Cardiovascular health through a sex and gender lens in six South Asian countries: Findings from the WHO STEPS surveillance
Bibliographic record
Abstract
Background: Sex and gender-based differences in cardiovascular health (CVH) has been explored in the context of high-income countries. However, these relationships have not been examined in low- and middle-income countries. The main aim of this study was to examine how sex and gender-related factors are associated with cardiovascular risk factors of people in South Asian countries. Methods: We conducted a retrospective analysis of the World Health Organization's "STEPwise approach to surveillance of risk factors for non-communicable disease" or "STEPS" from six South Asian countries, surveys conducted between 2014-2019. The main outcomes were CVH as measured by a composite measure of STEPS-HEART health index (smoking, physical activity, fruit and vegetable consumption, overweight/obesity, diabetes and hypertension), values ranging from 0 (worst) to 6 (best or ideal) and self-reported occurrence of cardiovascular disease (ie, heart attack and stroke). Multivariate linear and logistic regression models were performed. Multiple imputation with chained equations was performed. Results: = 0.31), significant in males. Conclusions: Among the South Asian population, being female may be advantageous in having an ideal CVH. However, gender-related factors such as marital status and large household size were associated with poorer CVH and greater risk of CVD, regardless of sex.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".