Life Expectancy and Record Keeping

Those of you who follow any sort of science/data/skepticism news on Twitter will have almost certainly have heard of the new pre-print taking the internet by storm this week: “Supercentenarians and the oldest-old are concentrated into regions with no birth certificates and short lifespans“.

This paper is making a splash for two reasons:

  1. It is taking on a hypothesis that has turned in to a cottage industry over the years.
  2. The statistical reasoning makes so much sense it makes you feel a little silly for not questioning point #1 earlier.

Of course #2 may be projection on my part, because I have definitely read the whole “Blue Zone” hypothesis (and one of the associated books) and never questioned the underlying data. So let’s go over what happened here, shall we?

For those of you not familiar with the whole “Blue Zone” concept, let’s start there. The Blue Zones were something popularized by Dan Buettner who wrote a long article about them for National Geographic magazine back in 2005. The article highlighted several regions in the world that seemed to have extraordinary longevity: Sardinia (Italy), Okinawa (Japan) and Loma Linda (California, USA). All of these areas seemed to have a very above average number of people living to be 100. They studied their habits to see if they could find anything the rest of us could learn. In the original article, that was this:

This concept proved so incredibly popular that Dan Buettner was able to write a book, then follow up books, then a whole company around the concept. Eventually Ikaria (Greece) and Nicoya Peninsula (Costa Rica) were added to the list.

As you can see the ultimate advice list obtained from these regions looks pretty good on its face. The idea that not smoking, making good family and social connections, daily activity and fruits and vegetables are good certainly isn’t turning conventional wisdom on it’s head. So what’s being questioned?

Basically the authors of the paper didn’t feel that alternative explanations for longevity had been adequately tested, specifically the hypothesis that maybe not all of these people were as old as they said they were or that otherwise bad record keeping was inflating the numbers. While many of the countries didn’t have clean data sets, they were able to pull some data sets from the US, and discovered that the chances of having people in your district live until they were 110 fell dramatically once state wide birth registration was introduced:

Now this graph is pretty interesting, and I’m not entirely sure what to make of it.  There seems to be a peak at around -15 years before implementation, which is interesting, with some notable fall off before birth registration is even introduced. One suspects birth registration might be some proxy for expanding records/increased awareness of birth year. Actually, now that I think about it, I bet we’re catching some WWI and WWII related things in here. I’m guessing the fall off before complete birth registration had something to do with the draft around those wars, where proving your age would have been very important. The paper notes that the years 1880 to 1900 have the most supercentenarians born in those years, and there was a draft in 1917 for men 21-30. Would be interesting to see if there’s a cluster of men at birth years just prior to 1887. Additionally the WWII draft start in 1941 went up to 45, so I wonder if there’s a cluster at 1897 or just before. Conversely, family lore says my grandfather exaggerated his age to join the service early in WWII, so it’s possible there are clusters at the young end too.

The other interesting thing about this graph is that it focused on supercentenarians, aka those who live to 110 or beyond. I’d be curious to seem the same data for centenarians (those who live to 100) to see if it’s as dramatic. A quick Google suggests that being a supercenetarian is really rare (300ish in the US out of 320 million) but 72,000 or so centenarians. Those living to 90 or over number well over a million. It’s much easier to overwhelm very rare event data with noise than more frequent data. I have the Blue Zone book on Kindle, so I did a quick search and noticed that he mentioned “supercenterians” 5 times, all on the same page. Centenarians are mentioned 167 times.

This is relevant because if we saw a drop off in all advanced ages when birth registrations were introduced, we’d know that this was potentially fraudulent. However, if we see that only the rarest ages were impacted, then we start to get in to issues like typos or other very rare events as opposed to systematic misrepresentation. Given the splash this paper has made already, I suspect someone will do that study soon. Additionally, the only US based “Blue Zone”, Loma Linda California, does not appear to have been studied specifically at all. That also may be worth looking at to see if the pattern still holds.

