ArticlePDF AvailableLiterature Review

Vegetarian Diets and Weight Reduction: a Meta-Analysis of Randomized Controlled Trials

Authors:

Abstract and Figures

Vegetarian diets may promote weight loss, but evidence remains inconclusive. PubMed, EMBASE and UpToDate databases were searched through September 22, 2014, and investigators extracted data regarding study characteristics and assessed study quality among selected randomized clinical trials. Population size, demographic (i.e., gender and age) and anthropometric (i.e., body mass index) characteristics, types of interventions, follow-up periods, and trial quality (Jadad score) were recorded. The net changes in body weight of subjects were analyzed and pooled after assessing heterogeneity with a random effects model. Subgroup analysis was performed based on type of vegetarian diet, type of energy restriction, study population, and follow-up period. Twelve randomized controlled trials were included, involving a total of 1151 subjects who received the intervention over a median duration of 18 weeks. Overall, individuals assigned to the vegetarian diet groups lost significantly more weight than those assigned to the non-vegetarian diet groups (weighted mean difference, -2.02 kg; 95 % confidence interval [CI]: -2.80 to -1.23). Subgroup analysis detected significant weight reduction in subjects consuming a vegan diet (-2.52 kg; 95 % CI: -3.02 to -1.98) and, to a lesser extent, in those given lacto-ovo-vegetarian diets (-1.48 kg; 95 % CI: -3.43 to 0.47). Studies on subjects consuming vegetarian diets with energy restriction (ER) revealed a significantly greater weight reduction (-2.21 kg; 95 % CI: -3.31 to -1.12) than those without ER (-1.66 kg; 95 % CI: -2.85 to -0.48). The weight loss for subjects with follow-up of <1 year was greater (-2.05 kg; 95 % CI: -2.85 to -1.25) than those with follow-up of ≥1 year (-1.13 kg; 95 % CI: -2.04 to -0.21). Vegetarian diets appeared to have significant benefits on weight reduction compared to non-vegetarian diets. Further long-term trials are needed to investigate the effects of vegetarian diets on body weight control.
Content may be subject to copyright.
REVIEW
Vegetarian Diets and Weight Reduction: a Meta-Analysis
of Randomized Controlled Trials
Ru-Yi Huang, MD, MPH
1,2,3
, Chuan-Chin Huang, ScD
4
, Frank B. Hu, MD, PhD
4,5
, and Jorge E.
Chavarro, MD, ScD
4,5
1
Department of Medical Education, Department of Family Medicine, E-Da Hospital, Kaohsiung City, Taiwan, Republic of China;
2
School of
Medicine,I-SHOU University, Kaohsiung City, Taiwan, Republic of China;
3
Department of Environmental Health, Harvard T.H. Chan School of Public
Health, Boston, MA, USA;
4
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA;
5
Department of Nutrition,
Harvard T.H. Chan School of Public Health, Boston, MA, USA.
BACKGROUND: Vegetarian diets may promote weight
loss, but evidence remains inconclusive.
METHODS: PubMed, EMBASE and UpToDate databases
were searched through September 22, 2014, and investi-
gators extracted data regarding study characteristics
and assessed study quality among selected random-
ized clinical trials. Population size, demographic (i.e.,
gender and age) and anthropometric (i.e., body mass
index) characteristics, types of interventions, follow-
up periods, and trial quality (Jadad score) were re-
corded. The net changes in body weight of subjects
were analyzed and pooled after assessing heteroge-
neity with a random effects model. Subgroup analy-
sis was performed based on type of vegetarian diet,
type of energy restriction, study population, and
follow-up period.
RESULTS: Twelve randomized controlled trials were in-
cluded, involving a total of 1151 subjects who received the
intervention over a median duration of 18 weeks. Overall,
individuals assigned to the vegetarian diet groups lost
significantly more weight than those assigned to the
non-vegetarian diet groups (weighted mean differ-
ence, 2.02 kg; 95 % confidence interval [CI]: 2.80
to 1.23). Subgroup analysis detected significant
weight reduction in subjects consuming a vegan diet
(2.52 kg; 95 % CI: 3.02 to 1.98) and, to a lesser
extent, in those given lacto-ovo-vegetarian diets
(1.48 kg; 95 % CI: 3.43 to 0.47). Studies on sub-
jects consuming vegetarian diets with energy restric-
tion (ER) revealed a significantly greater weight re-
duction (2.21 kg; 95 % CI: 3.31 to 1.12) than
those without ER (1.66 kg; 95 % CI: 2.85 to 0.48).
The weight loss for subjects with follow-up of <1 year
was greater (2.05 kg; 95 % CI: 2.85 to 1.25) than those
with follow-up of 1year(1.13 kg; 95 % CI: 2.04 to
0.21).
CONCLUSIONS: Vegetarian diets appeared to have signif-
icant benefits on weight reduction compared to non-
vegetarian diets. Further long-term trials are needed to
investigate the effects of vegetarian diets on body weight
control.
KEY WORDS: Vegan diet; Lacto-ovo-vegetarian diet; Overweight; Obesity;
Energy restriction.
J Gen Intern Med 31(1):10916
DOI: 10.1007/s11606-015-3390-7
© Society of General Internal Medicine 2015
INTRODUCTION
Obesity is a worldwide public health problem. Between 1980
and 2013, the proportion of overweight or obese adults in-
creased from 28.8 to 36.9 % in men and from 29.8 to 38.0 % in
women.
1
Obesity is associated with hyperlipidemia, hyperten-
sion, diabetes, cardiovascular disease, certain cancers, and all-
cause mortality.
2
It is estimated that overweight and obesity
were the cause of 3.4 million deaths and 3.8 % of disability-
adjusted life-years worldwide in 2010.
3
The prevalence of
obesity has increased sharply in the past four decades in the
United States, and two-thirds of American adults are over-
weight or obese.
4
In 1998, management of overweight or
obese individuals accounted for 9.1 % of annual U.S. medical
expenditures.
5
As part of efforts to reduce obesity and associated
morbidity, various diets for weight reduction have been
proposed. Vegetarian dietary patterns have been reported
to be associated with decreased risk of type 2 diabetes,
coronary heart disease, and all-cause mortality.
6
The two
major types of vegetarian diets are the lacto-ovo-
vegetarian diet, in which meats are avoided but con-
sumption of milk and eggs is allowed, and the vegan
diet, in which all products originating from animals are
avoided. Thus far, the results of randomized clinical
trials
719
investigating the affect of vegetarian diets on
weight reduction have been inconclusive, which could
be due to the diverse populations, small sample sizes,
different intervention durations, and poor adherence. As
therehavebeennostudieswithlargesamplesizes,we
performed a meta-analysis of randomized clinical trials
conducted to date in order to compare the effect of
vegetarian diets with that of non-vegetarian diets on
weight reduction in the general population. We also
investigated whether the effects of weight reduction
differed between lacto-ovo-vegetarian and vegan diets.
Electronic supplementary material The online version of this article
(doi:10.1007/s11606-015-3390-7) contains supplementary material,
which is available to authorized users.
Published online July 3, 2015
JGIM
109
METHODS
Data Sources and Searches
Adopting the Cochrane Collaboration search strategy,
20
we
searched PubMed via the NCBI Entrez system (1950 to
September 22, 2014) and EMBASE via Ovid (1988 to
September 22, 2014) for randomized controlled studies of the
effects of vegetarian diets compared to non-vegetarian diets on
weight reduction. Key words used to search for relevant publi-
cations included the following: (Bweight^AND Bvegetarian
diet^)OR(Bweight^AND Blacto-ovo-vegetarian diet^)OR
(Bweight^AND Bvegan diet^), with the scope of the search
limited to English literature. Bibliographies of identified studies
and UpToDate Database 2014 were reviewed for additional
reference. We contacted three original authors to clarify data.
Study Selection
We included studies that were randomized clinical controlled
trials solely applying vegan or lacto-ovo-vegetarian diets com-
pared to non-vegetarian diets, with the inclusion of changes in
body weight as a study parameter or where this information
could be derived by contacting the authors. We excluded non-
original publications, abstracts of conferences, and studies for
which details could not be obtained. Studies that included
other interventions such as combined physical activity and
diet interventions were also excluded, although studies where
exercise was advised with dietary intervention were included.
Data Extraction and Quality Assessment
For every eligible study, we collected information on the year of
publication, population characteristics, sample size, intervention
type, follow-up period, and weight change. The means and
standard deviations of weight change were obtained from all
studies. For articles that did not report standard deviations,
10,17,19
we imputed a change-from-baseline standard deviation using a
correlation coefficient of 0.96 estimated from trials
9,11,12,14,16
with available data based on Cochranesformula.
21
For three
studies
9,11,15
with repeated measurements during the follow-up
periods, we collected results at the 1-year time point. For one
study
10
that identified subjectsdietary preferences for lacto-ovo-
vegetarian diet or control diet before randomization, we
attempted to separate the preference group from the no-
preference group for comparison within each group. To explore
study quality, we used the Jadad score, which takes into consid-
eration the randomization appropriateness, blinded outcome as-
sessment, and complete description of loss to follow-up. We then
examined each component of the Jadad score as our study-level
factor to see whether it affected the heterogeneity of the results.
