Body mass index (BMI) trajectories in infancy differ by population ancestry and may presage disparities in early childhood obesity

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.

Overview of BMI and Other Ways of Measuring and Screening for Obesity in Pediatric Patients

Despite a long history of advances in measuring body size and composition, body mass index (BMI) has remained the most commonly used clinical measure. We explore the advantages and disadvantages of using BMI and other measures to estimate adipose tissue, recognizing that no measure of body size or adiposity has fulfilled the goal of differentiating health from disease. BMI and waist circumference remain widely-used clinical screening measures for appropriate risk stratification as it relates to obesity.

Modelling individual infancy growth trajectories to predict excessive gain in BMI z-score: a comparison of growth measures in the ABCD and GECKO Drenthe cohorts

BACKGROUND

Excessive weight gain during childhood is a strong predictor for adult overweight, but it remains unknown which growth measures in infancy (0-2 years of age), besides predictors known at birth, are the strongest predictors for excessive weight gain between 2 and 5-7 years of age.

METHODS

The Amsterdam Born Children and their Development (ABCD) study formed the derivation cohort, and the Groningen Expert Center for Kids with Obesity (GECKO) Drenthe study formed the validation cohort. Change (Δ) in body mass index (BMI) z-score between 2 and 5-7 years was the outcome of interest. The growth measures considered were weight, weight-for-length (WfL), and body mass index (BMI). Formats considered for each growth measure were values at 1, 6, 12, and 24 months, at the BMI peak, the change between aforementioned ages, and prepeak velocity. 10 model structures combining different variable formats and including predictors at birth were derived for each growth measure, resulting in 30 linear regression models. A Parsimonious Model considering all growth measures and a Birth Model considering none were also derived.

RESULTS

The derivation cohort consisted of 3139 infants of which 373 (11.9%) had excessive gain in BMI z-score (> 0.67). The validation cohort contained 2201 infants of which 592 (26.9%) had excessive gain. Across the 3 growth measures, 5 model structures which included measures related to the BMI peak and prepeak velocity (derivation cohort area under the curve [AUC] range = 0.765-0.855) achieved more accurate estimates than 3 model structures which included growth measure change over time (0.706-0.795). All model structures which used BMI were superior to those using weight or WfL. The AUC across all models was on average 0.126 lower in the validation cohort. The Parsimonious Model's AUCs in the derivation and validation cohorts were 0.856 and 0.766, respectively, compared to 0.690 and 0.491, respectively, for the Birth Model. The respective false positive rates were 28.2% and 20.1% for the Parsimonious Model and 70.0% and 74.6% for the Birth Model.

CONCLUSION

Models' performances varied significantly across model structures and growth measures. Developing the optimal model requires extensive testing of the many possibilities.

Prospective Association between Total and Trimester-Specific Gestational Weight Gain Rate and Physical Growth Status in Children within 24 Months after Birth

In this study, our aim was to investigate the potential correlation between the mother's total gestational weight gain (GWG) rate and the trimester-specific GWG rate (GWGR) with the physical development status of the child within 24 months of age. We utilized linear regression models and linear mixed effects models to explore both time point and longitudinal relationships between GWGR and children's anthropometric outcome z-scores at 0, 1, 2, 4, 6, 9, 12, 18, and 24 months. To examine the critical exposure windows, we employed multiple informant models. We also conducted a stratified analysis considering pre-pregnancy BMI and the gender of the children. Our findings revealed notable positive associations between total GWGR and z-scores for body mass index for age (BMIZ), head circumference for age (HCZ), weight for age (WAZ), length for age (LAZ), and weight for length (WHZ) across different trimesters of pregnancy (pint < 0.05). The GWGR during the first two trimesters mainly influenced the relationship between total GWGR and BMIZ, WAZ, and LAZ, while the GWGR during the first trimester had a significant impact on the correlation with HCZ (0.206, 95% CI 0.090 to 0.322). Notably, the associations of GWGR and children's BMIZ were pronounced in male children and pre-pregnancy normal-weight women. In conclusion, our study findings indicated that a higher GWGR during each trimester was associated with greater physical growth during the first 24 months of life, especially GWGR in the first and second trimesters.

Endocrine Health and Health Care Disparities in the Pediatric and Sexual and Gender Minority Populations: An Endocrine Society Scientific Statement

Endocrine care of pediatric and adult patients continues to be plagued by health and health care disparities that are perpetuated by the basic structures of our health systems and research modalities, as well as policies that impact access to care and social determinants of health. This scientific statement expands the Society's 2012 statement by focusing on endocrine disease disparities in the pediatric population and sexual and gender minority populations. These include pediatric and adult lesbian, gay, bisexual, transgender, queer, intersex, and asexual (LGBTQIA) persons. The writing group focused on highly prevalent conditions-growth disorders, puberty, metabolic bone disease, type 1 (T1D) and type 2 (T2D) diabetes mellitus, prediabetes, and obesity. Several important findings emerged. Compared with females and non-White children, non-Hispanic White males are more likely to come to medical attention for short stature. Racially and ethnically diverse populations and males are underrepresented in studies of pubertal development and attainment of peak bone mass, with current norms based on European populations. Like adults, racial and ethnic minority youth suffer a higher burden of disease from obesity, T1D and T2D, and have less access to diabetes treatment technologies and bariatric surgery. LGBTQIA youth and adults also face discrimination and multiple barriers to endocrine care due to pathologizing sexual orientation and gender identity, lack of culturally competent care providers, and policies. Multilevel interventions to address these disparities are required. Inclusion of racial, ethnic, and LGBTQIA populations in longitudinal life course studies is needed to assess growth, puberty, and attainment of peak bone mass. Growth and development charts may need to be adapted to non-European populations. In addition, extension of these studies will be required to understand the clinical and physiologic consequences of interventions to address abnormal development in these populations. Health policies should be recrafted to remove barriers in care for children with obesity and/or diabetes and for LGBTQIA children and adults to facilitate comprehensive access to care, therapeutics, and technological advances. Public health interventions encompassing collection of accurate demographic and social needs data, including the intersection of social determinants of health with health outcomes, and enactment of population health level interventions will be essential tools.

Genetically-predicted placental gene expression is associated with birthweight and adult body mass index

The placenta is critical to human growth and development and has been implicated in health outcomes. Understanding the mechanisms through which the placenta influences perinatal and later-life outcomes requires further investigation. We evaluated the relationships between birthweight and adult body mass index (BMI) and genetically-predicted gene expression in human placenta. Birthweight genome-wide association summary statistics were obtained from the Early Growth Genetics Consortium (N = 298,142). Adult BMI summary statistics were obtained from the GIANT consortium (N = 681,275). We used S-PrediXcan to evaluate associations between the outcomes and predicted gene expression in placental tissue and, to identify genes where placental expression was exclusively associated with the outcomes, compared to 48 other tissues (GTEx v7). We identified 24 genes where predicted placental expression was significantly associated with birthweight, 15 of which were not associated with birthweight in any other tissue. One of these genes has been previously linked to birthweight. Analyses identified 182 genes where placental expression was associated with adult BMI, 110 were not associated with BMI in any other tissue. Eleven genes that had placental gene expression levels exclusively associated with BMI have been previously associated with BMI. Expression of a single gene, PAX4, was associated with both outcomes exclusively in the placenta. Inter-individual variation of gene expression in placental tissue may contribute to observed variation in birthweight and adult BMI, supporting developmental origins hypothesis.

Prevalence of early childhood obesity in Ireland: Differences over time, between sexes and across child growth criteria

BACKGROUND

Various child growth criteria exist for monitoring overweight and obesity prevalence in young children.

OBJECTIVES

To estimate early overweight and obesity prevalence in Ireland and compare the differences in prevalence across ages, growth criteria and sexes.

METHODS

Longitudinal body mass index data from the nationally representative Growing Up in Ireland infant cohort (n = 11 134) were categorized ('under-/normal weight', 'risk of overweight', 'overweight', 'obesity') using the sex- and age-specific International Obesity Task Force growth reference, World Health Organization growth standard and World Health Organization growth reference criteria. Differences in prevalences between criteria and sexes, and changes in each weight category and criterion across ages (9 months, 3 years, 5 years), were investigated.

