Download Carbohydrate-Rich Foods in the Treatment of the Insulin Resistance

Comprehensive Summaries of Uppsala Dissertations
from the Faculty of Medicine 1100
_____________________________
_____________________________
Carbohydrate-Rich Foods
in the Treatment of the
Insulin Resistance Syndrome
Studies of the Importance of the
Glycaemic Index and Dietary Fibre
BY
ANETTE JÄRVI
ACTA UNIVERSITATIS UPSALIENSIS
UPPSALA 2001
Dissertation for the Degree of Doctor of Philosophy (Faculty of Medicine) in Geriatrics
- Clinical Nutrition presented at Uppsala University in 2001
ABSTRACT
Järvi, A. 2001. Carbohydrate-rich foods in the treatment of the insulin resistance
syndrome. Studies of the importance of the glycaemic index and dietary fibre. Acta
Universitatis Upsaliensis. Comprehensive Summaries of Uppsala Dissertations from the
Faculty of Medicine 1100. 81pp. Uppsala. ISBN 91-554-5166-7.
The glycaemic responses to various carbohydrate-rich foods are partly dependent on the
rate at which the carbohydrate is digested and absorbed. The glycaemic index (GI) is a
way of ranking foods according to their glycaemic response and is recommended as a
useful tool in identifying starch-rich foods that give the most favourable glycaemic
response. This investigation was undertaken to determine whether carbohydrate-rich
foods with a low GI and a high content of dietary fibre (DF) could have beneficial
metabolic effects in the insulin resistance syndrome. This question was addressed both
in single-meal studies and in randomised controlled clinical trials. Starch-rich foods
with low GI values incorporated into composite meals resulted in lower postprandial
responses of both glucose and insulin than foods with a high GI in meals with an
identical macronutrient and DF composition, in subjects with type 2 diabetes. After
three weeks on a diet including low GI starchy foods metabolic profile was improved in
subjects with type 2 diabetes, compared with a corresponding high GI diet. The glucose
and insulin responses throughout the day were lower, the total and low density
lipoprotein cholesterol was decreased, and the fibrinolytic activity was normalised. In
subjects with impaired insulin sensitivity and diabetes low GI foods rich in soluble DF
for breakfast gave a more favourable metabolic profile, with smaller glucose
fluctuations from baseline during the day, than a breakfast with high GI foods low in
DF. A low GI breakfast high in DF also resulted in lower responses of insulin and Cpeptide after breakfast and a lower triacylglycerol response after a standardised lunch.
However, none of the tested breakfasts improved the glucose and insulin responses after
lunch. Similar results were obtained in obese subjects after including a breakfast with a
low GI high in soluble DF for a period of four weeks in comparison with a breakfast
with a high GI and low content of DF.
These results support the therapeutic potential of a diet with a low GI in the treatment of
diabetes and also in the treatment of several of the metabolic disturbances related to the
insulin resistance syndrome.
Key words: Diabetes, insulin resistance, carbohydrates, starch, glycaemic index, dietary
fibre, postprandial, second-meal, glucose, insulin, triacylglycerol.
Anette Järvi, Department of Public Health & Caring Sciences, Section for
Geriatrics/Clinical Nutrition Research, Uppsala University, Box 609, SE-751 25
Uppsala, Sweden
© Anette Järvi 2001
ISSN 0282-7476
ISBN 91-554-5166-7
Printed in Sweden by Uppsala University, Tryck&Medier, Uppsala 2001
List of papers
This thesis is based on the following papers, which are referred to in the
text by their Roman numerals:
I.
Järvi AE, Karlström BE, Granfeldt YE, Björck IME, Vessby
BOH & Asp N-G. The influence of food structure on postprandial
metabolism in patients with non-insulin-dependent diabetes
mellitus. The American Journal of Clinical Nutrition
1995;61:837-42.*
II.
Järvi AE, Karlström BK, Granfeldt YE, Björck IME, Asp N-G &
Vessby BOH. Improved glycemic control and lipid profile and
normalized fibrinolytic activity on a low glycemic index diet in
type 2 diabetes mellitus patients. Diabetes Care 1999;22:10-18.*
III.
Järvi A, Granfeldt Y, Karlström B, Berglund L, Björck I &
Vessby B. A low glycaemic index breakfast high in soluble
dietary fibre efficiently suppresses non-esterified fatty acids and
gives a favourable triacylglycerol response after an ensuing meal
in men with impaired glucose tolerance. Manuscript.
IV.
Järvi AE, Liljeberg Elmståhl HGM, Karlström BE, Björck IME &
Vessby BOH. Lower postprandial triacylglycerol levels and more
efficiently suppressed non-esterified fatty acids in serum after
lunch following four weeks with a low glycaemic index-high
dietary fibre breakfast. Manuscript.
* Reprints were made with the permission of the publishers.
Contents
Abbreviations
Background
Introduction
Dietary carbohydrates in the treatment of diabetes
The glycaemic index
Glycaemic load
Determination of glycaemic index
Food factors influencing the glycaemic index
Glycaemic index, diabetes and hyperlipidaemia
Glycaemic index, satiety and weight management
Second-meal effects
Clinical use if the glycaemic index concept
Aims of the investigations
Subjects
Study design
Methods
Results
Discussion
Main findings
Glucose and insulin responses
Insulin sensitivity
Lipoproteins
Second-meal effects
Effects of fermentation
Effects on body weight
Carbohydrate-rich foods in the optimal diet in the insulin
resistance syndrome
What is considered to be a low glycaemic index?
The glycaemic index concept revisited
Methodological concerns, strengths and limitations of the studies
Conclusions
Future perspectives
Acknowledgements
References
6
7
7
8
9
9
10
10
12
12
13
13
15
16
18
21
38
48
48
49
51
51
53
55
55
56
58
58
59
61
62
64
66
Abbreviations
Apo
AUC
BMI
BS
CHD
C-peptide
CVD
DF
DM
DR
E%
FAO
GI
HbA1c
HDL
IR
kcal
kJ
LDL
Lp
LPL
M/I
MUFA
M-value
NEFA
OGTT
PAI-1
PUFA
SAFA
SD
TAG
VLDL
WHO
W/H ratio
WWB
Apolipoproteins
Area under the curve
Body mass index
Blood sampling
Coronary heart disease
Connecting peptide
Cardiovascular disease
Dietary fibre
Diabetes mellitus
Dietary record
Energy per cent
Food and Agriculture Organization
Glycaemic index
Glycosylated haemoglobin
High density lipoprotein
Insulin resistance
Kilocalorie
Kilojoule
Low density lipoprotein
Lipoprotein
Lipoprotein lipase
Insulin sensitivity index
Monounsaturated fatty acids
Glucose disposal (measurement of insulin sensitivity)
Non-esterified fatty acids
Oral glucose tolerance test
Plasminogen activator inhibitor-1 activity
Polyunsaturated fatty acids
Saturated fatty acids
Standard deviation
Triacylglycerol
Very low density lipoprotein
World Health Organisation
Waist to hip ratio
White wheat bread
6
Background
Introduction
Obesity, especially abdominal obesity, is a well known risk factor for type
2 diabetes, cardiovascular disease (CVD) and several of the metabolic
disorders that are directly or indirectly related to the insulin resistance
syndrome [1, 2]. As a consequence of a changing life-style, especially
changes in diet and physical activity, the incidence of obesity is increasing
epidemically. It is escalating worldwide and it is estimated that by the year
2025 as many as 300 million people will be obese [3, 4]. The obesogenic
environment, also known as a ‘pathoenvironment’, has been suggested as
the driving force for the rising prevalence [5]. In other words, this means
that obesity should be regarded as a normal response to an abnormal
environment [6]. As a consequence of the drastically increasing incidence
of obesity there is also a rapid rise in the incidence of diabetes. Diabetes
develops in predisposed individuals as a consequence of impaired insulin
sensitivity, in combination with inadequate glucose induced insulin
secretion. The number of adults with diabetes is predicted to rise from 135
million in 1995 to about 300 million in the year 2025 [7]. The metabolic
disorders that are seen in diabetes and which are part of the insulin
resistance syndrome are associated with a high risk for CVD and related
mortality and other secondary complications in diabetes.
Coronary artery disease is the major cause of mortality in patients with
diabetes. The greatest risk factors once diabetes has developed are
increased concentrations of low density lipoprotein (LDL) cholesterol,
decreased concentrations of high density lipoprotein (HDL) cholesterol,
elevated blood pressure and hyperglycaemia [8]. A high postprandial blood
glucose response is associated with micro- and macro-vascular
complications in diabetes, and is more strongly associated with the risk for
CVD than are fasting glucose levels [9-11]. Non-esterified fatty acid
(NEFA) suppression is impaired in obese persons, persons with impaired
glucose tolerance and those with type 2 diabetes. Failure to suppress the
NEFA supply in a normal way in the postprandial period is likely to impair
insulin action and may lead to sustained production of very-low density
lipoprotein (VLDL) and impaired clearance of triacylglycerol (TAG)-rich
lipoproteins in the postprandial period [12]. High postprandial TAG
concentrations are associated with an increased risk of developing
7
atherosclerotic cardiovascular disease, probably because of reduced
lipoprotein lipase (LPL) activity, causing a change in the composition of
the lipoproteins towards more small dense atherogenic LDL particles [13,
14]. Intensified blood glucose control has been shown to lead to a
substantial decrease in the risk of microvascular disease in type 2 diabetes
[15]. However, the major complications of type 2 diabetes is macrovascular
disease, which appears to be more effectively prevented by treatment of
other cardiovascular risk factors such as dyslipidaemia [16].
Strategies for prevention and treatment of obesity and type 2 diabetes
should mainly focus on life-style behaviour such as diet and physical
activity [3]. Since most of the day is spent in a postprandial state, it is of
great importance to find an effective dietary treatment that will improve the
insulin economy and result in lower and sustained postprandial glucose and
TAG responses with smaller postprandial peaks and intra-day excursions.
The purpose of the present work was to address the question whether
carbohydrate-rich foods with a low glycaemic index (GI) and a high
content of dietary fibre (DF) could have beneficial effects on components
of the insulin resistance syndrome, on type 2 diabetes and on its risk factors
for secondary complications.
Dietary carbohydrates in the treatment of diabetes
Diet is the cornerstone of all treatment in diabetes mellitus. As for all kinds
of treatment in diabetes, the aim of the nutritional management is to
optimise the glycaemic control and reduce risk factors for cardiovascular
disease and nephropathy [17-19].
As early as in 1939 it was shown that carbohydrate-containing foods with
the same macronutrient composition could differ in the glycaemic
responses that they produced [20]. In 1973, Otto et al [21] classified
carbohydrate-rich foods according to the glycaemic response. This
classification of carbohydrate-rich foods was based on the size of the
carbohydrate molecule, and starchy foods were classified as a
homogeneous group. It was believed that all starches were digested
similarly and that their digestion was slower than that of most lowmolecular-weight carbohydrates or foods containing such carbohydrates,
e.g. fruit or dairy products, resulting in smaller increases in blood glucose.
Further studies showed differences, between starch-rich foods with similar
macronutrient compositions [22-24], confirming that the glycaemic
8
response is strongly related to the rate of digestion of starchy foods [25]. A
great deal of interest has been focused on the effects of DF on the
glycaemic control in subjects with diabetes. High intakes of DF have been
shown to improve the metabolic control in patients with diabetes [26-28].
Many studies have dealt with effects of soluble DF. Both in acute and longterm experiments it was shown that viscous DF tended to improve the
blood glucose control and had favourable effects on the blood lipid status
in subjects with diabetes [29-32].
The glycaemic index
The glycaemic response to different starchy foods can differ greatly, and
one way of classifying food products according to their glycaemic response
is by estimating their GI, a concept that was introduced by Jenkins in 1981
[33]. The GI value should be regarded as a supplement to information
given in food tables.
“The glycaemic index is defined as the incremental area under the blood
glucose response curve of a 50 g carbohydrate portion of a test food
expressed as a percent of the response to the same amount of
carbohydrates from a standard food taken by the same subject.”
Definition given by the FAO/WHO Expert consultation, 1997 [34]
Both the test food and the reference food are given in 50 g glycaemic
carbohydrate portions (total carbohydrate minus DF) and either white bread
or glucose can be used as a reference food. GI values obtained with white
bread as a reference are about 1.4 times higher than those obtained with
glucose as a reference [34, 35].
In this thesis, and in the included papers, all GI values are given with white
bread as a reference food (white bread GI=100).
Glycaemic load
Not only the type of carbohydrate-rich food but also the total amount of
carbohydrates has to be taken into consideration. The term glycaemic load
represents both the quality and the quantity of the carbohydrates in a meal
[36, 37] and is an indicator of the blood glucose response or of the insulin
demand by the total carbohydrate intake. Each unit of dietary glycaemic
9
load represents the equivalent of 1 g of carbohydrate from white bread or
pure glucose [38]. Foods with high GI values and a high content of
carbohydrates have the highest glycaemic load.
Determination of glycaemic index
At least six subjects are required to determine the GI value of a food. The
reference food should be given at least three times on different days in each
subject, since blood glucose levels vary considerably from day to day
within subjects. Up to four test foods can be investigated in the same series,
on a total of seven test occasions in each subject, the foods being given on
separate days. The GI determination should be performed in the morning
after a 10-12-hour overnight fast, and a standardised drink of water, coffee
or tea should be given with each meal. The area under the curve is
calculated geometrically as the incremental area under the blood glucose
response curve, ignoring the area beneath the fasting level, by applying the
trapezoidal rule. Blood glucose is often measured in capillary whole blood,
since this is easier to obtain and the rise in blood glucose is greater and less
variable than in venous plasma glucose [34, 35]. It has been suggested that
ideally the measurement should be continued until the blood glucose
returns to the baseline levels, which means that blood samples should be
taken for up to 120 minutes after the start of the test meal in healthy
subjects and for up to 180 minutes for subjects with diabetes [35]. In the
FAO/WHO expert consultation it is recommended that the duration of
blood sampling should be 120 minutes after test meal ingestion in both
healthy and diabetic subjects [34]. A number of methods have been used
for GI determination and there is still some controversy regarding the
length of blood sampling.
