Correlates of antenatal care usage among adolescent mothers in Nigeria: a pooled data analysis

Abstract

This study examined selected correlates of timing and frequency of antenatal care visits among adolescent mothers aged 15–19 in Nigeria. Data from the women’s recode dataset of the Nigeria Demographic and Health Surveys between 2003 and 2018 were pooled, with a sample size of 4,775. Multivariate data analysis was carried out using binary logistic regression. It was found that being educated (aOR = 1.54; CI = 1.14–2.08; aOR = 1.64; CI = 1.11–2.42); higher wealth status (aOR = 1.88; CI = 1.45–2.43; aOR = 1.92; CI = 1.33–2.76); contributing to health decision-making (aOR = 1.44, CI = 1.15–1.81); having an educated partner (aOR = 1.73; CI = 1.31–2.30; aOR = 2.44; CI = 1.84–3.25); and living in the South West region (aOR = 3.68; CI = 1.72–7.87) were associated with higher complete antenatal care utilization. Having difficulty getting permission to go to the health facility (aOR = 0.75, CI = 0.57–0.99) and with the distance to the health facility (aOR = 0.61, CI = 0.49–0.75) were associated with lower likelihood of ANCU. Respondents with secondary and higher education were more likely to start ANC early (aOR = 1.57, CI = 1.05–2.34), but Muslim mothers (aOR = 0.61, CI = 0.40–0.32) and those living in the North West (aOR = 0.43, CI = 0.26–0.71), South-South (aOR = 0.30, CI = 0.17–0.53) and South West (aOR = 0.29, CI = 0.12–0.69) were less likely to begin ANC early. Therefore, interventions to increase antenatal care must be region-specific, and focus attention on lower status adolescent mothers with less autonomy.

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Correlates of antenatal care usage among
adolescent mothers in Nigeria: a pooled data
analysis
Christiana Alake Alex-Ojei & Clifford Obby Odimegwu
To cite this article: Christiana Alake Alex-Ojei & Clifford Obby Odimegwu (2021) Correlates of
antenatal care usage among adolescent mothers in Nigeria: a pooled data analysis, Women &
Health, 61:1, 38-49, DOI: 10.1080/03630242.2020.1844359
To link to this article: https://doi.org/10.1080/03630242.2020.1844359
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Correlates of antenatal care usage among adolescent mothers in
Nigeria: a pooled data analysis
Christiana Alake Alex-Ojei , PhD
a,b
and Cliord Obby Odimegwu , PhD
a
a
Demography and Population Studies Programme, Schools of Public Health and the Social Sciences, University of the
Witwatersrand, Johannesburg, South Africa;
b
Demography and Social Statistics Department, Faculty of Social Sciences,
Federal University, Oye-Ekiti, Nigeria
ABSTRACT
This study examined selected correlates of timing and frequency of antenatal
care visits among adolescent mothers aged 15–19 in Nigeria. Data from the
women’s recode dataset of the Nigeria Demographic and Health Surveys
between 2003 and 2018 were pooled, with a sample size of 4,775.
Multivariate data analysis was carried out using binary logistic regression. It
was found that being educated (aOR = 1.54; CI = 1.14–2.08; aOR = 1.64;
CI = 1.11–2.42); higher wealth status (aOR = 1.88; CI = 1.45–2.43; aOR = 1.92;
CI = 1.33–2.76); contributing to health decision-making (aOR = 1.44,
CI = 1.15–1.81); having an educated partner (aOR = 1.73; CI = 1.31–2.30;
aOR = 2.44; CI = 1.84–3.25); and living in the South West region (aOR = 3.68;
CI = 1.72–7.87) were associated with higher complete antenatal care utiliza-
tion. Having diculty getting permission to go to the health facility
(aOR = 0.75, CI = 0.57–0.99) and with the distance to the health facility
(aOR = 0.61, CI = 0.49–0.75) were associated with lower likelihood of ANCU.
Respondents with secondary and higher education were more likely to start
ANC early (aOR = 1.57, CI = 1.05–2.34), but Muslim mothers (aOR = 0.61,
CI = 0.40–0.32) and those living in the North West (aOR = 0.43,
CI = 0.26–0.71), South-South (aOR = 0.30, CI = 0.17–0.53) and South West
(aOR = 0.29, CI = 0.12–0.69) were less likely to begin ANC early. Therefore,
interventions to increase antenatal care must be region-specic, and focus
attention on lower status adolescent mothers with less autonomy.
