Lentil Consumption and Post-Prandial Glycemic Response: Evaluation G. Harvey Anderson University of Toronto
Lentil Consumption and Post-Prandial Glycemic Response: Research Guidance Need to agree on design and methods for post-prandial glycemic response claims of whole foods and of foods in meals as commonly consumed. HC guidelines does not address. Is a meta-analysis the right approach for function claims? Do function claims need the same standards of evidence as disease risk reduction claims? The quality appraisal tool excludes studies that provide answers to the limitations in the selected studies. The document does not capture the totality of evidence. Quantitative measures of highly variable parameters may lead companies to claims easily challenged. Legal issue.
The Questions Level of comfort that lentils lower glycemic response? Moderate for acute servings, but low for within meals. Level of comfort that lentils lower (or don t raise) insulin response? Uncertain. Research gaps? Yes. None of the studies designed to answer the question w.r.t. structure-function as outlined by HC or based on quality appraisal tool. Bread, a flour-based food, used as the control not a whole food. Are discussions and conclusions in the literature review well done? Need more on totality of evidence. Need more on the physiology of glucose control by foods. Does the lower glycemic response of lentils have anything to do with the CHO? Some contradictions in logic. Sample size for satiety and food intake is 25+; according to GI experts, 10 enough for glucose. Mollard et al. mixed meal study negative results dismissed due to sample size (n=25!) Does the literature review support a function claim? Not if one considers the recent HC Draft Guidelines. Yes, if one considers that totality of evidence and not only quantitative ratings of the included studies.
Overview of Health Canada s Draft Guidance Document on Food Health Claims Related to the Reduction in Post-Prandial Glycaemic Response PFSNRA Scientific-Technical Committee Meeting August 13, 2013 Maria Fernanda Nunez Harvey Anderson
Summary of HC Guidelines Reduction in post-prandial glycaemic (PPG) response claims are considered function claims concerning a food s acute effect on PPG within normal physiological ranges Characterization of the food Added food ingredients, substitution of ingredients, foods with multiple compositional changes, foods with inherent properties Characterization of the health effect BG concentrations at specific/various time points over 2 h following intake of the test food vs. reference food; Similar to EFSA for food but EFSA has post-prandial glycemic response for meals. Substantiation of PPG claims Test food should result in 20% in iauc vs. reference food (physiologically relevant) PPG must not be accompanied by disproportionately insulin iauc
Measuring PPG Response: Characterization of the Food Explicit claims about effects on PPG should sufficiently characterize the test and reference foods (e.g. physical properties, nutrient composition) while taking into account the amount likely to be consumed at one sitting Must be consistent with serving size and intended pattern of consumption (e.g. snack vs. meal); consumed as typically prepared Similar considerations as HC s satiety claims draft guidance (Sept 2012)
Measuring PPG Response: Characterization of the Food Addition of ingredients Substitution of ingredients Foods with multiple compositional changes Foods with inherent properties Test Food Reference Food Type of Claim E.g. Dietary fibre added to CHO-containing foods E.g. Total or partial substitution of non/lowdigestible CHO for highly digestible CHO E.g. Combination of addition + substitution of one or more ingredients E.g. Slow vs. fast rate of digestion Food without the added ingredient Food without substitution Similar food with different compositional characteristics Test food must be in the same food category or serve a similar dietary role as the reference food with equal or lower amounts of available CHO per serving Non-comparative. E.g. [A serving of stated size] of [name of product X] contains n grams of [name of ingredient Y]. This ingredient reduces the glycaemic response to this food Non-comparative. E.g. [Ingredient A] is replaced with [ingredient B] in [name of product]. This substitution results in a lower blood glucose/blood sugar rise Comparative. E.g. (A serving of stated size) of [name of product] results in a lower glycaemic response compared to (a serving of stated size) of [name of reference food] Comparative. E.g. (A serving of stated size) of [name of food A] results in a lower glycaemic response compared to (a serving of stated size) of [name of food B.]
Test/reference foods Draft Guidelines: Questions What standards should be used to determine serving size? Should it based on typical consumption patterns obtained from survey data or are there existing standard serving sizes that should be referenced? Weekly vs. daily consumption? Time of day? For claims on foods with added ingredients, it is unclear how studies should be conducted to substantiate claims for an ingredient. Can results obtained in test foods (e.g. muffins) be extrapolated to a broader category, such as baked goods, or must studies be performed for the specific foods bearing the claim? Will claims on mixed meal products be possible? If adding a caloric ingredient, will it be acceptable for the test and reference foods not to be isocaloric? What other factors should be matched?
Draft Guidelines: Questions Methodology Sample size? Reproducibility Is insulin a required measure? EFSA yes What is a disproportionate increase in insulin?
Lentils and Post-Prandial Glycemia Overall it is concluded that the qualifying studies indicate yes. Consistency of response: Glucose AUC 9/11=yes. Sample sizes are small in most studies (e.g. 6) Three of 12 experiments are of meal size of approximately 600 kcal. Other are 250-400 kcal. Are conclusions different? Only one studied a mixed meal. Collier et al. (AJCN, 1986) concluded meal vs. servings make a difference. No study adjusted for macronutrients except one. Confounders not considered in most studies authors of report conclude they were. Is white bread the right comparison food? Comparing a whole pulse with refined flour but should it be boiled whole wheat? Akhtar et al. (Nutr. Res., 1987) added fried egg and milk to control (bread) and milk was added to all treatments. What is the effect of protein? Jenkins et al. (BMJ, 1980). Exceptionally low blood glucose response to dried beans. Used boiled grains and pulses in comparison. (50g CHO)
Blood Glucose Response to Traditional Pakistani Dishes (Akhtar et al, Nutr. Res. 1987) Control (BE): Bread (111g), Egg and Ghee (45g), Milk (250ml) Total CHO=64g, Protein=32g Lentils (RL): Rice (43g), Lentils (89g), Milk (250ml) Total CHO=64g, Protein=38g Lentils (BL): Bread (55g), Lentils (89g), Milk (250 ml) Total CHO=64g, Protein=42g Subjects=14. Seven test meals. Great variation in fat and protein content. Measure: Glucose netauc to 120 min. Is bread the right control? BE=100. RL=67, BL=45 not different from each other. Conclusion: Meals containing legumes may be of use in dietary treatment of diabetes.
Milk and Blood Glucose Control Treatment (25g CHO) Glycemic Index Insulin Index W. Bread 100 a 100 a Lactose 68±8 b 50±6 b Whole Milk (500 ml) 30±4 c 90±8 a Ostman EM et al, AJCN 2001, 74:96-100
Blood Glucose Response to Traditional Pakistani Dishes (Akhtar et al., Nutr. Res. 1987)
Meal Studies: Nutritional Composition of Treatments Meals Treatments Macaroni and cheese Macaroni and Chickpea Macaroni and Lentil Macaroni and Yellow Pea Energy (kcal) 604.1 603.2 597.3 595.7 Weight (g) 446.5 757.7 756.2 762.1 Energy Density (kcal/g) 1.4 0.8 0.8 0.8 Volume (ml) 650 850 850 850 Available Carbohydrate (g) 100.4 98.7 103.2 103.5 Fibre (g) 2.8 18.3 18.7 14.1 Protein (g) 22.8 26.1 29.1 28.3 Fat (g) 12.6 12.5 8.7 8.5 Mollard et al. APNM 2011. Pulse additions 40% of energy in meal
Treatment (600 kcal) Pre-pizza. BG AUC 2 (260 min) (mmol min/l) Cumulative Pre-meal Post-meal Macaroni and Cheese Chickpea Lentils Yellow Pea 431.3 298.1 ± 25.3 a ± 17.8 344.5 232.0 ± 32.0 b ± 22.7 392.9 276.8 ± 32.7 ab ± 28.3 367.3 239.5 ± 30.5 ab ± 22.5 105.6 ± 15.3 ab 90.0 ± 10.8 b 85.6 ± 10.6 b 125.9 ± 11.2 a P 0.02 0.07 0.002
Blood Glucose Response to Fixed (600kcal) Pulse Meals Before and and after Pizza Meal-ad lib. (n=25)
Pulse Study: Meals to Satiation BJN 2012
Do Lentils Lower Insulin? Krezowski et al., 1987. Insulin and Glucose Responses to Various Types of Starch Containing Foods in Type II diabetic subjects. N=8 men. CHO 50g. Glucose, bread, potato, oatmeal, rice, kidney beans, lentils. Glucose was lower after lentils than after bread, oatmeal, rice and potatoes. Insulin was similar for potatoes, bread and rice, but highest after oatmeal and lowest after lentils and beans. The observed insulin response was significantly greater than the predicted based on the glucose rise. These results indicate that insulin cannot be predicted from the glucose response. Inappropriate stats applied in this study. Collier et al., 1984. Effect of Co-ingestion of Fat on the Metabolic Responses to Slowly and Rapidly Absorbed Carbohydrates. N=7 men. Dose 75 g CHO from lentils or potatoes with or without fat (37.5g). Lower post-prandial glucose after lentils and with fat additions. Lower insulin after lentils but insulin potentiated by fat.
Pasta meals 600 kcal, 40% of calories from pulses. N=14, young men
Is the Glycemic Effect of Lentils Lost when Powdered? Acute Effects of Commercially Processed Navy Bean, Lentil and Chickpea Powders on Glycaemic Response and Subjective Appetite
Study Design Summary Experiment 1 Navy beans Experiment 2 Lentils Experiment 3 Chickpeas Within-subject, randomized, single-blind and repeated-measures design Whole Canned Pulses Foods? Healthy Men Age: 18-30 years BMI: 20-25 kg/m Pureed Canned Pulses Pulse Powder Foods? Whole Wheat Flour (Control) Standardized for available carbohydrate (25g from pulses or whole wheat), sodium and weight
Experiment 2: Lentils Blood Glucose Time P< 0.0001,Trt P= 0.0001,Time*Trt P=0.0008 Time P< 0.0001,Trt P= 0.645,Time*Trt P=0.438 Mean ± SEM, n = 12. Two-way ANOVA with Tukey s post-hoc test. Values with different superscripts are significantly different, P < 0.05 23
The Questions Level of comfort that lentils lower glycemic response? Moderate for acute servings, but low within meals. Level of comfort that lentils lower (or don t raise) insulin response? Uncertain. Research gaps? Yes. None of the studies designed to answer the question w.r.t. to structure-function as outlined by HC or based on quality appraisal tool. Bread, a flour-based food, used as the control not a whole food. Are discussions and conclusions in the literature review well done? Need more on totality of evidence. Need more on the physiology of glucose control by foods. Does the lower glycemic response of lentils have anything to do with the CHO? Some contradictions in logic. Sample size for satiety and food intake is 25+; according to GI experts, 10 enough for glucose. Mollard et al. mixed meal study negative results dismissed due to sample size (n=25!). Does the literature review support a function claim? Not if one considers the recent HC Draft Guidelines. Yes, if one considers that totality of evidence and not quantitative ratings.
Lentil Consumption and Post-Prandial Glycemic Response: Research Guidance Need to agree on design and methods for post prandial glycemia claims of whole foods and of foods in meals as commonly consumed. Studies to confirm insulin response would be useful. Is a meta-analysis the right approach for function claims? Do function claims need the same standards of evidence as disease risk reduction claims? The quality appraisal tool excludes answers to many limitations in the selected studies. The document does not capture the totality of evidence. Quantitative measures of highly variable parameters may lead companies to claims easily challenged. Legal issue.
Consumer attitudes and misconceptions of sodium claims on food labels PFSNRA Technical Meeting Aug 13, 2013 Christina L. Wong, MSc 1 Co-authors: JoAnne Arcand 1, Julio Mendoza 3, Ying Qi 2, Mary R. L'Abbé 1 1. Department Nutritional Sciences, University of Toronto, Canada 2. Dalla Lana School of Public Health, University of Toronto, Canada, 3. Food, Agricultural and Resource Economics, University of Guelph, Canada
Mock Package Experiment: Testing Sodium Claims 1) 2) 3) 4)
Mean Rating How healthy do you think this food is for you? Effect of claim type = p <0.0001 Mean ± SEM Wong et al. Am J Clin Nutr. 2013, 97(6):1288-98
Conclusions and Implications Any sodium claim resulted in more positive attitudes compared to control Nutrient content vs. Disease risk reduction Attributed additional health benefits to products with sodium claims beyond hypertension
Overall Conclusion There is a totality of evidence to support a generic claim for benefits of lentils in post-prandial glucose control relative to other carbohydrate foods. In meals, lentils reduce food intake, an added factor in reducing post-meal glycemia (e.g. Mollard et al., BJN 2012) Research should focus on ways to incorporate lentil powders in commonly consumed foods and meals. Effective communication to consumers a challenge.
Thank You Bohdan Luhovyy, Rebecca Mollard, Chris Smith, Maria Fernanda Nunez and many more Financial and in-kind support: