Produce marketers who participate as farmers market vendors or otherwise directly market their goods should understand not only the location-related characteristics that affect consumer selection of local, fresh produce but also the product attributes that consumers prefer to find in local products. Understanding attribute-price relationships will allow marketers to better plan for value-added marketing opportunities. Using a hedonic pricing model, this study analyzed the influence that product attribute levels have on prices for seven types of produce: sweet corn, tomatoes, cantaloupe, cucumbers, green beans, bell peppers, and zucchini. Based on data collected from Missouri farmers markets, multiple attributes affect produce price variation. In the dataset, one of the strongest effects was exerted by sale location. The importance of this finding is that prices can be collected in a single location and extrapolated to other farmers market locations, which implies reduced search and reporting costs in collecting representative farmers market produce prices. Additionally, a higher weight may increase prices for some types of produce but decrease prices of others after a certain point. Farmers market vendors, as well as other direct marketers, can use attribute pricing information to identify the quality attributes that consumers prefer.

Nutrition-related health problems, such as obesity, stunting, anemia, and high blood pressure are common in Armenia. A large portion of the population lives below the national poverty line, and consumes less than the necessary energy intake per day. Linear programming is used in this study of diet optimization to create a healthy diet model for children and adults of different ages at the minimum cost. The model is based on culturally appropriate food products. The study finds that, while average Armenians can afford a healthy diet, their current dietary choices do not meet the requirements of Dietary Reference Intakes (DRIs). Moreover, people earning minimum salary need to spend more than half of their monthly income on food to afford a healthy diet. Based on the study’s findings, several policy recommendations are made.

Lower diet quality is a leading preventable risk factor for obesity and chronic diseases. This study assesses differences in the nutritional quality of at-home food purchases, using the Healthy Eating Index (HEI)-2015 and its components, among households with and without a member reporting type 2 diabetes (T2D), cardiovascular disease (CVD), obesity, and/or smoking. We use the 2015 IRI Consumer Network nationally representative household food purchase scanner data, combined with the IRI MedProfiler and the USDA’s Purchase-to-Plate Crosswalk datasets. For each/multiple condition(s), the difference in mean HEI score adjusted for covariates is tested for equivalence with the respective score against households without any member with the condition(s). The HEI score is higher for households without a member with reported T2D (2.4% higher), CVD (3.2%), obesity (3.3%), none of the three conditions (6.1%, vs. all three conditions), and smoking (10.5%) than for those with a member with the respective condition. Households with a member with T2D score better on the added sugar component than those with no member reporting T2D. We found that the average food purchase quality is lower than the recommended levels, especially for households with at least one member reporting a chronic condition(s).