The insulin index can be determined in the same way as the GI. There is a
positive correlation between the GI and the insulin response to starch-rich
foods [39-41].
Food factors influencing the glycaemic index
The glycaemic response to foods cannot be predicted simply from their
chemical composition, and despite an apparent lack of difference in their
macronutrient and DF compositions, different carbohydrate-rich foods can
produce very divergent glycaemic responses. The GI of a food is
10
influenced by the rate of digestion and absorption of the carbohydrates
[42]. Various food properties, other than the molecular size of the
carbohydrate component, have been shown to be important determinants of
the glycaemic response [43-45]. These food factors are related to the choice
of raw material and to the processing of foods [41]. One of the major
factors appears to be the food structure, and processes that reduce particle
size will increase the enzymatic availability of starch and therefore the
glycaemic response [46]. Usually, the more processed a food is, the higher
the glycaemic response it will produce [43, 47-51]. Decreasing the particle
size by grinding increases the surface area, which in turn will increase the
rate of digestion and absorption and hence the insulin secretion. The nature
of the starch has been shown to influence the glycaemic response, with a
lower response after ingestion of starch-rich foods with a high amylose
content [52-55]. The degree of gelatinisation that occurs during heat
treatment and retrogradation of gelatinised starch also have a major impact
on the GI in food [47].
The glycaemic response is also influenced by the content and type of DF in
the food, but high DF foods are not necessarily synonymous with low GI
foods [33, 56, 57]. Different types of DF have different effects. A high
content of purified soluble DF, such as guar and psyllium, improves the
glycaemic response [58]. However, viscous naturally occurring DF in
commonly eaten cereal products only has marginal reducing effects on the
GI [41]. The presence of certain organic acids, produced during sourdough
fermentation and when vinegar is added to starch-rich meals [59-61], and
antinutrients, such as lectins, phytate and polyphenols present in
leguminous food, have also been shown to lower the glucose response [62,
63]. Addition of fat and protein to a meal reduces the glycaemic response
[33, 46, 64, 65]. Addition of fat decreases the postprandial blood glucose
response without altering the insulin response [66, 67]. It has been argued
that differences in GI between foods diminish when the foods are
incorporated into normal meals, as the effects of protein and fat may
influence insulin secretion and gastric emptying. However, these effects
are not seen unless relatively large amounts of about 25 g of fat or protein
per 50 g of carbohydrates are added, which is not likely to occur in normal
meals [68, 69]. Although addition of fat and protein to a meal containing
carbohydrates may result in a lower glucose response, the relative
difference in response between starch-rich foods with different GIs remains
[39] Furthermore, not only the amount but also the type of fat seems to be
related to the postprandial glycaemic response [70-72]. However, it
should be stressed that low GI foods high in fat, particularly of saturated
11
origin, should not usually be recommended. In the case of some foods,
several factors can be responsible for their low GI values. Pulse vegetables,
for example, have a high content of soluble DF and a high amylose content.
Besides, their cell structure remains intact and after boiling, and they have
a high content of antinutrients.
Glycaemic index, diabetes and hyperlipidaemia
Several experimental studies have shown that a diet with a low GI has
favourable metabolic effects in subjects with type 2 diabetes [73-77] and
hyperlipidaemia [78-80]. Also, in type 1 diabetes a low GI diet has been
shown to improve the glycaemic control [81-83] and to lower the insulin
requirements [84], as well as to reduce the number of hypoglycaemic
events [85]. In a meta-analysis of 11 medium- to long-term studies
specifically dealing with the GI approach, that were carried out between
1987 and 1992 in subjects with diabetes or hyperlipidaemia and in healthy
subjects, a low GI diet was shown to lead to an average decrease in fasting
blood glucose by 5 %, average blood glucose by 6 %, glycosylated
haemoglobin A1c (HbA1c) by 9 %, fructosamine by 8 %, urinary C-peptide
by 20 %, total cholesterol by 6 %, and TAG by 9 %. Three of the four
studies concerning glucose tolerance showed improvements [76]. In all but
one study improvements in the carbohydrate and lipid metabolism were
observed. The lack of effect in one study might have been due to the small
difference in GI values between the compared diets. The GI value of the
diets investigated was on average reduced from 91 to 75 (white bread
=100). However, in many of the previous evaluations of the GI concept in
mixed meals there have also been differences in the type and amount of
DF, differences in the macronutrient composition, and differences in the
types of food tested, making it difficult to interpret the results. Other
factors that can make it hard to distinguish between effects of differences in
GI between tested diets are changes in body weight during the studies and
alterations in the treatment of diabetes and other, concomitant diseases.
Glycaemic index, satiety and weight management
The results obtained in the study by Jenkins et al in 1988 [86], who
investigated the effect of low GI starchy foods in the diabetic diet,
indicated that use low GI starchy foods may enhance weight loss. Low GI
foods have been shown to be associated with a greater feeling of satiety and
12
an inverse relationship has been found between peak satiety scores and
both the GI and the insulin index [87, 88]. The particle size of cereal foods
influences not only the glucose and insulin response but also the degree of
satiety after a meal [88]. A meal with a high GI induces hormonal and
metabolic changes that promote excessive food intake in obese subjects,
which suggests an advantageous effect of a low GI diet in the treatment of
obesity [89]. In a retrospective cohort of obese children a 4.3-month
intervention period with a low GI diet significantly decreased the body
weight and body mass index (BMI), compared with a reduced fat diet [90].
These results are promising, but additional trials are needed to investigate
the long-term weight loss and capability of weight maintenance.
Second-meal effects
Single-meal studies in both healthy and diabetic subjects have shown that
the GI of carbohydrate-containing foods not only influences the immediate
postprandial metabolic response, but also modifies the postprandial
response after an ensuing standardised meal, the so called “second-meal”
effect [84, 91-95]. The rate of delivery of carbohydrates, and consequent
insulin secretion after the first meal, may be of importance for the
metabolic response to a subsequent meal. A “second-meal” effect has been
demonstrated from breakfast to lunch [84, 92, 93], and from an evening
meal to the succeeding breakfast [91, 96]. Different fibre supplements,
such as guar and psyllium in relatively large amounts, have shown a
beneficial second-meal effect in both healthy and subjects with diabetes
[97-99]. However, it has not been established whether a change in the
breakfast composition only, in the direction of a low GI and a high content
of soluble DF, can improve the metabolic response later during the day in
the longer term also
Clinical use of the glycaemic index concept
GI values obtained from GI tables [100] can be used for calculation of an
expected glycaemic response after a mixed meal [34, 101], with a good
correlation between the calculated meal GI and the observed glycaemic
responses to meals with equal nutrient compositions. When comparing GI
values of different foods, with the purpose of predicting their glycaemic
responses, it is important to make comparisons between foods within the
same food group that are eaten in roughly the same amounts. It is also
13
important to point out that the GI concept is most useful in comparisons of
starch-rich foods. The clinical usefulness of the GI concept is controversial;
one point of the criticism being that it may not be applicable to mixed
meals. Also, the long-term effects have been questioned [102, 103]. From
some studies it has been concluded that the GI can be predicted from the GI
of the different carbohydrate-rich foods included [40, 104, 105] whereas
other authors have concluded that differences in GI between foods are
considerably diminished when the foods are incorporated into composite
meals [102, 103]. However, the most relevant question is whether a low GI
diet improves the glycaemic control in the long term.
In spite of the number of studies showing that replacement of foods with a
high GI by those with a low GI results in improved glycaemic control and
reduced fasting serum lipids, there is still no international consensus as to
the clinical usefulness of the GI concept in the dietary management of
diabetes. In the nutritional recommendations for people with diabetes from
the Diabetes and Nutrition Study Group (DNSG) of the European
Association for the Study of Diabetes in 1988, the attitude towards low GI
foods was cautious. A carbohydrate intake of 50-60 E % was encouraged
and carbohydrate-containing foods rich in soluble DF were especially
advocated, and low GI foods such as pulses, oats and barley were regarded
as potentially beneficial foods. In the dietary recommendations from the
DNSG published in 1995, and revised in 1999 [17, 106, 107], a clear
position for an increase in carbohydrate-rich foods with a low GI was
taken. In the healthy eating guidelines for people with diabetes in Australia
and New Zealand the GI concept is promoted [108]. The FAO/WHO [34]
also recommends a diet with a low GI, not only for people with diabetes
but also for those with in hyperlipidaemia or obesity, and for healthy
subjects. On the other hand, in the American Diabetes Association’s
“Nutrition Recommendations and Principles for People with Diabetes
Mellitus” [19, 109], it is stressed that the first priority should be given to
the total amount of carbohydrate consumed, rather than to the source of
carbohydrate. One of their stated reasons for not recommending a low GI
diet is that it would severely limit the food choice [18].
14
Aims of the investigations
The overall aim of these investigations was to evaluate the effects of
carbohydrate-rich foods in the treatment of the insulin resistance syndrome
with special reference to the importance of the GI and DF.
The specific aims were:
ƒ to evaluate the effect of differences in GI, achieved by varying the
botanical and physical structure of the starchy foods, on the
postprandial blood glucose and insulin responses in subjects with
type 2 diabetes, in order to establish whether the GI concept is
applicable to composite meals (paper I);
ƒ to evaluate the effects of pronounced differences in GI, mainly
achieved by varying the botanical structure of the starchy foods, on
the metabolic control in subjects with type 2 diabetes, in order to
establish whether the GI approach is useful in a realistic diabetic diet
for a relatively long period of time (paper II);
ƒ to evaluate the metabolic response postprandially and throughout the
day, with special emphasis on the second-meal response, after
breakfast meals with different GI values and amounts and types of
DF in subjects with impaired insulin sensitivity (paper III);
ƒ to evaluate metabolic effects of a period with either a low GI and
high DF breakfast, or a high GI and low DF breakfast, in an
otherwise unchanged diet in overweight men with special reference
to the second-meal effect after a subsequent standardised lunch
(paper IV).
15
Subjects
Paper I
Study I (paper I) was divided into two parts with ten subjects with type 2
diabetes in each part. The first part comprised five women and five men,
with a mean age of 57 years (range 36-72 years). Body weight was 78.2 r
14.6 kg (mean r SD), with a body mass index (BMI) of 26.7 r 3.7 kg/m2.
Six of the subjects were being treated with sulphonylurea, three of them in
combination with metformin; the other four were treated with diet only. In
the second part eight women and two men with a mean age of 61 years
(range 36-77 years) were studied. Their mean body weight was 73.4 r 8.2
kg, with a BMI of 27.0 r 2.9 kg/m2 (Table 1). Five of these ten subjects
were treated with sulphonylurea and five with diet only. The duration of
diabetes varied between 0.5 and 28 years in the subjects of the first part and
between 0.5 and 10 years in those of the second part, respectively. The
subjects were recruited from local primary health care centres in Uppsala.
Paper II
Twenty patients with type 2 diabetes mellitus participated in study II (paper
II). Five of them were women and 15 were men with a mean age of 66
years (range 50-77 years). Their mean body weight on admission was 76.3
r 7.5 kg, with a BMI of 25.3 r 2.7 kg/m2. The average HbA1c was 7.2 r 1.4
% (Table 1). Four of the patients were treated with diet only and the other
16 were dietary treated in combination with oral antidiabetic drugs. One
was being treated with metformin only and the other 15 were taking
sulphonylurea, nine in combination with metformin. The duration of
diabetes varied between 0.5 and 17 years. The subjects were recruited from
local primary health care centres in Uppsala.
Paper III
Twelve overweight men with a mean age of 73.4 r 1.2 years (range 71-75
years) with impaired insulin sensitivity participated in study III (paper III).
Their mean body weight was 81.1 r 8.7 kg, with a BMI of 27.3 r 1.9
16
kg/m2. Eight had type 2 diabetes mellitus. The mean fasting plasma glucose
was 6.2 r 0.8 mmol/l (Table 1). None were being treated with oral
antidiabetic drugs or insulin. All subjects were non-smokers. The subjects
were recruited from an ongoing health survey of 70-year-old men.
Paper IV
Study IV (paper IV) initially comprised 15 overweight or obese men with a
mean age of 49.1 r 7.8 years (range 33-61 years). Two of them did not
complete the study. The mean body weight of the remaining 13 subjects
was 99.6 r 7.2 kg, with a BMI of 30.6 r 2.8 kg/m2 (Table 1) and a waist
circumference of 103.3 r 5.8 cm. At screening the mean fasting plasma
glucose was 5.3 r 0.4 mmol/l, fasting serum cholesterol 5.6 r 1.0 mmol/l,
fasting LDL-cholesterol 3.4 r 0.8 mmol/l and fasting serum triacylglycerol
2.1 r 1.2 mmol/l. None of the subjects were being treated with any
medication that could have influenced the glucose or lipid metabolism. The
subjects were recruited by advertisement in the local newspaper.
Table 1. Characteristics of the subjects in studies I – IV before entry into the studies.
