Determinants of modern contraceptive use among adolescent girls and young women in Nigeria

INTRODUCTION

According to the 2020 World Youth Report, an estimated 1.2 billion individuals aged 15–24 years representing 16% of the global population—were alive in 2020.^1,2 By 2021, the United Nations projected that the number of young people would increase by 7%, reaching approximately 1.3 billion by 2030, the target year for achieving the sustainable development goals (SDGs).² Adolescents and young people living in humanitarian settings are particularly vulnerable due to the breakdown of social support systems, which increases their exposure to sexual coercion, exploitation, violence, early marriage and harmful coping strategies.³ These conditions contribute to a higher incidence of unintended pregnancies and increased demand for safe abortion services.³ Pregnancy remains a major public health concern, especially in low- and middle-income countries (LMICs), where adolescent girls experience high rates of unintended pregnancy, often with short inter-pregnancy intervals.^4,5 Sub-Saharan Africa has the highest prevalence of adolescent pregnancies globally, coupled with the lowest uptake of modern contraception.⁶ Although adolescent fertility has slightly declined over the past two decades, it remains persistently high across Africa. In sub-Saharan Africa, the adolescent birth rate was reported at 101 births per 1,000 females the highest regional rate worldwide.⁵

The highest rates of adolescent and young women pregnancies and the lowest rates of use of contemporary contraception are seen in Sub-Saharan Africa.⁶ Approximately one-third of adolescent pregnancies in the region are unintended and more than one-third of this end in unsafe abortions.⁷ Pregnancy-related complications are a leading cause of maternal mortality among adolescent girls aged 15–19 in LMICs.⁸ Furthermore, adolescent pregnancy is associated with adverse health outcomes, including anemia, preterm birth, low birth weight and poor mental health, in addition to limiting educational and employment opportunities.⁹

Nigeria presents one of the highest fertility rates globally, with a total fertility rate (TFR) of 5.4.¹⁰ Given global commitments to reduce fertility rates by 2050, Nigeria’s fertility dynamics are expected to significantly influence this trajectory. International and national frameworks including the 1994 International Conference on Population and Development (ICPD), the 2015 SDGs, the African Union Agenda 2063 and Nigeria’s 8-point reform agenda emphasize the importance of population management and improving well-being by slowing rapid population growth.

A critical component of this effort is raising the contraceptive prevalence rate (CPR) among women of reproductive age (15–49 years). Despite multiple family planning initiatives, Nigeria continues to record a low CPR of 17%, in stark contrast to other sub-Saharan African countries such as Malawi (66%), Kenya (65%), Rwanda (64%), Cabo Verde (56%) and South Africa (55%).¹⁰ Persistent demand-side barriers undermine progress in contraceptive uptake, limiting the effectiveness of government interventions to reduce fertility rates and population growth.^11,12

METHODS

Study design and setting

In this study, we analysed cross-sectional data from the most recent NDHSs. The datasets across all the states were used to determine barriers and enablers of modern contraceptive use among adolescent girls and young women in Nigeria.

Data source and study population

Data for this study were obtained from the NDHS conducted in 2018. The NDHS provides nationally representative data on demographic, health and sexual and reproductive health indicators, including family planning, fertility, pregnancy, maternal health, health-seeking behaviours and sexual behaviour. This study specifically utilized the women’s recode file (IR), which contains responses from women aged 15–49 years. The NDHS employed a two-stage stratified sampling design. In the first stage, enumeration areas (EAs) were selected using probability sampling proportional to size, with independent selections carried out within each sampling stratum. In the second stage, households within selected EAs were systematically sampled.

The study population comprised sexually active adolescent girls and young women (AGYW) aged 15–24 years who were not pregnant at the time of the survey. AGYW who were pregnant or who had never engaged in sexual activity were excluded from the analysis, as they were not considered eligible for modern contraceptive use. After applying these criteria, a weighted total of 8,825 AGYW aged 15–24 years were included in the analysis (Table 1). Respondents with missing data on variables of interest were excluded. The NDHS datasets used for this analysis are publicly available at http://dhsprogram.com/data/available-datasets.cfm.

Study variables

Outcome variable

The primary outcome variable for this study was the current use of modern contraceptives. This was derived from responses to a survey question asking AGYW about the type of contraceptive method they were using at the time of the survey. Reported methods were categorized into four groups: no method, folkloric method (i.e., cultural or spiritual practices), traditional method and modern method. For the purposes of this study, AGYW who reported using any modern contraceptive method were coded as “1” (users). Those who reported no method, folkloric methods or traditional methods including periodic abstinence (e.g., rhythm or calendar method), withdrawal, country-specific traditional methods and locally described or spiritual practices were classified as “0” (non-users).

