Maternal and Child Health Journal

, Volume 15, Issue 8, pp 1296–1307 | Cite as

Breastfeeding and the Child Cognitive Outcomes: A Propensity Score Matching Approach

  • Miao Jiang
  • E. Michael Foster
  • Christina M. Gibson-Davis
Article

Abstract

To estimate the effect of breastfeeding initiation and duration on child development outcomes. 3,271 children and their mothers participating in the Child Development Supplement of the Panel Study of Income Dynamics provide data for these analyses. Main outcomes include Woodcock Johnson Psycho-Educational Battery-Revised (WJ-R) test score (letter word, passage comprehension, applied problem, and broad reading), and Wechsler Intelligence Scale for Children-Revised (WISC-R) test score at the 2002 survey. Controlled variables include family, maternal, and child characteristics, many of which can be traced back to the year the child was born. The analytic technique is propensity score matching with multiple imputations. After using propensity scores to adjust for confounding factors, breastfeeding initiation showed statistically significant effects but the practical scale remains small. Breastfeeding duration showed a non-linear effect on those outcomes and most of the effects are not significant. The effects of breastfeeding on child’s cognitive outcomes are modest in practical terms. The non-linear effects suggest that selection into breastfeeding may account for the increased score of children who are breastfed.

Keywords

Breastfeeding Child cognitive outcomes Propensity score Multiple imputations Confounding Effect size 

Notes

Acknowledgments

This study was not funded by any governmental or non-governmental agency.

