According to the World Health Organization, roughly 16 million teen mothers aged 15 to 19 give birth annually resulting a 44,000 births per day worldwide.

Background: According to the World Health Organization, roughly 16 million teen mothers aged 15 to 19 give birth annually resulting a 44,000 births per day worldwide. Moreover, the vicious cycle of poverty in sub-Saharan Africa is exacerbated by adolescent pregnancy, this also increases maternal, perinatal, and infant mortality hindering SDG goal 5 and target 3 of ending the child marriage of 2030 to be achieved. This study aimed to identify the prevalence, trends, and determinants of teenage pregnancies in Rwanda between 2010 and 2020.

Methods: This study used Rwanda's demographic and health survey data from 2010, 2015, and 2020, and a cross-sectional study design. All data were cleaned and appended to get the final data set for analysis, all analyses were performed using R software package 4.3.1. Moreover, statistical significance was determined at a 5% p-value and 95% Confidence Interval (CI) while not crossing one.

Results: The total number of teenagers between 2010 and 2020 was 9,050 and among them, the prevalence of teenage pregnancy was 6.11% (n = 553/9050). By trend, teenage pregnancy in 2010 was 6.22%, in 2015, 7.30%, and in 2015 5.41% in prevalence. After adjusting the variables in a multivariate logistic regression model, the following were found to be potential predictors of teenage pregnancy in Rwanda: Region by Eastern province (AOR: 1.55:95% CI: 1.078,2.24), lack of education and primary school teens (AOR: 2.9:95% CI: 1.22,6.89) and AOR: 1.67:95% CI: 1.25,2.24)respectively, Poorest households AOR: 2.02:95% CI: 1.27,3.12), those with knowledge of contraceptive methods (AOR: 8.70:95% CI: 3.34,23.01), sexually active unmarried women (AOR: 3.50:95% CI: 1.58,7.78), teens who did not access social media (AOR: 2.03:95% CI: 1.41,2.91), and it was protective against family size.

Conclusion: These results imply that a combination of social, sociodemographic, and knowledge-related factors, as well as awareness of contraceptive techniques, may impact teenage pregnancy in Rwanda. The provision of contraception education and awareness should be the primary goal of efforts to minimize adolescent pregnancies in Rwanda, particularly in areas where the prevalence is higher. In addition, encouraging family planning and tackling economic inequalities can be effective tactics to lower adolescent pregnancy rates.

According to the World Health Organization, around 16 million girls aged 15-19 give birth each year, which means that there are approximately 44,000 births each day to teenage mothers globally [1]. While child sexual abuse and early marriage can increase the risk of adolescent pregnancy, they are not the only factors contributing to this issue. Other factors that can increase the risk of adolescent pregnancy include poverty, lack of education, limited access to sexual and reproductive health services, and gender inequality [2]. At 57 pregnancies per 1,000 females, the United States had the highest pregnancy rate among females aged 15 to 19 years, while Switzerland had the lowest rate [3]. In Low- and Middle-Income Nations (LMICs), girls between the ages of 15 and 19 had an estimated 21 million pregnancies annually as of 2019, about half of which were unintended and led to an estimated 12 million births [4,5]. Teenage pregnancies continue to be unacceptably high, particularly in sub-Saharan Africa, despite the decline in adolescent birth rates worldwide from 65 to 47 births per 1,000 women between 1990 and 2015 [5].

In low-income countries, teenage pregnancies are a serious public health issue. Pregnant teenagers have a higher risk of adverse health outcomes owing to biological and social factors. Teenagers' school dropout rates are exacerbated by pregnancy, which affects their prospects for employment and long-term financial security [6]. In a systematic review and meta-analysis conducted in Africa in 2018, the prevalence of adolescent pregnancies was 18.8%, while it was 19.3% in sub-Saharan Africa. East Africa had the highest prevalence (21.5%), while Northern Africa had the lowest (9.2%). Adolescent pregnancy risk factors include living in a rural area, having never married, not attending school, having neither parent completed their education, and not being adequately informed about Sexual and Reproductive Health (SRH) concerns by the media [7]. Furthermore, a study conducted in Rwanda revealed that many teenagers who become pregnant try unsafe abortions, some of which have resulted in severe genital organ damage or death, which puts them at a higher risk to health [8].

