Socio-demographic characteristics of respondents
The total numbers of married and/or sexually active fecund women included for the analysis were 8710 when it is weighted 9125. The mean (SD) ages of respondents were 29.7 and 7.47 years respectively. Almost two-thirds (58.80) of women were not formally educated. Coming to the place of residence, 7614(83.43) women were rural dwellers and 3,782(41.44) women were Orthodox followers (Table1).
Individual and community-level factors associated with unmet need for contraception (Fixed Effects)
After adjusting for individual and community-level factors (model 3) age of women, the total numbers of living children, a wealth of household, religion, married more than once and region were found to have a statistically significant association with unmet need for contraception.
Those women whose ages between 45-49 years were 2.3 times more likely to have an unmet need for contraception than those ages between 15-19 years [AOR=2.25, 95% CI: (1.34, 3.79)]. The odds of unmet need for women who had greater than or equal to three living children were, almost 1.9 times higher than those who had less than three children [AOR=1.87, 95 % CI: (1.40, 2.49)]. Those women who belong to the richer household were 27% less likely to have an unmet need for contraceptive as compared to the poorest [AOR=0.73, 95% CI: (0.54, 0.97)]. The odds of unmet need for contraceptive for women who follow Muslim were 1.4 times more likely then compare to Orthodox followers [AOR=1.37, 95% CI: (1.02, 1.83)]. Those women who married more than once were 1.3 times more likely to have an unmet need for contraceptive than married once [AOR=1.31, 95 % CI: (1.06, 1.62)]. Lastly, those women who belong to the Somali region were 66% less likely to have an unmet need for contraceptive than Addis Ababa [AOR=0.34, 95% CI: (0.19, 0.61)] (Table2).
Random effect (a measure of variation)
The results of multilevel logistic regression for random effects showed that there was a significant variation in the unmet need for contraception across the clusters (Table3). The Intra-cluster correlation coefficients showed that 12.74% of the variation in unmet need for contraceptives was related to community-level factors. The full model also showed that there is a statistically significant variation in unmet need to contraceptive across communities or clusters. About 33.33% of unmet need to contraceptives in clusters was explained in the full model. Besides, the MOR confirmed that the unmet need for contraceptives was attributed to community-level factors. The MOR for unmet need for contraceptive was 1.79 in the empty model which indicated that there was variation between communities (clustering) (1.79 times higher than the reference (MOR = 1)). The unexplained community variation in unmet need for contraceptives decreased to MOR of 1.46 when all factors were added to the model. This showed that when all factors are considered, the effects of clustering are still statistically significant in the full models.
Socio-demographic characteristics of respondents
The total numbers of women, who were fecund, married and/or sexually active and included in the analysis were 9,056. The mean (SD) ages of respondents were 29.68 and 7.42 years respectively. Almost two-thirds (59.12%) of women were not formally educated. Coming to the place of residence, 7,565 (83.53%) women were rural dwellers and 3,759 (41.51%) women were Orthodox followers (Table1).
Individual and community-level factors associated with unmet need for contraception (fixed-effects)
After adjusting for individual and community-level factors (model 3) age of women, the total numbers of living children, a wealth of household, religion, married more than once and region were found to have a statistically significant association with unmet need for contraception.
Those women whose ages between 45-49 years were 2.3 times more likely to have an unmet need for contraception than those ages between 15-19 years [AOR=2.25, 95% CI: (1.34, 3.79)]. The odds of unmet need for women who had greater than or equal to three living children were, almost 1.9 times higher than those who had less than three children [AOR=1.87, 95 % CI: (1.40, 2.49)]. Those women who belong to the richer household were 27% less likely to have an unmet need for contraceptive as compared to the poorest [AOR=0.73, 95% CI: (0.54, 0.97)]. The odds of unmet need for contraceptive for women who follow Muslim were 1.4 times more likely then compare to Orthodox followers [AOR=1.37, 95% CI: (1.02, 1.83)]. Those women who married more than once were 1.3 times more likely to have an unmet need for contraceptive than married once [AOR=1.31, 95 % CI: (1.06, 1.62)]. Lastly, those women who belong to the Somali region were 66% less likely to have an unmet need for contraceptive than Addis Ababa [AOR=0.34, 95% CI: (0.19, 0.61)] (Table2).
Random effect (a measure of variation)
The results of multilevel logistic regression for random effects showed that there was a significant variation in the unmet need for contraception across the clusters (Table3). The Intra-cluster correlation coefficients showed that 12.74% of the variation in unmet need for contraceptives was related to community-level factors. The full model also showed that there is a statistically significant variation in unmet need to contraceptive across communities or clusters. About 33.33% of unmet need to contraceptives in clusters was explained in the full model. Besides, the MOR confirmed that the unmet need for contraceptives was attributed to community-level factors. The MOR for unmet need for contraceptive was 1.79 in the empty model which indicated that there was variation between communities (clustering) (1.79 times higher than the reference (MOR = 1)). The unexplained community variation in unmet need for contraceptives decreased to MOR of 1.46 when all factors were added to the model. This showed that when all factors are considered, the effects of clustering are still statistically significant in the full models.