人体测量指数与慢性肾脏疾病之间的关系:来自NHANES 2009-2018的见解

IF 2.6 3区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
PLoS ONE Pub Date : 2025-02-14 eCollection Date: 2025-01-01 DOI:10.1371/journal.pone.0311547
Xinyun Chen, Zheng Wu, Xingyu Hou, Wenhui Yu, Chang Gao, Shenju Gou, Ping Fu
{"title":"人体测量指数与慢性肾脏疾病之间的关系:来自NHANES 2009-2018的见解","authors":"Xinyun Chen, Zheng Wu, Xingyu Hou, Wenhui Yu, Chang Gao, Shenju Gou, Ping Fu","doi":"10.1371/journal.pone.0311547","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>The strong association between obesity and chronic kidney disease (CKD) has been empirically validated, yet traditional measures like the Body Mass Index (BMI) fail to accurately assess the extent of obesity due to CKD's characteristics, such as reduced muscle mass and increased visceral fat. This study investigates the association between CKD and several anthropometric indices, including A Body Shape Index (ABSI), Body Roundness Index (BRI), Waist-to-Height Ratio (WHtR), and the Conicity Index (C-index), to determine their predictive capabilities.</p><p><strong>Methods: </strong>Based on the datasets from the National Health and Nutrition Examination Survey (NHANES) 2009-2018, weighted multivariable regression analyses were carried out to examine the independent relationship between two anthropometric indices and CKD. Also, subgroup analyses, restricted cubic spline regression (RCS), and receiver operating characteristic curve analysis were conducted for further data analyses.</p><p><strong>Results: </strong>A total of 24,162 participants were enrolled in this study. After adjusting for confounding factors, ABSI, BRI, WHtR, and the C-index were significantly associated with an increased risk of CKD, while BMI was not. Height showed a protective effect against CKD. ABSI and the C-index demonstrated the highest areas under the curve (AUCs), indicating superior predictive capabilities compared to traditional measures like BMI and waist circumference (WC). Subgroup analyses revealed significant interactions between the anthropometric indices and factors such as age, disease status, dietary intake, and physical activity levels.</p><p><strong>Conclusions: </strong>This study highlights the significant associations between various anthropometric indices (including ABSI, BRI, WHtR, and C-index) and the risk of CKD. ABSI and the C-index demonstrated the strongest predictive capabilities for CKD, with the highest AUC values.</p>","PeriodicalId":20189,"journal":{"name":"PLoS ONE","volume":"20 2","pages":"e0311547"},"PeriodicalIF":2.6000,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11828394/pdf/","citationCount":"0","resultStr":"{\"title\":\"Association between anthropometric indices and chronic kidney disease: Insights from NHANES 2009-2018.\",\"authors\":\"Xinyun Chen, Zheng Wu, Xingyu Hou, Wenhui Yu, Chang Gao, Shenju Gou, Ping Fu\",\"doi\":\"10.1371/journal.pone.0311547\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>The strong association between obesity and chronic kidney disease (CKD) has been empirically validated, yet traditional measures like the Body Mass Index (BMI) fail to accurately assess the extent of obesity due to CKD's characteristics, such as reduced muscle mass and increased visceral fat. This study investigates the association between CKD and several anthropometric indices, including A Body Shape Index (ABSI), Body Roundness Index (BRI), Waist-to-Height Ratio (WHtR), and the Conicity Index (C-index), to determine their predictive capabilities.</p><p><strong>Methods: </strong>Based on the datasets from the National Health and Nutrition Examination Survey (NHANES) 2009-2018, weighted multivariable regression analyses were carried out to examine the independent relationship between two anthropometric indices and CKD. Also, subgroup analyses, restricted cubic spline regression (RCS), and receiver operating characteristic curve analysis were conducted for further data analyses.</p><p><strong>Results: </strong>A total of 24,162 participants were enrolled in this study. After adjusting for confounding factors, ABSI, BRI, WHtR, and the C-index were significantly associated with an increased risk of CKD, while BMI was not. Height showed a protective effect against CKD. ABSI and the C-index demonstrated the highest areas under the curve (AUCs), indicating superior predictive capabilities compared to traditional measures like BMI and waist circumference (WC). Subgroup analyses revealed significant interactions between the anthropometric indices and factors such as age, disease status, dietary intake, and physical activity levels.</p><p><strong>Conclusions: </strong>This study highlights the significant associations between various anthropometric indices (including ABSI, BRI, WHtR, and C-index) and the risk of CKD. ABSI and the C-index demonstrated the strongest predictive capabilities for CKD, with the highest AUC values.</p>\",\"PeriodicalId\":20189,\"journal\":{\"name\":\"PLoS ONE\",\"volume\":\"20 2\",\"pages\":\"e0311547\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2025-02-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11828394/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"PLoS ONE\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1371/journal.pone.0311547\",\"RegionNum\":3,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"PLoS ONE","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1371/journal.pone.0311547","RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

