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Identifying Multiple Gestation Groups Using State-Level Birth and Fetal Death Certificate Data
Authors:Jane Lazar MPH  Milton Kotelchuck PhD   MPH  Angela Nannini PhD   FNP  Mary Barger MPH   CNM
Affiliation:(1) Department of Maternal and Child Health, Boston University School of Public Health, Boston, Massachusetts, USA;(2) Massachusetts Department of Public Health, Boston, Massachusetts, USA;(3) School of Nursing, Bouvé College of Health Sciences, Northeastern University, Boston, Massachusetts, USA;(4) 41 North Main Street, Natick, Massachusetts 01760, USA
Abstract:Purpose: Birth and fetal death certificates classify individuals as twins or higher order multiples, but do not identify multiple gestation groups. As a result, multiple gestations are consistently excluded from maternal and child health research studies despite the surge in multiple births since the early 1980s and the health risks associated with them. A standardized methodology for states to identify multiple gestation groups is proposed to allow researchers to account for multiple gestations in analyses, improve the accuracy of the incidence of multiple gestations and further knowledge of the impact of multiple gestations on birth outcomes. Methods: Using 3 years of Massachusetts birth and fetal death certificate data from 1998 to 2000 (247,959 births and 1358 fetal deaths), we assigned matching multiple gestation group numbers to records with identical combinations of mother's first name, last name, date of birth, and month of delivery. To validate our methodology, we calculated plurality and compared it to plurality reported on the existing birth and fetal death data. Results: This method correctly identified 10,765 records out of 10,795 validated multiple gestation deliveries (99.8%). Our method identified 71 additional multiple gestation deliveries, which were not identified by the birth and fetal death files. This method resulted in only 4 false positives and 51 false negatives over 3 years. Conclusions: This algorithm provides much needed information on multiple gestation groupings, and as an additional benefit, improves the identification of multiple gestation deliveries. This method has proven easy to use, employs state-level data, and offers numerous new analytic opportunities. Presentations: Maternal and Child Health Epidemiology annual meeting, Clearwater, FL, December 2002. Annual meetings of the American Public Health Association, San Francisco, CA, November 2003.
Keywords:reproductive health  twins  databases  research methodology  informatics
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