What drives the rural‑urban disparities in maternity‑care services utilisation? Evidence from Ethiopia

Yibrah Hagos Gebresilassie; Araya Mebrahtu Teka

doi:10.12688/f1000research.134166.1

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Research Article

What drives the rural‑urban disparities in maternity‑care services utilisation? Evidence from Ethiopia

[version 1; peer review: awaiting peer review]

Yibrah Hagos Gebresilassie¹, Araya Mebrahtu Teka²

PUBLISHED 13 Jun 2023

Author details Author details

¹ Aksum University, Aksum, Tigray, Ethiopia
² Tigray Institute of Policy Studies (TIPS), Mekelle, Tigray, Ethiopia

Yibrah Hagos Gebresilassie
Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Software, Supervision, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing

Araya Mebrahtu Teka
Roles: Methodology, Supervision, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS AWAITING PEER REVIEW

This article is included in the Health Services gateway.

This article is included in the Sociology of Health gateway.

Abstract

Background: Ethiopia has a high rate of maternal mortality. One of the most important interventions to reduce maternal death from pregnancy-related problems is the use of antenatal and delivery care services. However, the utilisation of these services continues to be unequal for Ethiopian women living in rural and urban areas. Therefore, this study aimed to examine the factors influencing rural‑urban disparity in the use of antenatal and delivery‑care services.
Methods: Data were acquired from the most recent 2019 Ethiopian demographic and health surveys. A total of 7,084 women of reproductive age (15‑49 years) participated in this study. An extended Oaxaca‑Blinder decomposition technique was used to examine the relative contribution of covariates explaining the rural‑urban gap in the factors of antenatal and delivery‑care services utilisation in Ethiopia.
Findings: The results revealed large gaps in maternity care services utilisation between rural and urban areas, with lower coverage in rural areas. The rural-urban gap is primarily influenced by women's socioeconomic and educational status, followed by their media exposure, whereas women's employment status and religious beliefs help to minimise the difference.
Conclusions: The disproportionate disparities in antenatal and delivery‑care services utilisation were due to the proportional differences among women in maternal educational and economic status. Hence, enhancing women's economic and educational status as well as prioritising intervention for the rural disadvantaged women could significantly minimise the disparities in antenatal and delivery‑care service utilisation.

Keywords

Antenatal care, delivery, disparity, gap, rural urban

Corresponding author: Yibrah Hagos Gebresilassie

Competing interests: No competing interests were disclosed.

Grant information: The author(s) declared that no grants were involved in supporting this work.

Copyright: © 2023 Gebresilassie YH and Teka AM. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Gebresilassie YH and Teka AM. What drives the rural‑urban disparities in maternity‑care services utilisation? Evidence from Ethiopia [version 1; peer review: awaiting peer review]. F1000Research 2023, 12:666 (https://doi.org/10.12688/f1000research.134166.1) First published: 13 Jun 2023, 12:666 (https://doi.org/10.12688/f1000research.134166.1) Latest published: 13 Jun 2023, 12:666 (https://doi.org/10.12688/f1000research.134166.1)

Introduction

In 2022, about 223 maternal deaths per 100,000 live births were estimated worldwide, down from 339 in 2000. This is a decline of 34.22 percent over the last two decades (2000-2020).¹ In the same year, the majority of maternal deaths occurred in Sub-Saharan Africa in 2020, Sub-Saharan Africa alone accounted for 70 percent of maternal deaths worldwide. This is due to multiple factors such as high fertility rates, and lack of access to and use of maternity-care services among the most vulnerable groups. The majority of maternal deaths might have been avoided if pregnant women had been able to utilise maternity-care services.¹

Maternity-care services utilisation (particularly antenatal care services: ANC and delivery-care services: DCS) are provided to women during pregnancy to promote awareness of their childbirth readiness and impediment readiness confirming optimum maternal outcomes both for themselves and their babies.² The most important factors in preventing maternal death are the use of antenatal care and delivery-care services.³^,⁴ One of the main reasons for high rates of maternal and infant mortality around the world is the lack of access to and utilisation of antenatal care services and delivery-care services.³^,⁵^–⁷ Maternal deaths have been reduced by using antenatal and delivery-care services supported by trained health workers.³ Despite the importance of giving birth in health facilities, more women choose to give birth outside of them.³^,⁶^,⁸^,⁹ Women in rural and urban settings use antenatal and delivery-care services at significantly different rates.⁵^,¹⁰

The maternal mortality rate in Ethiopia, which is the second-most populous nation in Sub-Saharan Africa, varies significantly between rural and urban areas. While maternal mortality decreased to 676 per 100,000 live births in 2016, there were 412 maternal deaths per 100,000 live births attributed to pregnancy-related deaths (including those caused by problems during pregnancy and childbirth).¹¹ However, there are still significant differences in maternal mortality between rural and urban areas. The worldwide Sustainable Development Goals (SDG) target 3.1: “Reduce global maternal mortality ratio to less than 70 maternal deaths per 100,000 live births by 2030” cannot be met, in part because of these inequities.¹²

The well-being and survival of both mother and child, as well as a decrease in both child and mother mortality, depend on maternity care services, including antenatal care during pregnancy and after delivery as well as delivery in a health facility supported by trained health personnel.¹² The official statistics in Ethiopia mask significant disparities in the usage of maternity care services between rural and urban areas.¹¹^–¹⁴ With a stark disparity between rural and urban areas, the country’s utilization of ANC and delivery care services remained high.¹¹^–¹⁵ In general, women in urban regions use ANC and delivery-care services more frequently than those in rural ones.⁸^,¹⁶^–¹⁸ Women between the ages of 15 and 49 who used ANC services grew from 37.4 percent in 2000 to 58.7 percent in 2019.¹¹ Between rural and urban women residents, there were significant differences in the use of ANC services.

In Ethiopia, rural women had a lower likelihood (40 percent) than their urban counterparts (70 percent) of receiving at least four ANC services in 2019.¹⁴ Utilising antenatal care services improves the likelihood that the delivery will take place in a health facility.⁸^,¹⁵^,¹⁷^,¹⁹ In Ethiopia, the utilisation of delivery-care services grew from 5 percent in 2000 to 47.5 percent in 2019.¹⁴ Utilising this service is essential for lowering mother and infant mortality.²⁰ Although the use of antenatal care and delivery-care services has increased slightly in Ethiopia, rural women continue to use these services the least frequently.⁸^,¹¹ The level, trends, and socioeconomic and demographic factors that influence the utilisation of antenatal and delivery-care services have all been studied in previous Ethiopian studies.⁴^,¹⁵^,¹⁷^,¹⁹^,²¹^–²³ Comparable to research done in developing nations,⁶^,²⁰^,²⁴^,²⁵ some local studies in Ethiopia revealed that low levels of education, low economic status, prevailing religious beliefs, and a lack of transportation options are among the most significant barriers to ANC and delivery-care services use.⁴^,⁸^,¹⁵^,¹⁷^,¹⁹^–²¹^,²⁶^,²⁷ The majority of these studies looked at the factors that influence the use of antenatal and delivery-care services and acknowledge the rural-urban disparities in these factors that may be responsible for rural-urban variations in maternity care services in Ethiopia. Most importantly, even though using antenatal and delivery-care facilities is essential for improving the health of the mother and her child as well as the importance of the household’s general economic status, the disparities between rural and urban areas in Ethiopia remain unclear in the country’s existing literature. Therefore, the purpose of this paper is to examine the factors affecting the differences in the utilisation of antenatal and delivery-care facilities between rural and urban areas of Ethiopia.

Method

Data

The most recent data from the 2019 Ethiopia Demographic and Health Survey (EDHS) were used in this study.²⁸ The “Ethiopian Public Health Institute (EPHI)” conducted the survey in collaboration with the “Central Statistical Agency (CSA)” and the “Federal Ministry of Health (FMOH),” under the supervision of the “Technical Working Group (TWG).” The EDHS data were collected from 21 March 2019 to 28 June 2019. The World Bank, USAID, and UNICEF financed the EDHS survey. Data collection for the survey involved a multi-stage stratified cluster method. The nine regional states of the country including both urban and rural areas were included in the survey (see Table 1). From all of the regions of the nation, sample enumeration areas or clusters were chosen for the first step. In the second stage, data were collected from a nationally representative sample of women between the ages of 15 and 49 who were living in fixed numbers of homes per cluster or enumeration areas using a systematic sampling technique.

