At the Mercy of the Gods: Associations Between Weather, Physical Activity, and Sedentary Time in Children
Bibliographic record
Abstract
OBJECTIVES: This study investigated associations between weather conditions, physical activity, and sedentary time in primary school-aged children in Australia and Canada. METHODS: Cross-sectional data on 9-11-year-old children from the Australian (n = 491) and Canadian (n = 524) sites of the International Study of Childhood Obesity, Lifestyle and the Environment were used. Minutes of daily moderate-to-vigorous-physical-activity (MVPA) and sedentary time were determined from 7-day, 24-h accelerometry (Actigraph GT3X+ triaxial accelerometer). Day-matched weather data (temperature, rainfall, snowfall, relative humidity, wind speed) were obtained from the closest weather station to participants' schools. Covariates included parental highest education level, day type, sex, and BMI z-scores. Generalized mixed model analyses allowing for clustering of participants within schools were completed. Scatterplots with Loess curves were created for maximum temperature, MVPA, and sedentary time. RESULTS: Daily maximum temperature was significantly associated with MVPA and sedentary time in Australia (MVPA p = .05, sedentary p = .01) and Canada (p < .001, p = .001). Rainfall was negatively associated with MVPA in Australia (p < .001) and positively associated with sedentary time in Canada (p = .02). CONCLUSIONS: MVPA and sedentary time appear to be optimal when the maximum temperature ranges between 20°C and 25°C in both countries. The findings have implications for study design and interpretation for surveillance and intervention studies.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".