265
Views
5
CrossRef citations to date
0
Altmetric
Original Articles

Influence of maternal obesity on the accuracy of ultrasonography birth weight prediction

ORCID Icon, , , & ORCID Icon
Pages 3056-3061 | Received 30 Oct 2018, Accepted 07 Jan 2019, Published online: 28 Jan 2019
 

Abstract

Objective: The aim of the study was to investigate whether the accuracy of ultrasound estimates of fetal weight (EFW) was dependent on maternal obesity.

Study design: A prospective cross-sectional study of 1064 singleton pregnant women classified according to body mass index (BMI) into two categories: normal (BMI < 25 kg/m2, n = 863) and obese (BMI ≥ 35 kg/m2, n = 201) was conducted. EFW were calculated using Hadlock’s formula, and the difference between EFW and the actual birthweight (absolute percent error) was analyzed in both groups. Spearman’s correlation was used to assess the relationship between ultrasound performance (absolute error), maternal BMI, and actual birth weight.

Results: Median absolute error of sonographic EFW was 5.90 and 6.47% for the normal and obese groups, respectively (p .38). A correlation between EFW and birth weight (BW) was found in both groups, r = 0.755 (p < .001) and r = 0.753 (p < .001), respectively. The correlation between absolute error, maternal BMI, and fetal birth weight was poor.

Conclusions: Maternal obesity is unrelated to the accuracy of sonographic EFW, and regardless of maternal or fetal size, ultrasound is currently an accurate method of prediction for both obese and normal weight pregnant women.

Disclosure statement

No potential conflict of interest was reported by the authors.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access
  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 65.00 Add to cart
* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.