Health insurance coverage and access to maternal healthcare services by women of reproductive age in Nigeria: a cross-sectional study

Abstract

Background

Inequitable financial access to maternal healthcare services (MHS) has contributed to maternal deaths, especially in low and middle-income countries. Evidence in the literature on women’s health insurance status and access to MHS in Nigeria is sparse. This study aimed to determine the association between health insurance coverage and access to MHS among Nigerian women of reproductive age.

Methods

This is a cross-sectional study that used the 2018 Nigeria Demographic and Health Survey (NDHS). A total of 12 935 women who had their last delivery within 2 years before the NDHS were included in the study. Access to MHS was assessed by using the number of antenatal care (ANC) visits and health facility delivery. Adjusted logistic regression models were fit to control for individual, household and community-level factors.

Results

Only 18.5% and 40.6% of the women in the study attended ≥8 ANC visits and delivered in a health facility, respectively. About 39.5% of women who had ≥8 ANC visits and 71.8% of those who delivered in health facilities had health insurance coverage. There were statistically significant associations between having health insurance and attendance of ≥8 ANC visits (adjusted OR (AOR) 1.9; 95% CI 1.26–2.95) and women delivering at a health facility (AOR 2.0; 95% CI 1.39–2.82). There were also lower significant odds of accessing ≥8 ANC visits and delivering in health facilities among the rural dwellers, unemployed, those with lower educational status and those in the lower social economic quintiles.

Conclusion

There was a low uptake of health insurance programmes among the Nigerian women in this study. Having health insurance coverage was significantly associated with ≥8 ANC visits and women delivering in health facilities. Thus, providing health insurance may be an important way to improve women’s access to MHS in Nigeria.

WHAT IS ALREADY KNOWN ON THIS TOPIC.

WHAT THIS STUDY ADDS

• Having a health insurance was significantly associated with women accessing 8+ ANC visits and delivering in health facilities after controlling for other individual and community-level factors using the latest Nigeria Demographic and Health Survey and among women who delivered within 2 years prior to the survey.

• Lower odds for accessing 8+ ANC visits and delivering in health facilities was also found among the rural dwellers, the unemployed, those with lower levels of education and those with poorer health status.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

• These findings serve as an advocacy tool for a women-focused health insurance package as Nigeria prepares to roll out its implementation plans for the newly promulgated mandatory National Health Insurance Authority Act.

Background

Access to affordable, high-quality maternal healthcare services (MHS) is a fundamental human right of all women irrespective of their age, residence and socioeconomic status.¹ Inequitable access to MHS has been reported globally, especially among the rural poor in low-income and in lower and middle-income countries (LMICs).^{2 3} The United Nations reported in 2019 that an estimated 1.9 million families in Africa spend more than 40% of their non-food, out-of-pocket expenses on MHS each year, which makes the cost of childbirth services catastrophic.⁴ A systematic review on MHS costs in LMICs showed that the median cost for antenatal care (ANC) visits could be as high as $30 and $78 in public and private health facilities, respectively, in India. The median cost for normal delivery in public health facilities ranged from $50 to $350 in Nepal and as high as $580 in private hospitals in India. These costs would be catastrophic for women and their households considering that 46.0% and 49.0% of the extremely poor people in the world reside in LMICs.⁵ For example, in Myanmar, the poverty ratio among women increased to 4.3%, 1.3% and 6.1% after the women made out-of-pocket payments to access ANC services, delivery services and both antenatal and delivery services, respectively.⁶

In 2021, a systematic review on the cost of MHS in LMICs reported ₦39 000~$246.3 as the mean expenditure estimate for delivery in Nigeria from a 2013 study, which was greater than the monthly income for 94.6% of the respondents assessed.^{5 7} There are also indirect costs incurred by women accessing MHS such as non-medical transportation costs, guardian costs and provider-induced fines that all worsen the impact of these costs on women and their households.⁸ The high cost of MHS deters women from accessing quality MHS, and drives them towards unsafe birth practices and home deliveries. According to the former Executive Director of the United Nations Children’s Fund, ‘When families cut corners to reduce maternal health care costs, both mothers and their babies suffer.’⁴

