A multi-method Analysis of Food Desert Residents’ Lived Experience with Food

Main Article Content

Terrence W. Thomas Murat Cankurt

Abstract

Accessibility is one of the main factors determining dietary habits. Food deserts are the zones where it is difficult to access healthy food. The main purpose of this study is to reveal the food perceptions, behaviors and food experiences of individuals living in food deserts in Guilford County, North Carolina. The ISAC analysis procedure (which includes identification, segmentation, and characterization stages), first published in this paper, was used to examine the study data. Factor analysis isolated the following dimensions of food value, emotional, environmental & social, economic, ethical and safety in the identification stage. Using these dimensions as clustering variables, segments labeled as value-positive, value-negative, and hedonic approaches to food values were identified. The Value-Positive segment consists mostly of African Americans who work full-time, are middle-aged, and live in one-person households. The Hedonic segment consists mostly of women, full-time workers, and young adults. Older, unemployed, and low-income individuals represent the value-negative segment. Results clearly show that each segment differed according to its demographic and behavioral characteristics. The qualitative analysis revealed that factors other than access to food are important in determining food desert residents’ relationship with food and even though residents recognize that food plays a key role in achieving good health, they are reluctant to follow healthier diets because it takes too long realize the positive effects. Overall, these results can be used to develop targeted strategies and policies for a healthier society and a better quality of life.

Article Details

How to Cite
THOMAS, Terrence W.; CANKURT, Murat. A multi-method Analysis of Food Desert Residents’ Lived Experience with Food. Medical Research Archives, [S.l.], v. 12, n. 10, nov. 2024. ISSN 2375-1924. Available at: <https://esmed.org/MRA/mra/article/view/6062>. Date accessed: 03 dec. 2024. doi: https://doi.org/10.18103/mra.v12i10.6062.
Section
Research Articles

