Prevalence of unintended pregnancy and associated factors among married women in west Belessa Woreda, Northwest Ethiopia, 2016

Reproductive Health, Volume 15, No. 1, Year 2018

Interpretation

Background: Unintended pregnancies can have adverse physical, mental, social, and economic outcomes. Illegal abortions and associated complications often follow unintended pregnancies and claim the lives of many women in developing countries. To better understand how unintended pregnancy impacts married women, this study aimed to assess the prevalence of unintended pregnancies and associated factors among married pregnant women in West Belessa woreda, Ethiopia. Methods: A community-based cross-sectional study was conducted from August to September 2015. A multistage stratified sampling technique was used to select nine kebeles, to participate in the study. A total of 619 married pregnant women were selected from these kebeles by the simple random sampling technique and data were collected with a structured questionnaire. Binary logistic regression analysis was used to identify factors associated with the unintended pregnancies. A p-value of < 0.05 in the multi-variable model was used to identify significance. Result: A total of 592 married pregnant women were surveyed regarding their intention to become pregnant. The prevalence of unintended pregnancy was 13.7%. Age at pregnancy (AOR: 15.2, 95% CI (1.9, 125.2)), history of stillbirth (AOR: 3.3, 95% CI (1.4, 7.9)), discussing pregnancy related issues with husbands (AOR: 2.3, 95% CI (1.1, 5.0)), making family planning decisions on their own (AOR: 0.4, (0.2, 0.8)), and making family planning decisions with their husbands (AOR: 95% CI 0.2 (0.1, 0.4)) were significantly associated with unintended pregnancies in this group. Conclusion: The magnitude of unintended pregnancy in the study area was low. Age at pregnancy, history of stillbirth and involvement of partners in making reproductive health choices were associated with unintended pregnancies. Empowering women to make family planning decisions and increasing partner involvement in reproductive health could decrease unintended pregnancies. A community-based cross-sectional study was conducted to assess unintended pregnancy and associated factors among married pregnant women in West Belessa Woreda, Northwest Ethiopia, from August to September 2015. West Belessa Woreda is in North Gondar Zone, Amhara National Regional State. The Woreda is located 784 km northwest of Addis Ababa, the capital of Ethiopia and 207 km from Bahir Dar, the regional capital. The Woreda has eight public health centers, 30 health posts, and two private clinics. Eighty-five percent of the population has access to health services. The district has ten health officers, three environmental health officers, 53 nurses, 12 pharmacy technicians, two pharmacists, six laboratory technicians and a technologist, two urban health extension workers, and 65 rural health extension workers that support the health system in the Woreda [15]. The study population consisted of married pregnant women living in West Belessa Woreda. Participants were selected randomly and married pregnant women who lived in the study area for at least 6 months were included and women who were seriously ill during the data collection period were excluded. The sample size was determined using a single population proportion formula considering the following assumptions of the prevalence of unintended pregnancy 26% [16], 95% confidence level, Z2α/2 = 1.96, and margin of error 5%. With a design effect of 2 and a 5% non-response rate, the total sample size needed was 619. A multistage stratified sampling technique was used to select the participants. According to information received from the Woreda health office, on average there were 100 to 300 pregnant women in each kebele (the smallest administrative unit). From 30 kebeles stratified into two (29 rural kebeles and one urban kebele), eight rural kebeles were selected by simple random sampling technique using the lottery method and the urban kebele was directly taken. The final sample size was distributed to each selected kebele proportional to the number of married pregnant women present (Fig. (Fig.1).1). A list of married pregnant women was provided by Health Extension Workers (HEW) working in the area and pregnant women were selected through a simple random sampling technique using computer-generated random numbers. Schematic presentation of sampling procedures The dependent variable was unintended pregnancy. The independent variables were the following: socio-demographic factors (age, educational status, family size, age at first marriage); institutional and organizational factors (supervision by HEW, supervision by Health Development Army (HDA), provision of family planning (FP), availability of transportation, delivery services); environmental and behavioral factors (distance of health facilities, accessibility of health facilities, knowledge of contraceptives, decision to use family planning, communication with husband about pregnancy), and maternal factors (comorbidity, gravidity, desired number of children, history of previous birth, power to decide on pregnancy, FP method utilization). Unintended pregnancy was defined as a pregnancy that was either unwanted or mistimed. Data were collected by interviewing married pregnant women using a standardized structured questionnaire. The questionnaire was first prepared in English and then translated into the local language Amharic and then translated back to English by a third party to check its consistency and conceptual equivalence. The Amharic version was pre-tested outside the study area. Trained clinical nurses collected the data under the supervision of trained public health professionals. The collected data were checked for completeness and consistency on a daily basis. Data entry, cleaning, and coding were done using Epi-Info version 7 and exported to SPSS version 20 for further analysis. Descriptive and summary statistics were done. Binary logistic regression analysis was used to identify determinants of unintended pregnancies. Variables which had a p-value of <=0.2 in the bivariable analysis were subsequently entered into a multivariable logistic regression analysis and variables with a p-value of < 0.05 in the multivariable model were identified as statistically significant.

