The social stratification of availability, affordability, and consumption of food in families with preschoolers in addis ababa; the eat addis study in Ethiopia

Nutrients, Volume 12, No. 10, Year 2020

Ukuhunyushwa

The aim of this study was to understand the quality of diet being consumed among families in Addis Ababa, and to what extent social stratification and perceptions of availability and affordability affect healthy food consumption. Data were collected from 5467 households in a face-to-face interview with mothers/caretakers and analyzed using mixed effect logistic regression models. All family food groups, except fish were perceived to be available by more than 90% of the participants. The food groups cereals/nuts/seeds, other vegetables, and legumes were considered highly affordable (80%) and were the most consumed (>75%). Households with the least educated mothers and those in the lowest wealth quintile had the lowest perception of affordability and also consumption. Consumption of foods rich in micronutrients and animal sources were significantly higher among households with higher perceived affordability, the highest wealth quintile, and with mothers who had better education. Households in Addis Ababa were generally seen to have a monotonous diet, despite the high perceived availability of different food groups within the food environment. There is a considerable difference in consumption of nutrient-rich foods across social strata, hence the cities food policies need to account for social differences in order to improve the nutritional status of the community. A community-based cross-sectional study was carried out in the months of July–August, 2017 and January–February, 2018 in Addis Ababa, the capital city of Ethiopia. Addis Ababa has been experiencing a rapid increase in population size along with diminishing open public space [36]. The rapid expansion of residential areas to accommodate the increasing population size has led to the loss of highly fertile agricultural land and green spaces thereby reducing food production within and in the vicinity of the city [37]. This in turn, escalates the food prices and further jeopardizes the food and nutrition security of urban dwellers. Additionally, the city has one of the highest literacy rates in the country with 80% of its population having basic literacy level, and a high level of unemployment with 23.5% of the population in this urban area being unemployed [38,39]. The study used a multi-stage sampling procedure. All 116 woredas (districts) in the city were included in the study in each of the two rounds of survey: First round took place during the wet season and second round during the dry season to consider seasonal variations. Each district was further divided into roughly five equal geographical clusters and one cluster was then selected using simple random sampling. Subsequently, systematic random sampling was used to visit 60 households in each cluster to check for eligibility. All households with at least one under five-year-old child were invited to participate. Additional households were visited if there were less than 20 eligible households in the cluster. Households in which the mother/caregiver was not available to interview after 3 repeat visits were then declared unavailable and excluded from the study without replacement. The necessary data for the study were collected through face to face interviews with the mother/caregiver using a structured questionnaire. The questionnaires included sections on demographic and household characteristics, perceived availability and affordability of food groups, and family food consumption. The questionnaire comprised of standard measures as well as newly developed measures to assess the perceived affordability and availability; this was based upon literature and the research team’s expertise in this field. A photo gallery of common foods was used to help respondents understand the food groups. The questionnaires were initially developed in English and translated into Amharic language (the official language of Ethiopia) by a panel of translators. The questionnaires were pretested in households that were not included in the study for comprehension of concepts and language. Data were collected using tablets pre-programmed with the questionnaire. The data collectors were trained on the objective of the study, the content of the questionnaires, the sampling procedures, and the use of the tablets. The data collection was supervised daily by members of the research team and on-site support was given to the teams to ensure the study procedures were strictly observed. Data were received directly onto the data server at the Addis Continental Institute of Public Health and a data manager provided regular feedback on the quality of data. The age of the mothers was grouped into five categories: 15–24, 25–34, 35–44, and 45+, and their educational levels were summarized as: never attended/finished a grade, grade 1–4, grade 5–8, grade 9–12, and college. Marital status was categorized as currently married (in union) and currently not married (single). Wealth index was computed from multiple variables including ownership of house, type of housing unit, housing material (floor, roof, wall material), access to a separate toilet facility and clean drinking water, and assets (including bicycle, motorbike, car, cell-phone, radio, TV, refrigerator, bed, electric stove for making the local bread “Injera” and a saving account) [40]. Households were then divided into wealth quintiles (lowest, second, third, fourth, and highest) to indicate their relative economic status. For this study, a modified version of the women’s minimum dietary diversity indicator was used; it measures quality of diet, both in terms of energy and micronutrient adequacy [41] instead of using the usual household diet diversity measures which reflect more on the economic access and dietary energy [42]. This modified measure used in this study, hereafter referred to “family food groups”, has eleven food groups rather than 10 as in the usual measures. Based on the local consumption patterns; food groups “fish and meat” and “Vitamin A rich fruits and vegetables” were both split; while merging “legumes” with “nuts and seeds” groups since the latter is not commonly consumed in the study setting. Perceived availability of family food was measured using a photo gallery of common foods from each of the family food groups (11-family food groups). Mothers were asked whether any of the foods shown in the photo were available in the market. The response options were “Yes”, “No”, and “Don’t know”. Then, each food group was dichotomized as “available” if the responses were “yes” and “not available” if the responses were “no”. “Don’t know” responses were treated as missing. Perceived affordability of family food was assessed by asking the mother/caregiver, “How often can your family afford to consume any of these foods?” Response options were coded: “as often as wanted”, “a little less frequently than wanted”, and “much less frequently than wanted/not at all”. Perception of affordability was dichotomized as “affordable” if response was “as often as wanted” and “not affordable” for the other categories. Household food consumption was measured by a combination of two complimentary methods; first the mothers were asked to recall foods consumed by the family in the last 24 h. Then, the enumerator read and showed the photos of common foods by family food group whilst asking: “did any household member consume any of these foods in this photo in the last 24 h?” The response options included “yes”, “no”, and “don’t know”; the response category “don’t know” was treated as missing. Analysis was conducted using the statistical software program Stata version 15.0 [43]. Standard descriptive statistics were computed for outcome and explanatory variables including percentages and their respective confidence intervals for categorical variables as well as mean and standard deviation for continuous variables. Mixed effect logistic regression models were used to assess the bivariate and multivariable associations between the dependent variables’ family food consumption and the explanatory variables including perceived affordability, wealth quintiles, and maternal education. All models were adjusted for clustering at district level. p-values of <0.05 were considered as statistically significant. The variance of random effect value along with 95% confidence intervals (CI) and standard error (SE) computed to observe heterogeneity between districts. An additional intraclass correlation coefficient (ICC) was conducted to check variance at district level. Ethical approval for the EAT Addis study was obtained from the institutional review board of Addis Continental Institute of Public Health with reference number ACIPH/IRB/004/2015 and University of Gondar institutional review board reference number V/P/RCS/05/352/2019. Verbal informed consent was obtained from each of the participants after explaining the purpose of the study and addressing any questions. Permission to conduct the study was obtained from all sub-cities and district level health offices.

