Perinatal Mortality Magnitude, Determinants and Causes in West Gojam: Population-Based Nested Case-Control Study

PLoS ONE, Volume 11, No. 7, Year 2016

Interpretation

Introduction In Ethiopia, even if a significant reduction in child mortality is recorded recently, perinatal mortality rate is still very high. This study assessed the magnitude, determinants and causes of perinatal death in West Gojam zone, Ethiopia. Methods and materials A nested case control study was conducted on 102 cases (mothers who lost their newborns for perinatal death) and 204 controls (mothers who had live infants in the same year) among a cohort of 4097 pregnant mothers in three districts of the West Gojam zone, from Feb 2011 to Mar 2012. Logistic regression models were used to identify the independent determinant factors for perinatal mortality. The World Health Organization verbal autopsy instrument for neonatal death was used to collect mortality data and cause of death was assigned by a pediatrician and a neonatologist. Result Perinatal mortality rate was 25.1(95% CI 20.3, 29.9) per 1000 live and stillbirths. Primiparous mothers had a higher risk of losing their newborn babies for perinatal death than mothers who gave birth to five or more children (AOR = 3.15, 95% CI 1.03-9.60). Babies who were born to women who had a previous history of losing their baby to perinatal death during their last pregnancy showed higher odds of perinatal death than their counterparts (AOR = 9.55, 95% CI 4.67-19.54). Preterm newborns were more at risk for perinatal death (AOR = 9.44, 95%CI 1.81-49.22) than term babies. Newborns who were born among a household of more than two had a lesser risk of dying during the perinatal period as compared to those who were born among a member of only two. Paradoxically, home delivery was found to protect against perinatal death (AOR = 0.07 95% CI, 0.02-0.24) in comparison to institutional delivery. Bacterial sepsis, birth asphyxia and obstructed labour were among the leading causes of perinatal death. Conclusion Perinatal mortality rate remains considerably high, but proper maternal and child health care services can significantly decrease the burden. This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. We conducted a population-based nested case control study among a cohort of pregnant mothers in three districts of West Gojam zone (North Achefer, South Achefer and Mecha). The zone is located 500 kms away to the north of the capital city, Addis Ababa. Twenty four kebles (i.e. the smallest administrative unit) were selected from the three districts; 7 from North and South Achefer each and 10 from Mecha district. The selected three districts were among the highly populous districts of the zone with a total population count of 292,250 in Mecha, 155,863, in South Achefer and 173,211 in North Achefer districts [9]. Each kebele had one health post run by community Health Extension Workers (HEWs), there were two health centers in each district and Bahir Dar Hospital serves as a referral hospital for the people living in the three districts [9]. The cohort was established in mid 2010 by Maternal and Newborn Health in Ethiopia Partnership (MaNHEP) project in collaboration with Ethiopian Federal Ministry of Health, Emory University and Addis Ababa University. Pregnant mothers, in their third trimester, were enrolled in to the cohort after they were identified by trained community volunteers. Once in the cohort, mothers and their close family members (i.e. mothers, mother-in-laws, and husbands) received repeated training on care during pregnancy, labour and delivery by the volunteers. Following delivery they stayed in the cohort till they received postnatal care (PNC) mainly by HEWs [10]. Though the cohort was established in mid 2010 this study involved only pregnant mothers who gave birth between March 2011 and Feb 2012. Out of 4097 pregnant mothers who were followed in the cohort, all mothers (102) who lost their newborns for perinatal death were included in the study as cases. The controls were 204 mothers who gave birth to a live baby who at least survived the first 28 days after birth. The controls were randomly selected from the list of mothers with a known pregnancy outcome that were registered forming the sampling frame. To minimize the effect of geographic differences, controls were randomly selected from the gotes (i.e. smaller segment of a kebele) of the respective cases using the sampling frame which contained list of all mothers who gave birth in the three districts. Perinatal death was the dependent variable. The independent variables under the socio demographic category were age of the mother, marital status, educational status, occupation, size of the household, where the index neonates were not counted as members of the household and household wealth. Pregnancy, labour and delivery related variables such as, gestational age (calculated from the last menstrual period), birth spacing, place of delivery, parity, history of perinatal death, history of abortion (both spontaneous and medically induced termination of pregnancy before the 28th week of gestation) were included. Three high school complete female data collectors who were trained for 5 days, collected the data. Mothers who lost their newborns were interviewed, earliest forty days after death of the newborn to minimize recall bias. In addition we used female interviewers, so that mothers would be comfortable to discuss reproductive health matters that they may not be comfortable to discuss with men. Data was entered using EpiData version 3.1 statistical software. After entry the data was exported to SPSS version 19 statistical software for analysis. Perinatal, early neonatal and stillbirth rates were calculated. Bivariate analysis was conducted to measure the association between the dependent and individual independent variables. To control the effect of confounding variables multiple binary logistic regression models were used. Crude and adjusted OR with 95% CI were used to interpret findings of the bivariate and multivariate analysis. A total of 15 dichotomous household asset variables were involved to generate wealth index using Principal component analysis. According to the index, households were divided into quintiles ranging from the poorest 20% to the richest 20%. The cause of death assignment (CODA) was done by two physicians, a neonatologist and a pediatrician. In the process of CODA, the verbal autopsy (VA) data was reviewed and causes of death were assigned separately for every case. Then consensual diagnosis was reached after the two physicians discussed on their views concerning the causes of death for every case. Finally the physicians gave codes to the identified causes of death according to the ICD-10 coding system. Ethical clearance was obtained from Addis Ababa University, College of Health Sciences, School of Public Health, Research and Ethics Committee. Prior to every interview the purpose of the study was explained to the participants and written consent was obtained. Mothers who lost their newborns were interviewed after forty days of culturally appropriate grieving period.

