The impact of freezing and toasting on the glycaemic response of white bread



To investigate the impact of freezing and toasting on the glycaemic response of white bread.


Ten healthy subjects (three male, seven female), aged 22–59 years, recruited from Oxford Brookes University and the local community. A homemade white bread and a commercial white bread were administered following four different storage and preparation conditions: (1) fresh; (2) frozen and defrosted; (3) toasted; (4) toasted following freezing and defrosting. They were administered randomized repeated measures design. Incremental blood glucose, peak glucose response, 2 h incremental area under the glucose response curve (IAUC).


The different storage and preparation conditions resulted in lower blood glucose IAUC values compared to both types of fresh white bread. In particular, compared to the fresh homemade bread (IAUC 259 mmol min/l), IAUC was significantly lower when the bread was frozen and defrosted (179 mmol min/l, P<0.05), toasted (193 mmol min/l, P<0.01) and toasted following freezing and defrosting (157 mmol min/l, P<0.01). Similarly, compared to the fresh commercial white bread (253 mmol min/l), IAUC was significantly lower when the bread was toasted (183 mmol min/l, P<0.01) and frozen, defrosted and toasted (187 mmol min/l, P<0.01).


All three procedures investigated, freezing and defrosting, toasting from fresh and toasting following freezing and defrosting, favourably altered the glucose response of the breads. This is the first study known to the authors to show reductions in glycaemic response as a result of changes in storage conditions and the preparation of white bread before consumption. In addition, the study highlights a need to define and maintain storage conditions of white bread if used as a reference food in the determination of the glycaemic index of foods.


The glycaemic index (GI), first introduced in 1981 (Jenkins et al., 1981), is a classification of the blood glucose raising potential of carbohydrate foods. It is defined as the incremental area under the blood glucose curve (IAUC) of a 50 g available carbohydrate portion of a test food expressed as a percentage of the response to 50 g available carbohydrate of a reference food taken by the same subject, on a different day (FAO/WHO, 1998).

Recent data support the preventive potential of a low-GI diet against the development of type 2 diabetes and cardiovascular disease (Salmeron et al., 1997a, 1997b; Frost et al., 1999). There is also an interest in the potential of low-GI diets in body weight management, with studies showing that low-GI foods, or lowering the GI of a food, may reduce hunger and result in a lower energy intake (Ludwig, 2000; Warren et al., 2003).

As consumer interest in GI has grown in recent years, a major challenge for the food industry is to develop and produce foods of low glycaemic response. In the UK, bread forms the most important staple amongst starch foods and is one of the largest sectors in the food industry, producing almost 12 million loaves and packs every day (Federation of Bakers, 2005). Moreover, white bread sales represent over 70% of all bread sales in the UK. In 2004–2005, the household consumption of white bread was almost 400 g per person per week compared to 120 and 45 g per person per week for wholemeal and brown bread, respectively (Department for Environment, Food and Rural Affairs, 2006).

In the UK, the baking industry predominantly uses the Chorleywood Bread Process (CBP), which is responsible for over 80% of bread produced. The CBP, developed in 1961, is a mechanical dough development process involving intensive mixing, the use of oxidants, a short fermentation process and the use of a pan for baking. In addition, the process has an important impact in the UK as it enables the use of low-protein home-produced wheat (Belderok, 2000). However, the result of developments in the bread-making process is a highly favoured, but medium- to high-GI white bread.

In the UK, an increase in time pressure in family life has meant that infrequent, bulk shopping and freezing are widespread. Consequently, the consumption of bread that has been defrosted following freezing is commonplace. In addition, consumption of bread in the form of toast, mainly at breakfast, is also customary.

Although some food processes, for example gelatinization, may lead to high-GI foods (Granfeldt et al., 2000), some food manufacturing and handling may have an effect on the degree of starch retrogradation, involving a rearrangement or realignment of initially heated starch molecules (Berry, 1986; Lang and Vitapole, 2004). Moreover, retrograded starch has been shown to reduce glycaemic response and there is evidence of this happening under conditions of cooling (Larsen et al., 2000; Frei et al., 2003). Retrogradation is greater where the degree of gelatinization is more complete, facilitated by higher temperature and greater water availability or with greater mixing, for example in the formation of bread dough. Furthermore, it has also been shown that overall starch recrystallization reaches a maximum at around 4°C and below this temperature further starch recrystallization is minimal (Lang and Vitapole, 2004; Goesaert et al., 2005). Importantly, the process of freezing and defrosting bread will involve bread passing through this point of maximal recrystallization and retrogradation twice, once while cooling and again during defrosting.

