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Non-Soy Legume Consumption Lowers Cholesterol Levels: A Meta-Analysis of Randomized Controlled Trials

Authors:
  • Ha noi university of mining and geology

Abstract

Studies evaluating the effect of legume consumption on cholesterol have focused on soybeans, however non-soy legumes, such as a variety of beans, peas, and some seeds, are commonly consumed in Western countries. We conducted a meta-analysis of randomized controlled trials evaluating the effects of non-soy legume consumption on blood lipids. Studies were retrieved by searching MEDLINE (from January 1966 through July 2009), EMBASE (from January 1980 to July 2009), and the Cochrane Collaboration's Central Register of Controlled Clinical Trials using the following terms as medical subject headings and keywords: fabaceae not soybeans not isoflavones and diet or dietary fiber and cholesterol or hypercholesterolemia or triglycerides or cardiovascular diseases. Bibliographies of all retrieved articles were also searched. From 140 relevant reports, 10 randomized clinical trials were selected which compared a non-soy legume diet to control, had a minimum duration of 3 weeks, and reported blood lipid changes during intervention and control. Data on sample size, participant characteristics, study design, intervention methods, duration, and treatment results were independently abstracted by 2 investigators using a standardized protocol. Data from 10 trials representing 268 participants were examined using a random-effects model. Pooled mean net change in total cholesterol for those treated with a legume diet compared to control was -11.8 mg/dL (95% confidence interval [CI], -16.1 to -7.5); mean net change in low-density lipoprotein cholesterol was -8.0mg/dL (95% CI, -11.4 to -4.6). These results indicate that a diet rich in legumes other than soy decreases total and LDL cholesterol.
Non-Soy Legume Consumption Lowers Cholesterol Levels: A
Meta-Analysis of Randomized Controlled Trials
Lydia A. Bazzano, MD, PhD, Angela M. Thompson, MSPH, Michael T. Tees, MD, MPH,
Cuong H. Nguyen, MPH, and Donna M. Winham, DrPH
Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine
(CHN, LAB, AMT), Department of Medicine, Tulane University School of Medicine (MTT, LAB),
New Orleans, Louisiana, and Department of Nutrition, Arizona State University Polytechnic
(DMW), Mesa, AZ
Abstract
Background and Aims—Studies evaluating the effect of legume consumption on cholesterol
have focused on soybeans, however non-soy legumes, such as a variety of beans, peas, and some
seeds, are commonly consumed in Western countries. We conducted a meta-analysis of
randomized controlled trials evaluating the effects of non-soy legume consumption on blood
lipids.
Methods and Results—Studies were retrieved by searching MEDLINE (from January 1966
through July 2009), EMBASE (from January 1980 to July 2009), and the Cochrane
Collaboration's Central Register of Controlled Clinical Trials using the following terms as medical
subject headings and keywords: fabaceae not soybeans not isoflavones and diet or dietary fiber
and cholesterol or hypercholesterolemia or triglycerides or cardiovascular diseases.
Bibliographies of all retrieved articles were also searched. From 140 relevant reports, 10
randomized clinical trials were selected which compared a non-soy legume diet to control, had a
minimum duration of 3 weeks, and reported blood lipid changes during intervention and control.
Data on sample size, participant characteristics, study design, intervention methods, duration, and
treatment results were independently abstracted by 2 investigators using a standardized protocol.
Data from 10 trials representing 268 participants were examined using a random-effects model.
Pooled mean net change in total cholesterol for those treated with a legume diet compared to
control was 11.8 mg/dL (95% confidence interval [CI], 16.1 to 7.5); mean net change in low
density lipoprotein cholesterol was 8.0 mg/dL (95% CI, 11.4 to 4.6).
Conclusion—These results indicate that a diet rich in legumes other than soy decreases total and
LDL cholesterol.
Keywords
legumes; fabaceae; meta-analysis; randomized controlled trial; cholesterol; cardiovascular diseases
© 2009 Elsevier B.V. All rights reserved.
Corresponding author, to whom requests for reprints should be addressed: Lydia A. Bazzano, MD, PhD Assistant Professor of
Epidemiology Clinical Assistant Professor of Medicine Tulane University School of Public Health and Tropical Medicine 1440 Canal
St, SL-18 New Orleans, LA 70112-2715 Tel: 504-988-7323 Fax: 504-988-1568 lbazzano@tulane.edu.
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Author Manuscript
Nutr Metab Cardiovasc Dis. Author manuscript; available in PMC 2012 February 1.
Published in final edited form as:
Nutr Metab Cardiovasc Dis
. 2011 February ; 21(2): 94–103. doi:10.1016/j.numecd.2009.08.012.
NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
INTRODUCTION
Worldwide, cardiovascular diseases (CVD) are estimated to be the leading cause of death
and loss of healthy life years resulting from disability (1). In the United States, CVD causes
1 of every 3 deaths (2). Recent data show that 71.3 million people in the United States have
two or more risk factors for heart disease (2). Studies have consistently shown that risk
factor modification can decrease the prevalence of cardiovascular diseases, such as coronary
heart disease and strokes (3-6). Diet is an important modifiable risk factor for many types of
heart disease (7,8).
