Sex- and age-specific seasonal variations in physical activity among adults
Bibliographic record
Abstract
BACKGROUND: To examine seasonal variations in self-reported physical activity among an urban population of Calgarian adults. METHOD: Telephone surveys were conducted with two independent random cross-sectional samples of adults in summer and autumn 2007 (n=2199) and in winter and spring 2008 (n=2223). Participation and duration of walking for recreation (WR), walking for transportation (WT), moderate (MODPA) and vigorous physical activity (VIGPA) undertaken in a usual week were captured. Seasonal comparisons of participation related to these activities and sufficient MODPA (≥210 min/week) and VIGPA (≥90 min/week) physical activity were examined using logistic regression. RESULTS: Compared with winter, participation in WR was significantly (p<0.05) more likely in summer (OR 1.42), autumn (OR 1.35) and spring (OR 1.40), WT was more likely in autumn (OR 1.27), and MODPA was more likely in summer (OR 1.42). Achievement of sufficient MODPA was significantly more likely in summer (OR 1.80), autumn (OR 1.31) and spring (OR 1.24). Although there was no seasonal variation in sufficient VIGPA overall, variations in seasonal pattern among sub-populations were observed. Sex- and age-specific seasonal patterns in physical activity were also found. CONCLUSION: Measuring physical activity throughout the year, rather than at one time point, would more accurately monitor physical activity and assist in developing seasonally appropriate physical activity interventions. Moreover, in countries that experience extreme weather conditions, creating physical activity-friendly environments that help overcome these conditions might contribute to year-long physical activity participation.
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 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".