Table 1. Sample design regions versus place of residences (rural versus urban).

Sample design	Freq.	Percent	Cum.	Sample design	Freq.	Percent	Cum.
Tigray-urban	139	1.96	1.96	Somali-rural	519	7.33	56.52
Tigray-rural	545	7.69	9.65	Benishangul-gumuz-urban	87	1.23	57.75
Afar-urban	136	1.92	11.57	Benishangul-gumuz-rural	647	9.13	66.88
Afar-rural	538	7.59	19.16	SNNP-urban	88	1.24	68.12
Amhara-urban	143	2.02	21.18	SNNP-rural	854	12.06	80.18
Amhara-rural	837	11.82	33	Gambela-urban	133	1.88	82.06
Oromia-urban	176	2.48	35.48	Gambela-rural	552	7.79	89.85
Oromia-rural	833	11.76	47.24	Harari-urban	431	6.08	95.93
Somali-urban	138	1.95	49.19	Harari-rural	288	4.07	100
Total					7,084	100

The EDHS teams have obtained verbal consent to conduct the interviews from the sample respondents to obtain the necessary data from them. In the end, a total sample of 7,084 women were included in this study. The analysis comprised women between the ages of 15 and 49 who were of reproductive age. Only reproductive women between the ages of 15 and 49 years old having complete cases on the study’s outcome variables were considered for the analyses. To assess the relative contribution of the chosen independent variables to the rural-urban disparities, antenatal and delivery-care services were analysed separately from urban and rural areas. On the fifth round EDHS 2019mini-report, specific details on the sampling method, sample size, etc. used in this study are provided.¹⁴

Description of variables

Dependent variables

In this study, two variables were taken into consideration as the key outcome variables of interest to compute the proportional differences between urban and rural areas in terms of the utilisation of maternity-care services (dependent variable). These are the use of antenatal care services (ANC) or optimal ANC and delivery-care services (DCS) or institutional delivery. According to the WHO’s recommendation, a woman is deemed to have received full ANC (or optimal ANC) if she had at least four ANC visits throughout her pregnancy.² An optimal ANC service user was defined as a woman of reproductive age (15 to 49 years) who had at least four ANC visits under the care of experienced medical professionals, as opposed to the others, who were classified as non-optimal service users. The ANC is a dichotomous variable with the following categories: “Yes = 1” if the woman utilised as least four ANC services, and “No = 0” if she utilised fewer than four ANC services. The second outcome variable in this study is the DCS or place of delivery. It is defined as the percentage of women between the ages of 15 and 49 years who either gave birth in a health facility with the assistance of trained medical professionals (classified as “Yes = 1”) or gave birth at home (classified as “No = 0”).

Independent variables

The independent variables included in the current study were chosen based on the literature’s associations with outcome variables of interest, the use of ANC and DCS⁶^,⁸^,⁹^,¹⁶^,¹⁷^,²⁰^,²²^,²⁵ and their availability in the EDHS datasets.¹⁴ These are the mother’s age at her first birth, the educational attainment of the women (categorised as no education, primary, secondary, and higher), households’ wealth status (categorised as the poorest, poor, middle, rich, and the richest), gender of the household head (categorised as male and female), mother’s religious affiliation (categorised as Christian and Muslim), women’s current working status (categorised as not working and working), number of living children under five years, and maternal mass media use (categorised as “Yes = 1” if they utilise and “No = 0” if they did not use). The criteria for the variables’ inclusion in this study were based on their accessibility in the EDHD datasets for all Ethiopian women aged 15 to 49 years old from both rural and urban areas who had given birth during the previous five years. When respondents or variables were unavailable, missed, or had incomplete information, they were not analysed in this study.

Decomposition estimation

Thus, this study employed a multivariate non-linear Oaxaca-Blinder decomposition technique to quantify the relative contribution of these determinants of the use of ANC and DCS.²⁹^,³⁰ A binary logistic regression was performed to analyse the relationship between antennal and delivery care services and the chosen independent variables using the most recent EDHS datasets. The Oaxaca Blinder decomposition is one of the methods most frequently used to identify group differences in the labour market, health, health economics, and other areas.²⁹^,³⁰ To decompose the rural-urban disparities in the use of ANC/DCS into contributions that may be attributed to various determinant factors, this study uses an extended Oaxaca-Blinder decomposition technique, which is appropriate for a binary model. Thus, using the expanded Oaxaca-Blinder decomposition method suggested by Fairlie,³¹ the rural-urban disparities in the utilisation of ANC/DCS was computed as follows.

(1)

{\bar{ANC / DCS}}^{Rural} {\bar{ANC / DCS}}^{Urban} = [({\bar{X}}^{Rural} {\bar{X}}^{Rural}) {\bar{α}}^{Rural}] + [{\bar{X}}^{Urban} [{\bar{α}}^{Rural} {\bar{α}}^{Urban}]]

Where ${\bar{X}}^{j}$ is a row vector of average values of independent variables and ${\bar{α}}^{j}$ represents the vector of coefficient estimates for the type of residence (rural vs urban). An extension equation (1) to a non-linear equation, ANC/DCS = (X ${\bar{α}}^{j}$ ) is expressed as:

(2)

{\bar{ANC / DCS}}^{Rural} {\bar{ANC / DCS}}^{Urban} = [\sum_{i = 1}^{N^{Rural}} F \frac{X_{i}^{Rural} {\bar{α}}^{Rural}}{N^{Rural}} \sum_{i = 1}^{N^{Urban}} F \frac{X_{i}^{Urban} {\bar{α}}^{Rural}}{N^{Urban}}] + [\sum_{i = 1}^{N^{Urban}} F \frac{X_{i}^{Urban} {\bar{α}}^{Rural}}{N^{Urban}} \sum_{i = 1}^{N^{Urban}} F \frac{X_{i}^{Urban} {\bar{α}}^{Urban}}{N^{Urban}}]

${\bar{ANC / DCS}}^{j}$ is the average probability of the binary outcome of interest (use of ANC services or DCS) group j and F is the cumulative logistic distribution function. ‘N’ denotes the sample size for both rural and urban areas. Using the coefficient estimates from the logistic regression, the individual covariate contribution of $X_{i 1}$ to the rural-urban gaps in the use of antenatal and delivery-care services is defined as follows:

(3)

{\bar{ANC / DCS}}^{Rural} {\bar{ANC / DCS}}^{Urban} = \frac{1}{N^{Urban}} \sum_{i = 1}^{Urban} F ({\hat{α}}^{*} + X_{1 i}^{Rural} {\hat{α}}_{1}^{*} + X_{2 i}^{Rural} {\hat{α}}_{2}^{*}) - F ({\hat{α}}^{*} + X_{1 i}^{Urban} {\hat{α}}_{1}^{*} + X_{2 i}^{Rural} {\hat{α}}_{2}^{*})

The disparities in ANC and DCS utilisation can arise from either the differences in the distributions of the observable factors affecting the use of ANC and DCS (characteristics effect, the first term in the left-hand side of the equation), or the differences in the effects of these factors (coefficient effect, the second term in the left-hand side of the equation). An extended Oaxaca-Blinder technique for non-linear binary outcome variables was recently developed by Powers,³² and it was used for thorough decomposition analysis. When a binary outcome variable is included in the decomposition analysis, it is primarily suggested for use in non-linear decomposition and is a viable strategy for dealing with “path dependency” and getting over “the identification problem” connected with the selection of a reference category. The “low-outcome group” is used as a reference category by multivariate extended Oaxaca Blinder decomposition approach, which automatically derives the “high-outcome group”. Stata version 14 was used to compute data analyses for this investigation.

Results

Descriptive statistics

Table 2 presents the bivariate analysis descriptive results of the sample characteristics of the women by rural-urban place of residence. Rural women are more deprived of most of the characteristics than their urban counterparts. For instance, only 7.67 percent of urban women compared with 31.31 percent of rural women belonged to the poorest wealth quintile; 25.3 percent of urban women have no education compared with 50.86 percent of rural women. Exposure to media is relatively higher among urban (31 percent) than rural (0.43 percent) women. The overall mean age was 43 years and the individuals were sub-divided into five age categories. 34.41 percent of women had optimal ANC visits during their pregnancy in urban areas, compared to their rural counterparts (19.94 percent). Further, about 35.17 percent of rural women gave birth in health facilities compared to 41.15 percent of their urban counterparts. The descriptive analysis shows that most births in Ethiopia took place at home. About 65 percent of the rural women gave birth at home while about 41.15 percent of the urban women gave birth at health facilities with the assistance of skilled health personnel. Further, most of the rural respondents were male-headed households (77.88 percent) while 40.45 percent of the urban respondents were female-headed households. This descriptive analysis summarises the factors affecting the utilisation of ANC and delivery-care services among women in Ethiopia who were pregnant or had given birth at least once preceding the survey. Most importantly, ANC and delivery-care services utilisation had significant disparity by rural-urban place of residence (Table 2).

Table 2. Background characteristics of women who utilised maternity-care services, 2019.

Covariates	Rural (n = 5,519)	Urban (n = 1,565)	Chi-square (χ²) test
ANC visits			.001^***
<4	1,253 (80.06)	4,172 (65.59)
≥4	312 (19.94)	1,347 (34.41)
Child delivery			.001^***
Home	3578 (64.83)	921 (58.85)
Health facilities	1941 (35.17)	544 (41.15)
Age of the respondents			.001^***
15-19	1,333 (24.15)	364 (23.26)
20-24	858 (15.55)	321 (20.51)
25-29	1,057 (19.15)	324 (20.71)
30-34	747 (13.54)	215 (13.74)
35-39	694 (12.57)	158 (10.11)
40-44	483 (8.75)	99 (6.33)
45-49	347 (6.29)	84 (5.37)
Mother's education level			.001^***
No education	2,807 (50.86)	396 (25.31)
Primary	2,121 (38.43)	604 (38.59)
Secondary	449 (8.14)	303 (19.36)
Higher	142 (2.57)	262 (16.74)
Wealth index			.001^***
Poorest	1,728 (31.31)	120 (7.67)
Poorer	1,198 (21.71)	64 (4.09)
Middle	1,151 (20.86)	67 (4.28)
Rich	1,090 (19.75)	187 (11.95)
Richest	352 (6.38)	1,127 (72.01)
Mother's exposure to media uses			.001^***
(Exposed = Yes)	24 (0.43)	482 (30.82)
(Unexposed = No)	5,495 (99.57)	1,083 (69.21)
Mother's religious affiliation			.001^***
Christian	3,232 (57.56)	626 (40.01)
Muslim	2,287 (42.44)	939 (60.02)
Sex of household head			.001^***
Male	4,298 (77.88)	932 (59.55)
Female	1,221 (22.12)	633 (40.45)

*** P < .01.

Trends in disparities in the use of maternity-care services

In Ethiopia, some gains were made between 2000 and 2019 in maternity-care services utilisation (particularly ANC and DCS utilisation). In this study, the disparities in the use of antenatal and delivery-care services utilisation were described by rural-urban places of residence. Table 3 presents the trend of disparities in optimal ANC and DCS utilisation (or institutional delivery) from 2000 to 2019. The national trend of optimal ANC services use increased from 10.4 percent in 2000 to 62.4 percent in 2016, and then decreased to 43 percent in 2019 while delivery-care services rapidly increased from 5 percent in 2000 to 47.5 percent in 2019; however, the increase was contributed mostly to urban women residents.¹¹^–¹²^,¹⁴^,³³ However, there were marked differences in the use of antenatal and delivery-care services between rural and urban areas. The optimal ANC services and delivery-care services utilisations were lower for rural women, compared to urban counterparts. The trend of optimal ANC visits increased from 8.1 percent in 2005 to 14.4 percent in 2011, and dramatically increased again to 58.3 percent in 2016, and then decreased to 37.4 percent in 2019 for women rural residents. Likewise, the trend of optimal ANC services use decreased from 54.5 percent in 2005 to 45.5 percent in 2011, significantly increased to 90.1 percent in 2016, and then dramatically decreased to 58.7 percent in 2019 for women urban residents. Similarly, the trend of delivery-care services utilisation increased for rural women from 31.5 percent in 2000 to 42.4 percent in 2005; increased to 49.8 percent in 2011, significantly increased to 79.2 percent in 2016, and then decreased back to 70.4 percent in 2019. Further, the trend of delivery-care services uses increased linearly for rural women residents, irrespective of their small rate of increase.

Table 3. Trends of ANC and DCS utilisations by rural-urban, Ethiopia, 2000-2019.

Year		ANC visits				Delivery-care services (DCS)
Year	Rural	Urban	Rural-urban Differences	National	Rural	Urban	Rural-urban Differences	National
2000	21.6	66.6	-45.1	10.4	1.9	31.5	-29.6	5.0
2005	8.1	54.5	-46.4	12.2	2.3	42.4	-40.1	5.3
2011	14.4	45.5	-31.1	19.1	4.1	49.8	-45.7	9.9
2016	58.3	90.1	-31.8	62.4	19.7	79.2	-59.5	26.2
2019	37.4	58.7	-21.3	43.0	40	70.4	-30.4	47.5

Thus, the number of urban women who have utilised optimal ANC services during pregnancy and who attended their births in health facilities with the help of medical professionals (DCS) exceeded that of their rural counterparts. Trend analysis of the rural-urban gaps shows that rural women were more disadvantaged than their urban counterparts in ANC and DCS utilisation. Trend analysis shows that huge rural-urban disparities in ANC services utilisation reduced across time while DCS utilisation decreased until 2016 but increased back in 2019 (30.4 percent) (Table 3).

Decomposition results

The decomposition analysis shows that maternity-care services significantly differ by rural-urban places of residence in Ethiopia. Table 4 illustrates the estimates of an aggregate decomposition analysis of the rural-urban gaps (or disparities) in ANC and DCS utilisation. The decomposition analysis has two component gaps; “a gap due to the difference in the distribution of the observed characteristics (explained)” and “a gap due to the difference in the effect of the coefficients (unexplained)”. Likewise, the table presents the contribution of individual covariates (characteristics) to the gaps in antenatal and delivery-care services utilisation.

Table 4. Decomposition of rural-urban disparity in factors associated with ANC and DCS utilisation in Ethiopia, 2019.

Decomposition	ANC		DCS
Decomposition	Coefficients	Share (%)	Coefficients	Share (%)
Total gap (rural-urban)	.584 (.016)	100	.198 (.021)	100
Explained gap	.479 (.049)	79.43	.109 (.013)	56.36
Unexplained gap	.109 (.052)	20.57	.003 (.023)	43.63
Explained gap (Difference due to characteristics)
Mother's age at first birth	.782 (.301)	2.867	.151 (.135)	10.631
Gender of the household head^® (female)	.412 (.159)	3.124	.423 (.012)	5.925
Mother's education^® (No education)
Primary	-.013 (.021)	36.356	-.002 (.032)	38.112
Secondary	.003 (.023)^**	14.176	.001 (.012)	6.037
Higher	.014 (.012)^***	25.176	.003 (.012)^**	20.694
Household's wealth index^® (Poorest)
Poorer	-.014 (.065)^***	-32.512	-.012 (.038)^***	-38.262
Middle	.021 (.018)	4.102	.003 (.009)^**	7.236
Rich	.071 (.003)	3. 341	.001 (.007)	8.768
Richest	.053 (.012)^***	42.713	.002 (.007)^**	29.879
Mother's working status^® (No)	-.005 (.013)^**	-5.848	-.036 (.045)^**	-3.184
Mother's exposure to media use^® (No)	.023 (.022)^**	10.952	-.015 (.004)^**	7.826
Number of children under-five years	-.021 (.036)	-4.894	-.003 (.062)^*	-5.062
Mother's religion^® (Christian)	-.019 (.002)^***	-11.460	.007 (.003)^**	-6.275
Unexplained gap (Difference due to coefficients)
Mother's age at first birth	.002 (.091)	4.568	.003 (.022)	9.013
Gender of the household head^® (female)	.005 (.008)	2.881	.010 (.015)	3.567
Mother's education^® (No education)
Primary	.002 (.003)^**	3.073	.005 (.021)	1.122
Secondary	.001 (.002)	.342	.013 (.032)	2.021
Higher	-.004 (.034)^**	-7.821	-.002 (.002)^**	-11.262
Household's wealth index^® (Poorest)
Poorer	.028 (.001) ^**	67.782	.041 (.021)^**	14.881
Middle	.071 (.741)	12.013	.027 (.006)	8.521
Rich	.087 (.141)	2.362	.005 (.032)	5.392
Richest	.059 (.016)^**	9.834	.072 (.006)^***	6.134
Mother's working status^® (Not working)	-.251 (.421)	-4.572	.012 (.029)	4.112
Mother's exposure to media use^® (No)	-.034 (.051)^*	-5.863	.002 (.013)^*	2.691
Number of children under-five years	-.009 (.021)	-2.771	-.008 (.004)	-3.693
Mother's religion^® (Christian)	.004 (.033)	.792	.012 (.013)	3.214
Number of observation	7,084		7,084

* P < .10.

