ArticleFrontiers in public health2025
The impact of online food delivery applications on dietary pattern disruption in the Arab region.
Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Determinants of food choices on online food delivery applications among university students: a cross-sectional study.Scientific reports · 2026Article
- Does food literacy influence healthy food choices? Findings from a cross-sectional study in Saudi Arabia.Frontiers in nutrition · 2026Article
- Prevalence and factors associated with regular fast-food consumption among adults in the UAE: a cross-sectional study.Public health nutrition · 2025Article
- What's in your card? The impact of online food delivery apps on depression and eating behaviors.Frontiers in nutrition · 2025Article
- Prevalence and factors associated with regular fast-food consumption among the adult population in Qatar: cross-sectional analysis from Qatar Biobank cohort.Frontiers in nutrition · 2025Article
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: While online food delivery applications (OFDAs) offer convenient food accessibility, their impact on dietary behaviors remains insufficiently explored, especially in the Arab region. This study applies machine learning (ML) techniques to identify the key behavioral and nutritional factors contributing to dietary disruption linked to OFD platforms. Methods: We conducted a cross-sectional study which involved 7,370 adults across 10 Arab countries using a comprehensive online survey. The study employed an ensemble ML approach, comparing Random Forest, XGBoost, CatBoost, and LightGBM tree-based models to analyze 31 features across six domains: demographics, ordering frequency, food preferences, nutritional perceptions, behavioral factors, and service attributes. Model performance was evaluated using multiple metrics, including sensitivity, precision, F1-score, and AUC. Clear interpretation of the risk factors was explained using partial dependence plots. Results: The findings revealed that the strongest predictors of dietary disruption were excessive food consumption, altered meal routines, and preferences for fatty foods. Younger individuals, males, and those with higher BMI reported higher disruption rates. Lebanon and Bahrain showed the highest rates for notable disruption, while Oman reported the lowest. ML analysis demonstrated high predictive performance, with Random Forest achieving the highest sensitivity (94.3%) and F1-score (89.3%). Feature importance analysis identified behavioral factors as more influential than socioeconomic indicators. Conclusion: OFDAs offer valuable convenience and market expansion while simultaneously posing significant challenges to maintaining optimal dietary health. With strategic interventions and public health collaborations, these platforms can shift from being disruptors of healthy dietary habits to catalysts for improved nutrition and well-being in the Arab region and beyond.
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