Content uploaded by Susan O'Connell
Author content
All content in this area was uploaded by Susan O'Connell on Apr 29, 2014
Content may be subject to copyright.
Both Dietary Protein and Fat Increase
Postprandial Glucose Excursions
in Children With Type 1 Diabetes,
and the Effect Is Additive
CARMEL E.M. SMART,RD,PHD
1,2
MEGAN EVANS,RD, PGRADDIPDIET
3
SUSAN M. O’CONNELL,MD,FRACP
3,4
PATRICK MCELDUFF,PHD
2
PRUDENCE E. LOPEZ,MD
2,5
TIMOTHY W. JONES,MD,FRACP
3,4,6
ELIZABETH A. DAVIS,MD,PHD
3,4,6
BRUCE R. KING,MD,PHD
1,5
OBJECTIVEdTo determine the separate and combined effects of high-protein (HP) and high-
fat (HF) meals, with the same carbohydrate content, on postprandial glycemia in children using
intensive insulin therapy (IIT).
RESEARCH DESIGN AND METHODSdThirty-three subjects aged 8–17 years were
given 4 test breakfasts with the same carbohydrate amount but varying protein and fat quantities:
low fat (LF)/low protein (LP), LF/HP, HF/LP, and HF/HP. LF and HF meals contained 4 g and 35 g
fat. LP and HP meals contained 5 g and 40 g protein. An individuallystandardized insulin dose was
given for each meal. Postprandial glycemia was assessed by 5-h continuous glucose monitoring.
RESULTSdCompared with the LF/LP meal, mean glucose excursions were greater from 180
min after the LF/HP meal (2.4 mmol/L [95% CI 1.1–3.7] vs. 0.5 mmol/L [20.8 to 1.8]; P=0.02)
and from 210 min after the HF/LP meal (1.8 mmol/L [0.3–3.2] vs. 20.5 mmol/L [21.9 to 0.8];
P= 0.01). The HF/HP meal resulted in higher glucose excursions from 180 min to 300 min (P,
0.04) compared with all other meals. There was a reduction in the risk of hypoglycemia after the
HP meals (odds ratio 0.16 [95% CI 0.06–0.41]; P,0.001).
CONCLUSIONSdMeals high in protein or fat increase glucose excursions in youth
using IIT from 3 h to 5 h postmeal. Protein and fat have an additive impact on the delayed
postprandial glycemic rise. Protein had a protective effect on the development of
hypoglycemia.
Diabetes Care 36:3897–3902, 2013
Current management of people with
type 1 diabetes (T1D) on intensive
insulin therapy (IIT) advocates al-
gorithms based on the carbohydrate con-
tent of the meal to calculate the prandial
insulin dose (1,2). This approach is recom-
mended as a means to improve glycemic
control and allow greater dietary flexibility
(3,4). Typically, these calculations do not
take into account the protein and fat con-
tent of the meal.
In recent years, novel algorithms have
recommended counting fat and protein
units, in addition to carbohydrate, in
order to determine a supplementary
insulin requirement for high-fat and
-protein meals (5). However, increased
postprandial hypoglycemia has been
observed in children following these rec-
ommendations (6). A recent study (7)
showed that meals high in fat do require
more insulin than lower-fat meals with the
same carbohydrate content, supporting
the need for alternative insulin dosing al-
gorithms for high-fat (HF) meals. How-
ever, there is a general paucity of
evidence regarding the impact of protein
and fat on postprandial glycemia in pa-
tients utilizing IIT, and consistent clinical
advice for optimal management of high-
protein (HP) and HF meals is lacking.
To date, protein has been considered
together with fat in test meal studies, and
controlled trials examining the effect of
variations in protein content, indepen-
dent of other macronutrients, on post-
prandial glucose levels have not been
performed in individuals with T1D using
insulin pump or multiple daily injection
therapies. Therefore, this study was un-
dertaken to examine the separate and
combined effects of HP and HF meals,
all with the same carbohydrate content,
on postprandial glycemia in children and
adolescents using IIT.