Observational epidemiologic studies have strongly indicated an inverse relationship between
fruit and vegetable consumption and the incidence of cardiovascular events (7,9). So much
so that not consuming fruits and vegetables daily may be responsible for up to 13.7% of
acute myocardial infarcts in one estimate(10). Several studies have also shown that persons
who consume diets high in whole grains and fiber have lower blood pressure and total
cholesterol levels (11,12). The Dietary Guidelines for Americans suggest consuming 3 cups
of legumes, which are rich in soluble dietary fiber and vegetable protein, per week; however
less than a third of the population meets this guideline (13,14). Legume consumption has
been associated with lower risks of coronary heart disease in observational epidemiologic
studies (15,16) and has been shown to decrease total cholesterol and low-density lipoprotein
cholesterol in clinical trials (17,18). However, the majority of studies that have evaluated the
hypocholesterolemic effects of legume consumption examined soybeans specifically rather
than the many non-soy legumes, which are more commonly consumed in the Western
hemisphere (19). Non-soy legumes include a variety of beans such as navy, pinto, kidney,
garbanzo and lima beans and peas such as split green peas or lentils. Randomized controlled
trials that have examined the potential hypocholesterolemic effects of a diet rich in non-soy
legumes have differed in their findings (20-31), with some finding no effect (22,24,31),
while other identified a significant cholesterol lowering effect (20,21,27). We conducted a
meta-analysis of randomized controlled trials to quantify the direction and magnitude of the
potential effect that consumption of non-soy legumes may have on serum cholesterol
concentrations.
METHODS
Study Selection
We searched the online databases MEDLINE (from January 1966 through July 2009) using
the following terms as medical subject headings and keywords: fabaceae not soybeans not
isoflavones and diet or dietary fiber and cholesterol or hypercholesterolemia or triglycerides
or cardiovascular diseases. An EMBASE database search (from January 1980 to July 2009)
was also performed using the database-specific medical subject headings and keywords:
legume or bean not soybean not isoflavone and dietary fiber or high fiber diet and
cholesterol or hypercholesterolemia or triacylglycerol or cardiovascular disease. Both
searches were limited to human subjects but not limited in language. The authors also
performed a search of the Cochrane Central Register of Controlled Trials with the same
search criteria and limits. A manual examination of the references in the published studies
and in suitable review articles was also performed. Experts in the field were contacted to
determine if any other studies were near completion.
The titles and abstracts of 140 studies were identified through the literature search and were
reviewed independently by two investigators (M.T.T., C.H.N.) in duplicate to determine
whether they met eligibility criteria for inclusion. Where discrepancies between
investigators occurred for inclusion or exclusion, a third investigator (L.A.B.) was involved
to conduct additional evaluation of the study, and discrepancies were resolved by consensus.
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Studies were eligible for inclusion if they met the following criteria: (1) the study design
was a randomized control trial; (2) the study had similar total energy and macronutrient
values in the control and legume diets; (3) the intervention and control groups reported total
cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), very low-
density lipoprotein (VLDL), and/or triglycerides; (4) the intervention consisted of non-soy
legume consumption; (5) the duration of intervention was at least 3 weeks; and (6) study
participants were adults.
Data abstraction
All data were independently abstracted in duplicate by 2 investigators (M.T.T., C.H.N.)
using a standardized data collection form. Discrepancies were resolved by discussion with a
third investigator (L.A.B.) and by referencing the original articles. If necessary, we
contacted authors for missing data. Publication characteristics were recorded as follows:
primary author's name, publication source and year, country of origin, study design (parallel,
factorial, or crossover trial), blinding (open, single, or double), whether there was a washout
period, if the treatment allocation was concealed, if intention-to-treat analysis was used,
study duration, sample size, percentage of male participants, mean age and range, baseline
mean levels of lipids, inclusion and exclusion criteria, and a description of legume
preparation. Dietary components for both treatment and control groups were recorded as
follows: caloric amount (kcal/d), protein (g/d), carbohydrates (g/d), total fat (g/d), saturated
fat (g/d), mono-unsaturated fat (g/d), poly-unsaturated fat (g/d), dietary cholesterol (mg/d),
total dietary fiber (g/d) and soluble dietary fiber (g/d). Mean study endpoints for the legume
and control diets were recorded for total cholesterol, HDL cholesterol, LDL cholesterol,
VLDL cholesterol, and triglycerides.
Statistical analysis
Some studies reported lipid levels in mg/dL, which required conversion to mmol/L prior to
computations. For conversion, 1 mg/dL=0.0259 mmol/L was used for cholesterol and 1 mg/
dL=0.0113 mmol/L was used for triglycerides.
The mean total cholesterol, HDL, LDL, VLDL, and triglycerides at baseline and at the end
of intervention period were used to calculate mean net changes for each study. For parallel
trials, mean net changes for the outcomes listed above were calculated as the difference
(legume diet minus control diet) of the changes (baseline minus endpoint) in mean values.
For crossover trials, mean net changes for the outcomes were calculated as the difference
(legume diet minus control diet) in values at the end of the intervention and control phases.
In studies where two amounts of the same legume were tested (23), we used the average
values from the two intervention arms for the change in cholesterol levels. One trial used a 3
phase crossover design to examine the effects of pinto beans and black-eyed peas separately
with only one control group (31). In order to avoid double use of the control group, we used
only the data from pinto beans to reduce possible between-study heterogeneity due to the
variety of legumes included in the meta-analysis.
