LinkNCA (Nutrition Causal Analysis)
A nutrition causal analysis (NCA) is a method for analysing the multicausality of undernutrition, as a starting point for improving the relevance and effectiveness of multi-sectoral nutrition security programming in a given context. Though there is an increasing global convergence around a well-defined package of ‘essential’ nutrition actions (A,B,C), implementing ‘off-the-shelf’ solutions without attention to the barriers and opportunities inherent to a specific context will often hinder the uptake and impact of any standard intervention.
The UNICEF conceptual framework on the causes of undernutrition was developed in 1990 to identify and clarify the causes of undernutrition(D). Though it was an essential contribution to highlighting the multi-factorial nature of undernutrition, it was not intended to be prescriptive of a set of universal causes of undernutrition relevant to every population, nor was it a method of assessment(E). Rather, it provides a useful starting point for understanding the risk factors of undernutrition in a given context, their interrelationships, and their relation to undernutrition. As stated in the 1990 policy review:
“It is important not to interpret this framework as a predictive model. Its deliberate lack of rigid limits or boundaries leaves room for different models to be developed in different contexts. The framework primarily helps in asking relevant questions in the development of such models.”
Methods and practices for estimating the prevalence of undernutrition and its public health significance are quite well established (see figure 1.1, step 1). While many different types of analyses of the causes of undernutrition have been implemented using a wide array of methods, routine assessment of undernutrition causality has been fairly limited among operational agencies working in nutrition. In part because undernutrition causality is multi-factorial, complex to capture, and specific to a local context, no standard Nutrition Causal Analysis (NCA) method has emerged. The lack of a structured method has further constrained operational agencies from carrying out this type of assessment as part of a typical programme cycle, and has led to results of varying quality. According to Levine and Chastre, the “quality of situational analysis can be very diverse. It is almost as if the UNICEF conceptual framework is used for programming as an actual causal chain for every situation(J)”. As a result, causal analysis at a local level is often weak, relying more on assumptions rather than evidence.
Studies that have attempted to ascertain the causes of undernutrition are also typically constrained in their usefulness due to some of the following reasons:
- They often yield only a static picture of the causes of undernutrition. In reality, the causes of undernutrition are influenced by a number of dynamic factors and therefore change as these factors evolve.
- They often fail to prioritise causes, rendering the results less actionable and operationally useful.
- Analyses using national level secondary data, such as Demographic and Health Survey data, focus on the average result, often overlooking the specific challenges of vulnerable and marginalized groups and the unique factors that contribute to their undernutrition vulnerability.
- The results are not always relevant for programming. As mentioned by FAO and ECHO, “if problem analysis is not done adequately, then the decision on an appropriate response cannot be taken in the most appropriate way(K)”. For too long, programmes for the prevention of undernutrition have been designed as if improving underlying causes would automatically reduce the risk of undernutrition(L), neglecting 1) the potential negative impacts of certain interventions, and 2) the importance of interdependent risk factors. A review of response practices(M) showed that response orientation is often based less on actual needs identified than on other factors such as context, the organization’s ethos, funding opportunities, and capacity. Efforts to tackle undernutrition require a holistic diagnosis and an integrated response across sectors.