Psychological Determinants of Millet Consumption among Diabetic Patients in Urban Kerala

Authors

  •   Chithu Elsa Chacko Master’s Student (Corresponding Author), Department of Agri-Business Management and Food Technology, North-Eastern Hill University (NEHU), Shillong - 793 022, Meghalaya ORCID logo https://orcid.org/0009-0006-3803-9797
  •   Deepak Bhagat Professor, Department of Agri-Business Management and Food Technology, North-Eastern Hill University (NEHU), Shillong - 793 022, Meghalaya
  •   Golli Mohan Assistant Professor, KL Business School, Koneru Lakshmaiah Education Foundation (Deemed to be University), Vaddeswaram, Guntur District - 522 502, Andhra Pradesh ORCID logo https://orcid.org/0000-0002-7742-1976
  •   Thrinadha Rao Bandaru Assistant Professor, Department of Management, North-Eastern Hill University (NEHU), Shillong - 793 022, Meghalaya

DOI:

https://doi.org/10.17010/ijom/2026/v56/i3/175229

Keywords:

diabetes mellitus, millet consumption, consumption intention, dietary behavior, psychological factors.
Publishing Chronology: Paper Submission Date : August 15, 2025 ; Paper sent back for Revision : January 20, 2026 ; Paper Acceptance Date : February 15, 2026 ; Paper Published Online : March 15, 2026

Abstract

Purpose : This study examined the psychological determinants of millet consumption behavior among individuals with diabetes in urban Kerala. Although millets are known for their nutritional benefits in diabetes management, their consumption remains low among patients with diabetes. The study researched the effects of attitudinal, social, and control-related factors on consumption intention and actual behavior.

Methodology : A quantitative cross-sectional research design was employed. Data were collected from diabetic patients in urban Kerala using a structured questionnaire. Of 300 questionnaires distributed, 258 valid responses were retained for analysis. Attitude, subjective norms, and perceived behavioral control were predictors, while consumption intention and actual behavior were outcomes. Data were analyzed with partial least squares structural equation modelling (PLS-SEM).

Findings : The results indicated that attitude, subjective norms, and perceived behavioral control significantly influenced consumption intention. Consumption intention, in turn, significantly affected actual millet consumption behavior and mediated the relationships between psychological determinants and behavior, highlighting its central role in dietary decision-making among diabetic patients.

Practical Implications : The results indicated that nutrition awareness, social support systems, and improved access to millet-based foods should be prioritized by healthcare professionals, policymakers, and food system stakeholders to promote healthier dietary practices and better diabetes management.

Originality : Unlike prior studies that primarily emphasized the nutritional or biomedical benefits of millets, this research provided behavioral insights by empirically examining the psychological determinants of millet consumption.

Downloads

Download data is not yet available.

Downloads

Published

2026-03-15

How to Cite

Chacko, C. E., Bhagat, D., Mohan, G., & Bandaru, T. R. (2026). Psychological Determinants of Millet Consumption among Diabetic Patients in Urban Kerala. Indian Journal of Marketing, 56(3), 30–48. https://doi.org/10.17010/ijom/2026/v56/i3/175229

Issue

Volume 56, Issue 3, March 2026

Section

Articles
Crossref
Scopus
Google Scholar
Europe PMC

References

1) Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T

2) Alharbi, M., Alharbi, M., Surrati, A., Alhilabi, M., Alrashdi, A., & Almokhalafi, M. (2024). Dietary knowledge assessment among the patients with type 2 diabetes in Madinah: A cross-sectional study. F1000Research, 12, Article no. 416. https://doi.org/10.12688/f1000research.131518.2

3) Anitha, S., Botha, R., Kane-Potaka, J., Givens, D. I., Rajendran, A., Tsusaka, T. W., & Bhandari, R. K. (2021). Can millet consumption help manage hyperlipidemia and obesity? A systematic review and meta-analysis. Frontiers in Nutrition, 8, Article ID 700778. https://doi.org/10.3389/fnut.2021.700778

4) Anitha, S., Tsusaka, T. W., Botha, R., Givens, D. I., Rajendran, A., Parasannanavar, D. J., Subramaniam, K., Bhandari, R. K., & Kane-Potaka, J. (2024). Impact of regular consumption of millets on fasting and post-prandial blood glucose level: A systematic review and meta-analysis. Frontiers in Sustainable Food Systems, 7, Article ID 1226474. https://doi.org/10.3389/fsufs.2023.1226474

