Spira-Cohen et al. the school-site PM or gaseous measurements (Table 2). Sensitivity analyses. To test whether overall results were driven by individual subjects with unusual characteristics, we excluded potentially outlying subjects and reevaluated the mixed model results. The PEF decrement effect esti- mate increased slightly from –9.1 L/min to –11.7 L/min, and the marginal significance of the pollution reached the p < 0.05 sig- nificance level, when we excluded one out- lier subject with extreme personal exposures. The FEV1 decline associated with personal PM2.5 decreased from –0.06 to –0.05, and the confidence band widened, when this subject was excluded. Overall, models were robust to exclusion of other potentially outlying subjects, including asymptomatic subjects, subjects with unusually low lung function measurements, and subjects with higher than average personal exposures. We also tested whether results may have been driven by individual schools by exclud- ing each school from the overall model. When we excluded School MS302, a school farther from a highway (1,216 feet), from the PEF model with personal EC, the marginal sig- nificance of the EC pollution increased to p = 0.43, although the effect estimate remained consistently negative, diminishing by one- third. We found a maximum change in coef- ficient size of less than one-third when we excluded any of the other schools from the PEF model, and p-values remained < 0.10. p-Values also increased when schools were excluded from FEV1 models with personal PM2.5, but the magnitude of the effect esti- mate was robust to exclusion of schools. Using percent predicted standardized lung function metrics also produced similar effect estimates. Models of a transformed lung func- tion outcome, computed by taking the dif- ference from each child’s mean value, showed stronger associations for personal EC with PEF (p < 0.02) but weaker, less significant pollutants. Exposure (pollution increment)a Personal EC (3.0 μg/m3), n = 434 Personal PM2.5 (55 μg/m3), n = 431 School-site EC (3.0 μg/m3), n = 454 School-site PM2.5 (22 μg/m3), n = 454 Rooftop PS154 PM2.5 (24 μg/m3), n = 454 NO2 (60 ppb), n = 454 O3 (40 ppb), n = 454 previously associated with asthma exacerbations (Delfino et al. 2006)], and SO2 (a known acute bronchoconstrictor [see U.S. Environmental Protection Agency (EPA) 2008]) to consider potential confounding of the PM–health associations by gaseous copollutants. The maximum outdoor daytime (6-hr average) O3 concentration during school hours (0900 hours to 1500 hours) was 73 ppb dur- ing the study (mean, 23 ppb). We found a significant association of increased 6-hr aver- age O3 with increased risk of wheeze severity with a 1-day lag. This association with 1-day lag O3 was robust to exclusion of the highest O3 day (O3 maximum decreased to 50 ppb after exclusion), as well as exclusion of the school experiencing days with the highest O3 levels (O3 maximum decreased to 40 ppb after exclusion). However, in a copollutant model of same-day EC and 1-day lag O3 with wheeze, EC remained a significant exposure factor. Six-hour average NO2 (0900 hours to 1500 hours) was not significantly associated with any of the health outcomes investigated, although risk of symptoms was greater than 1.0 with same-day concentrations. In a copol- lutant model of NO2 and EC, EC remained the significant exposure factor. Peak morning SO2 concentrations were also significantly associated with symptom outcomes. Peak morning SO2 was associated with increased risk of both cough (RR per 30 ppb SO2 = 1.42; 95% CI, 1.15–1.76) and wheeze (RR = 1.56; 95% CI, 1.11–2.19). SO2 and EC con- tributed equally in a copollutant model. School-site EC was not highly correlated with NO2 (r = 0.36) or O3 (r = 0.25) at the time intervals investigated in the health effects analysis. On an hourly basis, NO2 showed much higher correlations with school-site EC (r = 0.60), and SO2 was also moderately cor- related (r = 0.45) during these study sampling periods (i.e., during spring and fall). Thus, although O3 and SO2 were also associated with some asthma morbidity metrics, they did not displace EC in effects analyses. School-site sulfur analysis. We found sig- nificant elevated risks of symptoms with EC concentrations but not with total PM2.5 or the sulfur fraction in models separately evaluat- ing the school-site measurements of PM2.5, EC, and sulfur from the same filter. We found increased risk of cough and wheeze severity with school-site filter EC concentrations mea- sured from 1400 hours the previous day to 0700 hours the next morning (weekdays), but not with same-day school-hour filter EC (0700 hours to 1400 hours weekdays). We found nearly significant positive associations for increased risk of cough severity with school- site filter PM2.5 (1400 hours to 0700 hours). The sulfur fraction of the PM on the school- site filters was not associated with an increase in any of the symptom outcomes for either associations for personal PM2.5 with both FEV1 and PEF. We included school as a covariate in final symptom models because it was significant in all symptom models except wheeze. It was not a significant covariate in the lung func- tion models and did not change the lung function–pollutant effect estimates, and was therefore not included in those final models. An indicator variable for schools closer to a highway was significant only in models of shortness of breath (p < 0.05) and margin- ally significant in models of total symptoms (p = 0.09), with higher symptoms at schools closer to the highways. Symptom results remained robust even when subjects and schools were excluded from the models, although models of shortness of breath were least robust. Results were robust to exclusion of the school sampled in the fall season. The addition of indicator variables representing day of week, respiratory infec- tions (evening presence/absence), and school absences did not confound any of the signifi- cant associations. To determine whether model results were driven by subjects with more severe asthma, as indicated in our data by reporting an ED visit within the preceding 12 months, we investigated this group separately from the group reporting no ED visit. We found no significant difference in risk between the two subgroups, although relative risks were slightly higher in the group having visited an ED. For lung function, the EC–PEF association was larger in the subjects who had not visited an ED; however, the two groups’ estimates were also not statistically different from each other. School-site gaseous pollutant analysis. We also investigated the roles of O3 [a second- ary gaseous pollutant known to acutely affect asthma (Gent et al. 2003; Thurston and Bates 2003; Thurston et al. 1997; Trasande and Thurston 2005)], nitrogen dioxide [NO2; a general indicator of fresh traffic exhaust also Health outcomeb PEFc FEV1d PEF FEV1 PEF FEV1 PEF FEV1 PEF FEV1 PEF FEV1 PEF FEV1 Effect (95% CI) –9.13 (–19.13 to 0.86)* –0.02 (–0.09 to 0.04) –9.40 (–20.43 to 2.08) –0.06 (–0.14 to 0.01)* –4.58 (–14.01 to 4.85) 0.01 (–0.04 to 0.07) –3.06 (–15.11 to 8.98) –0.02 (–0.09 to 0.06) –0.11 (–12.48 to 12.32) –0.02 (–0.10 to 0.06) 5.97 (–6.53 to 18.46) 0.01 (–0.07 to 0.09) 0.47 (–12.48 to 13.42) 0.00 (–0.08 to 0.08) Table 2. Mixed-model estimates of lung function decrements associated with personal and school-site aFrom 5th to 95th percentile of pollutant concentration weekdays only, 0900 hours to 2100 hours. bSame-day afternoon lung function measurements. cPEF measured in L/min. dFEV1 measured in L. *p < 0.10 by t-test. 562 ovlume 119 | number 4 | April 2011 • Environmental Health Perspectives