A comparison of PM exposure estimates from different estimation methods and their associations with cognitive testing and brain MRI outcomes

Melinda C. Power, Milken Institute School of Public Health, George Washington University, 950 New Hampshire Ave, Washington, DC, 20052, USA. Electronic address: power@gwu.edu.
Katie M. Lynch, Milken Institute School of Public Health, George Washington University, 950 New Hampshire Ave, Washington, DC, 20052, USA.
Erin E. Bennett, Milken Institute School of Public Health, George Washington University, 950 New Hampshire Ave, Washington, DC, 20052, USA.
Qi Ying, Zachry Department of Civil & Environmental Engineering, Texas A&M University, 201 Dwight Look, College Station, TX, 77840, USA.
Eun Sug Park, Texas A&M Transportation Institute, Texas A&M University System, 3135 TAMU, College Station, TX, 77843, USA.
Xiaohui Xu, Department of Epidemiology & Biostatistics, Texas A&M Health Science Center School of Public Health, 212 Adriance Lab Rd, College Station, TX, 77843, USA.
Richard L. Smith, Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, 318 E Cameron Ave, Chapel Hill, NC, 27599, USA; Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Daur Dr, Chapel Hill, NC, 27516, USA.
James D. Stewart, Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Daur Dr, Chapel Hill, NC, 27516, USA.
Jeff D. Yanosky, Department of Public Health Sciences, College of Medicine, The Pennsylvania State University, 700 HMC Cres Rd, Hershey, PA, 17033, USA.
Duanping Liao, Department of Public Health Sciences, College of Medicine, The Pennsylvania State University, 700 HMC Cres Rd, Hershey, PA, 17033, USA.
Aaron van Donkelaar, Department of Energy, Environmental, and Chemical Engineering McKelvey School of Engineering, 1 Brookings Dr, St. Louis, MO, 63130, USA.
Joel D. Kaufman, Department of Medicine, School of Medicine, University of Washington, 1959 NE Pacific St, Seattle, WA, 98195, USA; Department of Epidemiology, School of Public Health, University of Washington, 3980 15th Ave NE, Seattle, WA, 98195, USA; Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, 3980 15th Ave NE, Seattle, WA, 98195, USA.
Lianne Sheppard, Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, 3980 15th Ave NE, Seattle, WA, 98195, USA; Department of Biostatistics, School of Public Health, University of Washington, 3980 15th Ave NE, Seattle, WA, 98195, USA.
Adam A. Szpiro, Department of Biostatistics, School of Public Health, University of Washington, 3980 15th Ave NE, Seattle, WA, 98195, USA.
Eric A. Whitsel, Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Daur Dr, Chapel Hill, NC, 27516, USA; Department of Medicine, School of Medicine, University of North Carolina at Chapel Hill, 321 S Columbia St, Chapel Hill, NC, 27599, USA.

Document Type

Journal Article

Publication Date

5-18-2024

Journal

Environmental research

Volume

256

DOI

10.1016/j.envres.2024.119178

Keywords

Air pollution; Cognition; Dementia; Exposure assessment; Particulate matter

Abstract

BACKGROUND: Reported associations between particulate matter with aerodynamic diameter ≤2.5 μm (PM) and cognitive outcomes remain mixed. Differences in exposure estimation method may contribute to this heterogeneity. OBJECTIVES: To assess agreement between PM exposure concentrations across 11 exposure estimation methods and to compare resulting associations between PM and cognitive or MRI outcomes. METHODS: We used Visit 5 (2011-2013) cognitive testing and brain MRI data from the Atherosclerosis Risk in Communities (ARIC) Study. We derived address-linked average 2000-2007 PM exposure concentrations in areas immediately surrounding the four ARIC recruitment sites (Forsyth County, NC; Jackson, MS; suburbs of Minneapolis, MN; Washington County, MD) using 11 estimation methods. We assessed agreement between method-specific PM concentrations using descriptive statistics and plots, overall and by site. We used adjusted linear regression to estimate associations of method-specific PM exposure estimates with cognitive scores (n = 4678) and MRI outcomes (n = 1518) stratified by study site and combined site-specific estimates using meta-analyses to derive overall estimates. We explored the potential impact of unmeasured confounding by spatially patterned factors. RESULTS: Exposure estimates from most methods had high agreement across sites, but low agreement within sites. Within-site exposure variation was limited for some methods. Consistently null findings for the PM-cognitive outcome associations regardless of method precluded empirical conclusions about the potential impact of method on study findings in contexts where positive associations are observed. Not accounting for study site led to consistent, adverse associations, regardless of exposure estimation method, suggesting the potential for substantial bias due to residual confounding by spatially patterned factors. DISCUSSION: PM estimation methods agreed across sites but not within sites. Choice of estimation method may impact findings when participants are concentrated in small geographic areas. Understanding unmeasured confounding by factors that are spatially patterned may be particularly important in studies of air pollution and cognitive or brain health.

Department

Epidemiology

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