Identifying factors associated with child malnutrition in Ghana: a cross-sectional study using Bayesian multilevel ordinal logistic regression approach

e075723.full.pdf

Dublin Core

Title

Identifying factors associated with child malnutrition in Ghana: a cross-sectional study using Bayesian multilevel ordinal logistic regression approach

Creator

Wahab Abdul Iddrisu, Opoku Gyabaah

Description

Objective
In developing countries, malnutrition is a noteworthy concern related to the well-being of people, and this study aimed to determine the factors that affect malnutrition among children below 5 years in Ghana.
Design
The study used a secondary data source, specifically the Ghanaian Multiple Indicator Cluster Survey Six (MICS 6), which was conducted by the Ghana Statistical Service in 2017–2018. The MICS data are hierarchical, as children are categorised within households, and households are further grouped within a higher cluster, violating the independence assumption that must be addressed in the analyses. This study used a Bayesian multilevel ordinal logistic regression to model, identify and analyse the factors linked to child malnutrition in Ghana.
Setting
The setting of the study was the household level across the previous 10 administrative regions in Ghana.
Participants
Data for 8875 children …

Publisher

British Medical Journal Publishing Group

Date

2023

Source

https://scholar.google.com/citations?view_op=view_citation&hl=en&user=ECTxVnYAAAAJ&citation_for_view=ECTxVnYAAAAJ:9yKSN-GCB0IC

Language

English