Determinants of depressive symptoms among postpartum mothers: a cross-sectional study in Ethiopia

BMJ Open, Volume 12, No. 9, Year 2022

Interpretação

Objective This study aims to assess the determinants of depressive symptoms among postpartum mothers. Design A community-based cross-sectional study was conducted. Setting Ten randomly selected rural kebeles of Meket district of Ethiopia. Participants A random sample of 232 mothers with infants 5-10 months was included in this study. Data analysis Forward multivariable logistic regression analysis. Results The factors significantly associated with increased odds of maternal postpartum depressive symptoms were: moderate (adjusted OR (AOR) 4.44, 95% CI 1.34 to 14.72) and severe (AOR 12.98, 95% CI 5.24 to 32.14) household food insecurity; infant underweight (AOR 2.99, 95% CI: 1.21 to 7.37) and infant acute respiratory infection (ARI) (AOR 7.0, 95% CI: 3.09 to 15.99). Maternal education, workload and age, household socioeconomic status, distance to the health facility, and child stunting, diarrhoea and fever were not significantly associated with postpartum depressive symptoms in adjusted logistic regression. Conclusion Household food insecurity, infant ARI and infant underweight had significant associations with postpartum depressive symptoms. Therefore, interventions that address infant nutrition and health and household food insecurity within the framework of the productive safety net programmes (PSNPs) as well as programmes focused on preventing, detecting and solving maternal mental health challenges may be helpful to improve maternal mental well-being and promote graduation from the PSNP. A community-based cross-sectional study was conducted in rural areas of northern Ethiopia from 1 March to 30 April 2018. The region had a high prevalence of stunting (46%) in under 5 children. The study area is characterised by a rocky landscape with inhabited mountains reaching from 1000 to 3600 m above sea level. The study participants were 232 mother–infant (5–10 months old) pairs who had participated in an earlier study on maternal depression and child undernutrition.4 All were PSNP beneficiaries. Study participants were selected using multistage sampling techniques. Of the 27 kebeles (the lowest administrative unit in Ethiopia) in the district, 10 were randomly selected. A listing of PSNP4 households with infants 5–10 months of age and who had lived at least 6 months in the selected kebeles was completed from the database that was compiled by the research team including local healthcare workers prior to actual data collection. The number of mother–child pairs to be selected was proportionally allocated to 10 kebeles based on the total number of the households with children aged 5–10 months old in each kebele. The study participants were then selected by systematic random sampling from the sampling frame. Sociodemographic data were collected using pretested interviewer-administered questionnaires. Infant illnesses were reported by the mother for the 2 weeks prior to data collection. The infant illnesses assessed were: (a) acute respiratory infections (ARIs) defined as cough with associated difficulty breathing; (b) diarrhoea, defined as three or more loose or fluid stools per day; and (c) fever. The Household Food Insecurity Access Scale was used to assess household food insecurity19 during the 4 weeks preceding the survey. Based on their scores, households were categorised as: food secure, mildly food insecure, moderately food insecure and severely food insecure. Infant length was measured to the nearest 0.1 cm using a portable wooden recumbent length board with a fixed head and sliding foot piece, and weight was measured with an electronic scale (UNICEF Seca 770) with light clothing to the nearest 0.01 kg. Anthropometric status was calculated as length-for-age z-score, weight-for-length z-score and weight-for-age z-score. Maternal depression was assessed using the Edinburgh Postnatal Depression Scale (EPDS).20 Scores ≥13 were used to classify mothers as depressed, and these results have been published.4 The EPDS has been validated in Ethiopian mothers21 and also used for another study in Ethiopia.22 The EPDS has also been used to assess PPD in several other sub-Saharan African countries23 24 and has shown wide utility as a screening scale for maternal depression. Data were coded and entered into SPSS V.20 by the principal investigator. Categorical data are presented by descriptive statistics (frequency and percentage); whereas range, mean and SD are used to present continuous variables. Wealth index was computed using principal component analysis as a composite indicator of living standard based on ownership of selected household assets, size of agricultural land, number of livestock, materials used for housing construction, ownership of improved water and sanitation facilities and household possessions (radio, television, mobile phone, table). Initially, 21 variables were considered for the analysis. During analysis, four variables (use of electricity service, ownership of improved water and sanitation facilities and size of agricultural land) were dropped as their communality scores were less than 50%. Ultimately, six principal components having eigen values greater than one were identified. The components explained 70.6% of the total variance which was above the recommended minimum value of 60%. Wealth index values were calculated by summing up the scores for the six components. Ultimately, the three categories (low, medium and high) were generated by splitting the wealth index values into three equal classes. The X2 test was used to assess the associations of maternal and household characteristics and infant anthropometric status with maternal depression. When significant associations were found, crude ORs (CORs) were computed to determine the strength of bivariate association. Forward multivariable logistic regression analysis was used to determine the most important determinants of maternal depression. Statistical significance was set at p<0.05. Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

AI Digest

Study Justification:

This study aimed to assess the determinants of depressive symptoms among postpartum mothers in Ethiopia. The justification for this study is to identify factors that contribute to postpartum depressive symptoms in order to develop interventions that can improve maternal mental well-being and promote graduation from the productive safety net programs (PSNPs).

