Introduction

Diabetes mellitus is an incurable chronic disease where blood sugar levels cannot be controlled. Conventionally, it has been broadly divided into two subcategories – type 1, an autoimmune condition, and type 2, an environmentally-induced condition. Type 2 diabetes (T2DM), the focus on this review, is currently increasing exponentially in prevalence worldwide. The classic explanatory model considers obesity (especially truncal fat) and physical inactivity the primary environmental causes.1, 2 The disease also clusters within families, indicating a heritable component of susceptibility.3, 4

The utility of this model is limited, however, as it fails to explain major differences in T2DM prevalence across geographical regions, or between ethnic groups inhabiting relatively similar environments. For example, China and India have rapidly acquired high prevalences among urban populations,5, 6 despite low levels of obesity according to criteria developed in European populations. Recent, a leading diabetologist argued that ‘T2DM is a disease in search of a definition’ and that our poor understanding of its heterogeneity is hindering global efforts to develop effective prevention strategies.7

The fact that T2DM risk is associated with each of (a) broader ecological factors (for example, level of economic development), (b) population factors (for example, ethnicity) and (c) developmental factors (for example, growth patterns) indicates a very complex scenario. An evolutionary perspective can shed more light on this complexity and integrate our understanding, by identifying broader mechanisms through which variability in diabetes susceptibility emerges, and then applying this approach to hominins and past and present humans.

A metabolic model of diabetes risk

T2DM can be considered a ‘two-hit’ disease, involving both insulin resistance in muscle tissue, and failure of the pancreatic beta-cells to produce enough insulin to compensate for this resistance.8 There is compelling evidence linking obesity with insulin resistance, although the connection may be bi-directional, involving positive feedback.9 However, poor early growth also contributes by reducing beta-cell function, which is further undermined by oxidative stress. Eventually, beta-cell ‘exhaustion’ provokes the transition from insulin resistance to overt diabetes.

Early studies on the developmental origins of T2DM identified elevated susceptibility among those born with low birth weight, initially interpreted as ‘fetal starvation’.10 Hales and Barker proposed the ‘thrifty phenotype’ hypothesis, which assumed that in response to fetal malnutrition, growth of organs such as the liver and pancreas was sacrificed to protect the vulnerable brain. This would promote short-term survival, but at a cost of reduced ability to tolerate a high plane of nutrition in later life.11

However, many studies show inverse dose-response associations of birth weight with later glucose intolerance across almost the full range of birth weight, with similar associations evident for thinness (low ponderal index) and length at birth,12, 13, 14 though T2DM risk increases again at high birth weights in some populations.15, 16 Thus, rather than overt fetal starvation provoking pathophysiology, there is a graded association between early growth and T2DM risk. Other non-communicable diseases show a very similar pattern.17

This spurred the development of a continuous ‘capacity-load’ model of disease risk, readily applied to T2DM. The approach emphasizes the interaction of two fundamental traits: ‘metabolic capacity’, referring to factors indexing the life-long capacity for homeostasis, and ‘metabolic load’, referring to factors that challenge homeostasis.18, 19 For T2DM, the most relevant components of metabolic capacity are beta-cell function (insulin production) and muscle mass (glucose clearance).20 Each of these traits is strongly contingent on fetal and infant growth patterns. The most relevant components of metabolic load are elevated adiposity (especially visceral adiposity), dietary glycemic load and sedentary lifestyle, all of which perturb glycemic control and promote insulin resistance and chronic inflammation, deleterious to beta-cell function.21, 22 However, psychosocial stress is also relevant.

Figure 1 illustrates the basic model, showing how the capacity-load relationship impacts regulation of blood sugar levels. Variability in this relationship over time then shapes the risk of developing diabetes. Longitudinal cohort studies support the model (Figure 2), illustrating the interactive effects of birth weight (a proxy for metabolic capacity) with markers of an unhealthy lifestyle, proxied by traits such as high body mass index, unhealthy diet, smoking and physical inactivity. For adults with healthy lifestyle, the diabetes risk following low birth weight is relatively modest, whereas for those with unhealthy lifestyle, risk increases strongly as birth weight declines.23

Figure 1
figure 1

Schematic diagram illustrating the basic capacity-load model of glycemic control, in which blood sugar levels rise in association with factors such as a high glycaemic diet, sedentary behavior and high body fatness, and decrease in proportion to the homeostatic capacity of the body, indexed by traits such as pancreatic beta cell mass and muscle mass. Reprinted with permission from Wells et al.20

Full size image
Figure 2
figure 2

The capacity-load model illustrated for the prospective risk of developing T2DMs in three US cohorts. Data from Li et al.23

Full size image

It should be emphasized that using growth traits to evaluate the capacity-load model does not address every mechanism through which adult disease susceptibility is shaped by developmental experience. For example, some fetal growth variability is not indexed by weight at birth or during infancy, while other mechanisms of developmental plasticity (for example, epigenetic effects) are also important.19 Nevertheless, interactive associations between early growth, adult phenotype and chronic disease risk have been widely replicated, and explain a substantial component of risk variance within and across populations.23

This simple model can be used to investigate T2DM risk in diverse ways, for example, exploring life-course risk-accumulation, ethnic differences in diabetes susceptibility20, 24 or longer-term evolutionary trends. Indices of body mass and activity patterns provide essential information about the magnitude of ‘metabolic load’, while stature or leg length represent simple markers of metabolic capacity, because they are associated with both birth weight and infant growth rate,25 which encompass key periods of pancreatic development.26, 27 Supporting this, many studies show an increased risk of T2DM in association with short stature, though a few populations do not follow this pattern.20 This inconsistency may emerge because in a few populations, taller individuals are also those most at risk of obesity.

Recently, this approach was used to provide an evolutionary perspective specifically on the elevated susceptibility of South Asian populations to T2DM.20 Here, I extend it into a broader evolutionary perspective. First, I argue that long-term trends in hominin body size and physique may have made humans generically at greater risk of T2DM compared to other primates. Second, I consider how subsequent diversification in body composition may have shaped ethnic differences in T2DM risk. In this broader context, South Asian populations appear to be merely at one extreme of a more general pattern of variability in T2DM susceptibility. Finally, I show how associations of phenotypic plasticity and T2DM can also be incorporated within an evolutionary perspective.

Long-term trends during human evolution

Through the 20th century, anthropologists assumed that hominin evolution had been driven primarily by adaptation to a relatively static savannah niche on the African continent. Most attention was directed to the emergence of traits shared by all humans, such as the large brain, bipedal locomotion and the capacities for language and material culture. Recently this perspective has undergone radical reappraisal, driven by growing awareness that hominin evolution occurred during a period when climate volatility steadily increased.28 Thus, the key ecological challenge facing our hominin ancestors derived not from a specific niche, but rather from the instability of any geographical niche over short and long-time periods.29, 30, 31 From 3.4 million years ago, Australopithecines were already able to tolerate major climatic instability in East Africa.32

Many components of hominin phenotype are now considered to represent ‘evolved solutions’ to such ecological volatility, including body size and composition, reproductive strategy, ageing profile, encephalization and bipedal locomotion.30, 33

Body composition can be considered a key component of this adaptive trend. Compared to other primates, including extent apes, contemporary humans have relatively low levels of muscle mass.34 This pattern continues a broader evolutionary trend, for primates themselves also show lower levels of muscle mass for their body mass compared to mammals in general, a scenario attributed to their specialization to arboreal habitats.35 Complementary to this trend in muscularity, adult humans of both sexes have greater adiposity than is typical of other tropical mammals, especially in females.36

Reconstructing body size, shape and composition in past hominins is notoriously difficult, as soft tissue does not preserve in the fossil record. The only option is to generate predictions from contemporary humans or primates. Each of these approaches must inevitably be imperfect, because hominins did not share associations between skeletal dimensions and soft tissue with either of these groups of organisms. Nevertheless, it is still informative to consider broader trends, using human data to interpret hominin skeletal characteristics.

Data on hominin size and shape have been reconstructed from fossilized skeletal dimensions,37, 38 giving estimations of height and weight for a range of different species. More recently, I developed an equation from diverse modern human populations that predicted lean mass from weight and height in each sex, which could then be applied to these hominin data.36

This approach identifies a broad decline among hominins in lean mass index (the lean component of body mass index), indicating increased ‘gracility’ from Australopithecus/Paranthropus to Homo, especially in females (Figure 3). In addition, both lean mass and fat mass indices show sexual dimorphism in most Homo species (H. rudolfensis, H. erectus and H. Sapiens, although not in H. habilis) in the opposite direction to that predicted for Australopithecines. As brain expansion occurred in species post-dating H. habilis, the reduced musculature and increased adiposity in Homo females may have helped meet the metabolic burden of producing large-brained offspring.39, 40

Figure 3
figure 3

Simulated trends in hominin body composition, plotting fat mass/height2 (FMI) against lean mass/height2 (LMI) which add up to body mass index (BMI). There is a broad trend to lower LMI in more recent hominins, especially in females, and the emergence of dimorphism in LMI and FMI in the main members of the genus Homo. Based on data from Wells.36

Full size image

If an alternative equation based on non-human primates is generated, only weight can be used to predict hominin lean mass, greatly reducing accuracy. Using this approach, no sex differences are predicted in any hominin, hence the approach fails for the one species (humans) where empirical evidence of body composition dimorphism is compelling.

Overall, this suggests that hominins would have become more prone to T2DM, by reducing the mass of lean tissue that could clear glucose. Nonetheless, the tendency for foragers to have at least moderate physical activity levels, combined with constraints on food supply, suggests that the emergence of overt T2DM may have been very rare. Indeed, a similar scenario can be seen in non-human primate species, where captivity typically elevates body fat levels and physical inactivity, provoking the spontaneous development of T2DM.41 This suggests that the fundamental physiology of diabetes risk is shared across primates, and that contemporary humans differ primarily in being more likely to experience environmental exposures that provoke the disease.

It might appear paradoxical that despite on average having relatively greater adiposity (metabolic load) and lower height and lean mass (markers of metabolic capacity), contemporary human females develop T2DM at higher body mass index values than males, and thus appear somewhat protected.42 This scenario can be explained by profound sex differences in the anatomical distribution of body fat. Females store reproductive fat in gluteo-femoral depots,43, 44 which in contrast to truncal and visceral fat are associated with insulin sensitivity and low diabetic risk.45, 46, 47 Thus, gender differences in fat distribution are themselves an indication that its ‘toxicity’ was an intrinsic stress during hominin evolution, and that females were selected to reduce this risk by storing fat in metabolically inert depots.

These body composition trends can be considered components of a broader reorganization of hominin life history strategy, in order to tolerate ecological volatility. Adiposity and plasticity in the schedule of growth and maturation (representing the sensitivity of both ‘capacity’ and ‘load’ to ecological stresses) emerged in combination with other components of phenotypic flexibility, such as cooperative breeding and longer lifespans. Collectively, all of these traits promote both (a) survival in tough conditions and (b) rapid reproduction during bountiful conditions (Table 1).33 The same traits are revisited later in this review, in the context of how diabetes risk is related to phenotypic plasticity within the life-course. Although hominin metabolism is often assumed to have adapted to guarantee the high energy demands of the Homo brain, an alternative hypothesis is that successful adaptation to stochastic environments generated a supply of energy sufficiently stable that encephalization became viable.33 From this broader Homo baseline, we can then consider how variability in morphology and metabolism might have emerged within the human species.

Table 1 Components of phenotypic plasticity and flexibility promoting adaptation to stochastic environments
Full size table

The emergence of population variability

Modern humans probably emerged ~20000 to ~150 000 years ago in Africa, although new calculation methods and richer genomic material constantly fine-tune these estimations.48, 49 Around 100 000 to 60 000 years ago, some populations dispersed out of Africa and progressively migrated across most of the global land mass. Australasia was reached at least 50 000 years ago, and the North American continent rather more recently.50, 51 The pattern of dispersal has clearly contributed to contemporary human diversity, mediated by the regional geographical routes taken, contrasting selective pressures and periodic local isolations, all of which have promoted inter-group differences and some genetic diversification.52, 53 Despite this, our species is characterized by remarkably high levels of genetic unity,54 fundamentally linked with our high levels of phenotypic plasticity. The selective pressures that favoured the capacity to tolerate ecological instability during hominin evolution have made modern humans extremely well adapted to colonising diverse environments.55

Both these migrations, and long-term exposure to diverse ecological niches, are widely assumed to have shaped variability within our species in metabolism and body size, morphology and composition. A complete picture is still emerging, but likely ecological stresses include the thermal environment, energy availability, dietary quality, pathogen burden and exposure to indices of volatility such as climate cycles.

Currently, the strongest evidence for adaptive variability in human body composition relates to the thermal environment. Since the 1950s, several studies have linked variation in human body size and shape with average annual temperature.56, 57 Physical laws suggest that organisms can promote heat loss by increasing their surface area relative to their mass, whereas heat conservation can be promoted by decreasing this ratio.58, 59 Broadly, humans show larger area-mass ratios in tropical relative to polar environments, and the length of body extremities is also greater in hot environments, maximizing heat loss from long slender limbs.57, 60, 61 Unsurprisingly, these patterns extend beyond shape to body composition, with lean mass relative to height scaling inversely in association with annual temperature.62

Low levels of lean/muscle mass have been linked with elevated susceptibility of populations such as South Asian and Australian aboriginals to insulin resistance in obesogenic settings,19, 20 and this scenario may apply to other populations with similar characteristics. Hence, climatic adaptation is very likely to have shaped T2DM susceptibility.

Body fatness also tends to increase in association with declining temperature, though in the past some polar populations had relatively low subcutaneous adiposity.62 Intriguingly, sexual dimorphism in body composition is itself associated with climatic conditions: for example, at colder temperatures males show a greater excess of lean mass relative to females, whereas females show greater adiposity relative to males.63

Historically, human body fat was widely assumed to have been selected as a defense against starvation, but this view is now considered very simplistic. There are numerous ‘fitness functions’ of adiposity, demonstrated by recent findings that the hormone leptin plays critical regulatory roles in maturation, reproduction and immune function.64, 65, 66, 67 An eco-geographical analysis identified an inverse association between subscapular skinfold thickness and markers of the local pathogen burden, suggesting that populations with high pathogen burdens metabolize central body fat to fund immune function.68 There is mechanistic support for this hypothesis, as visceral fat has high expression of genes involved in the complement system.69

This proposed link between adiposity and immune function has two important implications for contemporary variability in T2DM risk. First, populations that have experienced long-term exposure to high pathogen burdens might have an elevated predisposition to gain central fat in obesogenic settings. This is consistent with strong associations between economic development in low-/middle-income countries, efforts to reduce infectious diseases and rapid increases in waist circumference. Second, the specific diseases to which individual ethnic groups have experienced long-term exposure might have additionally shaped the metabolic profile of adipose tissue. The ‘variable disease selection’ hypothesis (Figure 4) posits that humans may have adapted to specific pathogens by favouring energy storage in specific regional fat depots, and by developing specific cytokine profiles.70

Figure 4
figure 4

Schematic diagram illustrating the ‘variable disease selection’ hypothesis, positing that different local infectious disease burdens select for contrasting anatomical distributions and cytokine profiles of adipose tissue.

Full size image

Regardless of whether this specific hypothesis is correct, ethnic differences in body fat distribution, lepin and cytokines are already well established.62, 68, 71, 72 In UK children, the association between adiposity and insulin resistance differs by ethnicity, so that body fat appears to be ‘more toxic’ in those of South Asian ancestry.73 Since the energy-deficit imposed by starvation can be assumed to be a human ‘constant’, and since most starvation deaths occur via infection, the notion that ethnic differences in adipose tissue biology may have been shaped by local infectious disease burdens merits further consideration.70

Overall, therefore, broader geographical stresses such as climate and pathogen burden appear to have promoted human variability in physique, impacting components of both metabolic capacity and metabolic load.19 However, the mechanisms underlying this variability remain poorly understood. It might be assumed that ethnic differences in physique and metabolism reflect genetic differences, but this issue is increasingly undergoing re-evaluation.

Variability in diabetes susceptibility: Genetics

In a classic article, Neel proposed that populations exposed to regular cycles of ‘feast and famine’ adapted by developing ‘thrifty genotypes’, coding for traits favouring ready accumulation of fat stores during spikes in food supply.74 Initially, such thriftiness was attributed to a fast insulin response, but others considered muscle insulin resistance the key mechanism, diverting excess energy to adipose issue.75 Regardless, thrifty genes were predicted to increase T2DM susceptibility following exposure to ‘permanent feast’ conditions, equivalent today to energy-dense diets and physical inactivity following economic development.

Although this hypothesis has stimulated substantial research, adiposity is now well recognized to be a polygenic trait, and as yet, very few candidate genes linking obesity and T2DM risk have been identified. More generally, few examples of metabolic adaptation to local ecological conditions have been identified. Rather, genetic variability in human metabolic phenotype can largely be attributed to geographic variability in gene frequencies.76, 77 For example, one study showed that the prevalence of T2DM ‘risk-alleles’ decreases in relation to the population’s distance from Africa, suggesting that increasing exposure to non-African environments favoured cumulative ‘diabetes protection’. Within that scenario, most T2DM risk-alleles appear to exert similar directions and magnitudes of effects in different ethnic groups,78 though there are exceptions such as the FTO gene.79 Most likely, geographical variability in human body composition derives in part from variability in the frequency of genes shaping early-life growth patterns and adult morphology and metabolism. However, the nature of any such adaptation is still being established.

More recent work has linked genes with both low birth weight and T2DM risk in adulthood.80 It remains unclear if such genes generate specific pathophysiological effects, or whether they merely shape growth trajectory at a broader level. I have previously suggested that natural selection must have favoured a polygenic basis for fetal growth, where each gene must have a very small magnitude of effect. Any gene producing a large increment in birth weight would be under strong selection from the stress of cephalo-pelvic disproportion, through the tendency for mothers malnourished in early life to grow small pelvises by adulthood.81

Initially, the elevated T2DM susceptibility of Pima Indians living in the US was considered some of the best evidence supporting the thrifty genotype hypothesis.82 Certainly, T2DM risk has a genetic component in this population, but recent studies suggest that chronic under-nutrition through the 20th century elevated their T2DM susceptibility through intergenerational plasticity.83, 84 This scenario is consistent with animal studies, where chronic under-nutrition over multiple generations causes profound changes in offspring epigenetics, growth and metabolism.85, 86

This scenario fits the ‘capacity-load’ model described above, which acknowledges that a component of T2DM risk derives from nutritional experience in development. Moreover, there is little doubt that the primary factor driving the global T2DM epidemic is the ‘nutrition transition’, driving changes in multiple forms of behavior. Beyond genetics and selection, an evolutionary perspective can help understand why patterns of nutrition and growth through the life course have such profound impact on T2DM risk.

Variability in diabetes susceptibility: plasticity

One attempt to develop an evolutionary model of developmental plasticity and adult chronic disease was the ‘predictive adaptive response’ hypothesis.87 This proposed that malnourished fetuses developed ‘thrifty’ traits that would be well adapted to famine, anticipated to persist in adult life. For T2DM, insulin resistance and central fat were specifically identified as ‘predictive adaptive responses’. However, this hypothesis has been strongly criticized on several grounds. First, long-term ecological prediction is implausible.88 Second, malnourished infants are not insulin resistant at birth, but rather acquire this phenotype if they develop overweight from childhood onwards.89 Third, outside obesogenic settings, those born with low birth weight do not develop insulin resistance or central fat.90 Alternative explanatory models are therefore required.

Unlike the predictive adaptive response hypothesis, evolutionary biologists conventionally address plasticity using life history theory. This assumes that every organism has finite quantities of energy, and must invest it optimally across four competing functions: maintenance, growth, reproduction and defense against pathogens/predators.91 Faster life histories are favoured in high-risk environments: for example, elevated extrinsic mortality risk accelerates the ‘pace’ at which the organism passes through the life course. Faster life histories inherently reduce investment in growth and long-term maintenance, prioritizing instead survival and reproduction.92, 93

From this perspective, a key benefit of ‘maintenance’ comprises protection against T2DM, through glucose homeostasis at the level of tissues and organs, and the suppression of oxidative stress at the molecular level.94 Stresses during early life alter energy-allocation patterns, potentially reducing investment in ‘maintenance’ and growth with long-term detrimental effects on homeostasis. Such stresses may derive directly from inadequate energy supply, or indirectly from allocating more energy to immune function.

For example, ecological instability early in life limits the acquisition of lean tissue. In Peru, children born around the time of the 1998 El Niño event showed reduced height and lean mass later in childhood compared to those unexposed, but no difference in adiposity.95 In other words, contemporary variability in physique tracks local ecological conditions along exactly the same lines as suggested for long-term hominin evolution.

More generally, phenotypic plasticity in humans has been selected to allow accommodation of prevailing ecological conditions in ways that maximize survival and reproduction (Table 1). This constellation of plastic traits provides over-arching flexibility in life history trajectory, allowing individuals to select a ‘slower’ or ‘faster’ trajectory depending on the conditions encountered during the life-course.

This is consistent with life-course research that has linked a series of developmental traits with T2DM susceptibility. These include lower birth weight, poor infant growth, rapid childhood weight gain, early puberty and short adult stature (Figure 5).12, 20, 96, 97 All these traits are markers of a faster life history, indicating how T2DM risk is shaped by the cumulative adjustment of developmental trajectory to ecological conditions to maximize fitness.19

Figure 5
figure 5

Schematic diagram (not to scale) illustrating the accelerated life history trajectory associated with chronic diseases (dotted line) relative to the slower and healthier trajectory (continuous line). While the second part of the healthy trajectory builds a larger body, this occurs slowly, and follows higher growth rates during fetal life. The faster life history trajectory superimposes a high metabolic load on a diminished metabolic capacity. Reprinted with permission from Wells.19

Full size image

T2DM develops over time, and overt disease typically occurs from middle-age onwards, following the accumulation of metabolic damage. In environments with high extrinsic mortality risk, such as the constant threat of fatal infectious disease, a high proportion of individuals would not live long enough to benefit from investing in homeostasis to an extent that would minimize metabolic deterioration in old age. Instead, fitness would be maximized by investing in reproduction, at the cost of ‘maintenance’, and only a small proportion who by random chance survived past middle-age would pay the long-term costs, for example, by developing T2DM at post-reproductive ages (Figure 6). This helps understand the ‘thrifty phenotype’ as a developmental strategy, trading off short-term survival and reproduction against longevity.

Figure 6
figure 6

Schematic diagram of extrinsic risk, life history strategy and metabolic phenotype.

Full size image

However, low maternal investment may provoke exactly the same response in the offspring, by reducing the intrinsic ‘somatic quality’ of the offspring. During fetal life, when much developmental adjustment occurs, the primary environmental influence is maternal phenotype.19 Low maternal investment constrains the offspring’s long-term capacity for homeostasis, making it more vulnerable to diverse risks. Once again, the best response is to shunt energy towards reproduction, in order to maximize reproductive fitness before mortality occurs.93 This hypothesis is supported by a study of South Asian women living in the UK. Those with low birth weight (indicating low maternal investment during early ‘critical periods’) showed faster maturation, shorter adult height, higher adiposity and higher blood pressure (Figure 7). This indicates a fast life history strategy: investing in maturation and storing energy for reproduction, at a cost to growth and homeostasis.

