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Fat and carbohydrate overfeeding in humans: Different effects on energy storage



Both the amount and composition of food eaten influence body-weight regulation. The purpose of this study was to determine whether and by what mechanism excess dietary fat leads to greater fat accumulation than does excess dietary carbohydrate. We overfed isoenergetic amounts (50% above energy requirements) of fat and carbohydrate (for 14 d each) to nine lean and seven obese men. A whole-room calorimeter was used to measure energy expenditure and nutrient oxidation on days 0, 1, 7, and 14 of each overfeeding period. From energy and nutrient balances (intake-expenditure) we estimated the amount and composition of energy stored. Carbohydrate overfeeding produced progressive increases in carbohydrate oxidation and total energy expenditure resulting in 75-85% of excess energy being stored. Alternatively, fat overfeeding had minimal effects on fat oxidation and total energy expenditure, leading to storage of 90-95% of excess energy. Excess dietary fat leads to greater fat accumulation than does excess dietary carbohydrate, and the difference was greatest early in the overfeeding period.
Am J Clin Nutr 1995;62:19-29. Printed in USA. © 1995 American Society for Clinical Nutrition 19
Fat and carbohydrate overfeeding in humans: different
effects on energy storage3
Tracy J Horton, Holly Drougas, Amy Brachey, George W Reed, John C Peters, and James 0 Hill
ABSTRACT Both the amount and composition of food eaten
influence body-weight regulation. The purpose of this study was to
determine whether and by what mechanism excess dietary fat leads
to greater fat accumulation than does excess dietary carbohydrate.
We overfed isoenergetic amounts (50% above energy require-
ments) of fat and carbohydrate (for 14 d each) to nine lean and
seven obese men. A whole-room calorimeter was used to measure
energy expenditure and nutrient oxidation on days 0, 1, 7, and 14
of each overfeeding period. From energy and nutrient balances
(intake-expenditure) we estimated the amount and composition of
energy stored. Carbohydrate overfeeding produced progressive
increases in carbohydrate oxidation and total energy expenditure
resulting in 75-85% of excess energy being stored. Alternatively,
fat overfeeding had minimal effects on fat oxidation and total
energy expenditure, leading to storage of 90-95% of excess en-
ergy. Excess dietary fat leads to greater fat accumulation than does
excess dietary carbohydrate, and the difference was greatest early
in the overfeeding period. Am J Clin Nutr 1995;62:19-29.
KEY WORDS Obesity, nutrient partitioning, nutrient bal-
ance, energy balance, diet composition
Obesity is a major health problem affecting more than 34
million Americans (1). An understanding of how obesity de-
velops is necessary to develop strategies for its prevention and
treatment. This could be facilitated by a better ability to iden-
tify individuals who are at risk of developing obesity. Such
individuals may be characterized by a metabolic and/or a
behavioral susceptibility to weight gain (2). Hill et al (2)
proposed that behavioral susceptibility to obesity creates the
opportunity for positive energy balance to occur (eg, overeat-
ing and underexercising), whereas metabolic susceptibility to
obesity determines the metabolic fate of the excess energy
when positive energy balance occurs. For example, an individ-
ual with a high metabolic susceptibility to obesity would be
inclined to accumulate more body fat but less glycogen during
periods of positive energy balance than would an individual
with a lesser metabolic susceptibility to obesity.
There are substantial data to suggest that individuals differ in
their behavioral response to different environmental condi-
tions. For example, many human subjects consume more total
energy on a high- than on a low-fat diet (3-6). Similarly, it is
unlikely that all subjects will show the same gain in body
weight and body fat when subjected to positive energy balance.
This was demonstrated in the overfeeding studies of Sims et al
(7) and Bouchard et al (8). Contrary to the concept of “luxu-
skonsumption”, many recent studies have demonstrated that
the majority of excess energy is stored and not expended as
heat during overfeeding (9-1 1). However, differences between
energy stored and energy expended and differences in the
composition of the fuel mixture oxidized may lead to important
individual differences in the metabolic fate of excess energy
under conditions of positive energy balance. These differences
could stem from differences in partitioning of excess energy
into 1) storage compared with expenditure, 2) storage in adi-
pose tissue compared with storage in lean body mass, and 3)
storage in visceral compared with peripheral adipose tissue.
Diet composition clearly has an important influence on
body-weight regulation. The strongest evidence for this comes
from rodent studies in which high-fat diets have been shown to
produce obesity independently of total energy intake (12, 13).
