Does the age at adiposity rebound reflect a critical period?

Timing based clustering of childhood BMI trajectories reveals differential maturational patterns; Study in the Northern Finland Birth Cohorts 1966 and 1986

BACKGROUND/OBJECTIVES

Children's biological age does not always correspond to their chronological age. In the case of BMI trajectories, this can appear as phase variation, which can be seen as shift, stretch, or shrinking between trajectories. With maturation thought of as a process moving towards the final state - adult BMI, we assessed whether children can be divided into latent groups reflecting similar maturational age of BMI. The groups were characterised by early factors and time-related features of the trajectories.

SUBJECTS/METHODS

We used data from two general population birth cohort studies, Northern Finland Birth Cohorts 1966 and 1986 (NFBC1966 and NFBC1986). Height (n = 6329) and weight (n = 6568) measurements were interpolated in 34 shared time points using B-splines, and BMI values were calculated between 3 months to 16 years. Pairwise phase distances of 2999 females and 3163 males were used as a similarity measure in k-medoids clustering.

RESULTS

We identified three clusters of trajectories in females and males (Type 1: females, n = 1566, males, n = 1669; Type 2: females, n = 1028, males, n = 973; Type 3: females, n = 405, males, n = 521). Similar distinct timing patterns were identified in males and females. The clusters did not differ by sex, or early growth determinants studied.

CONCLUSIONS

Trajectory cluster Type 1 reflected to the shape of what is typically illustrated as the childhood BMI trajectory in literature. However, the other two have not been identified previously. Type 2 pattern was more common in the NFBC1966 suggesting a generational shift in BMI maturational patterns.

Prospective prediction of childhood body mass index trajectories using multi-task Gaussian processes

BACKGROUND

Body mass index (BMI) trajectories have been used to assess the growth of children with respect to their peers, and to anticipate future obesity and disease risk. While retrospective BMI trajectories have been actively studied, models to prospectively predict continuous BMI trajectories have not been investigated.

MATERIALS AND METHODS

Using longitudinal BMI measurements between birth and age 10 y from a mother-offspring cohort, we leveraged a multi-task Gaussian process approach to develop and evaluate a unified framework for modeling, clustering, and prospective prediction of BMI trajectories. We compared its sensitivity to missing values in the longitudinal follow-up of children, compared its prediction performance to cubic B-spline and multilevel Jenss-Bayley models, and used prospectively predicted BMI trajectories to assess the probability of future BMIs crossing the clinical cutoffs for obesity.

RESULTS

MagmaClust identified 5 distinct patterns of BMI trajectories between 0 to 10 y. The method outperformed both cubic B-spline and multilevel Jenss-Bayley models in the accuracy of retrospective BMI trajectories while being more robust to missing data (up to 90%). It was also better at prospectively forecasting BMI trajectories of children for periods ranging from 2 to 8 years into the future, using historic BMI data. Given BMI data between birth and age 2 years, prediction of overweight/obesity status at age 10 years, as computed from MagmaClust's predictions exhibited high specificity (0.94), negative predictive value (0.89), and accuracy (0.86). The accuracy, sensitivity, and positive predictive value of predictions increased as BMI data from additional time points were utilized for prediction.

CONCLUSION

MagmaClust provides a unified, probabilistic, non-parametric framework to model, cluster, and prospectively predict childhood BMI trajectories and overweight/obesity risk. The proposed method offers a convenient tool for clinicians to monitor BMI growth in children, allowing them to prospectively identify children with high predicted overweight/obesity risk and implement timely interventions.

Differentially methylated regions interrogated for metastable epialleles associate with offspring adiposity

Aim: Assess if cord blood differentially methylated regions (DMRs) representing human metastable epialleles (MEs) associate with offspring adiposity in 588 maternal-infant dyads from the Colorado Health Start Study.Materials & methods: DNA methylation was assessed via the Illumina 450K array (~439,500 CpG sites). Offspring adiposity was obtained via air displacement plethysmography. Linear regression modeled the association of DMRs potentially representing MEs with adiposity.Results & conclusion: We identified two potential MEs, ZFP57, which associated with infant adiposity change and B4GALNT4, which associated with infancy and childhood adiposity change. Nine DMRs annotating to genes that annotated to MEs associated with change in offspring adiposity (false discovery rate <0.05). Methylation of approximately 80% of DMRs identified associated with decreased change in adiposity.

