Quantitative nuclear magnetic resonance to measure fat mass in infants and children

Relationships between physical behaviour phenotypes of mothers in pregnancy and their offspring with child body composition

AIM

The aim of this study was to identify physical behaviour phenotypes in mothers in the first trimester and in their offspring at 24 months of age. The secondary aim was to examine relationships between mother and child behaviours with child body composition at age 24 months.

METHODS

Longitudinal secondary analysis of the Glowing cohort collected between 1 February 2011 and 22 August 2017 in Little Rock, Arkansas. Behaviours were measured using ankle-worn accelerometers in mothers during the first trimester and offspring at 24 months of age, including total activity, sleep, sedentary time and a novel variable of daily variation, patternicity. Child body fat was measured using quantitative nuclear magnetic resonance.

RESULTS

Three phenotypes were identified for mothers and children (n = 159 complete dyads). There were no relationships between mother and child phenotypes, but higher maternal patternicity was associated with higher child patternicity (0.2, 95% CI 0.1, 0.3, p = 0.001). There were no associations between mother or child phenotypes with child body composition, however higher child activity was associated with lower body fat (-0.01, 95% CI: -0.02, -0.001, p = 0.031).

CONCLUSION

Limited associations were found between mothers' pregnancy physical behaviours with child behaviours or child body composition at 24 months of age. Factors such as child diet or current parental physical activity may be better predictors of early childhood outcomes.

Associations Between Maternal Physical Activity, Maternal Lipid Levels, and Infant Anthropometric Outcomes at Two Weeks of Age

BACKGROUND

This study determined the relationship between physical activity (PA), circulating lipids throughout pregnancy and infant anthropometric outcomes at birth and 2 weeks of age.

METHODS

Women (N = 234) with normal weight (NW, BMI 18.5-24.9 kg/m²) and with overweight and class I obesity (OW/OB, BMI 25-35 kg/m²) were categorized into high and low PA based on average cohort steps during pregnancy (8099 steps/day). Circulating fasting lipids were measured at each trimester. Standardized methods were used to obtain anthropometrics measures. Infant body composition was estimated by quantitative nuclear magnetic resonance (EchoMRI-AH small; ECHO Medical Systems).

RESULTS

Women with NW who had higher activity had lower circulating triglycerides (TG) and total cholesterol (TC) levels at 12 weeks compared to women with NW and low activity (p < 0.05). Women with OW/OB and high activity level throughout pregnancy had lower circulating TG, and low density lipoprotein (LDL), at 12 weeks, lower LDL at 24 weeks, and lower TG at 36 weeks compared to the women with OW/OB who had low activity levels (p < 0.05). For children born to women with OW/OB, maternal circulating TG and LDL were most associated with infant anthropometrics at 2 weeks of age.

CONCLUSION

This study supports that higher PA during pregnancy is associated with lower lipid levels throughout pregnancy with a greater effect size in women with OW/OB. Maternal lipids were associated with anthropometrics and infant body composition at two weeks of life in women with OW/OB.

Associations between maternal obesity and offspring gut microbiome in the first year of life

BACKGROUND

Maternal obesity is an important determinant of offspring obesity risk, which may be mediated via changes in the infant microbiome.

OBJECTIVES

We examined infant faecal microbiome, short-chain fatty acids (SCFA), and maternal human milk oligosaccharides (HMO) in mothers with overweight/obese body mass index (BMI) (OW) compared with normal weight (NW) (Clinicaltrials.gov NCT01131117).

METHODS

Infant stool samples at 1, 6, and 12 months were analysed by 16S rRNA sequencing. Maternal (BODPOD) and infant (quantitative nuclear magnetic resonance [QMR]) adiposity were measured. HMOs at 2 months postpartum and faecal SCFAs at 1 month were also assessed. Statistical analyses included multivariable and mixed linear models for assessment of microbiome diversity, composition, and associations of taxonomic abundance with metabolic and anthropometric variables.

RESULTS

At 1 month, offspring of women with obesity had lower abundance of SCFA-producing bacteria (including Ruminococcus and Turicibacter) and lower faecal butyric acid levels. Lachnospiraceae abundance was lower in OW group at 6 months, and infant fat mass was negatively associated with the levels of Sutterella. Gradient boosting machine models indicated that higher α-diversity and specific microbial taxa at 1 month predicted elevated adiposity at 12 months with overall accuracy of 76.5%. Associations between maternal HMO concentrations and infant bacterial taxa differed between NW and OW groups.

