Skip to main content

Coverage-level and predictors of maternity continuum of care in Nigeria: implications for maternal, newborn and child health programming

Abstract

Background

Completing maternity continuum of care from pregnancy to postpartum is a core strategy to reduce the burden of maternal and neonatal mortality dominant in sub-Saharan Africa, particularly Nigeria. Thus, we evaluated the level of completion, dropout and predictors of women uptake of optimal antenatal care (ANC) in pregnancy, continuation to use of skilled birth attendants (SBA) at childbirth and postnatal care (PNC) utilization at postpartum in Nigeria.

Methods

A cross-sectional analysis of nationally representative 21,447 pregnancies that resulted to births within five years preceding the 2018 Nigerian Demographic Health Survey. Maternity continuum of care model pathway based on WHO recommendation was the outcome measure while explanatory variables were classified as; socio-demographic, maternal and birth characteristics, pregnancy care quality, economic and autonomous factors. Descriptive statistics describes the factors, backward stepwise regression initially assessed association (p < 0.10), multivariable binary logistic regression and complementary-log–log model quantifies association at a 95% confidence interval (α = 0.05).

Results

Coverage decrease from 75.1% (turn-up at ANC) to 56.7% (optimal ANC) and to 37.4% (optimal ANC and SBA) while only 6.5% completed the essential continuum of care. Dropout in the model pathway however increase from 17.5% at ANC to 20.2% at SBA and 30.9% at PNC. Continuation and completion of maternity care are positively drive by women; with at least primary education (AOR = 1.27, 95%CI = 1.01–1.62), average wealth index (AOR = 1.83, 95%CI = 1.48 –2.25), southern geopolitical zone (AOR = 1.61, 95%CI = 1.29–2.01), making health decision alone (AOR = 1.39, 95%CI = 1.16–1.66), having nurse as ANC provider (AOR = 3.53, 95%CI = 2.01–6.17) and taking at least two dose of tetanus toxoid vaccine (AOR = 1.25, 95%CI = 1.06–1.62) while women in rural residence (AOR = 0.78, 95%CI = 0.68–0.90) and initiation of ANC as late as third trimester (AOR = 0.44, 95%CI = 0.34–0.58) negatively influenced continuation and completion.

Conclusions

6.5% coverage in maternity continuum of care completion is very low and far below the WHO recommended level in Nigeria. Women dropout more at postnatal care than at skilled delivery and antenatal. Education, wealth, women health decision power and tetanus toxoid vaccination drives continuation and completion of maternity care. Strategies optimizing these factors in maternity packages will be supreme to strengthen maternal, newborn and child health.

Peer Review reports

Introduction

Continuum of Care (CoC) for maternal healthcare involves an integrated system that connects essential maternal, newborn and child health (MNCH) services, throughout preconception, pregnancy, childbirth, postnatal and child care [1]. Strengthening MNCH framework through the integrated CoC model remains an optimum strategic design to accomplish mother and child survival, especially in sub-Saharan Africa (SSA) where the defunct Millennium Development Goals (MDG) 4 and 5 were not achieved by 2015 [2, 3]. The goals are now included in the Sustainable Development Goals (SDG) [4]. CoC that covered antenatal care (ANC), skilled delivery and postnatal care (PNC) services are therefore paramount to attain complication-free pregnancy, optimal health, and as well reduced maternal and neonatal morbidity and mortality [5].

However, most women in SSA including Nigeria either failed to complete the required antenatal, intrapartum and postpartum care or dropout from the CoC [6, 7]. High dropout in combination with other factors explained the high maternal mortality ratio (MMR) in SSA with Nigeria among the top four most affected countries [8]. Whereas, most of the maternal death in SSA that accounted for two-thirds of global MMR are preventable if the WHO recommendations for optimal ANC; through early initiation and a minimum of 4 contacts (and now 8 with specific components like; blood and urine test, tetanus toxoid vaccination, intermittent preventive treatment and so on) in pregnancy, intrapartum care during labor and childbirth and PNC within the first six weeks after births by skilled birth attendants (SBA) for a positive outcome were upheld [9,10,11,12].

The current MMR estimate in Nigeria according to WHO is 917 deaths per 100, 000 livebirths [8, 13]. Though the recent population health survey in Nigeria reported MMR as 512 deaths per 100,000 live births and pregnancy-related mortality ratio (PRMR) as 556 deaths per 100,000 livebirths while neonatal mortality rate (NMR) is 39 deaths per 1000 livebirths in 2018 and, thus implying about one death in every 25 livebirths [14]. The slightly lower MMR can be ascribed to a slight increase in ANC coverage from 61% in 2013 to 67% in 2018, skilled delivery increase from 39% in 2013 to 43% in 2018 while PNC coverage stayed at 42% in 2018 [14,15,16].

Despite the recent increase, Nigeria still fell short of the recommended coverage level for the three major maternity services and such little rise over the years has continued to slow progress in achieving MMR and NMR of less than 70 per 100,000 and 25 per 1000 livebirths by 2030 respectively [4, 17]. MNCH framework that incorporated CoC model strategy was evidently adopted in Egypt (Northern Africa) through programs that double SBA to parturient ratio and improved institutional facilities that encourage ANC and PNC has led to the achievement of more than 90% coverage, up to 50% CoC completion and reduced maternal and neonatal deaths [18, 19].

Parturient in Nigeria are however affected by many factors in the use of maternal health services [17, 20]. Studies have reported that wealth, education, type of residence among others are associated with the underutilization and utilization of ANC in Nigeria [21,22,23]. Literatures on SBA use in Nigeria highlighted births preparedness, ANC visit, pregnancy complications and women’s involvement in healthcare decisions as major determinants [13, 24,25,26]. The effect of both ANC and SBA utilization on PNC uptake has been reported [27,28,29]. Literatures on maternity CoC completion in Nigeria are limited but studies have found that maternity CoC Completion in Ethiopia is associated with ANC initiation within second trimester, secondary education, involving women in healthcare decision and reachable distance to health center [30, 31]. Similar factors in addition to media access, birth order and being informed of signs of pregnancy complications were determinants of continuity of maternity CoC in the Gambia [32]. Whereas, urine sample testing in pregnancy, household wealth status and delivery at a health facility were significantly associated with women’s continuation from use of SBA to PNC after receiving ANC in Cambodia [33].

Though studies have independently investigated ANC, SBA and PNC in Nigeria [21,22,23,24,25,26, 34], there is however paucity of information on the linkage among the three pillars of maternity CoC. Although Akinyemi et al. assessed dropout, the study did not consider the recommended optimal number of ANC contacts and the pregnancy-related factors [6]. Meanwhile, the policy goal of the healthcare system is to ensure that every pregnant woman receives all essential maternal health services across the pathway of the childbirth. Also, the coverage gap in the completion of maternity CoC based on time dimension (pregnancy to postpartum period) has not been studied in Nigeria.

This study thus adds to the body of knowledge on maternal and child health by considering the optimal ANC contacts recommended by WHO, delivery assisted by SBA, and first PNC within the first 48 h after childbirth in investigating the levels of coverage of maternity continuum of care and its determinants in Nigeria. In this study, we answered the following questions; What is the level of coverage of the maternity continuum of care in Nigeria? Is the rate of dropout from maternity healthcare similar along the continuum of care pathway? What are the socio-demographics and maternal health characteristics associated with the maternity continuum of care in Nigeria? The research findings will provide evidence-based information for MNCH programs that will support policy decisions toward strengthening pregnancy, childbirth, and puerperium care in Nigeria.

Methodology

Study design, data and area

The study is a secondary analysis of 2018 Nigerian Demographic and Health Survey (NDHS) data. NDHS is a cross-sectional population-based and nationally representative survey routinely collected in five years’ intervals in Nigeria. Nigeria is administratively grouped into six geopolitical zones (Northcentral, Northeast, Northwest, Southeast, Southsouth and Southwest) with an average of 6 states per geo-political zone and the federal capital territory (FCT) as the administrative headquarter [14]. Each state is further divided into local government areas that serve as the lowest and the closest administrative cadre of government for the people. The 36 states and FCT are shown in the study area map in Fig. 1.

Fig. 1
figure 1

Map of Nigeria showing the 36 states and FCT by the geopolitical zones

Sampling strategy and participants

The sampling frame of the 2018 nationally representative NDHS was obtained from the list of rural and urban enumeration areas collated by the National Population and Housing Census (NPHC) in Nigeria. A two-stage stratified random sampling design was used in the 2018 NDHS, where 1400 enumeration areas consisting of 820 rural and 580 urban strata were selected using probability proportional to size at the first sampling stage. Hence the difference in the number of urban and rural strata. Equal probability systematic sampling was then used to select the same number of households (30 households per enumeration area) in the second sampling stage. A total of 41,821 (22,658 in rural and 19,163 in urban) women participants were interviewed in the cross-sectional survey that achieve a 99% response rate [14]. 21,447 women who had at least one ANC visit and whose information were at least non-missing in one of the maternity CoC pathway made up the weighted sample size of the study. The survey also collected information on women’s demographics, socioeconomic and health-related characteristics that includes the key measures of the maternity continuum of care (ANC, SBA and PNC) investigated in this study.

Outcome variables

Outcomes of interest in this study are the maternity continuum of care received during pregnancy (ANC), childbirth (use of SBA) and post-delivery (PNC). A postpartum woman is regarded to have completed the three gamut of care if she received the recommended 4 or more ANC contacts in a healthcare facility during pregnancy, move on to utilize SBA i.e., delivery assisted by at least a doctor, nurse or midwive and subsequently received postnatal checkup within the first 48 h after childbirth [14]. The combined outcome was based on the WHO recommendation of at least 4 ANC visits and the use of SBA at birth, especially in low-resource settings of the lower-middle-income countries [11, 12]. We measured PNC within the first two days after birth which has been reported in the 2018 NDHS due to most maternal morbidity and mortality that occur at the time and therefore highlighted PNC (within two days) as an important measure in the maternity CoC model [33]. We avoided the adaptation of the recently recommended 8 ANC contacts since the DHS framework was designed on a minimum of 4 ANC visits as the optimal number of ANC visit and also; because the strategy to implement the 8 ANC visits was recently devised in the orientation package for healthcare providers in Nigeria after most of the respondents have had the indexed childbirth [14, 35, 36]. The outcome variable was obtained from the combination of responses to the following questions:

  • 1. How many times did you receive antenatal care during this pregnancy?

  • 2. Who assisted with the delivery of (NAME)?

  • 3. Did anyone check on your health after you left the facility i.e., the place of delivery?

Three sets of dichotomous variables were extracted, such that; a positive response to question ‘1’ is 4 or more ANC and negative response is ANC visit less than 4 (0, 1, 2, 3), response to question ‘2’ that delivery was assisted by doctor/nurse/midwife is a positive response and otherwise a negative response and similarly positive response to question ‘3’ is ‘Yes’ and ‘No’ is the negative response. The sequence of maternity continuum of care was drawn from the combination of positive responses. Hence, positive response to; question 1 indicate ANC (4 +) visits, question 2 indicate ANC (4 +) visits and SBA use and question 3 indicate maternity CoC completion in this study i.e., when ANC (4 +), SBA and PNC were all received.

Explanatory variables

Independent variables included in this study were based on similar factors considered by previous studies that investigated the maternity continuum of care [3, 5, 30,31,32,33, 37]. This can be defined under the broad categories as; socio-demographic characteristics, maternal health and birth factors, quality of pregnancy care received, economic status and physical and autonomy factors [13, 38, 39].

Socio-demographic characteristics

These includes maternal age (15–24, 25–34, 35–49 years), place of residence (urban, rural), educational level (none, primary, secondary, tertiary), marital status (never married, married, cohabiting, divorced/widowed/separated) husband educational level (none, primary, secondary, tertiary), geopolitical zone (northcentral, northeast, northwest, southeast, south-south, southwest).

Maternal health and birth factors

These are birth-related and women health-seeking characteristics. Which are; wanted last pregnancy (wanted then, wanted later, wanted no more), birth order (1, 2, 3 and 4 +), covered by health insurance (no, yes), the timing of first ANC visit (first, second and third trimester), institutional delivery (yes, no), delivery by caesarian section mode (yes, no), childbirth sex (male, female), child-size at birth (very small, smaller than average, average, larger than average, very large).

Quality of pregnancy care received

These are factors assessing pregnancy care which are; status of blood pressure measured during pregnancy (yes, no), urine sample taken during pregnancy (yes, no), blood sample taken during pregnancy (yes, no), iron-folic acid tablet taken during pregnancy (yes, no), number of tetanus toxoid vaccine taken during pregnancy (0, 1, 2 +), provider of ANC (no one/traditional birth attendant, community health ‘extension’ worker, auxiliary nurse/midwife, skilled nurse/midwife, doctor).

Economic status

Employment type (not-working/manual/clerical, agricultural, sales, services, professional/ managerial/technical/), Wealth index (poor, average, rich), Media access (no, yes).

Healthcare accessibility and autonomy factors

Distance to health facility (no problem, big problem), Person who usually decides on respondent’s healthcare (respondent alone, both, spouse alone), Person who usually decides on how respondent’s earnings are spent (partner alone, joint decision, respondent alone).

Statistical analysis

Descriptive statistics of the background characteristics and outcomes were reported in frequency and percentages. Missing data were reported for at least 1% of the observation and otherwise negligible i.e., less than 1%. Three sequences of maternity CoC model defined under the space that; postpartum women received at least 4 ANC visits during pregnancy was coded as 1 and 0 otherwise – model 1, continued from ANC (4 +) to use SBA at childbirth was coded as 1 and 0 otherwise – model 2 and completed the three key CoC which is from ANC (4 +) to SBA and to PNC after childbirth was equally coded as 1 and 0 otherwise – model 3 were fitted.

