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Application of glycemic index to mixed meals

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Plasma glucose and insulin responses to six different meals were determined and compared with values predicted by published glycemic indices of the component foods. The test meals were of different ethnic origins: Indian (lentil curry with rice), Italian (spaghetti bolognaise), Chinese (stir-fried vegetables and chicken with rice), Greek (lentil stew), Western (sirloin chop and vegetables); and Lebanese (sandwich with unleavened bread and hummos). Eight healthy volunteers were given 50 g carbohydrate portions of the above meals after an overnight fast. The glycemic and insulin indices were highest for the Lebanese meal and lowest for the Greek with significant differences among the meals (ANOVA, p less than 0.05). The observed glycemic indices correlated well with the predicted glycemic indices (r = 0.88, p less than 0.01) and insulin responses parallelled the glycemic responses (r = 0.83, p less than 0.05). These results suggest that the glycemic index approach will be useful in planning diets for diabetic people.
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Am J C/in Mar l988;47:53-6. Printed in USA. © 1988 American Society for CliniCal Nutrition 53
Application of glycemic index to mixed meals1’2
Irene Chew, BSc; Janette C Brand, PhD; Anne W Thorburn, BSc; and AS Truswell, MD
Introduction
ABSTRACI Plasma glucose and insulin responses to six different meals were determined
and compared with values predicted by published glycemic indices of the component foods.
The test meals were ofdifferent ethnic origins: Indian (lentil curry with rice), Italian (spaghetti
bolognaise), Chinese (stir-fried vegetables and chicken with rice), Greek (lentil stew), Western
(sirloin chop and vegetables); and Lebanese (sandwich with unleavened bread and hummos).
Eight healthy volunteers were given 50 g carbohydrate portions of the above meals after an
overnight fast. The glycemic and insulin indices were highest for the Lebanese meal and lowest
for the Greek with significant differences among the meals (ANOVA, p<0.05). The observed
glycemic indices correlated well with the predicted glycemic indices (r =0.88, p<0.01) and
insulin responses paralleled the glycemic responses (r =0.83, p<0.05). These results suggest
that the glycemic index approach will be useful in planning diets for diabetic people. Am
J Clin Nutr l988;47:53-6.
KEY WORDS Glycemic index, insulin responses
Methods
During the last few years it has been found that the
same weight of carbohydrate in different foods can pro-
duce widely different blood glucose reponses (glycemic
index). Tables are now available that compare the gly-
cemic index ofmany different foods, the implication being
that this approach will be helpful in planning meals for
individuals with diabetes (1). The nutrition committees
ofthe American and Canadian diabetes associations rec-
ommended that diets for diabetic people be planned with
the glycemic index of foods in mind (2, 3).
The question naturally arises whether glycemic index
can be used to predict the glycemic and insulin responses
to mixed meals. Coulston et al (4) reported that the gly-
cemic responses to mixed meals containing different types
of carbohydrate sources did not differ significantly and
concluded that the glycemic index approach would have
little clinical utility. Wolever et al (5) refuted these con-
clusions by demonstrating that the observed glycemic re-
sponses could be predicted by the glycemic indices of the
component foods.
The objective of this study is to determine the plasma
glucose and insulin responses of normal individuals to
six different mixed meals and to compare the results with
the values predicted by published glycemic indices of the
individual foods. The sources ofcarbohydrate were chosen
to represent the starchy staples of various ethnic groups,
ranging from high glycemic index (potato) in the Western
meal to low glycemic index (lentils) in the Greek meal.
The test meals were of six different ethnic origins: Indian
(lentil and cauliflower curry with rice), Italian (spaghetti bob-
gnaise), Greek (lentil stew with bread roll), Chinese (stir-fried
vegetables and chicken with rice), Western (sirloin chop with
vegetables and mashed potatoes), and Lebanese (sandwich of
unleavened bread, hummos, falafel, and tabouleh). Each meal
provided ‘-50 g available carbohydrate, 16 g fat, 16 g protein,
and 1700 Id (400 kcal) with 48% ofenergy as carbohydrate, 35%
as fat, and 17% as protein as determined by food composition
tables (6) (Table 1). A drink of water was given with the meals
to give a total meal weight of ‘-600 g.
Eight healthy volunteers (four women, four men) aged 21-
32 y with normal glucose tolerance participated in the study.
