Associations Between Metal Constituents of Ambient Particulate Matter and Mortality in England: an Ecological Study

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Associations Between Metal Constituents of Ambient Particulate Matter and Mortality in England: an Ecological Study Open access Original research BMJ Open: first published as 10.1136/bmjopen-2019-030140 on 3 December 2019. Downloaded from Associations between metal constituents of ambient particulate matter and mortality in England: an ecological study Aurore Lavigne,1 Anna Freni Sterrantino ,2 Silvia Liverani,3 Marta Blangiardo,2 Kees de Hoogh,4,5 John Molitor,6 Anna Hansell 7 To cite: Lavigne A, Freni ABSTRACT Strengths and limitations of this study Sterrantino A, Liverani S, Objectives To investigate long- term associations between et al. Associations between metal components of particulate matter (PM) and mortality ► One of the largest studies to explore exposure to metal constituents of and lung cancer incidence. ambient particulate matter metal components of ambient air in relation to mor- Design Small area (ecological) study. and mortality in England: an tality and lung cancer incidence, with 13.6 million Setting Population living in all wards (~9000 individuals ecological study. BMJ Open population. per ward) in the London and Oxford area of England, 2019;9:e030140. doi:10.1136/ ► A large number of cases: 108 478 cardiovascular comprising 13.6 million individuals. bmjopen-2019-030140 disease deaths, 48 483 respiratory deaths and 24 Exposure and outcome measures We used land 849 incident cases of lung cancer in the study pe- ► Prepublication history and use regression models originally used in the Transport additional material for this riod and area, providing good statistical power to related Air Pollution and Health Impacts—Integrated paper are available online. To examine small excess risks. Methodologies for Assessing Particulate Matter study to view these files, please visit ► Established exposure models, developed and evalu- estimate exposure to copper, iron and zinc in ambient the journal online (http:// dx. doi. ated with measurements from a standardised mon- copyright. air PM. We examined associations of metal exposure org/ 10. 1136/ bmjopen- 2019- itoring campaign. 030140). with Office for National Statistics mortality data from ► An ecological study using registry data, without ac- cardiovascular disease (CVD) and respiratory causes and cess to individual-level confounders other than age AL and AFS are joint first with lung cancer incidence during 2008–2011. and sex. authors. Results There were 108 478 CVD deaths, 48 483 ► Metals were very highly correlated so multipollutant respiratory deaths and 24 849 incident cases of lung http://bmjopen.bmj.com/ Received 28 February 2019 models could not be used. Revised 22 October 2019 cancer in the study period and area. Using Poisson Accepted 05 November 2019 regression models adjusted for area- level deprivation, tobacco sales and ethnicity, we found associations lung cancer or respiratory mortality.6 It has between cardiovascular mortality and PM copper with 2.5 been suggested that metal components of PM interdecile range (IDR 2.6–5.7 ng/m3) and IDR relative may in part be responsible for toxic effects of risk (RR) 1.005 (95%CI 1.001 to 1.009) and between air pollution on the cardiovascular and respi- respiratory mortality and PM10 zinc (IDR 1135–153 ng/ 7 m3) and IDR RR 1.136 (95%CI 1.010 to 1.277). We did not ratory system. find relevant associations for lung cancer incidence. Metal In the Transport related Air Pollution and on December 13, 2019 at Basel University. Protected by elements were highly correlated. Health Impacts—Integrated Methodologies Conclusion Our analysis showed small but not fully for Assessing Particulate Matter (TRANS- consistent adverse associations between mortality and PHORM) study, copper zinc and iron content particulate metal exposures likely derived from non- of PM (PM10 and PM2.5) were found to be tailpipe road traffic emissions (brake and tyre wear), associated—positively and significantly—with which have previously been associated with increases in increases in inflammatory markers in the inflammatory markers in the blood. blood,8 which might be expected to be associ- ated with increased risks of cardiovascular and other diseases. However, a separate TRANS- © Author(s) (or their 9 employer(s)) 2019. Re- use INTRODUCTION PHORM study analysis of 19 cohorts with permitted under CC BY. Chronic exposure to toxic substances in partic- 9545 CVD deaths did not find any statistically Published by BMJ. ulate matter (PM) with aerodynamic diameter significant associations with metal (or other) For numbered affiliations see 1–3 4 less than 10 µm (PM10) and 2.5 µm (PM2.5) particulate components (PM10 or PM2.5). Here end of article. is associated with increased mortality levels we use the same data sets to examine associa- 1 5 Correspondence to from cardiovascular disease (CVD). Some tions with mortality using a much larger data 9 Dr Anna Hansell; studies also show links between this long- term set than TRANSPHORM study, to