Skip to main content
Obstetrics and Gynecology International logoLink to Obstetrics and Gynecology International
. 2021 Dec 7;2021:6618676. doi: 10.1155/2021/6618676

Predictors and Utilization of Health Institution Services for Childbirth among Mothers in a Southern Nigerian City

Kazeem Arogundade 1,, June Sampson 2, Elizabeth Boath 3, Ubong Akpan 4, Olaposi Olatoregun 5, Oluwayemisi Femi-Pius 6, Jude Orjih 6, Barinaadaa Afirima 7, Nasir Umar 8
PMCID: PMC8670964  PMID: 34917151

Abstract

Background

Poor maternal health indices, including high maternal mortality, are among Nigeria's major public health problems. Most of these deaths can be prevented by timely access and utilization of maternity healthcare services by women. Aim/Objective. This study seeks to identify factors affecting the utilization of health facilities for the delivery of babies among mothers in Calabar, Cross River State, Nigeria. Methodology. The study was a community-based cross-sectional study. A structured questionnaire was administered to 422 women of reproductive age residents in the study area who had given birth at least once within the last five years prior to the survey using a multistage random sampling technique. Data generated were entered, coded, and analyzed using Statistical Packages for Social Sciences (SPSS version 22.0), and results were presented in tables and charts. Chi-squared tests and multiple logistic regression were used for the identification of variables associated with health facility-based delivery.

Result

The mean age of respondents was 27.3 years (SD = 8.4). Fifty-two percent of the respondents utilized the health facility for delivery, 89.6% attended at least one antenatal clinic (ANC), and 18.9% completed at least 3 ANC sessions. There was a statistically significant association between health facility delivery and marital status (P=0.007), education (P=0.042), and family size (P=0.002). Older women (OR = 0.7, CI = 0.169–3.714), Christians (OR = 1.9, CI = 0.093–41.1), divorcees (OR = 3.7, CI = 0.00–0.00), and respondents who registered early (first trimester) for ANC (OR = 4.9, CI = 0.78–31.48) were found to be higher users of delivery services at the health facility.

Conclusion

Community health intervention focusing on improving the knowledge and awareness of the significance of utilizing available delivery services at the healthcare facility should be developed and implemented.

1. Introduction

Complications during childbirth over the years have been largely responsible for most maternal deaths in the African region [1]. This is often exacerbated in poor-resource settings where access to maternal healthcare services is poor. Pregnancy and childbirth contribute to a low life expectancy of women in this region and constitute a significant threat to neonatal and infant survival [2].

The World Health Organization (WHO) estimated that about 810 women die every day in 2017 from obstetric complications, and developing countries contribute 94% of the total maternal death in the world [3]. In Nigeria, the Maternal Mortality Ratio (MMR) is currently 512 maternal deaths per 100,000 live births and is ranked the fourth highest globally [4, 5].

Complications arising during labor, delivery, and the postpartum period largely account for most maternal mortality [6]. The WHO noted that 75% of maternal mortality is primarily caused by obstetric hemorrhage, hypertension in pregnancy, infection, obstructed labor, and unsafe abortion [7]. Available evidence has shown that health facility-based delivery of babies by skilled birth attendants can reduce maternal mortality [6].

Most deliveries still occur at home without the assistance of a skilled birth attendant in developing countries [8]. Thus, although there has been a noticeable decline in maternal deaths by 38% from 342,000 in 2000 to 211,000 in 2017, the annual reduction rate of 2.9% is less than the required target of 6.4% to achieve the Sustainable Development Goal of 70 maternal deaths per 100,000 live births [9].

One in every 37 women faces a lifetime risk of dying during pregnancy or childbirth in Sub-Saharan Africa [7]. It has also been documented that 80% of global maternal deaths occur in Sub-Saharan Africa and Southern Asia [7]. However, delivery by skilled birth attendants was reportedly low, with 40% in Sub-Saharan Africa compared to 96% in developed countries [10]. Similarly, in Nigeria, delivery by skilled birth attendants is 43.3% (9% by doctors and 32% by midwives/nurses) [4].

