ArticlePDF AvailableLiterature Review

Abstract

Re-examine the chronic effect (> 7 days) of fructose consumption has on postprandial triglycerides (TG), in adolescents and adults. The research was carried out in March 2017 and used different electronic databases, such as Medline® (Pubmed®), Embase® and Cochrane. The review considered clinical trials (parallel or crossed) that evaluated the effect of fructose consumption for a longer period than 7 days, in humans. Two investigators independently performed data extraction. The outcome was the absolute delta of TG concentration in a 4-h postprandial period. The results were presented with delta mean difference between treatments with 95% confidence intervals (CI 95%). The calculations were made based on random effect models. Statistical heterogeneity of treatment effects between studies was assessed by Cochrane's "Q Test" and "I²" inconsistency test. The meta-analysis of the 12 selected interventions (n = 318) showed that fructose generated larger variation (delta) of TG concentrations during the postprandial period, compared to other carbohydrates (mean difference: 8.02 mg/dL; CI 95%: 0.46-15.58; I²: 74%). High heterogeneity was generated almost exclusively by one study, and its withdrawal did not alter the result. We concluded that chronic consumption of fructose (>7 days) plays a negative role on postprandial TG in healthy adolescents and adults, overweight/obese, but not in diabetics. This study was registered at http://www.crd.york.ac.uk/prospero as CRD42017059987
Effects of fructose consumption on postprandial TAG: an update on systematic
reviews with meta-analysis
Rodrigo C. O. Macedo*, Alexandra F. Vieira, Cesar E. J. Moritz and Alvaro Reischak-Oliveira
Grupo de Estudos em Fisiologia e Bioquímica do Exercício (GEFEX), Universidade Federal do Rio Grande do Sul (UFRGS),
Porto Alegre, RS, 90960-200, Brazil
(Submitted 20 November 2017 Final revision received 30 April 2018 Accepted 7 May 2018)
Abstract
The aim of this study was to re-examine the chronic effect (>7 d) of fructose consumption on postprandial TAG, in adolescents and adults. The
research was carried out in March 2017 and used different electronic databases, such as Medline
®
(Pubmed
®
), Embase
®
and Cochrane. The
review considered clinical trials (parallel or crossed) that evaluated the effect of fructose consumption for a period longer than 7 d, in humans.
Two investigators independently performed data extraction. The outcome was the absolute delta of TAG concentration in a 4-h postprandial
period. The results were presented with delta mean difference between treatments with 95 % CI. The calculations were made based on
random-effect models. Statistical heterogeneity of treatment effects between studies was assessed by CochranesQ Testand I
2
inconsistency
test. The meta-analysis of the twelve selected interventions (n318) showed that fructose generated larger variation (δ) of TAG concentrations
during the postprandial period, compared with other carbohydrates (mean difference: 8·02 (95 % CI 0·46, 15·58) mg/dl (0·09 (95 % CI 0·01,
0·18) mmol/l); I
2
: 74 %). High heterogeneity was generated almost exclusively by one study, and its withdrawal did not alter the result. We
concluded that chronic consumption of fructose (>7 d) has a negative role on postprandial TAG in healthy adolescents and adults, as well as in
overweight/obese individuals, but not in diabetics.
Key words: Fructose: Postprandial lipaemia: Sugar: Fat metabolism: Meta-analyses
Postprandial lipaemia (PPL) is a complex and dynamic process
that involves alteration of lipids and lipoproteins after one or
more meals
(1)
. Since 1947, it has been suggested that PPL plays
an atherogenic role
(2)
and, consequently, is related to the
pathogenesis of CVD
(37)
. Exaggerated elevation of TAG in the
postprandial period represents an abnormal response from the
metabolism and is associated with increased morbidity and
mortality
(8,9)
owing to reduced sensitivity to insulin
(10)
and
endothelial dysfunction by increasing oxidative stress
(11)
.
Several diet factors, such as sugar-rich meals, can worsen
postprandial hypertriacylglycerolaemic response
(5,1214)
.Among
these, fructose stands out. Several studies have shown the effect of
fructose-rich diets on postprandial TAG increase
(15,16)
dose-
related for quantities above 50 g/d
(17)
.Themechanismsseemto
be associated with the stimulation of liver lipogenesis
(14,18)
,
reduction of sensitivity to insulin
(18,19)
and secretion or reduction
of VLDL-TAG clearance
(20)
. For this connection with the increase
of atherogenic lipids and lipoproteins, it was suggested that
fructose has an indirect role in increased CVD risk
(8)
.
The effects of fructose consumption on fasting
(17,21,22)
and
postprandial TAG (in acute and chronic forms) have been
previously analysed by some systematic reviews with meta-
analysis
(17,23,24)
. Two of these studies
(21,24)
presented important
conicts of interest declared by investigators arising from
funding by the food industry and showed negative effects only
when it contributes to excess of energy in the diet. Therefore,
the aim of this study was to re-examine the chronic effect (>7d)
fructose consumption has on TAG during postprandial period,
in adolescents and adults.
Methods
The entire process used in this study was elaborated in accor-
dance with the guidelines presented in Preferred Reporting
Items for Systematic Reviews and Meta-Analyses
(25,26)
. This
review was registered at http://www.crd.york.ac.uk/prospero
as CRD42017059987.
Eligibility criteria
The review considered studies in humans, such as clinical trials
(parallel or cross-over designs) that evaluated the effect of
fructose consumption (dissolved in liquid or added to some
food and preparation) over a period of >7 d. The intervention
should be compared with any other carbohydrate that does not
contain fructose in the chemical composition, and there is no
requirement for energy balance between the comparisons.
Research was not limited by illnesses or exercise. The effect of
fructose consumption on the postprandial TAG concentration
*Corresponding author: R. C. O. Macedo, email nutricionistarodrigomacedo@gmail.com
British Journal of Nutrition, page 1 of 9 doi:10.1017/S0007114518001538
© The Authors 2018
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was evaluated by comparing it with another carbohydrate
(fructose-free) in hyperenergetic or isoenergetic conditions. Stu-
dies evaluating acute intervention were discarded. In cases of
studies with several publications, only one was included.
Research strategy
ThesearchwascarriedoutinMarch2017anduseddifferent
electronic databases such as Medline
®
(Pubmed
®
), Embase
®
and
Cochrane, and manual from the references of studies included.
Theresearchwascomposedofandassociatedwiththefollowing
terms (and their respective related terms): fructose,triglycerides,
hyperlipidemia.Toexpandtheresearch,therewasnodelimita-
tion of type or year of the study. Studies were limited to English,
Portuguese and Spanish languages. Research strategy is detailed
and available as online Supplementary Material.
Selection of studies
Two investigators (A. F. V. and C. E. J. M.) assessed titles and
abstracts independently from all studies found during the
research. Whenever the abstract did not provide sufcient
information about inclusion and exclusion criteria, the full
article was evaluated. Thereafter, the full study was evaluated
and selected by the reviewers independently. The selection of
studies was based on previously adopted eligibility criteria.
Disagreements were settled by consensus, and in the case of
continuing disagreement the evaluation was made by a third
investigator (R. C. O. M.). Sampling duplication criteria was
controlled by screening the period and place of recruitment,
and authors were contacted for clarication when necessary.
