The glycaemic and C-peptide responses of foods rich in dietary fibrefrom oat, buckwheat and lingonberry

SUSANNA ROKKA, ELISE KETOJA, EILA JARVENPAA, & RAIJA TAHVONEN

MTTAgrifood Research Finland, Jokioinen, Finland

AbstractDietary fibre has a beneficial effect on metabolic syndrome, e.g. by influencing the absorption of glucose. The source andstructure of fibre affect the glucose response. In this study, the glycaemic and insulinaemic response to oat bread, oat bread withlingonberry fibre, oat–buckwheat bread and buckwheat porridge were tested in a small-scale clinical study (KHSHP E514/09).Nine healthy volunteers consumed test foods after overnight fasting. Serum glucose and C-peptide levels were determined bycolorimetric and ELISA methods, respectively, from samples taken at seven time points during 120 min. The mean glycaemicand C-peptide indexes (C-pepIs) were 32 and 100 for oat bread, 47 and 119 for oat–lingonberry fibre bread, 58 and 105 foroat–buckwheat bread and 71 and 77 for buckwheat porridge. Similar to rye, buckwheat porridge having a relatively highglycaemic index (GI) tended to have a low C-pepI. Buckwheat and lingonberry fibres provide new alternatives for low GI foods.

Keywords: glycaemic response, C-peptide response, oat, buckwheat, lingonberry, fibre

Introduction

Breads and other grain foods, fruits and vegetables

are the most important sources for dietary fibre

(Paturi et al. 2008). Diets rich in dietary fibre decrease

risk of non-communicable life-style diseases such as

cardiovascular diseases, metabolic disorder and type 2

diabetes (T2D) (Barclay et al. 2008). Dietary fibre can

support the regulation of energy intake and satiety.

Greater satiety may result from the physical properties

of dietary fibre, modulation of gastric motor function

and weakening of glucose and insulin responses

(Papathanasopoulos and Camilleri 2010). The know-

ledge of the relationships of molecular structures of

dietary fibres from various sources and their health

effects is still limited (Gemen et al. 2011). According

to large cohort studies, the insoluble cereal fibre has

a more remarkable reducing effect on diabetes risk

and overweight than fruit or vegetable fibre (Weickert

and Pfeiffer 2008; Du et al. 2010). Health effects

of fibre can be substantiated only when the intake

is high enough – for healthy adults the amount seems

to be 25–38 g/d (Slavin et al. 2009). An increase in

the intake of dietary fibre has been difficult even in

intensive interventions (Lindstrom et al. 2006). New

sources of dietary fibre for consumers are thus needed.

Buckwheat (Fagopyrum esculentum Moench) is an

old crop, traditionally consumed as cooked or baked.

Buckwheat is classified as non-cereal but its seeds

contain cereal-like starch. It is gluten free and thus

suitable also for people suffering of celiac disease.

Animal trials have shown that the positive health

effects of buckwheat are associated especially with its

sugar and fibre components. For instance,D-chiro-inositol

in buckwheat is known to possess health-promoting

properties (Fonteles et al. 2000). A diet rich in

buckwheat fibre reduced many overweight-related risk

factors of cardiovascular diseases in rats (Son et al.

2008). Buckwheat is also a good source for anti-

oxidants (Gorinstein et al. 2007; Jiang et al. 2007).

It contains flavonoids such as quercetin and isoquer-

cetin that influence T2D by inhibiting a-amylase

activity (Li et al. 2009a, 2009b; Zhang et al. 2011) and

protein components that reduce perturbations in lipid

ISSN 0963-7486 print/ISSN 1465-3478 online q 2013 Informa UK, Ltd.

DOI: 10.3109/09637486.2013.763914

Correspondence: Susanna Rokka, MTT Agrifood Research Finland, Myllytie 1, 31600 Jokioinen, Finland. Tel: þ 358 29 5317684.E-mail: susanna.rokka@mtt.fi

International Journal of Food Sciences and Nutrition,

August 2013; 64(5): 528–534

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metabolism (Tomotake et al. 2006). Processing such

as hydrolysis or heating of buckwheat increases these

properties (Skrabanja et al. 2001).

