Abstract
Abstract Introduction Implementation of electronic health records (EHR) across healthcare systems linking clinical to survey data has enabled systematic assessments of longitudinal relationships between sleep traits and diseases classified by PheWAS codes where ICD-9/10 codes are collapsed to categories based on clinical similarity. In the Partners Biobank, a hospital-based virtual cohort from Mass General Brigham in greater Boston, MA, we aimed to assess associations between sleep traits and incident diseases. Methods Self-reported weekday/weekend bed and wake times from a survey at consent were used to derive sleep traits. Incident diseases were defined as two incident PheWAS codes on separate dates ≥1y after consent. Cox proportional hazards models compared short (<7h) and long (≥9h) sleep duration, with 7-8h (referent group), adjusted for age, gender, race/ethnicity, and employment status, then further adjusted for BMI. Similarly, sleep midpoint (midpoint between weekend wake/bed times), sleep debt (difference in weekend/weekday sleep duration), and social jetlag (difference in weekend/weekday sleep midpoint) were assessed. Results The analytical sample consisted of 24,065 adults (mean sleep duration =8.12h) seeking regular care with sleep data. Participants had a total of 7,513,649 ICD codes of which incident 323,946 ICD codes mapped to 137,137 PheWAS codes. Over a median follow-up of 2.73 years (interquartile range: 1.82-3.98), participants sleeping <7h had a significantly higher risk of incident Acute pain [hazard ratio(95% confidence interval)=1.46(1.2-1.78)], Tobacco use disorder [1.42(1.18-1.71)], Sciatica [1.72(1.3-2.27)], and Edema [1.69(1.25-2.28)]. Each additional hour of later sleep midpoint and increased sleep debt and social jetlag associated with higher risk of incident Major depressive disorder [midpoint:1.30(1.14-1.49); debt:1.23(1.09-1.38); jetlag:1.54(1.27-1.84)]. Associations retained significance upon further adjustment for BMI, except for Edema, and no other associations were observed at the Bonferroni threshold (P=0.0125). Conclusion Our findings in a large hospital-based virtual cohort support unique inter-relationships between sleep duration/timing on somatic, behavioral, and mental health outcomes. Support H.S.D. and R.S. are supported by NIDDK grant R01DK107859. B.C. is supported by K01-HL135405-01. S.R. and R.S. are partially supported by R35 NHLBI HL 135816.
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