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Mork D, Delaney S, Dominici F. Policy-induced air pollution health disparities: Statistical and data science considerations. Science 2024; 385:391-396. [PMID: 39052789 DOI: 10.1126/science.adp1870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Accepted: 06/13/2024] [Indexed: 07/27/2024]
Abstract
Air pollution causes premature death and disease and disproportionately harms non-white and lower-income groups in the United States. Government policies are responsible for the racial disparity in air pollution exposure and related health outcomes. Investigating complex relationships between policies, air pollution, and health requires (i) harmonized data connecting policies, environmental exposures, socioeconomic characteristics, and health at the individual and area level; (ii) interpretable estimands accounting for the complex interplay between policies and disparities in exposures and health outcomes; and (iii) data science approaches that can elucidate direct and indirect policy effects on disparities to identify effective interventions. We review statistical considerations and new data science approaches needed to scrutinize the policy impacts on disparities in air pollution exposure and health outcomes.
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Affiliation(s)
- Daniel Mork
- Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Scott Delaney
- Department of Environmental Health, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Francesca Dominici
- Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, MA, USA
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Boogaard H, Crouse DL, Tanner E, Mantus E, van Erp AM, Vedal S, Samet J. Assessing Adverse Health Effects of Long-Term Exposure to Low Levels of Ambient Air Pollution: The HEI Experience and What's Next? ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:12767-12783. [PMID: 38991107 PMCID: PMC11270999 DOI: 10.1021/acs.est.3c09745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 06/14/2024] [Accepted: 06/14/2024] [Indexed: 07/13/2024]
Abstract
Although concentrations of ambient air pollution continue to decline in high-income regions, epidemiological studies document adverse health effects at levels below current standards in many countries. The Health Effects Institute (HEI) recently completed a comprehensive research initiative to investigate the health effects of long-term exposure to low levels of air pollution in the United States (U.S.), Canada, and Europe. We provide an overview and synthesis of the results of this initiative along with other key research, the strengths and limitations of the research, and remaining research needs. The three studies funded through the HEI initiative estimated the effects of long-term ambient exposure to fine particulate matter (PM2.5), nitrogen dioxide, ozone, and other pollutants on a broad range of health outcomes, including cause-specific mortality and cardiovascular and respiratory morbidity. To ensure high quality research and comparability across studies, HEI worked actively with the study teams and engaged independent expert panels for project oversight and review. All three studies documented positive associations between mortality and exposure to PM2.5 below the U.S. National Ambient Air Quality Standards and current and proposed European Union limit values. Furthermore, the studies observed nonthreshold linear (U.S.), or supra-linear (Canada and Europe) exposure-response functions for PM2.5 and mortality. Heterogeneity was found in both the magnitude and shape of this association within and across studies. Strengths of the studies included the large populations (7-69 million), state-of-the-art exposure assessment methods, and thorough statistical analyses that applied novel methods. Future work is needed to better understand potential sources of heterogeneity in the findings across studies and regions. Other areas of future work include the changing and evolving nature of PM components and sources, including wildfires, and the role of indoor environments. This research initiative provided important new evidence of the adverse effects of long-term exposures to low levels of air pollution at and below current standards, suggesting that further reductions could yield larger benefits than previously anticipated.
