Protein intake and the incidence of pre-diabetes and diabetes in 4 population-based studies: the PREVIEW project

Association between total, animal, and plant protein intake and type 2 diabetes risk in adults: A systematic review and dose-response meta-analysis of prospective cohort studies

BACKGROUND AND AIMS

While clinical studies indicate that dietary protein may benefit glucose homeostasis in type 2 diabetes (T2D), the impact of dietary protein, including whether the protein is of animal or plant origin, on the risk of T2D is uncertain. We conducted a systematic review and meta-analysis to evaluate the associations of total, animal, and plant protein intakes with the risk of T2D.

METHODS

A systematic search was performed using multiple data sources, including PubMed/Medline, ISI Web of Science, Scopus, and Google Scholar, with the data cut-off in May 2023. Our selection criteria focused on prospective cohort studies that reported risk estimates for the association between protein intake and T2D risk. For data synthesis, we calculated summary relative risks and 95% confidence intervals for the highest versus lowest categories of protein intake using random-effects models. Furthermore, we conducted both linear and non-linear dose-response analyses to assess the dose-response associations between protein intake and T2D risk.

RESULTS

Sixteen prospective cohort studies, involving 615,125 participants and 52,342 T2D cases, were identified, of which eleven studies reported data on intake of both animal and plant protein. Intakes of total (pooled effect size: 1.14, 95% CI: 1.04-1.24) and animal (pooled effect size: 1.18, 95% CI: 1.09-1.27) protein were associated with an increased risk of T2D. These effects were dose-related - each 20-g increase in total or animal protein intake increased the risk of T2D by ∼3% and ∼7%, respectively. In contrast, there was no association between intake of plant protein and T2D risk (pooled effect size: 0.98, 95% CI: 0.89-1.08), while replacing animal with plant protein intake (per each 20 g) was associated with a reduced risk of T2D (pooled effect size: 0.80, 95% CI: 0.76-0.84).

CONCLUSIONS

Our findings indicate that long-term consumption of animal, but not plant, protein is associated with a significant and dose-dependent increase in the risk of T2D, with the implication that replacement of animal with plant protein intake may lower the risk of T2D.

Dietary protein, amino acids and type 2 diabetes mellitus: a short review

Diabetes is a widespread metabolic disorder and results from insulin resistance and impaired insulin secretion. Modifiable factors like diet, physical activity, and body weight play crucial roles in diabetes prevention, with targeted interventions reducing diabetes risk by about 60%. High-protein consumption, above the recommended intake of 0.8 g/kg body weight per day, have often explored in relation to diabetes risk. However, the relationship between dietary protein and diabetes is multifaceted. Observational studies have linked high total and animal protein intake to an increased risk of type 2 diabetes, particularly in obese women. Elevated levels of branched-chain amino acids (BCAA), which can result from dietary intake, protein breakdown, as well as an impaired catabolism, are strong predictors of cardiometabolic risk and insulin resistance. With several mechanism linking BCAA to insulin resistance. On the other hand, intervention studies suggest that high-protein diets can support weight loss and improve cardiometabolic risk factors. However, the impact on insulin sensitivity and glucose homeostasis is not straightforward. Proteins and amino acids stimulate both insulin and glucagon secretion, influencing glucose levels, but chronic effects remain uncertain. This short narrative review aims to provide an update on the relationship between increased dietary protein intake, amino acids, insulin resistance and type 2 diabetes, and to describe protein recommendations for type 2 diabetes.

