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Chen J, Braun D, Christidis T, Cork M, Rodopoulou S, Samoli E, Stafoggia M, Wolf K, Wu X, Yuchi W, Andersen ZJ, Atkinson R, Bauwelinck M, de Hoogh K, Janssen NA, Katsouyanni K, Klompmaker JO, Kristoffersen DT, Lim YH, Oftedal B, Strak M, Vienneau D, Zhang J, Burnett RT, Hoek G, Dominici F, Brauer M, Brunekreef B. Long-Term Exposure to Low-Level PM2.5 and Mortality: Investigation of Heterogeneity by Harmonizing Analyses in Large Cohort Studies in Canada, United States, and Europe. Environ Health Perspect 2023; 131:127003. [PMID: 38039140 PMCID: PMC10691665 DOI: 10.1289/ehp12141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 08/10/2023] [Accepted: 11/09/2023] [Indexed: 12/03/2023]
Abstract
BACKGROUND Studies across the globe generally reported increased mortality risks associated with particulate matter with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ) exposure with large heterogeneity in the magnitude of reported associations and the shape of concentration-response functions (CRFs). We aimed to evaluate the impact of key study design factors (including confounders, applied exposure model, population age, and outcome definition) on PM 2.5 effect estimates by harmonizing analyses on three previously published large studies in Canada [Mortality-Air Pollution Associations in Low Exposure Environments (MAPLE), 1991-2016], the United States (Medicare, 2000-2016), and Europe [Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE), 2000-2016] as much as possible. METHODS We harmonized the study populations to individuals 65 + years of age, applied the same satellite-derived PM 2.5 exposure estimates, and selected the same sets of potential confounders and the same outcome. We evaluated whether differences in previously published effect estimates across cohorts were reduced after harmonization among these factors. Additional analyses were conducted to assess the influence of key design features on estimated risks, including adjusted covariates and exposure assessment method. A combined CRF was assessed with meta-analysis based on the extended shape-constrained health impact function (eSCHIF). RESULTS More than 81 million participants were included, contributing 692 million person-years of follow-up. Hazard ratios and 95% confidence intervals (CIs) for all-cause mortality associated with a 5 - μ g / m 3 increase in PM 2.5 were 1.039 (1.032, 1.046) in MAPLE, 1.025 (1.021, 1.029) in Medicare, and 1.041 (1.014, 1.069) in ELAPSE. Applying a harmonized analytical approach marginally reduced difference in the observed associations across the three studies. Magnitude of the association was affected by the adjusted covariates, exposure assessment methodology, age of the population, and marginally by outcome definition. Shape of the CRFs differed across cohorts but generally showed associations down to the lowest observed PM 2.5 levels. A common CRF suggested a monotonically increased risk down to the lowest exposure level. https://doi.org/10.1289/EHP12141.
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Affiliation(s)
- Jie Chen
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
| | - Danielle Braun
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Tanya Christidis
- Health Analysis Division, Statistics Canada, Ottawa, Ontario, Canada
| | - Michael Cork
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Sophia Rodopoulou
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodstrian University of Athens, Athens, Greece
| | - Evangelia Samoli
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodstrian University of Athens, Athens, Greece
| | - Massimo Stafoggia
- Department of Epidemiology, Lazio Region Health Service/ASL Roma 1, Rome, Italy
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Kathrin Wolf
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Xiao Wu
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Weiran Yuchi
- School of Population and Public Health, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Zorana J. Andersen
- Section of Environmental Health, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Richard Atkinson
- Population Health Research Institute, St George’s, University of London, London, UK
| | - Mariska Bauwelinck
- Interface Demography, Department of Sociology, Vrije Universiteit Brussel, Brussels, Belgium
| | - Kees de Hoogh
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Nicole A.H. Janssen
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Klea Katsouyanni
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodstrian University of Athens, Athens, Greece
- MRC Center for Environment and Health, Environmental Research Group, School of Public Health, Imperial College London, London, UK
| | - Jochem O. Klompmaker
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Doris Tove Kristoffersen
- Division of Climate and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Youn-Hee Lim
- Section of Environmental Health, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Bente Oftedal
- Division of Climate and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Maciej Strak
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Danielle Vienneau
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Jiawei Zhang
- Section of Environmental Health, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | | | - Gerard Hoek
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
| | - Francesca Dominici
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Michael Brauer