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Affiliation(s)
- Hanna Boogaard
- Health
Effects Institute, 75 Federal Street, Boston, Massachusetts 02110-1940, United States
| | - Dan L. Crouse
- Health
Effects Institute, 75 Federal Street, Boston, Massachusetts 02110-1940, United States
| | - Eva Tanner
- Health
Effects Institute, 75 Federal Street, Boston, Massachusetts 02110-1940, United States
| | - Ellen Mantus
- Health
Effects Institute, 75 Federal Street, Boston, Massachusetts 02110-1940, United States
| | - Annemoon M. van Erp
- Health
Effects Institute, 75 Federal Street, Boston, Massachusetts 02110-1940, United States
| | - Sverre Vedal
- Department
of Environmental & Occupational Health Sciences, University of Washington, 4225 Roosevelt Way N.E., Seattle, Washington 98105, United States
| | - Jonathan Samet
- Department
of Environmental & Occupational Health, Department of Epidemiology, Colorado School of Public Health, 13001 East 17th Place, Aurora, Colorado 80045, United States
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3
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de Souza P, Anenberg S, Makarewicz C, Shirgaokar M, Duarte F, Ratti C, Durant JL, Kinney PL, Niemeier D. Quantifying Disparities in Air Pollution Exposures across the United States Using Home and Work Addresses. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:280-290. [PMID: 38153403 DOI: 10.1021/acs.est.3c07926] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2023]
Abstract
While human mobility plays a crucial role in determining ambient air pollution exposures and health risks, research to date has assessed risks on the basis of almost solely residential location. Here, we leveraged a database of ∼128-144 million workers in the United States and published ambient PM2.5 data between 2011 and 2018 to explore how incorporating information on both workplace and residential location changes our understanding of disparities in air pollution exposure. In general, we observed higher workplace exposures relative to home exposures, as well as increased exposures for nonwhite and less educated workers relative to the national average. Workplace exposure disparities were higher among racial and ethnic groups and job types than by income, education, age, and sex. Not considering workplace exposures can lead to systematic underestimations in disparities in exposure among these subpopulations. We also quantified the error in assigning workers home instead of a weighted home-and-work exposure. We observed that biases in associations between PM2.5 and health impacts by using home instead of home-and-work exposure were the highest among urban, younger populations.
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Affiliation(s)
- Priyanka de Souza
- Department of Urban and Regional Planning, University of Colorado Denver, Denver, Colorado 80202, United States
- CU Population Center, University of Colorado Boulder, Boulder, Colorado 80302, United States
- Senseable City Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Susan Anenberg
- Milken Institute School of Public Health, George Washington University, Washington, D.C. 20037, United States
| | - Carrie Makarewicz
- Department of Urban and Regional Planning, University of Colorado Denver, Denver, Colorado 80202, United States
| | - Manish Shirgaokar
- Department of Urban and Regional Planning, University of Colorado Denver, Denver, Colorado 80202, United States
| | - Fabio Duarte
- Senseable City Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Carlo Ratti
- Senseable City Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - John L Durant
- Department of Civil and Environmental Engineering, Tufts University, Medford, Massachusetts 02155, United States
| | - Patrick L Kinney
- Boston University School of Public Health, Boston, Massachusetts 02118, United States
| | - Deb Niemeier
- Department of Civil and Environmental Engineering, University of Maryland, College Park, Maryland 20742, United States
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Henneman L, Choirat C, Dedoussi I, Dominici F, Roberts J, Zigler C. Mortality risk from United States coal electricity generation. Science 2023; 382:941-946. [PMID: 37995235 PMCID: PMC10870829 DOI: 10.1126/science.adf4915] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 10/02/2023] [Indexed: 11/25/2023]
Abstract
Policy-makers seeking to limit the impact of coal electricity-generating units (EGUs, also known as power plants) on air quality and climate justify regulations by quantifying the health burden attributable to exposure from these sources. We defined "coal PM2.5" as fine particulate matter associated with coal EGU sulfur dioxide emissions and estimated annual exposure to coal PM2.5 from 480 EGUs in the US. We estimated the number of deaths attributable to coal PM2.5 from 1999 to 2020 using individual-level Medicare death records representing 650 million person-years. Exposure to coal PM2.5 was associated with 2.1 times greater mortality risk than exposure to PM2.5 from all sources. A total of 460,000 deaths were attributable to coal PM2.5, representing 25% of all PM2.5-related Medicare deaths before 2009 and 7% after 2012. Here, we quantify and visualize the contribution of individual EGUs to mortality.