ARTICLE HISTORY
Received 12 July 2019
Revised 22 September 2020
Accepted 24 October 2020
KEYWORDS
Adolescents; Africa;
antenatal care; maternal
health utilization; Nigeria
Introduction
Adolescent pregnancy is a common occurrence in Nigeria, with an adolescent fertility rate of 106
births per woman aged 15–19 (NPC and ICF International 2019). It is also estimated that about
270,000 girls under age 15 give birth every year in Nigeria (Neal and Hosegood 2015). As pregnant
adolescents are also still growing themselves, they usually have inadequate nutritional stores and are
not biologically mature enough to cope well with the stresses of pregnancy and delivery. As such, they
are susceptible to anemia, pregnancy complications, obstructed labor due to an incompletely devel-
oped pelvis, and other pregnancy-related morbidity and mortality (Ibrahim and Owoeye 2012; Ogu,
Agholor, and Okonofua 2016; Onoh et al. 2014; Wall 1998). Pregnancy-related mortality is the major
cause of death among girls aged 15–19 globally (World Health Organization 2017). Research has also
shown that adolescent mothers in Nigeria have higher incidences of perinatal mortality than older
mothers (Adebowale and Akinyemi 2016; Mairiga and Saleh 2009). Adolescent mothers are also more
likely to have low birth-weight, preterm and stillborn babies (Ibrahim and Owoeye 2012; Olusanya
and Ebuehi 2012; Onoh et al. 2014).
CONTACT Christiana Alake Alex-Ojei christiana.alexojei@gmail.com Demography and Population Studies Programme,
Schools of Public Health and the Social Sciences, University of the Witwatersrand, Johannesburg, South Africa.
WOMEN & HEALTH
2021, VOL. 61, NO. 1, 38–49
https://doi.org/10.1080/03630242.2020.1844359
© 2020 Taylor & Francis Group, LLC

Despite the risks associated with pregnancy at a young age however, adolescent mothers have the
lowest utilization rates of maternal health services in Nigeria, compared to older mothers (Babalola
and Fatusi, 2009; Dairo and Owoyokun 2010; Idowu et al. 2017; Izugbara, Ochako, and Izugbara 2011;
Ovikuomagbe 2017). Late booking and incomplete usage of antenatal care are common among
pregnant adolescents (Emelumadu et al. 2014; Shahabuddin et al. 2015). Adolescent mothers’ health-
seeking behavior is often influenced by factors beyond their personal control, and the decisions on
their healthcare are usually in the hands of others, such as their own and partners’ relatives (Atuyambe
et al. 2009, 2008). Shahabuddin et al. (2015) discovered that adolescent mothers who had higher levels
of personal autonomy were more likely to make use of antenatal care services. Adolescent mothers are
who are unmarried and have unwanted pregnancies have been discovered to have lower utilization of
maternal healthcare across several countries in sub-Saharan Africa (Magadi, Agwanda, and Obare
2007). Similarly, women of reproductive age who had unintended pregnancies in Indonesia had lower
maternal healthcare usage (Saptarini and Setyonaluri 2018).
Religion has been found to influence maternal healthcare utilization, as Muslim girls were found to
have lower utilization levels in Nigeria and India (Olusanya and Ebuehi 2012; Singh et al. 2014).
Adolescents with no education have lower usage of maternal healthcare services (Magadi, Agwanda,
and Obare 2007; Shahabuddin et al. 2015; Singh et al., 2014). Also, adolescent mothers who had
educated partners had higher antenatal care utilization (Mekonnen, Dune, and Perz 2019; Rai, Singh,
and Singh 2012; Singh et al. 2012, 2013). Furthermore, adolescent mothers who live in households with
higher wealth status are more likely to use maternal health services in low-income countries (Banke-
Thomas, Banke-Thomas, and Ameh 2017; Ochako et al. 2011; Rai, Singh, and Singh 2012). Urban
residence also results in higher antenatal care usage compared to rural residence (Atuyambe et al.
2009; Banke-Thomas, Banke-Thomas, and Ameh 2017; Ochako et al. 2011; Rai, Singh, and Singh
2012), and adolescent mothers who reported that their homes were distant from the health facility had
lower utilization rates of maternal and child health services (Atuyambe et al. 2009).
This study examined selected correlates of the number and timing of ANC visits among adolescent
mothers across Nigeria. It examined the relationship between age, age at first birth, education, wealth
status, religion, ethnicity, marital status, sex of household head, involvement in healthcare decision
making, partner age difference, pregnancy intention, issues in getting permission to go to health
center, getting money to pay for healthcare costs and the distance to the health facility, place and
region of residence on antenatal care use and timing of first ANC visit among adolescent mothers aged
15–19, using nationally representative data from the Nigeria Demographic and Health Surveys
conducted between 2003 and 2018.
Methods
Data
The study used a pooled dataset derived from combining the women recode dataset from
Demographic and Health Surveys conducted in Nigeria in 2003, 2008 2013, and 2018. The
Demographic and Health Surveys used a multistage cluster sampling design to select eligible house-
holds for the surveys. Within the households, all women who were aged 15–49 were eligible to
participate in the surveys. Overall, the study had a response rate of 97.6%. Inclusion criteria for the
sample for this study were being aged between 15 and 19 and being either currently pregnant or having
given birth to at least one child. The combined sample size of adolescent mothers from the four
datasets was 4,755. Ethical approval for the four surveys were obtained by the National Population
Commission and ORC Macro/ICF International, and permission was obtained from Measure DHS to
make use of the datasets for this study.
