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PRE- AND POSTNATAL DRIVERS OF CHILDHOOD INTELLIGENCE: EVIDENCE FROM SINGAPORE

Published online by Cambridge University Press:  19 April 2012

GAIL PACHECO ,
MARY HEDGES ,
CHRIS SCHILLING  and
SUSAN MORTON
GAIL PACHECO
Affiliation:
Department of Economics, Auckland University of Technology, Auckland, New Zealand
MARY HEDGES
Affiliation:
Department of Economics, University of Auckland, Auckland, New Zealand
CHRIS SCHILLING
Affiliation:
New Zealand Institute of Economic Research, Wellington, NZ
SUSAN MORTON
Affiliation:
School of Population Health, University of Auckland, Auckland, New Zealand
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Summary

This study seeks to investigate what influences intelligence in early childhood. The Singapore Cohort Study of the Risk Factors of Myopia (SCORM) is used to assess determinants of childhood IQ and changes in IQ. This longitudinal data set, collected in 1999, includes a wealth of demographic, socioeconomic and prenatal characteristics. The richness of the data allows various econometric approaches to be employed, including the use of ordered and multinomial logit analysis. Mother's education is found to be a consistent and key determinant of childhood IQ. Father's education and school quality are found to be key drivers for increasing IQ levels above the average sample movement.

Type
Research Article
Information
Journal of Biosocial Science , Volume 45 , Issue 1 , January 2013 , pp. 41 - 56
Copyright
Copyright © Cambridge University Press 2012

