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The Role of Grapefruit Consumption in CardiometabolicHealth in Overweight and Obese Adults
Item Type text; Electronic Dissertation
Authors Dow, Caitlin Ann
Publisher The University of Arizona.
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Download date 06/01/2022 20:07:19
Link to Item http://hdl.handle.net/10150/293398
THE ROLE OF GRAPEFRUIT CONSUMPTION IN CARDIOMETABOLIC
HEALTH IN OVERWEIGHT AND OBESE ADULTS
by
Caitlin Dow, M.S.
A Dissertation Submitted to the Faculty of the
DEPARTMENT OF NUTRITIONAL SCIENCES
In Partial Fulfillment of the Requirements
For the Degree of
DOCTOR OF PHILOSOPHY
In the Graduate College
THE UNIVERSITY OF ARIZONA
2013
2
THE UNIVERSITY OF ARIZONA
GRADUATE COLLEGE
As members of the Dissertation Committee, we certify that we have read the dissertation
prepared by Caitlin Dow, titled The Role of Grapefruit Consumption in Cardiometabolic Health
in Overweight and Obese Adults and recommend that it be accepted as fulfilling the dissertation
requirement for the Degree of Doctor of Philosophy.
4/16/13
Cynthia Thomson, PhD, RD
4/16/13
Scott Going, PhD
4/16/13
Hsiao-Hui (Sherry) Chow, PhD
4/16/13
Zoe Cohen, PhD
4/16/13
Patricia Thompson, PhD
Final approval and acceptance of this dissertation is contingent upon the candidate’s submission
of the final copies of the dissertation to the Graduate College.
I hereby certify that I have read this dissertation prepared under my direction and recommend
that it be accepted as fulfilling the dissertation requirement.
4/16/13
Dissertation Director: Cynthia Thomson, PhD, RD
3
STATEMENT BY AUTHOR
This dissertation has been submitted in partial fulfillment of requirements for an
advanced degree at The University of Arizona and is deposited in the University Library
to be made available to borrowers under rules of the Library.
Brief quotations from this dissertation are allowable without special permission, provided
that accurate acknowledgement of source is made. Requests for permission for extended
quotation from or reproduction of this manuscript in whole or in part may be granted by
the head of the major department or the Dean of the Graduate College when in his or her
judgment the proposed use of the material is in the interests of scholarship. In all other
instances, however, permission must be obtained from the author.
SIGNED: Caitlin Dow
4
ACKNOWLEDGEMENTS
The author would like to acknowledge the following groups for their role in making this
research possible.
The funding sources for this study:
o Vegetable and Fruit Improvement Center at Texas A&M and the United
States Department of Agriculture Cooperative State, Research, Education
and Extension Service (USDA-CSREES) (2010-34402-20875)
o United States Department of Agriculture National Needs Fellowship in
Obesity Research (USDA-NNF) (2010-38420-20369)
Rio Queen Citrus Inc. (Mission, TX) for their generous grapefruit donation.
Bayer Healthcare (Morristown, NJ) for their generous multivitamin donation.
Jennifer Ravia, Amy Butalla, Lindsey Diemert, and Julie West for their role in
coordination of the study.
Christina Preece for her work in biosample analysis.
5
TABLE OF CONTENTS
LIST OF FIGURES…………………………………………………………………8
LIST OF TABLES…………………………………………………………………..9
ABSTRACT………………………………………………………………………...10
CHAPTER 1: INTRODUCTION.……………………………….…………………12
Figure………………………………………………………………………..22
CHAPTER 2: THE EFFECTS OF DAILY CONSUMPTION OF GRAPEFRUIT
ON BODY WEIGHT, LIPIDS, AND BLOOD PRESSURE IN HEALTHY,
OVERWEIGHT ADULTS..............………………………………………….…….23
Introduction………………………………………………………………....23
Methods……………………………………………………………………..26
Results………………………………………………………………………31
Discussion…………………………………………………………………..34
Figures………………………………………………………………………42
Tables……………………………………………………………………….43
CHAPTER 3: DAILY CONSUMPTION OF GRAPEFRUIT FOR SIX WEEKS
DOES NOT REDUCE SVCAM-1, CRP, OR F2-ISOPROSTANES IN
OVERWEIGHT AND OBESE ADULTS………………………..…...……………47
Introduction………………………………………………………………....47
Methods……………………………………………………………………..49
Results………………………………………………………………………52
Discussion…………………………………………………………………..54
6
TABLE OF CONTENTS – Continued
Tables……………………………………………………………………….59
CHAPTER 4: GRAPEFRUIT INCREASES POSTPRANDIAL INSULIN AND
ATTENUATES F2-ISOPROSTANE AND IL-6 CONCENTRATIONS WHEN
CONSUMED WITH A HIGH-FAT, HIGH-CALORE MEAL.................................62
Introduction………………………………………………………………....62
Methods……………………………………………………………………..64
Results………………………………………………………………………67
Discussion…………………………………………………………………..69
Figures………………………………………………………………………75
Tables……………………………………………………………………….76
CHAPTER 5: Summary and Conclusions………………………………………….78
Obesity and Visceral Adiposity…………………………………………….78
Vascular Reactivity and Blood Pressure……………………………………80
Lipid Response………………………………………….…………………..83
Insulin Response………………………………………….………………...84
Inflammation and Oxidative Stress Modification…………………………..88
Limitations, Future Directions, and Conclusions…………………………..93
Figure……………………………………………………………………….97
APPENDIX A CONSENT FORM…………………………………………………98
APPENDIX B SUPPLEMENTAL MATERIALS
Grapefruit Weights…………………………………………………………106
7
TABLE OF CONTENTS - Continued
Compliance Logs………………...………………………………………....107
APPENDIX C- ADDITIONAL PUBLICATION #1: A review of evidence based
strategies to treat obesity in adults………………...…………………….......108
APPENDIX D- ADDITIONAL PUBLICATION #2: Associations between
mother’s BMI, fruit and vegetable intake and availability, and child’s body
shape as reported by women responding to an annual survey………..……..144
APPENDIX E- ADDITIONAL PUBLICATION #3: Predictors of
cardiometabolic risk factor improvements with weight loss in women...…..166
APPENDIX F- ADDITIONAL PUBLICATION #4: Use of herbal, botanical, and
natural product supplements in oncology and diabetes populations……..…194
REFERENCES……………………………………………………………………...214
8
LIST OF FIGURES
FIGURE 1. Pathophysiology of Atherosclerotic Plaque Production and Targets
for Risk Modification …………………………………………………….…22
FIGURE 2. Consort diagram describing the flow of participants through the
grapefruit intervention feeding trial.….……………………………………..42
FIGURE 3. Concentrations of various metabolic, inflammatory, and oxidative
stress markers following consumption of a HFHC meal alone or with ruby
red grapefruit……………………………………………………………….76
FIGURE 4. The Effect of Grapefruit on Pathophysiology of Atherosclerotic
Plaque Production and Targets for Risk Modification……………………...97
9
LIST OF TABLES
TABLE 1. Baseline characteristics of participants who completed the grapefruit
feeding trial: grapefruit vs. control ……………………………………….……43
TABLE 2. Anthropometric and blood pressure changes in participants who
completed the grapefruit feeding trial: grapefruit vs control.…...………...……44
TABLE 3. Comparison of diet composition in participants who completed the
grapefruit feeding trial: grapefruit vs control……………………………..……45
TABLE 4. Comparison of the lipid profile in those participants who completed
the Grapefruit Feeding Trial: Grapefruit vs Control, before and after the
intervention phase.……………………………………………………………….……46
TABLE 5. Baseline characteristics of participants who successfully completed
all study activities (n=69) ……………………………………………....…….59
TABLE 6. Change in biomarkers (mean ± SD) associated with atherosclerotic
plaque production in participants enrolled in a six-week grapefruit feeding
trial..…………………………………………………………………….…….60
TABLE 7. Associations between common cardiovascular disease (CVD) risk
factors and inflammatory/oxidative stress biomarkers in participants
enrolled in a grapefruit feeding trial (n=69)…………………………….……61
TABLE 8. Baseline characteristics of participants who completed the
grapefruit double meal challenge postprandial trial....……………..…..……77
TABLE 9. Comparison of AUC of biomarkers in response to a HFHC meal
eaten alone or with grapefruit (n=10)…………………………………..……77
10
ABSTRACT
Atherosclerotic cardiovascular diseases (CVD) are the leading cause of death and often
develop due to obesity-induced complications including hyperlipidemia, elevated blood
pressure (BP), inflammation, and oxidative stress. Epidemiological, animal model, and
cell culture studies indicate that citrus, and grapefruit specifically, exert cardiovascular
health benefits, likely due to the high flavonoid content in citrus fruits. Grapefruit and/or
isolated grapefruit flavonoids elicit cardiovascular benefits via improvements in lipid
metabolism and endothelial reactivity, and by antioxidant and anti-inflammatory actions.
The aim of this work was to determine the role of six-week daily consumption of
grapefruit on weight, lipid, and BP control as well as inflammatory and oxidative stress
markers in overweight/obese adults. Further, we sought to evaluate the acute,
postprandial effects of grapefruit consumption on metabolic, inflammatory, and oxidative
stress markers in response to a high fat, high calorie (HFHC) double meal challenge.
Participants were randomized to either a grapefruit group (n=42) in which they consumed
1.5 grapefruit/day for six weeks or to a control condition (n=32). Ten participants who
completed the feeding trial also participated in the postprandial study. On two test days
participants consumed a HFHC meal for breakfast and again for lunch. A ruby red
grapefruit was consumed with breakfast on the first test day. Blood samples were
collected at baseline and for the subsequent eight hours on each day. In the feeding trial,
grapefruit consumption resulted in reductions in waist circumference (p<0.001), systolic
BP (p=0.03), total cholesterol (p=0.001), and LDL-cholesterol (p=0.021) compared to
baseline values. F2-isoprostanes and hsCRP values were nonsignificantly lower in the
11
grapefruit vs. control arm following the intervention (p=0.063 and p=0.073, respectively).
In the postprandial evaluation, insulin concentrations were significantly higher 30
minutes (p=0.007) and 2 hours (p=0.025) post HFHC + grapefruit meal consumption vs.
HFHC alone. HFHC + grapefruit intake resulted in lower IL-6 concentrations after two
hours (p=0.017) and lower F2-isoprostanes after 5 hours (p=0.0125). These findings
suggest that regular grapefruit consumption may reduce CVD risk by targeting many of
the risk factors and pathogenic factors involved in endothelial dysfunction. However,
this dietary change alone is unlikely to result in significant CVD risk reduction.
12
CHAPTER 1
INTRODUCTION
Atherosclerotic cardiovascular diseases (CVD) are the leading cause of death in
the developed and developing world [1, 2], affecting over 79.4 million people in the US
alone [3]. Obesity also poses a significant public health threat; according to the most
recent National Center for Health Statistics report, 69.2% of the adult population in the
United States is overweight, and 35.7% are obese [4]. The link between obesity and
cardiometabolic complications that often result in atherosclerotic plaque formation is
well-characterized [2], and obesity is considered one of the primary modifiable risk
factors in the CVD risk profile [5]. Furthermore, obesity increases the risk of morbidity
and mortality from diseases of endothelial damage including hypertension, coronary
artery disease (CAD), and stroke [6]. Perhaps even more important than the role of
obesity in vascular disease pathogenesis, is the role of central obesity, characterized by an
increased volume of visceral adipose tissue.
Visceral adipose tissue (VAT) functions as a metabolic reservoir that becomes
highly dysregulated with increasing volume and is involved in the pathophysiology of
atherogenesis [2, 7]. Numerous reports indicate that elevated waist circumference, a
surrogate measure of visceral adiposity, is associated with an increased risk of CAD [8-
10]. VAT is pathogenically linked to metabolic issues that impact vascular function
including insulin resistance and secretion of excess triglycerides [7].
13
Several studies have shown positive associations between waist circumference
and circulating markers of inflammation and oxidative stress, including interleukin-6 (IL-
6), C-reactive protein (CRP), and F2-isoprostanes [11-13]. Evidence also indicates that
VAT is not only associated with circulating atherogenic molecules, but also directly
secretes inflammatory cytokines, growth factors, and vasoactive proteins which are
known to interact with the endothelium and promote atheroma development [12].
Additionally, an analysis of various fat depots in obese women suggested that adhesion
molecule expression and secretion is elevated in the vasculature of VAT [14], thus
providing more evidence for an innate link between endothelial dysfunction and visceral
adiposity.
These vasoactive proteins secreted from VAT interact with the endothelium, a
monolayer of cells that represents the interface between the blood and the vessel wall that
plays a critical role in maintaining vascular homeostasis. The endothelium is highly
reactive to the blood and its constituents and transmits signals to the underlying smooth
muscle cells, leading to activation of pathways involved in vasoreactivity [6]. Injury to
the endothelium results in endothelial dysfunction (ED), the first abnormality in the
process leading to plaque formation [2, 15, 16].
Risk factors for ED and atheroma development include dyslipidemia,
hyperglycemia, insulin resistance, chronic low-grade inflammation, and oxidative stress
[2, 15, 17], biological responses to stimuli such as diet, activity, infection, and
adiposity/adipokines. Collectively, these factors interact with the endothelium, leading to
endothelial cell activation, adhesion molecule expression, white blood cell recruitment, a
14
hyper-inflammatory response, and eventually, atheroma development [6] (Figure 1).
Over time and with accumulating damage, ischemic events are promoted causing
significant endothelial damage. Furthermore, these risk factors which are cumulatively
damaging to the vasculature typically cluster together as a result of obesity [2, 6, 15].
Given the irrefutable link between obesity and CVD, and the impact of VAT on
endothelial function, strategies that promote healthy weight and cardiovascular health,
particularly in the primary prevention setting, are warranted. Ideally, these strategies
would promote normal lipid values, while simultaneously reducing inflammation and
oxidative stress.
Evidence indicates that citrus, and grapefruit in particular, may be a beneficial
addition to the diet for weight, lipid, and blood pressure control [18-21]. These effects of
citrus are likely attributable to fruit-specific bioactive compounds including the
flavonoids, naringin and hesperidin, which are converted to the aglycones, naringenin and
hesperitin, in the gut [22]. Theses flavonones (a subclass of flavonoids specific to citrus
fruits) are known to have antioxidant, hypolipidemic, and anti-hypertensive properties
[20, 23], suggesting a possible role for these compounds in the prevention of
cardiovascular disease.
A retrospective analysis of the Nurse’s Health Study (NHS) and Health
Professional’s Follow-up Study provides support for the role of citrus in CVD risk
reduction. This analysis of 84,251 women and 42,148 men showed a 19% lower risk of
ischemic stroke in individuals who consumed the highest quintile versus the lowest
quintile of citrus fruits (RR: 0.81, 95% CI: 0.68-0.96) and a 25% lower risk for those
15
consuming citrus juices (RR: 0.75, 95% CI: 0.62-0.99) [24]. Similar risk lowering
associations were demonstrated in regard to myocardial infarction in 8,087 50-59 year
old men in Northern Ireland and France in the Prospective Epidemiological Study of
Myocardial Infarction (PRIME) study [25]. Additionally, an analysis of more than
34,400 postmenopausal women from the Iowa Women’s Health Study with 16 years of
follow-up suggested that citrus flavonones, quantified using data collected from a Food
Frequency Questionnaire and three USDA databases, were associated with a reduced risk
of total mortality, CAD, and CVD. Grapefruit intake of one serving or more per week
was associated with a 23% and 15% reduced risk of CAD and overall CVD, respectively
[26].
Grapefruit made its first appearance in the health market in the 1930’s as a “fat-
burning” food as part of the 800 to 1000 kcal Hollywood Diet [27]. While dieters
experienced weight loss, it is reasonable to assume that this effect was attributable to the
low energy composition of the diet, as further analyses of grapefruit have revealed that
the fruit has no thermogenic properties [28, 29].
While folklore promotes grapefruit as a weight loss food, clinical trials testing this
effect are limited and results have been inconsistent. A randomized, controlled study in
91 obese subjects by Fujioka, et al. evaluated weight change in participants assigned to
fresh grapefruit, grapefruit juice, a grapefruit capsule, or a placebo treatment. Consuming
fresh grapefruit over 12 weeks resulted in a 1.6 kg weight reduction as compared to a 1
kg weight loss in those randomized to the grapefruit juice or grapefruit capsule, while
those randomized to the placebo arm demonstrated no change in weight [19]. Some
16
evidence indicates that a food with high fiber/water content consumed before a meal may
induce satiety and reduce caloric intake at the meal [30]. A randomized study by Silver,
et al. investigated the role of grapefruit in weight loss comparing whole grapefruit,
grapefruit juice, or water as meal preloads in addition to 12.5% energy restriction in 85
obese adults. Significant weight loss was observed in all groups as compared to baseline
weight, though no significant difference between the three groups was observed. Further,
energy intake did not differ by preload assignment (water, grapefruit, grapefruit juice),
suggesting that the whole fruit had no additional effects above water or juice in reducing
energy intake [18]. It is possible that these trials may not have had adequate sample sizes
to observe statistically significant weight loss because of the 3-4 arm study designs.
Despite the inconclusive findings regarding grapefruit and weight control,
research does suggest that grapefruit may exert cardiovascular benefits through
modification of other risk factors. Cell culture and animal models support the role of
citrus and grapefruit bioactive compounds in modifying lipid metabolism. In particular,
naringenin has been shown to elicit its hypolipidemic actions by inducing hepatic
peroxisome proliferator-activated receptor (PPAR)-α and –γ expression in rats and
cultured human hepatocytes, thus improving lipid metabolism and fatty acid oxidation
[20, 31]. An in vitro study in HepG2 cells incubated with naringenin or hesperitin
resulted in reduced secretion of ApoB, the primary apoprotein in chylomicrons and low-
density lipoproteins (LDL), and upregulation of LDL receptor (LDL-R) transcription
[32]. To illustrate the bioactivity of a citrus flavonone using a rodent model system, rat
chow was supplemented with naringenin for six weeks at intake levels comparable to 1-4
17
cups of grapefruit juice per day in humans. Male Long-Evans hooded rats demonstrated
significantly reduced plasma and adipose tissue triglycerides and total plasma cholesterol
concentrations, as well as reductions in parametrial adipose tissue weight [20]. Further,
3% naringenin supplementation of a high cholesterol diet for 12 weeks resulted in
reductions in hepatic steatosis, VLDL overproduction, hyperlipidemia, atherosclerotic
lesion development in LDL-R-/- C57BL/6J mice [33]. These data from animal models
support the hypolipidemic properties of naringenin, though evidence from human studies
is conflicting.
The only human study to date to measure lipid changes in response to grapefruit
consumption as a primary outcome was a study of 57 hyperlipidemic patients who had
recently undergone coronary bypass surgery. After 30 days of daily intake, grapefruit
consumption resulted in significant reductions in total cholesterol, LDL-cholesterol, and
triglycerides in patients with coronary atherosclerosis (p<0.05 for all outcomes) [34].
However, 204 moderately hypercholesterolemic adults consuming either a naringin or a
hesperedin supplement at a dose of 500 mg and 800 mg, respectively, for four weeks
experienced no changes in the lipid profile [35]. These results are not consistent with the
rat study, but suggest that the whole fruit may be required to produce appreciable changes
in lipid parameters. Given the availability of grapefruit crop in the US and the potential
risk-reducing effects of regular consumption there is a need for further research in order
to elucidate the true effects of grapefruit on lipid control, as well as other factors
associated with CVD risk, including blood pressure, inflammation, and oxidative stress.
18
Studies on the direct vascular effects of citrus are limited, though promising. Ex
vivo studies of aortic tissue indicate that citrus flavonones induce vasorelaxation due to
inhibition of phosphodiesterases [21] and activation of endothelial nitric oxide synthase
(eNOS), thus inducing nitric oxide (NO) production [36]. Five-week consumption of
sweetie fruit (a hybrid of grapefruit and pummelo) juice resulted in a significant
reduction in diastolic blood pressure of 3.7 mmHg in 12 hypertensive men [37]. In a
randomized crossover study, 24 men consumed 500 mL of orange juice, a beverage with
added hesperidin, or a placebo beverage for four weeks each. Diastolic blood pressure
was lower by 3.2 mmHg and 5.5 mmHg after the hesperidin beverage or orange juice,
respectively, compared to the placebo beverage [38]. Further, a postprandial analysis of
each treatment revealed improved skin blood flow, a measure of microvascular reactivity,
after orange juice and hesperidin beverage intake compared to placebo [38].
Additionally, hesperitin treatment of bovine aortic endothelial cells (BAEC) stimulated
NO production, whereas 3 weeks of 500 mg hesperidin supplementation resulted in
improved flow mediated dilation, a measure of endothelial reactivity, compared to a
placebo treatment in 24 participants with the Metabolic Syndrome [36].
In addition to the effects of grapefruit on classic risk factors of CVD (weight loss,
lipid control, blood pressure), preliminary evidence suggests that citrus/grapefruit may
also play a role in reducing risk of CVD due to effects on novel risk factors including
inflammation and oxidative stress. Given the known roles of flavonoids in the
cardiovascular system, a cross-sectional analysis was performed to test the association
between intake of overall and specific flavonoid subgroups (flavonols, flavones,
19
flavonones, flavan-3-ols, anthocyanidins, and polymeric flavonoids) and biomarkers
associated with endothelial health (CRP, IL-6, IL-18, soluble TNF Receptor-2, soluble
vascular cellular adhesion molecule-1, soluble intercellular adhesion molecule-1, and E-
selectin) using the NHS prospective cohort of 2,115 women aged 43-70 [39]. In this
analysis, greater intake of grapefruit flavonones was associated with lower circulating
concentrations of CRP and soluble tumor necrosis factor-receptor 2 (sTNF-R2) [39]. A
recent evaluation of consumption of orange and blackcurrant juices in individuals with
peripheral artery disease resulted in reductions in CRP and F2-isoprostanes compared to a
control condition [40]. In vitro work also indicates that LDL-bound naringenin reduces
oxidation and glycation of LDL [41], thus potentially reducing the pro-atherogenic
properties of oxidized LDL.
When evaluating a dietary intervention in the context of CVD health, it is ideal to
determine both the acute and chronic effects. Atherosclerotic plaques develop over
decades [1]; however, it is also well recognized that endothelial activation and
subsequent plaque development are the products of metabolic, oxidative, and
inflammatory perturbations that arise during the postprandial period [42-44]. Indeed,
some data suggest that evaluation of fasting values of various CVD risk factors alone
does not predict future events and that study of the postprandial period provides a more
comprehensive and accurate risk profile [45-47]. Previous postprandial research suggests
that consuming antioxidant rich foods with a high fat, high calorie (HFHC) meal
attenuates the oxidative/inflammatory responses induced by the meal alone [48-51].
Only a few studies have evaluated the postprandial effects of citrus consumption, and the
20
exposures were either orange juice and/or a beverage containing hesperidin [38, 49, 52].
This is despite the epidemiological data that suggest that grapefruit has a more
pronounced effect on markers of endothelial health than orange juice [26, 39].
Nevertheless, these trials indicate that orange juice consumption reduces the pro-
inflammatory effects induced by a HFHC meal [49], improves serum antioxidant capacity
[52], and improves endothelial reactivity [38] in the postprandial period.
The goal of this research was to expand on the sparse human intervention trials to
prospectively evaluate the effect of regular grapefruit consumption on cardiovascular
disease risk factors, both classic and novel. We chose ruby red grapefruit for our studies
given evidence that suggests that the red grapefruit has higher bioactive content than the
white fruit cultivars [52]. We also targeted overweight and obese adults given the
propensity for the development of CVD and likelihood that baseline CVD biomarkers of
risk would be perturbed prior to participation in the trial. The aims of the current
randomized controlled trial were:
1) Evaluate the role of six weeks of daily consumption of ruby red grapefruit on
classical CVD risk factors including weight loss, blood pressure reduction, and
improvements in the lipid profile (reduced total cholesterol, LDL cholesterol, and
triglycerides and increased HDL cholesterol) in overweight and obese adults;
2) Evaluate the role of six weeks of daily consumption of ruby red grapefruit on
novel risk factors of cardiovascular health including circulating C-reactive
protein, soluble vascular adhesion molecule-1 (sVCAM-1), and F2-isoprostanes
21
in overweight and obese adults, and in a subsample of participants with the
Metabolic Syndrome;
3) Examine the acute, postprandial effects of ruby red grapefruit consumption when
consumed with a high fat, high carbohydrate meal on metabolic markers including
glucose, triglycerides, and insulin and inflammatory/oxidative markers including
interleukin-6 (IL-6), sVCAM-1, soluble intercellular adhesion molecule-1
(sICAM-1), and F2-isoprostanes in overweight and obese adults.
We expected that regular grapefruit feeding would not significantly modify weight, but
would reduce blood pressure as well as promote improvements in the lipid profile by
reducing total and LDL cholesterols and triglycerides. Further, we hypothesized that
grapefruit intake would reduce markers of inflammation and oxidative stress after six
weeks of feeding as well as in the postprandial setting compared to control conditions.
22
23
CHAPTER 2
THE EFFECTS OF DAILY CONSUMPTION OF GRAPEFRUIT ON BODY WEIGHT,
LIPIDS, AND BLOOD PRESSURE IN HEALTHY, OVERWEIGHT ADULTS
Introduction
The current obesity epidemic provides a significant challenge, from both
economical and clinical perspectives. Currently, 68% of the American population is
overweight, while 50% of the overweight population is considered obese [53]. Obese
individuals endure greater health care costs and experience a reduced quality of life, as
well as suffer from a number of obesity-related comorbidities such as diabetes and
cardiovascular disease (CVD) [54, 55]. CVD, specifically, affects 79.4 million
Americans [3], and with the aging population and current trends in obesity prevalence,
this number is expected to increase in the coming years [56]. Strategies that promote
healthy weight and metabolic health are essential, and whole food approaches may
provide this option.
Grapefruit was first introduced as a weight loss food as part of the Hollywood
Diet of the 1930’s, consisting of 800-1000 kcals/day and half of a fresh grapefruit before
every meal for twelve days [27]. It is now known that grapefruit has no thermogenic
properties, and that any weight loss observed was likely attributable to the hypocaloric
diet [28, 29]. Nevertheless, a biologically plausible association between grapefruit intake
and weight control can be suggested given the known effects of select bioactive
constituents in grapefruit on adiposity [20, 57], and the proposed effects of the whole
fruit on satiety [18, 19].
24
In fact, weight loss (1.6 kg-5.8 kg) has been observed in two clinical trials
evaluating the role of grapefruit in promoting healthy weight [18, 19]. A low-energy
dense preload, such as fruit, is thought to encourage reduced energy consumption at the
subsequent meal. Indeed, a clinical trial considering the form of the preload (solid,
pureed, or liquid) on energy intake showed that a solid preload of apple slices resulted in
a greater reduction in energy intake at the following meal compared to apple sauce or
apple juice. However, a study evaluating the effect of grapefruit preload to reduce energy
consumption before meals as compared to grapefruit juice or water alone showed no
difference between groups [18].
Despite the conflicting results regarding energy intake and fruit, there is a great
deal of evidence supporting citrus, and grapefruit specifically, in promoting
cardiovascular health. These effects are likely attributable to the flavonones found in the
pith of grapefruit, naringin, and hesperidin, which are converted to the aglycones,
naringenin and hesperitin in the gut [22]. These bioactives have demonstrated anti-
oxidant, hypolipidemic, and anti-hypertensive properties in cell culture, animal model,
and clinical trial studies [20, 21, 23, 35, 36, 38].
Naringenin’s hypolipidemic properties have been confirmed in numerous studies
in both rats and mice [20, 58-61]. Many animal studies use dosages of naringenin
unattainable by the human diet; however, one trial that tested naringenin supplementation
at a dose comparable to 1-4 cups of grapefruit juice/day resulted in a significant reduction
in plasma triglyceride and total cholesterol concentrations in rats [20]. While
naringenin’s hypolipidemic effects in animal models have been well characterized,
25
results from clinical trials are highly heterogenous. Some clinical trials of grapefruit
intake or a grapefruit flavonoid supplement have shown no change in any parameter of
the lipid profile [19, 35]. Conversely, a trial of whole grapefruit and grapefruit juice
demonstrated beneficial changes in HDL, but no other lipid measurements (TC, LDL-C,
and triglycerides) when compared to controls [18]. Another trial in patients with
coronary atherosclerosis showed reductions in triglycerides, LDL, and TC, but no change
in HDL [34] in response to daily grapefruit consumption. Clearly, more research is
necessary in order to elucidate a definitive role of grapefruit in lipid control.
Studies of blood pressure and citrus intake are limited, but suggestive of a
potential protective association. Ex vivo and in vitro models of naringenin/hesperitin
treatment have resulted in vasorelaxation and nitric oxide production [21, 36].
Additionally, clinical trials in adults using hesperitin or orange juice have shown
improvements in flow-mediated dilation [36], increased postprandial endothelial
reactivity, and reduced diastolic blood pressure [38]. Epidemiological data suggests an
inverse association between citrus intake and markers of endothelial dysfunction [39].
Despite these results, the two grapefruit feeding trials to date showed no effect on blood
pressure [18, 19].
Based on the gaps in the literature regarding grapefruit, CVD, and weight control,
the aims of this study were to determine the effects of daily consumption of 1.5 red
grapefruit for six weeks for reducing weight and blood pressure and improving the lipid
profile in overweight and obese adults.
26
Methods
Study Sample. Two hundred and ninety three overweight and obese men and
premenopausal women who responded to print and electronic advertising were screened
via telephone, and eighty-five were enrolled into this randomized clinical trial (Figure 2).
Postmenopausal women were excluded in order to avoid any potential changes in
hormone therapy that may have affected study outcomes. Study eligible individuals had a
BMI of 25-45 kg/m2, were in a period of weight maintenance (≤10 pound fluctuation for
at least six months), had abstained from use of tobacco products for at least five years,
were willing to maintain their current exercise regimen (not to exceed 10 hours/week),
and were willing to discontinue supplement and anti-inflammatory medication use.
Those individuals with a diagnosis of diabetes, high cholesterol (≥225mg/dL),
cardiovascular disease, cancer, inflammatory disease, or liver or kidney disease, or taking
medications metabolized by the cytochrome P450 3A enzyme were excluded from the
study. Two cohorts completed the study over the course of two grapefruit seasons from
October 2009-March 2011. Written informed consent was obtained from all study
participants prior to enrollment. The University of Arizona Institutional Review Board
approved this study protocol.
Study Design. The study was a randomized, controlled design in which subjects were
enrolled in two separate cohorts (winter 2009 and winter 2010) corresponding to
seasonality of red grapefruit crop production. During the 2009 season randomization was
balanced 2:1 for grapefruit intervention knowing the available crop and to assure
27
adequate numbers were enrolled in the intervention; during 2010, randomization was
reversed to support > recruitment to the control treatment in order to balance group size.
Subjects made four visits to the clinical research setting: at baseline, randomization
(week 3), three weeks into the intervention phase (week 6), and at the end of the
intervention phase (week 9). Anthropometry was performed at baseline, week 6, and
week 9. Blood biosamples were collected at weeks 3 and 9. Blood pressure was
measured in duplicate at all clinic visits using a ReliOn HEM-780REL.
Diet Intervention. Following the baseline visit, subjects consumed a diet low in bioactive
rich fruits and vegetables for the study duration. The washout was followed to increase
the probability that results could be attributed to grapefruit consumption itself and not
another component of the diet. The diet included fruits and vegetables such as apples,
pears, bananas, iceberg lettuce, cucumbers, white potatoes, and onions, and restricted
fruits and vegetables with high polyphenol and carotenoid content such as citrus, berries,
spinach, carrots, tomatoes, and sweet potatoes. All other food groups were consumed ad
libitum. Subjects were provided with a multivitamin/mineral supplement for the duration
of the study (One-A-Day®, Bayer Healthcare; Morristown, NJ) in order to standardize
supplementation; other dietary supplementation was prohibited for the duration of the
study.
The first three weeks of the trial entailed a washout phase, while the last six
weeks comprised the intervention phase. After the three-week washout, subjects were
randomized to the intervention group (n=42), in which they continued consuming the
28
washout diet and supplemented their diet with one half of a fresh ruby red grapefruit
(Texas Rio Star® Grapefruit; distributed by RioQueen Citrus, Mission, TX) fifteen
minutes prior to breakfast, lunch, and dinner for six weeks or to the control condition
(n=32), in which they continued consuming the washout diet. Subjects were trained to
peel the grapefruit and eat all portions of the peeled grapefruit, including the pith.
Subjects were instructed to not add sugar to their grapefruit and were provided with a
non-calorie sweetener for use if desired.
Outcome Measurements. Diet composition was determined from repeat 24-hour diet
recalls. Dietary recalls were collected during the washout phase (n=3) and again during
the intervention phase (n=3). A Registered Dietitian unaffiliated with the study collected
the dietary recalls via telephone using the USDA multi-pass protocol [62]. Dietary data
was analyzed using the University of Minnesota Nutrition Data System for Research
software (NDS-R 2009). Energy intake was determined separately for the washout phase
and the intervention phase. Data from the phase-specific 24-hour recalls were combined
and averaged to determine the average intake for each respective phase.
