Health status, hospitalizations, day procedures, and physician costs associated with body mass index (BMI) levels in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Obesity is today's principal neglected public health problem, as a rising proportion of adults will succumb to the medical complications of obesity. However, little is known about the burden of obesity in adults living in Ontario. OBJECTIVES: To present an overview of the human and economic burden associated with BMI categories in Ontario, Canada, in terms of socio-demographics, comorbidities, health-related quality of life (HRQoL) and costs associated with hospitalization, same day procedures and physician visits. METHODS: The records of all Ontarians who participated in the Canadian Community Health Survey (CCHS), cycle 1.1 and provided consent to data linkage were linked to three administrative databases. Socio-demographic variables, medical characteristics, HRQoL, one year hospitalization, day procedure and physician costs were described per BMI category. Regression analyses were conducted to identify predictors of medical characteristics, HRQoL and costs. RESULTS: More than 50% of adult participants were either overweight or obese in 2000/2001. Obese adults, and to a lesser extent overweight adults, were more likely to report physician-diagnosed comorbid conditions, to use medications, and to have a lower HRQoL. After covariate adjustment, the hospitalization and physician costs were respectively 40% and 22% higher among obese and overweight adults than among normal-weight adults. No statistical cost differences were observed between normal and underweight individuals or between normal and overweight individuals. HRQoL was significantly lower in underweight and obese adults when compared to normal-weight individuals. CONCLUSIONS: Due to the large human and economic burden associated with under- or excess-weight, policies promoting healthy weight should remain a priority for governments and employers.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".