| ObjectiveThe research aims to identify the priority issues the main intervention population.by analyzing the prevalence,the risk factors and their influencing factors of diabetes in Guangdong Province.At the same time,a diabetes risk prediction model for this population is established to provide a reasonable and effective prediction tool for the prevention and control of diabetes.Materials and MethodsAdult residents who had lived for more than 6 months were selected from 14 disease surveillance sites in Guangdong Province in 2015 to investigate the risk factors for chronic diseases.The complex weighted method was used to analyze the prevalence of diabetes,the main risk factors and the corresponding influencing factors of adult residents in Guangdong Province.Group comparisons and univariate analysis of categorical variables were performed using the?~2 test,and multivariate analysis was performed using unconditional logistic regression.Logistic regression and neural network methods were used to construct a non-invasive diabetes risk prediction model(scoring model and screening model)for adult residents in Guangdong Province.The scoring model used the ten-fold regression coefficient method to calculate the total risk score.The screening model used MLP and RBF neural networks Make predictions.Result(1)After complex weighted adjustments,the prevalence of diabetes in Guangdong’s adult residents was 5.0%in 2015,with men(5.7%)higher than women(4.3%),and rural(5.9%)higher than cities(4.6%);except for the elderly The prevalence of diabetes in all populations(aged 80 years and over)increased with age.In terms of cultural and occupational distribution,those with primary and below education(7.9%)and household and retired groups(6.7%)Has the highest prevalence of diabetes.(2)The univariate analysis results of diabetes risk factors showed that in the diet:excessive intake of edible salt(P=0.5843),insufficient intake of fruit(P=0.6925),and excessive intake of red meat(P=0.8204)are not risk factors,only insufficient vegetable intake(P=0.0230)is one of the risk factors;in terms of lifestyle:smoking(P=0.9648),second-hand smoke(P=0.1617),and sedentary(P=0.6969)are not risk factors,while excessive drinking(P=0.0195)and insufficient sleep(P=0.0092)are risk factors,while physical exercise is a protective factor(P<0.0001);in physiological and biochemical indicators:overweight and obesity(P<0.0001),centripetality Obesity(P<0.0001),hypertension(P<0.0001),and dyslipidemia(P<0.0001)are all risk factors.Multivariate analysis results showed that:rural(OR=1.289),age(OR:2.870～3.953),overweight and obesity(OR=1.249,1.573),central obesity(OR=1.629),hypertension(OR:1.147～1.466),and Dyslipidemia(OR=1.576)are risk factors for diabetes,and physical exercise(OR=0.676)is a protective factor.(3)The results of analysis of the influencing factors of the main risk factors showed(after complex weighted adjustment):the total prevalence of overweight and obesity in adult residents in Guangdong Province was31.6%,and the prevalence of concentric obesity was 19.1%.Low-education people,household chores and retirees are high-risk groups in common.From the perspective of behavioral factors,smoking is a common protective factor,and sedentary and insufficient sleep are common risk factors.The prevalence of hypertension among adult residents in Guangdong Province is 16.8%,and the prevalence of dyslipidemia is40.6%.Male groups,rural residents,low-educated people,household chores and retirees are high-risk groups with high blood pressure and dyslipidemia.From the perspective of behavioral factors,insufficient fruit intake,excessive alcohol consumption,insufficient sleep,and physical exercise hypertension are risk factors.As for dyslipidemia,smoking is the main behavioral risk factor.(4)After the total sample was stratified according to whether it has diabetes,age,gender,and urban-rural,there was no difference in the distribution of baseline characteristics of the total sample,(70%)modeling group,and(30%)test group.The non-invasive indicators finally included in the diabetes non-invasive risk score model are urban and rural,age,physical exercise,overweight and obesity,concentric obesity and hypertension.The overall AUC of the diabetes risk score model was 0.786(95%CI:0.777～0.795).The overall AUC of the neural network-based diabetes screening model was between 0.636 and 0.670,and the correct rate was between 89.4%and 90.0%.ConclusionIn 2015,the prevalence of diabetes in Guangdong’s adult residents was lower than that in 2013,and it was higher in rural areas than in urban areas.Real-life people(60～79 years old),household chores,retirees,and people with primary education or below The main population for diabetes health education activities and disease management.People who are overweight,obese,high blood pressure and dyslipidemia should strengthen the regular monitoring and management of blood glucose,take appropriate amount of fruits and vegetables,and actively participate in various appropriate forms of exercise to achieve early prevention,early detection,early diagnosis and early treatment of diabetes.The non-invasive prediction model established in this study is suitable for screening and self-monitoring of high-risk groups of diabetes,and has certain guidance and reference for disease prevention and control. |
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