According to the recent survey of Rwanda Demographic (RDHS 2019/2020) the found that teen pregnancy prevalence rate had changed from 6.1% in 2010 to 5.0% in 2020, generally teenage pregnancy seems to have a minimal reduction in prevalence looking the stated years from 2010 to 2020. However, this study aims to conduct a study on the prevalence, trends, and determinants of teenage pregnancies in Rwanda.

Study setting and design

Rwanda is a landlocked nation in the central-eastern part of Africa's Great Lakes region, measures 26,338 km2, and boasts a dense population. It is administratively segmented into the City of Kigali, which has 416 sectors, 30 districts, and four other provinces this was published by Rwanda's Ministry of Local Government in special gazette number 44 in 2005. It was further estimated that Rwanda's recent population of around 13.2 million as of the 2022 population and housing census report published by the National Institute of Statistics (NISR), again the majority of Rwanda's inhabitants, about 85%, work in agriculture. The country features a notably intricate and active hydrological system dotted with numerous lakes and rivers. Floodplains and wetlands span approximately 10% of its terrain. In addition, under the guidance of Vision 2020 and the Economic Development and Poverty Reduction Strategy (EDPRS), emphasis was placed on rural development and agricultural evolution as pivotal drivers for swift and enduring growth and this was reported by MINECOFIN, Rwanda for Vision 2020 plan.

Study population

This study considered all teenagers (females) aged 15 to 19 years old that is those who experienced or had pregnancies. The teenage data were derived from Individual Records (IR) where the women and their information details were contained and the main source was DHS.

Study sampling and sample size

The Rwandan demographic and health survey followed a two-stage sample design. It is intended to allow estimates of key indicators at the national level, as well as for urban and rural areas, five provinces, and each of Rwanda’s 30 districts for some limited indicators. The first stage involved selecting the sample points (clusters). The second stage involved a systematic sampling of households. Household listing and selection are always undertaken in all selected Enumeration Areas (EAs) of Rwanda housing and the population census of 2012.No sample calculation was needed because all participants were eligible to participate in the study. However, inclusion and exclusion criteria were used to come up with the final sample size (Figure 1).

Figure 1: Shows the flow diagram of the sample size used in the study.
Source: Author’s primary compilation.

Inclusion and exclusion criteria

An individual to be considered was supposed to be a permanent resident or visitor who stayed in a household the night before the survey started and was eligible for the survey. In addition, some specific tests such as anemia, HIV, and malaria were first conducted before sample collection; otherwise, participants were not included in the survey. Finally, unoccupied households were not considered in data collection.

Data collection tools used

The Rwanda Demographic and Health Survey used Computer-Assisted Personal Interviewing (CAPI) for data collection, and these were frequently published in RDHS reports. Moreover, different structured questionnaires were used to obtain stratified data. This study used a data set in which a women’s structured questionnaire was employed as a data collection tool, whereby all eligible individuals' information on the following was obtained: background information, reproductive information, vaccination status, nutrition and health, information access, and mortalities. Lastly, the questionnaire was coded in two different languages which are Kinyarwanda and English.

Data processing and analysis

This study used an Individual Record (IR) dataset from seven datasets in the RDHS data toolkit. The individual records data set was reserved for women-level analysis (Marriage and sexual activity) and contained household information. Because the study focused on 2010, 2015, and 2020 data, every dataset was cleaned and later appended using key identifiers. Data on sociodemographic variables and household information of selected teens were analyzed using descriptive analysis to determine frequencies and percentages. Bivariate analysis using a chi-square test of independence was carried out to test associations between predictors of teenage pregnancy, and the proportions were obtained as frequencies and percentages. Predictors in the bivariate analysis were considered statistically significant when the p-value was 5%. However, all predictors with p < 0.2 in the Chi-square test results were further taken into univariate and multivariate logistic regression analyses. Multivariable logistic regression analysis was conducted using stepwise forward logistic regression by adding one predictor at a time and using the predictors of the full model generated by univariate logistic regression. Furthermore, predictors with a correlation coefficient(r) less than (r < 0.8) or Variance inflation factor (< 10) were considered in the multivariable logistic regression. Odds Ratios (OR), 95% Confidence Intervals (CIs), and p-values are reported. All statistical analyses were conducted using R Software Version 4.3.1. Lastly, during analysis, all estimates were weighted by women's weight variable as a result of the sample design used in primary data collection.

