Sustainable under nutrition reduction program and dietary diversity among children’s aged 6-23 months, Northwest Ethiopia: Comparative cross-sectional study

International Journal for Equity in Health, Volume 19, No. 1, Year 2020

Interpretation

Introduction: Adequate dietary diversity is vital for the survival, growth and development of infants and children. Inadequate dietary diversity is the major cause of micronutrient deficiency in Sub-saharan Africa, including Ethiopia, where only less than one-fourth of the children aged 6-23 months obtain adequate diversified diet. Thus country implemented a strategy known as the Sustainable Undernutrtion Reduction (SUR) programs to alleviate the problem. However, empirical evidences are scarce on the impact of the program on children aged 6-23 months. Therefore, this study aimed to compare the level of dietary diversity among children aged 6-23 months in districts covered and not covered by SURE program in West Gojjam zone. Methods: A community based comparative cross-sectional study was conducted in three districts of West Gojjam zone, Ethiopia, from February 29 to April 20, 2019. A total of 832 mother and child pairs were selected by the simple random sampling technique. A pretested and structured interviewer-administered questionnaire was used to collect data. A binary logistic regression model was fitted to identify factors associated with dietary diversity. Crude odds and adjusted odds ratios with 95% confidence intervals (CI) were calculated to assess the strength of associations and significance of the identified factors for dietary diversity score. Result: The overall proportion of adequate dietary diversity among children aged 6-23 months was 29.9% (95% CI: 27.0-33.0), whereas in SURE covered and uncovered districts it was 33.4% (95%CI: 29.0-38.and 26.4%(95% CI: 22.0, 31.0), respectively. ANC (Antenatal care) (AOR = 1.7; 95% CI: 1.16, 2.55) and postnatal care services (AOR = 2.1; 95% CI: 1.38, 3.28), participating in food preparation programs (AOR = 1.9; 95% CI: 1.19, 2.96), GMP (AOR = 2.74,95%CI:1.80, 4.18), vitamin A supplementation (AOR = 2.10,95%CI:1.22, 3.61) and household visits by health extension workers (AOR = 2.0; 95% CI: 1.25, 3.21) were significantly associated with dietary diversity. Conclusion: The proportion of adequate dietary diversity was higher among children in the program than those out of the program. ANC visits, PNC follow-ups, women’s participating in food preparation programs and household visits by health extension workers were significantly associated with dietary diversity. Therefore, and strengthening and scaling up the program to non covered districts and providing health and nutrition counseling on Infant and Young Child Feeding (IYCF) during ANC and PNC services are recommended for achieving the recommended dietary diversity. A community- based comparative cross-sectional study was conducted in three selected districts of West Gojjam zone from February 29 to April 20, 2019. West Gojjam is one of the administrative zones in Amhara region, North West Ethiopia. It is located 567 km from Addis Ababa, the capital of Ethiopia, and has 16 districts and 444 kebeles. SURE and Save the children programs which were working to strengthen existing efforts in the country covered four of the 16 districts each, that is eight districts. A total of 117,673 mothers who had young children aged 6 to 23 months lived in the SURE covered (Yilimanadennsa) and the uncovered (Bahir-Dar Zuriya and Debub Achffer districts) which largely dependent on agriculture. The zone had 3 hospitals, 104 health centers, and 391 health posts that providing health services including maternal and child health care. All infants and young children aged 6–23 months and their mothers who had lived for at least 6 months in the area participated in the study. As this was a comparative cross-sectional study, the minimum sample size was determined by using the double population proportion formula with the assumptions exposed (intervention applied) and unexposed (intervention not applied) groups. To estimate the minimum sample size, a dietary diversity proportion (13%) was taken as p2 from a previous study [18]. However, since there has been no previous finding for the intervention group, the assumption that intervention increases the proportion of dietary diversity by 15% p1 yielded 28%. The final sample size was calculated using the Epi Info software with the assumption of a 95% confidence interval, 80% power, 1:1 ratio of exposed to unexposed, 3% design effect, and 10% non-response rate. Therefore, the final minimum adequate sample size was 832. A multistage stratified sampling and the simple random sampling technique was employed to select study participants in West Gojjam zone. Initially, districts were categorized as SURE program covered and uncovered. Three districts, one covered and two uncovered were selected using the lottery method for the study. The three selected districts had a total of 85 kebeles (35 covered and 50 uncovered).Out of the 85kebeles, seven in SURE covered and ten in uncovered districts were selected using the lottery method. Participants were proportionally assigned to each kebele using the community-based demographic and health related information registration book of health extension workers. Finally, mother to child pairs were selected from each keble using the simple random sampling methods after giving codes to each household which had young children aged 6 to 23 months. If there were more than one children in the households, we selected the index child by the lottery method. If children (aged 6–23 months) received at least four food groups out of seven in the preceding 24 h of the interview [10, 19]. Mothers/caregivers of children exposed to media at least once a week by reading newspapers or magazines or listening to the radio or watching TV [11].. Knowledge of mothers about child feeding, if the mothers answered seven knowledge questions out of the ten they have good knowledge [20]. HFIAS (household food insecurity access scale) was assessed from FANTA (Food and Nutrition Technical Assistance) 2007 with nine main question, HFIAS divided into (Food security defines the Household food security level of the summations were ≤ 1 point out of 27 scores while the household food security level of the summations ≥2 points out of 27 scores were food insecure) [21]. Data was collected through a face to face interview, using a structured and pre-tested questionnaire. In order to maintain the quality of data, 2 days training was given to data collectors and supervisors by the principal investigator. A 5% pretest was conducted in non selected districts, and the questionnaire was initially prepared in English and translated to Amharic and retranslated to English by language and public health experts to guarantee consistency. On-site supervision was performed, and each copy of the questionnaire was checked for completeness and accuracy before data entry; 17 clinical nurses and six BSc graduate nursing or public health field supervisors were involved in the data collection process. Dietary diversity practice was collected and calculated as the sum of the number of different food groups consumed by the child in the 24 h prior to the assessment. The list of food groups included, grains, roots, and tubers; legumes and nuts; dairy products (milk, yogurt, cheese); flesh foods (meat, fish, poultry and liver/organ meats); eggs; vitamin-A rich fruits and vegetables and other fruits and vegetables. Finally, if respondents consumed four or more of the food groups, they were considered as having adequate dietary diversity [2]. Household wealth index adopted from EDHS 2011 was determined using the Principal Component Analysis (PCA) by considering household assets, such as livestock, type of house, durable assets and productive assets. First, variables coded between 0 and 1 were entered and analyzed using PCA; then variables with commonality values of greater than 0.5 were used to produce factor scores. Finally, the factor scores were summed and ranked as “poor”, “medium” and “rich”. Food insecurity was measured using the FANTA (Food and Nutrition Technical Assistance Tool) household food insecurity access scale (HFIAS) [21]. It consisted of nine “occurrence questions” that represented a generally increasing level of severity of food insecurity (access) and nine “frequency-of-occurrence” questions that asked as a follow-up to each occurrence question to determine how often the condition occurred. The frequency-of-occurrence question was skipped if respondents reported when the condition described in the corresponding occurrence question was not experienced in the previous 4 weeks (30 days). Finally, individuals were considered as food secure, if they said “no” to all items or just experienced worry but rarely; mildly food insecure households were those who were defined sometimes or often worried about not having enough food and/or unable to eat favorite foods and/ or rarely ate a more monotonous diet than desired. Households that reported they rarely or sometimes ate more monotonous diets than desired sometimes or often and/or had started to cut back on quantity by reducing the size of meals or the number of meals were coded as moderately food insecure. Data were entered into EPI INFO version 7 and analyzed using the Statistical Package for Social Sciences (SPSS) version 20. Descriptive statistics, including frequencies and proportions were used to summarize the variables. A binary logistic regression model was fitted to identify factors associated with dietary diversity practices. Variables with P–values of < 0.2 in the bi-variable analysis were entered in to the multivariable analysis to control possible effects of confounders. The Adjusted Odds Ratio (AOR) with a 95% of confidence interval was used to examine the strength of associations, and a P– values ≤0.05 was used to declare statistical significance in the multivariable analysis.