RESULTS

Across criteria, 11%-40% of children had overweight or obesity at 9 months, 14%-46% at 3 years and 8%-32% at 5 years of age. Prevalence estimates were highest using the World Health Organization growth reference, followed by International Obesity Task Force estimates. Within each criterion, prevalence decreased significantly over time (p < 0.05). However, when combining both World Health Organization criteria, as recommended for population studies, prevalence increased, due to differences in definitions between them. Significantly more boys than girls had overweight/obesity using either World Health Organization criterion, which was reversed using the International Obesity Task Force growth reference.

CONCLUSIONS

To increase transparency and comparability, studies of childhood obesity need to consider differences in prevalence estimates across growth criteria. Effective prevention, intervention and policy-making are needed to control Ireland's high overweight and obesity prevalence.

Early childhood body mass index trajectory and overweight/obesity risk differed by maternal weight status

OBJECTIVES

To evaluate the associations of maternal prepregnancy body mass index (pp-BMI) and gestational weight gain (GWG) with the childhood BMI z-score (BMI-z) trajectories from birth to 2 years old and the risk of overweight/obesity (OWO) at 2 years of age.

SUBJECTS/METHODS

Mother-child dyads (23,617) were involved in the analysis. They were followed up from early pregnancy to 2 years postpartum with their healthcare data recorded in the Wuhan Maternal and Child Health Management Information System (WMCHMIS). The OWO in children was defined as BMI-z > 1. Linear mixed models (LMM) and unconditional logistic regression were used to evaluate the independent and joint associations of pp-BMI and GWG with the BMI-z trajectory of children per their anthropometric measurements at 0, 1, 3, 6, 9, 12, 18, and 24 months old and the risk of OWO at 2 years of age.

RESULTS

Maternal overweight/obesity and excessive GWG independently and jointly increased the risks of their offspring falling into high BMI-z trajectories of birth to 2 years (p < 0.001). In addition, the children whose mothers were overweight/obese before pregnancy and gained excessive weight during pregnancy independently and jointly increased the OWO risk in children at age 2, with adjusted odds ratios (adjOR) of 1.36 (95% CI, 1.22-1.53), 1.28 (95% CI, 1.18-1.39), and 1.76 (95% CI: 1.52-2.03), respectively.

CONCLUSIONS

Maternal prepregnancy overweight/obesity and excessive GWG can independently and jointly increase the risks of their children falling into high BMI-z trajectories from birth to 2 years of age and becoming overweight/obese at age 2. Maternal overweight/obesity and excessive gestational weight should be the prime targets for early obese prevention efforts.

Association between children and adolescents’ body composition with family income

ABSTRACT Objective To evaluate the association between children and adolescents’ body composition with family income. Methods Cross-sectional study, participants between 5 and 19 years were included. A standardized questionnaire assessed socioeconomic variables. The outcome variables were z-score of Body Mass Index and bioimpedance parameters (skeletal muscle mass, fat-free mass, and fat percentage) and predictor variables (age, sex, race, place of residence, father’s education, birth weight and breastfeeding) were analyzed using the quantile regression model and data from the 50th percentile are presented. The tests were bidirectional and the differences were considered significant with p<0.05. Results Among the 529 participants included, 284 (53.6%) were female and the mean age was 11.41±3.9 years. The Body Mass Index z-score was the only outcome that did not show differences between sexes (p=0.158). In the crude model, lower family income was associated with lower skeletal muscle mass (Difference=-7.70; 95% CI -9.32 to -5.89), p<0.001), lower fat-free mass (Difference= -13.40; 95% CI -16.40 to -10.39, p<0.001) and the lowest percentage of fat was associated with lower family income (Difference= -5.01, 95% CI -9.91 to -0.11, p=0.027). The z-score of BMI was not associated with family income. Conclusion Family income is directly associated with lower fat-free mass, fat percentage, and skeletal muscle mass in children and adolescents.

Perinatal determinants of growth trajectories in children born preterm

BACKGROUND

A growing amount of evidence indicates in utero and early life growth has profound, long-term consequences for an individual's health throughout the life course; however, there is limited data in preterm infants, a vulnerable population at risk for growth abnormalities.

OBJECTIVE

To address the gap in knowledge concerning early growth and its determinants in preterm infants.

METHODS

A retrospective cohort study was performed using a population of preterm (< 37 weeks gestation) infants obtained from an electronic medical record database. Weight z-scores were acquired from discharge until roughly two years corrected age. Linear mixed effects modeling, with random slopes and intercepts, was employed to estimate growth trajectories.

RESULTS

Thirteen variables, including maternal race, hypertension during pregnancy, preeclampsia, first trimester body mass index, multiple status, gestational age, birth weight, birth length, head circumference, year of birth, length of birth hospitalization stay, total parenteral nutrition, and dextrose treatment, were significantly associated with growth rates of preterm infants in univariate analyses. A small percentage (1.32% - 2.07%) of the variation in the growth of preterm infants can be explained in a joint model of these perinatal factors. In extremely preterm infants, additional variation in growth trajectories can be explained by conditions whose risk differs by degree of prematurity. Specifically, infants with periventricular leukomalacia or retinopathy of prematurity experienced decelerated rates of growth compared to infants without such conditions.

CONCLUSIONS

Factors found to influence growth over time in children born at term also affect growth of preterm infants. The strength of association and the magnitude of the effect varied by gestational age, revealing that significant heterogeneity in growth and its determinants exists within the preterm population.

Metabolite Profiles of the Relationship between Body Mass Index (BMI) Milestones and Metabolic Risk during Early Adolescence

Early growth is associated with future metabolic risk; however, little is known of the underlying biological pathways. In this prospective study of 249 boys and 227 girls, we sought to identify sex-specific metabolite profiles that mark the relationship between age and magnitude of the infancy body mass index (BMI) peak, and the childhood BMI rebound with a metabolic syndrome z-score (MetS z-score) during early adolescence (median age 12.8 years). Thirteen consensus metabolite networks were generated between male and female adolescents using weighted correlation network analysis. In girls, none of the networks were related to BMI milestones after false discovery rate (FDR) correction at 5%. In boys, age and/or magnitude of BMI at rebound were associated with three metabolite eigenvector (ME) networks comprising androgen hormones (ME7), lysophospholipids (ME8), and diacylglycerols (ME11) after FDR correction. These networks were also associated with MetS z-score in boys after accounting for age and race/ethnicity: ME7 (1.43 [95% CI: 0.52, 2.34] units higher MetS z-score per 1 unit of ME7), ME8 (-1.01 [95% CI: -1.96, -0.07]), and ME11 (2.88 [95% CI: 2.06, 3.70]). These findings suggest that alterations in sex steroid hormone and lipid metabolism are involved in the relationship of early growth with future metabolic risk in males.

Association of maternal prepregnancy weight and early childhood weight with obesity in adolescence: A population-based longitudinal cohort study in Japan

BACKGROUND

The impact of birth weight and obesity in early childhood on obesity in adolescence remains unclear.

OBJECTIVES

To examine the association of overweight/obesity at age 15 years with birth weight, overweight/obesity in early childhood and overweight/obesity in mothers.

METHODS

This population-based retrospective cohort study used early childhood and school age health check-up data of 1581 children in Japan, followed-up until age 15 years. Generalized estimation equation analyses were used to investigate the association of overweight/obesity at age 15 years with low/high birth weight, overweight/obesity in 3 years of age and overweight/obesity in mothers. The cutoff points for all variables were defined by international criteria.

RESULTS

Of 1581 mother-child pairs, 130 (8.2%) children had low birth weight, while 93 (5.9%) and 167 (10.6%) were overweight/obese at age 3 and 15 years, respectively. Overweight/obesity at age 3 years and overweight/obesity in mothers were associated with overweight/obesity at age 15 years (adjusted odds ratio [aOR], 4.26; 95% confidence interval [CI]: 2.51-7.25 and (aOR, 2.46; 95% CI: 1.41-4.30). No association between low birth weight and overweight/obesity at age 15 years was observed.

CONCLUSIONS

Overweight/obesity in mothers and overweight/obesity at 3 years of age, but not birth weight, were associated with overweight/obesity at age 15 years.

[Heritability of obesity in children aged 30-36 months and an analysis of single nucleotide polymorphisms at four loci in Xi'an, China]

OBJECTIVE

To study the heritability of obesity in children aged 30-36 months in Xi'an, China, as well as the role of four single nucleotide polymorphisms (SNPs) associated with body mass index in the susceptibility to obesity in children.

