Strategies for Healthy Weight Loss: From Vitamin C to
the Glycemic Response
Carol S. Johnston, PhD, FACN
Department of Nutrition, Arizona State University, Mesa, Arizona
Key words: weight loss, vitamin C, high-protein diets, vinegar, peanuts
Abstract America is experiencing a major obesity epidemic. The ramifications of this epidemic are immense
since obesity is associated with chronic metabolic abnormalities such as insulin resistance, dyslipidemia, and
heart disease. Reduced physical activity and/or increased energy intakes are important factors in this epidemic.
Additionally, a genetic susceptibility to obesity is associated with gene polymorphisms affecting biochemical
pathways that regulate fat oxidation, energy expenditure, or energy intake. However, these pathways are also
impacted by specific foods and nutrients. Vitamin C status is inversely related to body mass. Individuals with
adequate vitamin C status oxidize 30% more fat during a moderate exercise bout than individuals with low
vitamin C status; thus, vitamin C depleted individuals may be more resistant to fat mass loss. Food choices can
impact post-meal satiety and hunger. High-protein foods promote postprandial thermogenesis and greater satiety
as compared to high-carbohydrate, low-fat foods; thus, diet regimens high in protein foods may improve diet
compliance and diet effectiveness. Vinegar and peanut ingestion can reduce the glycemic effect of a meal, a
phenomenon that has been related to satiety and reduced food consumption. Thus, the effectiveness of regular
exercise and a prudent diet for weight loss may be enhanced by attention to specific diet details.
Key teaching points:
• Gene polymorphisms associated with biochemical pathways that regulate fat oxidation, energy expenditure, or energy intake have
been linked to genetic susceptibility to obesity.
• 30–70% of the variation in body weight and fat mass can be attributed to genetics; environmental conditions, including specific
dietary factors, may play a pronounced role in the expression of these phenotypes.
• Vitamin C status is associated with tissue carnitine concentrations and fat oxidation and may represent a modifiable condition that
would impact fat oxidation thereby affecting body composition and body mass.
• The thermic effect of food, which accounts for ?10% of daily energy expenditure, is related to dietary protein; thus, the greater
calorie-cost of high-protein diets, in association with the increased satiety of these diets, may protect against gradual weight gain.
• The glycemic response to food ingestion has been associated with subsequent hunger; complementary foods, such as vinegar or
peanut products, when added to meals, may attenuate meal-time glycemia promoting satiety and reduced energy intake.
America is experiencing a major epidemic of overweight
and obesity. In 2001–02, 66% of adults were overweight (body
mass index [BMI] ?25) and 31% of adults were obese (BMI
?30) . In comparison, the prevalences of overweight and
obesity respectively were 46% and 15% in 1976–80 and 56%
and 23% in 1988–94 . Excess weight is associated with the
leading causes of death in the U.S.: cardiovascular disease,
cancer, stroke, and type 2 diabetes. In fact, obesity is quickly
gaining on tobacco as the leading cause of preventable death in
the U.S. In 1993, tobacco contributed to 400,000 deaths annu-
ally versus the 300,000 deaths attributed to diet and inactivity
. By the year 2000, the gap had narrowed considerably with
435,000 deaths annually attributed to tobacco and 400,000
deaths attributed to diet and inactivity . As a sign of the
times, Medicare recently announced that it had changed its
Address reprint requests to: Carol S. Johnston, PhD, FACN, Department of Nutrition, Arizona State University East, 7001 E. Williams Field Rd., Mesa, AZ 85212. E-mail:
Presented in part at the 45th Annual Meeting of the American College of Nutrition in Long Beach, California, September 30–October 3, 2004.
Journal of the American College of Nutrition, Vol. 24, No. 3, 158–165 (2005)
Published by the American College of Nutrition
policy and will recognize obesity as an illness permitting cov-
erage for some obesity treatments. Hence, the ramifications of
the obesity epidemic are immense, from the increased risk of
debilitating conditions and death, to the tremendous economic
burden placed on America’s healthcare system.
The Dietary Guidelines for Americans reflect the prepon-
derance of the research evidence for effective strategies for
weight loss and weight maintenance: be physically active each
day; choose a variety of grains daily, especially whole grains;
and choose a diet that is low in saturated fat and cholesterol and
moderate in total fat [5–9]. However, 30–70% of the variation
in body weight and fat mass can be attributed to genetics
[10–12]; and the impact of a prudent diet and/or physical
activity varies considerably between overweight individuals
. Loos and Bouchard  described a three-tier model for
genetic susceptibility for obesity and postulated that the envi-
ronment has a permissive role in the severity of the obesity
phenotype. According to this model, at least 5% of the obesity
cases represent genetic obesity minimally impacted by the
environment. The more common forms of obesity would fall
into categories with either a strong or slight predisposition to
obesity, and environmental conditions would play a pro-
nounced role in the expression of the phenotype. Thus, in a
restrictive environment where food availability and labor sav-
ing devices are limited (similar to the adoption of a prudent diet
and exercise program), many individuals with a genetic pre-
disposition to obesity would likely be normal weight or slightly
overweight. But most Americans live in an ‘obesogenic’ envi-
ronment, and although some obese-promoting environmental
conditions have been identified, it is reasonable to expect that
there are other modifiable conditions impacting the obesity
phenotype. Attention to such variables may permit the fine-
tuning of weight loss strategies and promote greater successes.
