Infant Obesity and Severe Obesity Growth Patterns in the First Two Years of Life

Prenatal per- and polyfluoroalkyl substance mixtures and weight for length from birth to 12 months: The New Hampshire Birth Cohort Study

OBJECTIVE

To examine the joint associations of plasma concentrations of prenatal per- and polyfluoroalkyl substances (PFAS) mixtures with birth size and postnatal anthropometry measures.

MATERIAL AND METHODS

The current study included 641 mother-child dyads from the New Hampshire Birth Cohort Study. PFAS concentrations were quantified in maternal plasma samples collected during pregnancy (median: 28 weeks of gestation). Information on infant weight and length were abstracted from medical records and converted to sex- and age-standardized weight-for-length z-score according to the World Health Organization standard curves. Bayesian kernel machine regression (BKMR) was used to investigate the joint associations of multiple PFAS concentrations during pregnancy with weight-for-length z score at birth, 6-months, and 12-months. To account for longitudinal outcomes, we also fit linear mixed effect models between PFAS exposure burden score, a novel method to quantify total exposure burden to PFAS mixtures, and changes in weight-for-length from birth to 12 months of age. A multiplicative interaction term ("PFAS burden score × time [birth as a reference, 6 months, and 12 months of age]") was included to evaluate a potential time-varying relationship. All models were adjusted for maternal age, education, marital status, parity, smoking, seafood consumption, pre-pregnancy body mass index, and gestational week of blood draw.

RESULTS

In BKMR models, all 95 % credible intervals included the null value. In linear mixed effects models, PFAS exposure burden score was associated with a lower weight-for-length z-score (β = -0.20; 95 % confidence interval = -0.35, -0.04). The multiplicative interaction term was significant at both 6 and 12 months of age (P < 0.01 for both time points), particularly among female infants, suggesting a shift toward positive associations between the prenatal PFAS mixtures and weight-for-length z-score during infancy.

CONCLUSIONS

Prenatal PFAS mixtures may affect fetal and infant anthropometry measures differently by life stage and biological sex.

Associations of Infant Feeding, Sleep, and Weight Gain with the Toddler Gut Microbiome

This study examines how feeding, sleep, and growth during infancy impact the gut microbiome (GM) in toddlers. The research was conducted on toddlers (n = 36), born to Latina women of low-income with obesity. Their mothers completed retrospective feeding and sleeping questionnaires at 1, 6, and 12 months; at 36 months, fecal samples were collected. Sequencing of the 16S rRNA gene (V4 region) revealed that breastfeeding for at least 1 month and the introduction of solids before 6 months differentiated the GM in toddlerhood (Bray-Curtis, pseudo-F = 1.805, p = 0.018, and pseudo-F = 1.651, p = 0.044, respectively). Sleep had an effect across time; at 1 and 6 months of age, a lower proportion of nighttime sleep (relative to 24 h total sleep) was associated with a richer GM at three years of age (Shannon H = 4.395, p = 0.036 and OTU H = 5.559, p = 0.018, respectively). Toddlers experiencing rapid weight gain from birth to 6 months had lower phylogenetic diversity (Faith PD H = 3.633, p = 0.057). These findings suggest that early life nutrition, sleeping patterns, and growth rate in infancy may influence the GM composition. Further verification of these results with objective sleep data and a larger sample is needed.

Breast milk leptin concentrations and infant anthropometric indicators in SGA versus non-SGA breastfed infants born at term

Leptin concentrations in breast milk can influence metabolic programming during the first months of life. Small for gestational age (SGA) newborns show a peculiar growth pattern after birth, which can lead to adulthood diseases. This study aims to assess an association between leptin concentration in mature breast milk and the infant anthropometric indicators of the SGA and the non-SGA groups, in addition, to comparing the hormone level between these groups. A longitudinal study was performed with mother-infant pairs. The maternal sociodemographic information was collected in the first 48 h postpartum. Breast milk was collected at one month postpartum and leptin concentrations were obtained by immunoassays. The infant anthropometric measurements were collected at three and six months postpartum and included weight, height (to body mass index-BMI calculated), triceps skinfold (TSF), and subscapular skinfold (SSF). The BMI for age (BMI/A), TSF, and SSF were calculated by Z-score indicators. Data from 67 mother-infant pairs (n = 16 SGA and n = 51 non-SGA) were analyzed. In univariate analyses, the breast milk of the SGA group had lower leptin concentrations than the non-SGA group (p = 0.006), however, after adjustment, there was no difference between groups (p = 0.181). In the SGA group, there was a significant association between leptin concentrations and lower SSF at six months in infants, after adjustment (p = 0.003). In the non-SGA group, the breast milk leptin was associated with lower BMI/A at three and six months in infants, after adjustment (p = 0.002 and p = 0.010, respectively). The association between breast milk leptin concentrations with SSF in the SGA group and BMI/A in the non-SGA group suggests that leptin may be a modulating factor in infant growth in the first months of life.

