Hostname: page-component-8448b6f56d-cfpbc Total loading time: 0 Render date: 2024-04-16T04:13:03.567Z Has data issue: false hasContentIssue false

The role of infant nutrition in the global epidemic of non-communicable disease

Published online by Cambridge University Press:  24 February 2016

Atul Singhal*
Affiliation:
The Childhood Nutrition Research Centre, Institute of Child Health, University College London, 30 Guilford Street, London WC1N 1EH, UK
*
Corresponding author: Professor A. Singhal, fax 020 7831 9903, email a.singhal@ucl.ac.uk
Rights & Permissions [Opens in a new window]

Abstract

Non-communicable diseases (NCD) and atherosclerotic CVD in particular, are the most important health problems of the 21st century. Already in every world region except Africa, NCD account for greater mortality than communicable, maternal, perinatal and nutritional conditions combined. Although modifiable lifestyle factors in adults are the main determinants, substantial evidence now suggests that factors in early life also have a major role in the development of NCD; commonly referred to as the Developmental Origins of Health and Disease hypothesis. Factors in utero, early postnatal life and throughout childhood, have been shown to affect NCD by influencing risk factors for CVD such as obesity, diabetes, hypertension and dyslipidaemia. Infant nutrition (e.g. breastfeeding rather than bottle feeding) and a slower pattern of infant weight gain have been shown to be particularly protective against later risk of obesity and CVD in both low- and high-income countries. The mechanisms involved are poorly understood, but include epigenetic changes; effects on endocrine systems regulating body weight, food intake and fat deposition; and changes in appetite regulation. As a consequence, strategies to optimise early life nutrition could make a major contribution to stemming the current global epidemic of NCD. This review will consider the role of early life factors in the development of NCD, focusing on the impact of infant nutrition/growth on obesity and CVD. The review will highlight the experimental (randomised) evidence where available, briefly summarise the underlying mechanisms involved and consider the implications for public health.

Type
Conference on ‘Nutrition at key life stages: new findings, new approaches’
Copyright
Copyright © The Author 2016 

Atherosclerotic CVD is the leading cause of death and disability, the major consumer of health care resources and the most important public health priority worldwide( Reference Mendis, Puska and Norrving 1 ). Yet, despite great progress in medical care, its prevalence is increasing sharply. Thus, primary prevention is a major priority for global health policy and research( Reference Mendis, Puska and Norrving 1 ).

While the ‘obesogenic’ environment with abundant availability of energy dense foods and sedentary lifestyle is clearly the major contributor to the risk of non-communicable diseases (NCD), strategies based on the prevention of lifestyle risk factors in adults have met with limited success. However, recent evidence from animal models and epidemiological data from human subjects has led to the hypothesis that nutrition in early life (pre-pregnancy, pregnancy and infancy) rather than in adults may also impact the long-term risk of obesity, CVD and type 2 diabetes( Reference Mendis, Puska and Norrving 1 Reference Stettler 7 ). Optimising nutrition during critical windows early in life could therefore provide a new opportunity for primary prevention and hence reduce life-time risk of NCD( Reference Mendis, Puska and Norrving 1 Reference Demerath, Reed and Choh 22 ).

The idea that nutrition during critical windows in early life may influence later health is part of a broader process, generally called programming, which reflects the impact of a stimulus or insult during a critical or sensitive window, in producing long-term changes in the structure or function of the organism (as reviewed( Reference Singhal and Lucas 3 )). Whilst the concept of critical periods was conceived in the 19th century, evidence that early nutrition had long-term biological effects first emerged in the 1930s when McCay showed that energy restriction in early life reduced chronic disease and increased lifespan( Reference Singhal and Lucas 3 ). Then McCance in the 1960s showed in animals that early postnatal nutrition, during a brief critical window, had life-time effects( Reference Singhal and Lucas 3 ). Of relevance to CVD, in the 1970s Hahn found rats overfed during suckling developed higher plasma insulin and cholesterol in adulthood; later, Lewis found overfeeding in infant baboons programmed obesity, an effect that emerged only in adolescence, showing that programmed effects may be ‘remembered’ but not expressed as a phenotypic consequence until later( Reference Singhal and Lucas 3 ). Now, extensive evidence in animal models shows that nutrition in early postnatal life programmes the major risk factors for CVD (insulin resistance, obesity, dyslipidaemia and blood pressure( Reference Singhal and Lucas 3 Reference Singhal, Embleton, Katz and Ziegler 5 )), atherosclerosis( Reference Singhal, Cole and Fewtrell 6 ) and even longevity( Reference Jennings, Ozanne and Dorling 23 Reference Rollo 26 ).

In human subjects, one of the first studies to show programming effects was by Eid( Reference Eid 27 ) who found that faster weight gain in the first 6 weeks of life increased the risk of obesity 6–8 years later. Subsequently, in the 1980s and 1990s strong and consistent associations of low birth weight with CVD and type 2 diabetes in adulthood( Reference Barker 2 ), led to a change in focus from nutritional programming in infancy to the effects of nutrition in fetal life (commonly known as the Fetal Origins of Adult Disease or Barker hypothesis( Reference Barker 2 )). However, the key limitation of such observational studies has been the lack of experimental evidence for a causal role of early nutrition in programming human health. Thus, early nutritional practices have not been backed by rigorous experimental evidence of efficacy and safety, which is expected in other areas of public health; and have the potential to cause harm. For example, ‘intuitive’ attempts to promote growth in small, growth-retarded newborns could significantly increase later CVD and obesity( Reference Singhal and Lucas 3 Reference Singhal, Embleton, Katz and Ziegler 5 , Reference Baird, Fisher and Lucas 8 Reference Singhal, Kennedy and Lanigan 14 ). This lack of a sound evidence-base has prevented changes to nutritional and public health practice in infancy in order to prevent later NCD.

More recent research has emphasised the importance of experimental (randomised) evidence in the field of nutritional programming. Follow-up of randomised trials in preterm infants initiated in the 1980s provided the first experimental evidence that early nutrition had programming effects on the major risk factors for CVD (as reviewed( Reference Singhal and Lucas 3 )). For instance, in randomised trials comparing breast milk feeding to formula feeding (possible in preterm infants), breast milk was shown to have major beneficial effects on obesity, dyslipidaemia, high blood pressure, and insulin resistance and blood pressure in adolescence( Reference Singhal and Lucas 3 ). These trials, together with extensive epidemiological studies and evidence of dose–response effects of breastfeeding, supported a causal link between infant nutrition and later cardiovascular health, with important implications for inequalities in health and public health policy in nutrition. Effect sizes in these studies, although small for individuals, were substantial on a population basis. For example, breastfeeding and diets promoting slower infant weight gain reduced later diastolic blood pressure by about 3 mm Hg( Reference Singhal and Lucas 3 , Reference Singhal, Cole and Fewtrell 13 ), expected, on a population basis, to prevent over 100 000 cardiovascular events annually in the USA alone (as reviewed( Reference Singhal and Lucas 3 )). The 10 % lowering of LDL-cholesterol with breastfeeding( Reference Singhal and Lucas 3 ) is expected to reduce CVD incidence by 25 % and mortality by 13–14 %( Reference Singhal and Lucas 3 ). Nutritional interventions in early life therefore have the potential to have a major impact on disease prevalence, quality and quantity of life as well as health care costs.

Growth in the first few months: a critical window for programming of obesity and CVD

Plausible explanations for the effects of breastfeeding on later obesity and CVD risk have included residual confounding by socio-economic, demographic and behavioural differences between infants breast- or formula-fed. However, based on the previous epidemiological evidence of an association between infant weight gain and later risk of obesity, randomised trials in infants born preterm( Reference Singhal and Lucas 3 ), and subsequently in infants born at term but small for gestational age (SGA)( Reference Singhal, Cole and Fewtrell 13 , Reference Singhal, Kennedy and Lanigan 14 ), we suggested that the benefits of breastfeeding for later risk factors for CVD may be due to slower growth and relative undernutrition in breast-fed compared with formula-fed infants: the Growth Acceleration hypothesis( Reference Singhal and Lucas 3 ). This hypothesis proposed that faster postnatal growth (upward centile crossing for weight or length) programmed the major components of the metabolic syndrome, including higher blood pressure, obesity and endothelial dysfunction. Furthermore, postnatal growth acceleration could also explain, in part, adverse programming effects seen in infants born SGA who show catch-up growth immediately after birth( Reference Singhal and Lucas 3 ).

Since this early research, more than fifty studies now support the growth acceleration concept. For instance, faster weight gain in infancy (upward centile crossing for weight) is associated with a greater risk of later obesity in more than thirty studies (summarised in five systematic reviews,( Reference Baird, Fisher and Lucas 8 Reference Weng, Redsell and Swift 12 ) including an individual-level meta-analysis in 47 661 participants from ten cohorts( Reference Druet, Stettler and Sharp 11 )). This association is seen for the main components of the metabolic syndrome, in breast-fed and formula-fed populations, in high- and low-income countries representing many different ethnic groups( Reference Stettler 7 Reference Weng, Redsell and Swift 12 ), and is consistent for cohorts during the past 80 years( Reference Baird, Fisher and Lucas 8 ). The association is biologically plausible and experimentally reproducible in several animal models( Reference Stettler 7 ). For example, in mice faster growth during lactation, after growth restriction in the fetal period, alters the expression of several genes encoding enzymes involved in lipid/carbohydrate metabolism( Reference Bol, Delattre and Reusens 28 ). In fact, the idea that faster growth in early life adversely affects long-term survival (concept of grow now, pay later) appears to be a widespread, evolutionary conserved phenomenon seen across diverse animal species( Reference Metcalfe and Monaghan 29 ).

