The Relations Between Driving Behavior, Physical Activity, and Weight Status Among Canadian Adults
Bibliographic record
Abstract
BACKGROUND: Evidence regarding the relative contributions of physical activity (PA) and driving behavior on weight status is limited. This study examined the associations between driving and PA behavior and weight status among Canadian adults. METHODS: A random cross-section of Calgarian adults (n = 1026) completed a telephone-interview and a self-administered questionnaire. Weekly physical activity time, daily driving time, BMI, motor vehicle access, and demographic characteristics were captured. Logistic regression was used to estimate associations between driving minutes (0-209, 219-419, 420-839, 840-1679, and ≥ 1680 min/week), motor vehicle access, sufficient PA (210 min/week of moderate-intensity PA or 90 min/week of vigorous-intensity PA), and the likelihood of being 1) overweight/obese vs. healthy weight and 2) obese only vs. healthy/overweight. RESULTS: Compared with driving ≤ 209 min/week, driving 840 to 1679 min/week significantly (P < .05) increased the likelihood of being overweight/obese (OR 2.08). Insufficient PA was positively associated with being overweight/obese (OR 1.43). Each hour/week of driving was associated with a 1.6% reduction in the odds of achieving sufficient PA. A 3-fold increase (OR 3.73) in the likelihood of overweight was found among insufficiently active individuals who drove 210 to 419 min/week compared with sufficiently active individuals who drove ≤ 209 min/week. CONCLUSION: Interventions that decrease driving time and increase PA participation may be important for reducing weight among Canadian adults.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".