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Abstract

The most essentially effective approach for decreasing mother and newborn death is thorough treatment at a medical center during and post-pregnancy. This study aims to assess the factors affecting maternal mortality in the South Gondar zone and the prevalence of hospital delivery services. The community-based cross-sectional study design was used from May 2020 to May 2021. Data were collected using a structured questionnaire administered by an interviewer, targeting 434 women of reproductive age selected through a two-stage cluster sampling method, and logistic regression analysis was employed for the analysis. The study found that 76% of births in the study region took place at medical facilities. Women who completed primary, secondary, and tertiary education were 4.912 times (AOR = 4.912; 95% CI: [2.287, 10.552]), 7.609 times (AOR = 7.609; 95% CI: [2.215, 12.145]), and 17.533 times (AOR = 17.533; 95% CI: [11.083, 23.294]) more likely to give birth in a healthcare setting, respectively. Additionally, women with road access to healthcare facilities were 2.780 (AOR = 2.780; 95% CI: [1.540, 5.021]) times more likely to deliver in a health institution, while those who did not have media exposure were 57% (AOR = 0.429; 95% CI: [0.258, 0.712]) less likely to do so. In the study area, the use of healthcare facilities is extremely low. Efforts must be made to reduce maternal deaths by establishing a highly effective healthcare system, by providing ambulances that are available in every district and educational initiatives should be expanded.

Plain Language Summary

This study attempts to find out the major obstetric and maternal factors related to health delivery care because due to delivery care, the infant’s and maternal’s survival is reduced, subsequent growth and development of the child are also reduced, as well as the child’s being exposed to the risk of childhood illnesses. We used the primary data from women between the age ranges of 15 and 49 who were permanent residents of the selected households. The analysis was conducted through a community-based cross-sectional multivariable binary logistic regression analysis. Identifying the factors that are related to infant mortality and morbidity in the study area, calculating the prevalence of health facility delivery in the study area, and showing the clinical importance of public health programs and strategies to alleviate maternal and infant mortality related to poor health facility delivery were identified as the top three priorities in this study. As a result, all responsible entities, specifically the regional and zonal health bureaus, in coordination with the federal health minister, should take decisive action to reduce the number of maternal and neonatal deaths that occur due to poor maternal utilization of health facility services.

Keywords

maternal health South Gondar zone delivery care binary logistic regression model

Background

Public health programs, especially in developing countries, primarily focus on maternal mortality; it is also used as a proxy for the population’s degree of development in health and socioeconomic status, particularly in Sub-Saharan Africa (De Brouwere et al., 1998; World Health Organization, 2016). Sub-Saharan Africa still covers a significant portion of maternal mortality (South Gondar Zone Health Bureau, 2020), with around 303,000 daily deaths worldwide as a result of factors that can be avoided associated with gestation and childbearing despite a significant reduction in maternal death rates in high-income countries (McClure et al., 2007). In contrast, the United Nations Children’s Fund (UNICEF) estimates that 515,000 women each year died as a result of difficulties during pregnancy and delivery. Because of these complications, of the estimated 1,600 maternal deaths worldwide every day, the majority occur in underdeveloped countries (EDHS, 2016; Weil & Fernandez, 1999; World Health Organization, 2001, 2010a). Over 85% of total maternal mortality worldwide is accounted for by the WHO Sub-Saharan Africa and Southern Asia regions (286, 000). Despite having a higher rate, maternal mortality in Sub-Saharan Africa remained around two-thirds of the global average (World Health Organization, 2018; Zureick-Brown et al., 2013).

Ethiopia has one of the highest maternal fatality rates in the developing world, with 412 deaths per 100,000 live births, according to the 2016 EDHS (2016), indicating a 1 in 243 lifetime chance of maternal mortality. This is attributed to unavailability and low use of modern health services as well as a lower percentage of health-care delivery coverage around all regions of the country (Central Statistical Agency (Ethiopia) and ICF International, 2011; Ethiopia Demographic, 2006; UNICEF, 2008; World Health Organization, 2010b).

Despite the importance of medical centers for reducing maternal mortality, 32% of births in developing countries occur outside of health facilities (World Health Organization, 2014, 2016, 2018). The biggest risk of death for both infants and mothers comes during delivery, followed by the first hours and days after childbirth. The postnatal period is crucial for infants and mothers, but 87% of Sub-Saharan African mothers do not receive care within 2 days of delivery (Kassebaum et al., 2016; Tessema et al., 2017; World Health Organization, 2014). The critical use of maternal health care is a crucial method for reducing maternal mortality. Attendance at antenatal care, birth by a professional health worker, and postnatal care are all clearly associated with reduced mother and newborn deaths (Bekuma et al., 2020; World Health Organization, 2018).

EDHS (2016) report indicates Ethiopia’s coverage of prenatal care is low, with 32% coverage during pregnancy, 26% during delivery, and 17% during postnatal care. The country’s maternal healthcare coverage is significantly below the WHO’s recommended minimum level, indicating a significant lack of adequate healthcare (Bekuma et al., 2020; Central Statistical Agency, 2016). Access to medical treatment and sanitary conditions during pregnancy, delivery, and postpartum is crucial to reduce health risks and infections, but in the country, there is limited hospital-based delivery (Bekuma et al., 2020).