The inability to afford safe childbirth delivery services has contributed to numerous maternal and neonatal deaths globally, in Africa and in Nigeria. In 2019, the WHO reported that 94% of all maternal deaths occur in LMICs.⁹ Africa was reported to have a maternal mortality ratio (MMR) of 545/100 000 live births in 2020, which accounted for 70% of all global maternal deaths.¹⁰ Similarly, with Nigeria’s MMR reported as 512/100 000 in its 2018 Nigeria Demographic and Health Survey (NDHS),¹¹ Nigeria was ranked fourth among countries with the highest MMR according to modelled global estimates.¹ The WHO attributed the high prevalence of maternal deaths in Nigeria to inequalities in access to health services.¹² The highest proportion of maternal deaths of the poorest of women was 68% in 1990, which then increased to 80% in 2015.^{1 13} This disproportionately high prevalence of maternal deaths among the poorest of women can be reduced by increasing their uptake of health insurance programmes. The mean direct cost of accessing ANC services at a tertiary health facility in Southwest Nigeria by women with health insurance coverage was statistically and significantly lower when compared with the cost incurred by women who paid out of pocket.¹⁴

Countries with poor financing mechanisms for health service utilisation rely heavily on out-of-pocket payments and then suffer from catastrophic health expenditures, which leads to a vicious cycle that makes the poor poorer and in need of more critical health services. According to the 2018 NDHS, only ~3% of women had a health insurance coverage.¹¹ The National Health Insurance Scheme (NHIS) was launched in 2005 but with a perennially low coverage rate. To strengthen the Nigerian healthcare financing system, the NHIS was replaced with the National Health Insurance Authority (NHIA) Act which was enacted in 2022.¹⁵ The NHIA now mandates every Nigerian to register for a health insurance package.¹⁵ By the Act, the NHIA provides health insurance packages for employees in formal settings and individuals in informal settings. It also coordinates all the public and private health insurance programmes in the country. The NHIA also implements the Vulnerable Group Fund and 50% of the Basic Health Care Provision Fund to ensure the free provision of the basic minimum healthcare packages to the populace, especially indigents.¹⁶ These basic minimum health services include, but are not limited to, ANC, delivery and postnatal services. As the NHIA implements its strategic plan for assuring that all Nigerians are insured within the shortest possible time, it is critical to provide evidence that would guide the prioritisation of the populations to be insured during the implementation of the NHIA Act.¹⁷ New global targets for ending preventable maternal deaths have been established, and Nigeria must meet these targets.¹⁸ The Nigerian government had also established an 80% target for pregnant women who would attend at least eight ANC visits and 54% who would deliver in a health facility by 2021.¹⁹

Previous studies had reported the inequitable access to MHS using the 2008 and 2013 NDHS datasets,^{13 20} although only a few compared women’s access to MHS with their health insurance status.^{21 22} Nigeria was included in one publication that reported the effect of health insurance on women’s access to MHS in 28 African countries,²³ although none provided country-specific narratives on the effect of health insurance coverage on access to MHS. Therefore, this study aims to determine the association between health insurance coverage and access to MHS among women of reproductive age in Nigeria, after controlling for other individual, household and community-level factors related to MHS utilisation.

Conceptual framework

The study was guided by the conceptual framework as shown below which was conceptualised by the authors. The framework identifies individual, household and community-level factors that could influence women’s uptake of health insurance coverage and also influence their access to MHS. Their access to MHS was measured as ‘the number of ANC visits attended by the women, and their decision to deliver at the health facility’. However, central to the women’s access to MHS is their financial accessibility which can be provided for with their health insurance coverage. The women’s physical accessibility and social accessibility to MHS are also very important but they were not explored in this study and thus presented with broken lines (see figure 1).

Figure 1. Conceptual framework.

