Socio-demographic characteristics of caregivers
Out of the 821 children included for this study, the response rate was 98.9%. Thirty eight children with unverifiable records were excluded and a total of 774 children were included for analysis. Almost all 757 (97.8%) of the respondents as a care giver were mothers of the eligible child and two third 475 (61.4%) of respondents were in the age range of 25-34 years. About, 67% of respondents were from urban kebeles. Pertaining to educational status, majority (46%) had secondary education and above while 22% had no education. As indicated in table 1, from the total study participants 693 (89.5%) were married, 707(91.4%) were orthodox and 88 (11.4%) were government employed. With regard to sex of child, around 368 (47.6%) of children were females.
Table 1: Socio-demographic characters of caregivers in Gondar town, Ethiopia, 2018 [N=774]
Characteristics
|
Total (%)
|
|
|
Caregiver age in years
|
≤24
|
172 (22.2)
|
|
25-34
|
475 (61. 4)
|
|
≥35
|
127 (16.4)
|
|
Marital status
|
Married
|
693(89.5)
|
|
Others
|
81(10.5)
|
|
Religion
|
Orthodox
|
707(91.4)
|
|
Muslim
|
53 (6.8)
|
|
Others
|
14 (1.8)
|
|
Residence
|
Rural
|
252(32.6)
|
|
Urban
|
522(67.4)
|
|
Education
|
No education
|
171(22.1)
|
|
Primary
|
244(31.5)
|
|
Secondary and above
|
359(46.4)
|
|
Sex of child
|
Female
|
368(47.6)
|
|
Male
|
406 (52.4)
|
|
Occupation
|
Government employed
|
88(11.4)
|
|
Others
|
686(88.6)
|
|
Family size
|
<5
|
436 (56.3)
|
|
≥5
|
338(43.7)
|
|
Wealth Index
|
Poor
|
258 (33.3)
|
|
Middle
|
258 (33.3)
|
|
Rich
|
258 (33.3)
|
|
Health service related characteristics of caregivers
Majority 469 (60.6%) of caregivers reported that the mother had four and above ante natal care (ANC) visits for the child included for this study. Regarding place of delivery, only 54(6.9%) of deliveries were at home. Sixty eight percent of respondents reported that the mother of the child had two and more post natal care (PNC) visits. Of the included children for the study, 279 (36.1%) were in the first birth order while 148 (19.1%) reported that the birth order is four and above. Four hundred nighty two (63.6%) of the caregivers took their child to health center for vaccination and 391 (50.5%) of respondents reported that the distance to the vaccination site is less than fifteen minutes from their home [Table 2].
Table 2: Health service related factors of caregivers in Gondar town, Ethiopia, 2018 [N=774]
Variables
|
Total (%)
|
|
|
ANC
|
No
|
61 (7.9)
|
|
1-3
|
244 (31.5)
|
|
≥4
|
469 (60.6)
|
|
Place of delivery
|
Home
|
54 (6.9)
|
|
Health Facility
|
720 (93.1)
|
|
PNC
|
<2
|
243 (31.4)
|
|
≥2
|
531 (68.6)
|
|
Birth order
|
1st
|
279 (36.1)
|
|
2nd-3rd
|
347 (44.8)
|
|
4+
|
148 (19.1)
|
|
Distance to vaccination site
|
<15Minute
|
391 (50.5)
|
|
15-30Minute
|
309 (39.9)
|
|
>30Minute
|
74 (9.6)
|
|
Place of vaccination
|
Hospital
|
130 (16.8)
|
|
HP
|
152 (19.6)
|
|
HC
|
492 (63.6)
|
|
Over all vaccination status of children
Child vaccination card availability during the time of interview was 599 (77.4%) [Figure 1]. Of those caregivers who reported that their child’s vaccination card is available during the time of interview, 551 (91.9%) showed the vaccination cards for the interviewers.
Of the 774 children included for analysis, 498 (64.3%) with 95%CI: (60.9- 67.6%) were fully vaccinated while 247 (31.9%) with 95% CI (28.7- 35.3%) children were fully vaccinated on-time [Figure 1]. The study also indicated that only half of those fully vaccinated children had been fully vaccinated on-time.
