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Deng Y, Wang J, Sun L, Wang Y, Chen J, Zhao Z, Wang T, Xiang Y, Wang Y, Chen J, He M. Effects of Ambient O 3 on Respiratory Mortality, Especially the Combined Effects of PM 2.5 and O 3. TOXICS 2023; 11:892. [PMID: 37999544 PMCID: PMC10675328 DOI: 10.3390/toxics11110892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 10/25/2023] [Accepted: 10/26/2023] [Indexed: 11/25/2023]
Abstract
BACKGROUND In China, the increasing concentration of ozone (O3) has emerged as a significant air pollution issue, leading to adverse effects on public health, particularly the respiratory system. Despite the progress made in managing air pollution in China, it is crucial to address the problem of environmental O3 pollution at present. METHODS The connection between O3 exposure and respiratory mortality in Shenyang, China, from 2014 to 2018 was analyzed by a time-series generalized additive regression model (GAM) with quasi-Poisson regression. Additionally, the potential combined effects of fine particulate matter (PM2.5) and O3 were investigated using the synergy index (SI). RESULTS Our findings indicate that each 10 μg/m3 increase in O3 at lag 2 days was associated with a maximum relative risk (RR) of 1.0150 (95% CI: 1.0098-1.0202) for respiratory mortality in the total population. For individuals aged ≥55 years, unmarried individuals, those engaged in indoor occupations, and those with low educational attainment, each 10 μg/m3 increase in O3 at lag 07 days was linked to RR values of 1.0301 (95% CI: 1.0187-1.0417), 1.0437 (95% CI: 1.0266-1.0610), 1.0317 (95% CI: 1.0186-1.0450), and 1.0346 (95% CI: 1.0222-1.0471), respectively. Importantly, we discovered a synergistic effect of PM2.5 and O3, resulting in an SI of 2.372 on the occurrence of respiratory mortality. CONCLUSIONS This study confirmed a positive association between O3 exposure and respiratory mortality. Furthermore, it highlighted the interaction between O3 and PM2.5 in exacerbating respiratory deaths.
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Affiliation(s)
- Ye Deng
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, Ministry of Education, China Medical University, Shenyang 110122, China
| | - Junlong Wang
- Liaoning Provincial Center for Disease Control and Prevention, Shenyang 110005, China
| | - Li Sun
- Liaoning Provincial Center for Disease Control and Prevention, Shenyang 110005, China
| | - Yue Wang
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, Ministry of Education, China Medical University, Shenyang 110122, China
| | - Jiaoyang Chen
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, Ministry of Education, China Medical University, Shenyang 110122, China
| | - Zhixin Zhao
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, Ministry of Education, China Medical University, Shenyang 110122, China
| | - Tianyun Wang
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, Ministry of Education, China Medical University, Shenyang 110122, China
| | - Yuting Xiang
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, Ministry of Education, China Medical University, Shenyang 110122, China
| | - Yuting Wang
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, Ministry of Education, China Medical University, Shenyang 110122, China
| | - Jiamei Chen
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, Ministry of Education, China Medical University, Shenyang 110122, China
| | - Miao He
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, Ministry of Education, China Medical University, Shenyang 110122, China
- Key Laboratory of Environmental Stress and Chronic Disease Control & Prevention, Ministry of Education, China Medical University, Shenyang 110122, China
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Horton A, Jones SJ, Brunt H. Air pollution and public health vulnerabilities, susceptibilities and inequalities in Wales, UK. J Public Health (Oxf) 2022:6672910. [PMID: 35993370 DOI: 10.1093/pubmed/fdac083] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Outdoor air pollution is the largest environmental risk to health. Air pollution, deprivation and poor health status are inextricably linked; highlighting issues of environmental injustice, social and health inequalities. METHODS Air pollution (nitrogen dioxide, NO2 and fine particulate matter, PM2.5), population and deprivation data were identified at Lower Super Output Area level in Wales, UK, for 2012-18. Air pollution data were categorized according to different air pollution concentrations. Population and deprivation data were considered simultaneously to describe population vulnerabilities, susceptibilities and inequalities. Simple statistical analyses were performed using a difference in proportions method with 95% confidence intervals. RESULTS Over time, the majority of Welsh people transitioned to living in areas of lower NO2 and PM2.5 pollution. Areas of worse air pollution comprised more young people than people aged 65+; both populations are known to be susceptible to air pollution exposure. By 2018, significant socioeconomic inequality gaps were found where 'most deprived' population groups for both pollutants experienced greater disadvantage. CONCLUSION Air quality in Wales is improving. However, local-level variations in exposure risk still exist. System-wide action must ensure that air quality improvement-related benefits are equitable and acknowledge current evidence about the harms that even low levels of air pollution can have on health.
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Affiliation(s)
- Amber Horton
- Environmental Public Health, Health Protection, Public Health Wales, Tyndall Street, Cardiff CF10 4BZ, UK
| | - Sarah J Jones
- Environmental Public Health, Health Protection, Public Health Wales, Tyndall Street, Cardiff CF10 4BZ, UK
| | - Huw Brunt
- Environmental Public Health, Health Protection, Public Health Wales, Tyndall Street, Cardiff CF10 4BZ, UK
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Guo H, Li W, Yao F, Wu J, Zhou X, Yue Y, Yeh AGO. Who are more exposed to PM2.5 pollution: A mobile phone data approach. ENVIRONMENT INTERNATIONAL 2020; 143:105821. [PMID: 32702593 DOI: 10.1016/j.envint.2020.105821] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Revised: 05/18/2020] [Accepted: 05/18/2020] [Indexed: 05/17/2023]
Abstract
BACKGROUND Few studies have examined exposure disparity to ambient air pollution outside North America and Europe. Moreover, very few studies have investigated exposure disparity in terms of individual-level data or at multi-temporal scales. OBJECTIVES This work aims to examine the associations between individual- and neighbourhood-level economic statuses and individual exposure to PM2.5 across multi-temporal scales. METHODS The study population included 742,220 mobile phone users on a weekday in Shenzhen, China. A geo-informed backward propagation neural network model was developed to estimate hourly PM2.5 concentrations by the use of remote sensing and geospatial big data, which were then combined with individual trajectories to estimate individual total exposure during weekdays at multi-temporal scales. Coupling the estimated PM2.5 exposure with housing price, we examined the associations between individual- and neighbourhood-level economic statuses and individual exposure using linear regression and two-level hierarchical linear models. Furthermore, we performed five sensitivity analyses to test the robustness of the two-level effects. RESULTS We found positive associations between individual- and neighbourhood-level economic statuses and individual PM2.5 exposure at a daytime, daily, weekly, monthly, seasonal or annual scale. Findings on the effects of the two-level economic statuses were generally robust in the five sensitivity analyses. In particular, despite the insignificant effects observed in three of newly selected time periods in the sensitivity analysis, individual- and neighbourhood-level economic statuses were still positively associated with individual total exposure during each of other newly selected periods (including three other seasons). CONCLUSIONS There are statistically positive associations of individual PM2.5 exposure with individual- and neighbourhood-level economic statuses. That is, people living in areas with higher residential property prices are more exposed to PM2.5 pollution. Findings emphasize the need for public health intervention and urban planning initiatives targeting socio-economic disparity in ambient air pollution exposure, thus alleviating health disparities across socioeconomic groups.
