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

Cauble, Jennifer S.; Dewi, Mira; Hull, Holly R.

doi:10.1186/s12887-017-0844-6

Cited by 35 publications

(40 citation statements)

References 44 publications

(67 reference statements)

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“…Body fat mass was determined according to the following validated equation: Fat mass = 1000 (0.39055 (birth weight [grams]/1000) + 0.0453 (flank skinfold (mm) − 0.03237 (length [cm]) + 0.54657. Four neonates had negative fat mass according to the equation, and a fat mass of zero grams was substituted.…”

Section: Methodsmentioning

confidence: 99%

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

et al. 2019

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Summary 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.

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Section: Methodsmentioning

confidence: 99%

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

et al. 2019

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“…Especially, postnatal growth restriction of extremely preterm infants still remains a big challenge worldwide and is associated with an impaired neurodevelopmental outcome (2,3). Evaluation of the body composition and especially fat mass (FM) gain seems to be more accurate to evaluate the nutritional status in comparison to anthropometric parameters including Z-scores (4,5). The optimal body composition and reference values in ex premature infants at term-equivalent age are still unknown (6,7).…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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.

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“…The use of skinfold thickness to estimate FM is commonly used to circumvent the limitations of the aforementioned techniques, however; their use in infants is controversial, and the use of the correct prediction equations that account for ethnicity and age of the source population is essential in order to gain accurate estimates . Several studies have demonstrated low concordance in FM estimation between skinfold thickness and gold standard body composition measurements . This leaves a significant gap in body composition assessment during a critical window of growth that is important for understanding the development of obesity in research settings.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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. K E Y W O R D S air displacement plethysmography, body composition, dual-energy X-ray absorptiometry, fat mass, quantitative nuclear magnetic resonance 1 | INTRODUCTION Recent projections estimate that approximately 57% of children will be obese by 35 years of age, with half of those children developing obesity much earlier in childhood. 1 Previous analyses have shown that body mass index (BMI) >85th percentile at 2 weeks of age is associated with a two-fold risk of being overweight by the age of five. 2Further, increased adiposity (%fat mass [FM]) at birth persists through 5 months of age independent of early infant feeding and rapid infant growth. 3 BMI is commonly used in infants and children to assess growth, 4 effectiveness of intervention to reduce paediatric obesity, 5 and for prediction of obesity 6 and chronic diseases development. 7,8 While BMI in adults is related to clinical outcomes, its predictive value and usefulness in infants, children, and adolescents are less clear. 9 Further, complicating the use of BMI in infants and children is the interindividual variability for periods of rapid growth, for which BMI cannot Abbreviations: 4-C, four-compartment; ADP, air displacement plethysmography; BMI, body mass index; BV, body volume; BW, body weight; BMC, bone mineral content; DXA, dualenergy X-ray absorptiometry; FM, fat mass; MRI, magnetic resonance imaging; QMR, quantitative magnetic resonance; TBW, total body water.

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

Cited by 35 publications

References 44 publications

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

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

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

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

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