Nutrition education, farm production diversity, and commercialization on household and individual dietary diversity in Zimbabwe

Food and Nutrition Research, Volume 62, Year 2018

Interpretation

Background: Nutrition education is crucial for improved nutrition outcomes. However, there are no studies to the best of our knowledge that have jointly analysed the roles of nutrition education, farm production diversity and commercialization on household, women and child dietary diversity. Objective: This article jointly analyses the role of nutrition education, farm production diversity and commercialization on household, women and children dietary diversity in Zimbabwe. In addition, we analyze separately the roles of crop and livestock diversity and individual agricultural practices on dietary diversity. Design: Data were collected from 2,815 households randomly selected in eight districts. Negative binomial regression was used for model estimations. Results: Nutrition education increased household, women, and child dietary diversity by 3, 9 and 24%, respectively. Farm production diversity had a strong and positive association with household and women dietary diversity. Crop diversification led to a 4 and 5% increase in household and women dietary diversity, respectively. Furthermore, livestock diversification and market participation were positively associated with household, women, and children dietary diversity. The cultivation of pulses and fruits increased household, women, and children dietary diversity. Vegetable production and goat rearing increased household and women dietary diversity. Conclusion: Nutrition education and improving access to markets are promising strategies to improve dietary diversity at both household and individual level. Results demonstrate the value of promoting nutrition education; farm production diversity; small livestock; pulses, vegetables and fruits; crop-livestock integration; and market access for improved nutrition. The data used in this article were drawn from Crop and Livestock Production Survey conducted by Food and Agriculture Organization in 2016 as part of the annual assessment of the Livelihoods and Food Security Programme (LFSP). The programme is working to improve food security and nutrition of smallholder farmers and rural communities in eight districts of Zimbabwe (3). A total of 2,815 rural households were surveyed across eight districts (Table 1). In each district, 10 wards were purposively selected to include diversity of agricultural value chains, areas with biofortified crop production, and community-based micro-finance groups. Systematic random sampling was used to select households in each ward. About 36 households were selected per ward using beneficiary lists where the sampling interval was calculated by dividing the total number of beneficiaries by 36. The enumerators visited individual households selected through this process with an allowance of not more than two house recalls after which a replacement household was found. If someone was not present at the time of the visit, the next household on the same list was chosen and not the next-door neighbor. The survey collected information on household characteristics, agricultural practices, household nutrition, maternal and child nutrition, and food security. The total number of women and children (6–23 months of age) in the 2,815 households is 2,285 and 506, respectively. Sample A modified Household Dietary Diversity Score (HDDS) (22) was calculated for each household using recall data on consumption of foods over the previous 24 h. In general, shorter recall period improves the accuracy of estimates compared with longer recall periods of 7 days (23). The food items were categorized into 12 different food groups with each food group counting toward the household score if a food item from the group was consumed by anyone in the household in the previous 24 h. The modified HDDS, then, is a count variable from 0 to 12. The food groups used to calculate the modified HDDS included cereals, roots and tubers, vegetables, fruits, meat, eggs, fish and seafood, pulses and nuts, milk and milk products, oils and fats, sugar, and condiments. Women dietary diversity score (WDDS) is measured using the individual dietary diversity score (22) of women aged 15–49 years. We compute individual dietary diversity scores using 24-h dietary recall data of women’s own consumption from 11 food groups, namely, starchy staples; pulses; dark green leafy vegetables; vitamin A-rich fruits and vegetables; roots and tubers; other fruits and vegetables; milk and milk products; egg; fish; meat; and sugar and condiments (11, 22). The child dietary diversity scores (CDDS) were used to determine the quality of the individual child’s diet (14, 24). Dietary diversity of infants aged 6–23 months is measured by the number of food groups consumed in the last 24 h out of 16 food groups, namely, cereal-based foods; tubers; orange vegetables; green vegetables; orange fruits; other vegetables and fruits; juice; organ meat; meat; eggs; fish; pulses and nuts; dairy; oils; sugar; and liquids (14). Households’ nutrition education is captured in the data through two questions about whether household received information on nutrition and child feeding and care. These were captured as dummy variables. Recognizing the multidimensional determinants of malnutrition in society, the LFSP project uses pluralistic extension approaches for wider dissemination of nutrition education. Various nutrition messages, for example, healthy eating, four-star diets, dietary diversification, and importance of biofortified crops are disseminated to farmers through various training platforms such as community health clubs, information and communication technology platforms (podcasts, videos, WhatsApp), and field days. These messages are disseminated by public and private extension officers, health officers, project nutritionists, trained community-based volunteers, and lead farmers (25, 26). The number of crop and livestock species produced on a farm was used as the measure of farm production diversity (8, 18, 21). This is a simple, unweighted count measure. Second, we split and used the simple, unweighted count of only crop species produced on a farm (crop diversity) and livestock species (livestock diversity) separately. For robustness checks, we reran the model for crop and livestock diversity with a stepwise exclusion of relevant control variables in the model specifications to examine whether this influences the results significantly (27). There are various definitions of commercialization (13). For the purposes of this article, we limit our definition of commercialization to two definitions: (a) household’s market participation measured by the incidence of household selling crop and or livestock to the market and (b) the intensity of market participation measured by the share of crop output that the household sells to the market (13). The limitation of the first definition is its inability to measure the intensity of market participation.

AI Digest

Study Justification:

– Nutrition education is crucial for improved nutrition outcomes.
– There is a lack of studies analyzing the roles of nutrition education, farm production diversity, and commercialization on household and individual dietary diversity in Zimbabwe.

Highlights:

– Nutrition education increased household, women, and child dietary diversity by 3%, 9%, and 24% respectively.
– Farm production diversity had a strong and positive association with household and women dietary diversity.
– Crop diversification led to a 4% increase in household dietary diversity and a 5% increase in women dietary diversity.
– Livestock diversification and market participation were positively associated with household, women, and children dietary diversity.
– The cultivation of pulses and fruits, vegetable production, and goat rearing increased dietary diversity.
– Nutrition education and improving access to markets are promising strategies to improve dietary diversity at both household and individual levels.

Recommendations:

– Promote nutrition education.
– Encourage farm production diversity.
– Support small livestock rearing.
– Promote the cultivation of pulses, vegetables, and fruits.
– Encourage crop-livestock integration.
– Improve market access for farmers.

Key Role Players:

– Public and private extension officers.
– Health officers.
– Project nutritionists.
– Trained community-based volunteers.
– Lead farmers.

Cost Items for Planning Recommendations:

– Training platforms for nutrition education dissemination (e.g., community health clubs, information and communication technology platforms).
– Resources for promoting farm production diversity (e.g., seeds, tools).
– Support for small livestock rearing (e.g., training, veterinary services).
– Resources for promoting the cultivation of pulses, vegetables, and fruits (e.g., seeds, irrigation systems).
– Infrastructure for crop-livestock integration (e.g., fencing, housing).
– Investments in market infrastructure and logistics to improve market access for farmers.