In human subjects, diet composition can influence total energy
intake (3-6) and can alter nutrient balance without changing
total energy expenditure (14, 15). In response to acute changes
in diet composition, it has been shown that human subjects
increase carbohydrate oxidation and total energy expenditure in
response to excess carbohydrate (16), but fail to increase fat
oxidation or energy expenditure in response to excess fat
(17-19). This suggests that under conditions of excess, dietary
fat leads to greater fat accumulation than does dietary carbo-
Energy and nutrient balances can be assessed during dietary
challenges by combining indirect calorimetry with dietary con-
trol. A major advantage of this technique is that changes in
body nutrient stores can be detected well before they could be
measured with available techniques for assessing body com-
position. In this study we used this approach to determine how
lean and obese men partitioned excess energy provided as
carbohydrate or fat.
IFrom the Center for Human Nutrition, University of Colorado Health
Sciences Center, Denver; the Department of Pediatrics and Preventive
Medicine, Vanderbilt University, Nashville, TN; and the Procter & Gamble
Co, Cincinnati.
2Supported by NIH grants DK42549 and RR00095.
3Address reprint requests to TJ Horton, Center for Human Nutrition,
Box C225, University of Colorado Health Sciences Center, Denver, CO
Received June 15, 1994.
Accepted for publication February 16, 1995.
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Male subjects aged 18-46 y were recruited for the study.
Subjects were excluded if they smoked or if they had a history
of diabetes, cardiovascular disease, or major health problems
other than obesity. Highly trained individuals and subjects
habitually consuming a very-low- or very-high-fat diet were
excluded. Nine lean (90-1 10% of ideal body weight as deter-
mined by the 1983 Metropolitan Life Insurance Tables; 20) and
seven obese (130-180% of ideal body weight) subjects com-
pleted the study. The protocol was approved by the Committee
for the Protection of Human Subjects of Vanderbilt University.
Table 1 shows the descriptive characteristics of study par-
ticipants and their estimated baseline energy requirements.
Lean subjects had a significantly greater maximum oxygen
consumption (VO2max) than obese subjects. Initial body
weight, percent body fat, fat-free mass (FFM), fat mass (FM),
and age were all significantly greater in the obese group than in
the lean group. Similarly, obese subjects had higher baseline
energy requirements and lower levels of physical activity. The
percent fat in the baseline diet did not differ between lean and
obese subjects.
Experimental design
Each subject completed two separate 14-d periods of over-
feeding. Each overfeeding period was preceded by 1 wk of
consuming a baseline (maintenance) diet. Excess energy was
set at 50% above baseline energy intake and was provided
entirely as fat during one period and as carbohydrate during the
other. Subjects spent 24-h in a whole-room indirect calorimeter
to determine energy and nutrient balances on day 7 of baseline
(which corresponds to day 0 of the protocol) and on days 1, 7,
and 14 of each overfeeding period. This allowed us to estimate
how much excess energy was expended compared with stored,
as well as the form of stored energy in the body. Physical
Subject characteristics’
Lean subjects
Obese subjects
Age (y) 28.6 ±5.4 37.6 ±532
Height (m) 1.79 ±0.07 1.79 ±0.03
Weight (kg) 68.4 ±9.9 103.9 ±10.92
VO2 max
(mL kg’ .mm’) 41.7 ±4.7 31.5 ±3.8
Percent body fat (%) 21.4 ±3.2 35.4 ±5.22
Fat mass (kg) 14.7 ± 3.2 37.0 ± 8.22
Fat-free mass (kg) 53.8 ± 7.8 66.9 ± 6.22
Body mass index (kg/m2) 21.3 ±1.5 32.3 ±2.72
Baseline energy
requirements (kJ/d) 11 123 ±961 13 965 ± 8362
Percent fat in baseline
diet (%) 36 ±3 33 ±2.5
Baseline activity (Caltrac
units)3 345 ±33 237 ±102
‘1 ± SEM.
2Significantly different from lean, P<0.01.
3One caltrac unit =0.5 METS (one MET is equal to the oxygen
consumption of a seated individual at rest, =3.5 mL .kg1 .mint).
activity was held constant throughout the study as described
below. Sample diets are shown in Appendix A.
Determination of baseline energy requirements
We took great care to accurately assess usual energy intake
during baseline to ensure that the degree of overfeeding was
similar for each subject. After recruitment, each subject com-
pleted a 14-d weighed diet diary to estimate their usual food
intake. Subjects met with a dietitian and were provided with a
set of weighing scales and given detailed instructions of how to
accurately complete the diet record by describing types of food
consumed and to record appropriate weights. Periodic checks
were made to ensure that subjects were completing the record
in the required manner.