Additionally, in the Amhara region, antenatal care coverage is 32.4% throughout pregnancy, 27% during birth, and 14% during postnatal care (7, 22). Furthermore, in the study area, South Gondar zone, maternal health care coverage is also 37.7% for postnatal care, 48.7% for delivery, and 51.7% for pregnancy (Demissie, 2020; EDHS, 2016). In comparison to other regional states, the South Gondar zone has a relatively low coverage of maternal health care, which leads to a high annual risk of maternal and infant mortality. Additionally, there are few healthcare facilities in the area, which causes danger signs and pregnancy complications, difficulties during childbearing, and physical and mental disabilities in both the mother and the child (Demissie, 2020; South Gondar Zone Health Bureau, 2020). In the South Gondar zone, 37.3% of pregnant women did not receive at least one ANC check, and 48.3% did not meet WHO’s minimum requirement of four ANC visits during their pregnancy. About 42.68% of pregnant women give birth in a healthcare facility; while 51.32% give birth at home. Only 31.9% of mothers received PNC after their baby was born, whereas 68.1% of mothers did not. The health bureau reports that over 60 women die annually from preventable pregnancy, delivery, and postpartum diseases, with neonatal mortality covering 245 and stillbirth mortality covering 567 (Demissie, 2020; South Gondar Zone Health Bureau, 2020). Consequently, the purpose of this study is to assess the risk factors and coverage of healthcare facility delivery utilization in the South Gondar Zone.

Reviews of Literature

Theoretical and Empirical Literatures on Maternal Mortality and Healthcare Delivery

The maternal mortality rate exceeds the Sustainable Development Goal (SDG) target of 70 deaths per 100,000 live births (Central Statistical Agency, 2016; Tessema et al., 2017), with the World Health Organization recommending medical facility births as a key strategy (Claeson et al., 2000; Titaley et al., 2010). But in Sub-Saharan Africa, 48% of child births are delivered at health institutions (Central Statistical Agency, 2016; Tessema et al., 2017).

Healthcare delivery reduces maternal mortality and prevents obstetric complications. Women prefer home births due to preconceived ideas, traditional attendants, family support, and men’s reproductive health contributions. Husbands’ views influence women’s utilization of health facilities (Bishwajit et al., 2017; Gebrehiwot et al., 2014; Jackson et al., 2016). However, most research in Ethiopia shows low healthcare coverage, with women often not attending recommended ANC visits, influenced by factors like household head education, obstetric challenges, and hospital functional status (Bekuma et al., 2020; P. L. Paul & Pandey, 2020). Furthermore, many studies have identified the institutional place of delivery as a clinically important variable in reducing maternal and newborn mortality (Darmstadt et al., 2009; B. K. Paul & Rumsey, 2002). Previous studies done in Ethiopia indicated that formal education and being wealthiest decrease home delivery chances after ANC, while low ANC visits, lack of health insurance, and lack of birth preparedness plans encourage home delivery (Fekadu et al., 2019; Ketemaw et al., 2020; Nigatu et al., 2019; Wudineh et al., 2018), pregnancies wanted later encouraged women to give birth at home after antenatal care booking in Ethiopia (Fekadu et al., 2019); Wudineh et al. (2018), educational status (Asseffa et al., 2016; Fekadu et al., 2019; Ketemaw et al., 2020; Kifle et al., 2018; P. L. Paul & Pandey, 2020; Siyoum et al., 2018; Tsegaye et al., 2019; Yaya et al., 2019), place of residence (Ketemaw et al., 2020; Kifle et al., 2018; Nigatu & Gelaye, 2019; Nigatu et al., 2019; P. L. Paul & Pandey, 2020; Yaya et al., 2019), average household income (Asseffa et al., 2016; Ketemaw et al., 2020); Tsegaye et al. (2019); (Yaya et al., 2019), ANC follow up in current pregnancy (Asseffa et al., 2016; Berhe & Nigusie, 2020; Fekadu et al., 2019; Gedilu et al., 2018; Ketemaw et al., 2020; Nigatu & Gelaye, 2019; Nigatu et al., 2019; Tsegaye et al., 2019; Wudineh et al., 2018), gravidity (Ketemaw et al., 2020; Tsegaye et al., 2019), decision and knowledge on the difference of place of delivery (Berhe & Nigusie, 2020; Fekadu et al., 2019; Gedilu et al., 2018; Ketemaw et al., 2020; Nigatu & Gelaye, 2019; Nigatu et al., 2019), mothers’ occupation and decision making and traditional remedies (Berhe & Nigusie, 2020), how distant the mother’s house is from the health extension professionals (Asseffa et al., 2016; Fekadu et al., 2019; Ketemaw et al., 2020; Nigatu et al., 2019; Siyoum et al., 2018), health education (Ketemaw et al., 2020; Nigatu & Gelaye, 2019; Nigatu et al., 2019), planned pregnancy (Asseffa et al., 2016; Fekadu et al., 2019; Gedilu et al., 2018; Ketemaw et al., 2020), size of family in a household, accessibility of transportation, the women’s involvement in the monthly health conference, information about exempted service (Fekadu et al., 2019; Gedilu et al., 2018), maternal age, whether the family is a model family, the place of the most recent ANC visit attended (Asseffa et al., 2016; Fekadu et al., 2019; Ketemaw et al., 2020; Siyoum et al., 2018) were factors related with healthcare facility delivery.

