Associations between shift work patterns and sleep disturbance: an analysis of cross-sectional data from UK Biobank

To investigate associations between shift work patterns and sleep disturbance, and to assess if the association is modified by demographic factors, socioeconomic factors, anthropometric and lifestyle factors, health conditions or sleep traits.

Analysis of cross-sectional data obtained from the UK Biobank baseline assessment.

UK Biobank, a large-scale prospective cohort study which recruited half a million participants aged 40-69 years between 2006 and 2010 from across the UK.

A total of 285 175 employed or self-employed participants at baseline (2006-2010), including 148 296 (52.0%) females and 136 879 (48.0%) males. The sample comprised 94.0% White, 0.7% Mixed race, 0.36% East Asian, 2.0% South Asian, 1.8% Black and 0.89% from other ethnic backgrounds.

Sleep disturbance was defined as the presence of both insomnia and excessive sleepiness symptoms.

A total of 42 181 (14.8%) participants had sleep disturbance defined based on insomnia and excessive sleepiness. 236 200 (82.8%) were non-shift workers, while 48 975 (17.2%) were shift workers, which included 24 062 (49.1%) working day shifts only, 17 940 (36.6%) working night shifts sometimes or usually, and 6973 (14.2%) working night shifts always. Compared with non-shift workers, all shift workers had higher multivariable-adjusted odds of sleep disturbance: (non-night shifts: OR in model 3 (OR) 1.21 (95% CI 1.16 to 1.27); sometimes/usually night shifts: OR 1.37 (95% CI 1.30 to 1.44) and always night shifts: OR 1.50 (95% CI 1.38 to 1.63)). The association between shift work pattern and sleep disturbance was modified by age (p_interaction<0.0001), ethnicity (p_interaction=0.0005) and smoking status (p_interaction=0.04).

Shift work is associated with a higher odds of sleep disturbance compared with non-shift work in all participants, with greatest odds observed among those always working night shifts. The association was stronger among individuals who were younger than 55 years old, from an ethnic minority background and never smokers. Future large-scale longitudinal studies are needed to further investigate these associations.