Study I
Part 1
Study I
Part 2
Study II
Study III
Study IV
Type 2 DM
Type 2 DM
Type 2 DM
IR &
Type 2 DM
Overweight
or obese
n, total
10
10
20
12
13
Female/Male
5/5
8/2
5/15
0/12
0/13
Age (years)
57 (36-72)
61 (36-77)
66 (50-77)
73.4 (71-75)
49.1 (33-61)
Body weight (kg)
78.2 r 14.6
73.4 r 8.2
76.3 r 7.5
81.1 r 8.7
99.6 r 7.2
BMI (kg/m2)
26.7 r 3.7
27.0 r 2.9
25.3 r 2.7
27.3 r 1.9
30.6 r 2.8
P-glucose (mmol/L)
-
-
10.3 r 3.2
6.2 r 0.8
5.3 r 0.4
HbA1c (%)
-
-
7.2 r 1.4
-
4.4 r 0.2
Subjects
Mean r SD, (range). DM, diabetes mellitus; IR, insulin resistance
17
Study design
Paper I
This study was performed as a randomised crossover study. Each part of
the study consisted of a comparison between two test meals with different
GIs. The test meals were served at lunch after a standardised breakfast, and
were given in randomised order with one week in between. The meals were
composed in accordance with the dietary recommendations for people with
diabetes [110-112] and had an identical macronutrient and dietary fibre
composition but relatively large differences in GI. Blood glucose and
plasma insulin were measured before the test meal and 30, 60, 90, 120, 180
and 240 minutes after the meal for calculation of the area under the curve
(AUC). Plasma C-peptide was measured before and 60 and 180 minutes
after the meals. Serum cholesterol, serum TAG and HDL concentrations
were also measured before and 60 and 240 minutes after the meals.
Paper II
In this randomised crossover study the subjects were given two diets with
either a low or a high GI during two consecutive 3.5-week periods (Figure
1). Both diets were composed in accordance with dietary recommendations
for people with diabetes [110-112]. The two diets differed considerably in
GI, but did not differ in their macronutrient and dietary fibre composition.
At the entry and at the end of each dietary period the insulin sensitivity was
evaluated by the euglycaemic-hyperinsulinaemic clamp technique, and
blood samples were taken in the fasting state for determination of plasma
glucose, HbA1c, serum fructosamine, plasma insulin, plasma C-peptide,
serum lipoproteins, serum apolipoproteins, NEFA, fatty acid composition
of the serum cholesterol esters, serum tocopherols and plasminogen
activator inhibitor-1 (PAI-1) activity. In addition, blood samples were taken
throughout the day (profile days) for calculation of the AUC for glucose,
insulin, C-peptide and NEFAs. For AUC calculations of glucose and
insulin, blood samples were taken before and 60, 120, 180, 240, 300, 360,
480 and 540 minutes after breakfast. For AUC calculations of C-peptide,
serum lipoproteins and NEFA, blood samples were taken 120 and 300
minutes after breakfast. During profile days the subjects followed the study
diets, with breakfast at 08.00, lunch at 12.15, dinner at 16.15 and snacks at
18
10.00 and 14.00. Before entering the study the participants kept a 2-day
estimated dietary record, using household measures.
n=10
n=10
Weeks
0
ÏÏ
BS
Clamp
LOW GI
LOW GI
HIGH GI
HIGH GI
3.5
ÏÏ
BS
Clamp
ÏÏ
BS
Clamp
Figure 1. Design of study II. GI, glycaemic index; BS, blood sampling.
Paper III
In this randomised trial five bread- or cereal-based breakfasts, with
different GIs and with a varied type and amount of DF, were given to each
participant in varying order, followed by a standardised lunch after four
hours. Apart from the difference in GI and in the type and amount of DF,
the breakfast menus were matched for their contents of protein and fat, fat
quality and available carbohydrates. The study design made it possible to
address the question of whether other dietary factors, irrespective of the GI,
such the type and/or amount of DF, contributed to the second-meal
phenomenon. Blood samples were taken before and 30, 60, 90, 120, 180
and 240 minutes after each meal for measurement of glucose and insulin in
plasma and of cholesterol, TAG and NEFAs in serum.
19
Paper IV
In a randomised crossover design, subjects were given breakfast meals with
either a low GI and a high content of soluble DF (Low GI-High DF) or
with a high GI and a low content of DF (High GI-Low DF), as part of an
ordinary diet, for four weeks. Dietary periods were separated by a 3-week
washout period (Figure 2). Before and after each dietary period, and also
after the washout period, blood samples were taken in the fasting state for
measurement of blood glucose, HbA1c, plasma concentrations of
fructosamine, insulin and C-peptide, serum concentrations of TAG,
NEFAs, cholesterol, LDL-cholesterol and HDL-cholesterol, and PAI-1
activity, after a 12-hour overnight fast. At baseline and after each dietary
period, blood samples were taken for calculation of the AUC during the
day for glucose, insulin, C-peptide, TAG and NEFAs. During test days the
breakfasts were followed by a standardised lunch meal four hours later.
During both dietary periods, as well as during the washout period, the
subjects kept a 3-day weighed dietary food record.
n=8
LOW GI-HIGH DF
LOW GI-HIGH DF
WASH-OUT
n=5
Weeks 0
Ï
BS
HIGH GI-LOW DF
×
DR
HIGH GI-LOW DF
4
Ï
BS
×
DR
7
Ï
BS
×
DR
Figure 2. Design of study IV. BS, blood sampling; DR, dietary record
20
11
Ï
BS
Methods
Test meals and study diets
Paper I
Composite meals were created with starch-rich key foods with differences
in GI values as a basis. Differences in GI were mainly achieved by altering
the botanical and physical structures of the starchy foods. The starch-rich
key foods contributed with 50 g of the carbohydrates in all meals. Except
for the ingredients responsible for the differences in GI values, all
remaining ingredients in the two meals in each part of the study were
identical.
In the first part of the study, a meal containing pasta (Low GI) was
compared with a meal containing a white wheat bread (High GI). The
estimated GI values in these meals were 62 and 81 units, respectively. This
GI estimation was based on 94 per cent of the carbohydrates in the meals.
The calculated energy content was 650 kcal (2700 kJ), with an energy
percentage of 57, 18, and 25 for carbohydrates, protein and fat,
respectively. The nutrient compositions from chemical analyses are shown
in Table 2.
The differences in GI in the test meals were mainly due to differences in
the physical structure between pasta and white wheat bread but also to
some extent to differences in botanical structure between a whole and a
crushed apple. The durum wheat spaghetti in the Low GI meal was
industrially made (Storhushålls-spaghetti, Kungsörnen AB, Järna, Sweden).
The corresponding white wheat bread was made from the same type of
durum wheat and the same ingredients as were included in the spaghetti
and was baked in a home baking machine (Panasonic SD-BT 2P,
Matushiba Electric Trading, Osaka, Japan). The ingredients in the bread
were: 300 g durum wheat flour, 200 g water, 7.5 g monoglycerides, 3 g salt
and 3 g dry yeast. All ingredients were mixed, kneaded and fermented in
four steps and baked in the machine. The whole procedure took four hours.
After baking, the bread was allowed to cool to room temperature until the
next day. The bread and spaghetti were served with a sauce made from
margarine, wheat flour, low fat milk, smoked ham, mushrooms and leeks,
together with a salad made from white cabbage, peas, corn and red pepper
21
and a vinaigrette made from corn oil and vinegar (for amounts see paper I,
Table 2, Page 838 [113]). The spaghetti was boiled for 10 minutes in a
large amount of water. Immediately after boiling, the water was drained
through a colander. Before ingestion, both the spaghetti and the white bread
were baked in the oven together with the sauce and cheese.
In the second part of the study, a meal with parboiled rice, red kidney beans
and bread made from whole-wheat grain (Low GI), was compared with a
meal containing sticky rice, ground red kidney beans and bread made from
ground wheat (High GI). The GI values based on 95 per cent of the
carbohydrates in the meals were 58 and 80, respectively. The calculated
energy content was 670 kcal (2800 kJ) with an energy percentage of 53, 18,
and 29 for carbohydrates, protein and fat, respectively. The nutrient
compositions of the diets, obtained from chemical analyses, are shown in
Table 2.
The differences in GI values between these two meals were due to
differences in the chemical starch structure attributable to differences in the
amounts of amylose and amylopectin in the parboiled and sticky rice, and
differences in the botanical starch structure between the whole and the
ground red kidney beans and between bread made from whole wheat and
that made from ground wheat. The whole-wheat grain and the kidney beans
in the High GI meal were finely ground (Cemotec 1090 Tecator AB,
Höganäs, Sweden) to flour before preparation of the bread or meals. The
whole and the finely ground wheat grains was made into bread with the
following ingredients: 370 g whole or finely ground wheat, 520 g water, 93
g white wheat flour and 50 g yeast. The whole-wheat grain bread in the
high GI meal was made as follows: the whole-wheat grain was boiled in
370 g of water for 20 minutes and allowed to cool to room temperature.
The remaining ingredients were then added. The dough was left to rise for
45 minutes and then put in a baking-tin, and proved for 45 minutes. The
bread was baked at 200 qC for 45 minutes. The ground wheat grain bread
was made as follows: hot water (80 qC) was poured over the milled grain
and then cooled. The other ingredients were then added and the rising,
proving and baking procedure were the same as for the whole-wheat grain.
After baking, the bread was allowed to cool to room temperature and was
then frozen in slices until used. Before being mixed with the other
ingredients, the whole kidney beans were boiled for 1 hour and the milled
kidney beans were boiled for 10 minutes. The kidney beans were made into
a wok together with olive oil, beef, garlic, corn, haricots verts, cauliflower,
leeks, tomato juice, soy sauce, and beef bouillon (for amounts see paper I,
22
Table 3, Page 839 [113]). This dish was served together with rice and
bread with full-fat spread. Both varieties of rice were boiled for 20 minutes.
The standardised breakfast meal in both parts of the study consisted of 200
g low-fat yoghurt (0.5 % fat), 35 g home-made muesli (made from a
mixture of 15 g rye-flakes, 15 g oats and 5 g rye crisp bread), 60 g
raspberries, 24 g rye crisp bread, 6 g full-fat spread (80 % fat, 25 % linoleic
acid), 30 g liver paste (23 % fat) and 20 g fresh cucumber. This breakfast
had a calculated energy content of 450 kcal (1890 kJ) and the proportions
of energy derived from carbohydrates, protein, and fat were 55, 16, and 29
per cent respectively, and the DF content was 9 g.
Paper II
The diets in study II were planned with starch-rich key foods with
differences in GI values as a basis (for GI values of the starch-rich foods
included, see paper II, Table 2, Page 11 [114]). Dishes including these
foods were created and, in turn, were put together into a one-week menu
for each diet. Differences in GI were mainly achieved by altering the
botanical and physical structures of the starchy foods and to some extent
also by changing the chemical starch structure, in order to exclude
potential effects of differences in DF or other dietary components. Except
for differences in the starch structure, all dietary constituents in both diets
were kept identical and were included in the same amounts.
The GIs of the Low and High GI diets were 57 and 83, respectively. On
average, GI was calculated on the basis of data for 94 per cent of the
carbohydrates in the diets. In order to get the subject’s weight stable, the
estimated energy level was calculated on the basis of their initial body
weight. Female subjects received 30 kcal (125 kJ) and male subjects 35
kcal (145 kJ) per kg body weight. All food was prepared individually for
each subject. The body weight was measured on all occasions when the
subjects collected their food, and if necessary the energy level was
adjusted. Four different energy levels with the same relative contents of
nutrients were used. The menus were calculated on the 1600 kcal level, and
in order to achieve the other energy levels used, namely 2000 kcal (8400
kJ), 2400 kcal (10 100 kJ), and 2800 kcal (11 800 kJ), the ingredients of the
1600 kcal menu were multiplied by 1.25, 1.50 and 1.75, respectively. The
calculated proportions of energy derived from carbohydrates, protein, and
23
fat, were 55, 16 and 28 per cent, respectively. The nutrient compositions of
the diets obtained from chemical analyses, are shown in Table 2.
The starch-rich foods included in the low GI diet that were responsible for
the differences in GI were: whole barley, durum pasta, parboiled rice,
whole dried lentils and beans, and high-amylose maize starch. The
corresponding starchy foods in the high GI diet were ground barley, white
wheat bread, sticky rice, ground lentils and beans, and ordinary maize
starch. The whole and ground barley was made into bread and porridge.
The pasta and white wheat bread were used as components for composite
meals. The rice varieties were used as components in composite meals and
in porridge and desserts. The lentils and beans were included in composite
meals and the varieties of maize flour were used for cakes and dessert. For
barley, lentils and beans the differences in GI were due to differences in the
botanical starch structure. In the High GI diet the structure was disrupted
by grinding before preparation (Messerschmidt Kornmeister 55000,
Messerschmidt GmbH, Mönchweiler, Germany). For pasta and white
wheat bread the differences in GI were due to differences in the physical
structure. For rice, maize starch and maize flour the differences were due to
differences in the chemical starch structure attributable to differences in the
amounts of amylose and amylopectin.
There were three types of breakfast meals in the low and high GI menus.
The low GI diet included pasta porridge made from boiled spaghetti, which
was mixed in a food-processor, porridge made from whole barley kernels
and porridge made from parboiled rice, and the corresponding breakfast
meals in the high GI diet included white wheat bread, porridge made from
barley flour and porridge made from sticky rice.
The type of pasta used was the same as that described in study I. The white
wheat bread was made from the same ingredients in the same amounts and
in the same way as the white wheat bread in study I. The beans and the
bean flour were prepared in the same way as in study I before being added
to dishes or composite meals.
The whole-grain barley bread included in the Low GI diet was made as
follows: 3073 g whole barley grain was boiled in 3073 g of water for 20
minutes and allowed to cool to room temperature. Thereafter the remaining
ingredients, namely 1500 g water, 627 g wheat flour, 200 g yeast and 10 g
salt, were added. The dough was left to rise for 30 minutes and then put in
a baking-tin, and proved for 35 minutes. The bread was baked at 200 qC for
24
45 minutes. The wholemeal barley bread was made from 3073 g barley
flour, 3200 g water, 627 g wheat flour, 200 g yeast and 10 g salt. Hot water
(40qC) was poured over a mixture of part of the barley flour mixed with the
other ingredients. The remaining ground barley was then added and the
dough was kneaded. The dough was allowed to rise for 30 minutes and
then put in a baking-tin and proved for 45 minutes. The bread was baked at
200 qC for 27 minutes. After baking, the bread was allowed to rest for one
day and was then cut into slices and frozen until used.
The subjects were provided with all food throughout the study period, and
breakfast, lunch and dinner were prepared in ready-to-eat dishes. The
subjects received instructions about how to prepare the ready-to-eat dishes
from a dietitian before entering the study. In a written menu they were
informed about which dishes they should eat for each meal and each day.
They were requested to eat all the food they received and no other food was
allowed, except for water, mineral water, coffee and tea. If for some reason
a participant was unable to eat all of the food received, he or she was
instructed to bring it back to us.
25
26
602 (2500)
640 (2700)
601 (2500)
606 (2500)
1880 (7900)
1820 (7600)
464 (1900)
460 (1900)
463 (1900)
463 (1900)
465 (1900)
670 (2800)
660 (2800)
62
81
58
80
57
83
78
78
44
54
44
53
96
kcal (kJ)
units
88 (53)
87 (53)
47.3 (41)
47.1 (41)
46.5 (40)
46.3 (40)
46.5 (40)
255 (55)
239 (54)
84.5 (56)
83.6 (55)
84.8 (56)
89.7 (56)
g (E%)
CHO
33.5
3.5
1.9
5.7
5.9
24.1
24.2
38
34
14.0
17.2
11.5
11.0
g
DF
*
*
*
*
*
*
*
*
*
4.3
4.4
2.7
2.9
Soluble
DF
g
*
*
*
*
*
*
*
*
*
9.7
12.8
8.8
8.1
Insoluble
DF
g
g (E%)
Fat
30 (18)
30 (18)
20.9 (18)
21.1 (18)
21.0 (18)
21.0 (18)
21.1 (18)
84 (18)
78 (18)
21 (28)
22 (29)
21.4 (42)
21.9 (43)
21.2 (41)
21.8 (42)
21.3 (41)
57 (27)
60 (29)
28.4 (19) 16.6 (25)
26.8 (18) 18.3 (27)
29.9 (20) 15.9 (24)
32.5 (20) 16.8 (24)
g (E%)
Protein
*
*
13.3 (26)
13.4 (26)
12.6 (24)
11.1 (22)
12.2 (24)
19 (9)
18 (9)
3.1 (5)
3.4 (5)
5.8 (9)
6.1 (9)
g (E%)
SAFA
*
*
5.3 (10)
5.4 (10)
5.0 (10)
4.4 (8)
4.9 (9)
25 (12)
26 (12)
10.2 (15)
11.2 (17)
4.9 (7)
5.0 (7)
g (E%)
MUFA
*
*
0.6 (1)
0.6 (1)
0.6 (1)
0.5 (1)
0.6 (1)
14 (7)
15 (7)
3.3 (5)
3.7 (5)
5.2 (8)
5.7 (8)
g (E%)
PUFA
GI, glycaemic index; CHO, carbohydrates; DF, dietary fibre; SAFA, saturated fatty acids; MUFA, monounsaturated fatty acids; PUFA,
polyunsaturated fatty acids. GI values calculated on the whole meal or the whole diet. In studies I and II, the energy values and the energy per cent
were calculated on the basis of chemical analysis of carbohydrates, protein and fat. In study I, the chemical analysis were performed on portions
calculated to have a mean energy content of 650 kcal (2720 kJ). In study II, the chemical analyses were performed on a menu calculated to contain
2000 kcal (8370 kJ). In studies III and IV, the energy values and energy per cent were calculated on the basis of a combination of values from chemical
analyses of carbohydrates, protein and fat and values obtained from food tables. * Not analysed.
Study I - Part 1
Low GI meal
High GI meal
Study I - Part 2
Low GI meal
High GI meal
Study II
Low GI diet
High GI diet
Study III
WWB reference
High GI-Low DF
Low GI-Low DF
Low GI-High sol DF
Low GI-High insol DF
Study IV
Low GI-High DF
High GI-Low DF
Energy
GI
Table 2. GI values and nutrient composition of test meals and test diets in studies I – IV.
Paper III
The breakfast meals in this study were planned to achieve large differences
both in GI and in the DF content, as well as differences in the type of DF.
The key foods responsible for these differences were bread and cereals.
The energy content was 460 kcal (1900 kJ) with an energy percentage of
41, 18, and 41 per cent, for carbohydrates, protein and fat, respectively.
The contribution of carbohydrates from the starch-rich key foods was 25 g
in each test meal. The carbohydrate-rich foods included in the different
breakfasts were 1) high in GI (a white-wheat reference bread); 2) high in
GI and low in DF (a wholemeal wheat bread); 3) low in GI and low in DF
(minimally processed wheat flakes); 4) low in GI and high in soluble DF
(steamed barley flakes made from a E-glucan-rich genotype); 5) low in GI
and high in insoluble DF (minimally processed wheat flakes and wheat
bran) (Table 3). The nutrient compositions are shown in Table 2.
Table 3. GI values and DF content of the different bread and cereal products included in
the breakfast meals in study III.
Breakfast
GI
1) White wheat reference bread (WWB reference)
2) Whole-meal wheat bread (High GI-Low DF)
3) Wheat flakes (Low GI-Low DF)
4) Barley flakes (Low GI-High soluble DF)
5) Wheat flakes + wheat bran (Low GI-High insoluble DF)
units
DF
Soluble/insoluble
g
100
100
37
54
37
0.4/0.8
0.7/4.3
0.6/4.6
12.5/10.9
1.1/22.5
GI, glycaemic index. DF, dietary fibre. GI values based on 50 g of available carbohydrates for each food.
DF for the amount of bread and cereals included in the breakfasts (25 g of available carbohydrates). GI
value estimated for breakfast number 2 and adapted from Granfeldt, Eliasson & Björck (unpublished
data) for breakfast 3 & 4.
The bread and cereals were served together with butter, full-fat milk (3 %
fat), cream (40 % fat), strawberries, sugar (sucrose) and cheese. In order to
balance the fat and protein contents the amounts and types of milk, cheese
and cream differed between the breakfast meals.
The white wheat bread in the WWB reference breakfast was made from
ordinary wheat flour, but otherwise the bread was made from the same
ingredients and in the same way as the white wheat bread in study I. After
baking, the bread was allowed to cool to room temperature and was then
27
frozen in slices. Before ingestion the crust was discarded. The wholemeal
wheat bread included in the High GI-Low DF breakfast was made from
whole kernels of wheat, which were ground to a fine, wholemeal flour.
Except for the wholemeal wheat flour, both the ingredients and the baking
procedure were exactly the same as for the WWB. The minimally
processed wheat flakes included in the Low GI-Low DF breakfast were
prepared as follows: wheat grains were soaked in cold water until soft and
then flaked between rollers to a thickness of 0.5 mm in a full-scale plant.
The wheat flakes were thus not subjected to heat treatment. The barley
flakes included in the Low GI-High soluble DF breakfast, were made from
a E-glucan-rich barley genotype (Prowashonupana, 17.5 % E-glucans by
dry weight; Con Agra, Omaha, USA). The barley flakes were prepared as
follows: pearled barley was steamed and rolled to flakes with a thickness
of 0.5 mm in a full-scale plant. The Low GI-High insoluble DF breakfast
consisted of the same wheat flakes as in the Low GI-Low DF breakfast,
mixed with wheat bran (Fiberform£, Tricum AB, Höganäs, Sweden).
The standardised lunch meal was composed in accordance with results
from Swedish food surveys [115], and consisted of: meatballs with brown
sauce, boiled potatoes, green peas, carrots, lingonberry jam and crisp bread
with low-fat spread. The calculated energy content was 500 kcal (2090 kJ)
and the proportions of energy derived from carbohydrates, protein and fat
were 41, 21 and 38 per cent, respectively; the content of DF was 6 g. The
participants were not allowed to eat anything else but were allowed 1.5 dl
water together with both the breakfast and lunch meal, and the same
amount of water 120 minutes after both meals.
Paper IV
In this study the two breakfast meals were planned so as to achieve large
differences in both GI and the type and amount of DF. The key foods
responsible for these differences were bread and cereals. The two breakfast
meals had the same macronutrient composition and an identical total
energy content. The Low GI-High DF breakfast had a GI of 53 and a DF
content of 33.5 g, while the High GI-Low DF breakfast had a GI of 96 and
a DF content of 3.5 g. The GI estimation was based on 99 per cent of the
carbohydrates in the meals. The breakfast meals were planned to give
approximately 25 per cent of the total daily energy intake recommended for
men between 31 and 60 years of age. The energy contents were 660 and
670 kcal (2800 kJ) with an energy percentage of 53, 18, and 29 for
28
carbohydrates, protein and fat, respectively. The bread and breakfast
cereals contributed 52-55 g of carbohydrates, which corresponded to 60 per
cent of the total carbohydrate content of the breakfast meals. The nutrient
compositions of the breakfasts are shown in Table 2.
The Low GI-High DF breakfast was based on barley flakes made from a Eglucan-rich barley genotype (Prowashonupana, 17.5 % E-glucans by dry
weight; Con Agra, Omaha, USA) and a sourdough-fermented bread with
rye kernels, enriched with E-glucans from oat bran. The barley flakes were
processed as follows: barley grains were soaked in cold water until soft and
then flaked between rollers to a thickness of 0.5 mm in a full-scale plant.
The barley flakes were not heat-treated. The sourdough-fermented bread
was enriched with a E-glucan-rich oat bran concentrate (Liljeberg Elmståhl,
Frid & Björck, unpublished data).
The High GI-Low DF breakfast was based on Cornflakes (Kellogg’s®) and
a white wheat bread. The white wheat bread in the High GI-Low DF
breakfast was made without monoglycerides but otherwise from the same
ingredients in the same amounts and in the same way as the white wheat
bread in study III. After baking, the bread was allowed to cool to room
temperature and was then frozen in slices.
The standardised lunch was a typical Swedish dish composed in
accordance with the present dietary recommendations [116], with a total
energy content that was calculated to correspond to approximately 32 per
cent of the total daily energy intake recommended for men between 31 and
60 years of age. The lunch consisted of meatballs with brown sauce, boiled
potatoes, green peas, lingonberry jam, crisp bread with full-fat spread, a
banana and water. The energy content was 875 kcal and the proportions of
energy were 54, 16, and 30 per cent for carbohydrates, protein, and fat
respectively.
In this study the participants were supplied with the breakfast meals during
each dietary period and they collected the food twice a week. All
ingredients were packed separately for each day and the participants
received everything that they should eat for breakfast. They were asked to
adhere strictly to the breakfast and to consume the whole breakfast at the
same time, and not to eat anything else with their breakfast meals, but were
allowed to drink coffee, tea or water. They were also asked not to prepare
the ingredients in any way. If for some reason a participant was not able to
eat all of the food received, he was instructed to bring it back to us.
29
The content of available carbohydrates in all test meals, as well as in the
test diets compared, were planned to be identical within each study and the
food items with differences in GI and DF were purchased in one batch and
stored until used.
Calculation and determination of glycaemic index
The GI values for the whole meals (study I, III and IV) and the whole diets
(study II) were calculated according to the method of Wolever et al [35],
described in detail in the report from the FAO/WHO Expert Consultation
[34].
In studies I and II, the GI values had been measured for most food items
before the study began [51, 117-121], or derived by use of data from the
literature [100, 122]. If GI data were missing, GI values were predicted by
using an enzymatic in vitro procedure that has been shown to predict GI
values for a large number of cereal- and legume-based foods with good
accuracy, as described by Granfeldt et al [123].
In study III, the GI value for the wholemeal wheat bread was estimated and
the GIs for the minimally processed wheat flakes and the steamed barley
flakes made from a E-glucan-rich genotype were adapted from Granfeldt,
Eliasson & Björck (unpublished data). In study IV, the GI and insulin
index for the low GI barley flakes were determined, with measurement of
blood glucose and insulin up to 95 minutes as proposed by Liljeberg et al
[124]. The determinations were performed in ten healthy subjects, seven
women and three men, with a mean age of 34.8 years (range 24-56). Their
body weight was 71.9 ± 9.2 kg (mean ± SD), and their BMI 21.4 ± 1.9
kg/m2. The GI for the low GI sourdough-fermented bread, enriched with Eglucans from oat bran, has previously been measured in healthy subjects
(Liljeberg Elmståhl, Frid & Björck, unpublished data) and the GI values
for the other included carbohydrate-rich foods were derived by using data
from GI-tables [100].
Calculations of energy and nutrient content of test meals and study diets
In the calculations of the energy and nutrient contents and the amount of
DF in the test meals (study I, III and IV) and in the standardised meals
(study III and IV) and the study diets (study II), the database from the
Swedish National Food Administration and a computerised calculation
30
programme (Dietist, Kost och näringsdata AB, Bromma, Sweden) were
used. For some of the key foods included in order to obtain differences in
GI and in the type and amount of DF, values for macronutrients and DF
were missing in the database from the Swedish National Food
Administration. In those cases the products were analysed for their
macronutrient composition and DF content and the values obtained from
the analyses were inserted into the computerised calculation programme.
Chemical analyses of study meals and diets
In order to corroborate the calculated values for energy and macronutrient
composition chemical analysis of study meals and diets were performed.