- School of Population and Public Health, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Bert Brunekreef
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
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Yuchi W, Brauer M, Czekajlo A, Davies HW, Davis Z, Guhn M, Jarvis I, Jerrett M, Nesbitt L, Oberlander TF, Sbihi H, Su J, van den Bosch M. Neighborhood environmental exposures and incidence of attention deficit/hyperactivity disorder: A population-based cohort study. Environ Int 2022; 161:107120. [PMID: 35144157 DOI: 10.1016/j.envint.2022.107120] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 01/23/2022] [Accepted: 01/26/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND Emerging studies have associated low greenspace and high air pollution exposure with risk of child attention deficit/hyperactivity disorder (ADHD). Population-based studies are limited, however, and joint effects are rarely evaluated. We investigated associations of ADHD incidence with greenspace, air pollution, and noise in a population-based birth cohort. METHODS We assembled a cohort from administrative data of births from 2000 to 2001 (N ∼ 37,000) in Metro Vancouver, Canada. ADHD was identified by hospital records, physician visits, and prescriptions. Cox proportional hazards models were applied to assess associations between environmental exposures and ADHD incidence adjusting for available covariates. Greenspace was estimated using vegetation percentage derived from linear spectral unmixing of Landsat imagery. Fine particulate matter (PM2.5) and nitrogen dioxide (NO2) were estimated using land use regression models; noise was estimated using a deterministic model. Exposure period was from birth until the age of three. Joint effects of greenspace and PM2.5 were analysed in two-exposure models and by categorizing values into quintiles. RESULTS During seven-year follow-up, 1217 ADHD cases were diagnosed. Greenspace was associated with lower incidence of ADHD (hazard ratio, HR: 0.90 [0.81-0.99] per interquartile range increment), while PM2.5 was associated with increased incidence (HR: 1.11 [1.06-1.17] per interquartile range increment). NO2 (HR: 1.01 [0.96, 1.07]) and noise (HR: 1.00 [0.95, 1.05]) were not associated with ADHD. There was a 50% decrease in the HR for ADHD in locations with the lowest PM2.5 and highest greenspace exposure, compared to a 62% increase in HR in locations with the highest PM2.5 and lowest greenspace exposure. Effects of PM2.5 were attenuated by greenspace in two-exposure models. CONCLUSIONS We found evidence suggesting environmental inequalities where children living in greener neighborhoods with low air pollution had substantially lower risk of ADHD compared to those with higher air pollution and lower greenspace exposure.
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Affiliation(s)
- Weiran Yuchi
- School of Population and Public Health, Faculty of Medicine, The University of British Columbia, 2206 East Mall, Vancouver, British Columbia, Canada
| | - Michael Brauer
- School of Population and Public Health, Faculty of Medicine, The University of British Columbia, 2206 East Mall, Vancouver, British Columbia, Canada
| | - Agatha Czekajlo
- Department of Forest Resource Management, Faculty of Forestry, The University of British Columbia, 2424 Main Mall, Vancouver, Canada
| | - Hugh W Davies
- School of Population and Public Health, Faculty of Medicine, The University of British Columbia, 2206 East Mall, Vancouver, British Columbia, Canada
| | - Zoë Davis
- Department of Forest and Conservation Sciences, Faculty of Forestry, The University of British Columbia, 2424 Main Mall, Vancouver, Canada
| | - Martin Guhn
- School of Population and Public Health, Faculty of Medicine, The University of British Columbia, 2206 East Mall, Vancouver, British Columbia, Canada
| | - Ingrid Jarvis
- Department of Forest and Conservation Sciences, Faculty of Forestry, The University of British Columbia, 2424 Main Mall, Vancouver, Canada
| | - Michael Jerrett
- Fielding School of Public Health, University of California at Los Angeles, 650 Charles E. Young Drive South, Los Angeles, CA, the United States
| | - Lorien Nesbitt
- Department of Forest Resource Management, Faculty of Forestry, The University of British Columbia, 2424 Main Mall, Vancouver, Canada
| | - Tim F Oberlander
- School of Population and Public Health, Faculty of Medicine, The University of British Columbia, 2206 East Mall, Vancouver, British Columbia, Canada; Department of Pediatrics, The University of British Columbia, 4480 Oak St. Vancouver, Canada
| | - Hind Sbihi
- School of Population and Public Health, Faculty of Medicine, The University of British Columbia, 2206 East Mall, Vancouver, British Columbia, Canada; BC Centre for Disease Control, Vancouver, Canada
| | - Jason Su
- School of Public Health, University of California at Berkeley, 2121 Berkeley Way West, Berkeley, CA, the United States
| | - Matilda van den Bosch
- School of Population and Public Health, Faculty of Medicine, The University of British Columbia, 2206 East Mall, Vancouver, British Columbia, Canada; Department of Forest and Conservation Sciences, Faculty of Forestry, The University of British Columbia, 2424 Main Mall, Vancouver, Canada; ISGlobal, Parc de Recerca Biomèdica de Barcelona, Doctor Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra, Plaça de la Mercè, 10-12, 08002 Barcelona, Spain; Centro de Investigación Biomédica en Red Instituto de Salud Carlos III, Calle de Melchor Fernández Almagro, 3, 28029, Madrid, Spain.
