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Determination of Glycaemic Responses of Low Fat Milk Incorporated with Whey Proteins and Oats Powder



Objective: Investigation of glycaemic responses of low fat milk, enriched with whey proteins. Design: Randomized crossover study. Participants: Healthy volunteers (n=11) including both sexes (6 males and 5 females), aged between 20 and 30 years and with a body mass index of 18.5-23.5. Main outcome measures: Blood glucose concentrations at fasting and 30, 45, 60, 90, 120 min were measured following ingestion of; skimmed milk powder, incorporated with extra whey proteins and oats flour (4:1 ratio), containing 50 g of available carbohydrates. Glycaemic Index values were expressed as the average value of 11 subjects. Results: GI for the prepared formulation was 12 ± 2 and the average peak reduction of compared to the standard (Glucose) was 37.7%. Proximate analysis of the product indicated a higher total protein content (36.08 ± 2.5%) compared to fresh milk powder (21.9 ± 2.7%) and very low fat content (4.34 ± 0.5%) compared to fresh milk powder (29.3 ± 2.1%). Conclusions: Incorporation of whey powder have significantly reduced the Glycaemic index of milk (p<0.05). Although digestible carbohydrate content was increased by addition of oats and also being lower in fat; low GI milk powder formulations can be developed by incorporating whey proteins and cereal grains like oats.
Journal of Clinical Nutrition & Dietetics
ISSN 2472-1921
Vol.4 No.2:8
iMedPub Journals
Research Article
DOI: 10.4172/2472-1921.100070
© Under License of Creative Commons Attribution 3.0 License | This article is available in:
Manokaran S1,
Jayasinghe MA1*,
Senadheera AS2,
Gunathilaka SS3,
Kalina S1, Chandrajith VG1
and Ranaweera KDS1
1 Department of Food Science &
Technology, Faculty of Applied Sciences,
University of Sri Jayewardenepura, Sri
2 Department of Biochemistry, Faculty of
Medicine and Allied Sciences, Rajarata
University of Sri Lanka, Sri Lanka
3 Department of Microbiology, Faculty of
Medicine and Allied Sciences, Rajarata
University of Sri Lanka, Sri Lanka
*Corresponding author:
Madhura A. Jayasinghe
Department of Food Science & Technology,
Faculty of Applied Sciences, University of Sri
Jayewardenepura, Sri Lanka.
Tel: +94716255690
Citation: Manokaran S, Jayasinghe MA,
Senadheera AS, Gunathilaka SS,
Kalina S, et al. (2018) Determinaon of
Glycaemic Responses of Low Fat Milk
Incorporated with Whey Proteins and Oats
Powder. J Clin Nutr Diet Vol.4 No.2:8
Received: July 21, 2018; Accepted: August 03, 2018; Published: August 10, 2018
Objecve: Invesgaon of glycaemic responses of low fat milk, enriched with
whey proteins.
Design: Randomized crossover study.
Parcipants: Healthy volunteers (n=11) including both sexes (6 males and 5
females), aged between 20 and 30 years and with a body mass index of 18.5-23.5.
Main outcome measures: Blood glucose concentraons at fasng and 30, 45,
60, 90, 120 min were measured following ingeson of; skimmed milk powder,
incorporated with extra whey proteins and oats our (4:1 rao), containing 50 g
of available carbohydrates. Glycaemic Index values were expressed as the average
value of 11 subjects.
Results: GI for the prepared formulaon was 12 ± 2 and the average peak
reducon of compared to the standard (Glucose) was 37.7%. Proximate analysis
of the product indicated a higher total protein content (36.08 ± 2.5%) compared to
fresh milk powder (21.9 ± 2.7%) and very low fat content (4.34 ± 0.5%) compared
to fresh milk powder (29.3 ± 2.1%).
Conclusions: Incorporaon of whey powder have signicantly reduced the
Glycaemic index of milk (p<0.05). Although digesble carbohydrate content was
increased by addion of oats and also being lower in fat; low GI milk powder
formulaons can be developed by incorporang whey proteins and cereal grains
like oats.
Keywords: Glycaemic index; Low fat milk; Whey proteins; Oats
Determinaon of Glycaemic Responses of
Low Fat Milk Incorporated with Whey
Proteins and Oats Powder
In the current scenario, about 17% individuals in the world
populaon are assumed to be suering from diabetes and other
related non-communicable diseases, due of their improper food
habits [1]. Diabetes is a non-communicable disease which is
resulted by connued increase of the blood glucose levels rapidly
and habitually [2]. The concepts of Glycemic Index and glycemic
load are used widely to idenfy impacts by food sources on blood
glucose rise.
