ABSTRACT
Prematurity, the major cause of perinatal morbidity and mortality, results from a
multifactorial interaction of medical, historic, and psychosocial conditions. Although
the literature contains several reports of prematurity risk-scoring systems, the relative
importance of specific risk factors may depend on the population studied. This report
represents the first prematurity risk-scoring system designed specifically for a predominantly
Hispanic population in the United States.
Retrospective analysis of 8240 births occuring at Harbor/UCLA Medical Center from
July, 1979 to December, 1982 identified maternal prenatal risk factors that were found
to be statistically related to prematurity. A linear logistic regression model was
then employed to derive a composite risk score. Using the logistic risk scores, we
developed a simplified model for identifying women at risk for preterm birth. The
methodology and analyses provide a system for the development of population-specific
risk scoring.
