Modelling ethnic differences in the distribution of insulin resistance via Bayesian nonparametric processes: an application to the SABRE cohort study

Author:

Molinari Marco1ORCID,de Iorio Maria2,Chaturvedi Nishi3,Hughes Alun3,Tillin Therese3

Affiliation:

1. UCL , Statistical Science , London , UK

2. Yale-NUS College , Singapore , Singapore

3. UCL , Population Science & Experimental Medicine , London , UK

Abstract

Abstract We analyse data from the Southall And Brent REvisited (SABRE) tri-ethnic study, where measurements of metabolic and anthropometric variables have been recorded. In particular, we focus on modelling the distribution of insulin resistance which is strongly associated with the development of type 2 diabetes. We propose the use of a Bayesian nonparametric prior to model the distribution of Homeostasis Model Assessment insulin resistance, as it allows for data-driven clustering of the observations. Anthropometric variables and metabolites concentrations are included as covariates in a regression framework. This strategy highlights the presence of sub-populations in the data, characterised by different levels of risk of developing type 2 diabetes across ethnicities. Posterior inference is performed through Markov Chains Monte Carlo (MCMC) methods.

Publisher

Walter de Gruyter GmbH

Subject

Statistics, Probability and Uncertainty,General Medicine,Statistics and Probability

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