METHODS

Random sampling was performed to select 1 637 children, aged 30-36 months, from four communities of Xi'an from March 2017 to December 2018. Physical assessment was performed for these children, and a questionnaire survey was conducted for parents. Then the Falconer regression method was used to calculate the heritability of childhood obesity. Venous blood samples were collected from 297 children who underwent biochemical examinations, among whom there were 140 children with obesity/overweight (obesity/overweight group) and 157 with normal body weight (normal body weight group). The MassARRAY RS1000 typing technique was used to detect CDKAL1 gene rs2206734, KLF9 gene rs11142387, PCSK1 gene rs261967, and GP2 gene rs12597579. The distribution of alleles and genotypes was compared between the obesity/overweight and normal body weight groups. An unconditional logistic regression model was used to investigate the benefits of dominant and recessive genetic models.

RESULTS

For the 1 637 children, the heritability of obesity from the parents was 83%±8%, and the heritability from mother was slightly higher than that from father (86%±11% vs 78%±12%). There were significant differences in the distribution of rs2206734 alleles and genotypes and rs261967 genotypes between the obesity/overweight and normal body weight groups (P<0.0125). The children carrying T allele at rs2206734 had a significantly higher risk of obesity than those carrying CC (OR=0.24, P<0.0125), and the children carrying GG at rs261967 had a significantly higher risk of obesity than those carrying A allele (OR=4.11, P<0.0125).

CONCLUSIONS

Genetic factors play an important role in the pathogenesis of obesity in children, and the SNPs of CDKAL1 rs2206734 and PCSK1 rs261967 are associated with the susceptibility to obesity in children aged 30-36 months in Xi'an.

[Heritability of obesity in children aged 30-36 months and an analysis of single nucleotide polymorphisms at four loci in Xi'an, China]

OBJECTIVE

To study the heritability of obesity in children aged 30-36 months in Xi'an, China, as well as the role of four single nucleotide polymorphisms (SNPs) associated with body mass index in the susceptibility to obesity in children.

METHODS

Random sampling was performed to select 1 637 children, aged 30-36 months, from four communities of Xi'an from March 2017 to December 2018. Physical assessment was performed for these children, and a questionnaire survey was conducted for parents. Then the Falconer regression method was used to calculate the heritability of childhood obesity. Venous blood samples were collected from 297 children who underwent biochemical examinations, among whom there were 140 children with obesity/overweight (obesity/overweight group) and 157 with normal body weight (normal body weight group). The MassARRAY RS1000 typing technique was used to detect CDKAL1 gene rs2206734, KLF9 gene rs11142387, PCSK1 gene rs261967, and GP2 gene rs12597579. The distribution of alleles and genotypes was compared between the obesity/overweight and normal body weight groups. An unconditional logistic regression model was used to investigate the benefits of dominant and recessive genetic models.

RESULTS

For the 1 637 children, the heritability of obesity from the parents was 83%±8%, and the heritability from mother was slightly higher than that from father (86%±11% vs 78%±12%). There were significant differences in the distribution of rs2206734 alleles and genotypes and rs261967 genotypes between the obesity/overweight and normal body weight groups (P<0.0125). The children carrying T allele at rs2206734 had a significantly higher risk of obesity than those carrying CC (OR=0.24, P<0.0125), and the children carrying GG at rs261967 had a significantly higher risk of obesity than those carrying A allele (OR=4.11, P<0.0125).

CONCLUSIONS

Genetic factors play an important role in the pathogenesis of obesity in children, and the SNPs of CDKAL1 rs2206734 and PCSK1 rs261967 are associated with the susceptibility to obesity in children aged 30-36 months in Xi'an.

Association of Ancestral Genetic Admixture and Excess Weight at Twelve Months of Age

Background/Objective: Understanding the influence of genetically determined ancestry may give insight into the disparities of obesity seen in different ethnic groups beginning at a very early age. Aim: To investigate the relationship between children's ancestral genetic proportions and excess weight at 12 months of age. Methods: Eight hundred twenty-one 12-month-old children were included in this cross-sectional study. Their genetic admixture was estimated using the ancestry and kinship tool kit by projecting the samples into the 1000 Genomes principal component database. Weight-for-length percentile (WFLP) at 12 months of age was categorized as <95th percentile or ≥95th percentile. Multiple logistic regression analysis was performed to calculate odds ratios (ORs) with 95% confidence intervals (CIs) for the association of admixture proportions, including European (EUR), admixed American (AMR), African (AFR), South Asian (SAS), and East Asian (EAS) populations, with WFLP categories, adjusting for maternal education, birth weight, frequency of breastfeeding, and juice consumption. Results: Eight hundred twenty-one children were included; WFLP <95th percentile = 671 (81.7%) and WFLP ≥95th percentile = 150 (18.3%). Crude ORs showed that the EUR admixture was protective [OR 0.45 (95% CI 0.27-0.74)], whereas AMR [OR 3.85 (95% CI 1.92-7.70)] and AFR [OR 5.70 (95% CI 2.19-14.85)] admixtures were positively associated with excess weight. After adjusting for confounding variables, only the AFR admixture was associated with WFLP ≥95th percentile [OR 7.38 (95% CI 2.31-23.59)]. Conclusions: AFRs remain associated with early excess weight after accounting for confounding variables, suggesting that this ancestral genetic background may contribute to the differences seen in early childhood obesity.

Nutritional Status Trends in Brazilian Preschoolers: A Cohort Study

Background: Determining trends in the nutritional status of children may guide care prevention beyond this age in an effort to reduce the prevalence and incidence of overweight and/or obese children. The objective of this study is to evaluate the evolution of the nutritional status of preschool children in two moments, with an interval of 2 years. Methods: This is a cohort study of a random probabilistic sample of preschool children attending public schools within an urban area of high human development index city, in the hinterland of São Paulo state. In 2016, we reassessed the nutritional status of 351 preschoolers evaluated in 2014, comparing the prevalence of overweight according to BMI >1 z-score. Results: The prevalence of overweight was 31.05% (2014) and 31.06% (2016) and mean BMI z-scores were 0.58 and 0.57, respectively. The nutritional status classification of the preschool children showed almost no agreement between the two time points (κ = 0.053). Nevertheless, children with overweight in 2014 had a relative risk of 1.96 of being overweight or obese in 2016 (p = 0.0473). Conclusions: Prevalence of overweight among preschoolers was the same at 2 and 5 years of age, with no tendency to grow. Despite this, 2-year-old preschoolers with overweight present a twofold higher relative risk for excessive weight at 5 years of age. These changes of nutritional status at preschool age evince the great flexibility of their nutritional condition during this period of life.

GWAS on longitudinal growth traits reveals different genetic factors influencing infant, child, and adult BMI

Early childhood growth patterns are associated with adult health, yet the genetic factors and the developmental stages involved are not fully understood. Here, we combine genome-wide association studies with modeling of longitudinal growth traits to study the genetics of infant and child growth, followed by functional, pathway, genetic correlation, risk score, and colocalization analyses to determine how developmental timings, molecular pathways, and genetic determinants of these traits overlap with those of adult health. We found a robust overlap between the genetics of child and adult body mass index (BMI), with variants associated with adult BMI acting as early as 4 to 6 years old. However, we demonstrated a completely distinct genetic makeup for peak BMI during infancy, influenced by variation at the LEPR/LEPROT locus. These findings suggest that different genetic factors control infant and child BMI. In light of the obesity epidemic, these findings are important to inform the timing and targets of prevention strategies.

Risk Factors for Childhood Overweight and Obesity in Ukraine and Germany

OBJECTIVE

The prevalence of overweight and obesity in childhood and adolescence are rapidly increasing and influenced by genetic, familial, environmental, socioeconomic and cultural factors. The aim of the study was to compare risk factors for childhood obesity in Ukraine (UA) and Germany (DE) using comparable investigative tools.

METHODS

Two groups of children, aged 8 to 18 years, from DE (93 children) and UA (95 children) were divided into overweight and obese groups. Anthropometric data and detailed medical history were collected.

