Dietary Diversity Among Pregnant Women in Gurage Zone, South Central Ethiopia: Assessment Based on Longitudinal Repeated Measurement

International Journal of Women's Health, Volume 14, Year 2022

Ukuhunyushwa

Purpose: Dietary diversity is a key proxy indicator of nutrient adequacy; however, limited studies have been done on it among pregnant women in Ethiopia. The study aimed to examine the prevalence of sub-optimal dietary diversity and its associated factors among pregnant women in Gurage zone, South Central Ethiopia. Materials and Methods: A mixed-method approach, a longitudinal study complemented with an exploratory qualitative study, was conducted. In the longitudinal study, a consecutively included sample of 668 pregnant women was followed in three rounds of survey. Dietary diversity was assessed using the minimum dietary diversity score for women (MDD-W) tool. The average of three dietary diversity scores was used to define overall diversity. Consuming less than 5 of 10 standard food groups was considered as suboptimal dietary diversity. Multivariable logistic regression analysis was used to identify predictors of suboptimal dietary diversity. Qualitative data were analysed using the thematic analysis method. Results: During the 16 to 20, 28 to 29 and 36 to 37 weeks of gestation surveys, 75.0, 78.7 and 76.5% of the women had sub-optimal dietary diversity. In aggregate, 84.4% (95% CI: 81.6, 87.3) of the women had sub-optimal dietary diversity. Rural residents (AOR: 1.91, 95% CI: 1.01, 3.62), women with no formal education (AOR: 5.51, 95% CI: 1.96, 15.53) and from food insecure households (AOR: 2.44, 95% CI: 1.07, 5.59) had higher odds of suboptimal dietary diversity. Women with higher nutritional knowledge (AOR: 0.92, 95% CI: 0.87, 0.98) were less likely to have suboptimal dietary diversity. Food taboos, poor nutritional literacy and pregnancy complications were also reported as factors affecting dietary diversity. Conclusion: Majority of pregnant women in the area had sub-optimal dietary diversity. Improving the socio-economic status and promoting nutrition knowledge may improve women’s dietary diversity. The Gurage Zone is one of the zones in the Southern Nations, Nationalities and Peoples Region of Ethiopia with its center at Wolkite town located 158 km west of Addis Ababa. In terms of population, it is a densely populated zone in Ethiopia with 441 people per square kilometer. It is composed of 14 districts and 5 town administrations.23 The zone has seven hospitals (two non-governmental and five governmental) and 72 health centers. The main source of food and economic activity is rain-fed agriculture. Common staple foods are enset (Ensete ventricosum), teff in the form of injera, green cabbage, maize and other cereals.23,24 Data were collected through an institution-based longitudinal study supplemented by an exploratory qualitative study. The study population was all pregnant women attending antenatal care (ANC) in selected districts of the Gurage zone. Women in their second trimester (16–20 weeks) with a singleton pregnancy, permanent residents (lived at least 1 year) and aged 15–49 years were included in the study. Pregnant women with known medical conditions like HIV/AIDS and diabetes mellitus were excluded. The participants in the focus group discussion (FGD) were pregnant women, health extension workers and women’s development army. The health extension workers are trained professionals providing essential health services at health post. The women’s development armies are community health workers with no formal professional education but chosen as a leader to serve five households within the same neighborhood based on their clear understanding and practice of health extension packages.25 The key informants selected for in-depth interviews were heads of health centers and heads of district health departments. The sample size was calculated using single population proportion formula by considering the following assumption: 55.2% prevalence of inadequate dietary diversity,13 95% of confidence level and 5% marginal errors. To accommodate for the multistage nature of the study, we applied a design effect of 1.5. Furthermore, 20% was added for compensating possible non-response. Ultimately, a sample size of 684 was reached. There were 6 FGDs, involving pregnant women, health extension workers and women’s development army. Eleven participants, including 3 heads of health centers, 3 heads of the district health office, 2 maternal and child nutrition coordinators and 3 community elders were contacted for in-depth interviews. The final sample of the qualitative study was 55. For the quantitative study, a multistage cluster sampling method was used to select pregnant women. Initially, the study area was divided into rural districts and urban town administrations. Six districts and two town administrations were taken to represent 14 districts and 5 town administrations within the Zone. Two representative healthy facilities were randomly selected from each district. Then, the sample size was allocated proportionally to 16 selected health facilities. The participants who fulfilled the eligibility criteria were consecutively included until the sample size was filled and those samples followed up to the end of pregnancy. For the qualitative study, a purposive sampling method was used to select participants whom we think could provide rich information on the existing maternal nutrition situation in the study area. An interviewer-administered structured questionnaire that was prepared partly by reviewing several published articles13–15,26,27 and partly by adopting standardized data collection tools2,28 