Body Mass, Vitamin D and Alcohol Intake, Lactose Intolerance, and Television Watching Influence Bone Mineral Density of Young, Healthy Canadian Women
Bibliographic record
Abstract
OBJECTIVE: To report bone mineral density (BMD) in young, reportedly healthy Canadian women and to determine whether lifestyle factors that have been associated with bone health in older women are also associated with BMD in young women. METHOD: We recruited a convenience sample of 52 female undergraduate students in the Applied Human Nutrition program at the University of Guelph, Ontario, Canada. BMD was measured at the femoral neck, lumbar spine (L1 to L4), and whole body using a Discovery Wi (Hologic Inc.) dual-energy x-ray absorptiometer. Subjects completed a questionnaire to collect demographics, medical history, physical activity levels, and dietary habits; in addition, a subset of subjects (n = 31) completed a food frequency questionnaire to collect data on calcium and vitamin D intake. BMD data were examined using T- and Z-score classifications established by the World Health Organization (WHO); multiple regression analysis was used to predict BMD with biological and lifestyle variables. RESULTS: Mean BMD measured at the femoral neck, lumbar spine, and whole body was 0.863 ± 0.11, 1.019 ± 0.09, and 1.085 ± 0.07 g/cm(2), respectively. Body mass and body mass index were significantly positively correlated with BMD at all 3 sites. Television watching, lactose intolerance, number of alcoholic drinks consumed per week, and age were used to develop a linear regression model to predict whole-body BMD (r(2) = 0.727, p < 0.001). CONCLUSIONS: Based on criteria established by the WHO, women in this group presented with lower than expected BMD.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".