Centre for Child Health Research, Faculty of Medicine and Life Sciences, University of Tampere and Tampere University Hospital, Tampere, Finland.
Department of Paediatrics, Tampere University Hospital, Tampere, Finland.
Matern Child Nutr. 2018 Jul;14(3):e12585. doi: 10.1111/mcn.12585. Epub 2018 Jan 8.
More than 20 million babies are born with low birthweight annually. Small newborns have an increased risk for mortality, growth failure, and other adverse outcomes. Numerous antenatal risk factors for small newborn size have been identified, but individual interventions addressing them have not markedly improved the health outcomes of interest. We tested a hypothesis that in low-income settings, newborn size is influenced jointly by multiple maternal exposures and characterized pathways associating these exposures with newborn size. This was a prospective cohort study of pregnant women and their offspring nested in an intervention trial in rural Malawi. We collected information on maternal and placental characteristics and used regression analyses, structural equation modelling, and random forest models to build pathway maps for direct and indirect associations between these characteristics and newborn weight-for-age Z-score and length-for-age Z-score. We used multiple imputation to infer values for any missing data. Among 1,179 pregnant women and their babies, newborn weight-for-age Z-score was directly predicted by maternal primiparity, body mass index, and plasma alpha-1-acid glycoprotein concentration before 20 weeks of gestation, gestational weight gain, duration of pregnancy, placental weight, and newborn length-for-age Z-score (p < .05). The latter 5 variables were interconnected and were predicted by several more distal determinants. In low-income conditions like rural Malawi, maternal infections, inflammation, nutrition, and certain constitutional factors jointly influence newborn size. Because of this complex network, comprehensive interventions that concurrently address multiple adverse exposures are more likely to increase mean newborn size than focused interventions targeting only maternal nutrition or specific infections.
每年有超过 2000 万婴儿出生时体重过轻。新生儿体重过轻会增加死亡率、生长发育不良和其他不良后果的风险。已经确定了许多与新生儿体重小相关的产前风险因素,但针对这些因素的个别干预措施并没有显著改善相关的健康结果。我们检验了一个假设,即在低收入环境中,新生儿的大小受到多种产妇暴露因素的共同影响,并确定了将这些暴露因素与新生儿大小联系起来的途径。这是在马拉维农村一项干预试验中嵌套的一项前瞻性队列研究,研究了孕妇及其后代。我们收集了有关产妇和胎盘特征的信息,并使用回归分析、结构方程模型和随机森林模型,构建了这些特征与新生儿体重-年龄 Z 评分和身长-年龄 Z 评分之间直接和间接关联的途径图。我们使用多重插补来推断任何缺失数据的值。在 1179 名孕妇及其婴儿中,新生儿体重-年龄 Z 评分直接由产妇初产、身体质量指数和妊娠 20 周前的血浆α-1-酸性糖蛋白浓度、妊娠期体重增加、妊娠持续时间、胎盘重量和新生儿身长-年龄 Z 评分预测(p < 0.05)。后 5 个变量相互关联,并由几个更遥远的决定因素预测。在像马拉维农村这样的低收入环境中,母亲感染、炎症、营养和某些体质因素共同影响新生儿的大小。由于这种复杂的网络,综合干预措施同时解决多种不良暴露的可能性比针对特定感染或特定营养的集中干预措施更有可能增加新生儿的平均大小。