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Question 4: How much impact can we achieve with nutrition-specific interventions on stunting?

WHAT are the characteristics of a well-formulated policy question?Comments for Question 4
1. The question must respond to a relevant policy need The policy relevance is ensured by going through steps 1 and 2 of the question formulation process.
2. The question must be answerable with existing quantitative data Data experts need to identify the main datasets available that have estimates on stunting and coverage of nutrition-specific interventions.
3. The question must provide a timely answer for policy use The timeliness of the answer is discussed during steps 1 and 2 of the question formulation process. Note that only the data analysis plan will be able to define precisely the time needed for the analysis.
4. The analysis of the question must lead to actionable recommendations and decisions This is ensured by going through steps 1 and 2 of the question formulation process.
5. The question must specify:
a) the population groups
b) the type of intervention
c) the objective
d) the time frame
e)the expected outcomes
a) Need to specify the age groups: Children? Under-two or under-five?
b) The data analysis plan needs to specify the list of interventions that should be part of the analysis. The list of Essential Nutrition Actions or the interventions prioritised in the Nutrition Action Plan can be used.
c) The underlying “policy objective” could be made more specific as this would guide the development of the data analysis plan.
d) The time frame is not very precise. Is it based on official targets (e.g. 2025)?
e) Stunting is the outcome indicator. The data analysis plan will detail whether the analysis will use prevalence of stunting (global or severe or both) or the mean of the Height for Age Z-score. The data analysis plan needs to describe precisely the coverage indicators that should be included in the analysis.
6. The question must imply data analysis methods which are suitable for use with the NIPN approach The question implies the use of causal data analysis methods which are not suited because population-based data cannot provide a robust measure of the effect of an intervention on stunting, since there is no comparison possible with a control group.
However, some research studies have measured the effect of interventions on stunting, especially nutrition-specific interventions, and, on the basis of these studies, LiST has modelled how a coverage increase of nutrition-specific interventions may result in the number of stunted children prevented. LiST requires data on the coverage of interventions.
After reformulation, this question can be answered using the LiST tool:
What is the number of children prevented from being stunted and from dying if the coverage of a package of nutrition-specific interventions is increased by 20% between 2019 and 2025?