Seaw, K. M., Leow, M. K. S., & Bi, X. (2025). Early obesity risk prediction via non‐dietary lifestyle factors using machine learning approaches. Clinical Obesity. Portico. https://doi.org/10.1111/cob.70011
Abstract:
Summary
Obesity poses a significant health threat, contributing to the development of noncommunicable diseases (NCDs). Early identification of individuals at higher risk for obesity is crucial for implementing effective prevention strategies. This study explores the viability of non‐dietary factors such as lifestyle, family history, and demographics as predictors of obesity risk. The dataset comprised 1068 males and 1043 females, aged between 14 and 61 years. Only non‐dietary factors were used to build the machine learning models, including decision tree, random forest, support vector classification (SVC), k‐nearest neighbour (KNN), and Gaussian Naïve Bayes (GNB). Random forest emerged as the optimal model, demonstrating 66.9% test accuracy, 66.4% precision, 66.9% recall, 66.4% F1‐score, 94.5% specificity and 92.3% area under the receiver operating characteristic curve (AUC‐ROC). Variability of the models' performance was also evaluated through bootstrapping. Lifestyle factors, while less impactful than family history and demographics, also contributed to predictive power. This indicates the potential for predicting obesity while relying less on dietary data, paving the way for future studies to refine predictive models. This could play a crucial role in identifying lifestyle factors as predictors of obesity, thereby preventing and intervening early to address obesity‐related complications.
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Publisher Copyright
Funding Info:
This research is supported by core funding from: Singapore Institute of Food and Biotechnology Innovation
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Description:
This is the peer reviewed version of the following article: Seaw, K. M., Leow, M. K. S., & Bi, X. (2025). Early obesity risk prediction via non‐dietary lifestyle factors using machine learning approaches. Clinical Obesity. Portico, which has been published in final form at https://doi.org/10.1111/cob.70011. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.