The Generation R Study Group (AE006), Erasmus Medical Center, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands.
Eur J Epidemiol. 2011 Dec;26(12):919-26. doi: 10.1007/s10654-011-9629-7. Epub 2011 Nov 15.
Maternal and fetal characteristics are important determinants of fetal growth potential, and should ideally be taken into consideration when evaluating fetal growth variation. We developed a model for individually customised growth charts for estimated fetal weight, which takes into account physiological maternal and fetal characteristics known at the start of pregnancy. We used fetal ultrasound data of 8,162 pregnant women participating in the Generation R Study, a prospective, population-based cohort study from early pregnancy onwards. A repeated measurements regression model was constructed, using backward selection procedures for identifying relevant maternal and fetal characteristics. The final model for estimating expected fetal weight included gestational age, fetal sex, parity, ethnicity, maternal age, height and weight. Using this model, we developed individually customised growth charts, and their corresponding standard deviations, for fetal weight from 18 weeks onwards. Of the total of 495 fetuses who were classified as small size for gestational age (<10th percentile) when fetal weight was evaluated using the normal population growth chart, 80 (16%) were in the normal range when individually customised growth charts were used. 550 fetuses were classified as small size for gestational age using individually customised growth charts, and 135 of them (25%) were classified as normal if the unadjusted reference chart was used. In conclusion, this is the first study using ultrasound measurements in a large population-based study to fit a model to construct individually customised growth charts, taking into account physiological maternal and fetal characteristics. These charts might be useful for use in epidemiological studies and in clinical practice.
母体和胎儿特征是胎儿生长潜力的重要决定因素,在评估胎儿生长变异时,理想情况下应将其考虑在内。我们开发了一种用于估计胎儿体重的个体化定制生长图表的模型,该模型考虑了妊娠开始时已知的生理母体和胎儿特征。我们使用了 8162 名参与“世代研究”的孕妇的胎儿超声数据,这是一项从早孕开始的前瞻性、基于人群的队列研究。使用回归模型进行了构建,使用向后选择程序来识别相关的母体和胎儿特征。估计预期胎儿体重的最终模型包括胎龄、胎儿性别、产次、种族、母亲年龄、身高和体重。使用该模型,我们从 18 周开始为胎儿体重开发了个体化定制的生长图表及其相应的标准差。在使用正常人群生长图表评估胎儿体重时,共有 495 名胎儿被归类为小于胎龄儿(<第 10 百分位数),其中 80 名(16%)在使用个体化定制生长图表时处于正常范围内。使用个体化定制生长图表,550 名胎儿被归类为小于胎龄儿,其中 135 名(25%)如果使用未调整的参考图表,则被归类为正常。总之,这是第一项使用超声测量在大型基于人群的研究中拟合模型来构建个体化定制生长图表的研究,考虑了生理母体和胎儿特征。这些图表可能在流行病学研究和临床实践中有用。