Insight into the main determinants of the struggle against overweight and obesity in Chile: Use of random forest techniques and econometric models.

Overweight and obesity are considered the greatest public health problem in this emerging country, which worldwide has the second-highest percentage of overweight people among its population. The objective of this work was to analyse to what extent factors traditionally used in the study of overweig...

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Main Authors: Francisca Romo-Muñoz, Rodrigo Romo-Muñoz, Sebastián Niklitschek-Soto, Cristhian Aguilera-Carrasco, José M Gil
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2024-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0309351
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author Francisca Romo-Muñoz
Rodrigo Romo-Muñoz
Sebastián Niklitschek-Soto
Cristhian Aguilera-Carrasco
José M Gil
author_facet Francisca Romo-Muñoz
Rodrigo Romo-Muñoz
Sebastián Niklitschek-Soto
Cristhian Aguilera-Carrasco
José M Gil
author_sort Francisca Romo-Muñoz
collection DOAJ
description Overweight and obesity are considered the greatest public health problem in this emerging country, which worldwide has the second-highest percentage of overweight people among its population. The objective of this work was to analyse to what extent factors traditionally used in the study of overweight and obesity (such as sociodemographic and behavioural) and new variables proposed in the literature (such as stress, financial stress and emotional support) explain this disease in the adult population of Chile. Data were obtained from the III National Health Survey (ENS) administered by the Ministry of Health of Chile in 2017. The ENS collected a large amount of data with extensive geographic coverage. The survey comprised 4 questionnaires with a total of 576 questions, which were applied to a representative sample of the population in Chile. A double complementary methodological approach was adopted. A random forest (RF) classification model was used, and based on the results obtained, an econometric model of the censored dependent variable, specifically the Heckman sample selection model, was specified and estimated. The RF results allowed, for each of the factors considered in the research, the selection of variables with the greatest power to classify the individuals in the sample on the basis of nutritional state (normal weight, overweight or obese). Subsequently, the estimation of the parameters of the Heckman model made it possible to quantify the variables that most affected overweight and obesity. Most of the variables that make up the factors were found to be significant. Interestingly, psychosocial variables effectively influence overweight and obesity. In addition, the results for reviewing nutritional information and reviewing food warnings allow us to reflect on the impact that recent food policies have had on the Chilean population. The combination of RF and an econometric model allowed us to capitalize on the strength of both models to better explain the complex phenomenon of overweight and obesity. This approach allowed us to more accurately confirm the impact of traditional factors on overweight and obesity but to show also that other psychosocial factors are relevant and should be consider in future studies.
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spelling doaj-art-0772f322720c4a468f5b6478cd95a8a82025-08-20T02:58:07ZengPublic Library of Science (PLoS)PLoS ONE1932-62032024-01-011912e030935110.1371/journal.pone.0309351Insight into the main determinants of the struggle against overweight and obesity in Chile: Use of random forest techniques and econometric models.Francisca Romo-MuñozRodrigo Romo-MuñozSebastián Niklitschek-SotoCristhian Aguilera-CarrascoJosé M GilOverweight and obesity are considered the greatest public health problem in this emerging country, which worldwide has the second-highest percentage of overweight people among its population. The objective of this work was to analyse to what extent factors traditionally used in the study of overweight and obesity (such as sociodemographic and behavioural) and new variables proposed in the literature (such as stress, financial stress and emotional support) explain this disease in the adult population of Chile. Data were obtained from the III National Health Survey (ENS) administered by the Ministry of Health of Chile in 2017. The ENS collected a large amount of data with extensive geographic coverage. The survey comprised 4 questionnaires with a total of 576 questions, which were applied to a representative sample of the population in Chile. A double complementary methodological approach was adopted. A random forest (RF) classification model was used, and based on the results obtained, an econometric model of the censored dependent variable, specifically the Heckman sample selection model, was specified and estimated. The RF results allowed, for each of the factors considered in the research, the selection of variables with the greatest power to classify the individuals in the sample on the basis of nutritional state (normal weight, overweight or obese). Subsequently, the estimation of the parameters of the Heckman model made it possible to quantify the variables that most affected overweight and obesity. Most of the variables that make up the factors were found to be significant. Interestingly, psychosocial variables effectively influence overweight and obesity. In addition, the results for reviewing nutritional information and reviewing food warnings allow us to reflect on the impact that recent food policies have had on the Chilean population. The combination of RF and an econometric model allowed us to capitalize on the strength of both models to better explain the complex phenomenon of overweight and obesity. This approach allowed us to more accurately confirm the impact of traditional factors on overweight and obesity but to show also that other psychosocial factors are relevant and should be consider in future studies.https://doi.org/10.1371/journal.pone.0309351
spellingShingle Francisca Romo-Muñoz
Rodrigo Romo-Muñoz
Sebastián Niklitschek-Soto
Cristhian Aguilera-Carrasco
José M Gil
Insight into the main determinants of the struggle against overweight and obesity in Chile: Use of random forest techniques and econometric models.
PLoS ONE
title Insight into the main determinants of the struggle against overweight and obesity in Chile: Use of random forest techniques and econometric models.
title_full Insight into the main determinants of the struggle against overweight and obesity in Chile: Use of random forest techniques and econometric models.
title_fullStr Insight into the main determinants of the struggle against overweight and obesity in Chile: Use of random forest techniques and econometric models.
title_full_unstemmed Insight into the main determinants of the struggle against overweight and obesity in Chile: Use of random forest techniques and econometric models.
title_short Insight into the main determinants of the struggle against overweight and obesity in Chile: Use of random forest techniques and econometric models.
title_sort insight into the main determinants of the struggle against overweight and obesity in chile use of random forest techniques and econometric models
url https://doi.org/10.1371/journal.pone.0309351
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