Validity of anthropometric equations to estimate infant fat mass at birth and in early infancy

Predicting body fat percentage at 36 weeks of postmenstrual age in infants born preterm: A diagnostic accuracy study

BACKGROUND

Current standards for assessing body composition can be costly and technically challenging. There is a need for a predictive equation that combines multiple clinical and anthropometric factors to predictbody composition outcomes at 36 weeks of postmenstrual age (PMA) or discharge.

METHODS

To develop a widely applicable equation that predicts body fat percentage in preterm infants, we analyzed anthropometric data collected prospectively from a cohort of infants born very preterm between 2017 and 2018. We integrated clinical variables significantly associated with adiposity into a predictive equation using Bayesian linear regression models and leave-one-out cross-validation.

RESULTS

We analyzed data from 86 infants born at 32 weeks of gestation or less (median gestational age, 30 weeks; mean birthweight, 1471 ± 270 g). Weight gain and increase in length per week from birth to 36 weeks of PMA, midarm circumference at 36 weeks of PMA, male sex, and higher enteral fluid intake (>180 ml/kg/day) were the strongest predictors of body fat percentage in the model with the highest predictive value (R2  = 0.65). The correlation between actual and predicted body fat percentage using this Bayesian model was high (r = 0.82).

CONCLUSIONS

Weight gain and increase in length per week from birth to 36 weeks of PMA, midarm circumference at 36 weeks of PMA, male sex, and enteral fluid intake are significant predictors of body fat percentage at 36 weeks of PMA in very preterm infants.

Development and validation of anthropometric-based fat-mass prediction equations using air displacement plethysmography in Mexican infants

BACKGROUND/OBJECTIVES

Fat-mass (FM) assessment since birth using valid methodologies is crucial since excessive adiposity represents a risk factor for adverse metabolic outcomes.

AIM

To develop infant FM prediction equations using anthropometry and validate them against air-displacement plethysmography (ADP).

SUBJECTS/METHODS

Clinical, anthropometric (weight, length, body-mass index -BMI-, circumferences, and skinfolds), and FM (ADP) data were collected from healthy-term infants at 1 (n = 133), 3 (n = 105), and 6 (n = 101) months enrolled in the OBESO perinatal cohort (Mexico City). FM prediction models were developed in 3 steps: 1) Variable Selection (LASSO regression), 2) Model behavior evaluation (12-fold cross-validation, using Theil-Sen regressions), and 3) Final model evaluation (Bland-Altman plots, Deming regression).

RESULTS

Relevant variables in the FM prediction models included BMI, circumferences (waist, thigh, and calf), and skinfolds (waist, triceps, subscapular, thigh, and calf). The R2 of each model was 1 M: 0.54, 3 M: 0.69, 6 M: 0.63. Predicted FM showed high correlation values (r ≥ 0.73, p < 0.001) with FM measured with ADP. There were no significant differences between predicted vs measured FM (1 M: 0.62 vs 0.6; 3 M: 1.2 vs 1.35; 6 M: 1.65 vs 1.76 kg; p > 0.05). Bias were: 1 M -0.021 (95%CI: -0.050 to 0.008), 3 M: 0.014 (95%CI: 0.090-0.195), 6 M: 0.108 (95%CI: 0.046-0.169).

CONCLUSION

Anthropometry-based prediction equations are inexpensive and represent a more accessible method to estimate body composition. The proposed equations are useful for evaluating FM in Mexican infants.

Body composition in term neonates of mothers with hypertensive disorders of pregnancy

BACKGROUND

Neonates of gravidas with hypertensive disorders of pregnancy (HDP) are at increased lifelong risk of cardiometabolic complications. Neonatal adiposity measured by body composition (BC) is a better surrogate of nutritional status than birth weight. Data comparing BC in term neonates of hypertensive and normotensive pregnant patients is lacking. Our objective was to compare body composition in both groups of neonates.

METHODS

This was a retrospective cohort study from March 2018 to June 2019 at our tertiary institution where term neonatal BC are routinely measured. Neonates of patients with HDP and matched controls were included. Skin fold thickness (SFT) and percent body fat (PBF) were calculated using a validated anthropometric formula and compared using Mann-Whitney U and chi-square tests.

RESULTS

One hundred and forty-two neonates of patients with HDP were compared to 150 controls. Demographic characteristics were similar except for higher pre-pregnancy BMI (29.7 ± 8.4 vs 26.75 ± 7.1, p = <0.01) in the HDP group. SFT was not significantly different (4.6 vs 4.4 mm, p = 0.09) but PBF was higher in the hypertensive group (13.15 vs 11.72, p = 0.01).

CONCLUSIONS

PBF is higher in neonates of mothers with HDP, which may contribute to an increased risk of cardiometabolic complications later in life.

IMPACT

Birth weight percentiles do not explain the predisposition to cardiovascular complications in offspring of hypertensive mothers. Body composition estimation may provide an explanation for this increased risk. Percent body fat is higher in term neonates of mothers with hypertensive disorders of pregnancy than neonates of normotensive mothers. Body composition is different in term neonates of mothers with hypertensive disorders of pregnancy.

Body composition from birth to 2 years in term healthy Indian infants measured by deuterium dilution: Effect of being born small for gestational age and early catch-up growth

OBJECTIVES

South Asian body composition is characterized by higher body fat at any given BMI. While this does not occur during fetal growth, it is important to understand if inappropriate fat accretion then begins in the first 2 years in Indian infants.

