Calcium and Body Fat in Peripubertal Girls: Cross‐sectional and Longitudinal Observations
Bibliographic record
Abstract
OBJECTIVE: The objective was to investigate whether calcium intake is independently associated with body fat in peripubertal girls. RESEARCH METHODS AND PROCEDURES: A total of 45 healthy premenarcheal girls (initially 10.5 +/- 0.6 years of age) completed a 2-year prospective observational study. Percent body fat and trunk fat (by DXA), height, weight, maturational stage, and eating attitudes (children's Eating Attitudes Test [EAT]) were measured at baseline and at 1 and 2 years. Physical activity (by questionnaire) and calcium intake (by calcium-specific food frequency questionnaire and 3-day food records) were assessed at 6-month intervals. RESULTS: Girls with 2-year mean calcium intake below and above the median had similar age, height, lean mass, and maturational stage at baseline, but girls below the median had significantly higher baseline percentage body fat (29.3 +/- 10.3% vs. 22.0 +/- 6.8%, p < 0.01) and trunk fat (24.2 +/- 10.6% vs. 15.8 +/- 6.8%, p < 0.01). However, differences were no longer significant when covariates (most notably children's EAT dieting score) were considered. Regression analysis revealed that dieting score was a consistent positive predictor of percentage body and trunk fat at all cross-sectional time-points, accounting for >20% of the variance, but did not predict 2-year change in percentage fat. Calcium intake did not enter longitudinal regression equations for 2-year change in percentage fat. DISCUSSION: In this group of girls, an inverse cross-sectional association between calcium intake and body fat appeared to result from avoidance of foods high in calcium by girls who were concerned about their body weight or shape. Calcium intake was not associated with change in fat over time.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".