The relative importance of maternal body mass index and glucose levels for prediction of large-for-gestational-age births.
The relative importance of maternal body mass index and glucose levels for prediction of large-for-gestational-age births.
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DOI：
10.1186/s12884-015-0722-x
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发表时间：
2015-10-29
影响因子：
3.1
通讯作者：
Källén K
中科院分区：
文献类型：
--
作者：
Berntorp K;Anderberg E;Claesson R;Ignell C;Källén K
妊娠期糖尿病（GDM）的风险随着母体体重指数（BMI）的增加而显著增加。本研究的目的是评估母亲BMI和葡萄糖水平在预测大胎龄（LGA）出生中的相对重要性。这项观察性队列研究是基于2003-2005年在瑞典南部分娩的妇女。从以人口为基础的围产期登记中检索了10 974例怀孕的信息。孕28周行75 g口服葡萄糖耐量试验（OGTT）测定2 h血浆葡萄糖浓度。在妊娠早期获得BMI。数据集分为开发集和验证集。利用发育集进行多元logistic回归分析，确定与LGA相关的母体特征。通过受试者工作特征（ROC）曲线评估LGA的预测，LGA定义为出生体重> +2个标准差的平均值。在最后的多变量模型中，包括BMI、2小时血糖水平和产妇人口统计数据，与LGA相关性最强的因素是BMI（优势比1.1,95%可信区间[CI] 1.08-1.30）。基于总数据集，2 h葡萄糖水平预测LGA的ROC曲线下面积（AUC）为0.54 (95% CI 0.48 ~ 0.60)，表现不佳。使用验证数据库，最终多重模型的AUC为0.69 (95% CI 0.66-0.72)，与不包含2小时葡萄糖的模型的AUC相同（0.69,95% CI 0.66-0.72），大于包含2小时葡萄糖但不包含BMI的模型（0.63,95% CI 0.60-0.67）。OGTT的2小时血糖水平和母亲的BMI对LGA分娩的风险都有显著影响，但BMI的相对贡献更高。研究结果强调了关注孕妇健康体重的重要性，并在怀孕期间密切监测体重，以此作为降低胎儿过度生长风险的策略。
The risk of gestational diabetes mellitus (GDM) increases substantially with increasing maternal body mass index (BMI). The aim of the present study was to evaluate the relative importance of maternal BMI and glucose levels in prediction of large-for-gestational-age (LGA) births. This observational cohort study was based on women giving birth in southern Sweden during the years 2003–2005. Information on 10 974 pregnancies was retrieved from a population-based perinatal register. A 75-g oral glucose tolerance test (OGTT) was performed in the 28 week of pregnancy for determination of the 2-h plasma glucose concentration. BMI was obtained during the first trimester. The dataset was divided into a development set and a validation set. Using the development set, multiple logistic regression analysis was used to identify maternal characteristics associated with LGA. The prediction of LGA was assessed by receiver-operating characteristic (ROC) curves, with LGA defined as birth weight > +2 standard deviations of the mean. In the final multivariable model including BMI, 2-h glucose level and maternal demographics, the factor most strongly associated with LGA was BMI (odds ratio 1.1, 95 % confidence interval [CI] 1.08–1.30). Based on the total dataset, the area under the ROC curve (AUC) of 2-h glucose level to predict LGA was 0.54 (95 % CI 0.48–0.60), indicating poor performance. Using the validation database, the AUC for the final multiple model was 0.69 (95 % CI 0.66–0.72), which was identical to the AUC retrieved from a model not including 2-h glucose (0.69, 95 % CI 0.66–0.72), and larger than from a model including 2-h glucose but not BMI (0.63, 95 % CI 0.60–0.67). Both the 2-h glucose level of the OGTT and maternal BMI had a significant effect on the risk of LGA births, but the relative contribution was higher for BMI. The findings highlight the importance of concentrating on healthy body weight in pregnant women and closer monitoring of weight during pregnancy as a strategy for reducing the risk of excessive fetal growth.