RESEARCH DESIGN AND
METHODSdThe study design was a
four-by-four randomized crossover trial
conducted at two pediatric centers in
Australia (Princess Margaret Hospital in
Perth and John Hunter Children’s Hospital
in Newcastle). Children and adolescents
with T1D who had been diagnosed for
.1 year and who had been treated with
continuous subcutaneous insulin infusion
or multiple daily injection ($4 injections/
day) for .6 months were recruited. Inclu-
sion criteria included age between 8 and 17
years, glycated hemoglobin (HbA
1c
)
#8.0% (64 mmol/mol), and BMI #97th
percentile. Exclusion criteria were coexist-
ing medical problems (including celiac dis-
ease), evidence of complications of diabetes
(including gastroparesis), hyperlipidemia,
and dietary restrictions.
Ethics approval was obtained from
the ethics committees of the Princess
Margaret Children’sHospitalandthe
ccccccccccccccccccccccccccccccccccccccccccccccccc
From the
1
Department of Paediatric Endocrinology and Diabetes, John Hunter Children’s Hospital, Newcastle,
New South Wales, Australia; the
2
Hunter Medical Research Institute, School of Medicine and Public Health,
University of Newcastle, Rankin Park, New South Wales, Australia; the
3
Department of Endocrinology and
Diabetes, Princess Margaret Hospital for Children, Perth, Western Australia, Australia; the
4
Telethon In-
stitute for Child Health Research, Centre for Child Health Research, University of Western Australia, Perth,
Western Australia, Australia; the
5
Faculty of Health, School of Medicine, University of Newcastle, New-
castle, New South Wales, Australia; and the
6
School of Paediatrics and Child Health, University of Western
Australia, Perth, Western Australia, Australia.
Corresponding author: Bruce R. King, bruce.king@hnehealth.nsw.gov.au.
Received 20 May 2013 and accepted 27 July 2013.
DOI: 10.2337/dc13-1195
A slide set summarizing this article is available online.
© 2013 by the American Diabetes Association. Readers may use this article as long as the work is properly
cited, the use is educa tional and not for profit, and the work is not alte red. See http://creativecommons.org/
licenses/by-nc-nd/3.0/ for details.
care.diabetesjournals.org DIABETES CARE ,VOLUME 36, DECEMBER 2013 3897
Clinical Care/Education/Nutrition/Psychosocial Research
ORIGINAL ARTICLE
©
John Hunter Children’s Hospital. Written
informed consent was gained from all
participants and their parents.
In the week leading up to the study,
participants and their caregivers were
contacted daily by telephone to review
the subject’s blood glucose level (BGL).
Adjustments were made, if required, to
the participant’s insulin therapy to
meet a prebreakfast target range of 4–8
mmol/L and to optimize each partici-
pant’s insulin-to-carbohydrate ratio. If
the subject’s fasting glucose values were
high (.12.0 mmol/L) or low (,3.6
mmol/L), participants were instructed to
treat as normal, e.g., for hyperglycemia,
administer a correction bolus. This study
day was then excluded and repeated.
Participants received their breakfast
(test meal) under supervision by one of
the two study centers over four consecu-
tive mornings. Four standardized test
meals of high- or low-fat and high- or
low-protein content, all with the same
carbohydrate amount, were given under
supervision to each participant in random
order over the four study days. Children
were required to fast overnight for at least
10 h prior to breakfast, consume the test
meal in 20 min, and fast for 5 h after
completion of the test meal. Activity was
standardized (sedentary) during the 5-h
postprandial period for each participant.
The insulin dose for each participant
was determined for the carbohydrate
content using each participant’s individ-
ualized insulin-to-carbohydrate ratio.
This dose then remained constant for
each of the four test meals. The short-
acting insulin bolus was administered 10
min prior to test meal consumption via
subcutaneous injection or as a standard
bolus via the insulin pump. In the event
of hypoglycemia during the 5-h postpran-
dial period, 15 g oral carbohydrate was
given and analysis stopped at that point.
Participants using continuous subcutane-
ous insulin infusion changed their infu-
sion site on day 1 and day 3 of the study.
