A recent report suggests that road traffic pollution causes 5,000 premature deaths a year in the UK, whilst exhaust from planes adds another 2,000 (http://www.bbc.co.uk/news/science-environment-17704116 for summary, the actual report is a paper in Environmental Science and Technology which is a journal for which you need a subscription). The numbers are comparable with those produced by COMEAP (Committee On the Medical Effects of Air Pollution) "The Mortality Effects of Long-Term Exposure to Particulate Air Pollution in the United Kingdom" which estimates air pollution was responsible for 28,000 deaths in the UK in 2008 (the more recent study estimates 19,000 deaths in that year). One interesting statistics from the more recent report is that road traffic accidents caused only 1,850 deaths in 2010, meaning that traffic pollution is a more potent killer.

So what can we make of these figures. The exact number of deaths depends on how you calculate 'premature' deaths. This means you need to extract from the number of deaths those that would not have happened had it not been for the pollution. This means using life-table analysis to predict survival rates of different age groups. If air pollution improves, for example, you might expect everyone to have an improved survival change but that this would be greater for young children than for people in their 80s. The children who benefited from the reduction in pollution have to die sometime so the benefit is not sustained indefinitely. This means that you have a dynamic or continually changing death rate based on a reduction in pollution levels. The COMEAP report suggests that any benefits from reductions in air pollution should be expressed in terms of improved life expectancy or number of life-years gained but accept that the 'number of attributable deaths' is a much catchy way of expressing the information.

An interesting read for interpreting the 'deaths' is the appendix Technical Aspects of Life Table Analysis by Miller and Hurley. This short report goes through the technical aspects and assumptions involved in this sort of analysis. Be aware through it does get into the mathematics fairly quickly. Importantly, starting with 2008 as a baseline you construct an age-specific all-cause mortality hazard rates, hi, that acts upon age-specific populations, ei. Additionally, the number of viable births into the future is taken to be the same as the 2008 baseline. Changing policies alters the 'impact factors' which differ by age group and time. By altering this impact factor you change the the hazard impact and so alter the mortality rates.

Understanding how 'deaths' are calculated and the assumptions involved are vital to interpreting the information provided. This tends to be particularly important when, as in this report, the 'deaths' are the end result of mathematically modelling of a data set and a series of key assumptions about the impact of different scenarios. I am not suggesting that the mathematics is wrong, the use of life-table analysis has a long and profitable history in the insurance industry so the modelling is on a very sound base. The COMEAP report recognises this problem of interpretation (starting page 13) and knows that there is a trade-off between between full accuracy and accessibility. It is also acutely aware that the numbers are open to misunderstanding if the basis of their calculation is not understood. On page 14 of the report, for example, they state for the term 'number of attributable deaths' that:

In interpreting this type of data it is important to know how it was derived, to know if it was modelled, and if so how, and, as importantly, the exact technical definitions used for terms. The alternative is relying on others to interpret the data for you with all the attendant agendas potentially coming into play as they draw their conclusions.

So what can we make of these figures. The exact number of deaths depends on how you calculate 'premature' deaths. This means you need to extract from the number of deaths those that would not have happened had it not been for the pollution. This means using life-table analysis to predict survival rates of different age groups. If air pollution improves, for example, you might expect everyone to have an improved survival change but that this would be greater for young children than for people in their 80s. The children who benefited from the reduction in pollution have to die sometime so the benefit is not sustained indefinitely. This means that you have a dynamic or continually changing death rate based on a reduction in pollution levels. The COMEAP report suggests that any benefits from reductions in air pollution should be expressed in terms of improved life expectancy or number of life-years gained but accept that the 'number of attributable deaths' is a much catchy way of expressing the information.

An interesting read for interpreting the 'deaths' is the appendix Technical Aspects of Life Table Analysis by Miller and Hurley. This short report goes through the technical aspects and assumptions involved in this sort of analysis. Be aware through it does get into the mathematics fairly quickly. Importantly, starting with 2008 as a baseline you construct an age-specific all-cause mortality hazard rates, hi, that acts upon age-specific populations, ei. Additionally, the number of viable births into the future is taken to be the same as the 2008 baseline. Changing policies alters the 'impact factors' which differ by age group and time. By altering this impact factor you change the the hazard impact and so alter the mortality rates.

Understanding how 'deaths' are calculated and the assumptions involved are vital to interpreting the information provided. This tends to be particularly important when, as in this report, the 'deaths' are the end result of mathematically modelling of a data set and a series of key assumptions about the impact of different scenarios. I am not suggesting that the mathematics is wrong, the use of life-table analysis has a long and profitable history in the insurance industry so the modelling is on a very sound base. The COMEAP report recognises this problem of interpretation (starting page 13) and knows that there is a trade-off between between full accuracy and accessibility. It is also acutely aware that the numbers are open to misunderstanding if the basis of their calculation is not understood. On page 14 of the report, for example, they state for the term 'number of attributable deaths' that:

*To emphasize that the number of deaths derived are not a number of deaths for which the sole cause is air pollution, we prefer an expression of the results as “an effect equivalent to a specific number of deaths at typical ages”. It is incomplete without reference also to associated loss of life. The Committee considered it inadvisable to use annual numbers of deaths for assessing the impacts of pollution reduction, because these vary year by year in response to population dynamics resulting from reduced death rates.*In interpreting this type of data it is important to know how it was derived, to know if it was modelled, and if so how, and, as importantly, the exact technical definitions used for terms. The alternative is relying on others to interpret the data for you with all the attendant agendas potentially coming into play as they draw their conclusions.

The air pollution issue is really getting serious in UK. Sometimes when I come out and breathe in I feel my lungs are all covered with ashes... Opt for bicycles people!

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