Thursday, March 3, 2011

Dietary Fat and Breast Cancer, Part 1

Ah, dietary fat.  So delicious, yet so frowned upon.  If you look hard enough, you can find dietary fat associated with just about anything out there, from heart disease, to diabetes, to colon cancer, even in-grown toenails (not really).  But the breast cancer link is something I've heard about for years in the media, and from talking to people who watch too much local news.  A few weeks ago, in one of my classes, my professor showed us a graph of the relationship between dietary fat intake and prevalence of breast cancer by country. Here it is... you'll probably have to click on it to view the full-size version.


I found this one through a Google search.  Interestingly, the two points that don't seem to fit in line with the others, South Africa and Israel, were left out of the graph we saw in class, I guess my professor gave them the Ancel Keys treatment... but that's not the point here.  At first glance, this looks like a pretty strong relationship.  The more fat a nation eats, the higher its rate of death from breast cancer.  And even though this is just a correlation, meaning no cause and effect can be determined, it certainly piqued my interest.  I'm always very skeptical any time a study blames fat for anything; I find it impossible not to be after reading Good Calories, Bad Calories.  And I began to wonder, what else could possibly account for this correlation?  And that's when it clicked.  Sunlight.

If you look closely at the graph, the countries that consume less fat and have less mortality from breast cancer tend to be warmer climates, while the ones that consume more fat and have more mortality from breast cancer are colder climates.  Knowing that vitamin D (from sunshine) seems to have strong anti-cancer properties, of course the countries that get more sun would have less mortality from breast cancer.  If you're interested, watch Dr. Mercola's lecture on vitamin D, I don't want to get into the details here.  So I decided to plot this information in an excel graph.  I estimated the degrees of latitude from the equator for each country, and plotted that against breast cancer mortality rates.  Here's what I came out with...


That's what is called a confounding factor.  Not quite as neat of a correlation as the dietary fat graph, but there's clearly an association there.  So what does all this mean?  Does it mean vitamin D is the problem, not dietary fat?  I'd put my money on vitamin D deficiency playing a larger role in the deaths from breast cancer than dietary fat intake.  Actually, I'd argue against the very notion of lumping all types of fat into one group like this, doesn't make sense... but that's a topic for another day.  From an objective standpoint, you can't infer much of anything this data.  In observational studies like these, there are so many uncontrolled factors involved that you can't determine any cause and effect at all.  Here's a few other confounding factors that could be at play here...
  1. People who eat less fat tend to eat more vegetables.
  2. People in warmer climates are able to grow vegetables for a longer part of the year, so are more likely to eat them.
  3. People in cooler climates tend to eat more refined grains.
  4. People in warmer climates are more likely to get more physical activity.
I bet if I could plot that information in three more graphs, I'd get nice correlations as well.  The point is that when you see something on the local news about how breast cancer is associated with dietary fat, it doesn't mean dietary fat causes or even influences breast cancer.  It just means that the two occur at the same time.  Did you hear that fire trucks are associated with fires?  It's true, there's a strong association between fire trucks and fires, every time there's a fire, fire trucks are there... they must be causing the fires!  No...

What these observational studies are actually good for, however, is to form hypotheses that can be tested in more controlled trials.  It's been done in rats, and quite poorly I might add... we'll discuss that in part 2 of this series.

2 comments:

  1. Wow! What a fantastic post!

    You plugged in those latitude approximations & created the graph? Genius! It's unbelievable how similar the two are.

    I also love the firetruck comparison at the end. Classic.

    Keep up the great work man

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