The next item the paper took a shot at was the non-US locations, specifically Okinawa and Sardinia. From my reading I had always thought those areas were known for being healthy and long lived, but the paper claims they are actually some of the poorest areas with the shortest life expectancies in their countries. This was a surprise to me as I had never seen this mentioned before. But here’s their data from Sardinia:

The Sardinian provinces are in blue, and you’ll note that there is eventually a negative correlation between “chance of living to 55” and “chance of living to 110”. Strange. In the last graph in particular there seem to be 3 provinces in particular that are causing the correlation to go negative, and one wonders what’s going on there. Considering Sardinia as a whole has a population of 1.6 million, it would only take a few errors to produce that rate of longevity.

On the other hand, I was a little surprised to see the author cite Sardinia as having on of the lowest life expectancies. Exact quote “Italians over the age of 100 are concentrated into the poorest, most remote and shortest-lived provinces,”. In looking for a citation for this, I found on Wiki this report (in Italian). It had this table:

If I’m using Google translate correctly, Sardegna is Sardinia and this is a life expectancy table from 2014. While it doesn’t show Sardinia having the highest life expectancy, it doesn’t show it having the lowest either. I tried pulling the Japanese reports, but unfortunately the one that it looks the most useful is in Japanese. As noted though, the paper hasn’t yet gone through peer review, so it’s possible some of this will be clarified.

Finally, I was a little surprised to see the author say “[these] patterns are difficult to explain through biology, but are readily explained as economic drivers of pension fraud and reporting error.” While I completely agree about errors, I do actually think there’s a plausible mechanism that would cause poor people who didn’t live to 55 as often to have longer lifespans. Deaths under 55 tend to be from things like accidents, suicide, homicide and congenital anomalies….external forces. The CDC lists the leading causes of death by age group here:

Over 55, we mostly switch to heart disease and cancer. A white collar office worker with a high stress job and bad eating habits may be more likely to live to 55 than a shepherd who could get trampled, but once they’re both 75 the shepherd may get the upper hand.

I’m not doubting the overall hypothesis by the way….I do think fraud or errors in record keeping can definitely introduce issues in to the data. Checking outliers to make sure they aren’t errors is key, and having some skepticism about source data is always warranted. After writing most of this post though, I decided to check back in on the Blue Zones book to see if they addressed this.  To my surprise, the book claims that at least in Sardinia, this was actually done. On page 25 and 26, they mention specifically how much doubt they faced and how one doctor personally examined about 200 people to help establish their truthfulness about their age. Dr Michel Poulain (a Belgian demographer) apparently was nominated by a professional society specifically to go to Sardinia to check for signs of fraud. According to the book, he visited the region ten times to review records and interview people. I have no idea how thorough he was or how his methods hold up, but his work seems at odds with the idea that someone just blindly pulled ages out of a database or the papers claim that “These results may reflect a neglect of error processes as a potential generative factor in remarkable age records”. Interestingly, I’d imagine WWI and WWII actually help with much of the work here. Since I’d imagine most people have very vivid memories of where they were and what they were doing during the war years, those stories might go far to establishing age.

Basically, it seems like sporadic exaggeration, error or fraud might give mistaken impressions about how many supercenteranian people there are overall, but I do wonder if having an unusual cluster brings enough scrutiny that we don’t have to worry as much that something was missed. In the Blue Zone book, they mention the group that brought attention to the Sardinians had helped debunk 3 other similar claims. Also, as mentioned, the paper doesn’t mention if the one US blue zone was one of the ones to get late birth registration, but I do know the Seventh Day Adventists are one of the most intensely studied groups in the country.

Anyway, given the attention and research that has been paid to these areas, I’d imagine we’re going to hear some responses soon.  Dr Poulain appears to still be active, and one suspects he will be responding to this questioning of his work. This post is getting my “things to check back in on” tag. Stay tuned!



Beard Science

As long as I’ve been alive, my Dad has had a full beard [1].

When I was a kid, this wasn’t terribly common. Over the years this has become surprisingly more common, and now the fact that his is closely trimmed is the uncommon part.

With the sudden increase in the popularity of beards, studying how people perceive bearded vs clean shaven men has gotten more popular. Some of this research is about how women perceive men with beards, and there’s actually a “peak beard” theory that suggests that women’s preferences for beards goes up as the number of men with beards goes down and vice versa.