Compliance to the grapefruit diet was measured via self-report. Following
randomization to the grapefruit group, subjects were provided with a log book in which
they were instructed to indicate each time grapefruit was consumed throughout the six
week intervention. Submitted logs were analyzed for compliance (# of times grapefruit
consumed before each meal/# meals)*100.
29
Bioactive content of the grapefruit was also estimated using the USDA Database
for Flavonoid Content of Selected Foods, as measured by high performance liquid
chromatography at the Beltsville Human Nutrition Research Center. Flavonoid content is
reported in mg/100g. In order to estimate gram weight of grapefruit intake, a random
sample of ten grapefruits were weighed following peeling using an Ohaus CS 5000
digital food scale. Average weight of the grapefruits was calculated and recorded in
grams, and flavonoid content of the fruit was then estimated.
Anthropometry was performed at baseline, week 6, and week 9. Height was
measured without shoes to the nearest quarter inch using a wall-mounted stadiometer
[63]. Weight was measured without shoes or over garments to the nearest half pound
using a calibrated double ruler standing scale [63]. Waist and hip circumferences were
measured using a Gulick II measuring tape to the nearest quarter inch. Briefly, subjects
stood upright in front of a full-length mirror as the measuring tape was extended around
the waist or hip using the umbilicus and the widest part of the hip area as anatomical
reference points for the respective measurements [63]. Body fat was estimated using a
handheld Omron Body Fat Analyzer HBF-306 (Omron Healthcare, Inc.; Vernon Hills,
IL).
Blood pressure was measured in duplicate at baseline, week 3, week 6, and week
9 using a ReliOn HEM-780REL (Omron, Inc.; Bannockburn, IL) automated blood
pressure cuff. Subjects were instructed to place feet flat on the floor and not speak during
the measurement. Systolic, diastolic, and heart rate in beats per minute were recorded
separately and the average of the two measurements was used in analysis.
30
Following an eight-hour overnight fast, blood was collected from the antecubital
vein into a serum tube with a Z serum clot activator at week 3 (randomization) and week
9 (end of intervention phase). Serum tubes were gently inverted and stored at room
temperature for 45 minutes to allow for clotting. The blood was then centrifuged at 3,000
rpm for 10 minutes at 4oC in a Sorvall RT 6000B Centrifuge. Following centrifugation,
serum was aliquoted into storage cryovials and stored at -80 oC until analysis.
The lipid profile was analyzed using an LDX Cholestech System, a validated
approach for use in assessment of serum lipids in the published literature [64]. At the
time of analysis, serum samples were thawed until reaching room temperature. 35μL
serum was pipetted into an LDX cassette and placed in the LDX Cholestech System.
Outcome measures included total cholesterol, HDL, LDL, and triglycerides. All samples
were run in duplicate and recorded as an average of the two measurements. Variance of
greater than 10% resulted in a third measurement. The means of the two measures that
were within 10% of each other were averaged for final analysis.
Statistical Analysis. Baseline characteristics between each treatment arm (and between
those who did and did not complete the study) were compared using chi-square tests for
categorical variables and independent t-tests for continuous variables. Attrition rates
between treatment arms were compared using t-tests. Change in all anthropometric and
blood pressure measurements were compared from baseline to post-intervention using
paired t-tests. Lipid parameters were compared from post-washout to post-intervention
using paired t-tests. Post-intervention values were compared between the two treatment
31
arms using linear regression, adjusting for baseline measures; the Wald statistic p-value
for the post-intervention is reported. Measures of dietary intake were compared between
the washout phase and the intervention phase using paired t-tests within each treatment
arm. Intervention-phase values were compared between the two treatment arms using
linear regression, adjusting for washout-phase values; the Wald statistic p-value for the
intervention-phase term is reported. Differences were considered statistically significant
at p < 0.05 for all tests. No adjustments were made for multiple comparisons. Values are
expressed as mean ± standard deviation (SD). All statistical analyses were performed
using Stata 11.1 (StataCorp, College Station, TX).
Results
Subjects. Over the two enrollment periods, seventy-four subjects completed the three-
week washout phase and were randomly assigned to the control group (n=32; 25 women,
7 men) or the grapefruit group (n=42; 32 women, 10 men). Three subjects (all women)
randomized to the grapefruit treatment withdrew from the study during the six-week
intervention phase, resulting in 71 subjects completing the trial. At baseline, there were
no statistically significant differences between groups with regard to demographics,
anthropometrics, or blood pressure (Table 1). No significant differences in baseline
characteristics were observed between non-completers and completers.
Anthropometric and Blood Pressure Changes. Participants in the grapefruit group
demonstrated an average weight loss of −0.61±2.23 kg, a loss that approached
32
significance (p=0.097). Waist circumference and waist to hip ratio were significantly
reduced in those consuming grapefruit by −2.45±0.60 cm (p<0.001) and −0.01±0.01
(p=0.019), respectively. No significant anthropometric changes were observed in the
control group or between groups following the intervention phase after controlling for
baseline values.
Participants consuming grapefruit, but not the control group, demonstrated a
significant reduction in mean systolic blood pressure of −3.21±10.13 mmHg (p=0.039).
Reductions in diastolic blood pressure or resting heart rate were not observed in either
group. No significant differences were observed between groups with regard to blood
pressure following the intervention phase (Table 2).
Energy and Bioactive Intake and Compliance. Overall energy intake, macronutrient and
micronutrient content of the diet were not different between groups during the washout
phase or during the intervention phase. Additionally, no within group changes were
observed between phases in either study arm with regard to energy intake and
macronutrient distribution. Fruit and vegetable intake changed significantly in both
groups during the intervention phase. Fruit intake increased in the grapefruit group by
1.2 servings/day (p<0.001), while intake decreased in the control group by -0.8
servings/day (p<0.001), an effect that was significant between groups (p<0.001).
Vegetable intake also decreased during the intervention phase in the grapefruit group (-
0.7 servings/day, p=0.03).
33
During the intervention phase, daily Vitamin C intake increased from 56.0±29.2
mg to 155.4±74.5 mg in the grapefruit group. This increase was statistically significant
within the group when compared to washout phase values (p<0.001) and when compared
to the mean vitamin C intake during the intervention phase by the control group
(54.5±36.9 mg, p<0.001). Sodium intake also increased in the control group during the
intervention phase from 3381.3±1304.5 mg/day to 3747.3±1371.7 mg/day, which did not
reach statistical significance (p=0.079). This result was not observed in the grapefruit
group; however, a significant difference in sodium intake was observed between groups
during the intervention phase (p=0.012).
Thirty-two of the thirty-nine participants who completed the intervention
treatment logged their grapefruit consumption. Of those subjects, compliance was
recorded at 93±11%. Grapefruit weighed, on average, 298.4±22 grams (Appendix I).
Based on the USDA Flavonoid Content of Selected Foods Database, naringenin and
hesperitin content of pink grapefruit is estimated at 32.64 mg/100g and 0.35 mg/100g,
respectively. No estimates have been made regarding the flavonoid content of the Rio
Red fruit, though previous research has shown similarities in flavonoid content between
the Rio Red and the Thompson Pink juices [65]. Thus, we estimated that naringenin
intake in those consuming grapefruit was 146.2 mg/day, and hesperidin intake was
estimated at 1.57 mg/day.
Lipid Profile. The lipid profile was analyzed for all subjects whose blood was
successfully collected at both pre-randomization and post-intervention visits (n=69). At
34
pre-randomization (post-washout) and following the intervention phase, no significant
difference was observed between groups in regards to any parameter of the lipid profile
(total cholesterol, LDL cholesterol, HDL cholesterol, or triglycerides). However, total
cholesterol decreased significantly in both the intervention and control groups when
compared to their baseline values by -11.7 ± 21.3 mg/dL (p=0.002) and -6.9 ± 17.5
mg/dL (p=0.032), respectively. Additionally, those subjects in the grapefruit group
demonstrated a reduction in LDL cholesterol values of -16.0 ± 41.4 mg/dL (p=0.024)
when compared to their baseline values (Table 4).
Discussion
Several studies have investigated the effects of grapefruit and/or its bioactives for
attenuating the risk for CVD or as a weight loss food, though results are inconclusive.
The present study indicates a beneficial role for daily, pre-meal grapefruit for six weeks
in reducing the risk for CVD by promoting reductions in waist circumference, systolic
blood pressure, and total and LDL cholesterols compared to baseline values, but not
compared to values in those following a control treatment.
Six-week consumption of grapefruit did not result in a statistically significant
reduction in weight in this trial. Energy intake did not change significantly in either the
control or the grapefruit treatments, indicating that grapefruit does not promote a satiety-
induced restriction in energy. Results from previous studies show inconsistent results. In
a four arm study design, Fujioka et al observed a significant reduction in weight in those
consuming whole grapefruit compared to those consuming a placebo pill, while no
35
difference was observed in those consuming grapefruit juice or a grapefruit pill compared
to the placebo pill [19], suggesting that whole grapefruit does promote weight loss.
Conversely, Silver et al showed no difference in weight loss between those consuming
grapefruit, grapefruit juice, or water as preloads in addition to calorie restriction [18]. In
contrast to both of these studies, only our study observed a significant reduction in waist
circumference, a measure of central adiposity, in those randomized to the grapefruit
treatment. To our knowledge, only animal studies, not studies in humans, have shown
the beneficial effects of naringenin on reducing central adiposity [20]. Naringenin also
has known lipolytic effects in animals and cell culture studies [20, 57]. In the present
study a reduction in waist circumference was observed, though body fat percentage was
not changed, suggesting the effect may be specific to central adiposity. Of course,
circumferences are prone to measurement error even when trained personnel take
measures. Despite this, the literature indicates that central adiposity is more highly
correlated with risk for CVD than body fat percentage, suggesting that a reduction in
waist circumference is of greater relevance for cardiovascular health.
Grapefruit consumption also resulted in a significant reduction in systolic blood
pressure. Though the average BMI of participants in this study was 32 kg/m2, the
average baseline blood pressure was, on average, only 119/81 mmHg, suggestive of
borderline prehypertensive status. While our results were statistically significant, it can
be postulated that these effects may be more pronounced in a hypertensive population,
although this will need to be prospectively tested. In fact, many studies have shown a
beneficial effect of citrus intake on blood pressure, though this is the first to show an
36
effect of grapefruit, specifically, on blood pressure or of an effect of citrus on systolic
blood pressure. High flavonoid sweetie fruit intake was associated with a reduction in
diastolic blood pressure in hypertensive men [37]. Hesperidin supplementation has also
resulted in improved flow-mediated dilation of the brachial artery [36], as well as a
reduction in diastolic blood pressure and postprandial microvascular reactivity [38].
Naringenin treatment (0.1 mM) of the rat aortic myocytes resulted in inhibition of
calmodulin-associated phosphodiesterases, ultimately leading to vasorelaxation [21].
This concentration of naringenin is unattainable by the diet, even given the high intake in
our population (estimated at 146.2 mg/day). Nevertheless, the aforementioned pathway
may explain the mechanism by which naringenin intake facilitated the systolic pressure
reductions observed in our population.
Micronutrient content of the diet must also be considered when evaluating blood
pressure change. Potassium intake did not change. Vitamin C intake increased in the
grapefruit treatment group, an increase that was significant compared to baseline values
as well as intervention values in the control group. Vitamin C is a known antioxidant and
a potent scavenger of superoxide [66, 67]. Superoxide is known to inhibit eNOS,
ultimately producing a state of vasoconstriction [67]. Thus, vitamin C has been proposed
as a natural anti-hypertensive treatment, with some evidence to support this hypothesis
[66]. Considered in combination with the proposed effects of naringenin on the
vasculature, this may explain the blood pressure benefit observed in our trial.
Fruit and vegetable consumption changed in both the grapefruit and control
groups during the intervention phase when compared to the washout phase. Fruit intake
37
increased in the grapefruit group, as expected due to the increase in grapefruit
consumption. However, fruit intake decreased in the control group during the
intervention phase, perhaps due to the limited types of fruits and vegetables that they
could consume. Despite this reduction in fruit and vegetable consumption, outcomes
such as weight and blood pressure did not increase as a response in the control group.
Total cholesterol (TC) was significantly lowered in both groups, though this effect
was larger and more physiologically significant in those in the grapefruit group. More
importantly, LDL cholesterol (LDL-C) was reduced by an average of -16.0 mg/dL due to
daily grapefruit consumption. Results from previous research on grapefruit intake and
the lipid profile are extremely variable. Fujioka et al observed no changes in HDL
cholesterol and triglycerides after twelve weeks of treatment [19]. Silver et al observed a
significant increase in HDL in those consuming grapefruit or grapefruit juice as a preload
by 3.0 mg/dL or 4.9 mg/dL, respectively, but observed no changes in any other parameter
of the lipid profile after twelve weeks [18]. However, the present study and all other
studies evaluating citrus and lipid change have not shown this effect on HDL.
Eight-week naringin supplementation (400 mg/day) resulted in a 14% reduction in
TC and a 17% reduction in LDL-C in hypercholesterolemic patients, whereas the same
treatment showed no benefit in individuals with normal cholesterol values [68]. Type of
grapefruit consumed also seems to be an important factor in relation to the cholesterol-
lowering effects of grapefruit, though no mechanism currently exists to explain this
effect. In a study of 57 patients with coronary atherosclerosis, consumption of one ruby
red or white grapefruit for thirty days resulted in reduction in TC and LDL-C compared
38
to controls, but only those eating the ruby red cultivar observed additional reductions in
triglycerides [34]. Despite consuming red grapefruit, our population showed no
significant change in triglycerides possibly because the participants were overall healthy
and any history of cardiovascular disease was an exclusion criterion for the study. While
the grapefruit bioactives have known hypolipidemic effects as observed in many animal
model studies, 500 mg/day or 800 mg/day of naringin or hesperidin, respectively, showed
no benefit on any parameter of the lipid profile in mildly hypercholesterolemic adults
[35]. These results may suggest that the bioactive constituents must be consumed
simultaneously. In addition, fiber is known to reduce circulating cholesterol levels [69];
however, our population demonstrated no change in overall fiber intake. This suggests
that the lipid lowering effects of grapefruit are due to its high bioactive content, and not
its fiber.
The results of the present study regarding improvements in the lipid profile are
particularly robust when coupled with the change observed in waist circumference.
Dyslipidemia, characterized by elevated TC, LDL-C, and triglycerides, and reduced
HDL-C, is a risk factor for CAD and is associated with obesity [43-46]. Interestingly,
visceral adiposity is a much greater predictor of dyslipidemia than BMI [9] and is thought
to be its primary cause [70]. Visceral adipose tissue is more metabolically active than
subcutaneous adipose tissue, characterized by altered lipid metabolism, resulting in
increased triglycerides and LDL-C concentrations in circulation [70]. Thus, the reduction
observed in waist circumference may have triggered the decrease in TC, and particularly,
LDL-C.
39
The lipid lowering effects due to grapefruit are of important clinical significance
in that they may provide a primary prevention approach or an early intervention strategy
prior to pharmaceutical approaches. Statins, the primary lipid-lowering therapy, are
extremely effective at lowering lipids as well as reducing risk for cardiovascular events
and mortality [71]. Despite the benefits of statin therapy, compliance is low with
approximately 60-75% of cardiovascular patients discontinuing therapy within five years
due to side effects [71]. In a small, but significant population, statins may cause adverse
reactions including myalgia, muscular tenderness, pain, and in select cases advance to
extreme muscle weakness, known as myositis [72]. While our results do not compare to
the lipid lowering results of short term statin therapy [73], grapefruit may be considered
as an alternative therapy in those who do not require aggressive lipid reductions or in
those who may experience myositis and other complications.
The results of this study must be interpreted with caution, and the limitations
should be noted. Dietary composition was measured by 24 hour recalls, and a dietary
record may have resulted in greater accuracy, though this may have also increased
participant burden and resulted in greater attrition. Measurement of waist circumference
is also known to have a high degree of variability, even when performed by a trained
individual. Individuals performing measurements were not blinded to treatment
condition, which may have introduced bias, though they were blinded to previous
recorded measures. The Australian Risk Factor Prevalence Study, a study of 9, 279
adults, showed that waist circumference is subject to measurement error of approximately
1.84 cm and concluded that a change greater than 2 cm is statistically significant [74],
40
findings that suggest the change observed in our population is not due to measurement
error alone. Additionally, more precise and objective measures of body composition such
as is provided by dual x-ray absorptiometry, computed tomography, or magnetic
resonance imaging instead of bioelectrical impedance may have enhanced the capacity to
detect significant changes in body composition over time or by treatment group. The
present study was also limited in that physical activity was not measured or recorded.
Participants were instructed to maintain their physical activity regimen, not to exceed ten
hours per week. However, participants may have increased their physical activity, which
may have resulted in the reductions in blood pressure, lipids, and waist circumference.
An increase in fruit intake may also explain the results of this study. Grapefruit intake
was responsible for the increase in fruit consumption in the intervention group. It is
possible that the increase in fruit itself, not grapefruit specifically, may have driven the
positive results observed here. Finally, the present trial may have been limited by time.
Our intervention period lasted only six weeks, as compared to twelve weeks in the two
previous clinical trials evaluating grapefruit in weight and CVD risk factors [18, 19].
Had the trial lasted longer, it is possible that a significant reduction in weight may have
been observed.
Based on the results from the current trial, we conclude that 6 week consumption
of one and a half grapefruit per day is not effective at reducing weight in an overweight
and obese population when compared to a usual dietary intake control group. In spite of
this, grapefruit consumption does elicit beneficial effects compared to baseline values
that are associated with reducing the risk for CVD. We observed a significant decrease in
41
waist circumference, which may have facilitated a reduction in LDL and total cholesterol.
Finally, systolic blood pressure was significantly lowered, an effect not seen before in a
study of grapefruit consumption. Future research must replicate these findings in a larger
sample in order to confirm our results of grapefruit as a lipid and blood pressure lowering
food. Due to the variability in study design as well as outcomes from previous studies, it
will be necessary to elucidate an optimal dose of grapefruit consumption regarding lipid
and blood pressure control. The findings from the present study as well as from previous
studies regarding grapefruit, its bioactives, and similar citrus fruits suggest that grapefruit
may be a beneficial addition to a heart healthy diet and underscores the need for a larger,
longer duration trial.
42
FIGURES
Figure 2. Consort diagram describing the flow of participants through the grapefruit
intervention feeding trial.
Screened for Eligibility n=293
Intervention n=42 ½ ruby red grapefruit before
each meal
Control n=32 Maintain low bioactive
diet
Consented n=85 Consume low bioactive diet
Eat ½ low bioactive fruit before each meal
Completed trial
n=39
Completed trial
n=32
Excluded n=208 Not Willing to Participate n=50
Postmenopausal n=34
BMI out of range n=28
Medication n=22
Metabolic/Inflammatory
Smoker n=17
Weight Loss in prev 6 mos n=9
Lost to follow through n=12
Other n=22
Discontinued Trial n=11 Washout Diet too strict n=6
Wanted to take supplements n=2
Personal reasons n=3
Randomized n=74
Lost to follow up n=3
3-W
EE
K W
AS
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UT
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WE
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IN
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N
43
TABLES
TABLE 1. Baseline characteristics of participants who completed the grapefruit feeding trial:
grapefruit vs. control
Total (n = 71) Grapefruit (n = 39) Control (n = 32)
Age (Years) 41.2±11.0 39.4±10.7 44.0±11.0
Sex, n (%)
Female 54 (76.1) 29 (74.3) 25 (78.1)
Male 17 (23.9) 10 (25.6) 7 (21.9)
Race, n (%)
White 44 (62.0) 24 (61.5) 20 (62.5)
Other 27 (38.0) 15 (38.5) 12 (37.5)
Education, n (%)
High School Degree 26 (36.7) 13 (33.3) 13 (40.6)
Undergraduate Degree 23 (32.3) 15 (38.5) 8 (25)
Graduate Degree 5 (7) 2 (5) 3 (9)
Other 1 (1) 0 (0) 1 (3)
Weight (kg) 91.7±13.6 92.4±14.9 90.8±12.8
BMI (kg/m2) 32.1±4.1 32.9±4.2 31.4±3.8
Body Fat (%) 35.7±6.1 36.3±6.2 35±6.0
Waist Circumference (cm) 103.2±10.5 103.2±11.2 103.3±9.7
Hip Circumference (cm) 116.9±9.4 117.2±10.3 115.4±7.3
W:H Ratio 0.88±0.08 0.88±0.08 0.88±0.08
Systolic (mmHg) 119.1±16.6 118.4±16.9 119.1±15.9
Diastolic (mmHg) 80.6±10.5 80±10.2 81.3±11.1
Heart Rate (bpm) 72.8±11.1 72.6±10.4 73.1±12.1
Data shown indicate mean ± standard deviation. No differences existed between groups at baseline.
44
TABLE 2. Anthropometric and blood pressure changes in participants who completed the grapefruit feeding trial: grapefruit vs control.
Grapefruit (n=39)
Control (n=32)
Change Post-
interventiona
p valueb Change
Post-
interventiona
p valueb p value
c
Weight (kg) −0.61±2.23 90.9 0.098 −0.11±1.1 91.5 0.56 0.302
BMI (kg/m2) −0.23±0.13 31.9 0.09 −0.03±0.06 32.1 0.62 0.362
Body Fat (%) 0.67±1.0 35.8 0.13 0.12±0.3 36.1 0.682 0.307
Waist Circumference (cm) −2.45±0.60 100.0 <0.001 −1.23±0.71 101.8 0.092 0.188
Hip Circumference (cm) −0.77±3.17 116.0 0.135 0.02±0.44 116.8 0.972 0.311
W:H Ratio −0.01±0.01 0.87 0.019 −0.01±0.01 0.87 0.23 0.557
Systolic (mmHg) −3.21±10.13 114.7 0.039 −0.31±12.65 117.6 0.978 0.213
Diastolic (mmHg) −0.90±7.47 79.0 0.367 1.03±8.56 80.0 0.565 0.419
Heart Rate (bpm) −0.72±8.9 72.3 0.529 −2.63±9.62 70.8 0.151 0.425
P values comparing postwashout differences between study arms were insignificant. aPostintervention means are reported after controlling for potential confounders by ANCOVA: BMI, age, sex, and washout-phase values.
bWald statistic from linear regression model comparing post-intervention values within study arms, adjusted for washout-phase values.
cANCOVA comparing postintervention values between study arms, adjusted for washout-phase values, baseline BMI, age, and sex.
45
TABLE 3. Comparison of diet composition in participants who completed the grapefruit feeding trial: grapefruit vs control.
Grapefruit (n=38) p valuea Control (n = 32) p value
a p value
b
Washout Intervention
Washout Intervention
Energy (kcal) 1784±511 1839±488 0.437 1940±730 1913±536 0.791 0.955
Fruit (servings) 1.8±0.2 3.0±0.2 <0.001 1.9±0.2 1.1±0.2 <0.001 <0.001
Vegetable (servings) 3.3±0.3 2.6±0.2 0.03 2.9±0.3 3.1±0.3 0.562 0.115
Fat (g) 69±23 70±25 0.765 77±38 78±29 0.906 0.47
Saturated Fat (g) 23±8 24±10 0.337 25±13 26±10 0.716 0.743
Carbohydrate (g) 220±78 232±73 0.262 240±84 228±67 0.284 0.231
Protein (g) 73±19 74±16 0.74 77±33 78±25 0.709 0.458
Fiber (g) 22±9 23±9 0.62 23±9 21±7 0.199 0.129
Sodium (mg) 3357±1054 3161±836 0.244 3381±1305 3747±1372 0.079 0.012
Potassium (mg) 2545±819 2506±646 0.715 2637±949 2471±740 0.128 0.465
Folate (mcg) 393±151 395±146 0.917 387±161 441±175 0.139 0.184
Vitamin C (mg) 56±29 155±74 <0.001 60±29 55±37 0.372 < 0.001 aPaired t-test comparing dietary intake during the washout and intervention phases within each study arm.
bWald statistic from linear regression model comparing post-intervention values between study arms, adjusted for washout-phase values.
46
TABLE 4. Comparison of the lipid profile in those participants who completed the Grapefruit Feeding Trial: Grapefruit vs Control,
before and after the intervention phase.
Grapefruit (n=37)a p value
c Control (n = 32)
a p value
c p value
d
Pre Post Post
Pre Post Post
TC (mg/dL) 192.6±29.7 180.93±22.9 178.8 0.002 185.8±35.4 178.9±27.4 181.2 0.033 0.587
HDL (mg/dL) 43.7 ±11.8 42.8±11.2 43.4 0.493 41.6±14.0 43.9±13.9 43.8 0.493 0.832
LDL (mg/dL) 122.7±44.4 106.7±30.9 110.5 <0.001 110.6±36.3 106.8±27.2 111.2 0.009 0.871
TG (mg/dL) 111.5±73.3 119.9±68.1 127.4 0.346 133.3±91.4 130.4±72.9 126.7 0.644 0.95
TC = total cholesterol; HDL = high density lipoprotein; LDL = low density lipoprotein; TG = triglycerides. P values comparing
postwashout differences between study arms were insignificant. aLipid parameters were undetectable by the Cholestech LDX System in some serum samples. Grapefruit: TC and HDL (n=37), LDL
(n=34), TG (n=33); control: TC (n=32), HDL (n=31), LDL (n=28), TG (n=30). bPostintervention means are reported after controlling for potential confounders by ANCOVA: BMI, age, sex, and washout-phase
values. cPaired t-test comparing measurements of the lipid profile pre- and postintervention within each study arm
dANCOVA model comparing postintervention values between study arms, adjusted for washout-phase values.
47
CHAPTER 3
DAILY CONSUMPTION OF GRAPEFRUIT FOR SIX WEEKS
DOES NOT REDUCE SVCAM-1, CRP, OR F2-ISOPROSTANES IN
OVERWEIGHT AND OBESE ADULTS
Introduction
Atherosclerotic diseases, characterized by endothelial dysfunction, are the global
leading cause of death [2]. Atherosclerosis is the manifestation of damage to the
endothelium due to a dysregulated cardiometabolic state (elevated lipids, glucose, and
insulin), inflammation and oxidative stress [15]. Individuals with Metabolic Syndrome
(MetS) are at particularly high risk of developing atherosclerosis due to hyperlipidemia
and elevated inflammatory/oxidative processes that develop as a result of visceral
adiposity [2, 15]. Methods to reduce atherosclerotic plaque production via promotion of
a healthy cardiometabolic state and a reduction in inflammatory/oxidative processes are
warranted.
Large epidemiological trials suggest that citrus may be an important component
of a heart healthy diet. The Prospective Epidemiological Study of Myocardial Infarction
(PRIME) in 50-59 year old men found that citrus intake, but not intake of other fruits,
was associated with a reduction in incidence of ischemic events [25]. Data from the
Nurses’ Health Study (NHS) indicate that citrus and grapefruit intake specifically is
associated with lower levels of fasting pro-inflammatory, cardiovascular disease (CVD)-
associated cytokines [39]. Further, an analysis of dietary flavonoid intake in NHS
suggested that high flavonone (flavonoids in citrus) intake, but not other flavonoids,
48
reduced the risk of ischemic stroke [75]. Together, these data suggest both citrus and
grapefruit may promote cardiovascular health.
In addition to epidemiological evidence supporting a role for flavonones in CVD
health, experimental evidence has shown that flavonones exert significant antioxidant,
anti-inflammatory, and antihypertensive properties in cell culture and animal model
studies [21, 36, 76]. Randomized human trials are limited but suggest that flavonones
have endothelial protective properties, though flavonones from orange juice have been
the most widely tested [36, 38]. To date, no randomized human trials have been
conducted to assess the effect of whole grapefruit, rather than flavonone supplements or
orange juice, on outcomes associated with CVD in an at-risk population. Our group
recently demonstrated that six weeks of daily ruby red grapefruit intake significantly
reduced total and low-density lipoprotein (LDL) cholesterol, systolic blood pressure, and
waist circumference (WC) in healthy, overweight and obese adults [77].
The purpose of this secondary analysis was to determine the effect of six-week
consumption of ruby red grapefruit on biomarkers associated with atherosclerotic plaque
production: soluble vascular adhesion molecule-1 (sVCAM-1), high-sensitivity C
reactive protein (hsCRP), and F2-isoprostanes. Further, we sought to examine
associations between classic demographic and anthropometric cardiovascular risk factors
(age, sex, BMI, and WC) and atherogenic biomarkers at baseline and following the
intervention. Lastly, we assessed the role of grapefruit consumption in participants with
elevated risk for cardiometabolic diseases by performing a post hoc analysis on
participants classified as having MetS.
49
Methods
Study Population. The methods and primary results from this randomized, controlled
trial have been reported previously [77]. Briefly, 85 non-smoking healthy men and
premenopausal women over the age of 18 who were free of inflammatory diseases or
history of cancer, heart disease, hypercholesterolemia (≥225 mg/dL), hepatic or renal
disease, or diabetes were enrolled. Eligible participants had a body mass index (BMI)
between 25 and 45 kg/m2. Individuals taking medications metabolized by the
cytochrome P450-3A enzyme were excluded due to potential adverse interaction with
grapefruit [78]. The University of Arizona Institutional Review Board approved this
protocol, and all participants provided informed consent.
Study Design. This study was completed over two grapefruit seasons (winter 2009-10
and winter 2010-11). Participants were enrolled in the trial for a total of nine weeks and
made visits to the clinic at four time points (baseline, week 3, week 6, and week 9).
Following the baseline visit, participants consumed a washout diet, restricted in
bioactive-rich fruits and vegetables and devoid of all citrus fruit and juices. Seventy-four
participants completed the washout diet and were randomized either to the control group
(n=32), in which they continued consuming the low bioactive diet, or to the grapefruit
group (n=42), in which they consumed the low bioactive diet plus half of a fresh ruby
red grapefruit (Texas Rio Star Grapefruit; grown by Rio Queen Citrus, Mission, TX)
before each meal (3x daily) for six weeks. Participants were trained to peel the grapefruit
50
and eat all portions of the fruit, including the innermost white membrane of the fruit (the
albedo), without adding caloric sweeteners to the fruit.
Anthropometry and Blood Pressure Measures. Height, weight, and WC were measured
at baseline, week 6, and week 9. Height and weight were measured to the nearest quarter
inch and the nearest half-pound, respectively. WC was measured at the umbilicus using a
Gulick II (Elmsford, NY) measuring tape. Blood pressure was measured at baseline,
week 3, week 6, and week 9 using a ReliOn HEM 780REL (Omron; Bannockburn, IL)
automated blood pressure cuff following standard procedures [77].
Biosample Collection and Processing. Urine and blood samples were collected at the end
of the washout phase (week 3) and the end of the intervention phase (week 9).
Participants collected a first morning urine sample on the three days prior to their clinic
visit. Urine was stored in ice chests with ice packs until arrival at the research clinic.
The three collections were then pooled and centrifuged at 3,000 rpm for 10 minutes at
4°C. Following an eight-hour overnight fast, blood was collected into serum and plasma
tubes. Plasma and serum were processed following standard procedures [77]. After
centrifugation, plasma, serum, and urine were aliquoted into storage cryovials and stored
at -80°C until analysis.
Biosample Analysis. Serum samples were analyzed for high-density lipoprotein (HDL),
triglyceride, and glucose concentrations using an LDX Cholestech System (Hayward,
51
CA). Samples were run in duplicate and recorded as an average of the two
measurements.
Plasma samples were analyzed for hsCRP and sVCAM-1 concentrations using
enzyme linked immunosorbency assay (ELISA) kits (United States Biological, San
Antonio, TX and R&D Systems, Minneapolis, MN; respectively). The mean inter- and
intraassay coefficients of variation (CVs) were 3.3% and 6.3% (hsCRP) and 13.4% and
6.3% (sVCAM-1), respectively.
F2-isoprostanes were measured in 3-day, first morning, pooled urine samples.
Urine samples were purified by adding three volumes of ethanol to one volume of
sample, vortexed, and cooled to 4°C. Ethanol-sample mixtures were centrifuged for 20
minutes at 1,500xg. The supernatant was then decanted and the ethanol was evaporated
off using a centrifugal evaporator. F2-isoprostanes were quantified in the purified
samples in duplicate via a competitive ELISA kit (Cayman Chemical, Ann Arbor, MI).
Mean inter- and intraassay CVs were 10.8% and 2.5%, respectively. F2-isoprostane
values were corrected for creatinine concentration (Cayman Chemical, Ann Arbor, MI).
Metabolic Syndrome (MetS) Classification. Participants were classified as having MetS
at study entry, post hoc, based on guidelines set by the National Cholesterol Education
Program Adult Treatment Panel III (NCEP:ATPIII) [79]. MetS classification requires the
presence of at least three of the following five criteria: elevated triglycerides (>150
mg/dL), reduced HDL (<40 mg/dL in men, <50 mg/dL in women), elevated waist
52
circumference (>102 cm in men, >88 cm in women), elevated blood pressure (≥130/≥85
mmHg), or elevated fasting glucose (≥100 mg/dL).
