Background: Plant-based diets are not inherently healthy. Similar to omnivorous diets, they may contain excessive amounts of sugar, sodium, and saturated fats, or lack diversity. Moreover, vegans might be at risk of inadequate intake of certain vitamins and minerals commonly found in foods that they avoid. We developed the VEGANScreener, a tool designed to assess the diet quality of vegans in Europe. Methods: Our approach combined best practices in developing diet quality metrics with scale development approaches and involved the following: (a) narrative literature synthesis, (b) evidence evaluation by an international panel of experts, and (c) translation of evidence into a diet screener. We employed a modified Delphi technique to gather opinions from an international expert panel. Results: Twenty-five experts in the fields of nutrition, epidemiology, preventive medicine, and diet assessment participated in the first round, and nineteen participated in the subsequent round. Initially, these experts provided feedback on a pool of 38 proposed items from the literature review. Consequently, 35 revised items, with 17 having multiple versions, were suggested for further consideration. In the second round, 29 items were retained, and any residual issues were addressed in the final consensus meeting. The ultimate screener draft encompassed 29 questions, with 17 focusing on foods and nutrients to promote, and 12 addressing foods and nutrients to limit. The screener contained 24 food-based and 5 nutrient-based questions. Conclusions: We elucidated the development process of the VEGANScreener, a novel diet quality screener for vegans. Future endeavors involve contrasting the VEGANScreener against benchmark diet assessment methodologies and nutritional biomarkers and testing its acceptance. Once validated, this instrument holds potential for deployment as a self-assessment application for vegans and as a preliminary dietary screening and counseling tool in healthcare settings.

Background and Objectives: Gestational diabetes mellitus (GDM) is one of the most common medical conditions in pregnancy, with adverse effects on maternal and neonatal outcomes. Evidence suggests a beneficial effect of plant-based dietary patterns, rich in foods derived from plant sources and low in animal foods, on type 2 diabetes; however, their effects on GDM remain unclear. We aimed to investigate the association between pre-pregnancy provegetarian food patterns and the incidence of GDM in a Spanish cohort. Materials and Methods: This subsample of the Seguimiento Universidad de Navarra (SUN) cohort analyzed 3589 Spanish university graduate pregnant women with a mean (standard deviation) age of 28 (±4.3) who were initially free of pre-existing diabetes at baseline. Dietary food consumption was evaluated through a validated, 136-item semi-quantitative food frequency questionnaire. The pre-pregnancy provegetarian food pattern was obtained by assigning positive scores to plant-based food groups and reverse scores to animal food groups. Energy-adjusted quintiles were applied to allocate points to construct the provegetarian food pattern, ranging from 12 to 60 points. Logistic regression models were performed to estimate the odds ratios (OR) of GDM across quintiles of a pre-pregnancy provegetarian food pattern, using the lowest quintile as the reference category. Results: We identified 178 incidence cases of GDM. Women in the highest quintile (Q5) of provegetarian food pattern before pregnancy exhibited a 42% relative reduction in the odds of GDM [adjusted OR (95% CI) Q5 vs. Q1: 0.58 (0.35, 0.97); p-trend = 0.109]. Higher consumption of meat and dairy before pregnancy was associated with a significantly increased risk of GDM [adjusted OR (95% CI) Q5 vs. Q1: 1.94 (1.19, 3.16); p-trend = 0.005] and [adjusted OR (95% CI) Q5 vs. Q1: 1.77 (1.07, 2.94); p-trend = 0.082], respectively. Conclusions: Higher pre-pregnancy consumption of a provegetarian food pattern was associated with a lower risk of developing GDM in Spanish women. Further studies are needed to confirm these findings.

Background and Objectives: A provegetarian (PVG) food pattern, also known as a plant-based food pattern, which prioritizes the consumption of plant-based foods without completely excluding animal-based foods has been associated with health benefits. However, not all plant-based foods are healthy. We prospectively evaluated the association between different PVG food patterns and the risk of total mortality in the “Seguimiento Universidad de Navarra” (SUN) cohort. Methods: The SUN Project is a Mediterranean cohort study involving Spanish university graduates. A validated 136-item semi-quantitative food frequency questionnaire was used. A PVG food pattern, as previously proposed, was calculated assigning positive scores to plant-based foods and inverse scores to animal-based foods. Participants were categorized into quintiles based on their adherence to this pattern. Additionally, healthy and unhealthy PVG food patterns were derived. Results: Data from 17,989 participants with a mean baseline age (standard deviation) 38 (±12) years were analyzed. Over a mean follow-up period of 12 years, 460 deaths (2.6%) were recorded. Participants with higher adherence to the PVG food pattern (Q5) exhibited a 32% lower risk of total mortality [hazard ratio (HR): 0.68 (95% CI: (0.50–0.93); p for trend = 0.020] as compared to those with lower adherence (Q1), after adjusting for multiple confounders. This inverse association persisted for the healthy PVG food pattern [HR: 0.65 (95% CI: 0.47–0.90); p for trend = 0.016]. In contrast, the unhealthy PVG food pattern did not show any significant association with mortality [HR: 1.31 (95% CI: 0.94–1.83)]. Conclusions: Higher adherence to a PVG food pattern, which emphasizes the consumption of plant-based foods, reduces the risk of total mortality in the SUN cohort.