Each test meal (study I) and each test diet (study II) were analysed for the
amount of carbohydrates, DF, protein and fat and for the fatty acid
composition. When test meals were analysed (study I and III), every single
ingredient was weighed and the meals were prepared separately. When the
test diets were analysed (paper II), all seven days for each diet were
included and every single ingredient in every meal during a day was
prepared separately. In studies III and IV, the starch-rich products included
in the study breakfasts were analysed separately. Three duplicate portions
from each test meal or each day of the test diets were homogenised
separately together with hot water to get a temperature of 40 qC. After the
addition of water, the sample was weighed again. Samples were removed
and stored at -18 qC. For analyses of carbohydrates, DF and protein, the
samples were freeze-dried. The contents of insoluble and soluble DF were
measured by a gravimetric method according to Asp et al [125, 126]. The
starch content was determined by a method described by Holm et al [127]
and the other carbohydrates were measured by enzymatic methods
(Boehringer-Mannheim and Roche Diagnostics, Mannheim Germany). For
measurement of the total fat content and determination of the fatty acid
composition (study I, II and III), 10 g of the homogenate was extracted
with 50 ml methanol, 100 ml chloroform and 150 ml 0.2 mol sodium
dihydrogen phosphate/l. Ten ml of the chloroform phase was evaporated to
dryness and the total fat content was determined by weighing. Another
aliquot of the chloroform phase was used for determination of the fatty acid
composition. The fatty acids were transesterified to methyl esters and
analysed by gas-liquid chromatography as described by Boberg et al [128].
In studies III (wheat- and barley-flakes) and IV, fat was measured by the
Schmid-Bondzynski-Ratzlaff (SBR) method, including extraction with
31
ether after hydrolysis in HCl [129]. Protein was measured by wet digestion
according to the method of Kjeldahl, and for calculating the protein content
the factor 6.25 · nitrogen content was used.
Dietary assessment
Before keeping the dietary record (study II and IV) the subjects received
detailed oral and written instructions from a dietitian.
In study II, an estimated food record was kept for two days before entry
into the study, with the recommendation that the recordings should be
made on one weekday and one day at the weekend. The amounts of food
eaten were reported in household measures. These measures were
translated into weight in grams for each food or dish prior to nutrient
calculation. The nutrient intake was calculated using the database from the
Swedish National Food Administration and a computerised calculation
programme (Dietist, Kost och näringsdata AB, Bromma, Sweden). These
dietary records were also used for a rough calculation of the mean dietary
GI from available GI tables [100].
In study IV, the weighed dietary food records were kept on two weekdays
and one weekend day and each participant carried out the food recording
during the same weekdays and weekend day on all three occasions. The
food was weighed to the nearest gram on an electronic kitchen scale. The
nutrient intake was calculated using dietary food record were analysed by
using the food database from the Swedish National Food Administration
(PC-Kost 1_99, SLV, Uppsala, Sweden) and the software program Stor
MATs 4.05 SR-3 (Rudans Lättdata AB, Västerås, Sweden). Data on the
special products included, e.g. bread and cereals, were entered into the
database after analysis and used for the calculations of the breakfast meals
Anthropometrical measurements
Height was measured without shoes to the nearest 0.5 cm and body weight
was measured to the nearest 0.1 kg without shoes in light indoor clothing
on the same electronic scale on all occasions in each study. Body mass
index was calculated as the body weight (kg) divided by the height (m)
squared. Waist circumference (study IV) was measured midway between
the lowest rib and the iliac crest, and hip circumference at the widest part of
32
the hip, and the waist to hip ratio (W/H) was calculated. The waist and hip
circumference were measured in the supine position.
Blood pressure
Blood pressure (study IV) was measured in the right arm with the subject in
the supine position after a 5-minute rest, by indirect auscultation and with a
mercury sphygmomanometer. Systolic and diastolic blood pressures were
defined as Korotokoff phases 1 and 5, respectively.
Biochemical measurements
Blood sampling
Blood samples were drawn from an antecubital vein and all serum and
plasma samples were stored at -70˚C until analysed. All fasting blood
samples were taken after a 12-hour overnight fast. The subjects were asked
to avoid strenuous exercise the evening before the test days and in the
morning before each test. During the test days the participants were
sedentary.
Insulin sensitivity
Insulin sensitivity (study II) was evaluated by the euglycaemichyperinsulinaemic clamp technique according to the method of De Fronzo
et al [130] with minor modifications. The insulin (Actrapid R Human;
Novo, Copenhagen, Denmark) infusion rate during the clamp test was 56
mU/m2/minute, resulting in a mean plasma insulin concentration of about
100 mU/l. Euglycaemia was maintained by infusion of a 20 % glucose
infusion with adjustment of the infusion rate according to the results of
regular plasma glucose measurements. The target level of plasma glucose
during the clamp was 5.1 mmol/l. Insulin sensitivity is expressed as the
mean glucose uptake (M) and by the insulin sensitivity index (M/I60-120).
The M value (mg/kg body weight/min) represents the glucose uptake
during the last 60 minutes of the clamp test. The insulin sensitivity index is
a measure of the tissue sensitivity to insulin expressed per unit of insulin
obtained by dividing the mean glucose uptake by the mean insulin
concentration (I) during the last 60 minutes of the total 120-minute clamp
test (M/I, mg/kg body weight/min per mU/l multiplied by 100).
33
Glycaemic control
In studies I, II and III blood glucose concentrations were determined by the
glucose oxidase method [131], and in study IV they were measured directly
by the glucose dehydrogenase-based reaction in a HemoCue£ bloodglucose photometer (HemoCue AB, Sweden). HbA1c (studies II and IV)
was measured by fast performance liquid chromatography assay. Serum
fructosamine (study II) was determined with the use of a Roche reagent kit
(07-366694) (Roche, Basel), based on a nitro blue tetrazolium reduction in
alkaline medium, in a Cobas Bio centrifugal analyser.
Insulin and insulin secretion
In study I plasma insulin assays were performed by the Phadeseph insulin
test (Pharmacia, Uppsala, Sweden). In studies II and III plasma insulin
assays were performed by the enzyme-immunological test for quantitative
determination of human insulin in vitro (enzyme-linked immunosorbent
assay/1-step sandwich assay; Boehringer Mannheim Immunodiagnostics
for the ES300). In study IV an enzyme immunoassay, ELISA-kit
(Mercodia AB, Uppsala, Sweden) was used for measuring plasma insulin.
Plasma C-peptide was measured by the two-site enzyme immunoassay
(Mercodia C-peptide ELISA Enzyme immunoassay, Mercodia AB,
Uppsala, Sweden). Both plasma insulin and plasma C-peptide were
determined in a Coda Automated EIA Analyzer (Bio-Rad Laboratories AB,
Scandinavia). In studies I, II and III plasma C-peptide was measured
according to the method of Heding [132]. In study IV plasma C-peptide
was measured by the two-site enzyme immunoassay (Mercodia C-peptide
ELISA Enzyme immunoassay, Mercodia AB, Uppsala, Sweden) based on
the direct sandwich technique in which two monoclonal antibodies are
directed against separate antigenic determinants on the C-peptide molecule.
C-peptide was determined in the Coda Automated EIA Analyzer (Bio-Rad
Laboratories AB, Scandinavia).
Non-esterified fatty acids
Serum NEFAs (studies II, III and IV) were determined with a Wako NEFA
C-kit (994-75409) (Wako, Neuss, Germany), modified for use in a
Monarch apparatus (Instrumentation Laboratories, Lexington, MA, USA).
Lipoproteins
In study I, TAG and cholesterol concentrations in serum were determined
by enzymatic methods, using Boehringer Mannheim kits (Mannheim
Germany) modified for use in a Multistat IIIF/LS apparatus
(Instrumentation Laboratories, Lexington, MA, USA). In studies II, III and
34
IV, TAG and cholesterol concentrations were measured enzymatically in
serum and in the isolated lipoprotein fractions, using the IL Test cholesterol
method 181618-10 and the IL Test triglyceride enzymatic-colorimetric
method 181610-60 in a Monarch apparatus (Instrumentation Laboratories).
The concentrations of serum apolipoprotein (apo) A-1 and B (study II)
were determined by immunochemical assay (Orion Diagnostica, Espoo,
Finland) in a Monarch apparatus (Instrumentation Laboratories).
Lipoprotein (a) [Lp(a)] was measured by a Pharmacia apo (a)
radioimmunoassay method (Pharmacia, Uppsala, Sweden). This is based on
the direct sandwich technique, in which two monoclonal antibodies are
directed against separate antigenic determinants on the apo (a) in the
sample. The concentration is expressed in U/l. According to the
manufacturer, 1 U of apo (a) is approximately equal to 0.7 mg Lp (a).
In studies I, III and IV, HDL-cholesterol was separated by precipitation
with magnesium chloride/phosphotungstate [133]. LDL-cholesterol was
calculated with Friedwald´s formula: LDL=serum cholesterol – HDLcholesterol – (0.45 · serum triacylglycerol). In study II, VLDL, LDL, and
HDL-cholesterol were isolated by a combination of preparative
ultracentrifugation [134] and precipitation with a sodium phosphotungstate
and magnesium chloride solution [133].
Plasminogen activator inhibitor-1 activity
In study II, PAI-1 activity in plasma was measured with Spectrolyse/pL
kits from Biopool AB (Umeå, Sweden), using polylysine as a stimulator,
and in study IV, PAI-1 activity was analysed in citrate plasma using a
commercially available bio immunoassay
(Chromolize™ PAI-1,
Biopool®, Umeå, Sweden).
Tocopherols
The concentrations of Į- and Ȗ-tocopherol in serum (study II) were assayed
by high performance liquid chromatography using a fluorescence detector,
as described by Öhrvall et al [135].
Fatty acid composition
The fatty acid composition of the serum cholesterol esters (study II) were
determined by gas-liquid chromatography as described by Boberg et al
[128].
35
Statistical analyses
The statistical analysis was performed with the statistical program package
SAS for Windows, version 6.08 (study I & II) and 6.12 (study III & IV)
(SAS Institute, Cary, NC). Data are presented as means r SD except in
paper II, in which the results are presented as least-square means. Results
are expressed as fasting values, AUC, and fluctuations from baseline. The
AUC was calculated according to the trapezoidal model [136, 137].
In study I, the differences between the two test meals in both parts of the
study were analysed by Student’s t test for two-paired samples.
The analysis in studies II and IV took into account the design of the
experiment, the scales, and the distributions of variables [138]. For
continuous variables with normal distributions (for some variables after
logarithmic transformation), an analysis of variance model with factors for
treatment, subject, and time was used. Comparisons were made of the two
dietary periods (studies II & IV), and the results for each dietary period
were also compared with the results on admission. The mean value of
period one and period two minus the baseline value was used as the basis
of a test of different carry-over effects between the two treatment periods.
The test was performed as a t test between the two sequences. For
continuous variables with normal distributions, a t test for different carryover effects at the 10 % level was used. If this test was not significant, a t
test for different treatment effects at the 5 % level was used. If the carryover tests were significant, only data from the first dietary period were used
in comparisons of treatment effects. If the usual assumptions for t tests did
not hold, or if the data were on an ordinary scale, the t test was replaced by
the Mann-Whitney U test. Since no carry-over effects were identified in
studies II and IV, data from both periods on each diet were added
irrespective of the order of treatment.
In study II an analysis of covariance with change in body weight as a
covariate was carried out to separate the effects of treatment from those of
changes in body weight. Some of the data were unbalanced, since a few
values were missing. The results are therefore presented as least-square
means, which form the basis of the statistical tests and estimates in the
analyses and take the imbalance into account.
In studies III and IV, the calculated incremental AUCs after breakfast, after
lunch and for the whole day were adjusted for time point zero, which meant
that even when the AUC was calculated for 240 to 480 minutes the fasting
36
value was used as a basis. For comparisons of the mean values for AUC
between the five breakfast meals, an analysis of variance model with
factors for breakfast and subject was used. All breakfast comparisons were
made within subjects. If the test for the breakfast factor in this model was
significant at the 5 % level, all pair-wise comparisons were made.
Ethics
The studies were approved by the Ethics Committee of the Faculty of
Medicine at Uppsala University, Sweden and all subjects had given their
informed consent before entering the studies.
37
Results
Study I
Part 1: The AUC for both blood glucose (-35 %, P < 0.05) and insulin (-39
%, P < 0.01) was lower after the Low GI meal, containing pasta than after
the corresponding High GI meal containing white wheat bread. The blood
glucose concentrations were lower at 60, 90 and 120 minutes (Figure 3a)
and plasma insulin concentrations were lower at 90, 120 and 180 minutes
(Figure 3b) after the Low GI meal compared with the High GI meal.
Chapter 2 Figure 3a & b. Mean blood glucose and plasma insulin after consumption of
the Low-GI meal (Ɣ) compared with the High-GI meal (Ÿ). Areas under the curve (area
units) for the Low GI and the High GI meals were 95 r 51 and 146 r 48 for blood
glucose and 568 r 422 and 928 r 875 for plasma insulin, respectively. * P < 0.05, ** P
< 0.01.
Part 2: The AUC for blood glucose (-42 %, P < 0.001) and insulin (-39 %,
P < 0.01) was lower after the Low GI meal with parboiled rice, red kidney
beans and bread made from whole-wheat grains than after the
corresponding High GI meal. The blood glucose concentrations were lower
at 30, 60, 90, 120 and 180 minutes (Figure 4a) and the insulin
concentrations were lower at 30, 60, 90, 120 and 180 minutes (Figure 4b)
after the Low GI meal compared with the High GI meal.
38
Figure 4a & b. Mean blood glucose and plasma insulin after consumption of the LowGI meal (Ɣ) compared with the High-GI meal (Ÿ).Areas under the curve (area units)
for the Low GI and the High GI meals were 93 r 37 and 160 r 32 for blood glucose and
600 r 504 and 987 r 937 for plasma insulin, respectively * P < 0.05, ** P < 0.01, *** P
< 0.001.