WOMEN & HEALTH 39

Variables
The dependent and independent variables examined in this study with their descriptions are presented
in the variable identification table.
Variable identication
Variable Description
Antenatal care visits The number of antenatal visits adolescent mothers had during the course of their pregnancy.
Coded as “none/incomplete” when adolescent mothers had between 0 and 3 visits, and
“complete” when they had 4 or more visits.
Antenatal care timing This was coded as “late” when the adolescent mother commenced ANC in the second trimester
or later, and “early” when the first visit was at any time during the first trimester.
Age Age of adolescent mother at survey. This was coded as “15–17” and “18–19”.
Age at birth Age of adolescent mother at birth of child under consideration. Coded as “<15” and “ = >15”.
Educational level Respondent’s highest educational level. Coded as no education”, “primary” and “secondary and
higher”.
Wealth index The wealth status was recoded into three categories, “poor”, “middle” and “rich”, from the
original five categories presented in the DHS which are “poorest”, “poor”, “middle”, “rich”, and
“richest”.
Religion Respondent’s religion, categorized as “Christian” and “Muslim/other” due to the small number of
respondents in the “other religions” category.
Ethnicity Respondent’s ethnicity was categorized as “Yoruba”, “Igbo”, and “Hausa/Fulani”, while additional
ethnic groups were coded as “Others”.
Marital status Respondent’s marital status coded as “not married” and “married”. The “not married” category
was created by adding together the “never married” and “formerly married” categories of the
variable on marital status, as very few respondents were in the latter category.
Sex of household head Sex of the head of household where respondent lives, coded as “male” and “female”.
Healthcare decision-making Respondent’s involvement in healthcare decision making, coded as “respondent has no say”
when the respondent could not contribute to decision-making concerning their healthcare,
and “respondent has a say”, when respondents were able to contribute.
Partner age difference Age difference between respondent and her partner, categorized as “same age/small” when the
respondent’s partner was older by ten years or less, and “large” when the partner was more
than ten years older than the respondent.
Partner’s educational level Highest educational level of respondent’s partner, coded as no education”, “primary” and
“secondary and higher”.
Pregnancy intention This examines whether the respondent’s pregnancy was wanted or not, coded as “wanted” and
“mistimed/unwanted”.
Getting permission to go to
health facility
This examines how easy it is for the respondent to obtain permission to go to the health facility,
coded as “not a big problem” and “big problem”.
Getting money for healthcare
costs
This examines how easy it is for the respondent to obtain money to pay for healthcare costs,
coded as “not a big problem” and “big problem”.
Distance to health facility This examines how the challenge of getting to the health facility form the respondent’s home,
coded as “not a big problem” and “big problem”.
Place of residence Respondent’s place of residence, coded as “urban” and “rural”.
Region of residence Respondent’s region of residence, coded as “North Central”, “North West”, “North East”, “South
West”, “South East” and “South South”.
Analysis
Data analysis was carried out at the univariate, bivariate, and multivariate levels to examine the
correlates of the total number of antenatal visits as well as timing of the first ANC visit among
pregnant adolescents and new mothers aged 15–19. At the univariate level, simple frequencies and
percentages were computed to get a picture of the characteristics of the study population; at the
bivariate level, chi-square tests of association were carried out to examine the correlates of adolescent
antenatal care usage and timing, and at the multivariate level, binary logistic regression was carried out
to examine the relationship between multiple independent variables and the number of ANC visits
and the timing of first antenatal care visit among adolescent mothers in Nigeria.
40 C. A. ALEX-OJEI AND C. O. ODIMEGWU

A denormalized weight was generated for the pooled sample, taking into account the strata and
primary sampling units from the 4 years under study. Also, the subpopulation option was used to
extract the sample of adolescent mothers from the entire dataset, by restricting the population to
young girls aged 15 to 19 who had at least one child or were currently pregnant. At the multivariate
level of analysis, variables which were significant at the bivariate level of analysis were selected into the
binary logistic regression models.
Results
Univariate analysis
The frequency distribution of the sociodemographic characteristics and healthcare use patterns of
adolescent mothers are presented by individual years (Table 1). It was discovered across the four waves
that the majority of adolescent mothers were aged 18 and above. Also, consistently across the four
surveys, the majority of adolescent mothers were aged 15 and older at birth.
The study found that the majority of respondents had no education, followed by those with
secondary and higher education, and the smallest proportion was those with primary education
only. Similarly, the highest proportion of respondents were from poor households, followed by
those in middle-class and rich households. The majority of respondents were Muslim or adherents
of other religions. Similarly, adolescent mothers from the Hausa and Fulani ethnic groups made up the
majority of respondents from all four surveys, followed by respondents from other tribes, while
Yoruba and Igbo respondents were in the minority in all four surveys.
