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Academic Journal of Medicine & Health Sciences, 2024, 5(5); doi: 10.25236/AJMHS.2024.050509.

A Study on Prediction of Osteoporosis Risk in Middle-Aged and Elderly People Based on Lipid Indicators


Miao Zhang1, Yiran Wan1, Jialu Yang1, Pingping Yu2, Xun Lei1

Corresponding Author:
Xun Lei

1School of Public Health, Chongqing Medical University, Chongqing, 401331, China

2Department of Health Management Center, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, 400010, China


Osteoporosis is a common health problem in the middle-aged and elderly population, and its risk may be related to lipid levels. This study aimed to explore the effect of lipids on osteoporosis in middle-aged and elderly population and to develop a predictive model for osteoporosis. Middle-aged and elderly people over 45 years old who had undergone DEXA in several hospitals in Chongqing City from 2016 to 2020 as study subjects. After data cleaning and feature selection, the prediction model was established using the random forest (RF), light gradient boosting ma-chine (LightGBM), extreme gradient boosting (XGBoost) and classification boosting (CatBoost) algorithms. In the test set, the accuracy (0.83571) of the XGBoost model is significantly higher than that of RF (0.82142), CatBoost (0.80714), and LightGBM (0.79285). Lipid indicators could be used in osteoporosis prediction studies, and the established XGBoost model had the best prediction ability. The model needs to be further validated by a larger external sample.


Osteoporosis; Middle-aged and elderly; Lipid indicators; Prediction models; Machine learning

Cite This Paper

Miao Zhang, Yiran Wan, Jialu Yang, Pingping Yu, Xun Lei. A Study on Prediction of Osteoporosis Risk in Middle-Aged and Elderly People Based on Lipid Indicators. Academic Journal of Medicine & Health Sciences (2024), Vol. 5, Issue 5: 63-70. https://doi.org/10.25236/AJMHS.2024.050509.


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