Perhaps people who are either predisposed toward unhealthy outcomes, or are currently experiencing them (whether they realize it or not) are more sedentary. Correlation does not establish causation.
"Sitting correlates to Thinning in certain brain regions"
Can't this brain region become too large? What if the area is enlarged due to inflammation/swelling and these people with "thinning" are those without that problem?
If the brain is too large it is considered a problem: https://en.wikipedia.org/wiki/Megalencephaly
This guy apparently has the second largest brain ever measured, and he was a serial killer: https://en.wikipedia.org/wiki/Edward_H._Rulloff
There is some optimal size for this region when it comes to certain functions, probably relative to the size of other regions. That size is probably suboptimal when it comes to other functions and there are tradeoffs going on.
The press release seems to be assuming that thinner is bad automatically.
But you're right on the last point though, about assuming thinner is bad automatically. Heavy and chronic cannabis usage has been linked to an increase in density, but a reduction in total volume, which resulted in a slight overall decrease in IQ. The takeaway from all this being: Cognitive function is affected by a variety of parameters and we got more neuroscience to do still.
I wouldn't put much stock into these type of non-quantitative explanations wherein "this makes that go up which makes this go down", etc.
Usually the researchers measure a bunch of different things, analyze the data in a bunch of different ways, and only publish whatever is "significant". This works at the single lab level and multi-lab level since the "non-significant" results are considered boring and don't get published. By "usually" I mean this is standard behavior. You can call it p-hacking, file drawer effect, and more recently "forking paths":
http://andrewgelman.com/2017/12/29/forking-paths-plus-lack-t...
>"Cognitive function is affected by a variety of parameters and we got more neuroscience to do still."
Sure, that was the case before these studies were done too though.
Well, it's not unreasonable.
I don't know of any literature that says that a sedentary lifestyle is healthy for the brain, but a lot of it has found the opposite. I would like to avoid anything that reproduces the neurological effects of being sedentary.
Here are two I found:
>"More sedentary behavior was strongly predictive of more depressive symptomatology and, unexpectedly, of better cognitive performance." https://journals.humankinetics.com/doi/pdf/10.1123/japa.13.3...
>"Self-reported sedentary behavior was related to better performance on one cognitive task (trails A; p < .05)." https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4861254/
Obviously these are "undesirable" results, so you have to look a little bit deeper to find them.
Sedentary behavior associated with reduced medial temporal lobe thickness in middle-aged and older adults http://journals.plos.org/plosone/article?id=10.1371/journal....
To calculate thickness, for each gray matter voxel we computed the distance to the closest non-gray matter voxel. In 2D-space, for each voxel, we took the maximum distance value of the corresponding 3D voxels across all layers and multiplied by two. Mean thickness in each subregion was calculated by averaging thickness of all 2D voxels within each region of interest.
[0] http://journals.plos.org/plosone/article?id=10.1371/journal....
It does sound like quite a convoluted process but I don't see where you are getting anything like "density" from that description.
Also, reading the methods closer makes me think these are cherry picked results:
>"Once segmentation is complete, the original images are interpolated by a factor of 7, resulting in a final voxel size of 0.39 × 0.39 × 0.43 mm. Next, up to 18 connected layers of gray matter are grown out from the boundary of white matter, using a region-expansion algorithm to cover all pixels defined as gray matter."
Why 7? Why 18? These magic numbers shouldn't be there without some kind of sensitivity analysis.
Finally, you can see the dimensions of the voxels is something determined by their methods, not a property of the brains.
>"for each gray matter voxel we computed the distance to the closest non-gray matter voxel."
I do admit that whatever they did is difficult to follow without seeing images of the transform etc (and figure 1 does not help), but the idea they are somehow measuring density seems impossible to me.
I thought maybe you had some expertise regarding how they processed the data that could somehow make this (extremely strange thing) happen, but you have not demonstrated it. I guess I do not know for sure what they did without seeing the code, but if that is what they measured it is the most bizarre thing I have heard of when it comes to analyzing MRI data.
Regarding your comment about how incompetent I am, and how extremely strange this MRI analysis is:
Measuring cortical thickness by MRI is a standard technique in neuroanatomy since 15 years ago. And really, a quick search of the literature would have shown you this. But I suppose that's too much to ask.
I simply cannot imagine what you think is going on in order for them to be looking at "clumping" of gray matter as a proxy for density of the tissue via MRI and calling this "thickness".
>"Regarding your comment about how incompetent I am, and how extremely strange this MRI analysis is"
I thought perhaps you knew some technical detail about their analysis pipeline, but you still haven't mentioned anything technical... so I just don't have any idea what you are thinking.
>"Measuring cortical thickness by MRI is a standard technique in neuroanatomy since 15 years ago."
Sure, here is the first article I found regarding "cortical thickness":
"The shortest distance between the pial surface and the white/gray junction is the cortical thickness at each point." https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5561315/
That sounds exactly like what I would expect, nothing to do with density or clumping.