0406 Bedtime Technology Use and Sleep Health Among Rural Appalachian Adults: Findings from the REST-KY Study

Abstract Introduction Rural Appalachian populations experience significant sleep health disparities, yet little is known about how bedtime technology use affects multidimensional sleep health in these communities. This study examined associations between specific bedtime technology behaviors and overall sleep health, as well as individual sleep health dimensions, among adults in rural Eastern Kentucky. Methods Survey data from participants in the “Researching Equitable Sleep Time in Kentucky Communities” (REST-KY) study (N=315) were analyzed. We used the National Sleep Foundation’s 2011 “Sleep in America” poll to assess bedtime technology behaviors including social networking sites, working on computer, and computer/laptop use. Technology use was dichotomized as "often" (every/almost every night or few nights weekly) versus "rarely/never." Sleep health was measured using an expanded version of the Ru-SATED framework (i.e., the original components of regularity, satisfaction, alertness, timing, efficiency, and duration + sleep irregularity and social jetlag). Including wake after sleep onset (WASO) yielded both a continuous sleep health score and binary indicators of favorable versus non-favorable sleep health. We conducted bivariate analyses followed by multivariable linear regression models for overall sleep health and logistic regression models for individual sleep dimensions, adjusting for employment, sex, age, income, sleep medication use, anxiety/depression, and living alone. Results In adjusted models, social networking site use and two separate computer related items remained significantly associated with lower sleep health scores. Participants who rarely/never used social networking sites had 0.71-unit higher sleep health scores compared to frequent users (p=0.018). Those who rarely/never worked on a computer had 0.88-unit higher scores (p=0.002). Computer/laptop use showed statistically significant associations after adjustment (0.51-unit difference, p=0.039). Dimension-specific analyses revealed that individuals who rarely/never used social networking sites had higher adjusted odds of favorable sleep timing and duration, and those who rarely/never worked on a computer had higher odds of favorable alertness and duration irregularity. Conclusion Interactive and work-related bedtime technology behaviors are independently associated with poorer sleep health in rural Appalachian adults, with effects varying across specific sleep dimensions. Social networking sites and computer work show particularly robust associations, suggesting these behaviors as potential intervention targets for improving sleep health in this vulnerable population. Support (if any) R01MD016236