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ARTICLE
A Palaeolithic diet improves glucose tolerance
more than a Mediterranean-like diet in individuals
with ischaemic heart disease
S. Lindeberg & T. Jönsson & Y. Granfeldt &
E. Borgstrand & J. Soffman & K. Sjöström & B. Ahrén
Received: 1 May 2007 /Accepted: 4 May 2007 /Published online: 22 June 2007
#
Springer-Verlag 2007
Abstract
Aims/hypothesis Most studies of diet in glucose intolerance
and type 2 diabetes have focused on intakes of fat, carbo-
hydrate, fibre, fruits and vegetables. Instead, we aimed to
compare diets that were available during human evolution
with more recently introduced ones.
Methods Twenty-nine patients with ischaemic heart disease
plus either glucose intolerance or type 2 diabetes were ran-
domised to receive (1) a Palaeolithic ( ‘Old Stone Age’) diet
(n=14), based on lean meat, fish, fruits, vegetables, root
vegetables, eggs and nuts; or (2) a Consensus (Mediterra-
nean-like) diet (n=15), based on whole grains, low-fat dairy
products, vegetables, fruits, fish, oils and margarines. Pri-
mary outcome variables were changes in weight, waist cir-
cumference and plasma glucose AUC (AUC Glucose
0–120
)
and plasma insulin AU C (AUC Insulin
0–120
) in OGTTs.
Results Over 12 week s, there was a 26% decrease of AUC
Glucose
0–120
(p=0.0001) in the Palaeolithic group and a 7%
decrease (p=0.08) in the Consensus group. The larger (p=
0.001) improvement in the Palaeolithic group was indepen-
dent (p=0.0008) of change in waist circumference (−5.6 cm
in the Palaeolithic group, −2.9 cm in the Consensus group;
p=0.03). In the study population as a whole, there was no
relationship between change in AUC Glucose
0–120
and
changes in weight (r=−0.06, p=0.9) or waist circumference
(r=0.01, p=1.0). There was a tendency for a larger decrease
of AUC Insulin
0–120
in the Palaeolithic group, but because of
the strong association between change in AUC Insulin
0–120
and change in waist circumference (r=0.64, p=0.0003), this
did not remain after multivariate analysis.
Conclusions/interpretation A Palaeolithic diet may im-
prove glucose tolerance independently of decreased waist
circumference.
Keywords Diet
.
Evolution
.
Glucose intolerance
.
Ischaemic heart disease
.
Palaeolithic diet
.
Type 2 diabetes
Abbreviations
BIA bioelectrical impedance analysis
E% percentage of total energy intake
HOMA-IR homeostasis model assessment
of insulin resistance
IFG impaired fasting glucose
IGT impaired glucose tolerance
IHD ischaemic heart disease
NGT normal glucose tolerance
Introduction
Impaired glucose tolerance (IGT) and type 2 diabetes are
common risk factors for ischaemic heart disease (IHD) [1, 2],
which negatively affect t he long-term prognosis after
myocardial infarction [3, 4]. In fact, cross-sectional studies
have found only 35–54% of IHD patients have normal
glucose tolerance (NGT) [5–11]. Increased physical activity,
Diabetologia (2007) 50:1795–1807
DOI 10.1007/s00125-007-0716-y
Electronic supplementary material The online version of this article
(doi:10.1007/s00125-007-0716-y) contains supplementary material,
which is available to authorised users.
S. Lindeberg (*)
:
T. Jönsson
:
E. Borgstrand
:
J. Soffman
:
K. Sjöström
:
B. Ahrén
Department of Medicine, Hs 32, University of Lund,
SE-221 85 Lund, Sweden
e-mail: staffan.lindeberg@med.lu.se
Y. Granfeldt
Department of Applied Nutrition and Food Chemistry,
University of Lund,
Lund, Sweden
healthy food choices and decreased waist circumference may
help to lower the rate of progression from IGT to diabetes
[12–14]. Standard dietary advice for patients with IHD and/
or IGT generally includes whole-grain cereals, low-fat dairy
products, vegetables, fruits, legumes, oily fish and refined
fats that are rich in monounsaturated fatty acids and alpha-
linolenic acid while low in trans-unsaturated fatty acids [15–
17]. However, the optimal dietary treatment of IGT and
insulin resistance is a matter of debate, including the
preferred amounts and types of fat, carbohydrate and protein
[16, 18–21], and amounts of fruits [22] and sodium [23, 24].
Since nutritional science is hampered by confounders, an
evolutionary approach has been suggested. It is postulated
that foods that were regularly eaten during primate and
human evolution, in particular during the Palaeolithic (the
‘Old Stone Age,’ 2.5–0.01 million years BP), may be
optimal to prevent insulin resistance and glucose intolerance
[25, 26]. A Palaeolithic diet includes lean meat, fish,
shellfish, fruits, vegetables, roots, eggs and nuts, but not
grains, dairy products, salt or refined fats and sugar, which
became staple foods long after the appearance of fully
modern humans. We found that traditional Pacific Islanders
of Kitava, Papua New Guinea, had no signs of IHD, stroke
or markers of the metabolic syndrome, possibly because of
their traditional lifestyle [27–29]. In the present study, we
examined the effect of dietary advice according to this
Palaeolithic diet model on glucose tolerance and post-
challenge insulin response in glucose-intolerant IHD
patients recruited from a Coronary Care Unit, compared
with dietary advice according to standard clinical practice.
Our hypothesis was that the Palaeolithic diet would provide
metabolic benefits beyond its nutrient composition.
Materials and methods
Participants The study was a 12 week controlled dietary
intervention trial in 29 (out of 38 eligible) male IHD patients
with waist circumference >94 cm and increased blood
glucose or known diabetes, recruited from the Coronary
Care Unit at Lund University Hospital, Sweden. We included
patients with any of t he fol low ing c onditions: an ongoing
acute coronary syndrome, a history of myocardial infarc-
tion diagnosed by creatine kinase MB isoenzyme or tro-
ponin elevation, percutaneous coronary intervention or
coronary artery bypass surgery or angiographically diag-
nosed coronary stenosis ≥30%. Exclusion criteria were
BMI < 20 kg/m
2
, serum creatinine >130 μmol/l, poor gen-
eral condition, dementia, unwillingness/inability to pre-
pare food at home, participation in another medical trial,
chronic inflammatory bowel disease, type 1 diabetes and
treatment with hypoglycaemic agents, warfarin or oral
steroids. Other drugs were not restricted, and treatment
with statins and beta blockers was usually initiated and/or
changed during the trial. Approval for the study was ob-
tained from the regional Medical Ethi cs Committee, and
all individuals g ave written informed consent to participate
in the study. In addition to the 29 patients w ho completed
the trial, nine randomised subjects were excluded for the
following reasons: worse ni ng general cond it ion (n=4),
unwillingness to continue (n=3, all in the Palaeol ithic
group) or missing OGTT data (one in each group).
Procedure All eligible subjects were informed of the inten-
tion to compare two healthy diets and that it w as unknown
if either of them would be superior to the other with regard
to weight reduction and improve d glucose metabolism.
