jet

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[–] jet@hackertalks.com 3 points 2 weeks ago (4 children)

https://rentry.co/NSFW-Checkpoint

Not deleted, just they put up a speed bump

[–] jet@hackertalks.com 2 points 2 weeks ago (1 children)

I can't speak to soap, but rendering tallow for food purposes, the impurities can smell a bit wiffy. If I'm trying to render all the cow smell away I have to do the render and filter cycle 3ish times

[–] jet@hackertalks.com 3 points 2 weeks ago (2 children)

I always thought it was a choice for tdw and heat concerns. Intel tends to run a bit cooler (used to)

[–] jet@hackertalks.com 5 points 2 weeks ago (2 children)

Is this about memes?

[–] jet@hackertalks.com 2 points 2 weeks ago (1 children)

How the hell did the medical community go so sideways since then?

From what i've read the doctors who were uncovering the hormonal model of health in the 1930s were German and publishing in German based literature. After the world unpaused in the 1940s there wasn't much enthusiasm in the west for German publications.

Dr. Barry Sears (Biochem PhD, not MD) wrote about all this in the early 90’s in “The Zone” (with references).

Would you recommend reading that book?

[–] jet@hackertalks.com 8 points 2 weeks ago* (last edited 2 weeks ago) (2 children)

Calories are a useful approximation, but not how humans actually operate. A Bomb Calorimeter burns material and the resultant heat generated is what we call a calorie. As a illustrative example of the difference - gasoline is very calorie dense, but not helpful if eaten by a human.

do I gain the calories over the next few hours? Or is it delayed a day or two?

The human body will break down all food and drink into its base components then decide what it will keep, what it will excrete (more or less). So when you consume something you "gain" it immediately (its in your system), the time until its used in the body could be minutes (like carbohydrates), hours (fibre), etc. Often the body will decide to store any excess (carbs again) for later use (weight gain).

Because there will be days when I eat almost NOTHING, and then my scale says I gained 3 lbs. But then there’s other days where I feel I ate like a slob, and somehow lost 2 lbs.

The human body is an amazing homeostatic machine, it's trying to self regulate to optimal body composition. The trouble is lots of modern western food messes with the bodies ability to self regulate..... which brings us to the real topic

Losing weight is hard, but it might be easier if I understood the rules of how this all works.

The big secret is hormones, don't interfere with your hormones and the body will self regulate body composition to optimal (lose weight if your obese).

[Paper] The Carbohydrate-Insulin Model of Obesity - Beyond “Calories In, Calories Out” - 2018

TLDR - Eating sugar and carbohydrates forces blood glucose levels to rise (within minutes), elevated blood glucose forces insulin to rise (to reduce blood glucose), elevated insulin forces the body to go into anabolic (gain weight) state. Basically you can't lose any fat while your insulin is high, so every time someone eats a bunch of sugar or carbohydrates with a meal/snack they are putting a 2-4 hour pause on any fat loss.

[–] jet@hackertalks.com 5 points 2 weeks ago* (last edited 2 weeks ago) (7 children)

The importance of this cannot be understated, humans are amazing hormonal machines. Hormones control every aspect of our biology. The hormonal insulin model has dramatic application to human health and specifically obesity / insulin resistance / metabolic health.

TLDR: Insulin is the cause of almost all obesity you see. Carbohydrates drive blood sugar, blood sugar drives insulin, insulin drives weight gain. As a good example - T1Ds who don’t take their insulin wont gain weight, no matter how much they eat..

Notes:

rates of obesity remain intractably high despite intensive focus on reducing calorie intake (eat less) and increasing calorie expenditure (move more), with major implications to well-being, life-expectancy, and health care costs.

this model considers fat cells as central to the etiology of obesity, not passive storage sites of calorie excess.

Insulin decreases the circulating concentration of all major metabolic fuels by stimulating glucose uptake into tissues, suppressing release of fatty acids from adipose tissue, inhibiting production of ketones in the liver, and promoting fat and glycogen deposition.

Insulin is a super hormone, when its elevated the body stops feeding itself and stores everything.

inadequate insulin treatment of type 1 diabetes and drugs that inhibit insulin secretion cause weight loss.

