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A Cumulative Risk Factor Model for Early Identification of Academic Difficulties in Premature and Low Birth Weight Infants

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Abstract

Objectives: Premature and low birth weight children have a high prevalence of academic difficulties. This study examines a model comprised of cumulative risk factors that allows early identification of these difficulties. Methods: This is a secondary analysis of data from a large cohort of premature (<37 weeks gestation) and LBW (<2500 g) children. The study subjects were 8 years of age and 494 had data available for reading achievement and 469 for mathematics. Potential predictor variables were categorized into 4 domains: sociodemographic, neonatal, maternal mental health and early childhood (ages 3 and 5). Regression analysis was used to create a model to predict reading and mathematics scores. Results: Variables from all domains were significant in the model, predicting low achievement scores in reading (R2 of 0.49, model p-value < .0001) and mathematics (R2 of 0.44, model p-value <  .0001). Significant risk factors for lower reading scores, were: lower maternal education and income, and Black or Hispanic race (sociodemographic); lower birth weight and male gender (neonatal); lower maternal responsivity (maternal mental health); lower intelligence, visual-motor skill and higher behavioral disturbance scores (early childhood). Lower mathematics scores were predicted by lower maternal education, income and age and Black or Hispanic race (sociodemographic); lower birth weight and higher head circumference (neonatal); lower maternal responsivity (maternal mental health); lower intelligence, visual-motor skill and higher behavioral disturbance scores (early childhood). Conclusions: Sequential early childhood risk factors in premature and LBW children lead to a cumulative risk for academic difficulties and can be used for early identification.

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References

  1. Hack M, Klein NK, Taylor GH. Long-term developmental outcomes of low birth weight infants, in the future of children: Low birth weight; 1995.

  2. Taeusch HW, Yogman MW. Follow-up management of the high-risk infant. 1 ed. Boston, MA: Little,Brown and Company; 1987.

    Google Scholar 

  3. Hollomon HA, Dobbins DR, Scott KG. The effects of biological and social risk factors on special education placement: Birth weight and maternal education as an example. Res Dev Disabil 1998;19(3):281–94.

    Article  PubMed  CAS  Google Scholar 

  4. McCormick MC, Gortmaker SL, Sobol AM. Very low birth weight children: Behavior problems and school difficulty in a national sample. J Pediatr 1990;117(5):687–93.

    Article  PubMed  CAS  Google Scholar 

  5. Corman H, Chaikind S. The effect of low birthweight on the school performance and behavior of school-aged children. Econ Educ Rev 1998;17(3):307–16.

    Article  Google Scholar 

  6. Klebanov PK, Brooks-Gunn J, McCormick MC. School achievement and failure in very low birth weight children. J Dev Behav Pediatr 1994;15(4):248–56.

    Article  PubMed  CAS  Google Scholar 

  7. Bowen JR, Gibson FL, Hand PJ. Educational outcome at 8 years for children who were born extremely prematurely: A controlled study. J Paediatr Child Health 2002;38(5):438–44.

    Article  PubMed  CAS  Google Scholar 

  8. Saigal S, Hoult LA, Streiner DL. School difficulties at adolescence in a regional cohort of children who were extremely low birth weight. Pediatrics 2000;105(2):325–31.

    Article  PubMed  CAS  Google Scholar 

  9. Rickards AL, et al. Cognition, school performance, and behavior in very low birth weight and normal birth weight children at 8 years of age: a longitudinal study. J Dev Behav Pediatr 1993;14(6):363–8.

    Article  PubMed  CAS  Google Scholar 

  10. McGauhey PJ, et al. Social environment and vulnerability of low birth weight children: A social-epidemiological perspective. Pediatrics 1991;88(5):943–53.

    PubMed  CAS  Google Scholar 

  11. Stanton-Chapman T, Chapman DA, Scott KG. Identification of Early Risk Factors for learning Disabilities. J Early Interv 2001;24(3):193–206.

    Article  Google Scholar 

  12. Taylor HG, et al. Middle-school-age outcomes in children with very low birthweight. Child Dev 2000;71(6):1495–511.

    Article  PubMed  CAS  Google Scholar 

  13. Hack M, et al. The effect of very low birth weight and social risk on neurocognitive abilities at school age. J Dev Behav Pediatr 1992;13(6):412–20.

