UPDATE: Dr. Monnat has left a comment pointing out that I made a major error in reading her methods (I assumed she used non-standardized rates but in the methods she specifies that she did). So I have removed one criticism of her paper and modified another about regression. This doesn’t change the thrust of my argument (though if Dr. Monnat is patient enough to engage with more of my criticisms, maybe it will!)

Since late 2016 a theory has been circulating that Donald Trump’s election victory can be related to the opioid epidemic in rust belt America. Under this theory, parts of mid-West America with high levels of unemployment and economic dislocation that are experiencing high levels of opioid addiction switched votes from Democrat to Republican and elected Trump. This is part of a broader idea that America is suffering an epidemic of “deaths of despair” – deaths due to opioids, suicide and alcohol abuse – that are part of a newfound social problem primarily afflicting working class white people, and the recent rapid growth in the rate of these “deaths of despair” drove a rebellion against the Democrats, and towards Trump.

This theory is bullshit, for a lot of reasons, and in this post I want to talk about why. To be clear, it’s not just a bit wrong: it’s wrong in all of its particulars. The data doesn’t support the idea of a growing death rate amongst white working class people; the data does not support a link between “deaths of despair” and Trump voting; there is no such thing as a “death of despair”; and there is no viable explanation for why an epidemic of “deaths of despair” should drive votes for Trump. The theory is attractive to a certain kind of theorist because it enables them to pretend that the Trump phenomenon doesn’t represent a deep problem of racism in American society, but it doesn’t work. Let’s look at why.

The myth of rising white mortality

First let’s consider the central framework of this story, which is the idea that mortality rates have been rising rapidly among middle-aged whites in America over the past 20 years, popularized by two economists (Case and Deaton) in a paper in PNAS. This paper is deeply flawed because it does not adjust for age, which has been increasing rapidly among white Americans but not non-white Americans (due to differential birth and migration patterns in earlier eras). Case and Deaton studied mortality in 45-54 year old Americans, differentiating by race, but failed to adjust for age. This is important for surprising reasons, which perhaps only epidemiologists understand, and we’re only figuring this out recently and slowly: ageing is happening so fast in high-income countries that even when we look at relatively narrow age categories we need to take into account the possibility that the older parts of the age category have a lot more people than the younger parts, and this means that even the small differences in mortality between say 53 year olds and 45 year olds can make a difference to mortality rates in the age category as a whole. If this seems shocking, consider the case of Japan, where ageing is so advanced that even five year age categories (the finest band of age that most statistical organizations will present publicly) are vulnerable to differences in the population. In Japan, the difference in the size of the 84 year old population to the 80 year old population is so great that we may need to adjust for age even when looking at narrow age categories like 80-84 years. This problem is a new challenge for epidemiologists – we used to assume that if you reduce an analysis to a 10 or 15 year age category you don’t need to standardize, because the population within such a band is relatively stable, but this is no longer true.

In the case of the Case and Deaton study the effect of ageing in non-hispanic white populations is so great that failure to adjust for it completely biases their results. Andrew Gelman describes the problem  on his blog and presents age-adjusted data and data for individual years of age, showing fairly convincingly that the entire driver of the “problem” identified by Case and Deaton is age, not ill health. After adjustment it does appear that some categories of white women are seeing an increasing mortality rate, but this is a) likely due to the recent growth of smoking in this population and b) not a likely explanation for Trump’s success, since he was more popular with men than women.

White people are dying more in America because they’re getting older, not because they have a problem. I happen to think that getting older is a problem, but it’s not a problem that Trump or anyone else can fix.

The myth of “deaths of despair” and Trump voting

Case and Deaton followed up their paper on white mortality with further research on “deaths of despair” – deaths due to opioid abuse, suicide and alcohol use that are supposedly due to “despair”. This paper is a better, more exhaustive analysis of the problem but it is vulnerable to a lot of basic epidemiological errors, and the overall theory is ignorant of basic principles in drug and alcohol theory and suicide research. This new research does not properly adjust for age in narrow age groups, and it does not take into account socioeconomic influences on mortality due to these conditions. But on this topic Case and Deaton are not the main offenders – they did not posit a link between “deaths of despair” and Trump voting, which was added by a researcher called Shannon Monnat at Pennsylvania State University in late 2016. In her paper, Monnat argues for a direct link between rates of “deaths of despair” and voting for Trump at the county level, suggesting that voting for Trump was somehow a response to the specific pressures affecting white Americans. There are huge flaws in this paper, which I list here, approximately in their order of importance.

