|Inequality in fertility rate among adolescents: evidence from Timor-Leste demographic and health surveys 2009–2016|
||Sanni Yaya, Betregiorgis Zegeye, Bright Opoku Ahinkorah, Kelechi Elizabeth Oladimeji, and Gebretsadik Shibre
||Archives of Public Health, 78, Article number: 98
||Background: Despite a decline in global adolescent birth rate, many countries in South East Asia still experience a slower pace decline in adolescent birth rates. Timor-Leste is one of the countries in the region with the highest adolescent birth rate and huge disparities between socio-economic subgroups. Hence, this study assessed the magnitude and trends in adolescent fertility rates within different socio-demographic subgroups in Timor-Leste.
Methods: Using the World Health Organization’s (WHO) Health Equity Assessment Toolkit (HEAT) software, data from the Timor-Leste Demographic and Health surveys (TLDHS) were analyzed between 2009 and 2016. We approached the inequality analysis in two steps. First, we disaggregated adolescent fertility rates by four equity stratifiers: wealth index, education, residence and region. Second, we measured the inequality through summary measures, namely Difference, Population Attributable Risk, Ratio and Population Attributable Fraction. A 95% confidence interval was constructed for point estimates to measure statistical significance.
Results: We found large socio-economic and area-based inequalities over the last 7 years. Adolescent girls who were poor (Population Attributable Fraction: -54.87, 95% CI; - 57.73, - 52.02; Population Attributable Risk: -24.25, 95% CI; - 25.51, - 22.99), uneducated (Difference: 58.69, 95% CI; 31.19, 86.18; Population Attributable Fraction: -25.83, 95% CI; - 26.93, - 24.74), from rural areas (Ratio: 2.76, 95% CI; 1.91, 3.60; Population Attributable Risk: -23.10, 95% CI; - 24.12, - 22.09) and from the Oecussi region (Population Attributable Fraction: -53.37, 95% CI; - 56.07, - 50.67; Difference: 60.49, 95% CI; 29.57, 91.41) had higher chance of having more births than those who were rich, educated, urban residents and from the Dili region, respectively.
Conclusions: This study identified disproportionately higher burden of teenage birth among disadvantaged adolescents who are, poor, uneducated, rural residents and those living in regions such as Oecussi, Liquica and Manufahi, respectively. Policymakers should work to prevent child marriage and early fertility to ensure continuous education, reproductive health care and livelihood opportunities for adolescent girls. Specialized interventions should also be drawn to the subpopulation that had disproportionately higher adolescent childbirth.