Additionally, the majority of adolescent mothers were currently married or in union, and were
living in male-headed households. Data also showed that the majority of adolescent mothers were
unable to participate in decision-making concerning their healthcare. Furthermore, the majority of
adolescent mothers who were in a stable union had partners with no education, followed by those
whose partners had secondary or higher education, and the smallest proportion was those whose
partners had only primary education.
Findings showed that majority of the adolescent mothers had wanted pregnancies. The majority of
adolescent mothers did not find it difficult to obtain permission to go to the health facility. Also, across
the surveys, varying proportions of adolescent mothers did not find it difficult with getting money to
pay for healthcare. In 2003, three quarters of adolescent mothers did not find it difficult to obtain
money for healthcare costs; in 2008, only a little over a third of adolescent mothers reported that they
did not find it difficult obtaining money for healthcare costs, while in in 2013 and 2018, about half of
respondents said they did not find it difficult to obtain money for healthcare costs. Additionally, the
majority of adolescent mothers reported that they did not experience a lot of difficulty getting to the
health facility due to the distance from their homes. The majority of adolescent mothers surveyed in
the study lived in rural areas. Also, the majority of adolescent mothers lived in the North West and
North East zones, with the lowest proportion of respondents from the South West and South East
zones across the four surveys.
Complete antenatal care use by adolescent mothers was consistently low across the four surveys.
Also, adolescent mothers generally started antenatal care late, as consistently across all four surveys it
was seen that the majority of respondents started antenatal care in the fourth month or later.
Bivariate analysis
Respondents under 18 had lower levels of complete ANC usage compared to those 18 and above (Table 2).
Respondents with secondary and higher education had the highest usage of complete ANC, while
respondents with no education had the lowest usage rates. Similarly, respondents who were from middle
class and rich households had higher usage rates than those who were from poor households. Christian
adolescent mothers had higher usage of complete antenatal care than those who were Muslims or adherents
WOMEN & HEALTH 41

Table 1. Frequency distribution of respondents’ characteristics and healthcare utilization.
Variable
NDHS 2003 NDHS 2008 NDHS 2013 NDHS 2018
Frequency
Percentage
(%) Frequency
Percentage
(%) Frequency
Percentage
(%) Frequency
Percentage
(%)
Age
15–17
18–19
140
218
39.1
60.9
518
912
36.2
63.8
521
1015
33.9
66.1
456
995
31.4
68.6
Age at birth
<15
≤15
20
268
6.9
93.1
70
1041
6.3
93.7
78
1084
6.7
93.3
44
1080
3.9
96.1
Educational level
None
Primary
Secondary and
higher
218
69
71
60.9
19.3
19.8
862
232
336
60.3
16.2
23.5
836
285
415
54.4
18.6
27.0
834
177
440
57.5
12.2
30.3
Wealth index
Poor
Middle
Rich
156
88
114
43.6
24.6
31.8
928
253
249
64.9
17.7
17.4
922
338
276
60.0
22.0
18.0
928
285
238
64.0
19.6
16.4
Religion
Christian
Muslim/Others
87
271
24.3
75.7
406
1024
28.4
71.6
432
1104
28.1
71.9
385
1066
26.5
73.5
Ethnicity
Yoruba
Igbo
Hausa/Fulani
10
21
208
2.8
5.9
58.3
77
63
730
5.4
4.4
51.0
55
71
872
3.6
4.6
56.8
53
104
817
3.7
7.2
56.3
Marital status
Not married
Married
54
304
15.1
84.9
191
1238
13.4
86.6
216
1320
14.1
85.9
175
1276
12.1
87.9
Sex of household head
Male
Female
333
25
93.2
6.8
1287
143
89.4
10.6
1371
165
90.9
9.1
1302
149
90.3
9.7
Healthcare decision
making
Respondent has no
say
Respondent has a say
326
31
90.6
9.4
903
335
73.1
26.9
1042
278
79.4
20.6
988
288
79.1
20.9
Partner age difference
Same age/Small
Large
58
242
19.8
80.2
306
932
24.2
75.8
324
996
24.7
75.3
281
995
21.5
78.5
Partner’s education
level
None
Primary
Secondary and
higher
153
71
87
49.3
20.8
29.9
690
230
348
51.3
20.0
28.7
717
211
423
56.2
15.4
28.3
656
154
466
52.9
13.6
33.5
Pregnancy intention
Wanted
Mistimed/Unwanted
91
23
79.6
20.4
376
58
85.2
14.8
439
62
90.3
9.7
420
61
88.5
11.5
Getting permission to
go to health facility
Not a big problem
Big problem
312
46
86.3
13.7
1127
303
77.6
22.4
1263
273
82.3
17.7
1230
221
85.3
14.7
Getting money to pay
for healthcare costs
Not a big problem
Big problem
263
95
75.2
24.8
548
882
38.0
62.0
752
784
51.2
48.8
704
747
50.1
49.9
Distance to health
facility
Not a big problem
Big problem
256
102
72.9
27.1
776
654
56.0
44.0
940
596
60.9
39.1
913
538
65.5
34.5
Place of residence
Urban
Rural
107
251
23.1
76.9
253
1177
19.2
80.8
263
1273
18.2
81.8
289
1162
20.5
79.5
(Continued)
42 C. A. ALEX-OJEI AND C. O. ODIMEGWU

of other religions. Yoruba respondents had the highest usage rates of complete antenatal care, followed by
Igbos, respondents from other tribes, and least usage was among the Hausa/Fulani. Marital status was
associated with ANC usage, as respondents who were not married had higher usage of complete antenatal
care. A larger proportion of respondents who lived a female-headed household had complete usage of
ANC, compared to those who lived in male-headed households. Also, respondents who had a say in their
healthcare decision making had higher complete ANC usage than those living in male-headed households.