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Gan WQ, Henderson SB, Mckee G, Yuchi W, McLean KE, Hong KY, Auger N, Kosatsky T. Snowfall, Temperature, and the Risk of Death From Myocardial Infarction: A Case-Crossover Study. Am J Epidemiol 2020; 189:832-840. [PMID: 32128571 DOI: 10.1093/aje/kwaa029] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Revised: 02/21/2020] [Accepted: 02/26/2020] [Indexed: 12/26/2022] Open
Abstract
Previous research has associated snowfall with risk of myocardial infarction (MI). Most studies have been conducted in regions with harsh winters; it remains unclear whether snowfall is associated with risk of MI in regions with milder or more varied climates. A case-crossover design was used to investigate the association between snowfall and death from MI in British Columbia, Canada. Deaths from MI among British Columbia residents between October 15 and March 31 from 2009 to 2017 were identified. The day of each death from MI was treated as the case day, and each case day was matched to control days drawn from the same day of the week during the same month. Daily snowfall amount was assigned to case and control days at the residential address, using weather stations within 15 km of the residence and 100 m in elevation. In total, 3,300 MI case days were matched to 10,441 control days. Compared with days that had no snowfall, odds of death from MI increased 34% (95% confidence interval: 0%, 80%) on days with heavy snowfall (≥5 cm). In stratified analysis of deaths from MI as a function of both maximum temperature and snowfall, risk was significantly increased on snowfall days when the temperature was warmer.
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Yuchi W, Sbihi H, Davies H, Tamburic L, Brauer M. Road proximity, air pollution, noise, green space and neurologic disease incidence: a population-based cohort study. Environ Health 2020; 19:8. [PMID: 31964412 PMCID: PMC6974975 DOI: 10.1186/s12940-020-0565-4] [Citation(s) in RCA: 90] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Accepted: 01/07/2020] [Indexed: 05/05/2023]
Abstract
BACKGROUND Emerging evidence links road proximity and air pollution with cognitive impairment. Joint effects of noise and greenness have not been evaluated. We investigated associations between road proximity and exposures to air pollution, and joint effects of noise and greenness, on non-Alzheimer's dementia, Parkinson's and Alzheimer's disease and multiple sclerosis within a population-based cohort. METHODS We assembled administrative health database cohorts of 45-84 year old residents (N ~ 678,000) of Metro Vancouver, Canada. Cox proportional hazards models were built to assess associations between exposures and non-Alzheimer's dementia and Parkinson's disease. Given reduced case numbers, associations with Alzheimer's disease and multiple sclerosis were evaluated in nested case-control analyses by conditional logistic regression. RESULTS Road proximity was associated with all outcomes (e.g. non-Alzheimer's dementia hazard ratio: 1.14, [95% confidence interval: 1.07-1.20], for living < 50 m from a major road or < 150 m from a highway). Air pollutants were associated with incidence of Parkinson's disease and non-Alzheimer's dementia (e.g. Parkinson's disease hazard ratios of 1.09 [1.02-1.16], 1.03 [0.97-1.08], 1.12 [1.05-1.20] per interquartile increase in fine particulate matter, Black Carbon, and nitrogen dioxide) but not Alzheimer's disease or multiple sclerosis. Noise was not associated with any outcomes while associations with greenness suggested protective effects for Parkinson's disease and non-Alzheimer's dementia. CONCLUSIONS Road proximity was associated with incidence of non-Alzheimer's dementia, Parkinson's disease, Alzheimer's disease and multiple sclerosis. This association may be partially mediated by air pollution, whereas noise exposure did not affect associations. There was some evidence of protective effects of greenness.
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Affiliation(s)
- Weiran Yuchi
- School of Population and Public Health, Faculty of Medicine, The University of British Columbia, 2206 East Mall, Vancouver, British Columbia, V6T 1Z3, Canada
| | - Hind Sbihi
- School of Population and Public Health, Faculty of Medicine, The University of British Columbia, 2206 East Mall, Vancouver, British Columbia, V6T 1Z3, Canada
| | - Hugh Davies
- School of Population and Public Health, Faculty of Medicine, The University of British Columbia, 2206 East Mall, Vancouver, British Columbia, V6T 1Z3, Canada
| | - Lillian Tamburic
- School of Population and Public Health, Faculty of Medicine, The University of British Columbia, 2206 East Mall, Vancouver, British Columbia, V6T 1Z3, Canada
| | - Michael Brauer
- School of Population and Public Health, Faculty of Medicine, The University of British Columbia, 2206 East Mall, Vancouver, British Columbia, V6T 1Z3, Canada.
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5
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Yuchi W, Gombojav E, Boldbaatar B, Galsuren J, Enkhmaa S, Beejin B, Naidan G, Ochir C, Legtseg B, Byambaa T, Barn P, Henderson SB, Janes CR, Lanphear BP, McCandless LC, Takaro TK, Venners SA, Webster GM, Allen RW. Evaluation of random forest regression and multiple linear regression for predicting indoor fine particulate matter concentrations in a highly polluted city. Environ Pollut 2019; 245:746-753. [PMID: 30500754 DOI: 10.1016/j.envpol.2018.11.034] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Revised: 11/01/2018] [Accepted: 11/11/2018] [Indexed: 05/14/2023]
Abstract
BACKGROUND Indoor and outdoor fine particulate matter (PM2.5) are both leading risk factors for death and disease, but making indoor measurements is often infeasible for large study populations. METHODS We developed models to predict indoor PM2.5 concentrations for pregnant women who were part of a randomized controlled trial of portable air cleaners in Ulaanbaatar, Mongolia. We used multiple linear regression (MLR) and random forest regression (RFR) to model indoor PM2.5 concentrations with 447 independent 7-day PM2.5 measurements and 87 potential predictor variables obtained from outdoor monitoring data, questionnaires, home assessments, and geographic data sets. We also developed blended models that combined the MLR and RFR approaches. All models were evaluated in a 10-fold cross-validation. RESULTS The predictors in the MLR model were season, outdoor PM2.5 concentration, the number of air cleaners deployed, and the density of gers (traditional felt-lined yurts) surrounding the apartments. MLR and RFR had similar performance in cross-validation (R2 = 50.2%, R2 = 48.9% respectively). The blended MLR model that included RFR predictions had the best performance (cross validation R2 = 81.5%). Intervention status alone explained only 6.0% of the variation in indoor PM2.5 concentrations. CONCLUSIONS We predicted a moderate amount of variation in indoor PM2.5 concentrations using easily obtained predictor variables and the models explained substantially more variation than intervention status alone. While RFR shows promise for modelling indoor concentrations, our results highlight the importance of out-of-sample validation when evaluating model performance. We also demonstrate the improved performance of blended MLR/RFR models in predicting indoor air pollution.
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Affiliation(s)
- Weiran Yuchi
- Faculty of Health Sciences, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada
| | - Enkhjargal Gombojav
- School of Public Health, Mongolian National University of Medical Sciences, Zorig Street, Ulaanbaatar, 14210, Mongolia
| | - Buyantushig Boldbaatar
- School of Public Health, Mongolian National University of Medical Sciences, Zorig Street, Ulaanbaatar, 14210, Mongolia
| | - Jargalsaikhan Galsuren
- School of Public Health, Mongolian National University of Medical Sciences, Zorig Street, Ulaanbaatar, 14210, Mongolia
| | - Sarangerel Enkhmaa
- Institute of Meteorology and Environmental Monitoring, Ministry of Environment of Mongolia, Mongolia
| | - Bolor Beejin
- Mongolian National Center for Public Health, Olympic Street 2, Ulaanbaatar, Mongolia
| | - Gerel Naidan
- School of Public Health, Mongolian National University of Medical Sciences, Zorig Street, Ulaanbaatar, 14210, Mongolia
| | - Chimedsuren Ochir
- School of Public Health, Mongolian National University of Medical Sciences, Zorig Street, Ulaanbaatar, 14210, Mongolia
| | - Bayarkhuu Legtseg
- Sukhbaatar District Health Center, 11 Horoo, Tsagdaagiin Gudamj, Sukhbaatar District, Ulaanbaatar, Mongolia
| | - Tsogtbaatar Byambaa
- Ministry of Health of Mongolia, Olympic Street-2, Government Building VIII, Sukhbaatar District, Ulaanbaatar, Mongolia
| | - Prabjit Barn
- Faculty of Health Sciences, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada
| | - Sarah B Henderson
- Environmental Health Services, British Columbia Centre for Disease Control, 655 W. 12th Ave, Vancouver, BC, V5T 4R4, Canada
| | - Craig R Janes
- School of Public Health and Health Systems, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada
| | - Bruce P Lanphear
- Faculty of Health Sciences, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada
| | - Lawrence C McCandless
- Faculty of Health Sciences, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada
| | - Tim K Takaro
- Faculty of Health Sciences, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada
| | - Scott A Venners
- Faculty of Health Sciences, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada
| | - Glenys M Webster
- Faculty of Health Sciences, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada
| | - Ryan W Allen
- Faculty of Health Sciences, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada.
