Journal of Consumer Policy

, Volume 36, Issue 4, pp 403–423 | Cite as

Gender-Driven Food Choice: Explaining School Milk Consumption of Boys and Girls

  • Daniela Weible
Original Paper


The literature on the factors influencing children’s consumption behaviour is vast; however, gender-specific consumption behaviour and the determinants driving these discriminative decisions are largely unknown. This article contributes insights to the role of gender in food preferences using the example of school milk consumption by German primary school children. Study subjects included pupils, their parents, teachers, and other school personnel. The results of the multilevel model reveal that there are various factors influencing the probability that a child will decide to order school milk. In addition to individual factors such as socio-economics, eating habits, and preferences, consumption behaviour is also affected by social environmental factors. These factors include the preferences of parents, the consumption behaviour of teachers, teachers’ attitudes, and the attitude of the school principal. Additionally, policy-driven aspects (e.g., school milk price, product range) were included in the analysis and proved to have an impact on a child’s decision to order school milk. Although the results are limited to consumption behaviour for school milk, they can be used in the development of new or the revision of existing school food programmes. The example of school milk may shed light on how specific measures affect boys’ and girls’ consumption, e.g., how they react to price reductions or specific school settings.


Consumption behaviour Children Gender differences School environment Multilevel analysis School milk 


