scholarly journals Diet, Sleep, and Mental Health: Insights from the UK Biobank Study

Nutrients ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 2573
Author(s):  
Piril Hepsomali ◽  
John A. Groeger

Diet has long been the focus of attention as a leading risk factor for non-communicable diseases. As such, a better understanding of it is crucial to establish priorities for dietary guidelines and to inform, design, and implement strategies for preventing, helping manage, and stopping the progression of sleep and mental health-related symptoms/disorders. The aim of the current study is to conduct the largest investigation of diet, sleep, and mental health to date by utilizing the UK Biobank (UKB) dataset to identify the associations between diet and (i) sleep quality/health, and (ii) mental health symptomatology. This cross-sectional population-based study involved 502,494 middle-aged adults. UKB food frequency, sleep, and psychological factors and mental health questionnaires at baseline were used. Scores were also calculated for healthy diet, healthy sleep, mental health symptomatology, partial fibre intake, and milk intake. We observed positive associations with healthy diet and sleep and mental health, especially benefits of high intakes of vegetable, fruit, fish, water, and fibre. However, processed meat and milk intake were adversely associated with sleep and mental health. These findings make clear that there are health and wellbeing benefits and drawbacks of different diets, but do not, at this stage, demonstrate the clear causal relationships, which would support dietary interventions that might play a role in the treatment and also self-management of sleep and mental health disorders/symptoms. Further research is required to understand mechanisms of actions of which diet acts on to modulate sleep and mental health, while taking comorbidity of sleep and mental health disorders/symptoms into consideration.

Author(s):  
Sophie Wood ◽  
Sarah Rees ◽  
Ting Wang ◽  
Amanda Marchant ◽  
Ashley Akbari ◽  
...  

IntroductionThe diagnosis, management and services available for mental disorders are of growing concern and controversy in the UK. Transitional care between child and adult services and the interface between primary and secondary/ specialist services is often disjointed and thresholds for referral to Child and Adolescent Mental Health Services are high. Objectives and ApproachRoutinely collected healthcare datasets and data linkage were used to identify patterns of healthcare utilisation by young people and young adults with mental health disorders across the four UK Nations. We explored the extent to which routinely collected datasets can contribute to an assessment of the health needs and the quality of care that children and young people with mental health disorders receive. Data was requested from the national data providers in each country. A series of descriptive analyses were performed and methods were developed for cross- national comparisons to be made (e.g. Four Nation Person Spell). ResultsIt is feasible to explore healthcare utilisation across the four countries of the UK using routine data. However the recording, availability and access varied considerably between countries, making meaningful comparisons challenging. Descriptive analyses showed strong deprivation gradients in the diagnoses and care provided for young people and young adults with mental health disorders. Depression and anxiety were the most commonly recorded mental health conditions in primary care. In secondary care drug/alcohol disorders and self-harm were the most commonly recorded. Re-admissions to emergency departments were higher for those admitted for self-harm or psychiatric conditions. Conclusion/ImplicationsRoutine data has the potential to make a difference to care. However collection and access needs to be standardised in order to improve efficiency and effectiveness in improving the care for children and young people with mental health disorders. MQ has funded an Adolescent Data Platform to facilitate this.


2015 ◽  
Vol 15 (1) ◽  
Author(s):  
Samantha Bull ◽  
Gursimran Thandi ◽  
Mary Keeling ◽  
Melanie Chesnokov ◽  
Neil Greenberg ◽  
...  

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A75-A75
Author(s):  
Piril Hepsomali ◽  
John Groeger

Abstract Introduction It is well known that the prevalence of clinical and subclinical sleep issues is quite high, with a great economic and social burden on the society. As it is expected that the numbers of people suffering from clinical and subclinical sleep problems will increase in the coming years, new primary and/or complementary methods to improve and prevent poor sleep health across the population are urgently needed. In the current study, we aimed to conduct the largest investigation of diet and sleep health to date, through systematically examining the UK Biobank (UKB) data to find out whether diet quality and food groups play a role on sleep health. Methods This cross-sectional population-based study involved 502,494 participants. UKB food frequency and sleep questionnaires at baseline were used. Also, healthy diet, healthy sleep, and partial fibre intake scores were created. ANCOVA and regression models were used to examine the associations of healthy diet and dietary fibre intake scores with sleep health. Adjusted models included age, sex, BMI, and mental health symptomatology. Results We showed that both healthy diet and high partial fibre intake scores were associated with increased healthy sleep scores. Also, higher intakes of vegetables, fruits, fish, and unprocessed red meat were found to be associated with increased healthy sleep scores. On the other hand, processed meat intake was inversely associated with sleep health. Conclusion A healthy dietary pattern, and food groups (vegetables, fruits, fish, water) and nutrients (fibre) that are consumed as a part of a healthy dietary pattern were associated with better sleep health. Further work is needed to identify underlying mechanisms behind the impact of diet on sleep health. Support (if any) Acknowledgements: This research has been conducted using the UK Biobank Resource under Application Number ‘61818’. Funding: Funds received from Unilever UK Central Resources Limited to cover application fees.


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