Relatively small differences in the glycaemic response of regularly consumed starch foods have shown beneficial effects on health, including reduced cardiovascular disease risk and glycaemic control (Frost et al., 1998; Brand-Miller et al., 2003). Thus, investigations into ways of reducing the glycaemic response to white bread are of important application. In the light of the above, the aim of the present study was to determine whether the glycaemic response of white bread could be changed by everyday storage and preparation conditions such as procedures of freezing, defrosting and toasting.

Subjects and methods


Ten healthy subjects (three male and seven female) were recruited to participate in the study. Subjects were staff and students from Oxford Brookes University and from the wider community. To participate, subjects were required to be between 18 and 59 years of age, with a body mass index (BMI) <30 kg/m2. Interested subjects were asked to complete a health screening questionnaire to check against ill health, including clinically abnormal glucose metabolism (fasting blood glucose >6.1 mmol/l) and any medical conditions or medications that might affect glucose regulation, gastric emptying, body weight, appetite or energy expenditure.

Anthropometric measurements were made in the fasting state, using standardized methods, on the morning of the first test. Height was recorded to the nearest centimetre using a stadiometer (Seca Ltd, UK), with subjects standing erect and without shoes. Body weight was recorded to the nearest 0.1 kg using the Tanita BC-418 MA (Tanita UK Ltd), with subjects wearing light clothing and no shoes. BMI was calculated using the standard formula weight (kg)/height (m)2. Characteristics of the subjects are shown in Table 1.

Table 1 Characteristics of study population

Ethical approval for the study was obtained from the University Research and Ethics Committee at Oxford Brookes University. Subjects were given full details of the study protocol and the opportunity to ask questions. All subjects gave written informed consent before participation.

Study protocol

The method used to measure glycaemic response and to calculate the GI value was in line with procedures recommended by the FAO/WHO (1998). In addition, on the day preceding a test, subjects were asked to restrict their intake of alcohol and caffeine-containing drinks and to refrain from intense physical activity (e.g., long periods at the gym, excessive swimming, running, aerobics). To minimize the possible influence of the second meal effect, subjects were asked to refrain from eating an extra-large evening meal or have an unusually high or low food intake throughout the day preceding a test (Wolever, 1990). Where possible, subjects ate a similar meal type on the evening before testing; however subjects were asked to avoid consuming pulses for this meal to avoid the effects of colonic fermentation on postprandial glycaemic (Macintosh et al., 2003). All foods were tested in subjects after a 12 h overnight fast.

Test breads were administered to subjects in a randomized, repeated measures design, with each subject acting as his/her own control. Subjects travelled to the laboratory by car or public transport and rested for 10 min before the test commenced. Test breads were consumed first thing in the morning (i.e., as breakfasts) and were compared with a reference food (glucose) and were tested in equivalent amounts (50 g) of available carbohydrate. Available carbohydrate was estimated according to the FAO/WHO procedure (total carbohydrate minus dietary fibre), using calculated data of macronutrient content (Table 2). Thus, in this context, dietary fibre was defined as unavailable carbohydrate.

Table 2 Nutritional composition (per 100 g) of test breads, using manufacturers' data

As blood glucose responses vary within subjects from day to day, the reference food (glucose) was tested 3 times in each subject. Thus, subjects tested each test bread once and the reference food 3 times in random order on separate days, with at least a one-day gap between measurements to minimize carry over effects. All test breads and the reference food were served with 200 ml water. A further 200 ml water was given during the subsequent 2 h. Subjects were asked to eat the test breakfast within a 10–12 min period to reduce the influence of chewing on particle size (Hoebler et al. 1998).

Test breads

Two white breads, one homemade bread prepared using a standard home bread-making machine (Breadman Pro, Russell Hobbs, Manchester, UK) and one commercially available bread (Hovis Classic, British Bakeries Ltd, UK), were tested for glycaemic response. The homemade white bread was made from 500 g white wheat flour (Carr's white strong bread flour; a high-protein wheat that does not contain enzymes, improvers or bleach), 8 g NaCl, 6 g sugar, 287 ml water, 6 g butter, 7 g skimmed milk powder and 8 g dehydrated yeast without additives (Fermipan, DSM Bakery Ingredients, Holland). Details of the macronutrient, dietary fibre and sodium content of the two test breads are given in Table 2. Parallel investigations of homemade and commercial breads allowed investigation of any modulation, for example by additives, in commercial breads not found in the homemade bread.