The association of faster early growth with adverse effects on long-term health is not confined to infants with low birth weight( Reference Singhal, Embleton, Katz and Ziegler 5 , Reference Ong and Loos 10 ), is evident in both infants born preterm and at term( Reference Singhal and Lucas 3 Reference Singhal, Embleton, Katz and Ziegler 5 ), and can be detected even as early as the first few years of life( Reference Durmus, Mook-Kanamori and Holzhauer 20 , Reference Soto, Bazaes and Peña 30 ). For instance, faster weight gain in infancy was associated with abdominal adiposity at age 2 years( Reference Durmus, Mook-Kanamori and Holzhauer 20 ), and SGA infants who showed catch-up growth (weight gain >0·67 sd score) had higher fasting insulin concentration at age 1 year than those without catch-up growth( Reference Soto, Bazaes and Peña 30 ). The effect of faster infant growth appears to be the greatest for central or visceral adiposity( Reference Durmus, Mook-Kanamori and Holzhauer 20 Reference Demerath, Reed and Choh 22 ), a key risk factor for CVD and type 2 diabetes, and, at least in the data from observational studies, is seen in adults as well as children. Leunissen et al. showed that faster weight gain in the first 3 months of life was associated with lower insulin sensitivity and HDL-cholesterol concentrations, and greater waist circumference, TAG concentrations, percentage body fat and central adiposity at age 18–24 years( Reference Leunissen, Kerkhof and Stijnen 16 ). These studies suggest a large effect size. For example, over 20 % of later obesity risk can be explained by the rate of infant weight gain (as reviewed( Reference Singhal, Embleton, Katz and Ziegler 5 )) and the relative risk of later obesity associated with more rapid weight gain in infancy ranges from 1·2 to as high as 5·7( Reference Baird, Fisher and Lucas 8 ).

However, despite extensive epidemiological data linking faster infant weight gain with later cardiovascular risk factors, data for an effect of growth patterns in infancy on long-term clinical outcomes are contradictory. In a cohort from New Delhi, rapid gain in BMI in the first year was associated with development of the metabolic syndrome in adulthood but (in contrast to this finding) low gain in BMI was associated with glucose intolerance( Reference Fall, Sachdev and Osmond 15 ). In fact, previously, faster growth over the first 2 years has been suggested to offset the adverse programming effects of fetal growth restriction and low birth weight( Reference Barker, Osmond and Forsén 31 ). For example, in the Helsinki and New Delhi Birth cohorts, individuals with low birth weight who had lower weight gain in the first 2 years, and upward crossing of weight centiles in childhood were noted to be at highest risk of CVD and type 2 diabetes( Reference Barker, Osmond and Forsén 31 , Reference Bhargava, Sachdev and Fall 32 ). These data have supported the practice of actively promoting rapid weight gain in infancy to benefit long-term health especially in countries in transition such as India where undernutrition in childhood is common and of more immediate concern.

The discrepancy in the effects of early weight gain for later obesity and CVD risk can be partly explained if different periods within the first year of life have different programming effects. Gillman noted that in the Helsinki cohort, the BMI of those who eventually developed CVD had actually increased in the first 3 months before decreasing( Reference Gillman 33 ). Similarly, in the New Delhi cohort, gain in BMI in the first 6 months was associated with greater BMI in adulthood( Reference Gillman 33 ). Recent studies have confirmed the role of weight gain in the first 3 months on programming of obesity and CVD. Chomtho et al., in a study focused on the effect of weight gain in different periods in infancy on body composition in childhood (age 11·4 (sd 3·8) years), showed that faster weight gain between 0–3 and 3–6 months (but not between 6 and 12 months) was associated with greater total and truncal fat mass in childhood( Reference Chomtho, Wells and Williams 17 ). Faster weight gain during a critical window in the first few months of life may therefore have adverse consequences for the risk of later NCD in diverse populations.

Experimental (randomised) evidence for growth acceleration

The concept that faster infant growth can causally impact on later risk factors for CVD is now strongly supported by randomised studies in infants born prematurely( Reference Singhal and Lucas 3 ), SGA at term( Reference Singhal, Cole and Fewtrell 13 , Reference Singhal, Kennedy and Lanigan 14 ), and in healthy term infants( Reference Weber, Grote and Closa-Monasterolo 18 , Reference Inostroza, Haschke and Steenhout 19 ). For example, infants born preterm randomly assigned to a nutrient-enriched diet that promoted faster weight gain in the first few weeks after birth, had higher fasting concentrations of insulin, cholesterol and C-reactive protein, as well as leptin resistance in adolescence than controls( Reference Singhal and Lucas 3 ). Similarly, infants born SGA at term and randomly assigned to nutrient-enriched formula that increased weight gain had higher diastolic blood pressure at age 6–8 years( Reference Singhal, Cole and Fewtrell 13 ) and, in two trials, 18–38 % greater fat mass at age 5–8 years than controls( Reference Singhal, Kennedy and Lanigan 14 ). Notably, differences in fat mass or blood pressure in childhood were related to the rate of weight gain in infancy suggesting a dose–response association between early growth and later CVD risk( Reference Singhal, Cole and Fewtrell 13 , Reference Singhal, Kennedy and Lanigan 14 ). More recently, programming effects of infant nutrition/growth have been confirmed in experimental studies of term infants with appropriate birth weight for gestation. These effects have been seen in both high- and low-income countries (e.g. ChileReference Inostroza, Haschke and Steenhout 19 ), thereby supporting the concept that programming of CVD risk by faster early growth is a fundamental biological finding seen across populations( Reference Weber, Grote and Closa-Monasterolo 18 , Reference Inostroza, Haschke and Steenhout 19 ).