In low- and middle-income countries, the prevalence of health facility-based delivery of infants ranged from 23% in the Republic of Chad to 94% in the Gabon republic [11]. Despite the free maternal health service policy in Kenya and Ghana, 47.6% of deliveries happen in a health facility in Kenya and 59% in Ghana, respectively [12]. In Eritrea, 16% of women residing in rural communities patronize health facilities for delivery compared to 73.2% in urban areas [13].

In Nigeria, national and subregional variation exists in the prevalence of health facility-based deliveries. However, from the national outlook, 36% of deliveries occur in the health facility, and in the South South region of Nigeria, 50.1% of deliveries occur in the health facility [14]. In this light, the current study seeks to identify factors affecting the use of health facilities for childbirth among mothers in Calabar metropolis, Cross River State, Nigeria.

2. Methodology

2.1. Research Design

This was a community-based cross-sectional study. The study utilized a structured questionnaire adapted from Nigeria Demographic Health Survey [4] and a cross-sectional survey conducted in Ethiopia [15]. The questionnaire was pretested prior to the study in a community similar to and outside the study area.

2.2. Study Setting

The study was carried out in Calabar, the capital of Cross River State, Nigeria. It has an airport and a seaport. It has a population of 371,022 (National Population Census, 2006). There are two Local Government Areas (LGAs) in Calabar, namely, Calabar Municipal and Calabar South. The LGAs are well mapped into 10 and 12 wards (the smallest administrative unit within the LGA).

There are two tertiary hospitals (the University of Calabar Teaching Hospital and the Federal Neuropsychiatric Hospital), two General hospitals, many primary health centers, registered clinics, registered maternity homes, and numerous private hospitals involved in maternal-newborn care. The major occupations of the people are trading, farming, fishing, and civil service.

2.3. Study Population

The study population comprised women of reproductive age (15–49 years) who delivered a live baby at least once in the past five years prior to the study and are permanent residents in the study area (Calabar metropolis).

2.4. Sampling Technique

Considering the wide horizon of the study setting, a multistage sampling technique was used to select subjects for this study as follows:

  •   Phase I: a systematic random sampling technique was employed to select three wards from each of the two local government areas using the lottery method.

  •   Phase II: a simple random sampling technique was employed in each selected ward to select 8 settlements using the lottery method. Numbers were assigned to each settlement, folded, and put in envelopes. The first 8 settlements picked were recruited into the study (i.e., 6 wards × 8 settlements = 48 settlements).

  •   Phase III: in each selected settlement, simple random sampling techniques were used to select eligible households; that is, publicly available addresses were entered in excel random sample software, and 8 households per settlement were randomly selected (i.e., ∼8 households × 48 settlements = 384 persons).

2.5. Sample Size

The sample size was determined using the Kiss formula, which is expressed as follows: n = Z2Pq/d2, where n is sample size, Z is equal to 1.96 corresponding to 95% confidence interval (constant at 95% precision), d is the degree of accuracy set at 5%, q = 1−p (1–0.5 = 0.5) (proportion of women who had not delivered at the health facility), and p = 0.5 (proportion of women who had delivered at the health facility); hence, n = 1.96 × 1.96 × 0.5 × 0.5/0.05 × 0.05, n = 384.

To account for attrition and incompletely filled questionnaires, the computed sample size (384) was increased by 10%, which gave a final sample size of 422.

2.6. Inclusion Criteria

Women of reproductive age (15–49 years) who had delivered at least one baby in the past five years prior to the study and were permanent residents of the study area (Calabar) irrespective of the place and outcome of delivery were recruited into the study.

2.7. Exclusion Criteria

The exclusion criteria include women with a psychiatric problem or who are seriously ill at the time of data collection, women below the age of 15 years and above 49 years at the time of data collection, and women who did not consent to the study.

2.8. Data Collection Tools and Procedures

The household survey was then carried out using a structured questionnaire which constituted only closed-ended questions.

The questionnaires included sociodemographic, obstetric characteristics, delivery place, and practice of institutional delivery and were administered by an interviewer.