There are several factors aecng the GI of food. Recent studies
indicate that certain milk proteins have insulin tropic properes
and may substanally increase post prandial levels of insulin [3].
According to the Ercan’s research, he observed that a decrease
of the glucose response when a reasonable amount of fat was
ingested together with carbohydrates [4].
Though several people are avoiding the dairy and dairy products
because they believe it increase the obesity, osteoarthris and
CVD, according to the Serge Roz Enberg et al. [5], dairy products
do not increase the risk of cardiovascular disease, parcularly if
low fat.
This study was designed focusing on the glycemic responses in
milk powder; with reduced fat and increased whey proteins.
Many high protein dairy based powder formulaons available in
Vol.4 No.2:8
Journal of Clinical Nutrition & Dietetics
ISSN 2472-1921
This article is available in:
the market are also rich in other calorie contributors, namely fats
and carbohydrates. Although these milk powder products provide
high calories and proteins, their higher impact to elevate blood
glucose levels aer consumpon, may induce the risk of geng
pre-diabetes condions when regularly consumed. Further, the
high fat content may elevate total triglycerides and LDL in blood
as well. Hence, cow milk was formulated and standardized to
reduce its fat and, not all reduced fat has contributed in relave
increase of carbohydrates in milk, but more milk whey proteins
were incorporated to the nal formulaon. So, the nal milk
product is a low fat-high protein diet.
Many Asians including Sri Lankans incorporate sugar (sucrose)
when consuming milk powder as tea or as whole milk. Hence, it is
important to have an inial low Glycemic Index in the formulated
milk powder, which will not greatly increase the glycemic
responses aer incorporaon of sugar to it.
Both proteins and fats in food are known to reduce the blood
glucose elevaons [6], but it was unknown which may have
higher impact to reduce GI in dairy sources. Therefore, this
study will be a determining factor to understand the realisc and
relave impact on glycemic responses by milk whey proteins and
milk fat altogether.
Materials and Methods
Fat was reduced (5.31%) in cow milk (15 L) and was spray dried
to reduce moisture up to 3.5%. Oats powder and whey protein
powder were obtained from reputed commercial brands and
ground to make a ne powder (parcle size 0.05–0.01 mm). For
100 g of milk powder, 20 g of whey and 10 g of oats powder were
Preparaon of breakfast meals: Skimmed milk powder was mixed
with powdered oats and whey. The raos of food ingredients
for each food were selected by considering the palatability test
decided via a panel (non-trained).
Analysis of proximate composion: Proximate composions
of the powder mixture was determined. The moisture and ash
contents were measured by AOAC ocial methods [7,8]. The
digesble carbohydrate content, fat and soluble & insoluble
dietary bre was determined with Holm’s method [9], Croon
and Guchs [10] and by the method of Asp [11] respectively.
The crude protein was by Kjeldahl method using Copper/
Selenium catalysts [12].
Ethical clearance: Ethical clearance (No.77/17) was obtained
from the Ethical Review Commiee, Faculty of Medical Sciences,
University of Sri Jayewardenepura, Sri Lanka. Informed wrien
consent from all parcipang subjects was obtained prior to the
Determinaon of glycaemic indices: Determinaon of the GI
was carried out as a randomized crossover study, reviewed by
Brouns et al. in 2005 [13]. Healthy volunteers (n=11) including
both sexes (6 males and 5 females), aged 20 - 30 years and with
a body mass index of 18.5-23.5 were selected. The subjects were
asked to refrain from smoking, taking alcohol and to restrict
vigorous physical acvies the day before.
Glucose was used as the standard food (GI=100). The test food
(within 2 hours following preparaon) and the standard food
were served to the same individual on separate occasions
randomly. Following an overnight fast of 8 - 12 hours, a nger
prick capillary blood sample was obtained from the subject. The
subject was served with standard or test food containing 50 g
of digesble carbohydrate porons to be consumed within 10
minutes with 250 ml drinking water. Capillary blood samples were
collected at 30, 45, 60, 90 and 120 min following the rst bite of
the meal. Serum glucose concentraons were determined with a
Glucose-Oxidase kit (BIOLABOSATM; Biolabosa, France). The GI
was calculated using the mean of the individual incremental area
under the curve of the test food and of the standard food [13].
