代谢综合征的影响因素分析及列线图模型构建:横断面研究OA

Objective:This study aimed to investigate the prevalence and determinants of metabolic syndrome(MetS)among the population in Gannan(Southern Jiangxi),and to develop a nomogram for MetS prediction.Methods:In 2022,a multi-stage stratified random sampling method was used to select permanent residents aged 35 years and above in southern Jiangxi as study participants.MetS was defined according to the International Diabetes Federation(IDF)criteria.Participants'demographics,medical history,blood biochemistry data,and anthropometric variables were collected to screen for significant variables for the prediction model of MetS.Multivariable logistic regression was employed to explore the factors associated with MetS.Subsequently,the data were divided into a training set and a validation set,and a nomogram was developed to create the predictive model for MetS.The training set was utilized for nomogram model construction and preliminary validation,while the validation set was used for internal validation.The performance of the nomogram was assessed based on receiver operating characteristic curve(ROC),calibration curves,and decision curve analysis(DCA).Results:A total of 1 581 participants were enrolled in the study,revealing a prevalence of MetS of 27.39%(95%CI:25.19%-29.59%).The age-standardized prevalence was calculated to be 27.81%.Nine variables were identified as influencing factors for MetS:age,residence,occupation,history of hyperlipidemia,history of hyperuricemia,hip circumference,glycated hemoglobin A1c(HbA1c),resting heart rate(RHR),and body mass index(BMI).The participants were randomly divided into a training set(n=1 107,70%)and a validation set(n=474,30%).The nomogram was validated through preliminary validation area under curve(AUC:0.844)and internal validation(AUC:0.825).Calibration plots demonstrated good agreement in the training sets.Conclusion:The prevalence of MetS is notably high in Ganzhou,Jiangxi.The nomogram,which is based on age,residence,occupation,history of hyperlipidemia,history of hyperuricemia,hip circumference,HbA1c,RHR and BMI variables,exhibits strong predictive efficacy and can be utilized to assess the risk of MetS in middle-aged and elderly populations.