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Background: Despite the common restrictive abortion laws, abortion remains widespread in sub-Saharan Africa (SSA) countries. Women still utilize abortion services and put their lives and health at risk because abortion can only be procured illegally in private facilities such as mid-level or small patent medicine store that may be manned by unskilled providers or through a non-medicated approach. The objective of this study was to investigate the prevalence of abortion, the reasons women had abortions, median years to first abortion after sexual debut and examine the factors of time to first abortion among women of reproductive age in the Republic of Congo. Methods: We used data from the most recent Republic of Congo Demographic and Health Survey (DHS). A total sample of 3622 women aged 15–49 years was analyzed. We estimated the overall prevalence of abortion and median years to first abortion. Furthermore, we examined the factors of time to first abortion after sexual debut using multivariable Cox regression and reported the estimates using adjusted Hazard Ratio (aHR) and 95% confidence intervals (CI). Statistical significance was determined at p < 0.05. Results: The prevalence of abortion was 60.0% and median years of time to first abortion after sexual debut was 9.0. The prominent reasons for abortion were due to too short birth interval (23.8%), lack of money (21.0%) and that husband/partner did not need a child at that time (14.0%). Women’s age and region were notable factors in timing to first abortion. Furthermore, women from poorer, middle, richer and richest households had 34, 67, 86 and 94% higher risk of abortion respectively, when compared with women from poorest households (all p < 0.05). Women currently in union/living with a man and formerly in union had 41 and 29% reduction in the risk of abortion respectively, when compared with those never in union (all p < 0.05). In addition, women with primary and secondary+ education had 42 and 76% higher risk of abortion respectively, when compared with women with no formal education (all p < 0.05). Conclusion: There was high prevalence of abortion with short years at first abortion. Abortion was associated with women’s characteristics. There is need for unwanted pregnancy prevention intervention and the improvement in pregnancy care to reduce adverse pregnancy outcomes among women.
A cross-sectional data extracted from the Republic of Congo DHS 2012 was analyzed. A nationally representative sample of 3622 women who have had sex and aged 15–49 years were included in this study. On the other hand, the exclusion criterion was women with history of sexual abstinence. This was to ensure that only women exposed to pregnancy occurrence were analyzed. DHS data was collected through a stratified multistage cluster sampling technique. The procedure for stratification approach divides the population into groups by geographical region and commonly crossed by place of residence – urban vs. rural. A multi-level stratification approach is used to divide the population into first-level strata and to subdivide the first-level strata into second-level strata, and so on. DHS data is available in the public domain and accessed at; http://dhsprogram.com/data/available-datasets.cfm. DHS has been conducted in over 85 countries and repeated every years since 1984. A major advantage is that the sampling design and data collection approach are similar across countries which makes the results of different settings comparable. Though from the onset, DHS was designed to expand on fertility, demographic and family planning data collected in the World Fertility Surveys and Contraceptive Prevalence Surveys, nonetheless, it has become the prominent source of population surveillance for the monitoring of population health indices particularly in resource-constrained settings. DHS elicits information from respondents in a wide range of health-related areas including vaccination, child and maternal mortality, fertility, intimate partner violence, female genital mutilation, nutrition, lifestyle, infectious and non-infectious diseases, family planning, water and sanitation amongst others. DHS has great merits in collecting high-quality data through proper interviewer training, national coverage, standardized data collection instrument and proper operational definition of concepts to enhance understanding among policy and decision makers. DHS data is useful in formulating epidemiological research to estimate prevalence, trends and inequalities. The details of DHS has been reported previously [28]. The main outcome variable in this study was “abortion” also known as induced pregnancy termination. It was derived from the question; “Number of abortions” and responses were coded as “no” if a woman reported “0” indicating no history of abortion, and coded as “yes” if a woman reported “1”, “2”, “3”, “4” and so forth indicating history of abortion. In addition, the time to first abortion after sexual debut was also utilized. It was derived from the question; “Age at first abortion”. The difference in years between age at first abortion and “Age at first sex” was used as the time to first abortion. The main reason for abortion was derived from the question; “Main reason for putting an end to this pregnancy?” in the DHS individual woman dataset. The factors examined in this study are based on previous studies related to abortion and presented in Table 1 below [9, 11, 30–32]. Categories and operational definition of independent variables aFor the calculation of household wealth status, household assets such as ownership of television, radio, bicycle possessed by the household and housing quality such as type of floor, wall and roof were taken into consideration. Each item is assigned a factor score generated through principal component analysis which are then summed and standardized for the households. These standardised scores places the households in a continuous scale based on relative wealth scores. The scores thus obtained from a continuous scale are subsequently categorised into quintiles to rank the household as poorest/poorer/middle/richer/richest to richest [29] We used publicly available data in this study. Since the data was not collected by the authors of this manuscript, we sought permission from MEASURE DHS/ICF International and access to the data was provided after our intent for the request was assessed and approved. MEASURE DHS Program is consistent with the standards for ensuring the protection of respondents’ privacy. ICF International ensures that the survey complies with the U.S. Department of Health and Human Services regulations for the respect of human subjects. No further approval was required for this study. More details about data and ethical standards are available at http://goo.gl/ny8T6X. The survey (‘svy’) module was used to adjust for stratification, clustering and sampling weights to compute the estimates of abortion. To check multicollinearity, variance-inflation factor was employed and a value below 10 was considered acceptable [33, 34]. Consequently, no variable was excluded from the model as they were not found to be interdependent. We use percentage, Kaplan-Meier and Cox regression models to account for censoring in the estimation of exposure time to abortion [35, 36]. Statistical significance was determined at p < 0.05. Stata Version 14 (StataCorp., College Station, TX, USA) was used for data analysis.
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