Dietary diversity and associated factors among children (6–23 months) in Gedeo zone, Ethiopia: cross – sectional study

Italian Journal of Pediatrics, Volume 47, No. 1, Year 2021

Interpretation

Introduction: Different foods and food groups are good sources for various macro- and micronutrients. Diversified diet play an important role in both physical and mental growth and development of children. However, meeting minimum standards of dietary diversity for children is a challenge in many developing countries including Ethiopia. Objective: To assess dietary diversity and associated factors among children (6–23 months) in Gedieo Zone, Ethiopia. Method: Community based cross-sectional study was carried out at Gedieo Zone, Ethiopia, from January to March 15, 2019. Multi-stage sampling technique was used to get a total of 665 children with the age of between 6 and 23 months from their kebeles. Data was collected by using face-to-face interview with structured questionnaire. Data was entered into Epidata version 3.1 and exported to Statistical Package for the Social Sciences (SPSS) version 23.0 for analyses. Variables having p < 0.25 at bivariate analysis were fitted to multivariable analysis. Multivariable logistic regression model was used at 95% confidence interval and with P-Value < 0.05. Bivariate. Result: A total of 665 children were participated with response rate of 96.2%. Only 199(29.9%) of children were met the minimum requirements for dietary diversity. Age of children [AOR 4.237(1.743–10.295))], Educational status [AOR 2.864(1.156–7.094)], Number of families [AOR 2.865(1.776–4.619))] and household wealth index [AOR4.390(2.300–8.380)] were significantly associated with Dietary Diversity of children. Conclusion: Only, one out of four children aged of 6–23 months attained the minimum dietary diversity score. Children from low socioeconomic status and mothers with no formal educational attainment need special attention to improve the practice of appropriate feeding of children. This study was conducted at Gedeo Zone, Ethiopia. Gedeo zone is located in Southern which is 360Km far from Addis Ababa, capital city of Ethiopia with the administrative center of Dilla town, Sidama in the South, Abaya in the North, H/Mariam in the East and Kericha in the West bounding the zone. Gedeo zone has six districts and two city administrations and has a total population of 1,086,768 (532,516(49%) males and 554, 225(51%) females, with an area of 1210.89 km2 [30]. And in the zone there are 6 districts and two town cities with 164 kebeles with 31 urban kebeles and 133 rural kebeles with a total of 276 health facilities from this one referral hospital, three district hospitals,38 health centers,146 health posts, five NGO clinics, 36 private clinics and 47 drug venders. The study was conducted from January1 to February 15, 2019 GC. Community based cross-sectional study was conducted. All children aged 6–23 months paired with their mothers who lived in Gedeo Zone. All children aged 6–23 months paired with their mothers from the selected kebeles. Mothers or caregivers of children aged 6–23 months who were permanent residents in Gedeo zone for the last 6 months were included in the study. Mothers or caregivers who have a health problem that can affect the interview process and households that had a special ceremony on the day prior to data collection were excluded from the study. The sample size was determined by using single population proportion formula taking 0.05 margin of errors at 95% confidence level. Considering the fact that the proportion closer to 50% will give the largest sample size. It was used. n = (Zα/2)2p (1 − p)/d2, where n = minimum sample size, Z 1-α/2 = significance level at α =0.05 (standard normal variable at 95% confidence level = 1.96) d = expected margin of error (5%) P = proportion of children DD (50%) Since, multi-stage sampling technique was used. Therefore, the sample size was multiplied by the design effect of 1.5 for possible non-response rate during the study, the final sample size was increased by 20% to: n = 691. A multi-stage sampling technique was used. Initially, out of 6 districts of the Zone, three districts are selected by using simple random sampling techniques (lottery method). Namely, Yirgacheffie (31kebeles), Bule (29kebeles) and Dilla Town (9kebeles). From a total of 69 kebeles; 11, 10 and 3 kebeles are selected by using simple random sampling techniques from Yirgacheffie district, Wonago district and Bule district respectively. The final sample size was allocated proportionally for each kebeles based on the number of children. Finally, respondents were selected by using a simple random sampling technique. Dietary Diversity of children from the age of 6–23 months’ Socio-demographic and economic factors: Maternal (age, educational level, occupation, status in household), child age, birth order, breastfeeding status, starting time of complementary feeding, child sex, residence, household wealth, family size, chicken rearing, milking cow, vegetable gardening, Health care related factors: Antenatal care (ANC), postnatal care (PNC), Delivery site, follow-up programs for Growth Monitoring program (GMP), Vaccination, Dietary advice, Morbidity related factors: Child infection, Food refusal of children, Diet and food access related factors, Household food insecurity, Primary Source of food. Minimum dietary diversity score (the number of food groups the child consumed during the 24-h preceding the survey) was used as a proxy for dietary diversity. It was calculated and divided into two categories of meeting the minimum dietary diversity or not (i.e., consumption of < 4 or ≥ 4 food groups) based on the WHO guidelines who fed > 4 groups of foods from the seven food groups in 24 h. The time period was considered as met the minimum dietary diversity of children [7]. Child DD – 24 h’ qualitative dietary recall data of the children were collected from the mothers who were responsible for feeding during the previous day of the study. The data was collected by using face-to-face interviews with a structured questionnaire. The questionnaire was prepared in English then translated to Amharic and Gedieo offa languages, then back-translated to English by an independent translator for its consistency. Data was collected by using 15 data collectors and 5 supervisors who had a diploma and above in the health profession. Three days training was given for data collectors and supervisors on the overall procedure of the study. Data were checked for completeness, edited, coded. The data was entered by using Epi data version 3.1 software then exported to SPSS version 23.0 statistical software for analysis. Descriptive statistics such as mean, median, frequency and percentage were used. Bivariate analysis was done and all explanatory variables with P-value less than 0.25 was regressed in to multivariable analysis. Multivariable analysis was employed to determine independent determinant factor among explanatory variables. Adjusted odds ratio (AOR), 95% confidence interval and P-value less than or equal to 0.05 was used to decide a statistically significant association with the outcome variable. Model fitness was assessed by using Hosmer and Lemeshow test. Multicollinearity was checked by using variance inflation factor (VIF) and tolerance test. The result of VIF was less than 2 while the tolerance test was greater than 0.1, which was within the normal limit. The finding of this study presented in the form of text, charts and tables. To keep the data quality, standard questionnaire was adapted. The data collectors and supervisors were trained for 02 days on the aims of the research, content of the questionnaire and how to conduct the interview to increase their performance in the activities. Data was collected on all days of the week since people may eat differently on different days of the week. All interviews were conducted at the residences of the study participants. Vacant or closed houses during the day of visit was revisited two times to maintain the required sample size. The Collected data was checked every day by the supervisors and principal investigator for its completeness and consistency. All questionnaires were kept under lock and key for security and confidentiality of obtained information. The finding of the study is presented to College of Medicine and Health Science, Dilla University. The findings of the study will be distributed to all health facility staffs and other organizations working on nutrition and maternity and child health. The findings will also be presented in different seminars, meetings and workshops and publication in scientific journal will be considered to enable for wider access.

