Ann Nutr Metab 2011;58(suppl 2):30–41

Programming towards Childhood Obesity

Tounian P.
Department of Pediatric Nutrition, Armand Trousseau Hospital, Paris, France
email Corresponding Author


 goto top of outline Key Words

  • Childhood obesity
  • Genetic predisposition
  • Obesity programming

 goto top of outline Abstract

There is now considerable evidence that a constitutional susceptibility to fat gain is necessary for children to become obese under the pressure of an obesogenic environment; this is the programming towards obesity. The role of genetics in this programming is dominant. Besides the rare monogenic recessive forms of obesity secondary to mutations in genes involved in the hypothalamic appetite control pathways, obesity linked to mutations in melanocortin 3 and 4 receptors are more frequent due to their dominant mode of transmission. Predisposition to common obesity is polygenic and involves a network of genes; nevertheless, more research is required to elucidate their exact role. Fetal and perhaps early postnatal programming is also possible. Under- and overnutrition, diabetes, and maternal smoking during pregnancy were shown to promote later obesity and may affect the central body weight regulatory system during fetal development. The role of early postnatal factors such as formula-feeding rather than breastfeeding, excess in n–6 polyunsaturated fatty acids or protein intakes, and excessive weight gain early in life is more questionable and needs further investigation. Taking into consideration that childhood obesity is a programmed disease should modify its clinical management. Childhood obesity should no longer be considered as the result of inappropriate eating habits and/or excessive inactivity in order to relieve the obese children’s discrimination and their parents’ guilt. Since treatment of obese children requires a substantial motivation to continuously fight against the programmed excessive drive to eat, it seems wiser to wait for children to be old enough, thus more motivated, to initiate energy restriction. Moreover, with the great majority of children being not predisposed to obesity, prevention strategies should not be addressed to the whole pediatric population but targeted to those children at risk. Improvement of knowledge on programming towards obesity is essential to develop more promising therapeutic and preventive approaches.

Copyright © 2011 S. Karger AG, Basel

goto top of outline Key Messages

• In an obesogenic environment, research suggests that a network of genes and gene-gene interactions are mainly responsible for childhood obesity and its predisposition, acting by altering either the central body weight regulatory system or hypothalamic appetite control. The exact roles of these genes and/or ‘gene dosage’ effects need to be understood.

• Future investigations should focus on the respective contributions between genetic programming and lifestyle factors in developing childhood obesity. Clinical management should target only those children at risk and their families instead of the current, less promising strategies at population level.


goto top of outline Introduction

During the last decades, the increased availability of palatable food and the conditions of decreased physical activity (motorization/sedentary games) dramatically increased the prevalence of childhood obesity in industrialized countries. More recently, occurrence of this obesogenic environment in developing nations led to a rapid increase in the prevalence of childhood obesity in urban regions, whereas a lot of children still suffer from undernutrition in rural regions of the same countries [1].

This indicates that excessive weight gain only occurs in children who are living in a high-risk environment favoring obesity, with only a minority of children being concerned. Indeed, there is now considerable evidence that a constitutional susceptibility to fat gain is necessary to become obese under the pressure of an obesogenic environment [2,3,4]. In other words, only children programmed to develop obesity are at risk; abundant food availability or inactivity have no effect on nonpredisposed children. The obesogenic environment is therefore a trigger but not the primal cause of obesity; it just allows the phenotypic expression in children programmed to become overweight.

The purpose of this paper is to review all the mechanisms programming a child towards obesity. The primary is genetic predisposition to obesity, but other early possible programming factors occurring in utero or during the first months of life are also discussed. Finally, in view of these data, erroneous opinions about the origin of childhood obesity are brushed aside and relevant clinical practice deduced (fig. 1).

Fig. 1. Schematic representing the concepts regarding childhood obesity. The cone filter represents the requirement for a genetic predisposition. For children that are not genetically predisposed, inactivity or abundant food availability will have no effect on the risk of developing clinical obesity during childhood.


goto top of outline Evidence for the Need of a Constitutional Susceptibility to Become Obese

The increases in body weight in healthy children follow well-established curves included in specific charts, despite large daily energy mismatches. This process, which maintains a constant increase in body weight within a narrow and individualized range, is known as adipostat. Probably through peripheral adiposity signals [5], particularly leptin and ghrelin, the hypothalamus coordinates adaptive responses to energy imbalances via reciprocal alterations in appetite and energy expenditure in order to maintain a standard increase in body weight. Clearly, all these processes which control the body weight of humans and program the children’s increase in body weight mainly rely upon genetics [6].

It is likely that the increase in body weight in obese children is also programmed, but at a higher level than their non-obese counterparts. This hypothesis is more plausible than a dysregulation of their adipostat inducing an excess weight gain when the children eat more than they expend. Indeed, when obese children try to lose weight, their adipostat actively resists by stimulating appetite [7] and reducing energy expenditure [8] in order to maintain the elevated body weight. In obese children, this programmed, elevated weight gain is also mainly influenced by genes.

In a systematic review of studies in twins and adopted children, Silventoinen et al. [3] demonstrated that genetic factors have a much stronger effect than environmental factors on the evolution of body mass index (BMI) in children up to the age of 18 years. Interestingly, if environmental factors did moderately affect BMI variation in childhood, their effect disappeared in adolescence from 13 years of age. This suggests that parents may influence the BMI evolution of their children during the first decade of their life, but BMI curve takes back its programmed evolution when adolescents are less dependent on their relatives to eat and move.

The predominant genetic influence on BMI evolution persists until adulthood. Stunkard et al. [9] demonstrated that the intrapair correlation of the values for BMI at 21 years of age was similar in identical twins either reared apart (in a different environment) or together (in the same environment), and 2.5- to 5-fold higher in monozygotic twins than in dizygotic twin pairs. In a longitudinal cohort study, a strong correlation was found between parents’ BMI and the BMI of their offspring in both childhood (11 years) and midadulthood (44–45 years) [10]. These associations were not affected by adjustment for a wide range of lifestyle factors. Again, these studies demonstrate that BMI evolution is strongly influenced by the genetic background of each subject for many decades, while the effect of environmental factors is much less important.

