A U-shaped association between sleep duration and depression in adult prescription opioid users

Background The objective of this study was to investigate the correlation between sleep duration and depression in adult prescription opioid users. Methods Data on adults who had recently used prescription opioids were collected from the National Health and Nutrition Examination Survey (NHANES) in the United States, covering the period from 2007 to 2018. Depressive symptoms were assessed using the PHQ-9 scale. A multivariate logistic regression model was employed to examine the independent association between sleep duration and the occurrence of depression. To explore the potential non-linear relationship between sleep duration and depression, a restrictive cubic spline analysis was applied. Finally, propensity score matching (PSM) was utilized to validate our findings based on external datasets. Results This study was conducted on a population of 1319 adult users of prescription opioids, with a weighted total of 7319533.25 individuals. 23.2% of the subjects satisfied the diagnostic criteria for depression. After adjusting for all confounding variables, the prevalence of depression was 60% greater among individuals with insufficient sleep duration [OR = 1.60, 95% CI = 1.11-2.29, P = 0.012] in comparison to those with a normal sleep length. The subgroup analyses revealed that the connection between short sleep duration and depression was considerably influenced by both gender and lower socioeconomic status, as indicated by a statistically significant interaction effect. We identified a U-shaped correlation between sleep duration and depression scores using a two-segment linear regression model, with a turning point at 6.74 hours. The PSM analysis further revealed that the less than 6.74 hours of sleep time among opioid users was closely related to depression. Conclusions Only Insufficient sleep is associated with an increased risk of depression, and sleep duration showed a nonlinear dose response relationship in adult prescription opioid users.