Environmental project, 1005 – Time Series Study of Air Pollution Health Effects in COPSAC Children

Time Series Study of Air Pollution Health Effects in COPSAC Children

5 Discussion and Conclusion

We find consistent associations between daily ambient levels of air pollutants and daily incidence of respiratory symptoms in terms of wheezing during the first 18 month of life of children with atopic predisposition and living in Copenhagen. Among children from central Copenhagen the associations were statistically significant and positive with respect to street levels of CO and NO_x, and negative with respect to street levels of O₃, whereas positive associations with urban background levels of PM₁₀, CO and NO₂ were borderline significant. Among children living in Copenhagen suburbs or the rest of Zealand similar but much weaker associations with the gases were seen, only significant for street levels of NO₂ and O₃ at one station and only for children from outside Copenhagen, whereas there were no associations with PM₁₀ levels. These apparently differential associations related to distance from the sources of pollutants and monitoring sites supports causal relationships. Moreover, positive associations with the street levels of CO and NO_x and negative with street levels of ozone, which is consumed by NO from diesel emission, suggest traffic as the important source of pollutants relevant for airway symptoms. Associations with total number concentrations of ultrafine particles, which are mainly traffic generated, would also be expected, although these were not significant, but that may be due to the low number of days with measurements. We find furthermore that air pollution has small or no effect on development of the outcome on the concurrent day, but that the effect on airway symptoms comes with a delay of 2-4 days for different pollutants and that the effect is accumulated over several days.

An increase in 1 ppm in 6-day average CO measured at street level (Jagtvej and HCAB) is associated with 1.89 fold and 3.11-fold (with wide confidence intervals) increases in new cases of respiratory symptoms in small children living in Copenhagen inner city the following days, respectively (Table 4.1.1). Note that CO levels are measured in ppm and that 1 ppm corresponds to a little more than a doubling of average levels at Jagtvej and HCAB of 0.99 and 0.81 ppm, respectively. Associations with CO levels measured in city background are borderline significant (p=0.10) and it points at an almost 5-fold increase in respiratory disease incidences in small children the day after 6-day average CO pollution increase by 1 ppm. We find finally that concurrent day pollution has weak effect on the development of the symptoms on the same day, but that effect increases and lasts over several days, peaking at around 2 (street levels) or 3 (background levels) days delay. CO is not an irritant gas and it is unlikely to be causative in development of respiratory symptoms. However, CO is mainly emitted by gasoline powered vehicles and can be considered as an indicator of traffic. The levels of CO correlate very closely with NO_x and TON at the street stations (r>0.82), the correlations with NO_x are particularly strong (r>0.91). The relevance of the associations among children form central Copenhagen is supported by much weaker and non significant associations between CO in central Copenhagen and outcome among small children living farther away in Copenhagen suburbs (Table 4.2.1) and the rest of Zealand (Table 4.3.1).

