Skip to main content

Advertisement

SpringerLink
Log in

Determinants of child nutritional status in the eastern province of Zambia: the role of improved maize varieties

  • Original Paper
  • Published:
Food Security Aims and scope Submit manuscript

Abstract

Using household survey data from a sample of 810 households, this paper analyses the determinants of children’s nutritional status and evaluates the impacts of improved maize varieties on child malnutrition in eastern Zambia. The paper uses an endogenous switching regression technique, combined with propensity score matching, to assess the determinants of child malnutrition and impacts of improved maize varieties on nutritional status. The study finds that child nutrition worsens with the age of the child and improves with education of household head and female household members, number of adult females in the household, and access to better sanitation. The study also finds a robust and significant impact of improved maize varieties on child malnutrition. The empirical results indicate that adoption of improved maize varieties reduces the probability of stunting by an average of about 26 %.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Notes

  1. Since the treatment and outcome variables are both binary, we used a probit regression model to test validity of the instrumental variables. The results from these tests are not discussed because of limited space but are available on request

  2. A follow up survey will be conducted in 2015 where the same household who were interviewed at baseline will be interviewed.

  3. A camp is a catchment area made up of 8 different zones consisting of villages and is headed by an agricultural camp officer. A block is made up of camps and is managed by an agricultural block officer.

  4. An adopter in this study is defined as any farmer who planted or allocated land to at least one improved maize variety consistently for the past three years prior to the survey

  5. Exchange rate at the time of the survey: 1US$ = ZMK5,1974

References

  • Aakvik, A., Heckman, J., and Vytlacil, E. (2000). Treatment effect for discrete outcomes when responses to treatment vary among observationally identical persons: An application to Norwegian vocational rehabilitation programs., in: Research, N.B.o.E. (Ed.), Technical Paper 262, Cambridge

  • Abadie, A., & Imbens, G. W. (2011). Bias-corrected matching estimators for average treatment effects. Journal of Business and Economic Statistics, 29(1), 1–11.

    Article  Google Scholar 

  • Abdulai, A., & Huffman, W. (2014). The adoption and impact of soil and water conservation technology: An endogenous switching regression application. Land Economics, 90(1), 26–43.

    Article  Google Scholar 

  • Adegbola, P., & Gardebroek, C. (2007). The effect of information sources on technology adoption and modification decisions. Agricultural Economics, 37, 55–65.

    Article  Google Scholar 

  • Ajieroh, V. (2009). A quantitative analysis of determinants of child and maternal malnutrition in Nigeria. Background Paper No. NSSP10. IFPRI

  • Alderman, H., Hoogeveen, H., and Rossi, M. (2005). Reducing child malnutrition in Tanzania: Combined effects of income growth and program interventions. World Bank Policy Research Working Paper 3567

  • Alene, A. D., & Manyong, V. M. (2007). The effects of education on agricultural productivity under traditional and improved technology in northern Nigeria: An endogenous switching regression analysis. Empirical Economics, 32(1), 141–159.

    Article  Google Scholar 

  • Alene, A. D., Menkir, A., Ajala, S. O., Badu-Apraku, B., Olanrewaju, A. S., Manyong, V. M., et al. (2009). The economic and poverty impacts of maize research in west and central Africa. Agricultural Economics, 40(5), 535–550. doi:10.1111/j.1574-0862.2009.00396.x.

    Article  Google Scholar 

  • Ali, A., Abdulai, A. (2010). The adoption of genetically modified cotton and poverty reduction in Pakistan. Journal of Agricultural Economics, 61, 175–192

  • Apodaca, C. (2008). Preventing child malnutrition: Health and agriculture as determinants of child malnutrition. Journal of Children and Poverty, 14(1), 21–40.

    Article  Google Scholar 

  • Asenso-Okyere, W. K., Asante, F. A., & Nub’e, M. (1997). Nutritional status of children in Ghana. Agricultural Economics, 17, 59–74.

    Article  Google Scholar 

  • Augurzky, B., & Schmidt, C.M. (2001). The propensity score: a means to an end. Discussion Paper No. 271, IZA.