Methodology

Data Source and Study Area

This study, which was conducted in Ethiopia, aimed to identify maternal factors associated with healthcare facility delivery in the South Gondar zone, the Amhara National Regional State (ANRS) of Ethiopia. A total of about 468,238 households were surveyed, resulting in 453,658 dwelling units and an average of 4.38 persons per home (Central Statistical Agency, 2007).

Study Design and Potential Benefits

A community-based cross-sectional design was used to identify maternal factors associated with healthcare facility delivery in the South Gondar zone. This study design was used because of observing a population at a single point in time and minimizing harm to participants. It avoids extended follow-ups or interventions and data collection through surveys, interviews, or observational methods, ensuring participants are not put in harm’s way since they are not exposed to any new treatments, procedures, or conditions. It can advance scientific knowledge, improve health outcomes, inform public health policies, identify gaps in care, and reduce maternal and neonatal mortality rates. Participation in research can empower women to make informed decisions about their healthcare choices, leading to better outcomes for themselves and their babies.

Study Population, Inclusion and Exclusion Criteria

The research included all women aged 15 to 49 who had given birth in the South Gondar zone within the past 1 to 2 years, excluding those who had not lived there for more than 6 months or were not permanent residents.

Determination of Sample Size and Sampling Technique

A two-stage cluster random sampling technique was used to select a sample from three districts [Laygayint, Farta, and Fogera] and four kebele, with the sample size proportionally allocated based on the number of eligible mothers in each kebele. The study randomly selected mothers in selected kebeles and calculated the optimal sample size using a single proportion formula, resulting in 434 women aged 15 to 49 years, with a 47.3% healthcare facility delivery proportion, which is taken from a similar study conducted in Lay Gayint District (Nigatu et al., 2019); 95% confidence level, 4.8% margin of error, and adding the estimated non-response rate of 5% (Worku et al., 2013).

Methods for Gathering Data and Quality Control

The study utilized an interviewer-administered, structured questionnaire to gather data on socio-demographic, accessibility, behavioral, and obstetric factors. Data collectors and supervisors were trained on research objectives, data collection, completeness, confidentiality, and internal consistency. The study used Cronbach’s alpha to assess the reliability of questionnaires (Taherdoost, 2016). A pilot survey was conducted, and the reliability level was found to be excellent or very good, with a Cronbach’s alpha coefficient between .86 and .93.

Variables of the Study

Variables considered in this study are categorized into outcome and explanatory variables.

Dependent Variable

One key metric for assessing maternal health care services is the presence of institutional delivery care (World Health Organization, 2010a). The study questionnaire on delivery care (DC) includes questions on the place of delivery, which are defined as either home delivery or delivery at health care facilities. As a result, the dependent variable is health facility delivery, and it is constructed from these questions.

Explanatory Variables

The outcome variable is likely to be affected by different factors. The possible explanatory variables associated with health delivery care (HDC) were taken based on several studies conducted at the global level (Asseffa et al., 2016; Berhe & Nigusie, 2020; Gedilu et al., 2018; Ketemaw et al., 2020; Nigatu & Gelaye, 2019; P. L. Paul & Pandey, 2020; Siyoum et al., 2018; Yaya et al., 2019). The list of predictor variables considered in the study was presented in Table 1.

Table 1.

List of Explanatory Variables.

Variable	Categories	Variables	Categories
Age of respondents	<25	Family size	2–4
	25–29		5–7
	30–34		8 and above
Respondent religion	>34	Monthly income	≤1,000
	Orthodox		1,001–2,500
	Muslim		2,501–5,000
	Others		5,001 and above
Education level of respondent	Illiterate	Owns mobile telephone	No
	Only read and write	Owns mobile telephone	Yes
	Primary education	Decision of maternal care service utilization	Husband
	Secondary school		Wife
	Tertiary level		Both
Respondent occupation	Housewife	Exposed to mass media	Exposed
	Farmer	Exposed to mass media	Not exposed
	Governmental or non-governmental employee	Residence	Urban
	Merchant	Residence	Rural
Education level of husband’s	Daily Laborer	Marital status	Married
	Illiterate		Divorced
	Only read and write		Windowed
	Primary education		Single
	Secondary school	Husband’s occupation	Farmer
	Tertiary level		Governmental or non-governmental employee
			Merchant
			Daily Laborer
Birth order	First	Nearest health institution	Health center
	2–3		Private clinic
	4 and above		Hospital
Size of child at birth	Small	The time taken to get the nearest health facility	Below 1 hr
	Average		1–2 hr
	Large		Above 2 hr
Place of previous delivery	Home	Duty service of maternal health care	No
Place of previous delivery	Health institution	Duty service of maternal health care	Yes
Health problem in the last pregnancy	No	Transportation	On foot
Health problem in the last pregnancy	Yes	Transportation	By car
Planned pregnancy	No	Number of living children	1–3
Planned pregnancy	Yes	Number of living children	4 and above
Experienced death of neonate age less than 7 days	No	Experienced child death	No
Experienced death of neonate age less than 7 days	Yes	Experienced child death	Yes
History of abortion	No	Road accessibility to the HF	No
History of abortion	Yes	Road accessibility to the HF	Yes
Age at first pregnancy	<20	Counseling about maternal health care	No
Age at first pregnancy	≥20	Counseling about maternal health care	Yes
Post delivery shelter	No	Maternal health insurance	No
Post delivery shelter	Yes	Maternal health insurance	Yes
Existence of healthcare facility in kebele	No	Health provider behavior	Good
Existence of healthcare facility in kebele	Yes	Health provider behavior	Poor
Age at first marriage	Less than 15
	15–19
	20–24
	≥25

