Factors influencing time-location patterns and their impact on estimates of exposure: the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

• Published in: Journal of exposure science & environmental epidemiology 2016-06, Vol.26 (4), p.341-348
• Main Authors: Spalt, Elizabeth W, Curl, Cynthia L, Allen, Ryan W, Cohen, Martin, Williams, Kayleen, Hirsch, Jana A, Adar, Sara D, Kaufman, Joel D
• Format: Article
• Language: English
• Subjects: 692/699/75/593/2100; 692/700/478/174; 704/106/694/2739; Adult; African Americans; Aged; Aged, 80 and over; Air Pollutants; Air Pollution; Analysis; Arteriosclerosis; Asian Americans; Atherosclerosis; Built environment; Care and treatment; Cohort Studies; Demographic aspects; Demographics; Environmental aspects; Environmental Exposure - analysis; Environmental Exposure - statistics & numerical data; Environmental health; Epidemiology; Estimates; Ethnic Groups - statistics & numerical data; European Continental Ancestry Group - statistics & numerical data; Exposure; Female; Geography; Health aspects; Hispanic Americans; Humans; Indoor environments; Linear Models; Male; Medical research; Medicine; Medicine & Public Health; Medicine, Experimental; Middle Aged; original-article; Population-based studies; Residence Characteristics; Residential location; Risk factors; Surveys and Questionnaires; Time; United States; Urban environments
• ISSN: 1559-0631; 1559-064X
• DOI: 10.1038/jes.2015.26

We assessed time-location patterns and the role of individual- and residential-level characteristics on these patterns within the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) cohort and also investigated the impact of individual-level time-location patterns on individual-level estimates of exposure to outdoor air pollution. Reported time-location patterns varied significantly by demographic factors such as age, gender, race/ethnicity, income, education, and employment status. On average, Chinese participants reported spending significantly more time indoors and less time outdoors and in transit than White, Black, or Hispanic participants. Using a tiered linear regression approach, we predicted time indoors at home and total time indoors. Our model, developed using forward-selection procedures, explained 43% of the variability in time spent indoors at home, and incorporated demographic, health, lifestyle, and built environment factors. Time-weighted air pollution predictions calculated using recommended time indoors from USEPA overestimated exposures as compared with predictions made with MESA Air participant-specific information. These data fill an important gap in the literature by describing the impact of individual and residential characteristics on time-location patterns and by demonstrating the impact of population-specific data on exposure estimates.