Postnatal growth in small vulnerable newborns: a longitudinal study of 2 million Brazilians using routine register-based linked data

BACKGROUND

Preterm, low-birth weight (LBW) and small-for-gestational age (SGA) newborns have a higher frequency of adverse health outcomes, including linear and ponderal growth impairment.

OBJECTIVE

To describe the growth trajectories and to estimate catch-up growth during the first 5 y of life of small newborns according to 3 vulnerability phenotypes (preterm, LBW, SGA).

METHODS

Longitudinal study using linked data from the 100 Million Brazilian Cohort baseline, the Brazilian National Live Birth System (SINASC), and the Food and Nutrition Surveillance System (SISVAN) from 2011 to 2017. We estimated the length/height-for-age (L/HAZ) and weight-for-age z-score (WAZ) trajectories from children of 6-59 mo using the linear mixed model for each vulnerable newborn phenotype. Growth velocity for both L/HAZ and WAZ was calculated considering the change (Δ) in the mean z-score between 2 time points. Catch-up growth was defined as a change in z-score > 0.67 at any time during follow-up.

RESULTS

We analyzed 2,021,998 live born children and 8,726,599 observations. The prevalence of at least one of the vulnerable phenotypes was 16.7% and 0.6% were simultaneously preterm, LBW, and SGA. For those born at term, all phenotypes had a period of growth recovery from 12 mo. For preterm infants, the onset of L/HAZ growth recovery started later at 24 mo and the growth trajectories appear to be lower than those born at term, a condition aggravated among children with the 3 phenotypes. Preterm and female infants seem to experience slower growth recovery than those born at term and males. The catch-up growth occurs at 24-59 mo for males preterm: preterm + AGA + NBW (Δ = 0.80), preterm + AGA + LBW (Δ = 0.88), and preterm + SGA + LBW (Δ = 1.08); and among females: term + SGA + NBW (Δ = 0.69), term + AGA + LBW (Δ = 0.72), term + SGA + LBW (Δ = 0.77), preterm + AGA + LBW (Δ = 0.68), and preterm + SGA + LBW (Δ = 0.83).

CONCLUSIONS

Children born preterm seem to reach L/HAZ and WAZ growth trajectories lower than those attained by children born at term, a condition aggravated among the most vulnerable.

Birth outcomes and early growth patterns associated with age at adiposity rebound: the Ma'anshan birth cohort (MABC) study

OBJECTIVE

Early onset of adiposity rebound (AR) is considered an early indicator of obesity risk. Our objective was to investigate the association of birth outcomes and early physical growth patterns with early AR in children.

METHODS

Study subjects (n = 2705) were enrolled from the Ma'anshan birth cohort (MABC). The body mass index (BMI), head circumference, waist circumference, and body fat were collected. Rapid weight gain (RWG) was defined by the change in weight standard-deviation score in the first two years of life. Group-based trajectory modeling (GBTM) was used to determine children's physical growth trajectories. The age of AR was fitted using fractional polynomial function models.

RESULTS

Children with very high BMI trajectories (RR = 2.83; 95% CI 2.33 to 1.40), rising BMI trajectories (RR = 3.15; 95% CI 2.66 to 3.72), high waist circumference trajectories (RR = 4.17; 95% CI 3.43 to 5.06), and high body fat trajectories (RR = 3.01; 95% CI 2.62 to 3.46) before 72 months of age were at a greater risk of experiencing early AR. Low birth weight (LBW) (RR = 1.86; 95% CI 1.28 to 2.51), preterm birth (PTB) (RR = 1.50; 95% CI 1.17 to 1.93), and small for gestational age (SGA) (RR = 1.37; 95% CI 1.14 to 1.64) associated with increased risk of early AR. Moreover, infants experiencing RWG (RR = 1.59; 95% CI 1.40 to 1.83), low BMI trajectories (RR = 1.27; 95% CI 1.06 to 1.53) and rising BMI trajectories (RR = 1.50; 95% CI 1.22 to 1.84) in the first two years were at higher risk of developing early AR subsequently. Compared to the group with non-early AR, the BMI of children with early AR tended to be lower first (from birth to 6 months of age) and then higher (from 18 to 72 months of age).