** P < .05.

*** P < .01.

Rural-urban disparities in the factors associated with optimal ANC utilisation

Overall, the analysis revealed about 79.4 percent of disparities between rural and urban areas in ANC services utilisation, explained by households’ economic status which accounted for 43 percent of the gap in ANC services use, which is more than half of the total explained gap (76.42 percent). Likewise, maternal education has made significant contributions to the rural-urban disparities in the use of ANC services. The analysis indicates that women with a secondary level of education explained 14.2 percent of rural-urban gaps in ANC services use. Similarly, the analysis revealed that women with a higher educational level explained the rural-urban gap by 25.2 percent. Further, the proportional differences among women having a relatively large number of children under five years old (5 percent), a woman currently working or employed (6 percent), women exposed to media use (11 percent), being Muslim women (11.5 percent), and being a woman belonging to a low-income household (32.5 percent) explained the rural-urban disparities in ANC services utilisation.

Regarding the effects of covariate differences (differences due to coefficients) for ANC service utilisation, the results indicated the differences in coefficient effects (differences due to coefficients) accounted for 20.6 percent of the observed disparities between rural and urban areas in antenatal care service utilisation in Ethiopia. In particular, the effect of secondary and higher maternal levels of education was responsible for narrowing the disparities between rural and urban areas in ANC service utilisation by 14.2 percent and 25.2 percent, respectively if the rural women’s educational level enhanced from no education to primary, to secondary, and then to a higher level of education, respectively. Whereas, the effect of women’s primary and higher educational levels was responsible for widening the rural-urban gap in ANC services use by 3 percent and 8 percent, respectively. Also, the effect of the poor (68 percent) and the richest (10 percent) economic status of the women contributed to narrowing the rural-urban disparities in ANC service utilisation if the economic status of rural women enhanced from poorer to middle to rich, and then to the richest wealth level as their urban counterparts.

Rural-urban disparities in the factors associated with DCS utilisation

The analyses indicated that 56.4 percent of the rural-urban disparities in delivery-care services utilisation were attributable to the differences in the distribution of the observed covariates (characteristics effect). The household’s economic status (Richest category: 30 percent), mother’s higher level of education (Higher category: 21 percent), and women’s exposure to media use (8 percent) continued to be the main explanatory determinants of the rural-urban disparity in DCS utilisation. On the other hand, the proportional differences in women currently working (3.2 percent), being Muslim women (6.3 percent), women having a relatively large number of children under five years old (5.1 percent), and women who belong to households in the poorer wealth category (38.3 percent) explained the disparities in delivery-care services utilisation between rural and urban areas.

Regarding the effects of covariate differences (differences due to coefficients) for delivery-care services, the detailed decomposition analysis found that differences in coefficient effects (differences due to coefficients) accounted for 43.6 percent of the observed rural-urban disparities in delivery-care services utilisation in Ethiopia. The effect of poorer (15 percent) and richest (7 percent) households’ wealth status contributed to narrowing the rural-urban disparities in DCS if the wealth status of women who belong to rural households enhanced from poorer to middle, to rich, and then from rich to the richest wealth level as their urban women counterparts. Likewise, the effect of a higher maternal educational level was responsible for the widening of the disparities in the use of delivery-care services by 11 percent between rural and urban areas. Furthermore, the effect of mothers’ exposure to media use widened the gaps in DCS utilisation by 3 percent between rural and urban areas (Table 4).

Discussion

There are notable differences in the usage of maternity-care services (the use of ANC, delivery-care services, postnatal-care services, etc.) by rural versus urban areas of residence and by geographic regions in developing nations, including Ethiopia. In comparison to women in rural areas, urban women use maternity-care services more frequently in terms of using antenatal, delivery-care services, and postnatal-care services utilisation.¹¹^,¹⁶^,¹⁸^,³⁴ The location of a woman’s domicile affects her ability to receive and utilise maternity-care services as well as her access to basic information about health conditions and other aspects of life.¹⁴ Infant and mother mortality can be avoided by giving birth in a health facility with the support of trained health workers.¹³ Narrowing or minimising the socioeconomic disparities in maternity-care services utilisation mainly among deprived (rural) women is crucial in Ethiopia. Thus, this study tries to examine the determinants of rural-urban disparity in antenatal and delivery-care services utilisation in Ethiopia using an extended Oaxaca-Blinder decomposition technique, on which few studies have been conducted.

Antenatal care services (ANC) utilisation

Overall, maternity-care services in Ethiopia, notably the use of ANC and DCS have improved slightly, reflecting an improvement in access to and coverage of these services. However, over the last two decades (2000-2019), there have been noticeable differences in the use of these services between rural and urban areas. This disparity may be brought on by households’ lower economic status, having less access to media use, the predominance of religion, the lack of accessible transportation, and the low level of maternal education in Ethiopia.⁴^,⁸^,¹⁵^,²⁰^,²²^,²⁶^,²⁷^,³⁵ In general, urban-dwelling women are more likely than rural-dwelling women to use ANC services.¹⁶^,³⁵^,³⁶

The decomposition analysis revealed that more than three quarters (79.4 percent) of the disparities in the use of ANC services between rural and urban areas in Ethiopia was attributed to differences in the distribution of covariates between the uses of ANC groups, holding the coefficients effect constant. This implies that to reduce the rural-urban disparities in the use of optimal ANC services, the contribution of the observed characteristics changes (characteristics effect) was more important than behaviour changes (coefficients effect). Among the decomposed covariates, women’s economic and educational status were the main contributors to the gaps between rural and urban areas in the use of ANC services. The results of this study prove that households’ economic status is the most important determinant factor explaining rural-urban gap in making use of optimal ANC services. Enhancing the economic status of deprived rural women could reduce the financial barrier of that household to the use of ANC services and help reduce the high rate of child and maternal deaths. The wealth status of the households made the largest contribution to the rural-urban gap, which can be explained by the larger income-related differences between urban and rural areas. Women’s economic status accounts for a large portion of the socioeconomic difference in different maternal health outcomes across many Sub-Saharan African countries.⁶^,⁷^,³⁷^–⁴⁰ Women in more affluent households receive more antenatal care services and give birth in health facilities than do women from lower economic status households, which lowers the risk of maternal and child deaths.¹⁰^,³⁷

Additionally, the results reveal that disparities in the education levels of women were responsible for the gaps between rural and urban areas in the use of optimal ANC services. In particular, the results show that women with a higher level of education explained the rural-urban gap in the use of ANC services. The reason could be that women of reproductive age with higher levels of education have better access to basic health information, more decision-making autonomy, and can access to healthcare services.¹⁰ An educated woman is better able to decide whether to seek antenatal care and other healthcare services that will have a greater effect on her survival and the survival of her child.¹⁰ The findings of this study are in line with previous studies that found maternal educational attainment to be a key determinant of rural-urban disparities in the utilisation of ANC services.⁶^,¹⁰^,¹⁶^,²³^,³⁵^,³⁷ To increase the use of ANC services, health-related interventions must enhance the educational status of women in rural areas, which will minimise the disparities between rural and urban areas. In general, women with a higher educational level have better socioeconomic status, better knowledge of healthcare services, and more autonomy in decision-making in maternity-care services utilisation.¹⁰^,⁴¹

The exposure of a woman to media use was another factor that contributed to the gap in optimal ANC service utilisation between rural and urban areas. Women from rural households in Ethiopia have less exposure to media use.¹¹ Women’s exposure to media had a strong association with the maternal level of education. For example, compared to 4 percent of women with only primary education, 20 percent of women with a higher level of education reported being exposed to media use. Additionally, the economic status of households has an impact on media exposure. Compared to 10 percent of women in the highest economic status, only 1 percent of women in the lowest economic status got media exposure.¹¹ The results of this study reveal that the proportional differences in women’s media use were responsible for rural-urban disparities in ANC utilisation. This result was consistent with those of earlier studies, which suggested that women’s media use played a part in explaining the disparities in maternity-care services between rural and urban areas.²³^,³⁷

