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Statistical properties of longitudinal time-activity data for use in human exposure modeling

Journal of Exposure Science & Environmental Epidemiology volume 23, pages 328–336 (2013)Cite this article

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Abstract

Understanding the longitudinal properties of the time spent in different locations and activities is important in characterizing human exposure to pollutants. The results of a four-season longitudinal time-activity diary study in eight working adults are presented, with the goal of improving the parameterization of human activity algorithms in EPA’s exposure modeling efforts. Despite the longitudinal, multi-season nature of the study, participant non-compliance with the protocol over time did not play a major role in data collection. The diversity (D)—a ranked intraclass correlation coefficient (ICC)— and lag-one autocorrelation (A) statistics of study participants are presented for time spent in outdoor, motor vehicle, residential, and other-indoor locations. Day-type (workday versus non-workday, and weekday versus weekend), season, temperature, and gender differences in the time spent in selected locations and activities are described, and D & A statistics are presented. The overall D and ICC values ranged from approximately 0.08–0.26, while the mean population rank A values ranged from approximately 0.19–0.36. These statistics indicate that intra-individual variability exceeds explained inter-individual variability, and low day-to-day correlations among locations. Most exposure models do not address these behavioral characteristics, and thus underestimate population exposure distributions and subsequent health risks associated with environmental exposures.

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Authors and Affiliations

  1. US Environmental Protection Agency, Research Triangle Park, NC, USA

    Kristin Isaacs, Thomas McCurdy, April Errickson, Stephen Graham, Nicolle Tulve & Daniel Vallero

  2. Alion Science and Technology, Research Triangle Park, NC, USA

    Graham Glen, Melissa Nysewander & Luther Smith

  3. University of North Carolina, Chapel Hill, NC, USA

    April Errickson & Susan Forbes

  4. Unaffiliated, Orange County, NC, USA

    Lisa McCurdy

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  1. Kristin Isaacs
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Correspondence to Kristin Isaacs.

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The U.S.Environmental Protection Agency (EPA) through its Office of Research and Development conducted the research described in this paper. It has been subjected to Agency review and approved for publication.

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The authors declare no conflict of interest.

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Isaacs, K., McCurdy, T., Glen, G. et al. Statistical properties of longitudinal time-activity data for use in human exposure modeling. J Expo Sci Environ Epidemiol 23, 328–336 (2013). https://doi.org/10.1038/jes.2012.94

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