Methods for calculating population exposure estimates of daily weather

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. The project received contributions from The OzFoodNet of the Australian Department of Health and Ageing, and Dr Gillian Hall. The Bureau of Meteorology provided the climate data as an in-kind contribution under the the Australian Government Department of Health and Ageing's ‘Innovations’ program: ‘Atmospheric Environment and Health’ (NCEPH along with CSIRO, Bureau of Meteorology, University of Sydney and NSW Health).
Type
Activity
Activity Type
Project
Access Privileges
Meteorology and Health
Title
Methods for calculating population exposure estimates of daily weather
Alternate Title
A comparison of methods for calculating population exposure estimates of daily weather for health research
Date activity began
2012
Date the activity ended
2013
Brief Description
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.
Full Description
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. The project received contributions from The OzFoodNet of the Australian Department of Health and Ageing, and Dr Gillian Hall. The Bureau of Meteorology provided the climate data as an in-kind contribution under the the Australian Government Department of Health and Ageing's ‘Innovations’ program: ‘Atmospheric Environment and Health’ (NCEPH along with CSIRO, Bureau of Meteorology, University of Sydney and NSW Health).
Contact Email
Ivan.hanigan@anu.edu.au
Fields of Research
111706 - Epidemiology
Keywords
geographical areas; health; humidity; population; postal areas; postcodes; precipitation; temperature; weather; Environment, Conservation, Land use; rainfall; zones
Publications
uri
http://www.ij-healthgeographics.com/content/5/1/38
A comparison of methods for calculating population exposure estimates of daily weather for health research
Status: Published
Published to:
  • Australian National Data Service