The programming of the BMI curve in children does not mean that the evolution towards obesity is ineluctable. Both energy restriction and increased physical activity can contain or limit the programmed weight gain, even early in life. Genetic factors are predominant for the spontaneous evolution of BMI, but only environmental events are able to modify the BMI curve. However, these behavioral changes do not alter the previous programming of the weight gain curve, which remains identical because adipostat continuously resists to weight loss by stimulating appetite and reducing energy expenditure. This is the likely explanation for the failure of traditional obesity treatment.


goto top of outline Genetics of Childhood Obesity

Strong lines of evidence support the contention that individual differences in the predisposition to weight gain rely in a personal genetic profile. In contrast to the monogenic forms of obesity which are both rare and severe, common obesity is polygenic with no observable simple Mendelian inheritance, and its expression requires the pressure of an obesogenic environment. It is interesting to observe that whatever the origin of the obesity, most of the genes involved regulate food intake and energy balance.

goto top of outline Rare Monogenic Recessive Forms of Obesity

At least 200 cases of human obesity have been associated with homozygous forms of a single gene mutation [11]. In affected subjects, obesity develops since the genetic alterations impede key steps in the hypothalamic leptin (LEP)-melanocortin signaling pathways that regulate food intake and, to a lesser extent, energy expenditure [11]. The most well-known mutations affect LEP itself or its receptor (LEPR), proopiomelanocortin (POMC) and pro-hormone convertase subtilisin/kesin type 1 (PCSK1). These peptides are included in pathways which generate the anorectic peptide α-melanocyte-stimulating hormone, which exerts its effect through its binding to melanocortin 3 (MC3R) and melanocortin 4 (MC4R) receptors (fig. 2). Mutations in human genes coding for LEP [12], LEPR [13], POMC [14], and PCSK1 [15] lead to early-onset obesity (table 1). Patients show a rapid and dramatic increase in weight, as illustrated by the weight curve of LEPR-deficient subjects (fig. 3). Beside a frequent impulsive pattern of eating behavior and food seeking disorder, patients suffering these rare monogenic forms of obesity are also characterized by the presence of associated phenotypes like endocrine dysfunctions or impaired pubertal development (table 1). To date, only the congenital leptin deficiency, affecting only 13 children in the world, can be treated. In these patients, leptin replacement with recombinant human leptin leads to the disappearance of the obsessive hunger resulting in a rapid weight loss, and the normalization of the pubertal development [16].

Table 1. Monogenic forms of childhood obesity

Fig. 2. Oversimplified illustration of hypothalamic leptin-melanocortin signaling pathways. MSH: α-Melanocyte-stimulating hormone; SIM-1: single-minded homologue 1.

Fig. 3. BMI curves of 2 homozygous null leptin receptor mutants (LepR 1 and 2), 1 homozygous null melanocortin 4 receptor patient (null MC4R), 6 heterozygous (heterozygous MC4R) and 40 non-mutated obese controls. The reference curves are the standard French percentile curves [derived from ref. [11] ].

The discovery of these mutations has allowed the unraveling of the central mechanisms that regulate body weight and dispelled the preconceived notion that obesity represents an individual defect with no biological basis.

More recently, mutations in 3 genes involved in the neural development have proved to underlie rare monogenic obesity: single-minded homologue 1 [17], neurotrophic tyrosine kinase receptor type 2 [18] and brain-derived neurotrophic factor (BDNF) [19]. These genes are all involved in the functioning of the hypothalamus and alterations in the nucleotide sequence trigger hyperphagia. BDNF mutations were originally identified as a cause of rare monogenic obesity, but they revealed with time to be frequent enough to account for a non-negligible proportion of common obesity cases [19]. Further studies are necessary to confirm it.

goto top of outline MC4R-Linked Obesity

Due to its dominant mode of transmission, MC4R-linked obesity is the most prevalent form of monogenic obesity identified to date. It represents approximately 2–3% of childhood obesity with >90 different mutations throughout the gene described in different populations [11]. The penetrance of the disease is usually incomplete and clinical expression variable. This suggests an additional implication of the environment and other modulating genetic factors explaining why some carriers of the mutation are lean [20].

In contrast to rare monogenic recessive forms of obesity, even a meticulous clinical analysis does not easily detect obesity stemming from MC4R mutations because of a lack of obvious associated phenotypes (table 1). In heterozygous MC4R mutation carriers, the onset and magnitude of obesity vary and are related to the severity of the functional alteration caused by the mutation. In most cases, children show an early-onset obesity in parallel with increased linear growth, especially in the first 5 years of life, but do not appear to be taller in adulthood [21,22]. Obese children carrying MC4R mutations have a marked hyperphagia that decreases with age, but no specific trend to binge eating [23]. The metabolic rate is not decreased [23]. The patients do not suffer associated endocrine disorders [20,21,22]. The only physiological alterations, both reported in UK children [22], were an increase in bone mineral density. which may be explained, at least partially, by a decrease in bone resorption and fasting hyperinsulinemia [24].

Homozygous carriers of the MC4R mutation are very rare. Four carriers of homozygous null mutations in the gene receptor have been found [22,25,26]. The carriers display a very early onset of severe obesity, the weight gain being not associated with additional related phenotypes.

Numerous experiments have been conducted to highlight the functional abnormalities underlying the part played by MC4R mutations in the genesis of the associated obesity (fig. 4). Mutations can result in a varied panel of alterations: abnormal MC4R membrane expression, impaired agonist response, alterations in the basal tonic activity of the receptor, or a disruption in the intracellular transport of this protein by cytosolic retention. The latter has been described for the majority of MC4R mutations [27] and explains the impaired response to agonists.

