Please, please, try to understand the damn statistic

The UK\’s inequalities have been laid bare by new statistics that show wealthier British boys born today will live 13.5 years longer than their impoverished male peers. Meanwhile, a government-ordered report shows that low-income families are scrabbling to find more than £1bn to pay heating bills.

Data from the Office for National Statistics showed that between 2004-2006 and 2008-2010 the gap in life expectancy at birth between Kensington and Chelsea and Glasgow increased from 12.5 to 13.5 years for males and from 10.1 to 11.8 years for females.

This meant boys born in Glasgow between 2008 and 2010 could expect to live until 71.6 years. Girls born in the city at the same time had a life expectancy of 78 years.

The ONS said this suggested \”that health inequalities across the UK are increasing\”. Danny Dorling, a demographer at the University of Sheffield, said that the rich were pulling away from the poor – with the wealthy concentrating themselves in parts of London.

It\’s true that there is a life expectancy gap. It\’s also true that there\’s a geographical basis to this. However, what is not being measured is the expected life span of someone born in a particular place. That is only imputed from the information that is captured: the age of death of people in a particular place.

And the imputation is being taken the wrong way.

Now, if all people lived their lives in the ward or constituency they were born into then this would make no difference. However, people do not do so: people do move about a bit over the 60-80 years they live. Which leads to a number of possible things:

For example, let\’s say the rich do live longer than the poor. But, if you\’re born poor in a poor area and then become rich then you move away to a rich area. It\’s not entirely unknown for this to happen after all. So, our measurement of age of death in poor areas is not in fact measuring the age of death of those born there: it\’s measuring those who remained poor enough to stay living there. Thus we are underestimating the life span of someone born in a poor area as the long lived move away because of this rich/long lived thing.

Similarly, there could well be those who become poor and thus move from rich areas to poor areas. With our still assumption that the poor die younger than the rich we are therefore over-estimating the age at death of those born in rich areas: because those who become poor and die younger move away.

Now, as the Great Chris Dillow (pbuh) points out, there\’s an awful lot of things that are true but not all that important. These points are certainly true: the statistics do not adjust for them so there is some of this effect.

How much I\’ve no idea: and more to the point, no one else knows either. Because, at least as far as can be seen, no one at all is trying to adjust these statistics to account for them.

And then there\’s a much, much, more important point. When we go off and talk about health inequality, Marmot (and Danny Dorling) style. Yes, there most certainly is health inequality between poor and rich. However, the assumption made is that it\’s the poverty/richness which produces the health inequality.

I\’d not deny that this happens either. But as ever, there\’s another contrary effect as well. That health inequality produces poverty/wealth. Imagine two people, doing much the same work, nice middle class career type stuff. Married, two earner, couple of kids family, two professional earner perhaps, as associative mating is increasingly giving us.

So, in one case everything goes just like in the picture books. Solid (but not stellar) career, house onna mortgage etc. After 35/40 years, they\’re in the top 10% of families. They\’ve got that £850,000 of assets that qualifies, house, maybe holiday pad, decent pension plans (yes, this does count to the £850k), bit in ISAs etc. and everything is just lovely.

OK, same  basic set up but we throw in a chronic illness for one of the other of the couple at age, say, 35. You could posit divorce perhaps, or not as you prefer. But something debilitating, something career derailing. They ain\’t gonna make that top 10% any more. Not through any fault, just that one salary, reduced no doubt by time spent as a carer, just isn\’t going to achieve that transformation.

Now, we\’ve certainly got health inequality here. We\’ve also got economic inequality. But which has led to which? The economic inequality to the health inequality? Or the health inequality to the economic?

And that\’s where the problem is. The Marmot/Dorling assumption, thus the one used by absolutely everyone else, is that it is solely the economic which leads to the health. A position which we know absolutely is wrong and thus not one that we should be basing policy upon: but we are.

To point to a direct example on these \’ere intertubes. There will undoubtedly be wealth and income inequality as a result of this lady\’s illness. But the way the numbers are run it will be measured as that wealth or income inequality causing the health inequality. Something which simply isn\’t true, is it?

4 thoughts on “Please, please, try to understand the damn statistic”

  1. What about the inequality of opportunity for those born in endemic relatively poor areas to ‘get rich’ and move away?

  2. Arnald – What about [insert thing that is only tangentially related and does nothing to address Tim’s argument]?

  3. The causation vs correlation effect is indeed very relevant here – it makes just as much sense to say ‘the well are getting richer than the sick’…

    I wonder if medical advances have summat to do with it. Chronically ill people living longer have more time to become poor (relative to what their financial trajectory would be without illness), so when they die early it’s now ‘poor person dies fairly young’ not ‘rich person dies tragically young’ as it would be in the past.

    Arnald’s point isn’t irrelevant but it is just a second order effect. Acknowledging it means acknowledging the first order effect too!

    Btw isn’t it ‘assortive mating’ not ‘associative’?

  4. Extrapolation Fail.

    This is happening today therefore must be true in the future and always and forever.

    FFS Tim expect better of you.

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