  • It includes suicide: Obviously a county with high suicide mortality is in a horrible situation, which should be dealt with, but there is a big problem with using suicide as a predictor of Trump voting. This problem is guns. Uniquely among rich countries, the US has a very high prevalence of gun ownership and guns account for a much larger proportion of suicides in America than elsewhere – more than half, according to reputable studies. And unfortunately for rural Americans, the single biggest determinant of whether you commit suicide by gun is owning a gun – and gun ownership rates are much higher in counties that vote Republican. In America suicide is a proxy for gun ownership, not “despair”, and because gun-related suicide depends heavily on rates of gun ownership, inclusion of this mortality rate in the study heavily biases the total mortality rate being used towards a measure of gun ownership rather than despair.
  • It uses voting changes rather than voting odds: Like most studies of voting rates, Monnat compared the percentage voting for Trump with the percentage voting for Romney in 2012. This is a big flaw, because percentages do not vary evenly across their range. In Monnat’s study a county that increased its Republican voting proportion from 1% to 2% is treated exactly the same as a county that went from 50% to 51%. In one of these counties the vote doubled and Trump didn’t get elected; in the other it increased by 2% but Trump got elected. It’s important to account for this non linearity in analysis, but Monnat did not. Which leads to another problem …
  • It did not measure Trump’s success directly: In a first past the post electoral system, who wins is more important than by how much. Monnat used an ordinary least squares model of proportions voting Trump rather than a binomial model of Trump winning or losing, which means that meaningless small gains in “blue” states[1] had the same importance as small gains in “red” states that flipped them “blue”. This might not be important except that we know Trump lost the popular vote (which differences in proportions measure) but won the electoral college (which more closely resembles binary measures of win/lose). Not analyzing binary outcomes in a binomial model suggests you don’t understand the relationship between statistics and the political system you live in, i.e. your analysis is wrong.
  • It did not incorporate turnout: A 52% win for Trump can reflect two things – a change in attitude by 2% of the voters, or a non-proportionate increase in the number of people who chose to turn out and vote. If you analyze proportions (or differences in proportions) you don’t account for this problem. In addition, you don’t adjust for the overall size of the electorate. If you analyze proportions, an electorate where 52 people voted Trump and 48 people voted Clinton is given the same weight as an electorate where 5200 people voted Clinton and 4800 people voted Trump. If you use a proper binomial model, however, the latter electorate gets more weight and is implicitly treated as more meaningful in the assessment of results. A reminder of what is fast becoming a faustusnotes rule: the cool kids do not use ordinary least squares regression to analyze probabilities, we always use logistic regression.
  • It did not present the regression results: Although Monnat reports regression results in a footnote, the main results in the text are all unadjusted, even though in at least some states the impact of economic factors appears to eliminate the relationship with mortality rates. Given that people who own guns are much much more likely to vote Republican, and the main predictor variable here incorporated suicide, adjustment for gun ownership might have eliminated the effect of “deaths of despair” entirely. But it wasn’t done as far as I can tell, and wasn’t shown.
  • It did not adjust for trends: Monnat openly states in the beginning of the paper that “deaths of despair” have been rising over time but when she conducts the analysis she uses the average rate for the period 2006-2014. This means that she does not consider the possibility that mortality has been dropping in some counties and rising in others. A mortality rate of 100 per 100,000 could reflect a decline over the period 2006-2014 from 150 to 50 (a huge decrease) or an increase from 25 to 175. We don’t know, but it seems likely that if “deaths of despair” is an issue, it will have had more influence on electoral decisions in 2016 in counties where the rate has risen over that time than where it has declined. There are lots of policy reasons why the death rate might have increased or decreased, but whether these reflect issues relevant to Republican or Democrat policy is impossible to know without seeing the distribution of trends – which Monnat did not analyze[2].

So in summary the study that found this “relationship” between “deaths of despair” and voting Trump was deeply flawed. There is no such relationship in the data[3].

There is no such thing as a “death of despair”

This study has got a fair bit of attention on the internet, as have the prior Case and Deaton studies. For example here we see a Medium report on the “Oxy electorate” that repeats all these sour talking points, and in this blog post some dude who fancies himself a spokesperson for ordinary America talks up the same issue. The latter blog post has some comments by people taking oxycontin for pain relief, who make some important points that the “deaths of despair” crew have overlooked. To quote one commenter[4]:

I too am a long time chronic pain sufferer and until I was put on opiate medications my quality of life was ZERO. I’ve heard horror stories of people actually being suicidal because they can no longer deal with the constant pain. It took me two years before I realized I could no longer work as an account manager with a major telecom company. I was making decent money but leaving work everyday in pain. I finally started going to a pain management doctor who diagnosed me with degenerative disc disease. I had to go on medical leave and now am on SSDI. My doctor prescribed me opiates in the fall of 2006 and I’ve been on them ever since. I have to say, I totally AGREE with you. I don’t know how I would be able to manage without these medications. At least I’m able to clean my house now and now without being in horrible pain. I don’t know what I would do if suddenly I was told I could no longer be prescribed opiates.
Who is someone that will champion those of us who legitametly need these medications? Do we write to our senators?? I sure hope Trump takes into consideration our cases before kicking us all to the curb!

This person (and others) make the valid point that they are taking pain medication for a reason, and that they were in despair before they got hooked on opioids, not after. Unfortunately for these commenters, we now have fairly good evidence that opioids are not the best treatment for chronic pain and that they are very, very dangerous, but regardless of whether this treatment is exactly the best one for these patients they make the valid point that it is the treatment they got and it works for them. To use an Americanism, you can take the opioids from their cold dead hands. In stark contrast to other countries, a very large proportion of America’s opioid deaths are due to prescription drugs, not heroin, reflecting an epidemic of overdose due to legally accessible painkillers. It’s my suspicion that these painkillers were prescribed to people like the above commenter because they could not afford the treatment for the underlying cause of their pain, because America’s healthcare system sucks, and these people then became addicted to a very dangerous substance – but in the absence of proper health insurance these people cannot get the specialist opioid management they deserve. America’s opioid epidemic is a consequence of poor health system access, not “despair”, and if Americans had the same health system as, say, Frenchies or Britons they would not be taking these drugs for more than 6 months, because the underlying cause of their condition would have been treated – and for that small minority of pain patients with chronic pain, in any other rich country they would have regular affordable access to a specialist who could calibrate their dose and manage their risks.

The opioid death problem in America is a problem of access to healthcare, which should have been fixed by Obamacare. Which brings us to the last issue …

There is no theory linking opioid addiction to voting Trump

What exactly is the theory by which people hooked on oxycontin are more likely to vote Trump? On its face there are only two realistic explanations for this theory: 1) the areas where oxycontin is a huge problem are facing social devastation with no solution in sight, so vote for change (even Trump!) in hopes of a solution; or 2) people who use drugs are arseholes and losers. Putting aside the obvious ecological fallacy in Monnat’s study (it could be that everyone in the area who votes for Trump is a non-opiate user, and they voted Trump in hopes of getting the druggies killed Duterte-style, but the data doesn’t tell us who voted Trump, just what proportion of each area did), there are big problems with these two explanations even at the individual level. Let’s deal with each in turn.

