Thank you (and your soon-to-be brother-in-law) for the book rec. Queuing up the audiobook now lol.
I can't help but draw a parallel (which I'm sure has been drawn many times) between modern doctors' cognitive dissonance on weight science and ye olde doctors' repudiation of Joseph Lister, who implied they were doing harm this whole time by demonstrating how they could improve outcomes by sterilizing their tools.
Thank you! This is so well said. I have found the "ob*sity is a disease" paradigm so deeply entrenched in the culture of medicine that it's hard to even see it unless you look closely. It's just accepted as dogma. Very hard to argue against dogma.
I apologize for not having found the original paper. I was researching something related to a health condition and weight loss. The paper concluded that weight loss wasn't necessary to improve this health condition. Then the final paragraph said something to the effect of "We still think people should engage in weight loss to improve health." I am really annoyed I didn't keep the link.
Thank you for this excellent breakdown. It feels ever more important to look at, dissect, and make sense of the underlying reasoning within the systems that stigmatize and cause harm to us based on our size--because with weight loss drugs being constantly 'innovated' and then heralded as miracles, the media attention can be so loud. It is very frustrating, to see mainstream perspectives all speaking with one biased voice, and it's easy to feel defeated in the face of that supposed consensus. I find it helpful to think bigger picture like you do here, since we'll never improve things without rooting out the sources.
There are lots of ways in which research can be questionable. I always look first at the declaration of interests - who funds a paper tends to have a bearing on how the hypothesis is framed. The markers chosen can be so restrictive that it doesn't put the research in any kind of useful context. Then the statistical analysis gives huge scope for playing fast and loose with the data, as a lot of readers don't have sufficient understanding of statistics to identify anomalies. And finally sometimes the final analysis is just plain distorted.
Thank you (and your soon-to-be brother-in-law) for the book rec. Queuing up the audiobook now lol.
I can't help but draw a parallel (which I'm sure has been drawn many times) between modern doctors' cognitive dissonance on weight science and ye olde doctors' repudiation of Joseph Lister, who implied they were doing harm this whole time by demonstrating how they could improve outcomes by sterilizing their tools.
Thank you! This is so well said. I have found the "ob*sity is a disease" paradigm so deeply entrenched in the culture of medicine that it's hard to even see it unless you look closely. It's just accepted as dogma. Very hard to argue against dogma.
I apologize for not having found the original paper. I was researching something related to a health condition and weight loss. The paper concluded that weight loss wasn't necessary to improve this health condition. Then the final paragraph said something to the effect of "We still think people should engage in weight loss to improve health." I am really annoyed I didn't keep the link.
Thank you for this excellent breakdown. It feels ever more important to look at, dissect, and make sense of the underlying reasoning within the systems that stigmatize and cause harm to us based on our size--because with weight loss drugs being constantly 'innovated' and then heralded as miracles, the media attention can be so loud. It is very frustrating, to see mainstream perspectives all speaking with one biased voice, and it's easy to feel defeated in the face of that supposed consensus. I find it helpful to think bigger picture like you do here, since we'll never improve things without rooting out the sources.
There are lots of ways in which research can be questionable. I always look first at the declaration of interests - who funds a paper tends to have a bearing on how the hypothesis is framed. The markers chosen can be so restrictive that it doesn't put the research in any kind of useful context. Then the statistical analysis gives huge scope for playing fast and loose with the data, as a lot of readers don't have sufficient understanding of statistics to identify anomalies. And finally sometimes the final analysis is just plain distorted.
This is a BRILLIANT post as always Ragen - thank you! The closed loop parallel yes!