Coexistence of Osteoporosis and Cardiovascular Disease Risk Factors in Apparently Healthy, Untreated Postmenopausal Women
Bibliographic record
Abstract
This study aimed to determine whether apparently healthy, untreated postmenopausal women at risk of osteoporosis relative to nonmenopausal women are concomitantly at risk of cardiovascular disease (CVD) in terms of various aspects of lifestyle, personality, body shape and composition, and blood chemistry. Two homogeneous groups of 30 women having reached menopause for 3-5 years and 30 nonmenopausal controls, all non-estrogen users without apparent CVD risk factors, were compared in a cross-sectional design. Data related to physical activity, dietary intakes, personality type, anthropometry, and skinfold-thickness were collected. Plasma insulin-like growth factor (IGF-1) and serum lipids were measured and used as biochemical predictors of osteoporosis and CVD, respectively. Compared to nonmenopausal controls, postmenopausal women were at greater risk of bone loss given their lower plasma IGF-1, lower physical activity level, and even given their higher serum lipids, as recent literature suggests. Moreover, their dietary calcium intake fulfilled only 70% of the current recommendation, which may reduce protection against osteoporosis and CVD (particularly hypertension) as well. The two groups did not differ regarding energy intake, body weight and frame size, body mass index (BMI), waist circumference, and waist-hip ratio (WHR). However, postmenopausal subjects had more adipose tissue and differed in terms of lifestyle factors (lower dietary lipids and greater alcohol consumption). While neither group was at particular risk of CVD according to waist circumference, WHR, and serum triglycerides, postmenopausal women were at risk according to percent body adiposity and serum cholesterol. This study shows that several risk factors for osteoporosis and CVD can coexist in apparently healthy postmenopausal women after a few years of natural menopause. It emphasizes the need for a timely screening that would stress both heart and bone risk factors.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".