MODEL SAPUTRI: A Mobile-Based Tool for Community-Level Obesity Risk Screening in Women of Reproductive Age

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Ika Nur Saputri, Delmi Sulastri, Mudjiran, Eva Chundrayetti, Nur Indrawaty Lipoeto, Defrin, Meri Neherta, Hafni Bachtiar

2025 Journal of Applied Bioanalysis Vol. 11 Issue 4 Article Cited by 0

Abstract

Introduction: Obesity prevalence is a significant public health concern, often lacking integrated, accessible tools for early risk identification. This study addresses the need for a non-invasive, community-based predictive model that combines behavioral, nutritional, and physiological determinants to support prevention at the primary and community care levels. Methods: An analytical observational study with a cross-sectional design was conducted in Deli Serdang Regency, North Sumatra (August–September 2023), involving 90 women of childbearing age (WCA). Secondary data from Phase I were analyzed using logistic regression to identify associations between predisposing, reinforcing, and enabling factors— particularly behavioral predictors such as dietary intake, physical activity, and health knowledge—and obesity risk. The findings informed the development of MODEL SAPUTRI, a mobile-based expert system for early obesity risk screening. The application’s functionality and usability were validated by IT and public health experts, and a user manual was reviewed for clarity and applicability. Results: The MODEL SAPUTRI application demonstrated high feasibility and usability. Logistic regression revealed significant associations between obesity and excessive energy, carbohydrate, and fat intake, while adequate protein intake, good knowledge, and higher physical activity were protective factors. Age, employment, education, income, sleep duration, and attitude showed no statistically significant associations. Conclusion: MODEL SAPUTRI offers a practical, non-invasive tool for community-level obesity risk screening in WCA, highlighting the importance of behavioral and dietary factors in prevention strategies. Its validation by multidisciplinary experts supports its application in primary health care and community settings to facilitate early identification and intervention. © 2025, Green Publication. All rights reserved.

Affiliations

Faculty of Medicine, Universitas Andalas, Sumatera Barat, Padang, 25175, Indonesia; Faculty of Education, Universitas Negeri Padang, Padang, Indonesia; Faculty of Nursing, Universitas Andalas, Sumatera Barat, Padang, 25175, Indonesia