From John Ray's shorter notes


That wicked air pollution again: Veterans study

The article below is a riot of statistics but one thing it sedulously avoids is any mention of effect sizes. The effect size in other studies of this topic is usually negligible so that may tell you why.

None of the previous studies of this topic are exactly comparable but some of them have been pretty powerful. For instance, a 2018 study included the entire Medicare population from January 1, 2000, to December 31, 2012. And their finding that only one in a million people die from particulate air pollution is pretty decisive. If you bother about that tiny risk, you should never get out of bed.

In the present study, even a probability statistic or two would have been of some help, though the large sample size would show just about any effect as statistically significant.  The text of the article does imply that effect size statistics can be found in the supplementary material but when I clicked on the heading of the relevant table there nothing happened.  Very suspicious.

There are however some indications that the effects were very weak. The authors' reliance on inter-quartile ranges is characteristic of what you do when there is no overall significance in the data. And take the sentence below:

"PM2.5 exposure was associated with excess burden of death due to cardiovascular disease (56070.1 deaths [95% uncertainty interval {UI}, 51940.2-60318.3 deaths])"

As far as I can work out the number of deaths was just about in the middle of the uncertainty interval, again suggesting that nothing much was going on. One hopes that the authors provide some real and accessible statistics about effect size soon.

The big hole in studies of this topic is failure to take account of income.  Poor people commonly have much worse health and unless income is controlled for you may be simply seeing the effects of poverty, not what you think you are seeing.

To their credit, the authors did use an expansive demographic statistic to provide some sort of control on their results.  But their procedure there was rather brain-dead -- or perhaps the procedure of someone who doesn't really want to deal with demographics.  They created an Area Deprivation Index (ADI), which ranks geographic locations by socioeconomic status disadvantage and is composed of education, employment, housing quality, and poverty measures.

One wonder exactly what "poverty measures" were.  Nothing as simple as individual income, it would seem.  And that was it:  No attempt to control for individual poverty.

So even if the ADI index was well done, that is not the end of the story. Using the characteristics of an area as a proxy for individual characteristics is quite desperate.  Any one area will include a considerable demographic range.  A poor person living in a rich are will be characterized as rich -- which is madness.

So once again the study founders on the rock of a failure to control for income.  The illnesses observed might have been effects of poverty, not air pollution.  For a variety of reasons, poor people are more exposed to air pollution, something this study does concede

And at risk of killing a dead horse, the pollution measures were also area statistics rather than individual statistics.  That assumes that everyone living in the same area breathes in the same amount of pollution.  I hope I don't have to give reasons why that may not be so

But air pollution SHOULD be bad for you, someone will say.  It probably is -- at some level. But is the level normally encountered in American cities bad for you?  That is what no-one so far has been able to establish reliably.

Given our evolutionary history of sitting around campfires for perhaps a million years, one would expect that evolution would have given us a substantial tolerance of inhaled air pollution.  That is probably what is actually revealed in studies like the present one

Burden of Cause-Specific Mortality Associated With PM2.5 Air Pollution in the United States

Benjamin Bowe et al.


Importance:  Ambient fine particulate matter (PM2.5) air pollution is associated with increased risk of several causes of death. However, epidemiologic evidence suggests that current knowledge does not comprehensively capture all causes of death associated with PM2.5 exposure.

Objective:  To systematically identify causes of death associated with PM2.5 pollution and estimate the burden of death for each cause in the United States.

Design, Setting, and Participants:  In a cohort study of US veterans followed up between 2006 and 2016, ensemble modeling was used to identify and characterize morphology of the association between PM2.5 and causes of death. Burden of death associated with PM2.5 exposure in the contiguous United States and for each state was then estimated by application of estimated risk functions to county-level PM2.5 estimates from the US Environmental Protection Agency and cause-specific death rate data from the Centers for Disease Control and Prevention.

Main Outcomes and Measures:  Nonlinear exposure-response functions of the association between PM2.5 and causes of death and burden of death associated with PM2.5.

Exposures:  Annual mean PM2.5 levels.

Results:  A cohort of 4?522?160 US veterans (4?243?462 [93.8%] male; median [interquartile range] age, 64.1 [55.7-75.5] years; 3?702?942 [82.0%] white, 667?550 [14.8%] black, and 145?593 [3.2%] other race) was followed up for a median (interquartile range) of 10.0 (6.8-10.2) years. In the contiguous United States, PM2.5 exposure was associated with excess burden of death due to cardiovascular disease (56?070.1 deaths [95% uncertainty interval {UI}, 51?940.2-60?318.3 deaths]), cerebrovascular disease (40?466.1 deaths [95% UI, 21?770.1-46?487.9 deaths]), chronic kidney disease (7175.2 deaths [95% UI, 5910.2-8371.9 deaths]), chronic obstructive pulmonary disease (645.7 deaths [95% UI, 300.2-2490.9 deaths]), dementia (19?851.5 deaths [95% UI, 14?420.6-31?621.4 deaths]), type 2 diabetes (501.3 deaths [95% UI, 447.5-561.1 deaths]), hypertension (30?696.9 deaths [95% UI, 27?518.1-33?881.9 deaths]), lung cancer (17?545.3 deaths [95% UI, 15?055.3-20?464.5 deaths]), and pneumonia (8854.9 deaths [95% UI, 7696.2-10?710.6 deaths]). Burden exhibited substantial geographic variation. Estimated burden of death due to nonaccidental causes was 197?905.1 deaths (95% UI, 183?463.3-213?644.9 deaths); mean age-standardized death rates (per 100?000) due to nonaccidental causes were higher among black individuals (55.2 [95% UI, 50.5-60.6]) than nonblack individuals (51.0 [95% UI, 46.4-56.1]) and higher among those living in counties with high (65.3 [95% UI, 56.2-75.4]) vs low (46.1 [95% UI, 42.3-50.4]) socioeconomic deprivation; 99.0% of the burden of death due to nonaccidental causes was associated with PM2.5 levels below standards set by the US Environmental Protection Agency.

Conclusions and Relevance:  In this study, 9 causes of death were associated with PM2.5 exposure. The burden of death associated with PM2.5 was disproportionally borne by black individuals and socioeconomically disadvantaged communities. Effort toward cleaner air might reduce the burden of PM2.5-associated deaths.

JAMA Netw Open. 2019;2(11):e1915834. doi:10.1001/jamanetworkopen.2019.15834

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