Plant-Based Food for the Prevention of Type 2 Diabetes: Scoping Review

Type 2 Diabetes Mellitus (T2DM) is a chronic condition with growing worldwide prevalence. Besides genetic factors, a sedentary lifestyle, excess weight, and inadequate eating habits, characterized by an excess intake of refined carbohydrates and ultra-processed foods, are contributing factors for the development of the disease. In this scenario, promoting a plant-based diet, and limiting animal product consumption while increasing the intake of vegetables, concurrently with healthy lifestyle habits, is a promising strategy to prevent T2DM. This scoping review, carried out between 2017 and 2022, aimed to gather evidence substantiating the benefits of a plant-based diet in T2DM prevention, considering different eating patterns, such as vegetarian, vegan, Mediterranean, and DASH diets. Several studies demonstrate a significant reduction in T2DM incidence among individuals adopting plant-based eating patterns or emphasizing healthy plant-based food alongside decreased intake or exclusion of animal-based foods. There are still no robust data regarding plant-based diets and the prevention of diabetes without loss in body weight. Hence, prospective studies in plant-based diets with weight control are needed. Nevertheless, adopting plant-based diets appears to induce significant weight loss, which is crucial in an obesity-endemic context. Thus, embracing plant-based diets, along with healthy habits, emerges as a relevant strategy in obesity and T2DM prevention.

Amelioration of Insulin Resistance by Whey Protein in a High-Fat Diet-Induced Pediatric Obesity Male Mouse Model

This study examined whey protein's impact on insulin resistance in a high-fat diet-induced pediatric obesity mouse model. Pregnant mice were fed high-fat diets, and male pups continued this diet until 8 weeks old, then were split into high-fat, whey, and casein diet groups. At 12 weeks old, their body weight, fasting blood glucose (FBG), blood insulin level (IRI), homeostatic model assessment for insulin resistance (HOMA-IR), liver lipid metabolism gene expression, and liver metabolites were compared. The whey group showed significantly lower body weight than the casein group at 12 weeks old (p = 0.034). FBG was lower in the whey group compared to the high-fat diet group (p < 0.01) and casein group (p = 0.058); IRI and HOMA-IR were reduced in the whey group compared to the casein group (p = 0.02, p < 0.01, p < 0.01, respectively). The levels of peroxisome proliferator-activated receptor α and hormone-sensitive lipase were upregulated in the whey group compared to the casein group (p < 0.01, p = 0.03). Metabolomic analysis revealed that the levels of taurine and glycine, both known for their anti-inflammatory and antioxidant properties, were upregulated in the whey group in the liver tissue (p < 0.01, p < 0.01). The intake of whey protein was found to improve insulin resistance in a high-fat diet-induced pediatric obesity mouse model.

Dietary protein in early pregnancy and gestational diabetes mellitus: a prospective cohort study

PURPOSE

The relationship between dietary protein intake and the risk of gestational diabetes mellitus (GDM) remains inconsistent and unclear. Here, we examined the correlation between the various sources of protein intake among Chinese pregnant women and GDM.

METHODS

This prospective cohort study included 1060 pregnant women at 6-13+6 weeks of gestation from Guangdong Provincial Hospital for Women and Children, South China. The participants' intake of dietary protein was assessed using a validated quantitative food frequency questionnaire during the early trimester. GDM was diagnosed via an oral glucose tolerance test performed at 24-28 gestational weeks. Logistic regression analysis was used to evaluate the association between dietary protein intake during pregnancy and GDM. Furthermore, we applied restricted cubic splines to determine their linear relationship.

RESULTS

About 26.3% (n = 279) of pregnant women were diagnosed with GDM. Animal protein intake was revealed to have a positive correlation with GDM risk (Q4 vs. Q1: OR, 2.78; 95% CI, 1.46-5.34; P = 0.015), whereas high intake levels of dietary plant protein were linked to reduced GDM risk (Q4 vs. Q1: OR, 0.43; 95% CI, 0.25-0.73). In stratified analysis, the relationship between protein and GDM was stronger during early pregnancy in women with obesity. However, total protein intake did not show a significant association with GDM.

CONCLUSIONS

Our study findings suggest that a plant protein-based diet was associated with reduced GDM risk, whereas the dietary intake of animal protein was positively associated with GDM risk among Chinese women during early pregnancy.

Prognostic Factors for Hyperglycemia in Patients Receiving Chemotherapy

BACKGROUND

Approximately 10% to 30% of patients who receive chemotherapy experience hyperglycemia, which can affect the adverse reactions and treatment efficacy of chemotherapy. However, there is a paucity of research to explore the factors affecting hyperglycemia and include them in nursing interventions.

OBJECTIVE

The aim of this study was to understand the prognostic factors of hyperglycemia in cancer patients on chemotherapy.

