The clustering of neonatal deaths in triplet pregnancies: application of response conditional multivariate logistic regression models

Abstract 

Background and objective

A population-based retrospective cohort study of triplet pregnancies was conducted to estimate individual probabilities of neonatal mortality (death within 28 days of birth) conditional on the number of neonatal deaths experienced by other infants in the triplet set.

Methods

Data on 4,697 triplet sets (14,091 births) were derived from the U.S. 1995–1997 matched multiple birth file assembled by the National Center for Health Statistics. Response conditional multivariate logistic regression was used to model the association of neonatal mortality among cotriplets. To account for the correlation of the outcomes among cotriplets, regression parameters were estimated by the methodology of generalized estimating equations with robust variance estimates.

Results

Compared with a triplet where both cotriplets survived the neonatal period, the adjusted odds ratio and 95% confidence interval (CI) for a neonatal death associated with one and two cotriplet neonatal deaths were 1.80 (95% CI 1.06, 3.04), and 13.41 (95% CI 2.31, 77.7), respectively, after adjusting for birthweight and gestational age.

Conclusions

These results show strong evidence of clustering of neonatal deaths in triplet pregnancies.

Keywords:  Generalized estimating equations, Multivariate logistic regression, Neonatal mortality, Response conditional models, Triplets