Common perinatal mental disorders and post-infancy child development in rural Ethiopia: A population-based cohort study

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Study Justification:
This study aimed to investigate the association between maternal common mental disorders (CMD) in the postnatal period and child development in a rural low-income African setting. Previous studies have shown a relationship between maternal CMD and child development in urban and peri-urban settings in middle-income countries. However, it is important to understand if these findings hold true in areas characterized by high social adversity and food insecurity, such as rural Ethiopia. This study fills a gap in the literature by examining the impact of maternal CMD on child development in a low-resource and rural context.
Study Highlights:
– The study was conducted in the Butajira area of Ethiopia from 2005 to 2006.
– A population-based cohort of 496 women who had recently given birth to living, singleton babies participated in the study.
– Maternal CMD symptoms were measured using a locally validated WHO Self-Reporting Questionnaire.
– Child development was assessed at 2.5 and 3.5 years after birth using a locally adapted version of the Bayley Scales of Infant Development.
– After adjusting for confounders, there was no evidence for an association between postnatal CMD and overall child development or the cognitive sub-domain in the preschool period.
– The findings suggest that the risk and protective factors for child development may differ in areas characterized by high social adversity and food insecurity.
Study Recommendations:
– More studies are needed to investigate the impact of maternal CMD on child development in low-resource and rural areas.
– Future research should explore the specific risk and protective factors for child development in these contexts.
– Interventions and programs aimed at promoting child development should take into account the unique challenges faced by rural communities with high social adversity and food insecurity.
Key Role Players:
– Researchers and research assistants: Responsible for conducting the study, collecting data, and analyzing the results.
– Health professionals: Including nurses, paediatricians, and psychiatrists who provided training and expertise in administering assessments and measuring child development.
– Community workers: Trained to measure birth weight and assist with data collection in the participants’ homes.
– Ethical review committees: Approved the study and ensured the protection of participants’ rights and welfare.
Cost Items for Planning Recommendations:
– Research personnel: Salaries and benefits for researchers, research assistants, and data collectors.
– Training: Costs associated with training health professionals, community workers, and data collectors.
– Assessment tools: Expenses for acquiring and adapting assessment tools, such as the Bayley Scales of Infant Development.
– Transportation: Reimbursement for participants’ transportation costs and travel expenses for researchers and data collectors.
– Ethical considerations: Costs related to obtaining ethical approvals and ensuring participant welfare, including reimbursement for healthcare costs and referrals for mental health services.
– Data management and analysis: Costs for data entry, storage, and analysis using statistical software.
– Reporting and dissemination: Expenses for publishing the study findings in a scientific journal and sharing the results with relevant stakeholders.
Please note that the provided cost items are general categories and not actual cost estimates. The actual budget for implementing the recommendations would depend on various factors, such as the specific context, duration of the study, and available resources.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is rated 7 because it is based on a population-based cohort study conducted in a rural low-income African setting. The study used a sample size of 496 women and measured postnatal CMD and child development at 2.5 and 3.5 years after birth. The study adjusted for confounders and found no evidence for an association between postnatal CMD and overall child development or the cognitive sub-domain. However, the study acknowledges that previous studies in different settings have found a relationship between maternal CMD and child development. To improve the evidence, future studies could consider increasing the sample size, including a more diverse population, and conducting longitudinal follow-ups to assess long-term effects.

Objective: To investigate whether maternal common mental disorders (CMD) in the postnatal period are prospectively associated with child development at 2.5 and 3.5 years in a rural low-income African setting. Methods: This study was nested within the C-MaMiE (Child outcomes in relation to Maternal Mental health in Ethiopia) population-based cohort in Butajira, Ethiopia, and conducted from 2005 to 2006. The sample comprised of 496 women who had recently given birth to living, singleton babies with recorded birth weight measurements, who were 15 to 44 years of age, and residing in six rural sub-districts. Postnatal CMD measurements were ascertained 2 months after delivery. Language, cognitive, and motor development were obtained from the child 2.5 and 3.5 years after birth using a locally adapted version of the Bayley Scales of Infant Development (3rd Ed). Maternal CMD symptoms were measured using a locally validated WHO Self-Reporting Questionnaire. A linear mixed-effects regression model was used to analyze the relationship between postnatal CMD and child development. Results: After adjusting for confounders, there was no evidence for an association between postnatal CMD and overall child development or the cognitive sub-domain in the preschool period. There was no evidence of effect modification by levels of social support, socioeconomic status, stunting, or sex of the child. Conclusions: Previous studies from predominantly urban and peri-urban settings in middle-income countries have established a relationship between maternal CMD and child development, which contrasts with the findings from this study. The risk and protective factors for child development may differ in areas characterized by high social adversity and food insecurity. More studies are needed to investigate maternal CMD’s impact on child development in low-resource and rural areas.

