Cognitive aptitude, peers, and trajectories of marijuana use from adolescence through young adulthood

Electronic cigarette use in adolescence is associated with later cannabis use

BACKGROUND

Research is needed to determine whether e-cigarette use during adolescence is associated with higher odds of subsequent cannabis use, net of tobacco cigarette use and childhood confounders.

METHODS

Multivariable logistic regressions predicting using cannabis by age 17 based upon prospective, intergenerational data from 10,251 youth in a nationally representative UK birth cohort followed from infancy who had not used cannabis by age 14. The focal predictor is e-cigarette use by age 14 in the context of the potential confounder tobacco cigarette use. Regressions include sociodemographic background and risk factors assessed at age 11 (e.g., alcohol initiation, problem behaviors, parental and peer smoking) and during early childhood (e.g., maternal smoking during pregnancy, parental substance use).

RESULTS

Youth use of e-cigarettes by age 14 was associated with 2.8 times higher odds of subsequent cannabis use by age 17 [OR 2.75; 95% CI 1.82,4.15], net of tobacco cigarette smoking and childhood confounders. Similarly, use of e-cigarettes by age 14 was associated with 2.5 times higher odds [OR 2.46; 95% CI 1.48,4.08] of frequent cannabis use at age 17 (>10 times in prior year). If youth used both e-cigarettes and tobacco cigarettes by age 14, the probabilities of cannabis initiation were 75% and of frequent use was 25% by age 17, compared to probabilities of 23% and 6%, respectively, among youth who had used neither product.

CONCLUSIONS

Findings add to accumulating evidence that adolescent e-cigarette use is associated with higher odds of later cannabis initiation and frequent use, independent of tobacco cigarette use.

First-Year Trajectories of Medical Cannabis Use Among Adults Taking Opioids for Chronic Pain: An Observational Cohort Study

OBJECTIVE

To describe first-year trajectories of medical cannabis use and identify characteristics associated with patterns of use in a cohort of adults using opioids for chronic pain.

DESIGN

Latent class trajectory analysis of a prospective cohort study using data on the 14-day frequency of medical cannabis use.

SETTING

A large academic medical center and four medical cannabis dispensaries in the New York City metropolitan area.

SUBJECTS

Adults with chronic pain using opioids and newly certified for medical cannabis in New York between 2018 and 2020.

METHODS

Using latent class trajectory analysis, we identified clusters of participants based on the 14-day frequency of medical cannabis use. We used logistic regression to determine factors associated with cluster membership, including sociodemographic characteristics, pain, substance use, and mental health symptoms.

RESULTS

Among 99 participants, the mean age was 53 years; 62% were women, and 52% were White. We identified three clusters of medical cannabis use: infrequent use (n = 30, mean use = 1.5 days/14-day period), occasional use (n = 28, mean = 5.7 days/14-day period), and frequent use (n = 41, mean = 12.1 days/14-day period). Within clusters, use patterns did not vary significantly over 52 weeks. Differences were observed in two sociodemographic variables: Frequent (vs infrequent) use was associated with non-Hispanic White race/ethnicity (adjusted odds ratio 4.54, 95% confidence interval 1.49-14.29), while occasional (vs infrequent) use was associated with employment (adjusted odds ratio 13.84, 95% confidence interval 1.21-158.74).

CONCLUSIONS

Three clusters of medical cannabis use patterns emerged and were stable over time. Results suggest that structural factors related to race/ethnicity and employment may be major drivers of medical cannabis use, even among adults certified for its use.