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An integrated model of environmental factors in adult asthma lung function and disease severity: a cross-sectional study.
- Author(s): Trupin, Laura;
- Balmes, John R;
- Chen, Hubert;
- Eisner, Mark D;
- Hammond, S Katharine;
- Katz, Patricia P;
- Lurmann, Fred;
- Quinlan, Patricia J;
- Thorne, Peter S;
- Yelin, Edward H;
- Blanc, Paul D
- et al.
Published Web Locationhttps://doi.org/10.1186/1476-069x-9-24
BackgroundDiverse 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.
MethodsData 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.
ResultsMean 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).
ConclusionsMultivariate 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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