Fig. 4. MC4R-linked obesity is the most prevalent form of monogenic obesity identified to date. Functional abnormalities are depicted. a = Abnormal MC4R expression or impaired agonist response (satiety); b = alteration in the basal tonic activity of the receptor; c = disruption in the intracellular transport of proteins by cytosolic retention (e.g. BDNF). MSH = α-Melanocyte-stimulating hormone.

A new direct line of research on the genetic determinants of childhood obesity has been drawn lately, with the discovery of genetic variants in MC3R (table 1). MC3R, another receptor activated with POMC-derived peptides, has an important complementary role in the regulation of energy homeostasis next to MC4R. Common variants are associated with pediatric obesity due to a greater energy intake but not diminished energy expenditure [28]. Recently, several rare mutations with functional alterations proved to be associated with severe obesity in children [29,30]. Further epidemiological and functional research regarding the importance of MC3R mutations would shed light on the importance of MC3R mutants and potential combined effects with other genes in severe early-onset obesity.

In conclusion, childhood obesity linked to mutations in MC4R, and probably MC3R as well, resembles common forms of early-onset obesity and stands between exceptional forms of recessive monogenic obesity with complete penetrance and the polygenic forms of common obesity.

goto top of outline Polygenic Forms of Common Obesity

For the last 15 years, the numerous studies that have been carried out to delineate the architecture of genetic predisposition to common obesity has led to the discovery of a network of genes involved and gene-gene interactions, being as sophisticated as brain circuitry. However, their role remains to be elucidated. The fact that, in contrast to monogenic obesity, each mutation leads to a variant that brings only a susceptibility and requires the presence of other variants plus an obesogenic environment to determine a phenotype, makes the discovery a harsh task. Chronologically, the identification of susceptibility genes has, first, been based on genetic epidemiological approaches, i.e. genome-wide linkage and candidate gene association studies. In recent years, significant progress has been made through genome-wide association studies that provide more accurate genomic locations for obesity-related genes and has allowed confirming or ruling out the implication of variants suggested by first generation approaches.

Family-based genome-wide linkage scans examine whether genetic markers, located at different loci along the whole genome, cosegregate with a disease or a trait across generations. Linkage results had identified promising candidate genes such as GAD2 (glutamate decarboxylase 2) at the origin of the γ-aminobutyric acid that upregulates food intake, ENPP1 (ectonucleotide pyrophosphatase/phosphodiesterase 1), which plays a part in brain insulin sensing, and SLC6A14 (solute carrier family 6 membrane 14), a tryptophan transporter implicated in appetite regulation [31]. Linkage analyses succeed when variants are common and exert a rather strong effect. The failure to replicate associations at many loci in the studies suggests that the variants have only a small genetic effect when taken alone [32].

In candidate gene association studies, polymorphisms in genes known to code for proteins involved in the regulation of energy balance in animal models or human monogenic obesity are tested for association with obesity-related traits at the population level. Among the genes tested, polymorphisms in LEP and LEPR as well as different variants known to play a role in feeding behavior (PCSK1, POMC, or BDNF), neural signaling, e.g. cannabinoid receptor (CNR1), dopamine receptor (DRD2), or serotonin receptor (2C HTR2C), or function (SLC6A4) have been shown to be associated with obesity or predictive of BMI [31]. Interestingly, rare polymorphisms in MC4R have been quite consistently associated with a protective effect against obesity [33]. Candidate gene studies have provided suggestive evidence that multiple genes are involved in the predisposition to obesity. However, these genes were supported by data from grossly underpowered studies; thus, replication in large-scale studies and meta-analytical approaches could not conclude a definitive effect for most of the variants cited previously [31].

Genome-wide association studies have revolutionized the field of genetic epidemiology since they screen the whole genome at a very high resolution (hundreds of thousands of genetic variants). Thus, they make it possible to identify precisely those genetic variants robustly linked to obesity while they have relatively small effect sizes. So far, around 20 loci consistently associated with obesity-related traits have been discovered in adults [34]. In children, the most important locus was discovered in the fat mass and the obesity-associated gene FTO. FTO variants are associated with increased weight and ponderal index already at 2 weeks of age [35]. FTO is widely expressed in the brain, especially in the hypothalamic nuclei involved in regulating energy balance. Children who carry the risk allele display increased food intake and sometimes binge eating episodes with a preference for energy-dense food [36] as well as a decreased satiety [37]. Among all the other genes discovered, most of them act through effects in the central nervous system, although effects in other tissues for some of these genes remain possible [34]. The next step for all of these novel genes is to clarify the biological role of each variant in obesity.

More recently, a great deal of excitement has developed relating to a newly discovered genomic variability due to a variation in gene copy number. Copy number variation, or CNV, is defined as a variation from one person to the next in the number of copies (deletion, insertion, or duplication) of a given gene. This ‘gene dosage’ effect creates a risk for a disease, or confers protection from it. So far, several common obesity CNVs have been identified in extremely obese children. They consisted of deletions in a genomic region covering olfactory receptor genes. However, the author concluded that the association with obesity was too small to substantially contribute to the genetic basis of early onset of obesity [38]. Conversely, again in severely obese children, children harboring a rare large deletion in a chromosomic region encompassing the SH2B1 gene, which is known to be involved in leptin and insulin signaling, exhibited hyperphagia and severe insulin resistance with mental retardation [39]. Finally, CNVs (deletions or duplications) in 8 loci proved to contribute to genetic susceptibility of common childhood obesity [40]. The research on the part played by CNVs in the genesis of childhood obesity is expanding rapidly. Since gene variants explain only a small proportion of the overall heritability, there is hope that CNVs will prove to contribute to the missing heritability.