Dietary fat has little direct effect on insulin, providing a theoretical basis for the efficacy of high-fat diets.

the carbohydrate-insulin model of obesity (CIM) proposes that a high-carbohydrate diet—including large amounts of refined starchy foods and sugar, as commonly consumed in the lowfat diet era—produces postprandial hyperinsulinemia, promotes deposition of calories in fat cells instead of oxidation in lean tissues, and thereby predisposes to weight gain through increased hunger, slowing metabolic rate, or both

Carbs/Sugars drive weight gain and hunger, its a vicious cycle.

calorie restriction can be viewed as symptomatic treatment, destined to fail for most people in the modern food environment. Low-calorie, low-fat diets may actually exacerbate the underlying metabolic problem by further restricting energy available in the blood—triggering the starvation response comprised of rising hunger, falling metabolic rate, and elevated stress hormone levels

People eating a high carb diet are always hungry because all of their internal stored energy (fat) is unavailable to them. They are always starving even though they have plenty of fat.

Even when calorie-restricted to prevent excessive weight gain, insulin-treated animals still developed excessive body fat consistent with a prediction of the CIM regarding fuel partitioning

CICO / Eat Less Move More - Would say that the food doesnt matter, but in animals adding insulin without changing the diet causes weight gain! This disproves the simplistic CICO advice of weight loss.

calorie restriction to prevent excessive weight gain in animals on a high-GI diet did not prevent excessive adiposity or the associated cardiometabolic risk factors

If the insulin is elevated (carbs/sugar in the diet) even calorie restriction does not prevent obesity in animals.

[–] jet@hackertalks.com 2 points 2 weeks ago (1 children)

The only thing unhealthy in your neighbors diet is the sugar substitute in the coke zero. If he reduced his obesity down to a normal weight, his life has massively improved.

should eat their veggies

This is the party line, but its actually up for debate because the actual scientific literature doesn't have evidence that this is necessary.

I’m still thinking that can’t be healthy, but he does look healthier in comparison to morbidly obese.

Carnivores (which it sounds like your neighbor is) tend to be very data focused, ask if he would share his health metrics with you (lipid panel, hba1c, etc)... When you look at those metrics you will have to decide what "healthy" means (what outcomes you care about)

[–] jet@hackertalks.com 2 points 2 weeks ago (2 children)

If you know of a link to the full paper, I'd love to read it

[–] jet@hackertalks.com 1 points 2 weeks ago

Blue prince is a wonder experience! I'm glad your enjoying it.

[–] jet@hackertalks.com 4 points 2 weeks ago* (last edited 2 weeks ago)

This was one of the papers referenced in @xep@fedia.io 's cholesterol paper from a few days ago. Thought it was interesting for its own post.

Notes:

evidence from the Kuopio Ischemic Heart Disease Risk-Factor Study suggested that egg protein intake was associated with significantly reduced risk for T2D in Finnish men [6].

Subjects who were pregnant, planning to be pregnant during the study period, lactating, or of child-bearing potential and unwilling to commit to the use of a medically approved form of contraception throughout the study period were also excluded.

That really complicates analysis, if someone is using hormonal birth control that will change the hormones, but also if they start it for the study then it's skewing the results.

However, HOMA-IR was significantly increased following the Non- Egg (24.4%) compared with the Egg condition (1.4%). Although this finding suggests that replacing higher-CHO (primarily sugar) foods with egg-based foods at breakfast may have a favorable effect on whole-body insulin sen-sitivity, caution is warranted. The HOMA-IR value is calculated using a linear model based on population-derived estimates, whereas HOMA2-%S is calculated using a nonlinear model, which is theoretically more robust [19, 20, 27]. No significant differences were present between the Egg and Non-Egg conditions for HOMA2-% S based on fasting values, or the ISI from the short IVGTT

Short intervention study, where the Egg population was still consuming carbohydrates saw a very modest improvement in insulin sensitivity. I speculate this is because of the reduction of carbohydrates for a single meal.

