81 results found
Freni-Sterrantino A, Ghosh RE, Fecht D, et al., 2019, 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., Environ Int, Vol: 128, Pages: 109-115
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.
Cameletti M, Gómez-Rubio V, Blangiardo M, 2019, Bayesian modelling for spatially misaligned health and air pollution data through the INLA-SPDE approach, Spatial Statistics, Vol: 31, ISSN: 2211-6753
© 2019 Elsevier B.V. In air pollution studies a key issue concerns the change of support: pollutant concentrations are continuous phenomena in space but their measurements are typically available at a finite number of point-referenced monitoring stations or result from numerical models. When linking exposure to health outcomes, the latter are usually available at administrative level, hence on an irregular lattice, providing challenges in terms of data misalignment. In this paper we tackle the change of support problem for air pollution and health studies through a two-stage Bayesian approach; in the first stage our model estimates the air pollution concentration at the area level and then in the second stage it links the exposure to the health outcome, accounting for the uncertainty on the exposure estimates. We show through an extensive and realistic simulation that our model is able to predict the concentration accurately at the administrative level as well as estimate the association between exposure and health outcome. We use the Integrated Nested Laplace Approximation, coupled with the Stochastic Partial Differential Equation method for model implementation. Finally we apply the proposed model to evaluate the effect of NO 2 concentration on hospital admissions for respiratory diseases in the Piemonte region (Italy). We found that the upscaling method and the approach used to propagate uncertainty from the first to the second stage have an impact on the posterior distribution of the relative risk. Moreover, we found a significant increased risk of 1.6% and 1.8% associated with an increase of 10 μg∕m 3 in NO 2 concentration.
Chiaravalloti-Neto F, Alves da Silva R, Zini N, et al., Seroprevalence for dengue virus in a hyperendemic area and associated socioeconomic and demographic factors using a cross-sectional design and a geostatistical approach, state of São Paulo, Brazil., BMC Infectious Diseases, ISSN: 1471-2334
Manica M, Caputo B, Screti A, et al., Applying the N-mixture model approach to estimate mosquito population abundance from monitoring data., Journal of Applied Ecology, ISSN: 0021-8901
Blangiardo M, Pirani M, Kanapka L, et al., 2019, A hierarchical modelling approach to assess multi pollutant effects in time-series studies, PLOS ONE, Vol: 14, ISSN: 1932-6203
Rodriguez de Rivera O, Blangiardo M, Lopez-Quilez A, et al., 2019, Species distribution modelling through Bayesian hierarchical approach, THEORETICAL ECOLOGY, Vol: 12, Pages: 49-59, ISSN: 1874-1738
Font A, Guiseppin L, Blangiardo M, et al., 2019, A tale of two cities: is air pollution improving in Paris and London?, Environ Pollut, Vol: 249, Pages: 1-12
Paris and London are Europe's two megacities and both experience poor air quality with systemic breaches of the NO2 limit value. Policy initiatives have been taken to address this: some European-wide (e.g. Euro emission standards); others local (e.g. Low Emission Zone, LEZ). Trends in NOX, NO2 and particulate matter (PM10, PM2.5) for 2005-2016 in background and roadside locations; and trends in traffic increments were calculated in both cities to address their impact. Trends in traffic counts and the distribution in Euro standards for diesel vehicles were also evaluated. Linear-mixed effect models were built to determine the main determinants of traffic concentrations. There was an overall increase in roadside NO2 in 2005-2009 in both cities followed by a decrease of ∼5% year-1 from 2010. Downward trends were associated with the introduction of Euro V heavy vehicles. Despite NO2 decreasing, at current rates, roads will need 20 (Paris) and 193 years (London) to achieve the European Limit Value (40 μg m-3 annual mean). Euro 5 light diesel vehicles were associated with the decrease in roadside PM10. An increase in motorcycles in London since 2010 contributed to the lack of significant trend in PM2.5 roadside increment in 2010-16.
