Less Animal-Based Food, Better Weight Status: Associations of the Restriction of Animal-Based Product Intake with Body-Mass-Index, Depressive Symptoms and Personality in the General Population

Development and Implementation of a 3-Week Whole-Food Plant-Based Vegan Diet Intervention for College Students

OBJECTIVE

To describe the research methods used for the Diet and Health Study, a pilot-feasibility study to assess the impact of a whole-food plant-based vegan diet on college students' physical and mental health.

DESIGN

This 3-week theory-based pilot-feasibility study will employ a stratified, randomized control design (2 intervention groups and 1 comparison group) with measurement of primary and secondary outcomes at baseline and postintervention and end-of-study focus groups.

SETTING

Southeastern public state university.

PARTICIPANTS

Sixty undergraduate college students aged 18-25 years.

INTERVENTION

The study and intervention delivery were designed using an integration of the Theory of Planned Behavior and Social Cognitive Theory. Three consecutive weekly nutrition education lunch-and-learn sessions (75 minutes each) will be delivered using 2 different teaching modalities (ie, interactive-experiential vs lecture-based).

MAIN OUTCOME MEASURES

(1) Feasibility and acceptability of study procedures and theoretically-informed whole-food plant-based vegan diet intervention; (2) potential impacts of the intervention on intrapersonal, physical, and mental health, and dietary measures; and (3) potential differential impacts of 2 intervention modalities.

ANALYSIS

Descriptive statistics and effect sizes to assess changes to the outcome variables from baseline to postintervention across the 3 groups. Qualitative content analysis of the focus group transcripts.

Isolation and characterization of nettle (Urtica dioica L.) seed proteins: Conversion of underutilized by-products of the edible oil industry into food emulsifiers

This study aimed to upcycle a byproduct of the edible oil industry, cold-pressed nettle seed meal (CPNSM), into a plant-based emulsifier, thereby increasing the sustainability of the food system. The protein content of the nettle seed protein (NSP) powder was 48.3% with glutamic acid (16.6%), asparagine (10.7%), and arginine (9.7%) being the major amino acids. NSPs had a denaturation temperature of 66.6 °C and an isoelectric point of pH 4.3. They could be used as emulsifiers to form highly viscous coarse corn oil-in-water emulsions (10% oil, 4% NSP). Nevertheless, 10-fold diluted emulsions exhibited rapid creaming under different pH (2-9), salt (0-500 mM NaCl) and temperature (>40 °C) conditions, but they were relatively stable to aggregation. Our findings suggest that NSPs could be used as emulsifiers in highly viscous or gelled foods, like dressings, sauces, egg, cheese, or meat analogs.

Adherence to plant-based dietary patterns and anthropometric indices among primary school girls in Kerman: A cross-sectional study

The objective of the study was to evaluate the association between adherence to plant-based dietary patterns and anthropometric indices among primary school girls in Kerman. This cross-sectional study included 330 girls aged 6-12. A reliable and validated dish-based food frequency questionnaire was used to collect dietary data. Weight, height, and mid-arm circumference were measured, and z-score charts from the World Health Organization for girls between the ages of 5 and 19 were utilized. We used Satija et al. method to calculate plant-based diet index scores. After adjusting for age and energy, participants in the higher tertile of the overall plant-based diet index (PDI) had a lower height-for-age z score (HAZ) (0.38±0.12 vs. 0.59±0.12 kg; P = 0.033). Higher unhealthful plant-based diet index (uPDI) scores were significantly associated with decreased HAZ in models 2 (p = 0.028) and 3 (p = 0.035). A higher PDI score was associated with lower odds of being underweight and overweight, respectively (Model 1: P trend = 0.007, <0.001; Model 2: P trend = 0.010, 0.001). A significant inverse association was found between healthful plant-based diet index (hPDI) scores and underweight risk in the crude and adjusted models. (Model 1: P trend = 0.021; model 2: P trend = 0.018; Model 3: P trend = 0.031). Higher uPDI scores were associated with increased odds of being overweight and obese in all three models (Model 1: p trend<0.001; Model 2: p trend<0.001; Model 3: p trend = 0.001). We concluded that children who followed a plant-based diet had lower odds of being overweight and obese. Higher scores on the hPDI were linked to a decreased risk of being underweight, while higher scores on the uPDI were associated with an increased risk of being overweight and obese. The study suggests healthy plant-based diet may benefit children's weight and growth.