References

  1. 1.
    American Academy of Pediatrics. (2005). Breastfeeding and the use of human milk. Pediatrics, 115(2), 496–507.CrossRefGoogle Scholar
  2. 2.
    Uauy, R., & Peirano, P. (1999). Breast is best: Human milk is the optimal food for brain development. American Journal of Clinical Nutrition, 70, 433–434.PubMedGoogle Scholar
  3. 3.
    Oddy, W. H., Kendall, G. E., Blair, E., De Klerk, N. H., Stanley, F. J., Landau, L. I., et al. (2003). Breast feeding and cognitive development in childhood: A prospective birth cohort study. Paediatric and Perinatal Epidemiology, 17(1), 81–90.PubMedCrossRefGoogle Scholar
  4. 4.
    Angelsen, N. K., Vik, T., Jacobsen, G., & Bakketeig, L. S. (2001). Breast feeding and cognitive development at age 1 and 5 years. Archives of Disease in Childhood, 85(3), 183–188.PubMedCrossRefGoogle Scholar
  5. 5.
    Wigg, N. R., Tong, S., McMichael, A. J., Baghurst, P. A., Vimpani, G., & Roberts, R. (1998). Does breastfeeding at six months predict cognitive development? Australian and New Zealand Journal of Public Health, 22(2), 232–236.PubMedCrossRefGoogle Scholar
  6. 6.
    Lucas, A., Morley, R., Cole, T. J., Lister, G., & Leeson-Payne, C. (1992). Breast milk and subsequent intelligence quotient in children born preterm. Lancet (British edition), 339(8788), 261–264.Google Scholar
  7. 7.
    Gomez-Sanchiz, M., Canete, R., Rodero, I., Baeza, J. E., & Gonzalez, J. A. (2004). Influence of breast-feeding and parental intelligence on cognitive development in the 24-month-old child. Clinical Pediatrics, 43(8), 753–761.PubMedCrossRefGoogle Scholar
  8. 8.
    Carlson, S. E. (1999). Long-chain polyunsaturated fatty acids and development of human infants. Acta Paediatrica. Supplement, 88(430), 72–77.PubMedCrossRefGoogle Scholar
  9. 9.
    Rey, J. (2003). Breastfeeding and cognitive development. Acta Paediatrica, 92(8 supp 442), 11–18.Google Scholar
  10. 10.
    Koletzko, B., Agostoni, C., Carlson, S. E., Clandinin, T., Hornstra, G., Neuringer, M., et al. (2001). Long chain polyunsaturated fatty acids (LC-PUFA) and perinatal development. Acta Paediatrica, 90(4), 460–464.PubMedCrossRefGoogle Scholar
  11. 11.
    Lauritzen, L., Hansen, H. S., Jorgensen, M. H., & Michaelsen, K. F. (2001). The essentiality of long chain n-3 fatty acids in relation to development and function of the brain and retin. Progress in Lipid Research, 40(1–2), 1–94.PubMedCrossRefGoogle Scholar
  12. 12.
    McCann, J. C., & Ames, B. N. (2005). Is docosahexaenoic acid, an n-3 long-chain polyunsaturated fatty acid, required for development of normal brain function? An overview of evidence from cognitive and behavioral tests in humans and animals. American Journal of Clinical Nutrition, 82(2), 281–295.PubMedGoogle Scholar
  13. 13.
    Lucas, A., Stafford, M., Morley, R., Abbott, R., Stephenson, T., MacFadyen, U., et al. (1999). Efficacy and safety of long-chain polyunsaturated fatty acid supplementation of infant-formula milk: A randomised trial. Lancet, 354(91914), 1948–1954.PubMedCrossRefGoogle Scholar
  14. 14.
    Gustafsson, P. A., Duchen, K., Birberg, U., & Karlsson, T. (2004). Breastfeeding, very long polyunsaturated fatty acids (PUFA) and IQ at 6 1/2 years of age. Acta Paediatrica, 93(10), 1280–1287.PubMedCrossRefGoogle Scholar
  15. 15.
    Gomez-Sanchiz, M., Canete, R., Rodero, I., Baeza, J. E., & Avila, O. (2003). Influence of breast-feeding on mental and psychomotor development. Clinical Pediatrics, 42(1), 35–42.PubMedCrossRefGoogle Scholar
  16. 16.
    Rao, M. R., Hediger, M. L., Levine, R. J., Naficy, A. B., & Vik, T. (2002). Effect of breastfeeding on cognitive development of infants born small for gestational age. Acta Paediatrica, 91(3), 267–274.PubMedCrossRefGoogle Scholar
  17. 17.
    Quinn, P., O’Callaghan, M., GM, W., Najman, J., Andersen, M., & Bor, W. (2001). The effect of breastfeeding on child development at 5 years: A cohort study. Journal of Pediatrics & Child Health, 37(5), 465–469.CrossRefGoogle Scholar
  18. 18.