Predicting Childhood Obesity Based on Single and Multiple Well-Child Visit Data Using Machine Learning Classifiers

Childhood obesity is a public health concern in the United States. Consequences of childhood obesity include metabolic disease and heart, lung, kidney, and other health-related comorbidities. Therefore, the early determination of obesity risk is needed and predicting the trend of a child's body mass index (BMI) at an early age is crucial. Early identification of obesity can lead to early prevention. Multiple methods have been tested and evaluated to assess obesity trends in children. Available growth charts help determine a child's current obesity level but do not predict future obesity risk. The present methods of predicting obesity include regression analysis and machine learning-based classifications and risk factor (threshold)-based categorizations based on specific criteria. All the present techniques, especially current machine learning-based methods, require longitudinal data and information on a large number of variables related to a child's growth (e.g., socioeconomic, family-related factors) in order to predict future obesity-risk. In this paper, we propose three different techniques for three different scenarios to predict childhood obesity based on machine learning approaches and apply them to real data. Our proposed methods predict obesity for children at five years of age using the following three data sets: (1) a single well-child visit, (2) multiple well-child visits under the age of two, and (3) multiple random well-child visits under the age of five. Our models are especially important for situations where only the current patient information is available rather than having multiple data points from regular spaced well-child visits. Our models predict obesity using basic information such as birth BMI, gestational age, BMI measures from well-child visits, and gender. Our models can predict a child's obesity category (normal, overweight, or obese) at five years of age with an accuracy of 89%, 77%, and 89%, for the three application scenarios, respectively. Therefore, our proposed models can assist healthcare professionals by acting as a decision support tool to aid in predicting childhood obesity early in order to reduce obesity-related complications, and in turn, improve healthcare.

Effects of Soy-Based Infant Formula on Weight Gain and Neurodevelopment in an Autism Mouse Model

Mice fed soy-based diets exhibit increased weight gain compared to mice fed casein-based diets, and the effects are more pronounced in a model of fragile X syndrome (FXS; Fmr1KO). FXS is a neurodevelopmental disability characterized by intellectual impairment, seizures, autistic behavior, anxiety, and obesity. Here, we analyzed body weight as a function of mouse age, diet, and genotype to determine the effect of diet (soy, casein, and grain-based) on weight gain. We also assessed plasma protein biomarker expression and behavior in response to diet. Juvenile Fmr1KO mice fed a soy protein-based rodent chow throughout gestation and postnatal development exhibit increased weight gain compared to mice fed a casein-based purified ingredient diet or grain-based, low phytoestrogen chow. Adolescent and adult Fmr1KO mice fed a soy-based infant formula diet exhibited increased weight gain compared to reference diets. Increased body mass was due to increased lean mass. Wild-type male mice fed soy-based infant formula exhibited increased learning in a passive avoidance paradigm, and Fmr1KO male mice had a deficit in nest building. Thus, at the systems level, consumption of soy-based diets increases weight gain and affects behavior. At the molecular level, a soy-based infant formula diet was associated with altered expression of numerous plasma proteins, including the adipose hormone leptin and the β-amyloid degrading enzyme neprilysin. In conclusion, single-source, soy-based diets may contribute to the development of obesity and the exacerbation of neurological phenotypes in developmental disabilities, such as FXS.

The infant gut microbiota at 12 months of age is associated with human milk exposure but not with maternal pre-pregnancy body mass index or infant BMI-for-age z-scores

BACKGROUND

As obesity rates continue to rise, it is increasingly important to understand factors that can influence body weight and growth, especially from an early age. The infant gut microbiota has broad effects on a variety of bodily processes, but its relation to infant growth is not yet fully characterized. Since the infant gut microbiota is closely related to breastfeeding practices and maternal health, understanding the relationship between these factors and infant growth may provide insight into the origins of childhood obesity.

