ArticlePDF AvailableLiterature Review

Cereal grains, legumes, and weight management: A comprehensive review of the scientific evidence


Abstract and Figures

There is strong evidence that a diet high in whole grains is associated with lower body mass index, smaller waist circumference, and reduced risk of being overweight; that a diet high in whole grains and legumes can help reduce weight gain; and that significant weight loss is achievable with energy-controlled diets that are high in cereals and legumes. There is weak evidence that high intakes of refined grains may cause small increases in waist circumference in women. There is no evidence that low-carbohydrate diets that restrict cereal intakes offer long-term advantages for sustained weight loss. There is insufficient evidence to make clear conclusions about the protective effect of legumes on weight.
Content may be subject to copyright.
University of Wollongong
Research Online
Faculty of Health & Behavioural Sciences - Papers Faculty of Health and Behavioural Sciences
Cereal grains, legumes, and weight management: a
comprehensive review of the scientific evidence
P. G. Williams
University of Wollongong,
S. J. Grafenauer
University of Wollongong,
J. E. O'Shea
University of Wollongong,
Research Online is the open access institutional repository for the
University of Wollongong. For further information contact Manager
Repository Services:
Recommended Citation
Williams, P. G.; Grafenauer, S. J.; and O'Shea, J. E.: Cereal grains, legumes, and weight management: a comprehensive review of the
scientific evidence 2008.
Cereal grains, legumes, and weight management: a comprehensive review
of the scientific evidence
There is strong evidence that a diet high in wholegrains is associated with lower BMI, waist circumference
and risk of being overweight; that a diet high in wholegrains and legumes can help reduce weight gain; and
that significant weight loss is achievable with energy controlled diets that are high in cereals and legumes.
There is weak evidence that high intakes of refined grains may cause small increases in waist circumference in
women. There is no evidence that low carbohydrate diets that restrict cereal intakes offer long term
advantages for sustained weight loss. There is insufficient evidence to make clear conclusions about the
protective effect of legumes on weight.
cereals, grains, legumes, obesity, weight control
Publication Details
This article was originally published as Williams, PG, Gafenauer, SJ and O'Shea, JE, Cereal grains, legumes,
and weight management: a comprehensive review of the scientific evidence, Nutrition Reviews, 66(4), 2004,
This journal article is available at Research Online:
Full Title: Cereal grains, legumes and weight management:
a comprehensive review of the scientific evidence
Running Title: Grains and weight management
Authors: Peter G Williams1
Sara J Grafenauer1
Jane E O’Shea1
1 Smart Foods Centre, School of Health Sciences, University of Wollongong,
Wollongong, Australia
Guarantor and
correspondence to: A/Prof Peter Williams
Smart Foods Centre
School of Health Sciences
University of Wollongong
Wollongong NSW Australia 2522
Tel: 61 2 4221 4085
FAX: 61 2 4221 4096
Word Count: 5800
Version: V2-revised
PW was responsible for design of the study and preparation of the manuscript. SG and
JO were responsible for the literature searches.
There is strong evidence that a diet high in wholegrains is associated with lower BMI, waist
circumference and risk of being overweight; that a diet high in wholegrains and legumes can
help reduce weight gain; and that significant weight loss is achievable with energy controlled 5
diets that are high in cereals and legumes. There is weak evidence that high intakes of refined
grains may cause small increases in waist circumference in women. There is no evidence that
low carbohydrate diets that restrict cereal intakes offer long term advantages for sustained
weight loss. There is insufficient evidence to make clear conclusions about the protective
effect of legumes on weight. 10
Key Words: Cereals; grains; legumes; obesity; weight control
Overweight and obesity are key features of the metabolic syndrome and prevention of
excessive weight gain is a health priority internationally. An increased consumption of
wholegrain foods, like cereals and legumes, may protect against obesity, but there has also 5
been concern expressed that refined grain intake may directly contribute to increases in
obesity.1 It has been noted that high levels of carbohydrate consumption, especially from high
glycemic index cereals, is a relatively recent phenomenon in evolutionary terms and attention
has been drawn to the correlation between consumption of refined carbohydrate and the
increasing prevalence of obesity.2 10
Cereal grains are generally an excellent source of carbohydrate, dietary fiber, protein and are
a good source of many B-group vitamins, vitamin E, and a number of minerals – especially
iron, zinc, magnesium and phosphorus. In many countries national dietary guidelines
recommend plentiful consumption of grain foods as the basis of a healthy diet and 15
increasingly there has been emphasis placed on increasing consumption of wholegrains. One
of the key recommendations of the 2005 US Dietary Guidelines is “consume 3 or more
ounce-equivalents of wholegrain products per day, with the rest of the recommended grains
coming from enriched or wholegrain products. In general, at least half the grains should come
from whole grains”.3 20
From a consumer point of view, one of the most commonly held popular beliefs about diet is
that grains, and the carbohydrates they contain, provide excess energy to the body and are
therefore “fattening”.4 At the same time, one of the key benefits that consumers recognise
from eating a plant-based diet is the ability to help control body weight.5 There is therefore a 25
need to assess the evidence about the role of grains in the prevention and management of
overweight and obesity, to ensure health messages are evidence based and consistent with the
best research available.
Evidence base 30
While there is strong epidemiological evidence for a beneficial effect of wholegrain and
legume consumption on the risk of many chronic diseases, especially cardiovascular disease
and diabetes,6, 7 such evidence does not usually explain the mechanisms of action or
necessarily give sufficient guidance to base quantitative or qualitative recommendations. In
the case of grain foods it is unclear to what extent the fiber content, glycemic index, nutrient
density or other features (such as impact on gut flora) of the foods are the main causes of
these health effects.
Studies that have directly examined the relationship of grain intake to obesity are quite sparse. 5
They fall into three main categories: (1) cross-sectional epidemiological studies that have
noted associations between measures of overweight and obesity with either dietary patterns
that are higher in grain foods, or actual measures of particular foods; (2) prospective studies
that have measured changes in weight over time and examined associations of rates of weight
change with diet patterns, and (3) experimental clinical studies, where the intake of grain 10
foods is manipulated.
From an experimental approach, clinical trials are the gold standard in establishing cause and
effect relationships that have been potentially identified in epidemiological studies. However,
studies that aim to change one of the major components of a diet, like grains, can rarely be 15
conducted in a blind fashion and are always confounded by the inevitable consequent changes
to the nutritional profile of the diet as a result: the choice of foods that are replaced can be as
important as those that are added. Increasingly nutrition research is moving toward
examination of dietary patterns as a whole, rather than specific foods. The Dietary
Approaches to Stop Hypertension (DASH) study8 and the Lyon Diet Heart Study9 are 20
examples of this approach. However even these studies are relatively rare, and very often the
best data to base dietary recommendations is still largely epidemiological in nature – either
descriptive cross-sectional studies, or prospective studies examining changes in risk factors
over time and correlations with dietary patterns or changes.
Defining the term “wholegrain” presents difficulties in terms of analysing and interpreting all
these types of research studies and making dietary recommendations. Several epidemiological
studies have defined wholegrain foods as those products that contain 25% wholegrain
content or bran by weight.10-12 The United States Food and Drug Administration (FDA)
requires foods to contain >51% by weight of wholegrain ingredients in order to make health 30
claims.13 However neither of these definitions takes into account the structure of the grain,
and the glycemic index (GI) of wholegrain foods can vary significantly depending on their
degree of intactness. The fact that grain structure and GI are rarely considered in
epidemiological studies makes interpretation of the scientific literature imprecise.7
This paper reviews existing research regarding the role of cereal grains and legumes in the
prevention or management of overweight and obesity and considers how existing dietary
recommendations might be modified to take new information into account. We carried out a 5
search for original studies and reviews in the following databases: PubMed, Medline, Scopus,
Cinhal and ScienceDirect, from 1980 to 2005. The following search terms were used: cereal,
grain, wholegrain, legume, pulse, bread, pasta, rice, wheat, barley, oat, rye, soy, bean, pea, in
conjunction with the following terms: obesity, overweight, satiety, BMI, waist. Studies were
limited to those published in English, conducted in humans and reporting anthropometric 10
outcome measures. In addition, hand searching of references in identified papers was used to
supplement the electronic search. A total of 556 abstracts were identified for review. Of these
only 121 were directly relevant to the topic, with most others being excluded because they did
not report original data or because they only examined intermediate markers such as energy
intake or satiety hormones, rather than direct measures of overweight and obesity. Relevant 15
studies were assessed for scientific quality using the methods and criteria described by the
European Heart Network,14 and studies with a low quality rating were excluded (generally
because they lacked control groups or methods were inadequately described or validated).
This left a total of 53 eligible studies included in the final review,
Epidemiological Studies
Studies of dietary patterns
Principal component analysis and cluster analysis are two statistical techniques that have 5
become increasingly popular in the examination and description of complex dietary patterns.
There are 11 published studies that have reported analysis of dietary intakes that identified
patterns with higher levels of cereals and/or legumes. Only one of these, in a subsample of
466 men in the Health Professionals Follow-up Study, found no association between BMI and
quintiles of conformance with a prudent diet including higher intakes of wholegrains and 10
legumes.15 All the others have found such patterns to be associated with lower measures of
obesity. The studies include both male and female subjects from a wide range of age groups
(8-87 years) and in 12 different countries.