This week though, someone decided to study a phenomena that has always fascinated me: small children’s reaction to men with beards. Watching my Dad (a father of 4 who is pretty good with kids) over the years, we have noted that kids do seem a little unnerved by the beard. Babies who have never met him seem to cry more often when handed to him, and toddlers seem more frightened of him. The immediacy of these reactions have always suggested that there’s something about his appearance that does it, and the beard is the obvious choice.

Well, some researchers must have had the same thought because a few weeks ago a paper “Children’s judgements [sic] of facial hair are influenced by biological
development and experience” was published that looks at children’s reactions to bearded men. The NPR write up that caught my eye is here, and it led with this line “Science has some bad news for the bearded: young children think you’re really, really unattractive.”. Ouch.

I went looking for the paper to see how true that was, and found that the results were not quite as promised (shocking!). The study had an interesting set up. They had 37 male volunteers get pictures taken of themselves clean shaven, then had them all grow a beard for the next 4-8 weeks and took another picture. This of course controls for any sort of selection bias, though to note the subjects were all of European decent. Children were then shown the two pictures of the same man and asked things like “which face looks best?” and “which face looks older?”. The results are here:

So basically the NPR lead in contained two slight distortions of the findings: kids never ranked people as “unattractive”, they just picked which face they thought looked best, and young kids actually weren’t the most down on beards, tweens were.

Interestingly, I did see a few people on Twitter note that their kids love their father with a beard, and it’s good to note the study actually looked at this too. The rankings used to make the graph above were done purely on preferences about strangers, but they did ask kids if they had a father with a beard. For at least some measures in some age groups, having exposure to beards made kids feel more positively about beards. For adults, having a father or acquaintances with beards in childhood resulted in finding beards more attractive in adulthood. It’s also good to note that the authors did use the Bonferri correction to account for multiple comparisons, so they were rigorous in looking for these associations.

Overall, some interesting findings. Based on the discussion, the working theory is that early on kids are mostly exposed to people with smooth faces (their peers, women) so they find smooth faces preferable. Apparently early adolescence is associated with an increased sensitivity to sex specific traits, which may be why the dip occurs at age 10-13. They didn’t report the gender breakdown so I don’t know if it’s girls or boys changing their preference, or both.

No word if anyone’s working on validating this scale:

[1] Well, this isn’t entirely true, there were two exceptions. Both times he looked radically different in a way that unnerved his family, but I was fascinated to note that some of his acquaintances/coworkers couldn’t figure out what was different. The beard covers about a third of his face. This is why eye witness testimony is so unreliable.

What I’m Reading: July 2019

As always, Our World in Data provides some interesting numbers to think about, this time with food supply and caloric intake by country.

This article on chronic lyme disease and the whole “medical issue as personal identity” phenomena was REALLY good and very thought provoking.

Ever want to know where the Vibranium from Black Panther would land on the periodic table of elements? Well, now there’s a paper out to help guide your thinking. More than just a fun paper to write up, the professors involved here actually asked their students this on an exam to see how they would reason through it. I’m in favor of questions like this (provided kids know to have watched the movie) as I think it can engage some different types of critical thinking in a way that can be more fun than traditional testing.

I mentioned to someone recently that I have a white noise app on my phone, but after testing it out I found that brown noise tends to be more effective in helping me sleep than white noise. They asked what the difference was, and I found this article that explains different color noises. In my experience the noises that tend to be loudest and most likely to interfere with sleep tend to hang out at the low end of the spectrum, YMMV.

A new study “Surrogate endpoints in randomised controlled trials: a reality check” gives an interesting word of warning to the cancer world. It’s common in clinical trials to use surrogate endpoints like “progression free survival” or “response rate”to figure out if drugs are working. This is done because overall survival can take a long time to get and researchers/patients/drug companies want results faster and it seems like if the surrogate markers are good the drugs can’t possibly hurt.

Unfortunately, it appears this isn’t the case. A new drug venetoclex was studied and patients on it were eventually found to have better progression free survival, but eventually twice as many deaths as those treated with regular treatment. Ugh. The lead author has a great Twitter thread on his paper here, where he suggests this means that either the drug is a “double edge sword” with both better efficacy and higher toxicity than alternatives, or that it’s a “wolf in sheep’s clothing” that makes things look good for a while but causes changes that means relapse is swift and deadly. Lots to think about here.

