Today’s post comes from the Summer Issue of the Nutrition Close-Up, ENC’s newsletter that provides information on current nutrition and research trends and upcoming presentations. Please visit eggnutritioncenter.org to access the current and previous issues of the Nutrition Close-Up.
One size does not fit all when it comes to health. Be it diet, exercise, or prescription medications, what works wonderfully for one person may produce little effect or even the opposite effect in others. This is not surprising given metabolic differences between individuals. I remember observing this first-hand as an undergraduate student in a clinical chemistry course. Each student underwent some basic blood tests, and we compared results across the class. For some tests (e.g., liver enzymes), there was little variability among the students. But in others, there was quite a bit of diversity in results. For example, the blood glucose and insulin responses to an oral glucose tolerance test varied dramatically student to student. The athletic students in the class barely saw much rise in glucose, whereas several of the overweight students saw a dip in glucose below baseline in the late postprandial period (often called reactive hypoglycemia).
In conducting human nutrition intervention trials, I have gained an even greater appreciation for the inter-individual variability that occurs in response to diet and lifestyle interventions. However, this variability is often overlooked or unexplored. Mots scientific papers only report means for the subject population. The standard deviation of the mean can provide some insight into the variance of the dataset, but it does not provide descriptive information, such as the percent of the subject population that responded to a particular treatment. Yet in some cases, inter-individual variability may be important to our understanding of human health.
For example, there is a growing appreciation for understanding inter-individual variability with respect to achieving and maintaining an optimal body weight (i.e., specific genes, environmental factors, epigenetic effects, etc.). McClain et al. recently reported that women with insulin resistance were less successful in adhering to a low-fat weight loss diet and therefore, less likely to lose weight compared to those following a low-carbohydrate diet (1). The investigators hypothesize that higher carbohydrate intakes as part of a low-fat diet negatively influence glucose homeostasis, leading to greater levels of hunger. In an environment where highly palatable food is pervasive, it is easy to quell hunger the minute the urge strikes, compromising diet adherence.
In recent years, the gut microbiome has emerged as another factor that influences responses to diet and lifestyle factors, likely contributing to inter-individual variability in nutrition studies. There is a growing body of evidence that the diversity of bacteria within the gut microbiome is particularly important (2). For example, Santacruz et al. showed greater weight loss in a subset of individuals who showed more marked alterations in the diversity of gut microbiota in response to a calorie-restricted diet (3). Whether there are specific diet-microbiome relationships that further influence weight loss, as well as alter other aspects of physiology, remains to be determined. But based on the research to date, it seems highly likely that we are only beginning to understand the complex set of factors that not only make us who we are, but influence our responses to our environment, including diet.
If there is a theme in this issue of Nutrition Close-Up, it is this concept of “one size does not fit all” when it comes to nutrition. Differences between people, whether on a macro level (e.g., age, race, athletic status, dietary preferences, culture, etc.) or micro level (e.g., genetics, diversity of the gut microbiota, etc.), influence responses to diet. Given the increasing complexity of such differences, it may be decades before research provides solutions to prevent and manage chronic disease. In the near term, keeping abreast and appreciating such differences may be the best we can do.
- McClain AD, Otten JJ, Hekler EB, Gardner CD. Adherence to a low-fat vs. low-carbohydrate diet differs by insulin resistance status. Diabetes Obes Metab. 2013; 15:87-90.
- Erejuwa OO, Sulaiman SA, Ab Wahab MS. Modulation of gut microbiota in the management of metabolic disorders: the prospects and challenges. Int J Mol Sci. 2014; 15:4158-88.
- Santacruz A, Marcos A, Warnberg J, Marti A, Martin-Matilas M, Campoy C, Moreno LA, Veiga O, Redondo-Figuero C, Garagorri JM, Azcona C, Delgado M, Garcia-Fuentes M, Collado MC, Sanz Y; EVASYON Study Group. Interplay between weight loss and gut microbiota composition in overweight adolescents. Obesity (Silver Spring). 2009; 17:1906-15.