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Affiliation(s)
- Huagui Guo
- Department of Urban Planning and Design, The University of Hong Kong, Hong Kong, China; Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen 518057, PR China.
| | - Weifeng Li
- Department of Urban Planning and Design, The University of Hong Kong, Hong Kong, China; Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen 518057, PR China.
| | - Fei Yao
- School of GeoSciences, The University of Edinburgh, Edinburgh EH9 3FF, United Kingdom.
| | - Jiansheng Wu
- Key Laboratory for Urban Habitat Environmental Science and Technology, Shenzhen Graduate School, Peking University, Shenzhen 518055, PR China; Key Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, PR China.
| | - Xingang Zhou
- College of Architecture and Urban Planning, Tongji University, Shanghai 200092, PR China.
| | - Yang Yue
- Department of Urban Informatics, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518052, PR China.
| | - Anthony G O Yeh
- Department of Urban Planning and Design, The University of Hong Kong, Hong Kong, China; Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen 518057, PR China.
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Fan C, Ouyang W, Tian L, Song Y, Miao W. Elderly Health Inequality in China and its Determinants: A Geographical Perspective. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:E2953. [PMID: 31426371 PMCID: PMC6719074 DOI: 10.3390/ijerph16162953] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Revised: 07/20/2019] [Accepted: 07/31/2019] [Indexed: 11/16/2022]
Abstract
Inter-regional health differences and apparent inequalities in China have recently received significant attention. By collecting health status data and individual socio-economic information from the 2015 fourth sampling survey of the elderly population in China (4th SSEP), this paper uses the geographical differentiation index to reveal the spatial differentiation of health inequality among Chinese provinces. We test the determinants of inequalities by multilevel regression models at the provincial and individual levels, and find three main conclusions: 1) There were significant health differences on an inter-provincial level. For example, provinces with a very good or good health rating formed a good health hot-spot region in the Yangtze River Delta, versus elderly people living in Gansu and Hainan provinces, who had a poor health status. 2) Nearly 2.4% of the health differences in the elderly population were caused by inter-provincial inequalities; access (or lack of access) to economic, medical and educational resources was the main reason for health inequalities. 3) At the individual level, inequalities in annual income served to deepen elderly health differences, and elderly living in less developed areas were more vulnerable to urban vs. rural-related health inequalities.
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Affiliation(s)
- Chenjing Fan
- School of Architecture, Tsinghua University, Beijing 100084, China
- College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China
| | - Wei Ouyang
- School of Public Administration, Renmin University of China, Beijing 100872, China
| | - Li Tian
- School of Architecture, Tsinghua University, Beijing 100084, China.
| | - Yan Song
- Department of City and Regional Planning, University of North Carolina at Chapel Hill, NC 27599-3140, USA
| | - Wensheng Miao
- China Research Center on Aging, Beijing 100054, China
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Lee C, Lee J. National NO 2 exposure models for measuring its impact on vulnerable people in the US metropolitan areas. ENVIRONMENTAL MONITORING AND ASSESSMENT 2019; 191:484. [PMID: 31280377 DOI: 10.1007/s10661-019-7606-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Accepted: 06/18/2019] [Indexed: 06/09/2023]
Abstract
Epidemiological research requires accurate prediction of the concentrations of air pollutants. In this study, satellite-based estimates (OMI NO2), distance-weighted models (DWMs), and universal kriging (UK) are applied to land use regression (LUR) to predict annually and monthly averaged NO2 concentrations in the continental United States. In addition, to assess environmental risk, the relationship between NO2 concentrations and people potentially exposed to NO2 within urban areas is explored in 377 metropolitan statistical areas (MSAs). The results of this study show that the application of a combination of OMI NO2, UK, and DWMs to LUR yielded the highest cross-validated (CV) R2 values and the lowest root mean square error of prediction (RMSEP): 82.9% and 0.392 on a square root scale of ppb in the annual model and 70.4-83.5% and 0.408-0.518 on square root scale of ppb in the monthly models, respectively. Moreover, the model presented a spatially unbiased distribution of CV error terms. Models based on LUR provided more accurate NO2 predictions with lower RMSEP in urban areas than in rural areas. In addition, this study finds that the people living in the urban areas of MSAs, with larger populations and a higher percentage of children under 18 years of age, are likely to be exposed to higher NO2 concentrations. By contrast, people living in the urban areas of MSAs with a higher percentage of the elderly over 65 years of age are likely to be exposed to lower NO2 concentrations.
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Affiliation(s)
- Changyeon Lee
- Research Institute of Science and Technology, Hongik University, Seoul, South Korea.
| | - Jaekyung Lee
- Department of Urban Design & Planning, Hongik University, Seoul, South Korea
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Brunt H, Barnes J, Jones SJ, Longhurst JWS, Scally G, Hayes E. Air pollution, deprivation and health: understanding relationships to add value to local air quality management policy and practice in Wales, UK. J Public Health (Oxf) 2018; 39:485-497. [PMID: 27613763 DOI: 10.1093/pubmed/fdw084] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2016] [Accepted: 07/16/2016] [Indexed: 11/13/2022] Open
Abstract
Background Air pollution exposure reduces life expectancy. Air pollution, deprivation and poor-health status combinations can create increased and disproportionate disease burdens. Problems and solutions are rarely considered in a broad public health context, but doing so can add value to air quality management efforts by reducing air pollution risks, impacts and inequalities. Methods An ecological study assessed small-area associations between air pollution (nitrogen dioxide and particulate matter), deprivation status and health outcomes in Wales, UK. Results Air pollution concentrations were highest in 'most' deprived areas. When considered separately, deprivation-health associations were stronger than air pollution-health associations. Considered simultaneously, air pollution added to deprivation-health associations; interactions between air pollution and deprivation modified and strengthened associations with all-cause and respiratory disease mortality, especially in 'most' deprived areas where most-vulnerable people lived and where health needs were greatest. Conclusion There is a need to reduce air pollution-related risks for all. However, it is also the case that greater health gains can result from considering local air pollution problems and solutions in the context of wider health-determinants and acting on a better understanding of relationships. Informed and co-ordinated air pollution mitigation and public health action in high deprivation and pollution areas can reduce risks and inequalities. To achieve this, greater public health integration and collaboration in local air quality management policy and practice is needed.
