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Open Access Methodology

A comparison of methods for calculating population exposure estimates of daily weather for health research

Ivan Hanigan1*, Gillian Hall2 and Keith BG Dear2

Author Affiliations

1 School of Environmental Research, Charles Darwin University, Darwin, Northern Territory, 0909, Australia

2 National Centre for Epidemiology and Population Health, The Australian National University, Canberra, Australian Capital Territory, 0200, Australia

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International Journal of Health Geographics 2006, 5:38  doi:10.1186/1476-072X-5-38

Published: 13 September 2006

Abstract

Background

To explain the possible effects of exposure to weather conditions on population health outcomes, weather data need to be calculated at a level in space and time that is appropriate for the health data. There are various ways of estimating exposure values from raw data collected at weather stations but the rationale for using one technique rather than another; the significance of the difference in the values obtained; and the effect these have on a research question are factors often not explicitly considered. In this study we compare different techniques for allocating weather data observations to small geographical areas and different options for weighting averages of these observations when calculating estimates of daily precipitation and temperature for Australian Postal Areas. Options that weight observations based on distance from population centroids and population size are more computationally intensive but give estimates that conceptually are more closely related to the experience of the population.

Results

Options based on values derived from sites internal to postal areas, or from nearest neighbour sites – that is, using proximity polygons around weather stations intersected with postal areas – tended to include fewer stations' observations in their estimates, and missing values were common. Options based on observations from stations within 50 kilometres radius of centroids and weighting of data by distance from centroids gave more complete estimates. Using the geographic centroid of the postal area gave estimates that differed slightly from the population weighted centroids and the population weighted average of sub-unit estimates.

Conclusion

To calculate daily weather exposure values for analysis of health outcome data for small areas, the use of data from weather stations internal to the area only, or from neighbouring weather stations (allocated by the use of proximity polygons), is too limited. The most appropriate method conceptually is the use of weather data from sites within 50 kilometres radius of the area weighted to population centres, but a simpler acceptable option is to weight to the geographic centroid.