Magnitude and Associated Factors of Unintended Pregnancy among Pregnant Women at Saesie Tsaeda Emba Woreda Eastern Zone of Tigray, North Ethiopia, 2018

Machine learning to predict unintended pregnancy among reproductive-age women in Ethiopia: evidence from EDHS 2016

BACKGROUND

An unintended pregnancy is a pregnancy that is either unwanted or mistimed, such as when it occurs earlier than desired. It is one of the most important issues the public health system is currently facing, and it comes at a significant cost to society both economically and socially. The burden of an undesired pregnancy still weighs heavily on Ethiopia. The purpose of this study was to assess the effectiveness of machine learning algorithms in predicting unintended pregnancy in Ethiopia and to identify the key predictors.

METHOD

Machine learning techniques were used in the study to analyze secondary data from the 2016 Ethiopian Demographic and Health Survey. To predict and identify significant determinants of unintended pregnancy using Python software, six machine-learning algorithms were applied to a total sample of 7193 women. The top unplanned pregnancy predictors were chosen using the feature importance technique. The effectiveness of such models was evaluated using sensitivity, specificity, accuracy, and area under the curve.

RESULT

The ExtraTrees classifier was chosen as the top machine learning model after various performance evaluations. The region, the ideal number of children, religion, wealth index, age at first sex, husband education, refusal sex, total births, age at first birth, and mother's educational status are identified as contributing factors in that predict unintended pregnancy.

CONCLUSION

The ExtraTrees machine learning model has a better predictive performance for identifying predictors of unintended pregnancies among the chosen algorithms and could improve with better policy decision-making in this area. Using these important features to help direct appropriate policy can significantly increase the chances of mother survival.

Unintended Pregnancy and Associated Factors among Pregnant Women Attending Antenatal Care Unit in Public Health Facilities of Dire Dawa City, Eastern Ethiopia, 2021

Background

Unintended pregnancy refers to a pregnancy that is either mistimed or unwanted. Unintended pregnancy has been a troubling public health and reproductive health issue, which imposes appreciable adverse consequences on the mother, child, and the public in general. Globally 121 million unplanned pregnancies occurred from 2015 to 2019. A significant proportion (61%) of these pregnancies ended in abortions each year. In Ethiopia, the challenges of unintended pregnancy and its related complications still exist because of the high rate of unmet need for contraceptives. In addition, no research has been conducted on unintended pregnancy among pregnant women in Dire Dawa city administration.

Objective

To determine the prevalence of unintended pregnancy and associated factors among pregnant women attending antenatal care public health facilities in Dire Dawa in 2021.

Methods

A facility-based cross-sectional study was conducted. After being chosen randomly, 382 pregnant women were interviewed at 9 urban public health facilities. A pretested questionnaire was used to collect data, entered into Epi Info 7, and exported into SPSS version 25 for analysis. The variables, which were significant at P ≤ 0.25 in bivariate analysis, were included in multivariable analysis. Statistical significance was declared at a P value <0.05 and a 95% CI.

Results

In this study, the prevalence of unintended pregnancy was 23.8% at 95% CI (19.8-28.3). The following factors were associated with unintended pregnancy: single women (AOR = 10.93, 95% CI 3.65-32.74), low family income (2000 ETB) (AOR = 4.01, 95% CI 1.73-9.28), parity 3 (AOR = 10.3, 95% CI 4.07-25.84), no history of family planning use (AOR = 5.91, 95% CI 2.46-14.21), and husband decision-making role on reproductive health (AOR = 2.956, 95% CI 1.048-8.340). Conclusion and Recommendations. The prevalence of unintended pregnancy was relatively high in this study. Efforts should be made to scale up women's decision-making power on family planning services and give support to empower women economically. There is the need to promote family planning services to minimize unintended pregnancy and to decrease parity and family size.

Magnitude of unintended pregnancy and its determinants among childbearing age women in low and middle-income countries: evidence from 61 low and middle income countries

Background

Unintended pregnancy is one of the most serious health issues in low and Middle-Income Countries (LMICs), posing significant health, economic, and psychosocial costs to individuals and communities. However, there is limited evidence on the prevalence of unintended pregnancies and their determinants in LMICs. Hence, this study aimed to assess the prevalence of unintended pregnancy and its associated factors among childbearing-age women in LMICs.

Method

Data for the study were drawn from a recent 61 Demographic and Health Surveys (DHS) conducted in LMICs. A total sample of 187,347 mothers who gave birth in the five years preceding the survey was included. STATA version 16 was used to clean and analyze the data. Multilevel multivariable logistic regression was employed to identify individual and community-level factors of unintended pregnancy in LMICs. In the multivariable analysis, an adjusted odds ratio with a 95% confidence level was reported to indicate statistical association.

