Prevalence, Awareness, Treatment, and Control of Hypertension in China
Bibliographic record
Abstract
BACKGROUND: The present article aims to provide accurate estimates of the prevalence, awareness, treatment, and control of hypertension in adults in China. METHODS AND RESULTS: Data were obtained from sphygmomanometer measurements and an administered questionnaire from 141 892 Chinese adults >/=18 years of age who participated in the 2002 China National Nutrition and Health Survey. In 2002, approximately 153 million Chinese adults were hypertensive. The prevalence was higher among men than women (20% versus 17%; P<0.001) and was higher in successive age groups. Overall, the prevalence of hypertension was higher in urban compared with rural areas in men (23% versus 18%; P<0.01) and women (18% versus 16%; P<0.001). Of the 24% affected individuals who were aware of their condition, 78% were treated and 19% were adequately controlled. Despite evidence to suggest improved levels of treatment in individuals with hypertension over the past decade, compared with estimates from 1991, the ratio of controlled to treated hypertension has remained largely unchanged at 1:4. CONCLUSIONS: One in 6 Chinese adults is hypertensive, but only one quarter are aware of their condition. Despite increased rates of blood pressure-lowering treatment, few have their hypertension effectively controlled. National hypertension programs must focus on improving awareness in the wider community, as well as treatment and control, to prevent many tens of thousands of cardiovascular-related deaths.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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 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".