Pregnancy termination remains a delicate and contentious reproductive health issue because of a variety of political, economic, religious, and social reasons. The present study examined the associations between demographic and socio-economic factors and pregnancy termination among young Ghanaian women. This study used data from the 2014 Demographic and Health Survey of Ghana. A sample size of 2114 young women (15–24 years) was considered for the study. Both descriptive (frequency, percentages, and chi-square tests) and inferential (binary logistic regression) analyses were carried out in this study. Statistical significance was pegged at p < 0.05. Young women aged 20–24 were more likely to have a pregnancy terminated compared to those aged 15–19 (AOR = 3.81, CI = 2.62–5.54). The likelihood of having a pregnancy terminated was high among young women who were working compared to those who were not working (AOR = 1.60, CI = 1.19–2.14). Young women who had their first sex at the age of 20–24 (AOR = 0.19, CI = 0.10–0.39) and those whose first sex occurred at first union (AOR = 0.57, CI = 0.34–0.96) had lower odds of having a pregnancy terminated compared to those whose first sex happened when they were less than 15 years. Young women with parity of three or more had the lowest odds of having a pregnancy terminated compared to those with no births (AOR = 0.39, CI = 0.21–0.75). The likelihood of pregnancy termination was lower among young women who lived in rural areas (AOR = 0.65, CI = 0.46–0.92) and those in the Upper East region (AOR = 0.18, CI = 0.08–0.39). The findings indicate the importance of socio-demographic factors in pregnancy termination among young women in Ghana. Government and non-governmental organizations in Ghana should help develop programs (e.g., sexuality education) and strategies (e.g., regular sensitization programs) that reduce unintended pregnancies which often result in pregnancy termination. These programs and strategies should include easy access to contraceptives and comprehensive sexual and reproductive health education. These interventions should be designed considering the socio-demographic characteristics of young women. Such interventions will help to achieve Sustainable Development Goal 3.1 that seeks to reduce the global maternal mortality ratio to fewer than 70 per 100,000 live births by 2030.
Data from Ghana’s 2014 Demographic and Health Survey (DHS) were used for this study. The DHS is conducted in about 85 low- and middle-income countries around the world. Unintended pregnancy, contraception use, qualified birth participation, immunization of under-fives, and intimate partner abuse are among the main maternal and child health issues targeted by the survey. The survey used a stratified two-stage sampling method. The first step was to choose clusters from all over the country, in both urban and rural settings. These were used to establish the study’s enumeration areas (EAs). These clusters were chosen from the country’s ten former administrative regions, spanning urban (n = 216) and rural (n = 211) areas. The selected EAs were then subjected to a systematic household sampling. A total of 12,831 households were included in the study. A total of 9396 women were interviewed for the survey [44] from the 12,831 households (response rate of 97.3%). Only young women (15–24 years old) who had ever been pregnant and had complete cases on all of the variables studied (n = 2114) were included in this analysis. As a result, young women who had never been pregnant (n = 1211) were excluded from the study because they had no risk of terminating a pregnancy (see Figure 1). Flow chart showing how the respondents were selected. The dependent variable employed for this study was “pregnancy termination” which was derived from the question “have you ever had a terminated pregnancy?”, and the response was coded as 0 = “No” and 1 = “Yes”. Eleven variables were considered as explanatory variables. These are age, wealth quintile, occupation, educational level, religion, marital status, age at first sex, parity, media exposure, place of residence, and region. We selected these variables on the basis that previous studies have found them to have significant associations with pregnancy termination [45,46,47,48,49]. In this study, the original coding for age, wealth quintile, place of residence, and region was maintained, while the remaining six variables were recoded to make them meaningful for the analyses and interpretation of results. Age in the DHS was coded as 15–19 and 20–24 for women aged 15–24. The statistical software Stata version 13 (Stata Corporation, College Station, TX, USA) was used to process the data. All frequency distributions were weighted using the sample weight (v005/1,000,000), while the svy command was used to account for the complex survey design and generalizability of the findings. Both descriptive (frequency, percentages) and inferential (binary logistic regression) analyses were carried out in this study. Statistical significance was pegged at p < 0.05. First, frequencies and percentages were used to show the proportion of pregnancy termination across the socio-demographic characteristics of the respondents. This procedure was followed by both bivariate and multivariate binary logistic regression analyses to examine the predictors of pregnancy termination. Model 1 focused on the independent association between each of the explanatory variables and pregnancy termination, while in Model 2, we adjusted for the effect of all the explanatory variables by putting all of them in the same model with pregnancy termination. Binary logistic regression was employed because the dependent variable was measured as a binary factor. Results for the binary logistic regression analyses are presented as crude odds ratios (COR) and adjusted odds ratios (AOR) with their corresponding 95% confidence intervals (CI), signifying the precision and significance of the reported odds ratio values. Since the data are available in the public domain, no additional approval was needed for this study. However, according to the DHS, ORC Macro Inc.’s Ethics Committee provided ethical clearance. Before starting interviews with each respondent, both respondents gave their informed consent. The authors requested and received permission to download and use the data from MEASURE DHS. The data are available at https://dhsprogram.com/what-we-do/survey/survey-display-437.cfm (accessed on 6 April 2021).
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