Test meals
Test meals consisted of pancakes varying
in protein and fat content but identical in
carbohydrate amount. The low-fat (LF)
and HF meals contained 4 g fat and 35 g
fat, respectively, and the low-protein (LP)
meal and HP meals contained 5 g protein
and 40 g protein, respectively. All meals
contained the same amount of carbohy-
drate (30 g, 120 kcal). The total energy
content of the four test meals was 180 kcal
for the LF/LP meal, 330 kcal for the LF/HP
meal, 460 kcal for the HF/LF meal, and
615 kcal for the HF/HP meal. Beneprotein
(100% whey protein isolate) was used to
increase the protein content of the meals
without impacting the fat and carbohy-
drate quantities. See Table 1 for a detailed
description of the meals.
The fat and protein amounts were
based on quantities in foods commonly
consumed by children and adolescents
with diabetes (8). A weight-based cut
point for protein was derived from rec-
ommendations of upper levels of protein
intakes for children (9). To ensure an ap-
propriate protein amount for children
#45 kg, 75% of the total serving for
each pancake was provided. The reduc-
tion in the serving size for the smaller chil-
dren resulted in all macronutrients being
altered proportionally to provide 75% of
the amount in the full serving. The meal
types were given to patients in a random
order, which was predetermined based
on a generalized cyclic block design and
was generated using Proc Plan in SAS
v9.3, 2010 (SAS Institute, Cary, NC).
Food was prepared under controlled con-
ditions and weighed using Salter kitchen
scales (accuracy 61 g, model 323; Salter,
Kent, U.K.).
Glucose measurement
The iPro2 Continuous Glucose Monitor-
ing System (CGMS; MedtronicMiniMed,
Northbridge, CA) was used to record glu-
cose levels in the participants over the 4
days of the study. Subjects attended the
clinic on the day prior to the study
Table 1dMacronutrient composition for LF, HF, LP, and HP test meals
Test meal and ingredients Carbohydrate (g) Fat (g) Protein (g) Fiber (g)
LF/LP
Wheat flour 20.5 0.3 2.8 1.1
Full-cream milk 2.0 1.0 1.1 0.0
Eggs 0.0 1.1 1.4 0.0
Castor sugar 7.8 0.0 0.0 0.0
Sunflower oil 0.0 1.6 0.0 0.0
Total 30.3 4.0 5.3 1.1
LF/HP
Wheat flour 20.5 0.3 2.8 1.1
Evaporated skim milk 6.4 0.2 4.9 0.0
Skim milk powder 3.1 0.0 2.2 0.0
Eggs 0.0 1.1 1.4 0.0
Egg white 0.0 0.0 0.9 0.0
Sunflower oil 0.0 2.3 0.0 0.0
Beneprotein 0.0 0.0 27.8 0.0
Total 30.0 3.9 40.0 1.1
HF/LP
Wheat flour 20.5 0.3 2.8 1.1
Full-cream milk 2.0 1.0 1.1 0.0
Eggs 0.0 1.1 1.4 0.0
Castor sugar 7.8 0.0 0.0 0.0
Sunflower oil 0.0 8.2 0.0 0.0
Double cream (50% fat) 0.0 20.3 0.0 0.0
Butter 0.0 4.1 0.0 0.0
Total 30.3 35.0 5.3 1.1
HF/HP
Wheat flour 20.5 0.3 2.8 1.1
Evaporated full-fat milk 5.7 3.9 3.4 0.0
Full-cream milk powder 3.6 2.7 2.4 0.0
Eggs 0.0 1.7 2.1 0.0
Sunflower oil 0.0 6.4 0.0 0.0
Double cream (50% fat) 0.0 12.4 0.4 0.0
Butter 0.0 7.8 0.0 0.0
Beneprotein 0.0 0.0 28.9 0.0
Total 29.8 35.2 40.0 1.1
Subjects #45 kg consumed 75% of the total serve for each test meal.
3898 DIABETES CARE,VOLUME 36, DE CEMBER 2013 care.diabetesjournals.org
Protein and fat impact postprandial glycemia
©
commencement for insertion of CGMS.
Participants were asked to record at least
four capillary blood glucose measure-
ments per day into their study diary to
allow for calibration. At the completion
ofthestudy,dataweredownloaded
from the CGMS using the Medtronic
CareLinkiPro data system (Medtronic
MiniMed).