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Affiliation(s)
- H Brunt
- Air Quality Management Resource Centre, University of the West of England, Bristol, UK.,Health Protection Team, Public Health Wales, Cardiff, UK
| | - J Barnes
- Air Quality Management Resource Centre, University of the West of England, Bristol, UK
| | - S J Jones
- Health Protection Team, Public Health Wales,Cardiff, UK
| | - J W S Longhurst
- Air Quality Management Resource Centre, University of the West of England, Bristol, UK
| | - G Scally
- WHO Collaborating Centre for Healthy Urban Environments, University of the West of England, Bristol, UK
| | - E Hayes
- Air Quality Management Resource Centre, University of the West of England, Bristol, UK
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Rosofsky A, Levy JI, Zanobetti A, Janulewicz P, Fabian MP. Temporal trends in air pollution exposure inequality in Massachusetts. ENVIRONMENTAL RESEARCH 2018; 161:76-86. [PMID: 29101831 PMCID: PMC5761067 DOI: 10.1016/j.envres.2017.10.028] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2017] [Revised: 10/13/2017] [Accepted: 10/17/2017] [Indexed: 05/17/2023]
Abstract
Mounting evidence over the past several decades has demonstrated inequitable distribution of pollutants of ambient origin between sociodemographic groups in the United States. Most environmental inequality studies to date are cross-sectional and used proximity-based methods rather than modeled air pollution concentrations, limiting the ability to examine trends over time or the factors that drive exposure inequalities. In this paper, we use 1km2 modeled PM2.5 and NO2 concentrations in Massachusetts over an 8-year period and Census demographic data to quantify inequality between sociodemographic groups and to develop a more nuanced understanding of the drivers and trends in longitudinal air pollution inequality. Annual-average population-weighted PM2.5 and NO2 concentrations were highest for urban non-Hispanic black populations (11.8µg/m3 in 2003 and 8.4µg/m3 in 2010, vs. 11.3µg/m3 and 8.1µg/m3 for urban non-Hispanic whites) and urban Hispanic populations (15.9 ppb in 2005 and 13.0 ppb in 2010, vs. 13.0 ppb and 10.2 ppb for urban non-Hispanic whites), respectively. While population groups experienced similar absolute decreases in exposure over time, disparities in population-weighted concentrations increased over time when quantified by the Atkinson Index, a relative inequality measure. Exposure inequalities were approximately one order of magnitude greater for NO2 compared to PM2.5, were more pronounced in urban compared to rural geographies, and between racial/ethnic groups compared to income and educational attainment groups. Our results also revealed similar longitudinal PM2.5 and NO2 inequality trends using Census 2000 and Census 2010 data, indicating that spatio-temporal shifts in air pollution may best explain observed trends in inequality. These findings enhance our understanding of factors that contribute to persistent inequalities and underscore the importance of targeted exposure reduction strategies aimed at vulnerable populations and neighborhoods.
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Affiliation(s)
- Anna Rosofsky
- Department of Environmental Health, Boston University School of Public Health, Boston, MA, USA.
| | - Jonathan I Levy
- Department of Environmental Health, Boston University School of Public Health, Boston, MA, USA
| | - Antonella Zanobetti
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Patricia Janulewicz
- Department of Environmental Health, Boston University School of Public Health, Boston, MA, USA
| | - M Patricia Fabian
- Department of Environmental Health, Boston University School of Public Health, Boston, MA, USA
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Padilla CM, Kihal-Talantikit W, Perez S, Deguen S. Use of geographic indicators of healthcare, environment and socioeconomic factors to characterize environmental health disparities. Environ Health 2016; 15:79. [PMID: 27449640 PMCID: PMC4957910 DOI: 10.1186/s12940-016-0163-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2016] [Accepted: 06/30/2016] [Indexed: 05/21/2023]
Abstract
BACKGROUND An environmental health inequality is a major public health concern in Europe. However just few studies take into account a large set of characteristics to analyze this problematic. The aim of this study was to identify and describe how socioeconomic, health accessibility and exposure factors accumulate and interact in small areas in a French urban context, to assess environmental health inequalities related to infant and neonatal mortality. METHODS Environmental indicators on deprivation index, proximity to high-traffic roads, green space, and healthcare accessibility were created using the Geographical Information System. Cases were collected from death certificates in the city hall of each municipality in the Nice metropolitan area. Using the parental addresses, cases were geocoded to their census block of residence. A classification using a Multiple Component Analysis following by a Hierarchical Clustering allow us to characterize the census blocks in terms of level of socioeconomic, environmental and accessibility to healthcare, which are very diverse definition by nature. Relation between infant and neonatal mortality rate and the three environmental patterns which categorize the census blocks after the classification was performed using a standard Poisson regression model for count data after checking the assumption of dispersion. RESULTS Based on geographic indicators, three environmental patterns were identified. We found environmental inequalities and social health inequalities in Nice metropolitan area. Moreover these inequalities are counterbalance by the close proximity of deprived census blocks to healthcare facilities related to mother and newborn. So therefore we demonstrate no environmental health inequalities related to infant and neonatal mortality. CONCLUSION Examination of patterns of social, environmental and in relation with healthcare access is useful to identify census blocks with needs and their effects on health. Similar analyzes could be implemented and considered in other cities or related to other birth outcomes.
