It’s a sort of “case-study lite” approach. I gave the students the following in a packet:
- An article talking about research which showed people born by C-section are at a 50% greater risk of obesity than those that weren’t, and speculating C-sections may be behind the obesity epidemic
- An abstract of that research study
- A chart showing growth of C-sections since 1970
- An article talking about why C-sections have increased since 1970 (It’s not for the reasons you think).
- A chart showing the growth of obesity over since 1970
For this scenario, you will play the role of an obesity researcher who has been asked by a hospital to see if there are extraneous variables in this study that were not accounted for. The hospital is trying to decide whether they should include the following sentence in their materials on C-section:
“Choosing to deliver your child by C-section may increase your child’s risk of future obesity.”
- Produce a brief predictor-outcome statement. What is predicting what? How is it measured? What is the magnitude and direction of the association?
- Using the charts, produce a statement on whether the U.S. gains in childhood obesity roughly mirror the growth in C-sections.
- Produce a statement on whether the base rate of C-sections is large enough to have the suggested impact on obesity.
- Produce a list of all potential lurking variables controlled for.
- Produce a list of some lurking variables not controlled for.
- Give your gut-level take on whether any of the potential lurking variables not controlled for might dramatically reduce the magnitude of the association, or potentially reverse it. If you believe one of the lurking variables could do that, name it, and explain why it might account for the apparent association.
As with many simulations, we’ve loaded the dice a bit here. The news articles we used had reference to some confounders, but we removed those references. There is a very obvious lurking variable, one which was later controlled for in a subsequent study which found no effect of C-section on obesity.
The background information on the growth of C-sections holds the key to understanding what’s going on. In that article, it explains much of the growth of C-sections is due to overweight mothers — expecting mothers who are overweight often have to have C-sections due to obesity or obesity related illness.
That’s a classic lurking variable scenario. Overweight mothers will be over-represented in the C-section group due to medical reasons. Due to genetics, overweight mothers will also have overweight children at a higher rate than mothers not overweight. So it is completely expected that the C-section group would have a larger percentage of children who grow up to be obese.
The one mistake I made running this was to run it too slow, and without stages. I would suggest you budget at LEAST 45 minutes for this activity, and rather than have the student groups report out all the questions at the end, have them report out the answers to the first half of the questions, then give them some more time to put together answers for the second half.
I ran this in a much more compressed time frame, and one of my eight groups got it, and another very nearly got it — which wasn’t bad. But ideally you’d have at least half the groups get in the vicinity of the answer (or produce other, equally compelling answers).
If you try it, tell me how it goes.