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Tang R, Tian L, Thach TQ, Tsui TH, Brauer M, Lee M, Allen R, Yuchi W, Lai PC, Wong P, Barratt B. Integrating travel behavior with land use regression to estimate dynamic air pollution exposure in Hong Kong. Environ Int 2018; 113:100-108. [PMID: 29421398 DOI: 10.1016/j.envint.2018.01.009] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2017] [Revised: 12/24/2017] [Accepted: 01/15/2018] [Indexed: 06/08/2023]
Abstract
BACKGROUND Epidemiological studies typically use subjects' residential address to estimate individuals' air pollution exposure. However, in reality this exposure is rarely static as people move from home to work/study locations and commute during the day. Integrating mobility and time-activity data may reduce errors and biases, thereby improving estimates of health risks. OBJECTIVES To incorporate land use regression with movement and building infiltration data to estimate time-weighted air pollution exposures stratified by age, sex, and employment status for population subgroups in Hong Kong. METHODS A large population-representative survey (N = 89,385) was used to characterize travel behavior, and derive time-activity pattern for each subject. Infiltration factors calculated from indoor/outdoor monitoring campaigns were used to estimate micro-environmental concentrations. We evaluated dynamic and static (residential location-only) exposures in a staged modeling approach to quantify effects of each component. RESULTS Higher levels of exposures were found for working adults and students due to increased mobility. Compared to subjects aged 65 or older, exposures to PM2.5, BC, and NO2 were 13%, 39% and 14% higher, respectively for subjects aged below 18, and 3%, 18% and 11% higher, respectively for working adults. Exposures of females were approximately 4% lower than those of males. Dynamic exposures were around 20% lower than ambient exposures at residential addresses. CONCLUSIONS The incorporation of infiltration and mobility increased heterogeneity in population exposure and allowed identification of highly exposed groups. The use of ambient concentrations may lead to exposure misclassification which introduces bias, resulting in lower effect estimates than 'true' exposures.
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Affiliation(s)
- Robert Tang
- The University of Hong Kong, School of Public Health, Hong Kong Special Administrative Region
| | - Linwei Tian
- The University of Hong Kong, School of Public Health, Hong Kong Special Administrative Region
| | - Thuan-Quoc Thach
- The University of Hong Kong, School of Public Health, Hong Kong Special Administrative Region
| | - Tsz Him Tsui
- The University of Hong Kong, School of Public Health, Hong Kong Special Administrative Region
| | - Michael Brauer
- University of British Columbia, School of Population and Public Health, Canada
| | - Martha Lee
- University of British Columbia, School of Population and Public Health, Canada
| | - Ryan Allen
- Simon Fraser University, Faculty of Health Sciences, Canada
| | - Weiran Yuchi
- Simon Fraser University, Faculty of Health Sciences, Canada
| | - Poh-Chin Lai
- The University of Hong Kong, Department of Geography, Hong Kong Special Administrative Region
| | - Paulina Wong
- Lingnan University, Science Unit, Hong Kong Special Administrative Region
| | - Benjamin Barratt
- King's College London, MRC-PHE Centre for Environment & Health and NIHR HPRU Health Impact of Environmental Hazards, UK.