Vaccination coverage for specific vaccines
Figure 2 below depicted the vaccination coverage for specific vaccines. Coverage for each specific vaccine was calculated from all children included in this particular study. We found that the proportion of children with full vaccinations decreased from Penta I (95.5%) to Penta III (83.2%) and measles (76.2%) vaccine doses subsequently [Figure2]. The study also indicated that the Pentavalent vaccination drop-out rate was 12.8% and the BCG to measles vaccination dropout rate was 20.1%.
Timely vaccination for specific vaccines
Timeliness for each specific vaccine was calculated from those children vaccinated for that specific vaccine. As depicted in figure 3, timely vaccinations for each vaccine ranged from 62.4% for BCG vaccine to 80.5% for Rota 1 vaccine. The proportion of children who had received early vaccine doses ranged from 3.1% for PCV3 vaccine to 13.6% for measles vaccine. On the other hand, the proportion of children who had received vaccine doses lately ranged from 13.9% for Rota1 vaccine to 37.6% for BCG vaccines [Figure 3].
Attendance to vaccination schedules
Full attendance to vaccination schedules were measured historically by asking the caregivers and objectively measured from vaccination cards and registers. The findings showed that the proportion of full attendance to vaccination schedules measured historically from caregiver’s reports was 693(89.5%). On the other hand, the objective measurement from vaccination cards and registers indicated that proportion of full attendance to vaccination visits was 558 (72.1%).
Reasons for not attending vaccination schedules on-time
The reasons for not attending vaccination schedules were mentioned by those 81 caregivers who reported that their attendance to the vaccination schedules were not complete as scheduled. Among the reasons for not attending vaccination schedules on-time, 34% were due to forgetfulness, 28% being unaware of the schedules and 27% being busy to show up in vaccination schedules [Figure 4].
Bivariable and multivariable logistic regression analysis
The fixed effects and the random intercepts for on-time full vaccination are presented in Table 3. The ICC in the empty model implied that 25.7% of the total variance in on-time full vaccination was attributed to differences between communities [Table 3].
In Model-II only individual level variables were added. In this model the variables age of caregiver, marital status, religion, occupation, family size, number of children, sex of child, caregiver education, birth order, Ante natal care (ANC), place of delivery, Post natal care (PNC) and wealth index were included. With this, marital status, religion, family size, number of children and sex of child were insignificant at the bivariable analysis at P-value of 0.2. Finally, the variables occupation, birth order and place of delivery were statically insignificant at Model-II. The results showed that caregivers education level, household wealth index, antenatal care visits and post natal care visits were significantly associated with on-time full vaccination in Model-II. The ICC in Model-II indicated that, 23.5 % of the variation in on-time full vaccination was attributable to differences across communities. As shown by the PCV, 11.4 % of the variance in on-time vaccination across communities was explained by the individual level characteristics [Table 3].
In Model-III only community level variables were added. In model-III the community level characteristics residence, distance to vaccination site and place of vaccination were included. At the bivariable analysis all the three variables were statistically significant at P-Value of 0.2. In model-III, the variable residence became statistically insignificant. The results in Model-III revealed that place of vaccination and distance to the vaccination site were significantly associated with on-time full vaccination. The ICC in Model-III implied that differences between communities account for about 2.1 % of the variation in on-time full vaccination. In addition, the PCV indicated that 93.9% of the variation in on-time full vaccination between communities was explained by community level characteristics [Table 3].
Model-IV, the final model included both the individual and community level characteristics simultaneously. After controlling for other individual and community level factors, caregivers with age of greater than 35 years were 53% less likely (AOR= 0.469; 95 % CI: 0.253-0.869] to complete their child vaccination on-time as compared to those caregivers aged 25 years and less. The study also indicated that caregivers who had secondary education and above were 2.4 times (AOR = 2.391; 95 % CI: 1.317- 4.343) more likely to complete their child vaccination on-time as compared to those who had no education after controlling for other variables. After holding other factors constant, caregivers from richest households had 2.4 times higher chance of completing their child vaccination on-time (AOR = 2.381; 95 % CI: 1.502-3.773) as compared to caregivers from poorest households [Table 3].
Looking at ANC, children whose mothers had attended four and above ante natal care visits were 2.8 times (AOR = 2.844; 95 % CI: 1.310-6.174) more likely to complete their child vaccination on-time as compared to those children whose mothers had no antenatal care checkups. Keeping other variables constant, children whose mothers had two and more PNC visits were 2 times more likely (AOR =2.054; 95%CI:1.377-3.063) to fully vaccinate their child on-time as compared to their counterparts [Table 3].
