Melesse et al. Reprod Health 2021, 18(Suppl 1):117 https://doi.org/10.1186/s12978-021-01125-8 RESEARCH Open Access Inequalities in early marriage, childbearing and sexual debut among adolescents in sub-Saharan Africa Dessalegn Y. Melesse1* , Réka M. Cane2, Aveneni Mangombe3, Macellina Y. Ijadunola4, Adom Manu5, Eniola Bamgboye6, Abdu Mohiddin7, Rornald M. Kananura8, Elsie Akwara9, Elsabé du Plessis1, Yohannes D. Wado10, Martin K. Mutua10, Wubegzier Mekonnen11, Cheikh M. Faye12, Sarah Neal13 and Ties Boerma1 Abstract Background: Adolescent sexual and reproductive health (ASRH) is a major public health concern in sub-Saharan Africa (SSA). However, inequalities in ASRH have received less attention than many other public health priority areas, in part due to limited data. In this study, we examine inequalities in key ASRH indicators. Methods: We analyzed national household surveys from 37 countries in SSA, conducted during 1990–2018, to exam- ine trends and inequalities in adolescent behaviors related to early marriage, childbearing and sexual debut among adolescents using data from respondents 15–24 years. Survival analyses were conducted on each survey to obtain estimates for the ASRH indicators. Multilevel linear regression modelling was used to obtain estimates for 2000 and 2015 in four subregions of SSA for all indicators, disaggregated by sex, age, household wealth, urban–rural residence and educational status (primary or less versus secondary or higher education). Results: In 2015, 28% of adolescent girls in SSA were married before age 18, declined at an average annual rate of 1.5% during 2000–2015, while 47% of girls gave birth before age 20, declining at 0.6% per year. Child marriage was rare for boys (2.5%). About 54% and 43% of girls and boys, respectively, had their sexual debut before 18. The declines were greater for the indicators of early adolescence (10–14 years). Large differences in marriage and childbearing were observed between adolescent girls from rural versus urban areas and the poorest versus richest households, with much greater inequalities observed in West and Central Africa where the prevalence was highest. The urban– rural and wealth-related inequalities remained stagnant or widened during 2000–2015, as the decline was relatively slower among rural and the poorest compared to urban and the richest girls. The prevalence of the ASRH indicators did not decline or increase in either education categories. Conclusion: Early marriage, childbearing and sexual debut declined in SSA but the 2015 levels were still high, especially in Central and West Africa, and inequalities persisted or became larger. In particular, rural, less educated and poorest adolescent girls continued to face higher ASRH risks and vulnerabilities. Greater attention to disparities in ASRH is needed for better targeting of interventions and monitoring of progress. *Correspondence: Dessalegn.Melesse@umanitoba.ca 1 Countdown To 2030 for Women’s, Children’s and Adolescents’ Health, Institute for Global Public Health, University of Manitoba, R070 Med Rehab Building, 771 McDermot Avenue, Winnipeg, MB R3E 0T6, Canada Full list of author information is available at the end of the article © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. 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Reprod Health 2021, 18(Suppl 1):117 Page 2 of 15 Keywords: Adolescents, Girls, Boys, Child marriage, Childbearing, Sexual debut, Sub-Saharan Africa, Inequalities, Trends and patterns, Geographical disparities Background and present challenges to achieving the SDG equity The global adolescent population (10–19) is estimated to agenda. have reached 1.3 billion (49%: 15–19 years old) in 2020, This paper examines three dimensions of inequalities in of whom over 235 million (46%: 15–19  years old) live ASRH indicators, child marriage, childbearing and sexual in sub-Saharan Africa (SSA), accounting for 23% of the debut, in SSA as a whole and in four geographic subre- region’s population [1]. Healthy adolescence is critical for gions during 2000–2015 using national surveys con- the achievement of the Sustainable Development Goals ducted between 1990 and 2018. We use the World Health (SDGs), including those related to health, education, Organization (WHO) definition of adolescents as aged poverty, security, and reduction of inequalities [2, 3], in between 10 and 19 years and those between 10–14 and particular adolescent sexual and reproductive health 15–19 years of age hereafter are referred as younger and (ASRH). older adolescents, respectively [21]. ASRH risk behaviours are associated with unintended pregnancies, early sexual initiation (often coerced), early Methods marriage, HIV and other sexually transmitted infections The data used in this study were drawn from nationally (STIs)[4, 5]. Early marriage disproportionately affects representative Demographic and Health Surveys (DHS) girls, while unintended pregnancy often leads to school and AIDS Indicator Surveys, which collect health and dropout and compromises educational advancement and socio-demographic information using the same survey human capital development [6–8]. Early childbearing is methodology [22]. Data for adolescents and young peo- also associated with increased health risks