Methods

Study design and location

This is a cross-sectional study that uses a nationally representative sample obtained from the 2018 Nigeria Demographic and Health Survey (NDHS).²⁴ The DHS used a two-stage cluster design that stratified the 36 Nigerian states into urban and rural areas.

Study population and size

These were a total of 41 821 women of reproductive age (15–49) who participated in the 2018 NDHS. This study was limited to the 12 935 women who had their last birth within the 2 years before the 2018 NDHS (see figure 2).

Figure 2. A schematic representation of the sample determination. NDHS, Nigeria Demographic and Health Survey.

Data source/method of data collection

The raw dataset from the NDHS was sourced from The DHS Program at ICF in Rockville, Maryland. This dataset was collected during the NDHS 2018 with the Woman’s Questionnaire. The questionnaires were initially translated into Yoruba, Igbo and Hausa and then translated back into English to ensure that the original content was preserved. The individual women recode was used for this study.

Dependent variables

There were two dependent variables in this study: the number of ANC visits and health facility delivery. Those women who had at least eight ANC visits for their most recent birth in the 2 years before the survey were considered to have adequate ANC visits and were coded as 1, while others were coded as 0. This is based on the WHO 2016 ANC model,²⁵ which Nigeria has adopted.²⁶ Similarly, those who reported delivering in a health facility (both public and private health facilities) during their last pregnancy in the 2 years before the survey were considered to have delivered in a health facility and were coded as 1, while others who delivered at home and other homes such as with the traditional birth attendants were coded 0. The health facilities included government or private hospitals as well as health centres.

Independent variables

The main independent variable is health insurance coverage with a dichotomous response to the question, ‘if the respondent was covered by health insurance’. Other possible confounding variables at the individual, household and community levels were controlled and measured as shown in table 1. They were selected based on existing evidence of factors that may be associated with women’s access to MHS.^{27 28}

Table 1. Definitions of independent variables.

Independent variables	Description
Financial access
Health insurance coverage	Categorised as (1) covered, (0) not covered
Individual/household
Age of women at the time of birth	Categorised as <20 followed by 5-year age groups from 20–24 to 45–49
Education	Categorised as (0) none, (1) primary, (2) secondary, (3) higher
Marital status	Categorised as (0) never in union, (1) currently in union, (2) formerly in union
Employment status in the last 12 months	Categorised as (0) not employed, (1) employed
Birth order	Categorised as (1) 1, (2) 2–4, (3) >4
Household wealth index	Categorised as (1) poorest, (2) poorer, (3) middle, (4) richer, (5) richest
Community-level factors
Residence	Categorised as (1) urban, (2) rural
Region	Categorised as (1) North Central, (2) North East, (3) North West, (4) South East, (5) South South, (6) South West

Data analysis

Data were analysed with the STATA V.17 statistical package. Appropriate weighting was done to correct for sampling probability and non-response. Similarly, bivariate and multivariate-level analyses were conducted after incorporating the svyset command for survey data in STATA. The frequency distributions of all variables were described, and were cross-tabulated with health insurance coverage, and then the outcome variables. Two binary logistic regression models were fit for each of the dependent variables. The first model (model 0) was the crude model with the unadjusted rates, while the second model adjusted for all independent variables. Multicollinearity tests conducted by assessing the variance inflation factor (vif) gave a mean vif of 5.11 for the two binary logistic regression models. The hierarchical model or multilevel analysis was not considered because the emphasis of this paper is the relationship between health insurance, ANC visits and facility delivery, and not the contextual units that influence health insurance. The level of significance was set at p<0.05.

Patient and public involvement

Our study analysed a secondary data from a nationally representative survey, hence the authors had no access to the respondents and were unable to engage them in the design, conduct and reporting of the research.