AI Digest

Study Justification:

The study aimed to assess dietary diversity and associated factors among children (6–23 months) in Gedeo Zone, Ethiopia. This is important because diversified diets are crucial for the physical and mental growth and development of children. However, meeting minimum standards of dietary diversity for children is a challenge in many developing countries, including Ethiopia. By understanding the factors influencing dietary diversity, interventions can be developed to improve the feeding practices of children in the region.

Highlights:

– Only 29.9% of children aged 6–23 months met the minimum requirements for dietary diversity.
– Factors significantly associated with dietary diversity included the age of children, educational status of mothers, number of families, and household wealth index.
– Children from low socioeconomic status and mothers with no formal educational attainment require special attention to improve the practice of appropriate feeding.

Recommendations:

– Develop targeted interventions to improve dietary diversity among children aged 6–23 months in Gedeo Zone, Ethiopia.
– Implement educational programs to raise awareness among mothers about the importance of diversified diets and appropriate feeding practices.
– Strengthen socioeconomic support systems to address the barriers faced by families in providing diverse and nutritious foods for their children.

Key Role Players:

– Ministry of Health: Responsible for developing and implementing policies and programs related to child nutrition.
– Local Government Authorities: Involved in coordinating and supporting interventions at the community level.
– Health Facility Staff: Play a crucial role in providing counseling and support to mothers regarding appropriate feeding practices.
– Non-Governmental Organizations (NGOs): Can contribute by implementing nutrition programs and providing resources to improve dietary diversity.

Cost Items for Planning Recommendations:

– Development and printing of educational materials: Brochures, posters, and leaflets to raise awareness among mothers.
– Training programs: Conducting training sessions for health facility staff and community health workers on appropriate feeding practices.
– Community-based interventions: Organizing community events and workshops to promote diversified diets and provide practical guidance to mothers.
– Monitoring and evaluation: Allocating resources for regular monitoring and evaluation of the interventions to assess their effectiveness.
Please note that the cost items provided are general suggestions and may vary based on the specific context and resources available in Gedeo Zone, Ethiopia.

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 cross-sectional study, which provides valuable information on dietary diversity among children in Gedeo Zone, Ethiopia. The sample size calculation and sampling technique are clearly described, and data collection methods are explained. The statistical analysis used multivariable logistic regression to identify factors associated with dietary diversity. However, the abstract lacks information on the representativeness of the sample and the response rate. Additionally, the abstract does not mention any limitations of the study. To improve the evidence, it would be helpful to include information on the representativeness of the sample and the response rate, as well as a discussion of the study’s limitations.

Abstract

This study was conducted at Gedeo Zone, Ethiopia. Gedeo zone is located in Southern which is 360Km far from Addis Ababa, capital city of Ethiopia with the administrative center of Dilla town, Sidama in the South, Abaya in the North, H/Mariam in the East and Kericha in the West bounding the zone. Gedeo zone has six districts and two city administrations and has a total population of 1,086,768 (532,516(49%) males and 554, 225(51%) females, with an area of 1210.89 km2 [30]. And in the zone there are 6 districts and two town cities with 164 kebeles with 31 urban kebeles and 133 rural kebeles with a total of 276 health facilities from this one referral hospital, three district hospitals,38 health centers,146 health posts, five NGO clinics, 36 private clinics and 47 drug venders. The study was conducted from January1 to February 15, 2019 GC. Community based cross-sectional study was conducted. All children aged 6–23 months paired with their mothers who lived in Gedeo Zone. All children aged 6–23 months paired with their mothers from the selected kebeles. Mothers or caregivers of children aged 6–23 months who were permanent residents in Gedeo zone for the last 6 months were included in the study. Mothers or caregivers who have a health problem that can affect the interview process and households that had a special ceremony on the day prior to data collection were excluded from the study. The sample size was determined by using single population proportion formula taking 0.05 margin of errors at 95% confidence level. Considering the fact that the proportion closer to 50% will give the