A unit increase (1 ppb) in 6-day average city background NO_x pollution levels is associated with a 1.9 % (borderline significant) increase in new respiratory cases the following days, while a unit increase in 6-day average street level NO_x pollution at Jagtvej and HCAB results in 0.6% and 1.3% (significant) increases in new respiratory cases the next day respectively. Note that a 1 ppb increase corresponds to 7%, 1.6% and 1% increases from daily average levels of 15, 61 and 87 ppb at the city background, Jagtvej and HCAB monitoring stations, respectively. Thus, a doubling of the average levels at the city background, Jagtvej and HCAB monitoring stations would correspond to 29%, 37% and 113% increases in the outcome, respectively. This apparent effect occurs with a few days' delay, that seems to be strongest with a 3-day delay at city background levels, and 2-day delay at street levels. The associations of respiratory symptoms among children from central Copenhagen with monitoring station levels of NO₂ show a pattern similar to that of NO_x although with considerably higher but non-significant effect estimates, and similar 2-day lag. Similar positive but much weaker and non significant associations were found for symptoms and NO₂ and NO_x in the children living outside central Copenhagen a 2-day lag for city background measurements and less clear lag patterns for street level measurements, supporting the relevance of the associations in central Copenhagen. Levels of NO_x and NO₂ have previously been associated with the daily count of house calls related to upper and lower airway symptoms among Copenhagen children (Keiding et al. 1995). NO_x is the sum of NO and NO₂. NO is emitted in particular from diesel vehicles and reacts readily with available ozone to form NO₂. Thus, the levels of NO₂ are only a third of the NO_x at the street monitoring stations, whereas there is only a small difference between NO₂ (11.9 ppb) and NO_x (15.5 ppb) in city background and the correlation between them is stronger (r: 0.92) than at the street stations (r: 0.80 and 0.83). However, NO₂ is the gas with airway irritant properties whereas NO is generated in the human body and has e.g. vasoactive properties and neurosignialling properties. Several cohort studies have shown increased risk of persistent cough and shortness of breath among infants with high NO₂ levels in the home (van Strien et al.. 2004). Similarly, a Swedish nested in cohort case-control study showed that high NO₂ levels measured outside the dwelling of children aged up to two years were associated with increased risk of recurrent wheezing (Emenius et al. 2003). The only published panel based time-series study of infants similar to our study did not show consistent associations between daily incidence of wheezing bronchitis and NO₂, whereas no data for NO_x were reported (Pino et al. 2004). In a population based study in a part of London there was a non-significant association between daily NO₂ levels and daily counts of emergency room visits with wheezing among infants, whereas ozone levels and some hydrocarbons showed significant associations (Buchdahl et al. 2000). Accordingly, the present statistically stronger association between the respiratory outcome and NO_x than with respect to NO₂ and also the more clear association with street levels rather than city background levels could also suggest that the associations are not directly causal. NO_x levels could be an indicator of traffic generated air pollution e.g. in terms of ultrafine particles and it is closely correlated with TON at the street stations (r: 0.95 at Jagtvej and 0.76 at HCAB).

An apparently protective effect of O₃ on development of respiratory symptoms in COPSAC children is consistent across all three populations, except for city background measurements in central Copenhagen children, where we see positive non significant association. The apparent protective effect of O₃ measured at street level is significant in children from central Copenhagen and from Zealand beyond Copenhagen suburbs (pulations 1 and 3). This may be surprising because ozone is known as a strong airway irritant associated with e.g. incidence of asthma and airway symptoms (Buchdahl et al. 2000; McConnel et al. 2002). However, the levels are relatively low in Denmark and the apparently protective effect may be related to consumption of ozone by NO emitted from diesel vehicles, supporting that traffic generated air pollution could be responsible for the association with respiratory symptoms. Indeed, ozone is negatively correlated (r-values around -0.7) with CO and NO_x at both urban background and street monitoring stations.

Result from the moving average model for PM₁₀ for Copenhagen city background levels indicate positive but borderline significant (p=0.07) associations with new respiratory symptoms in children living in inner city, with the strongest effect after 3- to 4- days lag, where the associations were significant in the single day exposure lag model (Table 4.1.5). The effect estimate of a 1% increase in incidence of symptoms for a 1 µg/m³ increase in PM₁₀ is completely consistent with findings from Santiago, Chile (Pino et al. 2004). There, a 1% increase in wheezing bronchitis for 1 µg/m³ increase in PM_2.5 with a lag time of 2 to 10 days was found among 504 children aged 4-12 months in particular among those with predisposition for asthma. In the present study no association with urban background PM₁₀ was seen for the children living in Copenhagen suburbs or the rest of Zealand, nor for the PM₁₀ measured at Jagtvej (street level) and Lille Valby (rural levels), supporting the relevance of the findings. In Santiago, Chile, PM_2.5 was stated to be strongly dependent on traffic, which is not the case in Copenhagen, where long range transport is a main contributor to urban background levels. Nevertheless, urban background PM₁₀ levels are correlated with the traffic generated gases at the background as well as the street monitoring stations with r-values around 0.5. Part of this covariation is probably due to meteorological conditions with low wind speed, inversion and stagnant air favoring persistence of air pollution around the sources of emission. Thus, at present it is difficult to determine which air pollutants are most relevant for the airway symptoms in infants although traffic appears to be important.