Explanatory variables

Eighteen explanatory variables were included in this study, categorized into individual and community-level variables to align with the multilevel analytic approach. These variables were chosen based on their availability in the datasets and as potential determinants of modern contraceptive use based on the literature reviewed for this study.

Individual level variables

Modern contraception (not using, using), age (15-19 20-24), education level (no education, primary, secondary, higher ), marital status (never in union, currently in union, formerly in union), parity (no children, 1–2 children, 3+ children), fertility preference (want more, no more/sterilized/infecund, undecided), recent sexual activity (not active, active) age at first sex (≤14, 15–17, 18+), respondent currently working (no, yes), visited health facility last 12 months (no, yes), getting medical help for self: distance to health facility (big problem, not a big problem) wealth index (poorest, poorer, middle, richer, richest) and ever had a terminated pregnancy (no, yes).

Community level variables

Type of place of residence (Urban, Rural) Community wealth index (Poorest, Poorer, Middle, Richer, Richest) Years lived in place of residence (Recent mover (<5 years), Long-term (≥5 years/Always), Visitor) Region (North central, North east, North west, South east, South south, South west).

Statistical analysis

Data were processed, cleaned and analyzed using STATA/SE version 14. All analyses were weighted to account for the complex survey design, including clustering within sampling units, unequal probabilities of selection and potential non-response, thereby ensuring the reliability of estimates and standard errors.

Given the hierarchical structure of the DHS data which violates the assumptions of independence of observations and homoscedasticity required for ordinary logistic regression a multilevel mixed-effects logistic regression model was employed to account for between-cluster variability.

The analysis followed a three-step approach. First, descriptive statistics (frequencies and percentages) were computed to estimate the pooled prevalence of modern contraceptive use among AGYW in Nigeria. Second, bivariate analyses were conducted using the chi-square test of independence (χ²) at a 95% confidence level (CI) to explore the distribution of modern contraceptive use across individual- and community-level variables. Explanatory variables with a p-value≤0.20 were retained for multivariable analysis. Third, a multilevel logistic regression model was fitted, incorporating both fixed and random effects. Multicollinearity was assessed using the variance inflation factor (VIF), with results indicating no significant collinearity (Mean VIF=1.66; Maximum VIF=3.56; Minimum VIF=1.02).

A total of four models were specified. Model 1 was the empty model (without explanatory variables), which estimated the proportion of variance in the outcome attributable to clustering at the primary sampling unit (PSU) level. Model 2 included only individual-level determinants, Model 3 included only community-level determinants and Model 4 simultaneously included both individual- and community-level determinants. Fixed effects were reported as adjusted odds ratios (aORs) with 95% CIs, while random effects were assessed using the Intra-Cluster Correlation (ICC).

Model adequacy was evaluated using the Likelihood Ratio (LR) test and the Wald chi-square test. Model comparisons were based on the Akaike Information Criterion (AIC) and the Log-Likelihood Ratio (LLR), with the best-fitting model identified as the one with the lowest AIC and highest LLR value. All analyses and reporting followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.

RESULTS

A total of 8,825 adolescent girls and young women (AGYW) aged 15–24 years were included in the analysis. The weighted prevalence of modern contraceptive use among the study population was 9.1%, indicating very low uptake in this group. Regarding age distribution, about one-third of respondents were adolescents aged 15–19 years (34.4%), while the majority were young women aged 20–24 years (65.6%). Educational attainment varied widely: nearly two-fifths had no formal education (39.6%), while 13.4% attained primary education, 41.6% completed secondary education and only 5.4% had higher education.

Most respondents were currently married or in union (71.4%), while 28.6% were never married. Fertility experience was common, with 49.3% reporting one to two children, 12.9% having three or more children and 37.8% having no children. Fertility preference revealed a strong desire for future childbearing: 94.3% expressed wanting more children, whereas only 5.7% wanted no more. Sexual activity was reported by nearly two-thirds of participants, with 64.9% sexually active in the past four weeks. Early sexual debut was also prominent: 42.5% had first intercourse before age 18, while 57.5% initiated sexual activity at 18 years or older. A small proportion (8.5%) reported ever terminating a pregnancy.

