Greenies are cheering as research finds that air pollution gives you diabetes-- but does it?

Some rather amusing "research" below.  In summary, the controls were inadequate and the effects minute. As a bonus, sea air was found not to be especially good for you.

Two major demographics that affect health generally are poverty and IQ.  Smart people live longer and poor people die younger.  So unless you take account of both, your results could be a result of one or both instead of the cause you think you are studying.  But data on both is pesky to gather so most medical research ignores both -- thus rendering the findings moot.

So how does that work out in studies of this sort?  I have said all this before but if medical researchers keep churning out rubbish, I guess I have to churn out rebuttals.

Nobody likes breathing in polluted air, unless you like the smell of diesel of course.  And both rich people and smart people (two seriously overlapping categories) can usually manage to avoid it one way or another -- by moving to nicer suburbs or choosing a rural lifestyle, for instance. Poor people can't usually afford that and dumb people are too busy trying to get by to worry about refinements.

 So if you are living in a polluted area you are more likely to be poor and dumb. So if a polluted locality seems to be  bad for your health, it could be because of the poor and dumb people who live there, not because of the pollution itself.  And the present research is a prime example of that.  They cannot rule out that their findings were an effect of poverty and IQ and not pollution.  If they had gathered IQ and income data for each person they studied, they could have removed the influence of income and IQ from their results statistically (analysis of covariance, partial correlation etc).

They did not even attempt to gather IQ data.  They did not even measure education, which is a rough proxy for IQ and which has effects in its own right.  And their attempt to measure income was pathetic.  They looked at the percentage of poor people in the county where you lived and assigned that score as YOUR degree of poverty. That you can have both rich and poor people both living in the same county was ignored.

OK:  That's only one problem with the study.  The other problem -- regrettably common in these studies -- was the size of the effects they found.  They were tiny.  Their hazard ratio for the effect of pollution on diabetes was only 1.15.  Causative inferences normally require a HR of 2.0 or more.  To put that finding into context, compare the finding for the effect of "ambient air sodium concentration" (which I take to mean "sea-air") on diabetes.  They found a HR of 1.00, which they identified as non-significant, meaning no effect.  Yet 1.00 is only a touch behind the 1.15 ratio that the whole article is built on.  So you can summarize the study in one word:

Bullshit.

Regrettably non-academic language, I know.  But when is this nonsense about air pollution going to stop? It's just the same mistakes repeated over and over again.  Lancet should not have published such weak stuff but they are as Green as grass so they were upholding a Greenie cause.

As you have perhaps already guessed, I am feeling a bit peevish at the moment so let me expand my comments about British medical journals.  Both Lancet and BMJ seem to be edited by kneejerk Leftists who are incapable of independent thought. I forget which one but either Lancet or BMJ published a critical article at one stage about George Bush's invasion of Iraq. Strange territory for a medical journal! They went well outside their area of expertise and their article was in consequence an heroic example of inferential boldness -- which I and others promptly pointed out.  It is too sad that Leftist bigotry has now infiltrated the medical journals.  The effect on the quality of their articles is only too well shown by the article critiqued here

Inferential boldness does in fact seem to infect medical journals across the board. The basic statistical dictum that correlation is not causation seems to be some sort of Masonic secret to their editors and authors:  Poorly controlled articles that treat correlation as causation are common.  Every time it is examined, poverty is found to have strong health correlations but there are nonetheless untold numbers of articles that fail to control for income.  One understands that asking about income is a sensitive matter but there is usually no point in doing your study unless you do.  Doing almost any health study of humans without controlling for income simply renders moot the implication of your findings

I follow the popular article below with the journal abstract

Around one in seven cases of the disease were directly caused by air pollution around the world in 2016 – about 3.2million cases in total.

Researchers say the link is ‘significant’ even for low levels of air pollution which are considered to be safe.

The study is the first to estimate the number of diabetes cases caused by pollution globally.

Although type 2 diabetes is mainly thought to be caused by obesity, several recent studies have linked it to air pollution.

Experts believe tiny particles in the air reduce the body’s ability to respond to the hormone insulin, known as ‘insulin resistance’.

This causes the glucose levels in the blood to increase which can lead to type 2 diabetes.

