The impact of online food delivery applications on dietary pattern disruption in the Arab region
BackgroundWhile 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...
Saved in:
| Main Authors: | , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-06-01
|
| Series: | Frontiers in Public Health |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1569945/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850214886251954176 |
|---|---|
| author | Radwan Qasrawi Radwan Qasrawi Suliman Thwib Ghada Issa Malak Amro Razan AbuGhoush Maha Hoteit Maha Hoteit Sahar Khairy Narmeen Jamal Al-Awwad Narmeen Jamal Al-Awwad Khlood Bookari Sabika Allehdan Dalal Alkazemi Haleama Al Sabbah Salima Al Maamari Asma H. Malkawi Reema Tayyem |
| author_facet | Radwan Qasrawi Radwan Qasrawi Suliman Thwib Ghada Issa Malak Amro Razan AbuGhoush Maha Hoteit Maha Hoteit Sahar Khairy Narmeen Jamal Al-Awwad Narmeen Jamal Al-Awwad Khlood Bookari Sabika Allehdan Dalal Alkazemi Haleama Al Sabbah Salima Al Maamari Asma H. Malkawi Reema Tayyem |
| author_sort | Radwan Qasrawi |
| collection | DOAJ |
| description | BackgroundWhile 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.MethodsWe 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.ResultsThe 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.ConclusionOFDAs 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. |
| format | Article |
| id | doaj-art-f1466e59d5cc45ea9a9ae4e085d8378c |
| institution | OA Journals |
| issn | 2296-2565 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj-art-f1466e59d5cc45ea9a9ae4e085d8378c2025-08-20T02:08:46ZengFrontiers Media S.A.Frontiers in Public Health2296-25652025-06-011310.3389/fpubh.2025.15699451569945The impact of online food delivery applications on dietary pattern disruption in the Arab regionRadwan Qasrawi0Radwan Qasrawi1Suliman Thwib2Ghada Issa3Malak Amro4Razan AbuGhoush5Maha Hoteit6Maha Hoteit7Sahar Khairy8Narmeen Jamal Al-Awwad9Narmeen Jamal Al-Awwad10Khlood Bookari11Sabika Allehdan12Dalal Alkazemi13Haleama Al Sabbah14Salima Al Maamari15Asma H. Malkawi16Reema Tayyem17Department of Computer Science, Al-Quds University, Jerusalem, PalestineDepartment of Computer Engineering, Istinye University, Istanbul, TürkiyeDepartment of Computer Science, Al-Quds University, Jerusalem, PalestineDepartment of Computer Science, Al-Quds University, Jerusalem, PalestineDepartment of Computer Science, Al-Quds University, Jerusalem, PalestineDepartment of Computer Science, Al-Quds University, Jerusalem, PalestineFood Sciences Unit, National Council for Scientific Research of Lebanon (CNRS-L), Beirut, LebanonPHENOL Research Program, Faculty of Public Health, Section 1, Lebanese University, Beirut, LebanonNational Nutrition Institute, Cairo, EgyptDepartment of Clinical Nutrition and Dietetics, Faculty of Applied Medical Sciences, The Hashemite University, Zarqa, JordanDepartment of Nutrition and Integrative Health, Faculty of Allied Medical Sciences, Middle East University, Amman, JordanClinical Nutrition Development, Applied Medical Science College, Taibah University, Medina, Saudi ArabiaDepartment of Biology, College of Science, University of Bahrain, Zallaq, Bahrain0Department of Food Science and Nutrition, College of Life Sciences, Kuwait University, Kuwait City, Kuwait1Department of Public Health, College of Health Sciences, Abu Dhabi University, Abu Dhabi, United Arab Emirates2Nutrition Department, Ministry of Health, Muscat, Oman3Ibn Khaldon Center for Humanities and Social Sciences, Qatar University, Doha, Qatar4Department of Nutrition Sciences, College of Health Sciences, Qatar University, Doha, QatarBackgroundWhile 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.MethodsWe 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.ResultsThe 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.ConclusionOFDAs 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.https://www.frontiersin.org/articles/10.3389/fpubh.2025.1569945/fullfood delivery applicationsonline food deliverydietary patternsmachine learningdietary disruptions |
| spellingShingle | Radwan Qasrawi Radwan Qasrawi Suliman Thwib Ghada Issa Malak Amro Razan AbuGhoush Maha Hoteit Maha Hoteit Sahar Khairy Narmeen Jamal Al-Awwad Narmeen Jamal Al-Awwad Khlood Bookari Sabika Allehdan Dalal Alkazemi Haleama Al Sabbah Salima Al Maamari Asma H. Malkawi Reema Tayyem The impact of online food delivery applications on dietary pattern disruption in the Arab region Frontiers in Public Health food delivery applications online food delivery dietary patterns machine learning dietary disruptions |
| title | The impact of online food delivery applications on dietary pattern disruption in the Arab region |
| title_full | The impact of online food delivery applications on dietary pattern disruption in the Arab region |
| title_fullStr | The impact of online food delivery applications on dietary pattern disruption in the Arab region |
| title_full_unstemmed | The impact of online food delivery applications on dietary pattern disruption in the Arab region |
| title_short | The impact of online food delivery applications on dietary pattern disruption in the Arab region |
| title_sort | impact of online food delivery applications on dietary pattern disruption in the arab region |
| topic | food delivery applications online food delivery dietary patterns machine learning dietary disruptions |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1569945/full |
| work_keys_str_mv | AT radwanqasrawi theimpactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT radwanqasrawi theimpactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT sulimanthwib theimpactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT ghadaissa theimpactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT malakamro theimpactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT razanabughoush theimpactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT mahahoteit theimpactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT mahahoteit theimpactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT saharkhairy theimpactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT narmeenjamalalawwad theimpactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT narmeenjamalalawwad theimpactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT khloodbookari theimpactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT sabikaallehdan theimpactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT dalalalkazemi theimpactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT haleamaalsabbah theimpactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT salimaalmaamari theimpactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT asmahmalkawi theimpactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT reematayyem theimpactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT radwanqasrawi impactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT radwanqasrawi impactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT sulimanthwib impactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT ghadaissa impactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT malakamro impactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT razanabughoush impactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT mahahoteit impactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT mahahoteit impactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT saharkhairy impactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT narmeenjamalalawwad impactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT narmeenjamalalawwad impactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT khloodbookari impactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT sabikaallehdan impactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT dalalalkazemi impactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT haleamaalsabbah impactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT salimaalmaamari impactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT asmahmalkawi impactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion AT reematayyem impactofonlinefooddeliveryapplicationsondietarypatterndisruptioninthearabregion |