    Article  PubMed  CAS  Google Scholar 

  14. Johnson EO, Breslau N. Increased risk of learning disabilities in low birth weight boys at age 11 years. Biol Psychiatry 2000;47(6):490–500.

    Article  PubMed  CAS  Google Scholar 

  15. Bhutta AT, et al. Cognitive and behavioral outcomes of school-aged children who were born preterm: A meta-analysis. Jama 2002;288(6):728–37.

    Article  PubMed  Google Scholar 

  16. Taylor HG, et al. Predictors of early school age outcomes in very low birth weight children. J Dev Behav Pediatr 1998;19(4):235–43.

    Article  PubMed  CAS  Google Scholar 

  17. McGrath MM, et al. Longitudinal neurologic follow-up in neonatal intensive care unit survivors with various neonatal morbidities. Pediatrics 2000;106(6):1397–405.

    Article  PubMed  CAS  Google Scholar 

  18. Fletcher JM. Intelligence testing and the discrepancy model for children with learning disabilities. Learn Disabil Res Pract 1998;13:186–203.

    Google Scholar 

  19. Hughes CA, et al. Cognitive performance at school age of very low birth weight infants with bronchopulmonary dysplasia. J Dev Behav Pediatr 1999;20(1):1–8.

    Article  PubMed  CAS  Google Scholar 

  20. Fletcher JM, et al. Effects of intraventricular hemorrhage and hydrocephalus on the long-term neurobehavioral development of preterm very-low-birthweight infants. Dev Med Child Neurol 1997;39(9):596–606.

    Article  PubMed  CAS  Google Scholar 

  21. Laucht M, Esser G, Schmidt MH. Differential development of infants at risk for psychopathology: the moderating role of early maternal responsivity. Dev Med Child Neurol 2001;43(5):292–300.

    Article  PubMed  CAS  Google Scholar 

  22. Grunau RE, Whitfield MF, Davis C. Pattern of learning disabilities in children with extremely low birth weight and broadly average intelligence. Arch Pediatr Adolesc Med 2002;156(6):15–20.

    PubMed  Google Scholar 

  23. Anderson PJ, Doyle LW. Neurobehavioral outcomes of school-age children born extremely low birth weight or very preterm in the 1990s. Jama 2003;289(24):3264–72.

    Article  PubMed  Google Scholar 

  24. Campbell FA, et al. The development of cognitive and academic abilities: Growth curves from an early childhood educational experiment. Dev Psychol 2001;37:231–242.

    Article  PubMed  CAS  Google Scholar 

  25. From neurons to neighborhoods, The science of early childhood development, ed. S.J.a.P. DA. Washington, DC: National Academy Press; 2000.

  26. Schweinhart LJ, et al. Lifetime effects: The High/Scope Perry Preschool study through age 40. Monographs of the high/scope educational research foundation, 14. Ypsilanti, MI: High/Scope Press; In Press.

  27. Sameroff AJ, et al. Intelligence quotient scores of 4-year-old children: social-environmental risk factors. Pediatrics 1987;79(3):343–50.

    PubMed  CAS  Google Scholar 

  28. McCormick MC, et al. The Infant Health and Development Program: Interim summary. J Dev Behav Pediatr 1998;19(5):359–70.

    PubMed  CAS  Google Scholar 

  29. McCarton CM, et al. Results at age 8 years of early intervention for low-birth-weight premature infants. The infant health and development program. Jama 1997;277(2):126–32.

    Article  PubMed  CAS  Google Scholar 

  30. Scott DT, et al. The neonatal health index, in helping low birth weight premature babies. In: Gross R, Spiker D, Haynes CW, editor.: Palo Alto, CA:Stanford University Press; 1997.

  31. Goldberg DP. The detection of psychiatiric illness by questionnaire. London, UK: Oxford University Press; 1972.

    Google Scholar 

  32. Caldwell BM, Bradley RH. Home observation for the measurement of the environment. Littel Rock, AR: University of Arkansas at Little Rock; 1984.

    Google Scholar 

  33. Achenbach TM, Edelbrock C. Manual for the child behavior checklist and revised child behavior profile. Burlington, VT: Queen City Printers; 1983.