CONCLUSIONS

Children with overall high BMI, high waist circumference, and high body fat before 72 months of age are more likely to experience early AR, but infants with low BMI trajectories, rising BMI trajectories and infants experiencing RWG in the first two years of life similarly increase the risk of early AR. These results can help to understand the early factors and processes that lead to metabolic risks.

Different protein intake in the first year and its effects on adiposity rebound and obesity throughout childhood: 11 years follow-up of a randomized controlled trial

BACKGROUND AND OBJECTIVES

Infant feeding affects child growth and later obesity risk. We examined whether protein supply in infancy affects the adiposity rebound, body mass index (BMI) and overweight and obesity up to 11 years of age.

METHODS

We enrolled healthy term infants from five European countries in a double blind randomized trial, with anticipated 16 examinations within 11 years follow-up. Formula-fed infants (n = 1090) were randomized to isoenergetic formula with higher or lower protein content within the range stipulated by EU legislation in 2001. A breastfed reference group (n = 588) was included. Adiposity rebound and BMI trajectories were estimated by generalized additive mixed models in 917 children, with 712 participating in the 11 year follow-up.

RESULTS

BMI trajectories were elevated in the higher compared to the lower protein group, with significantly different BMI at adiposity rebound (0.24 kg/m², 0.01-0.47, p = 0.040), and an increased risk for overweight at 11 years (adjusted Odds Ratio 1.70; 1.06-2.73; p = 0.027) but no significant difference for obesity (adjusted Odds Ratio 1.47; 0.66-3.27). The two formula groups did not differ in the timing of adiposity rebound, but all children with obesity at 11 years had an early adiposity rebound before four years.

CONCLUSIONS

Compared to conventional high protein formula, feeding lower protein formula in infancy lowers BMI trajectories up to 11 years and achieves similar BMI values at adiposity rebound as observed in breastfed infants.

Predicting the earliest deviation in weight gain in the course towards manifest overweight in offspring exposed to obesity in pregnancy: a longitudinal cohort study

BACKGROUND

Obesity in pregnancy and related early-life factors place the offspring at the highest risk of being overweight. Despite convincing evidence on these associations, there is an unmet public health need to identify "high-risk" offspring by predicting very early deviations in weight gain patterns as a subclinical stage towards overweight. However, data and methods for individual risk prediction are lacking. We aimed to identify those infants exposed to obesity in pregnancy at ages 3 months, 1 year, and 2 years who likely will follow a higher-than-normal body mass index (BMI) growth trajectory towards manifest overweight by developing an early-risk quantification system.

METHODS

This study uses data from the prospective mother-child cohort study Programming of Enhanced Adiposity Risk in CHildhood-Early Screening (PEACHES) comprising 1671 mothers with pre-conception obesity and without (controls) and their offspring. Exposures were pre- and postnatal risks documented in patient-held maternal and child health records. The main outcome was a "higher-than-normal BMI growth pattern" preceding overweight, defined as BMI z-score >1 SD (i.e., World Health Organization [WHO] cut-off "at risk of overweight") at least twice during consecutive offspring growth periods between age 6 months and 5 years. The independent cohort PErinatal Prevention of Obesity (PEPO) comprising 11,730 mother-child pairs recruited close to school entry (around age 6 years) was available for data validation. Cluster analysis and sequential prediction modelling were performed.

RESULTS

Data of 1557 PEACHES mother-child pairs and the validation cohort were analyzed comprising more than 50,000 offspring BMI measurements. More than 1-in-5 offspring exposed to obesity in pregnancy belonged to an upper BMI z-score cluster as a distinct pattern of BMI development (above the cut-off of 1 SD) from the first months of life onwards resulting in preschool overweight/obesity (age 5 years: odds ratio [OR] 16.13; 95% confidence interval [CI] 9.98-26.05). Contributing early-life factors including excessive weight gain (OR 2.08; 95% CI 1.25-3.45) and smoking (OR 1.94; 95% CI 1.27-2.95) in pregnancy were instrumental in predicting a "higher-than-normal BMI growth pattern" at age 3 months and re-evaluating the risk at ages 1 year and 2 years (area under the receiver operating characteristic [AUROC] 0.69-0.79, sensitivity 70.7-76.0%, specificity 64.7-78.1%). External validation of prediction models demonstrated adequate predictive performances.