I-AI Digest

Study Justification:

– The study aimed to understand the quality of diet among families in Addis Ababa, Ethiopia, and how social stratification and perceptions of availability and affordability affect healthy food consumption.
– The study is important because it provides insights into the factors influencing food consumption patterns and highlights the need for targeted interventions to improve the nutritional status of the community.

Study Highlights:

– Data were collected from 5467 households in Addis Ababa through face-to-face interviews with mothers/caretakers.
– The study found that all family food groups, except fish, were perceived to be available by more than 90% of the participants.
– Cereals/nuts/seeds, other vegetables, and legumes were considered highly affordable (80%) and were the most consumed (>75%).
– Households with the least educated mothers and those in the lowest wealth quintile had the lowest perception of affordability and consumption.
– Consumption of foods rich in micronutrients and animal sources was significantly higher among households with higher perceived affordability, the highest wealth quintile, and better-educated mothers.
– The study revealed a monotonous diet among households in Addis Ababa, despite the high perceived availability of different food groups.

Recommendations for Lay Reader and Policy Maker:

– The study recommends that food policies in Addis Ababa should consider social differences to improve the nutritional status of the community.
– Targeted interventions should be implemented to address the low perception of affordability and consumption among households with less educated mothers and those in the lowest wealth quintile.
– Efforts should be made to promote the consumption of nutrient-rich foods, especially among households with lower perceived affordability.
– Strategies to diversify the diet and increase access to a variety of food groups should be developed and implemented.