If areas facing social devastation due to oxycontin are more likely to vote Trump, why didn’t they also vote Romney? Some of these areas were stronger Obama voters in 2012, according to Monnat’s data, but opioid use has been skyrocketing in these areas since 2006 (remember Monnat used averages from 2006-2014). The mortality data covers two election cycles where they voted Obama even though opioid deaths were rising, and suddenly they voted Trump? Why now? Why Trump and not Romney, or McCain? It’s as if there is something else about Trump …

Of course it’s possible that oxycontin users are racist arseholes – I have certainly seen this in my time working in clinics providing healthcare to injecting drug users – but even if we accept such a bleak view of drug users (and it’s not true!) the problem with this theory is that even as opioid use increases, it remains a tiny proportion of the total population of these areas. The opioid users directly cannot swing the election – it has to be their neighbours, friends and family. Now it’s possible that a high prevalence of opioid use and suicide drives people seeing this phenomenon to vote Trump but this is a strange outcome – in general people vote for Democrats/Labour in times of social catastrophe, which is why they voted Obama to start with – because he promised to fix the financial crisis and health care. There has to be some other explanation for why non-opioid using people switched vote in droves to Trump but not Romney. I wonder what it could be?

American liberals’ desperate desire to believe their country is not deeply racist

The problem is, of course, that Trump had a single distinguishing feature that no one before him in the GOP had – he was uniquely, floridly racist. Since the election this has become abundantly clear, but for Donnat writing in late 2016 I guess it still seemed vaguely plausibly deniable. But the reality is that his single distinction from all other GOP candidates was his florid racism. Lots of people in America want to believe that the country they live in – the country that just 150 years ago went to war over slavery, and just 50 years ago had explicit laws to drive black people out of the economic life of the nation – is not racist. I have even recently seen news reports that America is “losing its leadership in the movement for racial equality.” No, dudes, you never showed any leadership on that front. America is a deeply racist nation. It’s racist in a way that other countries can’t even begin to understand. The reason Trump won is that he energized a racist base, and the reason his approval remains greater than 30% despite the shitshow he is presiding over is that a large number of Americans are out-and-out fascists, for whom trolling “liberals” and crushing non-whites is a good thing. That’s why rural, gun-owning Americans voted for Trump, and if the data were analyzed properly that fact would be very clear. Lots of people in America want to believe second- or third-order causes like the rustbelt or opioids, but the reality is staring them in the face: it’s racism. Don’t blame people with chronic pain, blame people with chronic racism. And fix it, before the entire world has to pay for the vainglorious passions of a narrow swathe of white America.

fn1: I refuse to take the American use of “blue” and “red” seriously – they get scare quotes until they decide that Republicans are blue and Democrats are red. Sorry, but you guys need to sort your shit out. Get proper political colours and get rid of American Football, then you’ll be taken seriously on the world stage. Also learn to spell color with a “u”.

fn2: I’m joshing you here. Everyone knows that Republicans don’t give a flying fuck if an electorate is dying of opioid overdoses at a skyrocketing rate, and everyone knows that the idea that Republicans would offer people dying of “deaths of despair” any policy solutions to their problem except “be born rich” is a hilarious joke. The only possible policy intervention that could have helped counties seeing an increasing opioid death rate was Obamacare’s Medicaid expansion, and we know republicans rejected that in states they controlled because they’re evil.

fn3: Well, there might be, but no one has shown it with a robust method.

fn4: I’m such a cynic about everything American that I really hope this commenter isn’t a drug company plant…

Reports have been filtering out recently of a study that found a relationship between US unemployment rates and deaths due to opioid use. The Washington Post reported on these results, suggesting that there is a connection between unemployment and death due to “diseases of despair” (their words), and citing the unfortunate Case and Deaton study that found increasing mortality rates among non-hispanic whites in the USA. The implication is that some kind of post-2008 economic depression-related despair has driven the white working class to drugs, with an attendant high death toll. This is particularly poignant in light of the recent election, since some of the states (like West Virginia) that voted heavily for Trump are also heavily affected by opioid abuse. The implication here is that the economic despair supposedly driving Trump voting is also driving high mortality in these communities, which have also supposedly been hollowed out by globalization, immigration and Democratic neglect (only Democrats can neglect poor white people; Republicans ride in to save them with trickle down economics while Democrats abandon them for groovy inner-city Black Lives Matter activists and funky Chicago law professors). But is any of this true?

The news reports are based on the findings of a study by Hollingsworth, Ruhm and Simon, Macroeconomic conditions and opioid abuse, published in my bete-noir, the National Bureau of Economic Research (NBER) working papers series. This is where economists publish their brain farts before they are shot down in peer review, and this paper is a typical economist brain fart. This study suffers from the usual problems of NBER papers: it has a ludicrous model, uses the wrong modeling approach, does some dubious data manipulation, and probably isn’t representative. Worse still, the study is based on a failed and useless model of drug addiction that eschews a balanced understanding of drug addiction in favour of a lazy just-so story about the causes of drug addiction that has no basis in reality. I will briefly discuss the modeling problems that make this study useless, and then discuss in more detail the problem of its underlying theoretical structure.

Modeling problems with the study

The study is a classic example of how economists just cannot handle data well. First, the authors have presented a ludicrous model which has an enormous number of explanatory variables – one for every county in their data set, one for every year, and an additional term for the combination of states and years – which means that the model has a huge number of terms to be estimated. Worse still, they do not include age or sex in the model, so they don’t adjust at all for differences in age structure between different counties and states or ethnic groups. Non-heroin opioid addiction in the USA seems to be clustered in rural whites, and probably reflects addiction pursuant to pain relief for real health problems. If so the problem is likely more prevalent in older groups (which have higher levels of chronic pain) who may well be more vulnerable to early death – so adjustment for age is important in these studies. The authors find mortality rates in whites increasing much faster than blacks or hispanics but this could well be because these groups are younger and thus earlier into their drug addiction, or simply less likely to die. This complexity is further compounded by the authors decision to impute drug types to drug-related deaths where the drug is not specified – they simply statistically estimate what drug caused the death, which makes all their results highly vulnerable to the quality of the model by which they impute 30% of all drug-related deaths. So the authors have estimated a model with a huge number of terms and have not properly adjusted for the age structure of the population. This is extremely important, since the CDC has shown that opioid-related mortality is much higher in older people, and if areas with many old people also have high unemployment there will be a spurious relationship between unemployment and mortality if age is not adjusted for.

