Quantifying the Impact of Obesity Category on Major Chronic Diseases in Canada
Bibliographic record
Abstract
Adverse health effects differ with various levels of obesity, but limited national data existed previously for the Canadian population. We examined the associations of sociodemographic and behavioral factors with obesity levels in Canada, and measured the impact of each level on major chronic diseases. Data were extracted from the 2003 Canadian Community Health Survey. We grouped overweight/obese participants aged 18 years and over into four levels based on body mass index (BMI, kg/m2): overweight (25.0 C29.9), class I obesity (30.0 C34.9), class II obesity (35 C39.9), and class III obesity (extreme/clinical obesity, BMI > or = 40.0). We used logistic regression models to identify potential risk factors for the obesity levels and to estimate adjusted odds ratios (ORs) for major chronic diseases related to each level. We calculated population attributable risks (PARs) to help understand the impact of obesity levels on these chronic diseases. The overall prevalence of obesity was 16.2% in men and 14.6% in women, and the prevalence of obesity III was 1.0% in men and 1.4% in women. All levels of obesity increased with age, but then decreased in elderly participants. The prevalence of diabetes, hypertension, heart disease, arthritis, and asthma increased with increasing BMI level, and the highest values appeared in participants at the obesity III level. PAR was highest in the obesity III group for hypertension, followed by diabetes, and lowest for heart disease. When correlated with risk factors, fewer statistically significant ORs, comparing to the normal weight category, appeared for obesity II and III levels than for overweight and obesity I. ORs for the combination of low education level, infrequent exercise, and low household income rose significantly with BMI levels until the obesity II level, and in obesity III level, the OR remained at the same level as for obesity II, most significantly in women. These results suggest that the impact of obesity on Canadians inverted exclamation mark health should be studied and dealt with by obesity level. The greatest impact of clinical obesity was on hypertension and diabetes control in Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".