Variance of the mean net changes of the outcomes (total cholesterol, HDL, LDL, VLDL,
and triglycerides) for each trial was calculated using standard deviations or standard errors.
To calculate pooled mean net changes, each study was assigned a weight, calculated as the
reciprocal of the variance for the mean net changes.
The homogeneity of the effect size among studies was tested using a χ2 test. Our tests
indicated homogeneity across the studies included in the meta-analysis for total cholesterol
(p=0.26) and LDL cholesterol(p=0.65), and heterogeneity across the studies included for
HDL (p=0.005), VLDL (p<0.0001), and triglycerides (p= <0.0001). Due to the
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heterogeneity identified between studies, we used DerSimonian and Laird random-effects
models, which take into account between-study variations, to calculate the pooled mean net
change of lipids comparing the legume diets with control diets (32). A meta-regression was
also performed to examine sources of heterogeneity and determine the influences of study
characteristics including age of participants, proportion of male participants, study design,
country of origin, study size, and the duration of intervention, on effect-size estimates.
To assess for potential publication bias, we constructed funnel plots for each outcome in
which the mean net change was plotted against the study size (33). In addition, Begg's rank
correlation test was used to examine the association between mean net change and its
variance, and Egger's linear regression test, which regresses z statistics on the reciprocal of
the standard error (SE) for each study, was also used to detect publication bias (34,35). We
conducted an influence analysis where each trial was excluded in turn to evaluate the
influence of that trial on the pooled estimate and determine if that study was an outlier. All
analyses were conducted in STATA version 9.2 (StataCorp, College Station, TX). We
conformed to QUOROM (Quality of Reporting of Meta-analyses) guidelines in the report of
this meta-analysis of randomized controlled trials (36).
RESULTS
Figure 1 depicts the flow of study selection for the analysis. Of the 140 potentially relevant
references identified, 117 were excluded following review of abstract and title. A total of 23
full-text articles were retrieved and reviewed for inclusion. We further excluded 8 articles
due to multiple publications from an individual trial, 1 study was shorter than 3 weeks in
duration, 1 was excluded due to lack of control diet, 2 articles were excluded because they
reported insufficient information to calculate an effect size and/or its variance and 1 was
eliminated because the control diet was an active cholesterol lowering intervention. A total
of 10 randomized controlled trials were included in this meta-analysis, representing data
collected from 268 participants.(21-26,28-31)
The baseline characteristics of the study participants and designs of the randomized
controlled trials are presented in Table 1. Out of the 10 trials, 4 were conducted in the
United States, 2 in Australia, 2 in Spain, and 1 each in Chile, and New Zealand. A total of
268 participants were included in the analysis. There were 188 men in the trials,
representing 70.1% of all participants and 5 trials had exclusively male participants. Study
participants ranged in age from 18 to 78. Participants with high, borderline high, and normal
cholesterol levels were included and no studies included participants who were taking
cholesterol-lowering drugs. Total cholesterol at baseline was reported for 8 studies and study
means ranged from 199 to 294.6 mg/dL(22-26,29-31). Mean baseline LDL- and HDL-
cholesterol were reported in 6 studies and mean LDL cholesterol ranged from 138 to 200.4
mg/dL while mean HDL cholesterol ranged from 39.0 to 58.0 mg/dL.(22-26,30,31) Trials
primarily employed the crossover design, however 2 were parallel and 1 was factorial in
design. Most trials matched macronutrient and energy content between the legume diet and
control diet groups, including amounts of saturated and total fat in the diets (Table 2).
Various non-soy legumes were represented; intervention diets included the addition of
mixed legume dishes, whole chickpeas, field beans ground into flour, whole pinto beans,
canned baked beans, whole peas, and whole navy beans, among others (Table 1).
Comparison groups consisted of calorie and macronutrient-matched control diets, often with
a wheat-based or canned vegetable substitution. Intervention durations ranged from 3 to 8
weeks. Most of the studies were conducted in free-living adults, though 1 trial was
conducted in a metabolic lab (26) and in one trial all meals were eaten at the study kitchen.
(21)
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Mean net changes and corresponding 95% CIs for total serum cholesterol were reported in
10 studies (21-26,28-31), and HDL, LDL cholesterol and triglycerides were reported in 9
studies (21-26,28,30,31). For total cholesterol, the mean net changes in each study ranged
from 1.2 to 31.4 mg/dL. The pooled mean net change from a legume diet was 11.76 mg/
dL (95%CI: 16.06, 7.47, p<0.001; Χ2 for heterogeneity p=0.26), Figure 2, Panel A. The
mean net changes for HDL cholesterol ranged from 4.03 to 5.91 mg/dL, and the pooled
mean net change was 0.85 mg/dL (95%CI: 1.62, 3.32, p=0.05; Χ2 for heterogeneity
p=0.005), Figure 2, Panel B. For serum LDL cholesterol, mean net changes ranged from
18.91 to 0.0 mg/dL and pooled mean net change was 7.98 mg/dL (95%CI: 11.41,
4.54, p<0.001; Χ2 for heterogeneity p=0.65), Figure 2, Panel C. For triglycerides, mean net
changes ranged from 43.36 to 0.80 mg/dL. Pooled mean net change for serum triglycerides
was 18.94 mg/dL (95%CI: 38.04, 0.17, p=0.05; Χ2 for heterogeneity p<0.001), Figure 2,
Panel D. Only 3 studies reported information on VLDL as an outcome measure (not shown),
and mean net changes ranged from 8.24 mg/dL to 1.00 mg/dL and the pooled mean net
change was 3.34 mg/dL (95%CI: 9.13, 2.45, p=0.26; Χ2 for heterogeneity p<0.001).