Socioeconomic indicators showed a relatively even distribution across wealth quintiles, though skewed slightly toward poorer households: 22.9% in the poorest, 20.4% poorer, 19.4% middle, 19.5% richer and only 17.8% in the richest quintile. With respect to occupation, 46.8% of respondents were not engaged in any work, 27.5% were in agricultural or manual labor, while 25.7% were employed in professional, clerical or service-related jobs.

Religion and ethnicity reflected Nigeria’s demographic composition. A vast majority were Muslim (72.6%), while 27.4% were Christians or adherents of other religions. Ethnically, Hausa constituted 39.5%, Yoruba 13.3%, Igbo 13.7% and other minority ethnic groups 33.5%.

Most respondents resided in rural areas (65.2%), compared with 34.8% in urban settings. Residential stability was high, with 90.5% reporting living in the same community for at least five years. Regional distribution showed marked concentration in the northern zones, particularly the North West (43.2%), followed by North East (17.4%), North Central (15.7%), South South (9.6%), South West (8.6%) and South East (5.5%).

Access to health care services remained a concern, as 28.9% reported distance to a health facility as a major barrier, while the majority (71.1%) did not perceive distance as a problem. The bivariate analysis revealed strong and statistically significant associations between socio-demographic, reproductive and contextual factors and the uptake of modern contraceptives among adolescent girls and young women (p<0.05 for most variables).

Age was an important determinant: contraceptive use was lowest among adolescents aged 15–19 years (23.9%) compared to young women aged 20–24 years (76.1%) (p<0.0001). Similarly, education level showed a strong gradient—contraceptive uptake increased markedly with higher education, ranging from only 8.7% among those with no education to 68.2% among those with secondary education and 15.4% among those with higher education (p<0.0001). Marital status was also significant. While the majority of adolescents were currently in union, contraceptive use was disproportionately higher among those never in union (49.1%) compared to those currently married (49.7%) or formerly married (1.2%) (p<0.0001). Parity further highlighted this trend contraceptive use was highest among those without children (46.6%), declining with increasing number of children (p<0.0001).

With respect to fertility preference, those who desired no more children, were sterilized or infecund reported higher contraceptive use (91.2%) compared to those who wanted more children (94.2%) (p=0.011). Interestingly, recent sexual activity did not significantly influence contraceptive use (p=0.3403). However, earlier sexual debut (≤14 years) was associated with the lowest contraceptive use (12.5%), while initiation at older ages (≥18 years) was linked to higher uptake (39.9%) (p<0.0001).

Socioeconomic indicators showed consistent effects. Contraceptive use increased steadily with wealth, from 6.4% in the poorest quintile to 27.4% in the richest (p<0.0001). Similarly, those who reported that distance to a health facility was not a big problem had significantly higher contraceptive uptake (76.1%) compared to their counterparts (23.9%) (p=0.0072). Women who were currently employed were also more likely to use contraceptives (59.2%) compared to those not working (40.8%) (p=0.0003). Religious affiliation and ethnicity played significant roles. Contraceptive use was lowest among Muslim women (31.1%) compared to Catholics (13.5%) and other Christians (55.3%) (p<0.0001). Ethnic disparities were also pronounced, with use highest among women in the "Other" ethnic group (47.3%) and lowest among Hausa (13.5%) (p<0.0001).

Regarding community-level factors, women in urban areas reported significantly higher contraceptive uptake (51.1%) compared to rural residents (48.9%) (p<0.0001). Community wealth index further revealed that uptake increased progressively from poorest (8.5%) to richest communities (27.9%) (p<0.0001). Recent movers were more likely to use contraceptives (26.8%) compared to long-term residents (71.7%) and visitors (1.5%) (p=0.0185).

Regional variations were striking (p<0.0001). Uptake was lowest in the North West (14.4%) and North East (14.1%), while the highest levels were recorded in the South (22.3%) and South West (20.4%). In contrast, health service utilization indicators such as visiting a health facility in the last 12 months (p=0.4401) and history of pregnancy termination (p=0.1740) did not show significant associations with contraceptive use.

Table 3 presents the fixed and random effects from four models examining predictors of modern contraceptive use among adolescent girls and young women in Nigeria. Model 1 (null model) showed significant variation across clusters, with a PSU-level variance of 1.68 (95% CI: 1.34–2.12), corresponding to an intraclass correlation coefficient (ICC) of 33.9%. This justified the application of multilevel modeling.