Lingonberry (Vaccinium vitis-idaea) is commonly

used as jam or juice. The fibre fraction comprises a

constituent of the waste stream arising from the berry

juice processing, and is used as feedstock or discarded.

The majority of the phenolic compounds remain in the

press residue if the berries are fractioned by juice

pressing (Sandell et al. 2009). Phenolic compounds of

berries are at present a subject of active research.

Recently, Linderborg et al. (2012) proposed that the

glycaemia-lowering effect of lingonberry fibres and/or

polyphenols compensated the glycaemic effect of

sugars of the berries when consumed together with

added sugar. However, little is known to date about

the beneficial effects of the fibre fractions. Chemical

composition of only a few berry fibres has been

investigated (Wawer et al. 2006).

In this study, buckwheat bread, buckwheat por-

ridge, lingonberry fibre bread and oat bread as a

control were selected for different sources of dietary

fibre. Their glycaemic and C-peptide responses were

studied in a small-scale clinical experiment. Glycaemic

index (GI) and insulin index or C-peptide index

(C-pepI) describe how much food increases the blood

glucose and insulin levels compared to a reference

(usually glucose), respectively. In this study, C-peptide

is analysed instead of insulin in order to determine

insulin response. Equimolar amounts of C-peptide

and insulin are released when proinsulin is activated to

insulin. The half-life of C-peptide is longer than that of

insulin which makes it easier to measure from

peripheral blood samples. The aim was to evaluate

the effect of new non-cereal sources of dietary fibre on

glucose metabolism.

Materials and methods

Subjects

Nine normal, healthy subjects aged 20–54 years

(mean 35 years), two males and seven females from

HAMK University of applied sciences and MTT

Agrifood Research Finland participated in this study.

The mean body mass index of the test persons was

23.8. Subjects were free from metabolic disorders and

did not take any medications known to affect glucose

metabolism. The study was carried out in compliance

with the appropriate laws and institutional guidelines

and approved by the ethical committee of Kanta-

Hameen Sairaanhoitopiiri, KHSHP E514/09. An

informed written consent was obtained from each

subject before the study.

Test foods

Test breads (oat bread, oat bread with lingonberry

fibre and oat–buckwheat bread) were prepared, and

their carbohydrate and fibre contents were analysed at

MTT Agrifood Research Finland. The recipes are

given in Table I. Oat flour was obtained from

Helsingin Mylly (Jarvenpaa, Finland), lingonberry

powdered fibre from Kiantama Ltd (Suomussalmi,

Finland) and carboxymethyl cellulose (CMC) from

Maustepalvelu (Hameenlinna, Finland). Other bread

ingredients were purchased from local grocery stores.

Buckwheat porridge contained 74 g of buckwheat

flakes (Myllyn Paras, Hyvinkaa, Finland) and 4.5 dl

water. It was cooked in a microwave oven (800 W)

for 5 min.

The contents of test breads were analysed by MTT

in-house validated methods. Total fibre contents as a

sum of soluble and insoluble dietary fibre were

analysed by an enzymatic–gravimetric method,

which is based on AOAC 991.43 method. Starch was

determined by an enzymatic–spectrophotometric

method and resistant starch by the Megazyme kit

analysis method, based on AOAC Method 2002.02

and AACC Method 32-40. Sugars were analysed

using an in-house liquid chromatographic method.

Test protocol

Glycaemic responses (2-h tolerance test) of test foods

were measured in clinical studies according to

FAO/WHO recommendations (1998) noticing the

recent improvements in the methods. A standard

evening meal (supper) was provided for each test

person for the evenings before tests, and test persons

got exact orders for the exercise on the test morning.