CONCLUSIONS

Elevated maternal BMI is associated with relative depletion of butyrate-producing microbes and faecal butyrate in the early infant faecal microbiome. Overall microbial richness may aid in prediction of elevated adiposity in later infancy.

Infant intakes of human milk branched chain amino acids are negatively associated with infant growth and influenced by maternal body mass index

BACKGROUND

Branched-chain amino acids (BCAAs: isoleucine, leucine, and valine) and aromatic amino acids (AAAs: phenylalanine and tyrosine) are hypothesized to influence early-life obesity risk.

OBJECTIVE

To assess HM free amino acid (AA) concentrations and infant intakes of HM AAs from women with obesity (OB) compared to those with normal weight (NW) and determine the relationships between HM AA consumption and infant growth.

METHODS

HM samples were collected at 0.5 (n = 151), 2 (n = 129), and 6 (n = 93) months postpartum from mothers with NW (body mass index [BMI] = 18.5-24.9 kg/m² ) and OB (BMI > 30 kg/m² ). HM AAs were quantified via mass spectrometry. Infant HM intake, anthropometrics and body composition were assessed. Linear mixed-effects models (LMEM) examined the relationships between maternal BMI and HM AA intakes, and HM AA intake and infant growth over the first 6 months postpartum after adjusting for maternal and infant characteristics.

RESULTS

Maternal BMI was positively associated with infant intakes of isoleucine, leucine, and AAAs across timepoints. HM AA intakes were positively associated with weight-for-length z-score, fat mass index, and fat-free mass index in infants (p < 0.05).

CONCLUSIONS

Maternal BMI led to differences in HM AA composition, which was associated with infant body composition.

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.

A secondary analysis of maternal ultra-processed food intake in women with overweight or obesity and associations with gestational weight gain and neonatal body composition outcomes

BACKGROUND

This study is an observational secondary analysis of the Lifestyle Intervention for Two (LIFT) randomised controlled trial data. There is a paucity of data related to mechanisms of health effects and dietary intake of ultra-processed foods (UPF). Earlier studies demonstrate associations between greater UPF intake and weight gain. The purpose of the study was to describe associations among maternal UPF intake with gestational weight gain (GWG) and neonatal body composition.

MATERIAL AND METHODS

Women with overweight or obesity (n=156) and offspring (n=126) with complete energy intake, anthropometrics and body composition measures were selected. Maternal weights and diet recalls (Automated Self-Administered 24) were measured at weeks 14 and 35 gestational age (GA). Body composition was assessed by infant quantitative magnetic resonance (infant-QMR) and air displacement plethysmography (ADP) at birth. Dependent variables were GWG and neonatal fat mass, fat-free mass, and lean mass at birth; covariates were dietary, socioeconomic and biological. Stepwise linear regressions were used to test associations.

RESULTS

Highest quartile of percentage of energy intake from UPF (PEI-UPF) was not significantly correlated with maternal GWG (p=0.215), infant QMR fat (p=0.816) and lean mass (p=0.423) or ADP fat (p=0.482) or fat-free mass (p=0.835).

CONCLUSIONS

While no significant associations with UPF were observed in this smaller size cohort, further investigations would be justified in larger cohorts on the relationships of maternal UPF intake and GWG and offspring outcomes. Clinical Trial NCT01616147.

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.

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.

Human Milk Oligosaccharide Concentrations and Infant Intakes Are Associated with Maternal Overweight and Obesity and Predict Infant Growth

Human milk oligosaccharides (HMOs) are bioactive molecules playing a critical role in infant health. We aimed to quantify the composition of HMOs of women with normal weight (18.5–24.9 kg/m²), overweight (25.0–29.9 kg/m²), or obesity (30.0–60.0 kg/m²) and determine the effect of HMO intake on infant growth. Human milk (HM) samples collected at 2 months (2 M; n = 194) postpartum were analyzed for HMO concentrations via high-performance liquid chromatography. Infant HM intake, anthropometrics and body composition were assessed at 2 M and 6 M postpartum. Linear regressions and linear mixed-effects models were conducted examining the relationships between maternal BMI and HMO composition and HMO intake and infant growth over the first 6 M, respectively. Maternal obesity was associated with lower concentrations of several fucosylated and sialylated HMOs and infants born to women with obesity had lower intakes of these HMOs. Maternal BMI was positively associated with lacto-N-neotetraose, 3-fucosyllactose, 3-sialyllactose and 6-sialyllactose and negatively associated with disialyllacto-N-tetraose, disialyllacto-N-hexaose, fucodisialyllacto-N-hexaose and total acidic HMOs concentrations at 2 M. Infant intakes of 3-fucosyllactose, 3-sialyllactose, 6-sialyllactose, disialyllacto-N-tetraose, disialyllacto-N-hexaose, and total acidic HMOs were positively associated with infant growth over the first 6 M of life. Maternal obesity is associated with changes in HMO concentrations that are associated with infant adiposity.