One week after completing the diet records, subjects began
the first dietary control phase. For 1 wk, subjects were fed a
baseline diet reflecting their self-reported habitual intake of
energy, fat, carbohydrate, and protein, as assessed from their
diet records. The diets consisted, as much as possible, of the
foods usually consumed by the subjects and were delivered in
a pattern approximating the subject’s usual pattern. Additional
food modules (838 kJ), of the same nutrient composition as the
diet, were available on request. Use of these modules was
previously described (3). This approximated ad libitum feed-
ing. All food was provided and prepared by the Clinical Re-
search Center (CRC) metabolic kitchen, and subjects were
required to consume at least one meal at the CRC each day. All
other food was packaged to be taken away and eaten in the
subject’s home or workplace. Body weight was measured daily
during the baseline diet to confirm weight stability. In response
to trends to decrease body weight (there were no trends to
increase body weight), the dietitian met with the subject to alter
the diet plan as needed to reachieve weight stability.
Each subject’s usual level of physical activity was estimated
by using Caltrac accelerometers (Hemokinetics Inc, Madison,
WI). Each subject wore an accelerometer for 7 d before begin-
fling the overfeeding period. The accelerometer clips to the
waistband or pocket at the front of the body and measures
whole-body acceleration. It can be programmed to measure
movement in units, where 1 unit =2.0 METS. One MET is
equal to the oxygen consumption of a seated individual at rest,
which is “‘3.5 mL kg1 .min (21). Other activities that the
accelerometer cannot monitor (swimming, cycling, calisthen-
ics, weight training, etc) were recorded separately in terms of
type of activity, intensity, and duration. The Caltrac values
were averaged over the initial 7-d period, including estimates
of the unit equivalent of other activity [(METS/mm activity X
duration) X 0.5]. This value was used to design an appropriate
activity routine while the subject stayed in the whole-room
calorimeter and to check for possible changes in activity during
the overfeeding periods. Each subject spent the last baseline
day in the whole-room calorimeter eating at his usual energy
intake and undergoing a usual physical activity routine. It is
obviously not possible to exactly reproduce usual physical
activity in a room calorimeter, but for each subject, activity in
the calorimeter was constant during each stay and in the range
of usual activity.
Oveifeeding: phase 1
Immediately after the baseline week, subjects began the first
overfeeding period, which lasted for 14 d. Subjects were fed a
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0CHO Overfeeding
.Fat Overfeeding
00 7 14
Time (days)
FIGURE 1. Changes in body weight during and for 21 d after fat and
carbohydrate (CHO) overfeeding in 16 male subjects.
diet providing 150% of their energy intake during the baseline
week. The additional 50% of energy was given as either all fat
or all carbohydrate. All food was provided by the CRC. Daily
energy expenditure and nutrient oxidation were measured in
the whole-room calorimeter on days 1, 7, and 14 of overfeed-
ing. Subjects did not have access to food modules during the
overfeeding periods. Activity was monitored (with Caltrac
accelerometers) during the last 7 d of overfeeding.
Overfeeding: phase 2
A 4-wk washout period separated the first and second phases
of the experimental period. During the first 3 wk subjects were
free to consume whatever food they chose. In the fourth week
subjects were fed the diet reflecting their habitual intake. The
second overfeeding phase mirrored the first exactly except that
the form of the excess energy (fat or carbohydrate) was
switched. The diets were administered in a randomized cross-
over design.
Dependent measures
A treadmill test to exhaustion, using the protocol of Bruce et
al (21), was used to estimate maximal oxygen uptake of sub-
jects. Body weight and height were measured on a Platform
Detecto scale (Webb City, MO) and graduated wall meter,
respectively. Body composition was estimated from body den-
sity by using underwater weighing to determine body volume,
with simultaneous measurement of residual lung volume with
the closed-circuit, nitrogen-dilution technique (22). Percent
body fat was estimated from body density by using the revised
equation of Brozek et al (23). Body weight was measured on
each morning before entering the metabolic chamber and body
composition was determined immediately before and after each
overfeeding period.
Blood was taken from each subject to determine circulating
concentrations of free fatty acids, insulin, and glucose. Samples
were taken after an overnight fast during the week before
beginning each overfeeding period and at the end of each
overfeeding period.
