Abstract

The aim of this study was to assess the accuracy of a new formula for the calculation of an estimated fetal weight (EFW) and to evaluate value of fetal visceral adipose tissue (VAT) and abdominal subcutaneous fat (SF) thickness on the prediction of birth weight. In this prospective study, fetal biometry, EFW, fetal VAT and SF thickness were measured in low-risk 37–41 gestational weeks pregnant women by ultrasonography. The linear regression analysis was performed to investigate the relationship between birth weight and obstetric measurements. It was found that the most important factors in the prediction of a birth weight were the abdominal circumference (AC), SF and VAT. The new formula for EFW was EFW = − 2748 . 622 + 13 . 811 * AC + 56 . 795 * SF + 17 . 913 * VAT According to the Hadlock 3 and the new formula, 92% and 95% of all fetal weight estimations were within 10% of actual birth weight, respectively. Measurement of VAT and SF thickness in prediction of fetal weight could reduce a weight estimation error. Impact statement What is already known on this subject? An accurate prediction of fetal weight during gestation provides useful information for assessing the fetal and newborn health status. As the detection of growth abnormalities is vital, there is a need for a reliable method of assessing birth weight during labour. Unfortunately, although different methods are available, a simple, quick and reliable method of assessing birth weight is still in debate. Fetal visceral adipose (VAT) tissue measurement is a new method which could be used for the correct estimation of fetal weight. Like adults, the VAT and subcutaneous fat tissue (SF) thickness could be correlated with the weight and body-mass index. What do the results of this study add? It was found that SF and VAT are important factors in the prediction of birth weight, like the abdominal circumference (AC). What are the implications of these findings for clinical practice and/or further research? The measurement of VAT and SF thickness in prediction of fetal weight could reduce a weight estimation error.

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