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. Author manuscript; available in PMC: 2024 Sep 1.
Published in final edited form as: Addict Behav. 2023 Apr 12;144:107722. doi: 10.1016/j.addbeh.2023.107722

Bidirectional associations between sleep and addiction across populations: Introduction to the special issue

Mary Beth Miller a,*, Aesoon Park b
PMCID: PMC10461131  NIHMSID: NIHMS1923087  PMID: 37084566

1. Introduction

On average, humans spend one-third of their lives asleep, which is roughly the equivalent of 25 years for an adult in the United States (US). Unfortunately, one-third of US adults and ~10% of adolescents experience insomnia at some point in their lives (de Zambotti et al., 2018; Ohayon, 2011). The prevalence of insomnia has increased significantly in recent years, particularly since the COVID-19 pandemic (Ford et al., 2015; Morin et al., 2021). Rates of sleep disturbance are particularly high among those who use substances, with 70–74% of those in treatment for alcohol or other drug use reporting distress related to their sleep (Chaudhary et al., 2015; Roncero et al., 2012). Approximately 30% of those with insomnia also report using alcohol or other drugs to help with sleep (Roehrs et al., 2002), creating a paradox of substance use to help with sleep that ultimately makes sleep worse.

This special issue highlights the bidirectional nature of sleep and addictive behaviors across populations. We use the term “sleep” to characterize a range of sleep behaviors and experiences, including difficulty falling or staying asleep (“insomnia symptoms”), subjective sleep quality, daytime sleepiness/fatigue, inappropriate sleep timing, and inadequate sleep duration (Buysse, 2014). Likewise, addictive behaviors are assessed in terms of frequency, quantity, and impact or harm (e.g., alcohol-related problems, quality of life) (Shorter et al., 2021). The multidimensional nature of both sleep and addictive behavior is important to consider when interpreting findings and applying them to future work.

1.1. Alcohol use

Five studies in this issue focused on sleep and alcohol use, and two highlight the importance of multidimensional assessment of both constructs. Boness et al. (2022) examined cross-sectional associations between sleep characteristics and criteria for Alcohol Use Disorder (AUD) in a non-clinical sample of young adults (21–30y) who drink. Circadian factors (e.g., evening preference, mid-sleep timing) and shorter total sleep time were associated with hazardous use and role interference, with some indication that difficulty falling asleep may be linked to social/interpersonal problems. This study is novel in its multidimensional assessment of both sleep and alcohol use and emphasizes that sleep/alcohol associations depend on the dimensions assessed. Consistent with this idea, Miller et al. (2022) found that alcohol use was only associated with physiological consequences (e.g., blackout, pass out, nausea, hangover; not doing impulsive things or missing work), and only among college students reporting low (vs. high) symptoms of insomnia. Again, this indicates that specific sleep characteristics may have different associations with different types of alcohol-related outcomes.

Two studies measured sleep/alcohol associations prospectively over time. In a sample of 2,995 young adults (18–24y), Troxel et al. (2022) found that “good sleepers” (those reporting healthy sleep in all dimensions) reported lower levels of alcohol use and fewer alcohol-related consequences than “poor sleepers” (those reporting unhealthy sleep in all dimensions), and they reported less steep increases in consequences over five years. Graupensperger et al. (2022) asked young adults reporting simultaneous alcohol and cannabis use to complete five 14-day assessment bursts (70 days total) across a 16-month time span. They found that time in bed was associated with alcohol craving at the within-person daily and burst as well as between-person levels. Actual alcohol use was also greater during assessment bursts of less-than-typical time in bed, although day- and person-level associations with drinking quantity were not significant. Both of these studies link sleep to alcohol use outcomes – not just between-persons, but also within-persons over time.

Using data from the Canadian Longitudinal Study on Aging (N = 30,097), Hussain et al. (2022) found that participants reporting daily heavy drinking (past 30 days) and binge drinking also reported higher rates of insomnia symptoms and slightly higher odds of short sleep duration (<6 h) than those who did not drink; but they did not report significantly different satisfaction with sleep in adjusted models. These patterns were similar for men and women, although weighted rates of sleep dissatisfaction and insomnia symptoms were higher in women than men.