  • Ayuya, O. I., Gido, E. O., Bett, H. K., Lagat, J. K., Kahi, A. K., & Bauer, S. (2015). Effect of certified organic production systems on poverty among smallholder farmers: empirical evidence from Kenya. World Development, 67, 27–37.

    Article  Google Scholar 

  • Becerril, J., & Abdulai, A. (2010). The impact of improved maize varieties on poverty in Mexico: A propensity score-matching approach. World Development, 38(7), 1024–1035.

    Article  Google Scholar 

  • Brookhart, M. A., Schneeweiss, S., Rothman, K. J., Glynn, R. J., Avorn, J., & Stürmer, T. (2006). Variable selection for propensity score models. American Journal of Epidemiology, 163, 1149–1156.

    Article  PubMed Central  PubMed  Google Scholar 

  • Bwalya, B. B., Lemba, M., Mapoma, C. C., & Mutombo, N. (2015). Factors associated with stunting among children aged 6–23 months in zambian: evidence from the 2007 Zambia demographic and health survey. International Journal of Advanced Nutritional and Health Science, 3, 116–131.

    Google Scholar 

  • Caliendo, M., Kopeinig, S. (2008). Some practical guidance for the implementation of propensity score matching. Journal of Economic Surveys, 22, 31–72.

  • Chirwa, E. W., & Ngalawa, H. (2008). Determinants of child nutrition in Malawi. South African Journal of Economics, 76(4), 628–640.

    Article  Google Scholar 

  • Christiaensen, L., & Alderman, H. (2004). Child malnutrition in Ethiopia: Can maternal knowledge augment the role of income. Economic Development and Cultural Change, 52(2), 287–312.

    Article  Google Scholar 

  • CSO. (2012). The monthly. Zambia Central Statistics Office. Lusaka

  • Di Falco, S., & Veronesi, M. (2013). How can African agriculture adapt to climate change? A counterfactual analysis from Ethiopia. Land Economics, 89(4), 743–766.

    Article  Google Scholar 

  • Di Falco, S., Veronesi, M., & Yesuf, M. (2011). Does adaptation to climate change provide food security? A micro-perspective from Ethiopia. American Journal of Agricultural Economics, 93(3), 829–846.

    Article  Google Scholar 

  • Dorosh, P. A., Dradri, S., & Haggblade, S. (2009). Regional trade, government policy and food security: Recent evidence from Zambia. Food Policy, 34(4), 350–366.

    Article  Google Scholar 

  • Feder, G. R., Just, R. E., & Zilberman, D. (1985). Adoption of agricultural innovations in developing countries: a survey. Economic Development and Cultural Change, 33, 255–298.

    Article  Google Scholar 

  • Glewwe, P., Koch, S., & Nguyen, B. L. (2002). Child nutrition, economic growth and the provision of health care services in Vietnam in the 1990s. In Policy research working paper 2838. Washington, DC: World Bank.

    Google Scholar 

  • Gregory, C. A., & Coleman-Jensen, A. (2013). Do high food prices increase food insecurity in the United States? Applied Economic Perspectives and Policy, 35, 679–707.

    Article  Google Scholar 

  • Headey, D. D. (2013). Developmental drivers of nutritional change: a cross-country analysis. World Development, 42, 76–88.

    Article  Google Scholar 

  • Heckman, J., Tobias, J. L., & Vytlacil, E. (2001). Four parameters of interest in the evaluation of social programs. Southern Economic Journal, 68, 210–223.

    Article  Google Scholar 

  • Horton, S., Alderman, H., and Rivera, J. A. (2008). The challenge of hunger and malnutrition. Copenhagen Consensus. Copenhagen

  • Howard, J., & Mungoma, C. (1996). Zambia’s stop–and–go revolution: the impact of policies and organizations on the development and spread of maize technology. Department of Agricultural Economics, East Lansing: Michigan State University.

    Google Scholar 

  • Kabubo-Mariara, J., Ndenge, G. K., & Mwabu, D. K. (2008). Determinants of children’s nutritional status in Kenya: Evidence from demographic and health surveys. Journal of African Economies, 18(3), 363–387.

