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WHAT ARE THE PRIORITIES FOR INVESTMENT IN IMPROVED NUTRITION DATA?


A


CCESS TO THE RIGHT DATA AT THE RIGHT TIME IN THE RIGHT PLACE IS NECESSARY TO IMPROVE ACCOUNTABILITY, BUT NOT SUFFICIENT.THIS CHAPTER MAPS THE gaps, suggests criteria for prioritizing data collection efforts, and identifies some promising approaches to addressing the gaps.


THE GAPS AND IMPROVEMENTS NEEDED


To identify data gaps, we undertook several steps. First, as we developed the nutrition country profiles, we went from identifying ideal indicators to assessing the available indicators and developed a sense of what data were absent but needed. Second, we analyzed the 84 indicators in the 193 nutrition country profiles and mapped the gaps in these data by indicator group.1


Third, we noted the data gaps highlighted by the anal-


yses in this report; these are shown at the end of each chapter. Finally, we took a step back and asked ourselves, What are the issues that should be prioritized and the actions that should be taken to reduce malnutrition but are not—because of data gaps? We found that few studies have been done on how lack of data is constraining nutrition action, and we will undertake a more detailed literature review in a future report.


KEY POINTS


1. There are many gaps in data on nutrition outcomes, outputs, and inputs. For example, 40 percent of the 193 member countries of the United Nations cannot track more than two of the four World Health Assembly (WHA) indicators included in this report. Supporting all countries’ capacity to report on the WHA indicators is a priority.


2. To identify data gaps beyond the WHA indicators, we asked, What are the issues that should be prioritized and the actions that should be taken to reduce malnutrition but are not—because of data gaps? We identified four nutrition status indicators—anemia, overweight and obesity, wasting, and low birth weight—where progress is slow and data gaps could be holding back action. We also identified data gaps that we believe are holding back the scaling up and context-specific blending of nutrition-specific, nutrition-sensitive, and enabling-environment interventions.


3. Not all data gaps require the collection of new data. Data gaps can be filled by (1) using existing data better, (2) improving the collection of existing data, (3) improving data comparability across countries, (4) collecting data more frequently, and (5) collecting new data where there are not enough for good accountability. Each of these approaches offers scope for filling several data gaps.


4. Decisions about which data gaps are most important to fill need to be undertaken at the national level, based on nutrition policies, plans, and strategies. Answers to the following questions will help prioritize these gaps: Will the availability of the data lead to better or more intensive action for nutri- tion? Is the data collection practical? Is there demand for the data, or can such demand be created?


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