Data Synthesis and Analysis
Given the diversity in study design and populations, we
employed a random effects model, and we also conducted a
fixed effects model for sensitivity analysis.
22
We calculated
weighted mean differences for identical outcome measures in
the vegetarian and non-vegetarian diet groups. We assessed
heterogeneity of treatment effects in the included studies using
the I-squared statistic and the chi-square test of the q statistic.
We further evaluated study characteristics as potential sources
of heterogeneity using meta-regression including type of in-
tervention diet (vegan vs. lacto-ovo-vegetarian), type of die-
tary intervention (supplemented food vs. group session with
dieticians), inclusion of energy restriction in the intervention
diet (yes vs. no), study duration (greater vs. less than 1 year),
gender involved in studies (females alone vs. both genders),
overweight/obesity (selected individuals with body mass in-
dex [BMI] 25 vs. general population), population (patients
vs. healthy subjects), study quality (Jadad score high: 3vs.
low: < 3), description of randomization procedures (yes vs.
no), blinding (single or double vs. no) and dropout (analysis of
possible effect vs. no). We conducted subgroup analysis by
pooling effect estimates basedonimportantdomainsof
sources of bias and significant study-level factors in the
meta-regression. To address the uneven study quality, we
conducted sensitivity analyses only for high-quality studies.
Publication bias was examined by constructing a funnel plot
and was tested using the Begg
19
method. All statistical proce-
dures were conducted using Stata software (Version 12;
StataCorp LP, College Station, TX, USA). The work was not
sponsored or supported by specific institutes.
RESULTS
The literature search identified 1513 studies. After excluding
422 duplicates and 1036 articles based on title and abstract
review, 73 articles remained for full-text evaluation (Fig. 1).
We excluded 13 studies that were not original reports, five
studies where the main intervention was a physical activity
intervention, eight studies which were multiple reports of the
same population, 33 studies that did not include information
on outcomes of interest, and two studies that compared vegan
diets versus lacto-ovo-vegetarian diets. After these exclusions,
we identified 12 studies that fulfilled the inclusion criteria and
were used in the final analysis.
Study Characteristics
Table 1summarizes the characteristics of the 12 included
trials. A total of 1151 subjects were included in this analysis,
with baseline age ranging from 18 to 82 years. Three studies
targeted postmenopausal women and one study focused on
premenopausal women. For the studies that enrolled both
genders, the proportion of male subjects ranged from 13 to
52 %. The mean baseline BMI ranged from 25 to 53 kg/m
2
.
Six studies recruited overweight or obese patients, five studies
enrolled people with type 2 diabetes, and one study included
patients with rheumatoid arthritis. Vegan and lacto-ovo-
vegetarian diets were chosen as intervention diets in eight
and four studies, respectively. Among the eight trials on vegan
diets, six used low-fat (10 %) recipes, while one adopted
110 Huang et al: Vegetarian Diet and Weight Control JGIM
high-carbohydrate (60 %) ingredients. The design of non-
vegetarian diets varied across studies and included low-fat,
anti-diabetes, lipid-lowering, and weight reduction recipes. Of
the six studies that applied energy restriction, five applied the
restriction to both the intervention and control arms,
8,1012,16
while one study designated 1 week of energy restriction solely
to the intervention arm.
23
Among the remaining six studies
without energy restriction in the intervention arms, one
adopted energy restriction in their control groups who were
overweight.
9
The follow-up periods among these trials ranged
from 8 weeks to 2 years. Meta-regression identified the length
of follow-up (i.e., 1 year vs. < 1 year) as the only study-level
factor with borderline significance (P=0.045) for the pooling
outcome (Figs. 2and 3).
Quality of Trials
Most of the randomized clinical trials reported various ap-
proaches for evaluating adherence and causes of loss to fol-
low-up. Blinding is difficult in dietary interventions, and only
two trials
13,15
adopted a blind study design. Therefore, we
categorized the 13 studies based on Jadad score
24
as either
high quality (n = 5, score 3) or low quality (n=7, score<3).
Meta-regression analysis revealed that randomization,
blinding, follow-up, and type of dietary intervention were
not important effect modifiers.
Weight Change
Individuals assigned to vegetarian diets lost more weight than
those assigned to control diets (weighted mean difference, 2.02
Kg; 95 % CI: 2.80 to 1.23) in interventions ranging from 9 to
74 weeks. We observed a significant heterogeneity in weight
change (P=0.001 test for heterogeneity, I
2
=62.3 %), and conse-
quently conducted subgroup analyses in terms of intervention
type, follow-up duration, and population characteristics.
Individuals randomized to vegan diets (eight studies, intervention
ranging from 1248 weeks) lost more weight than those random-
ized to lacto-ovo-vegetarian diets (four studies, intervention rang-
ing from 9 to 74 weeks), relative to their respective counterparts
consuming control diets. Specifically, the weighted mean weight
reduction for individuals with vegan diets was 2.52 kg (95 %
CI: 3.02 to 1.98, P=0.406 for heterogeneity, subtotal
I
2
=3.0 %), whereas the corresponding weight change for lacto-
ovo-vegetarian diets was 1.48 kg; (95 % CI: 3.43 to 0.47,
P<0.001 for heterogeneity, subtotal I
2
=83.6 %).
Six trials of vegetarian diets with energy restriction in inter-
ventions ranging from 9 to 48 weeks showed greater weight loss
(2.21 Kg; 95 % CI: 3.31 to 1.12, P=0.002 for heterogeneity,
subtotal I
2
=71.8 %) than diets in those six trials without energy
restriction (1.66 Kg; 95 % CI: 2.85 to 0.48, P=0.115 for
heterogeneity, subtotal I
2
=43.6 %) in interventions ranging from
8 to 74 weeks. Weight loss achieved in 11 trials lasting less than
Fig. 1 Study flow diagram. RCT randomized controlled trial
111Huang et al: Vegetarian Diet and Weight ControlJGIM
Table 1 General Characteristics of Trials Comparing Vegetarian and Non-Vegetarian Diets
Study Key population characteristics Total N Age
Men, % BMI
Intervention Control Energy restriction Duration
||
(weeks)
Jadad
score
*
Mishra 2013
7
Overweight or type 2 diabetes 291 45±15 17 35±1 Low-fat vegan Habitual diet No 18 2
Kahleova 2013
8
Type 2 diabetes 74 3070 47 2553 Vegan Diabetes diet Yes 24 3
Barnard 2009
9
Type 2 diabetes 99 2782 39 2543 Low-fat vegan Diabetes diet Yes, for BMI>25
in control arm
74 3
Burke 2008
10
Sedentary, overweight 200 1855 13 2743 Lactoovovegetarian Low fat Yes
§
2472 3
Turner 2007
11
Overweight, obese
postmenopausal women
62 4473 0 2644 Low-fat vegan NCEP diet Yes 4896 2
Mahon 2007
12
Postmenopausal women 25 58±2 0 29±1 Lactoovovegetarian Habitual diet Yes 9 2
Gardner 2007
13
Premenopausal overweight
and obese women
155 2550 0 2740 Low-fat lactoovo
vegetarian
Calories from carbohydrate,
protein and fat split
40/30/30
No 48 4
Barnard 2005
16
Overweight or obese
postmenopausal women
64 4473 0 2644 Low-fat vegan NCEP diet Yes 14 2
Dansinger 2005
15
Overweight or obese 80 2272 52 2742 Low-fat
lactoovovegetarian
High-fat, high-protein,
low-carbohydrate diet
No 848 5
Nicholson 1999
17
Type 2 diabetes 11 3474 46 Low-fat vegan 5560 % of calories from
carbohydrates, < 30 %
from fat
No 12 2
Prescott 1988
19
Healthy omnivores 64 1860 40 High-protein lacto
ovovegetarian
High protein from meat,
1.5 g/Kg/day
No 12 2
Skoldstam 1979
18
Rheumatoid arthritis 26 3566 27 Lactoovo
vegetarian
Habitual diet Yes, 1st week
intervention
arm only
10 12
*Jadad score: briefly rates study quality by way of randomization, blinding, and follow-up using a 05 scoring system
Ranges of value
Values are reported as number (%)
§
If weight < 90.5 Kg, then 1200 Kcal for women and 1500 Kcal for men; if weight > 90.5 Kg, then 1500 Kcal for women and 1800 Kcal for men
||
The duration of follow-up in each study is equal to the intervention period except for three studies: Dansinger, 8 weeks of intervention; Turner, 14 weeks of intervention; and Gardener, 8 weeks of intervention
112 Huang et al: Vegetarian Diet and Weight Control JGIM
1 year (range: 624 weeks) was greater (2.05 kg; 95 % CI:
2.85 to 1.25, P=0.001 for heterogeneity, subtotal I
2
=66.4 %)
than in the five trials following subjects for 1 year or more (range:
874 weeks) (1.13 kg; 95 % CI: 2.04 to 0.21, P=0.580 for
heterogeneity, I
2
=0 %). In seven trials that included the general
population in interventions ranging from 9 to 74 weeks, vegetar-
ian diets resulted in substantially greater weight reduction
(2.61 kg; 95 % CI: 3.54 to 1.69, P=0.02 for heterogeneity,
subtotal I
2
=61.2%)thaninfivetrialsrestrictedtooverweight
or obese individuals at baseline in interventions ranging
from8to48weeks(1.23 kg; 95 % CI: 2.09 to 0.37,
P=0.38 for heterogeneity, I
2
=5.1 %). In sensitivity analy-
ses, the results of high-quality trials (1.43 kg; 95 % CI:
2.51 to 0.35 I
2
=57.8 %) and trials of low quality
(2.51 kg; 95 % CI: 3.53 to 1.49 I
2
=60.3 %) were
heterogeneous but not significantly different.