Incidentally, this paper gives completely different crude opioid mortality rates to the CDC, probably because it uses a subset of states with unusually high mortality rates. So there is a huge generalizability problem right there.

The other big problem with the model is that, of course, being economists, the authors do not use the correct modeling approach. Opioid mortality is a rare even with very small numbers of deaths when disaggregated by race at the county level – even the authors admit that many of their data points have zero deaths – but the authors have chosen to divide the counts of mortality by the population of the area, to get crude rates, and then to model these using ordinary least squares linear regression. As I have repeatedly said here, OLS regression is completely the wrong method to use on data that is constrained. In this case the data is constrained to be greater than or equal to zero, and is likely very close to zero in most cases. OLS regression assumes a completely different probability structure to the correct method, Poisson regression, and applying OLS regression to rates means that you are assuming all zero rates have the same probability. In contrast, a Poisson regression adjusted for population size models a zero count with a different probability depending on the population size, so a zero event in a large population has a different meaning to a zero event in a small population. It also models a non-linear relationship between the underlying death rate and the unemployment rate, which is crucial to understanding how the underlying death rate is related to unemployment. By not using a Poisson regression for rare events the authors have mushed together a bunch of very different mortality patterns as if they were all the same, and completely changed the nature of the relationship between unemployment and mortality.

Big no no!

So the modeling is completely flawed, but this isn’t the worst part of this study. The worst part of this study is that the underlying theory is completely flawed.

Opioid use is not a disease of despair

The fundamental problem with this model is the assumption that macroeconomic conditions drive opioid use. Figure 1 shows the observed and modeled number of monthly deaths due to heroin overdose in New South Wales, Australia between 1995 and 2003, taken from Degenhardt and Day, Impact of the Heroin Shortage: Additional Research (I prepared this figure for this technical report).

Figure 1: Monthly observed and modeled heroin overdose deaths in New South Wales, 1995-2003

This figure shows a clear rapid peak occurring in 1999, followed by a gradual decline and then a sudden downward step in January 2001. This downward step is even more evident in heroin possession offences (Figure 2, also prepared by me, from Gilmour et al, Using intervention time series analysis to assess the effects of imperfectly identifiable natural events: A general method and example, BMC Medical Research Methodology 2006; 6:16).

Figure 2: Observed and modeled trend in heroin possession offences in New South Wales, 1995-2003

Is it really conceivable that trends in unemployment were so intense over the 8 years of this data series that they caused heroin possession offences to more than double, and heroin mortality to double, within 2 years, and to then decline by 50% before halving in one month? What are the macroeconomic effects driving this phenomenon? In fact youth unemployment in NSW declined consistently over the 1990s, and was at a historic low when heroin mortality peaked. What changed over the 1990s was the availability of heroin, which was flooding the market in the mid-1990s; and what changed in 2001 was that new models of drug interdiction and cooperation between police agencies led to unprecedented success in fighting drug traffickers, so that in the early ’00s they pulled out of Australia in favour of easier targets. The result was a sudden precipitous decline in heroin availability, a massive increase in cost, a temporary increase in street-based sex work and cocaine use, and a rapid flight of young people from the market. This occurred against a backdrop of readily available harm reduction services and widespread, free methadone treatment, to which many drug users fled when the price skyrocketed.

The reality is that drug addiction patterns are driven primarily by availability of the drug and availability of treatments for drug addiction. Far from being a “disease of despair” as the Washington Post described it, with patterns of use determined by social dislocation and poverty, heroin addiction is a disease of opportunity, driven primarily by the presence of the drug, its ease of use, and the economic potential to purchase it. There is no relationship between drug use and unemployment or poverty, and we have known this since Robin Lee did her groundbreaking work on returning heroin addicts after the Vietnam war. I suspect the truth of the American opioid epidemic is much more boring, and much more difficult to explain, than unemployment: It is a problem of availability. I don’t know what causes that problem but my guess is that sometime in the 2000s legislative changes made opioids much more easily available. In 2003 the Medicare Prescription Act was passed, and my guess is that it made it much easier for middle-aged poor people to get access to pain relief – pain relief they desperately needed for a wide array of real problems. With access to affordable opiates but with no corresponding access to specialist pain management professionals a cohort of middle-aged workers became addicted to opioids, and in the subsequent 10 years they started dying. It’s a boring health policy explanation for a terrible problem, and it can only be fixed by improvements in quality of care, access to specialists, and careful attention to modern strategies for pain relief.

Unfortunately this story doesn’t fit with a narrative – popular on left and right – of drug addiction as a disease of despair. In this narrative the left sees drug addiction as a product of an alienating and destructive society, best solved by improvements in welfare and labour rights, while the right sees drug addiction as a consequence of unemployment and poverty, which are best solved by getting everyone into work (since good welfare programs are anathema to the right). For economists both of these stories show the primacy of economics as a driver of social problems, and make a good just so story. But the reality of opioid addiction is that it is a complex health policy problem best solved by careful attention to the way that opioids are dispensed and pain is managed. True, this policy prescription requires potentially quite radical changes in the way that doctors approach chronic illness, poverty and occupational health – but it’s completely boring outside of health policy. Stories of a “generation left behind”, forced to vote for Trump because of the carnage sweeping through their blighted communities, are much more interesting than “oh yeah, we made dangerous drugs cheaper and didn’t train doctors how to manage them.”

This article and the interest it drove are another example of two pernicious problems in modern debate: economists can’t be trusted with health data, and journalists are too quick to believe economists. When this is tied with a problem that is easily amenable to sensationalism and patronizing assumptions, of course you get a narrative that is completely divorced from the truth. In this case we don’t know what the truth of the numbers is, since the economists in question made a model so bad it has no bearing on the truth; and we were led into believing that this model could ever explain the very real problems facing these communities by credulous economists and journalists all too willing to believe lazy stereotypes about drug users and drug use.