CONCLUSIONS

We devised a novel sequential strategy of individual prediction and re-evaluation of a higher-than-normal weight gain in "high-risk" infants well before developing overweight to guide decision-making. The strategy holds promise to elaborate interventions in an early preventive manner for integration in systems of well-child care.

Prospective associations between dietary patterns, screen and outdoor play times at 2 years and age at adiposity rebound: The EDEN mother-child cohort

Although an early adiposity rebound (AR) is an established risk factor for later obesity, little is known regarding its determinants, especially modifiable ones. Using data from the French EDEN mother–child cohort (1903 children born in 2003–2006), we aimed to examine the association between diet and activity-related behaviors at 2 years of age and the timing of the AR. Two-year-old children (n = 1138) with parent-reported data on their foods/drinks intake, TV/DVD watching time, outdoor playtime, and with an estimated (via growth modelling) age at AR were included in the present study. Two dietary patterns, labelled 'Nutrient-dense foods' and 'Processed and fast foods', were identified in a previous study. Multivariable linear and logistic regression models were used to assess the association between dietary patterns and activity-related behaviors and, respectively, the age at AR (continuous) and the likelihood of having a very early AR (before 3.6 years for girls and 3.8 years for boys, i.e., below the 10th percentile of sex-specific distribution). A higher score on the ‘Processed and fast foods’ dietary pattern was associated with a higher likelihood of having a very early AR (OR = 1.23; 95% CI: 1.00 to 1.50). No significant association was observed between the ‘Nutrient-dense foods’ dietary pattern, TV/DVD watching and outdoor playing times and the timing of the AR. This finding emphasizes the importance of reducing nutrient-dense and processed foods from the early years of life, and provides further support for early interventions aimed at helping parents establish healthy eating habits for their growing child from the complementary period.

Infant feeding practices associated with adiposity peak and rebound in the EDEN mother-child cohort

BACKGROUND/OBJECTIVE

High magnitude of adiposity peak and early adiposity rebound are early risk markers of later obesity. Infant diet represents one of the main modifiable determinants of early growth. This study aimed to investigate the association between infant feeding practices and age and magnitude of adiposity peak and rebound.

SUBJECTS/METHODS

Analyses were based on data from the French EDEN mother-child cohort. Data on breastfeeding and complementary feeding were collected at birth and 4, 8, and 12 months. From clinical examinations and measurements collected in the child's health booklet up to 12 years, individual growth curves were modeled, and ages and magnitudes of adiposity peak and rebound were estimated. Associations between infant feeding practices and growth were investigated by multivariable linear regression in children after testing a child-sex interaction.

RESULTS

In the studied population (n = 1225), adiposity peak occurred at a mean of 9.9 ± 2 months and adiposity rebound at 5.5 ± 1.4 years. Associations between infant feeding practices and adiposity peak or rebound were moderated by child sex. For girls, each additional month of breastfeeding was related to a 2-day increase in the age at adiposity peak (p < 0.001), and an 18-day increase in the age at adiposity peak (p = 0.004). Whereas for boys, each additional month for the age at complementary food introduction was associated with a 29-day increase in the age at adiposity rebound (p = 0.02). For boys, long breastfeeding duration was only related to reduced body mass index at adiposity peak.

CONCLUSIONS

Child sex has a moderating effect on the association between infant feeding practices and adiposity peak or rebound. The well-known association between breastfeeding duration and early growth seems stronger in girls than boys. The association found for complementary feeding in boys may give new insights into preventing obesity.

Interrelationships among age at adiposity rebound, BMI during childhood, and BMI after age 14 years in an electronic health record database

OBJECTIVE

This study compared the importance of age at adiposity rebound versus childhood BMI to subsequent BMI levels in a longitudinal analysis.

METHODS

From the electronic health records of 4.35 million children, a total of 12,228 children were selected who were examined at least once each year between ages 2 and 7 years and reexamined after age 14 years. The minimum number of examinations per child was six. Each child's rebound age was estimated using locally weighted regression (lowess), a smoothing technique.