The C‐MaMiE study (Child outcomes in relation to Maternal Mental health in Ethiopia) is a population‐based cohort study [30]. Participants were recruited and assessed in pregnancy and underwent repeated assessments with the index child. Measurements in this analysis were taken at birth and 2 months, 2.5 and 3.5 years after delivery. The C‐MaMiE study was conducted in the Health and Demographic Surveillance Site (HDSS) in the Butajira area, Ethiopia. The Butajira HDSS is 130 kilometres south of the capital, Addis Ababa, and was established in 1986 as part of the Butajira Rural Health Programme [31]. At the time of the study, the HDSS population was 49,943, with 13,268 women of reproductive age [30]. One general hospital exists in Butajira town, and a second hospital is located 8 km outside of town. In addition, four primary health centres and seven health posts serve the HDSS population. Rural residents rely on a livelihood based on mixed farming of cash crops, mainly khat and chilli peppers, maize as the subsistence grain, and false bananas. Parts of the HDSS are food insecure because of a combination of overpopulation and intermittent drought [32]. Health‐centre‐based nurses and experienced project data collectors were trained for 10 days by the project co‐investigator (G.M.) to administer the Bayley III. The co‐investigator has a Master’s degree in applied statistics and experience working with the Bayley Scale in Butajira and was supported by an Ethiopian consultant paediatrician (B.W.) and an Ethiopian psychiatrist (A.A.). The paediatrician took a prominent role in observing the administration of the complete Bayley Scales by trainees, giving feedback, and discussing the findings in detail with the trainees. The data collectors and local female high‐school graduates surveyed using the HOME scale and structured demographic questionnaires. Both nurses and C‐MaMiE data collectors administered the Bayley III with comparably high reliability (Chronbach’s α > 0.7) in a previous validation study [33]. For the C‐MaMiE study, a sample of 1065 women was recruited from 1234 eligible women (86.3%) in the Butajira HDSS between July 2005 and February 2006 [30]. HDSS enumerators identified participants during their routine quarterly surveillance interviews. After giving verbal or written informed consent, the participants were interviewed by data collectors in their own homes. Women aged 15 to 49 years, able to speak Amharic, residing in the HDSS, and in their third trimester of pregnancy were eligible. Women with a known severe mental disorder, such as psychotic or bipolar disorder, or an emergency health condition during enrolment were excluded. The cohort was restricted to women with singleton, living births for the analytic sample, with birth weight measured within 48 hours of delivery, from rural sub‐districts (kebeles), and who had maternal CMD symptoms assessed 2 months postnatally. At the time of recruitment into the study, around 90% of deliveries took place at home [34]. In six rural sub‐districts, a community worker was trained to measure birth weight within 48 h of birth in the woman’s home [24]. Child development was measured with a composite of three sub‐scales (cognitive, motor, and language development) on the Bayley Scales of Infant Development, third edition (Bayley III). The Bayley III has been translated into Amharic and validated in Butajira with this cohort [33]. Items lacking cultural validity were adapted (e.g., pictures adapted for contextual relevance) or dropped (e.g., involving scissors or stairs). No time limit was imposed for the completion of items. Mokken scaling, a method based on non‐parametric item response theory, was used to create a hierarchical scale for the raw scores at both time points [35, 36]. Postnatal CMD was measured 2 months after birth, using the WHO 20‐item version of the Self‐Reporting Questionnaire (SRQ‐20) [37]. The SRQ‐20 functions as a screening tool that assesses the presence or absence of depressive, anxiety, and somatic symptoms in the previous month. The measure has been used in other Ethiopian studies [38, 39] and was validated with this cohort as a continuous measure [40]. A conceptual framework was developed for this analysis based on previous theoretical models and literature on the risk factors for maternal CMD and child development (Figure ​(Figure1)1) [21, 24, 41]. The selection of confounders, mediators, and confounders was theory‐driven. Factors were considered confounders if they were hypothesized to have a relationship with postnatal CMD and child development, affecting their relationship. In contrast, mediators were selected if they potentially explained the relationship between postnatal CMD and child development. Finally, effect modifiers were chosen if there was a hypothesis that the effect of postnatal CMD on child development varied across the levels of another variable. The measures were assessed