IFPRI Newsletter: IFPRI Report, Volume 18, Number 2, June 1996
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IFPRI Report

IFPRI Report

Volume 18, Number 2
June 1996

Ecoregional Mapping Helps Pinpoint Areas Prone to Malnutrition

Agroecological conditions largely determine the production potential of an agrarian area and its ability to support a number of people. Would it not make sense, therefore, to base economic and policy research on ecoregional zones, rather than on geographical or political boundaries alone? Switching to an agroecological framework is problematic, however, because data in almost all studies on the location, size, and distribution of poverty are regional or country-specific. "Overcoming Malnutrition: Is There an Ecoregional Dimension?," 2020 Vision for Food, Agriculture, and the Environment Discussion Paper 10, by Manohar Sharma, Marito Garcia, Aamir Qureshi, and Lynn Brown, is a first attempt to map the prevalence of underweight children by ecoregions, using malnutrition as a proxy for poverty. The authors distribute data on malnutrition among the four developing regions of the world and among nine agroecological zones (AEZs) to form ecoregions.

They conclude that while the natural environment does play a role in poverty and malnutrition, other socioeconomic factors have a strong influence. For example, much of Latin America and the Caribbean falls into ecoregions where children are prone to malnutrition, but because incomes are relatively high, the share of malnourished children is lower than would be expected.

Looked at from a geographical perspective, the sheer numbers of poor and malnourished people in the warm semi-arid tropic and subtropic zones--South Asia, for example--overwhelm the prevalence data. Looked at from an ecological perspective, however, the paper finds that the share of malnourished people in the cool tropic zones--the highlands--is larger, although the actual numbers are much smaller. By revealing where malnutrition and poverty are likely to be found, the new classification system enables policymakers to target relief programs more accurately and to customize income-generating and health and nutrition programs to the natural resource characteristics of an area.

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