The Carnivore Connection Hypothesis: Revisited

The “Carnivore Connection” hypothesizes that, during human evolution, a scarcity of dietary carbohydrate in diets with low plant : animal subsistence ratios led to insulin resistance providing a survival and reproductive advantage with selection of genes for insulin resistance. The selection pressure was relaxed at the beginning of the Agricultural Revolution when large quantities of cereals first entered human diets. The “Carnivore Connection” explains the high prevalence of intrinsic insulin resistance and type 2 diabetes in populations that transition rapidly from traditional diets with a low-glycemic load, to high-carbohydrate, high-glycemic index diets that characterize modern diets. Selection pressure has been relaxed longest in European populations, explaining a lower prevalence of insulin resistance and type 2 diabetes, despite recent exposure to famine and food scarcity. Increasing obesity and habitual consumption of high-glycemic-load diets worsens insulin resistance and increases the risk of type 2 diabetes in all populations

The Glycaemic Index-Food-Frequency Questionnaire: Development and validation of a food frequency questionnaire designed to estimate the dietary intake of glycaemic index and glycaemic load:An effort by the PREVIEW Consortium

Dietary glycaemic index (GI) and glycaemic load (GL) are indices used to quantify the effect of carbohydrate quality and quantity on postprandial glycaemia. GI/GL-health associations are widely studied but data on the validity of integrated GI/GL measurements are scarce. We evaluated the performance of a food-frequency questionnaire (FFQ) specifically developed to assess GI/GL. In total, 263 Dutch men and 212 women (aged 55 ± 11 years) completed a 58-item GI-FFQ, an 183-item general-FFQ and a 2-day 24 h-recall and donated blood for glycated haemoglobin (HbA1c) determination. The level of agreement between these methods was evaluated by (1) cross-classification, (2) correlations and (3) Bland and Altman plots. The three dietary assessment methods provided comparable mean intake estimates for total carbohydrates (range: 214–237 g/day), mono/disaccharides (100–107 g/day), polysaccharides (114–132 g/day), as well as bread, breakfast cereals, potatoes, pasta, rice, fruit, dairy, cakes/cookies and sweets. Mean (±SD) GI estimates were also comparable between the GI-FFQ (54 ± 3), general-FFQ (53 ± 4) and 24 h-recalls (53 ± 5). Mean (±SD) GI-FFQ GL (117 ± 37) was slightly lower than the general-FFQ GL (126 ± 38) and 24 h-recalls GL (127 ± 37). Classification of GI in quartiles was identical for the GI-FFQ and general-FFQ for 43% of the population (r = 0.58) and with 24 h-recalls for 35% of the population (de-attenuated r = 0.64). For GL, this was 48% (r = 0.65) and 44% (de-attenuated r = 0.74). Correlations between GI and HbA1c were low (r = −0.09 for GI-FFQ, r = −0.04 for general-FFQ and r = 0.07 for 24 h-recalls). In conclusion, compared to a general-FFQ and 24 h-recalls, the GI-FFQ showed a moderate to good relative validity for carbohydrates, carbohydrate-rich foods and GI/GL. No metric predicted HbA1c

Effect of the Glycemic Index of Carbohydrates on Acne vulgaris

Acne vulgaris may be improved by dietary factors that increase insulin sensitivity. We hypothesized that a low-glycemic index diet would improve facial acne severity and insulin sensitivity. Fifty-eight adolescent males (mean age ± standard deviation 16.5 ± 1.0 y and body mass index 23.1 ± 3.5 kg/m2) were alternately allocated to high or low glycemic index diets. Severity of inflammatory lesions on the face, insulin sensitivity (homeostasis modeling assessment of insulin resistance), androgens and insulin-like growth factor-1 and its binding proteins were assessed at baseline and at eight weeks, a period corresponding to the school term. Forty-three subjects (n = 23 low glycemic index and n = 20 high glycemic index) completed the study. Diets differed significantly in glycemic index (mean ± standard error of the mean, low glycemic index 51 ± 1 vs. high glycemic index 61 ± 2, p = 0.0002), but not in macronutrient distribution or fiber content. Facial acne improved on both diets (low glycemic index −26 ± 6%, p = 0.0004 and high glycemic index −16 ± 7%, p = 0.01), but differences between diets did not reach significance. Change in insulin sensitivity was not different between diets (low glycemic index 0.2 ± 0.1 and high glycemic index 0.1 ± 0.1, p = 0.60) and did not correlate with change in acne severity (Pearson correlation r = −0.196, p = 0.244). Longer time frames, greater reductions in glycemic load or/and weight loss may be necessary to detect improvements in acne among adolescent boys

Demographic and Social-Cognitive Factors Associated with Weight Loss in Overweight, Pre-diabetic Participants of the PREVIEW Study

PurposeWeight loss has been demonstrated to be a successful strategy in diabetes prevention. Although weight loss is greatly influenced by dietary behaviors, social-cognitive factors play an important role in behavioral determination. This study aimed to identify demographic and social-cognitive factors (intention, self-efficacy, outcome expectancies, social support, and motivation with regard to dietary behavior and goal adjustment) associated with weight loss in overweight and obese participants from the PREVIEW study who had pre-diabetes.MethodProspective correlational data from 1973 adult participants were analyzed. The participants completed psychological questionnaires that assessed social-cognitive variables with regard to dietary behavior. Stepwise multiple regression analyses were performed to identify baseline demographic and social-cognitive factors associated with weight loss.ResultsOverall, being male, having a higher baseline BMI, having a higher income, perceiving fewer disadvantages of a healthy diet (outcome expectancies), experiencing less discouragement for healthy eating by family and friends (social support), and lower education were independently linked to greater weight loss. When evaluating females and males separately, education was no longer associated with weight loss.ConclusionThe results indicate that a supportive environment in which family members and friends avoid discouraging healthy eating, with the application of a strategy that uses specific behavior change techniques to emphasize the benefits of outcomes, i.e., the benefits of a healthy diet, may support weight loss efforts. Weight loss programs should therefore always address the social environment of persons who try to lose body weight because family members and friends can be important supporters in reaching a weight loss goal.Peer reviewe

Testing Protein Leverage in Lean Humans: A Randomised Controlled Experimental Study

A significant contributor to the rising rates of human obesity is an increase in energy intake. The ‘protein leverage hypothesis’ proposes that a dominant appetite for protein in conjunction with a decline in the ratio of protein to fat and carbohydrate in the diet drives excess energy intake and could therefore promote the development of obesity. Our aim was to test the ‘protein leverage hypothesis’ in lean humans by disguising the macronutrient composition of foods offered to subjects under ad libitum feeding conditions. Energy intakes and hunger ratings were measured for 22 lean subjects studied over three 4-day periods of in-house dietary manipulation. Subjects were restricted to fixed menus in random order comprising 28 foods designed to be similar in palatability, availability, variety and sensory quality and providing 10%, 15% or 25% energy as protein. Nutrient and energy intake was calculated as the product of the amount of each food eaten and its composition. Lowering the percent protein of the diet from 15% to 10% resulted in higher (+12±4.5%, p = 0.02) total energy intake, predominantly from savoury-flavoured foods available between meals. This increased energy intake was not sufficient to maintain protein intake constant, indicating that protein leverage is incomplete. Urinary urea on the 10% and 15% protein diets did not differ statistically, nor did they differ from habitual values prior to the study. In contrast, increasing protein from 15% to 25% did not alter energy intake. On the fourth day of the trial, however, there was a greater increase in the hunger score between 1–2 h after the 10% protein breakfast versus the 25% protein breakfast (1.6±0.4 vs 25%: 0.5±0.3, p = 0.005). In our study population a change in the nutritional environment that dilutes dietary protein with carbohydrate and fat promotes overconsumption, enhancing the risk for potential weight gain

A Protein Diet Score, Including Plant and Animal Protein, Investigating the Association with HbA1c and eGFR-The PREVIEW Project

Higher-protein diets have been advocated for body-weight regulation for the past few decades. However, the potential health risks of these diets are still uncertain. We aimed to develop a protein score based on the quantity and source of protein, and to examine the association of the score with glycated haemoglobin (HbA1c) and estimated glomerular filtration rate (eGFR). Analyses were based on three population studies included in the PREVIEW project (PREVention of diabetes through lifestyle Intervention and population studies in Europe and around the World): NQplus, Lifelines, and the Young Finns Study. Cross-sectional data from food-frequency questionnaires (n = 76,777 subjects) were used to develop a protein score consisting of two components: 1) percentage of energy from total protein, and 2) plant to animal protein ratio. An inverse association between protein score and HbA1c (slope -0.02 +/- 0.01 mmol/mol, p <0.001) was seen in Lifelines. We found a positive association between the protein score and eGFR in Lifelines (slope 0.17 +/- 0.02 mL/min/1.73 m(2), p <0.0001). Protein scoring might be a useful tool to assess both the effect of quantity and source of protein on health parameters. Further studies are needed to validate this newly developed protein score.Peer reviewe

Objectively Measured Physical Activity and Sedentary Time Are Associated With Cardiometabolic Risk Factors in Adults With Prediabetes: The PREVIEW Study

OBJECTIVE The aim of the present cross-sectional study was to examine the association among physical activity (PA), sedentary time (ST), and cardiometabolic risk in adults with prediabetes.RESEARCH DESIGN AND METHODS Participants (n = 2,326; 25–70 years old, 67% female) from eight countries, with a BMI >25 kg ⋅ m−2 and impaired fasting glucose (5.6–6.9 mmol ⋅ L−1) or impaired glucose tolerance (7.8–11.0 mmol ⋅ L−1 at 2 h), participated. Seven-day accelerometry objectively assessed PA levels and ST.RESULTS Multiple linear regression revealed that moderate-to-vigorous PA (MVPA) was negatively associated with HOMA of insulin resistance (HOMA-IR) (standardized β = −0.078 [95% CI −0.128, −0.027]), waist circumference (WC) (β = −0.177 [−0.122, −0.134]), fasting insulin (β = −0.115 [−0.158, −0.072]), 2-h glucose (β = −0.069 [−0.112, −0.025]), triglycerides (β = −0.091 [−0.138, −0.044]), and CRP (β = −0.086 [−0.127, −0.045]). ST was positively associated with HOMA-IR (β = 0.175 [0.114, 0.236]), WC (β = 0.215 [0.026, 0.131]), fasting insulin (β = 0.155 [0.092, 0.219]), triglycerides (β = 0.106 [0.052, 0.16]), CRP (β = 0.106 [0.39, 0.172]), systolic blood pressure (BP) (β = 0.078 [0.026, 0.131]), and diastolic BP (β = 0.106 [0.39, −0.172]). Associations reported between total PA (counts ⋅ min−1) and all risk factors were comparable or stronger than for MVPA: HOMA-IR (β = −0.151 [−0.194, −0.107]), WC (β = −0.179 [−0.224, −0.134]), fasting insulin (β = −0.139 [−0.183, −0.096]), 2-h glucose (β = −0.088 [−0.131, −0.045]), triglycerides (β = −0.117 [−0.162, −0.071]), and CRP (β = −0.104 [−0.146, −0.062]).CONCLUSIONS In adults with prediabetes, objectively measured PA and ST were associated with cardiometabolic risk markers. Total PA was at least as strongly associated with cardiometabolic risk markers as MVPA, which may imply that the accumulation of total PA over the day is as important as achieving the intensity of MVPA

Socio-economic factors, mood, primary care utilization, and quality of life as predictors of intervention cessation and chronic stress in a type 2 diabetes prevention intervention (PREVIEW Study)

BACKGROUND: Sedentary lifestyle and unhealthy diet combined with overweight are risk factors for type 2 diabetes (T2D). Lifestyle interventions with weight-loss are effective in T2D-prevention, but unsuccessful completion and chronic stress may hinder efficacy. Determinants of chronic stress and premature cessation at the start of the 3-year PREVIEW study were examined. METHODS: Baseline Quality of Life (QoL), social support, primary care utilization, and mood were examined as predictors of intervention cessation and chronic stress for participants aged 25 to 70 with prediabetes (n = 2,220). Moderating effects of sex and socio-economic status (SES) and independence of predictor variables of BMI were tested. RESULTS: Participants with children, women, and higher SES quitted intervention earlier than those without children, lower SES, and men. Lower QoL, lack of family support, and primary care utilization were associated with cessation. Lower QoL and higher mood disturbances were associated with chronic stress. Predictor variables were independent (p ≤ .001) from BMI, but moderated by sex and SES. CONCLUSIONS: Policy-based strategy in public health should consider how preventive interventions may better accommodate different individual states and life situations, which could influence intervention completion. Intervention designs should enable in-built flexibility in delivery enabling response to individual needs. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01777893.publishersversionpublishe