Initially, model selection was carried out to assess the set of maternal factors/characteristics associated with the maternity CoC model (models 1, 2 and 3). This was carried out using the backward stepwise logistic regression for models 1 and 2 and backward stepwise complementary log–log regression for model 3 due to the rare outcome and since the probability of completing the three key maternity continuum of care is small (less than 10%). The backward regression started with the full model and at each model step, the variable whose removal significantly reduced the log likelihood (-2logL) was returned and retained in the model and otherwise removed. All the independent variables were given an equal chance of selection and variable inclusion was considered at p < 0.10.

Bivariate and Multivariate analysis that includes all the significant variables retained in the stepwise regression (final models 1, 2 and 3) were performed to determine the likelihood and significance of each of the predictor variables and the combined set of the predictors respectively. The respective unadjusted and adjusted odds ratio were reported for the binary logistic regression analysis of models 1 and 2 while the unadjusted and adjusted e(form) or exp(b) equivalent of the odds ratio was reported in the multivariable complementary log–log analysis of model 3. Data were weighted with the women’s sample weight indices included in the NDHS data and the svyset command was used to adjust for unequal group/population sizes due to the complex survey design. Bivariable and multivariable statistical analysis were performed at 10% and 5% level of significance (95% confidence level) respectively, using Stata version 16.0 (Stata Corp, Texas, USA). Variable (Union type) that causes multicollinearity (variance inflation factor > 5) was subsequently removed from the multivariate analysis.

The multivariable regression analysis

The multiple binary logistic regression and the complementary log–log modeled the odds of optimal ANC uptake and continuation to the use of SBA and PNC as a binary response [P(\({Y}_{i}=0\)), P(\({Y}_{i}=1)]\) [40, 41]. The multiple logistic model which equates the function of the odds to a linear combination of the regression terms and the predictors is generally expressed as:

$${Y}_{i}= \mathrm{ln}\left(\frac{P}{1-P}\right)= {\beta }_{0}+ {\beta }_{1}{X}_{1i}+\dots + {\beta }_{p}{X}_{pi}+ \varepsilon$$
(1)
$$E\left({Y}_{i}\right)={P}_{i}=\frac{\mathrm{exp}\left({\beta }_{0}+{\beta }_{1}{x}_{1i}+\cdots +{\beta }_{p}{x}_{pi}\right)}{1+\mathrm{exp}\left({\beta }_{0}+{\beta }_{1}{x}_{1i}+\cdots +{\beta }_{p}{x}_{pi}\right)}$$
(2)

where: \(\mathrm{ln}\left(\frac{P}{1-P}\right)\) is the log odds (P is the probability of success and 1-P is the failure probability).

\({\beta }_{0}\) is the logistic regression constant.

\({\beta }_{1}+\dots + {\beta }_{p}\) are the px1 vector of regression coefficient or estimates of the multiple predictors.

\({X}_{i1}+\dots +{X}_{ip}\) are the nxp matrix of explanatory variables predicting the log odds in the model.

When the probability of success “P” is very large or very small (less than 10%) leading to asymmetrical S-shape compared to the symmetric logistic curve [42], the use of the complementary log–log model becomes more appropriate (accurate) as it’s in rare CoC outcome. The complementary-log–log model is generally stated as:

$${Y}_{i}=\mathrm{log}\left\{-\mathrm{log}\right.\left.\left[1-\pi \left(\mathrm{x}\right)\right]\right\}={\beta }_{0}+{\beta }_{1}{X}_{1i}+\cdots +{\beta }_{p}{X}_{pi}+\varepsilon$$
(3)
$$\mathrm E\left(Y_i\right)=\pi\left(\mathrm x\right)=1-\exp\left[-\exp\left(\beta_1X_{1i}+\cdots+\beta_pX_{pi}\right)\right]$$
(4)

where log{-log[1-π(x)]} is the complementary log–log transformation with binary response (0, 1).

Results

Maternity continuum of care model pathway

Figure 2 shows the pathway of the continuum of care model (from pregnancy to delivery and to postpartum), based on the key maternity health service received at each stage. Antenatal care assessed maternal health service received in pregnancy, skilled birth attendant utilization at delivery and postnatal care at postpartum. Among the 21,447 pregnancies reported in NDHS 2018, 75.1% (16,114) received antenatal care at least once. Antenatal care was optimal in this study when a postpartum woman received at least 4 contacts (n = 12,362, P = 57.6%) which made up pregnant women’s inclusion in the first stage of the CoC model (Model-1).

Fig. 2
figure 2

Model pathway showing continuation to and dropout from maternity continuum of care in Nigeria

About 37.4% (8023) of Pregnant women continued to use skilled birth attendants at childbirth. Implying that 20.2% (4339) who had delivery performed by unskilled births attendants after receiving optimal antenatal care drop out at the second stage of the CoC model. Continuation to use of postnatal care service at the third stage after receiving optimal ANC and SBA indicates completion of the CoC by only 6.5% (1388) while 30.9% (6635) dropped out from postnatal care service after receiving optimal ANC and SBA. Dropout from any of the CoC models at any stage along the pathway will lead to incomplete receipt of the essential maternal health service across pregnancy to the puerperium continuum. The CoC model pathway is shown in Fig. 2.

Background characteristics

Table 1 shows the percentage distribution of women who had at least one birth in the last 5 years preceding the survey by background characteristics. About 25% of the women respondents were in the early maternal age (15–24 years), while 27.5% were in the late maternal age (35–49 years). Nine of ten (91.4%) were married, 2.8% were cohabiting while 3.5% are either divorced or widowed. 45.2% and 34.1% of women and their partner has no education while only 8.5% and 14.2% of women and their partners have completed higher education respectively. 61.0% of respondents resides in the urban area and, are not exposed to mass media and only 28.1% belonged to the rich wealth quintile. Most (35.6%) of the women respondents were from the northwest geopolitical zone compared to the few (9.0%) from the south-south (Table 1).

Table 1 Descriptive analysis of women characteristics

About 88% of the women wanted the pregnancy and about 50% have had at least four births. Only 2.2% were covered by health insurance while about 48.5 and 28.2% reported big problems in getting money for medical help and in reaching medical facilities respectively (Table 1). Most (56.2%) of women’s healthcare decisions were made by the partner while only 8.8% of the women made their healthcare decision alone. Nurse/Midwives were the providers of ANC for 56.8% of the women while 26.4% either had no-one or utilized TBA (Table 1). Only nearly 18% had first ANC in 1st trimester. 70.6, 65.8 and 64.8% of women had their blood pressure measured, blood and urine sample taken at ANC respectively. 69 and 53.1% of the women took iron folic acid and at least 2 dose of tetanus vaccine during pregnancy respectively. 40.4% of the women delivered at a hospital and 3.1% of them were through Caesarian mode. 51.2% of the women recently delivered a male child while 48.8% delivered a female child. About 2.8% of the women delivered a child that is very small in size while 8.9% delivered a very large child (Table 1).

Retention in the maternity continuum of care

Figure 3 shows that only 6.5% of the women population completed the maternity continuum of care (received optimal ANC, continue to use SBA at childbirth and received PNC service after delivery) while 93.5% of the women had an incomplete maternity continuum of care (at least one of the optimal ANC, SBA and PNC service was not received). 37.4% received optimal ANC and SBA, 57.6% received Optimal ANC only and 75.1% received at least one ANC (Fig. 3).