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Affiliation(s)
- Lucas Henneman
- Department of Civil, Environmental, and Infrastructure Engineering, George Mason University Volgenau School of Engineering, Fairfax, VA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard Data Science Initiative, Harvard University, Boston, MA, USA
| | - Christine Choirat
- Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Irene Dedoussi
- Section Aircraft Noise and Climate Effects, Faculty of Aerospace Engineering, Delft University of Technology, Delft, Netherlands
| | - Francesca Dominici
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard Data Science Initiative, Harvard University, Boston, MA, USA
| | - Jessica Roberts
- School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA, USA
| | - Corwin Zigler
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard Data Science Initiative, Harvard University, Boston, MA, USA
- Department of Statistics and Data Sciences, University of Texas, Austin, TX, USA
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deSouza P, Wang A, Machida Y, Duhl T, Mora S, Kumar P, Kahn R, Ratti C, Durant JL, Hudda N. Evaluating the Performance of Low-Cost PM 2.5 Sensors in Mobile Settings. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:15401-15411. [PMID: 37789620 DOI: 10.1021/acs.est.3c04843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Low-cost sensors (LCSs) for measuring air pollution are increasingly being deployed in mobile applications, but questions concerning the quality of the measurements remain unanswered. For example, what is the best way to correct LCS data in a mobile setting? Which factors most significantly contribute to differences between mobile LCS data and those of higher-quality instruments? Can data from LCSs be used to identify hotspots and generate generalizable pollutant concentration maps? To help address these questions, we deployed low-cost PM2.5 sensors (Alphasense OPC-N3) and a research-grade instrument (TSI DustTrak) in a mobile laboratory in Boston, MA, USA. We first collocated these instruments with stationary PM2.5 reference monitors (Teledyne T640) at nearby regulatory sites. Next, using the reference measurements, we developed different models to correct the OPC-N3 and DustTrak measurements and then transferred the corrections to the mobile setting. We observed that more complex correction models appeared to perform better than simpler models in the stationary setting; however, when transferred to the mobile setting, corrected OPC-N3 measurements agreed less well with the corrected DustTrak data. In general, corrections developed by using minute-level collocation measurements transferred better to the mobile setting than corrections developed using hourly-averaged data. Mobile laboratory speed, OPC-N3 orientation relative to the direction of travel, date, hour-of-the-day, and road class together explain a small but significant amount of variation between corrected OPC-N3 and DustTrak measurements during the mobile deployment. Persistent hotspots identified by the OPC-N3s agreed with those identified by the DustTrak. Similarly, maps of PM2.5 distribution produced from the mobile corrected OPC-N3 and DustTrak measurements agreed well. These results suggest that identifying hotspots and developing generalizable maps of PM2.5 are appropriate use-cases for mobile LCS data.
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Affiliation(s)
- Priyanka deSouza
- Department of Urban and Regional Planning, University of Colorado Denver, Denver, Colorado 80217, United States
- CU Population Center, University of Colorado Boulder, Boulder, Colorado 80309, United States
| | - An Wang
- MIT Senseable City Lab, Cambridge, Massachusetts 02139, United States
| | - Yuki Machida
- MIT Senseable City Lab, Cambridge, Massachusetts 02139, United States
| | - Tiffany Duhl
- Department of Civil and Environmental Engineering, Tufts University, Medford, Massachusetts 02155, United States
| | - Simone Mora
- MIT Senseable City Lab, Cambridge, Massachusetts 02139, United States
| | - Prashant Kumar
- Global Centre for Clean Air Research (GCARE), School of Sustainability, Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, GU2 7XH Surrey, U.K
- Institute for Sustainability, University of Surrey, Guildford, GU2 7XH Surrey, U.K
| | - Ralph Kahn
- NASA Goddard Space Flight Center, Greenbelt, Maryland 20771, United States
| | - Carlo Ratti
- MIT Senseable City Lab, Cambridge, Massachusetts 02139, United States
| | - John L Durant
- Department of Civil and Environmental Engineering, Tufts University, Medford, Massachusetts 02155, United States
| | - Neelakshi Hudda
- Department of Civil and Environmental Engineering, Tufts University, Medford, Massachusetts 02155, United States
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Josey K, Nethery R, Visaria A, Bates B, Gandhi P, Parthasarathi A, Rua M, Robinson D, Setoguchi S. Retrospective cohort study investigating synergism of air pollution and corticosteroid exposure in promoting cardiovascular and thromboembolic events in older adults. BMJ Open 2023; 13:e072810. [PMID: 37709308 PMCID: PMC10503335 DOI: 10.1136/bmjopen-2023-072810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 08/14/2023] [Indexed: 09/16/2023] Open
Abstract