RESULTS

Children who had a rebound age < 3 years were, on average, 7 kg/m2 heavier after age 14 years than were children with a rebound age ≥ 7 years. However, BMI after age 14 years was more strongly associated with BMI at the rebound than with rebound age (r = 0.57 vs. -0.44). Furthermore, a child's BMI at age 3 years provided more information on BMI after age 14 years than did rebound age. In addition, rebound age provided no information on subsequent BMI if a child's BMI at age 6 years was known.

CONCLUSIONS

Although rebound age is related to BMI after age 14 years, a child's BMI at age 3 years provides more information and is easier to obtain.

Adiposity rebound may be a predictive index of body size for adolescents-Based on retrospective cohort data in a Japanese rural area

BACKGROUND

We aimed to examine whether the timing of adiposity rebound (AR) could be a predictive index of body size in Japanese adolescents.

METHODS

The longitudinal individual data of 1438 Japanese children, including 714 boys and 724 girls born between 2001 and 2007, were obtained from child health check-ups conducted at ages 1.5, 2, 3, and 5 years, and then yearly after the age of 6 years. We examined whether the timing of AR could be used to estimate the body size at 14 years of age.

RESULTS

The AR had a normal distribution with a mean occurrence at age 6-7 years. The odds ratio of having obesity at age 14 were 8.32 for boys and 4.81 for girls, whereas boys and girls with later AR at the same age had a relative risk of thinness of 6.27 and 8.14, respectively. The probability that children with an early AR (i.e., <6 years old) would be obese was nearly 40%. Similar to obesity, the probability of thinness at 14 years remained approximately 8% for both sexes.

CONCLUSIONS

The findings suggest that early AR could raise the risk of obesity, and AR could later raise the risk of thinness. However, both probabilities of AR timing as predictors of adolescent weight status may only be about 10%-20%. This study cannot clearly determine whether the results were influenced by other factors after controlling for the timing of AR. Future studies that also consider lifestyle and genetic factors are warranted.

Obesity and Children

Pediatric obesity is a heterogeneous, chronic, relapsing disease associated with metabolic and psychosocial complications. Weight-based victimization, including unrelenting microaggressions, negatively impacts child mental and physical health. Evidence-based guidelines offer individualized, stepwise approaches to obesity treatment. Pediatric nurses positively impact children with obesity by providing affirmation, clinical management, and psychosocial support. Pediatric nurses are respected and positioned to present evidence-based obesity education, correct common obesity myths, sensitively address obesity-related bias and discrimination, and model person-first language and actions. This article shares how nurses in multiple practice areas can make a meaningful impact on the lives of children and adolescents with obesity.

Associations between Inhaled Corticosteroid in the First 6 Years of Life and Obesity Related Traits

Rationale Infants and young children might be particularly susceptible to the potential clinical side effects of inhaled corticosteroids (ICS) on body mass index (BMI), adiposity rebound and body composition, but this has rarely been studied in long-term studies in this age-group. Objective To determine the association between ICS exposure in the first 6 years of life on BMI, adiposity rebound, body composition and blood lipid levels. Methods Children from the two Copenhagen Prospective Studies on Asthma in Childhood mother-child cohorts were included. ICS use was registered prospectively to age 6 and the cumulative dose was calculated. Multiple linear regression models were used for analysis. Measurements and Main Results A total of 932 (84%) of the 1111 children from the COPSAC cohorts had data on BMI, 786 (71%) had DXA scan data at age 6 years, and 815 (73%) had adiposity rebound age calculated. 291 children (31%) received a cumulative ICS dose > 10 weeks of standard treatment before age 6. ICS treatment during 0-6 years of age was associated with an increased BMI z-score; 0.05 SD [95% CI: 0.005 to 0.09] per one-year standard treatment, p=0.03, an earlier age at adiposity rebound; -0.18 year [95% CI: -0.28 to -0.08], p=0.0006, and a 2 % increased geometric mean android fat percentage, p=0.05. ICS exposure and DXA scan data were not associated. Conclusions ICS use in early childhood was associated with increased BMI z-score at age six, an earlier adiposity rebound and a trend of association with increased android body fat percentage.