    Oddy, W. H., Kendall, G. E., Blair, E., De Klerk, N. H., Stanley, F. J., Landau, L. I., et al. (2003). Breast feeding and cognitive development in childhood: A prospective birth cohort study. Pediatric and Perinatal Epidemiology, 17(1), 81–90.PubMedCrossRefGoogle Scholar
  19. 19.
    Horwood, L. J., Darlow, B. A., & Mogridge, N. (2001). Breast milk feeding and cognitive ability at 7–8 years. Archives of Disease in Childhood. Fetal and Neonatal Edition, 84, f23–f27.PubMedCrossRefGoogle Scholar
  20. 20.
    Johnson, D. L., Swank, P. R., Howie, V. M., Baldwin, C. D., & Owen, M. (1996). Breast feeding and children’s intelligence. Psychological Reports, 79(3 Pt 2), 1179–1185.PubMedCrossRefGoogle Scholar
  21. 21.
    Anderson, J. W., Johnstone, B. M., & Remley, D. T. (1999). Breast-feeding and cognitive development: A meta-analysis. American Journal of Clinical Nutrition, 70(4), 525–535.PubMedGoogle Scholar
  22. 22.
    Reynolds, A. (2001). Breastfeeding and brain development. Pediatric Clinics of North America, 48(1), 159–171.PubMedCrossRefGoogle Scholar
  23. 23.
    Drane, D. L., & Logemann, J. A. (2000). A critical evaluation of the evidence on the association between type of infant feeding and cognitive development. Pediatric and Perinatal Epidemiology, 14(4), 349–356.PubMedCrossRefGoogle Scholar
  24. 24.
    Jacobson, S. W., Chiodo, L. M., & Jacobson, J. L. (1999). Breastfeeding effects on intelligence quotient in 4- and 11-year-old children. Pediatrics, 103, e71.PubMedCrossRefGoogle Scholar
  25. 25.
    Der, G., Batty, G. D., & Deary, I. J. (2006). Effect of breast feeding on intelligence in children: Prospective study, sibling pairs analysis, and meta-analysis. British Medical Journal, 333(7575), 945–950.PubMedCrossRefGoogle Scholar
  26. 26.
    Jain, A., Concato, J., & Leventhal, J. M. (2002). How good is the evidence linking breastfeeding and intelligence? Pediatrics, 109(6), 1044–1053.PubMedCrossRefGoogle Scholar
  27. 27.
    Greene, L. C., Lucas, A., Livingstone, M. B., Harland, P. S., & Baker, B. A. (1995). Relationship between early diet and subsequent cognitive performance during adolescence. Biochemical Society Transactions, 23(2), 376S.PubMedGoogle Scholar
  28. 28.
    Horwood, L. J., & Fergusson, D. M. (1998). Breastfeeding and later cognitive and academic outcomes. Pediatrics, 101(1), e9.PubMedCrossRefGoogle Scholar
  29. 29.
    Mortensen, E., Michaelsen, K., Sanders, S., & Reinisch, J. (2002). The association between duration of breastfeeding and adult intelligence. The Journal of the American Medical Association, 287(18), 2365–2371.CrossRefGoogle Scholar
  30. 30.
    Rogan, W. J., & Gladen, B. C. (1993). Breast-feeding and cognitive development. Early Human Development, 31(3), 181–193.PubMedCrossRefGoogle Scholar
  31. 31.
    Smith, M. M., Durkin, M., Hinton, V. J., Bellinger, D., & Kuhn, L. (2003). Influence of breastfeeding on cognitive outcomes at age 6–8 years: Follow-up of very low birth weight infants. American Journal of Epidemiology, 158(11), 1075–1082.PubMedCrossRefGoogle Scholar
  32. 32.
    Hernan, M. A., Hernandez-Diaz, S., & Robins, J. M. (2004). A structural approach to selection bias. Epidemiology, 15(5), 615–625.PubMedCrossRefGoogle Scholar
  33. 33.
    Greenland, S. (2003). Quantifying biases in causal models: Classical confounding vs collider-stratification bias. Epidemiology, 14(3), 300–306.PubMedGoogle Scholar
  34. 34.
    Pearl, J. (2009). Causality: Models, reasoning, and inference (2nd ed.). Cambridge, U.K.: Cambridge University Press.Google Scholar
  35. 35.
    McGonagle, K. A., & Schoeni, R. F. (2006). The panel study of income dynamics: overview & summary of scientific contributions after nearly 40 years. Retrieved May 21, 2007, from http://www.psidonline.isr.umich.edu/Publications/Papers/montreal.pdf.
  36. 36.
    Duncan, G. J., & Brooks-Gunn, J. (1997). Consequences of growing up poor. New York: Russell Sage Foundation.Google Scholar
  37. 37.
