Measuring Active Transportation on National Health Surveys in Canada From 1994 to 2020
Bibliographic record
Abstract
BACKGROUND: Active transportation (AT), described as self-powered modes of travel (eg, walking and cycling), is an important source of health-promoting physical activity. While AT behaviors have been measured on national health surveys in Canada for over 2 decades, historic prevalence has not been previously reported. We aimed to document the measures of AT on Canada's various national health surveys, examine AT over time, and interpret them within the context of evolving methods of assessment. METHODS: We compiled and summarized the questions used to measure AT among Canadians on 4 national health surveys: National Population Health Survey (1994-1998), Canadian Community Health Survey (2000-2020), Canadian Health Measures Survey (2007-2019), and the Health Behaviour in School-aged Children Study (2010-2018). Among youth and adults (12+ y), we summarized over time: (1) the prevalence of AT participation and (2) time spent in AT (in hours per week) among those who report any AT participation. Where possible, we reported separate estimates of walking and cycling and produced an aggregate estimate of total AT. We stratified results by age group and sex. RESULTS: Changes in AT survey questions over time and between surveys limit the interpretation and comparability of temporal trends. Nevertheless, a consistently higher proportion of females report walking, while a higher proportion of males report cycling. Irrespective of mode, males report spending more total time in AT. Participation in AT tends to decrease with age, with youth reporting the highest rates of AT and young adults often spending the most time in AT. CONCLUSIONS: Monitoring trends in AT can help assess patterns of behavior and identify whether promotion strategies are needed or whether population interventions are effective. Our evaluation of AT over time is limited by questions surveyed; however, consistent differences in AT by age and sex are evident over time. Moving forward, ensuring consistency of AT measurement over time is essential to monitoring this important behavior.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.019 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".