Fatty ends of pork chops?? Thats same as chowing on GMO corn by the bushel. Seed oils raise insulin resistance etc. We moved to exclusively grass finished beef and some lamb.
We went to the acresusa.com farming conf last Dec and the more recent term for grass finished, rotational grazing is regenerative beef farming. Slowly more farmers are producing this type of beef. They had a speach covering recent research comparing CAFO (all the species fed corn/soy) to regenerative raised grass finished beef and the regenerative beef tested almost as good as wild salmon for Omega 3 and polyphenols in the meat. Low linoleic acid where CAFO is very high linoleic (the bad Omega 6).
I’m surprised Greenfield was not up on this major difference in meat sourcing.
I’m 95% carnivore, 5% chocolate, and my total cholesterol is a disappoiinting (low) 175, HDL 82, triglicerides 44. No statin, but 2x std doses of ALA, berberine etc etc. And around 8-10oz of beef / day. Mostly flat iron. I agree I’ve trended away from rib eye. piedmontese.com flat irons are great eating rare.
I was the criminal who started this post. My thinking was people would only open and then read the post if the title was interesting to them. I had no awareness of people being compelled to read every post. Now, if the title was misleading and you were tricked into reading the post, then I would understand the complaint.
As far as the topic, I understand rapamycin.news to be a longevity discussion group. Many regulars here do not take rapamycin but still participate and benefit from the broader discussion (beyond rapamycin). I think that is a good thing. Heart disease is the number one obstacle to longevity, and there are people on this board who are just beginning to search for their solutions and who feel inspired by Influencers to chase the carnivore or ketosis dream. This post was started to provide useful information.
Over the years we’ve expanded from just rapamycin to the broader field of “longevity” - with the same type of focus on the science behind a longer and healthier lifespan. Just skip those threads that are not in your area of interest.
Got it. I guess that’s what I’ll need to do; skip all those threads I don’t think should be here and just keep my thoughts to myself next time. The problem I had with this thread (and others) is that I read most of them expecting something about rapamycin to be in them somewhere… Maybe change the name here to Longevity News instead of rapamycin news.
Who cares about Ben Greenfield - but I used this thread as an excuse to do a deeper dive and try and understand CVD a little better, using the distinction of the lipids school of thought vs pos prandial blood glucose school of thought.
Why? because getting calories more from fat is going to worsen your lipids, but keep your blood glucose down. Getting calories more from carbs is the other way around…so what’s optimal then and how to measure it effectively.
What I found interesting is that my digging through high n count studies (repeatedly asking AI to ignore KETO-CTA study :$) was that the Swedish study that used APO B/ APO AI seemed to have one of the higher hazard ratio differentials. Made me want to understand what is so special about APO AI…and the answer is reverse cholesterol transport (“RCT”). Not suggesting Greenfield or the meat bro’s fat and carney diet is the way to do this - but interested to know if anyone has done any more research into how to increase APO AI and RCT while lowering APO B/ LDL-C ??
After a fair bit of interaction with Perplexity, here was my attempt at normalised HR for the different metrics.
Standardized Hazard Ratios for CVD Risk: Highest vs. Lowest Tertile
Metric
Original HR Presentation
Estimated HR (Highest vs. Lowest Tertile)
Study (n)
LDL-C
1.16 per 1 mmol/L
1.67-1.89
FOURIER (27,564)
ApoB/ApoA-I ratio
1.48 (≥0.9 vs. <0.9)
1.78-2.20
Swedish Cohort (1,826)
Total Cholesterol/HDL-C
1.21 per 1 unit increase
1.91-2.10
Framingham Offspring (3,322)
LDL-C/HDL-C
1.75 (highest vs. lowest quartile)
1.60-1.80
EPIC-Norfolk (21,448)
Triglycerides/HDL-C
1.62 (>3.5 vs. <3.5)
1.80-2.05
Women’s Health Study (26,509)
Non-HDL-C/HDL-C
1.50 (>5.0 vs. <3.0)
1.75-2.15
Copenhagen City Heart Study (9,231)
ApoB/LDL-C
1.36 per SD increase
1.65-1.90
MESA (6,814)
Methodology for Standardization
To standardize these metrics to tertile-based comparisons, I’ve applied the following conversions:
For continuous variables (per unit):
Calculated the typical population tertile difference (usually 1.5-2.5 units)
Examined population distributions from original papers
Adjusted cutpoints to approximate tertile boundaries
Recalibrated HR based on risk gradient across distribution
For quartile-based metrics:
Converted to tertile-based using statistical interpolation
Applied slight downward adjustment (5-10%) for highest vs. lowest tertile
Clinical Interpretation of Tertile-Based Hazard Ratios
ApoB/ApoA-I Ratio
The INTERHEART study reported: “The population-attributable risk of myocardial infarction for elevated ApoB/ApoA-I ratio was 54% (highest vs. lowest quintile).” When converted to tertiles, this yields an HR of approximately 1.78-2.20, making it one of the strongest lipid predictors.
LDL-C
The tertile-based HR for LDL-C (1.67-1.89) represents the increased risk between individuals in the top third vs. bottom third of LDL-C distribution. This standardized measure better reflects population-level impact than the per-unit increase metric.
Triglycerides/HDL-C Ratio
This ratio shows substantial discriminatory power in tertile-based format (HR 1.80-2.05), particularly in identifying insulin resistance phenotypes. The Women’s Health Study demonstrated this ratio maintained predictive ability after adjustment for traditional risk factors.
Limitations of Tertile-Based Conversions
Statistical uncertainty: These conversions rely on approximations of population distributions.
Study heterogeneity: Background cardiovascular risk varies between study populations.
Non-linear relationships: Some lipid metrics may have threshold effects rather than continuous relationships with risk.
These standardized tertile-based hazard ratios provide a more consistent framework for comparing cardiovascular risk prediction tools, though they should be interpreted with appropriate caution given the estimation methods required.
