Role of socio-demographic factors on utilization of maternal health

care services in Ethiopia

Author

Eyerusalem Dagne

Year: 2010

Supervisor: Anders Emmelin

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Acknowledgment

I would like to thank the department of Public health and clinical Medicine, Umeå University for offering me the opportunity of Study and scholarship.

I also would like to acknowledge my supervisor for his continuous and constructive support throughout my thesis writing process. My warmest gratitude goes to all my teachers and administration workers especially for Karin and Birgitta for their unconditional support.

I would also like to thank my husband for supporting me throughout the whole course.

My appreciation and respect goes to Ethiopian community in Umeå for making my stay memorable.

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Abstract

Background:-Maternal mortality in Ethiopia is one of the highest in the world.

According to the 2005 demographic and health survey the maternal mortality rate

was 673/100,000. Far more many women also suffer from complications of

pregnancy and delivery and maternal health care service utilization is far below

the acceptable level. An effort has been made in this study to assess the effect of

socio-demographic factors on utilization of maternal health care services.

Methods: - Data was taken from the 2005 Ethiopian demographic and health

survey which is a nationally representative survey of women in the 15-49 years

age groups. Women who had at least one child in the three years before the survey

were included in the analysis. To estimate the effect of the socio-demographic

variables on maternal health service utilization two outcome variables were used

which were use of antenatal care services and use of assistance during delivery by

health professional. Then logistic regression technique was used to estimate

models of the outcome variables. Separate models were also done for the urban

and rural women since this group differ in many ways. In addition to this a

probability model was done to estimate the probability of use of the services by

selected variables from the logistic regression model.

Result:-The result showed that only 30% of the women received antenatal care

while 11% received assistance during delivery from health professional. Utilization

of these services was very low among rural women as compared to those living in

urban areas. In the logistic regression model educational status of the mother,

household wealth, place of residence, birth order of the child and educational and

occupational status of the husband were found to be strong indicators of

utilization in the total sample of women. Antenatal care use was found to be a

strong indicator of use of assistance during delivery. The effect of this indicator

variables vary according to place of residence. In the urban women household

wealth, sex of household head and occupation of the husband had no effect on

both antenatal care and use of assistance during delivery. Birth order and sex of

household head were not significantly related with antenatal care use in the rural

women and education of the mother was not found to be significantly related with

use of delivery assistance in the rural sample.

Conclusion:-To increase women’s utilization of health care services and improve

maternal health in Ethiopia some crucial steps should be taken on educating

women and strengthening antenatal care services. Great attention should be given

to the most vulnerable group of women in the country this includes those who are

living in rural areas with no education and in the low economic status group.

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Acronyms

AIDS Acquired immune deficiency syndrome

ANC Antenatal care

DHS Demographic and Health Survey

EDHS Ethiopian Demographic and Health Survey

EHNRI Ethiopian health and nutrition research institute

EMOC Emergency obstetric care

GDP Gross domestic product

GNI Gross national income

HIV Human immunodeficiency virus

HSDP Health sector development program

MDG Millennium development goal

MMR Maternal mortality rate

MoH Ministry of Health

NGO Nongovernmental organisation

NHA National health accounts

PHCU Primary health care unit

RH Reproductive health

USAID United States Agency for International Development

WHO World health organisation

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Contents

Acknowledgment-----------------------------------------------------------------------------------ii

Abstract----------------------------------------------------------------------------------------------iii

Acronyms--------------------------------------------------------------------------------------------iv

Contents-----------------------------------------------------------------------------------------------v

1. Introduction --------------------------------------------------------------------------------------1

1.1 Global overview of maternal health -----------------------------------------------1

1.2 Antenatal and delivery care ---------------------------------------------------------2

1.3 Ethiopia -----------------------------------------------------------------------------------6

1.3.1 Geography, population and economy-----------------------------------6

1.3.2 Health care system --------------------------------------------------------7

1.3.3 Maternal health ------------------------------------------------------------8

1.4 Relevance of the study-----------------------------------------------------------------9

2. Objectives ----------------------------------------------------------------------------------------------------9

3. Method--------------------------------------------------------------------------------------------------------10

3.1 Data----------------------------------------------------------------------------------------10

3.2 Sampling method--------------------------------------------------------------------- 10

3.3 Description of the variables--------------------------------------------------------12

3.3.1 Outcome variables------------------------------------------------------12

3.3.2 Independent variables-------------------------------------------------13

3.4 Data analysis---------------------------------------------------------------------------14

3.5 Ethical consideration ----------------------------------------------------------------14

4. Results--------------------------------------------------------------------------------------------15

4.1 Bivariate analysis-------------------------------------------------------------------16

4.2 Multivariate logistic regression analyses------------------------------------17

4.2.1 Use of antenatal care services-----------------------------------------17

4.2.2 Use of assistance during delivery------------------------------------19

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4.4 Predicted probability of use of maternal health services-------------------------21

4.4.1 Influence of place of residence, education and wealth index on antenatal use------------------------------------------------------------------------------------21

4.4.2 Influence of place of residence, antenatal care and education on delivery assistance------------------------------------------------------------------------------23

5. Discussion---------------------------------------------------------------------------------------24

6. Conclusion--------------------------------------------------------------------------------------27

7. References---------------------------------------------------------------------------------------28

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1. Introduction

1.1. Overview of maternal health Worldwide over half a million women die as a result of childbirth or complication due to pregnancy. Almost all or 99% of these deaths occur in developing countries. Asia and Africa alone take 95% 0f the share of the world’s maternal death and the number is almost equally divided between Asia (253,000) and Africa (251,000). Four percent of the deaths occur in Latin America and the remaining one percent in the more developed regions of the world.(1)

According to WHO maternal death is defined as death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the duration and site of the pregnancy, from any cause related to or aggravated by the pregnancy or its management, but not from accidental or incidental causes.(2)

The tragedy is not only of mortality but for every pregnant woman that dies around 20-30 more mothers will have short and long term complications related to pregnancy and child birth that leads to disability of the woman. These disabling complications include obstetric fistulas, ruptured uterus and pelvic inflammatory diseases.(3)

Around 80% of causes of maternal death are direct causes like haemorrhage, infection, obstructed labour, unsafe abortion and high blood pressure. Severe bleeding usually occurring after the mother gave birth is the single most feared complication claiming the life of most mothers. There are also some health conditions that may have developed before or during pregnancy which may lead indirectly to the death of a mother, some of these conditions include malaria, anaemia, hepatitis, heart diseases and HIV/AIDS.(4)

The conditions that lead to the death of the mother or that leaves her with the severe complications not only have an impact on her but also on the baby she is carrying. More than a million children lose their mothers each year due to maternal mortality. Evidences show that these children have a 3-10 times higher risk of dying than children who live with both parents within two years after birth.(5)

Globally it is estimated that about 5.1 million deaths of children occur only in the first month of life. This comprises 37% of deaths among under-five children. About three million of these deaths occur in the first week after birth and an additional 4.3 million foetal deaths before or during delivery. These huge numbers of newborn deaths each year are due mainly to poorly managed pregnancies; delivery and poor neonatal care. Most of these deaths are believed to be averted with provision of good care during pregnancy and delivery.(6)

