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Background: Despite the variances in abortion laws accounting for differences in incidence of abortion among African countries, it appears there is absence of literature on other factors that may also account for the differences in incidence of abortion. Specifically, there is paucity of information on how socio-demographic factors account for the disparities in prevalence of pregnancy termination among women of reproductive age in sub-Saharan Africa. In view of this, this paper examined how socio-demographic factors influence pregnancy termination among women in reproductive age in Mozambique and Ghana. Methods: The study made use of data from the 2014 Ghana and 2011 Mozambique Demographic and Health Survey for the study. For the purpose of this study a sample of 9375 and 13,660 made up of women in their reproductive ages (15-49) in Ghana and Mozambique respectively was used. The results on the analysis of the association between socio-demographic factors and pregnancy termination are presented as odds ratio (OR) with 95% confidence intervals (CI). Results: The results revealed that about 25% of the respondents in Ghana and 9% of the respondents in Mozambique reported ever had a pregnancy terminated. In both countries, the odds of pregnancy termination were high among women with primary education, those in the older age groups, women who were Christians and women who were employed. Similarly, higher odds of pregnancy termination were found among ever married women, those who less than four births or more and those who have had access to social media (radio and television). Conclusion: To reduce unintended pregnancies that could lead to pregnancy termination, there is a need for regular integrated community-based outreach programs targeted at generating community responsiveness of effective contraception and prevention of unintended pregnancy.
The 2014 Ghana and 2011 Mozambique Demographic and Health Survey data were used for the study. Demographic and Health Survey is a nationwide survey which is designed and conducted every five years. The DHS focuses on child and maternal health and is designed to provide adequate data to monitor the population and health situation in Ghana and Mozambique. Demographic and Health Survey was carried out by the Ghana Statistical Service and Ministerio da Saude – MISAU/Moçambique, Instituto Nacional de Estatística – INE/Moçambique with ICF Macro an international company, giving the technical support needed for the survey through MEASURE DHS. The survey employs a stratified two stage sampling technique. The first stage involves the selection of points or clusters (enumeration areas [EAs]). The second stage is the systematic sampling of households listed in each cluster or EA. All women in their reproductive ages (15–49) belonging to selected households or visitors who slept in the household on the night before the survey were considered for interview. The 2014 version of the Ghana Demographic and Health Survey (GDHS) interviewed 9396 women between the ages 15 and 49 from 12, 831 households covering 427 clusters throughout Ghana. It had a response rate of 97% [22]. Whereas the 2011 version of Mozambique Demographic and Health Survey (MDHS) interviewed 13,745 women between the ages 15 and 49 from 13,718 households throughout Mozambique. It had a response rate of 99.8% [23]. For the purpose of this study a sample of 13,660 was used. Permission to use the data set was given us by the MEASURE DHS following the assessment of a concept note. The dataset is available to the public (www.measuredhs.com). The dependent variable employed for this study was “pregnancy termination” which was derived from the question “have you ever had a terminated pregnancy” and responses were coded 0 = “No” and 1 = “Yes”. Eleven independent variables were used for the study, these were; residence, maternal age, marital status, educational level, wealth status, religion, birth history, and occupation. Others included frequency of watching television, frequency of reading newspapers or magazine and frequency of listening to radio, which were used to as proxy to examine the influence media. Residence was coded as urban =1 rural = 2, age was categorized into, 15–19 = 1, 20–24 = 2, 25–29 = 3, 20–34 = 4, 35–39 = 5, 40–44 = 6, 45–49 = 7. Marital status was captured as never in union =1, married =2, living with partner =3, widowed =4, divorced =5 and separated = 6. Educational level was classified into four categories: No education = 1, primary = 2, secondary = 3 and higher = 4. Wealth status was categorized in poorest = 1, poorer = 2, middle = 3, richer = 4 and richest = 5. Religion was recoded as Christian =1, Islam =2 and traditional/spiritual/other/no religion = 3. Birth history was also captured as Zero birth =1, one birth = 2, two births = 3, three births = 4 and four births or more = 5. Occupation was also categorized into two thus, unemployed = 1 and employed = 2. Frequency of watching television was captured as “not at all” = 1, “less than once a week” = 2, “at least once a week” = 3. Frequency of reading newspaper or magazine was coded as “not at all” = 1, “less than once a week” = 2, “at least once a week” = 3. Frequency of listening to radio was categorized as “not at all” = 1, “less than once a week” = 2, “at least once a week” = 3. Pearson Chi – square test was conducted to examine the relationship between background characteristics and pregnancy termination. Next, univariate and multivariate binary logistic analysis were conducted to assess the association between women’s socio-demographic and behaviour factors and pregnancy termination. The results from the logistic regression analysis are presented as odds ratio (OR) with 95% confidence intervals (CI). The binary logistic regression was employed since the dependent variable was a dichotomous variable and it allows the predictions on a mixture of continuous and categorical variables. All the analysis was stratified by country. All analysis was done using the women file from both Ghana and Mozambique separated with the aim of comparison among the countries. All analysis was done using STATA version 13.
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