Calcium plus vitamin D supplementation and fat mass loss in female very low-calcium consumers: potential link with a calcium-specific appetite control
Bibliographic record
Abstract
This randomized, double-blind, placebo-controlled study was conducted to compare the effect of a 15-week weight-reducing programme ( -2900 kJ/d) coupled with a calcium plus vitamin D (calcium+D) supplementation (600 mg elemental calcium and 5 microg vitamin D, consumed twice a day) or with a placebo, on body fat and on spontaneous energy/macronutrient intake. Sixty-three overweight or obese women (mean age 43 years, mean BMI 32 kg/m2) reporting a daily calcium intake < 800 mg participated in present study. Anthropometric variables, resting energy expenditure and spontaneous energy intake were measured before and after the 15-week programme. The calcium+D supplementation induced no statistically significant increase in fat mass loss in response to the programme. However, when analyses were limited to very low-calcium consumers only (initial calcium intake < or =600 mg/d, n 7 for calcium+D, n 6 for placebo), a significant decrease in body weight and fat mass (P < 0.01) and in spontaneous dietary lipid intake (P < 0.05) was observed in the calcium+D but not in the placebo group. In very low-calcium consumers, change in fat mass was positively correlated with change in lipid intake. During the weight-reducing programme, a calcium+D supplementation was necessary in female overweight/obese very low-calcium consumers to reach significant fat mass loss that seemed to be partly explained by a decrease in lipid intake. We propose that this change in lipid intake could be influenced by a calcium-specific appetite control.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".