Maternal depression is associated with child undernutrition: A cross-sectional study in Ethiopia

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Study Justification:
– Child undernutrition is a significant issue in low- and middle-income countries, leading to health and economic losses.
– Maternal depression has received little attention as a potential contributor to child undernutrition.
– This study aims to assess the association between maternal postpartum depression symptoms and infant stunting in northern Ethiopia.
Highlights:
– The study was conducted in rural areas of northern Ethiopia, where child undernutrition is prevalent.
– A total of 232 mother-infant pairs were included in the study.
– Maternal depression was found to be significantly associated with inappropriate complementary feeding and stunting.
– Improving complementary feeding practices, along with addressing maternal depression, is crucial for preventing stunting.
Recommendations:
– Efforts should be made to improve complementary feeding practices in the study area and other similar settings.
– Interventions should integrate strategies to address maternal depression, which can improve child feeding and caring practices.
Key Role Players:
– Researchers and experts in child nutrition and maternal mental health.
– Local government officials and policymakers.
– Healthcare providers and community health workers.
– Non-governmental organizations (NGOs) working in the field of maternal and child health.
Cost Items for Planning Recommendations:
– Training and capacity building for healthcare providers and community health workers.
– Development and implementation of educational materials and programs on complementary feeding and maternal mental health.
– Monitoring and evaluation of interventions.
– Awareness campaigns and community outreach activities.
– Collaboration with NGOs and other stakeholders.
– Research and data collection for ongoing monitoring and evaluation.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong. The study design is a community-based cross-sectional study, which provides valuable information on the association between maternal depression and child undernutrition. The sample size is relatively small (n = 232), which may limit the generalizability of the findings. To improve the strength of the evidence, future studies could consider using a larger sample size and a longitudinal design to establish causality. Additionally, conducting the study in multiple locations and including diverse populations would enhance the external validity of the findings.

Child undernutrition is widespread in low- and middle-income countries (LMIC) and is associated with health and economic losses. Undernutrition is estimated to contribute to 3.1 million deaths per year in children less than 5 years of age. A complex causal and contextual factors contributing to child undernutrition have been assessed, but maternal depression, which could contribute to child undernutrition by interfering with the mother’s child caring practice and ability, has been received little attention. The objective of this study was to assess the association between maternal postpartum depression symptoms and infant (5–10 months of age) stunting in northern Ethiopia. A community-based cross-sectional study was conducted among mother–infant pairs (n = 232) between March and April 2018. Through interviewer-administrated questionnaire, information on sociodemographic variables were collected, and maternal depression symptoms were assessed using the Edinburgh Postnatal Depression Scale (EPDS≥13). Infants’ length and weight were measured and converted to length and weight for age Z scores using the WHO growth standards. Breastfeeding was a norm, but the adequacy of complementary feeding practice was sub-optimal. Only 25% of the infants met the minimum meal frequency (MMF), less than 10% met the minimum dietary diversity (MMD; 9%) or minimum acceptable diet (7%). Maternal depression was prevalent (22.8%) and was significantly associated with inappropriate complementary feeding and stunting (P 30 min), washing clothes, land preparation, weeding, manual mowing, threshing, grinding and pounding grain and terracing. The final components which explained 70.6% of the total variance were retained and women were classified into three categories (low, medium and heavy) of workload based on their scores. Data on infant feeding practices were assessed using the WHO IYCF indicators (WHO, 2008). Early initiation of breastfeeding, exclusive and continued breastfeeding, introduction to complementary foods and complementary feeding indicators such as MMF, MMD and minimum adequate diet were assessed. Foods consumed in the 24 h prior the survey were categorized into the following seven food groups to calculate the dietary diversity score: (i) grains, roots and tubers; (ii) legumes and nuts; (iii) dairy products; (iv) eggs; (v) flesh foods (meat, fish, poultry and organ meats); (vi) vitamin A‐rich fruits and vegetables; and (vii) other fruits and vegetables. The proportion of breastfed infants meeting the MMF (≥3) and the MMD score (≥4) was calculated. The place of delivery of the infant and immunization status was recalled by the mother, and whenever available was confirmed by checking the immunization cards. Infant illness (morbidity) and healthcare‐seeking practices of the mother were assessed through maternal recall of signs and symptoms related to acute respiratory infections, diarrhoea, cough and/or cold and fever over the 2 weeks prior the survey. Maternal depression was assessed using the Edinburgh Postnatal Depression Scale (EPDS) (Cox, Holden, & Sagovsky, 1987) which included 10 items. Mothers rated the extent to which each item matched their feelings during the 7 days prior to the survey. Possible scores ranges from 0 to 30, with higher scores indicating greater severity of depression. A score of 13 and above indicated the postnatal depression. The EPDS has been used as a screening tool for detecting postnatal depression in different cultures (Kakyo et al., 2012) and has been used in several African countries (Madeghe, Kimani, Stoep, Nicodimos, & Kumar, 2016; Ukaegbe, Iteke, Bakare, & Agbata, 2012; Yator, Mathai, der Stoep, Rao, & Kumar, 2016). A validation study in Ethiopia also demonstrated the acceptability and utility of the Amharic version for use as a screening tool for postnatal depression (Tesfaye, Hanlon, Wondimagegn, & Alem, 2009). The internal consistency measured by Cronbach’s alpha (0.80) was acceptable. Data were checked, coded and entered into SPSS, v. 20, for analysis. Categorical data were analysed by descriptive statistics (frequency and percentage), whereas range, mean and standard deviations were used to present continuous variables. The normal distribution of the data was checked with the Kolmogorov‐Smirnov test (Mishra et al., 2019). Bivariate analyses were conducted, and all variables with P < .25 were included in multivariate logistic regression. The model fit was checked using the Hosmer–Lemeshow goodness of fit test. Statistical significance was considered at the 95% confidence interval, and both crude and adjusted odds ratios are reported.