As expected, adolescent mothers whose partners had secondary and higher education had the highest
complete antenatal care use, while those who had uneducated partners had the lowest incidence of use.
Respondents who said that they did not experience difficulty with getting permission to go to the health
facility, getting money to pay for healthcare costs, or with the distance to the health facility had the highest
proportions of complete antenatal care use, compared to mothers who reported that they experienced
difficulty in all three situations. It was also seen that adolescent mothers who were urban residents had
higher full antenatal care utilization rates than those living in rural areas. The highest rates of complete
ANC usage were found in the South East, followed by the South West and the South South, while the lowest
rates of usage were found in the North West, followed by the North East and North Central regions.
The highest proportion of adolescent mothers who started antenatal care early had secondary or
higher education (Table 2). Also, religion was associated with timing of first antenatal care visit, as
a higher proportion of adolescent mothers who were Christians started antenatal care early than Muslims
and adherents of other religions. Ethnicity was associated with timing of antenatal care, as adolescent
mothers from other tribes had the highest proportion of early commencement of antenatal care, followed
by adolescent mothers from the Igbo and Yoruba tribes, and least among Hausa/Fulani adolescent
mothers. It was observed that a higher proportion of respondents who had a say in their healthcare
decision-making started antenatal care early compared to those who did not have a say. Partner
education was associated with timing of first antenatal care visit, as the highest proportion of adolescent
mothers who started antenatal care early were whose partners had secondary or higher education.
Additionally, the highest proportion of respondents who started ANC early lives in the North Central,
followed by the South East and North East, while the lowest proportion came from the North West.
Multivariate analysis
In the multivariate analysis, the variables in the model for number of antenatal care visits were those
which were significant at the bivariate level, which were respondent’s age, age at birth, educational
level, wealth status, ethnicity, marital status, sex of household head, respondent healthcare decision
making, partner age difference, partner’s educational level, getting permission to go to health facility,
Table 1. (Continued).
Variable
NDHS 2003 NDHS 2008 NDHS 2013 NDHS 2018
Frequency
Percentage
(%) Frequency
Percentage
(%) Frequency
Percentage
(%) Frequency
Percentage
(%)
Region of residence
North Central
North East
North West
South East
South South
South West
43
109
153
13
29
11
9.8
29.0
44.4
2.7
11.5
2.6
234
441
487
60
123
85
13.9
23.4
40.2
4.8
8.9
8.7
184
374
665
64
165
84
12.7
21.1
49.7
4.1
7.1
5.3
219
393
575
92
110
62
12.1
23.3
48.8
5.4
6.1
4.4
Number of ANC visits
None/Incomplete
Complete
177
107
61.1
38.9
724
371
64.6
35.4
701
440
62.7
37.3
619
501
60.9
39.1
Timing of first ANC visit
Late
Early
122
35
76.4
23.6
386
123
77.3
22.7
499
141
79.7
20.3
583
166
79.7
20.3
WOMEN & HEALTH 43

Table 2. Percentage distribution of antenatal care visits and timing of first antenatal care visit by respondents’ characteristics.