Statistical analysis
The primary outcome measure was the
glucose excursion at each 30-min interval
from baseline to 300 min after each of the
four test meals. This was calculated as the
observed postprandial glucose level mi-
nus the subject’s glucose level at baseline.
Secondary outcomes included hypogly-
cemic event (defined as a capillary BGL
,3.6 mmol/L), peak glucose excursion,
and time to peak glucose excursion. Glu-
cose excursion data for children who
had a hypoglycemic event were not in-
cluded after the time of the event.
Differences in mean glucose excur-
sions between meal groups at a single time
point were tested using a generalized
linear mixed model to account for the
repeated measurements on the same chil-
dren. The outcome in the model was
glucose excursion, and the only predictor
was meal type, which was included as a
four-level factor. A second set of models
was fitted to examine the interaction
between the effect of fat and protein.
This set of models had predictors of fat,
protein, and the interaction of fat and
protein. Generalized linear mixed models
were also used to test for differences in
mean peak glucose excursions and mean
time to peak glucose excursions. Differences
between meal types in the proportion of
subjects who had a hypoglycemic event
were examined using a logistic regression
model within a generalized estimating
equation framework.
Pvalues ,0.05 were considered sta-
tistically significant. Data analysis was
conducted using SAS (SAS Institute) and
Stata statistical software, 2011, release 12
(StataCorp 2011, College Station, TX).
RESULTSdThe mean (SD) age of the
33 children who completed the study was
12.2 (2.5) years, and 17 (52%) were
female. Other baseline characteristics are
presented in Table 2.
The prebreakfast target range of 4–8
mmol/L was achieved on 78 days over the
132 study days. Ninety-seven percent of
fasting glucose values (n= 128) were be-
tween 3.6 and 12.0 mmol/L, requiring 4
study days to be repeated because of high
or low fasting glucose values. On each oc-
casion, the day was successfully repeated.
Nine children had incomplete study
days where data from 1 day were ex-
cluded from the analysis due to an in-
complete sensor reading over the 5-h
postprandial period (n= 7) or failure to
complete one of the test meals in 20 min
(n= 2). Data from all of the other days (n=
123) were included in the analysis.
Twelve children weighed #45 kg and
were given 75% of the total meal serving.
The outcome data for these children did
not differ significantly from subjects who
weighed .45 kg (P.0.05).
Postprandial glucose excursions
Figure 1 presents the mean postprandial
glucose excursions by meal type at each
time point (30-min increments from 0 to
300 min). Differences in mean glucose
excursions between the test meals became
apparent from ~120 min after the meals,
with a sustained and attenuated additive
effect of the HF/HP meal. The mean glu-
cose excursions after the LF/HP meal were
significantly greater than the mean glu-
cose excursions after the LF/LP meal com-
mencing at 180 min (P=0.02)and
continuing to 300 min (P,0.01) (Table
3). The mean glucose excursions after the
HF/LP meal were significantly higher than
the glucose excursions after the LF/LP meal
at 210 min (P= 0.01)and continuing to 300
min (P,0.01).
The HF/HP meal resulted in signifi-
cantly higher glucose excursions from
180 min to 300 min compared with all
other meals (P,0.04) (Fig. 1). Com-
pared with the LF/LP meal, mean glucose
excursions were significantly greater from
150 min after the HF/HP meal (P= 0.004)
(Table 3). At 300 min, the mean glucose
excursion for the HF/HP meal was 5.4
mmol/L higher than for the LF/LP meal
(P,0.001).
The HF/LP meal reduced the glucose
excursion within the first 60–90 min after
the meal compared with all other meals
(Table 3). The mean excursion at 60 min
after the HF/LP meal was significantly
lower than the excursion for the LF/LP
meal (P= 0.009). This effect was only
seen for the LP/HF meal.
Beyond 120 min, the glycemic pro-
files after the HF/LP meal were similar to
the profiles after the LF/HP meal (Fig. 1).