Maternal adiposity alters the human milk metabolome: associations between nonglucose monosaccharides and infant adiposity

BACKGROUND

Human milk composition is altered by maternal obesity. The association between milk metabolites and infant outcomes has not been thoroughly investigated.

OBJECTIVES

This study aimed to quantify maternal adiposity-related differences in the human milk metabolome and to identify metabolites associated with infant adiposity during the first 6 mo postpartum using untargeted metabolomics.

METHOD

Maternal anthropometrics were assessed ≤14 weeks of gestation. Human milk samples were collected at 0.5 mo (n = 159), 2 mo (n = 131), and 6 mo (n = 94) postpartum from normal weight (NW, BMI = 18.5-24.9 kg/m2) and obese (OB, BMI >30 kg/m2) mothers. GC-time-of-flight-MS was used to identify metabolic signatures that discriminate NW and OB women. Partial least squared (PLS)-discriminant analysis, and PLS-regression models were assessed to examine relations between metabolites and maternal BMI and fat mass. Metabolites altered by maternal obesity were used in linear mixed effect models to predict infant adiposity.

RESULTS

Multivariate modeling identified 23, 17, and 10 metabolites that described maternal adiposity indices at 0.5 mo, 2 mo, and 6 mo postpartum, respectively. Monosaccharides and sugar alcohols were the most representative annotated metabolite classes that were increased in milk from OB women and included: mannose, ribose, lyxose, lyxitol (0.5 mo); mannose, ribitol, glycerol, isothreonic acid, lyxitol (2 mo); lyxitol and isothreonic acid (6 mo). Other discriminant metabolites included: 1-monostearin, xylonolactone, shikimic acid, pseudo uridine, and dodecanol (0.5 mo); N-acetyl-D-hexosamine and fumaric acid (2 mo); uric acid and tyrosine (6 mo). Mannose, lyxitol, and shikimic acid predicted higher infant adiposity over the first 6 mo of life.

CONCLUSIONS

This study reports on 1 of the largest cohorts to date examining the metabolic profiles in human milk comparing NW and OB women. Maternal adiposity was associated with increased amounts of milk nonglucose monosaccharides. Human milk metabolomics may be useful in predicting infant adiposity. These trials were registered at www.clinicaltrials.gov as NCT01131117 and NCT02125149.

Human milk composition differs by maternal BMI in the first 9 months postpartum

BACKGROUND

Studies indicate that maternal weight status modulates human milk composition; however, results are conflicting.

OBJECTIVES

Our objective was to examine the relation between maternal body composition and human milk macronutrients and bioactive components and also their association with infant daily intakes and body composition.

METHODS

Human milk samples were obtained from a longitudinal study (NCT01131117) in normal weight (NW: 18.5-24.9 kg/m2, n = 88) and overweight/obese (OW: 25-35 kg/m2, n = 86) women between 0.5 and 9 mo postpartum. Macronutrient content was estimated using mid-infrared spectroscopy. Leptin, insulin, and C-reactive protein (CRP) were measured using electrochemiluminescence immunoassays. Infant body composition was obtained using quantitative MRI. Linear mixed models were adjusted for postpartum age and infant sex.

RESULTS

Human milk in OW mothers was higher in fat and protein and lower in carbohydrate content at some time points compared with that in NW mothers. Human milk leptin, insulin, and CRP concentrations were higher in OW mothers compared with NW mothers, with infants of OW mothers exposed to 1.5-2.5 times higher concentrations of leptin and insulin compared with infants of NW mothers. Similar results were observed when concentrations were normalized to infant daily intake and body weight. The effect sizes of infant daily intakes associated with infant growth parameters were small for macronutrients [0.005-0.05 z-score units and 0.02-0.45 fat mass index (FMI) or fat-free mass index units per unit of change in composition, P < 0.05]. Larger effect sizes were seen with human milk insulin and leptin (0.24 z-score units and 0.37-1.15 FMI units per unit of change in composition, P < 0.05).