The refining of methodological approaches, the use of large-scale cohorts with standardized phenotypes and the development of more accurate specific statistical tools will certainly enlighten the involvement of unsuspected loci and specify the role played by those already identified, especially in terms of gene-gene interactions. Moreover, pinpointing the respective contribution of genetic predisposition and lifestyle in determining individual weight is definitely the task to focus on. The findings to come will certainly increase our insights in the regulation of energy balance in humans and, hopefully, also provide new avenues for effective treatment and prevention since they will rely on the genetic profile of children at risk.


goto top of outline Early Programming in Childhood Obesity

Some observations suggest that the fetal and early postnatal environments may play a role in favoring the occurrence of overweight or obesity later in life (table 2). These early determinants of future obesity represent constitutive factors which are not inscribed in the genetic patrimony and, generally, not transmitted across generations. Most of them are certainly still to be discovered. An epigenetic origin is probably involved [41]. Epigenetics refers to processes that induce heritable changes in gene expression without altering the gene sequence. They consist mainly of DNA methylation and modifications of the histones around which DNA winds.

Table 2. Early programming in childhood obesity: summary of the possible constitutive factors

goto top of outline Under- or Overnutrition during Pregnancy

Studies of individuals exposed to famine in utero during World War II show that mothers who suffered famine periconceptually and in the first trimester of pregnancy gave birth to children with a normal weight at birth but exhibited increased risk of later obesity [42]. Conversely, in individuals whose mothers were exposed to famine during the last trimester of pregnancy the risk of obesity was absent [42]. The proposed mechanisms underlying this relationship are a dysfunction in the hypothalamic nuclei that control energy balance. It is hypothesized that undernutrition during central nervous system development (first months of gestation) generates a process favoring a better metabolic efficiency to compensate for the energetic deficit. This acquired energy-sparing system would lead to an excessive fat storage when enough food is available. The absence of an effect when mothers are deprived of food only during the last trimester could be explained by the fact that the development of the central body weight regulatory system was achieved when undernutrition occurred.

Prepregnancy obesity in mothers and gestational weight gain are also positively associated with obesity in offspring from childhood to adulthood [43]. This is likely to primarily reflect the genetic effect on obesity. However, maternal weight loss through bariatric surgery prevents transmission of obesity to children compared with the offspring of mothers who did not undergo the surgery and remained obese [44]. The mechanism underlying the relationship between the nutrition state of the mother and the predisposition to obesity in children still obviously needs to be elucidated. Epigenetic factors may be suggested since maternal intake of nutrients has been shown to alter the methylation of genes resulting in effects on fetal and offspring development [41].

goto top of outline Maternal Smoking during Pregnancy

Children whose mothers smoked during pregnancy are at elevated risk for becoming overweight from childhood to adulthood [45]. Mechanisms by which maternal smoking may program child weight are not yet well characterized. Since the association between maternal smoking and child overweight is independent of birth weight or fetal growth and postnatal weight gain, a more rapid postnatal weight gain as the cause of later obesity can be excluded [45]. Nicotine, which is transported across the placenta, may act at the fetal brain level during its development by altering the control center of appetite. The resulting fetal programming may be responsible for further obesity through alterations in the control of food intake. The modified appetite control observed in offspring of mothers who smoked during pregnancy supports this hypothesis [46].

goto top of outline Gestational Diabetes

Gestational diabetes has been associated with an increased rate of offspring childhood obesity [47], although the risks seem to be small [48]. Confounding factors like maternal obesity or increased insulin resistance susceptibility which favor the occurrence of both gestational diabetes and familial obesity may explain this association, all the more so as the relationship is statistically small. Gestational diabetes would therefore be a trait of the familial predisposition to obesity and not the cause of offspring overweight.

It is, however, also possible that fetal exposure to maternal hyperglycemia results in fetal hyperinsulinemia, which in turn may alter the development of the body weight regulation center in the brain. Further obesity in offspring would therefore be the consequence of metabolic imprinting [49].

goto top of outline Elevated Birth Weight

A birth weight >4 kg is associated with an increased risk of obesity later in life [50]. However, this association is probably due to confounding factors owing to maternal characteristics, among them, maternal obesity is likely to be predominant [50]. Therefore, elevated birth weight should not be considered as a risk factor for further obesity.

goto top of outline Rapid Weight Gain Early in Life

Greater early infancy weight gain has been suggested to be an important risk factor to develop further obesity [51]. A direct relationship between the excessive weight gain early in life and the occurrence of later overweight raises concern about the relevance of weight catch-up of small-for-gestational-age neonates. These results also suggest new strategies to prevent obesity by limiting weight gain in early infancy [52].

However, it can be speculated whether this increased early weight gain was the cause of further obesity or if it was only an early expression of a genetic predisposition to obesity. Recent studies using robust genetic markers of obesity clearly demonstrated that early infancy weight gain represents the early phenotypic expression of the genetic factors that predispose to later obesity and not its etiology [53]. Therefore, rapid weight gain early in life should not be considered as a problem with regard to prevention of further obesity, particularly in small-for-gestational-age neonates. The risks for later cardiovascular diseases or metabolic syndrome seem, however, to be much more convincing [54].

goto top of outline Formula Feeding versus Breastfeeding

Prevention of later obesity is recognized as one of the multiple benefits of breastfeeding [55]. When compared to formula feeding, lower content of protein and energy, better control of the amount of milk consumed and lower growth during the first year of life are the main underlying mechanisms suggested to explain the protective effect of breastfeeding against later obesity [56].

