New option in the Lives Saved Tool (LiST) allows for the conversion of prevalence of small-for-gestational-age and preterm births to prevalence of low birth weight

Document Type

Journal Article

Publication Date



Journal of Nutrition








Lives Saved Tool; Low birth weight; Neonatal health; Preterm birth; Small-for-gestational age


© 2017 American Society for Nutrition. Background: The Lives Saved Tool (LiST) is a software model that estimates the health impact of scaling up interventions on maternal and child health. One of the outputs of the model is an estimation of births by fetal size [appropriate-forgestational- age (AGA) or small-for-gestational-age (SGA)] and by length of gestation (term or preterm), both of which influence birth weight. LiST uses prevalence estimates of births in these categories rather than of birth weight categories, because the causes and health consequences differ between SGA and preterm birth. The World Health Assembly nutrition plan, however, has set the prevalence of low birth weight (LBW) as a key indicator, with a specific goal of a 30% reduction in LBW prevalence by 2025. Objective: The objective of the study is to develop an algorithm that will allow LiST users to estimate changes in prevalence of LBW on the basis of changes in coverage of interventions and the resulting impact on prevalence estimates of SGA and preterm births. Methods: The study used 13 prospective cohort data sets from low- and middle-income countries (LMICs; 4 from sub- Saharan Africa, 5 from Asia, and 4 from Latin America), with reliable measures of gestational age and birth weight. By calculating the proportion of LBW births among SGA and preterm births in each data set and meta-analyzing those estimates, we calculated region-specific pooled rates of LBW among SGA and preterm births. Results: In Africa, 0.4% of term-AGA, 36.7% of term-SGA, 49.3% of preterm-AGA, and 100.0% of preterm-SGA births were LBW. In Asia, 1.0% of term-SGA, 47.0% of term-SGA, 36.7% of preterm-AGA, and 100.0% of preterm-SGA births were LBW. In Latin America, 0.4% of term-AGA, 34.4% of term-SGA, 32.3% of preterm-AGA, and 100.0% of preterm- SGA births were LBW. Conclusions: The simple conversion factor proposed here allows for the estimation of LBW within LiST for most LMICs. This will allow LiST users to approximate the impact of their health programs on LBW prevalence via the impact on SGA and preterm prevalence.