Another potentially relevant factor regarding effects of different meals on CHO metabolism is time of day. Dif-ferences in sympathetic nervous system activity and/or diurnal patterns related to the release of incretin hormones (e.g., glucagon-like peptide-1 and gastric inhibitory poly-peptide in response to a meal) may affect insulin sensitivity [31], and markedly higher (~40%) insulin sensitivity has been observed in the morning compared with mid-afternoon or evening [32]. Jakubowicz et al. conducted a randomized crossover trial where subjects with T2D were fed either a meal pattern that included a high-energy breakfast plus a low-energy dinner (breakfast: 2946 kJ, lunch: 2523 kJ, and dinner: 858 kJ) or a meal pattern with a low-energy break-fast plus a high-energy dinner (breakfast: 858 kJ, lunch: 2523 kJ, and dinner: 2946 kJ) [32]. Despite isoenergetic intakes, those consuming the higher energy breakfast meal pattern had reduced postprandial hyperglycemia and higher levels of intact and total glucagon-like peptide-1. In the present trial, study products were consumed at the breakfast meal, when insulin sensitivity would be expected to be at its highest. It is uncertain whether similar results would be obtained with consumption of the study products in the afternoon or evening.

This is a curious result, and speaks to the point Xep made about eating and time of day, I'm still very curious if this holds in a fully ketogenic diet.

I think the variability of thus study compared to other egg studies indicates that the eggs are not the main variable of interest, its the carbohydrates that are accounting for the fluctuating signal across these studies.

 

TLDR - There is far from consensus in the vilification of red meat in dietary guidelines. This article dives into the details of the ongoing schism.

Mainstream dietary recommendations now commonly advise people to minimize the intake of red meat for health and environmental reasons. Most recently, a major report issued by the EAT-Lancet Commission recommended a planetary reference diet mostly based on plants and with no or very low (14 g/d) consumption of red meat. We argue that claims about the health dangers of red meat are not only improbable in the light of our evolutionary history, they are far from being supported by robust scientific evidence.

Full paper at https://pubmed.ncbi.nlm.nih.gov/31486336/

 

https://pubmed.ncbi.nlm.nih.gov/38354868/

TLDR - Meat has been unfairly blamed by bad (possibly biased) statistical analysis.

some investigators may test many alternative analytic specifications and selectively report results for the analysis that yields the most interesting findings.

when investigators analyze data from observational studies, there are often hundreds of equally justifiable ways of analyzing the data, each of which may produce results that vary in direction, magnitude, and statistical significance

Evidence shows that investigators’ prior beliefs and expectations influence their results [5]. In the presence of strong opinions, investigators’ beliefs and expectations may shape the literature to the detriment of empirical evidence

Basically given a all the possible variable permutations they took a very large sampling of inputs to outcomes and looked at the resultant hazard ratio, demonstrating that you can cherry pick to get the results you want (good or bad). This is the core weakness of observational studies.

Curve analysis demonstrates itself as a valuable too in iterating through many of the combinations of observational data to show stronger trends.

The left/blue side of the graph are outcomes that show meat decreased all cause mortality, the right/red side of the graph are outcomes that show meat increases all cause mortality. If you were a hungry researcher, you could publish unending papers indicating either way from this same observational data pool! - Hence the constant news cycle driven by dietary agendas - not based on hard science RCTs.

 

TLDR : Weak Science, Low Relationship, Healthy User Confounders - Nothing burger.

Results: The dementia analysis included 133,771 participants (65.4% female) with a mean baseline age of 48.9 years, the objective cognitive function analysis included 17,458 female participants with a mean baseline age of 74.3 years, and SCD analysis included 43,966 participants (77.1% female) with a mean baseline age of 77.9 years. Participants with processed red meat intake ≥0.25 serving per day, compared with <0.10 serving per day, had a 13% higher risk of dementia (hazard ratio [HR] 1.13; 95% CI 1.08-1.19; plinearity < 0.001) and a 14% higher risk of SCD (relative risk [RR] 1.14; 95% CI 1.04-1.25; plinearity = 0.004). Higher processed red meat intake was associated with accelerated aging in global cognition (1.61 years per 1 serving per day increment [95% CI 0.20-3.03]) and in verbal memory (1.69 years per 1 serving per day increment [95% CI 0.13-3.25], both plinearity = 0.03). Unprocessed red meat intake of ≥1.00 serving per day, compared with <0.50 serving per day, was associated with a 16% higher risk of SCD (RR 1.16; 95% CI 1.03-1.30; plinearity = 0.04). Replacing 1 serving per day of nuts and legumes for processed red meat was associated with a 19% lower risk of dementia (HR 0.81, 95% CI 0.75-0.86), 1.37 fewer years of cognitive aging (95% CI -2.49 to -0.25), and a 21% lower risk of SCD (RR 0.79, 95% CI 0.68-0.92).

Discussion: Higher intake of red meat, particularly processed red meat, was associated with a higher risk of developing dementia and worse cognition. Reducing red meat consumption could be included in dietary guidelines to promote cognitive health. Further research is needed to assess the generalizability of these findings to populations with diverse ethnic backgrounds.

https://pubmed.ncbi.nlm.nih.gov/39813632/ https://doi.org/10.1212/WNL.0000000000210286

Sounds really bad! But, Association is not causation, "could" also means "cloud not"

(I can't find the full paper, if you know a link please share it, I want to read the full paper)

Prospective cohort study, epidemiology, another slice of the Nurses Health Study, and the HPFS. Observational Research, cannot prove causation. The Hazard ratio is 1.13, that's nothing. You have to be at least 2 to even justify further research (unless there is an agenda). As a reference the hazard ratio for smoking was 30!

As always in observational studies, healthy patient confounders need to be considered. The person ignoring current advice eating pizza, fast food, etc is considered a "meat eater", but the person following the guidelines is more or less vegetarian (no processed meat, no red meat at least, not smoking, not drinking) at this point. The big difference between these groups? SUGAR AND CARBS.

Even with this massive confounder the Hazard Ratio was only 1.13 (1.0 means NO Correlation at all)

From this tiny data point, the news is flooded with "Red Meat Causes Dementia"

The research director at Harvard has a well established PBF bias, as well as funding from industry. This paper is just one is a series (there will be another for the next news cycle with the same hazard ratios, saying the same thing). At BEST this type of low probability correlation should be used to setup a real study, a RCT... not to set policy or demonize red meat.

Recall our previous discussion of how you slice the data looking for relationships is just as important as the results with a large body of observational data https://lemmy.dubvee.org/post/2623649

 

A great, great, great, in depth book going over how to do carnivore, how to use it as a tool to find a problem food, and how to go back to a standard diet after (or stay on carnivore). This is a very complete resource.