Central to the growth acceleration hypothesis is that fact that breast-fed infants grow more slowly than those fed formula, particularly in the first few weeks after birth and again between ages 3 and 12 months. This effect is probably because of the lower protein content of breast-milk (approximately 10 g/l compared with up to 15 g/l in some formulas), which means that formula-fed infants receive on average 0·5 g/kg per d greater protein than breast-fed infants( Reference Michaelsen and Greer 34 ). These differences in the rate of weight gain and protein intake between the bottle- and breast-fed infants has provided an opportunity to investigate the growth acceleration concept using randomised trials in healthy term infants.

In the largest study, the European Childhood Obesity Trial, formula-fed babies were randomly assigned to formulas with different protein concentrations and followed to age 6 years( Reference Weber, Grote and Closa-Monasterolo 18 ). The assigned diets were given as a standard infant formula (after the parents had decided to add formula) to age 6 months (1·25 g/100 ml in the lower protein formula v. 2·05 g/100 ml in the higher protein formula) followed by a follow-on formula to age 12 months (1·6 g/100 ml in the lower protein formula v. 3·2 g/100 ml in the higher protein formula). Consistent with an effect of protein intake on infant growth and the later risk of obesity, babies given the higher protein formula had a faster rate of weight gain in the first year, higher BMI at age 2 years, and 2·4× greater risk of obesity at age 6 years than those in the lower protein group( Reference Weber, Grote and Closa-Monasterolo 18 ). However, although strongly supporting the growth acceleration concept, the protein content of formulas used in this trial was much higher than those commonly used today, thereby limiting the practical relevance of this study.

Nonetheless, the possibility that a lower protein intake in the first year can reduce the later risk of obesity is strongly supported by a randomised trial from Chile in which infants of mothers with a BMI >25 kg/m2, were randomised to one of two infant formulas between ages 3 and 12 months. Infants were assigned either a standard-nutrient (protein, 1·77 g/100 ml; energy, 274·47 kJ (65·6 kcal) /100 ml); or a new low-nutrient formula with much lower protein concentration than conventional formula (protein, 1·04 g/100 ml; energy, 262·76 kJ (62·8 kcal) /100 ml)( Reference Inostroza, Haschke and Steenhout 19 ). Compared with controls, infants given the lower protein formula had 1·8 g/d slower weight gain between ages 3 and 6 months (primary outcome) and lower BMI at age 2 years( Reference Inostroza, Haschke and Steenhout 19 ). However, whether these effects on adiposity persist into later life and are observed in infants whose mothers are not overweight are unknown and remain key research questions.

Overall, although five randomised studies now support a causal link between faster infant weight gain and later risk factors for CVD, several research questions remain. Four out of five previous studies are in children aged 2–8 years( Reference Singhal, Cole and Fewtrell 13 , Reference Singhal, Kennedy and Lanigan 14 , Reference Weber, Grote and Closa-Monasterolo 18 , Reference Inostroza, Haschke and Steenhout 19 ), (the fifth study was in adolescents( Reference Singhal and Lucas 3 )) and therefore the impact of growth acceleration in infancy on adult CVD risk is unknown. Furthermore, these studies have not been able to demonstrate a causal link between early growth and later visceral adiposity, a suggested intermediate risk factor by which faster infant growth increases CVD risk( Reference Durmus, Mook-Kanamori and Holzhauer 20 Reference Demerath, Reed and Choh 22 ). Finally, it is unknown whether there is a particularly sensitive or critical window in infancy for these programming effects and whether programming effects of infant nutrition/growth persist into adult life and amplify with age (as in animal models), or are ‘overwhelmed’ by conventional CVD lifestyle risk factors in adulthood.

Mechanisms

A major limitation of the Development Origins of Health and Disease field is a relatively poor understanding of the underlying biological mechanisms involved. Nonetheless, there has been some progress in our knowledge of the coupling mechanisms that link early nutrition/growth with later CVD. These can be grouped into four main inter-related categories.

