Utilizing the COM‑B Model to Influence Low‑Glycemic Dietary Behavior in Urban Thai Adults with Prediabetes
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Abstract
Background: Type 2 diabetes mellitus is an escalating public health issue in rapidly urbanizing middle-income countries. In Thailand, working-age adults increasingly develop prediabetes due to sedentary lifestyles, high glycemic diets, and limited access to supportive food environments. Existing research on determinants of low glycemic dietary practices remains fragmented, with few studies applying an integrated behavioral framework.
Objective: This study examined behavioral pathways influencing low GI dietary behavior among urban adults with prediabetes, guided by the capability–opportunity–motivation–behavior (COM-B) model.
Design and Methodology: A cross-sectional analytical study was conducted among 450 adults clinically diagnosed with prediabetes in Bangkok. Data were collected using a COM-B based questionnaire for assessing psychological and physical capability, social and physical opportunity, and reflective and automatic motivation. Path analysis using maximum likelihood estimation in LISREL version 8.72 assessed model fit and structural relationships.
Results: The model demonstrated excellent fit (χ² = .32, df = 1, p = .57; RMSEA = .000; CFI = 1.00; SRMR = .005). Psychological capability (β = .47), physical capability (β = .42), physical opportunity (β = .53), social opportunity (β = .15), automatic motivation (β = .27), and reflective motivation (β = .09) significantly predicted low GI dietary behavior, explaining 77% of the variance.
Conclusion and Implications: Capability and opportunity were the strongest determinants of low GI dietary behavior. Interventions that enhance nutritional skills and strengthen supportive social and physical food environments may be more effective than motivation focused strategies for improving dietary practices among urban adults with prediabetes.
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References
Almeida, D. M., Charles, S. T., Mogle, J., Drewelies, J., Aldwin, C. M, Spiro, A., & Gerstorf, D. (2020). Charting adult development through (historically changing) daily stress processes. American Psychologist, 75(4), 511–524. https://doi.org/10.1037/amp0000597
Alvarez, S., Coffey, R., Mathias, P. M., & Algotar, A. M. (2025). Prediabetes. StatPearls Publishing. https://www.ncbi.nlm.nih.gov/books/NBK459332/
Atkins, L., Francis, J., Islam, R., O’Connor, D., Patey, A., Ivers, N., Foy, R., Duncan, E. M., Colquhoun, H., Grimshaw, J. M., Lawton, R., & Michie, S. (2017). A guide to using the theoretical domains framework of behaviour change to investigate implementation problems. Implementation Science, 12, 77. https://doi.org/10.1186/s13012-017-0605-9
Atkinson, F. S., Brand-Miller, J. C., Foster-Powell, K., Buyken, A. E., & Goletzke, J. (2021). International tables of glycemic index and glycemic load values 2021: A systematic review. American Journal of Clinical Nutrition, 114(5), 1625–1632. https://doi.org/10.1093/ajcn/nqab233
Barclay, A. W., Augustin, L. S. A., Brighenti, F., Delport, E., Henry, C. J., Sievenpiper, J. L., Usic, K., Yuexin, Y., Zurbau, A., Wolever, T. M. S., Astrup, A., Bulló, M., Buyken, A., Ceriello, A., Ellis, P. R., Vanginkel, M.-A., Kendall, C. W. C., La Vecchia, C., Livesey, G., Poli, A., Riccardi, G., Salas-Salvadó, J., Trichopoulou, A., Bhaskaran, K., Jenkins, D. J. A., Willett, W. C., & Brand-Miller, J. C. (2021). Dietary glycaemic index labelling: A global perspective. Nutrients, 13(9), 3244. https://doi.org/10.3390/nu13093244
Bureau of Non-Communicable Diseases. (2022). Thai NCDs annual report 2022. Ministry of Public Health. https://ddc.moph.go.th/uploads/publish/1392420230228064621.pdf [in Thai]
Chiavaroli, L., Lee, D., Ahmed, A., Cheung, A., Khan, T. A., Blanco Mejia, S., Mirrahimi, A., Jenkins, D. J. A., Livesey, G., Wolever, T. M. S., Rahelić, D., Kahleová, H., Salas-Salvadó, J., Kendall, C. W. C., & Sievenpiper, J. L. (2021). Effect of low glycaemic index or load dietary patterns on glycaemic control and cardiometabolic risk factors in diabetes: Systematic review and meta-analysis of randomised controlled trials. BMJ, 374, n1651. https://doi.org/10.1136/bmj.n1651
Darmon, N., & Drewnowski, A. (2015). Contribution of food prices and diet cost to socioeconomic disparities in diet quality and health: A systematic review and analysis. Nutrition Reviews, 73(10), 643–660. https://doi.org/10.1093/nutrit/nuv027
ElSayed, N. A., Aleppo, G., Aroda, V. R., Bannuru, R. R., Brown, F. M., Bruemmer, D., Collins, B. S., Hilliard, M. E., Isaacs, D., Johnson, E. L., Kahan, S., Khunti, K., Leon, J., Lyons, S. K., Perry, M. L., Prahalad, P., Pratley, R. E., Seley, J. J., Stanton, R. C., & Gabbay, R. A. (2023). Prevention or delay of diabetes and associated comorbidities: Standards of Care in Diabetes—2023. Diabetes Care, 46(Suppl. 1), S41–S48. https://doi.org/10.2337/dc23-S003
Futamura, I. (2018). Is extraordinary prosocial behavior more valuable than ordinary prosocial behavior? PLoS ONE, 13(4), e0196340. https://doi.org/10.1371/journal.pone.0196340
Gaupholm, J., Papadopoulos, A., Asif, A., Dodd, W., & Little, M. (2023). The influence of food environments on dietary behavior and nutrition in Southeast Asia: A systematic scoping review. Nutrition and Health, 29(2), 231–253. https://doi.org/10.1177/02601060221112810
Hair, J. F. Jr., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate data analysis (7th ed.). Pearson Education.
