{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T01:13:52Z","timestamp":1790212432477,"version":"4.1.0"},"reference-count":25,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T00:00:00Z","timestamp":1766016000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The National Social Science Fund of China","award":["21039"],"award-info":[{"award-number":["21039"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Vaccines"],"abstract":"<jats:p>Background: Childhood immunization is one of the most effective public health strategies for reducing morbidity and mortality from vaccine-preventable diseases. Although overall vaccination coverage in the United States remains high, disparities persist across socioeconomic and healthcare access groups. Understanding these disparities is particularly important in the post-COVID-19 era, when increased vaccine hesitancy may threaten progress in maintaining equitable coverage. Materials and Methods: We analyzed data from the National Immunization Survey\u2013Child (NIS-Child), focusing on U.S. children aged 19\u201335 months in 2023, corresponding to cohorts reaching this age during or after the COVID-19 pandemic. The primary outcome was receipt of the up-to-date combined 7-vaccine series (4:3:1:3:3:1:3: \u22654 doses of DTaP, \u22653 doses of polio, \u22651 dose of measles-containing vaccine, full Hib series, \u22653 doses of hepatitis B, \u22651 dose of varicella, and \u22653 doses of PCV). Logistic regression models were used to estimate associations between vaccination coverage and key explanatory variables: household income-to-poverty ratio, maternal education, health insurance type, and provider facility type, controlling for demographic and regional covariates. Disparities were quantified using concentration indices (CIs). Results: Among children in the analytic sample, overall coverage for the 7-vaccine series was only 78.5%. Nonetheless, disparities were evident. Children from households with lower income-to-poverty ratios (&lt;1 \u00d7 FPL: OR = 0.44, 95% CI = 0.37\u20130.53; 100\u2013200%: OR = 0.66, 95% CI = 0.56\u20130.79), those covered by Medicaid (OR = 0.54, 95% CI = 0.45\u20130.64), other insurance (OR = 0.48, 95% CI = 0.37\u20130.61), or uninsured (OR = 0.27, 95% CI = 0.18\u20130.42), and those whose mothers had lower educational attainment (&lt;12 years: OR = 0.35, 95% CI = 0.28\u20130.44) had significantly lower odds of being up-to-date. Similar associations were observed across specific vaccines. Unadjusted CIs for income-to-poverty ratio (0.04, p &lt; 0.01), maternal education (0.04, p &lt; 0.01), health insurance (0.03, p &lt; 0.01), and provider type (0.03, p &lt; 0.01) decreased but remained statistically significant after adjustment (0.02, 0.02, 0.01, and 0.02, respectively; all p &lt; 0.01). No significant disparities were found by census region or race\/ethnicity. Discussion: Despite relatively high overall vaccination coverage among U.S. children born during and after the COVID-19 pandemic, disparities by socioeconomic and healthcare access factors persisted. However, the absolute magnitude of these disparities was very small (concentration indices \u2264 0.04). These findings suggest that while inequities remain statistically measurable, their scale is limited in absolute terms. Targeted efforts to address income, insurance, maternal education, and provider-related barriers will be important to sustain equitable immunization coverage in the post-pandemic era.<\/jats:p>","DOI":"10.3390\/vaccines13121256","type":"journal-article","created":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T16:42:05Z","timestamp":1766076125000},"page":"1256","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Socioeconomic Disparities in Childhood Vaccination Coverage in the United States: Evidence from a Post-COVID-19 Birth Cohort"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0879-1057","authenticated-orcid":false,"given":"Xiaoyang","family":"Lv","sequence":"first","affiliation":[{"name":"School of Public Health, Peking University, Beijing 100191, China"},{"name":"China Center for Health Development Studies, Peking University, Beijing 100191, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antong","family":"Long","sequence":"additional","affiliation":[{"name":"School of Public Health, Peking University, Beijing 100191, China"},{"name":"China Center for Health Development Studies, Peking University, Beijing 100191, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yansheng","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Public Health, Peking University, Beijing 100191, China"},{"name":"China Center for Health Development Studies, Peking University, Beijing 100191, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hai","family":"Fang","sequence":"additional","affiliation":[{"name":"China Center for Health Development Studies, Peking University, Beijing 100191, China"},{"name":"Key Laboratory of Health System Reform and Governance (Peking University), National Health Commission, Beijing 100191, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,18]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (WHO) (2025, September 22). 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