Results

Table 2 shows the individual and community-level factors of Nigerian women aged 15–49 with a birth in the previous 2 years before the survey. The mean age of respondents when giving birth was 27.4±6.7. The majority of the respondents were within the age group of 20–34 (71.2%), were in union or living with a man at the time of the study (95.5%) and were employed in the last year before the survey (8971; 69.4%). Fewer than half of the respondents (40.8%) had completed a secondary-level education or more. Only 264 (2.0%) of the women aged 15–49 who had a delivery within 2 years of the survey had any form of health insurance coverage. With the community-level factors, the highest proportion of respondents in our analytical sample (35.9%) were residents in the North West Region of Nigeria and were predominantly rural (61.5%).

Table 2. Individual, household and community-level characteristics of Nigerian women aged 15–49 years with a birth in the last 2 years preceding the 2018 NDHS (n=12 935).

Variables	Frequency (n)	%
Health insurance coverage
No	12 671	98.0
Yes	264	2.0
Age as at the time of birth (years)
<20	1662	12.9
20–24	3209	24.8
25–29	3553	27.5
30–34	2445	18.9
35–39	1472	11.4
40–44	479	3.7
45–49	115	0.9
Mean age	27.4±6.7
Highest level of education completed
No education	5786	44.7
Primary	1877	14.5
Secondary	4186	32.4
Higher	1086	8.4
Marital status
Never in union	297	2.3
Currently in union	12 353	95.5
Formerly in union	285	2.2
Employment status in the last 12 months
Never worked	3964	30.6
Worked	8971	69.4
Wealth index
Poorest	2775	21.5
Poorer	2955	22.8
Middle	2666	20.6
Richer	2416	18.7
Richest	2123	16.4
Birth order
1 (most recent)	2453	18.9
2–4	5996	46.4
>4	4486	34.7
Region
North Central	1787	13.8
North East	2350	18.2
North West	4649	35.9
South East	1304	10.1
South South	1160	9.0
South West	1685	13.0
Type of residence
Urban	4979	38.5
Rural	7956	61.5

NDHSNigeria Demographic and Health Survey

Figure 3A,B show the distribution of the outcome variables, which were women who had eight or more ANC visits and those who delivered their most recent birth in the last 2 years in a health facility. Only 18.5% had ≥8 ANC visits, while 40.6% delivered in a health facility.

Figure 3. (A) Proportion with ≥8 antenatal care (ANC) visits. (B) Proportion with facility delivery.

Table 3 presents the sociodemographic characteristics and community-level factors of women with health insurance coverage. A higher proportion of women with higher level of education (12.8%) and from the richest quintile (7.7%) had a health insurance coverage, compared with less than 2% among women with less education and from the lower wealth quintiles, respectfully. Women with health insurance coverage who were residents in urban areas had more than three times the health insurance coverage compared with women who lived in rural areas (3.6% vs 1.1%).

Table 3. Individual, household and community characteristics by health insurance coverage among women of reproductive age in Nigeria (n=12 935).

Variables	%	95% CI	P value
		LL–UL
Age as at the time of birth (years)			<0.001
<20	0.7	0.4–1.2
20–24	1.3	0.9–2.0
25–29	2	1.5–2.6
30–34	3.4	2.5–4.6
35–39	3.1	2.0–4.7
40–44	1.7	0.9–3.4
45–49	1.2	0.2–8.2
Highest level of education completed			<0.001
No education	0.7	0.4–1.4
Primary	0.4	0.2–0.8
Secondary	1.8	1.4–2.4
Higher	12.8	10.1–16.0
Marital status			0.145
Never in union	0.7	0.1–3.2
Currently in union	2.1	1.7–2.6
Formerly in union	1.1	0.4–3.0
Employment status in the last 12 months			0.847
Never worked	2.1	1.5–2.8
Worked	2.0	1.6–2.5
Wealth index			<0.001
Poorest	0.5	0.2–1.6
Poorer	0.6	0.2–1.8
Middle	0.9	0.6–1.5
Richer	1.8	1.2–2.6
Richest	7.7	6.1–9.6
Birth order			0.002
1 (most recent)	1.8	1.3–2.5
2–4	2.7	2.2–3.3
>4	1.3	0.9–2.1
Region			0.015
North Central	1.7	1.0–2.8
North East	0.8	0.4–1.4
North West	2.3	1.6–3.3
South East	2.7	1.8–4.2
South South	2.0	1.2–3.3
South West	2.9	1.8–4.5
Type of residence			<0.001
Urban	3.6	2.9–4.6
Rural	1.1	0.7–1.5

