The relationships between health-related behaviours in the Canadian adult population
Bibliographic record
Abstract
BACKGROUND: Health-related behaviours such as physical inactivity, low fruit and vegetable intake, smoking, alcohol use, and inadequate sleep are significant predictors of adverse health outcomes. Health promotion strategies often focus on one behavior, though research suggests health-related behaviours tend to co-occur. The purpose of this study is to describe the relationships between health-related behaviours in the Canadian adult population. METHODS: Data from cycles 3 (2012-2013) and 4 (2014-2015) of the Canadian Health Measures Survey were pooled to describe health-related behaviours (current smoking status, high-risk alcohol use, fruit and vegetable intake, inadequate sleep, and physical activity) among adults according to sex, age group, household education, and income adequacy. Logistic regression was used to test for relationships between health-related behaviours. RESULTS: Findings indicated that adverse health-related behaviours co-occur frequently, with approximately half of Canadians reporting two or more adverse health-related behaviours. Overall, Canadian men were more likely to report adverse health-related behaviours compared to women, with the exception of inadequate sleep. Smoking status, fruit and vegetable intake, sleep and physical activity exhibited an income and education gradient. Sex-based patterns in grouping of behaviours were present such that adverse health-related behaviours were associated with current smoking among men and with high-risk alcohol use among women. CONCLUSION: Our findings suggest that health-related behaviours should be considered in both isolation and combination when designing intervention strategies. Sex-specific patterns of how these behaviours co-occur must also be taken into account.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".