Abstract and Figures

This systematic review and meta-analysis of randomized controlled trials (RCTs) was performed to summarize the effect of caffeine intake on weight loss. We searched the following databases until November 2017: MEDLINE, EMBASE, Web of Science, and Cochrane Central Register of Controlled Trials. The relevant data were extracted and assessed for quality of the studies according to the Cochrane risk of bias tool. We estimated an intake-status regression coefficient (Beta) for each primary study and estimated the overall pooled Beta and SE using random effects meta-analysis on a double-log scale. Heterogeneity between studies was assessed by the Cochran Q statistic and I-squared tests (I²). Thirteen RCTs with 606 participants were included in the meta-analyses. The overall pooled Beta for the effect of caffeine intake was 0.29 (95%CI: 0.19, 0.40; Q = 124.5, I² = 91.2%) for weigh, 0.23 (95%CI: 0.09, 0.36; Q = 71.0, I² = 93.0%) for BMI, and 0.36 (95% CI: 0.24, 0.48; Q = 167.36, I² = 94.0%) for fat mass. For every doubling in caffeine intake, the mean reduction in weight, BMI, and fat mass increased 2 Beta-fold (20.29 = 1.22, 20.23 = 1.17, and 20.36 = 1.28), which corresponding to 22, 17, and 28 percent, respectively. Overall, the current meta-analysis demonstrated that caffeine intake might promote weight, BMI and body fat reduction.
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Critical Reviews in Food Science and Nutrition
ISSN: 1040-8398 (Print) 1549-7852 (Online) Journal homepage: http://www.tandfonline.com/loi/bfsn20
The effects of caffeine intake on weight loss: a
systematic review and dos-response meta-analysis
of randomized controlled trials
Reza Tabrizi, Parvane Saneei, Kamran B Lankarani, Maryam Akbari, Fariba
Kolahdooz, Ahmad Esmaillzadeh, Somayyeh Nadi-Ravandi, Majid Mazoochi
& Zatollah Asemi
To cite this article: Reza Tabrizi, Parvane Saneei, Kamran B Lankarani, Maryam Akbari, Fariba
Kolahdooz, Ahmad Esmaillzadeh, Somayyeh Nadi-Ravandi, Majid Mazoochi & Zatollah Asemi
(2018): The effects of caffeine intake on weight loss: a systematic review and dos-response meta-
analysis of randomized controlled trials, Critical Reviews in Food Science and Nutrition, DOI:
10.1080/10408398.2018.1507996
To link to this article: https://doi.org/10.1080/10408398.2018.1507996
Published online: 18 Oct 2018.
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REVIEW
The effects of caffeine intake on weight loss: a systematic review and
dos-response meta-analysis of randomized controlled trials
Reza Tabrizi
a
, Parvane Saneei
b
, Kamran B Lankarani
c
, Maryam Akbari
a
, Fariba Kolahdooz
d
, Ahmad
Esmaillzadeh
b,e
, Somayyeh Nadi-Ravandi
f
, Majid Mazoochi
g
, and Zatollah Asemi
h
a
Health Policy Research Center, Institute of Health, Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran;
b
Food
Security Research Center, Department of Community Nutrition School of Nutrition and Food Science, Isfahan University of Medical Sciences,
Isfahan, Iran;
c
Health Policy Research Center, Shiraz University of Medical Sciences, Shiraz, Iran;
d
Indigenous and Global Health Research,
Department of Medicine, University of Alberta, Edmonton, Canada;
e
Department of Community Nutrition School of Nutritional Sciences and
Dietetics, Tehran University of Medical Sciences, Tehran, Iran;
f
Health Information Management Research Center, Kashan University of
Medical Sciences, Kashan, Iran;
g
Department of Cardiology School of Medicine, Kashan University of Medical Sciences, Kashan, Iran;
h
Research Center for Biochemistry and Nutrition in Metabolic Diseases, Kashan University of Medical Sciences, Kashan, Iran
ABSTRACT
This systematic review and meta-analysis of randomized controlled trials (RCTs) was performed to
summarize the effect of caffeine intake on weight loss. We searched the following databases until
November 2017: MEDLINE, EMBASE, Web of Science, and Cochrane Central Register of Controlled
Trials. The relevant data were extracted and assessed for quality of the studies according to the
Cochrane risk of bias tool. We estimated an intake-status regression coefficient (Beta) for each
primary study and estimated the overall pooled Beta and SE using random effects meta-analysis
on a double-log scale. Heterogeneity between studies was assessed by the Cochran Q statistic
and I-squared tests (I
2
). Thirteen RCTs with 606 participants were included in the meta-analyses.
