The Journal of International Medical Research · Oct 29, 2026

Exploring the association between Zhejiang University index and osteoporosis risk in middle-aged and older adults based on the National Health and Nutrition Examination Survey database

By Gu R, Zhang J, Ge Y et al.

BackgroundOsteoporosis is a metabolic bone disease characterized by reduced bone density and an increased risk of fractures. Metabolic factors, including body mass index and blood glucose levels, are associated with osteoporosis. The Zhejiang University index, which integrates these factors, may influence the risk of osteoporosis. Using data from the National Health and Nutrition Examination Survey database, this study examined the association between the Zhejiang University index and osteoporosis risk, thereby providing a potential novel indicator and strategy for the early detection and intervention of osteoporosis.MethodsData from the National Health and Nutrition Examination Survey (2007-2008 and 2013-2014) were analyzed, resulting in a final cohort of 1003 participants after accounting for fasting subsample and dual-energy X-ray absorptiometry data constraints. Weighted multivariable logistic regression and restricted cubic splines analyses were used to evaluate the association between the Zhejiang University index and osteoporosis. Several sensitivity analyses were conducted, including redefining the outcome using only dual-energy X-ray absorptiometry-confirmed cases and recalculating the Zhejiang University index without its intrinsic sex adjustment (+2 points for female participants). Variable selection was performed using Least Absolute Shrinkage and Selection Operator regression, and model performance was evaluated using receiver operating characteristic curves.ResultsThe Zhejiang University index was significantly inversely associated with the risk of osteoporosis. In the fully adjusted model, participants in the highest quartile had a significantly lower risk of osteoporosis than those in the lowest quartile (odds ratio = 0.18, 95% confidence interval: 0.11-0.31, p < 0.001). Conversely, when the highest quartile was used as the reference, individuals in the lowest quartile faced a 5.50-fold higher risk of osteoporosis (odds ratio = 5.50, 95% confidence interval: 3.21-9.43). Restricted cubic splines analysis confirmed a linear inverse relationship (p overall < 0.001, p nonlinear = 0.387). Sensitivity analyses demonstrated that the protective association was robust against diagnostic criteria and intrinsic sex weighting. The final 10-variable prediction model achieved an area under the curve of 0.763, demonstrating superior performance compared with models based solely on clinical factors.ConclusionThe Zhejiang University index independently predicts the risk of osteoporosis, and the associated prediction model demonstrated good performance, providing a useful tool for clinical screening.

doi.org/10.1177/03000605261477328Open accessPubMed 42957414Biomarkers