Fig. 3
figure 3

Coverage-level of maternity continuum of care by women with at least a birth

Modelling factors associated with the continuum of care

The result of backward stepwise regression in Table 2 highlighted selected variables associated with women uptake of optimal ANC (4 +) (model 1), continuation to use of SBA (model 2) and the use of PNC (model 3). In model 1, marital status (-2logL = 2.049, p = 0.152) and Employment type (-2logL = 0.855, p = 0.355), and other variables whose inclusion led to insignificant change in -2logL were removed from the full model 1 while the remaining variables whose removal led to significant (p < 0.10) change in -2logL were retained (Table 2). Similarly, institutional delivery (-2logL = 2341.697, p = 0.000) along with other variables led to a significant (p < 0.10) change in -2logL and were therefore retained in model 2. Also, the removal of women and partner education, women healthcare decider, provider of ANC, time of first ANC and others that led to a significant change in -2logL (Table 2) were subsequently retained in the final model 3 (CoC completion).

Table 2 Backward stepwise model selection of factors associated with maternity continuum of care

Multivariable regression analysis

Predictors of receiving optimal ANC (4 +) contacts among study participants

Model 1 (presented in Tables 3 and 4) shows the regression analysis of the predictors of optimal ANC (4 +) received by women who had at least one birth in the last five years preceding the survey. Average (UOR = 2.72, 95%CI = 2.52–2.93; AOR = 1.21, 95%CI = 1.06–1.37) and rich (UOR = 7.69, 95%CI = 7.16–8.27; AOR = 1.30, 95%CI = 1.11–1.51) women are more likely to receive 4 ANC than poor women. The odds of receiving at least 4 ANC increase by women and partner education and decrease by age and birth order. The place of residents and region were other socio-demographics predictors of receiving at least 4 ANC services (Tables 3 and 4).

Table 3 Unadjusted odds ratio of the association between maternity continuum of care by women characteristics
Table 4 Adjusted odds ratio of the association between maternity continuum of care by women characteristics

Healthcare decisions made alone by the women increase the odds of receiving at least 4 ANC by 30% compared to healthcare decisions made by the partner alone (AOR = 1.30, 95%CI = 1.08–1.54) (Table 4). Getting money for medical help however decrease the odds when it’s a big problem (UOR = 0.54, 95%CI = 0.51–0.57; AOR = 0.89, 95%CI = 0.81–0.99). ANC provided by the doctor was strongly associated with at least 4 ANC uptake when other variables were unadjusted (UOR = 121.2, 95%CI = 99.8–147.2) (Table 3). Women are 3 and 25 times less likely to receive at least 4 ANC when the first ANC received was in the second (UOR = 0.27, 95%CI = 0.23–0.31; AOR = 0.32, 95%CI = 0.27–0.37) and third (UOR = 0.03, 95%CI = 0.02–0.03; AOR = 0.04, 95%CI = 0.03–0.05) trimester respectively (Tables 3 and 4). Urine sample (AOR = 1.54, 95%CI = 1.34–1.75) and not less than 2 tetanus toxoid vaccine doses (AOR = 2.03, 95%CI = 1.75–2.36) taken in ANC approximately twice increase the odds of receiving 4 ANC (Table 4).

Predictors of women continuation to SBA after receiving optimal ANC (4 +) contacts

Factors predicting women continuation to the use of SBA after receiving optimal [4] ANC in pregnancy were determined from model 2 (ANC (4 +) and SBA) as shown in Tables 3 and 4. The result shows that all the factors (except partners’ education, getting money for medical help and urine sample taken in ANC) that were significant in model 1 were also significant in model 2 (including marital-status, distance to health facility and institutional delivery added to the model) (Tables 3 and 4). While women in maternal age 35–49 (UOR = 1.64, 95%CI = 1.51–1.77; AOR = 1.64, 95%CI = 1.29–1.95) are more likely to continue to the use of SBA after receiving 4 ANC, women residing in the rural (UOR = 0.19, 95%CI = 0.18–0.20; AOR = 0.75, 95%CI = 0.65–0.85) are less likely to continue to SBA after receiving 4 ANC (Tables 3 and 4).

Distance to health facility decrease the odds of continuation to SBA after receiving 4 ANC by almost half (48%) when other factors were unadjusted (UOR = 0.52, 95%CI = 0.48–0.55). The Odds of continuation to SBA otherwise increase when health decisions were made jointly (UOR = 4.38, 95%CI = 4.10–4.68; AOR = 1.26, 95%CI = 1.06–1.50) (Tables 3 and 4). Also, odds of continuation to SBA after 4 ANC increases and decreases by the rank of a healthcare provider when other factors were unadjusted and adjusted respectively. Similar to model 1, Women who received first ANC in second (UOR = 0.52, 95%CI = 0.44–0.62; AOR = 0.43, 95%CI = 0.40–0.47) and third (UOR = 0.08, 95%CI = 0.07–0.09; AOR = 0.08, 95%CI = 0.06–0.10) trimester are 2 and 13 times less likely to continue to SBA after receiving 4 ANC compared to those who received ANC in first trimester respectively (Tables 3 and 4). The odds of continuation to ANC increases when a woman took at least 2 doses of tetanus toxoid vaccine and had hospital delivery (Tables 3 and 4).

Predictors of women continuation to PNC after receiving optimal ANC (4 +) and using SBA at delivery (completion of the key continuum of care)

The predictive factors of PNC use after optimal ANC (4 +) contacts and SBA service were received were evaluated in model 3 (ANC (4 +), SBA and PNC) as presented in Tables 3 and 4. The result shows that other than marital status, all other predictors are significant in model 3 either under the unadjusted or adjusted (or both) association. Women from the southeast (UOR = 2.73, 95%CI = 2.26–3.32; AOR = 1.61, 95%CI = 1.29–2.01) and southwest (UOR = 2.73, 95%CI = 2.27–3.22; AOR = 1.68, 95%CI = 1.37–2.06) are approximately twice as likely as those from northcentral to continue to PNC after receiving 4 ANC and SBA (Tables 3 and 4). The odds of PNC use after receiving 4 ANC and SBA increases with women and their partners’ educational levels (Tables 3 and 4). Women in rich wealth quintiles increase the odds of PNC use after 4 ANC and SBA while women residing in the rural decrease the odds of PNC use after 4 ANC and SBA were received (Tables 3 and 4).

