Five Epidemiological Studies on Transport and Asthma: Objectives, design and descriptive results

Abstract

A case -control study was conducted in five French metropolitan areas in order to assess the role of traffic -related air pollution in the occurrence of childhood asthma. This paper presents the study design and describes the distribution of key exposure variables. A set of 217 pairs of matched 4 -to 14 -year -old cases and controls were investigated ( matching criteria: city, age, and gender ). Current and past environmental smoke exposures, indoor allergens or air pollution sources, and personal and family atopy were assessed by standard questionnaires. When possible, direct measurements were done to check the validity of this information, on current data: skin prick tests, urine cotinine, house dust mites densities, personal exposures to, and home indoor concentrations of NO x and PM 2.5 . Cumulative exposure to traffic -related pollutants was estimated through two indices: ''traffic density'' refers to a time -weighted average of the traffic density -to -road distance ratio for all home and school addresses of each child's life; ''air pollution'' index combines lifelong time -activity patterns and ambient air concentration estimates of NO x , using an air dispersion model of traffic exhausts. Average current PM 2.5 personal exposure is 23.8 g / m 3 ( SD = 17.4 ), and average indoor concentrations = 22.5 g / m 3 ( 18.2 ); corresponding values for NO 2 are 31.4 ( 13.9 ) and 36.1 ( 21.4 ) g / m 3 . Average lifelong calculated exposures to traffic -related NO x emissions are 62.6 g / m 3 ( 43.1 ). The five cities show important contrasts of exposure to traffic pollutants. These data will allow comparison of lifelong exposures to indicators of traffic exhausts between cases and controls, including during early ages, while controlling for a host of known enhancers or precipitators of airway chronic inflammation and for possible confounders.

Comparison of regression models with land-use and emissions data to predict the spatial distribution of traffic-related air pollution in Rome

“…Recent advances in techniques of geographic information systems (GIS) and related software development have provided promising tools for constructing such models. The approaches to assess traffic-related air pollution exposure of individuals have ranged from simple indicators like self-reports and residential distance to traffic (Ciccone et al, 1988;van Vliet et al, 1997;English et al, 1999;Wilkinson et al, 1999;Venn et al, 2000Venn et al, , 2001Wyler et al, 2000;Hoek et al, 2002;Langholz et al, 2002;Maheswaran and Elliott, 2003) to more complex models incorporating data on demographics, land-use or emissions data into GIS (Briggs, 2005(Briggs, , 2007Jerrett et al, 2005a, b) There are also hybrid approaches that combine monitoring data with some modeling techniques (Liu et al, 1997;Clench-Aas et al, 1999;Kramer et al, 2000;Mukala et al, 2000;Gauvin et al, 2001;Hoek et al, 2001;Zmirou et al, 2002).…”

Traffic related air pollution and incidence of childhood asthma: results of the Vesta case-control study

“…The study design has been presented in detail elsewhere. 26 Briefly, the study population was composed of children aged 4 to 14 years who had lived in any of the five study metropolitan areas since birth. Incident cases were subjects with a ''recent'' doctor diagnosis of asthma (at most two years before inclusion into the study), recruited among attendees of the paediatric departments of the local university hospitals (which also offer primary care in their community) and by a network of private paediatricians or general practitioners who volunteered to participate in the study; 10 to 20 practitioners were chosen, according to the study site, so that their practices were evenly scattered across each metropolitan area.…”

Retrospective assessment of exposure to traffic air pollution using the ExTra index in the VESTA French epidemiological study

“…Only four teams Pikhart et al, 2000;Hoek et al, 2001;Brauer et al, 2002;Gehring et al, 2002;Hoek et al, 2002;Brauer et al, 2003) had recourse to statistical regression models to estimate exposure to traffic air pollutants (TAP). Moreover, pollutant dispersion models have been developed to improve the estimate of exposure levels (Hertel and Berkowicz, 1989;Benson, 1992;Eerhens et al, 1993;Berkowicz et al, 1994), but they have rarely been used in epidemiology (Larssen et al, 1993;Pershagen et al, 1995;Bartonova et al, 1999;Clench-Aas et al, 1999a, b;Briggs et al, 2000;Clench-Aas et al, 2000;Nyberg et al, 2000;Pikhart et al, 2000;Raaschou-Nielsen et al, 2000;Bellander et al, 2001;Raaschou-Nielsen et al, 2001;Zmirou et al, 2002).…”

“…The design of the study is described elsewhere (Zmirou et al, 2002). Matching criteria between cases and controls are city, age (71 year) and gender.…”