AI Digest

Study Justification:

– Perinatal mortality rate in Ethiopia is still very high, despite a significant reduction in child mortality.
– Understanding the magnitude, determinants, and causes of perinatal death in specific regions, such as West Gojam, is crucial for developing effective interventions and improving maternal and child health care services.

Study Highlights:

– Perinatal mortality rate in West Gojam was found to be 25.1 per 1000 live and stillbirths.
– Primiparous mothers and those with a previous history of perinatal death had a higher risk of losing their newborns.
– Preterm newborns were more at risk for perinatal death than term babies.
– Home delivery was found to protect against perinatal death compared to institutional delivery.
– Bacterial sepsis, birth asphyxia, and obstructed labor were among the leading causes of perinatal death.

Study Recommendations:

– Proper maternal and child health care services can significantly decrease the burden of perinatal mortality.
– Interventions should focus on improving access to quality antenatal care, skilled birth attendance, and postnatal care.
– Strategies should be implemented to reduce preterm births and improve the management of complications such as bacterial sepsis, birth asphyxia, and obstructed labor.

Key Role Players:

– Ethiopian Federal Ministry of Health
– Maternal and Newborn Health in Ethiopia Partnership (MaNHEP) project
– Emory University
– Addis Ababa University
– Community Health Extension Workers (HEWs)
– Health centers and hospitals in West Gojam zone

Cost Items for Planning Recommendations:

– Training and capacity building for healthcare providers
– Infrastructure improvement in health facilities
– Equipment and supplies for maternal and child health care services
– Outreach programs and community engagement activities
– Monitoring and evaluation systems for tracking progress and impact
Please note that the provided information is based on the given description and may not include all details from the original study.

Strength of Evidence

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong because it is based on a population-based nested case-control study conducted on a cohort of pregnant mothers in West Gojam zone, Ethiopia. The study used logistic regression models to identify independent determinant factors for perinatal mortality. The study also collected mortality data using the World Health Organization verbal autopsy instrument and cause of death was assigned by a pediatrician and a neonatologist. However, to improve the evidence, the abstract could provide more information on the sample size and selection process, as well as the statistical significance of the findings.