largest sample size. It was used. n = (Zα/2)2p (1 − p)/d2, where n = minimum sample size, Z 1-α/2 = significance level at α =0.05 (standard normal variable at 95% confidence level = 1.96) d = expected margin of error (5%) P = proportion of children DD (50%) Since, multi-stage sampling technique was used. Therefore, the sample size was multiplied by the design effect of 1.5 for possible non-response rate during the study, the final sample size was increased by 20% to: n = 691. A multi-stage sampling technique was used. Initially, out of 6 districts of the Zone, three districts are selected by using simple random sampling techniques (lottery method). Namely, Yirgacheffie (31kebeles), Bule (29kebeles) and Dilla Town (9kebeles). From a total of 69 kebeles; 11, 10 and 3 kebeles are selected by using simple random sampling techniques from Yirgacheffie district, Wonago district and Bule district respectively. The final sample size was allocated proportionally for each kebeles based on the number of children. Finally, respondents were selected by using a simple random sampling technique. Dietary Diversity of children from the age of 6–23 months’ Socio-demographic and economic factors: Maternal (age, educational level, occupation, status in household), child age, birth order, breastfeeding status, starting time of complementary feeding, child sex, residence, household wealth, family size, chicken rearing, milking cow, vegetable gardening, Health care related factors: Antenatal care (ANC), postnatal care (PNC), Delivery site, follow-up programs for Growth Monitoring program (GMP), Vaccination, Dietary advice, Morbidity related factors: Child infection, Food refusal of children, Diet and food access related factors, Household food insecurity, Primary Source of food. Minimum dietary diversity score (the number of food groups the child consumed during the 24-h preceding the survey) was used as a proxy for dietary diversity. It was calculated and divided into two categories of meeting the minimum dietary diversity or not (i.e., consumption of 4 groups of foods from the seven food groups in 24 h. The time period was considered as met the minimum dietary diversity of children [7]. Child DD – 24 h’ qualitative dietary recall data of the children were collected from the mothers who were responsible for feeding during the previous day of the study. The data was collected by using face-to-face interviews with a structured questionnaire. The questionnaire was prepared in English then translated to Amharic and Gedieo offa languages, then back-translated to English by an independent translator for its consistency. Data was collected by using 15 data collectors and 5 supervisors who had a diploma and above in the health profession. Three days training was given for data collectors and supervisors on the overall procedure of the study. Data were checked for completeness, edited, coded. The data was entered by using Epi data version 3.1 software then exported to SPSS version 23.0 statistical software for analysis. Descriptive statistics such as mean, median, frequency and percentage were used. Bivariate analysis was done and all explanatory variables with P-value less than 0.25 was regressed in to multivariable analysis. Multivariable analysis was employed to determine independent determinant factor among explanatory variables. Adjusted odds ratio (AOR), 95% confidence interval and P-value less than or equal to 0.05 was used to decide a statistically significant association with the outcome variable. Model fitness was assessed by using Hosmer and Lemeshow test. Multicollinearity was checked by using variance inflation factor (VIF) and tolerance test. The result of VIF was less than 2 while the tolerance test was greater than 0.1, which was within the normal limit. The finding of this study presented in the form of text, charts and tables. To keep the data quality, standard questionnaire was adapted. The data collectors and supervisors were trained for 02 days on the aims of the research, content of the questionnaire and how to conduct the interview to increase their performance in the activities. Data was collected on all days of the week since people may eat differently on different days of the week. All interviews were conducted at the residences of the study participants. Vacant or closed houses during the day of visit was revisited two times to maintain the required sample size. The Collected data was checked every day by the supervisors and principal investigator for its completeness and consistency. All questionnaires were kept under lock and key for security and confidentiality of obtained information. The finding of the study is presented to College of Medicine and Health Science, Dilla University. The findings of the study will be distributed to all health facility staffs and other organizations working on nutrition and maternity and child health. The findings will also be presented in different seminars, meetings and workshops and publication in scientific journal will be considered to enable for wider access.