Finally, SSC has a good post up on bias arguments here. I especially like his points about when they are relevant.

The Evangelical Voter Turnout that (Maybe) Wasn’t

There was an interesting graph in a recent New York Times article  that got Twitter all abuzz:

Visually, this graph is pretty fascinating, showing an increasingly motivated white Evangelical group, whose voter participation rates must put every other group to shame. I was so taken aback by this I actually did share it with a few people as part of a point about voter turnout.

After sharing though, I started to wonder how this turnout rate compared to other religious groups, so I went looking for the source data. A quick Google took me to this Pew Research page, which contained this table:

Two things surprised me about this:

  1. Given the way the data is presented, it appears the Evangelical question was asked by itself as a binary yes/no, as opposed to being part of a list of other options.
  2. The question was not simply “are you Evangelical” but “are you Evangelical/born again”.

Now from researching all sorts of various things for this blog, I happen to know that one of the most common ways of calculating how many white Evangelicals there are in the population is to ask people their denominational affiliation from a menu of choices, then classify those denominations in to Evangelical/Catholic/etc. That’s what PPRI (the group that got the 15% number) does.

For the voting block question however, they were only asked if they were a “White born-again or evangelical Christian?

Now to get too far in to the theological nuances, but there are plenty of folks I know who would claim the “born again” label who don’t go to traditionally “Evangelical” churches.  In fact, according to Mark Silk over at Religion News (who noted this discrepancy at the time), he’s been involved with research that “found that 38.6 percent of mainline Protestants and 18.4 percent of Catholics identified as “born again or evangelical.” So yes, the numbers may be skewed. It’s also worth noting that Pew Research puts the number of Evangelical Protestants at 25%, in a grouping that categorizes historically black groups separately (and thus is presumably mostly white).

So is the Evangelical turnout better than other groups? Well, it might still be. However, it’s good to know that this graph isn’t strictly comparing apples to apples, but rather slightly different questions given to different groups for different purposes. As we know slight changes in questions can yield very different results, so it’s worth noting. Caveat emptor, caveats galore on this one.

Fentanyl Poisoning and Passive Exposure

The AVI sent along this article this week, which highlights the rising concern about passive fentanyl exposure among law enforcement.  They have a quote from a rehab counselor who claims that just getting fentanyl on your skin would be enough to addict you, and that merely entering a room where it’s in the air could cause instant addiction. Given that it’s Reason Magazine, they then promptly dispute the idea that this is actually happening.

I was interested in this article in part because my brother’s book contained the widely reported anecdote about the police officer who overdosed just by brushing fentanyl off of a fellow police officer. This anecdote has been seriously questioned since. Tim expressed concerns afterwards that had he realized this he would have left it out. I’ll admit that since my focus was mostly on his referenced scientific studies, I didn’t end up looking up various anecdotes he included.

This whole story indicates an interesting problem in health reporting. STAT news has more here, but there’s a couple things I noted. First, the viral anecdote really was widely reported, so I’m not surprised my brother heard about it. It has never technically been disproven….outside experts have said “it almost certainly couldn’t have happened this way” but neither the police officer nor the department have commented further. This makes it hard for the “probably not” articles to gain much traction.

Second, the “instant addiction” part was being pushed by a rehab counselor, not toxicologists who actually study how drugs interact with our body. Those experts point out that it took years to create a fentanyl patch that would get the drug to be absorbed through the skin, so the idea that skin contact is as effective as ingesting or breathing it in seems suspect.

Third, looking at the anecdotes, we realize these stories are NOT being reported by the highest risk groups. Pharmacists would be far more likely to accidentally brush away fentanyl than police officers, yet we do not hear these stories arising in hospital pharmacies. Plenty of patients have been legally prescribed fentanyl and do not suffer instant addiction. The fact that the passive exposure risk seems to only be arising in those who are around fentanyl in high stress circumstances suggests other things may be complicating this picture.

