Complementary feeding practices and associated factors of dietary diversity among uncomplicated severe acute malnourished children aged 6–23 months in Burkina Faso

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Study Justification:
The study aimed to investigate the dietary diversity among children aged 6-23 months being treated for severe acute malnutrition (SAM) in Burkina Faso. The use of ready-to-use therapeutic foods (RUTF) is the standard treatment for SAM, but reducing the dose of RUTF could potentially increase dietary diversity during treatment. Understanding the factors associated with dietary diversity in this population is crucial for improving nutritional interventions and outcomes.
Highlights:
– The study assessed the dietary diversity score (DDS), minimum dietary diversity (MDD), minimum meal frequency (MMF), and minimum acceptable diet (MAD) of 459 children aged 6-23 months with SAM.
– The study found that reducing the dose of RUTF during treatment did not impact the DDS.
– The most consumed food groups by the children were grains, roots or tubers, and legumes and nuts, while eggs consumption was low.
– Factors positively associated with DDS included child’s age, mother’s education, household wealth index, urban residence, and rainy season.
– The findings suggest that children with SAM consumed a variety of foods in addition to the prescribed RUTF ration.
Recommendations:
Based on the study findings, the following recommendations can be made:
1. Promote and educate caregivers about the importance of dietary diversity during the treatment of SAM.
2. Improve access to and availability of diverse food groups, especially eggs, to enhance dietary diversity among children with SAM.
3. Focus on interventions that target younger children, mothers with higher education levels, households with higher wealth index, urban areas, and the rainy season to improve dietary diversity.
Key Role Players:
1. Health professionals and nutritionists: Provide guidance and support in implementing interventions to improve dietary diversity among children with SAM.
2. Community health workers: Educate caregivers about the importance of dietary diversity and provide practical tips on incorporating diverse food groups into children’s diets.
3. Government agencies and policymakers: Develop and implement policies that promote access to diverse and nutritious foods for children with SAM.
4. Non-governmental organizations (NGOs): Collaborate with local communities to implement nutrition programs and interventions targeting children with SAM.
Cost Items for Planning Recommendations:
1. Education and training materials: Develop and distribute educational materials for caregivers and health professionals on the importance of dietary diversity and how to achieve it.
2. Food supply and distribution: Ensure an adequate supply of diverse food groups, including eggs, and establish distribution channels to reach children with SAM.
3. Monitoring and evaluation: Allocate resources for monitoring and evaluating the implementation and impact of interventions aimed at improving dietary diversity.
4. Capacity building: Provide training and capacity-building opportunities for health professionals and community health workers to effectively promote and support dietary diversity interventions.
Please note that the cost items provided are general categories and not actual cost estimates. The specific costs will depend on the context and scale of the interventions.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on a randomized controlled non-inferiority trial conducted in Burkina Faso. The study received approval from the Ethical Committee and the clinical trials board. The study provides detailed information on the methodology, sample size, data collection, and statistical analysis. However, to improve the evidence, it would be helpful to include information on the specific results and findings of the study, as well as any limitations or potential biases that may have affected the results.

Nutritional treatment of children with uncomplicated severe acute malnutrition (SAM) is based on ready-to-use therapeutic foods (RUTF). With treatment provided at community level, children could have access to other foods, and a reduction in the dose of RUTF could further increase dietary diversity during treatment. We assessed the dietary diversity score (DDS), the minimum dietary diversity (MDD), the minimum meal frequency (MMF) and the minimum acceptable diet (MAD) of 459 infants and young children aged 6–23 months being treated for SAM with different doses of RUTF. We also investigated the factors associated with DDS. Dietary intake was estimated using a single 24-h multipass dietary recall, 1 month after starting treatment, from December 2016 to August 2018. The DDS was calculated on the basis of eight food groups. Differences between children receiving the reduced RUTF and the standard RUTF dose and factors associated with DDS were assessed by Poisson and logistic regression models. RUTF dose was not associated with DDS (4.07 ± 1.25 for reduced RUTF and 4.01 ± 1.26 for standard RUTF; P = 0.77). Food groups most consumed by children were grains, roots or tubers (96%) and legumes and nuts (72%). Eggs consumption was low (3%). DDS was positively associated with child’s age, mother’s education, household wealth index, urban residence and rainy season. The present findings show that children with SAM consumed a variety of foods during treatment in addition to the RUTF ration prescribed to them. Reducing the dose of RUTF during SAM treatment did not impact DDS.