The glycaemic load (GL) value of the test food was calculated. (GL
= GI*digesble starch per serving (g))/100).
Stascal analysis: Proximate composion values were expressed
as the mean ± standard deviaon. GI values are expressed as the
mean with SEM. The means of the GI values of test food were
compared with typical cow milk, using a paired Student’s t-test
using Microso Excel 2013 at 95% condence level.
Proximate composions of fresh cow milk powder and the
formulated new powder sample are stated in Figure 1. Signicant
dierences were observed (p<0.05) in all three macronutrient
contents (fat, protein, digesble carbohydrates) between the
two samples. Crude bre contents in both samples were not
measurable. The remainders were considered to be mineral ash.
GI for the prepared formulaon was 12 ± 2 (Low GI) and that is
signicantly (p<0.05) lower compared to the stated GI of fresh
milk, that is 36 as was found by David et al. [14]. A lowering of GI
about three mes in the new powder formulaon was achieved
due to incorporaon of whey and oats powder to replace great
amount of milk fat.
The average maximum peak value for glucose is 162.7, and the
average peak value for the newly formulated powder was greatly
reduced up to 101.3 (Table 1). Hence the peak reducon is by
37.73% (Table 2).
The glycaemic response curve of the prepared powder formulaon
(Figure 2) clearly indicated a lower peak value compared to the
standard (Glucose). The peaking me was observed earlier by 15
minutes compared to glucose (Figure 2).
According to the Glycaemic Load scale GL values 20 are
considered as high, between 11 to 19 as intermediate and GL
10 as low. The calculated GL value for the formulated powder
sample was 2.3 (Table 2); that indicates of a very low GL value.
Journal of Clinical Nutrition & Dietetics
ISSN 2472-1921
© Under License of Creative Commons Attribution 3.0 License
Vol.4 No.2:8
to incorporaon of oats powder. The fat; which is a known factor
for reducing GI, was lower in the new formulaon compared to
fresh milk. The results of proximate analysis did not reveal of a
considerable inclusion of dietary bre by oats powder to the new
formulaon as well. Hence, the addion of whey proteins can be
considered as the crucial factor aecng the signicant reducon
observed in GI.
Cow milk contains, many essenal nutrients which helps to
maintain the healthy human life style. According to some
sciensts, there is no evidence to achieve essenal nutrients
requirement by a dairy free diet [5]. The problem is that; may
Asians including Sri Lankans carry the habit of incorporang
sugar when drinking milk. Hence, it is of utmost importance to
decrease the inial GI of milk as low as possible.
It was unknown that how the reducon of fat and increment
of whey proteins together impact on the glycemic impact on
milk; especially when the digesble carbohydrate content too is
increased by addion of cereals like oats. Both the increment of
digesble carbohydrate content by addion of cereal powder,
and also reducon of fat can increase the GI, but this study
reveals that; incorporaon of a considerable amount of whey
proteins can overcome both those impacts.
Glycaemic load allows comparisons of the likely glycaemic eect
of realisc porons of dierent foods, calculated as the amount
of carbohydrate in one serving mes the GI of the food. Majority
of the volunteers menoned that the poron size (89.5 g of
powder in total of 350 mL volume) of newly formulated powder
product as ‘larger’. Therefore, the GL value for the considered
powder formulaon may be lower, when considering the actual
poron size of a daily consumpon.
This study reveals of a very negave impact on blood glucose
elevaons by whey proteins which exceeds such an impact by
the milk fat content. Hence, these ndings may be of importance
for dairy powder producers in future.
Whey protein has a great impact on reducing glycemic responses
of milk. That can overtake the impact to increase the GI in
milk by reducon of fat and also a lile increase of digesble
carbohydrates by addion of cereal powders such as oats.
Hence, this informaon can be used by industrial producers in
formulang low fat-high protein milk powder products.
We are grateful to Prof. Sampath Amarathunga, the vice
chancellor of University of Sri Jayewardenepura – Sri Lanka and
Prof. Sudantha Liyanage, the Dean of the faculty of Applied
Food 0 min 15 min 30 min 45 min 60 min 90 min 120 min
(Glucose) 93.4 128.7 151.9 162.7 137.2 120.5 96.5
sample 92.4 99 101.3 95.8 95.3 97.4 93.1
Table 1: Average blood glucose values with me.
Mean GI 12 ±2
Standard error mean 1.7
Poron size 350 mL
Peaking me 30 min.
Peak reducon 61.4 mg/dL
% Peak Reducon (compared to Glucose) 37.73
% GI reducon (Compared to fresh milk) 66.7
Glycaemic Load 2.3
Table 2: Detailed glycemic response results in newly formulated powder.
Figure 2 Blood glucose response curves (Glucose vs. formu-
lated sample).
0 10 20 30 40 50 60 70 80 90 10 0
Blood glucose level (mg/dL)
Test time intraval
Curve 1
Curve 2
*Curve 1: Glucose (standard) Curve 2: Newly formulated
Figure 1 Comparison of macronutrient composion between
fresh milk and newly formulated powder product.
fat protein carbohydrate
Comparion of nutrion composion (grams in 100 g of powder)
Newly formulated
Fresh milk powder
Since there was a signicant reducon in GI compared to
fresh milk in the newly formulated powder; it can be assumed
that whey proteins has a great impact in reducing glycemic
responses. The digesble carbohydrate content was higher due
Vol.4 No.2:8
Journal of Clinical Nutrition & Dietetics
ISSN 2472-1921
This article is available in:
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... The findings revealed a significant difference in colonization with gram-negative enteric species that produce extended spectrum beta-lactamase (ESBL) [111]. Another study claims that L. casei has the ability to decrease colonization with beta lactamase producing pathogen in oropharyngeal flora [112]. These abilities of probiotics are used in nutraceutical and functional food development as symbiotic products [109]. ...
Food fermentation is one of the oldest food preservation and processing methods that uses live microorganisms and dates back thousands of years in human civilization. From those days, human society has used them without knowing the true value of these live microorganisms. But later, they understood the beneficial health effects of some organisms used in fermentation. Later they were named probiotics. With the advancement of science, the taxonomic and morphological details of probiotic bacteria and fungi were identified. In the early stage of human civilization, probiotics were used only for the preservation of excess food stuff, but now they have been used for many other aspects. Encapsulated probiotics and dried probiotics enhance the benefits of probiotics while reducing the major drawback of survivability in harsh conditions. Genetically engineered probiotics organisms open new avenues in the nutraceutical industry, having maximum benefits to the host. In modern medicine, probiotic functional foods have been used as nutraceuticals for multi-drug resisting organisms and as transport vectors. In the near future, Super probiotic organisms will be the new step in human civilization in terms of food and therapeutic medicine.
... response and glycemic load upon their co-ingestion 58 . Milk proteins are also known to have insulinotropic properties and thus, reduce the glycemic response 59 .Sugiyama et al. 60 also reported that the consumption of rice and milk attenuates; Sun et al. 58 also reported that co-ingestion of soymilk and dairy milk with bread significantly lowered the blood glucose levels. Out of two independent variables, CMC exhibited a dominant effect on pGI as compared to SMP (Eq. ...
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BACKGROUND: Continuous glucose monitoring highlights the complexity of postprandial glucose patterns present in type 1 diabetes and points to the limitations of current approaches to mealtime insulin dosing based primarily on carbohydrate counting. METHODS: A systematic review of all relevant biomedical databases, including MEDLINE, Embase, CINAHL, and the Cochrane Central Register of Controlled Trials, was conducted to identify research on the effects of dietary fat, protein, and glycemic index (GI) on acute postprandial glucose control in type 1 diabetes and prandial insulin dosing strategies for these dietary factors. RESULTS: All studies examining the effect of fat (n = 7), protein (n = 7), and GI (n = 7) indicated that these dietary factors modify postprandial glycemia. Late postprandial hyperglycemia was the predominant effect of dietary fat; however, in some studies, glucose concentrations were reduced in the first 2–3 h, possibly due to delayed gastric emptying. Ten studies examining insulin bolus dose and delivery patterns required for high-fat and/or high-protein meals were identified. Because of methodological differences and limitations in experimental design, study findings were inconsistent regarding optimal bolus delivery pattern; however, the studies indicated that high-fat/protein meals require more insulin than lower-fat/protein meals with identical carbohydrate content. CONCLUSIONS: These studies have important implications for clinical practice and patient education and point to the need for research focused on the development of new insulin dosing algorithms based on meal composition rather than on carbohydrate content alone.
