An explainable predictive model for anxiety symptoms risk among Chinese older adults with abdominal obesity using a machine learning and SHapley Additive exPlanations approach.

Journal: Frontiers in psychiatry
Published Date: Dec 10, 2024

Abstract

BACKGROUND: Early detection of anxiety symptoms can support early intervention and may help reduce the burden of disease in later life in the elderly with abdominal obesity, thereby increasing the chances of healthy aging. The objective of this research is to formulate and validate a predictive model that forecasts the probability of developing anxiety symptoms in elderly Chinese individuals with abdominal obesity.

Authors

  • Tengfei Niu
    Department of Basic Courses, Chongqing Medical and Pharmaceutical College, Chongqing, China.
  • Shiwei Cao
    The Second Clinical College, Chongqing Medical University, Chongqing, China.
  • Jingyu Cheng
    School of Public Health, Chongqing Medical University, Chongqing, China.
  • Yu Zhang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Zitong Zhang
    The Second Clinical College, Chongqing Medical University, Chongqing, China.
  • Ruiling Xue
    Department of Rehabilitation, Chongqing General Hospital, Chongqing, China.
  • Jingxi Ma
    Department of Neurology, Chongqing General Hospital, Chongqing, China.
  • Qian Ran
    Department of Basic Courses, Chongqing Medical and Pharmaceutical College, Chongqing, China.
  • Xiaobing Xian
    Operations Management and External Communications Department, The Thirteenth People's Hospital of Chongqing, Chongqing, China.

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