AI Digest

Study Justification:

– Adequate dietary diversity is crucial for the survival, growth, and development of infants and children.
– Inadequate dietary diversity is a major cause of micronutrient deficiency in Sub-Saharan Africa, including Ethiopia.
– The Sustainable Undernutrition Reduction (SURE) program was implemented in Ethiopia to address this issue, but its impact on children aged 6-23 months is not well understood.

Highlights:

– The study compared the level of dietary diversity among children aged 6-23 months in districts covered and not covered by the SURE program in West Gojjam zone, Ethiopia.
– A total of 832 mother and child pairs were included in the study.
– The overall proportion of adequate dietary diversity among children aged 6-23 months was 29.9%.
– Children in the SURE program districts had a higher proportion of adequate dietary diversity (33.4%) compared to those in non-covered districts (26.4%).
– Factors associated with dietary diversity included ANC and postnatal care services, participating in food preparation programs, GMP, vitamin A supplementation, and household visits by health extension workers.

Recommendations for Lay Reader:

– Strengthen and scale up the SURE program to non-covered districts to improve dietary diversity among children aged 6-23 months.
– Provide health and nutrition counseling on Infant and Young Child Feeding (IYCF) during ANC and PNC services to enhance dietary diversity.

Recommendations for Policy Maker:

– Expand the coverage of the SURE program to include all districts in the West Gojjam zone.
– Allocate resources to provide health and nutrition counseling on IYCF during ANC and PNC services.
– Enhance the training and deployment of health extension workers to conduct household visits and provide support for improving dietary diversity.

Key Role Players:

– Ministry of Health: Responsible for overall coordination and implementation of the SURE program and providing resources for scaling up.
– Health Extension Workers: Conduct household visits, provide health and nutrition counseling, and support families in improving dietary diversity.
– Community Leaders: Mobilize communities, raise awareness about the importance of dietary diversity, and support the implementation of the SURE program.
– Non-Governmental Organizations: Collaborate with the government to provide technical assistance, capacity building, and resources for program implementation.

Cost Items for Planning Recommendations:

– Training and capacity building for health extension workers and other healthcare providers.
– Development and dissemination of educational materials on IYCF and dietary diversity.
– Monitoring and evaluation activities to assess the impact of the program and identify areas for improvement.
– Provision of supplementary foods and micronutrient supplements for children aged 6-23 months.
– Communication and awareness campaigns to promote behavior change and community engagement.
– Infrastructure and logistics support for the expansion of the program to non-covered districts.

Strength of Evidence

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 comparative cross-sectional study, which allows for comparisons between different groups. The sample size of 832 mother and child pairs is adequate. The study provides adjusted odds ratios with 95% confidence intervals to assess the strength of associations. However, the study does not mention randomization or blinding, which could introduce bias. To improve the strength of the evidence, future studies could consider using a randomized controlled trial design and implementing blinding techniques to minimize bias.

Abstract

A community- based comparative cross-sectional study was conducted in three selected districts of West Gojjam zone from February 29 to April 20, 2019. West Gojjam is one of the administrative zones in Amhara region, North West Ethiopia. It is located 567 km from Addis Ababa, the capital of Ethiopia, and has 16 districts and 444 kebeles. SURE and Save the children programs which were working to strengthen existing efforts in the country covered four of the 16 districts each, that is eight districts. A total of 117,673 mothers who had young children aged 6 to 23 months lived in the SURE covered (Yilimanadennsa) and the uncovered (Bahir-Dar Zuriya and Debub Achffer districts) which largely dependent on agriculture. The zone had 3 hospitals, 104 health centers, and 391 health posts that providing health services including maternal and child health care. All infants and young children aged 6–23 months and their mothers who had lived for at least 6 months in the area participated in the study. As this was a comparative cross-sectional study, the minimum sample size was determined by using the double population proportion formula with the assumptions exposed (intervention applied) and unexposed (intervention not applied) groups. To estimate the minimum sample size, a dietary diversity proportion (13%) was taken as p2 from a previous study [18]. However, since there has been no previous finding for the intervention group, the assumption that intervention increases the proportion of dietary diversity by 15% p1 yielded 28%. The final sample size was calculated using the Epi Info software with the assumption of a 95% confidence interval, 80% power, 1:1 ratio of exposed to unexposed, 3% design effect, and 10% non-response rate. Therefore, the final minimum adequate sample size was 832. A multistage stratified sampling and the simple random sampling technique was employed to select study participants in West Gojjam zone. Initially, districts were categorized as SURE program covered and uncovered. Three districts, one covered and two uncovered were selected using the lottery method for the study. The three selected districts had a total of 85 kebeles (35 covered and 50 uncovered).Out of the 85kebeles, seven in SURE covered and ten in uncovered districts were selected using the lottery method. Participants were proportionally assigned to each kebele using the community-based demographic and health related information registration book of health extension workers. Finally, mother to child pairs were selected from each keble using the simple random sampling methods after giving codes to each household which had young children aged 6 to 23 months. If there were more than one children in the households, we selected the index child by the lottery method. If children (aged 6–23 months) received at least four food groups out of seven in the preceding 24 h of the interview [10, 19]. Mothers/caregivers of children exposed to media at least once a week by reading newspapers or magazines or listening to the radio or watching TV [11].. Knowledge of mothers about child feeding, if the mothers answered seven knowledge questions out of the ten they have good knowledge [20]. HFIAS (household food insecurity access scale) was assessed from FANTA (Food and Nutrition Technical Assistance) 2007 with nine main question, HFIAS divided into (Food security defines the Household food security level of the summations were ≤ 1 point out of 27 scores while the household food security level of the summations ≥2 points out of 27 scores were food insecure) [21]. Data was collected through a face to face interview, using a structured and pre-tested questionnaire. In order to maintain the quality of data, 2 days training was given to data collectors and supervisors by the principal investigator. A 5% pretest was conducted in non selected districts, and the questionnaire was initially prepared in English and translated to Amharic and retranslated to English by language and public health experts to guarantee consistency. On-site supervision was performed, and each copy of the questionnaire was checked for completeness and accuracy before data entry; 17 clinical nurses and six BSc graduate nursing or public health field supervisors were involved in the data collection process. Dietary diversity practice was collected and calculated as the sum of the number of different food groups consumed by the child in the 24 h prior to the assessment. The list of food groups included, grains, roots, and tubers; legumes and nuts; dairy products (milk, yogurt, cheese); flesh foods (meat, fish, poultry and liver/organ meats); eggs; vitamin-A rich fruits and vegetables and other fruits and vegetables. Finally, if respondents consumed four or more of the food groups, they were considered as having adequate dietary diversity [2]. Household wealth index adopted from EDHS 2011 was determined using the Principal Component Analysis (PCA) by considering household assets, such as livestock, type of house, durable assets and productive assets. First, variables coded between 0 and 1 were entered and analyzed using PCA; then variables with commonality values of greater than 0.5 were used to produce factor scores. Finally, the factor scores were summed and ranked as “poor”, “medium” and “rich”. Food insecurity was measured using the FANTA (Food and Nutrition Technical Assistance Tool) household food insecurity access scale (HFIAS) [21]. It consisted of nine “occurrence questions” that represented a generally increasing level of severity of food insecurity (access) and nine “frequency-of-occurrence” questions that asked as a follow-up to each occurrence question to determine how often the condition occurred. The frequency-of-occurrence question was skipped if respondents reported when the condition described in the corresponding occurrence question was not experienced in the previous 4 weeks (30 days). Finally, individuals were considered as food secure, if they said “no” to all items or just experienced worry but rarely; mildly food insecure households were those who were defined sometimes or often worried about not having enough food and/or unable to eat favorite foods and/ or rarely ate a more monotonous diet than desired. Households that reported they rarely or sometimes ate more monotonous diets than desired sometimes or often and/or had started to cut back on quantity by reducing the size of meals or the number of meals were coded as moderately food insecure. Data were entered into EPI INFO version 7 and analyzed using the Statistical Package for Social Sciences (SPSS) version 20. Descriptive statistics, including frequencies and proportions were used to summarize the variables. A binary logistic regression model was fitted to identify factors associated with dietary diversity practices. Variables with P–values of < 0.2 in the bi-variable analysis were entered in to the multivariable analysis to control possible effects of confounders. The Adjusted Odds Ratio (AOR) with a 95% of confidence interval was used to examine the strength of associations, and a P– values ≤0.05 was used to declare statistical significance in the multivariable analysis.

Materials

N/A

Innovations

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

1. Mobile Health (mHealth) Applications: Develop and implement mobile applications that provide pregnant women and new mothers with information and reminders about prenatal care, nutrition, and child feeding practices. These apps can also offer access to telemedicine services for remote consultations with healthcare providers.

2. Community Health Workers: Train and deploy community health workers to provide education and support to pregnant women and new mothers in rural areas. These workers can conduct home visits, offer counseling on maternal and child health, and facilitate referrals to healthcare facilities when needed.

3. Telemedicine: Establish telemedicine services that allow pregnant women and new mothers in remote areas to consult with healthcare providers through video calls or phone calls. This can help overcome geographical barriers and improve access to prenatal care and postnatal support.

4. Maternal Health Vouchers: Implement a voucher system that provides pregnant women with subsidized or free access to essential maternal health services, including antenatal care, delivery, and postnatal care. This can help reduce financial barriers and increase utilization of these services.

5. Maternal Waiting Homes: Set up maternal waiting homes near healthcare facilities in rural areas. These homes provide accommodation for pregnant women who live far from healthcare facilities, allowing them to stay closer to the facility in the weeks leading up to their expected delivery date. This can help ensure timely access to skilled birth attendants and emergency obstetric care.

6. Transportation Support: Develop transportation support programs that provide pregnant women with affordable and reliable transportation to healthcare facilities for antenatal care visits, delivery, and postnatal check-ups. This can help overcome transportation barriers, especially in remote areas with limited public transportation options.