Publication Bias
The funnel plot showed slight asymmetry in both the small and
large sample groups. Nevertheless, we found no evidence of
substantial publication bias (BeggstestP=0.32)
(Supplementary Fig., available online).
DISCUSSION
In this meta-analysis of randomized controlled trials compar-
ing body weight changes between individuals consuming
vegetarian diets and those consuming non-vegetarian diets,
the former showed a reduction in weight of approximately
2 kg compared to the latter. Among individuals consuming
vegetarian diets, interventions with vegan diets resulted in
greater weight loss than those with lacto-ovo-vegetarian diets.
Weight loss was also greater in trials with energy restriction. In
addition, analyses indicated that intervention effects were
attenuated over time after 1 year of follow-up, but remained
worthy of integration into daily practice.
Observational studies have suggested an association be-
tween self-reported vegetarian diets and weight control.
2527
In fact, the results from observational studies are in agreement
with our findings, but suggested an even stronger effect than
Fig. 2 Pooled weighted mean differences in weight reduction between vegetarian and non-vegetarian diets. Effects on estimated weight reduction
for each study depicted as solid squares; error bars indicate 95 % CIs. The pooled estimate of 1.99 kg (95 % CI, 2.72 to 1.25) of weight loss is
shown as the diamond. RE random effect, Weight inverse variance weight, WMD weighted mean difference, CI confidence interval
113Huang et al: Vegetarian Diet and Weight ControlJGIM
that documented in randomized trials. A prospective matched
cohort study of 116 individuals who followed strict vegetarian
diets for 3 years showed a 15-kg weight reduction compared to
the control group.
28
While this may imply that participants
with better adherence to a vegetarian diet could have more
profound weight loss, it also might also be explained by self-
selection, residual confounding, measurement error, or lack of
repeated diet and lifestyle assessment. A long-term interven-
tional study by Ornish et al. found a weight reduction of 10 kg
at1yearand8kgat5yearscomparedtobaselineinthegroup
consuming a vegetarian diet, while the control group
experienced an increase of 2 kg.
29
However, the sample size
was small, and the addition of moderate exercise could have
contributed to the substantial weight reduction in the vegetar-
ian diet group. In our meta-analysis, we avoided those issues
by including only randomized controlled trials and excluding
those that combined diet and exercise in the intervention.
For the lacto-ovo-vegetarian diets, the random effects mod-
el showed no significant effect, whereas the fixed model
yielded a small but significant effect on weight reduction.
The difference between the results of the fixed and random
effects models could be due to limited statistical power in the
A
NOTE: Weights are from random effects analysis
.
.
Overall (I-squared = 62.3%, p = 0.001)
Skoldstam (1979)
Barnard (2009)
Mahon (2007)
Subtotal (I-squared = 3.0%, p = 0.406)
Mishra (2013)
ID
1
Study
Gardner (2007)
Burke(no prefer) (2008)
Nicholson (1999)
Burke(prefer) (2008)
Subtotal (I-squared = 83.6%, p = 0.000)
Prescott (1988)
Turner (2007)
Kahleova (2013)
Dansinger (2005)
0
Barnard (2005)
-2.02 (-2.80, -1.23)
-2.00 (-3.63, -0.37)
-1.40 (-3.76, 0.96)
-4.40 (-5.58, -3.22)
-2.52 (-3.06, -1.98)
-2.84 (-3.77, -1.91)
WMD (95% CI)
-0.60 (-2.44, 1.24)
0.00 (-2.14, 2.14)
-3.40 (-10.38, 3.58)
-0.30 (-2.36, 1.76)
-1.48 (-3.43, 0.47)
-0.10 (-2.26, 2.06)
-2.50 (-4.87, -0.13)
-3.00 (-3.85, -2.15)
-2.70 (-6.13, 0.73)
-2.00 (-3.54, -0.46)
100.00
8.88
6.25
10.89
59.18
12.02
Weight
%
8.03
6.94
1.16
7.22
40.82
6.89
6.23
12.36
3.83
9.29
-2.02 (-2.80, -1.23)
-2.00 (-3.63, -0.37)
-1.40 (-3.76, 0.96)
-4.40 (-5.58, -3.22)
-2.52 (-3.06, -1.98)
-2.84 (-3.77, -1.91)
WMD (95% CI)
-0.60 (-2.44, 1.24)
0.00 (-2.14, 2.14)
-3.40 (-10.38, 3.58)
-0.30 (-2.36, 1.76)
-1.48 (-3.43, 0.47)
-0.10 (-2.26, 2.06)
-2.50 (-4.87, -0.13)
-3.00 (-3.85, -2.15)
-2.70 (-6.13, 0.73)
-2.00 (-3.54, -0.46)
100.00
8.88
6.25
10.89
59.18
12.02
Weight
%
8.03
6.94
1.16
7.22
40.82
6.89
6.23
12.36
3.83
9.29
LOV diet
Vegan diet
0-1 0 1
B
NOTE: Weights are from random effects analysis
.
.
Overall (I-squared = 62.3%, p = 0.001)
Barnard (2009)
Study
0
Prescott (1988)
Subtotal (I-squared = 43.6%, p = 0.115)
Mahon (2007)
Nicholson (1999)
Dansinger (2005)
Burke(no prefer) (2008)
1
Turner (2007)
Burke(prefer) (2008)
Mishra (2013)
Kahleova (2013)
ID
Skoldstam (1979)
Subtotal (I-squared = 71.8%, p = 0.002)
Barnard (2005)
Gardner (2007)
-2.02 (-2.80, -1.23)
-1.40 (-3.76, 0.96)
-0.10 (-2.26, 2.06)
-1.66 (-2.85, -0.48)
-4.40 (-5.58, -3.22)
-3.40 (-10.38, 3.58)
-2.70 (-6.13, 0.73)
0.00 (-2.14, 2.14)
-2.50 (-4.87, -0.13)
-0.30 (-2.36, 1.76)
-2.84 (-3.77, -1.91)
-3.00 (-3.85, -2.15)
WMD (95% CI)
-2.00 (-3.63, -0.37)
-2.21 (-3.31, -1.12)
-2.00 (-3.54, -0.46)
-0.60 (-2.44, 1.24)
100.00
6.25
%
6.89
38.18
10.89
1.16
3.83
6.94
6.23
7.22
12.02
12.36
Weight
8.88
61.82
9.29
8.03
-2.02 (-2.80, -1.23)
-1.40 (-3.76, 0.96)
-0.10 (-2.26, 2.06)
-1.66 (-2.85, -0.48)
-4.40 (-5.58, -3.22)
-3.40 (-10.38, 3.58)
-2.70 (-6.13, 0.73)
0.00 (-2.14, 2.14)
-2.50 (-4.87, -0.13)
-0.30 (-2.36, 1.76)
-2.84 (-3.77, -1.91)
-3.00 (-3.85, -2.15)
WMD (95% CI)
-2.00 (-3.63, -0.37)
-2.21 (-3.31, -1.12)
-2.00 (-3.54, -0.46)
-0.60 (-2.44, 1.24)
100.00
6.25
%
6.89
38.18
10.89
1.16
3.83
6.94
6.23
7.22
12.02
12.36
Weight
8.88
61.82
9.29
8.03
Energy Restriction
No Energy Restriction
0-1 0 1
C
NOTE: Weights are from random effects analysis
.
.
