Determinants of unintended pregnancies among currently married women in Uganda

Wasswa, Ronald; Kabagenyi, Allen; Atuhaire, Leonard

doi:10.1186/s41043-020-00218-7

Cited by 29 publications

(41 citation statements)

References 38 publications

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“…This concurred with the findings of Mutumba et al, among Africans and European countries [17]. Previous findings by Wasswa and colleagues revealed that married women in Uganda with higher age at first birth were at an increased risk of unintended pregnancies [40]. In the process of wanting to achieve their desired number of children, women with higher age at first birth may avoid using contraceptives.…”

Section: Discussionsupporting

confidence: 89%

Multilevel mixed effects analysis of individual and community level factors associated with modern contraceptive use among married women in Uganda

2021

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Background In spite of the universal right for women to decide freely for themselves when, and how many children they want to have in life, married women in Uganda are less likely to use modern contraceptives as compared to other marital categories. This study examines the individual and community factors associated with modern contraceptive use among married women in Uganda. Methods The study used data from the 2016 Uganda Demographic and Health Survey which comprised of 8671 married women aged 15–49 years who were fecund and non-pregnant at the time of the survey. Analysis was done using a multilevel mixed-effects logistic regression model. Results Findings showed that married women who were; Muslims (AOR = 0.78, CI = 0.66–0.91), had more than five children (AOR = 0.76, CI = 0.61–0.98), staying in communities with high poverty (AOR = 0.78, CI = 0.65–0.93), with older age at first birth (AOR = 0.94, CI = 0.92–0.96) as well as having spousal age difference of more than 9 years (AOR = 0.86, CI = 0.76–0.98) were associated with low modern contraceptive use. Women living in communities with higher age at first marriage (AOR = 0.93, CI = 0.88–0.98) or higher sexual debut (AOR = 0.91, CI = 0.85–0.98) were also associated with reduced odds of modern contraception. In addition, older women (AOR = 1.03, CI = 1.01–1.04), having secondary/higher education (AOR = 1.93, CI = 1.58–2.37), living in a rich household (AOR = 1.32, CI = 1.14–1.53), short distance to health facility (AOR = 1.18, CI = 1.06–1.31), high community education (AOR = 1.38, CI = 1.17–1.62), high community exposure to family planning messages (AOR = 1.24, CI = 1.08–1.42), and communities with high proportion of women working (AOR = 1.22, CI = 1.06–1.39) were more likely to use modern contraceptives. Conclusion The study revealed that both individual and community factors were important in explaining the factors associated with modern contraceptive use among married women in Uganda. Therefore, there is need to invest in community based programs like: family planning outreach services, mass media campaigns and community mobilization activities to help in dissemination of family planning information, increase awareness and promotion in use of modern contraceptives. Also, expansion of higher education and the need to make family planning services available and accessible to areas with limited physical access to health facilities will lead to sustained increase in uptake of modern contraceptives.

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Section: Discussionsupporting

confidence: 89%

Multilevel mixed effects analysis of individual and community level factors associated with modern contraceptive use among married women in Uganda

2021

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“…This is explained by educated partners having better access to health information and that they are more likely to realize the benefits of HIV testing during pregnancy to prevent HIV transmission and therefore more likely to seek, accept and test for HIV. Educated partners are more likely to have a planned pregnancy [ 67 , 68 ] and this may enable them to think carefully about what the pregnancy requires so that they can mobilize the resources that are needed for maternal services, including PMTCT services. Meaningfully, more than 90% of women in this study reported that their pregnancy was planned and of those, approximately 75% had been tested for HIV.…”

Section: Discussionmentioning

confidence: 99%

Prenatal HIV Test Uptake and Its Associated Factors for Prevention of Mother to Child Transmission of HIV in East Africa