  1. Addessi, E., Galloway, A. T., Visalberghi, E., & Birch, L. L. (2005). Specific social influences on the acceptance of novel foods in 2–5-year-old children. Appetite, 45(3), 264–71.CrossRefGoogle Scholar
  2. Bickel, R. (2007). Multilevel analysis for applied research: it’s just regression. New York: The Guilford Press.Google Scholar
  3. Biesalski, H. K., Fuerst, P., Kasper, H., Kluthe, R., Poelert, W., Puchstein, C., et al. (1999). Ernährungsmedizin. Stuttgart: Thieme.Google Scholar
  4. Birch, L. L. (1979). Preschool children’s food preferences and consumption patterns. J Nutr Educ, 11(4), 189–92.CrossRefGoogle Scholar
  5. Birch, L. L., & Davison, K. K. (2001). Family environmental factors influencing the developing behavioral controls of food intake and childhood overweight. Pediatr Clin N Am, 48(4), 893–907.CrossRefGoogle Scholar
  6. BMELF. Schulmilch-Beihilfen-Verordnung vom 8. November 1985. Bundesministerium für Ernährung, Landwirtschaft und Forsten; 1985.Google Scholar
  7. Christoph-Schulz I, Buergelt D, Peter G, Salamon P, Weible D. The small difference: How does gender affect preference for school milk? In Gasiorowska A, Zaleskiewicz T, Microcosm of Economic Psychology, Warsaw School of Social Sciences and Humanities, Faculty in Wroclaw, ISBN 978-83-935288-1-3; 2012Google Scholar
  8. Crockett, S. J., & Sims, L. S. (1995). Environmental influences on children’s eating. J Nutr Educ, 27(5), 235–49.CrossRefGoogle Scholar
  9. DGE. (2008). Ernährungsbericht. Bonn: Deutsche Gesellschaft für Ernährung.Google Scholar
  10. EC. (2007). Establishing a common organisation of agricultural markets and on specific provisions for certain agricultural products (Regulation No. 1234/2007). Brussels: European Commission.Google Scholar
  11. EC. (2008). Regulations laying down detailed rules for applying Council Regulation No. 1234/2007 as regards community aid for supplying milk and certain milk products to pupils in educational establishments (Regulation No. 657/2008). Brussels: European Commission.Google Scholar
  12. EC. (2010). Strategy for Europe on nutrition, overweight and obesity related health issues. Implementation progress report, December 2010. Brussels: European Commission.Google Scholar
  13. Golan, M., & Crow, S. (2004). Parents are key players in the prevention and treatment of weight-related problems. Nutr Rev, 62(1), 39–50.CrossRefGoogle Scholar
  14. Heck, R. H., & Thomas, S. L. (2009). An introduction to multilevel modeling techniques. New York: Routledge.Google Scholar
  15. Hendy, H. (1999). Comparison of five teacher actions to encourage children’s new food acceptance. Ann Behav Med, 21(1), 20–6.CrossRefGoogle Scholar
  16. Hendy, H. M. (2002). Effectiveness of trained peer models to encourage food acceptance in preschool children. Appetite, 39(3), 217–25.CrossRefGoogle Scholar
  17. Hendy, H. M., & Raudenbush, B. (2000). Effectiveness of teacher modeling to encourage food acceptance in preschool children. Appetite, 34(1), 61–76.CrossRefGoogle Scholar
  18. Holsten, J. E., Deatrick, J. A., Kumanyika, S., Pinto-Martin, J., & Compher, C. W. (2012). Children’s food choice process in the home environment. A qualitative descriptive study. Appetite, 58(1), 64–73.CrossRefGoogle Scholar
  19. Hox, J. (2002). Multilevel analysis: techniques and applications. Mahwah: Lawrence Erlbaum Associate.Google Scholar
  20. Jensen, K. O., & Holm, L. (1999). Preferences, quantities and concerns: socio-cultural perspectives on the gendered consumption of foods. Eur J Clin Nutr, 53(5), 351–9.CrossRefGoogle Scholar
  21. Kelder, S. H., Perry, C. L., Klepp, K. I., & Lytle, L. L. (1994). Longitudinal tracking of adolescent smoking, physical activity, and food choice behaviors. Am J Publ Health, 84(7), 1121–6.CrossRefGoogle Scholar
  22. Kemm, J. R. (1987). Eating patterns in childhood and adult health. Nutr Heal, 4(4), 205–15.CrossRefGoogle Scholar
  23. Koehler, J., & Leonhaeuser, I.-U. (2008). Changes in food preferences during aging. Ann Nutr Metab, 52, 15–9.CrossRefGoogle Scholar
  24. Larson, N. I., Neumark-Sztainer, D., Harnack, L., Wall, M., Story, M., & Eisenberg, M. E. (2009). Calcium and dairy intake: longitudinal trends during the transition to young adulthood and correlates of calcium intake. J Nutr Educ Behav, 41(4), 254–60.CrossRefGoogle Scholar
  25. Lien, N., Lytle, L. A., & Klepp, K.-I. (2001). Stability in consumption of fruit, vegetables, and sugary foods in a cohort from age 14 to age 21. Prev Med, 33(3), 217–26.CrossRefGoogle Scholar
  26. Maes, L., & Lievens, J. (2003). Can the school make a difference? A multilevel analysis of adolescent risk and health behaviour. Soc Sci Med, 56(3), 517–29.CrossRefGoogle Scholar
  27. Mensink, G. B., Richter, A., Vohmann, C., Stahl, A., Six, J., Kohler, S., et al. (2007). EsKiMo-Das Ernährungsmodul des Kinder-und Jugendgesundheitssurveys (KiGGS). Neu-Isenburg: Springer Gesundheits- und Pharmazieverlag.Google Scholar
  28. MRI. (2011). Ergebnisbericht - Einflussfaktoren auf die Nachfrage nach Schulmilch in Grundschulen in Nordrhein-Westfalen. Karlsruhe: Max Rubner-Institut. ( Accessed 16 May 2013.