Antenatal care utilization Timing of first antenatal care visit
Variables None/Incomplete (%) Complete (%) p-value Late (%) Early (%) p
Age
15–17
18–19
66.4
58.5
33.6
41.5
0.0001** 80.2
78.3
19.8
21.7
.386
Age at birth
<15
≤15
68.3
60.5
31.7
39.5
0.060 77.0
78.9
23.0
21.1
.711
Educational level
None
Primary
Secondary and higher
74.8
51.0
33.2
25.2
49.0
66.8
0.000** 83.9
75.8
74.5
16.1
24.2
25.5
.0001**
Wealth index
Poor
Middle
Rich
73.9
47.5
32.8
26.1
52.5
67.2
0.000** 79.7
77.8
78.3
20.3
22.2
21.7
.724
Religion
Christian
Muslim/Other
40.5
67.8
59.5
32.2
0.000** 72.9
82.0
27.1
18.0
.000**
Ethnicity
Yoruba
Igbo
Hausa/Fulani
Others
17.0
19.4
70.6
56.2
83.0
80.6
29.4
43.8
0.000** 75.0
74.6
84.3
73.3
25.0
25.4
15.7
26.7
.000**
Marital status
Not married
Married
43.5
63.4
56.5
36.6
0.000** 79.6
78.6
20.4
21.4
.722
Sex of household head
Male
Female
63.1
41.8
36.9
58.2
0.000** 78.6
80.2
21.4
19.8
.560
Healthcare decision making
Respondent has no say
Respondent has a say
67.5
47.1
32.5
52.9
0.000** 80.2
73.3
19.8
26.7
.009**
Partner age difference
Same age/Small
Large
65.4
62.9
34.6
37.1
0.323 78.9
78.5
21.1
21.5
.892
Partner’s education level
None
Primary
Secondary and higher
78.7
58.2
39.1
21.3
41.8
60.9
0.000** 84.8
76.3
74.6
15.2
23.7
25.4
.0001**
Pregnancy intention
Wanted then
Mistimed/Unwanted
68.5
56.5
31.5
43.5
0.107 80.7
80.6
19.3
19.4
.991
Getting permission to go to health facility
Not a big problem
Big problem
57.7
75.6
42.3
24.4
0.000** 78.6
80.3
21.4
19.7
.585
Getting money to pay for healthcare costs
Not a big problem
Big problem
54.7
66.5
45.3
33.5
0.000** 80.7
76.7
19.3
23.3
.052
Distance to health facility
Not a big problem
Big problem
53.3
72.9
46.7
27.1
0.000** 79.5
77.0
20.5
23.0
.255
Place of residence
Urban
Rural
35.3
67.0
64.7
33.0
0.000** 81.5
77.8
18.5
22.2
.121
Region of residence
North Central
North East
North West
South East
South South
South West
55.8
68.8
70.6
19.5
46.0
22.7
44.2
31.2
29.4
80.5
54.0
77.3
0.000** 63.6
78.4
85.8
73.3
80.4
78.7
36.4
21.6
14.2
26.7
19.6
21.3
.000**
*significant at p < .05 **significant at p < .01
None/Incomplete: Less than four antenatal care visits Complete: Four or more antenatal care visits
Early: booking for ANC in the first trimester of pregnancy Late: booking any time after the first trimester
44 C. A. ALEX-OJEI AND C. O. ODIMEGWU

getting money to pay for healthcare costs, distance to health facility, and place and region of residence
(Table 3). Adolescent mothers with primary and higher education were more likely to have complete
antenatal care compared to those with no education. Also, young mothers from middle and rich
backgrounds were nearly twice more likely to have complete ANC usage than mothers from poor
backgrounds.
Table 3. Binary logistic regression between selected independent variables and number of antenatal care visits
among adolescent mothers in Nigeria.
Variable
Antenatal care utilization
Unadjusted OR Adjusted OR
Age
15–17
18–19
RC
1.40** (1.18–1.67)
RC
1.05 (0.85–1.30)
Educational level
None
Primary
Secondary and higher
RC
2.86** (2.28–3.58)
5.98** (4.83–7.39)
RC
1.54** (1.14–2.08)
1.64* (1.11–2.42)
Wealth index
Poor
Middle
Rich
RC
3.13** (2.54–3.85)
5.80** (4.60–7.31)
RC
1.88** (1.45–2.43)
1.92** (1.33–2.76)
Religion
Christian
Muslim/Other
RC
0.32** (0.27–0.39)
RC
1.16 (0.76–1.77)
Ethnicity
Yoruba
Igbo
Hausa/Fulani
Others
RC
0.85 (0.46–1.58)
0.09** (0.05–0.14)
0.16** (0.10–0.26)
RC
1.06 (0.16–7.12)
1.09 (0.42–2.83)
1.03 (0.40–2.68)
Marital status
Not married
Married
RC
0.44** (0.35–0.56)
RC
2.06 (0.49–8.66)
Sex of household head
Male
Female
RC
2.38** (1.85–3.05)
RC
1.20 (0.80–1.80)
Healthcare decision-making
Respondent has no say
Respondent has a say
RC
2.34** (1.92–2.85)
RC
1.44** (1.15–1.81)
Partner’s education level
None
Primary
Secondary and higher
RC
2.65** (2.06–3.40)
5.77** (4.65–7.14)
RC
1.73** (1.31–2.30)
2.44** (1.84–3.25)
Getting permission to go to health facility
Not a big problem
Big problem
RC
0.44** (0.35–0.55)
RC
0.75* (0.57–0.99)
Getting money to pay for healthcare costs
Not a big problem
Big problem
RC
0.61** (0.52–0.71)
RC
0.82 (0.66–1.03)
Distance to health facility
Not a big problem
Big problem
RC
0.42** (0.36–0.50)
RC
0.61** (0.49–0.75)
Place of residence
Urban
Rural
RC
0.27** (0.21–0.34)
RC
0.77 (0.56–1.05)
Region of residence
North Central
North East
North West
South East
South South
South West
RC
0.57** (0.42–0.78)
0.53** (0.39–0.71)
5.22** (3.28–8.31)
1.48* (1.03–2.14)
4.30** (2.62–7.03)
RC
0.95 (0.68–1.34)
0.79 (0.54–1.14)
2.45 (0.43–14.07)
0.82 (0.50–1.35)
3.68** (1.72–7.87)
RC: reference category OR: odds ratio *significant at p < .05 **significant at p < 0.01
WOMEN & HEALTH 45

Respondents who could contribute to decision-making concerning their healthcare had a higher
likelihood of complete antenatal care, compared to those who could not contribute to decision-
making. Adolescent mothers whose partners had primary and secondary or higher education had
higher likelihood of having complete ANC usage compared to those whose partners had no education.