Model 2 (individual-level factors)

Age was significantly associated with contraceptive uptake: women aged 20–24 years were more likely to use modern methods compared to adolescents aged 15–19 (aOR=1.40, 95% CI: 1.12–1.74). Education showed a strong gradient effect, with odds of use increasing from primary (aOR=2.51, 95% CI: 1.71–3.68) to higher education (aOR=7.04, 95% CI: 4.65–10.65) relative to women with no education. Being currently or formerly in a union reduced the likelihood of use compared to never-married women. Higher parity (≥3 children) was strongly associated with contraceptive use (aOR=2.61, 95% CI: 1.78–3.81). Fertility preference also played a role, as women undecided about future childbearing were more likely to use contraception (aOR=1.46, 95% CI: 1.01–2.09). Household wealth showed a dose-response association, with the richest quintile having more than twice the odds of contraceptive use compared to the poorest (aOR=2.27, 95% CI: 1.51–3.41). Religion and ethnicity were significant predictors, with Muslim women having lower odds than Catholics (aOR=0.42, 95% CI: 0.29–0.61) and Yoruba and Fulani women showing higher uptake than Hausa. Rural residence reduced odds by half (aOR=0.50, 95% CI: 0.40–0.62). At the community level, higher community wealth was consistently associated with contraceptive uptake, with those in the richest communities having threefold higher odds compared to the poorest (aOR=3.10, 95% CI: 2.19–4.39).

Model 3 (interpersonal and household factors)

When interpersonal and household factors were introduced, the associations remained broadly consistent, although the effect sizes for education, parity and wealth were slightly attenuated. Religion retained significance, with Muslim women less likely to use modern contraception (aOR=0.56, 95% CI: 0.38–0.83). Region also emerged as a factor, with women in the South East having higher odds than those in the North Central (aOR=1.44, 95% CI: 1.01–2.05).

Model 4 (full model including community factors)

In the fully adjusted model, age, education, marital status and parity remained strong predictors of contraceptive use. Women aged 20–24 were 37% more likely to use contraception (aOR=1.37, 95% CI: 1.09–1.71) and those with higher education remained nearly six times more likely than those without education (aOR=5.60, 95% CI: 3.63–8.64). Being in union continued to reduce use, while higher parity increased it. Wealth remained important, with richer women more likely to adopt contraception. The religious gap persisted, with Muslim women significantly less likely than Catholics (aOR=0.56, 95% CI: 0.38–0.83). Ethnic and community-level effects diminished in significance after full adjustment, suggesting that individual and household characteristics account for much of the observed variation.

Random effects and model fit

Across models, PSU variance declined from 1.68 in the null model to 0.71 in the full model and ICC reduced from 33.9% to 17.8%, indicating that individual and community-level factors explained a substantial share of between-cluster differences. Likelihood ratio tests confirmed that multilevel models significantly improved fit over single-level models (p<0.001). Model fit statistics (AIC and BIC) also favored the full model. Overall, uptake of modern contraception among adolescent girls and young women was strongly patterned by age, education, marital status, parity, wealth and religion. Community and regional factors initially contributed, but their effects were attenuated once individual and household characteristics were considered.

*p<0.05, **p<0.01, ***p<0.001.

DISCUSSION

This study applied a multilevel modeling framework to examine determinants of modern contraceptive use among adolescent girls and young women in Nigeria, accounting for both individual- and community-level factors. The null model demonstrated substantial clustering of contraceptive use at the PSU level, with nearly one-third of the variation attributable to community differences. This justified the use of multilevel analysis rather than single-level models. At the individual level, age, education, marital status, parity and household wealth consistently emerged as strong predictors. Uptake was higher among young women aged 20–24 compared to adolescents 15–19, underscoring the persistent gap in contraceptive access among younger adolescents this is similar to some studies conducted.^13,14 Education showed a robust gradient effect, with higher education increasing the likelihood of contraceptive use more than fivefold which is similar to a study conducted in Ghana, highlighting the transformative role of female education in shaping reproductive behavior.¹⁵ Similarly, wealth exerted a dose–response relationship, with the richest women significantly more likely to use modern contraception than their poorest counterparts. These findings align with evidence from other Sub-Saharan African countries where socioeconomic empowerment facilitates contraceptive uptake.¹⁶

Marital status and parity also played crucial roles. Being in a union was associated with lower contraceptive use, suggesting that cultural or partner-related constraints may inhibit uptake among married adolescents and young women.¹⁷ In contrast, higher parity increased use, reflecting the tendency of women to adopt contraception after reaching desired family size which is similar to a study conducted in Ibadan Nigeria.¹⁸ Fertility preference further reinforced this pattern, with undecided women more likely to use contraception, possibly reflecting uncertainty about future childbearing desires.