Much of the work to understand the genetic susceptibility to
obesity has been to identify gene polymorphisms associated
with the biochemical pathways that regulate fat oxidation,
energy expenditure, or energy intake. Several proteins involved
in these pathways have been extensively studied: fatty acid
synthase, the mitochondrial uncoupling proteins, the ?- and
?2-adrenoceptors, leptin, and the leptin receptor [15–19]. We
have identified several dietary factors that also appear to mod-
ify energy expenditure and energy intake. Tweaking these
dietary factors to promote fat oxidation, energy expenditure, or
reduce energy intake may lessen the impact of a hedonistic
environment on the obesity phenotype.
Vitamin C Status
About 20% of U.S. adults are vitamin C depleted, plasma
concentrations 11–28 ?mol/L, and 12–17% are vitamin C
deficient and at risk of clinical scurvy, plasma concentrations
?11 ?mol/L [20,21]. Twenty-five years ago, the prevalence of
vitamin C deficiency was much lower, 3–5% of U.S. adults
. Correspondence among physicians suggest that the inci-
dence of scurvy may indeed be on the rise [23,24], a seeming
paradox given the wide availability of fresh fruits and vegeta-
bles and the addition of vitamin C to many processed foods.
Yet, vitamin C in foods is irreversibly oxidized by exposure to
light, oxygen, and/or heat, and reports suggest that fresh pro-
duce or juice may lose 50–100% of its vitamin C content due
to handling and processing [25–27]. Hence, the increased pro-
cessing of the food supply may be impacting the level of
dietary vitamin C available to consumers.
As an effective reducing agent and electron donor, vitamin
C has an essential role in numerous metabolic pathways, most
notably that of collagen synthesis. Vitamin C is required for the
post-translational modification of procollagen polypeptides to
form the resilient, cross-linked collagen molecule . Most of
the physiological symptoms attributed to scurvy (subcutaneous
and intramuscular hemorrhages, leg edema, joint pain, and
neuropathy) are related to defective collagen synthesis. Yet, as
reported by James Lind in 1753: “the first indication of the
approach of this disease is. . .a pale and bloated complexion;
with a listlessness to action or an aversion to any sort of
exercise. . .degenerates soon into a universal lassitude. . .much
fatigue and upon that occasion subject to breathlessness or
panting. And this lassitude, with a breathlessness upon motion,
are observed to be among the most constant concomitants of
the distemper”. Vitamin C is required for the biosynthesis of
carnitine, a small molecule responsible for shuttling long chain
fatty acids across the mitochondrial membrane for ?-oxidation
and subsequent fat oxidation [29,30]. Reduced tissue carnitine,
and the associated impact on fat oxidation, is considered the
cause of the fatigue of scurvy [31,32].
We have observed that individuals with poor vitamin C
status (n ? 15; plasma vitamin C ?34 ?mol/L) oxidize less fat
during a submaximal walking test than individuals with ade-
quate vitamin C status (n ? 7; plasma vitamin C ?34 ?mol/L)
(respiratory exchange ratio, RER: 0.87 ? 0.01 versus 0.83 ?
0.01, p ? 0.05) (unpublished data). Furthermore, fat energy
expended in these subjects was inversely correlated with
plasma carnitine (r ? ?0.489, p ? 0.043) and with fatigue as
determined by the POMS (Profile of Moods States) question-
naire (r ? ?0.611, p ? 0.009). We conducted a placebo-
controlled depletion-repletion trial to determine the impact of
vitamin C status on exercise performance and vigor . Sub-
jects with low vitamin C status (4 men and 5 women; 27.6 ?
2.5 y; plasma concentrations ?28 ?mol/L) consumed a placebo
capsule daily for three weeks (depletion period) and an identi-
cal looking capsule containing 500 mg vitamin C for the
following two weeks (repletion period). Subjects were unaware
of their vitamin C status and of the nature of the trial. At the end
of trial weeks 3 and 5, subjects completed a low intensity, 90
as [work rate (kcals/min)/energy expended (kcal/min)] ? 100.
In the vitamin C repleted state, subjects performed 10%
more work at 50% VO2max equating to a 14% improvement
Strategies for Healthy, Effective Weight Loss
JOURNAL OF THE AMERICAN COLLEGE OF NUTRITION159
in work efficiency (Table 1). Whether this improvement in
vigor and work performance was attributed to increased tissue
carnitine concentrations is not known since muscle biopsies
were not taken. However, plasma carnitine concentrations did
drop nearly 20% (p ? 0.05) indicating a rise in muscle carni-
tine. (In humans, carnitine synthesis from ?-butyrobetaine is
restricted to liver, brain, and kidney, and the transport of
carnitine into the muscle is dependent on a 1:1 exchange
process with ?-butyrobetaine that is synthesized in muscle
tissue, a vitamin C-dependent process [34,35]. Hence, in vita-
min C depletion, carnitine is trapped in plasma and plasma
carnitine concentrations rise .)