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Affiliation(s)
- Cindy M. Padilla
- />Department of Quantitative Methods in Public Health, EHESP School of Public Health, Sorbonne-Paris Cité, 35043 Rennes, France
| | - Wahida Kihal-Talantikit
- />Department of Environmental and Occupational Health, EHESP School of Public Health, Sorbonne-Paris Cité, 35043 Rennes, France
- />INSERM U1085-IRSET – Research institute of environmental and occupational health, Rennes, France
| | - Sandra Perez
- />UMR ESPACE 7300, University of Nice Sophia, Nice, France
| | - Severine Deguen
- />Department of Environmental and Occupational Health, EHESP School of Public Health, Sorbonne-Paris Cité, 35043 Rennes, France
- />INSERM U1085-IRSET – Research institute of environmental and occupational health, Rennes, France
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Bravo MA, Anthopolos R, Bell ML, Miranda ML. Racial isolation and exposure to airborne particulate matter and ozone in understudied US populations: Environmental justice applications of downscaled numerical model output. ENVIRONMENT INTERNATIONAL 2016; 92-93:247-55. [PMID: 27115915 DOI: 10.1016/j.envint.2016.04.008] [Citation(s) in RCA: 80] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2016] [Revised: 03/24/2016] [Accepted: 04/07/2016] [Indexed: 05/17/2023]
Abstract
BACKGROUND Researchers and policymakers are increasingly focused on combined exposures to social and environmental stressors, especially given how often these stressors tend to co-locate. Such exposures are equally relevant in urban and rural areas and may accrue disproportionately to particular communities or specific subpopulations. OBJECTIVES To estimate relationships between racial isolation (RI), a measure of the extent to which minority racial/ethnic group members are exposed to only one another, and long-term particulate matter with an aerodynamic diameter of <2.5μ (PM2.5) and ozone (O3) levels in urban and nonurban areas of the eastern two-thirds of the US. METHODS Long-term (5year average) census tract-level PM2.5 and O3 concentrations were calculated using output from a downscaler model (2002-2006). The downscaler uses a linear regression with additive and multiplicative bias coefficients to relate ambient monitoring data with gridded output from the Community Multi-scale Air Quality (CMAQ) model. A local, spatial measure of RI was calculated at the tract level, and tracts were classified by urbanicity, RI, and geographic region. We examined differences in estimated pollutant exposures by RI, urbanicity, and demographic subgroup (e.g., race/ethnicity, education, socioeconomic status, age), and used linear models to estimate associations between RI and air pollution levels in urban, suburban, and rural tracts. RESULTS High RI tracts (≥80th percentile) had higher average PM2.5 levels in each category of urbanicity compared to low RI tracts (<20th percentile), with the exception of the rural West. Patterns in O3 levels by urbanicity and RI differed by region. Linear models indicated that PM2.5 concentrations were significantly and positively associated with RI. The largest association between PM2.5 and RI was observed in the rural Midwest, where a one quintile increase in RI was associated with a 0.90μg/m(3) (95% confidence interval: 0.83, 0.99μg/m(3)) increase in PM2.5 concentration. Associations between O3 and RI in the Northeast, Midwest and West were positive and highest in suburban and rural tracts, even after controlling for potential confounders such as percentage in poverty. CONCLUSION RI is associated with higher 5year estimated PM2.5 concentrations in urban, suburban, and rural census tracts, adding to evidence that segregation is broadly associated with disparate air pollution exposures. Disproportionate burdens to adverse exposures such as air pollution may be a pathway to racial/ethnic disparities in health.
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Affiliation(s)
- Mercedes A Bravo
- Children's Environmental Health Initiative, Rice University, 6100 Main Street, MS-2, Houston, TX 77005, United States.
| | - Rebecca Anthopolos
- Children's Environmental Health Initiative, Rice University, 6100 Main Street, MS-2, Houston, TX 77005, United States.
| | - Michelle L Bell
- Yale University, School of Forestry and Environmental Studies, 195 Prospect St., New Haven, CT 06511, United States.
| | - Marie Lynn Miranda
- Children's Environmental Health Initiative, Rice University, 6100 Main Street, MS-2, Houston, TX 77005, United States; Rice University, Department of Statistics, 6100 Main Street, Houston, TX 77005, United States.
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Padilla CM, Kihal-Talantikit W, Vieira VM, Deguen S. City-Specific Spatiotemporal Infant and Neonatal Mortality Clusters: Links with Socioeconomic and Air Pollution Spatial Patterns in France. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2016; 13:E624. [PMID: 27338439 PMCID: PMC4924081 DOI: 10.3390/ijerph13060624] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2015] [Revised: 05/30/2016] [Accepted: 06/16/2016] [Indexed: 11/17/2022]
Abstract
Infant and neonatal mortality indicators are known to vary geographically, possibly as a result of socioeconomic and environmental inequalities. To better understand how these factors contribute to spatial and temporal patterns, we conducted a French ecological study comparing two time periods between 2002 and 2009 for three (purposefully distinct) Metropolitan Areas (MAs) and the city of Paris, using the French census block of parental residence as the geographic unit of analysis. We identified areas of excess risk and assessed the role of neighborhood deprivation and average nitrogen dioxide concentrations using generalized additive models to generate maps smoothed on longitude and latitude. Comparison of the two time periods indicated that statistically significant areas of elevated infant and neonatal mortality shifted northwards for the city of Paris, are present only in the earlier time period for Lille MA, only in the later time period for Lyon MA, and decrease over time for Marseille MA. These city-specific geographic patterns in neonatal and infant mortality are largely explained by socioeconomic and environmental inequalities. Spatial analysis can be a useful tool for understanding how risk factors contribute to disparities in health outcomes ranging from infant mortality to infectious disease-a leading cause of infant mortality.
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Affiliation(s)
- Cindy M Padilla
- Department of Quantitative Methods in Public Health, EHESP School of Public Health-Sorbonne-Paris Cité, Rennes 35043, France.
- IRSET-Research Institute of Environmental and Occupational Health, Rennes 35000, France.
| | - Wahida Kihal-Talantikit
- Department of Environmental and Occupational Health, EHESP School of Public Health, Rennes, Sorbonne-Paris Cité 35043, France.
| | - Verónica M Vieira
- Program in Public Health, Chao Family Cancer Center, University of Irvine, Irvine, CA 92697, USA.
| | - Séverine Deguen
- IRSET-Research Institute of Environmental and Occupational Health, Rennes 35000, France.
- Department of Environmental and Occupational Health, EHESP School of Public Health, Rennes, Sorbonne-Paris Cité 35043, France.