for mothers ple (15–24 years at time of survey) were extracted from and newborns [9]. Furthermore, premarital and extra- 129 national surveys conducted since 1990 in 37 coun- marital sex carry risks of unintended pregnancy, which tries in SSA, of which 32 countries had conducted at least may lead to unsafe abortion, and contracting STIs includ- two surveys and 33 at least one survey during 2010–2018 ing HIV. Many of these risks are greatest among younger (Additional file 1: Appendix Table S1). adolescents, yet most analyses fail to recognise and The key indicators were first marriage or consensual report events for this age group [9–12]. union (or cohabitation as if married, hereafter simply Inequalities in sexual and reproductive health persist as called marriage) before age 18, often referred to as child existing reviews document higher rates of early marriage marriage[23]; childbirth before age 20 which is related and childbearing among adolescents who are poorer, less to the SDG indicator of adolescent birth rate[24]; and educated and from rural areas [13, 14]. Recent evidence sexual debut before age 18. We also applied 15 years as shows that early marriage and childbearing among ado- an age cut-off for all three indicators to gain insight into lescents in SSA has declined, most notably among urban the trends and inequalities during early adolescence and better-educated populations [13–16]. Age at sexual (10–14 years). debut among adolescents in SSA has been increasing, We used data on reported current status on marriage, with some studies showing a relatively lower proportion childbirth and sexual debut by age of the respondent (e.g., of boys and girls reportedly initiating sexual intercourse are you currently married) and recalled age at first event before age 15 [17–19]. (e.g., age at first childbirth) from respondents 15–24 years A better understanding of ASRH challenges in SSA, to obtain a sufficiently large sample. To account for cen- based on disaggregated data for critical adolescent transi- soring we used Kaplan–Meier survival analysis in which tions, is crucial to strengthen policies and programs tar- the survival time to experiencing each event before a geting adolescent needs14, 16, 20. Much of our current specified age was obtained from a cumulated single-year knowledge is based on analyses of aggregate data and on percent distribution from the product-limit estimates of single-topics. However, the key life events during adoles- the survival curve (sts function in the statistical package cence, such as marriage, childbearing and sexual debut, of Stata version 15[25]). We derived our indicator values are intertwined and need to be systematically synthe- from the survival curves. Child marriage and childbear- sized as such for greater understanding of ASRH-related ing were measured by the cumulative probability of being issues. The lack of disaggregated data about adolescents married before the age of 18 years and having first birth implies that their specific needs and vulnerabilities before the age of 20 years, respectively. The distribution remain largely invisible to policy and program designers, of timing of first sex was estimated in the same way as M elesse et al. Reprod Health 2021, 18(Suppl 1):117 Page 3 of 15 age at first marriage by age 18 years. A similar approach activity before age 18 in SSA decreased from 61 to 54% was used to explore the distribution of the three key for girls and from 53 to 43% for boys during 2000–2015 life events occurring before age 15 years. For details see (AARC: − 0.7% and − 1.3% respectively). Additional file 1. There are marked differences within SSA. Marriage Gender-specific disaggregated analyses were conducted before age 18 among girls was most common in West by urban–rural residence, education status and socioeco- and Central Africa (35% and 29% respectively in 2015), nomic status for SSA. In this paper, we present the results and least prevalent in Southern Africa (13%). Adoles- for girls and boys but limited the disaggregated analy- cent childbearing exceeded 40% in all subregions in sis to girls given the low prevalence of marriage among 2015 and was most common in Central (51%) and West adolescent boys. Educational status was categorized into Africa (47%). Sexual debut before age 18 was also more two groups as primary or less education and secondary common among girls in Central and West Africa (66% or higher education, based on highest completed level and 58% respectively) than in Eastern and Southern of education at time of the interview. We computed and Africa (47% in both). Among boys, marriage before age used wealth tertiles rather than the conventional wealth 18 occurred in less than 5% of cases in all subregions quintiles from the standard DHS dataset index scores and was decreasing, while sex before age 18 was more [26] to reduce sampling errors. common in Central and West Africa (58% in both) and Using the estimates obtained from survival analysis, Southern Africa (increasing to 49% in 2015). multilevel mixed-effects linear regression analyses were The subregional patterns conceal considerable vari- performed on year of survey to derive crude estimates of ability within the subregions. Figure 2 shows the prev- average trends for the key