Advertisement

Estimating trends in prevalence of undernourishment: advantages of using HCES over the FAO approach in a case study from Cameroon

  • Jean Joël AmbagnaEmail author
  • Sandrine Dury
  • Marie Claude Dop
Original Paper
  • 99 Downloads

Abstract

Global and national food security policies require a good knowledge of trends in prevalence of undernourishment (PoU). Progress towards the Sustainable Development Goals might be difficult to assess if trends in undernourishment are not correctly estimated. However, methods of estimating PoU are still subject to debate. FAO Food Balance Sheets are used to measure food availability and undernourishment at country level. The aim of this paper is to compare trends in PoU using the FAO approach to that using Household Consumption and Expenditure Surveys (HCES). We used FAO Food Balance Sheets and parameters, and two nationwide representative Cameroonian Household Surveys (ECAM), conducted by the National Institute of Statistics (INS) in 2001 and 2007. Our findings, based on ECAM, show that 38% and 24% of the population were undernourished in 2001 and 2007, respectively. FAO estimates were 29% in 2001 and 17% in 2007. Both approaches showed a downward trend in PoU, but ECAM results showed a greater decrease. Using ECAM enabled disaggregation of trends in PoU by area of residence and region. This, in turn, will enable better targeting of vulnerable areas and disadvantaged segments of the population. The North and Far-North regions of the country were facing major food insecurity problems at the time of the surveys.