Also, respondents who reported that they found it difficult to get permission to go the health facility
reported a lower likelihood of having complete antenatal care use compared to those who reported
that they had greater difficulty in obtaining permission. Similarly, those who reported that they found
it difficult to get to the health facility, due to the distance from their homes, had lower likelihood of
having complete antenatal care usage. Additionally, adolescent mothers in the South West were more
than three times more likely to use complete ANC compared to mothers in the North Central.
Six variables which were significant at the bivariate level were entered into the binary logistic
regression model for timing of first antenatal care visit, namely educational level, religion, ethnicity,
healthcare decision making, partner’s educational level, and region of residence (Table 4). It was
discovered that adolescent mothers who had secondary and higher education were more likely to start
antenatal care early. Also, adolescent mothers who were Muslims or adherents of other religions were
less likely to begin antenatal care early than those who were Christians. Also, adolescent mothers from
the North West, South South and South West regions were less likely to start ANC early.
Discussion
This study examined the sociodemographic correlates of the number of antenatal care visits and the
timing of the first antenatal care visit among adolescent mothers in Nigeria. Understanding how these
factors influence antenatal care use is important when designing interventions to improve ANC
Table 4. Binary logistic regression between selected independent variables and timing of first
antenatal care visit among adolescent mothers in Nigeria.
Variable
Timing of first ANC visit
Unadjusted OR (Model 0) Adjusted OR (Model 1)
Educational level
None
Primary
Secondary and higher
RC
1.66** (1.20–2.30)
1.78**(1.37–2.31)
RC
1.34 (0.92–1.95)
1.57* (1.05–2.34)
Religion
Christian
Muslim/Other
RC
0.59**(0.46–0.76)
RC
0.61*(0.40–0.93)
Ethnicity
Yoruba
Igbo
Hausa/Fulani
Others
RC
1.02 (0.57–1.86)
0.55* (0.35–0.89)
1.10 (0.69–1.73)
RC
0.18 (0.02–1.33)
0.55 (0.22–1.45)
0.59 (0.23–1.49)
Healthcare decision making
Respondent has no say
Respondent has a say
RC
1.48** (1.10–1.99)
RC
1.14 (0.84–1.55)
Partner’s education level
None
Primary
Secondary and higher
RC
1.74** (1.19–2.53)
1.91** (1.44–2.53)
RC
1.47 (0.99–2.18)
1.23 (0.84–1.55)
Region of residence
North Central
North East
North West
South East
South South
South West
RC
0.48**(0.34–0.67)
0.29** (0.20–0.41)
0.64 (0.39–1.04)
0.42**(0.28–0.64)
0.47**(0.30–0.75)
RC
0.70 (0.46–1.06)
0.43** (0.26–0.71)
1.20 (0.20–7.33)
0.30**(0.17–0.53)
0.29**(0.12–0.69)
RC: reference category OR: odds ratio ANC: antenatal care *significant at p < .05 **significant at p < .01
46 C. A. ALEX-OJEI AND C. O. ODIMEGWU

utilization among adolescent mothers in Nigeria, while taking into account their special circum-
stances. Also, this study serves to extend the literature on maternal healthcare utilization in Nigeria
and Africa, as well as provide information for policymakers and program designers who want to work
on increasing maternal healthcare utilization among adolescent mothers in Nigeria, Africa and other
low-income settings globally.
Findings from the study confirmed that antenatal care utilization is low among adolescent mothers
in Nigeria (Babalola & Fatusi, 2009; Dairo and Owoyokun 2010; Izugbara, Wekesah, and Adedini
2016; Ovikuomagbe 2017), which is worrisome giving the recognition of their higher need for
maternal healthcare (Ibrahim and Owoeye 2012; Ogu, Agholor, and Okonofua 2016; Wall 1998).
Also, adolescent mothers generally initiated antenatal care in the fourth month or later (Emelumadu
et al. 2014; Shahabuddin et al. 2015).