2.9. Ethical Consideration

Approval was obtained from the Cross River State Ministry of Health Research Ethics Committee. Participation in the study was voluntary without any form of coercion, and those who were not willing to partake in the study were excluded from being interviewed. Written informed consent was obtained from each participant.

2.10. Data Management

Data were entered and analyzed using Statistical Package for Social Sciences (SPSS) version 22.0. Results were expressed in percentages and presented in tables and charts. Chi-square was used to determine the association between variables at 0.05 level of significance, whereas logistic regression was used to determine independent predictors for health services for childbirth.

3. Results

3.1. Sociodemographic Characteristics of Respondents

The mean age was 27.3(SD = 8.4) years. Most of the respondents, 292 (69%), were 30 years and below. About half, 51.4%, of the respondents, had postsecondary school education. A vast majority (84.2%) were employed. Details of the sociodemographic characteristics are shown in Table 1.

Table 1.

Sociodemographic characteristics of respondents, N = 422.

Variable Frequency Percentage
Religion
Christian 404 95.7
Muslim 16 3.8
Traditional African Religion 2 0.5
Total 422 100

Age in years
15–20 118 28
21–25 92 22
26–30 82 19
31–35 57 13
36–40 34 8
41–49 39 10
Total 422 100

Highest level of education
Postsecondary 217 51.4
Secondary school 186 44.1
Primary school 19 4.5
Total 422 100

Employment status
Employed 198 47
Self-employed 157 37.2
Unemployed 67 15.8
Total 422 100

Educational level of partner
Postsecondary 270 63.9
Secondary school 147 35
Primary school 5 1.1
Total 422 100

Occupation of partner
Farmer 122 28.9
Daily laborer 54 12.8
Businessman 68 16.1
Civil servant 178 42.2
Total 422 100

3.2. Maternal Health Information

Findings on maternal health information showed that the majority of respondents (69.9%) received no education on maternal health, while 30.1% were oriented on maternal health. Respondents' sources of information on maternal health included healthcare workers (68%), traditional birth attendants (7.9%), friends/relatives (16.7%), and radio/television (7.1%).

Some of the respondents (39.1%) identified nutritional problems as the major health problems in the community. Findings from the survey revealed that a higher proportion of the respondents (96.7%) reported having a health facility in their communities. Similarly, the majority of the respondents (90.9%) affirmed that the distance of the nearest health facility from their homes was less than one hour.

3.3. Obstetric Characteristics

More than half (56.9%) of the respondents were multiparous (two or more children). The study revealed that 89.6% attended antenatal care (ANC), while 10.4% of respondents did not attend ANC. In enquiring for reasons for non-ANC attendance, 56.8% of the total respondents that did not participate in ANC attributed it to workload (Figures 1 and 2). Among the ANC attendees, 46% of them registered for ANC in the first trimester of pregnancy (0–13 weeks of gestation), 41% registered in the second trimester (14–26 weeks of gestation), while about 13% registered for ANC in the last trimester (27–40 weeks). Only 18.5% of respondents attended ANC three times and above. Maternal ill health was a major reason for early ANC registration.

Figure 1.

Figure 1

Reasons for attending ANC sessions.

Figure 2.

Figure 2

Reasons for not attending ANC session.

Findings on sources of information on antenatal care for the recent pregnancy showed that a good proportion of the respondents (48.2%) got their information from government health centers, and a few of the respondents (1.8%) got their information from the traditional birth attendants. About 97% of the respondents received advice on where to deliver their babies during ANC visits. Also, a greater proportion of the respondents (90.7%) reported being told of the danger signs to watch out for during pregnancy.

3.4. Place of Delivery

The prevalence of health institutional delivery among the respondents was 52%. Of the remaining 48% who had childbirth outside health facilities, 72% of the respondents delivered in Traditional Birth Attendants' (TBAs) centers, while the rest delivered at their homes or worship centers. A greater proportion of the respondents (58.5%) decided by themselves where to give birth, while for about 20% of the respondents, the decision was made by their spouses or family members. However, a good proportion (87.4%) of the respondents agreed that giving birth in a health facility is better than giving birth at home because of cleanliness (5.9%) and shorter labor time (6.1%), in addition to saving baby's life (6.3%), saving mother's life (11%), and complication readiness in a health facility (70.7%). The majority of respondents (66.7%) attributed the reason for giving birth at home to “no need for transportation.” Other reasons for delivering at home included “no bleeding” (22.2%) and “no hospital cost” (11.1%) and about 0.9% of the respondents had difficulty with labor. The complications reported during labor were bleeding (50%), retained placenta (25%), and prolonged labor (25%).

