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Mandal S, Rajiva A, Kloog I, Menon JS, Lane KJ, Amini H, Walia GK, Dixit S, Nori-Sarma A, Dutta A, Sharma P, Jaganathan S, Madhipatla KK, Wellenius GA, de Bont J, Venkataraman C, Prabhakaran D, Prabhakaran P, Ljungman P, Schwartz J. Nationwide estimation of daily ambient PM 2.5 from 2008 to 2020 at 1 km 2 in India using an ensemble approach. PNAS NEXUS 2024; 3:pgae088. [PMID: 38456174 PMCID: PMC10919890 DOI: 10.1093/pnasnexus/pgae088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 02/16/2024] [Indexed: 03/09/2024]
Abstract
High-resolution assessment of historical levels is essential for assessing the health effects of ambient air pollution in the large Indian population. The diversity of geography, weather patterns, and progressive urbanization, combined with a sparse ground monitoring network makes it challenging to accurately capture the spatiotemporal patterns of ambient fine particulate matter (PM2.5) pollution in India. We developed a model for daily average ambient PM2.5 between 2008 and 2020 based on monitoring data, meteorology, land use, satellite observations, and emissions inventories. Daily average predictions at each 1 km × 1 km grid from each learner were ensembled using a Gaussian process regression with anisotropic smoothing over spatial coordinates, and regression calibration was used to account for exposure error. Cross-validating by leaving monitors out, the ensemble model had an R2 of 0.86 at the daily level in the validation data and outperformed each component learner (by 5-18%). Annual average levels in different zones ranged between 39.7 μg/m3 (interquartile range: 29.8-46.8) in 2008 and 30.4 μg/m3 (interquartile range: 22.7-37.2) in 2020, with a cross-validated (CV)-R2 of 0.94 at the annual level. Overall mean absolute daily errors (MAE) across the 13 years were between 14.4 and 25.4 μg/m3. We obtained high spatial accuracy with spatial R2 greater than 90% and spatial MAE ranging between 7.3-16.5 μg/m3 with relatively better performance in urban areas at low and moderate elevation. We have developed an important validated resource for studying PM2.5 at a very fine spatiotemporal resolution, which allows us to study the health effects of PM2.5 across India and to identify areas with exceedingly high levels.
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Affiliation(s)
- Siddhartha Mandal
- Centre for Chronic Disease Control, New Delhi 110016, India
- Public Health Foundation of India, New Delhi 110017, India
| | - Ajit Rajiva
- Public Health Foundation of India, New Delhi 110017, India
| | - Itai Kloog
- Department of Environmental, Geoinformatics and Urban Planning Sciences, Ben Gurion University of the Negev, Beer Sheva 84105, Israel
| | - Jyothi S Menon
- Public Health Foundation of India, New Delhi 110017, India
| | - Kevin J Lane
- Department of Environmental Health, Boston University School of Public Health, Boston, MA 02118, USA
| | - Heresh Amini
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Gagandeep K Walia
- Centre for Chronic Disease Control, New Delhi 110016, India
- Public Health Foundation of India, New Delhi 110017, India
| | - Shweta Dixit
- Public Health Foundation of India, New Delhi 110017, India
| | - Amruta Nori-Sarma
- Department of Environmental Health, Boston University School of Public Health, Boston, MA 02118, USA
| | - Anubrati Dutta
- Centre for Chronic Disease Control, New Delhi 110016, India
- Public Health Foundation of India, New Delhi 110017, India
| | - Praggya Sharma
- Centre for Chronic Disease Control, New Delhi 110016, India
| | - Suganthi Jaganathan
- Centre for Chronic Disease Control, New Delhi 110016, India
- Public Health Foundation of India, New Delhi 110017, India
- Institute of Environmental Medicine, Karolinska Institute, Stockholm 17177, Sweden
| | - Kishore K Madhipatla
- Center for Atmospheric Particle Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Gregory A Wellenius
- Department of Environmental Health, Boston University School of Public Health, Boston, MA 02118, USA
| | - Jeroen de Bont
- Institute of Environmental Medicine, Karolinska Institute, Stockholm 17177, Sweden
| | - Chandra Venkataraman
- Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai 400076, India
| | - Dorairaj Prabhakaran
- Centre for Chronic Disease Control, New Delhi 110016, India
- Public Health Foundation of India, New Delhi 110017, India
| | - Poornima Prabhakaran
- Centre for Chronic Disease Control, New Delhi 110016, India
- Public Health Foundation of India, New Delhi 110017, India