OBJECTIVES

Identify the relationship between human milk exposure, maternal pre-pregnancy body mass index (BMI), the infant gut microbiota, and 12-month-old BMI-for-age z-scores (12M BAZ) to identify key factors that shape infant growth.

METHODS

Two Michigan cohorts (ARCHGUT and BABYGUT) comprised of a total of 33 mother-infant dyads provided infant fecal samples at 12M. After DNA extraction, amplification, and sequencing of the V4 16S rRNA region using Illumina MiSeq v2 Chemistry, gut bacterial diversity metrics were analyzed in relation to human milk exposure, maternal pre-pregnancy BMI, and infant growth parameters.

RESULTS

Recent human milk exposure was inversely related to maternal pre-pregnancy BMI and most strongly associated with infant gut bacterial community membership and individual gut microbiota richness differences. Maternal pre-pregnancy BMI was not associated with the infant gut microbiota after adjusting for human milk exposure. However, maternal pre-pregnancy BMI was the only factor significantly associated with 12M BAZ.

CONCLUSIONS

Human milk exposure is one of the central influences on the infant gut microbiota at 12M of age. However, the lack of association between the infant gut microbiota and 12M-old infant BAZ suggests that genetic, physiological, dietary, and other environmental factors may play a more direct role than the gut microbiota in determining infant BAZ at 12M.

Off the Charts: Identifying and Visualizing Body Mass Index Trajectories of Rural, Poor Youth

OBJECTIVES

To identify body mass index (BMI) trajectories using methods and graphing tools that maintain and visualize variability of BMIs ≥95th percentile, and to investigate individual differences in early sociodemographic risk, infant growth and feeding patterns, and maternal weight status among these trajectories.

STUDY DESIGN

Participants included 1041 predominantly rural, poor families from the Family Life Project, a longitudinal birth cohort. Youth anthropometrics were measured 8 times between ages 2 months and 12 years. Mothers reported sociodemographic information, infant birth weight, and infant feeding at 2 months and reported child weight and height at 2 months and 12 years. At 6 months, mothers reported breastfeeding. At 2 years, maternal weight and height were measured.

RESULTS

Three BMI trajectories were identified: "maintained non-overweight," "developed obesity," and "developed severe obesity." Compared with the non-overweight trajectory, children with heavier trajectories were breastfed for a shorter duration and had heavier mothers at all assessments. The children with the "developed obesity" trajectory were not heavier at birth than those with the non-overweight trajectory, yet they displayed a greater change in weight-for-length percentile during infancy; in addition, their mothers had the greatest change in BMI between 2 months and 12 years. Children with the "developed severe obesity" trajectory were heavier at birth and more likely to have been heavy during infancy and to have been fed solid foods early.

CONCLUSIONS

Using informed analytical and graphing approaches, we described patterns of growth, and identified early predictors of obesity and severe obesity trajectories among a diverse sample of rural, poor youth. Researchers are urged to consider these approaches in future work, and to focus on identifying protective factors in youth with obesity and severe obesity.

A Review of Modifiable Risk Factors for Severe Obesity in Children Ages 5 and Under

Early-onset severe obesity in childhood presents a significant clinical challenge signaling an urgent need for effective and sustainable interventions. A large body of literature examines overweight and obesity, but little focuses specifically on the risk factors for severe obesity in children ages 5 and younger. This narrative review identified modifiable risk factors associated with severe obesity in children ages 5 and younger: nutrition (consuming sugar sweetened beverages and fast food), activity (low frequency of outdoor play and excessive screen time), behaviors (lower satiety responsiveness, sleeping with a bottle, lack of bedtime rules, and short sleep duration), and socio-environmental risk factors (informal child care setting, history of obesity in the mother, and gestational diabetes). The lack of literature on this topic highlights the need for additional research on potentially modifiable risk factors for early-onset severe obesity.

Provider Observations of Youth with Early Onset Severe Obesity in Tertiary Care Obesity Programs

BACKGROUND

Over 2% of children between the ages of 2 and 5 have severe obesity; however, little is known about the characteristics of this population to guide healthcare professionals in providing care. An initial step is to examine observations of practitioners who manage children with severe early onset obesity in the clinical setting.

METHODS

A total of 72 interdisciplinary healthcare providers with experience providing obesity treatment to children under age 5 with severe obesity completed a semistructured online questionnaire. Participants responded to 10 open-ended questions about provider observations on several topics, including nutrition, eating behavior, activity, family structure and history, medical history, psychological conditions, and household routines. Data analysis was conducted using grounded theory methods. Emerging themes and subthemes were analyzed based on topics and provider discipline (e.g., medical, nursing, and psychology).