We examined the potential for publication bias by plotting sample sizes versus mean net
change for total cholesterol, HDL, LDL, VLDL, and triglycerides among the trials included
in this meta-analysis using Begg's rank correlation test (p=0.09, p=0.75, p=0.30, p=0.12 and
p=0.99 for total, HDL, LDL and VLDL cholesterol, and triglycerides, respectively) and
Egger's linear regression tests (p=0.19, p=0.53, p=0.41, p=0.01 and p=0.55 for total, HDL,
LDL and VLDL cholesterol, and triglycerides, respectively).
We also examined heterogeneity between studies. Heterogeneity among the effect sizes of
individual trials for total, LDL, HDL and VLDL cholesterol and triglycerides had I-square
values of 19.7%, 63.8%, 0%, 89.0% and 97.9% respectively. Significant heterogeneity
remained between studies for HDL and VLDL cholesterol and triglycerides, therefore, we
performed a meta-regression analysis to examine characteristics of the trials and/or their
study populations which may affect the heterogeneity in mean net change for lipid
parameters. Significant predictors (p<0.05) of the mean net change in total cholesterol
among studies included the number of male participants and the length of the intervention
phase. For LDL cholesterol, significant predictors included mean age, number of male
participants, study design, number of participants and duration of the study. For triglycerides
only mean age was a significant predictor and for HDL cholesterol none of the study
characteristics were significant predictors.
We then performed sensitivity analyses on net change of lipid concentration using gender
distribution (trials with 100% vs. <100% male participants), median duration of the
intervention (< 5 vs. 5 weeks), study design (crossover vs. parallel or factorial design), and
type of control diet (matched vs. other), shown in Table 3. In the influence analysis,
exclusion of any single study did not change the significance of the pooled estimates for
total cholesterol, LDL, HDL, VLDL, or triglycerides.
DISCUSSION
CVD remains the leading cause of death in the US and other Western countries despite
advances in care (1). Therefore, modification of risk factors is an essential part of any
strategy to decrease the number of CVD events and deaths. Our results indicate that non-soy
legume consumption has a significant beneficial effect on serum cholesterol levels, one of
the most important risk factors for CVD. Both total and LDL cholesterol decreased, while
HDL cholesterol did not change significantly, when non-soy legumes were supplemented.
On average, men, who composed the majority of participants in these study populations,
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achieved lower cholesterol levels (total and LDL) than women while consuming legume-
supplemented diets.
This meta-analysis is one of the first to assess the effects of non-soy legume supplemented
diets on measures of CVD risk such as total cholesterol, LDL, HDL, VLDL, body weight, or
BMI. We identified only one previous analysis, conducted in 2002, which examined the
cholesterol lowering effects of non-soy legumes (17). However, in the latter study,
investigators did not describe a specific search strategy, present inclusion or exclusion
criteria, forest plots, sensitivity analyses, assessments for heterogeneity among studies, or
assessments for publication bias. In addition, several new, larger randomized controlled
trials of legume supplementation have been conducted in recent years (28-31).
The majority of previous meta-analyses have focused primarily on soy-based interventions.
For example, in a recent meta-analysis of 41 randomized controlled trials examining the
effect of isolated soy protein supplementation on cholesterol levels, Reynolds et al.
identified a significant reduction in total cholesterol (5.26 mg/dL, 95%CI: 7.14, 3.38),
LDL cholesterol (4.25 mg/dL, 95%CI: 6.00, 2.50), and triglycerides, and an increase in
HDL cholesterol (0.77 mg/dL, 95% CI: 0.20, 1.34) when soy protein supplements were
incorporated into the diet of participants (19). An earlier meta-analysis by Anderson et al.
which focused on soy-based dietary interventions examined 38 controlled clinical trials,
however not all studies included in the analysis used random assignment. Also, this meta-
analysis included studies with adults and children and both isolated soy protein and textured
soy protein supplementation. The authors reported a 9.3 percent reduction in total
cholesterol (23.2 mg/dL, 95% CI: 13.5, 32.9) and 12.9 percent reduction in LDL cholesterol
(21.7 mg/dL, 95% CI: 11.2, 31.7), as well as a modest, but non-significant 2.4 percent (1.2
mg/dL, 95% CI: 3.1, 5.4) increase in HDL cholesterol (37). While soy-based
supplementation appears to be beneficial, soybean consumption is not a traditional part of
Western dietary habits whereas the consumption of other legumes and seeds is traditional.
Thus, systematically examining the potential benefits of non-soy legume consumption has
important clinical implications in Western populations. The results of our meta-analysis
shows that a non-soy legume diet have similar effects as diet employing soy-based
supplementation with significant reductions in total and LDL cholesterol.
