BACKGROUND: The birth prevalence rate (BPR) of congenital anomalies (CAs) is heterogeneous and exhibits geographical and sociocultural variations throughout the world. In South America (SA), high birth prevalence regions of congenital anomalies have been observed. The aim of this study was to identify, describe, and characterize geographical clusters of congenital anomalies in SA. METHODS: This observational descriptive study is based on clinical epidemiological data registered by the Latin-American Collaborative Study of Congenital Malformations network. Between 1995 and 2012, a total of 25,082 malformed newborns were ascertained from 2,557,424 births at 129 hospitals in SA. The spatial scan statistic was used to determine geographical regions with high BPR of CAs. The BPR was obtained with a Poisson regression model. Odds ratios were estimated for several risk factors inside the geographical clusters. RESULTS: We confirmed the existence of high BPR regions of CAs in SA. Indicators of low socioeconomic conditions, such as a low maternal education, extreme age childbearing, infectious diseases, and medicine use during pregnancy were detected as risk factors inside these regions. Native and African ancestries with high frequency of consanguineous marriages could explain partially these high BPR clusters. CONCLUSION: The recognition of clusters could be a starting point in the identification of susceptibility genes associated with the occurrence of CA in high BPR regions.
BACKGROUND: The birth prevalence rate (BPR) of congenital anomalies (CAs) is heterogeneous and exhibits geographical and sociocultural variations throughout the world. In South America (SA), high birth prevalence regions of congenital anomalies have been observed. The aim of this study was to identify, describe, and characterize geographical clusters of congenital anomalies in SA. METHODS: This observational descriptive study is based on clinical epidemiological data registered by the Latin-American Collaborative Study of Congenital Malformations network. Between 1995 and 2012, a total of 25,082 malformed newborns were ascertained from 2,557,424 births at 129 hospitals in SA. The spatial scan statistic was used to determine geographical regions with high BPR of CAs. The BPR was obtained with a Poisson regression model. Odds ratios were estimated for several risk factors inside the geographical clusters. RESULTS: We confirmed the existence of high BPR regions of CAs in SA. Indicators of low socioeconomic conditions, such as a low maternal education, extreme age childbearing, infectious diseases, and medicine use during pregnancy were detected as risk factors inside these regions. Native and African ancestries with high frequency of consanguineous marriages could explain partially these high BPR clusters. CONCLUSION: The recognition of clusters could be a starting point in the identification of susceptibility genes associated with the occurrence of CA in high BPR regions.
Authors: Ignacio Zarante; Paula Hurtado-Villa; Salimah R Walani; Vijaya Kancherla; Jorge López Camelo; Roberto Giugliani; Boris Groisman; Christopher P Howson; Pablo Durán Journal: Rev Panam Salud Publica Date: 2019-02-14
Authors: Luciana M Fonseca; Glenda G Haddad; Guilherme P Mattar; Melaine C de Oliveira; Sharon S Simon; Laura M Guilhoto; Geraldo F Busatto; Shahid Zaman; Anthony J Holland; Marcelo Q Hoexter; Cassio M Bottino Journal: Braz J Psychiatry Date: 2018-10-22 Impact factor: 2.697