Background and Objectives: The role of diet in the risk and clinical course of immune-mediated inflammatory diseases (IMIDs) is an area of ongoing research, in which prospective evidence regarding the degree of food processing is limited. We prospectively assess the association between ultra-processed food (UPF) and minimally or unprocessed food (MUPF) consumption and incident psoriasis, rheumatoid arthritis and vitiligo, as well as a composite exploratory IMID outcome, in a Spanish cohort. Methods: We followed 15,874 IMID-free participants from the SUN Project (median follow-up: 15.1 years). Baseline diet was assessed via a validated FFQ and categorized by NOVA classification. Multivariable Cox models estimated hazard ratios (HRs) and 95% confidence intervals (CIs) across consumption tertiles (% g/day). Results: During follow-up, 298 self-reported diagnosed incident IMID cases occurred (1.31/1000 person-years, mostly psoriasis and rheumatoid arthritis). After adjusting for sociodemographic, lifestyle, and clinical factors, the highest UPF consumption was associated with an increased risk of self-reported diagnosed psoriasis (T3 vs. T1: HR = 1.63, 95% CI: 1.08–2.45) and rheumatoid arthritis (T3 vs. T1: HR = 1.97, 95% CI: 1.19–3.26; p-trend = 0.006), whereas no significant association was observed for vitiligo. Similar trends were observed for the exploratory composite IMID endpoint (T3 vs. T1: HR = 1.80, 95% CI: 1.31–2.45). Conversely, higher MUPF intake was associated with a lower risk of self-reported diagnosed psoriasis (T3 vs. T1: HR = 0.60, 95% CI: 0.40–0.92; p-trend = 0.014) and exploratory composite IMID endpoints (T3 vs. T1: HR = 0.64, 95% CI: 0.47–0.87; p-trend = 0.003). Conclusions: Higher UPF consumption is associated with an increased risk of self-reported diagnosed psoriasis and rheumatoid arthritis, whereas MUPF intake appears to be inversely associated with self-reported diagnosed psoriasis risk. These findings contribute to the ongoing evidence regarding the degree of food processing as a potential factor in the epidemiological profile of specific autoimmune conditions. However, given the observational design of the study, these findings reflect longitudinal associations and do not imply causation.

Background and Objectives: Consumption of plant-based diets, including vegan diets, requires attention towards diet quality and the early detection and prevention of nutritional deficiencies. The VEGANScreener project aims to develop and validate a standardized brief web- and app-based screening tool to assess and monitor diet quality among vegans in Europe. To this end, a clinical study will be performed to evaluate the VEGANScreener against a reference diet assessment method and nutritional biomarkers. Materials and Methods: An observational cross-sectional study will comprise six hundred participants across four European sites (Germany, Spain, Belgium, Czech Republic): 400 self-reported vegans (≥2 years on vegan diet) and 200 self-reported omnivore controls; without diseases affecting the metabolism and intestinal integrity; aged 18 to 65 years (1:1 ratio 18–35 and 36–65); males and females (1:1 ratio). Subjects will be enrolled after an online eligibility check. Informed consent will be obtained, and the subjects enrolled will be given a unique ID (pseudonymized). The initial clinical visit consists of structured medical history-taking, blood pressure, heart rate and anthropometric measurements, blood, spot urine and saliva sampling, distributing the VEGANScreener access, diet record instructions, and general survey access. A follow-up collection visit will be scheduled 14–21 days apart: 24 h urine and 4-day diet records will be collected, and subjects’ participation will be terminated. VEGANScreener will be administered twice to limit the within- person errors. Results: Field work is ongoing, and we expect to have results by the time of the conference. Discussion: The VEGANScreener tool will be validated for the target population. The primary objective is to assess the construct validity and criterion validity of the VEGANScreener through associations of the score with nutrient intakes from a 4-day diet record and associations with biomarkers of dietary intake. Standard statistical models will be implemented for cross-sectional comparisons of geographical groups. Secondary outcomes will include analyses of dietary data and metabolomics. Vegan subgroups will be identified with dimensionality reduction methods and univariable statistical tests. Major nutrient sources and variations across groups will be assessed. Exploratory metabolomic analysis (blood, urine, saliva) to identify novel concentration biomarkers of dietary intake and nutritional adequacy will be performed using multivariable analysis.