Delivery-care services (DCS) utilisation

The decomposition analyses indicate that more than half (56.4 percent) of the observed disparities in the use of delivery-care services between rural and urban areas can be attributed to differences in the distribution of covariates, holding the coefficients effect constant. A woman who uses antenatal care services during pregnancy can give birth in health facilities.⁸ Economic status, education, mothers’ media exposure, mothers’ employment status, and the number of living children under five years old were found to be the main contributing factors to explain the rural-urban disparities when socioeconomic factors were taken into account with the use of delivery care services. The results of this study specifically show that the maternal educational level was the most significant factor in explaining the disparities in delivery care services utilisation between rural and urban areas in Ethiopia. Education is crucial in utilising health facilities for birth. A woman with greater education can readily understand the effects of healthcare services and acquire new healthcare information.⁶^,²⁸^,³⁷^,⁴² The majority of Ethiopian women (40 percent) lacked formal education, and this varied by place of residence. Compared to 25 percent of urban women, about 48 percent of women in rural areas lack a formal education.²⁸ Compared to women without an education, those with secondary education or higher are more likely to give birth in a health facility.¹⁴ The findings of this study were also supported by other studies that indicated that women’s level of education explained the rural-urban disparities in delivery-care services utilisation.⁶^,³⁵^,³⁷ Therefore, raising maternal education levels in Ethiopia’s rural areas could encourage the use of delivery care facilities and lessen the gaps between rural and urban areas. In general, urban women, particularly Ethiopian women, are more likely than their rural counterparts to give birth in health facilities.¹⁴ This might be a result of urban women’s potential for superior antenatal education, media exposure, and economic position. These results are in line with those of earlier research.³⁸^,³⁹

In developing countries including Ethiopia, education is associated with the economic status of the household. The likelihood of an educated household having a stable economy is high. Due to the cost involved, most maternity-care services are often restricted to women of affluent households.⁴³ These were also supported by the results of this study, which showed that women with secondary and higher levels of education were more likely to use delivery-care services than women with no formal education. The greater impact of a woman’s education on the urban-rural disparities can be understood by the correlation between education and lower-income generation. This is likely because rural women work primarily in the agricultural sector, where employment is frequently irregular and income is low. Low maternal education rates among women in rural areas may impede women’s efforts to promote their health through limited education, which affects the usage of maternity-care services.³⁵^,⁴⁴ The findings of the present study, which shows that women with secondary and higher levels of education were more likely to use delivery-care services than women with no formal education, further supported these findings.

The findings of this study prove that economic status disparities between rural and urban households account for most of the overall gaps in delivery-care services utilisation in Ethiopia. This result is consistent with other research that discovered one of the most significant predictors of rural-urban disparities in the utilisation of delivery-care services to be women’s economic status. The likelihood that a woman will use health facilities for childbirth increases with her economic status.³⁵^,³⁹ This suggests that redistribution of accumulated income, enhancing antenatal care, and women’s access to media use would help reduce the rural-urban disparities in delivery-care services utilisation and enhancing mother and child health in Ethiopia’s rural areas. Several rural women gave birth at home due to financial restrictions even though the Ethiopian government offered free maternity and child healthcare services to increase the use of ANC and delivery care services.¹¹

Maternity-care services are essential for the mother’s and her baby’s health and survival as well as for lowering their mortality during pregnancy and after delivery.¹⁴ This study’s research of national trends reveals a rising tendency in the use of delivery care services over the past 20 years (2000-2019). The findings also indicate that women’s media exposure played a role in the rural-urban disparity in delivery care services utilisation. Rural women use birthing centres badly because of the lack of knowledge.⁴⁴ The findings of this study were consistent with those of earlier studies.¹⁵^,³⁷ Women who live in rural low-income households had limited access to and utilisation of maternity-care services. Because it can be challenging to acquire maternity-care services, they are more likely to give birth at home.⁹^,²⁷^,⁴² Other earlier research reinforced the fact that they lack education, which led to a lack of usage of antenatal and delivery-care facilities.²⁷ Women with lower levels of education, those from lower-income households, and those who live in rural areas use maternity-care services less frequently. The rural population appears to have greater death rates than their urban counterparts due to variations in the use of maternal-care services.³²

The proportion of children under the age of five, maternal religious beliefs, and the current employment status of mothers, on the other hand, all played a role in explaining disparities in the use of ANC and delivery-care services between rural and urban areas. Comparing a Muslim woman to a Christian woman, being a Muslim woman had a large counteracting effect on closing the rural-urban divide in the use of ANC and delivery care services. This emphasises the requirement for additional research to examine the part played by religious beliefs in the usage of maternity care services. This result is comparable to earlier studies that showed a high correlation between religious beliefs and the use of maternity-care services.⁴⁵ The findings of this study also showed that the proportional disparities in the number of children under the age of five among women reduced the disparities between the usage of antenatal and delivery-care services in rural and urban areas. Other earlier research produced similar findings.⁶ Women’s employment status also has a significant role in the rural-urban disparity in the use of maternity care services. These results are consistent with those from earlier research.⁴⁴

Previous studies in Ethiopia have also reported rural-urban disparities in maternity-care services utilisations, with the privileged urban women having better economic status and better health care services such as ANC services, institutional delivery, and postnatal-care services utilisation.⁴^,¹⁵^,¹⁷^,¹⁹^,³⁶ Improving rural women’s economic and educational status within the country could contribute to minimising the observed rural-urban gap in maternity-care services utilisations. Although this study’s decomposition analyses explained most of rural-urban disparities in ANC and DCS utilisation, the unexplained components for ANC services (20.6 percent) and for DCS utilisations (43.6 percent) signify the need for further studies to identify the contributory factors to the disparities in these outcome variables. For example, the distance to nearest health facilities, parents’ education, and women’s autonomy in decision-making might also explain the rural-urban disparities but were not included due to their absence in the 2019 Ethiopia DHS dataset.

Strengths and limitations

The use of data from the most recent nationally representative survey makes the findings of this study generalizable nationwide and comparable to other previous studies. Further, the large sample size, high response rate, and the rigorous statistical method utilisation in this study provide more reliable estimates. This study did have, however some drawbacks. First, this study used cross-sectional secondary data, which could limit how the results were interpreted in terms of causality. Second, the data was based on self-reported maternity-care services utilisation which is subject to measurement errors and bias in reporting. Third, the data excluded male participants and was restricted to women between the ages of 15 and 49 years old. Also, some variables or observations had missing information during data cleaning and analysis that were omitted for model-building purposes. Finally, the most recent changes in maternity-care services utilisation could not be captured in this study because the data came from the 2019 Ethiopia DHS. The results of this study should be considered in light of these limitations despite their existence.

Conclusion and recommendation

Although Ethiopia is slightly improving the utilisation of maternity-care services among women of reproductive age (15 to 49 years) over the last two decades (2000 – 2019), ANC and DCS utilisation remain disproportionately lower among women in rural and urban areas. The purpose of this study was to explore the factors contributing to the rural-urban disparities in ANC and DCS utilisation. The results indicate that there were significant rural-urban disparities in optimal ANC and DCS utilisation, with large disparities being attributable to the differences in households’ economic status, educational level, and maternal exposure to media use. The results of this study confirm that women who have no formal education and belong to low-income rural households have low use of antenatal care and health facility delivery services. The results of this study can be used to minimise disparities in the use of antenatal and delivery-care services findings which apply to reducing the disparities in antenatal and delivery-care services, as well as to help Ethiopia achieve the SDGs and reduce maternal and infant mortality. To further enhance maternity-care services utilisation in Ethiopia, there is a need to enhance mainly the economic and educational status of disadvantaged rural women.

