PDF(Pubmed)
Abstract：
BACKGROUND: Early pregnancy nutritional status can be associated with adverse birth outcomes such as small-for-gestational age (SGA) and low birth weight (LBW). BMI (Body Mass Index) and MUAC (Mid-upper arm circumference) are easy to use assessments and are indicative of the pre-pregnancy nutritional status if obtained in the first trimester. This study primarily assesses the association of maternal nutritional status using BMI and MUAC with SGA in a community-based cohort of Pakistani women. It also aims to determine the predictive ability of MUAC and BMI in predicting SGA. Secondarily, we assessed the association between maternal nutrition and large for gestational age (LGA) and LBW.
METHODS: This study is a secondary analysis of an ongoing pregnancy cohort \"Pregnancy Risk Infant Surveillance and Measurement Alliance (PRISMA)\"in Ibrahim Hyderi and Rehri Goth, Karachi. PRISMA participants who were enrolled between January 2021 to August 2022 were included given they had a gestational age < 14 weeks confirmed via ultrasound, MUAC and BMI measurements were available and birth weight was captured within 72 hours. Multivariable logistic regression was used to determine an association between maternal nutritional status and SGA. The PRISMA study was approved by the Aga Khan University Ethics Review Committee (2021-5920-15,518).
RESULTS: Of 926 women included in the analysis, 26.6% (n = 247) had a low MUAC (< 23 cm) while 18.4% (n = 171) were underweight (BMI < 18.5 kg/m2). Nearly one third of low MUAC and underweight women delivered SGA infants (34.4 and 35.1% respectively). Underweight women and women with low MUAC had a statistically significant association with SGA (Underweight: OR 1.49, 95% CI 1.1,2.4; Low MUAC-OR 1.64, 95% CI 1.2,2.3) as well as LBW (Underweight: OR-1.63, 95% CI 1.1,2.4; Low MUAC-OR-1.63, 95% CI 1.2,2.3). ROC curves showed that MUAC and BMI had modest predictability for SGA (AUC < 0.7).
CONCLUSIONS: Maternal nutritional status as indicated by BMI and MUAC are strongly associated with adverse pregnancy outcomes including SGA, LGA and LBW. Although MUAC and BMI are widely used to determine maternal nutritional status, they have poor predictive ability for newborn size. Further research is needed to identify other tools or a combination of tools to better predict adverse birth outcomes in resource-limited settings and plan interventions.
METHODS: This study is a secondary analysis of an ongoing pregnancy cohort \"Pregnancy Risk Infant Surveillance and Measurement Alliance (PRISMA)\"in Ibrahim Hyderi and Rehri Goth, Karachi. PRISMA participants who were enrolled between January 2021 to August 2022 were included given they had a gestational age < 14 weeks confirmed via ultrasound, MUAC and BMI measurements were available and birth weight was captured within 72 hours. Multivariable logistic regression was used to determine an association between maternal nutritional status and SGA. The PRISMA study was approved by the Aga Khan University Ethics Review Committee (2021-5920-15,518).
RESULTS: Of 926 women included in the analysis, 26.6% (n = 247) had a low MUAC (< 23 cm) while 18.4% (n = 171) were underweight (BMI < 18.5 kg/m2). Nearly one third of low MUAC and underweight women delivered SGA infants (34.4 and 35.1% respectively). Underweight women and women with low MUAC had a statistically significant association with SGA (Underweight: OR 1.49, 95% CI 1.1,2.4; Low MUAC-OR 1.64, 95% CI 1.2,2.3) as well as LBW (Underweight: OR-1.63, 95% CI 1.1,2.4; Low MUAC-OR-1.63, 95% CI 1.2,2.3). ROC curves showed that MUAC and BMI had modest predictability for SGA (AUC < 0.7).
CONCLUSIONS: Maternal nutritional status as indicated by BMI and MUAC are strongly associated with adverse pregnancy outcomes including SGA, LGA and LBW. Although MUAC and BMI are widely used to determine maternal nutritional status, they have poor predictive ability for newborn size. Further research is needed to identify other tools or a combination of tools to better predict adverse birth outcomes in resource-limited settings and plan interventions.
