Estimation of fat-free mass in Asian neonates using bioelectrical impedance analysis

Determination of resistance at zero and infinite frequencies in bioimpedance spectroscopy for assessment of body composition in babies

Objective. Bioimpedance spectroscopy (BIS) is a popular technique for the assessment of body composition in children and adults but has not found extensive use in babies and infants. This due primarily to technical difficulties of measurement in these groups. Although improvements in data modelling have, in part, mitigated this issue, the problem continues to yield unacceptably high rates of poor quality data. This study investigated an alternative data modelling procedure obviating issues associated with BIS measurements in babies and infants.Approach.BIS data are conventionally analysed according to the Cole model describing the impedance response of body tissues to an appliedACcurrent. This approach is susceptible to errors due to capacitive leakage errors of measurement at high frequency. The alternative is to model BIS data based on the resistance-frequency spectrum rather than the reactance-resistance Cole model thereby avoiding capacitive error impacts upon reactance measurements.Main results.The resistance-frequency approach allowed analysis of 100% of data files obtained from BIS measurements in 72 babies compared to 87% successful analyses with the Cole model. Resistance-frequency modelling error (percentage standard error of the estimate) was half that of the Cole method. Estimated resistances at zero and infinite frequency were used to predict body composition. Resistance-based prediction of fat-free mass (FFM) exhibited a 30% improvement in the two-standard deviation limits of agreement with reference FFM measured by air displacement plethysmography when compared to Cole model-based predictions.Significance.This study has demonstrated improvement in the analysis of BIS data based on the resistance frequency response rather than conventional Cole modelling. This approach is recommended for use where BIS data are compromised by high frequency capacitive leakage errors such as those obtained in babies and infants.

The bioelectrical impedance analysis (BIA) international database: aims, scope, and call for data

BACKGROUND

Bioelectrical impedance analysis (BIA) is a technique widely used for estimating body composition and health-related parameters. The technology is relatively simple, quick, and non-invasive, and is currently used globally in diverse settings, including private clinicians' offices, sports and health clubs, and hospitals, and across a spectrum of age, body weight, and disease states. BIA parameters can be used to estimate body composition (fat, fat-free mass, total-body water and its compartments). Moreover, raw measurements including resistance, reactance, phase angle, and impedance vector length can also be used to track health-related markers, including hydration and malnutrition, and disease-prognostic, athletic and general health status. Body composition shows profound variability in association with age, sex, race and ethnicity, geographic ancestry, lifestyle, and health status. To advance understanding of this variability, we propose to develop a large and diverse multi-country dataset of BIA raw measures and derived body components. The aim of this paper is to describe the 'BIA International Database' project and encourage researchers to join the consortium.

METHODS

The Exercise and Health Laboratory of the Faculty of Human Kinetics, University of Lisbon has agreed to host the database using an online portal. At present, the database contains 277,922 measures from individuals ranging from 11 months to 102 years, along with additional data on these participants.

CONCLUSION

The BIA International Database represents a key resource for research on body composition.

Development of a predictive model of body fat mass for newborns and infants

OBJECTIVES

The aim of this study is to develop predictive body fat mass models, one for newborns and one for infants, using air displacement plethysmography as a reference method.

METHODS

The study was carried out with 125 newborns (1-5 d of age) and 71 infants (≥3-6 mo). The stepwise method was used to estimate the final model from the predictors of sex, weight, length, triceps skinfold, waist circumference, mean arm circumference, and gestational age. The quality of the models was evaluated by the determination coefficient, variance inflation factor, and residual analysis. The paired t test and Bland-Altman plot were used to assess the agreement between observed and estimated values.

RESULTS

The final model for newborns was - 0.76638 + 0.2512 * weight (kg) + 0.0620 * PCT (mm) + 0.0754 * gender (R² = 70%) and the final model for infants: -2.22748 + 0.4928 * weight (kg) + 0.0737 * TSF (mm) + 0.2647 * gender (R² = 84%).