References

1. Guilford County DHHS. State of Guilford County Health Report. Guilford County Department of Health and Human Services. Available at: https://www.guilfordcountync.gov/our-county/human-services/health-department/health-statistics/2017-state-of-guilford-county-s-health-report 2017. Accessed June12, 2024.
2. Guilford County Department of Public Health. Health concern access to healthy food. Community Health Assessment Report; 2012-2013. Available at: https://www.guilfordcountync.gov/our-county/human-services/health-department/health-statistics/2012-2013-community-health-assessment . Accessed June 12, 2024.
3. Brown C, Dukas S. A national study of the association between food environments and county-level health outcomes. J Rural Health. 2011; 27:367-379.
4. Wrigley N, Warm D, Margetts B, Whelan A. Assessing the impact of improved retail access on diet in a ‘food desert’: A preliminary report. Urban Stud. 2002; 39:2061-2082.
5. Partnership To Fight Chronic Disease North Carolina Report. Available at: https://www.fightchronicdisease.org/sites/default/files/download/PFCD_NC_FactSheet_FINAL1.pdf Published 2024. Accessed August 1, 2024.
6. Thomas TW. Food Security, Food Desert, and Common-Sense Solutions. Open Access J Biogeneric Sci Res. 2021;1-3. doi:10.46718/JBGSR.2021.07.000167.
7. Caspi CE, Sorensen G, Subramanian SV, Kawachi I. The local food environment and diet: A systematic review. Health Place. 2012;18(5):1172-1187.
8. Walker RE, Keane CR, Burke JG. Disparities in access to healthy food in the United States: A review of food deserts literature. Health Place. 2010;16(5):876-884.
9. Glanz K, Bader MDM, Iyer S. Retail grocery store marketing strategies and obesity. Am J Prev Med. 2012; 42:503-512.
10. Becker GS. The Economic Approach to Human Behavior. University of Chicago Press; 1976.
11. Shove E, Pantzar M, Watson M. The Dynamics of Social Practice: Everyday Life and How it Changes. SAGE Publications; 2012.
12. Pentland A. Social Physics: How Good Ideas Spread-The Lessons from a New Science. Scribe Publications; 2015.
13. Watts DJ. Everything is Obvious: Once You Know the Answer. Crown Business; 2011.
14. Kuijer L. Implications of Social Practice Theory for Sustainable Design. [Doctoral Thesis]. Technische Universiteit Delft; 2014. ISBN: 978-94-6186-246-4.
15. Reckwitz A. The status of the 'material' in theories of culture: From 'social structure' to 'artefacts'. J Theory Soc Behav. 2002; 32:195-217.
16. Shove E, Watson M, Hand M, Ingram J. The Design of Everyday Life. Berg Oxford; 2007.
17. Centola, D. Change: How to Make Big Things Happen. Little, Brown Spark; 2021.
18. Christakis NA, Fowler JH. The Surprising Power of Our Social Networks and How They Shape Our Lives: How Your Friends' Friends' Friends Affect Everything You Feel, Think, and Do. Little, Brown; 2011.
19. Jackson MO. The Human Network. Atlantic Books; 2020.
20. Denzin NK, Lincoln YS, eds. Handbook of Qualitative Research. 2nd ed. Sage; 2000.
21. Dillman DA, Smyth JD, Christian LM. Internet, Mail, and Mixed-Mode Surveys: The Total Design Method. 3rd ed. John Wiley & Sons; 2009.
22. Cochran WG. Sampling Techniques. 3rd ed. Wiley; 1977.
23. Rubin DB, Little RJ. Statistical Analysis with Missing Data. John Wiley & Sons; 2002.
24. Thompson B. The future of test validity. Educ Res. 2009;38(6):545-556. doi:10.3102/0013189X09346117.
25. Thomas TW, Cankurt M. Influence of Food Environments on Dietary Habits: Insights from Quasi-Experimental Research. Foods. 2024;13(13):2013. https://doi.org/10.3390/foods13132013 .
26. Cankurt M. A Study on the Determination of Farmers’ Demand for Tractor Satisfaction of Tractor Use and Purchasing Attitudes Towards Tractor: The Case of Aydın. [Doctoral Thesis]. Ege University; 2009. https://tez.yok.gov.tr/UlusalTezMerkezi/tezDetay.jsp?id=MINo0CjC2iJewLbypTyrWA&no=52JdzBZ5zimkwRKg5bptJw
27. Cankurt M, Thomas T, Gunden C, Miran B. Consumer decision-making styles: Investigation of food shopping behavior. J Food Agric Environ. 2013;11(2):224-227.
28. Cankurt M, Miran B, Sahin A. Determining of the Effective Factors on Cattle Meat Preferences: The Case of Izmir. Journal of Animal Production. 2010;51(2):16-22.
29. Tabachnick BG, Fidell LS. Using Multivariate Statistics. 5th ed. Pearson; 2007.
30. Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate Data Analysis. 7th ed. Pearson Prentice Hall; 2010.
31. Tan PN, Steinbach M, Kumar V. Introduction to Data Mining. Pearson; 2006.
32. Jain AK, Murty MN, Flynn PJ. Data Clustering: A Review. ACM Comput Surv. 1999;31(3):264-323.
