Elevated Prevalence of Probable Insomnia among Young Men during Social Unrest in Hong Kong: A Population-Based Study.
Wai Sze ChanCecilia ChengPublished in: Behavioral sleep medicine (2021)
Objective/Background: Hong Kong has experienced a series of major protests in 2019, leading to deteriorating population mental health. Few studies have documented the impact of social unrest on sleep health. The present study examined the prevalence of probable insomnia and its demographic correlates in a population-based random sample of Hong Kong adults.Participants and Methods: A population-based cross-sectional telephone survey on lifestyle behaviors was conducted during the period between July and September 2019. Data obtained from 1004 participants who completed the insomnia measure were analyzed. The Chinese version of the Patient-Reported Outcomes Information System (PROMIS) v1.0 Sleep Disturbance Short Form was used to measure insomnia. Logistic regressions were conducted to evaluate if prevalence estimates differed by demographic variables.Results: The weighted prevalence of probable insomnia for the population was 20.7%, a nearly twofold increase compared to a prior population-based study in Hong Kong. A novel age by sex interaction was found (p = .046). Men had significantly greater odds of having probable insomnia than women in the 18-39 age group (M = 23.1 vs W = 16.5%), whereas women had greater odds of probable insomnia in the 40-59 (M = 14.8 vs W = 25.6%) and 60+ groups (M = 17.2 vs W = 25.2%).Conclusion: The present findings documented in a random population-based sample elevated prevalence of probable insomnia among Hong Kong adults, especially young men, during the social unrest in 2019. Easily accessible and scalable intervention is urgently needed to mitigate the potential impact of continued social unrest on deteriorating sleep health facing Hong Kong adults.
Keyphrases
- sleep quality
- mental health
- healthcare
- risk factors
- patient reported outcomes
- cross sectional
- physical activity
- middle aged
- public health
- depressive symptoms
- magnetic resonance
- type diabetes
- polycystic ovary syndrome
- metabolic syndrome
- health information
- risk assessment
- magnetic resonance imaging
- weight loss
- pregnant women
- artificial intelligence
- deep learning