However, the majority of the studies aimed at demonstrating that breastfeeding causes a reduction in risk of later obesity exhibit some serious bias. First of all, confounding factors such as socioeconomic status, ethnicity or paternal BMI are difficult to be taken into account in the statistical analyses and may therefore explain the relationship between breastfeeding and protection against obesity. Moreover, for obvious ethical reasons, almost all trials are not randomized. It is well known that breastfeeding is more frequent in families with higher socioeconomic status in which the risk of obesity is reduced. Reducing the effect of this important confounding factor in the statistical analyses is insufficient to exclude the huge bias introduced by the absence of randomization. In one report, preterm babies were randomly assigned to receive banked breast milk or infant formula. There were no significant differences in body weight at follow-up and at 13–15 years of age [57]. For all these reasons, serious concerns arise about the putative protective effect of breastfeeding against later obesity [58]. More evidence is necessary to assess the potential role of breastfeeding in reducing later obesity development [56,58].

goto top of outline Excess in n–6 Polyunsaturated Fatty Acid Intake

Animal studies have shown that an increase in the relative intake of n–6 to n–3 polyunsaturated fatty acids during pregnancy and lactation promotes adipose tissue development in offspring, which in turn may augment the risk of later obesity [59]. Subsequently, some authors hypothesized that the dramatic increase during the last decades in n–6 polyunsaturated fatty acid intake in lactating mothers and infants may have contributed to the childhood obesity epidemic [60]. However, robust data from human studies are lacking to support this hypothesis [61]. Further studies are required to test the putative relationship between excess n–6 polyunsaturated fatty acid intake and later obesity.

goto top of outline Excess in Protein Intake

Higher protein intake in the first months of life was associated with increased body fatness later in childhood [62]. As a consequence, a link between protein intake in infancy and the risk of later obesity was suggested. A higher protein intake stimulates secretion of insulin-like growth factor 1, which in turn might induce adipose cell proliferation and consecutively increased adipose tissue. However, later studies did not confirm these results [63,64].

To test the hypothesis that higher protein intake in infancy leads to more rapid weight gain and consecutively increases the risk of later obesity, a multicenter European study has been conducted [65]. More than 600 infants were randomly assigned to receive formula with lower or higher protein contents for the first year of life. Preliminary results at 2 years showed a significantly increased BMI z-score in the lower protein formula group. However, the mean difference was so small between the groups (180 g for body weight and 2 mm for height) that even if the follow-up of the study could confirm the tendency observed at 2 years, the role of an excess protein intake early in life in the development of later obesity, if present, can indeed be considered as negligible.

goto top of outline Conclusions

Clearly some environmental factors seem to induce a fetal programming towards obesity (under- or overnutrition and maternal smoking during pregnancy, or gestational diabetes), but the putative role of postnatal factors in early obesity programming (formula feeding rather than breastfeeding, excess in n–6 polyunsaturated fatty acids or protein intakes) needs to be further explored. In any case, genetic programming towards childhood obesity appears to be much more relevant than early fetal or postnatal programming. It can, however, be assumed that early environmental factors may accelerate the phenotypic expression of a genetic predisposition, explaining in part why children seem to become obese earlier in their lifetime than their parents [66].


goto top of outline Application to Childhood Obesity Management

According to the data presented above, we consider that childhood obesity is a programmed disease for which phenotypic expression needs an obesogenic environment. Psychological stress, drugs, brain tumors or brain damage due to sleep insufficiency have been shown to initiate excess weight gain in children. However, most of them act as a trigger in a predisposed child rather than an authentic cause. Considering that children become obese because they are programmed to, excess energy intake and inactivity should be regarded as a consequence of the disease and not its cause [67,68]. Thus, childhood obesity should not be considered as the result of either inappropriate eating habits or an abdication of parental responsibilities. Parents should not be blamed for the obesity of their children; nonetheless, their role in the outcome of the treatment of their children’s obesity remains fundamental. Unfortunately, these notions are not common and most people still think the opposite, contributing to increasing the discrimination and the stigmatization of obese children and their parents. It is urgent to inform people about the real origin of childhood obesity in order to relieve the distress of obese children and their families.

The constitutional origin of pediatric obesity may also explain the usual unsuccessful long-term outcome of its treatment [69,70]. Treatment of childhood obesity needs continuous energy restriction and/or increased physical activity to fight against the programmed BMI curve. Any slackening induces a quick and ineluctable return of BMI to its previously programmed curve. Maintaining a long-term energy restriction is all the more difficult since the adipostat resists weight loss by increasing appetite [7]. A substantial motivation is therefore necessary to resist to a programmed BMI curve. This probably explains the higher failure rate of obesity treatment in younger children [71]. Since the precocity of setting up the treatment is not a predictive factor of the long-term outcome [72,73], it is not necessary to begin energy restriction as soon as possible in children. Conversely, it is wiser to wait for the child to be enough motivated to start a diet, given the hunger induced by energy restriction is all the more hard to bear in young children. One should remember that whenever the treatment is initiated, it does not have any influence on the programming of the BMI curve [72,73].

The dramatically disappointing results of prevention programs may also be due to the programming of childhood obesity [74,75]. Indeed, these collective interventions aimed at preventing obesity are targeted at the whole pediatric population whereas only a minority of predisposed children is concerned. Moreover, this preventive approach may increase discrimination of obese children and induce eating behavioral disorders in the large number of non-predisposed children [74]. Since the majority of the children are not predisposed to obesity, prevention strategies should be targeted at children at risk. Children at risk of becoming obese are those with at least one obese parent and those who present an adiposity rebound before 6 years of age [76]. These at-risk children must be detected early in order to rapidly benefit from personalized intervention to prevent further fat gain. However, the efficacy of such tailored interventions remains to be demonstrated.


goto top of outline Conclusions

Considerable evidence is now available to support the existence of a programming towards childhood obesity, but the underlying mechanisms still remain to be explored. Clearly, the role of genetics dominates, but more research should be conducted to identify the genes involved. Fetal and perhaps early postnatal programming is also possible, but many studies are still required to confirm their contribution in pediatric obesity. Besides this programming, other factors such as viruses [77] or microbiota composition [78] may also be involved and need to be elucidated. In the future, improved knowledge on the pathophysiology of childhood obesity is absolutely essential to allow the development of more promising therapeutic and preventive approaches.


