GLUTEAL AMNESIA, also known as the "dead butt syndrome" simply means:
➡️ Your gluteal muscles have been "unused" for so long that they now fail to activate whenever your body needs them to
🔥The unexpected consequence of too much sitting 🔥
The negatives of a sedentary lifestyle are widely known❗️
One issue that doesn't get mentioned enough is GLUTEAL AMNESIA, also known as the "dead butt syndrome".
Thread - Read more 👇
GLUTEAL AMNESIA, also known as the "dead butt syndrome" simply means:
➡️ Your gluteal muscles have been "unused" for so long that they now fail to activate whenever your body needs them to
Role of the Glutes:
➡️ Play a major role in the way our body moves
➡️ Not just there for aesthetics
➡️ Crucial for keeping our torsos upright, moving/rotating of the thighs & walking/running
GLUTEAL AMNESIA ⁉️
➡️ Glutes get so weak that they forget to activate
➡️ Consequence: Other muscles need to compensate - such as your lower back muscles or hip flexors
➡️ This can cause all sorts of problems such as lower back pain, knee pain & poor posture
More from Health
This is a limited point about availability of efficacy data for vaccines under development in the context of the approval for CovidShield and Covaxin in India.
There have been many so-called experts on the idiotbox opining about apparent availability of P III data which 1/n
2/n apparently the SEC had access to based on which it "supposedly" approved Covaxin. Another argument that is prevalent is other regulators (US FDA and MHRA) also approved vaccines based on P II data alone. Let me give you a few facts so that you can make your own decision.
3/n The protocols for both mRNA vaccines are publicly available. You can check. Both protocols *define* when the interim analysis will be done. This is not subjective. They clearly define how many infections need to be documented before the Data Safety Monitoring Board meets.
4/n Find the protocols for the bridging study for CovidShield and Covaxin and look for a similar milestone.
Here is one set of efficacy data post the interim analysis of a mRNA vaccine.
Source: https://t.co/BAPnP3PxEb
5/n This data was analyzed post the interim analysis where the blind was broken by the DSMB. Now ask yourself this question:
How does the SEC, or the sponsor of these studies, or the experts who are offering their opinion liberally on the idiotbox know what the efficacy is
There have been many so-called experts on the idiotbox opining about apparent availability of P III data which 1/n
2/n apparently the SEC had access to based on which it "supposedly" approved Covaxin. Another argument that is prevalent is other regulators (US FDA and MHRA) also approved vaccines based on P II data alone. Let me give you a few facts so that you can make your own decision.
3/n The protocols for both mRNA vaccines are publicly available. You can check. Both protocols *define* when the interim analysis will be done. This is not subjective. They clearly define how many infections need to be documented before the Data Safety Monitoring Board meets.
4/n Find the protocols for the bridging study for CovidShield and Covaxin and look for a similar milestone.
Here is one set of efficacy data post the interim analysis of a mRNA vaccine.
Source: https://t.co/BAPnP3PxEb
5/n This data was analyzed post the interim analysis where the blind was broken by the DSMB. Now ask yourself this question:
How does the SEC, or the sponsor of these studies, or the experts who are offering their opinion liberally on the idiotbox know what the efficacy is
You gotta think about this one carefully!
Imagine you go to the doctor and get tested for a rare disease (only 1 in 10,000 people get it.)
The test is 99% effective in detecting both sick and healthy people.
Your test comes back positive.
Are you really sick? Explain below 👇
The most complete answer from every reply so far is from Dr. Lena. Thanks for taking the time and going through
You can get the answer using Bayes' theorem, but let's try to come up with it in a different —maybe more intuitive— way.
👇
Here is what we know:
- Out of 10,000 people, 1 is sick
- Out of 100 sick people, 99 test positive
- Out of 100 healthy people, 99 test negative
Assuming 1 million people take the test (including you):
- 100 of them are sick
- 999,900 of them are healthy
👇
Let's now test both groups, starting with the 100 people sick:
▫️ 99 of them will be diagnosed (correctly) as sick (99%)
▫️ 1 of them is going to be diagnosed (incorrectly) as healthy (1%)
👇
Imagine you go to the doctor and get tested for a rare disease (only 1 in 10,000 people get it.)
The test is 99% effective in detecting both sick and healthy people.
Your test comes back positive.
Are you really sick? Explain below 👇
The most complete answer from every reply so far is from Dr. Lena. Thanks for taking the time and going through
Really doesn\u2019t fit well in a tweet. pic.twitter.com/xN0pAyniFS
— Dr. Lena Sugar \U0001f3f3\ufe0f\u200d\U0001f308\U0001f1ea\U0001f1fa\U0001f1ef\U0001f1f5 (@_jvs) February 18, 2021
You can get the answer using Bayes' theorem, but let's try to come up with it in a different —maybe more intuitive— way.
👇
Here is what we know:
- Out of 10,000 people, 1 is sick
- Out of 100 sick people, 99 test positive
- Out of 100 healthy people, 99 test negative
Assuming 1 million people take the test (including you):
- 100 of them are sick
- 999,900 of them are healthy
👇
Let's now test both groups, starting with the 100 people sick:
▫️ 99 of them will be diagnosed (correctly) as sick (99%)
▫️ 1 of them is going to be diagnosed (incorrectly) as healthy (1%)
👇
Some thoughts on this: Firstly, it might be personal preference, but I am not keen on this kind of campaign as I feel like it trivialises cancer. Sometimes the serious message gets lost because people are sharing pics of cats or whatever and the important context is gone.
More importantly, the statistic being used in the campaign is misleading. It says 57% of women put off cervical screening if they can't get waxed. But on further investigation, that's not accurate.
The page here goes on to say "57% of women who regularly have their pubic hair professionally removed would put off attending their cervical screening appointment if they hadn’t been able to visit a beauty salon."
So the 57% represents a concern not across the whole population of women, but only those who regularly get waxed. So how big of an issue is this across the whole population? And what else is stopping people getting smears?
I think campaigns for cancer screening are really tricky because there is so much nuance that often doesn't fit into a catchy headline or hashtag. It's certainly not easy and is part of a bigger conversation.
It\u2019s #CervicalCancerPreventionWeek \U0001f499
— myGP (@myGPapp) January 18, 2021
Here\u2019s how you can help to raise awareness:
\U0001f431 Share an image of the cat that best reflects your undercarriage/flower/bits (technical term vulva!) current look.
#\u20e3Use the Hashtag #myCat.
\U0001f46dTell and tag your friends to let them know. pic.twitter.com/8aHf96ynjT
More importantly, the statistic being used in the campaign is misleading. It says 57% of women put off cervical screening if they can't get waxed. But on further investigation, that's not accurate.
The page here goes on to say "57% of women who regularly have their pubic hair professionally removed would put off attending their cervical screening appointment if they hadn’t been able to visit a beauty salon."
So the 57% represents a concern not across the whole population of women, but only those who regularly get waxed. So how big of an issue is this across the whole population? And what else is stopping people getting smears?
I think campaigns for cancer screening are really tricky because there is so much nuance that often doesn't fit into a catchy headline or hashtag. It's certainly not easy and is part of a bigger conversation.
