B. Rey deCastro1, Alison S. Geyh2, Andres Houseman3, Louise Ryan4, John D. Spengler5 ...

B. Rey deCastro1, Alison S. Geyh2, Andres Houseman3, Louise Ryan4, John D. Spengler5

1Westat, Rockville, MD.

2Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.

3Department of Work Environment, University of Massachusetts Lowell, Lowell, MA.

4CSIRO Mathematical and Information Sciences, New South Wales, Australia.

5Department of Environmental Health, Harvard School of Public Health, Boston, MA.

Collection of time-location data is a common feature of personal exposure studies and is intended to provide a basis for time-weighted exposure averaging. Particular difficulties posed by the outcome -- multiple non-ordered microenvironments -- have precluded routine statistical analysis, but such multinomial outcomes may be modeled within a regression framework using the generalized logit model (or discrete choice model). Conveniently, this model predicts the proportion of subjects in each microenvironment at each time interval, which may be construed most usefully as exposure weights in a formulation of total exposure. This presentation demonstrates application of the generalized logit model to data from a study of schoolchildren (N = 95, 7-11 years old) in southern California who reported their time-location at 30-minute intervals in diaries for 4 days per month for 12 months (June 1995–May 1996; N = 171,000). A generalized logit model of the proportion of subjects in each of five microenvironment -- indoor-home, indoor-school, indoor-other, commuting, outdoors -- shows that while subjects spent substantial time indoor-home, there was substantial variation for other microenvironments at all temporal scales. Consistent with a daily academic schedule, indoor-school time predominates at the 30-minute timescale. Yet, at the day and month timescales most variation is in indoor-other. This suggests that important longer-term exposures may be missed because non-home and non-school indoor microenvironments are not often monitored. The model also found that autocorrelation of microenvironment location was most positively correlated with the previous 30-minute interval and tapered through the preceding 3 hours.

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