Letter to the editor (The Contrived Association of Dietary Protein with Mortality)

The Contrived Association of Dietary Protein with Mortality


To the Editor:

We applaud efforts to improve human health by asking insightful questions that explore existing nutrition paradigms. Unfortunately, the paper by Levine et al. (Cell Metab 2014;19:407) is a flawed attempt to link health risks of a single nutrient, protein, to chronic disease states of cancer, CVD and diabetes. The study design and analyses are inappropriate; key contradictory data are neglected; and conclusions are not justified by the data. As scientists with decades of experience studying the impact of protein on health, we are concerned that translation of these flawed data and exaggerated conclusions to the public could have serious negative health consequences for adults seeking to maintain muscle health and avoid sarcopenia.

The optimum dietary intake of protein for adults remains a topic of scientific debate; however, research has established that balanced diets with protein intakes moderately above the RDA value of 0.8 g/kg/d (1) are beneficial for weight management, sarcopenia, diabetes and physical activity (2,3). While these reviews overwhelmingly demonstrate short-term benefits of moderate protein intake on metabolic status and body composition, the long-term impact of protein on disease risk or mortality is more difficult to assess and requires expert interpretation of large data sets such as the National Health and Nutrition Examination Survey (NHANES).

In their study, Levine et al. indicate (Figure 1, Table S1, and Discussion) that “…the level of protein is … not associated with differences in all-cause, cancer, or CVD mortality.”  In fact the data demonstrate that cancer mortality was actually ~10% higher in the low protein group compared with the higher protein group (ie. 9.8% versus 9.0% deaths). We would argue that the obvious findings are the most important.

Subsequent subdivision and reanalysis of the data raise serious questions about the validity of the authors’ approach and conclusions. First, the NHANES Linked Mortality Files contain information for almost 12,000 adults, however, without justification, the investigators eliminated almost one-half of the data and only reported results for 6,381 over the age of 50 yr. Second the investigators arbitrarily created ill-defined protein groups of low (LP: <10% of kcal), medium (MP: 10 – 19.9%) and high (HP: 20%+). As defined by the Institute of Medicine (IOM) the Acceptable Macronutrient Distribution Range for protein is 10% to 35% of daily energy intake (1); thus, the LP group (<10% of kcal) consuming ~41 g/d (Table S1) should be designated as protein inadequate. Applying the authors’ unusual protein categories resulted in only 437 individuals remaining in the LP group. A third major problem is use of only a single 24-h recall to derive dietary data to represent food intake over the 18-yr period of life. The limitations of this approach are hard to overstate. NHANES surveys contain additional dietary recall data allowing for calculation of more meaningful “estimated usual” food intakes as utilized by other investigators (4,5). A fourth major problem is failure to report body weight or BMI for the groups. Energy balance and body fat are major risk factors for mortality from diabetes, cancer and CVD. The footnote for Table S1 contains the definition for the BMI abbreviation but the table omits the data.

The investigators also looked at the diabetes mortality data. They report a trend for increased risk of diabetes mortality for adults with higher protein intakes (Fig. 1). However, these findings are derived from severely limited data. For diabetes mortality, they report 1.0% deaths (Table S1) or a total of 68 deaths in the entire population with only a single death in the LP group. Further, 47 of the individuals who died from diabetes had diabetes at baseline, before the first dietary measurements. The very low occurrence frequency increases the probability of statistical errors resulting in differences that are not biologically true; nonetheless, the investigators used these limited data to conclude “high protein was associated with … a 5-fold increase in mortality.” Further, the authors used Hazard Ratio (HR) analysis and concluded that the HP group had a 73-fold increased risk of dying from diabetes. The HR and confidence interval (CI) were reported as 73.52 (4.47 – 1,209.70). To our knowledge, that is the highest HR ever reported for any dietary component and certainly for one within dietary guidelines of the IOM. The CI with a 400-fold range and an upper value of 1,209.70 with 6-significant figures of accuracy is not credible.

Hazard Ratio analysis is a standard method for clinical studies with equal treatment groups and survival as a primary outcome, but have important a priori criteria for their use: 1) equal size groups, 2) no evidence of selection or group bias, and 3) linear outcomes over time. The present study fails to meet all three criteria. There are recent high quality papers using the same NHANES data focused on sugar and sodium/potassium using acceptable methods (4,5). The authors should justify not following establish procedures.

Our overall assessment of this paper is that the conclusions and analyses are biased, and flawed. While there is growing consensus that a moderate protein intake between 1.0 and 1.5 g/kg/d may confer health benefits beyond those afforded by the current RDA for protein, we also recognize there are gaps in the current knowledge base and encourage discussion of important contradictory evidence/data. Future research must be well designed, rigorously reviewed, and credibility communicated. Unfortunately, the article by Levine et al. presents conclusions not supported by their own analyses or the greater literature.


Donald K. Layman

Arne Astrup

Peter M. Clifton

Heather J. Leidy

Richard D. Mattes

Douglas Paddon-Jones

Stuart M. Phillips

Nancy R. Rodriguez

Robert R. Wolfe



  1. Institute of Medicine, Food and Nutrition Board. Dietary Reference Intakes for energy, carbohydrates, fiber, fat, fatty acids, cholesterol, protein, and amino acids. Washington DC: National Academy Press; 2002.
  2. Westerterp-Plantenga MS, Luscombe-Marsh N, Lejeune MPGM, et al. Dietary protein, metabolism, and body weight regulation: dose-response effects. Int J Obes 2006;30:S16-S23.
  3. Bauer J, Biolo G, Cederholm T, et al. Evidence-based recommendations for optimal dietary protein intake in older people: A position paper from the PROT-AGE study group. JAMDA 2013;14:542-559.
  4. Yang Q, Liu T, Kuklina E, et al. Sodium and potassium intake and mortality among US adults. Arch Intern Med 2011;171:1183-1191.
  5. Yang Q, Zhang Z, Gregg EW, et al. Added sugar intake and cardiovascular diseases mortality among US adults. JAMA Intern Med 2014; (doi: 10.1001/jamainternmed.2013.13563.

You can only absorb 30 grams of protein/meal

This is a myth!

Can you only absorb 30 G protein/meal for muscle protein synthesis? Probably not.

A study done by Tipton et al. (2016) shows otherwise:


Study type:

2-group, randomized, double-blind, crossover design.


Group 1- 20 g whey protein isolate

Group 2- 40 g whey protein isolate


Total= 30 healthy, resistance trained (>= 2 sessions/week for past 6 months) males divided into Group 1 (n=15) and Group 2 (n=15)


Volunteers participated in two infusion trials (used to measure MPS response) after doing whole-body resistance exercise and ingesting whey protein isolate. Group 1 was given 20 g, and Group 2 was given 40 g whey protein isolate, immediately post-exercise.


Overall, Group 2 had greater MPS than Group 1, following whole-body resistance exercise.


Based on this study, consuming more than 30 g high-quality protein following heavy resistance training is more beneficial for muscle growth. The level of resistance training and the type of exercises you perform may affect the amount of protein you can absorb.



Consuming More than 2.0 g/kg/d of protein when resistance trained impairs performance

This is a Myth!

Resistance Trained Individuals (resistance trained = weight training 2-3x/wk for at least past 6 mths) need higher levels of protein intake, but more has been proposed to be detrimental. It has been commonly accepted that 1.4-2.0g/kg/d (day) is sufficient.

But what about beyond 2.0g/kg/d?

2 major studies by Antonio et al. suggest otherwise:


4.4g/kg/d & 3.4g/kg/d; both examining body composition.


30 & 48 healthy resistance trained men and women.


In the 4.4g/kg/d study groups were split into 1. Control Group & 2. High Protein Group for 8 weeks. Both groups were asked to maintain the same training and dietary habits (i.e. carbohydrates &amp; fats). In the 3.4g/kg/d protocol similar groups emerged expect this time all participants completed a periodized split routine with heavy resistance.


1st study– NO adverse effects to a hypercaloric protein diet nor increase in body fat.

2nd study– NO adverse effects + the high protein group experienced higher decreases in fat mass & body fat %. Also the high protein group had greater performance gains in bench press, back squat, vertical jump, and pull-ups!


Consuming a high protein diet in conjunction with a heavy resistance training program improves body composition and performance gains!

Excess Protein Raises Blood Glucose And Insulin Too Much

This is a myth!

Main takeaway 🔽

Adding protein that’s rich in leucine (meat) to meals, will help increase insulin secretion and stabilize your blood glucose levels after meals.

Eating carbohydrate-rich meals that are low in protein will give you higher blood sugar levels, with less insulin secretion, leading to more fat storage.

Excess protein will equate into more calories, and anytime you consume excess calories you will store fat, albeit, excess protein is associated with less excess calories as compared to fat and carbohydrates.

(For the nerds 🤓)
Nillson et al. (2018) showed there was a correlation of insulin responses after meals with early incremental consumption of amino acids and protein. The strongest correlations were shown for leucine, valine, lysine, and isoleucine. Milk powder and whey were shown to have substantially lower blood glucose increases as compared to cod, gluten-low & gluten-high meals, bread, and cheese. The highest blood sugar increase was shown thirty minutes after consumption of cod, bread, and gluten with an even more considerable decrease in blood sugar levels at minute sixty after consumption.

Reconstituted milk powder and whey had significantly lower glucose spikes but higher levels of insulin released; therefore, more of the sugar is absorbed and utilized by the cells. The meals containing bread, cod, and gluten were shown to have lower amounts of leucine, the highest increase in blood glucose levels, and a half or less the amount of insulin released.
Therefore, if more glucose is released and even more is unused by the cells, then excess glucose will then be stored as glycogen and also converted to fat in the liver.
Protein does increase insulin, but at different levels; food proteins differ in their ability to stimulate insulin release. It is thought to be because of the amino acid profile of the food. Leucine, Alanine, and Arginine (fuels used by the pancreas to make energy) are associated with a higher release of insulin. Milk proteins have insulinotropic properties containing the predominating insulin secretagogue. We see our most substantial increases in blood sugar levels in carbohydrate-rich meals.

Meals in the study that were higher in the amino acid leucine were shown to have more stable blood sugar levels. Isoleucine, Lysine, and Valine were also demonstrated in correlation to better insulin responses.



Higher Protein Intake is Hard On the Kidneys

This is a myth!

Higher protein (HP) diets (above RDA recommendations) have been used to promote weight loss, preserve muscle mass, and prevent sarcopenia. However, there is a myth that higher protein diets lead to kidney dysfunction. The indicator would be a change in glomerular filtration rate (GFR).

It turns out that the data does not support such a myth.


A meta-analysis conducted by Phillips et al. looked at higher protein diets (≥1.5 g/kg body weight or ≥20% energy intake or ≥100 g protein/d) and their effects on kidney function. When compared to normal- or lower-protein (NLP; ≥5% less energy intake from protein/d) diets, HP diets resulted in higher GFR overall; however HP intake did not influence changes in GFR. Thus, it was concluded that HP intake does not negatively influence renal function in healthy adults.

A systematic review of randomized control trials and epidemiologic studies conducted by Elswyk et al found that HP intake (≥20% but <35% of energy or ≥10% higher than a comparison intake) had little to no effect on blood markers of kidney function (i.e., blood pressure) when compared to groups following US RDA recommendations (0.8 g/kg or 10-15% of energy).

Coming from the PROT-AGE study group, “both endurance- and resistance-type exercises are recommended at individualized levels that are safe and tolerated, and higher protein intake (i.e., ≥ 1.2 g/kg body weight/d) is advised for those who are exercising and otherwise active. Most older adults who have acute or chronic diseases need even more dietary protein (i.e., ‪1.2-1.5‬ g/kg body weight/d).” However, individuals with severe kidney disease (GFR <30 mL/min/1.73 m(2)), but who are not on dialysis, are an exception to the rule; this cohort may need to limit protein intake.

Our goal is to optimize. According to Schoenfeld et al., reaching the minimum threshold of 1.6 g/kg spread out evenly throughout the day is necessary to maximize anabolism.



If you goal is to maximize muscle growth, it doesn’t matter when you eat your protein, as long as you eat it

This is a myth!

Always identify the goals you have and more importantly, the strategies you’ll employ to maximize results.

That’s right- it’s not only about the daily protein amount that matters. There is a protein threshold that is required for maximizing muscle protein synthesis (MPS). That per-meal threshold for MPS varies depending on age, sex, level of training, and whether or not you’ve trained that day.

Tipton et al reported that a 20g dose of whey protein is sufficient for maximal stimulation of myofibrillar MPS for both rested and exercised muscle of healthy young men (20-24 yr).

Similarly, Phillips et al reported that MPS reaches a maximal stimulation after ingestion of 20g high-quality protein post-resistance training in young healthy men (20-24 yr).

Phillips et al reported that for older men (73 +/- 2 yrs), ingestion of 35 g whey protein results in greater AA absorption and use for de novo MPS, compared with ingestion of 10 or 20 g whey protein.

Thus, frequent protein ingestion of sub-threshold protein amounts won’t stimulate the anabolic response.

In addition, one would need less protein consumption during resistance training days. Ingestion of 20g protein is sufficient to maximally stimulate MPS and APS (Albumin protein synthesis) post-resistance exercise.

This is because the two drivers of MPS (resistance training and protein ingestion) are essential for those looking to maximize building muscle.

     Overall daily protein consumption matters greatly of course; if you are a healthy adult, above 1.2 g/kg is optimal. But if you want to really maximize muscle growth, dialing in protein consumption timing may level you up.



High protein causes bone demineralization

This is a myth!

Protein does not cause osteoporosis nor declining bone health. In fact, the opposite is true. High quality dietary protein is necessary for strong bones.


Heaney & Layman (2008) examined that bone health depended on a variety of factors:

1) Level of protein in the diet

2) Protein source

3) Calcium intake

4) Weight loss

5) Acid/base balance of the diet.

The review also acknowledged a study of 191 subjects over 20 years that found protein intakes from 0.41 – 1.96 g/kg had no effect on calcium absorption efficiency. No differences in measured markers in the blood for bone turnover were found in either a high protein or high carbohydrate diet.

Studies have shown that various protein sources may exhibit different effects on bone metabolism. It has been shown that:

Animal Source = Higher serum levels of IGF-1

Soy foods/Products = Lower levels of IGF-1.

High levels of IGF-1 are related to bone growth. As individuals age, there are declines in serum levels of IGF-1 concentration.

Both the level of protein and the type of protein in your diet may have an effect of IGF-1 levels in the body.

What about Calcium Intake?

Protein intake increases urinary calcium loss, but whether there is a negative calcium balance, depends on dietary calcium intake.

Highest Protein Intake + Calcium/Vitamin D Supplementation = Positive Bone Health

Take Away Point


High levels of protein do not result in bone demineralization or a decrease in bone mass. High protein diets, rich in calcium help to increase bone mineralization and decrease the risk of fracture.

Source: https://www.ncbi.nlm.nih.gov/m/pubmed/18469289/