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Prediction of birth weights from body weights of newborns
K V Sarma1, M V Rao, K Damayanthi
1National Institute of Nutrition, Indian Council of Medical Research, Jamai-Osmania, Hyderabad.
Insights
Newborn body weight measurements within the first week can accurately predict birth weight, aiding in low birth weight (LBW) assessment. This method is valuable for monitoring infant development programs.
Area of Science:
- Neonatal health
- Biostatistics
- Public health
Background:
- Accurate birth weight measurement is crucial for assessing neonatal health and identifying low birth weight (LBW) infants.
- Traditional birth weight recording can be challenging in certain field settings.
Purpose of the Study:
- To assess the accuracy of predicting newborn birth weights using body weights measured within the first six days after birth.
- To evaluate the utility of predicted birth weights for determining the prevalence of LBW.
Main Methods:
- A prospective follow-up study was conducted in four villages near Hyderabad.
- Weights of 47 newborns were recorded daily for seven days.
- Regression analysis was used to predict birth weights from daily measurements (2nd to 7th day), and sensitivity/specificity for LBW categorization were calculated.
Main Results:
- Prediction accuracy (R-square) decreased from 95% on day 2 to 86% on day 7, with increasing standard error (84g to 154g).
- Sensitivity and specificity for identifying LBW using predicted weights were high, ranging from 0.85-0.95 and 0.93-0.96, respectively.
- Predicted LBW prevalence closely matched actual observations.
Conclusions:
- Newborn body weight measured within the first week reliably estimates birth weight, especially for LBW classification.
- This predictive methodology offers a practical tool for monitoring and evaluating programs aimed at improving infant birth weights in resource-limited settings.
Objective:
To evaluate the accuracy of prediction of birth weights from body weights of newborns till six days after birth.
Design:
Prospective follow-up.
Setting:
Four villages near Hyderabad.
Methods:
Weights of 47 newborns were recorded daily from the day of birth for seven days. The birth weights were regressed on the weights of the babies taken on the 2nd day to the 7th day. Specificity and sensitivity of the predicted birth weights to arrive at the prevalence of low birth weight (LBW) were computed.
Results:
The co-efficient of determination (R-square) for between the days measurements decreased from 95% on the second day to 86% on seventh day with an increase in the standard error of the estimate from 84 g to 154 g. Based on the "predicted birth weights", the prevalence of LBW in the community was arrived at and compared with the actual observation. The sensitivity and specificity of these regression equations was high and ranged from 0.95 to 0.85 and 0.96 to 0.93, respectively.
Conclusions:
In situations where the birth weight cannot be recorded, weight of the baby taken within the first week after birth may be reliably utilized to assess the "birth weight", particularly in relation to categorization as LBW. This methodology can serve as a tool to monitor various developmental programs aimed at improving birth weights.