Several components of legumes are likely to contribute to their cholesterol-lowering effects.
Soluble fiber, in particular, is thought to bind to bile acids in the intestines and prevent re-
absorption into the body. Consequently, an increase in the production of bile acids decreases
the liver pool of cholesterol and increases uptake of serum cholesterol by the liver thereby
decreasing circulating cholesterol in the blood (38). In addition, prospective epidemiologic
studies have identified an association between higher intakes of dietary total and soluble
fiber and a lower incidence of coronary heart disease events (12,39,40). Currently, the
Dietary Guidelines for Americans recommends 14 g of dietary fiber for each 1,000 kcal of
energy consumed per day (13). Legumes are a particularly good source of dietary fiber.
Among the non-soy legumes included in this meta-analysis, one-half cup of cooked beans or
peas can provide a range of dietary fiber from 4.6 g in fava beans up to 9.6 g fiber in navy
beans, with a half cup of chick peas (garbanzo beans) providing 6.2 g of total fiber, and 1.3
grams soluble dietary fiber (see Appendix 1in supplemental materials for the nutrient
content of beans included in the meta-analysis). Specific phytochemicals may also
contribute to the hypocholesterolemic effects of legumes. For instance, phytosterols, a
component of plant cell membranes, have been shown to reduce blood cholesterol levels and
are present in small to moderate amounts in many types of legumes, such as chickpeas (41).
This meta-analysis has several important strengths which lend confidence to our findings.
Given that our meta-analysis draws on the results of randomized controlled trials, findings
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are less likely to be subject to confounding and bias than those from observational studies.
We did not find strong evidence of publication bias on testing; however it should be noted
that since the studies included in the meta-analysis had small sample sizes, the random error
is likely to be more widely scattered around the mean effect. Also small studies with large
effect sizes are more likely to be published therefore, the possibly of publication bias cannot
be completely excluded. In addition, our sensitivity analysis showed minimal influence on
the combined results for any single trial. Finally, while a diversity of non-soy legumes were
included in the intervention diets, they were similar in nutrient content; the nutrient content
of the control diets were also similar to legume diets in total energy and macronutrients.
An additional strength of the present meta-analysis is that there was no evidence of
heterogeneity in effect size for total or LDL cholesterol and these two lipid levels are the
focus of the National Cholesterol Education Program (NCEP) Adult Treatment Panel III
guidelines for reducing cardiovascular risk (3). One limitation of our study may be the
sample populations included in the trials. The majority of participants were middle-aged
men and many of those participating were hypercholesterolemic. While we would expect the
underlying mechanisms to operate similarly in persons with other characteristics, for
instance women and/or those with a normal cholesterol level, we cannot be sure of this
based on the results of our meta-analysis. Further studies should be conducted which
specifically enroll women, participants from racial and ethnic minority groups, pre- and
post-menopausal women, and obese as well as normal weight participants.
Additionally, weight- loss can independently affect cholesterol levels. A recent study
demonstrated that relatively small amounts of weight loss, ranging from 5.2 to 8.9% of body
weight (approximately 5 to 8.5 kg ) produced a 2.4-7.6% (approximately 5-15 mg/dL)
decrease in total cholesterol in obese participants after 6 months of lifestyle modification
(42). Another study demonstrated that as little as 2.5%loss in body weight was associated
with a 2.2% decrease in total cholesterol over three years of lifestyle intervention (43). In
this meta-analysis, 6 of the 10 trials reported change in weight as an outcome and mean net
changes in body weight ranged from 2.6 kg to 1.3 kg (about 2 to +1% body weight)
(21,23-25,28,29). This amount of weight loss is not likely to produce the changes in
cholesterol that were demonstrated in the meta-analysis (mean net change 11.8, 95% CI
16.1, 7.5) particularly due to the relatively short duration of these trials. Similarly,
exercise and physical activity could have confounded the results; however no trials reported
physical activity measures. For the trials that mentioned physical activity (n=4), all stated
that participants were asked to maintain their normal level of activity (22,28,30,31).
In summary, this meta-analysis of randomized controlled trials provides the strongest
evidence to date that non-soy legume consumption lowers serum total and LDL cholesterol,
and therefore may lower the risk CVD. Existing dietary guidelines call for the consumption
of 3 cups of dried beans or peas per week, however current consumption is less than half
that, while consumption of starchy vegetables, primarily white potatoes, is far above current
recommendations (14). Replacing white potatoes with legumes at some meals could result in
improved cholesterol levels. Dietary modification strategies that target the reduction of risk
factors for CVD should include an increase in legume consumption in addition to other
strategies which have been of proven benefit.
Supplementary Material
Refer to Web version on PubMed Central for supplementary material.
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Acknowledgments
The sponsor had no role in the design and conduct of the study; collection, management, analysis, and interpretation
of the data; and preparation, review, or approval of the manuscript. Dr. Bazzano had full access to all of the data in
the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Dr. Tees and Dr.
Nguyen assisted in the abstraction of data and writing of the manuscript. Ms. Thompson contributed to the analysis
of the data and editorial revision of the manuscript. Dr. Winham contributed to the writing and editorial revision of
the manuscript and to identification of studies in the field.
