Intersecting risk factors for physical inactivity among Canadian adults
Bibliographic record
Abstract
Background: On average, 45% of Canadian adults meet the recommended 150 minutes per week of moderate-to-vigorous physical activity. This singular statistic masks a wide range of adherence levels among different groups within the population. The purpose of this paper is to determine how sex, age, and family arrangement intersect with known risk factors for physical inactivity to identify groups within the Canadian population most at risk of not meeting the physical activity recommendation. Methods: Using six combined cycles of the Canadian Health Measures Survey (from 2007 to 2019), this study examines how the percentage of Canadian males and females aged 18 to 79 years meeting the physical activity recommendation differs across sociodemographic, family arrangement, and health factors. Logistic regression was used to examine whether the association between specific factors and adherence to the physical activity recommendation differed by sex. Latent class analysis was used to identify sex-specific combinations of sociodemographic, family arrangement and health-related factors within the Canadian population that are associated with varying levels of adherence to the physical activity recommendation. Results: More males met the physical activity recommendation compared with females (49% versus 38%). Latent classes with the lowest adherence to the physical activity recommendation (19% among females and 29% among males) primarily included those who were single or married with no children and who had a high probability of having many risk factors for physical inactivity, including being older, having a lower education, having lower income, smoking, having central adiposity, and having poor or fair self-rated general health. Latent classes with the highest adherence to the physical activity recommendation (61% among females and 67% among males) primarily included individuals with no spouse and no children and who had a low probability of having any risk factors for physical inactivity. For females, an additional class (32% of which met the physical activity recommendation) comprised young single mothers who had several risk factors for physical inactivity, including having low income, smoking and having central adiposity. Interpretation: Understanding how risk factors for physical inactivity intersect with sex, age, and family arrangement may inform strategies aimed at increasing physical activity among those who are most vulnerable.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".