783 Early Life Adversity and Central Symptoms of Sleep Disturbance: A Network Analysis

Introduction Individuals with early life adversity (ELA) experience a greater likelihood of sleep disturbance. Sleep disturbance is a hypothesized mechanism underlying the association between ELA and adverse health outcomes. However, it is unclear whether sleep disturbance presents differently in individuals with ELA when compared to individuals without ELA. Network analysis provides an analytic framework to examine the relationships and magnitudes of association between symptoms of sleep disturbance. Using a network framework, we investigated the differences in sleep disturbance symptoms between individuals with ELA and individuals without ELA. Methods College students (N=507; age=18±1, Female=72%) completed demographic measures, the Childhood Trauma Questionnaire (CTQ), and the Pittsburgh Sleep Quality Index using an online data collection platform from March-December 2020. Using clinical cutoffs, individuals with ELA were separated from individuals without ELA. Using the Pittsburgh Sleep Quality Index (PSQI; alpha=0.79), sleep disturbance was assessed. Two 7-node ELA-specific networks were generated using raw values for the 7 components of the PSQI. To assess network accuracy, stability coefficients were estimated using the ‘bootnet’ and ‘qgraph’ packages in R. The strength of association between each component and all other components of sleep disturbance were estimated using expected influence (EI). Network structures and measures of EI were examined for differences between exposure groups. Results Overall, the average global PSQI score was 7.50±3.37. Individuals with ELA had larger global PSQI scores when compared to individuals without ELA (8.18 versus 6.97, t=3.8, p Conclusion For individuals with ELA, duration and efficiency strongly underly sleep disturbance. Moreover, most symptoms had greater measures of EI in individuals with ELA when compared to individuals without ELA, suggesting that symptoms of sleep disturbance may be more likely to co-occur in individuals with ELA. Future research may explore the utility of these symptoms in predicting adverse health outcomes. Support (if any)