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Effects of Socioeconomic and Demographic Factors on Consumption of Selected Food Nutrients

Published online by Cambridge University Press:  15 September 2016

Rodolfo M. Nayga Jr.*
Affiliation:
Department of Agricultural Economics and Marketing, Rutgers University

Abstract

The effects of socioeconomic and demographic factors on the consumption of food energy, protein, vitamin A, vitamin C, thiamin, riboflavin, niacin, calcium, phosphorus, and iron are examined. Socioeconomic and demographic factors analyzed are urbanization, region, race, ethnicity, sex, employment status, food stamp participation, household size, weight, height, age, and income. Several of these factors significantly affect consumption of certain nutrients. Income is an important factor affecting the consumption of vitamin A, vitamin C, and calcium. Income elasticities are relatively small at low income levels. For example, income elasticities range from 0.016 for calcium to 0.123 for vitamin C at an income level of $20,000.

Type
Articles
Copyright
Copyright © 1994 Northeastern Agricultural and Resource Economics Association 

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References

Adrian, J., and Daniel, R.Impact of Socioeconomic Factors on Consumption of Selected Food Nutrients in the United States.” American Journal of Agricultural Economics. 58 (1976): 31–8.Google Scholar
Akin, J.D., Guilkey, D.K., and Popkin, B.M.The School Lunch Program and Nutrient Intake: A Switching Regression Analysis.” American Journal of Agricultural Economics 65 (1983): 477–85.Google Scholar
Basiotis, P., Brown, M., Johnson, S.R., and Morgan, K.J.Nutrient Availability, Food Costs, and Food Stamps.” American Journal of Agricultural Economics 65 (1983): 685–93.Google Scholar
Belsley, D.A., Kuh, E., and Welsch, R.E. Regression Diagnostics, Identifying Influential Data and Sources of Collinearity, Wiley, 1980.CrossRefGoogle Scholar
Breusch, T.S., and Pagan, A.R.A Simple Test for Heteroscedasticity and Random Coefficient Variation.” Econometrica 47 (1979): 1287–94.Google Scholar
Buse, R.C., and Salathe, L.E.Adult Equivalent Scales: An Alternative Approach.” American Journal of Agricultural Economics 60 (1978): 460–8.Google Scholar
Capps, O. Jr., and Schmitz, J.A Recognition of Health and Nutrition Factors in Demand Analysis.” Western Journal of Agricultural Economics 16 (1991): 2135.Google Scholar
Chavas, J.P., and Keplinger, K.O.Impact of Domestic Food Programs on Nutrient Intake of Low Income Persons in the United States.” Southern Journal of Agricultural Economics 15 (1983): 155–63.Google Scholar
Davis, C.G., and Neenan, P.H.The Impact of Food Stamps and Nutrition Education Programs on Food Groups Expenditure and Nutrient Intake of Low Income Households.” Southern Journal of Agricultural Economics 11 (1979): 121–9.Google Scholar
Devaney, B., and Fraker, T.The Dietary Impacts of the School Breakfast Program.” American Journal of Agricultural Economics 71 (1989): 932–48.Google Scholar
Devaney, B., and Moffitt, R.Dietary Effects of the Food Stamp Program.” American Journal of Agricultural Economics 73 (1991): 202–11.Google Scholar
Frazao, B., and Cleveland, L.Diet-Health Awareness about Fat and Cholesterol—Only a Start.” Food Review 17, 1 (1994): 1522.Google Scholar
Godfrey, L.G.Testing for Multiplicative Heteroscedasticity.” Journal of Econometrics 8 (1978): 227–36.CrossRefGoogle Scholar
Interagency Board for Nutrition Monitoring and Related Research, Nutrition Monitoring in the United States, eds. Ervin, B. and Reed, D., Hyattsville, Maryland, 1993.Google Scholar
Lane, S.Food Distribution and Food Stamp Program Effects on Nutritional Achievement of Low Income Persons in Kern County, California.” American Journal of Agricultural Economics 60 (1978): 108–16.Google Scholar
Lutz, S.M., Smallwood, D.M., Blaylock, J.R., and Hama, M.Y.Changes in Food Consumption and Expenditures in American Households during the 1980s.” U.S. Department of Agriculture Statistical Bulletin No. 849, Human Nutrition Information Service and Economic Research Service, Washington, DC, December 1992.Google Scholar
McCracken, V., and Brandt, J.Time Value and its Impact on Household Food Expenditures Away from Home.” Home Economics Research Journal 18 (1990): 267–85.CrossRefGoogle Scholar
Nayga, R.M. Jr. and Capps, O.Analysis of Away-from-Home and At-Home Intake of Saturated Fat and Cholesterol.” Review of Agricultural Economics 16 (1994): 429–40.CrossRefGoogle Scholar
Pindyck, R.S., and Rubinfeld, D.L. Econometric Models and Economic Forecasts, Third Edition, McGraw-Hill, 1991.Google Scholar
Price, D.W., West, D.A., Schier, G.E., and Price, D.Z.Food Delivery Programs and Other Factors Affecting Nutrient Intake of Children.” American Journal of Agricultural Economics 60 (1978): 609–18.CrossRefGoogle Scholar
Scearce, W.K., and Jensen, R.B.Food Stamp Program Effects on Availability of Food Nutrients for Low Income Families in the Southern Region of the United States.” Southern Journal of Agricultural Economics 11 (1979): 113–20.Google Scholar
Spencer, G.Population Estimates and Projections: 1988-2080,” Series P-25, No. 1018, U.S. Department of Commerce, Washington, D.C., 1989.Google Scholar
Windham, C., Wyse, B., Hansen, R., and Hurst, R.Nutrient Density of Diets in the USDA Nationwide Food Consumption Survey, 1977-78: Impact of Socioeconomic Status on Dietary Density.” Journal of the American Dietetic Association 82 (1983): 2834.CrossRefGoogle Scholar
Woodruff, C.W.Milk Intolerances,” In Present Knowledge of Nutrition, Hegsted, D.M., ed., 4th edition, New York, 1976.Google Scholar