Sleep-Related Predictors of Risk for Alcohol Use and Related Problems in Adolescents and Young Adults

Alcohol and cannabis as sleep aids among adolescents and associations with sleep quality and problematic use

BACKGROUND

Using alcohol and cannabis as sleep aids is a growing concern among adolescents due to associated health risks. This study examined the prevalence of alcohol and cannabis self-medication practices among adolescents and explored the concurrent (Study I) and prospective (Study II) association with sleep quality and problematic use.

METHODS

One cross-sectional and one longitudinal (6-m onth interval) study were conducted. Participants comprised 1,121 Spanish adolescents aged 15 to 18 (57.1 % female) for Study I, and 221 for Study II (55.7 % female). Measures included sleep quality, pre-sleep cognitive and physical arousal, daytime sleepiness, and use of alcohol, cannabis, and self-medication. Multivariate analyses and Generalized Linear Mixed Models were applied.

RESULTS

In Study I, 8.6 % (n = 96) of adolescents reported past-m onth self-medication, which correlated with poor sleep, sleepiness, and higher pre-sleep physical arousal. Likewise, cannabis self-medication was associated with greater number of joints and problematic use. Study II showed a significant increase in self-medication rates after six months (from 6.3 % to 9.5 %). Regarding sleep, pre-sleep cognitive (OR = 1.3; 95 %CI = 1.0-1.8; p = 0.035) and physical arousal (OR = 1.1; 95 %CI = 1.0-1.1; p < 0.001) predicted alcohol self-medication. Poor sleep predicted cannabis self-medication (OR = 1.9; 95 %CI = 1.0-3.5; p = 0.047), which in turn increased the probability of poor sleep (OR = 2.2; 95 %CI = 1.0-4.8; p = 0.045) and problematic use (OR = 1.9; 95 %CI = 1.2-2.9; p = 0.003).

CONCLUSIONS

Self-medication practices are common among adolescents, with increasing trends over time. Adolescents rely on substances as sleep aids, worsening their sleep and increasing problematic use. Findings underscore the need for preventive strategies to enhance sleep quality and reduce substance use.

Time Spent on Social Media and the Risk of Substance Use Among US Adolescents

BACKGROUND AND OBJECTIVES

Adolescence is a period marked by increased risk of substance use and extensive social media engagement. Investigating the link between social media usage and substance use among adolescents is crucial for developing effective interventions and public health policies.

METHODS

This study utilized data from the Population Assessment of Tobacco and Health (PATH) study, focusing on adolescents aged between 12 and 17 years old who reported no substance use at Wave 2. Participants were followed from Wave 2 through Wave 5. At baseline (Wave 2), daily time spent on social media use was reported, and past 30-day (P30D) substance use (e.g., alcohol, tobacco products, marijuana, and non-med drug use) was assessed in subsequent waves (Waves 3-5). Generalized Estimating Equation (GEE) models were used to analyze self-reported daily time spent on social media and P30D substance use, adjusting for demographic and time-varying covariates.

RESULTS

The study included 4769 adolescents, with nearly half identifying as male (47.0%) and as non-Hispanic white (49.1%). Over 75% of participants reported spending at least 30 min on social media daily. In adjusted models, a dose-response relationship was observed between time spent on social media and the odds of subsequent tobacco use. For alcohol and marijuana use, the association followed a curvilinear pattern, with the highest odds among adolescents who spent 30 min to 3 h per day on social media. For nonmedical drug use, a significant association was observed only for those spending 3-6 h on social media daily, who had nearly twice the odds of nonmedical drug use, compared to non-users.

CONCLUSIONS

The present study is among the first to quantify the association between daily time spent on social media and the risk of using substances, such as alcohol, cannabis, tobacco products, and illicit drugs in the US adolescent cohort. Social media could be leveraged for targeted interventions and public health initiatives aimed at reducing substance use in this population.

Sleep Disturbances During Childhood Can Predict Adult Alcohol Consumption: A Longitudinal Cohort Study

BACKGROUND

Sleep disturbances (SDs) in childhood can negatively impact behavioral and emotional control, which can lead to an increase in risky behaviors, such as substance use, including alcohol.

