The difference in hypertension control between older men and women.
Bibliographic record
Abstract
BACKGROUND: In Canada, as elsewhere, control of hypertension in older persons who are using antihypertensive medication is more likely in men than in women. The reasons for the observed difference are not known. DATA AND METHODS: Data are from cycle 1 of the 2007 to 2009 Canadian Health Measures Survey (CHMS). The CHMS includes a comprehensive questionnaire, automated blood pressure (BP) measures, and a variety of biological and anthropometric assessments. Frequencies, means, cross-tabulations and multivariate models were produced to study differences between the sexes in hypertension control in a weighted sample representative of the household population aged 60 to 79. RESULTS: The prevalence of hypertension was nearly equal among older men (60%) and women (59%), and the percentage of those with hypertension who were receiving pharmaceutical treatment was not statistically different (84% and 89%, respectively). However, despite current treatment, hypertension was uncontrolled in a substantially higher percentage of women (30%) than men (17%). The difference persisted when age, socio-economic status, co-morbidity, category of medication, anthropometry, and other correlates of hypertension were taken into account. INTERPRETATION: The factors considered in the analysis do not account for the advantage to older men in hypertension control. The findings underscore the importance of efforts to control blood pressure in older women.
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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 | 0.003 |
| 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) | 0.002 | 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".