About 53% of the respondents preferred to give birth at home in the subsequent pregnancy, while about 43% preferred to give birth in the health facility in the subsequent pregnancy. Also, a greater proportion of the respondents (82.2%) reported health facilities as their husbands preferred place of delivery. The majority of the respondents (69.7%) preferred to assist their mother/relatives during their next delivery. The most commonly used means of transportation to a health facility as reported by respondents included walking (45%), cars (41.5%), tricycles (6.4%), bus (4.9%), motorbikes (1.9%)

3.5. Predictors of Health Facility Delivery

The study revealed a statistically significant association between health facility delivery and marital status, education, and family size (see Table 2).

Table 2.

Predictors of health facility delivery.

Characteristics Delivered in health facility Delivered outside health facility χ 2 Df p value
Religion
Christian 209 195 0.021 2 0.990
Muslim 8 8
Traditional African Religion 1 1
Total 218 204

Marital status
Single 120 141 12.068 3 0.007
Married 83 59
Divorced/separated 8 3
Cohabiting 7 1
Total 218 204

Education
Postsecondary 102 115 6.326 2 0.042
Secondary school 102 84
Primary school 14 5
Total 218 204

Employment status
Employed 100 98 4.446 3 0.217
Self-employed 78 79
Unemployed 42 25
Total 218 204

Educational level of partner
Postsecondary 139 131 0.143 2 0.931
Secondary school 76 71
Primary school 3 2
Total 218 204

Occupation of partner
Farmer 55 67 11.539 3 0.009
Daily laborer 30 24
Businessman 47 21
Civil servant 86 92
Total 218 204

Health facility accessibility
Health facility accessible 211 197 0.016 1 0.899
Health facility not accessible 7 7
Total 218 204

Family size
One–three 141 127 11.668 4 0.020
Two–four 49 65
Five–seven 24 8
Eight–eleven 3 4
More than eleven 1 0
Total 218 204

ANC attendance
Attended ANC 194 184 0.164 1 0.686
Did not attend ANC 24 20
Total 218 204

Number of pregnancies in the last five years
One 76 60 1.567 2 0.457
Two 121 119
Three 21 24
Total 218 203

Age of respondents
15–20 years 57 59 10.683 6 0.099
21–25 years 47 45
26–30 years 34 49
31–35 years 32 26
36–40 years 21 13
41–45 years 19 9
46–49 years 8 3
Total 218 204

3.6. Logistic Regression Analysis

Multiple logistic regression analyses for odds of delivering in health facilities revealed that various factors play essential roles in determining the place for delivery. Older women are 0.7 times more likely to deliver in a health facility than young women (OR = 0.7, CI = 0.169–3.714). Divorcees are three times more likely to deliver in a health facility than single and married women (OR = 3.7, CI = 0.00–0.00). A partner's level of education can predict the choice of delivery in a health facility as respondents' partners with postsecondary education are 6 times more likely to deliver in a health facility than respondents with secondary education (OR = 6.4, CI = 0.57–72.47). Respondents who registered early (first trimester) for ANC are 4 times more likely to deliver in a health facility than those registered in the second and third trimester, respectively (OR = 4.9, CI = 0.78–31.48). Furthermore, the study revealed that respondents who received advice on where to deliver are 4 times more likely to deliver in a health facility (OR = 4.9, CI = 0.96–24.9) (Table 3).

Table 3.

Multiple logistic regression analysis to predict health facility delivery.