METHODS

The fat mass (FM) and fat-free mass (FFM) of healthy term newborns was evaluated at 12 days, 3.5 months, 1 year, and 2 years, by deuterium oxide (D₂O) dilution. The effect of being born small versus appropriate for gestational age (SGA vs. AGA), and accelerated early growth pattern on FM and FFM accretion was also investigated.

RESULTS

Newborns (262 total, 150 males) with mean birth weight of 2863 ± 418 g were enrolled. FM percentage (FM%) assessed by D₂O in 144, 166, 81, and 115 infants at 12 days, 3.5 months, 1 year, and 2 years respectively, was11.6 ± 6.8, 21.1 ± 7.0, 17.9 ± 8.2 and 22.4 ± 9.5%. Boys had higher FFM at all ages, but FM% was similar in both sexes. Children born SGA had similar FM index (FMI) but a lower FFM index (FFMI) at 2 years compared with those born AGA. Infants with catch-up growth between 0 and 2 years had higher FMI at 2 years compared to those without. Infants in the present study had a lower FM% and FMI till 1 year of age in comparison to previous studies from other countries, but had an increase in adiposity between 1 and 2 years, whereas in previous studies FM% remained stable or declined between 1 and 2 years of age.

CONCLUSION

There was an upward inflection in the curve of FM% and FMI between 1 and 2 years of age in the present study, which may represent an early adiposity rebound. Further longitudinal body composition data for Indian infants as well as those of other ethnicities but with low birth weight will clarify whether early accelerated growth pattern contributes to greater accrual of fat rather than lean mass during childhood.

Development and Validation of a Prediction Model for Infant Fat Mass

OBJECTIVES

To develop and validate a prediction model for fat mass in infants ≤12 kg using easily accessible measurements such as weight and length.

STUDY DESIGN

We used data from a pooled cohort of 359 infants age 1-24 months and weighing 3-12 kg from 3 studies across Southern California and New York City. The training data set (75% of the cohort) included 269 infants and the testing data set (25% of the cohort) included 90 infants age 1-24 months. Quantitative magnetic resonance was used as the standard measure for fat mass. We used multivariable linear regression analysis, with backwards selection of predictor variables and fractional polynomials for nonlinear relationships to predict infant fat mass (from which lean mass can be estimated by subtracting resulting estimates from total mass) in the training data set. We used 5-fold cross-validation to examine overfitting and generalizability of the model's predictive performance. Finally, we tested the adjusted model on the testing data set.

RESULTS

The final model included weight, length, sex, and age, and had high predictive ability for fat mass with good calibration of observed and predicted values in the training data set (optimism-adjusted R²: 92.1%). Performance on the test dataset showed promising generalizability (adjusted R²: 85.4%). The mean difference between observed and predicted values in the testing dataset was 0.015 kg (-0.043 to -0.072 kg; 0.7% of the mean).

CONCLUSIONS

Our model accurately predicted infant fat mass and could be used to improve the accuracy of assessments of infant body composition for effective early identification, surveillance, prevention, and management of obesity and future chronic disease risk.

Differences in body composition and growth persist postnatally in fetuses diagnosed with severe compared to mild fetal growth restriction

BACKGROUND

Fetal growth restriction (FGR) is most commonly diagnosed in pregnancy if the estimated fetal weight (EFW) is <  10th%. Those with abnormal Doppler velocimetry, indicating placental insufficiency and pathological FGR, demonstrate reduced fat and lean mass compared to both normally growing fetuses and FGR fetuses with normal Dopplers. The aim of this study was to determine how severity of FGR and abnormal Doppler velocimetry impacts neonatal body composition. Among a cohort of fetuses with an EFW <  10th%, we hypothesized that those with abnormal Dopplers and/or EFW <  3rd% would have persistent reductions in lean body mass and fat mass extending into the neonatal period compared to fetuses not meeting those criteria.

METHODS

A prospective cohort of FGR fetuses with an estimated fetal weight (EFW) <  10th% was categorized as severe (EFW <  3rd% and/or abnormal Dopplers; FGR-S) versus mild (EFW 3-10th% ; FGR-M). Air Displacement Plethysmography and anthropometrics were performed at birth and/or within the first 6-8 weeks of life.

RESULTS

FGR-S versus FGR-M were born one week earlier (P = 0.0024), were shorter (P = 0.0033), lighter (P = 0.0001) with smaller weight-for-age Z-scores (P = 0.0004), had smaller head circumference (P = 0.0004) and lower fat mass (P = 0.01) at birth. At approximately 6-8 weeks postmenstrual age, weight, head circumference, and fat mass were similar but FGR-S neonates were shorter (P = 0.0049) with lower lean mass (P = 0.0258).

CONCLUSION

Doppler velocimetry abnormalities in fetuses with an EFW <  10th% identified neonates who were smaller at birth and demonstrated catch-up growth by 6-8 weeks of life that favored fat mass accretion over lean mass and linear growth.

Anthropometric models to estimate fat mass at 3 days, 15 and 54 weeks

BACKGROUND

Currently available infant body composition measurement methods are impractical for routine clinical use. The study developed anthropometric equations (AEs) to estimate fat mass (FM, kg) during the first year using air displacement plethysmography (PEA POD® Infant Body Composition System) and Infant quantitative magnetic resonance (Infant-QMR) as criterion methods.