The MANGO study has been described in detail elsewhere (Kangas et al., 2019; Nikièma et al., 2021). In short, it was a randomized controlled non‐inferiority trial conducted in the health district of Fada N’Gourma, eastern region of Burkina Faso. The MANGO trial received the approval of the Ethical Committee (Comité d’éthique pour la Recherche en Santé) in Burkina Faso in December 2015 and the clinical trials board (Direction Générale de la Pharmacie, du Médicament et des Laboratoires) in September 2016. The study was conducted in 10 health centres. In 2018, in the eastern region, the prevalence of global acute malnutrition (GAM) defined by WHZ < −2 SD was estimated at 8.5% with 1.7% of SAM, defined as WHZ  10) were omitted from analyses. Possible predictors of DDS at individual, household, community and environmental levels have been selected to determine factors significantly associated with DDS (Abizari et al., 2017; Arsenault et al., 2014; Dafursa & Gebremedhin, 2019; Edris et al., 2018; Iqbal, 2017; Kuche et al., 2019). Given this, we selected at individual level some potential predictor variables such as child’s age (6–11 months or 12–23 months), sex (boy or girl), morbidity at last week before recall (yes or no), stunting at admission (yes or no), caregiver’s age ( = 25 years), caregiver’s education (no or yes) and caregiver’s ethnic group (Gourma, Mossi, Fulani, others). For household factors level, we selected food security status (food secure, mild food insecurity or moderate or severe food insecurity), household’s wealth index (low, medium or high), household’s water source (safe or unsafe) and household size ( = 5). Household’s residence (rural or urban) constituted a community‐level variable, and season of interview (dry or rainy) was considered an environmental‐level variable. To determine the factors significantly associated with DDS, multivariate standard Poisson regression analysis using a stepwise backward approach to model construction was computed (Dangura & Gebremedhin, 2017; Issaka, Agho, Page, et al., 2015b; Joshi et al., 2012; Mitchodigni et al., 2017) to estimate the coefficient and 95% confidence interval (CI). The association between each independent variable and DDS was initially assessed in unadjusted regression model; then variables with P‐value < 0.2 were entered for adjusted model. Assumptions of the adjusted regression model (linearity, absence of multicollinearity and homoscedasticity of error term) were checked (Casson & Farmer, 2014; Marill, 2004). Model fitness was assessed using Pearson goodness‐of‐fit P‐value (adjusted R‐squared value) and was satisfying. The outputs of the analyses are presented via crude and adjusted unstandardized Poisson regression coefficients (β). Findings were considered significant at P < 0.05. This study has been approved by the Burkina Faso Ethics Committee of Health Research. This trial was registered on 13 May 2016 at the IRSCTN registry (http://www.isrctn.com/ISRCTN50039021).

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

1. Mobile Health (mHealth) Applications: Develop mobile applications that provide information and guidance on maternal health, including nutrition, breastfeeding, and complementary feeding practices. These apps can be easily accessible to mothers and caregivers, providing them with accurate and up-to-date information.

2. Community-Based Education Programs: Implement community-based education programs that focus on maternal health and nutrition. These programs can involve local healthcare workers, community leaders, and volunteers who provide education and support to pregnant women and new mothers in their communities.

3. Telemedicine Services: Establish telemedicine services that allow pregnant women and new mothers to consult with healthcare professionals remotely. This can help overcome geographical barriers and provide access to medical advice and support, especially in rural or underserved areas.

4. Maternal Health Vouchers: Introduce voucher programs that provide financial assistance to pregnant women and new mothers for accessing maternal health services, including antenatal care, delivery, and postnatal care. These vouchers can be distributed through healthcare facilities or community organizations.

5. Maternal Health Clinics: Set up dedicated maternal health clinics that offer comprehensive care for pregnant women and new mothers. These clinics can provide antenatal care, postnatal care, family planning services, and counseling on nutrition and breastfeeding.

6. Public-Private Partnerships: Foster collaborations between public and private sectors to improve access to maternal health services. This can involve leveraging private healthcare providers and facilities to expand service coverage and reduce the burden on public healthcare systems.

7. Maternal Health Awareness Campaigns: Launch targeted awareness campaigns to educate communities about the importance of maternal health and the available services. These campaigns can use various communication channels, such as radio, television, social media, and community events, to reach a wide audience.

8. Transportation Support: Provide transportation support to pregnant women and new mothers, especially in remote areas, to ensure they can access healthcare facilities for antenatal care, delivery, and postnatal care.

9. Maternal Health Task Forces: Establish task forces or committees at the community or district level to coordinate and monitor maternal health initiatives. These task forces can bring together healthcare professionals, community leaders, and representatives from relevant organizations to identify and address barriers to access and quality of care.

