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

During follow-up, 3,949 participants (14.7%) developed chronic pain. Higher deep sleep predicted lower odds of hip pain (OR 0.73; p = 0.020) and low back pain (OR 0.72; p = 0.023). Longer sleep duration predicted hip (OR 1.09; p = 0.041) and neck pain (OR 1.11; p = 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.