LLlower limitULupper limit

The distribution of the women’s individual and community-level factors across the two outcome variables is shown in table 4. Having ≥8 ANC visits had statistically significant associations with all independent variables (age, educational status, household wealth index, work status, birth order, geopolitical zone and residence), except for marital status. Health facility delivery had statistically significant associations with all independent variables. The distribution showed that those with health insurance coverage, with increasing wealth quintile, current employment, higher education, urban residence and residence in the southern part of the country had higher percentages of having at least eight ANC visits and a delivery in a health facility.

Table 4. Background characteristics by adequacy of antenatal care visits and place of delivery (n=12 935).

Predictor variables	n	8+ ANC visits			Health facility delivery
		%	95% CI	P value	%	95% CI	P value
Health insurance
No	12 671	18.0	16.9–19.2	<0.001	39.9	38.2–41.7	<0.001
Yes	264	39.5	32.2–47.4		71.8	61.7–80.1
Age of women at the time of last birth (years)
<20	1662	10.4	8.7–12.5	<0.001	30.4	27.6–33.4	<0.001
20–24	3209	16.1	14.5–17.8		39.2	36.8–41.6
25–29	3553	19.7	17.8–21.7		43.2	40.6–45.9
30–34	2445	24.5	22.2–26.8		46.0	43.4–48.6
35–39	1472	19.9	17.4–22.6		43.0	39.7–46.4
40–44	479	18.6	13.3–25.4		31.8	26.8–37.1
45–49	115	16.4	9.6–26.5		35.3	25.7–46.2
Marital status
Never in union	297	23.7	18.5–29.9	0.130	54.0	46.8–61.1	<0.001
Currently in union	12 353	18.4	17.3–19.6		40.1	38.3–41.9
Formerly in union	285	16.4	11.5–22.8		48.1	39.9–56.3
Education
None	5786	3.9	3.3–4.7	<0.001	15.3	13.8–16.8	<0.001
Primary	1877	18.0	15.3–21.0		42.2	39.3–45.2
Secondary	4186	30.8	28.8–32.9		62.7	60.3–65.0
Higher	1086	49.2	45.2–53.2		87.3	84.5–89.7
Wealth index
Poorest	2775	4.0	3.1–5.2	<0.001	12.8	11.1–14.7	<0.001
Poor	2955	7.0	6.0–8.2		22.6	20.3–25.1
Middle	2666	15.7	13.7–17.9		40.8	37.7–44.0
Richer	2416	28.4	25.7–31.2		60.0	57.0–63.0
Richest	2123	45.4	42.3–48.7		79.5	76.5–82.1
Employment status
Not employed	3964	10.6	9.2–12.0	<0.001	28.9	26.6–31.3	<0.001
Employed	8971	21.9	20.6–23.3		45.7	43.9–47.6
Birth order
1	2453	25.2	22.9–27.5	<0.001	52.7	50.0–55.4	<0.001
2–4	5996	21.5	20.0–23.1		44.6	42.4–46.8
>4	4486	10.7	9.5–12.1		28.6	26.6–30.6
Region
North Central	1787	14.0	11.8–16.5	<0.001	51.0	47.1–55.0	<0.001
North East	2350	3.5	2.7–4.5		29.0	25.6–32.6
North West	4649	4.1	3.3–5.1		16.2	14.0–18.6
South East	1304	35.5	32.1–39.1		81.0	77.1–84.4
South South	1160	36.1	32.6–39.7		48.9	44.3–53.5
South West	1685	58.4	53.8–62.8		76.0	72.5–79.1
Residence
Urban	4979	32.3	30.1–34.5	<0.001	62.0	59.1–64.7	<0.001
Rural	7956	9.8	8.9–10.8		27.2	25.4–29.1

Bold values are statistically significant.

