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Predicting adverse infant health outcomes using routine screening variables: Modelling the impact of interdependent risk factors

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  • Peter Congdon

Abstract

This paper sets out a methodology for risk assessment of pregnancies in terms of adverse outcomes such as low birth-weight and neonatal mortality in a situation of multiple but possibly interdependent major dimensions of risk. In the present analysis, the outcome is very low birth-weight and the observed risk indicators are assumed to be linked to three main dimensions: socio-demographic, bio-medical status, and fertility history. Summary scores for each mother under each risk dimension are derived from observed indicators and used as the basis for a multidimensional classification to high or low risk. A fully Bayesian method of implementation is applied to estimation and prediction. A case study is presented of very low birth-weight singleton livebirths over 1991-93 in a health region covering North West London and parts of the adjacent South East of England, with validating predictions to maternities in 1994.

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  • Peter Congdon, 2001. "Predicting adverse infant health outcomes using routine screening variables: Modelling the impact of interdependent risk factors," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(2), pages 183-197.
    • Handle: RePEc:taf:japsta:v:28:y:2001:i:2:p:183-197
    DOI: 10.1080/02664760020016091
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    1. Geronimus, A.T., 1986. "The effects of race, residence, and prenatal care on the relationship of maternal age to neonatal mortality," American Journal of Public Health, American Public Health Association, vol. 76(12), pages 1416-1421.
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    3. Kotelchuck, M., 1994. "The Adequacy of Prenatal Care Utilization Index: Its US distribution and association with low birthweight," American Journal of Public Health, American Public Health Association, vol. 84(9), pages 1486-1489.
    4. Bengt Muthén, 1984. "A general structural equation model with dichotomous, ordered categorical, and continuous latent variable indicators," Psychometrika, Springer;The Psychometric Society, vol. 49(1), pages 115-132, March.
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