How robust are the estimated effects of air pollution on health? Accounting for model uncertainty using Bayesian model averaging

Berrocal, 2010, A spatio-temporal downscaler for output from numerical models, J Agric Biol Environ Stat, 15, 176, 10.1007/s13253-009-0004-z Besag, 1991, Bayesian image-restoration, with 2 applications in spatial statistics, Ann Inst Stat Math, 43, 1, 10.1007/BF00116466 Cesaroni, 2014, Long term exposure to ambient air pollution and incidence of acute coronary events: prospective cohort study and meta-analysis in 11 European cohorts from the ESCAPE project, BMJ (Clin Res Ed), 348 Clayton, 1993, Spatial correlation in ecological analysis, Int J Epidemiol, 22, 1193, 10.1093/ije/22.6.1193 Department for the Environment, Food and Rural Affairs, Air quality plans for the achievement of EU air quality limit values for nitrogen dioxide (NO2) in the UK. 2015. URL: https://uk-air.defra.gov.uk/library/no2ten/. [accessed 01.11.15]. Elliott, 2007, Long-term associations of outdoor air pollution with mortality in Great Britain, Thorax, 62, 1088, 10.1136/thx.2006.076851 Fuentes, 2005, Model evaluation and spatial interpolation by Bayesian combination of observations with outputs from numerical models, Biometrics, 61, 36, 10.1111/j.0006-341X.2005.030821.x Haining, 2010, Inference from ecological models: estimating the relative risk of stroke from air pollution exposure using small area data, Spat Spat Tempor Epidemiol, 1, 123, 10.1016/j.sste.2010.03.006 Hoeting, 1999, Bayesian model averaging: a tutorial, Stat Sci, 14, 382 Huang, 2015, An integrated Bayesian model for estimating the long-term health effects of air pollution by fusing modelled and measured pollution data: A case study of nitrogen dioxide concentrations in Scotland, Spat Spat Tempor Epidemiol, 10.1016/j.sste.2015.09.002 Hughes J., Cui X. ngspatial: Fitting the centered autologistic and sparse spatial generalized linear mixed models for areal data. 2015.R package version 1.0–5. Minneapolis, MN Hughes, 2013, Dimension reduction and alleviation of confounding for spatial generalized linear mixed models, J R Stat Soc Ser B, 75, 139, 10.1111/j.1467-9868.2012.01041.x Laurent, 2007, Effect of socioeconomic status on the relationship between atmospheric pollution and mortality, J Epidemiol Commun Health, 61, 665, 10.1136/jech.2006.053611 Lawson, 2012, Bayesian 2-stage space-time mixture modeling with spatial misalignment of the exposure in small area health data, J Agric Biol Environ Stat, 17, 417, 10.1007/s13253-012-0100-3 Lee, 2011, A comparison of conditional autoregressive models used in Bayesian disease mapping, Spat Spat Tempor Epidemiol, 2, 79, 10.1016/j.sste.2011.03.001 Lee, 2013, CARBayes: An R package for Bayesian spatial modeling with conditional autoregressive priors, J Stat Softw, 55, 1, 10.18637/jss.v055.i13 Lee, 2009, Air pollution and health in Scotland: a multicity study, Biostatistics, 10, 409, 10.1093/biostatistics/kxp010 Lee, 2014, A Bayesian localized conditional autoregressive model for estimating the health effects of air pollution, Biometrics, 70, 419, 10.1111/biom.12156 Lee, 2015, Controlling for unmeasured confounding and spatial misalignment in long-term air pollution and health studies, Environmetrics, 10.1002/env.2348 Leroux, 1999, Statistical models in epidemiology, the environment and clinical trials, 135 Mackenbach, 1997, Socioeconomic inequalities in morbidity and mortality in Western Europe. The EU working group on socioeconomic inequalities in health, Lancet, 349, 1655, 10.1016/S0140-6736(96)07226-1 Maheswaran, 2005, Outdoor air pollution and stroke in Sheffield, United Kingdom: a small-area level geographical study, Stroke, 36, 239, 10.1161/01.STR.0000151363.71221.12 Maheswaran, 2012, Outdoor air pollution and incidence of ischemic and hemorrhagic stroke: a small-area level ecological study, Stroke, 43, 22, 10.1161/STROKEAHA.110.610238 McMillan, 2009, Combining numerical model output and particulate data using Bayesian space-time modeling, Environmetrics, 10.1002/env.984 Ministry of Public Health, Mortality and morbidity during the London Smog of December 1952, 95, Her Majesty’s Stationery Office; 1954. Moran, 1950, Notes on continuous stochastic phenomena, Biometrika, 37, 17, 10.1093/biomet/37.1-2.17 Paciorek, 2010, The importance of scale for spatial-confounding bias and precision of spatial regression estimators, Stat Sci Rev J Inst Math Stat, 25, 107 Pannullo, 2015, Improving spatial nitrogen dioxide prediction using diffusion tubes: a case study in West Central Scotland, Atmos Environ, 118, 227, 10.1016/j.atmosenv.2015.08.009 Raftery, 1995, Bayesian model selection in social research, Sociol Methodol, 25, 111, 10.2307/271063 Reich, 2006, Effects of residual smoothing on the posterior of the fixed effects in disease-mapping models, Biometrics, 62, 1197, 10.1111/j.1541-0420.2006.00617.x Rushworth, 2014, A spatio-temporal model for estimating the long-term effects of air pollution on respiratory hospital admissions in Greater London, Spat Spat Tempor Epidemiol, 10, 29, 10.1016/j.sste.2014.05.001 R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing; Vienna, Austria;2015. URL: http://www.R-project.org/. [accessed 10.10.15]. Spiegelhalter, 2002, Bayesian measures of model complexity and fit, J R Stat Soc Ser B Stat Methodol, 64, 583, 10.1111/1467-9868.00353 Wang, 2009, Long-term exposure to gaseous air pollutants and cardio-respiratory mortality in Brisbane, Australia, Geospatial Health, 3, 257, 10.4081/gh.2009.225 Willocks, 2012, Cardiovascular disease and air pollution in Scotland: no association or insufficient data and study design?, BMC Public Health, 12, 227, 10.1186/1471-2458-12-227 World Health Organisation Ambient (outdoor) air quality and health: Fact sheet 313. 2014. URL: http://www.who.int/mediacentre/factsheets/fs313/en/ [accessed 16.10.15].