The Triple Burden of Malnutrition in the Era of Globalization

Introduction

The term “triple burden of malnutrition” refers to the coexistence of undernutrition (stunting and wasting), micronutrient deficiencies (often termed hidden hunger), and overnutrition (overweight and obesity) (Fig. 1). 

Globally, there is a strong inverse association between a country’s wealth measured as gross domestic product (GDP), undernutrition, and levels of micronutrient deficiencies (Fig. 2 ^{[1, 2]}). As countries pass through the economic transition and gain in wealth, it is gratifying to see that rates of undernutrition decline rapidly. But conversely, rates of overnutrition seem to inexorably grow with increasing wealth (Fig. 3). This overcorrection has not yet been successfully avoided by any emerging nation.

The three elements of the triple burden of malnutrition can be found simultaneously within many low-income populations and even within single families ^[3–5]. Initially, overweight and obesity are confined to the wealthier sectors of emerging societies, but after a decade or two, the demographic association flips and overweight becomes more prevalent among the poorer strata ^{[6, 7]}. 

There are common underlying causes to each element of the triple burden of malnutrition ^[8]. In broad terms these are as follows: poverty – a lack of access to the most nourishing foods; poor dietary choices – a lack of knowledge about what constitutes the most nourishing foods and a healthy diet; and food supply chain – production and marketing of cheap, low-quality foods. Some of these may be exacerbated by future threats to the food supply chain arising from climate change and a degraded planet.

It can be argued that the underlying influence of these distal factors are channeled through a single proximal cause – namely a low nutrient density of foods as summarized below.

Undernutrition

Stunting and wasting result from deficits of energy and protein supply. These deficits are often, but not always, consequent upon a poor dietary supply. Examination of aggregated growth curves from low- and middle-income countries reveals a precipitate decrease in weight, and especially in height z-scores in the first 2 years of life with a stabilization thereafter ^[9]. There is strong evidence to suggest that, in addition to the influence of low-quality weaning foods, infections are an important contributory cause and that nutrient deficits are exacerbated by a combination of loss of appetite, episodic periods of acute weight loss, chronic suppression of the insulin-like growth factor axis consequent upon inflammation, and nutrient malabsorption caused by chronic gut damage (so-called environmental enteric disease) ^[10].

In the light of this understanding of the important role of infections in driving undernutrition, there was great hope that implementation of water, sanitation and hygiene (WASH) interventions would reduce the prevalence of diarrhea and environmental enteric disease and hence improve growth. Three large randomized trials in Bangladesh, Kenya, and Zimbabwe tested the impact of improved WASH (with and without advice on infant and young child feeding based upon WHO’s recommended best practice) ^[11–13]. Disappointingly, the WASH interventions did not improve linear growth. It seems likely that the absence of impact can be attributed to the fact that there is a high hygiene threshold that must be overcome ^[14], and this has led to calls for so-called “transformative WASH” ^[15].

The importance of having a high energy density in the weaning diets of undernourished infants was elegantly demonstrated in a small intervention trial from Bangladesh [16]. This trial illustrates how manipulation of the energy density of weaning foods, together with enhanced feeding frequency, can greatly increase overall energy intakes in partially breastfed infants ^[16]. The investigators studied 18 stunted Bangladeshi infants aged 8–11 months. They offered 3 different complementary weaning foods with energy densities of 0.5, 1.0, or 1.5 kcal/g on 3, 4, or 5 occasions a day. The mothers were encouraged to continue breastfeeding as usual and breast milk intake was assessed by test weighing. Increasing the energy density and increasing the feed frequency of the weaning food each independently increased the weanlings’ overall energy intake. There was a small consequent reduction in breast milk intake, but, even accounting for this, there were clear increases in energy intake as summarized in Figure 4.

This example can be extrapolated to other nutrients for which a higher nutrient density would inevitably provide a higher overall nutrient intake. In fact, given that other nutrients would not suppress breast milk intake as was the case for energy, the net benefits would be even greater. It should be noted also that a high nutrient content of diets is especially important in periods when children are attempting catch-up growth as is frequently the case after infection-related bouts of weight faltering ^{[17, 18]}.

