Calcium Supplementation Does Not Contribute to Constipation in Healthy Women
Bibliographic record
Abstract
PURPOSE: It is commonly suggested that calcium supplementation contributes to constipation; however, little research has explored the effects of calcium supplementation on gut motility. METHODS: In an 8-week, randomized, double-blind, crossover pilot study, healthy females (n = 27, aged 43.0 ± 10.6 years) received a split dose of 500 mg/d of elemental calcium from calcium carbonate or calcium phosphate each for 2 weeks, after a 2-week baseline and separated by a 2-week washout. Participants completed daily questionnaires of stool frequency, Bristol Stool Form Scale (BSFS), and supplement intake compliance. RESULTS: There were no differences among periods. Mean ± SE stool frequency averaged 1.3 ± 0.1 stools/d in each period. Participants reported 34%, 34%, 37%, and 29% of stools were indicative of slow transit or constipation (BSFS of 1 or 2) during baseline, calcium carbonate, calcium phosphate, and washout periods, respectively. Participants also reported from 6% to 10% of stools as fast transit or diarrhea (BSFS of 6 or 7) during the periods. CONCLUSION: This study suggests that neither calcium carbonate nor calcium phosphate, providing 500 mg/d of calcium, affects stool frequency or form. Although stool frequency was normal, the healthy females participating in the study experienced stools indicating slow (constipation) and fast (diarrhea) transit.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".