at pregnancy, birth, and 2.5 and 3.5‐year timepoints (Figure S1). Conceptual framework for the association between postnatal maternal common mental disorders and child development During pregnancy, the following confounders were obtained through self‐report and included maternal age, parental education level, and parity [4]. Assets comprised ownership of 11 resources (e.g., land, house, crops). Socioeconomic status (SES) [4] was confirmed with Mokken scaling [38, 39] and included self‐report of hunger in the last month, indebtedness, lack of access to emergency resources, and perceived lower relative wealth. Marital discord [5] was summarised using Mokken scaling [24] and included self‐report of inadequate help from husband, relationship quality, frequency of quarrels, and perception of problematic alcohol consumption by the husband. Exposure to violence [4] assessed women’s experience of physical violence since birth. Social support [11] comprised women’s perception of the support received with housework and children. The sex of the child [43] was obtained at birth. Obstetric complications [30] summed the responses to instrumental or operative delivery, duration of labour greater than 24 h, and bleeding or fever after delivery. Birth weight [44] was measured within 48 h of delivery using SECA 725 scales to an accuracy of 10 g [35]. Home environment, child growth or stunting, and child illness were measured 2.5 and 3.5 years after birth. Home environment [45] was measured using the original Home Observation for Measurement of Environment (HOME) scale [46]. The HOME measure of environmental stimulation was not formally validated for the setting. Because of difficulties with the contextual adaptation of the HOME, we relied on the sub‐scales based on observation of mother‐child interactions. The other sub‐scales were more challenging as they assessed aspects of a stimulating environment (i.e., number of books and time spent watching television) that were difficult to adapt for this low‐resource, rural setting. The instrument measures the amount and quality of stimulation and support provided to a child. Sub‐scales include a responsivity and an acceptance scale focused on the parent’s attentiveness to the child and negative interactions. Height‐for‐Age Z scores [47] were calculated using WHO standard growth curves to define children as stunted at two Z‐scores below the median. Lower scores are indicative of higher levels of stunting in a child. Height‐for‐age has been argued to function as a better measure of cumulative undernutrition and more predictive of impaired child development [48]. A standard piece of medical equipment for height measurements, a stadiometer, was used to measure height with an adjustable headpiece. Child illness [11] was assessed through maternal recall for the presence of diarrhoea, fever, and severe illness episodes in the past 6 months. SES [11], social support [11], stunting, and sex of the child [17], were conceptualised as potential effect modifiers, and stunting [9] and home environment [12] as potential mediators. The analysis was conducted using Stata Version 16. Participants’ characteristics with missing data on the primary outcome were compared with those remaining in the cohort, using Pearson chi‐squared tests, t‐tests, and Wilcoxon rank‐sum tests. The multivariable analysis of the association between postnatal maternal CMD symptoms and total and cognitive development outcomes was hypothesis‐driven. A mixed‐effects linear regression model with a random intercept was fitted. Model fit was tested using likelihood ratio tests after adding random slopes. An interaction with time was included to estimate the association between postnatal CMD and the change in child development between 2.5‐ and 3.5‐year time points. All conceptualised confounders were added into the multivariable model sequentially, clustered by socio‐demographic, maternal and child, and environmental characteristics. The final model included all a priori confounders (Figure ​(Figure1).1). Effect modification was investigated by including interaction terms for SES, sex of the child, stunting, and social support. Home environment and stunting were individually added to the final model to assess for exploratory evidence of mediation. The National Ethical Review Committee for Ethiopia and the Research Ethics Committee of King’s College London in the U.K. approved the C‐MaMiE study. All participants gave informed consent. Literate women provided written consent, and non‐literate women indicated their consent with a thumbprint. Women received reimbursement for healthcare costs, and participants suffering from severe mental disorders, including psychotic or bipolar disorder, were referred to the local psychiatric unit and covered transportation costs. At baseline, women experiencing violence were directed to a local, community‐based non‐governmental organization for services.

