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

• Published in: PloS one Vol. 19; no. 12; p. e0309351
• Main Authors: Romo-Muñoz, Francisca, Romo-Muñoz, Rodrigo, Niklitschek-Soto, Sebastián, Aguilera-Carrasco, Cristhian, Gil, José M.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 16.12.2024; Public Library of Science (PLoS)
• Subjects: Adolescent; Adult; Aged; Biology and Life Sciences; Body weight; Care and treatment; Causes of; Chile - epidemiology; Chronic illnesses; Complex variables; Dependent variables; Descriptive labeling; Econometric models; Econometrics; Emotional behavior; Employment; Evaluation; Exercise; Families & family life; Female; Food; GDP; Gross Domestic Product; Health care expenditures; Health Surveys; Humans; Literature reviews; Machine learning; Male; Medicine and Health Sciences; Middle Aged; Models, Econometric; Nutrition research; Obesity; Obesity - epidemiology; Obesity - psychology; Overweight; Overweight - epidemiology; Parameter estimation; People and places; Physical Sciences; Population studies; Psychological aspects; Public health; Random Forest; Reviewing; Social Sciences; Sociodemographics; Socioeconomic Factors; Surveys; Young Adult; Chile; United States > US
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0309351

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.