Predictors Sig. OR 95% confidence interval
Lower bound Upper bound
Age
15–20 years 0.148 0.362 0.092 1.434
21–25 years 0.186 0.392 0.098 1.570
26–30 years 0.059 0.260 0.064 1.052
31–35 years 0.287 0.462 0.111 1.918
36–40 years 0.511 0.606 0.136 2.705
41–45 years 0.767 0.792 0.169 3.714

Religion
Christian 0.666 1.957 0.093 41.071
Muslim 0.668 0.469 0.015 14.992

Marital status
Single 0.991 1.071 0.000 0.000
Married 0.991 1.976 0.000 0.000
Divorced/separated 0.992 3.709 0.000 0.000

Educational status
Postsecondary 0.056 0.227 0.049 1.041
Secondary school 0.245 0.380 0.074 1.940

Employment status
Employed .000 7.972 4.047 1.570
Self-employed .000 7.478 3.783 1.478
Unemployed . 1.116 1.116 1.116

Occupation of partner
Farmer 0.709 0.901 0.522 1.557
Daily laborer 0.560 1.275 0.563 2.886
Business man 0.104 1.854 0.880 3.904

Partner's educational status
Postsecondary 0.130 6.463 0.576 72.475
Secondary school 0.217 4.979 0.390 63.516
Health facility available 0.722 0.629 0.049 8.089

ANC registration
First trimester 0.089 4.966 0.783 31.483
Second trimester 0.764 1.313 0.223 7.734
Third trimester 0.670 1.478 0.245 8.914
Received advice where to deliver 0.056 4.902 0.961 24.998

4. Discussion

ANC attendance in many settings does not translate to effective utilization of health institutions for childbirth. Some women prefer to deliver at home; they visit the ANC during pregnancy and get registered to be accepted at the health facility should they be confronted with any possible obstetric problems during childbirth [16]. Some women attend ANC so that they may be able to access intervention programs such as HIV drugs, intermittent preventive treatment for malaria, and long-lasting insecticide nets, as well as immunization services such as administration of antitetanus toxoids [17].

In this study, more than three-quarters (89.6%) of the respondents reported having attended antenatal care at least once during their last pregnancy. This is higher than the Cross River State average of 72.6% [14]. Perhaps, this is because the study was conducted in an urban area of the state with a good number of the participants being educated and the availability and proximity of various categories of health institutions.

However, just over 18% of the ANC attendees completed at least three ANC sessions below the WHO recommendation of eight visits [1], and only 13 (3.4%) women attended at least four ANC sessions.

Access to antenatal care services by pregnant women is essential in determining the choice of place of delivery. Antenatal clinics provide an opportunity for well-trained skilled birth attendants to provide their clients with correct and factual information, especially as it concerns maternal and child health. During antenatal care, risk assessment is usually carried out and institutional delivery is recommended [18, 19].

As a global standard, pregnant women without any form of complications are encouraged to attend at least eight ANC visits spread across the three trimesters to access all the needed care and information concerning their health, especially as it concerns pregnancy, labor, and childbirth [1]. Early ANC registration and attendance are significantly accompanied by the benefits of early detection and prompt management of maternal problems and taking immediate corrective measures to benefit the pregnant woman and her unborn baby [1]. One key benefit of ANC is its positive association with health facility-based delivery and assistance by skilled birth attendants [18]. Women who utilized ANC services more than once were more likely to deliver at a health facility than mothers who did not attend ANC [19].

The prevalence of institutional delivery among the respondents was just 52%. This figure is similar to the 52.6% prevalence reported by Nigeria Demographic Health Survey [4]. There is a slight improvement from the findings of the national survey conducted in 2013, which noted an estimated 40 percent health facility delivery in the entire state [20].

4.1. Predictors of Health Facility Delivery

The study shows that sociodemographic factors such as maternal age, religion, occupation of partner, parity, and educational status were also major determinants of childbirth. This is in accordance with a population-based study conducted in Senegal which reported that the variations in the sociodemographic profile of women significantly influenced their choice of place of delivery [21].

Early ANC registration and regular visits may predict the probability of utilizing an orthodox health institution for childbirth. Access to other reproductive services during ANC may promote attendance and institutional service utilization [21, 22].

