An Investigation of Healthy Food Consumption in Low-Income Families

Pei Liu^1, and Heyao Chandler Yu²

¹Hospitality Management, University of Missouri, Columbia, Missouri, US

²Hospitality Management, The Pennsylvania State University, University Park, Pennsylvania, US

Cite this paper:
Pei Liu and Heyao Chandler Yu. An Investigation of Healthy Food Consumption in Low-Income Families. Journal of Food and Nutrition Research. 2019; 7(7):514-521. doi: 10.12691/jfnr-7-7-5

Abstract

The highest obesity rates were associated with the lowest incomes and low educational levels. Little is currently known about low-income families’ perceptions about healthy food and their decision-making processes when selecting food items. The purpose of this project was to assess perceptions, determinants, and decision-making processes regarding healthy food choices among low-income families in the U.S. Study participants were recruited from a local food pantry in Ruston, Louisiana in the US from February 2016 to May 2016. Researchers set up a table inside of the food pantry, and participants were asked to complete a written survey during their food pantry visits. A total 153 participants completed the survey. The survey instrument was composed of three sections. The first part consisted of items assessing participants’ attitude, subjective norm, perceived behavioral control, and intention toward healthy food consumption. The second section included measurement items designed to assess salient beliefs and referents regarding healthy food consumption. The last section consisted of questions related to participants’ social demographic information, including gender, age, race, income level, education level, and self-reported height (feet and inches) and weight (pounds). Descriptive analysis, exploratory factor analysis, confirmatory factor analysis, and multi-group structural equation modeling were used in the study. Most of the low-income families participating in the study hold positive attitude and high intention towards consuming healthy food (β = 0.730, p < 0.01). For normal-weight, low-income individuals, intention to consume healthy food was only influenced by cost and environmental constraints (β = 0.552, p < 0.01), while perceptions of family members, friends, and health practitioners (β = 0.757, p < 0.01) significantly influenced overweight participants’ intention. Nutrition and health monitoring and assistance are very important for the well-being of overweight low-income residents.

Keywords:
healthy food the theory of planned behavior overweight low-income families

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References:

