Discordance between LMP-based and clinically estimated gestational age: implications for research, programs, and policy.

This study examines the comparability between the last menstrual period-based and clinically estimated gestational age as collected on certificates of live birth. It explores whether sociodemographic or delivery characteristics influence their agreement and contrasts health status and health care utilization indicators, such as preterm, small for gestational age, and adequacy of prenatal care percentages, produced by each gestational age measure. The 1989-91 South Carolina public use live birth files were used for this analysis. A total of 169,082 single births to resident mothers were selected for investigation. The clinically estimated gestational age distribution exhibited a higher mean and a tendency toward even number digit preference. The last menstrual period-based measure produced higher preterm and postterm percentages. More than 60 percent of the last menstrual period-based preterm births were classified as preterm by the clinical estimate. The sensitivity of the clinical estimate was 27 percent for postterm births. The overall concordance (the percentage of cases with the same value for both measures) was 47 percent, but it varied considerably by gestational age. Between 30 and 35 weeks, the clinical estimate exceeded the last menstrual period-based value by 2 weeks or more for more than 40 percent of the cases. Concordance also varied by race of mother, hospital delivery size, trimester prenatal care began, and birth weight. The last menstrual period-based and the clinically estimated gestational age distributions exhibited notable dissimilarities, produced marked differences in health status indicators, and varied in concordance by gestational age and by sociodemographic, prenatal care, and hospital characteristics. These systematic differences suggest that a transition from the traditionally used last menstrual period-based measure to the clinical estimate or a composite measure will not produce uniform results across geo-political areas and at-risk groups but will be appreciably influenced by population and health care characteristics.