was used for quantitative data collection. The questionnaire has different sections on socio-demographic variables, obstetric history, household food insecurity, maternal dietary diversity, maternal nutrition knowledge and practice. The questionnaire was prepared in the English language and translated to the local Amharic language. The consistency was checked by translating it back to English and was edited by a person with good knowledge of both languages. Data were collected by trained and supervised enumerators. The questionnaire was pretested among pregnant women not participating in the actual study but living in a similar setting. The actual data collection was done among women at their 16 to 20 weeks of gestation and maternal dietary diversity score was repeated in two subsequent phases; 28 to 29 weeks and 36 to 37 weeks of gestation. The completeness of data was checked each day at the end of data collection. Incomplete data was traced back and edited accordingly. The dependent variable of the study was maternal dietary diversity measured using the standard FAO’s minimum dietary diversity for women (MDD-W).2 This section of the questionnaire listed ten groups of food items: 1. Grains, white roots and tubers, 2. Pulses (beans, peas, and lentils), 3. Nuts and seeds, 4. Dairy products, 5. Meat, poultry, and fish, 6. Egg, 7. Dark green leafy vegetables, 8. Other vitamin A-rich fruits and vegetables, 9. Other vegetables, 10. Other fruits. Participants were asked whether they consumed items from each group in the preceding day from when they woke up in the morning, through the day and night for the subsequent 24 hours. Each food group consumed (scored 1) was summed up to a score ranging from 0 to 10. A score above 4 (women who consumed items from five or more groups) was categorized as optimal dietary diversity while those consuming food items from less than five groups were considered as having suboptimal dietary diversity.2,18 The average of sum of three dietary diversity scores was considered to determine overall dietary diversity across pregnancy. The independent variables included a basic socio-demographic profile of the study subjects including place of residence (urban or rural), marital status, religion, educational level, occupation, husband’s occupation, husband’s education, family size and monthly income, and reproductive history that were assessed using standard demographic and health survey (DHS) questionnaire.29 The other independent variable was household food insecurity that was assessed using the household food insecurity access scale (HFIAS). The scale had nine questions intended to assess the experience of household food insecurity that occurred within the previous month.30 The households were categorized into 4 levels of food insecurity: food secure and mildly, moderately, and severely food insecure as per guidelines.28 Maternal nutritional knowledge and practice-related variables were also considered as independent variables of the study. Maternal nutritional knowledge was assessed using a non-standard scale containing ten items. Then, ten nutrition-related questions asked were recorded as complete answers (scored 2), incomplete answers (scored 1) and wrong answers (scored 0). Ultimately, maternal nutritional knowledge was scored out of twenty. Maternal dietary practices including meal frequency, meal skip, avoidances of food, craving and household access to food aid were also assessed. Women asked whether they were getting at least three meals per day or not and other dietary practice variables were assessed by yes or no questions. A guide was used for the in-depth interviews and focus group discussions to explore factors contributing to dietary diversity among pregnant women, available in Appendix 1. The interview guide explored dietary practice in terms of diversity, knowledge on the advantages of a diversified diet and factors that influence dietary diversity during pregnancy. During data collection, each question was probed for further exploration and the responses were recorded in a notebook and digital electronic recorder for later transcription. The quantitative data were entered and cleaned using Epi-data statistical software and then exported to SPSS version 24. Frequency distribution, measure of central tendency and dispersion were used to describe the data. Numeric variables were checked for normality of the distribution by using probability plot and Shapiro Wilk test. The association between dependent and independent variables was assessed using bi-variable and multivariable logistic regression. To test independent predictors of dietary diversity, all independent variables with a p-value of less than 0.25 in the bi-variable logistic regression model were considered as candidate variables for the multivariable analysis. Then the relationship was presented using adjusted odds ratio (AOR) with its corresponding 95% confidence interval. For the qualitative study, research assistants who were familiar with the local language and culture were involved. The professional’s word-by-word transcribing of the data from audio records was done in the local language each day at the end of data collection. Then, the transcribed information was translated from the local Amharic language to the English language in the word document. The data were analyzed by thematic analysis using NVIVO-version 11 software. After re-organizing data, an exploration such as the summary of word frequency and word cloud was done. The relevant information was coded and categorized into different themes. Final analysis was done by exploring different factors and creating a hierarchy chart of themes.

