A multi-year analysis of trends in vaccination coverage, associated factors and effect on child growth in Kenya

Abstract

Vaccinations are one of the most cost-effective strategies for preventing diseases and achieving universal health coverage. However, incomplete vaccinations pose a significant challenge in Kenya, potentially leading to the resurgence of vaccine-preventable diseases (VPDs) and adverse growth outcomes in children. Key indicators of incomplete vaccination, including non-vaccination, under-vaccination, and Missed Opportunities for Vaccination (MOV), remain areas of concern. Despite the availability of data from the Kenya Demographic and Health Survey (KDHS) on levels and certain determinants of non-vaccination, comprehensive national data on the trends and determinants of non/under-vaccination and MOV are lacking. Addressing this gap in evidence, this study utilized nationally-representative data to analyze multi-year trends in vaccination coverage, associated factors, and their impact on child growth in Kenya from 2003 to 2014. The primary objectives were to examine trends in non-vaccination, under-vaccination, and MOV among children aged 0-23 months, identify demographic and socio-economic factors influencing these trends, explore the role of health system factors, and assess the effects of non-vaccination, under-vaccination, and MOV on child growth rates. Employing an explanatory sequential mixed-methods research design, the study comprised two phases. The first phase involved a quantitative analysis of child immunization datasets from the KDHS cross-sectional surveys conducted in 2003, 2008/09, and 2014. A total of 11,959 children aged 0-23 months were included in the analysis. Study specific data abstraction tools were used to collect children immunization data and their demographic and socio-economic information. Intervening variables such as non/under-vaccination and MOV were evaluated. Child growth outcomes were assessed using indicators of stunting, wasting, and underweight. Data coding and recoding were done using Stata (version 14; College Station, TX: StataCorp LP). Statistical analyses included the Cochrane-Armitage trend test to determine trends in non/under-vaccination and MOV proportions, multivariable logistic regression models to explore the influence of demographic and socio-economic factors, and mixed-effect multi-level linear regression modeling to assess the impact of vaccination status on growth outcomes. The second phase involved qualitative interviews with policymakers at the national and county levels to provide contextual insights. NVIVO software (QSR International Pty Ltd. Version 12, 2018) was used for coding and analysis. Thematic content analysis was employed, and findings were triangulated with quantitative results to identify areas of convergence and divergence. During the study period, non-vaccination decreased by 10%, under-vaccination remained relatively stable, and MOV increased by ~15%.Maternal education, age, marital status, region and family size were identified as significant influencers of vaccination status. Health system challenges such as negative staff attitudes, inadequate staffing, storage facility breakdowns and vaccine stock-outs hindered childhood vaccination services. In the mixed-effect multi-level linear regression modeling, MOV exhibited negative coefficients on Weight for Age Z-score (WAZ) and Weight for Height Z-score (WHZ) in 2003 and 2014, with coefficients of -0.25 (p < 0.001) and -0.12 (p = 0.013), respectively. Under-vaccination showed negative effects on WAZ in 2008/09 and 2014, as well as on WHZ in all three surveys, with coefficients of -1.61 (p < 0.001) for 2003, -0.40 (p = 0.022) for 2008/09, and -0.23 (p < 0.001) for 2014. Non-vaccination yielded mixed findings, with both significant negative and positive coefficients observed across the years. This comprehensive study contributes valuable insights into the relationship between vaccination status and child growth outcomes, enhancing our understanding of the implications of vaccination programs on public health in Kenya.