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Environ Int. 2019 Jul;128:109-115. doi: 10.1016/j.envint.2019.04.009. Epub 2019 May 3.

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.

Author information

1
UK Small Area Health Statistics Unit, MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, W2 1PG, UK. Electronic address: a.freni-sterrantino@imperial.ac.uk.
2
UK Small Area Health Statistics Unit, MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, W2 1PG, UK.
3
MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, Norfolk Place, London W2 1PG, UK; National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Health Impact of Environmental Hazards, Dept Epidemiology and Biostatistics, Imperial College London, UK.
4
UK Small Area Health Statistics Unit, MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, W2 1PG, UK; MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, Norfolk Place, London W2 1PG, UK; National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Health Impact of Environmental Hazards, Dept Epidemiology and Biostatistics, Imperial College London, UK.
5
UK Small Area Health Statistics Unit, MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, W2 1PG, UK; National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Health Impact of Environmental Hazards, Dept Epidemiology and Biostatistics, Imperial College London, UK; Directorate of Public Health and Primary Care, Imperial College Healthcare NHS Trust, London W2 1NY, UK; Centre for Environmental Health and Sustainability, George Davies Centre, Dept of Health Sciences, University of Leicester, UK.
6
MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, Norfolk Place, London W2 1PG, UK.

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.

KEYWORDS:

Bayesian models; Controls; Incinerators; Infant mortality; Interrupted time series; Spatial random effect

PMID:
31039518
DOI:
10.1016/j.envint.2019.04.009
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