Metabolic Syndrome and the Burden of Cardiovascular Disease in Caribbean Hispanic Women Living in Northern Manhattan: A Red Flag for Education
Bibliographic record
Abstract
BACKGROUND: Metabolic syndrome has the highest prevalence among Mexican-American women. Little information is available for Caribbean Hispanics, the largest and fastest growing ethnic minority in the United States. We sought to evaluate the frequency of metabolic syndrome and its relationship with race/ethnicity, socioeconomic position, and education in women of largely Caribbean Hispanic origin. METHODS: There were 204 women enrolled in a cross-sectional study who had demographics, fasting glucose, lipid profile, waist circumference, and blood pressure determined. Metabolic syndrome (defined by the National Cholesterol Education Program/Adult Treatment Panel III [NCEP/ATP III]) was analyzed using univariate and multivariate logistic regression to test age, race/ethnicity, education, health insurance, and residence on the risk of metabolic syndrome. A P value <0.05 was considered significant. RESULTS: Mean age was 58 +/- 11 years, Hispanic 44.1% (93% Caribbean), non-Hispanic white (NHW) 38.7%, and non-Hispanic black 9.8%. Education was some high school (<HS) 33.7%, HS graduate 11.2%, some college 12.9%, college graduate 10.1%, and postgraduate 32%. Health insurance was Medicaid 47.8% and commercial 52.2%. Area of residence was urban 77.1% and suburban 22.9%. The frequency of metabolic syndrome was 42.4%, and was increased in Hispanic women (63.3%) versus NHW (29.6%), women with <HS (72.6%) versus postgraduate education (32.1%), women with Medicaid (57.9% vs. 27.4%) and urban residence (47.5% vs. 27.2%). For all comparisons, P < 0.05. Education <HS was linked to increased risk of metabolic syndrome (odds ratio [OR] = 3.5 [1.2-10.0], P = 0.02). Hispanic women had the lowest level of education (P < 0.001) and the highest frequency of individual metabolic syndrome components (P < 0.01). CONCLUSIONS: Metabolic syndrome showed an alarming rate in less educated Caribbean Hispanic women and was independently associated with lower education level.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".