CONCLUSIONS

These findings demonstrate that infants of OW mothers are exposed to higher concentrations of insulin, leptin, and, to a lesser extent, CRP. The bioavailability of these 3 human milk bioactives and their mechanisms of action in the infant are unclear.This trial was registered at clinicaltrials.gov as NCT01131117.

Imaging of body composition in children

Overweight and obesity in children and adolescents have become a worldwide public health concern with an ever-increasing prevalence. An excessive accumulation of intraabdominal fat tissue increases the risk of developing insulin resistance, diabetes, and cardiovascular diseases in adulthood. Body composition has a role in metabolism regulation in children and adolescents with differences between genders and age groups. Until recently, Air Displacement Plethysmography and Dual-energy X-ray Absorptiometry (DXA) have been the most common techniques used to assess body composition in children. Ultrasound (US) is an accurate, readily available, and radiation-free technique to quantify intra-abdominal fat in adults, but its use in children has not yet been validated. Computed tomography (CT) is a reliable tool to assess body composition, but its use in children should be avoided due to the significant radiation burden. Quantitative Magnetic Resonance Imaging (qMRI) provides an accurate measurement of body composition, through the quantification of the visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and brown adipose tissue (BAT), as well as lean mass. Furthermore, qMRI provides other significant estimates such as the Proton Density Fat-Fraction of the fat tissue. This review article aims to briefly describe the state of art of the advanced imaging techniques to provide a quantitative assessment of body composition in children and adolescents.

Body Composition Measurements from Birth through 5 Years: Challenges, Gaps, and Existing & Emerging Technologies-A National Institutes of Health workshop

Body composition estimates are widely used in clinical research and field studies as measures of energy-nutrient balance, functionality and health. Despite their broad relevance and multiple applications, important gaps remain in techniques available for accurately and precisely quantifying body composition in infants and children from birth through 5 years. Identifying these gaps and highlighting research needs in this age group were the topics of a National Institutes of Health workshop held in Bethesda, MD, USA, 30-31 May 2019. Experts reviewed available methods (multicompartment models, air-displacement plethysmography, dual-energy X-ray absorptiometry, weight-length and height indices, bioimpedance analysis, anthropometry-skinfold techniques, quantitative magnetic resonance, optical imaging, omics and D3-creatine dilution), their limitations in this age range and high priority research needs. A summary of their individual and collective workshop deliberations is provided in this report.

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.

Maternal Adiposity is Associated with Fat Mass Accretion in Female but not Male Offspring During the First 2 Years of Life

OBJECTIVE

This study investigated which antenatal and postnatal factors determine offspring adiposity during the first 2 years of life.

METHODS

Participants were mother and child pairs (N = 224). Offspring percent fat mass (%FM) was obtained using quantitative nuclear magnetic resonance at 11 time points between ages 0.5 and 24 months. Independent variables included race, age, gestational weight gain, first-trimester %FM, delivery mode, gestational measures of resting energy expenditure, respiratory exchange ratio, physical activity, serum cytokines and lipids, and dietary intake for the mothers, as well as sex, birth weight and length, breastfeeding duration, and physical activity at age 2 years for the children. Linear mixed models were used to construct the best-fitted models for the entire cohort and for each sex.

RESULTS

Maternal %FM (P = 0.006), high-density lipoprotein (HDL) (P < 0.001), and breastfeeding duration (P = 0.023) were positively associated with female offspring adiposity, whereas maternal dietary fiber intake (P = 0.016) had a negative association. Birth weight (P = 0.004), maternal HDL (P = 0.013), and breastfeeding duration (P = 0.015) were all positively associated with male offspring adiposity.

CONCLUSIONS

Antenatal and postnatal factors differentially impact male and female offspring adiposity during the first 2 years of life.

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.

Body composition measurement in young children using quantitative magnetic resonance: a comparison with air displacement plethysmography

BACKGROUND

Quantitative magnetic resonance (QMR) has been increasingly used to measure human body composition, but its use and validation in children is limited.