Strength of Evidence

N/A

Abstract

The data used in this article were drawn from Crop and Livestock Production Survey conducted by Food and Agriculture Organization in 2016 as part of the annual assessment of the Livelihoods and Food Security Programme (LFSP). The programme is working to improve food security and nutrition of smallholder farmers and rural communities in eight districts of Zimbabwe (3). A total of 2,815 rural households were surveyed across eight districts (Table 1). In each district, 10 wards were purposively selected to include diversity of agricultural value chains, areas with biofortified crop production, and community-based micro-finance groups. Systematic random sampling was used to select households in each ward. About 36 households were selected per ward using beneficiary lists where the sampling interval was calculated by dividing the total number of beneficiaries by 36. The enumerators visited individual households selected through this process with an allowance of not more than two house recalls after which a replacement household was found. If someone was not present at the time of the visit, the next household on the same list was chosen and not the next-door neighbor. The survey collected information on household characteristics, agricultural practices, household nutrition, maternal and child nutrition, and food security. The total number of women and children (6–23 months of age) in the 2,815 households is 2,285 and 506, respectively. Sample A modified Household Dietary Diversity Score (HDDS) (22) was calculated for each household using recall data on consumption of foods over the previous 24 h. In general, shorter recall period improves the accuracy of estimates compared with longer recall periods of 7 days (23). The food items were categorized into 12 different food groups with each food group counting toward the household score if a food item from the group was consumed by anyone in the household in the previous 24 h. The modified HDDS, then, is a count variable from 0 to 12. The food groups used to calculate the modified HDDS included cereals, roots and tubers, vegetables, fruits, meat, eggs, fish and seafood, pulses and nuts, milk and milk products, oils and fats, sugar, and condiments. Women dietary diversity score (WDDS) is measured using the individual dietary diversity score (22) of women aged 15–49 years. We compute individual dietary diversity scores using 24-h dietary recall data of women’s own consumption from 11 food groups, namely, starchy staples; pulses; dark green leafy vegetables; vitamin A-rich fruits and vegetables; roots and tubers; other fruits and vegetables; milk and milk products; egg; fish; meat; and sugar and condiments (11, 22). The child dietary diversity scores (CDDS) were used to determine the quality of the individual child’s diet (14, 24). Dietary diversity of infants aged 6–23 months is measured by the number of food groups consumed in the last 24 h out of 16 food groups, namely, cereal-based foods; tubers; orange vegetables; green vegetables; orange fruits; other vegetables and fruits; juice; organ meat; meat; eggs; fish; pulses and nuts; dairy; oils; sugar; and liquids (14). Households’ nutrition education is captured in the data through two questions about whether household received information on nutrition and child feeding and care. These were captured as dummy variables. Recognizing the multidimensional determinants of malnutrition in society, the LFSP project uses pluralistic extension approaches for wider dissemination of nutrition education. Various nutrition messages, for example, healthy eating, four-star diets, dietary diversification, and importance of biofortified crops are disseminated to farmers through various training platforms such as community health clubs, information and communication technology platforms (podcasts, videos, WhatsApp), and field days. These messages are disseminated by public and private extension officers, health officers, project nutritionists, trained community-based volunteers, and lead farmers (25, 26). The number of crop and livestock species produced on a farm was used as the measure of farm production diversity (8, 18, 21). This is a simple, unweighted count measure. Second, we split and used the simple, unweighted count of only crop species produced on a farm (crop diversity) and livestock species (livestock diversity) separately. For robustness checks, we reran the model for crop and livestock diversity with a stepwise exclusion of relevant control variables in the model specifications to examine whether this influences the results significantly (27). There are various definitions of commercialization (13). For the purposes of this article, we limit our definition of commercialization to two definitions: (a) household’s market participation measured by the incidence of household selling crop and or livestock to the market and (b) the intensity of market participation measured by the share of crop output that the household sells to the market (13). The limitation of the first definition is its inability to measure the intensity of market participation.

Materials

N/A

Innovations

The study recommends implementing nutrition education programs and improving access to markets to improve access to maternal health. The study found that nutrition education increased household, women, and child dietary diversity by 3%, 9%, and 24% respectively. Farm production diversity, including crop and livestock diversity, was also positively associated with dietary diversity. Livestock diversification and market participation were found to be positively associated with household, women, and children dietary diversity. The cultivation of pulses, fruits, and vegetables, as well as goat rearing, were also found to increase dietary diversity.

To implement this recommendation, it is suggested to promote nutrition education programs that focus on healthy eating, dietary diversification, and the importance of biofortified crops. These programs can be disseminated through various training platforms such as community health clubs, information and communication technology platforms (podcasts, videos, WhatsApp), and field days. Public and private extension officers, health officers, project nutritionists, trained community-based volunteers, and lead farmers can be involved in delivering these messages.