The concepts which apply to maternal death and its determinants have been well documented and the health care solutions for preventing and treating the complications during pregnancy are available. The majority of maternal and perinatal deaths could be avoided by access to basic maternity care which is supported by adequate medical and surgical care.(7)

There is historical evidence that indicate the significant positive changes that can be observed when certain interventions are in place for maternal health care. Experiences from Sweden

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showed that the reduction of maternal mortality in the 1800s was due to a national policy that promoted establishment of standard care of pregnancy and delivery with midwifery care for all births. As a result, in Sweden, by the beginning of the twentieth century maternal mortality was the lowest in Europe 230 per 100,000 live births as compared to 500 per 100,000 in the mid 1800s.(8)

In 1987 a global campaign was held recognizing the horrifying consequence that pregnancy brought on women especially for those living in the developing countries. This campaign as a result, led to the establishment of the safe motherhood initiative. The key messages emphasised in this initiative were the importance of access to quality maternal healthcare services and the need of presence of skilled professional at every delivery.(9)

The important points to emphasise in relation to these statements are attendance of antenatal care, delivery in a medical setting and having a skilled health worker at delivery improves maternal health.

As part of a global initiative the millennium development goal (MDG) has the aim of reducing maternal mortality ratio by two third and achieving universal coverage of reproductive health by 2015. This goal was proposed to address the existing burden of maternal mortality which did not change significantly with the existing initiatives. As a strategy to achieve these goals the initiative has emphasised on the key role that the presence of skilled attendant at delivery has on improving maternal health outcomes.(9, 10)

1.2. Antenatal and delivery care

Providing special care for pregnant women in the public health services was not started until 1930s, which was initially introduced in the United Kingdom and Northern Ireland states. It was decided that every pregnant woman should get a regular check-up as an integral part of maternity care. This is one of the important components of maternal health which is now called antenatal care (ANC). Antenatal service is important as it offers pregnant women an opportunity to get different services which alerts the woman to the risks associated with pregnancy and for discussing her options for safe delivery.(11, 12)

The main contributory factor for the development of this special care for pregnant women was the realisation of increased occurrences of deaths due to eclampsia, while deaths due to the other common causes of maternal death like sepsis, haemorrhage and obstructed labour started to decrease during the 20th century. In order to decrease deaths due to eclampsia, it was necessary to detect the problem early during pregnancy by measuring blood pressure and by identifying those women at higher risk for convulsion and starting early intervention to decrease blood pressure when possible. (11)

Ideally ANC should consist of health education for pregnant women, early screening to identify those at high risk of developing complications and diagnosing problems if there are any. Whenever possible it is also important to intervene in order to prevent the development of complications. The diagnosis and treatment should not be limited to those conditions that developed during pregnancy but also for any pre-existing medical condition. These actions should lead to a decrease in the risk or severity of morbidity and mortality.(13)

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Evidences showed the health benefits that can be obtained from some specific services of ANC like tetanus immunization, prevention and treatment of malaria, management of anaemia during pregnancy, and treatment of sexually transmitted infections. Use of these services helps to improve foetal outcomes and maternal health. Recently ANC has become important as an entry point for HIV prevention and care including prevention of mother to child transmission of HIV.(14) Since women who have received ANC are more likely to seek assistance during delivery from a health professional, a focused ANC model in addition to its direct contribution to better health can also contribute to safe delivery.(15)

Globally 30% of women aged 15-40 do not have ANC. Forty six percent of those who did not have ANC are in south Asia while 34% are in sub-Saharan Africa. This low use of services leads to death and disability due to untreated hypertensive disorders or due to mal- or sub-nutrition like iron deficiency anaemia.(16) There has been a significant increase in antenatal service use between the years 1990-2000, the increase has been more than 20% in all the regions of the world except the sub-Saharan regions where only 4% increase was noted.(17)

Regarding delivery care one third of births take place at home without receiving assistance from a skilled birth attendant.(2) A skilled attendant of delivery is defined according to the WHO as an accredited health professional – such as a midwife, doctor or nurse – who has been educated and trained to proficiency in the skills needed to manage normal (uncomplicated) pregnancies, childbirth and the immediate postnatal period, and in the identification, management and referral of complications in women and newborns.(18)

Delivery care can be divided in to two general categories .The first one is basic care which includes attending normal deliveries, care of the newborn and immediate stabilization of a mother if she has complications before referral. The second one is emergency obstetric care (EMOC) which can further be divided into basic or comprehensive. In some developed countries like the United States and most countries in Europe almost all deliveries take place in hospitals with physicians attending all normal and complicated deliveries .In countries like Sweden and UK significant numbers of deliveries take place at home by trained midwives with physicians attending only women with complications or who are at high risk. On the other hand in developing countries most women deliver at home and if the woman has complications it may not be detected and she may or may not be taken to a health facility. These home deliveries may be attended by various health workers, untrained family member or others may deliver completely alone.(19)

There has been a significant change in the number of births attended by skilled professionals. In developing countries the proportion of births attended by skilled birth attendants increased from 42% to 53% over the decade from 1990 to 2000. In this period in Asia the births attended by skilled professionals reached 35% while on the other hand the change in the sub-Saharan regions was only 5%.(16)

Availability, quality and affordability of maternal health care services for sure influence use of the services by women. But good supply doesn’t create demand by itself. Even under same circumstances some women use the services more than the others. This shows that there are factors other than the health care service characteristics that influence the use of maternal

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health care services.(20)

Several studies have shown that socio-demographic factors affect utilization of maternal health care services.(20-23) Some studies showed women’s education increases the use of maternal health services.(20, 21) Educated women are more likely than are uneducated women to use ANC, to use it early and frequently, and to use trained providers and medical institutions, similarly education is positively associated with safe delivery. Female education was also seen to be a strong predictor of maternal mortality independent of income per head.(20) In one study from Nepal women with more than primary level education were more likely to use ANC than those with no education.(20) In a study conducted in Turkey based on the 1993 Turkey’s DHS to assess the socio-demographic determinants of maternal health care utilization women with six or more years of schooling were more likely to use ANC than women with no schooling.(21)

Place of residence is the other factor that was documented to significantly influence the use of maternal health care services. Rural women are generally less likely to give birth in health facility than their urban counterparts.(24, 25) A systematic review which assessed the inequalities in maternal health service utilization using 30 papers from 23 countries including Ethiopia showed that pattern of use of the maternal health services was different among countries and even within countries. Urban and wealthy women were more likely to deliver with assistance of health professional than rural and poor women. The study also showed that wealthier women were likely to seek early ANC than poor ones. (26)A study done based on the 2000 Ethiopian DHS demonstrated that 27% of mothers who gave birth in the five years before the survey received ANC from health professional and further analysis showed that urban women showed higher use of ANC than the rural counterparts, 83% of women in Addis to 22% women in the rural regions.(23)

In another study conducted in the Northwest part of Ethiopia (Gondar) to asses safe delivery service utilization among women of childbearing age 46% of the women attended ANC at least once in their pregnancy, the percentage of women living in urban area and receiving ANC was about three times higher than those mothers living in rural parts of the region. Only 14% of the mothers gave birth in health facilities out of this 2% of women living in the rural regions gave birth in health facilities.(24)