METHODS

This retrospective, descriptive study included 134 adult patients with cancer receiving chemotherapy at Keimyeng University Dongsan Hospital in Daegu between July 1, 2021, and March 31, 2022. Data were analyzed using frequency, percentage, average, and standard deviation statistics and compared by t test, χ2 test, and logistic regression analysis.

RESULTS

Logistic regression analysis revealed that sex (male) (95% confidence interval [CI], 7.24-745.49; odds ratio [OR], 73.48); education (95% CI, 4.02-201.59; OR, 28.46); exercise durations of 30 to 60 minutes (95% CI, 0.00-0.06; OR, 0.01), 60 to 90 minutes (95% CI, 0.00-0.05, OR = 0.01), and ≥90 minutes (95% CI, 0.00-0.42; OR, 0.03); exercise amount ≥ 2000 kcal/wk (95% CI, 0.01-0.77; OR, 0.06); and daily fat (95% CI, 1.02-1.14; OR, 1.08), protein (95% CI, 0.82-0.95; OR, 0.88), and seaweed (95% CI, 0.85-0.99; OR, 0.92) intake were significant predictors of hyperglycemia.

CONCLUSION

The prognostic factors of hyperglycemia should be included in nursing interventions to prevent and manage hyperglycemia, which in turn may help reduce adverse reactions related to chemotherapy and improve treatment efficacy.

IMPLICATIONS FOR PRACTICE

To prevent and manage hyperglycemia in patients on chemotherapy, prognostic factors, including exercise and protein, fat, and seaweed consumption, should be considered in nursing interventions. Particularly, in men and patients with low education levels who are at a high risk of hyperglycemia, nursing interventions for diet and exercise should be individualized.

Substitution of animal-based with plant-based foods on cardiometabolic health and all-cause mortality: a systematic review and meta-analysis of prospective studies

BACKGROUND

There is growing evidence that substituting animal-based with plant-based foods is associated with a lower risk of cardiovascular diseases (CVD), type 2 diabetes (T2D), and all-cause mortality. Our aim was to summarize and evaluate the evidence for the substitution of any animal-based foods with plant-based foods on cardiometabolic health and all-cause mortality in a systematic review and meta-analysis.

METHODS

We systematically searched MEDLINE, Embase, and Web of Science to March 2023 for prospective studies investigating the substitution of animal-based with plant-based foods on CVD, T2D, and all-cause mortality. We calculated summary hazard ratios (SHRs) and 95% confidence intervals (95% CI) using random-effects meta-analyses. We assessed the certainty of evidence (CoE) using the GRADE approach.

RESULTS

In total, 37 publications based on 24 cohorts were included. There was moderate CoE for a lower risk of CVD when substituting processed meat with nuts [SHR (95% CI): 0.73 (0.59, 0.91), n = 8 cohorts], legumes [0.77 (0.68, 0.87), n = 8], and whole grains [0.64 (0.54, 0.75), n = 7], as well as eggs with nuts [0.83 (0.78, 0.89), n = 8] and butter with olive oil [0.96 (0.95, 0.98), n = 3]. Furthermore, we found moderate CoE for an inverse association with T2D incidence when substituting red meat with whole grains/cereals [0.90 (0.84, 0.96), n = 6] and red meat or processed meat with nuts [0.92 (0.90, 0.94), n = 6 or 0.78 (0.69, 0.88), n = 6], as well as for replacing poultry with whole grains [0.87 (0.83, 0.90), n = 2] and eggs with nuts or whole grains [0.82 (0.79, 0.86), n = 2 or 0.79 (0.76, 0.83), n = 2]. Moreover, replacing red meat for nuts [0.93 (0.91, 0.95), n = 9] and whole grains [0.96 (0.95, 0.98), n = 3], processed meat with nuts [0.79 (0.71, 0.88), n = 9] and legumes [0.91 (0.85, 0.98), n = 9], dairy with nuts [0.94 (0.91, 0.97), n = 3], and eggs with nuts [0.85 (0.82, 0.89), n = 8] and legumes [0.90 (0.89, 0.91), n = 7] was associated with a reduced risk of all-cause mortality.

