Protein Study Fundamental Flaws


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  • Methionine/Glycine studies show only a minority of percentage improvements contrasted with calorie reduction.
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  • Hi Patrick

    By all means - I'm a fat, gristle and connective tissue consumer type, and don't go crazy on muscle meat alone, so happy enough with these inferences..... Notwithstanding the glycine goodies, the Protein Study remains risible.....anti-science at its best!

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  • Ivor ...

    Some bread crumbs for you to chew on - high protein ones ...

    the clue? IGF-1.
    The culprit? Methionine

    Methionine / Glycine imbalance in our diet may be the IGF-1 driving may equivalent of our n-6 / n-3 UFA imbalance.
    The cure? .... ' A fascinating but woefully little-known study in 2011 showed that in mice, supplementing with glycine—an amino acid found abundantly in connective tissue and gelatin and bone broth—had the exact same life-extending effect as restricting methionine. Without reducing calories or other amino acids, glycine supplementation increased the rodents’ lifespan, reduced fasting glucose and insulin, decreased IGF-1 levels, and nearly halved their triglycerides—the very perks that’ve variously been attributed to calorie restriction, protein restriction, and methionine restriction.'
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  • Hi James

    Yep, could be, but the only thing we can really assume is that old protein is standing around and looking bemused at the ludicrousness of what passes for 'science' these days (maybe even taking a moment to light up one of those cigarettes that Longo compared it to).

    As it happens, many of the subgroup characteristics are broadly similar: Race, Sex, Education, smoking etc

    Who knows - it's just all so irrelevant really, except for the real tragedy of misinforming the public with the blanket media coverage. On a final note, very insightful piece by Zoe Hargreaves earlier today (fair play - I should have caught that, oh well!):

    Hopefully this will get out properly in the media, it's run its technical course now to.............reductio ad absurdum.

    Best Regards
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  • Stratifying results by ethnic, socioeconomic, and protein source would probably explain a lot of the variation within groups. They arbitrarily grouped these people together and ignored possible explanatory details. It isn't even that hard to get socioeconomic data. All you need is an address or ZIP code and you can merge with the census block group data.

    A better way to approach this would be to identify statistically homogeneous cohorts and look for potential differences with protein consumption. But why would you, when you could just NOT do that and get your paper publish and posted in the Wall Street Journal...
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Protein Study Fundamental Flaws

