Association between machine learning-assisted heavy metal exposures and diabetic kidney disease: a cross-sectional survey and Mendelian randomization analysis.

Journal: Frontiers in public health
PMID: 38947355

Abstract

BACKGROUND AND OBJECTIVE: Heavy metals, ubiquitous in the environment, pose a global public health concern. The correlation between these and diabetic kidney disease (DKD) remains unclear. Our objective was to explore the correlation between heavy metal exposures and the incidence of DKD.

Authors

  • Ruiqi Zhao
  • Sen Lin
    Research Center of Intelligent Equipment Technology, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China.
  • Mengyao Han
  • Zhimei Lin
    The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, China.
  • Mengjiao Yu
    The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, China.
  • Bei Zhang
    College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
  • Lanyue Ma
    The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, China.
  • Danfei Li
    The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, China.
  • Lisheng Peng

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