Test persons fasted 8–12 h before each test. GIs of

servings of test foods providing 57—67 g of available

carbohydrates (Table II) were assessed relative to 50 g

of anhydrous glucose (Oriola, Espoo, Finland) as a

250 ml solution. With breads, 250 ml of water was

served. The glycaemic response to glucose was

assessed as average of three occasions. The series of

tests was started with a glucose test but the order of

the rest of the tests varied among the test persons. The

meals were provided during a period of maximum

three months. Capillary finger prick blood samples

were collected in 500ml lithium–heparin gel tubes

(MiniCollectw, Greiner-Bio-One, Kremsmunster,

Austria) after overnight fasting and at 15, 30, 45, 60,

90 and 120 min after consumption of each meal.

Collected bloods were immediately centrifuged at

8000 rpm for 5 min. Plasma was frozen and stored

at 2208C prior to analysis of glucose and C-peptide

concentrations. Between every test, there was at least

3 days wash-out period to eliminate the possible long-

term effects of the fasting or test food.

The glucose level of serum was measured using

quantitative colorimetric glucose assay kit (Biochain,

Hayward, CA, USA) at 650 nm. The concentrations

of C-peptide were analysed by the ELISA method

(IBL International GMBH, Hamburg, Germany).

Glycaemic and C-peptide responses of foods 529

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Data analysed

Incremental areas under the plasma glucose and

C-peptide response curves (IAUC), ignoring area

beneath the fasting level, were calculated geometri-

cally. The mean of IAUC values for the three repeated

glucose tests was calculated for each subject. The

IAUC for each food was expressed as a percentage of

the mean IAUC for glucose taken from the same

subject to give the GIs or C-pepIs for the food. The

aim of the test protocol was that each test meal

contains 50 g of available carbohydrates, the same

amount as the glucose tolerance test. The calculated

amounts of carbohydrates differed, however, from the

analysed amounts (Table II). Therefore, for each

subject the GI and C-pepI of each test food were

corrected by the relative amount of available carbo-

hydrate to be equivalent to 50 g of glucose.

Statistical analyses

The data of GIs and C-pepIs were analysed according

to the common mixed model for a randomized block

design where subject and experimental error were

random effects and test food was a fixed effect (Littell

et al. 2006). To satisfy the assumptions of the

constancy of the variance for all observations and

normality of the data, a logarithmic (base 10)

transformation was made on GIs. The precisions of

the estimated means were expressed through 95%

confidence intervals (CIs). For GI, the means of the

test foods and the endpoints of the 95% CIs were

back-transformed to the original scale. The pair wise

differences in the means between oat bread and the

other tests foods were tested by using two-sided

Dunnett’s test (Westfall et al. 1999). The analyses

were carried out by the MIXED procedure in

version 9.2 of the SAS/STAT software (SAS Institute

Inc. 2009).

Results

The fibre contents of the breads

The only source of dietary fibre in oat bread was oat,

whereas the buckwheat bread and lingonberry bread

had equal amounts of fibre from CMC, oat and

buckwheat or lingonberry (Tables I and II). The

amounts of oat fibre in each portion were 3.3, 3.6 and

7.6 g for oat–lingonberry, oat–buckwheat and oat

bread, respectively. In buckwheat bread and lingon-

berry bread, 50% of available carbohydrates were from

buckwheat flour or potato flour, respectively, 40%

from oat and 10% from syrup. In oat bread, the

sources for available carbohydrates were oat flour

(60%), potato flour (35%) and sugar beet

syrup (10%).

Serum responses

Oat bread resulted in a lower increase in serum glucose

levels than glucose or other test foods (Figure 1). The

Table II. The carbohydrate compositions of test foods (g/100 g) and the carbohydrate content of each test food serving (g).

Oat bread Lingonberry bread Buckwheat bread Buckwheat porridge

Test foods (g/100 g)

Total sugars 1.9 1.6 2.9 0.2

Starch 43 41 38 11

Total dietary fibre 5.5 7.6 6.7 0.8

Soluble fibre 3.0 3.0 3.0 n.a.*Insoluble fibre 2.5 4.5 3.6 n.a.

Test food servings (g)

Available carbohydrate 67 59 64 57

Total dietary fibre 7.6 10 10 4.3

* n.a. not analysed.