The study discovered that adolescent mothers with higher socioeconomic status had higher
incidence of complete antenatal care use, which is consistent with studies done elsewhere in Africa
(Banke-Thomas, Banke-Thomas, and Ameh 2017; Mekonnen, Dune, and Perz 2019). For instance,
being educated was an enabler of antenatal care use, as adolescent mothers who had primary or higher
education were more able to make use of antenatal care, and also have early ANC initiation
(Shahabuddin et al. 2015; Singh, Kumar, and Pranjali 2014). Previous studies have also highlighted
the role of partner education, and in this study, young mothers whose partners had at least primary
education had higher complete antenatal care use (Mekonnen, Dune, and Perz 2019; Rai, Singh, and
Singh 2012; Singh et al. 2012, 2013). The role of religion was also seen as an important determinant of
antenatal care use, as adolescent mothers who were Christians had higher complete antenatal care use
and booked earlier for ANC, compared to those who were Muslims or adherents of other religions
(Olusanya and Ebuehi 2012; Singh et al., 2014).
Adolescent mothers from households with higher wealth status had higher use of antenatal care
(Banke-Thomas, Banke-Thomas, and Ameh 2017; Ochako et al. 2011; Rai, Singh, and Singh 2012).
Also, autonomy was discovered to have a positive influence on ANC usage. Adolescent mothers who
were able to contribute to decision-making concerning their health had higher use of complete
antenatal care, compared to those who were unable to contribute to decision-making. Additionally,
adolescent mothers who reported that they could easily get permission from their families to go to the
health facility had higher likelihood of using antenatal care, similar to findings on autonomy by
Atuyambe et al. (2009) and Shahabuddin et al. (2015). Adolescent mothers who did not consider the
distance to the health facility as problematic were more likely to make use of antenatal care, as found
by Atuyambe et al. (2009) in Uganda. The problem of distance may also have arisen in rural areas, as
adolescent mothers living in rural areas had lower utilization of antenatal care, perhaps due to higher
distances between the health facility from and the young mothers’ homes (Banke-Thomas, Banke-
Thomas, and Ameh 2017; Ochako et al. 2011; Rai, Singh, and Singh 2012). It was discovered that
adolescent mothers in the South West region had higher likelihood of using complete antenatal care,
similar to the finding by Babalola and Fatusi (2009) who discovered higher usage of ANC in the
Southern zones in Nigeria. This may be because educational attainment is higher in the Southern
regions compared to the Northern regions, which may account for higher awareness of the importance
of antenatal care. It was also discovered that adolescent mothers in the South West, North West, and
South South zones were less likely to start ANC in the first trimester of their pregnancy. While lower
educational attainment (and thus lower awareness of the importance of antenatal care) may explain
this outcome in the North West, late initiation of ANC in the South South and South West may be due
to the stigma surrounding adolescent pregnancy. Unlike previous studies, pregnancy intention and
marital status were not significant correlates of antenatal care utilization (Magadi, Agwanda, and
Obare 2007; Saptarini and Setyonaluri 2018). These findings are possibly due to the fact that majority
of adolescent mothers in these study reported that their pregnancies were wanted, and also reported
being married.
If antenatal care is to be made accessible to adolescent mothers in Nigeria so that utilization can
increase in line with the Third Sustainable Development Goal, it is important to know the correlates of
WOMEN & HEALTH 47

antenatal care utilization among mothers in this age group. The study found that higher status
adolescent mothers are more likely to use antenatal healthcare than lower status mothers. This therefore
means that interventions on increasing antenatal care utilization among adolescent mothers must focus
their attention on adolescent mothers who are uneducated and from the poorest strata of society, who
also live under conditions where they lack autonomy and decision-making power. Resources must also
be deployed to establish more standard health facilities especially in rural areas, and as a temporary
palliative, community health extension workers may also be utilized to take antenatal care to the most
vulnerable adolescent mothers in their homes. Also, culturally sensitive messages must be developed to
sensitize adolescent mothers on the importance of antenatal care for positive pregnancy outcomes for
adolescent mothers in different regions. Furthermore, qualitative studies should be carried out to
discover additional social and cultural factors, which influence adolescent mothers’ usage of antenatal
care services as well as the timing of their antenatal care commencement.
The study is not without limitations. First of all, its cross-sectional nature means that causality
cannot be inferred from findings. Also, responses may be subject to social desirability bias, especially
as the incidence of wanted pregnancies was found to be quite high among adolescent mothers in this
study. Additionally, some respondents may have experienced difficulty in accurately recalling
responses to some of the questions asked. Despite these limitations, the study possesses certain
strengths. It made use of nationally representative data, ensuring greater generalizability of the results.
Also, data from four rounds of the Nigeria Demographic and Health Survey were pooled, resulting in
a larger sample and ensuring reduced sampling error. Additionally, the subpopulation, rather than
subsample option was used, resulting in more accurate sample variances. Furthermore, the study
chose to examine associations between independent variables and antenatal care use and timing,
rather than causality.
Disclosure statement
No potential conflict of interest was reported by the author(s).
ORCID
Clifford Obby Odimegwu , PhD http://orcid.org/0000-0002-6273-8807
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