Statistical Methodology

The study used SPSS software version 24.0 for data editing, labeling, recoding, and exploratory analyses to ensure consistency and treat missing values in the dataset. For further exploration of the data, we exported the data to R statistical software. In order to present the data by frequencies with percentages in table formats, descriptive statistics were used. A binary logistic regression model was employed for assessing factors associated with maternal health care utilization since the dependent variable is dichotomous. The model is given as follows.

$π (x = 1 / x = 0) = \frac{e^{β_{0} + β_{1} x_{1} + β_{2} x_{2} + \dots + β_{p} x_{p}}}{1 + e^{β_{0} + β_{1} x_{1} + β_{2} x_{2} + \dots + β_{p} x_{p}}};$

where $x :$ represents predictor variables and $π (x) :$ represent the probability of an event that depends on p covariates or independent variables. The adjusted odds ratio with a 95% confidence interval was used to interpret the result of binary logistic regression model. Any variable that has a p-value of less than or equal to .05 is deemed statistically significant.

Result

Descriptive Characteristics of Respondents

There are 434 eligible mothers in the study. The respondents’ average age was 33.63 ± 7.19 years, and their standard deviation was 33.63 ± 7.19 years. Of the responders, about 188 (43.3%) were older than 34 years. 390 (89.9%) of the participants were married and Orthodox. 155 (35.7%) and 194 (44.7%) mothers and their husbands, respectively, had low levels of education were unable to read and write. In terms of occupation, 157 (36.2%) of mothers and 228 (52.5%) of their husbands were farmers. Of the respondents, 252 (58.1%) lived in rural areas, which is more than half (Table 2).

Table 2.

Socio-Demographic Characteristics of Respondents in South Gondar Zone.

Variable	Categories	Frequency (%)	Health facility delivery
Variable	Categories	Frequency (%)	No (%)	Yes (%)
Age of respondents	<25	48 (11.1)	—	—
	25–29	91 (21.0)	—	—
	30–34	107 (24.7)	—	—
	>34	188 (43.3)	—	—
Respondent religion	Orthodox	390 (89.9)	—	—
	Muslim	37 (8.5)	—	—
	Others	7 (1.6)	—	—
Education level of respondent	Illiterate	194 (44.7)	81 (77.9)	113 (34.2)
	Only read and write	35 (8.1)	9 (8.7)	26 (7.9)
	Primary education	85 (19.6)	9 (8.7)	76 (23.0)
	Secondary school	49 (11.3)	3 (2.9)	46 (13.9)
	Tertiary level	71 (16.4)	2 (1.9)	69 (20.9)
Respondent occupation	Housewife	152 (35.0)	—	—
	Farmer	157 (36.2)	—	—
	Governmental or non-governmental employee	62 (14.3)	—	—
	Merchant	55 (12.7)	—	—
	Daily Laborer	8 (1.8)	—	—
Education level of husband’s	Illiterate	155 (35.7)	70 (67.3)	85 (25.8)
	Only read and write	57 (13.1)	17 (16.3)	40 (12.1)
	Primary education	75 (17.3)	8 (7.7)	67 (20.3)
	Secondary school	60 (13.8)	7 (6.7)	53 (16.1)
	Tertiary level	87 (20.0)	2 (1.9)	85 (25.8)
Husband’s occupation	Farmer	228 (52.5)	91 (87.5)	137 (41.5)
	Governmental or non-governmental employee	100 (23.0)	2 (1.9)	98 (29.7)
	Merchant	81 (18.7)	9 (8.7)	72 (21.8)
	Daily Laborer	25 (5.8)	2 (1.9)	23 (7.0)
Family size	2–4	175 (40.3)	13 (12.5)	162 (49.1)
	5–7	188 (43.3)	59 (56.7)	129 (39.1)
	8 and above	71 (16.4)	32 (30.8)	39 (11.8)
Monthly income	≤1,000	63 (14.5)	—	—
	1,001–2,500	124 (28.6)	—	—
	2,501–5,000	177 (40.8)	—	—
	5,001 and above	70 (16.1)	—	—
Owns mobile telephone	No	209 (48.2)	81 (77.9)	128 (38.8)
Owns mobile telephone	Yes	225 (51.8)	23 (22.1)	202 (61.2)
Decision of maternal care service utilization	Husband	14 (3.2)	9 (8.7)	5 (1.5)
	Wife	90 (20.7)	14 (13.5)	76 (23.0)
	Both	330 (76.0)	81 (77.9)	249 (75.5)
Exposed to mass media	Exposed	190 (43.8)	27 (26.0)	163 (49.4)
Exposed to mass media	Not exposed	244 (56.2)	77 (74.0)	167 (50.6)
Residence	Urban	182 (41.9)	11 (10.6)	171 (51.8)
Residence	Rural	252 (58.1)	93 (89.4)	159 (48.2)
Marital status	Married	390 (89.9)	—	—
	Divorced	24 (5.5)	—	—
	Windowed	14 (3.2)	—	—
	Single	6 (1.4)	—	—