10. Maternal Health Financing: Develop innovative financing mechanisms to ensure sustainable funding for maternal health programs. This can include exploring options such as health insurance schemes, public-private partnerships, and donor funding.

It’s important to note that the specific context and needs of the target population should be considered when implementing these innovations.
AI Innovations Description
Based on the provided description, the recommendation to improve access to maternal health is to focus on promoting complementary feeding practices for children with uncomplicated severe acute malnutrition (SAM). This can be achieved by implementing the following strategies:

1. Increase dietary diversity: Encourage the consumption of a variety of food groups, including grains, roots or tubers, legumes and nuts, dairy, flesh foods, eggs, vitamin A-rich fruits and vegetables, and other fruits and vegetables. This can be done by providing education and awareness to caregivers about the importance of offering a diverse range of foods to their children.

2. Improve nutrition education: Provide caregivers with information on the nutritional needs of children aged 6-23 months and the importance of complementary feeding. This can include guidance on appropriate portion sizes, cooking methods, and recipes to ensure a balanced and nutritious diet.

3. Enhance community-level treatment: Offer SAM treatment at the community level, where children have access to other foods in addition to ready-to-use therapeutic foods (RUTF). Reducing the dose of RUTF during treatment can further increase dietary diversity and promote the consumption of locally available foods.

4. Address socio-economic factors: Address factors such as mother’s education, household wealth index, and urban residence, which have been found to be positively associated with dietary diversity score (DDS). Implement interventions that aim to improve these socio-economic factors, such as promoting education and income-generating activities for mothers.

5. Seasonal considerations: Take into account the seasonal variations in food availability and consumption patterns. During the rainy season, when food availability may be higher, promote the consumption of vitamin A-rich fruits and vegetables, which are essential for child growth and development.

By implementing these recommendations, access to maternal health can be improved by ensuring that children with SAM receive a diverse and nutritious diet during treatment, leading to better health outcomes for both mothers and children.
AI Innovations Methodology
To improve access to maternal health, here are some potential recommendations:

1. Mobile Health (mHealth) Solutions: Implement mobile health technologies such as SMS reminders for prenatal care appointments, educational messages about maternal health, and telemedicine consultations for remote areas.

2. Community Health Workers: Train and deploy community health workers to provide maternal health services, including prenatal care, postnatal care, and health education, in underserved areas.

3. Maternal Health Vouchers: Introduce voucher programs that provide financial assistance to pregnant women for accessing maternal health services, including antenatal care, skilled birth attendance, and emergency obstetric care.

4. Transportation Support: Establish transportation systems or subsidies to help pregnant women reach healthcare facilities, particularly in rural or remote areas where access to transportation is limited.

5. Maternity Waiting Homes: Set up maternity waiting homes near healthcare facilities to accommodate pregnant women who live far away, allowing them to stay closer to the facility as their due date approaches.

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

1. Define the indicators: Determine the key indicators that reflect access to maternal health, such as the number of prenatal care visits, the percentage of skilled birth attendance, or the maternal mortality rate.

2. Collect baseline data: Gather data on the current status of these indicators in the target population or region. This could involve surveys, interviews, or analysis of existing data sources.

3. Develop a simulation model: Create a mathematical or statistical model that incorporates the potential impact of the recommendations on the chosen indicators. This model should consider factors such as population size, geographical distribution, and existing healthcare infrastructure.

4. Input recommendation parameters: Specify the parameters of each recommendation, such as the number of community health workers to be trained, the coverage of the voucher program, or the frequency of transportation support.

5. Run simulations: Use the simulation model to project the potential impact of the recommendations over a specified time period. This could involve running multiple scenarios with different parameter values to assess the range of possible outcomes.

6. Analyze results: Evaluate the simulation results to determine the expected changes in the chosen indicators. Assess the effectiveness of each recommendation and identify any potential synergies or trade-offs between different interventions.

7. Refine and iterate: Based on the simulation findings, refine the recommendations and their parameters as needed. Repeat the simulation process to assess the impact of the revised recommendations.

8. Communicate findings: Present the simulation results in a clear and concise manner, highlighting the expected improvements in access to maternal health. Use the findings to advocate for the implementation of the recommended interventions and secure necessary resources and support.

It’s important to note that the methodology described above is a general framework and may need to be adapted based on the specific context and data availability. Additionally, involving relevant stakeholders, such as healthcare providers, policymakers, and community members, in the simulation process can help ensure the recommendations are feasible and address the actual needs of the target population.

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