CONCLUSIONS

Our findings indicate that a shift from animal-based (e.g., red and processed meat, eggs, dairy, poultry, butter) to plant-based (e.g., nuts, legumes, whole grains, olive oil) foods is beneficially associated with cardiometabolic health and all-cause mortality.

Quantile forward regression for high-dimensional survival data

Despite the urgent need for an effective prediction model tailored to individual interests, existing models have mainly been developed for the mean outcome, targeting average people. Additionally, the direction and magnitude of covariates' effects on the mean outcome may not hold across different quantiles of the outcome distribution. To accommodate the heterogeneous characteristics of covariates and provide a flexible risk model, we propose a quantile forward regression model for high-dimensional survival data. Our method selects variables by maximizing the likelihood of the asymmetric Laplace distribution (ALD) and derives the final model based on the extended Bayesian Information Criterion (EBIC). We demonstrate that the proposed method enjoys a sure screening property and selection consistency. We apply it to the national health survey dataset to show the advantages of a quantile-specific prediction model. Finally, we discuss potential extensions of our approach, including the nonlinear model and the globally concerned quantile regression coefficients model.

Exploring the Interrelationships between Diabetes, Nutrition, Anxiety, and Depression: Implications for Treatment and Prevention Strategies

Across the world, diabetes, depression, and anxiety symptoms have gained widespread recognition as significant public health issues. Recent research has unveiled a mutually influential relationship between diabetes and these two mental health conditions, where each disorder impacts the course and outcomes of the others. The role of nutrition emerges as pivotal in preventing and treating depression, anxiety, and diabetes. A thorough literature review was undertaken to investigate the reciprocal effects between anxiety, depression, and diabetes, including their impact on the development and severity of each condition. Additionally, the effects of nutrition on the prevention and management of depression, anxiety, diabetes, and related complications in at-risk individuals were assessed. Our findings show that mental disorders, such as depression and anxiety, increase the risk of developing type 2 diabetes and are associated with poorer glycemic control, increased diabetes-related complications, and higher mortality rates. Conversely, diabetes is also linked with an increased risk of developing depression and anxiety. The biological, psychological, and social factors that contribute to the comorbidity between these two conditions are complex and multifaceted. Therefore, an integrated approach to the management of both conditions is critical for improving patient outcomes and reducing the overall burden of disease. Nutritional interventions should be utilized to reduce the risk of diabetes in patients with anxiety and depression as well as enhance mental health in patients with diabetes.

Cumulative Consumption of Sulfur Amino Acids and Risk of Diabetes: A Prospective Cohort Study

BACKGROUND

Cross-sectional studies have suggested that consumption of sulfur amino acids (SAAs), including methionine and cysteine, is associated with a higher risk of type 2 diabetes (T2D) in humans and with T2D-related biomarkers in animals. But whether higher long-term SAA intake increases the risk of T2D in humans remains unknown.

OBJECTIVES

We aimed to investigate the association between long-term dietary SAA intake and risk of T2D.

METHODS

We analyzed data collected from 2 different cohorts of the Framingham Heart Study, a long-term, prospective, and ongoing study. The Offspring cohort (1991-2014) included participants from fifth through ninth examinations, and the Third-Generation cohort (2002-2011) included participants from first and second examinations. After excluding participants with a clinical history of diabetes, missing dietary data, or implausible total energy intake, 3222 participants in the Offspring cohort and 3205 participants in the Third-Generation cohort were included. Dietary intake was assessed using a validated FFQ. The relations between energy-adjusted total SAA (methionine and cysteine) intake or individual SAA intake (in quintiles) and risk of incident T2D were estimated via Cox proportional hazards models after adjusting for dietary and nondietary risk factors. Associations across the 2 cohorts were determined by direct combination and meta-analysis.

RESULTS

During the 23 y of follow-up, 472 participants reported a new diagnosis of T2D in the 2 cohorts. In the meta-analysis, the HRs of T2D comparing the highest with the lowest intake of total SAAs, methionine, and cysteine were 1.8 (95% CI: 1.3, 2.5), 1.7 (95% CI: 1.2, 2.3), and 1.4 (95% CI: 1.0, 2.1), respectively. The association of SAA intake with T2D was attenuated after adjusting animal protein intake in sensitivity analyses.