Obstetric Related Characteristics of the Study Participants

Of the 321 participants, around three-fourths (74%) were pregnant for the first time after turning 19 years old. The majority of pregnancies, 369 (85.0%), were planned. 193 (44.5%) respondents said they had more than three live children, while 241 (55.5%) respondents said they had less than four. Of the respondents, 197 (45.4%) said that this was their first pregnancy, which is around one-fourth. Moreover, 68 (15.7%) of respondents had a history of newborn mortality, and 79 (18.2%) of the women had a history of abortion. Nearly half of the respondents (47.2%) were married and in the 20–24 age range (Table 3).

Table 3.

Obstetric Characteristics of Respondents in South Gondar Zone.

Variables in the study	Categories	Frequency (%)	Health facility delivery
Variables in the study	Categories	Frequency (%)	No (%)	Yes (%)
Birth order	First	81 (18.7)	—	—
	2–3	156 (35.9)	—	—
	4 and above	197 (45.4)	—	—
Counseling about maternal health care	No	90 (20.7)	—	—
Counseling about maternal health care	Yes	344 (79.3)	—	—
Size of child at birth	Small	111 (25.6)	—	—
	Average	240 (55.3)	—	—
	Large	83 (19.1)	—	—
Maternal health insurance	No	162 (37.3)	—	—
Maternal health insurance	Yes	272 (62.7)	—	—
Health provider behavior	Good	364 (83.9)	73 (70.2)	291 (88.2)
Health provider behavior	Poor	70 (16.1)	31 (29.8)	39 (11.8)
Post delivery shelter	No	42 (9.7)	—	—
Post delivery shelter	Yes	392 (90.7)	—	—
Existence of healthcare facility in kebele	No	61 (14.1)	29 (27.9)	32 (9.7)
Existence of healthcare facility in kebele	Yes	373 (85.9)	75 (72.1)	298 (90.3)
Nearest health institution	Health center	387 (89.2)	—	—
	Private clinic	14 (3.2)	—	—
	Hospital	33 (7.6)	—	—
Duty service of maternal health care	No	172 (39.6)	64 (61.5)	108 (32.7)
Duty service of maternal health care	Yes	262 (60.4)	40 (38.5)	222 (67.3)
Transportation	On foot	293 (67.5)	92 (88.5)	201 (60.9)
Transportation	By car	141 (32.5)	12 (11.5)	129 (39.1)
Number of living children	1–3	241 (55.5)	26 (25.0)	215 (65.2)
Number of living children	4 and above	193 (44.5)	78 (75.0)	115 (34.8)
Experienced child death	No	325 (74.9)	—	—
Experienced child death	Yes	109 (25.1)	—	—
Road accessibility to the HF	No	235 (54.1)	85 (81.7)	150 (45.5)
Road accessibility to the HF	Yes	199 (45.9)	19 (18.3)	180 (54.5)
Place of previous delivery	Home	187 (43.1)	102 (98.1)	85 (25.8)
Place of previous delivery	Health institution	247 (56.9)	2 (1.9)	245 (74.2)
Health problem in the last pregnancy	No	279 (64.3)	84 (80.8)	195 (59.1)
Health problem in the last pregnancy	Yes	155 (35.7)	20 (19.2)	135 (40.9)
Planned pregnancy	No	65 (15.0)	31 (29.8)	34 (10.3)
Planned pregnancy	Yes	369 (85.0)	73 (70.2)	296 (89.7)
Experienced death of neonate age less than 7 days	No	366 (84.3)	—	—
Experienced death of neonate age less than 7 days	Yes	68 (15.7)	—	—
History of abortion	No	355 (81.8)	—	—
History of abortion	Yes	79 (18.2)	—	—
Age at first pregnancy	<20	113 (26.0)	—	—
Age at first pregnancy	≥20	321 (74.0)	—	—
Age at first marriage	Less than 15	57 (13.1)	—	—
	15–19	146 (33.6)	—	—
	20–24	205 (47.2)	—	—
	≥25	26 (6.0)	—	—
The time taken to get the nearest health facility	Below 1 hr	243 (56.0)	29 (27.9)	214 (64.8)
	1–2 hr	162 (37.3)	58 (55.8)	104 (31.5)
	Above 2 hr	29 (6.7)	17 (16.3)	12 (3.6)
Place of delivery	Home delivery	104 (24.0)	(95% confidence interval; 71.74, 80.00)
	Healthcare delivery	330 (76.0)	(95% confidence interval; 71.74, 80.00)

Prevalence of Health Facility Delivery Care in South Gondar Zone

In this study, 434 respondents were involved, and the result of the study found a 76% (95% CI; [71.74, 80.00]) prevalence of institutional healthcare facility delivery utilization (Table 3).

