Mental Disorders and Hypertension: Factors Associated With Awareness and Treatment of Hypertension in the General Population of Germany
Bibliographic record
Abstract
Objective: The aim of the present study was to identify the association between mental disorders and awareness and treatment of hypertension in a large representative community sample. Methods: The analysis was based on data from 4149 respondents, ages 18 to 65 years, from the German National Health Interview and Examination Survey, a nationally representative multistage probability survey conducted from 1997 to 1999. Mental disorders were assessed by a modified version of the Composite International Diagnostic Interview. Blood pressure was measured during the medical examination by a health examiner. Results: There was no general association between awareness of hypertension and affective, anxiety, and substance abuse/dependence disorders. Men with acknowledged but untreated hypertension more often experienced affective and substance abuse/dependence disorders than men with treated hypertension. These relationships were stable after adjustment for sociodemographic and clinical characteristics. Conclusions: Our results suggest that it is important to distinguish between treated and acknowledged but untreated hypertension when evaluating the associations between mental disorders and hypertension. BMI = body mass index; CI = confidence interval; CIDI-S = Composite International Diagnostic Screener; CIDI = Composite International Diagnostic Interview; CVD = cardiovascular diseases; DBP = diastolic blood pressure; GHS = German National Health Interview and Examination Survey; OR = odds ratio; SBP = systolic blood pressure.
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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 | 0.001 |
| 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".