years was associated with higher fat as well as lean mass. Indian men and women who developed impaired glucose tolerance or type 2 diabetes in young adulthood appeared to follow the same pattern of slower early growth followed by faster growth in later childhood [88]. These discrepancies in the role of infant weight gain may be due to differing measurements or participant experiences across time or geography, but the true explanations are as yet unclear. In addition, the apparent cardiometabolic harms of rapid infant weight gain need to be balanced against its potential benefit for neurocognitive outcomes, especially in babies born preterm.
Infant diet quality and eating behaviors
One predictor of infant weight gain is infant feeding. In observational studies, having been breastfed at all or for a longer duration predicts a lower risk for subsequent obesity. In a meta‐analysis of 25 studies with a total of 226,508 participants from 12 countries, breastfeeding was associated with a significantly reduced risk of obesity in children (AOR 0.78; 95% CI: 0.74, 0.81). Categorical analysis of 17 studies revealed a dose‐response effect between breastfeeding duration and reduced risk of childhood obesity [89]. However, other data do not support a causal relationship between breastfeeding and lower obesity risk. It may be that infant growth predicts breastfeeding success, rather than the other way around, i.e. “confounding by indication” [90]. Furthermore, follow‐up of children in a large cluster‐randomized trial of breastfeeding promotion in the Republic of Belarus showed no intervention effect on anthropometric outcomes, obesity, or cardiometabolic risk factors through adolescence [91–93]. One should note, however, that all children in the Belarussian trial were initially breastfed, and the rates of obesity in the population overall were quite low.
Another group of investigators compared observational results from cohorts from high‐income with low‐ or middle‐income countries (LMIC), where confounding structures differ. They applied standardized approaches for assessing the confounding structure of breastfeeding by socio‐economic position to the British Avon Longitudinal Study of Parents and Children (ALSPAC) (N ≃ 5000) and Brazilian Pelotas 1993 cohorts (N ≃ 1000). Although a higher socio‐economic position was strongly associated with breastfeeding in ALSPAC, there was little such patterning in Pelotas. In ALSPAC, breastfeeding was associated with lower blood pressure (BP), lower BMI, and higher intelligence quotient (IQ), adjusted for confounders, but in the directions expected if due to socio‐economic patterning. In contrast, in Pelotas, breastfeeding was not strongly associated with BP or BMI but was associated with higher IQ. The authors concluded that reported associations of breastfeeding with child BP and BMI are likely to reflect residual confounding.
Other behaviors in infancy
Sleep duration is an issue of great salience to all new parents. It is by now well described in many studies among young adults, including mothers in the postpartum period [94], that short duration, poor quality, or irregular patterns of sleep are associated with excess adiposity gain and subsequent obesity risk [95]. This association is also now well‐described in children. In a meta‐analysis of 12 studies including 44,200 children from 15 cohorts, short sleep duration was strongly associated with obesity (RR 1.45; 95% CI: 1.14, 1.85) [96]. Although fewer data from infancy and early childhood are available, the same relationship appears to exist [97]. For example, in the Project Viva cohort, Taveras et al. have shown that infant sleep of less than 12 hours per day was associated with an OR of 2.20 (95% CI: 1.16, 4.19) for overweight at age 3 years [98] Shorter sleep duration from infancy through mid‐childhood was associated with poorer diet quality and both central and overall adiposity at age 7, but accounting for diet did not attenuate the association between sleep and BMI, suggesting that sleep acts on body weight regulation via other mechanisms [99,100].
It is worth noting that there is likely to be substantial confounding in relation to studies of childhood sleep. For example, in one analysis, 1‐year‐old children’s sleep characteristics such as bedtime, sleep latency, and sleep efficiency were predicted by maternal and paternal BMI [101]. Race/ethnicity and other sociodemographic factors associated with childhood obesity also strongly predicted child sleep habits [102]. Nonetheless, some emerging data from interventions suggest that improving sleep in infancy may promote healthier weight gain [103]. Although many children have poor sleep hygiene [104], sleep quality and possibly duration appear modifiable even in infancy [105].
Biology and mechanisms
Despite extensive studies addressing the potential relationship between events in early life and long‐term health, including obesity risk, there is still limited understanding of the mechanisms by which this may arise (reviewed in [106]).
Epigenetics
Much attention has been directed towards the role of epigenetic mechanisms. Epigenetics is a term used to describe mechanisms that alter gene activity without changing the DNA sequence. The most common mechanisms include changes in DNA methylation, histone modifications, and small noncoding RNAs. To date, the most frequently studied has been DNA methylation.
Most studies in humans addressing epigenetic mechanisms have focused on changes in DNA methylation in clinically accessible tissue, most commonly white blood cells rather than more metabolically relevant tissues. However, changes in white blood cell methylation have been observed in response to a number of in utero exposures. For example, a study of individuals currently in their sixties but exposed in utero to the Dutch Hunger Winter demonstrated altered methylation at a number of loci known to be involved in growth and metabolism [107]. Investigators in the Pregnancy and Childhood Epigenetics Consortium meta‐analyzed the association between pre‐pregnancy maternal BMI and methylation at over 450,000 sites in newborn blood DNA across 19 cohorts (9340 mother‐newborn pairs) [108]. In newborns, after adjustment for cell proportions, maternal BMI was associated with small methylation variation at 86 sites throughout the genome. At 72/86 sites, the direction of the association was the same in newborns and adolescents, suggesting the persistence of signals. In addition, epigenome‐wide analyses of blood from children at two different ages identified changes in DNA methylation that were associated with exposure in utero to maternal obesity and/or gestational diabetes [109]. However, changes in methylation were generally small in all analyses (<5%). Epigenome‐wide analysis has also identified changes in cord blood DNA methylation that are associated with maternal smoking during pregnancy. In one study, methylation of the locus GFI1 explained 12–19% of the reduction in birth weight resulting from maternal smoking [110]. Another study identified differences in placental methylation at seven sites that mediated the association between prenatal smoking and birth weight [111].
Studies in animal models have allowed the effects of changes in the early environment to be studied in metabolically relevant tissues. Although such studies enable causal effects of in utero exposures on the offspring epigenome to be determined, conclusions regarding the causal effects of specific epigenetic changes on the phenotypic outcome (e.g. offspring obesity) cannot be made. A study in rats demonstrated that high‐fat diet feeding during pregnancy caused hypermethylation of the promoter of POMC in the arcuate nucleus of the hypothalamus of the offspring, which was associated with increased feeding in response to a high‐fat diet [112].
Mediating metabolic factors
There has been much discussion of potential factors that could mediate the effects of suboptimal early exposures on long‐term risk of obesity. Because central regulation of energy balance plays a critical role in determination of weight regulation, development of neuronal pathways in the hypothalamus within the brain has been an area of interest. Animal studies have identified a number of hormonal and metabolic factors that influence development of hypothalamic circuits, including glucose, leptin, ghrelin, and insulin [113–116]. These factors can all be regulated by diet. Therefore, exposure to inappropriately high or low levels of these factors during critical periods of development could provide mechanisms by which nutrition during critical periods of development could impact on later obesity risk. However, translating such findings to humans is challenging.
Gut microbiota