Table of Contents

  • Chapter 1: The Elimination Diet: What It Is and Is Not
    • Skin Allergies on the Rise?
    • Why Identifying Food Reactions Is Important
    • What Is an Elimination Diet?
    • Asthma and Cesarean Deliveries
  • Chapter 2: It Starts with the Gut
    • Popular Elimination Diets
    • What Is It About Food?
    • Digestion
    • Acid Reflux Disease
    • Gut Disease
  • Chapter 3: Don’t Eat This
    • Food Additives Banned by the FDA
    • Artificial Food Dyes
    • Other Food Toxins
  • Chapter 4: Sugars and Sweeteners: The Rise of Disease
    • Carbohydrates Are Not Essential For Optimal Health
    • Essential Nutrients
    • Sugar in the Blood
    • Effects of Sugar Consumption
    • Sugar Addiction
  • Chapter 5: Genetically Modified Foods
    • What Glyphosate Is
    • Glyphosate Exposure
    • Glyphosate and the Shikimate Pathway
    • Where Glyphosate Is Used
    • Glyphosate and an Increase in Disease: Coincidence?
    • Monsanto, Bayer, and Germany
  • Chapter 6: The Plant Kingdom
    • Pesticides Used on Organic Plant-Based Foods
    • Caffeine and Coffee
    • Antinutrients
    • Other Problematic Compounds in Fruits and Vegetables
  • Chapter 7: How to Eat Plants: Soaking, Sprouting, Peeling, and Deseeding
    • Soaking and Sprouting
    • Fermentation
    • Removing Skin and Seeds
    • Other Options
    • A Thought
  • Chapter 8: Bioavailability of Proteins and Fats
    • Protein Digestibility
    • The Importance of Fats
    • Not All Fats Are Created Equal
    • Fat for Children
  • Chapter 9: Hello Meat: The Nutritional Value of Meat
    • Francis Pottenger’s Cat Studies
    • Meat and the Recommended Daily Allowance
    • The Power (and Danger) of Studies
  • Chapter 10: The Environmental and Ethical Dilemma of Eating
    • Meat
    • Ethical Farming and Climate Change
    • Carbon Sequestering and Regenerative Agriculture
  • Chapter 11: Nutritional Concerns on a Carnivore Diet
    • Calcium
    • Vitamin D
    • Cholesterol
    • Magnesium (and Potassium)
    • Vitamin C
    • Antioxidants
    • Fiber
    • Salt
    • Electrolytes
    • Iron and Ferritin
    • Insulin
    • Advanced Glycation End Products
    • Heterocyclic Amines and Polycyclic Aromatic Hydrocarbons
    • IGF-1 and mTOR
    • Low Energy and Homocysteine
  • Chapter 12: Hormones and Zero Carbohydrates
    • Stress, Adrenals, and Hormones
    • Perimenopause and Menopause
  • Chapter 13: Carnivore Cure Preparation
    • Eating Disorders and Using Food for Comfort
    • What to Expect on Carnivore Cure
    • Actionable Tools and Tips for Successfully Following Carnivore Cure
    • Knowing Yourself
    • Getting the Environment Ready
  • Chapter 14: How Much to Eat and Drink
    • Satiety Hormones
    • Macronutrient Amounts, Calories and Nutrient Calculators
    • Hydration
  • Chapter 15: Carnivore Cure Weekly Protocol
    • Week 1
    • Week 2
    • Week 3
    • Week 4
    • Week 5 and Beyond
    • Moving Ahead
  • Chapter 16: Detoxification
    • Going About It the Right Way
  • Chapter 17: Carnivore Cure Plant Reintroduction
    • Food Sensitivity Testing
    • Read Labels
    • Be Wary of Marketing Tactics
    • The Carnivore Cure Plant List
  • Chapter 18: Holistic Lifestyle Changes Sleep
    • Hormesis
    • Fasting, Autophagy, and Basal Metabolic Rate
    • Exercise
    • Meditation
    • Removing Environmental Toxins
    • Sunscreen
    • Harmful Toxins
    • The Importance of Touch and Purpose
  • Chapter 19: Frequently Asked Questions
  • Chapter 20: Sample Meal Plan and Animal Nutrition
  • Chapter 21: Resources and Testimonials
  • Chapter 22: Closing Thoughts
    • Balancing real life and the perfect diet for optimal health
  • Chapter 23: Carnivore Cure: The Program

Available at

 

Our large brain, long life span and high fertility are key elements of human evolutionary success and are often thought to have evolved in interplay with tool use, carnivory and hunting. However, the specific impact of carnivory on human evolution, life history and development remains controversial. Here we show in quantitative terms that dietary profile is a key factor influencing time to weaning across a wide taxonomic range of mammals, including humans. In a model encompassing a total of 67 species and genera from 12 mammalian orders, adult brain mass and two dichotomous variables reflecting species differences regarding limb biomechanics and dietary profile, accounted for 75.5%, 10.3% and 3.4% of variance in time to weaning, respectively, together capturing 89.2% of total variance. Crucially, carnivory predicted the time point of early weaning in humans with remarkable precision, yielding a prediction error of less than 5% with a sample of forty-six human natural fertility societies as reference. Hence, carnivory appears to provide both a necessary and sufficient explanation as to why humans wean so much earlier than the great apes. While early weaning is regarded as essentially differentiating the genus Homo from the great apes, its timing seems to be determined by the same limited set of factors in humans as in mammals in general, despite some 90 million years of evolution. Our analysis emphasizes the high degree of similarity of relative time scales in mammalian development and life history across 67 genera from 12 mammalian orders and shows that the impact of carnivory on time to weaning in humans is quantifiable, and critical. Since early weaning yields shorter interbirth intervals and higher rates of reproduction, with profound effects on population dynamics, our findings highlight the emergence of carnivory as a process fundamentally determining human evolution.

Full Paper https://doi.org/10.1371/journal.pone.0032452

 

TLDR: Nothing burger junk science paper we see pumped out every 3 months from the same observational food frequency questionnaires.

