Hypertension in overweight and obese primary care patients is highly prevalent and poorly controlled
Bibliographic record
Abstract
BACKGROUND: Although the relationship between body weight and blood pressure (BP) is well established, there is a lack of data regarding the impact of obesity on the prevalence of hypertension in primary care practice. The objective of this study was to assess the prevalence of hypertension and the diagnosis, treatment status, and control rates of hypertension in obese patients as compared to patients with normal weight. METHODS: A cross-sectional point prevalence study of 45,125 unselected consecutive primary care attendees was conducted in a representative nationwide sample of 1912 primary care physicians in Germany (HYDRA). RESULTS: Blood pressure levels were consistently higher in obese patients. Overall prevalence of hypertension (blood pressure >/=140/90 mm Hg or on antihypertensive medication) in normal weight patients was 34.3%, in overweight participants 60.6%, in grade 1 obesity 72.9%, in grade 2 obesity 77.1%, and in grade 3 obesity 74.1%. The odds ratio (OR) for good BP control (<140/90 mm Hg) in diagnosed and treated patients was 0.8 (95% confidence interval [CI] 0.7-0.9) in overweight patients, 0.6 (95% CI 0.6-0.7) in grade 1, 0.5 (95% CI 0.4-0.6) in grade 2, and 0.7 (95% CI 0.5-0.9) in grade 3 obese patients. CONCLUSIONS: The increasing prevalence of hypertension in obese patients and the low control rates in overweight and obese patients document the challenge that hypertension control in obese patients imposes on the primary care physician. These results highlight the need for specific evidence-based guidelines for the pharmacologic management of obesity-related hypertension in primary practice.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".