May 092011
 

My recent post, What do the anti-vaxers want, generated a lot of commentary from the anti-vax crowd, much more that I had expected to be honest. I do not intend to go over that commentary here. What I intend to do is to analyse a study that was linked to by one of the anti-vax enthusiasts. This study has been making the rounds lately in the anti-vax crowd (hello Mike “The Health Danger” Adams) because it purports to show a relationship between vaccine doses received and Infant Mortality Rates (IMR). The study in question has been published here, and David Gorski has done a thorough review of it over at Science-Based Medicine blog. I will not repeat what he wrote.

What I intend to do here is to show how easily numbers can be manipulated to show a trend which can then be touted as proof of a relationship. We always say that correlation does not equal causation, yet that is hard for some people to grasp without an example. This study provided the perfect example to illustrate the concept. So without further ado, let us show why this study does not really show anything in connection with vaccines.

What does the study say?

You can read the full thing yourself, but in a nutshell the authors looked at IMR in the U.S. and noticed that for the year 2009 it ranked 34th. They then took the IMRs for the other 33 countries that did better than the U.S. Then they counted the vaccine doses recommended for each country (they used a funny way of counting DTaP as 3 doses each time, but we’ll let that slide for the sake of our exercise). Then they plotted, in a graph, the number of vaccine doses vs. the IMR rate for each country. The results were SHOCKING:

Clearly the line is inching upwards as more and more doses are added to the vaccine schedule. The equation of the best fit line is : Y =0.148x + 1.566

To explain that quickly it is saying that at x=0 (unvaccinated person) we’d expect 1.566 deaths per 1,000 live births within the first year of live. For every additional x (every additional dose added to the vaccine schedule) we can expect an additional 0.148 deaths/1,000 live births. Or, that would be the case if there was actual causation.

Clearly, the anti-vaxers have been saying for the past few days, an expanded vaccine schedule leads to more infant deaths. They maintain this graph shows causation. Too many, too soon might have been right after all. Or has it?

The Experiment

We will follow the authors’ footsteps and do what they did, in a quicker, dirtier way of course (this is a blog after all), but we will replace automobile deaths for Infant Mortality Rates. Starting with the original list of countries, I searched for auto death rates, by country for 2009 and I stumbled accross this site. I have not verified that the numbers they provide represent faithfully the WHO numbers. Again this is a blog, and this exercise is for illustration purposes only.

I took the rates (listed as #of auto deaths/100,000 population) for the same 34 countries the authors used in their study for the same year (2009). Data was not available for five countries out of the 34, so they were excluded. Two had higher death rates than the US, so in line with what the study authors did, I excluded those, and looked only at the other countries that had better/lower death rates than the US, a total of 26 countries. I then plotted vaccine doses vs. auto deaths. The results may shock you.

This line is inching upwards too; not only that but it is doing so at a faster rate (slope=0.227 vs. 0.148 for IMRs). In other words if the study’s graph implied that adding 7 doses of vaccines leads to one extra death, this graph implies that it take only about 4.5 doses of vaccines to lead to an extra auto death, presumably a good number of years after the fact, since the assumption is that in most countries infants don’t drive. Apparently vaccines lead to more auto deaths, than infant deaths. That is if there was causation of course.

No one in their right track of mind, would say that the correlation thus showed between vaccine doses and auto deaths implies causation. This is a perfect example that correlation does not imply causation.

So why would someone deduce, from a weaker correlation (slope=0.227 vs. 0.148 for IMRs), that vaccines affect Infant Mortality Rates? Would it not make more sense that if we cannot trust the stronger correlation, the weaker one is even less worthy of our trust?

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  22 Responses to “Vaccines and auto deaths: a.k.a I can play with Excel too”

  1. You can show similar correlation between traffic fatalities and importation of lemons from Mexico. That data shows an extremely tight correlation (R^2~0.96).

    –Drew

  2. Excellent!
    Good point well made…
    Perhaps this could be the start of a series of posts (hell, why not even dedicate a while website to it) about ridiculous conclusions a good bit of data mining can find?

  3. Grrr, “whole”, not “while”! Typing on a phone sucks…

  4. Lies, damn lies, and statistics. :)

  5. i still want to know about microwave popcorn consumption & infant mortality

  6. Given that some anti-vaxxers have included “died in a car accident immediately after receiving HPV vaccine” as vaccine related deaths, I’m not so sure your reductio ad absurdum argument is going to work with them.

    • What? Are you serious?

      • Yes, the antivaxxers take their data from that system that records ALL deaths & serious injury after a certain amount of time post vaccine. That includes people who die in auto accidents, swimming accidents, and other totally unrelated events.

        For example, the antivaxxers went ballistic over 9 girls dying in India after they introduced the HPV vaccine. Out of those 9, several girls were suicides, one was drowning, and, I think 3 were death from venomous snake bites. Not a single girl out of that 9 actually died from a health complication that *could* have been linked to the vaccine, even erroneously. Pointing that out only resulted in comments completely ignoring that and repeating “but 9 girls DIED!”

        • And, of course, accusations of being a shill for Big Pharma and/or snookered by the Establishment’s evil propaganda and/or being blind to the conspiracy to kill all the young girls.

          It was fun to see them backpeddle and stutter when they challenged me to put my own life on the line & get vaccinated, to which I promptly responded that I was, in fact, completely current on all my vaccines, including the voluntary ones (yay TDaP at Dragon*Con!)

      • Yup. I’ve seen that argument too. The anti-vax movement seem to latch onto anything at all which can be twisted to prove their point.

      • 1. Don’t you know that everything reported to VAERS is the absolute gospel truth? Even turning into the Hulk.

        2. Don’t you know that a settlement or award in the National Vaccine Injury Compensation Program = “scientific proof” or “the government has conceded” that vaccine X “causes” condition Y.

  7. I think Vaccines are causing increase in my power bill. Every time I have another kid and vaccinate them my bills start going up. Especially in winter where vaccines effect power bills the most.

    • Just wait when they get their first Tdap and/or HPV vaccine when they become teenagers. Your water bills will skyrocket!

  8. Glad you find this all funny. Hope you all never have the life of living with a vaccine inured child.

    • Using a reductio ad absurdum argument doesn’t mean that you find the opposing argument funny. Further, it’s possible to find an argument funny while not finding the subject of the argument funny.

    • TT, I have disease injured child. So please stop clutching your pearls.

  9. [...] demonstrated time and time again as bloggers find correlations between unrelated things, such as vaccines and automobile deaths and the rise in global temperatures and the number of [...]

  10. There’s another reason that the US has a higher infant mortality rate. They measure differently from other countries, so that the number is higher than if they used the tighter criteria of other countries.

    That’s why the WHO recommends against using the raw numbers as a basis for comparison.

  11. We have provided all the data that we utilized for the analysis of IMR and vaccine doses–so there is transparency in our study, allowing any and all individuals to do the analysis completely independently–using appropriate/valid statistical techniques. Epidemiologists and biostatisticians agree that nations reporting just a few infant deaths should be excluded since this translates into extremely wide confidence intervals and IMR instability. Health department policies typically include such cautions concerning the use of such data. Please divide the data about the mean IMR value and mean (or median) number of vaccine doses and perform an odds ratio analysis and see if the trend is not confirmed. Please feel free to perform any longitudinal analyses as well and expand the selection of countries if desired.

    For example, one researcher wrote the following: “I found data on child poverty rates, low birth weights, breast feeding rates, teenage fertility rates, births out of wedlock rates, age at first marriage, percent of divorces with/without children involved, total fertility rates, pertussis incidence rates, and the mother’s index on many of the same nations that are given in your article. When I controlled for each of these factors, none of them lowered the partial correlation below 0.62 even though child poverty rate, pertussis vaccination rate, and teenage fertility rate were significant predictors of IMR. This confirms your study’s findings very strongly!”

    • Mr. Goldman, you will find a more thorough analysis of your mangled data at Vaccines and infant mortality rates: A false relationship promoted by the anti-vaccine movement. Sorry, you cannot respond there, but you did wait nine months before commenting.

      Oh, and I will remind others that Mr. Goldman’s PhD is in computer science, and not from an accredited university:

      Moreover, diploma mills and other unaccredited schools modify their billing practices so students can obtain payments for degrees by the federal government. Purporting to be a prospective student, our investigator placed telephone calls to three schools that award academic credits based on life experience and require no classroom instruction: Barrington University (Mobile, Alabama); Lacrosse University (Bay St. Louis, Mississippi); and Pacific Western University (Los Angeles, California). These schools each charge a flat fee for a degree.

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