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.

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.

[1] Weibo Xia, Zhenlin Zhang, Hua Lin, et al. Guidelines for the diagnosis and management of primary osteoporosis (2017). Chinese Journal of Osteoporosis, 2019, 25(03):281-309.

[2] International Osteoporosis Foundation. About Osteoporosis [EB/OL]. https://www.osteoporosis. foundation/patients/about-osteoporosis 

[3] International Osteoporosis Foundation. Facts & Statistics [EB/OL]. https://www.osteoporosis. foundation/facts-statistics/epidemiology-of-osteoporosis-and-fragility-fractures 

[4] Lane NE. Epidemiology, etiology, and diagnosis of osteoporosis. Am J Obstet Gynecol. 2006 Feb; 194(2 Suppl):S3-11. doi: 10.1016/j.ajog.2005.08.047. PMID: 16448873.

[5] Chinese Center for Disease Control and Prevention. NHSC Releases Results of China's Osteoporosis Epidemiology Survey. [EB/OL]. https://ncncd.chinacdc.cn/xwz/gzdt_ 11943/202009/ t20200920_ 220365.htm 

[6] Buizert PJ, van Schoor NM, Lips P, et al. Lipid levels: a link between cardiovascular disease and osteoporosis? J Bone Miner Res. 2009 Jun;24(6):1103-9. doi: 10.1359/jbmr.081262. PMID: 19113906.

[7] Laroche M, Pécourneau V, Blain H et al. Osteoporosis and ischemic cardiovascular disease. Joint Bone Spine. 2017 Jul; 84(4):427-432.

[8] Lello S, Capozzi A, Scambia G. Osteoporosis and cardiovascular disease: an update. Gynecol Endocrinol. 2015; 31(8):590-4.

[9] Emerging Risk Factors Collaboration; Di Angelantonio E, Gao P et al. Lipid-related markers and cardiovascular disease prediction. JAMA. 2012 Jun 20; 307(23):2499-506.

[10] Parhami F, Tintut Y, Beamer WG, Gharavi N, Goodman W, Demer LL. Atherogenic high-fat diet reduces bone mineralization in mice. J Bone Miner Res. 2001 Jan; 16(1):182-8.

[11] Panahi N, Soltani A, Ghasem-Zadeh A et al. Associations between the lipid profile and the lumbar spine bone mineral density and trabecular bone score in elderly Iranian individuals participating in the Bushehr Elderly Health Program: a population-based study. Arch Osteoporos. 2019 May 11; 14(1):52. 

[12] Bijelic R, Balaban J, Milicevic S. Correlation of the Lipid Profile, BMI and Bone Mineral Density in Postmenopausal Women. Mater Sociomed. 2016 Dec; 28(6):412-415.

[13] Li GH, Cheung CL, Chung AK et al. Evaluation of bi-directional causal association between depression and cardiovascular diseases: a Mendelian randomization study. Psychol Med. 2022 Jul; 52(9): 1765-1776. 

[14] Kan B, Zhao Q, Wang L, Xue S, Cai H, Yang S. Association between lipid biomarkers and osteoporosis: a cross-sectional study. BMC Musculoskelet Disord. 2021 Sep 6;22(1):759.

[15] Ghadiri-Anari A, Mortezaii-Shoroki Z, Modarresi M, Dehghan A. Association of lipid profile with bone mineral density in postmenopausal women in Yazd province. Int J Reprod Biomed. 2016 Sep; 14(9):597-602. 

[16] Sadatsafavi M, Moayyeri A, Soltani A, Larijani B, Nouraie M, Akhondzadeh S. Artificial neural networks in prediction of bone density among post-menopausal women. J Endocrinol Invest. 2005 May; 28(5):425-31. 

[17] Yingjie Zhi, Qinglin Cha, Yanming Xie. An exploratory study on the prediction of severe postmenopausal osteoporosis based on data mining technology. Lishizhen Medicine and Materia Medica Research, 2012, 23(07):1800-1802.

[18] Yoo TK, Kim SK, Kim DW et al. Osteoporosis risk prediction for bone mineral density assessment of postmenopausal women using machine learning. Yonsei Med J. 2013 Nov;54(6):1321-30. 

[19] Barron RL, Oster G, Grauer A, Crittenden DB, Weycker D. Determinants of imminent fracture risk in postmenopausal women with osteoporosis. Osteoporos Int. 2020 Nov;31(11):2103-2111. 

[20] NIH Consensus Development Panel on Osteoporosis Prevention, Diagnosis, and Therapy. Osteoporosis prevention, diagnosis, and therapy. JAMA. 2001 Feb 14;285(6):785-95. 

[21] Zhang L, Yin X, Wang J et al. Associations between VDR Gene Polymorphisms and Osteoporosis Risk and Bone Mineral Density in Postmenopausal Women: A systematic review and Meta-Analysis. Sci Rep. 2018 Jan 17;8(1):981. doi: 10.1038/s41598-017-18670-7. Retraction in: Sci Rep. 2021 Apr 21; 11(1):9030.

[22] Ahmadieh H, Basho A, Chehade A, Al Mallah A, Dakour A. Perception of peri-menopausal and postmenopausal Lebanese women on osteoporosis: A cross-sectional study. J Clin Transl Endocrinol. 2018 Oct 3;14:19-24. 

[23] Hiremath RN, Yadav AK, Ghodke S, Yadav J, Latwal S, Kotwal A. Osteoporosis among household women: A growing but neglected phenomenon. Med J Armed Forces India. 2018 Jan;74(1):5-10. doi: 10.1016/j.mjafi.2016.09.007. 

[24] Nguyen TV, Kelly PJ, Sambrook PN, Gilbert C, Pocock NA, Eisman JA. Lifestyle factors and bone density in the elderly: implications for osteoporosis prevention. J Bone Miner Res. 1994 Sep;9(9):1339-46. 

[25] Chen YW, Ramsook AH, Coxson HO, Bon J, Reid WD. Prevalence and Risk Factors for Osteoporosis in Individuals with COPD: A Systematic Review and Meta-analysis. Chest. 2019 Dec;156(6):1092-1110. 

[26] De Laet C, Kanis JA, Odén A et al. Body mass index as a predictor of fracture risk: a meta-analysis. Osteoporos Int. 2005 Nov; 16(11):1330-8.