Endocrine mechanisms

Nutritional programming has been suggested to permanently affect endocrine systems that regulate body weight, food intake and metabolism, and fat deposition in both man and animal models( Reference Bouret, Lucas, Makrides and Ziegler 35 ). Studies in animals suggest that the set points or ranges for endocrine feedback mechanisms may be influenced by the concentrations of the hormones themselves early in life( Reference Plagemann 36 ). Similar mechanisms may occur in man. For instance, higher nutrition postnatally may programme high leptin, and particularly, high insulin concentrations, which by predisposing to higher concentrations later in life, increase the threshold to satiety signals and hence the propensity to obesity. Consistent with this, preterm infants randomised to a protein-enriched neonatal diet had hyperinsulinism and leptin resistance in adolescence( Reference Singhal and Lucas 3 ).

Similarly, hypercortisolism in infancy could predispose to hypercorticolism throughout life( Reference Plagemann 36 ). There is evidence to suggest that higher insulin-like growth factor 1 concentrations facilitate catch-up growth in SGA infants in early life, but this permanently increases the activity of the hypothalamic–pituitary–adrenal axis so that infants born SGA have higher insulin-like growth factor 1 concentrations later in life( Reference Iniguez, Ong and Bazaes 37 ). Infant nutrition may also programme the hypothalamic–pituitary–adrenal axis. For example, insulin-like growth factor 1 concentrations are lower in breast-fed compared with formula-fed infants (who have more rapid weight gain) and, in a large randomised controlled trial, lower in infants given a standard v. a high protein infant formula( Reference Socha, Grote and Gruszfeld 38 ). However, whether these effects on insulin-like growth factor 1 persist into adult life, and their impact on development of appetite regulation, obesity (particularly visceral adiposity) and CVD are presently unknown.

Appetite regulation

Observational evidence suggests that early nutrition/growth affects appetite regulation which could affect energy intake and metabolism( Reference Ross and Desai 39 ). For example, formula rather than breast-feeding, rapid weight gain in infancy and the technique of feeding (e.g. breast v. bottle feeding) are all associated with a higher set point for appetite and recognition of satiety in early childhood which, when exposed to a nutrient dense diet, is likely to predispose to obesity( Reference Li, Fein and Grummer-Strawn 40 , Reference DiSantis, Collins and Fisher 41 ). However, the lack of experimental data means that a causal association between infant growth/nutrition and long-term appetite regulation in man has not been established and whether these programming effects persist longer-term, into adult life, where they may have a greater impact on the risk of CVD is unknown.

Epigenetic programming

One of the most researched mechanisms for nutritional programming has been into epigenetic regulation of gene expression, particularly in the role of programmed changes in DNA methylation. There is extensive evidence from animal models and emerging evidence from human subjects that changes in early nutrition and growth are associated with changes in DNA methylation in the offspring( Reference Godfrey, Lillycrop, Burdge, Gillman, Gluckman and Rosenfeld 42 ). Much less attention has been directed towards the role of post-transcriptional programming of gene expression although programmed changes in microRNA expression have been shown to substantially impact on adipocyte lipid storage capacity and therefore whole body insulin sensitivity( Reference Ferland-McCollough, Fernandez–Twinn and Cannell 43 ).

Accelerated biologic ageing

Many of the conditions associated with faster infant growth, such as type 2 diabetes and CVD are considered diseases of ageing, suggesting that the nutritional programming may be mediated by effects on ageing processes. This hypothesis is strongly supported by data from animals models showing that faster growth in early life is associated with reduced life span( Reference Jennings, Ozanne and Dorling 23 Reference Rollo 26 ), shorter telomere length (a marker of cellular ageing)( Reference Jennings, Ozanne and Dorling 23 , Reference Tarry-Adkins, Chen and Smith 44 ) and increased expression of mediators of cellular senescence such as p16 concentrations( Reference Tarry-Adkins, Chen and Smith 44 ). However, whether rapid infant growth affects accelerated cellular ageing leading to increased whole body ageing in man is unknown. This issue is of critical importance since effects of early life factors on biological ageing may be a common underlying pathway for the impact of infant growth/nutrition on diverse outcomes such as obesity, CVD and diabetes and other NCD, and could explain associations between shorter telomere length and ageing-related CVD in man( Reference Haycock, Heydon and Kaptoge 45 ).

Nutrition programming and low-income countries

Low-income countries face a massive increase in NCD. For example, in India alone, by 2030 there will be an estimated eighty million people with type 2 diabetes and Asian Indians will account for approximately 40 % of the global burden of CVD( Reference Wild, Roglic and Green 46 ). There is therefore an urgent need for primary prevention programmes, but whether the growth acceleration concept is relevant to low-income countries is uncertain( Reference Jain and Singhal 47 ). This question is particularly relevant for countries such as India which have the highest global burden of term infants born SGA, who are at higher risk of CVD( Reference Barker 2 ), but in whom the optimal pattern of weight gain for long-term health is not known( Reference Jain and Singhal 47 ).

