Sex and Age Differences in the Association Between Social Determinants of Health and Cardiovascular Health According to Household Income Among Mongolian Adults: Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Although social determinants of health (SDH) are an underlying cause of poor cardiovascular health (CVH), there is insufficient evidence for the association between SDH and CVH, which varies by sex and age among Mongolian adults. OBJECTIVE: We aimed to explore whether education, household income, and health insurance were associated with CVH according to sex and age among Mongolian adults. METHODS: The final sample included data on 5691 participants (male: n=2521. 44.3% and female: n=3170, 55.7%) aged 18-69 years from the 2019 World Health Organization STEPwise approach to noncommunicable disease risk-factor surveillance. CVH was measured using a modified version of Life's Simple 7 with 4 health behaviors (cigarette smoking, BMI, physical activity, and a healthy diet) and 3 biological factors (blood pressure, fasting glucose, and total cholesterol blood levels) and classified into poor, intermediate, and ideal levels as recommended by the American Heart Association. Multinomial logistic regression analyses examined the associations between SDH and CVH by monthly equivalized household income after adjusting for age, sex, work status, area, history of myocardial infarction or stroke, use of aspirin, and use of statin. Subgroup analyses were conducted to examine the associations between SDH and CVH based on sex and age, considering monthly equivalized household income as a key variable. RESULTS: Using the ideal level of CVH as a reference, among those with the lowest household income, having less than 12 years of education, and not having health insurance were associated with poor CVH (education level: odds ratio [OR] 2.42, 95% CI 1.30-4.51; P=.006; health insurance: OR 2.17, 95% CI 1.13-4.18; P=.02). These associations were more profound among female individuals (education level: OR 2.99, 95% CI 1.35-6.63; P=.007; health insurance: OR 2.54, 95% CI 1.09-5.90; P=.03) and those aged 18-44 years (education level: OR 3.22, 95% CI 1.54-6.72; P=.002; health insurance: OR 2.03, 95% CI 0.98-4.18; P=.06). CONCLUSIONS: Participants in the lowest household income group with lower educational levels and without health insurance were more likely to have poor CVH, and these results were more pronounced in female individuals and young adults. These findings suggest the need to develop strategies for CVH equity in Mongolian female individuals and young adults that consider income levels, education levels, and health insurance.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".