Association of dietary patterns of American adults with bone mineral density and fracture
Bibliographic record
Abstract
OBJECTIVE: In a representative sample of US adults, we investigated the associations of nutrient patterns (NP) with bone mineral density (BMD) and fractures. DESIGN: Cross-sectional. SETTING: US community-based National Health and Nutrition Examination Survey (NHANES). SUBJECTS: Participants with measured data on dietary intake and BMD from 2005 to 2010 were included. Principal components analysis was used to identify NP. BMD was measured using dual-energy X-ray absorptiometry. ANCOVA, adjusted logistic and linear regression models were employed, accounting for the complex survey design and sample weights. RESULTS: We included a total of 18 318 participants, with 47·0 % (n 8607) being men. The mean age was 45·8 years with no sex difference. Three NP emerged, explaining 55·9 % of the variance in nutrient consumption. Multivariable-adjusted linear regressions revealed significant inverse associations between the 'high-energy' NP (rich in carbohydrates and sugar, total fat and saturated fat) and total femur, femoral neck, trochanter and intertrochanter BMD (β coefficient: -0·029, -0·025, -0·034 and -0·021, respectively, all P<0·001), while there were significant associations between the 'nutrient-dense' NP (rich in vitamins, minerals and fibre) and 'healthy fat' NP (high dietary PUFA and MUFA) and BMD at total femur, femoral neck, trochanter and intertrochanter (all P<0·001). In adjusted logistic regression models, the odds of hip, wrist or spine fractures did not vary significantly across NP quartiles. CONCLUSIONS: Nutrient-dense and healthy fat NP are associated with higher BMD at various bone sites, while the high-energy NP is inversely associated with BMD measures.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".