Both breads were tested following four different storage and preparation conditions: (1) fresh; (2) frozen and defrosted; (3) fresh and toasted; (4) toasted following freezing and defrosting. Fresh bread was tested on the morning following baking or purchase. Frozen bread was defrosted overnight at room temperature before consumption the following morning. Breads were frozen between 2 and 7 days; it has been suggested that further retrogradation during freezing following temperature reduction to the frozen state does not occur (Gray and Bemiller, 2003). Bread was toasted on the morning following baking or purchase and, where applicable, following defrosting overnight at room temperature. For the duration of the study, a toaster was standardized to medium setting, ensuring consistent moderate toasting.

Blood glucose measurements

Finger-prick blood samples were taken for capillary blood glucose analysis. Recent reports suggest that capillary blood sampling is preferred for reliable GI testing (FAO/WHO, 1998; Wolever and Mehling, 2003). To establish blood glucose stability at the start of the blood glucose response curve, fasting blood samples were taken at −5 and 0 min before consumption of the food and the baseline value taken as a mean of these two values. The reference food/test bread was consumed immediately after this and further blood samples were taken at 15, 30, 45, 60, 90 and 120 min after starting to eat.

Blood was obtained by finger prick using the Glucolet 2 multi-patient lancing system (Bayer HealthCare, Newbury, UK). Where necessary, before a finger prick, subjects were encouraged to warm their hand under running warm water to increase blood flow. Fingers were not squeezed to extract blood from the fingertip as this may dilute with plasma. Blood glucose was measured using Ascensia Contour automatic blood glucose meters (Bayer HealthCare). The blood glucose meters were calibrated daily using control solutions from the manufacturer and were also regularly calibrated against a clinical dry chemistry analyser (Reflotron Plus, Roche, Welwyn Garden City, UK) and the HemoCue Glucose 201+ analyser (HemoCue Ltd, Dronfield, UK). Using the Bland–Altman analyses, there was a very strong correlation (r=0.980, P <0.001) and good agreement (mean difference −0.2 mmol, 95% CI −0.3 to −0.2, limits of agreement −0.80 and 0.32) between blood glucose measurements for a random selection of 140 blood samples simultaneously measured using the Ascensia Contour and the HemoCue Glucose 201+ analyser.

Statistical analysis

Statistical analysis was performed using the Statistical Package for the Social Sciences (SPSS version 11.0. 1, Chicago, IL, USA). Data are presented as means and standard deviations. Before statistical analysis, the normality of the data was tested using the Shapiro–Wilk statistic. The Pearson's correlation coefficient and the method of Bland and Altman (1986) were used to examine the correlation and agreement between the automatic analyser and the HemoCue Glucose 201+ analyser. Levels of intra-individual variation of the three reference (glucose) tests were assessed by determining the coefficient of variation (CV%=100 × standard deviation/mean). Repeated measures analysis of variance, with Bonferroni's correction, was used to compare glycaemic response between test breads stored and processed in different ways. Statistical significance was set at P<0.05.


The mean intra-individual variation in glycaemic response to the three reference tests in the subjects was 28% CV. This value is consistent with previously reported data in normal subjects (Wolever, 2006).

Figure 1 shows the incremental blood glucose response curves for the homemade white bread. There was no overall effect of storage and preparation on the peak rise in blood glucose response (P=0.64) in the homemade bread.

Figure 1

Blood glucose response curve for homemade bread: Glucose (*); fresh (); frozen, defrosted (•); fresh, toasted (□); frozen, defrosted, toasted (▪).

Table 3 shows the IAUC across the different storage and preparation conditions for the homemade white bread. Significant differences in IAUC (F=10.503, P<0.001) were seen. Compared to the fresh homemade bread, IAUC was significantly lower for homemade frozen and defrosted bread (P=0.010), homemade fresh toasted bread (P=0.007) and homemade bread that had been toasted following freezing and defrosting (P=0.001).

Table 3 IAUC (mmol·min/l) for homemade bread and commercial white bread with different storage and preparation conditions

Figure 2 shows the incremental blood glucose response curves for the commercial white bread. Peak rise in blood glucose was significantly different across the storage and preparation conditions (F=7.425, P=0.001). Peak rise in blood glucose for commercial fresh toasted bread and commercial bread that had been toasted following freezing and defrosting was significantly lower than fresh commercial bread (P=0.024 and P=0.018, respectively) and commercial bread that had been frozen and defrosted (P=0.020 and P=0.006, respectively).

Figure 2

Blood glucose response curve for commercial white bread: Glucose (*); fresh (); frozen, defrosted (•); fresh, toasted (□); frozen, defrosted, toasted (▪).

There were significant differences in IAUC (F=6.105, P=0.003) between the storage and preparation conditions for the commercial bread (Table 3). IAUC values for fresh toasted bread and bread that had been frozen, defrosted and toasted were significantly lower than for fresh bread (P=0.001 and P=0.026, respectively). The IAUC value for fresh toasted bread was also significantly lower compared to bread that had been frozen and defrosted (P=0.046).


The current study investigated the impact of storage conditions and food preparation on the glycaemic response to white bread. This is the first study known to the authors to show reductions in glycaemic response as a result of changes in storage conditions and the preparation of white bread before consumption. All three procedures investigated, that is freezing and defrosting, toasting from fresh and toasting following freezing and defrosting, led to a reduced glycaemic response and reduction in IAUC values.

The influence of food processing and cooking on glycaemic response is well documented (Brand et al., 1985; Bjorck et al., 1994). Treatments incorporating the generation of forces such as shearing, compression and extreme heat treatment increase gelatinization, which results in the breakdown of the starch granule. Thus, many processing conditions lead to an increased susceptibility of the starch granule to enzymatic salivary and pancreatic amylases following consumption, resulting in greater availability of glucose for absorption and increased glycaemic response. Examples of such treatments are flour milling, intensive mixing in bread dough formation, as in the CBP, and bread baking, which may explain the relatively highGI value of white bread.

Retrograded starch constitutes RS3, a form of resistant starch, and there is evidence of the formation of RS3 during the processes of cooling and freezing (Hoebler et al., 1999; Goesaert et al., 2005). There has been an increasing interest in resistant starch in recent years and positive health benefits have been demonstrated, mediated through effects on colonic fermentation and on both postprandial glucose and lipid metabolism (Robertson et al., 2003; Higgins et al., 2004).

An important difference in the constituents of the homemade and commercial white breads in this study was the presence of dough conditioners and improvers. These ingredients are widely used in commercial bread and are designed to optimize dough formation and quality, reduce staling rate and maintain water retention during baking (Goesaert et al., 2005). However, water content and activity within the dough facilitates the retrogradation process. Moreover, amylopectin retrogradation, together with moisture transfer between bread components, may be reduced by the use of dough improvers (Baik et al., 2003). This may explain smaller reductions in glycaemic response within the commercial bread, compared to changes within the homemade bread.

The implications of this study are twofold. First, it is suggested that simple household methods, such as freezing, defrosting and toasting, may alter the glycaemic response to white bread, thus white bread need not always be a highGI food. There still remains a preference for white bread in the UK (Department for Environment, Food and Rural Affairs, 2006), therefore the current study will be informative to consumers in terms of optimal storage and preparation of white bread to favourably alter glycaemic response. Second, this study highlights a need to reconsider the use of white bread as a reference food in GI methodology. Although GI values determined using white bread as a reference food can be converted to GI values based on glucose (Wolever, 2006), the findings from the current study suggest that if bread is unintentionally treated differently each time it is used as a reference food, reproducibility and comparisons of the GI of foods between different studies will be difficult.

Variability of glycaemic response has been a major criticism of the GI concept. This variability may be owing to a host of factors, acting independently or together. In this study, conscientious efforts were made to maximize standardizing of possible factors, to reduce intra- and inter-individual variability, including a 12 h fast before testing, restriction of exercise, alcohol and caffeine consumption the day before a test and time spent chewing the test food.

A limitation of this study was the indirect estimation of available carbohydrate content of the bread samples. It is recommended that future studies include such measurements, including resistant and retrograded starch (Englyst et al., 1992; McCleary and Monaghan, 2002), both before and after storage and preparation conditions. In addition, other methods have been proposed to classify the glycaemic impact of foods based on total carbohydrate rather than available carbohydrate, such as relative glycaemic effect (Brouns et al., 2005). However, further research is needed on the use of alternative indices to measure the glycaemic response of foods.

In conclusion, this is the first study known to the authors to show reductions in glycaemic response following different storage and preparation conditions of white bread and highlights the need to define and maintain storage conditions of food products when the glycaemic response of foods is determined. Relatively small differences in the glycaemic response of regularly consumed starch foods have been shown previously to have beneficial effects on health (Frost et al., 1998; Brand-Miller et al., 2003). Thus, considering the high consumption of white bread, the identification of ways to reduce the glycaemic response of white bread and other foods is important in the prevention and management of chronic disease.


  1. Baik M-Y, Dickinson LC, Chinachoti P (2003). Solid-state 13C CP/MAS NMR studies on aging of starch in white bread. J Agric Food Chem 51, 1242–1248.

    CAS  Article  Google Scholar 

  2. Belderok B (2000). Developments in bread-making processes. Plant Foods Hum Nutr 55, 1–86.

    CAS  Article  Google Scholar 

  3. Berry CS (1986). Resistant starch: formation and measurement of starch that survives exhaustive digestion with amylolytic enzymes during the fermentation of dietary fibre. J Cereal Sci 4, 301–314.

    CAS  Article  Google Scholar 

  4. Bjorck I, Granfeldt Y, Liljeberg H, Tovar J, Asp NG (1994). Food properties affecting the digestion and absorption of carbohydrates. Am J Clin Nutr 59, S699–S705.

    Article  Google Scholar 

  5. Bland JM, Altman DG (1986). Statistical methods for assessing agreement between two methods of clinical measurement. Lancet I, 307–310.

    Article  Google Scholar 

  6. Brand JC, Nicholson PL, Thorburn AW, Truswell AS (1985). Food processing and the glycemic index. Am J Clin Nutr 42, 1192–1196.

    CAS  Article  Google Scholar 

  7. Brand-Miller JC, Hayne S, Petocz P, Colagiuri S (2003). Low-glycemic index diets in the management of diabetes. A meta-analysis of randomized controlled trials. Diabetes Care 26, 2261–2267.

    Article  Google Scholar 

  8. Brouns F, Bjorck I, Frayn KN, Gibbs AL, Lang V, Slama G et al. (2005). Glycaemic index methodology. Br J Nutr 18, 145–171.

    CAS  Google Scholar 

  9. Department for Environment, Food and Rural Affairs (2006). Family Food in 2004-05. TSO: London.

  10. Englyst HN, Kingman SM, Cummings JH (1992). Classification and measurement of nutritionally important starch fractions. Eur J Clin Nutr 46, S33–S50.

    PubMed  PubMed Central  Google Scholar 

  11. FAO/WHO (1998). Carbohydrates in Human Nutrition Report of a Joint FAO/WHO Expert Consultation. FAO: Rome.

  12. Federation of Bakers (2005). The British Bread and Bakery Snacks Market Factsheet No.

  13. Frei M, Siddhuraju P, Becker K (2003). Studies on the in vitro starch digestibility and the glycaemic index of six different indigenous rice cultivars from the Philippines. Food Chem 83, 395–402.

    CAS  Article  Google Scholar 

  14. Frost G, Leeds A, Trew G, Margara R, Dornhorst A (1998). Insulin sensitivity in women at risk of coronary heart disease and the effect of a low glycemic diet. Metabolism 47, 1245–1251.

    CAS  Article  Google Scholar 

  15. Frost G, Leeds AA, Dore CJ, Madeiros S, Brading S, Dornhorst A (1999). Glycaemic index as a determinant of serum HDL-cholesterol concentration. Lancet 353, 1045–1048.

    CAS  Article  Google Scholar 

  16. Goesaert H, Brijs K, Veraverbeke WS, Courtin CM, Gebruers K, Delcour JA (2005). Wheat flour constituents: how they impact bread quality, and how they impact their functionality. Trends Food Sci Tech 16, 12–30.

    CAS  Article  Google Scholar 

  17. Granfeldt Y, Eliasson A-C, Bjork I (2000). An examination of the possibility of lowering the glycaemic index of oat and barley flakes by minimal processing. J Nutr 130, 2207–2214.

    CAS  Article  Google Scholar 

  18. Gray JA, Bemiller JN (2003). Bread staling: molecular basis and control. Comp Rev Food Sci Food Safety 2, 1–21.

    CAS  Article  Google Scholar 

  19. Higgins JA, Higbee DR, Donahoo WT, Brown IL, Bell ML, Bessesen DH (2004). Resistant starch consumption promote lipid oxidation. Nutr Metab 1, 8.

    Article  Google Scholar 

  20. Hoebler C, Karinthi A, Chiron H, Champ M, Barry JL (1999). Bioavailability of starch in bread rich in amylose: metabolic responses in healthy subjects and starch structure. Eur J Clin Nutr 53, 360–366.

    CAS  Article  Google Scholar 

  21. Hoebler C, Karinthi A, Devaux MF, Guillon F, Gallant DJG, Bouchet B et al. (1998). Physical and chemical transformations of cereal food during oral digestion in human subjects. Br J Nutr 80, 429–436.

    CAS  Article  Google Scholar 

  22. Jenkins DJA, Wolever TMS, Taylor RH, Barker H, Fielden H, Baldwin JM et al. (1981). Glycemic index of foods: a physiological basis for carbohydrate exchange. Am J Clin Nutr 34, 362–366.

    CAS  Article  Google Scholar 

  23. Lang V, Vitapole D (2004). Development of a range of industrialised cereal-based foodstuffs, high in slowly digestible starch. In: A-C Elliasson (ed). Starch in Food: Structure, Function and Applications. Woodhead Publishing: Cambridge. pp. 477–504.

    Google Scholar 

  24. Larsen HN, Rasmussen OW, Rasmussen PH, Alstrup KK, Biswas SK, Tetens I et al. (2002). Glycaemic index of parboiled rice depends on the severity of processing: study in type 2 diabetic subjects. Eur J Clin Nutr 54, 380–385.

    Article  Google Scholar 

  25. Ludwig DS (2000). The glycemic index. Physiological mechanisms relating to obesity, diabetes, and cardiovascular disease. JAMA 287, 2414–2423.

    Article  Google Scholar 

  26. Macintosh CG, Holt SHA, Brand-Miller JC (2003). The degree of fat saturation does not alter glycaemic, insulinaemic or satiety responses to a starchy staple in healthy men. J Nutr 133, 2577–2580.

    CAS  Article  Google Scholar 

  27. McCleary BV, Monaghan DA (2002). Measurement of resistant starch. J AOAC Int 85, 665–675.

    CAS  PubMed  Google Scholar 

  28. Robertson MD, Currie JM, Morgan LM, Jewell DP, Frayn KN (2003). Prior short-term consumption of resistant starch enhances postprandial insulin sensitivity in healthy subjects. Diabetologia 46, 659–665.

    CAS  Article  Google Scholar 

  29. Salmeron J, Ascherio A, Rimm EB, Colditz GA, Spiegelman D, Jenkins DJ et al. (1997a). Dietary fiber, glycaemic load, and risk of NIDDM in men. Diabetes Care 20, 545–550.

    CAS  Article  Google Scholar 

  30. Salmeron J, Manson JE, Stampfer MJ, Colditz GA, Wing AL, Willet EC (1997b). Dietary fiber, glycaemic load, and risk of non-insulin-dependent diabetes mellitus in women. JAMA 277, 472–477.

    CAS  Article  Google Scholar 

  31. Warren JM, Henry CJK, Simonite V (2003). Low glycaemic index breakfasts and reduced food intake in preadolescent children. Pediatrics 112, E414–E419.

    Article  Google Scholar 

  32. Wolever TMS (1990). The glycemic index. World Rev Nutr Diet 62, 120–185.

    CAS  Article  Google Scholar 

  33. Wolever TMS (2006). The Glycaemic Index. A Physiological Classification of Dietary Carbohydrate. Wallingford: CABI.

    Google Scholar 

  34. Wolever TMS, Mehling CC (2003). Long-term effect of varying the source or amount of dietary CHO on postprandial plasma glucose, insulin, triacylglycerol, and free fatty acid concentrations in subjects with impaired glucose tolerance. Am J Clin Nutr 77, 612–621.

    CAS  Article  Google Scholar 

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Sponsorship: This study was supported by a Biotechnology and Biological Sciences Research Council studentship.

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Correspondence to H J Lightowler.

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Contributors: PB planned and designed the study and was responsible for the collection of data and writing the manuscript. HJL advised on the study design and contributed to the preparation of the manuscript.

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Burton, P., Lightowler, H. The impact of freezing and toasting on the glycaemic response of white bread. Eur J Clin Nutr 62, 594–599 (2008).

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  • glycaemic response
  • bread
  • food storage
  • food preparation
  • blood glucose

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