Analysis of the diets of 4999 adults in the Malmö Diet and Cancer Cohort study identified six 15
diet patterns and found that central obesity (waist circumference above reference values of
94cm in men and 80cm in women) was least likely to occur in those consuming patterns
dominated by fiber-rich bread (OR 0.79 for women and 0.58 men). There was no evidence of
increased risk with diets dominated by white bread, providing 15-18%E.16 In the UK Women’s
Cohort Study with 33971 adults, seven clusters of food consumption were identified, three 20
with high cereal levels: Health conscious (high bran, wholemeal and pulses), Low diversity
vegetarians (high wholemeal bread and pulses) and High diversity vegetarians (high
wholemeal bread, cereals, pasta and rice and pulses).17 Women with these patterns had
significantly lower average BMI values as well as the lowest proportion of obese subjects (5-
9% vs 10-12% in the other four clusters). Another UK prospective study (the Isle of Ely study, 25
with 802 adults) identified four diet patterns and found the one with high intakes of rice, pasta
and pulses was negatively correlated with waist-to-hip (WHR) ratio.18
In the US, factor analysis of dietary data from the Baltimore Longitudinal Study of Aging
(BLSA) identified six food patterns among 449 adults aged 30-80y.19 Subjects consuming a 30
fiber-rich pattern, high in non-white bread, wholegrains, beans and legumes, had the lowest
BMI, smallest waist circumference (WC) and the smallest mean annual increase in BMI. In
older adults the same pattern was also found. Cluster analysis of the diets of subjects aged 70-
77y in the cross-sectional SENECA baseline study in Europe and the Framingham Heart Study
cohort identified five dietary patterns and the two that were significantly associated with the
lowest BMI and WC were those highest in grains and legumes, nuts and seeds.20
The same relationship was found in a longitudinal survey of 8-year old Australian children; a 5
food pattern with a high consumption of cereals and bread was an independent negative
predictor of BMI in multivariate models.21 Another study that has also reported a relationship
with a prudent diet pattern is from the Danish MONICA surveys, showing that diets with
more wholegrain cereals are associated with lower BMI.22 In Brazil, factor analysis of the
diets of 2489 adults identified three patterns, including the traditional diet relying mainly on 10
rice and beans.23 This pattern was associated with a lower risk of overweight or obesity in
logistic models adjusted for dieting, age, physical activity and energy expenditure (OR 0.87).
A few studies are more difficult to interpret because of the food group patterns that were
identified. One cluster analysis of the diets of 189 US adults aged 66-87y found a high 15
nutrient-density pattern (with higher intakes of cereal, rice, pasta and beans) was associated
with a lower risk of overweight and excessive WC; but this same pattern also had a lower
intake of bread.24 A study of two other US data sets – from the Geisinger Rural Aging Study
(GRAS) and the Boston Area study – also provide some contradictory results.25 A 2-cluster
analysis of the GRAS data found individuals in a cluster with more breakfast cereal, but less 20
bread, had a lower mean WC (93.5cm vs 97.2; p<0.05), and participants in the Boston study
with a pattern high in breakfast cereals, milk and fruit had significantly lower BMI (25.9) than
those consuming a pattern high in grains, bread and poultry (27.1). The types of breads were
not distinguished in these studies.
Because of the different food clusters identified in these studies, and the fact that many do not
report details of the amounts of individual foods consumed in each, it is difficult to reach firm
conclusions from their results. The great majority of these studies find an association between
a prudent dietary pattern with higher levels of cereals and legumes with lower measures of
overweight, and therefore support current recommendations to include these foods in a 30
healthy diet. However, these studies do not provide a clear consensus on the role of bread
specifically, nor the differing effects of wholegrain versus refined cereals. They also provide
no dose-response data about the relationship. Information from cross-sectional studies, with
more quantitative estimates of intakes, is needed to address these issues.
Cross-sectional studies
16 studies have examined weight status in relation to consumption of particular grain foods.
The largest of these is the Iowa Women’s Health study of 34,942 post menopausal women,
which used the 127-item food frequency questionnaire (FFQ) from the Nurses Health Study 5
and defined wholegrain foods as those with at least 25% wholegrain or bran by weight.11, 26
At both baseline and in follow-up surveys, higher grain intake was associated with lower BMI
and lower waist-to-hip ratio (WHR). Higher refined grain intake (median 30 serves per week)
was associated with a slightly higher WHR (0.836 vs 0.842 in quintiles 1 and 5 respectively),
but there was no significant association with BMI. 10
From diet recalls collected from 9323 participants in the USDA’s 1994-96 Continuing Survey
of Food Intakes by Individuals, it has been reported that those consuming wholegrain food
were less likely to be overweight: only 7% of people consuming at least 3 serves per day of
wholegrain foods had a BMI above 25, compared to 69% of non-consumers.27 The same 15
result was found in a survey of 285 Minnesota 13-year olds. Analysis of tertiles of wholegrain
intake found significant inverse associations with BMI (Q3: 21.9 vs Q1: 23.8; p=0.05) and
WC (76.8 vs 81.4; p=0.02) after adjustment for age, sex, and race.28
Some studies have reported no adverse relationship with refined grain intake. A cross-20
sectional study with data from the Framingham Offspring Study found subjects in the upper
quintile of wholegrain intake (20.5 serves per week) had lower BMI and WHR, whereas
there was no association with refined grain intake, up to a median of 38.9 serves per week in
the highest quintile.12 In results from the 1998-99 Portuguese National Health Survey, with
over 39000 individual dietary interviews, logistic regression analysis showed bread 25
consumption (which is traditionally mostly refined) was not related to the risk of BMI >30,
while consumption of starchy foods (rice/pasta/potatoes) was protective (p<0.001).29
A cross-sectional study of 827 adults in Tehran examined quartiles of intake of whole and
refined grain foods and reported multivariate adjusted odd ratios for obesity and abdominal 30
adiposity.30 There was no relationship between consumption of either grain type and obesity,
but the odds ratio of WC above the recommended limits was 0.90 in the highest quartile of
wholegrain intake (p for trend <0.04). The relationship with refined grain intake was not
significant. In a larger sample from the same study, there was also no relationship between
energy intake from carbohydrate and BMI.31
Baseline data from 13064 adults in the prospective ARIC study of cardiovascular disease,
found White Americans in the highest quintile for cereal fiber intake (5.1g/d) had a slight but 5
significantly lower BMI of 26.4 as against 26.8 in those in the lowest quintile of cereal fiber
(2.7g/d).32 However, in the African-American cohort those in the highest quintile for cereal
fiber intake had a higher BMI than those in the lowest quintile 29.3 vs 28.7. Similar trends
were found for legume fiber. Only one other study has provided data on legume intake. In a
study of 9984 adults in Tehran, the risk of being centrally obese in men in the fourth quartile 10
of legume intake (30g/d) was significantly lower than in other quartiles, but the relationship
was not found in women.33
Most of these studies have examined intakes of cereal or legume foods in general rather than
specific types. Six studies have examined the relationship between breakfast cereal 15
consumption and obesity. The largest of these is based on data from 17881 men in the
Physicians Health Study.34 At baseline, men in the lowest category for breakfast cereal
consumption were significantly heavier than those in the highest category (BMI 24.8 vs 24.1;
p <0.0001). At the 8-year follow-up, men with higher intake of cereals, regardless of grain
type, had a significantly lower weight gain, and at 13 years those who consumed at least one 20
serving of wholegrain cereal daily had a significantly lower weight gain than those who rarely
or never ate wholegrain cereals (2.28kg compared with 1.87kg; p <0.05).
NHANES survey data from 4218 adults in 1999-2000 also shows that consumers of ready-to-
eat breakfast cereal (RTEC) ate significantly less fat and more fiber (p<0.001) than non-25
RTEC consumers for both men and women.35 There was a significantly lower prevalence of
BMI >25 among the female RTEC breakfast eaters (OR = 0.7) and linear regression analyses
indicated an inverse association between RTEC consumption and BMI in women, but not in
In the National Heart, Lung and Blood Institute Growth and Health Study of 2379 girls aged
between 9 and 19 year, after adjusting for energy intake, mean days of eating breakfast cereal
(of any kind) was negatively correlated with BMI and risk of being overweight.36 Younger
children show the same relationship. A cross-sectional survey of 603 American children aged
6-12y also found a statistically significant inverse relationship between BMI and frequency of
eating RTEC.37 Only 16% of 7-9 year old children who ate >8 serves per 14 days were
overweight, compared to 50% of those who ate 3 serves (p<0.01).
Similar relationships have been found in European populations. In Cretan adolescents 5
frequency of RTEC intake was associated with significantly lower BMI and WC.38 In Spanish
schoolchildren, it was found that overweight subjects, particularly females, omitted breakfast
more frequently and took smaller quantities of cereals than did normal weight subjects.39
Many of these cross-sectional studies have limitations based on the use of food frequency 10
questionnaires that sometimes make it difficult to clearly separate whole and refined-grain
foods. For example the standard 127-item FFQ from the Nurses Health Study includes
amongst wholegrain foods some lower fiber foods such as popcorn, couscous and breakfast
cereals with 25% wholegrain content. This may therefore underestimate the protective effects
of wholegrain foods which meet the FDA definition of more than 50% by weight. Despite this 15
limitation, these cross-sectional studies are quite consistent in demonstrating that higher
intakes of wholegrain cereals and legumes are associated with lower BMI, WC and risk of
overweight. While one major study showed a slightly higher WHR (but not BMI) with higher
consumption of refined grains, three other studies have not supported this finding.
Longitudinal studies of weight change
Examining how food intakes are associated with changes in body weight may provide even
better information on which to base recommendations. It is recognised that for many people
returning from overweight to normal weight is difficult to achieve, and in some countries
dietary recommendations now put priority on minimising further weight gain rather than 25
losing weight.40 Table 1 summarises the eight studies of this kind that were identified.
The US Health Professionals Follow-up Study has data on 27082 males, and multivariate
linear regression has examined mean weight changes over 8 years against quintiles of
wholegrain intake and various fiber types.41 A strong dose-response relationship was 30
observed, and for every 40g/d increment in wholegrain intake from all foods, weight gain was
reduced by 0.49kg. Cereal fiber intake was also inversely associated with weight gain,
independent of wholegrain (p for trend <0.001). For every 20g/d increment in cereal fiber,
weight gain was reduced by 0.81kg.
The same relationship was seen in the 6-year follow-up of 12569 males in the Multiple Factor
Risk Intervention Trial.42 Those subjects who achieved the greatest weight loss (15lb) were
those who had the highest intakes of cereals and breads (p=0.002) and those who made the
largest increases in percentage energy contribution from breads and cereals (p<0.001). There 5
was no relationship with legume intake, but overall intakes were generally very low. These
results are supported in a small study of food selection habits by 36 subjects over 2 years
following weight loss.43 Consumption of high-fiber bread was one of the key sustainable
changes in food intake amongst those who were successful in maintaining weight loss.
In large studies including women the same pattern has been reported. In a two year follow-up
in the longitudinal EPIC study with 11005 women, consumption of higher levels of cereals
(pasta, breakfast cereals, rice) predicted large weight loss of 2kg or more (OR 1.43), but
neither bread nor legume consumption was related to weight change.44 A one year prospective
study in 1379 children aged 2-5 years found bread and cereal consumption, but not fiber, 15
significantly predicted weight loss.45 There was a 0.16 kg lower weight change per year with
each additional daily serve of breads and grains.
