with all other racial/ethnic groups included in the total). The gastroschisis case definition was based on the British Pediatric Association Classification of Diseases code (756.71) or the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code for gastroschisis (756.73, or before 10/1/2009, 756.79, with verification to confirm cases of gastroschisis, because the previous code was shared with omphalocele). Gastroschisis cases included live births, fetal deaths, † and elective terminations. § Data were pooled at CDC, and gastroschisis prevalence was calculated for each year, maternal age group, and race/ethnicity. Prevalence was calculated as number of gastroschisis cases among all birth outcomes divided by the total number of live births. The denominators of total number of live births in the same catchment area as the birth defects surveillance program were reported by states or obtained from public use data files. Poisson exact methods were used to calculate 95% CIs for each prevalence estimate. Prevalence ratios were calculated by dividing the prevalence during 2006-2012 by the prevalence during 1995-2005, and CIs for the prevalence ratios were calculated using Poisson regression.Because the comparison of prevalence between the two study periods involved an artificial breakpoint during the 18-year data span and only examined pooled prevalence within those periods, joinpoint regression analysis was used to identify statistically significant changes in the annual prevalence of gastroschisis over the course of the entire study period (1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012). Joinpoint regression initially models annual trend data by fitting a straight line (i.e., zero joinpoints). Then, joinpoints are added, one at a time, and a Monte Carlo permutation test is used to determine the optimal number of joinpoints. Each joinpoint in the final model corresponds to a significant change in the trend, and an AAPC and its 95% CI are calculated to describe how the rate changes within each time interval (3). The estimated overall percent change was calculated by first converting the AAPC to the projected single year change in prevalence and then exponentiating to the number of years studied minus one to estimate the total increase throughout the 18 years. This gives the magnitude of the increase, which

The aim of the study is to determine the prevalence, outcomes, and survival (among live births [LB]), in pregnancies diagnosed with trisomy 13 (T13) and 18 (T18), by con-genital anomaly register and region. Twenty-four population- and hospital-based birth defects surveillance registers from 18 countries, contributed data on T13 and T18 between 1974 and 2014 using a common data-reporting protocol. The mean total birth prevalence (i.e., LB, stillbirths, and elective termination of pregnancy for fetal anomalies [ETOPFA]) in the registers with ETOPFA (n = 15) for T13 was 1.68 (95% CI1.3–2.06), and for T18 was 4.08 (95% CI 3.01–5.15), per 10,000 births. The prevalence varied among the various registers. The mean prevalence among LB in all registers for T13 was 0.55 (95%CI 0.38–0.72), and for T18 was 1.07 (95% CI 0.77–1.38), per 10,000 births. The median mortality in the first week of life was 48% for T13 and 42% for T18, across all registers, half of which occurred on the first day of life. Across 16 registers with complete 1-year follow-up, mortality in first year of life was 87% for T13 and 88% for T18. This study provides an international perspective on prevalence and mortality of T13 and T18. Overall outcomes and survival among LB were poor with about half of live born infants not surviving first week of life; nevertheless about 10% survived the first year of life. Prevalence and outcomes varied by country and termination policies. The study highlights the variation in screening, data collection, and reporting practices for these conditions.

Background/Objectives: In this report, the National Birth Defects Prevention Network (NBDPN) examines and compares gastroschisis and omphalocele for a recent 5-year birth cohort using data from 30 population-based birth defect surveillance programs in the United States. Methods: As a special call for data for the 2019 NBDPN Annual Report, state programs reported expanded data on gastroschisis and omphalocele for birth years 2012–2016. We estimated the overall prevalence (per 10,000 live births) and 95% confidence intervals (CI) for each defect as well as by maternal race/ethnicity, maternal age, infant sex, and case ascertainment methodology utilized by the program (active vs. passive). We also compared distribution of cases by maternal and infant factors and presence/absence of other birth defects. Results: The overall prevalence estimates (per 10,000 live births) were 4.3 (95% CI:4.1–4.4) for gastroschisis and 2.1 (95% CI: 2.0–2.2) for omphalocele. Gastroschisis was more frequent among young mothers (<25 years) and omphalocele more common among older mothers (>40 years). Mothers of infants with gastroschisis were more likely to be underweight/normal weight prior to pregnancy and mothers of infants with omphalocele more likely to be overweight/obese. Omphalocele was twice as likely as gastroschisis to co-occur with other birth defects. Conclusions: This report highlights important differences between gastroschisis and omphalocele. These differences indicate the importance of distinguishing between these defects in epidemiologic assessments. The report also provides additional data on co-occurrence of gastroschisis and omphalocele with other birth defects. This information can provide a basis for future research to better understand these defects.

Background Congenital microcephaly has been linked to maternal Zika virus infection. However, ascertaining infants diagnosed with microcephaly can be challenging. Methods Thirty birth defects surveillance programs provided data on infants diagnosed with microcephaly born 2009 to 2013. The pooled prevalence of microcephaly per 10,000 live births was estimated overall and by maternal/infant characteristics. Variation in prevalence was examined across case finding methods. Nine programs provided data on head circumference and conditions potentially contributing to microcephaly. Results The pooled prevalence of microcephaly was 8.7 per 10,000 live births. Median prevalence (per 10,000 live births) was similar among programs using active (6.7) and passive (6.6) methods; the interdecile range of prevalence estimates was wider among programs using passive methods for all race/ethnicity categories except Hispanic. Prevalence (per 10,000 live births) was lowest among non-Hispanic Whites (6.5) and highest among non-Hispanic Blacks and Hispanics (11.2 and 11.9, respectively); estimates followed a U-shaped distribution by maternal age with the highest prevalence among mothers <20 years (11.5) and ≥40 years (13.2). For gestational age and birth weight, the highest prevalence was among infants <32 weeks gestation and infants <1500 gm. Case definitions varied; 41.8% of cases had an HC ≥ the 10th percentile for sex and gestational age. Conclusion Differences in methods, population distribution of maternal/infant characteristics, and case definitions for microcephaly can contribute to the wide range of observed prevalence estimates across individual birth defects surveillance programs. Addressing these factors in the setting of Zika virus infection can improve the quality of prevalence estimates.

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