7 New approaches to providing nutritional information J. A. Monro, New Zealand Institute for Crop & Food Research 7.1 Introduction Both food processors and consumers have a basic need for valid and relevant nutritional information; on the one hand to guide production and marketing of genuinely functional products, and on the other to allow selection of products according to efficacy. Data on product efficacy that are relevant, in the sense of being easily communicated, understood and appropriately applied are, however, often unavailable. There is little to guide evidence-based food choice to meet such widespread health challenges as control of blood glucose levels, and maintenance of large bowel function, two examples that will be considered in detail in this chapter. New approaches to nutritional information must, therefore, focus not only on data that validly represent physiological changes linked to health, but also on transforming the data to show meaningfully the relative efficacy with which prod- ucts can bring about change. This chapter focuses on new approaches to nutri- tional information that attempt to link food choice to health end-points through effective communication. 7.2 Why food processors need new types of nutritional information Food processing has been shown to have large effects on a range of nutritional properties. 1 Changes in macronutrients, such as starch and protein, 2,3 and the destruction of vitamins during food processing, 4 have been well documented, and are updated in this book. Most studies have been constrained by experimental design to a few foods and conditions, and apart from effects on nutrient levels measured in standard food analyses, nutritional information that reflects the effects of processing does not generally reach consumers in a form in which it can be widely used to choose foods. Similarly, food processors often do not have available means to apply, either accurately or practically, relevant nutritional criteria to select prototype products during development. Below are listed several reasons for the need for new nutritional information. 7.2.1 Showing effects of food properties on nutritional qualities Much of the impact of processing on nutritional quality comes about through changes in physicochemical properties of food polymers, such as dietary fibre, 5 that cannot be represented by food composition values. Changes in structure asso- ciated with such processes as starch hydration and gelatinisation, 6 milling, 7 and extrusion, 8 can have an large impact on the rate and extent of digestion, and consequently on a range of physiological markers linked to disease end-points. For example, the impact of cereals on blood glucose and insulin responses is increased markedly as particle size is reduced by milling, 7 or as starch is gelatinised. 6,9 7.2.2 Tracking changes in nutritional quality Information from rapid, valid, but relevant tests is needed to guide processing to healthy products. Because of the expense, time, ethics, compliance and other issues involved in clinical trials, human subjects are not usually suitable for mon- itoring effects of processing until potential products have been identified. Food processing for improved nutrition may require pragmatic choice of dif- ferent tests at different stages in product development, to maintain momentum in product development. Active ingredients and formulations may be identified with screening tests, using indirect predictors of health effects, such as ingredient prop- erties. Responses in animal models may guide food processing further, and most promising products then taken into clinical trials, in which effects on biomarkers with established links to health end-points are measured, 10,11 before a claim of efficacy is made. Increasing rigour in nutritional evaluation of functional prop- erties during the course of product development is illustrated in Table 7.1. As a general principle, the properties of foods that affect physiology should be measured under conditions as close as is reasonable to those in which the food property acts in vivo. Developing a soluble fibre-enriched product to lower blood cholesterol is an example. Ingredients of high soluble fibre content could be iden- tified using soluble fibre analysis under simulated gastrointestinal conditions. 12 As hypocholesterolaemic effects of soluble dietary fibres result from increased intestinal viscosity, 13 fibre viscosity should be measured, followed by in vitro digestion of products containing selections of viscous fibre sources, with mea- surement of digesta viscosity. Promising products could be subjected to animal trials to establish that predicted gut viscosity and blood lipid changes occur 166 The nutrition handbook for food processors in vivo. Final selections could then be clinically evaluated, to establish firmly their potential as functional foods for humans. 7.2.3 Avoiding unjustified extrapolation between products The complexity of processing effects on food matrices makes nutritional proper- ties susceptible to processing conditions, and extrapolation of function between different products uncertain. 14 Nonetheless, it is a common cost-cutting measure for marketers to use a functional effect of a bioactive in one product, to promote other foods containing the bioactive, but with a different processing history. To reduce unjustified extrapolation, information is required from tests that are prac- tical and inexpensive enough to use for detecting nutritional effects of different processing conditions in large numbers of samples. New approaches to providing nutritional information 167 Table 7.1 Types of nutritional tests that may be used in food processing at different stages of product development Level of Use in food processing Comments evidence Ingredient Identifying ingredients May change in processing. Affected by properties with desired properties. food matrix and gut milieu. Cheap and quick. Food Defining nutrient retention. Ignores physiochemical properties, composition Meeting labeling bioavailability, and bioactivity, but requirements. relatively cheap. In vitro Predicting responses to gut May give an indication of effects of digestion conditions. digestion on food properties, but not take other important food-host interactions into account. Animal Predicting effects in the May be physiologically different to models whole body context. humans. Require validation. Compliance good. Human Usually limited application Costly, slow, ethically difficult, study studies 95 until nearing final product. population variable, compliance may be poor. Intermediate endpoints required. Epidemiology Identifies possible health- Associations identified, but not cause- relevant food factors. effect relationship (uncertain). Ecologically valid. Not suitable for product testing. Case-control Identifying possible food Less controlled than experimental factors in health by methods leaving room for doubt about association. cause-effect. Experimental Provides basis for a health Most rigorous, but findings apply to the claim. experimental conditions – may lack external validity. 7.2.4 Helping consumers choose foods for health Food properties can be used to select foods for health only if supported by useable efficacy data. 15 Information from tests of the nutritional and functional properties of foods needs to be easily used by both processors and consumers, to discrimi- nate between products. Without scientific but communicable efficacy data, food processors cannot develop or ethically promote foods, and consumers cannot choose foods for real health effects. 7.2.5 Gaining consumer confidence Consumer confidence in a product or company requires that claimed benefits are delivered. Distrust is associated with perceptions of deliberate distortion of infor- mation, and having been proven wrong in the past. 16 Therefore, the more that the benefits of a food product are exaggerated and overextrapolated, while scrutiny by food regulators and nutritionists continues, the greater the likelihood of gen- erating mistrust. Investment in tests to demonstrate real differences in efficacy of products is, therefore, a prudent strategy. 7.3 Limitations of food composition data in food processing A number of related reasons why simple direct relationships between constituent levels in foods and effects on health cannot be assumed are outlined below. 7.3.1 People eating foods are complex systems consuming complex systems Food composition data are obtained from standardised analyses of discrete nutri- ents, whereas the nutritional effects of food components are modulated by mul- tiple interactions within the food matrix, 17 within the gut, 18 and within the body after absorption. 19 Effects of nutrients in foods are, therefore, seldom the same when consumed in a food, as they would be if consumed as a pure nutrient. Yet, food composition is often used as a measure of ‘nutritional quality’, and nutrient information panels have been the consumers’ main guide to healthy food selec- tion. The ability to make informed food choices for health has therefore been quite restricted. 7.3.2 Analytical data may not reflect bioactivity 20 Bioactivity is determined by response of the body to food. Several metabolic steps may converge to contribute more to a response than might be expected from amounts of a single active component in a food. For instance, vitamin A acti- vity may be obtained not only from vitamin A as retinal, but also from a range of provitamin A carotenoid precursors. 21 Therefore, analytical methods must 168 The nutrition handbook for food processors measure not only vitamin A in a food, but also carotenoids with the potential for conversion to active vitamin A, as vitamin A equivalents. Similarly, blood lipid is a biomarker that depends on more than dietary lipids as lipid type and carbo- hydrate intake, for instance, may also affect blood lipids. 22 7.3.3 Availability or extraction in analytical systems may not equate with bioavailability 23 Analyses are usually designed to measure all of a component of interest in a food, rather than the bioavailable fraction. Most samples are finely ground to facilitate complete extraction with an effective solvent. 24 As a result, food components may be much more soluble during food analysis than during digestion in the gut. Soluble dietary fibre is a good example; as prescribed in the American Associa- tion of Analytical Chemists method for soluble fibre analysis, 25 food samples must be finely ground and extracted in hot buffer at 100 °C, whereas in the gut extrac- tion is normally at 36.4 °C, from a mixture of particles. Soluble fibre extraction in gut conditions may therefore be much less than in fibre analysis. 26 7.3.4 Physiological effects of food constituents depend on prior physiological state The effects of food constituents are emergent consequences of the interaction between food and body, and subject to the existing physiological state. A viscous polysaccharide may, for instance, lower blood cholesterol in subjects with hyper- cholesterolaemia, with much less effect in normals. 27 Similarly, the impact of a food carbohydrate on blood glucose levels is affected by the capacity of the body’s cells to absorb glucose, which may be affected by insulin release, by sensitivity to insulin, and by the state of muscle glycogen reserves as a result of exercise. 28 The body may modulate uptake and utilisation of a nutrient in response to nutrient status; iron uptake is increased in states of iron deficiency, 29 and vitamin C is excreted when uptake exceeds requirements. 30 7.3.5 A single analytical value may represent a group of compounds differing in nutritional properties Physiological effects often depend on physicochemical properties that vary within a food constituent class that is represented by a single analytical value. Total dietary fibre as a single value in a food table is a family of compounds of diverse form, physicochemical properties, and physiological effects. 31 Dietary fibres exist as insoluble faecal bulking materials, such as wheat bran, that have little impact on blood cholesterol, 32 or as viscous, fermentable, cholesterol-lowering polysaccharides, such as guar gum, 33 that have relatively little impact on faecal bulk. 34 New approaches to providing nutritional information 169 7.3.6 Food matrix properties may strongly modulate nutritional effects 35 Food processing may give products of the same composition, with markedly different physiological effects, because of differences in structure and physico- chemical properties. For instance, digestion in a porous starch-protein matrix in the form of bread takes place much more rapidly than in a solid, non-porous matrix of similar composition, in the form of pasta or whole kernels, which con- sequently have less impact on blood glucose levels. 36,37 7.4 Foundations for practical nutritional information Several characteristics of nutritional information for evidence-based food choices for health, are summarized below and will be illustrated with reference to data sets for managing blood glucose (Table 7.2) and large bowel function respec- tively (Table 7.3). In a nutshell, health end-points need to be selected, markers 170 The nutrition handbook for food processors Table 7.2 Developing nutritional data sets related to health end-points associated with elevated blood glucose Consideration Relevance to blood glucose End-points Disorders from glycation and glycaemia, including vascular disease of retina, kidneys, nerves. Heart disease. Polyuria. Intermediate Postprandial glycaemic response: blood glucose elevation underlies end-point or many long term complications of diabetes mellitus, involving marker of hyperinsulinaemia and glycation. effect Currently Sugars and available carbohydrate: not dependable indicators of blood used indices glucose response, which depends on digestion rate of available carbohydrates and on their monosaccharide composition. Glycaemic index (GI): A percentage based on glycaemic response to food carbohydrate compared with response to glucose. Use restricted to equicarbohydrate comparisons and does not respond to food intake. Not useful for accurate blood glucose control. Relevant Relative glycaemic potency (RGP): 58 A percentage based on index comparison of food with glucose. RGP ranks whole foods by their glycaemic impact on an equal weight basis, but does not respond to food intake. Suitable for food comparisons on an equal weight basis. Practical Glycaemic glucose equivalents (GGE): 44 Derived from RGP. A units measure of glycaemic impact based on foods. Responsive to food quantity. Useful for communicating efficacy. Can be applied to food items of any weight. Validation Clinical measurements have shown that GGE intake predicts glycaemic response to foods of different GI, carbohydrate content, and intake at carbohydrate doses consumed in most meals. 61 identified that can be causally linked to the end-points, valid indicator variables that predict changes in markers identified for practical tests, and measurements communicated so they can be easily understood. 7.4.1 End-points that are important to well-being A number of health and disease end-points, affecting a large proportion of the population, need to be addressed in developing healthy foods. Some, such as car- diovascular disease, colorectal cancer, osteoporosis, and constipation are associ- ated with a combination of ageing and unhealthy dietary patterns. Others, such as obesity, are largely the result of food processors and marketers successfully providing foods that appeal to the basic human preferences for sweetness and fats, in all age groups. It would be best to design foods with a number of end- points in mind, and evaluate them with a battery of tests to demonstrate nutri- tional balance. Producing foods for specific functions or using foods as medicines risks unbalanced nutrient intake. 7.4.2 Biomarkers that are relevant 38 To be health-relevant and useable, food information needs to relate to practically measurable but valid markers linked to health end-points, 10,38 such as blood cho- lesterol in relation to cardiovascular disease, 39 or alterations in faecal components New approaches to providing nutritional information 171 Table 7.3 Developing nutritional data sets related to health end-points associated with insufficient faecal bulk Consideration Relevance to faecal bulk End-points Various large bowel disorders including constipation, diverticulosis, colorectal cancer. Intermediate Faecal mass, representing distal colonic bulk. end-point or biomarker Currently used Dietary fibre: does not reliably predict faecal bulk because bulking index effects depend on fermentability, water holding capacity and bacterial growth. Relevant index Faecal bulking index (FBI): 34 The impact of a whole food on faecal bulk as a percentage of the effect of an equal weight of wheat bran. Usable for measuring efficacy on an equal weight basis. Practical units Wheat bran equivalents (WBE fb ): 42 Expressed as a content in foods. May be used to communicate relative efficacy. Applicable to food items of any weight. Validation Faecal bulking response measured as mass of rat faecal pellets after hydration closely reflects response in humans. 85 in relation to colon cancer, 40 and to be obtained with standardised procedures that can be applied to a wide enough range of foods for comparisons to be made. Biomarkers are required because human death, disease and sub-optimal health are not permissible dependent variables, and many are the result of cumulative changes over long periods. Instead, intermediate biomarker ‘end-points’, markers of exposure to a food component, and food properties that research has already established as causal in disease and health must be used to assess health effects of food processing. Intermediate end-points must be either causal factors or correlated with changes that lead to end-points. For instance, hyperlipidaemia is an intermediate biomarker that is causally related to a true end-point – atherosclerosis. 39 However, as many factors are involved, evidence for the benefit of a product would be more convincing if several relevant biomarkers were measured. At present most biomarkers require clinical or laboratory mea- surement and are not widely used to monitor nutritional changes in the course of product development. A good deal of further work is required to develop tests that are useful to industry. 7.4.3 Validity that is balanced with practicality Validation is a crucial step in selecting variables that indicate effects of foods and food processes on biochemical precursors of health end-points. Because most foods are complex systems, ideal experimental trials in which one food factor is varied while all other variables are kept constant are not often possible, and there is a need to balance practical requirements of food processing with degree of nutritional validation. Given that final products should be comprehensively eval- uated, progress in food processing will often best be maintained by being pre- pared to sacrifice some degree of validity for expediency by appropriate choice of tests, as discussed in section 7.2.3 and illustrated in Table 7.1. 7.4.4 Nutrition information that is up-to-date Nutrition science is constantly advancing, and as hard data throws new light on the relationship between a food property or component and a health end-point, indices of food effects on health are likely to change. For instance, heart disease is now considered to be influenced less by intake of fat than by intake of specific fatty acids such as saturated and trans-fatty acids. 41 Such changes are not a sign that nutrition science cannot be relied on but that continuing research leads to clarification. A food company that had not kept abreast of nutritional knowledge recently formulated a new ‘diabetic muesli bar’, replacing all sucrose sources with dex- trins, in the belief that ‘sugar’ replacement would improve blood glucose control. However, such wisdom was obsolete, because sucrose, being half fructose, induces a much lower blood glucose response than dextrins, which are rapidly digested glucose polymers. The new ‘diabetic’ bar had a greater glycaemic impact than the unmodified version. 172 The nutrition handbook for food processors 7.4.5 Relevant indices that are based on factors that confer relevance on food data The relevance of food information is determined by validity, sufficiency, practi- cality, and communicability. Is an index a true reflection of a change in a bio- marker or end-point, is it sufficient on its own to predict a change in the end-point, is it a variable that can be measured easily, and expressed in terms that users understand well enough to use in food choice? 7.4.6 Food data that is easily understood Food data is not relevant if it cannot accurately link consumer behaviour to health end-points, in other words, if it cannot guide food choice for health. To do so it should be easily used. The relative efficacy of foods may, for instance, be expressed in terms of equivalents to a familiar reference that exhibits a specified effect to a known degree, as in wheat bran equivalents and faecal bulking. 42 Gly- caemic index (GI), on the other hand, is an example of a number that is supposed to represent the glycaemic potency of a food. 43 However, unlike intake of a nutri- ent, GI does not change with the composition, serving size, or intake of food, so it makes little sense to consumers, and cannot be used accurately to modify eating patterns that affect blood glucose. 44 7.5 Limitations of food composition data: the case of carbohydrates The above framework for building practical, evidence-based data sets linked to health end-points is illustrated below by reference to two physiological effects of food carbohydrates: postprandial glycaemia (post-meal elevation of blood glucose), and faecal bulking. Postprandial glycaemia is determined largely by carbohydrate digestibility, 45 and faecal bulk largely by non-digestible, non- fermentable polysaccharides. 46 7.5.1 Limitations of carbohydrate composition data Standard food analyses do not account for the large effects of the structure of car- bohydrate molecules and foods in the carbohydrate nutrition. Monosaccharide composition and order, glycosidic bonds, degree of polymerisation, chain con- figurations, non-covalent interactions between chains, and crosslinks that carbo- hydrates readily form may all greatly affect physicochemical properties, 6,47 and the physiological effects that depend on such properties. Furthermore, food struc- ture, such as particle size, may considerably modulate the ability of food carbo- hydrates to express their potential properties, 35 by limiting solubility, extraction, and access of digestive enzymes. Beyond effects on extraction, interactions between carbohydrates and other food components in the intestine are multiple and complex. 18 The amounts of carbohydrate fractions in foods are therefore not usually reliable guides to their physiological effectiveness. 33,48 New approaches to providing nutritional information 173 Postprandial glycaemia and distal colonic bulk are both physiological markers that are strongly influenced by the effects of food properties on carbohydrate availability, but which cannot be reliably predicted from food composition data. New nutritional information is required for control of postprandial glycaemia (Table 7.2) and distal colonic bulk (Table 7.3), taking into account end-points, biomarkers of exposure, current indices, relevant indices, their validation, and communication discussed above. 7.6 Relative glycaemic potency and glycaemic-glucose equivalents Control of postprandial glycaemia – the blood glucose response to food intake – is an increasingly important health issue. Diabetes mellitus, marked by an inabil- ity to control blood glucose levels, is increasing rapidly in many developed countries, in which an over-supply of high energy and highly digestible carbo- hydrate foods is coupled with predisposing factors, including physical inactivity, obesity, and inheritance. 28 Many consumers need to be able to manage postpran- dial glycaemia by selecting foods and food combinations according to glycaemic impact, but food labels at present give them little assistance. 7.6.1 End-point Health consequences of hyperglycaemia are multiple and most evident in the diabetes mellitus syndrome. 28,49,50 Persistently raised blood glucose causes protein glycation throughout the body, leading to cumulative, diffuse damage, emerging as pathology in a number of organ systems. Basal membrane damage is com- monly an underlying factor in changes to micro-vessels involving the eyes, kidneys and nerves. 51 Intense insulin production in response to diabetic hyper- glycaemia, or to repeated acute glucose loading from large intakes of highly digestible carbohydrate, is thought to contribute to the progression of glucose intolerance, through b-cell toxicity, leading to loss of the capacity of the pancreas to produce insulin. 52 Hyperinsulinaemia as a response to elevated blood glucose favours elevated blood lipids, obesity and hypertension, all risk factors in heart disease. 49,50,51 Post-prandial glycaemia may also lead to a number of acute and sometimes serious disorders, as the body attempts to counter the osmotic effects of high blood sugar levels. The excretion of sugar by the kidneys leads to water loss, excessive thirst, and in extreme cases, to fatal electrolyte imbalances. 53 7.6.2 Markers As blood glucose response is causal in glycation, insulin response, osmotic effects and other aspects of diabetic pathology, it is a highly relevant marker of the influence of foods and carbohydrates on progression towards disease end-points 174 The nutrition handbook for food processors related to diabetes. Indeed, persistent elevation of blood glucose is clinically a defining feature of diabetes mellitus. 7.6.3 Current indices Glycaemic carbohydrate components most commonly seen on food labels are ‘carbohydrate’, ‘available carbohydrate’, ‘complex carbohydrate’ (starch), and ‘sugars’. One of the main reasons for distinguishing between sugars and complex carbohydrates is the once-held belief that sugars have a more acute impact on blood glucose levels than starch. However, some starches are so rapidly digested that they induce a blood glucose response similar to that of pure glucose. For instance, starch in rice bubbles has a glycaemic index (GI) of 97 (gives 97% of the response to an equicarbohydrate dose of glucose) and baked potato a GI of 85, whereas starch in noodles has a GI of 46. 54 The relative amounts of sugar versus complex carbohydrate in a food is not, therefore, a reliable guide to its impact on blood glucose. Sugar type is another reason that ‘sugar’ content does not indicate glycaemic effect. Sucrose (‘cane sugar’) for instance has a GI of 61 because it is a disac- charide containing a fructose (GI = 23) and a glucose (GI = 100) unit. 55 While dietary sugars include sucrose, lactose, fructose, glucose, and other mono- and disaccharides, ‘blood sugar’ is blood glucose. GI is now being used to classify and promote foods by glycaemic impact. The GI of a food is the incremental effect of carbohydrate in a food on blood glucose, as a percentage of the effect of an equal weight of glucose. It is usually based on the glycaemic effect of enough food to provide a 50 g dose of carbohydrate, compared with the effect of 50 g glucose, or its carbohydrate equivalent in white bread, as the reference. [7.1] The glycaemic index was devised to take account of the relative differences in the impact of food carbohydrates on blood glucose resulting from the types of carbohydrate and their rates of digestion. 43 Two intrinsic characteristics of GI make it difficult to use alone in accurate blood glucose management. Firstly, because GI is based on an equicarbohydrate comparison it should be used to compare foods only at equal carbohydrate doses whereas most foods differ enormously in available carbohydrate content. It is often incorrectly stated that GI ranks foods according to their impact on blood glucose, 56 but it ranks carbohydrates in food, not foods, and ranks foods only if they contain equal amounts of carbohydrate. Secondly, as a percentage, GI does not change with food quantity, so cannot be used to predict relative gly- caemic responses to servings or intakes of food. It is an example of an impracti- cal index. GI Blood glucose increment due to Blood glucose increment due to 50g glucose =￥ 50 g carbohydrate in a food 100 New approaches to providing nutritional information 175 7.6.4 Relevant indices To overcome the limitations of GI, a food-based ‘GI’, termed Relative Glycaemic Potency (RGP), was calculated, and defined as the theoretical response to 50 g of a food as a percentage of the response to 50 g glucose: 57,58 [7.2] RGP is simply GI adjusted for the carbohydrate content of a food (%CHO), and it allows a comparison of foods, rather than food carbohydrates, on an equal weight basis. Adjustment for the carbohydrate content of a food results in a com- pletely different ranking of foods than is obtained with GI, as shown in Table 7.4. 7.6.5 Practical units Because they are based on whole foods, RGP values can easily be expressed as practical units that are related to food intakes. RGP is a percentage of the effect of glucose, so the RGP of a food can be regarded as the amount of glucose that would be equivalent to 100 g of the food in its glycaemic impact. In other words, an RGP 30 can be expressed as 30 glycaemic glucose equivalents (GGE) per 100 g food: RGP Blood glucose increment due to Blood glucose increment due 50g glucose =￥ 50 g food 100 176 The nutrition handbook for food processors Table 7.4 Foods within food groupings ranked by glycaemic index (GI), with corre- sponding values for glycaemic glucose equivalents (GGE) per common standard measure (CSM), and GGE per 100 g (RGP). 44 Rankings by GI did not similarly rank either RGP or GGE/CSM, showing that GI does not rank foods by glycaemic impact Food grouping Nature of CSM %CHO GI Glycaemic impact CSM wt(g) RGP GGE/CSM Bakery products Doughnut ring doughnut 42 44 76 33 14 Bagels, plain bagel 74 47 72 33.8 25 Bread, roll, white, soft roll 51 49 70 34.3 17.5 Bread, white, sliced med slice 26 43 70 30.1 7.8 Bread, wholemeal med slice 28 37 69 25.5 7.1 Croissants small 57 39 67 26.1 14.9 Crispbread, rye biscuit 6 64 65 41.6 2.5 Biscuit, digestive biscuit 14 63 58 37 5 Cake, sponge slice 89 60 46 28 25 Bread, multigrain ‘heavy’ med slice 28 37 52 19.2 5.4 Breakfast cereals Puffed rice cup 14 78 89 69 10 Corn flakes, Kelloggs serving 30 85 84 71.4 21.4 Wheat, puffed cup 14 64 74 47.4 6.6 Wheat biscuit, ‘Weet-Bix’ biscuit 15 62 70 43.4 6.5 Porridge, prepd. (milk & w) cup 260 10.5 61 6.4 16.7 Muesli, non toasted cup 107 57 56 32 31.9 Muesli, toasted, sweet cup 110 53 43 22.8 25.1 [7.3] [7.4] The number of GGEs donated by a food item or meal may be termed its relative glycemic impact (RGI): RGI = GGE intake at a time [7.5] [7.6] [7.7] Glycaemic impact (RGI), as GGE intake, then becomes a function, not of GI alone, but of GI, carbohydrate content, and serving size or food intake, so it takes into account all of the factors determining the RGI of a food, and gives freedom from the equicarbohydrate limitation of GI. The term ‘glycaemic loading’ is similar to RGI, but has been used in epidemiology to express cumulative or chronic exposure to glycaemia in response to foods over periods of months, 59 whereas RGI refers to acute impact. The inaccuracy of food classifications for glycaemic control based on GI alone, when foods differ in carbohydrate content and serving size, is shown in Fig. 7.1. Expressing glycaemic potency as a content of GGEs enables it to be treated like a nutrient, so that RGI and nutrient intake can be presented simultaneously, allowing complete nutritional management, and use in computer-based diet man- agement systems. 44 GGEs should also enable the combined effect of foods in meals to be gauged, because the GGE contents of different foods may, in theory, be added to give the glycaemic impact of the meal. =???()() ? no. CSMs food CSM weight CHO GI% 10 000 Food weight GGE g of food = GGE g food100 RGP CHO 100 GI= ()?% New approaches to providing nutritional information 177 Table 7.5 The glycaemic index (GI) of foods does not indicate relative glycaemic impact (glycaemic glucose equivalents per common standard measure; GGE/CSM). GI is not a useful guide to food choice for blood glucose control unless carbohydrate intakes are equal Common standard Weight (g) GI GGE/CSM measure of food 1 apricot 54 57 3 1 banana 128 58 18 2 scoops ice-cream 50 61 6.5 1 blueberry muffin 80 59 24 1 can Fanta TM 375 68 35 2 slices pineapple 125 66 6.6 1 glass orange juice 256 46 9.9 1 slice banana cake 80 47 22 1 slice dark rye bread 70 86 19 1 apple muffin 80 44 19 1 cup broad beans 160 79 14.2 1 cup spaghetti 180 41 23 178 The nutrition handbook for food processors 0 5 10 15 20 25 30 Food grouping GGE/serving Breads Breakfast cereals Fruit Vegetables Fig. 7.1 Glycaemic impact as glycaemic glucose equivalents (GGE) per serving of foods classified as low (<55; H17009._), medium (55–70; H17033) and high (>70; H17039) glycaemic index (GI), in each of the food groupings breads, breakfast cereals, fruit and vegetables. GI has not usefully classified foods in each food grouping by glycaemic impact, as GGE contents in the different GI classes overlap. GGE has potentially great practical advantages over GI in dietary man- agement of glycaemia and in food labelling. Responsiveness of GGE intake to food intake could greatly improve the precision with which glycaemia could be managed by diet, insulin and medication. GGE values on food labels would allow the relative glycaemic impact of any food item or quantity to be directly speci- fied, as the examples in Table 7.5 show. Because atherosclerosis is a common long-term complication of diabetes mel- litus, food products for diabetes should also contain a low proportion of saturated fat. Less than 7% of energy from saturated fat is the recommended guideline of the American Heart Association. 60 New approaches to providing nutritional information 179 0 5 10 15 20 25 30 Yam DM Biscuits DM Porridge DM Noodles DM Yam Biscuits Porridge Noodles IAUC/GGE Dose 1 2 x Dose 1 Fig. 7.2 Glycaemic responses (IAUC; mmol · min/L) per glycaemic glucose equivalent (GGE) for foods of differing glycaemic index (GI), carbohydrate (CHO) content, and intake, consumed at a single and a double GGE dose, by subjects with (DM) and with- out Type 2 diabetes. Yams, (GI, 35; CHO, 8.84%; intakes: 10 GGE, 323.2g; 20GGE, 646.4 g), biscuits (GI, 49.5; CHO, 72.9%; intakes: 10 GGE, 27.7 g; 20GGE, 55.4g), porridge (GI, 67.5; CHO, 13.1%; intakes: 10 GGE, 132.4 g; 20 GGE, 246.8 g), noodles (GI, 48; CHO, 16%; intakes: 24 GGE, 323.2 g; 48 GGE, 646.4 g). Results show that GGE content is a robust measure of glycaemic impact. 7.6.6 Validity of GGE intake in predicting glycaemic response GGE is a new concept, and only one study to date has directly tested the pre- dictive validity of GGE intake per se. 61 But GGEs are a combination of GI and carbohydrate dose so studies of joint effects of GI and carbohydrate dose on blood glucose are a test of GGE, and have shown that both amount of carbohydrate and its glycaemic potency (GI) in a food determine glycaemic response. 62,63 We fed subjects several foods, each at two GGE doses, one double the other. After adjust- ing for individual glycaemic responsiveness, glycaemic responses per unit GGE intake were similar across food types and doses to over 100 g carbohydrate intake. Figure 7.2 shows the increment in blood glucose response per GGE for several foods of differing GI, carbohydrate content and intake; it confirms that GGEs are a robust predictor of glycaemic impact. 7.6.7 Product screening for GGE content GGE content is calculated from GI which is a clinical measurement of relative blood glucose responses that may not be feasible to use in a food processing context. However, several tests of in vitro digestibility that correlate well with glycaemic responses in humans are now available and are suitable for screening starchy foods to gauge their relative glycaemic potencies. 64,65,66 Glucose release after 20 min of starch digestion appears to predict glycaemic response well. 66 More slowly digested starch has less impact on blood glucose, because the slower rate of glucose loading into the blood does not exceed the rate of cellular glucose uptake enough to produce an acute glycaemic response. The most accurate measurement of GGE content requires measurement of blood glucose responses to foods in humans, but, because of costs and time, in vitro digestion is a more practical option for the product development stages. 7.7 Faecal bulking index and wheat bran equivalents Faecal bulking capacity is an important property of foods because bulk in the large bowel has a crucial role in large bowel function and health (Table 7.6). The direct relationship between faecal bulk and ‘regularity’ is of concern to a large 180 The nutrition handbook for food processors Table 7.6 Putative links between properties and effects of bulk in the large intestine Property/effect Consequent effect Bulkiness Bulk transfer. Bulk transfer Toxin removal, colonic exposure reduced, decreased transit time. Replenishment of substrates for fermentation – decreased colon cancer risk. Decreased Less protein putrefaction to harmful nitrogenous products – decreased transit time colon cancer risk. Less time for dehydration and stool hardening. Increased Diluted colon contents, stool softening, pressure distribution – water load decreased risk of diverticulosis and haemorrhoids. Replenishment Provides substrates for bacterial growth. Butyrate produced by fermentaion protects against colorectal cancer. Short chain fatty acid production decreases pH and solubility of carcinogenic bile acids. Binding Reduced toxin/carcinogen activity. Pressure Reduces risk of diverticulosis and haemorrhoids by reducing localised distribution pressure points. Distension Stimulates defaecation, preventing stagnation. Defecation Comfort and continued flow, sense of well-being. proportion of the population, who assume that dietary fibre is the food compo- nent responsible, 67 a point well used by food marketers. Countless foods and supplements are promoted as containing dietary fibre, implying that they will promote regularity, but with no supporting efficacy data other than dietary fibre content. Dietary fibre values can, in fact, be a poor guide to faecal bulking. 34,68 Faecal bulk is a result of multiple interactions between the food, the host, and the gut ecosystem – food composition, digestion, endogenous secretions, fermentation, bacterial biomass, water-holding capacity, and particle structure will all play a role. 69 Materials that do not analyse as dietary fibre contribute to faecal bulk, 46 and the combined loss of polysaccharide and its water-holding capacity can be only partly compensated for by bacterial growth. 70 Pectin, for example, is a much less effective faecal bulker than psyllium gum, 34 because it is readily fermented, whereas psyllium is fermentation-resistant and remains highly hydrated in the colon. Both pectin and psyllium are non-starch polysaccharides, and therefore dietary fibre, but dietary fibre analysis gives no indication of the important dif- ferences in their physiological actions. 7.7.1 End-points Normal large bowel function and health are general end-points which, it is almost universally agreed, depend on a supply of bulk to the distal colon. 69,71 More spe- cific effects of bulk in the colon were summarised in Table 7.6. Colonic bulk has been related to a number of health end-points in a number of ways. It is a direct stimulus to defecation, dilutes various toxins and distributes intracolonic pres- sure, reducing the risk of diverticulosis. 69,72 The defecation that it induces allows movement of fermenting material into the distal colon, where it produces butyrate, thought to protect against colorectal cancer. 73 Replenishment of carbo- hydrates in the distal colon may also reduce formation of carcinogenic nitro- genous compounds, formed when proteins are used as a carbon source in fermentation after exhaustion of carbohydrate substrates. 74 Simple constipation resulting from an inadequate supply of moist bulk to the distal colon is one of the most widespread consequences of Western eating pat- terns. 75 If only to prevent constipation, faecal bulking efficacy deserves attention. 7.7.2 Markers Distal colonic bulk is a highly relevant marker of large bowel health because of the number of direct and indirect effects that it has (Table 7.6), and because it is a major factor in laxation. 7.7.3 Current indices Dietary fibre has traditionally been relied on to indicate the potential of a food to promote regularity of bowel function. Indeed, fibre analysis for human foods New approaches to providing nutritional information 181 originated from the physiological concept of dietary fibre as roughage – plant cell wall material not digested by human enzymes in the gut, and responsible for stool bulk. 76 The plant cell wall still remains central to most definitions of dietary fibre and corresponding methods of analysis, 77 although, the definition is being extended to include added non-digestible polysaccharides and oligosaccharides that have beneficial effects. 78,79 But ‘beneficial effects’ specified as part of the definition of dietary fibre include blood cholesterol-lowering and blood glucose-lowering effects, and are not confined to those associated with faecal bulking, so the definition has become too broad to be useful. In fact, dietary fibre analysis has never been congruent with the original physiological concept of dietary fibre as faecal bulking ‘roughage’, because it measures materials resistant to digestion by foregut proteases and amylases, while faecal bulk depends also on resistance to hind gut fermentation. Food components that are both resistant to digestion and to fermentation are not discretely analysed in fibre analysis. There is an overall statistical relationship between dietary fibre intake and faecal bulk, 80 but because of the large amount of variability in foods of low fibre content, fibre cannot be used as a guide to choosing any individual food for bulk, as the results in Fig. 7.3 show. Each food needs to be individually tested before it can be chosen for its faecal bulking efficacy. 182 The nutrition handbook for food processors R 2 = 0.3771 -5 0 5 10 15 20 036912 Fibre in test food (%) Increase in FHW (g/100 g diet) Fig. 7.3 Increase in hydrated faecal weight (FHW) induced by breakfast cereals fed to rats at 50% of the diet. The results show that dietary fibre content is not a reliable predictor of faecal bulking in most breakfast cereals. 7.7.4 Relevant indices The faecal bulking index (FBI) has been developed as an index of the distal colonic bulking efficacy of a food. 34 FBI is defined as the increment in hydrated faecal mass induced by a food as a percentage of the increase due to a wheat bran reference. [7.8] FBI allows foods to be ranked by relative bulking efficacy, on an equal weight basis. Ranking by FBI of a representative sample of Australasian breakfast cereals is shown in Fig. 7.4. FBI Increase in weight of rehydrated faeces per g of test food Increase in weight of rehydrated faeces per g of reference food =￥100 New approaches to providing nutritional information 183 -20 20 40 60 80 100 San Bran All Bran Bran Flakes Sultana Bran Wheat Bix Muesli Rolled Oats (Pam's) Vita Brits Sports Plus Fruity Bix Kornies Miniwheats Nut Feast Multiflakes Creamoata Just Right Sustain Fruitful porridge Rolled Oats (Flemming's) Berry Berry Nice Puffed Wheat Oat Bran (Flemming's) Special K Vita Crunch Chex Nutrigrain Puffed Rice Cornflakes Faecal bulking index 0 Fig. 7.4 Faceal bulking indices (FBI) of a representative selection of Australasian break- fast cereals. FBI gives the increment in faecal bulk indiced by a food relative to that induced by an equal weight of wheat bran. To measure FBI, rats are fed a nutritionally complete baseline diet containing 5% mixed dietary fibre and 50% sucrose, and the increase in hydrated faecal bulk when a proportion of the sucrose is replaced by a test food is compared with the increment induced by an equal weight of wheat bran reference. In the case of the breakfast cereals, all of the sucrose was replaced by cereal. 7.7.5 Valid measurement A crude estimate of faecal bulking would be resistance to fermentation by colonic bacteria in vitro. 81 But, because of the complex of host and food factors deter- mining faecal bulk, it is best measured in vivo, and ideally in humans. However, for the purposes of product screening in food processing, an animal model giving a valid representation of human responses would be expedient, to avoid the dif- ficulties of human research. The laboratory rat gives a reasonable prediction of the relative effects of foods on faecal bulk, 34,82 because, like humans, it is mono- gastric, and food residues from the small intestine undergo extensive mixed bac- terial fermentation in the hind gut, where extent of digestion will be limited more by substrate characteristics than by the availability of microbes. As in humans, dominant factors determining faecal dry matter are the mass of material resistant to mixed bacterial fermentation, bacterial mass, and endogenous secretions. 81 Transit time in the rat is shorter than in man, 83 the rat concentrates faecal dry matter as pellets, and is a caecal rather than a colonic fermenter. Its validity as a model is improved by using large rats (>250 g), preadapting them to mixed dietary fibre, and making sure that test foods are fed at realistic levels to avoid over- loading the gut or exceeding normal fermentation capacity. The problem of faecal dehydration is overcome if the rat faecal pellets are allowed to imbibe water passively to their full water-holding capacity, when their water content rises to that of fresh human stools, and the increase in faecal bulk per gram of wheat bran fibre is almost identical to that measured in humans. 84 The FBI assay gives a relatively quick in vivo measure of relative faecal bulking efficacy. However, as material entering the colon depends on diet com- position, not on one component of it, absolute effects may be influenced by other foods in the diet. 7.7.6 Practical units FBI is a percentage based on comparison of equal weights of foods, so, like GI, it is not a function of food quantity. This problem is addressed by expressing faecal bulking efficacy in terms of content of equivalents to a familiar faecal bulking reference material, so that choice of food type (content), and quantity, can be a guide in choosing foods. 42 To be consumer-friendly such a reference should be: ? Widely available. ? Familiar/identifiable – well known to consumers. 184 The nutrition handbook for food processors ? Understood – known for its effectiveness. ? Relevant – occurring widely in the normal diet. ? Constant – not varying in the relevant properties. ? Effective – exhibiting the property of interest to at least a moderately high degree. Hard red wheat bran is a relevant reference for faecal bulking: it is widely avail- able, familiar, well known for its bulking effects, widely consumed, and although it may vary between batches, it is available as an American Association of Analytical Chemists reference material for dietary fibre analysis. With wheat bran as the reference (FBI wheat bran = 100), faecal bulking efficacy may be expressed as the weight of wheat bran that would contribute the same faecal bulk as the given quantity of food, that is, as the content of wheat bran equivalents for faecal bulk (WBE fb ) in the food. WBE fb in a weight w A of Food A, with an FBI value of FBI A is: [7.9] The faecal bulking efficacies of some of the breakfast cereals in Fig. 7.4, expressed as WBE fb per serving, are shown in Table 7.7. WBE fb content allows direct comparison of different amounts of different products and can therefore be useful to both food processors and consumers. WBE fb allows the potential contributions to faecal bulk by food in a meal or diet to be monitored, in theory, by adding the WBE fb contributions of each food. Then, based on a desired daily WBE fb intake, any shortfall can be determined by dif- ference, and remedied with an appropriate food or bulking supplement. Individual WBE fb requirements will vary greatly, but once established, cumu- lative intake of WBE fb per day could be used to ensure that dietary goals are met. An average adult daily reference value for faecal bulking (DRV fb ) of 67.6 WBE fb per day has been calculated, 84 from associations between faecal weight and protection against large bowel disease measured in epidemiological studies. 80,85 7.7.7 Application of FBI assay to product screening An evaluation of the faecal bulking efficacy of Australasian breakfast cereals is an example of how the FBI assay might be used in product screening. 82 The results are shown in Fig. 7.5. Faecal bulking efficacies, as wheat bran equivalents per serving, were classified according to associated nutrient claims for dietary fibre. The results show that most breakfast cereals provided less than the average bulk per serving required to provide the DRV fb on current intakes of dietary fibre sources (10 servings per day; 6.7 WBE fb per serving required), or on recom- mended intakes (16 servings per day; 4.2 WBE fb per serving required). It was concluded that nutrient claims for dietary fibre in most breakfast cereals probably exaggerated their faecal bulking efficacy, although the findings would be best confirmed in human trials with some selections of the cereals. WBE w FBI g fb A A =?()()100 New approaches to providing nutritional information 185 7.8 Conclusion and future trends The discussion in this chapter has focused on the need for new tests of the nutri- tional functionality of foods, and on making information from such tests relevant in the sense of helping consumer choice for wellbeing. Without such data, neither food processors nor consumers will be able to make the choices required for the development of healthier food products on the one hand, and healthier diets on the other. The primary justification for objective nutrition research is that it improves health, and if food choice is part of that, nutritional information needs to facilitate healthy food choice to be truly relevant. It has been estimated that the market for functional foods in the USA will be worth US$ 34 billion in 2010, 86 and that ‘do it yourself’ health, based on supplements and functional/fortified foods is at present a US$ 42 billion oppor- 186 The nutrition handbook for food processors Table 7.7 Relative faecal bulking efficacy of breakfast cereals as faecal bulking indices (FBI), and as wheat bran equivalents for faecal bulk (WBE fb ) per serving FBI (= WBE fb /100 g) Serving size (g) WBE fb /serving (g) All Bran 51.3 45 23.1 Berry Berry Nice 8.6 30 2.6 Bran flakes 26.2 30 7.9 Chex 3.3 30 1.0 Cornflakes -1.7 30 -0.5 Creamoata 12.2 30 3.7 Fruitful porridge 10.5 40 4.2 Fruity Bix 13.8 40 5.5 Just right 11.7 45 5.3 Kornies 13.4 30 4.0 Miniwheats 13.0 30 3.9 Muesli 17.2 50 8.6 Multiflakes 12.6 45 5.7 Nut Feast 13.0 45 5.9 Nutrigrain 2.7 30 0.8 Oat Bran 7.7 30 2.3 Puffed rice -0.4 30 -0.1 Puffed wheat 8.4 30 2.5 Rolled Oats (Fleming’s) 9.0 30 2.7 Rolled Oats (Pam’s) 16.9 30 5.1 San Bran 81.7 45 36.8 Special K 7.5 30 2.2 Sports plus 15.1 50 7.6 Sultana bran 20.8 45 9.4 Sustain 10.6 45 4.7 Vita Brits 15.9 30 4.8 Vita crunch 4.8 60 2.9 Wheat biscuits 18.0 30 5.4 Wheat bran (reference) 100.0 67.5 67.5 tunity. 87 But there have also been signs that consumer support for some functional foods is faltering. Given the flood of functional foods onto the market, coupled with inadequate information for discriminatng between products, confusion and mistrust generated by extravagant claims, and apparently conflicting statements from nutritionists, some resistance in consumers who do not know what to believe or what to choose, is understandable. For the future, then, several needs must be met: 1. New information on the health–relevant food properties of specific foods from new tests of nutritional efficacy. 2. More comprehensive data sets to supplement food composition tables with data that better reflects health effects of foods. 3. Forms of data that are meaningful, for use in healthier food selection at point of sale. 4. Education to help give meaning to nutritional information for healthier food choices. The need for new tests and biomarkers to assess nutritional functionality is well recognised, 88 and detailed attention has been given to characteristics required New approaches to providing nutritional information 187 -10 0 10 20 30 40 No claim Source of fibre High in fibre Very high in fibre Nutrient claim Wheat bran equivalents (WBE fb ) per serving 6.7 Fig. 7.5 Faecal bulking efficacy as wheat bran equivalents (WBE fb ) per serving of break- fast cereals classified by the nutrient claims for dietary fibre in Australasia (no claim, <1.5 g fibre/serving; source of fibre, 1.5–3 g fibre/serving; high in fibre, 3–6 g fibre/serving; very high in fibre, >6 g dietary fibre/serving), relative to the mean WBE fb contribution per serving (6.7) required to satisfy average adult requirements in a diet containing 10 servings per day of dietary fibre sources. of tests for them to be valid predictors of food effects on health end-points. 38 Such discussions will give impetus to further work required to identify valid bio- markers and other measures for predicting effects of food components and prop- erties on health. The properties of individual processed foods have been the focus of this chapter, but at a higher level of complexity, interactions between foods in meals, and the place of foods in dietary patterns will be important determinants of health. Even when the efficacy of a food has been well established, its role in the diet, and the ways that other foods may modulate its effectiveness will need to be clarified. Many of the properties of foods that are beneficial to health are characteristic of unprocessed or ‘whole’ foods, and there is a movement to exploit the benefits of natural structure, as seen in the recent promotion of whole grains. 89,90 The same tests that are used to monitor nutritional effects of food processing in formulated products will be valuable in identifying processes that preserve the intrinsic value of natural foods. 7.9 Sources of further information and advice The need for new approaches to providing nutritional information has arisen from the recent interest in functional foods. 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