Prediction Model for Low Birth Weight and its Validation

• DOI: 10.1007/s12098-013-1161-1
• Publication Date: 2013-08-15T10:44:20Z
• Authors: Avantika Singh; Sugandha Arya; Harish Chellani; K. C. Aggarwal; R. M. Pandey
• Keywords: Male; 03 medical and health sciences; Models, Statistical; 0302 clinical medicine; Case-Control Studies; Infant, Newborn; Humans; Female; Infant, Low Birth Weight; Risk Assessment; Forecasting; 3. Good health

To evaluate the factors associated with low birth weight (LBW) and to formulate a scale to predict the probability of having a LBW infant.This hospital based case-control study was conducted in a tertiary care university hospital in North India. The study included 250 LBW neonates and 250 neonates with birth weight ≥2,500 g. Data were collected by interviewing mothers using pre-designed structured questionnaire and from hospital records.Factors significantly associated with LBW were inadequate weight gain by the mother during pregnancy (<8.9 kg), inadequate proteins in diet (<47 g/d), previous preterm baby, previous LBW baby, anemic mother and passive smoking. The prediction model made on these six variables has a sensitivity of 71.6 %, specificity 67.0 %, positive LR 2.17 and negative LR of 0.42 for a cut-off score of ≥29.25. On validation, it has a sensitivity of 72 % and specificity of 64 %.It is possible to predict LBW using a prediction model based on significant risk factors associated with LBW.