Social connections and hypertension in women and men: a population-based cross-sectional study of the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
BACKGROUND: Associations between social ties and hypertension are poorly understood in women and men. We investigated the association between marital status, living arrangement, social network size and social participation and hypertension by sex/gender. METHODS: Cross-sectional analysis of 28 238 middle-age and old-age adults (45-85 years) was conducted using the baseline Canadian Longitudinal Study on Aging Comprehensive cohort data. Blood pressure (BP) was measured using the automated BpTRU device and hypertension was defined as BP more than 140/90 mmHg, or more than 130/80 mmHg in participants with diabetes, self-reported history or receiving antihypertensive therapy. RESULTS: Being nonpartnered, having limited social participation (≤2 social activities per month) or a small social network size was associated with higher odds of having hypertension in women. Odds of hypertension were higher among widowed women [odds ratio 1.33 (95% confidence interval (CI): 1.16, 1.51)] compared with married women. The largest difference in adjusted mean SBP in women was between widowed [3.06 mmHg (95% CI: 2.01, 4.11)], vs. married women. For men, lone-living (vs. coliving) was linked to a lower odds of hypertension [odds ratio 0.85 (95% CI: 0.75, 0.96)] When considering two social ties simultaneously, the adverse associations between nonpartnership (mainly for singles and divorced) and BP were mitigated with increased social participation, especially among women. CONCLUSION: Social ties appear to be more strongly associated with hypertension in middle and older aged women than men. Women who are nonpartnered or who engage in few social activities and men who are coliving represent at risk groups for having hypertension. Healthcare professionals may need to consider these social factors in addressing risk for hypertension and cardiovascular disease prevention.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | high |
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 | 0.001 | 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 | 0.001 | 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) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".