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Background: Caesarean section (CS) is an intervention to reduce maternal and perinatal mortality, for complicated pregnancy and labour. We analysed trends in the prevalence of birth by CS in Ghana from 1998 to 2014. Methods: Using the World Health Organization’s (WHO) Health Equity Assessment Toolkit (HEAT) software, data from the 1998-2014 Ghana Demographic and Health Surveys (GDHS) were analysed with respect of inequality in birth by CS. First, we disaggregated birth by CS by four equity stratifiers: wealth index, education, residence, and region. Second, we measured inequality through simple unweighted measures (Difference (D) and Ratio (R)) and complex weighted measures (Population Attributable Risk (PAR) and Population Attributable Fraction (PAF)). A 95% confidence interval was constructed for point estimates to measure statistical significance. Results: The proportion of women who underwent CS increased significantly between 1998 (4.0%) and 2014 (12.8%). Throughout the 16-year period, the proportion of women who gave birth by CS was positively skewed towards women in the highest wealth quintile (i.e poorest vs richest: 1.5% vs 13.0% in 1998 and 4.0% vs 27.9% in 2014), those with secondary education (no education vs secondary education: 1.8% vs 6.5% in 1998 and 5.7% vs 17.2% in 2014) and women in urban areas (rural vs urban 2.5% vs 8.5% in 1998 and 7.9% vs 18.8% in 2014). These disparities were evident in both complex weighted measures of inequality (PAF, PAR) and simple unweighted measures (D and R), although some uneven trends were observed. There were also regional disparities in birth by CS to the advantage of women in the Greater Accra Region over the years (PAR 7.72; 95% CI 5.86 to 9.58 in 1998 and PAR 10.07; 95% CI 8.87 to 11.27 in 2014). Conclusion: Ghana experienced disparities in the prevalence of births by CS, which increased over time between 1998 and 2014. Our findings indicate that more work needs to be done to ensure that all subpopulations that need medically necessary CS are given access to maternity care to reduce maternal and perinatal deaths. Nevertheless, given the potential complications with CS, we advocate that the intervention is only undertaken when medically indicated.
Data from Ghana Demographic and Health Surveys (GDHS) in 1998, 2003, 2008 and 2014 were analysed. GDHS forms part of global surveys implemented by Measure DHS in about 85 LMICs worldwide. Overarching focus of DHS is to collate information on children, women and men. Among the cardinal issues captured are CS, fertility and family planning. When sampling, selection of enumeration areas (EAs) is the first step and takes cognisance of rural and urban locations in Ghana. This is ensued by household selection in the EAs. The complete sampling procedure has been elaborated in the final reports of the 1998, 2003, 2008 and 2014 GDHS. The sample for this study consisted of women with live births in the 5 years preceding the survey who were answerable to questions pertaining to CS (n = 15,432). Focus of the analysis was on recent births of women of reproductive age. Study outcome was whether mode of birth was by CS or not. Women who reported having given live birth by CS were categorised as “1”, whilst those without birth by CS were classified otherwise as “0”. Four stratifiers were used to assess inequality in births by CS: economic status measured by wealth quintile (quintile 1-5), education (no education, primary, secondary and above), residence (rural, urban) and region of residence (Western, Central, Greater Accra, Volta, Eastern, Ashanti, Brong Ahafo, Northern, Upper West, Upper East). Wealth index is derived by employing Principal Component Analysis (PCA). Education is measured by highest level of formal education completed. We used the 2019 updated WHO’s HEAT version 3.1 software for all analyses [18]. Estimates and confidence intervals of birth by caesarean section with respect to the aforementioned stratifiers were computed. Four measures were used to compute inequality namely Difference (D), Population Attributable risk (PAR), Population Attributable Fraction (PAF) and Ratio (R). Two of these are simple unweighted measures (D, R) and two are complex weighted measures (PAR, PAF). At the same time, R and PAF are relative measures whereas D and PAR are absolute measures. Summary measures were considered because WHO has indicated that both absolute and relative summary measures are essential for generating policy driven findings [18]. Unlike simple measures, the complex ones take size of categories inherent in a sub-population into account. WHO has extensively elaborated the procedure for generating summary measures [19].
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