Ranasinha Sanjeeva, Enticott Joanne, Harrison Cheryce, Teede Helena J
Monash Centre for Health Research and Implementation, Monash University, Melbourne, Victoria, Australia.
Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia.
BMJ Open. 2025 Mar 22;15(3):e087589. doi: 10.1136/bmjopen-2024-087589.
Monitoring and predicting optimal gestational weight gain (GWG) is important for maternal and child health. However, with recommendations based on total pregnancy GWG, available tools for real-time use in pregnancy care are lacking. These tools are prioritised by the WHO to enable healthcare providers to identify, monitor and target lifestyle interventions for those at high risk of suboptimal GWG and subsequent adverse health outcomes for mothers and babies.
This study aims to identify risk factors associated with GWG and to use these to develop an antenatal risk prediction tool for use during pregnancy to guide healthcare providers and women on optimal GWG, based on early pregnancy weight gain data.
Routine health data from the Australian Monash Health Network birthing outcome system were used to analyse GWG in women of different body mass index (BMI) categories. Using data from 10 to 15, 15-20 and 15-25 weeks of pregnancy, we predicted the probability of women gaining inadequate or excessive total GWG by term. We used multinomial logistic regression to investigate associations between US National Academy of Medicine (NAM) classifications (inadequate, sufficient and excessive GWG) and BMI, age, country of birth (COB) by region, parity, socioeconomic status and visit frequency.
We used individual patient data routinely collected during care from one of the largest antenatal health networks in Australia.
The study included 17 397 women from 149 countries (based on the COB) of diverse socioeconomic backgrounds, with pregnancies between 2017 and 2021.
Gestational weight gain.
Overall, 31.5% gained below, 35.7% within and 32.8% above NAM GWG recommendations. Risk factors for excess GWG were higher BMI and maternal COB by region. Compared with the healthy BMI group, the overweight group has a 4.05 times higher adjusted relative risk of excess GWG (95% CI 3.37 to 4.80), and the obese group had a relative risk of 6.64 (95% CI 5.27 to 8.37). The risk prediction tool receiver operating characteristic curve was 0.81 for the 15-25 week, 0.80 for the 15-20 week and 0.69 for the 10-15 week GWG groups, with excellent performance in both discrimination and reliability.
From a large population of women from diverse socioeconomic backgrounds, we have identified risk factors for suboptimal GWG and developed and internally validated a risk prediction tool for attainment of recommended GWG from early pregnancy, with high performance. This tool is designed to enable clinicians to prospectively predict attainment of NAM GWG recommendations to guide risk stratification, monitoring and appropriate intervention for those at risk of suboptimal GWG.
监测和预测最佳孕期体重增加（GWG）对母婴健康至关重要。然而，基于孕期总体重增加的建议，目前缺乏可在孕期护理中实时使用的工具。世界卫生组织将这些工具列为优先事项，以便医疗保健提供者能够识别、监测并针对那些GWG不理想及随后母婴出现不良健康结局风险较高的人群进行生活方式干预。
本研究旨在确定与GWG相关的风险因素，并利用这些因素开发一种产前风险预测工具，以便在孕期使用，根据孕早期体重增加数据指导医疗保健提供者和孕妇实现最佳GWG。
利用澳大利亚莫纳什健康网络分娩结局系统的常规健康数据，分析不同体重指数（BMI）类别的女性的GWG情况。利用妊娠10至15周、15至20周和15至25周的数据，我们预测了足月时女性总体重增加不足或过多的概率。我们使用多项逻辑回归研究美国国家医学院（NAM）分类（体重增加不足、充足和过多）与BMI、年龄、按地区划分的出生国家（COB）、产次、社会经济地位和就诊频率之间的关联。
我们使用了在澳大利亚最大的产前健康网络之一的护理过程中常规收集的个体患者数据。
该研究纳入了来自149个国家（根据COB）、社会经济背景各异的17397名女性，她们的妊娠时间在2017年至2021年之间。
孕期体重增加。
总体而言，31.5%的女性体重增加低于NAM的GWG建议，35.7%的女性体重增加在建议范围内，32.8%的女性体重增加高于建议。体重增加过多的风险因素包括较高的BMI和按地区划分的母亲COB。与健康BMI组相比，超重组体重增加过多的调整后相对风险高4.05倍（95%CI 3.37至4.80），肥胖组的相对风险为6.64（95%CI 5.27至8.37）。风险预测工具的受试者工作特征曲线在15至25周GWG组为0.81，在15至20周GWG组为0.80，在10至15周GWG组为0.69，在区分能力和可靠性方面均表现出色。
从大量社会经济背景各异的女性群体中，我们确定了GWG不理想的风险因素，并开发并在内部验证了一种从孕早期实现推荐GWG的风险预测工具，其性能良好。该工具旨在使临床医生能够前瞻性地预测是否达到NAM的GWG建议，以指导对GWG不理想风险人群的风险分层、监测和适当干预。