While these studies have considered cereals and grains in general, three have separately
compared the effects of wholegrain and refined cereals, and in each case refined grains were 20
positively associated with weight increases. In the Nurses Health Study, with 74091 health
women, the relationship between changes in grain consumption and development of obesity
over 12 years was examined.46 At baseline, women who consumed in the highest quintile of
whole grains weighed approximately 0.9kg less than those in the lowest quintile. Higher
intake of wholegrains over the 10 years was associated with less average weight gain in the 2-25
4y interval between assessments (mean increase of 1.58kg in the lowest quintile vs 1.07kg in
the highest; p<0.0001). In contrast higher intakes of refined grains were related to weight gain
(0.99kg vs 1.65kg, p<0.0001).
Two other studies have used food pattern analysis to provide some evidence on the different 30
effects of wholegrain and refined grains. The BLSA Study followed 449 subjects over 7 years
and related five dietary patterns to annual changes in BMI and WC.47 There was a
significantly greater annual increase in WC (but not BMI) among subjects on the White Bread
pattern (with the highest grain intake and 15.8% total energy from white bread), compared
with the Healthy Pattern (with only 3.2%E from white bread): 1.32cm vs 0.43cm; p<0.05).
An analysis of Danish data from the MONICA study examined associations between baseline
food intake and subsequent changes in BMI-adjusted WC over 6 years.48 A higher intake of
refined bread (white and rye) was associated with gain in WC in women (0.29cm per
quintile), but not in men (where there was a non-significant inverse association). There was 5
no association with wholegrain intake.
Even with these prospective studies, their observational nature hampers straightforward
interpretation. Because changes are time dependent, we cannot be certain that changes in diet
preceded changes in weight. For example, those who had recently gained weight might 10
increase their intake of grain products when following a lower fat/high fiber diet to lose
The overall results are therefore somewhat inconsistent. Most studies have found an inverse
relationship between wholegrain intake and weight gain, but there is still very limited 15
evidence in relation to legume intake. In a few studies, higher intakes of refined grains appear
to be associated with increases in WC and BMI in women, but the weight changes, though
statistically significant, appear to be relatively minor in absolute terms (<0.7kg over a 12 year
period). Furthermore, there have been no studies that have examined the association of high
and low GI grain consumption with body weight. 20
Intervention studies
While such observational studies are useful, they can only indicate associations between diets
and health outcomes, rather than provide evidence of causal relationships. Consumption of 25
cereals or legumes may be a marker for other healthy lifestyle practices such as physical
activity, smoking avoidance and lower fat and alcohol intakes. While good quality studies
attempt to control for some of these factors, they cannot reliably be used to predict outcomes
when diet patterns are changed.
A total of 17 intervention studies were found that examined the impact of increased intakes of
grains and legumes. Six of these only measured the effects on intermediate measures such as
satiety or energy intake; the other 11 directly report changes in weight or WC and these are
summarised in Table 2.
Only a few of these studies report a better rate of weight loss when the grain intake of the diet
is increased. One small Mexican trial compared a low and a high GI diet, providing 63 vs 55 g
respectively of carbohydrate from cereals and legumes.49 The low GI diet (high in wholegrain
bread and beans, and with less white bread and rice), resulted in improved glycemic control 5
and greater weight loss. Three other studies have examined the effect of increasing the RTEC
content of the diet, either replacing one evening meal with a cereal-based meal, or as
additional snacks.50-52 All three have reported modest but favourable reductions in weight in
the RTEC-supplemented diets, but all have been relatively short-term studies and long term
outcomes are uncertain. Nonetheless, these findings support the findings from the National 10
Weight Control Registry that regular breakfast consumption and eating a low-fat high-
carbohydrate diet are some of the behaviours of successful weight-loss maintainers.53
All of the other studies have demonstrated that a diet with a high cereal content can support
weight control, although most do not find a superior rate of weight loss when compared to 15
diets with lower cereal levels. The largest and most recent of these trials compared exercise
combined with two 500 kcal hypocaloric diets, where subjects were either instructed to avoid
cereals, or to eat at least two meals per day containing fiber-rich wholegrain cereals.54 Both
diet groups lost more weight than subjects only instructed to exercise, but weight loss was not
different between the two diet groups. 20
Another RCT, with 116 overweight subjects who were prescribed two 500 kcal-restricted
diets, found a significant decrease in both weight and WC in subjects following diets with 7-8
grain serves/day (including 3-4 serves of wholegrains), compared to a control diet with only
one serve of wholegrain per day.55 However this study did not have an energy restricted 25
control diet and so, while it can be concluded that weight loss is possible following a diet
including a total of 7-8 serves of grains, no conclusions can be drawn about the relative
efficacy of this dietary pattern.
One study, comparing high protein (HP), high fat (HF) and high carbohydrate (HC) diets, 30
found subjects lost significantly more weight on the HP and HF diets, but that the subjects
including at least 6 serves of wholegrains per day on the HC diet still achieved significant
reductions in weight and waist circumference.56 Another comparison of high and low CHO
1200 kcal diets (including 7 vs 4 serves of bread per day respectively) found both led to
significant weight loss, but there was no difference in reduction in BMI between the two
Other studies with increases in particular cereals have also been carried out. Supplements of
700 kcal of both rye and wheat bread resulted in similar weight loss in one study,58 but this 5
was in a study with cancer patients that was primarily examining outcomes of cell
proliferation and plasma lignans, so the relevance to healthy subjects is unclear. An 8-month
trial adding oats to energy restricted diets for overweight healthy men and women found a
trend toward reduced hunger in the high oat group, but no difference in effects on weight
loss.59 10
There are few intervention studies directly comparing the effects of wholegrains and refined
grains. One examined the different effects of a high wholegrain versus refined grain intake (in
diets with the same percentage of energy from carbohydrate) on insulin sensitivity in
overweight and obese adults.60 The authors found lower fasting insulin levels and higher 15
satiety ratings with the wholegrain-rich diets, but no difference in weight after a 6-week
period. This finding of increased satiety (and sometimes reduced energy intake) with higher
cereal intake has been confirmed in several other studies,61-65 although one study with 10%
lupin flour added to bread reported that, although this reduced the GI, it did not affect satiety
ratings of the bread or subsequent food intakes after consumption at breakfast.66 20
In summary, there are few well controlled studies that have specifically examined the effect of
higher intakes of cereals and legumes on weight reduction or maintenance in the long term,
nor compared the effects of refined and wholegrain cereals specifically. It may be that in short
term studies, low carbohydrate diets result in greater weight loss, but those that are 25
summarised here provide consistent evidence that weight loss is still achievable in diets that
are high in cereals, especially wholegrain.
Mechanisms of action of grain foods 30
Several of the studies reported here have noted that higher grain intakes are associated with
lower total energy intakes.11 The main postulated mechanism is through the higher fiber
content of diets high in wholegrains and legumes. Higher fiber diets can affect energy balance
through intrinsic effects (energy density and palatability), hormonal effects (such as gastric
emptying and post-prandial glycemia and insulinemia) and colonic effects (such as the
influence of short chain fatty acids on satiety).67, 68
While dietary fiber appears strongly associated inversely with body weight and weight gain in
epidemiological studies, the effects of different sources of fiber and resistant starch are not 5
well established and not all of the effect of wholegrains may be explained by their fiber
content. In the Health Professionals Study, associations between wholegrain and reduced
weight gain was attenuated after adjustment for micronutrients like magnesium, and persisted
after changes in bran and fiber intakes were accounted for, suggesting additional metabolic
effects beyond the effect of the fiber content.41 10
The lower GI values of diets high in wholegrains and legumes may be another important
factor.69 Low GI foods, and wholegrains in particular, are likely to be beneficial through
promoting satiety.70 The intake of wholegrains may also slow starch digestion or absorption,
which leads to relatively lower insulin and glucose responses that favour the oxidation and 15
lipolysis of fat rather than its storage. But it needs to be noted that not all wholegrain foods
are necessarily low GI (eg, some wholemeal breads) and some refined grain breakfast cereals
with added protein have a low GI value, so the effects of wholegrain and glycemic index are
not necessarily the same.
Nonetheless, the higher GI of most refined grains may be the possible mechanism whereby
refined grains were associated with small increases in waist circumference in some studies.
Experimental data indicate that refined grain products, unlike wholegrain products, can
induce an increase in fat synthesis in animal feeding trials even when the total energy intake is
unchanged and body weight remains constant,71 so advising people they can eat an unlimited 25
amount of highly refined carbohydrate diet is probably not appropriate.
Along with wholegrains, legumes constitute another food group that has been relatively
understudied in the epidemiological context. The current evidence for recommendations about
their inclusion in a healthy diet relate to their nutrient content (low in fat, and a good source 30
of soluble fiber and protein), rather than strong evidence for their role in chronic disease
prevention. In relation to weight control, it may be that their generally low GI value is the
main benefit in weight control which may enhance satiety,72 although there have been
suggestions that alpha-amylase inhibitors in legumes may play a role as well.73
Low carbohydrate diets
With the rising rates of overweight and obesity in most of the Western world, there has been a
recent growth in diet books promoting low carbohydrate diets, such as the Atkins Diet and the
South Beach Diet, with advice to avoid grain products and providing less than 30% from 5
Since 2003 six studies of 3-12 months duration have compared conventional and low-
carbohydrate diets.75-80 They have all reported slightly better results with the low-
carbohydrate diets, with weight loss differences ranging from 3.8 to 5.8kg over 6 months. 10
However, studies that followed participants for longer found the difference lost significance
after 12 months.81 The mechanism of action of low carbohydrate diets still seems to be solely
via decreased energy intake. This probably results from the greater satiety or monotony of the
food choices and not any special metabolic effect, such as ketosis. When energy and protein
intake is kept the same, there is no difference in weight loss when very low carbohydrate and 15
low fat diets are compared.82
There are data suggesting that diets high in carbohydrate are more satiating than diets high in
fat and that voluntary energy intake is likely to be lower with high carbohydrate than high fat
diets.83 Furthermore, surveys of people who are successful at long term maintenance of 20
substantial weight loss show that they follow high-carbohydrate, low-fat diets.84 In recent
evidence-based practice guidelines, the Australian National Health and Medical Research
Council cautioned against the use of low carbohydrate diets and has concluded that a low-fat
diet with increased activity is still the best approach for obesity management.85
The findings reported here are generally consistent with other studies which have concluded
that grains and legumes are protective against heart disease and diabetes and are consistent
with public health dietary recommendations to make bread and cereals the foundation of a 5
healthy diet and to emphasise wholegrain in this context. The risk of obesity may be reduced
by replacing refined cereal sources with more wholegrain, high-fiber, and low GI grain foods,
but further randomised trials are necessary to determine the absolute effect of such
interventions and to guide new product development. Moreover, the causes of obesity are
multifactorial and the outcomes from manipulations of diet alone are likely to be influenced 10
not only by patterns of activity but also by genetic factors that may determine how a person
In the published observational studies, the highest quintiles of wholegrain intakes that are
associated with lowest risk of obesity are at levels equal to 3 serves per day. In the US, the 15
average intakes of wholegrains is less than one serving a day and less than 10 percent of
Americans consume the recommended three servings per day,87 so there is substantial
opportunity to improve the grain and legume intake of most people. Unfortunately there are
also substantial barriers to increasing the consumption of wholegrain and legume foods,88
including traditional preferences for refined product, limited availability in supermarkets and 20
foodservice settings, unfamiliarity with cooking techniques and confusion in product
Our knowledge of the relationship between grains and obesity is still incomplete and at the
recent Whole Grain and Health summit at the University of Minnesota it was recommended 25
that further research is needed into: (1) the link between wholegrains and health, (2)
development of innovative products, (3) effective communication with consumers about
wholegrain foods. Nonetheless, the totality of evidence available from research to date shows
that there is little evidence that a high consumption of grains increases the risk of obesity and
does provide strong support for continuing messages to the public that a diet high in 30
wholegrain cereals and legumes will support good overall health and is likely to help maintain
a healthy weight.
