GLOBAL RESEARCH LANDSCAPE ON FAST FOOD CONSUMPTION AND ITS HEALTH IMPACTS: A BIBLIOMETRIC ANALYSIS AND VISUALISATION OF RESEARCH TRENDS AND THEMES
DOI:
https://doi.org/10.29121/shodhkosh.v5.i6.2024.4384Keywords:
Fast Food Consumption, Health, Bibliometric Analysis, Biblioshiny, VOSviewerAbstract [English]
Fast food consumption, characterized by the intake of calorie-dense and nutrient-poor meals, poses significant health risks, including obesity, chronic diseases, and mental health issues. This bibliometric analysis examines the research landscape on fast food consumption and its health impacts using data retrieved from the Scopus database, analyzing 545 publications spanning 1989 to 2023. Tools such as Biblioshiny and VOSviewer were employed to explore annual scientific production, identify prolific authors and key sources, and map the relationships between authors, sources, and countries using a three-field plot. The findings indicate a steady increase in research output, with the highest growth observed in the last decade, reflecting rising global concern. Trend analysis reveals a shift from foundational topics like obesity and BMI to emerging themes such as COVID-19, mental health, and food environments. The thematic map categorizes research into foundational, motor, niche, and emerging themes, highlighting key areas driving innovation and identifying underexplored topics. Bibliographic coupling analysis underscores the influence of foundational works while revealing integration opportunities for emerging studies. The co-occurrence network of keywords highlights the interdisciplinary nature of this research, spanning public health, behavioral science, and nutrition. Global collaboration patterns, led by the United States, reveal strong international partnerships but emphasize the need for enhanced regional efforts. This study provides insights into the evolving research priorities and underscores the necessity of interdisciplinary approaches to mitigate the health risks associated with fast food consumption.
References
Abbas, A. F., Jusoh, A., Masod, A., & Ali, J. (2021). A Bibliometric Analysis of Publications on Social Media Influencers Using Vosviewer. Journal of Theoretical and Applied Information Technology, 99(23), 5662–5676.
Archambault, É., Campbell, D., Gingras, Y., & Larivière, V. (2009). Comparing bibliometric statistics obtained from the Web of Science and Scopus. Journal of the American Society for Information Science and Technology, 60(7), 1320–1326. DOI: https://doi.org/10.1002/asi.21062
Beal, T., Morris, S. S., & Tumilowicz, A. (2019). Global Patterns of Adolescent Fruit, Vegetable, Carbonated Soft Drink, and Fast-Food Consumption: A Meta-Analysis of Global School-Based Student Health Surveys. Food and Nutrition Bulletin, 40(4), 444–459. Scopus. https://doi.org/10.1177/0379572119848287 DOI: https://doi.org/10.1177/0379572119848287
Bell, L. N., Singleton, C. R., & Bell, C. N. (2024). Household Composition, Income, and Fast-Food Consumption among Black Women and Men. Journal of Racial and Ethnic Health Disparities, 11(4), 2318–2328. Scopus. https://doi.org/10.1007/s40615-023-01699-y DOI: https://doi.org/10.1007/s40615-023-01699-y
Chowdhury, M. R., Haque Subho, M. R., Rahman, M. M., Islam, S., & Chaki, D. (2018). Impact of Fast Food Consumption on Health: A Study on University Students of Bangladesh. 2018 21st International Conference of Computer and Information Technology, ICCIT 2018. Scopus. https://doi.org/10.1109/ICCITECHN.2018.8631962 DOI: https://doi.org/10.1109/ICCITECHN.2018.8631962
Cobo, M. J., Martínez, M. A., Gutiérrez-Salcedo, M., Fujita, H., & Herrera-Viedma, E. (2015). 25years at Knowledge-Based Systems: A bibliometric analysis. 25th Anniversary of Knowledge-Based Systems, 80, 3–13. https://doi.org/10.1016/j.knosys.2014.12.035 DOI: https://doi.org/10.1016/j.knosys.2014.12.035
Fahamsyah, M. H., Mawardi, I., Laila, N., & Shabbir, M. S. (2023). Global Islamic Banking Development: A Review and Bibliometric Analysis Using R-Biblioshiny Application. Muqtasid: Jurnal Ekonomi Dan Perbankan Syariah, 14(1), 69–92. DOI: https://doi.org/10.18326/muqtasid.v14i1.69-92
Gordon-Larsen, P., Guilkey, D. K., & Popkin, B. M. (2011). An economic analysis of community-level fast food prices and individual-level fast food intake: A longitudinal study. Health & Place, 17(6), 1235–1241. DOI: https://doi.org/10.1016/j.healthplace.2011.07.011
Guleria, D., & Kaur, G. (2021). Bibliometric analysis of ecopreneurship using VOSviewer and RStudio Bibliometrix, 1989–2019. Library Hi Tech, 39(4), 1001–1024. DOI: https://doi.org/10.1108/LHT-09-2020-0218
Gupta, S. M., Naqvi, W. M., Mutkure, K. N., Varma, A., Thakur, S., Umate, R., Gupta, S., Mutkure, K., & Varma Sr, A. (2022). Bibliometric analysis on bibliometric studies of case reports in the medical field. Cureus, 14(10). https://doi.org/10.7759/cureus.29905 DOI: https://doi.org/10.7759/cureus.29905
Harzing, A.-W., & Alakangas, S. (2016). Google Scholar, Scopus and the Web of Science: A longitudinal and cross-disciplinary comparison. Scientometrics, 106, 787–804. DOI: https://doi.org/10.1007/s11192-015-1798-9
Huang, J.-H., Duan, X.-Y., He, F.-F., Wang, G.-J., & Hu, X.-Y. (2021). A historical review and Bibliometric analysis of research on Weak measurement research over the past decades based on Biblioshiny. arXiv Preprint arXiv:2108.11375.