Let’s score that as another failure for two of the worst professions, and hope we can make some real changes to prescription laws and pain management so that the people affected by this problem can find better, safer ways of managing their chronic pain. And please, please please, can economists please stop touching health data until they learn a method other than OLS regression?



This week’s New England Journal of Medicine reports on the relationship between coffee drinking and mortality in a cohort study of Americans. The study followed

229,119 men and 173,141 women in the National Institutes of Health–AARP Diet and Health Study who were 50 to 71 years of age at baseline

and this paper reports on their coffee drinking habits. Its main finding (my emphasis):

During 5,148,760 person-years of follow-up between 1995 and 2008, a total of 33,731 men and 18,784 women died. In age-adjusted models, the risk of death was increased among coffee drinkers. However, coffee drinkers were also more likely to smoke, and, after adjustment for tobacco-smoking status and other potential confounders, there was a significant inverse association between coffee consumption and mortality.

This is why we do confounder adjustment … so I can slurp down another black coffee in complete peace of mind. And check the details:

Adjusted hazard ratios for death among men who drank coffee as compared with those who did not were as follows: 0.99 (95% confidence interval [CI], 0.95 to 1.04) for drinking less than 1 cup per day, 0.94 (95% CI, 0.90 to 0.99) for 1 cup, 0.90 (95% CI, 0.86 to 0.93) for 2 or 3 cups, 0.88 (95% CI, 0.84 to 0.93) for 4 or 5 cups, and 0.90 (95% CI, 0.85 to 0.96) for 6 or more cups of coffee per day (P<0.001 for trend); the respective hazard ratios among women were 1.01 (95% CI, 0.96 to 1.07), 0.95 (95% CI, 0.90 to 1.01), 0.87 (95% CI, 0.83 to 0.92), 0.84 (95% CI, 0.79 to 0.90), and 0.85 (95% CI, 0.78 to 0.93) (P<0.001 for trend).

If we’re going on an American coffee standard, I’d say I’m drinking 6 or more cups of coffee per day, so I have a 10% reduced risk of mortality over 15 years (the rough period of the study). Sadly, though, I’m not protected against cancer:

Inverse associations were observed for deaths due to heart disease, respiratory disease, stroke, injuries and accidents, diabetes, and infections, but not for deaths due to cancer.

The effect was also observed in non-smokers (that’s me!)

So, the word is in from the world’s top medical journal: the more coffee you drink, the longer you live!

Primo Levi’s The Truce is a beautiful book that contains many insights into the human condition. For those who have not had the good fortune to read this masterpiece, it describes the year or so period over which Primo Levi recovered from his experience of Auschwitz and his return to Italy. Having been rescued by the Russians, Levi necessarily spent his time recovering in refugee camps and transit centres in the Soviet Union. In additional to his remarkable insights into the nature of humanity, Levi also gives us a unique picture of Russia under Stalin. Unlike most western writers of the time, he was not writing about his time in Russia in order to criticize or applaud communism; his experience was entirely tangential to it, and although thankful to his Soviet liberators and potentially a sympathizer (since a leftist during the war), he had no particular broader political motives for his book. This is about as unbiassed a snapshot of Soviet life as you could hope to get at the time, and it is remarkable for one common theme : chaos. Contrary to our image of communist life as regimented, strictly controlled and highly authoritarian, his experience of the Soviet Union was one of chaos, easy movement, rules flouted, and a kind of free-floating easiness of life that one wouldn’t expect in this putatively rigid society. One could argue that this was a consequence of the immediate confusion of the post-war era, but I don’t think this can be all of the reason: we know that the Soviet Union launched vicious crackdowns in its territories when the war was over, and very efficiently looted East Germany; surely if they had wanted to they could have run their refugee camps, railway stations and behind-the-lines towns with an iron fist. But they didn’t, and this surprised me when I read the book. One doesn’t associate chaotic and disordered, highly transient and quite libertine lifestyles with an immediate post-war Stalinist state.

Recently I have been reading a book called Passage to Manhood: Youth Migration, Heroin and AIDS in Southwest China, by Shao-hua Liu, which is a book about the development of heroin addiction and the HIV/AIDS epidemic in minority Nuoso people in Sichuan province, China. The book is based on ethnographic research carried out by Liu during 2005-2009, and describes the particular social and cultural context in which heroin addiction spread through this community. It’s billed as a work of “medical ethnography” and it certainly doesn’t disappoint in this regard. It’s a very interesting read! Although the fieldwork was conducted in the 2000s, much of the discussion concerns past events in the lives of the research subjects, and many of these past events focus around criminality: historically the Nuoso have entered manhood by looting neighbouring Han Chinese areas and taking slaves, and as modernity overtook their communities this practice shifted from looting neighbouring areas to going on journeys to large cities and engaging in petty crime in places like Chengdu, Xi’An, or even Beijing. The book contains accounts of some of these activities.

This is interesting because it gives us an insight into the interaction of criminals from an ethnic minority (supposedly discriminated against in China) with China’s public security officials. China is supposedly highly authoritarian and has a strong police force, large prison population, etc. So one would expect that there would be a fairly robust response to Nuoso criminality, and some evidence of the pervasive nature of Chinese authoritarianism. In fact, we read more of the same kinds of thing as Levi described. For example, in one passage we discover that an area of Han Chinese in Chengdu got permission from the police to set up an extra-judicial police force to patrol their areas and prevent Nuoso from entering them unless they had identification. You would think that a strong central state would prohibit private groups from this sort of thing, unless (perhaps) they were officially-supported militia. But compared to the states dealings with the Han Chinese, when they interact with Nuoso criminals things really get chaotic. Let us consider three examples.