Total daily energy expenditure and substrate oxidation were
measured in a whole-room indirect calorimeter, located in the
CRC, as described previously (3, 14, 24). Subjects entered the
chamber at 0800 and left the following day at 0700. Results
were extrapolated to 24 h. Oxygen consumption and carbon
dioxide production were determined from the flow rate and
differences in gas concentrations between entering and exiting
air. Values were corrected for temperature, barometric pres-
sure, and humidity. Energy expenditure was calculated from
oxygen consumption and respiratory quotient (RQ). The oper-
ation of the chamber was controlled by a personal computer by
using a software program written in TURBO C. The program
was based on calculations described by Jequier et al (25).
Values for all indexes were averaged over 2-mm intervals and
recorded in a data file. An activity button system was linked to
the computer. This was used to mark events (eg, sleep, meals,
exercise) and the appropriate button was pressed before com-
mending and on completion of an event.
Energy expenditure due to activity was estimated by using a
mechanical-force platform serving as the chamber floor. The
platform detects vertical and horizontal displacement of the
center of gravity and is capable of detecting displacements as
small as 50 g. This system was described in detail elsewhere
and has been shown to be accurate to within 1% (26). The
accelerometer was worn during each chamber stay and subjects
performed a prescribed amount of walking and stepping exer-
cises, aimed at mimicking the total amount of activity usually
performed outside the chamber. Walking was performed at a
rate of 8 m/10 s and stepping at 4 steps/lO s. The number and
duration of exercise bouts was individually adjusted to achieve
a value similar to the average accelerometer reading. Activity
was scheduled at 1030, 0130, 1600, and 1900 when necessary.
Subjects collected all of their urine while in the calorimeter.
Aliquots were analyzed for total nitrogen content (27).
Data analysis
Results were analyzed by using repeated-measures analysis
of variance (ANOVA) with obesity status as a grouping factor
(lean compared with obese). Diet (overfeeding fat compared
with overfeeding carbohydrate) and time (measures at baseline
and days 1, 7, and 14 for each diet) were repeated-measures
factors. A nonparametric Mann-Whitney Utest was used to
establish any differences in initial subject characteristics. SAS
statistical software (SAS Institute, Cary, NC) was used for the
Body weight and body composition
Body weight increased significantly after both fat and car-
bohydrate overfeeding (P <0.001), with the greatest increase
occurring between days 1 and 7 (Figure 1). Baseline body
weight was significantly positively correlated with weight gain
during the carbohydrate (r =0.55, P <0.05) but not the
high-fat (r =0.34, NS) overfeeding. At the end of the washout
period, body weight had declined to near prestudy values. The
body weights for lean subjects before the first and second
21 28 35
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Day 1 Day 7 Day 14
Changes in body composition’
 1.0
Cl) 0.9#{149}
Ot 0.8
 0.6
C 0.3
E 0.2
0. 0.0
FIGURE 3. The proportion of excess energy stored in the body is
shown for fat and carbohydrate (CHO) overfeeding in 16 male subjects.
The proportion of excess stored is calculated as (total excess minus the
measured increase in daily energy expenditure)/total excess.
overfeeding periods were 68.1 ± 3.3 and 68.8 ± 7.3 kg,
respectively. For obese subjects the weights before the first and
second overfeeding periods were 103.7 ± 9.1 and 105.1 ± 9.1
kg, respectively.
Body-composition changes, as determined by underwater
weighing, are shown in Table 2. FM and FFM increased
significantly with carbohydrate overfeeding (P <0.02) and fat
overfeeding (P <0.001). There were no significant differences
between diets and/or groups in body weight or body-composi-
tion changes. The percentage of weight gained as FM (54-
56%) or FFM (44-46%) was similar between diets and groups.
Note, however, that the changes in body composition were very
small and near the detection limits of our technique. The study
was not designed to produce significant alterations in body
composition, but rather to predict changes in body stores of
protein, carbohydrate, and fat from measures of intake and
oxidation of each.
Energy balance
The increase in energy expenditure caused by fat overfeed-
ing was not statistically significant. With carbohydrate over-
feeding there was a significant increase in energy expenditure
on days 7 and 14 (Figure 2). We assumed that excess energy
not expended was stored in the body. Figure 3 shows the
estimated energy stored as a proportion of excess ingested
 energy. This allows for differences between groups and mdi-
viduals in the absolute excess energy consumed. Overall, a
greater proportion of the excess energy was stored when the
excess was given as fat compared with carbohydrate (P <
0.002). However, there was a significant day Xdiet interaction
(P <0.05) so that energy storage remained constant over time
with fat but not carbohydrate overfeeding. With fat overfeeding
91-95% of the excess energy was stored throughout the study.
Although =90% of the excess energy was stored on the first
day of carbohydrate overfeeding, it declined significantly on
days 7 and 14, with 77% and 83% of the excess being stored,
respectively (P <0.04).