While this issue itself may be small in the grand scheme of things, it’s a good anecdote to support the theory that health fake news may actually cause the most damage. While political fake news seems to have most of our attention, fake or overblown stories about health issues can actually influence public policy or behavior. As the Reason article points out, if first responders delay care to someone who has overdosed because they are taking precautions against a risk that turns out to be overblown, the concern will hurt more people than it helps. Sometimes an abundance of precaution really can have negative outcomes.

Asylum Claims and Other Numbers at the Border

There’s a lot in the news right now about border crossing, immigration and asylum claims, and I’m seeing all sorts of numbers being thrown around on Twitter. I wanted to do a quick round up of some numbers/sources to help people wade through it.

First up, every month US Customs and Border Patrol publishes the number of apprehensions they have at the Southern US Border and how that compares to the last 5 years. They do this relatively close to real time, we have the numbers for May, but not yet for June. If you want to know why you’re seeing so much in the news, take a look at this graph:

So with 4 months left to go in the fiscal year, we’re already 100,000 over the highest year on that chart. To give some context to that though, apprehension numbers have actually been relatively low for the last few years. They peaked at 1.6 million in the late 90s/early 2000s. However, there have been some changes to the makeup of that group….family crossings. Vox published this chart based on the CBP data that shows how this has changed:

I couldn’t find what those numbers were during the last spike, but it seems to be a record high.

So now what about asylum claims? Recently acting DHS Secretary Kevin McAleenan said the 90% of asylum seekers were skipping their hearings, but others were claiming that actually 89% show up. That’s a MASSIVE discrepancy, so I wanted to see what was going on.

First up, the 89% rate. The DOJ publishes all sorts of statistics about asylum hearings, and in this massive report they showed the “in absentia” rates for asylum decisions (page 33):

So for FY17, asylum claimants were at their decision hearing 89% of the time.

So where did the “90% don’t show up” claim come from? Reading the full context of McAleenan’s quote, it appears that he was specifically referencing a new pilot program for families claiming asylum. From what I can tell the pilot program is not published anywhere, so it’s not possible to check the numbers.

So is it plausible it jumped from 11% to 90%? I tend to doubt it, but it’s important to note the lag time here. The last published DOJ numbers are from FY2017, but those are for hearings that took place in FY2017. The average wait time for hearings in these cases for these cases is enormous….727 days so far in 2019.  These wait times are climbing, but if you toggle the graph around, we can see that the wait time back in 2015 was nearly two years:

So essentially those with decisions in FY2017 probably filed in FY2015. And a lot has happened to the stats since then. First, here are the number of applications over the last few years:

So compared to 2015, the number of applications have tripled but the number of approvals has barely budged. We don’t yet know what that will do to the percentage of people who show up, but it seems very plausible that it could increase the absentee rate. Additionally, because family migration is increasing so rapidly, it’s not clear what that will do to the numbers. Regardless, McAleelan’s reference was specifically to that group, so it was only a subset of the numbers that were previously reported. Still, 90% seems awfully high.

Complicating things further of course is the fact that this was a “pilot program”. That means it could have selected just one country or point of entry. One of the more interesting fact sheets from the DOJ site was the rate of asylum approvals by country. In the past few years, here are the top countries (page 29 of this report):

The rates of granting asylum from each of these countries were wildly different in 2018 though. Chinese asylum seekers were 53% granted, El Salvador was 15%, Honduras was 14%, Guatemala was 11%, Mexico was 6%. It seems plausible that a pilot program might have just been addressing those that arrive at the southern border, so it’s possible that individual countries have different profiles.

Overall, it’s clear that the data on this topic is worth watching.

Twitter and Sundry

I finally got a vacation this week, which means I spent not a lot of time near a computer but had a decent amount of time to scroll through Twitter. A few good accounts I found:

Any other good ones I missed?

Speaking of good accounts to follow, apparently one of the first papers focused on a prominent (and anonymous) Twitter account was published, with this one on the role of Neuroskeptic in calling out scientific ethical breeches. Only paper I’ve ever seen where the conflict of interest statement included “…was banned from commenting by Leonid Schneider at his blog “forbetterscience”.

Finally, Neuroskeptic also follows up on an analysis done by Susan Fiske of who research methods blogs go after and how often.  A few years ago Fiske had caused a kerfluffle when she referred to many science/research methods bloggers as “methodological terrorists” and defended the replication crisis. Her new paper looks at 41 bloggers and categorized which other researchers they talked about most often. Interesting findings: 3 out of the top 4 talked about researchers resigned (Diederik StapelBrian Wansink and Jens Förster), , and the #1 guy is pretty notorious. Other interesting note: there was no clear gender bias in who got talked about. Men were more likely to critique other men, and men who got named were posted about more often. However, it’s not particularly clear what this means about bias, as a few large cases of misconduct got a LOT of coverage, and Bem seems to have become the go to for bad methods/good researcher examples.

Still, super interesting work and good for Fiske for doing it. Gotta respect someone who gets mad, then gets data. I look forward to this being expanded on in the future.

Vaccination Rates by County, State and Around the World

There’s a lot in the news recently about vaccination rates, both in the US and in other countries. After seeing a few comments on Twitter this week about the topic, I got curious about the exact numbers.

First off, it’s important to note that for all the press coverage of the measles outbreak, vaccine exemptions are not evenly distributed across the country. For example, here’s just my state broken down by county. The map on the left is those with exemptions, the one on the right is those without exemptions not meeting requirements. Functionally, the vaccination rate is likely 100%-(the number on the left+the number on the right).


Now not everyone on the right may be missing their vaccinations, for some it may be paperwork. The Boston suburbs probably do well because most working parents have been providing vaccination documentation to day cares for years prior to this.

So how does Massachusetts compare to the country? Well, the CDC puts together a rather awesome interactive map for Kindergarten vaccination rates here. This map shows something interesting. Per the NYTs graphic of the measles outbreak, Washington, New York and Michigan have seen the largest measles outbreaks in the country. However, New York actually has one of the highest vaccination rates in the country at 97.5%. This suggests that it’s not just having a high vaccination rate, but where the unvaccinated are located that causes outbreaks. For example, in Massachusetts the exemption rates are highest on Martha’s Vineyard, a wealthy spread out community with not many year round residents. The other counties with higher rates of exemptions are not close geographically. In New York City though, it’s groups living in close proximity with low rates that are getting hit by the outbreak. This leads to high overall vaccination rates by state, yet still record setting outbreaks in targeted communities.

Now how about worldwide? Well, after working on their childhood vaccination program for years, Mexico actually now has a higher rate of children vaccinated against measles than the US (96% vs 92%). Interestingly, a similar number of people doubt vaccination safety in both countries. According to Our World in Data, France and Russia have the most vaccine skeptics:

Using Our World in Data again though, apparently vaccine skepticism doesn’t always correlate with not getting vaccinated. Both France and Russian have >95% measles vaccination rates.

I thought all this was interesting because overall, many people believe that fewer children are vaccinated than actually are. For example, Americans estimated that only 35% of the worlds children were vaccinated against measles, when in reality 85% are. While knowing that rates are high can sometimes convince people that it doesn’t matter as much if they get their kids vaccinated, thinking many people aren’t vaccinated can sometimes convince people that it’s not important to do so. “Everybody’s doing it” is an effective slogan for a reason.


Quote for Election Season

Life is a bit chaotic this weekend, but as we head towards what looks to be a rather drawn out election season, here’s a quote to keep in mind:

“The public’s ‘opinion’ on almost any issue will be a function of the question asked.”
-Neil Postman, Technopoly (as found on Twitter)

The exact wording here is important…”a function of” does not mean the question fully makes the opinion, but rather that it transforms it in ways that can often be predicted. A good thing to remember when you see headlines saying “the public supports ______” or “low public support for _______”.

Addiction Nation: Recovery and Hope

This post is part of a series about my brother’s upcoming book Addiction Nation: What the Opioid Crisis Reveals about Us, discussing some of the science and stats he used throughout the books. Read the intro post here, part 1 here, part 2 here, part 3 here, or (best of all) pre-order the book on Amazon here. Only 2 more days until the release!

We’ve spent the last few weeks looking at a lot of areas of addiction, but (much like your book) I wanted to end this series on a positive note….talking about recovery and hope. Of course one of the biggest reasons people want to read about addiction is precisely to find hope, so I think it’s a good place to end. Sound good?