Keywords

Undernourishment Heterogeneity FAO HCES 

Notes

Acknowledgements

The authors would like to thank Romain Tchakoute from INS (Cameroon) who provided ECAM data, Nicolas Bricas (CIRAD, Montpellier, France) and Ibrahima Bocoum (University of Laval, Montreal, Canada) for their helpful comments. They also warmly thank the scientific editor and the two referees of Food Security for their relevant comments and repeated exchanges, which helped us to improve the original version significantly.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. Abdullah, Zhou, D., Shah, T., Ali, S., Ahmad, W., Din, I. U., & Ilyas, A. (2017). Factors affecting household food security in rural northern hinterland of Pakistan. Journal of the Saudi Society of Agricultural Sciences.  https://doi.org/10.1016/j.jssas.2017.05.003.
  2. Annegers, J. F. (1973). Seasonal food shortages in West Africa. Ecology of Food and Nutrition, 2(4), 251–257.  https://doi.org/10.1080/03670244.1973.9990345.CrossRefGoogle Scholar
  3. Bashir, M. K., Schilizzi, S., & Pandit, R. (2013). Impact of socio-economic characteristics of rural households on food security: The case of the Punjab. Pakistan. Journal of Animal and Plant Sciences, 23(2), 611–618.Google Scholar
  4. Bocoum, I., Dury, S., Egg, J., Herrera, J., & Prevel, Y. M. (2014). Does monetary poverty reflect caloric intake? Food Security, 6(1), 113–130.  https://doi.org/10.1007/s12571-013-0318-0.CrossRefGoogle Scholar
  5. Bogale, A. (2012). Vulnerability of smallholder rural households to food insecurity in eastern Ethiopia. Food Security, 4(4), 581–591.  https://doi.org/10.1007/s12571-012-0208-x.CrossRefGoogle Scholar
  6. Borlizzi, A., Delgrossi, M. E., & Cafiero, C. (2017). National food security assessment through the analysis of food consumption data from household consumption and expenditure surveys: The case of Brazil’s Pesquisa de Orçamento Familiares 2008/09. Food Policy, 72(Supplement C), 20–26.  https://doi.org/10.1016/j.foodpol.2017.08.009.CrossRefGoogle Scholar
  7. Carling, K. (2000). Resistant outlier rules and the non-Gaussian case. Computational Statistics & Data Analysis, 33(3), 249–258.  https://doi.org/10.1016/S0167-9473(99)00057-2.CrossRefGoogle Scholar
  8. De Haen, H., Klasen, S., & Qaim, M. (2011). What do we really know? Metrics for food insecurity and undernutrition. Food Policy, 36(6), 760–769.  https://doi.org/10.1016/j.foodpol.2011.08.003.CrossRefGoogle Scholar
  9. Deaton, A., & Dréze, J. (2009). Food and nutrition in India: Facts and interpretations. Economic and Political Weekly, 44(7), 42–65.Google Scholar
  10. Dury, S., & Essomba, J.-M. (Eds.). (2012). Dictionnaire des cultures alimentaires. Paris: PUF.Google Scholar
  11. FAO. (2003). « Les bilans alimentaires ». FAO. http://www.fao.org/docrep/005/x9892f/x9892f00.htm. Accessed 4 Nov 2016.
  12. FAO. (2004a). The state of food insecurity in the world: Monitoring the progress towards the world food summit and Millenium development goals. Rome: FAO.Google Scholar
  13. FAO. (2004b). Human energy requirements report of a joint FAO/WHO/UNU expert consultation. Rome: FAO.Google Scholar
  14. FAO. (2005). The state of food insecurity in the world: Eradicating world hunger-key to achieving the Millenium development goals. Rome: FAO.Google Scholar
  15. FAO, INFOODS, WAHO, & Biodiversity International. (2012). West African food composition table. In FAO.Google Scholar
  16. FAOSTAT. (2014). http://www.fao.org/faostat/en/#data/FS. Accessed 21 March 2015.
  17. Fellegi, I. P., & Holt, D. (1976). A systematic approach to automatic edit and imputation. Journal of the American Statistical Association, 71(353), 17–35.  https://doi.org/10.2307/2285726.CrossRefGoogle Scholar
  18. Haines, P. S., Hama, M. Y., Guilkey, D. K., & Popkin, B. M. (2003). Weekend eating in the United States is linked with greater energy, fat. and alcohol intake. Obesity, 11(8), 945–949.Google Scholar
  19. INS (2002). Conditions de vie des populations et profil de pauvreté au Cameroun en 2001. Yaoundé: Institut National de la Statistique.Google Scholar
  20. INS (2007). Troisième enquête camerounaise auprès des ménages: ECAM 3 Document de nomenclatures. Yaoundé, Cameroun: INS.Google Scholar
  21. INS (2008). Conditions de vie des populations et profil de pauvreté au Cameroun en 2007. Yaoundé: Institut National de la Statistique.Google Scholar
  22. INS, & ICF. International (2012). Enquête Démographique et de Santé et à Indicateurs Multiples du Cameroun 2011 (p. 576). Calverton, Maryland, USA: INS et ICF International.Google Scholar
  23. Kassie, M., Ndiritu, S. W., & Stage, J. (2014). What determines gender inequality in household food security in Kenya? Application of exogenous switching treatment regression. World Development, 56, 153–171.  https://doi.org/10.1016/j.worlddev.2013.10.025.CrossRefGoogle Scholar
  24. Kazianga, H., & Udry, C. (2006). Consumption smoothing? Livestock, insurance and drought in rural Burkina Faso. Journal of Development Economics, 79(2), 413–446.CrossRefGoogle Scholar
  25. Kearney, J. (2010). Food consumption trends and drivers. Philosophical Transactions of the Royal Society B: Biological Sciences, 365(1554), 2793–2807.  https://doi.org/10.1098/rstb.2010.0149.CrossRefGoogle Scholar
  26. Kidane, H., Alemu, Z. G., & Kundhlande, G. (2005). Causes of household food insecurity in Koredegaga peasant association, Oromiya zone, Ethiopia. Agrekon, 44(4), 543–560.  https://doi.org/10.1080/03031853.2005.9523727.CrossRefGoogle Scholar
  27. Moltedo, A., Troubat, N., Lokshin, M., & Sajaia, Z. (2013). Analyzing food security using household survey data: Streamlined analysis with ADePT software. Washington, DC: World Bank.Google Scholar
  28. PAM, & FAO. (2011). Situation de la sécurité alimentaire au Cameroun et des marchés: analyse globale de la sécurité alimentaire et de la vulnérabilité. Cameroun: PAM et FAO.Google Scholar
  29. Popkin, B., & Shu, W. (2007). The nutrition transition in high- and low-income countries: What are the policy lessons? Agricultural Economics, 37, 199–211.  https://doi.org/10.1111/j.1574-0862.2007.00245.x.CrossRefGoogle Scholar
  30. Sim, C. H., Gan, F. F., & Chang, T. C. (2005). Outlier labeling with boxplot procedures. Journal of the American Statistical Association, 100(470), 642–652.CrossRefGoogle Scholar
  31. Smith, L., & Subandoro, A. (2007). Measuring food security using households expenditures surveys. IFPRI.Google Scholar
  32. Smith, L., Alderman, H., & Aduayom, D. (2006). Food Insecurity in Sub-Saharan Africa: New Estimates from Household Expenditure Surveys (Research Report No. 46) (p. 134). Washington D.C: IFPRI.Google Scholar
  33. Smith, L., Dupriez, O., & Troubat, N. (2014). Assessment of the Reliability and Relevance of the Food Data Collected in National Household Consumption and Expenditure Surveys (Working Paper No. 008). IHSN.Google Scholar
  34. Svedberg, P. (1999). 841 million undernourished? World Development, 27(12), 2081–2098.  https://doi.org/10.1016/S0305-750X(99)00102-3.CrossRefGoogle Scholar
  35. Svedberg, P. (2002). Undernutrition overestimated. Economic Development and Cultural Change, 51(1), 5–36.  https://doi.org/10.1086/345308.CrossRefGoogle Scholar
  36. United Nations (2015). The Millennium Development Goals Report 2015. New-York: United Nations.Google Scholar
  37. Von Grebmer, K., Bernstein, J., Nabarro, D., Prasia, N., Amin, S., Yohannes, Y., et al. (2016). 2016 Global hunger index: Getting to zero hunger. Bonn Washington, DC and Dublin: Welthungerhilfe: International Food Policy Research Institute, and Concern Worldwide.  https://doi.org/10.2499/9780896292260
  38. Wanner, N., Cafiero, C., Troubat, N., & Conforti, P. (2014). Refinements to the FAO Methodology for Estimating the Prevalence of Undernourishment Indicator (ESS Working Paper No. 14–05). Rome: FAO.Google Scholar

Copyright information

© International Society for Plant Pathology and Springer Nature B.V. 2019

Authors and Affiliations

  • Jean Joël Ambagna
    • 1
    • 2
    • 3
    Email author
  • Sandrine Dury
    • 2
    • 3
  • Marie Claude Dop
    • 4
  1. 1.Ministry of EconomyPlanning and Regional DevelopmentYaoundéCameroon
  2. 2.UMR MOISACIRADMontpellierFrance
  3. 3.MOISA, CIHEAM-IAMM, CIRAD, INRA, Montpellier SupAgroUniversity of MontpellierMontpellierFrance
  4. 4.Independent consultantCastelnau Le LezFrance

Personalised recommendations