Physical activity fluctuations and body fat during adolescence
Bibliographic record
Abstract
OBJECTIVE: The objective of the study was to test the hypothesis that greater fluctuations in physical activity lead to greater increases in body fat during adolescence. METHODS: Seven hundred fifty-six adolescents in Montreal, Canada, aged 12-13 years at baseline, completed a 7-d physical activity recall questionnaire every 3 months over 5 years. Body mass index (BMI), waist circumference, and triceps and subscapular skinfold thickness were measured at baseline and at the end of follow-up. Subject-specific linear regressions, expressing physical activity as a function of time, were fitted and physical activity fluctuation scores were obtained by averaging the absolute values of regression residuals. The association between body fat after 5 years and the physical activity fluctuation score was assessed in linear regressions adjusting for baseline body fat, average number of physical activity sessions per week, diet and sociodemographic variables. RESULTS: Among boys, there were statistically significant positive associations between physical activity fluctuation and BMI (β, 95% confidence interval: 0.12, 0.02-0.21) and triceps skinfold (0.40, 0.17-0.63). The associations with waist circumference or subscapular skinfold were not statistically significant (0.22, -0.04-0.49; 0.13, -0.05-0.32, respectively). In girls, there were statistically significant negative associations between physical activity fluctuation and BMI (-0.12, -0.20 to -0.03), waist circumference (-0.54, -0.91 to -0.17), subscapular skinfold (-0.41, -0.56 to -0.26) and triceps skinfold (-0.22, -0.38 to -0.05). CONCLUSION: Physical activity fluctuations appear to affect body fat during adolescence. Sex-specific interventions may be needed given that greater physical activity fluctuations seem unfavourable for boys and beneficial for girls.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".