OBJECTIVE To evaluate the synergistic effects created by fine particulate matter (PM2.5) and corticosteroid use on hospitalisation and mortality in older adults at high risk for cardiovascular thromboembolic events (CTEs). DESIGN AND SETTING A retrospective cohort study using a US nationwide administrative healthcare claims database. PARTICIPANTS A 50% random sample of participants with high-risk conditions for CTE from the 2008-2016 Medicare Fee-for-Service population. EXPOSURES Corticosteroid therapy and seasonal-average PM2.5. MAIN OUTCOME MEASURES Incidences of myocardial infarction or acute coronary syndrome (MI/ACS), ischaemic stroke or transient ischaemic attack, heart failure (HF), venous thromboembolism, atrial fibrillation and all-cause mortality. We assessed additive interactions between PM2.5 and corticosteroids using estimates of the relative excess risk due to interaction (RERI) obtained using marginal structural models for causal inference. RESULTS Among the 1 936 786 individuals in the high CTE risk cohort (mean age 76.8, 40.0% male, 87.4% white), the mean PM2.5 exposure level was 8.3±2.4 µg/m3 and 37.7% had at least one prescription for a systemic corticosteroid during follow-up. For all outcomes, we observed increases in risk associated with corticosteroid use and with increasing PM2.5 exposure. PM2.5 demonstrated a non-linear relationship with some outcomes. We also observed evidence of an interaction existing between corticosteroid use and PM2.5 for some CTEs. For an increase in PM2.5 from 8 μg/m3 to 12 μg/m3 (a policy-relevant change), the RERI of corticosteroid use and PM2.5 was significant for HF (15.6%, 95% CI 4.0%, 27.3%). Increasing PM2.5 from 5 μg/m3 to 10 μg/m3 yielded significant RERIs for incidences of HF (32.4; 95% CI 14.9%, 49.9%) and MI/ACSs (29.8%; 95% CI 5.5%, 54.0%). CONCLUSION PM2.5 and systemic corticosteroid use were independently associated with increases in CTE hospitalisations. We also found evidence of significant additive interactions between the two exposures for HF and MI/ACSs suggesting synergy between these two exposures.
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Affiliation(s)
- Kevin Josey
- Department of Biostatistics, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA
| | - Rachel Nethery
- Department of Biostatistics, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA
| | - Aayush Visaria
- Department of Medicine, Rutgers Robert Wood Johnson Medical School, Piscataway, New Jersey, USA
| | - Benjamin Bates
- Department of Medicine, Rutgers Robert Wood Johnson Medical School, Piscataway, New Jersey, USA
| | - Poonam Gandhi
- Rutgers University Institute for Health, Health Care Policy and Aging Research, New Brunswick, New Jersey, USA
| | - Ashwaghosha Parthasarathi
- Rutgers University Institute for Health, Health Care Policy and Aging Research, New Brunswick, New Jersey, USA
| | - Melanie Rua
- Rutgers University Institute for Health, Health Care Policy and Aging Research, New Brunswick, New Jersey, USA
| | - David Robinson
- Department of Geography, Rutgers The State University of New Jersey, New Brunswick, New Jersey, USA
| | - Soko Setoguchi
- Department of Medicine, Rutgers Robert Wood Johnson Medical School, Piscataway, New Jersey, USA
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Nethery RC, Josey K, Gandhi P, Kim JH, Visaria A, Bates B, Schwartz J, Robinson D, Setoguchi S. Air Pollution and Cardiovascular and Thromboembolic Events in Older Adults With High-Risk Conditions. Am J Epidemiol 2023; 192:1358-1370. [PMID: 37070398 PMCID: PMC10666966 DOI: 10.1093/aje/kwad089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 01/11/2023] [Accepted: 04/11/2023] [Indexed: 04/19/2023] Open
Abstract
Little epidemiologic research has focused on pollution-related risks in medically vulnerable or marginalized groups. Using a nationwide 50% random sample of 2008-2016 Medicare Part D-eligible fee-for-service participants in the United States, we identified a cohort with high-risk conditions for cardiovascular and thromboembolic events (CTEs) and linked individuals with seasonal average zip-code-level concentrations of fine particulate matter (particulate matter with an aerodynamic diameter ≤ 2.5 μm (PM2.5)). We assessed the relationship between seasonal PM2.5 exposure and hospitalization for each of 7 CTE-related causes using history-adjusted marginal structural models with adjustment for individual demographic and neighborhood socioeconomic variables, as well as baseline comorbidity, health behaviors, and health-service measures. We examined effect modification across geographically and demographically defined subgroups. The cohort included 1,934,453 individuals with high-risk conditions (mean age = 77 years; 60% female, 87% White). A 1-μg/m3 increase in PM2.5 exposure was significantly associated with increased risk of 6 out of 7 types of CTE hospitalization. Strong increases were observed for transient ischemic attack (hazard ratio (HR) = 1.039, 95% confidence interval (CI): 1.034, 1.044), venous thromboembolism (HR = 1.031, 95% CI: 1.027, 1.035), and heart failure (HR = 1.019, 95% CI: 1.017, 1.020). Asian Americans were found to be particularly susceptible to thromboembolic effects of PM2.5 (venous thromboembolism: HR = 1.063, 95% CI: 1.021, 1.106), while Native Americans were most vulnerable to cerebrovascular effects (transient ischemic attack: HR = 1.093, 95% CI: 1.030, 1.161).
