JMIR Publications

ABSTRACT

Background:

Shift work may affect health and work functioning through multiple dimensions of work schedules. However, evidence on multidimensional work schedule patterns and their associations with health outcomes among middle-aged and older workers remains limited.

Objective:

This study aimed to identify multidimensional work schedule profiles among shift workers aged ≥40 years in South Korea and examine their associations with insomnia severity, health-related quality of life (HRQoL), and at-work productivity loss, accounting for chronic disease burden.

Methods:

This cross-sectional study included 501 shift workers aged ≥40 years who had worked ≥1 night shift in the preceding month. Latent profile analysis identified work schedule profiles using 7 standardized indicators of length of working hours, time of day, shift intensity, social aspects of working hours, and meal breaks. Associations between profile membership and participant characteristics were estimated using the R3STEP method. The Bolck–Croon–Hagenaars method was used to compare the Insomnia Severity Index (ISI), EQ-5D-5L utility, and Work Limitations Questionnaire (WLQ) scores across profiles. Outcome models were adjusted for age, sex, and occupation, as well as the number of chronic conditions.

Results:

Four work schedule profiles were identified: consecutive night-block (13.4%), short-break low-night (23.4%), scattered-night (56.9%), and extended-hours (6.4%). The consecutive night-block profile was characterized by frequent consecutive night shifts and limited recovery time, whereas the short-break low-night profile involved relatively few night shifts, frequent weekend work, and shorter meal times. The scattered-night profile had fewer consecutive night shifts, while the extended-hours profile was characterized by long weekly working hours and extended shifts. After adjustment for the number of chronic conditions, profile differences in HRQoL remained significant (overall P=.02), with lower HRQoL in the extended-hours profile than in the scattered-night profile (mean difference: −0.061, 95% CI: −0.102 to −0.020). Productivity loss also differed across profiles (overall P=.004), with greater loss in the short-break low-night profile (mean difference: 1.35 percentage points, 95% CI: 0.35 to 2.35) and lower loss in the consecutive night-block profile (−0.99 percentage points, 95% CI: −1.76 to −0.21), compared with the scattered-night profile. Differences in insomnia severity were attenuated after adjustment for the number of chronic conditions and were no longer statistically significant (overall P=.51). A higher number of chronic conditions was associated with greater insomnia severity and productivity loss and lower HRQoL after adjustment for demographic characteristics, occupational group, and work schedule profile.

Conclusions:

Work schedule profiles defined by multiple working time characteristics were associated with HRQoL and productivity loss beyond chronic disease burden, whereas differences in insomnia severity were attenuated after adjustment. Occupational health surveillance should consider multiple dimensions of work schedules alongside chronic disease burden. Longitudinal studies using objective working time data are needed to clarify these relationships.