Religion and ethnicity retained significance in several models. Muslim women consistently had lower odds of contraceptive use than Catholics, a pattern well documented in Nigerian reproductive health research and likely linked to socio-cultural norms and divergent family planning messages across faith communities, which is similar to a study conducted in Nigeria.^19,20 Ethnic differences were also observed, though these diminished after adjusting for socioeconomic and household factors, indicating that structural determinants may explain much of the variation initially attributed to ethnicity. The findings of this study reveal that living in urban areas was found to be associated with higher odds of using modern contraceptives, similar to findings of studies from other developing countries where young women from rural areas reported barriers to modern contraceptive use.^19,21

Community and regional contexts contributed importantly in the earlier models, particularly community wealth and regional location. However, their effects were attenuated in the fully adjusted model, suggesting that much of the between-community variation is mediated through individual and household-level characteristics such as education and wealth. Nevertheless, the persistence of significant random effects after full adjustment indicates that unobserved contextual influences remain, potentially reflecting differences in service availability, quality of family planning programs or local sociocultural environments.

The progressive reduction in PSU-level variance from 1.68 in the null model to 0.71 in the full model, alongside a decline in ICC from 33.9% to 17.8%, highlights that both individual and household factors substantially explained community-level differences in contraceptive use. Yet, the residual clustering underscores the continued importance of community-level dynamics in shaping contraceptive behavior. Overall, these findings emphasize that modern contraceptive uptake among adolescent girls and young women in Nigeria is driven primarily by individual-level socioeconomic and demographic factors, particularly age, education, marital status, parity, wealth and religion, while contextual effects remain secondary but non-negligible. Policy interventions should therefore prioritize adolescent-friendly strategies that expand access for younger, less educated and poorer women, while also addressing religious and cultural barriers to use. At the same time, strengthening community-level family planning services and fostering supportive environments remains essential to reducing the persistent clustering of contraceptive behavior.

Policy and program implications

These findings have important implications for family planning programs in Nigeria. First, strategies should prioritize reaching younger adolescents (15–19 years) and nulliparous women who are at high risk of unmet need but least likely to access services. Second, interventions must be tailored to address sociocultural barriers among married adolescents and Muslim communities, including engaging religious and community leaders to foster support for contraceptive use. Third, efforts to reduce socioeconomic and geographic inequities are critical, including scaling up mobile outreach services and removing financial and physical barriers to access. Fourth, education and empowerment of girls remain long-term but essential strategies to enhance contraceptive uptake. Finally, strengthening community-based and youth-friendly services is vital to ensure that health facility visits translate into actual contraceptive use.

Strengths

A major strength of this study lies in the use of nationally representative DHS data with robust multilevel modeling that accounts for both individual and contextual influences.

Limitations

However, limitations should be noted. The cross-sectional design precludes causal inference. Self-reported contraceptive use may be subject to recall or social desirability bias, particularly among unmarried adolescents. Furthermore, the DHS does not capture some critical determinants such as provider attitudes, quality of counseling or detailed measures of gender norms, which could explain the remaining cluster-level variance.

CONCLUSION

In conclusion, this study underscores the multifaceted determinants of modern contraceptive use among adolescent girls and young women in Nigeria. Age, parity, marital status, education, wealth, religion, ethnicity and community context all significantly influence uptake, with strong evidence of persistent contextual effects beyond individual characteristics. Addressing the unmet need for contraception in this population requires a comprehensive strategy that combines individual empowerment, sociocultural engagement, service delivery improvements and broader structural interventions. Tailoring policies and programs to the unique needs of adolescents and young women, particularly in underserved northern regions, will be essential to achieving Nigeria’s family planning goals and improving reproductive health outcomes.

