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A Multifactorial Approach to Sleep and Its Association with Health-Related Quality of Life in a Multiethnic Asian Working Population: A Cross-Sectional Analysis.

Gerard DunleavyAndre Comiran TononAi Ping ChuaYichi ZhangKei Long CheungThuan-Quoc ThachYuri RykovChee-Kiong SohGeorgios ChristopoulosHein de VriesJosip Car
Published in: International journal of environmental research and public health (2019)
This study aims to explore if objectively and subjectively measured sleep parameters are associated with physical and mental health-related quality of life in a multiethnic working population in Singapore. We performed a cross-sectional analysis with data from 329 full-time employees enrolled in a workplace cohort study in Singapore. The Short-Form 36v2 (SF-36v2) survey was used to assess health-related quality of life, in terms of physical and mental health. Subjective and objective sleep parameters were measured using the Pittsburgh Sleep Quality Index and wrist actigraphy, respectively. Generalized linear modeling was performed to examine the association between sleep parameters and health-related quality of life. After adjusting for confounders, subjectively measured sleep disturbances were associated with a lower physical health-related quality of life, whereas higher, objectively measured sleep efficiency was associated with greater physical health-related quality of life. Subjectively measured daytime dysfunction was associated with impaired mental health-related quality of life. Using both objective and subjective measurements of sleep, the current study suggests that there is an association between sleep and health-related quality of life. Workplace health-promotion planners in Singapore should consider programmes that educate workers on better sleep hygiene practices in an effort to improve sleep and health-related quality of life.
Keyphrases
  • sleep quality
  • physical activity
  • mental health
  • depressive symptoms
  • health promotion
  • healthcare
  • machine learning
  • deep learning
  • electronic health record