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Population sampling in European air pollution exposure study, EXPOLIS: comparisons between the cities and
1Department of Environmental Hygiene, National Public Health Institute, Kuopio, Finland. tuulia.rotko@helsinki.fi
Abstract:
A personal air pollution exposure study, EXPOLIS, was accomplished in six European cities among 25- to 55-year-old citizens. In order to compare the exposure results and different microenvironmental concentrations between the cities it is crucial to know the extent and effects of the population bias that has developed in sampling procedure and the sociodemographic characteristics of each measured population sample. In each participating city a random Base sample of 2000 to 3000 individuals was drawn from the census and a Short Questionnaire (SQ) was mailed to them. Two subsamples of the Respondents of the mailed questionnaire were randomly drawn: Diary sample for 48-h time--microenvironment--activity diary and extensive exposure questionnaires, and Exposure sample for the same plus personal exposure and microenvironmental monitoring. Significant differences existed between the EXPOLIS cities in the population-sampling procedure. Population-sampling bias was evaluated by comparing the Respondents with the total city populations. The share of women and individuals with more than 14 years of education is higher among the Respondents than the overall population except in Athens. Men, younger (25-34 years old) and unmarried individuals were hardest to get to participate in the study at least in Helsinki. The two subsamples differ from Respondents in having more employed and higher- educated individuals. The largest sample bias occurred at the first and easiest step of responding to the mailed Short Screening Questionnaire, and not at the last and most demanding stage of participating in the exposure measurements. Exposure data from some of EXPOLIS cities can only be compared to other cities with caution considering their large population bias or different sample selections. However the selection bias is not necessarily a problem for analyses about predictors of personal exposures or analyses within a city.
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