33. Kaufman L, Rousseeuw PJ. Finding Groups in Data: An Introduction to Cluster Analysis. Wiley; 2009.
34. Creswell JW. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. 4th ed. SAGE Publications; 2014.
35. Kotler P, Keller KL. Marketing Management. 15th ed. Pearson; 2016.
36. Solomon MR. Consumer Behavior: Buying, Having, and Being. 12th ed. Pearson; 2018.
37. Wedel M, Kamakura WA. Market Segmentation: Conceptual and Methodological Foundations. Kluwer Academic Publishers; 2000.
38. Kotler P, Roberto N, Lee N. Social Marketing: Improving the Quality of Life. 2nd ed. SAGE Publications; 2002.
39. Lanza ST, Tan X, Bray BC. Latent Class Analysis with Distal Outcomes: A Flexible Model-Based Approach. Struct Equ Model. 2013;20(1):1-26.
40. Muthén LK, Muthén BO. Mplus User’s Guide. 8th ed. Los Angeles, CA; 2017.
41. Dolnicar S, Grün B. Challenging 'factor-cluster segmentation.' J Travel Res. 2008;47(1):63-71.
42. Bhatnagar A, Gopalaswamy AK. A Persona-Based Approach for Customer Segmentation and Marketing. Int J Inf Manage. 2017;37(1):13-20.
43. Saarijärvi H, Sutinen UM, Harris LC. Uncovering Consumer Value Formation: A Study of Employee-Customer Interactions in Mobile Banking. Int J Bank Mark. 2017;35(1):90-102.
44. Dibb S, Simkin L. Targeting Segments and Positioning. Int J Mark Res. 2016;58(6):781-804.
45. González-Rodríguez M, Díaz-Fernández MC, Hernández-Fernández A. Profiling Consumers in the Sharing Economy: Motivations and Barriers for Participation. J Bus Res. 2020; 112:208-218.
46. Anagnostopoulos A, Skourlas C. Segmenting Consumers Based on Their Shopping Behaviour Patterns in the Retail Sector. J Retail Consum Serv. 2020; 55:102120.
47. Tavakol M, Dennick R. Making sense of Cronbach's alpha. Int J Med Educ. 2011; 2:53-55.
48. Costello AB, Osborne JW. Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Pract Assess Res Eval. 2005;10(7):1-9.
49. Fabrigar LR, Wegener DT, MacCallum RC, Strahan EJ. Evaluating the use of exploratory factor analysis in psychological research. Psychol Methods. 1999;4(3):272-299.
50. Zwick WR, Velicer WF. Comparison of five rules for determining the number of components to retain. Psychol Bull. 1986;99(3):432-442.
51. Kaiser HF. An index of factorial simplicity. Psychometrika. 1974;39(1):31-36.
52. Yong AG, Pearce S. A beginner’s guide to factor analysis: Focusing on exploratory factor analysis. Tutorial Quant Methods Psychol. 2013;9(2):79-94.
53. Mazzocchi M. Statistics for Marketing and Consumer Research. SAGE Publications; 2008.
54. Wedel M, Kamakura WA. Introduction to the Special Issue on Market Segmentation. Int J Res Mark. 2002;19(3):181-183.
55. Osterwalder A, Pigneur Y. Business Model Generation: A Handbook for Visionaries, Game Changers, and Challengers. Wiley; 2010.
56. Salinas EM, Perez JMP. Modeling the Brand Extensions’ Influence on Brand Image. J Bus Res. 2009;62(1):50-60.
57. Everitt BS, Landau S, Leese M, Stahl D. Cluster Analysis. 5th ed. Wiley; 2011.
58. Field A. Discovering Statistics Using IBM SPSS Statistics. 4th ed. SAGE Publications; 2013.
59. Tabachnick BG, Fidell LS. Using Multivariate Statistics. 7th ed. Pearson; 2019.
60. Thomas, T and Gunden, C and Legesse, B. Leveraging Food-Related Values for Impact in Community Nutrition Education Programs (Interventions), Foods, 2023, Volume 12, 4
61. Lusk, J.L.; Briggerman, B.C. Food values. Am. J. Agric. Econ. 2009, 91, 184–196.
62. Bazzani, C.; Gustavsen, G.W.; Nayga, N.M.; Rickertsen, K. A comparative study of food values between the United States and Norway. Eur. Rev. Agric. Econ. 2018, 45, 239–272.
63. Pérez-Villarreal HH, Martínez-Ruiz MP, Izquierdo-Yusta A, Gómez-Cantó CM. Food Values, Benefits and Their Influence on Attitudes and Purchase Intention: Evidence Obtained at Fast-Food Hamburger Restaurants. Sustainability. 2020; 12(18):7749. https://doi.org/10.3390/su12187749
64. Yang S-H, Panjaitan BP. A Multi-Country Comparison of Consumers’ Preferences for Imported Fruits and Vegetables. Horticulturae. 2021; 7(12):578. https://doi.org/10.3390/horticulturae7120578
65. Cankurt, M., Akpinar, A., Miran, B. An Exploratory Study on the Perception of Air, Water, Soil, Visual and General Pollution. Ekoloji 25, 98, 52-60 (2016) doi: 10.5053/ekoloji.2016.02
66. Harris CR, Jenkins M. Gender Differences in Risk Assessment: Why do Women Take Fewer Risksthan Men? Judgment and Decision Making. 2006;1(1):48-63. doi:10.1017/S1930297500000346
67. Banarjee AV, Duflo E. Poor Economics: A Radical Rethinking of the Way to Fight Global Poverty. New York, NY, 2011.