A lot of my vegan friends love high carbohydrate diets. On the whole, they tend to respond really well to them. But all too often, they make the deductive leap that because it works for them, then it must work for everybody. Low-carbers and keto-philes are equally guilty of this n=1 conundrum.
Someone recently approached me at a fitness expo and asked me whether they should be doing an 80-10-10 diet (80% carbs, 10% protein, 10% fat). I asked her in reply, “Why do you think you should do an 80-10-10 diet?” She went on to explain that she had been advised to try it by a fitness competitor who is an advocate of vegan, high-carb diets and had been on it for a number of months. So I asked “How’s that working out for you?” “Not well,” she replied. We went on to talk about what had worked for her in the past, and she realised that despite 80-10-10 working well for her friend, it certainly wasn’t the best option for her.
The essential truth is this: Whatever works well for me is not The Best Diet, even if it is the best diet for me.
This could be 80% of your calories, or 10%, depending on your genetics and other factors. [Photo credit: Pixabay]
The Current Science on Carb Tolerance
For the last few decades, I have promoted a method I call The Carbohydrate Appropriate Diet. With it, I seek to bridge the gap between low- and high-carb diets by looking instead at what is appropriate for any one individual based on their activity levels and genetic tolerance to carbs. Any good practitioner will recognise that different amounts of protein, carbohydrates, and fat affect individuals differently. This is why we should use ‘best-practice’ guidelines as a starting point for prescription, not an endpoint.
Several attempts have been made to describe this ‘metabolic typing’ or ‘metabolic tolerance,’ but currently there is no scientifically accepted way to determine this. Metabolic typing1 has failed to demonstrate different fat oxidation rates in different metabolic ‘types’;2 blood type diets3 don’t predict better outcomes for weight or cardiometabolic markers;4,5 and somatotyping (used to indicate relative ‘fatness,’ muscularity, and linearity of the physique) simply hasn’t been studied with respect to whether someone responds better to higher or lower amounts of carbs.
Based on emerging evidence, it seems that those who are more insulin resistant may lose more weight on a low-carb diet, while the more insulin sensitivity lose more weight on a higher carb diet.6,7,8 Low-carb diets may also promote greater improvements in HDL cholesterol, triglycerides, fasting glucose, insulin and blood pressure in insulin resistant people (but these results have not reached statistical significance).9 These findings are very preliminary, but important because of the growing rates of metabolic disorder and ‘pre-diabetes’, even among athletic populations.
But the problem with using insulin resistance to determine diet is two-fold: 1) Testing for insulin homeostasis is not commonly performed for ‘every day Joes,’ and 2) by the time you’re insulin resistant, the horse has already bolted. While it’s not fair to say insulin resistance (or at least the functional effect of it) isn’t reversible, it’d be nice to have a test or tests that can tell us someone’s carb tolerance before they become metabolically disordered.
There are exciting correlations between obesity and the copy number variants of a gene that codes for salivary amylase10 (the enzyme that begins the digestion of carbohydrate in the mouth). This ‘AMY1 copy number’ (AMY1 CNV) varies substantially among individuals and population groups.11 And populations which have traditionally consumed lower carbohydrate diets have fewer copy numbers of AMY1 compared to those from agricultural societies where starch is a prominent fuel source. So, this gene variation is likely to have evolved from nutritional pressures to allow the more efficient digestion of starch.12
The Best Diet Is the One That Works for You
I am currently working on performing randomised, controlled trials to evaluate several markers of carb-tolerance, and within the next few years we hope to have a much better idea of how to more accurately determine whether someone should be following a lower- or higher carbohydrate diet. But in the meantime the question is asked “Well what the heck should I do now?!”
For now, the best method is to use a step-wise approach to carb restriction to determine your unique tolerance. If you are doing fine now, eating loads of carbs, you’re lean, and your blood levels look great (low triglycerides, good HDL and LDL ratios, normal-low HbA1c) then stick to what you’re doing! But if you’re not as lean as you’d like to be or your levels (especially HbA1c and triglycerides) are not where they should be, make some adjustments. You can start to either peg back your total carb intake, or start to restrict classes of carbs until you are getting results and maintaining them. This restriction could be as simple as avoiding added sugars, all the way up to more extreme forms of ketogenic diets.
The most important thing to do is to look at your plate and make sure that 80% of what you see is natural, whole, unprocessed food. We have observed in clinical trials that when people focus on whole foods (and eat at least 6+ servings of veggies per day), they have a remarkable ability to ‘autoregulate’. In other words, they tend to not overeat, and they eat appropriate amounts of carbs, fat and protein for them without even trying to.
What can we glean about carb consumption from indigenous populations?
1. Wolcott, William L., and Trish Fahey. The Metabolic Typing Diet. New York: Doubleday, 2000.
2. Clarke, Daniel, David Edgar, Sam Higgins, and Andrea Braakhuis. “Physiological analysis of the metabolic typing diet in professional rugby union players.” New Zealand Journal of Sports Medicine 35, no. 2 (2008): 42-47.
3. D’Adamo, Peter. “Dr. Peter D’Adamo and the Blood Type Diet: Official Site.” Accessed September 09, 2016.
4. Wang, Jingzhou, Bibiana García-Bailo, Daiva E. Nielsen, and Ahmed El-Sohemy. “ABO Genotype, ‘Blood-Type’ Diet and Cardiometabolic Risk Factors.” PLoS ONE 9, no. 1 (2014). doi:10.1371/journal.pone.0084749.
5. Cusack, L., E. De Buck, V. Compernolle, and P. Vandekerckhove. “Blood Type Diets Lack Supporting Evidence: A Systematic Review.” American Journal of Clinical Nutrition 98, no. 1 (2013): 99-104. doi:10.3945/ajcn.113.058693.
6. Pittas, A. G., S. K. Das, C. L. Hajduk, J. Golden, E. Saltzman, P. C. Stark, A. S. Greenberg, and S.B. Roberts. “A Low-Glycemic Load Diet Facilitates Greater Weight Loss in Overweight Adults With High Insulin Secretion but Not in Overweight Adults With Low Insulin Secretion in the CALERIE Trial.” Diabetes Care 28, no. 12 (2005): 2939-941. doi:10.2337/diacare.28.12.2939.
7. Cornier, Marc-Andre, W. Troy Donahoo, Rocio Pereira, Inga Gurevich, Rickard Westergren, Sven Enerback, Peter J. Eckel, Marc L. Goalstone, James O. Hill, Robert H. Eckel, and Boris Draznin. “Insulin Sensitivity Determines the Effectiveness of Dietary Macronutrient Composition on Weight Loss in Obese Women.” Obesity Research 13, no. 4 (2005): 703-09. doi:10.1038/oby.2005.79.
8. Ebbeling, Cara B., Michael M. Leidig, Henry A. Feldman, Margaret M. Lovesky, and David S. Ludwig. “Effects of a Low–Glycemic Load vs Low-Fat Diet in Obese Young Adults.” Jama 297, no. 19 (2007): 2092. doi:10.1001/jama.297.19.2092.
9. Gardner, Christopher D., Lisa C. Offringa, Jennifer C. Hartle, Kris Kapphahn, and Rise Cherin. “Weight Loss on Low-fat vs. Low-carbohydrate Diets by Insulin Resistance Status among Overweight Adults and Adults with Obesity: A Randomized Pilot Trial.” Obesity 24, no. 1 (2015): 79-86. doi:10.1002/oby.21331.
10. Falchi, Mario, et al. “Low Copy Number of the Salivary Amylase Gene Predisposes to Obesity.” Nature Genetics 46, no. 5 (2014): 492-97. doi:10.1038/ng.2939.
11. Perry, George H., Nathaniel J. Dominy, Katrina G. Claw, Arthur S. Lee, Heike Fiegler, Richard Redon, John Werner, Fernando A. Villanea, Joanna L. Mountain, Rajeev Misra, Nigel P. Carter, Charles Lee, and Anne C. Stone. “Diet and the Evolution of Human Amylase Gene Copy Number Variation.” Nature Genetics Nat Genet 39, no. 10 (2007): 1256-260. doi:10.1038/ng2123.
12. Mandel, A. L., and P. A. S. Breslin. “High Endogenous Salivary Amylase Activity Is Associated with Improved Glycemic Homeostasis following Starch Ingestion in Adults.” Journal of Nutrition 142, no. 5 (2012): 853-58. doi:10.3945/jn.111.156984.