Researchers from the Washington University School of Medicine in St Louis, Missouri, looked at data from 1.7million US veterans who were followed for eight and a half years.

They found the risk of developing type 2 diabetes went up 10 per cent for every 10 microgram per cubic metre increase in fine particulate matter in the air.

The study, published in the journal Lancet Planetary Health, also estimated 8.2million years of healthy life were lost around the world in 2016 due to pollution-linked diabetes.

Dr Ziyad Al-Aly, from Washington University, said: ‘Our research shows a significant link between air pollution and diabetes globally. We found an increased risk, even at low levels of air pollution currently considered safe by the US Environmental Protection Agency and the World Health Organisation.

‘Evidence shows that current levels are still not sufficiently safe and need to be tightened.’

The findings are particularly worrying as many areas in the UK have very high levels of air pollution which breach safe limits. Figures from the World Health Organisation last month showed 30 towns and cities have levels of fine particulate matter above the recommended limit of 10 micrograms per cubic metre.

SOURCE


The 2016 global and national burden of diabetes mellitus attributable to PM2·5 air pollution

Benjamin Bowe, MPH et al.

Summary

Background:
PM2·5 air pollution is associated with increased risk of diabetes; however, a knowledge gap exists to further define and quantify the burden of diabetes attributable to PM2·5 air pollution. Therefore, we aimed to define the relationship between PM2·5 and diabetes. We also aimed to characterise an integrated exposure response function and to provide a quantitative estimate of the global and national burden of diabetes attributable to PM2·5.

Methods:
We did a longitudinal cohort study of the association of PM2·5 with diabetes. We built a cohort of US veterans with no previous history of diabetes from various databases. Participants were followed up for a median of 8·5 years, we and used survival models to examine the association between PM2·5 and the risk of diabetes. All models were adjusted for sociodemographic and health characteristics. We tested a positive outcome control (ie, risk of all-cause mortality), negative exposure control (ie, ambient air sodium concentrations), and a negative outcome control (ie, risk of lower limb fracture). Data for the models were reported as hazard ratios (HRs) and 95% CIs. Additionally, we reviewed studies of PM2·5 and the risk of diabetes, and used the estimates to build a non-linear integrated exposure response function to characterise the relationship across all concentrations of PM2·5 exposure. We included studies into the building of the integrated exposure response function if they scored at least a four on the Newcastle-Ottawa Quality Assessment Scale and were only included if the outcome was type 2 diabetes or all types of diabetes. Finally, we used the Global Burden of Disease study data and methodologies to estimate the attributable burden of disease (ABD) and disability-adjusted life-years (DALYs) of diabetes attributable to PM2·5 air pollution globally and in 194 countries and territories.

Findings:
We examined the relationship of PM2·5 and the risk of incident diabetes in a longitudinal cohort of 1 729 108 participants followed up for a median of 8·5 years (IQR 8·1–8·8). In adjusted models, a 10 μg/m3 increase in PM2·5 was associated with increased risk of diabetes (HR 1·15, 95% CI 1·08–1·22). PM2·5 was associated with increased risk of death as the positive outcome control (HR 1·08, 95% CI 1·03–1·13), but not with lower limb fracture as the negative outcome control (1·00, 0·91–1·09). An IQR increase (0·045 μg/m3) in ambient air sodium concentration as the negative exposure control exhibited no significant association with the risk of diabetes (HR 1·00, 95% CI 0·99–1·00). An integrated exposure response function showed that the risk of diabetes increased substantially above 2·4 μg/m3, and then exhibited a more moderate increase at concentrations above 10 μg/m3. Globally, ambient PM2·5 contributed to about 3·2 million (95% uncertainty interval [UI] 2·2–3·8) incident cases of diabetes, about 8·2 million (95% UI 5·8–11·0) DALYs caused by diabetes, and 206 105 (95% UI 153 408–259 119) deaths from diabetes attributable to PM2·5 exposure. The burden varied substantially among geographies and was more heavily skewed towards low-income and lower-to-middle-income countries.

Interpretation:
The global toll of diabetes attributable to PM2·5 air pollution is significant. Reduction in exposure will yield substantial health benefits.