Based on the information provided, it is difficult to identify specific innovations for improving access to maternal health. However, here are some potential recommendations that could be considered:

1. Telemedicine: Implementing telemedicine services can help overcome geographical barriers and provide access to healthcare professionals for remote areas. This can include virtual consultations, remote monitoring, and tele-education for healthcare providers.

2. Mobile health (mHealth) interventions: Utilize mobile technology to deliver maternal health information, reminders, and support to pregnant women and new mothers. This can include text messaging programs, mobile apps, and interactive voice response systems.

3. Community health workers: Train and deploy community health workers to provide essential maternal health services, education, and support in rural areas. These workers can help bridge the gap between communities and healthcare facilities.

4. Maternal health clinics: Establish dedicated maternal health clinics in rural areas to provide comprehensive prenatal care, postnatal care, and family planning services. These clinics can be staffed by skilled healthcare professionals and equipped with necessary resources.

5. Transportation support: Address transportation challenges by providing affordable or subsidized transportation options for pregnant women to access healthcare facilities. This can include community-based transportation services or partnerships with existing transportation providers.

6. Health education and awareness campaigns: Conduct targeted health education campaigns to raise awareness about the importance of maternal health and encourage women to seek timely care. These campaigns can be conducted through various channels, including radio, television, community meetings, and social media.

7. Strengthening referral systems: Improve the coordination and effectiveness of referral systems between community health workers, primary healthcare centers, and higher-level healthcare facilities. This can ensure timely and appropriate care for pregnant women and reduce delays in accessing emergency obstetric services.

8. Maternal waiting homes: Establish maternal waiting homes near healthcare facilities to accommodate pregnant women who live far away and need to stay closer to the facility during the final weeks of pregnancy. This can help ensure timely access to skilled birth attendants and emergency obstetric care.

It is important to note that the specific context and needs of the rural Ethiopian setting should be taken into consideration when implementing any innovation to improve access to maternal health.
AI Innovations Description
Based on the description provided, the recommendation to improve access to maternal health and address common perinatal mental disorders in rural Ethiopia is to implement the following strategies:

1. Increase awareness and education: Develop and implement community-based awareness campaigns to educate women and their families about the importance of maternal mental health and its impact on child development. This can be done through community meetings, workshops, and the distribution of informational materials in local languages.

2. Strengthen healthcare infrastructure: Improve access to healthcare services by increasing the number of healthcare facilities, including primary health centers and hospitals, in rural areas. This will ensure that women have access to quality maternal healthcare services, including mental health support.

3. Train healthcare providers: Provide training to healthcare providers, including nurses and midwives, on identifying and managing common perinatal mental disorders. This will enable them to provide appropriate support and interventions to women experiencing mental health challenges during pregnancy and postpartum.

4. Integrate mental health services into maternal healthcare: Integrate mental health services into existing maternal healthcare programs and services. This can be done by training healthcare providers to screen for and manage common perinatal mental disorders, as well as establishing referral pathways for women who require specialized mental health care.

5. Improve social support systems: Strengthen social support systems for women during pregnancy and postpartum. This can be achieved by establishing support groups, providing counseling services, and promoting community-based support networks.

6. Address socioeconomic factors: Address socioeconomic factors that contribute to poor maternal mental health, such as poverty and food insecurity. Implement programs that aim to improve socioeconomic conditions, such as income generation initiatives and access to nutritious food.

7. Conduct further research: Conduct additional research to better understand the relationship between maternal mental health and child development in low-resource and rural settings. This will help inform the development of targeted interventions and policies to improve maternal and child health outcomes.

By implementing these recommendations, it is hoped that access to maternal health services and support for common perinatal mental disorders will be improved, leading to better maternal and child health outcomes in rural Ethiopia.
AI Innovations Methodology
Based on the provided description, here are some potential recommendations to improve access to maternal health:

1. Increase awareness and education: Implement community-based programs to raise awareness about maternal mental health and its impact on child development. Provide education and information to pregnant women and their families about the importance of seeking support and treatment for common mental disorders.

2. Strengthen healthcare infrastructure: Improve access to healthcare facilities in rural areas by increasing the number of primary health centers and hospitals. Ensure that these facilities are equipped with trained healthcare professionals who can provide mental health support to pregnant women and new mothers.

3. Integrate mental health services into maternal health programs: Integrate mental health screening and support services into existing maternal health programs. This can be done by training healthcare workers to identify and address common mental disorders during antenatal and postnatal visits.

4. Promote social support networks: Establish support groups and community networks for pregnant women and new mothers. These networks can provide emotional support, share experiences, and connect women with resources and services.

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 measure access to maternal health, such as the number of women receiving antenatal and postnatal care, the percentage of women screened for common mental disorders, and the availability of mental health services in rural areas.

2. Collect baseline data: Gather data on the current state of access to maternal health services and mental health support in the target area. This can be done through surveys, interviews, and analysis of existing health records.

3. Simulate the impact: Use statistical modeling techniques to simulate the potential impact of the recommendations on the identified indicators. This can involve creating scenarios where the recommendations are implemented and estimating the resulting changes in access to maternal health services.

4. Analyze the results: Evaluate the simulated impact of the recommendations by comparing the baseline data with the simulated data. Assess the extent to which the recommendations improve access to maternal health and identify any potential challenges or limitations.

5. Refine and adjust: Based on the analysis of the simulated impact, refine the recommendations and adjust the methodology if necessary. Consider additional factors or interventions that may further enhance access to maternal health.

6. Implement and monitor: Implement the recommendations based on the findings of the simulation. Continuously monitor and evaluate the progress to ensure that the desired improvements in access to maternal health are being achieved.

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