Figure 7
figure 7

Empirical associations between maternal investment (proxied by birth size), maturation rate and adult phenotype in adult south Asian women. (a) Birth weight is directly associated with age at menarche. (b) Earlier menarche is associated with lower adult stature. (c) Earlier menarche is associated with higher adult subscapular skinfold. (d) Subscapular skinfold is positively associated with adult systolic blood pressure. Reprinted with permission from Wells et al.92

Full size image

In high-risk environments, where every offspring has a fair chance of random death, even well-nourished mothers will optimize their fitness by producing greater numbers of smaller offspring, rather than smaller numbers of large robust offspring. For multiple reasons, therefore, offspring size is expected to decrease in association with environmental risk, with implications for long-term T2DM risk.

Ethnic differences in birth weight are strongly implicated in differential susceptibility to T2DM, but it remains unclear whether, for example, relatively low birth weights in South Asian populations indicate genetic adaptation to past environments, or more recent intergenerational plasticity mediated by chronic under-nutrition. A recent study of parental ethnicity shed some light on this issue.

The study analyzed UK birth weight data, stratifying by European or Indian ethnicity of each parent. Compared to two European parents, two Indian parents produced a baby on average ~400 g lighter.98 This describes the overall difference of Indians versus Europeans in a high-income setting, but does not identify the underlying mechanism. Holding paternal ethnicity constant, Indian mothers produced offspring on average ~250 g lighter than European mothers. Maternal phenotype clearly makes a key contribution, but whether via genotype or metabolic phenotype remains unclear.

Among Indian mothers, birth weight averaged ~250 g more if the father was European, rather than Indian. This indicates that the nutritional constraint imposed by Indian mothers is not fixed, and can be modulated by the father. Conversely, among European mothers, birth weight averaged ~100 g lower if the father was Indian, rather than European. Thus, birth weight was apparently constrained by Indian paternity. Collectively, these results indicate some degree of paternal ‘adaptation’ in the Indian population to chronic maternal under-nutrition, involving either epigenetic or genetic mechanisms, through the medium of ‘parent-offspring conflict’ over fetal nutrition.97

Given that increased supplies of energy should promote investment in life-long ‘maintenance’, why are economic development and the nutrition transition so strongly implicated in the global epidemic of T2DM? There are several reasons. First, the acquisition of fat stores is occurring much faster than reductions in the prevalence of low birth weight or stunting. In other words, changes in metabolic load are substantially greater and faster than changes in metabolic capacity.99 Thus, each generation in chronically undernourished populations still starts life with an elevated susceptibility to T2DM, which is then activated by the impact of economic development via obesity and sedentary behavior. Second, the nutrition transition is not simply a shift to greater energy supply, rather it has deep structural connections with power relations at many levels of society, both within populations and between nations.19 The transition involves major changes in dietary quality, accompanied by exposure to multiple technologies that collectively promote sedentary lifestyles.

All of these changes are driven by the maximization of profit through repetitive behavior. In many cases, corporations based in high-income countries now sell to low/middle-income countries products (for example, tobacco, or foodstuffs high in trans-fats or refined carbohydrate) that in the high-income country have already been banned outright, or strongly targeted by public health policies. These products are not metabolically ‘neutral’, rather they are characterized by properties that favor repetitive consumption, and thereby themselves drive the nutrition transition. In this sense, unhealthy commodities play a key role in the ‘metabolic manufacturing of consent’ for economic development: those consuming them appear to legitimize the underlying politico-economic system.19 Populations of low/middle-income countries that, for reasons described above, have lower metabolic capacity are both more vulnerable to gaining excess metabolic load though the nutrition transition, and arguably less able to resist the corporate influences that drive the transition.

Conclusions

This article has presented a relatively simple evolutionary model of T2DM susceptibility, focusing on variability in two generic metabolic traits: those that help maintain homeostasis, and those that challenge homeostasis. My hypothesis is that both traits are prone to variation on several different timescales – long-term hominin evolution; the population-diversification that occurred as humans dispersed out of Africa into multiple ecological niches; and individual life-courses mediated by diverse ecological stresses, many transmitted across generations. The consequence is a wide spectrum of T2DM susceptibility within and across populations. Better understanding of this variability may improve the development of public health programs intended to reduce the burden of this disease.