International Journal of Epidemiology, Vol 28, 701-710, Copyright © 1999 by International Epidemiological Association
KB Kallen, EE Castilla, M da Graca Dutra, P Mastroiacovo, E Robert and BA Kallen
BACKGROUND: Infants with multiple malformations are important in birth
defect epidemiology and malformation monitoring because human teratogens
have often caused complex malformations. Various methods for the analysis
of multimalformed infants have been tried. METHOD: By using data from four
large registries of congenital malformations, 5256 infants were identified
with two or more among 73 selected malformations. Pairwise associations
between malformations were detected by multiple logistic regression
analyses, and putative confounders (programme, maternal age, autopsy, etc.)
were controlled for. For each significant pairwise association, further
analyses were performed in order to find associations with a possible third
malformation. RESULTS: The importance of controlling for several
confounders was demonstrated. Several well-known associations were found,
which supports the technique used. The interpretation of three- way
associations was discussed. Results from the present study were compared
with those obtained using some other methods. CONCLUSIONS: Different
confounders can cause biased associations. The method presented in the
paper takes this into consideration and is therefore more likely than
previously used techniques to give unbiased information on the clustering
of different malformations among multimalformed infants.
ARTICLES
A modified method for the epidemiological analysis of registry data on infants with multiple malformations
Tornblad Institute, University of Lund, Sweden. Karin.Kallen@anatom.lu.se
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