Trends in obesity across Canada from 2005 to 2018: a consecutive cross-sectional population-based study
Bibliographic record
Abstract
Background: Obesity is increasingly prevalent worldwide and is becoming an epidemic in many countries, including Canada. We sought to describe and analyze temporal obesity trends in the Canadian adult population from 2005 through 2018 at the national and provincial or territorial levels. Methods: We conducted a consecutive, cross-sectional study using data from 7 sequential Canadian Community Health Survey (CCHS) cycles (2005 to 2017/18). We included data from Canadian adults (age ≥ 18 yr) who participated in at least 1 of the 7 consecutive CCHS cycles and who had body mass index values (calculated by Statistics Canada based on respondents’ self-reported weight and height). Obesity prevalence (adjusted body mass index ≥ 30) was a primary outcome variable. We analyzed temporal trends in obesity prevalence using Pearson χ2 tests with Bonferroni adjustment, and the Cochran–Armitage test of trend. Results: We included data from 746 408 (403 582 female and 342 826 male) CCHS participants. Across Canada, the prevalence of obesity increased significantly between 2005 and 2017/18, from 22.2% to 27.2% (p < 0.001). We observed increases across both sexes, all age groups and all Canadian provinces and territories (p < 0.001). In 2017/18, the prevalence of obesity was higher among males than females (28.9% v. 25.4%; p < 0.001); the prevalence among adults aged 40–69 years exceeded 30%. In 2017/18, Newfoundland and Labrador had the highest prevalence (39.4%), and British Columbia had the lowest (22.8%) prevalence of obesity. Over the 14-year study period, Quebec and Alberta exhibited the largest relative increases in obesity. Interpretation: In 2017/18, more than 1 in 4 adult Canadians lived with obesity, and from 2005 to 2017/18, the prevalence of obesity among adults in Canada increased substantially across sexes, age groups and all Canadian provinces and territories to 27.2%. Our findings call for urgent actions to identify, implement and evaluate solutions for obesity prevention and management in all Canadian provinces and territories.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 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) | 0.001 | 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".