indicators for SSA and subre- alence of child marriage and childbearing by country, gions. The multilevel data used for analysis is character- based on the most recent national surveys. In West ized by a hierarchical or multilevel structure, where we Africa, Mali, Niger, Burkina Faso and Guinea stand out have countries—each with multiple date points meas- with higher prevalence of early marriage and childbear- ured from 1990 to 2018—nested within the sub-regions ing among adolescents, while Ghana is at the lower end and sub-regions nested within the bigger region of SSA. in both indicators. In Central Africa, Chad and Came- Informed by the United Nations Population Division roon had a more than threefold difference in both child subregional classification [27], countries were grouped marriage and childbearing among adolescents. In East- into four subregions (Central, West, Eastern and South- ern and Southern Africa, Mozambique and Zimbabwe ern Africa) of SSA (Additional file 1: Appendix Table S1). are outliers on the higher side of both indicators, while In order to obtain better estimates for the period 2000– Kenya (child marriage) and Ethiopia (childbearing) are 2015, a priori knowledge obtained from pre-2000 survey on the lower side. data points were used where available. The use of sur- Regarding early adolescence, the prevalence of mar- veys prior to 2000 provided a more accurate estimate to riage, childbearing and sexual debut among girls before measure the trends compared to using only surveys after age 15 were estimated at 7, 3 and 12% respectively, in 2000 or two end data points on year 2000 and 2015. We SSA (Table 1). For boys, only estimates for sexual debut computed confidence intervals for all estimates in 2000 could be made (marriage was rare), which was similar and 2015 where relevant, tested for statistical significance to that for girls in 2015 (12%). All indicators declined of changes over time using a standard approach [28] and between 2000 and 2015 at an average pace of 1.6–2.3% used the regression coefficient estimates to obtain the per year, which was faster than the overall ASRH average annual rate of change (AARC). These estimates indicators. of confidence intervals and p-values are available for ref- The subregional patterns among younger adolescents erence in respective tables. Further details are provided are similar to the indicators that include older adolescent in the Additional file 1. behaviours. In 2015, 10% and 9% of younger adolescent girls in West and Central Africa, were married before age Results 15, compared to 6.0% and 1.4% in Eastern and Southern General levels and trends Africa, respectively. Nearly 4% of girls in Central Africa In 2015, 28% of adolescent girls in SSA were married had their first birth before age 15 in 2015, compared to before age 18, declining from 35% in 2000 at an average the 2.5% in Eastern Africa and 1% in Southern Africa. All annual rate of 1.4% (Table  1 and Fig.  1a). Fewer boys four regions showed declines during 2000–2015, most (2.5%) were married by age 18 in 2015, a decline from prominently for sexual debut before age 15 (both girls 4.4% in 2000 at an average annual rate of 3.6%. Child- and boys) and marriage (girls). The average annual rate of bearing before age 20 declined at a rate of 0.6% per decline was greater in the West and Central Africa than year in recent decades to reach 46.5% in 2015. Sexual in the other subregions. Melesse et al. Reprod Health 2021, 18(Suppl 1):117 Page 4 of 15 Table 1 Levels and trends of child marriage, childbearing and sexual debut among adolescents by sex and sub-region in Sub-Saharan Africa, based on national surveys 1990–2018 in 37 countries, sub-Saharan Africa, in 2000 and 2015 (in parenthesis 95% confidence intervals) Before age 18 (20 for childbearing) Before age 15 2000 2015 AARC p 2000 2015 AARC p Sub-Saharan Africa Marriage F 34.8 [25.5, 44.2] 28.0 [18.6, 37.4] − 1.4 0.32 9.4 [5.9, 12.9] 6.7 [3.1, 10.2] − 2.3 0.29 M 4.4 [3.4, 5.3] 2.5 [1.0, 4.1] − 3.6 0.04 *** *** *** Childbearing F 50.9 [47.0, 54.8] 46.5 [42.5, 50.5] − 0.6 0.12 3.8 [2.5, 5.0] 2.9[1.7, 4.2] − 1.6 0.38 Sexual debut F 60.7 [51.7, 69.7] 54.3 [45.2, 63.3] − 0.7 0.33 16.7 [11.8, 21.7] 12.3 [7.3, 17.3] − 2.0 0.22 M 52.7 [43.5, 61.9] 42.8 [33.5, 52.1] − 1.3 < 0.001 16.1 [12.0, 20.3] 11.6 [7.4, 15.8] − 2.2 0.13 Central Africa Marriage F 42.6 [34.8, 50.3] 32.4 [24.4, 40.4] − 1.8 0.07 12.0 [7.9, 16.2] 8.6 [4.3, 12.9] − 2.2 0.27 M 5.1 [3.5, 6.7] 3.9 [0.8, 7.0] − 1.7 0.51 *** *** *** Childbearing F 57.8 [52.9, 62.6] 51.4 [46.0, 56.7] − 0.7 0.08 4.8 [3.3, 6.4] 4.2 [2.4, 5.9] − 1.0 0.59 Sexual debut F 74.1 [68.7, 79.5] 65.5 [59.7, 71.2] − 0.8 0.03 22.7 [14.8, 30.6] 17.4 [9.4, 25.4] − 1.8 0.36 M 66.8 [56.3, 77.3] 57.6 [47, 68.2] − 0.9 < 0.01 23.2 [19.9, 26.4] 17.6 [14.1, 21.2] − 1.8 0.12 West Africa Marriage F 43.5 [35.5, 51.6] 35.0 [26.8, 43.1] − 1.4 0.14 13.1 [9.0, 17.3] 9.8 [5.5, 14.0] − 2.0 0.27 M 2.1 [1.6, 2.5] 1.8 [0.9, 2.7] − 0.9 0.61 *** *** *** Childbearing F 52.4 [45.9, 58.8] 46.9 [40.4, 53.4] − 0.7 0.24 5.0 [3.7, 6.3] 3.9 [2.5, 5.3] − 1.7 0.25 Sexual debut F 66.2 [58.1, 74.3] 57.8 [49.6, 66.0] − 0.9 0.15 20 [16.1, 23.9] 14.6 [10.7, 18.6] − 4.0 0.06 M 44.2 [36.9, 51.5] 29.6 [22.2, 37.0] − 2.6 < 0.001 11.3 [8.9, 13.7] 6.2 [3.7, 8.7] − 