Multilevel analysis of predictors of multiple indicators of childhood vaccination in Nigeria

PLoS One. 2022 May 25;17(5):e0269066. doi: 10.1371/journal.pone.0269066. eCollection 2022.

Abstract

Background: Substantial inequalities exist in childhood vaccination coverage levels. To increase vaccine uptake, factors that predict vaccination coverage in children should be identified and addressed.

Methods: Using data from the 2018 Nigeria Demographic and Health Survey and geospatial data sets, we fitted Bayesian multilevel binomial and multinomial logistic regression models to analyse independent predictors of three vaccination outcomes: receipt of the first dose of Pentavalent vaccine (containing diphtheria-tetanus-pertussis, Hemophilus influenzae type B and Hepatitis B vaccines) (PENTA1) (n = 6059) and receipt of the third dose having received the first (PENTA3/1) (n = 3937) in children aged 12-23 months, and receipt of measles vaccine (MV) (n = 11839) among children aged 12-35 months.

Results: Factors associated with vaccination were broadly similar for documented versus recall evidence of vaccination. Based on any evidence of vaccination, we found that health card/document ownership, receipt of vitamin A and maternal educational level were significantly associated with each outcome. Although the coverage of each vaccine dose was higher in urban than rural areas, urban residence was not significant in multivariable analyses that included travel time. Indicators relating to socio-economic status, as well as ethnic group, skilled birth attendance, lower travel time to the nearest health facility and problems seeking health care were significantly associated with both PENTA1 and MV. Maternal religion was related to PENTA1 and PENTA3/1 and maternal age related to MV and PENTA3/1; other significant variables were associated with one outcome each. Substantial residual community level variances in different strata were observed in the fitted models for each outcome.

Conclusion: Our analysis has highlighted socio-demographic and health care access factors that affect not only beginning but completing the vaccination series in Nigeria. Other factors not measured by the DHS such as health service quality and community attitudes should also be investigated and addressed to tackle inequities in coverage.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bayes Theorem
  • Child
  • Hepatitis B Vaccines
  • Humans
  • Immunization Programs*
  • Infant
  • Measles Vaccine
  • Multilevel Analysis
  • Nigeria
  • Vaccination*

Substances

  • Hepatitis B Vaccines
  • Measles Vaccine

Grants and funding

This work was supported by funding from the Bill and Melinda Gates Foundation (Investment ID INV-003287). CEU and AJT received the grant. The funder did not play any role in the study design, data collection, analysis and interpretation of data, the report writing, and the decision to submit the manuscript for publication.