Joint Modeling of Poverty of Households and Malnutrition of Children Under Five Years from Demographic and Health Survey Data: Case of Rwanda
Abstract
The main objective of this study was to identify the risk factors associated to malnutrition of children under five years and poverty and assess the correlation between them. We created a composite index from three anthropometric indictors (stunting, underweight and wasting).A multivariate joint model using the generalized linear mixed model was utilized for the analyses of the data. Child age, birth order of the children, the gender of children, birth weights of the children, multiple birth of the child, fever, anemia of the mother, body mass index of the mother, mother’s education level, mother’s knowledge on nutrition, age of household head, source of drinking water, toilet facilities, place of residence of household, source of drinking water and province were found to be significantly related to poverty and malnutrition. The study revealed a positive correlation between poverty of household and malnutrition of children less than five yearsDownloads
References
Chatfield, C. & Collins, A. (1980). Introduction to multivariate analysis. London: Chapman and Hall. DOI: https://doi.org/10.1007/978-1-4899-3184-9
Das, S. & Rahman, R. M. (2011). Application of ordinal logistic regression analysis in determining risk factors of child malnutrition in Bangladesh. Nutrition journal, 10(1), 124. Demissie, S. & Worku, A. (2013). Magnitude and factors associated with malnutrition in children 6-59 months of age in pastoral community of Dollo Ado district, Somali region, Ethiopia. Scince Journal of Public Health,1(4), 175-183. DOI: https://doi.org/10.1186/1475-2891-10-124
Gueorguieva, R. (2001). A multivariate generalized linear mixed model for joint modelling of clustered outcomes in the exponential family. Statistical Modelling, 1(3), 177-193. Habyarimana, F., Zewotir, T. & Ramroop, S. (2015e). Spatial distribution of key determinants of malnutrition of children under five years in Rwanda: Simultaneous measurements of three anthropometric indices. Under review. Habyarimana, F., Zewotir, T. & Ramroop, S. (2015d). Key determinants of malnutrition of children under five years in Rwanda: Simultaneous measurement of three anthropometric indices. Under review.
Habyarimana, F., Zewotir, T. & Ramroop, S. (2015c). Determinants of poverty of households: Semiparametric analysis of demographic and health survey data from Rwanda. Journal of Economics and behavioural Studies, 7(3), 47-55. Habyarimana, F., Zewotir, T. & Ramroop, S. (2015b). Determinants of poverty of households in Rwanda: An application of quantile regression. Journal of Human Ecology, 50(1), 19-30. Habyarimana, F., Zewotir, T. & Ramroop, S. (2015a). Analysis of demographic and health survey data to measure poverty of household in Rwanda. African Population Studies, 29(1), 1472-1482. Habyarimana, F., Zewotir, T. & Ramroop, S. (2014). A Proportional Odds Model with Complex Sampling Design to Identify Key Determinants of Malnutrition of Children under Five Years in Rwanda. Mediterranean Journal of Social Sciences, 5(23), 1642-1648. Heinkens, G. T., Bunn, B. J., Amadi, B., Manary, M., Chhagan, M., Brkley, J. A., Rollins, N., Kelly, P., Adamczick, C., Maitland, K. & Tomkins, A. (2008). Case management of HIV-infected severely malnourished children: challenges in the area of highest prevalence. The Lancet, 371(2),1305-1307.
Islam, M. M., Alam, M., Tariquzaman, M., Kabir, M. A., Pervin, R., Begum, M. & Khan, M. M. H. (2013). Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model. BMC public health, 13(1), 11. DOI: https://doi.org/10.1186/1471-2458-13-11
Jackson, J. E. (2005). A user's guide to principal components. John Wiley & Sons. Jolliffe, I. T. (2002). Principal component analysis. Springer-Verlag. Justice, M. K. A., Thomas, J. K., Benjamin, M. T. & Petter, J. D. (2015). Childhood malnutrition and its determinants among uner-five children in Ghana. Paediatric and Perinatal Epidemiology, 29(6),552-561.
Kandala, N. B., Madungu, T. P., Emina, J. B., Nzita, K. P. & Cappuccio, F. P. (2011). Malnutrition among children under the age of five in the Democratic Republic of Congo (DRC): does geographic location matter? BMC public health, 11(1), 261-266. Kavosi, E., Hassanzadeh, R. Z., Kavosi, Z., Nasihatkon, A., Moghadam, M. & Heidari, M. (2014). Prevalence and determinants of under-nutrition among children under six: a cross-sectional survey in Fars province, Iran. Int J Health Policy Manag, 3(2), 71-76. Laghari, Z. A., Soomro, A. M., Tunio, S. A., Lashari, K., Baloach, F. G., Baig, N. M. & Bano, S. (2015). Malnutrition among children under five years in district Sanghar, Sindh, Pakistan. Gomal Journal of Medical Sciences, 13(1), 54-57.
Lewis-Beck, M. S. (1994). Factor analysis and related techniques. New London: Sage publication. Manly, B. F. (2004). Multivariate statistical methods: a primer: CRC Press.
Masibo, P. K. & Makoka, D. (2012). Trends and determinants of undernutrition among young Kenyan children: Kenya Demographic and Health survey: 1993, 1998, 2003 and 2008-2009. Public health nutrition, 15(9), 1715-1722. Matanda, D. J., Mittelmark, M. B. & Kigaru, D. M. D. (2014). Child undernutrition in Kenya: trend analyses from 1993 to 2008–2009. BMC pediatrics, 14(1), 5. Molenberghs, G. & Vebeke, G. (2005). Models for discrete longitudinal data. New York: Springer-Verlag. Nandy, S., Irving, M., Gordon, D., Subramanian, S. V. & Smith, G. D. (2005). Poverty and morbidity: new evidence from India. Bulletin of the World Health Organisation, 83(3),210-216. NISR, ICF & MoH (2012). Rwanda Demographic and Health Survey 2010, NISR.
Setboonsarng, S. (2005). Child malnutrition as a poverty indicator: An evaluation in the context of different development interventions in Indonesia: ADB Institute Discussion Papers.
WHO. (1995). Physical Status: the Use and Interpretation of Anthropometry:Report of a WHO Expert Committe.
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