Overall (I-squared = 60.8%, p = 0.000)
Barnard (2005)
Mahon (2007)
Kahleova (2013)
Mishra (2013)
Burke(no prefer 24 week) (2008)
Barnard (22 week) (2006)
Subtotal (I-squared = 66.4%, p = 0.001)
Burke (2006)
Barnard (74 week) (2009)
Turner (96 week) (2007)
Burke(no prefer 72 week) (2008)
Prescott (1988)
Study
Burke(prefer 24 week) (2008)
Dansinger (24 week) (2005)
1
Gardner (2007)
Nicholson (1999)
Skoldstam (1979)
Subtotal (I-squared = 0.0%, p = 0.580)
Dansinger (48 week) (2005)
ID
0
Burke(prefer 72 week) (2008)
-1.82 (-2.50, -1.15)
-2.00 (-3.54, -0.46)
-4.40 (-5.58, -3.22)
-3.00 (-3.85, -2.15)
-2.84 (-3.77, -1.91)
0.40 (-1.58, 2.38)
-1.50 (-3.23, 0.23)
-2.05 (-2.85, -1.25)
-0.53 (-2.35, 1.29)
-1.40 (-3.76, 0.96)
-2.45 (-4.92, 0.02)
-1.40 (-3.53, 0.73)
-0.10 (-2.26, 2.06)
-2.90 (-4.58, -1.22)
-0.90 (-3.87, 2.07)
-0.60 (-2.44, 1.24)
-3.40 (-10.38, 3.58)
-2.00 (-3.63, -0.37)
-1.13 (-2.04, -0.21)
-2.70 (-6.13, 0.73)
WMD (95% CI)
0.10 (-1.90, 2.10)
100.00
6.75
7.90
8.96
8.72
5.48
6.16
71.95
5.90
4.56
4.33
5.10
5.02
%
6.32
3.42
5.84
0.85
6.46
28.05
2.80
Weight
5.42
-1.82 (-2.50, -1.15)
-2.00 (-3.54, -0.46)
-4.40 (-5.58, -3.22)
-3.00 (-3.85, -2.15)
-2.84 (-3.77, -1.91)
0.40 (-1.58, 2.38)
-1.50 (-3.23, 0.23)
-2.05 (-2.85, -1.25)
-0.53 (-2.35, 1.29)
-1.40 (-3.76, 0.96)
-2.45 (-4.92, 0.02)
-1.40 (-3.53, 0.73)
-0.10 (-2.26, 2.06)
-2.90 (-4.58, -1.22)
-0.90 (-3.87, 2.07)
-0.60 (-2.44, 1.24)
-3.40 (-10.38, 3.58)
-2.00 (-3.63, -0.37)
-1.13 (-2.04, -0.21)
-2.70 (-6.13, 0.73)
WMD (95% CI)
0.10 (-1.90, 2.10)
100.00
6.75
7.90
8.96
8.72
5.48
6.16
71.95
5.90
4.56
4.33
5.10
5.02
%
6.32
3.42
5.84
0.85
6.46
28.05
2.80
Weight
5.42
<1 year
>=1 year
0-1 0 1
D
NOTE: Weights are from random effects analysis
.
.
Overall (I-squared = 62.3%, p = 0.001)
Nicholson (1999)
Kahleova (2013)
Burke(no prefer) (2008)
Gardner (2007)
Barnard (2009)
Barnard (2005)
Turner (2007)
Study
Subtotal (I-squared = 5.1%, p = 0.384)
Prescott (1988)
Subtotal (I-squared = 61.2%, p = 0.017)
Mishra (2013)
Skoldstam (1979)
Burke(prefer) (2008)
Mahon (2007)
1
Dansinger (2005)
0
ID
-2.02 (-2.80, -1.23)
-3.40 (-10.38, 3.58)
-3.00 (-3.85, -2.15)
0.00 (-2.14, 2.14)
-0.60 (-2.44, 1.24)
-1.40 (-3.76, 0.96)
-2.00 (-3.54, -0.46)
-2.50 (-4.87, -0.13)
-1.23 (-2.09, -0.37)
-0.10 (-2.26, 2.06)
-2.61 (-3.54, -1.69)
-2.84 (-3.77, -1.91)
-2.00 (-3.63, -0.37)
-0.30 (-2.36, 1.76)
-4.40 (-5.58, -3.22)
-2.70 (-6.13, 0.73)
WMD (95% CI)
100.00
1.16
12.36
6.94
8.03
6.25
9.29
6.23
%
41.55
6.89
58.45
12.02
8.88
7.22
10.89
3.83
Weight
-2.02 (-2.80, -1.23)
-3.40 (-10.38, 3.58)
-3.00 (-3.85, -2.15)
0.00 (-2.14, 2.14)
-0.60 (-2.44, 1.24)
-1.40 (-3.76, 0.96)
-2.00 (-3.54, -0.46)
-2.50 (-4.87, -0.13)
-1.23 (-2.09, -0.37)
-0.10 (-2.26, 2.06)
-2.61 (-3.54, -1.69)
-2.84 (-3.77, -1.91)
-2.00 (-3.63, -0.37)
-0.30 (-2.36, 1.76)
-4.40 (-5.58, -3.22)
-2.70 (-6.13, 0.73)
WMD (95% CI)
100.00
1.16
12.36
6.94
8.03
6.25
9.29
6.23
%
41.55
6.89
58.45
12.02
8.88
7.22
10.89
3.83
Weight
General Population
Obese or Overweight
0-1 0 1
Fig. 3 Pooled weighted mean differences in weight reduction by subgroup. Effects on estimated weight reduction for each study depicted as solid
squares; error bars indicate 95 % CIs. The pooled estimate of weight loss is shown as the diamond. RE random effect, Weight inverse variance
weight, WMD weighted mean difference, CI confidence interval. A. Vegan diets vs. lacto-ovo-vegetarian (LOV) diets. Vegan diets were defined
as avoiding all animal products, whereas lacto-ovo-vegetarian diets avoided meat but consumption of milk and eggs was allowed. B. Energy
restriction vs. no energy restriction group. C. Follow-up < 1 year vs. 1 year. D. General population vs. overweight or obese population.
Normal represents general population including normal-weight, overweight and obese individuals
114 Huang et al: Vegetarian Diet and Weight Control JGIM
lacto-ovo-vegetarian diets subgroup (number of studies = 5) in
the random effects model. Therefore, more studies are needed
to examine the effects of lacto-ovo-vegetarian diets. As the
total energy intake was not adjusted in the studies that assigned
meals to two groups,
8,17,19
it is not clear whether the different
weight reduction effects between vegan and lacto-ovo-
vegetarian diets was due to the discrepant total energy intake
in the two dietary patterns.
A possible mechanism underlying the effect of vegetarian
diets on weight reduction may be the abundant intake of whole
grains, fruits, and vegetables. Whole-grain products and veg-
etable generally have low glycemicindex values,and fruits are
rich in fiber, antioxidants, phytochemicals, and minerals.
2
Viscous fiber, around 20 to 50 % in whole-grain products,
could delay gastric emptying and intestinal absorption.
30
Several prospective studies have reported an inverse associa-
tion between fiber consumption and weight loss. The
Coronary Artery Risk Development in Young Adults
(CARDIA) study identified a significant association between
dietary fiber intake and lower body weight at baseline in both
whites and blacks.
31
In the NursesHealth Study (NHS),
women who had greatly increased their fiber intake reported
a mean weight gain that was 1.52 kg less than that in women
who reported a small increase in fiber intake.
32
He et al.
33
further found that women in the NHS with the largest increase
in fruit and vegetable intake had a 28 % lower risk of major
weight gain (25 kg) than those with lowest intake. A meta-
analysis that included 20 small randomized controlled trials
showed that soluble fiber supplementation was not efficacious
for enhancing weight loss,
34
although this result cannot be
generalized to long-term effects of fiber from foods on body
weight.
To the best of our knowledge, this study is the first meta-
analysis to examine the effect of a vegetarian diet on weight
loss relative to other diets (e.g., the American Diabetes
Association-recommended diet, the diet supported by the
National Cholesterol Education Program, and the Atkins diet).
We conducted an extensive literature search, thus diminishing
the possibility of publication bias. However, we found signif-
icant heterogeneity among trials, which may have been largely
due to different study designs, the variety of vegetarian diets,
the presence or absence of energy restriction, suboptimal study
quality as reflected in the lack of blindness in 11 out of 13
studies, a wide range of available dietary adherence from 51 to
83 %, and the intervention strategy (e.g., provided food or
dietician instruction-based). Although we did comprehensive
subgroup analysis, the reliability of results might be limited by
the relatively small sizes of the subgroups. While this meta-
analysis provides evidence that vegetarian diets are more
effective than non-vegetarian diets for weight loss, multiple
gaps in the literature remain. For example, while our analysis
suggested attenuation of effects over time, in agreement with
the wider literature on dietary interventions for weight loss,
most of the trials included in the meta-analysis lasted less than
12 months, and none lasted more than 18 months. Therefore,
the long-term effects of vegetarian diets on body weight
remain unsettled. The short duration of these trials also limits
the available information on other clinically relevant outcomes
such as cardiovascular morbidity and cardiovascular risk fac-
tors. Hence, further intervention trials are warranted to explore
the long-term effects of vegetarian diets on weight loss and
clinical outcomes.
CONCLUSIONS
In summary, vegetarian diets, and vegan diets in particular,
appear to have beneficial effects on weight reduction.
However, these benefits were attenuated over time. Longer-
term intervention trials are needed to investigate the effect of
vegetarian diets on weight control and cardiometabolic risk.
Acknowledgments: Dr. Chung Hsieh, Department of Epidemiology,
Harvard School of Public Health, provided conceptual advice, and Dr.
Stephanie Smith-Warner provided nutritional knowledge and statisti-
cal advice.
Support: This work was supported by NIH grants P30DK46200 and
1U54CA155626.
Conflict of Interest: The authors declare that they have no conflicts of
interest.
Corresponding Author: Jorge E. Chavarro, MD, ScD; Department of
Nutrition, Harvard T.H. Chan School of Public Health, Building 2, 3rd
Floor, 655 Hungtinton Avenue, Boston, MA 02115, USA
(e-mail: jchavarr@hsph.harvard.edu).
REFERENCES
1. Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, et al.
Global, regional, and national prevalence of overweight and obesity in
children and adults during 19802013: a systematic analysis for the
Global Burden of Disease Study 2013. Lancet. 2014. doi:10.1016/S0140-
6736(14)60460-8.
2. Hu FB, ed. Obesity Epidemiology. 1st ed. Boston: Oxford University Press;
2008.
3. Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, Lim
SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, et al. A
comparative risk assessment of burden of disease and injury attributable
to 67 risk factors and risk factor clusters in 21 regions, 19902010: a
systematic analysis for the Global Burden of Disease Study 2010. Lancet.
2012;380(9859):222460. doi:10.1016/S0140-6736(12)61766-8.
4. Wang Y, Beydoun MA. The obesity epidemic in the United Statesgender,
age, socioeconomic, racial/ethnic, and geographic characteristics: a
systematic review and meta-regression analysis. Epidemiol Rev.
2007;29:628. doi:10.1093/epirev/mxm007.
5. Finkelstein EA, Fiebelkorn IC, Wang G. National medical spending
attributable to overweight and obesity: how much, and who's paying?
Health Aff (Millwood). 2003;(Suppl Web Exclusives):W3-21926.
6. Fraser GE. Vegetarian diets: what do we know of their effects on common
chronic diseases? Am J Clin Nutr. 2009;89(5):1607S12. doi:10.3945/
ajcn.2009.26736K.
7. Mishra S, Xu J, Agarwal U, Gonzales J, Levin S, Barnard ND. A
multicenter randomized controlled trial of a plant-based nutrition
program to reduce body weight and cardiovascular risk in the
corporate setting: the GEICO study. Eur J Clin Nutr.
2013;67(7):71824. doi:10.1038/ejcn.2013.92.
115Huang et al: Vegetarian Diet and Weight ControlJGIM
8. Kahleova H, Matoulek M, Bratova M, Malinska H, Kazdova L, Hill M,
et al. Vegetarian diet-induced increase in linoleic acid in serum phospho-
lipids is associated with improved insulinsensitivity in subjects with type 2
diabetes. Nutr Diabetes. 2013;3, e75. doi:10.1038/nutd.2013.12.
9. Barnard ND, Cohen J, Jenkins DJ, Turner-McGrievy G, Gloede L,
Green A, et al. A low-fat vegan diet and a conventional diabetes diet in the
treatment of type 2 diabetes: a randomized, controlled, 74-wk clinical trial.
Am J Clin Nutr. 2009;89(5):1588S96. doi:10.3945/ajcn.2009.26736H.
10. Burke LE, Warziski M, Styn MA, Music E, Hudson AG, Sereika SM. A
randomized clinical trial of a standard versus vegetarian diet for weight
loss: the impact of treatment preference. Int J Obes (Lond).
2008;32(1):16676. doi:10.1038/sj.ijo.0803706.
11. Turner-McGrievy GM, Barnard ND, Scialli AR. Atwo-yearrandomized
weight loss trial comparing a vegan diet to a more moderate low-fat diet.
Obesity. 2007;15(9):227681.
12. Mahon AK, Flynn MG, Stewart LK, McFarlin BK, Iglay HB, Mattes RD,
et al. Protein intake durin g energy restriction : effects on body composition
and markers of metabolic and cardiovascular health in postmenopausal
women. J Am Coll Nutr. 2007;26(2):1829.
13. Gardner CD, Kiazand A, Alhassan S, Kim S, Stafford RS, Balise RR,
et al. Comparison of the Atkins, Zone, Ornish, and LEARN diets for change
in weight and related risk factors among overweight premenopausal
women: the A TO Z Weight Loss Study: a randomized trial. JAMA.
2007;297(9):96977. doi:10.1001/jama.297.9.969.
14. Barnard ND, Cohen J, Jenkins DJ, Turner-McGrievy G, Gloede L,
Jaster B, et al. A low-fat vegan diet improves glycemic control and
cardiovascular risk factors in a randomized clinical trial in individuals with
type 2 diabetes. Diabetes Care. 2006;29(8):177783. doi:10.2337/dc06-0606.
15. Dansinger ML, Gleason JA, Griffith JL, Selker HP, Schaefer EJ.
Comparison of the Atkins, Ornish, Weight Watchers, and Zone diets for
weight loss and heart disease risk reduction: a randomized trial. JAMA.
2005;293(1):4353. doi:10.1001/jama.293.1.43.
16. Barnard ND, Scialli AR, Turner-McGrievy G, Lanou AJ, Glass J. The
effects of a low-fat, plant-based dietary intervention on body weight,
metabolism, and insulin sensitivity. Am J Med. 2005;118(9):9917.
doi:10.1016/j.amjmed.2005.03.039.
17. Nicholson AS, Sklar M, Barnard ND, Gore S, Sullivan R, Browning S.
Toward improved management of NIDDM: a randomized, controlled, pilot
intervention using a lowfat, vegetarian diet. Prev Med. 1999;29(2):8791.
doi:10.1006/pmed.1999.0529.
18. Skoldstam L. Fasting and vegan diet in rheumatoid arthritis. Scand J
Rheumatol. 1986;15(2):21921.
19. Prescott SL, Jenner DA, Beilin LJ, Margetts BM, Vandongen R. A
randomized controlled trial of the effect on blood pressure of dietary non-
meat protein versus meat protein in normotensive omnivores. Clin Sci
(Lond). 1988;74(6):66572.
20. Dickersin K, Scherer R, Lefebvre C. Identifying relevant studies for
systematic reviews. BMJ. 1994;309(6964):128691.
21. Higgins JPT, Green S, eds. Cochrane Handbook For Systematic
Reviews of Interventions. Chichester, United Kingdom: Wiley-
Blackwell; 2008.
22. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin
Trials. 1986;7(3):17788.
23. Skoldstam L, Larsson L, Lindstrom FD. Effect of fasting and
lactovegetarian diet on rheumatoid arthritis. Scand J Rheumatol.
1979;8(4):24955.
24. Jadad AR, Moore RA, Carroll D, Jenkinson C, Reynolds DJ, Gavaghan
DJ, et al. Assessing the quality of reports of randomized clinical trials: is
blinding necessary? Control Clin Trials. 1996;17(1):112.
25. Spencer EA, Appleby PN, Davey GK, Key TJ. Diet and body mass index
in 38000 EPIC-Oxford meat-eaters, fish-eaters, vegetarians and vegans. Int
J Obes Relat Metab Disord. 2003;2 7(6):72834. doi :10.1038/sj.ij o.
0802300.
26. Kennedy ET, Bowman SA, Spence JT, Freedman M, King J. Popular
diets: correlation to health, nutrition, and obesity. J Am Diet Assoc.
2001;101(4):41120. doi:10.1016/S0002-8223(01)00108-0.
27. Newby P K, Tucker KL, Wolk A. Risk of overweight and obesity among
semivegetarian, lactovegetarian, and vegan women. Am J Clin Nutr.
2005;81(6):126774.
28. Sacks FM, Cas telli WP, Donner A, Kass EH. Plasma lipids and
lipoproteins in vegetarians and controls. N Engl J Med.
1975;292(22):114851. doi:10.1056/NEJM197505292922203.
29. Ornish D, Brown SE, Scherwitz LW, Billings JH, Armstrong WT, Ports
TA, e t a l. Can lifestyle changes reverse coronary heart disease? The
Lifestyle Heart. Trial Lancet. 1990;336(8708):12933.
30. Koh-Banerjee P, Rimm EB. Whole grain consumption and weight gain: a
review of the epidemiological evidence, potential mechanisms and oppor-
tunities for future research. Proc Nutr Soc. 2003;62(1):259. doi:10.1079/
PNS2002232.
31. Ludwig DS, Pereira MA, Kroenke CH, Hilner JE, Van Horn L, Slattery
ML, et al. Dietary fiber, weight gain, and cardiovascular disease risk
factors in young adults. JAMA. 1999;282(16):153946.
32. Liu S, Willett WC, Manson JE, Hu FB, Rosner B, Colditz G. Relation
between changes in intakes of dietary fiber and grain products and
changes in weight and development of obesity among middle-aged women.
Am J Clin Nutr. 2003;78(5):9207.
33. He K, Hu FB, Colditz GA, Manson JE, Willett WC, Liu S. Changes in
intake of fruits and vegetables in relation to risk of obesity and weight gain
among middle-aged women. Int J Obes Relat Metab Disord.
2004;28(12):156974. doi:10.1038/sj.ijo.0802795.
34. Pittler MH, Ernst E. Guar gum for body weight reduction: meta-analysis
of randomized trials. Am J Med. 2001;110(9):72430.
116 Huang et al: Vegetarian Diet and Weight Control JGIM
... diet allowing consumption of all foods of plant or animal origin) outcome any health outcomes, nutritional status and dietary intake study design systematic reviews with meta-analysis of observational (prospective, cross-sectional and retrospective) or interventional studies (randomized and non-randomized trials) of randomized controlled trials (RCT) pointed to beneficial effects of a vegan diet regarding cardiometabolic parameters, including reduced total cholesterol and LDL-cholesterol, glycemic control, and reductions in body weight and other anthropometric measures among generally healthy individuals or persons with underlying chronic diseases (e.g. diabetes) or at high cardiovascular diseases (CVD) risk (Lopez et al. 2019;Yokoyama, Levin, and Barnard 2017;Huang et al. 2016;. On the other hand, several safety issues have emerged from epidemiological evidence, such as the association of veganism with lower bone density and increased risk of fractures . ...