AI Digest

Study Justification:

– Unintended pregnancies can have adverse physical, mental, social, and economic outcomes.
– Illegal abortions and associated complications often follow unintended pregnancies and claim the lives of many women in developing countries.
– Understanding the prevalence and associated factors of unintended pregnancies among married women is crucial for developing effective interventions and policies.

Highlights:

– A community-based cross-sectional study was conducted in West Belessa Woreda, Northwest Ethiopia.
– The prevalence of unintended pregnancy among married pregnant women was found to be 13.7%.
– Factors significantly associated with unintended pregnancies included age at pregnancy, history of stillbirth, discussing pregnancy-related issues with husbands, and involvement of partners in making family planning decisions.
– Empowering women to make family planning decisions and increasing partner involvement in reproductive health could decrease unintended pregnancies.

Recommendations:

– Promote comprehensive reproductive health education and awareness programs targeting married women.
– Strengthen family planning services and ensure accessibility to contraceptives.
– Encourage open communication between spouses regarding pregnancy-related issues.
– Provide support and counseling for women who have experienced stillbirth.
– Involve husbands and partners in family planning decision-making processes.

Key Role Players:

– Health officers
– Environmental health officers
– Nurses
– Pharmacy technicians
– Pharmacists
– Laboratory technicians and technologists
– Urban and rural health extension workers

Cost Items for Planning Recommendations:

– Reproductive health education and awareness programs
– Training and capacity building for health professionals
– Family planning services and contraceptives
– Counseling and support services for women who have experienced stillbirth
– Communication and outreach campaigns
– Monitoring and evaluation activities

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is relatively strong, but there are some areas for improvement. The study design, community-based cross-sectional study, is appropriate for assessing the prevalence of unintended pregnancy and associated factors. The sample size calculation and sampling technique are also well-described. However, there are some limitations to consider. The study relies on self-reported data, which may introduce recall bias. Additionally, the study only includes married pregnant women in one specific region of Ethiopia, which may limit the generalizability of the findings. To improve the strength of the evidence, future studies could consider using a larger and more diverse sample, including both married and unmarried women, and utilize objective measures of unintended pregnancy. Additionally, conducting longitudinal studies could provide more robust evidence on the factors associated with unintended pregnancies.

