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

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Abstract：Objective：This study aimed to investigate the prevalence determinants metabolic syndrome（MetS） amongthepopulationin （Southern ），todevelopanomogram forMetS prediction.Methods：In2022， amulti-stage stratified rom sampling method wasused toselect permanent residentsaged 35years above in southern asstudyparticipants.MetSwasdefinedacordingtotheInternationalDiabetesFederation（IDF）criteria. Participants'demographics，medical history，blood biochemistrydata，anthropometric variableswerecolected to screen forsignificantvariablesforthe prediction modelMetS.Multivariablelogisticregresionwas employedto explore thefactors associatedwithMetS.Subsequently，thedataweredividedintoatrainingsetavalidationset，anomogram wasdeveloped tocreatethepredictive model forMetS.The training set wasutilizedfornomogrammodelconstruction preliminaryvalidation，whilethevalidationsetwasusedfor internalvalidation.Theperformance thenomogram was assessed basedonreceiver operating characteristic curve（ROC），calibration curves， decisioncurveanalysis （DCA）.Results：Atotal1581participants wereenrolled in thestudy，revealingaprevalence MetS 27.39 % （20 （ 95%CI ： 25.19 % -29.59 % ）.The age-stardized prevalence was calculated to be 27.81% .Ninevariableswere identifiedasinfluencingfactorsforMetS：ge，residence，occupation，historyhperlipidemia，historyhyperuricemia， hip circumference，glycated hemoglobin Alc（HbAlc），resting heart rate（RHR）， body massindex（BMI）.The participants were romlydivided into a training set （n=1 107， 70% ） a validation set （n=474， 30% ）. The nomogram wasvalidated through preliminaryvalidationarea under curve（AUC：O.844） internal validation（AUC：0.825）. Calibration plots demonstratedgoodagreementinthe trainingsets.Conclusion：The prevalence MetS isnotably high in ，.Thenomogram，whichisbasedonage，residence，occupation，history hyperlipidemia，history hyperuricemia，hipcircumference，HbAlc，RHRBMIvariables，exhibits strong predictive eficacycanbeutilizedto assess the risk MetS in middle-aged elderly populations.

KeyWords：;Metabolicsyndrome；Prevalence；Influencing factors；Nomogram CLCNumber：R589 Documentcode：A ArticleID：1001-5779（2025）09-0837-10 DOI：10.3969/j.issn.1001-5779.2025.09.003

摘要：目的：探讨赣南地区人群代谢综合征（Metabolic syndrome，MetS）的患病情况及其相关影响因素，并构建代谢综合征的患病风险列线图预测模型。（剩余24066字）