CONCLUSIONS

Our findings show that excess intake of SAAs is associated with higher risk of T2D. Dietary patterns that are low in SAAs could help in preventing T2D.

Emerging sources and applications of alternative proteins: An introduction

Food protein is an essential macronutrient. Even though daily per capita supply of protein has increased globally from 61g in 1961 to 81g in 2013, and most people in the developed world have sufficient protein intake from their diets, however, protein deficiencies continue to be pervasive globally. Protein deficiency is the single major factor responsible for impaired growth and suboptimal health worldwide. Animal proteins are high quality and contain adequate and balanced amino acids, animal protein production however is inefficient and resource intensive. Alternative proteins are expected to provide the solution to meet the growing protein demand within the environmental limits. Alternative proteins include proteins from plants (i.e., grains, legumes, pulse, and nuts), fungus (i.e., mushrooms), algae, insects and cultured (lab-grown) meat that can be used to replace conventional animal proteins. Major concerns for human consumption of alternative proteins are inferior organoleptic properties, consumer acceptability, affordability, and sustainability. There is a need to develop culturally diversified alternative proteins to mitigate global protein malnutrition. Food proteins are also found applications in biomaterials and as a source of bioactive peptides.

Associations Between Dietary Patterns and Incident Type 2 Diabetes: Prospective Cohort Study of 120,343 UK Biobank Participants

OBJECTIVE

To identify dietary patterns (DPs) characterized by a set of nutrients of concern and their association with incident type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

A total of 120,343 participants from the U.K. Biobank study with at least two 24 h dietary assessments were studied. Reduced rank regression was used to derive DPs explaining variability in energy density, free sugars, saturated fat, and fiber intakes. We investigated prospective associations with T2D using Cox proportional hazard models.

RESULTS

Over 8.4 years of follow-up from the latest dietary assessment, 2,878 participants developed T2D. Two DPs were identified that jointly explained a total of 63% variation in four nutrients. DP1 was characterized by high intakes of chocolate and confectionery, butter, low-fiber bread, and sugars and preserves, and low intakes of fruits and vegetables. DP1 was linearly associated with T2D in multivariable models without BMI adjustment (per z score, hazard ratio [HR] 1.11 [95% CI 1.08-1.14]) and after BMI adjustment (HR 1.09 [95% CI 1.06-1.12]). DP2 was characterized by high intakes of sugar-sweetened beverages, fruit juice, table sugars and preserves, and low intakes of high-fat cheese and butter, but showed no clear association with T2D. There were significant interactions between both DPs and age, with increased risks among younger people in DP1 (HR 1.13 [95% CI 1.09-1.18]) and DP2 (HR 1.10 [95% CI 1.05-1.15]), as well as with DP1 and BMI, with increased risks among people with obesity (HR 1.11 [95% CI 1.07-1.16]).

CONCLUSIONS

A DP characterized by high intakes of chocolate and confectionery, butter, low-fiber bread, and added sugars, and low in fresh fruits and vegetables intake is associated with a higher incidence of T2D, particularly among younger people and those with obesity.

A review of harmonization methods for studying dietary patterns

Data harmonization is the process by which each of the variables from different research studies are standardized to similar units resulting in comparable datasets. These data may be integrated for more powerful and accurate examination and prediction of outcomes for use in the intelligent and smart electronic health software programs and systems. Prospective harmonization is performed when researchers create guidelines for gathering and managing the data before data collection begins. In contrast, retrospective harmonization is performed by pooling previously collected data from various studies using expert domain knowledge to identify and translate variables. In nutritional epidemiology, dietary data harmonization is often necessary to construct the nutrient and food databases necessary to answer complex research questions and develop effective public health policy. In this paper, we review methods for effective data harmonization, including developing a harmonization plan, which common standards already exist for harmonization, and defining variables needed to harmonize datasets. Currently, several large-scale studies maintain harmonized nutrient databases, especially in Europe, and steps have been proposed to inform the retrospective harmonization process. As an example, data harmonization methods are applied to several U.S longitudinal diet datasets. Based on our review, considerations for future dietary data harmonization include user agreements for sharing private data among participating studies, defining variables and data dictionaries that accurately map variables among studies, and the use of secure data storage servers to maintain privacy. These considerations establish necessary components of harmonized data for smart health applications which can promote healthier eating and provide greater insights into the effect of dietary patterns on health.

