Trends in prevalence of hypertension in Brazil : a systematic review with meta-analyisi
Bibliographic record
Abstract
Background: The prevalence of hypertension in emerging nations was scarcely described to date. In Brazil, many population-based surveys evaluated the prevalence in cities throughout the country. However, there is no populationbased nationwide study of prevalence of hypertension. In this study, we estimated the prevalence of hypertension for the country and analyzed the trends for the last three decades. Methods: Cross-sectional and cohort studies conducted from 1980 to 2010 were independently identified by two reviewers, without language restriction, in the PubMed, Embase, LILACS, and Scielo electronic databases. Unpublished studies were identified in the Brazilian electronic database of theses and in annals of Cardiology congresses and meetings. In total, 40 studies were selected, comprising 122,018 individuals. Results: Summary estimates of prevalence by the former WHO criteria (BP≥160/95 mmHg) in the 1980’s and 1990’s were 23.6% (95% CI 17.3–31.4%) and 19.6% (16.4–23.3%) respectively. The prevalence of hypertension by the JNC criteria (BP≥140/90 mmHg) in the 1980’s, 1990’s and 2000’s were 36.1% (95% CI 28.7–44.2%), 32.9% (29.9–36.0%), and 28.7% (26.2– 31.4%), respectively (P,0.001). In the 2000’s, the pooled prevalence estimates of self-reported hypertension on telephone inquiries was 20.6% (19.0–22.4%), and of self-reported hypertension in home surveys was 25.2% (23.3–27.2%). Conclusions: The prevalence of hypertension in Brazil seems to have diminished 6% in the last three decades, but it still is approximately 30%. Nationwide surveys by self-reporting by telephone interviews underestimate the real prevalence. Rates of blood pressure control decreased in the same period, corresponding currently to only one quarter of individuals with hypertension.
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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 | 0.013 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.027 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".