2.1 < 0.001 Eastern Africa Marriage F 34.9 [27.3, 42.5] 29.4 [21.3, 37.4] − 1.1 0.33 8.4 [5.5, 11.2] 6.0 [3.1, 9.2] − 2.2 0.27 M 5.5 [3.4, 7.5] 4.8 [2.1, 7.6] − 0.8 0.73 *** *** *** Childbearing F 48.4 [39.6, 57.2] 44.4 [35.5, 53.4] − 0.5 0.54 3.1 [2.1, 4.1] 2.5 [1.5, 3.6] − 1.3 0.48 Sexual debut F 51.8 [40.3, 63.2] 46.9 [35.5, 58.4] − 0.6 0.57 15.0 [11.1, 18.8] 11.2 [7.2, 15.3] − 1.9 0.19 M 48.4 [38.5, 58.3] 41.1 [31.1, 51.1] − 1.0 < 0.001 16.7 [12.6, 20.9] 12.0 [7.7, 16.3] − 2.2 0.12 Southern Africa Marriage F 14.6 [6.5, 22.7] 13.2 [5, 21.4] − 0.6 0.83 1.7 [0.9, 2.6] 1.4 [0.6, 2.3] − 1.2 0.65 M 1.3 [1.2, 1.4] 1.0 [0.7, 1.2] − 1.8 0.01 *** *** *** Childbearing F 42.5 [37.6, 47.4] 41.3 [36.1, 46.4] − 0.1 0.76 1.5 [1.1, 1.8] 1.0 [0.5, 1.4] − 2.8 0.08 Sexual debut F 47.9 [42.6, 53.2] 46.7 [40.5, 52.9] − 0.1 0.77 7.3 [6.1, 8.4] 5.6 [4.4, 6.7] − 1.8 0.04 M 46.7 [31.4, 62.0] 49.3 [32.3, 66.3] 0.3 < 0.01 13.3 [6.7, 19.8] 12.0 [6.0, 18.1] − 0.6 0.80 AARC average annual rate of change (in percentage), and the minus sign indicates a declining trend; p-values reflect statistical significance of the absolute difference in proportion between the year 2000 and 2015; M male, F female. ***Data were not analysed due to small sample size M elesse et al. Reprod Health 2021, 18(Suppl 1):117 Page 5 of 15 Fig. 1 a–d Percentages of child marriage (age 18), childbearing (age 20) and sexual debut (age 18) among adolescents in sub-Saharan Africa, disaggregated by sex, and by residence and socioeconomic characteristics for girls, based on national surveys in 37 countries conducted during 1990–2018, 37 countries, sub-Saharan Africa Melesse et al. Reprod Health 2021, 18(Suppl 1):117 Page 6 of 15 a1 Marriage before age 18 a2 Marriage before age 15 b1 Childbearing before age 20 b2 Childbearing before age 15 c1 Sexual debut before age 18 c2 Sexual debut before age 15 Fig. 2 Geographical inequalities in early marriage (age 18 and 15), childbearing (age 15 and 20) and sexual debut (age 18 and 15) among adolescent girls in sub-Saharan Africa in 2015, based on national surveys conducted since 2010, sub-Saharan Africa Urban–rural inequalities overtime. The average annual reductions in marriage and The prevalence of marriage before age 18 was almost births were higher for urban than rural adolescent girls. twice as high for rural than urban girls (35% and 18% The subregional patterns for urban–rural residence respectively). Childbearing before age 20 was also much were similar to the differences observed in SSA as a more common (56% and 34%, respectively), as was sexual whole with rural adolescent girls at higher risk for all debut before age 18 (61% and 47% respectively). (Figs. 1b, three events. In all four subregions and for all three indi- 3 and Table 2). Although the rates declined during 2000– cators of adolescents, the urban AARC was greater than 2015, the absolute urban–rural differences as well as rural the rural AARC. Similarly, the absolute urban–rural dif- to urban ratios remained either stagnant or increased ference observed in year 2000 and 2015 between urban M elesse et al. Reprod Health 2021, 18(Suppl 1):117 Page 7 of 15 Fig. 3 Trends in child marriage, childbearing and sexual debut among adolescent girls by subregion, by urban–rural residence, based on national surveys in 37 countries conducted during 1990–2018, sub-Saharan Africa Melesse et al. Reprod Health 2021, 18(Suppl 1):117 Page 8 of 15 Table 2 Marriage, births and sexual debut among adolescent girls between 2000 and 2015 by urban–rural residence, education and household wealth tertile, based on national surveys 1990–2018 from 37 countries, sub-Saharan Africa (in parentheses 95% confidence intervals) Before age 18 (20 for childbearing) Before age 15 2000 2015 AARC p 2000 2015 AARC p Marriage Overall 34.8 [25.5, 44.2] 28.0 [18.6, 37.4] − 1.4 0.32 9.4 [5.9, 12.9] 6.7 [3.1, 10.2] − 2.3 0.29 Rural 41.2 [28.7, 53.8] 35.0 [22.5, 47.6] − 1.1 0.50 11.5 [6.7, 16.3] 8.7 [3.8, 13.5] − 1.9 0.43 Urban 24.9 [17.5, 32.3] 18.1 [10.6, 25.5] − 2.1 0.20 5.9 [3.5, 8.2] 3.8 [1.4, 6.2] − 2.9 0.24 None or primary 43.6 [34.8, 52.4] 43.4 [34.5, 52.3] 0.0 0.98 12.0 [7.9, 16.1] 10.9 [6.7, 15] − 0.6 0.73 Secondary + 14.7 [9.1, 20.3] 15.0 [9.4, 20.7] 0.2 0.93 2.3 [0.9, 3.7] 2.5 [1.1, 4] 0.6 0.85 Poorest (33.3%) 44.8 [32.6, 57.0] 39.8 [27.6, 52.1] − 0.8 0.59 12.7 [7.7, 17.7] 10.2 [5.2, 15.2] − 1.5 0.49 Middle (33.3%) 37.9 [27.3, 48.6] 29.9 [19.2, 40.6] − 1.6 0.30 10.2 [6.4, 14] 6.9 [3.1, 10.8] − 2.6 0.23 Richest (33.3%) 24.0 [17.8, 30.1] 15.7 [9.4, 22.0] − 2.8 0.06 5.7 [3.6, 7.7] 3.4 [1.3, 5.5] − 3.4 0.13 Childbearing Overall 50.9 [47, 54.8] 46.5 [42.5, 50.5] − 0.6 0.12 3.8 [2.5, 5.0] 2.9 [1.7, 4.2] − 1.6 0.38 Rural 58.0 [51.4, 64.7] 56.0 [49.3, 62.7] − 0.2 0.70 4.7 [2.8, 6.5] 3.7 [1.8, 5.6] − 1.5 0.50 Urban 40.7 [35.4, 46] 34.1 [28.8, 39.5] − 1.2 < 0.001 2.6 [1.8, 3.3] 2.0 [1.3, 2.8] − 1.6 0.31 None or primary 60.8 [56.4, 65.2] 63.6 [59.1, 68.2] 0.3 0.39 5.0 [3.5, 6.4] 4.8 [3.3, 6.3] − 0.2 0.90 Secondary + 30.2 [23.2, 37.3] 31.2 [24.0, 38.4] 0.2 < 0.01 1.0 [0.6, 1.5] 1.1 [0.6, 1.6] 0.5 0.81 Poorest (33.3%) 61.5 [56.7, 66.3] 61.9 [56.9, 66.8] 0.0 0.92 5.4 [3.5, 7.2] 4.6 [2.8, 6.5] − 1.0 0.59 Middle (33.3%) 54.7 [50.3, 59.2] 49.9 [45.3, 54.5] − 0.6 < 0.001 4.0 [2.6, 5.3] 3.0 [1.6, 4.4] − 1.8 0.35 