Micronutrient Deficiencies

It is self-evident that most micronutrient deficiencies are caused by a low nutrient density of diets (which generally arises from low dietary diversity and poor access to animal-sourced foods) and that consumption of higher-quality diets is constrained by multiple factors in poor populations (as summarized by Black et al. ^[3]). Consequently, there tend to be strong associations between deficiencies of different micronutrients; a child deficient in one micronutrient will, in general, suffer from multiple deficiencies.

The two main exceptions for which there is not always a clear association between intakes and deficiency are vitamin D (for which sunlight is a critical additional mediator) and iron.

Vitamin D deficiency is more common in higher latitudes and in circumstances where mothers and children have reduced exposure to sunlight for cultural reasons and/or have darker skins, which modulates the conversion of inactive to active vitamin D3. A review of the global prevalence of vitamin D deficiency highlights the importance of such variables ^[19]. Using cutoffs for 25(OH) D levels of <30 nmol/L (12 ng/mL), <50 nmol/L (<20 ng/mL), and <75 nmol/L (30 ng/mL) severe vitamin D deficiency (<30 nmol/L) in infants and young children is highly prevalent in some countries in the Middle East and Indian subcontinent, for example, Iran 86%, Turkey 51%, Kuwait 66%, Pakistan 33%, and India 61%. In the United States, the prevalence of moderate (<50 nmol/L) deficiency was 10% in white infants and 46% in black infants. Rates of deficiency are generally lower in Africa and especially in Central Africa where sun exposure is greatest ^[20]

In the case of iron, there are several infectious insults that can contribute to iron deficiency including intestinal helminth infections ^[21] and malaria ^[22]. Additionally, there are self-protective mechanisms – mediated by the hormone hepcidin – that have evolved to intentionally block intestinal iron absorption in the face of a threat of infection ^[23]. Hepcidin is upregulated by infections and inflammation and blocks both the absorption of iron by the enterocyte and its recirculation by macrophages. Our recent research has shown that Gambian infants sustain levels of hepcidin that inhibit iron absorption for an average of 50% of time and that the high hepcidin levels are promoted even at rather low levels of inflammation ^[24] and that respiratory infections were a major contributor to the inflammation and hence the deficit in iron status ^[24]. Under such circumstances, children may develop iron deficiency and anemia even against a background of a reasonable dietary iron supply.

Note that, as with the issues in relation to linear growth discussed above, interventions such as WASH that could reduce the infectious load should be effective in reducing the prevalence of iron deficiency. Unfortunately, as with linear growth, there was no benefit of WASH intervention on hemoglobin level ^[13]

Overnutrition

There is considerable evidence that overnutrition is driven by an excess consumption of foods that have a high or very high energy density ^{[25, 26]}. This arises from an asymmetry in human appetite control. Humans have a strong hunger drive, but weak satiety mechanisms in the face of foods with artificially enhanced energy density ^[27]. We demonstrated this in a series of experiments in which the fat (and hence energy density) of foods fed to volunteers was covertly manipulated while they lived in whole-body calorimeters that measured their energy and macronutrient balance with great precision. When asked to eat freely from a diet with 20% fat, the volunteers spontaneously went into negative energy balance and lost body fat ^[28]. At 40% fat, the volunteers remained in approximate energy balance, but at 60% fat, they gained over 50 g body fat per day. A remarkable observation was that the volunteers were entirely unaware of this gain and their physiological systems seemed to have no mechanism for autoregulatory homeostatic control. This result was subsequently replicated in free living volunteers ^[29]. Importantly, the effect of changing the fat: carbohydrate ratio of the diets was eliminated when energy density was maintained equal across the three treatments ^[30].

Food processing practices that involve high extraction rates for energy in the forms of refined carbohydrates and oils are a key feature of the era of globalization but had their origins many decades ago. Such trends started in North America and Europe, and both the postharvesting manufacturing practices and the products themselves (with the associated marketing practices) have been exported to most regions of the world ^[7].

There is an almost overwhelming literature linking highly refined foods (now frequently termed ultra-processed foods) with obesity and the consequent serious morbidities of obesity-related noncommunicable diseases. In this short overview of the triple burden of malnutrition, it is not possible to provide a comprehensive summary of the evidence; therefore, some selected exemplars are discussed to underscore the key public health messages.

Without the use of long-term intervention trials, it is theoretically impossible to confirm causality in the link between the high consumption of ultra-processed foods and obesity, but association and time course studies – backed by the physiological evidence for the plausibility of such linkage – make it hard to refute a causal link. An ecologic study across 19 European countries recorded availability of ultra-processed foods ranging from 10% of energy in Portugal to 50% in the United Kingdom ^[31]. After adjustment for a range of likely confounding factors, they found that each percentage point increase in the household availability of ultra-processed foods resulted in an increase of 0·25% points in obesity prevalence. Thus, the difference between Portugal and the United Kingdom could account for a 10% difference in obesity rate.

Foods containing high proportions of ultra-processed ingredients tend to be associated with high intakes of free sugars, sodium, and saturated and trans fatty acids and low intakes of dietary fiber and potassium ^[32]. Unless they are fortified, such foods generally have low intakes of essential vitamins and minerals and thus contribute to a diet with low nutrient density, thus compounding the threat of the triple burden of malnutrition.

There has been considerable research examining the associations between ultra-processed foods, body weight, and noncommunicable diseases with several meta-analyses available ^{[33, 34]}. Association studies are inevitably vulnerable to multiple confounding, whereby a propensity toward excess consumption of ultra-processed foods is likely to be associated with many other lifestyle and dietary factors, which cannot be adequately captured in attempts to adjust for these covariates. Nonetheless, there is compelling and unsurprising evidence that people who consume high amounts of ultra-processed foods are more likely to be overweight or obese.

Sugar-sweetened beverages (SSBs) have also been the target of extensive research to test whether excess consumption is associated with obesity. Most research has involved cross-sectional association studies and meta-analyses thereof ^[35], but randomized controlled trials and associated meta-analyses have also been published ^[36] together with analyses of the impact of legislation (e.g., increasing taxes on SSBs, mandatory labeling) on consumption patterns and national obesity rates ^{[37, 38]}. As with ultra-processed foods, association studies are vulnerable to multiple confounding. Notwithstanding this important limitation, there seems to be an association between high-SSB consumption and obesity (though the size of the effect on body mass index is likely less than 1 body mass index unit, i.e., under 2 kg of body weight). Randomized controlled trials provide moderately strong evidence that targeting a reduction in SSBs helps to reduce overall energy intake ^[39]. For further reading on this issue, readers are referred to the recent USDA’s Nutrition Evidence Systematic Review, which provides a comprehensive and judicious summary on the effects of milk, fruit juice, and SSB intakes on body weight and obesity ^[40]

A Unifying Concept for Tackling the Triple Burden of Malnutrition

It has been argued above that each of the three elements of the triple burden of malnutrition can be ascribed, at least in part, to a low nutrient density of foods and diets. Accordingly, encouraging mechanisms to put a greater emphasis on access to, and consumption of, higher quality foods would help provide a unifying solution to the triple burden of malnutrition. Such a transformation requires changes at all levels from agricultural and manufacturing practices, through marketing and distribution, and especially to educational campaigns. National governments have various levers available, through which they can enhance their country’s nutritional well-being. Until such a time as these systemic changes have occurred, nutritional education of mothers and families can achieve a great deal.

References 

1. Muthayya S, Rah JH, Sugimoto JD, Roos FF, Kraemer K, Black RE. The global hidden hunger indices and maps: an advocacy tool for action. PLoS One. 2013;8:e67860. 
2. Feenstra RC, Inklaar R, Timmer MP. The next generation of the Penn World Table. Am Econ Rev. 2015;105:3150–82. 
3. Black RE, Victora CG, Walker SP, et al. Maternal and child undernutrition and overweight in lowincome and middle-income countries. Lancet. 2013;382:427–51. 
4. Doak CM, Adair LS, Bentley M, Monteiro C, Popkin BM. The dual burden household and the nutrition transition paradox. Int J Obes. 2005;29:129–36.
5. Kimani-Murage EW, Muthuri SK, Oti SO, Mutua MK, van de Vijver S, Kyobutungi C. Evidence of a double burden of malnutrition in urban poor settings in Nairobi, Kenya. PLoS One. 2015;10:e0129943.
6. Stunkard AJ. Socioeconomic status and obesity. Ciba Found Symp. 1996;201:174–82.
7. Popkin BM. The nutrition transition: an overview of world patterns of change. Nutr Rev. 2004;62:S140–43.
8. Prentice AM. The double burden of malnutrition in countries passing through the economic transition. Ann Nutr Metab. 2018;72(Suppl. 3):47–54. 
9. Victora CG, De Onis M, Hallal PC, et al. Worldwide timing of growth faltering: revisiting implications interventions. Pediatrics. 2010;125:e473–80. 
10. Humphrey JH. Child undernutrition, tropical enteropathy, toilets, and handwashing. Lancet. 2009;374:1032–5. 
11. Luby SP, Rahman M, Arnold BF, et al. Effects or water quality, sanitation and handwashing, and nutritional interventions on diarrhoea and child growth in rural Bangladesh: a cluster-randomised trial. Lancet Global Health. 2018;6:e302–15.
12.  Null C, Stewart CP, Pickering AJ, et al. Effects or water quality, sanitation and handwashing, and nutritional interventions on diarrhoea and child growth in rural Kenya: a cluster-randomised trial. Lancet Global Health. 2018;6:e316–29.
13. Humphrey JH, Mbuya MNN, Ntozini R, et al. Independent and combined effects of improved water, sanitation and hygiene, and improved complementary feeding, on child stunting and anaemia in rural Zimbabwe: a cluster-randomised trial. Lancet Global Health. 2019;7:e132–47. 
14. Husseini M, Darboe MK, Moore SE, Nabwera HM, Prentice AM. Thresholds of socio-economic and environmental conditions necessary to escape from childhood malnutrition: a natural experiment in rural Gambia. BMC Med. 2018;16:199. 
15. Pickering AJ, Null C, Winch PJ, et al. The WASH benefits and SHINE trials: interpretation of WASH intervention effects on linear growth and diarrhoea. Lancet Global Health. 2019;7:e1139– 46. 
16. Islam MM, Khatun M, Peerson JM, et al. Effects of energy density and feeding frequency of complementary foods on total daily energy intakes and consumption of breast milk by healthy breastfed Bangladeshi children. Am J Clin Nutr. 2008;88:84–4. 
17. Ghosh S, Suri D, Uauy R. Assessment of protein adequacy in developing countries: quality matters. Br J Nutr. 2012;108(Suppl. 2):S77–87. 
18. Whitehead RG. Protein and energy requirements of young children living in the developing countries to allow for catch-up growth after infections. Am J Clin Nutr. 1977;30:1545–7. 
19. Palacios C, Gonzalez L. Is vitamin D deficiency a major global public health problem? J Steroid Biochem Mol Biol. 2014;144PA:138–45. 
20. Mogire RM, Morovat A, Muriuki JM, et al. Prevalence and predictors of vitamin D deficiency in young African children. BMC Med. 2021;19:115.
21.  World Health Organization. Iron deficiency anaemia: assessment, prevention, and control. A guide for programme managers. Geneva: WHO; 2001. 
22. Muriuki JM, Mentzer AJ, Mitchell R, et al. Malaria is a cause of iron deficiency in African children. Nat Med. 2021;27:653–8. 
