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Updated: Aug 28, 2025
Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Utility of anthropometric measures to identify small for gestational age newborns: A study from Eastern India
Saba Annigeri1, Arindam Ghosh1, Sunil Kumar Hemram1
1Department of Paediatrics, Midnapore Medical College, West Bengal, India.
Insights
Chest circumference is the best anthropometric measurement for identifying small-for-gestational-age (SGA) newborns when ultrasound is unavailable. This simple tool aids in early detection and intervention for at-risk infants.
Area of Science:
- Neonatal Health
- Pediatric Growth Monitoring
- Public Health Interventions
Background:
- Small-for-gestational-age (SGA) newborns face increased neonatal mortality risks.
- Accurate gestational age (GA) assessment is challenging in low-resource settings due to limited ultrasonography access.
- Early identification of SGA infants is critical for timely intervention and improved outcomes.
Purpose of the Study:
- To develop an alternative, accessible tool for identifying SGA newborns.
- To evaluate the efficacy of neonatal anthropometric measurements in predicting SGA.
- To establish optimal cut-off values for anthropometric parameters in SGA identification.
Main Methods:
- A prospective observational study involving 1451 newborns (30-40 weeks gestation).
- Gestational age (GA) determined by ultrasonography; SGA classification used NICHD Fetal Growth Studies reference chart.
- Neonatal anthropometry (head, chest, mid-upper arm circumference) measured within 48 hours of birth.
- Receiver operating characteristic (ROC) curves analyzed to determine optimal cut-offs and assess precision (AUC).
Main Results:
- SGA prevalence was 34.3%.
- Area Under the Curve (AUC) values: Head Circumference (HC) 0.888, Chest Circumference (CC) 0.890, Mid-Upper Arm Circumference (MUAC) 0.865.
- Optimal cut-offs: HC ≤32.45 cm, CC ≤29.75 cm, MUAC ≤8.55 cm, with high sensitivities and specificities.
- Chest circumference (CC) demonstrated the highest AUC, indicating superior precision.
Conclusions:
- Head circumference, chest circumference, and mid-upper arm circumference are viable anthropometric measures for identifying SGA newborns.
- Chest circumference (CC) emerged as the most effective anthropometric parameter for SGA identification in this cohort.
- These findings offer a practical alternative for SGA screening in settings with limited access to ultrasonography.
Introduction:
Small-for-gestational-age (SGA) is one of the important factors for neonatal mortality. Early identification and necessary intervention of these newborns is crucial to increase their chances of survival and reduce long-term disabilities. However, in low- and middle-income countries a large portion of pregnant women are unaware of their accurate gestational age (GA) due to the limited availability of ultrasonography. The purpose of our study was to build an alternative tool to identify SGA.
Methods:
A institutional-based, prospective observational study was conducted from August-2018 to February-2020, with 1451 live singleton-newborns of 30-40 weeks of gestation. Ultrasonography was used to evaluate accurate GA in early pregnancy and a reference chart for the Asian population, constructed by the National Institute of Child Health and Human Development (NICHD) Fetal Growth Studies was used to classify newborns as SGA. Neonatal anthropometry was measured within 48 hours of birth. Receiver operating characteristic curves were developed to identify the best cut-off point for each anthropometric parameter and the area under the curve (AUC) was estimated to assess the overall precision.
Results:
Prevalence of SGA was 34.3%. The AUC was 0.888 for head circumference (HC), 0.890 for chest circumference (CC), and 0.865 for mid-upper arm circumference (MUAC). The optimal cut-offs to classify SGA were ≤32.45 cm for HC, ≤29.75 cm for CC and ≤8.55 cm for MUAC with sensitivities of 85.9%, 86.9% and 85.4%, specificities of 75.5%, 85.1% and 72.1%, positive predictive values of 0.64, 0.75 and 0.61 and negative predictive values of 0.91, 0.93 and 0.90 respectively.
Conclusion:
All three anthropometric measurements could be used to identify SGA but, overall CC is the best.
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