Data extraction
Standardised form using the software Microsoft Ofce Excel
®
was adopted for proper data extraction, executed indepen-
dently by two reviewers (A. F. V. and C. E. J. M.). The main
features of the studies selected, such as author, year of
publication, population and sample, methods, intervention,
outcome and results, were written in detail. Eventual
disagreements were settled by consensus by a third investigator
(R. C. O. M.). Missing data were requested to the corresponding
author of the study. In case of no answer, denying provision or
data loss, the study was excluded. For data that were presented
only graphically, the results were extracted using DigitizeIt
®
software (I. Bormann). The studies in which the comparison
was not made with carbohydrates and/or acute intervention
(<7 d), as well as those using intravenous carbohydrate infu-
sion, were excluded.
The outcome was the absolute delta of TAG concentration in
a 4-h postprandial period. The deltas were calculated from peak
values (4 h) and basal values (immediately before breakfast) for
properly representing the postprandial TAG curve
(6,2729)
.
Values in mmol/l were transformed to mg/dl, multiplying
by 88·5. Standard δdeviation was imputed by the equation
proposed by Higgins & Green
(31)
.
Studies with two or more comparison or intervention groups
within the same sample were included only once. When the
study presented more than one comparison component
(another carbohydrate) for the intervention (fructose),
the data were extracted only by the following priority:
starch >glucose.
Evaluation of bias risk
Evaluation of the methodological quality of the studies included
proper randomisation generation, allocation concealment,
blinding participants and/or therapist, blinding the assessors of
outcomes and description of losses and exclusions, as proposed
by Cochrane
(31)
. When these characteristics were described in
the published document, it was considered that criteria were
met and that they were satised and classied as low riskand
otherwise as high risk. The studies that did not describe these
data were classied as unclear risk. Two reviewers (A. F. V.
and C. E. J. M.) carried out quality assessment independently.
Data analysis
The results were presented with mean δdifferences among
treatments with 95 % CI. Mean difference expresses the differ-
ence of the intervention effect, when outcome values are
standardised. The calculations were made based on random-
effect models. Statistic treatment effect heterogeneity between
studies was evaluated by CochranesQtest and I
2
incon-
sistency test, where it was considered that values higher than
50 % indicated high heterogeneity
(32)
. Meta-analysis included
comparison of fructose consumption with any other carbohy-
drate (without fructose in composition) on the variation of
postprandial TAG (expressed by the delta values) immediately
before breakfast (0) and at the 4-h peak. The value of α0·05
was considered statistically signicant.
The following sensitivity analyses were carried out: funding
source, randomisation, energy balance, form of the carbohy-
drate provided, type of comparison (comparator), time of
intervention (follow-up), amount of carbohydrate provided and
length of analysis. The analysis of period >12 h was also per-
formed by the 4-h data extraction, because not all studies
showed the peak values in longer periods. The use of values
other than the delta peak (in this case >12 h) would create a
confounding factor by the use of another way to measure
intervention v. control effect. Subdivision by amounts larger or
smaller than 87 g was based in the 95th percentile of fructose
consumption (p95) by the American population
(33)
. The soft-
ware Review Manager version 5.3 (Cochrane Collaboration)
was used.
Furthermore, the funnel plot of the variable analysed was
carried out to verify the bias of publication. Asymmetry was
tested by the Begg and Egger test, being considered meaningful
when P<0·10. The trim-and-ll test was used to estimate the
publications bias effects in interpreting results. The software
comprehensive meta-analysis version 2.0 was used.
Results
Research results
A total of 3337 studies were identied as eligible in the database
search. After duplicates were removed, there were 2805 studies
2 R. C. O. Macedo et al.
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remaining. Of these, it was determined that 2797 were irrelevant
based on title and/or summary review, and there were eight
studies left. After integral reading, eight studies
(18,3440)
and
twelve interest interventions (Fig. 1) were included.
Description of the studies
The complete description of the studies is included in Table 1.
Of the twelve interventions selected, ve were with healthy
individuals (41·6%)
(35,37,39,40)
, four with diabetics (33·3%)
(34,36)
and three with overweight/obese individuals (25 %)
(3840)
.
A total of 318 participants were included in this meta-analysis,
of whom 148 were men (46·6 %) and 170 were women (53·4 %),
with a mean age of 31 years (variation, 1764 years).
Among the interventions selected, most were carried out in a
cross-over (83·3 %) and randomised (75 %) design, and exclu-
sively in an environment external to the laboratory (41·6 %).
In most interventions, all foods and drinks of the diet were
supplied (75 %). The mean period of intervention was 28 d
(variation, 870 d).
The amount of fructose provided in the studies had a mean of
92·6 g (variation, 50182 g) or 20 % of the total energy of the diet
(variation, 1025 %), mainly provided in a mixed form (solid
and liquid) (58·3 %). Studies containing fructose in the com-
parison components composition, such as sucrose and maize
syrup rich in fructose, were not selected. Thus, 50 % of the
interventions used glucose and 50 % used starch as comparison
components. The amount of fat at breakfast (the main meal
analysed) had a variation of 3040 % (or 10·634·7 g) of the total
energy of the meal.
The participantsdiets were mainly composed of 55 %
carbohydrates, 15 % proteins and 30 % fats (83·3 %). The energy
balance was estimated as neutral (eight interventions) and
positive (two interventions). Two interventions had distinct
periods (positive and neutral), but were not separated because
they have equal amounts of energy and macronutrients
between the intervention and the comparator.
The most common analysis period for the referred variable,
postprandial TAG, was 4 h (41·6 %). This measure was chosen,
primarily, for most studies presenting peak value of this mea-
sure and because it provides a good evaluation of lipaemic
curve and is a simple protocol that can be used for clinical
purpose
(6,2729)
.
Funding source was extracted and detailed from interven-
tions, wherein 41·6 % were detailed, which could generate
conict of interest and alter the outcome of the study
(41,42)
. Data
were extracted as agency or agency/industry funding.
Risk of bias
Among the studies included, 75 % showed proper randomisa-
tion, 16·6 % reported allocation concealment, 33·3 % had blin-
ded the participants and investigators, 16·6 % had blinded the
assessors to the outcomes and 33·3 % reported description of
sample losses (Fig. 2 and 3).
Postprandial TAG
Compared with other carbohydrates (starch or glucose), fruc-
tose generated higher variation (delta) on the concentration of
TAG in the postprandial period, evaluated in 4 h (mean differ-
ence: 8·02 (95 % CI 0·46, 15·58) mg/dl (0·09 (95 % CI 0·01, 0·18)
mmol/l); I
2
: 74 %). The high heterogeneity found (P<0·0001)
was almost exclusively generated by one study
(39)
. Its exclusion
did not alter the total result of the meta-analysis (Fig. 4). There
was no difference in publication bias analysis (Eggers regres-
sion, P=0·128; online Supplementary Fig. S1).
3337 articles identified through
database search
2805 articles after the removal of
duplicates
2797 exclusions based on the title and/or
summary review
1699 did not study the target population
736 were not clinical trials
299 did not perform the intervention
39 did not evaluate the interest variables
20 did not have the adequate comparator
3 irretrievable reports
1 without translation
8 full-text articles assessed
for eligibility
8 articles included 4 studies with two different
populations
Identification
Selection
Eligibility
Inclusion
12 intervention included in the meta-analysis
Fig. 1. Flow chart of studies included.
Fructose and postprandial TAG 3
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Tab le 1 . Characteristics of included studies
(Mean values and standard deviations)
Age (years)
Control of
Studies Subjects Mean SD Place of intervention Study design consumption* Randomisation
Obese/overweight
Stanhope et al.
