Question 2: What are the determinants of stunting by region?
|WHAT are the characteristics of a well-formulated policy question?||Comments for Question 2|
|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 measure stunting and determinants of stunting. Population-based surveys seems to be a good source of information for this question.|
|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? Adolescents? All?|
b) This question is about a nutrition target and determinants, not a specific intervention.
c) The underlying “policy objective” could be made more specific as this would guide the development of the data analysis plan.
d) The question seems to suggest looking at the most recent data. If data is only available for 2005, is the analysis still relevant? The time frame can also be chosen based on official targets or a strategic year for the launch of a new plan.
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 Height- for-Age Z-score as the outcome indicator. The data analysis plan needs to describe precisely which “determinants” 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 do not lend themselves to the NIPN approach, as causal analysis using population-based data can be disputed and may not lead to actionable recommendations. Knowing that the levels of education, income, diarrhoea and exclusive breastfeeding are associated with stunting does not bring new information. A stronger association between one determinant and stunting in one region than elsewhere does not necessarily imply that this determinant should be a priority for intervention. Idem, in case a determinant is not associated with stunting.|
However, reformulating the question as follows: “What is the magnitude and severity of the prevalence of known determinants of stunting by region?” allows for descriptive analyses which are well suited here, and may lead to actionable recommendations and partly answer the policy objective. Comparing determinants as well as coverage of nutrition interventions between regions can lead to even more interesting recommendations. A sub-national nutrition dashboard could be helpful here (section 3.2).