Economic stability of households is also one of the well recognized factors that can affect the utilization behaviour of a woman. The poorest women in the poorest regions of the world have the lowest service coverage. A study in over 50 countries showed that on average more than 80% of births were attended for the richest women compared with only 34% of the poorest women.(17)

In a study from Nepal, household economic status in particular was found to be an important factor associated with utilization of maternal health care services. This can be explained by the ability to pay for services by economically well off groups but the fact that there was a significant relationship after controlling for other factors like place of residence suggests that the richest groups differ from their poor counterparts by more than just dispensable income.(20) Women’s economic opportunity in providing for the family measured by their involvement in gainful or paid employment, type of occupation and status of work also affects

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their health and health seeking behaviour. This might empower women and they will have increased control over income and on decision making concerning their health. As a result they will have increased health seeking behaviour leading to improved maternal health.(17) On the other hand employment may also pose physical exhaustion and in some cases employed women may not have the time to go to health services this may have a negative effect on use of the services. (17, 20) Religion is the other variable which was seen to have some significant relation with service utilization. In a study from the 2000 EDHS it was noticed that those individuals following orthodox/catholic, Muslim and protestant tend to use ANC more than those following traditional belief.(23)

Women having children with birth order of five or more and who are grand-multipara have a lesser chance of delivering in health institutions than those with lesser number of children.(27)

1.3 Ethiopia

1.3.1. Political, geography and economy

Ethiopia is a country located in the north- eastern part of Africa. It is one of the oldest states in Africa with great geographic diversity of mountains, high plateaus, deep gorges, river valleys, and lowland plains. The altitude in the country ranges from 4620 meters above sea level to 120 meters below sea level at the Danakil Depression.(28)

Despite the complexity of the topography, it is common to classify the country into the lowland (<1500 meters) and highland (>1500 meters) areas, where two-thirds of the land area is highland and the remaining one-third is lowland.(29) The country is a Federal Republic having nine Regional States, two city administrations, 611 Woredas and 15,000 Kebeles. Ethiopia is the second most populous nation in Africa next to Nigeria with a total population according to the third census of 74 million. Of these, 50.5% were males and 49.5% were females and a large proportion of women (24%) are in the reproductive age (15-49 years). The population of the country in the previous censuses of 1984 and 1994 were 40 and 53 million respectively. The Census results also showed that the population of Ethiopia grew at an average annual rate of 2.6% between 1994 and 2007. Majority of the population is under 15yrs (45%) and those who are 65+ were only 3.2%.(30)

Agriculture supports 85% of the population in terms of employment and livelihood. This sector constitutes 50% of the country’s GDP. It generates about 88% of the export earnings; and seventy three percent of supplies of raw materials for agriculture based domestic industries comes from this sector.(31)

The country is one of the poorest in the world. Gross national income per capita for 2002 was 100USD which when compared to the average GNI for sub-Saharan Africa (450 USD) was very low. The average GNI for the world in 2002 was 5080. Still millions of Ethiopians are living in absolute poverty.(32)

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Figure 1. Map of Ethiopia.

The low literacy status in the country has a serious implication on the health of the population it influences the spread of diseases, the acceptability of health practices and utilization of modern health services. The total adult literacy rate is 36% (46% for males and 25% for females). The gross enrolment ratio in primary schools at national level is 68% (59% for girls). Even if the enrolment has tripled from the 20% enrolment level of 1994 this figure is low on the sub-Saharan average.(32, 33)

1.3.2. Health care system

Ethiopia's health care system is among the least developed in Sub-Saharan Africa and is not, at present, able to effectively cope with the significant health problems facing the country. The health services in Ethiopia are organized primarily as decentralized within the regions of the country. The service centres are comprised of 143 hospitals, 690 health centres and 1,662 health stations from this 62%, 97% and 77% respectively are owned by ministry of health.

The government of Ethiopia has implemented a health sector development program (HSDP). It consists of four five year programs which focus on further improving health service delivery, capacity building and development of preventive health care and equal access to health services. This program also has a plan to move the services from facilities to the households.(34)

To facilitate the delivery of this services, the HSDP I introduced a four-tier system for health service delivery, characterized by a primary health care unit (PHCU), comprising one health centre with five satellite health posts, district hospital, zonal hospital and specialized

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hospital. A PHC-unit has been planned to serve 25,000 people, while a district and a zonal hospital are each expected to serve 250,000 and 1,000,000 people respectively.(33)

The health care coverage and utilization varies among different regions and demographic groups in the country however the overall coverage and utilization of the health care services in the country shows a steady increase. The potential health service coverage has increased from 45% to 57% and then 64% during 1997, 2002 and 2004 respectively. The per capita health service utilization that was 27% until 2000 has increased to 36% in 2004.(33)

Health care financing in the country similar to the other sub-Saharan Africa countries is characterized by low government financing with only 5% of the GDP going to health care as of 2004 and there is also low participation of private sectors. There has been a change in the national health expenditure from 356 million USD in the year 1999/2000 to 522 million USD in the year 2004/05, in this time period the per capita health expenditure also increased to 7.14USD from 5.6USD with the annual growth rate of 10.6% which is encouraging.(34)

The health care financing comes from different stake holders according to data from the 3rd National Health Accounts (NHA), the government and other public enterprises provides 31% of the financing, donors and NGOs 37%, households 31% and other private employers and funds about 2%. The share of government and households financing has decreased from 33% and 36%, respectively, in 1999/2000. (35)

Shortage of skilled human resources in the country is at a critical situation and the community-based health service is not well developed. The Federal MOH tried responding to these needs through the health service extension program in the context of the HSDP.

The health extension program was put in action by the MOH in 2003 and it brought some changes on expansion of primary health care in the country. The health extension program is organized in a way that two health workers most of which are women are recruited with salary from the community to work at each village health posts in the rural areas. Before taking this post the individuals are trained for one year including field work. As a result of the above initiative in the years 2003-2007 there was a change in publicly funded health care services which rose from 61% to 87% and the total health care coverage including services from private organisations has rose from 70% to 98% in the same period.(36)

1.3.3. Maternal health

Maternal health status in Ethiopia is one of the worst in the world. The country is characterized by high maternal and child mortality. The maternal mortality rate was estimated at 673/100,000 according to the 2005 EDHS and infant mortality rate was 77/1000.(37) It is noted that there has been a minimal change in maternal mortality in five years from 871/100,000 in 2000 to 673/100,000 in 2005. (37, 38)

The observed change in maternal mortality is very low and there is a need to accelerate the decline in mortality in order to achieve the MDG of reducing maternal mortality by two third. Among the leading causes of maternal death in the country haemorrhage constitutes 25% followed by puerperal infections 15%, eclampsia 13% and complicated abortion 10%.

