Occupational and environmental medicine · 2026
Principal component analysis of pre-sleep artificial light at night exposure patterns and the associations with sleep disturbances in Hong Kong shift-working nurses and daytime office workers.
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Li Beixi, Liu Yufei, Li Wenzhen, Ma Julie Y T, Huss Anke, Chan Joey, Wing Yun Kwok, Tse Lap Ah
Аннотация
BACKGROUND: This study investigated actigraphy-measured pre-sleep artificial light at night (ALAN) exposure patterns on non-workdays and their associations with sleep parameters among Hong Kong shift-working nurses and daytime office workers.
METHODS: Using a 7-day actigraphy-measured longitudinal study design, we recruited 136 shift nurses and 66 matched daytime office workers (July 2022-February 2023). ALAN exposure metrics and sleep parameters were derived from actigraphy data, supplemented by sociodemographic surveys and sleep-activity diaries. Principal component analysis (PCA) was performed on log-transformed light values to identify ALAN exposure patterns; mixed-effect models analysed associations with total sleep time (TST), sleep onset latency, wake after sleep onset (WASO) and sleep timing.
RESULTS: Shift nurses were younger (34.8 vs 36.0 years), showing no significant difference in TST (6.6 vs 6.8 hours, p=0.447) compared with daytime office workers. PCA identified Light PC1 (overall intensity) and Light PC2 (temporal pattern) patterns. In the adjusted models, wrist-worn Light PC1 showed strong associations with shorter TST (β=-0.59, SE=0.08, p<0.001), reduced WASO (β=-0.20, SE=0.04, p<0.001), later sleep onset (β=0.20, SE=0.07, p=0.003) and earlier wake-up time (β=-0.65, SE=0.09, p<0.001). Bedroom Light PC1 showed similar but weaker associations (TST: β=-0.21, SE=0.09, p=0.028). Light PC2 was not significantly associated with any sleep outcomes. Sensitivity analyses confirmed PCA's model fit, and subgroup analyses revealed no significant interaction effects (all p>0.05).
CONCLUSION: Our findings suggest sleep interventions should prioritise reducing personal light exposure before bed. Future studies could clarify the roles of specific light properties.
METHODS: Using a 7-day actigraphy-measured longitudinal study design, we recruited 136 shift nurses and 66 matched daytime office workers (July 2022-February 2023). ALAN exposure metrics and sleep parameters were derived from actigraphy data, supplemented by sociodemographic surveys and sleep-activity diaries. Principal component analysis (PCA) was performed on log-transformed light values to identify ALAN exposure patterns; mixed-effect models analysed associations with total sleep time (TST), sleep onset latency, wake after sleep onset (WASO) and sleep timing.
RESULTS: Shift nurses were younger (34.8 vs 36.0 years), showing no significant difference in TST (6.6 vs 6.8 hours, p=0.447) compared with daytime office workers. PCA identified Light PC1 (overall intensity) and Light PC2 (temporal pattern) patterns. In the adjusted models, wrist-worn Light PC1 showed strong associations with shorter TST (β=-0.59, SE=0.08, p<0.001), reduced WASO (β=-0.20, SE=0.04, p<0.001), later sleep onset (β=0.20, SE=0.07, p=0.003) and earlier wake-up time (β=-0.65, SE=0.09, p<0.001). Bedroom Light PC1 showed similar but weaker associations (TST: β=-0.21, SE=0.09, p=0.028). Light PC2 was not significantly associated with any sleep outcomes. Sensitivity analyses confirmed PCA's model fit, and subgroup analyses revealed no significant interaction effects (all p>0.05).
CONCLUSION: Our findings suggest sleep interventions should prioritise reducing personal light exposure before bed. Future studies could clarify the roles of specific light properties.