Adiposity rebound and cardiometabolic health in childhood: results from the Generation XXI birth cohort

BACKGROUND

We aimed to evaluate the association of adiposity rebound (AR) timing on cardiometabolic health in childhood.

METHODS

Participants were part of the Generation XXI birth cohort, enrolled in 2005/2006 in Porto. All measurements of the child's weight and height performed by health professionals as part of routine healthcare were collected. Individual body mass index (BMI) curves were fitted for 3372 children, using mixed-effects models with smooth spline functions for age and random effects. The AR was categorized into very early (<42 months), early (42-59 months), normal (60-83 months) and late (≥84 months). At age 10 years, cardiometabolic traits were assessed and age- and sex-specific z-scores were generated. Adjusted regression coefficients and 95% confidence intervals [β (95% CI)] were computed.

RESULTS

The mean age at AR was 61.9 months (standard deviations 15.7). Compared with children with normal AR, children with very early or early AR had higher z-scores for BMI [β = 0.40 (95% CI: 0.28; 0.53); β = 0.21 (95% CI: 0.12; 0.30)], waist circumference [β = 0.33 (95% CI: 0.23; 0.43); β = 0.18 (95% CI: 0.10; 0.25)], waist-height ratio [β = 0.34 (95% CI: 0.24; 0.44); β = 0.14 (95% CI: 0.07; 0.22)], fat mass index [β = 0.24 (95% CI: 0.15; 0.33); β = 0.14 (95% CI: 0.08; 0.21)], fat-free mass index [β = 0.25 (95% CI: 0.14; 0.35); β = 0.11 (95% CI: 0.03; 0.19)], systolic blood pressure [β = 0.10 (95% CI: 0.01; 0.20); β = 0.08 (95% CI: 0.01; 0.15)], insulin [β = 0.16 (95% CI: 0.04; 0.29); β = 0.10 (95% CI: 0.01; 0.19)], HOMA-IR [β = 0.17 (95% CI: 0.04; 0.29); β = 0.10 (95% CI: 0.03; 0.19)] and C-reactive protein [β = 0.14 (95% CI: 0.02; 0.26); β = 0.10 (95% CI: 0.01; 0.19)]. Children with very early AR also had worse levels of diastolic blood pressure [β = 0.09 (95% CI: 0.02; 0.16)], triglycerides [β = 0.21 (95% CI: 0.08; 0.34)] and high-density lipoprotein cholesterol [β=-0.18 (95% CI: -0.31; -0.04)]. When analysed continuously, each additional month of age at the AR was associated with healthier cardiometabolic traits.

CONCLUSION

The earlier the AR, the worse the cardiometabolic health in late childhood, which was consistently shown across a wide range of outcomes and in the categorical and continuous approach.

The Relation of Adiposity Rebound to Subsequent BMI in a Large Electronic Health Record Database

Objective: The beginning of postinfancy increase in BMI has been termed the adiposity rebound, and an early rebound increases the risk for obesity in adolescence and adulthood. We examined whether the relation of the age at BMI rebound (age_rebound) to subsequent BMI is independent of childhood BMI. Design: From the electronic health records of 2.8 million children, we selected 17,077 children examined at least once each year between ages 2 and <8 years, and who were reexamined between age 10 and <16 years. The mean age at the last visit was 12 years (SD = 1). We identified age_rebound for each child using lowess, a smoothing technique. Results: Children who had an age_rebound <3 years were, on average, 6.8 kg/m² heavier after age 10 years than were children with an age_rebound >7 years. However, BMI after age 10 years was more strongly associated with BMI at the rebound (BMI_rebound) than with age_rebound (r = 0.63 vs. -0.49). Although the relation of age_rebound to BMI at the last visit was mostly independent of the BMI_rebound, adjustment for age-5 BMI reduced the association's magnitude by about 55%. Conclusions: Both age_rebound and the BMI_rebound are independently related to BMI and obesity after age 10 years. However, a child's BMI_rebound and at ages 5 and 7 years accounts for more of the variability in BMI levels after age 10 years than does age_rebound.

Association between perinatal factors, genetic susceptibility to obesity and age at adiposity rebound in children of the EDEN mother-child cohort

BACKGROUND

Early adiposity rebound (AR) has been associated with increased risk of overweight or obesity in adulthood. However, little is known about early predictors of age at AR. We aimed to study the role of perinatal factors and genetic susceptibility to obesity in the kinetics of AR.

