Lifestyle risk factors for osteoporosis in Asian and Caucasian girls
Bibliographic record
Abstract
PURPOSE: We investigated ethnic differences in areal bone mineral density (aBMD; g x cm(-2)) and its determinants at two levels of maturity in Asian- and Caucasian-Canadian girls. METHODS: Participants were 131 Asian (26 Tanner breast stage I (aTI) and 30 Tanner II (aTII)), and Caucasian (30 Tanner I (cTI) and 45 Tanner II (cTII)) girls. We measured calcium intake by a food frequency questionnaire, general physical activity, and extracurricular sports with a modified Physical Activity Questionnaire for Children and loaded physical activity by 7-d recall. Fat mass, lean mass, and aBMD for the total body (TB), and aBMD at the lumbar spine (LS), proximal femur (PF), femoral neck (FN), and trochanter (TR) were measured by DXA (Hologic QDR 4500). We used ANCOVA (controlling for size and lean and fat mass) to compare bone mineral content (BMC) and aBMD between ethnicities within Tanner stages. RESULTS: Calcium intake was significantly lower for Asian girls in both TI and TII (P < 0.001) as compared with Caucasians. For physical activity measures, only the general score was greater in cTI than aTI (P < 0.05). Participation in loaded physical activities and extracurricular sports was significantly less for aTII than cTII (both, P < 0.01), whereas general physical activity did not differ. aBMD measures were similar between aTI and cTI. However, TB, PF, FN, and aBMD were significantly lower (approximately 9-14%) in aTII as compared with cTII. CONCLUSION: Thus, there was greater ethnic disparity in lifestyle factors related to bone health and absolute measures of bone mineral with advanced maturity.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".