(18)
32 (16M, 16W) 53 (SD 10) (M)
54 (SD 5·6) (W)
Ext/Lab Parallel Dietetic (Lab)
Supplementation
(External)
No
Swarbrick et al.
(38)
7 (0M, 7W) 64 7·9 Lab Crossed Dietetic No
Heden et al.
(40)
20 (11M, 9W) 17 (SD 0·5) (M)
17 (SD 0·6) (W)
Ext Crossed Dietetic Yes
Healthy
Bantle et al.
(35)
12W 29 (SD 7·3) (<40 years)
51 (SD 4·9) (>40 years)
Ext Crossed Dietetic Yes
Bantle et al.
(35)
12H 31 (SD 7·3) (<40 years)
54 (SD 9·8) (>40 years)
Ext Crossed Dietetic Yes
Stanhope et al.
(39)
32 (18M, 14W) 27 7·0 Ext/Lab Parallel Dietetic (Lab)
Supplementation
(External)
No
Swanson et al.
(37)
14 (7H, 7M) 34 1960 Ext Crossed Dietetic Yes
Heden et al.
(40)
20 (9M, 11W) 18 (SD 0·6) (M)
18 (SD 0·4) (W)
Ext Crossed Supplementation Yes
Diabetics
Bantle et al.
(34)
12 DM1 (6H, 6M) 23 1532 Lab Crossed Dietetic Yes
Bantle et al.
(34)
12 DM2 (5H, 7M) 62 3680 Lab Crossed Dietetic Yes
Bantle et al.
(36)
6 DM1 (3M, 3W) 23 1834 Ext/Lab Crossed Dietetic Yes
Bantle et al.
(36)
12 DM2 (4M, 8W) 62 4072 Ext/Lab Crossed Dietetic Yes
Dose of fructose§
Form of Comparison Intervention Energetic Analysis
g % consumption|| component¶ period (d) Diet** balance†† period (h) Financial support
Obese/overweight
Stanhope et al.
(18)
~182 25 Liquid Glucose 70 55:15:30 Neutral/positive 24 Agency
Swarbrick et al.
(38)
~125 25 Liquid Starch 70 55:15:30 Neutral 14 Agency
Heden et al.
(40)
50 10 Liquid Glucose 15 50:16:34 Positive 12 Agency
Healthy
Bantle et al.
(35)
70 14 Mixed Glucose 42 55:15:30 Neutral 24 Agency
Bantle et al.
(35)
70 14 Mixed Glucose 42 55:15:30 Neutral 24 Agency
Stanhope et al.
(39)
~145 25 Liquid Glucose 15 55:15:30 Neutral/positive 24 Agency
Swanson et al.
(37)
100 20 Mixed Starch 28 55:15:30 Neutral 4 Agency/industr y
Heden et al.
(40)
50 10 Liquid Glucose 15 50:16:34 Positive 12 Agency
Diabetics
Bantle et al.
(35)
85·25 21 Mixed Starch 8 55:15:30 Neutral 4 Agency/industry
Bantle et al.
(35)
85·25 21 Mixed Starch 8 55:15:30 Neutral 4 Agency/industry
Bantle et al.
(36)
100 20 Mixed Starch 28 55:15:30 Neutral 4 Agency/industr y
Bantle et al.
(36)
100 20 Mixed Starch 28 55:15:30 Neutral 4 Agency/industr y
M, men; W, women; Ext, external to the laboratory; Lab, laboratory; DM1, type 1 diabetes; DM2, type 2 diabetes.
* Consumption control: dietetic, when all foods, beverages and supplements were provided. Supplementation, when only the intervention carbohydrate was provided by the investigator.
Two studies presented periods in laboratory (neutral energy balance) and external environment (positive energy balance); however, there was no energy intake difference between the protocols (fructose v. glucose) of the study (isoenergetic).
Two studies characterised participants according to age, amount of fat or BMI. The outcome was analysed with all included, but the group or subgroups total mean age was not disclosed.
§ The amount of carbohydrates administered in g/d and total diet energy percentage (%). When preceded by ~, it represents the mean amount estimated reported indirectly by the study. In cases where data were unavailable, the value was calculated from 25% of the
total of a diet of 8368kJ (2000 kcal).
|| Fructose could be supplied in liquid form (in the form of sweetened drink) or mixed (from solid foods and sweetened drinks).
¶ Comparison component refers to another carbohydrate (control) provided with the intervention (fructose), regardless of whether or not it is hyperenergetic.
** Macronutrientsenergy values for carbohydrates: proteins: fats informed in the study.
†† Represents the ratio between participantsenergy consumption and output. Positive when there was energy surplus. Neutral when both were considered equivalent.
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The analysis of subgroups showed higher variation of
TAG concentration for overweight/obese individuals (mean
difference: 11·47 (95 % CI 4·51, 18·44) mg/dl (0·13 (95 % CI
0·05, 0·21) mmol/l); I
2
: 0 %) and healthy individuals (mean
difference: 13·55 (95 % CI 1·60, 25·49) mg/dl (0·15 (95 % CI
0·02, 0·29) mmol/l); I
2
: 76%) but not in diabetics (mean differ-
ence: 2·77 (95 % CI 10·54, 4·99) mg/dl (0·03 (95 % CI 0·12,
0·06) mmol/l); I
2
: 0 %). High heterogeneity in healthy indivi-
duals (P=0·002) was exclusively generated by one study
(39)
. Its
withdrawal did not alter the result of the subgroup.
Owing to the high heterogeneity, sensitivity analyses were
carried out in the interventions for the following: (a) funding,
industry/agency (mean difference: 2·63 (95 % CI 9·86, 4·60)
mg/dl (0·03 (95 % CI 0·11, 0·05) mmol/l); P=0·48; I
2
:0%)
and agency (mean difference: 15·20 (95 % CI 7·40, 23·00) mg/dl
(0·17 (95 % CI 0·08, 0·26) mmol/l); P=0·0001; I
2
: 65 %) (online
Supplementary Fig. S2); (b) amount of carbohydrate, <87 g
(mean difference: 6·97 (95 % CI 2·14, 11·80) mg/dl (0·08 (95 %
CI 0·02, 0·13) mmol/l); P=0·005; I
2
: 0 %) and >87 g (mean
difference: 7·55 (95 % CI 6·40, 21·49) mg/dl (0·09 (95 % CI
0·07, 0·24) mmol/l); P=0·29; I
2
: 81 %) (subdivision by
amounts larger or smaller than 87 g was based in the
p95 fructose consumption by the American population)
(33)
(online Supplementary Fig. S3); (c) randomisation, yes (mean
difference: 3·93 (95 % CI 1·42, 9·29) mg/dl (0·04 (95 % CI
0·02, 0·10) mmol/l); P=0·26; I
2
: 21 %) and no (mean differ-
ence: 22·8(95%CI17·96, 27·64) mg/dl (0·26 (95 % CI 0·20, 0·31)
mmol/l); P<0·00001; I
2
: 0 %) (online Supplementary Fig. S4); (d)
energy balance, positive (mean difference: 14·78 (95 % CI 3·94,
25·62) mg/dl (0·17 (95 % CI 0·04, 0·29) mmol/l); P=0·008;
I
2
:82%)andneutral(meandifference:3·11 (95 % CI 4·80, 11·01)
mg/dl (0·04 (95 % CI 0·05, 0·12) mmol/l); P=0·44; I
2
:36%)
(online Supplementary Fig. S5); (e) form of fructose, liquid
(mean difference: 14·78 (95 % CI 5·94, 23·62) mg/dl (0·17 (95 %
CI 0·07, 0·27) mmol/l); P=0·001; I
2
: 76 %) and mixed (mean
difference: 0·42 (95 % CI 7·58, 6·75) mg/dl (0·00 (95 % CI
0·09, 0·08) mmol/l); P=0·91; I
2
: 6 %) (online Supplementary
Fig. S6); (f) type of comparison (comparator), starch (mean dif-
ference: 1·19 (95 % CI 7·73, 9·51) mg/dl (0·01 (95 % CI 0·09,
0·11) mmol/l); P=0·78; I
2
: 40 %) and glucose (mean difference:
15·33 (95 % CI 6·02, 24·64) mg/dl (0·17 (95 % CI 0·07, 0·28) mmol/l);
P=0·001; I
2
: 70 %) (online Supplementary Fig. S7); (g) follow-
up, <30 d (mean difference: 4·92 (95 % CI 4·41, 14·25) mg/dl
(0·06 (95 % CI 0·05, 0·16) mmol/l); P=0·30; I
2
: 83 % and >30 d
(mean difference: 16·85 (95 % CI 6·35, 27·34) mg/dl (0·19 (95 %
CI 0·07, 0·31) mmol/l); P=0·002; I
2
: 0 %) (online Supplementary
Fig. S8); (h) length of analysis, 4 h (mean difference: 2·63 (95 %
CI 9·86, 4·60) mg/dl (0·03 (95 % CI 0·11, 0·05) mmol/l);
P=0·48; I
2
: 0 %) and >12 h (mean difference: 15·20 (95 % CI
7·40, 23·00) mg/dl (0·17 (95 % CI 0·08, 0·26) mmol/l);
P=0·0001; I
2
: 65 %) (online Supplementary Fig. S9).
