vious day (Spearman's rho -0.201, p = 0.034). When analysing for the presence of asthma, asthmatic subjects showed correlations between FEV1 and 24 hour average outdoor air pollution levels which just failed to reach statistical significance (Spearman's rho -0.187, p = 0.06), while non-asthmatic subjects showed no significant correlations. There was no significant correlation between peak PM10 levels and lung function in either asthmatics or non-asthmatics. In the asthmatic subjects, there were a number of associations noted between pollution and temperature variables and the use of any reliever medication which reached statistical significance. These were daytime indoor pollution – one day lag; night-time indoor pollution – same night and one day lag; temperature; minimum and maximum inside temperature, and relative humidity. There was no significant relationship between the use of any reliever medication and any of the lung function variables in the asthmatic group.
When multivariate analysis was undertaken, using six dependent lung function variables (FEV1 and PEF, morning and afternoon and daily variation in both measures), and lagging air pollution measures out to seven days, no pollution variable was retained in a regression model, with only minor temperature effects being retained. When asthmatics were studied separately, small but statistically significant associations between maximum outdoor air pollution levels and variability in FEV1, and night time PEFR were noted. With higher maximum out door pollution, FEV1 variability between morning and afternoon dropped, and afternoon PEFR dropped. Effect size was small, in the case of afternoon PEFR having an R2 of 3.6%. Reliever use was not retained in the regression models for any of the lung function data, except for daily variability in PEF.
When comparing median morning FEV1 between moderate/high pollution days (>20 μg/m3) and low pollution days, students with asthma demonstrated lower readings on high pollution days (p = 0.043). No effect was seen in non-asthmatic students. However, studying moderate/high pollution days only, no significant correlation between lung function and pollution level could be detected, either in asthmatics or normal students.
Diary card and symptom data
Symptom score data was available for a median of 119 time points (Range 109–119). A number of biologically plausible associations were identified between symptoms and both indoor and outdoor air pollution levels. The proportion of students reporting cough and ear, nose and throat symptoms increased with increasing indoor air pollution the previous day. Maximum outdoor air pollution levels the same day were associated with increasing proportion of students reporting cough. The effect of maximum outdoor air pollution remained significant when multivariate analysis was undertaken, and remained in the model, while weather effects were excluded by the model. The effect size however was small, with a change in PM10 of 50 μg/m3 being associated with a 1.5% increase in proportions of children reporting cough (equivalent to one extra report of cough on high pollution days in this cohort). The use of reliever medication was not retained in the model when asthmatics were studied separately, and in this sub-group, the effect of maximum outdoor air pollution remained statistically significant.
This study describes comprehensive pollution and respiratory health monitoring of a panel of students at the boarding house of a metropolitan school. Urinary 1-OHP levels were raised in association with pollution events, but no significant effect of pollution could be seen in the group as a whole either on lung function or airway inflammation and oxidative stress in healthy children. Minor increases in respiratory symptoms such as cough were associated with high pollution exposure. Children with asthma showed some small but statistically significant associations between peak levels of air pollution and lung function and symptoms, but no other significant differences in lung function or biomarkers of airway infla