In addition, efforts should be made to improve access to markets for smallholder farmers. This can be done by supporting market participation, such as facilitating the selling of crops and livestock to the market. The intensity of market participation can also be measured by the share of crop output that households sell to the market. Improving market access can help farmers generate income and increase their ability to access diverse and nutritious foods.

Overall, implementing nutrition education programs and improving access to markets can contribute to improved dietary diversity at both the household and individual level, thereby improving maternal health outcomes.

AI Innovations Description

The recommendation from the study to improve access to maternal health is to implement nutrition education programs and improve access to markets. The study found that nutrition education increased household, women, and child dietary diversity by 3%, 9%, and 24% respectively. Farm production diversity, including crop and livestock diversity, was also positively associated with dietary diversity. Livestock diversification and market participation were found to be positively associated with household, women, and children dietary diversity. The cultivation of pulses, fruits, and vegetables, as well as goat rearing, were also found to increase dietary diversity.

To implement this recommendation, it is suggested to promote nutrition education programs that focus on healthy eating, dietary diversification, and the importance of biofortified crops. These programs can be disseminated through various training platforms such as community health clubs, information and communication technology platforms (podcasts, videos, WhatsApp), and field days. Public and private extension officers, health officers, project nutritionists, trained community-based volunteers, and lead farmers can be involved in delivering these messages.

In addition, efforts should be made to improve access to markets for smallholder farmers. This can be done by supporting market participation, such as facilitating the selling of crops and livestock to the market. The intensity of market participation can also be measured by the share of crop output that households sell to the market. Improving market access can help farmers generate income and increase their ability to access diverse and nutritious foods.

Overall, implementing nutrition education programs and improving access to markets can contribute to improved dietary diversity at both the household and individual level, thereby improving maternal health outcomes.

AI Innovations Methodology

The methodology used in this study involved collecting data from 2,815 households in eight districts of Zimbabwe. The data was collected through a Crop and Livestock Production Survey conducted by the Food and Agriculture Organization as part of the Livelihoods and Food Security Programme. The households were selected using systematic random sampling, with 36 households selected per ward.

The survey collected information on household characteristics, agricultural practices, household nutrition, maternal and child nutrition, and food security. To measure dietary diversity, a modified Household Dietary Diversity Score (HDDS) was calculated for each household based on recall data on consumption of foods over the previous 24 hours. The food items were categorized into 12 different food groups, and the modified HDDS is a count variable from 0 to 12.

The study also measured women dietary diversity using the individual dietary diversity score of women aged 15-49 years. This score was calculated based on 24-hour dietary recall data from 11 food groups. Child dietary diversity scores were used to determine the quality of the individual child’s diet, with scores calculated based on the number of food groups consumed in the last 24 hours out of 16 food groups.

The study analyzed the role of nutrition education, farm production diversity, and commercialization on household, women, and children dietary diversity. Negative binomial regression was used for model estimations. The results showed that nutrition education increased household, women, and child dietary diversity by 3%, 9%, and 24% respectively. Farm production diversity, including crop and livestock diversity, was positively associated with dietary diversity. Livestock diversification and market participation were also positively associated with dietary diversity.

To simulate the impact of these recommendations on improving access to maternal health, a similar methodology could be used. Data could be collected from households in the target population, using a similar sampling method. Information on household characteristics, agricultural practices, nutrition, and food security could be collected. Dietary diversity scores could be calculated using recall data on food consumption.

The impact of nutrition education programs and improved access to markets could be assessed by comparing the dietary diversity scores of households before and after the implementation of these interventions. Statistical analysis, such as regression models, could be used to determine the association between nutrition education, farm production diversity, commercialization, and dietary diversity.

The findings from this simulation could provide insights into the potential impact of these interventions on improving access to maternal health. It could help policymakers and stakeholders make informed decisions about implementing nutrition education programs and improving access to markets to promote better maternal health outcomes.

Author

Dima Health

Statistics:

Citations: 30

Identifiers:

DOI: 10.29219/fnr.v62.1276

ISSN: 16546628

Research Areas:

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

Study Countries:

Zimbabwe

Study Design:

Cohort Study, Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Female