Outcome variable

A woman aged 15 to 19 who had at least one live birth, who had ever had an abortion or stillbirth, or who was pregnant at the time of the survey was considered to have teenage pregnancy as an outcome variable. The study assessed teenage pregnancy as a dichotomous variable, whereby teen pregnancies were coded as 1 and 0 for no pregnancy.

Independent variable(s)

Social demographic characteristics and household characteristics variables:

• Region: All regions of Rwanda (Eastern Province, Western Province, Southern Province, and Kigali City) were assessed.
• Place of residence: Whether the respondent was from an urban or rural area with codes 1-, urban, and 2-rural.
• Sex of the household head: This was categorized into a binary variable, where 1 was coded as mother and 0 as father.
• Education level of a teenager: this variable represents the highest level of education attained by the child's mother. It was categorized into three groups: no education, primary, secondary, and higher.
• Age at first birth (years): We categorized the patients into two groups: less than 15 years old and 15 to 19 years old.
• Literacy: This was categorized into two categories: able to read coded as 0 and not able to read coded as 1, and this is supported by other scientific literature.
• Religion: We categorized them into 3 categories: Christians, Muslims, and others (denominations).

Information access variables:

• Frequency of newspaper reading: This is a dichotomized variable recorded as yes (1) for those who access and no (0) for those who do not access or can read newspapers.
• Frequency of listening to a radio: This dichotomized variable recorded as yes (1) for those who access and no (0) for those who do not access or can listen to the radio.
• Frequency of watching television: This dichotomized variable recorded as yes (1) for those who access and no (0) for those who do not access or can watch TV.

eproductive health variables:

• Knowledge of family method: It was recorded as yes to teenagers who know FP methods and no to teenagers with no knowledge of the methods which is dichotomous as well.
• Knowledge of the ovulatory cycle: It was recorded as yes to teenagers who knew the ovulatory cycle and no knowledge of the ovulatory cycle, which is also dichotomous.

Ethical consideration: This is a secondary data analysis of the 2010-2020 Rwanda demographic and health survey. Therefore, no ethical approval was required because the principal investigator registered and requested access to data from the DHS online archive, which received approval for access and downloaded identified DHS data files. However, before primary data collection, the Rwanda National Institute of Statistics required an approval letter from the Rwanda National Ethics Committee.

The prevalence of teenage pregnancy in Rwanda from 2010 to 2020

Out of the total number of teenage pregnancies from 2010 to 2020, figure 2 data reveal that 180 (6.1%) were for 2010, 199 (7.3%) were for 2015, and 174 (5.2%) were for 2020.

Figure 2: Shows the trends of teenage pregnancy in Rwanda from 2010 to 2020 (n = 553).
Source: Primary author’s compilation.

Trends and proportions of teenage pregnancy

The findings in (Table 1) show the trend distribution of teenage pregnancies in Rwanda in of 2010, 2015 and 2020. According to the results, Eastern and Southern provinces showed a persistently high number of teenage pregnancies throughout the 2010, 2015 and 2020 DHS data, whereby the East had 56(30.4%) in 2010 and 67(38%) in 2020, while the South had 31(17%) and 39(22%) in 2020. Consistent with these findings, we observed that the majority of teenage pregnancies were from poor families (poorest and poor wealth index), via a sequence of study trends. The prevalence of poor families was 84(45%) in 2015, 91(44.5%) in 2015 and 81(46%) in 2020. Lastly, more than 50% of teenagers with teenage pregnancies had a primary level of education, and a minimal number had no education (Table 1).