Findings In this cohort study of 221 054 adults from 3 large cohorts, higher butter intake was associated with increased total and cancer mortality, while higher intake of plant-based oils was associated with lower total, cancer, and cardiovascular disease mortality.

Meaning Substituting butter with plant-based oils, particularly olive, soybean, and canola oils, may confer substantial benefits for preventing premature deaths.

Conclusions and Relevance In this cohort study, higher intake of butter was associated with increased mortality, while higher plant-based oils intake was associated with lower mortality. Substituting butter with plant-based oils may confer substantial benefits for preventing premature deaths.

Full paper: https://doi.org/10.1001/jamainternmed.2025.0205

 

We use the methodology of anthropometric history to investigate the nutritional status of equestrian nomads who lived on the Great Plains during the middle of the nineteenth century, a group for whom traditional measures of economic performance are unavailable. Historians have frequently portrayed Native Americans as merely unfortunate victims of European disease and aggression, with lives in disarray following the arrival of Columbus and other explorers, conquerors, and settlers. While much decimation occurred (Russell Thornton, 1987, 1997), the data we analyze show that some Native Americans were remarkably ingenious, adaptive, and successful in the face of exceptional demographic stress. Using height data originally collected by Franz Boas, we show that the Plains nomads were tallest in the world during the mid-nineteenth century, a result confirmed in travelers’ accounts and by the skeletal record. The analysis provides a useful mirror for understanding determinants of health in general.

https://doi.org/10.1257/aer.91.1.287

Full Paper on SciHub (better formatting) / https://web.archive.org/web/20081216230811id_/http://eh.net/XIIICongress/cd/papers/70PrinceSteckel378.pdf

 

Background: Animal-based, or so-called carnivore, diets largely exclude all plant-based foods and are gaining increasing popularity, mainly among individuals suffering from chronic diseases. This study aimed to explore subjective experiences and blood parameter changes of German followers of a carnivore diet.

Methodology: We conducted a statistical survey using a self-designed questionnaire and requesting blood panels. Inclusion criteria were: (i) following a carnivore-type diet for at least one month; (ii) completing the self-designed study questionnaire; and (iii) providing two sets of metabolic blood parameters from the period before and after adopting the carnivore diet. The survey was complemented by qualitative interviews with four subjects on a carnivore diet.

Results: Twenty-four individuals participated in the survey. Fifteen participants (62.5%) were male, and the median age was 46 (range 26-62) years. The majority (n = 16, 67%) reported at least one clinical diagnosis, and the main reason for switching to a carnivore diet was accordingly health-related. Improved health was also the major motivation to maintain the diet. Before the carnivore diet, participants consumed a variety of other diets, of which a ketogenic (n = 8) and standard diet (n = 7) were most frequently reported. There were no significant differences between on-diet and pre-diet blood parameters except for total (pre-diet median: 224 mg/dL; on-diet: 305 mg/dL; P < 0.0001) and low-density lipoprotein (LDL) cholesterol (pre-diet: 157 mg/dL; on-diet: 256 mg/dL; P = 0.00024) concentrations. However, two participants who initially had pre-diabetic HbA1c values and six participants with initially high (>130 mg/dL) triglyceride levels all experienced a reduction of these blood parameters during the carnivore diet.

Conclusions: Individuals adopting a carnivore diet do this mainly for health-related reasons and commonly experience subjective health improvements. Most blood parameters on the carnivore diet were within the reference ranges, and initially high HbA1c and triglyceride levels were reduced. However, the significant elevation of total and LDL cholesterol concentration is striking and warrants further investigation into potential adverse effects.

Full Paper https://doi.org/10.7759/cureus.82521 - https://assets.cureus.com/uploads/original_article/pdf/354775/20250418-428965-m7dvqf.pdf

TLDR: 24 people doing carnivore for at least one month, pre and post diet blood panels.

