Bayesian spatial modelling for quasi-experimental designs: an interrupted time series study of the opening of Municipal Waste Incinerators in relation to infant mortality and sex ratio
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Supporting information
Published version
Author(s)
Type
Journal Article
Abstract
Background
There is limited evidence on potential health risks from Municipal Waste Incinerators (MWIs), and previous studies on birth outcomes show inconsistent results. Here, we evaluate whether the opening of MWIs is associated with infant mortality and sex ratio in the surrounding areas, extending the Interrupted Time Series (ITS) methodological approach to account for spatial dependencies at the small area level.
Methods
We specified a Bayesian hierarchical model to investigate the annual risks of infant mortality and sex-ratio (female relative to male) within 10 km of eight MWIs in England and Wales, during the period 1996–2012. We included comparative areas matched one-to-one of similar size and area characteristics.
Results
During the study period, infant mortality rates decreased overall by 2.5% per year in England. The opening of an incinerator in the MWI area was associated with −8 deaths per 100,000 infants (95% CI −62, 40) and with a difference in sex ratio of −0.004 (95% CI −0.02, 0.01), comparing the period after opening with that before, corrected for before-after trends in the comparator areas.
Conclusion
Our method is suitable for the analysis of quasi-experimental time series studies in the presence of spatial structure and when there are global time trends in the outcome variable. Based on our approach, we do not find evidence of an association of MWI opening with changes in risks of infant mortality or sex ratio in comparison with control areas.
There is limited evidence on potential health risks from Municipal Waste Incinerators (MWIs), and previous studies on birth outcomes show inconsistent results. Here, we evaluate whether the opening of MWIs is associated with infant mortality and sex ratio in the surrounding areas, extending the Interrupted Time Series (ITS) methodological approach to account for spatial dependencies at the small area level.
Methods
We specified a Bayesian hierarchical model to investigate the annual risks of infant mortality and sex-ratio (female relative to male) within 10 km of eight MWIs in England and Wales, during the period 1996–2012. We included comparative areas matched one-to-one of similar size and area characteristics.
Results
During the study period, infant mortality rates decreased overall by 2.5% per year in England. The opening of an incinerator in the MWI area was associated with −8 deaths per 100,000 infants (95% CI −62, 40) and with a difference in sex ratio of −0.004 (95% CI −0.02, 0.01), comparing the period after opening with that before, corrected for before-after trends in the comparator areas.
Conclusion
Our method is suitable for the analysis of quasi-experimental time series studies in the presence of spatial structure and when there are global time trends in the outcome variable. Based on our approach, we do not find evidence of an association of MWI opening with changes in risks of infant mortality or sex ratio in comparison with control areas.
Date Issued
2019-07-01
Date Acceptance
2019-04-03
Citation
Environment International, 2019, 128, pp.109-115
ISSN
0160-4120
Publisher
Elsevier
Start Page
109
End Page
115
Journal / Book Title
Environment International
Volume
128
Copyright Statement
© 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/BY/4.0/)
Sponsor
Public Health England
Medical Research Council (MRC)
National Institute for Health Research
Medical Research Council (MRC)
Medical Research Council (MRC)
Imperial College Healthcare NHS Trust- BRC Funding
Grant Number
6509268
MR/L01341X/1
RTJ6219303-1
MR/L01632X/1
MR/L01632X/1
RDF03
Subjects
Bayesian models
Controls
Incinerators
Infant mortality
Interrupted time series
Spatial random effect
Environmental Sciences
MD Multidisciplinary
Publication Status
Published
Date Publish Online
2019-05-03