RESULTS

Risk factors in pregnancy (prematurity, weight gain >20 kg, early contractions) were equally frequent in both groups. Positive correlations of body mass index (BMI)-standard deviation score (SDS) between children and mothers were noted. The proportion of family members with diabetes mellitus was lower in the UA group. Obesity was more frequent at one year of age in DE children. The DE group also became overweight at an earlier age and remained overweight over a longer period of time compared to UA. The mean BMI-SDS of obese children was lower in the UA group. In both groups waist circumference to height ratio was >0.5, indicating presence of a cardiometabolic risk factor. About half of the patients in both groups had blood pressure values exceeding the 95^th percentile.

CONCLUSION

Similar risk factors for obesity were observed among two groups of children in UA and DE. Differences were observed regarding the prevalence of specific risk factors for childhood obesity. Population-specific distribution of risk factors needs to be considered in order to optimize prevention and treatment strategies.

[Influence of pre-pregnancy parental body mass index, maternal weight gain during pregnancy, and their interaction on neonatal birth weight]

OBJECTIVE

To investigate the influence of pre-pregnancy parental body mass index (BMI), maternal weight gain during pregnancy, and their interaction on neonatal birth weight.

METHODS

A total of 1 127 pregnant women who underwent regular prenatal examinations and full-term singleton delivery in the First Hospital of Xi'an Jiaotong University from January 2017 to October 2018 were enrolled. The data on their pre-pregnancy BMI, maternal weight gain during pregnancy, pre-pregnancy BMI of the husband, and neonatal birth weight were collected. The interaction between pre-pregnancy parental BMI and maternal weight gain during pregnancy was analyzed, and their correlation with neonatal birth weight was analyzed.

RESULTS

Among the 1 127 full-term neonates, the detection rates of low birth weight neonates and macrosomia were 2.22% (25/1 127) and 3.82% (43/1 127) respectively. There were significant differences in pre-pregnancy parental BMI and maternal weight gain during pregnancy among the low birth weight, normal birth weight, and macrosomia groups (P<0.05). Neonatal birth weight was positively correlated with pre-pregnancy parental BMI and maternal weight gain during pregnancy (r=0.097-0.322, P<0.05). Low maternal weight before pregnancy increased the risk of low birth weight (RR=4.17, 95%CI: 1.86-9.38), and maternal overweight/obesity before pregnancy (RR=3.59, 95%CI: 1.93-6.67) and excessive weight gain during pregnancy (RR=3.21, 95%CI: 1.39-7.37) increased the risk of macrosomia. No interaction between pre-pregnancy maternal BMI and maternal weight gain during pregnancy was observed.

CONCLUSIONS

Pre-pregnancy parental BMI and maternal weight gain during pregnancy are related to neonatal birth weight, and there is no interaction between pre-pregnancy maternal BMI and maternal weight gain during pregnancy.

Antibiotic use in early childhood and risk of obesity: longitudinal analysis of a national cohort

BACKGROUND

Taking oral antibiotics during childhood has been linked with an increased risk of childhood obesity. This study assessed any potential association in number of courses of antibiotics taken between 2-3 and 4-5 years of age and body mass trajectory up to age 5.

METHODS

The study was a secondary analysis of 8186 children and their parents from the infant cohort of the Irish National Longitudinal Study of Children. Antibiotic use was measured by parental recall between ages 2-3 and 4-5. Longitudinal models described the relationship between antibiotic exposure and body mass index (BMI) standard deviation scores and binary outcomes, and examined interactions between covariates, which included socioeconomic status, diet assessed by food frequency questionnaires and maternal BMI.

RESULTS

Any antibiotic usage between 2 and 3 years did not predict risk of overweight or obesity at age 5. Four or more courses of antibiotics between 2 and 3 years were independently associated with obesity at age 5 (odds ratio 1.6, 95% confidence interval 1.11-2.31). Effect size was modest (coefficient + 0.09 body mass SD units, standard error 0.04, P = 0.037). Maternal BMI modified the relationship: ≥ 4 courses of antibiotics between 2 and 3 years were associated with a + 0.12 body mass SD units increase in weight at age 5 among children of normal-weight mothers (P = 0.035), but not in children of overweight mothers.

CONCLUSIONS

Number of antibiotic courses, rather than antibiotic use, may be an important factor in any link between early antibiotic exposure and subsequent childhood obesity. Research is needed to confirm differential effects on babies of normal versus overweight/obese mothers independent of socioeconomic factors.

Maternal BMI-Increasing Genetic Risk Score and Fetal Weights among Diverse US Ethnic Groups

OBJECTIVE

Associations between maternal genetic risk for obesity and fetal weight were examined at the end of the first (13 weeks 6 days), second (27 weeks 6 days), and third (40 weeks 0 days) trimesters of pregnancy among four race/ethnic groups in the US.

METHODS

For 603 white, 591 black, 535 Hispanic, and 216 Asian women, maternal genetic risk score (GRS) was calculated as the sum of 189 BMI-increasing alleles and was categorized into high or low GRS. Associations between GRS (continuous and categorical) and estimated fetal weight were tested overall and stratified by prepregnancy BMI, gestational weight gain (GWG), and fetal sex.

RESULTS

High GRS compared with low GRS was associated with increased fetal weight at the end of the second (β: 22.7 g; 95% CI: 2.4-43.1; P = 0.03) and third trimesters (β: 88.3 g; 95% CI: 9.0-167.6; P = 0.03) among Hispanic women. The effect of GRS was stronger among Hispanic women with normal prepregnancy weight, adequate first trimester GWG, or inadequate second trimester GWG (P < 0.05). Among Asian women, high GRS was associated with increased weight among male fetuses but decreased weight among female fetuses (P < 0.05).

CONCLUSIONS

Maternal obesity genetic risk was associated with fetal weight with potential effect modifications by maternal prepregnancy BMI, GWG, and fetal sex.

Obesity, genomic ancestry, and socioeconomic variables in Latin American mestizos

OBJECTIVES

This article aims to assess the contribution of genomic ancestry and socioeconomic status to obesity in a sample of admixed Latin Americans.

METHODS

The study comprised 6776 adult volunteers from Brazil, Chile, Colombia, Mexico, and Peru. Each volunteer completed a questionnaire about socioeconomic variables. Anthropometric variables such as weight, height, waist, and hip circumference were measured to calculate body indices: body mass index, waist-to-hip ratio and waist-to-height ratio (WHtR). Genetic data were extracted from blood samples, and ancestry was estimated using chip genotypes. Multiple linear regression was used to evaluate the relationship between the indices and ancestry, educational level, and economic well-being. The body indices were dichotomized to obesity indices by using appropriate thresholds. Odds ratios were calculated for each obesity index.

RESULTS

The sample showed high percentages of obesity by all measurements. However, indices did not overlap consistently when classifying obesity. WHtR resulted in the highest prevalence of obesity. Overall, women with low education level and men with high economic wellness were more likely to be obese. American ancestry was statistically associated with obesity indices, although to a lesser extent than socioeconomic variables.

CONCLUSIONS

The proportion of obesity was heavily dependent on the index and the population. Genomic ancestry has a significant influence on the anthropometric measurements, especially on central adiposity. As a whole, we detected a large interpopulation variation that suggests that better approaches to overweight and obesity phenotypes are needed in order to obtain more precise reference values.

Maternal educational inequalities in measured body mass index trajectories in three European countries

BACKGROUND

Social inequalities in the prevalence of childhood overweight and obesity are well-established, but less is known about when the social gradient first emerges and how it evolves across childhood and adolescence.

OBJECTIVE

This study examines maternal education differentials in children's body mass trajectories in infancy, childhood and adolescence using data from four contemporary European child cohorts.

METHODS

Prospective data on children's body mass index (BMI) were obtained from four cohort studies-Generation XXI (G21-Portugal), Growing Up in Ireland (GUI) infant and child cohorts, and the Millennium Cohort Study (MCS-UK)-involving a total sample of 41,399 children and 120,140 observations. Children's BMI trajectories were modelled by maternal education level using mixed-effect models.

RESULTS

Maternal educational inequalities in children's BMI were evident as early as three years of age. Children from lower maternal educational backgrounds were characterised by accelerated BMI growth, and the extent of the disparity was such that boys from primary-educated backgrounds measured 0.42 kg/m² (95% CI 0.24, 0.60) heavier at 7 years of age in G21, 0.90 kg/m² (95% CI 0.60, 1.19) heavier at 13 years of age in GUI and 0.75 kg/m² (95% CI 0.52, 0.97) heavier in MCS at 14 years of age. The corresponding figures for girls were 0.71 kg/m² (95% CI 0.50, 0.91), 1.31 kg/m² (95% CI 1.00, 1.62) and 0.76 kg/m² (95% CI 0.53, 1.00) in G21, GUI and MCS, respectively.