Clearly, growth patterns in infancy are likely to have a different impact on health according to the environment in which the population lives. For instance, infants with slower weight gain may be at higher risk of infections and undernutrition and hence the overall risk–benefit may favour faster infant growth in many populations from low-income countries. However, low-income countries have very heterogeneous populations with a growing middle class at risk of long-term obesity and CVD. As in the West, faster weight gain in infancy is associated with the later risk of obesity in several middle- and low-income countries such as India, Seychelles, Brazil and South Africa( Reference Monteiro and Victora 9 ). In many of these countries promotion of rapid weight gain in infancy is normal cultural practice and, in order to achieve this, inappropriate addition of animal milks (including cow's milk, buffalo milk and donkey's milk) is common. Further research is therefore needed to define the risk–benefits of growth acceleration and guide infant nutrition policy in these countries( Reference Jain and Singhal 47 ).

Public health implications

The impact of infant nutrition/growth on future risk of NCD has considerable implications for public health and nutrition practice. For instance, there is substantial agreement, from systematic reviews and meta-analyses conducted by scientific advisory authorities (Dutch State Institute for Nutrition and Health 2005; WHO 2007; US Agency for Healthcare Research and Quality 2007; and the UK Scientific Advisory Committee on Nutrition 2011; as summarised( Reference Fewtrell 48 )) supporting a protective effect of breastfeeding against the risk of later obesity. Breastfeeding should therefore be promoted for its long-term as well as short-term health benefits. The strength of the evidence supporting the growth acceleration hypothesis has also led to changes in the nutritional practice. Professional bodies such as the Institute of Medicine in the USA, and the Royal College of Paediatrics and Child Health and the Scientific Advisory Committee on Nutrition in the UK have recognised the role of faster infant weight gain in increasing the risk of long-term obesity. Consequently, health care professionals are advised to prevent inappropriate upward centile crossing as well as growth faltering in infancy. The new WHO growth charts based on the exclusively breast-fed infant are likely to help in the prevention of overfeeding in infancy. Furthermore, contrary to the previous medical and public opinion, promoting catch-up growth by nutritional supplementation in healthy term infants born SGA may not be appropriate( Reference Clayton, Cianfarani and Czernichow 49 ).

Finally, the benefits of a slower rate of infant weight gain as seen in breast-fed compared with formula-fed infants has led to changes in infant formula to try to reduce the risk of overfeeding in formula-fed infants. These include reduction in the protein content of infant formulas and changes in recommendations for the composition of formula. For example, the European Food Safety Authority recently recommended a reduction in the maximum permitted protein content in infant formula and suggested recently that ‘infant formula and infant follow-on formula should ensure that the growth and development of infants fed infant formula are similar to those of infants who are exclusively breast-fed during the first 6 months of life’( 50 ).

Conclusions

In November 2012, the WHO identified NCD as the most important global health issue of the 21st century and agreed a target of reducing premature mortality from NCD by 25 % by 2025. Strong evidence now suggests that optimising growth and nutrition in infancy will help achieve these targets.

Financial Support

Professor Singhal is funded by the Great Ormond Street Hospital Children's Charity.

Conflicts of Interest

None.

Authorship

The author was solely responsible for all aspects of preparation of this paper.

