Scientific Reports (Nov 2024)

Relationship between weight-adjusted waist index (WWI) and osteoarthritis: a cross-sectional study using NHANES data

  • Xiangming Li,
  • Peixin Huang,
  • Huishu Wang,
  • Zehao Hu,
  • Shaoli Zheng,
  • Junhui Yang,
  • Xu Wu,
  • Guizhong Huang

DOI
https://doi.org/10.1038/s41598-024-80151-5
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 12

Abstract

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Abstract This study aims to evaluate the association between the Weight-Adjusted Waist Index (WWI) and osteoarthritis (OA) utilizing cross-sectional data from the 2005–2014 National Health and Nutrition Examination Survey (NHANES). The study analyzed data from 12,696 participants across the 2005–2014 NHANES cycles to examine differences in demographic, socioeconomic, lifestyle, and health-related variables across WWI quartiles. Multivariable logistic regression models were employed to assess the relationship between WWI and the risk of OA. Receiver Operating Characteristic (ROC) curve analysis was conducted to evaluate and compare the predictive ability of WWI, BMI, waist circumference, and weight in identifying OA risk. Scatter plots were generated to visualize the association between WWI and OA, with linear regression lines illustrating trends and statistical significance. Restricted cubic spline (RCS) analysis was used to further explore the nonlinear relationship between WWI and OA risk. Forest plots were used to display the impact of WWI on OA risk across subgroups such as gender, age, and race, showing that individuals with higher WWI generally exhibit a significantly increased risk of OA. After adjusting for multiple covariates, the findings indicated a significant association between higher WWI and an increased risk of OA. Subgroup analyses, including gender, age, and race, further reinforced the consistent association between WWI and OA risk. In the U.S. adult population, an elevated WWI is significantly associated with an increased risk of OA, suggesting that WWI could serve as a potential indicator for assessing OA risk.

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