Factors associated with teenage pregnancy in Rwanda

The results of (Table 2) show a chi-square test analysis to check the association between household characteristics and sociodemographic characteristics with teenage pregnancies in Rwanda. The proportion of teenage pregnancies in the eastern and southern provinces at 190(8.2%) and 107(5.0%), respectively, showed higher teenage pregnancies and were significantly associated with teenage pregnancies (p = 0.044). Teenage pregnancies appeared more frequently in teens who only attended primary school than in the groups with 415(7.7%) and were significantly associated (p < 0.001). Teenage pregnancies were significantly higher in poor households 255(16.6%) than in the richest ones (95 (4.2%) at (p < 0.001). The results further showed that 480(6.9) who experienced teenage pregnancies had access to listen to and watch the media and 85(4.1%) did not watch, and these showed a significant association at p < 0.001. Lastly, dependent variables such as knowledge of contraceptive methods, sexually active unmarried women, literacy status, and size of household members in the household showed a significant association with teenage pregnancies (p < 0.05) (Table 2).

Factors associated

With teenage pregnancy in Rwanda: The results in table 3 show the factors associated with teenage pregnancy: City of Kigali and East province show increased odds of having teenage pregnancies at (AOR: 2.06:95% CI:1.28-3.31) and (AOR: 1.55:95% CI: 1.078,2.24) respectively. Considering the level of education versus teenage pregnancy, teenagers with no education are more likely to have teenage pregnancies at (AOR: 2.9:95% CI: 1.22-6.89) followed by those in the primary level of education (AOR: 1.67:95% CI: 1.25-2.24) than teenagers who reached secondary or university. Households with the poorest wealth index are more likely to have teenage pregnancies at (AOR: 2.02:95% CI: 1.27,3.12). Results show that teenagers who don’t access social media (Television and watching TV) have higher odds of getting teenage pregnancies than those who have access to social media (AOR: 2.03:95% CI: 1.41,2.91). Results again show that teenagers with knowledge of the method have higher odds of getting teenage pregnancies than teenagers who don’t know (AOR: 8.7:95% CI: 3.34-23.0). Sexually active unmarried women/girls in range of teenage age group have higher odds of getting teenage pregnancies (AOR: 3.5:95% CI: 1.58-7.78) than the group who were not sexually active. Lastly, divided groups of the size of household members all show no likelihood of getting teenage pregnancies (AOR: < 1: with 95%CI in range) not crossing one (Table 3).

Teenage pregnancy is considered a burden in sub-Saharan Africa, and it results in negative health consequences, such as mothers experiencing higher rates of postpartum depression and being less likely to start breastfeeding, children being more likely to be delivered preterm, with lower birth weight babies, and higher neonatal mortality [9,10]. The study highlighted the information on the trend and prevalence of teenage pregnancies simultaneously with the factors associated with it by the level of education, wealth index, region, media access and use, literacy level, knowledge of the contraceptive methods, and sexually active unmarried women, which played a paramount role in responding to the study objectives.

During the analysis, the study found that the prevalence of teenage pregnancies in Rwanda was 6.1 in 2010,7.3 in 2014/2015 and 5.2 in 2019/2020, and we can see fluctuations in prevalence with a minimal decline and increase. The above findings are comparable with DHS data and the UNFPA report of 2019 on teenage pregnancies: in 2016, Uganda had 25%, in 2016/2017 Burundi had 26%, in 2013/2014 DRC had 24%, while in 2014, Kenya accounted for 18% [11]. This study showed that having no education or primary education is associated with teenage pregnancy. These results are comparable to those of other studies conducted in African countries [12,13]. Women may postpone marriage while they are in school, and they may also have better access to knowledge about sexual and reproductive health, making them more likely to make informed decisions and less likely to become pregnant [14]. However, women who become pregnant before finishing secondary school may be unable to finish their schooling because of their pregnancy, and it was again found that education opens teenagers to access information either on sexual reproductive health or others in line with capacity building [15]. The above elaboration on access to information again reflects our findings, where we found that teenagers who do not have access to social media (watching television and listening to radio) were associated with teenage pregnancies.

