Analysis of Risk Factors for Type 2 Diabetes Mellitus Using Response Surface Methodology

This study analyses the risk factors that affect glycosylated hemoglobin index in type 2 diabetes mellitus. The purpose of this study was to determine the relative importance of each factor and design a polynomial model for predicting blood glucose levels according to the factors influencing it. In this study, risk factors including weight, systolic and diastolic blood pressure, total cholesterol level and high-density lipoprotein level, were assessed among 403 subjects(170 males and 233 females) with age range of 19 to 75 years-old through interviews and tests. Then using Response Surface Methodology(RSM) technique that is based on the regression analysis, the most important risk factors effective on glycosylated hemoglobin index were determined and a polynomial model was introduced for predicting the level of this index. The results show that at least 78 percent of changes of glycosylated hemoglobin index are described by risk factors of weight, systolic and diastolic blood pressure, total cholesterol, high-density lipoprotein, and remaining changes depend on other risk factors and genetic factors. Owing to these results, it can be declared that in men high-density lipoprotein and weight have the most and the least impact on the index value, respectively; while in women diastolic blood pressure and cholesterol level have the most and the least impact on the index value, respectively.