Association of eight anthropometric indexes related to obesity with the prevalence of clinical osteoarthritis among American adults: a national cross-sectional study.
{"title":"Association of eight anthropometric indexes related to obesity with the prevalence of clinical osteoarthritis among American adults: a national cross-sectional study.","authors":"Jingtao Huang, Xuan Zhang, Haoxian Tang, Shicheng Jia, Jiayou Chen, Rongji Liang, Qinglong Yang, Hanyuan Lin, Nan Luo, Yuxiang Ren, Jianjing Lin, Xintao Zhang","doi":"10.1186/s40001-025-03131-z","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>The aim of the current study is to investigate the association between clinical osteoarthritis (OA) and eight anthropometric indexes related to obesity, including non-hematological indexes (body mass index [BMI], body roundness index [BRI], weight-adjusted waist index [WWI], and waist-height ratio [WHtR]), and hematological indexes (triglyceride-glucose index [TyG], lipid accumulation product [LAP], visceral adiposity index [VAI], and waist triglyceride index [WTI]).</p><p><strong>Methods: </strong>Utilizing data from the National Health and Nutrition Examination Surveys (NHANES) spanning the years 2005-2018, a total of 19,867 adults (aged ≥ 20 years) were examined. Eight anthropometric indexes were calculated. Clinical OA was assessed through participants' self-reported responses by questionnaires. Multivariable logistic regression analysis and secondary analysis such as restricted cubic splines (RCS), receiver operating characteristic (ROC), decision curve analysis (DCA) and the area under the curve (AUC) analysis were employed to investigate the associations between anthropometric indexes and clinical OA.</p><p><strong>Results: </strong>The average age of the participants was 46.94 and 49.98% were female. Multivariable logistic regression analysis demonstrated significant associations between all indexes and clinical OA, especially BMI (per 1 standard deviation [SD], odd ration [OR] [95% Confidence interval [CI]] = 1.52[1.40, 1.66]), WTI (OR [95%CI] = 1.50[1.36, 1.65]) and WHtR (OR [95%CI] = 1.50[1.36, 1.64]). Latent profile analysis showed higher indexes could increase clinical OA risk. Additionally, AUC of WWI was the highest, at 0.6724, and DCA indicated that net profit of WWI was higher than other indexes when threshold was below 25%. The results of subgroup analysis proved the robustness of the findings in different sub-populations.</p><p><strong>Conclusion: </strong>Eight anthropometric indexes related to obesity were all significantly positively associated with clinical OA. Particularly, non-hematological indexes such as WWI and WHtR may show better efficacy in predicting and interventions for clinical OA outcomes, indicating their potential as the preferred strategy for early detection and management of clinical OA.</p>","PeriodicalId":11949,"journal":{"name":"European Journal of Medical Research","volume":"30 1","pages":"871"},"PeriodicalIF":3.4000,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12465158/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Medical Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s40001-025-03131-z","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: The aim of the current study is to investigate the association between clinical osteoarthritis (OA) and eight anthropometric indexes related to obesity, including non-hematological indexes (body mass index [BMI], body roundness index [BRI], weight-adjusted waist index [WWI], and waist-height ratio [WHtR]), and hematological indexes (triglyceride-glucose index [TyG], lipid accumulation product [LAP], visceral adiposity index [VAI], and waist triglyceride index [WTI]).
Methods: Utilizing data from the National Health and Nutrition Examination Surveys (NHANES) spanning the years 2005-2018, a total of 19,867 adults (aged ≥ 20 years) were examined. Eight anthropometric indexes were calculated. Clinical OA was assessed through participants' self-reported responses by questionnaires. Multivariable logistic regression analysis and secondary analysis such as restricted cubic splines (RCS), receiver operating characteristic (ROC), decision curve analysis (DCA) and the area under the curve (AUC) analysis were employed to investigate the associations between anthropometric indexes and clinical OA.
Results: The average age of the participants was 46.94 and 49.98% were female. Multivariable logistic regression analysis demonstrated significant associations between all indexes and clinical OA, especially BMI (per 1 standard deviation [SD], odd ration [OR] [95% Confidence interval [CI]] = 1.52[1.40, 1.66]), WTI (OR [95%CI] = 1.50[1.36, 1.65]) and WHtR (OR [95%CI] = 1.50[1.36, 1.64]). Latent profile analysis showed higher indexes could increase clinical OA risk. Additionally, AUC of WWI was the highest, at 0.6724, and DCA indicated that net profit of WWI was higher than other indexes when threshold was below 25%. The results of subgroup analysis proved the robustness of the findings in different sub-populations.
Conclusion: Eight anthropometric indexes related to obesity were all significantly positively associated with clinical OA. Particularly, non-hematological indexes such as WWI and WHtR may show better efficacy in predicting and interventions for clinical OA outcomes, indicating their potential as the preferred strategy for early detection and management of clinical OA.
期刊介绍:
European Journal of Medical Research publishes translational and clinical research of international interest across all medical disciplines, enabling clinicians and other researchers to learn about developments and innovations within these disciplines and across the boundaries between disciplines. The journal publishes high quality research and reviews and aims to ensure that the results of all well-conducted research are published, regardless of their outcome.