Lifetime marijuana use in relation to insulin resistance in lean, overweight, and obese US adults
Bibliographic record
Abstract
BACKGROUND: Obese individuals are more likely to show insulin resistance (IR). However, limited population studies on marijuana use with markers of IR have yielded mixed results. The aim of this study was to examine the association of marijuana use with IR in US adults with different body mass index (BMI) status. METHODS: Data from the 2009 to 2016 National Health and Nutrition Examination Survey (NHANES) were abstracted. Minimal lifetime marijuana use was estimated using the duration of regular exposure and frequency of use. The association of marijuana use with both fasting insulin (FINS) and homeostasis model assessment of insulin resistance (HOMA-IR) was determined in lean, overweight, and obese individuals separately using generalized linear models. Interview weight years of data were used to account for the unequal probability of sampling and non-response. RESULTS: Of all 129 509 adults aged 18 to 59 years, 50.3% were women. In current obese marijuana consumers, mean FINS in those with less than four uses per month was 52% (95% confidence interval [CI] 19%-71%) lower than in never users. In former obese consumers with eight or more uses per month and who stopped marijuana use <12 months ago, mean FINS was 47% (95% CI 18%-66%) lower than in never users. Mean FINS in those who quit marijuana 12 to 119 and 120 months and more prior the survey was 36% (95% CI 7%-57%) and 36% (95% CI 10%-54%) lower, respectively. CONCLUSIONS: Marijuana use is associated with lower FINS and HOMA-IR in obese but not non-obese adults, even at low frequency of less than four uses per month. Former marijuana consumers with high lifetime use had significantly lower FINS levels that persisted, independent of the duration of time since last use.
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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".