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

Autor: A. Freni-Sterrantino, R.E. Ghosh, D. Fecht, M.B. Toledano, P. Elliott, A.L. Hansell, M. Blangiardo
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Environment International, Vol 128, Iss , Pp 109-115 (2019)
Druh dokumentu: article
ISSN: 0160-4120
DOI: 10.1016/j.envint.2019.04.009
Popis: 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: Incinerators, Infant mortality, Interrupted time series, Controls, Bayesian models, Spatial random effect
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