Halloran, E. C. (2024). Adult development and associated health risks. Journal of Patient-Centered Research and Reviews, 11(1), 63–67. https://doi.org/10.17294/2330-0698.2050
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
Jindarattanaporn, N. (2022). A study of the food and beverage marketing situation in Thailand. Thai Health Promotion Journal, 1(3), 274–283. https://nutrition2.anamai.moph.go.th/th/fmc/download/?did=212268&id=101311 [in Thai]
Kline, R. B. (2015). Principles and practice of structural equation modeling (4th ed.). Guilford Press.
Kongkachuichai, R., Sirijakrawan, P., Yaembrisut, U., Charoensiri, R., & Nuanmusik, J. (2018). Glycemic index and glycemic load handbook for Thai diabetic meal planning. Pornsup Printing. https://oer.learn.in.th/search_detail/result/117102 [in Thai]
Kwasnicka, D., Dombrowski, S. U., White, M., & Sniehotta, F. (2016). Theoretical explanations for maintenance of behavior change: A systematic review of behavior theories. Health Psychology Review, 10(3), 277–296. https://doi.org/10.1080/17437199.2016.1151372
Malik, V. S., & Hu, F. B. (2019). Sugar-sweetened beverages and cardiometabolic health: An update of the evidence. Nutrients, 11(8), 1840. https://doi.org/10.3390/nu11081840
Michie, S., Atkins, L., & West, R. (2014). The behavior change wheel: A guide to designing interventions. Silverback Publishing.
Michie, S., van Stralen, M. M., & West, R. (2011). The behavior change wheel: A new method for characterising and designing behavior change interventions. Implementation Science, 6, 42. https://doi.org/10.1186/1748-5908-6-42
Ng, C. A., Lasala, A. C. F., De Vera, J. F. S., & Caringal-Go, J. F. (2024). Coping behaviors of Filipino students during the COVID-19 pandemic: A contextual application of the PERMA-H framework. The Journal of Behavioral Science, 19(1), 1–17. https://so06.tci-thaijo.org/index.php/IJBS/article/view/266642
Pongutta, S., Suphanchaimat, R., Patcharanarumol, W., & Tangcharoensathien, V. (2019). Lessons from the Thai health promotion foundation. Bulletin of the World Health Organization, 97(3), 213–220. https://doi.org/10.2471/BLT.18.220277
Popkin, B. M., & Kenan, W. R. Jr. (2016). Preventing type 2 diabetes: Changing the food industry. Best Practice & Research Clinical Endocrinology & Metabolism, 30(3), 373–383. https://doi.org/10.1016/j.beem.2016.05.001
Ranasinghe, P., Rathnayake, N., Wijayawardhana, S., Jeyapragasam, H., Meegoda, V. J., Jayawardena, R., & Misra, A. (2024). Rising trends of diabetes in South Asia: A systematic review and meta-analysis. Diabetes & Metabolic Syndrome, 18(11), 103160. https://doi.org/10.1016/j.dsx.2024.103160
Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness. Yale University Press.
UN-Habitat. (2020). World cities report 2020: The value of sustainable urbanization. United Nations Human Settlements Programme. https://unhabitat.org/world-cities-report-2020-the-value-of-sustainable-urbanization
United Nations. (2023). The sustainable development goals report 2023. Department of Economic and Social Affairs. https://unstats.un.org/sdgs/report/2023/
Wang, H., Li, N., & Chivese, T. (2022). IDF diabetes atlas: Estimation of global and regional gestational diabetes mellitus prevalence for 2021 by International association of diabetes in pregnancy study group’s criteria. Diabetes Research and Clinical Practice, 183, 109050. https://doi.org/10.1016/j.diabres.2021.109050