Statistical Methods. Baseline characteristics of participants in each treatment arm (or for
participants with and without MetS) were compared using χ2
tests for categorical
variables and t-tests for continuous variables. Within each treatment arm (total enrolled
and only those with MetS), inflammatory and oxidative stress markers were compared
from pre- to post-intervention using paired t-tests. Change values (total enrolled and only
those with MetS) were compared between the two arms using linear regression,
controlling for baseline values.
Linear regression models were conducted to explore the relationship between risk
factors of cardiometabolic diseases and levels of inflammatory/oxidative stress markers
in the entire cohort at baseline and in each arm separately post-intervention. Potential
interactions between cardiometabolic risk factors and treatment arm on each post-
intervention biomarker outcome were tested using likelihood ratio tests. Analyses were
performed using Stata 12.1 (StataCorp, College Station, TX).
Results
Three participants randomized to the grapefruit group were lost to follow up
during the intervention phase, and blood collections were unsuccessful for two additional
participants, leaving 37 and 32 participants randomized to the grapefruit and control
groups, respectively. Participants had a mean ± standard deviation (SD) age of 41.8±10.7
53
years and BMI of 32.1±4.1 kg/m2 (Table 5). Of the 69 participants who successfully
completed the study, 29 (42%) were classified as having MetS at baseline. There were
no statistically significant differences at baseline for any measurement, including
inflammatory/oxidative stress measurements between randomization groups.
Changes in inflammation and oxidative stress were analyzed within and between
randomization arms. No significant difference was detected with regard to change in
sVCAM-1 values from baseline to post-intervention between groups (Table 6a); changes
in sVCAM-1 were also not significant over time within treatment groups. Though not
statistically significant, hsCRP values decreased in in the grapefruit group and increased
in the control group; the difference in hsCRP change score between groups was
marginally significant (p=0.073). Similarly, F2-isoprostanes decreased in the grapefruit
group and increased in the control group, demonstrating a difference that approached
significance in F2-isoprostane change between groups (p=0.063).
To further explore the effect of grapefruit consumption on cardiometabolic risk
factors, post hoc analyses of participants with MetS were performed (n=14 in the
grapefruit arm, n=15 in the control arm). At baseline hsCRP values averaged 2.7±1.6 in
participants with MetS compared to 2.0±1.8 in participants without MetS a difference
that was marginally significant (p=0.076). In an analysis restricted to those with MetS,
there was no significant change in sVCAM-1 regardless of group assignment nor were
there any differences between groups at the post-intervention timepoint (Table 6b).
Similar null results were shown for hsCRP values. Similar to the results from the entire
cohort, F2-isoprostane values in participants with MetS were marginally significantly
54
lower in the grapefruit intervention group compared to the control group, post-
intervention (11.9±4.7 vs. 18.3±10.9, respectively; p=0.058).
Associations between CVD risk factors (BMI, waist circumference, age, and sex)
and inflammatory/oxidative stress markers (sVCAM-1, hsCRP, and F2-isoprostanes)
were tested at baseline in the entire cohort and post-intervention in each arm separately.
At baseline, sVCAM-1 values were associated with age, hsCRP values were associated
with BMI and waist circumference, while F2-isoprostanes were only associated with WC
(p<0.05 for all associations, Table 7). WC and post-intervention F2-isoprostanes were
significantly inversely related in the grapefruit arm, but they were positively associated in
the control arm (test for waist-by-assignment interaction, p=0.004). There was also a
nonsignificant inverse association between male sex and F2-isoprostanes in the
grapefruit, but not the control, arm (test for sex-by-assignment interaction, p=0.015).
Discussion
In this first randomized trial assessing grapefruit consumption on biomarkers
associated with inflammation/oxidative stress and, more specifically, atherosclerotic
plaque production, we found that six weeks of daily grapefruit consumption did not
reduce sVCAM, hsCRP and F2-isoprostane levels. However, in a subsample of
participants with MetS, those who consumed grapefruit demonstrated marginally
significantly lower F2-isoprostane values compared to those assigned to the control
condition following the intervention.
55
VCAM-1 is an adhesion molecule expressed by endothelial cells and vascular
smooth muscle cells in response to inflammatory/oxidative stimuli [80], and circulating
values correlate with risk of coronary death [81]. In vitro work also indicates that
flavonoids may attenuate inflammatory-induced adhesion molecule expression [82]. To
date, two studies have evaluated the effects of citrus flavonoids (in the form of orange
juice or its main flavonoid, hesperidin) on sVCAM-1 levels. Daily consumption of
orange juice or a hesperidin enriched beverage for four weeks nonsignificantly lowered
sVCAM-1 levels in overweight men [38]. In line with our results, a study of 3 week of
daily hesperidin supplementation (500 mg/day) in participants with MetS did not change
sVCAM-1 levels [36]. Our results are also supported by a similar study using high
polyphenol grape powder for 30 days wherein no change in sVCAM-1 levels in men with
MetS was demonstrated. In that trial other outcomes associated with endothelial health
did improve (e.g. flow mediated dilation, soluble intercellular adhesion molecule-1),
though these measures were not assessed in our study [83]. Epidemiological evidence
from NHS indicated that women with the highest flavonol intake had a 4% reduction in
sVCAM-1 levels compared to women in the lowest quintile of intake [39]. These data,
coupled with our own, suggest that sVCAM-1 levels are not highly responsive to short-
term exposures of flavonoid intake, but long term, habitual intake may promote healthy
sVCAM-1 values.
A significant body of evidence suggests that CRP is associated with risk of CVD
[84] [80]. CRP was once considered a pathologically insignificant hepatic marker of a
larger inflammatory cascade, but more recent evidence demonstrates that CRP is also
56
produced by the endothelium in response to injury [80] and has proatherogenic properties
[2]. In the epidemiological NHS, Landberg et al. showed that grapefruit intake (≥1
serving/day) was inversely associated with CRP values [39], in contrast to findings of our
randomized, controlled trial that showed no significant reduction in CRP in response to
eating 3 servings/day for a period of six weeks. These inconsistent results may reflect
differential periods of exposure or could suggest our study was underpowered to detect a
significant change. [39]. Alternately, our dose may have been inadequate to induce short-
term changes in inflammatory markers. A recent randomized crossover study by Dalgard
et al. resulted in an 11% reduction in CRP values after four-week consumption of orange
and blackcurrant juices compared to a placebo drink in participants with peripheral artery
disease (PAD) [40]. Of note, a study in healthy adults who consumed 500 mL orange
juice for 14 days demonstrated a nonsignificant reduction in CRP [85]. These findings
suggest that the health status of the cohort may explain differential effects demonstrated
across the published studies. Patients with vascular diseases may benefit more from
consumption of a high polyphenol/flavonoid diet than overall healthy individuals.
F2-isoprostanes are a validated marker of lipid peroxidation, a key mechanism
leading to atheroma formation [86]. Previous studies have shown a reduction in plasma
F2-isoprostanes following orange juice consumption in healthy adults [85] as well as in
patients with PAD consuming orange and blackcurrant juices [40]. Our intervention
resulted in a nonsignificant reduction in F2-isoprostanes in those consuming grapefruit,
compared to a rise in F2-isoprostanes in the control participants, consistent with results
observed in the orange and blackcurrant juices study [40].
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Data from the Framingham Heart study indicate that visceral adiposity is highly
correlated with isoprostane values [13]. At baseline, WC was positively associated with
isoprostane values. Grapefruit consumption modulated this relationship and resulted in
an inverse association between baseline WC and F2-isoprostane values, a result not seen
in the control group. However we cannot ascertain if the reduction in isoprostanes was
directly due to grapefruit consumption or if it was an outcome secondary to WC
reduction, as we had previously shown a significant reduction in WC following six weeks
of grapefruit consumption [77].
Further, individuals with MetS have an increased WC and present with greater
levels of oxidative stress [87]. Thus, it is not surprising that the subpopulation of MetS
individuals consuming grapefruit seemed to be particularly protected from increases in
F2-isoprostanes compared to MetS participants in the control group. Though not
statistically significant, these results are particularly striking given the very small
subsample size.
This study has both strengths and limitations. This randomized controlled trial
evaluated the anti-inflammatory and antioxidant effects of ruby red grapefruit, a widely
available whole food, in overweight/obese individuals, a population that is subject to high
rates of CVD [15]. Outcomes were also evaluated in a subsample of participants with
MetS, a population with a 2 to 5-fold increased risk of CVD compared to metabolically
healthy controls [88]. The original trial was powered for change in weight [77], not
inflammatory/oxidative biomarkers. Nevertheless, grapefruit consumption did lead to
reductions in these markers compared to the control condition, suggesting these
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interventions should be tested in a larger sample before definitive conclusions can be
drawn. In our sample baseline sVCAM-1 values were more similar to those of a healthy
population [39], while previous studies in patients with MetS [83] or coronary artery
disease [81] show that circulating sVCAM-1 values may be as much as 2-3-times greater
in at-risk populations. This may explain why sVCAM-1 values did not change in relation
to the grapefruit intervention. A similar intervention in a high-risk population may be
beneficial given previous findings demonstrating sVCAM-1 responsiveness to flavonoids
[82, 89].
Atherosclerosis develops in response to multiple stimuli and signaling pathways
and the cardioprotective response to grapefruit could potentially be detected using a
variety of biomarkers. Here we evaluated biomarkers with the most robust preliminary
data in relation to the pathogenesis of atheroma formation and responsiveness to dietary
flavonoids. Overall, our results cannot support daily citrus and/or grapefruit to
significantly modify CVD risk associated with the selected biomarkers.
Coupled with previous research, our trial suggests future research in the field of
grapefruit/citrus consumption and cardioprotection should focus on populations at high
risk for cardiovascular disease, including MetS individuals, in a sufficiently large sample
size to test these important hypotheses.
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Tables
TABLE 5. Baseline characteristics of participants who successfully completed all study activities (n=69)
Total (n=69) Grapefruit (n=37) Control (n=32)
Age (y) 41.8±10.7 40.6±10.8 43.2±10.6
Female, n (%) 48 (69.6) 25 (67.6) 23 (71.9)
Non-Hispanic white
race/ethnicity, n (%) 43 (62.3) 23 (62.1) 20 (62.5)
Weight (kg) 91.5±13.9 92.1±15.0 90.8±12.8
Body mass index (kg/m2) 32.1±4.1 32.8±4.2 31.4±3.8
Waist circumference (cm) 103.0±10.2 102.8±10.7 103.3±9.7
Systolic blood pressure (mmHg) 119.7±16.5 120.5±17.7 118.7±15.2
Diastolic blood pressure (mmHg) 80.9±10.5 81.9±10.9 79.7±10.1
Metabolic Syndrome, n (%) 29 (42.0) 14 (37.8) 15 (46.9)
Blood Pressure not available for one participant: n=31 in control group. No differences were
found between groups at baseline for any measure.
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TABLE 6. Change in biomarkers (mean ± SD) associated with atherosclerotic plaque production in participants enrolled in a six-week
grapefruit feeding trial
2a. Entire cohort (n=69)
Biomarker
Grapefruit (n=37)
Control (n=32)
Difference
between arms
P-valueb
Pre Post
Paired t-test
p-valuea
Pre Post Paired t-
test p-valuea
sVCAM-1 (ng/mL) 627.6 ± 117.0 614.3 ± 122.5 0.114 623.0±125.1 610.5±110.5 0.261 0.987
hsCRP (mg/L) 2.2±1.5 2.1±1.5 0.596 2.4±2.0 2.8±2.0 0.136 0.073
F2-isoprostanes
(ng/mg creatinine) 14.1±7.7 12.4±6.4 0.092 14.7±6.5 15.9±9.0 0.452 0.063
2b. Participants with Metabolic Syndrome (MetS) at baseline (n=29)
Biomarker
Grapefruit (n=14) Control (n=15)
Difference
between arms
P-valueb
Pre Post
Paired t-test
p-valuea
Pre Post Paired t-
test p-valuea
sVCAM-1 (ng/mL) 665.5±133.7 650.1±144.8 0.540 603.1±86.3 594.1±93.6 0.303 0.840
hsCRP (mg/L) 2.3±1.7 2.0±1.0 0.380 3.1±1.5 3.1±1.6 0.966 0.106
F2-isoprostanes
(ng/mg creatinine) 14.3±6.7 12.0±4.5 0.239 15.0±6.9 18.3±10.9 0.257 0.058
No differences were found between groups at baseline for any biomarker. A definitive value for biomarkers was not determined in all
samples: sVCAM-1: n=36, n=30; hsCRP: n=36, n=30; F2-isoprostanes: n=34, n=32. aChange in biomarker within each arm using paired t-tests.
bDifference between arms post-intervention, adjusting for baseline value of biomarker, using linear regression.
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TABLE 7. Associations between common cardiovascular disease (CVD) risk factors and inflammatory/oxidative stress biomarkers
in participants enrolled in a grapefruit feeding trial (n=69)
Biomarker
CVD risk
factor
Predicted Effect on
Biomarker at
Baseline (95% CI)a Predicted change in biomarker (95% CI)
b P interaction
c
Control Arm Grapefruit Arm
sVCAM-1
(ng/mL) BMI (kg/m
2) −0.84 (-8.21, 6.54) −0.26 (-5.75, 5.23) −1.61 (-5.77, 2.55) 0.681
Waist (cm) −0.16 (-3.12, 2.79) −0.29 (-2.42, 1.83) −0.81 (-2.42, 0.81) 0.661
Age (y) 3.15 (0.49, 5.80)* −0.12 (-2.08, 1.84) 1.0 (-0.71, 2.71) 0.184
Sex (male) 26.47 (-89.89, 36.95) −36.17 (-6.16, 78.50) −2.41 (-34.95, 39.77) 0.161
hsCRP (mg/L) BMI (kg/m2) 0.15 (0.05, 0.25)* 0.02 (-0.11, 0.16) 0.02 (-0.08, 0.12) 0.662
Waist (cm) 0.06 (0.02, 0.10)* −0.03 (-0.08, 0.02) 0.02 (-0.02, 0.06) 0.220
Age (y) 0.01 (-0.02, 0.05) −0.02 (-0.06, 0.03) 0.003 (-0.032, 0.039) 0.486
Sex (male) 0.01 (-0.94, 0.92) -0.22 (-0.83, 1.23) 0.28 (-1.10, 0.54) 0.425
F2-isoprostanes
(ng/mg creatinine) BMI (kg/m
2) 0.10 (-0.33, 0.53) 0.50 (-0.29, 1.28) −0.20 (-0.59, 0.18) 0.076
Waist (cm) 0.19 (0.02, 0.36)* 0.32 (0.02, 0.63) −0.16 (-0.32, −0.01) 0.004
Age (y) 0.10 (-0.06, 0.26) −0.07 (-0.36, 0.22) −0.06 (-0.21, 0.10) 0.914
Sex (male) 2.16 (-5.95, 1.64) 5.78 (-12.30, 0.74) −2.68 (-0.75, 6.11) 0.015 aLinear regression models testing associations between risk factors and biomarkers in the entire cohort at baseline and
bwithin each
arm post-intervention, adjusting for baseline values. .
cLikelihood ratio test for interactions between intervention arm and each CVD risk factor on each biomarker, post-intervention.
*Significant association between risk factor and biomarker at baseline, p<0.05.
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CHAPTER 4
GRAPEFRUIT INCREASES POSTPRANDIAL INSULIN AND ATTENUATES
THE RISE IN F2-ISOPROSTANE AND IL-6 CONCENTRATIONS ASSOCIATED
WITH CONSUMPTION OF A HIGH-FAT, HIGH-CALORIE MEAL
Introduction
There is a large body of evidence indicating that each meal incites an inflammatory
response that promotes the development of atherosclerosis [42, 90]. Meal consumption
results in a postprandial period which lasts 4-8 hours, depending on meal size and
macronutrient composition. With the Westernization of food and dietary behaviors, meal
size and frequency have increased; thus, humans spend the majority of each day in the
postprandial state [44, 91]. The postprandial period represents a dynamic phase of metabolic
trafficking and transport of macronutrients, micronutrients, and phytochemicals [42], all of
which come into direct contact with the endothelium via vascular transport. As compared to
prudent meals low in fat and refined carbohydrates, a Western-style diet, high in refined
carbohydrates and fat, is associated with greater postprandial dysmetabolism (hyperglycemia
and hypertriglyceridemia) and is recognized as a pro-inflammatory and pro-oxidative pattern
of eating [92]. Due to the exaggerated metabolic and inflammatory perturbations caused by
this type of diet, a Western pattern of eating is considered causal in the development of
endothelial dysfunction and atherosclerotic plaques [92-95]. Further, spikes in glucose and
triglycerides induced by Western meal consumption that are repeated multiple times daily
may eventually contribute to an increased risk of coronary artery disease (CAD) [92].
63
Ultimately, the purpose of studying the postprandial period is to determine how this
detrimental short, but repetitive exposure to metabolic dysregulation may be modified to
reduce cardiovascular disease (CVD) risk. One plausible approach would be to introduce
foods into the diet with some regularity that would attenuate the endothelial “damage”
promoted during the postprandial period. While data are limited, evidence from a few
postprandial studies indicate that consuming an antioxidant-rich food (e.g. orange juice,
blackcurrant juice, raisins) with a high-fat, high-calorie (HFHC) meal significantly reduces
the pro-inflammatory and pro-oxidative processes that foster atherosclerotic plaque
development induced by the rest of the meal [49, 50, 96].
Large epidemiological trials also suggest that citrus, specifically grapefruit, may
promote cardiovascular health [25, 39]. As a citrus fruit, grapefruit contains appreciable
amounts of the flavonoids naringenin and hesperitin. These bioactive compounds may
explain grapefruit’s cardioprotective properties as these flavonoids have been shown to exert
hypoglycemic, hypolipidemic, antioxidant, and anti-inflammatory properties in cell culture
[97], animal models [20, 98], and randomized human trials [35, 36, 38, 77].
While results from postprandial studies suggest that eating an antioxidant rich food
with an HFHC meal attenuates the oxidative/inflammatory stress induced by the meal and
improves endothelial function [38, 49-51], there are still significant gaps in this field of
research. The beneficial role of grapefruit as a cardioprotective food has been
demonstrated across the spectrum of studies from large population trials to cell culture
studies [20, 25, 35, 36, 38, 39, 52, 77, 97]. However, there has yet to be a trial examining
the acute, postprandial effects of grapefruit when consumed with an HFHC meal on
64
biomarkers associated with cardiovascular health and disease in humans. Furthermore,
traditional American breakfast meals are typically high in calories and laden in fat, and
grapefruit is a common breakfast food. Thus, it is reasonable to study grapefruit
consumption with an HFHC breakfast meal, as it is a feasible meal option when
considering the human condition. Additionally, trials to date have failed to evaluate the
effects of any bioactive-rich food beyond a single meal. The purpose of this crossover,
double meal challenge, postprandial pilot trial was to evaluate the potential endothelial
protective role of grapefruit on HFHC meal-induced dysmetabolism, inflammation, and
oxidative stress in healthy, overweight and obese adults.
Methods
Participants. Five men and five women who participated in a 6-week grapefruit feeding
trial aimed at evaluating the impact of daily consumption of ruby red grapefruit (Texas
Rio Star Grapefruit, grown by Rio Queen Citrus; Mission, TX) on anthropometry, blood
pressure, lipids, and inflammation/oxidative stress [77] were enrolled in this ancillary
postprandial study. All volunteers completed the feeding trial at least two weeks prior to
participation in this study and abstained from consumption of citrus fruits and juices and
the use of anti-inflammatory drugs while enrolled in the postprandial study. Eligible
participants included healthy, nonsmoking men and premenopausal women with a body
mass index (BMI) between 25-45 kg/m2. Potential participants were excluded if they
reported a history of chronic conditions including cancer, inflammatory disease, hepatic
or renal disease, diabetes, hypercholesterolemia (>225 mg/dL), or heart disease.
65
Individuals using medications to control lipids or inflammation or drugs metabolized by
the cytochrome P450-3A enzyme were excluded due to potential interactions with
grapefruit [78]. The University of Arizona Institutional Review Board approved this
study protocol, and all participants provided written informed consent.
Study design. On the day prior to the postprandial investigation, participants were asked
to abstain from vigorous physical activity and alcohol consumption. Participants reported
to the laboratory following a 12-hour overnight fast on two individual test days, separated
by at least one week. Upon arrival, a flexible indwelling catheter was fixed to the
antecubital region of one arm where it remained for the subsequent 8.5 hours, and a
fasting blood sample was collected. Participants were then given an HFHC breakfast
meal consisting of scrambled eggs, a biscuit with butter, and a sausage patty (740 kcal, 28
g protein, 48 g fat, 17 g saturated fat, 51 g carbohydrate, 2 g fiber), which was consumed
within 20 minutes. On test day one, all participants ate one ruby red grapefruit (68 kcal,
1 g protein, 0 g fat, 16 g carbohydrate, 2.5 g fiber) with the breakfast meal. Four hours
after breakfast a second HFHC meal was provided, which included a double
cheeseburger and French fries (670 kcal, 28 g protein, 34 g fat, 12.5 g saturated fat, 63 g
carbohydrate, 5 g fiber) and was consumed within 20 minutes. Participants were
permitted to drink water ad libitum for the duration of each test day.
In addition to the baseline blood collection, samples were taken 30 minutes and 2,
5, and 8 hours after consumption of the breakfast meal. Blood was collected into serum
66
and heparin-coated plasma tubes and processed following standard procedures [77].
After centrifugation, samples were aliquoted into storage cryovials and stored at -80°C.
Biosample analysis. Blood samples from all time points collected on each test day were
analyzed for metabolic, inflammatory, or oxidative stress biomarkers. Glucose and
triglycerides were measured in plasma samples using colorimetric assay kits (Cayman
Chemical, Ann Arbor, MI). Insulin concentrations were quantified in plasma samples
using a monoclonal antibody enzyme linked immunosorbency assay (ELISA) kit (Dako
Ltd., Carpinteria, CA). sVCAM-1, sICAM-1, and IL-6 concentrations were measured in
serum samples via ELISA (R&D Systems, Minneapolis, MN). All samples for each
subject were analyzed in duplicate on the same plate, and inter- and intra-assay
coefficients of variation (CVs) were less than 10% for all analytes.
To measure F2-isoprostanes, plasma was mixed with 15% potassium hydroxide in
equal volumes and incubated at 40C for 60 minutes. The samples were then neutralized
by addition of three volumes of 1M potassium phosphate buffer to one volume of sample.
The prepared samples were purified by adding 3 volumes of ethanol to one volume of
sample, followed by vortexing and incubation at 4C for 5 minutes. Ethanol-sample
mixtures were centrifuged at 1500xg for 10 minutes. The supernatant was then decanted
and the ethanol was evaporated off using a centrifugal evaporator. Finally, F2-
isoprostanes were quantified in the purified samples using a competitive ELISA kit
(Cayman Chemical, Ann Arbor, MI). Inter- and intra-assay CVs were below 10%.
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Statistical Methods. Median biomarker concentrations (glucose, insulin, triglycerides,
IL-6, sVCAM-1, sICAM-1, and F2-isoprostanes) were compared between test days at
each time point using Wilcoxon sign-rank tests. The median area under the curve (AUC)
for each biomarker was calculated using the trapezoidal rule [99] for each participant on
each test day and compared between test days using Wilcoxon sign-rank tests. Findings
were verified using student’s t-tests. Wilcoxon rank-sum tests were used to evaluate the
relationship between CVD risk factors, such as BMI (overweight and obese) and gender
(male and female), and the AUC of each metabolic/inflammatory/oxidative stress
outcome. Spearman correlation coefficients were performed to evaluate the relationship
between age and the AUC of each outcome. Analyses were performed using Stata 12.1
(StataCorp, College Station, TX).
Results
Baseline demographics and compliance. Participants included five men and five women
with mean age of 47.5 ± 11.1 years. Participants had a mean BMI of 31.3 ± 2.6 kg/m2
(Table 8). All participants reported compliance with the dietary and activity restrictions
while enrolled in the trial, and all blood draws were completed according to study
protocol. However, only plasma, and not serum, was collected from one participant at
the final time point on both days; thus, final concentrations of IL-6, sVCAM-1, and
sICAM-1 were not available for this participant.
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Impact of HFHC meal consumption, with and without grapefruit, on cardiometabolic
biomarkers. As expected, no differences were detectable in baseline values of any
biomarkers between test days. Median insulin concentrations were significantly higher
30 minutes and 2 hours after HFHC+grapefruit (GF) consumption compared with HFHC
consumption alone (63.2 versus 24.2 μIU/mL, P=0.007 and 31.7 versus 23.2 μIU/mL,
P=0.025, respectively; Figure 3). Additionally, serum IL-6 concentrations were
significantly lower 30 minutes after the HFHC+GF meal compared with HFHC alone
(0.077 versus 0.862 pg/mL, P=0.017). Interestingly, median sVCAM-1 was significantly
higher at hour 5 following HFHC+GF compared with HFHC alone (498 versus 482
ng/mL, P=0.017). HFHC+GF meal consumption resulted in lower F2-isoprostane values
after 5 hours versus HFHC alone (45.5 versus 77.0 pg/mL, P=0.013), though no
significant differences were observed by 8 hours. Furthermore, glucose, triglyceride, and
sICAM-1 concentrations were not significantly different at any time point between test
days.
There were no differences in median AUC for most biomarkers between test days
(Table 9). Median AUC insulin concentration was higher following HFHC+GF meal
consumption as compared to the HFHC alone (371.5 versus 247.7 μIU/mL, P=0.059).
Conversely, F2-isoprostanes were lower when the meal was consumed with grapefruit as
compared to when the meal was consumed without grapefruit (403.7 versus 556.0 pg/mL,
P=0.114), though this difference was not statistically significant.
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Cardiometabolic biomarkers and potential confounders. Finally, the relationship
between the AUC of each biomarker and risk factors associated with CVD were
evaluated. BMI category (overweight versus obese) was associated with AUC IL-6
values. When the HFHC+GF meal was consumed, the median AUC IL-6 was higher in
overweight than obese individuals (19.3 versus 2.8 pg/mL, P=0.087). Likewise, when
the meal was consumed alone, the median AUC IL-6 was higher in overweight than
obese individuals (18.1 versus 7.3 pg/mL, P=0.139). All other biomarker outcomes were
not different based on BMI status, and none of the biomarkers were associated with
gender (data not shown). Spearman’s correlation coefficients were calculated for the
relationship between age and AUC of each biomarker. F2-isoprostane values were
inversely correlated with age on both test days (HFHC: rho= -0.585, P=0.080;
HFHC+GF: rho= -0.659, P=0.039), though no significant correlations were found
between age and other biomarkers (data not shown).
Discussion
In this first double meal, postprandial trial evaluating the effects of grapefruit on
endothelial health, grapefruit consumption resulted in a significant increase in insulin and
a reduction in IL-6 during the first two hours following a meal, and a reduction in F2-
isoprostanes following the second, pro-inflammatory meal. No differences were detected
in glucose, triglycerides, or sICAM-1 when an HFHC meal was eaten alone or with
grapefruit, while sVCAM-1 values were higher following HFHC meal consumption with
grapefruit.
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Insulin is well characterized for its role in glucose metabolism. Insulin signaling also
plays a vital role in the maintenance of endothelial health and vasoreactivity as it induces
nitric oxide (NO) production via activation of the phosphatidylinositol-3 kinase-protein
kinase B-endothelial NO synthase (PI3K-PKB-eNOS) pathway [100]. Insulin resistance
leads to the loss of vascular tone and endothelial reactivity and ultimately increases the
risk of endothelial dysfunction and atherogenesis [100]. In this study, serum insulin
concentrations were significantly higher 30 minutes and two hours after eating the HFHC
meal with grapefruit than when the meal was eaten alone. This response is considered
favorable in that it reflects an immediate and necessary biological response to maintain
glucose homeostasis within cells. Ghanim, et al. observed a similar pattern in
postprandial insulin concentrations in a study assessing the effects of HFHC meal
consumption with orange juice. Insulin concentrations were significantly higher in
response to an HFHC meal+orange juice (OJ) compared with an HFHC meal consumed
with an isocaloric glucose beverage [49]. Interestingly, in the Ghanim trial, beverages
were matched for glucose intake (75 g), though one-hour postprandial glucose values
were suppressed following HFHC+OJ consumption compared with HFHC alone. In the
current study, participants consumed an extra 16 g carbohydrate with the HFHC+GF
meal, though circulating glucose values were not significantly different between test days
at any time point, suggesting the grapefruit supported greater insulin sensitivity in
response to an HFHC meal. These results also suggest that citrus foods may influence
beta cell secretion of insulin, thus increasing glucose uptake in the cells and reducing
postprandial blood glucose concentrations, though we cannot ascertain if the observed
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increase in serum insulin concentrations had any direct effect on endothelial function. It
is possible that the hyperinsulinemic response to the HFHC+GF diet may have been due
to the extra 16 g of carbohydrate delivered by the grapefruit and that the results observed
here were not due to activity of grapefruit-specific flavonoids. However, 16 g is a
relatively modest carbohydrate load, and may not have had any notable effect on insulin
secretion. Further exploration is warranted given that this immediate hyperinsulinemic
response to citrus in the postprandial period has now been demonstrated in two studies.
Our results related to postprandial inflammatory response are intriguing. Evidence
indicates that flavonoids and other polyphenols reduce inflammatory processes linked to
CVD, in part by reducing IL-6 [101, 102], a cytokine known to promote inflammatory
processes in atherosclerotic plaques and vascular smooth muscle cells [103]. IL-6 was
significantly reduced two hours after HFHC+GF meal consumption in this study. These
findings are supported by previous studies, which have demonstrated reductions in IL-6
in response to high-fat meals consumed with tomatoes [104] or strawberries [49, 105].
Surprisingly, IL-6 concentrations were also nonsignificantly higher in overweight
compared to obese individuals in this study. These findings disagree with reports that
show that IL-6 is positively associated with BMI and waist circumference in men and
women [106, 107] and may suggest an adaptive response in people with prolonged
exposure to adipokine-associated inflammatory response. It is also possible that this
difference was observed by chance due to the small sample size. Of note, IL-6 was more
responsive to grapefruit in obese individuals as compared to overweight subjects wherein
IL-6 was relatively unchanged in response to the addition of GF to the meal. These
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findings may suggest a potential underlying inflammatory pathology in overweight
individuals that is less responsive to dietary change.
Adhesion molecules are intrinsically involved in the promotion of endothelial
dysfunction and atheroma formation, as they facilitate pavementing of monocytes to the
endothelium [108]. sICAM-1 is produced by the monocytes themselves, whereas
sVCAM-1 is expressed by the endothelium. The majority of work evaluating endothelial
responses during the postprandial period has focused on the effects of dietary fat, and
numerous reports indicate that these adhesion molecules are responsive to varying dietary
fat loads and types in the postprandial period [109-112]. In this study, grapefruit
consumption did not significantly impact the effect of an HFHC meal on sICAM-1
values. Very little research has evaluated sICAM-1 or sVCAM-1 in response to a
flavonoid or polyphenol-rich food in the postprandial period, though a study with a
similar design in overweight individuals indicate that neither adhesion molecules were
significantly lower when a high-fat meal was consumed with polyphenol-rich raisins
[96]. Interestingly, in our study, significantly higher levels of sVCAM-1 were observed
five hours post breakfast meal + GF consumption compared to the HFHC meal. The few
studies that have evaluated the postprandial effects of citrus (in the form of orange juice)
have not evaluated sVCAM-1 [49, 95, 113], limiting the ability to make comparisons.
However, in vivo work suggests that flavonoids can inhibit inflammatory-induced
sVCAM-1 expression [82, 114], though the effect of citrus flavonoids, specifically, has
not been evaluated. Given the evidence that suggests that citrus is cardioprotective and
promotes endothelial health, it is possible that the effects on sVCAM-1 were observed by
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chance due to the small sample size. Nevertheless, these results indicate that grapefruit is
unlikely to significantly decrease sICAM-1 or sVCAM-1 in response to HFHC meal
feeding.
Flavonoids benefit biological systems through a variety of functions, though the most
well-known and characterized mechanisms are through antioxidant activities [42, 115].
Lipid peroxidation is particularly important in the context of endothelial dysfunction, as
oxidized lipids or lipoproteins are often involved in the primary insult to the endothelium,
thus propagating inflammatory processes and eventual atheroma formation [6, 44].
Previous postprandial evaluations of the effect of flavonoid-rich foods such as
strawberries or cocoa on oxidative stress have suggested that these foods are effective at
reducing lipid peroxidation (oxidized low-density lipoprotein or F2-isoprostanes) induced
by meal consumption [48, 116]. In this study, the AUC of F2-isoprostanes was
marginally lower when the HFHC meal was eaten with grapefruit versus alone, and F2-
isoprostanes were significantly lower 5 hours after HFHC meal consumption with
grapefruit. Importantly, this reduction in F2-isoprostanes was apparent after the second
meal was consumed in this double meal challenge, suggesting an increased serum
antioxidant capacity that accumulated during the first four hours of the challenge. In
agreement with the results shown here, a 3-hour postprandial study in 16 healthy young
adults resulted in higher serum antioxidant capacity and reduced lipoprotein oxidation
following intake of a citrus flavonone mixture or orange juice compared with a placebo
beverage [52]. Ghanim, et al. observed reductions in p47phox
expression, nuclear factor
κB binding, and reactive oxygen species generation in polymorphonuclear cells following
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HFHC meal +OJ compared with meal alone [49], indicating that, postprandially, citrus
constituents may suppress cellular mechanisms involved in oxidative stress. The data
shown here, taken in consideration with previous work, suggest that citrus foods improve
postprandial oxidative metabolism, and these benefits may extend beyond a single meal.
There are strengths and limitations of this study. This is the first trial to evaluate
grapefruit as a cardioprotective dietary agent in the postprandial period, despite
epidemiological and basic science studies that indicate that grapefruit may be an
important constituent of a heart healthy diet. Additionally, to our knowledge, this is the
first study to evaluate a flavonoid or polyphenol rich food associated with cardiovascular
health in a double meal challenge design. The findings of this trial suggest that grapefruit
consumption with a HFHC meal may modify insulin and IL-6 response nearly
immediately, while the antioxidant effects of the fruit may be observed after a second
HFHC challenge. However, this trial had a small sample size, which likely explains the
nonsignificant results in some of the outcomes. Furthermore, there was wide variability
in response to the meals, and a larger sample size may resolve this issue. Regardless,
significant outcomes of increased insulin concentrations and reduced IL-6 and F2-
isoprostanes are particularly robust.
In conclusion, the results of this trial suggest that grapefruit consumption with an
HFHC meal modifies some of the selected biomarkers associated with endothelial health
and disease. These findings, coupled with previous research of the postprandial response
to citrus fruits and their flavonoids, highlight the role of citrus as a potential vascular
protective food. These results also underscore the need for studies with larger samples
75
and the potential to study cellular processes in order to elucidate the exact mechanisms by
which citrus benefits the cardiovascular system.
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FIGURE 3. Concentrations of various metabolic, inflammatory, and oxidative stress markers
following consumption of a HFHC meal alone or with ruby red grapefruit
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Tables
TABLE 8. Baseline characteristics of participants who completed the grapefruit double meal
challenge postprandial trial.
Subject Gender Race Age (y) Weight (kg) BMI (kg/m2)
1 female H 40.5 76.8 30.9
2 female NHW 48.5 90.5 27.0
3 male NHW 53.0 102.3 27.9
4 female H 47.0 83.1 29.1
5 male NHW 40.5 93.5 32.4
6 female NHW 53.0 77.5 30.3
7 male AA 29.0 109.2 33.7
8 male NHW 70.5 104 33.6
9 male H 40.5 105.2 34.0
10 female NHW 52.0 91.8 33.7
Total 50% female 60% NHW 47.5 ± 11.1 93.4 ± 11.7 31.3 ± 2.6
Abbreviations: BMI, body mass index; H, Hispanic; NWH, non-Hispanic white;
AA, African American. Totals for age, weight, and BMI represent mean ± SD.
TABLE 9. Comparison of AUC of biomarkers in response to a HFHC meal eaten alone or with
grapefruit (n=10)
Biomarker Test day Median AUC IQR P value
Glucose (mg/dL) HFHC 809.1 (680.7, 867.1)
0.575 HFHC+GF 777.1 (717.8, 881.5)
Insulin (μIU/mL) HFHC 247.7 (176.9, 445.2)
0.059 HFHC+GF 371.5 (189.4, 493.5)
Triglycerides (mg/dL) HFHC 179.9 (716.4, 2102.5)
0.800 HFHC+GF 1393.6 (1087.7, 1501.6)
IL-6 (pg/mL) HFHC 9.34 (1.52, 18.13)
0.721 HFHC+GF 10.70 (2.22, 19.33)
sVCAM-1 (ng/mL) HFHC 3851.1 (3668.0, 4209.5)
0.139 HFHC+GF 3909.3 (3743.9, 4097.9)
sICAM-1 (ng/mL) HFHC 1219.0 (1074.9, 1324.5)
0.959 HFHC+GF 1256.9 (1072.3, 1350.3)
F2-isoprostanes
(pg/mL)
HFHC 556.0 (401.1, 758.3) 0.114
HFHC+GF 403.7 (344.1, 403.7)
Abbreviations: AUC, area under the curve; HFHC, high-fat, high-calorie; GF, grapefruit;
IQR, interquartile range
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CHAPTER 5
SUMMARY AND CONCLUSIONS
The current research indicates a beneficial effect of daily ruby red grapefruit
intake on risk factors for CVD such as reducing central adiposity, blood pressure, various
parameters of the lipid profile, and, potentially, inflammation and oxidative stress. Six-
week consumption of grapefruit resulted in significant reductions in waist circumference,
total cholesterol, LDL-cholesterol, systolic blood pressure compared to baseline values.
Additionally, marginally significant reductions in hsCRP and F2-isoprostanes were
observed compared to the control condition, post-intervention. Grapefruit consumption
with an HFHC meal reduced IL-6 and F2-isoprostane concentrations in the postprandial
period, while insulin levels were significantly higher during the eight-hour postprandial
period after HFHC+GF consumption (Figure 4, pg. 97).
Obesity and Visceral Adiposity
Obesity is not only a disease in and of itself, but also significantly increases the
risk of cardiovascular events and, together, obesity and CVD impose a substantial burden
on individual and community health [117]. The literature suggests that modest weight
loss of 5-10% results in cardiovascular benefit [6, 117], in part by promoting vasodilation
and endothelial health [6]. Additionally, the favorable effects of weight loss on
endothelial health can be observed in as little as six weeks [118]. In the present study,
those randomized to daily grapefruit consumption for six weeks demonstrated a slight
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reduction in weight, though this effect was not statistically significant. Based on self-
reported energy intake, grapefruit did not promote appetite suppression and lead to a
reduction in energy consumption, as has been hypothesized [18]. Previous research
evaluating grapefruit as a weight loss food has yielded conflicting results. A four-arm
study comparing whole grapefruit, grapefruit juice, a grapefruit capsule, and a placebo
resulted in weight loss of 1.6 kg, 1.5 kg, 1.1 kg, and 0.3 kg, respectively [19]. A
significant difference in weight loss was detected between those randomized to the fresh
grapefruit group and those in the placebo group [19]. However, another study comparing
preloads of fresh grapefruit, grapefruit juice, and water in addition to 12.5% calorie
restriction over twelve weeks showed non-significant differences in weight loss between
groups [18], indicating that grapefruit had no further effects on promoting weight loss
than calorie restriction alone. Taken together, the results from the present trial and
previous research suggest that grapefruit is unlikely to stimulate weight loss robust
enough to promote metabolic or vascular health.
High VAT volume, as measured by waist circumference, is also a major risk
factor for cardiovascular disease [2, 117], and is more predictive of CAD than BMI [8].
Visceral fat secretes a slew of pro-atherogenic molecules that are known to activate
endothelial cells [2, 6], and reductions in waist circumference may result in more
beneficial effects on vascular health than overall weight loss alone [6, 7, 117]. In this
six-week grapefruit feeding trial, waist circumference and waist-to-hip ratio were
significantly reduced in those consuming grapefruit compared to baseline values, though
these results were not significantly different from those randomized to the control
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condition. Conversely, studies by Fujioka, et al. and Silver, et al. showed no effect of
grapefruit consumption on waist circumference in obese adults [18, 19].
Cell culture and animal model studies that have explored the effects of citrus
flavonoids on lipolysis may explain the findings observed in our study. Studies in Long
Evans Hooded rats and LDL-Receptor (LDL-R) -/- mice fed high fat diets supplemented
with naringenin found reductions in parametrial adipose tissue volume [20] and reduced
adipocyte size [33] compared to control conditions. The exact mechanisms that may
have caused these results were not explored. Some research suggests that citrus
flavonoids impact the cAMP cascade, which may further explain the results observed in
our trial and in the aforementioned rodent studies. cAMP activates protein kinase A
(PKA), which in turn activates lipases, whereas phosphodiesterases (PDE) breakdown
cAMP, thus preventing lipolysis. Human adipocytes (ex vivo) treated with SINETROL (a
flavonoid-rich supplement made of an extract of the juice, peels, and seeds of blood,
sweet, and bitter oranges and grapefruit) demonstrated increased lipolysis and free fatty
acid release due to SINETROL inhibition of cAMP-PDE [57]. These results suggest that
citrus flavonoids may promote lipolysis by promoting activity of the cAMP signaling
cascade.
Vascular Reactivity and Blood Pressure
Hypertension is one of the most important contributing factors for atherosclerotic
CVD risk, and a recent American Heart Association: Heart Disease and Stroke Statistics
2013 Update indicates that 33% of American adults (78 million) are hypertensive [119].
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Lifestyle interventions that promote a diet rich in fruits and vegetables, such as the
Dietary Approaches to Stop Hypertension (DASH) plan are effective at promoting
systolic and diastolic blood pressure reduction of 6 and 3 mmHg, respectively, in pre-
hypertensive adults [120]. These results are comparable to use of angiotensin converting
enzyme (ACE) inhibitors, one of the primary pharmacotherapies utilized for treatment of
pre-hypertension or hypertension [120]. In this trial, daily consumption of grapefruit
resulted in a significant reduction in SBP of 3 mmHg, compared to baseline values.
Though these results are not as pronounced as that seen when following the DASH diet,
they do suggest that a simple dietary change can significantly improve blood pressure.
Of note, though this population had an average BMI categorized in the obese range, their
baseline blood pressure averaged 119.1/80.6, indicative of borderline pre-hypertension.
While the reduction in SBP was significant, this effect may be more marked in a
hypertensive population, though this hypothesis will need to be prospectively tested.
To our knowledge, this is the first study showing a reduction in blood pressure as
a result of grapefruit intake. However, studies in grapefruit bioactives or similar citrus
fruits have indicated blood pressure benefit and explored potential mechanisms
explaining these effects. Daily supplementation of 500 mg hesperidin for three weeks in
patients with MetS resulted in a significant improvement in flow-mediated dilation
(FMD) of the brachial artery, a measure of endothelial reactivity [36]. Furthermore, a
study exploring the role of orange juice (OJ) compared to a control drink with added
hesperidin (CDH, both containing approximately 292 mg hesperidin) or a control drink
alone resulted in reduced diastolic blood pressure after four week daily consumption of
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OJ or the CDH as well as improved postprandial microvascular endothelial reactivity
compared to the control drink [38].
The results from cell culture and animal model trials may explain the effect of
citrus on endothelial function and promotion of healthy blood pressure. Acute hesperitin
treatment of bovine aortic endothelial cells (BAEC) resulted in eNOS phosphorylation,
thus promoting NO production in endothelial cells [36], the primary mechanism involved
in vasodilation. Hesperidin consumption in our population was extremely low (1.57
mg/day) compared to the previously mentioned studies on hesperidin and vascular
function [36, 38]. Due to their similar structure, it is plausible that naringenin induces
similar results on these various enzymes, though there has yet to be a study testing this
hypothesis. The mechanisms underlying the results observed here and in other studies
may be due to naringenin’s effect on phosphodiesterases. Phosphodiesterases are
involved in the degradation of cGMP, a molecule that inhibits calcium influx into the
vascular smooth muscle cell, and ultimately inhibits vasoconstriction. Similar to the
effects of SINETROL on cAMP-PDE, naringenin (0.1mM) treatment of rat aortic
myocytes resulted in inhibition of cGMP-PDE, thus promoting vasodilation [21].
Though the concentration of naringenin explored in the aforementioned study is
unattainable by the human diet, even in our population who consumed a great deal of
naringin (146.2 mg/day), this evidence may explain the mechanism by which grapefruit
consumption elicited its blood pressure lowering effects in our population. Additionally,
intake of Vitamin C, a potent superoxide scavenger, also significantly increased in those
consuming grapefruit, as expected. Superoxide, a reactive oxygen specie (ROS), couples
83
with NO to form peroxynitrite, leading to the uncoupling of the eNOS homodimer and
subsequently preventing NO formation [67]. As a scavenger of superoxide, Vitamin C
prevents peroxynitrite formation and the uncoupling of eNOS, and promotes
vasorelaxation and the maintenance of a healthy endoethelium [66, 67]. Therefore, the
proposed roles of Vitamin C, naringenin, and hesperidin in the endothelium may
collectively explain the effect of grapefruit consumption on blood pressure as observed in
this study.
Lipid Response
An important aspect of cardiometabolic health that contributes heavily to CVD
risk is dyslipidemia. Elevated levels of TC, LDL-C, triglycerides, and suppressed HDL-
C are all associated with risk of CAD [117]. LDL and triglyceride-rich lipoproteins both
facilitate endothelial dysfunction and atheroma formation by activating the endothelial
cells, disrupting the endothelial layer, and migrating into the subendothelial space [121].
Thus, reducing TC, LDL-C, and triglyceride values are important targets in CVD risk
reduction.
TC decreased in both the grapefruit and control groups, though a more marked
reduction was observed due to grapefruit intake (approximate reductions of 12 mg/dL and
7 mg/dL, respectively). These results are interesting given that the baseline values of TC
were already within a normal range in this sample. A striking decrease in LDL-C of
approximately 19 mg/dL was observed in those consuming grapefruit, which is of
particular significance given the short time frame of the study. The effects of 8-week
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naringin supplementation (400 mg/day) resulted in a 14% reduction in TC and a 17%
reduction in LDL-C in hypercholesterolemic patients, while those with healthy
cholesterol values observed no benefit [68]. A differential effect of the type of grapefruit
consumed was found in patients with coronary atherosclerosis. Those consuming either
one ruby red or one white grapefruit (which differ in lycopene and flavonoid content)
daily for thirty days demonstrated reductions in both TC and LDL-C. Only those eating
ruby red grapefruit observed reductions in triglycerides [34], suggesting an increased
benefit of consuming the ruby red cultivar, though no change was observed in
triglycerides in this trial. In spite of the positive results in many studies, four-week
supplementation of 800 mg/day or 500 mg/day of hesperidin or naringin, respectively,
revealed no benefit in any lipid parameter in mildly hypercholesterolemic adults [35].
This may suggest that the bioactives in grapefruit need to be consumed simultaneously.
Additionally, fiber intake did not change in our population, indicating that the role of
grapefruit in lipid control was likely a result of the bioactives and potentially other
micronutrients, and not the fiber content of the fruit.
Insulin Response
Insulin is well characterized for its essential role in glucose metabolism. In the
last twenty years, research has shed light on the effect of insulin’s signal transduction
mechanisms that impact cardiometabolic health outcomes [100]. Insulin signaling is of
particular importance in hepatic tissue, and insulin sensitivity promotes healthy lipid
metabolism by inhibiting microsomal triglyceride transfer protein and subsequent
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apolipoprotein-(apo)B100 lipoprotein assembly and secretion [122]. Insulin is also
intrinsically involved in maintenance of vascular health through signaling of the PI3K-
Akt-eNOS cascade. Activation of this pathway leads to vasodilation and also promotes
cardiovascular cell survival, reduces inflammatory processes, and inhibits oxidative stress
[100]. Thus, insulin sensitivity is an important goal for cardiometabolic disease risk
reduction.
Pre-clinical and in vitro studies suggest that citrus flavonones improve insulin
sensitivity. Naringenin increases hepatic expression of PPAR-γ and -α [20, 31, 123],
receptors involved in glucose homeostasis and lipid metabolism, and activation of which
improves insulin sensitivity [123]. In a study of LDL-R -/- mice fed a high fat, high
cholesterol diet, naringenin supplementation reduced fasting insulin values, as well as
reduced plasma glucose levels in a 60-minute glucose tolerance test, suggesting enhanced
insulin sensitivity [33]. Male Wistar rats fed a high fat diet developed hyperinsulinemia,
insulin resistance, and hyperglycemia, though naringin supplementation significantly
reduced all of these deleterious metabolic outcomes [123]. However, in the only clinical
trial to evaluate the effects of grapefruit on parameters associated with metabolic
(dys)function, 12-weeek grapefruit consumption in pill, juice, or whole fruit form had no
significant impact on fasting insulin concentrations [19].
Insulin was not evaluated before and after the six-week grapefruit feeding trial,
though the effects of acute grapefruit consumption on the postprandial insulin response
were assessed. Fasting insulin concentrations were not different between test days,
though addition of grapefruit to a HFHC meal resulted in elevated serum insulin
86
concentrations 30 minutes and 2 hours post feeding. Of note, these effects were no
longer present after the second HFHC meal was consumed, indicating an immediate
effect of grapefruit on insulin secretion. These results are supported by a study by
Ghanim and colleagues, in which a HFHC meal was consumed with OJ, a glucose
beverage, or water. HFHC+OJ resulted in elevated postprandial insulin values compared
to the other two treatments, though glucose values were suppressed [49]. The results of
both of these trials suggest that citrus fruits or the bioactives therein induce pancreatic
beta cell secretion of insulin and concomitant tissue uptake of glucose. This hypothesis is
supported by a study in which pancreatic histology of male Wistar rats fed a high fat diet
supplemented with naringin for 28 days revealed reduced injury of islet cells and
increased numbers of insulin secretory granules [123]. Importantly, this effect was
observed after chronic naringin supplementation and at levels unattainable by the human
diet, limiting the ability to compare the results from this animal study and the human
postprandial condition. Nevertheless, these results, taken in consideration with the results
from the present trial and the Ghanim, et al. trial suggest that citrus flavonones may
preserve beta cell function in the context of a high fat diet.
There are inconsistencies in the literature regarding the effect of dietary
flavonoids on insulin secretion, as postprandial evaluations have demonstrated reduced
insulin concentrations in response to flavonoid-rich berries consumed with a high fat
meal [105] or alone [124]. Conversely, black tea consumed with a 75 g glucose load and
cranberry juice both elicit a hyperinsulinemic response within 60 or 90 minutes of
consumption, respectively, compared to control conditions (caffeinated beverage or a
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high fructose beverage, respectively) [125, 126]. Of note, the postprandial evaluations of
insulin response to dietary flavonoids to date have all been performed in healthy adults
with no history of cardiovascular diseases or diabetes. In order to elucidate the effects of
dietary flavonoids on postprandial insulin concentrations, similar evaluations should be
completed in a population with known insulin resistance.
Inflammatory and Oxidative Stress Modification
Oxidative stress and inflammation are two of the key underlying causes of CVD,
and obese individuals, particularly those with central obesity, present with high
circulating values of inflammatory and oxidative stress markers [6, 127]. Obesity is
characterized by chronic, low-grade inflammation/oxidative stress and metabolic,
oxidative, and inflammatory pathways are heavily interconnected and function in a
reciprocal, positive feedback fashion, often leading to dysregulation of one another [127].
These pathways converge at the endothelium and induce endothelial dysfunction,
characterized by increased activity of proatherogenic factors [127], including
inflammatory cytokines, adhesion molecules, and ROS, amongst others [2, 6].
Inflammatory Cytokines
IL-6 and CRP are inflammatory cytokines involved in the promotion and
progression of atherosclerotic plaques [103]. IL-6 is secreted by adipocytes, immune
cells, and endothelial cells and induces hepatic CRP synthesis [2, 106]. Previous reports
indicate that CRP and IL-6 are detectable in atherosclerotic lesions, and both are involved
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in endothelial cell-induced expression of adhesion molecules, and other pro-inflammatory
cytokines [80, 128]. Further, CRP induces secretion of monocyte chemoattractant
protein-1 (MCP-1) by endothelial cells [129], whereas IL-6 stimulates macrophages to
secrete MCP-1 [130], thus facilitating the homing of monocytes to the endothelial cells
(Figures 1 & 4).
In this study, six-week daily consumption of ruby red grapefruit resulted in
marginal reductions in hsCRP compared to the control condition, an effect that was more
pronounced (though not statistically significant) in individuals with MetS. These
nonsignificant results are likely due to the small sample size in this study, and may be
significant in a study adequately powered to demonstrate changes in CRP. In the acute
setting, HFHC meal consumption with grapefruit resulted in 2-hour post meal reductions
in IL-6 compared to HFHC alone. However, this effect was short-lived, suggesting that
anti-inflammatory foods may need to be consumed at regular time intervals in order to
prevent increases in IL-6 concentrations. No human clinical trial has evaluated the
potential role of grapefruit in attenuation of inflammatory cytokines. There is extensive
evidence that supports naringenin’s ability to prevent inflammatory processes. Ex vivo
work indicates that naringenin treatment of cultured human macrophages reduces
secretion of IL-6 [131]. Additionally, IL-6 production and secretion was reduced by
dietary naringenin supplementation in diabetic mice [132]. Basic science evaluations
have repeatedly demonstrated naringenin’s ability to prevent nuclear factor kappa B
(NFκB) expression and activity in both rodent [123, 132] and cell culture models [133,
134]. NFκB is a transcription factor that promotes the transcription of multiple
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inflammatory molecules (including IL-6 and CRP), oxidative stress enzymes, and
adhesion molecules (including ICAM-1 and VCAM-1). Therefore, the potent anti-NFκB
effects of naringenin may explain the responses of CRP and IL-6 to grapefruit in this
study.
Adhesion Molecules
Adhesion molecules are intrinsic in the pathogenesis of atherosclerotic plaque
development. Endothelial cells express adhesion molecules in response to inflammation,
oxidative stress, or endothelial injury and mediate the binding of circulating monocytes to
the endothelium [6, 81]. ICAM and VCAM are the most well characterized of the
adhesion molecules, and soluble values correlate with risk of coronary death [81].
Studies in rabbits indicate that naringin or naringenin supplementation of a high
cholesterol diet results in lower circulating values of both sICAM-1 [135] and sVCAM-1
[136]. Additionally, hesperitin treatment of BAEC resulted in reduced sVCAM-1
expression in response to TNF-alpha stimulation [36], all of which suggests that citrus
flavonones have a role in promoting endothelial health by suppressing adhesion molecule
expression.
In this study, sVCAM-1 levels were not modified by six weeks of daily ruby red
grapefruit consumption. In a study of overweight men, sVCAM-1 levels were
nonsignificantly lower following 4 weeks of orange juice or a hesperidin enriched
beverage compared to placebo [38]. Of note, sVCAM-1 levels in our sample were
similar to that of healthy individuals [39]. Previous evaluations in participants with MetS
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[83], pre-hypertension [38] or CAD [81] have shown that sVCAM-1 levels may be as
much as 2-3 fold higher in at-risk populations, which could explain why sVCAM-1 levels
were not modified in this trial. Furthermore, 3 weeks of hesperidin supplementation (500
mg/day) in MetS individuals resulted in no change is sVCAM-1, though E-selectin values
were reduced compared to placebo [36], suggesting that E-selectin may be more
responsive to citrus flavonoids than sVCAM-1.
In the acute setting, sICAM-1 levels were not affected by grapefruit, whereas
sVCAM-1 levels were significantly higher five hours post HFHC+GF feeding compared
to HFHC alone. Postprandial evaluations of citrus intake have not assessed these
adhesion molecules, though previous work indicates that both sICAM-1 and sVCAM-1
are responsive to various types of dietary fat in the postprandial period [110-112]. The
response of sVCAM-1 to HFHC+GF meal consumption was unexpected, but may have
happened by chance simply due to the small sample size. Also, it is important to
recognize that, like the individuals studied in the larger feeding trial, this sample
presented with relatively low fasting adhesion molecule concentrations. Therefore, the
slight increase in sVCAM-1 values 5 hours post HFHC+GF meal may not be
pathologically significant. However, the results from both the six-week and postprandial
feeding trials indicate that ruby red grapefruit intake is unlikely to significantly modify
circulating sVCAM-1 and sICAM-1 values.
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Lipid Peroxidation
Free radicals and ROS are involved in the development and progression of
atherosclerosis due to activation of inflammatory processes, cellular remodeling, and
lipid peroxidation [86, 116]. F2-isoprostanes are the result of non-enzymatic free-
radical-mediated lipid peroxidation of polyunsaturated fatty acids [116, 137], and are
validated markers of lipid peroxidation [86]. F2-isoprostanes can be released from cell
membranes via phospholipases and circulate freely in the blood, though isoprostanes are
also found associated with lipoproteins [86, 137]. Regardless of whether they are
transported in the blood freely or bound to lipoproteins, isoprostanes can interact with the
endothelium and promote endothelial dysfunction. Flavonoids are known for their free-
radical scavenging behavior [116], and flavonoid-rich foods have been shown to reduce
lipid peroxidation [116].
In this trial, six weeks of grapefruit consumption resulted in nonsignificant
reductions in F2-isoprostanes, and this reduction was more pronounced in participants
with MetS. Previous work indicates that orange juice consumption in a healthy
population [85] or those with peripheral artery disease [40] results in reductions in F2-
isoprostanes, though this is the first study to measure F2-isoprostanes in response to
grapefruit, specifically.
In the postprandial evaluation, F2-isoprostane values were significantly lower five
hours post breakfast meal (1 hour post lunch meal) consumption. In a study by Gopaul
and colleagues, F2-isoprostanes increased 2 hours post meal consumption in nine healthy
adults who ate a single fast-food meal, similar to what was consumed in this study, [137].
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However, samples were not collected longer than 2 hours postprandially, limiting the
ability to compare the studies further. Nevertheless, the Gopaul study and this trial
indicate that F2-isoprostanes are sensitive to dietary changes in the postprandial period.
This is the first postprandial evaluation to measure F2-isoprostanes in response to citrus
consumption, though previous work indicates that orange juice consumption improves
serum antioxidant capacity [52]. The results from the studies conducted here along with
previous work on orange juice consumption suggest that regular citrus intake reduces
lipid peroxidation in an acute setting and potentially in response to chronic intake. The
results from this trial also suggest that oxidative outcomes in individuals with MetS may
be more responsive to citrus consumption, though this hypothesis will need to be tested in
an adequately powered trial.
Inflammatory and oxidative processes are strongly connected and highly
reciprocal, and their role in atheroma development is irrefutable [2, 6, 127]. The
strongest mechanistic link that influences all of these processes is NFκB activity [138].
Inhibition of NFκB reduces inflammatory and oxidative cascades, which translates into
improved cardiometabolic health [138]. Given the basic science evidence that supports a
role of naringenin in NFκB inhibition, we can postulate that the results observed in the
trials described here may be due to NFκB downregulation by grapefruit. However,
peripheral blood was not collected in these trials, thus preventing our ability to test NFκB
expression or activity, as NFκB is not secreted into circulation. Additionally, the effect
of grapefruit consumption on oxidative stress, inflammation, and adhesion molecule
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concentrations as described here was modest, suggesting that if NFκB modulation was in
fact the mechanism underlying these changes, regular grapefruit intake is unlikely to
significantly inhibit this transcription factor’s expression/activity.
Limitations, Future Directions, and Conclusions
The research described here is not without limitations, many of which could be
addressed in future work. In some instances, the sample size may not have been adequate
to observe statistically significant changes in the outcomes evaluated, though the
magnitude of these changes were quite striking in many instancesn ju . The primary aim
of this work, and the outcome for which this study was powered, was evaluation of the
effects of grapefruit on weight change. The application of these findings is also limited
to individuals who are not using pharmacotherapies that are metabolized by the CYP3A4
enzyme, as grapefruit is known to inhibit its activity, thus increasing the bioavailability of
drugs that are metabolized by CYP3A4. Many cardiovascular medications, including
statins and calcium channel blockers, are substrates of CYP3A4 [78]. Taking these
interactions into consideration along with the findings from the present study, grapefruit
could be recommended in the primary prevention setting in those who have not
developed overt CVD.
The overweight and obese population for this study was selected as the link
between elevated BMI and risk of CVD is well established [5, 117]. Overweight/obese
individuals are typically at higher risk for CVD due to the presence of factors that
influence endothelial function including dyslipidemia, hypertension, chronic low-grade
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inflammation and oxidative stress [2, 6, 117, 127]. The population enrolled in this trial
may have been too healthy to significantly modify many outcomes of CVD risk, as
baseline values of almost all clinical CVD risk factors were within normal ranges.
Results would likely be more robust and significant in a population at higher risk for
CVD, and future trials should enroll individuals with MetS and/or who are insulin
resistant, as these individuals are more likely to present with an elevated atherogenic risk
profile [79, 88] that would be responsive to a dietary citrus intervention.
In this trial, we showed significant improvements in total cholesterol and LDL-
cholesterol. However, the current literature indicates that particle size of lipoproteins
may be more predictive of future CVD events than only evaluating the type of lipoprotein
(LDL versus HDL) [7]. Individuals may present with normal LDL and HDL cholesterol,
but be at higher risk for cardiovascular events [139] due to increased concentrations of
small, dense LDL particles and suppressed concentrations of large, HDL particles that
result due to remodeling of the lipoproteins by cholesteryl ester transfer protein and
hepatic triglyceride lipase [7]. Due to the effects of citrus flavonoids on hepatic lipid
metabolism, an evaluation of the effect of dietary citrus on lipoprotein particle size is
warranted in order to provide a more comprehensive perspective of the role of citrus on
CVD risk.
Fasting insulin values were also not assessed in the six-week feeding trial. In
light of animal model studies that suggest a beneficial role of dietary naringenin
supplementation on beta cell function, and evaluations of flavonoid-rich foods that have
resulted in increased postprandial insulin secretion, further research is needed. A study
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evaluating both the chronic effects of citrus consumption on fasting insulin as well as the
acute effects of citrus on postprandial insulin in a population at risk for cardiometabolic
diseases should be implemented in order to elucidate the relationship between citrus
consumption and insulin secretion/sensitivity. Additionally, the effect of grapefruit on
markers of oxidative stress/inflammation was relatively modest. These results may be
due to biomarker selection, as endothelial dysfunction and atheroma development
develops in response to multiple stimuli, and a variety of different biomarkers could have
been used. However, the biomarkers evaluated in this study were chosen because of the
preliminary data regarding the role of atheroma pathogenesis and responsiveness to
dietary flavonoids in preclinical or clinical trials. Lastly, a functional measure of
endothelial reactivity and vascular tone such as flow mediated dilation was not evaluated
in this trial. FMD is a mechanical measure of a vessel’s ability to react to changes in
blood flow, and has been validated as a prognostic indicator of vascular disease [140]. A
comprehensive assessment of the effects of citrus consumption on endothelial health
should include an analysis of vascular tone in conjunction with measures of metabolic
health, oxidative stress, and inflammation.
There is a significant body of evidence that suggests that citrus fruits are an
important addition to a heart healthy diet. Animal models, cell culture, and
epidemiological data continually demonstrate that grapefruit and its primary flavonoids,
naringin and hesperidin, are cardioprotective. Previous clinical trials evaluating
grapefruit consumption have all evaluated limited numbers of outcomes related to
cardiometabolic health, reducing the ability to compare study results and draw
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conclusions. The research described here expands on previous work by testing the effects
of regular grapefruit consumption in a semi-chronic setting as well as in the postprandial
period on a wide range of risk factors that are strongly associated with cardiometabolic
diseases, and specifically, endothelial (dys)function and atheroma development. Based
on the results of this six-week feeding trial and the postprandial evaluation, grapefruit
could be recommended as part of a heart healthy diet, though this dietary change alone is
unlikely to result in significant CVD risk reduction.
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APPENDIX A
SUBJECT'S CONSENT FORM
Project Title: Efficiency of daily grapefruit exposure in reducing body weight and
inflammatory markers
You are being asked to read this form so that you know about this research study.
Federal regulations require that you know about the study and the risks involved. If
you decide that you want to participate in this study (consent), signing this form will
say that you know about this study. If you decide you do not want to participate,
that is okay. There will be no penalty to you and you will not lose any benefit which
you would normally have.
WHY IS THIS STUDY BEING DONE? You have the choice to participate in this research project. The purpose of this project is
to determine if grapefruit will produce a greater reduction in oxidative stress (common
damage to cells), inflammation (low level swelling of cells in your body) and weight loss
in overweight adults.
WHY ARE YOU BEING ASKED TO BE IN THIS STUDY? The Principal Investigator or a member of her study staff will discuss the requirements
for participation in this study with you. To be eligible to participate, you should be over
18 years old and if you are female you should be premenopausal. You must be in general
good health with no diagnosis of diabetes, liver, renal disease or cardiovascular disease
and not taking any over the counter or physician prescribed drugs to treat inflammation
(swelling). You must not be taking medications that interact with grapefruit such as
Felodipine, Diltiazem, Nisoldipine, Amlodipine, Nitrendipine and Verapamil. You will
be asked to consume the study provided multivitamins.
