2006, Schweizer, Christian, Edwards, Rufus David, Bayer-Oglesby, Lucy, Gauderman, William James, Ilacqua, Vito, Juhani Jantunen, Matti, Lai, Hak Kan, Nieuwenhuijsen, Mark, Künzli, Nino

Personal exposure to environmental substances is largely determined by time-microenvironment-activity patterns while moving across locations or microenvironments. Therefore, time-microenvironment-activity data are particularly useful in modeling exposure. We investigated determinants of workday time-microenvironment-activity patterns of the adult urban population in seven European cities. The EXPOLIS study assessed workday time-microenvironment-activity patterns among a total of 1427 subjects (age 19-60 years) in Helsinki (Finland), Athens (Greece), Basel (Switzerland), Grenoble (France), Milan (Italy), Prague (Czech Republic), and Oxford (UK). Subjects completed time-microenvironment-activity diaries during two working days. We present time spent indoors--at home, at work, and elsewhere, and time exposed to tobacco smoke indoors for all cities. The contribution of sociodemographic factors has been assessed using regression models. More than 90% of the variance in indoor time-microenvironment-activity patterns originated from differences between and within subjects rather than between cities. The most common factors that were associated with indoor time-microenvironment-activity patterns, with similar contributions in all cities, were the specific work status, employment status, whether the participants were living alone, and whether the participants had children at home. Gender and season were associated with indoor time-microenvironment-activity patterns as well but the effects were rather heterogeneous across the seven cities. Exposure to second-hand tobacco smoke differed substantially across these cities. The heterogeneity of these factors across cities may reflect city-specific characteristics but selection biases in the sampled local populations may also explain part of the findings. Determinants of time-microenvironment-activity patterns need to be taken into account in exposure assessment, epidemiological analyses, exposure simulations, as well as in the development of preventive strategies that focus on time-microenvironment-activity patterns that ultimately determine exposures.

2005, Edwards, Rufus D., Schweizer, Christian, Jantunen, Matti, Lai, Hak Kan, Bayer-Oglesby, Lucy, Katsouyanni, Klea, Nieuwenhuijsen, Mark, Saarela, Kristiina, Sram, Radim, Künzli, Nino

Evaluation of relationships between median residential indoor, indoor workplace and population exposures may obscure potential strategies for exposure reduction. Evaluation of participants with personal exposures above median levels in the EXPOLIS study in Athens, Helsinki, Oxford and Prague illustrated that these participants frequently showed a different relationship to indoor and workplace levels than that shown by the population median. Thus, prioritization of environments for control measures based on median exposures may exclude important areas where effectively focused control measures are possible, and may therefore have little impact on the highest and most harmful exposures. Further, personal exposures at the upper end of the distribution may exceed the US EPA inhalation reference concentration (Rfc), illustrated here using hexane, naphthalene and benzene. For example upper 90th percentile personal exposures to benzene in Athens and Prague were 64 and 27 μg m−3 with peak exposures of 217 and 38 μg m−3, respectively for non-ETS exposed participants relative to an Rfc of 30 μg m−3. Strategies to reduce exposures to individual compounds, therefore, may benefit from focus on the high end of the distribution to identify activities and behaviors that result in elevated exposures. Control strategies targeting activities that lead to exposures in the upper end of the distribution would reduce the variability associated with population median values by bringing the upper end of the exposure distribution closer to median values. Thus, compliance with health-based standards would be more protective of the higher exposed fraction of the population, in whom health effects would be more expected.

2006, Lai, Hak Kan, Bayer-Oglesby, Lucy, Colvile, Roy N., Götschi, Thomas, Jantunen, Matt J., Künzli, Nino, Kulinskaya, Elena, Schweizer, Christian, Nieuwenhuijsen, Mark J.

EXPOLIS was a large-scale population-based study of urban adult exposures to multiple pollutants, and was conducted between 1996 and 2000 in six European cities. Measurements made using standardised protocols in Athens (Greece), Basel (Switzerland), Helsinki (Finland), Milan (Italy), Oxford (UK), and Prague (Czech Republic), allow similarities and differences between contrasting European regions, climates and populations to be identified. Two consecutive days of home indoor and home outdoor measurements of fine particulate matter (PM2.5), black smoke (BS), and nitrogen dioxide (NO2) were carried out at the homes of adult participants on different dates and seasons during the sampling period. Regression models with interactions searched by all-possible subset method were used to assess the city effects and the determinants of home indoor PM2.5 (adj R2 ¼ 0:60, n ¼ 413), BS (adj R2 ¼ 0:79, n ¼ 382) and NO2 (adj R2 ¼ 0:67, n ¼ 302) levels. Both bi-directional (positive and negative signs of associations) and unidirectional (consistently either positive or negative sign of associations) city effects on different determinants in each indoor model were shown. Smoking, gas-stove usage, outdoor temperature, and wind speed were the common determinants in all three indoor models. Other determinants, including the presence of wooden material, heating, and being located in suburb area, were also identified. They were likely linked to cultural and socio-economic factors.

2006, Edwards, Rufus D., Schweizer, Christian, Llacqua, Vito, Lai, Hak Kan, Jantunen, Matti, Bayer-Oglesby, Lucy, Künzli, Nino

Social and demographic factors have been found to play a significant role in differences between time–activity patterns of population subgroups. Since time–activity patterns largely influence personal exposure to compounds as individuals move across microenvironments, exposure subgroups within the population may be defined by factors that influence daily activity patterns. Socio-demographic and environmental factors that define time–activity subgroups also define quantifiable differences in VOC personal exposures to different sources and individual compounds in the Expolis study. Significant differences in exposures to traffic-related compounds ethylbenzene, m- and p-xylene and o-xylene were observed in relation to gender, number of children and living alone. Categorization of exposures further indicated time exposed to traffic at work and time in a car as important determinants. Increased exposures to decane, nonane and undecane were observed for males, housewives and self-employed. Categorization of exposures indicated exposure subgroups related to workshop use and living downtown. Higher exposures to 3-carene and a-pinene commonly found in household cleaning products and fragrances were associated with more children, while exposures to traffic compounds ethylbenzene, m- and p-xylene and o-xylene were reduced with more children. Considerable unexplained variation remained in categorization of exposures associated with home product use and fragrances, due to individual behavior and product choice. More targeted data collection methods in VOC exposure studies for these sources should be used. Living alone was associated with decreased exposures to 2-methyl-1-propanol and 1-butanol, and traffic-related compounds. Identification of these subgroups may help to reduce the large amount of unexplained variation in VOC exposure studies. Further they may help in assessing impacts of urban planning that result in changes in behavior of individuals, resulting in shifts in the patterns of exposure experienced by the population.