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.

Higher infant body fat with excessive gestational weight gain in overweight women.

OBJECTIVE: Gestational weight gain (GWG) is positively associated with birthweight and maternal prepregnancy body mass index (BMI) is directly related to infant fat mass (FM). This study examined whether differences exist in infant body composition based on 2009 GWG recommendations. STUDY DESIGN: Body composition was measured in 306 infants, and GWG was categorized as appropriate or excessive. Analysis of covariance was used to investigate the effects of GWG and prepregnancy BMI and their interaction on infant body composition. RESULTS: Within the appropriate group, infants from obese mothers had greater percent fat (%fat) and FM than offspring from normal and overweight mothers. Within the excessive group, infants from normal mothers had less %fat and FM than infants from overweight and obese mothers. A difference was found for %fat and FM within the overweight group between GWG categories. CONCLUSION: Excessive GWG is associated with greater infant body fat and the effect is greatest in overweight women.

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.

Increased Visceral Adipose Tissue Without Weight Retention at 59 Weeks Postpartum.

OBJECTIVE: This study aimed to determine whether controlling maternal gestational weight gain (GWG) influences adipose tissue distribution at 1 year postpartum. METHODS: Women with overweight or obesity (n = 210, BMI ≥ 25 or ≥ 30) were randomized to a lifestyle intervention (LI) designed to control GWG or to usual obstetrical care (UC). Measures included anthropometry, whole-body magnetic resonance imaging for visceral (VAT), intermuscular, and subcutaneous adipose tissue, and cardiometabolic risk factors in pregnancy (15 and 35 weeks) and after delivery (15 and 59 weeks). RESULTS: Baseline (15 weeks) characteristics were similar (mean [SD]: age, 33.8 [4.3] years; weight, 81.9 [13.7] kg; BMI, 30.4 [4.5]; gestational age at randomization, 14.9 [0.8] weeks). LI had less GWG (1.79 kg; P = 0.003) and subcutaneous adipose tissue gain at 35 weeks gestation (P < 0.01). UC postpartum weight (2.92 kg) was higher at 15 weeks but not different from baseline or LI at 59 weeks postpartum. Postpartum VAT increased from baseline in LI by 0.23 kg at 15 weeks and 0.55 kg at 59 weeks; in UC, it increased by 0.34 kg at 15 and 59 weeks. Intermuscular adipose tissue remained elevated in LI (0.22 kg) at 59 weeks. VAT was associated with several cardiometabolic risk factors at 59 weeks. CONCLUSIONS: Despite no weight retention at 59 weeks postpartum, women had increased VAT by ~30%. Postpartum modifiable behaviors are warranted to lower the risk of VAT retention.

Greater Neonatal Fat-Free Mass and Similar Fat Mass Following a Randomized Trial to Control Excess Gestational Weight Gain.

OBJECTIVE: The objective of this study was to determine the effectiveness of controlling maternal gestational weight gain (GWG) in the second and third trimesters on neonate body composition. METHODS: Two hundred ten healthy women with overweight (25 > BMI < 30) or obesity (BMI ≥ 30) were randomly assigned to a lifestyle intervention (LI) program focused on controlling GWG through nutrition and activity behaviors or to usual obstetrical care (UC). Infant fat and fat-free mass (FFM) at birth were measured by using air displacement plethysmography (PEA POD) and by using quantitative magnetic resonance (QMR). RESULTS: At baseline, there were no between-group differences in maternal characteristics (mean [SD]): age: 33.8 (4.3) years, weight: 81.9 (13.7) kg, BMI: 30.4 (4.5), and gestational age at randomization: 14.9 (0.8) weeks. GWG was less in the LI group by 1.79 kg (P = 0.003) or 0.0501 kg/wk (P = 0.002). Compared with UC infants, LI infants had greater weight (131 ± 59 g P = 0.03), FFM (98 ± 45 g; P = 0.03) measured by PEA POD, and lean mass (105 ± 38 g; P = 0.006) measured by QMR. Fat mass and percent fat were not significantly different. CONCLUSIONS: Intervening in women with overweight and obesity through behaviors promoting healthy diet and physical activity to control GWG resulted in neonates with similar fat and greater FFM.

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.

An anthropometric model to estimate neonatal fat mass using air displacement plethysmography.

BACKGROUND: Current validated neonatal body composition methods are limited/impractical for use outside of a clinical setting because they are labor intensive, time consuming, and require expensive equipment. The purpose of this study was to develop an anthropometric model to estimate neonatal fat mass (kg) using an air displacement plethysmography (PEA POD® Infant Body Composition System) as the criterion. METHODS: A total of 128 healthy term infants, 60 females and 68 males, from a multiethnic cohort were included in the analyses. Gender, race/ethnicity, gestational age, age (in days), anthropometric measurements of weight, length, abdominal circumference, skin-fold thicknesses (triceps, biceps, sub scapular, and thigh), and body composition by PEA POD® were collected within 1-3 days of birth. Backward stepwise linear regression was used to determine the model that best predicted neonatal fat mass. RESULTS: The statistical model that best predicted neonatal fat mass (kg) was: -0.012 -0.064*gender + 0.024*day of measurement post-delivery -0.150*weight (kg) + 0.055*weight (kg)2 + 0.046*ethnicity + 0.020*sum of three skin-fold thicknesses (triceps, sub scapular, and thigh); R2 = 0.81, MSE = 0.08 kg. CONCLUSIONS: Our anthropometric model explained 81% of the variance in neonatal fat mass. Future studies with a greater variety of neonatal anthropometric measurements may provide equations that explain more of the variance.