Nutrient scoring for the DEGS1-FFQ - from food intake to nutrient intake

BACKGROUND

While necessary for studying dietary decision-making or public health, estimates of nutrient supply based on self-reported food intake are barely accessible or fully lacking and remain a challenge in human research. In particular, detailed information on dietary fiber is limited. In this study we introduce an automated openly available approach to assess self-reported nutrient intake for research purposes for a popular, validated German food frequency questionnaire (FFQ).

METHODS

To this end, we i) developed and shared a code for assessing nutrients (carbohydrates, fat, protein, sugar, fiber, etc.) for 53 items of the quantitative, validated German DEGS1-FFQ questionnaire implementing expert-guided nutritional values of diverse sources with several raters. In a sample of individuals (nGUT-BRAIN = 61 (21 female) overweight, omnivorous), we ii) cross-validated nutrient intake of the last 7 days and the last 24 h and iii) computed test-retest reliability across two timepoints. Further, iv) we reported newly computed nutrient intake for two independent cross-sectional cohorts with continuous weight status and different dietary habits (nMensa = 134 (79 female, 1 diverse), nGREADT = 76 male). Exploratively, we v) correlated computed, energy-adjusted nutrient intake with anthropometric markers and HbA1c and vi) used linear mixed models to analyse the predictability of BMI and WHR by nutrient intake.

RESULTS

In overweight adults (n = 61 (21 female), mean age 28.2 ± 6.5 years, BMI 27.4 ± 1.6 kg/m2) nutrient intakes were mostly within recommended reference nutrient ranges for both last 7 days and last 24 h. Recommended fiber intake was not reached and sugar intake was surpassed. Calculated energy intake was significantly higher from last 24 h than from last 7 days but energy-adjusted nutrient intakes did not differ between those timeframes. Reliability of nutrient values between last 7 days and 24 h per visit was moderate (Pearson's rhoall ≥ 0.33, rhomax = 0.62) and absolute agreement across two timepoints was low to high for 7 days (Pearson's rhomin = 0.12, rhomax = 0.64,) and low to moderate for 24 h (Pearson's rhomin = 0.11, rhomax = 0.45). Associations of dietary components to anthropometric markers showed distinct sex differences, with overall higher intake by males compared to females and only females presenting a negative association of BMI with fiber intake. Lastly, in the overweight sample (but not when extending the analysis to a wider BMI range of 18.6-36.4 kg/m2), we could confirm that higher BMI was predicted by lower energy-adjusted fiber intake and higher energy-adjusted fat intake (when adjusting for age, sex and physical activity) while higher WHR was predicted by higher energy intake.

CONCLUSION

We provide an openly available tool to systematically assess nutrient intake, including fiber, based on self-report by a common German FFQ. The computed nutrient scores resembled overall plausible and reliable measures of nutrient intake given the known limitations of FFQs regarding over- or underreporting and suggest valid comparability when adjusting for energy intake. Our open code nutrient scoring can help to examine dietary intake in experimental studies, including dietary fiber, and can be readily adapted to other FFQs. Further validation of computed nutrients with biomarkers and nutrient-specific metabolites in serum, urine or feces will help to interpret self-reported dietary intake.

Effects of single plant-based vs. animal-based meals on satiety and mood in real-world smartphone-embedded studies

Adopting plant-based diets high in fiber may reduce global warming and obesity prevalence. Physiological and psychological determinants of plant-based food intake remain unclear. As fiber has been linked with improved gut-brain signaling, we hypothesized that a single plant-based (vegetarian and vegan) compared to an animal-based (animal flesh) meal, would induce higher satiety, higher mood and less stress. In three large-scale smartphone-based studies, adults (nall = 16,379) ranked satiety and mood before and after meal intake. Meal intake induced satiety and higher mood. Plant-based meal choices did not explain differences in post-meal hunger. Individuals choosing a plant-based meal reported slightly higher mood before and smaller mood increases after the meal compared to those choosing animal-based meals. Protein content marginally mediated post-meal satiety, while gender and taste ratings had a strong effect on satiety and mood in general. We could not detect the profound effects of plant-based vs. animal-based meals on satiety and mood.

