体圆指数对代谢相关脂肪性肝病发生风险的预测价值

张琪振; 刘素彤; 张丽慧; 刘鸣昊

doi:10.12449/JCH251015

体圆指数对代谢相关脂肪性肝病发生风险的预测价值

DOI: 10.12449/JCH251015

张琪振^{1, 2},
刘素彤¹,
张丽慧¹,
刘鸣昊^{1, 3, 4, , ,}

1.
河南中医药大学第一附属医院脾胃肝胆科，郑州 450000
2.
河南中医药大学第一临床医学院，郑州 450000
3.
中西医防治重大疾病河南省协同创新中心，河南开封 475399
4.
豫药全产业链研发河南省协同创新中心，郑州 450007

基金项目:

国家自然科学基金 (81904154);

国家自然科学基金 (82205086);

河南省科技攻关计划 (242102310500);

河南省“双一流”创建学科中医学科学研究专项 (HSRP-DFCTCM-2023-1-10);

河南省科技研发计划联合基金（优势学科培育类） (242301420096);

河南省科技研发计划联合基金（优势学科培育类） (242301420021);

河南省卫生健康委员会中医药传承创新专项 (2023ZXZX1162)

伦理学声明：本研究所用数据来源于NHANES，该项目已获得美国国家卫生统计中心（NCHS）研究伦理审查委员会（ERB）批准，NCHS IRB/ERB协议编号：Protocol #2011-17、Protocol #2018-01。所有调查对象均签署了书面知情同意书。

利益冲突声明：本文不存在任何利益冲突。

作者贡献声明：张琪振负责论文撰写，统计学分析，绘制图表；刘素彤、张丽慧参与研究数据的获取；刘鸣昊负责拟定写作思路，指导论文撰写并提供研究经费。

详细信息

通信作者:
刘鸣昊， liumh015@163.com （ORCID： 0009-0001-7712-4605）

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出版历程
- 收稿日期: 2025-04-23
- 录用日期: 2025-07-21
- 出版日期: 2025-10-25

Value of body roundness index in predicting the risk of metabolic dysfunction-associated fatty liver disease

Qizhen ZHANG^{1, 2},
Sutong LIU¹,
Lihui ZHANG¹,
Minghao LIU^{1, 3, 4
, ,
,}

1.
Department of Spleen，Stomach，Liver and Gallbladder，The First Affiliated Hospital of Henan University of Chinese Medicine，Zhengzhou 450000，China
2.
The First Clinical Medical College of Henan University of Chinese Medicine，Zhengzhou 450000，China
3.
Collaborative Innovation Center of Prevention and Treatment of Major Diseases by Chinese and Western Medicine，Kaifeng，Henan 475399，China
4.
Collaborative Innovation Center of Research and Development on the Whole Industry Chain of Yu-Yao，Zhengzhou 450007，China

Research funding:

National Natural Science Foundation of China (81904154);

National Natural Science Foundation of China (82205086);

Henan Province Science and Technology Research Program (242102310500);

Special Scientific Research Project on Traditional Chinese Medicine under the “Double First-Class” Initiative in Henan Province (HSRP-DFCTCM-2023-1-10);

Joint Fund of the Henan Provincial Science and Technology Research Program （Project of Advantageous Discipline Cultivation） (242301420096);

Joint Fund of the Henan Provincial Science and Technology Research Program （Project of Advantageous Discipline Cultivation） (242301420021);

Traditional Chinese Medicine Inheritance and Innovation Project of Henan Provincial Health Commission (2023ZXZX1162)