Furthermore, our study shows that multiparity is a negative predictor of hospital supervised delivery which is similar to a study in rural Tanzania which showed that utilization of health facility delivery was higher among women with low parity as compared to their high parity counterparts [23]. In contrast, the Ghana Demographic health survey analysis revealed that multiparous women had an increased tendency to deliver in a health facility than low parity women [24].

First trimester ANC registration largely accounts for the high rate of institutional delivery among the women compared to those who registered later. A systematic review in Ethiopia showed an increased likelihood of health facility delivery with early ANC registration [19]. This study also showed that women's employment status has a strong positive association with institutional delivery, where employed women were higher users of health facility delivery. This is in line with a cross-sectional study carried out in Sub-Saharan African countries [11]).

4.2. Limitations of the Study

This study did not explore women's views and perceptions of healthcare workers' attitudes towards pregnant women, including the quality of maternal care services they provide. Nevertheless, this could be one of the determining factors of health facility delivery.

The study was conducted in an urban area and cannot be generalized to rural settings.

5. Conclusion

In conclusion, the study revealed an association between social factors such as marital status, the mother's educational level, religion, and family size with the utilization of health facilities for delivery services. A key determining factor for better maternal and neonatal outcomes is the continual availability and regular use of reproductive health services provided by well-trained and certified healthcare providers.

Data Availability

The numerical model simulations upon which this study is based are too large to archive or transfer. Instead, we provide all the information needed to replicate the simulations and can be found in the references. The model code, compilation script, initial and boundary condition files, and the namelist settings are available on the reference page.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

