Observational studyMedicine2026
Nicotine metabolite ratio and clinically significant depressive symptoms in U.S. adults: A smoker-specific association.
Observational study in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Nicotine metabolite ratio (NMR) is a biomarker for the rate of nicotine metabolism and may be linked to depression, but evidence from large, representative populations is scarce. The role of smoking status as a potential effect modifier of this association is poorly understood. Identifying smoker-specific vulnerability may inform risk stratification and integration of mental-health screening within smoking-cessation settings. We aimed to investigate the association between NMR and clinically significant depressive symptoms in U.S. adults and among active smokers. We conducted a cross-sectional, observational analysis of 9287 adults (≥20 years) from the National Health and Nutrition Examination Survey 2013 to 2018. The exposure was the natural ln(NMR). The outcome was clinically significant depressive symptoms (Patient Health Questionnaire-9 [PHQ-9] score ≥10). We used survey-weighted modified Poisson regression to estimate relative risks with 95% confidence intervals; missing covariates were addressed using multiple imputation. Analyses were stratified by smoking status using a union definition (self-report or serum cotinine ≥3 ng/mL); robustness was evaluated using a stricter threshold of ≥10 ng/mL. In the overall population, ln(NMR) was not associated with depressive symptoms (per 1- standard deviation [SD] increase, RR 1.03; 95% CI 0.93-1.14). However, among smokers (union definition; cotinine ≥3 ng/mL), a higher ln(NMR) was associated with a higher prevalence of clinically significant depressive symptoms (RR per 1-SD, 1.15; 95% CI, 1.02-1.29). This finding was robust using a stricter cotinine cutoff of ≥10 ng/mL (RR per 1-SD, 1.16; 95% CI, 1.02-1.32). Restricted cubic splines revealed a near-linear dose-response relationship in smokers only. Significant interactions were observed across multiple covariates - including body mass index, poverty-income ratio, race/ethnicity, sex, smoking status, hypertension, diabetes, cotinine level, and stroke - after false discovery rate control. In this study, higher ln(NMR) was associated with a higher prevalence of clinically significant depressive symptoms among active smokers, but not in the overall U.S. adult. These findings highlight a smoker-specific vulnerability and suggest that NMR may be useful for risk stratification to support integrated smoking-cessation and mental-health screening; longitudinal and interventional studies are needed to clarify directionality and clinical utility.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.