Wang Y, Pirani M, Hansell AL, et al., 2019, Using ecological propensity score to adjust for missing confounders in small area studies, BIOSTATISTICS, Vol: 20, Pages: 1-16, ISSN: 1465-4644
Ghosh RE, Freni-Sterrantino A, Douglas P, et al., 2019, Fetal growth, stillbirth, infant mortality and other birth outcomes near UK municipal waste incinerators; retrospective population based cohort and case-control study, ENVIRONMENT INTERNATIONAL, Vol: 122, Pages: 151-158, ISSN: 0160-4120
Python A, Illian JB, Jones-Todd CM, et al., 2019, A Bayesian approach to modelling subnational spatial dynamics of worldwide non-state terrorism, 2010-2016, JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY, Vol: 182, Pages: 323-344, ISSN: 0964-1998
Williams D, Haworth J, Blangiardo M, et al., 2019, A Spatiotemporal Bayesian Hierarchical Approach to Investigating Patterns of Confidence in the Police at the Neighborhood Level, GEOGRAPHICAL ANALYSIS, Vol: 51, Pages: 90-110, ISSN: 0016-7363
Boulieri A, Bennett JE, Blangiardo M, 2018, A Bayesian mixture modeling approach for public health surveillance., Biostatistics
Spatial monitoring of trends in health data plays an important part of public health surveillance. Most commonly, it is used to understand the etiology of a public health issue, to assess the impact of an intervention, or to provide detection of unusual behavior. In this article, we present a Bayesian mixture model for public health surveillance, which is able to provide estimates of the disease risk in space and time, and also to detect areas with unusual behavior. The model is designed to deal with a range of spatial and temporal patterns in the data, and with time series of different lengths. We carry out a simulation study to assess the performance of the model under different scenarios, and we compare it against a recently proposed Bayesian model for short time series. Finally, the proposed model is used for surveillance of road traffic accidents data in England over the years 2005-2015.
Rodriguez de Rivera O, Lopez-Quilez A, Blangiardo M, 2018, Assessing the Spatial and Spatio-Temporal Distribution of Forest Species via Bayesian Hierarchical Modeling, FORESTS, Vol: 9, ISSN: 1999-4907
Costa DNCC, Blangiardo M, Rodas LAC, et al., 2018, Canine visceral leishmaniasis in Araçatuba, state of São Paulo, Brazil, and its relationship with characteristics of dogs and their owners: a cross-sectional and spatial analysis using a geostatistical approach., BMC Vet Res, Vol: 14
BACKGROUND: The incidence of visceral leishmaniasis (VL), one of the most important neglected diseases worldwide, is increasing in Brazil. The objectives of this study were to determine the canine VL (CanL) seroprevalence in an urban area of Araçatuba municipality and to evaluate its relationship with the characteristics of dogs and their owners. RESULTS: The CanL seroprevalence in the study area was 0.081 (95% credible interval [CI]: 0.068-0.096). The following covariates/categories were positively associated with the occurrence of a seropositive dog: more than 10 dogs that had lived in the house (odds ratio [OR] = 2.36; 95% CI: 1.03-5.43) (baseline: 0-10 dogs); house with dogs that previously died of VL (OR = 4.85; 95% CI: 2.65-8.86) or died of causes other than old age (OR = 2.26; 95% CI: 1.12-4.46) (baseline: natural or no deaths); dogs that spent the day in a sheltered backyard (OR = 2.14; 95% CI: 1.05-4.40); dogs that spent the day in an unsheltered backyard or the street (OR = 2.67; 95% CI: 1.28-5.57) (baseline: inside home). Spatial dependence among observations occurred within about 45.7 m. CONCLUSIONS: The number of dogs that had lived in the house, previous deaths by VL or other cause, and the place the dog stayed during the day were associated with the occurrence of a VL seropositive dog. The short-distance spatial dependence could be related to the vector characteristics, producing a local neighbourhood VL transmission pattern. The geostatistical approach in a Bayesian context using integrated nested Laplace approximation (INLA) allowed to identify the covariates associated with VL, including its spatially dependent transmission pattern.
Cai Y, Hodgson S, Blangiardo M, et al., 2018, Road traffic noise, air pollution and incident cardiovascular disease: A joint analysis of the HUNT, EPIC-Oxford and UK Biobank cohorts, ENVIRONMENT INTERNATIONAL, Vol: 114, Pages: 191-201, ISSN: 0160-4120
Wilunda C, Yoshida S, Blangiardo M, et al., 2018, Caesarean delivery and anaemia risk in children in 45 low- and middle-income countries, MATERNAL AND CHILD NUTRITION, Vol: 14, ISSN: 1740-8695
Cai Y, Hansell A, Hodgson S, et al., Road traffic noise, air pollution and incident cardiovascular disease: a joint analysis of the HUNT, EPIC-Oxford and UK Biobank cohorts, Environment International, ISSN: 0160-4120
