中国全科医学 ›› 2023, Vol. 26 ›› Issue (06): 672-680.DOI: 10.12114/j.issn.1007-9572.2022.0573

所属专题: 消化系统疾病最新文章合集 肥胖最新文章合集

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体脂成分及代谢指标与非肥胖人群代谢相关脂肪性肝病的相关性研究

王颖捷1, 程昊然2, 周卫红1,*()   

  1. 1.210008 江苏省南京市,南京大学医学院附属鼓楼医院健康管理中心
    2.30314 美国亚特兰大,埃默里大学罗林斯公共卫生学院
  • 收稿日期:2022-07-26 修回日期:2022-09-12 出版日期:2023-02-20 发布日期:2022-10-09
  • 通讯作者: 周卫红
  • 王颖捷与程昊然为共同第一作者 王颖捷,程昊然,周卫红.体脂成分及代谢指标与非肥胖人群代谢相关脂肪性肝病的相关性研究[J].中国全科医学,2023,26(6):672-680. [www.chinagp.net]
    作者贡献:王颖捷负责提出研究思路,设计研究方案,对主要研究结果进行分析与解释,撰写论文及最终版本修订;程昊然负责检索文献,数据收集、整理及统计学分析,英文修订;周卫红负责文章的质量控制,监督管理,对文章整体负责。

Correlation of Body Fat Composition and Metabolic Indicators with Metabolic-associated Fatty Liver Disease in a Non-obese Population

WANG Yingjie1, CHENG Haoran2, ZHOU Weihong1,*()   

  1. 1. Health Management Center, Nanjing Drum Tower Hospital/the Affiliated Hospital of Nanjing University Medical School, Nanjing 210008, China
    2. Rollins School of Public Health, Emory University, Atlanta 30314, USA
  • Received:2022-07-26 Revised:2022-09-12 Published:2023-02-20 Online:2022-10-09
  • Contact: ZHOU Weihong
  • About author:
    WANG Y J, CHENG H R, ZHOU W H. Correlation of body fat composition and metabolic indicators with metabolic-associated fatty liver disease in a non-obese population[J]. Chinese General Practice, 2023, 26 (6) : 672-680. WANG Yingjie and CHENG Haoran are co-first authors

摘要: 背景 近年来,代谢相关脂肪性肝病(MAFLD)患病率增长迅速,非肥胖MAFLD患者体脂成分和代谢指标的特点及各指标对该病预测价值的研究结论尚不一致。 目的 分析非肥胖MAFLD患者的体脂成分及关键代谢指标的变化特点,明确非肥胖MAFLD的危险因素,探讨以上指标与非肥胖MAFLD相关性及对该病的预测价值。 方法 选取2018年1月至2019年1月南京大学医学院附属鼓楼医院健康管理中心体检人员为研究对象,根据肝脏B超结果分为脂肪肝患者和非脂肪肝者,排除脂肪肝患者中的非MAFLD患者后,再根据体质指数(BMI)将两组体检者分为非肥胖非脂肪肝组(n=129)、肥胖MAFLD组(n=129)、肥胖非脂肪肝组(n=129)、非肥胖MAFLD组(n=129),比较非肥胖MAFLD组与其他3组间体脂成分及代谢指标,分析各指标与非肥胖MAFLD的相关性,采用Logistic回归分析明确非肥胖MAFLD的独立危险因素,采用受试者工作特征(ROC)曲线分析各指标对非肥胖MAFLD的预测价值。 结果 (1)体脂成分及代谢指标比较:非肥胖MAFLD组BMI、体脂肪(BF)、体脂率(BFR)、内脏脂肪面积(VFA)、腰围(WC)、腰臀比(WHR)、总胆固醇(TC)、三酰甘油(TG)、低密度脂蛋白胆固醇(LDL-C)、尿酸(UA)、丙氨酸氨基转移酶(ALT)及谷酰转肽酶(GGT)高于非肥胖非脂肪肝组,高密度脂蛋白胆固醇(HDL-C)低于非肥胖非脂肪肝组(P<0.05);非肥胖MAFLD组BMI、BF、VFA、WC、WHR、空腹血糖(FPG)、糖化血红蛋白(HbA1c)低于肥胖MAFLD组(P<0.05);非肥胖MAFLD组BMI、BF、WC低于肥胖非脂肪肝组,TG、UA、ALT、GGT高于肥胖非脂肪肝组(P<0.05);非肥胖MAFLD组中女性年龄、BF、BFR、VFA高于男性,WC、UA、GGT低于男性(P<0.05)。(2)Kendall's相关分析结果显示,BFR、VFA、WHR、TC、TG、LDL-C、UA、ALT、GGT与非肥胖MAFLD呈正相关(r=0.099、0.092、0.136、0.095、0.176、0.092、0.114、0.125、0.142,P<0.05),HDL-C与非肥胖MAFLD呈负相关(r=-0.112,P<0.05)。(3)多因素Logistic回归分析结果显示,TG、ALT、UA、BFR和VFA为非肥胖MAFLD的影响因素(P<0.05)。(4)BFR、VFA、TG、UA、ALT预测非肥胖MAFLD的ROC曲线下面积(AUC)分别为0.853〔95%CI(0.807,0.898)〕、0.938〔95%CI(0.906,0.970)〕、0.807〔95%CI(0.754,0.860)〕、0.665〔95%CI(0.599,0.731)〕、0.752〔95%CI(0.692,0.812)〕,灵敏度分别为0.789、0.852、0.822、0.605、0.814,特异度分别为0.770、0.904、0.713、0.682、0.770,最佳临界值分别为22.30%、61.45 cm2、1.02 mmol/L、356.00 μmol/L、18.35 U/L。 结论 非肥胖MAFLD患者与非肥胖非脂肪肝人群相比,BF及内脏脂肪增多,脂质代谢异常,UA水平升高,转氨酶上升;TG、ALT、UA、BFR和VFA为非肥胖MAFLD的影响因素;BFR、VFA、TG、UA、ALT对非肥胖MAFLD具有一定诊断价值,可用于预测非肥胖MAFLD的发生,以便尽早进行干预。

