cohort.1,9,10 With CM the leading cause of infant mortality and morbidity, it is important to estimate its burden among live births because health planning and health resource allocation is based on the disease burden on live births. From a public health perspective, an estimate of CM prevalence among live births, instead of all births, is a more applicable form of epidemiologic data. In addition, our data will be complementary to those from studies that looked at all births as difference in estimates may represent modification of prenatal risk factors or pregnancy termination for prenatally diagnosed fetal anomalies. Second, our estimates were based on weighted data that were derived from a national database of hospitalization information collected from approximately 1000 hospitals to approximate a 20% sample of community hospitals in the United States. As a result, our study population is more representative of the general newborn population in the country in comparison to other studies that were based on specific locations in a country1,10 or on international cohorts.9 Considering the heterogeneity of the United States population, it is imperative to have estimates that are based on a representative sample population. Third, we had a large sample size of more than 1.2 million live births, which makes this the largest study of CM prevalence in the United States. Because of our sample size, our study had sufficient power to analyze 62 different CM diagnoses. This study has some limitations. First, it is a retrospective review of entries from a de-identified administrative database. Second, there is always the risk of “double counting” when using data from a de-identified database. We circumvented this problem by including only cases of CM Table 3 (continued) Male Female OR (CI) Term Preterm OR (CI) Diaphragmatic hernia.1) APVR Z anomalous pulmonary venous return; CI Z 95% confidence interval; COA/IAA Z coarctation of aorta/interrupted aortic arch; dTGA Z complete transposition of great arteries; DORV Z double outlet right ventricle; GI Z gastrointestinal; HLHS Z hypoplastic left heart syndrome; NOS Z not otherwise specified; NTD Z neural tube defect; Omph Z omphalocele; OR Z odds ratio; TEF Z tracheoesophageal fistula; UPJ Z uteropelvic junction) *Healthcare Cost and Utilization Project (HCUP) data use agreement prohibits reporting data with a cell size of 10. This table shows genetic syndromes with cell size 11. CI Z 95% confidence interval; OR Z odds ratio. y Indicates data were not analyzed. z Indicates statistical significance. Congenital Malformations in the Newborn Population 29 that were diagnosed during the birth hospitalization. Our study population included only neonates; therefore, we could not have missed cases of CM diagnosis that presented after birth hospitalization. Newborn data in the NIS database were not linked to maternal data and so we were unable to control for confounding factors such as maternal age, race, and prenatal risk factors. Third, the NIS database had some missing data on gestational maturity. This factor must be taken into consideration when interpreting our data on differences of Congenital heart disease (CHD) incidence by gestational maturity. 5. Conclusion We described the effect of sex and prematurity on the prevalence of CM diagnoses during birth hospitalization. Our study is the largest and most comprehensive analysis of CM prevalence in neonates in the United States. We believe that our up-to-date estimates will serve as a reference guide for clinicians and other health professionals with regard to counseling and public health planning. We also showed a strong association between prematurity and CM. We hope that our work will serve as a foundation for future research to delineate a cause-effect relationship between prematurity and CM. Conflicts of interest The authors have no relevant financial interests, affiliations or conflicts of interest to disclose. Acknowledgments We acknowledge the Nationwide Inpatient Sample (NIS) of the Healthcare Cost and Utilization Project (HCUP) by the Agency for Healthcare Research and Quality (Rockville, MD, USA) for granting us unlimited access to their database. We also thank Jen Yau and Ugochi Egbe for their contributions in data mining, formatting, statistical analysis, and proofreading. References 1. Parker SE, Mai CT, Canfield MA, Rickard R, Wang Y, Meyer RE, et al. Updated national birth prevalence estimates for selected birth defects in the United States, 2004e2006. Birth Defects Res A Clin Mol Teratol 2010;88:1008e16. 2. 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