Further analysis showed that the poorest economic status/wealth index is associated with teenage pregnancy, which is consistent with other study findings [16-18]. When developing initiatives, economic status should always be considered because it affects access to healthcare and educational opportunities and can be integrated into possible policy implementation protocols. However, in Rwanda, many young people are jobless and monetarily dependent on their parents [19]. The study results showed that the odds of teenagers with knowledge of contraceptives and those who use contraceptive methods are more associated with teenage pregnancy than their counterparts. However, the scientific literature has shown that, to some extent, teenagers use contraceptive methods after getting their first birth and others acquire knowledge but lack access to contraceptives due to multifactorial reasons such as government policies, culture, and beliefs [20,21]. Additionally, even though increasing teenagers' access to contraceptives is successful in preventing unwanted pregnancies, many teenagers still lack access to a reliable source of contraceptives [22-25].

The study showed that Kigali and the Eastern provinces of Rwanda are the most prone to a high risk of teenage pregnancy. The above findings are comparable with those of other studies, such as the systematic review studies conducted in Uganda, where the occurrence of high teen pregnancies was regional. It was again found that due to programs implemented against teenage pregnancies, an implementation plan is not achieved in an equal magnitude in a timely manner, which leads to discrepancies in case prevalence [26,27]. The results revealed that sexually active unmarried women were positively associated with teenage pregnancy. The obtained results are consistent with numerous studies and program reports where they iterated that the majority of sexually active women under the age of 15 to 19 years tend to have unintended or teenage pregnancies [28,29]. However, household size of the family was found to be protective against teenage pregnancy outcomes. This means that households, either small or large, are not a problem with the occurrence of teenage pregnancies. The above findings are not consistent with the study conducted in Rwanda on risk factors associated with teenage pregnancy in 2014, where small household size was associated with teenage pregnancies [8].

Before data analysis, data management was maximized to avoid overestimation or underestimation of the estimates used, and the sample was sufficient for decision-making purposes after predicting associations. It is also important to consider the study's shortcomings when interpreting the results. This research was limited to the analysis of the secondary dataset because it was unable to examine all variables that the DHS did not collect, which might be related to teen pregnancies. Qualitative research may help us gain a better grasp of other aspects of community-level beliefs, attitudes, and practices as well as how they affect teenage pregnancies. Additionally, conducting an analytical study showing trends in the key risk factors associated with teenage pregnancies each year will explain the periodic changes in the factors associated with teenage pregnancy in Rwanda.

The study results show that teenage pregnancy in Rwanda is strongly stimulated by key factors, such as poverty, lack of sufficient accessibility to sexual reproductive health services, and lack of education. a). This study, however, suggests that policymakers should consider programs to keep girls in school, at least up to the secondary level, when developing programs and policies to address teen pregnancies. Additionally, programs for sexual and reproductive health should not just stress abstinence; that is, teenagers can make better decisions if they have access to knowledge about reproductive health. Furthermore, it is important to promote expanding young people's access to a variety of effective reproductive options. b). There is a need to revise and re-structure an implementable and favorable model by integrated sectors like the Ministry of Health, Ministry of Local Government, and Ministry of Education facilitating education overall with much effort at the poor communities where there are many poor families and cultural beliefs. c). There is a need to explore the best way in which social media can be used to disseminate health information regarding sexual reproductive services which can be done by the Ministry of Health and its implementing partners.