CONCLUSIONS

This work determined equations to estimate the BFM of term newborns and infants. The models can be used in clinical practice, especially in health units without access to technologies for measuring body composition, adding important information for nutritional monitoring.

Infant body composition: A comprehensive overview of assessment techniques, nutrition factors, and health outcomes

Body composition assessment is a valuable tool for clinical assessment and research that has implications for long-term health. Unlike traditional measurements such as anthropometrics or body mass index, body composition assessments provide more accurate measures of body fatness and lean mass. Moreover, depending on the technique, they can offer insight into regional body composition, bone mineral density, and brown adipose tissue. Various methods of body composition assessment exist, including air displacement plethysmography, dual-energy x-ray absorptiometry, bioelectrical impedance, magnetic resonance imaging, D3 creatine, ultrasound, and skinfold thickness, each with its own strengths and limitations. In infants, several feeding practices and nutrition factors are associated with body composition outcomes, such as breast milk vs formula feeding, protein intake, breast milk composition, and postdischarge formulas for preterm infants. Longitudinal studies suggest that body composition in infancy predicts later body composition, obesity, and other cardiometabolic outcomes in childhood, making it a useful early marker of cardiometabolic health in both term and preterm infants. Emerging evidence also suggests that body composition during infancy predicts neurodevelopmental outcomes, particularly in preterm infants at high risk of neurodevelopmental impairment. The purpose of this narrative review is to provide clinicians and researchers with a comprehensive overview of body composition assessment techniques, summarize the links between specific nutrition practices and body composition in infancy, and describe the neurodevelopmental and cardiometabolic outcomes associated with body composition patterns in term and preterm infants.

Safety, Tolerability, and Pharmacokinetics of β-Cryptoxanthin Supplementation in Healthy Women: A Double-Blind, Randomized, Placebo-Controlled Clinical Trial

BACKGROUND

β-cryptoxanthin is a dietary carotenoid for which there have been few studies on the safety and pharmacokinetics following daily oral supplementation.

METHODS

90 healthy Asian women between 21 and 35 years were randomized into three groups: 3 and 6 mg/day oral β-cryptoxanthin, and placebo. At 2, 4, and 8 weeks of supplementation, plasma carotenoid levels were measured. The effects of β-cryptoxanthin on blood retinoid-dependent gene expression, mood, physical activity and sleep, metabolic parameters, and fecal microbial composition were investigated.

RESULTS

β-cryptoxanthin supplementation for 8 weeks (3 and 6 mg/day) was found to be safe and well tolerated. Plasma β-cryptoxanthin concentration was significantly higher in the 6 mg/day group (9.0 ± 4.1 µmol/L) compared to 3 mg/day group (6.0 ± 2.6 µmol/L) (p < 0.03), and placebo (0.4 ± 0.1 µmol/L) (p < 0.001) after 8 weeks. Plasma all-trans retinol, α-cryptoxanthin, α-carotene, β-carotene, lycopene, lutein, and zeaxanthin levels were not significantly changed. No effects were found on blood retinol-dependent gene expression, mood, physical activity and sleep, metabolic parameters, and fecal microbial composition.

CONCLUSIONS

Oral β-cryptoxanthin supplementation over 8 weeks lead to high plasma concentrations of β-cryptoxanthin, with no impact on other carotenoids, and was well tolerated in healthy women.

Predictive models of newborn body composition: a systematic review

OBJECTIVE

To analyze the prediction models of fat-free mass and fat mass of neonates who had air displacement plethysmography as a reference test.

DATA SOURCE

A systematic review of studies identified in the PubMed, Virtual Health Library (BVS), SciELO, and ScienceDirect databases was carried out. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist was used for inclusion of studies, the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) report was used to select only predictive models studies, and the Prediction Model Risk of Bias Assessment Tool (PROBAST) was used to assess the risk of bias in the models.

DATA SYNTHESIS

This study is registered in PROSPERO with identification CRD42020175048. Five hundred and three studies were found during the searches, and only four papers (six models) were eligible. Most studies (three) used the sum of different skinfolds to predict neonatal body fat and all presented weight as the variable with the highest contribution to predicting neonatal body composition. Two models that used skinfolds showed high coefficients of determination and explained, significantly, 81% of the body fat measured by air displacement plethysmography, while the models using bioimpedance did not find a significant correlation between the impedance index and the fat-free mass.