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The 2000 DHS showed only 27% of the mothers received ANC from health professional and less than one percent of mothers received ANC from traditional birth attendants. The proportion of institutional deliveries was also low for all the regions of the country with only eight or less percents delivering in health facilities.(38)

For many years, like that of many other developing countries Ethiopia has been implementing a narrow focused maternal and child health programmes. But in recent years with better understanding of the complexity of social and cultural factors related with maternal health a more comprehensive reproductive health (RH) concept has been advanced. This concept emphasizes empowering and improving the status of women by creating equal opportunity for education, elimination of discrimination against women and increasing their control over decisions in their household. The other related concepts includes community participation and involvement of partners of the women in every aspect of the reproductive health issues.(39)

The HSDP has also given a great attention to maternal health by recognising the importance of use of assistance from skilled personnel during delivery. The weak organisation and performance of health services due to lack of trained personnel, lack of basic equipments and poor referral linkage can be taken as possible reasons for the low utilization of maternal health services. This as a result creates a challenge to improve maternal health. It is also true that health seeking behaviour is influenced by much more factors than the availability and quality of the health services.

1.4. Relevance of the study Sstudies have been done to explore the determinants of maternal health service utilization in the country.(22, 23) These studies have shown that different factors affect maternal health care service utilization in the country. None of the studies have tried to look at the relationship between use of antenatal care services and safe delivery and did not include any characteristics of the husband to the analysis. This study has tried to look into these issues. In addition this study tried to estimate the probabilities of use of the services by using a probability model.

2. Objective

• To describe the utilization of maternal health care services specifically antenatal and delivery services.

• To estimate the effect of socio-demographic factors on utilization of maternal health care service.

• To determine the effect of ANC utilization on safe delivery. • To show the probabilities of use of ANC and delivery assistance using some selected

independent variables.

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3. Methods

3.1. Data Data for this study was taken from the 2005 Ethiopian DHS which was conducted for the second time in Ethiopia the first one being in 2000.

The United States Agency for International development (USAID) introduced the DHS programme in 1984. Since the establishment this program has helped more than 85 countries by giving technical support in conducting more than 240 surveys. This program has gained reputation in collecting accurate and representative data throughout the world. The survey is primarily designed to collect data on marriage, fertility, family planning, maternal and child health, HIV/AIDS, malaria, nutrition and gender. In relation to this women of reproductive age are the main focus of this survey. The DHS surveys are typically conducted every five years and usually based on a large sample.(40)

The 2005 EDHS collected information from nationally representative samples of 14,070 women aged 15-49 years and 6033 men aged 15-59 years. All these individuals were interviewed during the survey using structured questionnaires. Three questionnaires were used for the interview; household’s questionnaire, men’s questionnaire and women’s questionnaire. The 2005 survey is different from the first one in that it included HIV/AIDS and anaemia estimates for the population. The different stake holders in this survey were ORC MACRO through its MEASURE DHS project, national organizations like ministry of health of Ethiopia, central statistics agency and the Ethiopian Health and Nutrition Research institute (EHNRI).(37) For this study the data was directly downloaded from MEASURE DHS website after proper permission was obtained. The data downloaded was the individual recode files from the 2005 dataset.(41)

3.2. Sampling method Sampling in the 2005 EDHS was made in a way appropriate to give estimates on demographic and health estimates of the population. The sample provides estimates for the country as a whole, for urban and rural regions of the country separately and for each of the 9 regions and 2 city administrations in the country.

The sampling in the 2005 EDHS is stratified, clustered and selected in two stages. In the first stage 540 clusters were selected (145 urban and 395 rural) from the list of enumeration areas from the 1994 census sampling frame. In the second stage a complete household listing was carried out in each selected clusters. Between 24 and 32 households from each cluster were then systematically selected for participation in the survey. This gave rise to selection of 14,500 households giving representative sample of 14,070 women between the ages of 15-49 and 6033 men. (37)

In the survey, information on ANC use and delivery care was collected from women who had at least one birth in the five years before the survey. This analysis was limited to women with in the age group 15-49 years who had at least one birth in the three years preceding the survey the total number of women who had at least one birth in the three years were 5115.The reason for selecting three years was to minimize the time lag between visit to the health service and the interview. If the woman had more than one child in the three years before the

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survey information about use of the services was collected for the last child only.

Since some household characteristics were also going to be used as independent variables we did not include those women who were not usual residents of the household. Only those who were ever married were taken which led to an additional dropping of 30 cases. There were 10 cases in which information on the relevant variables were missing and these cases were excluded from the analysis. At the end 5024 cases were included in the analysis.

Figure 2. Flow chart showing the data generation process

Twenty three percent of the total clusters in the DHS sample were urban clusters. From the sample of women selected for this analysis 14% of the women were living in urban areas. This difference came from our selection criteria of taking only those women who gave birth in the three years before the survey and the exclusion of those women who were not usual residents and who were never married. In addition to this the households were systematically selected from the clusters in the second stage of sampling. This may bring about inclusion of less number of women who gave birth in the three years before the survey.

540 clusters

(145 urban and 395 rural)

14,500 households

14,070 women of Age 15-49

5115 women had at least one birth in the three

years before the survey Missing (10)

Visitors and never married

women (71)

5024 women included in

analysis

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3.3. Description of the variables For this study two outcome variables were used as indicators of maternal health care utilization. The independent or predictor variables used in the logistic regression model were selected based on Andersen’s behavioral model of health service utilization. This model was developed in 1968. According to this model determinants of health care utilization are put into three categories; these are predisposing factors, enabling resources and need based characteristics.(42)

• Predisposing factors -Demographic -Social structure -Health beliefs

• Enabling resources -Personal/family -Community

• Need based characteristics -Perceived -Evaluated

The Andersen behavioral model was later modified in 1970s to include a health care system characteristic which includes policy, resources and organization. According to the model this factors determine the individual’s decision on using health services which later results in consumer satisfaction (42)

For this study the independent variables selected were in the categories of predisposing factors and enabling characteristics. The variables considered as predisposing factors include age of the mother, educational status of the mother, religion, work status, sex of head of the household and educational and occupational status of the husband. The enabling characteristics include household wealth and place of residence.

3.3.1. Outcome variables

Two outcome variables were considered for this analysis:

• Use of antenatal care service: A woman is considered to have used ANC if she was checked by a health professional (doctor, nurse or midwife) at least once during her pregnancy. This variable was coded as 1 if the woman received care from a health professional and 0 if otherwise. The WHO recommends four or more visits as optimal number of visits for those with uncomplicated pregnancy. In this analysis no hypothesis was formulated to assess the content and quality of ANC. As women who never used the service are significantly different from those who used ANC services at least once, ANC use status was classified as above. This classification was used to assess use of the service in most analysis using the DHS. (21,23,49)

• Assistance during delivery: Defined as whether the woman received assistance from a certified health professional (doctor, nurse or midwife). This was coded as 1 if the woman received assistance from a health professional and coded as 0 if otherwise.

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3.3.2. Independent variables Several socio-demographic variables were taken to investigate their effects on use of the maternal health services. These variables are described in table below.

Table1 Description of the independent variables.

Variable Measurment

Place of residence

Age of respondent

This is a dichotomous variable (urban and rural) according to where the woman was living at the time of the survey. It was coded as 0 for urban and 1 for rural.

This variable refers to age of the woman at the time of the survey and has three categories ranging from 15-49 and is categorized as15-19, 20-34, and 35-49.

Educational status Educational status refers to the highest educational level the woman attained and it was categorized into three groups as no education, primary and secondary plus higher. In the survey the category secondary and higher education were separate categories but for this study the two were merged because the numbers of women in the higher education group were very few.

