Socio-economic and geographical inequalities in adolescent fertility rate in Ghana, 1993-2014 |
Authors: |
Bright Opoku Ahinkorah, Eugene Budu, Henry Ofori Duah, Joshua Okyere, and Abdul-Aziz Seidu |
Source: |
Archives of Public Health, DOI: 10.1186/s13690-021-00644-x |
Topic(s): |
Fertility Inequality Residence Spatial analysis Wealth Index Youth
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Country: |
Africa
Ghana
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Published: |
JUL 2021 |
Abstract: |
Background: Despite public health interventions to control adolescent fertility, it remains high in sub-Saharan Africa. Ghana is one of the countries in sub-Saharan Africa with the highest adolescent fertility rates. We examined the trends and socio-economic and geographical patterns of disparities in adolescent fertility in Ghana from 1993 to 2014.
Methods: Using the World Health Organization's (WHO) Health Equity Assessment Toolkit (HEAT) software, data from the 1993-2014 Ghana Demographic and Health surveys were analyzed. First, we disaggregated adolescent fertility rates (AFR) by four equity stratifiers: wealth index, education, residence and region. Second, we measured the inequality through summary measures, namely Difference (D), Population Attributable Risk (PAR), Ratio (R) and Population Attributable Fraction (PAF). A 95 % confidence interval was constructed for point estimates to measure statistical significance.
Results: We observed substantial absolute and relative wealth-driven inequality in AFR (PAR=-47.18, 95 % CI; -49.24, -45.13) and (PAF= -64.39, 95 % CI; -67.19, -61.59) respectively in favour of the economically advantaged subpopulations. We found significant absolute (D = 69.56, 95 % CI; 33.85, 105.27) and relative (R = 3.67, 95 % CI; 0.95, 6.39) education-based inequality in AFR, with higher burden of AFR among disadvantaged subpopulations (no formal education). The Ratio measure (R = 2.00, 95 % CI; 1.53, 2.47) indicates huge relative pro-urban disparities in AFR with over time increasing pattern. Our results also show absolute (D, PAR) and relative (R, PAF) inequality in AFR across subnational region, between 2003 and 2014. For example, in the 2014 survey, the PAR measure (D=-28.22, 95 % CI; -30.58, -25.86) and the PAF measure (PAF=-38.51, 95 % CI; -41.73, -35.29) indicate substantial absolute and relative regional inequality.
Conclusions: This study has indicated the existence of inequality in adolescent fertility rate in Ghana, with higher ferlitiy rates among adolescent girls who are poor, uneducated, rural residents and those living in regions such as Northern, Brong Ahafo, and Central region, with increasing disparity over the time period of the study. There is the need for policy interventions that target adolescent girls residing in the rural areas and those in the low socioeconomic subgroups to enable the country to avert the high maternal/newborn morbidity and mortality usually associated with adolescent childbearing. |
Web: |
https://pubmed.ncbi.nlm.nih.gov/34229753/ |
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