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.

中文翻译：

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通过贝叶斯非参数过程模拟胰岛素抵抗分布的种族差异：在 SABRE 队列研究中的应用

我们分析了 Southall 和 Brent REvisited (SABRE) 三族研究的数据，其中记录了代谢和人体测量变量的测量值。特别是，我们专注于对与 2 型糖尿病的发展密切相关的胰岛素抵抗的分布进行建模。我们建议在对稳态模型评估胰岛素抵抗的分布进行建模之前使用贝叶斯非参数，因为它允许数据驱动的观察聚类。人体测量变量和代谢物浓度作为协变量包含在回归框架中。该策略强调了数据中存在的亚群，其特征是不同种族的 2 型糖尿病风险水平不同。后验推理是通过马尔可夫链蒙特卡罗 (MCMC) 方法执行的。