Nutrient balance
Nutrient oxidation
The observed changes in nutrient oxidation were very dif-
ferent between carbohydrate and fat overfeeding. Figures 4
and 5show changes in daily oxidation rates of protein, carbo-
All subjects
Carbohydrate overfeeding
Body fat (%) 0.69 ±0.62 0.77 ±0.31 0.72 ±0.37
Fat mass (kg) 1.09 ±0.49 2.06 ± 0.232 1.48 ±0.322
Fat-free mass (kg) 1.38 ±0.52 1.41 ±56 1.40 ±0.372
Fat overfeeding
zBody fat (%) 0.93 ±0.28 0.80 ±0.22 0.88 ±0.182
zFat mass (kg) 1.21 ± 0.29 1.90 ± 0.392 1.51 ± 0.242
Fat-free mass (kg) 1.10 ±0.25 1.08 ±0.192 1.09 ± 0.162
‘5 ± SEM.
2Significantly different from zero.
CHO overfeeding
Fat overfeeding
FIGURE 2. The increase in total daily energy expenditure above
baseline (day 0) is shown for each overfeeding period in 16 male subjects.
hydrate, and fat during each overfeeding period. Protein oxi-
dation decreased over time during both overfeeding periods
(P <0.05), with a trend for this to be greater with carbohydrate
than fat overfeeding (P <0.08). Fat overfeeding produced only
minimal changes in fat and carbohydrate oxidation whereas
carbohydrate overfeeding produced significant changes in both
(P <0.001). During carbohydrate overfeeding there was a
rapid increase in carbohydrate oxidation and a significant de-
dine in fat oxidation.
Nutrient storage
The accumulation of energy, protein, fat, and carbohydrate
was estimated from the balance of each (Figure 6). Energy
balance was near zero at baseline and became positive during
both overfeeding periods. Carbohydrate balance was positive
and fat balance was negative at baseline. This was likely due to
the inability to exactly reproduce amount and type of usual
0CHO Overfeeding
.Fat Overfeeding
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Protein Oxidation
Protein Oxidation
ID 8
-) 6
 6
Carbohydrate Oxidation
12 -
> 10-
 8-
14 -
12 -
10 -
 6-
Fat Oxidation
>, 10
t5 8
Fat Oxidation
0 1 7 14
0 1 7
FIGURE 4. Total daily oxidation rates of protein, carbohydrate, and fat
at baseline and during the carbohydrate overfeeding period for 16 male
physical activity in the calorimeter. Protein balance increased
over time with both overfeeding diets (day effect, P<0.03).
Because fat overfeeding had minimal effects on fat and carbo-
hydrate oxidation, the majority of the excess dietary fat was
stored as body fat. This remained constant throughout the
overfeeding period. Fat accumulation was initially lower and
carbohydrate accumulation higher with carbohydrate than with
fat overfeeding (P <0.001). However, with the progressive
decline in fat oxidation, fat storage increased so that on day 14
there was no difference between diets in fat or carbohydrate
>1 10.
. 8
 6
Carbohydrate Oxidation
FIGURE 5. Total daily oxidation rates of protein, carbohydrate, and fat
at baseline and during the fat overfeeding period for 16 male subjects.
Figure 7 shows nutrient storage expressed relative to the
total excess energy. This takes into account the different abso-
lute amounts of excess energy fed to subjects and groups.
Relative fat balance was significantly greater and carbohydrate
balance less during fat than during carbohydrate overfeeding
(P <0.001). However, relative fat balance during carbohydrate
overfeeding increased significantly over time (P <0.05),
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2000 Energy Balance
-) 500
0-500 0 2 4 6 8 10 12 14 16
Time (days)
Carbohydrate Balance
CHO overfeeding
Fat Overfeeding
0 2 4 6 8 10 12 14 16
Time (days)
Fat Balance
0 2 4 6 8 10121416 0 2 4 6 8 10121416
Time (days) Time (days)
FIGURE 6. Daily balances of energy, protein, carbohydrate (CHO), and fat are shown for fat and CHO overfeeding for 16 male subjects. Daily balances
were calculated as total intake minus total oxidation of each nutrient.
Protein Balance
achieving a similar amount of fat storage by day 14 as with fat
overfeeding day 14.
Lean-obese differences
We examined differences in the response to overfeeding
between lean and obese subjects. In general, both groups re-
sponded similarly to overfeeding, keeping in mind that over-
feeding was based on energy requirements, so that obese sub-
jects received more total energy during overfeeding than lean
subjects. There were no significant differences between groups
in energy or nutrient balance, although the individual differ-
ences in these measures were large. Obese subjects, however,
had a higher average RQ and oxidized proportionally more
carbohydrate than lean subjects during both overfeeding pen-
ods (P <0.007).
