Multinomial logistic regression analysis of the determinants of anaemia severity among children aged 6–59 months in Ghana: new evidence from the 2019 Malaria Indicator Survey

Abstract

Background Anaemia among children under age five is a major public health issue. Although anaemia prevalence is declining in Ghana, the severity among anaemic children is worsening. This study aims to investigate the determinants of anaemia severity among children aged 6 to 59 months in Ghana. Method The study utilized a weighted sample of 1,258 children with anaemia with data obtained from the 2019 Ghana Malaria Indicator Survey. The predictor variables included maternal, household child and health system characteristics. SPSS version. At the multivariate level, three different multinomial logistic models were run with selected predictor variables. All tests were conducted at the 95% confidence level. Results The overall anaemia prevalence among children under age five was 43.5%. Of these, 2.6% were severely anaemic, 48.5% were moderately anaemic, and 48.9% had mild anaemia. The multinomial analysis showed that maternal, household, child and health system factors significantly predicted anaemia levels among anaemic children. The results indicate that a lower likelihood of anaemia severity is likely to be found among children whose mothers belong to Pentecostal/Charismatic faith (AOR = 0.18-model I; AOR = 0.15-model III) and children who tested negative for malaria (AOR = 0.28-model II and III). Again, a higher probability of anaemia severity was found among anaemic children whose mothers were not aware of NHIS coverage of malaria (AOR = 2.41-model II, AOR = 2.60-model III). With regard to moderate anaemia level, children who belong to the poorest, poorer and middle household wealth index had a higher likelihood of being moderately anaemic compared to those in rich households. Similarly, anaemic children who were less than 12 months old (AOR = 2.21-model II, AOR = 2.29-model III) and those between the ages of 1–2 years (AOR = 1.84-model II, AOR = 1.83-model III) were more likely to have moderate anaemia levels. Conclusion The study findings show the importance of understanding the interrelation among different factors that influence anaemia severity among children under age five as critical in developing strategies and programmes aimed at addressing childhood anaemia.

Anemia prevalence and its predictors among children under‐five years in Ghana. A multilevel analysis of the cross‐sectional 2019 Ghana Malaria Indicator Survey

“…Our modeling approach is an improvement on previous studies that examined factors associated with anemia among children under‐fives in Ghana and ignored the hierarchical structure of the datasets used in their study. For example, Klu et al, 44 , 45 used data from the 2019 Ghana Malaria Indicator Survey where children are nested within communities (cluster) but did not consider the clustering of observations on these children from the same community, which could lead to spurious statistical significance and its associated incorrect statistical inference and misleading policy decisions. 46 The population‐level nature of the data allows making inferences to cover all children under‐fives in Ghana and in other similar settings.…”

The influence of socioeconomic and demographic factors on rural-urban disparities in infant mortality in Kakamega Central Sub-County, Kakamega County, Kenya

“…Inferential analysis engaged multinomial logistic regression modelling at univariate (Models 1 and 2) and multivariate (Model 3) analytical levels. Multinomial logistic regression has been used in other related studies (Omedi & Amwoliza, 2015; Ari, 2016; Al-Neyazy, 2021; Sakala & Kombe, 2022; Klu et al, 2023). In model 1, multinomial logistic regression analysis was conducted to analyse data on the influence of level of education qualification of the mother and maternal occupation on the death of infants in rural and urban areas.…”