METHODS

Data from 2,132 subjects who participated in the French TEMPO cohort from 1991 to 2018 were used. Sleep disturbances observed from ages 3 to 16 years defined our exposure. Alcohol use in adulthood was measured by alcohol consumption trajectories ascertained by using Group-Based Trajectory Modeling (GBTM) and constitutes our outcomes. The association between sleep disturbances in childhood and alcohol consumption trajectories was studied using multinomial logistic regression.

RESULTS

Sleep disturbances at ≤ 16 years were observed in 26.7% of participants. Three alcohol use trajectories were defined: "light-drinkers", "moderate-drinkers", and "heavy-drinkers". Accounting for many confounders, we found statistically significant associations between sleep disturbances and alcohol use trajectories. Using "light-drinkers" trajectory as reference, we found that compared to children with no sleep disturbances, those with sleep disturbances had a higher likelihood to be in the "moderate-drinkers" (ORa = 1.51; 95% CI = 1.09-2.10) and "heavy-drinkers" trajectory (ORa = 2.34; 95% CI = 1.27-4.34).

CONCLUSION

This study suggests that sleep disturbances in childhood are associated with an increased risk of higher alcohol consumption in adulthood and highlights the importance of healthy sleep, particularly in children and adolescents, to prevent the onset of certain risky behaviors.

Natural language processing in mixed-methods evaluation of a digital sleep-alcohol intervention for young adults

We used natural language processing (NLP) in convergent mixed methods to evaluate young adults' experiences with Call it a Night (CIAN), a digital personalized feedback and coaching sleep-alcohol intervention. Young adults with heavy drinking (N = 120) were randomized to CIAN or controls (A + SM: web-based advice + self-monitoring or A: advice; clinicaltrials.gov, 8/31/18, #NCT03658954). Most CIAN participants (72.0%) preferred coaching to control interventions. Control participants found advice more helpful than CIAN participants (X2 = 27.34, p < 0.001). Most participants were interested in sleep factors besides alcohol and appreciated increased awareness through monitoring. NLP corroborated generally positive sentiments (M = 15.07(10.54)) and added critical insight that sleep (40%), not alcohol use (12%), was a main participant motivator. All groups had high adherence, satisfaction, and feasibility. CIAN (Δ = 0.48, p = 0.008) and A + SM (Δ = 0.55, p < 0.001) had higher reported effectiveness than A (F(2, 115) = 8.45, p < 0.001). Digital sleep-alcohol interventions are acceptable, and improving sleep and wellness may be important motivations for young adults.

Do sleep and circadian characteristics predict alcohol use in adult drinkers?

BACKGROUND

While sleep and circadian rhythms are recognized contributors to the risk for alcohol use and related problems, few studies have examined whether objective sleep and circadian measures can predict future alcohol use in humans, and no such studies have been conducted in adults. This study examined whether any baseline sleep and/or circadian characteristics of otherwise healthy adults predicted their alcohol use over the subsequent 12 months.

METHODS

Participants (21-42 years) included 28 light and 50 heavy drinkers. At baseline, a comprehensive range of self-reported and objective sleep/circadian measures was assessed via questionnaires, wrist actigraphy, and measurement of dim light melatonin onset and circadian photoreceptor responsivity. Following this, the number of alcoholic drinks per week and binge drinking episodes per month were assessed quarterly over the subsequent 12 months. Anticipated effects of alcohol (stimulation, sedation, and rewarding aspects) were also assessed quarterly over the 12 months. Analyses included generalized linear mixed-effects models and causal mediation analysis.

RESULTS

Across the range of measures, only self-reported insomnia symptoms and a longer total sleep time at baseline predicted more drinks per week and binges per month (ps <0.02). There was a trend for the anticipated alcohol effect of wanting more alcohol at the 6-month timepoint to mediate the relationship between insomnia symptoms at baseline and drinks per week at 12 months (p = 0.069).

CONCLUSIONS

These results suggest that in otherwise healthy adults, insomnia symptoms, even if subclinical, are a significant predictor of future drinking, and appear to outweigh the influence of circadian factors on future drinking, at least in otherwise healthy adults. Insomnia symptoms may be a modifiable target for reducing the risk of alcohol misuse.