7. Maternal Health Education Campaigns: Launch targeted education campaigns to raise awareness about the importance of maternal health and encourage women to seek timely and appropriate care. These campaigns can utilize various communication channels, including radio, television, social media, and community outreach programs.

8. Integration of Maternal Health Services: Strengthen the integration of maternal health services with other healthcare programs, such as family planning, immunization, and nutrition services. This can improve the efficiency and effectiveness of service delivery and ensure comprehensive care for women and their children.

9. Public-Private Partnerships: Foster partnerships between the public and private sectors to improve access to maternal health services. This can involve collaborations with private healthcare providers, pharmaceutical companies, and technology companies to leverage their resources and expertise in expanding access to care.

10. Maternal Health Financing: Advocate for increased investment in maternal health by governments and international donors. This can help improve infrastructure, train healthcare providers, and ensure the availability of essential medicines and supplies for maternal health services.

AI Innovations Description

The recommendation to improve access to maternal health based on the described study is to strengthen and scale up the Sustainable Undernutrition Reduction (SURE) program to non-covered districts in Northwest Ethiopia. This program has shown a positive impact on improving dietary diversity among children aged 6-23 months. By expanding the program to more districts, more children will have access to adequate and diversified diets, which are essential for their survival, growth, and development.

Additionally, it is recommended to provide health and nutrition counseling on Infant and Young Child Feeding (IYCF) during Antenatal Care (ANC) and Postnatal Care (PNC) services. This will ensure that mothers receive the necessary information and support to provide optimal nutrition for their children. ANC visits, PNC follow-ups, and participation in food preparation programs were found to be significantly associated with dietary diversity, indicating the importance of integrating nutrition education into existing maternal and child health services.

Furthermore, household visits by health extension workers were also found to be significantly associated with dietary diversity. Therefore, increasing the frequency of these visits and ensuring that health extension workers are trained in providing nutrition counseling can further improve access to maternal health and nutrition services.

Overall, by expanding the SURE program, integrating nutrition counseling into ANC and PNC services, and increasing household visits by health extension workers, access to maternal health and improved dietary diversity among children can be achieved in Northwest Ethiopia.

AI Innovations Methodology

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

1. Strengthen and scale up the Sustainable Undernutrition Reduction (SURE) program to non-covered districts: The study found that the proportion of adequate dietary diversity was higher among children in the program compared to those outside of the program. Therefore, expanding the program to districts that are not currently covered can help improve access to maternal health services.

2. Provide health and nutrition counseling on Infant and Young Child Feeding (IYCF) during Antenatal Care (ANC) and Postnatal Care (PNC) services: The study identified ANC visits, PNC follow-ups, and participating in food preparation programs as factors significantly associated with dietary diversity. Integrating health and nutrition counseling on IYCF into ANC and PNC services can help improve maternal and child nutrition.

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 proportion of pregnant women receiving ANC, the proportion of women receiving PNC, or the proportion of women with adequate dietary diversity.

2. Collect baseline data: Gather data on the current status of the indicators in the target population. This could involve conducting surveys, reviewing existing data, or using other data collection methods.

3. Implement the recommendations: Introduce the recommended interventions, such as scaling up the SURE program and providing health and nutrition counseling during ANC and PNC services.

4. Monitor and evaluate: Continuously monitor the implementation of the interventions and collect data on the indicators. This could involve conducting follow-up surveys or using routine data collection systems.

5. Analyze the data: Compare the baseline data with the post-intervention data to assess the impact of the recommendations on the indicators. This could be done using statistical analysis techniques, such as calculating proportions, conducting regression analyses, or using other appropriate methods.

6. Interpret the results: Analyze the findings to determine the extent to which the recommendations have improved access to maternal health. Consider factors that may have influenced the outcomes, such as contextual factors or implementation challenges.

7. Adjust and refine: Based on the results, make any necessary adjustments or refinements to the interventions to further improve access to maternal health. This could involve modifying the implementation strategies, addressing identified barriers, or expanding successful interventions to other areas.

By following this methodology, stakeholders can assess the impact of the recommendations on improving access to maternal health and make informed decisions for future interventions and programs.

Author

Dima Health

Statistics:

Citations: 8

Identifiers:

DOI: 10.1186/s12939-019-1120-1

Research Areas:

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

Study Countries:

Ethiopia

Study Design:

Case-Control Study, Cohort Study, Cross Sectional Study, Grounded Theory, randomised-control-trial

Study Approach:

Quantitative

Participants Gender:

Female