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Socio-economic Inequality in Stunting among Children Aged 6-59 Months in a Ugandan Population Based Cross-sectional Study

Received: 18 April 2019     Accepted: 14 June 2019     Published: 6 August 2019
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Abstract

Socio-economic status is an important predictor of stunting, however published population based studies on socio-economic inequalities in stunting among children under-five years of age is scarce in Uganda. Data from the 2016 Uganda Demographic and Health Survey was used to identify possible socio-economic inequalities in stunting among 3941 children aged 6-59 months. Multivariate binary logistic regression models were fitted to calculate the odds ratios and their corresponding 95% confidence intervals for stunting by maternal formal education and household wealth index. The overall prevalence of stunting among children was 30.1%. The risk of stunting was higher among children whose mothers had no formal education (OR: 4.35; 95% CI, 2.45-7.71), attained primary (OR: 2.74 95% CI, 1.62-4.63) and secondary level education (OR: 2.30 95% CI, 1.34-3.96) compared to those whose mothers attained tertiary level education. Similarly higher risk of stunting was found among children that lived in the poorest (OR: 1.78 95% CI, 1.23-2.59), poorer (OR: 1.88; 95% CI, (1.28-2.74), middle (OR: 1.91, 95% CI, 1.31-2.77) and richer households (OR: 1.60; 95% CI, 1.10-2.32) compared to those in the richest households. Socio-economic differences in stunting among children under-five years of age were found. Targeting stunting prevention interventions to less affluent mother-child dyads and households might be important in reducing social inequalities in stunting among children under-five years of age in Uganda.

Published in American Journal of Pediatrics (Volume 5, Issue 3)
DOI 10.11648/j.ajp.20190503.18
Page(s) 125-132
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Stunting, Children, Socio-economic Status, Inequalities, Uganda

