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G Rushton

Publications and source records attributed to G Rushton.

24 records · Page 2Linked to original sources
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Exploratory spatial analysis of birth defect rates in an urban population.

Are birth defect rates unusually high in particular urban localities? The answer requires that the birth defect rate for which 'significance' is claimed be adjusted for the variable population sizes of each area for which the rate is computed and for the spatial dependence of rates based on shared observations between neighboring areas. By address-matching birth and birth defect records to a digital road map, we are able to compute local birth defect rates at regular grid locations by dividing the number of birth defects that occurred in the geographical vicinity of a grid location by the total number of births in the same vicinity. We test for significance, at regular spatial intervals, against the null hypothesis that the observed rate at any locality could reasonably have arisen by chance alone, given the underlying geographical variation in births. Significance is determined by using Monte Carlo simulations, where each birth location has an identical probability of being a defect. From 1000 simulations, a statistical distribution of the birth defect rate for each grid location is determined. The proportion of the simulated birth defect rates that are less than the observed rate at any grid location is the probability that the observed rate is significant. These probabilities, portrayed as isarithmic maps, show areas that have significantly high birth defect rates. Our results show birth defect rates for the period 1983 to 1990 in Des Moines, Iowa, U.S.A.

Cluster Analysis↗
PubMedDate not supplied

The spatial relationship between infant mortality and birth defect rates in a U.S. city.

The spatial patterns of infant mortality and birth defect rates in the Des Moines, Iowa, urban region are described as a contoured surface based on the punctual kriging of address-matched vital statistics records from The Iowa Department of Public Health. Areas defined as having high rates are shown to be sensitive to the size of the spatial filtering units. There is no correlation between infant mortality and birth defect rates in the region. The significance of areas with high rates is determined by a Monte Carlo simulation procedure. One area of high infant mortality is found in the region, which contrasts with many smaller areas with high birth defect rates in the region. The observed birth defect rate pattern is consistent with the hypothesis that each birth was equally likely to result in a birth defect, while the infant mortality pattern is unlikely to be the result of such an equal likelihood process.

Congenital Abnormalities↗