Funding: African Union Commission through the Pan African University Life and Earth Sciences Institute (including Health and Agriculture), Ibadan, Nigeria

Conflict of interest: None declared

Ethical approval: The study was approved by the Institutional Ethics Committee

REFERENCES

1. 1. UNESCO. UNESCO with, by and for youth. Paris: UNESCO. 2023. Available at: https://www.unesco.org/en/youth. Accessed on 17 August 2025.
2. 2. United Nations. Global issues: youth. New York: United Nations. 2021. Available at: https://www.un.org/en/global-issues/youth. Accessed on 17 August 2025.
3. 3. UNFPA, Save the Children. Adolescent sexual and reproductive health toolkit for humanitarian settings: a companion to the inter-agency field manual on reproductive health in humanitarian settings. New York: The United Nations sexual and reproductive health agency. 2009. Available at: https://www.unfpa.org/publications/adolescent-sexual-and-reproductive-health-toolkithumanitarian-settings. Accessed on 21 August 2025.
4. 4. Amongin D. Time trends in and factors associated with repeat adolescent birth in Uganda: Analysis of six demographic and health surveys. Plos One. 2020;15(4):232145.
5. 5. Sidibé S. Trends in contraceptive use, unmet need and associated factors of modern contraceptive use among urban adolescents and young women in Guinea. BMC Public Health. 2020;20:1840.
6. 6. Dennis ML, Radovich E, Wong KLM, Owolabi O. Pathways to increased coverage: an analysis of time trends in contraceptive need and use among adolescents and young women in Kenya, Rwanda, Tanzania and Uganda. Reproductive Health. 2017;14(1):1-14.
7. 7. Sserwanja Q, Musaba MW, Mukunya D. Prevalence and factors associated with modern contraceptives utilization among female adolescents in Uganda. BMC Women’s Health. 2021;21:61.
8. 8. de Vargas Nunes Coll C, Ewerling F, Hellwig F, de Barros AJD. Contraception in adolescence: the influence of parity and marital status on contraceptive use in 73 low-and middle-income countries. Reproductive Health. 2019;16(1):1-12.
9. 9. Sserwanja Q, Musaba MW, Mukunya D. Prevalence and factors associated with modern contraceptives utilization among female adolescents in Uganda. BMC Women’s Health. 2021;21:61.
10. 10. Waithaka MW, Gichangi P, Thiongo M. Assessing the magnitude of and factors associated to demand for long-acting reversible contraceptives. MedRxiv. 2020;11:30383.
11. 11. Sambah F, Aboagye RG, Seidu AA, Tengan CL, Salihu T, Ahinkorah BO. Long-acting reversible contraceptives use among adolescent girls and young women in high fertility countries in sub-Saharan Africa. Reprod Health. 2022;19:209.
12. 12. Bolarinwa OA, Olagunju OS. Knowledge and factors influencing long-acting reversible contraceptives use among women of reproductive age in Nigeria. Gates Open Research. 2020;3:7-16.
13. 13. Makwinja AK. Delivery strategies for optimizing uptake of contraceptives among adolescents aged 15–19 years in Nsanje District, Malawi. Reprod Health. 2021;18:132.
14. 14. Sanni OF. A comparative analysis of factors associated with modern contraceptive use among youth in Northern and Southern Nigeria: A cross-sectional population-based survey (2011–2021). PLOS Glob Public Health. 2025;5(6):4685.
15. 15. Oppong FB. Determinants of contraceptive use among sexually active unmarried adolescent girls and young women aged 15–24 years in Ghana: a nationally representative cross-sectional study. BMJ Open. 2020;10:35041.
16. 16. Mutua MK. Wealth-related inequalities in demand for family planning satisfied among married and unmarried adolescent girls and young women in sub-Saharan Africa. Reprod Health. 2021;14:116.
17. 17. Chandra-Mouli V, Parameshwar PS, Parry M. A never-before opportunity to strengthen investment and action on adolescent contraception and what we must do to make full use of it. Reprod Health. 2017;14(1):81.
18. 18. Atoyebi AO, Olaoye SO, Okunlola MA. Trends and pattern of contraceptive use among women attending a family planning clinic at a tertiary health facility in Ibadan, Nigeria. BMC Public Health. 2025;25:2134.
19. 19. Bolarinwa OA. Inequality gaps in modern contraceptive use and associated factors among women of reproductive age in Nigeria between 2003 and 2018. BMC Womens Health. 2024;24(3):317.
20. 20. Beson P, Appiah R, Adomah-Afari A. Modern contraceptive use among reproductive-aged women in Ghana: Prevalence, predictors and policy implications. BMC Womens Health. 2018;18:157.
21. 21. Mankelkl G, Kassaw AB, Kinfe B. Factors associated with modern contraceptive utilization among reproductive age women in Kenya; evidenced by the 2022 Kenyan demographic and health survey. Contracept Reprod Med. 2024;9(1):10.