Food-based dietary guidelines promote consumption of a variety of nutritious foods for optimal health and prevention of chronic disease. However, adherence to these guidelines is challenging because of high food costs. The present study aimed to determine the nutrient density of foods relative to cost in South Africa, with the aim to identify foods within food groups with the best nutritional value per cost. A checklist of 116 food items was developed to record the type, unit, brand and cost of foods. Food prices were obtained from the websites of three national supermarkets and the average cost per 100 g edible portion was used to calculate cost per 100 kcal (418 kJ) for each food item. Nutrient content of the food items was obtained from the South African Food Composition Tables. Nutrient density was calculated using the Nutrient Rich Food (NRF9.3) Index. Nutrient density relative to cost was calculated as NRF9.3/price per 100 kcal. Vegetables and fruits had the highest NRF9.3 score and cost per 100 kcal. Overall, pulses had the highest nutritional value per cost. Fortified maizemeal porridge and bread had the best nutritional value per cost within the starchy food group. Foods with the least nutritional value per cost were fats, oils, foods high in fat and sugar, and foods and drinks high in sugar. Analysis of nutrient density and cost of foods can be used to develop tools to guide low-income consumers to make healthier food choices by identifying foods with the best nutritional value per cost.

Higher consumption of ‘ultra-processed’ (UP) foods has been linked to adverse health outcomes. The present paper aims to characterise percentage energy from UP foods by participant socio-economic status (SES), diet quality, self-reported food expenditure and energy-adjusted diet cost. Participants in the population-based Seattle Obesity Study III (n 755) conducted in WA in 2016–2017 completed socio-demographic and food expenditure surveys and the FFQ. Education and residential property values were measures of SES. Retail prices of FFQ component foods (n 378) were used to estimate individual-level diet cost. Healthy Eating Index (HEI-2015) and Nutrient Rich Food Index 9.3 (NRF9.3) were measures of diet quality. UP foods were identified following NOVA classification. Multivariable linear regressions were used to test associations between UP foods energy, socio-demographics, two estimates of food spending and diet quality measures. Higher percentage energy from UP foods was associated with higher energy density, lower HEI-2015 and NRF9.3 scores. The bottom decile of diet cost ($216·4/month) was associated with 67·5 % energy from UP foods; the top decile ($369·9/month) was associated with only 48·7 % energy from UP foods. Percentage energy from UP foods was inversely linked to lower food expenditures and diet cost. In multivariate analysis, percentage energy from UP foods was predicted by lower food expenditures, diet cost and education, adjusting for covariates. Percentage energy from UP foods was linked to lower food spending and lower SES. Efforts to reduce UP foods consumption, an increasingly common policy measure, need to take affordability, food expenditures and diet costs into account.