Richest (33.3%) 37.8 [33.7, 41.9] 29.4 [25.1, 33.6] − 1.7 0.38 2.2 [1.5, 2.9] 1.5 [0.8, 2.2] − 2.5 0.19 Sexual debut Overall 60.8 [51.7, 69.8] 54.3 [45.3, 63.4] − 0.7 0.33 16.7 [11.8, 21.7] 12.3 [7.3, 17.3] − 2.0 0.22 Rural 65.1 [54.3, 75.9] 60.6 [49.7, 71.4] − 0.5 0.57 19.9 [13.1, 26.6] 15.4 [8.6, 22.2] − 1.7 0.36 Urban 54.7 [45.7, 63.7] 46.5 [37.4, 55.6] − 1.1 < 0.001 12.8 [8.6, 17] 8.9 [4.6, 13.1] − 2.4 0.20 None or primary 68.2 [60.3, 76.2] 67.5 [59.4, 75.5] − 0.1 0.91 21.0 [15.7, 26.3] 18.8 [13.4, 24.1] − 0.7 0.57 Secondary + 46.1 [35.6, 56.5] 44.1 [33.5, 54.6] − 0.3 < 0.001 7.9 [4.7, 11.1] 7.4 [4.2, 10.6] − 0.5 0.83 Poorest (33.3%) 67.7 [58.7, 76.6] 64.9 [55.8, 73.9] − 0.3 0.68 21.4 [15, 27.8] 17.5 [11, 23.9] − 1.4 0.40 Middle (33.3%) 63.3 [53.4, 73.3] 57.3 [47.2, 67.3] − 0.7 < 0.01 17.6 [12.4, 22.8] 12.9 [7.7, 18.1] − 2.1 0.21 Richest (33.3%) 51.8 [43.0, 60.5] 42.4 [33.6, 51.2] − 1.3 0.37 11.8 [8.1, 15.6] 7.5 [3.7, 11.3] − 3.1 0.11 AARC average annual rate of change (in percentage), and the minus sign indicates a declining trend; p-values reflect statistical significance of the absolute difference in proportion between the year 2000 and 2015. Secondary + refers to completed education level reported as secondary or higher girls and rural girls has increased for all indicators in all Wealth‑related inequalities subregions, with the exception of child marriage in West There were marked differences in ASRH indicators Africa (Additional file 1: Appendix Tables S3–6). South- between the richest and poorest households in SSA. In ern Africa recorded the slowest declines for the three 2015, nearly 40% of girls in the poorest tertile were mar- indicators. ried before age 18, and 62% had their first birth before In early adolescence (before age 15), 15% of rural girls age 20, compared to 16% and 29%, respectively, in the and 9% of urban girls in SSA had initiated sex in 2015 richest tertile (Figs. 1d,  4 and Table 2). There was little or (Table  2). Rural girls were more than twice as likely to no change in marriage and births among adolescent girls be married before age 15 than urban girls (9% and 4% in the poorest tertile during 2000–2015 (AARC: -0.8% respectively), and almost twice as likely to give birth (4% for child marriage and 0.0% for childbearing). A faster and 2% respectively). Marriage, sexual debut and, to a decline was observed among those in the richest tertile, lesser extent childbearing declined, reducing at an aver- with child marriage reducing at 2.8% and childbear- age rate of at least 1.5% per year in both rural and urban ing with 1.7% annually. Therefore, relative gaps in child girls. Declines were observed in all four subregions in marriage, adolescent birth and sexual debut between the both urban and rural girls, but the relatively faster pace of richest and poorest tertiles in SSA expanded. decline in urban girls in all three indicators was observed Similar patterns were observed across subregions with in West and Central Africa. little progress among girls in the poorest tertile. Since Melesse et al. Reprod Health 2021, 18(Suppl 1):117 Page 9 of 15 Fig. 4 Trends in child marriage, childbearing and sexual debut among adolescent girls by subregion, by household wealth tertile, based on national surveys in 37 countries conducted during 1990–2018, sub-Saharan Africa Melesse et al. Reprod Health 2021, 18(Suppl 1):117 Page 10 of 15 girls in the richest tertile made progress on all three in any of the three indicators of early adolescent behav- ASRH indicators, the gap between the poorest and rich- iours in either education group. est girls widened considerably in all four subregions. The increases of the inequalities were most pronounced in Discussion Central, Eastern and West Africa for childbearing and in We observed considerable progress in ASRH outcomes Central and West Africa for sexual debut. throughout the region of SSA, as the overall prevalence of The results for younger adolescents were similar, with child marriage, childbearing and sexual debut decreased girls from the poorest households experiencing higher during 2000–2015 for adolescent girls and boys in early prevalence levels and slower declines than those in the and late adolescent periods. However, profound geo- richest tertile of households. For instance, in the West graphical disparities within and between sub-regions still Africa subregion, marriage before age 15 declined from persistent, and are characterized by large gaps in urban– 19 to 15% among the poorest, compared to a decline rural differences and inequalities in socioeconomic char- from 7 to 4% among the richest, while childbearing acteristics. The increase and persistence of long-run declined from 7 to 6% among the poorest compared to inequalities for ASRH indicators signify the continued a decline from 3 to 2% among the richest, in 2000 and importance of ASRH as public health issue in the region. 2015, respectively. In particular, adolescent girls living in rural areas and in the poorest households report higher prevalence rates when compared with their more advantaged urban and Inequalities by education richer counterparts. The disparities in ASRH indicators for girls by education Early child marriage and childbearing before age 15 are large (Figs. 1c, 5, Table 2). In 2015, the absolute gaps have declined more markedly for younger adolescents between girls with primary or less education and those (before age 15) than in later adolescence, which can per- with secondary or higher education were 28% for child haps be attributed to multi-sectoral efforts to increase marriage, 32% for childbearing and 23% for sexual debut girls’ access to basic education as observed over recent by age 18. Among adolescent girls with primary or less decades [29–32]. Our study shows, however, that in 2015 education, 43% were married by age 18 – nearly three nearly 7% of girls in SSA still reported that they were times more than those with higher education (15%)—and married, 3% had their first birth and 12% had their first 64% had their first birth by age 20, twice as high as among sexual intercourse before the age of 15 years. This is con- girls with higher education. For marriage, the gaps by cerning as the risk of both maternal and infant mortality education were larger than the gaps by urban—rural resi- is greatest for girls aged below 15 years [9–11], and often dence or wealth tertile, but not for the other two indica- too little resources are directed towards the younger ado- tors. The trends differed from those by place of residence lescent girls [33]. and wealth. There was little or no change between 2000 Our study confirmed that the transition of ASRH is and 2015 within each of the two education categories in occurring across most SSA, though there are major dif- SSA. No average annual rate of change exceeded 0.3% for ferences between the four subregions [34–37]. In West the three indicators. and Central Africa marriage is more common among The subregional patterns were similar to the overall adolescent girls than boys and about half of the adoles- pattern for SSA. The only subregion with a decline was cent girls reported childbearing in 2015. The prevalence Central Africa where the prevalence of marriage before of child marriage in South Africa is relatively low com- age 18 reduced by 0.8% and 1.6% per year during 2000– pared to the rates reported for childbearing and sexual 2015 among those with primary or less education and debut before age 18 in other subregions. Eastern Africa secondary or more education respectively. is often in an intermediate position. Sexual debut before Girls with primary or less education are much more age 18 followed a similar pattern for girls and boys, with likely be married as well as have their first child before the exception of boys in West Africa who had the lowest the age of 15 than those with secondary or higher educa- levels of the four subregions. Studies have shown that the tion. In 2015, 11% of women 15–24 with primary or less persistence of child marriage and unplanned pregnancy education were married before age 15 and 5% of them in most parts of SSA are partly attributable to societal had their first child before age 15, compared to 2.5% and factors such as poverty, cultural norms and traditional 1% of women with higher education. This was consist- attitudes [30, 38–40]. While many countries have made ent across all subregions, with marriage and childbear- efforts to reduce child marriage, such as the adoption ing ranging from 4% in Southern Africa to 14% in Central or reform of minimum-age-at-marriage laws and anti- Africa for young women aged 15–24 with primary/no child marriage campaigns [40], our results show that education. In general, there was no evidence of a decline child marriage persists, particularly in West and Central M elesse et al. Reprod Health 2021, 18(Suppl 1):117 Page 11 of 15 Fig. 5 Trends in child marriage, childbearing and sexual debut among adolescent girls by subregion, by education status, based on national surveys in 37 countries conducted during 1990–2018, sub-Saharan Africa Melesse et al. Reprod Health 2021, 18(Suppl 1):117 Page 12 of 15 Africa, in rural settings and among the poorest segments individual [49, 50]. Early initiation of sexual intercourse of the population. Analyses such as ours, that highlight also elevates adolescents’ potential risk for unplanned where inequalities persist, may provide prevention efforts pregnancy, abortion and STIs including HIV. Girls with crucial information that will allow programs to who become pregnant or marry early are more likely to reach their intended audience. drop out of school and this in turn limits their future The greater decline in child marriage compared to opportunities. sexual debut before age 18 implies an increase in premar- The concerning increase in inequality for early mar- ital sex: a phenomenon that has been identified and dis- riage and childbearing among adolescents highlights the cussed in previous research for a number of sub-Saharan need for a multisectoral approach to improving ASRH. African countries [41]. The slower decline in childbearing Improving all girls’ access to education and implementing compared to marriage and sexual debut among adoles- gender-sensitive policies and programs that enable girls cent girls points to the inadequate access to modern con- to remain in school (particularly the poorest) will foster traceptives and other ASRH services for sexually active delayed and chosen marriage and childbearing, and is single adolescents as an issue in many countries with critical to subsequently end early marriage and births in marked socioeconomic inequalities, as shown in other the region. Keeping girls in school not only reduce their studies [37, 42, 43]. risk from HIV and other STIs and unintended pregnan- Early marriage and childbearing were much more com- cies [30, 51], it also contributes to their social, psycholog- mon in rural than urban areas and among adolescent ical and health wellbeing and brings opportunities that girls in the poorest tertile of household wealth com- could enhance their families’ socioeconomic status in the pared to the richest tertile. These gaps persisted or even future [30, 49, 50, 52, 53]. As far as current evidence is increased over time and were present in all subregions. concerned, it is important to recognize that policies aim- These adverse trends highlight that the disadvantages ing to end child marriage alone could positively impact associated with these outcomes are increasingly con- over one-third of the adolescent girls in most countries centrated within already vulnerable poor and rural girls. in SSA [49]. Unequal access to education and health services are likely contributing factors [44, 45]. To make progress towards Limitations national and international goals such as the SDGs which Our study has several limitations. We used unweighted pledge to “leaving no one behind” [46], greater attention country data for the regional and subregional regression is needed for ASRH of rural and the poorest adolescents analyses for a broad assessment of levels and trends in than is currently the case. inequalities in SSA. Weighting by population size would The findings on trends by education presented a dif- likely give a somewhat different picture of the regional ferent pattern. Similar to the urban–rural and poorest- and subregional inequalities. We did not go into detail for richest disparities girls with less education (primary or specific countries, even though there are large differences less) have earlier sexual debut, marriage and childbear- between countries within SSA and even within the sub- ing. Marriage and childbearing may be triggers to leav- regions. Country-specific analyses are needed to obtain ing school and also out of schoolgirls may be more likely deeper insights into inequalities in ASRH. This will also to be married or get pregnant [8, 39, 47, 48]. The trends allow for analysis of within country disparities in ASRH in the ASRH indicators during 2000–2015 however were which will be necessary for effective targeting of pro- either stable or increasing for both education categories, grams to improve ASRH. even though the overall trend for all girls, irrespective of The triple disaggregation of surveys for the analyses of educational status, declined for all three ASRH indica- ASRH indicators (by age, sex and socioeconomic char- tors. This can only be explained by a major shift in the acteristics), which we have presented in this paper, have proportion of girls from the lower to the higher educa- received too little attention, partly due to sample size tion category during 2000–2015. Elsewhere, it has been limitations. Some of the changes reached statistical sig- shown that this change in educational attainment is nificance at the 5% level but many did not due to such indeed the main driver of changes in the age at first mar- limitations. However, the overall picture of inequality riage, first sex and first birth [31, 38]. levels and trends that emerged from our analysis was There are grave and irreversible consequences to early coherent and consistent for the SSA as a whole and four marriage and childbirth, affecting the social, psycho- subregional level. This shows that it is possible to study logical and health wellbeing of both young women and inequalities in ASRH with DHS surveys, in spite of sam- children. Child marriage is a violation of the individu- ple size challenges. Therefore, we recommend that future al’s right to make informed choices and decisions, and survey analyses pay greater attention to inequalities by compromises opportunities and future prospects of the disaggregated analyses. M elesse et al. Reprod Health 2021, 18(Suppl 1):117 Page 13 of 15 Our dimensions of inequality have measurement Our study presents, to our knowledge, is one of the errors. Wealth (as measured using the asset index) is largest and most comprehensive assessments of inequali- recorded at time of survey, and a number of years may ties in ASRH including marriage, childbearing and sexual have elapsed between ASRH event and survey. In par- debut among adolescents in SSA. Disaggregated data on ticular, adolescent girls who were married may have adolescents are crucial to reach all adolescent girls and moved into a household with an economic status that dif- boys as part of the 2030 SDG equity agenda. The major fers from the household in which they grew up. For edu- and persistent inequalities identified in this study need to cation we used the status at the time of the survey. Some be given more attention and addressed. Our study shows respondents may still move to the higher education cat- that monitoring progress with national survey data is egory by entering secondary school after the survey, but