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Dietary patterns at 6, 15 and 24 months of age are associated with IQ at 8 years of age


Diet supplies the nutrients needed for the development of neural tissues that occurs over the first 2 years of life. Our aim was to examine associations between dietary patterns at 6, 15 and 24 months and intelligence quotient (IQ) scores at 8 years. Participants were enrolled in an observational birth cohort (ALSPAC study, n = 7,097). Dietary data was collected by questionnaire and patterns were extracted at each time using principal component analysis. IQ was measured using the Wechsler Intelligence Scale for Children at 8 years. Associations between dietary patterns and IQ were examined in regression analyses adjusted for potential confounding and by propensity score matching, with data imputation for missing values. At all ages, higher scores on a Discretionary pattern (characterized by biscuits, chocolate, sweets, soda, crisps) were associated with 1–2 point lower IQ. A Breastfeeding pattern at 6 months and Home-made contemporary patterns at 15 and 24 months (herbs, legumes, cheese, raw fruit and vegetables) were associated with 1-to-2 point higher IQ. A Home-made traditional pattern (meat, cooked vegetables, desserts) at 6 months was positively associated with higher IQ scores, but there was no association with similar patterns at 15 or 24 months. Negative associations were found with patterns characterized by Ready-prepared baby foods at 6 and 15 months and positive associations with a Ready-to-eat foods pattern at 24 months. Propensity score analyses were consistent with regression analyses. This study suggests that dietary patterns from 6 to 24 months may have a small but persistent effect on IQ at 8 years.

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Fig. 1



Avon longitudinal study of parents and children


Certificate of secondary education


Full scale intelligence quotient




Intelligence quotient


Principal component analysis


Performance intelligence quotient




Verbal intelligence quotient


Wechsler intelligence scale for children


  1. Kramer MS, Aboud F, Mironova E, Vanilovich I, Platt RW, Matush L, et al. Breastfeeding and child cognitive development. Arch Gen Psychiatr. 2008;65(5):578–84.

    Article  PubMed  Google Scholar 

  2. Brion M-JA, Lawlor DA, Matijasevich A, Horta B, Anselmi L, Araújo CL, et al. What are the causal effects of breastfeeding on IQ, obesity and blood pressure? Evidence from comparing high-income with middle-income cohorts. Int J Epidemiol. 2011;. doi:10.1093/ije/dyr020.

    PubMed  Google Scholar 

  3. McCann JC, Ames BN. An overview of evidence for a causal relation between iron deficiency during development and deficits in cognitive or behavioral function. Am J Clin Nutr. 2007;82(4):931–45.

    Google Scholar 

  4. Birch E, Garfield S, Hoffman DR, Uauy R, Birch D. A randomized controlled trial of early dietary supply of long-chain polyunsaturated fatty acids and mental development in term infants. Dev Med Child Neurol. 2000;42:174–81.

    Article  PubMed  CAS  Google Scholar 

  5. Gordon RC, Rose MC, Skeaff SA, Gray AR, Morgan KM, Ruffman T. Iodine supplementation improves cognition in mildly iodine-deficient children. Am J Clin Nutr. 2009;90(5):1264–71.

    Article  PubMed  CAS  Google Scholar 

  6. Smithers LG, Golley R, Brazionis L, Lynch JW. Characterizing whole diets of young children from developed countries and the association between diet and health: a systematic review. Nutr Rev. 2011;69(8):449–67.

    Article  PubMed  Google Scholar 

  7. Gale CR, Martyn CN, Marriott LD, Limond J, Crozier S, Inskip HM, et al. Dietary patterns in infancy and cognitive and neuropsychological function in childhood. J Child Psychol Psychiatr. 2009;50(7):816–23.

    Article  Google Scholar 

  8. Northstone K, Joinson C, Emmett P, Ness A, Paus T. Are dietary patterns in childhood associated with IQ at 8 years of age? A population-based cohort study. J Epidemiol Community Health. 2011;. doi:10.1136/jech.2010.111955.

    PubMed  Google Scholar 

  9. Smithers LG, Brazionis L, Golley RK, Mittinty MN, Northsone K, Emett P, McNaughton SA, Campbell KJ, Lynch JW. Dietary patterns at 6 and 15 months of age and socio-demographic factors. Eur J Clin Nutr. 2012;. doi:10.1038/ejcn.2011.219.

    PubMed  Google Scholar 

  10. Golding J, the ALSPAC Study Team. Children of the Nineties: a resource for assessing the magnitude of long-term effects of prenatal, perinatal and subsequent events. Contemp Rev Obstet Gynaecol. 1996;8:89–92.

    Google Scholar 

  11. Wechsler D. The Wechsler intelligence scale for children. 3rd ed. San Antonio: The Psychological Corporation; 1991.

    Google Scholar 

  12. Office of Population Censuses & Surveys. Standard occupational classification. London: Her Majesty’s Stationery Office; 1991.

    Google Scholar 

  13. Caldwell BM, Bradley RH. Home observation for measurement of the environment. Little Rock: University of Arkansas; 1979.

    Google Scholar 

  14. Sterne JA, White IR, Carlin JB, Spratt M, Royston P, Kenward MG, et al. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. Br Med J. 2009;29(338):b2393.

    Article  Google Scholar 

  15. Rubin DB. Inference and missing data. Biometrika. 1976;63(3):581–92.

    Article  Google Scholar 

  16. Royston P. Multiple imputation of missing values. STATA J. 2004;4(3):227–41.

    Google Scholar 

  17. Little RJA, Rubin DB. Bayes and multiple imputation. Statistical analysis with missing data. 2nd ed. Hoboken: Wiley; 2002. p. 200–22.

  18. D’Agostino RB. Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group. Stat Med. 1998;17(19):2265–81.

    Article  PubMed  Google Scholar 

  19. Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70(1):44–55.

    Article  Google Scholar 

  20. Rosenbaum PR, Rubin DB. Constructing a control group using multivariate matched sampling incorporating the propensity score. Am Stat. 1985;39:33–8.

    Google Scholar 

  21. Austin PC. Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies. Pharm Stat. 2010;10:150–61.

    Article  Google Scholar 

  22. Northstone K, Emmett P. Are dietary patterns stable throughout early and mid-childhood? A birth cohort study. Br J Nutr. 2008;100:1069–76.

    Article  PubMed  CAS  Google Scholar 

  23. Mikkila V, Rasanen L, Raitakari OT, Pietinen P, Viikari J. Consistent dietary patterns identified from childhood to adulthood: the cardiovascular risk in young finns study. Br J Nutr. 2005;93(6):923–31.

    Article  PubMed  CAS  Google Scholar 

  24. Robinson S, Marriott L, Poole J, Crozier S, Borland S, Lawrence W, et al. Dietary patterns in infancy: the importance of maternal and family influences on feeding practice. Br J Nutr. 2007;98(05):1029–37.

    Article  PubMed  CAS  Google Scholar 

  25. Jiang M, Foster EM, Gibson-Davis CM. Breastfeeding and the child cognitive outcomes: a propensity score matching approach. Matern Child Health J. 2010;15(8):1296–307.

    Article  Google Scholar 

  26. Iacovou M, Sanz AS. Children’s cognitive development: does breastfeeding really make a difference. Longit Life Course Stud. 2010;1(3):89.

    Google Scholar 

  27. North K, Emmet P, Avon Longitudinal Study of Pregnancy and Childhood (ALSPAC) Study Team. Multivariate analysis of diet a month three-year-old children and associations with socio-demographic characteristics. Eur J Clin Nutr. 2000;54:73–80.

    Article  PubMed  CAS  Google Scholar 

  28. Der G, Batty GD, Deary IJ. Effect of breast feeding on intelligence in children: prospective study, sibling pairs analysis, and meta-analysis. Br Med J. 2006;333(7575):945.

    Article  Google Scholar 

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We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. The UK Medical Research Council, the Wellcome Trust (Grant ref: 092731) and the University of Bristol provide core support for the ALSPAC study. JWL is supported by an Australia Fellowship (570120) and RKG with a Postdoctoral Training Fellowship (478115) from the National Health and Medical Research Council of Australia. LGS, LB and MNM are supported by funds from the Australia Fellowship awarded to JWL. KN and PE are partly supported by funding from European Community’s Seventh Framework Programme (245012).

Conflict of interest

PE and KN have both received support from commercial infant food manufacturers and undertaken invited lectures. The other authors have no conflicts of interest to declare.

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Correspondence to Lisa G. Smithers.

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Smithers, L.G., Golley, R.K., Mittinty, M.N. et al. Dietary patterns at 6, 15 and 24 months of age are associated with IQ at 8 years of age. Eur J Epidemiol 27, 525–535 (2012).

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  • Dietary patterns
  • Infant
  • Toddler
  • Intelligence quotient