There was no statistically significant inter-
action between the effects of the fat and
protein on glucose excursions at all time
points (P.0.05), which is consistent
with their effects being additive. The ef-
fects of protein and fat on glucose excur-
sions were additive, as indicated by the
lack of interaction of the two effects and
as seen in Fig. 1. For example, at 180 min
the mean glucose excursion for the HF/
HP meal (4.2 mmol/L [95% CI 2.5–5.9])
was equivalent to the combined excur-
sions of the LF/HP meal (2.4 mmol/L
[1.1–3.7]) and the HF/LP meal (1.8
mmol/L [0.5–3.0]).
Peak glucose excursion and time
to peak glucose
There was a significant difference in peak
glucose excursions between meal types
(P= 0.049), with the highest value
recorded after the HF/HP meal. The
mean peak glucose excursions from
baseline for the LF/LP, LF/HP, HF/LP, and
Table 2dClinical characteristics of participants
Demographics
Center
Perth, Australia 23
Newcastle, Australia 10
Sex 16
Male
Female 17
Insulin pump therapy 27
Multiple daily injection therapy 6
Age (years) 12.2 62.5
Duration of diabetes (years) 4.9 63.2
BMI zscore 0.6 60.8
HbA
1c
, % (mmol/mol) 7.2 60.8 (55 68.7)
Insulin-to-carbohydrate ratio (units/g) 1:11.0 64.8
Data are presented as means 6SD.
care.diabetesjournals.org DIABETES CARE ,VOLUME 36, DECEMBER 2013 3899
Smart and Associates
©
HF/HP meals, respectively, were 4.7
mmol/L (95% CI 3.6–5.8), 4.4 mmol/L
(3.5–5.3), 4.3 mmol/L (3.1 to 5.4), and
5.9 mmol/L (4.6–7.3).
There was also a statistically signifi-
cant difference in the time to mean peak
glucose excursion between meal types (P
,0.001), with the longest time being ob-
served after the HF/HP meal. The mean
time to peak glucose excursion for the LF/
LP, LF/HP, HF/LP, and HF/HP meals, re-
spectively, were 79 min (95% CI 68–89),
96 min (74–119) min, 126 min (97–154)
min, and 143 min (112 to 174).
Hypoglycemic events
Twenty-nine symptomatic hypoglycemic
events occurred in the 5-h postprandial
period during the study. Fourteen oc-
curred in the LF/LP group, 10 in the HF/
LP group, 4 in the LF/HP group, and 1 in
the HF/HP group. There were no episodes
of severe hypoglycemia. The number of
hypoglycemic events differed signifi-
cantly between the four meal types (P=
0.003). There was a statistically signifi-
cant reduction in the odds of a hypogly-
cemic event when children consumed
the HP meals (odds ratio 0.16 [95% CI
0.06–0.41]; P,0.001) but not when
they consumed the HF meals (odds ratio
0.50 [0.22–1.09]; P= 0.08).
CONCLUSIONSdThis study has
demonstrated an effect of dietary protein
independent of fat on postprandial glyce-
mia in children with T1D. Importantly,
the glycemic rise after protein was shown
in meals of both HF and LF contents, with
identical carbohydrate quantities. In ad-
dition, when a meal containing high levels
of both protein and fat was eaten, the
impact of protein and fat was additive and
caused significantly higher glucose excur-
sions between 3 and 5 h postprandially
compared with meals of only HF or HP
contents.
An important finding of this study
was that there were significantly higher
glycemic excursions for the HP and HF
mealscomparedwiththeLP/LFmeal
from ~180 to 300 min postprandially.
This late effect was increased and sus-
tained when the HF and HP loads were
combined. As expected, the HF meal
initially reduced the glycemic excursion
for up to 90 min after the meal. This is
most likely due to the effect of fat in
delaying gastric emptying (10,11) and is
consistent with studies in both adoles-
cents with T1D (10) and patients with
type 2 diabetes (12). However in our
study, the addition of protein to the HF
meal prevented this, suggesting that
proteinmayhaveaprotectiveeffectin
the development of early postprandial
hypoglycemia.
The cause of the late sustained hy-
perglycemia noted when meals high in
protein and fat are eaten has been postu-
lated but is currently unknown. Protein
may lead to delayed hyperglycemia by
Figure 1dMean postprandial glucose excursions from 0 to 300 min for 33 subjects after test
meals of LF/LP (C), LF/HP (◆), HF/LP (▲), and HF/HP (,) content. Carbohydrate amount
was the same in all meals. There were significant differences in glucose excursions between meal
types from 150 to 300 min (P,0.03). Error bars represent 95% CIs.
Table 3dMean postprandial glucose excursions by meal type at 30-min intervals to 300 min
Minutes
after meal
Mean postprandial glucose excursions (mmol/L)
LF/LP LF/HP HF/LP HF/HP
30 1.6 (1.1–2.1) 1.8 (1.4–2.2) 0.9 (0.5–1.3)* 1.6 (1.1–2.1)
60 3.6 (2.7–4.4) 3.4 (2.7–4.1) 2.2 (1.5–3.0)* 3.5 (2.3–4.6)
90 4.0 (2.9–5.1) 3.5 (2.6–4.4) 3.4 (2.3–4.5) 4.0 (2.6–5.4)
120 3.3 (2.0–4.5) 3.2 (2.1–4.2) 3.1 (1.9–4.4) 4.1 (2.6–5.6)
150 1.8 (0.6–3.0) 3.0 (1.7–4.3) 2.4 (1.1–3.6) 4.2 (2.5–5.9)*
180 0.5 (20.8 to 1.8) 2.4 (1.1–3.7)* 1.8 (0.5–3.0) 4.2 (2.5–5.9)*
210 20.5 (21.9 to 0.8) 1.9 (0.5–3.1)* 1.8 (0.3–3.2)* 3.9 (2.0–5.7)*
240 21.4 (22.8 to 20.1) 1.2 (20.1 to 2.5)* 1.5 (20.2 to 3.1)* 4.1 (2.3–5.8)*
270 22.2 (23.6 to 20.8) 0.6 (20.8 to 1.9)* 0.7 (21.0 to 2.4)* 2.7 (0.9–4.5)*
300 22.9 (24.5 to 21.3) 20.3 (21.8 to 1.2)* 0.6 (21.6 to 2.7)* 2.5 (0.5–4.5)*
Data are presented as means (95% CI). *Statistically different compared with glucose excursion for the LF/LP meal at that time point (P#0.05).
3900 DIABETES CARE,VOLUME 36, DE CEMBER 2013 care.diabetesjournals.org
Protein and fat impact postprandial glycemia
©
gluconeogenesis and increased glucagon
secretion (13). Proposed mechanisms by
which dietary fat and free fatty acids con-
tribute to hyperglycemia are by impairing
insulin sensitivity and enhancement of
hepatic glucose production, along with
delayed gastric emptying, which causes
an increase in the peak time and ampli-
tude of the glucose response (11). Fur-
ther studies are required to fully
elucidate the pathways of action.
The results of this study have direct
clinical translation. The protein, fat, and
carbohydrate contents in this study were
based on real meals commonly consumed
by children and adolescents. For such
meals, patients may be advised that sig-
nificant hyperglycemia is likely to occur
between 3 and 5 h after the meal, partic-
ularly accentuated and prolonged for the
HF/HP meal. The findings of this study
suggest the need for both prolonging
insulin delivery by the use of a different
wave form, such as a dual-wave bolus in
those on pump therapy and that addi-
tional insulin is required to match the
delayed hyperglycemia. Future studies
are needed to determine an alternative
insulin dosing algorithm to separately
account for the fat and protein in HF/HP
meals.
Typically, insulin bolus dosing has
been determined using the insulin-to-
carbohydrate ratio. Our findings support
recent evidence that dietary fat increases
insulin requirements (7), but suggest that
the additional insulin should be given by
an extended insulin bolus or as a split bo-
lus in order to prevent early hypoglyce-
mia. This study also adds new data
pointing to the need for additional insulin
for HP meals independent of the fat con-
tent. A feature of insulin pump therapy
that is potentially advantageous is the
ability to vary the delivery of a bolus of
insulin over time by use of a dual-wave or
square-wave bolus. A dual-wave bolus
has already been shown to limit glycemic
excursions in pizza studies (14,15). The
question of the optimal timing and distri-
bution of the bolus in combined HF and
HP meals, however, requires more inves-
tigation. Some centers have recently re-
ported their experiences in pump
patients of calculating fat and protein
units and using these to determine insulin
bolus dosing for the mixed meals (6,16).