The overall pooled Beta for the effect of caffeine intake was 0.29 (95%CI: 0.19, 0.40; Q ¼124.5,
I
2
¼91.2%) for weigh, 0.23 (95%CI: 0.09, 0.36; Q ¼71.0, I
2
¼93.0%) for BMI, and 0.36 (95% CI: 0.24,
0.48; Q ¼167.36, I
2
¼94.0%) for fat mass. For every doubling in caffeine intake, the mean reduction
in weight, BMI, and fat mass increased 2 Beta-fold (20.29 ¼1.22, 20.23 ¼1.17, and 20.36 ¼1.28),
which corresponding to 22, 17, and 28 percent, respectively. Overall, the current meta-analysis
demonstrated that caffeine intake might promote weight, BMI and body fat reduction.
KEYWORDS
Caffeine; weight loss;
meta-analysis
Introduction
An estimated 64% of American populations are overweight or
obese [body mass index (BMI) 25 kg/m
2
] (Flegal et al. 2002).
Obesityisamajorriskfactorforanumberofmetabolicdis-
eases, including coronary heart diseases (CHD), hypertension,
type 2 diabetes mellitus (T2DM), pulmonary dysfunction, and
non-metabolic such as osteoarthritis, and certain types of can-
cer (Kromhout 1983;Lynchetal.2009). Common treatments
for managing obesity include lifestyle changes such as weight
loss, appropriate diet, and increased physical activity, as well as
the appropriate use of pharmacological agents to reduce the
specific risk factors (Villareal et al. 2011).
Modest weight loss, 510% of the initial body weight,
would result in beneficial health effects (Wing et al.
1992).Caffeine has been widely used as an practical approach
in obesity management (Astrup 2000). Caffeine increases both
noradrenaline and dopamine release, and therefore stimulates
the neuronal activity in several brain regions (Zheng and
Hasegawa 2016),whichinturncandecreaseweighandbody
fat. Caffeine may increase fat oxidation through inhibiting
phosphodiesterase and the suppression of negative effects of
adenosine on increased noradrenaline release (Dulloo,
Seydoux, and Girardier 1992). Despite reported anti-obesity
effects and weight maintenance of caffeine in some clinical
trials (Boozer et al. 2002; Coffey et al. 2004;Molnaretal.
2000; Westerterp-Plantenga, Lejeune, and Kovacs 2005), few
studies did not show any beneficiary effect of caffeine for
body weight and weight maintenance after weight loss (Hursel
and Westerterp-Plantenga 2009; Lee et al. 2005).Therefore, the
effect of caffeine consumption to improve weight loss diet and
reduce percentage of body fat remains controversial.
We are aware of no systematic review and meta-analysis
of RCTs about the effect of caffeine intake on weight loss.
This meta-analysis was performed to summarize the avail-
able evidence of RCTs to investigate the effect of caffeine
intake on weight loss.
Methods
Search strategy and study selection
This meta-analysis was undertaken according to PRISMA
(Preferred Reporting Items for Systematic Reviews and
CONTACT Zatollah Asemi asemi_r@yahoo.com Research Center for Biochemistry and Nutrition in Metabolic Diseases, Kashan University of Medical
Sciences, Kashan, Iran.
Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/bfsn.
ß2018 Taylor & Francis Group, LLC
CRITICAL REVIEWS IN FOOD SCIENCE AND NUTRITION
https://doi.org/10.1080/10408398.2018.1507996
Meta-Analyses) guideline. Two authors were independently
conducted the search, data selection, data extraction, and
evaluation of risk of bias. In the case of a disagreement, it is
resolved by consensus and/or discussion with a third author.
The following online databases were searched for relevant
RCTs studies published through November 2017: Cochrane
Library, EMBASE, MEDLINE, and Web of Science data-
bases. In addition, ongoing trials were searched from data-
bases including the International Standard Randomized
Controlled Trial Number Register and Meta-register for
RCTs. In addition, we did not publish the review protocol.
We conducted searches on gray literature using databases
including institute for scientific and technical information
(INIST) and the healthcare management information con-
sortium (HMIC), also to find other unpublished studies, we
contacted with experts and centers of related field. Trials
retrieved that examined the effect of caffeine intake on
weight, BMI and/or body fat by using the following MeSH
and text words [(caffeine[Mesh] OR coffee[Mesh] OR
caffeine [tiab] OR coffee [tiab]) OR caffeinated beverages
[tiab] AND (body weight[Mesh] OR body mass
index[Mesh] OR body fat[Mesh] OR body weight [tiab]
OR body mass index [tiab] OR body fat [tiab]) AND
(randomized clinical trial [pt] OR controlled clinical trials
[pt] OR randomized [tiab] OR placebo [tiab] OR randomly
[tiab] OR trial [tiab])].
The reference lists of all known related studies, including
original research papers and review articles, were reviewed as
an additional manual search. Trials applied that were pub-
lished in the English language without time restrictions for
Figure 1. Literature search and review flowchart for selection of studies.