Abstract

We conducted a population-based nested case control study among a cohort of pregnant mothers in three districts of West Gojam zone (North Achefer, South Achefer and Mecha). The zone is located 500 kms away to the north of the capital city, Addis Ababa. Twenty four kebles (i.e. the smallest administrative unit) were selected from the three districts; 7 from North and South Achefer each and 10 from Mecha district. The selected three districts were among the highly populous districts of the zone with a total population count of 292,250 in Mecha, 155,863, in South Achefer and 173,211 in North Achefer districts [9]. Each kebele had one health post run by community Health Extension Workers (HEWs), there were two health centers in each district and Bahir Dar Hospital serves as a referral hospital for the people living in the three districts [9]. The cohort was established in mid 2010 by Maternal and Newborn Health in Ethiopia Partnership (MaNHEP) project in collaboration with Ethiopian Federal Ministry of Health, Emory University and Addis Ababa University. Pregnant mothers, in their third trimester, were enrolled in to the cohort after they were identified by trained community volunteers. Once in the cohort, mothers and their close family members (i.e. mothers, mother-in-laws, and husbands) received repeated training on care during pregnancy, labour and delivery by the volunteers. Following delivery they stayed in the cohort till they received postnatal care (PNC) mainly by HEWs [10]. Though the cohort was established in mid 2010 this study involved only pregnant mothers who gave birth between March 2011 and Feb 2012. Out of 4097 pregnant mothers who were followed in the cohort, all mothers (102) who lost their newborns for perinatal death were included in the study as cases. The controls were 204 mothers who gave birth to a live baby who at least survived the first 28 days after birth. The controls were randomly selected from the list of mothers with a known pregnancy outcome that were registered forming the sampling frame. To minimize the effect of geographic differences, controls were randomly selected from the gotes (i.e. smaller segment of a kebele) of the respective cases using the sampling frame which contained list of all mothers who gave birth in the three districts. Perinatal death was the dependent variable. The independent variables under the socio demographic category were age of the mother, marital status, educational status, occupation, size of the household, where the index neonates were not counted as members of the household and household wealth. Pregnancy, labour and delivery related variables such as, gestational age (calculated from the last menstrual period), birth spacing, place of delivery, parity, history of perinatal death, history of abortion (both spontaneous and medically induced termination of pregnancy before the 28th week of gestation) were included. Three high school complete female data collectors who were trained for 5 days, collected the data. Mothers who lost their newborns were interviewed, earliest forty days after death of the newborn to minimize recall bias. In addition we used female interviewers, so that mothers would be comfortable to discuss reproductive health matters that they may not be comfortable to discuss with men. Data was entered using EpiData version 3.1 statistical software. After entry the data was exported to SPSS version 19 statistical software for analysis. Perinatal, early neonatal and stillbirth rates were calculated. Bivariate analysis was conducted to measure the association between the dependent and individual independent variables. To control the effect of confounding variables multiple binary logistic regression models were used. Crude and adjusted OR with 95% CI were used to interpret findings of the bivariate and multivariate analysis. A total of 15 dichotomous household asset variables were involved to generate wealth index using Principal component analysis. According to the index, households were divided into quintiles ranging from the poorest 20% to the richest 20%. The cause of death assignment (CODA) was done by two physicians, a neonatologist and a pediatrician. In the process of CODA, the verbal autopsy (VA) data was reviewed and causes of death were assigned separately for every case. Then consensual diagnosis was reached after the two physicians discussed on their views concerning the causes of death for every case. Finally the physicians gave codes to the identified causes of death according to the ICD-10 coding system. Ethical clearance was obtained from Addis Ababa University, College of Health Sciences, School of Public Health, Research and Ethics Committee. Prior to every interview the purpose of the study was explained to the participants and written consent was obtained. Mothers who lost their newborns were interviewed after forty days of culturally appropriate grieving period.

Materials

N/A

Innovations

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

1. Mobile health (mHealth) interventions: Develop mobile applications or text messaging services to provide pregnant women with important information about prenatal care, nutrition, and warning signs during pregnancy. This can help improve access to information and support for maternal health.

2. Community-based interventions: Implement community health worker programs to provide education, support, and referrals for pregnant women in rural areas. These community health workers can help bridge the gap between healthcare facilities and remote communities, ensuring that pregnant women receive the care they need.

3. Telemedicine: Use telemedicine technologies to connect pregnant women in remote areas with healthcare providers. This can allow for remote consultations, monitoring, and support, reducing the need for women to travel long distances for prenatal care.

4. Improved transportation infrastructure: Invest in improving transportation infrastructure, such as roads and transportation services, to ensure that pregnant women can easily access healthcare facilities for prenatal care, delivery, and emergency services.

5. Maternal waiting homes: Establish maternal waiting homes near healthcare facilities to provide a safe and comfortable place for pregnant women to stay as they approach their due dates. This can help ensure that women have timely access to skilled birth attendants and emergency obstetric care.

6. Strengthening healthcare systems: Invest in training and capacity-building for healthcare providers, particularly in rural areas, to improve the quality of maternal healthcare services. This can include training on emergency obstetric care, infection prevention, and respectful maternity care.

7. Financial incentives: Implement financial incentives, such as cash transfers or vouchers, to encourage pregnant women to seek prenatal care and deliver at healthcare facilities. This can help reduce financial barriers to accessing maternal healthcare.

8. 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 healthcare infrastructure and services in underserved areas.

9. Quality improvement initiatives: Implement quality improvement initiatives in healthcare facilities to ensure that pregnant women receive evidence-based, respectful, and culturally sensitive care. This can involve regular monitoring, feedback, and training for healthcare providers.

10. Health education campaigns: Launch targeted health education campaigns to raise awareness about the importance of prenatal care, skilled birth attendance, and postnatal care. These campaigns can help dispel myths and misconceptions, and encourage women to seek timely and appropriate care.

It is important to note that the specific context and needs of the community should be taken into consideration when implementing these innovations.

