Link between Physical Activity Type in Adolescence and Body Composition in Adulthood
Bibliographic record
Abstract
PURPOSE: We investigated whether type of physical activity (PA) (sports, running, and fitness/dance) engaged in during adolescence is associated with body composition in late adolescence or early adulthood. METHODS: Data were drawn from 631 participants in the Nicotine Dependence in Teens study, a prospective investigation of students ages 12-13 yr at inception. Self-report PA data were collected at baseline, in grade 7, and every 3-4 months thereafter during the 5 yr of high school (1999-2005). Anthropometric indicators (height, weight, waist circumference, triceps, and subscapular skinfold thickness) were measured at ages 12, 16, and 24 yr. On the basis of prior exploratory factor analysis, PA was categorized into one of three types (sports, running, and fitness/dance). Regression models estimated the association between number of years participating in each PA type (0-5 yr) during high school and body composition measures in later adolescence or early adulthood. RESULTS: In multivariable models accounting for age, sex, and parent education, more number of years participating in running during adolescence was associated with lower body mass index, waist circumference, and skinfold thickness in later adolescence and early adulthood (all P < 0.01). This association was no longer apparent in models that accounted for body composition at age 12 yr. The number of years participating in sports was positively associated with body mass index in early adulthood (P = 0.02), but fitness/dance was not statistically significantly associated with any outcome. CONCLUSION: Sustaining participation in running, but not in other PA types, during adolescence was related to lower body composition in later adolescence and adulthood. However, more research is needed to determine whether this association is attributable to a relationship between PA and body composition in early adolescence.
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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 | 0.000 | 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) | 0.001 | 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".