To examine the effect of vitamin C status on substrate
oxidation specifically, we recruited eleven sedentary individu-
als with poor vitamin C status (plasma vitamin C concentration
?34 ?mol/L). Subjects were free living and maintained their
usual dietary patterns; however, they were instructed not to
consume certain fruits, vegetables, and juices, mainly orange
juice, oranges, strawberries, melons, broccoli, tomatoes, and
peppers (i.e. foods containing ?30 mg of vitamin C per serv-
ing). During trial weeks 1–4 all subjects consumed a placebo
capsule daily (washout). Subjects were then randomized to the
repleted group (n ? 6; 500 mg vitamin C daily; capsule
identical in appearance to placebo) or the depleted group (n ?
5; placebo daily). At the end of trial weeks 4 and 8, subjects
completed a 60-min submaximal treadmill walking test. Fat
energy expended during exercise at week 8 was significantly
raised in repleted subjects as compared to depleted subjects
(2.03 ? 0.02 and 0.48 ? 0.11 kcals/kg, p ? 0.031) (Table 2).
RER was slightly lower in repleted subjects as compared to
depleted subjects at week 8 (0.879 ? 0.018 and 0.937 ? 0.026
respectively, p ? 0.096). Plasma carnitine did not differ by
group at week 8 (Table 2); however, plasma vitamin C and
carnitine were weakly inversely related (r ? ?0.441, p ?
0.087). Plasma vitamin C was correlated to fat energy expen-
diture (r ? 0.655, p ? 0.006) (Fig. 1); thus, vitamin C status
explained 43% of the variation in fat oxidation during submaxi-
Together these data provide preliminary evidence that vita-
min C status influences fat oxidation, exercise performance,
and vigor. Since impaired fat oxidation has been implicated in
the development of obesity and in failed weight loss attempts
[37–39], vitamin C depletion may create a metabolic perturba-
tion that could potentially impact body mass. Several studies
have reported a significant inverse relationship between plasma
vitamin C concentrations and degree of obesity [40,41]. In our
trials, a weak inverse relationship was noted for plasma vitamin
C and body mass (r ? ?0.36; p ? 0.10). Interestingly, a
randomized, double blind trial demonstrated that vitamin C
supplementation was associated with significantly greater
weight loss versus placebo (2.53 kg versus 0.95 kg) after 6
weeks . Thus, vitamin C status may represent a modifiable
condition that would impact the expression of the obesity
Table 1. Effect of Vitamin C Status on Blood Indices and on
Heart Rate, Substrate Utilization and Aerobic Function
during Submaximal Exercise1
Plasma vitamin C
Plasma vitamin C, ?mol/L
Plasma free carnitine, ?mol/L
Heart rate, beats/min
Work efficiency, %
17.2 ? 2.8
58.1 ? 4.7
129 ? 8
2059 ? 206
7.8 ? 0.8
49.4 ? 3.5*
47.2 ? 3.7*
130 ? 10
2255 ? 216*
8.9 ? 0.8*
1Data are mean ? SE; asterisk indicates significant difference from depleted
state (p ? 0.05; repeated measures ANOVA) (adapted from ).
Table 2. Metabolic Indices in Subjects with Poor Vitamin C
Status (Placebo-Controlled Washout; Trial Week 4) Who
Were Randomly Assigned to One of Two Treatment Groups:
Repleted (N ? 5; 500 Mg Vitamin C Daily) or Depleted
(N ? 3; Placebo Daily)1
Week 4Week 8
Plasma vitamin C,
Fat energy expended,
Plasma Carnitine, ?mol/L
11.7 ? 5.0
12.7 ? 5.2
1.00 ? 0.34
1.46 ? 0.22
0.911 ? 0.010
0.875 ? 0.019
73.2 ? 9.3
56.9 ? 6.2
9.7 ? 1.0*
41.7 ? 0.9
0.48 ? 0.11*
2.03 ? 0.37
0.937 ? 0.026**
0.879 ? 0.018
65.1 ? 13.0
50.9 ? 6.2
1Data are mean ? SE; asterisks indicate differences between groups at the end
of week 8: * p ? 0.05, ** 0.05 ? p ? 0.10, 2 ? 2 repeated measures ANOVA
with Bonferroni post-hoc test.
Fig. 1. Relationship between plasma vitamin C and fat oxidation during
Strategies for Healthy, Effective Weight Loss
160VOL. 24, NO. 3
Macronutrient Profile of Diet
The thermic effect of food (TEF) accounts for roughly 10%
of daily energy expenditure. TEF is the increment in energy
expenditure above resting values that occurs following food
intake. TEF encompasses the obligatory energy costs of ingest-
ing, digesting, absorbing, and metabolizing food and the fac-
ultative energy cost related to the disposal of excess, non-
essential energy . This latter component of TEF is
influenced by autonomic nervous function, which may be mod-
ulated by genotype [44,45]. A defect in postprandial thermo-
genesis would favor weight gain, and a 25–60% reduction in
TEF has been reported in obese individuals as compared to
their lean counterparts [46,47].
