The abstract begins, "Growing evidence supports early eating to control appetite and energy balance". What does that mean? My unskilled reading of it is that there is recent evidence that eating breakfast helps with weight loss. But I'm confused because there was a 2019 meta-analysis that found that eating breakfast does NOT help with weight loss. https://www.bmj.com/content/364/bmj.l42
We saw this effect in a small study, so it's worth doing a larger study.
It's worth publishing because it's evidence and motivation to do further studying. And if you're asking "Why not start large?" the answer is obvious: money.
Especially in dietary studies. You either spend a lot on high quality, controlled studies where you can nail down parameters (takes a LOT of labour), or you spend on facilitating much larger studies where you make up for precision and control with volume.
There are trade offs in either case and some types of research where one is more suitable than the other. But the best case is a combination of the two, and it's exceedingly rare.
Maybe there are other options but this seems to be the polar nature of these studies from what I've seen.
The paper includes a section on power analysis which justifies the sample size (although the justification is for a sample of 20, they recruited 25 eligible participants and lost 6 in screening).
Some points though:
- A within-participants study has inherently more power than a between-subjects study. Trying two different diets with the same person removes a lot of variables that you'd need to control for in between-subjects studies (and yes, they randomized the order of intervention and found no difference based on order)
- It looks like this was conducted in a way that supported compliance with the protocol, and using analysis techniques that would be unwieldy for a much larger sample size.
Even with N=19, the reported significance is very compelling.
They used a crossover design, so each subject served as their own control. Not a bad choice for trials like this as you gain a lot of statistical power with fewer participants than a parallel-arm, non-crossover design.
I feel like the regular weight loss group was? Since it isn't necessarily rocket science for having mostly men stay in an easily determinable caloric deficit to lose weight. (Women have usually would be harder due to more conditions and hormone interactions that make finding a TDEE not as simple.)
TLDR: A weight loss diet centered around a big breakfast yields weight loss results. That breakfast loaded with protein made you feel fuller and suppressed your appetite (which helps you follow a diet), where a fiber loaded diet produced more beneficial gut bacteria.
The study has a pretty small sample size, but it seems well designed and matches what you'd expect.
Who in their own mind decided that this is a "study" worth publishing?
You read
In actuality it is It's worth publishing because it's evidence and motivation to do further studying. And if you're asking "Why not start large?" the answer is obvious: money.There are trade offs in either case and some types of research where one is more suitable than the other. But the best case is a combination of the two, and it's exceedingly rare.
Maybe there are other options but this seems to be the polar nature of these studies from what I've seen.
Some points though:
- A within-participants study has inherently more power than a between-subjects study. Trying two different diets with the same person removes a lot of variables that you'd need to control for in between-subjects studies (and yes, they randomized the order of intervention and found no difference based on order)
- It looks like this was conducted in a way that supported compliance with the protocol, and using analysis techniques that would be unwieldy for a much larger sample size.
Even with N=19, the reported significance is very compelling.
Why not add a third high-fiber + high-protein group for example?
Soon we will have more participants in the HN comments for the study, than were studied in the study.
I'll see myself out.
The study has a pretty small sample size, but it seems well designed and matches what you'd expect.