2 R. TABRIZI ET AL.
Table 1. The effect of caffeine on weight, BMI and body fat reduction: overview of selected studies for dose-response meta-analysis.
Authors (y) Country
Publication
year Age (y) Gender
Sample size
(control/
intervention) RCT type
Energy
restriction
Intervention
(name and daily dose)
Dosage
of
caffeine
(mg/day) Control
Duration
(wk)
Presented
data Participants
Colker et al. (1999) USA 1999 Range: >21 y F/M 7/9 Parallel No 975 C aurantium, 528 mg
C, 900 mg St. Johns
240 Maltodextrin
placebo
6 Weight, body fat Overweight
Molnar et al. (2000) Hungary 2000 Mean: 16 ± 1 F/M
1
13/16 Parallel Yes <80 kg:300 mg C/30 mg
E
2
Or >80 kg: 600 mg
C/60 mg E
450 Placebo 20 Weight, BMI,
body fat
Obese
Boozer et al. (2002) USA 2002 Range: 18-80 F/M 38/39 Parallel Yes 192 mg C/90 mg E 192 Placebo 24 Weight, body fat Obese
Boozer et al. (2002) USA 2002 Range: 25-55 F/M 24/24 Parallel No 240 mg C/72 mg E 100 Placebo 8 Weight, body fat Overweight/
Obese
Coffey et al. (2004) USA 2004 Range: 18-65 F/M 50/52 Parallel No 360 mg C/60 mg E/
90 mg salicin
360 Placebo 12 Weight, BMI,
body fat
Obese
Greenway et al. (2004) USA 2004 Range: 18-65 F/M 20/20 Parallel Yes 210 mg C/72mg E 210 Placebo 12 Weight Healthy
Hackman et al. (2006) USA 2006 Range: 25-74 F 23/19 Parallel No 100 mg C/40 mg E 100 Placebo 36 Weight, body fat Overweight/
Obese
Thom (2007) Norway 2007 Mean: 24.2 ±3.2 F/M 15/15 crossover No 10 g of Coffee Slender 528 10 g of decaf-
feinated
coffee
12 Weight, body fat Overweight/
Obese
Hursel and
Westerterp-
Plantenga,
(2009)
Netherla-
nds
2009 Mean: 44 ± 2 F/M 20/20 Parallel No 150 mg C/270 mg
green tea
150 Placebo 13 Weight, BMI,
body fat
Overweight/
Obese
Bakuradze et al. (2011) Germany 2011 Range: 20-44 M 33/33 Consecuti-
ve
No 750 ml freshly
brewed coffee
720 Water 8 Weight, BMI,
body fat
Healthy
Liu et al. (2013) USA 2013 Range: 18-60 F/M 26/17 Parallel Yes 600 mg C/60 mg E 600 60 mg Leptin 24 Weight, body fat Obese
Bracale et al. (2014) Italy 2014 Mean:
36.3 ± 10.3
F 7/6 Parallel Yes 60 mg C/600 mg E 60 Placebo 4 Weight, BMI Obese
Davoodi et al. (2014) Iran 2014 Mean:
39.22 ± 5.81
F 30/30 Parallel Yes 5mg C/kg BW 425 Nothing 6 Weight, BMI,
body fat
Overweight/
Obese
1
F, Female; M, Male.
2
C, caffeine; E, ephedrine; OBLI, online basic lifestyle information; OBWM, online behavioral weight management; BEV, fortified diet cola beverage, soluble fiber dextrin and caffeine.
CRITICAL REVIEWS IN FOOD SCIENCE AND NUTRITION 3
publication. Two authors (RT, MA) independently selected
studies in a two-steps process. In the first stage, authors
screened the titles and/or abstract for eligible trials. In the
second stage, the full-texts of related studies were retrieved to
assess the eligibility of selected studies using inclusion and
exclusion criteria. Studies did not contain proper data to be
included in the met-analysis, though presented the other
inclusion criteria were considered for a qualitative analyses to
help identify confounding parameters. Trials that met the
following criteria were selected for meta-analysis: (1) human
RCTs; (2) intervention group consumed caffeine or caffein-
ated coffee, whereas the control group received placebo; and
(3) the trials reported mean changes or mean difference
of weight and/or BMI and/or body fat loss with standard
deviation (SD) for the intervention and control groups or
reported enough data acquirable to assess Beta (B) and its
Standard Error (SE) for the assumed linear regression on the
log
e
-log
e
scale.
Data extraction and quality assessment
Two independent authors (ZA and MA) extracted data from
each trial. The Cochrane Collaboration risk of bias tool was
used to assess the quality of all relevant RCTs based on the
following domains: random sequence generation, allocation
concealment, blinding of participants and outcome assess-
ment, incomplete outcome data, and selective outcome
reporting, and other sources of bias. The following data were
extracted: first authorsname, publication year, age, gender,
country, sample size, study design, energy restriction, the
dose of caffeine intake in intervention and control groups,
the duration of intervention, the mean change and standard
deviation on weight, BMI, and body fat in intervention and
control groups at the end of the intervention. We converted
the reported dosage of caffeine intake into milligram per day
(mg/d).