... 121 full texts were checked for eligibility. Finally, 17 published systematic reviews with meta-analyses (Dinu et al. 2017;Lopez et al. 2019;Yokoyama, Levin, and Barnard 2017;Huang et al. 2016;Iguacel et al. 2019;Lee and Park 2017;Li et al. 2020;Benatar and Stewart 2018;Picasso et al. 2019;Chiavaroli et al. 2018;Craddock et al. 2019;Obersby et al. 2013;Iguacel et al. 2020;Brain et al. 2019;Foster et al. 2013;Viguiliouk et al. 2019), including 79 estimates for a vegan diet and 38 different outcomes were included in the present umbrella review ( Figure S1). A list of excluded studies with the reasons for exclusion is shown in Table S3. ...
... ), diabetes prevalence(Lee and Park 2017), fractures incidence(Iguacel et al. 2019), weight(Huang et al. 2016;Li et al. 2020), height(Li et al. 2020), BMI (Benatar and Stewart 2018), waist circumference (Benatar and Stewart 2018), systolic and diastolic blood pressure (Lopez et al. 2019), triglycerides (Yokoyama, Levin, and Barnard 2017), total cholesterol (Yokoyama, Levin, and Barnard 2017), LDL-cholesterol (Yokoyama, Levin, and Barnard 2017; Benatar and Stewart 2018), HDL-cholesterol (Yokoyama, Levin, and Barnard 2017; Picasso et al. 2019), Apo B (Chiavaroli et al. 2018), fasting glucose (Yokoyama, Levin, and Barnard 2017), HOMA-IR (Yokoyama, Levin, and Barnard 2017), 10-years CHD risk score (Chiavaroli et al. 2018), CRP (Craddock et al. 2019), bone mass density (lumbar spine, femoral neck, whole-body) (Iguacel et al. 2019), mental disorders ...
... Vegetarians in this study also had significantly lower calculated cardiovascular risk scores. Consistent with these findings, various meta-analyses have reported vegetarian diets as effective in lowering blood pressure [4], improving glycemic control [17], and promoting weight loss [18], among other favorable health outcomes. ...
Article
Full-text available
Background Diet plays a critical role in the prevention and treatment of metabolic syndrome (MetS). In addition to being environmentally sustainable, plant-based diets (PBD) have demonstrated a range of health benefits, including a protective effect against MetS. Most research on this topic has focused on PBDs as a whole, without considering the influence of diet quality. Methods Data were obtained from 29 individuals with MetS. Subjects were asked to follow a PBD for 13 weeks. PBD quality was assessed using healthful PBD index (hPDI) and unhealthful PBD index (uPDI). Higher hPDI represented greater consumption of healthy plant foods and lower consumption of less-healthy plant foods. Higher uPDI represented greater consumption of less-healthy plant foods and lower consumption of healthy plant foods. For each participant, hPDI and uPDI scores were calculated at baseline and 9-weeks follow-up. Participants were divided into quintiles according to hPDI and uPDI scores. Statistical analyses were performed to determine the association between biomarker measures and PBD quality scores. Results After 2 weeks, mean weight was lower in hPDI quintile 5 compared to hPDI quintile 1, and higher in uPDI quintile 5 compared to uPDI quintile 1 (p < .05). At baseline, hPDI was inversely associated with weight (r = −0.445, p < .05), and uPDI positively associated with weight (r = 0.437, p < .05). Using follow-up data, HDL-C was positively associated with hPDI (r = .411, p < .05) and negatively associated with uPDI (r = −0.411, p < .05). Conclusions In individuals with MetS, adherence to a healthful plant-based diet was associated with lower weight and higher HDL cholesterol, highlighting the influence of diet quality on the health effects associated with PBDs.
... We found that high adherence to plant-based diet scores was effective in reducing the risk of common non-communicable diseases (overweight/obesity, diabetes, and hypertension). This is consistent with previous analyses of individual foods and the risk of weight change, diabetes, and hypertension development in these cohorts (4)(5)(6)(7). Another major strength of our study is the detailed collection of dietary intake data, which were collected through repeatedly validated 24-h dietary records based on an extensive database containing 6,900 food items. ...
Article
Full-text available
Background A wide range of health benefits are associated with consuming a diet high in plant-based foods. Diet quality can be accurately assessed using plant-based diet indices, however there is inadequate evidence that plant-based diet indices are linked to obesity, hypertension, and type 2 diabetes (T2D), especially in Chinese cultures who have traditionally consumed plant-rich foods. Methods The data came from the China Nutrition and Health Survey. Overall, 11,580 adult participants were enrolled between 2004 and 2006 and followed up until 2009 or 2015 (follow-up rate: 73.4%). Dietary intake was assessed across three 24-h recalls, and two plant-based dietary indices [overall plant-based diet indice (PDI) and healthy plant-based diet indice (hPDI)] were calculated using China Food Composition Code and categorized into quintiles. The study's endpoints were overweight/obesity, hypertension, and T2D. The Hazard ratio (HR) and dose-response relationship were assessed using the Cox proportional risk model and restricted cubic splines. The areas under the curve of the receiver operating characteristic curve analyses were used to evaluate the predictive performance of the PDI and hPDI. Results During the median follow-up period of more than 10 years, 1,270 (33.4%), 1,509 (31.6%), and 720 (11.5%) participants developed overweight / obesity, hypertension, and T2D, respectively. The higher PDI score was linked with a reduced risk of overweight/obesity [HR: 0.71 (95% CI: 0.55–0.93), P -trend <0.001], hypertension [HR: 0.63 (95% CI: 0.51–0.79), P -trend <0.001], and T2D [HR: 0.79 (95% CI: 0.72–0.87), P -trend <0.001]. The hPDI score was inversely associated with overweight/obesity [HR: 0.79 (95% CI: 0.62–0.98), P -trend = 0.02] and T2D [HR: 0.84 (95% CI: 0.75–0.93), P -trend = 0.001]. In the aged <55-year-old group, subgroup analysis indicated a significant negative association between PDI/hPDI and overweight/obesity, hypertension, and T2D. There was no significant difference in the areas under the curve of the fully adjusted obesity, hypertension, and diabetes prediction models between PDI and hPDI. Conclusion The PDI and hPDI scores were very similar in application in Chinese populations, and our findings highlight that adherence to overall plant-based diet index helps to reduce the risk of T2D, obesity, and hypertension in Chinese adults who habitually consume plant-based foods, especially for those aged <55 year. Further understanding of how plant-based diet quality is associated with chronic disease will be needed in the future, which will help develop dietary strategies to prevent diabetes, hypertension, and related chronic diseases.
... However, vegetarianbased diets in combination with energy restriction have shown significant weight loss compared with nonvegetarian-based diets. [64][65][66] Meal Timing. Meal Timing (ie, intermittent fasting) is another approach to promote weight loss and metabolic benefits that is comparable to a standard daily energy restriction. ...
Article
Purpose Nutrition is an important lifestyle modification used in the treatment of obesity. The purpose of this review is to highlight different dietary interventions used to promote weight loss in both adults and children. Methods A search using PubMed was performed for articles on topics related to nutrition and management and/or treatment of obesity in adults adolescents and children. The literature was reviewed and pertinent sources were used for this narrative review. Discussion There are many effective nutrition interventions used to treat obesity, including altering macronutrient composition, implementing different dietary patterns, and changing meal timing. Although these interventions can induce weight loss in adults, management of obesity in children is more difficult given their varied nutrition needs in growth and development. The use of food as medicine in obesity treatment is individualized based on patient's age, food preference, and concurrent medical conditions. Implications Given the multifactorial etiology of obesity, treatment requires multidisciplinary care beyond nutrition intervention.
... For example, a vegan diet encourages people to abstain from eating any animal products (e.g., milk, eggs, meat). Not only is this encouraged for personal health and weight loss [85,86], but it has also been promoted as a way to combat climate change [87,88]. Another example is the Keto Diet, a popular diet that encourages people to eat less carbohydrates (e.g., bread, rice, pasta) and more fats (e.g., eggs, avocado, cheese). ...
Article
Full-text available
Nowadays, many people are deeply concerned about their physical well-being; as a result, they invest much time and effort investigating health-related topics. In response to this, many online websites and social media profiles have been created, resulting in a plethora of information on such topics. In a given topic, oftentimes, much of the information is conflicting, resulting in online camps that have different positions and arguments. We refer to the collection of all such positionings and entrenched camps on a topic such as an online public health debate. The information people encounter regarding such debates can ultimately influence how they make decisions, what they believe, and how they act. Therefore, there is a need for public health stakeholders (i.e., people with a vested interest in public health issues) to be able to make sense of online debates quickly and accurately. In this paper, we present a framework-based approach for investigating online public health debates—a preliminary work that can be expanded upon. We first introduce the concept of online debate entities (ODEs), which is a generalization for those who participate in online debates (e.g., websites and Twitter profiles). We then present the framework ODIN (Online Debate entIty aNalyzer), in which we identify, define, and justify ODE attributes that we consider important for making sense of online debates. Next, we provide an overview of four online public health debates (vaccines, statins, cannabis, and dieting plans) using ODIN. Finally, we showcase four prototype visual analytics systems whose design elements are informed by the ODIN framework.
