Objective grocery transactions may reflect diet, but it is unclear whether the diet quality of grocery purchases mirrors geographic and racial/ethnic disparities in diet-related diseases. This cross-sectional analysis of 3961 households in the nationally representative Food Acquisition and Purchase Survey evaluated geographic and racial/ethnic disparities in grocery purchase quality. Respondents self-reported demographics and recorded purchases over 7 days; the Healthy Eating Index (HEI) 2015 assessed diet quality. Survey-weighted multivariable-adjusted regression determined whether there were geographic and racial/ethnic differences in HEI-15 scores. Respondents were, on average, 50.6 years, non-Hispanic white (NHW) (70.3%), female (70.2%), and had attended some college (57.8%). HEI-15 scores differed across geographic region (p < 0.05), with the highest scores in the West (57.0 ± 0.8) and lowest scores in the South (53.1 ± 0.8), and there was effect modification by race/ethnicity (p-interaction = 0.02). Regionally, there were diet disparities among NHW and non-Hispanic black (NHB) households; NHWs in the South had HEI-15 scores 3.2 points lower than NHWs in the West (p = 0.003). Southern NHB households had HEI-15 scores 8.1 points lower than Western NHB households (p = 0.013). Racial/ethnic disparities in total HEI-15 by region existed in the Midwest and South, where Hispanic households in the Midwest and South had significantly lower diet quality than NHW households. Heterogeneous disparities in the diet quality of grocery purchases by region and race/ethnicity necessitate tailored approaches to reduce diet-related disease.

Patterns of protein intake are strong characteristics of diets, and protein sources have been linked to the environmental and nutrition/health impacts of diets. However, few studies have worked on protein profiles, and most of them have focused on specific diets like vegetarian or vegan diets. Furthermore, the description of the environmental impact of diets has often been limited to greenhouse gas emissions (GHGe) and land use. This paper analyzes the alignment of environmental pressures and nutritional impacts in a diversity of representative protein profiles of a western population. Using data from a representative survey in France (INCA3, n = 1,125), we identified protein profiles using hierarchical ascendant classification on protein intake (g) from main protein sources (refined grains, whole grains, dairy, eggs, ruminant meat, poultry, pork, processed meat, fish, fruits & vegetables, pulses). We assessed their diet quality using 6 dietary scores, including assessment of long-term risk for health, and associated 14 environmental pressure indicators using the Agribalyse database completed by the SHARP database for GHGe. Five protein profiles were identified according to the high contributions of ruminant meat, pork, poultry, fish, or, conversely, as low contribution from meat. The profile including the lowest protein from meat had the lowest impact on almost all environmental indicators and had the lowest long-term risk. Conversely, the profile with high protein from ruminant-based foods had the highest pressures on most environmental indicators, including GHGe. We found that the protein profile with low contribution from meat has great potential for human health and environment preservation. Shifting a large part of the population toward this profile could be an easy first step toward building a more sustainable diet. Graphical Environmental pressure by profile: All data are in percentage compared to the mean value of the population. GHG is the emission of greenhouse gases measured in kg CO ₂ eq. The ozone depletion is in kg CFC-11eq. The photochemical ozone formation is in kg of Non-Methane Volatile Organic Compounds eq. Particulate matter is in kg of PM _2.5 emitted. The acidification is in mol H ⁺ eq. The terrestrial eutrophication is in mol N eq, the freshwater eutrophication is in kg P eq, and the marine eutrophication is in kg N eq. The freshwater ecotoxicity is based on the USEtox model. Land use is in kg C deficit, water use in m ³ , fossils resource use in MJ, and Metals and minerals use in kg SB eq. Nutritional and health indicators by profile: All data are in percentage of difference to the mean value of the population. The HiDiet was used to assess the diet impact on long-term mortality and morbidity (variation between -1 and 1). The Alternative Healthy Eating Index (AHEI-2010) is a modified Healthy Eating Index, assessing the adherence to Dietary Guidelines for Americans , improving target food choices and macronutrient sources associated with reduced chronic disease risk (maxpoint = 100). The PANDiet evaluates the probability of adequate nutrient intake (maxpoint = 100). The SecDiet evaluates the nutrient risk of overt deficiency (maxpoint = 1). The Literature-Based Adherence Score to the Mediterranean Diet (LAMD) assesses adherence to the Mediterranean diet (maxpoint = 16). sPNNS-GS2 the adherence to the French Food-based Dietary Guidelines (maxpoint = 10.5).

Background: Scientific literature about environmental pressures associated with dietary patterns has been considerably growing over the last decade. However, few studies have analyzed the environmental impacts associated with the consumption of ultra-processed food (UPF) and which steps of the food system that contribute most to environmental pressures. The objective of this study was to investigate, in a representative sample of the adult French population, the environmental pressures of diets according to UPF consumption. Methods: The study was conducted in 2,121 adults of the French nationally representative survey INCA 3. Food intakes were analyzed to define the %UPF (in weight) in the diet according to NOVA classification. Using detailed environmental data of foods of Agribalyse, we could assess the contribution of UPF to 14 indicators of environmental pressure and details those related to the stage of the food consumed: production, processing, storage, packaging, transport and retailing at the food level. The data was described according to quintiles of % of UPF in the diet and analyzed using crude and energy-adjusted models. Results: Compared to low consumers of UPF (Q1, median UPF= 7%), high consumers (Q5, median UPF= 35%) had a higher energy intake (+22%) which came along with different environmental pressures (e.g. +15% greenhouse gas emissions (GHGe), +17% land use, -7% water use and +8% cumulative energy demand). Higher pressures could be ascribed to higher energy. However, the processing and packaging stages were significant contributor to energy demand. In Q5, contributions of the UPF category to total pressure were 35%, 39%, 28% and 42% for GHGe, water use land use, and energy demand, respectively, while ranging from 11 to 15% in Q1. Conclusions: Diets rich in UPF, compared to low, were overall associated with intensification in GHGe, land use, and energy demand and with higher contribution of post-farm stages, in particular processing regarding energy demand. Highlights: Overall, higher UPF consumption was associated with higher environmental impact, in particular GHGE and land use Low UPF consumers had overall higher water footprint (due to their high fruit and vegetable intake) A large part of the higher pressures observed among participants with higher UPF consumption was explained by their higher dietary energy intake since the associations did not remain or were even reversed after energy adjustment Regardless of the % UPF in the diet, GHGe, land use and water use pressures mostly occurred at the stage of agricultural production, in contrast, packaging and processing stages were also important contributors to energy demand Contribution of the UPF category to total impact/pressure varied across indicators, with a high contribution of the UPF category to energy demand, due to the packaging and processing stages, but a low contribution to GHGe and land use, because higher consumers of UPF are lower consumers of animal products