5) Ashrafi, E., Mansourian, M., Azar, F. E., Rahideh, S. T., Ezadi, B., & Osmani, F. (2023). Investigation of factors related to healthy eating behavior based on the developed theory of

planned behavior in adolescents. Journal of Education and Health Promotion, 12, Article no. 274. https://doi.org/10.4103/jehp.jehp_904_22

6) Bakshi, M., & Verma, R. (2023). Cause-related marketing and purchase intention: A study on Indian millennials. Prabandhan: Indian Journal of Management, 16(10), 32–45. https://doi.org/10.17010/pijom/2023/v16i10/173196

7) Baumgartner, H., & Weijters, B. (2021). Dealing with common method variance in international marketing research. Journal of International Marketing, 29(3), 7–22. https://doi.org/10.1177/1069031X219958

8) Canova, L., Bobbio, A., & Manganelli, A. M. (2020). Buying organic food products: The role of trust in the theory of planned behavior. Frontiers in Psychology, 11, Article no. 575820. https://doi.org/10.3389/fpsyg.2020.575820

9) Chande, M., Muhimbula, H., Mremi, R., Muzanila, Y. C., Kumwenda, N. C., Msuya, J., Masere, H., Bekunda, M., Okori, P., & Gichohi-Wainaina, W. N. (2021). Drivers of millet consumption among school-aged children in Central Tanzania. Frontiers in Sustainable Food Systems, 5, Article ID 694160. https://doi.org/10.3389/fsufs.2021.694160

10) Chatterjee, S., & Kundu, A. (2020). Sub-conscious decision mapping and network framework for retail market consumption. Indian Journal of Marketing, 50(2), 35–51. https://doi.org/10.17010/ijom/2020/v50/i2/150440

11) Chen, W., Ma, G., & Jia, Z. (2024). Consumer behavior and healthy food consumption: Quasi-natural experimental evidence from Chinese household participation in long-term care insurance. Frontiers in Sustainable Food Systems, 8, Article ID 1364749. https://doi.org/10.3389/fsufs.2024.1364749

12) Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Routledge. https://doi.org/10.4324/9780203771587

13) Dash, G., Akmal, S., & Chakraborty, D. (2022). A study on adoption of e-health services: Developing an integrated framework in a multinational context. Indian Journal of Marketing, 52(5), 25–40. https://doi.org/10.17010/ijom/2022/v52/i5/169415

14) Dirgiatmo, Y. (2025). Chapter 11: Testing the discriminant validity and heterotrait–monotrait ratio of correlation (HTMT): A case in Indonesian SMEs. In W. A. Barnett & B. S. Sergi (eds.), Macroeconomic risk and growth in the Southeast Asian countries: Insight from Indonesia (Vol. 33A). Emerald Publishing Limited. https://doi.org/10.1108/S1571-0386202333A

15) Duraiswamy, M., Jayaseelan, V., Ramakrishnan, J., Rengaraj, S., Krishnamoorthy, Y., Kais, M., & Subbaiah, M. (2024). Effect of millets once a day on glycaemic control among women with gestational diabetes mellitus in a tertiary care setting: A randomized controlled trial. Indian Journal of Endocrinology and Metabolism, 28(6), 581–588. https://doi.org/10.4103/ijem.ijem_314_24

16) Erler, M., Keck, M., & Dittrich, C. (2022). The changing meaning of millets: Organic shops and distinctive consumption practices in Bengaluru, India. Journal of Consumer Culture, 22(1), 124–142. https://doi.org/10.1177/1469540520902508

17) Gefen, D., Straub, D., & Boudreau, M.-C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the Association for Information Systems, 4(1), Article 7. https://doi.org/10.17705/1CAIS.00407

18) Gifford, R., Lacroix, K., Asgarizadeh, Z., Anderson, E. A., Milne-Ives, M., & Sugrue, P. (2024). Applying the theory of behavioral choice to plant-based dietary intentions. Appetite, 197, Article ID 107271. https://doi.org/10.1016/j.appet.2024.107271

19) Gireesh, S., Dinesh, G. K., Adityan, S., Abinaya, S., Aravindharajan, S. T., Anokhe, A., Venkatramanan, V., Manu, S. M., Shahidha, P. A., Geetha, I. R., & Surendhar, P. (2025). Assessing India's millet promotion policies: Schemes and initiatives of the Government of India to promote millets for food and nutritional security through a systematic approach. AGRIVITA Journal of Agricultural Science, 47(3), 616–629. https://doi.org/10.17503/agrivita.v47i3.4332

20) Hair, J. F., Babin, B. J., Ringle, C. M., Sarstedt, M., & Becker, J.-M. (2025). Covariance-based structural equation modeling (CB-SEM): A SmartPLS 4 software tutorial. Journal of Marketing Analytics, 13, 709–724. https://doi.org/10.1057/s41270-025-00414-6

21) Hair, J. F., Hult, G. T., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). SAGE Publications.

22) Hassan, Z. M., Sebola, A., & Mabelebele, M. (2021). The nutritional use of millet grain for food and feed: A review. Agriculture & Food Security, 10, Article no. 16. https://doi.org/10.1186/s40066-020-00282-6

23) ICMR–INDIAB Study Group. (2023). India: Health of the nation's states – The India state-level disease burden initiative – Diabetes collaborators. Indian Council of Medical Research.

24) Indian Council of Medical Research. (2011). ICMR–India Diabetes (INDIAB) study – Phase I: Prevalence of diabetes in Kerala. https://iidkerala.org/assets/image/pdf/ICMR.pdf

25) International Diabetes Federation. (2023). IDF diabetes atlas (10th ed.). IDF. https://diabetesatlas.org

26) Kane-Potaka, J., Anitha, S., Tsusaka, T. W., Botha, R., Budumuru, M., Upadhyay, S., Kumar, P., Mallesh, K., Hunasgi, R., Jalagam, A. K., & Nedumaran, S. (2021). Assessing millets and sorghum consumption behavior in urban India: A large-scale survey. Frontiers in Sustainable Food Systems, 5, Article ID 680777. https://doi.org/10.3389/fsufs.2021.680777

27) Kate, N., Chaudhary, P., & More, M. (2024). Antecedents to organic tea buying behavior and consumption among millennials in India: Through the lens of theory of planned behavior. Indian Journal of Marketing, 54(1), 44–62. https://doi.org/10.17010/ijom/2024/v54/i1/173382

28) Katkuri, S., Saxena, S., Komarraju, S., Dasarathan, S., & Muralidharan, S. (2024). Physicians' perceived barriers to millet-based diets in clinical practice: A cross-sectional survey. Journal of Biological Methods, 11(4), Article ID e99010030. https://doi.org/10.14440/jbm.2024.0040

29) Kock, N. (2020). Harman's single-factor test in PLS-SEM: Checking for common method bias. Data Analysis Perspectives Journal, 2(2), 1–6. https://www.scirp.org/reference/referencespapers?referenceid=3741290

30) Kumar, A., Mallick, S. S., Hota, S. L., Vasudevan, A., & Şimşek, S. A. (2025). Green marketing strategies: Enhancing brand image and consumer trust in sustainable development. Prabandhan: Indian Journal of Management, 17(12), 8–27. https://doi.org/10.17010/pijom/2024/v17i12/174054

31) La Barbera, F., & Ajzen, I. (2020). Control interactions in the theory of planned behavior: Rethinking the role of subjective norm. Europe's Journal of Psychology, 16(3), 401–417. https://doi.org/10.5964/ejop.v16i3.2056

32) Lakhani, K. G., Prajapati, P., Hamid, R., Patel, S. K., Dwivedi, A., & Suthar, K. P. (2024). From millets to medicine: ADMET insights into diabetes with P. sumatrense compounds. Biocatalysis and Agricultural Biotechnology, 61, 103396. https://doi.org/10.1016/j.bcab.2024.103396

33) Li, Y., & Shan, B. (2025). Exploring the role of health consciousness and environmental awareness in purchase intentions for green-packaged organic foods: An extended TPB model. Frontiers in Nutrition: Food Policy and Economics, 12, 1528016. https://doi.org/10.3389/fnut.2025.1528016

34) Linge, A., Singh, M., Kakde, B., & Punjani, K. K. (2022). Application of the theory of planned behaviour to predict college students' online purchase intention: A systematic review and meta-analysis. Indian Journal of Marketing, 52(12), 39–57. https://doi.org/10.17010/ijom/2022/v52/i12/172561

35) Lwin, M. O., Malik, S., & Lau, J. (2020). Association between food availability and young people's fruit and vegetable consumption: Understanding the mediation role of the theory of planned behaviour. Public Health Nutrition, 23(12), 2155–2164. https://doi.org/10.1017/S1368980019005263

36) Majumder, J., Gangopadhyay, S., & Biswas, S. (2025). Gender, sustainability, and behavior: A TPB analysis of Eastern India's green purchases. Prabandhan: Indian Journal of Management, 18(5), 27–49. https://doi.org/10.17010/pijom/2025/v18i5/174410

37) Mathur, S., Vishnoi, S. K., Bagga, T., Mittal, A., & Mittal, A. (2024). Examining the impact of argument quality and source credibility on consumers' behavioral intention toward green cosmetics: The moderating role of perceived innovativeness. Prabandhan: Indian Journal of Management, 17(3), 26–47. https://doi.org/10.17010/pijom/2024/v17i3/173364

38) Ministry of Health and Family Welfare, Government of India. (2021). National Family Health Survey (NFHS-5), 2019–21: India Report. International Institute for Population Sciences. https://dhsprogram.com/pubs/pdf/FR375/FR375.pdf

39) Mohan, R., & Kinslin, D. (2022). The theory of planned behaviour and examining consumer purchase behaviours of energy-efficient lighting products. International Journal of Professional Business Review, 7(2), Article ID e0422. https://doi.org/10.26668/businessreview/2022.v7i2.422

40) Nandi, S., & Singh, S. (2021). Young adults' engagement with Facebook advertisements: An exploratory study using the theory of planned behaviour. Indian Journal of Marketing, 51(2), 9–23. https://doi.org/10.17010/ijom/2021/v51/i2/157548

41) Nik Mat, N. K., & Sentosa, I. (2008). The integration of theory of planned behavior (TPB) and technology acceptance model in internet purchasing: A structural equation modeling (SEM) approach. In Proceedings of the Applied International Business Conference, 466–481. https://www.researchgate.net/publication/275214932

42) Pahari, S., Ghosal, I., Prasad, B., & Dildar, S. M. (2023). Which determinants impact consumer purchase behavior toward online purchasing of organic food products? Prabandhan: Indian Journal of Management, 16(1), 25–41. https://doi.org/10.17010/pijom/2023/v16i1/172667

43) Pandey, P. K., Verma, P., & Trayambak, S. (2020). Empirical analysis of interrelationship between service quality, consumer involvement, and consumer satisfaction. Indian Journal of Marketing, 50(4), 25–42. https://doi.org/10.17010/ijom/2020/v50/i4/151571

44) Pappu, S., Kotni, V. V., Prasanna, I. L., & Krishna, S. V. (2025). Digital marketing influence research in consumer behavior: A systematic literature review using TCCM and future research agenda. Indian Journal of Marketing, 55(6), 9–28. https://doi.org/10.17010/ijom/2025/v55/i6/175108

45) Pingali, P., Aiyar, A., Abraham, M., & Rahman, A. (2019). Transforming food systems for a rising India. Palgrave Macmillan Cham. https://doi.org/10.1007/978-3-030-14409-8

46) Podsakoff, P. M., & Organ, D. W. (1986). Self-reports in organizational research: Problems and prospects. Journal of Management, 12(4), 531–544. https://doi.org/10.1177/014920638601200408

47) Podsakoff, P. M., Podsakoff, N. P., Williams, L. J., Huang, C., & Yang, J. (2024). Common method bias: It's bad, it's complex, it's widespread, and it's not easy to fix. Annual Review of Organizational Psychology and Organizational Behavior, 11, 17–61. https://doi.org/10.1146/annurev-orgpsych-110721-040030

48) Premi, H., Sharma, M., & Dangayach, G. S. (2021). Green marketing: A systematic literature review. Indian Journal of Marketing, 51(8), 39–57. https://doi.org/10.17010/ijom/2021/v51/i8/165761

49) Randall, T., Cousins, A. L., Neilson, L., Price, M., Hardman, C. A., & Wilkinson, L. L. (2024). Sustainable food consumption across western and non-western cultures: A scoping review considering the theory of planned behaviour. Food Quality and Preference, 114, Article ID 105086. https://doi.org/10.1016/j.foodqual.2023.105086

50) Sagayanathan, G. J., & Sudhagar, D. P. (2025). Testing theory of planned behaviour to predict purchase intention of millets. International Research Journal of Economics and Management Studies, 4(3), 210–217. https://doi.org/10.56472/25835238/IRJEMS-V4I3P123

