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Title: | Spatial variability of excess mortality during prolonged dust events in a high-density city : a time-stratified spatial regression approach | Authors: | Wong, MS Ho, HC Yang, L Shi, WZ Yang, JX Chan, TC |
Issue Date: | 2017 | Source: | International journal of health geographics, 2017, v. 16, 26, p. 1-14 | Abstract: | Background: Dust events have long been recognized to be associated with a higher mortality risk. However, no study has investigated how prolonged dust events affect the spatial variability of mortality across districts in a downwind city. Methods: In this study, we applied a spatial regression approach to estimate the district-level mortality during two extreme dust events in Hong Kong. We compared spatial and non-spatial models to evaluate the ability of each regression to estimate mortality. We also compared prolonged dust events with non-dust events to determine the influences of community factors on mortality across the city. Results: The density of a built environment (estimated by the sky view factor) had positive association with excess mortality in each district, while socioeconomic deprivation contributed by lower income and lower education induced higher mortality impact in each territory planning unit during a prolonged dust event. Based on the model comparison, spatial error modelling with the 1st order of queen contiguity consistently outperformed other models. The high-risk areas with higher increase in mortality were located in an urban high-density environment with higher socioeconomic deprivation. Conclusion: Our model design shows the ability to predict spatial variability of mortality risk during an extreme weather event that is not able to be estimated based on traditional time-series analysis or ecological studies. Our spatial protocol can be used for public health surveillance, sustainable planning and disaster preparation when relevant data are available. | Keywords: | Spatial analytics Extreme weather event Dust mortality Spatial variability Community vulnerability Geospatial modelling |
Publisher: | BioMed Central | Journal: | International journal of health geographics | ISSN: | 1476-072X | DOI: | 10.1186/s12942-017-0099-3 | Rights: | © The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. The following publication Wong, M. S., Ho, H. C., Yang, L., Shi, W. Z., Yang, J. X., & Chan, T. C. (2017). Spatial variability of excess mortality during prolonged dust events in a high-density city : a time-stratified spatial regression approach. International Journal of Health Geographics, 16, 26, 1-14 is available at https://dx.doi.org/10.1186/s12942-017-0099-3 |
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Wong_Spatial_Variability_Excess.pdf | 2.76 MB | Adobe PDF | View/Open |
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