The diabesity epidemic in the light of evolution: insights from the capacity-load model

Abstract

The global nutrition transition, which embraces major changes in how food is produced, distributed and consumed, is associated with rapid increases in the prevalence of obesity, but the implications for diabetes differ between populations. A simple conceptual model treats diabetes risk as the function of two interacting traits: 'metabolic capacity,' which promotes glucose homeostasis, and 'metabolic load', which challenges glucose homoeostasis. Population variability in diabetes prevalence is consistent with this conceptual model, indicating that the effect of obesity varies by ethnicity. Evolutionary life history theory can help explain why variability in metabolic capacity and metabolic load emerges. At the species level (hominin evolution), across human populations and within individual life courses, phenotypic variability emerges under selective pressure to maximise reproductive fitness rather than metabolic health. Those exposed to adverse environments may express or develop several metabolic traits that are individually beneficial for reproductive fitness, but which cumulatively increase diabetes risk. Public health interventions can help promote metabolic capacity, but there are limits to the benefits that can emerge within a single generation. This means that efforts to curb metabolic load (obesity, unhealthy lifestyles) must remain at the forefront of diabetes prevention. Such efforts should go beyond individuals and target the broader food system and socioeconomic factors, in order to maximise their efficacy.

Keywords: Body composition; Capacity–load model; Diabetes; Evolution; Life course development; Public health; Review.

Fig. 1

The capacity–load conceptual model. (a) Greater metabolic capacity promotes glycaemic homeostasis; however, the development of metabolic capacity in early life is adversely influenced by several components of maternal malnutrition. Metabolic load is detrimental for glycaemic homeostasis, leading to higher blood sugar levels, and a number of components of an individual’s lifestyle exacerbate this effect. (b) Three-dimensional diagram of the interactive associations of metabolic capacity and load with diabetes risk. (a) Adapted from [30] under the terms of the Creative Commons Attribution License (CC BY), which permits use, distribution or reproduction in other forums; (b) adapted with permission from [9], ©2010 Wiley-Liss, Inc. This figure is available as part of a downloadable slideset

Fig. 2

Patterns of diabetes prevalence and metabolic risk markers across 80 countries. (a) Diabetes prevalence and obesity prevalence in women. (b) Diabetes prevalence and obesity prevalence in men. (c) Birthweight and adult female height. (d) Adult female height and birthweight. Red circles, South Asian population; blue triangles, Middle Eastern and North African populations; white circles, all other populations. Data sources: Obesity and diabetes prevalence (2014): www.ncdrisc.org; Birthweight (studies conducted before 1990): [23]; Female adult height (1996): [24]. This figure is available as part of a downloadable slideset

Fig. 3

Life history theory and trade-offs in energy allocation. (a) The basic model assumes that energy must be allocated between four competing traits. (b) An example of a trade-off, where activating immune function to overcome an infection temporarily reduces energy availability for other functions. (c) An intergenerational model, where the energy budget of offspring during early life is determined by the life history trade-offs made by the mother. Offspring allocations to maintenance and growth (highlighted in grey) are especially sensitive to this maternal allocation during early ‘critical windows of development’, generating life-long effects on diabetes risk, as summarised in Fig. 5. This figure is available as part of a downloadable slideset

Fig. 4

Schematic diagram illustrating how declines in adult height across generations drive a reduction in pelvic dimensions, which, in turn, forces a reduction in birthweight. This biological mechanism may have played a key role in the emergence of low birthweights in the Indian subcontinent over the last 10,000 years, through both genetic and plastic mechanisms. BP, before present. This figure is available as part of a downloadable slideset

Fig. 5

Schematic diagram of contrasting intergenerational cycles, characterised by developmental trade-offs that favour either (a) growth and maintenance or (b) survival and reproduction. Blue arrows represent life course developmental associations, red arrows represent cardiometabolic effects. These contrasting patterns favour different levels of maternal capital transfer to offspring, and favour the occurrence of similar trade-offs across generations. FFM, fat-free mass. This figure is available as part of a downloadable slideset