Does the Choice of Metric Matter for Identifying Areas for Policy Priority? An Empirical Assessment Using Child Undernutrition in India

Abstract

AbstractRatio-based prevalence and absolute headcounts are the two most commonly accepted metrics to measure the burden of various socioeconomic phenomenon. However, ratio-based prevalence, calculated as the number of cases with certain conditions relative to the total population, is by far the most widely used to rank burden and consequently for targeting, across different populations, often defined in terms of geographical areas. In this regard, targeting areas exclusively based on prevalence-based metric poses certain fundamental difficulties with some serious policy implications. Drawing the data from the National Family Health Survey 2015–2016, and Census 2011, this paper takes four indicators of child undernutrition in India as an example to examine two contextual questions: first, does the choice of metric matter for targeting areas for reducing child undernutrition in India? and second; which metric should be used to facilitate comparisons and targeting across variable populations? Our findings suggest a moderate correlation between prevalence estimates and absolute headcounts implying that choice of metric does matter when targeting child undernutrition. Huge variations were observed between prevalence-based and absolute count-based ranking of the districts. In fact, in various cases, districts with the highest absolute number of undernourished children were ranked as relatively lower-burden districts based on prevalence. A simple comparison between the two approaches—when applied to targeting undernourished children in India—indicates that prevalence-based prioritization may miss high-burden areas where substantially higher number of undernourished children are concentrated. For developing populous countries like India, which is already grappling with high levels of maternal and child malnutrition and poor health infrastructure along with intrinsic socioeconomic inequalities, it is critical to adopt an appropriate metric for effective targeting and prioritization.