Taking at least 2 doses of tetanus toxoid vaccine (UOR = 9.17, 95%CI = 7.21–11.2) and checking blood pressures (UOR = 1.54,95%CI = 1.17–2.01) in ANC increase the odds of receiving PNC after 4 ANC and SBA by 817% and 54% respectively, but the odds decrease by 38% When getting money for medical help is a big problem (Tables 3 and 4). Institutional delivery increase and decrease the odds of receiving PNC after 4 ANC and SBA by 156% and 56% (UOR = 2.56, 95%CI = 2.29–2.85; AOR = 0.54, 95%CI = 0.47–0.62) respectively (Tables 3 and 4). Women who took iron folic acid in ANC (AOR = 1.98, 95%CI = 1.57–2.49) and had Caesarian delivery (AOR = 1.57, 95%CI = 1.28–1.91) are almost twice as likely as those who don’t to continue to PNC after receiving 4 ANC and SBA. Healthcare decisions made alone by women and ANC provided by doctors were strongly and positively associated with PNC use while the first ANC received in the second and third trimester were also strongly but negatively associated with PNC use respectively (Tables 3 and 4).

Discussion

We investigated the gaps in the maternity continuum of care by evaluating the level of coverage and predictors of maternity continuation of care from pregnancy to childbirth and to the postpartum period in Nigeria. The goal is to inform a programming guide on designing improved MNCH intervention policy strategy, since CoC connects the essential maternal health services (ANC, SBA and PNC) and were assessed in this study based on the WHO recommendations for optimal care.

Coverage of antenatal care service in Nigeria has improved but has remained below the recommended 90% level as only 75% of pregnant women attended antenatal care at least once. It is however discouraging that barely 58% of pregnant women received at least four ANC contacts. This is in consonance with the report of the demographic health survey and a recent study on the sub-national analysis of optimal ANC utilization and satisfaction in Nigeria [10, 14, 43]. Continuation from optimal antenatal care to skilled delivery care service was observed in only over a third (37.4%) of the women while only one of every 15 (6.5%) pregnant women continued from ANC to SBA and PNC due to high dropout rate along the pathway of the continuum of care. Thus, there is more dropout between delivery and postnatal period than between pregnancy and childbirth period and therefore explain the irregular pattern in the continuation of care as reported in similar study in Nigeria and Ethiopia in SSA [6, 44].

Individual factors associated with women’s optimal ANC received in pregnancy are also associated with whether they utilized skilled delivery at birth and whether such women received postnatal care in the first 48 h after delivery. Hence the reason for the parallel identification of factors by the backward stepwise regression across the CoC model pathway. Women’s educational level, place of residence, region and wealth status were the socio-demographic and economic factors associated with the three essential maternal health service utilization while women’s healthcare decision-maker, provider of ANC, the timing of first ANC contact and number of tetanus toxoid vaccines taken as well as place (hospital) and mode (caesarian) of delivery were the associated interacting health system factors across the pathway of pregnancy to postpartum continuum and from delivery to post-delivery respectively. A similar factor has been identified by other studies in sub-Saharan Africa and Southeast Asia though with different statistical techniques (chi-square test of association) due to the comparability of women’s social-demographic, economic and health-related characteristics that includes quality of pregnancy care [6, 32, 33, 37].

Regardless of adjustment for women’s background characteristics, Women’s educational level is significantly associated with the use of ANC and continuation to the use of SBA and PNC. This implies that women with at least primary education are more likely to receive optimal ANC service and go on to use SBA and PNC at delivery and post-delivery respectively than those without any formal education. This aligns with studies that also found the significant effect of education on CoC in maternal health services [30, 33, 37]. Women residing in rural communities are however less likely to receive optimal ANC service, continue to use SBA at delivery and even complete the maternity continuum of care compared to those residing in the urban area. This can be attributed to a low level of education, preference for traditional births and the problem of accessibility and poor perception about primary healthcare service in the proximity of sub-Sahara African women [45]. Also, ANC provided by skilled and trained healthcare workers like; doctors, nurse/midwife was strongly and significantly associated with the maternity continuum of care across the 3 key maternity healthcare services (optimal ANC, SBA and PNC). Thus, women who received ANC from skilled providers have a higher likelihood of completing the care continuum than those who received care from unskilled providers. This highlighted the motivating impact of skilled healthcare providers on pregnancy outcomes compared to unskilled healthcare providers [46]. Also, in agreement with the study assessing women narrative of skilled delivery care provider and the implications for policy perspective in Nigeria and Ghana [47, 48].

Furthermore, geopolitical zone and socio-economic level positively influenced the use of optimal ANC, continuation to SBA and PNC as women from wealthier households and in the southern region (especially southeast and southwest) are more likely to receive and complete maternal health service than the poor women and those living in the northern region respectively. Inequality in the social-economic and geographical distribution of healthcare infrastructure has remained a militating factor of maternal health practice in Nigeria and Africa due to low coverage and selective health insurance package [21, 49, 50]. Late initiation of ANC (any time after the recommended first trimester) on the other hand negatively influence receiving optimal ANC, continuing to the use of SBA and PNC while receiving at least two tetanus vaccine during pregnancy increase the odds of receiving optimal ANC and sequentially completing the care of maternity continuum. The significance of ANC timing and tetanus vaccine status were also discovered in studies investigating the completion of maternity health services in Ethiopia [3, 5, 31]. We further observed that Women’s healthcare decision power is strongly associated with optimal ANC received, continuation to use of SBA and use of PNC. This is similar to findings from studies in Nigeria which reported the impact of women’s healthcare decision power on SBA use [13, 25] and comparable to a CoC study somewhere else that found an association between women’s healthcare decision power and the receipt of optimal ANC and continuation to use of PNC [37].

Maternal age and birth order (which decrease the odds of CoC as parity increases) were other significant predictors of optimal ANC receipt and continuation to use of SBA but not PNC. This finding was also reported in a study across 28 sub-Saharan African countries that investigated predictors of retentions in SBA after ANC service utilization [7]. Partners’ educational level and getting the money needed for medical help predicts women’s receipt of optimal ANC and PNC but not SBA. The problem of getting money for medical help is due to poor health insurance coverage and this along with the parity effect has been reported as determinant of ANC and optimal ANC use in a systematic review in SSA and a cross-sectional study in Nigeria respectively [10, 51].

Institutional delivery however predicts the use of SBA and subsequent use of PNC which was found to be significant in similar studies [33, 37, 52], Caesarian delivery is only associated with PNC visit. This can be recognized from the fact that hospital and caesarian delivery are assisted by skilled healthcare providers and most women who had caesarian birth will likely receive postnatal care to ensure recovery from the surgical site pain and to avoid infection as women with a normal vaginal delivery are more likely to have a better postnatal quality of life [53].

We further deduce that urine samples taken in ANC increase the chance of receiving optimal ANC while women who perceived distance to a health facility as a big problem are less likely to utilize SBA at delivery even if they receive optimal ANC. Which is in agreement with findings from similar studies in Nigeria and the Gambia [13, 32]. Blood pressure checked in ANC and iron-folic acid taken independently predict women’s continuation to use of PNC after receiving optimal ANC and SBA. However, marital status is not significantly associated with any of the CoC models which is in disagreement with the study that highlighted the significance of paternal influence on maternal health service utilization [54]. The model selection secluded factors assessing employment, health insurance, media exposure and blood sample taken in ANC across the maternity CoC, which was reportedly identified as predictors of SBA use [7, 25]. However, Differences in predictors of maternity CoC at different model stage across the pathway has been substantiated [33, 37].

Conclusions

Despite encouraging turn-up at ANC, coverage of maternity continuum of care is low and below the WHO recommended level and standards in Nigeria. Less than three-fifths, two-fifths and one-fifteenth of pregnant women received optimal ANC, continue to the use of SBA and PNC respectively. The dropout rate across the continuum of care model pathway is alarming and needs an urgent revisit. There is however more dropout at the PNC than SBA and at the optimal ANC. Educational attainment, place of residence, geopolitical zone and wealth status were the joint socio-demographic predictors while women’s healthcare decision power, skilled ANC provider, the timing of first ANC and number of tetanus toxoid vaccines taken in ANC were the equivalent health-related predictors of the key maternity continuum of care. While maternal age and parity were associated with the continuation of care from ANC to SBA, partners’ education and medical finances were associated with PNC continuity after ANC. Hospital delivery predicts the use of SBA and continuation to PNC while Caesarian delivery influences the use of PNC.

Study strengths and limitations

It is not improbable that the study suffers from responder bias since the data quality depends on respondents’ ability to recall events in the last five years preceding the survey. The study investigated the association between women’s characteristics and maternity CoC and does not infer that these factors are causes of maternity CoC due to the cross-sectional design of the data. Therefore, interpretation should be limited to the association. The application of secondary data posed the difficulty of data incompleteness and restricted the authors to the choice of the available set of independent factors assessed in the survey, which was minimized by the analysis of a weighted sample of women with at least one birth in the last five years preceding the survey and the automated model selection approach. Non-availability of variables or data to assess the type of healthcare facility or women first place of care which experience could be the reason for dropout or incomplete CoC was also a limitation. However, the study strength can be observed from the application of a nationally representative sample which increases the study generalizability. The fact that we adjust for complex survey design based on the sample weighting, clustering and stratification improves the reliability of the study findings and accuracy therein. Furthermore, this is the first study that assessed the maternity CoC completion in Nigeria using the well-known and utilized WHO standards on a minimum of 4 ANC, SBA by doctor/nurse/midwife and first PNC within the first 48 h and therefore presents an opportunity to strategize towards transitioning into the newly recommended minimum of 8 ANC contacts and achieving the SDG-3 in Nigeria.

Recommendations

We infer from the study findings that, coverage of the three essentials maternity continuum of care (ANC, SBA and PNC) in Nigeria is below the 90% recommendation, which will halt the attainment of the 2030 SDG on improving childhood health in Nigeria. A centralized strategy that will improve MNCH program practice is however required to unify national programs and breach the coverage gap. Governmental and nongovernmental agencies need to be steadfast in providing improved support for sensitization programs around early ANC initiation and an optimal number of ANC visits (the minimum of 4 and transition into 8). Improved ANC packages that strengthen women in; pregnancy care, healthcare decision power and educational awareness for childbirth preparedness are recommended to improve pregnancy outcomes. Capacity building for pregnant women to improve the use of SBA at delivery and the least utilized PNC at post-delivery is also vital to optimize mother and child survival. Contextual research investigating the reason for dropout and non-compliance with the WHO recommendations of the maternity continuum of care is required to better provide intervention strategy to improve on the low completion coverage.

Availability of data and materials

The anonymized data is available in the public domain. Dataset used (generated and/or analyzed) in this current study are available on reasonable request from the corresponding author, at www.dhsprogram.com and in the DHS program open repository http://dhsprogram.com/pubs/pdf/FR359/FR359.pdf.

Abbreviations

ANC:

Antenatal Care

CoC:

Continuum of Care

CI:

Confidence Interval

FCT:

Federal Capital Territory

LMICs:

Lower-Middle-Income Countries

MMR:

Maternal Mortality Ratio

MNCH:

Maternal Newborn and Child Health

NPHC:

National Population and Housing Census

NMR:

Neonatal Mortality Rate

NDHS:

Nigerian Demographic and Health Survey

PNC:

Postnatal Care

PRMR:

Pregnancy-related Mortality Ratio

SBA:

Skilled Birth Attendants

SSA:

Sub-Saharan Africa

SDG:

Sustainable Development Goals

WHO:

World Health Organization

References

  1. de Graft-Johnson J, Kerber K, Tinker A, Otchere S, Narayanan I, Shoo R. The continuum of care – reaching mothers and babies at the crucial time and place: Opportunities for Africa’s Newborns. 2006;23–36.

  2. Kerber KJ, de Graft-Johnson JE, qar Bhutta ZA, Okong P, Starrs A, Lawn JE. Continuum of care for maternal, newborn, and child health: from slogan to service delivery. The Lancet. 2007;370. Available from: www.thelancet.com.

  3. Asratie MH, Muche AA, Geremew AB. Completion of maternity continuum of care among women in the post-partum period: Magnitude and associated factors in the northwest. Ethiopia PLoS One. 2020;15(8):1–14. https://doi.org/10.1371/journal.pone.0237980.

    Article  CAS  Google Scholar 

  4. United Nations. Sustainable Development Goals (SDG). Washington, DC; 2015.

  5. Haile D, Kondale M, Andarge E, Tunje A, Fikadu T, Boti N. Level of completion along continuum of care for maternal and newborn health services and factors associated with it among women in Arba Minch Zuria woreda, Gamo zone, Southern Ethiopia: a community based crosssectional study. PLoS ONE. 2020;15(6):1–18. https://doi.org/10.1371/journal.pone.0221670.

    Article  CAS  Google Scholar 

  6. Akinyemi JO, Afolabi RF, Awolude OA. Patterns and determinants of dropout from maternity care continuum in Nigeria. BMC Pregnancy Childbirth. 2016;16(1):1–11. https://doi.org/10.1186/s12884-016-1083-9.

    Article  Google Scholar 

  7. Chukwuma A, Wosu AC, Mbachu C, Weze K. Quality of antenatal care predicts retention in skilled birth attendance: A multilevel analysis of 28 African countries. BMC Pregnancy Childbirth. 2017;17(1):152. https://doi.org/10.1186/s12884-017-1337-1.

    Article  Google Scholar 

  8. World Health Organization. Trends in maternal mortality 2000 TO 2017: Estimates by WHO, UNICEF, UNFPA, World Bank Group and United Nations Population Division. 2019. 119 p.

  9. Merdad L, Ali MM. Timing of maternal death: Levels, trends, and ecological correlates using sibling data from 34 sub-Saharan African countries. PLoS One. 2018;13(1):e0189416. https://doi.org/10.1371/journal.pone.0189416.

    Article  CAS  Google Scholar 

  10. Fagbamigbe AF, Olaseinde O, Setlhare V. Sub-national analysis and determinants of numbers of antenatal care contacts in Nigeria: assessing the compliance with the WHO recommended standard guidelines. BMC Pregnancy Childbirth. 2021;21(1):402. https://doi.org/10.1186/s12884-021-03837-y.