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

1. Integrated Mental Health Services: Implementing mental health screening and support services within maternal health programs can help identify and address maternal depression, which has been shown to be associated with child undernutrition. This could involve training healthcare providers to assess and manage maternal mental health, as well as providing counseling and support services for mothers experiencing depression.

2. Community-Based Interventions: Engaging community health workers and volunteers to provide education and support to mothers can help improve maternal and child health outcomes. These interventions could include home visits to provide information on proper infant feeding and caring practices, as well as offering emotional support and referrals for mental health services.

3. Strengthening Complementary Feeding Practices: Developing and implementing targeted interventions to improve complementary feeding practices can help prevent stunting and improve child nutrition. This could involve providing education and resources on appropriate complementary foods, meal frequency, and dietary diversity, as well as addressing barriers to accessing nutritious foods.

4. Mobile Health (mHealth) Solutions: Utilizing mobile technology to deliver maternal health information and support can help overcome barriers to accessing healthcare services. This could include mobile apps or text messaging programs that provide educational resources, reminders for healthcare appointments, and support for managing maternal depression.

5. Collaborative Care Models: Implementing collaborative care models that involve coordination between healthcare providers, mental health specialists, and community organizations can help ensure comprehensive and integrated care for mothers and their infants. This could involve establishing referral networks, care coordination protocols, and regular communication between different healthcare providers involved in maternal and child health.

These innovations have the potential to improve access to maternal health and address the association between maternal depression and child undernutrition. However, it is important to note that the specific implementation and effectiveness of these innovations would need to be further researched and evaluated in the context of the local healthcare system and community needs.
AI Innovations Description
Based on the description provided, the following recommendation can be developed into an innovation to improve access to maternal health:

1. Integrated Approach: Develop an integrated approach that combines efforts to improve complementary feeding practices with interventions to address maternal depression. This approach should focus on improving child feeding and caring practices to effectively prevent stunting.

2. Training and Education: Provide training and education to healthcare providers and community health workers on the identification and management of maternal depression. This will help ensure that women experiencing postpartum depression receive appropriate support and treatment.

3. Screening and Referral: Implement routine screening for maternal depression during antenatal and postnatal care visits. This will help identify women at risk and facilitate timely referral to mental health services for further assessment and treatment.

4. Community Engagement: Engage community leaders, organizations, and stakeholders to raise awareness about maternal depression and its impact on child undernutrition. This can be done through community-based campaigns, support groups, and educational sessions to reduce stigma and promote help-seeking behaviors.

5. Telemedicine and Digital Solutions: Explore the use of telemedicine and digital solutions to provide remote mental health support to women in rural areas where access to healthcare services is limited. This can include tele-counseling, mobile applications, and online resources for self-help and guidance.

6. Collaboration and Partnerships: Foster collaboration and partnerships between healthcare providers, government agencies, non-governmental organizations, and other stakeholders to ensure a coordinated and comprehensive approach to improving access to maternal health services. This can involve sharing resources, expertise, and best practices to maximize impact and reach.

By implementing these recommendations, it is possible to develop innovative solutions that address the complex factors contributing to child undernutrition and improve access to maternal health in low- and middle-income countries like Ethiopia.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations to improve access to maternal health:

1. Implement maternal mental health screening programs: Given the association between maternal depression and child undernutrition, it is important to identify and address maternal mental health issues. Implementing routine screening programs for maternal depression can help identify at-risk mothers and provide appropriate support and treatment.

2. Strengthen community-based healthcare services: Enhancing access to maternal health services at the community level can improve the overall accessibility and utilization of healthcare. This can include establishing more health posts or clinics in rural areas, training community health workers to provide basic maternal health services, and promoting awareness and education about maternal health within the community.

3. Improve complementary feeding practices: As inadequate complementary feeding practices were identified as a contributing factor to child undernutrition, interventions should focus on improving the quality and quantity of complementary foods provided to infants. This can be achieved through community-based education programs, counseling sessions for mothers, and support for local food production and availability.

4. Enhance social support networks: Building strong social support networks for mothers can help alleviate the burden of maternal depression and improve access to maternal health services. This can involve establishing support groups, providing counseling services, and promoting community engagement and involvement in maternal health initiatives.

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 reflect access to maternal health, such as the number of women receiving antenatal care, the percentage of women delivering in a healthcare facility, or the rate of maternal depression screening.

2. Collect baseline data: Gather data on the current status of the selected indicators in the target population. This can be done through surveys, interviews, or existing data sources.

3. Develop a simulation model: Create a model that incorporates the potential impact of the recommendations on the selected indicators. This can be a mathematical model or a computer-based simulation.

4. Input intervention parameters: Specify the parameters of the interventions, such as the coverage of maternal mental health screening programs, the number of community-based healthcare services to be established, or the level of improvement in complementary feeding practices.

5. Run simulations: Use the simulation model to project the potential impact of the interventions on the selected indicators. This can involve running multiple scenarios with different intervention parameters to assess the range of possible outcomes.

6. Analyze results: Evaluate the simulation results to determine the potential impact of the recommendations on improving access to maternal health. This can include comparing the projected outcomes with the baseline data and identifying any significant changes or improvements.

7. Refine and validate the model: Continuously refine and validate the simulation model based on feedback, additional data, and real-world observations. This will help ensure the accuracy and reliability of the simulation results.

By following this methodology, policymakers and healthcare providers can gain insights into the potential effects of implementing the recommended interventions and make informed decisions to improve access to maternal health.

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