Due to the high metabolic cost of metabolizing protein,
dietary protein can exert up to three times more TEF than
isocaloric amounts of carbohydrate or fat . We compared
the daylong energy-cost of a high-protein, low-fat (HPLF) diet
to that of a high-carbohydrate, low-fat (HCLF) diet in young
healthy, lean women (n ? 10; 19.0 ? 0.4 y; 64.4 ? 2.4 kg)
. Subjects consumed each of the two experimental diets,
which were composed of common foods and meal plans, in a
randomized crossover manner, and metabolic testing was sep-
arated by 4-week intervals to control for possible confounding
effects of menstrual cycle on energy expenditure. The fasting,
morning energy expenditure was similar by diet, 1359 ? 59
and 1396 ? 53 kcals/24/h for the HPLF and HCLF diets
respectively. Postprandial energy expenditure at 2.5 h post-
meals was 8, 8, and 14 kcals/h higher on the HPLF diet plan as
compared to the HCLF diet plan for the breakfast, lunch, and
dinner meals respectively (Fig. 2). Assuming that this same
energy differential was maintained for 2–3 h intervals post-
meals, the higher TEF associated with the HPLF diet would
represent an added energy cost of 60–90 kcals/d equating to a
loss of ?1 kg every 12–24 weeks (or 2–4 kg/y). Short-term
investigations (6–12 weeks) have reported similar weight loss
in overweight subjects randomized to energy-restricted, low-fat
diets either high (30% energy) or low (15% energy) in dietary
protein [50,51]; yet, over longer periods of time, the modest
effect of dietary protein on TEF may promote greater weight
losses or protect against gradual weight gain.
Dietary protein is also the macronutrient generally associ-
ated with increased satiety ; yet, mechanisms controlling
satiety are not clear . The thermic effect of protein has been
related to satiety , possibly due to the obligatory oxidative
disposal of amino acids. Dietary protein also is a potent stim-
ulator of the gastrointestinal hormones cholecystokinin and
glucagon-like peptide , both important mediators of satiety
via effects on gastrointestinal functions. Voluntary reductions
in energy consumption are noted in subjects consuming high-
protein meals ad libitum as compared with high-carbohydrate
meals [56,57]. Furthermore, in short-term trials, energy con-
sumption at subsequent meals was significantly less in subjects
consuming high-protein versus high-carbohydrate preloads
[57,58]. During a strictly controlled 6-wk weight loss trial
comparing a high-protein, low-fat, calorie restricted diet to a
high-carbohydrate, low-fat, calorie restricted diet , we
asked subjects to indicate on a 7-point Likert-scale (extremely
hungry to extremely full) how they generally had felt over the
past week. The experimental diets were equally effective at
reducing body weight and fat mass, but the HPLF subjects
reported feeling more satiated in the first 4 weeks of the feeding
trial compared with HCLF subjects (Fig. 3). Moreover, 20% of
the subjects randomized to the HCLF diet were dropped from
the trial since they were unable to comply with the calorie
restrictions due to unendurable hunger.
Thus, dietary protein may represent a dietary factor that can
be manipulated to influence the obesity phenotype via effects
Fig. 2. Postprandial thermogenesis (difference between post-meal en-
ergy expenditure and baseline energy expenditure) in young, healthy
women after ingestion of high-protein, low-fat (HPLF) meals versus
high-carbohydrate, low-fat (HCLF) meals. Values are means ? SE;
asterisks denote significant difference by diet (p ? 0.05; repeated
measures ANOVA). (Adapted from ).
Fig. 3. Perceived satiety for subjects consuming high-protein (HPLF,
n ? 9) or high-carbohydrate (HCLF, n ? 7) low-fat, energy-restricted
diets for 6 weeks using a 7-point Likert scale. Values are means ? SE.
(Adapted from ).
Strategies for Healthy, Effective Weight Loss
JOURNAL OF THE AMERICAN COLLEGE OF NUTRITION 161
on energy expenditure and energy intake. In this view, the
recent successes attributed to low-carbohydrate, high-protein
(Atkins-like) diets may simply reflect the thermogenesis and
the greater satiety afforded by higher intakes of protein and not
the ‘very low carbohydrate’ nature of the diets [59,60].
Glycemic Response to Meals
The current American diet is composed mainly of carbohy-
drates (50% total energy) , and carbohydrate-containing
foods are differentiated by their glycemic index (GI), an esti-
mate of the magnitude of the blood glucose response following
food ingestion. As compared to high-GI foods (processed
grains, foods composed of white flour, potato products, and
sweets), low-GI foods (whole grains, fruits, vegetables, dairy
products, and legumes) benefit body weight regulation by pro-
moting satiety. Of 20 studies published between 1977 and
1999, 16 demonstrated that low-GI foods promoted post-meal
satiety and/or reduced subsequent hunger . In children
attending an outpatient pediatric obesity program, patients who
followed a low-GI diet lost significantly more weight after 4
months than patients who followed a reduced-fat diet (change
in body weight, ?2.03 kg versus ?1.31 kg, p ?0.05) .
