The detrimental effects of air pollution on human health came to public prominence in the mid 1900s, as a result of high pollution episodes in the Meuse valley, Belgium (1930), Donora, Pennsylvania (1948), and London, England (1952). The latter was associated with more than 3,000 excess deaths [1], and was the catalyst for legislation such as the UK Clean Air Act in 1956. Since then, a large number of studies have investigated the health risks from air pollution, and found consistent associations between components of ambient air pollution and measures of ill health. Numerous health endpoints have been considered in such studies, with the most common being mortality [2] and morbidity [3] from respiratory [4] and cardiovascular [5] disease. A number of different pollutants have also been considered in such studies, including, carbon monoxide [6], ozone [7] and both coarse [8] and fine [3] particulate matter. These studies have investigated the effects of both long-term [9] and [10] and short-term [11] and [12] pollution exposure, with the latter typically utilising an ecological time series design. Such time series studies make use of routinely available health and pollution data, and are thus the most common study design because they are inexpensive to conduct.

Studies such as those highlighted above provide evidence for the creation of air pollution legislation and guidelines, with examples in the UK being the Clean Air Act (1993) and the Air Quality Strategy (2007). In recent times, the conduit for such studies to effect UK legislation has been the independent Committee On the Medical Effects of Air Pollution (COMEAP), which informs governmental policy by critiquing the evidence provided by such studies. However, surprisingly few of these studies quantify the effects of pollution in the UK, with the majority being based in the USA [12] and [13], mainland Europe [11] and [14] or Asia [15] and [16]. As a result, COMEAP has been forced to base its recommendations to government on studies from further afield, particularly the USA. The transportation of evidence from one continent to another has its own problems (as acknowledged by COMEAP), and suggests that more studies are required to further assess the effects of air pollution in the UK. Furthermore, the studies that have been conducted in the UK have been predominantly based in London [17] and [18], with relatively few assessing the health impact of air pollution in Wales, Northern Ireland or Scotland.

In Scotland, studies estimating the short-term effects of pollution are limited to [19] and [20]. The short-term study [19] was based in Edinburgh, and investigated the effects of multiple pollutants, including nitrogen dioxide, ozone and particulate matter, on multiple health end-points between 1981 and 1995. The results from this study were largely negative, consistently showing no relationship between pollution and ill health. Study [20] extended study [19] to Aberdeen, Edinburgh and Glasgow, the three largest cities in Scotland, and performed a meta-analysis to give overall results for urban Scotland. Their study was based on data from 1981 to 2001, and also failed to find any consistent associations.

Therefore the aim of this paper is two-fold. Firstly, we extend [19] and [20] using more recent data (2000 to 2006), allowing us to add to the limited body of evidence about the effects of air pollution on health in Scotland, as well as in the UK more generally. Secondly, we provide a critique of the challenges inherent in conducting ecological time series studies of this type, particularly the appropriateness of using routinely available health and pollution data for this purpose in small to medium sized cities. Our study focuses on coronary heart disease (CHD) and stroke as the health outcomes, because they are leading causes of death and ill health in Scotland, and are clinical and public health priorities for NHS Scotland. The pollutant we consider is coarse particulate matter (PM₁₀, particles less than 10 micrograms per cubic metre), because it is the pollutant most often linked to health, and because measurements of finer particulate matter (PM_2.5 and PM₁) are not available.

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 μg/m³ and 22.5 μg/m³ respectively, which are substantially lower than in five of the eight cities studied in [11] during the 1990s (the average concentrations in μg/m³ 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 PM_2.5, PM₁ 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 PM_2.5 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.

This study suggests that in small cities where air quality is relatively good, then: either there is no relationship between concentrations of PM₁₀ and cardiovascular ill health; or that time series studies lack the necessary statistical power to detect an effect and hence may not be an appropriate study design in this context.