The Mummy Clause

In one instance, a mother was arrested for drug dealing in Yunnan province and sent to a detention centre. The mother had a baby of several months who she was nursing, and so her family petitioned the local Communist Party to let her go for a year so she could nurse her baby. They did, on the condition that she return to detention after a year. At the end of that year she absconded and returned to drug dealing in Chengdu. The story does not contain any suggestion that the police were able to follow her. This is an example of an informal judicial arrangement being made for an ethnic minority mother – is it consistent with our expectation of a strong Chinese security apparatus?

Public Cremation

In Nuosu theology, it is very important to cremate the body of a dead person, and to return at least some of their skeleton and ashes to the family so that their three souls can gain proper rest. Of course, for homeless Nuosu drug users in big cities far from their homes, this is very difficult. Many Nuosu died of drug overdose and had to be cremated in the cities where they died, but this often cost far more than even a wealthy Nuosu could afford. In one account, a Nuosu man describes his experience of burning the dead in the parks of Xi’an:

One time, in the middle of a cremation on the fringes of Xi’an City, policemen suddenly arrived and accused me of being a murder. I told them, “I didn’t kill him. He was my own brother! We Yizu [minorities] do this to teh dead all the time.” I showed the policemen the dead man’s hukou[registration card]. I thought it might be needed, so I had brought it with me from Limu. I also gave the policemen the telephone number of the Zhoujue County Police Station. They made a call to the Zhaojue and realized that we Yizu do cremate the dead this way. So they didn’t arrest me but warned me not to burn bodies this way anymore.

So this is the fearful Chinese police in action. They catch you burning a body in one of China’s major cities, and they ask you not to do it again, and decide not to investigate a murder, after calling a rural police station and being told that this sort of thing happens. Can you imagine if you tried burning a body in a bit of scrubland on the edge of the city you currently live in, and the police caught you? Would it be sufficient to say “I can’t afford a crematorium”? If an Aboriginal man tried to do a customary burning of a body on the outskirts of an Australian city, would he be let off with a caution by passing cops? I think not!

Anti-drug Campaigns

The author also describes the initial efforts by Chinese police to break up drug dealing in the Nuosu towns. Having initially left it to the local Nuosu elders (“lineage groups”) to resolve the problem – itself not the sort of behaviour one associates with a state that is oppressing minorities –  the police finally started acting on the increasing problems that were being experienced in these towns. In one instance they broke up a group of youths who were watching tv in front of a school. The Nuosu being interviewed tells us

Everybody ran and hastily threw the drugs behind the TV set. The police arrested a five-year-old boy who happened to pick up a small packet of drugs! His lineage headmen complained to the police about their arrest of an innocent kid and finally were able to take him back home.

What happened to the terrifying police? Where are their powers of arbitrary detention? What about using the kid as a hostage to enforce good behaviour by the barbarian minority?! What about swapping the kid for a drug dealer, or sending the lot of them to work camps? And just precisely how official and intimidating and well-organized could this raid possibly have been, when everyone was able to run and throw their drugs behind the TV. Imagine if the police in your country did a drug bust, and your level of terror of them was sufficiently low that throwing your drugs behind a communal tv would be sufficient to get you out of trouble.

I’ve seen COPS, and I don’t think that things would have panned out quite the same way for a group of young men from an American minority in the same situation.

This is not the kind of thing one expects of a society with a strong police state, where untold hordes of people are supposedly shuffling around in re-education camps, while those who are “free” yearn for the real freedoms of the west. In fact, the USA has a much higher rate of imprisonment than China, and debate about whether China has a more punitive public security system than the US centres around the numbers of unofficial prisoners (the shambling hordes in the work camps) and the treatment of minorities. This book suggests to me that the Chinese handling of (non-political) crimes is much less punitive than the US, and more chaotic and based on individual discretion (not always a good thing) and that there is a lot of confusion in its public security apparatus. It also suggests to me that their system of handling minorities is not as oppressive as some commentators would have us believe.

As ever, nothing of what we’re told by our friends in the media can be trusted…



This post has come about because over at Crooked Timber I was outed as one of the authors on this paper, while defending the prohibition of heroin (I’m the third author on that paper, and have a brace like it[1]). I don’t usually like to reveal my identity on the internet, because … well, because the internet is a dangerous place, and also it seems a bit pretentious. But since it came up on that thread, and I didn’t want to do a threadjack (the OP was about “zombie economics,” not “zombie drug policy”), I thought I’d give the definitive Faustusnotes position on the Legalization of Heroin.

First though, in the interests of all this clarity of identity, I thought I’d add that I’m currently teaching this topic in a special lecture at Ritsumeikan Asia Pacific University, on the special topic of Global Crime and Public Health, in which I get to add some of my own theories about the importance of governance and corruption in modern drug policy. My views, of course, don’t represent those of the University or my colleagues, though I sincerely hope that they do reflect those of my students by the end of the course[2] . Also, Professor Quiggin, the author of the original post at Crooked Timber, has a couple of posts about prohibition at his own blog that express a common problem many on the civil libertarian side of politics (whether right or left) have with drug prohibition – even if we accept it is practically a good idea, how can we justify it when we don’t prohibit alcohol or tobacco? I’ll try to answer that on practical grounds in this post as well.

As a final point, I should add that my views don’t represent those of my co-authors, though I think we agree in the main on most of these issues, but it would be wise to assume we differ in various small ways about details of the wide range of issues that fall within the rubric of modern drug policy.

The harm reduction vs. prohibition debate and the war on drugs

As with a lot of modern policy debate, the drug “debate” has been poisoned by the involvement of the US on the prohibition side of things. US prohibition policy – the so-called “war on drugs” – is much tougher and harsher than that in action in other countries of the developed world, and involves a whole series of abuses of freedom that don’t really occur in the rest of the developed world. The US also lacks a coherent national harm reduction policy, which means that the worst effects of the drug trade on its prime victims (the drug users) is not ameliorated or softened effectively by health or welfare agencies. I find when discussing the issue of whether drugs should be legalized that it is best to completely ignore the US experience of prohibiting heroin and cocaine, because it has been done in such a cruel and heartless way that it really doesn’t represent what can be achieved.