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The glycaemic index (GI) concept was originally introduced to classify different sources of carbohydrate (CHO)-rich foods, usually having an energy content of >80 % from CHO, to their effect on post-meal glycaemia. It was assumed to apply to foods that primarily deliver available CHO, causing hyperglycaemia. Low-GI foods were classified as being digested and absorbed slowly and high-GI foods as being rapidly digested and absorbed, resulting in different glycaemic responses. Low-GI foods were found to induce benefits on certain risk factors for CVD and diabetes. Accordingly it has been proposed that GI classification of foods and drinks could be useful to help consumers make 'healthy food choices' within specific food groups. Classification of foods according to their impact on blood glucose responses requires a standardised way of measuring such responses. The present review discusses the most relevant methodological considerations and highlights specific recommendations regarding number of subjects, sex, subject status, inclusion and exclusion criteria, pre-test conditions, CHO test dose, blood sampling procedures, sampling times, test randomisation and calculation of glycaemic response area under the curve. All together, these technical recommendations will help to implement or reinforce measurement of GI in laboratories and help to ensure quality of results. Since there is current international interest in alternative ways of expressing glycaemic responses to foods, some of these methods are discussed.
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In normal subjects, ingestion of fat with potato in a morning meal resulted in a decrease in the glucose response. Therefore, we wished to determine whether a fat-induced decrease in blood glucose also would be observed after a second identical meal. In addition, we were interested in determining if fat ingestion with a morning meal would have an effect on the blood glucose and insulin responses to a second meal not containing fat. Nine healthy male subjects ingested two meals consisting of an amount of potato containing 50 g carbohydrate, either alone or with 50 g fat as butter. The meals were served in four combinations as follows: 1) potato for the first meal, potato for the second meal; 2) potato for the first meal, potato with fat for the second meal; 3) potato with fat for the first meal, potato for the second meal; and 4) potato with fat for the first meal, potato with fat for the second meal. Meals were ingested at 8:00 A.M. and noon. Plasma glucose and C-peptide, serum insulin, triglyceride, and free fatty acid (FFA) concentrations were determined over an 8-h period. The integrated area responses to the meals were quantified over the subsequent 4-h period using the fasting value or the noon value as baseline for the first and second meals, respectively. When the first meal contained potato only, the glucose area response to the second meal was significantly less when the second meal contained fat. However, fat ingestion had no effect on the glucose area response to the second meal when fat was present in the first meal. The insulin area responses to the first and second meals were similar after ingestion of potato or potato with fat. However, the insulin response to the second meal always was less than that to the first meal. The C-peptide area responses after ingestion of the second meal also were all higher than those after the first meal. The triglyceride area responses were slightly negative after ingestion of potato alone in the first meal. When fat was ingested, they were positive. When the first meal contained fat but the second meal did not, there was a rise in triglyceride concentration after the second meal as well as after the first meal. That is, a rise occurred without ingestion of fat with the second meal. If fat was present in the second meal the rise was even greater. The FFA area responses were similar to the triglyceride area responses. When fat was ingested with carbohydrate in either the first or second meal, the glucose area response was decreased. However, when both meals contained fat, a decrease in the glucose area response did not occur with the second meal. The glucose area responses all were greater after the second meal compared with those after the first meal, i.e., the opposite of a Staub-Traugott effect was observed. The insulin area responses to the first and second meals were similar whether fat was ingested or not.
A rapid enzymic method for starch analysis, especially in cereal products, is presented. One person can analyze 30 samples per day. The method includes a 15 min gelatinization step in a boiling water bath in the presence of a thermostable α-amylase, a 30 min amyloglucosidase incubation of a subsample, and subsequent determination of glucose with a glucose oxidase/peroxidase reagent. The method was evaluated by analysis of the starch content in various raw and industrially processed wheat samples. The method showed high precision (CV=0.6–1.0%) and accuracy. Some factors which might affect the enzymic availability of starch and thus its recovery in the analysis are evaluated and discussed. Eine schnelle Methode Zur Bestimmung von Stärke. Es wird eine schnelle enzymatische Methode zur Bestimmung von Stärke, insbesondere in Getreideprodukten, vorgestellt. Eine Person kann 30 Proben am Tag untersuchen. Die Methode umfaße eine 15 min lange Verkleisterung in Gegenwart einer thermostabilen α-Amylase in einem kochenden Wasserbad, eine 30 min lange Behandlung eines Teiles der Probe mit Amyloglucosidase und eine nachfolgende Bestimmung der Glucose mit einem Glucoseoxidase/Peroxidase-Reagens. Die Beurteilung der Methode erfolgte durch die Bestimmung des Stärkegehaltes in verschiedenen rohen und industriell verarbeiteten Weizenproben, sie zeigte große Genauigkeit (CV = 0,6–1,0%). Einige Faktoren, welche die enzymatische Verfügbarkeit von Stärke und somit ihre Erfassung bei der Bestimmung beeinflussen, werden diskutiert.
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.
A gravimetric, enzymatic method for the determination of both soluble and insoluble dietary fiber is presented. This method makes it possible to analyze 10-15 duplicate samples in 1 day. The procedure includes the following main steps: gelatinization by boiling 15 min in the presence of a heat-stable α-amylase, incubation with pepsin at acid pH for 1 h, and incubation with pancreatin at neutral pH for 1 h. Insoluble dietary fiber is filtered off with Celite 545 as the filter aid. Soluble dietary fiber is precipitated from the filtrate with 4 volumes of ethanol and recovered by filtration in the same way as insoluble dietary fiber. As an alternative the alcohol precipitation can be performed immediately after the enzyme incubations. Both soluble and insoluble components can then be recovered in one single filtration. All dietary fiber components seem to be determined. Practically all starch is solubilized, but some protein remains undigested. Microbial enzymes were also tested. When the materials used in the EEC/IARC collaborative study were analyzed, the two enzyme systems gave very similar results.
Milk products deviate from other carbohydrate-containing foods in that they produce high insulin responses, despite their low GI. The insulinotropic mechanism of milk has not been elucidated. The objective was to evaluate the effect of common dietary sources of animal or vegetable proteins on concentrations of postprandial blood glucose, insulin, amino acids, and incretin hormones [glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide 1] in healthy subjects. Twelve healthy volunteers were served test meals consisting of reconstituted milk, cheese, whey, cod, and wheat gluten with equivalent amounts of lactose. An equicarbohydrate load of white-wheat bread was used as a reference meal. A correlation was found between postprandial insulin responses and early increments in plasma amino acids; the strongest correlations were seen for leucine, valine, lysine, and isoleucine. A correlation was also obtained between responses of insulin and GIP concentrations. Reconstituted milk powder and whey had substantially lower postprandial glucose areas under the curve (AUCs) than did the bread reference (-62% and -57%, respectively). Whey meal was accompanied by higher AUCs for insulin (90%) and GIP (54%). It can be concluded that food proteins differ in their capacity to stimulate insulin release, possibly by differently affecting the early release of incretin hormones and insulinotropic amino acids. Milk proteins have insulinotropic properties; the whey fraction contains the predominating insulin secretagogue.
The effects of protein and fat on glycemic responses have not been studied systematically. Therefore, our aim was to determine the dose-response effects of protein and fat on the glycemic response elicited by 50 g glucose in humans and whether subjects' fasting plasma insulin (FPI) and diet influenced the results. Nondiabetic humans, 10 with FPI < [corrected] or =40 pmol/L and 10 with FPI >40 pmol/L, were studied on 18 occasions after 10 14-h overnight fasts. Subjects consumed 50 g glucose dissolved in 250 mL water plus 0, 5, 10, or 30 g fat and/or 0, 5, 10, or 30 g protein. Each level of fat was tested with each level of protein. Dietary intake was measured using a 3-d food record. Gram per gram, protein reduced glucose responses approximately 2 times more than fat (P < 0.001) with no significant fat x protein interaction (P = 0.051). The effect of protein on glycemic responses was related to waist circumference (WC) (r = -0.56, P = 0.011) and intake of dietary fiber (r = -0.60, P = 0.005) but was unrelated to FPI or other nutrient intakes. The effect of fat on glycemic responses was related to FPI (r = 0.49, P = 0.029) but was unrelated to WC or diet. We conclude that, across the range of 0-30 g, protein and fat reduced glycemic responses independently from each other in a linear, dose-dependent fashion, with protein having approximately 3-times the effect of fat. A large protein effect was associated with high WC and high dietary-fiber intake, whereas a large fat effect was associated with low FPI. These conclusions may not apply to solid meals. Further studies are needed to determine the mechanisms for these effects.
Crude fat analysis of different flours and flour products
  • L B Croon
  • G Guch
Croon LB, Guch G (1980) Crude fat analysis of different flours and flour products. Var Foda 32: 427-425.