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脂滴蓄积产物是诊断美国成年人代谢功能障碍相关脂肪性肝病的有力工具。

The lipid accumulation product is a powerful tool to diagnose metabolic dysfunction-associated fatty liver disease in the United States adults.

机构信息

Department of Endocrinology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.

出版信息

Front Endocrinol (Lausanne). 2022 Nov 4;13:977625. doi: 10.3389/fendo.2022.977625. eCollection 2022.

DOI:10.3389/fendo.2022.977625
PMID:36407325
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9672518/
Abstract

BACKGROUND & OBJECTIVES: Body mass index (BMI) and waist circumference (WC) are widely used to assess obesity, but they are limited in their ability to distinguish complicated body metabolic situations (fat mass, lean body mass, visceral and subcutaneous fat deposits in the abdomen). The purpose of this study was to evaluate the diagnostic efficacy of different anthropometric indices in metabolic dysfunction-associated fatty liver disease (MAFLD) and to identify the best cut-off point for the diagnosis of MAFLD in United States adults.

METHODS

A cross-sectional study among 4,195 participants over 18 years old in the National Health and Nutrition Examination Survey (NHANES) 2017-2018 was performed. All patients underwent vibration controlled transient elastography (VCTE). Assess the anthropometric measurements, including BMI, WC, waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), cardiometabolic index (CMI), triglyceride-glucose (TyG) index, hepatic steatosis index (HSI), lipid accumulation product (LAP), body roundness index (BRI), visceral fat index (VAI), abdominal volume index (AVI), cone index (CI), and body fat index (BAI). Logistic regression analyses were conducted to estimate the impact of these indices, on the odds ratio (OR) values of MAFLD. Receiver operator characteristic (ROC) analyses were performed to assess the diagnosing capacity of these anthropometric indices for MAFLD and identify the optimal cut-offs points.

RESULTS

A total of 4,195 (2,069 men and 2,126 women) participants were performed, with 45.4 ± 0.64 (mean ± SD) years old. All anthropometric metrics were positively associated with MAFLD, irrespective of whether it was treated as continuous or categorical variable (P<0.05). Multivariate logistic regression showed a positive correlation between AVI, HSI, WHtR, BRI, and MAFLD, with significant interaction with gender. ROC curves results showed that LAP had the highest AUC [0.813 (95% CI, 0.800-0.826)], especially in participants aged between 18 and 50 years old. Furthermore, LAP showed the highest ROC in both the training set [0.812 (95% CI, 0.800-0.835)] and the validation set [0.809 (95% CI, 0.791-0.827)].

CONCLUSIONS

In the present study, we showed that those anthropometric indices were significantly associated with MAFLD in United States adults. Besides, the association of HSI, BRI, AVI, and WHtR with MAFLD was more obvious in men than in women. LAP may be a sensitive marker for diagnosing MAFLD in U.S. adults.

摘要

背景与目的

体重指数(BMI)和腰围(WC)广泛用于评估肥胖,但它们在区分复杂的身体代谢情况(脂肪量、瘦体重、腹部内脏和皮下脂肪沉积)方面能力有限。本研究旨在评估不同人体测量指标在代谢相关脂肪性肝病(MAFLD)中的诊断效能,并确定美国成年人 MAFLD 诊断的最佳截断点。

方法

对 2017-2018 年全国健康与营养调查(NHANES)中 4195 名 18 岁以上成年人进行横断面研究。所有患者均接受振动控制瞬态弹性成像(VCTE)检查。评估人体测量指标,包括 BMI、WC、腰高比(WHtR)、腰臀比(WHR)、心脏代谢指数(CMI)、甘油三酯-葡萄糖(TyG)指数、肝脂肪指数(HSI)、脂质蓄积产物(LAP)、体圆度指数(BRI)、内脏脂肪指数(VAI)、腹部体积指数(AVI)、锥指数(CI)和体脂指数(BAI)。进行逻辑回归分析,以估计这些指标对 MAFLD 的比值比(OR)值的影响。进行受试者工作特征(ROC)分析,以评估这些人体测量指标对 MAFLD 的诊断能力,并确定最佳截断点。

结果

共纳入 4195 名(2069 名男性和 2126 名女性)参与者,年龄为 45.4±0.64(均值±标准差)。所有人体测量指标均与 MAFLD 呈正相关,无论作为连续变量还是分类变量(P<0.05)。多变量逻辑回归显示,AVI、HSI、WHtR、BRI 与 MAFLD 呈正相关,与性别存在显著交互作用。ROC 曲线结果显示,LAP 的 AUC 值最高[0.813(95%CI,0.800-0.826)],特别是在 18-50 岁的参与者中。此外,LAP 在训练集[0.812(95%CI,0.800-0.835)]和验证集[0.809(95%CI,0.791-0.827)]中均具有最高的 ROC。

结论

本研究表明,这些人体测量指标在美国成年人中与 MAFLD 显著相关。此外,HSI、BRI、AVI 和 WHtR 与 MAFLD 的关联在男性中比在女性中更为明显。LAP 可能是美国成年人诊断 MAFLD 的敏感标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e15/9672518/4f524266948d/fendo-13-977625-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e15/9672518/d11cff4908d5/fendo-13-977625-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e15/9672518/a667a5a7d9ef/fendo-13-977625-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e15/9672518/a0709dd86301/fendo-13-977625-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e15/9672518/4f524266948d/fendo-13-977625-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e15/9672518/d11cff4908d5/fendo-13-977625-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e15/9672518/a667a5a7d9ef/fendo-13-977625-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e15/9672518/a0709dd86301/fendo-13-977625-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e15/9672518/4f524266948d/fendo-13-977625-g004.jpg

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