Factors Affecting Nutrition around Uganda: District and Subregional Snapshots

Uganda, like other Scaling Up Nutrition (SUN) countries, is facing competing demands for time, human resources, and funding within the realm of nutrition programming. The priorities assigned by the international agreements to which Uganda is a signatory (such as SUN, the Millennium Development Goals [MDGs], and others) include a wide array of goals and corresponding targets, many of which are integrated into Uganda’s nutrition action plan (UNAP). Given the wide and diverse mandate needed to achieve these targets, it is important to learn how key decision-makers choose what activities to prioritize, when, and where in the country.

This set of quantitative snapshots acts as a complement to the qualitative and financial analysis being conducted as part of SPRING’s Pathways to Better Nutrition Case Study Series, with all work converging to answer the question of how countries prioritize activities with national nutrition plans to produce significant reductions in undernutrition.

When thinking of “scaling up” nutrition, it is important to understand the mixture of causes of undernutrition across the country. These snapshots provide a look at the prevalence of key UNAP indicators for the 10 subregions of Uganda, which is the lowest level of representativeness of the surveys that serve as source data. Data are presented on selected indicators for each of the strategic national objectives named by the UNAP for reducing undernutrition in Uganda. One can best interpret these snapshots as a set, looking at each subregion to assess what objectives or set of constraints are most pressing in each area, and across subregions to see how indicators vary across the country. There may be some universal concerns, while others may be acute concerns but only in select geographic areas.

Table 1 summarizes the key impact indicators across Uganda. The first data column is the national UNAP targets that are meant to be achieved by 2016. The second show the national average; to the right of that is each subnational area average, where the result is color-coded green to red (best to worst), with yellow indicating a values around the national average (+/- one percentage point). For the first eleven indicators, lower prevalence is better, while for the last three indicators, higher prevalence is better.

Table 1. Key UNAP Indicator Summary Table

Compared to National Average

Compared to UNAP Target

There is interesting diversity when looking across this table. Average calorie consumption in Western and Southwest subregions is much higher than the rest of the country, pulling up the national average—the rest of the subregions are either at or below average. In Karamoja, residents consume just over half of the calories consumed in Southwest, and only 65 percent of the calories consumed in Western. Yet, stunting rates in Karamoja, Western, and Southwest are within four percentage points and are the three highest rates in the country. Underweight is by far the highest in Karamoja, but it is also above average in the Western subregion, despite in the second highest level of calorie consumption in Uganda. The North (tied with Karamoja for the lowest amount of calories consumed) and Kampala both appear to have lower than average child underweight, stunting, and wasting prevalence despite low calorie consumption. Eastern subregion appears to have greater prevalence of vitamin A and iron deficiencies as compared to other subregions, despite average or above average prevalence of other conditions. Conversely, Karamoja is well above average for vitamin A deficiency (VAD), possibly due to a recent campaign in that region. Nationally, anemia rates vary significantly, but no clear visual pattern emerges in relation to any other indicators.

It is also useful to note some methodological challenges to monitoring the UNAP targets. For instance, the UNAP has chosen to set targets for a dietary diversity index of 75 percent; however, we could not find reference or data for this type of index. There are other options for displaying dietary diversity among children, the most common (found in the Demographic and Health Surveys [DHS]) is provided in the table; however this means there is no target reference for dietary diversity. VAD and anemia are both available in the latest DHS, but are not always regularly collected by the DHS or other surveys, so extra effort will need to be made to collect these indicators within the period of performance of the UNAP.

Causes for variation in the key nutrition conditions can relate to contextual factors in each subregion. Some of these factors have been identified in activities related to the UNAP objective. SPRING has endeavored to attach indicators to these activities, and has selected some of the best indicators (based on relevance, data quality, availability, and regional variation) to show some of the context below the national level. Table 2 shows a comparison of these indicators representing the key objective areas from the UNAP. As with Table 1, gold represents the average within one percentage point of the national average, green represents above average, and red is below the national average.

These barriers and drivers can be related to the key impact indicators from Table 1. For instance, West Nile, which has higher than average underweight and stunting in Table 1, does fairly well in Table 2 with the exception of a concentration of below average scores around supply side issues in the health and nutrition care, including limited ANC access and ANC nutrition counseling, low growth monitoring, and lower than average health facility density, suggesting a focus area for interventions in that subregion. They also have some of the lowest levels of inputs for hand washing, and issues related to drought. The Southwest, despite having high calorie consumption, appears below average on most of the objective indicators except for those related to biofortified food consumption and facing drought conditions. It also scores lowest on female control over income. This set of constraints may explain some of the difference between calorie availability and nutritional outcomes (other information on resources and constraints in selected Southwest and Northern districts are highlighted in Community Connector’s baseline situation analysis report (Community Connector [2012]). Knowing that there is high calorie availability and also higher rates of overweight in this region perhaps signals a need for a nuanced intervention approach, perhaps related to the harvest low season. Kampala is above average on all indicators except HMIS reporting and Objective 2 indicators, which relates to enhancing consumption of diverse diets.

A few barriers appear to be a problem across many subregions. With the exception of Kampala, there seems to be national issue with health post vacancy—just over half of all health posts are filled. In addition, school feeding does not appear to be a regular program anywhere except Karamoja and West Nile. Across the country it appears there is low ownership of handwashing inputs and facility nutrition testing. There also seems to be very little in the way of bio-fortified food consumption, though this measure may be flawed due to its exclusive focus on sweet potatoes, and dependent on mother’s knowledge of the source of that food. Given that biofortification is a key strategy under Objective 2, more explicit efforts to collect data around these types of crops may be necessary to monitor progress.