Patterns and predictors of sitting time over ten years in a large population-based Canadian sample: Findings from the Canadian Multicentre Osteoporosis Study (CaMos)
Bibliographic record
Abstract
Our objective was to describe patterns and predictors of sedentary behavior (sitting time) over 10 years among a large Canadian cohort. Data are from the Canadian Multicentre Osteoporosis Study, a prospective study of women and men randomly selected from the general population. Respondents reported socio-demographics, lifestyle behaviors and health outcomes in interviewer-administered questionnaires; weight and height were measured. Baseline data were collected between 1995 and 1997 (n = 9418; participation rate = 42%), and at 5- (n = 7648) and 10-year follow-ups (n = 5567). Total sitting time was summed across domain-specific questions at three time points and dichotomized into “low” (≤ 7 h/day) and “high” (> 7 h/day), based on recent meta-analytic evidence on time sitting and all-cause mortality. Ten-year sitting patterns were classified as “consistently high”, “consistently low”, “increased”, “decreased”, and “mixed”. Predictors of sedentary behavior patterns were explored using chi-square tests, ANOVA and logistic regression. At baseline (mean age = 62.1 years ± 13.4) average sitting was 6.9 h/day; it was 7.0 at 5- and 10-year follow-ups (p for trend = 0.12). Overall 23% reported consistently high sitting time, 22% consistently low sitting, 14% decreased sitting, 17% increased sitting with 24% mixed patterns. Consistently high sitters were more likely to be men, university educated, full-time employed, obese, and to report consistently low physical activity levels. This is one of the first population-based studies to explore patterns of sedentary behavior (multi-domain sitting) within men and women over years. Risk classification of sitting among many adults changed during follow-up. Thus, studies of sitting and health would benefit from multiple measures of sitting over time.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".