Development of a diet quality score and adherence to the Swiss dietary recommendations for vegans.

BACKGROUND: Vegan diets have recently gained popularity in Switzerland as well as globally. The aim of the present study was to develop a diet quality score for vegans (DQS-V) based on the Swiss dietary recommendations for vegans. METHODS: The dataset included 52 healthy vegan adults. Dietary intake data were assessed by three-day weighed food records. Body weight and height were measured, and a venous blood sample for the analysis of vitamin and mineral status was collected. Spearman rank correlation coefficients were used due to not-normally distributed data. Dietary patterns were identified using principal component analysis (PCA). RESULTS: The DQS-V score (mean ± SD) was 48.9 ± 14.7. Most vegans adhered to the recommended portions of vegetables, vitamin C-rich vegetables, fruits, omega-3-rich nuts, fats and oils, and iodized salt. However, the intake of green leafy vegetables, vitamin C-rich fruits, wholegrains, legumes, nuts and seeds, selenium-rich nuts, zero caloric liquid, and calcium-fortified foods was suboptimal. The sample overconsumed sweet-, salty-, fried foods, and alcohol. The DQS-V had a significantly positive correlation with intakes of fibre, polyunsaturated fatty acids, potassium, zinc, and phosphorus intakes (p's < 0.05) but was negatively correlated with vitamin B12 and niacin intakes (p's < 0.05). Two dietary patterns were derived from PCA: 1) refined grains and sweets and 2) wholegrains and nuts. The correlation between the DQS-V and the first dietary pattern was negative (- 0.41, p = 0.004) and positive for the second dietary pattern (0.37, p = 0.01). The refined grains and sweets dietary pattern was inversely correlated with beta-carotene status (- 0.41, p = 0.004) and vitamin C status (r = - 0.51, p = 0.0002). CONCLUSION: The newly developed DQS-V provides a single score for estimating diet quality among vegan adults. Further validation studies examining the DQS-V in relation to an independent dietary assessment method and to biomarkers of nutritional intake and status are still needed before the general application of the DQS-V.

The Nutritional Content of Meal Images in Free-Living Conditions-Automatic Assessment with goFOODTM.

A healthy diet can help to prevent or manage many important conditions and diseases, particularly obesity, malnutrition, and diabetes. Recent advancements in artificial intelligence and smartphone technologies have enabled applications to conduct automatic nutritional assessment from meal images, providing a convenient, efficient, and accurate method for continuous diet evaluation. We now extend the goFOODTM automatic system to perform food segmentation, recognition, volume, as well as calorie and macro-nutrient estimation from single images that are captured by a smartphone. In order to assess our system's performance, we conducted a feasibility study with 50 participants from Switzerland. We recorded their meals for one day and then dietitians carried out a 24 h recall. We retrospectively analysed the collected images to assess the nutritional content of the meals. By comparing our results with the dietitians' estimations, we demonstrated that the newly introduced system has comparable energy and macronutrient estimation performance with the previous method; however, it only requires a single image instead of two. The system can be applied in a real-life scenarios, and it can be easily used to assess dietary intake. This system could help individuals gain a better understanding of their dietary consumption. Additionally, it could serve as a valuable resource for dietitians, and could contribute to nutritional research.

Protein Quality Changes of Vegan Day Menus with Different Plant Protein Source Compositions.

To underline the importance of protein quality in plant-based diets, we estimated the protein quality of different exclusively plant-protein-based day menus that are based on the "planetary health diet" developed by the EAT-Lancet Commission. PDCAAS and DIAAS were used to estimate the protein quality (PQ) and fulfilling of the amino acid recommendation for adults in vegan daily menus based on the planetary health diet: 2 days with only low-quality (LQ) protein sources and 2 days with low + high-quality (HQ) protein sources. The protein quality of Day 1LQ (DIAAS 76, PDCAAS 88) was increased by the addition of high-quality protein sources (HQPS): Day 1HQ (DIAAS 94, PDCAAS 98). Day 2LQ had a low PQ (DIAAS 71, PDCAAS 74), but when HQPS were used (Day 2HQ), the PQ increased (DIAAS 83, PDCAAS 88). Scenarios (day 1HQ, day 1LQ, and day 2 HQ) were classified as of good PQ. However, day 1LQ had a low protein quality. Consuming HQPS in a vegan diet can help to fulfil the recommendation of essential amino acids. This work served to understand and apply methods to estimate protein quality that can be applied to optimize protein mixtures to fulfil amino acid requirements in the future.