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11
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Characterizing the spatial distribution of multiple pollutants and populations at risk in Atlanta, Georgia. Spat Spatiotemporal Epidemiol 2016; 18:13-23. [PMID: 27494956 DOI: 10.1016/j.sste.2016.02.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2015] [Revised: 02/16/2016] [Accepted: 02/23/2016] [Indexed: 11/24/2022]
Abstract
BACKGROUND Exposure metrics that identify spatial contrasts in multipollutant air quality are needed to better understand multipollutant geographies and health effects from air pollution. Our aim is to improve understanding of: (1) long-term spatial distributions of multiple pollutants; and (2) demographic characteristics of populations residing within areas of differing air quality. METHODS We obtained average concentrations for ten air pollutants (p=10) across a 12 km grid (n=253) covering Atlanta, Georgia for 2002-2008. We apply a self-organizing map (SOM) to our data to derive multipollutant patterns observed across our grid and classify locations under their most similar pattern (i.e, multipollutant spatial type (MST)). Finally, we geographically map classifications to delineate regions of similar multipollutant characteristics and characterize associated demographics. RESULTS We found six MSTs well describe our data, with profiles highlighting a range of combinations, from locations experiencing generally clean air to locations experiencing conditions that were relatively dirty. Mapping MSTs highlighted that downtown areas were dominated by primary pollution and that suburban areas experienced relatively higher levels of secondary pollution. Demographics show the largest proportion of the overall population resided in downtown locations experiencing higher levels of primary pollution. Moreover, higher proportions of nonwhites and children in poverty reside in these areas when compared to suburban populations that resided in areas exhibiting relatively lower pollution. CONCLUSION Our approach reveals the nature and spatial distribution of differential pollutant combinations across urban environments and provides helpful insights for identifying spatial exposure and demographic contrasts for future health studies.
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Abstract
The existing reviews and meta-analyses addressing unequal exposure of environmental hazards on certain populations have focused on several environmental pollutants or on the siting of hazardous facilities. This review updates and contributes to the environmental inequality literature by focusing on ambient criteria air pollutants (including NOx), by evaluating studies related to inequality by socioeconomic status (as opposed to race/ethnicity) and by providing a more global perspective. Overall, most North American studies have shown that areas where low-socioeconomic-status (SES) communities dwell experience higher concentrations of criteria air pollutants, while European research has been mixed. Research from Asia, Africa, and other parts of the world has shown a general trend similar to that of North America, but research in these parts of the world is limited.
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Affiliation(s)
- Anjum Hajat
- Department of Epidemiology, University of Washington, 4225 Roosevelt Way NE, Seattle, WA, 98105, USA.
| | - Charlene Hsia
- Department of Environmental and Occupational Health Sciences, University of Washington, 4225 Roosevelt Way NE, Seattle, WA, 98105, USA.
| | - Marie S O'Neill
- Departments of Environmental Health Sciences and Epidemiology, University of Michigan, 6623 SPH Tower 1415 Washington Heights, Ann Arbor, MI, 48109-2029, USA.
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Abstract
BACKGROUND Air pollution, particularly from vehicle exhaust, has been shown to influence hormonal activity. However, it is unknown whether air pollution exposure is associated with the occurrence of uterine leiomyomata, a hormonally sensitive tumor of the uterus. METHODS For 85,251 women 25-42 years of age at enrollment in the Nurses' Health Study II, we examined proximity to major roadways and outdoor levels of particulate matter less than 10 microns (PM10) or 2.5 microns (PM2.5) or between 10 and 2.5 microns (PM10-2.5) in diameter for all residential addresses from September 1989 to May 2007. To be eligible for this analysis, a woman had to be alive and respond to questionnaires, premenopausal with an intact uterus, and without diagnoses of cancer or prevalent uterine leiomyomata. Incidence of ultrasound- or hysterectomy-confirmed uterine leiomyomata and covariates were reported on biennial questionnaires sent through May 2007. Multivariable time-varying Cox proportional hazard models were used to estimate the relationship between distance to road or PM exposures and uterine leiomyomata risk. RESULTS During 837,573 person-years of follow-up, there were 7760 incident cases of uterine leiomyomata. Living close to a major road and exposures to PM10 or PM10-2.5 were not associated with an increased risk of uterine leiomyomata. However, each 10 μg/m increase in 2-year average, 4-year average, or cumulative average PM2.5 was associated with an adjusted hazard ratio of 1.08 (95% confidence interval = 1.00-1.17), 1.09 (0.99-1.19), and 1.11 (1.03-1.19), respectively. CONCLUSIONS Chronic exposure to PM2.5 may be associated with a modest increased risk of uterine leiomyomata.
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Assessing environmental inequalities in ambient air pollution across urban Australia. Spat Spatiotemporal Epidemiol 2015; 13:1-6. [DOI: 10.1016/j.sste.2015.03.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2013] [Revised: 12/23/2014] [Accepted: 03/19/2015] [Indexed: 11/17/2022]
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Padilla CM, Kihal-Talantikite W, Vieira VM, Rossello P, Le Nir G, Zmirou-Navier D, Deguen S. Air quality and social deprivation in four French metropolitan areas--a localized spatio-temporal environmental inequality analysis. ENVIRONMENTAL RESEARCH 2014; 134:315-24. [PMID: 25199972 PMCID: PMC4294705 DOI: 10.1016/j.envres.2014.07.017] [Citation(s) in RCA: 67] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2013] [Revised: 07/23/2014] [Accepted: 07/25/2014] [Indexed: 05/02/2023]
Abstract
Several studies have documented that more deprived populations tend to live in areas characterized by higher levels of environmental pollution. Yet, time trends and geographic patterns of this disproportionate distribution of environmental burden remain poorly assessed, especially in Europe. We investigated the spatial and temporal relationship between ambient air nitrogen dioxide (NO2) concentrations and socioeconomic and demographic data in four French metropolitan areas (Lille in the North, Lyon in the center, Marseille in the South, and Paris) during two different time periods. The geographical unit used was the census block. The dependent variable was the NO2 annual average concentration (μg/m(3)) per census block, and the explanatory variables were a neighborhood deprivation index and socioeconomic and demographic data derived from the national census. Generalized additive models were used to account for spatial autocorrelation. We found that the strength and direction of the association between deprivation and NO2 estimates varied between cities. In Paris, census blocks with the higher social categories are exposed to higher mean concentrations of NO2. However, in Lille and Marseille, the most deprived census blocks are the most exposed to NO2. In Lyon, the census blocks in the middle social categories were more likely to have higher concentrations than in the lower social categories. Despite a general reduction in NO2 concentrations over the study period in the four metropolitan areas, we found contrasting results in the temporal trend of environmental inequalities. There is clear evidence of city-specific spatial and temporal environmental inequalities that relate to the historical socioeconomic make-up of the cities and its evolution. Hence, general statements about environmental and social inequalities can be made.
