| BackgroundDiabetes mellitus is one of the key chronic non-communicable diseases,and it has caused great burden to human health,economy and society.With the development of disease,new risk factors and complications continue to increase,and the complexity of diabetes mellitus and its complications continue to emerge.At the same time,the rapid development of information science has provided new thinking for technological innovation in various fields,and also provided new opportunities for innovation in health care management models.Therefore,to explore the risk factors of diabetes mellitus and their association with complications in an all-round way,and to apply the integrated disease management model supported by emerging technology have important guiding significance for the prevention and control of diabetes mellitus.ObjectiveThis study focused on the comprehensive management of risk factors prevention and control of diabetes,and was based on multi-source data mining and classification of diabetes risk factors.It was aimed to evaluate the risk intensity and evidence level of risk factors,and identify common risk factors for different types of diabetes.The dynamic cohort data was used to explore the association between risk factors and type2 diabetes and its complications,and the impact of different complications on type 2diabetes outcomes.Meanwhile,the study was also aimed to explore the construction of a comprehensive management model for type 2 diabetes and complications,conducte a comparative empirical test,evaluate the intervention effect of the integrated management model on type 2 diabetes and complications,and propose an optimization strategy for prevention and control management.Methods1.The English databases of Pubmed,Web of science,Embase and Cochrane Library were searched,and the meta-analysis and original literature research on diabetes risk factors were screened according to the literature inclusion criteria,and the corresponding risk factors were extracted.Risk factors are classified according to the level of risk factors in the Global Burden of Diseases(GBD).AMSTAR scoring tool was used to evaluate the quality of the meta-analysis from 11 evaluation indicators.Cytoscape software was used to visualize the risk factors of different types of diabetes mellitus.The heterogeneity evaluation index and bias evaluation index were calculated by software Stata 14.0.Evidence grade evaluation of risk factors was divided into four grades: I,II,III and IV.2.We analyzed qualitative data by chi-square test,we analyzed quantitative data by t-test or variance analysis by using SPSS 22.0 software.We also analyzed the dynamic queue baseline data by descriptive statistics.The association rules based on Apriori algorithm were used to analyze the relationship between risk factors and type2 diabetes mellitus,complications(hypertension,hyperlipidemia,coronary heart disease,liver disease,kidney disease),and the distribution of complications in type 2diabetes mellitus by using R software.We modeled the outcomes of 16 indices of longitudinal data of different complications of type 2 diabetes mellitus by using generalized estimation equation.3.Based on PDCA theoretical framework,the comprehensive management model of diabetes mellitus was constructed,and the effect of the comprehensive management model of type 2 diabetes mellitus was evaluated.The results of follow-up observation at different time points in the integrated management group and the conventional control group were compared by using repeated measurement design variance analysis and mixed effect model in SPSS 22.0 software.Results1.This study identified 291 risk factors associated with different types of diabetes,including T1 DM,T2DM,GDM,LADA,PTDM and DMAAP.Risk factors were distributed into five levels,including seven categories in the first level:environmental/occupational risks,behavioral risks,metabolic risks,health intervention,social/psychological/cultural/economic risks,disease and treatment.The results of network analysis showed that the available evidence support that 24 risk factors were associated with at least two types of diabetes.Among them,high BMI was a common risk factor for four types of diabetes: T1 DM,T2DM,GDM and LADA.In addition,high BMI and vitamin D deficiency were common risk factors for three types of diabetes: T1 DM,T2DM and GDM.Active smoking was a common risk factor for three types of diabetes: T2 DM,GDM and LADA.Evidence grade evaluation showed that caesarean section was the type I evidence of risk factors related to T1 DM.Apple and pear,total protein,sugary beverage intake,nicotinic acid therapy,preterm delivery,sex and serum vitamin D were the type I evidence of risk factors related to T2 DM.Weight gain during pregnancy was the type I evidence of risk factors related to GDM.2.In this study,association rules were used to mine risk factors for different complications.The results of single rule analysis showed that e GFR and UA were correlated with hypertension to some extent.TG,GGT,LDL had a certain degree of correlation with hyperlipidemia;e GFR,CHOL and coronary heart disease had a certain degree of correlation;ALT,GGT,P2 BG and liver disease had a certain degree of correlation;CREA,PRO,e GFR and kidney disease had a certain degree of correlation.Comorbidity pattern analysis showed that comorbid hypertension and hyperlipidemia was the most common pattern.The results of generalized estimating equation showed that there were significant statistical differences in 12 biochemical indicators including Hb A1 c,P2BG,CHOL,TG,LDL,HDL,GGT,ALT,AST,CREA,UA and PRO(P < 0.05).3.Based on the PDCA theoretical framework,the comprehensive diabetes management model was constructed,including risk assessment,health intervention,follow-up monitoring and effect evaluation.The results of variance analysis of repeated measurement design showed that there were significant differences in ALT indexes,time points(baseline,6 months,12 months)and interaction between groups and time between the integrated management group and the conventional management group(P < 0.05).The results showed that the level of ALT in the integrated management group was significantly lower than that in the conventional management group.Compared with the baseline,the level of ALT in the two groups showed a downward trend.The results of mixed effect model showed that there were significant differences in the changes of P2 BG,GGT,ALT,AST,UREA and HGB between the comprehensive management group and the conventional control group(P< 0.05),and the comprehensive management group was better than the control group.ConclusionThis study identified 291 multidimensional risk factors for diabetes,nine of which were evaluated as class I evidence.Risk factors have an interactive relationship with the main complications of type 2 diabetes mellitus,and different complications have a significant impact on the outcome of the indicators of type 2 diabetes mellitus.For the evaluation of the empirical effect,the overall effect of the comprehensive management group of diabetes risk and complications in reducing blood sugar and lipid levels and improving liver and kidney function is significantly better than that of the conventional management group.These findings will provide a new perspective for comprehensive prevention and control strategy of diabetes mellitus.Policy SuggestionsThis study proposes the following policy suggestions from three aspects:constructing a comprehensive prevention and control system for diabetes risk factors,realizing the joint management of diseases and complications,and applying the integrated management model supported by emerging technology.1.Establish a monitoring system for diabetes risk factors and clarify the roles of different management subjects.2.Strengthen the identification and prediction of diabetes risk factors,and consolidate grassroots prevention and control work.3.Adopt targeted preventive management measures to enhance individual prevention and control capabilities.4.Establish a risk prediction model for complications to curb the early onset of chronic diseases.5.Integrate the mechanism associated with diabetes and its complications,and improve the clinical pathway formulation.6.Develope prevention and control strategies for chronic disease,and realize joint management of multiple complications.7.Integrate a multidimensional prevention and treatment model based on emerging technologies,and facilitate the all-round management of diabetes.8.Regulate the management of chronic disease information,and promote health big data interconnection and commonality.9.Promote the application of big data in health care and build community health information platform.10.Implement comprehensive management strategies,and improve public health literacy and prevention and control level. |
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