目的探讨体检人群血脂与人体成分指标的相关性并建立预测模型。方法选取贵州省2020年6—12月在我院进行体检的1 299名体检人群为调查对象,记录其人体成分及血脂数据。按照血脂水平分为正常组和异常组。采用Logistic回归分析及非限制立方样条(restricted cubic spline,RCS)分析人体成分指标对血脂的影响,以及受试者工作特征(receiver operator characteristic curve,ROC)曲线分析血脂异常预测效果。结果两组受检者在身高、年龄、体重、体脂肪、体重指数(body mass index,BMI)、体脂百分率和内脏脂肪等级差异均有统计学意义。血脂异常与肌肉质量密切相关。人体成分指标预测模型AUC达0.718,95%CI区间为0.691～0.746。年龄(OR=1.053)、BMI(OR=1.091)和体脂百分率(OR=1.100)是影响血脂异常的危险因素(P<0.05)。年龄(非线性<0.001,P<0.001)、BMI(非线性=0.171,P<0.001)和体脂百分率(非线性=0.005,<0.001)与血脂异常风险呈显著线性关系。结论人体成分指标与血脂异常相关,年龄、BMI和体脂百分率可作为血脂异常风险评估的首选方法,且增加肌肉量,降低体脂百分率是预防血脂异常的有效途径。

Objective To investigate the correlation between blood lipids and body composition indexes in the physical examination population and to establish a prediction model.Methods A total of 1 299 people who underwent physical examination in our hospital in Guizhou Province from June to December 2020 were selected as the survey subjects,and their body composition and blood lipid data were recorded.According to the level of blood lipids,they were divided into normal blood lipid group and dyslipidemia group.Logistic regression analysis and unrestricted cubic spline(RCS) were used to analyze the effect of body composition indexes on blood lipids,and receiver operating characteristic(ROC) curve was used to analyze the prediction effect of dyslipidemia.Results There were statistically significant differences in height,age,weight,body fat,BMI,body fat percentage,and visceral fat grade between the two groups.Dyslipidemia was closely related to muscle mass.The AUC of the body composition index prediction model was 0.718,and the 95% CI interval was 0.691～0.746.Age(OR=1.053),BMI(OR=1.091),and body fat percentage(OR=1.100) were risk factors for dyslipidemia(P<0.05).There were a significant linear relationship between age(nonlinear<0.001,P<0.001),BMI(nonlinear=0.171,P<0.001) and body fat percentage(nonlinear=0.005,P<0.001) and the risk of dyslipidemia.Conclusion Body composition indexes are related to dyslipidemia,and age,BMI and body fat percentage can be used as the preferred methods for dyslipidemia risk assessment,and increasing muscle mass and decreasing body fat percentage are effective ways to prevent dyslipidemia.