23. Drakesmith H, Prentice AM. Hepcidin and the iron-infection axis. Science. 2012;338:768–72. 
24. Prentice AM, Bah A, Jallow MW, et al. Respiratory infections drive hepcidin-mediated blockade of iron absorption leading to iron deficiency anemia in African children. Sci Adv. 2019;5:eaav9020.
25. Rolls BJ. Dietary energy density: applying behavioural science to weight management. Nutr Bull. 2017;42:246–53. 
26. Rouhani MH, Haghighatdoost F, Surkan PJ, Azadbakht L. Associations between dietary energy density and obesity: a systematic review and meta-analysis of observational studies. Nutrition. 2016;32:1037–47. 
27. Stubbs RJ, Whybrow S. Energy density, diet composition and palatability: influences on overall food energy intake in humans. Physiol Behav. 2004;81:755–64.
28. Stubbs RJ, Harbron CG, Murgatroyd PR, Prentice AM. Covert manipulation of dietary fat and energy density: effect on substrate flux and food intake in men eating ad libitum. Am J Clin Nutr. 1995;62:316–29 
29. Stubbs RJ, Ritz P, Coward WA, Prentice AM. Covert manipulation of the ratio of dietary fat to carbohydrate and energy density: effect on food intake and energy balance in free-living men eating ad libitum. Am J Clin Nutr. 1995;62:330–7. 
30. Stubbs RJ, Harbron CG, Prentice AM. Covert manipulation of the dietary fat to carbohydrate ratio of isoenergetically dense diets: effect on food intake in feeding men ad libitum. Int J Obes Relat Metab Disord. 1996;20:651–60. 
31. Monteiro CA, Moubarac JC, Levy RB, Canella DS, Louzada MLDC, Cannon G. Household availability of ultra-processed foods and obesity in nineteen European countries. Public Health Nutr. 2018;21:18–26. 
32. Machado PP, Steele EM, Levy RB, et al. Ultraprocessed foods and recommended intake levels of nutrients linked to non-communicable diseases in Australia: evidence from a nationally representative cross-sectional study. BMJ Open. 2019;9:e029544. 
33. Moradi S, Entezari MH, Mohammadi H, et al. Ultra-processed food consumption and adult obesity risk: a systematic review and dose-response meta-analysis. Crit Rev Food Sci Nutr. 2021:1–12. 
34. Pagliai G, Dinu M, Madarena MP, Bonaccio M, Iacoviello L, Sofi F. Consumption of ultra-processed foods and health status: a systematic review and meta-analysis. Br J Nutr. 2021;125:308– 18. 
35. Farhangi MA, Tofigh AM, Jahangiri L, Nikniaz Z, Nikniaz L. Sugar-sweetened beverages intake and the risk of obesity in children: an updated systematic review and dose-response meta-analysis. Pediatr Obes. 2022;17:e12914. 
36. Duncanson K, Shrewsbury V, Burrows T, et al. Impact of weight management nutrition interventions on dietary outcomes in children and adolescents with overweight or obesity: a systematic review with meta-analysis. J Hum Nutr Diet. 2021;34:147–77. 
37. Scheelbeek PFD, Cornelsen L, Marteau TM, Jebb SA, Smith RD. Potential impact on prevalence of obesity in the UK of a 20% price increase in high sugar snacks: modelling study. BMJ. 2019;366:l4786. 
38. von Philipsborn P, Stratil JM, Burns J, et al. Environmental interventions to reduce the consumption of sugar-sweetened beverages and their effects on health. Cochrane Database Syst Rev. 2019;6:CD012292. 
39. Jakobsen DD, Brader L, Bruun JM. Effects of foods, beverages and macronutrients on BMI z-score and body composition in children and adolescents: a systematic review and meta-analysis of randomized controlled trials. Eur J Nutr. 2022. 
40. Mayer-Davis E, Leidy H, Mattes R, et al. Beverage consumption and growth, size, body composition, and risk of overweight and obesity: a systematic review. Alexandria (VA): USDA Nutrition Evidence Systematic Review; 2020 Jul.