Apparently, authors or studies that received funding support
from the industry had a tendency to show no increase in
TAG concentration after fructose consumption. Non-randomised
Random sequence generation (selection bias)
Allocation concealment (selection bias)
Blinding of participants and personnel (performance bias)
Blinding of outcome assessment (detection bias)
Incomplete outcome data (attrition bias)
0 % 25 % 50 % 75 % 100 %
Fig. 2. Risk of bias of the studies included (percentage). , Low risk of bias; , unclear risk of bias; , high risk of bias.
Bantle et al., 1986a DM1 +–
+–
+–
+–
+–
+–
+++
+–
+
++++
++++
++
+
+–
Random sequence generation (selection bias)
Allocation concealment (selection bias)
Blinding of participatns and personnel (performance bias)
Blinding of outcome assessment (detection bias)
Incomplete outcome data (attrition bias)
Bantle et al., 1992a DM1
Bantle et al., 2000a Females
Heden et al., 2014a Obese
Heden et al., 2014b Lean
Stanhope et al., 2009
Stanhope et al., 2011
Swanson et al., 1992
Swarbrick et al., 2008
Bantle et al., 1986b DM2
Bantle et al., 1992b DM2
Bantle et al., 2000b Males
Fig. 3. Summary of risk of bias of the studies included. DM1, type 1 diabetes;
DM2, type 2 diabetes.
Fructose and postprandial TAG 5
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interventions, positive energy balance, liquid fructose, glucose
comparison component, total period of intervention >30 d (follow-
up) and length of analysis >12 h inuenced the results of the study.
Discussion
The main nding of this systematic review with meta-analysis is
that chronic fructose consumption (>7 d) causes higher variation
of TAG concentration in the postprandial period when compared
with other carbohydrates (glucose or starch). This variation (delta)
from fasting (immediately before breakfast) to 4-h peak TAG was
about 8·02 mg/dl (0·09 mmol/l). This effect occurred in healthy
and overweight/obese individuals, but not in diabetics.
Fructose is absorbed in the nal portion of the duodenum
and ileum, in the small intestine, from non-dependent Na pro-
cess. From portal circulation, the monosaccharide is transported
to the liver, where it can be converted to glucose, lactate, gly-
cogen, glycerol and fatty acids
(4345)
, regardless of insulin
secretion
(39)
. In healthy individuals, fructose is oxidised at
approximately 45 %, within a period from 3 to 6 h after inges-
tion, including the entry of carbons in the lipogenesis path-
way
(43)
. The postprandial hyperlipidic effect of fructose seems
to originate directly from the synthesis of fatty acids and gly-
cerol in hepatocytes
(14,20)
, and indirectly by the smaller with-
drawal of TAG from the plasma by reduction in the activation of
lipoprotein lipase from the adipose tissue
(20)
.
Different studies showed that fructose-rich diets induce
alterations in the lipid metabolism in eutrophic and overweight/
obese individuals
(15,18,39,46)
. The addition of fructose (1·03·0g/kg
per d) to the diet increases fasting
(15,47,48)
and postprandial
(16,18,39)
lipaemia. Moreover, it is associated with the reduction of liver
sensitivity to insulin
(49)
, even at moderate doses (40 g/d)
(19)
,and
decrease of fat oxidation
(50)
.
A series of sensitivity analyses was carried out in order
to verify heterogeneity on the results found. One analysis
accentuated the relation between industry funding and null
results of fructose on postprandial TAG. Clearly, the conict of
interests can interfere in the conclusions of a particular
study
(42)
. Currently, the inuence of funding by the food
industry on several health outcomes has been discussed,
as well as how it could modify guidelines of nutrition
(41,51,52)
.
Some systematic reviews with meta-analysis have been
published on the effects of fructose on blood lipids
(17,21,53)
,
glycaemic control on diabetes
(54)
, blood pressure
(55)
, markers
of non-alcoholic liver steatosis
(56)
, weight gain
(57)
, uric acid
(58)
and postprandial TAG
(24)
. These studies also compared fructose
with fructose-containing carbohydrates, including sucrose and
high-fructose maize syrup (HFCS), which are more likely to
show a small or no effect on different metabolic outcomes
(59)
.
Despite the fact that all these studies received funding support
from the food industry (which produces or uses fructose
in products), results remain feasible but must be interpreted
with caution.
Study or subgroup
1.1.1 Obese/overweight
1.1.2 Healthy
1.1.3 Diabetics
Heden et al., 2014a Obese
Bantle et al., 2000a Women
Bantle et al., 1992b DM2
Bantle et al., 1992a DM1
Bantle et al., 1986b DM2
Bantle et al., 1986a DM1
Bantle et al., 2000b Men
Heden et al., 2014b Eutrophic
Heterogeneity: 2=0
.00; 2=1
.27, df = 2 (P=0
.53); I2=0%
Heterogeneity: 2=108.52; 2=16
.53, df = 4 (P=0
.002); I2=76%
Heterogeneity: 2=0
.00; 2=2
.71, df = 3 (P=0
.44); I2=0%
Heterogeneity: 2=106.46; 2=41
.61, df = 11 (P<0
.0001); I2=74%
Test for overall effect: Z= 3.23 (P=0
.001)
Test for overall effect: Z= 2.22 (P=0
.03)
Test for overall effect: Z= 0.70 (P=0
.48)
Test for overall effect: Z= 2.08 (P=0
.04)
Test for subgroup differences: 2=8
.77, df = 2 (P=0
.01), I2=77
.2%
Stanhope et al., 2009
Stanhope et al., 2011
Swanson et al., 1992
Subtotal (95 % CI)
Subtotal (95 % CI)
Subtotal (95 % CI)
Total (95 % CI)
Swarbrick et al., 2008
31.5
37.1
49
74
23.9
39.0
7.3
14.5
7.3
14.5
12
12
6
12
52
65
29.2
50.4
20.2
27.6
20.2
27.6
12
12
6
12
42
10.3
7.9
8.1
7.9
34.242
75.2
16.5
46.6
31.0
41.9
41.9
11.6
8.4
28.5
24.7
49.6
9.0
22.5
32.7
36.4
36.4
12.9
6.8
25.1
12
12
20
16
14
12
12
20
16
14
74 74
4.1
4.1
12.2
13.1
7.1
40.6
61.4
59.3
9.9
57.1
13.3
22.5
34.9
44.3
16.9
48.0
10.6
20
15
7
11.89
.00 0.42, 17.58
26.50 –9.93, 62.93
15.00 2.40, 27.60
11.47 4.51, 18.44
12.40 –19.00, 43.80
25.60 –5.80, 57.00
7.50 –0.10, 15.10
24.10 18.80, 29.40
–1.70 –21.59, 18.19
13.55 1.60, 25.49
–3.00 –15.15, 9.15
9.00 –8.64, 26.64
–5.30 –22.49, 11.89
–11.40 –29.04, 6.24
–2.77 –10.54, 4.99
158 100.0160 8.02 0.46, 15.58
–100 –50 0
Fructose Any CHO
50 100
3.3
10.1
20
44 42 25.2
17
7
Fructose Any CHO Mean difference
Mean SD Total
Weight
(%) IV, random, 95 % CI
Mean difference
IV, random, 95 % CIMean TotalSD
Fig. 4. Forest plot of the effect of fructose or any carbohydrate (CHO) consumption on postprandial TAG in obese/overweight, healthy and diabetic individuals. The
estimation for each group (subtotal) and combined effect (total) are detailed. The data are in mean difference and 95 % CI (mg/dl) of the δbetween fasting and 4-h peak
TAG. Significance values for the random-effect model. Values in mg/dl can be transformed to mmol/l by multiplying by 0·0113. DM, diabetes mellitus.
6 R. C. O. Macedo et al.
https://doi.org/10.1017/S0007114518001538
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The median amount of fructose among the studies selected
was approximately 93 g, which represents approximately
86 % higher than AHA recommendations, but only approxi-
mately 7 % above p95 of the consumption by the American
population
(33)
. This meta-analysis found that quantities smaller
than 87 g of fructose/d are enough to promote variation
in postprandial TAG, as demonstrated in a previous
meta-analysis that observed the threshold of 50 g/d for
the general population
(17)
and 60 g/d for type 2 diabetes
(53)
.
These thresholds are very close to the average consumption (49 g)
by the American
(33)
and Dutch
(60)
population.However,some
authors stated that this effect only occurs when there is positive
energy balance or when fructose is generating a hyperenergetic
conditionincomparisonwithanothercarbohydrate
(21,24)
.This
effect was equally found in our study from sensitivity analysis.
The recent meta-analysis by Evans et al.
(23)
found no differ-
ence in postprandial TAG with acute fructose consumption
when compared with glucose or sucrose. Furthermore, the
authors also propose replacing those sugars for fructose, once
they did not nd TAG alterations, and glycaemia and insuli-
naemia reduction were found in the postprandial period. Our
view is contrary, as our sensitivity analysis showed that a total
time of intervention (follow-up) extended for over 30 d inu-
enced TAG variation. Although increasingly studied, the effects
of chronic fructose consumption are still discordant and are not
fully elucidated in the literature because of a number of con-
founding factors (e.g. fructose dose, excess of energy in the
diet, diabetes, obesity)
(61)
.
Some limitations are present in our study. (1) Data showed
high heterogeneity; sensitivity analysis demonstrated that this
effect was being almost exclusively generated by one study
(39)
but its removal does not alter the result of subgroups and total
results of the meta-analysis. (2) The inclusion of a study with
adolescents
(40)
could create a confusion factor, but it was
considered important for representing the metabolic interven-
tion effect on different age groups. (3) One study
(38)
did not
clearly show the amount of fructose provided (in grams or % of
the diet) and, in this case, had to be removed. (4) The amount
of fructose varied to a great extent among studies (50182 g),
showing lack of intervention standardisation and often the
provision of supraphysiological doses
(62)
. (5) All interventions
that evaluated diabetics analysed plasma TAG over a period of
4 h, which may represent a bias; studies with longer analysis
periods especially in diabetic subjects are needed. (6) The
quality of studies varied between groups, presenting higher risk
of bias in diabetes interventions.
Findings from this systematic review with meta-analysis
update the results previously described by Wang et al.
(24)
and
showed the negative effects of chronic (>7 d) fructose con-
sumption on postprandial TAG, in healthy adolescents and
adults, as well as in overweight/obese individuals, but not in
diabetics. As chronic ingestion of fructose may promote lipae-
mic alterations, and hypertriacylglycerolaemia in the post-
prandial period is associated with increased morbimortality,
recommendations for the population are needed to limit
intake, especially from liquids (e.g. sweetened beverages).
Longitudinal studies (>30 d), well-controlled, with habitual
doses of consumption between 49 and 87 g (close to the p95 of
the population) and in different forms (free fructose, HFCS,
sucrose) are necessary to clarify the interrelationship between
fructose, lipaemia and CVD.
Acknowledgements
The authors thank authors Timothy Daniel Heden, Jill Kanaley
and John Sievenpiper for responding our emails and Josianne
Krause and Daniel Umpierre for aiding with data analysis.
C. E. J. M. has received PhD scholarship from the Coorde-
nação de Aperfeiçoamento de Pessoal de Nível Superior.
R. C. O. M. formulated the research question; A. F. V. and
C.E.J.M.readandextracteddata.A.F.V.,C.E.J.M.,R.C.O.M.
analysed the data. R. C.O.M.,A.F.V.,C.E.J.M.andA.R.-O.
wrote, reviewed, performed and perfected this study.
The authors declare that there are no conicts of interest to
declare.
Supplementary material
For supplementary material/s referred to in this article, please
visit https://doi.org/10.1017/S0007114518001538
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Fructose and postprandial TAG 9
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... The results were presented with the standardized mean difference (SMD) and their 95% CI, using a random-effect model. Heterogeneity between studies was assessed via the I 2 value and the p-value obtained from the Q-test, where values above 50% were defined as substantially heterogenous [13]. Results were considered statistically significant when p < 0.05. ...
... Sensitivity analysis suggested the impact of some of the individual studies on two variables, although the SMD results remained nearly similar after their omission. For the EGI, the selected studies from Ren et al. [13] and Péronnet et al. [14] were withdrawn, and the heterogeneity dropped considerably. This may be explained by the lowest levels of EGI and GP for the two studies. ...
