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DEVELOPING MEANINGFUL COHORTS FOR HUMAN EXPOSURE MODELS
Citation:
Graham, S E. AND T R. McCurdy. DEVELOPING MEANINGFUL COHORTS FOR HUMAN EXPOSURE MODELS. JOURNAL OF EXPOSURE ANALYSIS AND ENVIRONMENTAL EPIDEMIOLOGY 14(1):23-43, (2004).
Impact/Purpose:
The two main objectives of this research are (1) to improve and update and (2) to analyze the CHAD database.
For objective 1, we will
* Reconfigure the CHAD program into a completely modularized Oracle database.
* Redesign User Interface for effcient utilization of the program's capability.
* Obtain dates for those surveys that did not provide them to us, so that we can obtain associated meteorological/climatic inputs for the person-days of information without them.
* Revise the upper and lower bound delimiters in the energy expenditure distributions used for activity-specific estimates.
For objective 2, we will
* Evaluate data quality.
* Evaluate trends and activities for various subgroups.
* Identify temporal patterns for longitudinal data.
* Characterize resolution required for output for exposure and dose models.
Description:
This paper summarizes numerous statistical analyses focused on the U.S. Environmental Protection Agency's Consolidated Human Activity Database (CHAD), used by many exposure modelers as the basis for data on what people do and where they spend their time. In doing so, modelers tend to divide the total population being analyzed into "cohorts", to reduce extraneous inter-individual variability by focusing on people with common characteristics. Age and gender are typically used as the primary cohort defining-attributes, but more complex exposure models also use weather, day-of-the-week, and employment attributes for this purpose. We analyzed all of these attributes and others to determine if statistically significant differences exist among them to warrant their being used to define distinct cohort groups. We focused our attention mostly on the relationship between cohort attributes and the time spent outdoors, indoors, and in motor vehicles. Our results indicate that besides age and gender, other important attributes for defining cohorts are the physical activity level of individuals, weather factors such as daily maximum temperature in combination with months of the year, and combined weekday/weekend with employment status. Less important are precipitation and ethnic data. While statistically significant, the collective set of attributes does not explain a large amount of variance in outdoor, indoor, or in-vehicle locational decisions. Based on other research, parameters such as lifestyle and life stages that are absent from CHAD might have reduced the amount of unexplained variance. At this time, we recommend that exposure modelers use age and gender as "first order" attributes to define cohorts followed with physical activity level, daily maximum temperature or other suitable weather parameter, and day-type possibly beyond a simple weekday/weekend classification.
This work has been funded wholly by the United States Environmental Protection Agency. It has been subjected to Agency review and approved for publication. Mention of trade names of commercial products does not constitute an endorsement or recommendation for use.