References
[1] Black, R. E., et al., Maternal and child undernutrition: global and regional exposures and health consequences. The lancet, 2008. 371 (9608): p. 243-260.
[2] Dewey, K. G. and K. Begum, Long‐term consequences of stunting in early life. Maternal & child nutrition, 2011. 7: p. 5-18.
[3] Stunting, C., Context, Causes and Consequences WHO Conceptual Framework. 2013, WHO.
[4] Black, R. E., et al., Maternal and child undernutrition and overweight in low-income and middle-income countries. The lancet, 2013. 382 (9890): p. 427-451.
[5] De Onis, M., M. Blössner, and E. Borghi, Prevalence and trends of stunting among pre-school children, 1990–2020. Public health nutrition, 2012. 15 (1): p. 142-148.
[6] UNICEF, Joint child malnutrition estimates—Levels and trends. 2017.
[7] UNICEF, W., and The World Bank., Levels and trends in child malnutrition: key findings of the 2019 Edition of the Joint Child Malnutrition Estimates. 2019: Geneva.
[8] Yang, Y. Y., et al., Trends and determinants of stunting among under-5s: evidence from the 1995, 2001, 2006 and 2011 Uganda Demographic and Health Surveys. Public health nutrition, 2018. 21 (16): p. 2915-2928.
[9] Statistics, U. B. o. and U. ICF % J Kampala, Uganda demographic and health survey 2016: key indicators report. 2017, UBOS, and Rockville Maryland.
[10] Bank, W., the Uganda Poverty Assessment Report 2016 2016.
[11] Statistics, U. B. o. and ICF, Uganda Demographic and Health Survey 2016: Key Indicators Report. 2017, Uganda Bureau of Statistics (UBOS), and Rockville, MD: UBOS and ICF Kampala.
[12] Nambuusi, B. B., et al., The effects and contribution of childhood diseases on the geographical distribution of all-cause under-five mortality in Uganda. Parasite Epidemiology and Control, 2019: p. e00089.
[13] Achadi, E., et al., Global Nutrition Report: From Promise to Impact: Ending Malnutrition by 2030. 2016: International Food Policy Research Institute.
[14] Marmot, M., et al., Fair society, healthy lives. 2008.
[15] Adekanmbi, V. T., G. A. Kayode, and O. A. Uthman, Individual and contextual factors associated with childhood stunting in Nigeria: a multilevel analysis. Maternal & child nutrition, 2013. 9 (2): p. 244-259.
[16] Mawa, R. and S. Lawoko, Malnutrition Among Children Under Five Years in Uganda. American Journal of Health Research, 2018. 6 (2): p. 56-66.
[17] Dake, S. K., et al., Predictors of stunting among children 6–59 months of age in Sodo Zuria District, South Ethiopia: a community based cross-sectional study. 2019. 5 (1): p. 23.
[18] Akombi, B., et al., Stunting, wasting and underweight in sub-Saharan Africa: a systematic review. 2017. 14 (8): p. 863.
[19] Casale, D., G. Espi, and S. A. J. P. h. n. Norris, Estimating the pathways through which maternal education affects stunting: evidence from an urban cohort in South Africa. 2018. 21 (10): p. 1810-1818.
[20] Mawa, R. and S. J. A. J. o. H. R. Lawoko, Malnutrition Among Children Under Five Years in Uganda. 2018. 6 (2): p. 56-66.
[21] Abuya, B., et al., Influence of maternal education on child immunization and stunting in Kenya. 2011. 15 (8): p. 1389-1399.
[22] Keino, S., et al., Determinants of stunting and overweight among young children and adolescents in sub-Saharan Africa. 2014. 35 (2): p. 167-178.
[23] Howe, L. D., J. R. Hargreaves, and S. R. Huttly, Issues in the construction of wealth indices for the measurement of socio-economic position in low-income countries. Emerging themes in epidemiology, 2008. 5 (1): p. 3.
[24] Mensch, B. S., et al., Evidence for causal links between education and maternal and child health: Systematic review. Tropical Medicine & International Health, 2019.
[25] Habaasa, G. J. B. p., An investigation on factors associated with malnutrition among underfive children in Nakaseke and Nakasongola districts, Uganda. 2015. 15 (1): p. 134.
[26] Kikafunda, J. and J. Tumwine, Diet and socio-economic factors and their association with the nutritional status of pre-school children in a low income suburb of Kampala City, Uganda. East African medical journal, 2006. 83 (10): p. 565-574.
[27] Prentice, A. M. J. N. and G. Yearbook, Stunting in Developing Countries. 2019. 119: p. 171-183.
[28] Wamani, H., et al., Boys are more stunted than girls in sub-Saharan Africa: a meta-analysis of 16 demographic and health surveys. 2007. 7 (1): p. 17.
[29] Schoenbuchner, S. M., et al., The relationship between wasting and stunting: a retrospective cohort analysis of longitudinal data in Gambian children from 1976 to 2016. The American journal of clinical nutrition, 2019.
[30] Foundation, N., The HUNGaMA Survey Report 2011.
[31] Abuya, B. A., J. Ciera, and E. J. B. p. Kimani-Murage, Effect of mother’s education on child’s nutritional status in the slums of Nairobi. 2012. 12 (1): p. 80.
[32] Fikadu, T., S. Assegid, and L. Dube, Factors associated with stunting among children of age 24 to 59 months in Meskan district, Gurage Zone, South Ethiopia: a case-control study. BMC Public Health, 2014. 14 (1): p. 800.
[33] Jolliffe, I. T. and J. Cadima, Principal component analysis: a review and recent developments. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2016. 374 (2065): p. 20150202.
[34] Habaasa, G., An investigation on factors associated with malnutrition among underfive children in Nakaseke and Nakasongola districts, Uganda. BMC pediatrics, 2015. 15 (1): p. 134.
[35] Mistry, S. K., et al., Individual-, maternal-and household-level factors associated with stunting among children aged 0–23 months in Bangladesh. Public health nutrition, 2019: p. 1-10.
[36] Sharaf, M. F., E. I. Mansour, and A. S. Rashad, child nutritional status in egypt: a comprehensive analysis of socioeconomic determinants using a quantile regression approach. Journal of biosocial science, 2019. 51 (1): p. 1-17.
Cite This Article
  • APA Style

    Baru Ruth Sharon Apio, Ratib Mawa, Stephen Lawoko, Krishna Nand Sharma. (2019). Socio-economic Inequality in Stunting among Children Aged 6-59 Months in a Ugandan Population Based Cross-sectional Study. American Journal of Pediatrics, 5(3), 125-132. https://doi.org/10.11648/j.ajp.20190503.18

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    ACS Style

    Baru Ruth Sharon Apio; Ratib Mawa; Stephen Lawoko; Krishna Nand Sharma. Socio-economic Inequality in Stunting among Children Aged 6-59 Months in a Ugandan Population Based Cross-sectional Study. Am. J. Pediatr. 2019, 5(3), 125-132. doi: 10.11648/j.ajp.20190503.18