RESULTS

The most commonly observed and reported characteristic of young children with severe obesity was a parent-described dysfunctional approach to food, including frequent complaints about hunger, food seeking, and lack of satiety. Other characteristics included the presence of externalizing behaviors in the child such as temper tantrums and ADHD, developmental delays, medical comorbidities (e.g., asthma and sleep apnea), and unstructured home environments.

CONCLUSIONS

Drawing on the experience of an interdisciplinary group of healthcare providers, this is the first study to describe provider observations of the young child with severe early onset obesity. If validated, these observations can serve to illuminate areas for further education and inform potential clinical subtyping, providing an opportunity to identify target areas for intervention.

BMI Trajectories from Birth to Young Adulthood

OBJECTIVE

This study aimed to compare BMI trajectories from childhood to early adulthood in those with overweight and/or obesity versus severe obesity.

METHODS

Longitudinal BMI values (2,542 measurements) were calculated from measured heights and weights for 103 children, adolescents, or young adults with overweight, obesity, or severe obesity. Segmented regression with splines was used to model BMI trajectories.

RESULTS

Sixty-nine participants were classified as ever having severe obesity versus 34 who never had severe obesity. Trajectories and slopes did not differ by sex or race/ethnicity. Compared with those who never had severe obesity, BMI was higher in the group with severe obesity at all ages, and BMI slope was higher for those with severe obesity at age 14 (P = 0.002), with peak slope occurring later (18 years vs. 16 years) and higher (4.5 ± 0.5 kg/m² /y vs. 2.9 ± 0.5 kg/m² /y; P < 0.02). In the group without severe obesity, BMI fell below zero by the mid-20s (-0.3 ± 0.6 kg/m² /y); in those with severe obesity, BMI slope never reached zero (0.9 ± 0.5 kg/m² /y).

CONCLUSIONS

Youth with severe obesity, compared with their peers without, started with higher BMIs, had more rapid rates of BMI increase beginning at age 14, as well as a higher peak and longer period of increase, and never achieved weight stabilization.

Predictors of Severe Obesity in Low-Income, Predominantly Hispanic/Latino Children: The Texas Childhood Obesity Research Demonstration Study

INTRODUCTION

The objective of this study was to identify predictors of severe obesity in a low-income, predominantly Hispanic/Latino sample of children in Texas.

METHODS

This cross-sectional analysis examined baseline data on 517 children from the secondary prevention component of the Texas Childhood Obesity Research Demonstration (TX CORD) study; data were collected from September 2012 through February 2014. Self-administered surveys were used to collect data from parents of children who were aged 2 to 12 years, had a body mass index (BMI) in the 85th percentile or higher, and resided in Austin, Texas, or Houston, Texas. Multivariable logistic regression models adjusted for sociodemographic covariates were used to examine associations of children's early-life and maternal factors (large-for-gestational-age, exclusive breastfeeding for ≥4 months, maternal severe obesity [BMI ≥35.0 kg/m2]) and children's behavioral factors (fruit and vegetable consumption, physical activity, screen time) with severe obesity (BMI ≥120% of 95th percentile), by age group (2-5 y, 6-8 y, and 9-12 y).

RESULTS

Across all ages, 184 (35.6%) children had severe obesity. Among children aged 9 to 12 years, large-for-gestational-age at birth (odds ratio [OR] = 2.31; 95% confidence interval [CI], 1.13-4.73) was significantly associated with severe obesity. Maternal severe obesity was significantly associated with severe obesity among children aged 2 to 5 years (OR = 2.67; 95% CI, 1.10-6.47) and 9 to 12 years (OR = 4.12; 95% CI, 1.84-9.23). No significant association was observed between behavioral factors and severe obesity in any age group.

CONCLUSION

In this low-income, predominantly Hispanic/Latino sample of children, large-for-gestational-age and maternal severe obesity were risk factors for severe obesity among children in certain age groups. Promoting healthy lifestyle practices during preconception and prenatal periods could be an important intervention strategy for addressing childhood obesity.

Infant Growth following Maternal Participation in a Gestational Weight Management Intervention

BACKGROUND

Obesity is widespread and treatment strategies have demonstrated limited success. Changes to obstetrical practice in response to obesity may support obesity prevention by influencing offspring growth trajectories.