Summary points
There is good evidence from both epidemiological and intervention studies that (1) a diet high
in wholegrains is associated with lower BMI, waist circumference and risk of being 5
overweight, (2) a diet high in wholegrains and legumes can help reduce weight gain and (3)
significant weight loss is achievable with energy controlled diets that are high in cereals and
There is weak evidence that high intakes of refined grains may cause small increases in waist 10
circumference in women. There is no evidence that low carbohydrate diets that restrict cereal
intakes offer long term advantages for sustained weight loss. There is insufficient evidence to
make clear conclusions about the protective effect of legumes on weight. The levels reported
in most epidemiological studies are too low to demonstrate clear effects and there have been
no clinical trials examining the effect of increased legume intake on longer term weight 15
Go Grains Health & Nutrition Ltd sponsored this review. The authors confirm the sponsor
had no role in writing this review.
Table 1. Prospective observational studies investigating the effect of cereals or legumes on changes of weight or waist circumference
Author Subjects Study design Outcomes
Key results
Stamler & Dolecek
(1997) 42
12569 males in
the Multiple Risk
Intervention Trial
(with baseline
mean BMI 27.7)
Weight and BMI measured annually for 6 years
comparing a special intervention (SI) group
with usual care (UC). The SI group was initially
counseled in 10 weekly group session to modify
diets to reduce total and saturated fat,
cholesterol and alcohol and to increase
polyunsaturated fats Regression analyses
assessed relations between food group intakes
and weight change.
Weight loss
In both groups weight loss was associated
with increased or higher percentages of
energy from total carbohydrate and fiber
intake and, for SI men, higher percentages
of energy from starch. Subjects who
achieved the greatest weight loss (6.8kg)
had the highest energy intakes from breads
and cereals and the highest 6 year increases
in bread and cereals intake (3.5%E); those
who gained weight had the lowest overall
intakes and the smallest increases
Schultz et al (2002)
11005 women
and 6364 men in
the EPIC-
Potsdam cohort
(all non-smokers)
Large multi-centre European cohort study. 2
year changes in measured weight and diet
assessed by FFQ. Differences in mean food
group intake across weight changes were tested
using ANOVA.
Among women, large weight loss (>2kg/y)
was significantly predicted by higher
intakes of cereals (pasta, rice breakfast
cereals) with an odds ratio of 1.43 (p<0.05)
but was unrelated to bread or legume intake.
Among men there were no significant
Liu et al (2003) 46 74091 females in
the Nurses’
Health Study
The US cohort has been followed every two
years since 1976 using a validated FFQ and
self-reported weight. Data is presented from
1984-96. Multiple regression analysis examined
relationships with wholegrain and refined grain
OR of
At baseline, the mean weight of women in
the highest quintile of wholegrain intake
was 0.9kg less than those in the lowest
quintile (p<0.0001). The odds ratio for
developing obesity over 12 years was 0.81
in the highest quintile of wholegrains
(p=0.0002) and 1.18 for refined grains
Koh-Banerjee et al
(2004) 41
27082 men aged
40-75 years at
baseline in the
Follow-up Study
Longitudinal prospective study over 8 years
(1986-1994). Self-reported weights, and
validated FFQ administered in 1986, 1990 and
1994. Multivariate linear regression used to
examine changes in grain intake and weight.
Weight An increase in WG intake was inversely
associated with long-term weight gain
(p<0001). For every 40g/d increment in WG
weight gain was reduced by 0.49kg.
Association with WG persisted after
accounting for changes in bran and fiber
Newby et al
(2003a) 45
1379 healthy
children in North
Dakota aged 2-5
One year prospective study with dietary and
anthropometric data collected at 2 visits 6-12
months apart. Linear regression used to
examine associations between weight change
and food group intake.
Food group
A 0.19kg lower weight gain per year was
observed with each additional serving of
breads and grains – including rice, pasta and
breakfast cereals (p<0.001). Total fat and
fiber was not related to weight change.
Newby et al
(2003b) 47
449 healthy
subjects aged 30-
80 years in the
Study of Aging
7 year follow-up from 1984-1991. Heights and
weights were measured bi-annually. Dietary
intakes were measured with 7-day records at
entry. Cluster analysis was used to define five
dietary patterns
Mean annual change in WC was more than
3 times as great for subjects in the “white-
bread” cluster (1.32cm) as for those in the
“healthy” cluster which included the highest
levels of WG cereals and legumes (0.43cm)
Halkjaer et al
(2004) 48
1200 women and
1236 men aged
30-60 years in the
MONICA1 study
in Denmark
Height and weights were measured and a 26-
item FFQ administered in 1982, 1987 and 1993.
Multiple regression analysis examined
associations of weight change and intakes of 10
food groups.
A high intake of refined bread was
associated with 6-year increase in WC for
women, even after adjustment of BMI
(r=0.29; p<0.05). WG intake was associated
(but not significantly) with decreased WC.
Borg et al (2004) 43 36 obese men 35-
50y in a RCT to
reduce weight
with a very low
calorie and
31 month follow up with dietary assessment by
a 4 day food diary and classification of 15 food
groups used in counselling, including high-fiber
breads (to be increased) and other grain
products (to be used moderately)
Three Factor
Increased consumption of high-fiber bread
was one of the best maintained behaviour
changes and was correlated with food
restraint scores (r=36; p=0.03).
BMI, body mass index; WC, waist circumference; WG, wholegrain; FFQ, food frequency questionnaire; OR, odds ratio;
RCT, randomised controlled trial
Table 2. Intervention studies that have investigated the effect of cereals or legumes on weight or waist circumference
Author Subjects Study design Diet Outcomes
Key results
Melanson et al
180 overweight
and obese
RCT with two 12-week
phases (counselling and
1) 500 kcal hypocaloric
plus exercise (avoiding
2) Hypocaloric fiber-rich
diet with WG plus
3) Exercise only
and BMI
Hypocaloric diet with cereals resulted in
higher fiber intake (27.5 vs 17.5g
p<0.001) than low cereal diet. Weight loss
on wholegrain diet (4.7kg; p<0.001) was
not different from the diet with less cereal.
Azadbakht et al
116 overweight
men and
6-month RCT with 2
intervention diets and
one “eat as usual”
1) 500 kcal restriction
(3serves WG/d)
2) 500 kcal restricted
DASH diet (4 serves
and WC
Reduced weight (13-16kg) and WC (5-
7cm) (p<0.04) in the two intervention
diets compared to a control
McAuley et al
96 overweight
insulin resistant
RCT with 8 weeks
weight loss and 16
weeks maintenance
High Fat (Atkins) diet,
High Protein (Zone) diet,
High CHO (at least 6
serves of wholegrain)
BMI and
Subjects on the HP and HF diet lost
significantly more weight and WC by 24
weeks (6.9kg/8.8cm and 7.1kg/9.8cm;
respectively; compared to those on the HC
diet (4.7kg/6.9); p<0.01.
Waller et al
62 healthy men
and women
4 week RCT 1 cup of breakfast cereal
with milk consumed 90min
after dinner meal
Weight No significant difference between groups
overall, but high compliance subjects lost
more weight (-1.85kg) than non-compliers
(-0.39kg) p=0.06
Jimenez-Cruz et
al (2003)49
14 overweight
subjects with
type 2 diabetes
Randomised 6 week
crossover trial
Low and high GI diets.
Low GI diet was high in
wholegrain bread and
and BMI
Reduction of BMI by 0.6 and weight
(1.5kg) (p=0.04) in low-GI period. No
change during high-GI period.
Bylund et al
18 men with
prostate cancer
12 week RCT pilot
study with added bread
700 kcal rye or wheat soft
bread and crispbreads as
part of a 30%E fat diet.
Weight Weight decreased significantly in both
groups rye (1.1kg) and wheat (1.5kg)
Pereira et al
11 diabetic
overweight men
and women
Randomised controlled
cross-ever trial with
food provided for two
6–week periods
Wholegrain diet (28g/d
dietary fiber) vs Refined
grain diet (18g/d fiber).
