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Glycemic Response to Pasta: Effect of Surface Area, Degree of Cooking, and Protein Enrichment

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To see whether food form, the degree of cooking, or protein enrichment affected the glycemic response to pasta, we gave test-meal breakfasts to 13 diabetic patients. Macaroni had a significantly greater glycemic index (GI) (68 +/- 8) than spaghetti (45 +/- 6, P less than .01); the GI of star pastina was intermediate (54 +/- 6). The GI of spaghetti was not significantly affected by cooking for 5 or 15 min (45 +/- 6 and 46 +/- 5, respectively), or by protein enrichment (38 +/- 4). The GI of spaghetti was similar in 11 non-insulin-dependent and 6 insulin-dependent diabetic patients (49 +/- 7 compared with 57 +/- 8). We conclude that different types of pasta may produce different glycemic responses but that these are not necessarily related to differences in cooking or surface area.
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G
lycemic
Response to Pasta: Effect of
Surface
Area, Degree of Cooking, and
Protein
Enrichment
T.
M. S.
WOLEVER, BM, MSc,
D. J. A.
JENKINS, DM,
J.
KALMUSKY, RPDt,
C.
GIORDANO, RPDt,
S.
GIUDICI, RPDt,
A.
L.
JENKINS, RPDt,
L. U.
THOMPSON, PhD,
G. S.
WONG, MD, AND
R. G.
JOSSE,
MD
To
see whether food form, the degree of
cooking,
or protein enrichment affected the glycemic response
to
pasta, we gave test-meal breakfasts to 13 diabetic patients. Macaroni had a significantly greater
glycemic
index (GI) (68 ± 8) than spaghetti (45 ± 6, P < .01); the GI of star pastina was intermediate
(54
± 6). The GI of spaghetti was not significantly affected by cooking for 5 or 15 min (45 ± 6 and
46
± 5, respectively), or by protein enrichment (38 ± 4). The GI of spaghetti was similar in 11 non-
insulin-dependent
and 6 insulin-dependent diabetic patients (49 ± 7 compared with 57 ± 8). We
conclude
that different types of pasta may produce different glycemic responses but that these are not
necessarily
related to differences in cooking or surface area,
DIABETES
CARE
1986;
9=401-404.
T
here is much interest in the glycemic responses to
carbohydrate foods in diabetic patients.1"8 Many
factors affect the glycemic response to meals: im-
portant among these are the food form,69 particle
size,
10
'
11
protein content of the meal,12 and the degree of
cooking.713 Pasta is a popular starchy food, which, in the
form of spaghetti, has been shown to have a low glycemic
response, ~60% that of bread.4'6 However, there are many
different types of pasta available, and each type may have
potentially different metabolic effects because of different sur-
face areas and protein contents. In addition, the traditional
Italian method of cooking pasta
is
different from that in North
America; the Italians prefer their pasta relatively under-
cooked, or "al dente." We have therefore investigated the
effect on the glycemic response in diabetic patients of five
different forms of pasta: "overcooked" spaghetti, "under-
cooked" spaghetti, macaroni, star pastina (small pasta stars),
and protein-enriched spaghetti.
METHODS
Seventeen diabetic patients who had no evidence of gastro-
paresis were studied. Six were classified as insulin dependent
(IDDM: fasting C peptide <0.6 ng/ml with no postprandial
rise) and 11 as non-insulin dependent (NIDDM). Charac-
teristics of the IDDM and NIDDM subjects, respectively,
were
as
follows:
age, 50 ± 6 and 70 ±
2
yr; ideal body weight,
107 ± 5 and 129 ± 10%; duration of diabetes, 19 ± 4 and
10 ± 2 yr; mean fasting blood glucose, 8.7 ± 0.8 and
7.2 ± 0.5 mmol/L; and mean HbAlc, 8.2 ± 0.7 and
6.7 ± 0.4%. The IDDM patients took a mean of
31
± 5 U
of insulin per day. Seven of the NIDDM patients were treated
with insulin (mean 28 ± 11 U/day), three with oral hypo-
glycemic agents, and one with diet only. Fasting fingerprick
capillary blood samples were obtained (Autolet lancets, Owen
Mumford, Woodstock, Oxford, UK). Five minutes after the
patients took their usual insulin or other diabetes medications
(if any), a test meal was given. Fingerprick blood samples
were obtained every 30 min for 3 h after the start of each
meal for measurement of whole blood glucose with an au-
tomatic analyzer (Model 27, Yellow Springs Instruments, Yel-
low Springs, OH).