Study Highlights:

The study found that household food insecurity, infant acute respiratory infection (ARI), and infant underweight were significantly associated with increased odds of maternal postpartum depressive symptoms. However, factors such as maternal education, workload and age, household socioeconomic status, distance to the health facility, and child stunting, diarrhea, and fever were not significantly associated with postpartum depressive symptoms.

Recommendations for Lay Readers:

Based on the study findings, it is recommended to implement interventions that address infant nutrition and health, as well as household food insecurity within the framework of the PSNPs. Additionally, programs focused on preventing, detecting, and solving maternal mental health challenges should be implemented to improve maternal mental well-being.

Recommendations for Policy Makers:

Policy makers should consider integrating interventions for infant nutrition and health, as well as household food insecurity, into existing programs such as the PSNPs. Furthermore, policies and programs should be developed to address maternal mental health challenges and promote the well-being of postpartum mothers.

Key Role Players:

To address the recommendations, key role players may include policymakers, government agencies responsible for health and social welfare, healthcare providers, community health workers, non-governmental organizations (NGOs) working in maternal and child health, and community leaders.

Cost Items for Planning Recommendations:

While the actual cost is not provided, budget items to consider for planning the recommendations may include funding for training healthcare providers and community health workers, implementing nutrition and health interventions, conducting awareness campaigns on maternal mental health, developing and disseminating educational materials, and monitoring and evaluation of the interventions.

Força da prova

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is rated 8 because it provides specific details about the study design, setting, participants, data analysis, and results. However, it does not mention the sample size calculation or any limitations of the study. To improve the evidence, the abstract could include information about the sample size calculation and potential limitations of the study, such as selection bias or generalizability issues.

Resumo

A community-based cross-sectional study was conducted in rural areas of northern Ethiopia from 1 March to 30 April 2018. The region had a high prevalence of stunting (46%) in under 5 children. The study area is characterised by a rocky landscape with inhabited mountains reaching from 1000 to 3600 m above sea level. The study participants were 232 mother–infant (5–10 months old) pairs who had participated in an earlier study on maternal depression and child undernutrition.4 All were PSNP beneficiaries. Study participants were selected using multistage sampling techniques. Of the 27 kebeles (the lowest administrative unit in Ethiopia) in the district, 10 were randomly selected. A listing of PSNP4 households with infants 5–10 months of age and who had lived at least 6 months in the selected kebeles was completed from the database that was compiled by the research team including local healthcare workers prior to actual data collection. The number of mother–child pairs to be selected was proportionally allocated to 10 kebeles based on the total number of the households with children aged 5–10 months old in each kebele. The study participants were then selected by systematic random sampling from the sampling frame. Sociodemographic data were collected using pretested interviewer-administered questionnaires. Infant illnesses were reported by the mother for the 2 weeks prior to data collection. The infant illnesses assessed were: (a) acute respiratory infections (ARIs) defined as cough with associated difficulty breathing; (b) diarrhoea, defined as three or more loose or fluid stools per day; and (c) fever. The Household Food Insecurity Access Scale was used to assess household food insecurity19 during the 4 weeks preceding the survey. Based on their scores, households were categorised as: food secure, mildly food insecure, moderately food insecure and severely food insecure. Infant length was measured to the nearest 0.1 cm using a portable wooden recumbent length board with a fixed head and sliding foot piece, and weight was measured with an electronic scale (UNICEF Seca 770) with light clothing to the nearest 0.01 kg. Anthropometric status was calculated as length-for-age z-score, weight-for-length z-score and weight-for-age z-score. Maternal depression was assessed using the Edinburgh Postnatal Depression Scale (EPDS).20 Scores ≥13 were used to classify mothers as depressed, and these results have been published.4 The EPDS has been validated in Ethiopian mothers21 and also used for another study in Ethiopia.22 The EPDS has also been used to assess PPD in several other sub-Saharan African countries23 24 and has shown wide utility as a screening scale for maternal depression. Data were coded and entered into SPSS V.20 by the principal investigator. Categorical data are presented by descriptive statistics (frequency and percentage); whereas range, mean and SD are used to present continuous variables. Wealth index was computed using principal component analysis as a composite indicator of living standard based on ownership of selected household assets, size of agricultural land, number of livestock, materials used for housing construction, ownership of improved water and sanitation facilities and household possessions (radio, television, mobile phone, table). Initially, 21 variables were considered for the analysis. During analysis, four variables (use of electricity service, ownership of improved water and sanitation facilities and size of agricultural land) were dropped as their communality scores were less than 50%. Ultimately, six principal components having eigen values greater than one were identified. The components explained 70.6% of the total variance which was above the recommended minimum value of 60%. Wealth index values were calculated by summing up the scores for the six components. Ultimately, the three categories (low, medium and high) were generated by splitting the wealth index values into three equal classes. The X2 test was used to assess the associations of maternal and household characteristics and infant anthropometric status with maternal depression. When significant associations were found, crude ORs (CORs) were computed to determine the strength of bivariate association. Forward multivariable logistic regression analysis was used to determine the most important determinants of maternal depression. Statistical significance was set at p<0.05. Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Materiais

Inovações

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

1. Mobile Health (mHealth) Applications: Develop and implement mobile applications that provide information and support for maternal mental health, infant nutrition, and household food security. These apps can provide educational resources, reminders for healthcare appointments, and access to telemedicine services.

