The main finding of this study is that there was no association between PM10
concentrations and cardiovascular hospital admissions in urban Scotland between 2000 and 2006. This result is consistent with the earlier studies [19
] and [20
] in Scotland, but goes against the majority of the published literature (see for example [11
] and [13
], especially the systematic review of the existing evidence published by the COMEAP in 2006 [23
]. This in turn raises the question of why no association was found, and there are a number of possible explanations.
The first is that PM10
concentrations may not have a detrimental effect on cardiovascular ill health in urban Scotland during the time period considered by this study. The lack of such an association could be because the level of PM10
was too low to have an effect on cardiovascular ill health, as the concentrations observed are well below the limits set by the UK air quality strategy in 2007. In addition, PM10
concentrations have fallen by around 50% in the UK between 1990 and 2006 (http://www.scotland.gov.uk/Topics/Statistics/Browse/Environment/TrendPM10
), and many of the existing studies that found positive associations predate such improvements in air quality. For example, in the present study the median concentrations observed in Edinburgh and Glasgow were 20 μ
and 22.5 μ
respectively, which are substantially lower than in five of the eight cities studied in [11
] during the 1990s (the average concentrations in μ
in these five cities were 28, 39, 51, 52, 56).
A second explanation is that the air pollution monitoring network in Scotland may not be sufficient to accurately characterise the spatial pattern in PM10
concentrations across the two cities, thus potentially leading to errors in the daily exposure estimates. Such errors may occur because the pollution network measures ambient (outdoor) concentrations from a small number of centrally sited monitors, some of which are located next to busy roads. Therefore the concentrations recorded by these monitors are unlikely to be representative of the levels of pollution to which the population are actually exposed. A number of statistical approaches have been proposed to tackle this problem, including the use of exposure simulators [24
] and measurement error models [25
]. However, such approaches are not a substitute for improved data collection, and different monitoring strategies may be required for air pollution in the future.
A third possibility to explain the null results found in this study is that PM10
is not the most appropriate exposure measure, because it contains relatively coarse particles that cannot travel deep into the lungs. In fact, recent evidence (see for example [26
] and [27
]) has shown that smaller particles, such as PM2.5
and ultra fine particles, are likely to be more toxic to human health, in part because they can travel further into the lungs. However, as already discussed, air pollution monitoring in Scotland was relatively sparse during the study period, and PM2.5
concentrations were not measured consistently until early 2008 in Edinburgh and late 2004 in Glasgow.
An alternative statistical explanation of our results may be that the study design did not provide enough statistical power to detect a pollution-health relationship. The choice of a time series design for this study was made for two reasons, comparability with existing research, and the routine availability of the required data. The latter is likely to be one of the major reasons why time series designs make up the largest proportion of air pollution and health studies, because they are fast and inexpensive to conduct. However, for this study design to have enough statistical power to detect an effect, both the exposure and the response series need to have sufficient levels of day-to-day variation. For the Scottish data analysed here this may not have been the case, as the levels of variation in both series were relatively low. The inter-quartile ranges for the daily cardiovascular disease counts ranged from 4 to 8 cases per day in Edinburgh, compared with between 8 and 13 cases per day in Glasgow. The variations in the daily PM10 concentrations were also relatively small, with inter-quartile ranges of between 16.0 and 26.0 in Edinburgh, compared with between 17.0 and 30.5 in Glasgow.
These low levels of day-to-day variation in both series may have led to a lack of statistical power in the study, which in turn may have contributed to the null associations observed here. This suggests that such routinely available data may not be sufficient for estimating the association between air pollution and ill health in small to medium sized cities such as Glasgow and Edinburgh, where the levels of day-to-day variation in both pollution and ill health are relatively small. Therefore, in the future alternative study designs with more statistical power may be required to accurately estimate the effects of air pollution on human health in Scotland. One possibility would be conduct a cohort study similar to [26
] and [27
], although such a study would require individual level measurements of health and pollution exposure, which would be expensive to obtain. Such an individual level study would also require data on confounding factors such as smoking status, which are not required in ecological time series studies because the distribution of such covariates across the population under study is unlikely to change on a day-to-day basis.