Associations of protein intake and protein source with bone mineral density and fracture risk: A population-based cohort study
Bibliographic record
Abstract
UNLABELLED: High dietary protein has been hypothesized to cause lower bone mineral density (BMD) and greater fracture risk. Previous results are conflicting and few studies have assessed potential differences related to differing protein sources. OBJECTIVE: To determine associations between total protein intake, and protein intake by source (dairy, non-dairy animal, plant) with BMD, BMD change, and incident osteoporotic fracture. DESIGN/SETTING: Prospective cohort study (Canadian Multicentre Osteoporosis Study). Participants/Measures: Protein intake was assessed as percent of total energy intake (TEI) at Year 2 (1997-99) using a food frequency questionnaire (N=6510). Participants were contacted annually to ascertain incident fracture. Total hip and lumbar spine BMD was measured at baseline and Year 5. Analyses were stratified by group (men 25-49 y, men 50+ y, premenopausal women 25-49 y, and postmenopausal women 50+ y) and adjusted for major confounders. Fracture analyses were limited to those 50+ y. RESULTS: Intakes of dairy protein (with adjustment for BMI) were positively associated with total hip BMD among men and women aged 50+ y, and in men aged 25-49. Among adults aged 50+ y, those with protein intakes of <12% TEI (women) and <11% TEI (men) had increased fracture risk compared to those with intakes of 15% TEI. Fracture risk did not significantly change as intake increased above 15% TEI, and was not significantly associated with protein source. CONCLUSIONS: In contrast to hypothesized risk of high protein, we found that for adults 50+ y, low protein intake (below 15% TEI) may lead to increased fracture risk. Source of protein was a determinant of BMD, but not fracture risk.
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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 | 0.004 | 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 | 0.001 |
| 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".