Does greater individual social capital improve the management of hypertension? Cross-national analysis of 61 229 individuals in 21 countries
Bibliographic record
Abstract
INTRODUCTION: Social capital, characterised by trust, reciprocity and cooperation, is positively associated with a number of health outcomes. We test the hypothesis that among hypertensive individuals, those with greater social capital are more likely to have their hypertension detected, treated and controlled. METHODS: Cross-sectional data from 21 countries in the Prospective Urban and Rural Epidemiology study were collected covering 61 229 hypertensive individuals aged 35-70 years, their households and the 656 communities in which they live. Outcomes include whether hypertensive participants have their condition detected, treated and/or controlled. Multivariate statistical models adjusting for community fixed effects were used to assess the associations of three social capital measures: (1) membership of any social organisation, (2) trust in other people and (3) trust in organisations, stratified into high-income and low-income country samples. RESULTS: In low-income countries, membership of any social organisation was associated with a 3% greater likelihood of having one's hypertension detected and controlled, while greater trust in organisations significantly increased the likelihood of detection by 4%. These associations were not observed among participants in high-income countries. CONCLUSION: Although the observed associations are modest, some aspects of social capital are associated with better management of hypertension in low-income countries where health systems are often weak. Given that hypertension affects millions in these countries, even modest gains at all points along the treatment pathway could improve management for many, and translate into the prevention of thousands of cardiovascular events each year.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".