Obesity and the Prevalence and Management of Hypertension in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: We evaluated the association of body weight with the prevalence of hypertension by age and sex, as well as the treatment and control rates in obese and nonobese hypertensives among adults in the province of Ontario, Canada. METHODS: Cross-sectional, population-based survey of 2,510 adults, 20-79 years of age representative of the Ontario population of 7,996,653. Height, weight, arm and waist circumference, and blood pressure (BP) were directly measured by a trained nurse. RESULTS: Prevalence of obesity (body mass index (BMI) > or =30) increased from 16% in the 20-39 years age-group to 33% in the 60-79 years age group, similarly in men and women. Prevalence of hypertension increased as BMI and age increased: in the older age group (60+) from 36% in the lean to 51% for the overweight, 59% in the obese stage I, and 68% in the obese stage II/III. Prevalence of self-reported diabetes followed a similar pattern. Presence of other risk factors (diabetes and dyslipidemia) was independently associated with higher hypertension rates. Treatment and control rates of hypertension varied by BMI and gender. Lean hypertensive males had the lowest control rates (42%) and the highest systolic BPs compared to overweight (79%) and obese (64%) males. This difference was not apparent in females. CONCLUSIONS: Obesity is associated with markedly higher prevalence of hypertension and diabetes with age. If obesity per se is indeed a contributing factor, public health strategies to reduce the obesity epidemic would also markedly reduce the burden of hypertension and diabetes.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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 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".