Sustaining Protein Nutrition Through Plant-Based Foods

Proteins are essential components of the human diet. Dietary proteins could be derived from animals and plants. Animal protein, although higher in demand, is generally considered less environmentally sustainable. Therefore, a gradual transition from animal- to plant-based protein food may be desirable to maintain environmental stability, ethical reasons, food affordability, greater food safety, fulfilling higher consumer demand, and combating of protein-energy malnutrition. Due to these reasons, plant-based proteins are steadily gaining popularity, and this upward trend is expected to continue for the next few decades. Plant proteins are a good source of many essential amino acids, vital macronutrients, and are sufficient to achieve complete protein nutrition. The main goal of this review is to provide an overview of plant-based protein that helps sustain a better life for humans and the nutritional quality of plant proteins. Therefore, the present review comprehensively explores the nutritional quality of the plant proteins, their cost-effective extraction and processing technologies, impacts on nutrition, different food wastes as an alternative source of plant protein, and their environmental impact. Furthermore, it focuses on the emerging technologies for improving plant proteins' bioavailability, digestibility, and organoleptic properties, and highlights the aforementioned technological challenges for future research work.

Associations of changes in reported and estimated protein and energy intake with changes in insulin resistance, glycated hemoglobin, and BMI during the PREVIEW lifestyle intervention study

BACKGROUND

Observed associations of high-protein diets with changes in insulin resistance are inconclusive.

OBJECTIVES

We aimed to assess associations of changes in both reported and estimated protein (PRep; PEst) and energy intake (EIRep; EIEst) with changes in HOMA-IR, glycated hemoglobin (HbA1c), and BMI (in kg/m2), in 1822 decreasing to 833 adults (week 156) with overweight and prediabetes, during the 3-y PREVIEW (PREVention of diabetes through lifestyle intervention and population studies In Europe and around the World) study on weight-loss maintenance. Eating behavior and measurement errors (MEs) of dietary intake were assessed. Thus, observational post hoc analyses were applied.

METHODS

Associations of changes in EIEst, EIRep, PEst, and PRep with changes in HOMA-IR, HbA1c, and BMI were determined by linear mixed-model analysis in 2 arms [high-protein-low-glycemic-index (GI) diet and moderate-protein-moderate-GI diet] of the PREVIEW study. EIEst was derived from energy requirement: total energy expenditure = basal metabolic rate × physical activity level; PEst from urinary nitrogen, and urea. MEs were calculated as [(EIEst - EIRep)/EIEst] × 100% and [(PRep - PEst)/PEst] × 100%. Eating behavior was determined using the Three Factor Eating Questionnaire, examining cognitive dietary restraint, disinhibition, and hunger.

RESULTS

Increases in PEst and PRep and decreases in EIEst and EIRep were associated with decreases in BMI, but not independently with decreases in HOMA-IR. Increases in PEst and PRep were associated with decreases in HbA1c. PRep and EIRep showed larger changes and stronger associations than PEst and EIEst. Mean ± SD MEs of EIRep and PRep were 38% ± 9% and 14% ± 4%, respectively; ME changes in EIRep and En% PRep were positively associated with changes in BMI and cognitive dietary restraint and inversely with disinhibition and hunger.

CONCLUSIONS

During weight-loss maintenance in adults with prediabetes, increase in protein intake and decrease in energy intake were not associated with decrease in HOMA-IR beyond associations with decrease in BMI. Increases in PEst and PRep were associated with decrease in HbA1c.This trial was registered at clinicaltrials.gov as NCT01777893.

Protein Intake and Human Health: Implications of Units of Protein Intake

Understanding the health effects of protein intake is bedeviled by a number of factors, including protein quality and source. In addition, different units, including grams, grams per kilogram body weight (g/kg BW), and percent energy, may contribute to confusion about protein's effects on health, especially BW-based units in increasingly obese populations. We aimed to review the literature and to conduct a modeling demonstration of various units of protein intake in relation to markers of cardiometabolic health. Data from the Framingham Heart Study Offspring (n = 1847; 60.3 y; 62.5% women) and Third Generation (n = 2548; 46.2 y; 55.3% women) cohorts and the NHANES 2003-04 (n = 1625; 46.2 y; 49.7% women) and 2005-06 (n = 1347; 43.7 y; 49.5% women) cycles were used to model cross-sectional associations between 7 protein units (grams, percent energy, g/kg ideal BW, g/kg actual BW, BW-adjusted g/kg actual BW, g/kg lean BW, and g/kg fat-free BW) and 9 cardiometabolic outcomes (fasting glucose, systolic and diastolic blood pressure, total and HDL cholesterol, triglycerides, BMI, waist circumference, and estimated glomerular filtration rate). The literature review indicated the use of myriad units of protein intake, with differential results on cardiometabolic outcomes. The modeling demonstration showed units expressed in BW were confounded by BW, irrespective of outcome. Units expressed in grams, percent energy, and ideal BW showed similar results, with or without adjustment for body size. After adjusting for BW, results of units expressed in BW aligned with results of grams, percent energy, and ideal BW. In conclusion, protein intake in cardiometabolic health appears to depend on protein's unit of expression. Authors should be specific about the use of WHO (g/kg ideal BW) compared with US (g/kg actual BW) units, and ideally use gram or percent energy in observational studies. In populations where overweight/obesity are prevalent, intake based on actual BW should be reevaluated.

The PREVIEW intervention study: Results from a 3-year randomized 2 x 2 factorial multinational trial investigating the role of protein, glycaemic index and physical activity for prevention of type 2 diabetes

AIM

To compare the impact of two long-term weight-maintenance diets, a high protein (HP) and low glycaemic index (GI) diet versus a moderate protein (MP) and moderate GI diet, combined with either high intensity (HI) or moderate intensity physical activity (PA), on the incidence of type 2 diabetes (T2D) after rapid weight loss.

MATERIALS AND METHODS

A 3-year multicentre randomized trial in eight countries using a 2 x 2 diet-by-PA factorial design was conducted. Eight-week weight reduction was followed by a 3-year randomized weight-maintenance phase. In total, 2326 adults (age 25-70 years, body mass index ≥ 25 kg/m² ) with prediabetes were enrolled. The primary endpoint was 3-year incidence of T2D analysed by diet treatment. Secondary outcomes included glucose, insulin, HbA1c and body weight.

RESULTS

The total number of T2D cases was 62 and the cumulative incidence rate was 3.1%, with no significant differences between the two diets, PA or their combination. T2D incidence was similar across intervention centres, irrespective of attrition. Significantly fewer participants achieved normoglycaemia in the HP compared with the MP group (P < .0001). At 3 years, normoglycaemia was lowest in HP-HI (11.9%) compared with the other three groups (20.0%-21.0%, P < .05). There were no group differences in body weight change (-11% after 8-week weight reduction; -5% after 3-year weight maintenance) or in other secondary outcomes.

CONCLUSIONS

Three-year incidence of T2D was much lower than predicted and did not differ between diets, PA or their combination. Maintaining the target intakes of protein and GI over 3 years was difficult, but the overall protocol combining weight loss, healthy eating and PA was successful in markedly reducing the risk of T2D. This is an important clinically relevant outcome.

Cow's Milk and Dairy Consumption: Is There Now Consensus for Cardiometabolic Health?

Cow's milk and dairy products derived from this complex food source have long been proposed as beneficial to human health, yet underlying clinical evidence of direct benefit continues to raise controversy. Limited evidence supports positive cardiometabolic effects of a number of dairy macro- and micronutrient components including whey protein and casein, unsaturated fats, milk fat globule membrane (MFGM) and polar phospholipids, vitamin D and calcium, in addition to non-bovine components including bacterial and yeast probiotics. More controversial remain lipid components trans fats, including trans vaccenic acid, trans palmitoleic acid, and conjugated cis trans linoleic acid (CLA), plus medium-chain and odd-chain dairy fats. New evidence is rapidly identifying multiple pathways by which these dairy nutrients may effect health. Processing, including fermentation and homogenization, may also have positive effects. Conversely, the high saturated fat content of dairy has long raised concern, aligned with international guidelines to minimize dietary intake of animal-origin saturated fatty acids (SFA) to achieve better cardiometabolic health. However, led in part by observational studies and meta-analyses showing dairy to have no or even an inverse association with cardiometabolic health, evidence from randomized controlled trials (RCTs) has been scrutinized over the last 5 years, and focus on low-fat dairy has been challenged. Recent evidence supports the hypothesis that adverse effects of SFAs on metabolic health may be ameliorated when these fats are consumed within a complex matrix such as milk, cheese or yogurt, and that dairy food categories may influence outcomes as much as total fat content. For example, yogurt and high-fat, high-SFA cheese have a negative association with risk of type 2 diabetes (T2D) in many, not all, published trials. However, large sample dairy RCTs of long duration with CVD or T2D incidence as primary endpoints are lacking. This is a clear research gap, with these clinical studies required if a causative link between dairy and improved cardiometabolic health is to be confirmed and in turn promoted through dietary guidelines. Current advisories from national guidance groups such as American Heart Association (AHA) and European Society of Cardiology (ESC) continue to promote consumption of low-fat dairy products, whilst liquid milk and yogurt remain part of nutrition guidelines from joint American Diabetes Association (ADA)/European Association for Study of Diabetes (EASD) reports, and as part of a "no-one-size-fits-all" answer to diet and T2D by the ADA in their most recent 2019 Consensus Report.

Dietary protein insufficiency: an important consideration in fatty liver disease?

Dietary protein insufficiency has been linked to excessive TAG storage and non-alcoholic fatty liver disease (NAFLD) in developing countries. Hepatic TAG accumulation following a low-protein diet may be due to altered peroxisomal, mitochondrial and gut microbiota function. Hepatic peroxisomes and mitochondria normally mediate metabolism of nutrients to provide energy and substrates for lipogenesis. Peroxisome biogenesis and activities can be modulated by odd-chain fatty acids (OCFA) and SCFA that are derived from gut bacteria, for example, propionate and butyrate. Also produced during amino acid metabolism by peroxisomes and mitochondria, propionate and butyrate concentrations correlate inversely with risk of obesity, insulin resistance and NAFLD. In this horizon-scanning review, we have compiled available evidence on the effects of protein malnutrition on OCFA production, arising from loss in mitochondrial, peroxisomal and gut microbiota function, and its association with lipid accumulation in the liver. The methyl donor amino acid composition of dietary protein is an important contributor to liver function and lipid storage; the presence and abundance of dietary branched-chain amino acids can modulate the composition and metabolic activity of the gut microbiome and, on the other hand, can affect protective OCFA and SCFA production in the liver. In preclinical animal models fed with low-protein diets, specific amino acid supplementation can ameliorate fatty liver disease. The association between low dietary protein intake and fatty liver disease is underexplored and merits further investigation, particularly in vulnerable groups with dietary protein restriction in developing countries.

Nutritional Challenges in Metabolic Syndrome

Metabolic Syndrome (MetS) is a combination of risk factors for the development of cardiovascular disease (CVD) and type 2 diabetes. Different diagnostic criteria were proposed, but a consensus was reached in 2009 based on values of waist circumference, blood pressure, fasting glycemia, triglycerides, and high-density lipoprotein (HDL)-cholesterol levels. The main underlying etiologic factor is insulin resistance. The quality and quantity of individual macronutrients have an influence on the development and resolution of this syndrome. However, the main treatment goal is weight loss and a decrease in insulin resistance. A controlled energy dietary recommendation, together with moderate levels of physical activity, may positively change the parameters of MetS. However, there is no single dietary or exercise prescription that works for all patients. Dietary patterns such as Mediterranean-style, dietary approaches to stop hypertension (DASH), low-carbohydrate, and low-fat diets can ameliorate insulin resistance and MetS. Long-term adherence to a healthy lifestyle is key in assuring that individuals significantly reduce the risk of CVD and diabetes mellitus.