ArticleBMC pregnancy and childbirth2024
Association of maternal nutritional status and small for gestational age neonates in peri-urban communities of Karachi, Pakistan: findings from the PRISMA study.
Article in BMC pregnancy and childbirth, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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7 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Association between endometriosis and adverse reproductive and perinatal outcomes in women undergoing assisted reproductive technology: a systematic review and meta-analysis.Frontiers in medicine · 2026Pooled it
- Dietary choline intake during pregnancy and birth weight in a Chinese population: a cross-sectional study.Nutrition journal · 2026Observational
- Association between pre-pregnancy body mass index and neonatal outcomes in women undergoing assisted reproductive technology: a retrospective study.BMC pregnancy and childbirth · 2026Article
- Maternal Nutrition During Pregnancy and Fetal Outcome, Short- and Long-Term Health Effects: A Narrative Review.Nutrients · 2026Review
- Association of fetal FTO gene variants with maternal postload glucose levels in pregnancy.International journal of obesity (2005) · 2025Article
- Assessment of mid-upper arm circumference for detecting obesity in pregnant women: a cross-sectional study.Frontiers in global women's health · 2025Article
- Can maternal inflammatory and nutritional status, evaluated by the hemoglobin, albumin, lymphocyte, and platelet (HALP) score and the prognostic nutritional index (PNI) in the first trimester, predict late-onset fetal growth restriction?BMC pregnancy and childbirth · 2024Article
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5 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundEarly 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.
methodsThis 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).
resultsOf 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).
conclusionMaternal 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.
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