Key Role Players:

– Government agencies responsible for food and nutrition policies
– Non-governmental organizations working in the field of nutrition and food security
– Community leaders and local authorities
– Health professionals and nutritionists
– Researchers and academics

Cost Items for Planning Recommendations:

– Development and implementation of targeted interventions: funding for program design, materials, and implementation
– Awareness campaigns and educational programs: funding for materials, training, and dissemination
– Monitoring and evaluation: funding for data collection, analysis, and reporting
– Research and data analysis: funding for research activities, data collection, and analysis
– Collaboration and coordination: funding for meetings, workshops, and networking activities

Amandla Obufakazi

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is relatively strong, but there are some areas for improvement. The study used a large sample size and employed mixed effect logistic regression models for analysis, which enhances the validity of the findings. The study also collected data through face-to-face interviews using a structured questionnaire, which helps ensure data quality. However, there are a few areas that could be improved. Firstly, the abstract does not provide information on the response rate, which is important for assessing the representativeness of the sample. Secondly, the abstract does not mention any measures taken to address potential biases, such as selection bias or social desirability bias. It would be beneficial to include information on how these biases were addressed in the study design and analysis. Lastly, the abstract does not provide information on the limitations of the study, such as potential confounding factors or generalizability of the findings. Including this information would help readers interpret the results more accurately.

Abstract

A community-based cross-sectional study was carried out in the months of July–August, 2017 and January–February, 2018 in Addis Ababa, the capital city of Ethiopia. Addis Ababa has been experiencing a rapid increase in population size along with diminishing open public space [36]. The rapid expansion of residential areas to accommodate the increasing population size has led to the loss of highly fertile agricultural land and green spaces thereby reducing food production within and in the vicinity of the city [37]. This in turn, escalates the food prices and further jeopardizes the food and nutrition security of urban dwellers. Additionally, the city has one of the highest literacy rates in the country with 80% of its population having basic literacy level, and a high level of unemployment with 23.5% of the population in this urban area being unemployed [38,39]. The study used a multi-stage sampling procedure. All 116 woredas (districts) in the city were included in the study in each of the two rounds of survey: First round took place during the wet season and second round during the dry season to consider seasonal variations. Each district was further divided into roughly five equal geographical clusters and one cluster was then selected using simple random sampling. Subsequently, systematic random sampling was used to visit 60 households in each cluster to check for eligibility. All households with at least one under five-year-old child were invited to participate. Additional households were visited if there were less than 20 eligible households in the cluster. Households in which the mother/caregiver was not available to interview after 3 repeat visits were then declared unavailable and excluded from the study without replacement. The necessary data for the study were collected through face to face interviews with the mother/caregiver using a structured questionnaire. The questionnaires included sections on demographic and household characteristics, perceived availability and affordability of food groups, and family food consumption. The questionnaire comprised of standard measures as well as newly developed measures to assess the perceived affordability and availability; this was based upon literature and the research team’s expertise in this field. A photo gallery of common foods was used to help respondents understand the food groups. The questionnaires were initially developed in English and translated into Amharic language (the official language of Ethiopia) by a panel of translators. The questionnaires were pretested in households that were not included in the study for comprehension of concepts and language. Data were collected using tablets pre-programmed with the questionnaire. The data collectors were trained on the objective of the study, the content of the questionnaires, the sampling procedures, and the use of the tablets. The data collection was supervised daily by members of the research team and on-site support was given to the teams to ensure the study procedures were strictly observed. Data were received directly onto the data server at the Addis Continental Institute of Public Health and a data manager provided regular feedback on the quality of data. The age of the mothers was grouped into five categories: 15–24, 25–34, 35–44, and 45+, and their educational levels were summarized as: never attended/finished a grade, grade 1–4, grade 5–8, grade 9–12, and college. Marital status was categorized as currently married (in union) and currently not married (single). Wealth index was computed from multiple variables including ownership of house, type of housing unit, housing material (floor, roof, wall material), access to a separate toilet facility and clean drinking water, and assets (including bicycle, motorbike, car, cell-phone, radio, TV, refrigerator, bed, electric stove for making the local bread “Injera” and a saving account) [40]. Households were then divided into wealth quintiles (lowest, second, third, fourth, and highest) to indicate their relative economic status. For this study, a modified version of the women’s minimum dietary diversity indicator was used; it measures quality of diet, both in terms of energy and micronutrient adequacy [41] instead of using the usual household diet diversity measures which reflect more on the economic access and dietary energy [42]. This modified measure used in this study, hereafter referred to “family food groups”, has eleven food groups rather than 10 as in the usual measures. Based on the local consumption patterns; food groups “fish and meat” and “Vitamin A rich fruits and vegetables” were both split; while merging “legumes” with “nuts and seeds” groups since the latter is not commonly consumed in the study setting. Perceived availability of family food was measured using a photo gallery of common foods from each of the family food groups (11-family food groups). Mothers were asked whether any of the foods shown in the photo were available in the market. The response options were “Yes”, “No”, and “Don’t know”. Then, each food group was dichotomized as “available” if the responses were “yes” and “not available” if the responses were “no”. “Don’t know” responses were treated as missing. Perceived affordability of family food was assessed by asking the mother/caregiver, “How often can your family afford to consume any of these foods?” Response options were coded: “as often as wanted”, “a little less frequently than wanted”, and “much less frequently than wanted/not at all”. Perception of affordability was dichotomized as “affordable” if response was “as often as wanted” and “not affordable” for the other categories. Household food consumption was measured by a combination of two complimentary methods; first the mothers were asked to recall foods consumed by the family in the last 24 h. Then, the enumerator read and showed the photos of common foods by family food group whilst asking: “did any household member consume any of these foods in this photo in the last 24 h?” The response options included “yes”, “no”, and “don’t know”; the response category “don’t know” was treated as missing. Analysis was conducted using the statistical software program Stata version 15.0 [43]. Standard descriptive statistics were computed for outcome and explanatory variables including percentages and their respective confidence intervals for categorical variables as well as mean and standard deviation for continuous variables. Mixed effect logistic regression models were used to assess the bivariate and multivariable associations between the dependent variables’ family food consumption and the explanatory variables including perceived affordability, wealth quintiles, and maternal education. All models were adjusted for clustering at district level. p-values of <0.05 were considered as statistically significant. The variance of random effect value along with 95% confidence intervals (CI) and standard error (SE) computed to observe heterogeneity between districts. An additional intraclass correlation coefficient (ICC) was conducted to check variance at district level. Ethical approval for the EAT Addis study was obtained from the institutional review board of Addis Continental Institute of Public Health with reference number ACIPH/IRB/004/2015 and University of Gondar institutional review board reference number V/P/RCS/05/352/2019. Verbal informed consent was obtained from each of the participants after explaining the purpose of the study and addressing any questions. Permission to conduct the study was obtained from all sub-cities and district level health offices.

