Risk Factors for Delay in Age-Appropriate Vaccination

• Published in: Public health reports (1974) 2004-03, Vol.119 (2), p.144-155
• Main Authors: Dombkowski, Kevin J., Lantz, Paula M., Freed, Gary L.
• Format: Article
• Language: English
• Subjects: Age; Age Factors; Biological and medical sciences; Child; Child health; Child health services; Child, Preschool; Children; Children & youth; Diphtheria-Tetanus-Pertussis Vaccine - administration & dosage; Education; Family Characteristics; Female; General aspects; Health conditions; Health insurance; Humans; Immunization; Immunization Programs; Immunization Schedule; Insurance, Health; Logistic Models; Male; Measles-Mumps-Rubella Vaccine - administration & dosage; Medicaid; Medical sciences; Miscellaneous; National health insurance; Odds Ratio; Parents; Pediatrics; Poliovirus Vaccines - administration & dosage; Predisposing factors; Public health; Public health. Hygiene; Public health. Hygiene-occupational medicine; Risk; Risk Factors; Statistics; Telephone; Time Factors; United States; Vaccination; Vaccination and vaccines; Vaccines
• ISSN: 0033-3549; 1468-2877
• DOI: 10.1177/003335490411900207

Objective: To estimate the risk factors of children experiencing delay in age-appropriate vaccination using a nationally representative population of children, and to compare risk factors for vaccination delay with those based on up-to-date vaccination status models. Methods: The authors compared predictors of delay in age-appropriate vaccination with those for children who were not up-to-date, using a nationally representative sample of children from five years of pooled data (1992-1996) from the National Health Interview Survey (NHIS) Immunization Supplement. Duration of delay was calculated for the DTP4, Polio3, MMR1 doses and 4:3:1 series using age-appropriate vaccination standards; up-to-date status (i.e., whether or not a dose was received) was also determined. Adjusted odds ratios were estimated using multivariate logistic regression for models of vaccination delay and up-to-date vaccination status. Results: Absence of a two-parent household, large family size, parental education, Medicaid enrollment, absence of a usual provider, no insurance coverage, and households without a telephone were significantly related to increased odds of a child experiencing vaccination delay (p≤0.05). Conclusions: Many of the risk factors observed in models of vaccination delay were not found to be significant in risk models based upon up-to-date status. Consequently, risk models of delays in age-appropriate vaccination may foster identification of children at increased risk for inadequate vaccination. Populations at increased risk of inadequate vaccination can be more clearly identified through risk models of delays in age-appropriate vaccination.