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Background: Mother-to-child transmission (MTCT) is the largest source of HIV infection in children below the age of 15 years, and more than 90% of pediatric HIV are infected through mother to child transmission. Without treatment, one-half of those infected children will die before the age of 2 years. Despite this, there is limited evidence on PMTCT and its determinants. Therefore, this study aimed to determine the factors affecting the PMTCT service utilisation in Ethiopia. Methods: A two-stage stratified sampling technique was used to identify 4081 women from 2016 Ethiopian Demographic and Health Survey (EDHS). A multilevel mixed-effect binary logistic regression analysis was used to identify the individual and community level factors associated with PMTCT services utilisation. In the final model, a p-value of < 0.05 and Adjusted Odds Ratio (AOR) with 95% confidence interval (CI) were used to declare statistically significant factors with the utilisation. Results: Overall, 21.9% (95% CI, 20.6–23.2) of the women were utilized PMTCT services. Educational status; primary (AOR: 1.65, 95% CI: 1.27–2.13), secondary (AOR: 1.52, 95% CI: 1.03–2.24) and higher school (AOR: 2.48, 95% CI: 1.45–4.22), poorer (AOR: 1.62, 95% CI: 1.12–2.37), middle (AOR: 1.82, 95% CI: 1.10–3.02), richer (AOR: 2.44, 95% CI: 1.42–4.21) and richest (AOR: 4.45, 95% CI: 2.43–8.14) wealth status and orthodox religion follower (AOR: 1.62, 95% CI: 1.22–2.16) were the individual level factors. Moreover, having basic (AOR: 1.66, 95% CI: 1.34–2.06) and comprehensive (AOR: 1.73, 95% CI: 1.38–2.18) knowledge on HIV prevention methods, having knowledge on MTCT of HIV (AOR: 2.69, 95% CI: 2.16–3.36) were also factors at individual level. Whereas, rural residence (AOR: 0.52, 95% CI: 0.32–0.85) was the community level factors that affects the utilization. Conclusions: Less than one-fourth of the mothers had utilised the PMTCT services in Ethiopia. To increase the utilisation of the services, the health care providers should give emphases on counselling, awareness creation, and strengthen the existing frontline integrated health care services in the country.
The study was carried out in Ethiopia, which is the second populous country in Africa, with a population density of 115 people per Km2 [15]. Ethiopia is divided into two administrative units (Addis Ababa and Dire Dawa) and nine regions (Tigray, Afar, Amhara, Oromia, Somali, Benishangul, SNNPR, Gambella, and Harari). This analysis used the 2016 Ethiopian Demographic and Health Survey (EDHS) data, which is a nationally representative household survey data conducted every 5 years by Ethiopia’s Central Statistical Agency (CSA) [16]. In the survey, all women aged 15 to 49 who are regular members of the selected households were included. Finally, data from the 2016 EDHS datasets were analysed using STATA version 14 software, and a total weighted of 4081 women were included in the final analysis. Individual and community level independent variables were identified and further analysis was done. The study’s dependent variable was PMTCT utilization. PMTCT utilization was measured as a dichotomous variable; when a pregnant woman received all the components of PMTCT services (pre and post-test counselling, HIV testing, and receiving test results) during each of the three phases of the visit (antepartum, intrapartum, and postpartum), the utilisation was measured as ‘YES’, otherwise ‘NO’ [4, 6, 9, 17]. The information was gathered from mother’s verbal responses; during ANC visits, labor and delivery, and postnatal care. Explanatory variables included the individual and community levels variable. Both maternal (socio-demographic and maternal health-care-related characteristics) and child-related variables were included in the individual level variables. At the same time, community-level variables included place of residence, region, distance to a health facility, community-level poverty, women empowerment and media exposure. Distance to a health facility was assessed by the question “distance to the nearest health facility is a problem?” and the responses were categorised as “big problem” or “not a problem”. Women empowerment was measured by their decision-making power and the justification for wife-beating. Women who were empowered were those who, in all situations, engaged in decision-making, either alone or with their husbands, and never justified wife-beating. The asset index was used to assess community-level poverty, based on data from the entire sample on separate scores prepared for rural and urban households, and combined to produce a single asset index for all households at the community level, which was then ranked into three categories (poor, middle, and rich). Community media exposure was assessed as “yes” if they have access to all three media (newsletter, radio, and TV) at least once a week, otherwise “no”. The data were extracted, cleaned, re-coded, and analysed using STATA version 14.1 software. Weighting was considered during the analysis to adjust for unequal probability of selection due to the sampling design used in EDHS data. Since the DHS data had hierarchical nature (an individual were nested within communities), a two-level binary logistic regression model was fitted to estimate the effect of both individual and community-level variables on PMTCT service utilisation [18]. As a principle in multilevel analysis, four models were considered for the data. The first model was an empty (null) model without any explanatory variables. The second model was fitted with individual-level variables only; the third model was fitted community-level variables only and the fourth was adjusted for both individual and community-level variables. The variation between clusters was assessed by computing Intra-Class Correlation Coefficient (ICC) and Proportional Change in Variance (PCV). The ICC is the proportion of variance explained by the grouping structure in the population which computed as: ICC=σμ2σμ2+π23; where the standard logit distribution has a variance of π23, σμ2 indicates the community variance. Whereas PCV measures the total variation explained by individual and community level variables in the models as compared to the null model, which is computed as: variance of null model−variance of full modelvariance of null model [19, 20]. Both bi-variable and multivariable multilevel binary logistic regressions were estimated and a p-value of less than 0.05 and an Adjusted Odds Ratio (AOR) with 95% Confidence Interval (CI) were used to declare statistically significant factors associated with PMTCT services utilisation in the selected model.
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