Data availability

The dataset used for this study is collected and organised by the Demographic and Health Survey (DHS) Program. The data is available for researchers on request through the online permission registration at https://www.dhsprogram.com/data/dataset_admin/login_main.cfm and getting access links. We selected Ethiopia (under select country button), then clicked Download under “Survey Dataset” Phase DHS-VIII for Ethiopia 2019. The ET_2019_INTERIMDHS_03022023_1227_134385 dataset; ETHR81DT filename; ETHRFL.DTA ‘Stata data file’ has been used for analysis in this study.²⁸

References

1. World Health Organization (WHO): Trends in maternal mortality 2000 to 2020: estimates by WHO, UNICEF, UNFPA, World Bank Group and UNDESA/Population Division. Geneva: World Health Organization; 2023. Licence: CC BY-NC-SA 3.0 IGO. 2023.
2. WHO: Provision of effective antenatal care: Integrated Management of Pregnancy and Child Birth (IMPAC). Geneva, Switzerland: Standards for Maternal and Neonatal Care (1.6), Department of Making Pregnancy Safer; 2006.
3. Dewau R, Angaw DA, Kassa GM, et al.: Urban-rural disparities in institutional delivery among women in East Africa: A decomposition analysis. PLoS One. 2021 Jul 30; 16(7): e0255094. PubMed Abstract | Publisher Full Text | Free Full Text
4. Yoseph M, Abebe SM, Mekonnen FA: Institutional delivery services utilization and its determinant factors among women who gave birth in the past 24 months in Southwest Ethiopia. BMC Health Serv. Res. 2020 Dec; 20(1): 1. PubMed Abstract | Publisher Full Text | Free Full Text
5. Ahinkorah BO, Aboagye RG, Seidu AA, et al.: Rural–urban disparities in caesarean deliveries in sub-Saharan Africa: a multivariate non-linear decomposition modelling of Demographic and Health Survey data. BMC Pregnancy Childbirth. 2022 Sep 17; 22(1): 709. PubMed Abstract | Publisher Full Text | Free Full Text
6. Laksono AD, Rukmini R, Wulandari RD: Regional disparities in antenatal care utilization in Indonesia. PLoS One. 2020 Feb 13; 15(2): e0224006. PubMed Abstract | Publisher Full Text | Free Full Text
7. Novignon J, Ofori B, Tabiri KG, et al.: Socioeconomic inequalities in maternal health care utilization in Ghana. Int. J. Equity Health. 2019 Dec; 18: 141–141. PubMed Abstract | Publisher Full Text | Free Full Text
8. Bobo FT, Yesuf EA, Woldie M: Inequities in utilization of reproductive and maternal health services in Ethiopia. Int. J. Equity Health. 2017 Dec; 16(1): 105–108. PubMed Abstract | Publisher Full Text | Free Full Text
9. Yebyo H, Alemayehu M, Kahsay A: Why do women deliver at home? Multilevel modeling of Ethiopian National Demographic and Health Survey data. PLoS One. 2015 Apr 15; 10(4): e0124718. PubMed Abstract | Publisher Full Text | Free Full Text
10. Wulandari RD, Laksono AD, Rohmah N: Urban-rural disparities of antenatal care in South East Asia: a case study in the Philippines and Indonesia. BMC Public Health. 2021 Dec; 21(1): 1221–1229. PubMed Abstract | Publisher Full Text | Free Full Text
11. CSA [Ethiopia] & ICF: Ethiopia Demographic and Health Survey 2016. Addis Ababa, Ethiopia, and Rockville, Maryland, USA: CSA and ICF; 2016.
12. World health statistics: Monitoring health for the SDGs, sustainable development goals. Geneva: World Health Organization; 2022. Licence: CC BY-NC-SA 3.0 IGO.
13. CSA [Ethiopia] & ICF: Ethiopia Demographic and Health Survey 2011. Addis Ababa, Ethiopia and Calverton, Maryland, USA: Central Statistical Agency and ICF International; 2012.
14. EPHI [Ethiopia] & ICF: Ethiopia Mini Demographic and Health Survey 2019: Key Indicators. Rockville, Maryland, USA: EPHI and ICF; 2019.
15. Mekonnen T, Dune T, Perz J, et al.: Trends and determinants of antenatal care service use in Ethiopia between 2000 and 2016. Int. J. Environ. Res. Public Health. 2019 Mar; 16(5): 748. PubMed Abstract | Publisher Full Text | Free Full Text
16. Anwar I, Nababan HY, Mostari S, et al.: Trends and inequities in use of maternal health care services in Bangladesh, 1991-2011. PLoS One. 2015 Mar 23; 10(3): e0120309. PubMed Abstract | Publisher Full Text | Free Full Text
17. Gezae KE, Berhie KA, Gebresilassie AA, et al.: Contextual Disparity on Trend and Determinants of Optimal Antenatal Care (ANC4+) Use for Women in Eastern Tigray, Ethiopia: Evidence from KA-HDSS Database. Int. J. Women’s Health. 2023 Dec 31; 15: 511–521. Publisher Full Text
18. Lukwa AT, Siya A, Odunitan-Wayas FA, et al.: Decomposing maternal socioeconomic inequalities in Zimbabwe; leaving no woman behind. BMC Pregnancy Childbirth. 2022 Dec; 22(1): 236–239. PubMed Abstract | Publisher Full Text | Free Full Text
19. Alemayehu M, Gebrehiwot TG, Medhanyie AA, et al.: Utilization and factors associated with antenatal, delivery and postnatal Care Services in Tigray Region, Ethiopia: a community-based cross-sectional study. BMC Pregnancy Childbirth. 2020 Dec; 20(1): 333–334. PubMed Abstract | Publisher Full Text | Free Full Text
20. Zegeye B, Ahinkorah BO, Ameyaw EK, et al.: Disparities in use of skilled birth attendants and neonatal mortality rate in Guinea over two decades. BMC Pregnancy Childbirth. 2022 Jan 21; 22(1): 56. PubMed Abstract | Publisher Full Text | Free Full Text
21. Mekonnen Y, Mekonnen A: Factors influencing the use of maternal healthcare services in Ethiopia. J. Health Popul. Nutr. 2003 Dec; 21(4): 374–382. PubMed Abstract Reference Source
22. Tsegay Y, Gebrehiwot T, Goicolea I, et al.: Determinants of antenatal and delivery care utilization in Tigray region, Ethiopia: a cross-sectional study. Int. J. Equity Health. 2013 Dec; 12: 1. PubMed Abstract | Publisher Full Text | Free Full Text
23. Yesuf EA, Calderon-Margalit R: Disparities in the use of antenatal care service in Ethiopia over a period of fifteen years. BMC Pregnancy Childbirth. 2013 Dec; 13(1): 1. Publisher Full Text
24. Yaya S, Bishwajit G, Ekholuenetale M, et al.: Urban-rural difference in satisfaction with primary healthcare services in Ghana. BMC Health Serv. Res. 2017 Dec; 17(1): 776–779. PubMed Abstract | Publisher Full Text | Free Full Text
25. Samuel O, Zewotir T, North D: Decomposing the urban–rural inequalities in the utilisation of maternal health care services: evidence from 27 selected countries in Sub-Saharan Africa. Reprod. Health. 2021 Dec; 18(1): 1–2. Publisher Full Text
26. Arba MA, Darebo TD, Koyira MM: Institutional delivery service utilization among women from rural districts of Wolaita and Dawro zones, southern Ethiopia; a community based cross-sectional study. PLoS One. 2016 Mar 17; 11(3): e0151082. PubMed Abstract | Publisher Full Text | Free Full Text
27. Mekonnen ZA, Lerebo WT, Gebrehiwot TG, et al.: Multilevel analysis of individual and community level factors associated with institutional delivery in Ethiopia. BMC. Res. Notes. 2015 Dec; 8(1): 376–379. PubMed Abstract | Publisher Full Text | Free Full Text
28. EDHS: DHS program. [dataset]. ET_2019_INTERIMDHS_03022023_1227_134385.
29. Blinder AS: Wage discrimination: reduced form and structural estimates. J. Hum. Resour. 1973 Oct; 8(4): 436–455. Publisher Full Text
30. Oaxaca R: Male-female wage differentials in urban labor markets. Int. Econ. Rev. 1973 Oct 1; 14: 693–709. Publisher Full Text Reference Source
31. Fairlie RW: An extension of the Blinder-Oaxaca decomposition technique to logit and probit models. J. Econ. Soc. Meas. 2005 Jan 1; 30(4): 305–316. Publisher Full Text Reference Source
32. Powers DA, Yoshioka H, Yun MS: mvdcmp: Multivariate decomposition for nonlinear response models. Stata J. 2011 Dec; 11(4): 556–576. Publisher Full Text
33. CSA [Ethiopia] & ORC Macro: Ethiopia Demographic and Health Survey 2005. Addis Ababa, Ethiopia and Calverton, Maryland, USA: Central Statistical Agency & ORC Macro; 2006.
34. Kenya National Bureau of Statistics: The DHS Program, ICF International Rockville, Maryland U. Kenya Demographic and Health Survey 2014. Nairobi; Kenya Rockville, Maryland, USA: 2014.
35. Bintabara D, Basinda N: Twelve-year persistence of inequalities in antenatal care utilisation among women in Tanzania: a decomposition analysis of population-based cross-sectional surveys. BMJ Open. 2021 Apr 1; 11(4): e040450. PubMed Abstract | Publisher Full Text | Free Full Text
36. Tekelab T, Chojenta C, Smith R, et al.: Factors affecting utilization of antenatal care in Ethiopia: a systematic review and meta-analysis. PLoS One. 2019 Apr 11; 14(4): e0214848. PubMed Abstract | Publisher Full Text | Free Full Text
37. Afful-Mensah G, Nketiah-Amponsah E, Boakye-Yiadom L: Rural-urban differences in the utilization of maternal healthcare in Ghana: the case of antenatal and delivery services. Afr. Soc. Sci. Rev. 2014; 4(1): 58–73. Publisher Full Text Reference Source
38. Ali B, Dhillon P, Mohanty SK: Inequalities in the utilization of maternal health care in the pre-and post-National Health Mission periods in India. J. Biosoc. Sci. 2020 Mar; 52(2): 198–212. PubMed Abstract | Publisher Full Text
39. Amporfu E, Grépin KA: Measuring and explaining changing patterns of inequality in institutional deliveries between urban and rural women in Ghana: a decomposition analysis. Int. J. Equity Health. 2019 Dec; 18(1): 122–123. PubMed Abstract | Publisher Full Text | Free Full Text
40. Nwosu CO, Ataguba JE: Socioeconomic inequalities in maternal health service utilisation: a case of antenatal care in Nigeria using a decomposition approach. BMC Public Health. 2019 Dec; 19(1): 1491–1493. PubMed Abstract | Publisher Full Text | Free Full Text
41. Ba DM, Ssentongo P, Agbese E, et al.: Prevalence and predictors of contraceptive use among women of reproductive age in 17 sub-Saharan African countries: a large population-based study. Sex. Reprod. Healthc. 2019 Oct 1; 21: 26–32. PubMed Abstract | Publisher Full Text
42. Nababan HY, Hasan M, Marthias T, et al.: Trends and inequities in use of maternal health care services in Indonesia, 1986–2012. Int. J. Women’s Health. 2017 Dec 29; 10: 11–24. PubMed Abstract | Publisher Full Text | Free Full Text
43. Hodge A, Firth S, Bermejo R, et al.: Utilisation of health services and the poor: deconstructing wealth-based differences in facility-based delivery in the Philippines. BMC Public Health. 2016 Dec; 16(1): 522–523. PubMed Abstract | Publisher Full Text | Free Full Text
44. Weinhold I, Gurtner S: Rural-urban differences in determinants of patient satisfaction with primary care. Soc. Sci. Med. 2018 Sep 1; 212: 76–85. PubMed Abstract | Publisher Full Text
45. Ganle JK: Why Muslim women in Northern Ghana do not use skilled maternal healthcare services at health facilities: a qualitative study. BMC Int. Health Hum. Rights. 2015 Dec; 15: 10–16. PubMed Abstract | Publisher Full Text | Free Full Text

