Inequities in Childhood Vaccination Coverage in Zhejiang, Province

Evidence from a Decomposition Analysis on Two-Round Surveys

Datos Bibliográficos

ID15460418
AutoresYu Hu (0000-0001-8388-0696, Zhejiang Center for Disease Control and Prevention, autor de correspondencia), Hui Liang (0000-0003-1341-6980, Zhejiang Center for Disease Control and Prevention), Ying Wang (0000-0003-3126-1134, Zhejiang Center for Disease Control and Prevention), Yaping Chen (0000-0002-7502-1848, Zhejiang Center for Disease Control and Prevention)
Año2018
Volumen15
Número9
Páginas2000-2000
Fecha de publicación2018-09-13
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaInternational Journal of Environmental Research and Public Health (JOURNAL)
Identificadores de la revistaISSN: 1661-7827 • E-ISSN: 1660-4601
EditorialMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph15092000
PMID30217080
OpenAlexW2891889437
IdiomaEN
Citas recibidas5
Referencias citadas33

Objective : The objectives of this study were to determine the degree and risk factors of the inequity in the childhood coverage of full primary immunization (FPI) in Zhejiang province. Method : We used data from two rounds of vaccination coverage surveys among children aged 24−35 months conducted in 2014 and 2017, respectively. The household income per month was used as an index of socioeconomic status for the inequality analysis. The concentration index (CI) was used to quantify the degree of inequality, and the decomposition approach was applied to quantify the contributions from demographic factors to inequality in the coverage of FPI. Results : The coverage rates of FPI were 80.6%, with a CI value of 0.12028 for the 2014 survey, while the coverage rates of FPI were 85.2%, with a CI value of 0.10129 for the 2017 survey. The results of decomposition analysis suggested that 68.2% and 67.1% of the socioeconomic inequality in the coverage of FPI could be explained by the mother's education level for the 2014 and 2017 survey, respectively. Other risk factors including birth order, ethnic group, mother's age, maternal employment status, residence, immigration status, GDP per-capita, and the percentage of the total health spending allocated to public health could also explain this inequality. Conclusion : The socioeconomic inequity in the coverage of FPI still remained, although this gap was reduced between 2014 and 2017. Policy recommendations for health interventions on reducing the inequality in the coverage of FPI should be focused on eliminating poverty and women's illiteracy

Economic growth · Economics · Environmental health · Geography · Household income · Inequality · Per capita · Population · Poverty · Psychological intervention · Residence · Socioeconomic status · Sociology · Demography · Global Maternal and Child Health · Healthcare Systems and Reforms · Mathematics · Medicine · Vaccine Coverage and Hesitancy