Identifying factors associated with the uptake of prevention of mother to child HIV transmission programme in Tigray region, Ethiopia: A multilevel modeling approach

Background: Prevention of mother to child HIV transmission (PMTCT) remains a challenge in low and middle-income countries. Determinants of utilization occur – and often interact – at both individual and community levels, but most studies do not address how determinants interact across levels. Multilevel models allow for the importance of both groups and individuals in understanding health outcomes and provide one way to link the traditionally distinct ecological- and individual-level studies. This study examined individual and community level determinants of mother and child receiving PMTCT services in Tigray region, Ethiopia. Methods. A multistage probability sampling method was used for this 2011 cross-sectional study of 220 HIV positive post-partum women attending child immunization services at 50 health facilities in 46 districts. In view of the nested nature of the data, we used multilevel modeling methods and assessed macro level random effects. Results: Seventy nine percent of mothers and 55.7% of their children had received PMTCT services. Multivariate multilevel modeling found that mothers who delivered at a health facility were 18 times (AOR = 18.21; 95% CI 4.37,75.91) and children born at a health facility were 5 times (AOR = 4.77; 95% CI 1.21,18.83) more likely to receive PMTCT services, compared to mothers delivering at home. For every addition of one nurse per 1500 people, the likelihood of getting PMTCT services for a mother increases by 7.22 fold (AOR = 7.22; 95% CI 1.02,51.26), when other individual and community level factors were controlled simultaneously. In addition, district-level variation was low for mothers receiving PMTCT services (0.6% between districts) but higher for children (27.2% variation between districts). Conclusions: This study, using a multilevel modeling approach, was able to identify factors operating at both individual and community levels that affect mothers and children getting PMTCT services. This may allow differentiating and accentuating approaches for different settings in Ethiopia. Increasing health facility delivery and HCT coverage could increase mother-child pairs who are getting PMTCT. Reducing the distance to health facility and increasing the number of nurses and laboratory technicians are also important variables to be considered by the government. © 2014 Lerebo et al.; licensee BioMed Central Ltd. The economy of Ethiopia is dependent on agriculture, contributing 47% to the Gross National Product (GNP) and accounting for more than 80% of exports, as well as providing employment for 85% of the population [33]. The Tigray Region has a total population of more than 4.3 million; urban inhabitants make up 19.5% of the population [34]. The estimated population density is 86.15 people per square kilometre. The region has 1 million households, with an average of 4.4 persons to a household, with urban households having on average 3.4 and rural households 4.6 people. Only half of the population has access to health services. The ANC coverage in Tigray region in 2009 was 73.0%, 43% of mothers utilizing ANC were tested for HIV, and of these, 3.1% tested positive [35]. Only half of HIV positive pregnant women and 38% of babies born to HIV positive mothers were given single dose nevirapine (sdNVP) or combination antiretroviral treatment (cART). From May 05 to July 15, 2011 a health facility based cross-sectional study was conducted in Tigray, Ethiopia. The participants were selected by using a multistage sampling. Forty six districts, comprising 13 hospitals and 208 health centers were determined by the Tigray region Bureau of Health [35]. One health center from each district randomly and all available hospitals were chosen. Thirty to 36 post-partum women were purposively selected from each health facility. The managers of all of the selected health facilities and districts were also interviewed. All participants were interviewed face to face by a trained nurse using structured questionnaire to collect information on demographic, socio-economic characteristics and on women’s maternal healthcare, for instance, prenatal care, delivery and postnatal care related to PMTCT. Informed consent was obtained from each participant at the start of the survey. The study was approved by the ethics committee of University of the Western Cape, and Tigray region Health Bureau. “Getting PMTCT service” during the last pregnancy and delivery was used as the principal outcome indicator in the analysis of the demographic and socio-economic determinants at the individual and community level. This indicator, coded 1 for “yes” or 0 for “no”, was defined in accordance with the Ministry of Health PMTCT guidelines as follows: the mother was asked if she received antiretroviral medication, before, after or/and at the time of labour depending on her clinical stage, and whether the child received prophylaxis at the time of birth or/and after birth depending on the mother’s clinical stage. A two level logistic regression model was used to assess the explanatory effects of the independent variables on getting PMTCT services by considering the hierarchical structure of the study sample. The first level represents the individual and the second level is the district/community. The community level covariate was the geographical demarcation of the districts. Individual level covariates comprised age group (≤24, 25–34, or ≥35) years; education (categorized as none, primary, or secondary/higher); number of pregnancy (≤2 or ≥3); place of delivery (home or health facility); ever stigmatized (yes or no); ever discriminated (yes or no); planned pregnancy (yes or no); any CD4 count done (yes or no); time of HIV status knowledge (before being pregnant, during pregnancy, at the time of delivery, or after giving birth); HIV status disclosure to the spouse (yes or no); who attended the birth of child (traditional birth attended, doctor, or nurse/mid-wife/other); and socio-economic status (SES) quintile (1st quintile (poorest), 2nd quintile, 3rd quintile, 4th quintile, or 5th quintile (wealthiest)). The quintile combined information on a set of household assets and living conditions: the household income, employment status, main source of water, type of toilet, main fuel used for cooking, and main material the house built. Data on the community level variables included in the model were obtained from the questionnaires for mothers health facility and district managers and complemented by official data from secondary source [35]. Place of residence grouped as urban, rural; proportion of women with no education in the district grouped as <30%, 30-50%, >50%; proximity grouped as <1 km, 1-5 kms, >5 kms; nurse workload defined as ≤1500, >1500 people per nurse; proportion of poor and poorest household in the district grouped as <30%, 30-60%, >60%; people per health worker defined as ≤500, >500; people per health facility defined as ≤25000, >25000; lab technician workload defined as ≤3100, >3100 people; and people per HCT site grouped as ≤25000, >25000. The community level random effects were estimated, using xtmelogit function, at a 2-level multilevel model as shown: With β0 as the intercept and the slope β1, defined as the expected change in getting PMTCT service. A set of intercepts was estimated for the community level, where πij is the probability of utilizing HCT for a pregnant woman i, in a district j, and β0j is a parameter associated with the fixed part of the model. Therefore, for every one unit increase in X (a set of predictor variables) there is a corresponding effect on the probability mother or child getting PMTCT service. By assuming that each community has a different intercept β0j and a different slope β1j the clustered data structure and the within and between community variations is now taken into account. To capture the extent by which choice of different option of getting PMTCT service, which are contrast specific, varies randomly at the individual level, the results of random effects (measures of variation) are presented as variance partition coefficient (VPC): Where, π2/3 denotes the variance between mother or child from the same district (individual level) and σ2u0 is the variance between districts (community level variance). Data analyses were conducted using Stata 11 (Stata Corp. Inc., TX, USA). The statistical significance of the explanatory variables was estimated using Wald statistics, with all results at <5% alpha level considered significant. The results of the fixed (measure of association) effects were presented as odds ratio (OR) at their 95% confidence intervals (95% CIs). As this study used several explanatory variables that might be correlated to each other (such as mother’s education, father’s education and household wealth index), the multicollinearity assessment was conducted using the means of variance inflation factors and it is small (1.22) indicated the absence of any significant collinearity between explanatory variables in the regression model.