Systemic inflammation and family history in relation to the prevalence of type 2 diabetes based on an alternating decision tree

To investigate unknown patterns associated with type 2 diabetes in the Japanese population, we first used an alternating decision tree (ADTree) algorithm, a powerful classification algorithm from data mining, for the data from 1,102 subjects aged 35–69 years. On the basis of the investigated patterns, we then evaluated the associations of serum high-sensitivity C-reactive protein (hs-CRP) as a biomarker of systemic inflammation and family history of diabetes (negative, positive or unknown) with the prevalence of type 2 diabetes because their detailed associations have been scarcely reported. Elevated serum hs-CRP levels were proportionally associated with the increased prevalence of type 2 diabetes after adjusting for probable covariates, including body mass index and family history of diabetes (P for trend = 0.016). Stratified analyses revealed that elevated serum hs-CRP levels were proportionally associated with increased prevalence of diabetes in subjects without a family history of diabetes (P for trend = 0.020) but not in those with a family history or with an unknown family history of diabetes. Our study demonstrates that systemic inflammation was proportionally associated with increased prevalence of type 2 diabetes even after adjusting for body mass index, especially in subjects without a family history of diabetes.

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