Abstract

Background

The current literature lacks robust clinical data and evidence delineating the relationship between obesity measurement indexes and knee osteoarthritis (KOA). Consequently, this investigation seeks to elucidate the potential link between obesity measurement indexes and KOA among Chinese adults in a nationally representative study.

Methods

Firstly, this research performed an observational study in the China Health and Retirement Longitudinal Study (CHARLS). The variables were extracted from interviews and compared between KOA and non-KOA participants. The relationship between obesity measurement indexes and KOA was analyzed by multivariate logistic regression. Restricted cubic spline (RCS) regression tests the nonlinearity of the relationship between obesity measurement indexes and KOA. Subgroup analyses were performed by sex to verify the robustness of the findings.

Results

In this cross-sectional analysis, we found a positive association between obesity measurement indexes and KOA. These results did not change on multiple imputations(BMI: OR = 1.02, 95% CI, 1.01–1.04, P < 0.05; WHtR: OR = 2.85, 95% CI, 1.08–7.51, P < 0.05; BRI: OR = 1.07, 95% CI, 1.01–1.12, P < 0.05; BFP: OR = 1.02 95% CI, 1.00-1.03, P < 0.05). All the effects of obesity measurement indexes with KOA are present in females. None of the stratifying variables significantly affected the association between obesity measurement indexes and KOA. RCS regression test revealed the linear positive correlation between obesity measurement indexes and KOA.

Conclusion

In this cross-sectional study, we found a significant association between obesity measurement indexes and KOA. This relationship is not affected by stratification and confounding factors.

Details

Title
Association between obesity measurement indexes and symptomatic knee osteoarthritis among the Chinese population: analysis from a nationwide longitudinal study
Author
Lv, Hao; Wang, Yan; Zhang, Ge; Wang, Xingyu; Hu, Zhimu; Chu, Qingsong; Zhou, Yao; Yang, Yuxiang; Jiang, Ting; Wang, Jiuxiang
Pages
1-11
Section
Research
Publication year
2024
Publication date
2024
Publisher
Springer Nature B.V.
e-ISSN
14712474
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3142300159
Copyright
© 2024. This work is licensed under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.