METHODS

Body mass index (BMI) curves were modelled by using mixed-effects cubic models, and age at AR was estimated for 1415 children of the EDEN mother-child cohort study. A combined obesity risk-allele score was calculated from genotypes for 27 variants identified by genome-wide association studies of adult BMI. Perinatal factors of interest were maternal age at delivery, parental education, parental BMI, gestational weight gain, maternal smoking during pregnancy, and newborn characteristics (sex, prematurity, and birth weight). We used a hierarchical level approach with multivariable linear regression model to investigate the association between these factors, obesity risk-allele score, and age at AR.

RESULTS

A higher genetic susceptibility to obesity score was associated with an earlier age at AR. At the most distal level of the hierarchical model, maternal and paternal educational levels were positively associated with age at AR. Children born to parents with higher BMI were more likely to exhibit earlier age at AR. In addition, higher gestational weight gain was related to earlier age at AR. For children born small for gestational age, the average age at AR was 88 [±39] days lower than for children born appropriate for gestational age and 91 [±56] days lower than for children born large for gestational age.

CONCLUSION

The timing of AR seems to be an early childhood manifestation of the genetic susceptibility to adult obesity. We further identified low birth weight and gestational weight gain as novel predictors of early AR, highlighting the role of the intrauterine environment in the kinetics of adiposity.

Childhood obesity: rapid weight gain in early childhood and subsequent cardiometabolic risk

Dynamic changes in body weight have long been recognized as important indicators of risk for human health. Many population-based observational studies have shown that rapid weight gain during infancy, including a catch-up growth phenomenon or adiposity rebound in early childhood, predisposes a person to the development of obesity, type 2 diabetes, and cardiovascular diseases later in life. However, a consensus has not been established regarding which period of weight gain contributes to future risks. This review evaluates recent evidence on the relationship between early rapid growth and future obesity and cardiometabolic risk, with a focus on the differential significance of rapid weight gain in infancy and early childhood. Although there is a need for attention to childhood growth during early infancy before 1 yr of age as it may be related to future obesity, emerging evidence strongly suggests that toddlers showing an increase in body mass index (BMI) before 3 yr of age, a period normally characterized by decreased BMI, are prone to developing later cardiometabolic risk.

Comparison between type A and type B early adiposity rebound in predicting overweight and obesity in children: a longitudinal study

Early adiposity rebound (EAR) predicts paediatric overweight/obesity, but current approaches do not consider both the starting point of EAR and the BMI trajectory. We compared the clinical characteristics at birth, age 3-5 and 6-8 years of children, according to the EAR and to its type (type A/type B-EAR). We assessed the children's odds of being classified as overweight/obese at age 6-8 years, according to the type of EAR as defined at age 3-5 years. As part of this two-wave observational study, 1055 children were recruited and examined at age 3-5 years. Antenatal and postnatal information was collected through interviews with parents, and weight and height from the health records. Type A and type B-EAR were defined in wave 1 according to the BMI nadir and the variation of BMI z-score between the starting point of the adiposity rebound and the last point on the curve. At 6-8 years (wave 2), 867 children were followed up; 426 (40·4 %) children demonstrated EAR. Among them, 172 had type A-EAR, higher rates of parental obesity (P < 0·05) and greater birth weight compared with other children (P < 0·001). Odds for overweight/obesity at 6-8 years, when adjusting for antenatal and postnatal factors, was 21·35 (95 % CI 10·94, 41·66) in type A-EAR children and not significant in type B-EAR children (OR 1·76; 95 % CI 0·84, 3·68) compared with children without EAR. Classification of EAR into two subtypes provides physicians with a reliable approach to identify children at risk for overweight/obesity before the age of 5 years.

Late Adiposity Rebound and the Probability of Developing and Reversing Childhood Obesity

OBJECTIVE

To evaluate the associations between late adiposity rebound (at or after 7.0 years of age) and the probability of developing and reversing obesity during elementary school years.

