Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-26T03:40:27.322Z Has data issue: false hasContentIssue false

Socio-economic and behavioural factors are predictors of food use in the National Food Stamp Program Survey

Published online by Cambridge University Press:  09 March 2007

Alok Bhargava*
Affiliation:
Department of Economics, University of Houston, Houston, Texas, USA
*
*Corresponding author: fax +1 713 743 3798, Email [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

The unhealthy dietary patterns in the USA especially among low-income households demand complex strategies for health promotion. The present paper analysed the proximate determinants of 7 d food use by 919 participants in the National Food Stamp Program Survey conducted in 1996. The households' consumption of dietary energy, carbohydrate, protein, fibre, saturated, monounsaturated and polyunsaturated fats, Ca, Fe, β-carotene and vitamin C were explained by background, socio-economic and behavioural factors. Certain methodological issues arising in modelling food use data were addressed. The results showed that the subjects' knowledge of the US Department of Agriculture food pyramid, reading nutrition labels, adopting a low-fat diet, selecting fruits and vegetables, saving money at grocery stores and frequency of shopping trips were often significantly associated (P>0·05) with the densities of nutrient use. The results identified certain aspects of nutrition education programmes that deserve greater emphasis for improving diet quality. The model for energy intake indicated that disbursing half the food stamp benefits on a 2-week basis and better shopping practices can enhance food availability.

Type
Research Article
Copyright
Copyright © The Nutrition Society 2004

References

Agency for Healthcare Research and Quality Efficacy of Interventions to Modify Dietary Behavior Related to Cancer Risk. http://www.ahrq.gov/clinic/epcsums/dietsumm.htm (2001)Google Scholar
Akaike, HInformation theory and the extension of the maximum likelihood principle. In Second International Symposium on Information Theory, pp. 267281 [Petrov, B and Csaki, F, editors]. Budapest: Akademai Kiado. (1973)Google Scholar
Basiotis, P, Brown, M, Johnson, SR & Morgan, KJNutrient availability, food costs, and food stamps. Am J Agric Econ (1983) 65, 685693.CrossRefGoogle Scholar
Bhargava, A & Guthrie, JFUnhealthy eating habits, physical exercise and macronutrient intakes are predictors of anthropometric indicators in the women's health trial: feasibility study in minority populations. Br J Nutr (2002) 88, 719728.CrossRefGoogle ScholarPubMed
Bhargava, A & Hays, JBehavioural variables and education are predictors of dietary change in the Women’s Health Trial: feasibility study in minority populations. Prev Med (2004) 38, 442451.CrossRefGoogle ScholarPubMed
Bhargava, A & Reeds, PJRequirements for what? Is the measurement of energy expenditure a sufficient estimate of energy needs? J Nutr (1995) 125, 13581362.Google ScholarPubMed
Cohen, B, Ohls, J, Andrews, M, Ponza, M, Moreno, L, Zambrowski, A & Cohen, RFood Stamp Participants, Food Security and Nutrient Availability. Technical Report, Economic Research Service. Washington, DC: US Department of Agriculture. (1999)Google Scholar
Contento, IThe effectiveness of nutrition education and implications, nutrition education policy, programs, and research: a review of research. J Nutr Educ (1995) 27, 279418.Google Scholar
Cox, DR & Hinkley, DVTheoretical Statistics. London: Chapman and Hall. (1974)CrossRefGoogle Scholar
Cronbach, LJEssentials of Psychological Testing, 4th ed. New York: Harper and Row. (1984)Google Scholar
Goldberg, GR, Black, AE, Jebb, SA, Cole, TJ, Murgatroyd, PR, Coward, WA & Prentice, AMCrucial evaluation of energy intake data using fundamental principals of energy physiology: 1. Derivation of cut-off limits to identify underrecording. Eur J Clin Nutr (1991) 45, 569581.Google Scholar
Hersey, J, Anliker, J, Miller, C, Mullis, R, Daugherty, S, Das, S, Bray, C, Dennee, P, Sigman-Grant, M & Thomas, HOFood shopping practices are associated with dietary quality in lowincome households. J Nutr Educ (2001) 33, S16S26.CrossRefGoogle ScholarPubMed
James, WPT & Schofield, EHuman Energy Requirements. Oxford: Oxford University Press (1990)Google Scholar
Lutz, SF, Ammerman, AS, Atwood, J, Campbell, MK, DeVellis, RF & Rosamond, WDInnovative newsletter interventions improve fruit and vegetable consumption in healthy adults. J Am Diet Assoc (1999) 99, 705709.CrossRefGoogle ScholarPubMed
Monsen, ER & Balintfy, JLCalculating dietary iron bioavailability: refinement and computerization. J Am Diet Assoc (1982) 80, 307311.CrossRefGoogle ScholarPubMed
National Cancer Institute 5 a Day for Better Health Program. National Insititutes of Health Publication no. 01-5019. Bethesda, MD: NIH. (2001)Google Scholar
Pérez-Escamilla, R & Haldeman, LFood label use modifies association of income with dietary quality. J Nutr (2002) 132, 768772.CrossRefGoogle ScholarPubMed
Rose, DEconomic determinants and dietary consequences of food insecurity in the United States. J Nutr (1999) 129, 517S520S.CrossRefGoogle ScholarPubMed
Scrimshaw, NS & SanGiovanni, JPSynergism of nutrition, infection, and immunity: an overview. Am J Clin Nutr (1997) 66, 464S477S.CrossRefGoogle ScholarPubMed
Steptoe, A, Dohert, A, Kerry, A, Rink, E & Hilton, SSociodemographic and psychological predictors of change in dietary fat consumption in adults with high blood cholesterol following counseling in primary care. Health Psychol (1999) 19, 411419.CrossRefGoogle Scholar
Townsend, MS, Peerson, J, Love, B, Achterberg, C & Murphy, SFood insecurity is positively related to overweight in women. J Nutr (2001) 131, 17381745.CrossRefGoogle ScholarPubMed
US Department of Agriculture Promoting Healthy Eating: An Investment in the Future. Report to the US Congress Alexandria, VA: Food and Nutrition Service. (1999)Google Scholar
US Department of Agriculture/Department of Health and Human Services Nutrition and Your Health: Dietary Guidelines for Americans, 5th ed. Washington, DC: DHSS. (2000)Google Scholar
Wilde, PE & Ranney, CKThe monthly food stamp cycle: shopping frequency and food intake decisions in an endogenous switching regression framework. Am J Agric Econ (2000) 82, 200213.CrossRefGoogle Scholar
Young, L & Swinburn, BImpact of the Pick the Tick food information programme on the salt content of food in New Zealand. Health Promote Int (2002) 17, 1319.CrossRefGoogle ScholarPubMed