Customized Fetal Growth Charts for Parents' Characteristics, Race, and Parity by Quantile Regression Analysis: A Cross‐sectional Multicenter Italian Study. (1st January 2016)

• Record Type: Journal Article
• Authors: Ghi, Tullio; Cariello, Luisa; Rizzo, Ludovica; Ferrazzi, Enrico; Periti, Enrico; Prefumo, Federico; Stampalija, Tamara; Viora, Elsa; Verrotti, Carla; Rizzo, Giuseppe
• Is Part Of: Journal of ultrasound in medicine. Volume 35:Number 1(2016)
• Page Start: 83
• Page End: 92
• Publication Date: 2016-01-01
• Subjects: customized growth charts -- fetal biometry -- obstetric ultrasound -- quantile regression analysis; Ultrasonics in medicine -- Periodicals; Ultrasonics; Ultrasonography; Ultrasonics in medicine; Electronic journals; Periodicals; Periodicals; 616.07543
• DOI: 10.7863/ultra.15.03003
• Languages: English
• ISSNs: 0278-4297

Abstract

Abstract : Objectives: The purpose of this study was to construct fetal biometric charts between 16 and 40 weeks' gestation that were customized for parental characteristics, race, and parity, using quantile regression analysis. Methods: In a multicenter cross‐sectional study, 8070 sonographic examinations from low‐risk pregnancies between 16 and 40 weeks' gestation were analyzed. The fetal measurements obtained were biparietal diameter, head circumference, abdominal circumference, and femur diaphysis length. Quantile regression was used to examine the impact of parental height and weight, parity, and race across biometric percentiles for the fetal measurements considered. Results: Paternal and maternal height were significant covariates for all of the measurements considered ( P < .05). Maternal weight significantly influenced head circumference, abdominal circumference, and femur diaphysis length. Parity was significantly associated with biparietal diameter and head circumference. Central African race was associated with head circumference and femur diaphysis length, whereas North African race was only associated with femur diaphysis length. Conclusions: In this study we constructed customized biometric growth charts using quantile regression in a large cohort of low‐risk pregnancies. These charts offer the advantage of defining individualized normal ranges of fetal biometric parameters at each specific percentile corrected for parental height and weight, parity, and race. This study supports the importance of including these variables in routine sonographic screening for fetal growth abnormalities.