studies were conducted in the United Kingdom and centered on the prevalence of CVD by ethnicity, age and sex. An important sub-theme identified was the disparities in health service utilization/hospital admission. Coronary Heart Disease (CHD) and Peripheral Arterial Disease (PAD) were less prevalent among Afro-Caribbeans compared to Caucasian and South East Asian ethnic groups. The prevalence of CHD ranged from 0-7% in Afro-Caribbean to 2-22% in Caucasians. Strokes were more common among Afro-Caribbeans. There are inadequate data on morbidity and mortality from CVD, particularly across the socio-economic gradient, in Afro-Caribbean populations. CONCLUSIONS: There are important differences in morbidity and mortality from CVD across ethnic groups. Important knowledge gaps remain in understanding the social determinants of these disparities in CVD. More research exploring these gaps by varying disparity indicators needs to be undertaken.
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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 | 0.008 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.016 | 0.018 |
| 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) | 0.005 | 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".