More Information

Corresponding author: LIU Minghao， liumh015@163.com （ORCID： 0009-0001-7712-4605）

摘要

摘要: 目的基于美国国家健康与营养调查（NHANES）数据库，系统评估体圆指数（BRI）与代谢相关脂肪性肝病（MAFLD）风险的关联性，并探讨BRI作为非侵入性风险预测工具的临床应用价值。方法利用2015—2020年NHANES数据，将纳入人群（n=4 573）分为 MAFLD组（n=2 508）和non-MAFLD组（n=2 065），计算各参与者的BRI。为确保数据质量并减少异常值对分析结果的干扰，本研究采用箱线图方法对BRI进行异常值剔除，从而提高数据的稳健性。计量资料两组间比较采用Wilcoxon秩和检验；计数资料两组间比较采用χ²检验。为探讨BRI与MAFLD之间的关系，构建多重调整的Logistic回归模型。将BRI根据四分位数分为4组，以第1个四分位数（Q1）为参考并计算3个模型中的比值比（OR）和95%可信区间（95%CI）。应用限制性立方样条分析探讨BRI与MAFLD之间的效应剂量关系。为评估BRI对MAFLD的诊断效能，绘制受试者操作特征曲线（ROC曲线），并计算曲线下面积（AUC）。采用决策曲线分析评估模型在实际应用中的潜在临床价值。通过交互作用分析和亚组分析，探讨不同人群中BRI与MAFLD关联的差异。采用Lasso回归进行特征变量筛选与分析。结果与non-MAFLD组相比，MAFLD组受试者的BRI显著升高（Z=36.29，P<0.001）。在完全校正Logistic回归模型（调整年龄、性别、种族、受教育程度、贫困收入比、婚姻状况、吸烟状况、高血压、糖尿病、ALT、AST、GGT及高密度脂蛋白胆固醇等变量）中，BRI与MAFLD患病风险呈显著正相关（OR=2.53，95%CI：2.28～2.80，P<0.001）。此外，BRI最高四分位数（Q4）组MAFLD风险明显高于Q1组（OR=83.45，95%CI：51.87～134.26，P<0.001）。限制性立方样条分析进一步确认了BRI与MAFLD之间存在显著的非线性关系（P for nonlinear<0.001）。交互作用与亚组分析显示，高血压与BRI之间的交互作用具有统计学意义（P_交互=0.003）；与无高血压者相比，在高血压人群中，BRI与MAFLD的关联性更强（OR=1.60，95%CI：1.23～2.08，P<0.001）。ROC曲线分析显示，以BRI为核心构建的完全校正模型在区分MAFLD与非MAFLD方面具有较高判别力，AUC为0.887（95%CI：0.877～0.896）。决策曲线分析显示，在临床常用的风险阈值0.10～0.75范围内，完全校正模型具有较好的净获益。Lasso回归筛选关键变量后建立的模型AUC为0.882（95%CI：0.872～0.892），验证了预测结果的稳定性。结论 BRI与MAFLD风险存在显著的正向关联，且在高血压人群中相关性更强。BRI作为反映腹型肥胖和内脏脂肪积聚的体型指标，在MAFLD的风险评估中具有良好的应用前景。
- 代谢相关脂肪性肝病 /
- 体圆指数 /
- 危险性评估
Abstract: Objective To investigate the association between body roundness index （BRI） and the risk of metabolic dysfunction-associated fatty liver disease （MAFLD） based on the National Health and Nutrition Examination Survey （NHANES） database， as well as the clinical value of BRI as a noninvasive tool for risk prediction. Methods Based on the NHANES data in 2015—2020， the 4 573 individuals were divided into MAFLD group with 2 508 individuals and non-MAFLD group with 2 065 individuals， and BRI was calculated for each individual. In order to ensure data quality and reduce the impact of abnormal values on analytical results， the boxplot method was used to remove abnormal levels of BRI and improve the robustness of data. The Wilcoxon rank-sum test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. The multivariate Logistic regression model was established to investigate the association between BRI and MAFLD. BRI was divided into four groups based on quantiles， and with the first quantile （Q1） as reference， odds ratio （OR） and 95% confidence interval （CI） were calculated for the other three models. Restricted cubic spline was used to investigate the dose-effect relationship between BRI and MAFLD. The receiver operating characteristic （ROC） curve was plotted and the area under the ROC curve （AUC） was calculated to assess the efficacy of BRI in the diagnosis of MAFLD. The decision curve analysis was used to investigate the potential clinical value of the model in clinical practice. The interaction analysis and the subgroup analysis were performed to investigate the difference in the association between BRI and MAFLD between different populations. The Lasso regression analysis was conducted for the screening and analysis of characteristic variables. Results Compared with the non-MAFLD group， the MAFLD group had a significantly higher BRI （Z=36.29， P<0.001）. After adjustment for the variables including age， sex， ethnicity， educational level， the proportion of individuals with poor income， marital status， smoking， hypertension， diabetes， alanine aminotransferase， aspartate aminotransferase， gamma-glutamyl transpeptidase， and high-density lipoprotein cholesterol， the fully adjusted Logistic regression model showed that BRI was significantly positively associated with the risk of MAFLD （OR=2.53， 95%CI： 2.28 — 2.80， P<0.001）. In addition， the highest BRI quartile （Q4） group had a significantly higher risk of MAFLD than the lowest quartile （Q1） group （OR=83.45， 95%CI： 51.87 — 134.26， P<0.001）. The restricted cubic spline analysis further confirmed the significant nonlinear association between BRI and MAFLD （P for nonlinear<0.001）. The interaction analysis and the subgroup analysis showed that the interaction between hypertension and BRI had statistical significance （P for interaction=0.003）， and compared with the individuals without hypertension， the individuals with hypertension had a stronger association between BRI and MAFLD （OR=1.60， 95%CI： 1.23 — 2.08， P<0.001）. The ROC curve analysis showed that the fully adjusted model based on BRI had a strong discriminatory ability in differentiating MAFLD from non-MAFLD， with an AUC of 0.887 （95%CI： 0.877 — 0.896）. The decision curve analysis showed that the fully adjusted model had good net benefits within the risk threshold of 0.10 — 0.75， which was commonly used in clinical practice. The model based on the key variables identified by the Lasso regression analysis had an AUC of 0.882 （95%CI： 0.872 — 0.892）， which confirmed the robustness of the prediction results. Conclusion There is a significant positive correlation between BRI and the risk of MAFLD， with a stronger association observed in the hypertensive population. As a body index reflecting abdominal obesity and visceral fat accumulation， BRI shows promising application prospects in the risk assessment of MAFLD.
- Metabolic Dysfunction-Associated Fatty Liver Disease /
- Body Roundness Index /
- Risk Assessment

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图 1 BRI与MAFLD的剂量-反应关系曲线

Figure 1. Dose-response relationship between BRI and MAFLD

下载: 全尺寸图片幻灯片

注： a，ROC曲线；b，决策曲线。

图 2 BRI预测MAFLD的ROC曲线与决策曲线分析

Figure 2. ROC curve and decision curve analysis for BRI in predicting MAFLD

下载: 全尺寸图片幻灯片

注： a，Lasso回归模型中各变量系数随λ值变化的路径图；b，Lasso回归模型的交叉验证损失均值随λ值变化的折线图，红色虚线为最优λ；c，Lasso回归模型与完全校正模型预测MAFLD的ROC曲线比较。

图 3 Lasso回归分析与完全校正模型预测性能比较

Figure 3. Comparison of predictive performance between Lasso regression and the fully adjusted model

下载: 全尺寸图片幻灯片

表 1 研究队列的基线特征

Table 1. Baseline characteristics of the study cohort

变量	总计（n=4 573）	non-MAFLD组（n=2 065）	MAFLD组（n=2 508）	统计值	P值
年龄（岁）	50.00（35.00～63.00）	45.00（31.00～62.00）	54.00（40.00～64.00）	Z=8.23	<0.001
性别［例（%）］				χ²=21.82	<0.001
男	2 300（50.30）	960（46.49）	1 340（53.43）
女	2 273（49.70）	1 105（53.51）	1 168（46.57）
种族［例（%）］				χ²=34.95	<0.001
墨西哥裔美国人	634（13.86）	233（11.28）	401（15.99）
非西班牙裔白人	1 646（35.99）	708（34.29）	938（37.40）
非西班牙裔黑人	1 015（22.20）	498（24.12）	517（20.61）
其他种族	1 278（27.95）	626（30.31）	652（26.00）
教育程度［例（%）］				χ²=16.06	<0.001
高中以下学历	857（18.74）	360（17.43）	497（19.82）
高中或同等学历	1 055（23.07）	437（21.16）	618（24.64）
高中以上学历	2 661（58.19）	1 268（61.40）	1 393（55.54）
婚姻状况［例（%）］				χ²=53.60	<0.001
已婚/与伴侣同居	2 782（60.84）	1 195（57.87）	1 587（63.28）
离婚/分居/丧偶	980（21.43）	410（19.85）	570（22.73）
从未结婚	811（17.73）	460（22.28）	351（14.00）
PIR［例（%）］				χ²=4.58	0.101
<1.3	1 267（27.71）	581（28.14）	686（27.35）
1.3～3.5	1 834（40.10）	794（38.45）	1 040（41.47）
>3.5	1 472（32.19）	690（33.41）	782（31.18）
BMI（kg/m²）	28.30（24.50～32.80）	24.70（22.20～27.70）	31.60（28.25～35.80）	Z=37.31	<0.001
WC（cm）	98.50（88.50～109.70）	88.80（80.80～96.20）	107.20（98.90～116.70）	Z=40.39	<0.001
BRI	5.21（3.94～6.77）	3.99（3.06～5.00）	6.35（5.17～7.85）	Z=36.29	<0.001
ALT（U/L）	19.00（14.00～27.00）	17.00（13.00～23.00）	22.00（16.00～32.00）	Z=13.43	<0.001
AST（U/L）	21.00（17.00～26.00）	20.00（17.00～25.00）	21.00（17.00～27.00）	Z=3.93	<0.001
GGT（U/L）	20.00（15.00～31.00）	17.00（12.00～24.00）	24.00（17.00～38.00）	Z=18.80	<0.001
HDL-C（mg/dL）	52.00（42.00～63.00）	58.00（48.00～70.00）	47.00（40.00～57.00）	Z=-17.72	<0.001
高血压［例（%）］				χ²=238.33	<0.001
否	2 266（49.55）	1 283（62.13）	983（39.19）
是	2 307（50.45）	782（37.87）	1 525（60.81）
糖尿病［例（%）］				χ²=250.65	<0.001
否	3 628（79.34）	1 854（89.78）	1 774（70.73）
是	945（20.66）	211（10.22）	734（29.27）
吸烟状况［例（%）］				χ²=42.69	<0.001
从未吸烟	2 556（55.89）	1 215（58.84）	1 341（53.47）
既往吸烟	1 130（24.71）	416（20.15）	714（28.47）
当前吸烟	887（19.40）	434（21.02）	453（18.06）

下载: 导出CSV

表 2 BRI与MAFLD的Logistic回归分析

Table 2. Logistic regression analysis of BRI and MAFLD

变量	模型1		模型2		模型3
变量	OR（95%CI）	P值	OR（95%CI）	P值	OR（95%CI）	P值
BRI	2.66（2.44～2.91）	<0.001	2.90（2.63～3.20）	<0.001	2.53（2.28～2.80）	<0.001
BRI分类
Q1	1.00		1.00		1.00
Q2	6.52（4.77～8.92）	<0.001	6.36（4.61～8.77）	<0.001	4.47（3.20～6.26）	<0.001
Q3	20.39（14.78～28.12）	<0.001	22.73（16.08～32.14）	<0.001	13.43（9.27～19.46）	<0.001
Q4	105.22（68.81～160.90）	<0.001	159.89（101.24～252.50）	<0.001	83.45（51.87～134.26）	<0.001
注：模型1中未调整变量；模型2中调整年龄、性别、种族、教育程度、PIR、婚姻状况等人口学变量；模型3为完全校正模型，在模型2的基础上进一步调整了吸烟状况、高血压、糖尿病、HDL-C、ALT、AST及GGT等变量。

下载: 导出CSV

表 3 BRI与MAFLD风险交互作用和亚组分析

Table 3. Subgroup and interaction analysis of BRI and MAFLD

变量	例数	OR（95%CI）	P_交互
年龄			0.506
>59岁	1 539	1.00
18～44岁	1 835	0.73（0.54～0.98）
45～59岁	1 199	1.40（1.01～1.95）
性别			0.320
女	2 273	1.00
男	2 300	1.81（1.37～2.39）
种族			0.140
墨西哥裔美国人	634	1.00
非西班牙裔黑人	1 015	0.71（0.50～1.00）
非西班牙裔白人	1 646	1.19（0.89～1.59）
其他种族	1 278	1.01（0.73～1.40）
教育程度			0.580
高中以上学历	2 661	1.00
高中以下学历	857	0.83（0.60～1.14）
高中或同等学历	1 055	1.14（0.85～1.54）
PIR			0.126
<1.3	1 267	1.00
>3.5	1 472	1.56（1.13～2.15）
1.3～3.5	1 834	1.20（0.88～1.63）
婚姻状况			0.195
已婚/与伴侣同居	2 782	1.00
离婚/分居/丧偶	980	0.65（0.48～0.89）
从未结婚	811	0.48（0.36～0.66）
高血压			0.003
否	2 266	1.00
是	2 307	1.60（1.23～2.08）
糖尿病			0.222
否	3 628	1.00
是	945	1.34（0.94～1.90）
吸烟状况			0.066
当前吸烟	887	1.00
从未吸烟	2 556	1.00（0.71～1.40）
既往吸烟	1 130	1.29（0.87～1.90）

下载: 导出CSV

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