Abstract

The study uses averages of predictor variables measured at 643 sampling clusters selected for the 2016 Ethiopian Demographic and Health Survey to assess the strength of their individual and combined impacts on the average number of children ever born at the sampling cluster. The 2016 Ethiopian Demographic and Health Survey data on women aged 15 to 49 was used. In a multivariate analysis, the average values of nine predictor variables were regressed on the average number of children ever born per sampling cluster. The statistical analysis system software (SAS) version 9.4 and the geographic information system (GIS) software ArcGIS 10.4 were used. All but one of the nine predictor variables - the presence or absence of co-wives – are found to have a statistically significant effect (P < 0.001) on the number of children ever born to Ethiopian women currently in their reproductive years. The adjusted R-Square of 0.74 for the model is also statistically significant with the average number of deceased sons per cluster having the greatest contribution. The altitude of a cluster is the only non-socioeconomic variable considered. It too has a small but statistically significant effect (p < 0.001). The nine predictor variables explained three-fourths of the spatial variability in the number of children ever born. Measures that can help reduce infant and child mortality in general and the mortality of boys in particular can help reduce the number of children overborn which remains high due to the need to replace deceased children. As this work is based on cluster-level averages, the goodness of fit shown by the R2 value of the model appears to be better than that which could have been achieved by using individual scores.

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