Abstract

A community-based cross-sectional study was conducted to assess unintended pregnancy and associated factors among married pregnant women in West Belessa Woreda, Northwest Ethiopia, from August to September 2015. West Belessa Woreda is in North Gondar Zone, Amhara National Regional State. The Woreda is located 784 km northwest of Addis Ababa, the capital of Ethiopia and 207 km from Bahir Dar, the regional capital. The Woreda has eight public health centers, 30 health posts, and two private clinics. Eighty-five percent of the population has access to health services. The district has ten health officers, three environmental health officers, 53 nurses, 12 pharmacy technicians, two pharmacists, six laboratory technicians and a technologist, two urban health extension workers, and 65 rural health extension workers that support the health system in the Woreda [15]. The study population consisted of married pregnant women living in West Belessa Woreda. Participants were selected randomly and married pregnant women who lived in the study area for at least 6 months were included and women who were seriously ill during the data collection period were excluded. The sample size was determined using a single population proportion formula considering the following assumptions of the prevalence of unintended pregnancy 26% [16], 95% confidence level, Z2α/2 = 1.96, and margin of error 5%. With a design effect of 2 and a 5% non-response rate, the total sample size needed was 619. A multistage stratified sampling technique was used to select the participants. According to information received from the Woreda health office, on average there were 100 to 300 pregnant women in each kebele (the smallest administrative unit). From 30 kebeles stratified into two (29 rural kebeles and one urban kebele), eight rural kebeles were selected by simple random sampling technique using the lottery method and the urban kebele was directly taken. The final sample size was distributed to each selected kebele proportional to the number of married pregnant women present (Fig. (Fig.1).1). A list of married pregnant women was provided by Health Extension Workers (HEW) working in the area and pregnant women were selected through a simple random sampling technique using computer-generated random numbers. Schematic presentation of sampling procedures The dependent variable was unintended pregnancy. The independent variables were the following: socio-demographic factors (age, educational status, family size, age at first marriage); institutional and organizational factors (supervision by HEW, supervision by Health Development Army (HDA), provision of family planning (FP), availability of transportation, delivery services); environmental and behavioral factors (distance of health facilities, accessibility of health facilities, knowledge of contraceptives, decision to use family planning, communication with husband about pregnancy), and maternal factors (comorbidity, gravidity, desired number of children, history of previous birth, power to decide on pregnancy, FP method utilization). Unintended pregnancy was defined as a pregnancy that was either unwanted or mistimed. Data were collected by interviewing married pregnant women using a standardized structured questionnaire. The questionnaire was first prepared in English and then translated into the local language Amharic and then translated back to English by a third party to check its consistency and conceptual equivalence. The Amharic version was pre-tested outside the study area. Trained clinical nurses collected the data under the supervision of trained public health professionals. The collected data were checked for completeness and consistency on a daily basis. Data entry, cleaning, and coding were done using Epi-Info version 7 and exported to SPSS version 20 for further analysis. Descriptive and summary statistics were done. Binary logistic regression analysis was used to identify determinants of unintended pregnancies. Variables which had a p-value of <=0.2 in the bivariable analysis were subsequently entered into a multivariable logistic regression analysis and variables with a p-value of < 0.05 in the multivariable model were identified as statistically significant.

Materials

N/A

Innovations

Based on the provided information, here are some potential innovations that can be used to improve access to maternal health:

1. Mobile Health (mHealth) Applications: Develop mobile applications that provide information on family planning, pregnancy care, and maternal health services. These apps can also send reminders for prenatal visits and provide access to telemedicine consultations.

2. Community Health Workers (CHWs): Train and deploy CHWs to provide education and counseling on family planning, prenatal care, and safe pregnancy practices. CHWs can also conduct home visits to monitor the health of pregnant women and refer them to health facilities when necessary.

3. Telemedicine: Establish telemedicine services to enable pregnant women in remote areas to consult with healthcare providers and receive prenatal care remotely. This can help overcome geographical barriers and improve access to specialized care.

4. Maternal Health Vouchers: Implement voucher programs that provide pregnant women with financial assistance to access maternal health services. These vouchers can cover the cost of prenatal visits, delivery, and postnatal care, ensuring that women can afford essential healthcare services.

5. Strengthening Health Facilities: Invest in improving the infrastructure and capacity of health facilities to provide quality maternal health services. This includes ensuring the availability of skilled healthcare providers, essential medical supplies, and equipment for safe deliveries.

6. Male Involvement Programs: Develop programs that encourage male partners to actively participate in maternal health decision-making and support their partners throughout pregnancy. This can help create a supportive environment for pregnant women and improve their access to care.

7. Health Education Campaigns: Conduct community-based health education campaigns to raise awareness about the importance of family planning, prenatal care, and safe pregnancy practices. These campaigns can address cultural and social barriers that prevent women from seeking maternal health services.

8. Integration of Services: Integrate maternal health services with other healthcare programs, such as HIV/AIDS prevention and treatment, to provide comprehensive care for pregnant women. This can improve efficiency and ensure that women receive all the necessary services in one location.

9. Task Shifting: Train and empower non-physician healthcare providers, such as nurses and midwives, to provide a wider range of maternal health services. This can help alleviate the shortage of skilled healthcare providers and improve access to care in underserved areas.