OBJECTIVE

We compared body composition measurement by QMR and air displacement plethysmography (ADP) in preschool children from Singapore's multi-ethnic Asian population (n = 152; mean ± SD age: 5.0 ± 0.1 years).

METHODS

Agreements between QMR-based and ADP-based fat mass and fat mass index (FMI) were assessed using intraclass correlation coefficient (ICC), reduced major axis regression and Bland-Altman plot analyses. Analyses were stratified for the child's sex.

RESULTS

Substantial agreement was observed between QMR-based and ADP-based fat mass (ICC: 0.85) and FMI (ICC: 0.82). Reduced major axis regression analysis suggested that QMR measurements were generally lower than ADP measurements. Bland-Altman analysis similarly revealed that QMR-based fat mass were (mean difference [95% limits of agreement]) -0.5 (-2.1 to +1.1) kg lower than ADP-based fat mass and QMR-based FMI were -0.4 (-1.8 to +0.9) kg/m² lower than ADP-based FMI. Stratification by offspring sex revealed better agreement of QMR and ADP measurements in girls than in boys.

CONCLUSIONS

QMR-based fat mass and FMI showed substantial agreement with, but was generally lower than, ADP-based measures in young Asian children.

Current body composition measurement techniques

PURPOSE OF REVIEW

The current article reviews the most innovative and precise, available methods for quantification of in-vivo human body composition.

RECENT FINDINGS

Body composition measurement methods are continuously being perfected. Ongoing efforts involve multisegmental and multifrequency bioelectrical impedance analysis, quantitative magnetic resonance for total body water, fat, and lean tissue measurements, imaging to further define ectopic fat depots. Available techniques allow for the measurement of fat, fat-free mass, bone mineral content, total body water, extracellular water, total adipose tissue and its subdepots (visceral, subcutaneous, and intermuscular), skeletal muscle, select organs, and ectopic fat depots.

SUMMARY

There is an ongoing need for methods that yield information on metabolic and biological functions. Based on the wide range of measurable properties, analytical methods and known body composition models, clinicians, and scientists can quantify a number of body components and with longitudinal assessment, can track changes in health and disease with implications for understanding efficacy of nutritional and clinical interventions, diagnosis, prevention, and treatment in clinical settings. With the greater need to understand precursors of health risk beginning prior to conception, a gap exists in appropriate in-vivo measurement methods with application beginning during gestation, that is, fetal development.

Reliability of the EchoMRI Infants System for Water and Fat Measurements in Newborns

OBJECTIVE

The precision and accuracy of a quantitative magnetic resonance (EchoMRI Infants) system in newborns were determined.

METHODS

Canola oil and drinking water phantoms (increments of 10 g to 1.9 kg) were scanned four times. Instrument reproducibility was assessed from three scans (within 10 minutes) in 42 healthy term newborns (12-70 hours post birth). Instrument precision was determined from the coefficient of variation (CV) of repeated scans for total water, lean mass, and fat measures for newborns and the mean difference between weight and measurement for phantoms. In newborns, the system accuracy for total body water (TBW) was tested against deuterium dilution (D₂ O).

RESULTS

In phantoms, the repeatability and accuracy of fat and water measurements increased as the weight of oil and water increased. TBW was overestimated in amounts >200 g. In newborns weighing 3.14 kg, fat, lean mass, and TBW were 0.52 kg (16.48%), 2.28 kg, and 2.40 kg, respectively. EchoMRI's reproducibility (CV) was 3.27%, 1.83%, and 1.34% for total body fat, lean mass, and TBW, respectively. EchoMRI-TBW values did not differ from D₂ O; mean difference, -1.95 ± 6.76%, P = 0.387; mean bias (limits of agreement), 0.046 kg (-0.30 to 0.39 kg).

CONCLUSIONS

The EchoMRI Infants system's precision and accuracy for total body fat and lean mass are better than established techniques and equivalent to D₂ O for TBW in phantoms and newborns.