Izinto zokwakha

N/A

Emisha

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

1. Mobile Health (mHealth) Applications: Develop mobile applications that provide pregnant women with access to important health information, such as prenatal care guidelines, nutrition advice, and reminders for medical appointments. These apps can also include features for tracking maternal health indicators and connecting women with healthcare providers.

2. Telemedicine Services: Implement telemedicine services that allow pregnant women to consult with healthcare professionals remotely. This can be especially beneficial for women in rural or underserved areas who may have limited access to healthcare facilities.

3. Community Health Workers: Train and deploy community health workers who can provide education and support to pregnant women in their communities. These workers can conduct home visits, offer guidance on prenatal care and nutrition, and refer women to appropriate healthcare services.

4. Maternal Health Vouchers: Introduce voucher programs that provide pregnant women with financial assistance to access essential maternal health services, such as antenatal care, delivery, and postnatal care. These vouchers can be distributed to women in need and redeemed at participating healthcare facilities.

5. Maternal Health Clinics: Establish dedicated maternal health clinics that offer comprehensive services for pregnant women, including prenatal care, childbirth support, and postnatal care. These clinics can be equipped with specialized staff and resources to ensure high-quality care for expectant mothers.

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 to expand service coverage, implementing public-private financing mechanisms, and promoting innovative solutions through joint initiatives.

It’s important to note that the specific context and needs of the community should be considered when implementing these innovations. Additionally, ongoing monitoring and evaluation should be conducted to assess their effectiveness and make necessary adjustments.

AI Innovations Description

Based on the description provided, the study “The social stratification of availability, affordability, and consumption of food in families with preschoolers in Addis Ababa; the eat Addis study in Ethiopia” focuses on understanding the quality of diet among families in Addis Ababa and how social stratification and perceptions of availability and affordability affect healthy food consumption. The study collected data from 5467 households through face-to-face interviews with mothers/caretakers and analyzed the data using mixed effect logistic regression models.

The study found that all family food groups, except fish, were perceived to be available by more than 90% of the participants. The food groups cereals/nuts/seeds, other vegetables, and legumes were considered highly affordable (80%) and were the most consumed (>75%). However, households with the least educated mothers and those in the lowest wealth quintile had the lowest perception of affordability and also consumption. On the other hand, households with higher perceived affordability, the highest wealth quintile, and mothers with better education had higher consumption of foods rich in micronutrients and animal sources.