METHODS

Multi-ethnic full-term infants (n = 191) were measured at 3 days, 15 and 54 weeks. Sex, race/ethnicity, gestational age, age (days), weight-kg (W), length-cm (L), head circumferences-cm (HC), skinfold thicknesses mm [triceps (TRI), thigh (THI), subscapular (SCP), and iliac (IL)], and FM by PEA POD® and Infant-QMR were collected. Stepwise linear regression determined the model that best predicted FM.

RESULTS

Weight, length, head circumference, and skinfolds of triceps, thigh, and subscapular, but not iliac, significantly predicted FM throughout infancy in both the Infant-QMR and PEA POD models. Sex had an interaction effect at 3 days and 15 weeks for both the models. The coefficient of determination [R² ] and root mean square error were 0.87 (66 g) at 3 days, 0.92 (153 g) at 15 weeks, and 0.82 (278 g) at 54 weeks for the Infant-QMR models; 0.77 (80 g) at 3 days and 0.82 (195 g) at 15 weeks for the PEA POD models respectively.

CONCLUSIONS

Both PEA POD and Infant-QMR derived models predict FM using skinfolds, weight, head circumference, and length with acceptable R² and residual patterns.

Estimation of neonatal body fat percentage predicts neonatal hypothermia better than birthweight centile

INTRODUCTION

PEA POD™ air displacement plethysmography quickly and noninvasively estimates neonatal body fat percentage (BF%). Low PEA POD™ BF% predicts morbidity better than classification as small-for-gestational-age (SGA; <10th centile), but PEA PODs are not widely available. We examined whether skinfold measurements could effectively identify neonates at risk; comparing skinfold BF%, PEA POD™ BF% and birthweight centiles' prediction of hypothermia - a marker of reduced in utero nutrition.

METHODS

Neonates had customized birthweight centiles calculated, and BF% prospectively estimated by: (i) triceps and subscapular skinfolds using sex-specific equations; and (ii) PEA POD™. Medical record review identified hypothermic (<36.5 °C) episodes.

RESULTS

42/149 (28%) neonates had hypothermia. Skinfold BF%, with an area under the curve (AUC) of 0.66, predicted hypothermia as well as PEA POD™ BF% (AUC = 0.62) and birthweight centile (AUC = 0.61). Birthweight <10^th centile demonstrated 11.9% sensitivity, 38.5% positive predictive value (PPV) and 92.5% specificity for hypothermia. At equal specificity, skinfold and PEA POD™ BF% more than doubled sensitivity (26.2%) and PPV increased to 57.9%.

CONCLUSION

Neonatal BF% performs better to predict neonatal hypothermia than birthweight centile, and may be a better measure of true fetal growth restriction. Estimation of neonatal BF% by skinfold measurements is an inexpensive alternative to PEA POD™.

Elevated lipid oxidation is associated with exceeding gestational weight gain recommendations and increased neonatal anthropometrics: a cross-sectional analysis

BACKGROUND

Deviations from gestational weight gain (GWG) recommendations are associated with unfavorable maternal and neonatal outcomes. There is a need to understand how maternal substrate metabolism, independent of weight status, may contribute to GWG and neonatal outcomes. The purpose of this study was to explore the potential link between maternal lipid oxidation rate, GWG, and neonatal anthropometric outcomes.

METHODS

Women (N = 32) with a lean pre-pregnancy BMI were recruited during late pregnancy and substrate metabolism was assessed using indirect calorimetry, before and after consumption of a high-fat meal. GWG was categorized as follows: inadequate, adequate, or excess. Shortly after delivery (within 48 h), neonatal anthropometrics were obtained.

RESULTS

Using ANOVA, we found that fasting maternal lipid oxidation rate (grams/minute) was higher (p = 0.003) among women with excess GWG (0.1019 ± 0.0416) compared to women without excess GWG (inadequate = 0.0586 ± 0.0273, adequate = 0.0569 ± 0.0238). Findings were similar when lipid oxidation was assessed post-meal and also when expressed relative to kilograms of fat free mass. Absolute GWG was positively correlated to absolute lipid oxidation expressed in grams/minute at baseline (r = 0.507, p = 0.003), 2 h post-meal (r = 0.531, p = 0.002), and 4 h post-meal (r = 0.546, p = 0.001). Fasting and post-meal lipid oxidation (grams/minute) were positively correlated to neonatal birthweight (fasting r = 0.426, p = 0.015; 2-hour r = 0.393, p = 0.026; 4-hour r = 0.540, p = 0.001) and also to neonatal absolute fat mass (fasting r = 0.493, p = 0.004; 2-hour r = 0.450, p = 0.010; 4-hour r = 0.552, p = 0.001).

CONCLUSIONS

A better understanding of the metabolic profile of women during pregnancy may be critical in truly understanding a woman's risk of GWG outside the recommendations. GWG counseling during prenatal care may need to be tailored to women based not just on their weight status, but other metabolic characteristics.

No sustained effects of an intervention to prevent excessive GWG on offspring fat and lean mass at 54 weeks: Yet a greater head circumference persists

BACKGROUND

LIFT (Lifestyle Intervention for Two) trial found that intervening in women with overweight and obesity through promoting healthy diet and physical activity to control gestational weight gain (GWG) resulted in neonates with greater weight, lean mass and head circumference and similar fat mass at birth. Whether these neonate outcomes are sustained at 1-year was the focus of this investigation.