  1. 1. A case study of confounding and associated scientific misinterpretation, highlighting the dangers of poor engineering inference, which can misinform the public and policymakers alike: The Study in Question: Low Protein Intake Is Associated with a Major Reduction in IGF-1, Cancer, and Overall Mortality in the 65 and Younger but Not Older Population Morgan E. Levine, Jorge A. Suarez, Sebastian Brandhorst, Priya Balasubramanian, Chia-Wei Cheng, Federica Madia, Luigi Fontana, Mario G. Mirisola, Jaime Guevara-Aguirre, Junxiang Wan, Giuseppe Passarino, Brian K. Kennedy, Min Wei, Pinchas Cohen, Eileen M. Crimmins, and Valter D. Longo Most of the interesting data is contained in the Supplemental Information Section, NOT INCLUDED IN THE PUBLISHED STUDY, but available at : 2013 Ivor Cummins BE(Chem) MIEI
  2. 2. Analysis of Baseline Data from the Study: I hypothesize that this is the small (6% of total): healthy eating, High-Vegetable, Low-Sugar, low-GI, low Diabetes, and incidentally “Low-Protein” cohort Medium/High Protein cohort has much lower cancer previous history - Why? Medium/High Protein cohorts struggling with HUGE diabetes history? Why? Medium/High Protein cohort struggling with diet control? (Bad US Junkfooders?) Medium/High bad diet survey responders far fewer calories?? (under-report their sodas etc?) Medium/High cohort less comfortable acknowledging they often eat more? Table S1 from the study Supplemental Information section Low Protein Intake Is Associated with a Major Reduction in IGF-1, Cancer, and Overall Mortality in the 65 and Younger but Not Older Population Medium Protein group lowest death overall – (except for Diabetes) 2013 Ivor Cummins BE(Chem) MIEI
  3. 3. Baseline Data Anomaly #1: Diabetes 1. 2. 3. 4. 5. 6. 7. Baseline data shows massive difference between “protein” groups for diabetes Factor X between groups drives this dose-response difference – what is Factor X ? X is NOT Protein content in diet – did the Native Indians, Masai or countless other very high protein cultures have 20% Diabetes? No, they had effectively ZERO T2D. Did the Americans in the 1960’s who consumed higher protein and Animal products have ultra-high T2 Diabetes prevalence? No, they had vastly less. What drives Diabetes, drives very poor health - this is known – and it’s a emerging US crisis in the past 30 years – the researchers should know this. It is known that what chronically drives Diabetes is SUGAR and High GIycemic Load Carb ingestion; a substantial portion of the Factor X in this mess. So Protein is proven to be a total confounder by this evidence alone – and the Study Authors left the data out of the main report – thus rendering the report’s conclusions worthless
  4. 4. Baseline Data Anomaly #2: Cancer 1. 2. 3. 4. 5. 6. 7. Baseline data shows significant difference between “protein” groups for Cancer before the 18 year follow-up began Again this is a dose-response difference between the groups – what is Factor X ? So the 6% of population “Low Protein” group had a lot higher cancer history at the study start. And this “Low Protein” group had much lower cancer death for 50-65 y.o. in the 18 year follow-up. And this “Low Protein” group had much higher cancer death for >65 year old group in the 18 year follow-up. So “Low Protein” drives cancer up for age <50, drives it down 50-65, and drives it up again >65? Not even addressing this absurdity, renders the report’s conclusions worthless
  5. 5. Baseline Data Anomaly #3 : Calories Reported 1. 2. 3. 4. 5. 6. 7. Baseline data shows significant difference between “protein” groups for Calories reported by groups before the 18 year follow-up began Again this is a dose-response difference between the groups – why are the higher protein groups grossly understating what they ate in the questionnaire? The 6% of population “Low Protein” group had an 1965 kCal disclosure – they are under-reporting, but somewhat honest (as healthy eaters often are) The “Moderate Protein” group had an 1862 kCal disclosure – they are underreporting solidly, (as people who leave out the snacks and sodas often do) The “High Protein” group had an 1593 kCal disclosure – they are grossly underreporting, (as people who are very conscious of their bad diet always do) All groups have the same BMI, emphasizing the farcical nature of the data? Not even addressing this absurdity, renders the report’s conclusions worthless
  6. 6. Summary 1. Baseline Diabetes Prevalence across groups makes the study conclusion completely invalid. 2. Baseline Cancer Prevalence across groups, along with mentioned age group anomalies in follow-up, renders the study conclusions invalid. 3. Dramatic and increasing Calorie Under-Reporting with “Protein defined” groups is critically relevant, and ignoring it again renders the protein conclusion invalid. 4. The best hypothesis that can be gleaned from judging the FULL data (especially the UNREPORTED Baseline Data), is that the “Low Protein” 6% of population group is dominated by honest reporting, healthy eating, sugar/junk avoiding types. 5. The above hypothesis is largely in concordance with the data, but one can never say anyway with an epidemiological, 1-day diet questionnaire type “Study”.
  7. 7. Backup
  8. 8. Key Baseline Data not included: Diabetes
  9. 9. Problem: Yet More Other Data from the Study Table S7 from the study Supplemental Information section Table S7: Associations between Diabetes Mortality and Protein Intake Among Participants with No Diabetes at Baseline. Related to Table 1.. 1. OK this is just totally taking the Mickey: T2D Hazard Ratios from 23 to 73 just for increasing protein within reasonable historical ranges??? So these guys are actually suggesting that moderate or high protein is effectively the TOTAL driver for Diabetes in America?? 2. Yes, that’s what they are suggesting here by inference – and it’s totally absurd. 3. This obvious confounding absolutely discredits protein as a probable driver for the OTHER mortality issues seen - if protein doesn’t cause the ridiculous levels of Diabetes, then all bets are OFF for protein causing the other issues – so we’re back to factor X then – the crazy American Sugar/Refined Wheat/Omega 6 Diet. MIEI 2013 Ivor Cummins BE(Chem)
  10. 10. Problem: IGF-1 Tracking with Issues?? 1. OK we know protein level is totally confounded from the previous few slides, so let’s look at this extra information from the Study Supplemental Data, shall we? 2. I would say that the “highest protein” Diabetesridden group has many members really hitting the junk food and sugar as discussed earlier, with poor old protein along for the ride, driving their IGF-1 up accordingly; just one ref below for consideration (as if I need a ref for this): Figure S2 from the study Supplemental Information section “Unhealthy Type Carbohydrates, on the other hand, generally trigger sharp increases in blood sugar, insulin and IGF-1. They include sugar and sugary foods, baked goods made with white flour, as well as some naturally starchy foods such as potatoes (and especially French fries) Unfortunately, some foods generally thought of as “healthy” (e.g. sports drinks, rice crackers, bagels, corn flakes or oven-baked potatoes) can also cause rapid increases in blood glucose and should be avoided wherever possible”. 2013 Ivor Cummins BE(Chem) MIEI
  11. 11. And the Age Enigma? 1. The higher protein cohort >65 years old when the survey started (in 1997?) went on to benefit hugely by high protein in the next 18 years, while the higher protein cohort 50-65 years old got hammered with death in the ensuing 18 years. 2. But from the original data of the participants, cancer history was 11.7% in the low protein group, 7.5% in the moderate protein group, and 5.0% in the high protein group?? 3. So high protein saves you when you’re <50, kills you big time when you’re 50-65, and massively saves you when you’re over 65! 4. Ok, Right, call an engineer please, and dump the academics. 5. What about just one alternative hypothesis?: 1. The people in their mid 50’s who were generally eating bad to worse food were in for a reckoning from 1997 to 2013 2. The people around 70 at the study start who were doing the bad food thing would have been in the US toxic bad-food environment for less of their lives, and may also benefit from reduced calories/gluttony with their advanced age, and thus the pendulum swung relative to the 50-65 guys…..? 3. Who knows, it’s only observational crap after all, pulled lazily from a database, far too dangerous for massive worldwide publishing – right? 2013 Ivor Cummins BE(Chem) MIEI
  12. 12. Appendix – Animal Foods and Protein have dropped as Obesity and Diabetes have Skyrocketed