Dataset Information

Body composition and growth in full-term small for gestational age and large for gestational age Swedish infants assessed with air displacement plethysmography at birth and at 3-4 months of age.

ABSTRACT: BACKGROUND:Being born small for gestational age (SGA) or large for gestational age (LGA) has short and long term metabolic consequences. There is a growing interest in the extent to which body composition, both in the short and the long term, differs in infants born at the extremes of these birth weights. METHODS:Body composition in 25 SGA and 25 LGA infants were assessed during the first days of life and at 3-4 months of age using air displacement plethysmography. RESULTS:SGA infants had significantly lower body fat (%) at birth compared to LGA infants. SGA infants increased their body weight and length at a significantly higher rate between birth and 3-4 months than LGA infants. Fat mass (g) in SGA infants increased 23 times between birth and 3-4 months of age compared to 2.8 times for LGA infants. At 3-4 months of age LGA infants reached a threshold in body fat (%) while SGA infants were still gaining body fat (%). CONCLUSION:Several significant differences have been identified between SGA and LGA infants, indicating that the effects of intrauterine life continues to play an important role in body composition and growth during the first 3-4 months of life.

SUBMITTER: Larsson A

PROVIDER: S-EPMC6519902 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Body composition and growth in full-term small for gestational age and large for gestational age Swedish infants assessed with air displacement plethysmography at birth and at 3-4 months of age.

Larsson Anna A Ottosson Peter P Törnqvist Caroline C Olhager Elisabeth E

PloS one 20190515 5

<h4>Background</h4>Being born small for gestational age (SGA) or large for gestational age (LGA) has short and long term metabolic consequences. There is a growing interest in the extent to which body composition, both in the short and the long term, differs in infants born at the extremes of these birth weights.<h4>Methods</h4>Body composition in 25 SGA and 25 LGA infants were assessed during the first days of life and at 3-4 months of age using air displacement plethysmography.<h4>Results</h4> ...[more]

PMID: 31091240

Similar Datasets

Project description:With the greatest burden of infant undernutrition and morbidity in low and middle income countries (LMICs), there is a need for suitable approaches to monitor infants in a simple, low-cost and effective manner. Anthropometry continues to play a major role in characterising growth and nutritional status.We developed a range of models to aid in identifying neonates at risk of malnutrition. We first adopted a logistic regression approach to screen for a composite neonatal morbidity, low and high body fat (BF%) infants. We then developed linear regression models for the estimation of neonatal fat mass as an assessment of body composition and nutritional status.We fitted logistic regression models combining up to four anthropometric variables to predict composite morbidity and low and high BF% neonates. The greatest area under receiver-operator characteristic curves (AUC with 95% confidence intervals (CI)) for identifying composite morbidity was 0.740 (0.63, 0.85), resulting from the combination of birthweight, length, chest and mid-thigh circumferences. The AUCs (95% CI) for identifying low and high BF% were 0.827 (0.78, 0.88) and 0.834 (0.79, 0.88), respectively. For identifying composite morbidity, BF% as measured via air displacement plethysmography showed strong predictive ability (AUC 0.786 (0.70, 0.88)), while birthweight percentiles had a lower AUC (0.695 (0.57, 0.82)). Birthweight percentiles could also identify low and high BF% neonates with AUCs of 0.792 (0.74, 0.85) and 0.834 (0.79, 0.88). We applied a sex-specific approach to anthropometric estimation of neonatal fat mass, demonstrating the influence of the testing sample size on the final model performance.These models display potential for further development and evaluation in LMICs to detect infants in need of further nutritional management, especially where traditional methods of risk management such as birthweight for gestational age percentiles may be variable or non-existent, or unable to detect appropriately grown, low fat newborns.

Dataset Information

Body composition and growth in full-term small for gestational age and large for gestational age Swedish infants assessed with air displacement plethysmography at birth and at 3-4 months of age.

Publications

Body composition and growth in full-term small for gestational age and large for gestational age Swedish infants assessed with air displacement plethysmography at birth and at 3-4 months of age.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets