The evaluation of Suchana, a large-scale development program to prevent chronic undernutrition in north-eastern Bangladesh

Abstract

Evidence of the impact of community-based nutrition programs is uncommon for two main reasons: the lack of untreated controls, and implementation does not account for the evaluation design. Suchana is a large-scale program to prevent malnutrition in children in Sylhet division, Bangladesh by improving the livelihoods and nutrition knowledge of poor and very poor households. Suchana is being implemented in 157 unions, the smallest administrative unit of government, in two districts of Sylhet. Suchana will deliver a package of interventions to poor people in about 40 randomly selected new unions annually over 4 years, until all are covered. All beneficiaries will receive the normal government nutrition services. For evaluation purposes the last 40 unions will act as a control for the first 40 intervention unions. The remaining unions will receive the program but will not take part in the evaluation. A baseline survey was conducted in both intervention and control unions; it will be repeated after 3 years to estimate the impact on the prevalence of stunted children and other indicators. This stepped wedge design has several advantages for both the implementation and evaluation of services, as well as some disadvantages. The units of delivery are randomized, which controls for other influences on outcomes; the program supports government service delivery systems, so it is replicable and scalable; and the program can be improved over time as lessons are learned. The main disadvantages are the difficulty of estimating the impact of each component of the program, and the geographical distribution of unions, which increases program delivery costs. Stepped implementation allows a cluster randomized trial to be achieved within a large-scale poverty alleviation program and phased-in and scaled-up over a period of time. This paper may encourage evaluators to consider how to estimate attributable impact by using stepped implementation, which allows the counterfactual group eventually to be treated.