*3.2. Factors Associated with Incomplete General Immunization Coverage*

The binary logistic regression model was adjusted for the child's sex, type of community, housing zone, mesoregion, number of people in the house, and health professional visits in the last year. These variables had a *p*-value of less than 0.25 in the bivariate analysis. Based on the multiple analysis, it was observed that the odds of an incomplete vaccination schedule were higher in children who had not received a visit from a health professional in the last year (AOR: 1.96; 95%CI: 1.03–3.73) compared to those who had received such visits (Table 4).

**Table 4.** Factors associated with incomplete general vaccination coverage for the first year. Goiás, Brazil, 2015–2017.



**Table 4.** *Cont*.

Note: Incomplete and complete vaccination coverage is presented as *n* (%), where *n* is the number of observations in the sample and % is the percentage weighted by the complex sampling design. AOR: Adjusted Odds Ratio; 95.0%CI: 95% Confidence Interval; OR: Odds Ratio. \* Binary logistic regression model adjusted for child's gender, type of community, housing zone, mesoregion, number of people in the house, and health professional visit in the last year.