Fasting concentrations of insulin, glucose, and free
fatty acids
Table 3 shows the fasting concentrations of insulin, glucose,
and free fatty acids on day 0 and on the morning of day 15 of
each overfeeding period. Values are shown separately for lean
and obese subjects. In general, insulin concentrations were
higher and free fatty acid concentrations were lower on the
morning of day 15 after carbohydrate overfeeding than on day
15 after fat ovenfeeding. Glucose concentrations did not vary
significantly with either diet.
Results of this study demonstrate that diet composition can
have important effects on energy expenditure and body energy
storage when subjects are in positive energy balance. Greater
than 75% of the excess energy consumed by our subjects was
stored in the body, not expended, regardless of the composition
of the excess. Other recent overfeeding studies have reached
the same conclusion (9-11). However, our results demonstrate
that excess carbohydrate affects energy and nutrient balances
differently than does excess fat. We found that for equivalent
amounts of excess energy, fat leads to more body fat accumu-
lation than does carbohydrate.
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. a
LU -#{176}
 04
FIGURE 7. Storage of each nutrient during fat and carbohydrate (CHO)
overfeeding is expressed as a percent of total excess energy stored in each
of 16 male subjects. This accounts for differences in intake of each nutrient
between subjects.
2 4 6 8 10 12 14 16
Time (days)
oCHO overfeeding
#{149}Fat Overfeeding
Using our whole-room calorimeter, we were able to demon-
strate different effects of excess fat compared with excess
carbohydrate on energy expenditure, substrate oxidation, and
nutrient balance. It is generally accepted that dietary carbohy-
drate promotes its own oxidation, whereas dietary fat does not
(16-19). This was clearly the case in the present study. Four-
teen days of fat overfeeding produced no significant changes in
fat oxidation or total daily energy expenditure. The small
increase in energy expenditure with fat overfeeding can be
explained by an increased thermic effect of food (TEF) and a
slight increase in body mass. By comparing fat intake with fat
oxidation, we found that the degree of positive fat balance
during fat ovenfeeding was equal to 90-95% of the total excess
energy consumed. Moreover, because fat ovenfeeding hardly
increased substrate oxidation, this high storage efficiency con-
tinued throughout the study.
Carbohydrate overfeeding produced a very different picture.
Progressive increases in both carbohydrate oxidation and total
energy expenditure were seen with carbohydrate overfeeding.
Both were evident on the first day of overfeeding and reached
maximum by day 7. The increased energy expenditure seen
with carbohydrate overfeeding was approximately double that
which could be explained by the combination of increased TEF
and increased body mass. Thus with carbohydrate overfeeding,
more of the excess energy was oxidized and less stored in the
body than was seen during fat overfeeding.
We anticipated that sustained carbohydrate overfeeding
would lead to accumulation of body fat due to de novo lipo-
genesis. Although the issue of whether carbohydrate overfeed-
ing led to de novo lipogenesis in tissues such as the liver cannot
be definitively determined in this study, the calorimetry data
indicate that net lipogenesis from carbohydrate did not occur.
There were short periods during some carbohydrate overfeed-
ing days in which the nonprotein RQ was >1 .0, suggesting that
some de novo lipogenesis occurred. It is impossible under
conditions of this study to accurately quantify this de novo
lipogenesis. Other investigators using isotopic techniques have
reported that de novo lipogenesis in human subjects is not a
major way to accumulate body fat stores (28). It may, however,
be slightly higher in hypeninsulinemic obese subjects than in
lean subjects and may depend on the type of carbohydrate in
the diet (29). From these results, however, we conclude that
positive fat balance was due to a decrease in fat oxidation
accompanying the increase in carbohydrate oxidation. By day
14 of the overfeeding period, the proportion of total stored
energy that was stored as body fat did not differ between the
two diets.
When the total 14-d overfeeding period is considered (ie,
areas under the curve for total energy and fat), substantially
more total energy and more total fat is stored when the excess
is fat compared with carbohydrate. Even on day 14, when the
portion of the excess stored as fat was not significantly differ-
ent between the two diets, total energy expenditure was higher
with carbohydrate overfeeding so that the total stored energy
was less than with fat overfeeding.