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References

Alderman, H. & Behrman, J. (2004) Estimated economic benefits of reducing low birth weight in low-income countries. Health, Nutrition and Population discussion paper No. 35548, 34. URL: http://www-wds.worldbank.org/external/default/WDSContentServer/WDSP/IB/2006/03/27/000090341_20060327091428/Rendered/PDF/355480HNP0Alde1LowBirthWeight1whole.pdfGoogle Scholar
Batty, G. D., Clark, H., Morton, S. M. B., MacIntyre, S. & Leon, D. A. (2002) Intelligence in childhood and mortality, migration, questionnaire reponse rate, and self-reported morbidity and risk factor levels in adulthood: preliminary findings from the Aberdeen children of the 1950s' study. Journal of Epidemiology and Community Health 56 (Supplement 2), A1.Google Scholar
Batty, G. D. & Deary, I. J. (2004) Early life intelligence and adult health. Emerging associations, plausible mechanisms, and public health importance. British Medical Journal 329(7466), 585–586.CrossRefGoogle Scholar
Batty, G. D., Deary, I. J. et al. (2007) Premorbid (early life) IQ and later mortality risk: systematic review. Annals of Epidemiology 17(4), 278–288.CrossRefGoogle ScholarPubMed
Becker, G. S. (1993) Human Capital (3rd edition). The University of Chicago Press, Chicago.CrossRefGoogle Scholar
Boardman, J. D., Powers, D. A., Padilla, Y. C. & Hummer, R. A. (2002) Low birth weight, social factors, and developmental outcomes among children in the United States. Demography 39(2), 353–368.CrossRefGoogle ScholarPubMed
Boat, B., Campbell, F. & Ramey, C. (1986) Preventive education and birth order as co-determinants of IQ in disadvantaged 5-year olds. Child: Care, Health and Development 21(1), 25–36.CrossRefGoogle Scholar
Boocock, S. S. (1995) Early childhood programs in other nations: goals and outcomes. The Future of Children 5(3), 94–114.CrossRefGoogle ScholarPubMed
Bouchard, T. J. Jr. & McGue, M. (1981) Familial studies of intelligence: a review. Science 212, 1055–1059.CrossRefGoogle ScholarPubMed
Breslau, N., Chilcoat, H., DelDotto, J., Andreski, P. & Brown, G. (1996) Low birth weight and neurocognitive status at six years of age. Biological Psychiatry 40(5), 389–397.CrossRefGoogle ScholarPubMed
Broekman, B., Chan, Y., Chong, Y. et al. (2009) The influence of birth size on intelligence in healthy children. Pediatrics 123(6), S1011–S1016.CrossRefGoogle ScholarPubMed
Cesur, R. & Kelly, I. R. (2010) From cradle to classroom: high birth weight and cognitive outcomes. Forum for Health Eocnomics & Policy 13(2), 1–24.Google Scholar
Deary, I., Johnson, W. & Houlihan, L. M. (2009) Genetic foundations of human intelligence. Human Genetics 126, 215–232.CrossRefGoogle ScholarPubMed
Deary, I., Whiteman, M. C., Starr, J. M., Whalley, L. J. & Fox, H. C. (2004) The impact of childhood intelligence on later life: following up the Scottish Mental Surveys of 1932 and 1947. Journal of Personality and Social Psychology 86(1), 130–147.CrossRefGoogle ScholarPubMed
Flynn, J. R. (1994) IQ gains over time. In Sternberg, R. J. (ed.) Encyclopedia of Human Intelligence. Macmillan, New York, pp. 617–623.Google Scholar
Galton, F. (1865) Heredity, talent, and character. Macmillan's Magazine 12, 157–166.Google Scholar
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.CrossRefGoogle ScholarPubMed
Greene, W. (2012) Econometric Analysis (7th Edition). Prentice Hall.Google Scholar
Guo, G. & Harris, K. M. (2000) The mechanisms mediating the effects of poverty on children's intellectual development. Demography 37(4), 431–447.CrossRefGoogle ScholarPubMed
Hart, C. L., Taylor, M. D., Davey Smith, G. et al. (2003) Childhood IQ, social class, deprivation, and their relationships with mortality and morbidity risk in later life: prospective observational study linking the Scottish Mental Survey 1932 and the midspan studies Psychosomatic Medicine 65(5), 877–883.CrossRefGoogle ScholarPubMed
Illsley, R. (2002) A city's schools: from equality of input to inequality of outcome. Oxford Review of Education 28(4), 427–444.CrossRefGoogle Scholar
Jefferis, B. J., Power, C. & Hertzman, C. (2002) Birth weight, childhood socioeconomic environment, and cognitive development in the 1958 British Birth Cohort Study. British Medical Journal 325(7359), 305.CrossRefGoogle ScholarPubMed
Kirkegaard, I., Obel, C., Hedegaard, M. & Henriksen, T. (2006) Gestational age and birth weight in relation to school performance of 10-year-old children: a follow-up study of children born after 32 completed weeks. Pediatrics 118(4), 1600–1606.CrossRefGoogle ScholarPubMed
Kleinbaum, D. & Klein, M. (2010) Logistic Regression (3rd Edition). Springer-Verlag, New York.CrossRefGoogle Scholar
Kramer, R. A., Allen, L. & Gergen, P. J. (1995) Health and social characteristics and children's cognitive functioning: results from a national cohort. American Journal of Public Health 85(3), 312–318.CrossRefGoogle ScholarPubMed