You must be willing to discontinue all citrus fruits and be randomized to either a daily
grapefruit or a control diet for a period of 9 weeks. If randomized to the daily grapefruit
diet, you must be willing to consume the assigned amount of Ruby Red grapefruit; 1/2 a
grapefruit, 3x daily before meals for a period of 6 weeks. Sweeteners will be provided by
the study (3 pack/day) which you can use with your grapefruit. Adding sweeteners to
your grapefruit is optional. You must be willing to adhere to a low bioactive fruit and
vegetable diet (such as iceberg lettuce, white potatoes, cucumbers, corn, bananas etc.)
and stop all dietary self-prescribed supplements except for those provided to you by the
study investigator for the entire duration of the study. Additionally, you must discontinue
the consumption of all other citrus fruits for the duration of the study. No other changes
to your diet will be required. You will be asked to fill out a hunger/satiety scale on days
1, 21, and 39 of the study. If you are randomized to the grapefruit group you will be
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asked to fill out the hunger/satiety scale 15min before and 15 min after consuming the
grapefruit and eat your meal 15 min after the grapefruit consumption. If you are
randomized to the control group you will be asked to fill out the hunger satiety scale
15min before each meal during the above specified days.
You will not be eligible to participate if it is determined by study investigators that you
have a body mass index (BMI) of greater than 40 or less than 25 kg/m2. These values
will be calculated by the study coordinator using your height and weight. Additionally,
you will not be eligible if you have a body fat percentage of less than 25%, as measured
by electrical impedance. You will not be eligible to participate if you have a history of
smoking in the past 10 years. You are also not eligible if you participate in planned
exercise for more than 10 hours per week.
You must be available for clinic visits, telephone contact and be able to complete study
questionnaires.
A total of approximately 110 individuals will be enrolled in this study locally.
WHAT ARE THE ALTERNATIVES TO BEING IN THIS STUDY? This is not a medical treatment study. The alternative is not to participate; you may want
to talk to your personal doctor to discuss your participation.
WHAT WILL YOU BE ASKED TO DO IN THIS STUDY? Your participation in this study will last up to 10 weeks and includes 4 visits. Each visit is
described below.
Visit 1 (Consent Visit, Week 1)
This visit will last about 60 to 75 minutes. During this visit you will be asked to
complete questionnaires to describe information such as your age, gender,
education, and medical history. The questionnaires should take approximately 30
to 60 minutes to complete. You will also have you height, weight, blood pressure
and body measurements taken at this clinic visit.
You will be advised to complete a ‘run-in’ diet during this time. The purpose of a
run-in is to determine if you can routinely consume a given fruit every day, three
times a day, for several weeks. You may pick any fruit from the designated study
fruit/vegetable list, such as a banana, and are required to eat 1/2 serving of that
fruit three times daily for the 3 week period and to record your intake in the study
provided food log.
You will also be asked to limit your fruit and vegetable intake for the 3 week run-
in/wash out period, selecting only those fruits and vegetables on the study
fruit/vegetable list. The “run-in/wash out” phase is a period of time in the study
to clean out the body of bioactive compounds (nutrients) so a baseline value can
be set to measure against.
You will also be asked to complete three diet recalls during the run-in/wash out
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period. A certified, trained study personnel from the University Of Arizona
Department Of Nutritional Sciences will contact you by telephone on 3 random
days during this 3 week “run-in/wash out” period to collect a 24 hour recall of
food intake. You will be excluded from study participation if you fail to meet
requirements of the “run-in/wash out” period.
You will be asked to eat half of a grapefruit to evaluate palatability (taste) and
tolerance.
Visit 2 (Week 4)
This visit will last about 30 to 45 minutes. At the end of the three week “run
in/wash out” period you will be asked to come back to the study clinic where
inflammatory (swelling) markers will be assessed by the collection of
approximately 2 tablespoons of blood. In addition you will be asked to collect
your first morning urine during the final 2 days of the “run-in/wash out” period
and the morning of your clinic visit. Urine will need to be stored in the containers
provided by the study investigator and kept on ice in the study provided cooler
throughout the collection (3 days). You will bring the urine samples (3) to the
study clinic on the final morning (day 3) of urine collection. This urine sample
will be used to measure oxidative stress (cell damage) in the body. Your blood
pressure will be measured at this visit. You will then be randomized to one of the
following groups: the grapefruit intervention group (½ grapefruit eaten three
times daily before meals and discontinue all other citrus fruits) or the control
group which requires you to discontinue all citrus fruit intake for 6 weeks.
If you are randomized to the grapefruit group, you will be asked to eat ½ of a
grapefruit 3x daily before meal, continue the low bioactive fruit and vegetable
consumption, and discontinue all other citrus fruit intake for 6 weeks. At the end
of this visit a one week supply of grapefruits will be provided. A schedule will be
provided to you for weekly grapefruit pick up scheduled at your convenience.
During this clinic visit, you will be given written instructions on how to prepare
grapefruits for consumption. During this period a diary will be provided to you to
record your grapefruit intake and record your satiety. If you are randomized to
the control group, you will be asked to continue with the low bioactive fruit and
vegetable consumption and discontinue the consumption of all citrus fruits for 6
weeks.
During the intervention phase (6 weeks) of the study you will be asked to fill out a
satiety scale on days 1, 21, and 39.
During the 6 week intervention phase of the study a certified, trained study
personnel from the University Of Arizona Department Of Nutritional Sciences will
contact you by telephone on 3 random days to collect a 24 hour recall of food
intake.
Visit 3 (Week 6)
This visit will last about 20 minutes. At this visit weight, blood pressure, and body
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measurements will be collected.
Visit 4 (End of Week 9)
This visit will last about 30 to 45 minutes. At the end of the six week grapefruit
intervention you will be asked to return to the study clinic where inflammatory
(swelling) markers will be assessed by the collection of approximately 2 tablespoons
of blood. In addition you will be asked to collect your first morning urine during the
final 2 days of the “run in/wash out” period and the next morning of your clinic visit.
Urine will need to be stored in the containers provided by the study investigator and
kept on ice in the study provided cooler throughout the collection (3 days). You will
bring the urine samples (3) to the study clinic on the final morning (day 3) of urine
collection. This urine sample will be used to measure oxidative stress (cell damage) in
the body. You will also have your weight, body measurements and blood pressure
taken at this clinic visit.
Upon completion of the study, participants will be offered a one-time weight loss
counseling session with a registered dietitian (valued at $100).
PHARMACOKINETIC TRIAL
In addition to the grapefruit feeding trial, we will also be performing a two day ancillary
investigation to evaluate the effects of grapefruit on attenuating the oxidative stress and
inflammation that is known to follow the consumption of a high fat, high carbohydrate
meal. A sub sample of twenty participants from the feeding trial will take part in these
additional study activities. This multi-meal feeding component will be scheduled 2-8
wks post completion with at least 7 days between feeding days.
You will be asked to report to the CATS research facility at the Arizona Cancer Center
(3838 N. Campbell Avenue) on two separate occasions. You will arrive at 7 a.m. and
will be required to be in the fasting state for the previous 12 hours. Upon arrival, a nurse
will fit a port onto the ante-cubital region of your arm. This will remain in place for the
entire day (about 10 hours). A fasting blood draw will be collected directly following port
placement. Participants will have eat a high fat, high carbohydrate breakfast style meal
consisting of biscuits, gravy, sausage, and scrambled eggs (approximately 800 kcals).
You will be asked to consume all food provided within a 20 minute time period. Ten
participants will be randomly selected to eat one ruby red grapefruit along with this meal.
Four hours after consuming the breakfast, a second high fat, high carbohydrate meal will
be provided to all participants. This meal will consist of a cheeseburger and french fries
(approximately 800 kcals). You will be permitted to drink water throughout the day.
Blood will be drawn from the port and urine will be collected on multiple occasions
following the consumption of the meals (see timeline below for schedule of day’s
events).
7 am: Report to clinic, have port fixed to arm, blood collection #1, urine collection #1
7:30 am: Eat breakfast
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8:00 am: Blood collection #2
9:00 am: Blood collection #3
10:00 am: Blood collection #4, Urine Collection #2
11:00 am: Blood collection #5
12:00 pm: Eat lunch
12:30 pm: Blood collection #6, Urine Collection #3
2:30 pm: Blood collection #7
4:30 pm: Blood collection #8, Urine Collection #4
You will remain at the CATS facility for a total of ten hours on each of the feeding days.
The CATS facility will have space and equipment available for you to work on
computers, read, and watch movies. Upon completion of the first feeding day, you will
be asked to return the following week for another day that replicates the first feeding day.
Those who were not selected to eat grapefruit on the first day will eat grapefruit with
their breakfast meal on the second day. Those who ate grapefruit the first day will not eat
grapefruit with their breakfast meal on the second feeding day.
There are risks to participating in the pharmacokinetic trial. The main risk involves the
port, which will be fixed to the arm for use in blood collections. Port placement could
lead to pain, swelling, bruising, or infection at the blood draw site, similar to a standard
blood draw. A trained, experienced Registered Nurse will place this port in order to
minimize these risks.
Those who choose to take part in this pharmacokinetic trial will be compensated. You
will receive a $75 Target gift card upon completion of each feeding day, for a total
compensation of $150.
Consent to participate in the pharmacokinetic feeding is not a necessary component for
participation in the grapefruit feeding trial. Do you agree to participate in the
pharmacokinetic feeding? Please indicate your response below and sign:
_____ YES ______ NO Participant Signature: ________________________
ARE THERE ANY RISKS TO ME?
The collection of blood may cause pain, swelling, bruising, or infection at the site of the
needle puncture. Subjects may experience stomach upset related to daily intake of
grapefruit.
ARE THERE ANY BENEFITS TO ME? Your participation may help establish a better understanding of bioactive food
compounds in the body in relation to weight loss and inflammation (swelling) in
overweight adults. You will also receive information about your body measurements.
WILL I BE PAID TO BE IN THIS STUDY?
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You will receive $25 gift card at the completion of the wash out diet, at the 3 week clinic
visit, and at the end the grapefruit intervention for a total compensation of $75.
WILL I HAVE TO PAY ANYTHING TO BE IN THIS STUDY? Costs for your participation in this study include your cost of transportation to and from
the study clinic and your personal time to complete the study questionnaires, clinic
measurements and blood draws. You will be provided all grapefruits for the duration of
the study.
WILL I WILL HAVE TO PAY ANYTHING IF I GET HURT IN THIS STUDY? Medical treatment is available if you have an injury. You can get more information about
these treatments by calling Cynthia Thomson at (520) 626-1565.
You may need to pay for immediate and necessary care for side effects if you are injured because of being in this research project. The University of Arizona will not provide for the costs of further treatment beyond immediate necessary care or provide monetary compensation for such injury.
Bad things can happen in any research study even with the use of high standards of care.
These events may not be your fault or the fault of the researcher involved. Known side
effects have been described in this consent form. However, unforeseeable harm may
occur and require care. You do not give up any of your legal rights by signing this form.
If you believe you are injured because of the research or are billed for medical care for
injuries that you feel has been caused by the research, you should contact the Principal
Investigator Cynthia Thomson, PhD, RD at (520) 626-1565.
WILL INFORMATION FROM THIS STUDY BE KEPT CONFIDENTIAL? Information about you will be stored in locked file cabinet; computer files protected with
a password. This consent form will be filed in an official area.
Information about you will be kept confidential to the extent permitted or required by
law. People who have access to your information include the Principal Investigator and
research study personnel. Representatives of regulatory agencies such as OHRP or the
FDA and entities such as the University of Arizona Human Subjects Protection Program
may access your records to make sure the study is being run correctly and that
information is collected properly. The agency that funds this study (Vegetable and Fruit
Improvement Center – Texas A&M University) and the institution(s) where study
procedures are being performed (Nutritional Research clinic at 1601 N. Tucson Blvd
suite 23) may also see your information. However, any information that is sent to them
will be coded with a number so that they cannot tell who you are. Representatives from
these entities can see information that has your name on it if they come to the study site
to view records. If there are any reports about this study, your name will not be in them.
104
Both urine and blood samples will be stored for up to 10 years for use in ancillary
research studies, but samples will only be identified by the study participant
identification number, not by name and/or birth date or identifying information.
The type of research to be performed using stored urine and blood will focus on
additional measures of oxidative stress and/or inflammation. In the event that new
and/or better methods for measuring oxidative stress and/or inflammation and/or
additional research funds become available the research team would like to be
able to re-test the stored samples.
Agreement to have your samples stored for future analysis is not necessary to participate
in this study. Do you agree to have your urine and blood samples stored for these
ancillary studies should additional funding for these measures be secured? Please initial
your response below:
_______YES ______NO Participant
Initials:_________________
WHO CAN BE CONTACTED ABOUT THIS STUDY? You can call the Principal Investigator to tell her about a concern or complaint about this
research study. The Principal Investigator Cynthia Thomson, PhD, RD can be called at
(520) 626-1565. If you have questions about your rights as a research subject you may
call the University of Arizona Human Subjects Protection Program office at (520) 626-
6721. If you have questions, complaints, or concerns about the research and cannot reach
the Principal Investigator; or want to talk to someone other than the Investigator, you can
contact the Human Subjects Protection Program via the web (this can be anonymous),
please visit http://orcr.vpr.arizona.edu/irb.
STATEMENT OF CONSENT
The procedures, risks, and benefits of this study have been told to me and I agree to
be in this study and sign this form. My questions have been answered. I may ask
more questions whenever I want. I can stop participating in this study at any time
and there will be no bad feelings. My medical care will not change if I quit. The
researcher can remove me from the study at any time and tell me why I have to
stop. New information about this research study will be given to me as it is available.
I do not give up any legal rights by signing this form. A copy of this signed consent
form will be given to me.
___________________________________
____________________________________
Subject's Signature Date
INVESTIGATOR'S AFFIDAVIT:
Either I have or my agent has carefully explained to the subject the nature of the above
project. I hereby certify that to the best of my knowledge the person who signed this
105
consent form was informed of the nature, demands, benefits, and risks involved in his/her
participation.
___________________________________
________________________
____________
Signature of Presenter Date
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APPENDIX B
SUPPLEMENTAL MATERIALS
Grapefruit Weights
Average grapefruit weights, separated by shipment.
Shipment Date Weight±SD (g)
12/14/09 410.0±18.0
1/25/10 399.0±34.7
2/22/10 387.4±37.3
3/8/10 438.6±37.4
3/22/10 380.4±22.0
11/5/10 344.4±13.8
3/22/2010* 298.4±13.8
All grapefruit weighed with peel. *Indicates fruit without peel.
Weights are reported as the average of ten randomly selected
grapefruits.
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APPENDIX B continued
Compliance Logs
PPT
#times GF
eaten
Rate of
Compliance PPT
#times GF
eaten
Rate of
Compliance
1 N/A N/A 20 126 1.0
2 126 1.0 21 126 1.0
3 N/A N/A 22 73 0.58
4 83 0.66 23 121 0.96
5 126 1.0 24 126 1.0
6 126 1.0 25 116 0.92
7 126 1.0 26 116 0.92
8 N/A N/A 27 103 0.82
9 122 0.97 28 N/A N/A
10 125 0.99 29 126 1.0
11 120 0.95 30 99 0.79
12 125 0.99 31 124 0.98
13 120 0.95 32 122 0.97
14 124 0.98 33 116 0.92
15 126 1.0 34 126 1.0
16 N/A N/A 35 85 0.67
17 126 1.0 36 104 0.82
18 122 0.97 37 126 1.0
19 121 0.96
PPT=participant.
Thirty-seven of the thirty-nine participants who completed the grapefruit
treatment returned their compliance logs. Five were not filled out properly, denoted by
“N/A” in the table.
Participants had the opportunity to eat grapefruit a total of 126 times. Thus,
compliance was calculated as (# times GF eaten/126)*100. The average rate of
compliance was calculated as 93±11%.
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APPENDIX C
ADDITIONAL PUBLICATION #1:
A REVIEW OF EVIDENCE BASED STRATEGIES TO TREAT OBESITY IN
ADULTS
Authors: Deepika Laddu, Caitlin Dow, Melanie Hingle, Cynthia Thomson, Scott Going
as published in Nutrition in Clinical Practice. 2011; 26: 512-525.
Abstract
Obesity, with its comorbidities, is a major public health problem. Population-based
surveys estimate 2 of every 3 U.S. adults are overweight or obese. Despite billions of
dollars spent annually on weight loss attempts, recidivism is high and long-term results are
disappointing. In simplest terms, weight loss and maintenance depends on energy balance,
and a combination of increased energy expenditure by exercise and decreased energy
intake through caloric restriction is the mainstay of behavioral interventions. Many
individuals successfully lose 5-10% of body weight through behavioral approaches, and
thereby significantly improve health. Similar success occurs with some weight loss
prescriptions although evidence for successful weight loss with over the counter
medications and supplements is weak. Commercial weight loss programs have helped
many individuals achieve their goals although few programs have been carefully evaluated
and compared, limiting recommendations of one program over another. For the very
obese, bariatric surgery is an option which leads to significant weight loss and improved
health although risks must be carefully weighed. Lifestyle changes, including regular
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physical activity, healthy food choices and portion control, must be adopted, regardless of
the weight loss approach, which requires ongoing support. Patients can best decide the
appropriate approach working with a multi-disciplinary team including their health care
provider and experts in nutrition, exercise and behavioral intervention.
Introduction
Obesity is the result of a chronic surplus in energy intake relative to expenditure.
While the specific causes remain unclear, obesity is thought to arise from a dynamic
interaction between an organism’s biology, behavior, and the increasingly obesogenic
environment. In the United States, the prevalence of obesity is estimated to be 34% in
adults1 and an alarming 17% in children and adolescents.
2
Obesity is associated with a wide variety of comorbidities, including diabetes,
hyperlipidemia, fatty liver disease, obstructive sleep apnea, GERD, vertebral disk disease,
osteoarthritis, and increased risk of post-menopausal breast, endometrial, colon, kidney,
and esophageal cancers.3 Obesity also has significant economic consequences. Recent
figures suggest the increased need for medical care and lost productivity due to higher
rates of disease, disability, and death now exceeds $270 billion annually in the U.S.4
Even small reductions in body weight of 5 to 7% usual weight have been
demonstrated to significantly decrease obesity-related co-morbidities.5 However, once
established, obesity is highly refractory to treatment. Successful weight loss requires
significant lifestyle modifications. Sustaining weight control for the longer term will likely
110
require individual behavioral change as well as social support and policy shifts to help
maintain lost weight.
The purpose of this review is to provide clinicians and health care professionals
with an update of the current evidence supporting effective interventions for weight
control and the treatment of obesity. As described, a variety of treatment options exist,
including dietary programs, medical nutrition therapy, physical activity, behavior therapy,
pharmacotherapy, bariatric surgery, or a combination of approaches.6 There are, of
course, some individuals who are overweight or obese and who do not suffer from obesity
comorbidities and for whom weight loss attempts may be unnecessary. These individuals
may be better served if they are counseled regarding size acceptance.
Dietary Programs for Weight Loss
Caloric restriction combined with exercise or alone in order to create a daily
energy deficit is the foundation of most weight loss programs. In the absence of precise
measurements of energy expenditure (i.e., direct calorimetry or doubly labeled water), the
resting energy expenditure (REE) of an overweight or obese individual may be estimated
using standard prediction equations based on age, gender, height, and weight7,8
and a
calculation of ideal body weight (IBW) (versus actual body weight). The estimated REE
can then be multiplied by an appropriate physical activity level (PAL) factor to yield an
estimate of total energy expenditure (TEE), which may be further adjusted by the clinician
to help the patient achieve a target energy deficit that promotes weight loss. Low calorie
diets (LCD) (goal of 500-1000 kcal deficit/day) are often used to promote weight loss in
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obese individuals and overweight (300-500 kcal deficit/day) individuals.9 This type of low
calorie diet followed for 3-12 months can elicit up to an 8% loss of body weight.9 Very
low calorie diets (VLCD) (800 kcals/day or less) induce rapid weight loss in obese
individuals, although these diets are not recommended for long term use and should only
be attempted under the supervision of a physician.9-11
Notably, individuals on VLCD’s
have experienced the same degree of weight loss as those on LCD’s over the long term
due to decreased adherence to the diet.9,11
The impact of dietary macronutrient composition on weight loss has been
extensively investigated.12
Low carbohydrate (≥40-60 g CHO/d) macronutrient patterns
remain a popular option since participants on these diets can consume highly palatable
foods while adhering to a hypocaloric regimen. A 2008 systematic review that compared
the efficacy of low carbohydrate diets to low fat diets demonstrated an overall greater
weight loss with a low carbohydrate diet at 6 months, although this difference was not
evident at 12 months.12
Low CHO diets are associated with slightly higher protein intake,
and the additional protein intake has been hypothesized to have satiating effects, perhaps
leading to an overall decrease in energy intake.13,14
The Mediterranean Diet (MED),
consisting of high intakes of fruits and vegetables, olive oil, fish, and whole grain, has also
been proposed as an effective dietary intervention for weight loss, although only if it is
also hypocaloric.15
A recent two-year intervention study showed that the low carbohydrate
energy-restricted diet and the energy-restricted Mediterranean diet led to more weight loss
than a similar energy-restricted diet administered with a low fat macronutrient distribution
112
(Table 1).16
Ultimately, these data suggest that weight loss depends more on restricting
total energy intake than modification of the macronutrient distribution.
Commercial weight loss programs are commonly employed as a weight loss
strategy, though randomized controlled trials evaluating their efficacy have been limited.
A study by Rock et al assessed the efficacy of a two-year commercial weight loss program
in 446 overweight/obese adult women randomized to a center-based program, a web and
telephone-based program, or usual care (counseling with a Registered Dietitian).17
The
results suggested that all three interventions were associated with significant weight loss at
12 and 24 months, although women in the commercial program demonstrated greater
weight loss than usual care. Of importance, this is one of the few studies to show
participants’ maintenance of weight loss at 24 months.(Table 1)17
The retention rate of
this study was high, averaging 94%, likely because of various incentives, no fee for
participation, and frequent contact by study staff. A study of the same commercial weight
loss program completed in 2002 showed that of the 60,164 women who voluntarily
enrolled, only 7% remained in the program at one-year.18,19
Those who completed the
study achieved the greatest weight loss,19
suggesting that participation with good
adherence is the strongest predictor of weight loss (a consistent finding in any type of
weight loss program). Very few studies have compared commercial weight loss
programs, and those reported here demonstrate high attrition rates, ranging from 27% to
93%.18,20
One study performed in the UK compared four popular weight loss programs
(low carbohydrate, low fat, high fiber using a point system, or meal replacements) and
found equal weight loss (approximately 5.9 kg, see Table 1) across treatment approaches
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at 6 months.20
Currently, evaluations across commercial weight loss program are lacking
and more studies are needed.
Advances in technology have supported increased access to weight loss programs
at a lower cost than face-to-face programs.21
Results from randomized clinical trials of
online weight loss programs have had mixed results, with very few showing clinically
significant weight loss beyond the Rock study described earlier.21
Tate et al found that
participants who received online behavioral therapy and frequent virtual contact with a
registered dietitian over a 6 month period demonstrated greater weight loss than those who
received education only (-4.1kg versus 1.7 kg).21,22
In contrast, Womble et al reported that
education alone was more effective in promoting weight control than the virtual contact
approach.21,23
Despite the rationale that online weight loss is user-friendly and may
increase study retention rates due to greater flexibility with activities and meetings,
attrition rates are high in online weight loss studies, ranging from 20-40%.21
These
programs should continue to undergo evaluation especially as the population advances in
the frequency and understanding of computer use.
There is also a question of intervention ‘dose.’ In the Shape Up Rhode Island
study, increased feedback with regard to behavioral strategies for weight and self
monitoring during an online weight loss intervention resulted in weight loss of more than
5% body weight compared to those who received no feedback about behavior.24
The
DIAL (Drop It At Last) Study tested different amounts of telephone coaching with obese
adults and found that those who received 20 sessions lost more weight than those who
only received 10 coaching session (4.9 kg versus 3.2 kg, respectively).25
This data
114
suggests that using distance methods (including online methods) may be effective, but
amount of contact, feedback, and social support should be considered.
Physical Activity
Physical activity is a mainstay of behavioral intervention for weight management.
Evidence continues to grow suggesting that physical activity should be combined with
dietary energy restriction for optimal outcome in the setting of weight loss. First, the dose
of exercise necessary to elicit significant weight loss is relatively large.26,27
Second,
caloric restriction is more efficacious for rapid weight loss than exercise alone.
Importantly, combining exercise with energy restriction helps to counter the common
detrimental effects of caloric restriction alone including loss of lean tissue and lowered
resting metabolic rate. Finally, exercise can improve metabolic fitness, even in the absence
of significant weight loss.26,28,29
A combination of moderate caloric restriction and a
moderate increase in exercise energy expenditure is typically recommended since for
many, modest changes in dietary and exercise behaviors are easier to achieve than a major
change in either behavior alone.
Current physical activity recommendations call for approximately 30 minutes of
moderate to vigorous physical activity 5-7 days per week. The health benefits of this level
of physical activity are well documented and reasonable for most people to attain,
particularly if completed in multiple, short bouts. 30,31
. When weight loss is the primary
goal, a greater volume of exercise is needed, especially in the absence of significant
caloric restriction. Based on analyses of studies of energy expenditure using doubly
labeled water, Schoeller et al suggest a minimum of 60 minutes of daily MVPA is
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necessary for weight loss.32
Similarly, Jakicic and others33-35
have shown that a weekly
exercise energy expenditure upward of 2,000 kcals/week is necessary for significant
weight loss through exercise alone.36-39
Even at this level of expenditure, average weight
loss is modest, which can be discouraging and likely limits adherence, although the health
benefits are significant. It is important to note, however, that percent of weight lost as fat,
as well as reduction in abdominal and visceral fat is greater with exercise than diet.26,28,29
and regular exercise is the primary predictor of maintenance of weight after weight loss,38-
40
Dynamic, moderate-intensity, aerobic activity (e.g., walking, cycling, swimming,
etc.) is most commonly recommended for weight loss and maintenance since aerobic
activity elicits significant energy expenditure and improves cardiovascular and metabolic
fitness.40
Strength training activities also have significant benefits, promoting lean mass
and maintaining resting metabolic rate, and improving muscle strength and endurance,
thereby supporting further increases in physical activity.41,42
For persons with limitations
in mobility, resistance exercise may be a feasible alternative to other forms of exercise to
promote initial weight loss. Weight loss and fat loss may be less with resistance training
compared to aerobic exercise unless energy expenditure is equated.27
There is some
evidence that resistance training combined with higher protein intake promotes weight and
fat loss while maintaining muscle mass, which is important in obese individuals who are
losing large amounts of weight and in older individuals with sarcopenic obesity, in whom
further muscle loss presents a significant health risk.40,41,43,44
116
Clinicians can play a vital role in promoting physical activity along with dietary
change for weight management, which includes understanding of the published guidelines
for physical activity goals for prevention of weight gain (~150 minutes of MVPA per
week), active weight loss (150-420 minutes of MVPA per week), and weight maintenance
after loss (200-400 minutes of MVPA per week).40
Registered dietitians and other health
care providers should regularly promote the health benefits of regular physical activity,
although the final exercise program should be developed in collaboration with the patient
or client’s physician and a certified exercise specialist.
Behavioral Therapy
Behavioral Management
Real or perceived obstacles to weight loss may limit short term adherence and
long-term maintenance of weight loss. Behavioral therapy is a relatively inexpensive
strategy for weight control and is less invasive and more acceptable than surgical and/or
pharmacological approaches.21
Overall, behavioral therapy has been shown to be effective
in decreasing body weight (on average 7-10% over 6 months of intensive therapy), but
maintenance of weight loss has proven to be more challenging.10,24,45,46
One of the most common issues in any weight loss or weight maintenance program
is adherence.47
Length of time participating in an intervention is inversely associated with
adherence. 47,48
As participation time increases, adherence decreases, and weight loss is
not as pronounced as in the initial phase of loss.10,47,48
Self-monitoring of dietary intake
and physical activity is considered a central behavioral strategy to promote adherence and
117
indirectly promote weight loss.47
Participants who attend more group counseling sessions
and complete self-monitoring assignments are more likely to lose weight compared to
those who do not self-monitor.45,48
While self-monitoring is time consuming, frequency
of self-monitoring appears to predict adherence to weight loss regimes.47
Additionally,
perceptions of the complexity of weight loss program rules have been inversely associated
with adherence and amount of weight loss achieved.49
Standard behavioral therapy that focuses on changing lifestyle behaviors has been
used as a weight loss strategy for decades,46,47
yet its efficacy in producing long-term
weight loss has not been clearly demonstrated. Data suggest that rewards, behavioral cues,
and reminders all key components of standard behavioral therapy, become less effective in
eliciting lifestyle behavior changes over time.45
Further, the psychosocial literature shows
that boredom related to the intervention, loss of motivation, and emotional eating are
common barriers to weight control.11,45,50
The efficacy of cognitive behavioral therapy in conjunction with standard
behavioral therapy was recently evaluated for weight control. 51
Cognitive behavioral
therapy is based on the concept that thoughts control feelings and behaviors, thus
managing thoughts regarding self-worth, body image and others can direct weight loss
behaviors and prevent post-intervention weight regain.51
A summary of the results of
cognitive behavioral therapy interventions is given in Table 2 and generally indicate
significant weight loss during the intervention, with concomitant weight regain during
follow-up.
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Maintenance Tailored Therapy is a newer behavioral approach that is focused not
only on the promotion of weight loss but also weight maintenance after weight loss. This
approach administers various behavioral strategies at different times, for different
durations and even at variable doses to keep participants actively engaged long term in the
overall behavior-based intervention. Jeffery et al 45
tested maintenance tailored therapy
using a 6-phase program, each lasting eight weeks, with a four-week break between each
phase. Each phase had a specific concentration: i. calorie counting and goal setting, ii.
walking 10,000 steps per day, iii. meal replacement, iv. 3000 kcal exercise/week, v. the
stop light diet, and vi. deposit contracts.45
Although statistically equivalent weight loss
was seen in intervention and control groups, the maintenance tailored therapy group
demonstrated weight loss during all phases as well as break periods; most important, no
relapse in weight loss had occurred after 18 months in the intervention (Table 2).45
While
preliminary results are encouraging, more research is needed regarding this type of
behavioral intervention.
Motivational interviewing is a common weight loss technique used by clinicians.
One study assessed physicians’ counseling strategies using the 5A’s model of weight loss
-i. Assess risk, behavior, and readiness to change, ii. Advise change of behaviors, iii.
Agree and set goals, iv. Assist in addressing barriers and securing support, v. Arrange for
follow-up, and showed that physicians use an average of 5 of the possible 18 counseling
techniques. 52
Patients whose physicians used more counseling techniques were more
motivated to lose weight.52
A separate study showed that patients whose physicians
employed motivational interviewing techniques lost 1.6 kg more weight after three months
119
than those patients whose physicians did not use motivational interviewing.53
In an 8-
week weight loss study where participants were randomized to guided self help (GSH) or
GSH with motivaltional interviewing (MI), the GSH/MI group lost slightly more weight
and had less attrition than those receiving GSH alone.54
Based on present data and the
benefits of motivational interviewing, clinicians should be trained using this technique to
enhance weight loss in obese patients.
Pharmacotherapy
Dietary supplements that claim to treat obesity are widely distributed and readily
obtained in health food stores, grocery stores, pharmacies, on the Internet, and by mail.
According to the Natural Medicines Comprehensive Database, there are over 50
individual dietary supplements and 125 combination products marketed for weight loss.55
Population based surveys suggest that approximately that 15.2% of American adults
(20.6% women and 9.7% men) use dietary supplements for weight loss,56,57
most
commonly supplements with a stimulant as the active ingredient57
are used. Easy access,
low cost, no need for a prescription, and no need for behavioral modifications are the
primary reasons why individuals seek out dietary supplements as weight loss aids. Lack of
scientific evidence regarding efficacy and safety precludes informed recommendations for
use of weight-loss supplements, even if used only as adjunct to other weight management
strategies.
Common characteristics of individuals who used weight reduction supplements
included repeated, unsuccessful attempts at weight loss, and the use of multiple weight
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loss methods (>4) to achieve a target weight. 58
59
Higher usage of dietary supplements
was also observed in women (44.9%) then men (19.8%), and in obese minorities, aged 25-
34 years. Individuals of low socioeconomic status or who were less educated (high school
degree or less), were also more likely to use dietary supplements.59
Appetite suppressants are the most common supplement used for weight reduction.
