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Prelacteal feeding (PLF)—giving infants food or liquid other than breastmilk within the first 3 days of life—remains common and hinders optimal breastfeeding in Bangladesh. This study assessed changes in PLF practices in rural Bangladesh from 2004 to 2019 and examined associate household, maternal, and infant factors. We analyzed data from two cluster-randomized trials in rural northwest Bangladesh (n = 16,551; n = 4,401). Trained staff collected sociodemographic and birth data through household visits. We used multivariable logistic regression to examine associations between household, maternal, and infant characteristics and PLF and a non-linear approximation of the Oaxaca-Blinder regression decomposition to understand the factors associated with the changing prevalence of PLF. The prevalence of PLF declined from 89% in 2004 to 24% in 2019. Factors associated with PLF shifted over time, particularly household wealth, infant sex, and birth weight. Institutional delivery (OR=0.27; 95% CI 0.22, 0.32 in 2004; OR=0.78; 95% CI 0.61, 1.00 in 2019) and multigravida status (OR=0.68; 95% CI 0.58, 0.79 in 2004; OR=0.73; 95% CI 0.58, 0.93 in 2019) were consistently associated with reduced odds of PLF across cohorts in the multivariable analysis. The decomposition analysis based on the two trials indicated that changes in prevalence of the covariates explained 15% of the decrease in prevalence of PLF, primarily accounted for by increases in health facility deliveries (86%), increases in infant birth weight (13%), and increasing gravidity (12%). 85% of the change remains unexplained by the measured variables. The prevalence of PLF declined considerably in rural Bangladesh over the 15-year period. There are shifts in factors associated with PLF overtime. Improvements in socio-demographic factors played a modest but meaningful role in reducing PLF. However the majority of the reduction remains unexplained by the measured variables. Further research is needed to identify other potential drivers for changes in the prevalence of PLF.

Background Early and exclusive breastfeeding may reduce neonatal and post-neonatal mortality in low-resource settings. However, prelacteal feeding (PLF), the practice of giving food or liquid before breastfeeding is established, is still a barrier to optimal breastfeeding practices in many South Asian countries. We used a prospective cohort study to assess the association between feeding non-breastmilk food or liquid in the first three days of life and infant size at 3–5 months of age. Methods The analysis used data from 3,332 mother-infant pairs enrolled in a randomized controlled trial in northwestern rural Bangladesh conducted from 2018 to 2019. Trained interviewers visited women in their households during pregnancy to collect sociodemographic data. Project staff were notified of a birth by telephone and interviewers visited the home within approximately three days and three months post-partum. At each visit, interviewers collected data on breastfeeding practices and anthropometric measures. Infant length and weight measurements were used to produce length-for-age (LAZ), weight-for-age (WAZ), and weight-for-length (WLZ) Z-scores. We used multiple linear regression to assess the association between anthropometric indices and PLF practices, controlling for household wealth, maternal age, weight, education, occupation, and infant age, sex, and neonatal sizes. Results The prevalence of PLF was 23%. Compared to infants who did not receive PLF, infants who received PLF may have a higher LAZ (Mean difference (MD) = 0.02 [95% CI: -0.04, 0.08]) score, a lower WLZ (MD=-0.06 [95% CI: -0.15, 0.03]) score, and a lower WAZ (MD=-0.02 [95% CI: -0.08, 0.05]) score at 3–5 months of age, but none of the differences were statistically significant. In the adjusted model, female sex, larger size during the neonatal period, higher maternal education, and wealthier households were associated with larger infant size. Conclusion PLF was a common practice in this setting. Although no association between PLF and infant growth was identified, we cannot ignore the potential harm posed by PLF. Future studies could assess infant size at an earlier time point, such as 1-month postpartum, or use longitudinal data to assess more subtle differences in growth trajectories with PLF. Trial registration ClinicalTrials.gov: NCT03683667 and NCT02909179.

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. 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. 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. 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.

Small for gestational age (SGA) is a public health concern since it is associated with mortality in neonatal and post-neonatal period. Despite the large magnitude of the problem, little is known about the population-attributable risk (PAR) of various risk factors for SGA. This study estimated the relative contribution of risk factors for SGA, as a basis for identifying priority areas for developing and/or implementing interventions to reduce the incidence of SGA births and related mortality and morbidity. We conducted a literature review on 63 potential risk factors for SGA to quantify the risk relationship and estimate the prevalence of risk factors (RFs). We calculated the population-attributable fraction for each of the identified RF for 81 Countdown countries and calculated regional estimates. Twenty-five RFs were included in the final model while extended model included all the 25 RFs from the final model and two additional RFs. In the final and extended models, the RFs included in each model have a total PAF equal to 63.97% and 69.66%, respectively of SGA across the 81 LMICs. In the extended model, maternal nutritional status has the greatest PAF (28.15%), followed by environmental and other exposures during pregnancy (15.82%), pregnancy history (11.01%), and general health issues or morbidity (10.34%). The RFs included in the final and extended model for Sub-Saharan African (SSA) region have a total PAF of 63.28% and 65.72% of SGA, respectively. In SSA, the top three RF categories in the extended model are nutrition (25.05%), environment and other exposure (13.01%), and general health issues or morbidity (10.72%), while in South-Asia's it was nutrition (30.56%), environment and other exposure (15.27%) and pregnancy history (11.68%). The various types of RFs that play a role in SGA births highlight the importance of a multifaceted approach to tackle SGA. Depending on the types of RFs, intervention should be strategically targeted at either individual or household and/or community or policy level. There is also a need to research the mechanisms by which some of the RFs might hinder fetal growth.