Lawlor, D. A., Batty, G. D., Morton, S. M. B., Deary, I. J., Macintyre, S., Ronalds, G. & Leon, D. (2005) Early life predictors of childhood intelligence: evidence form the Aberdeen children of the 1950s study. Journal of Epidemiology Community Health 59(7), 656–663.CrossRefGoogle Scholar
Lynn, R. & Vanhanen, T. (2002) IQ and the Wealth of Nations. Praeger, Westport, CT.Google Scholar
Lynn, R. & Vanhanen, T. (2006) IQ and Global Inequality. Washington Summit Books, Athens, GA.Google Scholar
McLoyd, V. C. (1998) Socioeconomic disadvantage and child development. American Psychologist 53(2), 185–204.CrossRefGoogle ScholarPubMed
Ministry of Education (2011) Primary 1 Registration Info sheet. URL: http://www.moe.gov.sg/education/primary/files/primary-one-registration-info-sheet.pdf (accessed May 2011).Google Scholar
O'Callaghan, M., Williams, G. M., Andersen, M. J. & Bar, W. & Najman, J. M. (1995) Social and biological risk factors for mild and borderline impairment of language comprehension in a cohort of five-year-old children. Developmental Medicine and Child Neurology 37(12), 1051–1061.CrossRefGoogle Scholar
Osler, M., Andersen, A. M., Due, P., Lund, R., Damsgaard, M. T. & Holstein, B. E. (2003) Socioeconomic position in early life, birth weight, childhood cognitive function, and adult mortality. A longitudinal study of Danish men born in 1953. Journal of Epidemiology and Community Health 57(11), 681–686.CrossRefGoogle ScholarPubMed
Plomin, R., Fulker, D. W., Corley, R. & Defries, J. C. (1997) Nature, nurture, and cognitive development from 1 to 16 years: a parent–offspring adoption study. Psychological Science 8(6), 442–447.CrossRefGoogle Scholar
Raven, J., Raven, J. C. & Court, J. H. (1998) Manual for Raven's Standard Pogressive Matrices. Oxford Psychologists' Press, Oxford.Google Scholar
Richards, M., Hardy, R., Kuh, D. & Wadsworth, M. E. J. (2001) Birth weight and cognitive function in the British 1946 birth cohort: longitudinal population based study. British Medical Journal 322(7280), 199–203.CrossRefGoogle ScholarPubMed
Richards, M., Hardy, R., Kuh, D. et al. (2002) Birthweight, postnatal growth and cognitive function in a national UK birth cohort. International Journal of Epidemiology 31(2), 342–348.CrossRefGoogle Scholar
Rowe, D. C., Jacobson, K. C. & Van den Oord, E. J. (1999) Genetic and environmental influences on vocabulary IQ: parental education level as moderator. Child Development 70(5), 1151–1162.CrossRefGoogle ScholarPubMed
Saw, S.-M., Chua, W.-H., Hong, C.-Y., Wu, H.-M., Chan, W.-Y., Chia, K.-S. et al. (2002) Nearwork in early-onset myopia. Investigative Ophthalmology & Visual Science 43(2), 332–339.Google ScholarPubMed
Saw, S.-M., Shankar, A., Tan, S.-B., Taylor, H. et al. (2006) A Cohort study of incident myopia in Singaporean children. Investigative Ophthalmology & Visual Science 47(5), 1839–1844.CrossRefGoogle ScholarPubMed
Saw, S.-M., Tong, L., Chua, W.-H. et al. (2005) Incidence and progression of myopia in Singaporean school children. Investigative Ophthalmology & Visual Science 46(1), 51–57.CrossRefGoogle ScholarPubMed
Scarr, S. & Cart-Saltzman, L. (1982) Genetics and intelligence. In Sternberg, R. J. (ed.) Handbook for Human Intelligence. Cambridge University Press, p. 896.Google Scholar
Shenkin, S. D., Starr, J. M. & Deary, I. J. (2004) Birth weight and cognitive ability in childhood: a systematic review. Psychological Bulletin 6(130), 989–1012.CrossRefGoogle Scholar
Shenkin, S. D., Starr, J. M., Pattie, A., Rush, M. A., Whalley, L. J. & Deary, I. J. (2001) Birth weight and cognitive function at age 11 years: the Scottish Mental Survey 1932. Archives of Disease in Childhood 85(3), 189–197.CrossRefGoogle ScholarPubMed
Starr, J. M., Taylor, M. D., Hart, C. L. et al. (2004) Childhood mental ability and blood pressure at midlife: linking the Scottish mental survey 1932 and the Midspan studies. Journal of Hypertension 22(5), 893–897CrossRefGoogle ScholarPubMed
Tarling, R. (2009) Statistical Modelling for Social Researchers: Principles and Practice. Routledge, Oxfordshire.Google Scholar
Taylor, M. D., Hart, C. L., Davey Smith, G. et al. (2003) Childhood mental ability and smoking cessation in adulthood: prospective observational study linking the Scottish Mental Survey 1932 and the midspan studies. Journal of Epidemiology and Community Health 57(6), 464–465.CrossRefGoogle ScholarPubMed
Turkheimer, E., Haley, A., Waldron, M., D'Onofrio, B. & Gottesman, I. (2003) Socioeconomic status modifies heritability of IQ in young children. Psychological Science 14(6), 623–628.CrossRefGoogle ScholarPubMed
Wechsler, D. (1989) Wechsler Preschool and Primary Scale of Intelligence-Revised (Wppsi-R). The Psychological Corporation, San Antonio, TX.Google Scholar
Wechsler, D. (1991) Wechsler Intelligence Scale for Children (3rd Edition). The Psychological Corporation, San Antonio, TX.Google Scholar
Whalley, L. J. & Deary, I. J. (2001) Longitudinal cohort study of childhood IQ and survival up to age 76. British Medical Journal 322(7290), 819–823.CrossRefGoogle ScholarPubMed