Their mean ± SEM body mass index was 22.3 ± 0.8 kg/rn2. The
subjects consumed each meal or 50 g glucose in randomized
order after an overnight fast on separate mornings 1 wk apart.
The meals were given at --0900 h and were eaten over 20 mm
with zero time as the time eating commenced. Fingerprick blood
samples were taken from warmed hands using an Autolet device
(EMP Surgical Pty Ltd. Collingwood, Victoria, Australia) at 0,
20, 30, 60, 90, 120, 1 50, and 1 80 mm. A 500-800 #L aliquot
ofcapillary blood was collected and mixed with 0.4 mg EDTA.
1From the Human Nutrition Unit, Department ofBiochemistry and
School of Public Health and Tropical Medicine, University of Sydney,
Sydney, Australia.
2Address reprint requests to Dr J Brand, Human Nutrition Unit,
008, University of Sydney, NSW 2006, Australia.
Received August 27, 1986.
Accepted for publication February 3, 1987.
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54 CHEW ET AL
TABLE 1
The nutritional composition of the meals
Chinese Indian Greek Italian Western Lebanese
Meal weight (g) 245 360 489 360 361 166
Energy(kJ) 1709 1685 1643 1680 1716 1717
(kcal) 407 401 391 400 409 409
Protein(g) 17 17 17 17 17 14
Fat(g) 16 16 15 17 15 16
Available carbohydrate (g) 515 1 50 48 53 50
Principal carbohydrate (g)
Rice 44 36
Lentils 13 24
Bread 16
Spaghetti 39
Potato 45
Lebanese bread 40
Chick peas 4
Plasma was removed after centrifugation (12 500 X g, I mm)
and stored at -80 #{176}C.Glucose was assayed by the glucose hexo-
kinase assay using the Glucose Rapid Centrifichem System
(Roche Diagnostica, Basle, Switzerland) and insulin by radio-
immunoassay (BioRIA, Montreal, Canada).
The glycemic index and insulin index of each meal in each
subject was determined using the following equations:
incremental area under 2 h
. . plasma glucose curve for meal x 100
Glvcemic index =. (1)
incremental area under 2 h
plasma glucose curve for 50 g glucose
incremental area under 2 h
.plasma insulin curve for meal X 100
Insulin index =incremental area under 2 h
plasma insulin curve for 50 g glucose
Results have been expressed as the mean ± SEM for the eight
subjects. Two-way analysis of variance (ANOVA) was used to
determine whether significant differences existed between the
glycemic and insulin indices ofthe meals. The observed glycemic
mndices were compared with those predicted by the published
TABLE 2
glycemic indices of the component foods (1) and with the gly-
cemic index of white bread used for Lebanese bread. The pre-
dicted values were calculated by summing the percent carbo-
hydrate contributions ofthe component carbohydrate-containing
foods (Table 2) multiplied by the published glycemic index value
for the single foods (1). Linear regression was used to measure
correlation between variables.
The study was approved by the Medical Ethical Review Com-
mittee of the University of Sydney.
Results
The mean glycemic and insulin response curves for the
(2) meals are shown in Figures 1and 2. The calculated gly-
cemic indices ranged from 40 ± 5 for the Greek meal to
86 ± 12 for the Lebanese meal (Table 2) with significant
differences among the meals (p <0.05). Insulin indices
ranged from 1 17 ± 33 for the Italian meal to 243 ± 74
for the Lebanese meal (Table 2)with significant differences
among the meals (p <0.05). There was a positive cor-
relation between the glycemic index and insulin index of
Predicted and observed glycemic and insulin indices ofthe meals and contribution ofthe carbohydrate-riCh foods to total carbohydrate content
Meal Contribution to
total carbohydrates Predicted
glycemic index Observed
glycemic index Observed
insulin index
%mean ±SEM mean ±SEM
Greek Lentils 48
Bread 32 38 40± 5 143±36
Italian Spaghetti 81 40 52± 9 117±33
Indian Lentils 26
Rice 71
60 60±10 188±63
Chinese Rice 86 65 73±17 188±58
Western Potato 85 69 66±12 226±78
Lebanese Lebanese bread 80
Chick peas 869 86 ±12 243 ± 74
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3
J- Western
Chinese
- Lebanese
Indian
.- Italian
Greek
0
-1’
f___ -
02030 60
Time (mm) 90 120
FIG 1. Mean glycemiC responses to each ofthe meals.