1. World Health Organization. World Health Organization. Teenage Pregnancy. 2021.
2. Mezmur H, Assefa N, Alemayehu T. Teenage Pregnancy and Its Associated Factors in Eastern Ethiopia: A Community-Based Study. Int J Womens Health. 2021 Feb 26;13:267-278. doi: 10.2147/IJWH.S287715. PMID: 33664597; PMCID: PMC7924244.
3. Sedgh G, Finer LB, Bankole A, Eilers MA, Singh S. Adolescent pregnancy, birth, and abortion rates across countries: levels and recent trends. J Adolesc Health. 2015 Feb;56(2):223-30. doi: 10.1016/j.jadohealth.2014.09.007. PMID: 25620306; PMCID: PMC4852976.
4. World Health Organization, World Health Organization. Adolescent Pregnancies. 2022.
5. Maharaj NR. Adolescent pregnancy in sub-Saharan Africa - a cause for concern. Front Reprod Health. 2022 Dec 2;4:984303. doi: 10.3389/frph.2022.984303. PMID: 36531444; PMCID: PMC9755883.
6. Alukagberie ME, Elmusharaf K, Ibra him N, Poix S. Factors associated with adolescent pregnancy and public health interventions to address in Nigeria: a scoping review. Reprod Health. 2023 Jun 24;20(1):95. doi: 10.1186/s12978-023-01629-5. PMID: 37355659; PMCID: PMC10290377.
7. Hakizimana D, Logan J, Wong R. Risk factors for pregnancies among females age 15 to 19 in Rwanda: A secondary data analysis of the 2014/2015 Rwanda Demographic and Health Survey (RDHS). Journal of Management and Strategy. 2019;10:49. doi: 10.5430/jms.v10n2p49.
8. Kassa GM, Arowojolu AO, Odukogbe AA, Yalew AW. Prevalence and determinants of adolescent pregnancy in Africa: a systematic review and Meta-analysis. Reprod Health. 2018 Nov 29;15(1):195. doi: 10.1186/s12978-018-0640-2. PMID: 30497509; PMCID: PMC6267053.
9. Uwizeye D, Muhayiteto R, Kantarama E, Wiehler S, Murangwa Y. Prevalence of teenage pregnancy and the associated contextual correlates in Rwanda. Heliyon. 2020;6(10):e05037. doi: 10.1016/j.heliyon.2020.e05037.
10. Kingston D, Heaman M, Fell D, Chalmers B, Maternity Experiences Study Group of the Canadian Perinatal Surveillance System, Public Health Agency of Canada. Comparison of adolescent, young adult, and adult women’s maternity experiences and practices. Pediatrics. 2012;129: e1228-1237. doi: 10.1542/peds.2011-1447. Cited: in: PMID: 22529278.
11. Adolescent Pregnancy UNFPA Rwanda. 2019.
12. Wall-Wieler E, Roos LL, Nickel NC. Teenage pregnancy: the impact of maternal adolescent childbearing and older sister's teenage pregnancy on a younger sister. BMC Pregnancy Childbirth. 2016 May 25;16(1):120. doi: 10.1186/s12884-016-0911-2. PMID: 27225972; PMCID: PMC4880827.
13. Odimegwu C, Mkwananzi S. Factors Associated with Teen Pregnancy in sub-Saharan Africa: A Multi-Country Cross-Sectional Study. Afr J Reprod Health. 2016 Sep;20(3):94-107. doi: 10.29063/ajrh2016/v20i3.14. PMID: 29553199.
14. Ahinkorah BO, Hagan JE, Seidu A-A, Sambah F, Adoboi F, Schack T, Budu E. Female adolescents’ reproductive health decision-making capacity and contraceptive use in sub-Saharan Africa: What does the future hold? PLoS One. 2020;15: e0235601. doi: 10.1371/journal.pone.0235601. Cited: in:: PMID: 32649697.
15. Sychareun V, Vongxay V, Houaboun S, Thammavongsa V, Phummavongsa P, Chaleunvong K, Durham J. Determinants of adolescent pregnancy and access to reproductive and sexual health services for married and unmarried adolescents in rural Lao PDR: a qualitative study. BMC Pregnancy Childbirth. 2018 Jun 8;18(1):219. doi: 10.1186/s12884-018-1859-1. PMID: 29884139; PMCID: PMC5994100.
16. Francois K. Socio-economic factors associated with teenage pregnancy in Rwanda: A secondary analysis of Rwanda Demographic and Health Survey data from 2014-2015.