These supplements are purported to promote weight loss by several mechanisms,
including increasing energy expenditure, increasing satiety, increasing fat oxidation,
inhibiting dietary fat absorption, modulating carbohydrate metabolism, increasing fat
excretion, increasing water elimination, and enhancing mood.56
Since multiple metabolic
pathways are targeted, these weight loss supplements are known to increase the risk of
adverse events. Meta-analysis of studies of Ephedra, for example, which contained
caffeine and resulted in only slightly higher weight loss compared to placebo, showed a
two to three-fold increased risk of developing severe neurological, psychological,
gastrointestinal and cardiovascular complications as well as death, and therefore was
deemed unsafe and removed from the market in 2004.56
The evidence in support of dietary supplements for weight reduction is not
convincing and there is a need for more research regarding long-term efficacy and
safety.60
The efficacy of the majority of supplements for altering weight and body fat
remains inconclusive. Side effects may be brand specific or vary within the same brand,
and there remains limited information regarding the dietary and drug interactions that
supplements may induce. The benefits and risks of dietary supplements for weight loss
have not been demonstrated in well-designed trials.
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Anti-Obesity Drugs
According to the National Institutes of Health, pharmacotherapy agents are recommended
for individuals who have been unable to achieve weight loss goals with diet and physical
activity alone, have a body mass index (BMI) greater than 27kg/m2, and exhibit serious
obesity comorbidities such as diabetes or high blood pressure.61,62 Currently, two
avenues involving merging of pharmacology and nutrition are being explored: 1)
inhibition of energy intake through targeting orexigenic signaling into the hypothalamic
feeding center and 2) increasing of energy expenditure through anorexic signals to
promote a caloric deficit (Table 3).63 Despite these efforts in drug development, it
remains unclear which targeted pathways will translate into safe, significant, and long
term weight loss.63
Although weight reduction with pharmaceutical treatment is typically modest (5-10%
reduction of total body weight) and similar to outcomes with behavioral interventions,
individuals on pharmacotherapy report an easier time maintaining weight post therapy
treatment.62 Additional benefits of pharmacotherapy include decreased blood pressure,
lipid levels, and blood glucose levels, respectively, along with an increase in insulin
sensitivity and reduced risk of cardiovascular disease and related co-morbidities.64
The majority of FDA-approved weight loss drugs are for short-term use (a few weeks or
months) (Table 4).65 Currently, there are two primary types of drugs for obesity
treatment: fat absorption inhibitors and anorexins.62 Both types are more effective when
122
combined with additional weight-loss practices such as calorie-restriction, exercise, and
behavioral modification.
Fat-absorption inhibitors work by reducing dietary fat absorption. The most
recently FDA approved fat absorption inhibitor is Xenical (Hoffman-LaRoche Inc, South
San Francisco, CA), which works by blocking approximately 30% of dietary fat.62
To
date, Xenical is the only weight loss drug that has been approved for long-term use in
severely obese individuals in the United States although its safety and efficacy has only
been established up to 2 years (Table 4). The over-the-counter version, Alli ®, is also
available, but at a lower dose than Xenical®.
Anorexins (appetite suppressants) work by promoting satiation (reduced desire to
eat) by slowing down the gastric emptying process. Mechanistically, anorexins interfere
with neurological pathways operating through the hypothalamus by inhibiting orexigenic
pathways while simultaneously enhancing anorexigenic pathways (Table 3). Anorexins
also decrease appetite by increasing serotonin or catecholamine, the two primary
neurotransmitters responsible for controlling mood and appetite.66
The net result is
enhanced satiation (reduced desire to eat), satiety (enhanced level of fullness on eating), or
both. These drugs generally come in the form of tablets or extended-release capsules, and
can be obtained via prescription or over the counter.66
The risks associated with weight-loss medications include development of
tolerance or addiction, thus a change in medication therapy may be necessary for
continued weight loss and in the case of addiction, various restrictions may apply;
continuous monitoring is recommended (Table 4). The majority of these drugs are
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designed for short-term use to limit the risks. Limited success has been achieved at
reducing body weight in obese populations by modulating fat absorption or altering
signaling input to the brain's feeding center. Further, the probability of achieving weight
loss greater than 10% remains low. Typically, individual weight loss plateaus after 6
months.66
It is unclear whether this plateau is due to a tolerance or if the effectiveness of
the medication has been maximized. Although most side effects are mild in nature, it is
uncertain whether these effects will progress or subside as the body adjusts to the
medications.
Bariatric Surgery
For obese individuals unable to achieve normal weight for height through
behavioral or other approaches, bariatric surgery offers an effective method for major
weight loss. The most efficacious surgical procedures reduce body weight by ~35-40%,
and most of the weight loss is maintained for at least 15 years.67-70
Intestinal
malabsorption and gastric restriction are the two most obvious mechanisms to explain
weight loss after bariatric surgery. Malabsorptive procedures, such as the jejunoileal
bypass (JIB) and biliopancreatic diversion (BPD) have been associated with serious
complications which have led to the abandonment of JIB from clinical practice and
restricted use of BPD to the superobese (BMI > 50 kg·m-2
).69
Purely restrictive bariatric operations cause weight loss by limiting the capacity of
the stomach to accommodate food and constricting the flow of injected nutrients.
Gastroplasty, often called “stomach stapling”, involves placing a horizontal staple line to
124
partition the stomach into a small, proximal pouch and a large distal remnant, connected
via a narrow stoma.71
High failure rate led to the vertical banded gastroplasty (VBG) in
which the partitioning line extends upward from the angle of his and a polypropylene
mesh reinforces the stoma.72
Although VBG effectively limits food consumption and
results in 30-50% reduction of body weight over 1-2 years, long-term results have been
disappointing.69
Recipients often compensate by eating frequent, small meals and calorie
dense foods. A nearly 80% failure rate has been reported after 10 years.73
Adjustable
gastric banding (AGB), a purely restrictive procedure, has been popular worldwide. An
adjustable variant of VBG, this approach involves placement of a prosthetic band around
the upper stomach to partition it into a small proximal pouch and a large, distal remnant,
connected through a narrow constriction.74,75
Free of anastomoses, this approach
eliminates staple-line dehiscence, is readily accomplished laparoscopically, and the
aperture can be modified noninvasively as needed. Risks include band slippage or erosion
into the stomach and reflux esophagitis. Weight loss after gastric banding is usually less
than bypass surgeries, but short and long-term complications are also less frequent.67
The Roux-en-y-gastric bypass (RYGB) appears to offer the best balance of
effectiveness versus risk and is the most widely used surgery in the U.S. for morbidly
obese people. Massive weight loss after this procedure reduces obesity-related
comorbidities and mortality. The operation may also improve glucose homeostasis
through physiological mechanisms not explained by weight loss alone,76
increasing
interest in its application in NIDDM patients.
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The modern RYGB divides the stomach into a small, proximal pouch and a
separate large, distal, remnant. The upper pouch is joined to the proximal jejunum through
a narrow gastrojejunal anastomosis (Roux-en-y configuration).76
Thus, the storage
capacity of the stomach is reduced to ~5% of its normal value, and injected food bypasses
approximately 95% of the stomach, the entire duodenum, and a small portion of the
proximal jejunum. Patients typically lose 35-40% of body weight, and long-term (> 15
years) maintenance of weight loss is good.68,70
Peri-operative mortality, largely from
pulmonary embolism or sepsis, is ~1%, but may be more in the hands of less experienced
surgeons. Post-operative complications occur in 10% of cases, and include deep vein
thrombosis, anastomotic leaks, internal hernias, gastrointestinal bleeding, ulcers in the
bypassed segments, torsion or volvulus of the roux limb, closed loop obstruction, stomal
stenosis, wound complications, staple-line disruption and gallstone formation with rapid
weight loss.67,69,70
Bypassing of the stomach and duodenum impairs absorption of iron,
calcium, thiamine and vitamin B12, thus supplementation of these micronutrients and
periodic monitoring for deficiencies are required.
In randomized, prospective trials, RYGB has caused 50-80% loss of excess body
weight as opposed to 30-50% after the equally restrictive VBG,77-80
and weight loss after
RYGB is more durable than after VBG. The two mechanisms cited most often to explain
the greater efficacy of RYGB over VBG are malabsorption and dumping syndrome.
However, clinically significant malabsorption, measured by indices such as albumin,
prealbumin, and fecal fat, is not observed after the standard proximal RYGB81-83
and the
severity of dumping, although it sometimes occurs, correlates poorly with the efficacy of
126
RYGB.76
Cummings et al (2004) suggest RYGB is more effective than VBG primarily
because loss of appetite from RYGB is greater and more consistent than VBG. The effect
is not explained by early satiety from restriction since it extends beyond the early
postprandial period. Also, levels of leptin and insulin, adiposity hormones, decrease as
expected with weight loss and thus do not account for weight loss84,85
and its regulation at
a lower level. Similarly, alterations in gut hormones do not seem to mediate the effects
since cholecystokin, serotonin and vasoactive intestinal peptide are unaffected by gastric
bypass.86,87
In contrast, impairment in ghrelin, a circulating orexigen, may explain at least
some of the loss of appetite following RYGB. Ghrelin is produced by the stomach and, to
a lesser extent, the duodenum, the areas affected by RYGB. Because ingested nutrients are
dominant regulators of its production, and because most of the ghrelin-producing tissue is
permanently excluded from contact with ingested nutrients after RYGB, disruption of
ghrelin regulation may explain the appetite suppression following RYGB. Indeed, several
prospective trials have reported decreased or very low ghrelin,88-92
even after massive
weight loss, although one group reported an increase as expected with other modes of
weight loss.93
Ghrelin also exerts several diabetogenic effects, and suppression of ghrelin
after RYGB may enhance glucose disposal and contribute to the rapid reversal of Type 2
diabetes mellitus that follows gastric bypass.76
Genetics in Weight Loss Response
Regardless of the approach (e.g., diet, exercise, surgery, and pharmacological), and even
with good compliance, weight loss and maintenance results vary significantly among
127
patients. This large variability amongst individuals on similar programs suggests genetics
play an important role in modifying the response to weight loss and weight maintenance
programs.94
Indeed, studies done with monozygotic twins show that weight loss on the
same intervention is quite similar within twin pairs, with significant differences between
pairs, demonstrating the strong contribution of genes to weight loss.95
A comprehensive discussion of the role of genetics in weight loss and maintenance
is beyond the scope of this review. For more information the reader is referred to Hainer 95
and Hetherington. 96
It is important for clinicians to understand that despite good
adherence, results for some individuals may be less than what was targeted. The Human
Obesity Gene Map, released in 2005, reports over 600 loci of single nucleotide
polymorphisms that may be associated with obesity.97
Most cases of obesity are thought
to be due to an interaction of multiple candidate genes, known as polygenic obesity,95
and
very few (perhaps 4-5% of severely obese individuals) are due to a single gene, referred to
as monogenic obesity. The complexity is evident in appetite dysregulation, for example,
which may be a consequence of multiple genetic polymorphisms in obese individuals, and
is a compelling example of polygenic obesity. Variations in the genes for cholecystokinin,
leptin and the leptin receptor, as well as those involved in lipid metabolism, have all been
implicated in increased meal size, poor postprandial compensation response, and
excessive snacking behaviors.95
Taken together, these factors reveal the complex
interaction between genetics and environment in obesity. While dramatic advances in
technology have allowed researchers to study the role of genes in weight loss, we are far
from providing individualized weight loss programs based on genetics.94
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Summary and Conclusion
Obesity remains a significant and challenging clinical condition. Effective
strategies for long term weight loss elude us. The following recommendations can be
proposed based on current knowledge:
Prevention is the most effective approach to reducing the substantial co-morbidity
associated obesity.
Clinicians have a primary responsibility to address weight control with patients
who are overweight/obese or demonstrating an upward trend in body weight.
Weight, waist circumference and when possible, body composition, should be
evaluated regularly to detect undesirable trends so that intervention can be initiated
early.
Targeted, behavior-based interventions that employ standard behavioral therapy,
motivational interviewing, or cognitive behavioral therapy can be effective in
promoting adherence and weight loss, although ongoing support is desirable to
counter recidivism.
Physical activity should be combined with energy restriction to promote caloric
deficit and weight loss and maintain lean mass and resting energy expenditure.
There are no effective dietary supplements for weight control; ephedra and
products containing ephredra-related compounds should be considered dangerous
and not be prescribed for weight control.
129
Evidence suggests FDA-approved pharmacological agents, while limited in terms
of available products, can promote weight loss of 5 to 10%.
Commercial weight loss programs have been sparsely evaluated and rarely
compared in controlled studies; nevertheless, current evidence suggests these
programs can be effective for weight loss.
For very obese persons who have failed with other approaches, a surgical
procedure such as the RYGB or AGB can promote significant weight loss and
improve obesity comorbidities, although the risks of these procedures must be
carefully considered.
For many obese persons, even modest weight loss of 5-10% has significant health
benefits, although even this level of loss is difficult to maintain. Ongoing support for
behavior change is essential and can best be delivered by a multi-disciplinary team
including the patient’s physician and experts in nutrition, exercise and behavioral
therapy.
130
Table 1. Efficacy of various diets and programs on weight loss and weight maintenance.
Diet/Program Tested Against Population Duration of
Intervention
Duration of
Follow Up
Findings Reference
Low Carbohydrate Diet
(Energy not restricted. 20g
CHO/day during induction
phase, increasing to 120g/day)
Med Diet / LF
n=322; ob
Israeli M&F;
medical
clinic
employees
6 months 18 months
>6 kg weight loss at 6 months;
4.7 kg total weight loss at 24
months
16
Med Diet (1500 kcals for
women; 1800 kcals for men.
35% kcals from fat, focusing
on olive oil and nuts)
LC / LF
n=322; ob
Israeli M&F;
medical
clinic
employees
6 months 18 months
~4.5 kg weight loss at 6
months; 4.4 kg total weight loss
at 24 months, virtually no
rebound
16
Low Fat Diet (1500 kcals for
females; 11800 kcals for males.
30% energy ffrom fat, 10%
from saturated fat, 300mg
cholesterol)
LC / Med Diet
n=322; ob
Israeli M&F;
medical
clinic
employees
6 months 18 months
~4.5 kg weight loss at 6
months; 2.9 kg total weight loss
at 24 months
16
Commercial Weight Loss
Program - Center Based
Commercial
Weight Loss
Program -
Phone Based /
Usual Care
n=442;
ovwt/ob F 2 years N/A
Energy restriction of 500-1000
kcal/day; prepackaged foods
comprised 42%-68% of energy
needs; weekly meetings with
consultant; goal of increased
physical activity.
7.4 kg, 6.2 kg, 2.0 kg weight
loss, respectively, after 2 years;
94% retention; meals provided
free of charge
17
131
BBC (British Broadcasting
Corporation) Diet Trials
Comparison of
LC / Point
System / Meal
Replacement /
LF
n=293;
obwt/ob
British M&F
6 months 6 months
6 months: Weight loss of 6.0,
6.6, 4.8, 6.3 kg, respectively; 12
months: total weight loss (54%
of original sample) of 8.5, 8.03,
6.49, 8.76 kg, respectively
20
Internet Behavior Therapy
(Received weekly lessons
regarding PA and nutrition;
submitted self monitoring
diaries online; received
feedback from therapist
regarding diaries)
Internet
Education
n=91;
ovwt/ob
M&F;
hospital
employees
6 months N/A
Both groups were given goals
to restrict energy intake to
1200-1500 kcals/day and to
increase energy expenditure to
at least 1000 kcals/week.
4.1 kg weight loss compared to
1.6 kg weight loss
22
Commercial Internet Weight
Loss
LEARN
Weight Loss
Manual
n=47;
ovwt/ob F 4 months 8 months
4 months: 0.9% compared to
3.6% weight loss. 12 months:
1.1% compared to 4.0% weight
loss.
23
132
FU= Follow Up; SBT=Standard Behavior Therapy; GSH=Guided Self Help; MI=Motivational Interviewing;
M=Male; F=Female
Table 2. Efficacy of various theories and programs on weight loss and weight maintenance.
Theory/Pr
ogram
Tested
Against
Populatio
n
Duration of
Intervention FU Findings Reference
Cognitive
Theory
SBT &
GSH
n=150; ob
F 10 months 3 years
10 months: 8.17 kg, 11.6,
5.24 kg weight loss,
respectfully. 3 years post-
intervention: Total weight
loss of 0.84, 3.21, .04 kg,
respectfully
51
Cognitive
Theory
Exercise
Dietetic
Treatment
n=204;
ovwt/ob
M&F
10 weeks 1 year
Decrease 1.36 and 1.44
points on BMI scale after
10 weeks. Less rebound
compared to EDT after 1
year.
98
Cognitive
Theory +
Mediterra
nean Diet
N/A
n=1406
ovwt/ob
Spanish
M&F
8.5 months N/A
Non-randomized; 7.8 kg
weight loss; very low
attrition rate
50
Mainte
nance
Tailored
Therapy
SBT n=213;
ob M&F
18
months
12
months
18 months: 8.2 kg and
9.3 kg weight loss
respectively. Higher
adherence than SBT; no
rebound over 18 months
versus significant rebound
in SBT. Follow up: 31%
less weight regain than
SBT
45
Guided
Self Help
+
Motivatio
nal
Interview
ing
Guided
Self Help
n=39;
ovwt
M&F
11 weeks N/A
Decrease 1.48 on BMI
scale, compared to -.7
points in GSH group;
higher retention rate in
GSH/MI
54
133
Table 3. Signaling pathways targeted by current
anti-obesity medications and their action
Inhibit EI Enhance EE
Orexigenic Signals Anorexic Signals
Neuropeptide Y (NPY) Pro-opiomelanocortin
(POMC)
Agouti-related protein
(ARGP)
Melanocortin system (a-
MSH)
Melanin-containing hormone:
(MCH)
Cocaine and
anphetamine-regulated
transcript (CART)
Endocanabinoids Glucagon like Peptide-1
(GLP-1)
Hypocretins/Orexins Amine neurotransmittrs
Ghrelin Peptide YY
EI = energy intake, EE = energy expenditure
134
Table 4. Weight Loss Medications
Conventional
Medicines Trade Name Mechanism of action Efficacy Side Effects
Approved
Use Reference
Orlistat Alli (OTC )
Blocks the digestion
and absorption of fat in
stomach and intestines.
Reduces 25% of
dietary fat; weight-
loss less for OTC vs.
prescription
Loose or more frequent
stools; intestinal cramps,
gas, oily spotting; less
GI events than
prescription
Long-term 99,62
**Orlistat Xenical
(prescription)
Gastric and pancreatic
lipase inhibitor; reduces
absortion of 30%
dietary fat consumed
Reduces ≈30%
dietary fat
absorption
Intestinal cramps, gas,
oily spotting Long-term
100
Benzphetamin
e Didrex
CNS stimulant;
mechanism uncertain;
decreases appetite,
increases energy
expenditure
Small increase in
weight loss of drug-
treated patients
only a fraction of a
pound a week
Palpitation, tachycardia,
increased blood pressure,
restlessness, dizziness,
insomnia, nausea,
diarrhea, other
gastrointestinal
disturbances
Short-term 101,62
Diethylpropion Tenuate
CNS stimulant;
mechanism uncertain;
decreases appetite,
increases energy
expenditure
Weight loss is 0.5
kg per week;
tolerance to
medications in this
class usually
develops a few
weeks
Increased blood
pressure; tachycardia,
insomnia, dizziness;
increased risk for
valvulopathy
Short-term 62
135
Phendimetrazi
ne
Bontril;
Prelu-2
Stimulates satiety in
hypothalamus and
limbic regions
Efficacy with other
anorectic agents has
not been studied;
combined use has
the potential for
serious cardiac
problems.
Arteriosclerosis,
symptomatic
cardiovascular disease,
moderate and severe
hypertension,
hyperthyroidism, and
glaucoma.
Short-term 102
Phentermine Adipex;
Ionamine
CNS stimulant;
mechanism uncertain;
decreases appetite,
increases energy
expenditure
Not established
Dizziness, dry mouth,
difficulty sleeping,
irritability, nausea,
vomiting, diarrhea, or
constipation may occur.
Short-term 62
Phenylpropran
olamine Dexatrim
May act through the
paraventricular
hypothalamus to
suppress appetite; may
be mediated by the
alpha-1 adrenergic
satiety receptors.
associated with an
increased risk of
hemorrhagic stroke
in women; FDA
does not recommend
using this product
closing of your throat;
swelling of lips, tongue,
or face; or hives;
short-term;
removed
from market
due to
increased risk
of
hemorrhagic
stoke
103
Rimonabant Accomplia
blocks endocannabinoid
receptors in brain,
adipose tissue, digestive
system, liver and
muscles; anorexic effect
on CNS, also acts on
gut to increase
sensation of satiety.
Average 4-5kg
weight reduction;
decreased waist
circumference;
increased in HDL-C,
decreased in LDL-C
particles, decreased
insulin resistance
naseau, diarrhea,
vomiting, anxiety,
depression, dizziness
Long term 100
136
***Sibutramin
e
Meridia;
Reducti
monoamine-reuptake
inhibitor, to reduce food
intake
Average weight
losses of 4–5 kg;
improvements in
HDL-C,
triglycerides and
HBA1c; supported
by 2 year efficacy
and safety trial
Increases in blood
pressure and heart rate
Long-term;
removed
from market
in 2010 due
to increased
risk of serious
heart events,
including
non-fatal
heart attack
and stroke.
100,104
*DEA schedule= abuse potential
**Orlistat is also available in a reduced-strength form without a prescription (Alli)
***Sibutramine recently was removed from the market in 2010.
137
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APPENDIX D
ADDITIONAL PUBLICATION #2:
ASSOCIATIONS BETWEEN MOTHER’S BMI, FRUIT AND VEGETABLE INTAKE
AND AVAILABILITY, AND CHILD’S BODY SHAPE AS REPORTED BY WOMEN
RESPONDING TO AN ANNUAL SURVEY
Authors: Caitlin A. Dow, Betsy C. Wertheim, Elizabeth Pivonka, Cynthia A. Thomson
as published in Food and Nutrition Sciences. 2012, 3, 1636-1643.
Abstract
Previous evidence indicates that a child’s body mass index (BMI) and eating behaviors
are often related to the BMI and eating behaviors of his/her parents. Additionally, there
is evidence suggesting that fruit and vegetable intake may impart weight control benefits.
The purpose of this study was to examine the relationship between mother’s BMI and the
intake/availability of fruits and vegetables in the home, as well as mother’s perceived
body shape of her child. This is a cross sectional, descriptive analysis of results from a
large internet-based survey of Generation X and Y mothers evaluating the role of fruit
and vegetable consumption and health behaviors in U.S. families. Mothers (n=1,469)
with children under the age of 18 living in the home reported her BMI, her fruit and
vegetable intake, and fruit and vegetable availability in the home. Additionally, mothers
with children between the ages of 2 and 12 (n=1,177) reported her child’s body shape
(using graduated images of children ranging from the 3rd
-97th
percentiles of BMI).
Mother’s BMI was not related to fruit or vegetable intake, though it was inversely related
145
to fruit, but not vegetable, availability in the home. Mother’s BMI was also
positively related to child’s body shape, and mother’s fruit, but not vegetable, intake was
inversely related to child’s body shape. Our findings support a potential role for fruit
availability promoting healthy BMI in mothers and/or healthier body shape in their
children.
Introduction
Obesity is a health concern in adults and children [1-3], ultimately resulting in an
increased risk for chronic diseases including Type 2 Diabetes, cardiovascular disease, and
cancer [4, 5]. Evidence suggests that children’s body mass index (BMI) and eating
behaviors are associated with the BMI and eating behaviors of their parents [2, 6, 7].
Increased fruit and vegetable (FV) consumption as part of a healthy, balanced diet is an
established health goal in the U.S. [8] and is often recommended by practitioners as a
targeted behavioral strategy to reduce body weight [9-11].
The social ecological theory suggests that the environment plays an important role in
behavior development, and the family environment is especially important in the
development of eating behaviors in children [12]. Evidence correlating FV intake in
children and the role of parental FV consumption and attitudes has been evaluated in both
systematic reviews and nationally representative surveys [12, 13], though a recent
systematic review and meta-analysis found only a weak association [14]. A review
evaluating the role of the home environment on FV intake in children and adolescents
showed that availability, parental modeling, and parental intake were all positively
146
associated with children’s FV consumption [12]. The role of the mother in children’s
eating behaviors may be of particular importance, as mothers characteristically spend
more time than fathers with children and have more influence over feeding activities [15].
There is a large body of evidence suggesting that parental intake of FV, specifically, is
highly associated with children’s intake [7, 13, 16].
Despite the established role of parental choices and modeling on children’s FV intake,
there is a lack of data regarding the complex relationship between a mother’s FV intake
and her BMI and the relationship of these parameters to her child’s FV intake and body
shape (i.e. ectomorph, mesomorph, or endomorph).
A large internet survey of mothers with children residing in the home conducted annually
on behalf of the Produce for Better Health Foundation affords a unique opportunity to
further explore these relationships. Specifically, this report sought to evaluate the
relationships between FV intake/availability and BMI of mothers, maternal BMI and her
child’s body shape, and maternal FV intake/availability and mother’s perception of her
child’s body shape. We anticipated that FV intake/availability would have an inverse
relationship with BMI, maternal BMI would be associated with larger reported body
shape of the child, and maternal FV intake/availability would be associated with smaller
perceived child’s body shape.
METHODS
Survey Development
147
An annual online consumer survey was originally developed by the Produce for
Better Health Foundation Research Board in collaboration with Ogilvy Public Relations
Worldwide, the public relations agency for Fruits & Veggies—More Matters®
and
OnResearch, Inc. (Ontario, Canada). A pilot study was conducted in 2006 in Generation
X (GenX; individuals born between 1965-1979) mothers (n=73), further reviewed and
refined, and sent to outside reviewers with behavioral expertise for additional review. The
baseline survey was fielded in February 2007 in 1,000 mothers and has been completed
annually since 2007 in US mothers.
Questions were developed to obtain information about knowledge, attitudes, and beliefs
of GenX mothers and to gain insight into barriers to providing fruits and vegetables to
their families. The sample of potential participants was drawn from membership lists of
survey panels for online companies who partner with OnResearch, Inc. Potential
respondents who met inclusion criteria were invited via email to participate in the survey.
Respondents included mothers born between 1965 and 1990 with at least one child under
the age of 18. Those who completed the survey were given a small cash reward for
participating. Each year, the survey is completed in women who have not participated in
previous years.
Most questions were answered using a 5-point Likert scale, though several questions
required open-ended responses. Respondents were asked to provide information
regarding their personal FV intake and FV availability in their home (including fresh,
canned, frozen, or dried). The survey stated that a serving of fruit/vegetable was
148
approximately the size of a tennis ball, and women provided a numerical response for
the number of servings they ate each day. Women reported their average daily intake of
fruits and vegetables separately.
Additional Survey Sections Added in 2011 Survey
In 2011, additional survey questions were developed that had not been used in previous
surveys. All data for the current analysis were collected January 14-31, 2011. Mother’s
BMI was calculated using information from those respondents who elected to provide
data on their height and weight (92.9%, n=1,486). Those who reported a BMI <15 kg/m2
(n=9) or >60 kg/m2 (n=8) were excluded from the analytical dataset. Thus, data from
1,469 mothers were included in our analyses.
Additionally in 2011, respondents were asked to report on their child’s body shape only if
they had children between the ages of 2 and 12 years living in the home. If a woman
reported having more than one child between 2 and 12 years of age, they were asked to
report on the body shape of only one child chosen at random by the survey software
(n=1,177). The images used to inform on child’s body shape were produced by Truby and
Paxton in 2002 [17]. The children depicted in these images ranged in size based on the
1979 National Center for Health Statistics (NCHS) BMI percentiles (A=3rd
, B=10th
,
C=25th
, D=50th
, E=75th
, F=90th
, and G=97th
) (Figure 1). In order to assess outcomes
associated with children’s body size, the eight categories were collapsed into clinically
relevant BMI groups: ≤25th
percentile (groups A, B, and C combined), 50th
percentile
(group D), 75th
percentile (group E), and ≥90th
percentile (groups F and G combined).
149
Statistical Analysis
Associations between mother’s BMI and fruit or vegetable intake were tested using linear
regression. Wilcoxon’s rank sum test was used to test the difference in FV intake
between women who opted to provide height and weight compared to those who did not.
The relationship between FV intake and FV availability in the home was tested using
multinomial logistic regression and assessed for confounding by mother’s BMI, though
no confounding was observed. Linear regression models were also used to evaluate the
differences in BMI between women who selected specific categories of FV availability
among the variety of responses available. Associations were assessed for potential
confounding by education, employment, marital status, age, number of children, daily
physical activity, fruit or vegetable intake, and ethnicity. Covariates that resulted in a beta
coefficient change of more than 10% were included in the final adjusted model. The
covariates included in the model for fruit availability and BMI were physical activity and
education, whereas the model for vegetable availability and BMI included physical
activity, education, marital status, and ethnicity.
Differences in BMI between mothers who selected various body shapes for their children
were tested using ordinal logistic regression. The association between child’s body shape
and FV availability in the home was tested using chi-square tests. Lastly, the relationship
between mother’s FV intake and child’s body shape was tested using ordinal logistic
regression. Trends were tested by including child’s body shape category as an ordinal
variable in the model, wherein categories A/B/C=1, D=2, E=3, and F/G=4. This trend
150
was assessed for potential confounding by mother’s BMI; no confounding was
observed. All tests were considered statistically significant at p<0.05. Statistical
analyses were performed using Stata 11.1 (StataCorp, College Station, TX).
RESULTS
Survey respondents had a mean ± SD age of 36.4 ± 6.1 years and 2.0 ± 1.0 children under
age 18 living in the home. The mean BMI (calculated from self-reported height and
weight) of mothers was 27.5 ± 7.3 kg/m2, and 54.2% of women were considered
overweight or obese (BMI ≥ 25 kg/m2). Mothers reported a mean number of daily
servings of fruits of 2.6 ± 3.0 and a median of 2 servings. The mean number of daily
servings of vegetables was 2.5 ± 2.0 servings, and the median intake was 2 servings
(Table 1). There was no difference in fruit or vegetable intake between women who
elected to provide height/weight compared to those who did not (P=0.599 and P=0.680,
respectively).
Associations between Mothers’ BMI, FV Intake, and FV Availability
No significant association was found between mother’s BMI and self-reported daily
servings of fruit or vegetable intake (P=0.125 and P=0.099, respectively). However,
women who reported greater availability of FV in their home did report significantly
greater daily intake than those who reported lower availability (Table 2).
BMI of respondents was compared across FV availability categories. Women who
reported that fruit was “always available” had a significantly lower BMI than those who
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reported that fruit was “almost always/ usually available” (26.6 ± 6.6 versus 28.1 ±
7.9 kg/m2, respectively; P<0.001) or “occasionally/ rarely/ never available” (26.6 ± 6.6
versus 29.4 ± 7.1 kg/m2; P<0.001) in the home (Table 3). This relationship held when
adjusted for education and physical activity. Furthermore, the BMI of women who
selected that vegetables were “always available” was significantly lower than those who
selected that vegetables were “almost always/usually available” (26.9 ± 6.8 versus 28.1 ±
7.8, respectively; P=0.001); women who selected that vegetables were
“occasionally/rarely/never available” also demonstrated a higher BMI compared to the
“always available group,” but this difference was not significantly different, likely due to
the small number of women reporting low availability (n=74). After adjusting for
education, physical activity, marital status, and ethnicity, the relationship between BMI
and vegetables “almost always/usually available” was attenuated and no longer
statistically significant (P=0.100) (Table 3).
Associations between Child’s Body Shape, FV Availability, and Mother’s FV Intake
Child’s body shape was assessed using the images in Figure 1. Most women (n=915,
77.7%) selected that their child resembled images A, B, or C (relating to ≤25th
BMI
percentile) while very few women (n=70, 5.9%) selected images F/G (relating to ≥90th
BMI percentile). There was a significant association between mother’s BMI and child’s
body shape (P=0.001) (Figure 2). Additionally, those women who selected that her child
resembled endomorphic images (E or F/G) had significantly higher BMIs than those who
selected that their child resembled more ectomorphic or mesomorphic images (A/B/C).
152
No significant differences existed amongst categories of child’s body shape when
compared to FV availability categories (data not shown). However, mothers who
reported greater fruit intake were more likely to report their child’s body shape in the
lower BMI categories (P=0.007), though this inverse association did not hold true in
relation to mother’s vegetable intake and child’s body shape (P=0.809) (Table 4).
DISCUSSION
This study provides hypothesis-generating results regarding the role of mothers’ practices
specific to FV intake/availability and both her and her child’s body size. There was a
significant inverse relationship between mother’s BMI and fruit and, to a lesser extent,
vegetable availability, though we did not find a significant association between mother’s
BMI and reported FV intake. We also found an association between mother’s fruit, but
not vegetable, intake and the reported body shape of her child; mothers who reported
children in the higher percentiles of BMI reported significantly lower fruit intake than
mothers who reported their child’s body size in the lower or normal BMI percentiles.