METHODS

Measures included body composition by PEA POD air displacement plethysmography (ADP) and Echo Infant quantitative magnetic resonance (QMR) and head circumference at birth (n = 169), 14 (n = 136) and 54 weeks (n = 137). Differences in fat and lean mass between lifestyle intervention (LI) and Usual care (UC) groups were examined using ANCOVA adjusting for maternal age and BMI, GWG, offspring sex and age.

RESULTS

Compared to UC, LI infants had similar weight (112 ± 131 g; P = .40), fat mass (14 ± 80 g; P = .86), lean mass (100 ± 63 g; P = .12) at 14 weeks and similar weight (168 ± 183 g; P = .36), fat mass (148 ± 124 g; P = .24), lean mass (117 ± 92 g; P = .21) at 54 weeks. Head circumference was greater in LI at 54 weeks (0.46 ± 2.1 cm P = .03).

CONCLUSIONS

Greater lean mass observed at birth in LI offspring was not sustained at 14 and 54 weeks, whereas the greater head circumference in LI offspring persisted at 54 weeks.

Do Lifestyle Interventions in Pregnant Women with Overweight or Obesity Have an Effect on Neonatal Adiposity? A Systematic Review with Meta-Analysis

Excessive body fat at birth is a risk factor for the development of childhood obesity. The aim of the present systematic review with meta-analysis was to evaluate the effect of lifestyle interventions in pregnant women with overweight or obesity on neonatal adiposity. The PubMed, Embase, Web of Science, Scopus, and LILACS databases were used as information sources. Original articles from randomized clinical trials of lifestyle intervention studies on pregnant women with excessive body weight and the effect on neonatal adiposity were considered eligible. The risk of bias was assessed using Cochrane criteria. The meta-analysis was calculated using the inverse variance for continuous data expressed as mean difference (MD), using the random effect model with a 95% confidence interval (CI). The outcomes were submitted to the GRADE evaluation. Of 2877 studies, four were included in the qualitative and quantitative synthesis (n = 1494). All studies were conducted in developed countries, with three including pregnant women with overweight or obesity, and one only pregnant women with obesity. The interventions had no effect on neonatal adiposity [Heterogeneity = 56%, MD = −0.21, CI = (−0.92, 0.50)] with low confidence in the evidence, according to GRADE. Studies are needed in low- and medium-developed countries with different ethnic-racial populations. PROSPERO (CRD42020152489).

Maternal dietary fat intake during pregnancy and newborn body composition

OBJECTIVE

Increased infant birth weight and adiposity are associated with an altered risk of adult chronic diseases. The objective was to investigate the association between maternal dietary fat intake during pregnancy and newborn adiposity.

STUDY DESIGN

The study included 79 singleton pregnancies. Associations between maternal dietary fat intake during each trimester and infant adiposity at birth were assessed.

RESULT

Average total grams of maternal total dietary fat and unsaturated fat intake during pregnancy correlated with infant percent body fat after adjusting for potential confounding variables (r = 0.23, p = 0.045; r = 0.24, p = 0.037). Maternal average daily intake of total fat, saturated fat, and unsaturated fat during the second trimester of pregnancy were each associated with infant percent body fat (r = 0.25, p = 0.029; r = 0.23, p = 0.046; r = 0.25, p = 0.031; respectively).

CONCLUSIONS

The second trimester of pregnancy is a key time period for fetal adipose tissue metabolic programming and therefore a target for nutritional intervention.

Body adiposity and oral feeding outcomes in infants: a pilot study

BACKGROUND

Prevalence of oral feeding difficulties in high-risk infants is increasing. Desire to take orally can be influenced by hunger and satiety, which may influence growth and body fat.

OBJECTIVE

To determine the association between body adiposity and infant oral feeding.

METHODS

Retrospective case-control study of infants ≥37-week postmenstrual age (PMA). Infants on tube feeding (cases) compared to birth gestation-matched infants on full oral feeding (controls). Body composition was determined by air displacement plethysmography.

RESULTS

Overall, 16 cases vs. 16 controls. At study, cases vs. controls had similar PMA, weight and length z-scores, and calorie intake. The mean oral intake was significantly less in cases vs. controls (66 vs. 168 ml/kg/day, p < 0.001). Cases had significantly higher percentage of fat mass (18.7 vs. 10.9) and fat-mass z-score (1.62 vs. 0.08) (p < 0.05), but similar fat-free mass vs. controls. Five case infants required gastrostomy.

CONCLUSIONS

Higher body adiposity may worsen the infant oral feeding outcomes.

Effect of prenatal lifestyle intervention on maternal postpartum weight retention and child body mass index z-score at 36 months

BACKGROUND/OBJECTIVES

We previously reported results from a randomized trial showing that a behavioral intervention during pregnancy reduced excess gestational weight gain but did not impact maternal weight at 12 months. We now examine the longer-term effects of this prenatal intervention on maternal postpartum weight retention and toddler body-mass-index z scores (BMIz) over 36 months.

SUBJECTS/METHODS

Pregnant women (N = 264; 13.7 weeks' gestation; 41.6% Hispanic) with overweight or obesity were randomized into usual care or prenatal intervention. Anthropometric assessments in mothers and toddlers occurred at baseline, 35 weeks' gestation and after delivery at 6, 12, 18, 24, and 36 months.