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Affiliation(s)
- Cindy M Padilla
- EHESP School of Public Health, Sorbonne Paris-Cité, Rennes, France; INSERM U1085-IRSET - Research Institute of Environmental and Occupational Health, Rennes, France; French Environment and Energy Management Agency, Angers, France.
| | | | - Verónica M Vieira
- Program in Public Health, Chao Family Cancer Center, University of Irvine, CA 92697, USA.
| | - Philippe Rossello
- Air Quality Monitoring Associations (AASQA), Airparif, Paris, Air PACA, Marseille, France.
| | - Geraldine Le Nir
- Air Quality Monitoring Associations (AASQA), Airparif, Paris, Air PACA, Marseille, France.
| | - Denis Zmirou-Navier
- EHESP School of Public Health, Sorbonne Paris-Cité, Rennes, France; INSERM U1085-IRSET - Research Institute of Environmental and Occupational Health, Rennes, France; Lorraine University Medical School, Vandoeuvre-les-Nancy, France.
| | - Severine Deguen
- EHESP School of Public Health, Sorbonne Paris-Cité, Rennes, France; INSERM U1085-IRSET - Research Institute of Environmental and Occupational Health, Rennes, France.
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National patterns in environmental injustice and inequality: outdoor NO2 air pollution in the United States. PLoS One 2014; 9:e94431. [PMID: 24736569 PMCID: PMC3988057 DOI: 10.1371/journal.pone.0094431] [Citation(s) in RCA: 183] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2013] [Accepted: 03/15/2014] [Indexed: 01/22/2023] Open
Abstract
We describe spatial patterns in environmental injustice and inequality for residential outdoor nitrogen dioxide (NO2) concentrations in the contiguous United States. Our approach employs Census demographic data and a recently published high-resolution dataset of outdoor NO2 concentrations. Nationally, population-weighted mean NO2 concentrations are 4.6 ppb (38%, p<0.01) higher for nonwhites than for whites. The environmental health implications of that concentration disparity are compelling. For example, we estimate that reducing nonwhites' NO2 concentrations to levels experienced by whites would reduce Ischemic Heart Disease (IHD) mortality by ∼7,000 deaths per year, which is equivalent to 16 million people increasing their physical activity level from inactive (0 hours/week of physical activity) to sufficiently active (>2.5 hours/week of physical activity). Inequality for NO2 concentration is greater than inequality for income (Atkinson Index: 0.11 versus 0.08). Low-income nonwhite young children and elderly people are disproportionately exposed to residential outdoor NO2. Our findings establish a national context for previous work that has documented air pollution environmental injustice and inequality within individual US metropolitan areas and regions. Results given here can aid policy-makers in identifying locations with high environmental injustice and inequality. For example, states with both high injustice and high inequality (top quintile) for outdoor residential NO2 include New York, Michigan, and Wisconsin.
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Gray SC, Edwards SE, Schultz BD, Miranda ML. Assessing the impact of race, social factors and air pollution on birth outcomes: a population-based study. Environ Health 2014; 13:4. [PMID: 24476365 PMCID: PMC3922656 DOI: 10.1186/1476-069x-13-4] [Citation(s) in RCA: 112] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2013] [Accepted: 07/31/2013] [Indexed: 05/04/2023]
Abstract
BACKGROUND Both air pollution exposure and socioeconomic status (SES) are important indicators of children's health. Using highly resolved modeled predictive surfaces, we examine the joint effects of air pollution exposure and measures of SES in a population level analysis of pregnancy outcomes in North Carolina (NC). METHODS Daily measurements of particulate matter <2.5 μm in aerodynamic diameter (PM2.5) and ozone (O3) were calculated through a spatial hierarchical Bayesian model which produces census-tract level point predictions. Using multilevel models and NC birth data from 2002-2006, we examine the association between pregnancy averaged PM2.5 and O3, individual and area-based SES indicators, and birth outcomes. RESULTS Maternal race and education, and neighborhood household income were associated with adverse birth outcomes. Predicted concentrations of PM2.5 and O3 were also associated with an additional effect on reductions in birth weight and increased risks of being born low birth weight and small for gestational age. CONCLUSIONS This paper builds on and complements previous work on the relationship between pregnancy outcomes and air pollution exposure by using 1) highly resolved air pollution exposure data; 2) a five-year population level sample of pregnancies; and 3) including personal and areal level measures of social determinants of pregnancy outcomes. Results show a stable and negative association between air pollution exposure and adverse birth outcomes. Additionally, the more socially disadvantaged populations are at a greater risk; controlling for both SES and environmental stressors provides a better understanding of the contributing factors to poor children's health outcomes.
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Affiliation(s)
- Simone C Gray
- U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Sharon E Edwards
- Children’s Environmental Health Initiative, School of Natural Resources and Environment, University of Michigan, Ann Arbor, Michigan, USA
| | - Bradley D Schultz
- U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Marie Lynn Miranda
- Children’s Environmental Health Initiative, School of Natural Resources and Environment, University of Michigan, Ann Arbor, Michigan, USA
- Department of Pediatrics, University of Michigan, Ann Arbor, Michigan, USA
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Mahalingaiah S, Hart JE, Laden F, Aschengrau A, Missmer SA. Air pollution exposures during adulthood and risk of endometriosis in the Nurses' Health Study II. ENVIRONMENTAL HEALTH PERSPECTIVES 2014; 122:58-64. [PMID: 24225723 PMCID: PMC3888567 DOI: 10.1289/ehp.1306627] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2013] [Accepted: 11/08/2013] [Indexed: 05/05/2023]
Abstract
BACKGROUND Particulate matter and proximity to large roadways may promote disease mechanisms, including systemic inflammation, hormonal alteration, and vascular proliferation, that may contribute to the development and severity of endometriosis. OBJECTIVE Our goal was to determine the association of air pollution exposures during adulthood, including distance to road, particulate matter<2.5 μm, between 2.5 and 10 μm, and <10 μm, (PM2.5, PM10-2.5, PM10), and timing of exposure with risk of endometriosis in the Nurses' Health Study II. METHODS Proximity to major roadways and outdoor levels of PM2.5, PM10-2.5, and PM10 were determined for all residential addresses from 1993 to 2007. Multivariable-adjusted time-varying Cox proportional hazard models were used to estimate the relation between these air pollution exposures and endometriosis risk. RESULTS Among 84,060 women, 2,486 incident cases of surgically confirmed endometriosis were identified over 710,230 person-years of follow-up. There was no evidence of an association between endometriosis risk and distance to road or exposure to PM2.5, PM10-2.5, or PM10 averaged over follow-up or during the previous 2- or 4-year period. CONCLUSIONS Traffic and air pollution exposures during adulthood were not associated with incident endometriosis in this cohort of women.