Short-term interventions indicate that increasing FV intake may be a good strategy for
weight control as part of a balanced diet, as FV’s increase feelings of satiety and may
reduce intake of high-energy foods [9, 18]. However, observational data evaluating the
relationship between FV intake and BMI provide inconclusive results [9, 18, 19]. A
systematic review of the literature suggests that there may be a relationship between low
FV intake and higher BMI [19]; however, most studies that assess this relationship are
designed with endpoints of FV intake and chronic disease outcomes [20], making it
difficult to accurately extrapolate their findings to obesity, specifically. Our study did
153
show a statistically significant relationship between fruit availability and BMI in
mothers. These findings are consistent with much of the research regarding home FV
availability and weight status, most of which has focused on children and adolescents and
not adults [21, 22]. Interestingly, this effect was not seen with vegetable availability and
BMI, as mothers who selected that vegetables were “occasionally/rarely/never available”
in their home had lower BMIs than those who selected that vegetables were “almost
always/usually available.” Supporting our data, an analysis from the USDA’s 1994-1996
Continuing Survey of Food Intakes by Individuals (CSFII) found that lower BMI was
associated with greater fruit, but not vegetable, intake in adults and children [23].
Although we did not see a significant difference in BMI between women selecting the
highest and lowest vegetable availability categories, it should be noted that women who
indicated that vegetables were always available in their home had a lower BMI than those
who did not choose this option. In addition, the BMI of this group was similar to the
BMI of the group who indicated that fruits were always available in the home. One
important issue that may potentially explain these results is the very low number of
women who selected the lowest categories of vegetable availability (n=74) compared
with those who indicated that vegetables were always available (n=753). Furthermore,
we did not obtain information regarding fruit and vegetable preparation methods.
Vegetables consumed may have been fried or eaten with high calorie sauces or butter.
This effect may explain the lack of an association between vegetable availability and
BMI.
154
According to the social ecological theory, there are many factors that influence
children’s weight status, including parental behaviors and beliefs [12, 15]. Our study
explored the relationship between mother’s BMI and child’s (aged 2-12 years) body
shape. Child’s body shape was used as a proxy for child’s BMI, as validated by Saxton
et al. [24]. We found a significant association between mother’s BMI and child’s body
shape. Women who selected that their child resembled an image of a larger body size
had higher BMIs than those who selected a smaller body size. These findings agree with
previous reports regarding parental BMI and child’s weight status [25, 26].
In addition to the relationship between mother’s BMI and child’s body shape, we
explored additional variables that may influence child’s weight status. Previous work
suggests that FV availability in the home is related to children’s FV intake [22].
Children’s FV intake may then confer benefits such as healthier weight status and
reduced adiposity [18, 22]. Despite this rationale, we failed to observe a relationship
between FV availability and child’s body shape. However, actual intake of FV in children
was not assessed.
There is a large body of evidence exploring the relationship between mother-child FV
intake resemblance [13, 14, 27] as well as FV intake and BMI in both adults and children
[18, 19]. To our knowledge, this is the first study examining the relationship between
maternal FV intake and child’s body shape. We observed a significant inverse association
between mother’s fruit intake and child’s body shape, suggesting that lower maternal
fruit intake may be associated with her child’s larger body size. This relationship did not
exist between vegetable intake and child’s shape, perhaps for the same reasons that it did
155
not exist between mother’s BMI and home vegetable availability. These findings
provide further evidence suggesting that interventions to improve FV intake in children
should also focus on promoting FV intake in mothers, as the family environment is a
strong determinant of behavior development [12].
This is the first internet-based study to target a specific generation of mothers and for
which we have novel information regarding mother’s perception of child’s body size to
evaluate the role of FV in family health. The study was large with responses from over
1,400 mothers. However, the study does have limitations. This study was conducted
using cross-sectional data, limiting the ability to determine causation. Additionally, this
study was conducted online and is therefore biased towards women with internet access.
This study was also based on self-reported height and weight, FV intake, and FV
availability; thus, respondents may have provided inaccurate information. Without a
marker of validation (height and weight measured by a trained professional, a biomarker
of intake such as serum carotenoids, or in-home appraisal of FV availability), we cannot
ascertain the validity of self-reported data in the current study. We also did not have any
information regarding other aspects of the diet, making it difficult to control for other
potential confounders. Furthermore, social desirability may have resulted in answers that
were not truly representative of actual behaviors and beliefs.
Additionally, our survey collected information on mother’s perceptions of her child’s
body shape. Although these images were designed using BMI percentiles developed over
30 years ago, the scale itself was not developed until 2002 [17] and currently represents
the most up-to-date scale of children’s body images. Furthermore, this scale is unique as
156
each image is an actual photograph of a child that correlates to a specific BMI,
whereas previously developed scales simply depict silhouettes that do not necessarily
correspond to actual BMI values [17]. A validation study by Saxton et al. in 2009
indicated that children were able to identify their body shape using these images with
reasonably high accuracy [24]. However, there is literature that indicates that mothers
tend to underestimate their child’s body size [28, 29]. Currently, 16.9% of American
children are classified as obese [30], while only 5.9% of women in this survey chose the
body images that most closely correlate with obesity (F=90th
percentile; G=97th
percentile). This suggests that some women may have misclassified her child or that the
sample of women surveyed is not largely representative of the American population.
Conclusions
The relationships between mother’s BMI, FV intake, FV availability, and child’s weight
status are extremely complex and not well understood. Using a national sampling of
mothers, we were able to evaluate FV availability in the home in relation to the BMI of
the mother and also the body size of the child. The current study supports a role of fruit
and, to a lesser degree, vegetable availability in BMI of mothers. Our data suggest a
relationship between mother’s fruit, but not vegetable, intake and child’s body shape.
The evidence generated from this study, particularly that regarding women’s BMI and
home FV availability, and mother’s FV intake and child’s body shape, should be further
explored in longitudinal studies in order to inform on future interventions targeting FV
consumption and healthy weight in the family setting.
157
FIGURES
Figure 1. Child’s body shape images shown to mothers responding to an annual survey
regarding fruits and vegetables. Images produced by Truby and Paxton et al.
158
10
20
30
40
50
60
Mo
ther's b
ody m
ass ind
ex (
kg/m
2)
A/B/C D E F/G
Child’s Body Shape
n=91
5 BMI=26.8±6.5 n=12
3 BMI=26.5±6.9 n=6
9 BMI=29.1±8.0* n=70
BMI=30.9±9.6*
M
oth
er’
s
Bo
dy
Ma
ss
Ind
ex
(kg
/m2)
BMI values represent mean ± SD. *Significantly different from the BMI of mothers who selected images A/B/C. P trend=0.001
Figure 2. Comparison of BMI of mother’s who selected images that most
closely resembled their child’s body shape.
159
TABLES
Table 1. Characteristics of mothers responding to an
annual survey regarding fruits and vegetables in
2011 (n=1469)
n (%) or
mean ± SD
Age (years) 36.4 ± 6.1
Number of children per mother 2.0 ± 1.0
Number of girls per mother 1.0 ± 0.9
Number of boys per mother 1.0 ± 0.9
Age of children (years) 7.6 ± 4.6
Ethnicity
White/Caucasian 1171 (79.7)
Black/African American 107 (7.3)
Hispanic/Latino 97 (6.6)
Asian/Pacific Islander 75 (5.1)
Other 19 (1.3)
Annual household income
<$25,000 274 (18.7)
$25,000-$49,999 400 (27.2)
$50,000-$74,999 348 (23.7)
$75,000-$99,999 235 (16.0)
$100,000-$149,999 161 (11.0)
>$150,000 51 (3.5)
Marital status
Married/living with someone 1178 (80.2)
Single 150 (10.2)
Separated/divorced 133 (9.1)
Widowed 8 (0.5)
Aerobic physical activity (min/day)
<30 814 (55.4)
30-60 590 (40.2)
>60 65 (4.4)
Body mass index (kg/m2) 27.5 ± 7.3
Underweight (<18.49) 49 (3.3)
Normal weight (18.5-24.9) 625 (42.6)
Overweight (25.0-29.9) 368 (25.1)
Obese (>30.0) 427 (29.1)
Fruit intake (servings/day)
2.6 ± 3.0
[2.0]a
Vegetable intake (servings/day)
2.5 ± 2.0
[2.0]a
aMedian intake of fruits or vegetables.
160
Table 2. Reported home fruit/vegetable availability
versus fruit/vegetable intake in mothers responding to
an annual survey (n=1,463)
Intake
(servings/day)
Fruit Availability
Always 2.8 ± 1.5
Almost always/usually 2.2 ± 1.5a
Occasionally/rarely/never 1.4 ± 1.4a,b
Vegetable Availability
Always 2.7 ± 1.5
Almost always/usually 2.1 ± 1.5a
Occasionally/rarely/never 1.4 ± 1.2a,b
aSignificantly different from "always” available
(P<0.001). bSignificantly different from "almost always/usually”
available (P<0.001).
161
Table 3. Differences in BMI based on fruit/vegetable availability in mothers responding to an annual survey regarding fruits/vegetable in
health (n=1,463)
n (%)
BMI
(kg/m2)
Unadjusted
Adjusted
β Coefficient (95%
CI) P value β Coefficient (95% CI) P value
Fruit Availability
Always 734 (50.0) 26.6 ± 6.6 Reference Reference
Almost always/usually 629 (42.8) 28.1 ± 7.9 1.56 (0.80-2.33) <0.001 1.053 (0.28-1.83)a 0.008
a
Occasionally/rarely/never 106 (7.2) 29.4 ± 7.1 2.77 (1.30-4.24) <0.001 1.912 (0.44-3.38)a 0.011
a
Vegetable Availability
Always 753 (51.3) 26.9 ± 6.8 Reference Reference
Almost always/usually 642 (43.7) 28.1 ± 7.8 1.25 (0.49-2.01) 0.001 0.628 (-0.12-1.38)b 0.100
b
Occasionally/rarely/never 74 (5.0) 27.9 ± 7.1 1.06 (-0.66-2.79) 0.229 0.068 (-1.62-1.76)b 0.937
b
aAdjusted for education and physical activity.
bAdjusted for education, physical activity, marital status, and ethnicity.
162
Table 4. Mother's fruit/vegetable intake versus mother’s report of
child's body shape in mothers responding to an annual survey
regarding the role of fruits/vegetables in health
Child’s body
shape category
Fruit or
Vegetable n (%)
Mother’s Intake
(mean ± SD)
A/B/C Fruit 910
(77.8) 2.5 ± 1.6
D Fruit 123
(10.5) 2.5 ± 1.4
E Fruit 68 (5.8) 2.3 ± 1.3
F/G Fruit 68 (5.8) 2.0 ± 1.6
Total Fruit
1169
(100) a0.007
A/B/C Vegetable 912
(77.7) 2.4 ± 1.6
D Vegetable 123
(10.5) 2.5 ± 1.5
E Vegetable 69 (5.9) 2.6 ± 1.7
F/G Vegetable 69 (5.9) 2.1 ± 1.3
Total Vegetable 1173
(100) a0.809
aP for trend across body shape categories.
163
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APPENDIX E
ADDITIONAL PUBLICATION #3:
PREDICTORS OF CARDIOMETABOLIC RISK FACTOR IMPROVEMENTS WITH
WEIGHT LOSS IN WOMEN
Authors: Caitlin A. Dow, MS; Cynthia A. Thomson, PhD, RD; Shirley W. Flatt, MS;
Nancy E. Sherwood, PhD; Njeri Karanja, PhD; Bilge Pakiz, EdD; Cheryl L. Rock, PhD,
RD
Submitted to: Journal of the American Heart Association, February 2013
Abstract
Background: Weight loss is associated with improvements in cardiometabolic risk
factors, including serum glucose, insulin, C-reactive protein (CRP), and blood lipids. Few
studies have evaluated the long-term (>18 months) effect of weight loss on these risk
factors or sought to identify factors associated with sustained improvements in these
measures.
Methods and Results: In 442 overweight/obese women (mean [SD] age of 44 [10]
years) participating in a weight loss trial, we sought to identify predictors of weight loss-
associated cardiometabolic risk factors at 12 and 24 months of intervention. Total
cholesterol (TC), LDL-cholesterol, HDL-cholesterol, non-HDL cholesterol, triglycerides,
insulin, glucose, CRP, and cardiopulmonary fitness were measured at baseline, 12
months, and 24 months. At 24 months, significant reductions in body weight, waist
circumference, CRP, TC, LDL-C, HDL-C, and non-HDL cholesterol were observed
167
(P<0.05). At 24 months, mean TC and non-HDL cholesterol were reduced regardless of
the amount of weight lost, whereas reductions in LDL-C, CRP, insulin, and triglycerides
were observed only in those who lost ≥10% body weight. Step test performance
improved only in those who lost ≥10% body weight after 24 months. Change in weight
demonstrated a positive predictive value for change in cholesterol, insulin, glucose, and
triglycerides. Baseline level of the biomarker showed the greatest predictive value for
follow-up measures for insulin, cholesterol, glucose, and triglycerides.
Conclusion: Our data extend the results from short-term weight loss trials and suggest
that the magnitude of weight loss and baseline risk factors are associated with
improvements in cardiometabolic risk factors even after 24 months.
INTRODUCTION
Obesity remains a significant risk factor for disease-associated morbidity and mortality in
the U.S., including that associated with diabetes, coronary heart disease, and stroke.1
Obese individuals often present with elevated fasting values of glucose,2 lipids,
1 and
inflammatory markers,2 as well as insulin resistance.
3 Even with modest weight loss,
individuals may demonstrate significant improvements in metabolic risk factors for
obesity-related disease, particularly cardiovascular disease and diabetes.1,4-6
It is
estimated that a 10% reduction in body weight in an obese individual can promote
significant reductions in metabolic parameters including circulating glucose, insulin and
inflammatory markers, even if the body mass index (BMI) remains within an at-risk
category.7 Yet, few studies have evaluated this relationship beyond 12 months.
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The ability to promote weight loss through dietary interventions is well-established, and
behavioral weight loss programs and counseling remain a primary clinical approach to
reduce body weight in overweight and obese adults.6 These programs vary in intensity,
delivery approach, behavioral constructs applied, dietary plan and duration. But
independent of the approach, energy deficit can be achieved and is associated with
modest weight loss.3,5,8
Further, the demonstrated weight loss associated with targeted
dietary interventions generally translates to improvements in metabolic indices associated
with obesity-associated disease. 4,6,9-11
In a recently conducted randomized controlled weight loss study, women were
randomized to receive a structured weight loss program delivered either in person or via
telephone or to receive minimal diet counseling, considered usual care, for a period of 24
months. Women assigned to the structured weight loss program arms demonstrated
greater reductions in body weight, BMI, and waist circumference over time than those in
usual care condition.12
Changes in lipids and CRP according to study arm assignment
have been previously reported.12
The purpose of this analysis was to assess changes in
cardiometabolic risk factors associated with weight loss. Further, this analysis sought to
determine what factors (baseline value of biomarker, baseline weight, % change in body
weight, age, ethnicity) predicted improvement in cardiometabolic risk factors at 12 and
24 months.
169
METHODS
Study Subjects and Recruitment
The weight loss intervention trial recruited 446 overweight/obese women from a screened
sample of 564 women. Women were eligible to participate if they were >18 years of age,
had a BMI between 25 and 40 kg/m2 and were a minimum of 15 kg above ideal body
weight as defined by the 1983 Metropolitan Life tables.13
Participants were recruited via
list serves and flyers distributed through each of the four study sites (University of
California, San Diego; University of Arizona, Tucson; University of Minnesota,
Minneapolis; and Kaiser Permanente Center Northwest, Portland, OR). Any woman who
was pregnant, planning a pregnancy, lactating or reported a history of eating disorders,
other psychiatric disorders, co-morbid conditions, food allergies, or was unable to
perform a 3-minute step-test for cardiopulmonary fitness assessment was excluded from
enrollment. All study participants completed the consent process and provided written
informed consent prior to randomization. The Institutional Review Boards approved this
study for Human Subjects’ Protection at each recruitment site prior to initiation. Clinical
trials Identifier: NCT00640900.
Intervention
The details of the study trial participation have been previously described.12
Briefly,
eligible women were randomized in a 3:3:2 allocation to center-based, telephone-based,
or usual care that included weight loss counseling by a dietetics professional. Women in
the center-based intervention arm visited the weight loss center weekly for brief
170
counseling sessions and weigh-ins with designated, trained staff; they also had access to
web-based resource materials. Women in the telephone-based arm similarly received
weekly counseling by telephone to reinforce weight loss behaviors and goals and also had
access to web-based resource materials. Prepackaged meals and snacks provided 42-68%
of total energy needs of the prescribed eating plan and were provided free-of-charge for
participants randomized to these two study arms. Generally after the initial 12-month
period, women were transitioned to fewer pre-packaged meals and more self-selected
food items. In addition to the prepackaged foods, women assigned to the weight loss
program received one-on-one counseling to promote adherence to a low fat (20-30% total
energy), reduced energy (1200-2000 kcal), high fruit and vegetable eating plan with
recommendations for increased physical activity to achieve current guidelines14
of 30
minutes of planned exercise 5 or more days/week.
Usual care counseling sessions took place once at baseline and again at 6 months. Usual
care study participants received written educational materials to support their dietary
goals (500-1000 kcal/day deficit); regular physical activity was also promoted.
Outcomes
The primary outcome of the study was change in body weight. Weight and height (from
which BMI was calculated) were measured at baseline and every 6 months throughout
the study. Waist and hip circumference were also measured and recorded at each time
point. A 3-minute step-test was administered at baseline and repeated at 12 and 24
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months. This test measures heart rate during the first 30 seconds of recovery from
stepping.
Subjects also provided a fasting blood sample at baseline, 12, and 24 months for
evaluation of cardiometabolic risk factors. Specifically, fasting plasma was sampled to
measure lipid profiles including total cholesterol, triglycerides, and high density
lipoprotein (HDL) using enzymatic methods (Kodak Ektachem Analyzer System,
Johnson & Johnson Clinical Diagnostics, New York, NY). Low density lipoprotein
(LDL) was calculated using the Friedewald equation.15
Non-HDL cholesterol (non-
HDL-C) was calculated by subtracting HDL from the total cholesterol value. Blood
glucose was determined using enzymatic methods (Kodak Ektachem DT60 Analyzer,
Johnson & Johnson, Rochester, NY). A double antibody radioimmunoassay, with <0.2%
cross-reactivity with human proinsulin, was used for the analysis of fasting serum insulin
(Linco Research Inc., St. Charles, MO). The homeostasis model assessment of insulin
resistance (HOMA-IR) was calculated by dividing the product of fasting glucose (mg/dL)
and fasting insulin (μU/mL) by 405.16
CRP was quantified using a high sensitivity
polystyrene-enhanced turbidimetric in vitro immunoassay kit (DiaSorin Inc., Stillwater,
MN).
Statistical Analysis
Risk categories for levels of CRP,17
total cholesterol,18
HDL-cholesterol,18
LDL-
cholesterol,19
non-HDL cholesterol,20
glucose,18
insulin,21
HOMA-IR,16
waist,22
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triglycerides,18
and cardiopulmonary fitness23
were identified and used as cut-points in
tabulation.
Differences in biochemical risk factors between baseline and 12 or 24 months (overall
and stratified by biomarker risk category) were analyzed using paired t-tests. Regression
models predicted change in laboratory values as a function of ethnicity, age, baseline
levels of laboratory analyte, waist circumference, and weight change. All regression
models were adjusted for randomization assignment, cardiorespiratory fitness, and
waist/height ratio. For each term in each model, we present parameter estimates (beta
coefficients). To further explore the relationship between change in body weight and
cardiometabolic risk factors, a stratified analysis was conducted in which women were
classified as either losing ≥10% baseline body weight or losing <10% of baseline body
weight. Analyses were conducted using SAS version 9.3 (SAS Institute, Inc., Cary,
NC).
RESULTS
Four hundred and forty six overweight/obese women were enrolled; four were removed
from analysis due to post-randomization exclusions, leaving 442 in the study sample.
Thirty-five women did not complete the 12-month clinic visit, and of the 407 remaining
women, inadequate blood sample was available to complete glucose (1 subject) or lipid
(2 subjects) analysis.
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Table 1 provides baseline demographic characteristics of the study population. Women
enrolled in the study were a mean (SD) age of 44 (10) years, a mean weight of 92.1
(10.8) kg with a BMI of 33.9 (3.4), and a waist circumference of 108.6 (9.5) cm. At
baseline, 159 (36%) women were postmenopausal. At follow-up, mean weight loss as a
percentage of baseline weight was 8.6% (0.4%) in 417 subjects with available measured
body weight at 12 months, and 6.6% (0.5%) in 407 subjects with weight data at 24
months. At study entry, 2 women were using hypoglycemic agents, and 1% (n=5) were
using them at study end. Twenty-six subjects took lipid-lowering drugs at study entry, 30
women took them at 24 months, and 17 women reported estrogen use throughout the
study (data not shown).
When categorized by cardiometabolic risk level (Table 2), the median level of CRP was
3.0 mg/L, and 45% of subjects exceeded this level. There was an overall decrease in
median (interquartile range) of CRP from 3.0 (1.6-5.6) to 1.9 (1.0-4.1) after 12 months,
with the greatest decrease in women who entered the trial with a CRP value ≥3.0 mg/L.
In a sensitivity analysis excluding subjects with CRP ≥10 mg/L (n=38), paired t-tests
among subjects with CRP ≥3 mg/L and <10 mg/L still showed significant decreases in
log-transformed CRP at 12 and 24 months (data not shown). Baseline mean glucose
values were within the normal range with a mean (SD) of 94 (11) mg/dL. At both 12 and
24 months, the follow-up metabolic assessments suggested that participation in the trial
was associated with a significant increase in fasting glucose among women who entered
the trial with a glucose value <100 mg/dL, whereas at 24 months there was a significant
174
decrease in glucose in those with elevated baseline levels. Baseline insulin levels were
elevated above the 15 μU/mL cut-point at an average value of 17.8 (8.9) μU/mL and were
significantly reduced after 12 months. Insulin levels significantly increased at 24 months
in those with baseline values <15 μU/mL from 11.1 (2.7) μU/mL to 13.4 (5.5) μU/mL.
Overall and in the high-risk subjects, HOMA-IR showed a pattern similar to insulin, with
a decrease at 12 months that was no longer significant at 24 months. Total cholesterol
decreased in the entire cohort after 24 months, on average by 12 mg/dL from 196 (36)
mg/dL to 184 (37) mg/dL. LDL-cholesterol was significantly decreased at 12 and 24-
month follow-up in participants with a baseline level above 130 mg/dL. HDL values
were slightly below target at 57 (16) mg/dL at baseline, and increased after 12 months of
intervention only in women with depressed baseline values (<60 mg/dL), though HDL-
cholesterol returned to baseline values by 24 months in this group. Non-HDL cholesterol
values were significantly reduced after 24 months in women who started with elevated
levels (≥160 mg/dL). Triglycerides were reduced after 12 months only in women with
elevated baseline values. In a sensitivity analysis that excluded women (n=10) who
began a lipid-lowering regimen during the trial, results in lipid changes were essentially
unchanged (data not shown). Waist circumference was significantly reduced after 12 and
24 months. At baseline, all women had a waist-to-height ratio (WHtR) above the
recommended cutoff point of 0.5. WhtR was significantly reduced from 0.66 (0.06) at
baseline to 0.60 (0.06) and 0.61 (0.07) at 12 and 24 months, respectively. In sensitivity
analyses limited to postmenopausal women, outcomes were similar to those in the entire
cohort.
175
As shown in Table 3, baseline level of each biomarker was strongly and inversely
associated with follow-up measures in the individual marker. Further, age was positively
associated with cholesterol levels. Baseline weight or waist circumference was not
associated with change in any of the markers with the exception of waist circumference
being positively associated with insulin level at 12 months (R2= 0.29).
Models were stratified by weight loss percentage at both 12 months (Table 4) and 24
months (Table 5). At 12 months, 167 women lost at least 10% of initial body weight. In
these women, CRP was reduced from 2.9 mg/L to 1.2 mg/L. WHtR, total cholesterol,
and LDL-C were reduced regardless of weight loss percentage (Table 4). However, in
those who lost ≥10% of initial weight, reduction in total cholesterol was more
pronounced, dropping from a mean (SD) of 194 (38) mg/dL to 185 (38) mg/dL versus
from 198 (34) mg/dL to 192 (34) mg/dL in women losing <10% of initial weight.
Likewise, at 24 months (Table 5), total cholesterol was reduced, regardless of degree of
weight loss, reducing to 180 (32) mg/dL in those who lost ≥10% of initial weight versus
186 (33) mg/dL in those who lost <10% of initial weight. LDL-C reduction was only
maintained at 24 months in those who lost at least 10% of their weight. Non-HDL-C was
reduced in both weight loss categories at 12 and 24 months. Reductions in triglycerides,
insulin, and HOMA-IR were only evident in women who lost ≥10% body weight at both
12 and 24 months.
176
Cardiopulmonary fitness (based on the 3-minute step-test) also improved in study
participants. Interestingly, this effect was independent of the degree of weight loss only
at 12 months (Table 4). After 24 months, however, cardiopulmonary fitness significantly
improved in women whose weight loss was ≥10%, while it was significantly reduced in
those who did not lose 10% of initial weight, compared to baseline values (Table 5).
DISCUSSION
In this study of overweight women, participants in the structured weight loss program lost
an average of 7% of baseline body weight at two-year follow-up. Weight loss resulted in
an improvement in numerous cardiometabolic risk factors, including biochemical values
and a functional test of cardiopulmonary fitness. Importantly, the improvements in most
risk factors were evident at both 12 and 24 months despite modest recidivism in weight
loss over time. These results are supported by several shorter-term studies, including an
8-week study by Te Morenga et al. in 83 adults, wherein weight loss ranged from 3.3 to
4.5 kg and resulted in significant reductions in LDL-cholesterol, triglycerides, and
glucose.8 A weight loss intervention by Muzio et al. resulted in significant reductions in
weight, waist circumference, triglycerides and LDL-cholesterol after 5 months.11
Short-
term studies have also demonstrated a reduction in CRP,24
but seldom to the degree
necessary to reduce clinical risk as observed in this trial. In a 12-week weight loss study
by Clifton et al. in 79 overweight/obese adult females, significant weight loss was also
demonstrated, but importantly, this is one of only a few trials that re-assessed the
177
intervention efficacy longer term.10
As with the present study, long-term improvements in
glucose, insulin, CRP, and LDL-cholesterol were demonstrated.10
Longer-term studies are limited, but a few have evaluated changes in cardiometabolic
parameters over time in relation to weight loss. Four-year data from the LookAHEAD
trial, a study performed in individuals with type 2 diabetes, support our results and show
that a lifestyle intervention aimed at weight reduction results in significant reductions in
triglycerides and LDL-cholesterol.25
In one of the larger samples studied, Foster et al.
showed an 11 kg average weight loss at year 1 (n=307; 68% female) and 7 kg loss at year
2 (n=113),26
weight loss effects similar to what our sample achieved. Consistent with our
findings, triglycerides improved at year 1 and were not significantly different from
baseline at year 2 in that study. In contrast to our findings, their results suggested no
significant reduction in LDL-cholesterol at 24 months.26
In a study of 176
overweight/obese adults of which 87% were female, Burke et al. showed significant
improvements in total cholesterol and LDL:HDL ratio as well as HOMA-IR, a measure
of insulin resistance, after 12 months of intervention, changes that were generally
sustained at six-month post-intervention follow-up.27
These results, taken in
consideration with our results, suggest that efforts to favorably modulate cardiometabolic
risk factors through modest weight loss in numerous short-term trials generally translate
to longer-term follow-up, even with modest weight regain between 12 and 24 months.
178
Improvements in several CVD risk factors were demonstrated in response to participation
in this weight loss study. WHtR is an adiposity index that more accurately predicts
cardiometabolic risk than BMI or waist circumference.28,29
In this study, WHtR was
reduced regardless of the degree of weight lost, though this effect was more pronounced
in women who lost ≥10% of their initial body weight. Recent evidence also indicates that
non-HDL cholesterol more accurately predicts risk of coronary heart disease than LDL-C
as it encompasses all cholesterol-containing atherogenic particles including LDL-C and
VLDL-C.30
Women with elevated baseline non-HDL cholesterol (≥160 mg/dL)
demonstrated reductions to within a normal range after 24 months, and non-HDL
cholesterol values were reduced at 12 and 24 months, regardless of the degree of weight
loss. The literature regarding lifestyle interventions for weight loss and non-HDL
cholesterol response is extremely limited, though our findings suggest that non-HDL
cholesterol is responsive to a weight loss intervention and could be included as an
outcome in future studies targeting cardiometabolic risk via weight reduction.
Previous work has demonstrated that reductions in insulin resistance are observed with
increases in physical activity, independent of weight loss.31
Other intervention studies for
weight reduction agree that exercise is a necessary component, in addition to diet
modification, to reduce insulin resistance.32
In this study, diet was the major lifestyle
modification addressed, but regular physical activity was also promoted through
counseling. In response, insulin levels and, perhaps more importantly, HOMA-IR values,
were significantly reduced at 12 months, but only in women demonstrating a weight loss
179
≥10% of their initial body weight. We cannot ascertain if this effect was due solely to
changes in diet or physical activity.
This study also had the benefit of evaluating cardiopulmonary fitness, an indicator of
health also known to improve with physical activity.33
Performance improved over time
regardless of percent weight loss but was not associated with cardiometabolic factors.
These results suggest that efforts to expand outcome measures in weight loss studies
targeting improved cardiometabolic risk should consider biochemical biomarkers as well
as functional measures. Improvements in cardiopulmonary fitness have been reported in
other weight loss studies,32,34
although not consistently.35
While control for baseline values of the respective outcome (i.e. weight, biomarker) when
conducting regression analysis is sometimes applied, estimation of the predictive nature
of the baseline value is seldom evaluated.36
Our study suggests that one important
predictor of change in cardiometabolic biomarkers is the baseline level of the individual
biomarker. These data suggest that lifestyle interventions targeting weight loss are
effective for improving cardiometabolic risk in individuals presenting with unfavorable
measures. Our data suggest that these measures should be expected to show significant
and sustained improvement if a degree of weight loss is achieved and maintained.
Limitations to this study include a lack of assessment of lipoprotein particle size, known
to be associated with cardiovascular risk37
and responsive to dietary intervention.9
180
Further, we did not conduct hemodynamic measures, such as blood pressure, during the
three-minute step test. These measures likely would have provided more robust data
regarding cardiopulmonary fitness.33
However, cardiopulmonary fitness was not a
primary endpoint of this study, and although less accurate than measuring maximal
oxygen uptake (VO2max) and hemodynamics during test administration, the three-minute
step test has high reliability, is sensitive to change, and has been used broadly to assess
change in cardiopulmonary fitness in clinical trials.23
Finally, we did not collect specific
information on diet or physical activity that can influence these biomarkers; however, it is
apparent that women were generally in negative energy balance given the substantial
weight loss demonstrated by so many study participants. It is well recognized that
negative energy balance can modulate many of these targeted risk factors whether that
occurs through dietary intervention or in combination with physical
activity.11,24,25,30,35,36,38,39
Strengths of the trial include the 24-month intervention and follow-up period in a
relatively large sample of women with robust and repeated measures of cardiometabolic
risk factors. The sample size and variance in weight loss also afforded an opportunity to
ascertain differences in risk factors over time in women who were more (≥10% body
weight loss) versus less (<10% body weight loss) responsive to the weight loss
interventions.
181
In conclusion, participation in a weight loss intervention resulted in significant reductions
in body weight, BMI, and waist circumference after 12 and 24 months. This weight loss
was associated with significant improvements in several of the cardiometabolic risk
factors that are commonly assessed in the clinical setting. Moreover, weight loss of
≥10% after 12 months produced significant reductions in these risk factors, often
lowering the risk factor from a category of high risk to that of medium or low risk (i.e.
CRP and insulin). These data also show that baseline cardiometabolic risk factors
(cholesterol, fasting glucose, insulin, triglycerides, and CRP) have significant predictive
value in determining favorable risk reduction response to the weight loss intervention,
suggesting that these risk factors could be used to identify women more likely to respond
favorably to weight loss interventions.