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Citation: Wang, Y.; Zhou, X.; Xiang, X.; Miao, M. Association of Slowly Digestible Starch Intake with Reduction of Postprandial Glycemic Response: An Update Meta-Analysis. Foods 2023, 12, 89. https://doi. Abstract: Slowly digestible starch (SDS) has been shown to digest slowly throughout the entire small intestine, generating slow and prolonged release of glucose, according to the in vitro Englyst assay. The aim of this work was to conduct a meta-analysis of up-to-date evidence to evaluate the association between SDS consumption and a reduction in the postprandial glycemic response, including extended glycemic index (EGI) or glycemic profile (GP) parameters, during in vivo digestion. We searched the Web of Science, PubMed, Europe PMC, Cochrane Library, and Embase to identify related articles published up to September 2022. Human trials investigating the effect of the SDS amount on the postprandial glucose profile were estimated at the standard mean difference (SMD), with a 95% confidence interval (CI), using random effect models. The review followed the systematic reviews and meta-analyses (PRISMA) guidelines. The meta-analysis included a total of 65 participants. The results revealed that the EGI experienced a greater increase (SMD = 24.61, I2 = 79.2%, p < 0.01) after SDS intake, while the GP exhibited similar trends (SMD = 29.18, I2 = 73.3%, p < 0.01). High heterogeneity vanished in the subgroup and sensitivity analysis (EGI: I2 = 14.6%, p = 0.31; GP: I2 = 0.0%, p = 0.97). There was no evidence of publication bias for EGI (p = 0.41) or GP (p = 0.99).The present meta-analysis provides evidence that SDS intake is positively correlated with EGI and GP levels. The quantitative relationship of the reduction in the postprandial glycemic response and SDS consumption was used to quantify the slow digestion property on an extended time scale, and supplement the in vitro concept of SDS.
Article
Background and aims The aim of this study was to evaluate the glycemic parameters, lipid profiles, uric acid levels, and triglyceride-glucose (TyG) index of individuals who consume different amounts of fructose. Additionally, the relationship between the TyG index and the homeostatic model assessment for insulin resistance (HOMA-IR) values was investigated. Methods This cross-sectional study was conducted on healthy adults aged between 18 and 55 who applied to a university hospital in Istanbul, Turkey. Demographic characteristics and food consumption were recorded using the face-to-face interview method. Participants were divided into two groups according to their fructose consumption (≤50 g/day: moderate; >50 g/day: high). The glycemic parameters, lipid profiles, and uric acid levels were measured and TyG index was calculated. Results Fructose consumption of >50 g/day was reported by 25% of the participants. There was no relationship between lipid profile, uric acid, and fructose consumption. The fasting blood glucose (FBG), fasting insulin, HOMA-IR, and TyG index values in the moderate fructose consumption group were significantly lower than those for the high fructose consumption group (P < 0.05). The TyG index was associated with fructose consumption and HOMA-IR (P < 0.05). High fructose consumers exhibited FBG and HOMA-IR levels 1.18 (95% confidence interval [95% CI] = 1.01-1.37) and 1.42 (95% CI = 1.09-1.84) times higher than those for the moderate fructose consumers (P < 0.05). Conclusions The results of this study confirmed that high fructose consumption negatively affects glycemic status in healthy adults. Additionally, this study revealed that there is a significant association between daily fructose consumption and TyG index.
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Background: The excessive consumption of free sugars, including fructose, is considered a cause of overweight and metabolic syndrome throughout the Western world. In Germany, the prevalence of overweight and obesity among adults (54%, 18%) and children (15%, 6%) has risen in the past few decades and has now become stable at a high level. The causative role of fructose is unclear. Methods: This review is based on publications retrieved by a selective search in PubMed and the Cochrane Library, with special attention to international guidelines and expert recommendations. Results: The hepatic metabolism of fructose is insulin-independent; because of the lack of a feedback mechanism, it leads to substrate accumulation, with de novo lipogenesis and gluconeogenesis. Recent meta-analyses with observation periods of one to ten weeks have shown that the consumption of fructose in large amounts leads to weight gain (+ 0.5 kg [0.26; 0.79]), elevated triglyceride levels (+ 0.3 mmol/L [0.11; 0.41]), and steatosis hepatis (intrahepatocellular fat content: + 54% [29; 79%]) when it is associated with a positive energy balance (fructose dose + 25-40% of the total caloric requirement). Meta-analyses in the isocaloric setting have not shown any comparable effects. Children, with their preference for sweet foods and drinks, are prone to excessive sugar consumption. Toddlers under age two are especially vulnerable. Conclusion: The effects that have been observed with the consumption of large amounts of fructose cannot be reliably distinguished from the effects of a generally excessive caloric intake. Further randomized and controlled intervention trials of high quality are needed in order to determine the metabolic effects of fructose consumed under isocaloric conditions. To lessen individual consumption of sugar, sugary dietary items such as sweetened soft drinks, fruit juice, and smoothies should be avoided in favor of water as a beverage and fresh fruit.
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High-fructose syrups are used as sugar substitutes due to their physical and functional properties. High fructose corn syrup (HFCS) is used in bakery products, dairy products, breakfast cereals and beverages, but it has been reported that there might be a direct relationship between high fructose intake and adverse health effects such as obesity and the metabolic syndrome. Thus, fructose has recently received much attention, most of which was negative. Although studies have indicated that there might be a correlation between high fructose-rich diet and several adverse effects, however, the results of these studies cannot be certainly generalised to the effects of HFCS; because they have investigated pure fructose at very high concentrations in measurement of metabolic upsets. This review critically considered the advantages and possible disadvantages of HFCS application and consumption in food industry, as a current challenging issue between nutritionists and food technologists.
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Purpose of review: To review recent evidence for the role of carbohydrates in the promotion of de novo lipogenesis and lipoprotein secretion from the intestine. Recent findings: The consumption of diets rich in carbohydrates have been shown to promote elevations in circulating lipids. In particular, the consumption of monosaccharides, such as glucose and fructose, have been shown to induce increases in intestinal de novo lipogenesis, as well as be used as a substrate for the synthesis of triglycerides and lipoprotein export in the form of chylomicrons. Recently, various systematic reviews have analyzed the relative contribution of dietary fructose to intestinal lipogenesis. Although, there remains controversy within the literature, the body of evidence supports lipogenic effects of high fructose diets. In addition, alterations in markers of de novo lipogenesis within the jejunum of patients with insulin resistance may explain the alterations in their postprandial lipid profile. Summary: Recent evidence supports the contribution of dietary carbohydrates to intestinal lipogenesis and lipoprotein secretion; however, further research is required to fully understand the mechanisms underlying this complex process.
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: Protocols of systematic reviews and meta-analyses allow for planning and documentation of review methods, act as a guard against arbitrary decision making during review conduct, enable readers to assess for the presence of selective reporting against completed reviews, and, when made publicly available, reduce duplication of efforts and potentially prompt collaboration. Evidence documenting the existence of selective reporting and excessive duplication of reviews on the same or similar topics is accumulating and many calls have been made in support of the documentation and public availability of review protocols. Several efforts have emerged in recent years to rectify these problems, including development of an international register for prospective reviews (PROSPERO) and launch of the first open access journal dedicated to the exclusive publication of systematic review products, including protocols (BioMed Central's Systematic Reviews). Furthering these efforts and building on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines, an international group of experts has created a guideline to improve the transparency, accuracy, completeness, and frequency of documented systematic review and meta-analysis protocols--PRISMA-P (for protocols) 2015. The PRISMA-P checklist contains 17 items considered to be essential and minimum components of a systematic review or meta-analysis protocol.This PRISMA-P 2015 Explanation and Elaboration paper provides readers with a full understanding of and evidence about the necessity of each item as well as a model example from an existing published protocol. This paper should be read together with the PRISMA-P 2015 statement. Systematic review authors and assessors are strongly encouraged to make use of PRISMA-P when drafting and appraising review protocols.