Husain, F., & Mustafa, M. S. (2023). A Decade of Islamic Banking Research: Bibliometric Review with Biblioshiny and Vosviewer. Jambura Science of Management, 5(2), 67–85. DOI: https://doi.org/10.37479/jsm.v5i2.19295
Janssen, H. G., Davies, I. G., Richardson, L. D., & Stevenson, L. (2018a). Determinants of takeaway and fast food consumption: A narrative review. Nutrition Research Reviews, 31(1), 16–34.
Janssen, H. G., Davies, I. G., Richardson, L. D., & Stevenson, L. (2018b). Determinants of takeaway and fast food consumption: A narrative review. Nutrition Research Reviews, 31(1), 16–34. DOI: https://doi.org/10.1017/S0954422417000178
Jaworowska, A., Blackham, T., Davies, I. G., & Stevenson, L. (2013). Nutritional challenges and health implications of takeaway and fast food. Nutrition Reviews, 71(5), 310–318. DOI: https://doi.org/10.1111/nure.12031
Kawuki, J., Yu, X., & Musa, T. H. (2020). Bibliometric Analysis of Ebola Research Indexed in Web of Science and Scopus (2010-2020). In BioMed Research International (Vol. 2020). https://doi.org/10.1155/2020/5476567 DOI: https://doi.org/10.1155/2020/5476567
Komperda, R. (2017). Likert-type survey data analysis with R and RStudio. In ACS Symposium Series (Vol. 1260, pp. 91–116). https://doi.org/10.1021/bk-2017-1260.ch007 DOI: https://doi.org/10.1021/bk-2017-1260.ch007
Kumar, D., Shandilya, A. K., & Choudhuri, S. (2023). Artificial Intelligence-Enabled Bibliometric Analysis in Tourism and Hospitality Using Biblioshiny and VOSviewer Software. In AI-Centric Modeling and Analytics (pp. 260–291). CRC Press. DOI: https://doi.org/10.1201/9781003400110-15
Kuzior, A., & Sira, M. (2022). A bibliometric analysis of blockchain technology research using VOSviewer. Sustainability, 14(13), 8206. DOI: https://doi.org/10.3390/su14138206
Lee, S. T., & Lien, N. H. (2015). The influence of adult family members on children’s fast food consumption: A health belief perspective. Journal of Communication in Healthcare, 8(3), 185–196. Scopus. https://doi.org/10.1179/1753807615Y.0000000017 DOI: https://doi.org/10.1179/1753807615Y.0000000017
Lim, H.-S., Kim, T.-H., Lee, H.-H., Park, Y.-H., Lee, B.-R., Park, Y.-J., & Kim, Y.-S. (2018). Fast food consumption alongside socioeconomic status, stress, exercise, and sleep duration are associated with menstrual irregularities in Korean adolescents: Korea National Health and Nutrition Examination Survey 2009-2013. Asia Pacific Journal of Clinical Nutrition, 27(5), 1146–1154. Scopus. https://doi.org/10.6133/apjcn.032018.03
Maryanti, R., Nandiyanto, A. B. D., Hufad, A., Sunardi, S., Al Husaeni, D., & Al Husaeni, D. (2023). A computational bibliometric analysis of science education research using vosviewer. Journal of Engineering Science and Technology, 18(1), 301–309.
