Hypertension Prevalence and Blood Pressure Levels in 6 European Countries, Canada, and the United States
Bibliographic record
Abstract
CONTEXT: Geographic variations in cardiovascular disease (CVD) and associated risk factors have been recognized worldwide. However, little attention has been directed to potential differences in hypertension between Europe and North America. OBJECTIVE: To determine whether higher blood pressure (BP) levels and hypertension are more prevalent in Europe than in the United States and Canada. DESIGN, SETTING, AND PARTICIPANTS: Sample surveys that were national in scope and conducted in the 1990s were identified in Germany, Finland, Sweden, England, Spain, Italy, Canada, and the United States. Collaborating investigators provided tabular data in a consistent format by age and sex for persons at least 35 years of age. Population registries were the main basis for sampling. Survey sizes ranged from 1800 to 23 100, with response rates of 61% to 87.5%. The data were analyzed to provide age-specific and age-adjusted estimates of BP and hypertension prevalence by country and region (eg, European vs North American). MAIN OUTCOME MEASURES: Blood pressure levels and prevalence of hypertension in Europe, the United States, and Canada. RESULTS: Average BP was 136/83 mm Hg in the European countries and 127/77 mm Hg in Canada and the United States among men and women combined who were 35 to 74 years of age. This difference already existed among younger persons (35-39 years) in whom treatment was uncommon (ie, 124/78 mm Hg and 115/75 mm Hg, respectively), and the slope with age was steeper in the European countries. For all age groups, BP measurements were lowest in the United States and highest in Germany. The age- and sex-adjusted prevalence of hypertension was 28% in the North American countries and 44% in the European countries at the 140/90 mm Hg threshold. The findings for men and women by region were similar. Hypertension prevalence was strongly correlated with stroke mortality (r = 0.78) and more modestly with total CVD (r = 0.44). CONCLUSIONS: Despite extensive research on geographic patterns of CVD, the 60% higher prevalence of hypertension in Europe compared with the United States and Canada has not been generally appreciated. The implication of this finding for national prevention strategies should be vigorously explored.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".