Work status In the survey this was defined as if the woman has been working in any field other than household work in the seven days before the survey. This was classified as working or not working

Relegion Classification of this variable was developed according to previous literature by merging together the orthodox and catholic religion because women in the catholic group were few. The other categories are protestant, Muslim and traditional religion.

Wealth index Measured by a composite score of several indicators of household possession. This was based on the questions about whether the household has items and facilities as piped water, toilet, type of floor, electricity, radio, television and bicycle. Then according to the answer each asset was given weight .Each household then was assigned a score according to each asset and the scores were summed for each household. The higher the score the higher was the economic status of the household.

Partner’s educational level

Similar to educational level of the women this was categorized into three groups as no education, primary and secondary plus higher education.

Sex of household head

This is classified as male or female. Based on the answer from the usual residents of the households on who the head of the household is.

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Occupation of the partner

Has two categories of skilled or not skilled .Partners who never worked, who were working in agriculture and unskilled manual work were classified as not skilled and those working as clerical, sales ,services and skilled manual work were classified as skilled workers.

Birth order This refers to the rank of the child at birth. It has five categories starting from 1, 2-3, 4-5, 6-7, and 8+. For example 1 refers to the first born child.

These categories of the independent variables were coded starting from zero to make it appropriate for further analysis using logistic regression methods.

3.4. Data analysis The data analysis was carried out using STATA. Descriptive statistics (frequency and percentages) was used to describe the data. Bivariate analysis was done by taking each independent variables and calculating the proportion of use of antenatal and delivery assistance.

Since both outcome variables were dichotomous logistic regression analysis was used to estimate the effect of the indicator variables on the outcome variables. Two logistic regression models were fitted using the two main outcome variables for the total sample of women. Since the rural and urban women were different in most of the characteristics separate models were fitted for the urban and rural women.

The logistic regression model also makes it possible to calculate the probability of use of the maternal health care services. For the calculation of the probabilities of use of ANC and delivery assistance a separate logistic regression model was fitted by using some of the independent variables.

3.5. Ethical consideration The survey data of DHS can be downloaded from the website and is free to use by researchers for further analysis. In order to access the data from DHS MEASURE one needs to submit a written request to the DHS MACRO. A written inquiry was submitted to the organization and permission was granted to use the data for this survey.

14

4. Results

Result of utilization pattern for antenatal care and assistance during delivery is presented in table3. From the total sample of women 30.25 % received antenatal care from a health professional. Rural women were less likely to receive the care (23.06%) as compared to urban women where 74.61% of them received antenatal care service from health professional.

Table 2. Distribution of use of antenatal care and assistance during delivery of the study population

While looking at the pattern of delivery assistance only 11.6% of the women gave birth with assistance from a health professional which includes doctors, nurses and midwives. The distribution was uneven between the urban and rural women where only 3.8% of rural women delivered with health professional assistance while 59.2% of the urban women were assisted during delivery by a health professional. Table 3 shows that about 16% of the women had four or more ANC visits and the median months of pregnancy at first ANC was six months.

Table 3. Distribution of women according to number of ANC visits.

Number of ANC visit Number

%

None 3453 68.7

1 214

4.3

2-3

529

10.5

4+

828

16.5

Total 5024 100

Variable Description

Total

No. %

Urban

No. %

Rural

No. %

Antenatal care

Received antenatal care service from health professional at least once during pregnancy

Yes 1520 30.3 523 74.6 997 23.1

No 3504 69.7 178 25.4 3326 76.9

Assistance during delivery

Received assistance during delivery from health professional. (Doctor, nurse or midwife)

Yes 581 11.6 415 59.2 166 3.8

No 4443 88.4 286 40.8 4157 96.2

Total 5024 100 701 100 4323 100

15

4.2. Bivariate analysis

Table 4, Percent distribution of women according to use of ANC and delivery assistance by different

characteristics.

Characteristics Total women

N %

Women who received ANC N %

Women who delivered with assistance

N %

Age of respondent 15-19 386 7.6 112 29.0 48 12.4 20-34 3555 70.8 1149 32.3 455 12.8 35-49 1083 21.6 259 23.9 78 7.2 Education No education 3833 76.3 850 22.2 172 4.5 Primary 805 16.0 346 43 137 17.0 Secondary+ 386 7.7 324 83.9 272 70.5 Religion Orthodox/catholic 2083 41.5 784 37.6 327 15.7 Protestant 892 17.7 270 30.3 98 11 Muslim 1933 38.5 451 23.3 151 7.8 Traditional 116 2.3 15 12.9 5 4.3 Work status Not Working 3872 77.1 1105 28.5 398 10.3 Working 1152 22.9 415 36 183 15.9 Sex of household head Male 4358 86.7 1278 29.3 429 9.8 Female 666 13.3 242 36.3 152 22.8 Birth order 1 947 18.9 384 40.6 236 24.9 2-3 1553 30.9 506 32.6 213 13.7 4-5 1156 23.0 317 27.4 73 6.3 6-7 788 15.7 186 23.6 37 4.7 8+ 580 11.5 127 21.9 22 3.8 Educational level of the husband

No education 2905 57.8 543 18.7 90 3.1 Primary 1348 26.8 481 35.7 135 10. Secondary+ 771 15.4 496 64.3 356 46.2 Occupation of the husband Skilled 4163 82.9 979 23.5 184 4.4 Not skilled 861 17.1 541 62.8 397 46.1 Residence Urban 701 14 523 74.6 415 59.2 Rural 4323 86 997 23.1 166 3.8 Wealth index Poorest 1241 24.7 147 11.9 23 1.9 Poor 968 19.3 180 18.6 18 1.9 Middle 946 18.8 252 26.6 23 2.4 Rich 849 16.9 278 32.7 56 6.6 Richest 1020 20.3 663 65.0 461 45.2 Total 5024

16

Median age of the women was 28 years with range of 15-49 years. Eighty six percent of the women were living in rural areas. Three out of four (76%) women had no education and did not work (77%). Orthodox and catholic religion constitute the majority (42%) and 24% of the women were in the poorest wealth index category. In one out of six households’ women were the head. Among husbands 58% had no education and only 17% were skilled workers. From the total births in the three years before the survey 5.9% of children were not alive.

About 84% of the women with a secondary or higher education used the service as compared to women with no education (22%). This difference was also seen in the distribution of use by wealth index 65% of women in the richest wealth index category used the service while only 11 % of those in the poorest category used the service. Working mothers and mothers who were head of the household had a relatively higher percentage of use of antenatal care services when compared to those who were not working and who were not the head of the household. Most women (40%) used antenatal care service for the first child than the later ones.

Sixty four percent and 62% of women who had partners with secondary or higher education and whose partners were working in skilled profession respectively used antenatal care service.

As seen above in the table the use of assistance during delivery had a similar distribution by the different variables as of antenatal care utilization. One of the characteristics that showed major difference in the proportion of use of assistance during delivery was educational level of the woman. About 70% of women with secondary or higher education delivered with assistance from health professional where as women with no education group had a 3.8% chance of receiving assistance during delivery. As shown in the table place of residence, household wealth, educational level of the partner and work status of the partner were the other variables that showed a significant difference in proportion of using the service.