Body composition during fetal development and infancy through the age of 5 years

Fetal body composition is an important determinant of body composition at birth, and it is likely to be an important determinant at later stages in life. The purpose of this work is to provide a comprehensive overview by presenting data from previously published studies that report on body composition during fetal development in newborns and the infant/child through 5 years of age. Understanding the changes in body composition that occur both in utero and during infancy and childhood, and how they may be related, may help inform evidence-based practice during pregnancy and childhood. We describe body composition measurement techniques from the in utero period to 5 years of age, and identify gaps in knowledge to direct future research efforts. Available literature on chemical and cadaver analyses of fetal studies during gestation is presented to show the timing and accretion rates of adipose and lean tissues. Quantitative and qualitative aspects of fetal lean and fat mass accretion could be especially useful in the clinical setting for diagnostic purposes. The practicality of different pediatric body composition measurement methods in the clinical setting is discussed by presenting the assumptions and limitations associated with each method that may assist the clinician in characterizing the health and nutritional status of the fetus, infant and child. It is our hope that this review will help guide future research efforts directed at increasing the understanding of how body composition in early development may be associated with chronic diseases in later life.

Emerging Technologies and their Applications in Lipid Compartment Measurement

Non-Communicable diseases (NCDs), including obesity, are emerging as the major health concern of the 21st century. Excess adiposity and related NCD metabolic disturbances have stimulated development of new lipid compartment measurement technologies to help us to understand cellular energy exchange, to refine phenotypes, and to develop predictive markers of adverse clinical outcomes. Recent advances now allow quantification of multiple intracellular lipid and adipose tissue compartments that can be evaluated across the human lifespan. With magnetic resonance methods leading the way, newer approaches will give molecular structural and metabolic information beyond the laboratory in real-world settings. The union between these new technologies and the growing NCD population is creating an exciting interface in advancing our understanding of chronic disease mechanisms.

Application of standards and models in body composition analysis

The aim of this review is to extend present concepts of body composition and to integrate it into physiology. In vivo body composition analysis (BCA) has a sound theoretical and methodological basis. Present methods used for BCA are reliable and valid. Individual data on body components, organs and tissues are included into different models, e.g. a 2-, 3-, 4- or multi-component model. Today the so-called 4-compartment model as well as whole body MRI (or computed tomography) scans are considered as gold standards of BCA. In practice the use of the appropriate method depends on the question of interest and the accuracy needed to address it. Body composition data are descriptive and used for normative analyses (e.g. generating normal values, centiles and cut offs). Advanced models of BCA go beyond description and normative approaches. The concept of functional body composition (FBC) takes into account the relationships between individual body components, organs and tissues and related metabolic and physical functions. FBC can be further extended to the model of healthy body composition (HBC) based on horizontal (i.e. structural) and vertical (e.g. metabolism and its neuroendocrine control) relationships between individual components as well as between component and body functions using mathematical modelling with a hierarchical multi-level multi-scale approach at the software level. HBC integrates into whole body systems of cardiovascular, respiratory, hepatic and renal functions. To conclude BCA is a prerequisite for detailed phenotyping of individuals providing a sound basis for in depth biomedical research and clinical decision making.

Assessment of fat and lean mass by quantitative magnetic resonance: a future technology of body composition research?

PURPOSE OF REVIEW

For the assessment of energy balance or monitoring of therapeutic interventions, there is a need for noninvasive and highly precise methods of body composition analysis that are able to accurately measure small changes in fat and fat-free mass (FFM).

RECENT FINDINGS

The use of quantitative magnetic resonance (QMR) for measurement of body composition has long been established in animal studies. There are, however, only a few human studies that examine the validity of this method. These studies have consistently shown a high precision of QMR and only a small underestimation of fat mass by QMR when compared with a 4-compartment model as a reference. An underestimation of fat mass by QMR is also supported by the comparison between measured energy balance (as a difference between energy intake and energy expenditure) and energy balance predicted from changes in fat mass and FFM. Fewer calories were lost and gained as fat mass compared with the value expected from measured energy balance.

SUMMARY

Current evidence in healthy humans has shown that QMR is a valid and precise method for noninvasive measurement of body composition. Contrary to standard reference methods, such as densitometry and dual X-ray absorptiometry, QMR results are independent of FFM hydration. However, despite a high accuracy and a low minimal detectable change, underestimation of fat mass by QMR is possible and limits the use of this method for quantification of energy balance.

Imaging methods for analyzing body composition in human obesity and cardiometabolic disease

Advances in the technological qualities of imaging modalities for assessing human body composition have been stimulated by accumulating evidence that individual components of body composition have significant influences on chronic disease onset, disease progression, treatment response, and health outcomes. Importantly, imaging modalities have provided a systematic method for differentiating phenotypes of body composition that diverge from what is considered normal, that is, having low bone mass (osteopenia/osteoporosis), low muscle mass (sarcopenia), high fat mass (obesity), or high fat with low muscle mass (sarcopenic obesity). Moreover, advances over the past three decades in the sensitivity and quality of imaging not just to discern the amount and distribution of adipose and lean tissue but also to differentiate layers or depots within tissues and cells is enhancing our understanding of distinct mechanistic, metabolic, and functional roles of body composition within human phenotypes. In this review, we focus on advances in imaging technologies that show great promise for future investigation of human body composition and how they are being used to address the pandemic of obesity, metabolic syndrome, and diabetes.

Correlation of X-ray computed tomography with quantitative nuclear magnetic resonance methods for pre-clinical measurement of adipose and lean tissues in living mice

Numerous obesity studies have coupled murine models with non-invasive methods to quantify body composition in longitudinal experiments, including X-ray computed tomography (CT) or quantitative nuclear magnetic resonance (QMR). Both microCT and QMR have been separately validated with invasive techniques of adipose tissue quantification, like post-mortem fat extraction and measurement. Here we report a head-to-head study of both protocols using oil phantoms and mouse populations to determine the parameters that best align CT data with that from QMR. First, an in vitro analysis of oil/water mixtures was used to calibrate and assess the overall accuracy of microCT vs. QMR data. Next, experiments were conducted with two cohorts of living mice (either homogenous or heterogeneous by sex, age and genetic backgrounds) to assess the microCT imaging technique for adipose tissue segmentation and quantification relative to QMR. Adipose mass values were obtained from microCT data with three different resolutions, after which the data were analyzed with different filter and segmentation settings. Strong linearity was noted between the adipose mass values obtained with microCT and QMR, with optimal parameters and scan conditions reported herein. Lean tissue (muscle, internal organs) was also segmented and quantified using the microCT method relative to the analogous QMR values. Overall, the rigorous calibration and validation of the microCT method for murine body composition, relative to QMR, ensures its validity for segmentation, quantification and visualization of both adipose and lean tissues.

Noninvasive measurements of body composition and body water via quantitative magnetic resonance, deuterium water, and dual-energy x-ray absorptiometry in cats

OBJECTIVE

To compare quantitative magnetic resonance (QMR), dual-energy x-ray absorptiometry (DXA), and deuterium oxide (D2O) dilution methods for measurement of total body water (TBW), lean body mass (LBM), and fat mass (FM) in healthy cats and to assess QMR precision and accuracy.

ANIMALS

Domestic shorthair cats (58 and 32 cats for trials 1 and 2, respectively).

PROCEDURES

QMR scans of awake cats performed with 2 units were followed by administration of D2O tracer (100 mg/kg, PO). Cats then were anesthetized, which was followed by QMR and DXA scans. Jugular blood samples were collected before and 120 minutes after D2O administration.

RESULTS

QMR precision was similar between units (coefficient of variation < 2.9% for all measures). Fat mass, LBM, and TBW were similar for awake or sedated cats and differed by 4.0%, 3.4%, and 3.9%, respectively, depending on the unit. The QMR minimally underestimated TBW (1.4%) and LBM (4.4%) but significantly underestimated FM (29%), whereas DXA significantly underestimated LBM (9.2%) and quantitatively underestimated FM (9.3%). A significant relationship with D2O measurement was detected for all QMR (r(2) > 0.84) and DXA (r(2) > 0.84) measurements.

CONCLUSIONS AND CLINICAL RELEVANCE

QMR was useful for determining body composition in cats; precision was improved over DXA. Quantitative magnetic resonance can be used to safely and rapidly acquire data without the need for anesthesia, facilitating frequent monitoring of weight changes in geriatric, extremely young, or ill pets. Compared with the D2O dilution method, QMR correction equations provided accurate data over a range of body compositions.

Noninvasive measurements of body composition and body water via quantitative magnetic resonance, deuterium water, and dual-energy x-ray absorptiometry in awake and sedated dogs

OBJECTIVE

To compare quantitative magnetic resonance (QMR), dual-energy x-ray absorptiometry (DXA), and deuterium oxide (D2O) methods for measurement of total body water (TBW), lean body mass (LBM), and fat mass (FM) in healthy dogs and to assess QMR accuracy.