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Background: Conflicting evidence exists on the effects of fructose consumption in people with type 1 and type 2 diabetes mellitus. No systematic review has addressed the effect of isoenergetic fructose replacement of glucose or sucrose on peak postprandial glucose, insulin, and triglyceride concentrations. Objective: The objective of this study was to review the evidence for postprandial glycemic and insulinemic responses after isoenergetic replacement of either glucose or sucrose in foods or beverages with fructose. Design: We searched the Cochrane Library, MEDLINE, EMBASE, the WHO International Clinical Trials Registry Platform Search Portal, and clinicaltrials.gov. The date of the last search was 26 April 2016. We included randomized controlled trials measuring peak postprandial glycemia after isoenergetic replacement of glucose, sucrose, or both with fructose in healthy adults or children with or without diabetes. The main outcomes analyzed were peak postprandial blood glucose, insulin, and triglyceride concentrations. Results: Replacement of either glucose or sucrose by fructose resulted in significantly lowered peak postprandial blood glucose, particularly in people with prediabetes and type 1 and type 2 diabetes. Similar results were obtained for insulin. Peak postprandial blood triglyceride concentrations did not significantly increase. Conclusions: Strong evidence exists that substituting fructose for glucose or sucrose in food or beverages lowers peak postprandial blood glucose and insulin concentrations. Isoenergetic replacement does not result in a substantial increase in blood triglyceride concentrations.
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Background: Conflicting evidence exists on the role of long-term fructose consumption on health. No systematic review has addressed the effect of isoenergetic fructose replacement of other sugars and its effect on glycated hemoglobin (HbA1c), fasting blood glucose, insulin, and triglycerides. Objective: The objective of this study was to review the evidence for a reduction in fasting glycemic and insulinemic markers after chronic, isoenergetic replacement of glucose or sucrose in foods or beverages by fructose. The target populations were persons without diabetes, those with impaired glucose tolerance, and those with type 2 diabetes. Design: We searched the Cochrane Library, MEDLINE, EMBASE, the WHO International Clinical Trials Registry Platform Search Portal, and clinicaltrials.gov. The date of the last search was 26 April 2016. We included randomized controlled trials of isoenergetic replacement of glucose, sucrose, or both by fructose in adults or children with or without diabetes of ≥2 wk duration that measured fasting blood glucose. The main outcomes analyzed were fasting blood glucose and insulin as well as fasting triglycerides, blood lipoproteins, HbA1c, and body weight. Results: We included 14 comparison arms from 11 trials, including 277 patients. The studies varied in length from 2 to 10 wk (mean: 28 d) and included doses of fructose between 40 and 150 g/d (mean: 68 g/d). Fructose substitution in some subgroups resulted in significantly but only slightly lowered fasting blood glucose (-0.14 mmol/L; 95% CI: -0.24, -0.036 mmol/L), HbA1c [-10 g/L (95% CI: -12.90, -7.10 g/L; impaired glucose tolerance) and -6 g/L (95% CI: -8.47, -3.53 g/L; normoglycemia)], triglycerides (-0.08 mmol/L; 95% CI: -0.14, -0.02 mmol/L), and body weight (-1.40 kg; 95% CI: -2.07, -0.74 kg). There was no effect on fasting blood insulin or blood lipids. Conclusions: The evidence suggests that the substitution of fructose for glucose or sucrose in food or beverages may be of benefit to individuals, particularly those with impaired glucose tolerance or type 2 diabetes. However, additional high-quality studies in these populations are required.
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Background: Conflicting evidence exists on the role of long-term fructose consumption on health. No systematic review has addressed the effect of isoenergetic fructose replacement of other sugars and its effect on glycated hemoglobin (HbA1c), fasting blood glucose, insulin, and triglycerides. Objective: The objective of this study was to review the evidence for a reduction in fasting glycemic and insulinemic markers after chronic, isoenergetic replacement of glucose or sucrose in foods or beverages by fructose. The target populations were persons without diabetes, those with impaired glucose tolerance, and those with type 2 diabetes. Design: We searched the Cochrane Library, MEDLINE, EMBASE, the WHO International Clinical Trials Registry Platform Search Portal, and clinicaltrials.gov. The date of the last search was 26 April 2016. We included randomized controlled trials of isoenergetic replacement of glucose, sucrose, or both by fructose in adults or children with or without diabetes of ≥2 wk duration that measured fasting blood glucose. The main outcomes analyzed were fasting blood glucose and insulin as well as fasting triglycerides, blood lipoproteins, HbA1c, and body weight. Results: We included 14 comparison arms from 11 trials, including 277 patients. The studies varied in length from 2 to 10 wk (mean: 28 d) and included doses of fructose between 40 and 150 g/d (mean: 68 g/d). Fructose substitution in some subgroups resulted in significantly but only slightly lowered fasting blood glucose (−0.14 mmol/L; 95% CI: −0.24, −0.036 mmol/L), HbA1c [−10 g/L (95% CI: −12.90, −7.10 g/L; impaired glucose tolerance) and −6 g/L (95% CI: −8.47, −3.53 g/L; normoglycemia)], triglycerides (−0.08 mmol/L; 95% CI: −0.14, −0.02 mmol/L), and body weight (−1.40 kg; 95% CI: −2.07, −0.74 kg). There was no effect on fasting blood insulin or blood lipids. Conclusions: The evidence suggests that the substitution of fructose for glucose or sucrose in food or beverages may be of benefit to individuals, particularly those with impaired glucose tolerance or type 2 diabetes. However, additional high-quality studies in these populations are required.
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Background: Conflicting evidence exists on the effects of fructose consumption in people with type 1 and type 2 diabetes mellitus. No systematic review has addressed the effect of isoenergetic fructose replacement of glucose or sucrose on peak postprandial glucose, insulin, and triglyceride concentrations. Objective: The objective of this study was to review the evidence for postprandial glycemic and insulinemic responses after isoenergetic replacement of either glucose or sucrose in foods or beverages with fructose. Design: We searched the Cochrane Library, MEDLINE, EMBASE, the WHO International Clinical Trials Registry Platform Search Portal, and clinicaltrials.gov. The date of the last search was 26 April 2016. We included randomized controlled trials measuring peak postprandial glycemia after isoenergetic replacement of glucose, sucrose, or both with fructose in healthy adults or children with or without diabetes. The main outcomes analyzed were peak postprandial blood glucose, insulin, and triglyceride concentrations. Results: Replacement of either glucose or sucrose by fructose resulted in significantly lowered peak postprandial blood glucose, particularly in people with prediabetes and type 1 and type 2 diabetes. Similar results were obtained for insulin. Peak postprandial blood triglyceride concentrations did not significantly increase. Conclusions: Strong evidence exists that substituting fructose for glucose or sucrose in food or beverages lowers peak postprandial blood glucose and insulin concentrations. Isoenergetic replacement does not result in a substantial increase in blood triglyceride concentrations.
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Across medical and scientific research, few areas are as relevant to health as food and nutrition. Suboptimal diet is associated with more deaths and disability worldwide than any other modifiable factor; in the United States alone, poor diet is linked to almost 1000 cardiovascular and diabetes deaths per day.¹ The direct and indirect costs of diet-related chronic diseases are astonishing and in the United States are estimated to be as much as $1 trillion annually.
