CONICET | Buscador de Institutos y Recursos Humanos

To the Editor:The Latin-American Collaborative Study of Congenital Malformations (ECLAMC) network1 has studied the frequencies of congenital anomalies in South America for over 40 years and has reported heterogeneous rates across countries for some birth defects.2,3Cluster detection using spatial scan analysis4 may be an efficient approach to identifying environmental and/or genetic factors involved in birth defects. This statistical method has the advantage of delimiting areas of high birth prevalence rate independent of political boundaries, which renders this approach useful for identifying etiologic factors and generating causal hypotheses regarding the specified geographic areas.We conducted an ecological study to identify regions with a high birth prevalence rates of specific isolated congenital anomalies in South America, using clinical epidemiologic data registered by the ECLAMC network. A total of 25,082 malformed newborns were ascertained from 2,557,424 births at 129 hospitals in South America between 1995 and 2012. Each case was codified as one of 17 congenital anomalies categories. We selected the following categories because they are conspicuous, have a high observational value at birth, or are of high clinical-epidemiologic value for health policy. The isolated congenital anomalies were: anencephaly, encephalocele (at any level), hydrocephaly, spina bifida (with or without hydrocephalus, at any level), microtia, cleft palate only, cleft lip only, cleft lip with cleft palate, cleft lip with or without cleft palate, esophageal atresia (with or without fistula, at any level), hypospadias (any grade), postaxial polydactyly (feet or hands), preaxial polydactyly (feet or hands), diaphragmatic hernia, omphalocele, gastroschisis, and Down syndrome.We used the Spatial Scan Statistic4 to determine geographical regions with high birth prevalence rate of congenital anomalies. We assessed differences in ascertainment by including dummy variables for each hospital in a Poisson regression that captures the fixed effects of the mean frequency in the regression coefficient for each hospital. We calculated the birth prevalence rate and 95% confidence intervals. For the regression model, we adjusted the standard errors according to the Huber method to consider outlying values or correlations among hospitals located in the same region.We identified five high birth prevalence rate regions associated with five congenital anomalies in South America (Table). Hospitals from Cañar and Azogues regions in Ecuador have a high birth prevalence rate of oral clefts and microtia, which were systematically reported by the ECLAMC network.5,6 Both of these congenital anomalies have been associated with high altitude, Amerindian ancestry, and low socioeconomic status, three factors shared between the regions and these two anomalies. It is also worth noting that this region is reported to have high levels of consanguinity,7 a key factor to be considered in diseases with a strong genetic component.TABLE. Geographic Re...Image ToolsPostaxial polydactyly has been observed to occur at a high frequency in populations with African ancestry.2 In our study, hospitals from Belo Horizonte, Campinas, Sao Paulo, Ribeirao Preto and Porto Alegre (Brazil), and Coro and Bolivar (Venezuela) exhibited both high proportions of African ancestry and a high birth prevalence rate of postaxial polydactyly. In these regions, a high frequency of consanguineous mating was reported in the literature,7 with the frequency of consanguineous marriage reaching as high as twice the expected value for Brazil. Indeed, consanguineous marriage was previously described as a risk factor for postaxial polydactyly.8Preaxial polydactyly was reported more frequently in Native American and Amerindian populations.9 A high frequency of polydactyly, without distinction regarding the type, was already reported in Colombian ECLAMC hospitals.10Increased susceptibility in people of Native and African ancestries with high frequency of consanguinity could partially explain the high birth prevalence rate clusters. The recognition of clusters could be the starting point for the identification of susceptibility genes associated with the occurrence of congenital anomalies in high birth prevalence rate regions.

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