Data analysis
We estimated a caffeine intake-status regression coefficient
(Beta) for each primary study on the baseline value when
the assumption of a linear correlation on the log
e
-log
e
scale
exists; caffeine intake compared with mean change weight,
BMI, and body fat. Algebraically derivation of an estimate
from primary study of the Beta and its SE, we compared
findings from studies with heterogeneously reported associa-
tions and the associated effects. The overall pooled Beta and
its SE were estimated by using random effects meta-analysis
following DerSimonian and Laird method (DerSimonian
and Laird 1986). In the meta-regression model, the equation
intercepts were calculated by using the meanX (the mean of
the caffeine intake on the ln scale) and the meanY (the
change of mean for weight, BMI, and fat mass status on the
ln scale) for every trial and weighted these by multiplying
with the weighting agent of the trial. Finally, we took the
mean of the weighted meanX and mean of the weighted
meanY as the coordination point at that the regression lines
were hung up. This point, together with Betas, presented the
intercept. All statistical transformation to provide Beta and
its SE were conducted using the Microsoft Excel version 7.0
(Microsoft, Inc). For each trial, we weighted these by multi-
plying with the weighting agent of the trial. Heterogeneity
between studies was assessed by Cochran Q test and I-
squared statistic (I
2
). I
2
higher than 50 percent with P-value
<0.05 represented significant heterogeneity. Potential source
of heterogeneity between studies such as duration of study
(12 weeks vs. <12 weeks), geographic area (US vs. non-
US), gender (female vs. male), and energy restriction (no vs.
yes) were examined by using subgroup analysis based on
stratified random effects meta-analysis. We used the median
of intervention duration, which was 12 weeks to do sub-
group analyses in order to have equal distribution of data
for comparison analyses. For linear dose response analyses,
we used the transformations method to derive coherent
single-study calculates from available summary statistics
(Souverein et al. 2012). The present study applied a basee
logarithmic transformation on the caffeine intake and mean
change of weight, BMI, and body fat before estimation of
trial-specific Betas, therefore the overall Beta provides the
difference in the loge-transformed and predicted mean
change of weight, BMI, and body fat for each 1 unit differ-
ence in the loge transformed value in caffeine intake.
Eggers test was used to detect the existence of potential
publication bias for the primary outcome measure. To meas-
ure the pooled estimates, nonparametric test (Duval and
Figure 2. The methodological quality of included studies based on review authorsjudgments about each risk of bias item presented as percentages across all
included studies.
4 R. TABRIZI ET AL.
Figure 3. AC. Random effects meta analysis of 13 randomized controlled trials that examined the association or effect of caffeine intake on change mean
(A) weight, (B) for BMI, (C) for body fat in intervention and control groups by using regression coefficients (Bets) for the liner association between loge-transformed
caffeine intake and loge transformed change mean in weight, BMI, and fat mass status (CI ¼95%).
CRITICAL REVIEWS IN FOOD SCIENCE AND NUTRITION 5
Tweedie) was used. We used STATA version 12.0 (Stata
Corp., College Station, TX) and RevMan V.5.3 software
(Cochrane Collaboration, Copenhagen, Denmark) for data anal-
yses. P-Values <0.05 were considered as statistically significant.
Results
Our initial search found 945 potential citations, after screen-
ing 13 trials with total of 606 participants were potentially
relevant and was included in the meta-analysis. Figure 1
shows the details of the study selection and Table 1 shows
the characteristics of the included studies that were pub-
lished between 1999 to 2014. Sample size varied between 13
to 102 participants. A consecutive design was performed in
one study, cross-over design in one study, and parallel group
design in the remaining 11 trials. To incorporating cross-
over trials, we were included only data from the first period.
Twelve trials have reported mean changes on weight
(Bakuradze et al. 2011; Boozer et al. 2002; Bracale et al.
2014; Coffey et al. 2004; Colker et al. 1999; Davoodi et al.
2014; Greenway et al. 2004; Hackman et al. 2006; Hursel
and Westerterp-Plantenga, 2009; Liu et al. 2013; Molnar
et al. 2000; Thom, 2007), six on BMI (Bakuradze et al. 2011;
Bracale et al. 2014; Coffey et al. 2004; Davoodi et al. 2014;
Hursel and Westerterp-Plantenga, 2009; Molnar et al. 2000),
and one on body fat loss (Greenway et al. 2004). The dur-
ation of intervention among trials varied between 4 and
36 weeks. The dosage of caffeine or caffeinated coffee in
intervention group was from 60 to 4000 mg/day (median:
360 mg/day). Seven trials were conducted in USA (Boozer
et al. 2002; Coffey et al. 2004; Colker et al. 1999; Greenway
et al. 2004; Hackman et al. 2006; Liu et al. 2013), and one in
each of the following countries, Iran (Davoodi et al. 2014),
Italy (Bracale et al. 2014), Germany (Bakuradze et al. 2011),
Netherlands (Hursel and Westerterp-Plantenga, 2009),
Hungary (Molnar et al. 2000), and Norway (Thom, 2007).
Figure 2 shows risk of bias of included trials.
The pooled analyses yielded a Beta coefficient of 0.29
(95%CI: 0.19, 0.40; Q ¼124.5, I
2
¼91.2%) for weight, 0.23
(95%CI: 0.09, 0.36; Q ¼71.0, I
2
¼93.0%) for BMI, and 0.36
(95%CI: 0.24, 0.48; Q ¼167.36, I
2
¼94.0%) for body fat
(Figures 3 and 4). The dose-response analyses showed that a
person who consumed 2 mg of caffeine per day compared to
1 mg of caffeine intake per day have 22% more reduction in
weight, 17% more reduction in BMI, and 28% more reduc-
tion in body fat.
The subgroup analysis for potential confounder variables
for heterogeneity including the dosage of caffeine intake, the
duration of the intervention, geographic area, gender, and
energy restriction are summarized in Table 2. The results of
subgroup analyses showed that the Betas were different in
some specific strata of suspected variables.
Eggers regression tests indicated no significant publica-
tion bias for the effect of caffeine intake on mean reduction
in weight (B ¼3.23, P¼0.22), and BMI (B ¼3.79,
P¼0.29). There was evidence of possible publication bias
in the effect of caffeine intake and fat mass (B ¼7.81,
P¼0.001). The results showed that the summary regression
coefficient (Beta) on body fat significantly decreased between
before (Beta 0.36; 95%CI, 0.24, 0.24) and after (Beta 0.22;
95%CI, 0.10, 0.34) censored trials were included into
the analysis.
Discussion
This systematic review and meta-analysis is the first report
of the effect of caffeine intake on weight, BMI and body fat
and showed that caffeine intake might promote weight, BMI
and body fat reduction.
Obesity is associated with multiple metabolic and non-
metabolic disorders such as CHD, T2DM, and certain types of
cancer (Kromhout, 1983; Lynch et al. 2009). The current meta-
analysis of RCTs demonstrated that caffeine consumption
resulted in a significant decrease in weight, BMI and body fat.
In a meta-analysis by Phung et al.(Phung et al. 2010), it was
documented that the administration of green tea catechins
(GTCs) with caffeine was correlated with a significant decrease
in BMI, body weight, and waist circumference. Among healthy
people intake of green tea extract containing 270 mg of
Figure 4. AC. The change of mean weight, BMI, and fat mass status as a
function of dietary of caffeine intake (mg/d) calculated using random effects
meta-analyses of randomized controlled trails on )A) weight
[loge(y) ¼0.29 loge(x) 0.90], )B) BMI [loge(y) ¼0.23 loge(x) 1.93], )C)
body fat loge(y) ¼0.36 loge(x) 1.10].
6 R. TABRIZI ET AL.
epigallocatechin gallate and 150 mg of caffeine, were associated
with a significant increase in energy expenditure (by 4%)
compared with people who consumed caffeine alone. It was
also found that; there was a significant decrease in fat oxida-
tion (by 41%) for people who consumed green tea compared
with people who consumed caffeine (by 33%) (Dulloo et al.
1999). Few studies have reported the beneficial effects of caf-
feine on metabolic profiles. In a meta-analysis by Shi et al. (Shi
et al. 2016), caffeine intake significantly reduced insulin sensi-
tivity in healthy people. In another meta-analysis, the adminis-
tration of GTCs with or without caffeine led to a significant
drop in fasting glucose concentrations (Zheng et al. 2013).
Earlier, it was reported that the family of insulin-like growth
factors and their binding proteins involved in energy restriction
(Hamilton-Fairley et al. 1993), might interfere with reduction
in weight, BMI and body fat (Kiddy et al. 1989). Increased
insulin sensitivity would result in elevated IGF-binding pro-
tein-1 during short-term energy restriction (Moran et al. 2003).
In the current meta-analysis, we selected weight, BMI,
and body fat because they are known as the main diagnostic
variables in overweight and obese people, as well as being
the independent risk factors for CVD and diabetes (NHLBI
Obesity Education Initiative Expert Panel 1998). Despite the
statistical significance found between caffeine intake and
reduction in weight, BMI, and body fat in the current study,
the observed changes might not possibly be clinically rele-
vant. For instance, for anti-obesity agents available in the
market, subjects are considered to have failed their treat-
ment if they have not achieved a weight loss of 2 kg after
4 weeks of the therapy (NHLBI Obesity Education Initiative
Expert Panel 1998). It is noteworthy to mention that, in the
current meta-analysis, caffeine consumption provided an
average weight loss of <2 kg after 4 weeks of intervention
compared with the control group.