RESULTS

At 36 months, prenatal intervention vs. usual care had no significant effect on the proportion of participants who returned to their early pregnancy weight or below (33.3% vs. 39.5%; p = 0.12) and had no effect on the magnitude of weight retained (2.8 [0.8, 4.8] vs 3.0 kg [1.0, 4.9], respectively; mean difference = 0.14 [-3.0, 2.7]). There was also no statistically significant intervention vs. usual care effect on infant BMIz or skinfold changes over time; toddler BMIz increased by 1.4 [-1.7, 1.0] units in the intervention group and 1.6 [-1.2, 1.8] units in the usual care group from delivery to 36 months (difference = 0.16 [-0.32. 0.63]). The proportion of toddlers at risk for obesity at 36 months was similar in intervention and usual care groups (28/77 [36.4%] vs 30/80 [37.5%]; p = 0.77).

CONCLUSIONS

Compared with usual care, lifestyle intervention during pregnancy resulted in similar maternal and toddler anthropometric outcomes at 36-months postpartum in a diverse US sample of women with overweight and obesity. To sustain improved maternal weight management initiated during pregnancy, continued intervention during the postpartum years may be needed.

Metabolic flexibility during late pregnancy is associated with neonatal adiposity

The aim of this study was to determine the relationships between maternal metabolic flexibility during pregnancy and neonatal health outcomes. Percent change in lipid oxidation (before and after a high-fat meal) was calculated as the measure of "metabolic flexibility". Neonatal adiposity was assessed within 48 h of delivery by skinfold anthropometry. Metabolic flexibility (r = -0.271, p = 0.034), maternal HOMA-IR (r = 0.280, p = 0.030), and maternal body mass index (r = 0.299, p = 0.018) were correlated with neonatal subscapular skinfold (i.e., measure of neonatal adiposity). Clinical Trail Registration Number: NCT03504319. Novelty: This is the first study to link maternal metabolic flexibility, body mass index, and insulin resistance during pregnancy to neonatal adiposity at parturition.

Methods to Assess Fat Mass in Infants and Young Children: A Comparative Study Using Skinfold Thickness and Air-Displacement Plethysmography

Background: Traditionally, fat mass is estimated using anthropometric models. Air-displacement plethysmography (ADP) is a relatively new technique for determining fat mass. There is limited information on the agreement between these methods in infants and young children. Therefore we aimed to longitudinally compare fat mass percentage values predicted from skinfold thicknesses (SFTs) and ADP in healthy infants and young children. Methods: Anthropometry and body composition were determined at the ages of 1, 4, and 6 months and 2 years. We quantified the agreement between the two methods using the Bland–Altman procedure, linear mixed-model analysis, and intra-class correlation coefficients (ICC). Results: During the first 6 months of life, fat mass% predicted with SFT was significantly different from that measured with ADP in healthy, term-born infants (n = 245). ICCs ranged from 0.33 (at 2 years of age) and 0.47 (at 4 months of age). Although the mean difference (bias) between the methods was low, the Bland–Altman plots showed proportional differences at all ages with wide limits of agreement. Conclusions: There is poor agreement between ADP and SFTs for estimating fat mass in infancy or early childhood. The amount of body fat was found to influence the agreement between the methods.

A comparative study using dual-energy X-ray absorptiometry, air displacement plethysmography, and skinfolds to assess fat mass in preterms at term equivalent age

The aim of this study was to compare whole body composition, generated by air displacement plethysmography (ADP) and dual-energy X-ray absorptiometry (DXA), and to evaluate the potential predictive value of the sum of skinfolds (∑SFT) for whole body composition, in preterm infants at term equivalent age. A convenience sample of sixty-five preterm infants with a mean (SD) gestational age of 29 (1.6) weeks was studied at term equivalent age. Fat mass measured by DXA and ADP were compared and the ability of the ∑SFT to predict whole body fat mass was investigated. There was poor agreement between fat mass percentage measured with ADP compared with DXA (limits of agreement: - 4.8% and 13.7%). A previously modeled predictive equation with the ∑SFT as a predictor for absolute fat mass could not be validated. Corrected for confounders, the ∑SFT explained 42% (ADP, p = 0.001) and 75% (DXA, p = 0.001) of the variance in fat mass percentage.Conclusions: The ∑SFT was not able to accurately predict fat mass and ADP and DXA did not show comparable results. It remains to be elucidated whether or not DXA provides more accurate assessment of whole body fat mass than ADP in preterm infants.Trial registration: NTR5311 What is Known: • Diverse methods are used to assess fat mass in preterm infants. What is New: • This study showed that there is poor agreement between dual-energy X-ray absorptiometry, air displacement plethysmography, and skinfold thickness measurements. • Our results affirm the need for consensus guidelines on how to measure fat mass in preterm infants, to improve the assimilation of data from different studies and the implementation of the findings from those studies.

Anthropometry-based prediction of body fat in infants from birth to 6 months: the Baby-bod study

BACKGROUND/OBJECTIVES

Prediction equations generated from anthropometric measures are frequently used to quantify paediatric body composition. We tested the agreeability and predictive power of select (Lingwood and Aris) fat mass prediction equations against body fat measured via ADP; and generated and evaluated new anthropometry-based models for use in the first 6 months of life.

SUBJECTS/METHODS

Data were obtained from 278 white European Australian infants at birth, 3 and 6 months. Prediction models (i.e. Baby-bod models) were generated for each time point via stepwise linear regression and compared for agreeability with ADP via limits of agreement, mean difference and total bias in Bland-Altman analyses. Predictive power of all equations in comparison to ADP were assessed using linear regression analysis.