Both 54%E CHO
No difference in weight between diets;
fasting insulin less on wholegrain and
satiety higher
Mattes (2002)51 109 overweight
mean and
RCT with 2 week
RTEC supplementation
phase and 4 week
Volumetric diet phase,
compared to 2 control
1 serve RTEC (either
Special K or a variety) with
skim milk and one serve
fruit replacing either lunch
or dinner
Fat mass
Losses of 1.91kg and 1.37kg in the two
RTEC groups was mostly in fat mass and
significantly greater than control groups
(p<0.05). No change in control groups
Saltzman et al
52 healthy men
and women,
both normal and
8-month RCT 2 energy restricted diets,
one with 45g
Weight Both groups lost weight but no difference
with higher oat content
Kirk et al
22 overweight
2 weeks replacing one
meal with breakfast
cereal, followed by 4
weeks ad lib high
carbohydrate regime
Stage 1: 45g RTEC with
skim milk
Stage 2: encouraged to use
RTEC as snack
Weight Weight loss of 2kg (p<0.001) in
intervention phase maintained over 4
weeks of high CHO diet
Lean et al
110 overweight
6-month RCT
outpatients with 12
month follow-up
1200 kcal high
carbohydrate diet (58%E: 7
serves of bread/d) vs low
carbohydrate (35%E; 4
serves of bread/d)
BMI and
6 month reductions in BMI (-2.2) and WC
(-5.7cm) on high CHO diet (p<0.001) not
significantly different to low CHO diet
BMI, body mass index; CHO, carbohydrate; DASH, Dietary Approaches to Stop Hypertension; HC, high carbohydrate; HF, high fat; HP, high
protein; GI, glycemic index; RCT, randomised controlled trial; RTEC, ready-to-eat cereal; WC, waist circumference; WG, wholegrain
1. Koh-Banerjee P Rimm E. Whole grain consumption and weight gain: a review
of the epidemiological evidence, possible mechanisms and opportunities for
further research. Proc Nutr Soc 2003;62:25-29.
2. Gross L, Li L, Ford E et al. Increased consumption of refined carbohydrates
and the epidemic of type 2 diabetes in the United States: an ecologic
assessment. Am J Clin Nutr 2004;79:774-779.
3. US Department of Agriculture (USDA) Department of Health and Human
Services(HHS). Dietary Guidelines for Americans 2005. 2005 [cited 20
February 2006]; Available from:
4. Stephen A. Grains and health - an update. Can J Diet Prac Res 2003;64:G1-
5. Lea E, Crawford D Worsley A. Consumers' readiness to eat a plant-based diet.
Eur J Clin Nutr 2006;60:342-351.
6. Flight I Clifton P. Cereal grains and legumes in the prevention of coronary
heart disease and stroke: a review of the literature. Eur J Clin Nutr
7. Venn B Mann J. Cereal grains, legumes and diabetes. Eur J Clin Nutr
8. Appel L, Moore T, Obarzanek E et al. A clinical trial of the effects of dietary
patterns on blood pressure: DASH Collaborative Research Group. New Eng J
Med 1997;336:1117-1124.
9. de Longeril M, Salen P, JL M et al. Mediterranean diet, traditional risk factors,
and the rate of cardiovascular complications after myocardial infarction: final
report of the Lyon Diet Heart Study. Circulation 1999;99:779-785.
10. Liu, S, Manson J, Stampfer M et al. A prospective study of whole-grain intake
and risk of type 2 diabetes mellitus in US women. Am J Public Health
11. Meyer KA, Kushi LH, Jacobs DR, Jr. et al. Carbohydrates, dietary fiber, and
incident type 2 diabetes in older women. Am J Clin Nutr 2000;71:921-930.
12. McKeown NM, Meigs J, Liu S et al. Whole-grain intake is favorably
associated with metabolic risk factors for type 2 diabetes and cardiovascular
disease in the Framingham Offspring Study. Am J Clin Nutr 2002;76:390-8.
13. FDA. Health claim notification for whole grain foods. 1999 [cited 10 January
2006]; Available from:
14. Cowburn G Stockley L. A systematic review of the research on consumer
understanding of nutrition labelling. Brussels: European Heart Network, 2003.
15. Fung T, Rimm E, Speigelman D et al. Association between dietary patterns
and plasma biomarkers of obesity and cardiovascular disease risk. Am J Clin
Nutr 2001;73:61-67.
16. Wirfalt E, Hedblad B, Guliberg B et al. Food patterns and components of the
metabolic syndrome in men and women: a cross-sectional study within the
Malmo Diet and Cancer Cohort. Am J Epidemiol 2001;154:1150-1159.
17. Greenwood D, Cade J, Draper A et al. Seven unique food consumption
patterns identified among women in the UK Women's Cohort Study. Eur J
Clin Nutr 2000;54:314-320.
18. Williams D, Prevost A, Whichelow M et al. A cross-sectional study of dietary
patterns with glucose intolerance and other features of the metabolic
syndrome. Br J Nutr 2000;83:257-266.
19. Newby P, Muller D, Hallfrisch J et al. Food patterns measured by factor
analysis and anthropometric changes in adults. Am J Clin Nutr 2004;80:504-
20. Haveman-Nies A, Tucker K, De Groot L et al. Evaluation of dietary quality in
relationship to nutritional and lifestyle factors in elderly people in the US
Framingham Heart Study and the European SENECA study. Eur J Clin Nutr
21. Burke V, Beilin L, Simmer K et al. Predictors of body mass index and
associations with cardiovascular risk factors in Australian children: a
prospective cohort study. Int J Obes 2005;29:15-23.
22. Osler M, Heitmann B, Holdrup S et al. Food intake patterns, self rated health
and mortality in Danish men and women. A prospective observational study. J
Epidem Community Health 2001;55:399-403.
23. Sichieri R. Dietary patterns and their associations with obesity in the Brazilian
City of Rio de Janeiro. Obesity Res 2002;10:42-48.
24. Ledikwe J, Smiciklas-Wright H, Mitchell D et al. Dietary patterns of rural
older adults are associated with weight and nutritional status. J Am Geriatr
Soc 2004;52:589-595.
25. Smiciklas-Wright H, Mitchell D Tucker K. Association of weight status with
dietary patterns in older adults. Top Clin Med 2004;19:193-199.
26. Jacobs DR, Jr., Meyer KA, Kushi LH et al. Whole-grain intake may reduce the
risk of ischemic heart disease death in postmenopausal women: the Iowa
Women's Health Study. Am J Clin Nutr 1998;68:248-257.
27. Cleveland L, Moshfegh A, Albertson A et al. Dietary intake of whole grains. J
Am Coll Nutr 2000;19:331S-338S.
28. Steffen L, Jacobs D, Murtaugh M et al. Whole grain intake is associated with
lower body mass and greater insulin sensitivity among adolescents. Am J
Epidemiol 2003;158:243-250.
29. Moreira P Padrao P. Educational, economic and dietary determinants of
obesity in Portuguese adults: a cross-sectional study. Eating Behav
30. Esmaillzadeh A, Mirmiran P Azizi F. Whole-grain consumption and the
metabolic syndrome: a favourable association in Tehranian adults. Eur J Clin
Nutr 2005;59:353-362.
31. Mirmiran P, Esmaillzadeh A Azizi F. Diet composition and body mass index
in Tehranian adults. Asia Pacific J Clin Nutr 2006;15:224-230.
32. Stevens J, Kyungmi A, Juhaeri et al. Dietary fiber intake and glycemic index
and incidence of diabetes in African-American and White adults. Diabetes
Care 2002;25:1715-1721.
33. Azadbakht L, Mirmiran P, Shiva N et al. General obesity and central adiposity
in a representative sample of Tehranian adults: prevalence and determinants.
Int J Vit Nutr Res 2005;75:297-304.
34. Bazzano LA, Song Y, Bubes V et al. Dietary intake of whole and refined grain
breakfast cereals and weight gain in men. Obesity Res 2005;13:1952-1960.
35. Song W, Chun O, Obayashi S et al. Is consumption of breakfast associated
with body mass index in US adults? J Am Diet Assoc 2005;105:1373-1382.
36. Barton A, Eldridge A, Thompson D et al. The relationship of breakfast and
cereal consumption to nutrient intake and body mass index: the National
Heart, Lung and Blood Institute Growth and Health Study. J Am Diet Assoc
37. Albertson A, Anderson G, Crockett P et al. Ready-to-eat cereal consumption:
its relationship with BMI and nutrient intake of children aged 4 to 12 years. J
Am Diet Assoc 2003;103:1613-1619.
38. Kafatos A, Linardakis M, Bertsias G et al. Consumption of ready-to-eat
cereals in relation to health and diet indicators among school adolescents in
Crete, Greece. Ann Nutr Metab 2004;49:165-172.
39. Ortega R, Ortega A, Lopez-Sobaler A et al. Differences in the breakfast habits
of overweight/obese and normal weight schoolchildren. Int J Vit Nutr Res
40. National Health and Medical Research Council. Food for Health: Dietary
Guidelines for Australian Adults. Canberra: NH&MRC, 2003.
41. Koh-Banerjee P, Franz M, Sampson L et al. Changes in whole-grain, bran, and
cereal fiber consumption in relation to 8-y weight gain among men. Am J Clin
Nutr 2004;80:1237-1245.
42. Stamler J Dolecek T. Relation of food and nutrient intakes to body mass in the
special intervention and usual care groups in the Multiple Risk Factor
Intervention Trial. Am J Clin Nutr 1997;65:366S-373.
43. Borg P, Fogelholm M Kukkonen-Harjula K. Food selection and eating
behaviour during weight maintenance intervention and 2-y follow-up in obese
men. Eur J Clin Nutr 2004;28:1548-1554.
44. Schulz M, Kroke A, Liese AD et al. Food groups as predictors for short-term
weight changes in men and women of the EPIC-Potsdam Cohort. J. Nutr.
45. Newby P, Peterson K, Berkey C et al. Dietary composition and weight gain
among low-income preschool children. Arch Pediatr Adolesc Med
46. Liu S, Willett WC, Manson JE et al. 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;78:920-927.
47. Newby P, Muller D, Hallfrisch J et al. Dietary patterns and changes in body
mass index and waist circumference in adults. Am J Clin Nutr 2003;77:1417-
48. Halkjaer A, Sorenson T, Tjonneland A et al. Food and drinking patterns as
predictors of 6-year BMI-adjusted changes in waist circumference. Br J Nutr
49. Jimenez-Cruz A, Bacardi-Gascon M, Turnbull W et al. A flexible, low-
glycemic index, Mexican-style diet in overweight and obese subjects with type
2 diabetes improves metabolic parameters during a 6-week treatment period.
Diabetes Care 2003;26:1967-1970.
50. Waller S, Vander J, Klurfeld D et al. Evening ready-to-eat cereal consumption
contributes to weight management. J Am Coll Nutr 2004;23:316-321.
51. Mattes R. Ready-to-eat cereal used as a meal replacement promotes weight
loss in humans. J Am Coll Nutr 2002;21:570-577.