possible. Further success in the area of ASRH requires this is likely to be a small proportion at age 15 onwards. increased political will, investment, and engagement of It should also be noted that this study is limited to adolescents in the process of designing and implemen- three ASRH indicators, each with two age cut-offs, to tation of policies and programs, with much attention assess younger and older adolescent behaviours in rela- paid to multisectoral and life skills-oriented approaches, tion to early marriage, childbearing and sexual debut. within the social, cultural and structural contexts. Further research is warranted to obtain greater insights into ASRH trends and inequalities, such as in age differ- ences between spouses, sexual activity beyond first sex, AbbreviationsASRH: Adolescent sexual and reproductive health; SRH: Sexual and reproduc- contraceptive access and use, abortion, gender equity, tive health; SSA: Sub-Saharan Africa; AARC : Average annual rate of change; and other critical dimensions of ASRH to inform policy SDGs: Sustainable development goals; HIV: Human immunodeficiency virus; and program development with effective targeting of the AIDS: Acquired immunodeficiency syndrome; STIs: Sexually transmitted infec-tions; DHS: Demographic and health survey. most vulnerable adolescents. Further studies are also required for in-depth understanding of family formation Supplementary Information dynamics and sequencing of life events in SSA and how The online version contains supplementary material available at https:// doi. they vary across subregions in order to identify factors org/ 10. 1186/ s12978-0 21- 01125-8. leading to disparities in geographical trends and patterns in SRH indicators. Additional file 1. Study populations and data sources, definitions, Addi- Our analysis is based on self-reported events in the tional Tables S1–6 and Additional Figures S1–16. surveys, which, particularly for sexual debut, are likely to be influenced by social desirability bias [54, 55]. There Acknowledgements is some evidence suggesting girls may deny their sexual Not applicable. activity, while boys may exaggerate or overstate their About this supplement experiences [12]. It has also been reported that younger This articles hasbeen published as part of Reproductive Health Volume 18 adolescents who have had an early first birth or mar- Supplement 12021: ASRH for all in SSA: are inequalities reducing?. The full riage are more likely to overstate their age at time of sur- contents ofthe supplement are available at https://r epro ducti ve- health jour nal. biomed cent ral. com/ articl es/ suppl ements/ volume-1 8-s upple ment-1. vey, leading to underestimation of these events [56]. The marriage indicator also raises some methodological con- Disclaimer cerns, as in many contexts, marriage may be a process, The boundaries and names shown and designations employed and the pres-entation of the material on the maps in this paper do not imply the expression which is difficult to date, or concepts and definitions of of any opinion whatsoever on the part of WHO and any other institutions marriage may vary across time and populations. which authors are affiliated to concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitations of its frontiers or boundaries. Every effort is made to ensure the maps in this paper Conclusions are free of errors, but there is no warrant the features are either spatially or temporally accurate or fit for a particular use. The maps used in this paper are Early marriage and childbearing among young and older provided without any warranty of any kind whatsoever, either expressed or adolescent girls and boys were declining in SSA although implied. profound subregional disparities persisted, alongside Authors’ contributions marked urban–rural and socioeconomic inequalities. DYM and TB conceived the framework of the paper and prepared a first Disparities between rural and urban girls, and between draft of the article. DYM performed data analyses and wrote the draft of the the poorest and richest households were increasing dur- manuscript. DYM, TB and SN synthesized results with the support from RMC, AvM, MYI, AdM, EB, AbM, RMK, EA, EdP, YDW, MKM, WM and CMF through ing 2000–2015. The widening of this gap was greater in discussions and other country participants who attended the Countdown to Central and West Africa where the highest prevalence 2030 for Women’s, Children’s and Adolescents’ Health analysis workshop on levels of child marriage and adolescent birth are found. adolescent sexual and reproductive health, 24–27 June 2019, Addis Ababa, Ethiopia. All authors critically reviewed the final draft, contributed to the These compound the disadvantages of already vulnerable finalization and approved the final manuscript. All authors read and approved populations. the final manuscript. Melesse et al. Reprod Health 2021, 18(Suppl 1):117 Page 14 of 15 Funding adolescent sexual and reproductive health and rights in the 25 years The Countdown to 2030 for Women’s, Children’s and Adolescents’ Health is since the international conference on population and development. J the recipient of an investment of the Bill & Melinda Gates Foundation. 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