Article
In parallel with an increased focus on climate changes and carbon footprint, the interest in plant‐based diets and its potential health effects have increased over the past decade. The objective of this systematic review and meta‐analysis was to examine the effect of vegan diets (≥12 weeks) on cardiometabolic risk factors in people with overweight or type 2 diabetes. We identified 11 trials (796 participants). In comparison with control diets, vegan diets reduced body weight (−4.1 kg, 95% confidence interval (CI) −5.9 to −2.4, p < 0.001), body mass index (BMI) (−1.38 kg/m2, 95% CI −1.96 to −0.80, p < 0.001), glycated hemoglobin (HbA1c) (−0.18% points, 95% CI −0.29 to −0.07, p = 0.002), total cholesterol (−0.30 mmol/L, 95% CI −0.52 to −0.08, p = 0.007), and low‐density lipoprotein cholesterol (−0.24 mmol/L, 95% CI −0.40 to −0.07, p = 0.005). We identified no effect on blood pressure, high‐density lipoprotein cholesterol, and triglycerides. We found that adhering to vegan diets for at least 12 weeks may be effective in individuals with overweight or type 2 diabetes to induce a meaningful decrease in body weight and improve glycemia. Some of this effect may be contributed to differences in the macronutrient composition and energy intake in the vegan versus control diets. Therefore, more research is needed regarding vegan diets and cardiometabolic health.
Article
We hypothesised that a plant-based diet, without excluding any specific animal food, may be beneficial for body composition. This study aims to evaluate if the consumption of a plant-based diet impacts body composition of adults, through a systematic review of the literature. The review was reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The literature search was conducted in EMBASE, PubMed, Scopus and Web of Science in February 2021. Cross-sectionals, interventional trials, and cohort studies were included if changes in the body composition, were associated with olant-based index (PDI). Meta-analyses were performed using DerSimonian and Laird random effects model with 95% confidence intervals even in the absence of statistical heterogeneity. A total of 6680 citations were found in the systematic search and after the screening process, 12 studies were included. Out of the 11 studies evaluating body mass index, 8 provided data of BMI from a total of 134,128 participants among the quantiles of PDI and a meta-analysis was performed (SMD = 0.17 kg/m², 95% CI = [0.02; 0.32]). Out of the 7 studies that evaluated waist circumference (WC), 4 provided data of WC among the quantiles of PDI from a total of 12.968 participants. Like BMI, the pooled analysis indicated an increase (SMD = 0.50 kg/m², 95% CI = [0.01; 1.00]) of WC as greater was the PDI. Both analyses were influenced by a large study, and in the sensitive analysis the significance was lost.Our findings did not observe an association between a higher PDI and body composition. Also, most studies evaluating total and central adiposity did not find any association with the PDI. Probably, PDI must be considered in the context of food processing, considering that not all vegetable foods are healthy.
Article
Background: Many traditional lifestyle interventions use calorie prescriptions, but most individuals have difficulty sustaining calorie tracking and thus weight loss. By contrast, whole food plant-based diets (WFPBD) have previously shown significant weight loss without this issue. However, most WFPBD interventions are face-to-face, time intensive, and do not leverage gold-standard behavioral strategies for health behavior change. Objective: This open pilot trial was the first to evaluate the feasibility of a fully-featured remotely delivered behavioral weight loss intervention using an ad libitum WFPBD. Methods: Over 12-weeks, participants (N = 15) with overweight/obesity received a newly-designed program that integrated behavioral weight loss and a WFPBD prescription via weekly online modules and brief phone coaching calls. Assessments occurred at baseline, mid-treatment, (6-weeks) and post-treatment (12-weeks). Results: The intervention was rated as highly acceptable (M = 4.40 out of 5), and attrition was low (6.7%). Sixty-nine percent of participants lost 5% weight (M = -5.89 kg, SE = .68). Predefined benchmarks of quality of life were met. Conclusions: A pilot digital behavioral weight loss intervention with a non-energy restricted WFPBD was feasible, and mean acceptability was high. Minimal contact time (100–150 minutes of study interventionist time per participant over 12 weeks) led to clinically relevant weight loss, dietary adherence, and quality of life improvements for most participants. We hope this work serves as a springboard for future larger scale randomized controlled studies evaluating the efficacy of such programs for weight loss, dietary change, and quality of life. Clinical Trial: ClinicalTrials.gov identifier: NCT04892030
Article
Full-text available
Background: In 2010, overweight and obesity were estimated to cause 3·4 million deaths, 3·9% of years of life lost, and 3·8% of disability-adjusted life-years (DALYs) worldwide. The rise in obesity has led to widespread calls for regular monitoring of changes in overweight and obesity prevalence in all populations. Comparable, up-to-date information about levels and trends is essential to quantify population health effects and to prompt decision makers to prioritise action. We estimate the global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013. Methods: We systematically identified surveys, reports, and published studies (n=1769) that included data for height and weight, both through physical measurements and self-reports. We used mixed effects linear regression to correct for bias in self-reports. We obtained data for prevalence of obesity and overweight by age, sex, country, and year (n=19,244) with a spatiotemporal Gaussian process regression model to estimate prevalence with 95% uncertainty intervals (UIs). Findings: Worldwide, the proportion of adults with a body-mass index (BMI) of 25 kg/m(2) or greater increased between 1980 and 2013 from 28·8% (95% UI 28·4-29·3) to 36·9% (36·3-37·4) in men, and from 29·8% (29·3-30·2) to 38·0% (37·5-38·5) in women. Prevalence has increased substantially in children and adolescents in developed countries; 23·8% (22·9-24·7) of boys and 22·6% (21·7-23·6) of girls were overweight or obese in 2013. The prevalence of overweight and obesity has also increased in children and adolescents in developing countries, from 8·1% (7·7-8·6) to 12·9% (12·3-13·5) in 2013 for boys and from 8·4% (8·1-8·8) to 13·4% (13·0-13·9) in girls. In adults, estimated prevalence of obesity exceeded 50% in men in Tonga and in women in Kuwait, Kiribati, Federated States of Micronesia, Libya, Qatar, Tonga, and Samoa. Since 2006, the increase in adult obesity in developed countries has slowed down. Interpretation: Because of the established health risks and substantial increases in prevalence, obesity has become a major global health challenge. Not only is obesity increasing, but no national success stories have been reported in the past 33 years. Urgent global action and leadership is needed to help countries to more effectively intervene. Funding: Bill & Melinda Gates Foundation.
Article
Full-text available
Fatty acids are important cellular constituents that may affect many metabolic processes relevant for the development of diabetes and its complications. We showed previously that vegetarian diet leads to greater increase in metabolic clearance rate of glucose (MCR) than conventional hypocaloric diet. The aim of this secondary analysis was to explore the role of changes in fatty acid composition of serum phospholipids in diet- and exercise-induced changes in MCR in subjects with type 2 diabetes (T2D). Subjects with T2D (n=74) were randomly assigned into a vegetarian group (VG, n=37) following vegetarian diet or a control group (CG, n=37) following a conventional diet. Both diets were calorie restricted (-500 kcal day(-1)). Participants were examined at baseline, 12 weeks of diet intervention and 24 weeks (subsequent 12 weeks of diet were combined with aerobic exercise). The fatty acid composition of serum phospholipids was measured by gas liquid chromatography. MCR was measured by hyperinsulinemic isoglycemic clamp. Visceral fat (VF) was measured by magnetic resonance imaging. Linoleic acid (LA; 18:2n6) increased in VG (P=0.04), whereas it decreased in CG (P=0.04) in response to dietary interventions. It did not change significantly after the addition of exercise in either group (group × time P<0.001). In VG, changes in 18:2n6 correlated positively with changes in MCR (r=+0.22; P=0.04) and negatively with changes in VF (r=-0.43; P=0.01). After adjustment for changes in body mass index, the association between 18:2n6 and MCR was no longer significant. The addition of exercise resulted in greater changes of phospholipid fatty acids composition in VG than in CG. We demonstrated that the insulin-sensitizing effect of a vegetarian diet might be related to the increased proportion of LA in serum phospholipids.
Article
Full-text available
Background/objectives: To determine the effects of a low-fat plant-based diet program on anthropometric and biochemical measures in a multicenter corporate setting. Subjects/methods: Employees from 10 sites of a major US company with body mass index ≥ 25 kg/m(2) and/or previous diagnosis of type 2 diabetes were randomized to either follow a low-fat vegan diet, with weekly group support and work cafeteria options available, or make no diet changes for 18 weeks. Dietary intake, body weight, plasma lipid concentrations, blood pressure and glycated hemoglobin (HbA1C) were determined at baseline and 18 weeks. Results: Mean body weight fell 2.9 kg and 0.06 kg in the intervention and control groups, respectively (P<0.001). Total and low-density lipoprotein (LDL) cholesterol fell 8.0 and 8.1 mg/dl in the intervention group and 0.01 and 0.9 mg/dl in the control group (P<0.01). HbA1C fell 0.6 percentage point and 0.08 percentage point in the intervention and control group, respectively (P<0.01).Among study completers, mean changes in body weight were -4.3 kg and -0.08 kg in the intervention and control groups, respectively (P<0.001). Total and LDL cholesterol fell 13.7 and 13.0 mg/dl in the intervention group and 1.3 and 1.7 mg/dl in the control group (P<0.001). HbA1C levels decreased 0.7 percentage point and 0.1 percentage point in the intervention and control group, respectively (P<0.01). Conclusions: An 18-week dietary intervention using a low-fat plant-based diet in a corporate setting improves body weight, plasma lipids, and, in individuals with diabetes, glycemic control.