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Affiliation(s)
- Shruthi Mahalingaiah
- Department of Obstetrics and Gynecology, Boston University School of Medicine, Boston, Massachusetts, USA
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Dons E, Kochan B, Bellemans T, Wets G, Panis LI. Modeling Personal Exposure to Air Pollution with AB2C: Environmental Inequality. ACTA ACUST UNITED AC 2014. [DOI: 10.1016/j.procs.2014.05.424] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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Hajat A, Diez-Roux AV, Adar SD, Auchincloss AH, Lovasi GS, O'Neill MS, Sheppard L, Kaufman JD. Air pollution and individual and neighborhood socioeconomic status: evidence from the Multi-Ethnic Study of Atherosclerosis (MESA). ENVIRONMENTAL HEALTH PERSPECTIVES 2013; 121:1325-33. [PMID: 24076625 PMCID: PMC3855503 DOI: 10.1289/ehp.1206337] [Citation(s) in RCA: 188] [Impact Index Per Article: 17.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2012] [Accepted: 09/26/2013] [Indexed: 05/02/2023]
Abstract
BACKGROUND Although research has shown that low socioeconomic status (SES) and minority communities have higher exposure to air pollution, few studies have simultaneously investigated the associations of individual and neighborhood SES with pollutants across multiple sites. OBJECTIVES We characterized the distribution of ambient air pollution by both individual and neighborhood SES using spatial regression methods. METHODS The study population comprised 6,140 participants from the Multi-Ethnic Study of Atherosclerosis (MESA). Year 2000 annual average ambient PM2.5 and NOx concentrations were calculated for each study participant's home address at baseline examination. We investigated individual and neighborhood (2000 U.S. Census tract level) SES measures corresponding to the domains of income, wealth, education, and occupation. We used a spatial intrinsic conditional autoregressive model for multivariable analysis and examined pooled and metropolitan area-specific models. RESULTS A 1-unit increase in the z-score for family income was associated with 0.03-μg/m3 lower PM2.5 (95% CI: -0.05, -0.01) and 0.93% lower NOx (95% CI: -1.33, -0.53) after adjustment for covariates. A 1-SD-unit increase in the neighborhood's percentage of persons with at least a high school degree was associated with 0.47-μg/m3 lower mean PM2.5 (95% CI: -0.55, -0.40) and 9.61% lower NOx (95% CI: -10.85, -8.37). Metropolitan area-specific results exhibited considerable heterogeneity. For example, in New York, high-SES neighborhoods were associated with higher concentrations of pollution. CONCLUSIONS We found statistically significant associations of SES measures with predicted air pollutant concentrations, demonstrating the importance of accounting for neighborhood- and individual-level SES in air pollution health effects research.
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Affiliation(s)
- Anjum Hajat
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA
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21
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Gray SC, Edwards SE, Miranda ML. Race, socioeconomic status, and air pollution exposure in North Carolina. ENVIRONMENTAL RESEARCH 2013; 126:152-8. [PMID: 23850144 DOI: 10.1016/j.envres.2013.06.005] [Citation(s) in RCA: 80] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2012] [Revised: 03/07/2013] [Accepted: 06/13/2013] [Indexed: 05/18/2023]
Abstract
BACKGROUND Although studies suggest that exposure to pollutants is associated with race/ethnicity and socio-economic status (SES), many studies are limited to the geographic regions where monitoring stations are located. OBJECTIVES This study uses modeled predictive surfaces to examine the relationship between air pollution exposure, race/ethnicity, and measures of SES across the entire State of North Carolina. METHODS The daily predictions of particulate matter <2.5 µm in aerodynamic diameter (PM2.5) and ozone (O3) were determined using a spatial model that fused data from two sources: point air monitoring data and gridded numerical output. These daily predicted pollution levels for 2002 were linked with Census data. We examine the relationship between the census-tract level predicted concentration measures, SES, and racial composition. RESULTS SES and race/ethnicity were related to predicted concentrations of both PM2.5 and O3 for census tracts in North Carolina. Lower SES and higher proportion minority population were associated with higher levels of PM2.5. An interquartile range (IQR) increase of median household income reduced the predicted average PM2.5 level by 0.10 µg/m3. The opposite relationship was true for O3. An IQR increase of median household income increased the predicted average O3 measure by 0.11 ppb. CONCLUSIONS The analyses demonstrate that SES and race/ethnicity are related to predicted estimates of PM2.5 and O3 for census tracts in North Carolina. These findings offer a baseline for future exposure modeling work involving SES and air pollution for the entire state and not just among the populations residing near monitoring networks.
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Affiliation(s)
- Simone C Gray
- Children's Environmental Health Initiative, School of Natural Resources and Environment, University of Michigan, Ann Arbor, MI, USA.
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Schwartz J, Bellinger D, Glass T. Exploring potential sources of differential vulnerability and susceptibility in risk from environmental hazards to expand the scope of risk assessment. Am J Public Health 2011; 101 Suppl 1:S94-101. [PMID: 22021315 DOI: 10.2105/ajph.2011.300272] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Genetic factors, other exposures, individual disease states and allostatic load, psychosocial stress, and socioeconomic position all have the potential to modify the response to environmental exposures. Moreover, many of these modifiers covary with the exposure, leading to much higher risks in some subgroups. These are not theoretical concerns; rather, all these patterns have already been demonstrated in studies of the effects of lead and air pollution. However, recent regulatory impact assessments for these exposures have generally not incorporated these findings. Therefore, differential risk and vulnerability is a critically important but neglected area within risk assessment, and should be incorporated in the future.
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Affiliation(s)
- Joel Schwartz
- Department of Environmental Health and Epidemiology, Harvard School of Public Health, and Harvard Center for Risk Analysis, Harvard University, Boston, MA 02215, USA.
