Association Between Sedentary Behavior, Physical Activity, and Obesity: Inactivity Among Active Kids
Bibliographic record
Abstract
INTRODUCTION: Sedentary behavior and physical activity are not mutually exclusive behaviors. The relative risk of overweight for adolescents who are highly sedentary and highly physically active is unclear. A better understanding of the relationship between sedentary behaviors, physical activity, and body mass index (BMI) would provide insight for developing interventions to prevent or reduce overweight. METHODS: Using the physical activity module of the School Health Action, Planning and Evaluation System (SHAPES), we collected data from 25,060 students in grades 9 through 12 from 76 secondary schools in Ontario, Canada. Sex-specific logistic regression analyses were performed to examine how BMI, weight perceptions, social influences, team sports participation, and smoking behavior were associated with being 1) high active-high sedentary, 2) low active-low sedentary, and 3) low active-high sedentary. RESULTS: Low active-high sedentary boys were more likely to be overweight than high active-low sedentary boys (adjusted odds ratio [AOR], 1.60; 95% confidence interval [CI], 1.01-2.58). When compared with high active-low sedentary girls, girls who were low active-high sedentary (OR, 2.24; 95% CI, 1.23-4.09) or high active-high sedentary (OR, 1.91; 95% CI, 1.01-3.61) were more likely to be overweight. CONCLUSION: Sedentary behavior may moderate the relationship between physical activity and overweight. Developing a better understanding of sedentary behavior in relation to physical activity and overweight is critical for preventing and reducing overweight among youth.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".