Device-assessed physical activity and sedentary behaviors in Canadians with chronic disease(s): findings from the Canadian Health Measures Survey
Bibliographic record
Abstract
Background: Physical activity and sedentary behaviors are major determinants of quality of life in adults with one or more chronic disease(s). However, there are no Canadian representative population-based studies investigating objectively measured physical activity and sedentary behaviors in adults with and without chronic disease(s).Objective: To compare objectively measured physical activity and sedentary behaviors in a representative sample of Canadian adults with and without chronic disease(s). Methods: Data were obtained from the Canadian Health Measure Survey (CHMS) (2007-2013). Physical activity and sedentary behaviors were measured using accelerometry in Canadians aged between 35 and 79 years. Data are characterized as daily mean time spent in moderate to vigorous physical activity (MVPA), light physical activity (LPA), and sedentary behavior, as well as steps accumulated per day. Chronic diseases (chronic obstructive pulmonary disease, diabetes, heart diseases, cancer) were assessed via self-report diagnostic or laboratory data. Four weighted multivariable analyses of covariance comparing physical activity and sedentary behavior variables among adults without and with one or more chronic diseases were conducted.Results: In the total, 6270 CHMS participants were included. Analyses indicated that 23.9%, 4.9% and 0.5% had one, two, and three or more chronic diseases. Adults with two or three and more chronic diseases had significantly lower daily duration of MVPA and LPA, lower daily step counts, and higher daily duration of sedentary behavior compared to adults with no chronic diseases, with low effect sizes.Conclusions: Canadian multimorbid adults might benefit from targeted interventions to increase physical activity and reduce sedentary behaviors.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".