Objectively measured daytime sleepiness predicts weight change among adults: Findings from the Wisconsin Sleep Cohort Study

Abstract

ObjectiveBody mass index (BMI) trajectories are associated with night-time sleep, but it is not clear how they relate to daytime sleepiness in population data. This study aimed to examine longitudinal associations between levels and changes in daytime sleepiness and BMI trajectories among men and women. MethodsWe estimated growth curve models among 827 participants in the Wisconsin Sleep Cohort Study (mean [sd] age = 55.2 [8.0] years at baseline). The outcome variable was BMI (kg/m2) and the key predictor was daytime sleepiness measured by Multiple Sleep Latency Test (MSLT) scores. Covariates included demographics, health behaviors, retirement status, stimulant use, and depressive symptoms. In sensitivity analyses, we evaluated the potential effects of cardiovascular disease, shift work status, and sleep apnea on the robustness of sleepiness and BMI associations. ResultsAt the between-person level, men who were sleepier had higher BMI levels. At the within-person level, age moderated the positive association between sleepiness and BMI among women. Specifically, young women who became sleepier over time gained more BMI than older women with comparable increases in sleepiness. Furthermore, while BMI tended to increase with age among women, BMI trajectories were steeper among sleepy women than among well-rested women, who experienced less increase in BMI over time. ConclusionThe study suggested that levels and changes in daytime sleepiness as objectively measured by MSLT scores are associated with body mass among adults.