ANCantenatal care

Table 5 shows the role of having a health insurance coverage on women who had ≥8 ANC visits and facility delivery. In the unadjusted model, health insurance coverage had a statistically significant association with attending ≥8 ANC visits, so that women with health insurance had three times greater odds of ≥8 ANC visits compared with those with no health insurance coverage (OR 3.0; 95% CI 2.15–4.12). The statistically significant association persisted after controlling for the possible confounding factors in the full model (adjusted OR (AOR) 1.9; 95% CI 1.26–2.95).

Table 5. Association between health insurance and outcome variables (8 ANC visits and health facility delivery) controlling for individual, household and community factors.

Predictor variables	8+ ANC visits				Health facility delivery
	Unadjusted		Adjusted		Unadjusted		Adjusted
	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI
Health insurance
No	1		1		1		1
Yes	3.0***	2.15–4.12	1.9**	1.26–2.95	3.8***	2.42–6.07	2.0***	1.39–2.82
Age of women at the time of last birth (years)
Mean age	1.0***	1.02–1.04	1.0***	1.01–1.04	1.0***	1.01–1.02	1.0***	1.01–1.03
Marital status
Never in union	1		1		1		1
Currently in union	0.7	0.52–1.00	1.8**	1.25–2.67	0.6***	0.42–0.76	1.4	1.00–2.04
Formerly in union	0.63	0.38–1.03	1.6	0.89–2.80	0.8	0.52–1.19	1.9*	1.15–3.04
Education
Less than secondary	1				1		1
Secondary and above	6.7***	5.58–7.96	1.6***	1.35–1.91	7.5***	6.59–8.57	2.2***	1.91–2.62
Wealth index
Poorest	1		1		1		1
Poor	1.8***	1.31–2.47	1.2	0.91–1.70	2.0***	1.65–2.40	1.7***	1.39–2.03
Middle	4.5***	3.3–6.12	1.7***	1.28–2.37	4.7***	3.82–5.79	2.8***	2.27–3.48
Richer	9.5***	6.95–13.00	1.9***	1.38–2.62	10.2***	8.29–12.66	3.9***	3.08–4.88
Richest	20.0***	14.62–27.26	2.4***	1.70–3.37	26.4***	20.80–33.49	7.1***	5.35–9.42
Employment status
Not employed	1		1		1		1
Employed	2.38***	2.04–2.77	1.24*	1.04–1.48	2.1***	1.86–2.32	1.4***	1.21–1.57
Birth order
1	1		1		1		1
2–4	0.8**	0.71–0.94	0.7***	0.59–0.83	0.7***	0.64–0.81	0.6***	0.51–0.72
>4	0.4***	0.30–0.43	0.5***	0.39–0.65	0.4***	0.32–0.41	0.5***	0.39–0.59
Region
North Central	1		1		1		1
North East	0.2***	0.16–0.31	0.3***	0.23–0.45	0.4***	0.31–0.49	0.6***	0.51–0.80
North West	0.3**	0.19–0.36	0.4***	0.28–0.50	0.2***	0.15–0.23	0.3***	0.21–0.32
South East	3.4***	2.65–4.35	2.2***	1.69–2.88	4.1***	3.07–5.44	2.1***	1.65–2.78
South South	3.5***	2.71–4.46	2.5***	1.93–3.16	0.9***	0.72–1.17	0.4***	0.32–0.53
South West	8.6***	6.60–11.30	5.2***	3.97–6.79	3.0***	2.39–3.86	1.2	0.96–1.61
Residence
Urban	1		1		1		1
Rural	0.2***	0.20–0.26	0.7***	0.64–0.87	0.2***	0.20–0.27	0.8*	0.69–0.95

Notes: OR – Odds ratio; – Confidence interval; Ref – Reference value; * Statistically significant; *pStatistically significant; *p<0.05, **p**p<0.01, ***p***p<0.001.