The results for PM_2.5 measured at street level (HCAB) indicate weak negative and far from significant associations in all three populations. With the single day exposure model lag findings among children from central Copenhagen are however consistent with the positive association for PM₁₀ where the strongest effect is seen at around 4-day lag (Table 4.1.7). Note that there was limited number of observation for the PM_2.5 analyses.

Analyses with TON (part./cm³) show that there is no significant association with the incidence of respiratory disease in small children in any of the populations of children. For the Jagtvej street station with the unconstrained distributed lag model and with the single day exposure model also for the city background station there are some signs of a positive association with a lag of 3 to 4 days. Note that the analyses with TON are based on a limited amount of available data. TON includes all ultrafine particles both liquid and solid, including soot. The latter may be the most relevant where effect may disappear when all particles are considered. Although, small children with there small airways may be expected to be particularly susceptible to ultrafine particles there are not yet data published to support that notion. In the only available study, which included older children (7-12 years old), with asthma symptoms were associated more closely with PM₁₀ and soot than with ultrafine particles (Pekkanen et al. 1997); whereas ultrafine particles were more closely associated with asthma symptoms in adults patients than fine and coarse particles were (Peters et al. 1997; Pentinen et al. 2001).

The results seen above should be take with some caution due to limitations of our study which include small number of outcomes due to small cohort of asthma susceptible children, large number of missing data for certain pollutants, and multiple testing issues due to large number of available pollutants from several measuring stations. In addition, as explained in Appendix C, our modeling approach where we treat day-to-day outcome as independent, may underestimate standard errors of the estimates and thus lead to overestimated p-values. With further appropriate adjustment for p-values for multiple testing, some of the significant p-values we report may no longer be significant. The small number of outcomes also affects the p-values. However, due to strength of our study of large number of available pollutant data, from several different sources, we get convincingly consistent estimates for pollutants across different measuring stations for the same populations, which validate these associations, and point at their true effect, regardless of significance.

The levels of air pollutants as well as the respiratory symptoms show seasonal and other time-dependent variation and both may be affected be meteorological conditions, which could cause confounding. However, season, day of the week and meteorology were controlled for in our GAM model with relevant smoothing functions, although it cannot be excluded that residual confounding from seasonal variation and/or other unidentified confounders are responsible for the apparent association between lower respiratory symptoms and air pollutant levels. Nevertheless, the apparent differential relationship between outcome and air pollutant levels which were much stronger with dwelling close to the monitoring stations than with dwelling farther away is strongly supportive of relevant associations.

Strengths of our study include a well defined and well characterized birth cohort of 400 susceptible small children followed for 1½ year and a large pool of pollutant data from several different measuring stations. Our study has a unique outcome recorded prospectively. The outcome consists of all R068 symptoms recorded daily into diaries by parents of the children regardless of their origin (asthma, influenza, etc.), where most other studies of air pollution health effects in small children include outcomes based on physician defined diagnoses of asthma, wheezing bronchitis, etc. and focus on one outcome for each child, i.e. diagnosis or not related to a cumulated exposure. That may allow risk of confounding due to other person related factors. Thus, effect estimates are not easily compared except between time-series based studies and here our results compare well with the only other published study by Pino et al. (2004) as described above. A strength of the time-series based design is that the subjects in principle are their own control and only factors with temporal variation give rise to serious risk of confounding.

Our results confirm our hypothesis that children living in central Copenhagen (postcode ≤ 2450) are the most relevant population choice, as it is most representative of pollution levels measured in urban background at in the street at Jagtvej and HCAB. The association between symptoms and in particular CO and NO_x and inverse association with ozone suggest a relationship with traffic related air pollution as there is no other significant sources, where CO is mainly associated with petrol driven cars whereas NO_x is associated with diesel powered vehicles. Thus, ultrafine particles, which are emitted from particularly diesel vehicles, would also be expected to show associations but showed less consistency, Our results for particles were borderline significant for PM₁₀ which have other main sources than traffic, but completely consistent with the only published similar study from Santiago, Chile, where traffic may be more important for fine particles (Pino et al. 2004). Only the data for CO, NO_x and NO₂ are close to complete for the study periods, whereas data on PM₁₀ and ultrafine number concentrations are very incomplete. Thus, lack of significant associations with symptoms may also be related to low statistical power as can be seen from the large standard errors for most of the coefficient estimates.