Table I. The ingredients of the bread doughs and porridge (g/100 g).

Oat bread Lingonberry bread Buckwheat bread Buckwheat porridge

Oat flour 19 24 17 0

Oat gruel (oat 85 g/l) 27 27 25 0

Buckwheat flour 0 0 23 0

Buckwheat bran 0 0 3 0

Finax/wheat starch 10 0 0 0

CMC 0 2 2 0

Syrup 4 4 3 0

Potato flour 13 15 0 0

Lingonberry fibre 0 2 0 0

Buckwheat flake 0 0 0 14

Non-carbohydrate ingredients 27 26 27 86*

* Only water was added to flakes prior cooking.

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main serum glucose peak after consuming glucose can

be seen after less than 30 min, whereas the main peak

of all test food comes later, with oat–buckwheat bread

having the slowest increase in serum glucose levels

(peak at 45 min).

The mean fasting levels of C-peptide responses vary

among the test foods due to the small number of test

persons (Figure 1e–h). C-peptide being the precursor

of insulin is secreted in cycles, and the fasting level

depends on the phase of the cycle. Glucose was tested

three times for each test person, so the fasting level of

C-peptide for glucose is likely to be close to the normal

average level. The oat–lingonberry bread had the

lowest C-peptide response, whereas oat–buckwheat

bread and oat bread had the highest response. The

C-peptide responses followed the glucose responses.

The C-peptide responses of oat bread and buckwheat

porridge increased at early stage similar to glucose

response, whereas the oat–lingonberry fibre bread and

oat–buckwheat bread resulted in slower responses.

Glycaemic and C-pepI

The estimated mean glycaemic and C-pepIs of test

foods are presented in Table III. The GI of oat bread

tended to be lower than the GIs of oat–buckwheat

Serum glucose (mg/dl)

Oat bread Oat bread200

180

160

140

120

100

80

60

14

12

10

8

6

4

2

0

0 30 60 90 120 0 30 60 90 120

(a) (e) Serum C – peptide (ng/ml)

200

180

160

140

120

100

80

60

200

180

160

140

120

100

80

60

14

12

10

8

6

4

2

00 30 60 90 120

0 30 60 90 120

0 30 60 90 120

0 30 60 90 120

0 30 60 90 120

0 30 60 90 120

(b)

(c)

200

180

160

140

120

100

80

60

(d)

(f)

14

12

10

8

6

4

2

0

14

12

10

8

6

4

2

0

(g)

(h)

Lingonberry breadLingonberry bread

Buckwheat bread

Buckwheat porridge Buckwheat porridge

Buckwheat bread

Time (min) Time (min)

Figure 1. Serum glucose (on the left) and C-peptide responses (on the right) for test foods as arithmetic means of raw (uncorrected) data of all

test persons. The response curves to glucose are shown as dotted line in each figure for comparison. The bars represent the SD, which for glucose

are only shown with oat bread response curves.

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bread or porridge, whereas GI of oat bread containing

lingonberry fibre did not statistically differ from GI of

oat bread. Buckwheat porridge had the lowest mean

C-pepI (77), and lingonberry bread had the highest

C-pepI (119) but when comparing the other foods to

oat bread the differences were not statistically

significant. The variation in fasting values affected

the IAUC values for C-peptide and thus caused large

variation in C-pepI values and low precision in the

estimated means as shown by the wide CIs (Table III).

Discussion

In this study, the glycaemic and C-pepIs of four

foodstuffs containing dietary fibre from three different

sources (oat, buckwheat and lingonberry) were

determined. High plasma insulin values are likely to

reflect insulin resistance, and high insulin levels are a

predictor of the development of T2D (Cefalu 2001).

Insulin resistance syndrome is a risk factor for

coronary heart disease in non-diabetic men (Lempiai-

nen et al. 1999). In cohort studies, it has been

concluded that the intake of cereal fibre but not fruit or

vegetables is associated with lower incidence of T2D

(Montonen et al. 2003). Also among cereals the

molecular structure of dietary fibres influences

mechanisms involved in blood glucose and insulin

regulation (Gemen et al. 2011).