Background: This study aimed to investigate the effects of long-term exposure to road traffic noiseand air pollutionon incident cardiovascular disease (CVD)in three large cohorts: HUNT, EPIC-Oxford and UK Biobank. Methods: In pooled complete-casesample of the three cohorts from Norway and the United Kingdom(N=355,732), 21,081 incident all CVD cases including 5,259ischemic heart disease (IHD)and 2,871cerebrovascular cases were ascertained between baseline (1993-2010)and end of follow-up (2008-2013)through medical recordlinkage. Annual mean 24-hour weighted road traffic noise(Lden) and air pollution (particulate matter with aerodynamic diameter ≤10 μm [PM10],≤2.5 μm [PM2.5]andnitrogen 39dioxide[NO2])exposure at baseline address was modelled using a simplified version of the Common Noise Assessment Methods in Europe (CNOSSOS-EU)and European-wide Land Use Regression models.Individual-level covariate data were harmonised and physically pooled across the three cohorts. Analysis was via Cox proportional hazard model with mutual adjustmentsforboth noise and air pollution andpotential confounders. Results: No significant associations were found between annual mean Ldenand incidentCVD,IHD or cerebrovascular disease in the overall populationexcept that the association withincident IHD was significantamong current-smokers.In the fully adjusted models including adjustmentfor Lden, an interquartile range (IQR) higher PM10(4.1μg/m3) or PM2.5(1.4μg/m3) was associated witha5.8% (95%CI: 2.5%-9.3%) and 3.7% (95%CI: 0.2%-7.4%) higherrisk for all incident CVD respectively. No significant associations were found between NO2and any of the CVD outcomes. Conclusions: We found suggestive evidence of a possible association between road traffic noise and incident IHD, consistent with current literature. Long-term particulate air pollution exposure, even at concentrations below current European air quality standards, w
Smith RB, Fecht D, Gulliver J, et al., 2017, Impact of London's road traffic air and noise pollution on birth weight: retrospective population based cohort study, BMJ-BRITISH MEDICAL JOURNAL, Vol: 359, ISSN: 1756-1833
Cai Y, Hansell AL, Blangiardo M, et al., 2017, Long-termexposure to road traffic noise, ambient air pollution, and cardiovascular risk factors in the HUNT and lifelines cohorts, EUROPEAN HEART JOURNAL, Vol: 38, Pages: 2290-+, ISSN: 0195-668X
Douglas P, Freni-Sterrantino A, Sanchez ML, et al., 2017, Estimating Particulate Exposure from Modern Municipal Waste Incinerators in Great Britain, ENVIRONMENTAL SCIENCE & TECHNOLOGY, Vol: 51, Pages: 7511-7519, ISSN: 0013-936X
Scheelbeek PFD, Chowdhury MAH, Haines A, et al., 2017, Drinking Water Salinity and Raised Blood Pressure: Evidence from a Cohort Study in Coastal Bangladesh, ENVIRONMENTAL HEALTH PERSPECTIVES, Vol: 125, ISSN: 0091-6765
Nomura S, Tsubokura M, Ozaki A, et al., 2017, Towards a Long-Term Strategy for Voluntary-Based Internal Radiation Contamination Monitoring: A Population-Level Analysis of Monitoring Prevalence and Factors Associated with Monitoring Participation Behavior in Fukushima, Japan, INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, Vol: 14, ISSN: 1660-4601
Dehbi H-M, Blangiardo M, Gulliver J, et al., 2017, Air pollution and cardiovascular mortality with over 25 years follow-up: A combined analysis of two British cohorts, ENVIRONMENT INTERNATIONAL, Vol: 99, Pages: 275-281, ISSN: 0160-4120
Python A, Illian J, Jones-Todd C, et al., 2017, Explaining the Lethality of Boko Haram's Terrorist Attacks in Nigeria, 2009-2014: A Hierarchical Bayesian Approach, 3rd Bayesian Young Statisticians Meeting (BAYSM), Publisher: SPRINGER INTERNATIONAL PUBLISHING AG, Pages: 231-239, ISSN: 2194-1009
Cai Y, Hodgson S, Blangiardo M, et al., 2017, Ambient Air Pollution, Traffic Noise And Adult-Onset Asthma: The Hunt Study, Norway, International Conference of the American-Thoracic-Society (ATS), Publisher: AMER THORACIC SOC, ISSN: 1073-449X
Cai Y, Zijlema WL, Doiron D, et al., 2017, Ambient air pollution, traffic noise and adult asthma prevalence: a BioSHaRE approach, EUROPEAN RESPIRATORY JOURNAL, Vol: 49, ISSN: 0903-1936
Halonen JI, Dehbi H-M, Hansell AL, et al., 2017, Associations of night-time road traffic noise with carotid intima-media thickness and blood pressure: The Whitehall II and SABRE study cohorts, ENVIRONMENT INTERNATIONAL, Vol: 98, Pages: 54-61, ISSN: 0160-4120
Boulieri A, Liverani S, de Hoogh K, et al., 2017, A space-time multivariate Bayesian model to analyse road traffic accidents by severity, JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY, Vol: 180, Pages: 119-139, ISSN: 0964-1998
Boulieri A, Hansell A, Blangiardo M, 2016, Investigating trends in asthma and COPD through multiple data sources: A small area study, SPATIAL AND SPATIO-TEMPORAL EPIDEMIOLOGY, Vol: 19, Pages: 28-36, ISSN: 1877-5845
Hansell A, Ghosh R, Blangiardo M, et al., 2016, Respiratory mortality risks in England and Wales associated with air pollution exposures up to 38 years previously, Publisher: EUROPEAN RESPIRATORY SOC JOURNALS LTD, ISSN: 0903-1936
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