[1]	Centers for Disease Control and Prevention (2010a), “Number of Americans with diabetes projected to double or triple by 2050”, available at: http://www.cdc.gov/media/pressrel/2010/r101022.html (accessed December 2017).
[2]	Centers for Disease Control and Prevention (2017b), “Healthy weight”, available at: http://www.cdc.gov/healthyweight/assessing/ (accessed December 2017).
[3]	Centers for Disease Control and Prevention (2017c), “National diabetes statistics report”, available at: https://www.cdc.gov/diabetes/pdfs/data/statistics/national-diabetes-statistics-report.pdf (accessed December 2017).
[4]	Centers for Disease Control and Prevention (2017d), “Overweight and obesity”, available at http://www.cdc.gov/obesity/index.html (accessed December 2017).
[5]	American Diabetes Associations (2017), “Fast facts: Data and statistics about diabetes”, available at: http://www.diabetes.org/assets/pdfs/basics/cdc-statistics-report-2017.pdf (accessed December 2017).
[6]	Department of Health and Human Service (DHHS) (2010), “Federal interagency forum on aging-related statistics. Old Americans 2008: key indicators of well-being”, available at: https://agingstats.gov/docs/PastReports/2008/OA2008.pdf (accessed December 2017).
[7]	USDA (2015), “Dietary guidelines for Americans 2015-2020. 8th ed.”, available at https://health.gov/dietaryguidelines/2015/resources/2015-2020_Dietary_Guidelines.pdf (accessed December 2017).
[8]	Anderson, K. and Mirosa, M. (2013), “Revealing barriers to healthier fast food consumption choices”, British Food Journal, Vol. 116, pp. 821-831.
[9]	Ajzen, I. (1991), “The theory of planned behavior”, Organization Behavior Human Decision Process, Vol. 50, pp. 179-211.
[10]	Conner, M., Norman, P., and Bell, R. (2002), “The theory of planned behavior and healthy eating”, Health Psychology, Vol. 21, pp. 194-201.
[11]	Conner, M., Norman, P., and Bell, R. (2006), “The theory of planned behavior and healthy eating”, Health Psychology, Vol. 21 No. 2, pp. 194-201.
[12]	Lien, N., Lytle, L. A., and Komro, K. A. (2002), “Applying theory of planned behavior to fruit and vegetable consumption of young adolescents”, American Journal of Health Promotion, Vol. 16 No. 4, pp. 189-197.
[13]	Armitage, C. J. and Conner, M. (2009), ““Distinguishing perceptions of control from self-efficacy: Predicting consumption of a low-fat diet using the theory of planned behavior”: Erratum.”, Journal of Applied Social Psychology, Vol. 39 No. 8, pp. 2021.
[14]	Ajzen, I. and Fishbein, M. (1980), Understanding Attitudes and Predicting Social Behavior. Englewood Cliffs, NJ: Prentice-Hall.
[15]	Muthén, L. K., and Muthén, B. O. (2009), “How to use a Monte Carlo study to decide on sample size and determine power”, Structural Equation Modeling: A Multidisciplinary Journal, Vol. 9 No. 4, No. 4, pp. 599-620.
[16]	Proctor, B. D., Semega, J. L., and Kollar, M.A. (2016), “Current population reports”, available at: https://www.census.gov/content/dam/Census/library/publications/2016/demo/p60-256.pdf (accessed November 2017).
[17]	Enders, C. K. and Bandalos, D. L. (2001) “The relative performance of full information maximum likelihood estimation for missing data in structural equation models”, Structural Equation Modeling: A Multidisciplinary, Vol. 8, pp. 430-457.
[18]	Kline, R. (2015), Principles and Practice of Structural Equation Modeling. NY: The Guilford Press.
[19]	Cohen, A. (1969), “Political anthropology: The analysis of the symbolism of power relations”, Man, Vol. 4, pp. 215-235.
[20]	Liu, Y., West, S. G., Levy, R. and Aiken, L. S. (2017), “Tests of simple slopes in multiple regression models with an interaction: Comparison of four approaches”, Multivariate Behavioral Research, Vol. 52 No. 4, pp.1-20.
[21]	Hearty, A. P., McCarthy, S. N, Kearney, J.M and Gibney, M. J. (2007), “Relationship between attitudes towards healthy eating and dietary behaviour, lifestyle and demographic factors in a representative sample of Irish adults”, Appetite, Vol. 48, pp. 1-11.
[22]	Fila, S. A. and Smith, C. (2006), “Applying the theory of planned behavior to healthy eating behaviors in urban Native American youth”, International Journal of Behavioral Nutrition Physical Activity, Vol. 3, pp. 11.
[23]	Conner, M., Sheeran, P., Norman, P., and Armitage, C. J. (2000), “Temporal stability as a moderator of relationships in the theory of planned behavior”, British Journal of Social Psychology, Vol. 39, pp. 469-493.
[24]	Armitage, C. J. and Conner, M. (2001), “Efficacy of the theory of planned behaviour: A meta-analytic review”, British Journal of Social Psychology, Vol. 40, pp. 471-499.
[25]	Leung, C. W., Epel, E. S., Ritchie, L. D., Crawford, P. B., and Laraia, B. A. (2014), “Food insecurity is inversely associated with diet quality of lower-income adults”, Journal of Academy of Nutrition and Dietetics, Vol. 114, pp. 943-1953.
[26]	Armitage, C. J. and Conner, M. (1999), “Distinguishing perceptions of control from self-efficacy: Predicting consumption of a low-fat diet using the theory of planned behavior”, Journal of Applied Social Psychology, Vol. 29, pp. 72-90.
[27]	Boyington, J. E. A., Carter-Edwards, L., Piehl, M., Hutson, J., Langdon, D., and McManus, S. (2008), “Cultural attitudes toward weight, diet, and physical activity among overweight African American girls”, Preventing Chronic Disease, Vol. 5 No. 2, pp.1.
[28]	Little, T. D. (2013), Longitudinal Structural Equation Modeling. NY: The Guilford Press.
[29]	Walker, R.E and Kawachi, I. (2012), “Use of concept mapping to explore the influence of food security on food buying practices”, Journal of the Academy of Nutrition and Dietetics, Vol. 112 No. 5, pp. 711-717
[30]	Tarasuk, V., McIntyre, L., and Li, J. (2007), “Low-income women's dietary intakes are sensitive to the depletion of household resources in one month”, The Journal of Nutrition, Vol. 137, pp. 1980-1987.
[31]	Konttinen, H., Haukkala, A., Sarlio-Lähteenkorva, S. Silventoinen, K., and Jousilahti, P. (2009), “Eating styles, self-control and obesity indicators. The moderating role of obesity status and dieting history on restrained eating”, Appetite, Vol. 53, pp. 131-134.
[32]	Crescioni, A. W., Ehrlinger, J., Alquist, J. L., Conlon, K. E., Baumeister, R. F., Schatschneider, C., and Dutton, G. R. (2011), “High trait self-control predicts positive health behaviors and success in weight loss.”, Journal of Health Psychology, Vol. 16 No. 5, pp. 50-759.
[33]	Elfhag, K., and Morey, L. C. (2008), “Personality traits and eating behavior in the obese: Poor self-control in emotional and external eating but personality assets in restrained eating”, Eating Behaviors, Vol. 9, pp. 285-293.
[34]	Cooke, R., Dahdah, M., Norman, P. and French, D. P. (2016), “How well does the theory of planned behaviour predict alcohol consumption? A systematic review and meta-analysis”, Health Psychology Review, Vol. 10, pp. 148-167.
[35]	De Jong, M. G., Pieters, R., and Fox, J. P. (2010), “Reducing social desirability bias through item randomized response: An application to measure underreported desires”, Journal of Marketing Research, Vol. 47, pp. 14-27.
[36]	Kaplan, D. (2000), Structural Equation Modeling: Foundations and Extensions. Thousand Oaks, Calif: Sage Publications.