It’s also important to ignore the distinction between harm reduction and prohibition, and to assume for a moment that they can a) work side by side, and b) aim for the same goal (improvements in health). We can, at least in theory, argue for prohibition on the basis of its benefits for health.

For the benefit of my American reader(s), harm reduction is a suite of practical policies aimed at reducing the damage drug use does, without attempting to judge the behaviour, and based on the assumption that harmful behaviour occurs regardless of our judgments and even where it is illegal. Because harm reduction doesn’t explicitly try to stop the underlying activity, many people think of it as a kind of “gateway policy” for drug legalization, but in my experience this is a pretty big mistake. Harm reduction is typically represented by policies like Needle Syringe Programs (dispensing free needles), free availability of methadone treatment, and sometimes more radical experiments like medically supervised injecting centres[3] or medical prescription of heroin[4]. Many harm reduction practices do actually attempt to change behaviour, reduce drug use or stop drug use (that’s pretty much what methadone is designed to do), so the claim that harm reduction as a policy suite condones drug use is a bit shallow.

Prohibition, on the other hand, is an attempt to stop the use of drugs, typically by banning their production, sale and/or use. Prohibition has recognized negative effects, the main ones being (and these are all important):

  • Criminalization of drug users for their personal behaviour, which generally doesn’t harm others
  • Invasion of the rights of non- drug users as part of police activity
  • Stigmatization of drug users
  • Significant public health effects deriving from the need of users to keep their use secret

Note that stigmatization is important in the era of HIV. Stigmatized people don’t seek health care. This means that there is a risk they will unknowingly spread HIV. Thus stigmatization is practically an important issue even if you, personally, think that the stigma is deserved.

Why Prohibit Heroin?

Heroin, particularly, needs to be prohibited for a simple reason – it is extremely dangerous when used as an injectable drug. It is dangerous for two simple reasons, and neither of these reasons will go away just because the substance is legal. These are:

  • Transmission of Blood Borne Viruses (BBVIs): particularly HIV and Hepatitis C (HCV). HCV is now the single biggest cause of liver transplant in Australia, surpassing alcohol-related liver damage, so it’s an extremely costly and unpleasant disease. HIV is a bullet that the developed world largely dodged by good luck and very rapid implementation of harm reduction policy. BBVIs are primarily spread in the developed world through needle sharing by IDUs (in fact, it’s the only way to transfer HCV). To give a sense of how endemic these diseases can be, HCV was around in Australian IDUs in the 70s, before the implementation of NSP and harm reduction policies. Its current prevalence in IDUs is about 60%, and in US areas without NSP it is up above 90%. HIV in Australian IDUs is low, less than 1% in fact, and this is almost entirely due to the provision of clean needles to IDUs before the disease became widespread.
  • Overdose: Heroin kills its users, randomly, and rapidly. During the late 1990s in Australia heroin became one of the top killers of young people, with nearly 1000 deaths in 1999. Although overdose is associated with using other central nervous system depressants (especially alcohol and benzodiazepines), the epidemiology of overdose is still not clear and there is pretty strong evidence of at least some randomness in the death rate – autopsies suggest that people who have died from overdose have similar levels of residual heroin in their system to those who didn’t, whether or not they had other substances at the time of death. OD is a random risk that heroin users face.

If heroin were legalized, it would become much more widely available and the rates of BBVIs and HCV would surely climb. There are clear reasons why this will happen, but before I describe them, anyone who has read this far should ask themselves these three questions:

  • Have you ever got drunker than you expected from a couple of beers, or experienced greater effects from the amount of alcohol consumed than you expected? i.e. is your experience of alcohol’s potency the same every time you drink the same alcohol?
  • Have you ever had unsafe sex when you fully intended to have safe sex, had the condoms with you, and knew the risks? Do you know people who have done this?
  • Have you, your partner, or a completely reasonable and sane person you know, ever experienced an unplanned pregnancy? Do you think those people knew the risks? Do you think that the high teen pregnancy rate in the UK is entirely related to lack of availability of condoms?

I present these questions in support of the unasked questions about the behaviour that will flow from legalization. Legalization is not a panacaea that will instantly solve all our drug use problems, and turn previously chaotic, criminally involved addicts into beautiful people. It just means more people will be at risk of these mistakes.

The consequences of legalization

The two main consequences of legalization of heroin are an increase in overdose deaths and an increase in the prevalence of BBVIs. These, I think, are inevitable, because of the reality of injecting drug use.

Increase in Overdose Deaths: heroin does not kill users because it is cut with bad stuff, as many claim. It kills users because it randomly kills people. Some people claim that steady purity will prevent this from happening, because users will know how much they’re taking, but this isn’t necessarily the case. We don’t know the biological causes of overdose clearly, and we don’t clearly understand the relationship between heroin purity and overdose. I am sure it’s well understood in medical settings, but people won’t be injecting heroin in a medical setting – they’ll be injecting it in their loungeroom, with their friends, in the same context that people drink alcohol now. The effects won’t be controlled, and peoples’ behaviour is not so straightforward. There will be people who misjudge the time since they last had a drink, or how drunk they “think” they are, or who think the first shot just isn’t enough and don’t wait long enough for the second one, or who’re feeling particularly nasty today, or… then there will be people (presumably those who map to the 30% of ODs whose residual levels of morphine are lower than in OD survivors) who just die randomly. There will also be people who’ve tried to give up, and come back for a shot but forget their tolerance has gone down; people coming out of gaol or the army or a long overseas trip.

Increase in BBVIs: HCV is not a rare disease that IDUs get through crazy mistakes. It’s an environmental hazard that happens to people who are IDUs. It happens because people shoot up in silly situations, like the toilet behind the restaurant, or the party with 5 of their mates, or 6 times today during a cocaine binge, or… I once watched 10 people in a room at a house party injecting speed, all sharing the drug from the same bag by the light of a couple of candles, most of them drunk, music loud, people passing around various objects, bags, spoons, water… in this situation needles get misplaced easily, people think they’re using their own but they’re not… with 60% prevalence of a virus, this becomes a significant risk of its spread.

