Analysis of risk factors and their interactions in type 2 diabetes mellitus: A cross‐sectional survey in Guilin, China. Issue 2 (9th August 2016)

• Record Type: Journal Article
• Authors: Zou, Disha; Ye, Yao; Zou, Nina; Yu, Jian
• Is Part Of: Journal of diabetes investigation. Volume 8:Issue 2(2017)
• Page Start: 188
• Page End: 194
• Publication Date: 2016-08-09
• Subjects: Interaction -- Risk factor -- Type 2 diabetes; Diabetes -- Periodicals; Diabetes -- Research -- Periodicals; Diabetes Mellitus -- Periodicals; 616.462005
• DOI: 10.1111/jdi.12549
• Languages: English
• ISSNs: 2040-1116

Abstract

Abstract : The study is a cross‐sectional survey of type 2 diabetes in Guilin, China.The study aimed to not only analyze the influence of single factor for type 2 diabetes, but also investigate the interaction effects between risk factors. Abstract: Aims/Introduction: Type 2 diabetes is a metabolic disease characterized by insulin resistance, and is associated with the effects of genetic and environmental factors. The present study aimed to not only analyze the influence of a single factor for type 2 diabetes, but also to investigate the interaction effects between risk factors. Materials and Methods: A total of 6, 660 individuals selected by the method of cluster random sampling accepted a cross‐sectional survey (questionnaire investigation, physical measurement, laboratory examination and liver ultrasound examination). The classification tree was used to analyze the risk factors and their interactions in type 2 diabetes. The clinical and metabolic characteristics were compared between type 2 diabetes patients and controls, and the non‐conditional logistic regression model was used to quantitatively analyze the interactions. Results: A total of 338 participants were classified as type 2 diabetes (217 men and 121 women), the classification tree model showed three variables with close associations with type 2 diabetes: age, triglycerides (TG) and non‐alcoholic fatty liver disease (NAFLD). Type 2 diabetes patients had higher age and incidences of high TG, NAFLD, hypertension, high body mass index, high uric acid, high total cholesterol, high low‐density lipoprotein cholesterol and low high‐density lipoprotein cholesterol. The multivariate logistic regression analysis showed that the following factors had interactions in type2 diabetes: high TG × advanced age (odds ratio 2.499, 95% confidence interval 1.868–3.344, P = 0.000), NAFLD × advanced age (odds ratio 1.250, 95% confidence interval 1.048–1.491, P = 0.013) and NAFLD × high TG (odds ratio 1.349, 95% confidence interval 1.144–1.590, P = 0.000). Conclusions: The present study showed that type 2 diabetes resulted from the interactions of many factors; the interactions among age, TG and NAFLD are important risk factors for type 2 diabetes.