CONCLUSIONS

Maternal education is a strong predictor of BMI across European nations. Socio-economic differentials emerge early and widen across childhood, highlighting the need for early intervention.

Early rapid weight gain among formula-fed infants: Impact of formula type and maternal feeding styles

BACKGROUND

What and how infants are fed are considered important determinants for the risk factor of early rapid gain weight.

OBJECTIVES

We conducted secondary analyses on data from a randomized clinical trial, wherein infants randomized to feed cow milk formula had double the incidence of early rapid weight gain than those fed extensively hydrolyzed protein formula, to determine whether maternal feeding styles had independent effects or interactive effects with infant formula type on early rapid weight gain.

METHODS

Anthropometry and feeding patterning (number of daily formula feeds) were measured monthly, and maternal feeding styles were measured at 0.5, 3.5, and 4.5 months. Longitudinal models were fitted using generalized estimating equations and separate logistic models conducted.

RESULTS

The treatment groups did not differ in formula feeding patterning or in maternal feeding styles, which were stable across the first 4.5 months. Feeding styles had no significant effects on early rapid weight gain and did not interact with formula group. However, type of infant formula had a direct and independent impact on early rapid weight gain (P = 0.003).

CONCLUSIONS

The type of infant formula had a differential impact on early rapid weight gain independent of maternal feeding style, highlighting the self-regulatory capabilities of infants.

Body Mass Index Changes in Early Childhood

OBJECTIVE

To longitudinally investigate body mass index (BMI) in young children in Ireland and identify factors and critical time points associated with changes in BMI.

STUDY DESIGN

Data on 11 134 children were collected in the nationally representative Growing Up in Ireland infant cohort study. Height and weight were measured at 9 months, 3 years, and 5 years of age. Multilevel regression was used to identify risk factors associated with changes in BMI over time (n = 10 377), combining a unique set of covariates collected from the child and the 2 main caregivers (usually the mother and father).

RESULTS

The proportion of children ≥85th percentile of World Health Organization growth criteria was 39% at 9 months, 44% at 3 years, and 30% at 5 years. Children born large for gestational age (13%) and those with rapid infant weight gain (25%) consistently had higher BMI. Low average BMIs were consistently seen in children born small for gestational age (10%) or before 37 weeks (7%). Smaller variations in BMI existed for other factors including ethnicity, household structure, caregiver weight status, breastfeeding, sex, socioeconomic status, sleeping hours, childcare, and region.

CONCLUSIONS

In this study, differences at birth and in infancy appear to be most strongly associated with variation in BMI at all ages. Nevertheless, belonging to a number of other high-risk groups cumulatively could lead children to develop critical weight states. Policy-makers should target families with interventions before and during pregnancy when dominant risk factors are still modifiable. Longer-term follow-up of children may be needed to study associations later in childhood.

Acceleration of BMI in Early Childhood and Risk of Sustained Obesity

BACKGROUND

The dynamics of body-mass index (BMI) in children from birth to adolescence are unclear, and whether susceptibility for the development of sustained obesity occurs at a specific age in children is important to determine.

METHODS

To assess the age at onset of obesity, we performed prospective and retrospective analyses of the course of BMI over time in a population-based sample of 51,505 children for whom sequential anthropometric data were available during childhood (0 to 14 years of age) and adolescence (15 to 18 years of age). In addition, we assessed the dynamics of annual BMI increments, defined as the change in BMI standard-deviation score per year, during childhood in 34,196 children.

RESULTS

In retrospective analyses, we found that most of the adolescents with normal weight had always had a normal weight throughout childhood. Approximately half (53%) of the obese adolescents had been overweight or obese from 5 years of age onward, and the BMI standard-deviation score further increased with age. In prospective analyses, we found that almost 90% of the children who were obese at 3 years of age were overweight or obese in adolescence. Among the adolescents who were obese, the greatest acceleration in annual BMI increments had occurred between 2 and 6 years of age, with a further rise in BMI percentile thereafter. High acceleration in annual BMI increments during the preschool years (but not during the school years) was associated with a risk of overweight or obesity in adolescence that was 1.4 times as high as the risk among children who had had stable BMI. The rate of overweight or obesity in adolescence was higher among children who had been large for gestational age at birth (43.7%) than among those who had been at an appropriate weight for gestational age (28.4%) or small for gestational age (27.2%), which corresponded to a risk of adolescent obesity that was 1.55 times as high among those who had been large for gestational age as among the other groups.

CONCLUSIONS

Among obese adolescents, the most rapid weight gain had occurred between 2 and 6 years of age; most children who were obese at that age were obese in adolescence. (Funded by the German Research Council for the Clinical Research Center "Obesity Mechanisms" and others; ClinicalTrials.gov number, NCT03072537 .).

Pre-, Perinatal, and Parental Predictors of Body Mass Index Trajectory Milestones

OBJECTIVE

To assess associations of pre-, perinatal, and parental factors with age and magnitude at body mass index (BMI) peak and rebound.

STUDY DESIGN

Among 1681 children with BMI data from birth to mid-childhood in Project Viva, we fitted individual BMI trajectories using mixed-effect models with natural cubic spline functions and estimated age and magnitude at peak in infancy and rebound in early childhood. We used stepwise multivariable regression to identify predictors of peak and rebound in the 1354 (63.6%) children with estimable trajectory milestones.

RESULTS

The mean (SD) of age at BMI peak was 8.4 (2.7) months and at rebound was 59.8 (19.6) months, and the mean (SD) of magnitude at peak was 18.0 (1.4) kg/m² and at rebound was 15.9 (1.2) kg/m². Girls had a later age at peak, earlier age at rebound, and lower magnitudes at peak and rebound than boys. Maternal isolated hyperglycemia (vs normoglycemia: β 0.7 months [95% CI 0.2-1.2]) and pre-eclampsia (vs normal blood pressure: 1.6 months [0.8-2.4]) were associated with a later peak, and impaired glucose tolerance (vs normoglycemia: -0.5 kg/m² [-0.9, -0.1]) was associated with a lower magnitude at peak. Greater maternal first-trimester weight gain, smoking during pregnancy, no breastfeeding, parental obesity, and no university education were associated with greater BMI at rebound.

CONCLUSIONS

We have identified modifiable prenatal and parental predictors of BMI peak in infancy and rebound in childhood. Early-life interventions that address these factors may be effective in changing BMI peak and rebound and potentially preventing later obesity.

Association of Weight for Length vs Body Mass Index During the First 2 Years of Life With Cardiometabolic Risk in Early Adolescence

Importance

The American Academy of Pediatrics currently recommends weight for length (WFL) for assessment of weight status in children younger than 2 years but body mass index (BMI) for children older than 2 years. However, the clinical implications of using WFL vs BMI in children younger than 2 years as an indicator of future health outcomes remains understudied.

Objective

To compare associations of overweight based on WFL vs BMI in children younger than 2 years with cardiometabolic outcomes during early adolescence.

Design, Setting, and Participants

This prospective study of birth cohorts in the United States (Project Viva) and Belarus (Promotion of Breastfeeding Intervention Trial [PROBIT]) performed from June 1, 1996, to November 31, 2002, included 13 666 children younger than 2 years.

Main Exposures

Overweight defined as Centers for Disease Control and Prevention (CDC) WFL in the 95th percentile or greater, World Health Organization (WHO) WFL in the 97.7th percentile or greater, or WHO BMI in the 97.7th percentile or greater at 6, 12, 18, or 24 months of age.

Main Outcomes and Measures

Primary outcomes were fat mass index, insulin resistance, metabolic risk score, and obesity during early adolescence. Secondary outcomes were height and BMI z scores, sum of skinfolds, waist circumference, and systolic blood pressure during early adolescence.