52. Kirk T, Crombie N Cursiter M. Promotion of dietary carbohydrate as an
approach to weight maintenance after initial weight loss: a pilot study. J Hum
Nutr Diet 2000;13:277-285.
53. Wyatt H, Grunwald G, Mosca C et al. Long-term weight loss and breakfast in
subjects in the National Weight Control Registry. Obes Res 2002;10:78-82.
54. Melansen K, Angelopoulos T, Nguyen V et al. Consumption of whole-grain
cereals during weight loss: effects on dietary quality, dietary fiber,
magnesium, vitamin B-6 and obesity. J Am Diet Assoc 2006;106:1380-1388.
55. Azadbakht L, Azizi T, Mirmiran P et al. Beneficial effects of a Dietary
Approaches to Stop Hypertension eating plan on features of the metabolic
syndrome. Diabetes Care 2005;28:2823-2831.
56. McAuley K, Hopkins C, Smith K et al. Comparison of high-fat and high-
protein diets with a high-carbohydrate diet in insulin-resistant obese women.
Diabetol 2005;48:8-16.
57. Lean M, Han T, Prvan T et al. Weight loss with high and low carbohydrate
1200kcal diets in free living women. Eur J Clin Nutr 1997;51:243-248.
58. Bylund A, Lundin E, Zhang J et al. Randomised controlled short-term
intervention pilot study on rye bran bread in prostate cancer. Eur J Canc Prev
59. Saltzman E, Moriguti J, Das S et al. Effects of a cereal rich in soluble fiber on
body composition and dietary compliance during consumption of a
hypocaloric diet. J Am Coll Nutr 2001;20:50-57.
60. Pereira M, Jacobs D, Pins J et al. Effect of whole grains on insulin sensitivity
in overweight hyperinsulinemic adults. Am J Clin Nutr 2002;75:848-855.
61. Holt S, Delargy H, Lawton C et al. The effects of high-carbohydrate vs high-
fat breakfasts on feelings of fullness and alertness, and subsequent food intake.
Int J Food Sci Nutr 1999;50:13-28.
62. Levine A, Tallman J, Grace M et al. Effect of breakfast cereal on short-term
food intake. Am J Clin Nutr 1989;50:1303-7.
63. Berti C, Riso P, Brusamolino A et al. Effect of appetite control of minor cereal
and pseudocereal products. Br J Nutr 2005;94:850-858.
64. Turconi G, Bazzano R, Caramella R et al. The effects of high intakes of fibre
ingested at breakfast on satiety. Eur J Clin Nutr 1995;49(Suppl 3):S281-S285.
65. Warren J, Henry J Simonite V. Low glycemic index breakfasts and reduced
food intake in preadolescent children. Pediatr 2003;112:1174-5.
66. Hall R, Thomas S Johnson S. Australian sweet lupin flour addition reduces the
glycaemic index of a white bread breakfast without affecting palatability in
healthy human volunteers. Asia Pacific J Clin Nutr 2005;14:91-91.
67. Swinburn B, Caterson I, Seidel J et al. Diet, nutrition and the prevention of
excess weight gain and obesity. Pub Health Nutr 2004;71:123-146.
68. Slavin J. Dietary fiber and body weight. Nutr 2005;21:411-418.
69. Brand-Miller JC, Holt SHA, Pawlak DB et al. Glycemic index and obesity.
Am J Clin Nutr 2002;76:281S-285.
70. Slavin J, Martini M, Jacobs D et al. Plausible mechanisms for the
protectiveness of whole grains. Am J Clin Nutr 1999;70(suppl):459S-463S.
71. Pawlak D, Bryson J, Denyer G et al. High glycemic index starch promotes
hypersecretion of insulin and higher body fat in rats without affecting insulin
sensitivity. Journal of Nutrition 2001;131:99-104.
72. Geil P Anderson M. Nutrition and health implications of dry beans: a review.
J Am Coll Nutr 1994;13:549-558.
73. Duranti M. Grain legume proteins and nutraceutical properties. Fitoterapia
74. Kennedy E, Bowman S, Spence J et al. Popular diets: correlation to health,
nutrition and obesity. J Am Diet Assoc 2001;101:411-420.
75. Dansinger M, Gleason J, Griffith J et al. Comparison of the Atkins, Ornish,
Weight Watchers, and Zone diets for weight loss and heart disease risk
reduction: a randomized trial. JAMA 2005;293:43-53.
76. Brehm B, Seeley R, Daniels S et al. A randomized trial comparing very low
carbohydrate diet and a calorie-restricted low fat diet on body weight and
cardiovascular risk factors in healthy women. J Clin Endocrinol Metab
77. Samaha F, Iqbal N, Seshadri P et al. A low-carbohydrate as compared with a
low-fat diet in severe obesity. New Eng J Med 2003;348:2074-2081.
78. Sondike S, Copperman N Jacobson M. Effects of a low-carbohydrate diet on
weight loss and cardiovascular risk factors in overweight adolescents. J
Paediatr 2003;142:253-258.
79. Foster G, Wyatt H, Hill J et al. A randomized trial of a low-carbohydrate diet
for obesity. New Eng J Med 2003;348:2082-2090.
80. Yancy W, Olsen M, Guyton J et al. A low-carbohydrate, ketogenic diet versus
a low-fat diet to treat obesity and hyperlipidemia: a randomized, controlled
trial. Arch Intern Med 2004;140:769-777.
81. Nordmann A, Nordmann A, Briel M et al. Effects of low-carbohydrate vs low-
fat diets on weight loss and cardiovascular risk factors. Arch Intern Med
82. Segal-Isaacson C, Johnson S, Tomuta V et al. A randomized trial comparing
low-fat and low-carbohydrate diets matched for energy and protein. Obesity
Res 2004;12:130S-140.
83. Horton T, Drougas H, Brachey A et al. Fat and carbohydrate overfeeding in
humans: different effects on energy storage. Am J Clin Nutr 1995;62:19-29.
84. Klem M, Wing R, McGuire M et al. A descriptive study of individuals
successful at long-term maintenance of substantial weight loss. Am J Clin Nutr
85. National Health and Medical Research Council. Clinical practice guidelines
for the management of overweight and obesity in adults. Canberra:
NH&MRC, 2003.
86. Friedrich M. Better strategies sought against obesity. JAMA 2006;296:1577-
87. Edge M, Jones J Marquart L. A new life for whole grains. J Am Diet Assoc
88. Adams J Engstrom A. Helping consumers achieve recommended intakes of
whole grain foods. J Am Coll Nutr 2000;19:339S-344S.
... Moreover, another study showed that soy protein is at least as good as other protein sources for weight loss during low-calorie dietary interventions in older adults [11]. Nevertheless, some studies have also shown that the protective effect of legumes on weight remains insufficient [25][26][27]. In addition, a systematic review and meta-analysis suggested that soy had no statistically significant effect on weight in the general population, yet an obesogenic effect of soy was observed in obese subjects (BMI ≥ 30 kg/m 2 ) and participants whose daily soy food intake included at least 40 g of soy protein [28]. ...
... Another study recorded significant changes in the median percentage of body weight (−1.5%, p = 0.005) and BMI (−1.5%, p = 0.05) in the soy group [24]. There are also studies reporting that the protective effect of legumes, including soy food, beans, and soy dietary supplements, on weight is still insufficient [25][26][27]. Moreover, some studies present conflicting results. ...
Full-text available
The associations between soy food intake and cardio-metabolic risk factors in children remain unclear due to limited evidence. We aim to explore soy food intake and its association with the risks of obesity and hypertension in Chinese children and adolescents. A total of 10,536 children and adolescents aged 7-18 years (5125 boys and 5411 girls) were enrolled in a cross-sectional study in Guangzhou City, southern China. Data on demographic characteristics and dietary consumption were collected using self-reported questionnaires, and anthropometric characteristics were measured. Obesity, abdominal obesity, and hypertension were defined using Chinese criteria for children and adolescents. A multiple logistic regression model was applied to estimate the association between soy food intake and obesity and hypertension. Roughly 39.5% of the participants consumed soy food more than three times per week. The mean amounts of liquid and solid soy food intake were 0.35 ± 0.54 cups/day and 0.46 ± 0.63 servings/day, respectively. The adjusted odds ratios (OR) of hypertension among those with high liquid soy food intake and a high frequency of all soy food intake (more than three times/week) were 0.79 (95% confidence interval (CI), 0.67-0.94), and 0.83 (95% CI, 0.70-0.97) compared to those with no intake. Additionally, the adjusted OR of obesity among those with high solid soy food intake and a high frequency of all soy food intake were 1.34 (95% CI, 1.09-1.63) and 1.30 (95% CI, 1.07-1.58), respectively. In conclusion, 39.5% of southern Chinese children and adolescents had high soy food intake (more than three times/week), which was significantly associated with a lower prevalence of hypertension and a greater prevalence of obesity.
... The decline in bread consumption might be due to the general public belief that "bread fattens" [5,6], or to its high glycemic index compared to other cereal-based products, such as pasta [7,8]. However, it is worth pointing out that a correlation between bread consumption and weight gain has not been established so far [4,8,9]. ...
... In this scenario, to broaden the knowledge on the relation between information on the food pack and the overall nutritional quality of products, on 2018 the Food Labelling of Italian Products (FLIP) project was conceived by the Working Group SINU (Italian Society of Human Nutrition) Young, with the aim of systematically evaluating the nutritional quality of commercial foods sold on the Italian market. The aim of the present work was to investigate the nutritional declaration of pre-packed bread and bread substitute categories mainly sold in Italy, by collecting their nutritional information from Foods 2020, 9,1905 3 of 13 their food label. Then, we aimed at comparing differences in energy and nutrient content within bread and bread substitute categories, whereby products were classified for different characteristics: type of product, GF declaration and presence of NHC. ...