goto top of outline Disclosure Statement

The author declares that no financial or other conflict of interest exists in relation to the content of the article. The writing of this article was supported by the Nestlé Nutrition Institute.

 goto top of outline References
  1. de Onis M, Blössner M, Borghi E: Global prevalence and trends of overweight and obesity among preschool children. Am J Clin Nutr 2010;92:1257–1264.
  2. Wardle J, Carnell S, Haworth CMA, Plomin R: Evidence for the strong genetic influence on childhood adiposity despite the force of the obesogenic environment. Am J Clin Nutr 2008;87:398–404.
  3. Silventoinen K, Rokholm B, Kaprio J, Sørensen TIA: The genetic and environmental influences on childhood obesity: a systematic review of twin and adoption studies. Int J Obes 2010;34:29–40.
  4. Bouchard C: Defining the genetic architecture of the predisposition to obesity: a challenging but not insurmountable task. Am J Clin Nutr 2010;91:5–6.
  5. Cancello R, Tounian A, Poitou C, Clément K: Adiposity signals, genetic and body weight regulation in humans. Diabetes Metab 2004;30:215–227.
  6. Speliotes EK, Willer CJ, Berndt SI, Monda KL, et al: Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat Genet 2010;42:937–948.
  7. King NA, Hester J, Gately PJ: The effect of a medium-term activity- and diet-induced energy deficit on subjective appetite sensations in obese children. Int J Obes 2007;31:334–339.
  8. Tounian P, Frelut ML, Parlier G, et al: Weight loss and changes in energy metabolism in massively obese adolescents. Int J Obes Relat Metab Disord 1999;23:830–837.
  9. Stunkard AJ, Harris JR, Pedersen NL, McClearn GE: The body-mass index of twins who have been reared apart. N Engl J Med 1990;322:1483–1487.
  10. Cooper R, Hyppönen E, Berry D, Power C: Associations between parental and offspring adiposity up to midlife: the contribution of adult lifestyle factors in the 1958 British Birth Cohort Study. Am J Clin Nutr 2010;92:946–953.
  11. Dubern B, Tounian P, Clément K: Obesity; in Weiss RE, Refetoff S (eds): Genetic Diagnosis of Endocrine Disorders. London, Elsevier Academic Press, 2010, pp 27–37.
  12. Montague CT, Farooqi IS, Whitehead JP, et al: Congenital leptin deficiency is associated with severe early-onset obesity in humans. Nature 1997;387:903–908.
  13. Clement K, Vaisse C, Lahlou N, et al: Mutation in the human leptin receptor gene causes obesity and pituitary dysfunction. Nature 1998;392:398–401.
  14. Krude H, Biebermann H, Schnabel D, et al: Obesity due to proopiomelanocortin deficiency: three new cases and treatment trials with thyroid hormone and ACTH4–10. J Clin Endocrinol Metab 2003;88:4633–4640.
  15. Jackson RS, Creemers JW, Ohagi S, et al: Obesity and impaired prohormone processing associated with mutations in the human prohormone convertase 1 gene. Nat Genet 1997;16:303–306.
  16. Farooqi IS, Matarese G, Lord GM, et al: Beneficial effects of leptin on obesity, T cell hyporesponsiveness, and neuroendocrine/metabolic dysfunction of human congenital leptin deficiency. J Clin Invest 2002;110:1093–1103.
  17. Holder JL Jr, Butte NF, Zinn AR: Profound obesity associated with a balanced translocation that disrupts the SIM 1 gene. Hum Mol Genet 2000;9:101–108.
  18. Yeo GS, Connie Hung CC, Rochford J, et al: A de novo mutation affecting human TrkB associated with severe obesity and developmental delay. Nat Neurosci 2004;7:1187–1189.
  19. Friedel S, Horro FF, Wermter AK, et al: Mutation screen of the brain derived neurotrophic factor gene (BDNF): identification of several genetic variants and association studies in patients with obesity, eating disorders, and attention-deficit/hyperactivity disorder. Am J Med Genet B Neuropsychiatr Genet 2005;132B:196–199.
  20. Lubrano-Berthelier C, Dubern B, Lacorte JM, et al: Melanocortin 4 receptor mutations in a large cohort of severely obese adults: prevalence, functional classification, genotype-phenotype relationship, and lack of association with binge eating. J Clin Endocrinol Metab 2006;9:1811–1818.

    External Resources

  21. Vaisse C, Clement K, Durand E, et al: Melanocortin-4 receptor mutations are a frequent and heterogeneous cause of morbid obesity. J Clin Invest 2000;106:253–262.
  22. Farooqi IS, Keogh JM, Yeo GS, et al: Clinical spectrum of obesity and mutations in the melanocortin 4 receptor gene. N Engl J Med 2003;348:1085–1095.
  23. MacKenzie RG: Obesity-associated mutations in the human melanocortin-4 receptor gene. Peptides 2006;27:395–403.
  24. Ahn JD, Dubern B, Lubrano-Berthelier C, et al: CART overexpression is the only identifiable cause of high bone mass in melanocortin 4 receptor deficiency. Endocrinology 2006;147:3196–3202.
  25. Lubrano-Berthelier C, Le Stunff C, Bougnères P, Vaisse C: A homozygous null mutation delineates the role of the melanocortin-4 receptor in humans. J Clin Endocrinol Metab 2004;89:2028–2032.
  26. Dubern B, Bisbis S, Talbaoui H, Le Beyec J, Tounian P, Lacorte JM, Clément K: Identification of a novel homozygous null mutation of the melanocortin-4 receptor with severe early-onset obesity. J Pediatr 2007;150:613–617.
  27. Lubrano-Berthelier C, Durand E, Dubern B, et al: Intracellular retention is a common characteristic of childhood obesity-associated MC4R mutations. Hum Mol Genet 2003;12:145–153.
  28. Savastano DM, Tanofsky-Kraff M, Han JC, et al: Energy intake and energy expenditure among children with polymorphisms of the melanocortin-3 receptor. Am J Clin Nutr 2009;90:912–920.
  29. Mencarelli M, Dubern B, Alili R, et al: Rare melanocortin-3 receptor mutations with in vitro functional consequences are associated with human obesity. Hum Mol Genet 2011;20:392–399.
  30. Zegers D, Beckers S, de Freitas F, et al: Identification of three novel genetic variants in the melanocortin-3 receptor of obese children. Obesity 2011;19:152–159.
  31. Walley AJ, Asher JE, Froguel P: The genetic contribution to non-syndromic obesity. Nat Rev Genet 2009;10:431–442.
  32. Saunders CL, Chioni BD, Sham P, et al: Meta-analysis of genome-wide linkage studies in BMI and obesity. Obesity 2007;15:2263–2275.