Results

The study included 919 children (mean [SD] age, 12.9 [0.9] years; 460 [50.1%] male; and 598 [65.1%] white) from Project Viva and 12 747 children (mean [SD] age, 11.5 [0.5] years; 6204 [48.7%] male; and 12 747 [100%] white) from PROBIT. During 6 to 24 months of age, in Project Viva, 206 children (22.4%) were overweight at any of the 4 times points according to the CDC WFL, 160 (17.4%) according to WHO WFL, and 161 (17.5%) according to WHO BMI cut points. In PROBIT, 3715 children (29.1%) were overweight at any of the 4 time points according to the CDC WFL, 3069 (24.1%) according to WHO WFL, and 3125 (24.5%) according to WHO BMI cut points. After maternal and child characteristics were adjusted for, being ever overweight (vs never overweight) during 6 to 24 months of age was associated with higher likelihood of adverse cardiometabolic risk markers during early adolescence, but associations did not differ substantially across WFL and BMI cut points in either cohort. For example, for fat mass index in Project Viva, β = 0.9 (95% CI, 0.5-1.4) for the CDC WFL, β = 1.1 (95% CI, 0.6-1.6) for WHO WFL, and β = 1.4 (95% CI, 0.9-1.9) for WHO BMI. For PROBIT, β = 0.5 (95% CI, 0.4-0.6) for the CDC WFL, β = 0.6 (95% CI, 0.5-0.7) for WHO WFL, and β = 0.6 (95% CI, 0.5-0.6) for WHO BMI. Neither growth metric in infancy was superior over the others based on F statistics (Project Viva: 17.1-17.8; PROBIT: 87.1-88.7). Findings were similar for insulin resistance, metabolic risk score, obesity, and secondary outcomes.

Conclusions and Relevance

Choice of WFL vs BMI to define overweight during the first 2 years of life may not greatly affect the association with cardiometabolic outcomes during early adolescence. The findings appear to have important implications for investigators seeking to use BMI as a growth metric for epidemiologic research and for practitioners monitoring the weight status of children younger than 2 years.

Genetic risk score for adult body mass index associations with childhood and adolescent weight gain in an African population

Background

Ninety-seven independent single nucleotide polymorphisms (SNPs) are robustly associated with adult body mass index (BMI kg/m²) in Caucasian populations. The relevance of such variants in African populations at different stages of the life course (such as childhood) is unclear. We tested whether a genetic risk score composed of the aforementioned SNPs was associated with BMI from infancy to early adulthood. We further tested whether this genetic effect was mediated by conditional weight gain at different growth periods. We used data from the Birth to Twenty Plus Cohort (Bt20+), for 971 urban South African black children from birth to 18 years. DNA was collected at 13 years old and was genotyped using the Metabochip (Illumina) array. The weighted genetic risk score (wGRS) for BMI was constructed based on 71 of the 97 previously reported SNPs.

Results

The cross-sectional association between the wGRS and BMI strengthened with age from 5 to 18 years. The significant associations were observed from 11 to 18 years, and peak effect sizes were observed at 13 and 14 years of age. Results from the linear mixed effects models showed significant interactions between the wGRS and age on longitudinal BMI but no such interactions were observed in sex and the wGRS. A higher wGRS was associated with an increased relative risk of belonging to the early onset obese longitudinal BMI trajectory (relative risk = 1.88; 95%CI 1.28 to 2.76) compared to belonging to a normal longitudinal BMI trajectory. Adolescent conditional relative weight gain had a suggestive mediation effect of 56% on the association between wGRS and obesity risk at 18 years.

Conclusions

The results suggest that genetic susceptibility to higher adult BMI can be tracked from childhood in this African population. This supports the notion that prevention of adult obesity should begin early in life. The genetic risk score combined with other non-genetic risk factors, such as BMI trajectory membership in our case, has the potential to be used to screen for early identification of individuals at increased risk of obesity and other related NCD risk factors in order to reduce the adverse health risk outcomes later.

Electronic supplementary material

The online version of this article (10.1186/s12263-018-0613-7) contains supplementary material, which is available to authorized users.

Associations of the infancy body mass index peak with anthropometry and cardiometabolic risk in Mexican adolescents

BACKGROUND

Early-life growth dynamics are associated with future health. Little is known regarding timing and magnitude of the infancy body mass index (BMI) peak with adiposity and metabolic biomarkers during adolescence.

AIM

To examine associations of the infancy BMI peak with anthropometry and cardiometabolic risk during peripuberty.

METHODS

Among 163 ELEMENT participants, this study estimated age and magnitude of the infancy BMI peak from eight anthropometric measurements from birth-36 months using Newton's Growth Models, an acceleration-based process model. Associations were examined of the infancy milestones with anthropometry and cardiometabolic risk at 8-14 years using linear regression models that accounted for maternal calcium supplementation and age; child's birthweight, sex, and age; and the other infancy milestone.

RESULTS

Median age at the infancy BMI peak was 9.6 months, and median peak BMI was 16.5 kg/m2. Later age and larger magnitude of the peak predicted higher BMI z-score, waist circumference, and skinfold thicknesses; i.e. each 1 month of age at peak and each 1 kg/m2 of peak BMI corresponded with 0.04 (0.01-0.07) and 0.33 (0.17-0.48) units of higher BMI z-score, respectively. Later age at peak was also a determinant of worse glycaemia and higher blood pressure.

CONCLUSION

Later age and larger magnitude of the infancy BMI peak are associated with higher adiposity at 8-14 years of age. Later age but not magnitude of the BMI peak are related to a worse cardiometabolic profile during peripuberty.

Validity of Body Mass Index as a Measure of Adiposity in Infancy

OBJECTIVES

To assess the validity of body mass index (BMI) and age- and sex-standardized BMI z-score (BMIZ) as surrogates for adiposity (body fat percentage [BF%], fat mass, and fat mass index [kg/m²]) at 3 time points in infancy (1, 4, and 7 months) and to assess the extent to which the change in BMIZ represents change in adiposity.

STUDY DESIGN

We performed a secondary analysis of 447 full-term infants in a previous trial of maternal vitamin D supplementation during lactation. Study staff measured infant anthropometrics and assessed body composition with dual-energy x-ray absorptiometry at 1, 4, and 7 months of age. We calculated Spearman correlations (r_s) among BMI, BMIZ, and adiposity at each time point, and between change in BMIZ and change in adiposity between time points.

RESULTS

Infants (N = 447) were 52% male, 38% white, 31% black, and 29% Hispanic. The BMIZ was moderately correlated with BF% (r_s = 0.43, 0.55, 0.48 at 1, 4, and 7 months of age, respectively). BMIZ correlated more strongly with fat mass and fat mass index, particularly at 4 and 7 months of age (fat mass r_s = 0.72-0.76; fat mass index r_s = 0.75-0.79). Changes in BMIZ were moderately correlated with adiposity changes from 1 to 4 months of age (r_s = 0.44 with BF% change; r_s = 0.53 with fat mass change), but only weakly correlated from 4 to 7 months of age (r_s = 0.21 with BF% change; r_s = 0.27 with fat mass change).

CONCLUSIONS

BMIZ is moderately correlated with adiposity in infancy. Changes in BMIZ are a poor indicator of adiposity changes in later infancy. BMI and BMIZ are limited as surrogates for adiposity and especially adiposity changes in infancy.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT00412074.

Infant body mass index peak and early childhood cardio-metabolic risk markers in a multi-ethnic Asian birth cohort

Background

: Infant body mass index (BMI) peak has received much interest recently as a potential predictor of future obesity and metabolic risk. No studies, however, have examined infant BMI peak in Asian populations, in whom the risk of metabolic disease is higher.

Methods

: We utilized data among 1020 infants from a mother-offspring cohort, who were Singapore citizens or permanent residents of Chinese, Malay or Indian ethnicity with homogeneous parental ethnic backgrounds, and did not receive chemotherapy, psychotropic drugs or have diabetes mellitus. Ethnicity was self-reported at recruitment and later confirmed using genotype analysis. Subject-specific BMI curves were fitted to infant BMI data using natural cubic splines with random coefficients to account for repeated measures in each child. We estimated characteristics of the child's BMI peak [age and magnitude at peak, average pre-peak velocity (aPPV)]. Systolic (SBP) and diastolic blood pressure (DBP), BMI, sum of skinfolds (SSF) and fat-mass index (FMI) were measured during a follow-up visit at age 48 months. Weighted multivariable linear regression was used to assess the predictors (maternal BMI, gestational weight gain, ethnicity, infant sex, gestational age, birthweight-for-gestational age and breastfeeding duration) of infant BMI peak and its associations with outcomes at 48 months. Comparisons between ethnicities were tested using Bonferroni post-hoc correction.