Patients qualified for the study if they had known type 2
diabetes or, at a screening OGTT with 75 g glucose, a
fasting capillary blood glucose ≥6.1mmol/lora2hcapillary
blood glucose ≥7.8 mmol/l. In 13 subjects, this screening
OGTT was performed after an acute coronary episode
(Table 1). The remaining 16 subjects, eight in each group,
were recruited between 2 months and 2 years after hospital
discharge. Blood glucose concentrations were analysed in
capillary whole blood immediately after coll ection with a
HemoCue photometer (HemoCue, Ängelholm, Sweden).
A second OGTT w as performe d within 2 wee ks, when
venous plasma samples were collected <5 min before and
30and120minafteringestionof75gofglucoseandana-
lysed for glucose by the glucose oxidase technique and for
insulin by RIA (Linco Research, St Charles, MO, USA).
Normal plasma glu cos e was de fi ned as a fa sti ng veno us
plasma glucose <6.1 mmol/l and a 2 h venous plasma
glucose <7.8 mmol/l. IGT was defined as 2 h plasma glucose
of 7.9–11.0 mmol /l and f asting plasma glucose <7 mmol/l,
and diabetic lev els as fast ing pl asma glu cos e ≥7.0 mmol/l or
2 h pl as ma glucose ≥11.1 mmol/l. I mpa ired fasting glucose
(IFG) was defined as a fasting plasma glucose 6.1–6.9
mmol/l an d a 2 h venou s plasma glucose <7.8 mmol /l.
Diets Immediately after the second OGTT, subjects were
randomised to one of two healthy diets: (1) a Consensus
(Medite rranean-like) diet ( n=15) based on whole-grain
cereals, low-fat dairy products, potatoes, legumes, vegeta-
bles, fruits, fatty fish and refined fats rich in monoun-
saturated fatty acids and alpha-linolenic acid; or (2) a
Palaeolithic diet (n=14) based on lean meat, fish, fruits,
leafy and cruciferous vegetables, root vegetables (including
restricted amounts of potatoes), eggs and nuts. All subjects
were never-smokers or ex-smokers (Table 1), five of whom
had stopp ed smoking ≤2 weeks prior to study start (three in
the Palaeolithic group and two in the Consensus group).
The others had stopped smoking >6 months ago.
All subjects were informed individually (by S. Lindeberg,
K. Sjöström or E. Borgstrand) during two 1 h sessions and
1796 Diabetologia (2007) 50:1795–1807
were given written dietary advice and food recipes. Only
subjects in the Consensus group were informed of the
possible benefits of Mediterranean-like diets rich in whole
grains and about the Lyon Diet Heart Study [30]. The
Consensus group was also educated by use of a dietary
questionnaire for nutrition counselling (‘20 questions’)[31]
used in a successful health promotion programme, ‘Live
For Life,’ which led to lowered cardiovascular and total
mortality in the Habo municipality, Sweden [32] (Supple-
mentary Table 1).
Only subjects in the Palaeolithic group were educated in
the concept of evolutionary health promotion [33] and the
potential benefits of a Palaeolithic diet. They were advised
to increase their intake of lean meat, fish, fruits and vege-
tables and to avoid all kinds of dairy products, cereals
(including rice), beans, sugar, bakery products, soft drinks
and beer. The following items were accepted in limited
amounts for the Palaeolithic group: eggs (one or fewer per
day), nuts (preferentially walnuts), potatoes (two or fewer
medium-sized per day), rapeseed or olive oil (one or fewer
tablespoons per day). The intake of other foods was not
restricted and no advice was given with regard to
proportions of food categories (e.g. animal vs plant foods).
The type of dietary advice given to the Consensus group
was similar to the established programme at the Coronary
Care Unit. Since the required increase in education intensity
in order to match the Palaeolithic group was rather small,
no ‘usual care’ control group was considered necessary.
Advice about regular physical activity was given equally to
the two groups. Both groups were advised not to consum e
more than one glass of wine per day.
Evaluation Changes in the AUC between 0 and 120 min
during OGTT for plasma glucose (AUC Glucose
0–120
) and
plasma insulin (AUC Insulin
0–120
) were predefined primary
endpoints, along with changes in body weight and waist
circumference. The base of the AUC was set at 0 mmol/l for
glucose and 0 pmol/l for insulin. The computer-generated ho-
meostasis model assessment of insulin resistance (HOMA-IR)
index, which has been suggested to provide a reasonable es-
timate of insulin resistance, was derived from fasting plasma
glucose and insulin (www .dtu.ox.ac.uk)[34]. The early phase
of post-challenge glucose and insulin responses were
represented by the AUCs (Incremental AUC Glucose
0–30
and Incremental AUC Insulin
0–30
) during the first 30 min of
the OGTT, using levels at 0 min as the base of the area.
A 4 day weighed food record on four consecutive days,
including one weekend day, with weighing of each food
item on a digital weighing scale (that could be set to zero),
was completed by the participants, starting 15±5 days after
Table 1 Patient characteristics
at baseline
Values are means±SD for all
continuous variables except
C-reactive protein, for which
values are geometric means
(ranges)
a
For difference between
groups
b
<1 week between acute coro-
nary syndrome (myocardial
infarction and/or percutaneous
coronary intervention) and
dietary intervention
Group p value
a
Palaeolithic (n=14) Consensus (n=15)
Age (years) 65±10 57±7 0.01
Weight (kg) 92±11 96±12 0.3
BMI (kg/m
2
) 29±4 30±2 0.3
Waist (cm) 106±8 107±8 0.8
Fasting plasma glucose (mmol/l) 6.8±1.3 7.1±1.8 0.6
2 h plasma glucose (mmol/l) 8.9±1.8 8.8±3.8 1.0
Glucose AUC (mmol/l×min) 1,104±116 1,145±298 0.6
HbA
1c
(%) 4.8±0.3 4.9±0.8 0.6
IFG/IGT/diabetes (capillary), n 2/10/3 3/9/5 0.7
IFG/IGT/diabetes (OGTT), n 0/2/10 2/4/9 0.7
Fasting plasma insulin (pmol/l) 102±36 123±68 0.3
2 h plasma insulin (pmol/l) 988±570 674±532 0.14
ln HOMA-IR 0.62±0.38 0.75±0.53 0.5
Insulin AUC (nmol/l×min) 81±41 70±45 0.5
Systolic blood pressure (mmHg) 132±12 129±19 0.6
Diastolic blood pressure (mmHg) 77±9 78±11 0.7
Serum cholesterol (mmol/l) 4.2±0.6 4.5±0.9 0.3
Serum triacylglycerols (mmol/l) 1.3±0.6 1.9±0.8 0.06
C-reactive protein (μg/ml) 4.5 (0.8–88) 4.5 (0.8–43) 1.0
Study start <2 weeks