肥胖与慢性肾脏疾病(CKD)之间的密切联系已经得到实证验证,然而传统的测量方法,如身体质量指数(BMI),并不能准确评估由于CKD的特征(如肌肉质量减少和内脏脂肪增加)导致的肥胖程度。本研究探讨了CKD与几个人体测量指标之间的关系,包括身体形状指数(ABSI)、身体圆度指数(BRI)、腰高比(WHtR)和圆度指数(C-index),以确定它们的预测能力。方法:基于2009-2018年国家健康与营养检查调查(NHANES)数据集,采用加权多变量回归分析,检验两项人体测量指标与CKD之间的独立关系。并进行亚组分析、限制性三次样条回归(RCS)和受试者工作特征曲线分析,进一步进行数据分析。结果:共有24162名参与者参加了这项研究。在调整混杂因素后,ABSI、BRI、WHtR和c指数与CKD风险增加显著相关,而BMI则无关。身高对慢性肾病有保护作用。ABSI和c指数显示出最高的曲线下面积(auc),与BMI和腰围(WC)等传统测量方法相比,表明了更高的预测能力。亚组分析显示,人体测量指数与年龄、疾病状况、饮食摄入和身体活动水平等因素之间存在显著的相互作用。结论:本研究强调了各种人体测量指标(包括ABSI、BRI、WHtR和C-index)与CKD风险之间的显著相关性。ABSI和c指数对CKD的预测能力最强,AUC值最高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Association between anthropometric indices and chronic kidney disease: Insights from NHANES 2009-2018.

Association between anthropometric indices and chronic kidney disease: Insights from NHANES 2009-2018.

Association between anthropometric indices and chronic kidney disease: Insights from NHANES 2009-2018.

Association between anthropometric indices and chronic kidney disease: Insights from NHANES 2009-2018.

Introduction: The strong association between obesity and chronic kidney disease (CKD) has been empirically validated, yet traditional measures like the Body Mass Index (BMI) fail to accurately assess the extent of obesity due to CKD's characteristics, such as reduced muscle mass and increased visceral fat. This study investigates the association between CKD and several anthropometric indices, including A Body Shape Index (ABSI), Body Roundness Index (BRI), Waist-to-Height Ratio (WHtR), and the Conicity Index (C-index), to determine their predictive capabilities.

Methods: Based on the datasets from the National Health and Nutrition Examination Survey (NHANES) 2009-2018, weighted multivariable regression analyses were carried out to examine the independent relationship between two anthropometric indices and CKD. Also, subgroup analyses, restricted cubic spline regression (RCS), and receiver operating characteristic curve analysis were conducted for further data analyses.

Results: A total of 24,162 participants were enrolled in this study. After adjusting for confounding factors, ABSI, BRI, WHtR, and the C-index were significantly associated with an increased risk of CKD, while BMI was not. Height showed a protective effect against CKD. ABSI and the C-index demonstrated the highest areas under the curve (AUCs), indicating superior predictive capabilities compared to traditional measures like BMI and waist circumference (WC). Subgroup analyses revealed significant interactions between the anthropometric indices and factors such as age, disease status, dietary intake, and physical activity levels.

Conclusions: This study highlights the significant associations between various anthropometric indices (including ABSI, BRI, WHtR, and C-index) and the risk of CKD. ABSI and the C-index demonstrated the strongest predictive capabilities for CKD, with the highest AUC values.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
PLoS ONE
PLoS ONE 生物-生物学
CiteScore
6.20
自引率
5.40%
发文量
14242
审稿时长
3.7 months
期刊介绍: PLOS ONE is an international, peer-reviewed, open-access, online publication. PLOS ONE welcomes reports on primary research from any scientific discipline. It provides: * Open-access—freely accessible online, authors retain copyright * Fast publication times * Peer review by expert, practicing researchers * Post-publication tools to indicate quality and impact * Community-based dialogue on articles * Worldwide media coverage
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信