Article
Full-text available
Quantification of the disease burden caused by different risks informs prevention by providing an account of health loss different to that provided by a disease-by-disease analysis. No complete revision of global disease burden caused by risk factors has been done since a comparative risk assessment in 2000, and no previous analysis has assessed changes in burden attributable to risk factors over time. METHODS We estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability [YLD] and years of life lost [YLL]) attributable to the independent effects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010. We estimated exposure distributions for each year, region, sex, and age group, and relative risks per unit of exposure by systematically reviewing and synthesising published and unpublished data. We used these estimates, together with estimates of cause-specific deaths and DALYs from the Global Burden of Disease Study 2010, to calculate the burden attributable to each risk factor exposure compared with the theoretical-minimum-risk exposure. We incorporated uncertainty in disease burden, relative risks, and exposures into our estimates of attributable burden. FINDINGS In 2010, the three leading risk factors for global disease burden were high blood pressure (7·0% [95% uncertainty interval 6·2-7·7] of global DALYs), tobacco smoking including second-hand smoke (6·3% [5·5-7·0]), and alcohol use (5·5% [5·0-5·9]). In 1990, the leading risks were childhood underweight (7·9% [6·8-9·4]), household air pollution from solid fuels (HAP; 7·0% [5·6-8·3]), and tobacco smoking including second-hand smoke (6·1% [5·4-6·8]). Dietary risk factors and physical inactivity collectively accounted for 10·0% (95% UI 9·2-10·8) of global DALYs in 2010, with the most prominent dietary risks being diets low in fruits and those high in sodium. Several risks that primarily affect childhood communicable diseases, including unimproved water and sanitation and childhood micronutrient deficiencies, fell in rank between 1990 and 2010, with unimproved water and sanitation accounting for 0·9% (0·4-1·6) of global DALYs in 2010. However, in most of sub-Saharan Africa childhood underweight, HAP, and non-exclusive and discontinued breastfeeding were the leading risks in 2010, while HAP was the leading risk in south Asia. The leading risk factor in Eastern Europe, most of Latin America, and southern sub-Saharan Africa in 2010 was alcohol use; in most of Asia, North Africa and Middle East, and central Europe it was high blood pressure. Despite declines, tobacco smoking including second-hand smoke remained the leading risk in high-income north America and western Europe. High body-mass index has increased globally and it is the leading risk in Australasia and southern Latin America, and also ranks high in other high-income regions, North Africa and Middle East, and Oceania. INTERPRETATION Worldwide, the contribution of different risk factors to disease burden has changed substantially, with a shift away from risks for communicable diseases in children towards those for non-communicable diseases in adults. These changes are related to the ageing population, decreased mortality among children younger than 5 years, changes in cause-of-death composition, and changes in risk factor exposures. New evidence has led to changes in the magnitude of key risks including unimproved water and sanitation, vitamin A and zinc deficiencies, and ambient particulate matter pollution. The extent to which the epidemiological shift has occurred and what the leading risks currently are varies greatly across regions. In much of sub-Saharan Africa, the leading risks are still those associated with poverty and those that affect children. FUNDING Bill & Melinda Gates Foundation.
Article
Full-text available
Objective: To examine the changes in intake of fruits and vegetables in relation to risk of obesity and weight gain among middle-aged women. Design: Prospective cohort study with 12 y of follow-up conducted in the Nurses' Health Study. Subjects: A total of 74,063 female nurses aged 38-63 y, who were free of cardiovascular disease, cancer, and diabetes at baseline in 1984. Measurements: Dietary information was collected using a validated food frequency questionnaire, and body weight and height were self-reported. Results: During the 12-y follow-up, participants tended to gain weight with aging, but those with the largest increase in fruit and vegetable intake had a 24% of lower risk of becoming obese (BMI> or =30 kg/m2) compared with those who had the largest decrease in intake after adjustment for age, physical activity, smoking, total energy intake, and other lifestyle variables (relative risk (RR), 0.76; 95% confidence interval (CI), 0.69-0.86; P for trend <0.0001). For major weight gain (> or =25 kg), women with the largest increase in intake of fruits and vegetables had a 28% lower risk compared to those in the other extreme group (RR, 0.72; 95% CI, 0.55-0.93; P=0.01). Similar results were observed for changes in intake of fruits and vegetables when analyzed separately. Conclusions: Our findings suggest that increasing intake of fruits and vegetables may reduce long-term risk of obesity and weight gain among middle-aged women.
Article
Context Dietary composition may affect insulin secretion, and high insulin levels, in turn, may increase the risk for cardiovascular disease (CVD).Objective To examine the role of fiber consumption and its association with insulin levels, weight gain, and other CVD risk factors compared with other major dietary components.Design and Setting The Coronary Artery Risk Development in Young Adults (CARDIA) Study, a multicenter population-based cohort study of the change in CVD risk factors over 10 years (1985-1986 to 1995-1996) in Birmingham, Ala; Chicago, Ill; Minneapolis, Minn; and Oakland, Calif.Participants A total of 2909 healthy black and white adults, 18 to 30 years of age at enrollment.Main Outcome Measures Body weight, insulin levels, and other CVD risk factors at year 10, adjusted for baseline values.Results After adjustment for potential confounding factors, dietary fiber showed linear associations from lowest to highest quintiles of intake with the following: body weight (whites: 174.8-166.7 lb [78.3-75.0 kg], P<.001; blacks: 185.6-177.6 lb [83.5-79.9 kg], P = .001), waist-to-hip ratio (whites: 0.813-0.801, P = .004; blacks: 0.809-0.799, P = .05), fasting insulin adjusted for body mass index (whites: 77.8-72.2 pmol/L [11.2-10.4 µU/mL], P = .007;blacks: 92.4-82.6 pmol/L [13.3-11.9 µU/mL], P = .01) and 2-hour postglucose insulin adjusted for body mass index (whites: 261.1-234.7 pmol/L [37.6-33.8 µU/mL], P = .03; blacks: 370.2-259.7 pmol/L [53.3-37.4 µU/mL], P<.001). Fiber was also associated with blood pressure and levels of triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and fibrinogen; these associations were substantially attenuated by adjustment for fasting insulin level. In comparison with fiber, intake of fat, carbohydrate, and protein had inconsistent or weak associations with all CVD risk factors.Conclusions Fiber consumption predicted insulin levels, weight gain, and other CVD risk factors more strongly than did total or saturated fat consumption. High-fiber diets may protect against obesity and CVD by lowering insulin levels.
Article
Context: The scarcity of data addressing the health effects of popular diets is an important public health concern, especially since patients and physicians are interested in using popular diets as individualized eating strategies for disease prevention. Objective: To assess adherence rates and the effectiveness of 4 popular diets (Atkins, Zone, Weight Watchers, and Ornish) for weight loss and cardiac risk factor reduction. Design, Setting, and Participants: A single-center randomized trial at an academic medical center in Boston, Mass, of overweight or obese (body mass index: mean, 35; range, 27-42) adults aged 22 to 72 years with known hypertension, dyslipidemia, or fasting hyperglycemia. Participants were enrolled starting July 18, 2000, and randomized to 4 popular diet groups until January 24, 2002. Intervention: A total of 160 participants were randomly assigned to either Atkins (carbohydrate restriction, n=40). Zone (macronutrient balance, n=40), Weight Watchers (calorie restriction, n=40), or Ornish (fat restriction, n=40) diet groups. After 2 months of maximum effort, participants selected their own levels of dietary adherence. Main Outcome Measures: One-year changes in baseline weight and cardiac risk factors, and self-selected dietary adherence rates per self-report. Results: Assuming no change from baseline for participants who discontinued the study, mean (SD) weight loss at 1 year was 2.1 (4.8) kg for Atkins (21 [53 %] of 40 participants completed, P=.009), 3.2 (6.0) kg for Zone (26 [65%] of 40 completed, P=.002), 3.0 (4.9) kg for Weight Watchers (26 [65%] of 40 completed, P<.001), and 3.3 (7.3) kg for Ornish (20 [50%] of 40 completed, P=.007). Greater effects were observed in study completers. Each diet significantly reduced the low-density lipoprotein/high-density lipoprotein (HDL) cholesterol ratio by approximately 10% (all P<.05), with no significant effects on blood pressure or glucose at 1 year. Amount of weight loss was associated with self-reported dietary adherence level (r=0.60; P<.001) but not with diet type (r=0.07; P= .40). For each diet, decreasing levels of total/HDL cholesterol, C-reactive protein, and insulin were significantly associated with weight loss (mean r=0.36, 0.37, and 0.39, respectively) with no significant difference between diets (P= .48, P= .57, P= .31, respectively). Conclusions: Each popular diet modestly reduced body weight and several cardiac risk factors at 1 year. Overall dietary adherence rates were low, although increased adherence was associated with greater weight loss and cardiac risk factor reductions for each diet group.