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Background: Clinical research affecting how doctors practice medicine is increasingly sponsored by companies that make drugs and medical devices. Previous systematic reviews have found that pharmaceutical-industry sponsored studies are more often favorable to the sponsor's product compared with studies with other sources of sponsorship. A similar association between sponsorship and outcomes have been found for device studies, but the body of evidence is not as strong as for sponsorship of drug studies. This review is an update of a previous Cochrane review and includes empirical studies on the association between sponsorship and research outcome. Objectives: To investigate whether industry sponsored drug and device studies have more favorable outcomes and differ in risk of bias, compared with studies having other sources of sponsorship. Search methods: In this update we searched MEDLINE (2010 to February 2015), Embase (2010 to February 2015), the Cochrane Methodology Register (2015, Issue 2) and Web of Science (June 2015). In addition, we searched reference lists of included papers, previous systematic reviews and author files. Selection criteria: Cross-sectional studies, cohort studies, systematic reviews and meta-analyses that quantitatively compared primary research studies of drugs or medical devices sponsored by industry with studies with other sources of sponsorship. We had no language restrictions. Data collection and analysis: Two assessors screened abstracts and identified and included relevant papers. Two assessors extracted data, and we contacted authors of included papers for additional unpublished data. Outcomes included favorable results, favorable conclusions, effect size, risk of bias and whether the conclusions agreed with the study results. Two assessors assessed risk of bias of included papers. We calculated pooled risk ratios (RR) for dichotomous data (with 95% confidence intervals (CIs)). Main results: Twenty-seven new papers were included in this update and in total the review contains 75 included papers. Industry sponsored studies more often had favorable efficacy results, RR: 1.27 (95% CI: 1.17 to 1.37) (25 papers) (moderate quality evidence), similar harms results RR: 1.37 (95% CI: 0.64 to 2.93) (four papers) (very low quality evidence) and more often favorable conclusions RR: 1.34 (95% CI: 1.19 to 1.51) (29 papers) (low quality evidence) compared with non-industry sponsored studies. Nineteen papers reported on sponsorship and efficacy effect size, but could not be pooled due to differences in their reporting of data and the results were heterogeneous. We did not find a difference between drug and device studies in the association between sponsorship and conclusions (test for interaction, P = 0.98) (four papers). Comparing industry and non-industry sponsored studies, we did not find a difference in risk of bias from sequence generation, allocation concealment, follow-up and selective outcome reporting. However, industry sponsored studies more often had low risk of bias from blinding, RR: 1.25 (95% CI: 1.05 to 1.50) (13 papers), compared with non-industry sponsored studies. In industry sponsored studies, there was less agreement between the results and the conclusions than in non-industry sponsored studies, RR: 0.83 (95% CI: 0.70 to 0.98) (six papers). Authors' conclusions: Sponsorship of drug and device studies by the manufacturing company leads to more favorable efficacy results and conclusions than sponsorship by other sources. Our analyses suggest the existence of an industry bias that cannot be explained by standard 'Risk of bias' assessments.
Article
Background: High fructose consumption has been suggested to contribute to several features of metabolic syndrome including insulin resistance, but to our knowledge, no previous meta-analyses have investigated the effect of fructose on insulin sensitivity in nondiabetic subjects. Objective: We performed a systematic review and meta-analysis of controlled diet-intervention studies in nondiabetic subjects to determine the effect of fructose on insulin sensitivity. Design: We searched MEDLINE, EMBASE, and the Cochrane Library for relevant trials on the basis of predetermined eligibility criteria. Two investigators independently performed the study selection, quality assessment, and data extraction. Results were pooled with the use of the generic inverse-variance method with random effects weighting and were expressed as mean differences (MDs) or standardized mean differences (SMDs) with 95% CIs. Results: Twenty-nine articles that described 46 comparisons in 1005 normal-weight and overweight or obese participants met the eligibility criteria. An energy-matched (isocaloric) exchange of dietary carbohydrates by fructose promoted hepatic insulin resistance (SMD: 0.47; 95% CI: 0.03, 0.91; P = 0.04) but had no effect on fasting plasma insulin concentrations (MD: −0.79 pmol/L; 95% CI: −6.41, 4.84 pmol/L; P = 0.78), the homeostasis model assessment of insulin resistance (HOMA-IR) (MD: 0.13; 95% CI: −0.07, 0.34; P = 0.21), or glucose disposal rates under euglycemic hyperinsulinemic clamp conditions (SMD: 0.00; 95% CI: 20.41, 0.41; P = 1.00). Hypercaloric fructose (∼25% excess of energy compared with that of the weight-maintenance control diet) raised fasting plasma insulin concentrations (MD: 3.38 pmol/L; 95% CI: 0.03, 6.73 pmol/L; P < 0.05) and induced hepatic insulin resistance (SMD: 0.77; 95% CI: 0.28, 1.26; P < 0.01) without affecting the HOMA-IR (MD: 0.18; 95% CI: −0.02, 0.39; P = 0.08) or glucose disposal rates (SMD: 0.10; 95% CI: −0.21, 0.40; P = 0.54). Results may have been limited by the low quality, small sample size, and short duration (mostly <60 d) of included trials. Conclusions: Short-term fructose consumption, in isocaloric exchange or in hypercaloric supplementation, promotes the development of hepatic insulin resistance in nondiabetic adults without affecting peripheral or muscle insulin sensitivity. Larger and longer-term studies are needed to assess whether real-world fructose consumption has adverse effects on insulin sensitivity and long-term outcomes.
Article
Importance: Food industry sponsorship of nutrition research may bias research reports, systematic reviews, and dietary guidelines. Objective: To determine whether food industry sponsorship is associated with effect sizes, statistical significance of results, and conclusions of nutrition studies with findings that are favorable to the sponsor and, secondarily, to determine whether nutrition studies differ in their methodological quality depending on whether they are industry sponsored. Data sources: OVID MEDLINE, PubMed, Web of Science, and Scopus from inception until October 2015; the reference lists of included reports. Study selection: Reports that evaluated primary research studies or reviews and that quantitatively compared food industry-sponsored studies with those that had no or other sources of sponsorship. Data extraction: Two reviewers independently extracted data from each report and rated its quality using the ratings of the Oxford Centre for Evidence-Based Medicine, ranging from a highest quality rating of 1 to a lowest of 5. Main outcomes and measures: Results (statistical significance and effect size) favorable to the sponsor and conclusions favorable to the sponsor. If data were appropriate for meta-analysis, we used an inverse variance DerSimonian-Laird random-effects model. Results: Of 775 reports reviewed, 12, with quality ratings ranging from 1 to 4, met the inclusion criteria. Two reports, with data that could not be combined, assessed the association of food industry sponsorship and the statistical significance of research results; neither found an association. One report examined effect sizes and found that studies sponsored by the food industry reported significantly smaller harmful effects for the association of soft drink consumption with energy intake and body weight than those not sponsored by the food industry. Eight reports, including 340 studies, assessed the association of industry sponsorship with authors' conclusions. Although industry-sponsored studies were more likely to have favorable conclusions than non-industry-sponsored studies, the difference was not significant (risk ratio, 1.31 [95% CI, 0.99-1.72]). Five reports assessed methodological quality; none found an association with industry sponsorship. Conclusions and relevance: Although industry-sponsored studies were more likely to have conclusions favorable to industry than non-industry-sponsored studies, the difference was not significant. There was also insufficient evidence to assess the quantitative effect of industry sponsorship on the results and quality of nutrition research. These findings suggest but do not establish that industry sponsorship of nutrition studies is associated with conclusions that favor the sponsors, and further investigation of differences in study results and quality is needed.