The relationship between adiponectin and blood pressure in premenopausal and postmenopausal women
Bibliographic record
Abstract
PURPOSE: Menopause can affect the reportedly inverse association between adiponectin and blood pressure (BP); however, this relationship is still poorly understood. The present study cross-sectionally compared the relationship between adiponectin and BP in pre- and postmenopausal women. METHODS: Healthy, asymptomatic women on no medication (n = 262) were divided into a premenopausal group (n = 125, mean age 44.7 years) and a postmenopausal group (n = 137, mean age 65.6 years). Fasting values of serum adiponectin and BP were measured, in addition to body mass index (BMI), blood glucose and lipids. The correlation between the levels of adiponectin/BMI and mean BP (MBP) was analyzed with a linear regression model for the respective groups. RESULTS: The median adiponectin/BMI did not significantly differ between the pre- and postmenopausal groups (0.37 and 0.42, P = 0.08), and the premenopausal group had a significantly lower level of mean MBP than the postmenopausal group (87.6 and 100.7 mmHg, P < 0.001). In an unadjusted analysis, adiponectin/BMI was found to be significantly and inversely correlated with MBP in the premenopausal group (r = -0.499, P < 0.001) and the postmenopausal group (r = -0.203, P < 0.01), respectively. In a stepwise multivariate-adjusted analysis, adiponectin/BMI remained significantly, inversely and independently correlated with MBP in the premenopausal group (β = -0.383, P < 0.001), while no significant correlation was found between adiponectin/BMI and MBP for the postmenopausal group. CONCLUSIONS: The adiponectin-BP relationship appears to be associated with premenopausal state.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".