The longitudinal relationship between cannabis use and hypertension
Bibliographic record
Abstract
Abstract Introduction The relationship between cannabis use and hypertension is not clear based on prior epidemiological studies. Thus, we examined this relationship over a 3‐year follow‐up period using a large population‐based sample from the USA. Methods Self‐reported longitudinal data were obtained from the National Epidemiologic Survey on Alcohol and Related Conditions Wave 1 (2001/2002) and Wave 2 (2004/2005). The sample was restricted to participants who did not report hypertension at baseline ( n = 26 844; 51% 40 years and older, 51% female, 71% white). χ 2 ‐tests were used to examine the distributions of confounders stratified by the incidence of hypertension. Thereafter, multiple logistic regression analyses were conducted to quantify the relationships between lifetime cannabis use, 12‐month cannabis use and 12‐month cannabis use frequency and incidence of hypertension while adjusting for confounders. Results Cannabis use was associated with a decreased incidence of hypertension in the unadjusted analyses. However, the relationships were confounded by age. After adjustment for all confounders, neither lifetime cannabis use (odds ratio, 95% confidence interval 0.89, 0.77 to 1.02), 12‐month cannabis use (0.78, 0.56 to 1.09) nor 12‐month cannabis use frequency [at least monthly use (0.85, 0.57 to 1.28) and less than monthly use (0.67, 0.40 to 1.11)] were associated above chance with the incidence of hypertension. Discussion and Conclusions Lifetime cannabis use, 12‐month cannabis use and 12‐month cannabis use frequency were not associated with the incidence of hypertension.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".