ANCantenatal care

As with the number of ANC visits, the unadjusted model showed a statistically significant association with facility delivery, which also persisted after controlling for confounding factors. In the full model, those with health insurance coverage had 2.0 times greater odds of delivering in health facilities compared with those without health insurance coverage (AOR 2.0; 95% CI 1.39–2.82).

The southern regions had greater odds, while the northern regions had lower odds for accessing 8+ ANC visits compared with the North Central Region. However, for facility delivery, only the South East Region had greater odds compared with the North Central Region. In addition, ANC visits and facility delivery were significantly higher among urban dwellers, the employed, the more highly educated and those with increasing wealth.

Discussion

In this study, we explored the influence of having health insurance coverage on access to MHS (defined as attending ≥8 ANC visits and health facility delivery) among women of reproductive age who delivered within 2 years of the survey using the latest 2018 NDHS dataset. Having a health insurance coverage was significantly associated with attending ≥8 ANC visits and delivering at a health facility after controlling for individual and community-level factors.

These findings reveal the critical role that health insurance coverage plays in increasing the uptake of ANC and health facility delivery, and in improving women’s access to the skilled birth attendants who work in health facilities. This is expected to reduce the incidence of maternal morbidities and mortalities. This also shows the pivotal role that a substantial health insurance coverage has on Nigeria’s prospects of meeting the maternal health targets of the Sustainable Development Goal (SDG) 3, which includes Targets 3.1 (reduced maternal mortality), 3.2 (neonatal and child mortality) and 3.7 (improved access to sexual and reproductive health services).²⁹ The findings also strongly contribute to Nigeria’s meeting the Target 3.8 of SDG 3, which addresses financial risk protection and access to quality essential healthcare services, including MHS. In addition, women who choose to deliver at a health facility because they have a health insurance coverage will be encouraged to attend ANC visits during their subsequent pregnancies.

The current abysmally low uptake of health insurance coverage (2.0%) among Nigerian women of reproductive age who delivered in the last 2 years before the survey is worrisome. This is similar to the findings across Africa, with only four African countries having ≥20% of their population with health insurance coverage: (Rwanda (79%), Ghana (58%), Gabon (41%) and Burundi (22%)) of the 36 sub-Saharan African countries assessed in 2021.³⁰ With a mean average of <10% health insurance coverage, Nigeria ranked 26th of the 36 countries assessed. In Nigeria, with a 44.5% poverty rate and 5.5% employment rate in 2021, a low health insurance uptake may lead to catastrophic health spending, preventable deaths and worsening maternal health indices.³⁰

There were significant disparities in the uptake of health insurance coverage across the different categories in the individual characteristics of the women and the community-level factors explored in our study. The prevalence of health insurance coverage was least among the adolescent mothers and peaked in the 30–34 age group, although it declined afterwards. There is the need to investigate the reasons for this low uptake of health insurance among adolescents, with many of them within the age limit (<18 years) that is usually covered under their parents’ insurance.¹⁶ Having health insurance coverage was highest among the most educated women and the women in the highest wealth quintile. This is similar to the findings from a meta-analysis of 48 studies across 17 countries, which showed greater odds of health insurance enrolment in the most educated and wealthiest households.³¹ Older age, better educational levels and wealth status also consistently significantly predicted health insurance ownership among women of reproductive age across five sub-Saharan African countries.³² Our findings also showed significant inequalities in health insurance coverage with the worst among the rural dwellers and women residents in the northern regions in Nigeria. This suggests that the more vulnerable populations such as the poor, rural dwellers and least educated are not being reached with government interventions such as having health insurance coverage.