Thus, a reduction in the meal-time glycemic load (GL; GI ? g
total carbohydrate) is associated with reduced energy consump-
tion and weight loss; and, this strategy may represent an im-
portant approach to the prevention and treatment of obesity
We have examined the possibility of complementary foods
to reduce postprandial glycemia and to enhance satiety. This
approach is simpler than approaches that would require dietary
change. Preliminary work in our laboratories has indicated that
vinegar  and peanut product consumption at mealtime
reduced the glycemic response to meals. Eleven healthy adults
(27.9 ? 2.9 y; body mass index, 22.7 ? 1.0 kg/m2) consumed
two different test meals (bagel and juice, GL ? 81; or teriyaki
chicken on rice, GL ? 48) in random order under three differ-
ent experimental treatments: control, vinegar, and peanut. Wa-
ter sweetened with saccharine (60 g) was consumed pre-meal
for the control and peanut treatments, and a similarly sweetened
diluted vinegar drink was consumed pre-meal for the vinegar
treatments. For the peanut treatment, peanut butter (25 g) was
substituted for butter in the bagel and juice meal, and roasted
peanuts (25 g) were substituted for butter in the teriyaki meal.
These changes did not alter the GL of the meals.
Vinegar or peanut ingestion reduced the 60-min glucose
response (calculated as the incremental area-under-the-curve)
to either test meal by 50–55% (Fig. 4). After consumption of
the bagel and juice meal, energy consumption for the remainder
of the day was weakly affected by the vinegar and peanut
treatments (?12 to ?16% or a reduction of ?200–275 kilo-
calories; p ? 0.111) (Fig. 5). Later energy consumption did not
vary by treatment when the teriyaki chicken test meal was
consumed, perhaps a reflection of the lower GL of this meal.
Regression analysis indicated that the 60-min glucose response
to the test meals explained 11 to 16% of the variation in later
energy ingestion (p ? 0.05). The acetic acid in vinegar may
reduce the glycemic response to high GL foods by inhibiting
disaccharidases in the small intestinal epithelium  or by
stimulating glucose uptake and utilization in peripheral tissues
. Peanuts contain high levels of the amino acid arginine
which is a potent insulin secretagogue [69,70]; thus, peanut
consumption may affect glycemia by rapid stimulation of in-
sulin release and glucose uptake. These data indicate that the
addition of vinegar or peanut products to a high-GL meal
reduces postprandial glycemia.
Long-term trials would determine whether this simple con-
cept of complementary foods to attenuate postprandial glyce-
mia would favorably impact the obesity phenotype. Unpub-
lished data from our laboratories indicated that subjects
randomized to receive vinegar daily (n ? 12; 2 Tbls red
raspberry vinegar twice daily) lost weight after 4 weeks as
compared to a slight weight gain in the control subjects (n ?
10; 2 Tbls cranberry juice twice daily), ?0.72 ? 0.24 kg and
Fig. 4. Postprandial blood glucose concentrations depicted as incre-
mental area-under-curve (trapezoidal rule) for each experimental con-
dition. Values are means ? SE; asterisks indicate significant difference
from control value (multivariate general linear model for repeated
Fig. 5. Dietary energy ingestion following the consumption of two test
meals (bagel and juice meal [GL ? 81], dark bars; or teriyaki chicken
on rice meal [GL ? 48], open bars) under three experimental condi-
tions: control, peanut, vinegar. Dietary energy encompasses all foods
and beverages consumed for the entire day excluding the test meal.
Values are means ? SE (n ? 11); p values represent multivariate
general linear model for repeated measures.
Strategies for Healthy, Effective Weight Loss
162 VOL. 24, NO. 3
?0.27 ? 0.32 kg respectively (p ? 0.020). Interestingly, epi-
demiologic trials designed to examine the benefits of regular
nut consumption on cardiovascular disease risk have indicated
an inverse association between frequency of nut consumption
and body mass index , an effect possibly related to en-
hanced satiety .
A slight to strong genetic predisposition for obesity likely
exists for many individuals, a result of susceptibility alleles at
a number of loci rather than a specific gene mutation. Hence the
environment plays a key role in the permissive expression of
obesity phenotypes. The identification of easily manipulated
dietary factors (i.e., nutrient supplements or complementary
foods) that affect biochemical pathways involved in fat oxida-
tion, energy expenditure, or energy intake, would lay the basis
for new adjunct therapies for body weight management. We
have preliminary evidence suggesting that the regular ingestion
of vitamin C supplements, dietary protein, vinegar, and/or nuts
may help stimulate energy expenditure, promote satiety, and/or
modulate fat production. Thus, the effectiveness of regular
exercise and a prudent diet for weight loss may be enhanced by
attention to specific diet details.
I am grateful to my long-time friend and colleague, Pamela
Swan, for her expertise in obesity and energy expenditure, and
I am indebted to the staff of the Department of Nutrition at
Arizona State University East, particularly our research tech-
nician and phlebotomist, Michael Stroup. Funding for much of
this work was from the Lloyd S. Hubbard Nutrition Research
Fund of the Arizona State University Foundation.
1. Hedley AA, Ogden CL, Johnson CL, Carroll MD, Curtin LR,
Flegal KM: Prevalence of overweight and obesity among US
children, adolescents, and adults, 1999–2002. JAMA 291:2847–
2. Flegal KM, Carroll MD, Kuczmarski RJ, Johnson CL: Overs-
weight and obesity in the United States: prevalence and trends,
1960–1994. Int J Obes Relat Metab Disord 22:39–47, 1998.
3. McGinnis JM, Foege WH: Actual causes of death in the United
States. JAMA 270:2207–2212, 1993.
4. Mokdad AH, Marks JS, Stroup DF, Gerberding JL: Actual causes
of death in the United States, 2000. JAMA 291:1238–1245, 2004.
5. Jakicic JM: The role of physical activity in prevention and treat-
ment of body weight gain in adults. J Nutr 132:3826S–3829S,
6. Sherwood NE, Jeffery RW, French SA, Hannan PJ, Murray DM:
Predictors of weight gain in the pound of Prevention study. Int J
Obes Relat Metab Disord 24:359–403, 2000.
7. Astrup A: Healthy lifestyles in Europe: prevention of obesity and
type II diabetes by diet and physical activity. Public Health Nutr
8. Liu S, Willett WC, Manson JE, Hu FB, Rosner B, Colditz G:
Relation between changes in intakes of dietary fiber and grain
products and changes in weight and development of obesity among
middle-aged women. Am J Clin Nutr 78:920–927, 2003.
9. Astrup AM, Ryan Grunwald GK, Storgaard M, Saris W, Melanson
E, Hill: The role of dietary fat in body fatness: evidence from a
preliminary meta-analysis of ad libitum low-fat dietary interven-
tion studies. Br J Nutr 83:S25–S32, 2000.
10. Faith MS, Peitrobelli A, Nunez C, Heo M, Heymsfield SB, Allison
DB: Evidence for independent genetic influences on fat mass and
body mass index in a pediatric twin sample. Pediatrics 104:61–67,
11. Maes HHM, Neale MC, Eaves LJ: Genetic and environmental
factors in relative body weight and human adiposity. Behav Genet
12. Sorensen TI, Holst C, Stunkard AJ: Adoption study of environ-
mental modifications of the genetic influences on obesity. Int J
Obes Relat Metab Disord 22:73–81, 1998.
13. Hewitt JK: The genetics of obesity: what have genetic studies told
us about the environment. Behav Genet 27:353–358, 1997.
14. Loos RJF, Bouchard C: Obesity—is it a genetic disorder? J Inter
Med 254:401–425, 2003.
15. Kovacs P, Harper I, Hanson RL, Infante AM, Bogardus C,
Tataranni PA, Baier LJ: A novel missense substitution (val1483Ile)
in the fatty acid synthase gene (FAS) is associated with percentage
of body fat and substrate oxidation rates in nondiabetic Pima
Indians. Diabetes. 53:1915–1919, 2004.
16. Matsushita H, Kurabayashi T, Tomita M, Kato N, Tanaka K:
Effects of uncoupling pritein 1 and ?-adrenergic receptor gene
polymorphisms on body size and serum lipid concentrations in
Japanese women. Maturitas 45:39–45, 2003.
17. Hesselink MK, Mensink M, Schrauwen P: Human uncoupling
protein-3 and obesity: an update. Obes Res 11:1429–1443, 2003.
18. Shiwaku K, Nogi A, Anuurad E, Kitajima K, Enkhmaa B, Shi-
mono K, Yamane Y: Difficulty in losing weight by behavioral
intervention for women with Trp64Arg polymorphism of the be-
ta3-adrenergic receptor gene. Int J Obes Relat Metab Disord 27:
19. Mensink M, Blaak EE, Vidal H, de Bruin TWA, Glatz JFC, Saris
WHM: Lifestyle changes and lipid metabolism gene expression
and protein content in skeletal muscle of subjects with impaired
glucose tolerance. Diabetolgia 46: 1082–1089, 2004.
20. Hampl JS, Taylor CA, Johnston CS: Vitamin C deficiency and
depletion in the United States: the Third National Health and
Nutrition Examination Survey, 1988–1994. Am J Pub Health 94:
21. Dickinson VA, Block G, Russek-Cohen E: Supplement use, other
dietary and demographic variables, and serum vitamin C in
NHANES II. J Am Coll Nutr 13:22–32, 1994.
22. U.S. Department of Health and Human Services. Hematological
and nutritional biochemistry reference data for persons 6
months–74 years of age. United States, 1976–1980. Hyattsville,
Md. National Center for Health Statistics. 1982. Advance data
from Vital and Health Statistics, No. 83-1682: 124–139.
23. De Luna RH, Colley BJ, Smith K, Divers SG, Rinehart J, Marques
MB: Scurvy: an often forgotten cause of bleeding. Am J Hematol
24. Blee TH, Cogbill TH, Lambert PJ: Hemorrhage associated with
Strategies for Healthy, Effective Weight Loss
JOURNAL OF THE AMERICAN COLLEGE OF NUTRITION 163
vitamin C deficiency in surgical patients. Surgery 131:408–412,
25. Severi S, Bedogni G, Zoboli GP, Severi S, Bedogni G, Zoboli GP,
Manzieri AM, Poli M, Gatti G, Battistini N: Effects of home-based
food preparation practices on the micronutrient content of foods.
Eur J Cancer Prev 7:331–335, 1998.
26. Gil MI, Ferreres F, Tomas-Barberan FA: Effect of postharvest
storage and processing on the antioxidant constituents (flavonoids
and vitamin C) of fresh-cut spinach. J Agric Food Chem 47:2213–
27. Johnston CS, Bowling DL: Stability of ascorbic acid in commer-
cially available orange juices. J Am Diet Assoc 102:525–529,
28. Kypreos KE, Birk D, Trinkaus-Randall V, Hartmann DJ, Sonen-
shein GE: Type V collagen regulates the assembly of collagen
fibrils in cultures of bovine vascular smooth muscle cells. J Cell
Biochem 80:146–155, 2000.
29. Siliprandi N, Sartorelli L, Ciman M, Di Lisa F: Carnitine: metab-
olism and clinical chemistry. Clin Chim Acta. 183:3–12, 1989.
30. Reda E, D’Iddio S, Nicolai R, Benatti P, Calvani M: The carnitine
system and body composition. Acta Diabetol 40:S106–S113, 2003.
31. Rebouche CJ: Ascorbic acid and carnitine biosynthesis. Am J Clin
Nutr 54(6 Suppl):1147S–1152S, 1991.
32. Hughes RE, Hurley RJ, Jones E: Dietary ascorbic acid and muscle
carnitine (beta-OH-gamma-(trimethylamino) butyric acid) in guin-
ea-pigs. Br J Nutr 43:385–387, 1980.
33. Johnston CS, Swan PD, Corte C: Substrate utilization and work
efficiency during submaximal exercise in vitamin C depleted-
repleted adults. Int J Vit Nutr Res 69:41–44, 1999.
34. Sartorelli L, Ciman M, Mantovani G, Siliprandi N: Carnitine
transport in rat heart slices: I. The action of thiol reagents on the
acetylcarnitine/carnitine exchange. Ital J Biochem 34:275–281,
35. Sartorelli L, Ciman M, Mantovani G, Siliprandi N: Carnitine
transport in rat heart slices: II. The carnitine/deoxycarnitine anti-
port. Ital J Biochem 34:282–287, 1985.
36. Henderson LM, Nelson PJ, Henderson L: Mammalian enzymes of
trimethyllysine conversion to trimethylaminobutyrate. Fed Proc
37. Seidell JC, Muller DC, Sorkin JD, Andres R: Fasting respiratory
exchange ratio and resting metabolic rate as predictors of weight
gain: the Baltimore Longitudinal Study on Aging. Int J Obes Relat
Metab Disord 16:667–674, 1992.
38. Blaak EE, Saris WHM: Substrate oxidation, obesity and exercise
training. Best Pract Res Clin Endocrinol Metab 6:667–78, 2002.
39. Zurlo F, Lillioja S, Esposito-Del Puente A, Nyomba BL, Raz I,
Saad MF, Swinburn BA, Knowler WC, Bogardus C, Ravussin E:
Low ratio of fat to carbohydrate oxidation as predictor of weight
gain: study of 24-h RQ. Am J Physiol 259:E650–E657, 1990.
40. Kant AK: Interaction of body mass index and attempt to lose
weight in a national sample of US adults: association with reported
food and nutrient intake, and biomarkers. Eur J Clin Nutr 57:249–
41. Moor de Burgos A, Wartanowicz M, Ziemlanski S: Blood vitamin
and lipid levels in overweight and obese women. Eur J Clin Nutr
42. Naylor GJ, Grant L, Smith C. A double blind placebo controlled
trial of ascorbic acid in obesity. Nutr Health 4:25–28, 1985.
43. Stock MJ: Gluttony and thermogenesis revisited. Int J Obes 23:
44. Sivenius K, Niskanen L, Laakso M, Uusitupa M: A deletion in the
alph2B-adrenergic receptor gene and autonomic nervous function
in central obesity Obes Res 11:962–970, 2003.
45. de Jonge L, Bray GA: The thermic effect of food and obesity: a
critical review. Obes Res 5: 622–631, 1997.
46. Segal KR, Albu J, Chun A, Edano A, Legaspi B, Pi-Sunyer FX:
Independent effects of obesity and insulin resistance on postpran-
dial thermogenesis in men. J Clin Invest 89:824–833, 1992.
47. Maffeis C, Schutz Y, Zoccante L, Micciolo R, Pinelli L: Meal-
induced thermogenesis in lean and obese prepubertal children.
Am J Clin Nutr 57:481–485, 1993.
48. Karst H, Steiniger J, Noack R, Steglich HD: Diet-induced thermo-
genesis in man: thermic effects of single proteins, carbohydrates
and fats depending on their energy amount. Ann Nutr Metab
49. Johnston CS, Day CS, Swan PD: Postprandial thermogenesis is
increased 100% on a high-protein, low-fat diet versus and high-
carbohydrate, low-fat diet in healthy, young women. J Am Coll
Nutr 21:55–61, 2002.
