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Identifying high-risk babies born in the community using foot length measurement at birth in Uganda


Elizabeth Nabiwemba, School of Public Health, Makerere University College of Health Sciences. P.O. Box 7072, Kampala 256, Uganda. E-mail:


Background  Low birthweight and prematurity are risk factors for neonatal mortality. Identifying low birthweight and premature babies at birth and giving them appropriate care could increase their chances of survival. This study aimed at assessing the use of foot length as a surrogate for low birthweight and prematurity, and recommending an operational cut-off for identifying high-risk babies at the community level in low resource settings.

Methods  A hospital-based cross-sectional study was carried out between 1 September and 17 December 2009 in Uganda. Foot length of 711 newborns was measured using three different methods and their weight taken using a digital salter scale within 24 h of life. Gestational age of the newborns was also estimated using the Eregie method. Non-parametric receiver operating characteristic curve analysis was carried out to determine the foot length method with the highest predictive value to predict low birthweight and premature newborns. Sensitivity, specificity and predictive values for a range of foot lengths were estimated to determine the optimal cut-off to predict low birthweight and prematurity in this setting.

Results  Of the 711 babies recruited on day 1, 85 (12%) babies were low birthweight (<2500 g) and 29 (4%) premature (<37 weeks). The operational cut-off for foot length to detect small babies was defined as 7.6 cm, with sensitivity 85% [95% confidence interval (CI) 75–92] and specificity 81% (95% CI 78–84) for low birthweight, and sensitivity 96% (95% CI 82–100) and specificity 76% (95% CI 73–79) for premature babies.

Conclusion  Foot length in the first days of life can predict low birthweight and prematurity among newborn babies in this setting. Further evaluation is needed to assess the feasibility of its use by community health workers to identify babies that need extra care.