Lifetime Average Cannabis Use in Relation to Hypertriglyceridemic Waist Phenotype in U.S. Adults: A Population-Based Cross-Sectional Study
Bibliographic record
Abstract
Background and Aims: With a growing number of states legalizing recreational or medical cannabis, prevalence of cannabis users is expected to markedly increase in the future. We aim to determine the association between lifetime cannabis use and the likelihood for hypertriglyceridemic waist (HTGW+/+) phenotype in U.S. adults. Methods: We abstracted data from the National Health and Nutrition Examination Survey from 2009 to 2016. We estimated the minimal lifetime cannabis use using the duration of regular exposure and the frequency of use. Outcomes were HTGW+/+ phenotype, defined as being waist circumference >90 cm (for men) or 85 cm (for women), and serum fasting triglycerides ≥177 mg/dL. We used multiple logistic regression models to estimate the adjusted odds ratio (AOR) and 95% confidence intervals (CIs). Results: Of the 47,364 adults included, 48.5% were women. The prevalence of HTGW+/+ phenotype was 11.7%. Current, but not former, users were less likely to show HTGW+/+ phenotype. Current cannabis users with greater or equal to four uses per week showed a significant lower likelihood for HTGW+/+ than those who never used cannabis (AOR 0.46 [95% CI, 0.22–0.97]). HTGW+/+ phenotype was associated with neither two to three uses per week (AOR 1.12 [95% CI, 0.40–3.12]) nor less than two uses per week (AOR 0.56 [95% CI, 0.18–1.73]). Conclusions: Average lifetime frequency of greater or equal to four cannabis uses per week is linked to lower odds of HTGW+/+ in current users. Former use is not associated with HTGW+/+.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".