An integrative approach to dietary balance across the life course

Abstract

Animals require specific blends of nutrients that vary across the life course and with circumstances, e.g., health and activity levels. Underpinning and complicating these requirements is that individual traits may be optimized on different dietary compositions leading to nutrition-mediated trade-offs among outcomes. Additionally, the food environment may constrain which nutrient mixtures are achievable. Natural selection has equipped animals for solving such multi-dimensional, dynamic challenges of nutrition, but little is understood about the details and their theoretical and practical implications. We present an integrative framework, nutritional geometry, which models complex nutritional interactions in the context of multiple nutrients and across levels of biological organization (e.g., cellular, individual, and population) and levels of analysis (e.g., mechanistic, developmental, ecological, and evolutionary). The framework is generalizable across different situations and taxa. We illustrate this using examples spanning insects to primates and settings (laboratory, and the wild), and demonstrate its relevance for human health.

Keywords: Endocrinology; biological sciences; evolutionary biology; physiology.

Graphical abstract

Figure 1

Hypothetical two-dimensional nutrient space representing protein and carbohydrate. Intakes of two individuals (Ind. 1 and Ind. 2) are shown by the red crosses Different colored regions within the space (hence different dietary compositions) are associated with maximization of different phenotypic traits—e.g., adiposity (brown), cardiometabolic and immune functioning (orange), or reproductive functioning (purple). Because the animal cannot simultaneously select more than one dietary composition, diet selection inevitably involves trade-offs where some functional outcomes are served better than others. Evolutionary theory suggests that natural selection should have shaped an organism’s appetite systems such that it selects the diet associated with a state that optimally trades off the different traits to maximize evolutionary fitness (intake target region). The coordinates of trait-specific maxima may change as the organism ages (e.g., maximal life expectancy at birth and at t-years-old could be different). The optimal trade-off between traits may also vary across environments causing the region maximizing fitness to move (black arrow). Relative positions loosely based on published data in mice.

Figure 2

Nutrient-specific foraging in wild monkeys (A) Daily macronutrient intakes by wild golden snub-nosed monkeys in spring and winter. Also shown is the seasonal difference in the cost of thermoregulation (329 kJ/Kg), which closely matched seasonal difference in fat and carbohydrate intake ( 326kJ/Kg). Modified with permission from Guo et al. (2018), (B) Macronutrient intakes by wild lactating (hollow symbols) and non-lactating (solid symbols) rhesus macaques in the spring of three successive years (red = 2013, green = 2014, blue = 2015). The negative diagonal lines show average energy intakes by the two categories of monkey across the three years. All data are presented as bivariate mean (±SE). Reproduced with permission from from Cui et al. (2018).

Figure 3

Estimated age-specific mortality of C57BL/6 mice (mixed sex), as a function of the ratio of dietary protein to carbohydrate (PC ratio) We assume an energy density of 15.77 kJ/g of food, with fat fixed at 3.77 kJ/g. The vertical black and purple dashed lines constitute a ratio of 0.3 (low PC) and 1.3 (high PC), respectively. Redrawn from data in Senior et al. (2019).

Figure 4

Effect on protein leverage (PL) of increased protein requirements relative to non-protein energy T1 represents the reference intake target, achievable on a diet with protein:non-protein energy ratio shown by the blue line labeled Diet 1. T2 represents an increased protein (P) requirement due, for example, to reduced nitrogen efficiency caused by an early history of being fed high protein infant formula (Raubenheimer et al., 2014). On a protein-dilute diet (Diet 2), the increased P requirement amplifies protein leverage, such that the over-ingestion of non-protein energy is greater for T2 than T1 (PL2 > PL1). Modified with permission from Raubenheimer and Simpson (2019a).