RISK FACTORS ASSOCIATED WITH STUNTING AND WASTING LEVELS AMONG UNDER FIVE CHILDREN IN ETHIOPIA
Keywords:
Stunting and wasting, Proportional odds model, partial proportional odds model.Abstract
Introduction: Childhood stunting is one of the most significant impediments to human development. Stunting is a major health problem in children under-five years in many low and middle income countries around the world. Wasting is sometimes referred to as acute malnutrition because it is believed that episodes of wasting have a short duration, in contrast to stunting, which is regarded as chronic malnutrition.
Method: The data for the study were taken from Ethiopian Demographic Health Survey (EDHS) of year 2011. For stunting levels parallel line assumption of proportional odds model is violated. Thus, Partial proportional odds model was preferred over proportional odds model, generalized ordered logit model and multinomial logistic regression based on Akaike’s Information Criterion evidence. Proportional odds model is used to analyze wasting levels since the parallel assumption of proportional odds model is not violated.
Result: This study revealed that the relative frequency distributions of the stunting and wasting status of child. 16.5% are severely stunted, 20.6% are moderately stunted and 62.9% are not stunted and also shows that 1.4% of children are severely wasted, 9% are moderately wasted and 89.6% are not wasted. The result indicates that age of child in month, region, place of residence, wealth index, mothers BMI, birth order of child, incidence of diarrhea for two weeks preceding the survey, incidence of fever for two weeks before survey, mothers and husband/partner educational levels are significantly associated with stunting levels. The result also shows that age of child, wealth index, mothers nutritional status, sex of child, incidence of diarrhea and fever for two weeks before survey, type of toilet, husbands/partner and employment status of mothers are significantly associated with wasting levels.
Conclusions: PPOM fitted the data adequately in predicting severity status of stunting because of POM assumption is violated but POM is appropriate for wasting status. Children younger than 11 months had low risk of stunting and wasting status than other age groups. This could be because of breastfeeding in the early stages of child growth. Children in rural areas are more likely to be stunted than children in urban areas.
Downloads
References
Alemu Adeba, Sileshi Garoma, Habtamu Fekadu and Wondu Garoma 2014 Prevalence’s of Wasting and its Associated Factors of Children among 6-59 Months Age in Guto Gida District, Oromia Regional State, Ethiopia
Blessing J.Akombi, Kingsley E.Agho, Dafna Merom, John J.Hall and Andre M.Renzaho published January 2017 Multilevel Analysis of Factors Associated with Wasting and Underweight among Children Under-Five Years in Nigeria
Bloem M. Preventing stunting: why it matters, what it takes. In: Eggersdorfer M, Kraemer K, Ruel M, Biesalski HK, Bloem M et al., editors.The road to good nutrition. Basel: Karger;2013:1324 (http://www.karger.com/ProdukteDB/Katalogteile/isbn3_318/_025/_49/roa _04.pdf, accessed 21 October 2014).
Caulfield, et al. Under nutrition as an underlying cause of child deaths associated with diarrhea, pneumonia, malaria and measles. American Journal of Clinical Nutrition, 2004; 80:195.
Desalegne Amare, Ayenew Negesse, Baye Tsegaye, Birtukan Assefa, and Birehanu Ayenie. Prevalence of Undernutrition and Its Associated Factors among Children below Five Years of Age in Bure Town, West Gojjam Zone, Amhara National Regional State, Northwest Ethiopia
De Onis M. WHO child growth standards: length/height-for-age, weight-for-age, weight-for-length, weight-forheight and body mass index-for-age. WHO. 2006.
Fotso JC, Kuate-Defo B. Socioeconomic inequalities in early childhood malnutrition and morbidity: modification of the household-level effects by the community SES. Health Place 2005;11: 205–25.
Fu, Vincent, K., (1998). Estimating Generalized Ordered Logit Models, STATA
Genebo Timotiows and Girma Woldemariam. (2002).“Determinants of Nutritional Status of Women and Children in Ethiopia”. ORC Macro, Calverton, Maryland USA. P. 1-36. (Assessed at http://www.measuredhs. comnutrition. pdf dated May 22nd, 2007).