After acute coronary syndrome
b
(n) 6 7 0.8
Number of days 4±2 4±2 1.0
After statin treatment initiated (n) 6 6 0.9
After quitting smoking (n) 2 1 0.8
No statin treatment (n) 1 2 0.9
Smoking: never/ex- (n) 5/9 4/11 0.7
Diabetologia (2007) 50:1795–1807 1797
Table 2 Primary outcome variables
Group p value
a
Palaeolithic (n=14) Consensus (n=15)
Weight (kg)
Baseline 91.7±11.2 96.1±12.4 0.3
6 weeks 88.0±10.7 93.6±12.8 0.2
Change 0–6 weeks −3.7±2.2 −2.5±2.3 0.2
95% CI −4.9 to −2.4 −3.8 to −1.2
p value for change within group 0.0001 0.0009
12 weeks 86.7±11.3 92.2±12.9 0.2
Change 6–12 weeks −1.4±2.1 −1.3±1.1 0.9
95% CI −2.6 to −0.1 −1.9 to −0.7
p value for change within group 0.03 0.0003
Change 0–12 weeks −5.0±3.3 −3.8±2.4 0.3
95% CI −6.9 to −3.1 −5.2 to −2.5
p value for change within group 0.0001 0.0001
Waist circumference (cm)
Baseline 105.8±7.6 106.6±8.0 0.8
6 weeks 102.8±7.8 105.2±8.8 0.5
Change 0–6 weeks −3.0±1.8 −1.5±2.0 0.04
95% CI −4.0 to −2.0 −2.7 to −0.2
p value for change within group 0.0001 0.02
12 weeks 100.2±7.7 103.6±8.6 0.11
Change 6–12 weeks −2.6±2.4 −1.5±1.8 0.2
95% CI −3.9 to −1.2 −2.7 to −0.7
p value for change within group 0.001 0.003
Change 0–12 weeks −5.6±2.8 −2.9±3.1 0.03
95% CI −7.2 to −3.9 −4.8 to −1.1
p value for change within group 0.0001 0.004
AUC
b
Glucose
0–120
(mmol/l×min)
Baseline 1,104±118 1,145±298 0.6
6 weeks 877±161 1,024±339 0.15
Change 0–6 weeks −220±206 −120±255 0.3
95% CI −339 to −101 −262 to +21
p value for change within group 0.002 0.09
12 weeks 807±107 1,065±250 0.001
Change 6–12 weeks −70±156 +41±179 0.09
95% CI −160; +20 −59; +140
p value for change within group 0.12 0.4
Change 0–12 weeks −290±143 −80±168 0.001
95% CI −373 to −208 −173 to +13
p value for change within group 0.0001 0.09
AUC
b
Insulin
0–120
(nmol/l×min)
Baseline 80.5±41.1 69.7±44.7 0.5
6 weeks 63.1±30.0 54.1±37.2 0.5
Change 0–6 weeks −17.4±27.7 −15.5±16.9 0.8
95% CI −33.4 to −1.3 −24.9 to −6.2
p value for change within group 0.04 0.003
12 weeks 56.1±30.1 60.4±46.4 0.8
Change 6–12 weeks −7.0±16.9 +6.2±25.8 0.12
95% CI −16.7 to +2.8 −8.1 to +20.5
p value for change within group 0.15 0.4
Change 0–12 weeks −24.3±28.4 −9.3±23.3 0.13
95% CI −40.7 to −8.0 −22.2 to +3.6
p value for change within group 0.007 0.14
Values are means±SD
a
For difference between groups
b
AUC for glucose and insulin response to a 75 g OGTT. The base of the AUC was set at 0 mmol/l for glucose and 0 nmol/l for insulin.
1798 Diabetologia (2007) 50:1795–1807
initiating the dietary change. Nutrients were calculated using
Matsedel dietary analysis software (Kost och Näringsdata
AB, Bromma, Sweden). Glycaemic load was calculated by
multiplying the content of availab le carbohydrate in the
serving of each food by the food’s Glycaemic Index (with
glucose as the reference) as given by Foster-Powell et al.
[35]. Under-reporting was checked for by comparing food
records with baseline weight and achieved weight loss, and
by evalua ting distribution and amount of consumed food.
Body composition was estimated in a subset of 15 patients
by use of leg-to-leg bioelectrical impedance analysis (BIA),
using a Tanita Body Fat Analyzer (Model TBF 105; Tanita
Corporation of America, Arlington Heights, IL, USA).
Statistics A pre-study power calculation showed that 12
subjects would be needed in each group in order to detect,
with 80% power and at a significance level of 5%, a 20%
reduction in AUC Glucose
0–120
. Group assignment was
made by use of minimisation, a restricted randomisation
procedure which lowers the risk of baseline differences
[36], using diabetes at screening (no/yes) and BMI (below
or above 27 kg/m
2
) as restricting variables. A two-way
paired t test was used to analyse within-subject differences
in absolute values, while a two-way unpaired t test and
repeated-measures ANOVA were used to analyse between-
subject differences in these changes. Simple and multiple
linear regression was u sed to analyse univariate and
bivariate relationships. All variables showed reasonable
normal distribution in normal plots, but change in AUC
Glucose
0–120
, HOMA-IR and fruit intake showed perfect
normal distribution only after ln transformation.
Results
The two groups differed at baseline only with regard to age
being higher (p=0.01) and plasma triacylglycerols being
lower (p=0.0 6) in the Palaeolithic group (Table 1). There
was no relationship between age and any of the outcome
variables at study start (Supplementary Tables 2, 3, 4, 5 and
6). During the 12 week dietary intervention, both groups
decreased their waist circumference with a greater decrease
in the Palaeolithic group (p=0.03; Table 2). Weight loss
was on average 4.4 kg wi th no significant group difference.
In the Palaeolithic group, there was a 20% decrease in
the OGTT AUC Glucose
0–120
during the first 6 weeks
(p=0.0001), and an 8% decrease between weeks 6 and 12
(p=0.12; Figs 1 and 2, Table 2). In the Consensus group, a
10% decrease of AUC Glucose
0–120
was seen after the first
6 weeks (p=0.09) with no further change at 12 weeks
(+4%, p=0.4), despite a further decrease of weight (p=
0.0003) and waist circumference ( p=0.003). In the whole
study populatio n, there was no relationship between change
in AUC Glucose
0–120
and changes in weight (r=− 0.06, p=
0.9) or waist circumference (r=0.01, p=1.0) during the
whole study period (Supplementary Table 6), whi ch,
consequently, did not explain the larger improvement of
AUC Glucose
0–120
in the Palaeolithic group (Supplementary
Table 2).
In each group, AUC Insulin
0–120
, decreased durin g the
first 6 weeks by 22%, but the decrease over 12 week s was
significant only in the Palaeolithic group (Table 2, Fig. 3).
After adjustment for waist loss, the tendency for a larger
decrease of AUC Insulin
0–120
in the Palaeolithic group was no
longer significant (Supplementary Table 3). Among the two
groups combined, there was no association between change
in AUC Glucose
0–120
and change in AUC Insulin
0–120
(r=
0.19, p=0.3), and thus the group difference in improvement
of AUC Glucose
0–120
was independent of changes in AUC
Insulin
0–120
(p=0.002) or ln HOMA-IR (p=0.0009; Supple-
mentary Table 2).