Caffeine intake may contribute to a decrease in anthropo-
metric measures through increased energy expenditure (Astrup
et al. 1990; Dulloo et al. 1989), and increased thermogenesis
(Astrup et al. 1990). Current evidence indicates the presence of
caffeine antagonize adenosine receptors (Graham 2001;Thong
and Graham 2002b) both in skeletal muscle (Graham 2001;
Han et al. 1998) and in the central nervous system, with the
latter results in an elevation in sympathetic activity (Thong
and Graham 2002a), which might results in weight loss.
The strengths of the current study include: (1) we made a
quantitative evaluation on how caffeine intake may influence
weight and BMI, based on the best available evidence from
RCTs; and (2) we combined all available dose in our dose-
response meta-analysis across a large range of exposure, and
the validity of the dose-response estimates have been increased.
There are several limitations in this meta-analysis, which
should be taken into consideration when assess the results.
Firstly, the number of studies, which were included in low-
grade and high-grade subgroup analyses, was too small to
gain solid conclusions; therefore more relevant studies are
Table 2. The effects of caffeine intake on weight, BMI and body fat reduction based on subgroup analysis.
Parameter
Number
of trials Subgroups
Pooled Beta
(random effect) 95% CI I-squared (%) Overall I-squared (%)
Weight Dosage of caffeine (mg/day) 3 <200 0.18 0.04, 0.32 86.2 91.2
5 200- 450 0.44 0.21, 0.67 95.9
3 450 <0.24 0.15, 0.33 0.0
Duration of study (week) 8 12 0.25 0.12, 0.39 91.7
413 0.37 0.17, 0.58 92.3
Geographic area 7 US 0.33 0.23, 0.44 82.8
5 Non US 0.24 0.04, 0.45 94.2
Gender 3 Female 0.11 0.09, 0.30 89.3
1 Male 0.18 0.02, 0.33
8 Both 0.38 0.26, 0.50 88.2
Energy restriction 6 No 0.33 0.24, 0.42 70.0
6 Yes 0.27 0.10, 0.44 93.7
BMI Dosage of caffeine (mg/day) 2 <200 0.10 0.06, 0.14 0.0 93.0
3 200- 450 0.33 0.07, 0.60 95.7
1 450 <0.21 0.06, 0.36
Duration of study (week) 4 12 0.20 0.01, 0.40 93.0
213 0.28 0.07, 0.62 95.8
Geographic area 1 US 0.46 0.36, 0.55
5 Non US 0.17 0.07, 0.28 85.1
Gender 2 Female 0.09 0.03, 0.15 0.0
1 Male 0.21 0.06, 0.36
3 Both 0.34 0.06, 0.61 96.8
Energy restriction 3 No 0.26 0.01, 0.50 95.7
3 Yes 0.20 0.03, 0.42 91.7
Fat mass Dosage of caffeine (mg/day) 4 <200 0.29 0.13, 0.46 94.0 94.0
4 200- 450 0.34 0.11, 0.56 95.6
3 450 <0.53 0.10, 0.96 94.3
Duration of study (week) 6 12 0.34 0.17, 0.52 94.6
513 0.39 0.20, 0.58 94.6
Geographic area 6 US 0.45 0.25, 0.65 94.1
5 Non US 0.27 0.11, 0.44 94.8
Gender 2 Female 0.30 0.17, 0.77 96.4
1 Male 0.12 0.01, 0.26
8 Both 0.41 0.27, 0.56 94.3
Energy restriction 7 No 0.38 0.23, 0.53 92.8
4 Yes 0.33 0.11, 0.55 95.7
CRITICAL REVIEWS IN FOOD SCIENCE AND NUTRITION 7
needed to further explore this association. Secondly, sub-
stantial heterogeneity was observed across studies, which
was expected considering differences in types of caffeine
(e.g., only caffeine vs. caffeine plus other compositions), and
participantscharacteristics (e.g., gender, geographic region,
genetic background, and gene-environment interactions).
Thirdly, our search was limited to English language.
Overall, the current meta-analysis demonstrated that caf-
feine intake promoted weight, BMI and body fat reduction.
Additional prospective studies investigating the effect of caf-
feine supplementation on weight, BMI, and body fat loss
are necessary.
Disclosure statement
None.
Funding
The current study was founded by a grant from the Vice-chancellor for
Research, Shiraz University of Medical Sciences, Shiraz, and Iran.
