| Objective: This study was a longitudinal study based on a large cohort of healthy people,aiming to investigate the sex-specific components of Metabolic Syndrome(MS),and to establish the structure of Type 2 Diabetes Mellitus(T2DM),based on the characteristics of MS components.The risk prediction model of T2DM was used to assess the risk of T2DM population and identify the high-risk groups of T2DM,so as to provide reference for the protection of T2DM.Methods: From January 1,2015 to December 31,2020,a total of 4153 people diagnosed with MS in the Health Management Center of a third-class hospital in Dalian were selected to analyze the components of gender-specific metabolic network factors in MS population.1074 people with T2DM were detected.Among healthy people without T2DM,press 1: 2.A proportion of 2148 people were randomly selected to construct a T2DM diagnosis model based on MS component factors,and Receiver Operating Characteristic(ROC)curve was drawn to determine the diagnosis criteria.A total of 1,968 people were included at baseline in 2015 and followed up for 5 years.Cox proportional hazard regression model was used to explore the MS component factors that lead to T2DM morbidity.ROC curve was drawn and prediction reference values were analyzed to construct a T2DM prediction model based on MS component factors,and the prediction model was verified internally and externally.The prediction model constructed in this study was used to evaluate the proportion of people at high risk of developing T2DM at all ages in the population without T2DM detected during this period as a function of age.Results: 1.Among the people with MS,there were 3208 males with a mean age of47.582±12.471 years and 945 females with a mean age of 57.168±15.934 years.The5-year cohort was followed up with 1218 males(mean age 45.197±10.544 years old)and 750 females(mean age 41.548±9.690 years old).There were 264 newly diagnosed T2DM patients(222 males,42 females).The cumulative incidence was 13.415%(18.277% males,5.600% for women).2.The results of MS component model analysis under gender specificity showed that the MS component factors found in male were liver enzyme factor,inflammatory factor,bilirubin factor,lipid factor,blood factor,blood pressure factor,blood glucose and obesity factor,blood glucose and renal function factor.The components of MS in women were liver enzyme factor,inflammatory factor,bilirubin factor,lipid factor,blood factor,blood pressure factor,blood glucose and obesity factor,and renal function factor.3.Gender-specific T2DM disease discrimination model based on MS component factors showed that: Male age,liver enzyme factor,inflammatory factor,bilirubin factor,lipid factor,blood factor,blood pressure factor,blood glucose and obesity factor,blood glucose and renal function factor were all statistically significant factors for T2DM diagnosis(P<0.05).AUC of discriminant model was 0.977(95%CI:0.971-0.982,P<0.001),sensitivity and specificity were 91.2% and 96.4%,the critical point was 0.876,respectively.Female age,liver enzyme factor,inflammatory factor,blood factor,blood pressure factor,blood glucose and obesity factor were statistically significant factors for T2DM diagnosis(P < 0.05).AUC of discriminant model was 0.993(95%CI:0.989-0.996,P<0.001),sensitivity and specificity were 97.3% and 95.5%,the critical point was 0.928,respectively.4.Gender specific MS component factor based T2DM risk prediction model results showed: Male age,liver enzyme factor,inflammatory factor,blood pressure factor,blood glucose and obesity factor were risk factors for T2DM(P<0.05).The AUC of the prediction model was 0.765(95%CI:0.729-0.801,P<0.001),and the sensitivity and specificity were 77.5% and 67.6%,the predicted critical point is 0.451,respectively.The accuracy of internal verification in predicting the onset and absence of disease was69.87% and 98.80%,respectively.The accuracy of external validation in predicting morbidity and non-morbidity was 73.58% and 98.83%,respectively.Female,inflammatory factor and blood pressure factor were risk factors for T2DM(P<0.05).The AUC of the prediction model was 0.816(95%CI:0.739-0.892,P<0.001),and the sensitivity and specificity were 69.0% and 87.4%,the predicted critical point is 0.564,respectively.The accuracy of internal verification in predicting the onset and absence of disease was 53.57% and 98.27%,respectively.The accuracy of external validation in predicting morbidity and non-morbidity was 64.29% and 99.71%,respectively.5.The group risk assessment results showed that: A total of 10,531 males and10,503 females participated in the high-risk assessment of T2DM.The proportion of high-risk individuals for both males and females gradually increased with age.The proportion of high-risk individuals for 20-30 years old females was greater than that for males,and the proportion of high-risk individuals for 35-70 years old males was greater than that for females.The proportion of women at high risk aged 75-90 years was slightly higher than that of men(both>80%),and men over 55 years old and women over 65 years old(both>70%)had a higher risk of T2DM.Conclusions: 1.The pathogenesis of MS is complex,which may be the result of the comprehensive effects of various physiological mechanisms such as blood viscosity,dyslipidemia,hypertension,abnormal liver function,obesity,inflammation,etc.,and is closely related to the disease of T2DM.2.The elderly population is at a higher risk of T2DM.Inflammatory response and hypertension in both men and women are important physiological reference states for T2DM.Meanwhile,abnormal liver function and obesity in men are also closely related to the onset of T2DM.In order to achieve early prevention of T2DM.3.The prediction model of T2DM morbidity risk based on MS components is easy to obtain,has strong prediction ability and wide application range,which reduces the cost of predicting the morbidity of T2DM to a certain extent,and has strong guiding significance for screening the high-risk population of T2DM morbidity. |
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