Association of urinary metal elements with sarcopenia and glucose metabolism abnormalities: Insights from NHANES data using machine learning approaches

Association of urinary metal elements with sarcopenia and glucose metabolism abnormalities: Insights from NHANES data using machine learning approaches

Background: Sarcopenia, a condition marked by the decline of skeletal muscle mass and function, is prevalent in the elderly and closely linked to abnormal glucose metabolism, particularly type 2 diabetes. Hyperglycemia can increase the formation of advanced glycation end-products (AGEs) in muscle pr...

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Bibliographic Details
Main Authors: Xinmin Jin, Lei Li, Xiaoyan Hu, Pengfei Bi, Song Zhang, Qian Wang, Zhongwei Xiao, Hua Yang, Tongtong Liu, Lifang Feng, Jinhuan Wang
Format: Article
Language:English
Published: Elsevier 2025-07-01
Series:Ecotoxicology and Environmental Safety
Subjects:
Urinary Metal Elements
Sarcopenia
Glucose Metabolism Abnormalities
NHANES
Machine Learning
Online Access:http://www.sciencedirect.com/science/article/pii/S0147651325008097
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