| | - Petter Ljungman
- Institute of Environmental Medicine, Karolinska Institute, Stockholm 17177, Sweden
- Department of Cardiology, Danderyd Hospital, Stockholm 18257, Sweden
| | - Joel Schwartz
- Department of Environmental Health, Harvard TH Chan School of Public Health, Harvard University, Boston, MA 02115, USA
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Abstract
BACKGROUND Air pollution cohort studies are frequently analyzed in two stages, first modeling exposure then using predicted exposures to estimate health effects in a second regression model. The difference between predicted and unobserved true exposures introduces a form of measurement error in the second stage health model. Recent methods for spatial data correct for measurement error with a bootstrap and by requiring the study design ensure spatial compatibility, that is, monitor and subject locations are drawn from the same spatial distribution. These methods have not previously been applied to spatiotemporal exposure data. METHODS We analyzed the association between fine particulate matter (PM2.5) and birth weight in the US state of Georgia using records with estimated date of conception during 2002-2005 (n = 403,881). We predicted trimester-specific PM2.5 exposure using a complex spatiotemporal exposure model. To improve spatial compatibility, we restricted to mothers residing in counties with a PM2.5 monitor (n = 180,440). We accounted for additional measurement error via a nonparametric bootstrap. RESULTS Third trimester PM2.5 exposure was associated with lower birth weight in the uncorrected (-2.4 g per 1 μg/m difference in exposure; 95% confidence interval [CI]: -3.9, -0.8) and bootstrap-corrected (-2.5 g, 95% CI: -4.2, -0.8) analyses. Results for the unrestricted analysis were attenuated (-0.66 g, 95% CI: -1.7, 0.35). CONCLUSIONS This study presents a novel application of measurement error correction for spatiotemporal air pollution exposures. Our results demonstrate the importance of spatial compatibility between monitor and subject locations and provide evidence of the association between air pollution exposure and birth weight.
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Turner MC, Vineis P, Seleiro E, Dijmarescu M, Balshaw D, Bertollini R, Chadeau-Hyam M, Gant T, Gulliver J, Jeong A, Kyrtopoulos S, Martuzzi M, Miller GW, Nawrot T, Nieuwenhuijsen M, Phillips DH, Probst-Hensch N, Samet J, Vermeulen R, Vlaanderen J, Vrijheid M, Wild C, Kogevinas M. EXPOsOMICS: final policy workshop and stakeholder consultation. BMC Public Health 2018; 18:260. [PMID: 29448939 PMCID: PMC5815236 DOI: 10.1186/s12889-018-5160-z] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2017] [Accepted: 02/06/2018] [Indexed: 11/25/2022] Open
Abstract
The final meeting of the EXPOsOMICS project “Final Policy Workshop and Stakeholder Consultation” took place 28–29 March 2017 to present the main results of the project and discuss their implications both for future research and for regulatory and policy activities. This paper summarizes presentations and discussions at the meeting related with the main results and advances in exposome research achieved through the EXPOsOMICS project; on other parallel research initiatives on the study of the exposome in Europe and in the United States and their complementarity to EXPOsOMICS; lessons learned from these early studies on the exposome and how they may shape the future of research on environmental exposure assessment; and finally the broader implications of exposome research for risk assessment and policy development on environmental exposures. The main results of EXPOsOMICS in relation to studies of the external exposome and internal exposome in relation to both air pollution and water contaminants were presented as well as new technologies for environmental health research (adductomics) and advances in statistical methods. Although exposome research strengthens the scientific basis for policy development, there is a need in terms of showing added value for public health to: improve communication of research results to non-scientific audiences; target research to the broader landscape of societal challenges; and draw applicable conclusions. Priorities for future work include the development and standardization of methodologies and technologies for assessing the external and internal exposome, improved data sharing and integration, and the demonstration of the added value of exposome science over conventional approaches in answering priority policy questions.
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Affiliation(s)
- Michelle C Turner
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.,McLaughlin Centre for Population Health Risk Assessment, University of Ottawa, Ottawa, Canada
| | - Paolo Vineis
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, Norfolk Place, W2 1PG, London, UK.
| | | | - Michaela Dijmarescu
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, Norfolk Place, W2 1PG, London, UK
| | - David Balshaw
- National Institute of Environmental Health Sciences, Research Triangle Park, Durham, North Carolina, USA
| | - Roberto Bertollini
- Former WHO Chief Scientist and Representative to the European Union, Brussels, Belgium
| | - Marc Chadeau-Hyam
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, Norfolk Place, W2 1PG, London, UK
| | | | - John Gulliver
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, Norfolk Place, W2 1PG, London, UK
| | - Ayoung Jeong
- University of Basel, Swiss Tropical and Public Health Institute, Basel, Switzerland
| | | | | | | | | | - Mark Nieuwenhuijsen
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | | | - Nicole Probst-Hensch
- University of Basel, Swiss Tropical and Public Health Institute, Basel, Switzerland
| | | | | | | | - Martine Vrijheid
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | | | - Manolis Kogevinas
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
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Barceló MA, Varga D, Tobias A, Diaz J, Linares C, Saez M. Long term effects of traffic noise on mortality in the city of Barcelona, 2004-2007. ENVIRONMENTAL RESEARCH 2016; 147:193-206. [PMID: 26894815 DOI: 10.1016/j.envres.2016.02.010] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2015] [Revised: 02/05/2016] [Accepted: 02/05/2016] [Indexed: 06/05/2023]
Abstract
Numerous studies showing statistically significant associations between environmental noise and adverse health effects already exist for short-term (over one day at most) and long-term (over a year or more) noise exposure, both for morbidity and (albeit to a lesser extent) mortality. Recently, several studies have shown this association to be independent from confounders, mainly those of air pollutants. However, what has not been addressed is the problem of misalignment (i.e. the exposure data locations and health outcomes have different spatial locations). Without any explicit control of such misalignment inference is seriously compromised. Our objective is to assess the long-term effects of traffic noise on mortality in the city of Barcelona (Spain) during 2004-2007. We take into account the control of confounding, for both air pollution and socioeconomic factors at a contextual level and, in particular, we explicitly address the problem of misalignment. We employed a case-control design with individual data. We used deaths resulting from myocardial infarction, hypertension, or Type II diabetes mellitus in Barcelona between 2004 and 2007 as cases for the study, while for controls we used deaths (likewise in Barcelona and over the same period of time) resulting from AIDS or external causes (e.g. accidental falls, accidental poisoning by psychotropic drugs, drugs of abuse, suicide and self-harm, or injuries resulting from motor vehicle accidents). The controls were matched with the cases by sex and age. We used the annual average equivalent A-weighted sound pressure levels for daytime (7-21h), evening-time (21-23h) and night-time (23-7h), and controlled for the following confounders: i) air pollutants (NO2, PM10 and benzene), ii) material deprivation (at a census tract level) and iii) land use and other spatial variables. We explicitly controlled for heterogeneity (uneven distribution of both response and environmental exposures within an area), spatial dependency (of the observations of the response variables), temporal trends (long-term behaviour of the response variables) and spatial misalignment (between response and environmental exposure locations). We used a fully Bayesian method, through the Integrated Nested Laplace Approximation (INLA). Specifically, we plugged the whole model for the exposure into the health model and obtained a linear predictor defined on the entire spatial domain. Separate analyses were carried out for men and for women. After adjusting for confounders, we found that traffic noise was associated with myocardial infarction mortality along with Type II diabetes mellitus in men (in both cases, odds ratios (OR) were around 1.02) and mortality from hypertension in women (ORs around 1.01). Nevertheless, only in the case of hypertension in women, does the association remain statistically significant for all age groups considered (all ages, ≥65 years and ≥75 years).
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Affiliation(s)
- Maria Antònia Barceló
- Research Group on Statistics, Econometrics and Health (GRECS), University of Girona, Girona, Spain; CIBER of Epidemiology and Public Health (CIBERESP), Spain
| | - Diego Varga
- Research Group on Statistics, Econometrics and Health (GRECS), University of Girona, Girona, Spain
| | - Aurelio Tobias
- Research Group on Statistics, Econometrics and Health (GRECS), University of Girona, Girona, Spain; Institute of Environmental Assessment and Water Research (IDAEA), Spanish Council for Scientific Research (CSIC), Barcelona, Spain
| | - Julio Diaz
- National School of Health, Instituto de Salud Carlos III, Madrid, Spain
| | - Cristina Linares
- National School of Health, Instituto de Salud Carlos III, Madrid, Spain
| | - Marc Saez
- Research Group on Statistics, Econometrics and Health (GRECS), University of Girona, Girona, Spain; CIBER of Epidemiology and Public Health (CIBERESP), Spain.
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