1.2. Alcohol, sleep, and mental health

Two studies tested sleep’s compounding role in associations between alcohol use and mental health. In a large, cross-sectional sample of college students (N = 2,676), Lehinger et al. (2023) found that post-traumatic stress disorder (PTSD) symptoms were associated with typical/peak drinking quantity only among drinkers reporting poor (vs good) sleep quality. Importantly, however, the association between PTSD symptoms and peak drinking quantity was only significant among men (not women) with poor sleep quality; and the rate of clinically significant PTSD symptoms in the sample was low (~10%). Davis et al. (2022) attempted to tease apart the temporality of these PTSD/alcohol/sleep associations in a sample of post-9/11 Veterans, 30% of whom screened positive for PTSD, over 12 months. Interestingly, they found that higher (vs. lower) proportional levels of insomnia were associated with increases in PTSD (but decreases in frequency of alcohol use) over time. In the dynamic portions of their model, increases in insomnia were associated with increases in alcohol use (but not PTSD); increases in alcohol use were associated with increases in insomnia (but not PTSD); and increases in PTSD were associated with increases in both insomnia and alcohol use. Although causality cannot be determined in either of these studies, both suggest that poor sleep compounds and/or facilitates the negative health outcomes of other mental health symptoms.

1.3. Nicotine

Three studies in this special issue tested associations between sleep and nicotine use. In a racially diverse sample of adolescents (84% Latinx), Sutherland et al. (2022) found no significant prospective associations between amygdala-insula resting-state functional connectivity (rsFC), sleep problems, or depressive symptoms and frequency of e-cigarette use 15 months later. However, baseline amygdala-insula rsFC was associated with increased sleep problems at 15 months. In a racially diverse sample of adults who smoke cigarettes (48% Black, age M = 41y), Chana et al. (2023) found cross-sectional associations between everyday discrimination, depressive symptoms, nicotine withdrawal, and insomnia symptoms. These studies provide preliminary data linking sleep and nicotine use/withdrawal in racial/ethnic minority groups. This is supported by Hussain et al. (2022)’s study of Canadian older/middle-aged adults, which also found higher rates of insomnia and short sleep duration among daily smokers.

1.4. Cannabis

Six articles tested associations between sleep and cannabis use. Two of these tested cross-sectional associations in diverse groups. Keen et al. (2022) examined sleep disturbance as a function of cannabis use disorder severity among students at a historically Black university; while Belloir et al. (2022) tested associations between everyday discrimination, problematic drug use (primarily cannabis use), and sleep disturbance among transgender and nonbinary adults.

The remaining studies tested longitudinal associations. In a study of 407 racially-diverse ninth-to-eleventh graders, Goodhines et al. (2022) found that 8% of all participants and 31% of past-year cannabis users reported using cannabis specifically to help with sleep. Importantly, use of cannabis as a sleep aid was associated with increases in cannabis dependence symptoms and odds of binge drinking and cigarette use over one year, without the intended benefits in insomnia symptoms or sleep duration. Graupensperger et al. (2022) failed to find within-person associations between sleep and actual cannabis use in their study of young adults (18–25y) reporting simultaneous alcohol and cannabis use, although participants did report stronger craving for cannabis following nights of shorter time in bed. Similar to what they found for alcohol use, Troxel et al. (2022) found young adults reporting “good sleep” reported less frequent cannabis use and fewer cannabis-related consequences than those reporting “poor sleep.” However, there were no significant group differences in trajectories of cannabis use or consequences over time. Berey et al. (2022) examined prospective associations between sleep and cannabis use among post-9/11 Veterans. Poor sleep quality was indirectly associated with greater cannabis use frequency and quantity (but not problems) at one year through its association with cannabis reinforcing value at 6 months.

1.5. Opioids & benzodiazepines

Two studies examined associations between sleep and opioid or benzodiazepine use. In a large, nationally representative sample of adolescents and young adults, Short et al. (2023) tested bidirectional associations between sleep and (a) prescription opioid and (b) benzodiazepine use. Increases in insomnia symptoms were associated with a small increase in the likelihood of prescription opioid (but not benzodiazepine) misuse 8 years later; and both prescription opioid and benzodiazepine misuse were associated with small increases in insomnia symptoms. Given the national representation and potential duration of associations, continued research in this area is warranted.

Berro et al. (2022) investigated the acute effects of three medications for opioid use disorder (methadone, buprenorphine, and naltrexone) on actigraphy-assessed sleep parameters in male rhesus monkeys. Naltrexone was the only medication to improve both sleep onset latency and sleep efficiency. Methadone (used in the morning and evening) increased sleep onset latency and decreased sleep efficiency. Buprenorphine also led to worse sleep outcomes, but only at low (not high) doses; and these effects were especially pronounced in the evening. These data provide evidence that opioid medications may alter sleep parameters. They also highlight the potential role of opioid mechanisms in sleep/wake regulation.

1.6. Behavioral addiction

Associations between sleep and behavioral addictions have been examined less frequently in the literature and were tested in only one of the articles included here. Guo et al. (2022) tested daily associations between mobile gaming/screen time and sleep problems (and vice versa) in a sample of 41 Chinese college students. Nights of any insomnia symptom were followed by more time spent gaming the next day. However, gaming-time did not predict insomnia symptoms; and there were no within-person associations between sleep and total screen time.

1.7. Treatment-seeking populations

Three papers examined sleep/addiction associations in treatment-seeking populations. In a sample of 58 adults who met criteria for moderate to severe Alcohol Use Disorder, Baskerville et al. (2022) found no differences in sleep quality among those with and without a history of treatment. Indeed, 85% of their sample screened positive for “poor sleep” on the Pittsburgh Sleep Quality Index (Buysse et al., 1989). That said, worse sleep quality was associated with tonic (but not cue-induced) craving, which may help explain the elevated risk of relapse among those with insomnia (Brooks et al., 2020; Kolla et al., 2015). In line with this idea, Schick et al. (2022) found that intra-individual variability in total sleep time (but not average total sleep time) during the first week of substance use treatment was associated with higher odds of relapse one month post-treatment. Again, this highlights the importance of considering not only sleep in substance use treatment, but also the multidimensional nature of sleep as a construct. Finally, Krouse et al. (2023) tested the efficacy of quetiapine, a medication commonly used “off-label” to treat craving and insomnia in patients with substance use disorders, in reducing alcohol craving among AUD patients with and without insomnia. Quetiapine reduced insomnia severity relative to placebo, but only among patients who screened positive for insomnia at baseline and only for the duration of treatment. There were no group differences in change in craving over time. This adds to a growing literature indicating that insomnia treatment reduces insomnia among patients with AUD, but rarely has direct effects on alcohol use outcomes (Chakravorty et al., 2019; Miller et al., 2017).

2. Conclusion

The state of the science on sleep and addictive behaviors is growing rapidly, with dozens of articles published since this call for papers was posted in the fall of 2021. However, longitudinal and experimental studies specifically designed to test these associations remain rare, many studies focus on unidirectional (rather than reciprocal) associations over time, and many studies rely on single items or measure only one domain of sleep and/or substance use. The articles in this special issue offer at least four contributions to the field: (1) documentation of prospective, bidirectional associations between sleep and both alcohol and opioid use; (2) observation of longitudinal, but potentially indirect, associations between sleep and cannabis use; (3) evidence of high comorbidity between sleep and addictive behaviors across racial/ethnic groups and ages; and (4) a call for multidimensional assessment of both sleep and addictive behaviors. We hope this special issue inspires continued research on the importance of sleep in the etiology and treatment of addictive behaviors across populations.

Acknowledgements

The authors declare no conflict of interest related to this manuscript. Preparation of this article was supported by the National Institutes of Health grant awards K23AA026895 and R01AA027677. This publication is the work of the authors, and the authors will serve as guarantors for the contents of this paper.

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