Socioeconomic inequality in modern contraceptive utilization among reproductive-age women in sub-Saharan African countries: a decomposition analysis

Introduction: Family planning services allow individuals to achieve desired birth spacing, family size, and contribute to improved health outcomes for infants, children, women, and families, and prevent unintended pregnancy. Births resulting from unintended pregnancies can have negative consequences Children from unintended pregnancies are more likely to experience poor mental and physical health during childhood. Even though many international organizations work to ensure universal access to sexual and reproductive health services, reproductive health service utilization is concentrated among individuals with rich socioeconomic status. Therefore, this study aimed to assess the presence of socioeconomic inequality in modern contraceptive utilization and its contributors in sub-Saharan African countries. Methods: A total of 466,282 weighted reproductive-aged women samples from DHS data SSA countries were included in the study. Erreygers normalized concentration index and its concentration curve were used to assess socioeconomic-related inequality in modern contraceptive utilization. Decomposition analysis was performed to identify factors contributing to socioeconomic-related inequality. Results: The weighted Erreygers normalized concentration index for modern contraceptive utilization was 0.079 with Standard error = 0.0013 (P value< 0.0001); indicating that There is small amount but statistically significant pro rich distribution of wealth related in equalities of modern contraceptive utilization among reproductive age women. The decomposition analysis revealed that mass media exposure, wealth index., place of residency, and distance of health facility were the major contributors to the pro-rich socioeconomic inequalities in modern contraceptive utilization. Conclusion and recommendation: In this study, there is a small amount but statistically significant pro rich distribution of modern contraceptive utilization. Therefore, give priority to modifiable factors such as promoting the accessibility of health facilities, media exposure of the household, and improving their country’s economy to a higher economic level to improve the wealth status of the population. The data source for this study was the recent standard Demographic health survey data of Sub-Saharan African countries conducted within 10 years (2010–2020), which was a crossectional study conducted every five-year interval (Table 1). The DHS is a national survey that collects information on basic health indicators such as mortality, morbidity, family planning service use, fertility, and mother and child health. The sub-Saharan is the area in the continent of Africa that lies south of the Sahara and consists of four geographically distinct regions namely Eastern Africa, Central Africa, Western Africa, and Southern Africa. Sample size determination of modern contraceptive utilization and factor associated with it among reproductive age women in each sub-Saharan Africa: based on 2010–2020 DHS The source population was all reproductive-age women across 33 Sub-Saharan African countries. Whereas the study population was reproductive-age women in the selected Enumeration Areas (EAs) and the mother was interviewed for the survey in each country. All reproductive-age women in the selected EAs in each SSA country were included in this study. Five countries that did not have a survey report after the 2010/2011 survey year were excluded due to the recent updates: Central Africa Republic, Eswatini, Sao Tome Principe, Madagascar, and Sudan. As well as three Sub-Saharan Countries (Botswana, Mauritania, and Eritrea) were excluded due to the dataset not being publicly available. A total of 47 countries are located in sub-Saharan Africa. Of these countries, only 33 countries had Demographic and Health Survey Report after 2010. A two-stage stratified cluster sampling technique was employed in DHS data. First, clusters/enumeration areas (EAs) were randomly selected from the sampling frame (i.e. are usually developed from the available latest national census). Second, systematic random sampling was conducted on households listed in each cluster or EA. Finally, interviews were conducted in selected households with target populations (women aged 15–49 and men aged 15–64) [19]. Weighted values were used to restore the representativeness of the sample data and were calculated from Individual Record (IR) DHS datasets. Finally, a total weighted sample of 466,282 reproductive-aged women was included from all 33 countries in sub-Saharan African countries (Table ​(Table11). Socioeconomic-related inequality in current modern contraceptive use was the outcome variable in this study. Current modern contraceptive utilization was a composite variable. If women reported the use of one of the following methods: female sterilization, male sterilization, the contraceptive pill, intrauterine contraceptive device (IUD), injectables (Depo Provera), implants, female condom, male condom, diaphragm, contraceptive foam and contraceptive jelly, lactational amenorrhea method (LAM), standard days method (SDM), country-specific modern methods and respondent-mentioned other modern contraceptive methods (including cervical cap, contraceptive sponge, and others were considered as currently using modern contraceptive while if a woman didn’t use none of the above modern contraceptive methods were considered as not using modern contraceptive currently [19]. The socioeconomic-related inequality of current modern contraceptive utilization can be expressed as the covariance between current modern contraceptive use and the measurement for living standards distribution (wealth index). Then, it was classified into either pro-poor, pro-rich, or no inequality. When the curve lies above the line of equality (when the ECI takes a negative value) the health variable in this case modern contraceptive use is concentrated among the poor (pro-poor). However, the ECI value can be positive, the curve will be below the line of equality indicating the health variable is concentrated among the rich (pro-rich). The ECI will be zero in the case when there is no socioeconomic-related inequality, the concentration curve lies at a 45-degree line (the line of perfect equality). Women’s age, educational level, wealth index, sex of household head, mass media exposure, place of residence, husbands’ educational level, current working status, parity, modern contraceptive knowledge, women’s involvement on decision-making of maternal health, −sub-regions in SSA and distance of health facility were incorporated as explanatory variables. The socioeconomic status was measured using the wealth index from DHS data sets. In the DHS data, the wealth index was constructed using principal component analysis and then categorized as poorest (quintile 1), poorer (quintile 2), middle (quintile 3), richer (quintile 4), richest (quintile 5) [20]. media exposure (media exposure was created from the three variables: watching television, listening radio, and reading a newspaper, and labeled as yes if a woman has exposure to either of the three media sources or no if a woman has exposure to none of them [21]. This study was performed based on the DHS data obtained from the official DHS measure website. DHS data in STATA format then cleaned, transformed, and append to produce favorable variables for the analysis. STATA 16 software was used to generate both descriptive and analytic statistics of the appended 33 countries’ data. Sampling weight was used throughout the analyses to adjust for the unequal probability of selection of the sample and the possible differences in response rates. The frequency with percent was used to indicate the distribution of respondents’ background characteristics and p-values were computed using Pearson’s chi-squared test. The study used a concentration curve to identify whether socioeconomic inequality in some health variables exists and to examine whether it is more pronounced at one point than another. Besides, the study also used a concentration index [22] to quantify and compare the degree of socio-economic-related inequality in a health variable [23, 24]. The concentration index is twice the area between the concentration curve and the line of equity with the range of − 1 to + 1 and the sign indicates the direction of the relationship between current modern contraceptive utilization and the distribution of living standards (wealth status) (Accordingly, CI = 0 indicated the distribution was proportionate, CI = 1 displayed that the richest person had all of the health variables, whereas CI = − 1 indicated that the poorest person had all of the health variables) [25, 26] But the outcome variable in the present study is binary (use/not use modern contraceptive), the bounds of C depend on the mean (μ) of the outcome variable and do not vary between 1 and-1. Thus, the bounds of C vary between μ–1 (lower bound) and 1–μ (upper bound) so the present study used Erreygers normalized concentration index (ECI) which is a modified version of the concentration index [27]. Mathematically, ECI can be defined as: Where ECI is Erreygers concentration index, CI(y) is the generalized concentration index and μ is the mean of the health variable, current modern contraceptive utilization. Then, the ECI with the standard error (SE) was reported in this study. To graphically show the socioeconomic-related inequality in current modern contraceptive utilization, Concentration curves show the cumulative percentage of the current modern contraceptive use (y-axis) against the cumulative share of the population ranked by living standards beginning with the poorest and ending with the richest (x-axis) [26]. The ECI would be a 450-line running from the bottom left-hand corner to the top right-hand corner indicating the absence of Inequality (ECI = 0). Furthermore, the concentration curve lying above and below the equality line (450) indicated that the health variable is disproportionately concentrated between poor(pro-poor or ECI < 0) and rich(pro-rich or ECI > 0), respectively [26, 28]. Visual inspection of a concentration curve can give information regarding whether the concentration curve lies above or below the line of equality. To assess the statistical significance of the difference between the concentration curve and the line of perfect equality (45-degree or diagonal line), the ECI with its p-value was calculated. To identify the relative contribution of various factors to socioeconomic-related inequality in current modern contraceptive utilization, a decomposition of the ECI was performed [26, 28, 29]. For any linear additive regression model of health outcome (y) [26], The concentration index for y, CI, is given as: Where “y” is the health outcome variable (in this case socioeconomic related inequality of modern contraceptive utilization), Xk is a set of the socioeconomic determinants of the health outcome, α is the intercept, βk is the coefficient of Xk, μ is the mean of y, X¯k is the mean of Xk, Ck is the CI for Xk, gc∈ is the generalized CI for the error term (∈), βkX¯kμ is the elasticity of y with respect to X¯k [29, 30].