Other investigators have demonstrated in a single meal (18,
19) and over an entire day (17) that excess fat does not increase
fat oxidation. These results extend that work to show that fat
has only a slight effect on fat oxidation over the course of a
2-wk ovenfeeding period. This is consistent with the notion that
increases in fat oxidation occur secondary to increases in the
body fat mass (30). The change in body fat mass in the present
study was small. The effects of excess carbohydrate on energy
and nutrient balance require further explanation. In particular,
the extent of fat storage during carbohydrate overfeeding de-
pended on the extent to which fat oxidation was inhibited.
As might be expected, carbohydrate overfeeding was asso-
ciated with a small increase in overnight fasting plasma insulin
and a decrease in nonestenified fatty acids, whereas fat over-
feeding did not affect these measures. These responses are
consistent with the observed pattern of changes in substrate
oxidation in which carbohydrate overfeeding stimulated carbo-
hydrate utilization while suppressing fat oxidation. Fat over-
feeding did not noticeably alter fuel metabolism. The lack of a
more substantial change in these measures, especially with
carbohydrate overfeeding, is not surprising.
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Fasting plasma insulin and free fatty acid (FFA) concentrations’
Lean subjects Obese subjects
CHO overfeeding Fat overfeeding CHO overfeeding Fat overfeeding
Day 0 Day 15 Day 0 Day 15 Day 0 Day 15 Day 0 Day 15
Insulin (pmolfL)
Glucose (mmol/L)
132 ± 50
4.9 ±0.2
207 ± 110
4.8 ±0.1
228 ±120
4.6 ± 0.2
108 ± 312
5.0 ±0.22
199 ±42
5.0 ±0.2
332 ±10923
4.9 ±0.3
172 ±77
4.9 ±O.i
278 ±7023
5.0 ± 0.1
FFA(mgfL) 90±13 43±72 88±15 58±112 86±15 54±7 80±20 74±16
Ii ±SEM.
2Significantly different from day 0, P<0.05.
3Significantly different from lean subjects, P<0.05.
Whereas lean and obese subjects responded similarly, in
general, to the overfeeding periods, there was one important
difference. Regardless of the composition of the overfeeding
diet, obese subjects oxidized proportionally more carbohydrate
and less fat than did lean subjects. We have proposed that
subjects who show the greatest reliance on carbohydrate oxi-
dation during perturbations to energy balance may be most at
risk to develop obesity (2, 3). Others have also suggested that
a high RQ may be associated with susceptibility to obesity
(31). Because the obese subjects in this study were already
obese, it is impossible to determine whether a high reliance on
carbohydrate oxidation in response to overfeeding contributed
to obesity development. It could clearly contribute to mainte-
nance of the obese state. It may be hypothesized that individual
differences in RQ after overfeeding predict susceptibility to
obesity. This has been demonstrated in rats, in whom a high
RQ in response to a high-fat diet predicts subsequent weight
gain (32).
We believe it is important to consider individual differences
in the influence of diet composition on body-weight regulation.
Individual differences in fat compared with carbohydrate oxi-
dation may underlie differences in fat storage during overfeed-
ing. Much longer periods of overfeeding may be necessary to
see such individual differences during fat overfeeding, because
such differences may occur secondary to substantial changes in
body fat mass (30). However, a 14-d period appears to provide
a good opportunity to study individual differences in response
to carbohydrate overfeeding. For example, it would be inter-
esting in future studies to assess whether the lean subjects who
showed the greatest reduction in fat oxidation during carbohy-
drate overfeeding would be more metabolically susceptible to
develop obesity than those with a lesser decline. In support of
this speculation, Bouchard et al (8) reported large differences
in the amount and composition of weight gained during exper-
imental overfeeding of mixed diets. Those subjects with the
highest oxidative capacity of skeletal muscle (as assessed by
citrate synthase activity) had the lowest ratio of fat to lean mass
in weight gain (33). Similar, we (34) and others (35) have
demonstrated that the fiber composition of skeletal muscle may
predict development of obesity.
In evaluating the role of diet composition on body-weight
regulation, the plane of energy balance (ie, positive, negative,
or zero) must be considered. Whereas fat and carbohydrate
clearly differ in effects on energy expenditure and substrate
oxidation during overfeeding, such differences may not be as
apparent when overfeeding is not present. For example, when
fed high- compared with low-fat diets containing a fixed
amount of energy estimated to provide maintenance energy
requirements, human subjects rapidly adjust substrate oxida-
tion to substrate intake, with no significant differences in total
energy expenditure (14). Leibel et al (36) found no difference
in body weight when subjects were fed maintenance levels of
diets differing in fat content. Similarly, differences in diet
composition during energy restriction would be expected to
have only slight effects on energy and nutrient balance (37).
