Traffic Light Statistics

14 June 2013 by Tania Browne, posted in Epidemiology, Statistics

Image: Public Health England

If you read a newspaper or news website regularly at all, it will come as no surprise to you that there are vast inequalities in people’s health around the world. What may come as a bit more of a shock is that these inequalities don’t only exist between different countries. If you look at the newly created  Public Health England’s latest website, you’re in for a treat. Or at least, a treat to a budding epidemiologist like me. But while generally good, the site also has serious shortcomings. Like statistics quoted in advertising, you should always be wary of simplistic infographics that may possibly have political motivations.

On Tuesday PHE launched Longer Lives, a website which aims to point out the differences between local authority areas in mortality rates for the four biggest causes of premature death - cancer, heart disease and stroke, lung diseases and liver disease. The resulting map looks surprisingly like a traffic light at first glance - a big scary red patch near the top, a few brief smatterings of yellow and amber in the middle and (for the most part) a nice green swathe below The Wash, in the south of England.

The Longer Lives campaign has gathered its data from the Office for National Statistics, which In turn uses the coded categories provided by the latest version of the International Classification of Diseases, entered on the database by a Medical Examiner. These codes are used around the world to track and register disease, and categorise causes of death provided on death certificates. But there is not always complete agreement between the doctor who wrote the death certificate and the medical examiner in Southport who will assess and add the details. This can lead to quite significant wobbles in the statistics. A study by Vickers et al quoted in a blog post from the Socialist Health Association cited 548 deaths, where for 142 cases the original certifier and the medical examiner came to different conclusions. And most of these difference were centred around the "Big Four" that Longer Lives has chosen to focus on.

Another problem is that the site is mainly interested in what we classify in the UK as “premature death”, people who die below the average life expectancy of 75 years. This figure in itself is a bit of a fudge between genders as women generally live longer than men, and not based on a real average but a guess of an average which is adjusted for the year you were born in and then the figure… well. You get the idea. Life expectancy is a pretty broad figure to work on, and once again an adjustment of a few years more or less would lead to quite big differences in what we class as "premature". Another problem with using life expectancy figures for small local authority areas is that they'll have quite big fluctuations in mortality rates from year to year. One person dying prematurely in an area with 10 000 people will have more statistical weight than one person in 600 000 somewhere else.

On the whole, the most frightening thing about the premature mortality figures here is how closely they tally with areas of economic deprivation. Do you live in Wokingham or Richmond Upon Thames? Congratulations, your area has 200 people dying prematurely per 100 000 population. You’re also classed as living in two of the least deprived areas of England. Blackpool or Manchester? The number of deaths per 100 000 more than doubles and – you guessed it – you are in two of the most deprived areas. PHE categorises Local Authorities into 5 groups using something called the Indices of Multiple Deprivation, complex calculations that don't necessarily measure our socio-economic status.

How do we decide what is “deprived”, and if it has a bearing on our health? A favourite phrase in epidemiology is, as with much of science, “it’s a bit more complicated than you might think”. Premature mortality rates give us a broad picture, but there’s a whole wealth of information on wider determinants of health which show just how complex this gets. The Public Health Outcomes Data Tool provides data on some factors which you may never even have considered, such as how many children are living in poverty, the rate of school attendance, the number of adults with a learning disability, re-offending levels for both violent and non-violent crime, the number of complaints about noise and the use of parks and leisure centres. It may seem amazing, but all of these factors have a clear correlation to how healthy we are. There are also more obvious indicators of improvement in people’s health such as birth weight, the prevalence of breast feeding, the proportion of children with excess weight, cancer screening coverage, smoking prevalence and successful completions of drug treatment for opiate users. You may also want to consider the rate of injuries from falls in the elderly, and quite simply asking people how happy they are. The government may use factors like these to judge how well a local authority is addressing health issues within its borders.

But there is something else that the Public Health Outcomes Data Tool states, which has an important bearing to the "traffic light" style of Longer Lives. Public Health Outcomes very purposefully do not use a red, amber and green colour scheme. This is, they point out, because their aim is transparency rather than to be used as a stick to beat Local Authorities on the head with. There has been some concern that Public Health England, as part of the Civil Service rather than the National Health Service, may be too close to government and too vulnerable to being used for political aims. As the Public Health Outcomes site is now also under the civil service umbrella as part of Public Health England, they state their colour coding policy may change. It's important that Local Authorities in England are not judged solely on their simplistic campaigns that emphasise our personal responsibilities for our health, and on the factors mentioned above such as obesity in chidren and cancer screening rates. Life is so much more complicated than that.

Image: Wikimedia commons

With the addition of a few vital missing parts of information, the website could be useful in other ways. In the last 70 years Britain has gone through an enormous Health Transition. Infectious disease and the diseases of childhood have declined hugely, child mortality rates have receded and in some ways our health has improved. But in other ways, we’re in a worse state than we were in the immediate post-war period. Modern UK diseases are less to do with infection and more to do with our lifestyles. Cancers and heart disease in particular are more common, and as well as a health transition we have undergone a Health Care Transition. Health care services are chameleon-like, changing their funding emphasis all the time to try and best respond to predicted health issues. A map like PHE’s not only shows up the inequalities, but at a more detailed level it could enable health care providers to develop strategies for the future in a world of extremely limited funds and snipped budgets. The broad sweep of the information at the moment, together with the fears of possible political motivation, makes this difficult.

On the whole, I applaud the effort that's gone into making both the Longer Lives and Public Health Outcomes websites. While infographics like these have their limits, they are a great way for getting health information across to people with a general rather than professional interest. But I would also be cautious about how suggested interventions to improve the figures emphasise what we can do to improve our health on a personal level, while glossing over wider public health interventions that could be put in place with some decent funding, I would also worry that the figures might be used in future to rank local authorities into some kind of league table system that simply isn't appropriate to this kind of issue. The information is a great tool, but be careful who is giving you your tools and how they intend you to use them.

One Response to “Traffic Light Statistics”

  1. Sparkles Reply | Permalink

    There are some impressive public health maps at a lower level than the Longer Lives one, for instance the local health profiles ( which include estimates at ward level.

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