Prevalence of malnutrition and associated factors in Chinese children and adolescents aged 3-14 years using machine learning algorithms.

Journal: Journal of global health
Published Date: Jul 21, 2025

Abstract

BACKGROUND: Child malnutrition represents a critical global public health issue and it is characterised by high prevalence and severe long-term consequences for growth and development. A better understanding of its contributory factors is essential to inform the design of targeted prevention strategies and evidence-based interventions. We aimed to estimate the prevalence of malnutrition in children and adolescents aged 3-14 years, and further to identify promising factors associated with child malnutrition using machine learning algorithms.

Authors

  • Fangjieyi Zheng
    Center for Evidence-Based Medicine, Capital Institute of Pediatrics, Beijing, China.
  • Kening Chen
    China-Japan Friendship Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
  • Xiaoqian Zhang
    Department of Stomatology, Haiyuan College of Kunming Medical University, Kunming, China.
  • Qiong Wang
    Beijing Meiling Biotechnology Corporation, Beijing, 102600, PR China.
  • Zhixin Zhang
    School of Mathematics Sciences, Anhui University, Hefei 230601, China.
  • Wenquan Niu
    Institute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing 100029, China. Electronic address: niuwenquan_shcn@163.com.

Keywords

External Resources

Popular Topics
Recent Journals