Is there an Association between Dietary Micronutrients Intake and Bone Fractures among Malaysian Reproductive-Age Women? The PURE Malaysia Study
Bibliographic record
Abstract
Background: Bone fractures represent a significant health issue and impose a considerable burden on healthcare systems globally. However, data pertaining to bone fractures, especially among reproductive-age women in Malaysia, are very limited. Micronutrients like calcium, magnesium and phosphorus play vital roles in bone health, influencing bone mineral density and fracture risk. The objective of this study was to determine the prevalence of bone fractures among reproductive-age women and the association with dietary micronutrient intakes. Methods: In this cross-sectional study, a total of 1,730 participants of reproductive-age women from the Malaysia Prospective Urban and Rural Epidemiological (PURE) study were recruited. The participants’ dietary intakes were assessed using a validated semi-quantitative food frequency questionnaire (FFQ). Selected micronutrients in the participants’ diets were calculated using the Malaysian food composition and the US Department of Agriculture food composition databases. The association between micronutrient intakes, comorbidities and physical activity levels with bone fractures were evaluated to identify predictors of bone fractures among reproductive-age women. Results: The prevalence of bone fractures among Malaysian reproductive-age women was low (3.7%). The multiple logistic regression analysis showed that none of the micronutrients was associated with bone fractures. However, factors of diabetes and passive smoking in this study showed 2.6- and 4.0-times-higher odds of having bone fractures, respectively (AOR 2.580; 95% CI: 1.173–5.672) and (AOR 4.012; 95% CI: 2.265–7.107). Conclusions: It was found that the majority of women in this study were taking lower micronutrient intakes of calcium, magnesium, and vitamin K than the Malaysia recommended nutrient intakes (RNI). Although this study showed that a low micronutrient intake is not significantly associated with bone fractures, it is recommended that future studies focus on controlled trials or prospective data analyses to establish causal relationships and the optimal micronutrient requirements for maintaining strong and healthy bones in women of reproductive age.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".