Principal Investigator: Mr Onkabetse Mabikwa
Department: Epidemiology and Biostatistics
Institution: University of LeedsTags: 26883, alcohol, blood pressure, Type 2 diabetes
1a: The balance of effects of alcohol consumption on cardiovascular risk factors in people with type 2 diabetes is of considerable interest. Most studies reporting the effects of alcohol in type 2 diabetes has focused on insulin sensitivity, lipids/high density lipoprotein-cholesterol (HDL-C) and haemostatic factors. We aim to investigate the effects of alcohol intake on blood pressure (BP) in patients with type 2 diabetes. Various statistical approaches are applied to determine the direction, turning points and magnitudes of different doses of alcohol on BP. Interventions aimed at managing BP in alcohol consumers with type 2 diabetes are lacking.
1b: Our research meets the UK Biobank’s aim of improving and promoting healthy living within our societies. Knowledge gained in the research will support and promote the administration of patients living with type 2 diabetes hence improving care and quality of life. Further, by comparing different application methods, the research also have the potential to inform future studies on appropriate statistical approaches for analysing the exposure-outcome relationships
1c: Our study will examine the association of alcohol intake as an exposure and blood pressure outcomes in people with type 2 diabetes. Different statistical models will be fitted to establish a suitable exposure-outcome association with biologically meaningful interpretations. To account for potential risk factors, statistical models with multiple possible predictors will also be built for comparison. This approach enables us to examine the association models with predictor variables previously studied elsewhere and also examine other unknown variables supported by evidence found in the UK Biobank.
1d: We request the full cohort of type 2 diabetes patients (n=23,843) identified using the self-reported baseline assessment data.
A full reference to this cohort is described in an article by Eastwood et al (2016) below:
Eastwood, S. V., Mathur, R., Atkinson, M., Brophy, S., Sudlow, C., Flaig, R., . . . Chaturvedi, N. (2016). Algorithms for the Capture and Adjudication of Prevalent and Incident Diabetes in UK Biobank. PLoS One, 11(9), e0162388. doi: 10.1371/journal.pone.0162388