Statistical methods for investigating and controlling for weather-health dependences in time series data

Lead Research Organisation: London Sch of Hygiene and Trop Medicine
Department Name: Public Health and Policy

Abstract

Interest has grown recently on the effects of weather, especially temperature, on health. One cause of this is the concern over health effects of global climate change. Another is the emergence, mostly as a by-product of studies of air pollution and health, of evidence pointing to substantial importance of weather in causing poor health – in particular events such as death or admission to hospitalisation. Although variation in health according to season have long been known, the details of this relationship remain only partly understood.
Studies to estimate health effects of weather and of climate change depend heavily on complex statistical methods. These are currently poorly developed, so we propose in this research project to improve them.
This research will improve the ability of future studies to identify with confidence the effects of weather and climate. Improving this knowledge will help us develop policies to reduce effects of weather and future changes in climate on our health.

Technical Summary

There is convincing evidence that weather, primarily temperature, substantially affects several health outcomes, but many details are unclear. Concerns over effects of climate change have increased interest in this association. The primary source of evidence on weather-effects is from studies of associations between variations in health and in weather over time. Statistical methods for investigating such time series have recently been enormously developed in the context of studies of air pollution and health. However, these methods are subject to ongoing debate, and aspects of their application to weather are undeveloped. Furthermore control for weather effects is one of the most debated points of air pollution studies.

We propose to identify, clarify, and develop new methods for investigating the relationship of weather and health. In particular we will clarify best methods to control confounding, model the typically non-linear and multi-lag association of outcomes with temperature, estimate the extent to which excess outcomes are due to short term displacement (?harvesting?), and investigate modifiers of weather effects. We will address these objectives by exploratory analyses on real data, analytic clarification of model properties, and simulations. Completing this work will improve capacity to clarify weather-health effects and control confounding by them in pollution studies.

Publications

10 25 50

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Armstrong BG (2011) Association of mortality with high temperatures in a temperate climate: England and Wales. in Journal of epidemiology and community health

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Gasparrini A (2012) The effect of high temperatures on cause-specific mortality in England and Wales. in Occupational and environmental medicine

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Gasparrini A (2011) Distributed Lag Linear and Non-Linear Models in R: The Package dlnm. in Journal of statistical software

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Gasparrini A (2010) Distributed lag non-linear models. in Statistics in medicine

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Gasparrini A (2011) The impact of heat waves on mortality. in Epidemiology (Cambridge, Mass.)

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Gasparrini A (2013) Reducing and meta-analysing estimates from distributed lag non-linear models in BMC Medical Research Methodology

 
Description Climate Resilience of Care Settings
Amount £251,957 (GBP)
Funding ID NE/S016767/1 
Organisation Natural Environment Research Council 
Sector Public
Country United Kingdom
Start 02/2019 
End 01/2020
 
Description Research Methodology Fellowship
Amount £276,364 (GBP)
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start 12/2011 
End 12/2014
 
Title dlnm R package 
Description The computer package for the public-domain R statistical environment, written by Antonio Gasparrini, implements the distributed lag non-linear models that we have presented in our research publications. 
Type Of Material Data analysis technique 
Year Produced 2009 
Provided To Others? Yes  
Impact Researchers have noted their use of this technique/package in acknowledgements in published papers (at least 30 publications from other research teams) 
 
Title mvmeta R package 
Description The computer package for the public-domain R statistical environment, written by Antonio Gasparrini, implements the multivariate meta-analysis models that we have presented in our research publications. 
Type Of Material Data analysis technique 
Year Produced 2011 
Provided To Others? Yes  
Impact Given the encouraging feedback from other research teams about the other R package dlnm. I expect this new tool to have a similar impact. 
 
Title dlnm R package 
Description The computer package for the public-domain R statistical environment, written by Antonio Gasparrini, implements the distributed lag non-linear models that we have presented in our research publications. 
IP Reference  
Protection Copyrighted (e.g. software)
Year Protection Granted 2009
Licensed Yes
Impact The R package is released under the GNU General Public License. The package and the source code can be therefore used or modified without permission (as long as the author is properly acknowledged) under the same license terms. Researchers have noted their use of this technique/package in acknowledgements in published papers (at least 30 publications from other research teams).
 
Title mvmeta R package 
Description The computer package for the public-domain R statistical environment, written by Antonio Gasparrini, implements the multivariate meta-analysis models that we have presented in our research publications. 
IP Reference  
Protection Copyrighted (e.g. software)
Year Protection Granted 2011
Licensed Yes
Impact The R package is released under the GNU General Public License. The package and the source code can be therefore used or modified without permission (as long as the author is properly acknowledged) under the same license terms.
 
Description Heatwave seminar of Health Protection Agency 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Primary Audience Health professionals
Results and Impact The meeting was attended by some 40 persons from Government departments, Local Authorities, and various health agencies, as well as universities. The purpose of the presentations was to inform policy and practice in preventing adverse health effects of heat.

Not known
Year(s) Of Engagement Activity 2010
 
Description Seminar at the Health Protection Agency - Chilton 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Primary Audience Health professionals
Results and Impact 6 among statisticians and other health professional conducting studies at HPA, who were potentially interested in the application of methodologies developed within the research project.

Potential for future collaborations on analysis of existing datasets in HPA
Year(s) Of Engagement Activity 2011