These studies provide some data using a
normal-wave bolus given for carbohy-
drate and also a square-wave bolus with
supplementary insulin for the fat and pro-
tein content. While reduced postprandial
hyperglycemia has been noted, the rate of
hypoglycemia using these calculations
has been unacceptably high (33–35%)
(6,16). There has also been a lack of stan-
dardization of bolus types between the
groups (16), which makes it difficult to
compare the effect of additional insulin
as opposed to the method of insulin de-
livery. Clearly, further studies are needed
to refine and quantify the extra insulin
that is required for HF or HP meals and
to determine algorithms for the best dose
and rate of insulin delivery over time.
A limitation of the study was that we
did not examine the effect of protein and
fat beyond 5 h, although previous studies
have noted an effect of HF/HP meals after
this time period (14,15). During daylight
hours, food is typically eaten so frequently
that additional bolus doses of insulin
within a few hours of the meal may correct
the hyperglycemia. We therefore suggest
that the composition of the evening meal
is particularly important to consider in
mealtime insulin calculations, as in the
case of fasting overnight no additional in-
sulin is given and prolonged hyperglycemia
may result. Furthermore, our data from
this and previous studies (17,18) indicate
that postprandial testing may be more ap-
propriate at 3 h rather than 2 h after the
meal, as the glycemic excursion from even
those meals lower in fat and protein did not
return to baseline until this time.
In conclusion, this is the first study to
demonstrate that the addition of protein
and fat to meals containing the same
carbohydrate amount results in pro-
longed postprandial hyperglycemia in
childrenusingIIT.Whentheprotein
and fat were consumed together, there
wasanadditiveeffectonpostprandial
glycemia. Furthermore, the protein ap-
peared to have a protective effect against
hypoglycemia. This study provides sup-
portive evidence that protein and fat
should both be considered in insulin
dosing.
AcknowledgmentsdA Telethon Foundation
Fellowship grant supported S.M.O.’s contri-
bution to this study. A Hunter Children’sRe-
search Foundation grant supported the
Newcastle study site.
This project was supported by a Pfizer
Australia Paediatric Endocrine Care Research
grant. No other potential conflicts of interest
relevant to this article were reported.
C.E.M.S. conceived, designed, and con-
ducted the study; recruited subjects; collected
data; and wrote th e manuscript. M.E. recruited
subjects, conducted the study, and collected
data. S.M.O. designed and conducted the
study, recruited subjects, collected data, and
wrote the manuscript. P.M. analyzed data and
contributed to the writing of the manuscript.
P.E.L. recruited subjects, conducted the study,
collected data, and contributed to the writing
of the manuscript. T.W.J., E.A.D., and B.R.K.
contributed to the discussion and reviewed
and edited the manuscript. B.R.K. is the
guarantor of this work and, as such, had full
access to all the data in the study and takes
responsibility for the integrity of the data and
the accuracy of the data analysis.
Parts of this study we re presented in abstract
form at the 73rd ScientificSessionsofthe
American Diabetes Association, Chicago, Illi-
nois, 21–25 June 2013.
The authors thank Niru Paramalingam and
Adam Retterath, Princess Margaret Hospital,
and Virginia McRory, John Hunter Children’s
Hospital, for their support with the equipment
and preparation of the test meals.
References
1. Laurenzi A, Bolla AM, Panigoni G, et al.
Effects of carbohydrate counting on glu-
cose control and quality of life over 24
weeks in adult patients with type 1 di-
abetes on continuous subcutaneous in-
sulin infusion: a randomized, prospective
clinical trial (GIOCAR). Diabetes Care
2011;34:823–827
2. DAFNE Study Group. Training in flexible,
intensive insulin management to enable
dietary freedom in people with type 1
diabetes: dose adjustment for normal
eating (DAFNE) randomised controlled
trial. BMJ 2002;325:746–749
3. Scavone G, Manto A, Pitocco D, et al. Ef-
fect of carbohydrate counting and medical
nutritional therapy on glycaemic control
in Type 1 diabetic subjects: a pilot study.
Diabet Med 2010;27:477–479
4. Lowe J, Linjawi S, Mensch M, James K,
Attia J. Flexible eating and flexible insulin
dosing in patient s with diabetes: Results of
an intensive self-management course. Di-
abetes Res Clin Pract 2008;80:439–443
5. Pa
nkowska E, Szypowska A, Lipka M,
Szpota
nska M, BłazikM,GroeleL.Ap-
plication of novel dual wave meal bolus
and its impact on glycated hemoglobin
A1c level in children with type 1 diabetes.
Pediatr Diabetes 2009;10:298–303
6. Kordonouri O, Hartmann R, Remus K,
Bläsig S, Sadeghian E, Danne T. Benefitof
supplementary fat plus protein counting
as compared with conventional carbohy-
drate counting for insulin bolus calcula-
tion in children with pump therapy.
Pediatr Diabetes 2012;13:540–544
7. Wolpert HA, Atakov-Castillo A, Smith SA,
Steil GM. Dietary fat acutely increases
glucose concentrations and insulin re-
quirements in patients with type 1 diabetes:
implications for carbohydrate-based bolus
dose calculation and intensive diabetes
care.diabetesjournals.org DIABETES CARE ,VOLUME 36, DECEMBER 2013 3901
Smart and Associates
©
management. Diabetes Care 2013;36:
810–816
8. Øverby NC, Flaaten V, Veierød MB, et al.
Children and adolescents with type 1 di-
abetes eat a more atherosclerosis-prone
diet than healthy control subjects. Dia-
betologia 2007;50:307–316
9. National Health and Medical Research
Council. Nutrient Reference Values for Aus-
tralia and New Zealand Executive Summary.
Canberra, Australia, Department of Health
and Ageing, 2005
10. Lodefalk MAJ, Aman J, Bang P. Effects of fat
supplementation on glycaemic response and
gastric emptying in adolescents with Type 1
diabetes. Diabet Med 2008;25:1030–1035
11. Wolever TMMY, Mullan YM. Sugars and
fat have different effects on postprandial
glucose responses in normal and type 1
diabetic subjects. Nutr Metab Cardiovasc
Dis 2011;21:719–725
12. Gentilcore D, Chaikomin R, Jones KL, et al.
Effects of fat on gastric emptying of and the
glycemic, insulin, and incretin responses to a
carbohydrate meal in type 2 diabetes. J Clin
Endocrinol Metab 2006;91:2062–2067
13. Peters AL, Davidson MB. Protein and fat
effects on glucose responses and insulin
requirements in subjects with insulin-
dependent diabetes mellitus. Am J Clin
Nutr 1993;58:555–560
14. Jones SM, Quarry JL, Caldwell-McMillan
M, Mauger DT, Gabbay RA. Optimal in-
sulin pump dosing and postprandial gly-
cemia following a pizza meal using the
continuous glucose montoring system.
Diabetes Technol Ther 2005;7:233–240
15. Lee SW, Cao M, Sajid S, et al. The dual-
wave bolus feature in continuous sub-
cutaneous insulin infusion pumps controls
prolonged post-prandial hyperglycaemia
better than standard bolus in Type 1
diabetes. Diabetes Nutr Metab 2004;17:
211–216
16. Pa
nkowska E, Blazik M, Groele L. Does
the fat-protein meal increase postprandial
glucose level in type 1 diabetes patients on
insulin pump: the conclusion of a ran-
domized study. Diabetes Technol Ther
2012;14:16–22
17. SmartCE,RossK,EdgeJA,CollinsCE,
Colyvas K, King BR. Children and
adolescents on intensive insulin ther-
apy maintain postprandial glycaemic
control without precise carbohydrate
counting. Diabet Med 2009;26:279–
285
18. Smart CE, King BR, McElduff P, Collins
CE. In children using intensive insulin
therapy, a 20-g variation in carbohydrate
amount significantly impacts on post-
prandial glycaemia. Diabet Med 2012;29:
e21–e24
3902 DIABETES CARE,VOLUME 36, DE CEMBER 2013 care.diabetesjournals.org
Protein and fat impact postprandial glycemia
©