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Barn P, Gombojav E, Ochir C, Laagan B, Beejin B, Naidan G, Boldbaatar B, Galsuren J, Byambaa T, Janes C, Janssen PA, Lanphear BP, Takaro TK, Venners SA, Webster GM, Yuchi W, Palmer CD, Parsons PJ, Roh YM, Allen RW. The effect of portable HEPA filter air cleaners on indoor PM 2.5 concentrations and second hand tobacco smoke exposure among pregnant women in Ulaanbaatar, Mongolia: The UGAAR randomized controlled trial. Sci Total Environ 2018; 615:1379-1389. [PMID: 29751442 DOI: 10.1016/j.scitotenv.2017.09.291] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2017] [Revised: 09/20/2017] [Accepted: 09/27/2017] [Indexed: 05/22/2023]
Abstract
BACKGROUND Portable HEPA filter air cleaners can reduce indoor fine particulate matter (PM2.5), but their use has not been adequately evaluated in high pollution settings. We assessed air cleaner effectiveness in reducing indoor residential PM2.5 and second hand smoke (SHS) exposures among non-smoking pregnant women in Ulaanbaatar, Mongolia. METHODS We randomized 540 participants to an intervention group receiving 1 or 2 HEPA filter air cleaners or a control group receiving no air cleaners. We followed 259 intervention and 253 control participants to the end of pregnancy. We measured one-week indoor residential PM2.5 concentrations in early (~11weeks gestation) and late (~31weeks gestation) pregnancy and collected outdoor PM2.5 data from centrally-located government monitors. We assessed blood cadmium in late pregnancy. Hair nicotine was quantified in a subset (n=125) to evaluate blood cadmium as a biomarker of SHS exposure. We evaluated air cleaner effectiveness using mixed effects and multiple linear regression models and used stratified models and interaction terms to evaluate potential modifiers of effectiveness. RESULTS The overall geometric mean (GM) one-week outdoor PM2.5 concentration was 47.9μg/m3 (95% CI: 44.6, 51.6μg/m3), with highest concentrations in winter (118.0μg/m3; 110.4, 126.2μg/m3). One-week indoor and outdoor PM2.5 concentrations were correlated (r=0.69). Indoor PM2.5 concentrations were 29% (21, 37%) lower in intervention versus control apartments, with GMs of 17.3μg/m3 (15.8, 18.8μg/m3) and 24.5μg/m3 (22.2, 27.0μg/m3), respectively. Air cleaner effectiveness was greater when air cleaners were first deployed (40%; 31, 48%) than after approximately five months of use (15%; 0, 27%). Blood cadmium concentrations were 14% (4, 23%) lower among intervention participants, likely due to reduced SHS exposure. CONCLUSIONS Portable HEPA filter air cleaners can lower indoor PM2.5 concentrations and SHS exposures in highly polluted settings.
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Affiliation(s)
- Prabjit Barn
- Faculty of Health Sciences, Simon Fraser University, 8888 University Drive, Burnaby V5A 1S6, Canada.
| | - Enkhjargal Gombojav
- School of Public Health, Mongolian National University of Medical Sciences, Zorig Street, Ulaanbaatar 14210, Mongolia.
| | - Chimedsuren Ochir
- School of Public Health, Mongolian National University of Medical Sciences, Zorig Street, Ulaanbaatar 14210, Mongolia.
| | - Bayarkhuu Laagan
- Sukhbaatar District Health Center, 11 Horoo, Tsagdaagiin Gudamj, Sukhbaatar District, Ulaanbaatar, Mongolia
| | - Bolor Beejin
- Mongolian National Center for Public Health, Olympic Street 2, Ulaanbaatar, Mongolia.
| | - Gerel Naidan
- School of Public Health, Mongolian National University of Medical Sciences, Zorig Street, Ulaanbaatar 14210, Mongolia
| | - Buyantushig Boldbaatar
- School of Public Health, Mongolian National University of Medical Sciences, Zorig Street, Ulaanbaatar 14210, Mongolia
| | - Jargalsaikhan Galsuren
- School of Public Health, Mongolian National University of Medical Sciences, Zorig Street, Ulaanbaatar 14210, Mongolia
| | - Tsogtbaatar Byambaa
- Mongolian National Center for Public Health, Olympic Street 2, Ulaanbaatar, Mongolia.
| | - Craig Janes
- School of Public Health and Health Systems, University of Waterloo, 200 University Avenue West, Waterloo N2L 3G1, Canada.
