Wearable-derived sleep architecture and chronic musculoskeletal pain: a national cohort study

AIMS: Sleep disturbances are associated with chronic pain risk, but most large studies rely on self-reported sleep duration. We evaluated whether wearable-derived sleep architecture predicts incident musculoskeletal pain in a large United States national cohort. MATERIALS AND METHODS: We analyzed 26,852 adults in the NIH All of Us Research Program with wearable sleep data. Average nightly sleep duration and percentage of deep sleep, a wearable-derived proxy for slow-wave sleep (SWS), were estimated prior to a 12-month washout period before diagnosis. Multivariable logistic regression evaluated associations with incident chronic hip, low back, neck, and shoulder pain. False discovery rate (FDR) correction was applied across site-specific models. RESULTS: = 0.025). After FDR correction, only the associations between higher deep sleep and hip and low back pain remained significant. CONCLUSIONS: Lower deep sleep was associated with higher risk of hip and low back pain. Wearable-derived sleep architecture may represent a potential marker associated with musculoskeletal pain risk, although these findings require prospective validation.