Daily Associations of Sleep and Rest-activity Patterns with Pain Intensity in Adults with Chronic Pain

Introduction: Sleep and pain share a bidirectional relationship, with emerging evidence suggesting that poor self-reported sleep quality more strongly predicts subsequent pain intensity than vice versa, particularly in individuals with chronic pain (CP). However, sleep comprises only one component of the 24-hour rest-activity rhythm (RAR). Few studies have explored how sleep, daytime activity, and RAR patterns jointly influence next-day pain experiences in individuals with CP. Therfore, this study aimed to investigate whether temporal associations exist between self-reported and actigraphy-measured sleep, physical activity (PA), and 24-hour RAR patterns, and how these variables influence next-day pain in people living with CP in the UK.

Materials and methods: A total of 193 participants with CP wore a MotionWatch 8 (MW8) actigraphy device on their non-dominant wrist continuously for seven days in their natural sleep-wake environment. Participants also completed daily sleep diaries to report sleep efficiency (SR-SE; the proportion of time spent asleep in bed) and sleep quality (SR-SQ; subjective perception of sleep), as well as three daily surveys capturing pain intensity as the outcome variable. Objective actigraphic sleep metrics included actigraphy-derived sleep efficiency (A-SE) and fragmentation index (A-FI), while PA variables encompassed total activity counts (TAC) and total sedentary behaviour (TSB). RAR parameters included intradaily variability (IV; rhythm fragmentation) and relative amplitude (RA; rhythm robustness). Multilevel modeling (MLM) was used to examine the prospective associations between sleep, PA, RAR variables, and next-day pain, accounting for demographic covariates.

Results: In the multilevel modeling (MLM) analysis, higher self-reported sleep quality (SR-SQ; β = -0.057, p < .001, 95% CI [-0.085, -0.013]) and self-reported sleep efficiency (SR-SE; β = -0.051, p < .01, 95% CI [-0.089, -0.028]) significantly predicted lower next-day pain intensity. Conversely, actigraphic measures of sleep efficiency (A-SE) and fragmentation index (A-FI) were not significant predictors of next-day pain intensity. Regarding physical activity (PA) patterns, neither total activity counts (TAC) nor total sedentary behavior (TSB) from the previous day were significant predictors of next-day pain intensity. Similarly, rest-activity rhythm (RAR) parameters reflecting rhythm robustness or fragmentation, including intradaily variability (IV) and relative amplitude (RA), did not predict next-day pain intensity. The MLM results further indicated that pain intensity scores did not significantly vary across the daily surveys or days of measurement. Among demographic covariates, older age (β = 0.152, p < .01, 95% CI [0.053, 0.251]) and higher body mass index (BMI; β = 0.110, p < .05, 95% CI [0.019, 0.200]) were associated with greater reported pain intensity.

Conclusions: Self-reported sleep quality and efficiency emerged as robust and consistent predictors of lower next-day pain intensity, independent of objective activity levels or RAR characteristics. These findings underscore the critical role of high-quality sleep in managing daily pain in individuals with CP and suggest that improving sleep may help mitigate pain regardless of activity levels or circadian rhythm stability. Emphasizing subjective sleep quality could therefore serve as a practical target in chronic pain interventions to enhance daily functioning and quality of life.