...- Western
Chinese
-Lebanese
-Indian
-Italian
Greek
E
C
0
C
S
E
S
S
a
.s 20
S
C
S
.C
C)
the meals (r =0.83, p <0.05) and between the observed
glycemic index and the predicted glycemic index (r =0.88,
p<0.01, Table 2).
Discussion
This study shows that there are significant differences
in the glycemic and insulin responses of healthy individ-
uals to different mixed meals. Moreover, the glycemic
indices of the mixed meals could be predicted from the
glycemic indices of the component carbohydrate foods.
Rank orders coincided for measured and predicted values
almost completely (Table 2). These results are contrary
to the report by Coulston et al (4) in which there were no
significant differences in the glycemic and insulin re-
sponses to three of the four mixed meals. There are im-
portant differences, however, between the two studies.
Coulston et al used individuals with noninsulin-dependent
diabetes and gave standardized meals containing a much
smaller amount ofthe varying test carbohydrate (30 g vs
39-49 g). The contribution of the test carbohydrate to
the total energy of the meal was therefore smaller (30%
vs 39-46%) and conversely the fat contribution was higher
(40% vs 35%). Because there are diurnal variations in oral
I-
020 30 60 90
Time (mm)
FIG 2. Mean insulin responses to each of the meals.
GLYCEMIC INDEX OF MIXED MEALS 55
glucose tolerance (7), it is also relevant that Coulston’s
meals were fed at 1200 h compared with 0900 h in this
study. Furthermore, unlike in Coulston’s study we did
not standardize the protein and fat sources. These factors
together may account for the difference in outcome be-
tween the two studies. Our study is in agreement with
other recent studies (5, 8) that have also shown that the
glycemic index approach is successful in predicting the
glycemic responses of healthy individuals as well as dia-
betic subjects to mixed meals.
Plasma insulin responses are also important in the study
ofphysiological responses to foods. Some meals have been
shown to give divergent plasma insulin responses in the
face ofsimilar plasma glucose responses (9). In our study,
the insulin indices correlated well with the glycemic in-
dices although they did not fall into the same rank order.
All the meals gave higher plasma insulin responses than
did oral glucose, which suggests that factors such as pro-
tein, fat, and other components of a mixed meal act as
insulin secretagogues.
Increasing evidence suggests that diets high in carbo-
hydrate and fiber and low in fat are beneficial in improving
50
40
30
10
120
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56 CHEW ET AL
carbohydrate metabolism in individuals with diabetes
(10). The findings of this study along with other recent
reports suggest that choice of carbohydrate-rich food is
important. The reduction of postprandial hyperglycemia
and hyperinsulinemia is an important treatment goal and
dietary management should be based on the sound
knowledge of plasma glucose and insulin responses to
mixed meals. The incorporation of low-glycemic index
carbohydrate foods such as legumes into the diet has
been shown to reduce both the postprandial and 24 h
glucose profile in individuals with diabetes (1 1). Unfor-
tunately legumes are not a major component of Western
diets and the required change in diet pattern may be dii’-
ficult to achieve. Palatability may be increased by using
a combination of low- and high-glycemic index foods as
was used in this study: the Greek meal (lentil soup) in-
eluded a bread roll and the Indian lentil curry included
rice. Although these results need to be confirmed in in-
dividuals with diabetes and with many more mixed meals,
they suggest that the glycemic index approach will be use-
ful in dietary planning. Other aspects such as fat content
need to be considered (12) and glycemic responses to
meals may also vary with the method of cooking and
processing (13).
Our results do not, of course, imply that all Greek and
Italian meals will give lower glycemic indices than Leba-
nese and Western meals. Nonetheless it is interesting to
speculate that the increasing prevalence of diabetes in
many countries may be partly related to fast-release nature
of the staple carbohydrate foods. We have suggested that
the slow-release nature of the traditional foods of Asia,
India, Oceania, and Southern Europe may be protective
against diabetes (14), particularly in those populations
which show a genetic predisposition to hyperinsulinemia.
Long-term studies oflow- and high-glycemic index diets
on carbohydrate metabolism in normal and diabetic in-
dividuals are therefore needed. B
References
I. Jenkins DJA, Wolever TMS, Taylor RH, et al. Glycemic index of
foods: a physiological basis for carbohydrate exchange. Am J Gin
Nutr l98l;34:362-6.
