Quantifying the impact of current and future concentrations of air pollutants on respiratory disease risk in England
Abstract Background Estimating the long-term health impact of air pollution in a spatio-temporal ecological study requires representative concentrations of air pollutants to be constructed for each geographical unit and time period. Averaging concentrations in space and time is commonly carried out,...
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| Format: | Article |
| Language: | English |
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BMC
2017-03-01
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| Series: | Environmental Health |
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| Online Access: | http://link.springer.com/article/10.1186/s12940-017-0237-1 |
| _version_ | 1811301384177319936 |
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| author | Francesca Pannullo Duncan Lee Lucy Neal Mohit Dalvi Paul Agnew Fiona M. O’Connor Sabyasachi Mukhopadhyay Sujit Sahu Christophe Sarran |
| author_facet | Francesca Pannullo Duncan Lee Lucy Neal Mohit Dalvi Paul Agnew Fiona M. O’Connor Sabyasachi Mukhopadhyay Sujit Sahu Christophe Sarran |
| author_sort | Francesca Pannullo |
| collection | DOAJ |
| description | Abstract Background Estimating the long-term health impact of air pollution in a spatio-temporal ecological study requires representative concentrations of air pollutants to be constructed for each geographical unit and time period. Averaging concentrations in space and time is commonly carried out, but little is known about how robust the estimated health effects are to different aggregation functions. A second under researched question is what impact air pollution is likely to have in the future. Methods We conducted a study for England between 2007 and 2011, investigating the relationship between respiratory hospital admissions and different pollutants: nitrogen dioxide (NO2); ozone (O3); particulate matter, the latter including particles with an aerodynamic diameter less than 2.5 micrometers (PM2.5), and less than 10 micrometers (PM10); and sulphur dioxide (SO2). Bayesian Poisson regression models accounting for localised spatio-temporal autocorrelation were used to estimate the relative risks (RRs) of pollution on disease risk, and for each pollutant four representative concentrations were constructed using combinations of spatial and temporal averages and maximums. The estimated RRs were then used to make projections of the numbers of likely respiratory hospital admissions in the 2050s attributable to air pollution, based on emission projections from a number of Representative Concentration Pathways (RCP). Results NO2 exhibited the largest association with respiratory hospital admissions out of the pollutants considered, with estimated increased risks of between 0.9 and 1.6% for a one standard deviation increase in concentrations. In the future the projected numbers of respiratory hospital admissions attributable to NO2 in the 2050s are lower than present day rates under 3 Representative Concentration Pathways (RCPs): 2.6, 6.0, and 8.5, which is due to projected reductions in future NO2 emissions and concentrations. Conclusions NO2 concentrations exhibit consistent substantial present-day health effects regardless of how a representative concentration is constructed in space and time. Thus as concentrations are predicted to remain above limits set by European Union Legislation until the 2030s in parts of urban England, it will remain a substantial health risk for some time. |
| first_indexed | 2024-04-13T07:07:54Z |
| format | Article |
| id | doaj.art-a37c52670f764e178bf51fda929fb795 |
| institution | Directory Open Access Journal |
| issn | 1476-069X |
| language | English |
| last_indexed | 2024-04-13T07:07:54Z |
| publishDate | 2017-03-01 |
| publisher | BMC |
| record_format | Article |
| series | Environmental Health |
| spelling | doaj.art-a37c52670f764e178bf51fda929fb7952022-12-22T02:56:56ZengBMCEnvironmental Health1476-069X2017-03-0116111410.1186/s12940-017-0237-1Quantifying the impact of current and future concentrations of air pollutants on respiratory disease risk in EnglandFrancesca Pannullo0Duncan Lee1Lucy Neal2Mohit Dalvi3Paul Agnew4Fiona M. O’Connor5Sabyasachi Mukhopadhyay6Sujit Sahu7Christophe Sarran8School of Mathematics and Statistics, University of GlasgowSchool of Mathematics and Statistics, University of GlasgowMet Office, FitzRoy RoadMet Office Hadley Centre, FitzRoy RoadMet Office, FitzRoy RoadMet Office Hadley Centre, FitzRoy RoadMathematical Sciences, University of Southampton, HighfieldMathematical Sciences, University of Southampton, HighfieldMet Office, FitzRoy RoadAbstract Background Estimating the long-term health impact of air pollution in a spatio-temporal ecological study requires representative concentrations of air pollutants to be constructed for each geographical unit and time period. Averaging concentrations in space and time is commonly carried out, but little is known about how robust the estimated health effects are to different aggregation functions. A second under researched question is what impact air pollution is likely to have in the future. Methods We conducted a study for England between 2007 and 2011, investigating the relationship between respiratory hospital admissions and different pollutants: nitrogen dioxide (NO2); ozone (O3); particulate matter, the latter including particles with an aerodynamic diameter less than 2.5 micrometers (PM2.5), and less than 10 micrometers (PM10); and sulphur dioxide (SO2). Bayesian Poisson regression models accounting for localised spatio-temporal autocorrelation were used to estimate the relative risks (RRs) of pollution on disease risk, and for each pollutant four representative concentrations were constructed using combinations of spatial and temporal averages and maximums. The estimated RRs were then used to make projections of the numbers of likely respiratory hospital admissions in the 2050s attributable to air pollution, based on emission projections from a number of Representative Concentration Pathways (RCP). Results NO2 exhibited the largest association with respiratory hospital admissions out of the pollutants considered, with estimated increased risks of between 0.9 and 1.6% for a one standard deviation increase in concentrations. In the future the projected numbers of respiratory hospital admissions attributable to NO2 in the 2050s are lower than present day rates under 3 Representative Concentration Pathways (RCPs): 2.6, 6.0, and 8.5, which is due to projected reductions in future NO2 emissions and concentrations. Conclusions NO2 concentrations exhibit consistent substantial present-day health effects regardless of how a representative concentration is constructed in space and time. Thus as concentrations are predicted to remain above limits set by European Union Legislation until the 2030s in parts of urban England, it will remain a substantial health risk for some time.http://link.springer.com/article/10.1186/s12940-017-0237-1Air pollutionPresent day and future health effectsSpatio-temporal ecological study |
| spellingShingle | Francesca Pannullo Duncan Lee Lucy Neal Mohit Dalvi Paul Agnew Fiona M. O’Connor Sabyasachi Mukhopadhyay Sujit Sahu Christophe Sarran Quantifying the impact of current and future concentrations of air pollutants on respiratory disease risk in England Environmental Health Air pollution Present day and future health effects Spatio-temporal ecological study |
| title | Quantifying the impact of current and future concentrations of air pollutants on respiratory disease risk in England |
| title_full | Quantifying the impact of current and future concentrations of air pollutants on respiratory disease risk in England |
| title_fullStr | Quantifying the impact of current and future concentrations of air pollutants on respiratory disease risk in England |
| title_full_unstemmed | Quantifying the impact of current and future concentrations of air pollutants on respiratory disease risk in England |
| title_short | Quantifying the impact of current and future concentrations of air pollutants on respiratory disease risk in England |
| title_sort | quantifying the impact of current and future concentrations of air pollutants on respiratory disease risk in england |
| topic | Air pollution Present day and future health effects Spatio-temporal ecological study |
| url | http://link.springer.com/article/10.1186/s12940-017-0237-1 |
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