    External Resources

  33. Stutzmann F, Vatin V, Cauchi S, et al: Non-synonymous polymorphisms in melanocortin-4 receptor protect against obesity: the two facets of a Janus obesity gene. Hum Mol Genet 2007;16:1837–1844.
  34. Loos RJ: Recent progress in the genetics of common obesity. Br J Clin Pharmacol 2009;68:811–829.
  35. Lopez-Bermejo A, Petry CJ, Diaz M, et al: The association between the FTO gene and fat mass in humans develops by the postnatal age of two weeks. J Clin Endocrinol Metab 2008;93:1501–1505.
  36. Tanofsky-Kraff M, Han JC, Anandalingam K, et al: The FTO gene rs9939609 obesity-risk allele and loss of control over eating. Am J Clin Nutr 2009;90:1483–1488.
  37. Wardle J, Carnell S, Haworth CM, et al: Obesity associated genetic variation in FTO is associated with diminished satiety. J Clin Endocrinol Metab 2008;93:3640–3643.
  38. Jarick I, Vogel CL, Scherag S, et al: Novel common copy number variation for early onset extreme obesity on chromosome 11q11 identified by a genome-wide analysis. Hum Mol Genet 2011;20:840–852.
  39. Bochukova EG, Huang Ni, Keogh J, et al: Large, rare, chromosomal deletions associated with severe early-onset obesity. Nature 2010;463:666–670.
  40. Glessner JT, Bradfield JP, Wang K, et al: A genome-wide study reveals copy number variants exclusive to childhood obesity cases. Am J Hum Genet 2010;12:661–666.

    External Resources

  41. Lillycrop KA, Burdge GC: Epigenetic changes in early life and future risk of obesity. Int J Obes 2011;35:72–83.

    External Resources

  42. Ravelli GP, van der Meulen JH, Osmond C, Barker DJ, Bleker OP: Obesity at the age of 50 y in men and women exposed to famine prenatally. Am J Clin Nutr 1999;70:811–816.
  43. Schack-Nielsen L, Michaelsen KF, Gamborg M, Mortensen EL, Sørensen TIA: Gestational weight gain in relation to offspring body mass index and obesity from infancy through adulthood. Int J Obes 2010;34:67–74.
  44. Kral JG, Biron S, Simard S, et al: Large maternal weight loss from obesity surgery prevents transmission of obesity to children who were followed for 2 to 18 years. Pediatrics 2006;118:1644–1649.
  45. Oken E, Levitan EB, Gillman LW: Maternal smoking during pregnancy and child overweight: systematic review and meta-analysis. Int J Obes 2008;32:201–210.
  46. Toschke AM, Ehlin AG, von Kries R, Ekbom A, Montgomery SM: Maternal smoking during pregnancy and appetite control in offspring. J Perinat Med 2003;31:251–256.
  47. Hillier TA, Pedula KL, Schmidt MM, Mullen JA, Charles MA, Pettitt DJ: Childhood obesity and metabolic imprinting: the ongoing effects of maternal hyperglycemia. Diabetes Care 2007;30:2287–2292.
  48. Pirkola J, Pouta A, Bloigu A, et al: Risks of overweight and abdominal obesity at age 16 years associated with prenatal exposures to maternal prepregnancy overweight and gestational diabetes mellitus. Diabetes Care 2010;33:1115–1121.

    External Resources

  49. Dabelea D, Pettitt DJ: Intrauterine diabetic environment confers risks for type 2 diabetes mellitus and obesity in the offspring, in addition to genetic susceptibility. J Pediatr Endocrinol Metab 2001;14:1085–1091.
  50. The NS, Adair LS, Gordon-Larsen P: A study of the birth weight-obesity relation using a longitudinal cohort and sibling and twin pairs. Am J Epidemiol 2010;172:549–557.

    External Resources

  51. Stettler N, Kumanyika SK, Katz SH, Zemel BS, Stallings VA: Rapid weight gain during infancy and obesity in young adulthood in a cohort of African Americans. Am J Clin Nutr 2003;77:1374–1378.
  52. Singhal A, Kennedy K, Lanigan J, et al: Nutrition in infancy and long-term risk of obesity: evidence from 2 randomized controlled trials. Am J Clin Nutr 2010;92:1133–1144.
  53. Elks CE, Loos RJF, Sharp SJ, et al: Genetic markers of adult obesity risk are associated with greater early infancy weight gain and growth. PLoS Med 2010;7:e1000284.