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    AMA Style

    Baru Ruth Sharon Apio, Ratib Mawa, Stephen Lawoko, Krishna Nand Sharma. Socio-economic Inequality in Stunting among Children Aged 6-59 Months in a Ugandan Population Based Cross-sectional Study. Am J Pediatr. 2019;5(3):125-132. doi: 10.11648/j.ajp.20190503.18

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  • @article{10.11648/j.ajp.20190503.18,
      author = {Baru Ruth Sharon Apio and Ratib Mawa and Stephen Lawoko and Krishna Nand Sharma},
      title = {Socio-economic Inequality in Stunting among Children Aged 6-59 Months in a Ugandan Population Based Cross-sectional Study},
      journal = {American Journal of Pediatrics},
      volume = {5},
      number = {3},
      pages = {125-132},
      doi = {10.11648/j.ajp.20190503.18},
      url = {https://doi.org/10.11648/j.ajp.20190503.18},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajp.20190503.18},
      abstract = {Socio-economic status is an important predictor of stunting, however published population based studies on socio-economic inequalities in stunting among children under-five years of age is scarce in Uganda. Data from the 2016 Uganda Demographic and Health Survey was used to identify possible socio-economic inequalities in stunting among 3941 children aged 6-59 months. Multivariate binary logistic regression models were fitted to calculate the odds ratios and their corresponding 95% confidence intervals for stunting by maternal formal education and household wealth index. The overall prevalence of stunting among children was 30.1%. The risk of stunting was higher among children whose mothers had no formal education (OR: 4.35; 95% CI, 2.45-7.71), attained primary (OR: 2.74 95% CI, 1.62-4.63) and secondary level education (OR: 2.30 95% CI, 1.34-3.96) compared to those whose mothers attained tertiary level education. Similarly higher risk of stunting was found among children that lived in the poorest (OR: 1.78 95% CI, 1.23-2.59), poorer (OR: 1.88; 95% CI, (1.28-2.74), middle (OR: 1.91, 95% CI, 1.31-2.77) and richer households (OR: 1.60; 95% CI, 1.10-2.32) compared to those in the richest households. Socio-economic differences in stunting among children under-five years of age were found. Targeting stunting prevention interventions to less affluent mother-child dyads and households might be important in reducing social inequalities in stunting among children under-five years of age in Uganda.},
     year = {2019}
    }
    

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  • TY  - JOUR
    T1  - Socio-economic Inequality in Stunting among Children Aged 6-59 Months in a Ugandan Population Based Cross-sectional Study
    AU  - Baru Ruth Sharon Apio
    AU  - Ratib Mawa
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    AB  - Socio-economic status is an important predictor of stunting, however published population based studies on socio-economic inequalities in stunting among children under-five years of age is scarce in Uganda. Data from the 2016 Uganda Demographic and Health Survey was used to identify possible socio-economic inequalities in stunting among 3941 children aged 6-59 months. Multivariate binary logistic regression models were fitted to calculate the odds ratios and their corresponding 95% confidence intervals for stunting by maternal formal education and household wealth index. The overall prevalence of stunting among children was 30.1%. The risk of stunting was higher among children whose mothers had no formal education (OR: 4.35; 95% CI, 2.45-7.71), attained primary (OR: 2.74 95% CI, 1.62-4.63) and secondary level education (OR: 2.30 95% CI, 1.34-3.96) compared to those whose mothers attained tertiary level education. Similarly higher risk of stunting was found among children that lived in the poorest (OR: 1.78 95% CI, 1.23-2.59), poorer (OR: 1.88; 95% CI, (1.28-2.74), middle (OR: 1.91, 95% CI, 1.31-2.77) and richer households (OR: 1.60; 95% CI, 1.10-2.32) compared to those in the richest households. Socio-economic differences in stunting among children under-five years of age were found. Targeting stunting prevention interventions to less affluent mother-child dyads and households might be important in reducing social inequalities in stunting among children under-five years of age in Uganda.
    VL  - 5
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Author Information
  • Department of Public Health, Faculty of Health Sciences, Victoria University Kampala, Kampala, Uganda

  • Department of Public Health, Faculty of Health Sciences, Victoria University Kampala, Kampala, Uganda

  • Department of Public Health, Faculty of Health Sciences, Victoria University Kampala, Kampala, Uganda

  • Department of Public Health, Faculty of Health Sciences, Victoria University Kampala, Kampala, Uganda

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