关键词: 脂肪肝, 非肥胖代谢相关脂肪性肝病, 血脂, 血糖, 尿酸, 内脏脂肪, 危险因素, 灵敏度, 特异度, 影响因素分析, 诊断

Abstract:

Background

The prevalence of metabolic-associated fatty liver disease (MAFLD) has increased rapidly. And there is no conclusion on body fat composition, characteristics of metabolic indicators, and their predictive values for MAFLD in non-obese populations.

Objective

To identify the risk factors for MAFLD by comparing body fat composition and key metabolic indicators (blood lipids, blood sugar, uric acid) between obese and non-obese MAFLD patients, and to assess their associations with MAFLD as well as their predictive values for MAFLD in non-obese patients.

Methods

Physical examinees with and without liver B-ultrasound-detected fatty liver were recruited from Health Management Center, Nanjing Drum Tower Hospital from January 2018 to January 2019 after excluding those with non-MAFLD, and divided into obese group (including 129 cases with MAFLD, and 129 without fatty liver) and non-obese group (including 129 without fatty liver cases, and 129 with MAFLD) by BMI. The body fat composition and metabolic indices in non-obese MAFLD cases were compared with those of the other three subgroups. The correlation of each index with MAFLD in non-obese cases was analyzed. The independent risk factors of MAFLD in non-obese cases were identified by using Logistic regression. The predictive value of each index for MAFLD in non-obese was assessed using the receiver operating characteristic (ROC) curve.

Results

(1) Comparison of body fat composition and metabolic indicators: compared with non-obese without fatty liver cases, non-obese cases with MAFLD had greater average BMI, body fat (BF), body fat ratio (BFR), visceral fat area (VFA), waist circumference (WC), waist-hip-ratio (WHR), total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), uric acid (UA), alanine transaminase (ALT) and gamma-glutamyl transpeptidase (GGT), and lower high-density lipoprotein cholesterol (HDL-C) (P<0.05). In comparison with obese cases with MAFLD, non-obese cases with MAFLD had lower average BMI, BF, VFA, WC, WHR, fasting plasma glucose (FPG), and glycosylated hemoglobin (HbA1c) (P<0.05). Non-obese cases with MAFLD had lower average BMI, BF and WC, and higher average TG, UA, ALT and GGT than obese cases without fatty liver (P<0.05). Non-obese female cases with MAFLD had greater average age, BF, BFR and VFA and lower WC, VA, GGT than non-obese male cases with MAFLD (P<0.05). (2) Kendall's rank correlation analysis showed that the risk of MAFLD in non-obese cases increased with the growth of BFR, VFA, WHR, TC, TG, LDL-C, UA, ALT, and GGT (r=0.099, 0.092, 0.136, 0.095, 0.176, 0.092, 0.114, 0.125, 0.142, P<0.05), but decreased with the growth of HDL-C (r=-0.112, P<0.05). (3) Multivariate Logistic regression analysis showed that TG, ALT, UA, BFR and VFA were risk factors of MAFLD in non-obese cases. (4) The results of ROC analysis of the performance of five indicators predicting MAFLD in non-obese cases were as follows: BFR had an AUC of 0.853〔95%CI (0.807, 0.898) 〕, with 0.789 sensitivity, 0.770 specificity when 22.30% was chosen as the optimal cut-off value; VFA had an AUC of 0.938〔95%CI (0.906, 0.970) 〕, with 0.852 sensitivity, 0.904 specificity when 61.45 cm2 was chosen as the optimal cut-off value; TG had an AUC of 0.807〔95%CI (0.754, 0.860) 〕, with 0.822 sensitivity, 0.713 specificity when 1.02 mmol/L was chosen as the optimal cut-off value; UA had an AUC of 0.665〔95%CI (0.599, 0.731) 〕, with 0.605 sensitivity, 0.682 specificity when 356.00 μmol/L was chosen as the optimal cut-off value; ALT had an AUC of 0.752〔95%CI (0.692, 0.812) 〕, with 0.814 sensitivity, 0.770 specificity when 18.35 U/L was chosen as the optimal cut-off value.

Conclusion

Compared with non-obese people without fatty liver, non-obese people with MAFLD had increased BF and visceral fat, abnormal lipid metabolism, elevated levels of UA and transaminase. The risk of MAFLD in non-obese people increased with the increase in TG, ALT, UA, BFR and VFA, but decreased with the increase in HDL-C. BFR, VFA, TG, UA and ALT could partially predict and diagnose MAFLD in non-obese people, providing evidence for the delivery of interventions as soon as possible.

Key words: Fatty liver, Nonobese metabolic fatty liver disease, Blood lipid, Blood glucose, Uric acid, Visceral fat, Risk factors, Sensitivity, Specificity, Root cause analysis, Diagnosis