Head Circumference and Birth Length as Predictor of Low Birth Weight among Bengali Hindu Population of Kolkata, West Bengal, India
Introduction: Low Birth Weight (LBW) is an important decisive factor for most of the neonatal deaths, hence, Birth Weight (BW) is essential to identify immediately after birth for neonate survival and post-natal growth. The proper neonatal care and logistics are not available in every situation, esp...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
JCDR Research and Publications Private Limited
2019-08-01
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| Series: | Journal of Clinical and Diagnostic Research |
| Subjects: | |
| Online Access: | https://jcdr.net/articles/PDF/13043/39757_CE[Ra1]_F(KM)_PF1(AJ_KM)_PFA(AJ_SL_KM)_PN(SL).pdf |
| Summary: | Introduction: Low Birth Weight (LBW) is an important decisive factor for most of the neonatal deaths, hence, Birth Weight (BW) is essential to identify immediately after birth for neonate survival and post-natal growth. The proper neonatal care and logistics are not available in every situation, especially in noninstitutional or home deliveries bear’s difficulties to identify the relative risks of intra-uterine growth retardations and/or of newborns LBW. Aim: To identify the surrogate anthropometric measurements of Birth length (BL) and Head circumference (HC) as a proxy measure of newborns LBW and determine the operational cutoff points among the Bengali Hindu population of Kolkata, West Bengal, India. Materials and Methods: A total of 495 newborn BW data were collected from the hospital records from August 2016 to March 2017. Data were collected among Bengali Hindu mothers completed full gestational periods and delivered a normal singleton newborn. The data comprises of BW, BL and HC which were recorded using standard anthropometric procedures. The data were analysed in terms of descriptive statistics, correlation coefficients, linear and Binary logistic regression (BLR) and AUC-ROC analysis using SPSS (version, 16.0). Results: Out of 495 newborns included mean BW and LBW were 2.72±0.44 kg and 27.10%, respectively. The BW was correlated with BL (r=0.791) than HC (r=0.757) (p<0.001). Linear and BLR analysis showed that BL and HC exhibited significant influences on newborns BW (p<0.01). ROC-AUC analyses of BL (AUC=0.89, 95% CI 0.86-0.92) and HC (AUC=0.91, 95% CI 0.88-0.94) showed optimal surrogate indicators with LBW (p<0.01). The optimal cut-points for BL and HC to identify LBW newborns were <46.5 cm and <32.5 cm, respectively. Conclusion: BL is the best suitable anthropometric measure followed by HC to predict LBW newborns. These proxies anthropometric indicators would help to identify the relative risks LBW and neonates requiring intervention in field situations. |
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| ISSN: | 2249-782X 0973-709X |