Test
meals.
Test-meal constituents and cooking methods
are shown in Table 1. White flour and the uncooked spaghetti
were analyzed for nutrient14 and dietary fiber content.15 Mac-
aroni and star pastina were assumed to have the same com-
position as the spaghetti from the same manufacturer.
Each test meal contained 50 g available carbohydrate from
white bread or pasta. For palatability, all the test meals were
served with 32 g cheddar cheese plus 100 g cooked tomato.
Each subject also took at least three test meals of white bread
only (mean 5.6 ± 0.7, range 3-12).
The test meals were consumed in random order. Four of
the IDDM subjects were unable to complete all the tests and
were given only the 5-min spaghetti test meal. Because no
significant difference in the glycemic response to spaghetti
DIABETES
CARE, VOL. 9 NO. 4, JULY-AUGUST 1986
401
GLYCEMIC RESPONSE TO PASTA/T. M. S. WOLEVER AND ASSOCIATES
TABLE 1
Test-meal constituents, cooking methods, and mean ± SE glycemic indices
FoodDry wt
(g)Cooking methodGlycemic index'
White bread
White bread + C + Tt
5-min spaghetti§ + C + T
15-min spaghetti§ + C + T
Macaroni§ + C + T
Star pastina§ + C + T
Spaghetti|| + C + T
(protein-enriched)
67.0t
67.
Ot
66.0
66.0
66.0
66.0
66.3
Baked in diet kitchen
Baked in diet kitchen
Boiled, 180 ml water, 5 min
Boiled, 300 ml water, 15 min;
frozen, reheated before test
Boiled, 180 ml water, 5 min
Boiled, 180 ml water, 5 min
Boiled, 180 ml water, 7 min
100A
99 ± 4A
45 ± 6B
46 ± 6B
64 ± 8C
54 ± 6BC
38±4
R
Excess water from cooking was consumed with the test meals.
'Means not sharing the same letter superscript are significantly different (P < .01).
tWeight of flour. $C = 32 g mild cheddar cheese, T = 100 g cooked tomato. §Lancia-Bravo Foods Ltd., Toronto, Canada; ||Catelli Plus, Catelli Ltd.,
Montreal, Canada.
was found between IDDM and NIDDM subjects, the results
of 2 IDDM subjects who completed all the test meals were
pooled with the results of the 11 NIDDM subjects.
The study was approved by the human experimentation
ethics committee of the University of Toronto.
Data
analysis.
The glycemic indices (GIs) of the test meals
were calculated using the three white bread tests taken closest
to the date of each test meal, which has been shown to
minimize the variability of GI calculations.16 Results are ex-
pressed as means ± SE. The dimensions of uncooked pasta
were measured and the surface areas calculated by appropriate
formulas. Incremental areas under the blood glucose response
-O White bread
-#-
White bread plus cheese and tomato
60 120
Time (min)180
FIG. I. Mean ± SE blood glucose responses of 13 diabetic patients
(I I NIDDM and 2 IDDM) who took meals of white bread containing
50 g available carbohydrate or same amount of white bread with 32 g
cheddar cheese plus 100 g cooked tomato.
curves were calculated geometrically using the blood glucose
increments.17 Any area beneath the fasting blood glucose
level was ignored. After demonstration of significant heter-
ogeneity by two-way analysis of variance,18 the means were
compared using Fisher's test (if F > 10) or Tukey's test (if
F < 10). The significance of the differences for the six IDDM
patients who tested spaghetti and bread was assessed by Stu-
dent's t test for paired data.
RESULTS
Effect of added cheese and tomato. The effect on the glycemic
response of adding cheese and tomato to bread was negligible
(Fig. 1, Table 1). Therefore, no adjustment for added cheese
and tomato was made to the GI of the pasta meals.
Effect
of
type
of pasta. The mean glycemic responses to the
pasta meals were significantly lower than those to the bread
meals (Fig. 2, Table 1). The GI of spaghetti was significantly
lower than that of macaroni (P < .01). The glycemic re-
sponses to star pastina and protein-enriched spaghetti were
not significantly different from those to regular spaghetti (Fig.
2,
Table 1).
Effect of
cooking.
Cooking spaghetti for 5 or 15 min had
virtually no impact on the mean glycemic response (Fig. 2)
orGI (Table 1).
