Evidence is beginning to surface of the possible health effects of the rapid social polarisation that is taking place in the UK. This evidence is often hidden, or at the very least hard to find, but it will soon emerge more fully into public debate. In September 2015, at the annual British Sociological Association Medical Sociology conference at the University of York, I used the following graph to show that there has been a stalling in one of the key official indicators of health improvement in the UK in recent years. The indicator concerns Potential Years Lost of Life or early mortality, among men (see Chart 1).
Chart 1: Source: http://www.lgcplus.com/Journals/2015/05/22/e/i/u/QCRC-Board-Paper—copy-version-2.pdf “Quality and Clinical Risk Committee Paper – NHS England – October 2014
The document, that this graph came from, was found in a report prepared as background material for a meeting that was held a year ago titled: “Medical Directorate Senior Management Team Meeting, 2 October 2014, 4d Deterioration in Rate of PYLL Improvement”. The document is marked “In confidence – not for publication” – but it is on an open access website – anyone can read it and it has been on the website for many months. Unless it is soon removed anyone can find a copy (other interesting background information is available here)
Within the medical directorate’s document of October 2014 was the following statement: “The attached analysis, which is based on new provisional mortality data that we have obtained from ONS shows that PYLL in men has been improving steadily until 2010, but in 2012, 2013 and 2014 the improvement has been much more gradual. Further, male PYLL is likely to have deteriorated for the first time in 2013 and this deterioration is partly linked to a particular peak in male PYLL in April 2013, which is as yet uninvestigated.”
Clearly there are considerations as to whether the introduction of the tenth International Classification of Disease (ICD10) coding changes may have influenced the trend. That is what the word “coding” on the graph refers to. However, there are also political considerations, as the addition of the word “election” on the original graph made clear. What we know is that the long-term improvements in years of life lost due to premature mortality is beginning to stall; although we only know it if we are good at using Google and understand acronyms well.
For NHS England and Public Health England PYLL is a key statistical indicator: Potential Years of Life Lost (PYLL) is a measure of premature deaths attributable from causes considered amenable to healthcare. It is the NHS Top Indicator, Labelled 1a, and is the primary key outcome measure that NHS England asks Clinical Commissioning Groups (CCGs) to monitor. The earlier someone dies as a result of a cause of death that is treatable or otherwise preventable, the more that damages this measure. For the years 2013/14, PYLL was described as the “Overarching indicator” to be used to monitor health in England. Given that, it is odd that as yet concerns about recent trends in health outcomes in the UK have been so muted.
For a year it has been known that improvement in the PYLL indicator is stalling for men. For longer we have known that female life expectancy in old age has been declining in the UK since shortly after that 2010 election. In April 2015 it was suggested that the sudden drops in female life expectancy in the UK could be due to the rise in smoking among women in the past. However, that rise in smoking among women was not a sudden affair, and even if it had been the impact decades later would have been spread over several years, it would not have been so sudden. For both men and women in the UK past improvements in health outcomes are either rapidly stalling or actually reversing.
There will be a great many reasons to explain these trends. Some are sudden such as the huge increase in people, mainly men, dying due to drug poisoning in 2014, the highest number since records began. Two thirds of these 3346 deaths involved the use of illegal drugs. Between 2012 and 2014 there was a 64% increase in deaths involving heroin or morphine in England and Wales. Some explanations will be about less sudden changes – the effects since 2010 of slow and steady drops in the rates of visiting of (and care of) the elderly, especially single elderly people who are mostly women, as well as the impact of cuts to pensioner credits and many other services linked to the mortality of elderly women. Other possible explanations will turn out to be red herrings, such as one initial theory that the rise in elderly mortality was due to influenza or a cold winter (neither was the case).
It is at points like this that medical sociology can move understanding beyond the clinical immediacy of drug overdoses and neglect. There are economic and sociological reasons underlying the sudden rise in the numbers of young people taking drugs that can kill them. There are reasons why people visit their elderly relatives less when average income fall and the cost of petrol rise. There are reasons why higher rates of infant mortality are tolerated in more unequal affluent countries. See the graph below of infant deaths per 1000 births in the richest 25 large countries in the world.