References

1. WHO (2011) Global Atlas on Cardiovascular Disease Prevention and Control Chap 2, pp. 8–9 [Mendis, S, Puska, P and Norrving, B, editors]. Geneva: World Health Organization.Google Scholar
2. Barker, DJP (2004) The developmental origins of adult disease. J Am Coll Nutr 23, 588S595S.Google Scholar
3. Singhal, A & Lucas, A (2004) Early origins of cardiovascular disease: is there a unifying hypothesis?. Lancet 363, 16421645.CrossRefGoogle Scholar
4. Singhal, A (2010) Does early growth affect long-term risk factors for cardiovascular disease? In Importance of Growth for Health and Development. Nestle Nutrition Institute Workshop Ser Pediatr Program, vol. 65, pp. 5569 [Lucas, A, Makrides, M and Ziegler, EE, editors]. Basel: Nestec Ltd., Vevey/S: Karger AG Press.Google Scholar
5. Singhal, A (2015) Should we promote catch-up growth or growth acceleration in low-birthweight infants? In Low-birthweight Baby: Born too Soon or Too Small. Nestle Nutrition Institute Workshop Ser Pediatr Program, vol. 81, pp. 5160 [Embleton, ND, Katz, J and Ziegler, EE, editors]. Basel: Nestec Ltd., Vevey/S: Karger AG Press.Google Scholar
6. Singhal, A, Cole, TJ, Fewtrell, M et al. (2004) Is slower early growth beneficial for long-term cardiovascular health? Circulation 109, 11081113.Google Scholar
7. Stettler, N (2007) Nature and strength of epidemiological evidence for origins of childhood and adult obesity in the first year of life. Int J Obes 31, 10351043.Google Scholar
8. Baird, J, Fisher, D, Lucas, P et al. (2005) Being big or growing fast: systematic review of size and growth in infancy and later obesity. BMJ 331, 929931.Google Scholar
9. Monteiro, POA & Victora, CG (2005) Rapid growth in infancy and childhood and obesity in later life – a systematic review. Obes Rev 6, 143154.CrossRefGoogle ScholarPubMed
10. Ong, KK & Loos, RJ (2006) Rapid infancy weight gain and subsequent obesity: systematic reviews and hopeful suggestions. Acta Paediatr 95, 904908.Google Scholar
11. Druet, C, Stettler, N, Sharp, S et al. (2012) Prediction of childhood obesity by infancy weight gain: an individual-level meta-analysis. Paediatr Perinat Epidemiol 26, 1926.CrossRefGoogle ScholarPubMed
12. Weng, SF, Redsell, SA, Swift, JA et al. (2012) Systematic review and meta-analyses of risk factors for childhood overweight identifiable during infancy. Arch Dis Child 97, 10191026.Google Scholar
13. Singhal, A, Cole, TJ, Fewtrell, M et al. (2007) Promotion of faster weight gain in infants born small for gestational age: is there an adverse effect on later blood pressure? Circulation 115, 213220.CrossRefGoogle ScholarPubMed
14. Singhal, A, Kennedy, K, Lanigan, J et al. (2010) Nutrition in infancy and long-term risk of obesity: evidence from two randomised controlled trials. Am J Clin Nutr 92, 11331144.Google Scholar
15. Fall, CH, Sachdev, HS, Osmond, C et al. (2008) Adult metabolic syndrome and impaired glucose tolerance are associated with different patterns of BMI gain during infancy: data from the New Delhi Birth Cohort. Diab Care 31, 23492356.Google Scholar
16. Leunissen, RW, Kerkhof, GF, Stijnen, T et al. (2009) Timing and tempo of first-year rapid growth in relation to cardiovascular and metabolic risk profile in early adulthood. JAMA 301, 22342242.Google Scholar
17. Chomtho, S, Wells, JC, Williams, JE et al. (2008) Infant growth and later body composition: evidence from the 4-component model. Am J Clin Nutr 87, 17761784.Google Scholar
18. Weber, M, Grote, V, Closa-Monasterolo, R et al. (2014) Lower protein content in infant formula reduces BMI and obesity risk at school age: follow-up of a randomized trial. Am J Clin Nutr 99, 10411051.Google Scholar
19. Inostroza, J, Haschke, F, Steenhout, P et al. (2014) Low-protein formula slows weight gain in infants of overweight mothers. J Pediatr Gastroenterol Nutr 59, 7077.Google Scholar
20. Durmus, B, Mook-Kanamori, DO, Holzhauer, S et al. (2010) Growth in foetal life and infancy is associated with abdominal adiposity at the age of 2 years: the generation R study. Clin Endocrinol 72, 633640.Google Scholar
21. Ibanez, L, Suarez, L, Lopez-Bermejo, A et al. (2008) Early development of visceral fat excess after spontaneous catch-up growth in children with low birth weight. J Clin Endocrinol Metab 93, 925928.Google Scholar
22. Demerath, EW, Reed, D, Choh, AC et al. (2009) Rapid postnatal weight gain and visceral adiposity in adulthood: the Fels longitudinal study. Obesity (Silver Spring) 17, 20602066.Google Scholar
23. Jennings, BJ, Ozanne, SE, Dorling, MW et al. (1999) Early growth determines longevity in male rats and may be related to telomere shortening in the kidney. FEBS Lett 448, 48.CrossRefGoogle ScholarPubMed
24. Ozanne, SE & Hales, N (2004) Lifespan: catch-up growth and obesity in male mice. Nature 427, 411412.Google Scholar
25. Longo, VD & Finch, CE (2003) Evolutionary medicine: from dwarf model systems to healthy centenarians? Science 299, 13421346.Google Scholar
26. Rollo, CD (2002) Growth negatively impacts the life span of mammals. Evol Dev 4, 5561.Google Scholar
