Maternal and child nutrition in the Lives Saved Tool: Results of a recent update

Abstract

Background The Lives Saved Tool (LiST) is a mathematical modelling tool for estimating the survival, health, and nutritional impacts of scaling intervention coverage in low- and middle-income countries (LMICs). Various nutrition interventions are included in LiST and are regularly (and independently) reviewed and updated as new data emerge. This manuscript describes our latest in-depth review of nutrition evidence, focusing on intervention efficacy, appropriate population-affected fractions, and new interventions for potential inclusion in the LiST model. Methods An external advisory group (EAG) was assembled to review evidence from systematic reviews on intervention-outcome (I-O) pairs for women and children under five years of age. GRADE quality was assigned to each pair based on a LiST-specific checklist to facilitate consistent decisions during the consideration. For existing interventions with new information, the EAG was asked to recommend whether to update the default efficacy values and population-affected fractions. For the new interventions, the EAG decided whether there was sufficient evidence of benefit, and in affirmative cases, information on the efficacy and affected fraction values that could be used. Decisions were based on expert group consensus. Results Overall, the group reviewed 53 nutrition-related I-O pairs, including 25 existing and 28 new ones. Efficacy and population-affected fractions were updated for seven I-O pairs; three pairs were updated for efficacy estimates only, three were updated for population-affected fractions only; and nine new I-O pairs were added to the model, bringing the total of nutrition-related I-O pairs to 34. Included in the new I-O pairs were two new nutrition interventions added to LIST: zinc fortification and neonatal vitamin A supplementation. Conclusions For modelling tools like LiST to be useful, it is crucial to update interventions, efficacy and population-affected fractions as new evidence becomes available. The present updates will enable LiST users to better estimate the potential health, nutrition, and survival benefits of investing in nutrition.

Modeled impacts of bouillon fortification with micronutrients on child mortality in Senegal, Burkina Faso, and Nigeria

“…First, the LiST model estimates lives saved for a select few micronutrient interventions. Other micronutrients (e.g., iron, B12) were excluded from this analysis based on limited evidence 50 regarding their direct effects on child mortality, but these nutrients have important benefits in terms of child health and development. LiST does permit modeling the impact of iron on maternal anemia, and the impacts of selected interventions such as multiple micronutrient supplements in pregnancy, but these pathways were excluded because the primary emphasis was on the impact of bouillon fortification on lives saved.…”

“…As a result, in the typical LiST model for vitamin A and zinc, the components of the lives saved calculation (estimates of coverage, affected fraction, and effectiveness) were defined to estimate the impacts of supplementation on child mortality (Table 1). It should be noted that since this analysis was planned and conducted, LiST was updated to include a pathway to estimate the impact of zinc fortification on child mortality; we elected to retain the methods described here rather than use the new pathway because the LiST zinc fortification pathway uses zinc supplementation effectiveness values and we opted for a more conservative approach 50 . To estimate the impact of LSFF interventions on child mortality, we developed methods to adjust the typical LiST methodology to use estimates of affected fraction (proportion to which the benefits of the intervention apply) and effective coverage (based on achieving adequate dietary intake through fortification) produced by the MINIMOD model 36 .…”

“…It should be noted that since this analysis was planned and conducted, LiST was updated to include a pathway to estimate the impact of zinc fortification on child mortality; we elected to retain the methods described here rather than use the new pathway because the LiST zinc fortification pathway uses zinc supplementation effectiveness values and we opted for a more conservative approach. 50 To estimate the impact of LSFF interventions on child mortality, we developed methods to adjust the typical LiST methodology to use estimates of affected fraction (proportion to which the benefits of the intervention apply) and effective coverage (based on achieving adequate dietary intake through fortification) produced by the MINIMOD model. 36 Briefly, as summarized in Table 1, this adapted model used MINIMOD estimates for affected fraction and effective coverage of LSFF interventions rather than coverage of supplementation programs.…”

Optimal Allocation of Antenatal and Young Child Nutrition Interventions: An Individual-Based GBD-Calibrated Microsimulation

“…While our models generally utilize similar data sources for intervention effect estimations, they differ with respect to the derivation of MAM and SAM treatment intervention impacts on recovery rates, with our model ultimately utilizing a slightly lower effect of MAM treatment on MAM recovery and slightly higher effect of SAM treatment on SAM recovery. Further, unlike our model, LiST applies intervention effects to subsets of the population only; for instance, the effect of SQ-LNS is applied to the food-insecure portion of the population only (43). With regard to the impact of the BEP supplementation intervention, our model bene ts from a correlation of the population eligible for BEP (low BMI pregnancies) with low birthweight outcomes, which is not the case in the LiST and Optima Nutrition models.…”

Why small-quantity lipid-based nutrient supplements should be integrated into comprehensive strategies to prevent child undernutrition in nutritionally vulnerable populations: response to Gupta et al.’s commentary

“…At present, however, evidence of the efficacy or feasibility of such interventions is lacking. In fact, there is very little evidence from randomized trials of the impact of providing unfortified complementary foods in general -in a recent review of provision of complementary foods (Tong et al 2022), only 3 studies were cited in the category of "local foods", which varied widely in the type of food offered (caterpillar cereal, egg, or dry milk + cooking oil) and impact on growth, with no significant effects overall.…”