  29. Nicklas, T. A., Baranowski, T., Baranowski, J. C., Cullen, K., Rittenberry, L., & Olvera, N. (2001). Family and child-care provider influences on preschool children’s fruit, juice, and vegetable consumption. Nutr Rev, 59(7), 224–35.CrossRefGoogle Scholar
  30. Nu, C. T., MacLeod, P., & Barthelemy, J. (1996). Effects of age and gender on adolescents’ food habits and preferences. Food Qual Prefer, 7(3–4), 251–62.CrossRefGoogle Scholar
  31. Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: applications and data analysis methods. Thousand Oaks: Sage Publications.Google Scholar
  32. Reinaerts, E., de Nooijer, J., Candel, M., & de Vries, N. (2007). Explaining school children’s fruit and vegetable consumption: the contributions of availability, accessibility, exposure, parental consumption and habit in addition to psychosocial factors. Appetite, 48(2), 248–58.CrossRefGoogle Scholar
  33. Reisch, L. A., & Gwozdz, W. (2010). The impact of consumer behavior on the development of overweight in children. An overview. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz, 53(7), 725–32.CrossRefGoogle Scholar
  34. Robinson, J. S. (1978). Special milk program evaluation and national school lunch program survey. Washington, DC: U.S. Department of Agriculture, Food and Nutrition Service.Google Scholar
  35. Roos, E., Lehto, R., & Ray, C. (2012). Parental family food choice motives and children’s food intake. Food Qual Prefer, 24(1), 85–91.CrossRefGoogle Scholar
  36. Salamon, P., Pfau, C., Grillenberger, M., Christoph, I. B., Straßburg, A., Weber, S. A., et al. (2010). School milk demand: design and first results of the German federal research project “Focus on school milk”. vTI Agric For Res, 60(1), 1–10.Google Scholar
  37. Salvy, S.-J., de la Haye, K., Bowker, J. C., & Hermans, R. C. J. (2012). Influence of peers and friends on children’s and adolescents’ eating and activity behaviors. Physiol Behav, 106(3), 369–78.CrossRefGoogle Scholar
  38. Salvy, S.-J., & Pliner, P. P. (2010). Chapter 50—Social influences on eating in children and adults. In D. Laurette, B. Antoine, D. Alain, D. Adam, L. Jordan, J. Philip, & Y. Y. Rickey (Eds.), Obesity prevention (pp. 617–27). San Diego: Academic Press.CrossRefGoogle Scholar
  39. Salvy, S.-J., Vartanian, L. R., Coelho, J. S., Jarrin, D., & Pliner, P. P. (2008). The role of familiarity on modeling of eating and food consumption in children. Appetite, 50(2–3), 514–8.CrossRefGoogle Scholar
  40. Snijders, T. A. B., & Bosker, R. J. (2003). Multilevel analysis: an introduction to basic and advanced multilevel modeling. London: Sage.Google Scholar
  41. Story, M., Neumark-Sztainer, D., & French, S. (2002). Individual and environmental influences on adolescent eating behaviors. J Am Diet Assoc, 102(3, Supplement), 40–51.CrossRefGoogle Scholar
  42. Sweeting, H. (2008). Gendered dimensions of obesity in childhood and adolescence. Nutr J, 7(1), 1–14.CrossRefGoogle Scholar
  43. Vereecken, C., Huybrechts, I., Maes, L., & De Henauw, S. (2008). Food consumption among preschoolers. Does the school make a difference? Appetite, 51(3), 723–6.CrossRefGoogle Scholar
  44. Vereecken, C. A., Van Damme, W., & Maes, L. (2005). Measuring attitudes, self-efficacy, and social and environmental influences on fruit and vegetable consumption of 11- and 12-year-old children: reliability and validity. J Am Diet Assoc, 105(2), 257–61.CrossRefGoogle Scholar
  45. vTI. (2011). Endbericht–Ökonomische Begleitforschung zum Bundesmodellvorhaben “Schulmilch im Fokus”, Projekt des BMELV. Braunschweig: Johann Heinrich von Thünen-Institut. ( Accessed 16 May 2013.
  46. Weber Cullen, K., Baranowski, T., Rittenberry, L., Cosart, C., Hebert, D., & Moor, C. (2001). Child-reported family and peer influences on fruit, juice and vegetable consumption: reliability and validity of measures. Heal Educ Res, 16(2), 187–200.CrossRefGoogle Scholar
  47. Weible D., Buergelt D., Christoph I. B., Peter G., Rothe A., Salamon P., Weber S. A. School milk demand in Germany: individual as well as contextual factors play a major role—preliminary results. Selected paper prepared for presentation at the EAAE 2011 Congress “Change and Uncertainty; challenges for agriculture, food and national resources”, Zurich, Switzerland; 2011Google Scholar
  48. Weindlmaier, H., & Fallscheer, T. (1997). Schulmilchversorgung in Deutschland: Situation, Problembereiche, Ansatzpunkte für eine Erhöhung des Distributionsgrades. Special Publication of the Trade Association for Carton Packaging of Liquid Foodstuffs (FKN). Wiesbaden.Google Scholar
  49. WHO. (2012a). Regional Office for Europe. The double burden of nutritional diseases—a global challenge. Geneva: World Health Organisation.Google Scholar
  50. WHO. (2012b). Regional Office for Europe. European Childhood Obesity Surveillance Initiative (COSI). Geneva: World Health Organisation.Google Scholar
  51. Wind, M., de Bourdeaudhuij, I., te Velde, S. J., Sandvik, C., Due, P., Klepp, K. I., et al. (2006). Correlates of fruit and vegetable consumption among 11-year-old Belgian-Flemish and Dutch schoolchildren. J Nutr Educ Behav, 38(4), 211–21.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Thünen Institute of Market AnalysisFederal Research Institute for Rural Areas, Forestry and FisheriesBraunschweigGermany

Personalised recommendations