    External Resources

  54. Singhal A, Lucas A: Early origins of cardiovascular disease. Is there a unifying hypothesis? Lancet 2004;363:1642–1645.
  55. Horta B, Bahl R, Martines J, Victora C: Evidence of the Long-Term Effects of Breastfeeding: Systematic Reviews and Meta-Analysis. Geneva, World Health Organization, 2007.
  56. ESPGHAN Committee on Nutrition: Breast-feeding: a commentary by the ESPGHAN Committee on Nutrition. J Pediatr Gastroenterol Nutr 2009;49:112–125.
  57. Singhal A, Cole TJ, Fewtrell M, Lucas A: Breast-milk feeding and lipoprotein profile in adolescents born preterm: follow-up of a prospective randomised study. Lancet 2004;363:1571–1578.
  58. Cope MB, Allison DB: Critical review of the World Health Organization’s (WHO) 2007 report on ‘evidence of the long-term effects of breastfeeding: systematic reviews and meta-analysis’ with respect to obesity. Obes Rev 2008;9:594–605.
  59. Massiera F, Saint-Marc P, Seydoux J, et al: Arachidonic acid and prostacyclin signaling promote adipose tissue development: a human health concern? J Lipid Res 2003;44:271–279.
  60. Ailhaud G, Guesnet P: Fatty acid composition of fats is an early determinant of childhood obesity: a short review and an opinion. Obes Rev 2004;5:21–26.
  61. Muhlhausler BS, Gibson RA, Makrides M: Effect of long-chain polyunsaturated fatty acid supplementation during pregnancy or lactation on infant and child body composition: a systematic review. Am J Clin Nutr 2010;92:857–863.
  62. Rolland-Cachera MF, Deheeger M, Akrout M, Bellisle F: Influence of macronutrients on adiposity development: a follow up study of nutrition and growth from 10 months to 8 years of age. Int J Obes Relat Metab Disord 1995;19:573–578.
  63. Hoppe C, Molgaard C, Thomsen BL, et al: Protein intake at 9 mo of age is associated with body size but not with body fat in 10-y-old Danish children. Am J Clin Nutr 2004;79:494–501.
  64. Günther ALB, Buyken AE, Kroke A: The influence of habitual protein intake in early childhood on BMI and age at adiposity rebound: results from the DONALD Study. Int J Obes (Lond) 2006;30:1072–1079.
  65. Koletzko B, von Kries R, Closa R, et al: Lower protein infant formula is associated with lower weight up to age 2 y: a randomized clinical trial. Am J Clin Nutr 2009;89:1836–1845.
  66. Li L, Law C, Lo Conte R, Power C: Intergenerational influences on childhood body mass index: the effect of parental body mass index trajectories. Am J Clin Nutr 2009;89:551–557.
  67. Llewellyn CH, van Jaarsveld CHM, Johnson L, et al: Nature and nurture in infant appetite: analysis of the Gemini twin birth cohort. Am J Clin Nutr 2010;91:1172–1179.
  68. Metcalf BS, Hosking J, Jeffery AN, et al: Fatness leads to inactivity, but inactivity does not lead to fatness: a longitudinal study in children. Arch Dis Child 2010, E-pub ahead of print, DOI: 10.1136/adc.2009.175927.

    External Resources

  69. McGovern L, Johnson JN, Paulo R, et al: Treatment of pediatric obesity: a systematic review and meta-analysis of randomized trials. J Clin Endocrinol Metab 2008;93:4600–4605.
  70. Oude Luttikhuis H, Baur L, Jansen H, et al: Interventions for treating obesity in children. Cochrane Database Syst Rev 2009;1:CD001872.
  71. Wake M, Baur LA, Gerner B, et al: Outcomes and costs of primary care surveillance and intervention for overweight or obese children: the LEAP 2 randomised controlled trial. BMJ 2009;339:b3308.

    External Resources

  72. Ficheux L, Boelle PY, Achtari O, Santos L, Tounian P: Predictive factors of long-term weight evolution in treated obese children. Nutr Clin Metab 2009;23(suppl 1):S58–S59.
  73. Togashi K, Masuda H, Rankinen T, et al: A 12-year follow-up study of treated obese children in Japan. Int J Obes Relat Metab Disord 2002;26:770–777.
  74. Kamath CC, Vickers KS, Ehrlich A, et al: Clinical review: behavorial interventions to prevent childhood obesity: a systematic review and metaanalyses of randomized trial. J Clin Endocrinol Metab 2008;93:4606–4615.
  75. Harris KC, Kuramoto LK, Schulzer M, Retallack JE: Effect of school-based physical activity interventions on body mass index in children: a meta-analysis. CMAJ 2009;180:719–726.

    External Resources

  76. Rolland-Cachera MF, Deheeger M, Bellisle F, Sempé M, Guilloud-Bataille M, Patois E: Adiposity rebound in children: a simple indicator for predicting obesity. Am J Clin Nutr 1984;39:129–135.
  77. Atkinson RL, Dhurandhar NV, Allison DB, et al: Human adenovirus-36 is associated with increased body weight and paradoxical reduction of serum lipids. Int J Obes 2005;29:281–286.
  78. Reinhardt C, Reigstad CS, Bäckhed F: Intestinal microbiota during infancy and its implications for obesity. J Pediatr Gastroenterol Nutr 2009;48:249–256.

    External Resources

 goto top of outline Author Contacts

Patrick Tounian
Department of Pediatric Nutrition, Armand Trousseau Hospital
26 avenue du Dr. Arnold-Netter
FR–75571 Paris Cedex 12 (France)
Tel. +33 1 4473 6446, E-Mail

 goto top of outline Article Information

Published online: August 12, 2011
Number of Print Pages : 12
Number of Figures : 4, Number of Tables : 2, Number of References : 78

 goto top of outline Publication Details

Annals of Nutrition and Metabolism (Journal of Nutrition, Metabolic Diseases and Dietetics)

Vol. 58, No. Suppl. 2, Year 2011 (Cover Date: August 2011)

Journal Editor: Koletzko B. (Munich)
ISSN: 0250-6807 (Print), eISSN: 1421-9697 (Online)

For additional information:

Copyright / Drug Dosage / Disclaimer

Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher or, in the case of photocopying, direct payment of a specified fee to the Copyright Clearance Center.
Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in goverment regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug.
Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.