摘要：
背景：孕早期营养状况可能与不良分娩结局相关，如小于胎龄儿（SGA）和低出生体重（LBW）。BMI（身体质量指数）和MUAC（中上臂围）易于使用的评估，并且如果在孕早期获得，则表明孕前营养状况。这项研究主要在基于社区的巴基斯坦妇女队列中使用BMI和MUAC与SGA评估产妇营养状况的关联。它还旨在确定MUAC和BMI在预测SGA中的预测能力。其次，我们评估了孕妇营养与大于胎龄(LGA)和LBW之间的关系.
方法：这项研究是对IbrahimHyderi和RehriGoth正在进行的妊娠队列“妊娠风险婴儿监测和测量联盟（PRISMA）”的二次分析，卡拉奇.在2021年1月至2022年8月之间招募的PRISMA参与者被纳入，因为他们的胎龄<14周，通过超声确认。MUAC和BMI测量是可用的，出生体重在72小时内被捕获。使用多变量逻辑回归来确定孕妇营养状况与SGA之间的关联。PRISMA研究获得了阿加汗大学伦理审查委员会的批准（2021-5920-15,518）。
结果：在分析中包括的926名女性中，26.6％（n=247）的MUAC较低（<23cm），而18.4％（n=171）的体重不足（BMI<18.5kg/m2）。近三分之一的低MUAC和体重不足的妇女分娩了SGA婴儿（分别为34.4％和35.1％）。体重过重的女性和MUAC低的女性与SGA（体重过重：OR1.49，95％CI1.1,2.4；低MUAC-OR1.64，95％CI1.2,2.3）以及LBW（体重过轻：OR-1.63，95％CI1.1,2.4；低MUAC-OR-1.63，95％CI1.2,2.3）具有统计学意义。ROC曲线显示MUAC和BMI对SGA具有适度的可预测性(AUC<0.7)。
结论：BMI和MUAC显示的产妇营养状况与不良妊娠结局密切相关，包括SGA，LGA和LBW。尽管MUAC和BMI被广泛用于确定产妇的营养状况，他们对新生儿大小的预测能力较差。需要进一步的研究来确定其他工具或工具的组合，以更好地预测资源有限的环境和计划干预措施中的不良出生结局。
方法：这项研究是对IbrahimHyderi和RehriGoth正在进行的妊娠队列“妊娠风险婴儿监测和测量联盟（PRISMA）”的二次分析，卡拉奇.在2021年1月至2022年8月之间招募的PRISMA参与者被纳入，因为他们的胎龄<14周，通过超声确认。MUAC和BMI测量是可用的，出生体重在72小时内被捕获。使用多变量逻辑回归来确定孕妇营养状况与SGA之间的关联。PRISMA研究获得了阿加汗大学伦理审查委员会的批准（2021-5920-15,518）。
结果：在分析中包括的926名女性中，26.6％（n=247）的MUAC较低（<23cm），而18.4％（n=171）的体重不足（BMI<18.5kg/m2）。近三分之一的低MUAC和体重不足的妇女分娩了SGA婴儿（分别为34.4％和35.1％）。体重过重的女性和MUAC低的女性与SGA（体重过重：OR1.49，95％CI1.1,2.4；低MUAC-OR1.64，95％CI1.2,2.3）以及LBW（体重过轻：OR-1.63，95％CI1.1,2.4；低MUAC-OR-1.63，95％CI1.2,2.3）具有统计学意义。ROC曲线显示MUAC和BMI对SGA具有适度的可预测性(AUC<0.7)。
结论：BMI和MUAC显示的产妇营养状况与不良妊娠结局密切相关，包括SGA，LGA和LBW。尽管MUAC和BMI被广泛用于确定产妇的营养状况，他们对新生儿大小的预测能力较差。需要进一步的研究来确定其他工具或工具的组合，以更好地预测资源有限的环境和计划干预措施中的不良出生结局。
