2. Lift. Do strength training. Twice a week Four movements X 3-5 sets X 3-5 reps at 80% one rep max is good
Every podcast, journal or book that I have read on health and upstream work boils down to these few steps. If u can get them right, u will be in great shape. A thread
2. Lift. Do strength training. Twice a week Four movements X 3-5 sets X 3-5 reps at 80% one rep max is good
4. HIIT once a week is good to improve anaerobic capacity
5. Sunlight - One of the most important thing that u can do for ur health is spending some time early in the morning
6. Protein- Make sure to get in 1.5-2gm protein per kg body weight.
7. Fibres - Aim to have 15 gms fibre per 1000 calorie. Half plate every meal preferably should be veggies.
9. Processed Sugar best avoided.
10. Fasting has its own advantage but u can do without it if u are managing ur calories. If u eat ur protein and fibre , u will not feel the hunger for rightly processed carbs
12. Sleep - 7-9 hours. Dark and cold room. Avoid heavy food 2-3 hours before slew. Shut off electronics 2 hours before.
12. Chew food. Eat mindful. 20-30 chews.
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Public Health Scholarships
This may help for those considering MS/PhD in Public Health
1. The Erasmus Mundus Joint Master Degree in Public Health in Disasters
https://t.co/1Z5qpstsSu
2. Afya Bora Global Health
3. Carl Duisberg Scholarships
https://t.co/HnNXdbWBxy
4. Commonwealth Scholarships for Developing Countries
https://t.co/3fWGf5b2OH
5. Fellowships in Public Health & Tropical
6. Fellowships to Promote Mental Health Journalism
https://t.co/MVV9PFsBJ1
7. 2021-22 Jeroen Ensink Memorial Fund
8. Paul S. Lietman Global Travel Grant for Residents & Fellows
https://t.co/qK76R495QT
9. Global Health Internships and Funding
https://t.co/FD9Gh2wXvO
10. Kofi Annan Global Health Leadership
11. MA in European Public Health
https://t.co/5x0Vr7b1j8
12. MSc in Public Health Scholarships - Maastricht University,
This may help for those considering MS/PhD in Public Health
1. The Erasmus Mundus Joint Master Degree in Public Health in Disasters
https://t.co/1Z5qpstsSu
2. Afya Bora Global Health
3. Carl Duisberg Scholarships
https://t.co/HnNXdbWBxy
4. Commonwealth Scholarships for Developing Countries
https://t.co/3fWGf5b2OH
5. Fellowships in Public Health & Tropical
6. Fellowships to Promote Mental Health Journalism
https://t.co/MVV9PFsBJ1
7. 2021-22 Jeroen Ensink Memorial Fund
8. Paul S. Lietman Global Travel Grant for Residents & Fellows
https://t.co/qK76R495QT
9. Global Health Internships and Funding
https://t.co/FD9Gh2wXvO
10. Kofi Annan Global Health Leadership
11. MA in European Public Health
https://t.co/5x0Vr7b1j8
12. MSc in Public Health Scholarships - Maastricht University,
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%)
👇
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And smile XRP-eyed faces also appear related to Egypt. In particular, to the Eye of Horus. https://t.co/i4rRzuQ0gZ 5/*

I believe that @ripple_crippler and @looP_rM311_7211 are the same person. I know, nobody believes that. 2/*
Today I want to prove that Mr Pool smile faces mean XRP and price increase. In Ripple_Crippler, previous to Mr Pool existence, smile faces were frequent. They were very similar to the ones Mr Pool posts. The eyes also were usually a couple of "x", in fact, XRP logo. 3/*

The smile XRP-eyed face also appears related to the Moon. XRP going to the Moon. 4/*

And smile XRP-eyed faces also appear related to Egypt. In particular, to the Eye of Horus. https://t.co/i4rRzuQ0gZ 5/*