Habaasa Gilbert (2010); Determinants of Malnutrition among Under-Five Children in Nakaseke and Nakasongola Districts, Uganda
Hosmer, D. W. and Lemeshow, S. (2000): Applied logistic regression, John Wiley & Sons, New York, 2nd edition.
Jeyaseelan, L. (1997). Risk factors for malnutrition in South India children. Journal of Biosocial Science, 1, 93-100.
Kabubo-Mariara, J., Ndenge, G.K., and Kirii, D.M. (2006). Determinants of Children’s Nutritional Status in Kenya:Evidence from Demographic and Health Surveys. Paper Presented at the Centre for the Study of African Economies Conference, University of Oxford, March 17-21, 2006.
Kleinbaum, D.G. and Ananth, C.V., (1997). Regression Models for Ordinal Responses
Loida Maria Garcia Cruz, Gloria Gonzalez Azpeitia, Desiderio Reyes Suarez, Alfredo Santana Rodriguez, Juan Francisco Loro Ferrer and Lluis Serra-Majem (2017). Factors Associated with Stunting among Children Aged 0 to 59 Months from the Central Region of Mozambique
M. De Onis, D. Brown, M. Blossner, and E. Borghi, Levels and Trends in Child Malnutrition. UNICEF-WHOThe World Bank Joint Child Malnutrition Estimates, UNICEF, New York, NY, USA, 2012.
McCullagh P. and Nelder J. A. (1989), Generalized linear models (2nd Ed.). London: Chapman and Hall.
Mussie Alemayehu et al (2014). Nutritional status and associated factors among under-five children, Tigray, Northern Ethiopia.
Nguyen, N.H., and Kam.S. (2008).Nutritional status and the characteristics related to malnutrition in children under-five years of age in Nghean, Vietnam. Journal of preventive medicine and public health, 41(4), 232-240.
Nure, A. S., Nuruzzaman, H., Abdul, G. (2011). Mulnutrition of underfive children: Evidence from Bangladesh.Asian Journal of medical sciences 2,113-119.
Peterson, B. L., and Harrell, F. E. (1990). Partial Proportional Odds Models for Ordinal Response Variables. Applied Statistics, 39(3), 205-217.
Semali, I.A.; Tengia-Kessy, A.; Mmbaga, E.J.; Leyna, G. Prevalence and determinants of stunting in under-fivechildren in central Tanzania: Remaining threats to achieving Millennium Development Goal 4. BMC Public Health 2015, 15, 1153. [CrossRef] [PubMed]
Shen T, Habicht JP, Chang Y. Effect of economic reforms on child growth in urban and rural areas of China. N Engl J Med. 1996;335(6):400-406
Shrimpton, R., Victoria, C.G., Onis, M.de., Lima, R.C., Blossner, M., and Clugston, G. (2001). Worldwide Timing of growth faltering: Implications for nutritional interventions. Paediatrics, 107,75-81.
Sommerfelt, A., and Stewart, K. (1994). Children’s nutritional status. DHS Comparative Studies. Calverton, Maryland, USA: Macro International Inc.
Tadiwos Zewdie and Degnet Abebaw. Determinants of Child Malnutrition: Empirical Evidence from Kombolcha District of Eastern Hararghe Zone, Ethiopia. Quarterly Journal of International Agriculture 52(2013), No.4:357-372
UNICEF, Improving Child Nutrition: The Achievable Imperative for Global Progress, United Nations Children’s Fund, 2013
WHO (2000) Global agenda for combating malnutrition: progress report. Geneva, World Health
Organization World health organization. Guideline: updates on the management of severe acute malnutrition in infants and CHILDREN; World Health organization: Geneva, Switzerland, 2013).
Downloads
Published
How to Cite
Issue
Section
License
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution (CC-BY) 4.0 License that allows others to share the work with an acknowledgment of the work’s authorship and initial publication in this journal.