Factors Affecting Healthcare Facility Delivery Usage

Table 4 provided a summary of the findings from the bivariable and multivariable binary logistic regression analyses. The model demonstrated that the following factors were significantly associated with maternal healthcare utilization: road accessibility, health provider behavior, presence of a delivery care facility in their village, transportation, size of family, maternal education, maternal occupation, husband’s education and occupation, media exposure, time taken to get to the nearest healthcare facility, planned pregnancy, preferred health profession by women, source of information about maternal care, residence, duty service of maternal health care, and number of living children.

Table 4.

Factors Associated with the Utilization of Health Facility Delivery in South Gondar Zone.

Variables in the study	COR [95% CI]	AOR [95% CI]	p-Value	Variables in the study	COR [95% CI]	AOR [95% CI]	p-Value
Education level of respondent				Source of information
Illiterate	1	1		Health institution	1	1
Only read and write	2.07 [0.92, 4.66]	1.85 [0.81, 4.22]	0.0204	Health extension workers	0.34 [0.20, 0.57]	0.34 [0.19, 0.58]	<0.0001
Primary education	6.05 [2.87, 12.78]	4.91 [2.29, 10.55]	0.001	Radio/television	0.72 [0.29, 1.77]	0.71 [0.28, 1.78]	0.0307
Secondary school	10.99 [3.30, 36.57]	7.61 [2.22, 12.15]	<0.0001	Relatives and friends	0.21 [0.11, 0.42]	0.27 [0.13, 0.55]	<0.0001
Tertiary level	24.73 [5.89, 43.81]	17.53 [11.08, 23.29]	<0.0001	Owns mobile telephone
Education level of husband’s				Yes	5.56 [3.33, 9.29]	5.79 [3.10, 9.88]	0.0063
Illiterate	1	1		No	1	1
Only read and write	1.94 [1.012, 3.711]	1.70 [0.87, 3.33]	<0.0001	Residence
Primary education	6.90 [3.10, 15.33]	3.55 [1.47, 8.59]	0.0025	Urban	1	1
Secondary school	6.24 [2.67, 14.58]	2.73 [1.03, 7.23]	0.018	Rural	0.11 [0.06, 0.21]	0.17 [0.09, 0.36]	<0.0001
Tertiary level	35.00 [8.31, 147.33]	11.48 [2.04, 64.6]	<0.0001	Road accessibility
Husband’s occupation				Yes	5.37 [3.12, 9.24]	2.78 [1.54, 5.02]	0.0062
Farmer	1	1		No	1	1
Governmental or non-governmental employee	32.55 [7.83, 135.31]	34.57 [7.91, 151.14]	0.0041	Health provider behavior
Merchant	5.31 [2.53, 11.16]	5.57 [2.50, 12.37]	0.026	Good	1	1
Daily laborer	7.64 [1.76, 33.19]	7.74 [1.78, 33.69]	<0.0001	Poor	0.42 [0.24, 0.76]	0.48 [0.26, 0.89]	<0.0001
Exposed to mass media				Health facility in kebele
Exposed	1	1		Yes	2.72 [1.50, 4.97]	2.46 [1.32, 4.58]	<0.0001
Not exposed	0.36 [0.22, 0.59]	0.43 [0.26, 0.71]	<0.0001	No	1	1
Time to the nearest HF				Duty service of maternal health care
Below 1 hr	1	1		Yes	2.63 [1.64, 4.21]	2.67 [1.66, 4.30]	<0.0001
1–2 hr	0.24 [0.15, 0.40]	0.29 [0.17, 0.51]	<0.0001	No	1	1
Above 2 hr	0.10 [0.04, 0.22]	0.11 [0.05, 0.27]	<0.0001	Transportation
Planned pregnancy				On foot	1	1
Yes	3.70 [2.13, 6.41]	2.69 [1.49, 4.85]	0.0314	By car	3.94 [2.05, 7.58]	3.67 [1.87, 7.20]	<0.0001
No	1	1		Family size
Health problem in the last pregnancy				2–4	1	1
Yes	5.20 [2.71, 9.99]	3.55 [1.10, 6.30]	<0.0001	5–7	0.32 [0.14, 0.73]	0.33 [0.15, 0.75]	0.0058
No	1	1		8 and above	0.24 [0.09, 0.66]	0.24 [0.09, 0.66]	0.029
ANC visit				Number of living children
No	1	1		1–3	1	1
Yes	6.90 [4.18, 11.40]	5.95 [3.55, 9.98]	<0.0001	4 and above	0.40 [0.20, 0.79]	0.43 [0.21, 0.87]	<0.0001
Place of previous delivery				Health profession preferred by women
Health institution	4.31 [2.34, 7.92]	4.21 [2.29, 7.76]	<0.0001	Yes	4.44 [2.34, 8.43]	3.67 [1.85, 7.28]	<0.0001
Home	1	1		No	1	1
Decision of maternal care service
Husband	1	1
Wife	9.77 [2.85, 33.53]	8.06 [2.05, 31.75]	<0.0001
Both	5.53 [1.80, 16.99]	6.67 [1.93, 23.10]	0.034

Note. 1 = reference category.