This is just a survey, its suggestive but not a strong signal to take any conclusions away from. the fact that the on-diet blood panels were of various lengths of carnivore makes the data very messy (1 month to 5 years)

 

The gut microbiome of the carnivore was dominated by the phylum Firmicutes and the genera Faecalibacterium, Blautia, unspecific Lachnospiraceae, Bacteroides, and Roseburia—bacteria known for fiber degradation. Furthermore, neither alpha- nor beta-diversity, nor the functional capacity of the gut microbiome, showed differences when compared to the control groups. Additionally, the gut microbiome of the carnivore showed the least similarities with the microbiome of the cohort consuming meat on a daily basis.

In our study, we showcase the compositional and functional characteristics of the gut microbiome in an individual on a carnivorous diet, finding no differences in comparison to a control cohort. Further research is needed to investigate the short- and long-term impacts of a carnivorous diet on gut health through cross-sectional and longitudinal studies.

Full Paper - https://doi.org/10.1530/MAH-24-0006

 

We reviewed data on the American diet from 1800 to 2019. Methods: We examined food availability and estimated consumption data from 1800 to 2019 using historical sources from the federal government and additional public data sources. Results: Processed and ultra-processed foods increased from <5 to >60% of foods. Large increases occurred for sugar, white and whole wheat flour, rice, poultry, eggs, vegetable oils, dairy products, and fresh vegetables. Saturated fats from animal sources declined while polyunsaturated fats from vegetable oils rose. Non-communicable diseases (NCDs) rose over the twentieth century in parallel with increased consumption of processed foods, including sugar, refined flour and rice, and vegetable oils. Saturated fats from animal sources were inversely correlated with the prevalence of NCDs. Conclusions: As observed from the food availability data, processed and ultra-processed foods dramatically increased over the past two centuries, especially sugar, white flour, white rice, vegetable oils, and ready-to-eat meals. These changes paralleled the rising incidence of NCDs, while animal fat consumption was inversely correlated.

Annual total caloric and macronutrient availability per capita from 1909 to 2010 (Source: USDA ERS).

Full Paper - http://dx.doi.org/10.3389/fnut.2021.748847

 

Characterizing the potential health effects of exposure to risk factors such as red meat consumption is essential to inform health policy and practice. Previous meta-analyses evaluating the effects of red meat intake have generated mixed findings and do not formally assess evidence strength. Here, we conducted a systematic review and implemented a meta-regression— relaxing conventional log-linearity assumptions and incorporating between-study heterogeneity—to evaluate the relation-ships between unprocessed red meat consumption and six potential health outcomes. We found weak evidence of association between unprocessed red meat consumption and colorectal cancer, breast cancer, type 2 diabetes and ischemic heart disease. Moreover, we found no evidence of an association between unprocessed red meat and ischemic stroke or hemorrhagic stroke. We also found that while risk for the six outcomes in our analysis combined was minimized at 0 g unprocessed red meat intake per day, the 95% uncertainty interval that incorporated between-study heterogeneity was very wide: from 0–200 g d−1. While there is some evidence that eating unprocessed red meat is associated with increased risk of disease incidence and mortality, it is weak and insufficient to make stronger or more conclusive recommendations. More rigorous, well-powered research is needed to better understand and quantify the relationship between consumption of unprocessed red meat and chronic disease.

Full Paper - https://doi.org/10.1038/s41591-022-01968-z

 

This is a interesting study of two geographically near tribes of people eating a plant based diet vs a animal based diet.

This type of reporting is rare, since the western diet has changed every group of humans it has contacted.

https://doi.org/10.1001/jama.1931.02730200061030

Full text: https://babel.hathitrust.org/cgi/pt?id=coo.31924003510108

This is a contribution to knowledge concerning the relation of diet to physique and to health. The two tribes selected for this investigation were chosen because of the fact that, although their territories were adjoining, their dietary customs were different, "the Akikuyu being almost exclusively vegetarian and the Masai chiefly carnivorous." The field work in this investigation covered such categories as chemical analysis of all foods in common use, articles of diet in the raw state, cooked foods, edible earths, physical examination of both adults and children, and clinical observations. Additional features of this study pertain to laboratory and hospital work dealing with the adequacy of hospital and prison diets, the effect of additions to the diet of various seemingly desirable supplements, feeding tests with prescribed diets on four groups each of forty boys, and blood studies dealing particularly with calcium and phosphorus content, sugar tolerance, ph and alkali reserve,

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