182
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186
Tables
Table 1. Baseline Characteristics of Overweight / Obese Women Enrolled in a
Weight Loss Study (n=442)
Characteristic Baseline Value, Mean (SD)
Age (years) 44(10)
Weight (kg) 92.1(10.8)
Height (cm) 164.9(6.3)
BMI (kg/m2) 33.9(3.4)
Waist Circumference (cm) 108.6(9.5)
Hip Circumference (cm) 120.2(8.2)
Waist to Hip Ratio 0.9(0.06)
Postmenopausal (%) 159 (36%)
Education (n)
High School or less 52
Some College 189
College Graduate 95
Graduate School 106
187
Table 2: Change in Cardiometabolic Risk Factors in Relation to Baseline Values, Stratified
by Clinical Risk
Risk Factor Baseline
Mean (SD)
n=442
n1 12 Months
Mean (SD)
n=407
n1 24 Months
Mean (SD)
n=383
Glucose, Mean (SD) 94 (11) 406 95 (18) 383 94 (13)
<100 mg/dL 89 (7) 310 91 (9) ‡
293 91 (10) †
≥100 mg/dL 110 (19) 96 107 (32) 90 101 (18) ‡
Insulin, Mean (SD) 17.8 (8.9) 407 15.6 (9.8) ‡ 383 18.5 (11.2)*
<15 μU/ml 11.1 (2.7) 180 11.0 (4.5) 174 13.4 (5.5) ‡
≥15 μU/ml 23.1 (8.4) 227 19.3 (11.2) ‡ 209 22.7 (12.8)
HOMA-IR2 4.24 (2.53) 405 3.72 (2.58)
‡ 383 4.37 (3.10)*
<3 2.27 (0.54) 138 2.39 (1.11) 135 2.95 (1.38) ‡
≥3 5.26 (2.55) 267 4.41 (2.84) ‡ 248 5.15(3.49)
CRP mg/L, Median (IQR) 3.0 (1.6, 5.6) 407 1.9 (1.0, 4.1) † 383 2.1 (1.0, 4.0)
‡
CRP <1 mg/L
(low risk)
0.6 (0.2) 38 0.8 (0.6) 35 1.0 (0.7) †
CRP 1-2.99 mg/L
(medium risk)
1.9 (0.6) 169 1.9 (3.9) † 164 3.1 (12.5)
†
CRP ≥ 3 mg/L
(high risk)
6.8 (4.7) 200 5.1(6.8) † 184 5.4 (6.2)*
Total Cholesterol mg/dL
Mean (SD)
196 (36) 406 189 (36) ‡
383 184 (37) ‡
<200 mg/dL 171 (21) 228 172 (28) 215 168 (27)
≥200 mg/dL 229 (21) 178 211 (34) ‡
168 204 (37) ‡
188
LDL Cholesterol mg/dL
Mean (SD)
117 (33) 405 111 (34) ‡ 382 113 (37)*
<130 mg/dL 99 (20) 266 99 (27) 255 104 (33)*
≥130 mg/dL 154 (17) 139 133 (35) ‡ 127 132 (38)
‡
HDL Cholesterol mg/dL,
Mean (SD)
57 (16) 405 57 (16) 383 53 (15) ‡
<60 mg/dL 47 (7) 252 52 (13) ‡ 239 47 (10)
≥60 mg/dL 73 (12) 153 66 (15) ‡ 144 63 (17)
‡
Non-HDL Cholesterol
mg/dL
134 (36) 405 132 (35) ‡ 383 131 (38)
‡
<160 mg/dL 123 (34) 294 121 (28) 280 120 (30)
≥160 mg/dL 186 (18) 111 162 (38) ‡ 103 159 (42)
‡
Triglycerides mg/dL,
Mean (SD)
110 (57) 406 106 (55)* 383 117 (93)
<150 mg/dL 91 (26) 337 93 (34) 317 100 (43) ‡
≥150 mg/dL 206 (69) 69 168 (89) ‡ 66 195 (186)
Waist cm, Mean (SD) 108.3 (9.4) 409 99.0 (10.1) ‡ 392 101.1 (10.7)
‡
<88 cm 86.7 (1.2) 4 86.0 (11.3) 4 82.9 (6.5)
≥88 cm 108.8 (9.3) 405 99.2 (10.0) ‡ 388 101.3 (10.5)
‡
Waist/Height Ratio
<0.5 N/A
≥0.5 0.66 (0.06) 409 0.60 (0.06) ‡ 392 0.61 (0.07)
‡
*P<.05, †P<.01,
‡P <.001
1Sample size represents n for paired t tests at 12 or 24 months and varies based on completion of 12- or 24-
month clinic activities. 2Homeostasis model for insulin resistance. Insulin sensitive is <3; insulin resistant is ≥3.
189
Table 3: Predictors of Cardiometabolic Biomarker Change
Models Predicting 12-Month Biomarker Values (n=406)
Insulin
R2 = .37
Cholesterol
R2 = .46
Glucose
R2 = .26
TG
R2 = .66
CRP
R2 = .16
Baseline level of
biomarker
0.551‡
0.597‡
0.786‡
0.752‡
0.470‡
Baseline weight -0.057 -0.093 0.069 0.286 0.041
% change in weight 0.274‡ 0.403* 0.351
‡ 1.514
‡ 0.091
†
Baseline waist 0.294* 0.409 0.211 -0.585 0.013
Age -0.025 0.520‡ 0.016 0.301 -0.021
White
race/ethnicity
-2.022* 5.980 -0.964 1.428 -0.420
Models Predicting 24 Month Biomarker Values (n=383)
Insulin
R2 = .52
Cholesterol
R2 = .39
Glucose
R2 = .31
TG
R2 = .56
CRP
R2 = .07
Baseline level of
biomarker
0.770‡ 0.505
‡ 0.525
‡ 1.150
‡ 0.430
†
Baseline weight 0.073 -0.300 0.104 0.673 -0.060
% change in weight 0.399‡ 0.544
† 0.406
‡ 1.788
‡ 0.064
Baseline waist -0.173 0.847 -0.306 -2.147 -0.029
Age 0.067 0.637‡ 0.064 0.817* -0.098*
White
race/ethnicity
-0.744 5.592 -1.137 -3.287 -2.545*
*P<.05, †P<.01,
‡P <.001. Values shown are beta coefficients in a regression model for each biomarker at
each time period, adjusted for randomization assignment, step test heart rate, and waist/height ratio. CRP
refers to C-Reactive Protein; TG refers to triglycerides.
190
Table 4: Change in Cardiometabolic Risk Factors, Stratified by Percent Weight Loss
after 12 Months
Lost 10% weight after 12
months (n=167)
Did not lose 10% weight
after 12 months (n=240)
Baseline 12 Months Baseline 12 Months
Weight kg, Mean (SD) 93.2(11.3) 77.3(10.7)‡ 91.0(10.3) 88.3(11.2)
‡
Waist cm, Mean (SD) 109.1(9.5) 93.8(8.5)‡ 107.8(9.4) 102.7(9.5)
‡
Waist/Height Ratio 0.66(0.06) 0.58(0.05) ‡ 0.66(0.06) 0.63(0.06)
‡
Body Mass Index,
Mean (SD)
33.9(3.4) 28.2(3.4)‡ 33.7(3.4) 32.7(3.8)
‡
CRP mg/L, Median (IQR) 2.9(1.5, 5.7) 1.2(0.7, 2.6)† 3.1(1.7, 5.5) 2.4(1.3, 4.9)
CRP <1 mg/L
(low risk %)
9.0 40.4‡ 9.2 15.8
†
CRP 1-2.99 mg/L
(medium risk %)
41.9 40.1 39.2 39.4
CRP ≥3 mg/L
(high risk %)
49.1 19.3‡ 51.6 44.8*
Total Cholesterol mg/dL,
Mean (SD)
194(38) 185(38)† 198(34) 192(34)
‡
LDL mg/dL, Mean (SD) 115(34) 109(37)* 119(32) 112(32)‡
HDL mg/dL, Mean (SD) 57(15) 57(15) 56(16) 57(16)
Non-HDL mg/dL, Mean(SD) 136 (38) 128 (39)† 142 (35) 135 (34)
†
TG mg/dL, Mean (SD) 107(48) 94(39)‡ 113(64) 114(63)
191
Glucose mg/dL, Mean (SD) 94(11) 93(24) 94(11) 96(13)†
Insulin uU/mL, Mean (SD) 16.9(9.1) 12.9(10.0)‡ 18.2(8.7) 17.5(9.2)
HOMA-IR, % Insulin
Resistant1
62% 35%‡ 68% 65%
Step Test Heart
Rate/30 sec, Mean (SD)
54(10) 46(9)‡ 54(9) 50(9)
‡
Step test poor to
fair (%)
68.5 30.7‡ 70.2 58.4
‡
Step test good to
outstanding (%)
31.5 69.3‡ 29.8 41.6
‡
*P<.05, †P<.01,
‡P <.001.
1Homeostasis model for insulin resistance. Insulin sensitive is <3; insulin
resistant is ≥3.
192
Table 5: Change in Cardiometabolic Risk Factors, Stratified by Percent Weight Loss
after 24 Months
Lost 10% weight after 24
months (n=130)
Did not lose 10% weight
after 24 months (n=253)
Baseline 24 Months Baseline 24 Months
Weight kg, Mean (SD) 93.3(10.3) 77.3(10.1) ‡ 91.0(10.9) 89.7(11.9)
†
Waist cm, Mean (SD) 109.0(9.2) 94.8(8.9) ‡ 107.8(9.5) 104.2(9.8)
‡
Waist/Height Ratio 0.66(0.06) 0.57(0,06) ‡ 0.66(0.06) 0.63(0.06)
‡
Body Mass Index,
Mean (SD)
34.0(3.3) 28.2(3.4) ‡ 33.6(3.4) 33.2(4.0)
†
CRP mg/L, Median (IQR) 2.9(1.6, 5.5) 1.3(0.7, 2.8) ‡ 3.0(1.7, 5.6) 2.5(1.3, 5.2)
CRP <1 mg/L
(low risk %)
7.7 42.3‡ 9.9 13.8
CRP 1-2.99 mg/L
(medium risk %)
44.6 33.1 39.1 43.9
CRP ≥3 mg/L
(high risk %)
47.7 24.6‡ 51.0 42.4
†
Total Cholesterol mg/dL,
Mean (SD)
194(38) 180(32) ‡ 197(35) 186(33)
‡
LDL mg/dL, Mean (SD) 116(34) 108(34)* 118(32) 116(39)
HDL mg/dL, Mean (SD) 57(15) 56(14) 57(16) 52(15) ‡
Non-HDL mg/dL 137(38) 124(43) ‡ 140(35) 134(35)
‡
TG mg/dL, Mean (SD) 104(45) 92(33) ‡ 114(56) 124(61)
‡
193
Glucose mg/dL, Mean
(SD)
93(10) 89(11) ‡ 94(11) 96(14)
Insulin uU/mL, Mean (SD) 16.3(8.1) 13.3(6.2) ‡ 18.1(8.6) 21.1(12.2)
‡
HOMA-IR, % Insulin
Resistant1
61% 39%‡ 67% 78%
‡
Step Test Heart
Rate/30 sec, Mean (SD)
54(9) 46(8) ‡ 54(10) 50(9)
‡
Step test poor to
fair (%)
68.5 36.8‡ 46.1 87.1
‡
Step test good to
outstanding (%)
31.5 63.8‡ 53.9 12.9
‡
*P<.05, †P<.01,
‡P <.001.
1Homeostasis model for insulin resistance. Insulin sensitive is <3; insulin
resistant is ≥3.
194
APPENDIX F
ADDITIONAL PUBLICATION #4:
USE OF HERBAL, BOTANICAL, AND NATURAL PRODUCT SUPPLEMENTS IN
ONCOLOGY AND DIABETES POPULATIONS
Authors: Caitlin Dow, MS and Maureen Leser, MS, RD, CSO, LD
In press: Oncology Nutrition Connection
Introduction
It is well recognized that herbal and botanical products exert biologic effects. Over 50%
of commercial drugs are derived from bioactive compounds of non-human origin, many
of which are plants (1). As increasing numbers of Americans have became disillusioned
with perceived over-use, adverse side effects, and high cost of prescription drugs, they
have turned to herbal and botanical supplements, which they consider natural and safer
than synthetic medications (2). A new medical diagnosis can also stimulate lifestyle
changes including an increase in the use of dietary supplements (3).
Dietary supplement use, particularly multivitamins, is highly prevalent in the United
States. Use is reportedly higher in older, female, overweight/obese individuals as well as
those with health concerns. Data from the 2003-2006 National Health and Nutrition
Examination Survey (NHANES) indicate that approximately 54% of adults (excluding
pregnant women) and 70% of adults >71 years take multi-vitamin and mineral
supplements while 20% of Americans use a supplement with at least one botanical
ingredient (4). A survey published in 2008 by the National Center for Complementary
and Alternative Medicine (NCCAM) indicated that herbal therapy or use of natural
products other than vitamins and minerals was the second most prevalent alternative
195
medicine modality (excluding prayer), and used by 18.9% of adults (5). Individuals with
chronic disease, including cancer and diabetes mellitus, frequently supplement their diets
with herbal and natural therapies, possibly due to real or perceived limitations of
conventional treatments (6).
The evidence base for herbal/dietary supplements used to prevent or improve therapeutic
outcomes in diabetes and cancer remains limited and concern over potential harm
remains (6-7). Because of the widespread use of these products, it is important for the
registered dietitian (RD) to understand and recognize potential benefits as well as
potential adverse events associated with supplementation. This paper briefly reviews
usage of supplements in oncology and diabetes patients, potential biological benefits and
risks of select supplements used by each population, the current legislative framework for
dietary supplements, and the role of the RD in counseling patients on supplement usage.
Chronic Disease and Dietary Supplements
Adults with cancer or other chronic conditions are more likely to report use of
supplements than healthy populations (8). Supplement usage is widespread amongst
oncology patients, and data indicate that usage typically ranges from 30-75% in these
patients (9). One pilot study of 140 oncology patients indicated that 52% were taking
some kind of dietary supplements and, of those, 23% were using herbal supplements.
Demographic factors associated with herbal supplement use were female gender, age,
fatigue, cancer pain, and presence of metastasis (7). A subset of participants enrolled in
196
the American Cancer Society’s Study of Cancer Survivors-I (SCS-I) self-administered a
dietary supplement survey. Of 827 surveys included in the review, approximately 97% of
participants had undergone conventional therapy for their cancer, yet 69.3% also reported
using dietary supplements after their cancer diagnosis. Garlic, echinacea, ginseng, black
cohosh, and gingko biloba were included in the list of supplements (other than
multivitamins) taken by 10 or more people in this study (10).
Similar to patients diagnosed with cancer, supplementation with herbal/dietary agents
also is common in people diagnosed with diabetes. Those with diabetes often report use
of dietary supplements and other alternative medicines because of a desire to take an
active role in their health, to improve their quality of life, or due to a belief that
conventional therapies do not work or are too expensive (11). Data from the 2002 and
2007 National Health Interview Study found that, of the 4,150 individuals diagnosed with
Type 1 or Type 2 Diabetes, approximately 34% were taking at least one non-vitamin/non-
mineral dietary supplement (11). A recent retrospective study in 459 adults with diabetes
indicated that 55% used some form of vitamin, mineral, or herbal supplement on a daily
basis (12). Interestingly, the use of non-mineral/non-vitamin supplements was twice as
common among type 2 diabetics as compared to type 1 diabetics (39% vs. 20%,
respectively) (12). Among the more frequently consumed dietary supplements were
cinnamon, coenzyme Q10, chromium, and alpha-lipoic acid.
Target Mechanisms for Diet Supplementation in Cancer and Diabetes
The use of dietary supplements is often driven by an assumption that such products may
197
modify health by targeting specific pathology associated with disease. For cancer patients
and/or those with a diagnosis of diabetes this may include modulation of inflammation,
oxidative stress, insulin resistance, and/or hyperglycemia. Evidence exists to suggest that
some compounds do favorably alter these biological responses. Curcumin may reduce
inflammation through its ability to inhibit cyclooxygenase-2 (COX-2) (13). Alpha-lipoic
acid is an endogenously produced antioxidant, though there is some data that
supplementation also improves insulin sensitivity (14). Evidence indicates that ginseng
and magnesium may improve insulin secretion/sensitivity (15-16) while chromium and
oat bran may improve glycemic control in patients with Type 2 Diabetes (17-18).
Supplements with anti-cancer properties often modulate cell cycles and help eliminate
abnormal cells that may become cancerous. Allyl sulfides, a variety of which make up
94% of compounds in garlic, are believed to suppress in vitro and in vivo growth of
multiple types of cancer cells via apoptosis and cell cycle arrest (19). Unfortunately,
evidence remains inconclusive for the use of many supplements in individuals with health
issues, as a large number of studies in this field are limited by small sample sizes and/or
poor designs.
Legislation
Though plants have long been considered the “medicine of mankind,” it was reasoned
that scientific discoveries, growth and sophistication of the pharmaceutical industry and
government oversight would give consumers what nature could not - safe and effective
medicines that are consistent from dose to dose. But a series of events in the early to mid
198
20th
century cast doubt on this assumption and prompted Congress to pass regulations
(20-23) intended to establish a pharmaceutical industry based on “purity, truth in
labeling, and effectiveness” (20). The Dietary Supplement and Health Education Act
(DSHEA) was passed almost 20 years ago to define and provide a regulatory framework
for dietary supplements. To prevent manufacturers from making unsubstantiated claims
regarding supplements, DSHEA established specific guidelines for dietary supplement
labels. Table 1 summarizes those guidelines.
Table 1: Permissible Dietary Supplement Label Claims and Guidance as established
by DSHEA
Three Categories of Claims Allowed for Dietary Supplements (24):
Health Claims Describe the connection between a nutrient or food substance and a disease or health
related condition. FDA reviews scientific evidence or statements from authoritative
scientific bodies before approving health claims.
Nutrient Content
Claims
Describe the level of a nutrient in a food or dietary supplement.
Structure/function
Claims
Describe the role of a nutrient or dietary supplement intended to affect the structure
or function of the body, the mechanism of how it maintains that structure or
function, or general well being. FDA does not pre-approve structure/function claims
so they must include the disclaimer “This statement has not been evaluated by the
Food and Drug Administration. This product is not intended to diagnose, treat, cure,
or prevent any disease.” Structure/function claims must be substantiated with
“competent and reliable scientific evidence”.
199
Health Risks of Herbal Supplements
Critics of DSHEA argue that herbal supplements suffer from the same safety concerns
that existed when pharmaceutical medicines were first developed; that a lack of
standardization and quality control poses risk to the integrity of the product and consumer
safety. In fiscal year 2011, FDA records indicate that 1,777 mandatory adverse event
reports were submitted from the dietary supplement industry (25), while US Poison
Control Centers recorded 29,000 calls regarding use of dietary supplements in 2009, with
500 related to moderate to severe events (26). Potential safety risks posed by dietary
supplements may be mitigated by evidence-based patient education provided by RDs.
Herbal Supplements, Medical Practice, and the role of the RD
Significant numbers of Americans do not share information regarding use of dietary
supplements with their health care team; one study suggested that 70% of patients
surveyed failed to disclose their use of herbal medicine during preoperative assessment
(27). Failure to communicate with health professionals regarding use of dietary
supplements may result in unidentified adverse interactions between prescribed
medication, over-the-counter medication, foods, and supplements. As distinctions
between fortified foods, functional foods, medical foods and dietary supplements
continue to narrow, the need for patient education becomes more important. RDs
routinely evaluate the use of dietary supplements within a comprehensive nutrition
assessment, and should integrate education and counseling on supplements into their
nutrition practices.
200
The Academy of Nutrition and Dietetics describe RDs as “consumers’ bridge
between evidence-based research and optimal health” (28). The Academy’s Position
Paper on Functional Foods states that RDs should incorporate functional food
assessment into evidence-based nutrition practice.
RD knowledge of DSHEA provides a strong background for answering legislative
questions on herbal and other dietary supplements.
RDs should provide patient education and report (MedWatch) any potential
interactions between herbal supplements and prescription drugs.
RDs already examine interrelationships between food, functional foods, and
prescribed drugs on nutrition outcomes. Assessing effects of herbal supplements,
either on promoting or managing nutritional health, is an appropriate extension of
that role.
Conclusion:
Individuals with cancer and/or diabetes commonly consume dietary supplements. Some
have demonstrated efficacy in nutritional therapy, others do not, and still others may be
associated with adverse health consequences. The unique knowledge and skill set of the
RD positions her/him as a provider of assessment and education on evidence-based
information on benefits, risks and potential interactions between dietary supplements,
food, and prescription as well as non-prescription medicines. Tables 2 and 3 summarize
201
current evidence of select supplements commonly used for the prevention and/or
treatment of cancer and diabetes.
202
Table 2: Evidence of Efficacy of Select Herbal Supplements used by Cancer Survivors Agent
Reported Benefits/Side
Effects
Evidence RD Message
Black Cohosh
(Cimmicifua
Racemosa):
Rhizome and roots used
in herbal treatments;
Remifemin®, a
commercial preparation
of black cohosh,
provides 10 mg
root/rhizome per tablet.
Reported Benefits: Suppress hot flashes in
menopausal women;
cancer treatment
Potential Side Effects: May be toxic to the liver
(29); may interfere with
some cancer treatments
Meta-analysis concludes that evidence is
insufficient for recommending black
cohosh as a treatment for menopausal
symptoms (30).
In a six month study, black cohosh was
more effective than fluoxetine for treating
hot flushes and night sweats associated
with menopause (31)
German Commission E has found black
cohosh to be effective at treating nervous
symptoms associated with menopause (32)
No evidence suggests black cohosh may be
effective as an anticancer treatment, but it
may interfere with conventional cancer
treatments including tamoxifen (33), and
may increase toxic effects of doxorubicin
and docetaxel (34).
Some studies suggest that Black Cohosh
may reduce menopausal symptoms, but
the body of evidence does not support its
use.
No evidence supports efficacy in cancer
treatment, and black cohosh may
interfere with some conventional cancer
treatments as well as atorvastatin
azathioprine, and ctclosporine.
Garlic:
Perennial bulb used in
cooking and as an
herbal treatment
Reported Cancer
Benefit: Garlic may
stimulate apoptosis and
control the cell cycle
Potential Side Effects: May interfere with
function of some
prescription drugs,
including saquinavir and
antiplatelet medications
200 milligrams (mg) synthetic allitridum
and 100 micrograms (mcg) selenium given
every other day reduced risk for all tumors
by 33% and risk of stomach cancer by 52%
as compared to placebo (35).
Ajoene, a compound found in crushed
garlic, stimulated apoptosis in
promyeloleukemic cells (36).
Allyl sulfides, which comprise 94% of
compounds in garlic, may promote
apoptosis, cell cycle arrest, and inhibit
growth of tumor cells (19).
Garlic contains compounds that show
potential as anti-cancer treatments.
However, evidence is insufficient for
recommending garlic supplements for
cancer treatment. Garlic may interfere
with the activity of some medications, in
particular anticoagulant drugs.
The World Health Organization (WHO)
describes an average daily dose of garlic
as 1-5 grams fresh garlic; 0.4-1.2 grams
(g) dried powder; 205 mg garlic oil, and
300-1000 mg garlic extract (37).
Ginger (Zingiber
officinale):
Rhizome is used as an
Reported Cancer
Benefit: Manage nausea
associated with
0.5-1.0 g ginger/day significantly reduced
severity of acute chemotherapy-induced
nausea in adult cancer patients (38).
Some but not all studies suggest that
ginger may reduce nausea and vomiting
associated with chemotherapy. However,
203
herbal treatment.
chemotherapy
Potential Side Effects: GI complaints reported
with powdered ginger;
may prolong effect
platelet activity
1.0-2.0 g ginger daily for 3 days, given with
antiemetic medicine, did not reduce the
prevalence or severity of acute or delayed
nausea (39).
evidence is insufficient for
recommending ginger supplements for
anti-emetic treatment.
Ginger may interfere with the activity of
some medications, in particular
anticoagulant drugs.
Gingko Biloba:
Seeds and leaves are
used in herbal
treatments.
Reported Cancer
Benefit: May inhibit
proliferation of cancer
cells
Potential Side Effects:
Side effects are
uncommon; may
potentiate effects of
monoamine oxidase
inhibitors (MAO-I),
anticoagulants, and anti-
platelets
Gingko Evaluation of Memory (GEM)
study found that those who received gingko
(as opposed to a placebo) were not less
likely to develop cancer over a 6-year
period (40).
Treatment of pancreatic cell lines with
70uM kaempferol (an active component of
gingko) for 4 days significantly inhibited
cell proliferation.
Combining kaempferol with 5-fU increased
the inhibitory effect on cell growth (41).
Cell studies suggest that researchers
should explore the anticancer potential
of gingko but at this time evidence is
insufficient for recommending gingko
for cancer treatment
Gingko may interfere with the activity of
some medications, in particular
anticoagulant and anticonvulsant drugs
and MAO-I inhibitors.
St. John’s Wort
(Hypericum
perforatum):
Bush that blooms
around June 24th
, the
birthday of St. John the
Baptist. Yellow flowers
from this bush are used
as herbal remedies.
Reported Cancer
Benefit:
May make caner cells
more sensitive to light
therapies
Potential Side Effects:
May interact with many
medications including
irinotecan, imatinib, and
immunosuppressant
medication.
In VITamins And Lifestyle cohort (VITAL
study) use of St. John’s Wort was inversely
associated with risk of colorectal cancer
(42).
Cell and animal studies suggest that St.
John’s wort may make cancer cells more
sensitive to light therapies, and therefore
may have potential to improve anti-cancer
effects of photodynamic therapy (43).
Most studies do not suggest a role for St.
John’s wort in cancer treatment, and this
herb may interfere with the activity of
some chemotherapy agents.
Curcumin (cucurma
longa):
Found in turmeric; the
rhizome is used in
herbal treatments.
Reported Cancer
Benefit: May inhibit
growth of cancer cells;
has anti-inflammatory
properties
Potential Side Effects:
May interact with
Inhibits growth of esophageal cancer cells
in vitro, (44-45) and modulates signaling
factors that decrease cell proliferation of
prostate cancer cells (46).
4 grams of curcumin daily for 30 days is
commonly used in clinical trials.
8,000 mg/day was maximal tolerated dose
Emerging research suggests that
curcumin should undergo further study
for anticancer effects, but at this time
evidence is insufficient for
recommending curcurmin for cancer
treatment
Curcumin may interfere with the activity
204
cyclophosphamide and
doxorubicin; also may
interact with medicines
used to manage blood
coagulation.
in Phase I trial for advanced and metastatic
breast cancer Some biological and clinical
responses were seen, but many patients
dropped out because of side effects (47).
of some anticancer medications.
The bioavailability of curcumin is poor,
which increases pill burden and potential
for side effects.
205
Table 3. Evidence of Efficacy of Select Herbal Supplements used by Patients with Diabetes
Agent
Reported
Benefit /
Concern
Evidence RD Message
Fenugreek
(Trigonella
foenugraecum):
Most research studies
administer fenugreek
seed powders.
Glycemic
control
10 grams (g)/day to 100 g/day results in significant
reductions in fasting blood glucose (FBG) in Type 2
Diabetes Mellitus (T2DM) (48) and Type 1 Diabetes
Mellitus (T1DM) patients (49).
May also reduce FBG and hemoglobin A1C
(HbA1C) when taken with a sulfonylurea (50).
No impact on postprandial glucose values compared
to placebo conditions (51).
Study designs and dosages have been
inconsistent. The effectiveness of
fenugreek supplementation in glycemic
control is still questionable. Further,
fenugreek may interact with
anticoagulants and MAOIs.
American Ginseng
(Panax
quinquefolius):
Dried roots of
ginseng plants are
used in herbal
supplements.
Glycemic
control, insulin
secretion
3g dosage reduced FBG and HbA1C (52) and
postprandial glucose in T2DM patients (53). Higher
dosages demonstrated no further benefit (53).
In vitro studies indicate that American ginseng
stimulates insulin production and reduces pancreatic
beta cell apoptosis (15), though human studies
demonstrate no change in fasting insulin values with
American ginseng supplementation (52).
Research results are limited by small
sample sizes (n=9-24), though preliminary
evidence suggests that American ginseng
may play a role in glucose metabolism.
Delayed onset of hypoglycemia may be a
side effect of American ginseng, so blood
glucose should be monitored closely.
American ginseng may interact with
warfarin, MAOIs, estrogens, nifedipine,
and loop diuretics..
Cinnamon
(Cinnamomum
aromaticum):
A common spice used
in culturally diverse
cuisines, cinnamon is
typically
administered as an
encapsulated powder.
Glycemic
control
1-6 g/daily intake of cinnamon capsules significantly
reduced FBG (54), while 1 g/daily reduced HbA1C
by 0.83% (55) in T2DM patients.
Other research has shown no effect of cinnamon
supplementation on HbA1C, FBG, or insulin
sensitivity in T2DM patients (56-57).
A Cochrane systematic review and meta-analysis,
which included a total of 577 participants, found no
overall benefit of cinnamon supplementation on
diabetes endpoints (58).
Collectively, it appears that cinnamon
likely has no substantial effect on
glycemic control. In addition, cinnamon is
high in coumarin, which may cause
hepatotoxicity in patients with liver
disease.
206
Prickly Pear Cactus
(Opuntia
streptocantha or
Opuntia ficus
indica):
A common foodstuff
in Arizona and
Mexico. Prickly pear
is typically consumed
as a dehydrated
extract or by broiling
the stems of the
young plant.
Glycemic
control
Preliminary trials indicate that the stems, but no other
part of the plant, may have hypoglycemic effects (59-
61).
All results are limited by study sample
size (n=8-32), and the only studies of
prickly pear and hypoglycemia in humans
were performed over two decades ago.
Prickly pear is likely safe when consumed
orally as a food.
Oat Bran:
High in fiber, and
commonly used for
treating
hypercholesterolemia.
Usually consumed as
oat bran flour.
Glycemic
control
(postprandial
and 24-hour)
Studies in T2DM patients indicate that long term and
acute oat bran flour consumption reduces
postprandial glucose (18,62-63).
Oat bran is not approved by the German
Commission E for diabetes treatment,
though it has Generally Recognized as
Safe (GRAS) status in the United States.
Chromium:
Essential in
carbohydrate and
lipid metabolism.
Brewer’s Yeast is
commonly used as a
chromium
supplement.
Glycemic
control
40 to 1000 micrograms (μg) daily supplementation
results in reductions in HbA1C, FBG, and
postprandial glucose in T2DM patients (64,20,65).
T2DM patients with well-controlled diabetes due to
oral hypoglycemic agents do not benefit from 400
μg/day chromium supplementation (66).
Studies examining effects of chromium on
glucose control have been somewhat
limited by sample size (n=3-180), so
conclusive results are difficult to draw.
Chromium supplements have not provided
added benefit when glucose control is
already well controlled with oral
hypoglycemic agents. Use of chromium
supplements (up to 1000 μg/day) have
been found to be safe when used short
term (up to 6 months of supplementation).
207
Magnesium (Mg2+
):
Essential cofactor in
enzymes/proteins
involved in glucose
metabolism,
including the insulin
receptor. Typically
administered as
MgCl2 liquid
solution.
Insulin
sensitivity,
glycemic
control
A meta-analysis including over 536,000 prospective
cohort study participants suggests an inverse
relationship between risk of T2DM development and
Mg2+
intake (67). A dose-response analysis resulted
in a 14% reduction in risk of developing T2DM with
100 milligrams (mg)/day incremental increases in
Mg2+ intake (67).
Some studies suggest that Mg2+
supplementation can
reduce FBG and improve insulin sensitivity (16,68),
whereas others show no effect (69-70).
Higher Mg2+
intake may reduce risk of
developing T2DM, though study sample
size limits the ability to draw conclusions
regarding glycemic control once diabetes
has developed. However, Mg2+
supplementation is likely safe at doses
below the tolerable upper limit of 350
mg/day.
Selenium:
An essential cofactor
in glutathione
peroxidases.
Typically
administered as
selenized yeast.
Increased risk
of developing
T2DM
Epidemiological evidence suggests that higher serum
selenium values are associated with an increased risk
of T2DM (71).
Results from a large clinical trial suggest indicate an
increased risk of developing T2DM in those
randomized to consume 200 μg selenium/day for 7.7
years compared to those in the placebo group (72).
Unless advised by an MD or an RD,
supplements providing more than the DRI
of 55 μg of selenium should be avoided.
Alpha-Lipoic Acid
(ALA):
A cofactor of many
insulin sensitizing
and glucose
metabolism enzymes.
Administered as a
capsule.
Insulin
senstivity,
peripheral
neuropathy
300 to 1800 mg of daily ALA supplementation for
four weeks improves insulin sensitivity in T2DM
patients (73-74,14).
Improvements in symptoms of peripheral neuropathy
including burning, pain, and numbness of the feet and
legs is observed after 3 weeks of 600 mg/daily ALA
supplementation (75-76).
600 mg/daily supplementation is safe and reduces
progression of neuropathy in diabetic patients (77).
Evidence suggests that ALA may improve
insulin sensitivity and reduce progression
of peripheral neuropathy, long and short
term. Patients wit T2DM should consult a
medical professional regarding use of this
product. However, ALA is expensive, and
Vitamin E produces similar results as an
antioxidant at reduced cost.
Coenzyme Q10
(CoQ):
Increased risk
of developing
T2DM
Some studies show reductions in HbA1C in
individuals with T2DM who consume 200 mg CoQ
for 12 weeks (78-79).
Study providing 200 mg CoQ for 12 weeks found no
effect on HbA1C or any other diabetes-associated
outcomes (80).
Few studies have tested the role of CoQ in
parameters associated with diabetes
outcomes, though it is used in patients
with neurological disorders, heart failure,
hypertension, and in those taking statins.
There is insufficient data to make a
recommendation for the supplementation
of CoQ in diabetics seeking HbA1C
reduction.
208
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