References

  • 1.WHO. WHO Recommendations on Antenatal Care for a Positive Pregnancy Experience . Geneva, Switzerland: WHO; 2016. https://www.who.int/publications/i/item/9789241549912 . [PubMed] [Google Scholar]
  • 2.Bellows B., Kyobutungi C., Mutua M. K., Warren C., Ezeh A. Increase in facility-based deliveries associated with a maternal health voucher program in informal settlements in Nairobi, Kenya. Health Policy and Planning Journal . 2013;28(2):134–142. doi: 10.1093/heapol/czs030. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.WHO. Maternal Mortality Key Facts . Geneva, Switzerland: WHO; 2019a. [Google Scholar]
  • 4.ICF NPC. Nigeria Demographic and Health Survey . Norwich, England: NDHS; 2019. [Google Scholar]
  • 5.Roser M., Ritchie H. Maternal Mortality-Our World in Data . 2015. https://ourworldindata.org/maternal-mortality . [Google Scholar]
  • 6.Campbell O. M., Graham W. J., Graham A. Strategies for reducing maternal mortality: getting on with what works. The Lancet . 2006;368(9543):1284–1299. doi: 10.1016/s0140-6736(06)69381-1. [DOI] [PubMed] [Google Scholar]
  • 7.WHO. More Women and Children Survive Today than Ever Before . Geneva, Switzerland: WHO; 2019b. https://www.who.int/news/item/19-09-2019-more-women-and-children-survive-today-than-ever-before-un-report . [Google Scholar]
  • 8.Kitui J., Lewis S., Davey G. Factors influencing place of delivery for women in Kenya: an analysis of the Kenya demographic and health survey, 2008/2009. BMC Pregnancy and Childbirth . 2013;13 doi: 10.1186/1471-2393-13-40. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.UNICEF. Maternal Mortality Rates and Statistics . New York, NY, USA: UNICEF; 2019. [Google Scholar]
  • 10.Doctor H. V., Nkhana-Salimu S., Abdulsalam-Anibilowo M. Health facility delivery in sub-saharan Africa: successes, challenges, and implications for the 2030 development agenda. BMC Public Health . 2018;18(1):765–12. doi: 10.1186/s12889-018-5695-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Adde K. S., Dickson K. S., Hubert A. Prevalence and determinants of the place of delivery among reproductive age women in sub–Saharan Africa. PLoS One . 2020;15(12):1–14. doi: 10.1371/journal.pone.0244875. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Manyeh A. K. Socio-demographic determinants of skilled birth attendant at delivery in rural southern Ghana. BMC Research Notes . 2017;10(1):1–7. doi: 10.1186/s13104-017-2591-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.National Statistics Office. Asamara, Eritrea, and Norway FAFO Institute for Applied International Studies, Oslo 2013. Population and Health Survey 2010 . New Delhi, India: NSO; 2013. https://www.afro.who.int/sites/default/files/2017-05/ephs2010_final_report_v4.pdf . [Google Scholar]
  • 14.Feyisetan B., Fikree F., Saad A., Mai M., Azogu J., Jega F. Summary Report of the Pre-intervention Health Facility Assessment of Emergency Obstetric Care in Cross River State, Nigeria: The Saving Mothers, Giving Life Initiative . Washington, DC, USA: USAID; 2017. https://www.e2aproject.org/wp-content/uploads/SMGL-Nigeria-Consolidated-Report-FINAL.pdf . [Google Scholar]
  • 15.Tsegay Y., Gebrehiwot T., Goicolea I., Edin K., Lemma H., Sebastian M. S. Determinants of antenatal and delivery care utilization in Tigray region, Ethiopia: a cross-sectional study. International Journal for Equity in Health . 2013;12(30) doi: 10.1186/1475-9276-12-30. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Lwelamira J., Safari J. Choice of place for childbirth: prevalence and determinants of health facility delivery among women in Bahi district, Central Tanzania. Asian Journal of Medical Sciences . 2012;4(3):105–112. http://www.maxwellsci.com/print/ajms/v4-105-112.pdf . [Google Scholar]
  • 17.Akpan U., Asibong U., Asibong U., Ekott M., Omoko B., Etuk S. Awareness and factors that influence birth preparedness and complication readiness among pregnant women attending Antenatal clinic in the General Hospital Calabar, Nigeria. Public Health Research . 2013;7(3):78–84. doi: 10.5923/j.phr.20170703.04. [DOI] [Google Scholar]
  • 18.Abebe E., Gedefaw G., Haile Z. T., Ice G. Association between antenatal care follow-up and institutional delivery service utilization: analysis of 2016 Ethiopia demographic and health survey. BMC Public Health . 2019;19:2–7. doi: 10.1186/s12889-019-7854-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Fekadu G. A., Kassa G. M., Berhe A. K., Muche A. A., Katiso N. A. The effect of antenatal care on use of institutional delivery service and postnatal care in Ethiopia: a systematic review and meta-analysis. BMC Health Services Research . 2018;18:1–11. doi: 10.1186/s12913-018-3370-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.National Populations Commission. ICF International, and USA Rockville, Maryland. 2014. Nigeria Demographic and Health Survey 2013 . Abuja, Nigeria: National Populations Commission; 2014. https://dhsprogram.com/pubs/pdf/fr293/fr293.pdf . [Google Scholar]
  • 21.Zegeye B., Ahinkorah B. O., Wheelr D. I., Oladimeji O., Yaya S. Predictors of institutional delivery service utilization among women of reproductive age in Senegal: a population-based study. BMC . 2021;79:1–11. doi: 10.1186/s13690-020-00520-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Adjiwanou V., LeGrand T. Does antenatal care matter in the use of skilled birth attendance in rural Africa: a multi-country analysis. Social Science and Medicine . 2013;86:26–34. doi: 10.1016/j.socscimed.2013.02.047. [DOI] [PubMed] [Google Scholar]
  • 23.Ndao-Brumblay S. K., Godfrey M., Kruk M. E. Parity and institutional delivery in rural Tanzania: a multilevel analysis and policy implications. The Journal on Health Policy and Systems Research . 2013;28(6):647–657. doi: 10.1093/heapol/czs104. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Baatiema L., Ameyaw E. K., Moomin A., Zankawah M. M., Koramah D. Does antenatal care translate into skilled birth attendance? analysis of 2014 Ghana demographic and health survey. Advances in Public Health . 2019;2019:7. doi: 10.1155/2019/6716938.6716938 [DOI] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The numerical model simulations upon which this study is based are too large to archive or transfer. Instead, we provide all the information needed to replicate the simulations and can be found in the references. The model code, compilation script, initial and boundary condition files, and the namelist settings are available on the reference page.


Articles from Obstetrics and Gynecology International are provided here courtesy of Wiley

RESOURCES