Tim: Awesome! I wanted to note one other hopeful thing up front. There are some pretty terrible treatment programs out there. I didn’t get into the corruption or the number of facilities that don’t use evidence-based treatment methodologies. They really do have low success rates. 

One critical thing to look at is how specific studies define “success.” If they only definition of “success” is total abstinence for a person’s entire life (or even just the length of the study) then a lot of numbers are going to look pretty grim.  But, if success is defined by decreasing overdoses, a reduction in harmful behavior or even just using less of the substance, then there is a lot of reason to hope. 

Another thing I didn’t get to dive into is “spontaneous remission” or when a person recovers from an addiction without any professional treatment. It happens a lot more than you would expect. This means that increasing access to treatment is really important but we can also save a lot of lives by trying to keep people alive long enough for that spontaneous remission to occur. 

Ooooh….defining success metrics clearly. I like it.

Okay, so first up, last week we talked about the Rat Park study, and you mentioned a study that often gets brought up with that one. It’s a 1974 study called “How Permanent Was Vietnam Drug Addiction?“, and it looked at the rates of addiction among American soldiers in Vietnam as they were leaving Vietnam, then got back in touch with them after they got home. The results are here:

The most often quoted statistic (and the one you use in the book) is the amazing drop from 20% reporting an addiction issue to just 1% reporting an issue a year later. It’s an incredible statistic, made stronger by the fact that this study had a very low non-response rate (<5%) and that urine testing backed up the self reported usage. You quote the study as saying:

There have been no studies of addict populations in this country that show anything like the 95 percent remission rate after ten months, which is what a drop from 20 percent addicted while in Vietnam to 1 percent after Vietnam suggests.

I can see why that stat gets all the headlines, but one of the things I found most interesting about this study when I dove in to it was that there’s actually a lot more in it for us to think about. You weren’t able to get in to it in the book, but I found their breakdown of the subgroups within that group fascinating:

So basically 85% of soldiers returned to their pre-Vietnam status. 8% who had used before Vietnam actually stopped using after returning from Vietnam, and 7% who weren’t using before started using and never stopped.

Now the authors throw in a caveat here that just because these veterans stopped using narcotics doesn’t mean they didn’t pick up another problem (alcoholism, barbiturates, etc), and they note that those who continued their addiction tended to have a much bigger problem than they did before going to Vietnam. However, even with those notes, this does fly in the face of the idea that using narcotics will always lead to a permanent addiction problem with that particular substance.

Tim: Absolutely. There is a good reason to believe that this is the norm, not the exception. This is why “heroin-assisted treatment” has been pretty well documented to be effective in the long term. It reduces other health risks, like Hep C and HIV, provides consistent dosage and reduces drug-related crimes. While some people will just keep using indefinitely, a lot of others will experience spontaneous remission or eventually decide to engage in another kind of treatment. 

It also indicates that there are almost certainly people who might be more “situational” addicts, and we may need to treat them differently from those whose addictions seem more persistent. Looking at your story, one could call you a “situational” addict, don’t you think? Any thoughts on this?

Tim: The Vietnam study was actually the inspiration for Bruce Alexander’s “Rat Park.” I think Alexander would argue that almost everyone is a “situational” in their addictions. 

I wouldn’t want to create a strict duality but think this a better category for a spectrum, how big a role does your situation play? For alcohol consumption, there are a lot of folks who have problematic consumption levels that could be classified as alcoholism throughout college and into their twenties and early thirties. But, they eventually change their behavior in a way that is often triggered by major life events.  

But, in Switzerland, about 20% of people have continued using since the beginning of the heroin-assisted treatment program. This remaining population would probably be covered by life trauma, mental illness and some other genetic factors. 

While I focus a lot on environmental and social factors for addiction, you can’t escape some sort of genetic predisposition. Even if it isn’t necessarily for “addiction” but a bodily response to certain substances. 

For example, both us were prescribed opiates in high school/college for oral surgery. You took them and felt terrible. As soon as you could, you moved to ibuprofen because the narcotics made you feel sick. I finished the entire bottle, even though my surgery was less significant because I really enjoyed how they made me feel. 

That’s true. I get incredibly nauseous when I take opioids and have refused them ever since that surgery. Taking enough of them to get addicted would be a downright struggle for me.