    Article  Google Scholar 

  • Kalinda, T., Tembo, G., & Kuntashula, E. (2014). Adoption of improved maize seed varieties in southern Zambia. Asian Journal of Agricultural Sciences, 6, 33–39.

    Google Scholar 

  • Kassie, M., Jaleta, M., Shiferaw, B., Mmbando, F., & Mekuria, M. (2013). Adoption of interrelated sustainable agricultural practices in smallholder systems: evidence from rural Tanzania. Technological Forecasting and Social Change, 80, 525–540.

    Article  Google Scholar 

  • Khonje, M., Manda, J., Alene, A. D., & Kassie, M. (2015). Analysis of adoption and impacts of improved maize varieties in eastern Zambia. World Development, 66, 695–706.

    Article  Google Scholar 

  • Kumar, S.K. (1994). Adoption of hybrid maize in Zambia: effects on gender roles, food consumption, and nutrition (Research Report 100). Washington, DC: International Food Policy Research Institute.

  • Kumar, D., Goel, N., Mittal, P. C., & Misra, P. (2006). Influence of infant-feeding practices on nutritional status of under-five children. The Indian Journal of Pediatrics, 73(5), 417–421.

    Article  PubMed  Google Scholar 

  • Lokshin, M., & Glinskaya, E. (2009). The effect of male migration on employment patterns of women in Nepal. The World Bank Economic Review, 23, 481–507.

    Article  Google Scholar 

  • Lokshin, M., & Sajaia, Z. (2011). Impact of interventions on discrete outcomes: maximum likelihood estimation of the binary choice models with binary endogenous regressors. Stata Journal, 11, 368–385.

    Google Scholar 

  • MacRobert, J., Setimela, P., Gethi, J., and Regasa, M.W. (2014). Maize hybrid seed production manual

  • Masiye, F., Chama, C., Chitah, B., and Jonsson, D. (2010). Determinants of child nutritional status in Zambia: An analysis of a national survey. Zambia Social Science Journal, 1. No. 1, Article 4

  • Masset, E., Haddad, L., Cornelius, A., and Isaza-Castro, J. (2011). A systematic review of agricultural interventions that aim to improve nutritional status of children

  • Morrisson, C., Thorbecke, E., Guilmeau, H., and Linkens, C. (2002). Poverty and malnutrition in Sub-Saharan Africa. Cornell University, Ithaca, N.Y

  • O’Donnell, O., Doorslaer, E.V., Wagstaff, A., and Lindelow, M. (2008). Analyzing health equity using household survey data: a guide to techniques and their implementation. WBI Learning Resources Series

  • Ojiako, I. A., Manyong, V. M., & Ikpi, A. E. (2009). Determinants of nutritional status of preschool children from rural households in Kaduna and Kano States, Nigeria. Pakistan Journal of Nutrition, 8(9), 1497–1505.

    Article  Google Scholar 

  • Onyango, A., Tucker, K., & Eisemon, T. (1994). Household headship and child nutrition: a case study in western Kenya. Social Science and Medicine, 39(12), 1633–1639.

    Article  CAS  PubMed  Google Scholar 

  • Raj, A., Saggurti, N., Winter, M., Labonte, A., Decker, M. R., Balaiah, D., et al. (2010). The effect of maternal child marriage on morbidity and mortality of children under 5 in India: cross sectional study of a nationally representative sample. BMJ, 340, b4258.

    Article  PubMed Central  PubMed  Google Scholar 

  • Rao, E. J. O., & Qaim, M. (2011). Supermarkets, farm household income, and poverty: insights from Kenya. World Development, 39(5), 784–796.

    Article  Google Scholar 

  • Rosenbaum, P.R., Rubin, D.B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70, 41–55.

  • Sanginga, P. C., Adesina, A. A., Manyong, V. M., Otite, O., and Dashiell, K. E. (1999). Social impact of soybean in Nigeria’s southern Guinea savanna. International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria

  • Sarmistha, P. (1999). An analysis of childhood malnutrition in rural India: Role of gender, income and other household characteristics. World Development, 27(7), 1151–1171.