Among secondary outcome variables, the most marked
change was a 36% decrease in 2 h plasma glucose in the
Palaeolithic group (from 8.9 to 5.6 mmol/l, p=0.0003;
Table 3). In contrast, 2 h plasma glucose decreased by only
Fig. 1 Plasma glucose during
OGTTs at study start (baseline,
closed circles) and after 12
weeks (open circles) in the
Palaeolithic (a) and Consensus
(b) groups. Values are
means±SE. ***p<0.001
Diabetologia (2007) 50:1795–1807 1799
7% in the Consensus group (p=0.10), and the difference
between the groups was highly significant. After 12 weeks,
all 14 subjects in the Palaeolithic group had normal values,
compared with 7 of 15 subjects in the Consensus group (p=
0.0007 for group difference; Table 4). At 12 weeks, five
subjects in the Consensus group still had diabetic values.
There was a decrease of HOMA-IR in both groups with
no significant difference between the two groups (Table 4).
The QUICKI index of insulin sensitivity [1/(ln fasting
plasma insulin+ln fasting plasma glucose)] did not change
more in the Palaeolithic group than in the Consensus group
(p=0.23, data not shown). The early phase of post-
challenge glucose and insulin responses, as represented by
Incremental AUC Glucose
0–30
and Incremental AUC
Insulin
0–30
, did not change significantly during the trial,
although a trend towards lowered Incremental AUC
Insulin
0–30
was seen in both groups (Table 4).
Reported food composition differed between the two
groups such that subjects in the Palaeolithic group had a
much lower intake of dairy products, cereals and oil/
margarine, and a higher intake of fruits and nuts (Table 5).
The intake of vegetables, meat, meat products or fish did
not differ significantly between the groups. Total fat intake
was low with no difference between the groups (Table 6).
Absolute protein intake was identical in the two groups
while relative protein intake (as a percentage of total energy
intake [E%]) was higher in the Palaeolithic group. Absolute
carbohydrate intake was 43% lower in the Palaeolithic
group, and 23% lower in terms of E%. Glycaemic load was
47% lower in the Palaeolithic group and correlated strongly
with cereal intake (r=0.75, p<0.0001).
Energy intake was 25% lower in the Palaeolithic group
(p=0.004; Table 6) despite similar quantities of consumed
food (by weight; Table 5). After adjustment for energy
intake, the improvement of AUC Glucose
0–120
was still
larger in the Palaeolithic group (p=0.02; Supplementary
Table 2), while the larger waist loss, and the tendency for
larger decrease of AUC Insulin
0–120
, compared with the
Consensus group, disappeared (Supplementary Table 3).
In post hoc analysis among the whole study population, a
positive association between intake of cereals and change in
waist circumference explained 42% of waist loss among the
whole study population (p=0.0003; Supplementary Table 6),
and 40% in the Consensus group alone (p=0.016). In con-
trast, there was a negative correlation between fruit intake
and change in waist circumference, which explained 21% of
waist loss (p=0.01). Each of these associations remained
significant after adjustment for dietary assignment, energy
intake, carbohydrate intake or glycaemic load (Supplemen-
tary Table 5). Thus, waist loss increased with increasing
a
b
100
1,000
0
20 40 60 80 100
120
Time (min)
Plasma insulin (pmol/l)
*
100
1,000
0
20
40 60 80 100
120
Time
(
min
)
Plasma insulin (pmol/l)
*
**
Fig. 3 Plasma insulin during
OGTTs at study start (baseline,
closed circles) and after 12
weeks (open circles) in the
Palaeolithic (a) and Consensus
(b) groups. Values are means
SE. *p<0.05; **p>0.01
0
200
400
600
800
1,000
1,200
1,400
Palaeolithic Consensus
Glucose AUC
0−120
(mmol/l x min)
Fig. 2 Mean glucose AUCs (0–120 min) during OGTTs at study start
(baseline, light grey columns) and after 6 weeks (dark grey columns)
and 12 weeks (black columns) in the Palaeolithic and Consensus
groups. Error bars denote 95% CIs
1800 Diabetologia (2007) 50:1795–1807
intake of fruits and decreasing intake of cereals, associations
which explained most of the group difference in waist loss.
Compared with waist change, weight change was generally
less clearly associated with dietary assignment and other
variables (Table 2, Supplementary Tables 2, 3, 4, 5 and 6).
Glycaemic load was positively associated with changes
in waist (r=0.52, p=0.008) and AUC Glucose
0–120
(r=
0.50, p=0.01) but not with change in AUC Insulin
0–120
(r=
0.30, p=0.15). When glycaemic load and dietary assign-
ment were entered simultaneously as explanatory variables
in bivariate linear regression, neither of these was signifi-
cantly associated with change in AUC Glucose
0–120
(Supplementary Table 2). In forward stepwise linear re-
gression with glycaemic load and dietary assignment as
independent variables, only dietary assignment was associ-
ated with change in AUC Glucose
0–120
(data not shown).
None of the other effects, nor lack of effects, of group
assignment on primary outcome variables (changes in weight,
Table 3 Glucose and
insulin responses to OGTTs
(secondary outcome variables)
during the trial
Values are means±SD
a
For difference between
groups
*p<0.01 by paired t test
for change within group
(6 week level is compared with
baseline and 12 week level is
compared with 6 week level)
**p<0.05 by paired t test
for change within group
(6 week level is compared with
baseline and 12 week level
is compared with 6 week level)
Group p value
a
Palaeolithic (n=14) Consensus (n=15)
Fasting plasma glucose (mmol/l)
Baseline 6.8±1.3 7.1±1.8 0.6
6 weeks 5.2±1.1* 5.8±1.2** 0.2
12 weeks 5.1±1.0 6.2±1.4 0.02
Change 0–12 weeks −1.7±1.7 −0.9±1.8 0.2
95% CI −2.7 to −0.7 −1.9 to +0.08
p value for change within group 0.003 0.07
30 min plasma glucose (mmol/l)
Baseline 10.0±1.1 10.7±2.4 0.3
6 weeks 8.4±1.6* 9.8±3.3 0.16
12 weeks 8.0±1.1 10.3±2.1 0.001
Change 0–12 weeks −2.0±1.2 −0.4±1.6 0.008
95% CI −2.7 to −1.3 −1.3 to +0.5
p value for change within group 0.0001 0.3
120 min plasma glucose (mmol/l)
Baseline 8.9±1.8 8.8±3.8 1.0
6 weeks 6.6±1.5* 7.8±4.1 0.3
12 weeks 5.6±1.5** 7.9±3.1 0.01
Change 0–12 weeks −3.3±1.9 −0.9±2.0 0.003
95% CI −4.4 to −2.2 −2.0 to +0.2
p value for change within group 0.0001 0.10
Fasting plasma insulin (pmol/l)
Baseline 102±36 123±68 0.3
6 weeks 91±32 100±45 0.5
12 weeks 86±36 101±53 0.4
Change 0–12 weeks −16±27 −22±54 0.7
95% CI −32 to −0.3 −51 to +8
p value for change within group 0.047 0.15
30 min plasma insulin (pmol/l)
Baseline 575±290 625±416 0.7
6 weeks 503±222 516±393 0.9
12 weeks 453±226 507±355 0.7
Change 0–12 weeks −121±230 −118±202 1.0
95% CI −254 to +12 −230 to −6
p value for change within group 0.07 0.04
120 min plasma insulin (pmol/l)
Baseline 988±570 674±532 0.14
6 weeks 702±423** 482±374* 0.15
12 weeks 615±443 631±633 1.0
Change 0–12 weeks
−374±408 −42±408 0.04
95% CI −609 to −138 −268 to +183
p value for change within group 0.005 0.7
Diabetologia (2007) 50:1795–1807 1801
waist, AUC Glucose
0–120
and AUC Insulin
0–120
)was
essentially altered after adjustment for age or baseline levels
of weight, waist, glucose, insulin, AUC Glucose
0–120
or
AUC Insulin
0–120
, n or after adjustment for intake (g/day or
E%) of carbohydrate, protein, total fat, saturated fat,
monounsatur ated fat, polyun satur at ed f at, f ibre or sodium.
