In one paragraphArticle in American journal of epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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.
2 · The registryThe 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.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
5 authors.
Katherine M KeyesDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, United States.ORCID 0000-0002-5624-021X Daniel GiovencoDepartment of Sociomedical Sciences, Mailman School of Public Health, Columbia University, New York, NY, United States.ORCID 0000-0001-6256-9612 Silvia S MartinsDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, United States.ORCID 0000-0003-3059-9993 Kara E RudolphDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, United States.ORCID 0000-0002-9417-7960 Funding
RESEARCH TRAINING PROGRAM IN PSYCHIATRIC EPIDEMIOLOGYT32MH013043 · NIMH · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI Katherine M. Keyes · 1985 to 2026
$11.7MSubstance Abuse Epidemiology Training Program (SAETP) at Columbia UniversityT32DA031099 · NIDA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI DEBORAH S HASIN, Silvia Saboia Martins · 2012 to 2026
$6.1MExamining the Synergistic Effects of Cannabis and Prescription Opioid Policies on Chronic Pain, Opioid Prescribing, and Opioid OverdoseR01DA045872 · NIDA · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI CERDA, MAGDALENA, MARTINS, SILVIA SABOIA · 2019 to 2023
$4.3MState-level opioid policies and policies that regulate substance use duringpregnancy: a mixed methods exploration of their effects on maternal and infantoutcomesR01DA053745 · NIDA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Silvia Saboia Martins, Morgan Mari Philbin · 2022 to 2026
$3.8MTemperature, shade, and adolescent psychopathology: understanding how place shapes healthR01MH128734 · NIMH · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI KEYES, KATHERINE M., RUNDLE, ANDREW G · 2021 to 2025
$3.4MSuicide as a contagion: modeling and forecasting emergent outbreaksR01MH121410 · NIMH · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI KEYES, KATHERINE M., SHAMAN, JEFFREY L · 2020 to 2024
$3.2MRole of disability and pain in opioid overdose: mechanism and risk mitigationR01DA053243 · NIDA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Kara Elizabeth Rudolph · 2022 to 2026
$3.1MDesign and analysis advances to improve generalizability of clinical trials for treating opioid use disorderR01DA056407 · NIDA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Kara Elizabeth Rudolph, Elizabeth A. Stuart · 2022 to 2026
$3.1MAssessing the impact, equity, and mechanisms of a novel policy intervention to reduce tobacco retailer density in communitiesR01CA269848 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Daniel Philip Giovenco · 2023 to 2026
$2.2MAs adolescent substance use declines, internalizing symptoms increase: identifying high-risk substance using groups and the role of social media, parental supervision, and unsupervised timeR01DA048853 · NIDA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI KEYES, KATHERINE M. · 2019 to 2023
$2.0MGeographic variation in the diverse tobacco retail environment and its impact on tobacco use disparitiesDP5OD023064 · OD · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GIOVENCO, DANIEL PHILIP · 2016 to 2020
$2.0MAge, period, and cohort effects on gender differences in alcohol use and alcohol use disorders in 47 national, longitudinally-followed cohortsR01AA026861 · NIAAA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI JAGER, JUSTIN O, KEYES, KATHERINE M. · 2018 to 2022
$1.9MNational Institute on Mental Health 5T32MH013043-52National Office of the Director 5DP5OD023064-06NCI NIH HHS 1R01CA269848-01A1NCI NIH HHS R01 CA269848NIAAA NIH HHS 5R01AA026861-05NIAAA NIH HHS R01 AA026861NIDA NIH HHS 5R01DA048853NIDA NIH HHS R00 DA042127NIDA NIH HHS R01 DA045872NIDA NIH HHS R01 DA048853NIDA NIH HHS R01 DA053243NIDA NIH HHS R01 DA053745NIDA NIH HHS R01 DA056407NIDA NIH HHS T32 DA031099NIH HHS DP5 OD023064NIMH NIH HHS R01 MH121410NIMH NIH HHS R01 MH128734NIMH NIH HHS T32 MH013043US National Institutes of Health
6 · The paper itselfAbstract
Prior studies estimating longitudinal associations between nicotine vaping and subsequent initiation of cannabis and other substances (eg, cocaine, heroin) have been limited by short follow-up periods, convenience sampling, and possibly inadequate confounding control. We sought to address some of these gaps using the nationally representative Population Assessment of Tobacco and Health Study (PATH) to estimate longitudinal associations between nicotine vaping and the initiation of cannabis or other substances among adolescents transitioning to adulthood from 2013 to 2019, adjusting for treatment-confounder feedback. Estimands like the longitudinal average treatment effect were not identified because of extensive practical positivity violations. Therefore, we estimated longitudinal incremental propensity score effects, which were identified. We found that reduced odds of nicotine vaping were associated with decreased risks of cannabis or other substance initiation; these associations strengthened over time. For example, by the final wave (2018-2019), cannabis and other substance initiation risks were 6.2 (95% CI, 4.6-7.7) and 1.8 (95% CI, 0.4-3.2) percentage points lower when odds of nicotine vaping were reduced to be 90% lower in all preceding waves (2013-2014 to 2016-2018), as compared with observed risks. Strategies to lower nicotine vaping prevalence during this period may have resulted in fewer young people initiating cannabis and other substances.
Indexed as
Substance-Related DisordersVapingAdolescentAdolescent BehaviorFemaleHumansLongitudinal StudiesMaleUnited StatesYoung Adultadolescentscannabisemerging adultsnicotinesubstance usevaping
Identifiers
PMID38988255
PMCPMC12055472
What OpenQuestion holds
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