ORCID
Kamran B Lankarani http://orcid.org/0000-0002-7524-9017
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CRITICAL REVIEWS IN FOOD SCIENCE AND NUTRITION 9
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Background Energy drinks (EDs) are a type of beverage that mostly contains caffeine and other dietary supplements (if present) and does not contain any alcohol in the ingredients. The products in this category include Red Bull, Redline, Monster, Full Throttle, and others. They are claimed to help in boosting energy, stamina, sports performance, and concentration among individuals. This article focused on the review of the benefits and disadvantages of consumption of energy drinks to health and well-being. ED provides health benefits effects such as improved physical performance, mood and attitude, cognition, and weight loss. Some adverse negative health challenges have been linked to consumption of ED. Therefore, this review is a wholistic appraisal of benefits or detriments of consumption of energy drink to our health and suggestions to curtail the excesses of ED consumption. Main body Energy drink has been around since 1950, and it is marketed as energy booster and comes in different types, energy shots, fruit-based, non-fruit-based (regular), sugar-free, and plant-based. These products are marketed as a low-calorie “instant” energy drink that can be consumed in a single sip, or bottle to boost energy or to boost the nutritional value of conventional products. Many of them contain different ingredients such as caffeine, guarana, ginseng, yerba mate, acai berry, ginkgo biloba, methylxanthines, sugar, glucuronolactone, taurine, maltodextrin, B vitamins. Vitamin B2 (riboflavin), B3 (niacin), B6 (pyridoxine, pyridoxal, and pyridoxamine), Inositol B8 and B12, vitamin C and vitamin D; calcium, Iron, chromium, zinc, manganese, molybdenum; artificial sweeteners, aspartame, and sucralose. Health benefits such as improved physical performance, improved mood and attitude, improved concentration, and memory, good source of vitamin B and weight loss have been reported. Negative impact on health such as adverse cardiovascular effect, headaches, epileptic seizures, ischemic stroke, hallucinations, muscular twitching, restlessness, sleeplessness, anxiety, depression, gastrointestinal effect, renal effects, dental effects, obesity and type II diabetes, cancer, and caffeine toxicity has been reported. Conclusions Most of the health detriments caused because of consumption of energy drink is mostly due to the presence of excess quantity of caffeine and sugar. If the quantities of caffeine and sugar content in energy drink are kept at FDA- and WHO-recommended daily consumption amount, then it will not be present any problem to health. Consumption of energy drink that contains natural ingredients such as yerba mate, acai berry, ginkgo biloba, methylxanthines, amino acid, guarana, and ginseng with moderate FDA- and WHO-approved daily consumption of caffeine and sugar is not detrimental to health.
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To evaluate the influence of oral probiotic Bifidobacterium animalis subsp. lactis (BL-11) supplementation on salivary microbiota composition and the association with growth parameters, and behavioral symptoms in individuals with Prader-Willi syndrome (PWS). In this post hoc analysis, we included a subset of 36 PWS patients with available saliva samples from our original randomized, double-blinded, placebo-controlled trial (Chinese Clinical Trial Registry, ChiCTR1900022646, April 20, 2019). Among the 36 subjects, 17 subjects were allocated to the probiotic group for daily use of the BL-11 probiotic and 19 subjects were allocated to the placebo group. Groupwise and longitudinal differences in salivary microbiota abundances, biodiversity metrics, and height were analyzed. Linear correlations were found between identified differentially abundant salivary microbiota and clinical parameters. Salivary microbiome α-diversity was found to be higher in the probiotic-treated group at week 12 relative to placebo controls (P < 0.05). Leptotrichia, Paracoccus, and Faecalibacterium were found to be more abundant in the probiotic-treated group (P < 0.05). Salivary microbiota abundance and predicted functional profiling abundance correlations were found to be associated with anti-inflammation, anti-obesity, toxin degradation, and anti-oxidative injury effects (Q < 0.1). Several oral taxa also displayed correlations with social behavior severity scores in the probiotic-treated group (Q < 0.1). The findings suggest novel salivary microbiota compositional changes in response to the oral supplementation of BL-11 probiotic in individuals with PWS. The observed differentially abundant taxa between groups post-treatment were highly correlated with interventional effects on growth and social behaviors, although further investigation is warranted. Clinical Trial Registration The original clinical trial was registered under the Chinese Clinical Trial Registry with registration number ChiCTR1900022646 (April 20, 2019).
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Background This Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) is intended to provide clinicians an overview of the body weight effects of concomitant medications (i.e., pharmacotherapies not specifically for the treatment of obesity) and functional foods, as well as adverse side effects of common supplements sometimes used by patients with pre-obesity/obesity. Methods The scientific information for this CPS is based upon published scientific citations, clinical perspectives of OMA authors, and peer review by the Obesity Medicine Association leadership. Results This CPS outlines clinically relevant aspects of concomitant medications, functional foods, and many of the more common supplements as they relate to pre-obesity and obesity. Topics include a discussion of medications that may be associated with weight gain or loss, functional foods as they relate to obesity, and side effects of supplements (i.e., with a focus on supplements taken for weight loss). Special attention is given to the warnings and lack of regulation surrounding weight loss supplements. Conclusions This Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) on concomitant medications, functional foods, and supplements is one of a series of OMA CPSs designed to assist clinicians in the care of patients with the disease of pre-obesity/obesity. Implementation of appropriate practices in these areas may improve the health of patients, especially those with adverse fat mass and adiposopathic metabolic consequences.