Results

: Of 1020 infants, 80.5% were followed up at the 48-month visit. Mean (SD) BMI, SSF and FMI at 48 months were 15.6 (1.8) kg/m 2 , 16.5 (5.3) mm and 3.8 (1.3) kg/m 2 , respectively. Mean (SD) age at peak BMI was 6.0 (1.6) months, with a magnitude of 17.2 (1.4) kg/m 2 and pre-peak velocity of 0.7 (0.3) kg/m 2 /month. Compared with Chinese infants, the peak occurred later in Malay {B [95% confidence interval (CI): 0.64 mo (0.36, 0.92)]} and Indian infants [1.11 mo (0.76, 1.46)] and was lower in magnitude in Indian infants [-0.45 kg/m 2 (-0.69, -0.20)]. Adjusting for maternal education, BMI, gestational weight gain, ethnicity, infant sex, gestational age, birthweight-for-gestational-age and breastfeeding duration, higher peak and aPPV were associated with greater BMI, SSF and FMI at 48 months. Age at peak was positively associated with BMI at 48 months [0.15 units (0.09, 0.22)], whereas peak magnitude was associated with SBP [0.17 units (0.05, 0.30)] and DBP at 48 months [0.10 units (0.01, 0.22)]. Older age and higher magnitude at peak were associated with increased risk of overweight at 48 months [Relative Risk (95% CI): 1.35 (1.12-1.62) for age; 1.89 (1.60-2.24) for magnitude]. The associations of BMI peak with BMI and SSF at 48 months were stronger in Malay and Indian children than in Chinese children.

Conclusions

: Ethnic-specific differences in BMI peak characteristics, and associations of BMI peak with early childhood cardio-metabolic markers, suggest an important impact of early BMI development on later metabolic outcomes in Asian populations.

An overview of assessment methodology for obesity-related variables in infants at risk

BACKGROUND

The first 2 years of a child's life are a particularly critical time period for obesity prevention.

AIM

An increasing amount of research across the world is aimed at understanding factors that impact early childhood obesity and developing interventions that target these factors effectively. With this growing interest, new and interdisciplinary research teams are developing to meet this research need. Due to rapid growth velocity during this phase of the lifespan, typical assessments used in older populations may not be valid or applicable in infants, and investigators need to be aware of the pros and cons of specific methodological strategies.

METHODS

This paper provides an overview of methodology available to assess obesity-related factors in the areas of anthropometry and body composition, nutrient intake, and energy expenditure in infants aged 0-2 years.

RESULTS

Gold standard measures for body composition, such as dual-energy X-ray absorptiometry (DXA) or other imaging techniques, are costly, require highly trained personnel, and are limited for research application. Nutrient intake methodology primarily includes surveys and questionnaires completed via parent proxy report. In terms of energy expenditure, methods of calorimetry are expensive and may not differentiate between different activities. Questionnaires or physical activity sensors offer another way of energy expenditure assessment. However, questionnaires have a certain recall bias, while the sensors require further validation.

CONCLUSIONS

Overall, in addition to understanding the pros and cons of each assessment tool, researchers should take into consideration the experience of the interdisciplinary team of investigators, as well as the cost and availability of measures at their institution.

Infant BMI peak as a predictor of overweight and obesity at age 2 years in a Chinese community-based cohort

OBJECTIVES

Infant body mass index (BMI) peak has proven to be a useful indicator for predicting childhood obesity risk in American and European populations. However, it has not been assessed in China. We characterised infant BMI trajectories in a Chinese longitudinal cohort and evaluated whether BMI peak can predict overweight and obesity at age 2 years.

METHODS

Serial measurements (n=6-12) of weight and length were taken from healthy term infants (n=2073) in a birth cohort established in urban Shanghai. Measurements were used to estimate BMI growth curves from birth to 13.5 months using a polynomial regression model. BMI peak characteristics, including age (in months) and magnitude (BMI, in kg/m²) at peak and prepeak velocities (in kg/m²/month), were estimated. The relationship between infant BMI peak and childhood BMI at age 2 years was examined using binary logistic analysis.

RESULTS

Mean age at peak BMI was 7.61 months, with a magnitude of 18.33 kg/m². Boys (n=1022) had a higher average peak BMI (18.60 vs 18.07 kg/m², p<0.001) and earlier average achievement of peak value (7.54 vs 7.67 months, p<0.05) than girls (n=1051). With 1 kg/m² increase in peak BMI and 1 month increase in peak time, the risk of overweight at age 2 years increased by 2.11 times (OR 3.11; 95% CI 2.64 to 3.66) and 35% (OR 1.35; 95% CI 1.21 to 1.50), respectively. Similarly, higher BMI magnitude (OR 2.69; 95% CI 2.00 to 3.61) and later timing of infant BMI peak (OR 1.35; 95% CI 1.08 to 1.68) were associated with an increased risk of childhood obesity at age 2 years.

CONCLUSIONS

We have shown that infant BMI peak is valuable for predicting early childhood overweight and obesity in urban Shanghai. Because this is the first Chinese community-based cohort study of this nature, future research is required to examine infant populations in other areas of China.

Does the association between early life growth and later obesity differ by race/ethnicity or socioeconomic status? A systematic review

PURPOSE

Rapid growth during infancy predicts higher risk of obesity later in childhood. The association between patterns of early life growth and later obesity may differ by race/ethnicity or socioeconomic status (SES), but prior evidence syntheses do not consider vulnerable subpopulations.

METHODS

We systemically reviewed published studies that explored patterns of early life growth (0-24 months of age) as predictors of later obesity (>24 months) that were either conducted in racial/ethnic minority or low-SES study populations or assessed effect modification of this association by race/ethnicity or SES. Literature searches were conducted in PubMed and SocINDEX.

RESULTS

Ten studies met the inclusion criteria. Faster growth during the first 2 years of life was consistently associated with later obesity irrespective of definition and timing of exposure and outcome measures. Associations were strongest in populations composed of greater proportions of racial/ethnic minority and/or low-SES children. For example, ORs ranged from 1.17 (95% CI: 1.11, 1.24) in a heterogeneous population to 9.24 (95% CI: 3.73, 22.9) in an entirely low-SES nonwhite population.

CONCLUSIONS

The impact of rapid growth in infancy on later obesity may differ by social stratification factors such as race/ethnicity and family income. More robust and inclusive studies examining these associations are needed.

Body Composition within the First 3 Months: Optimized Correction for Length and Correlation with BMI at 2 Years

BACKGROUND/AIMS

Although early infant growth has implications for future health, body composition reference data in infancy are limited. The aim of this study was to describe reference data for fat mass (FM) and fat-free mass (FFM) corrected for length (L) within the first 3 months and to evaluate if these measures predict the body mass index (BMI) at 2 years.

METHODS

Term infants had air displacement plethysmography performed at birth (n = 1,063) and approximately 2 months later (n = 922, between 49 and 86 days). Age- and sex-specific reference data were generated for FM, FFM, FM/L³ and FFM/L² and compared with BMI at 2 years.

RESULTS

FM/L³ and FFM/L² were the optimal indices independent of length. In the first 3 months, mean FM/L³ increased (males, from 2.7 to 5.9 kg/m³; females, from 3.2 to 6.1 kg/m³), whereas FFM/L² remained relatively stable (males, from 11.8 to 12.7 kg/m²; females, from 12.8 to 12.1 kg/m²). The odds of a BMI Z-score ≥2 at 2 years increased with increasing FM (OR 2.7, 95% CI 1.97-3.7) and weight (OR 2.27, 95% CI 1.64-3.13) Z-scores at 2 months.

CONCLUSIONS

FM/L³ and FFM/L² provide length-independent measures of FM and FFM in infancy. During the first 3 months, there is an increase in FM/L³, but not in FFM/L². The weight Z-score at 2 months is as good at predicting BMI at 2 years as body composition parameters. © 2016 S. Karger AG, Basel.

High Body Mass Index in Infancy May Predict Severe Obesity in Early Childhood

OBJECTIVE

To characterize growth trajectories of children who develop severe obesity by age 6 years and identify clinical thresholds for detection of high-risk children before the onset of obesity.