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Affiliation(s)
- Rachel C Nethery
- Correspondence to Dr. Rachel C. Nethery, Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Building 2, 4th Floor, Boston, MA 02115 (e-mail: )
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Josey KP, Delaney SW, Wu X, Nethery RC, DeSouza P, Braun D, Dominici F. Air Pollution and Mortality at the Intersection of Race and Social Class. N Engl J Med 2023; 388:1396-1404. [PMID: 36961127 PMCID: PMC10182569 DOI: 10.1056/nejmsa2300523] [Citation(s) in RCA: 59] [Impact Index Per Article: 59.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/25/2023]
Abstract
BACKGROUND Black Americans are exposed to higher annual levels of air pollution containing fine particulate matter (particles with an aerodynamic diameter of ≤2.5 μm [PM2.5]) than White Americans and may be more susceptible to its health effects. Low-income Americans may also be more susceptible to PM2.5 pollution than high-income Americans. Because information is lacking on exposure-response curves for PM2.5 exposure and mortality among marginalized subpopulations categorized according to both race and socioeconomic position, the Environmental Protection Agency lacks important evidence to inform its regulatory rulemaking for PM2.5 standards. METHODS We analyzed 623 million person-years of Medicare data from 73 million persons 65 years of age or older from 2000 through 2016 to estimate associations between annual PM2.5 exposure and mortality in subpopulations defined simultaneously by racial identity (Black vs. White) and income level (Medicaid eligible vs. ineligible). RESULTS Lower PM2.5 exposure was associated with lower mortality in the full population, but marginalized subpopulations appeared to benefit more as PM2.5 levels decreased. For example, the hazard ratio associated with decreasing PM2.5 from 12 μg per cubic meter to 8 μg per cubic meter for the White higher-income subpopulation was 0.963 (95% confidence interval [CI], 0.955 to 0.970), whereas equivalent hazard ratios for marginalized subpopulations were lower: 0.931 (95% CI, 0.909 to 0.953) for the Black higher-income subpopulation, 0.940 (95% CI, 0.931 to 0.948) for the White low-income subpopulation, and 0.939 (95% CI, 0.921 to 0.957) for the Black low-income subpopulation. CONCLUSIONS Higher-income Black persons, low-income White persons, and low-income Black persons may benefit more from lower PM2.5 levels than higher-income White persons. These findings underscore the importance of considering racial identity and income together when assessing health inequities. (Funded by the National Institutes of Health and the Alfred P. Sloan Foundation.).