The study also highlighted that households in Addis Ababa generally had a monotonous diet, despite the high perceived availability of different food groups within the food environment. There was a considerable difference in the consumption of nutrient-rich foods across social strata, indicating the need for city food policies to account for social differences in order to improve the nutritional status of the community.

Based on these findings, a recommendation to develop an innovation to improve access to maternal health could be to implement targeted interventions that address the social stratification and perceptions of availability and affordability of healthy food. This could include initiatives such as:

1. Education and awareness programs: Implement programs that focus on educating mothers/caretakers about the importance of a diverse and nutrient-rich diet during pregnancy and lactation. These programs can also provide information on affordable and accessible sources of healthy food.

2. Subsidies and incentives: Introduce subsidies or incentives to make healthy food more affordable for households in the lowest wealth quintile. This could involve collaborations with local farmers and markets to provide discounted prices for nutritious food items.

3. Community gardens and urban agriculture: Promote community gardens and urban agriculture initiatives to increase the availability of fresh and affordable fruits, vegetables, and other nutrient-rich foods within the city. This can also help address the loss of agricultural land and green spaces in Addis Ababa.

4. Collaboration with local businesses: Partner with local businesses, such as supermarkets and food vendors, to ensure the availability of a wide range of healthy food options at affordable prices. This could involve negotiating discounts or special offers for nutritious food items.

5. Policy changes: Advocate for policy changes that prioritize the nutritional needs of pregnant women and lactating mothers. This could include measures such as mandatory labeling of nutritional information on food products, restrictions on the marketing of unhealthy food to pregnant women, and the inclusion of nutrition education in school curricula.

By implementing these recommendations, it is possible to improve access to maternal health by addressing the social stratification and perceptions of availability and affordability of healthy food in Addis Ababa.

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 comprehensive education programs to raise awareness about the importance of maternal health and the available services. This can include community workshops, health campaigns, and targeted messaging through various media channels.

2. Strengthen healthcare infrastructure: Invest in improving healthcare facilities, especially in areas with limited access to maternal health services. This can involve building or renovating clinics, equipping them with necessary medical supplies and equipment, and ensuring the availability of skilled healthcare professionals.

3. Enhance transportation services: Develop and improve transportation systems to ensure that pregnant women can easily access healthcare facilities. This can include providing affordable or free transportation options, such as ambulances or community transport services, and improving road infrastructure in remote areas.

4. Expand telemedicine services: Utilize technology to provide remote access to maternal health services. This can involve implementing telemedicine programs that allow pregnant women to consult with healthcare professionals through video calls or phone consultations, reducing the need for physical travel.

5. Strengthen community-based care: Establish and support community-based programs that provide maternal health services closer to where women live. This can include training and empowering local healthcare workers, such as midwives or community health workers, to provide basic prenatal care and education.

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 that measure access to maternal health, such as the number of pregnant women receiving prenatal care, the distance to the nearest healthcare facility, or the percentage of women receiving skilled birth attendance.

2. Collect baseline data: Gather data on the current status of these indicators in the target population. This can be done through surveys, interviews, or existing data sources.

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

4. Input recommendation scenarios: Input different scenarios into the simulation model to assess their potential impact. For example, simulate the effect of increasing awareness and education by varying the coverage and intensity of education programs.

5. Analyze results: Analyze the simulation results to determine the potential impact of each recommendation scenario on the chosen indicators. This can involve comparing the baseline data with the simulated outcomes and identifying trends or patterns.

6. Refine and optimize recommendations: Based on the simulation results, refine and optimize the recommendations to maximize their impact on improving access to maternal health. This can involve adjusting the intensity, coverage, or implementation strategies of each recommendation.

7. Implement and monitor: Implement the refined recommendations and closely monitor the progress and outcomes. Continuously collect data to assess the actual impact of the implemented interventions and make necessary adjustments as needed.

By following this methodology, policymakers and stakeholders can make informed decisions on which recommendations to prioritize and how to allocate resources effectively to improve access to maternal health.

Umbhali

Dima Health

Statistics:

Citations: 4

Identifiers:

DOI: 10.3390/nu12103168

Research Areas:

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

Study Countries:

Ethiopia

Study Design:

Cross Sectional Study, Grounded Theory

Study Approach:

Quantitative

Participants Gender:

Female

Yabelana ngalokhu: