University of Arkansas, Fayetteville
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Theses and Dissertations
5-2017
The Effect of Omega-3 Fatty Acids on Energy
Metabolism, Energy Intake, and Metabolic
Response in Normal Weight and Overweight and
Obese School Aged Children (8-12 years)
Charlayne Mitchell
University of Arkansas, Fayetteville
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Weight and Overweight and Obese School Aged Children (8-12 years)" (2017). Theses and Dissertations. 2008.
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The Effect of Omega-3 Fatty Acids on Energy Metabolism, Energy Intake, and Metabolic
Response in Normal Weight and Overweight and Obese School Aged Children (8-12 years)
A thesis submitted in partial fulfillment
of the requirement for the degree of
Master of Science in Human Environmental Sciences
by
Charlayne Mitchell
University of Arkansas
Bachelor of Science in Human Environmental Sciences, 2006
May 2017
University of Arkansas
This thesis is approved for recommendation to the Graduate Council
Dr. Jamie I Baum
Thesis Director
Dr. Sun-Ok Lee
Committee Member
Dr. Sabrina Trudo
Committee Member
Dr. Stavros Kavouras
Committee Member
Abstract
Background: Obesity is a major health concern in the United States. Omega-3 fatty acids
(O3FA) have been observed to improve metabolic health and therefore might be useful in
treatment of obesity. However, little is known regarding the effect of O3FA on school aged
normal weight and overweight children.
Objective: The objective of this thesis was to determine if habitual intake of O3FA at
breakfast improves energy metabolism, appetite, and metabolic response in overweight and
obese school-aged children.
Design: Twenty healthy, normal weight (NW; n = 11) and overweight (OW; n = 9)
children aged 8-12 years were randomly assigned to receive either a vegetable oil based
(Control) breakfast drink or a O3FA based breakfast based drink to observe postprandial effects
of each treatment. Anthropometrics, appetite, resting energy expenditure (REE), substrate
oxidation, and food intake were evaluated for each treatment.
Results: Body weight (P < 0.001), and BMI percentile (P < 0.001) were higher in the
OW group. Fat mass and free fat mass were higher in the OW group (P < 0.001) and (P < 0.05),
respectively. There was an effect of breakfast type (P < 0.05) on carbohydrate oxidation after
O3FA consumption. There was an effect of time and body weight on hunger (P < 0.001). There
was also an effect of breakfast over time on feelings of fullness (P < 0.05). There was no
difference in leptin or adiponectin in response to breakfast. There was no statistical significance
of total food (kcal) intake in Control or O3FA
Conclusion: Taken together, these data suggest that increasing O3FA in the diets of schoolaged children may have beneficial effects on EE, satiety, and metabolic responses throughout the
day.
Acknowledgement
I would like to express a special recognition and appreciation to my advisor, Dr. Jamie I. Baum,
who has provided her support, mentorship, and guidance over the last two years. I can say
without her persistence and guidance I would not be where I am as a graduate student,
academically, or professionally.
I would also like to thank Sarah Russell, Stephanie Shouse, Hexirui Wu, Aubree Worden,
and Eva Dehane. All, whom this thesis would have been impossible to achieve without their
dedication, effort, and most of all friendship. Additionally, I would like to thank my committee
members for insight, guidance, and candid feedback through my Master’s program.
Lastly, I would like to thank my husband and support structure, André Mitchell, my
children, AJ, Halle, and Hezekiah, whom laid beside me on the couch as I worked through the
night, my parents, and grandmother (Big Momma) for instilling in me that anything not working
hard for is worth having during my two years at the University of Arkansas.
Dedication
This thesis is dedicated to my husband, André Mitchell, children, AJ, Halle, and
Hezekiah, my parents, Charles and Elaine, and grandmother Lou Della as without them I would
not be who I am or where I am today.
Table of Contents
Introduction………………………………………………………………………………………..1
Literature Review………………...……………………………………………………….…..…...3
Childhood Obesity……...………………………………………………………………....3
Contributors to Childhood Obesity………………………………………………..…........3
Obesity Link to Chronic Diseases………….………………………………………...........4
Energy Metabolism and Energy Expenditure…………………………………………......6
Importance of Breakast………………………………………….………………….……..7
Omega-3 Fatty Acids………………………………………………………………….…..9
Materials and Methods ………………………………………………..…………..………….….16
Participant Characteristics…………………...…………………………………………..16
Study Design……………………………………………………………………………..17
Test Breakfast………………………………………………………………………...….18
Anthropedmetric Measurements…………………………………………………………18
Satiety Hormone Measurements…………………………………………………………18
Energy Expenditure and Substrate Oxidation………………………………………...….19
Appetitite and Palatability Measurement……………………………………..………….19
Dietary Assessment………………………………………………………………………20
Statistical Analysis………………………………………………………..…………..….21
Results…….………………………………………………………………………………….…..23
Discussion………………………………………………………………………………………..25
Conclusion…………………………………………………………………………………….…28
References…………………………………………………………………………………..........29
Tables and Figures………………………………………………………………...………….….48
Appendix A……………………………………………………………………………………....57
Introduction
In the United States rates of childhood obesity have doubled from ~7% to 17.2% in the
last thirty years [15, 16]. Moreover, in Arkansas, childhood obesity rates are 14.4% in children
aged 2-4 and 20 % in children aged 10-17 [17]. Obesity is associated with body mass index
(BMI). The BMI of children is calculated in percentiles based on height and weight in
comparison with other children with in their same sex and age group (<85th percentile, normal
weight; >85th percentile, <95th percentile, overweight; and ≥95th percentile, obese). With this
increase obesity comes health consequences such as, cardiovascular (dyslipidemia), and
endocrine (type 2 diabetes mellitus (T2DM) disorders [24].
Obesity is a metabolic disorder with multiple contributors. Factors such as genetics [25],
environment [26], and energy balance (energy intake versus energy expenditure) are among the
contributors to the prevalence of obesity [27, 28]. However, when there is a constant state of
energy imbalance, e.g. energy intake exceeds energy expended, weight gain and/or obesity may
occur [30]. The concept of energy balance has been the focus of obesity research for decades
[31] with a specific focus on decreasing energy intake and increasing energy expenditure (EE) in
order to enhance weight loss [32]. Whole body EE has three primary components; resting energy
expenditure (REE), the energy needed to maintain bodily functions at rest; the thermogenic
effect of feeding (TEF), the energy increase associated with digestion and absorption of
macronutrients; and activity induced thermogenesis, energy associated with physical activity [29,
33]. Thermogenic effect of feeding is unique because it can change with dietary macronutrient
composition making it an ideal target for obesity treatment and/or prevention
Diets higher in dietary fats, have proven to be successful strategies to improve metabolic
health disorders associated with obesity [38]. In addition, O3FA supplementation has been
1
shown to sustain appetite reduction, resulting in increased satiation and a subsequent decrease in
food intake [14]. Ebrahimi et al [39], conducted a six-month interevention where individuals
were provided O3FA capsules that contained 180mg eicosapentaenoic acid (EPA) and 120mg
docosahexaenoic acid (DHA) per day for six months resulting increased weight loss (2.63 kg or
3.8% body weight) compared to a control group who had the same protocols, but were not given
supplementation. Taken together, data suggests that supplementation of O3FA could be an
effective interevention and treatment for obesity [36, 41-49].
Breakfast has been suggested to be the most important meal of the day [4-7, 50, 51].
However, according to 47 observational review studies within the United States and Europe,
breakfast skipping has been a frequent lifestyle behavior and 10%-30% of children and
adolescents do not consume breakfast [52]. Consequently, breakfast skipping is linked to obesity
due to it having a strong correlation with overeating at subsequent meals [57, 58]. Recent
research has found that there is a positive effect on satiety of breakfast type with increased
dietary fat at breakfast [59-64]. However, more research is needed to define what a quality
breakfast consists of to the guide optimal macronutrient composition of breakfast, which may
lead to a strategy to decrease the prevalence of obesity.
Therefore, the objective of this thesis was to determine if habitual intake of O3FA at
breakfast improves energy metabolism, appetite, and metabolic response in overweight and
obese school-aged children. We hypothesized that increasing O3FA intake at breakfast would
improve energy metabolism and reduce energy intake throughout the day in overweight/obese
school aged children.
2
Literature Review
Childhood Obesity
Childhood obesity has become the number one health concern to parents in the United
States [71]. The prevalence of obesity in youth aged 2-19 years has doubled over the last 30
years [72]. Arkansas is currently ranked 6th in adult obesity and 6th in childhood obesity [73].
Obesity is more likely to occur in children between the ages of 5 and 14 years [74]. Obese
individuals have an increased risk for developing chronic diseases such as type 2 diabetes,
hypertension, dyslipidemia and nonalcoholic fatty liver disease [75]. Once restricted to adults,
these diseases are now being diagnosed in children [75]. A population sample survey conducted
by the Centers for Disease Control and Prevention showed that 70% of children between the ages
of 5-17 years had at least one risk factor of cardiovascular disease [76]. In addition, children who
are obese are more likely to be obese in adulthood [72]. There are several nutritional behaviors
that contribute to obesity such as high intakes of energy dense, nutrient poor foods and diets rich
in fats that do not offer a varied meal composition or satiation [77, 78]. With the increase in the
prevalence of obesity and the morbidity attached to it, there is a need to not just treat the
symptom, but to find the cause so that preventative measures can be taken.
Contributors to Childhood Obesity
The development of childhood obesity has multiple contributing factors, such as
environment, genetics, and lifestyle behaviors [74, 79-81]. Increased energy intake has been
identified as playing the largest functional role in obesity [29, 82-86] and has been attributed to
environmental changes such as increased portion size, increased energy dense convenient foods,
and decreased physical activity [84, 86]. Rolls et al [84] showed that a 50% increase in portion
sizes can sustain increased energy intake for up to 11 days, resulting in increased intake of 423
3
kcal in excess over the daily recommended value [84]. Consistent findings by French et al [82]
showed that when individuals are provided a meal with increased portion size, energy intake will
increase overtime when compared with individuals provided meals with smaller portions [82].
Although these studies were conducted in adults they provide evidence that environments that
when larger meal portions are provided, energy intake will increase overtime [87]. Behaviors,
such an increased intake of energy dense convenient foods can modulate the development of
obesity. Researchers observed over three shopping occasion where a total of 399 products were
purchased that over half of the product’s audience were targeted to children, two-thirds fit into
five categories: cereal, fruit snacks, meal products, frozen desserts, and candy [88]. Thus, most
of the products marketed as healthy, however fell into the low nutritional value category.
Additionally, physical activity has decreased and sedentary behavior has increased. For example,
recent data demonstrates that sedentary behavior is linked to T2DM and cardiovascular disease
[89]. The increase in technological advances (e.g. video games and smart phone) has also been
associated childhood obesity [90]. In a nationally representative survey, Kann et al [91] observed
that 77% of children 9-13 years of age reported participating in physical activity, however as
they enter high school only 29% report to participate in any physical activity.
Obesity Link to Chronic Diseases
Obesity is linked to serious health consequences and independently increases the risk of
developing chronic diseases such as type 2 diabetes, heart disease, stroke, and certain types of
cancer [1, 92]. Moreover, these metabolic disorders once only associated with adults now are
being diagnosed in children. Diabetes mellitus is characterized as a disease that prevents the
human body from efficiently utilizing glucose for energy [93]. Currently, type 2 diabetes
(T2DM) accounts for ninety to ninety-five percent of cases of diabetes diagnosed [94]. T2DM is
4
a common metabolic disorder, whereas in the past it has been associated with the aging
population it is now a common diagnosis in overweight and obese individuals [89, 95-97]. There
is also an increased incidence of children being diagnosed with T2DM in the United States [98,
99]. The increase in the incidence of T2DM was first observed in children and adolescents in
minority groups, such as Pima Indians in Arizona [100]. Within the Pima Indian population the
frequency of the disease was 22.3:1000 in children and adolescents 10-14, and 51:1000 in
adolescents 15-19 years of age [100]. T2DM also increases the risk of developing other chronic
diseases, such as heart disease [101].
Coronary heart disease is the primary form of heart disease and is one of the leading
causes of death in the United States [102, 103]. Recent research has shown that individuals with
a higher BMI have an increased risk for developing heart disease [104]. In addition, previous
research revealed that individuals with a higher BMI not only had an association with heart
disease, but having a higher BMI could be a predictor of heart disease [105-107]. Obesity has
been linked to heart disease and Kang et al [104] provided evidence that individuals with higher
BMI showed signs of coronary syndrome. Research has also shown that overweight or obese
children have an increased risk of developing diseases such as high blood pressure and high
cholesterol which increase the risk of developing heart disease [108]. In addition, several studies
have revealed that childhood obesity is associated with early onset of type I lesions in the artery
walls, which are a precursor to the advancement of coronary atherosclerosis [109-113].
Nutrition interventions are an inexpensive method for treating and/or preventing chronic
diseases associated with obesity [114-116]. For example, research observed that changing the
macronutrient distribution in the diet (e.g. the ratio of protein, carbohydrate and fat), resulted in
successfully decreasing food intake and increased EE, likely due to the satiating effect of
5
supplementation of O3FA [117]. Decreasing food intake is directly related to health status; over
consumption of energy dense foods result in weight gain, increasing the risk for metabolic
related diseases, such as T2DM, and cardiovascular disease [101, 118]. In addition, increasing
EE is a mechanism for decreasing weight gain and regulating energy balance [30, 119].
Furthermore, the satiating effects of O3FA have also been observed [14]. The result of one study
showed that the supplementation of O3FA in men and women aged 20-41 years over an eight
week period randomized to either sunflower oil capsules, lean fish 150 g portion of cod 3 times
per week , fatty fish 150 g portion of salmon 3 times per week, and, fish oil capsules
(DHA/EPA) observed a significant decrease in body weight with O3FA intake (.45 times loss
from baseline to midpoint), suggesting that diets with O3FA result in weight loss may be
associated with increased satiety [120]. Taken together, this suggests that nutrition interventions
at breakfast could be a potential preventative and treatment strategy.
Energy Metabolism and Energy Expenditure
Increasing energy expenditure through macronutrient composition is a well-established
method to decrease fat mass [33, 35, 121-124]. Total body EE has three primary components;
resting energy expenditure (REE), the energy needed to maintain bodily functions at rest; the
thermic effect of feeding (TEF), the energy increase associated with digestion and absorption of
macronutrients; and activity induce thermogenesis, energy associated with physical activity [29,
33]. REE represents 60% - 70% of whole body EE and is the component of EE that represents
energy produced for the body to function at rest. Experts have linked body composition as being
a major factor that determines REE and have found a disproportionally large span of kcal/d per
individual [29]. AEE is the second largest component of EE, costing the body 20%- 30% of
energy expended through physical activity (PA), and has the most variability of the three
6
measurements of energy expenditure [29]. The increase of metabolic rate after food consumption
is the component of energy expenditure where the energy expended to breakdown food during
thermic effect of food (TEF) [125].
Several studies have shown a relationship between the regulation of energy balance and
obesity [126-128]. The regulation of energy balance is dependent upon calories consumed and is
influenced by macronutrient composition [125]. TEF is considered one of the smaller
components of energy expenditure, but could play a large role in the energy balance and assist in
fighting obesity [129]. Maffeis et al [130] reported that the role of TEF and nutrient composition
especially high fat intake in children may lower postprandial thermogenesis than a diet
isoenergetic, isoproteic and lower in fat.
Dietary fat has been viewed as a contributor to obesity and not as treatment or
preventative mechanism for obesity. Moreover, literature provides evidence that meal
composition is a major contributor to metabolic homeostasis [131-133]. Thus, indicating that
may be the fat source should be examined versus fat alone. Energy imbalance results in multimetabolic dysfunctions, however O3FA’s have shown the reversal effects in health status, such
as increased energy expenditure, subsequently inducing weight loss [134]. Logan et al [135]
demonstrated that the supplementation of 3 g/d of O3FA over a 12 week intervention
significantly increased REE by 14%. Therefore, supporting that consumption of O3FA may be a
strategy to decrease fat mass. Previous and recent studies provide evidence that increased EE
through modulating macronutrients at breakfast is an effective strategy prevent and treat obesity
[4, 35, 136, 137]. However, there is a gap in knowledge in the effects of O3FA on EE in relation
to school-aged children.
The Importance of Breakfast
7
The benefits of breakfast consumption have been extensively studied [6, 7, 136, 138],
especially breakfasts higher in protein [35, 44, 53, 58, 139]. Breakfast has been defined across
literature as being the first meal of the day consumed prior to 10:00 am [138]. In the literature,
breakfast skipping has been defined as missing the breakfast meal more than five more times per
week [138]. Eating habits such as breakfast skipping are also associated with diet quality [55,
140]. There is a negative association between breakfast skipping, the nutrient quality of the meal,
and energy intake throughout the day [4, 35, 36, 44, 53, 58, 68, 69, 136, 141-144]. Data shows
that children who do not regularly consume breakfast do not meet two-thirds of the
recommended dietary allowance (RDA) for vitamins A, E, D, and minerals calcium, phosphorus,
magnesium and riboflavin [5]. Affenito et al [145] observed the eating behaviors of 2,379 girls
aged 9-19 and found that as the frequency in breakfast consumption decreased there was a
reduction in calcium and fiber intake.
Childhood is a crucial period in life that requires adequate nutrition. A review of
literature by Affenito et al [7] revealed that breakfast is a missed opportunity and between 1030% of American’s and Europeans skip breakfast, particularly children aged 1-10 years and
adolescents aged 11-18 years [7]. Moreover, there is an association between breakfast skipping
and obesity [57, 146-148]. Literature has shown a correlation between increased BMI in
individuals who skip breakfast compared with those who regularly consume breakfast [65, 66,
68, 149, 150], and this is a trend that continues through adulthood [56, 148, 151]. In addition,
studies have shown that girls skip breakfast more often than boys, typically as means of weight
loss [150, 152]. However, girls who skip breakfast are 15% more likely to be overweight or
obese [149].
8
Breakfast intake has been observed to improve cognitive thinking and academic
performance in children [150, 153]. Breakfast consumption is also associated with improved
appetite response [44, 70, 139]. Leidy et al [44] conducted a study in breakfast skipping
adolescents and found that breakfast intake increased the feeling of fullness compared with
breakfast skipping. This observation is further supported throughout literature [5, 68, 70, 151,
154]. A review by McCrory et al [155] summarized similar findings from three acute studies
(less than one day) where breakfast consumption increased the feeling of fullness and decreased
energy intake (EI). In longer-term studies (more than seven days), Leidy et al [139] found that
the intake of breakfast increased the feeling of fullness compared to 7 days of breakfast skipping.
Data has also shown that regularly consuming breakfast could be a successful strategy for
improving metabolic health. Frid et al [54] observed in fourteen adults diagnosed with T2DM
that meals supplemented with whey protein at breakfast or lunch increased insulin response and
blood glucose reduced by -21%. Additionally, one study showed that the intake of breakfast has
an acute response on appetite control resulting in reduced energy intake [139]
Macronutrient intake at breakfast is correlated with health status [132, 156, 157]. It is
well established that omega-3 fatty acids (O3FA) decrease the risk of heart disease and improve
brain development in children. Moreover, there is recent evidence suggesting that diets with
omega-3 fatty acids (O3FA) supplementation may be a possible treatment for metabolic
disorders such as obesity [39, 46, 158, 159]. In addition, there is still a gap in the scientific
literature regarding the role of O3FA supplementation in children.
Omega- 3 Fatty Acids
In previous years, diets high in fat have been suggested to increase chronic disease and
risk of obesity in individuals [160-162]. However, the Dietary Guidelines for Americans 2015-
9
2020 [163], suggest that not all fats should be avoided, with the exception of trans and saturated
fats. Trans and saturated fats are linked to metabolic disorders, such CVD, high cholesterol,
coronary heart disease, T2DM, and high blood pressure [161, 164, 165].Willet et al [166] suggest
in a review of short- and long-term studies that fat intake and obesity are not directly correlated.
A review of the short term studies revealed a trend of modest weight reduction on a low fat diets
and in longer term studies of a year or more there was a daily fat consumption between 18-40,
which is suggested to have little effect on adiposity [166].
Fatty acids play an important role as metabolic substrates, involved in fat metabolism,
and increasing lipogenesis a process mainly in the adipose tissue where the body converts excess
glucose into fatty acids [167]. Polyunsaturated fats (PUFAs) are a classification of O3FA, and
are described as an essential fatty acid due to our inability to synthesize them in the body,
therefore they must be obtained through the diet. These fats are typically found in fatty fish (e.g.
salmon) and nuts (e.g. walnuts) [168]. Another benefit of O3FA is the beneficial role they play in
preventing and treating chronic diseases due to their anti-inflammatory properties and
modulation of lipid metabolism [169, 170].
Omega-3 fatty acid supplementation has become of research interest due to its effects on
body fat loss through the mechanisms of adipogenesis, lipid homeostasis, and reduced
inflammation [38, 40, 171]. There is much supported evidence that O3FA are associated with
decreasing the effects of cardiovascular disease (CVD) and that O3FA play an important role in
providing DHA for growth and brain development [172-178]. Less is known regarding the
effects of O3FA in weight loss and management, especially in children.
There are contradicting conclusions regarding fat intake in the literature. For example, a
critical review by Anderson el al [179] describes the negative impact of fats on health, (e.g.
10
CVD, insulin resistance, increased levels of low-density lipoprotein). However, more recent data
suggests the opposite [117, 135, 180, 181] The harmful effects of fat appear to be due to the type
of fat (e.g. trans fat and saturated fat), and not the quantity of fat in the diet [182]. Therefore, the
dietary guidelines have shifted focus regarding recommendations for dietary fat intake, by
recommending an increase in the intake of healthy fats such as monounsaturated fat (O6FA; e.g.
olive oil, avocados, and peanut butter) and polyunsaturated fat (O3FA; e.g. sunflower oil,
salmon, trout, and walnuts), and decreasing the intake of saturated fats (e.g. hydrogenated
vegetable oil and animal fats), in order to help lower the risk of CVD, a leading cause of death in
the United States [163, 182-186]. However, there is recent evidence that reveals the positive
effects on metabolic disorders such as CVD, insulin resistance, vitamin D deficiency associated
with obesity, and non-alcoholic fatty liver disease [38, 47, 158, 187-190].
In a randomized, cross sectional study Maffeis et al [77] observed in ten obese
prepubertal boys that a moderate fat meal (pasta, olive oil, grana cheese, and ice cream with 27%
energy from fat) improved postprandial triglyceride levels. Additionally, providing evidence that
meal composition is important in satiety, a meal with moderate fat reduced appetite, and was
more effective in increasing TEF [77]. A recent study by Logan et al [135], where women > 60
years of age were randomly assigned to either 3 g/d eicosapentaenoic acid (EPA) and
docosahexaenoic acid (DHA) or a placebo (olive oil) for 12 weeks. The diets with O3FA
supplementation increased REE 14%, EE during PA 27%, lowered triglyceride levels by 29%,
and increased lean mass by 4%. This supports previous findings by Gerling et al [117], who
conducted a randomly assigned single-blind were active males were supplemented with 3.0 g/d
EPA and DHA or olive oil for 12 weeks that found O3FA supplementation increased resting
metabolic rate (RMR) and reliance on fat oxidation. However, as described above,, dietary fat is
11
linked to slower gastric emptying which may result in postprandial satiation [191]. Furthermore,
it is argued that the satiating effects of fats be due to a brain-gut connection such as
gastrointestinal hormones secreted from the that control feeding (leptin, a satiety hormone and
ghrelin, a hunger hormone) that circulate in the bloodstream relaying neural signals to the brain
stem [192].
The regulation of fatty acid and triglyceride synthesis plays an important role in
controlling metabolism, which influences energy storage and the development of obesity [193,
194]. There may be a strong association between O3FAs and the regulation of hepatic glucose
output expressed in diabetes and obesity [195, 196]. Extensive reviews by Jump [194, 197]
defined dietary fat as an important essential component in the diet, however dietary fat could
result in energy imbalance and metabolic dysfunctions if consumed in excessive amounts [197].
Obesity is associated with excessive amounts of fat deposit in the tissue [198] Furthermore, diets
high in fat (e.g. trans and saturated) have been shown to increase adiposity or amount of body fat
an individual has compared with lean mass [199, 200]. There is also an associated increase in
serum cholesterol with diets high in fat, which is linked to coronary heart disease [164, 201].
However, there is also evidence that these metabolic diseases can be prevented or treated with
supplementation or consumption of foods high in O3FA [12, 158, 186, 189, 202].
A recent review summarized the effects of O3FA and omega-6 fatty acids (O6FA) and
their ratio on obesity in the human diet; because of the increased intake of O6FA in the Western
diet, changing the ratio from 1:1 to 20:1 or higher increased the prevalence of metabolic
disorders associated with obesity, such CVD [46, 203, 204]. Randomized controlled trials
examining the relationship between O3FA supplementation and health outcomes observed
12
positive changes in body composition, such as weight reduction, although not measured the
weight loss may have been result of the effects of O3FA in appetite regulation.
Consumption of O3FA is also associated with improved appetite response. In an eightweek nutritional intervention by Thorsdottir et al [120], 320 men and women were randomized
to four isocaloric diets; control capsules (6 times/day), cod 150 g (3 times/week), salmon 150 g
(3 times/week), and fish oil capsules (6 times/day). Health outcomes measured included weight
loss (6.5 kg ± 3.3 kg) in men and (4.2 kg ± 2.4 kg) in women. There was a significant interaction
of EI by diet in groups that received diets with O3FA compared to those that received lean fish.
Furthermore, supporting the previous findings, Parra et al [14] examined, in an eight-week
nutritional intervention, how the supplementation of O3FA modulated satiety in overweight and
obese males and females aged 20 – 40. Participants were randomized into four diet types; control
capsules (6 times/day), cod 150 g (3 times/week), salmon 150 g (3 times/week), and fish oil
capsules (6 times/day). At baseline, there was no difference in EI. However, immediately after
consuming the fatty fish group had an immediate feeling of fullness compared with the lean fish,
in addition the fatty fish group had more fullness compared with the lean fish group 2 hours
postprandial. Concluding that O3FA supplementation of 6 fish oil capsules/day or the intake of
150 g of food rich in O3FA could be an effective weight loss strategy modulating postprandial
satiety in overweight and obese individuals. In the same comparison study, correlation analysis
showed significant correlations between circulating hormones leptin, ghrelin, and insulin with
appetite response, a positive effect of O3FA consumption.
Hormones play a key role in appetite regulation [205]. Moreover, leptin is released from
the adipose tissue and is link to satiety [206]. However, the amount of leptin circulating in the
body increases with fat mass [207]. Therefore, overweight and obese individuals have an
13
increased amount of leptin compared to normal weight individuals, however overweight and
obese individuals have a decreased responsiveness to leptin signaling [208]. Leptin acts on the
hypothalamus; however, the hormone response is decreased with obesity and is known as leptin
resistance [209].
Furthermore, Itoh et al [210] provided evidence in a single blind study that parallel to
increased leptin signaling O3FA also increases circulating adiponectin, a hormone secreted from
the adipose tissue. In 52 men and women that satisfied characteristics for metabolic syndrome it
was found after a three-month purified EPA treatment of 1.8 g/day that plasma concentrations of
adiponectin were increased compared to control (e.g. diet alone), in addition there was also a
significant decrease in blood serum triglyceride concentration. Furthermore, these findings in
humans supported previous finds in rodent and rat models where O3FA supplementation
increased leptin [211-213]. Therefore, showing that there is a correlation between obesity and
hormone regulation.
There is also emerging evidence that O3FA assist with muscle protein synthesis [47].
Smith et al [47] provided evidence that there is an interaction between muscle protein and lipid
metabolism. In a study of healthy 25-45-year-old individuals showed an acute response, that with
O3FA supplementation increased muscle protein synthesis [47]. Lastly, the effects of O3FA in
insulin resistance has also proved positive [214]. Farsi et al [215] observed improved insulin
sensitivity in a randomized study of four-forty T2DM participants after a 4 g/day
supplementation of O3FA in gel capsule form over a 10-week period. In addition, supporting
these finding Albert et al [216] assessed red blood cell EPA concentrations twice, 16 weeks apart
found a 45% increase in insulin sensitivity in men who had a high O3FA index compared with
14
those who had a lower O3FA index. Therefore, these findings may further emphasize the
importance of which source of fats are consumed and the health benefits associated with O3FAs.
Positive outcomes from O3FA supplementation and increased protein intake have been
observed in both acute and chronic conditions. Although there is a lack health outcomes with
supplementation at breakfast, is evidence of increased REE, and metabolic health, with similar
findings in protein intake. However, additional information is needed in school-aged children.
Furthermore, data is needed regarding the adaptive response to EE, and appetite hormones leptin
and adiponectin.
Objective and Hypothesis
The objective of this proposed research is to determine if habitual O3FA intake at
breakfast improves energy metabolism in overweight and obese school-aged children. We
hypothesize that increasing O3FA intake at breakfast will improve energy metabolism and
reduce energy intake throughout the day in overweight/obese school aged children.
15
MATERIALS AND METHODS
Participant Characteristics
This protocol was approved by the Institutional Review Board IRB approval # 15-09094) and the Institutional Biosafety Committee (IBC) #16002 at the university of Arkansas.
School age children, 8-12 years whom resided in Northwest Arkansas (Fayetteville, Bentonville,
Rogers, Springdale and surrounding areas) were recruited to participate in this study. The
participants were recruited through a University of Arkansas Newswire advertisement and via
flyers in the Food Science Department building. Only participants who had no known food
allergies, diet restrictions, ate breakfast habitually, were not picky eaters, were females who had
not started menstruation, and did not have any other diet related conditions were recruited to
participate in the study. Written consent was obtained from the legal guardian of the children as
well as written assent obtained from the child to participate in this study. Male and female,
normal weight and overweight/obese subjects were recruited to participate aged 8-12 years.
Upon completion of the study the participants were compensated with $400 cash.
Two screenings were required to participate in the study. The first screening occurred via
phone conversation with the parent or legal guardian of the child to determine if the minimum
qualifications were met. The second screening occurred at the Health, Human, Performance, and
Recreation (HHPR) building and included baseline height, measured to the nearest 0.1cm, and
weight 0.1 kg for weight. The participants were then placed into one of two intervention
classifications: 1) normal weight (NW) with BMI ≤85 percentile for age, sex, and height; or 2)
overweight with BMI ≥85 percentile according to the CDC BMI percentile growth charts ages 219 years [217]. Body composition (fat-free mass and fat mass) was assessed with the use of Dual
Energy X-Ray Absorptiometry (DEXA) (Lunar Prodigy, GE Healthcare).
16
Study Design
The study was a double-blind randomized, crossover design. Each participant in the study
acted as their own control. Subjects were randomly assigned to one of the four treatment groups
(NW control, NW O3FA (n=11), OW control, OW O3FA (n=9)) selected using Excel©,
Microsoft 365 randomizing function to control for treatment type. All participants completed
four study day visits over a six to ten-week period to the Energy Metabolism Laboratory in the
Department of Food Science (refer to Appendix A for an outline of the study day). At each
laboratory visit the participant had anthropometric measurements (height and weight) taken. On
study day one (D1) each participant was randomly assigned to one of two color-coded isocaloric
and macronutrient-matched breakfast beverage drink groups: breakfast beverage #1 omega-3
fatty acids-based or breakfast beverage #2 vegetable oil-based. Participants were given fifteen
minutes to consume their assigned beverage. Following the first test day, each participant
consumed the assigned breakfast beverages before 10AM and prior to consuming any other food
item daily for two weeks. On study day 14 (D14) each participant returned to the Food Science
Department around 7:30 AM in a fasted state to have blood drawn and REE measured. A
minimum of a 7- day washout period occurred between each treatment to attain dietary
adaptation control to eliminate residual diet from previous treatment [218].This protocol was
repeated for the second test beverage. All the breakfast beverages were provided to the
participants throughout the duration of the study. Participants with the guidance of their parents
were asked to complete a 3-day food record and physical activity levels during each week of the
study, consecutive food record days were assigned to the participants to be recorded one-week
day and two weekend days, however this is not standard protocol (two weekdays and one
weekend day) and to correct this error we averaged the three-day food intake over the two-week
17
period per treatment. Day 8 and day 14 of each intervention subjects returned their empty
beverage containers for ensured compliance.
Test Breakfasts
Participants were assigned to one of two breakfast beverages presented in Table 1. All
breakfast beverages were supplied by SmartFish (Oslo, Norway). Participants were provided
containers by our lab and were instructed to shake the beverages to ensure that contents of the
drink that may have separated were well mixed. Participants were instructed to place the straw
that came with beverage into the container to assist with consuming it, then place their lips on the
straw and begin to drink on the count of three so that they were ready to consume the beverage.
At the first sip of the breakfast beverage the four–hour testing period began. The participants
were required to finish the breakfast beverage within fifteen minutes or they were removed from
the study.
Anthropometric Measurements
Body height was measured to the nearest 0.01 cm using a stadiometer (Detecto, St. Louis,
MO) with participants barefoot, in a freestanding position. Body weight was measured in the
fasting state with participants barefoot to the nearest 0.01 kg using a calibrated balance scale
(Detecto, St. Louis, MO. BMI percentile was calculated using CDC Child and Teen calculator,
https://www.cdc.gov/healthyweight/assessing/bmi/childrens_bmi/about_childrens_bmi.html.
Body composition was assessed by dual energy x-ray absorptiometry (DXA; Lunar Prodigy, GE
Healthcare, Belgium) in the Human Performance Laboratory at the University of Arkansas.
Satiety Hormone Measurements
On D1 of each dietary intervention, each participant had three individual blood draws
repeated at time-points baseline (prior to breakfast treatment), 90, and 240 minutes, post
18
consumption of breakfast beverage. Blood collection was conducted by a licensed phlebotomist.
Blood (10ml) was collected using one 10ml BD Vacutainer EDTA, Spray-Dried tubes (Becton,
Dickinson and Company ©, Franklin New Jersey, USA) per time-point where three 10ml tubes
totaling 30 ml of blood per participant D1 of each dietary intervention. Blood was centrifuged at
1,800 x g for 10 minutes at 4°C in an Allegra TM X-22R Centrifuge (Beckman Coulter, Inc.,
Brea, California, USA). Plasma was collected and stored at -80°C. The plasma collected was
used to measure biomarkers of satiety (adiponectin and leptin), using 96 wells enzyme
immunometric assay (EIA) kits, (Caymen Chemicals) and the Biotech Plate Reader (absorbance
read at 450 nm) was used to read the intensity of color within each well to determine the
immunological response of human adiponectin and leptin over time.
Energy Expenditure and Substrate Oxidation
The TrueMax 2400 metabolic cart (Parvomedics, Sandy, Utah) was used to measure resting
energy expenditure (REE) in a supine, reclined position, and used the method of indirect
calorimetry, a non- invasive measurement of metabolic rate in humans with the use of the
ventilation hood technique that uses the heat produced by living organisms by measuring their
production carbon dioxide [35, 219]. D1 REE (kilocalories per minute) was measured at baseline
for 30 minutes [219]. After breakfast treatment consumption REE was measured in 20 minute
increments starting at time-point 60 minutes, which is the first time-point being used after the
breakfast beverage was consumed and to provide time in between each REE measurement so that
the participant was not continuously under the metabolic hood and subsequently at 120, and 240
minutes to assess the thermic effect of feeding (TEF) [122, 220]. Respiratory quotient (RQ), the
ratio of carbon dioxide expelled (VCO2; liters per minute) to oxygen consumption (VO 2; liters per
19
minute) was calculated, providing a parameter of measurement for substrate oxidation rates [219,
221].
Appetite and Palatability Assessment
Appetite and palatability were assessed on D1 of each dietary intervention using visual
analog scale (VAS) questionnaires. The questionnaires asked the participants to rate their
perception at that moment of hunger, fullness, and desire to eat using a 100mm VAS with
opposing anchors such as; not full or extremely full [222, 223]. There were 7 questions asked at
baseline and subsequently at 15, 30, 60, 120, 180, and 240 minutes. Participants were asked to
place an “X” along the line in the order of: “how hungry do you feel at this moment,” “how full
do you feel at this moment,” “how strong is your desire to eat at this moment,” “how much food
could you eat at this moment,” “how strong is your desire for something salty,” “how strong is
your desire for something sweet,” “how strong is your desire for a snack.” Participants were also
asked evaluate palatability, “how much do you like the taste of the drink,” with opposing anchors
“dislike extremely or “like extremely” once they had consumed at least half of the breakfast
beverage on D1.
Dietary Assessment
After the completion day 7 of each treatment participants returned weighed, food records
to the laboratory. Participants were provided blank 24-hour food records and a digital scale with
weight units in grams, ounces, pounds, and milliliters (Amir Direct®, Amazon.com, Seattle,
WA). Participants were given a tutorial on how to record food consumed on their first laboratory
visit and provided an example of the level of detail needed when completing the food records.
The participants measured, weighed, and recorded each item consumed as well as the time of day
with the assistance of their parent or legal guardian. To ensure compliance each food record
20
entry was reviewed with the parent and child to ensure each section was descriptive and
complete. Food records were analyzed using Genesis R&D nutrient analysis software (ESHA
Research, Salem, OR).
Statistical Analysis
Statistical summaries were performed by using net incremental area under the curve (niAUC)
to calculate REE, protein and fat substrate oxidation, appetite ratings, adiponectin and leptin
values [44]. Two-sample independent test were used to determine differences between NW and
OW and to analyze participant characteristics, breakfast palatability, and comparison of niAUC
between treatments (control versus O3FA). When significant differences were found two-sample
independent t-test was used to determine the degree of significance. One-Way analysis of
variance (ANOVA) were used to calculate differences in niAUC of treatment groups for appetite
response, palatability, adiponectin, leptin, REE and to measure weighed food record
macronutrient intake. Two-way ANOVA was used to examine significant differences between
treatments and weight groups intake of diet over time for appetite responses, adiponectin, leptin,
energy expenditure, and substrate oxidation. One-way ANOVA was used to analyze differences
macronutrient intake and beverage palatability. When significant differences were found twosample independent t-test was used to determine the degree of significance. Net increment under
the curve (niAUC) was calculated for appetite rankings, REE, substrate oxidation, leptin and
adiponectin concentrations. Where significance was observed the Tukey correction for multiple
comparisons was applied within the analyses to two-sample independent t- test was used to
determine the degree of significance. Results were expressed as ± standard error of the mean
(SEM). GraphPad Prism 7 © (GraphPad Software, Inc. La Jolla, California, USA) was used to
21
analyze data and determine statistical significance. P-value of less than 0.05 was considered
statistically significant.
22
Results
Participant Characteristics
After screening and participant selection, data from 20 children were collected. The
physical characteristics of the participants are presented in Table 2. There was no statistical
difference in age and height between NW and OW groups, however body weight (P < 0.001),
and BMI percentile (P < 0.001) were higher in the OW group. Fat mass and free fat mass were
higher in the OW group (P < 0.01) and (P < 0.05), respectively.
Energy Expenditure and Substrate Oxidation
Energy expenditure and substrate oxidation are expressed as line graphs (individual time
points) and bar graphs (niAUC) in Figure 1. The overall analysis showed that O3FA trended to
slightly increase REE, carbohydrate oxidation, and fat oxidation. However, there was no
statistically significant effect of breakfast type in NW and OW, where we hypothesized O3FA
would have an effect. Overall, there was no observed statistical significance in energy
expenditure and substrate oxidation O3FA statistically significant increased. The results for RQ,
VO2, VCO2 are presented in Table 3.
Appetite and Palatability Response
Based on the participants’ self-reported appetite and palatability ratings measured at each
time interval using a VAS for perceived hunger, fullness, desire to eat, and prospective food
consumption (how “much” food a participant perceived they could consume) are presented in
line graphs (individual time points) and bar graphs (niAUC) Figure 2. For each appetite
response, there was an effect of time between NW and OW groups (P < 0.001). However, for
fullness there was a significant breakfast over time interaction (P < 0.05). The results for food
cravings are presented in Figure 3, There was an effect of time (P < 0.001). The perceived taste
23
response to each breakfast beverage was measure after the first beverage was consumed. There
was no significant difference in taste between control or O3FA breakfasts. Results are presented
in Table 2.
Satiety Hormone Variables
The results for leptin responses are presented in Figure 4. Leptin levels significantly
differed (P < 0.05) at time point 0 (prior to breakfast consumption) between NW control and NW
O3FA. In addition, OW control leptin values at time point 0 minutes were significantly higher
than at time point 90 minutes compared with OW O3FA. However, adiponectin did not result in
a significant difference as seen in Figure 5. There was no difference in niAUC leptin or
adiponectin concentrations between control or O3FA breakfast.
Dietary Assessment
The results for average daily energy intake are presented in Table 4. There was no
statistical significance of total food (kcal) intake in NW and OW groups consuming the Control
or O3FA treatments. However, there was a slight trend in both NW and OW participants
consuming O3FA to consume less food. In addition, there was a trend for both NW and OW
O3FA group to consume more protein and less carbohydrate. However, the OW, O3FA group
tended to consume more fat than in the OW, Control group.
24
Discussion
To our knowledge, this is one of the first studies to examine the effect of O3FA and
protein supplementation on energy metabolism, energy intake, and appetite response in NW and
OW school-aged children. It was hypothesized that increasing O3FA at breakfast would improve
energy metabolism and reduce energy intake throughout the day in OW children. The primary
finding was that breakfast consumption (both control and O3FA beverages) had an effect
overtime. Secondly, O3FA tended to slightly improve energy metabolism by increasing REE,
presented in Table 3.
Furthermore, it has been suggested that dietary fats in particularly O3FA have metabolic
effects as increased EE, satiety, and a decrease in the risk of certain metabolic disorders (e.g.
T2DM and cardiovascular disease) in adults. Several studies have examined the effects of protein
beverages on EE [144, 224, 225], however few of studies have examined the effects of O3FA on
EE, especially in children [226]. The current study is unique because it is the first to compare the
effects of O3FA intake on energy expenditure in 8-12-year-old children. In addition, many
studies examining the effect of O3FA have used capsules as a supplement. The current study is
unique because it uses O3FA incorporated into a breakfast beverage rather than as capsule. One
study examined five male and five females who consumed either encapsulated (1 g) or
emulsified (5 g ~ teaspoon) O3FA over a 48- hour timeframe. At the end of the intervention
emulsified O3FA had an enhanced and extended rate of absorption compared to the encapsulated
O3FA [226]. Although this study did not investigate the absorption rate of O3FA it did provide
findings that OW participants had an increased REE over an acute period compared with the
control. However, Logan et al [135], supported the findings in this study that O3FA increases EE
in individuals in a study of older women where EE was increased by 14% with 3g/d O3FA
25
supplementation for 12 weeks. These findings provide evidence that increased O3FA in the diet
increases EE, similarly to the results of this study. Although not examined directly at breakfast
these studies did demonstrate that O3FA have a positive effect on increasing EE. The present
study observed that O3FA tended to decrease carbohydrate and fat oxidation when consumed at
breakfast, suggesting that there may be an association between O3FA and increased substrate
oxidation. However, a longer data collection period is needed.
In terms of appetite regulation, a study where rats were injected with monounsaturated
oleic acid (OA) or polyunsaturated O3FA docosahexaenoic acid (DHA) it was demonstrated that
rats injected with O3FA had reduced energy intake and a decrease in body weight for 48 hours
following injections [38]. In addition, Parra el al [14] showed that appetite control plays a major
role in obesity in a study of 248 volunteers that suggested that O3FA intake modulates
postprandial satiety in OW individuals. Participants in the current study had a significant
increase in fullness following breakfast consumption, with no effect of either protein or O3FA.
However, this could be because macronutrient percentage and caloric content were the same
between breakfast beverages. It could also be due to the short duration of the appetite response
period since appetite was assessed four hours postprandial on the first study day and not
following the 14-day adaptation period.
Several studies focus on the effect of O3FA intake on increased leptin signaling in adults
[213, 227, 228], there is no data on the effect of O3FA in children. Kazmi et al [229] studied 40
NW and 50 OW participants and found that OW adults had a much higher serum leptin levels,
which is consistent with the finding in this study. Leptin concentrations are strongly associated
with BMI and long-term regulation of leptin is dependent upon adiposity, due to leptin’s role in
acting as a gauge to energy reserves that signals the central nervous system to adjust food intake
26
to assist with energy balance [230, 231]. However, breakfast skipping can interrupt energy
balance and decrease leptin signaling [208, 232].
Children who consume breakfast regularly tend to have improved nutritional balance
(intake of all needed calories, macronutrients, and micronutrients from diet to increase health
status), and are less likely to have micronutrient deficiencies such as calcium and iron [149, 151,
233]. Children who consume breakfast are also less likely to be overweight or obese compared
with those who skip breakfast [147]. However, data suggest that the macronutrient composition
of breakfast is also important. Breakfast macronutrient composition is associated with improved
health benefits such as improved circulating adiponectin and regulation of leptin signaling [208,
213, 227, 228, 234]. Our current study observed an increase in leptin concentration in both NW
and OW children who consumed the O3FA breakfast compared with the control breakfast. There
was a similar effect of O3FA was observed in a study using rat models fed demonstrated that the
presence of O3FA in a sucrose–rich diet (SRD), prevented adiposity and increased circulating
plasma leptin [235] .
There were several limitations to this study. The first limitation was the duration, this study
only focused on the postprandial effects of the first day of each dietary treatment. Future studies
should examine the effects of O3FA supplementation after a longer adaptation period since most
of the literature reports an effect of O3FA supplementation following several months of
supplementation [117, 135]. However, O3FA content was comparable to levels published in
literature. Several studies show the cardio-metabolic benefits of increasing O3FA intake in the
diet [135, 236-238]. Another limitation was the difficulty in recruiting overweight and obese
subjects. A longer recruiting period for future studies will be needed to increase the number of
obese and overweight participants. The low sample size meant that this study may not have been
27
adequately powered to see significance. Finally, there was difficulty with taking blood samples
from some subjects due either to anxiety from the participant or the inability to find a vein,
which resulted in a lower sample size for some of the plasma analysis.
Conclusion
In conclusion, dietary interventions have shown promising results for the treatment of
obesity. Breakfast consumption of O3FA tended to increased EE. In addition, there was an
increase in carbohydrate oxidation in O3FA compared to control. Omega-3 fatty acid
supplementation influenced satiety with and observed increase of fullness over time.
Additionally, O3FA supplementation was observed to have a biochemical response on leptin in
OW children. Taken together, these data suggest that increasing O3FA in the diets of school
aged children has beneficial effects on EE, satiety, and metabolic responses throughout the day,
however it may be beneficial to conduct more interventions in school aged children to have more
comparative data.
28
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47
1.5
1.0
0.5
0.0
0
1.5
60
120
180
20
10
l
ro
nt
o
C
240
NW Control
OW Control
NW O3FA
OW O3FA
O
A
3F
200
CO niAUC, g/0 min
1.0
0.5
150
100
50
C
120
180
240
NW Control
OW Control
NW O3FA
OW O3FA
0.5
3F
A
60
O
0
C
on
0.0
tr
ol
0
200
150
100
50
60
120
180
240
3F
A
O
0
on
t
0.0
ro
l
0
C
Carbohydrate Oxidation, g/min
30
0
B
Fat Oxidation, g/min
OW Control
OW O3FA
REE niAUC, g/0 min
NW Control
NW O3FA
FO niAUC, g/ 0 min
Resting Energy Expenditure kcal/min
A
Figure 1. Day 1 postprandial EE and substrate oxidation after ingestion of either a control
or O3FA breakfast in NW and OW children. Data are means ± SEMs; NW n= 11, OW n =
9. EE overtime per weight group and niAUC for each for each breakfast type combined
(A). CO over time per weight group and niAUC with groups combined for CO each
breakfast type (B). FO over time per weight group and niAUC with weights combined for
FO for each breakfast type (C). O3FA, Omega-3 fatty acid based breakfast; REE, resting
energy expenditure; CO, carbohydrate oxidation; niAUC, net increment under the curve,
NW, normal weight; OW, overweight/obese.
48
120
OW O3FA
Time effect, P < 0.001
Breakfast effect, P < 0.001
Time x Breakfast, P <0.05
a
30
0 15 NW Control
60
120 OW Control
180
Perceived Desire to Eat, mm
240
OW O3FA
60
30
Time effect, P < 0.001
Breakfast effect, ns
Time x Breakfast interaction, ns
0 15
60
120
180
240
OW Control
OW O3FA
90
60
30
0
0
C
ol
tr
on
Time effect, P < 0.001
Breakfast effect, ns
Time x Breakfast interaction, ns
0 15
60
120
180
240
O
A
3F
15000
10000
5000
0
C
90
0
5000
ol
tr
on
O
A
3F
20000
15000
10000
5000
0
C
on
tr
ol
60
NW O3FA
Perceived Much to Eat, mm
240
90
NW Control
NW O3FA
D
180
OW Control
10000
3F
A
60
NW Control
NW O3FA
15000
O
0 15
20000
Perceived Desire to Eat niAUC, mm × 0 min
Perceived Fullness, mm
Time effect, P < 0.001
Breakfast effect, ns
Time x Breakfast interaction, ns
Perceived Hunger niAUC, mm × 0 min
30
0
C
OW O3FA
60
0
B
OW Control
NW O3FA
Perceived Fullness niAUC, mm × 0 min
90
NW Control
Perceived Much to Eat niAUC, mm × 0 min
Perceived Hunger, mm
A
20000
15000
10000
5000
0
C
ol
tr
on
O
A
3F
Figure 2. Ratings of appetite after consumption of either control or O3FA in
NW or OW children with the use of visual analog scales. Data are ± SEMs; NW
n =11, OW n = 9 children. Perceived hunger over time per weight group and
breakfast type and net incremental area under the curve (niAUC) per breakfast
type, with weight groups combined (A). Perceived fullness over time per
weight group and niAUC per breakfast type, with weight groups combined (B).
Perceived desire to eat over time per weight group and niAUC per breakfast
type, with weight groups combined (C). Perceived much over time per weight
group and niAUC per breakfast type, with weight groups combined (D).
49
180OW Control
240
NW O3FA
OW O3FA
90
60
30
0 15
60
120
180
240
O
3F
A
tr
ol
15000
10000
5000
0
nt
Co
l
ro
O
A
3F
20000
15000
10000
5000
0
C
0
Time effect, P < 0.001
Breakfast effect, ns
Time x Breakfast interaction, ns
0
3F
A
0 15 NW60Control 120
5000
O
30
10000
C
on
Time effect, ns
Breakfast effect, ns
Time x Breakfast interaction, ns
0
NW Control
OW Control
0 15
60
120
180
240
NW O3FA
OW O3FA
90
Time effect, ns
Breakfast effect, ns
Time x Breakfast interaction, ns
60
Perceived Sweet niAUC, mm × 0 min
30
15000
on
tr
ol
Perceived Snack, mm
NW O3FA
60
0
C
OW O3FA
OW Control
Perceived Salty niAUC, mm × 0 min
90
NW Control
Perceived Snack niAUC, mm × 0 min
B
Perceived Salty, mm
Perceived Sweet, mm
A
Figure 3. Ratings of food cravings after consumption of either control or
O3FA in NW or OW children with the use of visual analog scales. Data are ±
SEMs; NW n =11, OW n = 9 children. Perceived sweet craving over time per
weight group and net incremental area under the curve (niAUC) per breakfast
type, with weight groups (A). Perceived salty craving over time per weight
group and niAUC per breakfast type, with weight groups combined (B).
Perceived snack craving over time per weight group and niAUC per breakfast
type, with weight groups combined (C).
50
OW Control
NW O3FA
OW O3FA
60
ng
L
/m
1.0
40
0.5
20
0.0
-0.5
60
120
180
240
,
C
U
A
tin
ep
L
Leptin, ng /mL
1.5
NW Control
0
Time after Breakfast, min
Time effect, P < 0.05
Breakfast effect, ns
Time x Breakfast interaction, ns
N
W
C
on
ol
tr
N
W
O
A
3F
O
W
C
on
ol
tr
O
W
O
A
3F
Figure 4. Changes in leptin concentrations after consumption of either control or O3FA in NW or OW
children. Data are means ± SEMs; NW n = 11, OW n = 9. Leptin concentrations net incremental area
under the curve (niAUC) per breakfast type, with weight groups combined. Data points with a letter
indicate a difference between breakfast types (control versus O3FA), P < 0.05. O3FA, omega-3 fatty acid,
niAUC net incremental area under the curve; NW, normal weight; OW, overweight/obese.
51
OW Control
NW O3FA
OW O3FA
150
0.5
0.0
60
120
180
240
Time after Breakfast, min
-0.5
Adiponectin niAUC, ng /mL
Adiponectin, ng /mL
1.0
NW Control
100
50
0
Time effect, ns
Breakfast effect, ns
Time x Breakfast interaction, ns
W
N
C
l
ro
t
on
N
W
A
3F
O
O
W
C
l
ro
t
on
W
O
O
A
3F
Figure 5. Changes in adiponectin concentrations after consumption of either control or O3FA
in NW or OW children. Data are means ± SEMs; NW n = 11, OW n = 9. Adiponectin
concentrations niAUC per breakfast type, with weight groups combined. ns. O3FA, omega-3
fatty acid, niAUC, net incremental area under the curve; NW, normal weight; OW,
overweight/obese.
52
Table 1. Dietary Characteristics of Test Breakfast1
Control
O3FA
Energy content, kcal
320
320
Total Protein, g
10
10
Total Carbohydrate, g
28
28
Fiber, g
7.6
7.6
Total fat, g
17.2
17.2
2
Total O3FA , g
0
5000
DHA, mg
0
2000
EPA, mg
0
2000
3
Breakfast palatability, mm
61.3 ± 10.3
74.3 ± 9.3
1
Values are means ± SEMs unless otherwise indicated, n = 20.
Control, protein + vegetable oil based-breakfast (fat source
unknown); O3FA, protein + O3FA based-breakfast.
2
Total O3FA = 5000 g; 1000 mg fat source unknown
3
Units are in millimeters (mm) accordng to the tradional 100mm visual analog scale
53
Table 2. Participant Demographics
1
Participants, n
Age, y
Height, cm
Weight, kg
BMI Percentile, %
Fat Mass, kg
Free Fat Mass, kg
NW
11
9.8 ± 0.4
144.4 ± 3.8
34.9 ± 2.6
50.0 ± 10.0
7.3 ± 1.2
28.0 ± 2.7
OW
9
10.2 ± 0.5
151.0 ± 4.5
56.3 ± 4.8***
100.0 ± 0.0***
19.6 ± 2.7**
36.2 ± 3.8*
Gender
Male
Female
5
6
5
4
Caucasian
African American
†Biracial
8
1
2
5
3
1
Ethnicity
1
Age, height, weight, BMI percentile, fat mass, and free fat mass are expressed
as mean ± SEM or n. *, **, *** Different from NW *P < 0.05, ** P < 0.01, ***P
< 0.001. NW, normal weight; OW overweight/obese.
†Indicates one parent as Caucasian and one parent as African American
54
1
Table 3. Metabolic Variables following consumption of either control or O3FA- based test breakfast
Time
Following
Breakfast, min
55
group
RQ
0
60
120
240
VO2 mL/min
0
60
120
240
VCO2 mL/min
0
60
120
240
NW D1 (n=11)
Control
OW D1 (n=9)
O3FA
0.79 ± 0.10
0.79 ± 0.10
0.92 ± 0.02
0.78 ± 0.10
Control
0.89 ± 0.01
0.84 ± 0.1
0.90 ± 0.01
0.90 ± 0.01
Time x
Breakfast
Type
interaction
ns
ns
ns
ns
<0.0001
ns
<0.05
<0.0001
ns
O3FA
0.91 ± 0.02
0.96 ± 0.01
0.92 ± 0.01
0.87 ± 0.02
a
Effect of
Time
Effect of
Breakfast
Type
0.92 ± 0.02
0.93 ± 0.01
0.91 ± 0.02
0.86 ± 0.02
127.28 ± 16.30
a
150.67 ± 17.80
a
147.07 ± 9.60
a
145.29 ± 17.30
a
157.60 ± 8.40
a
168.10 ± 18.70
a
177.78 ± 7.70
a
166.37 ± 7.10
204.22 ± 10.60
b
224.47 ± 11.90
b
208.09 ± 12.80
b
208.09 ± 12.80
b
207.968 ± 14.54
b
229.273 ± 19.56
b
220.54 ± 17.24
b
214.86 ± 19.13
145.44 ± 18.10 a
a
160.34 ± 18.2
160.37 ± 9.90a
a
125.96 ± 15.80
140.23 ± 7.40a
a
154.46 ± 17.10
a
160.98 ± 7.80
a
141.51 ± 6.60
185.49 ± 9.02b
b
215.66 ± 11.90
191.80 ± 11.80 b
b
182.48 ± 10.70
191.68 ± 14.67 b
b
212.10 ± 18.20
202.08 ± 17.02 b
b
184.14 ± 17.57
1
b
Values are means ± SEMs. Labeled means within a treatment column without a common upper case letter differ, P < 0.05. Labeled means within a row
without a common lower case differ P < 0.05. If a row does not contain a lowercase letter, there is no difference within that row. Respiratory Quotient RQ.
55
Table 4. Energy and macronutrient compostion of food intake D1 in NW and OW children after Control or O3FA1
NW (n =11)
OW (n=9)
Control
O3FA
Control
O3FA
Energy intake, kcal
Total
867.7 ± 126.6
840.8 ± 68.8
963.1 ± 130.4
920.5 ± 117.2
Protein
Carbohydrate
Fat
87.1 ± 13.5
349.8 ± 105.1
430.8 ± 89.5
100.1 ± 10.8
320.4 ± 54.3
420.3 ± 76.7
80.5 ± 11.8
489.0 ± 156.6
393.6 ± 73.5
92.8 ± 12.9
369.6 ± 93.0
458.1 ± 116.0
56
Marcronutrient intake, % energy
Protein
10
12
8
10
Carbohydrate
40
38
51
40
Fat
50
50
41
50
1
Values are means are ± SEMs. Data obtained from D1 (weekday or weekend), day 1 weighed food records.
Control, vegetable oil based-breakfast (fat source unknown); NW, normal weight; OW, overweight/obese; O3FA,
O3FA based-breakfast.
56
Appendix A
DEXA
Mins.
Anthropometrics
-30
Blood
collection
0
+15
Metabolic
Cart
Visual Analog Scale
+30
+60
57
+90
O3FA breakfast
+120
+180
3-day food log
+240
Office of Research Compliance
Institutional Review Board
January 20, 2016
MEMORANDUM
TO:
Jamie Baum
Brianna Neumann
Stephanie Shouse
Charlayne Mitchell
FROM:
Ro Windwalker
IRB Coordinator
RE:
New Protocol Approval
IRB Protocol #:
15-09-094
Protocol Title:
Nutrition Intervention to Improve Energy Metabolism, Energy Intake, and
Metabolic Response in Overweight and Obese School-Aged Children
Review Type:
Approved Project Period:
EXEMPT
EXPEDITED
FULL IRB
Start Date: 01/19/2016 Expiration Date: 01/18/2017
Your protocol has been approved by the IRB. Protocols are approved for a maximum period of one
year. If you wish to continue the project past the approved project period (see above), you must submit
a request, using the form Continuing Review for IRB Approved Projects, prior to the expiration date.
This form is available from the IRB Coordinator or on the Research Compliance website
(https://vpred.uark.edu/units/rscp/index.php). As a courtesy, you will be sent a reminder two months in
advance of that date. However, failure to receive a reminder does not negate your obligation to make
the request in sufficient time for review and approval. Federal regulations prohibit retroactive approval
of continuation. Failure to receive approval to continue the project prior to the expiration date will result
in Termination of the protocol approval. The IRB Coordinator can give you guidance on submission
times.
This protocol has been approved for 200 participants. If you wish to make any modifications in the
approved protocol, including enrolling more than this number, you must seek approval prior to
implementing those changes. All modifications should be requested in writing (email is acceptable) and
must provide sufficient detail to assess the impact of the change.
If you have questions or need any assistance from the IRB, please contact me at 109 MLKG Building,
5-2208, or [email protected].
109 MLKG • 1 University of Arkansas • Fayetteville, AR 72701-1201 • (479) 575-2208 • Fax (479) 575-6527 • Email [email protected]
The University of Arkansas is an equal opportunity/affirmative action institution.
58
May 16, 2016
MEMORANDUM
TO:
Dr. Jamie Baum
FROM:
Ines Pinto, Biosafety Committee Chair
RE:
Protocol Modification
PROTOCOL #:
16002
PROTOCOL TITLE:
throughout the lifecycle
The impact of nutrient quantity, quality and timing on metabolic health
APPROVED PROJECT PERIOD:
Start Date August 13, 2015
Expiration Date August 12, 2018
The Institutional Biosafety Committee (IBC) has approved your request, dated March 6, 2016, to modify
Protocol # 16002, “The impact of nutrient quantity, quality and timing on metabolic health throughout
the lifecycle” on the condition that you do not ship any fecal samples until DOT (Department of
Transportation) training is obtained and proof provided to the IBC.
The IBC appreciates your assistance and cooperation in complying with University and Federal guidelines
for research involving hazardous biological materials.
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