Astawesegn

Stulz

Agho

et al. 2021

IJERPH

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Identifying the socioeconomic and structural issues that act as enablers and/or barriers to HIV testing services is critical in combatting HIV/AIDS amongst mothers and children in Africa. In this study, we used a weighted sample of 46,645 women aged 15–49 who gave birth in the two years preceding the survey from the recent DHS dataset of ten East African countries. Multivariable logistic regression was used to investigate the factors associated with prenatal HIV test uptake in East Africa. The overall prenatal HIV test uptake for the prevention of mother-to-child transmission (PMTCT) of HIV was 80.8% (95% CI: 74.5–78.9%) in East Africa, with highest in Rwanda (97.9%, 95% CI: 97.2–98.3%) and lowest in Comoros (17.0%, 95% CI: 13.9–20.7%). Common factors associated with prenatal HIV test service uptake were higher maternal education level (AOR = 1.29; 95% CI: 1.10–1.50 for primary education and AOR = 1.96; 95% CI: 1.53–2.51 for secondary or higher education), higher partner education level (AOR = 1.24; 95% CI: 1.06–1.45 for primary education and AOR = 1.56; 95% CI: 1.26–1.94 for secondary or higher school), women from higher household wealth index (AOR = 1.29; 95% CI: 1.11–1.50 for middle wealth index; AOR= 1.57; 95% CL: 1.17–2.11 for rich wealth index), improved maternal exposure to the media, and increased awareness about MTCT of HIV. However, residents living in rural communities (AOR=0.66; 95% CI: 0.51–0.85) and travelling long distances to the health facility (AOR = 0.8; 95% CI: 0.69–0.91) were associated with non-use of prenatal HIV test service in East African countries. In each East African country, factors associated with prenatal HIV test uptake for PMTCT varied. In conclusion, the pooled prenatal HIV test uptake for PMTCT of HIV was low in East Africa compared to the global target. Scaling up interventions to improve enablers whilst addressing barriers to the use of prenatal HIV test services are essential to end the HIV/AIDS epidemic in East African countries.

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“…This method had been discussed by numerous authors in literature [ 7 , 8 ]. In this study, we applied a machine learning approach to evaluate various algorithms' performance.…”

Section: Methodsmentioning

confidence: 99%

“…According to a recent DHS survey, the unexpected pregnancy rate in Ethiopia is 28% [ 6 ]. Another study of a Ugandan woman who is currently married found that 37% of pregnancies were unplanned [ 7 ]. Research based on data from six South Asian countries shows that about 28% of married women in Bangladesh have unintended pregnancies.…”

Section: Introductionmentioning

confidence: 99%

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Performance Evaluation of Machine Learning Algorithm for Classification of Unintended Pregnancy among Married Women in Bangladesh

Hossain

Habib

Saleheen

et al. 2022

Journal of Healthcare Engineering

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Intended pregnancy is one of the significant indicators of women’s well-being. Globally, 74 million women become pregnant every year without planning. Unintended pregnancies account for 28% of all pregnancies among married women in Bangladesh. This study aimed to investigate the performance of six different machine learning (ML) algorithms applied to predict unintended pregnancies among married women in Bangladesh. From BDHS 2017-18, only 1129 pregnant women aged 15–49 were eligible for this study. An independent χ 2 test had performed before we considered six popular ML algorithms, such as logistic regression (LR), random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), naïve Bayes (NB), and elastic net regression (ENR) to predict the unintended pregnancy. Accuracy, sensitivity, specificity, Cohen’s Kappa statistic, and area under curve (AUC) value were used as model evaluation. The bivariate analysis result showed that women aged 30–49 years, poor, not educated, and living in male-headed households had a higher percentage of unintended pregnancy. We found various performance parameters for the classification of unintended pregnancy: LR accuracy = 79.29%, LR AUC = 72.12%; RF accuracy = 77.81%, RF AUC = 72.17%; SVM accuracy = 76.92%, SVM AUC = 70.90%; KNN accuracy = 77.22%, KNN AUC = 70.27%; NB accuracy = 78%, NB AUC = 73.06%; and ENR accuracy = 77.51%, ENR AUC = 74.67%. Based on the AUC value, we can conclude that of all the ML algorithms we investigated, the ENR algorithm provides the most accurate classification for predicting unwanted pregnancy among Bangladeshi women. Our findings contribute to a better understanding of how to categorize pregnancy intentions among Bangladeshi women. As a result, the government can initiate an effective campaign to raise contraception awareness.

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Determinants of unintended pregnancies among currently married women in Uganda

Cited by 29 publications

References 38 publications

Multilevel mixed effects analysis of individual and community level factors associated with modern contraceptive use among married women in Uganda

Multilevel mixed effects analysis of individual and community level factors associated with modern contraceptive use among married women in Uganda

Prenatal HIV Test Uptake and Its Associated Factors for Prevention of Mother to Child Transmission of HIV in East Africa

Performance Evaluation of Machine Learning Algorithm for Classification of Unintended Pregnancy among Married Women in Bangladesh

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