Sources of Support: Dr. Bazzano was partially supported by Grant No. 2P20RR017659-06 from the National
Center for Research Resources (NCRR), a component of the National Institutes of Health, Bethesda, MD via the
Tulane University Hypertension and Renal Center of Excellence
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Figure 1.
Flow diagram of articles identified and evaluated during the study selection process.
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Figure 2.
Mean net change in total (Panel A), HDL (Panel B), and LDL cholesterol (Panel C) and
triglycerides (Panel D) and corresponding 95% confidence intervals by trial and pooled.
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Table 1
Baseline characteristics of participants and design characteristics of randomized controlled trials of non-soy legume consumption.
Source N Mean Age, y Men, % Total Cholesterol, mg/dL LDL, mg/dL HDL, mg/dL TG, mg/dL Type of Legume Design*Legume, g/d Length of
Intervention
(Phase), d
Type of
Control
Diet
Nervi et al, 198921 20 18-22§100 -- -- -- -- Peas, lentils C 120 30 matched
Cobiac et al,
199022 20 29-65§100 246.3 181.1 48.3 99.1 Baked beans C 440 28 spaghett
Anderson et al
199023 24 58.0 100 294.6 200.4 41.7 255.8 Baked beans C 120;162 21 matched
Mackay et al,
199224 39 28-66§56.4 266.8 161.8 44.4 134.5 Pinto, haricot, kidney F 80 42 matched
Fruhbeck et al,
199725 40 18-21§100 223.9 155.4 39.0 148.9 Field bean flour P 90 30 matched
Duane WC, 199726 9 58.0 100 204 -- -- -- Red, navy, lima,
peas, lentils C 120 42-49 matched
Pittaway et al,
200628 47 53.0 40.4 -- -- -- -- Chickpeas C 140 35 wheat
Crujeiras et al,
200729 30 36.0 57 199 -- -- -- Lentils, chickpeas,
peas, fava P -- 56 matched
Winham et al,
200730 23 45.9 43.48 218 138 58 133.0 Baked beans (Navy
beans) C 130 56 carrots
Winham et al,
200731 16 43.0 43.75 217 138 54 150.0 Pinto OR black-eyed
peas C 130 56 carrots
*P denotes parallel; C denotes crossover; F denotes factorial.
§The age range of participants were provided in lieu of a mean age.
matched denotes macronutrient and total energy contents of intervention and control diets are the same.
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Table 2
Dietary composition of non-soy legume diets as compared to control diets.
Nutrients
Study Diet Total Energy (kcal/d) Protein (g/d) Carbohydrate (g/d) Dietary Fiber (g/d) Fat (g/d) SFA (g/d) MUFA (g/d) PUFA (g/d) Dietary Cholesterol (mg/d)
Nervi et al, 198921 Legume 3219 116 438 12.4 118 -- -- -- 300
Control 3219 118 430 12.5 120 -- -- -- 302
Cobiac et al,
199022 Legume 2318 99 279 22.5 85 35 28.9 13 --
Control 2287 95 283 11 82 32.7 26.8 12.4 --
Anderson et al
199023 Legume 1855 89 204 22.6 78 25.3 32.3 10.3 415
Control 1812 89 203 12.9 77 26.3 32.3 9.5 412
Mackay et al,
199224 Legume 1710 71 227 -- 51.8 16.6 -- -- 161
Control 1664 67 221 -- 53.6 18.5 -- -- 188
Fruhbeck et al,
199725 Legume 3302 75 272 20 39 13 16 5 221
Control 3298 74 271 19 38 12 16 5 218
Duane WC, 199726 Legume -- -- -- 24.1 -- -- -- -- 350
Control -- -- -- 19.1 -- -- -- -- 350
Pittaway et al,
200628 Legume 1959 89 224 30.5 69.7 26.5 25.6 11.9 --
Control 2005 95 221 27.9 73.8 29.0 30.0 11.7 --
Crujeiras et al,
200729 Legume 1462 69 184 25 50.9 -- -- -- 81
Control 1462 69 184 18 54.3 -- -- 93
Winham et al,
200730 Legume 2046 77 262 23 73 23 16 8 211
Control 2214 91 275 21 80 27 19 8 227
Winham et al,
200731 Legume 2086 88 263 25.5 73 24 18 7.8 280
Control 2122 88 265 20.7 79 27 17 7.6 276
*SFA denotes saturated fatty acids; MUFA denotes monounsaturated fatty acids; PUFA denotes polyunsaturated fatty acids.
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Table 3
Sensitivity analysis of mean net change in serum lipid concentrations using different exclusion criteria.