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¹ Aksum University, Aksum, Tigray, Ethiopia
² Tigray Institute of Policy Studies (TIPS), Mekelle, Tigray, Ethiopia

Yibrah Hagos Gebresilassie
Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Software, Supervision, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing

Araya Mebrahtu Teka
Roles: Methodology, Supervision, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

The author(s) declared that no grants were involved in supporting this work.

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Gebresilassie YH and Teka AM. What drives the rural‑urban disparities in maternity‑care services utilisation? Evidence from Ethiopia [version 1; peer review: awaiting peer review]. F1000Research 2023, 12:666 (https://doi.org/10.12688/f1000research.134166.1)

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[1] 1. World Health Organization (WHO): Trends in maternal mortality 2000 to 2020: estimates by WHO, UNICEF, UNFPA, World Bank Group and UNDESA/Population Division. Geneva: World Health Organization; 2023. Licence: CC BY-NC-SA 3.0 IGO. 2023.

[2] 2. WHO: Provision of effective antenatal care: Integrated Management of Pregnancy and Child Birth (IMPAC). Geneva, Switzerland: Standards for Maternal and Neonatal Care (1.6), Department of Making Pregnancy Safer; 2006.

[3] 3. Dewau R, Angaw DA, Kassa GM, et al.: Urban-rural disparities in institutional delivery among women in East Africa: A decomposition analysis. PLoS One. 2021 Jul 30; 16(7): e0255094. PubMed Abstract | Publisher Full Text | Free Full Text

[4] 4. Yoseph M, Abebe SM, Mekonnen FA: Institutional delivery services utilization and its determinant factors among women who gave birth in the past 24 months in Southwest Ethiopia. BMC Health Serv. Res. 2020 Dec; 20(1): 1. PubMed Abstract | Publisher Full Text | Free Full Text

[5] 5. Ahinkorah BO, Aboagye RG, Seidu AA, et al.: Rural–urban disparities in caesarean deliveries in sub-Saharan Africa: a multivariate non-linear decomposition modelling of Demographic and Health Survey data. BMC Pregnancy Childbirth. 2022 Sep 17; 22(1): 709. PubMed Abstract | Publisher Full Text | Free Full Text

[6] 6. Laksono AD, Rukmini R, Wulandari RD: Regional disparities in antenatal care utilization in Indonesia. PLoS One. 2020 Feb 13; 15(2): e0224006. PubMed Abstract | Publisher Full Text | Free Full Text

[7] 7. Novignon J, Ofori B, Tabiri KG, et al.: Socioeconomic inequalities in maternal health care utilization in Ghana. Int. J. Equity Health. 2019 Dec; 18: 141–141. PubMed Abstract | Publisher Full Text | Free Full Text

[8] 8. Bobo FT, Yesuf EA, Woldie M: Inequities in utilization of reproductive and maternal health services in Ethiopia. Int. J. Equity Health. 2017 Dec; 16(1): 105–108. PubMed Abstract | Publisher Full Text | Free Full Text

[9] 9. Yebyo H, Alemayehu M, Kahsay A: Why do women deliver at home? Multilevel modeling of Ethiopian National Demographic and Health Survey data. PLoS One. 2015 Apr 15; 10(4): e0124718. PubMed Abstract | Publisher Full Text | Free Full Text

[10] 10. Wulandari RD, Laksono AD, Rohmah N: Urban-rural disparities of antenatal care in South East Asia: a case study in the Philippines and Indonesia. BMC Public Health. 2021 Dec; 21(1): 1221–1229. PubMed Abstract | Publisher Full Text | Free Full Text

[11] 11. CSA [Ethiopia] & ICF: Ethiopia Demographic and Health Survey 2016. Addis Ababa, Ethiopia, and Rockville, Maryland, USA: CSA and ICF; 2016.

[12] 12. World health statistics: Monitoring health for the SDGs, sustainable development goals. Geneva: World Health Organization; 2022. Licence: CC BY-NC-SA 3.0 IGO.

[13] 13. CSA [Ethiopia] & ICF: Ethiopia Demographic and Health Survey 2011. Addis Ababa, Ethiopia and Calverton, Maryland, USA: Central Statistical Agency and ICF International; 2012.

[14] 14. EPHI [Ethiopia] & ICF: Ethiopia Mini Demographic and Health Survey 2019: Key Indicators. Rockville, Maryland, USA: EPHI and ICF; 2019.