4.3 .Multivariate logistic regression analysis

4.3.1 Use of antenatal care

In table 5 below the multivariate logistic regression result is shown. This analysis shows the net effect of each variable on the status of use of antenatal care services. The result showed that women who were living in rural areas were less likely to receive antenatal care from a health professional (OR=0.5 95% CI 0.4-0.6) as compared to women living in urban areas while controlling for all the other variables in the model.

A statistically significant difference was seen by education even after controlling for the other variables. The odds of using antenatal care service was three times higher if the woman has secondary education or more as compared to those with no education (OR 3.2 95% CI 2.3-4.5) and a 1.5 times higher odds if the woman has primary education when compared to women with no education (OR 1.5 95% CI 1.2-1.8). For the urban sample the odds of using antenatal care was found to be statistically non significant for the primary education group when compared to those with no education (OR 1.2 95% CI 0.7- 2.1).

17

Table 5 Multivariate logistic regression results with odds ratios and 95% confidence interval for use

of antenatal care services.

Characteristics Total

N %

Urban N %

Rural

N %

Age of respondent 15-19 1 1 1 20-34 1.3 0.9-1.7 1.9 1.0-3.4 1.1 0.8-1.5 35-49 1.1 0.8-1.6 1.6 0.7-3.6 0.9 0.6-1.4 Education No education 1 1 1 Primary 1.5 1.2-1.8 1.2 0.7-2.1 1.5 1.3-1.9 Secondary+ 3.2 2.3-4.5 2.7 1.5-4.7 2.8 1.7-4.8 Religion Orthodox/catholic 1 1 1 Protestant 0.7 0.6-0.9 0.9 0.5-1.7 0.7 0.6-0.9 Muslim 0.8 0.6-0.9 0.8 0.5-1.3 0.7 0.6-0.9 Traditional 0.5 0.3-0.9 - 0.5 0.3-0.9 Work status Not Working 1 1 1 Working 1.2 1.0-1.4 1.1 0.7-1.7 1.2 1.0-1.4 Sex of household head Male 1 1 1 Female 0.9 0.8-1.2 0.8 0.5- 1.3 1.0 0.8-1.3 Birth order 1 1 1 1 2-3 0.8 0.6-0.9 0.5 0.3-0.9 0.8 0.7-1.1 4-5 0.9 0.8-1.0 0.7 0.5-1.0 0.9 0.8-1.2 6-7 0.9 0.6-0.9 0.7 0.5-0.9 0.8 0.8-1.2 8+ 1.0 0.9-1.0 1.0 0.7-1.3 1.0 0.9-1.3 Educational level of the husband

No education 1 1 1 Primary 1.5 1.3-1.8 2.0 1.1-3.5 1.5 1.3-1.8 Secondary+ 1.9 1.5-2.4 2.7 1.6-4.7 1.74 1.3-2.3 Occupation of the husband Skilled 1 1 1 Not skilled 1.3 1.0-1.6 1.5 1.0-2.4 1.2 0.9-1.6 Residence Urban 1 - - - - Rural 0.5 0.4-0.6 - - - - Wealth index Poorest 1 1 1 Poor 1.5 1.2-1.9 0.3 0.1-4.5 1.5 1.2-2.0 Middle 2.2 1.8-2.8 0.6 0.1-5.5 2.3 1.8-2.9 Rich 2.6 2.0-3.2 1.1 0.1-8.9 2.6 2.1-3.4 Richest 3.7 2.8-4.8 2.1 0.3-15.4 3.6 2.7-4.8

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Women following traditional religion had a fifty percent less odds of using antenatal care services while compared to those following orthodox or catholic Christianity (OR 0.5 95% CI 0.3-0.9). The odds of using ANC increased with increase in household wealth index in the total sample. The odds of using the service was about four times higher if the woman belongs to the highest wealth index group as compared to those belonging to the lowest wealth index group (OR 3.7 95% CI 2.8-4.8). Household wealth had no statistical significance on the use of antenatal care services in the urban sample.

Women whose husband’s educational level was secondary or above had a two times higher odds of use of ANC when compared to those with partners who had no education (OR 1.9 95% CI 1.5-2.4).

4.3.2 Use of assistance during delivery

In table 6 Result for the multivariate regression model for assistance during delivery is shown. In the analysis of the factors that influence assistance during delivery an additional indicator variable (use of antenatal care service) was included in the model. The reason for including this variable in the model was that use of antenatal care service was seen to be a strong positive predictor of safe delivery.

The result of multivariate analysis showed that women who used antenatal care service had a five times higher odds of delivering with assistance by health professional (OR 5.1 95% CI 3.8-6.7) as compared to those who did not use antenatal care services. Household wealth was also related with assistance during delivery, the result shows a statistical significance for women in the rich and richest wealth group (OR 1.8 95% CI 1.1-3.1) and (OR3.4 95% CI 2.0-5.9) respectively. However, similar to the use of antenatal care services the result was not statistically significant for women living in the urban areas.

Women living in rural areas had a 69% less odds of delivering by assistance from health professionals when compared to urban women (OR 0.3 95% CI 0.2-0.4). A woman with a secondary or higher education has 2.4 times higher odds of delivering with assistance when compared to women with no education in the total sample. The logistic regression result for the rural sample showed no statistical significance for the relation between secondary plus higher education and assistance during delivery. The odds of using delivery assistance showed a decreasing trend with increase in birth order in the total, urban and rural samples of women.

Women with partners who had a secondary or higher education had two times higher odds of delivering with professional assistance when compared to those with partners having no education (OR 2.2 95% CI 1.5-3.2). Similarly, women who had partners who were skilled workers had a 1.8 times higher odds of delivering with professional assistance than women with partners who were not skilled professionals (OR 1.8 95% CI 1.3-2.4). This association was seen to be statistically non significant in the urban sample.

19

Table 6 Multivariate logistic regression results with odds ratios and 95% confidence interval for use of assistance during delivery.

Characteristics Total

OR 95 % CI

Urban OR 95 % CI

Rural OR 95 % CI

Age of respondent 15-19 1 1 1 20-34 1.2 0.8-2.0 0.6 0.3-1.4 2.0 1.0-3.6 35-49 1.7 0.9-3.3 1.0 0.4-3.0 1.8 0.7-4.6 Education No education 1 1 1 Primary 1.4 1.0-1.9 1.3 0.8-2.2 1.5 1.0-2.2 Secondary+ 2.4 1.7- 3.6 3.0 1.7-5.1 1.4 0.6-2.9 Religion Orthodox/catholic 1 1 1 Protestant 1.4 1.0-2.0 1.8 1.0-3.4 1.1 0.7-1.7 Muslim 1.1 0.8-1.5 1.7 1.1-2.8 0.7 0.5-1.1 Traditional 2.5 1.0-6.7 - 2.1 0.8-5.5 Work status Not Working 1 1 1 Working 1.2 0.9-1.6 1.2 0.8-1.8 1.2 0.8-1.7 Sex of household head Male 1 1 1 Female 1.5 1.1- 2.1 1.4 0.9-2.2 1.6 1.0-2.6 Birth order 1 1 1 1 2-3 0.4 0.3-0.6 0.6 0.4-0.9 0.3 0.2-0.5 4-5 0.5 0.4-0.7 0.4 0.2-0.7 0.5 0.4-0.6 6-7 0.6 0.5-0.7 0.4 0.2-0.9 0.6 0.4-0.7 8+ 0.7 0.6-0.8 0.3 0.1-0.9 0.7 0.6-0.9 Antenatal care No 1 1 1 Yes 5.1 3.8-6.7 5.7 3.6-9.1 5.0 3.5-7.2 Educational level of the husband

