Design Of Exposure Measurements For Epidemiologic Studies
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This presentation will describe the following items: (1) London daily air pollution and deaths that demonstrate how time series epidemiology can indicate that air pollution caused death; (2) Sophisticated statistical models required to establish this relationship for lower pollution levels; three basic types of air pollution epidemiology and the air quality measurements required for them; requirements for time-series epidemiology; (3) the Exposure paradox-personal exposure does not correlate with ambient concentrations, yet daily deaths correlate with daily pollution (two possible explainations are (a) differences between cross-sectional and longitudinal measurements of the personal exposure/ambient concentration relationships and (b) reinterpreting personal exposure to particulate matter from (i) exposure to the sum of all particles experienced in a series of different environments, to (ii) exposure to various classes of particles experienced in all different environments); (4) exposure to particles of ambient origin (experienced indoors and outdoors) is a key measurement for EPA; (5) the Particle Total Exposure Assessment Methodology (PTEAM) data show a lack of correlation between exposure to particles of ambient origin and exposure to indoor-generated plus personal-activity particles; (6) how to determine indoor concentrations of particles of ambient origin; and (7) the importance of basing new exposure studies on either model development or probability procedures that account for the variations in exposure resulting from differences in people's activities and differences in ambient concentrations.