AI Innovations Description

The study titled “Perinatal Mortality Magnitude, Determinants and Causes in West Gojam: Population-Based Nested Case-Control Study” conducted in Ethiopia aimed to assess the magnitude, determinants, and causes of perinatal death in the West Gojam zone. The study involved a cohort of pregnant mothers in three districts of the zone and collected data using a nested case-control design.

The study found that the perinatal mortality rate in the study area was 25.1 per 1000 live and stillbirths. Several factors were identified as determinants of perinatal mortality, including primiparity (mothers giving birth for the first time), previous history of perinatal death, preterm birth, and household size. Surprisingly, home delivery was found to be protective against perinatal death compared to institutional delivery.

The leading causes of perinatal death identified in the study were bacterial sepsis, birth asphyxia, and obstructed labor. The study concluded that although the perinatal mortality rate in the area was high, proper maternal and child health care services could significantly reduce this burden.

Based on these findings, a recommendation to improve access to maternal health and reduce perinatal mortality could be to focus on the following strategies:

1. Strengthening antenatal care services: Providing comprehensive antenatal care to pregnant women, including regular check-ups, screening for high-risk pregnancies, and education on healthy behaviors during pregnancy.

2. Enhancing skilled birth attendance: Ensuring that all pregnant women have access to skilled birth attendants during delivery, whether at home or in health facilities, to reduce the risk of complications and improve outcomes.

3. Improving postnatal care: Ensuring that mothers and newborns receive appropriate postnatal care, including follow-up visits, breastfeeding support, and screening for postpartum complications.

4. Promoting community-based interventions: Engaging community health workers and volunteers to provide education and support to pregnant women and their families, particularly in remote or underserved areas.

5. Strengthening referral systems: Ensuring that pregnant women with high-risk pregnancies or complications have access to timely and appropriate referral services to higher-level health facilities.

6. Addressing social determinants of health: Implementing interventions to address factors such as poverty, education, and gender inequality that contribute to poor maternal and child health outcomes.

By implementing these recommendations, it is possible to improve access to maternal health services, reduce perinatal mortality, and ultimately improve the health and well-being of mothers and newborns in the West Gojam zone and similar settings.

AI Innovations Methodology

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

1. Strengthening antenatal care services: Increase the availability and accessibility of antenatal care services, including regular check-ups, screenings, and health education for pregnant women. This can help identify and address any potential risks or complications early on.

2. Enhancing postnatal care: Improve postnatal care services to ensure that mothers and newborns receive appropriate care and support after delivery. This can include providing breastfeeding support, newborn care education, and monitoring for any postpartum complications.

3. Promoting institutional delivery: Encourage more women to give birth in healthcare facilities by addressing barriers such as cost, transportation, and cultural beliefs. This can help ensure that skilled healthcare professionals are available to manage any complications that may arise during childbirth.

4. Strengthening referral systems: Improve the coordination and effectiveness of referral systems between different levels of healthcare facilities. This can help ensure that pregnant women and newborns receive timely and appropriate care, especially in cases where higher-level care is needed.

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

1. Define the indicators: Identify specific indicators that will be used to measure the impact of the recommendations, such as the percentage of pregnant women receiving antenatal care, the percentage of institutional deliveries, or the perinatal mortality rate.

2. Collect baseline data: Gather data on the current status of maternal health access and outcomes in the target population. This can include information on the utilization of antenatal and postnatal care services, place of delivery, and perinatal mortality rates.

3. Develop a simulation model: Create a simulation model that incorporates the identified recommendations and their potential impact on the selected indicators. This model should take into account factors such as population size, healthcare infrastructure, and resource availability.

4. Input data and run simulations: Input the baseline data into the simulation model and run multiple simulations to estimate the potential impact of the recommendations. This can involve adjusting the input parameters to reflect different scenarios or interventions.

5. Analyze results: Analyze the simulation results to assess the potential impact of the recommendations on improving access to maternal health. This can include comparing the simulated outcomes to the baseline data and identifying any significant changes or improvements.

6. Validate and refine the model: Validate the simulation model by comparing the simulated outcomes to real-world data, if available. Refine the model based on the validation results and any additional insights gained from the analysis.

7. Communicate findings: Present the findings of the simulation study to relevant stakeholders, such as policymakers, healthcare providers, and community members. Use the results to advocate for the implementation of the recommended interventions and to inform decision-making processes.

It is important to note that the methodology described above is a general framework and may need to be adapted based on the specific context and available data.

Author

Dima Health

Statistics:

Citations: 21

Identifiers:

DOI: 10.1371/journal.pone.0159390

Research Areas:

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

Study Countries:

Ethiopia

Study Design:

Case-Control Study, Cohort Study, Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Male & Female