Women who can just read and write sentences had a 1.854-fold higher chance of giving birth in a medical facility than women who are illiterate. Primary, secondary, and tertiary school-educated women were 4.912 (AOR = 4.912; 95% CI: [2.287, 10.552]), 7.609 (AOR = 7.609; 95% CI: [2.215, 12.145]), and 17.533 (AOR = 17.533; 95% CI: [11.083, 23.294]) times more likely to give birth in a medical facility, respectively, than illiterate women.

Compared to women whose husbands were farmers, women whose husbands were employed by the government or non-government sector had a 34.567 (AOR = 34.567; 95% CI: [7.905, 151.143]) times higher chance of giving birth in a medical facility. Furthermore, compared to their counterparts, women who had to travel 2 hr or more to reach the closest medical center had a 0.113 (AOR = 0.113; 95% CI: [00.048, 0.269]) lower chance of giving birth in a medical institution. The use of healthcare facility delivery services was additionally associated to the respondents’ media exposure. Those mothers who did not have media exposure were 57% (AOR = 0.429; 95% CI: [0.258, 0.712]) less likely than those who did to give birth in a medical institution. Furthermore, compared to women without a cell phone, those with a phone had a 5.792 (AOR = 5.792; 95% CI: [3.395, 9.880]) higher chance of giving birth in a health institution.

The use of institutional delivery services was substantially correlated with women’s preferred health professions and road accessibility. Women who had road access to the healthcare facility were 2.780 (AOR = 2.780; 95% CI: [1.540, 5.021]) times more likely to give birth in a medical facility than women who did not have road access. Additionally, compared to women who did not choose a health profession, those who did had a 3.667 (AOR = 3.667; 95% CI: [1.847, 7.282]) lower chance of giving birth in a medical facility.

There was a positive relationship between planned pregnancy and birth at a medical facility. Pregnant women with planned pregnancies were 2.689 (AOR = 2.689, 95% CI: [1.492, 4.846]) times more likely to give birth in a medical institution than those with unplanned pregnancies. Additionally, there is a statistically significant correlation between ANC visits and the delivery of healthcare facilities. Pregnant women who got ANC had a 5.953 (AOR = 5.953; 95% CI: [3.551, 9.980]) higher chance of giving birth in a medical facility than those who did not. A significant correlation was found between residence and the use of health facility delivery. Rural women were less likely than urban women to give birth in a medical institution (AOR = 0.171, 95% CI: [0.085, 0.346]).

Discussions

The results of this study showed that the following factors were statistically associated with institutional delivery care. Residence, husband and mother’s educational status, occupation, place of previous delivery, time to the closest health facility, family size, road accessibility, transportation, decision on maternal care service, household income, ANC visit, information source about maternity care, planned pregnancy, maternity care access issues, maternity care provider behavior, and access to mass media.

In the area of this study, women’s level of educational was found to be a major predictor of health facility delivery. The findings of this study are consistent with those of other investigations in Ethiopia (Ketemaw et al., 2020; Tsegaye et al., 2019), Guinea-Bissau (Yaya et al., 2019), and India (P. L. Paul & Pandey, 2020). This could be as a result of well-educated women being more aware of the benefits of giving birth in medical facilities, gaining knowledge and decision-making power. Moreover, higher maternal education leads to increased financial resources and greater freedom for women to seek medical treatment (Doctor et al., 2018; Hwang & Park, 2019).

This finding revealed that women who were exposed to the media were more likely to go to institutions for medical care. This can occur as a result of the media’s coverage of ANC and PNC services for hospital births and maternal health care. ANC visits were higher among women who had access to the media, consistent with previous study in Eritrea (Kifle et al., 2018). Additionally, mothers who are exposed to the media are more likely to use maternal care services; in lined with a study conducted in rural India (Sunil et al., 2006) Mothers exposed to multiple media sources had better maternal care services compared to those without exposure to any media.

According to this study, women who regularly attend ANC appointments are more likely to choose a facility-based delivery because they are getting crucial guidance and knowledge about safe birthing practices and are more likely to comprehend the advantages of giving birth in a medical setting, in line with a study in Sub-Saharan Africa where ANC attendance is a strong predictor of giving birth at a healthcare facility (Doctor et al., 2018). Hence, mothers who have better ANC attendance are likely due to increased awareness of benefits and danger signs.

The time to the nearest medical center is significant predictor variable affecting maternal care services utilization. This demonstrates that longer travel times to the facility lead to increased pregnancy problems because of poor economic growth, lack of transportation payments, and limited access to healthcare systems. This result is consistent with research done in Ethiopia (Fekadu et al., 2019; Gedilu et al., 2018) and Eritrea (Kifle et al., 2018). Furthermore, in a developing country like Ethiopia, inadequate transportation infrastructure negatively impacts maternal health, causing longer travel times to health facilities. Hence, non-governmental organizations should focus on developing healthcare infrastructure for improved accessibility, in line with studies (Gage & Guirlène Calixte, 2006; Sagna & Sunil, 2012; Sunil et al., 2006).

The study found that mobile phone usage significantly influences the utilization of health facility delivery services for mothers. This suggests that women who own cell phones understand the importance of healthcare facility delivery for mothers and their children better since mobile technology enhances communication, service uptake, and management of pregnancy problems, ultimately reducing maternal morbidity and death. The finding is supported by studies conducted in North-Western part of Ethiopia (Delele et al., 2021).