Total Cholesterol LDL Cholesterol HDL Cholesterol Triglycerides
N Net Change (95% CI) I2N Net Change (95% CI) I2N Net Change (95% CI) I2N Net Change (95% CI) I2
Gender Distribution
100% male 5 −13.0 (−20.3, −5.8) 41.7% 5 −10.3 (−16.0, −4.6) 0.0% 5 0.33 (2.98, 3.64) 79.2% 5 −22.5 (−41.0, −4.0) 89.5%
<100% male 5 −10.2 (−15.1, −5.2) 0.0% 4 −6.7 (−11.0, −2.3) 0.0% 4 2.59 (0.68, 5,86) 0.0% 4 −8.0 ( −22.4, 6.3) 37.5%
Study Duration
<5 weeks 4 −14.4 (−24.2, −4.6) 54.2% 4 −9.9 (−16.7, −3.0) 10.9% 4 −0.11 (−5.2, 5.0) 84.3% 4 −24.8 (−45.2, −4.5) 90.4%
5 weeks 6 −10.1 (−14.6, −5.6) 0.0% 5 −7.2 (−11.3, −3.1) 0.0% 5 1.4 (0.2, 3.0) 0.0% 5 −7.0 (−17.3, 3.2) 29.7%
Study Design
Crossover 7 −12.0 (−17.5, −6.5) 27.4% 5 −8.2 (−11.9, −4.4) 0.0% 7 −0.25 (−1.71, 1.21) 0.0% 7 −15.8 (−29.6, −2.0) 79.9%
P* or F* 3 −11.8 (−21.3, −2.0) 30.5% 4 −6.6 (−16.1, −2.9) 17.2% 2 5.52 ( 3.20, 7.84) 0.0% 2 −24.1 (−65.6, 17.3) 90.1%
Type of Control Diet
Matched 6 −14.1 (−20.6, −7.7) 27.3% 5 −10.8 (−16.6, −4.9) 0.0% 5 1.54 (1.81, 4.88) 78.7% 5 −23.9 (−40.9, −6.9) 85.8%
Other 4 −9.2 (−14.2, −4.1) 0.0% 4 −6.5 (−10.8, −2.3) 0.0% 4 −1.17 (−4.23, 1.88) 0.0% 4 −5.9 (−17.8, 6.0) 38.7%
N=Number of Studies included in each sensitivity analysis; *P= Parallel; *F = Factorial;
Nutr Metab Cardiovasc Dis. Author manuscript; available in PMC 2012 February 1.
... As a result, increased bile acid synthesis decreases the liver's cholesterol pool and increases serum cholesterol absorption, lowering blood cholesterol levels [77]. Phytosterols, a component of plant cell membranes that have been shown to lower blood cholesterol levels, are found in low to moderate concentrations in a variety of legumes, including chickpeas [78,79]. Legumes are also high in saponins, which may help reduce cholesterol absorption from the gut [80]. ...
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Animal models form the foundation for preclinical biomedical research and will certainly do so, seeing as their life span, albeit, brief, unmistakably mimics that of humans – and further affirms the universality of the aging process. When it comes to animal models for aging research it is important to note that some organisms, such as mice, age diametrically than humans. It is also paramount to note that no single animal model is perfect; therefore, it is prudent to utilise data from both conventional and non-conventional model systems, provided the results are not skewed. The best approach to picking animal models for aging and age-related research is the multifaceted approach, which involves the use of different models. The use of model animals in aging research is risky in light of the fact that our capacity to extrapolate across the tree of life is not clear. On one hand, there are moderated pathways that direct life expectancy in creatures, including yeast, nematodes, natural product flies, and mice. On the other hand, many middle taxa across the tree of life seem not to age by any means, and there is considerable variety in aging mechanisms and patterns – once in a while, even between firmly related species. There are multitude of evidence that show that active behaviours performed by animals daily may have short-term and, sometimes, long-term physiological cost, causing an increase in oxidative stress, DNA damage, and, in some instances, reducing survivability. Quantification of physical activity (such as reproductive events, migration) and measurement of its resulting physiological costs (such as immune-compromisation, production of reactive oxygen species, DNA damage, and distortion of physiological homeostasis) is important in studying the physiology of aging. Understanding the peculiarities of very slow-aging and long-lived creatures, as well as broad comparison trends, will be critical. Aging appears to be significantly influenced by evolutionary history, ecological context, and the habitat in which an organism lives, therefore findings must be evaluated with caution and always in a comparative context. Only by continuing to apply a multi-pronged strategy that includes standard lab models, uncommon lab models, wild animals, and comparative physiological and demographic data will the mysteries of aging be unraveled.
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The present study aims at optimizing the process variables for development of horse gram flour incorporated biscuits, high in protein and dietary fiber. Box‐Behnken design was employed to optimize the levels of three independent variables viz. flour: fat ratio, % whole wheat flour (WWF) replaced by horse gram flour (HF) and baking time (minutes) and their effects were determined over the response parameters i.e. overall acceptability, fat content (g/100 g), dietary fiber (g/100 g), hardness and colour difference (ΔE). Results showed that increasing the flour: fat ratio and % of WWF replaced by HF significantly decreased (p<0.05) the overall acceptability. Fat content of biscuits was also significantly affected by the flour: fat ratio and % of HF. The hardness and dietary fiber content of biscuits was found to be positively correlated with flour: fat ratio and % WWF replaced by HF. It was observed that prolonging the baking time led to an increase (p < 0.05) in the hardness and colour difference of biscuits. The optimized nutritious biscuits were obtained at flour: fat ratio 4.15:1, 23.5 % WWF replaced by HF and baking time 29 minutes. Horse gram flour incorporated biscuits thus optimized were high in dietary fiber (9.37 g/100 g) and low in fat (16.41 g/100 g). Other responses predicted in terms of OA, hardness and colour difference (ΔE) were 7.03, 31.53 N and 8.01 respectively. The study thus explains that the under‐utilized grain legume – horse gram can be successfully incorporated to develop fiber rich nutritious biscuits with good consumer acceptability.
Article
The cholesterol-lowering benefits of two by-products of soybean processing, soy protein isolate (SPI) and soy soluble polysaccharide (SSPS), have been well known in the field, but it remains to be determined whether the combined use of both ingredients can produce synergic benefiting effects. In the work, we reported that the glycation with SSPS with increasing degrees of glycation (DG) progressively improved the potential cholesterol-lowering benefits of SPI. The cholesterol-lowering benefits were evaluated with an in vitro pepsin-trypsin digestion model, by determining the cholesterol-lowering activities (including cholesterol and bile acids binding capacities, and inhibition of micellar cholesterol solubilization) of the gastrointestinal digests. As compared with the conventional heating method (at 60 °C for 7 days under controlled relative humidity conditions), the microwave treatment was much more efficient and effective to form covalent SPI-SSPS conjugates with excellent cholesterol-lowering benefits. An extensive glycation (e.g., with DG values > 40%) significantly inhibited the hydrolysis of the proteins by the proteases, and greatly facilitated the formation of insoluble aggregates during the post digestion. The remarkably improved cholesterol-lowering benefits of the extensively glycated SPIs with SSPS could be largely attributed to the enhanced tendency to form the insoluble aggregates in the digests. In contrast, the improved benefits of the moderately glycated SPIs might be mainly associated with the formation of micelle-like SPI-SSPS conjugate assemblies in the digests. This is the first report to indicate that proteins and polysaccharides may produce synergic cholesterol-lowering benefits. Considering that both SPI and SSPS are important food ingredients, the results may have great implications for the development of plant protein-based functional foods with outstanding cholesterol-lowering benefits.
Article
There is growing evidence that cereals and legumes play important roles in the prevention of chronic diseases. Early epidemiologic studies of these associations focused on intake of dietary fiber rather than intake of grains or legumes. Generally, these studies indicated an inverse association between dietary fiber intake and risk of coronary artery disease; this observation has been replicated in recent cohort studies. Studies that focused on grain or cereal intake are fewer in number; these tend to support an inverse association between intake of whole grains and coronary artery disease. Studies on the association of dietary fiber with colon and other cancers have generally shown inverse relations, but whether these relations are attributable to cereals, other fiber sources, or other factors is less clear. Although legumes have been shown to lower blood cholesterol concentrations, epidemiologic studies are few and inconclusive regarding the association of legumes with risk of coronary artery disease. It has been hypothesized that legumes, in particular soybeans, reduce the risk of some cancers, but epidemiologic studies are equivocal in this regard. Overall, there is substantial epidemiologic evidence that dietary fiber and whole grains are associated with decreased risk of coronary artery disease and some cancers, whereas the role of legumes in these diseases appears promising but as yet inconclusive.
Article
Background: The Quality of Reporting of Meta-analyses (QUOROM) conference was convened to address standards for improving the quality of reporting of meta-analyses of clinical randomised controlled trials (RCTs). Methods: The QUOROM group consisted of 30 clinical epidemiologists, clinicians, statisticians, editors, and researchers. In conference, the group was asked to identify items they thought should be included in a checklist of standards. Whenever possible, checklist items were guided by research evidence suggesting that failure to adhere to the item proposed could lead to biased results. A modified Delphi technique was used in assessing candidate items. Findings: The conference resulted in the QUOROM statement, a checklist, and a flow diagram. The checklist describes our preferred way to present the abstract, introduction, methods, results, and discussion sections of a report of a meta-analysis. It is organised into 21 headings and subheadings regarding searches, selection, validity assessment, data abstraction, study characteristics, and quantitative data synthesis, and in the results with "trial flow", study characteristics, and quantitative data synthesis; research documentation was identified for eight of the 18 items. The flow diagram provides information about both the numbers of RCTs identified, included, and excluded and the reasons for exclusion of trials. Interpretation: We hope this report will generate further thought about ways to improve the quality of reports of meta-analyses of RCTs and that interested readers, reviewers, researchers, and editors will use the QUOROM statement and generate ideas for its improvement.
Article
The combination of sibutramine and lifestyle counseling induced a clinically and statistically significant weight loss at 6 months in all intervention groups ranging from 5.2% (SELF) to 8.9% (HF-F2F) of initial weight (from 4.5% to 7.5% by using the last observation carried forward). Therefore, we confirmed our hypothesis that overweight and obese patients lost the most weight when exposed to frequent face-to-face dietitian contact and lost the least weight when assigned to a self-help intervention. The HF-F2F group also had the highest percentage of participants who lost at least 5% of their baseline body weight (62%). These results are consistent with those of a recent study (4) that also combined sibutramine with a lifestyle modification program. The higher frequency of the behavioral intervention, which included weekly meetings during the first 18 weeks, the group format of the counseling sessions, and a higher dose of sibutramine (15 mg/d), could explain the greater weight loss seen in that study (estimated at about 11% at 6 months) (4). Contact frequency proved to be an important factor for weight-loss success in our study because for the same type of contact, the LF-F2F group, which had only monthly counseling, yielded statistically significantly lower weight loss (6.4% for repeated-measures approach and 5.4% for last observation carried forward) than did the HF-F2F group at 6 months.