Vaccination assessments using the Demographic and Health Survey, 2005–2018: a scoping review. Issue 12 (2nd December 2020)

• Record Type: Journal Article
• Authors: Shenton, Luke M; Wagner, Abram L; Ji, Mengdi; Carlson, Bradley F; Boulton, Matthew L
• Is Part Of: BMJ open. Volume 10:Issue 12(2020)
• Publication Date: 2020-12-02
• Subjects: paediatric infectious disease & immunisation -- public health -- international health services; Medicine -- Research -- Periodicals; 610.72
• DOI: 10.1136/bmjopen-2020-039693
• Languages: English
• ISSNs: 2044-6055

Abstract

Abstract : Objective: To characterise studies which have used Demographic and Health Survey (DHS) datasets to evaluate vaccination status. Design: Scoping review. Data sources: Electronic databases including PubMed, EBSCOhost and POPLINE, from 2005 to 2018. Study selection: All English studies with vaccination status as the outcome and the use of DHS data. Data extraction: Studies were selected using a predetermined list of eligibility criteria and data were extracted independently by two authors. Data related to the study population, the outcome of interest (vaccination) and commonly seen predictors were extracted. Results: A total of 125 articles were identified for inclusion in the review. The number of countries covered by individual studies varied widely (1–86), with the most published papers using data from India, Nigeria, Pakistan and Ethiopia. Many different definitions of full vaccination were used although the majority used a traditional schedule recommended in the WHO's Expanded Programme on Immunisation. We found studies analysed a wide variety of predictors, but the most common were maternal education, wealth, urbanicity and child's sex. Most commonly reported predictors had consistent relationships with the vaccination outcome, outside of sibling composition. Conclusions: Researchers make frequent use of the DHS dataset to describe vaccination patterns within one or more countries. A clearer idea of past use of DHS can inform the development of more rigorous studies in the future. Researchers should carefully consider whether a variable needs to be included in the multivariable model, or if there are mediating relationships across predictor variables.