Heterogeneous effects of socio-economic and cultural factors on fertility differentials in Burundi and Morocco during their fertility transition periods: a retrospective, cross-sectional and comparative study.

Introduction: few studies have examined the factors influencing fertility differentials and the variation in their effects in countries with different socioeconomic and cultural backgrounds and different fertility transition paces. To address this gap, our study sought to first identify the factors that influenced fertility differentials in Morocco and Burundi during their fertility transition periods, and then to compare the effects of these factors between the two countries. Methods: using data from the 2003-4 Morocco and 2010 Burundi Demographic and Health Surveys, bivariable and multivariable Poisson regression analyses offset by the natural logarithm of the women´s age were performed to identify the socioeconomic and cultural factors that influenced fertility differentials in Morocco and Burundi during their fertility transition. Results: our main findings showed that the total number of children ever born ranged from 0 to 17 with a mean of 2.71 ± 2.89 in Burundi and from 0 to 16 with a mean of 1.88 ± 2.80 in Morocco. In Burundi, both socioeconomic and cultural factors like rural residence adjusted incident rate ratio (AIRR) = 1.159, 95% CI: 1.103 - 1.217, P=0.020), women´s illiteracy (AIRR=1.465, 95% CI: 1.241- 1.729, P <0.001) and agricultural profession (AIRR=1. 332, 95% CI: 1.263 - 1.401, P = 0.004), household poverty (AIRR= 1.381, 95% CI: 1.223 - 1.431, p<0.001), infant mortality (AIRR= 1.602, 95% CI: 1.562 - 1.643, p<0.001), early marriage (AIRR= 1.313, 95% CI: 1.264 - 1.364, p<0.001), lack of knowledge of any contraceptives (AIRR= 1.263, 95% CI: 1.125 - 1.310, p = 0.003) and failure to use modern contraceptives (AIRR= 1.520, 95% CI: 1.487 - 1.611, p<0.001) were associated with high number of children ever born. However, in Morocco socioeconomic factors like residence place, women´s agricultural profession and household poverty were not significant. In this country, women´s illiteracy (AIRR=1.428, 95% CI: 1.315 - 1.551, P <0.001), lack of access to mass media (AIRR= 1.241, 95% CI: 1.108 - 1.375, p = 0.006), infant mortality (AIRR=1.222, 95%CI: 1.184 - 1.361, p<0.001), early marriage (AIRR1.481, 95% CI: 1.435 - 1.529, p<0.001), lack of knowledge of any contraceptives (AIRR1.508, 95% CI: 1.409 - 1.613, p<0.001) and failure to use modern contraceptives (AIRR1.745, 95% CI: 1.627 - 1.863, p<0.001) were associated with high fertility but with different effects than in Burundi. Conclusion: the evidence from this study suggests that interventions to accelerate the fertility transition processes in Burundi and many other countries with slow fertility transitions should be designed and implemented according to each country's local context.

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

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.

Determinants of fertility differentials in Burundi: evidence from the 2016-17 Burundi demographic and health survey.

INTRODUCTION: although fertility control remains a major priority for the Burundian government and most of its partners, few studies on Burundi´s fertility determinants are available to guide interventions. To address this gap, our study aims to examine the most factors influencing fertility differentials in Burundi by using the latest Burundi demographic and health survey data. METHODS: using data from the 2016-17 Burundi demographic and health survey, one-way analysis of variance was performed to describe variations in mean number of children ever born across categories of correlate variables. Then univariable and multivariable poisson regression analyses were carried out to identify the most factors influencing fertility differentials in Burundi. RESULTS: in our sample, the total number of children ever born ranged from 0 to 15 children by women with a mean number of 2.7 children (±2.8 SD). Factors such as urban residence (aIRR 0.769, 95% CI: 0.739 - 0.782, p = 0.008), increase in the level of education of both women and husbands (aIRRs of 0.718, 95% CI: 0.643 - 0.802, P<0.001 and 0.729, 95% CI: 0.711 - 0.763, p<0.001 respectively), no history of infant mortality experience (aIRR 0.722, 95% IC: 0.710 - 0.734, p<0.001) and increase in age at first marriage or first birth (aIRRs of 0.864, 95% CI: 0.837 - 0.891, P<0.001 and 0.812, 95% CI: 0.781 - 0.845, p<0.001 respectively) are associated with a low fertility rate while factors such as residence especially in Southern region (aIRR 1.129, 95% IC: 1.077 - 1.184, p<0.001), women and husband´s agricultural profession (aIRRs of 1.521, 95% CI: 1.429 - 1.568, P<0.001 and 1.294, 95% CI: 1.211 - 1.316, p<0.001 respectively), household poverty (aIRR 1.117, 95% IC: 1.080 - 1.155, p<0.001), lack of knowledge of any contraceptive method (aIRR 1.502, 95% IC: 1.494 - 1.564, p<0.001) and non-use of modern contraceptive methods (aIRR 1.583, 95% IC: 1.562 - 1.607, p<0.001) are associated with a high fertility rate. CONCLUSION: the results of this study suggest that actions aimed at promoting education in general especially female education, improving child survival, women´s socio-economic status, agriculture mechanization and increasing number and scope of family planning services, could help reduce Burundi fertility rate.