The serum lipid levels showed similar responses after all of the tested
meals.
39
Study II
The peripheral insulin sensitivity increased significantly and the fasting
plasma glucose decreased during both treatment periods, with no difference
between the two dietary periods. The changes in the serum fructosamine
concentrations differed significantly between the two periods (P < 0.05).
The incremental AUC for both blood glucose and plasma insulin was ~ 30
% lower after the Low- than after the High GI diet (Figure 5 and 6). Total
cholesterol and LDL cholesterol were markedly reduced after both diets,
but the reduction was more pronounced after the Low-GI diet; total
cholesterol being 5 % (P < 0.01) lower and the LDL cholesterol being 8 %
(P < 0.01) lower after the Low GI diet than after the High GI diet. PAI-1
activity was normalised on the Low-GI diet, (-58 %, P < 0.001), but
remained unchanged on the High-GI diet (Figure 7).
Figure 5. Mean plasma glucose after the period with the Low GI diet (Ÿ) compared
with after the High GI diet (Ɣ). Areas under the curve (area units) for the low and the
high GI diet were 1495 r 671.8 and 2125 r 1469 respectively. **P < 0.01, ***P <
0.001.
40
Figure 6. Mean plasma insulin after the period on the Low GI diet (Ÿ) compared with
after the High GI diet (Ɣ). The areas under the curve (area units) for the Low and the
High GI diet were 12927 r 6729 and 17724 r 10318, respectively. * P < 0.05, **P <
0.01, ***P < 0.001
25
***
**
20
15
10
5
0
Mean ± sd
Admission
22.2 ± 14.7
Low GI
9.4 ± 11.0
High GI
20.2 ± 16.1
Figure 7. Comparisons of the effects on the activity of plasminogen activator
inhibitor -1 (PAI-1) after the Low- and High-GI diets. **P < 0.01, ***P < 0.001.
41
The results from the 2-day estimated dietary record, kept by the subjects
before entry into the study showed a mean energy intake of 1650 ± 510
kcal (6900 ± 2130 kJ). The proportions of energy derived from
carbohydrates, protein and fat were 44, 18 and 34 per cent, respectively. GI
data were obtained for 84 per cent of the carbohydrates included. The GI
values for the remaining carbohydrate-rich foods were approximated,
resulting in an estimated GI of the habitual diet of 80-90 units.
The fatty acid composition of the serum cholesterol esters did not differ
between the dietary periods. The proportions of D-linolenic acid and
docosahexaenoic acid had increased and the proportions of palmitoleic and
stearic acid had decreased compared with those on admission, indicating
good compliance in both dietary periods.
42
Study III
The early postprandial responses of both plasma glucose and insulin when
calculated as AUC up to 90 minutes after breakfast were, as expected from
the GI values for the starch-rich foods included, lower after the three low
GI breakfasts than after the high GI breakfasts. When the AUC for glucose
was calculated for up to 240 minutes after breakfast, the Low GI-High
soluble DF breakfast showed a lower AUC after breakfast compared with
all the other breakfast meals, and the AUC for plasma insulin was
significantly lower after all breakfasts with low GI values than after the two
high GI breakfasts. The Low GI-High insoluble DF breakfast showed a
higher AUC for glucose after lunch than did the high GI breakfasts (P <
0.05), with an insulin response in parallel with the glucose response. The
Low GI-High soluble DF breakfast yielded smaller fluctuations of plasma
glucose from baseline compared with both high GI breakfasts, and smaller
fluctuations after lunch than after the Low GI-High insoluble DF breakfast.
However, none of the breakfasts could improve the glucose and insulin
response after lunch. The Low GI-High insoluble DF breakfast resulted in
effective suppression of NEFAs after lunch (Figure 8), and the response of
TAG after lunch was lower after the low GI than after the high GI
breakfasts (Figure 9).
0
-0,1
-0,2
-0,3
-0,4
-0,5
0
60
120
180 240 300
Time (min)
360
420
480
Figure 8. Mean serum non-esterified fatty acid (s-NEFA) response throughout the day,
after the High GI-Low DF (‫)ڗ‬, Low GI-Low DF (Ÿ), Low GI-High soluble DF (٩),
and Low GI-High insoluble DF (‫ )ڏ‬breakfast meals compared with the WWB reference
breakfast (…).
43
1,2
1
0,8
0,6
0,4
0,2
0
-0,2
0
60
120
180 240 300
Time (min)
360
420
480
Figure 9. Mean serum triacylglycerol response throughout the day, after the High GILow DF (‫)ڗ‬, Low GI-Low DF (Ÿ), Low GI-High soluble DF (٩), and Low GI-High
insoluble DF (‫ )ڏ‬breakfast meals compared with the WWB reference breakfast (…).
44
Study IV
No differences were seen between the dietary periods in any of the
parameters measured or analysed in the fasting state.
The glucose and insulin responses, calculated as the AUC up to 90 minutes
after breakfast, were as expected from the GI values of the starch-rich
foods included, with a significantly lower AUC for both blood glucose and
plasma insulin after the Low GI-High DF than after the High GI-Low DF
breakfast. Also, fluctuations from baseline after breakfast and during the
day for glucose was lower after the low GI-high DF breakfast period
(Figure 10). However, when the calculation of the AUC for blood glucose
was lengthened up to lunch (240 minutes), no differences were found
between the two breakfast periods. Neither was any differences seen in
blood glucose after lunch. The AUC for plasma insulin was lower after the
Low GI-High DF breakfast (also when calculated up to 240 minutes) (32%, P = 0.0001) (Figure 11) than after the high GI-low DF breakfast
period. After the low GI-high DF breakfast the AUC for TAGs after lunch
was also lower (-47%, P = 0.002) compared with the period after the High
GI-Low DF breakfast (Figure 12). There was no significant difference in
serum NEFA response after breakfast or lunch between the two breakfast
periods (Figure 13).
4
3
2
1
0
-1
0
60
120
180 240 300
Time (min)
360
420
480
Figure 10. Mean blood glucose response throughout the day after the Low GI-High DF
(‫ )ڗ‬and the High GI-Low DF (Ÿ) breakfasts. The incremental areas under curve (area
units) were 86.4 r 106.9 (mean r SD) and 130.2 r 136.1 after breakfast (0-240 minutes)
and 113.0 r 136.6 and 91.0 r 128.3 after the standardised lunch (240-480 minutes) for
the Low GI-High DF and High GI-Low DF breakfasts, respectively.
45
100
80
60
40
20
0
0
60
120
180 240 300
Time (min)
360
420
480
Figure 11. Mean plasma insulin response throughout the day after the Low GI-High DF
(‫ )ڗ‬and the High GI-Low DF (Ÿ) breakfasts. The incremental areas under curve (area
units) were 6105 r 3661 (mean r SD) and 8916 r 4442 after breakfast (0-240 minutes)
and 9535 r 5453 and 8465 r 4678 after the standardised lunch (240-480 minutes) for
the Low GI-High DF and High GI-Low DF breakfasts, respectively.
1,4
1,2
1
0,8
0,6
0,4
0,2
0
-0,2
0
60
120 180 240 300 360 420 480
Tim e (m in)
Figure 12. Mean serum triacylglycerol (s-TAG) response throughout the day after the
Low GI-High DF (‫ )ڗ‬and the High GI-Low DF (Ÿ) breakfasts. The incremental areas
under curve (area units) were 49.6 r 40.2 (mean r SD) and 50.1 r 39.6 after breakfast
(0-240 minutes) and 190.1 r 99.7 and 253.5 r 91.6 after the standardised lunch (240480 minutes) for the Low GI-High DF and High GI-Low DF breakfasts, respectively.
46
0
-0,1
-0,2
-0,3
-0,4
0
60
120 180 240 300 360 420 480
Time (min)
Figure 13. Mean serum non-esterified fatty acid (s-NEFA) response throughout the day,
after the Low GI-High DF (Ɣ) and the High GI-Low DF breakfasts (Ÿ). The
incremental areas under the curve (area units) were -61.2 r 24.2 (mean r SD) and -65.8
r 24.2 after breakfast (0-240 minutes) and -67.2 r 31.1 and -60.2 r 24.1 and after the
standardised lunch (240-480 minutes) for the Low GI-High DF and High GI-Low DF
breakfasts, respectively.
There were no differences in the energy and macronutrient composition
between the two dietary periods, except for the intake of dietary fibre,
which was higher after the Low GI-High DF than after the High GI-Low
DF period.
47
Discussion
Main findings
Starch-rich foods with low GI values incorporated into composite meals
gave lower postprandial responses of both glucose and insulin than meals
with a high GI with an identical macronutrient and DF composition in
subjects with type 2 diabetes. A low GI diet taken for a period of three
weeks results in a considerably improved metabolic profile with lower
glucose and insulin responses throughout the day and an improved lipid
profile and capacity for fibrinolysis in subjects with type 2 diabetes
compared with a corresponding high GI diet. Low GI foods, especially
those high in soluble DF, for breakfast tend to give a more favourable
metabolic profile both when included in single meals and after inclusion in
breakfast meals for a period of three weeks. A lower early glucose
response and smaller glucose fluctuations from baseline after both
breakfast and lunch were seen. Low GI breakfasts also resulted in lower
responses of insulin and C-peptide after breakfast and lower postprandial
TAG levels after a second meal. A breakfast with a low GI and a high
content of insoluble DF suppressed NEFAs efficiently. However, none of
the low GI breakfasts tested improved the glucose and insulin responses
after lunch.
These results support the idea of a therapeutic potential of a low GI diet
high in DF in the treatment of diabetes and also for prevention and
treatment of several of the metabolic disturbances related to the insulin
resistance syndrome. They emphasise the importance of preserving the
structure of common starchy foods.
Interestingly, epidemiological studies have shown that a diet with a low
glycaemic load and a high amount of cereal fibre is associated with a low
relative risk of developing type 2 diabetes in both men and women [36,
139]. A low glycaemic load and a high amount of cereal fibre have also
been shown to be associated with a lower relative risk of myocardial
infarction in women [38], with a more pronounced risk reduction among
the overweight and obese. In two large prospective cohort studies in
women, whole grain consumption has been found to be inversely
associated with a risk of diabetes and coronary heart disease (CHD) [140142]. Despite its high content of insoluble DF, only cereal fibre has been
48
shown to be strongly associated with a reduced risk of CHD among women
[143]. It has been hypothesised that the high concentrations of magnesium
and antioxidant vitamins in fibre-rich cereal products might mediate the
protective effect of cereal DF [144].
Glucose and insulin responses
In study I, both the glucose and insulin responses were considerably lower
after consumption of composite lunch meals with low GIs. This is in
agreement with earlier findings in healthy [40] and diabetic subjects [105,
145] given test meals with a similar macronutrient composition. The actual
difference in postprandial glucose AUCs in our study was even larger than
that predicted from calculations of GI values of the test meals. This study
shows that the glycaemic response following a meal can actually be
predicted from the calculated GI of the meal. However, in the study by
Coulston et al [146], almost identical plasma glucose and insulin responses
occurred after different mixed meals with larger differences in the
calculated meal GI than in our study. This inconsistency could possibly be
an effect of a rather high fat content (40 % of energy) and low carbohydrate
content (40 % of energy) in their study. It might also be a result of
calculating the absolute area instead of the incremental area under the
curve.
After a period of 3.5 weeks on a low GI diet (study II), both the glucose
and insulin responses throughout the day were lower than after the
corresponding high GI diet, further supporting that the effects of low GI
foods included in composite meals persist when these foods are
incorporated into whole diets [76]. Since the carbohydrate-rich key foods
responsible for the differences in GI were basically made from the same
ingredients, this eliminates potential effects of variations in DF and
nutrients. Thus, the difference between the effects of the two dietary
periods can mainly be explained by the differences in GI.
In studies III and IV, the early glucose and insulin responses, calculated as
the AUC for up to 90 minutes, were as expected from the determined and
calculated GI values of the breakfasts compared. This was in accordance
with reports from studies both in both healthy and diabetic subjects who
were given breakfast meals with a high concentration of E-glucans from
oat bran and high E-glucan barley [121, 147]. In study III, the low GI
breakfasts produced smaller glucose fluctuations from baseline. This effect
49
was even more pronounced, with lower responses and smaller fluctuations
from baseline also after lunch, when the low GI was combined with a high
content of DF, especially of the soluble type. In agreement with this, the
low GI breakfast high in soluble DF in study IV also showed smaller
glucose fluctuations from baseline during the day. There were no
differences in fasting levels of serum insulin between the two breakfast
periods in study IV. This is in contrast to the report by Golay et al [148],
who found lower fasting insulin and a lower mean day-long plasma glucose
after a two-week period with muesli compared with cornflakes for
breakfast.
Except for the lower AUC for plasma glucose after the Low GI-High
soluble DF breakfast (in study III) compared with all other breakfasts, there
were no differences in AUC for plasma glucose between the breakfasts
when calculated over a longer postprandial period of 240 minutes. The
reason for this was that the blood glucose had already returned to a level
below baseline at 120 minutes and that negative areas are subtracted from
positive ones when the AUC is calculated according to the trapezoidal
model [136, 137]. In contrast to the glucose response, the insulin level
remained above baseline until the next meal at 240 minutes after both the
high and the low GI breakfast in studies III and IV. Different starch-rich
foods result in lower glucose and insulin responses in healthy subjects than
in subjects with diabetes. Glucose values usually return to baseline
somewhere between 90 and 120 minutes after the beginning of the meal in
healthy persons, whereas the values are still above baseline at 240 minutes
in subjects with diabetes [149]. The lack of difference in AUC between the
two breakfasts when the calculation was made up to 240 minutes in study
IV could be expected. However, in study III the lack of difference when the
AUC was calculated up to 240 minutes was unexpected, since the subjects
had impaired insulin sensitivity and type 2 diabetes.
In studies II and IV there were no differences in HbA1c between the dietary
periods. Compared to baseline, the low GI diet in study II resulted in
significantly decreased levels of HbA1c, but a similar trend was also noted
for the high GI diet. However, the changes in the serum fructosamine
concentration, which may be a more appropriate indicator of glycosylation
of serum protein than HbA1c during short periods of time, differed
significantly between the two dietary periods. These studies were probably
too short to show any significant differences in HbA1c between the diets.
Since there were differences in the serum fructosamine concentrations after
diets with different GIs and since fluctuations of blood glucose from
50
baseline during the day were smaller after the Low GI-High DF breakfast
in study IV, we believe that a longer period on a diet with a low GI might
result in a lower HbA1c.
Insulin sensitivity
In study II, the peripheral insulin sensitivity, measured by the clamp
technique, increased significantly during both dietary periods. The
improvement in insulin sensitivity was more accentuated after the low GI
(+30 %) than after the high GI diet (+20 %), but no significant differences
were seen between diets. Improvement of insulin sensitivity and of glucose
tolerance (measured by OGTT and insulin-stimulated glucose uptake in
isolated adipocytes) by a low GI diet has also been observed in a group of
patients with advanced CHD [150]. In addition, a low GI diet has been
shown to improve both adipocyte insulin sensitivity in women with a
family history of CHD and in vivo insulin sensitivity measured by a short
insulin tolerance test in women with and without a family history of CHD
[151]. In a cross-sectional study in men and women the GI of the diet was
found to be the only dietary variable significantly related to the HDLcholesterol level [152]. It was suggested that this was an effect of
improvement of insulin sensitivity by a low GI diet.
Lipoproteins
The extent of the total reduction of serum cholesterol and LDL cholesterol
observed after both dietary periods in study II, compared with that on
admission, is comparable to the reduction achieved by treatment with
hydroxy-methyl-glutaryl (HMG)-CoA reductase inhibitors, such as
simvastatin [153] and pravastatin [154], which lowered the plasma
cholesterol by 25 and 20 per cent and LDL cholesterol by 35 and 26 per
cent, respectively. An increased concentration of LDL cholesterol or total
cholesterol is a major risk factor for coronary artery disease in persons with
type 2 diabetes [8]. It is also a major risk factor for the general population
[153-155], but because of the presence of small dense LDL particles [156]
and oxidation of glycated LDL cholesterol [157] it may be more
pathogenic in subjects with diabetes. Lowering of serum cholesterol has
been shown to be an effective and safe method of reducing ischaemic heart
disease. Results from prospective studies and clinical trials have shown that
a modest reduction in serum cholesterol levels of 10 per cent in the longer
51
term may lower the risk by about 50 per cent (at age 40) [155, 158]. This
reduction can reduce the mortality by 25-30 per cent in people aged 55-64
years. Thus, the pronounced reduction shown in study II could potentially
be of great importance if maintained over a period of many years.
Inclusion of E-glucans from oat bran and oat fibre extract in a diet for a
period of three weeks have been shown to lower both total and LDL
cholesterol in hypercholesterolaemic subjects [159, 160]. Even though the
total amount of E-glucans in the Low GI-High DF breakfast in study IV
was almost twice as high as in these studies, there were no effects on
fasting lipids. The key mechanism whereby E-glucans decreases the
cholesterol level is through an increased viscosity of the gastrointestinal
content [161]. It is therefore possible that a low viscosity might explain the
lack of effect in this study.
The most interesting finding in studies III and IV was the lower response of
TAG after a standardised lunch following low GI breakfasts. This is in line
with the results from a single meal study [95] in which the second-meal
effect was investigated after breakfast meals with low GI values. A lower
response of TAG after lunch has also been observed in healthy, slightly
overweight men after a period of five weeks on a carbohydrate-rich diet
low in GI, compared with a high GI diet [162]. When carbohydrate
absorption is prolonged, the blood glucose shows less tendency to decrease
to below the basal level. This may lead to a smaller counter-regulatory
response and improved glucose disposal after the next meal. A lower
counter-regulatory response will in turn, result in lower levels of NEFAs
[97]. Effective suppression of NEFAs as a result of a prolonged absorptive
phase following breakfast could also improve the insulin sensitivity at the
time of the lunch meal [41]. In studies III and IV, the lower TAG response
after the breakfast with a low GI and a high content of insoluble DF might
be explained by the higher insulin levels after lunch, which would result in
suppressed hormone-sensitive lipase and ensure effective suppression of
NEFAs, which in turn would prevent the rebound of TAG. Many of the
metabolic benefits associated with a low GI carbohydrate intake can be
attributed to their ability to reduce adipocyte NEFA release [163]. In study
IV there was no significant difference in the post-lunch insulin and NEFA
responses between the two breakfast periods, but the suppression of fat
mobilisation by insulin occurs at very low insulin concentrations, ranging
from around 2 mU to 20 mU/l [12, 164]. However, this cannot explain the
lower TAG response after the low GI breakfast high in soluble DF in study
III.
52
Postprandial lipaemia interacts with the process of thrombosis, in that an
elevated postprandial TAG concentration has the ability to activate the
coagulation factor VII and PAI-1 activity [14]. In study II we found that
PAI-1 activity was normalised after a period with a low GI diet but not
after a high GI diet. We found no difference in the fasting TAG response
between these two dietary periods. Unfortunately, we did not measure the
postprandial TAG response. A low DF intake has been shown to be
associated with high PAI-1 activity [165]. It should be stressed that there
were no differences in the amount and source of DF between the high and
low GI diets in study II. Earlier studies have demonstrated that a reduction
in fat intake and an increase in DF intake may improve the fibrinolytic
activity [166, 167]. Starchy foods have also shown a more favourable
impact than sucrose on factor VII coagulant activity [168]. It has been
suggested that the optimal “anti-thrombotic diet” should have a low fat
content and be naturally rich in DF [169].
In study II, HDL-cholesterol was lower than the baseline value after both
dietary periods. This was almost certainly an effect of a lowered total
dietary fat intake during both periods compared with the amount usually
eaten.
Second-meal effects
We found no second-meal effects on glucose and insulin after any of the
low GI breakfasts tested in studies III and IV. It has been suggested that the
second-meal effect occurs when carbohydrates are more slowly absorbed,
with a less rapid rise in glucose and a lower tendency for glucose levels to
undershoot the baseline value after the first meal, leading to a smaller
counter-regulatory response and improved glucose disposal after the next
meal. In study III, the lack of improved second-meal carbohydrate
tolerance could probably be due to a low carbohydrate content of the
breakfast in comparison with that in other studies [67, 91-95]. In nondiabetic subjects, a low GI (GI = 70) was shown to be effective in
suppressing NEFAs and improving second-meal carbohydrate tolerance
only when present in a breakfast with a carbohydrate content almost twice
as high as that in study III, while a breakfast with the same GI and a lower
carbohydrate content tended to impair the second-meal carbohydrate
tolerance [92]. The question has been raised whether differences in the type
and amount of carbohydrate affect NEFAs in subjects with insulin
resistance and diabetes, who have high fasting and postprandial NEFA
53
concentrations [68, 170]. The NEFA suppression achieved by the Low GIHigh insoluble DF breakfast in study III suggests that this is the case.
Giacco et al [171] found lower glucose and TAG levels after a breakfast
meal rich in resistant starch, but reported that, in conformity with our low
GI breakfasts (study III), this meal had no effect on the response after the
subsequent meal. In spite of a higher carbohydrate content, a low GI and a
high amount of soluble DF in the Low GI-High DF breakfast in study IV
(compared with the breakfasts given in study III), we observed no secondmeal effects on either glucose or insulin.
The effects on NEFAs noted after the low GI breakfast high in insoluble
DF in study III are in conformity with the results reported after seven
weeks of a high dose of uncooked cornstarch (with almost the same amount
of carbohydrates as in our study) at bedtime [172]. Compared with a starchfree placebo, the nocturnal glucose and insulin responses were lower and
NEFAs were suppressed. The glucose tolerance and C-peptide response
were improved after breakfast the next morning. There were no
improvements in insulin sensitivity or HbA1c levels. A low dose of
uncooked cornstarch lowered the fasting blood glucose response after only
four weeks and this effect was shown to persist after seven weeks, although
no improvements in HbA1c was observed.
In a study by Liljeberg et al [94] a breakfast based on barley flakes made
from Prowashonupana barley and a high amylose barley bread baked for a
long time improved the glucose tolerance at a second meal in healthy,
normal weight subjects. The metabolic response was only measured after
the standardised lunch, but since the test meals resulting in improved
second-meal carbohydrate tolerance showed a significantly higher blood
glucose response as measured in the fasting state between meals, the
glucose response after breakfast was probably above baseline for up to 240
minutes after breakfast.
The lack of a second-meal effect on glucose in studies III and IV might
have been due to the fact that the glucose response returned to the baseline
level as early as half time between breakfast and lunch. It may be
speculated that only low GI foods, giving a more smooth glucose response,
with glucose levels that remain above baseline until lunchtime, will result
in improved second-meal carbohydrate tolerance.
54
Effects of fermentation
Resistant starch and unabsorbed carbohydrates will be fermented by the
colonic microflora. It has been proposed that short-chain fatty acids,
produced during fermentation, may play a role in improving postprandial
glycaemia after high-fibre, high-carbohydrate diets, by inhibition of hepatic
glucose production [173]. Fermentation and its products are expected to
peak 12-16 hours after consumption of soluble DF and unabsorbable
carbohydrates [173] and a period of three days have been shown to be
sufficient to increase the bowel fermentation [174]. It is therefore unlikely
that formation of metabolically active short-chain fatty acids will explain
the results of study III even if the wheat flakes can be expected to contain a
certain amount of resistant starch. The dietary periods in studies II and IV
seem to have been sufficiently long to enable possible effects of the
fermentation process to be demonstrated. Even if the test diets in study II
were based on identical ingredients, the low GI diet can be expected to
contain somewhat larger amounts of resistant starch [42]. However, in
patients with CHD who are insulin resistant, stimulation of large bowel
fermentation by lactulose has been found to have no effects on insulin,
glucose, NEFAs or glucagon-like peptide 1 [175]. Battilana et al [174]
investigated the effects of three days on a diet with 8.9 g of E-glucans per
day as compared with a diet without E-glucans. On the third day the effects
on lipid and carbohydrate metabolism were evaluated by giving the test
diets every hour for 9 hours. The two diets resulted in similar lipid and
carbohydrate metabolism, which does not support the hypothesis that
metabolites produced during E-glucan fermentation in the large intestine
exert beneficial effects on carbohydrate metabolism. The authors concluded
that the effect of a meal containing E-glucans on the postprandial glucose
concentration is essentially due to delayed and somewhat reduced
carbohydrate absorption from the gut and is not attributable to fermentation
in the colon.
Effects on body weight
In study II we did not manage to keep the subjects’ weight stable
throughout the study period. The intention was to keep it stable throughout
the study, but owing to the large volume of the foods included in both diets,
and its effect on satiety, this was not always possible. All subjects stated
that they had never eaten so much before without gaining weight. As a
consequence of this there was a slight and similar reduction in body weight
55
during both dietary periods. However, all results presented in paper II have
been adjusted for changes in body weight. Promising results of a low GI
diet on body weight have also been reported in obese children [90] and in
slightly overweight men, in whom a 5-week period on a low GI diet
decreased the total fat mass, mostly abdominal fat, by 500 g [162],
although there was no effect on body weight. No differences in body
weight or waist and hip circumference were found when only the breakfast
meal was changed (paper IV). Neither were there any differences in energy
and nutrient intake after the two periods with different breakfasts. A
relatively long period with a low GI high DF breakfast might lead to
changes in the dietary intake, which in turn might prevent weight gain and
possibly reduce both the body weight and the waist and hip circumference.
Thus, a low GI diet should be considered in weight loss regimes [176].
Furthermore, compliance with a prescribed low energy intake may be
easier if the diet has a low GI as well, because of the low energy density of
most starch-rich low GI foods and their greater effect on satiety.
Carbohydrate-rich foods in the optimal diet in the insulin resistance
syndrome
The target for the treatment of the insulin resistance syndrome should be to
improve insulin sensitivity and to prevent or correct associated metabolic
and cardiovascular abnormalities [177]. Since obesity is the dominant
factor leading to metabolic complications, the treatment in overweight
subjects should primarily focus on weight reduction [3]. One target group
should be first-degree relatives of subjects with type 2 diabetes [178]. The
nutritional strategies for prevention and treatment of the insulin resistance
syndrome are similar to those recommended for people with diabetes and
those aimed at the population as a whole [17, 179]. Two basic
requirements should be fulfilled, namely: reduced intake of saturated fatty
acids and an increase in the intake of vegetables, legumes, fruit and low GI
starchy foods [177].
In study II dramatic reductions in plasma glucose, serum cholesterol and
LDL cholesterol, and improved insulin sensitivity, were also seen after the
high GI diet. This indicates that both diets had a favourable nutrient
composition, i.e. they had a low fat quantity, an improved fat quality and a
high DF content, a composition that apparently differed from that of the
habitual diet of the participants. Lowering the GI by keeping the structure
of the starchy foods intact, without altering the macronutrient and DF
56
content, gave further improvements. In study II the subjects were provided
with all the food that they should eat throughout the study period. To make
all these changes in real life would probably require substantial efforts for
most people. In the UK Prospective Diabetes Study (UKPDS), the effect of
3 months of diet therapy was evaluated in newly diagnosed type 2 diabetic
patients [180]. Body weight was reduced by 5 %, plasma glucose fell by 3
mmol/l, HbA1c decreased by 2 % from 9 % and TAG showed a substantial
reduction by 17 % in men and 10 % in women. In the UKPDS study the
metabolic improvements were almost certainly due to a large extent to the
weight reduction. However, the dietary advice given was based on the
recommendations published by the British Diabetic Association in 1982, in
which information about GI and fat quality was not included. Thus,
inclusion of recommendations regarding low GI starchy foods and an
improved fat quality would most likely have yielded further improvements,
perhaps somewhere between the results of study II and those of the
UKPDS diet therapy study.
