BMC Pregnancy and Childbirth (Sep 2022)

Prevalence, trend and determinants of adolescent childbearing in Burundi: a multilevel analysis of the 1987 to 2016–17 Burundi Demographic and Health Surveys data

  • Jean Claude Nibaruta,
  • Bella Kamana,
  • Mohamed Chahboune,
  • Milouda Chebabe,
  • Saad Elmadani,
  • Jack E. Turman,
  • Morad Guennouni,
  • Hakima Amor,
  • Abdellatif Baali,
  • Noureddine Elkhoudri

DOI
https://doi.org/10.1186/s12884-022-05009-y
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 13

Abstract

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Abstract Background Very little is known about factors influencing adolescent childbearing despite an upward trend in adolescent childbearing prevalence in Burundi, and its perceived implications on the rapid population growth and ill-health of young mothers and their babies. To adress this gap, this study aimed to examine the prevalence, trends and determinants of adolescent childbearing in Burundi. Methods Secondary analyses of the 1987, 2010 and 2016–17 Burundi Demographic and Health Surveys (BDHS) data were conducted using STATA. Weighted samples of 731 (1987 BDHS), 2359 (2010 BDHS) and 3859 (2016-17BDHS) adolescent girls aged 15–19 years old were used for descriptive and trend analyses. Both bivariable and multivariable two-level logistic regression analyses were performed to identify the main factors associated with adolescent childbearing using only the 2016–17 BDHS data. Results The prevalence of adolescent childbearing increased from 5.9% in 1987 to 8.3% in 2016/17. Factors such as adolescent girls aged 18–19 years old (aOR =5.85, 95% CI: 3.54–9.65, p < 0.001), adolescent illiteracy (aOR = 4.18, 95% CI: 1.88–9.30, p < 0.001), living in poor communities (aOR = 2.19, 95% CI: 1.03–4.64, p = 0.042), early marriage (aOR = 9.28, 95% CI: 3.11–27.65, p < 0.001), lack of knowledge of any contraceptive methods (aOR = 5.33, 95% CI: 1.48–19.16, p = 0.010), and non-use of modern contraceptive methods (aOR = 24.48, 95% CI: 9.80–61.14), p < 0.001) were associated with higher odds of adolescent childbearing. While factors such as living in the richest household index (aOR = 0.52, 95% IC: 0.45–0.87, p = 0.00), living in West region (aOR = 0.26, 95%CI: 0.08–0.86, p = 0.027) or in South region (aOR = 0.31, 95% CI: 0.10–0.96, p = 0.041) were associated with lower odds of adolescent childbearing. Conclusion Our study found an upward trend in adolescent childbearing prevalence and there were significant variations in the odds of adolescent childbearing by some individual and community-level factors. School-and community-based intervention programs aimed at promoting girls’ education, improving socioeconomic status, knowledge and utilization of contraceptives and prevention of early marriage among adolescent girls is crucial to reduce adolescent childbearing in Burundi.

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