Chart 2: Source: WHO, OECD, LIS and others UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org. The New York Times Income Distribution Database (2014) assembled by Janet Gornick (LIS), Thierry Kruten (LIS), Branko Milanovic (LIS), David Leonhardt (NYT), and Kevin Quealy (NYT), www.lisdatacenter.org/resources/other-databases/, 19/06/2015
The ratio of income inequality shown in the graph above is the fraction of mean equivalised household income of the top to the bottom decile group of households. The data is from the latest Luxemburg Income Study (LIS) dataset available. Other sources were used to construct the graph above when LIS data is missing. The key importance of this measure of income inequality is that it includes all people in both extreme decile groups. It is the total income of the richest tenth of people living in households divided by the total income of poorest tenth in each country.
Why are these extreme decile groups important? Some politicians try to invoke what the Economist magazine recently called “statistical tricks” to suggest that inequality is falling in the UK. The graph below was produced in the Economist Magazine to illustrate how a claim made by UK Prime Minister David Cameron in 2015 that inequality is falling was based on a measure of income inequality that ignored the incomes of everyone in the best-off and worse-off tenths of society. It was what he called the 90:10 ratio and has fallen rapidly since 2010. The magazine contrasted this with a measure of the take of the best-off 1%. The Economist is not a radical publication, when it criticizes a Prime Minster it is because the Prime Minster has made a mistake.
Chart 2: Source. The Economist Magazine, July 18th 2015, article titled “Statistical Tricks”
The 90:10 ratio the Prime Minster was referring to is the ratio of the decile points, not groups. It is the income of the household just below the best-off tenth of households divided by the income of that household who is a fraction better off than all of the poorest 10%. It intentionally and entirely ignores the incomes of the richest and poorest 10% of households – when combined these groups make up a fifth of the population! In contrast the 90:10 decile group ratio used to draw the graph above showing income inequality related to infant mortality is based entirely on the incomes of people in those extreme groups.
Many measures of health outcome in the UK are now deteriorating. Health inequalities are rising. Incomes inequalities are rising when the income of the best-off tenth is included because the incomes of the best-off 1% are so very high. Wealth inequalities show even worse trends in very recent years with the richest thousand families in the country doubling their wealth in a very short period of time. It is time we began to recognise the repercussions of all of these trends. They are linked and not coincidental events. As the levels of inequality are exacerbated this evidence becomes harder and harder to obscure.
About the Author:
Danny Dorling is an Academician of the Academy of the Learned Societies in the Social Sciences, Honorary President of the Society of Cartographers and a patron of Roadpeace, the national charity for road crash victims. He has published widely with many colleagues on issues related to social inequalities in Britain. Much of this work is available open access and will be added to his website soon.
2 Responses
Aaron on Oct 2, 2015
Thanks for this Danny. It is noteworthy that the stagnation in PYLL is primarily observed among men and not women and so I wonder whether this could be explained by the rise in suicide over this same period, which has also been concentrated in men. Those suicides appear linked with the crisis and then austerity and so still fit with the overarching argument but if suicide is the primary driver then perhaps the policy implications are different.
Mariadivair on Feb 14, 2016
whatever is going on for the avegrae American, there are a huge group of Americans worse off, in absolute and relative terms, in the wages they get in the current market economy and with the wealth they’ve tried to build. Your conclusion is unsupported by the charts.The charts shows differences in amounts held or earned by percentile groups, but it is not measuring the difference in wealth or income among the same families. The Census definition of family is related individuals living together.Having more young people move out of their parent’s homes, more divorces, more cohabitation for which a family measurement does not combine the partners income or wealth, more dual earning husbands and wives, and more retirees and especially more older retirees would produce much of your results. Immigration differences will also affect the inequality measurements.Many studies show that the top earners and wealth holders are not static over a decade or longer. There is considerable churning at the top, middle and the bottom with many moving out of their initial percentile ranking by several deciles. Longitude studies that track families, households or individuals over time show income and wealth gains as one moves from new entrant into the workforce to experienced worker to dual worker household to retiree. They also show a decline in family income as one enters retirement or divorces and a wealth loss in retirement and after divorce.Over long time periods, 30 years, of measured inequality and wealth changes, we have a changing amounts, and changing relative weights, of new entrants, established workers, married, divorced and retired.Unless one controls for normal life events, and establishes equal weight at the beginning and end of the period, then the different amounts of normal life events in the beginning and ending time periods will cause much of all the supposed inequality measurements.If opportunities for wealth and income gains did not exist for new workforce entrants in the US, I would expect an increase in emigration and a decrease in immigration as one sees in other countries without economic opportunities. Yet, the US has a low emigration rate and a high immigration rate.