It’s also not the case that IDUs in Australia share needles because of the illegality of the drug. Most IDUs in Australia have regular, reliable and uninterrupted access to clean needles and don’t have to share, and sharing rates are generally low. Nonetheless, prevalence of HCV is high. This is because when the majority of people in your community have a disease that is linked to the main behaviour that defines your community, that disease becomes an environmental hazard, rather than an avoidable medical condition (like HIV).

Addiction: The other thing that will happen if the drug is legalized is a lot of people will try it and become addicted. We have evidence from the Vietnam war that when the drug is available young men will try it; if legal in Australia and easily purchased, the number of people trying it will increase and with it the pool of addicted people. Addiction to heroin is associated with poverty – you can’t shoot up 3 times a day and hold down many forms of work. Addiction to heroin is also associated with loss of children (through neglect) and family. Unless the legally available drug is very cheap, it will also lead to crime – an addicted person will be having to spend upwards of $30 a day on their habit, which is worse than most serious smokers do. Having lost their job and family support, where will this money come from?

Many people try heroin and don’t become addicted, but those who do become addicted typically see their lives fall apart around them. We don’t need to expand the pool of people to whom this applies.

Australia’s Prohibition Success

In January 2001 Australia experienced a sudden reduction in the availability of heroin, that led to a marked change in the heroin markets and drove a lot of young people and new users out of the heroin market, probably permanently. There was a sustained 60% reduction in heroin deaths, 70% reduction in ambulance attendances at overdose, and a 15% reduction in cocaine possession offences. There was no long term increase in acquisitive crime, prostitution offences or BBVIs. New entrants to methadone increased, indicating people trying to leave the market; it’s likely that the overall number of new and young users permanently declined. This was a huge public health gain with very little downside, and it occurred through a sustained campaign of harm reduction and prohibition that ramped up, and improved, with the 1997 release of the National Drug Strategy (under the conservative government of John Howard). Increased treatment places, novel harm reduction policies, and improved health services to IDUs, meant that they were sheltered from the worst effects of the shortage; improved coordination of federal customs and police, improved intelligence-gathering and coordination of local police, and significant reductions in police corruption, meant that drug importation stopped being profitable, and the supply side of the market collapsed.

Our argument (in the paper linked above) is that harm reduction was a key part of this success of prohibition, both in reducing demand for heroin (through methadone treatment) and in protecting users from the worst of the effects of prohibition when it happened. The long term reforms of sex work and police behaviour towards petty crime also helped with this – in my opinion, on a local level we saw the lessons of the Inquiry into Aboriginal Deaths in Custody, the Wood Royal Commission into Police Corruption[5], the National Drug Strategy and the Drug Courts all coming together in 2000/2001 to destroy the viability of the market for heroin.

Why we Prohibit Heroin but not Alcohol

There is understandable concern that it’s hard to support prohibiting heroin but not alcohol; and that the bad historical lessons of the latter should inform our decision to try the former. But in fact the two drugs are completely different, and there are practical reasons why even if we wanted to prohibit alcohol we can’t. John Quiggin touches on these in his posts on prohibition, but I think he misses the point a little. We can’t prohibit alcohol for many practical reasons that don’t apply to heroin:

  • It has a long-standing tradition of use, that isn’t just window-dressing. Alcohol is an important part of our culture, not something we can just wish away, with a role in festivals and the bonds of social life
  • The raw materials are accessible to anyone – they’re in shops down the road
  • The production process is well understood and can be done in a back yard, so the prohibition is trivial to avoid
  • Declaring alcohol illegal means that the people charged with enforcing the law will be declared criminal overnight, unless they stop a long-term habit (Police do like a drink)
  • There is an existing industry with a significant role in society – not something that ever applied to heroin

In addition, we know that alcohol can be used safely, while heroin can’t. So it’s really hard to put up a justification for banning alcohol “for the protection of the user,” while we can do so for heroin. Now, many people object to banning a substance if the only victim is the user, which is why we only ban substances we are sure you can’t use safely; or substances that affect others as well as the user. This applies in spades for heroin, which has no safe level of use, is highly addictive, and whose habitual users commit significant amounts of crime to fund their habit. Heroin is a public order as well as a personal health problem, and the possibility that legalizing it will suddenly cause all those public order problems to disappear rather than worsen is really something that we don’t need to take a risk and find out – especially since we have perfectly good policies in place to prevent prohibition from becoming the vicious, poisonous political problem that is in the US.

A Final Note on Narco-States

It is my firm opinion that drug dealing does not destroy nations (like Columbia or Guinea-Bissau). Rather, states in the process of collapse become havens for drug dealers, which in turn destabilizes parts of those states, and leads to massive corruption problems that further fragment the states. Australia grows lots of opium, but you don’t see Tasmania turning into a narco state. This is because we have a strong state, that can control crime in its borders. There is no causal process from drug dealing to failed states; it’s the other way around.


On civil liberties grounds alone no substance should be banned if it is just bad for the user. But if the drug is randomly fatal, causes addiction and poverty of the kind that inevitably leads people to be tempted to commit crime, and is associated with a significant public health problem like HCV or HIV, then it should be banned if it is possible to do so. It is practically possible to prohibit heroin, we have shown it can be done and that harm reduction can prevent such prohibition from being a threat to health; so I think we should maintain heroin’s illegal status, and do all we can to prevent its production, importation, and use. It should, in short, remain illegal.

fn1: including an interesting test of the relative importance of long-term epidemic trends in the heroin market, compared to a sudden shock; and a general method for statistical analysis of imperfectly-dated natural experiments

fn2: Said facetiously, of course…

fn3: One of which I had a small part in helping to set up

fn4: Which I support

fn5: Which I think was hugely important for police corruption in Australia