Repeated-measures ANOVA gave similar results for
primary and secondary outcome variables, and addition
of baseline values as covariates confirmed the independent
effect of Palaeolithic d iet on improveme nt of gluco se
tolerance (data not shown). Serum lipids changed to a
similar extent in b oth groups, due to initiation of statin
treatment in mos t patients, and there was no decreas e in
blood pressure (data not shown). The impact of medication
was not anal ys ed.
Among the 15 subjects who underwent BIA for body
composition, change of fat mass did not differ between the
groups (Table 7), and it explained 50% of weight change (p=
Table 4 Other glucometabolic
variables in the two groups
Values are means±SD
*p<0.05 by paired t test
for change within group
(6 week level is compared with
baseline and 12 week level
is compared with 6 week level)
a
For difference between
groups
b
Fasting venous plasma
glucose ≤6.0 mmol/l and
2 h venous plasma glucose
<7.8 mmol/l at OGTT
(despite increased capillary
blood glucose at screening)
c
Fasting venous plasma
glucose ≥7.0 mmol/l or 2 h
venous plasma glucose
≥11.1 mmol/l at OGTT
d
Incremental AUC
0–30
, incre-
mental AUC during the first
30 min of OGTT, using levels
at 0 min as the base of the
area
Group p value
a
Palaeolithic (n=14) Consensus (n=15)
HbA
1c
(%)
Baseline 4.76±0.26 4.89±0.79 0.6
6 weeks 4.61±0.25* 4.84±0.72 0.3
12 weeks 4.64±0.22 4.85±0.69 0.3
Change 0–12 weeks −0.13±0.26 −0.03±0.39 0.4
95% CI −0.28 to +0.02 −0.24 to +0.17
p value for change within group 0.09 0.7
Normal glucose levels
b
(n)
Baseline 2 2 0.8
6 weeks 10 10 0.7
12 weeks 14 7 0.0007
Diabetic glucose levels
c
(n)
Baseline 10 9 0.4
6 weeks 1 3 0.2
12 weeks 0 5 0.01
ln HOMA-IR
Baseline 0.62±0.38 0.75±0.53 0.5
6 weeks 0.47±0.33* 0.55±0.42* 0.6
12 weeks 0.39±0.36 0.55±0.46 0.3
Change 0–12 weeks −0.24±0.29 −0.19±0.36 0.7
95% CI −0.40 to −0.07 −0.39 to +0.01
p value for change within group 0.01 0.03
Insulin/Glucose
0–30
Baseline 172±125 145±110 0.5
6 weeks 135±61 133±144 1.0
12 weeks 139±72 112±126 0.5
Change 0–12 weeks −33±94 −33±71 1.0
95% CI −87 to +21 −73 to +8
p value for change within group 0.2 0.11
Incremental Glucose AUC
0–30
d
Baseline 48±20 54±20 0.4
6 weeks 48±19 60±40 0.3
12 weeks 44±20 62±26 0.06
Change 0–12 weeks −4±24 +7±21 0.19
95% CI −18 to +10 −4 to +19
p value for change within group 0.6 0.2
Incremental Insulin AUC
0–30
d
Baseline 7.1±4.0 7.5±5.9 0.8
6 weeks 6.2±3.0 6.2±5.6 1.0
12 weeks 5.5±2.9 6.1±4.8 0.7
Change 0–12 weeks −1.6±3.1 −1.5±2.7 0.9
95% CI −3.4 to +0.2 −3.0 to +0.07
p value for change within group 0.08 0.06
1802 Diabetologia (2007) 50:1795–1807
0.002). In this subset of patients, change in fat mass
explained <l% of change in AUC Glucose
0–120
.
Discussion
We found mark ed improvement of glucose tolerance after
advice to eat a Palaeolithic diet, based on lean meat, fish,
fruits, vegetables, root vegetables, eggs and nuts as staple
foods, while avoiding cereals, dairy products, refined fat,
sugar and salt. Control subjects, who were advised to
follow a Consensus (Mediterranean-like) diet based on
whole grains, low-fat dairy products, fish, fruits and
vegetables, did not significantly improve their glucose
tolerance despite decreases in weight and waist circumfer-
ence. The more pronou nced improvement of g lucose
tolerance in the Palaeolithic group was unrelated to weight
loss or decrease in waist circu mference. In contrast, the
insulin response changed more as a result of change in
waist circumference than of dietary assignment or food
choice.
The higher drop-out rate in the Palaeolithic group (three
vs none) does not appear to be an important source of bias. If
we assume no change in primary outcome variables in any of
the drop-out subjects, had they finished the trial, we would
still have found larger decreases in AUC Glucose
0–120
(p=
0.01) and 2 h glucose (p=0.02) in the Palaeolithic group
than in the Consensus group.
