Quantifying Long-term Patterns Of Sedentary Behavior In A Large Population-based Canadian Cohort
Bibliographic record
Abstract
PURPOSE: Despite growing research interest in sedentary behavior and health, few studies have examined long-term patterns of sedentary behavior within individuals. This study aims to describe patterns of sedentary behavior over 10 years among a large population-based Canadian cohort, and to explore predictors of patterns of sedentary behavior. METHODS: Data are from the Canadian Multi-center Osteoporosis Study (CaMos), a cohort study of adults randomly selected from the general population in 9 large Canadian cities. Respondents reported their sociodemographic information, lifestyle behaviors and disease history during telephone interviews. The baseline data collection was completed in 1997 (n=9418) and a similar questionnaire was administered at 5- (n=7647) and 10-year follow-up (n=5567). Total sitting time was calculated from domain-specific sitting questions at each time point and was dichotomized into ‘low’ (≤7 h/day) and ‘high’ (>7 h/day), based on recent meta-analytic evidence on sitting time and all-cause mortality. Respondents’ sitting patterns over 10 years were classified as ‘consistently high’, ‘consistently low’, ‘increased’, ‘decreased’, and ‘mixed’. Predictors of sedentary behavior patterns were explored using chi-square test, ANOVA, and polychotomous logistic regression. RESULTS: At baseline, the mean age was 62.1 years (SD=13.4). More than 69% were women, 50% completed high school education, and 16% had a university degree. The average sitting time was 6.9 hours/day at baseline, and 7.0 at 5- and 10-year follow-up (p for trend=0.12). Over the three time points, 23% reported consistently high sitting time, 22% reported consistently low sitting time, 14% decreased sitting, 17% increased sitting, and 24% had mixed patterns. Those who reported consistently high sitting time were more likely to be younger, men, university educated, full-time employed, and were more likely to be obese, and consistently report low levels of physical activity. CONCLUSIONS: This is one of the first studies to establish patterns of sedentary behavior within individuals over-time. This study found that risk classification of sedentary behavior among some adults changed over time. Future epidemiological studies on sitting and health should take into account long-term behavioral patterns.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".