Sexually transmissible infections are important causes of loss of health and lives in women and infants worldwide. This paper presents the methods and results of a systematic review that focuses on the impact of antibiotic treatment for syphilis, chlamydia, and gonorrhoea during pregnancy on birth outcomes for the Lives Saved Tool (LiST). We searched PubMed, Embase, Cochrane Libraries, Global Health and Global Index Medicus for articles available until May 23rd, 2022. The search criteria focused on the impact of treatment for the three sexually transmitted infection among pregnant women. Nearly all the articles found were non-randomized studies. Treatment for pregnant women with active syphilis reduced the risk of preterm birth by 52% (95% CI = 42%-61%; 11 043 participants, 15 studies; low quality); stillbirth by 79% (95% CI = 65%-88%; 14 667 participants, eight studies; low quality); and low birth weight by 50% (95% CI = 41%-58%; 9778 participants, seven studies; moderate quality). Treatment for pregnant women with chlamydia infection reduced the risk of preterm birth by 42% (95% CI = 7%-64%; 5468 participants, seven studies; low quality) and might reduce the risk of low birth weight by 40% (95% CI = 0%-64%; 4684 participants, four studies; low quality). No studies provided data on treatment of gonorrhoea therefore no meta-analysis was conducted. Because few studies adjusted for potential confounding factors, the overall quality of evidence was considered low. However, given the consistent and large effects, we recommend updating the estimated effect of timely detection and treatment for syphilis on preterm birth and stillbirth in the LiST model. More research is required to ascertain the effect of antibiotic treatment for chlamydia and gonorrhoea infection in pregnancy.

The global nutrition community has been interested in investigating investment strategies that could be used to promote an increased focus and investment in nutrition programming in low- and middle-income countries. The Lives Saved Tool (LiST) was used to evaluate lives saved and the costs of nutrition interventions in nine high-burden countries. In this case study, we detail the analyses that were conducted with LiST and how the results were packaged to develop Nourish the Future - a five-year proposal for the US government to scale up lifesaving malnutrition interventions. Scaling up a proposed package of critical nutrition interventions including micronutrient supplementation for pregnant women, breastfeeding support, Vitamin A supplementation for children, and treatments for moderate and severe acute malnutrition is an effective and cost-effective way to avert millions of child deaths and stillbirths. This is one of the few case studies that outlines how a nutrition modeling tool (in this case LiST) was used to engage in a prioritisation exercise to inform a US-based advocacy ask. We share reflections and provide practical insights into user motivation and preferences for existing and future modeling tool developers. This case study also emphasises how integral evidence translation and strategic advocacy are to ensure the use of the modeling results.

Complications associated with preterm birth (PTB) are the largest contributor to under-five mortality globally. Success in reaching the Sustainable Development Goal target requires identifying potentially modifiable risk factors for PTB, estimating the relative importance of these risk factors, and identifying/implementing effective prevention strategies to address them. We conducted a literature review to define risk relationships and estimate prevalence for established risk factors for spontaneous PTB (sPTB). We then estimated population attributable fractions (PAF) for the sPTB risk factors identified in the review as statistically significant for the 81 low- and middle-income (LMIC) countries included in the Countdown 2030 initiative. We summed country-level findings to produce PAFs for each risk factor and regional estimates for sub-Saharan Africa and South Asia. Forty-four potential sPTB risk factors were identified. and the final analysis included twenty-four risk factors with evidence of significant associations with sPTB. A second model with three additional risk factors with borderline insignificant associations was also run. Taken together, the twenty-four risk factors had a total PAF of 73% for all 81 countries and 77% and 72% of sPTB in sub-Saharan Africa and South Asia, respectively. For all countries, maternal undernutrition had the highest PAF (17.5%), followed by maternal infections (16.6%), environmental exposures (16%) and pregnancy history (8.7%). While multiple risk factors contribute to sPTB, no single risk factor addresses a predominant fraction, and 27% of spontaneous preterm births are not associated with risk factors that we identified. Despite the significant role of preterm birth in child survival, there are major data gaps in LMIC settings. Furthermore, there is a paucity of evidence for effective interventions to prevent preterm birth. Preventing sPTB requires understanding underlying mechanisms leading to sPTB in different populations, and the identification/implementation of effective interventions.

Policymakers seeking to prioritize the use of restricted financial resources need to understand the relative costs and benefits of interventions for improving nutritional status. Improved linear growth can lead to increased education attainment and improved economic productivity in low- and middle-income countries (LMICs), though these non-health-related benefits are not reflected in current long-term modelling efforts, including the Lives Saved Tool (LiST). Our objective was to integrate the effects of improved linear growth on non-health related benefit into LiST by estimating subsequent gains in years of schooling and wage earnings. We then estimated the impacts of reaching the Sustainable Development Goals (SDGs) target for stunting in South Asian countries on lifetime productivity. In the first step, we used LiST outputs to estimate the improved linear growth due to scaled-up nutrition interventions and used published estimates to quantify the education gain resulting from an increase in height for age z-score (HAZ). In the second step, we used published country-level estimates on economic returns to schooling to quantify the relative gains in wages that children born today will experience because of their additional education attainment in the future. In the last step, we used country-level data on wages to estimate the net present value of future earnings gained due to early childhood growth improvement per birth cohort. If South Asia countries reach the SDG target by 2025, an estimated 8.6 million years of schooling will be obtained by six birth cohorts of 2020 to 2025. These six birth cohorts will also gain an estimated US$64 893 million in the present value term, at a 5% discount rate, in lifetime earnings. India has the largest expected gain in years of schooling (7367 years) and lifetime earnings (US$59 390 million in present value terms, at a 5% discount rate). Two non-health-related benefits of improved linear growth - additional years of schooling and lifetime earnings - are added in LiST. Together with LiST costing, users can now conduct both cost-effective and benefit-cost analyses. Using both analyses will provide more comprehensive insights into nutrition interventions' relative costs and benefits.