Construction and validation of a multi-dimensional health indicator-driven osteoporosis risk prediction model: a large-sample cross-sectional study based on two centers.

ABSTRACT:

Background

Rising osteoporosis prevalence among elderly populations and limitations of current single-factor screening methods necessitate development of comprehensive multi-dimensional risk prediction models.

Methods

A two-center cross-sectional study was conducted, enrolling 15,307 elderly participants in 2023. Among them, 11,957 participants from Zhangjiagang Center for Disease Control and Prevention were randomly divided into training set (8369 cases) and internal validation set (3588 cases) at a 7:3 ratio, while 3,350 participants from Zhangjiagang fifth People's Hospital served as the external validation set. Multi-dimensional health data including demographic information, physiological indicators, lifestyle factors, nutritional supplementation, and laboratory examinat

SUBMITTER: Cai Z 

PROVIDER: S-EPMC12535037 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature