Machine Learning Identification of Obesity Causes In Children

Project Details

Description

The MALOBIC project aims to investigate the causes of obesity among children, adolescents, and young adults, in Denmark and the U.S. The project uses machine learning and statistical analysis to identify and evaluate potential determinants of obesity across life stages (ages 7, 11, and 18).

The research will be performed in two phases. The first involves a broad exploration of multiple potential causes using cross-sectional data to identify new and existing associations with obesity. The second will narrow down the focus to a few selected causes, conducting longitudinal analysis to assess their plausibility and impact. This includes evaluating the combined effects of these determinants and identifying outliers using mechanistic models of obesity.

The study aims to understand the complex interplay of factors contributing to obesity, including genetic, environmental, and lifestyle elements, and to identify reversible determinants that could inform effective interventions.
AcronymMALOBIC
StatusActive
Effective start/end date01/09/202331/12/2027

Collaborative partners

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

Keywords

  • obesity
  • Obesity causes
  • children
  • adolescents
  • growth trajectories
  • Machine Learning

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