Author:
Marcos-Pasero Helena,Colmenarejo Gonzalo,Aguilar-Aguilar Elena,Ramírez de Molina Ana,Reglero Guillermo,Loria-Kohen Viviana
Abstract
AbstractThe increased prevalence of childhood obesity is expected to translate in the near future into a concomitant soaring of multiple cardio-metabolic diseases. Obesity has a complex, multifactorial etiology, that includes multiple and multidomain potential risk factors: genetics, dietary and physical activity habits, socio-economic environment, lifestyle, etc. In addition, all these factors are expected to exert their influence through a specific and especially convoluted way during childhood, given the fast growth along this period. Machine Learning methods are the appropriate tools to model this complexity, given their ability to cope with high-dimensional, non-linear data. Here, we have analyzed by Machine Learning a sample of 221 children (6–9 years) from Madrid, Spain. Both Random Forest and Gradient Boosting Machine models have been derived to predict the body mass index from a wide set of 190 multidomain variables (including age, sex, genetic polymorphisms, lifestyle, socio-economic, diet, exercise, and gestation ones). A consensus relative importance of the predictors has been estimated through variable importance measures, implemented robustly through an iterative process that included permutation and multiple imputation. We expect this analysis will help to shed light on the most important variables associated to childhood obesity, in order to choose better treatments for its prevention.
Publisher
Springer Science and Business Media LLC
Reference60 articles.
1. Nutrition—EU Science Hub—European Commission. EU Science Hub https://ec.europa.eu/jrc/en/research-topic/nutrition (2014).
2. Townsend, N., Rutter, H. & Foster, C. Evaluating the evidence that the prevalence of childhood overweight is plateauing. Pediatr. Obes. 7, 343–346 (2012).
3. Childhood Obesity Surveillance Initiative (COSI) Factsheet. Highlights 2015–17 (2018). http://www.euro.who.int/en/health-topics/disease-prevention/nutrition/activities/who-european-childhood-obesity-surveillance-initiative-cosi/cosi-publications/childhood-obesity-surveillance-initiative-cosi-factsheet.-highlights-2015-17-2018 (2018).
4. Agencia Española de Consumo, Seguridad Alimentaria y Nutrición. Ministerio de Sanidad, Servicios Sociales e Igualdad. Estudio ALADINO 2015: Estudio de Vigilancia del Crecimiento, Alimentación, Actividad Física, Desarrollo Infantil y Obesidad en España 2015. (2016).
5. Kunwar, R., Minhas, S. & Mangla, V. Is obesity a problem among school children?. Indian J. Public Health 62, 153 (2018).
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