4.7 Article

Maternal and infant factors associated with excess kindergarten costs

Journal

PEDIATRICS
Volume 114, Issue 3, Pages 720-728

Publisher

AMER ACAD PEDIATRICS
DOI: 10.1542/peds.2003-1028-L

Keywords

developmental disabilities; epidemiology; special education; economics; very low birth weight; longitudinal studies; risk factors

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Objective. To estimate the excess educational costs at kindergarten from infant and maternal factors that are reported routinely at birth. Methods. Birth and school records were analyzed for all children who were born in Florida between September 1, 1990, and August 31, 1991, and entered kindergarten from 1996 through 1999 (N=120554). Outcome measure was cost to state, derived from base allocation for students in regular classrooms plus multiplier weights for those who were assigned to 8 mutually exclusive special education categories or who repeated kindergarten. Results. More than one quarter of the study cohort was found to be assigned to special education classes at kindergarten. Regression model estimates indicated that children who were born at <1000 g (n=380) generated 71% higher costs in kindergarten than children who were born at >= 2500 g. Children who were born at 1000 to 1499 g (n=839) generated 49% higher costs. Other birth conditions, independent of birth weight, were associated with higher kindergarten costs: family poverty (31%), congenital anomalies (29%), maternal education less than high school (20%), and no prenatal care (14%). Because of their prevalence, family poverty and low maternal education accounted for >75% of excess kindergarten costs. If 9% of infants who weighed between 1500 and 2499 g (n=1027) could be delivered at 2500 g, then the state of Florida potentially could save $1 million in kindergarten costs. Savings of a similar magnitude might be achieved if 3% of mothers who left school without a diploma (n=1528) were to graduate. Conclusions. Any policy recommendation aimed at reducing education costs in kindergarten must take into consideration 3 factors: the prevalence of risk conditions whose amelioration is desired, the potential cost savings associated with reducing those conditions, and the costs of amelioration. Projecting these costs from information that is available at birth can assist school districts and state agencies in allocating resources.

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