It’s easy enough to understand how this finding will be used. Young northerners die at higher rates than young southerners. This is undoubtedly the result of inequality so we’ve got to tax everyone much more – especially the rich b’stards – in order to pay for more diversity advisers. This may not be the right conclusion to draw from the initial finding as even the paper itself notes. Quite apart from anything else inequality is higher in the south – all those rich b’stards in The City – therefore the effects of inequality should be felt more heavily there.
A much better explanation is internal migration:
There has been a “profoundly concerning” rise in early deaths from accidents, suicide, alcohol misuse, smoking, cancer and drug addiction in the north of England, deepening the north-south divide, research has found.
Socioeconomic deprivation has led to a particularly sharp rise in deaths among 25 to 44-year-olds , according to new data analysis from Manchester university.
Northerners in that age group were 47% more likely to die from cardiovascular complications, 109% from alcohol misuse and 60% from drug misuse, compared with southerners, the paper published in the Lancet Public Health medical journal stated.
I’ve no doubt the effect is there. Well, with a caveat that is. The question is, rather, what’s causing it? As the paper itself says:
The possible causes of these regional disparities in England are complex, and are likely to include environmental, occupational, migratory, epigenetic, and lifestyle factors, in addition to long-term structural imbalances of resources and investment in the south, particularly in and around London.
I would argue – do argue – that it’s the migratory that matters.
There was a similar finding about Appalachia and life spans over in the US:
A new report out showing that there’s a 20 years life expectancy gap across US counties. This is something that will shock many and will, undoubtedly, be used as an example of the pernicious and terrible inequality within the country. However, by the standards of these things it’s not hugely out of line. The life expectancy gap in the much smaller and rather less unequal UK is of about the same size, around and about 20 years on average between the longest lived areas and shortest. The American experience is a little different in that the original indigenes are still treated rather differently in a manner that those of Britain are not but other than that the findings are about the same.
The part of this to understand is that no one, no one at all, is measuring the life spans of where people are born nor where they grow up. What is being measured is that average age at which people die in a particular area. Thus migration over lifetimes can be a significant influence. As indeed it is. Imagine that there was a county in Florida (there may even be) which was nothing but retirement homes. It’s an obvious truth that people who have already survived to 65 have a longer expected total lifespan than people of 18 for there are always some deaths by accident, premature deaths from disease and so on over the intervening 47 years. So, if we’ve a place which is solely populated by those who have already reached 65 then it’s going to have a longer expected lifespan than everywhere else.
But note the flip side of that too–that this place has a higher lifespan means that some other areas will have lower. Because the people who would have died old in those areas now go on to be 90 in that Florida county. It is vital to understand this when considering these statistics about variable life spans across American geography.
And we’ve even the ONS saying that something similar is happening in the UK:
One factor that has received less attention is the selective migration of healthy individuals from poorer health areas into better health areas or vice-versa. This type of migration has been shown to play a significant role in increasing or decreasing location-specific illness and mortality rates, which then consequently impact on life expectancy figures. Norman, Boyle and Rees (2005) demonstrated that the largest absolute flow within England and Wales between 1971 and 1991 was of relatively healthy people moving from more deprived into less deprived areas. The impact of this migration was to raise ill-health and mortality rates where these people originated from and lower them in the destination areas. The authors also noted that the benefit to less deprived areas was reinforced by a significant group of people in poor health who moved from less to more deprived locations.
Think of it in the rather brutal terms that we must use to consider mortality. Among any population of young people – I’ve recently graduated to that level of maturity where late 40s in other people makes them young – there are going to be some who kill themselves with lifestyle, as here. There will also be those who don’t. And in any such population we also know that it will be the poorer and iller educated, the two quite possibly being the same thing, who will do so more than their richer fellow young peeps.
Now add migration of the young with get up and go out of poor areas and not-migration of those without it. The observed rate of death by lifestyle will rise in our poor area. Not because there’s been any change at all in the number dying from tabs’n’booze, just because those less likely to do so have left. Our incidence of the problem hasn’t changed one iota. Our observed rate has. Note that the young less likely to do this moving to the richer areas also brings down the rate in those rich areas, doubling the observed gap.
Now, is this all of it? It’s certainly possible. At least one serious statistician thinks that this is the total explanation of the Appalachia problem. Is it also so of the UK north/south one? I’d argue that’s the way to bet, certainly. What I would insist upon though is that until we’ve pulled out from the more general figures that migration effect then we cannot conclude that it’s got toss all to do with inequality nor anything else. On the useful enough basis that we’ve no idea which is causing what amount of it.