10. Public-Private Partnerships: Foster collaborations between the public and private sectors to improve access to maternal health services. This can involve leveraging private sector resources and expertise to expand service delivery and reach more women in need.

AI Innovations Description

Based on the study conducted in West Belessa Woreda, Northwest Ethiopia, the following recommendations can be developed into an innovation to improve access to maternal health:

1. Increase awareness and education: Develop and implement comprehensive educational programs to increase awareness about unintended pregnancies and the importance of family planning. This can include providing information on contraceptive methods, their effectiveness, and how to access them.

2. Strengthen reproductive health services: Improve the availability and accessibility of reproductive health services, including family planning, antenatal care, and postnatal care. This can be done by increasing the number of health facilities, trained healthcare providers, and ensuring the availability of necessary supplies and equipment.

3. Empower women in decision-making: Promote women’s empowerment by encouraging open communication between couples about pregnancy and family planning decisions. This can be achieved through community-based interventions that promote gender equality and encourage women to actively participate in decision-making processes.

4. Involve partners in reproductive health: Engage men as partners in reproductive health by providing them with information and resources on family planning and the importance of supporting their partners’ reproductive health choices. This can be done through targeted interventions that address men’s knowledge gaps and promote positive attitudes towards family planning.

5. Strengthen community support systems: Establish and strengthen community support systems that provide information, counseling, and referrals for maternal health services. This can involve training community health workers and volunteers to provide support and guidance to pregnant women and their families.

By implementing these recommendations, it is possible to improve access to maternal health services, reduce unintended pregnancies, and ultimately improve the health outcomes of women and their families in West Belessa Woreda, Northwest Ethiopia.

AI Innovations Methodology

Based on the provided information, here are some potential recommendations to improve access to maternal health:

1. Strengthening reproductive health education: Implement comprehensive reproductive health education programs that provide accurate information about family planning methods, pregnancy, and childbirth. This can help increase awareness and knowledge among women and their partners, enabling them to make informed decisions about their reproductive health.

2. Increasing availability of family planning services: Ensure that family planning services, including contraceptives, are easily accessible and affordable for women in the study area. This can be achieved by improving the distribution and availability of contraceptives in health centers and clinics, as well as training healthcare providers to offer quality family planning counseling.

3. Empowering women in decision-making: Promote women’s empowerment by encouraging their active participation in making reproductive health decisions. This can be done through community-based interventions that provide support and resources for women to have control over their reproductive choices.

4. Strengthening partner involvement: Encourage men to actively participate in reproductive health discussions and decision-making processes. This can be achieved through community awareness campaigns that promote the importance of male involvement in maternal health and family planning.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Baseline data collection: Collect data on the current status of access to maternal health services, including factors such as availability of family planning services, knowledge and awareness of reproductive health, and women’s involvement in decision-making.

2. Intervention implementation: Implement the recommended interventions, such as reproductive health education programs, improving availability of family planning services, and promoting women’s empowerment and partner involvement. Ensure that these interventions are implemented consistently and monitored closely.

3. Data collection after intervention: Collect data after the implementation of the interventions to assess any changes in access to maternal health services. This can include measuring indicators such as increased utilization of family planning services, improved knowledge and awareness among women, and increased involvement of women and their partners in decision-making.

4. Data analysis: Analyze the collected data to determine the impact of the interventions on improving access to maternal health. This can be done by comparing the baseline data with the post-intervention data and identifying any significant changes or improvements.

5. Evaluation and adjustment: Evaluate the effectiveness of the interventions and make any necessary adjustments or improvements based on the findings. This can involve identifying any challenges or barriers that may have hindered the desired impact and developing strategies to address them.

By following this methodology, it would be possible to simulate the impact of the recommended interventions on improving access to maternal health in the study area.

Author

Dima Health

Statistics:

Citations: 24

Identifiers:

DOI: 10.1186/s12978-018-0649-6

Research Areas:

Community Interventions, Disparities, Environmental, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants

Study Countries:

Ethiopia

Study Design:

Cross Sectional Study, Grounded Theory

Study Approach:

Quantitative

Participants Gender:

Female