Identifying the factors related to body fat percentage among Vietnamese adolescents using machine learning techniques

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UDC: 
612.3-004.42
DOI: 
10.21668/health.risk/2024.1.16.eng
Authors: 

Nguyen Thi Hong Hanh1, Le Thi Tuyet1, Nguyen Thi Trung Thu1, Do Thi Nhu Trang1, Duong Thi Anh Dao1, Le Thi Thuy Dung2, Dang Xuan Tho3

Organization: 

1Hanoi National University of Education, 136 Xuan Thuy St., Hanoi, Vietnam
2Binh Duong General Hospital, 5 Pham Ngoc Thach, Hiep Thanh, Binh Duong, Vietnam
3Academy of Policy and Development, Hoai Duc district, Hanoi, Vietnam

Abstract: 

The aim of this study was to investigate the factors influencing Body Fat Percentage (BFP) among Vietnamese adolescents aged 11 to 15 employing machine learning techniques for predictive analysis.

A total of 1,208 adolescents, comprising 598 boys and 610 girls, drawn from nine junior high schools in Vietnam's capital, were enrolled in the study. Body composition measurements were conducted using the HBF 375 (Omron) device by Bioelectrical Impedance Analysis method. The study questionnaire, initially validated by The National Institute of Nutrition, encompassed inquiries related to dietary behaviors, meal frequencies, physical activities, sedentary habits, and nutritional knowledge. A machine learning methodology employing a decision tree algorithm was employed to discern the primary determinants most significantly correlated with BFP.

This study successfully identified six distinct predictor groups associated with BFP among adolescents, leveraging the decision tree model, with Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) values of 4.80 and 3.80, respectively. Among these predictors, frequency of fruit consumption, snacking habits, mode of transportation to school, and screen time (computer and/or cell phone usage) emerged as the most influential factors linked to BFP in adolescents. The combination of these factors and interactions with gender and pubertal status can BFP in Vietnamese adolescents.

This research sheds light on the complex and diverse factors impacting BFP in Vietnamese adolescents. This study's results underscore the practical importance of promoting healthy eating and exercise habits among adolescents, offering valuable insights for parents and schools to enhance their childcare strategies.

Keywords: 
machine learning, body fat percentage, predictability, influencing factors, eating habits, physical activity,Vietnamese adolescents, the decision tree
Nguyen Thi Hong Hanh, Le Thi Tuyet, Nguyen Thi Trung Thu, Do Thi Nhu Trang, Duong Thi Anh Dao, Le Thi Thuy Dung, Dang Xuan Tho. Identifying the factors related to body fat percentage among Vietnamese adolescents using machine learning techniques. Health Risk Analysis, 2024, no. 1, pp. 158–168. DOI: 10.21668/health.risk/2024.1.16.eng
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Received: 
25.01.2024
Approved: 
29.02.2024
Accepted for publication: 
20.03.2024

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