RESULTS

Overall, there was poor agreeability between percent body fat predicted via published equations and ADP. Proportional bias was detected for both methods (i.e. published equations and Baby-bod models) of body fat prediction. At birth, both Lingwood and BB0 equations overestimated percent body fat at the lower end of the FM spectrum. This trend was repeated at 3 months with all equations displaying a propensity to overestimate body fat at lower FM levels and underestimate at higher FM levels.

CONCLUSIONS

The results indicate that anthropometry, although less costly and relatively easier to implement, does not always produce comparable results with objective measures such as ADP. Given the importance of the accurate assessment of physical growth, including body composition in early life, it is timely to recommend the increased utilisation of techniques such as ADP.

Evaluation of anthropometric equations developed to estimate neonates' body composition: a systematic review

This article aims to evaluate the anthropometric equations developed by selected studies in order to estimate the body composition of neonates. The systematic review consisted in the research of published articles in the following databases: PubMed, Brazilian Virtual Health Library, Embase and ScienceDirect by utilizing the following descriptors: "fat mass, fat free mass, anthropometry, air displacement plethysmography, validation, neonate". For doing so, the PRISMA protocol has been utilized. The bibliographical research resulted in 181 articles. However, only eight were selected for the present review because repetition in different databases and having been performed in adults, during pregnancy, in athletes, in preterm and children. There was discrepancy in terms of study method, mainly over the variables of the anthropometric equations, age and ethnicity of the neonates. All studies used the plethysmography method as a reference apart from one study. Only four studies had their equations validated. The studies that developed anthropometric models for estimating the body composition of neonates are scarce, and the use of these equations needs to be conducted carefully in order to avoid errors in nutritional diagnosis.

Direct Comparison of (Anthropometric) Methods for the Assessment of Body Composition

OBJECTIVE

Several methods for the assessment of body composition exist, yet they yield different results. The present study aimed to assess the extent of these differences on a sample of young, healthy subjects. We hypothesised that differences in body composition results obtained with different methods will vary to the extent that a subject can be misclassified into different nutritional categories.

RESEARCH METHODS AND PROCEDURES

Underwater weighing (UWW), bioelectrical impedance analysis (BIA), anthropometry (ANT), and dual-energy X-ray absorptiometry (DXA) were used to assess body composition. An extensive list of ANT regression equations (or sets of equations) was analysed in terms of accuracy and precision relative to DXA.

RESULTS

When DXA-determined body fat (BF) values were taken as a reference, UWW overestimated BF in both genders. In contrast, BIA (measured with a given bioimpedance analyser) underestimated BF in females, although BIA-determined BF did not differ from DXA in males. A huge difference in BF estimates (8-29% for females and 6-29% for males, for DXA-determined BF of 25.5% and 13.9% for females in males, respectively) was observed across a number of ANT regression equations; yet, ANT proved not to be inferior to DXA, provided that regression equations with the highest combinations of accuracy and precision were chosen.

CONCLUSIONS

The study proved grounds for comparison of body composition results of young, healthy subjects, obtained with different methods and across a wide range of ANT regression equations. It also revealed a list of the most appropriate ANT regression equations for the selected sample and reported their accuracy and precision.

Evaluating body composition in infancy and childhood: A comparison between 4C, QMR, DXA, and ADP

BACKGROUND

Accurate and precise methods to measure of body composition in infancy and childhood are needed.

OBJECTIVES

This study evaluated differences and precision of three methods when compared with the four-compartment (4C) model for estimating fat mass (FM).

METHODS

FM of children (age 14 days to 6 years of age, N = 346) was obtained using quantitative nuclear magnetic resonance (QMR, EchoMRI-AH), air-displacement plethysmography (ADP, PeaPod, less than or equal to 8 kg, BodPod age 6 years or older), and dual-energy X-ray absorptiometry (DXA, Hologic QDR). The 4C model was computed. Correlation, concordance, and Bland-Altman analyses were performed.

RESULTS

In infants, PeaPod had high individual FM accuracy, whereas DXA had high group FM accuracy compared with 4C. In children, DXA had high group and individual FM accuracies compared with 4C. QMR underestimated group FM in infants and children (300 and 510 g, respectively). The instrument FM precision was best for QMR (10 g) followed by BodPod (34 g), PeaPod (38 g), and DXA (45 g).

CONCLUSIONS

In infants, PeaPod was the best method to estimate individual FM whereas DXA was best to estimate group FM. In children, DXA was best to estimate individual and group FM. QMR had the highest instrument precision.

Social and economic factors, maternal behaviours in pregnancy and neonatal adiposity in the PANDORA cohort

BACKGROUND

Australian Indigenous women experience high rates of social disadvantage and type 2 diabetes (T2D) in pregnancy, but it is not known how social factors and maternal behaviours impact neonatal adiposity in offspring of women with hyperglycaemia in pregnancy.

METHODS

Participants were Indigenous (n = 404) and Europid (n = 240) women with gestational diabetes mellitus (GDM) or T2D in pregnancy and their offspring in the Pregnancy and Neonatal Diabetes Outcomes in Remote Australia (PANDORA) study. Social, economic factors, and maternal behaviours were measured in pregnancy and six neonatal anthropometric outcomes were examined after birth.