    Article  Google Scholar 

  11. World Health Organization. WHO recommendations: Intrapartum care for a positive childbirth experience. Transforming care of women and babies for improved health and well-being Executive summary. 2018;1–8. Available from: https://apps.who.int/iris/bitstream/handle/10665/272447/WHO-RHR-18.12-eng.pdf

  12. World Health Organization. WHO recommendations on antenatal care for a positive pregnancy experience. 2016. 172 p.

  13. Fagbamigbe AF, Oyedele OK. Multivariate decomposition of trends, inequalities and predictors of skilled birth attendants utilisation in Nigeria (1990–2018): a cross-sectional analysis of change drivers. BMJ Open. 2022;12(4):e051791. https://doi.org/10.1136/bmjopen-2021-051791.

    Article  Google Scholar 

  14. National Population Commission, ICF International. Nigeria Demographic and Health Survey 2018. Abuja, Nigeria, And Rockville, Maryland, USA; 2019.

  15. National Population Commission, ICF International. Nigeria Demographic and Health Survey, 2008. DHS Measure Macro, New York and Nigeria Population Commission, Abuja, Nigeria; 2009.

  16. National Population Commission, ICF International. Nigeria Demographic Health Survey, 2013. Abuja; 2014.

  17. Dahiru T, Oche OM. Determinants of antenatal care, institutional delivery and postnatal care services utilization in Nigeria. Pan Afr Med J. 2015;21:1–17. https://doi.org/10.11604/pamj.2015.21.321.6527.

    Article  Google Scholar 

  18. Graham WJ, Hussein J. Universal reporting of maternal mortality: an achievable goal? Int J Gynaecol Obstet. 2006;94(3):234–42. https://doi.org/10.1016/j.ijgo.2006.04.004.

    Article  CAS  Google Scholar 

  19. Hamed A, Mohamed E, Sabry M. Egyptian status of continuum of care for maternal, newborn, and child health: Sohag Governorate as an example. Int J Med Sci Public Health. 2018;7(6):417–26.

    Google Scholar 

  20. Adebowale SA, Akinyemi JO. Maternal Health Assessment. Afr J Reprod Health. 2016;20(2). https://doi.org/10.29063/ajrh2016/v20i2.8

  21. Fagbamigbe AF, Idemudia ES. Wealth and antenatal care utilization in Nigeria: policy implications. Health Care Women Int. 2017;38(1):17–37. https://doi.org/10.1080/07399332.2016.1225743.

    Article  Google Scholar 

  22. Adewuyi EO, Auta A, Khanal V, Bamidele OD, Akuoko CP, Adefemi K, et al. Prevalence and factors associated with underutilization of antenatal care services in Nigeria: a comparative study of rural and urban residences based on the 2013 Nigeria demographic and health survey. PLoS ONE. 2018;13(5):1–21. https://doi.org/10.1371/journal.pone.0197324.

    Article  CAS  Google Scholar 

  23. Oluwamotemi CA, Edoni EE, Ukoha CE, Adelekan AL. Factors associated with utilization of antenatal care services among women of child bearing in Osogbo. Nigeria IJRRGY. 2020;3(1):32–42. Available from: https://journalijrrgy.com/index.php/IJRRGY/article/view/5.

    Google Scholar 

  24. Adewemimo AW, Msuya SE, Olaniyan CT, Adegoke AA. Utilisation of skilled birth attendance in Northern Nigeria: a cross-sectional survey. Midwifery. 2014;30(1):e7. https://doi.org/10.1016/j.midw.2013.09.005.

    Article  Google Scholar 

  25. Fagbamigbe AF, Hurricane-Ike EO, Yusuf OB, Idemudia ES. Trends and drivers of skilled birth attendant use in Nigeria (1990–2013): Policy implications for child and maternal health. Int J Womens Health. 2017;9:843–53. https://doi.org/10.2147/IJWH.S137848.

    Article  Google Scholar 

  26. Olowokere A, Oyedele A, Komolafe A, Olajubu A. Birth preparedness, utilization of skilled birth attendants and delivery outcomes among pregnant women in Ogun State, Nigeria. Eur J Midwifery. 2020;4:22. https://doi.org/10.18332/ejm/120116.

    Article  Google Scholar 

  27. Agho KE, Ezeh OK, Issaka AI, Enoma AI, Baines S, Renzaho AMN. Population attributable risk estimates for factors associated with non-use of postnatal care services among women in Nigeria. BMJ Open. 2016;6(7):1–8. https://doi.org/10.1136/bmjopen-2015-010493.

    Article  Google Scholar 

  28. Igboanusi CJC, Sabitu K, Gobir AA, Nmadu AG, Joshua IA. Factors affecting the utilization of postnatal care services in primary health care facilities in urban and rural settlements in Kaduna State, north-western Nigeria. Am J Public Health Res. 2019;7(3):111–7. Available from: http://www.sciepub.com/AJPHR/abstract/10649.

    Google Scholar 

  29. Olajubu AO, Olowokere AE, Ogundipe MJ, Olajubu TO. Predictors of Postnatal Care Services Utilization Among Women in Nigeria: A Facility-Based Study. J Nurs Scholarsh. 2019;51(4):408–16.

    Article  Google Scholar 

  30. Shitie A, Assefa N, Dhressa M, Dilnessa T. Completion and factors associated with maternity continuum of care among mothers who gave birth in the last one year in Enemay district. Northwest Ethiopia J Pregnancy. 2020. https://doi.org/10.1155/2020/7019676.

    Article  Google Scholar 

  31. Tizazu MA, Sharew NT, Mamo T, Zeru AB, Asefa EY, Amare NS. Completing the continuum of maternity care and associated factors in debre berhan town, amhara, Ethiopia, 2020. J Multidiscip Healthc. 2021;14:21–32. https://doi.org/10.1136/bmjopen-2015-010493.

    Article  Google Scholar 

  32. Oh J, Moon J, Choi JW, Kim K. Factors associated with the continuum of care for maternal, newborn and child health in the Gambia: a cross-sectional study using demographic and health survey 2013. BMJ Open. 2020;10(11):1–10. https://doi.org/10.1136/bmjopen-2019-036516.

    Article  Google Scholar 

  33. Wang W, Hong R. Levels and determinants of continuum of care for maternal and newborn health in Cambodia-evidence from a population-based survey. BMC Pregnancy Childbirth. 2015;15(1):1–9. https://doi.org/10.1186/s12884-015-0497-0.

    Article  Google Scholar 

  34. Agho KE, Ezeh OK, Ogbo FA, Enoma AI, Raynes-Greenow C. Factors associated with inadequate receipt of components and use of antenatal care services in Nigeria: A population-based study. Int Health. 2018;10(3):172–81. https://doi.org/10.1093/inthealth/ihy011.

    Article  Google Scholar 

  35. World Health Organization. WHO antenatal care randomized trial: manual for the implementation of the new model. Health Policy Plann. 2002;7.

  36. Federal Ministry of Health Nigeria. Antenatal Care: An orientation package for healthcare providers. 2017. 1–101 p.

  37. Chham S, Radovich E, Buffel V, Ir P, Wouters E. Determinants of the continuum of maternal health care in Cambodia: an analysis of the Cambodia demographic health survey 2014. BMC Pregnancy Childbirth. 2021;21(1):410. https://doi.org/10.1186/s12884-021-03890-7.