    Google Scholar 

  34. Terman LM, Merrill MA. Staqnford-Binet intelligence scale, manual for the third revision. Boston, MA: Houghton Mifflin Co; 1973.

    Google Scholar 

  35. Wechsler D. Wechsler Preschool and primary scale of intelligence. New York, NY: Psychological Corporation; 1989.

    Google Scholar 

  36. Beery KE, Buktenica NA, Beery NA. Manual for the beery-buktenica developmental test of visual-motor integration, 3rd revision. Cleveland, OH: Modern Curriculum Press; 1989.

    Google Scholar 

  37. Woodcock RW, Johnson MB. Manual for the Woodcock- Johnson tests of achievement- revised. Allen, TX: RCL Enterprises; 1990.

    Google Scholar 

  38. Taylor H, Klein N, Hack M. School-age consequences of birth weight less than 750 g: A review and update. Dev Neuropsychol 2000;17(3):289–321.

    Article  PubMed  CAS  Google Scholar 

  39. Preschool IQ. Prenatal and early developmental correlates. 1 ed. In: Broman SN, Kennedy PL, WA, editor. Hillsdale, NJ: Lawrence Erlbaum Associates; 1975.

  40. Vohr BR, et al. School-age outcomes of very low birth weight infants in the indomethacin intraventricular hemorrhage prevention trial. Pediatrics 2003;111(4 Pt 1):e340–6.

    Article  PubMed  Google Scholar 

  41. Brooks-Gunn J, Klebanov PK, Duncan GJ. Ethnic differences in children’s intelligence test scores: role of economic deprivation, home environment, and maternal characteristics. Child Dev 1996;67(2):396–408.

    Article  PubMed  CAS  Google Scholar 

  42. Klebanov PK, Brooks-Gunn J, McCormick MC. School achievement and failure in very low birth weight children. J Dev Behav Pediatr 1994;248–56.

  43. Laucht M, Esser G, Schmidt MH. Differential development of infants at risk for psychopathology: the moderating role of early maternal responsivity. Dev Med Child Neurol 2001;292–300.

  44. Sameroff AJ, Mackenzie MJ. Research strategies for capturing transactional models of development: the limits of the possible. Dev Psychopathol 2003;15(3):613–40.

    Article  PubMed  Google Scholar 

  45. Carvajal HH, et al. Relationships between scores on Wechsler Preschool and primary scale of intelligence–revised and Stanford-Binet IV. Psychol Rep 1991;69(1):23–6.

    Article  PubMed  CAS  Google Scholar 

  46. Dyck MJ, et al. Is the discrepancy criterion for defining developmental disorders valid? J Child Psychol Psychiatry 2004;45(5):979–95.

    Article  PubMed  Google Scholar 

  47. Sinn JK, Ward MC, Henderson-Smart DJ. Developmental outcome of preterm infants after surfactant therapy: Systematic review of randomized controlled trials. J Paediatr Child Health 2002;38(6):597–600.

    Article  PubMed  CAS  Google Scholar 

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Acknowledgements

This study was supported by a fellowship training grant (# 2T77MC00011-10) from the Maternal and Child Health Bureau and by a public health scholarship (# 334394) from the National Health and Medical Research Council of Australia.

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Authors and Affiliations

  1. Murdoch Children’s Research Institute, Royal Children’s Hospital, Flemington Road, Parkville, VIC 3052, Melbourne, Australia

    G. Roberts

  2. Division of Neurology, Children’s Hospital, Boston, MA, USA

    D. Bellinger

  3. Department of Society, Human Development and Health, Harvard School of Public Health, Boston, MA, USA

    M. C. McCormick

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  1. G. Roberts
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  2. D. Bellinger
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  3. M. C. McCormick
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Correspondence to G. Roberts.

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Roberts, G., Bellinger, D. & McCormick, M.C. A Cumulative Risk Factor Model for Early Identification of Academic Difficulties in Premature and Low Birth Weight Infants. Matern Child Health J 11, 161–172 (2007). https://doi.org/10.1007/s10995-006-0158-z

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  • DOI: https://doi.org/10.1007/s10995-006-0158-z

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