No education 1 1 1 Primary 1.3 0.9-1.8 1.2 0.6-2.2 1.3 0.8-2.0 Secondary+ 2.2 1.5- 3.2 2.0 1.1-3.6 2.5 1.5-4.3 Occupation of the husband Skilled 1 1 1 Not skilled 1.8 1.3-2.4 1.2 0.8-1.8 2.5 1.6-3.8 Residence Urban 1 - - Rural 0.3 0.2-0.4 - - Wealth index Poorest 1 1 1 Poor 0.8 0.4-1.5 1.2 0.1-30.2 0.7 0.4-1.5 Middle 0.9 0.5-1.6 0.4 0.1-8.2 0.9 0.5-1.7 Rich 1.8 1.1-3.1 0.5 0.1-7.7 1.9 1.1-3.4 Richest 3.4 2.0-5.9 3.2 0.2-41.3 2.6 1.4-4.8

20

4.4. Result for calculations of Predicted probabilities of use of maternal health services 4.4.1. Influence of place of residence, education and wealth index on the use of antenatal care services

Predicted probabilities of antenatal care utilization were calculated using three of the variables that showed strong effect in the logistic regression model.

These variables were place of residence, wealth index and education status of the mother. A separate logistic regression model was fitted using these three independent variables by taking antenatal care use as an outcome variable.

Then the probability was calculated as follows.

Logit (probability of use of antenatal care) = -1.14 +β1X1+ β2X2+ β3X3

Where,

X1= Educational level of the mother X2=Wealth index X3=place of residence. The B coefficients for each variable were taken from the logistic regression model output.

Table 7 Description of the level and values of β coefficients for the independent variables included

in calculation of predicted probabilities of use of antenatal care.

Predictor variables Level of predictor variables Value of β coefficient

Education No education Primary Secondary Wealth index Poorest Poorer Middle Rich Richer Place of residence Urban Rural

X10=0 X11=1 X12=2 X20=0 X21=1 X22=2 X23=3 X24=4 X30=0 X31=1

β 10 =0 β 11 =0.57 β 12 =1.58 β 20 =0 β 21 =0.50 β 22 =0.93 β 23 =1.12 β 24 =1.59 β 30 =0 β 31 =-0.95

The graph below (Fig 2.) was constructed form the results of the probability calculation. It is seen that the probability of using antenatal care increases with increasing wealth index and the probability shows a different pattern by combined measures of educational status and place of residence.

Women in the lowest wealth index group with no education and living in rural areas showed the lowest probability of use of antenatal care (1/1+e-(-1.14+(0)(0)+(0)(0)+(1)(-0.95)) which was 0.12 or 12% followed by those with no education and living in the urban areas.

21

Figure 3. Predicted probability of use of antenatal care by place of residence, educational status of the mother and

wealth index in Ethiopia.

At the highest wealth index level place of residence and educational status of the mother seem to have same probabilities of using antenatal care. As wealth index increases the gap between the education/residence groups decreases. The highest probability of use of ANC was observed for women living in the urban area, with secondary education and in the highest wealth index group (1/1+e-(-1.14+(4)1.59+(2)1.58+(0)(0)) which is 99%.

4.4.2. Influence of place of residence, use of antenatal care services and education on using assistance during delivery.

Predicted probability of using assistance during delivery is calculated using variables that showed strong association in the logistic regression model. These variables were use of antenatal care, place of residence and educational status of the mother. A separate logistic regression model was fitted using these variables.

The probability was calculated as follows:

Logit (probability of assistance during delivery) = -1.95+ β1X1+ β2X2+ β3X3

Where,

X1= Educational status of the mother X2=Antenatal care use X3=Place of residence

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

Poorest Poor Middle Rich Richest

prob

ability

wealth index

No education/Rural

No education/Urban

Primary/Rural

Primary/Urban

Secondary+/Rural

Secondary+/Urban

22

Table 8 Description of the level and values of β coefficients for the independent variables included

in calculation of predicted probabilities of use of assistance during delivery.

Predictor variables Level of predictor variables Value of β coefficient

Education

No education

Primary

Secondary

Use of antenatal care

No ANC

Used ANC

Place of residence

Urban

Rural

X10=0

X11=1

X12=2

X2o=0

X21=1

X30=0

X31=1

β 10 =0

β 11 =0.84

β 12 =1.83

β 20 =0

β 21 =1.85

β 30 =0

β 31 =-2.34

From the graph below (Fig 3) it is seen that women living in urban areas and who received antenatal care were more likely to delivery with health professional assistance and from these women those with secondary and higher education showed the highest use. Women in this group were 97% (1/1+e-(-1.95+1.85(1)+1.83(2)+(0)(0)) more likely to deliver with assistance.

Women from rural areas with no antenatal care service use and with no education showed the lowest probability (1/1+e-(-1.95+(0)(0)+(0)(0)-2.34(1))which is 0.014 or 1.4% of delivering with professional assistance when compared to the rest of the women.

Women with higher level of education have a higher probability of using assistance during delivery in both rural and urban regions but this result varies by the status of use of ANC. Urban women with no education who have used antenatal care had a higher probability of using assistance during delivery (1/1+e-(-1.95+1.850(1)+(0)(0)+(0)(0)) 47.4% than rural women with secondary or more education who did not use antenatal services with probability of (1/1+e-(-1.95+1.83(2)-2.34(1)) 34.6%.

23

Figure 4. Predicted probability of using assistance during delivery by antenatal care use, education

and place of residence in Ethiopia.

0

0,2

0,4

0,6

0,8

1

Urban/ANC Urban/No ANC

Rural/ANC Rural/No ANC

No education

Primary education

Secondary+ education

24

5. Discussion

A total of 5024 women were included in this study to investigate the factors that influence utilization of maternal health care services. It was seen that about 30% of the women received ANC and 11% used assistance during delivery from a health professional. The status of use of maternal health services noted here is one of the lowest from countries in sub-Sahara region.(43-45)

Lower rate of ANC utilization and delivery assistance services has been established as contributing factors for higher rate of maternal mortality. In disadvantaged regions of the world like Ethiopia where such service are poorly developed, maternal mortality remained to be a big challenge in public health. To address these issue different stake holders at international, national and regional levels have been implementing different strategies. The MDG has been one of the internationally coordinated biggest initiatives. But countries having poor infrastructures, low ANC utilization and assistance delivery rates have been progressing poorly, Ethiopia could be an example. Use of maternal health services have shown almost no change in the country in the five years from 2000-2005 in the country and MMR remains one of the highest in the world.(37, 38)

The relatively higher level of utilization of ANC when compared to the use of assistance during delivery is consistent with other studies from developing countries.(25, 46, 47) This could partially be explained by the unpredictability of onset of labour together with poor infrastructures like roads for transportation which would make access difficult.(25)

Different socio demographic variables were found to be strongly related with the utilization of ANC and delivery services. The most significant ones include educational status of the mother, wealth index, place of residence, birth order, religion and husband´s educational status. In addition to the above mentioned factors use of antenatal care services was found to be a very strong predictor of use of assistance during delivery.

