Prevalence of overweight And Obesity in Canadian Children: A Decade of Progress in the Canadian Community Health and Health Measure Surveys
Bibliographic record
Abstract
Abstract BACKGROUND: Previous studies using the Canadian Community Health Survey (CCHS) demonstrated an increase in the prevalence of overweight or obesity in Canadian children from 23.3% to 34.7% (1978– 2004) using the new 2010 WHO for Canada Growth Charts. OBJECTIVES: To better define temporal trends in overweight and obesity status, this study examines additional data from the Canadian Health Measures Survey (CHMS, 2009-2013) by applying current Canadian definitions based on WHO body mass index (BMI) thresholds and recently validated waist-circumference norms from NHANES III (1988-1994). Associations with variables such as family income, parent education and number of parents were also explored over this time frame. DESIGN/METHODS: Directly measured heights and weights were available for 14,014 children aged 3-19y from the decade 2004 to2013 in CCHS (n=8976)CHMS cycle 2 (n=2578) and CHMS cycle 3 (n= 2460). Z-scores for BMI, height, and weight were based on the 2014 WHO Growth Charts for Canada, including their new extension of weight-for-age beyond 10y. For waist circumference and waist-height ratios, we used new charts from the NHANES III reference population. Inverse probability survey weights were used to account for non-response and under-coverage. RESULTS: The sex distribution was similar in each survey cycle and ~ 80% were of white race/ethnicity. Using current WHO definitions based on BMI, we observed a decline in the proportion ‘overweight or obese’ from 30.7% (95%CI=29.4–32.0) to 27.0% (25.7–28.3, p<0.001) and a stabilizations in obesity rates at ~13%. Rates of overweight and obesity were higher in boys, non-whites, and older children. These trends persisted after regression adjustment for age, gender, and race-ethnicity. Although declining, median Z-scores for BMI, weight, and height were positive compared to the WHO reference population. Waist-circumference and waist-height ratio Z-scores were negative, with less central adiposity than American children in historic or contemporary NHANES cohorts. Temporal trends in overweight/obesity appear to vary with family income, educational achievement, and immigrant status. CONCLUSION: After a period of dramatic growth, both BMI-Z-scores and the prevalence of overweight or obesity appear to be declining in in Canadian children, attesting to progress against this important public health challenge.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.031 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".