Exploration of Machine Learning and Statistical Techniques in Development of a Low-Cost Screening Method Featuring the Global Diet Quality Score for Detecting Prediabetes in Rural India.

Journal: The Journal of nutrition
PMID: 34689190

Abstract

BACKGROUND: The prevalence of type 2 diabetes has increased substantially in India over the past 3 decades. Undiagnosed diabetes presents a public health challenge, especially in rural areas, where access to laboratory testing for diagnosis may not be readily available.

Authors

  • Nick Birk
    Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, MA, USA.
  • Mika Matsuzaki
    Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA.
  • Teresa T Fung
    Nutrition Department, Simmons University, Boston, MA, USA.
  • Yanping Li
    College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China.
  • Carolina Batis
    CONACYT-Health and Nutrition Research Center, National Institute of Public Health, Cuernavaca, Mexico.
  • Meir J Stampfer
    Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA.
  • Megan Deitchler
    Intake-Center for Dietary Assessment, FHI Solutions, Washington, DC, USA.
  • Walter C Willett
    Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA.
  • Wafaie W Fawzi
    Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA.
  • Sabri Bromage
    Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA.
  • Sanjay Kinra
    Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, University of London, London, United Kingdom.
  • Shilpa N Bhupathiraju
    Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA.
  • Erin Lake
    Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, MA, USA.

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