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Affiliation(s)
- Kevin P Josey
- From the Departments of Biostatistics (K.P.J., R.C.N., D.B., F.D.) and Environmental Health (S.W.D.), Harvard T.H. Chan School of Public Health, Boston; the Department of Biostatistics, Mailman School of Public Health, Columbia University, New York (X.W.); and the Department of Urban and Regional Planning, University of Colorado Denver, Denver (P.D.)
| | - Scott W Delaney
- From the Departments of Biostatistics (K.P.J., R.C.N., D.B., F.D.) and Environmental Health (S.W.D.), Harvard T.H. Chan School of Public Health, Boston; the Department of Biostatistics, Mailman School of Public Health, Columbia University, New York (X.W.); and the Department of Urban and Regional Planning, University of Colorado Denver, Denver (P.D.)
| | - Xiao Wu
- From the Departments of Biostatistics (K.P.J., R.C.N., D.B., F.D.) and Environmental Health (S.W.D.), Harvard T.H. Chan School of Public Health, Boston; the Department of Biostatistics, Mailman School of Public Health, Columbia University, New York (X.W.); and the Department of Urban and Regional Planning, University of Colorado Denver, Denver (P.D.)
| | - Rachel C Nethery
- From the Departments of Biostatistics (K.P.J., R.C.N., D.B., F.D.) and Environmental Health (S.W.D.), Harvard T.H. Chan School of Public Health, Boston; the Department of Biostatistics, Mailman School of Public Health, Columbia University, New York (X.W.); and the Department of Urban and Regional Planning, University of Colorado Denver, Denver (P.D.)
| | - Priyanka DeSouza
- From the Departments of Biostatistics (K.P.J., R.C.N., D.B., F.D.) and Environmental Health (S.W.D.), Harvard T.H. Chan School of Public Health, Boston; the Department of Biostatistics, Mailman School of Public Health, Columbia University, New York (X.W.); and the Department of Urban and Regional Planning, University of Colorado Denver, Denver (P.D.)
| | - Danielle Braun
- From the Departments of Biostatistics (K.P.J., R.C.N., D.B., F.D.) and Environmental Health (S.W.D.), Harvard T.H. Chan School of Public Health, Boston; the Department of Biostatistics, Mailman School of Public Health, Columbia University, New York (X.W.); and the Department of Urban and Regional Planning, University of Colorado Denver, Denver (P.D.)
| | - Francesca Dominici
- From the Departments of Biostatistics (K.P.J., R.C.N., D.B., F.D.) and Environmental Health (S.W.D.), Harvard T.H. Chan School of Public Health, Boston; the Department of Biostatistics, Mailman School of Public Health, Columbia University, New York (X.W.); and the Department of Urban and Regional Planning, University of Colorado Denver, Denver (P.D.)
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Mork D, Braun D, Zanobetti A. Time-lagged relationships between a decade of air pollution exposure and first hospitalization with Alzheimer's disease and related dementias. ENVIRONMENT INTERNATIONAL 2023; 171:107694. [PMID: 36521347 PMCID: PMC9885762 DOI: 10.1016/j.envint.2022.107694] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 12/11/2022] [Accepted: 12/11/2022] [Indexed: 05/09/2023]
Abstract
Alzheimer's disease and related dementias (ADRD) poses substantial health challenges among an aging population. One of the primary challenges in studying ADRD is that biological processes underlying these ailments begin decades prior to diagnosis. Previous studies indicate a relationship between ADRD and air pollution exposure to both fine particulate matter (PM2.5) and nitrogen dioxide (NO2) but are limited in their interpretation because they consider exposure measurements at a single time point. Our retrospective cohort study considered 27 + million Medicare enrollees in the United States followed up to 17 years and matched with highly accurate annual air pollution exposure measurements for PM2.5, NO2, and summer ozone. We applied distributed lag models and estimated the lagged associations between air pollution and odds of first hospitalization with ADRD. We found significantly increased odds due to overall PM2.5 and NO2 exposure and time-lagged exposure 10 and 8 years prior to admission, respectively. Furthermore, we found the connection between air pollution exposure and increased odds of first hospitalization with ADRD exists at air pollution levels below current National Ambient Air Quality Standards set by the US Environmental Protection Agency, with the steepest increase in odds occurring at low concentrations of PM2.5. Our findings are the first to show that air pollution exposures from as many as 10 years prior to the admission are related to increased odds of hospitalizations with ADRD. As there are no clear treatments available for ADRD, identifying modifiable risk factors such as air pollution exposure may make significant contributions towards prevention or delayed disease progression.
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Affiliation(s)
- Daniel Mork
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Danielle Braun
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Antonella Zanobetti
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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