Cadmium-Induced Effects on Bone in a Population-Based Study of Women
Bibliographic record
Abstract
High cadmium exposure is known to cause bone damage, but the association between low-level cadmium exposure and osteoporosis remains to be clarified. Using a population-based women's health survey in southern Sweden [Women's Health in the Lund Area (WHILA) ] with no known historical cadmium contamination, we investigated cadmium-related effects on bone in 820 women (53-64 years of age) . We measured cadmium in blood and urine and lead in blood, an array of markers of bone metabolism, and forearm bone mineral density (BMD) . Associations were evaluated in multiple linear regression analysis including information on the possible confounders or effect modifiers: weight, menopausal status, use of hormone replacement therapy, age at menarche, alcohol consumption, smoking history, and physical activity. Median urinary cadmium was 0.52 microg/L adjusted to density (0.67 microg/g creatinine) . After multivariate adjustment, BMD, parathyroid hormone, and urinary deoxypyridinoline (U-DPD) were adversely associated with concentrations of urinary cadmium (p < 0.05) in all subjects. These associations persisted in the group of never-smokers, which had the lowest cadmium exposure (mainly dietary) . For U-DPD, there was a significant interaction between cadmium and menopause (p = 0.022) . Our results suggest negative effects of low-level cadmium exposure on bone, possibly exerted via increased bone resorption, which seemed to be intensified after menopause. Based on the prevalence of osteoporosis and the low level of exposure, the observed effects, although slight, should be considered as early signals of potentially more adverse health effects. Key words: biochemical bone markers, bone mineral density, cadmium, lead, osteoporosis, women.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".