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Brochu PJ, Yanosky JD, Paciorek CJ, Schwartz J, Chen JT, Herrick RF, Suh HH. Particulate air pollution and socioeconomic position in rural and urban areas of the Northeastern United States. Am J Public Health 2011; 101 Suppl 1:S224-30. [PMID: 21836114 DOI: 10.2105/ajph.2011.300232] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
OBJECTIVES Although differential exposure by socioeconomic position (SEP) to hazardous waste and lead is well demonstrated, there is less evidence for particulate air pollution (PM), which is associated with risk of death and illness. This study determined the relationship of ambient PM and SEP across several spatial scales. METHODS Geographic information system-based, spatio-temporal models were used to predict PM in the Northeastern United States. Predicted concentrations were related to census tract SEP and racial composition using generalized additive models. RESULTS Lower SEP was associated with small, significant increases in PM. Annual PM(10) decreased between 0.09 and 0.93 micrograms per cubic meter and PM(2.5) between 0.02 and 0.94 micrograms per cubic meter for interquartile range increases in income. Decrements in PM with SEP increased with spatial scale, indicating that between-city spatial gradients were greater than within-city differences. The PM-SEP relation in urban tracts was not substantially modified by racial composition. CONCLUSIONS Lower compared with higher SEP populations were exposed to higher ambient PM in the Northeastern United States. Given the small percentage change in annual PM(2.5) and PM(10), SEP was not likely a major source of confounding in epidemiological studies of PM, especially those conducted within a single urban/metropolitan area.
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Affiliation(s)
- Paul J Brochu
- Exposure, Epidemiology and Risk Program, Department of Environmental Health, Harvard School of Public Health, Boston, MA 02465, USA
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Oiamo TH, Luginaah IN, Atari DO, Gorey KM. Air pollution and general practitioner access and utilization: a population based study in Sarnia, 'Chemical Valley,' Ontario. Environ Health 2011; 10:71. [PMID: 21827645 PMCID: PMC3171295 DOI: 10.1186/1476-069x-10-71] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2011] [Accepted: 08/09/2011] [Indexed: 05/06/2023]
Abstract
BACKGROUND Health impacts of poor environmental quality have been identified in studies around the world and in Canada. While many of the studies have identified associations between air pollution and mortality or morbidity, few have focused on the role of health care as a potential moderator of impacts. This study assessed the determinants of health care access and utilization in the context of ambient air pollution in Sarnia, Ontario, Canada. METHODS Residents of Sarnia participated in a Community Health Study administered by phone, while several ambient air pollutants including nitrogen dioxide (NO2), sulphur dioxide (SO2) and the volatile organic compounds benzene, toluene, ethylbenzene, mp- and o-xylene (BTEX) were monitored across the city. Land Use Regression models were used to estimate individual exposures to the measured pollutants and logistic regression models were utilized to assess the relative influence of environmental, socioeconomic and health related covariates on general practitioner access and utilization outcomes. RESULTS The results show that general practitioner use increased with levels of exposure to nitrogen dioxide (NO2- Odds Ratio [OR]: 1.16, p < 0.05) and sulphur dioxide (SO2- OR: 1.61, p < 0.05). Low household income was a stronger predictor of having no family doctor in areas exposed to high concentrations of NO2 and SO2. Respondents without regular care living in high pollution areas were also more likely to report travelling or waiting for care in excess of 20 minutes (OR: 3.28, p < 0.05) than their low exposure counterparts (OR: 1.11, p > 0.05). CONCLUSIONS This study provides evidence for inequitable health care access and utilization in Sarnia, with particular relevance to its situation as a sentinel high exposure environment. Levels of exposure to pollution appears to influence utilization of health care services, but poor access to primary health care services additionally burden certain groups in Sarnia, Ontario, Canada.
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Affiliation(s)
- Tor H Oiamo
- Department of Geography, The University of Western Ontario, London, Ontario, Canada
| | - Isaac N Luginaah
- Department of Geography, The University of Western Ontario, London, Ontario, Canada
| | - Dominic O Atari
- Department of Geography, Nipissing University, North Bay, Ontario, Canada
| | - Kevin M Gorey
- School of Social Work, University of Windsor, Ontario, Canada
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Llop S, Ballester F, Estarlich M, Iñiguez C, Ramón R, Gonzalez MC, Murcia M, Esplugues A, Rebagliato M. Social factors associated with nitrogen dioxide (NO2) exposure during pregnancy: the INMA-Valencia project in Spain. Soc Sci Med 2011; 72:890-8. [PMID: 21345566 DOI: 10.1016/j.socscimed.2010.12.018] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2009] [Revised: 09/03/2010] [Accepted: 12/16/2010] [Indexed: 10/18/2022]
Abstract
Numerous studies have focused on the effects of exposure to air pollution on health; however, certain subsets of the population tend to be more exposed to such pollutants depending on their social or demographic characteristics. In addition, exposure to toxicants during pregnancy may play a deleterious role in fetal development as fetuses are especially vulnerable to external insults. The present study was carried out within the framework of the INMA (Infancia y Medio Ambiente or Childhood and the Environment) multicenter cohort study with the objective of identifying the social, demographic, and life-style factors associated with nitrogen dioxide (NO(2)) exposure in the subjects in the cohort. The study comprised 785 pregnant women who formed part of the INMA cohort in Valencia, Spain. Outdoor levels of NO(2) were measured at 93 sampling sites spread over the study area during four different sampling periods lasting 7 days each. Multiple regression models were used for mapping outdoor NO(2) throughout the area. Individual exposure was assigned as: 1) the estimated outdoor NO(2) levels at home, and 2) the average of estimated outdoor NO(2) levels at home and work, weighted according to the time spent in each environment. The subjects' socio-demographic and life-style information was obtained through a questionnaire. In the multiple linear analyses, the outdoor NO(2) levels assigned to each home were taken to be the dependent variable. Other variables included in the model were: age, country of origin, smoking during pregnancy, parity, season of the year, and social class. These same variables remained in the model when the dependent variable was changed to the NO(2) levels adjusted for the subjects' time-activity patterns. We found that younger women, those coming from Latin American countries, and those belonging to the lower social strata were exposed to higher NO(2) levels, both as measured outside their homes as well as when time-activity patterns were taken into account. These subgroups also have a higher probability of being exposed to NO(2) levels over 40 μg/m(3), which is the annual limit for maximum safe exposure, as established by European Directive 2008/50/EC.
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Affiliation(s)
- Sabrina Llop
- Unit of Environment and Health, Centre of Public Health Research (CSISP), Valencia, Spain.
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