2. Community Health Workers: Train and deploy community health workers to provide support and education to postpartum mothers in rural areas. These workers can conduct home visits, provide counseling, and connect mothers to local resources and services.

3. Integrated Care Programs: Implement integrated care programs that address both maternal mental health and infant nutrition. These programs can provide comprehensive support, including mental health screenings, nutrition counseling, and access to food assistance programs.

4. Telemedicine Services: Establish telemedicine services to provide remote consultations and support for postpartum mothers. This can help overcome barriers such as distance to health facilities and improve access to healthcare professionals.

5. Strengthening Productive Safety Net Programs (PSNPs): Collaborate with PSNPs to incorporate interventions that address infant nutrition and health, as well as household food insecurity. This can help improve maternal mental well-being and promote graduation from the PSNP.

It’s important to note that these recommendations are based on the specific findings and context of the study mentioned. Further research and evaluation would be needed to determine the effectiveness and feasibility of these innovations in improving access to maternal health in other settings.

AI Innovations Description

The study mentioned aims to assess the determinants of depressive symptoms among postpartum mothers in rural areas of Ethiopia. The factors found to be significantly associated with increased odds of maternal postpartum depressive symptoms were moderate and severe household food insecurity, infant underweight, and infant acute respiratory infection (ARI). Other factors such as maternal education, workload and age, household socioeconomic status, distance to the health facility, and child stunting, diarrhea, and fever were not significantly associated with postpartum depressive symptoms.

Based on the findings of this study, a recommendation to improve access to maternal health and address postpartum depressive symptoms would be to implement interventions that focus on infant nutrition and health, as well as household food insecurity. These interventions could be integrated into existing programs such as the productive safety net programs (PSNPs) in Ethiopia. Additionally, programs that aim to prevent, detect, and address maternal mental health challenges should be implemented to improve maternal mental well-being. By addressing these factors, it is expected that maternal health outcomes will improve, leading to better overall maternal well-being and potentially graduation from the PSNPs.

AI Innovations Methodology

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

1. Strengthening nutrition programs: Given the association between infant underweight and postpartum depressive symptoms, it is important to prioritize nutrition interventions for both mothers and infants. This can include promoting exclusive breastfeeding, providing nutritional supplements, and offering counseling on proper infant feeding practices.

2. Integrating mental health services: Implementing programs that focus on preventing, detecting, and addressing maternal mental health challenges can significantly improve maternal well-being. This can involve training healthcare providers to identify and manage postpartum depression, as well as providing counseling and support services for affected mothers.

3. Enhancing household food security: Household food insecurity was found to be significantly associated with postpartum depressive symptoms. Interventions that address food insecurity, such as the productive safety net programs (PSNPs), can help improve maternal mental well-being. This can include providing food assistance, promoting income-generating activities, and improving agricultural practices.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Baseline data collection: Gather information on the current state of maternal health access, including indicators such as maternal mortality rates, availability of healthcare facilities, and utilization of maternal health services.

2. Define key variables: Identify the key variables that will be used to measure the impact of the recommendations. This can include indicators related to nutrition, mental health, household food security, and maternal health outcomes.

3. Intervention implementation: Implement the recommended interventions in selected communities or regions. This can involve training healthcare providers, distributing nutritional supplements, implementing food security programs, and integrating mental health services into existing healthcare systems.

4. Data collection post-intervention: Collect data after the interventions have been implemented to assess changes in the identified variables. This can involve surveys, interviews, and medical record reviews to gather information on maternal health outcomes, utilization of services, and changes in nutrition and mental health indicators.

5. Data analysis: Analyze the collected data using appropriate statistical methods. Compare the pre-intervention and post-intervention data to determine the impact of the recommendations on improving access to maternal health. This can include calculating changes in maternal health indicators, assessing the utilization of services, and identifying any significant associations between the interventions and the outcomes.

6. Interpretation and dissemination: Interpret the findings of the analysis and communicate the results to relevant stakeholders, including policymakers, healthcare providers, and community members. This can help guide future interventions and policies aimed at improving access to maternal health.

It is important to note that the methodology described above is a general framework and can be adapted based on the specific context and resources available for the study.

Autor

Dima Health

Identifiers:

DOI: 10.1136/bmjopen-2021-058633

Research Areas:

Community Interventions, Disparities, Environmental, Food Security, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Mental Health, Quality of Care, Social Determinants

Study Countries:

Ethiopia

Study Design:

Cross Sectional Study, Grounded Theory

Study Approach:

Quantitative

Partilhar isto: