Approved research
Investigating causal effects of accelerometer measures and body composition on chronic disease
Approved Research ID: 16391
Approval date: April 1st 2016
Lay summary
We aim to examine the causal pathways involved in observed associations between objectively-measured physical activity, sleep duration/quality and body composition, and their interacting influences on health-related consequences including cardiometabolic disease and cancer. By unpicking the complex relationships between physical activity, sleep and body composition we hope to identify the causal agents which play a key role in aetiology of disease which may then be used to prioritise intervention targets for disease prevention. We hope to make use of the genome-wide genetic data in UK Biobank in order to identify genetic variants which are robustly associated with physical activity, sleep and body composition measures. These genetic variants may then be investigated in the context of the exposures they proxy to establish the causal effects of these exposures on each other and on health-related outcomes using an approach known as Mendelian randomization, an increasingly important tool for appraising causality in observational epidemiology. We would require data on all individuals with available accelerometry measures and genetic information.
Scope extension:
We aim to examine the causal pathways involved in observed associations between objectively-measured physical activity, sleep duration/quality and body composition, and their interacting influences on health-related consequences including cardiometabolic disease and cancer.
We wish to extend the scope of the study to investigate the role of sleep, activity and body composition in relation to human reproduction. We hope to apply the methods already described (genome-wide association studies, LD score regression, Mendelian randomization) in order to appraise the causal relationship between these factors in relation to reproductive traits (age at menarche, age at voice breaking, age at menopause, age at first birth, number of children, infertility, sex hormones) and menstrual conditions (dysmenorrhea, PCOS, endometriosis, menstrual cycle length).