STUDY DESIGN

Two lean (body mass index [BMI] 5th to ≤75th percentile) and 2 severely obese (BMI ≥99th percentile) groups were selected from populations treated at pediatric referral and primary care clinics. A population-based cohort was used to validate the utility of identified risk thresholds. Repeated-measures mixed modeling and logistic regression were used for analysis.

RESULTS

A total of 783 participants of normal weight and 480 participants with severe obesity were included in the initial study. BMI differed significantly between the severely obese and normal-weight cohorts by age 4 months (P < .001), at 1 year before the median age at onset of obesity. A cutoff of the World Health Organization (WHO) 85th percentile for BMI at 6, 12, and 18 months was a strong predictor of severe obesity by age 6 years (sensitivity, 51%-95%; specificity, 95%). This BMI threshold was validated in a second independent cohort (n = 2649), with a sensitivity of 33%-77% and a specificity of 74%-87%. A BMI ≥85th percentile in infancy increases the risk of severe obesity by age 6 years by 2.5-fold and the risk of clinical obesity by age 6 years by 3-fold.

CONCLUSIONS

BMI trajectories in children who develop severe obesity by age 6 years differ from those in children who remain at normal weight by age 4-6 months, before the onset of obesity. Infants with a WHO BMI ≥85th percentile are at increased risk for developing severe obesity by age 6 years.

Association between body mass index percentile trajectories in infancy and adiposity in childhood and early adulthood

OBJECTIVE

To identify distinct body mass index (BMI) percentile trajectories during early childhood and examine adiposity levels in childhood and early adulthood according to the BMI percentile trajectories.

METHODS

Iowa Fluoride Study cohort parents (n = 1,093) reported their child's anthropometric data on average six times between ages 0 and 23 months. A subset of the cohort underwent DXA scans at approximately age 8 years (n = 495) and again at approximately age 19 years (n = 314). Group-based trajectory analysis was conducted to identify distinct BMI percentile trajectories from ages 0 to 23 months. Sex-specific age-adjusted linear regression analyses were conducted to compare fat mass index in childhood and early adulthood among subgroups that follow the distinct BMI percentile patterns.

RESULTS

Four BMI percentile patterns were identified: consistently low (group 1: 9.8%), increase in the second year (group 2: 33.7%), increase in the first year (group 3: 23.9%), and consistently high (group 4: 32.6%). Compared with group 2 females, groups 3 and 4 females had higher fat mass index in childhood and early adulthood (P < 0.05). However, no significant difference was found in males.

CONCLUSIONS

Females who experience a steep increase of BMI percentile in the first year of life, as opposed to a steep increase in the second year of life, may have higher body fat later in life, but this was not found in males.

The impact of length and weight on survival after heart transplantation in children less than 24 months of age

Adults, older children, and adolescent patients with a BMI categorized as overweight or obese have decreased survival after HTx. Anthropometric correlates of survival after HTx in infants have not been well defined. In a retrospective analysis of the UNOS registry, patients age 0-24 months were classified according to the WHO height-for-age and weight-for-age norms, as well as arbitrary BMI-for-age percentiles. Outcomes of 1-year survival, conditional long-term survival, and cause-specific mortality were examined. Infants with stunted growth according to the WHO definition had increased risks of early mortality, late mortality, and death due to graft failure after HTx. Secondary analysis of first-year survival demonstrated increased mortality in children who were underweight according to weight-for-age, but a survival disadvantage in the highest BMI-for-age category, likely due to short recumbent length leading to relatively high BMI values. Stunted growth relative to WHO standards predicts mortality following heart transplant in children less than 2 years of age. The association between post-transplant mortality and high BMI-for-age, as demonstrated in older cohorts, was observed in the infant cohort only due to stunting, and not due to overweight classification.

Infant BMI or Weight-for-Length and Obesity Risk in Early Childhood

BACKGROUND

Weight-for-length (WFL) is currently used to assess adiposity under 2 years. We assessed WFL- versus BMI-based estimates of adiposity in healthy infants in determining risk for early obesity.

METHODS

Anthropometrics were extracted from electronic medical records for well-child visits for 73 949 full-term infants from a large pediatric network. World Health Organization WFL and BMI z scores (WFL-z and BMI-z, respectively) were calculated up to age 24 months. Correlation analyses assessed the agreement between WFL-z and BMI-z and within-subject tracking over time. Logistic regression determined odds of obesity at 2 years on the basis of adiposity classification at 2 months.

RESULTS

Agreement between WFL-z and BMI-z increased from birth to 6 months and remained high thereafter. BMI-z at 2 months was more consistent with measurements at older ages than WFL-z at 2 months. Infants with high BMI (≥85th percentile) and reference WFL (5th-85th percentiles) at 2 months had greater odds of obesity at 2 years than those with high WFL (≥85th percentile) and reference BMI (5th-85th percentiles; odds ratio, 5.49 vs 1.40; P < .001). At 2 months, BMI had a higher positive predictive value than WFL for obesity at 2 years using cut-points of either the 85th percentile (31% vs 23%) or 97.7th percentile (47% vs 29%).

CONCLUSIONS

High BMI in early infancy is more strongly associated with early childhood obesity than high WFL. Forty-seven percent of infants with BMI ≥97.7th percentile at 2 months (versus 29% of infants with WFL ≥97.7th percentile at 2 months) were obese at 2 years. Epidemiologic studies focused on assessing childhood obesity risk should consider using BMI in early infancy.

Connecting the Dots in Childhood Obesity Disparities: A Review of Growth Patterns from Birth to Pre-Adolescence

In this review, we considered how disparities in obesity emerge between birth, when socially disadvantaged infants tend to be small, and later in childhood, when socially disadvantaged groups have high risk of obesity. We reviewed epidemiologic evidence of socioeconomic and racial/ethnic differences in growth from infancy to pre-adolescence. Minority race/ethnicity and lower socioeconomic status was associated with rapid weight gain in infancy but not in older age groups, and social differences in linear growth and relative weight were unclear. Infant feeding practices was the most consistent mediator of social disparities in growth, but mediation analysis was uncommon and other factors have only begun to be explored. Complex life course processes challenge the field of social epidemiology to develop innovative study designs and analytic techniques with which to pose and test challenging yet impactful research questions about how obesity disparities evolve throughout childhood.

The Genetics of Pediatric Obesity

Obesity among children and adults has notably escalated over recent decades and represents a global major health problem. We now know that both genetic and environmental factors contribute to its complex etiology. Genome-wide association studies (GWAS) have revealed compelling genetic signals influencing obesity risk in adults. Recent reports for childhood obesity revealed that many adult loci also play a role in the pediatric setting. Childhood GWAS have uncovered novel loci below the detection range in adult studies, suggesting that obesity genes may be more easily uncovered in the pediatric setting. Shedding light on the genetic architecture of childhood obesity will facilitate the prevention and treatment of pediatric cases, and will have fundamental implications for diseases that present later in life.

Racial and Ethnic Disparities in Early Childhood Obesity: Growth Trajectories in Body Mass Index

OBJECTIVE

The aims of this study are to describe growth trajectories in the body mass index (BMI) among the major racial and ethnic groups of US children and to identify predictors of children's BMI trajectories.

METHODS

The Early Childhood Longitudinal Study-Birth Cohort (ECLS-B) was used to identify predictors of BMI growth trajectories, including child characteristics, maternal attributes, home practices related to diet and social behaviors, and family sociodemographic factors. Growth models, spanning 48 to 72 months of age, were estimated with hierarchical linear modeling via STATA/Xtmixed methods.

RESULTS

Approximately one-third of 4-year-old females and males were overweight and/or obese. African-American and Latino children displayed higher predicted mean BMI scores and differing mean BMI trajectories, compared with White children, adjusting for time-independent and time-dependent predictors. Several factors were significantly associated with lower mean BMI trajectories, including very low birth weight, higher maternal education level, residing in a two-parent household, and breastfeeding during infancy. Greater consumption of soda and fast food was associated with higher mean BMI growth. Soda consumption was a particularly strong predictor of mean BMI growth trajectory for young Black children. Neither the child's inactivity linked to television viewing nor fruit nor vegetable consumption was predictive of BMI growth for any racial/ethnic group.

CONCLUSION

Significant racial and ethnic differences are discernible in BMI trajectories among young children. Raising parents' and health practitioners' awareness of how fast food and sweetened-beverage consumption contributes to early obesity and growth in BMI-especially for Blacks and Latinos-could improve the health status of young children.