石河子市某体检人群肥胖及部分指标相关因素分析

Analysis of Obesity and Some Indicator-related Factors in a Medical Examination Population in Shihezi City

目的:探索石河子地区体检人群不同体质指数(Body Mass Index,BMI)与肥胖相关指标异常检出率的差异并分析相关危险因素,为后续的疾病防治提供科学建议。方法:选取2019年5月至2022年5月三年间石河子大学第一附属医院健康管理中心体检的人群,将其相关指标[BMI、血压(BP)、血糖(Glu)、血尿酸(sUA)、甘油三酯(TG)、总胆固醇(TC)、同型半胱氨酸(Hcy)和脂肪肝(FLD)]从体检系统中导出后创建EXCEL数据库,使用SPSS23.0软件进行统计分析。结果:(1)BMI分别与收缩压(SBP)、舒张压(DBP)、sUA、TG、TC和Glu呈正相关(P<0.05);(2)三年共同危险因素:高尿酸血症的危险因素为BMI、性别和FLD;高糖血症的危险因素为年龄与sUA;高胆固醇血症的危险因素为TG;高甘油三酯血症的危险因素为Glu、sUA、TC和FLD;高同型半胱氨酸血症的危险因素为性别与sUA;脂肪肝的危险因素为BMI、sUA和TG。结论:(1)经BMI分组后,SBP、DBP、sUA、TG、TC和Glu水平与异常检出率随BMI增加而升高;(2)选取经单因素分析后有统计学意义的指标创建二元Logistic回归模型后,相关变量间互为危险因素。

Objective:To explore the difference of abnormal detection rate of obesity-related indexes among different body mass index(BMI)physical examination population in Shihezi region and analyze the related risk factors,so as to provide scientific suggestions for subsequent disease prevention and treatment.Methods:The indicators related to obesity in the health management center of First Affiliated Hospital,School of Medicine,Shihezi University during the three-year period from May 2019 to May 2022 were selected:BMI,blood pressure(BP),blood glucose(Glu),blood uric acid(sUA),triglycerides(TG),total cholesterol(TC),homocysteine(Hcy),and fatty liver(FLD),were exported through the physical examination system to create an EXCEL database,and statistical analysis was performed by SPSS23.0 software.Results:(1)BMI was positively correlated with systolic blood pressure(SBP),diastolic blood pressure(DBP),sUA,TG,TC and Glu,respectively(P<0.05).(2)Three-year common risk factors:the risk factors for hyperuricemia were BMI,gender and FLD.Risk factors for hyperglycemia were age and sUA.Risk factors for hypercholesterolemia were TG.Risk factors for hypertriglyceridemia were Glu,sUA,TC&FLD.Risk factors for hyperhomocysteinemia were gender and sUA.Risk factors for fatty liver were BMI,sUA&TG.Conclusions:(1)After BMI grouping,the levels of SBP,DBP,sUA,TG,TC and Glu and the abnormality detection rate increased with the increase of BMI.(2)After selecting indicators that were statistically significant after univariate analysis and establishing a binary logistic regression model,the relevant variables were mutually risk factors.