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Modeling residential indoor concentrations of PM2.5, NO2, NOx,and secondhand smoke in the Subpopulations and Intermediate Outcome Measures in COPD (SPIROMICS) Air study |
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| Authors: | Marina Zusman Amanda J Gassett Kipruto Kirwa R Graham Barr Christopher B Cooper MeiLan K Han Richard E Kanner Kirsten Koehler Victor E Ortega Robert Paine rd Laura Paulin Cheryl Pirozzi Ana Rule Nadia N Hansel Joel D Kaufman |
| Affiliation: | 1. Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA;2. Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA
Contribution: Data curation (lead), Formal analysis (supporting), Methodology (supporting), Project administration (lead), Supervision (supporting), Writing - review & editing (equal);3. Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA Contribution: Writing - review & editing (equal);4. Presbyterian Hospital, Columbia University Medical Center, New York, NY, USA Contribution: Writing - review & editing (equal);5. Department of Medicine, UCLA School of Medicine, Los Angeles, CA, USA Contribution: Writing - review & editing (equal);6. Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI, USA Contribution: Writing - review & editing (equal);7. Division of Respiratory, Critical Care, and Occupational Pulmonary Medicine, Department of Medicine, University of Utah Health Sciences Center, Salt Lake City, UT, USA Contribution: Writing - review & editing (equal);8. Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA;9. Section on Pulmonary, Critical Care, Allergy and Immunologic Diseases, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA Contribution: Writing - review & editing (equal);10. Division of Pulmonary Medicine, University Of Utah Hospital, Salt Lake City, UT, USA Contribution: Writing - review & editing (equal);11. Pulmonary/Critical Care, Dartmouth Hitchcock Medical Center, Lebanon, NH, USA Contribution: Writing - review & editing (equal);12. University of Utah Hospital, Salt Lake City, UT, USA Contribution: Writing - review & editing (equal);13. Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA Contribution: Writing - review & editing (equal);14. Department of Medicine, Johns Hopkins University, Baltimore, MD, USA Contribution: Conceptualization (equal), Data curation (equal), Funding acquisition (equal), Project administration (equal), Resources (equal), Supervision (supporting), Writing - review & editing (equal) |
| Abstract: | Increased outdoor concentrations of fine particulate matter (PM2.5) and oxides of nitrogen (NO2, NOx) are associated with respiratory and cardiovascular morbidity in adults and children. However, people spend most of their time indoors and this is particularly true for individuals with chronic obstructive pulmonary disease (COPD). Both outdoor and indoor air pollution may accelerate lung function loss in individuals with COPD, but it is not feasible to measure indoor pollutant concentrations in all participants in large cohort studies. We aimed to understand indoor exposures in a cohort of adults (SPIROMICS Air, the SubPopulations and Intermediate Outcome Measures in COPD Study of Air pollution). We developed models for the entire cohort based on monitoring in a subset of homes, to predict mean 2-week–measured concentrations of PM2.5, NO2, NOx, and nicotine, using home and behavioral questionnaire responses available in the full cohort. Models incorporating socioeconomic, meteorological, behavioral, and residential information together explained about 60% of the variation in indoor concentration of each pollutant. Cross-validated R2 for best indoor prediction models ranged from 0.43 (NOx) to 0.51 (NO2). Models based on questionnaire responses and estimated outdoor concentrations successfully explained most variation in indoor PM2.5, NO2, NOx, and nicotine concentrations. |
| Keywords: | air pollutants exposure assessment indoor exposure questionnaires indoor monitoring prediction modeling residential behavior |