51) Sarstedt, M., Hair Jr., J. F., Cheah, J.-H., Becker, J.-M., & Ringle, C. M. (2019). How to specify, estimate, and validate higher-order constructs in PLS-SEM. Australasian Marketing Journal, 27(3), 197–211. https://doi.org/10.1016/j.ausmj.2019.05.003

52) Sen, S., & Nayak, S. (2021). Moderating role of cultural values on the relationship among hedonism, materialism, and impulse buying: A conceptual framework. Indian Journal of Marketing, 51(1), 26–40. https://doi.org/10.17010/ijom/2021/v51/i1/156932

53) Shah, P., Mahajan, H., Sompura, N. H., Sunil, A., & Naldurgakar, R. (2025). Consumer decision‐making processes regarding healthy food choices: A systematic literature review and future research agenda. International Journal of Consumer Studies, 49(1), Article ID e70021. https://doi.org/10.1111/ijcs.70021

54) Shah, P., Mehta, N., & Shah, S. (2024). Exploring the factors that drive millet consumption: Insights from regular and occasional consumers. Journal of Retailing and Consumer Services, 76, Article ID 103598. https://doi.org/10.1016/j.jretconser.2023.103598

55) Sharief, Z., & Panghal, A. (2023). Sustainable consumption: Consumer behavior when purchasing sustainability-labeled food products. Indian Journal of Marketing, 53(8), 47–65. https://doi.org/10.17010/ijom/2023/v53/i8/172975

56) Sherman, B. W., Stiehl, E., Gupta, R., & Pratap, P. L. (2024). The importance of human-centered design in equitable health promotion initiatives. American Journal of Health Promotion, 38(3), 443–447. https://doi.org/10.1177/08901171241232057f

57) Sobaih, A. E., Algezawy, M., & Elshaer, I. A. (2023). Adopting an extended theory of planned behaviour to examine buying intention and behaviour of nutrition-labelled menu for healthy food choices in quick service restaurants: Does the culture of consumers really matter? International Journal of Environmental Research and Public Health, 20(5), 4498. https://doi.org/10.3390/ijerph20054498

58) Sogari, G., Pucci, T., Caputo, V., & Van Loo, E. J. (2023). The theory of planned behaviour and healthy diet: Examining the mediating effect of traditional food. Food Quality and Preference, 104, Article ID 104709. https://doi.org/10.1016/j.foodqual.2022.104709

59) Sohil, P., Mahajan, S., Deshmukh, R., Gothankar, J., & Adhya, S. (2025). Millet consumption in type 2 diabetics in urban slums of India: A pilot study. International Journal of Public Health Science, 14(2), 904–911. http://doi.org/10.11591/ijphs.v14i2.25422

60) Sreedevi, A., Valsalan, R., & Kumar, S. (2025). Prevalence and determinants of complications of type 2 diabetes in Kerala, India. BMJ Public Health, 3(1), e002333. https://doi.org/10.1136/bmjph-2024-002333

61) Srivastava, S., & Arya, C. (2021). Millets: Malnutrition and nutrition security. In A. Kumar, M. K. Tripathi, D. Joshi, & V. Kumar (eds.), Millets and millet technology (pp. 81–100). Springer Nature. https://doi.org/10.1007/978-981-16-0676-2_4

62) Stone, M. (1974). Cross-validation and multinomial prediction. Biometrika, 61(3), 509–515. https://doi.org/10.1093/biomet/61.3.509

63) Thakur, C. K., Vijay, T. S., & Chatterjee, T. K. (2022). A study on travelers' motivation to provide online reviews. Indian Journal of Marketing, 52(2), 8–22. https://doi.org/10.17010/ijom/2022/v52/i2/164156

64) Upadhyaya, A. S., & Sijoria, C. (2024). Customers' purchase intention of green cosmetics in India: Empirical validations using an extended theory of planned behavior (TPB). Indian Journal of Marketing, 54(8), 60–77. https://doi.org/10.17010/ijom/2024/v54/i8/174187

65) Verma, A., Lata, K., Verma, S., Rani, S., Kumar, A., & Kumar, P. N. (2024). Attitude and behavior regarding millet consumption in children with type 1 diabetes mellitus. Asian Journal of Medical Sciences, 15(5), 218–222. https://doi.org/10.3126/ajms.v15i5.62291

66) Yadav, N., & Sijoria, C. (2024). Drivers of zero-waste purchase decisions: The mediating role of the theory of planned behavior. Indian Journal of Marketing, 54(9), 37–53. https://doi.org/10.17010/ijom/2024/v54/i9/174396