Okay, to tease out one last part of that study, I found the entire idea that 8% of the men had a problem before they went to Vietnam but came back and stopped using totally fascinating. That’s pretty much the reverse of what we tend to think about with addiction….that traumatic events must always make it worse. With addiction though, we know this isn’t always the case. As you say in your book:

As discussed earlier, over time, severe addiction reduces the amount of gray matter in the part of our brain most responsible for higher-level reasoning and self-control. A 2013 study of the brains of those struggling with cocaine addiction suggests something interesting. Within a few months of sobriety, that gray matter began to return. Within six to twelve months, the gray matter had returned to baseline levels and was about the same as those who had never been addicted. But soon after that is when the most amazing thing happened: those areas began to form an even greater level of density than for those who had never used cocaine.

You got this from a study called “Dissociated Grey Matter Changes with Prolonged Addiction and Extended Abstinence in Cocaine Users“, which contained this very cool graphic:

So basically, substance use can get bad in a hurry because many substances actually erode the very parts of the brain that normally help us avoid doing impulsive things. Prolonged abstinence actually reinforces those parts of the brain beyond the baseline levels. As the study says:

If addiction can be characterized as a loss of self-directed volitional control , abstinence and its maintenance may be characterized by a reassertion of these aspects of executive function. Current cocaine users demonstrate reduced GM in brain regions critical to executive function, such as the anterior cingulate, lateral prefrontal, orbitofrontal and insular cortices. In contrast, the group of abstinent CD users reported here show elevations in GM as a function of abstinence duration that exceeds control levels after 36 weeks, on average, of abstinence.

They do note (as all good studies do) that they don’t really know causality here either. It could be that these addicts had above-average levels of grey matter beforehand (they were not measured pre-addiction) or it could be that recovery caused them to grow more grey matter than they originally had. It could be a little of both. It’s pure anecdote, but based on what I’ve seen out of successful recovered addicts I’ve known, I’d say the change is real.  How about you? On a personal level, do you feel addiction and recovery changed your brain at all?

Tim: My struggle would be classified as a relatively mild opioid use disorder. While the addictive process at work certainly would have changed my brain it would have been less significant than if it had gone on for years or decades. Since the initial change was not as substantial I don’t think my process of recovery likely changed things as much. 

I have been amazed that whenever I talk with someone who is also open about their recovery, there is often a sense of connection because there are different truths we’ve realized about ourselves that creates a kind of bond. 

Three thoughts related to that. 

First, I wanted to tell my story because early detection matters. If you are able to see what is happening and get support early on, recovery won’t be as difficult. I think a lot of people end up letting an addiction progress because of the shame and stigma that surrounds it. Admitting you are feeling out of control seems like a life and world ending admission. That makes it harder to do. 

Second, I do think this journey has led me to a place of diving deeper into the techniques of cognitive behavioral therapy. My research in that area made me realize how important those tools can be for improving my outlook and life more broadly. Writing a book about opioid addiction made me reflect on my alcohol consumption. It isn’t problematic at the moment but if I was to continue to drink 1-2 more alcoholic beverages a week for the next 10-20 years, there could be significant negative effects. So, I’ve started using what I’ve learned to be more thoughtful about the role alcohol plays in my life. 

Third, has been a deepening of my own spiritual and religious practices including various forms of meditation and prayer. Mindfulness training is now integrated into a lot of different recovery practices. Even though I don’t feel a day to day tug towards opioid usage, I’ve tried to dig into these practices that could provide some anchoring because I am now well aware how easily the addictive process can kick up. 

Alright, well that wraps up the series! If you want to see more from my brother, take a look at his book/author page here or buy the book and get it on Tuesday! Anything else you want to say to the nice people Tim?

Thanks for reading and I’m sure I’ll be back some time soon!

Agreed! You didn’t put it in the book, but I’d love to dig more in to the research around some of the heroin assistance programs. Crazy stuff.

Thanks for posting brother, and thank you so much for letting me opine on your work. It’s been an honor to go through so much of this journey with you, both the addiction part and the book writing part. I’m proud of you on both counts, and can’t wait to see what’s next in your journey.