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Approved research

Sleep as a biomarker of healthy ageing, metabolic health and cognition

Principal Investigator: Miss Gewei Zhu
Approved Research ID: 43537
Approval date: November 1st 2018

Lay summary

Nowadays, lack of sleep is very common in our society which can cause many problems. Sleep loss can lead to slower response rate, low alertness and inattention. They can be very dangerous in some situations, such as when driving. It would put both the drivers and others around them in danger. Many scientific studies have found that higher level cognition, for example, memory and perception is also affected by lack of sleep. Impaired memory can cause inconvenience and may even be dangerous in some cases, such as forgetting to take certain medications or taking too much medications. Sleep is controlled by circadian rhythms which allow us to adapt to the environmental variations. It is important in the regulation of blood glucose level. Abnormal circadian rhythm was found to be linked with diseases such as diabetes and heart diseases. It is also associated with mental disorders, for example depression, anxiety and mania. Lack of sleep increases people's risk for heart diseases and diabetes because it can affect the glucose metabolism. Studies have shown that extending the sleep duration in those who are lack of sleep is very beneficial. Lack of sleep is also known to affect people's optimism and self-esteem which both can affect the mood. This project aims to study the effect of sleep on cognition and mood, as well as the relationship between mood disorders and cognitive functions using the large dataset from the UK Biobank. It also aims to study how sleep affect metabolic health. We will divide the data into three groups based on the sleep duration of these subjects: (1) Short sleepers: subjects who sleep less than 7 hours/night. (2) Normal sleepers: subjects who sleep between 7 and 8 hours/night. (3) Long sleepers: subjects who sleep longer than 8 hours/night. Analysis will then be carried out using a statistical software (IBM SPSS) to find out the proportion of subject with certain mental and cognitive disorders in each sleep groups. Abnormalities in circadian rhythms can also be identified from the sleep data. Since mental health disorders are relatively difficult to diagnose. Careful monitor of those with sleep disorders may help to identify those at high risk of mental and metabolic disorders at an early stage so that early intervention can be provided.