RESULTS

On univariate analysis, maternal education < 12 years (p = 0.03), unemployment (p = 0.001), welfare income vs no welfare income (p = 0.001), lower area based socio-economic score (p < 0.001), and fast food intake > 2 times/week (p = 0.002) were associated with increased sum of skinfolds (SSF) in offspring. Smoking was significantly associated with a reduction in anthropometric measures, except SSF. In multivariable models adjusted for ethnicity, BMI and hyperglycaemia, social and economic factors were no longer significant predictors of neonatal outcomes. Smoking was independently associated with a reduction in length, head circumference and fat free mass. Frequent fast food intake remained independently associated with SSF (β-coefficient 1.08 mm, p = 0.02).

CONCLUSION

In women with hyperglycaemia in pregnancy, social factors were associated with neonatal adiposity, particularly skinfold measures. Promoting smoking cessation and limited intake of energy-dense, nutrient-poor foods in pregnancy are important to improve neonatal adiposity and lean mass outcomes. Addressing inequities in social and economic factors are likely to be important, particularly for Indigenous women or women experiencing social disadvantage.

Cord blood metabolic markers are strong mediators of the effect of maternal adiposity on fetal growth in pregnancies across the glucose tolerance spectrum: the PANDORA study

AIMS/HYPOTHESIS

We aimed to assess associations between cord blood metabolic markers and fetal overgrowth, and whether cord markers mediated the impact of maternal adiposity on neonatal anthropometric outcomes among children born to Indigenous and Non-Indigenous Australian women with normal glucose tolerance (NGT), gestational diabetes mellitus (GDM) and pregestational type 2 diabetes mellitus.

METHODS

From the Pregnancy and Neonatal Outcomes in Remote Australia (PANDORA) study, an observational cohort of 1135 mother-baby pairs, venous cord blood was available for 645 singleton babies (49% Indigenous Australian) of women with NGT (n = 129), GDM (n = 419) and type 2 diabetes (n = 97). Cord glucose, triacylglycerol, HDL-cholesterol, C-reactive protein (CRP) and C-peptide were measured. Multivariable logistic and linear regression were used to assess the associations between cord blood metabolic markers and the outcomes of birthweight z score, sum of skinfold thickness (SSF), being large for gestational age (LGA) and percentage of body fat. Pathway analysis assessed whether cord markers mediated the associations between maternal and neonatal adiposity.

RESULTS

Elevated cord C-peptide was significantly associated with increasing birthweight z score (β 0.57 [95% CI 0.42, 0.71]), SSF (β 0.83 [95% CI 0.41, 1.25]), percentage of body fat (β 1.20 [95% CI 0.69, 1.71]) and risk for LGA [OR 3.14 [95% CI 2.11, 4.68]), after adjusting for age, ethnicity and diabetes type. Cord triacylglycerol was negatively associated with birthweight z score for Indigenous Australian women only. No associations between cord glucose, HDL-cholesterol and CRP >0.3 mg/l (2.9 nmol/l) with neonatal outcomes were observed. C-peptide mediated 18% (95% CI 13, 36) of the association of maternal BMI with LGA and 11% (95% CI 8, 17) of the association with per cent neonatal fat.

CONCLUSIONS/INTERPRETATION

Cord blood C-peptide is an important mediator of the association between maternal and infant adiposity, across the spectrum of maternal glucose tolerance.

Extremely Preterm Infants Have a Higher Fat Mass Percentage in Comparison to Very Preterm Infants at Term-Equivalent Age

Background: Early nutritional support of preterm infants is important because it influences long-term health and development. Body composition has an influence on cardiovascular disease, metabolic syndrome, and neurocognitive outcome in the long term. Objective: To assess body composition in preterm infants <32 weeks of gestation at term-equivalent age and to analyze the influence of an optimized nutritional approach. Methods: This is a prespecified secondary outcome analysis of a prospective observational study comparing the body composition in regard to gestational age. The preterm infants were classified according to gestational age as extremely preterm infants (<28 weeks gestation at birth) and very preterm infants (≥28 weeks gestation at birth) and according to weight percentile as appropriate for gestational age and small for gestational age. Body composition was determined by air displacement plethysmography using the PEA POD. The preterm infants obtained nutrition according to the ESPGHAN 2010 Guidelines. Results: Seventy-four preterm infants were analyzed. The mean (SD) gestational age was 28.7 (2.4) weeks, and birth weight was 1,162 (372) g. Fat mass percentage was significantly higher in extremely preterm infants in comparison to very preterm infants [17.0, 95% confidence interval (CI) 15.9-18.1 vs. 15.5, 95% CI 14.7-16.2]. There was no significant difference of fat mass percentage according to weight percentiles. Conclusions: Extremely preterm infants had a significantly higher fat mass percentage compared to very preterm infants at term-equivalent age. There was no significant difference of fat mass percentage according to weight percentiles.

Maternal body mass index, excess gestational weight gain, and diabetes are positively associated with neonatal adiposity in the Pregnancy and Neonatal Diabetes Outcomes in Remote Australia (PANDORA) study

BACKGROUND

In-utero exposures likely influence the onset and severity of obesity in youth. With increasing rates of type 2 diabetes mellitus (T2DM) and maternal adiposity in pregnancy globally, it is important to assess the impact of these factors on neonatal adipose measures.

OBJECTIVES

To evaluate the contribution of maternal ethnicity, body mass index (BMI), gestational weight gain, and hyperglycaemia to neonatal adiposity.

METHODS

Pregnancy and Neonatal Diabetes Outcomes in Remote Australia (PANDORA) is a longitudinal cohort study of Australian mother and neonate pairs. In this analysis, Indigenous (n = 519) and Europid (n = 358) women were included, of whom 644 had hyperglycaemia (type 2 diabetes [T2DM], diabetes in pregnancy [DIP], or gestational diabetes [GDM]). Associations between maternal ethnicity, hyperglycaemia, BMI and gestational weight gain, and the neonatal outcomes of length, head circumference, sum of skinfolds, total body fat, and percentage body fat were examined. Models were adjusted for maternal age, smoking status, parity, education, neonatal gender, and gestational age.

RESULTS

Among those with hyperglycaemia in pregnancy, Indigenous women had a higher proportion of T2DM and DIP (36%, 13%) compared with Europid women (4%, 3%). In multivariate analysis, maternal T2DM (compared with no hyperglycaemia), BMI during pregnancy, and excess compared with appropriate gestational weight gain, were significantly associated with greater neonatal measures. DIP was associated with greater sum of skinfolds, total body fat, and percentage body fat. Indigenous ethnicity was associated with greater sum of skinfolds.

CONCLUSIONS

Maternal BMI, excess gestational weight gain, and hyperglycaemia operated as independent factors influencing neonatal adiposity. Interventions addressing these factors are needed to reduce neonatal adiposity.

Longitudinal changes in maternal anthropometry in relation to neonatal anthropometry

OBJECTIVE

To characterize the association of longitudinal changes in maternal anthropometric measures with neonatal anthropometry and to assess to what extent late-gestational changes in maternal anthropometry are associated with neonatal body composition.

DESIGN

In a prospective cohort of pregnant women, maternal anthropometry was measured at six study visits across pregnancy and after birth, neonates were measured and fat and lean mass calculated. We estimated maternal anthropometric trajectories and separately assessed rate of change in the second (15-28 weeks) and third trimester (28-39 weeks) in relation to neonatal anthropometry. We investigated the extent to which tertiles of third-trimester maternal anthropometry change were associated with neonatal outcomes.

SETTING

Women were recruited from twelve US sites (2009-2013).ParticipantsNon-obese women with singleton pregnancies (n 2334).

RESULTS

A higher rate of increase in gestational weight gain was associated with larger-birth-weight infants with greater lean and fat mass. In contrast, higher rates of increase in maternal anthropometry measures were not associated with infant birth weight but were associated with decreased neonatal lean mass. In the third trimester, women in the tertile of lowest change in triceps skinfold (-0·57 to -0·06 mm per week) had neonates with 35·8 g more lean mass than neonates of mothers in the middle tertile of rate of change (-0·05 to 0·06 mm per week).

CONCLUSIONS

The rate of change in third-trimester maternal anthropometry measures may be related to neonatal lean and fat mass yet have a negligible impact on infant birth weight, indicating that neonatal anthropometry may provide additional information over birth weight alone.

Air displacement plethysmography (pea pod) in full-term and pre-term infants: a comprehensive review of accuracy, reproducibility, and practical challenges

Air displacement plethysmography (ADP) has been widely utilised to track body composition because it is considered to be practical, reliable, and valid. Pea Pod is the infant version of ADP that accommodates infants up to the age of 6 months and has been widely utilised to assess the body composition of full-term infants, and more recently pre-term infants. The primary goal of this comprehensive review is to 1) discuss the accuracy/reproducibility of Pea Pod in both full- and pre-term infants, 2) highlight and discuss practical challenges and potential sources of measurement errors in relation to Pea Pod operating principles, and 3) make suggestions for future research direction to overcome the identified limitations.

An anthropometric approach to characterising neonatal morbidity and body composition, using air displacement plethysmography as a criterion method

Background

With the greatest burden of infant undernutrition and morbidity in low and middle income countries (LMICs), there is a need for suitable approaches to monitor infants in a simple, low-cost and effective manner. Anthropometry continues to play a major role in characterising growth and nutritional status.

Methods

We developed a range of models to aid in identifying neonates at risk of malnutrition. We first adopted a logistic regression approach to screen for a composite neonatal morbidity, low and high body fat (BF%) infants. We then developed linear regression models for the estimation of neonatal fat mass as an assessment of body composition and nutritional status.

Results

We fitted logistic regression models combining up to four anthropometric variables to predict composite morbidity and low and high BF% neonates. The greatest area under receiver-operator characteristic curves (AUC with 95% confidence intervals (CI)) for identifying composite morbidity was 0.740 (0.63, 0.85), resulting from the combination of birthweight, length, chest and mid-thigh circumferences. The AUCs (95% CI) for identifying low and high BF% were 0.827 (0.78, 0.88) and 0.834 (0.79, 0.88), respectively.

For identifying composite morbidity, BF% as measured via air displacement plethysmography showed strong predictive ability (AUC 0.786 (0.70, 0.88)), while birthweight percentiles had a lower AUC (0.695 (0.57, 0.82)). Birthweight percentiles could also identify low and high BF% neonates with AUCs of 0.792 (0.74, 0.85) and 0.834 (0.79, 0.88). We applied a sex-specific approach to anthropometric estimation of neonatal fat mass, demonstrating the influence of the testing sample size on the final model performance.

Conclusions

These models display potential for further development and evaluation in LMICs to detect infants in need of further nutritional management, especially where traditional methods of risk management such as birthweight for gestational age percentiles may be variable or non-existent, or unable to detect appropriately grown, low fat newborns.

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.