The full picture may be a little more complex, though. I was at Queen’s a few weeks ago for a talk, and had a chance to chat with Louise de Lannoy, one of the authors of the 2015 study. She updated me on her latest work, and filled me in on the ongoing debate about individual response and the challenges in accurately measuring and analyzing it.
De Lannoy’s newest study was published in PLoS ONE a few days ago, and it provides further analysis from the experiment described in the 2015 study, in which subjects did 24 weeks of exercise with a combination of low or high volume and intensity.
In the original study, the outcome was aerobic fitness (what’s often called VO2 max), and in the group doing high volume (40 minutes per workout, five times a week) and high intensity (75 percent of VO2 max), everyone improved by a significant margin.
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The new study, in contrast, looks at insulin and glucose response, which are risk factors that typically precede Type 2 diabetes. It’s well established that moderate exercise improves these parameters on average—but does everyone improve?
De Lannoy’s results are sobering. The average results did show that both insulin and glucose response improved in the high-volume, high-intensity exercise. But looking at the individual results, only about 20 percent of the subjects showed significant improvements in these parameters, regardless of exercise group.
Why is this? Part of the explanation is that the researchers set a relatively high bar for what was considered a significant improvement. Based on the before-and-after measurements of the control group (which did no exercise), they estimated the typical day-to-day variation in these measures; a significant improvement, they argued, would be one that was more than twice the size of this typical variation.
If they used a lower threshold for improvement, like “anything above zero,” then there would be more responders—between 50 and 90 percent, depending on the exercise group. But with this approach, you would also have to conclude that 50 percent of the control group had made a “significant” improvement, which is illogical.
In a sense, you’re stuck with an inevitable conflict between minimizing false positives and false negatives, with no perfect answer. If you had a perfect measurement system, you’d probably conclude that more than 20 percent of people improved their glucose and insulin response, but considerably fewer than 100 percent.
When I asked de Lannoy about this, she said that they assume more than 20 percent of people improve, but that they can only be confident about the improvement in 20 percent of them. To correctly identify more responders, they would need to take multiple repeated measures—something that’s not cheap or easy either in a clinical or research setting.
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So where does this leave us on the overall question of non-response? I’m still inclined to believe…