I-AI Digest

Study Justification:

– Limited studies have been done on dietary diversity among pregnant women in Ethiopia.
– Dietary diversity is a key indicator of nutrient adequacy.
– Understanding the prevalence and factors associated with sub-optimal dietary diversity among pregnant women is important for improving maternal and child health outcomes.

Highlights:

– The study was conducted in the Gurage Zone, South Central Ethiopia.
– A mixed-method approach was used, including a longitudinal study and an exploratory qualitative study.
– The study included 668 pregnant women who were followed in three rounds of survey.
– The prevalence of sub-optimal dietary diversity among pregnant women was assessed using the minimum dietary diversity score for women (MDD-W) tool.
– Results showed that 84.4% of the women had sub-optimal dietary diversity.
– Factors associated with sub-optimal dietary diversity included rural residence, no formal education, food insecurity, and low nutritional knowledge.
– Qualitative data highlighted food taboos, poor nutritional literacy, and pregnancy complications as factors affecting dietary diversity.

Recommendations:

– Improve the socio-economic status of pregnant women in the Gurage Zone.
– Promote nutrition knowledge among pregnant women to improve dietary diversity.
– Address food insecurity to ensure access to a diverse range of foods.
– Raise awareness about the importance of dietary diversity during pregnancy and address cultural beliefs and practices that may hinder it.

Key Role Players:

– Health extension workers: Provide essential health services and can play a role in promoting nutrition knowledge and practices among pregnant women.
– Women’s development army: Community health workers who can support pregnant women in improving their dietary diversity.
– Heads of health centers and district health departments: Provide leadership and support in implementing interventions to improve dietary diversity among pregnant women.
– Maternal and child nutrition coordinators: Provide expertise and guidance in developing and implementing nutrition interventions.

Cost Items for Planning Recommendations:

– Training and capacity building for health extension workers and women’s development army.
– Awareness campaigns and educational materials on nutrition and dietary diversity.
– Support for income-generating activities to improve the socio-economic status of pregnant women.
– Food security interventions, such as providing food aid or promoting agricultural practices.
– Monitoring and evaluation activities to assess the impact of interventions and make necessary adjustments.

Amandla Obufakazi

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is rated 7 because it provides a clear description of the study design, sample size, data collection methods, and statistical analysis. However, it does not provide information on the validity and reliability of the measures used or the generalizability of the findings. To improve the evidence, the abstract could include information on the validity and reliability of the measures used, as well as the limitations of the study. Additionally, it could provide information on the generalizability of the findings to other populations or settings.

Abstract

The Gurage Zone is one of the zones in the Southern Nations, Nationalities and Peoples Region of Ethiopia with its center at Wolkite town located 158 km west of Addis Ababa. In terms of population, it is a densely populated zone in Ethiopia with 441 people per square kilometer. It is composed of 14 districts and 5 town administrations.23 The zone has seven hospitals (two non-governmental and five governmental) and 72 health centers. The main source of food and economic activity is rain-fed agriculture. Common staple foods are enset (Ensete ventricosum), teff in the form of injera, green cabbage, maize and other cereals.23,24 Data were collected through an institution-based longitudinal study supplemented by an exploratory qualitative study. The study population was all pregnant women attending antenatal care (ANC) in selected districts of the Gurage zone. Women in their second trimester (16–20 weeks) with a singleton pregnancy, permanent residents (lived at least 1 year) and aged 15–49 years were included in the study. Pregnant women with known medical conditions like HIV/AIDS and diabetes mellitus were excluded. The participants in the focus group discussion (FGD) were pregnant women, health extension workers and women’s development army. The health extension workers are trained professionals providing essential health services at health post. The women’s development armies are community health workers with no formal professional education but chosen as a leader to serve five households within the same neighborhood based on their clear understanding and practice of health extension packages.25 The key informants selected for in-depth interviews were heads of health centers and heads of district health departments. The sample size was calculated using single population proportion formula by considering the following assumption: 55.2% prevalence of inadequate dietary diversity,13 95% of confidence level and 5% marginal errors. To accommodate for the multistage nature of the study, we applied a design effect of 1.5. Furthermore, 20% was added for compensating possible non-response. Ultimately, a sample size of 684 was reached. There were 6 FGDs, involving pregnant women, health extension workers and women’s development army. Eleven participants, including 3 heads of health centers, 3 heads of the district health office, 2 maternal and child nutrition coordinators and 3 community elders were contacted for in-depth interviews. The final sample of the qualitative study was 55. For the quantitative study, a multistage cluster sampling method was used to select pregnant women. Initially, the study area was divided into rural districts and urban town administrations. Six districts and two town administrations were taken to represent 14 districts and 5 town administrations within the Zone. Two representative healthy facilities were randomly selected from each district. Then, the sample size was allocated proportionally to 16 selected health facilities. The participants who fulfilled the eligibility criteria were consecutively included until the sample size was filled and those samples followed up to the end of pregnancy. For the qualitative study, a purposive sampling method was used to select participants whom we think could provide rich information on the existing maternal nutrition situation in the study area. An interviewer-administered structured questionnaire that was prepared partly by reviewing several published articles13–15,26,27 and partly by adopting standardized data collection tools2,28 was used for quantitative data collection. The questionnaire has different sections on socio-demographic variables, obstetric history, household food insecurity, maternal dietary diversity, maternal nutrition knowledge and practice. The questionnaire was prepared in the English language and translated to the local Amharic language. The consistency was checked by translating it back to English and was edited by a person with good knowledge of both languages. Data were collected by trained and supervised enumerators. The questionnaire was pretested among pregnant women not participating in the actual study but living in a similar setting. The actual data collection was done among women at their 16 to 20 weeks of gestation and maternal dietary diversity score was repeated in two subsequent phases; 28 to 29 weeks and 36 to 37 weeks of gestation. The completeness of data was checked each day at the end of data collection. Incomplete data was traced back and edited accordingly. The dependent variable of the study was maternal dietary diversity measured using the standard FAO’s minimum dietary diversity for women (MDD-W).2 This section of the questionnaire listed ten groups of food items: 1. Grains, white roots and tubers, 2. Pulses (beans, peas, and lentils), 3. Nuts and seeds, 4. Dairy products, 5. Meat, poultry, and fish, 6. Egg, 7. Dark green leafy vegetables, 8. Other vitamin A-rich fruits and vegetables, 9. Other vegetables, 10. Other fruits. Participants were asked whether they consumed items from each group in the preceding day from when they woke up in the morning, through the day and night for the subsequent 24 hours. Each food group consumed (scored 1) was summed up to a score ranging from 0 to 10. A score above 4 (women who consumed items from five or more groups) was categorized as optimal dietary diversity while those consuming food items from less than five groups were considered as having suboptimal dietary diversity.2,18 The average of sum of three dietary diversity scores was considered to determine overall dietary diversity across pregnancy. The independent variables included a basic socio-demographic profile of the study subjects including place of residence (urban or rural), marital status, religion, educational level, occupation, husband’s occupation, husband’s education, family size and monthly income, and reproductive history that were assessed using standard demographic and health survey (DHS) questionnaire.29 The other independent variable was household food insecurity that was assessed using the household food insecurity access scale (HFIAS). The scale had nine questions intended to assess the experience of household food insecurity that occurred within the previous month.30 The households were categorized into 4 levels of food insecurity: food secure and mildly, moderately, and severely food insecure as per guidelines.28 Maternal nutritional knowledge and practice-related variables were also considered as independent variables of the study. Maternal nutritional knowledge was assessed using a non-standard scale containing ten items. Then, ten nutrition-related questions asked were recorded as complete answers (scored 2), incomplete answers (scored 1) and wrong answers (scored 0). Ultimately, maternal nutritional knowledge was scored out of twenty. Maternal dietary practices including meal frequency, meal skip, avoidances of food, craving and household access to food aid were also assessed. Women asked whether they were getting at least three meals per day or not and other dietary practice variables were assessed by yes or no questions. A guide was used for the in-depth interviews and focus group discussions to explore factors contributing to dietary diversity among pregnant women, available in Appendix 1. The interview guide explored dietary practice in terms of diversity, knowledge on the advantages of a diversified diet and factors that influence dietary diversity during pregnancy. During data collection, each question was probed for further exploration and the responses were recorded in a notebook and digital electronic recorder for later transcription. The quantitative data were entered and cleaned using Epi-data statistical software and then exported to SPSS version 24. Frequency distribution, measure of central tendency and dispersion were used to describe the data. Numeric variables were checked for normality of the distribution by using probability plot and Shapiro Wilk test. The association between dependent and independent variables was assessed using bi-variable and multivariable logistic regression. To test independent predictors of dietary diversity, all independent variables with a p-value of less than 0.25 in the bi-variable logistic regression model were considered as candidate variables for the multivariable analysis. Then the relationship was presented using adjusted odds ratio (AOR) with its corresponding 95% confidence interval. For the qualitative study, research assistants who were familiar with the local language and culture were involved. The professional’s word-by-word transcribing of the data from audio records was done in the local language each day at the end of data collection. Then, the transcribed information was translated from the local Amharic language to the English language in the word document. The data were analyzed by thematic analysis using NVIVO-version 11 software. After re-organizing data, an exploration such as the summary of word frequency and word cloud was done. The relevant information was coded and categorized into different themes. Final analysis was done by exploring different factors and creating a hierarchy chart of themes.

Izinto zokwakha

N/A

Emisha

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 with information on dietary diversity, nutrition, and maternal health. These apps can also send reminders and notifications to encourage healthy eating habits and regular antenatal care visits.

2. Community Health Workers: Train and deploy community health workers to educate pregnant women in rural areas about the importance of dietary diversity and provide them with guidance on nutrition during pregnancy. These workers can also conduct regular home visits to monitor the dietary practices of pregnant women and provide support and counseling.

3. Nutrition Education Programs: Establish nutrition education programs specifically targeting pregnant women in the Gurage Zone. These programs can include workshops, cooking demonstrations, and interactive sessions to educate women about the benefits of a diverse diet and provide them with practical tips on meal planning and preparation.

4. Food Security Initiatives: Implement initiatives to improve food security in the Gurage Zone, such as promoting sustainable agriculture practices, providing access to irrigation systems, and supporting income-generating activities for pregnant women and their families. This can help ensure a steady supply of diverse and nutritious foods for pregnant women.

5. Public-Private Partnerships: Foster collaborations between the government, non-profit organizations, and private sector entities to improve access to affordable and diverse food options for pregnant women. This can involve initiatives such as subsidizing the cost of nutritious foods, establishing community gardens, and supporting local food producers.

6. Telemedicine Services: Introduce telemedicine services that allow pregnant women in remote areas to consult with healthcare professionals and receive guidance on nutrition and maternal health through virtual platforms. This can help overcome geographical barriers and ensure access to timely and accurate information.

7. Maternal Health Vouchers: Implement voucher programs that provide pregnant women with financial assistance to access essential maternal health services, including nutrition counseling and antenatal care visits. These vouchers can be distributed through healthcare facilities or community-based organizations.

8. Public Awareness Campaigns: Launch public awareness campaigns to educate the general population about the importance of maternal health and the role of dietary diversity in ensuring a healthy pregnancy. These campaigns can utilize various media channels, including radio, television, and social media, to reach a wide audience.

It is important to note that the implementation of these innovations should be context-specific and tailored to the needs and resources of the Gurage Zone in South Central Ethiopia.