It is conceivable, but not very likely, that the more
pronounced improvement of glucose tolerance in the
Palaeolithic group was due to higher motivation (rather
than different food patt erns). We were meticulous in our
efforts not to give the subjects in the Consensus group a
feeling of belonging to a control group. Thus, we told
eligible persons that we were to compare two healthy diets,
Table 5 Diet composition (g/day) in the two groups, as estimated
from 4 day weighed food records
Group p
value
a
Palaeolithic
(n=14)
Consensus
(n=15)
Fruits 493±335 252±179 0.03
Vegetables
b
327±233 202±88 0.07
Potatoes 51±42 77±78 0.3
Nuts 11±12 2±6 0.02
Meat, fresh 143±95 97±67 0.16
Meat products 65±59 58±49 0.8
Fish 119±92 77±56 0.16
Eggs 29±23 19±18 0.21
Beans, peas 8±21 15±26 0.5
Cereals 18±52 268±96 0.0001
Milk and dairy products 45±119 287±193 0.0006
Oil, margarine
c
1±3 16±11 0.0001
Sauce 2±6 25±31 0.02
Pastry 1±3 13±25 0.12
Jam 1±3 6±10 0.12
Total amount of food 1,311±598 1,382±222 0.7
Wine 59±63 37±51 0.3
Beer, light
d
11±27 27±47 0.3
Sweet beverages
(excluding juice)
18±46 53±90 0.2
Juice 38±75 88±141 0.3
Values are means±SD
a
For difference between groups
b
Including root vegetables (but excluding potatoes and beans with
pods)
c
Butter was not reported to be consumed by anyone
d
Stronger beer or liquor was not consumed, as reported
Table 6 Daily intake of macronutrients, dietary fibre, cholesterol,
sodium, potassium, magnesium and calcium in the two groups, as
estimated from 4 day weighed food records
Group p value
a
Palaeolithic
(n=14)
Consensus
(n=15)
Energy
MJ 5.6±2.2 7.5±1.3
kcal 1,344±521 1,795±306 0.01
Protein
g 90±41 89±20 0.9
g/kg body weight 0.98±0.4 0.95±0.2 0.8
E% 27.9±6.8 20.5±3.6 0.002
Total fat
g 42±20 50±13 0.2
g/kg body weight 0.44±0.2 0.55±0.2 0.12
E% 26.9±6.4 24.7±4.3 0.3
Fatty acids
Saturated (g) 11.5±4.8 16.8±4.2 0.005
E% 7.7±2.4 8.3±1.7 0.4
Monounsaturated (g) 16.3±7.4 19.0±5.0 0.3
E% 10.7±2.6 9.4±1.9 0.2
Polyunsaturated (g) 9.6±7.5 9.0±3.0 0.8
E% 5.8±2.5 4.4±1.1 0.06
Carbohydrate
g 134±56 231±48 0.0001
g/kg body weight 1.4±0.6 2.5±0.6 0.0001
E% 40.2±8.3 51.7±5.3 0.0002
Glycaemic load
b
65±30 122±28 0.0001
Alcohol (E%) 3.9±4.4 2.3±3.0 0.3
Fibre (g) 21.4±13.2 26.8±7.4 0.2
Cholesterol (mg) 397±192 295±122 0.11
Salt (g)
Sodium 1.9±0.6 2.9±0.7 0.0006
Sodium chloride 4.7±1.6 7.2±1.7 0.0006
Values are means±SD
a
For difference between groups
b
The Glycaemic Index (with glucose as the reference food) multiplied
by the amount of carbohydrate
Diabetologia (2007) 50:1795–1807 1803
not knowing which was the better one. We informed all
subjects individually of the presumed benefits of their
respective diet (but not of those of the other diet) during
two 1 h sessions, and all subjects were provided with
recipes and written dietary advice of equal length. During
the 12 week trial, waist circumference decreased more in
the Palaeolithic group, but this did not explain the more
pronounced decrease in fasting and post-prandial plasma
glucose in these subjects.
Among the whole study population, change in AUC
Glucose
0–120
was not related to changes in weight or waist
circumference. Considering the large variation in weight
loss (between −10.7 and +1.3 kg), and in light of earlier
studies showing weight loss to be the major deter minant of
improved glucose tolerance [12], this lack of relationship is
unexpected. In the Diabetes Prevention Project, weight loss
was the dominant predictor of reduced diabetes incidence
among glucose-intolerant subjects who were randomised to
lifestyle modification [37]. However, weight change does
not explain all of the improvement in glucose tolerance in
such trials, and in a meta-analysis on the efficacy of
lifestyle education to prevent type 2 diabetes in high-risk
individuals, four out of eight trials did not find any effect
on 2 h plasma glucose despite significant weight loss [12].
Furthermore, in epidemiological studies most of the
variation in glucos e tolerance among the general population
is not explained by adiposity [38]. Therefore, an improve-
ment in glucose tolerance that is independent of weight
change is not entirely unexpected.
There was no apparent influence of dietary assignment
on the HOMA-IR index of insulin sensitivity, and adjust-
ment for changes in waist circumference or body weight
eliminated the tendency towards larger decrease of AUC
Insulin
0–120
in the Palaeolithic group. This is in contrast to a
recent feeding trial in pigs, where we found markedly lower
insulin response by the frequently sampled IVGTT,
independent of body weight, after 15 months of a cereal-
free Palaeolithic diet, compared with a cereal-based swine
feed [39]. This discrepancy may be due to the use of
frequently sampled IVGTT in the study in pigs, which
gives a more precise measure of insulin sensi tivity than that
of the present study (HOMA-IR). Since we did not perform
euglycaemic insulin clamp measurements, the gold standard
for assessing whole-body insulin sensitivity, we may have
Table 7 Leg-to-leg BIA in a
subset of patients (n=15)
Values are means±SD
a
For difference between
groups
*p<0.05 by paired t test
for change within group
(6 week level is compared with
baseline and 12 week level
is compared with 6 week level)
**p<0.01 by paired t test
for change within group
(6 week level is compared with
baseline and 12 week level
is compared with 6 week level)
Group p value
a
Palaeolithic (n =8) Consensus (n=7)
Fat mass (kg)
Baseline 28.7±5.4 33.0±8.6 0.3
6 weeks 26.5±4.5* 31.7±8.5* 0.16
12 weeks 24.9±4.5* 30.8±8.7 0.12
Change 0–12 weeks −3.9±2.9 −2.3±1.0 0.18
95% CI −6.3 to −1.5 −3.2 to −1.4
p value for change within group 0.007 0.0009
Fat mass (% of body mass)
Baseline 30.0±3.0 32.6±5.7 0.3
6 weeks 28.9±2.7 31.8±5.6* 0.2
12 weeks 27.4±2.7** 31.0±5.9 0.14
Change 0–12 weeks −2.6±2.3 −1.6±0.6 0.3
95% CI −4.5 to −0.7 −2.2 to −1.1
p value for change within group 0.02 0.0004
Fat-free mass (kg)
Baseline 66.6±6.3 66.7±4.8 1.0
6 weeks 64.8±6.1 66.6±4.9 0.5
12 weeks 65.6±6.6
*
66.9±4.9 0.7
Change 0–12 weeks −1.0±2.7 +0.2±0.9 0.3
95% CI −3.3 to +1.3 −0.7 to +1.0
p value for change within group 0.3 0.6
Total body water (kg)
Baseline 48.7±4.6 48.8±3.5 1.0
6 weeks 47.4±4.5 48.7±3.6 0.6
12 weeks 48.0±4.8* 49.0±3.6 0.7
Change 0–12 weeks −0.7±2.0 +0.2±0.7 0.3
95% CI −2.4 to +0.9 −0.5 to +0.8
p value for change within group 0.3 0.5
1804 Diabetologia (2007) 50:1795–1807
missed a significant effect on insulin sensitivity. If not, our
findings add to the evidence that reduction of waist
circumference is more important than dietary composition
for the treatment of insulin resistance [19].
The very low reported energy intake in the Palaeolithic
group, as calculated from 4 day weighed food records
(registered early in the trial), does not necessarily imply
under-reporting of food intake. An energy deficit of 4 MJ/day
would be expected to cause a weight loss of 1 kg/week in the
second and third months of energy restriction, and even more
during the first month [40]. Thus, assuming a pre-study
energy intake of at least 10 MJ/day, the reported i n-trial
energy intake is actually higher than expected from the
observed weight loss, even in the Palaeolithic group. In
addition, the similar w eight loss in the two groups is not
incompatible with different energy intakes. In this cont ext,
the laws of thermodynamics need to be considered
thoroughly. These laws state that energy is constant and
cannot be destr oye d. H oweve r, the y also st at e that e ne rgy
can take various forms, including heat, and that conver-
sion from one form of energy to a noth er is more or le ss
efficient [41]. Highly relevant, then, is the finding in
animal ex per ime nts of decreased body temperat ur e on
low-calorie diets [42, 43]. Accordingly, identical weight
loss on differen t ene rgy int akes does not violate the laws
of thermodynamics [41].
It is important to separate glycaemic control, as
measured by HbA
1c
, from glucose tolerance. A habitual
diet which reduces the post-prandial glucose response, such
as a low glycaemic load diet, can reduce the metabolic
consequences of glucose intolerance, including delaying the
manifestation of diabet es, without necessarily improving
glucose tolerance itself [19, 44]. Although we cannot rule
out glycaemic load as an important factor for glucose
tolerance, our finding that the effect of Palaeolithic diet on
glucose tolerance was independent of carbohydrate intake
agrees with earlier studies which do not indicate a
beneficial effect of carbohydrate restriction on glucose
tolerance [20, 45–47].
The high fruit intake in the Palaeolithic group, almost
sevenfold higher than the median intake among Swedish
men (75 g/day) [48], and twice as high as in the Consensus
group, should also be viewed against this background. Des-
pite large variation in fruit intake (range 160–1,435 g/day
in the Palaeolithic group and 53–679 g/day in the Con-
sensus group), it was not associated with change in AUC
Glucose
0–120
(r=−0.02, p=0.9) or AUC Insulin
0–120
(r=
−0.02, p=0.9) and did not explain the effects of group
assignment on these outcome variables. Furthermore, a
high fruit intake was associated with larger waist loss.
Thus, our study lends no support to the notion that fruit
intake should be restricted in patients with diabetes or
glucose intolerance.
This is, to the best of our knowledge, the first controlled
study of the effects of an ancestral human diet in patients
with IGT or diabetes. In a non-controlled study of ten
Australian Aborigines with diabetes and a mean BMI of 27
kg/m
2
,O’Dea et al. found that reversion to a hunter–
gatherer lifestyle during 7 weeks led to 10% weight loss
andreductionsinfastingand2hglucoseof45and36%
(p<0.0001 for all) [49 ]. Fasting insulin decreased by 48%
(p<0.0001), while 2 h insulin did not change (+20%, not
significant). Both die t an d physical activity changed
markedly, which precludes evaluation about t he isolated
role of diet. In contrast, in a similar study on healthy
Australian Aborigines by the same authors, the insulin
response to 70 g of starch from white bread (and butter)
was reduced, while the glucose response was not, after 10–12
weeks of reversion to a traditional lifestyle [50].
In conclusion, we found marked improvement of glucose
tolerance in IHD patients with increased blood glucose or
diabetes after advice to follow a Palaeolithic diet compared
with a healthy Western diet. The larger improvement of
glucose tolerance in the Palaeolithic group was independent
of energy intake and macronutrient composition, which
suggests that avoiding Western foods is more imp ortant
than counting calories, fat, carbohydrate or protein. The
study adds to the notion that healthy diets based on whole-
grain cereals and low-fat dairy products are only the second
best choice in the prevention and treatment of type 2
diabetes.
Acknowledgements The study was funded by Region Skåne and
Lund University.
Duality of interest The authors declare that there is no duality of
interest associated with this manuscript.
References
1. Nielson C, Lange T, Hadjokas N (2006) Blood glucose and
coronary artery disease in nondiabetic patients. Diabetes Care
29:998–1001
2. Brunner EJ, Shipley MJ, Witte DR, Fuller JH, Marmot MG
(2006) Relation between blood glucose and coronary mortality
over 33 years in the Whitehall Study. Diabetes Care 29:26–31
3. Bartnik M, Malmberg K, Norhammar A, Tenerz A, Ohrvik J,
Ryden L (2004) Newly detected abnormal glucose tolerance: an
important predictor of long-term outcome after myocardial
infarction. Eur Heart J 25:1990–1997
4. Fisman EZ, Motro M, Tenenbaum A, Boyko V, Mand elzweig L,
Behar S (2001) Impaired fasting glucose concentrations in
nondiabetic patients with ischemic heart disease: a marker for a
worse prognosis. Am Heart J 141:485–490
5. Norhammar A, Tenerz A, Nilsson G et al (2002) Glucose
metabolism in patients with acute myocardial infarction and no
previous diagnosis of diabetes mellitus: a prospective study.
Lancet 359:2140–2144
Diabetologia (2007) 50:1795–1807 1805
6. Bartnik M, Ryden L, Ferrari R et al (2004) The prevalence of
abnormal glucose regulation in patients with coronary artery
disease across Europe. The Euro Heart Survey on diabetes and the
heart. Eur Heart J 25:1880–1890
7. Hashimoto K, Ikewaki K, Yagi H et al (2005) Glucose intolerance
is common in Japanese patients with acute coronary syndrome
who were not previously diagnosed with diabetes. Diabetes Care
28:1182–1186
8. Ishihara M, Inoue I, Kawagoe T et al (2006) Is admission
hyperglycaemia in non-diabetic patients with acute myocardia l
infarction a surrogate for previously undiagnosed abnormal
glucose tolerance? Eur Heart J 27:2413–2419
9. Hu DY, Pan CY, Yu JM (2006) The relationship between coronary
artery disease and abnormal glucose regulation in China: the
China Heart Survey. Eur Heart J 27:2573–2579
10. Johansen OE, Birkeland KI, Brustad E et al (2006) Undiagnosed
dysglycaemia and inflammation in cardiovascular disease. Eur J
Clin Investig 36:544–551
11. Harding SA, Anscombe R, Weatherall M, Prasad S, Lever N,
Krebs J (2006) Abnormal glucose metabolism and features of the
metabolic syndrome are common in patients presenting f or
elective cardiac catheterization. Intern Med J 36:759–764
12. Yamaoka K, Tango T (2005) Efficacy of lifestyle education to
prevent type 2 diabetes: a meta-analysis of randomized controlled
trials. Diabetes Care 28:2780–2786
13. Knowler WC, Barrett-Connor E, Fowler SE et al (2002)
Reduction in the incidence of type 2 diabetes with lifestyle
intervention or metformin. N Engl J Med 346:393–403
14. Tuomilehto J, Lindstrom J, Eriksson JG et al (2001) Prevention of
type 2 diabetes mellitus by changes in lifestyle among subjects
with impaired glucose tolerance. N Engl J Med 344:1343–1350
15. De Backer G, Ambrosioni E, Borch-Johnsen K et al (2003)
European guidelines on cardiovascular disease prevention in
clinical practice. Third Joint Task Force of European and Other
Societies on Cardiovascular Disease Prevention in Clinical
Practice. Eur Heart J 24:1601–1610
16. Mann JI, De Leeuw I, Hermansen K et al (2004) Evidence-based
nutritional approaches to the treatment and prevention of diabetes
mellitus. Nutr Metab Cardiovasc Dis 14:373–394
17. Franz MJ, Bantle JP, Beebe CA et al (2002) Evidence-based
nutrition principles and recommendations for the treatment and
prevention of diabetes and related complications. Diabetes Care
25:148–198
18. Kennedy RL, Chokkalingam K, Farshchi HR (2005) Nutrition in
patients with type 2 diabetes: are low-carbohydrate diets effective,
safe or desirable? Diabet Med 22:821–832
19. Reaven GM (2005) The insulin resistance syndrome: definition
and dietary approaches to treatment. Annu Rev Nut r 25:391–
406
20. Noakes M, Foster PR, Keogh JB, James AP, Mamo JC, Clifton
PM (2006) Comparison of isocaloric very low carbohydrate/high
saturated fat and high carbohydrate/low saturated fat diets on body
composition and cardiovascular risk. Nutr Metab (Lond) 3:7
21. Lavigne C, Tremblay F, Asselin G, Jacques H, Marette A (2001)
Prevention of skeletal muscle insulin resistance by dietary cod
protein in high fat-fed rats. Am J Physiol Endocrinol Metab 281:
E62–E71
22. Vasankari TJ, Vasankari TM (2006) Effect of dietary fructose on
lipid metabolism, body weight and glucose tolerance in humans.
