Associations between hypertension with reproductive and menopausal factors: An integrated women’s health programme (IWHP) study
Bibliographic record
Abstract
BACKGROUND: Women are less likely to have classic cardiovascular risk factors than men, and events during their reproductive and menopausal years may increase hypertension risk. The aim of this study is to examine woman-specific factors, including menstrual, reproductive and pregnancy complications, in relation to the prevalence of hypertension in mid-life Asian women. METHODS: This is a cross-sectional study of 1146 healthy women aged 45-69 years, from a multi-ethnic Asian cohort. The women completed an extensive questionnaire that included their sociodemographic details, medical history, lifestyle and physical activity, and reproductive and menopausal history. They also underwent objectively measured physical performance tests and a dual X-ray absorptiometry scan. Hypertension was defined as a systolic BP ≥140 and/or diastolic BP ≥90mm Hg, past diagnosis by a physician, or use of antihypertensive medications. Multivariable logistic regression was used to assess the independent risk factors for hypertension. RESULTS: The average age of the 1146 women analysed was 56.3 (SD 6.2) years, and 55.2 percent of them were hypertensive. The prevalence of gestational diabetes and gestational hypertension was 12.6% and 9.4%, respectively. Besides age, abnormal menstrual cycle length at 25 years of age (OR:2.35, CI:1.34-4.13), preeclampsia (OR:2.46, CI:1.06-5.74), increased visceral adiposity (OR:4.21, CI:2.28-7.79) and reduced physical performance (OR:2.83, CI:1.46-5.47) were independently associated with hypertension in Asian women. CONCLUSIONS: Our findings highlight the necessity of including features of menstrual and reproductive history as possible indicators of hypertension risk in cardiovascular disease risk assessment and prevention among Asian women. Reducing visceral adiposity and exercise to improve physical performance may help women avoid developing hypertension.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".