CONCLUSIONS

The few studies found on this topic had numerous methodological differences. However, the subscapular skinfold was a strong predictor of neonatal body fat in three studies. It is noteworthy that such model validation studies should be carried out in the future, allowing them to be subsequently applied to the population. The development of these models with low-cost tools will contribute to better nutritional monitoring of children and could prevent complications in adulthood.

Prediction of fat-free mass in a multi-ethnic cohort of infants using bioelectrical impedance: Validation against the PEA POD

Background

Bioelectrical impedance analysis (BIA) is widely used to measure body composition but has not been adequately evaluated in infancy. Prior studies have largely been of poor quality, and few included healthy term-born offspring, so it is unclear if BIA can accurately predict body composition at this age.

Aim

This study evaluated impedance technology to predict fat-free mass (FFM) among a large multi-ethnic cohort of infants from the United Kingdom, Singapore, and New Zealand at ages 6 weeks and 6 months (n = 292 and 212, respectively).

Materials and methods

Using air displacement plethysmography (PEA POD) as the reference, two impedance approaches were evaluated: (1) empirical prediction equations; (2) Cole modeling and mixture theory prediction. Sex-specific equations were developed among ∼70% of the cohort. Equations were validated in the remaining ∼30% and in an independent University of Queensland cohort. Mixture theory estimates of FFM were validated using the entire cohort at both ages.

Results

Sex-specific equations based on weight and length explained 75-81% of FFM variance at 6 weeks but only 48-57% at 6 months. At both ages, the margin of error for these equations was 5-6% of mean FFM, as assessed by the root mean squared errors (RMSE). The stepwise addition of clinically-relevant covariates (i.e., gestational age, birthweight SDS, subscapular skinfold thickness, abdominal circumference) improved model accuracy (i.e., lowered RMSE). However, improvements in model accuracy were not consistently observed when impedance parameters (as the impedance index) were incorporated instead of length. The bioimpedance equations had mean absolute percentage errors (MAPE) < 5% when validated. Limits of agreement analyses showed that biases were low (< 100 g) and limits of agreement were narrower for bioimpedance-based than anthropometry-based equations, with no clear benefit following the addition of clinically-relevant variables. Estimates of FFM from BIS mixture theory prediction were inaccurate (MAPE 11-12%).

Conclusion

The addition of the impedance index improved the accuracy of empirical FFM predictions. However, improvements were modest, so the benefits of using bioimpedance in the field remain unclear and require further investigation. Mixture theory prediction of FFM from BIS is inaccurate in infancy and cannot be recommended.

The Kynurenine Pathway Metabolites in Cord Blood Positively Correlate With Early Childhood Adiposity

CONTEXT

The kynurenine pathway generates metabolites integral to energy metabolism, neurotransmission, and immune function. Circulating kynurenine metabolites positively correlate with adiposity in children and adults, yet it is not known whether this relationship is present already at birth.

OBJECTIVE

In this prospective longitudinal study, we investigate the relationship between cord blood kynurenine metabolites and measures of adiposity from birth to 4.5 years.

METHODS

Liquid chromatography-tandem mass spectrometry was used to quantify cord blood kynurenine metabolites in 812 neonates from the Growing Up in Singapore Towards healthy Outcomes (GUSTO) study. Fat percentage was measured by air displacement plethysmography and abdominal adipose tissue compartment volumes; superficial (sSAT) and deep subcutaneous (dSAT) and internal adipose tissue were quantified by magnetic resonance imaging at early infancy in a smaller subset of neonates, and again at 4 to 4.5 years of age.

RESULTS

Cord blood kynurenine metabolites appeared to be higher in female newborns, higher in Indian newborns compared with Chinese newborns, and higher in infants born by cesarean section compared with vaginal delivery. Kynurenine, xanthurenic acid, and quinolinic acid were positively associated with birthweight, but not with subsequent weight during infancy and childhood. Quinolinic acid was positively associated with sSAT at birth. Kynurenic acid and quinolinic acid were positively associated with fat percentage at 4 years.

CONCLUSION

Several cord blood kynurenine metabolite concentrations were positively associated with birthweight, with higher kynurenic acid and quinolinic acid correlating to higher percentage body fat in childhood, suggesting these cord blood metabolites as biomarkers of early childhood adiposity.

Individualized body geometry correction factor (KB) for use when predicting body composition from bioimpedance spectroscopy

OBJECTIVE

Prediction of body composition from bioimpedance spectroscopy (BIS) measurements using mixture theory-based biophysical modelling invokes a factor (K_B) to account for differing body geometry (or proportions) between individuals. To date, a single constant value is commonly used. The aim of this study was to investigate variation in KB across individuals and to develop a procedure for estimating an individualized K_Bvalue.

APPROACH

Publicly available body dimension data, primarily from the garment industry, were used to calculate K_Bvalues for individuals of varying body sizes across the life-span. The 3-D surface relationship between weight, height and K_B, was determined and used to create look-up tables to enable estimation of K_Bin individuals based on height and weight. The utility of the proposed method was assessed by comparing body composition predictions from BIS using either a constant K_Bvalue or the individualized value.

RESULTS

Computed KB values were well fitted to height and weight by a 3-D surface (R2 = 0.988). Body composition was predicted more accurately compared to reference methods when using individualized K_Bthan a constant value in infants and children but improvement in prediction was less in adults particularly those with high body mass index.

SIGNIFICANCE

Prediction of body composition from BIS and mixture theory is improved by using an individualized body proportion factor in those of small body habitus, e.g. children. Improvement is small in adults or non-existent in those of large body size. Further improvements may be possible by incorporating a factor to account for trunk size, i.e., waist circumference.

Anthropometry-based prediction of body composition in early infancy compared to air-displacement plethysmography

BACKGROUND

Anthropometry-based equations are commonly used to estimate infant body composition. However, existing equations were designed for newborns or adolescents. We aimed to (a) derive new prediction equations in infancy against air-displacement plethysmography (ADP-PEA Pod) as the criterion, (b) validate the newly developed equations in an independent infant cohort and (c) compare them with published equations (Slaughter-1988, Aris-2013, Catalano-1995).

METHODS

Cambridge Baby Growth Study (CBGS), UK, had anthropometry data at 6 weeks (N = 55) and 3 months (N = 64), including skinfold thicknesses (SFT) at four sites (triceps, subscapular, quadriceps and flank) and ADP-derived total body fat mass (FM) and fat-free mass (FFM). Prediction equations for FM and FFM were developed in CBGS using linear regression models and were validated in Sophia Pluto cohort, the Netherlands, (N = 571 and N = 447 aged 3 and 6 months, respectively) using Bland-Altman analyses to assess bias and 95% limits of agreement (LOA).

RESULTS

CBGS equations consisted of sex, age, weight, length and SFT from three sites and explained 65% of the variance in FM and 79% in FFM. In Sophia Pluto, these equations showed smaller mean bias than the three published equations in estimating FM: mean bias (LOA) 0.008 (-0.489, 0.505) kg at 3 months and 0.084 (-0.545, 0.713) kg at 6 months. Mean bias in estimating FFM was 0.099 (-0.394, 0.592) kg at 3 months and -0.021 (-0.663, 0.621) kg at 6 months.

CONCLUSIONS

CBGS prediction equations for infant FM and FFM showed better validity in an independent cohort at ages 3 and 6 months than existing equations.

Bioelectrical impedance analysis for assessment of body composition in infants and young children-A systematic literature review

Bioelectrical impedance analysis (BIA) is an easy to use, portable tool, but the accuracy of the technique in infants and young children (<24 months) remains unclear. A systematic literature review was conducted to identify studies that have developed and validated BIA equations in this age group. MEDLINE, Scopus, EMBASE, and CENTRAL were searched for relevant literature published up until June 30, 2020, using terms related to bioelectrical impedance, body composition, and paediatrics. Two reviewers independently screened studies for eligibility, resulting in 15 studies that had developed and/or validated equations. Forty-six equations were developed and 34 validations were conducted. Most equations were developed in young infants (≤6 months), whereas only seven were developed among older infants and children (6-24 months). Most studies were identified as having a high risk of bias, and only a few included predominantly healthy children born at term. Using the best available evidence, BIA appears to predict body composition at least as well as other body composition tools; however, among younger infants BIA may provide little benefit over anthropometry-based prediction equations. Currently, none of the available equations can be recommended for use in research or in clinical practice.

Development of population-specific prediction equations for bioelectrical impedance analyses in Vietnamese children

There is a need for accurate, inexpensive and field-friendly methods to assess body composition in children. Bioelectrical impedance analysis (BIA) is a promising approach; however, there have been limited validation and use among young children in resource-poor settings. We aim to develop and validate population-specific prediction equations for estimating total fat mass (FM), fat free-mass (FFM) and percentage body fat (PBF) in Vietnamese children (4-7 years) using reactance and resistance from BIA, anthropometric variables and demographic information. We conducted a cross-sectional survey of 120 children. Body composition was measured using dual-energy X-ray absorptiometry (DXA), BIA and anthropometry. To develop prediction equations, we split all data into development (70 %) and validation datasets (30 %). The model performance was evaluated using predicted residual error sum of squares, root mean squared error (RMSE), mean absolute error (MAE) and R2. We identified a top performing model with the least number of parameters (age, sex, weight and resistance index or resistance and height), low RMSE (FM 0·70, FFM 0·74, PBF 3·10), low MAE (FM 0·55, FFM 0·62, PBF 2·49), high R2 (FM 0·95, FFM 0·92, PBF 0·82) and the least difference between predicted values and actual values from DXA (FM 0·03 kg or 0·01 sd, FFM 0·06 kg or 0·02 sd, PBF 0·27 % or 0·04 sd). In conclusion, we developed the first valid and highly predictive equations to estimate FM, FFM and PBF in Vietnamese children using BIA. These findings have important implications for future research on the double burden of disease and risks associated with overweight and obesity in young children.

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.

Bioelectrical Impedance Analysis-An Easy Tool for Quantifying Body Composition in Infancy?

There has been increasing interest in understanding body composition in early life and factors that may influence its evolution. While several technologies exist to measure body composition in infancy, the equipment is typically large, and thus not readily portable, is expensive, and requires a qualified operator. Bioelectrical impedance analysis shows promise as an inexpensive, portable, and easy to use tool. Despite the technique being widely used to assess body composition for over 35 years, it has been seldom used in infancy. This may be related to the evolving nature of the fat-free mass compartment during this period. Nonetheless, a number of factors have been identified that may influence bioelectrical impedance measurements, which, when controlled for, may result in more accurate measurements. Despite this, questions remain in infants regarding the optimal size and placement of electrodes, the standardization of normal hydration, and the influence of body position on the distribution of water throughout the body. The technology requires further evaluation before being considered as a suitable tool to assess body composition in infancy.

Neonatal body composition by air displacement plethysmography in healthy term singletons: a systematic review

BACKGROUND

There is increasing evidence that intrauterine environment and, consequently, growth in utero have both immediate and far-reaching consequences for health. Neonatal body composition might be a more sensitive marker of intrauterine environment and neonatal adiposity than birth weight and could serve as a predictor for non-communicable diseases later in life.

METHODS

To perform a systematic literature review on neonatal body composition determined by air displacement plethysmography in healthy infants. The systematic review was performed using the search terms "air displacement plethysmography", "infant" and "newborn" in Pubmed. Data are displayed as mean (Standard deviation).

RESULTS

Fourteen studies (including n = 6231 infants) using air displacement plethysmography fulfilled inclusion criteria for meta-analysis. In these, weighted mean body fat percentage was 10.0 (4.1) % and weighted mean fat free mass was 2883 (356) g in healthy term infants. Female infants had a higher body fat percentage (11.1 (4.1) % vs. 9.6 (4.0) %) and lower fat free mass (2827 (316) g vs. 2979 (344) g). In the Caucasian subpopulation (n = 2202 infants) mean body fat percentage was 10.8 (4.1), whereas data for reference values of other ethnic groups are still sparse.

CONCLUSIONS

Body composition varies depending on gender and ethnicity. These aggregated data may serve as reference for body composition in healthy, term, singletons at least for the Caucasian subpopulation.

Measuring body composition in the preterm infant: Evidence base and practicalities

Preterm birth and body composition have demonstrable effects on growth and later health outcomes. Preterm infants reach term equivalent age with a lower proportion of lean mass and higher body fat percentage than their term equivalent counterparts. Weight and length do not give an accurate assessment of body composition. Tracking body composition rather than just weight is a fundamental part of improving nutritional outcomes. This is important given the ongoing controversies regarding the nutritional needs of preterm infants, as well as establishing suitable targets for their growth. In this review we describe current methodologies used in the measurement of body composition of the preterm infant and the review the recent published evidence for their accuracy and utility. Current measurement techniques employed include air displacement plethysmography, bioelectrical impedance analysis, isotope dilution techniques, MRI and a combination of manual measurements including skinfold thickness, body mass index and mid upper arm/mid-thigh circumference. These measures allow for the estimation of fat mass, fat-free mass and regional assessment of adiposity. Some methods, such as dual-energy X-ray absorptiometry and air displacement plethysmography do allow for comparison of change in body composition over time in cohorts of preterm infants that may be studied over a longer period of time and into adult life. However, none of the currently described methods give an accurate and practically achievable method of obtaining body composition measures in preterm infants in day to day routine clinical practise, although this remains a key priority when decisions are being made about how best to feed.

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.

Which anthropometric measures best reflect neonatal adiposity?

BACKGROUND

Studying the determinants and the long-term consequences of fetal adipose accretion requires accurate assessment of neonatal body composition. In large epidemiological studies, in-depth body composition measurement methods are usually not feasible for cost and logistical reasons, and there is a need to identify anthropometric measures that adequately reflect neonatal adiposity.

METHODS

In a multiethnic Asian mother-offspring cohort in Singapore, anthropometric measures (weight, length, abdominal circumference, skinfold thicknesses) were measured using standardized protocols in newborn infants, and anthropometric indices (weight/length, weight/length² (body mass index, BMI), weight/length³ (ponderal index, PI)) derived. Neonatal total adiposity was measured using air displacement plethysmography (ADP) and abdominal adiposity using magnetic resonance imaging (MRI). Correlations of the anthropometric measures with ADP- and MRI-based adiposity were assessed using Pearson's correlation coefficients (r_p), including in subsamples stratified by sex and ethnicity.

RESULTS

Study neonates (n=251) had a mean (s.d.) age of 10.2 (2.5) days. Correlations between ADP-based fat mass (ADP_FM) and anthropometric measures were moderate (r_p range: 0.44-0.67), with the strongest being with weight/length, weight, BMI and sum of skinfolds (r_p=0.67, 0.66, 0.62, 0.62, respectively, all P<0.01). All anthropometric measures except skinfold thicknesses correlated more strongly with ADP-based fat-free mass than ADP_FM, indicating that skinfold measures may have more discriminative power in terms of neonatal total body adiposity. For MRI-based measures, weight and weight/length consistently showed strong positive correlations (r_p⩾0.7) with abdominal adipose tissue compartments. These correlations were consistent in boys and girls, across different ethnic groups, and when conventional determinants of neonatal adiposity were adjusted for potential confounding. Abdominal circumference was not strongly associated with ADP_FM or abdominal fat mass.

CONCLUSIONS

Simple anthropometric measures (weight and weight/length) correlated strongly with neonatal adiposity, with some evidence for greater discriminative power for skinfold measures. These simple measures could be of value in large epidemiological studies.