Impact of obesity and diet on brain structure and function: a gut-brain-body crosstalk

Most societies witness an ever increasing prevalence of both obesity and dementia, a scenario related to often underestimated individual and public health burden. Overnutrition and weight gain have been linked with abnormal functionality of homoeostasis brain networks and changes in higher cognitive functions such as reward evaluation, executive functions and learning and memory. In parallel, evidence has accumulated that modifiable factors such as obesity and diet impact the gut-brain axis and modulate brain health and cognition through various pathways. Using neuroimaging data from epidemiological studies and randomised clinical trials, we aim to shed light on the underlying mechanisms and to determine both determinants and consequences of obesity and diet at the level of human brain structure and function. We analysed multimodal 3T MRI of about 2600 randomly selected adults (47 % female, 18-80 years of age, BMI 18-47 kg/m²) of the LIFE-Adult study, a deeply phenotyped population-based cohort. In addition, brain MRI data of controlled intervention studies on weight loss and healthy diets acquired in lean, overweight and obese participants may help to understand the role of the gut-brain axis in food craving and cognitive ageing. We find that higher BMI and visceral fat accumulation correlate with accelerated brain age, microstructure of the hypothalamus, lower thickness and connectivity in default mode- and reward-related areas, as well as with subtle grey matter atrophy and white matter lesion load in non-demented individuals. Mediation analyses indicated that higher visceral fat affects brain tissue through systemic low-grade inflammation, and that obesity-related regional changes translate into cognitive disadvantages. Considering longitudinal studies, some, but not all data indicate beneficial effects of weight loss and healthy diets such as plant-based nutrients and dietary patterns on brain ageing and cognition. Confounding effects of concurrent changes in other lifestyle factors or false positives might help to explain these findings. Therefore a more holistic intervention approach, along with open science tools such as data and code sharing, in-depth pre-registration and pooling of data could help to overcome these limitations. In addition, as higher BMI relates to increased head micro-movements during MRI, and as head motion in turn systematically induces image artefacts, future studies need to rigorously control for head motion during MRI to enable valid neuroimaging results. In sum, our results support the view that overweight and obesity are intertwined with markers of brain health in the general population, and that weight loss and plant-based diets may help to promote brain plasticity. Meta-analyses and longitudinal cohort studies are underway to further differentiate causation from correlation in obesity- and nutrition-brain research.

Volumetric changes in specific neurofunctional subfields of the hippocampus in major depressive disorder

OBJECTIVE

There is evidence that hippocampal volume is abnormal in patients with major depressive disorder (MDD), but there have been no studies on volumetric changes in different subfields based on functional topography. This was investigated in the present study by comparing hippocampal neurofunctional subfield volumes between MDD patients and healthy control (HC) subjects.

METHODS

Patients with MDD (n = 44) and HCs (n = 27) recruited at Shanghai Traditional Chinese Medicine Integrated Hospital underwent a T1-weighted anatomical MRI scan in the sagittal orientation, and the data were used to calculate hippocampal subfield volumes. Logistic regression was used to evaluate the association between the volumes and risk of MDD. A nomogram for predicting MDD risk based on volume changes in different subfields was developed, and its predictive power was evaluated by calculating the concordance (C)-index.

RESULTS

Compared with HCs, MDD patients showed reduced volume in hippocampal neurofunctional subfields, specifically in left (L)1, right (R)1, and R2 (related to emotion) and L2, L3, and R4 (related to cognition and perception). The logistic regression analysis revealed that the risk of MDD was 4.59-, 5.8-, 8.33-, and 6.92-fold higher with atrophies of L1, L2, L3, and R4, respectively. A nomogram for predicting MDD risk was developed based on age; sex; and hippocampal L1, L2, L3, and R4 subfield volumes and showed good accuracy, with a C-index of 0.784.

CONCLUSION

Volumetric changes in the neurofunctional subfield of the hippocampus are potential imaging markers that can predict the occurrence of MDD.