HbA1c Control Status Of T2DM Patient And Comparison Of Anthropomorphic Indicators And Bioelectrical Impedance Analysis Indicators In Predicting T2DM

Part one: The Status of Glycemic Control in T2DM Patients in OutpatientObjective: To study the control status of HbA1c of T2DM in outpatient in Shaanxiprovince and assess the related influencing factors.Methods: The data was the Shaanxi part of National Monitoring Net of HbA1c,which was a cross-sectional study covered six hospitals in Shaanxi province from9thMarch to29th June in2012. The first7patients on each day were recruited in this randomselective study. All the objectives were given a questionnaire about general information,glycaemia, blood pressure, lipid, self blood glucose monitoring, treatments andcomplications.Results: There were2266objectives enrolled in this study,1425of which were male,and841objectives were female. The average age was57.33±12.54years, the averageduration was5.38±5.50years. According to the recommended targets in ChineseGuideline of Type2Diabetes Mellitus, version2010,26.0%of the patients achieved theHbA1c goal,26.5%of the patients achieved the blood pressure goal, and the percentage of which achieved the optimal lipid goal was22.4%. Only4.7%of the2266patients gotsimultaneously control of HbA1c, blood pressure and lipids. High triglycerides(OR=1.098, P=0.028), high LDL-C (OR=1.215, P<0.001), long duration (OR=1.028,P=0.010), high HbA1c at diagnosis (OR=1.331, P<0.001) were risk influencing factors ofHbA1c control, self blood glucose monitoring (OR=0.724, P=0.032) was the protectivefactors of HbA1c control.Conclusion: Not only glycemic control, but also blood pressure and lipid control ofT2DM patients were unsatisfied in Shaanxi province, efforts need to be paid to getsimultaneously control of HbA1c, blood pressure and lipids.Part two: Comparison of Anthropomorphic Indicators and Bioelectrical ImpedanceAnalysis Indicators in Predicting DM in A Follow-up StudyObjective: To compare the predictive value of WHR, WHtR, BMI and BF%, FMI inidentifying the onset of DM.Methods: The studying data was derived from a5-year follow up study. The baselinestudy was designed to evaluate the prevalence of diabetes and metabolic disorders inShaanxi province. All the participants were local residents living over5years in the regionwho aged older than20years. All the participants received body examinations, blood testand questionnaire. We chose the participants who were free of DM at the baseline, and allthe procedures had been implemented again when they were followed up5years later.Multivariate logistic regression and ROC analysis were applied to evaluate the predictiveability of bioelectrical impedance analysis indicators (BF%, FMI) and anthropomorphicindicators (WHR, WHtR, BMI) assessing indicators in identifying the onset of DM.Results: A total of633objectives enrolled in this study,42.2%of which were male,57.8%of them were female, and the average age of the overall subjects was45.96±12.78years. The results of ROC analysis and multivariate logistic regression indicated thesimilar conclusion. In males, FMI (AUC=0.683) was found to be the superior indicators inpredicting T2DM when compared to BF%(AUC=0.664), WHtR (AUC=0.604), BMI(AUC=0.594), WHR (AUC=0.524). BF%(AUC=0.701) has a comparable ability with FMI (AUC=0.701) in identifying the onset of DM in females, whereas the ability ofWHtR (AUC=0.679), BMI (AUC=0.670), WHR (AUC=0.555) were relatively weake.Conclusion: The ability of BF%, FMI in identifying onset of DM is stronger than WHR,WHtR, BMI.