27. Eid, EE (1970) Follow-up study of physical growth of children who had excessive weight gain in first six months of life. BMJ 2, 7476.Google Scholar
28. Bol, VV, Delattre, AI, Reusens, B et al. (2009) Forced catch-up growth after fetal protein restriction alters the adipose tissue gene expression program leading to obesity in adult mice. Am J Physiol Regul Integr Comp Physiol 297, R291R299.Google Scholar
29. Metcalfe, NB & Monaghan, P et al. (2001) Compensation for a bad start: grow now, pay later? Trends Ecol Evol 16, 254260.Google Scholar
30. Soto, N, Bazaes, RA, Peña, V et al. (2003) Insulin sensitivity and secretion are related to catch-up growth in small for gestational age infants at age 1 year: results from a prospective cohort. J Clin Endocrinol Metab 88, 36453650.Google Scholar
31. Barker, JPD, Osmond, C, Forsén, TJ et al. (2005) Trajectories of growth among children who have coronary events as adults. N Engl J Med 353, 18021809.Google Scholar
32. Bhargava, S, Sachdev, HS, Fall, CHD et al. (2004) Relation of serial changes in childhood body-mass index to impaired glucose intolerance in young adulthood. N Engl J Med 350, 865875.Google Scholar
33. Gillman, MW (2008) The first months of life: a critical period for development of obesity. Am J Clin Nutr 87, 15871589.Google Scholar
34. Michaelsen, KF & Greer, FR (2014) Protein needs early in life and long-term health. Am J Clin Nutr 99, Suppl., 718S722S.CrossRefGoogle ScholarPubMed
35. Bouret, SG (2010) Leptin, nutrition and the programming of hypothalamic feeding circuits. In Importance of Growth for Health and Development. Nestle Nutrition Institute Workshop Ser Pediatr Program, vol. 65, pp. 2539 [Lucas, A, Makrides, M and Ziegler, EE, editors]. Basel: Nestec Ltd., Vevey/S: Karger AG Press.Google Scholar
36. Plagemann, A (2005) Perinatal programming and functional teratogenesis: impact on body weight regulation and obesity. Physiol Behav 86, 661668.CrossRefGoogle ScholarPubMed
37. Iniguez, G, Ong, K, Bazaes, R et al. (2006) Longitudinal changes in IGF-1, insulin sensitivity and secretion from birth to age three years in small for gestational-age children. J Clin Endocrinol Metab 91, 46454649.Google Scholar
38. Socha, P, Grote, V, Gruszfeld, D et al. (2011) Milk protein intake, the metabolic-endocrine response, and growth in infancy: data from a randomized clinical trial. Am J Clin Nutr 94, Suppl., 1776S1784S.Google Scholar
39. Ross, MG & Desai, M (2014) Developmental programming of appetite/satiety. Ann Nutr Metab 64, 3644.Google Scholar
40. Li, R, Fein, SB & Grummer-Strawn, LM (2010) Do infants fed from bottles lack self-regulation of milk intake compared with directly breastfed infants? Pediatrics 125, e1386e1393.Google Scholar
41. DiSantis, KI, Collins, BN, Fisher, JO et al. (2011) Do infants fed directly from the breast have improved appetite regulation and slower growth compared with infants fed from a bottle. Int J Behav Nutr Phys Act 8, 89100.Google Scholar
42. Godfrey, KM, Lillycrop, KA, Burdge, GC et al. (2013) Non-imprinted epigenetics in fetal and postnatal development and growth. In Recent Advances in Growth Research: Nutritional, Molecular and Endocrine Perspectives. Nestle Nutrition Institute Workshop Ser Pediatr Program, vol. 71, pp. 5763 [Gillman, M, Gluckman, PD and Rosenfeld, RG, editors]. Basel: Nestec Ltd., Vevey/S: Karger AG Press.Google Scholar
43. Ferland-McCollough, D, Fernandez–Twinn, DS, Cannell, IG et al. (2012) Programming of adipose tissue miR-483-3p and GDF-3 expression by maternal diet in type 2 diabetes. Cell Death Diff 19, 10031012.Google Scholar
44. Tarry-Adkins, JL, Chen, JH, Smith, NS et al. (2009) Poor maternal nutrition followed by accelerated postnatal growth leads to telomere shortening and increased markers of cell senescence in rat islets. FASEB J 23, 15211528.Google Scholar
45. Haycock, PC, Heydon, EE, Kaptoge, S et al. (2014) Leucocyte telomere length and risk of cardiovascular disease: systematic review and meta-analysis. BMJ 349, g4227.Google Scholar
46. Wild, S, Roglic, G, Green, A, et al. (2004) Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diab Care 27, 10471053.CrossRefGoogle ScholarPubMed
47. Jain, V & Singhal, A (2012) Catch up growth in low birth weight infants: striking a healthy balance. Rev Endocr Metab Disord 13, 141147.Google Scholar
48. Fewtrell, MS (2011) The evidence for public health recommendations on infant feeding. Early Hum Dev 87, 715721.CrossRefGoogle ScholarPubMed
49. Clayton, PE, Cianfarani, S, Czernichow, P et al. (2007) Management of the child born small for gestational age through to adulthood: a consensus statement of the International Societies of Pediatric Endocrinology and the Growth Hormone Research Society. J Clin Endocrinol Metab 92, 804810.Google Scholar
50. EFSA Panel on Dietetic Products, Nutrition and Allergies (2014) Scientific opinion on the essential composition of infant and follow-on formulae. EFSA J 12, 3760, 14.Google Scholar