METHODS

This retrospective cohort study examined growth among infants born to obese mothers who participated in Nutrition in Pregnancy (NIP), a prenatal nutrition intervention at one urban hospital. NIP participants had Medicaid insurance and BMIs of 30 kg/m(2) or greater. We compared NIP infant growth to a historical control cohort, matched on maternal factors: age, race/ethnicity, prepregnancy BMI, parity, and history of prepregnancy hypertension or preterm birth.

RESULTS

Growth data were available for 61 NIP and 145 control infants. Most mothers were African American (94%). Mean maternal BMI was 39.9 kg/m(2) (standard deviation [SD], 5.6) for NIP participants and 38.8 kg/m(2) (SD, 6.0) for controls. Pregnancy outcomes, including preterm birth, gestational diabetes, and birth weight, did not differ between groups. NIP participants were more likely to attend a postpartum visit (69% vs. 52%; p value, 0.03). At 1 year, 17% of NIP infants and 15% of controls had weight-for-length (WFL) ≥95th percentile (p value, 0.66). Other markers of accelerated infant growth, including crossing WFL percentiles and peak infant BMI, did not differ between groups.

CONCLUSIONS

There was no difference in growth between infants whose mothers participated in a prenatal nutrition intervention and those whose mothers did not. Existing prenatal programs for obese women may be inadequate to prevent pediatric obesity without pediatric collaboration to promote family-centered support beyond pregnancy.

Risk Factors for Childhood Obesity in the First 1,000 Days: A Systematic Review

CONTEXT

Mounting evidence suggests that the origins of childhood obesity and related disparities can be found as early as the "first 1,000 days"-the period from conception to age 2 years. The main goal of this study is to systematically review existing evidence for modifiable childhood obesity risk factors present from conception to age 2 years.

EVIDENCE ACQUISITION

PubMed, Embase, and Web of Science were searched for studies published between January 1, 1980, and December 12, 2014, of childhood obesity risk factors present during the first 1,000 days. Prospective, original human subject, English-language research with exposure occurrence during the first 1,000 days and with the outcome of childhood overweight or obesity (BMI ≥85th percentile for age and sex) collected between age 6 months and 18 years were analyzed between December 13, 2014, and March 15, 2015.

EVIDENCE SYNTHESIS

Of 5,952 identified citations, 282 studies met inclusion criteria. Several risk factors during the first 1,000 days were consistently associated with later childhood obesity. These included higher maternal pre-pregnancy BMI, prenatal tobacco exposure, maternal excess gestational weight gain, high infant birth weight, and accelerated infant weight gain. Fewer studies also supported gestational diabetes, child care attendance, low strength of maternal-infant relationship, low SES, curtailed infant sleep, inappropriate bottle use, introduction of solid food intake before age 4 months, and infant antibiotic exposure as risk factors for childhood obesity.

CONCLUSIONS

Modifiable risk factors in the first 1,000 days can inform future research and policy priorities and intervention efforts to prevent childhood obesity.

WHO Child Growth Standards Are Often Incorrectly Applied to Children Born Preterm in Epidemiologic Research

In epidemiologic research, there is no standard approach for accounting for gestational age (GA) at birth when interpreting postnatal anthropometric data in analyses of cohorts that include children born preterm (CBP). A scoping review was conducted to describe analytical approaches to account for GA at birth when applying the WHO Growth Standards (WHO-GS) to anthropometric data in epidemiologic studies. We searched PubMed, Scopus, MEDLINE, Embase, and Web of Science for studies that applied WHO-GS, included CBP in the study population, had access to data within 1 mo of age, and were published between 2006 and 2015 in English. Of the 80 included studies that used the WHO-GS, 80% (64 of 80) included all children regardless of GA, whereas 20% (16 of 80) restricted analyses that used WHO-GS to term-born children. Among the 64 studies that included all children, 53 (83%) used chronological age and 11 (17%) used corrected age for CBP. Of the 53 studies that used chronological age, 12 (23%) excluded data that were likely contributed by CBP (e.g., very low birth weight or extremely low outlying z scores) and 19 (36%) adjusted for or stratified by GA at birth in regression analyses. In summary, researchers commonly apply WHO-GS to CBP, usually based on chronological age. Methodologic challenges of analyzing data from CBP in the application of WHO-GS were rarely explicitly addressed. Further efforts are required to establish acceptable approaches to account for heterogeneity in GA at birth in the analysis of post-term anthropometric data in epidemiologic research.