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

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.

Predictors of Daily Mobility of Adults in Peri-Urban South India

“…Specifically, men’s mobility variability over time was greater for activity locations indicators, time spent at home, and linear distance from home. The variability over time found in the present study was much larger than in high-income countries population [ 35 , 44 ]. An important characteristic of the workforce in India is the multiple activities performed [ 45 ], which may explain the variability over the course of the day and from one day to another in men.…”

“…Typically for adults in high-income countries, time spent at home changed and activity locations differed from weekends to week days [ 35 , 44 ]. In our population, this was only the case for men (more mobility in and around home and smaller and more circular activity space on weekends).…”

“…Similarly, in a study in California, day type had stronger effect on men’s time-activity patterns than on women’s [ 35 ]. Isaacs et al found that day type, along with the season, were more important predictors than sex for time-activity patterns [ 44 ]. In our population, the post-monsoon related to less time spent at home for women and bigger activity space for men, compared to other seasons.…”

A pilot investigation using global positioning systems into the outdoor activity of people with severe traumatic brain injury

“…Consequently, no examinations of other important intrinsic or extrinsic factors such as cognitive status and environmental barriers to physical activity which may have influenced physical activity levels were performed. Additionally, we did not control for or record the days that the participant did not wear the device, and therefore our results may be biased if one group wore the device more on weekends [ 19 ]. We also used informed, but subjective, assessment to determine incidences of outdoor physical activity based on location, velocity of movement and the number of satellites fixes.…”

Determination of Similar Exposure Groups Using Weekday Time Activity Patterns of Urban Populations

“…Each subject completed a diary for 2 consecutive days, either on weekdays or weekends. The 2-day weekday and weekend activity diaries were completed by 19 …”