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Comparison of PM2.5 Air Pollution Exposures and Health Effects Associations Using 11 Different Modeling Approaches in the Women's Health Initiative Memory Study (WHIMS).

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Title: Comparison of PM2.5 Air Pollution Exposures and Health Effects Associations Using 11 Different Modeling Approaches in the Women's Health Initiative Memory Study (WHIMS).
Authors: Power, Melinda C.1, Bennett, Erin E.1, Lynch, Katie M.1, Stewart, James D.2, Xiaohui Xu3, Eun Sug Park4, Smith, Richard L.5, Vizuete, Will6, Margolis, Helene G.7, Casanova, Ramon8, Wallace, Robert9,10, Sheppard, Lianne11,12, Qi Ying13, Serre, Marc L.6, Szpiro, Adam A.12, Jiu-Chiuan Chen14,15, Liao, Duanping16, Wellenius, Gregory A.17, van Donkelaar, Aaron18, Yanosky, Jeff D.16
Source: Environmental Health Perspectives. Jan2024, Vol. 132 Issue 1, p017003-1-017003-18. 18p.
Subject Terms: *Air pollution, *Particulate matter, Descriptive statistics, Research funding
Abstract: BACKGROUND: Many approaches to quantifying air pollution exposures have been developed. However, the impact of choice of approach on air pollution estimates and health-effects associations remains unclear. OBJECTIVES: Our objective is to compare particulate matter with aerodynamic diameter ≤2.5 μm (PM2.5) concentrations and resulting health effects associations using multiple estimation approaches previously used in epidemiologic analyses. METHODS: We assigned annual PM2.5 exposure estimates from 1999 to 2004 derived from 11 different approaches to Women’s Health Initiative Memory Study (WHIMS) participant addresses within the contiguous US. Approaches included geostatistical interpolation approaches, land-use regression or spatiotemporal models, satellite-derived approaches, air dispersion and chemical transport models, and hybrid models. We used descriptive statistics and plots to assess relative and absolute agreement among exposure estimates and examined the impact of approach on associations between PM2.5 and death due to natural causes, cardiovascular disease (CVD) mortality, and incident CVD events, adjusting for individual-level covariates and climate-based region. RESULTS: With a few exceptions, relative agreement of approach-specific PM2.5 exposure estimates was high for PM2.5 concentrations across the contiguous US. Agreement among approach-specific exposure estimates was stronger near PM2.5 monitors, in certain regions of the country, and in 2004 vs. 1999. Collectively, our results suggest but do not quantify lower agreement at local spatial scales for PM2.5. There was no evidence of large differences in health effects associations with PM2.5 among estimation approaches in analyses adjusted for climate region. CONCLUSIONS: Different estimation approaches produced similar spatial patterns of PM2.5 concentrations across the contiguous US and in areas with dense monitoring data, and PM2.5-health effects associations were similar among estimation approaches. PM2.5 estimates and PM2.5-health effects associations may differ more in samples drawn from smaller areas or areas without substantial monitoring data, or in analyses with finer adjustment for participant location. Our results can inform decisions about PM2.5 estimation approach in epidemiologic studies, as investigators balance concerns about bias, efficiency, and resource allocation. Future work is needed to understand whether these conclusions also apply in the context of other air pollutants of interest [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: Comparison of PM<subscript>2.5</subscript> Air Pollution Exposures and Health Effects Associations Using 11 Different Modeling Approaches in the Women's Health Initiative Memory Study (WHIMS).
