Major Depression as a Risk Factor for High Blood Pressure: Epidemiologic Evidence From a National Longitudinal Study
Bibliographic record
Abstract
Objective: To determine whether major depression (MD) leads to an increased risk of new-onset high blood pressure diagnoses. Methods: The data source was the Canadian National Population Health Survey (NPHS). The NPHS included a short-form version of the Composite International Diagnostic Interview (CIDI-SF) to assess MD and collected self-report data about professionally diagnosed high blood pressure and the use of antihypertensive medications. The analysis included 12,270 respondents who did not report high blood pressure or the use of antihypertensive medications at a baseline interview conducted in 1994. Proportional hazards models were used to compare the incidence of high blood pressure in respondents with and without MD during 10 years of subsequent follow-up. Results: After adjustment for age, the risk of developing high blood pressure was elevated in those with MD. The hazard ratio was 1.6 (95% Confidence Interval = 1.2–2.1), p = .001, indicating a 60% increase in risk. Adjustment for additional covariates did not alter the association. Conclusions: MD may be a risk factor for new-onset high blood pressure. Epidemiologic data cannot definitely confirm a causal role, and the association may be due to shared etiologic factors. However, the increased risk may warrant closer monitoring of blood pressure in people with depressive disorders. MD = major depression; HR = hazard ratio; CI = Confidence Interval; NPHS = National Population Health Survey; OR = odds ratio; CARDIA Study = Coronary Artery Risk Development in Young Adults; CES-D = Center for Epidemiologic Studies Depression Rating Scale; CIDI-SF = Composite International Diagnostic Interview Short Form.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".