Materials

N/A

Innovations

Based on the provided information, 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 pregnant women and new mothers with access to important health information, reminders for prenatal and postnatal care appointments, and educational resources on nutrition and child development.

2. Telemedicine: Establish telemedicine services that allow pregnant women in remote areas to consult with healthcare professionals through video calls or phone calls, reducing the need for travel and improving access to medical advice and support.

3. Community Health Workers: Train and deploy community health workers who can provide basic prenatal and postnatal care, conduct health education sessions, and refer women to healthcare facilities when necessary. This can help reach women in underserved areas who may have limited access to healthcare facilities.

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

5. Transportation Support: Develop transportation initiatives that provide pregnant women with affordable and reliable transportation to healthcare facilities for prenatal and postnatal care visits and emergency obstetric care. This can help overcome geographical barriers and ensure timely access to healthcare services.

6. Maternity Waiting Homes: Establish maternity waiting homes near healthcare facilities, where pregnant women from remote areas can stay during the final weeks of pregnancy to ensure proximity to skilled birth attendants and emergency obstetric care. This can help reduce delays in accessing care during childbirth.

7. Health Education and Awareness Campaigns: Conduct targeted health education and awareness campaigns to improve knowledge and understanding of maternal health issues, including the importance of prenatal care, nutrition, and breastfeeding. This can help empower women to make informed decisions about their health and seek appropriate care.

8. Public-Private Partnerships: Foster collaborations between the 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.

9. Maternal Health Financing: Explore innovative financing mechanisms, such as health insurance schemes or microfinance programs, to make maternal health services more affordable and accessible to women, particularly those from low-income backgrounds.