ANIMALS

58 Beagles (9 months to 11.5 years old).

PROCEDURES

QMR scans were performed on awake dogs. A D2O tracer was administered (100 mg/kg, PO) immediately before dogs were sedated, which was followed by a second QMR or DXA scan. Jugular blood samples were collected before and 120 minutes after D2O administration.

RESULTS

TBW, LBM, and FM determined via QMR were not significantly different between awake or sedated dogs, and means differed by only 2.0%, 2.2%, and 4.3%, respectively. Compared with results for D2O dilution, QMR significantly underestimated TBW (10.2%), LBM (13.4%), and FM (15.4%). Similarly, DXA underestimated LBM (7.3%) and FM (8.4%). A significant relationship was detected between FM measured via D2O dilution and QMR (r(2) > 0.89) or DXA (r(2) > 0.88). Even though means of TBW and LBM differed significantly between D2O dilution and QMR or DXA, values were highly related (r(2) > 0.92).

CONCLUSIONS AND CLINICAL RELEVANCE

QMR was useful for determining body composition in dogs and can be used to safely and rapidly acquire accurate data without the need for sedation or anesthesia. These benefits can facilitate frequent scans, particularly in geriatric, extremely young, or ill pets. Compared with the D2O dilution method, QMR correction equations provided accurate assessment over a range of body compositions.

Body fat in Singaporean infants: development of body fat prediction equations in Asian newborns

BACKGROUND/OBJECTIVES

Prediction equations are commonly used to estimate body fat from anthropometric measurements, but are population specific. We aimed to establish and validate a body composition prediction formula for Asian newborns, and compared the performance of this formula with that of a published equation.

SUBJECTS/METHODS

Among 262 neonates (174 from day 0, 88 from days 1-3 post delivery) from a prospective cohort study, body composition was measured using air-displacement plethysmography (PEA POD), with standard anthropometric measurements, including triceps and subscapular skinfolds. Using fat mass measurement by PEA POD as a reference, stepwise linear regression was utilized to develop a prediction equation in a randomly selected subgroup of 62 infants measured on days 1-3, which was then validated in another subgroup of 200 infants measured on days 0-3.

RESULTS

Regression analyses revealed subscapular skinfolds, weight, gender and gestational age were significant predictors of neonatal fat mass, explaining 81.1% of the variance, but not triceps skinfold or ethnicity. By Bland-Altman analyses, our prediction equation revealed a non-significant bias with limits of agreement (LOA) similar to those of a published equation for infants measured on days 1-3 (95% LOA: (-0.25, 0.26) kg vs (-0.23, 0.21) kg) and on day 0 (95% LOA: (-0.19, 0.17) kg vs (-0.17, 0.18) kg). The published equation, however, exhibited a systematic bias in our sample.

CONCLUSIONS

Our equation requires only one skinfold site measurement, which can significantly reduce time and effort. It does not require the input of ethnicity and, thus, aid its application to other Asian neonatal populations.

Air displacement plethysmography, dual-energy X-ray absorptiometry, and total body water to evaluate body composition in preschool-age children

Anthropometrics and body mass index are only proxies in the evaluation of adiposity in the pediatric population. Air displacement plethysmography technology was not available for children aged 6 months to 9 years until recently. Our study was designed to test the precision of air displacement plethysmography (ADP) in measuring body fat mass in children at ages 3 to 5 years compared with a criterion method, deuterium oxide dilution (D(2)O), which estimates total body water and a commonly used methodology, dual-energy x-ray absorptiometry (DXA). A prospective, cross-sectional cohort of 66 healthy children (35 girls) was recruited in the central Arkansas region between 2007 and 2009. Weight and height were obtained using standardized procedures. Fat mass (%) was measured using ADP, DXA, and D(2)O. Concordance correlation coefficient and Bland-Altman plots were used to investigate the precision of the ADP techniques against D(2)O and DXA in children at ages 3 to 5 years. ADP concordance correlation coefficient for fat mass was weak (0.179) when compared with D(2)O. Bland-Altman plots revealed a low accuracy and large scatter of ADP fat mass (%) results (mean=-2.5, 95% CI -20.3 to 15.4) compared with D(2)O. DXA fat mass (%) results were more consistent although DXA systematically overestimated fat mass by 4% to 5% compared with D(2)O. Compared with D(2)O, ADP does not accurately assess percent fat mass in children aged 3 to 5 years. Thus, D(2)O, DXA, or quantitative nuclear magnetic resonance may be considered better options for assessing fat mass in young children.