Full-text available
Bread is one of the most common staple foods, despite the increasing consumption of the so-called “bread substitutes”. The aim of the present work is to survey the nutritional quality intended as a nutrition declaration of 339 pre-packed bread products and 1020 bread substitutes sold in the major retailers present on the Italian market. Comparisons of energy, macronutrient, and salt content within product types, and between regular and gluten-free (GF) products and products with or without nutrition claim (NC) and health claim (HC) declarations, were performed. A high inter-product variability was detected. The median energy contents were 274 (interquartile range 255–289) and 412 (380–437) kcal/100 for bread products and substitutes, respectively. Irrespective of the category, GF products had lower amounts of energy than their gluten-containing counterpart (p < 0.001), whereas products carrying NC had lower energy, sugar and salt amounts than the products without these declarations on the pack (p < 0.001 for all). A strong positive correlation was observed between energy and carbohydrate in bread (rho = 0.73, p < 0.001), but not in substitutes (rho = 0.033, p = 0.29). The present work highlighted a high variability in the apparent nutritional quality of bread products and substitutes sold on the Italian market, and suggested that bread alternatives should not be considered tout court as substitutes from a nutritional point of view.
... Overall, the majority of individual investigations studying the relationship between legume intake and body weight and body fat have resulted in nonsignificant findings. As part of a comprehensive literature review, Williams et al. concluded, " ere is insufficient evidence to make clear conclusions about the protective effect of legumes on weight" [12]. Failure to find significant evidence could be partially due to the use of small sample sizes and the lack of statistical power. ...
... However, when combined using meta-analysis, results have been promising [2,10]. On the other hand, Williams indicates that there is not sufficient evidence to conclude that legumes help with weight management [12]. As mentioned previously, the problem may be that most individual RCTs have lacked statistical power, as sample sizes have been modest, at best. ...
Full-text available
Beans and other legumes have multiple nutritional qualities that reduce the risk of many diseases. However, the link between legume intake and obesity remains unclear. Therefore, the present study was designed to examine the association between bean intake, body fat percentage (BF%), and waist circumference, in 246 women. BF% was measured using dual-energy X-ray absorptiometry (DXA). Bean intake was assessed using the Block Food Frequency Questionnaire and indexed using total cups of bean-based food items and also factor scores derived from a factor analysis showing adherence to a bean-based dietary pattern. Bean consumption was expressed as cups per 1000 kilocalories. R\egression results showed that the relationship between bean intake (total cups) and BF% was inverse and linear (F = 7.4, P=0.0069). Moreover, with bean consumption being divided into tertiles, there were mean differences across groups in BF% (F = 7.4, P=0.0008) and waist circumference (F = 4.2, P=0.0164). Specifically, women who consumed moderate or high amounts of beans had less body fat and smaller waists than those with low intakes. Similarly, using tertiles to categorize participants based on adherence to a bean-based dietary pattern, developed using factor analysis, those with low adherence had higher BF% (F = 7.9, P=0.0005) and larger waists (F = 4.5, P=0.0118) than their counterparts. The associations remained significant after adjusting for potential confounders. In conclusion, beans and other legumes seem to have dietary qualities that may be beneficial in the battle against obesity.
... Epidemiologic studies provide evidence that diets high in whole grains are associated with reduced risk of type 2 diabetes (Anderson & Conley, 2007;Montonen, Knekt, Järvinen, Aromaa, & Reunanen, 2003;Murtaugh, Jacobs, Jacob, Steffen, & Marquart, 2003), cardiovascular disease (Seal & Brownlee, 2010;Slavin, 2007), certain types of cancers (Jacobs, Marquart, Slavin, & Kushi, 1998;Mclntosh, 2007), and obesity (McKeown, Serdula, & Liu, 2007; Van de Vijver, Van den Bosch, Van den Brandt, & Goldbohm, 2009;Williams, Grafenauer, & O'Shea, 2008). ...
... Obesity is associated with the Western diet [1], as eating patterns in Western industrialized countries are characterized by high energy consumption and chronic over-consumption of saturated fat, cholesterol, sugar and salt, which is also related to the development of other pathologies such as diabetes, cardiovascular and degenerative disorders, cancer, hepatic steatosis and obesity, that are hallmarks of the metabolic syndrome [2][3][4]. In this context, it has been proposed that weight loss could be achieved by consuming controlled energy diets with a high content of cereals and legumes [5]. Legumes have long been an important component of the human diet because of their content in protein, carbohydrates (mainly in the form of starch) and many other nutrients [6]. ...
Full-text available
Legume consumption has been reported to induce beneficial effects on obesity-associated metabolic disorders, but the underlying mechanisms have not been fully clarified. In the current work, pea (Pisum sativum L.) seed meal proteins (albumins, legumins and vicilins) were isolated, submitted to a simulated gastrointestinal digestion, and the effects of their hydrolysates (pea albumins hydrolysates (PAH), pea legumins hydrolysates (PLH) and pea vicilin hydrolysates (PVH), respectively) on 3T3-L1 murine pre-adipocytes were investigated. The pea vicilin hydrolysate (PVH), but not native pea vicilins, increased lipid accumulation during adipocyte differentiation. PVH also increased the mRNA expression levels of the adipocyte fatty acid-binding protein (aP2) and decreased that of pre-adipocyte factor-1 (Pref-1) (a pre-adipocyte marker gene), suggesting that PVH promotes adipocyte differentiation. Moreover, PVH induced adiponectin and insulin-responsive glucose transporter 4 (GLUT4) and stimulated glucose uptake. The expression levels of peroxisome proliferator-activated receptor γ (PPARγ), a key regulator of adipocyte differentiation, were up-regulated in 3T3-L1 cells treated with PVH during adipocyte differentiation. Finally, PVH exhibited PPARγ ligand activity. Lactalbumin or other pea hydrolysates (PAH, PLH) did not exhibit such effects. These findings show that PVH stimulates adipocyte differentiation via, at least in part, the up-regulation of PPARγ expression levels and ligand activity. These effects of PVH might be relevant in the context of the beneficial health effects of legume consumption in obesity-associated metabolic disorders.
Full-text available
Refined grains are included as part of an unhealthy, or Western, dietary pattern, which has been shown to be associated with increased risk of cardiovascular disease (CVD). To clarify the association between refined grain intake and CVD risk, Pubmed and Scopus databases were searched for relevant cohort studies from database inception to June 30, 2022. Only studies that examined refined grains as a distinct consumption category and not as part of a dietary pattern, were included. Meta-analyses were performed using Cochrane's RevMan 5.4.1 software, applying inverse variance risk ratios in random effects models for each outcome of interest. Heterogeneity was assessed with Cochrane's Q (chi²) and I² statistics. Meta-analyses of hazard ratios (HR) and 95% confidence intervals (CI) obtained from 17 prospective cohort studies (>875,000 participants) indicated that refined grain intake was not associated with risk of CVD (HR = 1.08, 95% CI, 0.99-1.18, I² = 70%; 9 cohorts), stroke (HR = 1.06, 95% CI 0.92-1.23, I² = 25%; 9 cohorts), or heart failure (HR = 0.95, 95% CI 0.77-1.16, I² = 10%; 5 cohorts). White rice intake was also not associated with risk of CVD (HR = 0.93, 95% CI 0.86-1.00, I² = 25%; 5 cohorts) or stroke (HR = 1.03, 95% CI 0.93-1.14, I² = 22%; 7 cohorts). No significant publication bias was evident (Egger's test P values all > 0.05). The lack of association between refined grain intake and CVD risk was observed in meta-analyses of studies that restricted analyses to only staple grain foods (e.g., bread, cereal, pasta, white rice), as well as for meta-analyses of studies that included both staple and indulgent grain foods (e.g., cakes, cookies, doughnuts, brownies, muffins, pastries). Probable confounding from unmeasured variables in studies included in the meta-analyses diminishes the overall quality of evidence. Although refined grains are included as a component of the Western dietary pattern, the results of the meta-analyses suggest that refined grains do not contribute to the higher CVD risk associated with this unhealthy dietary pattern. This information should be considered in formulation of future dietary recommendations
Full-text available
Background/objectives Epidemiological studies suggest that whole grain intake has inverse associations with low-grade inflammation, but findings regarding refined grains are inconclusive. Our objective was to investigate whether consumption of whole or refined grains is associated with serum high sensitivity CRP (hs-CRP). Subjects/methods The study included 756 generally healthy men and women aged 53–73 years from the Kuopio Ischaemic Heart Disease Risk Factory Study, examined in 1999–2001. Dietary intakes were assessed using 4-day food records. ANCOVA and linear regression were used for analyses. Results The mean intake of whole and refined grains was 136 g/day (SD 80) and 84 g/day (SD 46), respectively. Higher whole grain intake was associated with lower hs-CRP concentration and higher refined grain intake with higher concentration after adjustment for lifestyle and dietary factors. Each 50 g/d higher whole grain intake was associated with 0.12 mg/L (95% Cl 0.02–0.21 mg/L) lower hs-CRP concentration and each 50 g/d higher refined grain intake with 0.23 mg/L (95% Cl 0.08–0.38) higher concentration. Adjustment for fibre from grains attenuated the associations especially with whole grains. There were no statistically significant interactions according to gender or BMI (P for interactions >0.065). Conclusions The results of this study suggest that higher intake of whole grains is associated with lower concentrations of hs-CRP and higher intake of refined grains is associated with higher concentrations. However, especially the association with whole grain intake was attenuated after adjusting for fibre intake from grains, suggesting that cereal fibre may partly explain the association.
Background The prevalence of obesity is increasing in many Asian countries. However, longitudinal data on the impacts of dietary factors on weight gain in Asian populations are sparse. Objectives We evaluated the relationship between changes in intakes of nutrients, foods, and beverages and diet quality and long-term changes in body weight. Methods We used data (n = 3064) from the Singapore Multi-Ethnic Cohort, a prospective cohort including Chinese, Indian, and Malay residents aged 21–65 years. Dietary intakes were assessed using an FFQ, and body weight and waist circumference were measured during health examinations. Diet quality was evaluated using the Dietary Approaches to Stop Hypertension (DASH) and Alternative Healthy Eating Index (AHEI-2010) scores. Data were collected at baseline (2004–2010) and follow-up (2011–2016), with a mean follow-up of 6.0 years. Linear regression was used to assess the associations between dietary changes and weight change, adjusted for socio-demographic and lifestyle variables. Results Improvements in dietary quality scores (DASH, −0.34 kg per 5 points; AHEI-2010, −0.35 kg per 10 points) and replacement of carbohydrates with protein (−0.44 kg per 5% of energy) were significantly associated with less weight gain. Increased intakes of white rice (+0.25 kg per serving/d), soft drinks (+0.69 kg), red meat (+0.58 kg), and poultry with skin (+0.74 kg) were directly associated with weight gain. The replacement of 1 serving per day of white rice with whole grains (−0.68 kg), vegetables (−0.33 kg), poultry without skin (−0.79 kg), and eggs (−0.87 kg) was associated with less weight gain. Similar associations were observed between changes in dietary factors and changes in waist circumference. Conclusions Among Asian adults, increasing dietary quality, reducing soft drink consumption, and replacing white rice with whole grains, vegetables, and selected high-protein foods was associated with less weight gain.
