4.6 Article

Modeling residential indoor concentrations of PM2.5, NO2, NOx, and secondhand smoke in the Subpopulations and Intermediate Outcome Measures in COPD (SPIROMICS) Air study

期刊

INDOOR AIR
卷 31, 期 3, 页码 702-716

出版社

WILEY
DOI: 10.1111/ina.12760

关键词

air pollutants; exposure assessment; indoor exposure questionnaires; indoor monitoring; prediction modeling; residential behavior

资金

  1. National Institute of Environmental Health Sciences [K23ES025781, P30ES007033, R01ES023500]
  2. National Heart, Lung, and Blood Institute [HHSN268200900013C, HHSN268200900014C, HHSN268200900015C, HHSN268200900016C, HHSN268200900017C, HHSN268200900018C, HHSN268200900019C, HHSN268200900020C, U01 HL137880, U24 HL141762]

向作者/读者索取更多资源

Increased outdoor concentrations of fine particulate matter and oxides of nitrogen are associated with respiratory and cardiovascular morbidity. Indoor and outdoor air pollution may accelerate lung function loss in individuals with COPD. Models based on questionnaire responses and estimated outdoor concentrations successfully explained most variation in indoor PM2.5, NO2, NOx, and nicotine concentrations.
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 R-2 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.

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