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Background According to previous meta-analyses, coffee consumption reduces the risk of type 2 diabetes mellitus. However, the underlying mechanism remains unknown. Whether caffeine, the key ingredient in coffee, has a beneficial effect on the glycemic homeostasis and the anti-diabetic effect is particularly controversial. The aim of this study was to summarize the effect of acute caffeine ingestion on insulin sensitivity in healthy men. MethodsA comprehensive literature search for papers published before April 2016 was conducted in EMBASE, PubMed, and Cochrane Library databases. Randomized controlled trials (RCTs) that investigated the effect of caffeine on insulin sensitivity in healthy humans without diabetes were included. A random effects meta-analysis was conducted using Review Manager 5.3. ResultsThe search yielded 7 RCTs in which caffeine intake was the single variant. Compared with placebo, caffeine intake significantly decreased the insulin sensitivity index, with a standardized mean difference of −2.06 (95% confidence interval −2.67 to −1.44, I2 = 49%, P for heterogeneity = 0.06). Conclusion Acute caffeine ingestion reduces insulin sensitivity in healthy subjects. Thus, in the short term, caffeine might shift glycemic homeostasis toward hyperglycemia. Long-term trials investigating the role of caffeine in the anti-diabetic effect of coffee are needed.
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Caffeine is a common substance in the diets of most athletes and it is now appearing in many new products, including energy drinks, sport gels, alcoholic beverages and diet aids. It can be a powerful ergogenic aid at levels that are considerably lower than the acceptable limit of the International Olympic Committee and could be beneficial in training and in competition. Caffeine does not improve maximal oxygen capacity directly, but could permit the athlete to train at a greater power output and/or to train longer. It has also ben shown to increase speed and/or power output in simulated race conditions. These effects have been found in activities that last as little as 60 seconds or as long as 2 hours. There is less information about the effects of caffeine on strength; however, recent work suggests no effect on maximal ability, but enhanced endurance or resistance to fatigue. There is no evidence that caffeine ingestion before exercise leads to dehydration, ion imbalance, or any other adverse effects. The ingestion of caffeine as coffee appears to be ineffective compared to doping with pure caffeine. Related compounds such as theophylline are also potent ergogenic aids. Caffeine may act synergistically with other drugs including ephedrine and anti-inflammatory agents. It appears that male and female athletes have similar caffeine pharmacokinetics, i.e., for a given dose of caffeine, the time course and absolute plasma concentrations of caffeine and its metabolites are the same. In addition, exercise or dehydration does not affect caffeine pharmacokinetics. The limited information available suggests that caffeine non-users and users respond similarly and that withdrawal from caffeine may not be important. The mechanism(s) by which caffeine elicits its ergogenic effects are unknown, but the popular theory that it enhances fat oxidation and spares muscle glycogen has very little support and is an incomplete explanation at best. Caffeine may work, in part, by creating a more favourable intracellular ionic environment in active muscle. This could facilitate force production by each motor unit.
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Context The prevalence of obesity and overweight increased in the United States between 1978 and 1991. More recent reports have suggested continued increases but are based on self-reported data.Objective To examine trends and prevalences of overweight (body mass index [BMI] ≥25) and obesity (BMI ≥30), using measured height and weight data.Design, Setting, and Participants Survey of 4115 adult men and women conducted in 1999 and 2000 as part of the National Health and Nutrition Examination Survey (NHANES), a nationally representative sample of the US population.Main Outcome Measure Age-adjusted prevalence of overweight, obesity, and extreme obesity compared with prior surveys, and sex-, age-, and race/ethnicity–specific estimates.Results The age-adjusted prevalence of obesity was 30.5% in 1999-2000 compared with 22.9% in NHANES III (1988-1994; P<.001). The prevalence of overweight also increased during this period from 55.9% to 64.5% (P<.001). Extreme obesity (BMI ≥40) also increased significantly in the population, from 2.9% to 4.7% (P = .002). Although not all changes were statistically significant, increases occurred for both men and women in all age groups and for non-Hispanic whites, non-Hispanic blacks, and Mexican Americans. Racial/ethnic groups did not differ significantly in the prevalence of obesity or overweight for men. Among women, obesity and overweight prevalences were highest among non-Hispanic black women. More than half of non-Hispanic black women aged 40 years or older were obese and more than 80% were overweight.Conclusions The increases in the prevalences of obesity and overweight previously observed continued in 1999-2000. The potential health benefits from reduction in overweight and obesity are of considerable public health importance.
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