Associations of weather conditions with adolescents’ daily physical activity, sedentary time, and sleep duration
Bibliographic record
Abstract
Weather has been recognized as an environmental factor that affects daily activities. However, the effects of a humid subtropical climate on daily activity behavior are unclear. This study investigated the associations of weather conditions with physical activity (PA), sedentary time (ST), and sleep duration in a sample of 740 Hong Kong adolescents (mean age: 14.7 ± 1.6 years). The activPAL was used to assess the time spent during moderate to vigorous PA (MVPA), ST, and sleep. Weather data (e.g., temperature, relative humidity, rainfall amount, and sunlight duration) were obtained from the Hong Kong Observatory. Linear mixed models were constructed to examine the associations of weather conditions with the durations of MVPA, ST, and sleep on weekdays and weekend days, respectively. The analysis included valid data from 561 students (51.9% male). Among Hong Kong adolescents, a higher relative humidity was associated with reduced MVPA on weekdays and weekends, more ST on weekdays, and a longer sleep duration on weekends. A longer duration of sunlight induced less MVPA on weekends, but a longer sleep duration on weekdays. On weekends, higher temperatures correlated with increases in MVPA and ST but a decrease in sleep duration. Rainfall correlated inversely with sleep duration and positively with ST on weekdays. The associations of rainfall with MVPA exhibited opposite trends on weekdays and weekends. In summary, the relationships between weather conditions and daily activities exhibited day-type patterns. The findings suggest that environment-controlled indoor PA should be recommended during weather conditions of high relative humidity and higher temperatures.
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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 | 0.000 | 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".