We have presented the results of a study of the health effects of large industrial incinerators in England between 1998 and 2008. Across a broad range of outcomes that have been linked to pollutants released by incinerators in previous studies, our results show no elevated risk for individuals living in areas containing an incinerator compared to individuals living in matched areas without an incinerator.
In the models that constitute the main analysis, we made allowances for both the age–sex structure of the underlying population, through indirect standardisation, and the key confounder of deprivation, measured at the small-area (LSOA) level. The results of fitting a continuous risk function to reflect the patterns of risk of specific outcomes across regions containing an incinerator need to be interpreted carefully. There was an apparently increased risk of leukaemia incidence for those living in case regions, but for this outcome the distance effect was non-significant and the trend, counter-intuitively, was towards a decreased risk in the vicinity of the incinerator.
For all outcomes considered, within case circles, there is little evidence of an increase in risk for those living in proximity to an incinerator compared to those living further away. One might have anticipated a dose–response relationship with distance from the incinerator if the incinerators were responsible for causing an elevation in disease or mortality risk. The fact that no such relationships emerged supports our general conclusions.
have used dispersion modelling of emissions to further define exposure, particularly of dioxins, proven carcinogens. In this study, we chose to use a distance-based proxy measure of exposure because we did not have accurate retrospective data on location-specific emissions, and there remain doubts about the accuracy of air dispersion model outputs in this setting, especially when they cannot be validated against reliable measurements from monitoring networks.34
Part of the background to this study is the continuing community concern about incinerators, a concern which does not discriminate incinerators by emissions. Although it is possible that incinerator emissions differ between sites, they are likely to be more consistent over time and space than is sometimes suggested, combustion conditions being more important than precursor waste content. This supports our decision to treat incinerators at different sites as if they are homogeneous units, although differences in emissions between sites or over time may reduce the power of our study to identify authentic health effects.
Although some of the cancers we examined may have longer lead times from exposure to clinical disease than the period covered by the study, infant mortality and some of the childhood cancers have much shorter lead times, less than the 10 years covered by the period of the present study. For the adult cancers, repeating our study at an appropriate interval, based on the same sites which are now subject to more stringent controls than before 2005, may go some way to address this issue.
Exploratory analysis showed substantial differences in case numbers between different circles, possibly due to factors such as increased levels of deprivation. This emphasised the importance of including the pairing as a factor in the model. While no clear effect of distance from the incinerator was observed, it is possible that a distance effect was masked by other factors not taken into account in these plots, such as the deprivation of the area.
Higher counts in case circles than control circles were observed for leukaemia incidence and infant mortality (). This may indicate a potential incinerator effect, but may also be at least partially explained by other factors. In particular, this initial analysis makes no adjustment for the age–sex structure of the regions or differences in deprivation level.
Several other factors relating to the design and nature of the study may explain our findings. In common with other studies in this field,5
ours may suffer from unobserved confounding factors that our analysis has been unable to address. Although the dataset, based on official data from the ONS, is as comprehensive as could be expected for a study of this type, our analysis is based on small-area-level data, and therefore we are unable to adjust for individual-level risk factors such as smoking status, diet and genetic risk factors, which are strongly associated with many of the outcomes considered.35–39
Higher levels of deprivation are strikingly linked to increased incidence in many of the disease outcomes we have considered: all-cause and infant mortality, lung cancer incidence and liver cancer incidence and mortality. The decision to employ a circle-matched design in this study, in which case and control circles were also matched on a variety of other socioeconomic factors, reduced the need to adjust for many of these factors explicitly in our analysis but does not entirely eliminate it. Also, while the IMD is a generally accepted summary measure of deprivation, it cannot fully capture aspects of deprivation that may affect the risk for specific diseases. In addition, we did not take into account other sources of local air pollution. This may be a beneficial avenue for future studies to explore.
The statistical methods used in our analysis include a continuously decaying distance function model, which provided an adequate fit and gives additional information about the likely effect of distance on disease risk. Diggle et al6
have suggested fitting step function models, which include a plateau of constant elevated risk up to an unknown distance δ, and models allowing for angular direction from a point source. When we attempted to fit these models to our data, we found that parameter estimates were unstable. Further research is needed to evaluate the practical feasibility of fitting these models to area-level data.
In summary, our findings broadly support those of previous research,2
even though the residential histories of the individuals contributing to this study are unknown and many of the cancers considered have long lead times. It may require a carefully constructed individual-level cohort study, possibly also using validated dispersion modelling of emissions, to address these concerns definitively.