50. Luscombe ND, Clifton PM, Noakes M, Parker B, Wittert G:
Effects of energy-restricted diets containing increased protein on
weight loss, resting energy expenditure, and the thermic effect of
feeding in type 2 diabetes. Diabetes Care 25:652–657, 2002.
51. Johnston CS, Tjonn SL, Swan PD: High-protein, low-fat diets are
effective for weight loss and favorably alter biomarkers in healthy
adults. J Nutr 134:586–591, 2004.
52. Anderson GH, Moore SE: Dietary proteins in the regulation of
food intake and body weight in humans. J Nutr 134:974S–979S,
53. de Graaf C, Blom WA, Smeets PA, Stafleu A, Hendriks HF:
Biomarkers of satiation and satiety. Am J Clin Nutr 79:946–61,
54. Crovetti R, Porrini M, Santangelo A, Testolin G: The influence of
thermic effect of food on satiety. Eur J Clin Nutr 52:482–488,
55. Hall WL, Millward DJ, Long SJ, Morgan LM: Casein and whey
exert different effects on plasma amino acid profiles, gastrointes-
tinal hormone secretion and appetite. Br J Nutr 89:239–48, 2003.
56. Skov AR, Toubro S, Ronn B, Holm L, Astrup A: Randomized trial
on protein versus carbohydrate in ad libitum fat reduced diet for the
treatment of obesity. Int J Obes 23:528–536, 1999.
57. Araya H, Hills J, Alvina M, Vera G: Short-term satiety in pre-
school children: a comparison between high protein meal and a
high complex carbohydrate meal. Int J Food Sci Nutr 51:119–124,
58. Popitt SD, McCormack D, Buffenstein R: Short-term effects of
macronutrient preloads on appetite and energy intake in lean
women. Physiol Behav 64:279–285, 1998.
59. Foster GD, Wyatt HR, Hill JO, McGuckin BG, Brill C, Moham-
med BS, Szapary PO, Rader DJ, Edman JS, Klein S: A randomized
trial of a low-carbohydrate diet for obesity. N Engl J Med 348:
60. Samaha FF, Iqbal N, Seshadri P, Chicano KL, Daily DA, McGrory
J, Williams T, Williams M, Gracely EJ, Stern L: A low-
carbohydrate as compared with a low-fat diet in severe obesity.
N Engl J Med 348:2074–2081, 2003.
Strategies for Healthy, Effective Weight Loss
164 VOL. 24, NO. 3
61. Centers for Disease Control and Prevention (CDC): Trends in
intake of energy and macronutrients—United States, 1971–2000.
MMWR Morb Mortal Wkly Rep 53:80–82, 2004.
62. Robers SB: High-glycemic index foods, hunger, and obesity: is
there a connection? Nutr Rev 58:163–169, 2000.
63. Spieth LE, Harnish JD, Lenders CM, Raezer LB, Pereira MA,
Hangen SJ, Ludwig DS: A low-glycemic index diet in the treat-
ment of pediatric obesity. Arch Pediatr Adolesc Med 154:947–951,
64. Ludwig DS: Novel treatments for obesity. Asia Pac J Clin Nutr
65. Warren JM, Henry CJ, Simonite V: Low glycemic index breakfasts
and reduced food intake in preadolescent children. Pediatrics 112:
66. Johnston CS, Kim CM, Buller AJ: Vinegar improves insulin sen-
sitivity to a high-carbohydrate meal in subjects with insulin resis-
tance or type 2 diabetes. Diabetes Care 27:281–282, 2004.
67. Ogawa N, Satsu H, Watanabe H, Fukaya M, Tsukamoto Y, Miy-
amoto Y, Shimizu M: Acetic acid suppresses the increase in
disaccharidase activity that occurs during culture of Caco-2 cells.
J Nutr 130:507–513, 2000.
68. Fushimi T, Tayama K, Fukaya M, Kitakoshi K, Nakai N, Tsuka-
moto Y, Sato Y: Acetic acid feeding enhances glycogen repletion
in liver and skeletal muscle of rats. J Nutr 131:1973–1977, 2001.
69. Nesher R, Anteby E, Yedovizky M, Warwar N, Kaiser N, Cerasi E:
Beta-cell protein kinases and the dynamics of the insulin response
to glucose. Diabetes 51 Suppl 1:S68–73, 2002.
70. Tong BC, Barbul A: Cellular and physiological effects of arginine.
Mini Rev Med Chem 4:823–832, 2004.
71. Sabate J: Nut consumption and body weight. Am J Clin Nutr 78(3
Suppl): 6475–6505, 2003.
72. Garcia-Lorda P, Megias Rangil I, Salas-Salvado J: Nut consump-
tion, body weight and insulin resistance. Eur J Clin Nutr 57(Suppl
1): S8–S11, 2003.
Received July 27, 2004; revision accepted February 8, 2005.
Strategies for Healthy, Effective Weight Loss
JOURNAL OF THE AMERICAN COLLEGE OF NUTRITION165