|Abstract||Background: Diverse environmental exposures, studied separately, have been linked to health outcomes in adult asthma, but integrated multi-factorial effects have not been modeled. We sought to evaluate the contribution of combined social and physical environmental exposures to adult asthma lung function and disease severity. Methods: Data on 176 subjects with asthma and/or rhinitis were collected via telephone interviews for sociodemographic factors and asthma severity (scored on a 0-28 point range). Dust, indoor air quality, antigen-specific IgE antibodies, and lung function (percent predicted FEV1) were assessed through home visits. Neighborhood socioeconomic status, proximity to traffic, land use, and ambient air quality data were linked to the individual-level data via residential geocoding. Multiple linear regression separately tested the explanatory power of five groups of environmental factors for the outcomes, percent predicted FEV1 and asthma severity. Final models retained all variables statistically associated (p < 0.20) with each of the two outcomes. Results: Mean FEV1 was 85.0 ± 18.6%; mean asthma severity score was 6.9 ± 5.6. Of 29 variables screened, 13 were retained in the final model of FEV1 (R2 = 0.30; p < 0.001) and 15 for severity (R2 = 0.16; p < 0.001), including factors from each of the five groups. Adding FEV1 as an independent variable to the severity model further increased its explanatory power (R2 = 0.25). Conclusions: Multivariate models covering a range of individual and environmental factors explained nearly a third of FEV1 variability and, taking into account lung function, one quarter of variability in asthma severity. These data support an integrated approach to modeling adult asthma outcomes, including both the physical and the social environment.|
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|Name||Affiliation||Home page||Total pubs|
|Balmes JR||Division of Environmental Health Sciences, School of Public Health, University of California Berkeley, Berkeley, CA USA||1|
|Blanc PD||Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California, San Francisco, UCSF Box 0924, San Francisco, CA 94113-0924, USA||2|
|Chen H||College of Environmental Science and Engineering, Donghua University, Shanghai 200051, Chinaemail@example.com||3|
|Eisner MD||Department of Medicine, University of California, San Francisco, UCSF Box 0924, San Francisco, CA 94113-0924, USA||2|
|Hammond SK||Division of Environmental Health Sciences, School of Public Health, University of California Berkeley, Berkeley, CA USA||1|
|Katz PP||nstitute for Health Policy Studies, University of California, San Francisco, UCSF Box 0920, San Francisco, CA 94113-0920, USA||2|
|Lurmann F||Sonoma Technology Incorporated, Petaluma, CA USA||1|
|Quinlan PJ||Department of Medicine, University of California San Francisco, San Francisco, CA USA||1|
|Thorne PS||Department of Occupational and Environmental Health, College of Public Health, University of Iowa, Iowa City, IA USA||1|
|Trupin L||Department of Medicine, University of California, San Francisco, UCSF Box 0924, San Francisco, CA 94113-0924, USAfirstname.lastname@example.org||2|
|Yelin EH||Institute for Health Policy Studies, University of California, San Francisco, UCSF Box 0920, San Francisco, CA 94113-0920, USA||2|
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