Advertisement

Are Food and Beverage Purchases in Households with Preschoolers Changing?

A Longitudinal Analysis from 2000 to 2011

      Background

      U.S. dietary studies from 2003 to 2010 show decreases in children’s caloric intake. We examined purchases of consumer packaged foods/beverages in the U.S. between 2000 and 2011 among households with children aged 2–5 years.

      Purpose

      To describe changes in consumer packaged goods (CPG) purchases between 2000 and 2011 after adjusting for economic indicators, and explore differences by race, education, and household income level.

      Methods

      CPG purchase data were obtained for 42,753 U.S. households with one or more child aged 2–5 years using the Nielsen Homescan Panel. Top sources of purchased calories were grouped, and random effects regression was used to model the relationship between calories purchased from each group and race, female head of household education, and household income. Models adjusted for household composition, market-level unemployment rate, prices, and quarter, with Bonferroni correction for multiple comparisons (α=0.05).

      Results

      Between 2000 and 2011, adjusted total calories purchased from foods (–182 kcal/day) and beverages (–100 kcal/day) declined significantly. Decreases in purchases of milk (–40 kcal); soft drinks (–27 kcal/day); juice and juice drinks (–24 kcal/day); grain-based desserts (–24 kcal/day); savory snacks (–17 kcal/day); and sweet snacks and candy (–13 kcal/day) were among the major changes. Changes in CPG purchases differed significantly by race, female head of household education, and household income.

      Conclusions

      Trends in CPG purchases suggest that solid fats and added sugars are decreasing in the food supply of U.S. preschoolers. Pronounced differences by race, education, and household income persist.
      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to American Journal of Preventive Medicine
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Welsh J.A.
        • Sharma A.J.
        • Grellinger L.
        • Vos M.B.
        Consumption of added sugars is decreasing in the U.S.
        Am J Clin Nutr. 2011; 94: 726-734
        • Slining M.
        • Popkin B.
        Trends in intakes and sources of solid fats and added sugars among US children and adolescents: 1994–2010.
        Pediatr Obes. 2013; 8: 307-324
        • Kit B.K.
        • Carroll M.D.
        • Ogden C.L.
        Low-fat milk consumption among children and adolescents in the U.S., 2007-2008.
        NCHS Data Brief. 2011; 75: 1-8
        • Hiza H.A.
        • Casavale K.O.
        • Guenther P.M.
        • Davis C.A.
        Diet quality of Americans differs by age, sex, race/ethnicity, income, and education level.
        J Acad Nutr Diet. 2013; 113: 297-306
        • Johnson R.K.
        • Panely C.V.
        • Wang M.Q.
        Associations between the milk mothers drink and the milk consumed by their school-aged children.
        Fam Econ Nutr Rev. 2001; 13: 27
        • Dennison B.A.
        • Erb T.A.
        • Jenkins P.L.
        Predictors of dietary milk fat intake by preschool children.
        Prev Med. 2001; 33: 536-542
        • Popkin B.M.
        • Siega-Riz A.M.
        • Haines P.S.
        A comparison of dietary trends among racial and socioeconomic groups in the U.S.
        N Engl J Med. 1996; 335: 716-720
        • Andrews M.
        USDA Economic Research Service—More Americans relied on food assistance during recession. 2013;
        • Bagliano F.C.
        • Morana C.
        The Great Recession: U.S. dynamics and spillovers to the world economy.
        J Banking Finance. 2012; 36: 1-13
      1. The Nielsen Co. Nielsen retail measures. 2013; en-us.nielsen.com/.

        • Einav L.
        • Leibtag E.
        • Nevo A.
        On the accuracy of Nielsen Homescan data.
        Economic Research Service, USDA, Washington DC2008
        • Zhen C.
        • Taylor J.L.
        • Muth M.K.
        • Leibtag E.
        Understanding differences in self-reported expenditures between household scanner data and diary survey data: a comparison of Homescan and consumer expenditure survey.
        Appl Econ Persp Policy. 2009; 31: 470-492
        • Slining M.M.
        • Ng S.W.
        • Popkin B.M.
        Food companies׳ calorie-reduction pledges to improve U.S. diet.
        Am J Prev Med. 2013; 44: 174-184
      2. Bureau of Labor Statistics. Local area unemployment statistics [database on the Internet]. 2012. http://www.bls.gov/lau/.

        • Dave D.M.
        • Kelly I.R.
        How does the business cycle affect eating habits?.
        Soc Sci Med. 2012; 74: 254-262
        • Miller R.G.
        Simultaneous statistical inference.
        McGraw-Hill, New York1966
        • Reedy J.
        • Krebs-Smith S.M.
        Dietary sources of energy, solid fats, and added sugars among children and adolescents in the U.S.
        J Am Diet Assoc. 2010; 110: 1477-1484
        • Cullen K.
        • Baranowski T.
        • Watson K.
        • et al.
        Food category purchases vary by household education and race/ethnicity: results from grocery receipts.
        J Am Diet Assoc. 2007; 107: 1747-1752
        • Powell L.M.
        • Slater S.
        • Mirtcheva D.
        • Bao Y.
        • Chaloupka F.J.
        Food store availability and neighborhood characteristics in the U.S.
        Prev Med. 2007; 44: 189-195
        • Crawford P.B.
        • Obarzanek E.
        • Schreiber G.B.
        • et al.
        The effects of race, household income, and parental education on nutrient intakes of 9- and 10-year-old girls. NHLBI Growth and Health Study.
        Ann Epidemiol. 1995; 5: 360-368
        • Northstone K.
        • Emmett P.
        Multivariate analysis of diet in children at four and seven years of age and associations with socio-demographic characteristics.
        Eur J Clin Nutr. 2005; 59: 751-760
        • Hendricks K.
        • Briefel R.
        • Novak T.
        • Ziegler P.
        Maternal and child characteristics associated with infant and toddler feeding practices.
        J Am Diet Assoc. 2006; 106: S135-S148
        • Kant A.K.
        • Graubard B.I.
        Family income and education were related with 30-year time trends in dietary and meal behaviors of american children and adolescents.
        J Nutr. 2013; 143: 690-700
        • Kantor L.S.
        • Lipton K.
        • Manchester A.
        • Oliveira V.
        Estimating and addressing America’s food losses.
        Food Rev. 1997; 20: 2-12
        • Buzby J.C.
        • Hyman J.
        Total and per capita value of food loss in the U.S.
        Food Policy. 2012; 37: 561-570
        • Muth M.K.
        • Karns S.A.
        • Nielsen S.J.
        • Buzby J.C.
        • Wells H.F.
        Consumer-level food loss estimates and their use in the ERS loss-adjusted food availability data.
        Economic Research Service, USDA, Washington DC2011 (Technical Bulletin No.: TB-1927)
        • Poti J.M.
        • Popkin B.M.
        Trends in energy intake among U.S. children by eating location and food source, 1977-2006.
        J Am Diet Assoc. 2011; 111: 1156-1164
        • Lusk J.L.
        • Brooks K.
        Who Participates in Household Scanning Panels?.
        Am J Agric Econ. 2011; 93: 226-240