Comparison of IDDM with NIDDM subjects. IDDM and
NIDDM subjects responded similarly to spaghetti cooked for
5 min, or "al dente" (Fig. 3). The GIs for spaghetti in IDDM
(57 ± 8, N = 6) and NIDDM (49 ± 7, N = 11) patients
were not significantly different.
DISCUSSION
T
he results confirm the low GI of pasta.6 In addition,
they indicate that differences exist in the glycemic
response to different forms of pasta; these differ-
ences are not necessarily related to the surface area,
the degree of cooking, or protein enrichment.
Surface area has been ascribed an important role in deter-
402DIABETES CARE, VOL. 9 NO. 4, JULY-AUGUST 1986
GLYCEMIC RESPONSE TO PASTA/T. M. S. WOLEVER AND ASSOCIATES
O-White Bread
-A- Star Pastina
Macaroni
Spaghetti
-O White Bread -#- Enriched Spaghetti
Spaghetti -Q- 15min Spaghetti
60 120
Time (min)180
FIG.
2.
Mean
± SE
blood glucose responses
of 13
diabetic patients
(11 N/DDM and
2
IDDM) who took meals of white
bread,
macaroni,
star pastina,
5-min
("aldente")
spaghetti,
15-min {overcooked) spaghetti,
or protein-enriched
spaghetti.
For each time, means not sharing same letter
are significantly different
(P < .01).
mining the rate of digestion of starch, which, in turn, is
related to the glycemic response.19 Increasing the surface area
by grinding rice, for example, has been associated with an
increased rate of enzymatic hydrolysis and enhanced glycemic
and endocrine responses.1011 Although the surface areas of
the 66-g portions of uncooked spaghetti, macaroni, and star
pastina were quite different
(0.11,
0.091,
and 0.14 m2, re-
spectively), they did not relate to the glycemic response. This
was probably because the surface areas would have been in-
creased to different extents by chewing.
Starch produces a greater glycemic response when cooked
than when consumed raw,713 presumably because cooking
increases the degree of starch gelatinization and its suscep-
tibility to enzymatic digestion. In this study, the difference
between cooking spaghetti for 5 or 15 min was not reflected
in a different glycemic response, despite the fact that the
"overcooked" spaghetti was frozen and reheated as well as
cooked for a longer period of time and was, therefore, much
softer than the 5-min spaghetti. Nevertheless, our "over-
cooked" spaghetti may not have been overcooked enough to
see the true effect of the very-overcooked pasta that is some-
times eaten in North America (e.g., canned pasta).
The addition of protein to meals has been found to increase
insulin secretion and reduce the glycemic response12 only
when relatively large amounts of protein (30-50 g protein/
50
g
carbohydrate) are used. The lack of effect of added cheese
and tomato (containing 9.1 g protein) or of protein-enriched
spaghetti (2.3 g more protein than the portion of regular
o-White bread
-•- Aldente spaghetti
IDDM
60 120
Time (min)180
FIG.
3.
Mean
±
SE blood glucose responses of 6 IDDM subjects (top
panel) and JJ NIDDM
subjects
(bottom panel) who took meab of
white bread or "al dente" spaghetti.
DIABETES CARE, VOL. 9 NO. 4, JULY-AUGUST 1986403
GLYCEMIC RESPONSE TO PASTA/T. M. S. WOLEVER AND ASSOCIATES
spaghetti) on the glycemic response was probably due to the
small amounts of protein added.
We conclude that pasta has a significantly lower GI than
bread. However, different types of pasta have different gly-
cemic responses that are not necessarily related to surface
area, the degree of cooking, or protein enrichment.
ACKNOWLEDGMENTS:
T.M.S. W. received a Fellowship from the
Kellogg's Company, Battle Creek, Michigan. These studies
were supported by the Natural Sciences and Engineering Re-
search Council of Canada.
From the Department of Nutritional Sciences, Faculty of Med-
icine (T.M.S.W., D.J.A.J., J.K., C.G., S.G., A.L.J., L.U.I.); and
the Division of Endocrinology and Metabolism, St. Michael's Hos-
pital (T.M.S.W., D.J.A.J., G.S.W., R.G.J.), University of Toronto,
Toronto, Ontario M5S 1A8, Canada.
Address reprint requests to Dr. Thomas M. S. Wolever at the
above address.
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404DIABETES CARE, VOL. 9 NO. 4, JULY-AUGUST 1986
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Diet plays a critical role in the management of many chronic diseases. It is well known that individuals with type 2 diabetes (T2D) need to pay close attention to foods rich in carbohydrates to better manage their blood sugar. Usually, individuals are told to increase their dietary fiber intake which is associated with better glycemic control and limit their overall carbohydrate consumption. However, there are many other cooking strategies available to reduce the glycemic response to meals rich in carbohydrates and with a high glycemic index, such as adding fats, proteins, or vinegar, modifying the cooking or preparation processes, and even the selection and storage of foods consumed. The aim of the present narrative review is to summarize some of these existing strategies applied to the cooking process and their ability to modulate glycemic response to meals in individuals with T2D.
... La combinaison de niveaux d'humidité élevés et de températures élevées (par exemple pendant la cuisson ou le séchage au tambour) ou la haute pression et le cisaillement (comme dans la cuisson par extrusion) va entraîner un changement de structure de l'amidon : le SDS devient alors plus rapidement digestible [440], alors qu'un degré inférieur de gélatinisation ou le gonflement limité des granules d'amidon, qui est principalement déterminé par des niveaux d'humidité modérés, le temps de cuisson et la température, préserve la teneur en SDS comme pour le riz étuvé et certains type de biscuits et de pâtes [453,454]. Selon les procédés utilisés, le ratio SDS/RDS du produit final va être modifié et c'est finalement ce ratio qui va moduler la réponse glycémique. Pour illustrer l'impact de ces facteurs, Vinoy et al. [440] ont produit trois produits céréaliers transformés selon trois méthodes différentes : des biscuits (cuisson au four), du pain blanc (panification) et des céréales extrudées (cuisson au four-extrusion). ...
Thesis
L’hyperglycémie chronique est impliquée dans le développement de complications associées au DT2 et la variabilité glycémique (VG) apparait comme une composante à part entière de l'homéostasie du glucose. Les mesures hygiéno-diététiques, en première ligne dans la prise en charge du DT2, passent entre autres par une modification de l’alimentation, dans laquelle les glucides occupent une place prépondérante. Au-delà de la quantité, la qualité des glucides a été mise en avant comme ayant un impact déterminant sur les excursions glycémiques. Notamment, la digestibilité des produits à base d’amidon pourrait alors avoir un impact sur le contrôle glycémique chez les patients atteints de DT2. Mais il y a aujourd’hui un réel besoin d’apporter une caractérisation des produits plus complète sur cet aspect et de mener des études de faisabilité et d’efficacité de tels régimes modulant la digestibilité de l’amidon. Mes travaux de thèse montrent qu’il est possible de concevoir un régime riche en amidon lentement digestible (SDS), grâce à des choix de produits amylacés disponibles dans le commerce, des conseils de cuisson et des recommandations adaptées. Pour la première fois, nous avons montré que le contrôle de la digestibilité de l'amidon de produits amylacés avec des instructions de cuisson appropriées dans une population atteinte de DT2 augmentait la consommation de contenu en SDS dans un contexte de vie réelle et que ce type de régime était bien accepté dans telle population. De plus, nous avons montré que l’augmentation du rapport SDS/glucides était associée à une amélioration du contrôle glycémique postprandial et qu’il existait une corrélation linéaire inverse entre les paramètres de VG et la teneur en SDS. La mise en œuvre d’un régime riche en amidon lentement digestible dans une population atteinte de DT2, a montré une différence significative sur le profil de variabilité glycémique, mais également sur les excursions glycémiques postprandiales, évalués par le CGMS, en comparaison avec un régime pauvre en amidon lentement digestible. Ce type de régime a également permis aux patients d’atteindre des cibles glycémiques postprandiales plus appropriées. Grâce à un travail de revue de la littérature, nous avons mis en évidence que la déviation standard (SD), le coefficient de variation (CV), l’amplitude moyenne des excursions glycémiques (MAGE) et la moyenne glycémique (MBG) étaient les paramètres de VG les plus étudiés en termes de relation avec les paramètres de diagnostic du DT2 et les complications liées au DT2 et qu’ils montraient des relations fortes, en particulier avec l’HbA1c. Dans les études interventionnelles, nous avons pu voir que la SD, le MAGE et le temps dans la cible (TIR) étaient les paramètres les plus utilisés comme critères d’évaluation, montrant des améliorations significatives suite aux interventions pharmacologiques ou nutritionnelles, souvent en lien avec des paramètres de contrôle glycémique comme l’HbA1c, la glycémie à jeun ou en postprandial. La VG apparaît donc comme une composante clé de la dysglycémie du DT2. Au-delà de son utilisation par le patient comme support du contrôle glycémique, le CGMS apparait comme un outil pertinent en recherche clinique pour évaluer l’efficacité des interventions même si à ce jour, il reste encore très peu utilisé pour les interventions nutritionnelles. Des études plus approfondies seront cependant nécessaires pour confirmer l'impact bénéfique de telles interventions alimentaires à long terme. Nous avons conçu une étude à plus grande échelle pour étudier l'impact à long terme d’un régime riche en SDS sur la variabilité et le contrôle glycémiques (CGMS) et les complications et comorbidités associées chez le patient atteint de DT2. La modulation de la digestibilité de l'amidon dans l'alimentation pourrait alors être utilisée comme un outil nutritionnel simple et approprié pour améliorer l'homéostasie glucidique au quotidien dans le DT2.
... Le Dockounou optimisé (IG=79) et le Dockounou traditionnel (IG=81) ont montré des valeurs IG presque similaires et l'analyse statistique n'a pas révélé de différences entre les valeurs d'IG. Les valeurs d'IG des aliments testés ont été identifiées comme étant des IG élevés[30],[31]. Ces gâteaux sont donc considérés comme des aliments hyperglycémiants. ...
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Des données récentes recueillies à partir de l'optimisation de la fabrication du gâteau dockounou ont montré qu'un dockounou optimisé pourrait être un excellent moyen de valorisation de la banane plantain trop mûre. Mais, à ce jour, il existe peu de données scientifiques sur les propriétés glycémiques de cet aliment, qui est intégré dans les habitudes alimentaires urbaines. Nous avons donc déterminé l'index glycémique et la charge glycémique d’un dockounou traditionnel et le dockounou optimisé. En outre, nous avons réalisé leur profilage glucidique, dont la présence dans ces mets n’a été que peu étudiée. Dans l'ensemble, il n'y a pas eu de variations considérables dans leur composition nutritionnelle, à l'exception des cendres et des glucides. Les valeurs suivantes ont été obtenues pour les composantes glucidiques (g/100 g): amidon (32,4-33,7); saccharose (4,1- 8,8); glucose (20,1-20,7); fructose (21,1-22,6); fibres solubles (2,5-2,5) et fibres insolubles (6,9-6,9). L’index glycémique et la charge glycémique étaient respectivement de 79 et 20,4 pour le dockounou optimisé et respectivement de 81 et 21,3 pour le dockounou traditionnel. Ces résultats confirment bien que ces aliments sont une bonne source de glucides, notamment de la fraction glucose. Cependant, les niveaux élevés d'index glycémique et de charge glycémique impliquent une consommation avec modération.
... Two different types of pasta (spaghetti and penne), which represent the 2 best-selling types, were analyzed for potential differences due to shapes and sizes. This comparison demonstrated a lower glycemic response of the long pasta (spaghetti) compared with the short pasta (penne), as previously found (27,28). There were no clear differences in the amount of saliva, particle size distribution, or starch hydrolysis rates of spaghetti and penne boluses that could explain the difference seen in postprandial responses. ...
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Background: Structure and protein-starch interactions in pasta products may be responsible for lower postprandial glycemic responses compared with other cereal foods. Objective: We tested the effect on postprandial glucose metabolism induced by two pasta products, couscous and bread, through their structural changes during mastication and simulated gastric digestion. Methods: Two randomized controlled trials (n = 30/trial) in healthy normal weight adults (23.9 and 23.0 kg/m2) evaluated postprandial glucose metabolism modulation to 50g of available carbohydrate portions of durum wheat semolina spaghetti, penne, couscous, and bread. A mastication trial involving 26 normal weight adults was conducted to investigate mastication processes and changes in particle size distribution and microstructure (light microscopy) of boluses after mastication and in vitro gastric digestion. Results: Both pasta products resulted in lower areas under the 2h-curve for blood glucose (-40% for spaghetti and -22% for penne vs couscous; -41% for spaghetti and -30% for penne vs bread), compared with the other grain products (P < 0.05). Pasta products required more chews (spaghetti: 34 ± 18; penne: 38 ± 20; bread: 27 ± 13; couscous: 24 ± 17) and longer oral processing (spaghetti: 21 ± 13 s; penne: 23 ± 14 s; bread: 18 ± 9 s; couscous: 14 ± 10 s) than bread or couscous (P < 0.01). Pastas contained more large particles (46-67% of total particle area) compared to bread (0-30%) and couscous (1%) after mastication and in vitro gastric digestion. After in vitro gastric digestion, pasta samples still contained large areas of non-hydrolyzed starch embedded within the protein network, protein in bread and couscous was almost entirely digested, and starch was hydrolyzed. Conclusions: Preservation of the pasta structure during mastication and gastric digestion explains slower starch hydrolysis and, consequently, lower postprandial glycemia compared to bread or couscous prepared from the same durum wheat semolina flour in healthy adults. Postprandial in vivo trials were registered at clinicaltrials.gov as NCT03098017 & NCT03104686.Clinical Trial Registry: NCT03098017 & NCT03104686 www.clinicaltrials.gov.
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There has been much interest in the use of the glycemic index (GI). A recent study reporting plasma glucose responses to mixed meals containing fat and protein concluded that the results were totally disparate from what would have been expected from published GI values of the foods fed. However, this conclusion was based upon an inappropriate assessment of the data using absolute rather than incremental blood glucose response areas. The present report demonstrates how data may be analyzed to make use of the GI values of individual foods to predict the GI of mixed meals (r = 0.987; p less than 0.02). It is concluded that the GI concept applies well to mixed meals containing fat and protein.
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Unexpected plasma glucose responses to different mixed meals fed to normal and diabetic volunteers have recently been reported. We have therefore examined in normal volunteers the effect of mixing carbohydrate foods of different glycemic indices (GIs) without the addition of fat and protein. The observed GI of the mixed meal was within 2% of the expected value. In studies in the literature where fat and protein were added to mixed meals, the observed blood glucose responses also related significantly to the meal GIs calculated from the individual foods. Addition of fat and protein in the quantities used did not obscure this relationship. Studies to determine sources of error in comparing glycemic responses showed that type II diabetic patients displayed the least within-individual variation, and type I diabetic patients the most. Expression of results as the GI rather than as absolute glycemic response areas reduced by 50% the between-subject variation. The mean GI values of rice tested in type I and type II patients were similar (82 +/- 22 compared with 74 +/- 19) and the reproducibility 22 mo later in the same group of subjects was excellent (81 +/- 15 compared with 83 +/- 15). However, the lack of precise GI values for all foods fed in the test meals indicates a need for GI values to be derived for a wider range of individual foodstuffs. The GI approach to classifying foods according to physiologic effect may play a useful role in planning meals and diets in which specific blood glucose profiles are required.
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To examine whether the form of dietary carbohydrate influences glucose and insulin responses, we studied the glucose and insulin responses to five meals--each containing a different form of carbohydrate but all with nearly identical amounts of total carbohydrate, protein, and fat--in 10 healthy subjects, 12 patients with Type I diabetes, and 10 patients with Type II diabetes. The test carbohydrates were glucose, fructose, sucrose, potato starch, and wheat starch. In all three groups, the meal containing sucrose as the test carbohydrate did not produce significantly greater peak increments in the plasma concentration of glucose or greater increments in the area under the plasma glucose-response curves than did meals containing potato, wheat, or glucose as test carbohydrates. Urinary excretion of glucose in patients with diabetes was not significantly greater after the sucrose meal. The meal containing fructose as the test carbohydrate produced the smallest increments in plasma glucose levels, but the differences were not always statistically significant. In healthy subjects and patients with Type II diabetes, peak serum concentrations of insulin were not significantly different in response to the five test carbohydrates. Our data do not support the view that dietary sucrose, when consumed as part of a meal, aggravates postprandial hyperglycemia.
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The effect on plasma glucose concentration of four different, approximately isocaloric breakfasts designed using the American Diabetes Association food exchange lists was studied in eight type II diabetic patients. The meals were estimated to contain similar amounts of carbohydrate, protein, and fat and were given in random order. The plasma glucose responses to the different meals were similar except for one meal. This meal resulted in a greater glucose increase but the latter could be explained by the substitution of banana for orange juice in the meal. Banana contains starch as well as fructose and glucose, whereas orange juice contains glucose, fructose, and sucrose. In regard to the postmeal glucose response, these data indicate that the ADA food exchange list is useful in meal planning, at least for breakfast.
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