[15] 15. Mekonnen T, Dune T, Perz J, et al.: Trends and determinants of antenatal care service use in Ethiopia between 2000 and 2016. Int. J. Environ. Res. Public Health. 2019 Mar; 16(5): 748. PubMed Abstract | Publisher Full Text | Free Full Text

[16] 16. Anwar I, Nababan HY, Mostari S, et al.: Trends and inequities in use of maternal health care services in Bangladesh, 1991-2011. PLoS One. 2015 Mar 23; 10(3): e0120309. PubMed Abstract | Publisher Full Text | Free Full Text

[17] 17. Gezae KE, Berhie KA, Gebresilassie AA, et al.: Contextual Disparity on Trend and Determinants of Optimal Antenatal Care (ANC4+) Use for Women in Eastern Tigray, Ethiopia: Evidence from KA-HDSS Database. Int. J. Women’s Health. 2023 Dec 31; 15: 511–521. Publisher Full Text

[18] 18. Lukwa AT, Siya A, Odunitan-Wayas FA, et al.: Decomposing maternal socioeconomic inequalities in Zimbabwe; leaving no woman behind. BMC Pregnancy Childbirth. 2022 Dec; 22(1): 236–239. PubMed Abstract | Publisher Full Text | Free Full Text

[19] 19. Alemayehu M, Gebrehiwot TG, Medhanyie AA, et al.: Utilization and factors associated with antenatal, delivery and postnatal Care Services in Tigray Region, Ethiopia: a community-based cross-sectional study. BMC Pregnancy Childbirth. 2020 Dec; 20(1): 333–334. PubMed Abstract | Publisher Full Text | Free Full Text

[20] 20. Zegeye B, Ahinkorah BO, Ameyaw EK, et al.: Disparities in use of skilled birth attendants and neonatal mortality rate in Guinea over two decades. BMC Pregnancy Childbirth. 2022 Jan 21; 22(1): 56. PubMed Abstract | Publisher Full Text | Free Full Text

[21] 21. Mekonnen Y, Mekonnen A: Factors influencing the use of maternal healthcare services in Ethiopia. J. Health Popul. Nutr. 2003 Dec; 21(4): 374–382. PubMed Abstract Reference Source

[22] 22. Tsegay Y, Gebrehiwot T, Goicolea I, et al.: Determinants of antenatal and delivery care utilization in Tigray region, Ethiopia: a cross-sectional study. Int. J. Equity Health. 2013 Dec; 12: 1. PubMed Abstract | Publisher Full Text | Free Full Text

[23] 23. Yesuf EA, Calderon-Margalit R: Disparities in the use of antenatal care service in Ethiopia over a period of fifteen years. BMC Pregnancy Childbirth. 2013 Dec; 13(1): 1. Publisher Full Text

[24] 24. Yaya S, Bishwajit G, Ekholuenetale M, et al.: Urban-rural difference in satisfaction with primary healthcare services in Ghana. BMC Health Serv. Res. 2017 Dec; 17(1): 776–779. PubMed Abstract | Publisher Full Text | Free Full Text

[25] 25. Samuel O, Zewotir T, North D: Decomposing the urban–rural inequalities in the utilisation of maternal health care services: evidence from 27 selected countries in Sub-Saharan Africa. Reprod. Health. 2021 Dec; 18(1): 1–2. Publisher Full Text

[26] 26. Arba MA, Darebo TD, Koyira MM: Institutional delivery service utilization among women from rural districts of Wolaita and Dawro zones, southern Ethiopia; a community based cross-sectional study. PLoS One. 2016 Mar 17; 11(3): e0151082. PubMed Abstract | Publisher Full Text | Free Full Text

[27] 27. Mekonnen ZA, Lerebo WT, Gebrehiwot TG, et al.: Multilevel analysis of individual and community level factors associated with institutional delivery in Ethiopia. BMC. Res. Notes. 2015 Dec; 8(1): 376–379. PubMed Abstract | Publisher Full Text | Free Full Text

[28] 28. EDHS: DHS program. [dataset]. ET_2019_INTERIMDHS_03022023_1227_134385.

[29] 29. Blinder AS: Wage discrimination: reduced form and structural estimates. J. Hum. Resour. 1973 Oct; 8(4): 436–455. Publisher Full Text

[30] 30. Oaxaca R: Male-female wage differentials in urban labor markets. Int. Econ. Rev. 1973 Oct 1; 14: 693–709. Publisher Full Text Reference Source

[31] 31. Fairlie RW: An extension of the Blinder-Oaxaca decomposition technique to logit and probit models. J. Econ. Soc. Meas. 2005 Jan 1; 30(4): 305–316. Publisher Full Text Reference Source

[32] 32. Powers DA, Yoshioka H, Yun MS: mvdcmp: Multivariate decomposition for nonlinear response models. Stata J. 2011 Dec; 11(4): 556–576. Publisher Full Text

[33] 33. CSA [Ethiopia] & ORC Macro: Ethiopia Demographic and Health Survey 2005. Addis Ababa, Ethiopia and Calverton, Maryland, USA: Central Statistical Agency & ORC Macro; 2006.

[34] 34. Kenya National Bureau of Statistics: The DHS Program, ICF International Rockville, Maryland U. Kenya Demographic and Health Survey 2014. Nairobi; Kenya Rockville, Maryland, USA: 2014.

[35] 35. Bintabara D, Basinda N: Twelve-year persistence of inequalities in antenatal care utilisation among women in Tanzania: a decomposition analysis of population-based cross-sectional surveys. BMJ Open. 2021 Apr 1; 11(4): e040450. PubMed Abstract | Publisher Full Text | Free Full Text

[36] 36. Tekelab T, Chojenta C, Smith R, et al.: Factors affecting utilization of antenatal care in Ethiopia: a systematic review and meta-analysis. PLoS One. 2019 Apr 11; 14(4): e0214848. PubMed Abstract | Publisher Full Text | Free Full Text

[37] 37. Afful-Mensah G, Nketiah-Amponsah E, Boakye-Yiadom L: Rural-urban differences in the utilization of maternal healthcare in Ghana: the case of antenatal and delivery services. Afr. Soc. Sci. Rev. 2014; 4(1): 58–73. Publisher Full Text Reference Source

[38] 38. Ali B, Dhillon P, Mohanty SK: Inequalities in the utilization of maternal health care in the pre-and post-National Health Mission periods in India. J. Biosoc. Sci. 2020 Mar; 52(2): 198–212. PubMed Abstract | Publisher Full Text

[39] 39. Amporfu E, Grépin KA: Measuring and explaining changing patterns of inequality in institutional deliveries between urban and rural women in Ghana: a decomposition analysis. Int. J. Equity Health. 2019 Dec; 18(1): 122–123. PubMed Abstract | Publisher Full Text | Free Full Text

[40] 40. Nwosu CO, Ataguba JE: Socioeconomic inequalities in maternal health service utilisation: a case of antenatal care in Nigeria using a decomposition approach. BMC Public Health. 2019 Dec; 19(1): 1491–1493. PubMed Abstract | Publisher Full Text | Free Full Text

[41] 41. Ba DM, Ssentongo P, Agbese E, et al.: Prevalence and predictors of contraceptive use among women of reproductive age in 17 sub-Saharan African countries: a large population-based study. Sex. Reprod. Healthc. 2019 Oct 1; 21: 26–32. PubMed Abstract | Publisher Full Text

[42] 42. Nababan HY, Hasan M, Marthias T, et al.: Trends and inequities in use of maternal health care services in Indonesia, 1986–2012. Int. J. Women’s Health. 2017 Dec 29; 10: 11–24. PubMed Abstract | Publisher Full Text | Free Full Text

[43] 43. Hodge A, Firth S, Bermejo R, et al.: Utilisation of health services and the poor: deconstructing wealth-based differences in facility-based delivery in the Philippines. BMC Public Health. 2016 Dec; 16(1): 522–523. PubMed Abstract | Publisher Full Text | Free Full Text

[44] 44. Weinhold I, Gurtner S: Rural-urban differences in determinants of patient satisfaction with primary care. Soc. Sci. Med. 2018 Sep 1; 212: 76–85. PubMed Abstract | Publisher Full Text

[45] 45. Ganle JK: Why Muslim women in Northern Ghana do not use skilled maternal healthcare services at health facilities: a qualitative study. BMC Int. Health Hum. Rights. 2015 Dec; 15: 10–16. PubMed Abstract | Publisher Full Text | Free Full Text

What drives the rural‑urban disparities in maternity‑care services utilisation? Evidence from Ethiopia

Abstract

Keywords

Introduction

Method

Data

Table 1. Sample design regions versus place of residences (rural versus urban).

Description of variables

Decomposition estimation

(1)

(2)

(3)

Results

Descriptive statistics

Table 2. Background characteristics of women who utilised maternity-care services, 2019.

Trends in disparities in the use of maternity-care services

Table 3. Trends of ANC and DCS utilisations by rural-urban, Ethiopia, 2000-2019.

Decomposition results

Table 4. Decomposition of rural-urban disparity in factors associated with ANC and DCS utilisation in Ethiopia, 2019.

Rural-urban disparities in the factors associated with optimal ANC utilisation

Rural-urban disparities in the factors associated with DCS utilisation

Discussion

Antenatal care services (ANC) utilisation

Delivery-care services (DCS) utilisation

Strengths and limitations

Conclusion and recommendation

Data availability

References

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