As expected, utilization of these services varied greatly between urban and rural residency. Seventy four percent of the women living in urban areas received antenatal care as compared to 23% in rural areas. The same was true for delivery care, which was 59.2% and 3.84% in the urban and rural areas respectively. Place of residence also came out to be a strong predictor of use of this services in the logistic regression model. This result is consistent with a number of other studies.(21, 25, 46, 48) One possible reason for this discrepancy is the inequitable distribution of health care services; most of the health care services are concentrated in the urban areas, for example evidence from the 2000 EDHS showed that two third of the women in the capital city (Addis Ababa) had access to skilled birth attendants as compared to 2.3% in rural areas. Different studies have also revealed the role of distance to health facilities in the utilization of health care services and to make things worse in most of the rural areas there is no means of transportation to the services.(25, 49) In addition to this access to Medias like radio and television is high in urban areas as a result woman in urban areas are likely to gain more information on activities that promote safe delivery.

Many literatures documented women education to be a major factor influencing maternal health service utilization.(17, 20, 21, 23, 46) There has been an argument that the positive

25

effect of education on utilization of maternal health services is merely due to the fact that educated women are from a wealthy household and live in urban areas. In this study education remained a strong predictor of use of the maternal health services after controlling for the above mentioned factors. Education increases knowledge and autonomy of women which would give them the ability to decide on own and family health issues. This would in turn increase their use of maternal health care services.

Strong association has been found between household wealth and the use of maternal health services which is also supported by other studies.(25) This can be explained by the fact that women should be able to cover the costs needed in order to access health care services. Even in areas where maternal health care services are provided for free, women still have to pay for transportation and additional costs. As a result only those women who can afford to pay for such costs are able to visit health facilities.

The result of predicted probabilities for use of ANC in this study showed, women in the highest wealth index group despite their difference in place of residence and educational level women were found to have higher level of use of ANC. This depicts that household wealth is a very strong determinant of health service utilization. This finding was also consistent with a study done in Bangladesh.(50)

The effect of household wealth in this study however was not found to be significant on use of antenatal care and of assistance during delivery for women living in the urban areas. This finding can be related to the explanation given previously for place of residence, women living in the urban areas may not need additional costs for transportation and other costs related to distance to access health care services.

The other important finding of this study was the strong association between ANC use and use of assistance during delivery. This finding was consistent with other studies.(15, 51) Routine antenatal care helps in raising awareness on safe delivery and gives women a familiarity with health services and this can be archived with fewer visits.

Birth order of the child shows significant association with use of ANC services and use of assistance during delivery. Use of these maternal health services was shown to decrease with increase in birth order. The decrease in odds was especially more consistent in the use of assistance during delivery. This finding is similar with other studies(22, 24). One study from Bangladeshi showed that women with parity of five or more were seen to have a low health seeking behaviour when compared to those who had only one child. The possible explanation could be women who have more children usually do not have enough time to go to the health services. In addition to this as the number of children in the household increase there will also be scarcity of resources.(27)

Religion is found be significantly related with use of antenatal care services but not with use of assistance during delivery. It was observed that women who follow traditional beliefs had a 50% lower chance of receiving antenatal care service when compare with those who follow orthodox/catholic Christianity.

Age of the mother was not found to be significantly related to both use of antenatal care

26

services and use of assistance during delivery in the total sample. This finding was similar to 2000 EDHS. However, it was seen that there was a slightly higher likelihood of use of ANC services for women in the age group 20-34 as compared to those who were less than 20 years of age in the urban regions.

Work status of the mother was found to be specifically associated with utilization of antenatal care services in this study. Experiences and roles as economic providers might empower women through increased control over income which, in turn, may increase their power in decision-making about health care and their ability to access and pay for the services that they need when they are pregnant. This result was not significant for assistance during delivery.

Being head of the household had a positive effect in using assistance during delivery. This might give women a higher autonomy which makes them able to decide on household maters including their health seeking behaviour. However in one study from Ruanda it was seen that households headed by women were found to have low health care behaviour.(48)

In addition some background characteristics of the husbands’ mainly educational level and occupation were found to be associated with usage of these services. Women having partner with secondary or higher educational level tend to use the service more than those who had uneducated partners.(48) Women whose husbands were skilled workers tends to use the service more specifically this was significant for assistance during delivery.(46) Partners who are skilled workers have a higher ability to pay for the services than those who are unskilled. In many social context women’s voices are not heard as much as those of men and women usually have to ask for money and permission from their husbands to access health care.(52) Partners with secondary or higher level of education and those working in the skilled work sector are more likely to agree with the women on use or initiate the use of these services by the mothers.

There were some limitations in this study. The cross sectional nature of the data had made it impossible to reach at causal relation between the different independent variables and use of the specific health services. Since use of the services during pregnancy and delivery in most of the cases happened before the interview while some information on the independent variables show the status of the woman at the time of the interview. In addition Data on distance to the health facilities was not collected so it was not possible to directly assess access to these facilities and its effect on use of the services rather a proxy measure of place of residence was taken. This approach may have affected the findings in some way as different rural and urban areas would vary greatly on their existing facilities and infrastructures. On the other hand the national representativeness of the data, the large sample size and detailed content of the data has given the opportunity to explore the existing situation of maternal health care services in the country.

27

6. Conclusion

This study has tried to answer important issues on the status of use of maternal health services in Ethiopia. Maternal health service utilization was found to be very low and it was seen that use of this services were unequally distributed. The distribution varied depending on place of residence and among the different strata’s of socioeconomic and education groups. Education of the mother was a very strong predictor showing the importance of women’s education in order to achieve the millennium development goal of reducing maternal mortality and even more to improve survival of their children.

Those women living in the rural regions and those in the lower socio-economic group were at a greater disadvantage. An Appropriate package of delivering service to vulnerable groups rural, uneducated and poor women, should be prepared to minimize the disastrous consequences of pregnancy and child birth.

The other message with policy implication is the strong effect of use of antenatal care services on choosing assistance during delivery. Improving the quality of antenatal care services should be given great attention specifically focusing on giving appropriate advice on safe delivery. This includes giving advice on delivering with assistance from a health professional and delivering in health facilities since delivery the outcome is unpredictable.

Most of the unfavourable consequences of pregnancy can be prevented with appropriate delivery assistance service which would be strengthened with appropriate scale up of ANC service utilization. The policy implication is that proper scale up of ANC service will more likely be followed with delivery assistance services once access is not a constraint. The current health extension program implemented by the ministry of health will more likely have an effect in the overall utilization of ANC services and delivery assistance. In addition to this involvement of partners in maternal health issues should be give great attention, since it is seen that the utilization of the services varied by different characteristics of the partners.

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