Greg Mushen Profile picture
Nov 3 19 tweets 4 min read Read on X
Longevity is a game of avoiding chronic disease for as long as possible. The more diseases you accumulate over time, the shorter you will live.

Subsistence populations are largely free of chronic disease, and despite wildly different diets, there’s one metric they share 👇
Most chronic diseases are flux issues. If our inputs exceed our outputs, that’s when we start developing disease.
Insulin resistance

For example, insulin resistance (except in genetic disorders) occurs when we are in a chronic energy surplus.

Over time, fat build up in cells (primarily ceramides).

This can happen in muscle, our liver, our fat, etc. but the pattern is the same.
Insulin resistance is therefore mostly a flux problem.

Our inputs are too high relative to clearance.

We don’t clear enough glucose, this gets stored as fat, and over time, we become insulin resistant.
Atherosclerosis is largely the same.

When we ingest lipids, we increase our absolute secretion (there are exceptions).

We clear through reducing secretion and increasing clearance through LDL-R.

This is primarily done with movement, although, statins work the same way.
And once again, there are many genetic patterns that can impair this, such as APOE, APOB R3500Q, etc.

But outside of genetic clearance issues, the rule prevails.

The longer the lipids hang around (residence time), the higher the exposure, and lifetime exposure drives the risk.
The primary reason why subsistence populations are free of chronic disease is due to having flux balance.

The inputs are roughly equal to the output.

This ensures proper clearance, and less storage, so they have extremely low rates of insulin resistance, and heart disease.
This is even true of populations that have extremely high clearance thresholds, such as the Maasai.

They eat up to 100-200g of saturated fat, which increases their clearance requirements.

But they walk 12-16 miles per day, so they can clear most of it.

Despite this, they have some atherosclerosis. It’s just not at a level where their frequently die from it.
The Tsimane on the other hand, have diets lower in saturated fat.

They walk 18k steps per day through hilly jungle terrain.

This is enough for them to meet lipid clearance requirements, and they have the lowest recorded CAC levels ever recorded in a population.
So it’s not that diet doesn’t matter. It does.

It’s just that when diet elements exceed clearance, that’s when people get into trouble.
This can be roughly approximated by a metric called PAL, which stands for physical activity level.

It is a metric of TEE / BMR

TEE = total energy expenditure
BMR = base metabolic rate

Once this ratio is around 2.0, that’s when we see chronic disease drop dramatically.
When members of subsistence populations are moved to cities, we see this ratio drop.

Once it goes below 1.6, that’s when we start to see chronic disease rear its head: insulin resistance, higher blood pressure, etc.

Move them back, these start disappearing.
And we can see this in the chart.

TEE is remarkable consistent amongst populations.

But it’s the physical activity that will drive high PAL. Image
But this chart is somewhat misleading.

For example, Japan can have a higher PAL despite moderate movement because they have a high protein diet and smaller stature. So they can hit 1.8-1.9 just with this combo.

People in the US on the other hand have higher BMR because they are larger, but are sedentary, which lands them in the 1.6 range.
The larger you are, the more movement you will need to hit clearance requirements.

I’m 184 lbs, so to hit PAL = 2, I’ll need roughly 20k steps a day and a strength training workout because my BMR is higher.
Does it matter how you get there? Probably not.

Elite endurance athletes for example, can maintain an average PAL of 2.5 for the year. This likely is the upper human limit driven by the limits of training load and digestion itself.

But for us mortals, any combo of calorie burn will likely be sufficient.
The physical activity required to achieve this ratio is upstream from popular longevity metrics:

- Low resting inflammation
- High HDL/low ApoB
- Excellent endothelial function
- Vo2max in the upper quartile
- Low fasting insulin and glucose
- Low visceral fat

Outside of genetic issues, if you hit that PAL ratio, it’s almost certain you will hit the ideal metrics for all of these over time.
In my opinion, if you want a simple and single longevity metric, this is the one to track.

Give it a year, and watch your markers improve.
Health = clearance >= input

Longevity = sustained flux balance (PAL ~ 2.0)

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More from @gregmushen

Oct 29
Deconstructing CICO vs CIM: What Actually Drives Sustainable Fat Loss

Nearly every chronic disease traces back to poor metabolic health.

But when it comes to fat loss, two camps dominate: CICO vs CIM.

Which model actually holds up, and what’s sustainable long term? 👇
First is the CICO camp. This is the energy balance model.

If energy balance is negative, you will lose weight.

If energy balance is positive, you will gain weight.

This is empirically true, and I’ve outlined the entire model here:
CICO is also remarkably predictive.

As a case study, I outlined how we could predict how long weight loss would take with Angus Barbieri, who famously lost 276 pounds by not eating for over a year.
Read 17 tweets
Oct 28
Do low carb diets increase energy expenditure or fat loss independent of calories?

This is the central prediction of the carbohydrate-insulin model.

Lower insulin -> greater fat oxidation -> more fat loss.

But does it work in practice? 👇
Kevin Hall and Juen Guo analyzed 32 controlled feeding studies (563 participants) testing how carb-to-fat ratio affects body energy change when total calories and protein are the same. Image
Hall & Guo pooled ward and tightly controlled feeding trials where:

- Food intake was precisely provided.
- Protein was matched.
- Only carbohydrate <> fat ratio varied.
- Body composition and energy expenditure were measured directly.
Read 12 tweets
Oct 27
Deconstructing CICO

Many people say that “CICO is oversimplified”

But it’s one of the most misunderstood concepts in nutrition.

Here is how energy balance actually works, and how macros can change what you lose, not how much 👇
CICO is based on the first law of thermodynamics. That energy can neither be created nor destroyed.

Some say that this law only applies to closed systems. That is not true.
In its simplest form, CICO can be described by the equation:

ΔEbody = Ein - Eout

So the change in energy in the body is the difference between energy coming in and energy going out.
Read 19 tweets
Oct 22
Very interesting paper. For the past 6-7 years, there has been talk of a constrained energy model, where calories don’t scale linearly with physical activity. But this paper says the opposite. Why the conflicting data? 👇
First, some background. In 2016, Pontzer et al. studied subsistence populations.

When weight matched with sedentary westerners, they appeared to have the same TEE, despite the vast difference in movement (~17k steps versus mostly sedentary). Image
The thinking was that at a certain point, the body would start shutting down certain processes (inflammation, etc.) and allocate more energy to locomotion.

So the difference in calorie burn was explained by more locomotion in subsistence populations and less energy elsewhere (inflammation?) and less energy in locomotion in westerners and more energy elsewhere (inflammation?).
Read 14 tweets
Oct 20
One of the most confusing things about cholesterol is that it’s a dynamic system attempting to reach equilibrium.

The measures we use are snapshots of parts of the system.

Furthermore, at times, only parts of the system are talked about.

This leads to confusion 👇
Yes, LDL is causal. Given enough circulating LDL which contains ApoB, and enough time, ApoB will get trapped in the endothelia.

This is the initiating event for atherosclerosis.

Nothing else needed. Inflammation is not needed.

Only circulating LDL and time.
Yet, paradoxically, LDL isn’t the biggest risk factor.

Things like insulin resistance, high blood pressure, smoking, etc. are much higher risk factors to ASCVD than LDL alone.

Does this mean that LDL isn’t causal? No, it doesn’t.

LDL still matters.
Read 16 tweets
Oct 19
Is the ideal cholesterol 200?

This graph has been making the rounds on social media. It was from a Korean study with 12.8m people.

But is has some serious flaws, and the true ideal cholesterol is much lower 👇 Image
Problem #1 Reverse Causation

Certain diseases cause cholesterol to be lower: chronic inflammation, cachexia, liver dysfunction, frailty, and certain kinds of cancer.

So if someone enters the study, and they have one of these conditions, they are already unhealthy.
So if they die during the study, from one of those conditions, they will have low cholesterol, and this will make it look like low cholesterol is unhealthy, when in fact, the unhealthy condition they had caused the low cholesterol.
Read 15 tweets

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