Pertaining place of vaccination, those caregivers who vaccinated their child at health posts were 86% (AOR=0.144; 95%CI: 0.048-0.428) less likely to fully vaccinate their child on-time as compared to those who vaccinated their child in hospital. In terms of distance to vaccination site, those caregivers who travelled more than 30 minutes to the vaccination site were 84% (AOR= 0.158; 95%CI: 0.033-0.739) less likely to fully vaccinate their child on-time as compared to those who travelled less than 15 minutes to the vaccination site [Table 3].
As shown by the estimated ICC in model-IV, 2.4% of the variability in on-time full vaccination was attributable to differences between communities. The PCV indicated that, 93.1 % of the variation in on-time full vaccination across communities was explained by both individual and community level factors included in model-IV [Table 3].
Comparison of models
Akakie Information Criterion (AIC) and log likelihood were used to compare the models. The AIC and the log likelihood values for each subsequent models were compared and Model-IV with lowest values of AIC and log likelihood was considered to be the better model [Table 3].
Multicollinearity and model fitness test
Multicollineraity was checked for those variables included in the final model using VIF. Accordingly, the VIF for all predictor variables included in the final model was below 10 indicating that there was no multicollinearity among the predictor variables. Similarly, goodness of fit test for the final model was done using hosmer and lemeshow test. The hosmer and lemeshow test was statically insignificant indicating that the final model fits the data very well (P-value: 0.2792).
Table3: Multilevel regression analysis of factors associated with on-time full vaccination, Gondar town, Ethiopia, 2018
Fixed effects of individual and community level variables
|
Model-I
|
Model-II
AOR [95%CI]
|
Model-III
AOR [95%CI]
|
Model-IV
AOR [95%CI]
|
Age of caregivers
|
≤24 years
|
|
1
|
-
|
1
|
25-34 years
|
|
1.012 [0.669,1.531]
|
-
|
1.031[0.681,1.561]
|
≥35 years
|
|
0.441[0.238,0.813]
|
-
|
0.469[0.253,0.869]
|
Education of caregivers
|
No education
|
|
1
|
-
|
1
|
Primary
|
|
1.901[1.012,3.571]
|
-
|
1.786[0.954,3.343]
|
Secondary and above
|
|
2.587[1.407,4.756]
|
-
|
2.391[1.317,4.343]
|
Wealth Index
|
Poor
|
|
1
|
-
|
1
|
Middle
|
|
1.419[0.915,2.201]
|
-
|
1.494[0.976,2.287]
|
Rich
|
|
2.269[1.419,3.627]
|
-
|
2.381[1.502,3.773]
|
ANC
|
No
|
|
1
|
-
|
1
|
1-3
|
|
1.416[0.627,3.201]
|
-
|
1.404[0.618,3.191]
|
4+
|
|
3.139[1.456,6.764]
|
-
|
2.844[1.310,6.174]
|
PNC
|
<2
|
|
1
|
-
|
1
|
≥2
|
|
2.067[1.373,3.109]
|
-
|
2.054[1.377,3.063]
|
Place of vaccination
|
Hospital
|
|
-
|
1
|
1
|
HP
|
|
-
|
0.103[0.036,0.289]
|
0.144[0.048,0.428]
|
HC
|
|
-
|
0.809[0.511,1.282]
|
1.011[0.612,1.671]
|
Distance to vaccination site (minute)
|
<15 minute
|
|
-
|
1
|
1
|
15-30 minute
|
|
-
|
0.661[0.469,0.933]
|
0.746[0.516,1.080]
|
>30 minute
|
|
-
|
0.155[0.034,0.701]
|
0.158 [0.033,0.739]
|
Random effects
Random effect
|
Model-I
|
Model-II
|
Model-III
|
Model-IV
|
Community variance (SE)
|
1.14 (0.62)
|
1.01 (.59)
|
0.069 (0.08)
|
0.079 (0.093)
|
ICC (%)
|
25.7%
|
23.5%
|
2.1%
|
2.4%
|
PCV (%)
|
Ref
|
11.4%
|
93.9%
|
93.1%
|
Model comparison statistics
Model comparison
|
Model-I
|
Model-II
|
Model-III
|
Model-IV
|
Log likelihood
|
-447.77844
|
-407.19174
|
-432.57621
|
-393.93011
|
AIC
|
899.5569
|
836.3835
|
877.1524
|
817.8602
|