In our study, the mean GI was 32 for oat bread, 58

for oat–buckwheat bread, 47 for oat–lingonberry fibre

bread and 71 for buckwheat porridge. All three

breads tested were based on oat flour and contained

5.5–7.6% dietary fibre, whereas in porridge the only

source of fibre was buckwheat (Table I). The results

indicate that oat affects the GIs of buckwheat bread

and lingonberry bread more than dietary fibres of

buckwheat or lingonberry. This is an important

finding, because only one-third of the fibre content

of lingonberry and buckwheat bread was of oat flour

origin, one-third of CMC and one-third of the

lingonberry or buckwheat, respectively. Oat is known

to have a low GI which is believed to be due to

b-glucan. Atkinson et al. (2008) summarized the GIs

of oat bread in published studies to be between 44 and

65. Shen et al. (2011) tested the hypoglycaemic effect

of oat products rich in b-glucan in diabetic mice, and

the results indicated that oat increased the secretion of

insulin and glucagon-like peptide-1 and also decreased

the free fatty acid level and improved insulin sensitivity

index and peroxisome proliferators activator receptors

g (PPARg). b-Glucan thus has many beneficial effects

on energy metabolism.

GI for buckwheat bread has been determined at

least in two previous experiments (Atkinson et al.

2008). GI and insulin index for buckwheat grains and

bread containing 50% buckwheat flour and 50%

wheat flour have been determined earlier as compared

to wheat bread instead of glucose (Skrabanja et al.

2001). The GIs (means ^ SEM) were 64 ^ 10 and

67 ^ 10 and insulin indexes 52 ^ 11 and 72 ^ 10 at

120 min for grains and bread, respectively. In their test

the amount of available carbohydrate was only 21 g,

and the volunteers also consumed butter, cheese and

coffee or tea. Despite these differences in the

experimental protocol, the mean GIs of buckwheat

bread and porridge in this study were close to these

results. In the study of Yang et al. (2006), the average

GIs of buckwheat powder, noodles and bread varied

between 54 and 67. They concluded that processing of

food influences the values. The insulin (measured as

C-peptide) responses to buckwheat of the current

experiment were, however, higher than those of

Skrabanja et al. (2001), most likely due to differences

in the experimental design.

In vitro studies by Takahama and Hirota (2010)

indicate that buckwheat starch is digested slowly in the

intestine. Buckwheat contains iminosugar D-fagomine

that slows down the postprandial glucose release from

oligomeric and polymeric carbohydrates by inhibiting

intestinal disaccharidases. It structurally resembles

D-glucose and D-mannose. D-Fagomine shifted the

time of maximum blood glucose concentration from

15 to 30 min in rats (Gomez et al. 2012). Similarly, the

maximum blood glucose caused by buckwheat bread

was shifted to 45 min (Figure 1c). This shift was,

however, not seen by buckwheat porridge which

resulted in the highest glucose response. In our

experiment, the amount of available carbohydrates

was highest in buckwheat porridge. Starch does not

break down when cooking porridge, whereas in bread

making starch degrades. Interestingly, even though

there were no statistically significant differences in the

mean C-pepIs between the different foods tested,

the buckwheat porridge having the highest GI value

has the lowest C-pepI value. Similar effect has been

seen with rye products (Leinonen et al. 1999; Hatonen

Table III. Estimated (model-based) means for glycaemic and C-peptide indexes of test foods and 95% CIs for the means.

GI C-pepI

Food n Mean 95% CI P-value for oat bread versus food Mean 95% CI P-value for oat bread versus food

Oat bread 8 32 20–52 100 46–154

Lingonberry bread 6 47 28–81 0.43 119 60–178 0.85

Buckwheat bread 8 58 36–94 0.10 105 51–160 0.99

Buckwheat porridge 7 71 43–118 0.03 77 20–133 0.73

Note: n ¼ number of subjects which varied because of voluntarines.

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et al. 2006; Rosen et al. 2009). The low insulin

response could explain the delayed glucose decline

which results in larger IAUC and thus higher GI.

Recently, a fermented oatmeal drink containing

bilberries has been found to give a low insulin response

as compared to glucose response (Granfeldt and

Bjorck 2011). It is possible that the berry fibres or

phenolic compounds attached to it slow down the

digestion of carbohydrates. Berries such as lingonberry

and bilberry are known to be a rich source of

proanthocyanidins and phenolic acids (Mattila et al.

2006; Hellstrom et al. 2009), which might affect

the insulinaemic responses. Torronen et al. (2012)

reported a berry meal to result in a postprandial

glucose and insulin responses low at 15 min and high

at 90 min as compared to control meal similarly to the

profiles caused by lingonberry fibre bread (Figure 1b

and f). They believed that the beneficial effect of

barriers on postprandial responses was mainly caused

by the phenolic compounds of the berries, and less

by berry fibre and semi-solid consistency of the berry

meal. The differences in the slopes of C-peptide

responses in our study might be due to different

structures of test foods. Lingonberry and buckwheat

breads contained CMC which makes a gel-like

structure. According to sensory evaluation comments

these breads were rubbery and moist whereas oat

bread was more porous and crumble. Furthermore,

CMC increases the viscosity of small intestine juice

and thus has a postprandial hypoglycaemic effect

(Brenelli et al. 1997).

FAO/WHO (1998) recommends using a minimum

of seven test persons for GI tests and performing the

test of the reference food at least three times in each

subject. In our data, the CIs for the mean insulin

indexes of the test foods were wide indicating that the

number of 6–8 test persons was not sufficient for firm

conclusions. In the statistical analysis, the magnitude

of the variability of individual C-pepIs could be

divided into two components, variance between

subjects and error variance. In our experiment, the

variance component estimates were 2983 and 2521 for

the between-subject and error variation of insulin

indexes, respectively, and thus 46% of the total

variation in C-pepIs was attributable to experimental

error. Even though the evening meal was standardized

and test persons were informed to avoid exercise,

normal life is a source of error variation. Furthermore,

insulin release from pancreas oscillates with a period of

3–6 min causing error variation in serum C-peptide

concentrations. This could be reduced by taking more

than one fasting sample per each subject before eating

test foods. Furthermore, according to the results of

Hatonen et al. (2006) testing test foods twice would

diminish error variation in GI measurements. In

their experiment, the coefficient of variation was

24% for a test food (white bread) measured on two or

three occasions and 43% for the food tested only

once. Consequently, to diminish the magnitude of the

error variance of C-pepIs, either the tests of all foods

should be repeated and/or the number of test persons

increased. According to the power analysis which was

based on the C-pepI means in Table III and on the

variance component estimates above, 32 subjects

would be needed in order the F test for the main

(overall) effect of test food to have power of 0.81.

However, with 32 subjects the expected standard error

of a test food mean will be 13 units and the expected

width of the 95% CI for a mean will be 52 units in our

study (evaluated as in Gbur et al. 2012). To halve the

standard error and the width of the CI, 130 subjects

would have been needed in our experiment. The

number of C-peptide responses published is still

scarce, and further studies are needed. Also in relation

to metabolic disorders, the focus should be more on

the effect of diet on insulin than on bare GI values.

Conclusions

As a conclusion, oat fibre seems to have a very efficient

effect on glucose response, and buckwheat and

lingonberry fibres can be used to get variation in low

GI diet and food formulations. Buckwheat has an

interesting effect on insulin response, and it should be

studied more.

Acknowledgements

The authors thank the test persons and corresponding

doctor Maria Tiusanen. Dr Tuula Sontag-Strohm is

acknowledged for assistance and recipes for buck-

wheat bread.

Declaration of interest: This study was funded by

Finnish Cultural Foundation. The authors report no

conflicts of interest. The authors alone are responsible

for the content and writing of the paper.

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