Scand J Food Nutr 50:55–63
23. Petrie JR, Morris AD, Minamisawa K et al (1998) Dietary sodium
restriction impairs insulin sensitivity in noninsulin-depend ent
diabetes mellitus. J Clin Endocrinol Metab 83:1552–1557
24. Donovan DS, Solomon CG, Seely EW, Williams GH, Simonson
DC (1993) Effect of sodium intake on insulin sensitivity. Am J
Physiol 264:E730–734
25. Eaton S, Konner M (1985) Paleolithic nutrition. A consideration
of its nature and current implications. N Engl J Med 312:283–289
26. Lindeberg S, Cordain L, Eaton SB (2003) Biological and clinical
potential of a palaeolithic diet. J Nutr Environ Med 13:1–12
27. Lindeberg S, Lundh B (1993) Apparent absence of stroke and
ischaemic heart disease in a traditional Melanesian island: a
clinical study in Kitava. J Intern Med 233:269
–275
28. Lindeberg S, Nilsson-Ehle P, Terént A, Vessby B, Scherstén B
(1994) Cardiovascular risk factors in a Melanesian population
apparently free from stroke and ischaemic heart disease—the
Kitava study. J Intern Med 236:331–340
29. Lindeberg S, Eliasson M, Lindahl B, Ahrén B (1999) Low serum
insulin in traditional Pacific Islanders—the Kitava Study. Metab-
olism 48:1216–1219
30. de Lorgeril M, Renaud S, Mamelle N et al (1994) Mediterranean
alpha-linolenic acid-rich diet in secondary prevention of coronary
heart disease. Lancet 343:1454–1459
31. Lingfors H, Lindström K, Persson L-G et al (1994) Evaluation of
a pedagogic dietary questionnaire aimed for health surveys. Scand
J Nutr 38:106–111
32. Lingfors H, Persson LG, Lindstrom K, Ljungquist B, Bengtsson C
(2002) Time for a “vision zero” concerning premature death from
ischaemic heart disease? Scand J Prim Health Care 20:28–32
33. Eaton SB, Strassman BI, Nesse RM et al (2002) Evolutionary
health promotion. Prev Med 34:109–118
34. Levy JC, Matthews DR, Hermans MP (1998) Correct homeostasis
model assessment (HOMA) evaluation uses the computer pro-
gram. Diabetes Care 21:2191–2192
35. Foster-Powell K, Holt SH, Brand-Miller JC (2002) International
table of glycemic index and glycemic load values: 2002. Am J
Clin Nutr 76:5–56
36. Altman DG (1991) Practical statistics fo r medical research.
Chapman & Hall, London
37. Hamman RF, Wing RR, Edelstein SL et al (2006) Effect of weight
loss with lifestyle intervention on risk of diabetes. Diabetes Care
29:2102–2107
38. McKeigue PM, Pierpoint T, Ferrie JE, Marmot MG ( 1992)
Relationship of glucose intolerance and hyperinsulinaemia to body
fat pattern in south Asians and Europeans. Diabetologia 35:785–791
39. Jönsson T, Ahren B, Pacini G et al (2006) A Paleolithic diet
confers higher insulin sensitivity, lower C-reactive protein and
lower blood pressure than a cereal-based diet in domestic pigs.
Nutr Metab (Lond) 3:39
40. Garrow JS (2000) Obesity. In: Garrow JS, James WPT (eds)
Human nutrition and dietetics. Churchill Livingstone, Edinburgh,
pp 527–545
41. Feinman RD, Fine EJ (2004) “A calorie is a calorie” violates the
second law of thermodynamics. Nutr J 3:9
42. Lane MA, Baer DJ, Rumpler WV et al (1996) Calorie restriction
lowers body temperature in rhesus monkeys, consistent with a
postulated anti-aging mechanism in rodents. Proc Natl Acad Sci
USA 93:4159–4164
43. Saper CB (2006) Biomedicine. Life, the universe, and body
temperature. Science 314:773–774
44. Gannon MC, Nuttall FQ (2006) Control of blood glucose in type
2 diabetes without weight loss by modification of diet composi-
tion. Nutr Metab (Lond) 3:16
45. Pittas AG, Roberts SB, Das SK et al (2006) The effects of the
dietary glycemic load on type 2 diabetes risk factors during weight
loss. Obesity (Silver Spring) 14:2200–2209
46. Nestel P, Cehun M, Chronopoulos A (2004) Effects of long-term
consumption and single meals of chickpeas on plasma glucose,
insulin, and triacylglycer ol concentrations. Am J Clin Nutr
79:390–395
47. Vidon C, Boucher P, Cachefo A, Peroni O, Diraison F, Beylot M
(2001) Effects of isoenergetic high-carbohydrate compared with
1806 Diabetologia (2007) 50:1795–1807
high-fat diets on human cholesterol synthesis and expression of
key regulatory genes of cholesterol metabolism. Am J Clin Nutr
73:878–884
48. Becker W, Pearson M (2002) Dietary habits and nutrient intake in
Sweden 1997–98: the Second National Food Consumption Survey
(in Swedish). Swedish National Food Administration, Uppsala
49. O’Dea K (1984) Marked improvement in carbohydrate and lipid
metabolism in diabetic Australi an aborigines after temporary
reversion to traditional lifestyle. Diabetes 33:596– 603
50. O’Dea K, Spargo RM, Akerman K (1980) The effect of transition
from traditional to urban life-style on the i nsulin secretory
response in Australian Aborigines. Diabetes Care 3:31–37
Diabetologia (2007) 50:1795–1807 1807