    Article  Google Scholar 

  • Sitko, N., Chapoto A, Kabwe S, Tembo S, Hichaambwa M, Lubinda R, Chiwawa, H., Mataa, M., Heck, S., and Nthani, D. (2011). Technical Compendium: Descriptive Agricultural Statistics and Analysis for Zambia in Support of the USAID Mission’s Feed the Future Strategic Review. Working Paper No. 52 Food Security Research Project, Lusaka

  • Smale, M., & Mason, N. (2014). Hybrid seed and the economic well-being of smallholder maize farmers in Zambia. Journal of Development Studies, 1–16.

  • Ssewanyana, N. S. (2003). Food security and child nutrition status among urban poor households in Uganda: Implications for poverty alleviation. AERC Research Paper 130

  • Staatz, J. (2000). Strategic pathways and interactions to cutting hunger in half in Africa. Paper presented at the future opportunities for rural Africa workshop, November 26, hosted by IFPRI and USAID

  • Svedberg, P. (1990). Undernutrition in sub-saharan Africa: is there a gender bias? Journal of Development Studies, 26(3), 469–486.

    Article  Google Scholar 

  • Tembo, S., & Sitko, N. (2013). Technical compendium: descriptive agricultural statistics and analysis for Zambia indaba agricultural policy research institute (IAPRI). Zambia: Lusaka.

    Google Scholar 

  • UNDP. (2011). Zambia Human Development Report 2011: Service delivery for sustainable human development. In G. Luchsinger (Ed.). Lusaka

  • UNICEF. (2008). Zambia situation analysis of children and women 2008. Lusaka: UNICEF Zambia

  • WHO (World Health Organization). (1995). “Physical Status: The use and interpretation of anthropometry. Report of a WHO Expert Committee.” World Health Organ Tech Rep Ser 854: 1–452

  • World Bank (2008). World development report 2008: agriculture for development. World: Bank.

    Book  Google Scholar 

  • Zeng, D., Alwang, J., Norton, G. W., Shiferaw, B., Jaleta, M., and Yirga, C. (2014). Agricultural technology adoption and child nutrition: Improved maize varieties in rural Ethiopia. In Selected Paper prepared for presentation at the Agricultural and Applied Economics Association’s 2014 AAEA Annual Meeting. Minneapolis

Download references

Acknowledgments

The authors gratefully acknowledge financial support from the USAID Zambia Mission (USAID/Zambia). The household survey was conducted in collaboration with the Ministry of Agriculture and Livestock of Zambia and the Zambia Agricultural Research Institute (ZARI). We thank Bernadette Chimai of the University of Zambia who ably supervised the data collection process. We are grateful to three anonymous referees and the Editor-in-Chief of this journal for their comments on an earlier draft of the paper.

Author information

Authors and Affiliations

  1. International Institute of Tropical Agriculture (IITA), Lilongwe, Malawi

    Julius Manda, Makaiko G. Khonje & Arega D. Alene

  2. Agricultural Economics and Rural Policy Group, Wageningen University, Wageningen, The Netherlands

    Cornelis Gardebroek

  3. The International Maize and Wheat Improvement Center (CIMMYT), Harare, Zimbabwe

    Munyaradzi Mutenje

  4. The International Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya

    Menale Kassie

Authors
  1. Julius Manda
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Cornelis Gardebroek
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Makaiko G. Khonje
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Arega D. Alene
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Munyaradzi Mutenje
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Menale Kassie
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Julius Manda.

Appendix

Appendix

Table 10

Table 10 Probit estimates of determinants of adoption of improved maize varieties in eastern Zambia
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Manda, J., Gardebroek, C., Khonje, M.G. et al. Determinants of child nutritional status in the eastern province of Zambia: the role of improved maize varieties. Food Sec. 8, 239–253 (2016). https://doi.org/10.1007/s12571-015-0541-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12571-015-0541-y

Keywords

Search

Navigation