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Predictors of full vaccination among children aged 12-23months in Zambia- A quantitative secondary analysis of the 2018 Zambia Demographic and Health Survey.

Introduction Zambia is aiming to achieve the World Health Organisation (WHO) target of 90% vaccination coverage among children under five years. The 2018 Zambia Demographic and Health Survey (ZDHS) established that Copperbelt province had the highest vaccination coverage at 83%. However, Luapula province was lowest at 67%. The aim of this study was to identify predictors of full vaccination among children aged 12-23 months in Zambia. Methods A cross-sectional design was used to draw information about individual, relationship, community and societal predictors of full vaccination among children aged 12-23 months. Data was collected using a structured closed question format interview administered to mothers from the 2018 ZDHS. The information collected was on background characteristics such as age and education of mothers with vaccinations of their children. chi-square test was used for associations and binary logistic regression was used for multivariable analysis. Results Children born from mothers 20-24 years were most vaccinated 27.4%. Logistic regression showed higher education 10.55 AOR; 95% CI, 1.27-87.53, ability to read whole sentence 1.59 AOR; 95% CI, 1.07-2.35, currently working 1.37 AOR; 95% CI, 1.01-1.86, owning a mobile telephone 1.44 AOR; 95% CI, 1.00-2.34, residing in rural area 1.46 AOR; 95% CI, 1.67-3.62, watching television daily 1.92 AOR; 95% CI, 1.15-3.21 and belonging to a middle category 1.91 AOR; 95% CI, 1.15-3.15 increased odds of full vaccination. Conclusion This study has shown that predictors of full vaccination cut across all the four levels of the Socio Ecological Model (SEM) hence the need for a holistic approach.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-487600
Date January 2022
CreatorsMafulauzi, Evaristo
PublisherUppsala universitet, Institutionen för kvinnors och barns hälsa
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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