Results

The pooled magnitude of unintended pregnancy in LMICs was 26.46%% (95% CI: 25.30%, 27.62%), ranging from 19.25%% in Egypt to 61.71% in Bolivia. Working status (AOR =  1.03; 95% CI: 1.01, 1.06), having a husband with no education (AOR = 1.07; 95% CI: 1.00, 1.15), and primary education (AOR =  1.05; 95% CI: 1.01, 1.11), women from male-headed households (AOR = 1.04; 95% CI: 1.00, 1.08), media exposure (AOR = 1.05; 95% CI: 1.02, 1.08), unmet need for contraception (AOR = 1.05; 95% CI: 1.02, 1.08), distance from a health facility (AOR = 1.03; 95% CI: 1.00, 1.06) were significantly associated with unintended pregnancy.

Conclusion

Unintended pregnancy rates remain high in LMICs. Women whose husband has no education and primary education, women with media exposure, working status, women who live in a household headed by male, women with unmet need for contraception, and women with a big problem of distance to health facilities were variables that were significant predictors of unintended pregnancy. When attempting to minimize unintended pregnancy in LMICs, these factors need to be considered. Furthermore, most of these attempts should be driven by government entities in low and middle-income countries.

Trend, multivariate decomposition and spatial variations of unintended pregnancy among reproductive-age women in Ethiopia: evidence from demographic and health surveys

Background

The magnitude of unintended pregnancy is unacceptably high and more than half of it end up with abortions. This may limit lower and middle-income countries to achieve the sustainable development goal targets of reduction of neonatal and maternal mortalities. Evidence on trends and spatial distribution of unintended pregnancy is limited. Therefore, this study aimed to assess the trend, multivariate decomposition, and spatial variations of unintended pregnancy among reproductive-age women in Ethiopia from 2000 to 2016.

Methods

Ethiopian Demographic and Health Data of 2000 to 2016 were used. A total weighted sample of 30,780 reproductive-age women participated. A multivariate decomposition analysis was employed to identify factors contributing to the change in the rate of unintended pregnancy in Ethiopia for 20 years from (1996 to 2016). The concentration index and graph were used to assess wealth-related inequalities, whereas spatial analysis was done to identify the hotspot of unintended pregnancy in Ethiopia.

Results

The 20-year trend analysis showed that the magnitude of unintended pregnancy among reproductive-age women decreased by 13.19 percentage points (from 39.76% in 2000 to 26.57% in 2016 EDHS). About 84.97% of the overall decrement was due to the difference in coefficient of the variables, whereas the remaining 15.03% was due to the difference in composition of the respondent. The differences in coefficient of the variables were decomposed by living metropolitan cities, having previous terminated pregnancy, and not having exposure to media; whereas, the change due to the composition, was expressed by having a household size of 1–3, living in metropolitan cities, being multipara and grand para, being unmarried and having no terminated pregnancy. Moreover, unintended pregnancies were more clustered in Addis Ababa and disproportionately concentrated in the poor groups.

Conclusions

In Ethiopia, a substantial decrement in unintended pregnancy was observed in the past decade. More than four-fifths of this overall decrement was due to the difference in the coefficient of the variables. There was spatial clustering of unintended pregnancy in Ethiopia. A program intervention is needed for high-risk regions such as Addis Ababa. Health education and media campaign should perform for high-risk women such as those having terminated pregnancy, and professing Islam faith.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41182-022-00440-5.

Spatial distribution, prevalence, and determinants of unintended pregnancy among youth (15-24) in Ethiopia: Further analysis of Ethiopia Demographic and Health Survey

Objectives:

This study aimed to determine the spatial distribution, prevalence, and determinant factors of unintended pregnancy among youth in Ethiopia.

Methods:

Using the Ethiopian Demographic and Health Survey 2016, a total of 2446 pregnant women aged 15–24 in the last 5 years, including current pregnancy, were included in the study. The unintended pregnancy data were spatially visualized using coordinates for each respondent in the survey using ArcGIS 10.3. The Bernoulli model was used to identify the presence of purely spatial unintended pregnancy cluster using SaTScan software. Logistic regression analysis was fitted to determine factors associated with unintended pregnancy among youth.

Results:

Unintended pregnancy among youth had spatial variation across the country. Among youth, 20.5% (confidence interval: (19.0, 22.2)) of pregnancies were estimated to be unintended. Spatial scan statistics identified 72 primary clusters (log-likelihood ratio of 37.6, at p < 0.001) which were located in Addis Ababa, southern part of Amhara, northwest of Oromia and northeast of Southern Nations, Nationalities and Peoples Region. Age, region, marital status, occupation, sex of household head, and number of household members were the determinant factors of unintended pregnancy among youth in Ethiopia.