estimate ah618@ leicester. ac. uk exposure to traffic- related air pollution and particulate metal exposures for a population Lavigne A, et al. BMJ Open 2019;9:e030140. doi:10.1136/bmjopen-2019-030140 1 Open access BMJ Open: first published as 10.1136/bmjopen-2019-030140 on 3 December 2019. Downloaded from In the analyses, we used copper (Cu), iron (Fe) and zinc (Zn) in the PM10 fraction and copper and iron in 12 the PM2.5 fraction, all linked to non- tailpipe emissions. LUR models for this selection of elements showed a good leave- one- out validation, explaining more than 77% (R2) of the observed variability. Confounder data—deprivation, ethnicity and smoking data To adjust for possible confounders in this study, we included area- level ethnicity from Census 2011 and accounted for percent of White and Asian people per ward as covariates in the models. We also used the 2007 index of multiple deprivation (IMD) as a relative measure of area- level deprivation (publicly available from the Department for Communities and Local Government Figure 1 Study area compromising London and Oxford data. gov. uk). This combines seven domains: ‘income’, areas, with major roads and motorways. In the inset the area ‘employment’, ‘education’, ‘barriers to housing and localisation with regard to England map contains National services’, ‘crime’, ‘health’ and ‘living environment’. The Statistics data, Crown copyright and database right 2018; latter is divided into two subdomains: ‘indoor’ measuring contains OS data, Crown copyright and database right 2018. the quality of housing and ‘outdoor’ linked to air quality All rights reserved. and road traffic accidents.13 We excluded from the study the ‘health’ and ‘outdoor living environment’ domains,14 since we examined associations between health outcomes of 13.6 million living in and near London, England, with and air pollution measures. The remaining domains were 108478 CVD deaths and additionally 48 483 respiratory linearly combined to generate a ‘modified IMD’ relative deaths and 24 849 incident cases of lung cancer. score used in the analysis. High values of the modified IMD indicate higher deprivation. As a proxy for smoking, METHODS we used ward level tobacco expenditure (pounds/week/ copyright. Our study region covered a 10 782 km2 area around inhabitant) data obtained from CACI (CACI tobacco London and Oxford (figure 1) in 1533 wards, an English expenditure data are copyright 1996–2014 CACI Ltd.). Census area classification (primary unit of the English electoral geography) with a mean surface area ~7.0 km2 Health data and average 8892 inhabitants per ward, in our study Mortality counts for cardiovascular (International Classi- http://bmjopen.bmj.com/ period. fication of Diseases, Tenth Revision (ICD10) I00- I99) and respiratory (CDC10 J00- J99) disease and lung cancer inci- Exposure data dence counts (C33 and C34 ICD10 codes) were extracted In the region of London and Oxford PM was monitored for 2008–2011 from Office National Statistics data held during the years 2010–2011 as part of the European by the Small Area Health Statistics Unit, which provide Study of Cohorts and Air Pollution Effects (ESCAPE) 100% coverage of deaths. The counts were then adjusted 10 11 project. Filters measuring PM10 and PM2.5 from the by sex and 5- year age band. ESCAPE project were analysed for elemental compo- on December 13, 2019 at Basel University. Protected by sition and de Hoogh et al (2013)12 developed land use Patient and public involvement regression (LUR) models for a number of the elemental Patients were not involved in the development of the components including metals as part of the TRANS- research question or the design and conducting of the PHORM project. These models were used to predict PM10 study. and PM2.5 elemental composition for our study popula- tion for 2010–2011. In brief, 20 sites were monitored for Statistical analysis 10 three 2- week periods and PM2.5 and PM10 were separately The effect of PM exposure to copper, iron and zinc on collected using Harvard impactors. Their elemental health outcomes was analysed with Poisson regression composition was analysed using energy dispersive X-ray (a generalised linear model) of count data at small area fluorescence. The association of PM elemental compo- (ward) level, implemented in a Bayesian framework nents with land use covariates relative to traffic, popula- with spatial residuals, see online supplementary figure tion, industry, or nature was evaluated with LUR models. 1 for a graphical representation of the possible causal Then, local estimates at the postcode level were predicted mechanism. and aggregated at the super output area (SOA) level, with Let Yi denote the number of cases recorded in the spatial a population- weighted mean, for all SOAs in the study. unit i and Ei the expected count taking into account the Exposure was assigned for each case or incidence at post- age and sex structure of the population at risk (internal code level. standardisation). Then, using Poisson regression, Yi is 2 Lavigne A, et al. BMJ Open 2019;9:e030140.
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