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  Data: <searchLink fieldCode="AR" term="%22Power%2C+Melinda+C%2E%22">Power, Melinda C.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Bennett%2C+Erin+E%2E%22">Bennett, Erin E.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Lynch%2C+Katie+M%2E%22">Lynch, Katie M.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Stewart%2C+James+D%2E%22">Stewart, James D.</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Xiaohui+Xu%22">Xiaohui Xu</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Eun+Sug+Park%22">Eun Sug Park</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Smith%2C+Richard+L%2E%22">Smith, Richard L.</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Vizuete%2C+Will%22">Vizuete, Will</searchLink><relatesTo>6</relatesTo><br /><searchLink fieldCode="AR" term="%22Margolis%2C+Helene+G%2E%22">Margolis, Helene G.</searchLink><relatesTo>7</relatesTo><br /><searchLink fieldCode="AR" term="%22Casanova%2C+Ramon%22">Casanova, Ramon</searchLink><relatesTo>8</relatesTo><br /><searchLink fieldCode="AR" term="%22Wallace%2C+Robert%22">Wallace, Robert</searchLink><relatesTo>9,10</relatesTo><br /><searchLink fieldCode="AR" term="%22Sheppard%2C+Lianne%22">Sheppard, Lianne</searchLink><relatesTo>11,12</relatesTo><br /><searchLink fieldCode="AR" term="%22Qi+Ying%22">Qi Ying</searchLink><relatesTo>13</relatesTo><br /><searchLink fieldCode="AR" term="%22Serre%2C+Marc+L%2E%22">Serre, Marc L.</searchLink><relatesTo>6</relatesTo><br /><searchLink fieldCode="AR" term="%22Szpiro%2C+Adam+A%2E%22">Szpiro, Adam A.</searchLink><relatesTo>12</relatesTo><br /><searchLink fieldCode="AR" term="%22Jiu-Chiuan+Chen%22">Jiu-Chiuan Chen</searchLink><relatesTo>14,15</relatesTo><br /><searchLink fieldCode="AR" term="%22Liao%2C+Duanping%22">Liao, Duanping</searchLink><relatesTo>16</relatesTo><br /><searchLink fieldCode="AR" term="%22Wellenius%2C+Gregory+A%2E%22">Wellenius, Gregory A.</searchLink><relatesTo>17</relatesTo><br /><searchLink fieldCode="AR" term="%22van+Donkelaar%2C+Aaron%22">van Donkelaar, Aaron</searchLink><relatesTo>18</relatesTo><br /><searchLink fieldCode="AR" term="%22Yanosky%2C+Jeff+D%2E%22">Yanosky, Jeff D.</searchLink><relatesTo>16</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Environmental+Health+Perspectives%22">Environmental Health Perspectives</searchLink>. Jan2024, Vol. 132 Issue 1, p017003-1-017003-18. 18p.
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  Label: Abstract
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  Data: BACKGROUND: Many approaches to quantifying air pollution exposures have been developed. However, the impact of choice of approach on air pollution estimates and health-effects associations remains unclear. OBJECTIVES: Our objective is to compare particulate matter with aerodynamic diameter ≤2.5 μm (PM2.5) concentrations and resulting health effects associations using multiple estimation approaches previously used in epidemiologic analyses. METHODS: We assigned annual PM2.5 exposure estimates from 1999 to 2004 derived from 11 different approaches to Women’s Health Initiative Memory Study (WHIMS) participant addresses within the contiguous US. Approaches included geostatistical interpolation approaches, land-use regression or spatiotemporal models, satellite-derived approaches, air dispersion and chemical transport models, and hybrid models. We used descriptive statistics and plots to assess relative and absolute agreement among exposure estimates and examined the impact of approach on associations between PM2.5 and death due to natural causes, cardiovascular disease (CVD) mortality, and incident CVD events, adjusting for individual-level covariates and climate-based region. RESULTS: With a few exceptions, relative agreement of approach-specific PM2.5 exposure estimates was high for PM2.5 concentrations across the contiguous US. Agreement among approach-specific exposure estimates was stronger near PM2.5 monitors, in certain regions of the country, and in 2004 vs. 1999. Collectively, our results suggest but do not quantify lower agreement at local spatial scales for PM2.5. There was no evidence of large differences in health effects associations with PM2.5 among estimation approaches in analyses adjusted for climate region. CONCLUSIONS: Different estimation approaches produced similar spatial patterns of PM2.5 concentrations across the contiguous US and in areas with dense monitoring data, and PM2.5-health effects associations were similar among estimation approaches. PM2.5 estimates and PM2.5-health effects associations may differ more in samples drawn from smaller areas or areas without substantial monitoring data, or in analyses with finer adjustment for participant location. Our results can inform decisions about PM2.5 estimation approach in epidemiologic studies, as investigators balance concerns about bias, efficiency, and resource allocation. Future work is needed to understand whether these conclusions also apply in the context of other air pollutants of interest [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/EHP12995
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        Text: English
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      – SubjectFull: Descriptive statistics
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