Comprehensive Childhood Vaccination and Its Determinants: Insights from the Indonesia Family Life Survey (IFLS)

Journal of Infection and Public Health(2024)

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摘要
Background: Immunization is the most effective intervention for reducing morbidity and mortality rates associated with vaccine-preventable diseases. Despite the Indonesian government's inclusion of several childhood vaccinations in the national immunization program (NIP), the number of unvaccinated or partially vaccinated children remains high. This observational study aimed to determine the completeness of childhood immunization and the factors influencing it in Indonesia. Methods: Data were extracted from the fifth wave of the Indonesia Family Life Survey (IFLS). The sample (n = 16,236) consists of children residing in 13 provinces, representing over 80% of Indonesia's population. The difference between groups was tested using the chi-square test. Logistic regression was performed to identify the variables associated with the completeness of basic immunization. Immunization is categorized as complete when children have received all the mandatory vaccines recommended by the Ministry of Health. We examined and compared the results using complete case analysis, inverse probability weighting, and multiple imputations. Results: The highest percentages of complete vaccinations were polio, tuberculosis, and DPT. Children who live in Sumatera and Kalimantan were more likely to be fully immunized, with ORs of 0.6 (95%CI 0.48–0.74) and 0.54 (0.37–0.80), respectively. Children who live in urban areas, have mothers who received the tetanus vaccine during pregnancy, have mothers with a higher level of education and health insurance, have fathers aged 41–50, and live with a large number of family members were more likely to be fully immunized (p < 0.05). Conclusion: Socioeconomic determinants were strongly correlated with the completeness of childhood vaccination in Indonesia.
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关键词
childhood vaccination,immunization,vaccine,vaccine hesitancy,inverse probability weighting,multiple imputation
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