Background & Objective: Prematurity and low birth weights are the important risk factors for Neonatal and Infant mortality. It is not possible to weight significant proportions of newborns in rural areas of many developing countries, mostly due to unavailability of weighing scales. These low birth weight newborns, even if they survive, they used to suffer from long term disability such as malnutrition or gross developmental delay. Many studies earlier have attempted to identify surrogate makers of LBW to find out solution of this problem, but still there is no consensus of cutoff value for these surrogate markers, which can correlate uniformly with LBW. The reproducibility and reliability of these surrogate markers vary in different races and locations. The aim of this study was to identify the reliable surrogate markers for LBW. Methods: This prospective cross sectional study was carried out in a tertiary level hospital located in central India. The aim of the study was to identify a surrogate marker/s which can be reliably used for identification of low birth weight newborn. Results: All the anthropometric measurements correlate significantly with birth weight. Multiple linear regression analysis showed the best predictors in the descending order for low birth weight were Chest C., Calf C., Head C., length & MUAC with a variance of 77.4%, 3.0%, 1.4%, 1.0%, 0.7% respectively. Sensitivity for head and chest circumference was 92.42 and 92.20 respectively, whereas sensitivity for MUAC was 95.26, the highest among all parameters. This study suggests that mid upper arm circumference below <11 cm may be an optimum anthropometric surrogate to identify LBW newborns. Conclusion: Head and chest circumferences were the best specific anthropometric surrogates of LBW. MUAC was the best sensitive and easier and convenient surrogate marker, but it can overestimate LBW infants. Combining MUAC with either HC or CC will be most appropriate for identifying LBW infants in resource limited areas. Further studies are needed in the field to cross-validate our results.
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