| | - Patricia A Janssen
- School of Population and Public Health, University of British Columbia, 2206 East Mall, Vancouver V6T 1Z3, Canada.
| | - Bruce P Lanphear
- Faculty of Health Sciences, Simon Fraser University, 8888 University Drive, Burnaby V5A 1S6, Canada.
| | - Tim K Takaro
- Faculty of Health Sciences, Simon Fraser University, 8888 University Drive, Burnaby V5A 1S6, Canada.
| | - Scott A Venners
- Faculty of Health Sciences, Simon Fraser University, 8888 University Drive, Burnaby V5A 1S6, Canada.
| | - Glenys M Webster
- Faculty of Health Sciences, Simon Fraser University, 8888 University Drive, Burnaby V5A 1S6, Canada.
| | - Weiran Yuchi
- Faculty of Health Sciences, Simon Fraser University, 8888 University Drive, Burnaby V5A 1S6, Canada.
| | - Christopher D Palmer
- New York State Department of Health, Wadsworth Center, Albany, NY, PO Box 509, 12201, USA; School of Public Health, University at Albany, State University of New York, One University Place, Rensselaer, NY 12144, USA.
| | - Patrick J Parsons
- New York State Department of Health, Wadsworth Center, Albany, NY, PO Box 509, 12201, USA; School of Public Health, University at Albany, State University of New York, One University Place, Rensselaer, NY 12144, USA.
| | - Young Man Roh
- College of Health Sciences, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Ryan W Allen
- Faculty of Health Sciences, Simon Fraser University, 8888 University Drive, Burnaby V5A 1S6, Canada.
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Krstic N, Yuchi W, Ho HC, Walker BB, Knudby AJ, Henderson SB. The Heat Exposure Integrated Deprivation Index (HEIDI): A data-driven approach to quantifying neighborhood risk during extreme hot weather. Environ Int 2017; 109:42-52. [PMID: 28934628 DOI: 10.1016/j.envint.2017.09.011] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2017] [Revised: 09/01/2017] [Accepted: 09/09/2017] [Indexed: 06/07/2023]
Abstract
Mortality attributable to extreme hot weather is a growing concern in many urban environments, and spatial heat vulnerability indexes are often used to identify areas at relatively higher and lower risk. Three indexes were developed for greater Vancouver, Canada using a pool of 20 potentially predictive variables categorized to reflect social vulnerability, population density, temperature exposure, and urban form. One variable was chosen from each category: an existing deprivation index, senior population density, apparent temperature, and road density, respectively. The three indexes were constructed from these variables using (1) unweighted, (2) weighted, and (3) data-driven Heat Exposure Integrated Deprivation Index (HEIDI) approaches. The performance of each index was assessed using mortality data from 1998-2014, and the maps were compared with respect to spatial patterns identified. The population-weighted spatial correlation between the three indexes ranged from 0.68-0.89. The HEIDI approach produced a graduated map of vulnerability, whereas the other approaches primarily identified areas of highest risk. All indexes performed best under extreme temperatures, but HEIDI was more useful at lower thresholds. Each of the indexes in isolation provides valuable information for public health protection, but combining the HEIDI approach with unweighted and weighted methods provides richer information about areas most vulnerable to heat.
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Affiliation(s)
- Nikolas Krstic
- Environmental Health Services, British Columbia Centre for Disease Control, 655 West 12th Avenue, Vancouver, BC V5Z 4R4, Canada
| | - Weiran Yuchi
- Environmental Health Services, British Columbia Centre for Disease Control, 655 West 12th Avenue, Vancouver, BC V5Z 4R4, Canada
| | - Hung Chak Ho
- Department of Land Surveying and Geo-informatics, Hong Kong Polytechnic University, 181 Chatham Road South, Kowloon, Hong Kong
| | - Blake B Walker
- Geographisches Institut, Universität Humboldt zu Berlin, Unter den Linden 6, 10099 Berlin, Germany
| | - Anders J Knudby
- Department of Geography, Environment and Geomatics, University of Ottawa, 60 University Private, Ottawa, ON K1N 6N5, Canada
| | - Sarah B Henderson
- Environmental Health Services, British Columbia Centre for Disease Control, 655 West 12th Avenue, Vancouver, BC V5Z 4R4, Canada; School of Population and Public Health, University of British Columbia, 2206 East Mall, 3rd Floor, Vancouver, BC V6T 1Z3, Canada.
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