10. Data-driven Decision Making: Utilize data collection and analysis tools to identify gaps in maternal health service delivery and monitor progress towards improving access. This can help inform evidence-based decision making and resource allocation for targeted interventions.

AI Innovations Description

The study titled “Dietary diversity and associated factors among children (6–23 months) in Gedeo zone, Ethiopia: cross-sectional study” aimed to assess dietary diversity and its associated factors among children in Gedeo Zone, Ethiopia. The study found that only 29.9% of children met the minimum requirements for dietary diversity. Factors such as the age of children, educational status of mothers, number of families, and household wealth index were significantly associated with dietary diversity.

Based on the findings of this study, a recommendation to improve access to maternal health could be to implement interventions that focus on improving dietary diversity among children aged 6–23 months. This could include:

1. Nutrition education and counseling: Providing mothers and caregivers with information on the importance of a diversified diet for children’s growth and development, as well as practical guidance on how to achieve it.

2. Promotion of locally available nutritious foods: Encouraging the consumption of locally available foods that are rich in essential nutrients, such as fruits, vegetables, legumes, and animal-source foods.

3. Support for income generation activities: Implementing programs that help families improve their economic status, as household wealth was found to be associated with dietary diversity. This could include providing training and resources for income-generating activities, such as small-scale farming or entrepreneurship.

4. Strengthening health care services: Integrating nutrition counseling and support into existing maternal and child health services, such as antenatal care, postnatal care, and growth monitoring programs. This can help ensure that mothers receive appropriate guidance on feeding practices and have access to necessary resources.

5. Community engagement and awareness: Conducting community-based awareness campaigns to raise awareness about the importance of dietary diversity and its impact on maternal and child health. This could involve community meetings, radio programs, and the involvement of local leaders and influencers.

By implementing these recommendations, it is expected that access to maternal health can be improved by addressing the nutritional needs of children, which in turn can contribute to better maternal and child health outcomes.

AI Innovations Methodology

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

1. Increase awareness and education: Implement community-based education programs to raise awareness about the importance of maternal health and the benefits of proper nutrition during pregnancy.

2. Strengthen healthcare infrastructure: Improve the availability and accessibility of healthcare facilities, particularly in rural areas, by increasing the number of health centers and hospitals, and ensuring they are well-equipped and staffed.

3. Enhance antenatal and postnatal care: Provide comprehensive antenatal and postnatal care services, including regular check-ups, nutritional counseling, and support for breastfeeding.

4. Promote dietary diversity: Develop and implement programs that promote dietary diversity among pregnant women, including education on the importance of consuming a variety of foods to meet nutritional needs.

5. Address socioeconomic factors: Address socioeconomic factors that contribute to poor maternal health, such as poverty, lack of education, and limited access to resources. This can be done through targeted interventions, such as income-generating activities and educational programs.

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

1. Define indicators: Identify key indicators to measure the impact of the recommendations, such as the percentage of pregnant women receiving antenatal care, the percentage of women with access to healthcare facilities, and the percentage of women with improved dietary diversity.

2. Data collection: Collect baseline data on the selected indicators before implementing the recommendations. This can be done through surveys, interviews, and data from healthcare facilities.

3. Intervention implementation: Implement the recommended interventions, such as awareness campaigns, infrastructure improvements, and healthcare services.

4. Data analysis: After a certain period of time, collect post-intervention data on the selected indicators. Compare the post-intervention data with the baseline data to assess the impact of the recommendations.

5. Evaluation: Analyze the data to evaluate the effectiveness of the recommendations in improving access to maternal health. This can be done through statistical analysis and comparison of pre- and post-intervention data.

6. Adjustments and improvements: Based on the evaluation results, make any necessary adjustments or improvements to the recommendations to further enhance their impact on improving access to maternal health.

7. Monitoring and continuous improvement: Continuously monitor the indicators and make ongoing improvements to the recommendations to ensure sustained and long-term improvements in access to maternal health.

Author

Dima Health

Statistics:

Citations: 6

Identifiers:

DOI: 10.1186/s13052-021-01181-7

ISSN: 17208424

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

Study Approach:

Mixed-methods, Qualitative, Quantitative

Participants Gender:

Female