Association of breakfast consumption with body mass index and prevalence of overweight/obesity in a nationally-representative survey of Canadian adults
Bibliographic record
Abstract
BACKGROUND: This study examined the association of breakfast consumption, and the type of breakfast consumed, with body mass index (BMI; kg/m(2)) and prevalence rates and odds ratios (OR) of overweight/obesity among Canadian adults. These associations were examined by age group and sex. METHODS: We used data from non-pregnant, non-lactating participants aged ≥ 18 years (n = 12,377) in the Canadian Community Health Survey Cycle 2.2, a population-based, nationally-representative, cross-sectional study. Height and weight were measured, and BMI was calculated. Breakfast consumption was self-reported during a standardized 24-h recall; individuals were classified as breakfast non-consumers, consumers of breakfasts that included ready-to-eat cereal (RTEC) or as other breakfast consumers. Mean BMI and prevalence and OR of overweight/obesity (BMI ≥ 25) were compared among breakfast groups, with adjustment for sociodemographic variables (including age, sex, race, marital status, food security, language spoken at home, physical activity category, smoking, education level and supplement use). RESULTS: For the entire sample, mean BMI was significantly lower among RTEC-breakfast consumers than other breakfast consumers (mean ± SE 26.5 ± 0.2 vs. 27.1 ± 0.1 kg/m(2)), but neither group differed significantly from breakfast non-consumers (27.1 ± 0.3 kg/m(2)). Similar results were seen in women only, but BMI of men did not differ by breakfast category. Overweight/obesity prevalence and OR did not differ among breakfast groups for the entire sample or for all men and women separately. When examined by sex and age group, differences were inconsistent, but tended to be more apparent in women than men. CONCLUSION: Among Canadian adults, breakfast consumption was not consistently associated with differences in BMI or overweight/obesity prevalence.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 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".