Moore, L. V., Diez Roux, A. V., Nettleton, J. A., Jacobs, D. R., & Franco, M. (2009). Fast-food consumption, diet quality, and neighborhood exposure to fast food: The multi-ethnic study of atherosclerosis. American Journal of Epidemiology, 170(1), 29–36. DOI: https://doi.org/10.1093/aje/kwp090
Mumena, W. A., Ateek, A. A., Alamri, R. K., Alobaid, S. A., Alshallali, S. H., Afifi, S. Y., Aljohani, G. A., & Kutbi, H. A. (2022). Fast-Food Consumption, Dietary Quality, and Dietary Intake of Adolescents in Saudi Arabia. International Journal of Environmental Research and Public Health, 19(22). Scopus. https://doi.org/10.3390/ijerph192215083 DOI: https://doi.org/10.3390/ijerph192215083
Namdar, A., Naghizadeh, M. M., Zamani, M., & Montazeri, A. (2021). Exploring the relationship between health literacy and fast food consumption: A population-based study from southern Iran. BMC Public Health, 21(1). Scopus. https://doi.org/10.1186/s12889-021-10763-3 DOI: https://doi.org/10.1186/s12889-021-10763-3
Nandiyanto, A. B. D., & Al Husaeni, D. F. (2022). Bibliometric analysis of engineering research using vosviewer indexed by google scholar. Journal of Engineering Science and Technology, 17(2), 883–894.
Racine, J. S. (2012). RStudio: A platform-independent IDE for R and Sweave. JSTOR. DOI: https://doi.org/10.1002/jae.1278
Richardson, A. S., Boone-Heinonen, J., Popkin, B. M., & Gordon-Larsen, P. (2011). Neighborhood fast food restaurants and fast food consumption: A national study. BMC Public Health, 11, 1–8. DOI: https://doi.org/10.1186/1471-2458-11-543
Rosenheck, R. (2008). Fast food consumption and increased caloric intake: A systematic review of a trajectory towards weight gain and obesity risk. Obesity Reviews, 9(6), 535–547. Scopus. https://doi.org/10.1111/j.1467-789X.2008.00477.x DOI: https://doi.org/10.1111/j.1467-789X.2008.00477.x
Sarhan, M. M., & Alhazmi, H. A. (2024). Fast food consumption and its relationship with oral health among US adults: A cross-sectional NHANES-based study. Saudi Dental Journal, 36(5), 728–732. Scopus. https://doi.org/10.1016/j.sdentj.2024.02.021 DOI: https://doi.org/10.1016/j.sdentj.2024.02.021
Shahadati, A., & Modarresi, S. M. A.-H. A. (2019). Prerequisite to Design a Health Promotion Intervention with a Social Marketing Approach to Reduce Fast Food Consumption among Students: A Formative Research with Mixed-Methods Approach. Iranian Journal of Health Education and Health Promotion, 7(4), 371–387. Scopus. https://doi.org/10.29252/IJHEHP.7.4.371 DOI: https://doi.org/10.29252/ijhehp.7.4.371
Shahzad, M. F., Lee, M. S., Hasni, M. J. S., & Rashid, Y. (2022). How does addiction of fast‐food turn into anti‐consumption of fast‐food? The mediating role of health concerns. Journal of Consumer Behaviour, 21(4), 697–712. DOI: https://doi.org/10.1002/cb.2025
Song, Y. (2016). Factors that affect fast food consumption: A review of the literature. MBA Student Scholarship, 53.
Souza de Cursi, E. (2023). Some Tips to Use R and RStudio. In E. Souza de Cursi (Ed.), Uncertainty Quantification using R (pp. 1–108). Springer International Publishing. https://doi.org/10.1007/978-3-031-17785-9_1 DOI: https://doi.org/10.1007/978-3-031-17785-9_1
Tambalis, K. D., Panagiotakos, D. B., Psarra, G., & Sidossis, L. S. (2018). Association between fast-food consumption and lifestyle characteristics in Greek children and adolescents; Results from the EYZHN (National Action for Children’s Health) programme. Public Health Nutrition, 21(18), 3386–3394. Scopus. https://doi.org/10.1017/S1368980018002707 DOI: https://doi.org/10.1017/S1368980018002707
Van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. https://doi.org/10.1007/s11192-009-0146-3 DOI: https://doi.org/10.1007/s11192-009-0146-3
Wu, Y., Wang, L., Zhu, J., Gao, L., & Wang, Y. (2021). Growing fast food consumption and obesity in Asia: Challenges and implications. Social Science & Medicine, 269, 113601. DOI: https://doi.org/10.1016/j.socscimed.2020.113601
Yu, Y., Li, Y., Zhang, Z., Gu, Z., Zhong, H., Zha, Q., Yang, L., Zhu, C., & Chen, E. (2020). A bibliometric analysis using VOSviewer of publications on COVID-19. Annals of Translational Medicine, 8(13), 816–816. https://doi.org/10.21037/atm-20-4235 DOI: https://doi.org/10.21037/atm-20-4235
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