Background: Worldwide, pregnancy termination due to unintended pregnancy is crucial in maternal health, particularly in settings where abortion laws are restrictive. Presently, there is a paucity of literature on determinants of induced abortion among women of reproductive age in Sierra Leone. The study findings could be used to improve the country’s maternal mortality indices and inform health programs and reproductive health policies geared toward tackling induced abortion. Methods: We analyzed secondary data from the 2013 and 2019 Sierra Leone Demographic and Health Surveys. The surveys were nationally representative, with weighted samples comprising 16,658 (2013) and 15,574 (2019) women of reproductive age. Descriptive statistics, including frequencies and percentages, were computed, while Chi-square and Binomial Logistics Regression were employed to identify correlates of induced abortion. Results: The results showed that a minority (9%) of the participants had induced abortion in both surveys. Abortion was significantly associated with age, marital status, employment status, education, parity, and frequency of listening to the radio and watching television (p < 0.05). For instance, women aged 45–49 years (AOR = 7.91; 95% CI: 5.76–10.87), married women (AOR = 2.52; 95% CI: 1.95–3.26), and working women (AOR = 1.65; 95% CI: 1.45–1.87) had a higher likelihood of induced abortion compared to their counterparts. Moreover, women with primary education (AOR = 1.27; 95% CI:1.11–1.46) and those who watch television once a week (AOR = 1.29; 95% CI: 1.11–1.49) were more likely to terminate a pregnancy. Women with six or more children (AOR = 0.40; 95% CI: 0.31–0.52) were less likely to terminate a pregnancy compared to those with no child. Conclusion: The study revealed that a minority of the women had induced abortions. The prevalence of induced abortion did not change over time. Induced abortion was influenced by age, marital status, employment status, education, parity, and exposure to mass media. Therefore, policies and programs to reduce unwanted pregnancies should focus on increasing access to modern contraceptives among women of lower socio-economic status.
Sierra Leone is located on the west coast of Africa and covers an area of 72,000 square kilometers [18]. It shares a border with Guinea on the north and northeast, Liberia on the east and southeast, and the west by the Atlantic Ocean [18]. According to the 2015 Population and Housing Census, the country has a total population of 7,092,113 with just over half being female (50.8%) [24]. This study analyzed the women's data from the two most recent 2013 and 2019 Sierra Leone Demographic and Health Surveys (SLDHS) [18, 22]. The DHS is a household-based, nationally representative survey. It uses a two-stage sample design. For instance, in the 2013 DHS, the first stage involved selecting 435 enumeration areas from 27 strata with probability proportional to size, using the 2004 Population and Housing Census report [23], while the second comprised the selection of 30 households from each cluster. A total number of 13,006 households within the enumeration areas were selected. We obtained 16,658 women as the weighted sample size of women aged 15–49 years. Similarly, in the 2019 DHS, the first stage comprised the selection of 578 enumeration areas from 31 strata, proportional to size employing the 2015 Population and Housing Census report [24], while the second stage involved the selection of 24 households from each cluster, resulting in a total sample size of approximately 13,872. A total of 15,574 women aged 15–49 years were obtained as a weighted sample. The target population was women of reproductive age who had ever terminated a pregnancy and passed the night before the survey in the selected households. The anonymized data was cleaned, missing values were dropped and adjusted for the complex nature of the survey. Permission to use the DHS data was sought from Measure DHS. The anonymized datasets were only downloaded on approval of the request to undertake this analysis. The data analysed in this study were saved on a password-protected personal computer. The data was declared survey data using sampling weight, weight, and strata or employing the 'svy' STATA command. Detailed information about the 2013 and 2019 DHS is included elsewhere [18, 22]. The dependent variable in this study was ever terminated a pregnancy (induced abortion), coded as yes = 1 and no = 0. The independent variables mentioned in the literature include those characteristics of the women who attest to having terminated a pregnancy. These include women's age (15–19 = 1; 20–24 = 2; 25–29 = 3; 30–34 = 4; 35–39 = 5; 40–44 = 6; 45–49 = 7), educational status (no education = 1; primary = 2; secondary = 3; higher = 4), employment status (not working = 1; working = 2), wealth index (poorest = 1; second = 2; middle = 3; fourth = 4; richest = 5), religion (Christianity = 1; Muslim = 2; others religion = 3), place of residence (urban = 1; rural = 2), marital status (never in union = 1; married/in union = 2; single (formerly married/in union) = 3), and parity (none = 1; 1–2 children = 2; 3–5 children = 3; 6 or more children = 4). Other independent variables were current contraceptive use (no method = 1; modern method = 2; traditional method = 3), knowledge about ovulation, correct (halfway between two menstrual periods) = 1; incorrect = 2; don’t know = 3), frequency of reading newspaper, listening to radio and watching television (not at all = 1; less than once a week = 2; at least once a week = 3). All analyses were carried out using STATA/SE version 16 (Stata Corp, College Station., Texas, USA). Descriptive statistics of the background characteristic of respondents were computed and summarized (Table (Table1).1). At the bivariate level, the Chi-squared test was used to determine the association between variables under study and the outcome of interest. Similarly, at the multivariable level, binary logistics regression was used to determine the predictors of induced abortion among women of reproductive age. In all, three models were computed. Model 1 looked at predictors of induced abortion in 2013, while model 2 focused on predictors of induced abortion in 2019. The third model (model 3) focused on predictors of induced abortion in 2013 and 2019 (combined) while adjusting for the survey year. The significance for the analysis was set at p < 0.05, while the strength of association was examined using odds ratios and their 95% confidence interval. Participant characteristics
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