Parental attitudes and childhood immunization.

Strobino, Donna M.; Hughart, Nancy; Guyer, Bernard

doi:10.2105/ajph.89.9.1442-b

Cited by 25 publications

(38 citation statements)

References 12 publications

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“…These factors are each associated with reduced risk of vaccination delay, and therefore the bias associated with excluding the subpopulation of children who do not have written vaccination records is likely to result in an understatement of the reported risk factors for vaccination delay. [7][8][9][10][11]14,26,35 Although more current NHIS data have been released subsequent to the completion of our study, we believe that our conclusions regarding the improved sensitivity of risk models based upon delays in age-appropriate vaccination would be unlikely to change using more recent data. However, recently released public use data sets now offer the opportunity to consider variations in the risk of vaccination delays from additional perspectives, such as by state and for additional vaccination doses and series, using providervalidated data.…”

Section: Discussionmentioning

confidence: 99%

Risk Factors for Delay in Age-Appropriate Vaccination

2004

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SYNOPSISObjective. To estimate the risk factors of children experiencing delay in ageappropriate 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)(1993)(1994)(1995)(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 (pՅ0.05).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.

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Section: Discussionmentioning

confidence: 99%

Risk Factors for Delay in Age-Appropriate Vaccination

2004

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“…20 Even so, it is acknowledged that cultural factors and individual behavior are very complex aspects and that the effect of variables, such as social preferences and competing needs, require more extensive analysis. Several studies on poor urban populations have also shown that sociodemographic factors and individual characteristics of the population, including their attitudes and beliefs, did not fully explain their vaccination use.…”

Section: Discussionmentioning

confidence: 99%

Determinants of vaccination after the Colombian health system reform

et al. 2005

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Descritores Vacinação. Programas de imunização. Acesso aos serviços de saúde.Reforma do setor saúde. Colômbia. Abstract ObjectiveTo assess the effects of individual, household and healthcare system factors on poor children's use of vaccination after the reform of the Colombian health system. Methods A household survey was carried out in a random sample of insured poor population in Bogota, in 1999. The conceptual and analytical framework was based on the Andersen's Behavioral Model of Health Services Utilization. It considers two units of analysis for studying vaccination use and its determinants: the insured poor population, including the children and their families characteristics; and the health care system. Statistical analysis were carried out by chi-square test with 95% confidence intervals, multivariate regression models and Cronbach's alpha coefficient. ResultsThe logistic regression analysis showed that vaccination use was related not only to population characteristics such as family size (OR=4.3), living area (OR=1.7), child's age (OR=0.7) and head-of-household's years of schooling (OR=0.5), but also strongly related to health care system features, such as having a regular health provider (OR=6.0) and information on providers' schedules and requirements for obtaining care services (OR=2.1). ConclusionsThe low vaccination use and the relevant relationships to health care delivery systems characteristics show that there are barriers in the healthcare system, which should be assessed and eliminated. Non-availability of regular healthcare and deficient information to the population are factors that can limit service utilization.

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“…10,16,41 In fact, there is some evidence that parents of these children are less likely to be concerned about vaccine safety or efficacy than parents of nonpoor or white children. 42 Similarly, there is little evidence that provider bias or ineffectiveness account for these disparities; in fact, some data suggest that providers serving high-risk populations are more aggressive in their immunization practices than providers serving populations of higher socioeconomic status. [43][44][45] The major cause of lower immunization rates 16,46 seems to be "the immunization information gap" 47 -a combination of patient factors such as barriers to care, missed appointments, and unfamiliarity with the vaccination schedule; provider factors including failure to identify children who are behind and to apply effective interventions such as reminder and recall; and health care system factors including lack of community-wide immunization registries or interventions, access barriers, and cost issues.…”

Section: Commentmentioning

confidence: 99%

Reducing Geographic, Racial, and Ethnic Disparities in Childhood Immunization Rates by Using Reminder/Recall Interventions in Urban Primary Care Practices

et al. 2002

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ABSTRACT.Context. An overarching national health goal of Healthy People 2010 is to eliminate disparities in leading health care indicators including immunizations. Disparities in US childhood immunization rates persist, with inner-city, black, and Hispanic children having lower rates. Although practice or clinic-based interventions, such as patient reminder/recall systems, have been found to improve immunization rates in specific settings, there is little evidence that those site-based interventions can reduce disparities in immunization rates at the community level.Objective. To assess the effect of a community-wide reminder, recall, and outreach (RRO) system for childhood immunizations on known disparities in immunization rates between inner-city versus suburban populations and among white, black, and Hispanic children within an entire county.Setting. Monroe County, New York (birth cohort: 10 000, total population: 750 000), which includes the city of Rochester. Three geographic regions within the county were compared: the inner city of Rochester, which contains the greatest concentration of poverty (among 2-yearold children, 64% have Medicaid); the rest of the city of Rochester (38% have Medicaid); and the suburbs of the county (8% have Medicaid).Interventions. An RRO system was implemented in 8 city practices in 1995 (covering 64% of inner-city children) and was expanded to 10 city practices by 1999 (covering 74% of inner-city children, 61% of rest-of-city children, and 9% of suburban children). The RRO intervention involved lay community-based outreach workers who were assigned to city practices to track immunization rates of all 0-to 2-year-olds, and to provide a staged intervention with increasing intensity depending on the degree to which children were behind in immunizations (tracking for all children, mail, or telephone reminders for most children, assistance with transportation or scheduling for some children, and home visits for 5% of children who were most behind in immunizations and who faced complex barriers).Study Participants. Three separate cohorts of 0-to 2-year-old children were assessed-those residing in the county in 1993, 1996, and 1999.Study Design. Immunization rates were measured for each geographic region in Monroe County at 3 time periods: before the implementation of a systematic RRO system (1993), during early phases of implementation of the RRO system (1996), and after implementation of the RRO system in 10 city practices (1999). Immunization rates were compared for children living in the 3 geographic regions, and for white, black, and Hispanic children.Immunization rates were measured by the same methodology in each of the 3 time periods. A denominator of children was obtained by merging patient lists from the practice files of most pediatric and family medicine practices in the county (covering 85% to 89% of county children). A random sample of children (>500 from the suburbs and >1200 from the city for each sampling period) was then selected for medical chart review at practices...

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Parental attitudes and childhood immunization.

Cited by 25 publications

References 12 publications

Risk Factors for Delay in Age-Appropriate Vaccination

Risk Factors for Delay in Age-Appropriate Vaccination

Determinants of vaccination after the Colombian health system reform

Reducing Geographic, Racial, and Ethnic Disparities in Childhood Immunization Rates by Using Reminder/Recall Interventions in Urban Primary Care Practices

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