Having health insurance coverage is expected to provide financial risk protection and reduce disparities in financial access to MHS.^{21 29} To ensure this, the Nigerian government established the National Health Insurance Scheme (NHIS) in 1999 which became fully operational in 2005. However, since the formal launch of the NHIS in 2005, the scheme had yet to enrol up to 10% of the population in 2022.³³ Several packages had been introduced to improve the coverage of health insurance uptake. These targeted the general population irrespective of their gender, with some focus on the disabled, the vulnerable and students.³⁴ However, many of these efforts were not women focused. Universal health coverage may thus not be universal in access to care, when the needs and demands of women’s health are yet to be met.³⁵ In the past, some state governments had offered free MHS in an attempt to meet the needs of women, but many have been unsustainable because of changes in the government and a worsening economy. There is a need for affordable health insurance packages that would cover women’s reproductive years and address all their MHS needs. In 2022, the National Health Insurance Authority (NHIA) Act was promulgated, which now makes a health insurance coverage mandatory for all in Nigeria.¹⁵ In its recently published operational guidelines in October 2023,³⁶ indigent pregnant women were included under its non-contributory health insurance scheme. This is a good step but a detailed implementation plan may be needed.³⁷

Having health insurance coverage was significantly associated with women attending ≥8 ANC visits and delivering in a health facility after controlling for both the individual and community-level factors. Health insurance removes the financial barrier to accessing MHS caused by out-of-pocket payments and its catastrophic effects that makes the poor poorer. The resultant effect is a more equitable access to care with the potential for improved maternal health outcomes. Ownership of health insurance was a predictor of ≥4 ANC visits and skilled birth attendance during childbirth in Ethiopia and 28 countries in sub-Saharan Africa reported in 2021 and 2022 by reusing the countries’ most recent DHS data.^{22 23} The WHO has since raised the minimum standard for ANC visits during pregnancy from at least four to eight visits.²⁵ This stresses the need for greater health insurance coverage among women of reproductive age to increase their likelihood of complying with the WHO minimum standards. Eighty per cent of 63 266 women of reproductive age who had given birth 5 years before the 2018 and 2020 DHS conducted in eight countries, Nigeria inclusive, were not compliant with the WHO-recommended ≥8 ANC visits.³⁸ However, women enrolled in health insurance had lower odds of non-compliance.³⁸ The findings measured women’s ANC practice in periods preceding the release of the new guideline in 2016. Our study is more representative since we included women who delivered only 2 years before the 2018 NDHS and presented our findings based on the new WHO recommendation.

Policy implications

Our study provides evidence for prioritising health insurance for women of reproductive age to improve their access to MHS. There is therefore a need for the government and its agencies to rapidly scale up uptake of health insurance among women of reproductive age in Nigeria especially for accessing maternal health services through more innovative women-targeted packages. The poor, uneducated and rural dwellers should be particularly targeted as the access to MHS was poorest among them. It is hoped that these would contribute to the reduction of maternal morbidities and mortalities and ensure no woman is left behind in receiving MHS.

This study had its limitations. We could not assess the cost of women accessing MHS being a secondary data. We did not also disaggregate the type of health insurance coverage, if private or public, nor their type of occupation if privately engaged or not. We, however, made do with other variables such as if they had been employed over a 12-month period consistently. We recommend a qualitative exploration to identify why Nigerian women of reproductive age would not uptake a health insurance coverage. We also recommend that governments engage women while designing a women-targeted package to ensure their uptake of health insurance coverage and thus access to MHS.

Conclusion

Access to health insurance was a strong predictor of women attending at least eight ANC visits and delivering in a health facility after controlling for confounders. Irrespective of the other determinants of women’s access to MHS, there is a need to pay close attention to improving uptake of health insurance among women of reproductive age, especially targeting the rural dwellers and women who reside in the northern regions of Nigeria. Authorities may need to prioritise women of reproductive age in the design and implementation of health insurance programmes in order to increase their uptake. This would provide financial risk protection and facilitate access to MHS and possible attainment of Nigeria’s SDG 3 targets.

The views expressed are those of the authors and do not necessarily reflect the views of USAID or the US government.

Data availability statement

Data are available upon reasonable request.