Evidence Brief – Trends and projections of obesity among Canadians
Bibliographic record
Abstract
The prevalence of obesity, defined as body mass index (BMI) of 30 kg/m2 or higher for adults and as 2 standard deviations above the World Health Organization growth standard mean for children, has increased in many parts of the world. Obese adults are at an increased risk of certain chronic conditions, including hypertension, type 2 diabetes, cardiovascular diseases and some cancers, and of premature death. Obese children have increased cardiometabolic risk, including dyslipidemia, insulin resistance and elevated blood pressure. Excess childhood body weight that continues into adulthood can affect quality of life, educational attainment and earnings over the lifecourse. The Public Health Agency of Canada has projected an annual direct health care cost (including physician, hospitalization and medication costs) of those categorized as obese in Canada in constant 2001 Canadian dollars. Calculated as $7.0 billion in 2011, this annual direct health care cost is projected to rise to $8.8 billion by 2021, based on simulated average direct health care costs, which are higher among the obese ($2,283) than the overweight ($1,726), the underweight ($1,298) and those at normal weight ($1,284). Canadian estimates from 2006 and 2008 that used different methodologies place the annual economic burden (direct and indirect costs) of obesity between $4.6 billion and $7.1 billion. The purpose of this evidence brief is to show current Canadian obesity prevalence rates and estimates for the future using objectively measured height and weight to calculate BMI. The use of objectively measured height and weight to derive BMI is strongly recommended, especially for children and adolescents, as self- or proxy-reported height and weight tend to underestimate actual weight and consequently BMI and obesity prevalence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".