2. American Diabetes Association. Policy statement glycemiC effects
ofeffects ofcarbohydrates. Diabetes Care l984;7:607-8.
3. Special Report Committee, Canadian Diabetes Association. Guide-
lines for the nutritional management of diabetes mellitus. J Can
Diet Assoc l981;42:1 10-8.
4. Coulston AM, Hollenbeck CB, Liu GC, et al. Effects of source of
dietary carbohydrate on plasma glucose, insulin and gastric inhibitory
polypeptide responses to test meals in subjects with noninsulin-
dependent diabetes mellitus. Am J Gin Nutr 1984;40:965-70.
5. Wolever TMS, Nuttall FQ, Lee R, et al. Prediction of the relative
blood glucose response ofmixed meals usingthe white bread glycemic
index. Diabetes Care l985;8:4l8-28.
6. Paul AA, Southgate DAT. MeCance and Widdowson’s the com-
position offoods. London: Her Majesty’s Stationery Office, 1979.
7. Jarrett RJ, Baker IA, Keen H, Oakley NW. Diurnal variation in
oral glucose tolerance: blood sugarandplasma insulinlevels morning,
afternoon and evening. Br Med J 1972;1:l99-201.
8. Collier GR, Wolever TMS, Wong GS, Josse RG. Prediction of gly-
cemic response to mixed meals in noninsulin-dependent diabetic
subjects. Am J Clin Nutr l986;44:349-52.
9. Collier G, McLean A, O’Dea K. Effect ofco-ingestion of fat on the
metabolic responses to slowly and rapidly absorbed carbohydrates.
Diabetologia 1984;26:50-4.
10. Mann JI. Lines to legumes: changing concepts ofdiabetic diets. Di-
abetic Med 1984;l:19l-9.
11. Simpson HCR, Simpson RW, Lousley 5, et al. A high carbohydrate
(leguminous fibre)diet improvesall aspectsofdiabeticcontroL Lancet
l98l;l:l-5.
12. Thorburn AW, Brand JC, Truswell AS. The glycemic index of foods.
Med J Aust l986;l44:580-2.
I 3. Brand JC, Nicholson PL, Thorburn AW, Truswell AS. Food pro-
cessing and the glycemic index. Am J Gin Nutr l985;42:l 192-6.
14. Thorburn AW, Brand JC, Truswell AS. Slowly digested and absorbed
carbohydrate in traditional bushfoods: a protective factor against
diabetes. Am J Gin Nutr l987;45:98-l06.
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The glycaemic index of foods describes the hyperglycaemic effect of isolated foods. It is measured by the ratio of the area under the glycaemic curve observed after ingestion of a 50 gram carbohydrate dose of the tested food to the area observed after ingestion of the same amount of a reference food (white bread). The glycaemic index classification provides an approach of the diabetic diet based on the glucose response to foods. Widely accepted when applied to isolated foods, its clinical utility during mixed meals remains discussed. The improvement of the average metabolic control which can be expected from its use is modest. However, its major interest could be observed during snacks and meals in order to control precisely post-prandial glucose variations, in association with blood glucose self-monitoring. As it allows high sweet taste-low-glycaemic index-carbohydrate foods to be consumed, it could significantly improve the quality of life of diabetic patients.
Article
The determine the effect of different foods on the blood glucose, 62 commonly eaten foods and sugars were fed individually to groups of 5 to 10 healthy fasting volunteers. Blood glucose levels were measured over 2 h, and expressed as a percentage of the area under the glucose response curve when the same amount of carbohydrate was taken as glucose. The largest rises were seen with vegetables (70 +/- 5%), followed by breakfast cereals (65 +/- 5%), cereals and biscuits (60 +/- 3%), fruit (50 +/- 5%), dairy products (35 +/- 1%), and dried legumes (31 +/- 3%). A significant negative relationship was seen between fat (p less than 0.01) and protein (p less than 0.001) and postprandial glucose rise but not with fiber or sugar content.
Effects of source of dietary carbohydrate on plasma glucose, insulin and gastric inhibitory polypeptide responses to test meals in subjects with noninsulindependent diabetes mellitus
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  • G C Liu
CB, Liu GC, et al. Effects of source of dietary carbohydrate on plasma glucose, insulin and gastric inhibitory polypeptide responses to test meals in subjects with noninsulindependent diabetes mellitus. Am J Gin Nutr 1984;40:965-70.