Dose-dependent Relationships of Same-day and Typical Substance Use to Sleep Duration in College Cannabis and Alcohol Users: A Multilevel Modeling Approach Using Daily Diary Data
Abstract
This study characterized how quantities of cannabis and alcohol use affect sleep. Single-day and typical cannabis and alcohol use patterns were considered to assess acute-chronic use interactions. Linear and non-linear associations assessed dose-dependence. College students (n=337; 52% female) provided 11,417 days of data, with up to five time points per day. Daily self-reported sleep duration, cannabis use quantity, and alcohol use quantity were subjected to linear mixed modeling to capture linear and curvilinear associations between single-day and typical use on same-night and typical sleep. Sleep duration (difference between bedtime and waketime) was the outcome. Quantity of cannabis used each day andtypical quantity used across all days were predictors in the cannabis models. Parallel single-day and typical alcohol variables were predictors in the alcohol models. Follow-up analyses excluded days with alcohol-cannabis co-use. Main effects of single-day and typical cannabis quantity on sleep duration were observed when all cannabis-use days were modeled. Higher than typical doses of single-day and typical cannabis were associated with longer sleep durations, but only to a point; at the highest doses, cannabis shortened sleep. A main effect of single-day alcohol quantity and two interactions (single-day use with both linear and curvilinear typical use) on sleep duration were observed when all alcohol-use days were modeled. Greater alcohol consumption on a given day led to shorter same-night sleep, but typically heavier drinkers required higher doses than typically lighter drinkers to experience these adverse effects. Follow-up models suggested alcohol co-use may contribute to the purported sleep-promoting effects of cannabis.
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Copyright (c) 2023 Neel Muzumdar, Kristina Jackson, Jennifer Buckman, Andrea Spaeth, Alexander Sokolovsky, Anthony Pawlak, Helene White
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.