Conclusion:

The distribution of unintended pregnancy among youth in Ethiopia was nonrandom. Unintended pregnancy prevention strategies among youth need to be targeted on the identified factors. Hence, we recommend creating awareness on sexual and reproductive health rights with special priority to the identified hotspot areas (Amhara, Addis Ababa, Gambella, Northern part of Southern Nations, Nationalities and Peoples Region, and northwest of Oromia region) to reduce unintended pregnancy.

Prevalence and determinants of unintended pregnancy in Ethiopia: narrative synthesis and meta-analysis

BACKGROUND

Unintended pregnancy has enormous health, social and psychological impacts. Thus, comprehensive local evidence is required to guide interventions to prevent the occurrence and consequences of unintended pregnancy. This systematic review was conducted to examine the prevalence and determinants of unintended pregnancy in Ethiopia.

METHODS

The review was done following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Synthesis Without Meta-analysis (SWiM) guideline. Electronic databases including Medline/PubMed, Cochrane Library, CINAHL, Google scholar, and African journal online were searched to retrieve studies published from January 1/1990 to October 30/2020. Grey literatures were accessed from the online libraries of academic institutions in Ethiopia using the Google search engine. The qualities of the studies were assessed using Joanna Briggs Institute critical appraisal checklists. The retrieved studies were analyzed using STATA software version 13. The prevalence of unintended pregnancy was pooled using the random-effects model. The evidences on the determinants of unintended pregnancy were summarized in a narrative format. The statistical heterogeneity between studies was quantified by using the I-square values. Sub-group analysis and meta-regressions were done to identify the sources of heterogeneity among studies.

RESULTS

A total of 250 studies were retrieved of which 25 studies with 23,030 women were included for meta-analysis. Only 24 studies scrutinized the determinants of unintended pregnancy. The overall prevalence of unintended pregnancy was 30 % (95% CI; 27-33 %) with high heterogeneity among studies (I2 = 95.06 %). The pooled prevalence of unwanted and mistimed pregnancy was 12 &17% respectively. The study region was the source of heterogeneity whereas study setting, study year, sample size, and study quality score were not the sources of heterogeneity (p > 0.1). Unintended pregnancy was positively associated with a low level of education, poverty, multiparity, rural residence, extreme ages, being unmarried, lack of decision-making power, inaccessibility of health facilities, poor knowledge, and non-use of contraceptives.

CONCLUSIONS

The pooled prevalence of unintended pregnancy in Ethiopia was high. Empowering women and ensuring the accessibility of quality family planning services can reduce the prevailing high prevalence of unintended pregnancy. Interventions that target rural, poor, unmarried, multiparous, less-educated, and adolescent women are also important to avert untended pregnancy in Ethiopia.

Unintended Pregnancy During COVID-19 Pandemic Among Women Attending Antenatal Care in Northwest Ethiopia: Magnitude and Associated Factors

Background

COVID-19 pandemic has a great impact on the disruption of maternal health-care services. Family planning is one component of maternal health-care service that needs attention during this devastating time. Compromise on family planning services and the preventive strategies of COVID-19 might increase the burden of unintended pregnancy, but there is limited evidence that shows the magnitude of unintended pregnancy during the COVID-19 pandemic. Therefore, the objective of this study was to assess unintended pregnancy during the COVID-19 pandemic and its associated factors among women attending antenatal care in northwest Ethiopia.

Methods

This study was an institutional-based cross-sectional study, including 424 women attending antenatal care from November 12/2020 to December 12/2020. The study participants were selected using a systematic random sampling technique. A pretested questionnaire was used. Binary logistic regression (bivariable and multivariable) was employed. The adjusted odds ratio with a 95% confidence interval was used to declare statistically significant variables based on p<0.05 in the multivariable logistic regression model.

Results

The magnitude of unintended pregnancy during the COVID-19 pandemic among women attending antenatal care was found to be 47.17% (42.2–52.2%). Women did not expose to community education (AOR=2.2; 95% CI1.1–4), women with no bad obstetric history (AOR=2.3; 95% CI1.3–4.1), a woman was not the primary decision maker for family planning service (AOR=2.9; 95% CI 1.5–5.7), no complication during index pregnancy (AOR=5.4; 95% CI 2.2–13) and women with no health-care provider support (AOR=2.4, 95% CI1.4–3.9) were significantly associated with unintended pregnancy.

Conclusions

The magnitude of unintended pregnancy was found to be high. Community education about maternal health services including family planning, improving women’s decision-making power for maternal health-care services, giving emphasis on pregnancy-related complications with health-care provider support, and pregnant women with bad obstetric history were suggested to reduce the problem.