17. Chirwa GC, Mazalale J, Likupe G, Nkhoma D, Chiwaula L, Chintsanya J. An evolution of socioeconomic-related inequality in teenage pregnancy and childbearing in Malawi. PLoS One. 2019;14: e0225374. doi: 10.1371/journal.pone.0225374. Cited: in: : PMID: 31747437
18. Neal SE, Chandra-Mouli V, Chou D. Adolescent first births in East Africa: disaggregating characteristics, trends and determinants. Reprod Health. 2015 Feb 19;12:13. doi: 10.1186/1742-4755-12-13. PMID: 25971731; PMCID: PMC4429933.
19. Africa Development Bank. Analysis of Gender and Youth Employment in Rwanda.
20. Christofides NJ, Jewkes RK, Dunkle KL, McCarty F, Shai NJ, Nduna M, Sterk C. Risk factors for unplanned and unwanted teenage pregnancies occurring over two years of follow-up among a cohort of young South African women. Global Health Action. 2014;7:23719. doi: 10.3402/gha.v7.23719. Cited: in: : PMID: 28672659.
21. Closson K, Dietrich JJ, Beksinska M, Gibbs A, Hornschuh S, Smith T, Smit J, Gray G, Ndung'u T, Brockman M, Kaida A. Measuring sexual relationship power equity among young women and young men South Africa: Implications for gender-transformative programming. PLoS One. 2019 Sep 25;14(9):e0221554. doi: 10.1371/journal.pone.0221554. PMID: 31553723; PMCID: PMC6760831.
22. Neption by adolescents: What progress has been made, what lessons have been learnt, and what are the implications for action? Best Pract Res Clin Obstet Gynaecol. 2020 Jul;66:107-118. doi: 10.1016/j.bpobgyn.2020.04.003. Epub 2020 Apr 24. PMID: 32527659; PMCID: PMC7438971.
23. Chandra-Mouli V, McCarraher DR, Phillips SJ, Williamson NE, Hainsworth G. Contraception for adolescents in low and middle income countries: needs, barriers, and access. Reprod Health. 2014 Jan 2;11(1):1. doi: 10.1186/1742-4755-11-1. PMID: 24383405; PMCID: PMC3882494.
24. Kawuki J, Gatasi G, Sserwanja Q, Mukunya D, Musaba MW. Utilization of modern contraceptives by sexually active adolescent girls in Rwanda: a nationwide cross-sectional study. BMC Womens Health. 2022; 22:369. doi: 10.1186/s12905-022-01956-y. Cited: in:: PMID: 36068524.
25. Schwandt H, Boulware A, Corey J, Herrera A, Hudler E, Imbabazi C, King I, Linus J, Manzi I, Merritt M, Mezier L, Miller A, Morris H, Musemakweli D, Musekura U, Mutuyimana D, Ntakarutimana C, Patel N, Scanteianu A, Shemeza BE, Sterling-Donaldson G, Umutoni C, Uwera L, Zeiler M, Feinberg S. "She is courageous because she does not care what people think about her…": attitudes toward adolescent contraception use among Rwandan family planning providers and adult female modern contraceptive users. Reprod Health. 2022 Nov 4;19(1):204. doi: 10.1186/s12978-022-01517-4. PMID: 36333785; PMCID: PMC9636625.
26. Ahinkorah BO, Kang M, Perry L, Brooks F, Hayen A. Prevalence of first adolescent pregnancy and its associated factors in sub-Saharan Africa: A multi-country analysis. PLoS One. 2021 Feb 4;16(2):e0246308. doi: 10.1371/journal.pone.0246308. PMID: 33539394; PMCID: PMC7861528.
27. Eyeberu A, Getachew T, Sertsu A, Sisay M, Baye Y, Debella A, Alemu A. Teenage pregnancy and its predictors in Africa: A systematic review and meta-analysis. Int J Health Sci (Qassim). 2022; 16:47–60. Cited: in: PMID: 36475034.
28. Ikamari L, Towett R. Sexual initiation and contraceptive use among female adolescents in Kenya. African Journal of Health Sciences. 2008;14. doi: 10.4314/ajhs.v14i1.30841.
29. Adeneye A. Factors associated with unplanned pregnancy among unmarried adolescents in selected communities of Ogun state, Nigeria. Arch Prev Med. 2017;2:001-009. doi: 10.17352/apm.000005.