    Article  Google Scholar 

  38. Gabrysch S, Campbell OMR. Still too far to walk: Literature review of the determinants of delivery service use. BMC Pregnancy Childbirth. 2009;9:34. https://doi.org/10.1186/1471-2393-9-34.

    Article  Google Scholar 

  39. Austin A, Fapohunda B, Langer A, Idemudia E. Trends in delivery with no one present in Nigeria between 2003 and 2013. Int J womens Health. 2015;7:345–56. https://doi.org/10.2147/IJWH.S79573.

    Article  Google Scholar 

  40. Tesfaw LM, Fenta HM. Multivariate logistic regression analysis on the association between anthropometric indicators of under-five children in Nigeria: NDHS 2018. BMC Pediatr. 2021;21(1):193. https://doi.org/10.1186/s12887-021-02657-5.

    Article  Google Scholar 

  41. Srimaneekarn N, Hayter A, Liu W, Tantipoj C. Binary response analysis using logistic regression in dentistry. Int J Dent. 2022;8(2022):1–7. https://doi.org/10.1155/2022/5358602.

    Article  Google Scholar 

  42. Lin JH, Lee WC. Complementary log regression for sufficient-cause modeling of epidemiologic data. Sci Rep. 2016;13(6):39023. https://doi.org/10.1038/srep39023.

    Article  CAS  Google Scholar 

  43. Phoebe Nwamaka K, Nkechi Chiejina E, Nwamaka P, Nkechi E. regnant women’s satisfaction with the antenatal services provided by midwives in government-owned health care facilities in south-south, Nigeria. IJRHSN. 2020;6(2):14–27. https://doi.org/10.53555/hsn.v6i12.1423.

    Article  Google Scholar 

  44. Muluneh AG, Kassa GM, Alemayehu GA, Merid MW. High dropout rate from maternity continuum of care after antenatal care booking and its associated factors among reproductive age women in Ethiopia, Evidence from Demographic and Health Survey 2016. PLoS One. 2020;15(6):1–11. https://doi.org/10.1371/journal.pone.0234741.

    Article  CAS  Google Scholar 

  45. Okonofua F, Ntoimo L, Ogungbangbe J, Anjorin S, Imongan W, Yaya S. Predictors of women’s utilization of primary health care for skilled pregnancy care in rural Nigeria. BMC Pregnancy Childbirth. 2018;18(1):106. https://doi.org/10.1186/s12884-018-1730-4.

    Article  Google Scholar 

  46. Okeke E, Glick P, Chari A, Abubakar IS, Pitchforth E, Exley J, et al. The effect of increasing the supply of skilled health providers on pregnancy and birth outcomes: evidence from the midwives’ service scheme in Nigeria. BMC Health Serv Res. 2016;16(1):425. https://doi.org/10.1186/s12913-016-1688-8.

    Article  Google Scholar 

  47. Okonofua F, Ntoimo L, Ogungbangbe J, Anjorin S, ImUdenigwe O, Okonofua FE, Ntoimo LFC, Imongan W, Igboin B, Yaya S. Perspectives of policymakers and health providers on barriers and facilitators to skilled pregnancy care: findings from a qualitative study in rural Nigeria. BMC Pregnancy Childbirth. 2021;21(1):20. https://doi.org/10.1186/s12884-020-03493-8.

    Article  Google Scholar 

  48. Sumankuuro J, Mahama MY, Crockett J, Wang S, Young J. Narratives on why pregnant women delay seeking maternal health care during delivery and obstetric complications in rural Ghana. BMC Pregnancy Childbirth. 2019;19(1):260. https://doi.org/10.1186/s12884-019-2414-4.

    Article  Google Scholar 

  49. Okoli C, Hajizadeh M, Rahman MM, Khanam R. Geographical and socioeconomic inequalities in the utilization of maternal healthcare services in Nigeria. BMC Health Serv Res. 2020;20(1):849. https://doi.org/10.1186/s12913-020-05700-w.

    Article  Google Scholar 

  50. Sanogo NA, Yaya S. Wealth status, health insurance, and maternal health care utilization in Africa: evidence from Gabon. Biomed Res Int. 2020. https://doi.org/10.1155/2020/4036830.

    Article  Google Scholar 

  51. Okedo-Alex IN, Akamike IC, Ezeanosike OB, Uneke CJ. Determinants of antenatal care utilisation in sub-Saharan Africa: a systematic review. BMJ Open. 2019;9(10):1–14. https://doi.org/10.1136/bmjopen-2019-031890.

    Article  Google Scholar 

  52. Oyedele OK, Fagbamigbe AF, Ayeni O. Modelling time-to-discontinuation of exclusive breastfeeding: Analysis of infants and under-2 survival in Nigeria. Etude de la Population Africaine. 2020;34(1):5132–42. https://doi.org/10.11564/34-1-1500.

    Article  Google Scholar 

  53. Torkan B, Parsay S, Lamyian M, Kazemnejad A. Postnatal quality of life in women after normal vaginal delivery and caesarean section. BMC Pregnancy Childbirth. 2009;9:4. https://doi.org/10.1186/1471-2393-9-4.

    Article  Google Scholar 

  54. Mohammed BH, Johnston JM, Vackova D, Hassen SM, Yi H. The role of male partner in utilization of maternal health care services in Ethiopia: A community-based couple study. BMC Pregnancy Childbirth. 2019;19(1):28. https://doi.org/10.1186/s12884-019-2176-z.

    Article  Google Scholar 

Download references

Acknowledgements

The authors appreciate the ICF Macro, owners of the DHS data for granting access to the dataset.

Funding

The authors received no funds from any funder in the public, private or not for profit sector.

Author information

Authors and Affiliations

Authors

Contributions

OKO conceptualized and designed the study, OKO analyzed the data, interpreted the result and wrote the manuscript, AFF, OJA and ASA reviewed the manuscript and contributed to the methodology and interpretation of results. All authors reviewed and approved the final version of the manuscript.

Corresponding author

Correspondence to Oyewole Kazeem Oyedele.

Ethics declarations

Ethics approval and consent to participate

Ethical approval (FWA000008450) was obtained from the Institutional Review Board (IRB) of Inner City Fund (ICF) International Macro at Fairfax, Virginia, United States. We were granted access to the data with the authorization letter 144644. Written informed consent was obtained from all participants prior to data collection as per IRB ethical guidelines for conduct of research. This study did not involve any conduct of experiment or clinical trial. All methods were implemented in accordance with the relevant guidelines and regulations.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Oyedele, O.K., Fagbamigbe, A.F., Akinyemi, O.J. et al. Coverage-level and predictors of maternity continuum of care in Nigeria: implications for maternal, newborn and child health programming. BMC Pregnancy Childbirth 23, 36 (2023). https://doi.org/10.1186/s12884-023-05372-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12884-023-05372-4

Keywords

  • Maternity continuum of care
  • Antenatal care
  • Skilled birth attendants
  • Postnatal care
  • Model Pathway
  • Backward stepwise regression
  • Complementary-log–log model