AI Innovations Description

The study titled “Dietary Diversity Among Pregnant Women in Gurage Zone, South Central Ethiopia: Assessment Based on Longitudinal Repeated Measurement” aims to examine the prevalence of sub-optimal dietary diversity and its associated factors among pregnant women in Gurage zone, South Central Ethiopia. The study used a mixed-method approach, including a longitudinal study and an exploratory qualitative study.

The findings of the study revealed that a majority of pregnant women in the Gurage zone had sub-optimal dietary diversity. During the surveys conducted at different stages of gestation, 75.0%, 78.7%, and 76.5% of the women had sub-optimal dietary diversity. In aggregate, 84.4% of the women had sub-optimal dietary diversity. Factors associated with sub-optimal dietary diversity included rural residence, lack of formal education, food insecurity, and lower nutritional knowledge. The study also identified food taboos, poor nutritional literacy, and pregnancy complications as factors affecting dietary diversity.

Based on these findings, a recommendation to improve access to maternal health would be to develop interventions that focus on improving the socio-economic status of pregnant women and promoting nutrition knowledge. This could include providing education and resources to pregnant women, particularly those in rural areas and with limited education, to enhance their understanding of the importance of a diverse and nutritious diet during pregnancy. Additionally, efforts should be made to address food insecurity and provide support to pregnant women from food-insecure households. By addressing these factors, it is expected that women’s dietary diversity and overall maternal health outcomes will improve.

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 education programs to raise awareness about the importance of maternal health and nutrition. This can include educating pregnant women and their families about the benefits of a diverse and nutritious diet during pregnancy.

2. Improve access to nutritious food: Enhance access to a variety of nutritious foods by promoting agricultural practices that increase crop diversity and improve food security. This can involve providing support and resources to farmers to grow a wider range of crops, including fruits, vegetables, and protein-rich foods.

3. Strengthen healthcare infrastructure: Invest in improving healthcare facilities, particularly in rural areas, to ensure that pregnant women have access to quality antenatal care services. This can include training healthcare providers, equipping facilities with necessary resources and equipment, and improving transportation systems to facilitate access to healthcare facilities.

4. Address socio-economic factors: Address socio-economic factors that contribute to suboptimal dietary diversity among pregnant women. This can involve implementing programs to improve women’s education, income generation opportunities, and household food security.

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

1. Define indicators: Identify specific indicators that can measure the impact of the recommendations, such as the percentage of pregnant women with improved dietary diversity, the number of healthcare facilities with improved services, or changes in maternal health outcomes.

2. Collect baseline data: Gather baseline data on the current status of maternal health and dietary diversity in the target population. This can involve conducting surveys, interviews, or reviewing existing data sources.

3. Develop a simulation model: Create a simulation model that incorporates the identified recommendations and their potential impact on the defined indicators. This model should consider factors such as population size, geographical distribution, and socio-economic characteristics.

4. Input data and parameters: Input the collected baseline data into the simulation model, along with relevant parameters such as the expected implementation timeline, resource allocation, and potential barriers or challenges.

5. Run simulations: Run the simulation model to project the potential impact of the recommendations on improving access to maternal health. This can involve running multiple scenarios to assess the effectiveness of different interventions or combinations of interventions.

6. Analyze results: Analyze the simulation results to evaluate the projected impact of the recommendations. This can include assessing changes in the defined indicators, identifying potential gaps or limitations, and exploring alternative strategies.

7. Refine and iterate: Based on the analysis of the simulation results, refine the recommendations and simulation model as needed. Iterate the process to further optimize the interventions and improve the accuracy of the projections.

By following this methodology, stakeholders can gain insights into the potential impact of different recommendations on improving access to maternal health and make informed decisions on implementing the most effective interventions.

Ababhali & Co-Ababhali

Statistics:

Authors: 3

Identifiers:

DOI: 10.2147/IJWH.S354536

Research Areas:

Community Interventions, Disparities, Food Security, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Noncommunicable Diseases, Quality of Care, Sexual and Reproductive Health, Social Determinants, Workforce

Study Countries:

Ethiopia

Study Design:

Case-Control Study, Cohort Study, Cross Sectional Study, Exploratory Study, Grounded Theory

Study Approach:

Mixed-methods, Qualitative, Quantitative

Participants Gender:

Female

Yabelana ngalokhu: