Strak et al. characterization of PM air pollution was performed on-site. Preexposure and post- exposure measurements were made to assess respiratory health. We used a semiexperimental rather than a pure observational design to reduce exposure measurement error. Our design with multiple sampling days at multiple locations used tem- poral and spatial variability to increase contrast in the measured PM characteristics and reduce correlations. Briefly, we selected five loca- tions in the Netherlands with different source characteristics to increase exposure contrasts and reduce correlations between PM charac- teristics (Strak et al. 2011). The locations were an underground train station, a continuous traffic location, a stop-and-go traffic location, a farm, and an urban background site. None of the locations were > 70 km away from the col- lection point located at the Utrecht University campus where all preexposure and some post- exposure health measurements were made. We aimed to recruit 32 volunteers, each undertaking 7 study visits. Each participant had to visit all five locations once, with the two remaining visits assigned randomly to a location. We planned 30 sampling days dur- ing March through October 2009, one site per day, with 8 participants exposed during each visit. Results of a previous screening phase showed much higher concentrations at the underground site compared with the out- door sites, which also strongly influenced cor- relations between specific air pollutants (Strak et al. 2011). In order to separate the health associations at the underground site and the four outdoor sites, we scheduled 9 visits at the underground and 21 at the remaining four sites. Due to practical constraints, we finally included 31 volunteers, who were measured for an average of 5.5 sampling days (range, 3–7 days). Twenty-six participants visited the underground site at least once, and 13 visited all five sites at least once. In summary, we obtained 45 observations at the underground site and 28–37 at the other sites. To avoid potential carryover effects from previous exposures, an individual’s visits to the sites were separated by ≥ 14 days. Exposure of each participant was started between 0900 and 0930 hours and lasted for 5 hr. The partici- pants cycled for 20 min on a stationary bicycle each hour. We selected a 5-hr exposure period with intermittent exercise in order to increase the contrast between preexposure and post- exposure to ambient air pollution. Moreover, we hypothesized that longer exposure would result in a clearer health response required to study the independent associations with differ- ent pollutants. To keep the dose similar among the participants, before the study began we determined for each participant the heart rate corresponding to a minute ventilation rate of 20 L/min/body surface area (square meters) 1184 (Zuurbier et al. 2009); we then instructed participants to monitor their heart rates as they cycled in order to maintain the desired ventila- tion rate. Exercise may affect the measured respiratory variables, but with each participant cycling at a consistent minute ventilation rate each sampling day, bias in associations between the fluctuating air pollution and health end points is likely small. We measured lung func- tion [i.e., forced vital capacity (FVC), forced expiratory volume in 1 sec (FEV1), forced expi- ratory flow between 25% and 75% of FVC (FEF25–75), peak expiratory flow (PEF)], mea- sured the fraction of nitric oxide in exhaled air (FENO) as an indicator of airway inflamma- tion, and recorded respiratory symptoms of the participants—all respiratory health indica- tors that are widely used. These health param- eters were measured before exposure (t = 0; collection point), before exposure (t = 2; sam- pling location), immediately after exposure (t = 7; sampling location), 2 hr after exposure (t = 9; collection point), and the next morn- ing (t = 25; collection point). The measure- ments at t = 2 were performed to investigate the effect of transport between the collection point and the sampling location. To avoid day- of-week effects, we obtained all measurements on Monday through Thursday of each week. Study population. We recruited 31 healthy, young, nonsmoking participants from among Utrecht University students living on campus to minimize exposure to traffic-related air pol- lution when traveling to the collection point. The participants completed an online screening questionnaire. Exclusion criteria included smoking or living in a household with a smoker; lifetime diagnosis of asthma or chronic obstructive pulmonary disease; or history of cardiovascular disease, diabetes mel- litus, or pregnancy. Before the study, each participant was examined by a physician and obtained medical clearance for participation. The study was approved by the ethics com- mittee at University Medical Center Utrecht. Written informed consent was provided by all participants. Exposure measurements. The methods for measuring air pollution on-site during each day of participants’ exposure have been described elsewhere [Strak et al. 2011; see also Supplemental Material, p. 2 (http://dx.doi. org/10.1289/ehp.1104389)]. Briefly, we mea- sured PM10 and PM2.5, and we determined the absorbance of PM2.5 samples and endo- toxin content of PM10 samples. We made real-time measurements of particle number concentration (PNC) and the gaseous pol- lutants ozone (O3), nitrogen dioxide (NO2), and (nitrogen oxides (NOx). We measured the concentrations of elemental carbon (EC), organic carbon (OC), trace metals, nitrate, and sulfate in PM2.5–10 and PM2.5 samples. OP was measured in three fractions—PM2.5–10, PM0.18–2.5, and PM0.18—and assessed in vitro by measuring antioxidant depletion of ascor- bate (OPAA) and reduced glutathione (OPGSH) (Godri et al. 2010). We equipped a minibus with a custom- made cabin air filter to minimize exposure during transport of participants between the collection point and the sampling locations. To estimate traffic-related air pollution during transport, we measured the PNC in the mini- bus during each commute. Clinical measurements. FENO was mea- sured with a Niox Mino monitor (Aerocrine, Solna, Sweden), an instrument that complies with recommendations from the American Thoracic Society/European Respiratory Society (ATS/ERS 2005). The instrument was also used to measure ambient-air nitric oxide levels where FENO measurements were performed. Lung function parameters (FVC, FEV1, FEF25–75, PEF) were measured with an EasyOne electronic spirometer (ndd, Zürich, Switzerland), which meets ATS/ERS spirom- etry standards (Miller et al. 2005). Each par- ticipant performed at least three maneuvers supervised by one of the eight technicians operating the device. The best value from the technically correct maneuvers was selected according to the maximum value method of the European Respiratory Society (Quanjer et al. 1993). After each sampling day, two syringe checks using a calibrated 3-L syringe were recorded to monitor the accuracy of the device, which had to be within 3%. At each time point, a short questionnaire was administered to subjectively grade respira- tory symptoms that were present (e.g., cough, congestion/rhinorrhea, wheeze): symptoms were scaled from 0 (no complaints) to 3 (severe complaints). Before the morning health measurements, the participants completed a questionnaire reporting additional exposure to traffic- or workplace-related air pollution, medication use, and so forth during the preceding 24 hr. Data analyses. We analyzed the associa- tions between air pollution concentrations during exposure at the sampling locations and the difference in lung function and FENO between postexposure (t = 7, t = 9, t = 25) and preexposure (t = 0) for each sampling day using mixed linear regression. We used mixed models to account for the influence of repeated observations per participant (using compound symmetry of the residuals). We did not include sampling location in the analy- sis because it was not significantly associated with the outcome after including exposure and potential confounders. We used the 5-hr average concentrations of air pollutants mea- sured at the locations as independent variables. For OP and trace metals, the data from the individual PM size fractions were aggregated. We first specified single-pollutant models. ovlume 120 | number 8 | August 2012 • Environmental Health Perspectives