Improving the immunization and health status of children in the Women, Infants, and Children (WIC) Program.
Maintaining enrollment in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) and continued exposure of these children to immunization-promoting and nutritional benefits within the program is essential to improve the health status of this vulnerable population. Logistic regression was used to determine characteristics of 2 groups of children: those who dropped out of the program despite being eligible and those who remained in the program but were underimmunized. Of over 20,000 children 19-35 months old, 49% had participated in WIC but only 50% were still enrolled. Factors most strongly associated with dropping out of the program were older age of child; white, black, or American Indian race; living in an urban or suburban area; higher socioeconomic status but still eligible for the program; having only 1 child at home; and having mothers who were unmarried or less than 30 years old (p<0.05). Among current participants, factors most strongly associated with under-vaccination included younger age of the child; black or Asian race; moving from another state since birth; mother with less than a high-school education; and having 2 or more children under 18 years old living in the household (p<0.05). Routinely collected child/family information can be used to target outreach and immunization-promoting interventions toward children most likely to drop out of the program or to be underimmunized.
Shefer
Abigail
A
Health Services Research and Evaluation Branch, National Immunization Program, Centers for Disease Control and Prevention, USA.
Smith
Philip J
PJ
D000385:Aid to Families with Dependent Children / Q000706:statistics & numerical data*; D002662:Child Health Services / Q000191:economics / Q000706:statistics & numerical data*; D002669:Child Welfare; D002675:Child, Preschool; D019538:Health Care Surveys; D006801:Humans; D017589:Immunization Programs / Q000191:economics / Q000706:statistics & numerical data*; D007223:Infant; D016015:Logistic Models; D008913:Minority Groups / Q000706:statistics & numerical data; D010352:Patient Dropouts / Q000706:statistics & numerical data*; D011203:Poverty / Q000208:ethnology / Q000706:statistics & numerical data; D012307:Risk Factors; D012959:Socioeconomic Factors; D014481:United States