Cuban Data Refute Mainstream Health Beliefs

A new BMJ paper looks at Cuban health before and after the economic crisis of 1991-1995, when the Cuban economy nose-dived. There wasn’t enough gasoline for cars. so bike riding greatly increased. In addition, people ate less. What effect did these changes (more exercise, less eating) have on health?

You know what is supposed to happen: Better health. Walter Willett, the Harvard epidemiologist, wrote a commentary about the study that concluded “The current findings add powerful evidence that a reduction in overweight and obesity would have major population-wide [health] benefits.” In other words, Willett said that what happened supports conventional beliefs.

But it didn’t. In several ways, what happened contradicts conventional beliefs.

1. A popular belief is that exercise causes weight loss. However, the percentage of “physically active individuals” doubled from 1985 to 2010 (from about 30% to 60%). In spite of this, the prevalence of obesity considerably increased (from about 13% to 18%) at the same time. Apparently exercise is considerably less important than something else. I have never heard a public health advocate say this.

2. A graph showing rates of heart disease, cancer, and stroke (the three main killers) over the period showed no change in rates of cancer and stroke. In spite of big changes in both exercise and obesity. The rate of heart disease stayed constant during the period when obesity went down. It steadily dropped during the period of time when obesity went up. Apparently the factors that control obesity and the factors that control heart disease are quite different (contradicting the usual view that exercise reduces both).

3. There is no simple connection between diabetes and obesity. During the economic crisis, when the prevalence of obesity went down by half (from 15% to 7%) and exercise greatly increased, the prevalence of diabetes slightly increased . Only after the crisis did the usual correlation (more obesity, more diabetes) emerge.

4. The only lifestyle factor to have its conventional effect: smoking. When you stop smoking, you gain weight is the usual belief (which I also believe). The data definitely support this connection. A huge reduction in the fraction of people who smoke (from 30% to 10%) did not reduce cancer but did coincide with a great increase in obesity.

5. Cubans are doing something right, as shown by the considerable decrease in heart disease and diabetes deaths. Apparently they are also more health-conscious, as shown by much higher rates of exercise and much lower rates of smoking. (Assuming that cigarettes did not become too expensive.) They are getting fatter, too, but apparently that is less damaging than we are told.

Willett and the authors of the study look at subsets of the data and use theories about “time-lag” to draw reassuring conclusions. In fact, large portions of the data are not easily explained by conventional ideas, as I’ve shown. You can look at the data many ways, but to me the study makes two main points. 1. During a period when everyone was forced to do what doctors recommend (exercise more, eat less), health did not improve. 2. During a period (post-crisis) when obesity got steadily worse, health improved (heart disease rates went down, cancer stayed the same, diabetes mortality went down). Cuba is too poor for the improvement to be due to better high-tech modern medicine. Taken together, these findings suggest we should be more skeptical of what we are told by doctors and health experts such as Willett.

30 thoughts on “Cuban Data Refute Mainstream Health Beliefs

  1. Nice. There’s no animal study that shows a negative health effect from smoking. The global epidemiology on smoking is totally contradictory to the mainstream view.

    Clearly what the Cubans were eating was more important than how much.

  2. Guys, I would take any study coming from Cuba with a grain so salt. Having lived in Miami and knowing many refugees, including a nurse, the situation there is deplorable beyond words… Scabies being spread in hospital, dentists requiring bribes like soap before working on you… It is an experience so far removed from our (dare I say it) priviledged existence that might a well be mars. Potemkin study.

    –Ed

  3. Seth –

    I could not parse two data points you laid out. I have not read the original study. You say in #1 that “In spite of this, the prevalence of obesity considerably increased (from about 13% to 18%)” and then you say in #3 that “During the economic crisis, when the prevalence of obesity went down by half (from 15% to 7%)”.

    Thanks!

    Seth: Look at the dates associated with the two sets of percentages (13-18 and 15-7). They are quite different.

  4. Ed M.’s got a good point, but there’s a related, and larger one: communist governments are famous for faking statistics to make themselves look better.

    The CIA learned the hard way that trusting the official statistics coming out of the USSR was not a wise course of action.

    This one deserves a far larger grain of salt than Willett’s work usually requires!

    “…But Raúl Castro has demanded more accurate information since he stepped in for Fidel Castro, his ailing brother, in July 2006 and officially became president in February last year.

    “In a speech to parliament in 2006 he attacked shoddy data as “preventing us from knowing what has been done and what remains to be done”.”

    If Cuban statistics stink, you’d think Castro would know…

    https://havanajournal.com/business/entry/national-statistics-office-in-cuba-releases-more-business-and-economic-data/

  5. “This Wikipedia entry suggests that there are such studies:”

    As far as I can tell from the entry, I’ve seen all or nearly all of the studies listed.

    Painting tar on skin is not smoking. The only tumors that developed were in breeds that develop tumors everywhere, and due to tobacco’s stimulative effects on blood flow the tumors were somewhat larger in the lungs. Tracheotomizing dogs is obviously not going to improve their life expectancy. There were other handling problems with studies. Basically as long as the smoke didn’t reach asphyxiating levels, the animals who smoked always lived longer than the controls.

    Feel free to refute by providing one pdf that shows a clear negative result for smoking without cheating in some ridiculous way.

  6. Koanic — I’m not sure where this is going. Do you believe that it’s a myth that smoking causes health problems in humans? If it’s not a myth, then why wouldn’t you expect smoking to cause health problems in animals?

  7. I don’t disagree so much as I think the implied idea (that smoking is harmless) is very… unusual. I thought that the harmfulness of smoking was about as well-supported as any medical hypothesis can be (and consistent with my own personal experience of observing chain-smoking relatives dying from emphysema and cancer). I was asking you to provide more information. I have no PDFs to post.

  8. “I thought that the harmfulness of smoking was about as well-supported as any medical hypothesis can be”

    Now you have reason to suspect that it is not, and apparently that’s as far as it will go with you, which I’m fine with. Anyone else who wishes to provide a pdf proving causal link is welcome to do so.

  9. “Now you have reason to suspect that it is not’. Actually, I don’t — as you haven’t given me any reason. Not any substantial reason, anyway. I thought there might be something relevant on your homepage, but it all seems to be dedicated to blog posts about picking up women.

  10. Interesting read here: https://smokescreens.org/lungcancer.htm

    “Based upon what the media and anti-tobacco organizations say, one would think that if you smoke, you get lung cancer (a 100% correlation) or at least expect a 50+% occurrence before someone uses the word ’cause.’

    Would you believe that the real number is < 10% (see Appendix A)? Yes, a US white male (USWM) cigarette smoker has an 8% lifetime chance of dying from lung cancer but the USWM nonsmoker also has a 1% chance of dying from lung cancer (see Appendix A). In fact, the data used is biased in the way that it was collected and the actual risk for a smoker is probably less."

    Haven't fact checked the numbers, but if true, it is interesting.

  11. 1) “I thought that the harmfulness of smoking was about as well-supported as any medical hypothesis can be”: well, as well-supported as it can be in the inevitable absence of controlled experiment on humans.

    2) Eightfold, Adam; wouldn’t it depend on how much he smoked? And for how long? The rule I’ve seen quoted says that the 25-a-day smoker increases his risk of contracting lung cancer 25-fold. (Or perhaps that refers to his risk of dying of lung cancer: my memory isn’t clear on that.) How many years he has to smoke to qualify for “the rule of 25″ also escapes my memory. But the lack of any allusion to the extent of smoking in your quotation makes me leery of it. And as for its source, I just guffawed at “It first appeared on the Journal of Theoretics”.

  12. “well, as well-supported as it can be in the inevitable absence of controlled experiment on humans.”

    False, it is not established by controlled studies in animals, as I have stated.

    For example, it could be that there’s something generally carcinogenic in the USA, and the bloodflow stimulating effects of tobacco merely grow the tumors faster in the lungs compared to other parts of the body. Or that tobacco alone doesn’t cause cancer, but only in combination with some aspect of the American diet. It could be like sunshine and melanoma – if in other places in the world people get lots of sun without getting skin cancer.

    There is no way it is a very well established medical fact, UNLESS someone can provide a simple animal study proving causation.

  13. “False, it is not established by controlled studies in animals, as I have stated.” Don’t be silly, nobody gives a hoot whether smoking would kill animals. The question is whether it kills people, and the only evidence that would be conclusive would be controlled experiments on people. Since those can’t be done, people have to settle for the inconclusive but highly suggestive results of epidemiology.

  14. While we’re on the subject of your silliness, Koanic, why the parochialism of your use of “USA” and “American”: aren’t you taking American Exceptionalism a little far?

  15. You’re wrong. Cancer is a very straightforward disease to induce. If cigarettes don’t give cancer to monkeys or mice, they won’t to humans either.

    Seth: How do you explain the strong association between smoking and lung cancer? With high rates of smoking (e.g., 2 packs/day) the association is very strong (compared to other epidemiological associations). With low rates of smoking (e.g., a cigarette/day) it is entirely possible that smoking is beneficial, as this book argues.

  16. If I recall correctly, the cancer smoking connection looks compelling when you take a naive look at American epidemiology snapshot, but fails to hold when looking at time series or international comparisons, as you partially discovered with Cuba. The “1/d healthy, 2 packs/d unhealthy” hypotheses *really* doesn’t fit the international data, since other countries tend to smoke much more than the US, yet have far less cancer. The data fits a melanoma type hypothesis much better – American doctors rightly tell Americans to stay out of the sun, but sun doesn’t actually cause cancer for more paleo countries or for people eating more paleo diets. Quite the opposite, sun is actually healthy. This would explain why animals who smoke live longer in properly controlled experiments.

    “Apparently, arsenic causes cancer in humans but not in animals.”

    Key word, apparently. What you should have said is there is a correlation between arsenic exposure in humans and cancer. I have no information about whether this correlation is reliable enough to be considered established without any controlled experiments to back the causal link.

  17. The cancer-causing properties of smoking were first discovered in pre-war Germany. Apparently those abroad who noticed the results rejected them on the grounds that they probably were just pandering to Hitler’s dislike of smoking. So the study that changed everything was a postwar British one by Bradford Hill and Doll. At the very least, then, you have to explain why smoking apparently mows down Krauts and Brits and Yanks.

    I wouldn’t be surprised if smoking affects different races differently, even races as similar as, say, Germans and Italians. Even if one accepted the idiocy that race is just a social construct, one could look at habits – including diet – that varied among, say, the European nations, but one would need to come up with a hypothesis as well supported and biologically plausible as the smoking hypothesis. Still, never say never, eh?

  18. The origination of the theory in three countries does not mean the theory is correct in three countries. Furthermore, this is a logical fallacy:

    “but one would need to come up with a hypothesis as well supported and biologically plausible as the smoking hypothesis.”

    I certainly do have my own hypotheses, better informed than those here, but I do not need to advance them. I am content to shred the logical errors of the defenders of the status quo view, which I have done. That nobody has offered evidence to alter my opinions strengthens my estimation of their accuracy.

    It is precisely this sort of thinking that has permitted the fat theory of obesity to dominate.

  19. As another example, there is much talk about how a sedentary lifestyle is bad, but my own observation is that a sedentary lifestyle has no impact on my health. At most, modest exercise when healthy is nice but not necessary, and overtraining is quite bad. Instead, I have observed a very strong correlation between being sick and being sedentary, with the causation running the other way. Therefore I conclude the epidemiological emphasis on the health benefits of exercise for the non-obese is mostly garbage. Rather, when one is healthy one will naturally not be sedentary, in the sense of at least walking around, up stairs, etc. The only exception would be extremely long working hours at a desk. If humans are adapted to long periods of inactivity during e.g. winter, then evolutionary biology supports my conclusion.

  20. haha love how these comments are completely off-topic
    you should see koanic on his youtube channel, smoking like it’s his day job

  21. When I say garbage, I mean it is positively harmful. Not that there aren’t benefits from exercise, but people who are sedentary are probably unhealthy, and therefore need to be sedentary, aka rest. Telling them to exercise expends or overexpends their limited energy resources, preventing them from taking actions that would actually make them healthier, such as improving diet and environment, getting more sleep, or whatever. Given the many documented positive effects of smoking, it is likely that the correlation between sick people and smoking is similar to the correlation between sick people and being sedentary.

  22. Difficult to interprete data indeed. But after reading the original article I have to disagree with a few of your points:

    > 3. There is no simple connection between diabetes and obesity.
    > During the economic crisis, when the prevalence of obesity
    > went down by half (from 15% to 7%) and exercise greatly
    > increased, the prevalence of diabetes slightly increased. Only
    > after the crisis did the usual correlation (more obesity, more
    > diabetes) emerge.
    This is true for prevalence – but not for incidence. I.e. people were not cured from diabetes, but fewer got sick. This shows up clearly.

    > 2. A graph showing rates of heart disease, cancer,
    > and stroke (the three main killers) over the period
    > showed no change in rates of cancer and stroke.
    There is no graph showing the rates of these diseases – the graph shows the mortality attributed to these diseases. Makes a big difference when thinking about whether the “time lag” hypothesis is believable (inho it is for mortality much more than for prevalance). But also making it even more difficult to interpret the data, because changes in treatment for these conditions (e.g. treatment for high blood pressure) could also affect the mortality by a lot.

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