STUDY DESIGN

Using nationally representative cohorts from Early Childhood Longitudinal Studies, Kindergarten Class of 1998-1999 and 2010-2011, weighted extended Cox hazard models were used to assess the probability of developing and reversing obesity (cut-offs for extended models were 6 and 12 months after kindergarten entry, respectively). Measurements used in the study were collected 6 times between kindergarten and fifth grade (Early Childhood Longitudinal Studies, Kindergarten Class of 1998-1999) and 8 times between kindergarten through fourth grade (Early Childhood Longitudinal Studies, Kindergarten Class of 2010-2011).

RESULTS

Among children with obesity at kindergarten entry, within 6 months, the risk of developing obesity was 73% and 76% lower for boys with late adiposity rebound than their classmates without late adiposity rebound (hazard ratio 0.27 and 0.24). Six months after entering kindergarten, similar association was observed for both boys and girls. Among children without obesity at kindergarten entry, within 12 months, the probability of reversing obesity was 52% and 54% higher for boys with late adiposity rebound than their peers without late adiposity rebound (hazard ratio 1.52 and 1.54). Twelve months after entering kindergarten, the probability of reversing obesity among both sexes with late adiposity rebound was 6-8 times that among children without late adiposity rebound.

CONCLUSIONS

Late adiposity rebound was significantly associated with a decreased risk of developing obesity and an increased probability of reversing obesity among kindergarteners.

A hypothesis linking the energy demand of the brain to obesity risk

We propose that variation in brain energy expenditure during childhood is an unexplored but important influence on obesity risk. This hypothesis is supported by evidence that the energy required by the developing brain decreases in later childhood as the rate of body weight gain is increasing. The hypothesis is further supported by findings of genetic and brain imaging research indicating a trade-off between the body mass index (BMI) and the volume of cortical and subcortical structures, and inverse associations between BMI and energetically costly executive cognitive functions. Efforts to quantify variability in brain energy use across children could inspire new educational strategies that increase brain energy demands and thereby reduce obesity risk.

The causes of obesity are complex and multifactorial. We propose that one unconsidered but likely important factor is the energetic demand of brain development, which could constrain energy available for body growth and other functions, including fat deposition. Humans are leanest during early childhood and regain body fat in later childhood. Children reaching this adiposity rebound (AR) early are at risk for adult obesity. In aggregate data, the developing brain consumes a lifetime peak of 66% of resting energy expenditure in the years preceding the AR, and brain energy use is inversely related to body weight gain from infancy until puberty. Building on this finding, we hypothesize that individual variation in childhood brain energy expenditure will help explain variation in the timing of the AR and subsequent obesity risk. The idea that brain energetics constrain fat deposition is consistent with evidence that genes that elevate BMI are expressed in the brain and mediate a trade-off between the size of brain structures and BMI. Variability in energy expended on brain development and function could also help explain widely documented inverse relationships between the BMI and cognitive abilities. We estimate that variability in brain energetics could explain the weight differential separating children at the 50th and 70th BMI-for-age centiles immediately before the AR. Our model proposes a role for brain energetics as a driver of variation within a population’s BMI distribution and suggests that educational interventions that boost global brain energy use during childhood could help reduce the burden of obesity.

Child temperament predicts the adiposity rebound. A 9-year prospective sibling control study

METHODS

We repeatedly examined 25889 siblings within the Norwegian Mother and Child Cohort Study, following them from the mothers' pregnancy through child age 8 years. Information on the children's height and weight was collected by means of health registries and maternal reports. Information on the siblings' temperament was collected by questionnaires completed when they were 1.5, 3, and 5 years old. We examined the associations of temperament at different child ages with the timing of the adiposity rebound among siblings and controls by means of growth curve and multilevel analyses.

RESULTS

Within siblings, high scores on the approach trait of sociability predicted an earlier adiposity rebound and high scores on the avoidance trait of shyness predicted a later adiposity rebound with timing differences ranging between 6 and 16 weeks. Surprisingly, negative emotionality did not predict the adiposity rebound. The associations between temperament and the adiposity rebound increased with increasing child age. The results within controls-comparing siblings with the population, broadly paralleled those within siblings.

CONCLUSIONS

The findings encourage the notion that child temperament functions as an early marker for the adiposity rebound. Future studies may advance our knowledge by including measures of child personality along the taxonomy of the adult Five Personality Factors.