Full-text available
Although dietary guidance recommends increasing consumption of whole grains and concurrently limiting consumption of refined and/or enriched grain foods, emerging research suggests that certain refined grains may be part of a healthy dietary pattern. A scientific expert panel was convened to review published data since the release of 2015 dietary guidance in defined areas of grain research, which included nutrient intakes, diet quality, enrichment/fortification, and associations with weight-related outcomes. Based on a 1-d roundtable discussion, the expert panel reached consensus that 1) whole grains and refined grains can make meaningful nutrient contributions to dietary patterns, 2) whole and refined grain foods contribute nutrient density, 3) fortification and enrichment of grains remain vital in delivering nutrient adequacy in the American diet, 4) there is inconclusive scientific evidence that refined grain foods are linked to overweight and obesity, and 5) gaps exist in the scientific literature with regard to grain foods and health. Curr Dev Nutr 2020;4:nzaa125.
Full-text available
Although dietary guidance recommends increasing consumption of whole grains and concurrently limiting consumption of refined and/or enriched grain foods, emerging research suggests that certain refined grains may be part of a healthy dietary pattern. A scientific expert panel was convened to review published data since the release of 2015 dietary guidance in defined areas of grain research, which included nutrient intakes, diet quality, enrichment/fortification, and associations with weight-related outcomes. Based on a 1-d roundtable discussion, the expert panel reached consensus that 1) whole grains and refined grains can make meaningful nutrient contributions to dietary patterns, 2) whole and refined grain foods contribute nutrient density, 3) fortification and enrichment of grains remain vital in delivering nutrient adequacy in the American diet, 4) there is inconclusive scientific evidence that refined grain foods are linked to overweight and obesity, and 5) gaps exist in the scientific literature with regard to grain foods and health.
Full-text available
Although weight loss can be achieved by any means of energy restriction, current dietary guidelines have not prevented weight regain or population-level increases in obesity and overweight. Many high-carbohydrate, low-fat diets may be counterproductive to weight control because they markedly increase postprandial hyperglycemia and hyperinsulinemia. Many high-carbohydrate foods common to Western diets produce a high glycemic response [high-glycemic-index (GI) foods], promoting postprandial carbohydrate oxidation at the expense of fat oxidation, thus altering fuel partitioning in a way that may be conducive to body fat gain. In contrast, diets based on low-fat foods that produce a low glycemic response (low-GI foods) may enhance weight control because they promote satiety, minimize postprandial insulin secretion, and maintain insulin sensitivity. This hypothesis is supported by several intervention studies in humans in which energy-restricted diets based on low-GI foods produced greater weight loss than did equivalent diets based on high-GI foods. Long-term studies in animal models have also shown that diets based on high-GI starches promote weight gain, visceral adiposity, and higher concentrations of lipogenic enzymes than do isoenergetic, macronutrientcontrolled, low-GI-starch diets. In a study of healthy pregnant women, a high-GI diet was associated with greater weight at term than was a nutrient-balanced, low-GI diet. In a study of diet and complications of type 1 diabetes, the GI of the overall diet was an independent predictor of waist circumference in men. These findings provide the scientific rationale to justify randomized, controlled, multicenter intervention studies comparing the effects of conventional and low-GI diets on weight control.
Full-text available
The National Weight Control Registry (NWCR) is, to the best of our knowledge, the largest study of individuals successful at long-term maintenance of weight loss. Despite extensive histories of overweight, the 629 women and 155 men in the registry lost an average of 30 kg and maintained a required minimum weight loss of 13.6 kg for 5 y. A little over one-half of the sample lost weight through formal programs; the remainder lost weight on their own. Both groups reported having used both diet and exercise to lose weight and nearly 77% of the sample reported that a triggering event had preceded their successful weight loss. Mean (+/-SD) current consumption reported by registry members was 5778 +/- 2200 kJ/d, with 24 +/- 9% of energy from fat, Members also appear to be highly active: they reported expending approximately 11830 kJ/wk through physical activity. Surprisingly, 42% of the sample reported that maintaining their weight loss was less difficult than losing weight. Nearly all registry members indicated that weight loss led to improvements in their level of energy, physical mobility, general mood, self-confidence, and physical health. In summary, the NWCR identified a large sample of individuals who were highly successful at maintaining weight loss. Future prospective studies will determine variables that predict continued maintenance of weight loss.
Conference Paper
Objectives: The primary aim was to determine whether ready-to-eat cereal used as a portion-controlled, meal replacement promotes weight loss. Additional aims were to determine whether weight loss differed if the cereal was provided as a single brand or variety of brands and whether this use of ready-to-eat cereal promotes continued weight loss following transition to a high-fiber, high-volume (Volumetric) diet. Methods: Body composition was measured and diet records, appetite questionnaires and activity logs were completed during baseline and end of intervention weeks 2 and 6. Participants were assigned to one of four treatment groups. Group 1 (6 M, 22 F, mean age 43.0 +/- 1.9 years, mean initial BMI 28.9 +/- 0.4 kg/m(2)) consumed a serving of a single brand of ready-to-eat cereal with 2/3 C skim milk and a 100 Kcal portion of fruit for breakfast and as a replacement for either lunch or dinner for weeks 1 and 2. No restrictions were placed on the non-cereal meal. They then followed the Volumetric diet for weeks 3 to 6 with a target energy restriction of 500 kcal/day. Group 2 (3 M, 25 F, mean age 40.9 +/- 2.3 years, mean initial BMI 29.39 +/- 0.6 kg/m(2)) followed the same protocol, but was permitted to select from a variety of ready-to-eat cereals during weeks 1 and 2. Group 3 (7 M, 19 F, mean age 41.6 +/- 2.4 years, mean initial BMI 29.3 +/- 0.6 kg/m(2)) received no dietary instruction during the six-week study and Group 4 (9 M, 18 F, mean age 38.8 +/- 2.8 years, mean initial BMI 29.3 +/- 0.6 kg/m(2)) received no intervention prior to adoption of the Volumetric diet for weeks 3 to 6. Results: The cereal interventions resulted in 640 +/- 109 and 617 +/- 105 kcal/day reductions of energy intake in Groups I and 2, respectively, during the two-week cereal intervention. This led to comparable mean weight losses (1.91 +/- 0.19 kg-Group 1, 1.37 +/- 0.15 kg-Group 2) that were significantly greater than that observed in Group 3 (0.08 +/- 0.15 kg). The losses were primarily of fat mass. No significant changes of total body water were observed. Weight loss continued during the Volumetric diet in Groups I and 2. The changes were comparable to those observed in Group 4, and all were significantly greater than that of Group 3. Self-reported hunger was slightly, but significantly higher than baseline in Groups I and 2 during the cereal intervention, but similar to baseline in Groups 1, 2 and 3 during the Volumetric diet. Based on predicted weight loss, compliance with the Volumetric diet was similar and limited in all three intervention groups. Conclusions: Ready-to-eat cereals may be used to promote weight loss when consumed as a portion-controlled, meal replacement. Provision of a variety of brands does not compromise efficacy. Weight losses may be maintained or increased after transition to the Volumetric diet. The later regimen effectively controls hunger and may lead to weight loss, but compliance is limited.
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.
Background: Low-carbohydrate diets remain popular despite a paucity of scientific evidence on their effectiveness. Objective: To compare the effects of a low-carbohydrate, ketogenic diet program with those of a low-fat, low-cholesterol, reduced-calorie diet. Design: Randomized, controlled trial. Setting: Outpatient research clinic. Participants: 120 overweight, hyperlipidemic volunteers from the community. Intervention: Low-carbohydrate diet (initially, <20 g of carbohydrate daily) plus nutritional supplementation, exercise recommendation, and group meetings, or low-fat diet (<30% energy from fat, <300 mg of cholesterol daily, and deficit of 500 to 1000 kcal/d) plus exercise recommendation and group meetings. Measurements: Body weight, body composition, fasting serum lipid levels, and tolerability. Results: A greater proportion of the low-carbohydrate diet group than the low-fat diet group completed the study (76% vs. 57%; P = 0.02). At 24 weeks, weight loss was greater in the low-carbohydrate diet group than in the low-fat diet group (mean change, -12.9% vs. -6.7%; P < 0.001). Patients in both groups lost substantially more fat mass (change, -9.4 kg with the low-carbohydrate diet vs. -4.8 kg with the low-fat diet) than fat-free mass (change, -3.3 kg vs. -2.4 kg, respectively). Compared with recipients of the low-fat diet, recipients of the low-carbohydrate diet had greater decreases in serum triglyceride levels (change, -0.84 mmol/L vs. -0.31 mmol/L [-74.2 mg/dL vs. -27.9 mg/dL]; P = 0.004) and greater increases in high-density lipoprotein cholesterol levels (0.14 mmol/L vs. -0.04 mmol/L [5.5 mg/dL vs. -1.6 mg/dL]; P < 0.001). Changes in low-density lipoprotein cholesterol level did not differ statistically (0.04 mmol/L [1.6 mg/dL] with the low-carbohydrate diet and -0.19 mmol/L [-7.4 mg/dL] with the low-fat diet; P = 0.2). Minor adverse effects were more frequent in the low-carbohydrate diet group. Limitations: We could not definitively distinguish effects of the low-carbohydrate diet and those of the nutritional supplements provided only to that group. In addition, participants were healthy and were followed for only 24 weeks. These factors limit the generalizability of the study results. Conclusions: Compared with a low-fat diet, a low-carbohydrate diet program had better participant retention and greater weight loss. During active weight loss, serum triglyceride levels decreased more and high-density lipoprotein cholesterol level increased more with the low-carbohydrate diet than with the low-fat diet.
Dietary patterns and weight status are reported for 2 groups of community-living older adults, a rural Pennsylvania group and an urban Boston group. Diet patterns were defined by cluster analysis. Two major dietary patterns were identified for rural study participants and 4 major dietary patterns were identified for urban study participants. Findings from both groups suggest that both diet quality and weight status were improved by food patterns rich in fruits, cereals, and milk.