A reduction of the GI of carbohydrate rich foods at several meals will
require substantial changes in dietary habits. It is probably not enough
merely to incorporate low GI foods in the breakfast meal if one wants to
achieve major changes in the metabolic profile. Also, the present study
(paper IV) might have been too short to show major effects on the
measured parameters after changing the composition of only one meal.
However, a change in the breakfast meal is probably quite easy to
accomplish and if improvements could be shown this could be of practical
clinical importance for the motivation to make further changes in the
dietary habits.
An alternative approach to achieve an extended blood glucose response to
low GI and high DF foods could be to eat more frequently, with some small
meals between the large meals or several small meals during a longer
period of the day, also known as nibbling. An increased meal frequency has
shown cholesterol-lowering effects [181, 182] and advantages for
carbohydrate tolerance in type 2 diabetes [183, 184]. However, in the only
long-term study that has addressed the effects of an increased meal
frequency in subjects with diabetes, no change in either carbohydrate or
lipid metabolism was found (Arnold, Ball & Mann, unpublished data)
[185].
57
In study II we found improvements of many of the components of the
insulin resistance syndrome. To treat these metabolic abnormalities the
“traditional way” of using drugs would require multipharmaceutic
measures. Many of the drugs will alleviate symptoms, but will not really
affect the cause of the disease.
What is considered to be a low glycaemic index?
In free-living subjects with type 2 diabetes it has been shown that the GI of
the diet ranges from 70 to 97.8 units, with a mean of 85 ± 5 (mean ± SD)
[186]. This is comparable to the GI calculated for the high GI diet in study
II and to the calculations based on the 2-day dietary record kept by the
participants before entering the study. In a prospective study in elderly
men, similar GI values were found when calculated from dietary history
records [187]. When the GI is calculated from dietary records, only a rough
estimation can be obtained, since defined GI values are still lacking for
many carbohydrate-rich foods. In one study concerning the effect of a low
GI in the management of hyperlipidaemia, GI values similar to those in our
Low GI diet in study II were achieved [78]. In subjects with type 2 diabetes
who were given dietary instructions weekly by a dietitian during a period
of 12 weeks, the dietary GI was found to be 77 in comparison with 91
when advice about a high GI diet was given [188]. In another study, lasting
12 weeks, in subjects with type 2 diabetes, a decrease in the GI from 82 to
77 units was found [77]. A dietary GI of about 60 must be considered quite
low. However, every reduction of the dietary GI, even if it does not reach
such a low level, is probably to be considered beneficial.
The glycaemic index concept revisited
When the GI is determined during time periods of up to 90 and 120
minutes, the extended metabolic response after that time point and up to the
next meal is not known. The GI value alone does not give any information
about the length of the response and the shape of the glucose curve. Foods
with similar GI values can yield very divergent shapes of the glucose
response curve. Hypothetically the glucose response can be very high and
short, and may therefore go below the baseline levels even during the GI
determination (early postprandial response); or it can be low and extended
through the late postprandial period (2-3 h). Carbohydrate-rich foods can
58
have the same GI but result in large differences in glucose fluctuations
from baseline when studied for an extended period after the meal.
Carbohydrate-rich foods with low GI values that give a prolonged glucose
and insulin response with small intra-day excursions are probably the most
favourable. This usually means a low early response and a prolonged
absorption phase. An extended glycaemic response may promote a secondmeal effect. The shape of the curve is indicative of the late glucose
response. It is suggested that a GI value published in a GI table could be
supplemented with a glucose response curve. To evaluate the possible
second-meal effect of a low GI food, the determination of the glucose
response should preferably be extended until it is time for the next meal.
When the GI is determined for separate foods, the glucose response is
calculated up to 90 or 120 minutes. Extension of measurements after
fasting levels have been re-established may lead to smaller differences in
GI between foods, and if the area calculated includes the negative area, a
very low response (below baseline) could be evaluated as a better response
than it actually is. In addition to the AUC calculation, differences in
fluctuations from baseline can be calculated as a measure of intra-day
excursions. It has been suggested that the peak blood glucose value may
give a better indication of the “true” glycaemic effect [189]. Since high GI
foods result in relatively fast glucose responses with high peaks, there is
also a tendency to undershoot baseline levels. The length of the early
glucose response up to the time when the value goes beneath the baseline
level could also give additional information.
Methodological concerns, strengths and limitations of the studies
In studies I and II the carbohydrate-rich key foods responsible for the
differences in GI were basically made from the same ingredients. This
eliminates potential effects of variations in DF and nutrients and makes it
possible to evaluate the effects of differences in GI only. Compared to that
in many other investigations of the second-meal effect of different
carbohydrate-rich foods, the amount of carbohydrates in study III was
smaller and corresponded to what could be considered realistic for a
breakfast. However, the amount of soluble DF in the low GI breakfast
meals is probably higher than one can expect to have in a standard
breakfast. In study IV, the amount of breakfast cereals in the low GI
breakfast was quite large.
59
The last sample for measurement of serum TAG in studies III and IV was
obtained 4 hours after the standardised lunch. Since the plasma TAG
concentration reaches a peak between 4 and 6 hours after a carbohydraterich meal [190], this period might have been too short for an optimal
evaluation of the differences in AUC for TAG. We did not measure the
quality of the postprandial TAG response, and therefore we do not know
whether the TAGs are exogenously or endogenously synthesised. The
higher TAG level seen after the high GI, low DF breakfasts could be due to
a prolonged elimination of exogenous TAG-rich chylomicrons,
chylomicron remnants, or increased endogenous lipid synthesis. It is
probably a combination of both.
The treatment periods in studies II and IV were relatively short. In study II
it was not possible to elongate the study period, mainly because of
inconvenience for the study subjects. However, to examine the effects of a
change in the breakfast only (study IV) would have been possible, even in
the longer term.
The studies were performed in different categories of subjects, probably
with differences in their severity of glucose intolerance. The effect of a diet
high in carbohydrates and low in DF on the blood glucose control has been
shown to vary according to severity of glucose intolerance [191]. Thus the
results from studies III and IV may not be relevant in all respects for
subjects with type 2 diabetes.
60
Conclusions
As discussed above, there is much evidence supporting the benefit of
including low GI foods in the diet for people with the insulin resistance
syndrome – with or without diabetes mellitus.
Main conclusions:
ƒ Differences in postprandial responses to starchy foods persist even
when the foods are incorporated into mixed meals composed in
accordance with dietary recommendations, and with identical
nutrient compositions and DF contents (paper I).
ƒ A diet characterised by low GI starchy foods lowers the glucose and
insulin responses throughout the day and improves the lipid profile
and capacity for fibrinolysis. A low GI diet thus has several
advantages in the treatment of type 2 diabetes and the insulin
resistance syndrome (paper II).
ƒ Even a moderate change of the diet, such as selecting low GI foods
high in soluble DF for breakfast, gives a more favourable metabolic
profile, with smaller excursions of glucose during the day, with
lower peaks and less undershoot below baseline after the meal
(papers III and IV).
ƒ Low GI breakfasts give lower insulin and C-peptide responses and
lower the TAG level after a standardised lunch. These effects were
even more pronounced when the low GI was combined with a large
amount of soluble DF (papers III and IV).
ƒ A low GI breakfast high in insoluble DF suppresses the NEFA levels
efficiently throughout the day (paper III).
61
Future perspectives
The result of many studies support the inclusion of low GI foods in the diet
for people with diabetes and the insulin resistance syndrome. However,
most of these investigations have been conducted during rather short time
periods. There is a need for a large well-planned investigation of the longterm effects of a diet with a low GI. This should preferably be performed in
subjects with insulin resistance and overweight persons. Specific aims
should be to establish whether a change towards a diet with a lower GI is
feasible in the long term and whether the metabolic effects seen in shortterm studies persist or can even be reinforced. Long-term effects on weight
control are another specific question to be addressed.
The GI tables need to be further developed and native foods and traditional
dishes should be tested for their GI values. With GI values of additional
foods included in the tables, it could be possible, in addition to calculating
the energy, nutrient and DF contents, to calculate the GI by computerised
programs. Low GI foods should be regarded as a part of a healthy diet and
the concept should be made more “user-friendly”, with practical advice
about foods low in GI in educational materials.
There is a need for more low GI products, especially breakfast cereals and
bread. Today there is much knowledge regarding ways of optimising the GI
of foods through the choice of raw material and changes in processing
conditions, sometimes even by modest modifications [41]. Low GI foods
are valuable especially for those with diabetes, hyperlipidaemia and
obesity, but it should be stressed that such foods can probably be regarded
as healthy for most people.
As for dietary fat, dietary carbohydrates are not homogeneous with respect
to chemical structure and biological functions. Thus all carbohydrates
should not be regarded as equal, and the type of carbohydrate-rich foods
included in the diet should be considered when investigating the effects of
other nutrients. Information about the content of DF is sometimes given but
there is rarely any information about the GI of the carbohydrate-rich foods.
Diets high in monounsaturated fatty acids are sometimes considered to be
more healthy for people with diabetes [19] than are diets with a high
carbohydrate content. A high-carbohydrate diet has been regarded as
62
detrimental for people with diabetes, as it may induce hypertriglyceridaemia and lower the HDL cholesterol as well as increasing the
blood glucose level [192]. It is important to emphasise that these effects
have mainly been observed in isoenergetic weight-maintaining diets, often
without a definition of the type of carbohydrate-rich foods included.
Studies on the long-term effects on the metabolic control and body weight
after advice about a diet high in monounsaturated fatty acids in
comparison with a diet high in low GI carbohydrate-rich foods would be
desirable.
63
Acknowledgements
The work was carried out at the Department of Public Health and Caring Sciences,
Section for Geriatrics/Clinical Nutrition Research at Uppsala University, Sweden. I
wish to express my sincere gratitude and appreciation to everyone who have been
involved in the work underlying this thesis, with special thanks to:
Bengt Vessby, my supervisor, who encouraged me to perform this work, for your never
ending enthusiasm, for expert scientific support, great knowledge in nutrition research,
constructive criticism and for never ending patience and encouragement.
Brita Karlström, my second supervisor, co-worker and friend for introducing me into
clinical nutrition research, teaching me all about the practicalities in nutrition research,
for great support and optimism and for showing me how to enjoy the good things in life.
Hans Lithell, the head of the department for providing me the opportunity to carry out
my project at the department and for creating a productive working atmosphere.
Marina Spoverud-Älvebratt, the chef in the metabolic kitchen for preparing all the
different (and sometimes strange) diets and enthusiastically encouraging the subjects to
participate.
The entire staff at the metabolic ward, for good collaboration throughout the years both
at the clinic and with the research work. Especially thanks to those in charge of the
blood sampling in the studies for taking excellent care of the study participants, GunBritt Ångman, Bitte Söderling and Birgitta Hyvänen.
Barbro Simu, Eva Sejby and Siv Tengblad, for excellent laboratory work
Lars Berglund and Rawya Mohsen, for skilled and invaluable help with the statistics.
My friends and colleagues in Bengt´s group at the section for Clinical Nutrition
Research: Agneta Andersson, Achraf Daryani, Johanna Helmersson, Marie LemckeNorojärvi, Margaretha Nydahl, Cecilia Nälsén, Ulf Risérus, Annika Smedman and Eva
Södergren for interesting discussions at the nutrition seminars and for sharing the joy of
being a PhD student in nutrition research. A special thanks to Agneta, for being a good
friend and the perfect coach, trying to teach me that winning isn’t everything – it’s the
only thing!
All dietitian colleagues at “Länsgeriatriska kliniken” and “Medicinkliniken”, Uppsala
University Hospital for being great colleagues and friends. A special thanks to Susanne
Fredén, Agneta Nilsson and Erika Olsson for happy workdays at the clinic during many
years.
Åsa Andersson, for introducing me to Brita Karlström, nearly 12 years ago.
64
Karin Andersson and Boel Sollenberg for helping me with energy and nutrient
calculations.
Jan Hall, for preparation of figures and illustrations.
My co-workers at the Department of Applied Nutrition and Food Chemistry, Chemical
Centre, Lund University: Inger Björck, Yvonne Granfeldt, Helena Liljeberg Elmståhl
and Nils-Georg Asp, for fruitful collaboration between our research groups.
My friends and colleagues at the section for Geriatrics and Clinical Nutrition Research:
Anders, Ann-Cristin, Anu, Arvo, Björn, Claes, Johan S, Johan Ä, Kristina B, Kristina D,
Lena K, Lennart, Liisa, Margareta Ö, Merike, Meta, Per-Erik, Rickard and Samar for
creating a pleasant working atmosphere.
Maud Marsden, for excellent linguistic revision of the manuscripts, making them
readable.
Study participants, for your enthusiastic participation in our studies.
My parents and my brother and sister with their families for always supporting me.
Fredrik, for patience and never ending support.
This work was supported by grants from the Swedish Medical Research Council, The
Cerealia Foundation for Research and Development, The Swedish Nutrition
Foundation, The Swedish Diabetes Association, Albert Påhlsson´s Foundation, the
Swedish Council for Forestry and Agricultural Research, the Ernfors Foundation, the
School of Household Management Fund and Birger Giertz foundation.
65
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