Integrative Bodybuilding: When It Comes to Diet, One Size Fits One

TAGS: protein absorption, body composition, genetics, Scott Stevenson, weight loss, fat loss, diet

Fad diets playing upon your desires…

In my thirty odd years as a consumer and provider in the health and fitness industry, I’m proud to say that I’ve developed a keen awareness of the obvious—tell people what they want to hear and you can sell them just about anything.

This is my best explanation as to why two diabolically opposite ploys are both effective in selling fad diets:

  • The magic bullet: There is a quick, easy, and nearly effortless “solution.” A one-size-fits-all packaged dietary “system” exists that is equally (and quite) effective for all people. To get amazing results, you need only focus on some magical food (or product) and/or essentially eliminate certain foods but for a short (tolerable) period of time.
  • You are a snowflake: You are special, biologically speaking, and this is encapsulated in a diet based upon your body type, blood type, hair style, handedness, or some other set of physiological bells n’ whistles that can be tallied up to determine your tailored (but still “canned”) dietary plan.

I won't be critiquing fad diets in this article, but if you plan to give one a shot, I encourage you to at least go beyond scratching the surface of its scientific underpinnings. (Of course, a fad diet might not actually have any scientific underpinnings.) For example, any statement of a scientific nature would logically be justified with a reference that you can find and check out for yourself. If, for instance, pickle juice has been “scientifically proven to melt away body fat,” there should be some readily available information that you can access about how that was demonstrated. (FYI, I don't have anything against pickle juice. It does seem to prevent muscle cramps and dehydration (1–3).)

Of course, this isn't to say that a “fad” diet can’t be effective if it provides structure and/or minimizes sources of significant caloric excess. Even a scientifically shameful sales gimmick can enhance your outcome if (some part of) you believes that it will work (4).

“Well, Scott, I’m not a food faddist.”

Don’t get me wrong. I recognize that if you’re reading this, you likely aren't getting nutritional guidance perusing magazines in the grocery store check-out line. However, even the scientists aren’t entirely in agreement on basic matters like whether caloric restriction is really all that is needed for effective weight loss (5, 6) or if a low carb approach is better than a low fat approach for short-term (7, 8) or long-term results (9).

With regard to one-size-fits-all, I’m often asked at what level, specifically, someone should set caloric and/or macronutrient intake for fat loss or muscle gain. If you’ve been in the bodybuilding game a while and/or have coached others, you’ll know that despite scientifically derived caloric expenditure prediction equations like those of Harris and Benedict (10), “cookie cutters” simply “don’t cut it” when it comes to effective dieting.

The food faddist “magic bullet” approach (not particularly favored among the scientific community (11) is really just an exaggerated form of the one-size-fits-all approach. Sports nutritional scientists are seeing in the data that this approach is a bit narrow-minded. When it comes to optimal protein intake for athletes, a range is typically given (12, 13), suggesting biological variability among individuals. Beyond this, others have recognized that effecting a change in muscle and strength requires a sufficient increase above and beyond habitual levels of protein intake (14). When it comes to dietary protein, what “works” depends on the person as well as that person’s nutritional context (habitual dietary starting point).

Gather a dozen clients in a room and ask an experienced bodybuilding coach whether the same dietary approach will work for all of them and he’d laugh at you. However, a typical scientific study utilizing groups of twelve subjects may not consider how this inter-individual variability affects statistical power (15).

Yes, you are a snowflake

When it comes down to how you respond to a diet, you are indeed as special as a snowflake. I’d like to introduce you to a very “hands on” pair of studies demonstrating how highly variable the responses are when packing on the pounds by overeating and when dropping body fat (in this case, by adding aerobic exercise into the equation).

Canadian researcher Claude Bouchard and colleagues located several pairs of (young, male) identical twins (i.e. those with identical DNA) to go the extra mile for these experiments. In both studies, the twins were sequestered under 24-hour surveillance for approximately three months. In the first study, they underwent “overfeeding” to the tune of 1000 kcal/day six out of seven days per week (100 days total) above and beyond an initial baseline calorically balanced diet (16). In the follow-up study, dietary energy intake was maintained, but the subjects put in two daily cardio sessions on the cycle ergometer, creating an average daily energy expenditure of 1000 kcal (93 days long) (17).

This wasn't a nonchalant effort on the part of Bouchard and colleagues. Both studies were preceded by two uninterrupted weeks within the facility to familiarize subjects with their new home, gather baseline measurements, and establish energy balanced (intake matches expenditure) baseline diets for each subject. Diet was controlled and adjusted daily by nutritionists, and food was eaten in the presence of two “watchers” to make sure that there wasn't any “cheating.” Exercise session energy expenditure was also monitored and adjusted on an individual and daily basis in the weight loss study. Essentially, when it comes to food and (aerobic) exercise, these studies did what every coach and personal trainer would love to be able to do—take full control of an athlete/client’s diet and exercise around the clock, 24/7.

So what happened?

You guessed it, Snowflake. The changes in body mass and composition were extraordinarily variable. In the “pack it on” study, subjects averaged a weight gain of approximately 18 pounds (12 pounds of fat), but this ranged from 9.5 to over 29 pounds! Changes in visceral fat ranged from virtually no change to an increase of over 200 percent. Not surprisingly, those who gained the most weight also tended to gain the most fat relative to fat-free mass. (These folks might be the ones who claim they can gain weight just by driving by a McDonald’s.)

During the “cut up with cardio” study, 12 pounds of body fat was lost on average, with essentially no loss of fat-free mass (on average). (Aside: Imagine if resistance training had been the exercise modality...) Weight loss ranged from approximately 2 to 17 pounds but wasn't correlated with the energy intake or energy expenditure. In other words, neither diet nor cardio were predictive of weight loss. This is because diet and cardio were intentionally tightly controlled from start to finish to create what would be the same caloric deficit if all subjects adapted identically. Indeed, the source of variation in weight loss wasn't the intervention (as intended) but rather how the subjects adapted to the caloric deficit imposed by exercise.

Genetics, baby.

The beauty of studying identical twins, barring differences due to previous environmental influence such as those affecting epigenetics (18, 19), is that doing so provides an excellent means of separating the experimental variability (by comparing genetically identical twin A with twin B) from variability due to the differences across the twin pairs. For instance, “identical” twins would respond differently primarily because of errors in controlling food intake or exercise expenditure but not because they have a different set of genes controlling metabolic adaptation. Variability across the sets of twins tells us about inter-individuality in biological response—not everyone is the same.

In the case of both Bouchard studies, the genetic influence on the adaptation to excess or deficient caloric intake, respectively, was abundantly clear. There was about six to seven times as much variance in weight changes spanning the pairs of twins compared to the variance within twin pairs. In the weight loss study, variation in fat loss across the different twin pairs was actually more than fourteen times as great as the variability noted when comparing twin to twin.

Back to the scenario I presented above. Gather six pairs of identical twins in a room and ask an experienced bodybuilding coach whether the same dietary approach will work for all of them. He might say, “Yes, maybe. I might be able to keep a few of those twin pairs on the same diet if I can hire an assistant to watch them around the clock and make sure that they don’t skimp out on their cardio. It would be easier simply to consider them individuals and adjust accordingly.”

It doesn’t stop there

Similar work by Bouchard and colleagues has shown that endurance exercise adaptations (improvements in aerobic power) are just as variable, and genetically linked, as the adaptations to caloric manipulation (20). A retrospective analysis of the overfeeding study showed that having higher androgen levels, smaller fat cells, and greater thermic responses to a meal were, as one might expect, predictive of more favorable gains in fat-free mass relative to body fat (21).  Since the initial Bouchard twin studies, a multitude of genetic markers have also been identified, suggesting that roughly 50 percent of physical traits related to body composition and physical performance are under strong genetic control (22, 23).

If repeated today, the Bouchard studies might have looked even more closely at variables that can affect weight gain and loss. For instance, non-exercise activity thermogenesis (i.e. fidgeting type activity) can add considerably to daily energy expenditure (24, 25). The Bouchard diets were based on initial caloric intake but standardized to a specific macronutrient ratio thereafter (50 percent carbohydrate, 35 percent fat, 15 percent fat), regardless of individual preference. Per the “protein leverage hypothesis” whereby protein intake is the predominant macronutrient guiding satiety, diets higher in protein might have proven more satiating during the weight loss experiment (26). A higher protein intake might also have evoked even better results in terms of body composition changes in the exercise study (27).

One size fits one, Snowflake

Physical and physiological characteristics as well as genetic markers are beginning to paint a clearer picture of DNA-driven control of body composition and exercise adaptation. For you, the dieter and/or coach trying to devise a way to a leaner and/or larger, more muscular individual, I suggest using these details as guideposts only. I’d be willing to bet that the identical twins out there reading this will agree—only one size fits you when it comes to your diet. This is true even if you don’t like it when I call you, “Snowflake.”

References

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  2. Miller KC, et al (2009) Electrolyte and plasma changes after ingestion of pickle juice, water, and a common carbohydrate-electrolyte solution. J Athl Train 44(5):454–61.
  3. Dale RB, et al (2003) A Compositional Analysis of a Common Acetic Acid Solution With Practical Implications for Ingestion. J Athl Train 38(1):57–61.
  4. Rosenthal R (2010) Pygmalion Effect. In: The Corsini Encyclopedia of Psychology. John Wiley & Sons, Inc.
  5. Katz DL (2003) Pandemic obesity and the contagion of nutritional nonsense. Public Health Rev 31(1):33–44.
  6. Katz DL (2005) Competing Dietary Claims for Weight Loss: Finding the Forest Through Truculent Trees. Annual Review of Public Health 26:61–88.
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  8. Yancy WS Jr, et al (2004) A Low-Carbohydrate, Ketogenic Diet versus a Low-Fat Diet To Treat Obesity and Hyperlipidemia: A Randomized, Controlled Trial. Annals of Internal Medicine 140(10):769–77.
  9. Bueno NB, et al (2013) Very-low-carbohydrate ketogenic diet v. low-fat diet for long-term weight loss: a meta-analysis of randomized controlled trials. Br J Nutr 110(7):1178–87.
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  19. Machin G (2009) Non-identical monozygotic twins, intermediate twin types, zygosity testing, and the non-random nature of monozygotic twinning: a review. Am J Med Genet C Semin Med Genet 151c(2):110–27.
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  23. Costa AM, et al (2012) Genetic inheritance effects on endurance and muscle strength: an update. Sports medicine 42(6):449–58.
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