The study found that the choice of a health professional or use of maternity care services by women was significantly related to health delivery service. Ethiopian men are dissatisfied with paying for prescriptions and supplies, while women are engaged in learning about risk indications for their health during and after pregnancy, leading to a close association between healthcare facility delivery and maternity care choices. This finding is consistent with other previous studies conducted in Ethiopia (Fekadu et al., 2019; Gedilu et al., 2018) and Eritrea (Kifle et al., 2018).

The study found that planned pregnancy is positively associated with health facility delivery, which is in line with previous research in Ethiopia (Asseffa et al., 2016; Ketemaw et al., 2020). This is possibly due to mothers prioritizing prenatal care, ANC, and delivery location who wish to have a child plan and want to have a good pregnancy. Furthermore, this study suggests that place of residence significantly influences institutional delivery, possibly due to urban women’s media exposure and proximity to healthcare institutions, in line with studies in Ethiopia (Ketemaw et al., 2020; Nigatu et al., 2019). Rural areas have lower percentage of maternal healthcare facility utilization compared to urban dwellers, consistent with a study in rural India (Sunil et al., 2006).

Conclusion

The binary logistic regression model showed that predictor variables, including educational level of mother and her husband, ANC visits, residence, media exposure, wealth index, husband occupation, road accessibility, transportation, and time to reach health facilities, were statistically significant. Hence, the Amhara regional and South Gondar zone health bureaus are urged to take decisive action to reduce maternal and neonate deaths due to poor utilization of health facility services. Moreover, the government should maintain a functional referral system, strengthen the free maternal care policy, and expand educational programs to educate mothers. The finding of this study will provide valuable bases of data on factors affecting maternal healthcare facility delivery in South Gondar Zone, guiding future research and interventions in the region. It will also guide further research studies on these issues, which are limited in the context of the South Gondar Zone of Amhara Regional State.

Limitations

The study uses primary data to accurately estimate the needs of women without access to medical facilities. However, this study used verbal interviews with women and household heads to gather data on delivery decisions in the past. This may be feasible, but this method is subject to recall bias. In addition, the study lacks independent examination of psychological factors and makes it difficult to infer causal relationships.

Implication of the Study

The study highlights low healthcare delivery utilization in the area, suggesting improvements in maternal and infant health through education on ANC visits, postnatal care, and delivery. It also suggests prioritizing women’s empowerment through formal education, training healthcare professionals, and social media. The study also suggests policymakers should develop interventions to boost facility-based deliveries and improve maternal and neonatal health outcomes by empowering women’s decision-making. Family planning initiatives should be promoted to emphasize the importance of planned pregnancies to help women and families make informed decisions about the timing and spacing of pregnancies, and training programs for healthcare providers should be given to improve their responsiveness to women seeking maternal care. Furthermore, this study appreciates that conducting community outreach programs should raise awareness about healthcare facility delivery benefits, address accessibility barriers, and use media exposure to disseminate information about facilities and services. We also hope that the current findings will help the government and other interested parties address the accessibility issues.

Footnotes

The authors are thankful to the Debre Tabor University that give the opportunity and gave us a supportive letter. We would also like to direct our thanks to the study participants for their permission and cooperation to participate in this study. We also thank our data collectors and supervisor.

Abbreviations

ANC: antenatal care

AOR: adjusted odds ratio

CI: confidence interval

CSA: Central Statistical Agency

COR: crude odds ratio

DC: delivery care

EDHS: Ethiopia Demographic and Health Survey

HF: health facility

PLD: place of delivery

PNC: postnatal care

SDG: sustainable development goal

SPSS: Statistical Package for Social Science

UNICEF: United Nations Children’s Fund

WHO: World Health Organization

ORCID iDs

Hailegebrael Birhan Biresaw

Setegn Muche Fenta

Bezanesh Melese Masresha

Kenaw Derebe Fentaw

Yikeber Abebaw Moyehodie

Alebachew Taye Belay

Mequanint Melkam Yalew

Ethical Considerations

This was not an interventional or trial study that involved experiments on live women’s. The study adhered to the Debre Tabor University,Department of Statistics guidelines and the Departmental Research Review Committee (DRRC) approved it with an approval letter referenced DTU/Stat/05/2020.

Consent for Publication

Verbal informed consent was obtained from all subjects and from the legally authorized representatives of the subjects who were unable to read and write before the interviews and discussions in the presence of an independent witness. The name and signature of the witnesses will be available upon request.

Author Contributions

HB and SM wrote the proposal,drafted the paper,and prepared the manuscript,and involved in the study design. HB,SM,BM,YA,AT,KD and MM participated in data collection. HB,SM,BM,KD,YA,AT,and MM analyzed the data,approved it with few revisions,participated in data analysis,and revised subsequent drafts of the paper. All the authors read and approved the final manuscript sent for publication.

Funding

The author(s) received no financial support for the research,authorship,and/or publication of this article.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research,authorship,and/or publication of this article.

Data Availability Statement

The dataset and supporting materials will be obtained based on a request from the corresponding author on a reasonable request.

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