Eating Attitudes and Habitual Calcium Intake in Peripubertal Girls Are Associated with Initial Bone Mineral Content and Its Change over 2 Years
Bibliographic record
Abstract
This 2-year prospective study examined associations among bone mineral acquisition and physical, maturational, and lifestyle variables during the pubertal transition in healthy girls. Forty-five girls, initially 10.5+/-0.6 years, participated. Body composition and bone mineral content (BMC) at the spine and total body (TB) were assessed at baseline and annually thereafter using dual-energy X-ray absorptiometry (DXA). Nutrient intakes were assessed using 3-day diet records and a calcium food frequency questionnaire (FFQ), physical activity by questionnaire, sexual maturation using Tanner's stages of breast and pubic hair maturation, growth by height and weight, and eating attitudes using the children's Eating Attitudes Test (Children's EAT). Mean children's EAT subscale scores (dieting, oral control [OC], and bulimia) were stable over time. Median split of OC subscale scores was used to form high and low OC groups. Groups had similar body composition, dietary intake, activity, and Tanner stage at baseline and 2 years. Using height, weight, and Tanner breast stage as covariates, girls with low OC scores had greater TB BMC at baseline (1452+/-221 g vs. 1387+/-197 g; p = 0.030) and 2 years (2003+/-323 g vs. 1909+/-299 g; p = 0.049) and greater lumbar spine (LS) BMC at 2 years (45.2+/-8.8 g vs. 41.2+/-9.6 g; p = 0.042). In multiple regression analysis, OC score predicted baseline, 2 years, and 2-year change in TB and spinal BMC, contributing 0.9-7.6% to explained variance. Calcium intake predicted baseline, 2 years, and 2-year change in TB BMC, explaining 1.6-5.3% of variance. We conclude that both OC and habitual calcium intake may influence bone mineral acquisition.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".