    PSID Data Center. CDS frequently asked questions. Retrieved May 21, 2007, from http://psidonline.isr.umich.edu/CDS/faq.aspx.
  38. 38.
    Woodcock, R. W. (1989). Woodcock–Johnson tests of achievement–Revised. Allen, TX: DLM Teaching Resources.Google Scholar
  39. 39.
    Mainieri, T. (2006). The panel study of income dynamics child development supplement: User guide for CDS-II. Retrieved December 5, 2009, from http://psidonline.isr.umich.edu/CDS/cdsii_userGd.pdf.
  40. 40.
    Wechsler, D. (1974). Wechsler intelligence scale for children-revised. New York, NY: The Psychological Corporation.Google Scholar
  41. 41.
    Alexander, G. R., Himes, J. H., Kaufman, R. B., Mor, J., & Kogan, M. (1996). A United States national reference for fetal growth. Obstetrics and Gynecology, 87(2), 163–168.PubMedCrossRefGoogle Scholar
  42. 42.
    Caldwell, B. M., & Bradley, R. H. (1984). Home observation for measurement of the environment. Little Rock: University of Arkansas.Google Scholar
  43. 43.
    Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55.CrossRefGoogle Scholar
  44. 44.
    Heckman, J. J., Ichimura, H., & Todd, P. (1998). Matching as an econometric evaluation estimator. The Review of Economic Studies, 65(2), 261–294.CrossRefGoogle Scholar
  45. 45.
    Blundell, R., Dearden, L., & Sianesi, B. (2005). Evaluating the effect of education on earnings: models, methods and results from the National Child Development Survey. Journal of the Royal Statistical Society: Series A (Statistics in Society), 168(3), 473–512.CrossRefGoogle Scholar
  46. 46.
    Lee, M. (2005). Micro-econometrics for policy, program, and treatment effects. New York: Oxford University Press.CrossRefGoogle Scholar
  47. 47.
    Rosenbaum, P. R. (2002). Observational studies. New York: Springer.Google Scholar
  48. 48.
    Winship, C., & Morgan, S. L. (1999). The estimation of causal effects from observational data. Annual Review of Sociology, 25(1), 659–707.CrossRefGoogle Scholar
  49. 49.
    Gibson-Davis, C. M., & Brooks-Gunn, J. (2006). Breastfeeding and verbal ability of 3-year-olds in a multicity sample. Pediatrics, 118(5), e1444–e1451.PubMedCrossRefGoogle Scholar
  50. 50.
    Morgan, S. L., & Winship, C. (2007). Counterfactuals and causal inference: Methods and principles for social research. New York: Cambridge University Press.Google Scholar
  51. 51.
    Heckman, J. J., & Navarro-Lozano, S. (2004). Using matching, instrumental variables, and control functions to estimate economic choice models. Review of Economics and Statistics, 86(1), 30–57.CrossRefGoogle Scholar
  52. 52.
    Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
  53. 53.
    Imbens, G. W. (2000). The role of the propensity score in estimating dose-response functions. Biometrika, 87(3), 706–710.CrossRefGoogle Scholar
  54. 54.
    Rosenbaum, P. R. (1987). Model-based direct adjustment. Journal of the American Statistical Association, 82(398), 387–394.CrossRefGoogle Scholar
  55. 55.
    Horvitz, D. G., & Thompson, D. J. (1952). A Generalization of sampling without replacement from a finite universe. Journal of the American Statistical Association, 47(260), 663–685.CrossRefGoogle Scholar
  56. 56.
    Veroff, J., McClelland, L., & Marquis, K. (1971). Measuring intelligence and achievement motivation in surveys: Final report to HEW. OEO.Google Scholar
  57. 57.
    Rubin, D. B. (1987). Multiple imputation for nonresponse in surveys. New York: Wiley.CrossRefGoogle Scholar
  58. 58.
    Leuven, E., & Sianesi, B. (2003). PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing. Version 3.0.0. Retrieved April 7, 2009, from http://ideas.repec.org/c/boc/bocode/s432001.html.
  59. 59.
    Royston, P. (2005). Multiple imputation of missing values: Update of ICE. Stata Journal, 5(4), 527–536.Google Scholar
  60. 60.
    Stata statistical software: Release 10 [program]. (2007). College Station, TX.Google Scholar
  61. 61.
    Brooks-Gunn, J., Duncan, G. J., & Maritato, N. (1997). Poor families, poor outcomes: The well-being of children and youth. In J. Brooks-Gunn & G. J. Duncan (Eds.), The consequences of growing up poor (pp. 1–17). New York: Russell Sage.Google Scholar
  62. 62.
    Greene, W. H. (2008). Econometric analysis (6th ed.). Upper Saddle River, N.J.: Prentice Hall.Google Scholar
  63. 63.
    Morrow-Tlucak, M., Haude, R. H., & Ernhart, C. B. (1988). Breastfeeding and cognitive development in the first 2 years of life. Social Science and Medicine, 26(6), 635–639.PubMedCrossRefGoogle Scholar
  64. 64.
    Rey, J. (2003). Breastfeeding and cognitive development. Acta Pediatric Supplement, 442(Suppl), 11–18.Google Scholar
  65. 65.
    National Center for Health Statistics. (1996). NHANES III reference manual and reports [CD-ROM]. Hyattsville, MD: Centers for Disease Control and Prevention.Google Scholar
  66. 66.
    Li, R., Ogden, C., Ballew, C., Gillespie, C., & Grummer-Strawn, L. (2002). Prevalence of exclusive breastfeeding among US infants: The Third National Health and Nutrition Examination Survey (phase II, 1991–1994). American Journal of Public Health, 92(7), 1107.PubMedCrossRefGoogle Scholar
  67. 67.
    Gdalevich, M., Mimouni, D., David, M., & Mimouni, M. (2001). Breast-feeding and the onset of atopic dermatitis in childhood: A systematic review and meta-analysis of prospective studies. Journal of the American Academy of Dermatology, 45(4), 520–527.PubMedCrossRefGoogle Scholar
  68. 68.
    Oddy, W. H., Holt, P. G., Sly, P. D., Read, A. W., Landau, L. I., Stanley, F. J., et al. (1999). Association between breast feeding and asthma in 6 year old children: Findings of a prospective birth cohort study. British Medical Journal, 319(7213), 815–819.PubMedGoogle Scholar
  69. 69.
    Centers for Disease Control and Prevention. (2004). Any and exclusive breastfeeding rates by age among children born in 2004. Retrieved January 3, 2008, from http://www.cdc.gov/breastfeeding/data/nis_data/data_2004.htm.
  70. 70.
    Manski, C. F. (2007). Identification for prediction and decision. Cambridge, Mass: Harvard University Press.Google Scholar
  71. 71.
    Cook, T. D., Shadish, W. R., & Wong, V. C. (2008). Three conditions under which experiments and observational studies produce comparable causal estimates: New findings from within-study comparisons. Journal of Policy Analysis and Management, 27(4), 724–750.CrossRefGoogle Scholar
  72. 72.
    Steiner, P. M., Cook, T. D., Shadish, W. R., & Clark, M. H. (2009). The importance of covariate selection in controlling for selection bias in observational studies.Google Scholar
  73. 73.
    Shakespeare, J., Blake, F., & Garcia, J. (2004). Breast-feeding difficulties experienced by women taking part in a qualitative interview study of postnatal depression. Midwifery, 20(3), 251–260.PubMedCrossRefGoogle Scholar
  74. 74.
    Sibolboro Mezzacappa, E., & Endicott, J. (2007). Parity mediates the association between infant feeding method and maternal depressive symptoms in the postpartum. Archives of Women’s Mental Health, 10(6), 259–266.PubMedCrossRefGoogle Scholar
  75. 75.
    Carson, C. (2004). Breastfeeding: Barriers and breakthroughs. RCM Midwives Journal, 7(5), 192.PubMedGoogle Scholar
  76. 76.
    Julvez, J., Ribas-Fito, N., Torrent, M., Forns, M., Garcia-Esteban, R., & Sunyer, J. (2007). Maternal smoking habits and cognitive development of children at age 4 years in a population-based birth cohort. International Journal of Epidemiology, 36(4), 825–832.PubMedCrossRefGoogle Scholar
  77. 77.
    Hack, M., Flannery, D. J., Schluchter, M., Cartar, L., Borawski, E., & Klein, N. (2002). Outcomes in young adulthood for very-low-birth-weight infants. The New England Journal of Medicine, 346(3), 149.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Miao Jiang
    • 1
  • E. Michael Foster
    • 1
  • Christina M. Gibson-Davis
    • 2
  1. 1.Department of Maternal and Child HealthUniversity of North Carolina-Chapel HillChapel HillUSA
  2. 2.Terry Sanford Institute of Public PolicyDuke UniversityDurhamUSA

Personalised recommendations