Exploring the association between agricultural production systems and household diets in Viet Nam.

The government of Viet Nam promotes an integrated and diversified production system that focuses on the symbiotic relationship of livestock, aquaculture, and fruits and vegetables (F&V), locally known as Vuon Ao Chuong (VAC). The expectation is that this system can prevent soil degradation, while improving dietary quality and income. This study examines the correlation between VAC production systems and diets using cross-sectional data from the 2016 round of the Viet Nam Household Living Standards Survey (VHLSS). Using ordinary least squares, we model four continuous outcome variables related to quantity consumed of fruits and vegetables, fiber, animal protein, and dietary energy; while using logistical regression, we model three indicator variables related to whether diets are balanced in terms of intake of dietary energy derived from carbohydrates, proteins, and fats. While individual components of VAC, such as aquaculture or F&V production, show a positive correlation with one or more dietary indicators, adoption of the full VAC system is found to be positively correlated only with dietary fiber consumption, making it challenging to establish a causal link between system adoption and improved dietary quality. However, we find that several socioeconomic variables, such as access to markets, household wealth, education of the household members, and household size are positively associated with one or more dietary indicators. Further research is needed to establish strong and causal relationships, or lack thereof, between VAC system and diets by exploiting the panel structure of VHLSS to examine the role of VAC in improving nutritional outcomes in Viet Nam.

Analyzing the Drivers of Household Dietary Diversity: Evidence from Burkina Faso.

BACKGROUND: The diets of millions of poor individuals lack adequate amount of essential nutrients. OBJECTIVE: To examine the determinants of household dietary diversity in Burkina Faso and assess whether the choice of a diversity metric matters. METHODS: Using survey data from 2014, we construct 3 metrics-Household Dietary Diversity Score (HDDS), Berry Index (BI), and Healthy Food Diversity Index (HFDI). Unlike the oft-used HDDS, the BI captures the quantity distribution of food items while the HFDI captures all 3 aspects of a healthy diet-count, quantity distribution, and health value. We fit linear (for BI and HFDI) and Poisson (for HDDS) models controlling for several socioeconomic and climatic covariates. RESULTS: Some parameter estimates are sensitive to the diversity metric with fewer significant covariates observed in the HFDI model. Overall, diets are more diverse for households in urban areas, with female or better educated heads, with higher asset-based wealth and with more diverse on-farm production, while remoteness reduces dietary diversity. Higher precipitation seems to reduce diversity, potentially driven by the spatial heterogeneity in precipitation and on-farm production diversity. CONCLUSIONS: The sensitivity of estimates to the metric used underscores potentially more complex interactions that determine the quantity distribution of food items consumed. Policies that enhance on-farm production diversity, market access, and women's empowerment may help improve dietary diversity and subsequent nutritional benefits. Efforts should be made to compile health value data that are relevant to developing countries facing nutrition transition.