Researchers analyzing UK Biobank data have uncovered a strong link between irregular sleep patterns and a heightened risk of 172 diseases, with sleep consistency emerging as a key determinant of health outcomes. The study, led by teams from Peking University and Army Medical University, analyzed seven years of sleep data from 88,461 adults, focusing on factors such as sleep duration, onset timing, rhythm, and fragmentation. The findings suggest that consistent sleep schedules are more critical for health than the total number of hours spent sleeping, challenging traditional assumptions about what constitutes ‘good sleep.’
In the study’s analysis, researchers compared sleep data to health outcomes from the National Health Service, the Cancer Registry, and the National Death Index. They found that for 92 diseases, including Parkinson’s and acute kidney failure, 20% of the risk was directly tied to irregular sleep patterns. Furthermore, 42 diseases, such as age-related frailty, gangrene, and liver cirrhosis, showed at least double the risk associated with poor sleep behavior. The study also identified that poor sleep traits increased the risk of 122 other diseases, including type 2 diabetes, respiratory failure, and urinary incontinence.
The researchers highlighted inflammatory pathways as a possible biological mechanism connecting irregular sleep to disease. They emphasized that sleep consistency plays a vital role in preventing chronic conditions, as seen in diseases like Parkinson’s, diabetes, and obesity. The study was published in the journal Health Data Science, with Prof. Shengfeng Wang, the senior author, stating that the findings underscore the importance of redefining ‘good sleep’ beyond sleep duration.
Notable experts, such as Ashley Curtis from the Cognition, Aging, Sleep, and Health (CASH) Lab at the University of South Florida, have commented on the study, stressing the growing evidence of sleep as a critical modifiable risk factor for medical disorders. However, Curtis also pointed out limitations in the study, including its non-representative sample of middle-aged and elderly individuals and the reliance on a single point-in-time sleep assessment. She emphasized the value of objective measurements provided by wearable technology and called for future studies to include more comprehensive assessments of sleep disorders like insomnia and sleep apnea.
The research team acknowledges the study’s limitations, including the potential for external factors and reverse causation bias, which may have influenced the results. They also noted the lack of data on conditions such as insomnia and sleep apnea, which are common in aging populations. The study authors plan to conduct further research to explore causal relationships and the impact of sleep interventions on chronic disease outcomes. The findings were supported by several funding sources, including the National Key R&D Program of China and the Beijing Municipal Health Development Research Fund.