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Comparative Study
. 2009 Jun 27:8:37.
doi: 10.1186/1476-072X-8-37.

Estimation of undernutrition and mean calorie intake in Africa: methodology, findings and implications

Affiliations
Comparative Study

Estimation of undernutrition and mean calorie intake in Africa: methodology, findings and implications

Cornelia F A van Wesenbeeck et al. Int J Health Geogr. .

Abstract

Background: As poverty and hunger are basic yardsticks of underdevelopment and destitution, the need for reliable statistics in this domain is self-evident. While the measurement of poverty through surveys is relatively well documented in the literature, for hunger, information is much scarcer, particularly for adults, and very different methodologies are applied for children and adults. Our paper seeks to improve on this practice in two ways. One is that we estimate the prevalence of undernutrition in sub-Saharan Africa (SSA) for both children and adults based on anthropometric data available at province or district level, and secondly, we estimate the mean calorie intake and implied calorie gap for SSA, also using anthropometric data on the same geographical aggregation level.

Results: Our main results are, first, that we find a much lower prevalence of hunger than presented in the Millennium Development reports (17.3% against 27.8% for the continent as a whole). Secondly, we find that there is much less spread in mean calorie intake across the continent than reported by the Food and Agricultural Organization (FAO) in the State of Food and Agriculture, 2007, the only estimate that covers the whole of Africa. While FAO estimates for calorie availability vary from a low of 1760 Kcal/capita/day for Central Africa to a high of 2825 Kcal/capita/day for Southern Africa, our estimates lay in a range of 2245 Kcal/capita/day (Eastern Africa) to 2618 Kcal/capita/day for Southern Africa. Thirdly, we validate the main data sources used (the Demographic and Health Surveys) by comparing them over time and with other available data sources for various countries.

Conclusion: We conclude that the picture of Africa that emerges from anthropometric data is much less negative than that usually presented. Especially for Eastern and Central Africa, the nutritional status is less critical than commonly assumed and also mean calorie intake is higher, which implies that agricultural production and hence income must also have been growing at a pace at least high enough to keep up with population growth. In terms of methodology, our estimates form a base line for 2005 for the whole continent that can be easily updated with far less information for individual countries, as we show in an example for Ethiopia.

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Figures

Figure 1
Figure 1
Undernutrition map of sub-Saharan Africa: % of total population in 2005 that suffers from undernutrition. Source: own calculations.
Figure 2
Figure 2
Nutrition map of West Africa: per capita daily food intake in 2005 in kilocalories. Source: own calculations.
Figure 3
Figure 3
Hunger gap map for Ethiopia: per capita daily shortfall in food intake, measured in kilocalories. Source: own calculations.
Figure 4
Figure 4
Undernutrition prevalence rates in children (low height-for-age) in sets of two successive surveys for 13 Asian countries (18 comparison sets). Source: own calculations.
Figure 5
Figure 5
Undernutrition prevalence rates in children (low height-for-age) in sets of successive surveys for 15 African countries. Source: own calculations.
Figure 6
Figure 6
Undernutrition prevalence rates in children (low height-for-age) in the 9 provinces of Zambia, as reported in three successive surveys over a period of 10 years. Source: own calculations.
Figure 7
Figure 7
Ethiopia: Calorie gap for Ethiopia: total shortfall in food intake in billions of Kcal per year per province. Source: own calculations.

References

    1. The World Bank poverty mapping webpage http://go.worldbank.org/33CTPSVDC0
    1. Davis B. Choosing a method for poverty mapping. Rome: FAO; 2003.
    1. Elbers CT, Lanjouw JO, Lanjouw PF. Micro-level estimation of poverty and inequality. Econometrica . 2003;71:355–364. doi: 10.1111/1468-0262.00399. - DOI
    1. UNICEF The state of the world's children, 2008. . New York. 2008.
    1. WHO Global database on child growth and malnutrition http://www.who.int/nutgrowthdb/en/index.html

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