Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Feb 12;11(1):3759.
doi: 10.1038/s41598-021-82755-7.

Predictors of stunting among children age 6-59 months in Ethiopia using Bayesian multi-level analysis

Amare Muche  1 , Lemma Derseh Gezie  2 , Adhanom Gebre-Egzabher Baraki  2 , Erkihun Tadesse Amsalu  3
Affiliations

Predictors of stunting among children age 6-59 months in Ethiopia using Bayesian multi-level analysis

Amare Muche et al. Sci Rep. .

Abstract

In developing countries including Ethiopia stunting remained a major public health burden. It is associated with adverse health consequences, thus, investigating predictors of childhood stunting is crucial to design appropriate strategies to intervene the problem stunting. The study uses data from the Ethiopian Demographic and Health Survey (EDHS) conducted from January 18 to June 27, 2016 in Ethiopia. A total of 8117 children aged 6-59 months were included in the study with a stratified two stage cluster sampling technique. A Bayesian multilevel logistic regression was fitted using Win BUGS version 1.4.3 software to identify predictors of stunting among children age 6-59 months. Adjusted odds ratio (AOR) with 95% credible intervals was used to ascertain the strength and direction of association. In this study, increasing child's age (AOR = 1.022; 95% CrI 1.018-1.026), being a male child (AOR = 1.16; 95%CrI 1.05-1.29), a twin (AOR = 2.55; 95% CrI 1.78-3.56), having fever (AOR = 1.23; 95%CrI 1.02-1.46), having no formal education (AOR = 1.99; 95%CrI 1.28-2.96) and primary education (AOR = 83; 95%CrI 1.19-2.73), birth interval less than 24 months (AOR = 1.40; 95% CrI 1.20-1.61), increasing maternal BMI (AOR = 0.95; 95% CrI 0.93-0.97), and poorest household wealth status (AOR = 1.78; 95% CrI 1.35-2.30) were predictors of childhood stunting at individual level. Similarly, region and type of toilet facility were predictors of childhood stunting at community level. The current study revealed that both individual and community level factors were predictors of childhood stunting in Ethiopia. Thus, more emphasize should be given by the concerned bodies to intervene the problem stunting by improving maternal education, promotion of girl education, improving the economic status of households, promotion of context-specific child feeding practices, improving maternal nutrition education and counseling, and improving sanitation and hygiene practices.

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
The sampling procedure of the study predictors of stunting among children aged 6–59 months in Ethiopia (n = 8117).
See this image and copyright information in PMC

References

    1. UNICEF. UNICEF Data:Monitoring the situation of Children and women. Malnutrition, 2018. Retrieved from http://data.unicef.org/nutrition/malnutrition.html.
    1. World Bank Group et al. Reaching the global target to reduce stunting: How much will it cost and how can we pay for it? Breastfeeding Med. 2016;11(8):413–415. doi: 10.1089/bfm.2016.0128. - DOI - PubMed
    1. UNICEF. Stop Stunting: Progress Report 2013–2015. Unicef, 2015. Global Reference List of 100 Core Health Indicators (plus health-related SDGs). Geneva: World Health Organization; 2018. Licence: CC BY-NC-SA 3.0 IGO.
    1. UNICEF/WHO/World Bank. Levels and trends in child malnutrition: UNICEF/WHO/World Bank Group Joint Malnutrition Estimates (2018). 10.1016/S0266-6138(96)90067-4.
    1. IFPRI. Global Nutrition Report 2016: From Promise to Impact: Ending Malnutrition by 2030. International Food Policy Research Institute (IFPRI). 2016.