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Modeling the Residential Infiltration of Outdoor PM2.5 in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air).

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Title: Modeling the Residential Infiltration of Outdoor PM2.5 in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air).
Authors: Allen, Ryan W.1 allenr@sfu.ca, Adar, Sara D.2, Avol, Ed3, Cohen, Martin4, Curl, Cynthia L.4, Larson, Timothy4,5, Liu, L. -J. Sally4,6, Sheppard, Lianne4,7, Kaufman, Joel D.4,8,9
Source: Environmental Health Perspectives. Jun2012, Vol. 120 Issue 6, p824-830. 7p. 2 Charts, 3 Graphs.
Subjects: Epidemiology research methodology, Environmental monitoring, Air pollution, Atherosclerosis, Indoor air pollution, Longitudinal method, Questionnaires, Research funding, Seasons, Environmental exposure, Residential patterns, Particulate matter, Statistical models, Descriptive statistics
Geographic Terms: United States
Abstract: Background: Epidemiologic studies of fine particulate matter [aerodynamic diameter ≤ 2.5 μm (PM2.5)] typically use outdoor concentrations as exposure surrogates. Failure to account for variation in residential infiltration efficiencies (Finf) will affect epidemiologic study results.Objective: We aimed to develop models to predict Finf for > 6,000 homes in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air), a prospective cohort study of PM2.5 exposure, subclinical cardiovascular disease, and clinical outcomes.Methods: We collected 526 two-week, paired indoor-outdoor PM2.5 filter samples from a subset of study homes. PM2.5 elemental composition was measured by X-ray fluorescence, and Finf was estimated as the indoor/outdoor sulfur ratio. We regressed Finf on meteorologic variables and questionnaire-based predictors in season-specific models. Models were evaluated using the R2 and root mean square error (RMSE) from a 10-fold cross-validation.Results: The mean ± SD Finf across all communities and seasons was 0.62 ± 0.21, and community-specific means ranged from 0.47 ± 0.15 in Winston-Salem, North Carolina, to 0.82 ± 0.14 in New York, New York. Finf was generally greater during the warm (> 18°C) season. Central air conditioning (AC) use, frequency of AC use, and window opening frequency were the most important predictors during the warm season; outdoor temperature and forced-air heat were the best cold-season predictors. The models predicted 60% of the variance in 2-week Finf, with an RMSE of 0.13.Conclusions: We developed intuitive models that can predict Finf using easily obtained variables. Using these models, MESA Air will be the first large epidemiologic study to incorporate variation in residential Finf into an exposure assessment. [ABSTRACT FROM AUTHOR]
Copyright of Environmental Health Perspectives is the property of National Institute of Environmental Health Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Modeling the Residential Infiltration of Outdoor PM<subscript>2.5</subscript> in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air).
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  Data: Background: Epidemiologic studies of fine particulate matter [aerodynamic diameter ≤ 2.5 μm (PM2.5)] typically use outdoor concentrations as exposure surrogates. Failure to account for variation in residential infiltration efficiencies (Finf) will affect epidemiologic study results.Objective: We aimed to develop models to predict Finf for > 6,000 homes in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air), a prospective cohort study of PM2.5 exposure, subclinical cardiovascular disease, and clinical outcomes.Methods: We collected 526 two-week, paired indoor-outdoor PM2.5 filter samples from a subset of study homes. PM2.5 elemental composition was measured by X-ray fluorescence, and Finf was estimated as the indoor/outdoor sulfur ratio. We regressed Finf on meteorologic variables and questionnaire-based predictors in season-specific models. Models were evaluated using the R2 and root mean square error (RMSE) from a 10-fold cross-validation.Results: The mean ± SD Finf across all communities and seasons was 0.62 ± 0.21, and community-specific means ranged from 0.47 ± 0.15 in Winston-Salem, North Carolina, to 0.82 ± 0.14 in New York, New York. Finf was generally greater during the warm (> 18°C) season. Central air conditioning (AC) use, frequency of AC use, and window opening frequency were the most important predictors during the warm season; outdoor temperature and forced-air heat were the best cold-season predictors. The models predicted 60% of the variance in 2-week Finf, with an RMSE of 0.13.Conclusions: We developed intuitive models that can predict Finf using easily obtained variables. Using these models, MESA Air will be the first large epidemiologic study to incorporate variation in residential Finf into an exposure assessment. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Environmental Health Perspectives is the property of National Institute of Environmental Health Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1289/ehp.1104447
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        Text: English
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        Type: general
      – SubjectFull: Environmental monitoring
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      – SubjectFull: Air pollution
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      – SubjectFull: Atherosclerosis
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      – SubjectFull: Indoor air pollution
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      – SubjectFull: Residential patterns
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      – SubjectFull: Particulate matter
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      – SubjectFull: Descriptive statistics
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      – SubjectFull: United States
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              Text: Jun2012
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