FACTORS DETERMINING THE CHOICE OF HEALTH CARE FACILITIES BY PREGNANT WOMEN IN IJERO EKITI
The main aim of this study was to examine factors determining women’s preference for places to give birth in Addis Ababa, Ethiopia. A quantitative and cross-sectional community based study design was employed. Data was collected using structured questionnaire administered to 901 women aged 15–49 years through a stratified two-stage cluster sampling technique. Multinomial logistic regression model was employed to identify predictors of delivery care. More than three-fourth of slum women gave birth at public healthcare facilities compared to slightly more than half of the nonslum residents. Education, wealth quintile, the age of respondent, number of children, pregnancy intention, and cohabitation showed net effect on women’s preference for places to give birth. Despite the high number of ANC attendances, still many pregnant women especially among slum residents chose to deliver at home. Most respondents delivered in public healthcare institutions despite the general doubts about the quality of services in these institutions. Future studies should examine motivating factors for continued deliveries at home and whether there is real significant difference between the quality of maternal care service offered at public and private health facilities.
Assurance of healthcare for all segments of the population with special attention given to the health needs of women and children was one of the top priorities in the Ethiopian Health Policy  . The endorsement of MDG 5 in the HSDPs is an indication of the commitment or political will of the government towards reducing maternal mortality across the nation  . Yet, Ethiopia’s health system is underdeveloped and underfinanced  . While some progress has been made in providing basic health services to poor women and their children, the progress may be uneven because many people are not reached with services  .
Ethiopia’s total health expenditure as a percentage of the gross domestic product (GDP) has remained stable at 4.3% for years. With emphasis given to publicly funded healthcare, out-of-pocket payment constitutes 42%  . The public health sector is the main provider of primary healthcare and serves two-thirds of the population who cannot afford private healthcare. The main objective of the public sector service provision, as stated in the National Health Policy, is “to give comprehensive and integrated primary health care services in a decentralized and equitable fashion” .
Childbirth and its process are one of the most significant life events to a woman . The time of birth as well as shortly thereafter is the most dangerous period in a child’s life especially in the developing world. Hence the choice of place of delivery for a pregnant woman is an important aspect of maternal healthcare. The place of delivery is an important factor often related to the quality of care received by the mother and infant for influencing maternal and child healthcare outcomes. In Addis Ababa, the capital of Ethiopia, though the private health facilities (hospitals and clinics) outnumber public clinics , only 20% of deliveries take place in the private sectors and 17% of mothers deliver at home .
This study aims to systematically explore the differences and the factors that influence women’s preferences for places to give birth in Addis Ababa. It is envisaged that a clear understanding of such factors is key in building a responsive maternal healthcare system and improving health outcomes in Ethiopia.
2. Research Design and Methods
2.1. Sampling and Data Collection
Addis Ababa, the study area, is divided into 10 subcities and each subcity is further divided into several small administrative units called Kebeles. In the 2007 Ethiopia Housing and Population Census, Kebeles were further subdivided into enumeration areas (EAs). An EA is a geographic area consisting of a convenient number of dwelling units which was used as a counting unit for the census. The average number of households (HHs) per EA in urban Ethiopia is 169. The number of clusters (EAs) in Addis Ababa was about 3865 .
Because of the different levels of political or administrative structures and wider geographic areas, cluster sampling technique was employed for this study. The study employed a stratified, two-stage cluster design. Since Addis Ababa is entirely urban, stratification was achieved by using the subcities (10 strata). Using the 2007 Population and Housing Census data, in the first stage 30 enumeration areas (EAs) were selected independently from all the strata with probability proportional to (EA) size (PPS) of households. In the second stage, 906 households were selected with PPS of households in each EA. The systematic random sampling of the eligible households was done based on the number of households recorded during the complete listing of households in each EA during the last EDHS 2011 . To minimize sampling errors that may arise due to changes in the years after the last enumeration (complete household listing), approaching the subcity and Kebele administrations as well as community members in the respective EAs was an important step in the survey process. It was necessary to be aware of and be sensitive to the various community level dynamics in the study area. Hence, the demolition of significant portions of four EAs from four strata due to the city’s reconstruction process was the major change reported and verified by the first author. Three EAs were replaced by other randomly selected three adjacent EAs and remaining households of the fourth EA were completed from a section of a randomly selected adjacent EA.
In this study verbal face-to-face interview was administered using a structured questionnaire. Recall bias was taken into consideration during the development of the questionnaire. Therefore, women were asked about their most recent or last birth and the date of birth of the child was asked. Ethical clearance was obtained from the National Research Ethics Review Committee of the Ministry of Science and Technology, Ethiopia. The target population was all women of 15–49 years of age who have experienced at least one birth in the last 1–3 years before the date of data collection, December 2013–January 2014.
2.2. Description of Variables
The independent variables for this study were selected based on a modified version of the Behavioural Model of Health Services. The model distinguished three sets of factors related to healthcare seeking behaviour of individuals: the predisposing, enabling, and need factors.
Under the predisposing factors, demographic variables such as age, number of living children, current marital status, and pregnancy intention related to last childbirth and social structure variables such as education, occupation, and ethnicity were considered at individual, household, and community levels. As regards pregnancy intention, women were asked about their recent births whether they wanted it then, wanted it later, or did not want to have any more children at all. In the analyses, the intention status of the birth was further defined as a dichotomy variable: intended for births wanted by then versus unintended for being either mistimed or unwanted by then. Women’s education was defined here as the highest level of schooling attended regardless of whether the woman completed the level.
Under the enabling factors, individual and family resource indicator variables including housing tenure, health insurance, and wealth quintile were included. Those who visited health facility for ANC were also asked whether there was an organization or agency that either partially or fully covered their expenses and the responses were grouped as “yes” or “no.” Housing tenure was categorised as the house in which the respondent lives is either owned by her or not owned by her, that is, owned versus rental. The type of residence was categorised as slum and nonslum residences based on the five indicators including access to improved water, access to improved sanitation, sufficient living area, durability of housing, and secure tenure (housing tenure) developed by United Nations Human Settlements Programme