This illustrates that obesity cannot develop without an initial
period in which energy intake exceeds energy expenditure and
that overfeeding is an important tool for studying obesity
There are several reasons in general to be concerned about
high-fat diets. Such diets are much more likely to be associated
with overeating than are diets high in carbohydrate (3-6).
Second, excess energy as fat is stored more efficiently than is
excess energy as carbohydrate (12). Finally, diets high in fat
may have a negative impact on health independently of obesity
We found the greatest differences between fat and carbohy-
drate overfeeding early in the overfeeding period, before car-
bohydrate overeating produced substantial decreases in fat
oxidation. From these results we can speculate that if obesity
arises as a result of long periods of sustained overeating, the
composition of excess energy would have relatively small
effects on fat storage, with slightly more fat stored if the excess
is high in fat rather than in carbohydrate. However, if obesity
arises as a result of multiple periods of overeating over a single
day or over a few days, the difference in fat storage would be
greater with excess fat than with excess carbohydrate. Future
work will be necessary to determine whether the same pattern
of differences seen in this study would be seen during a second
or third bout of overfeeding.
It is important to note that in this study we required subjects
to eat all excess food during periods of overfeeding. There are
data suggesting that diets high in carbohydrate are more sati-
ating than are diets high in fat (3-5), and that voluntary intake
is likely to be lower with high-carbohydrate than with high-fat
diets. However, some people may be poor regulators of food
intake, and these individuals should be aware that intake of
low-fat foods also needs to be regulated because body fat
accumulation can result from overconsumption of these foods.
In summary, this study provides important information about
the potential impact of diet composition on body-weight reg-
ulation and obesity development. First, all overeating will
eventually lead to obesity. Regardless of diet composition,
most excess energy is stored in the body and not expended as
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heat. Although we demonstrated differences between carbohy-
drate and fat overfeeding, which we believe are important, the
fact remains that obesity can develop from overeating carbo-
hydrate. Advising people that they can eat an unlimited amount
of a high-carbohydrate diet is not appropriate. Second, excess
dietary fat is stored with a very high efficiency and the body
does not acutely adjust to increased fat intake. If overeating
occurs, more of the excess will end up as body fat if the excess
is fat compared with carbohydrate. This may be particularly
important if obesity develops in some people from cumulative
acute periods of overeating. Third, whereas fat overeating
would be predicted to lead to efficient storage of excess energy
in all subjects, some differences might be seen with carbohy-
drate overfeeding. In particular, those subjects who show the
greatest inhibition of fat oxidation during carbohydrate over-
feeding would be expected to show the greatest accumulation
of body fat. A major goal for weight maintenance should be
avoidance of a positive fat balance. This can be accomplished
by both reducing dietary intake of fat and increasing physical
activity. A
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2. Hill JO, Pagliassotti MJ, Peters JC. Nongenetic determinants of obe-
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3. Thomas CD, Peters JC, Reed OW, Abumrad NN, Sun M, Hill JO.
Nutrient balance and energy expenditure during ad libitum feeding of
high-fat and high-carbohydrate diets in humans. Am J Clin Nutr
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8. Bouchard C, Tremblay A, Despr#{233}s JP, et al. The response to
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9. Klein 5, Goran M. Energy metabolism in response to overfeeding in
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Metabolic response to experimental overfeeding in lean and over-
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11. Roberts SB, Young yR. Fuss P. et al. Energy expenditure and subse-
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12. Oscai LB, Brown MM, Miller WC. Effect ofdietary fat on food intake,
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Nutrient balance in humans: effects of diet composition. Am J Clin
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16. Acheson KJ, Schutz Y, Bessard T, Anantharaman K, Flatt JP,
J#{233}quier E. Olycogen storage capacity and de novo lipogenesis
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(MIDA). FASEB J 1993;7:A867(abstr).
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Physiol 1990;259:R1096-102.
33. D#{233}riaz0, Fournier 0, Tremblay A, Despr#{233}sJP, Bouchard C. Lean-
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Skeletal muscle composition in dietary obesity-susceptible and dietary
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Carbohydrate overfeeding: diet example
38. Hayek T, Ito Y, Azrolan N, et al. Dietary fat increases high density
lipoprotein (HDL) levels both by increasing the transport rates and
decreasing the fractional catabolic rates of HDL cholesterol ester and
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Food item Weight
Maintenance: diet example
Plain bagel
Cream cheese
Milk (2% fat)
White sugar
Brewed coffee
White bread
Round steak (lean, broiled)
Potato chips
Brewed tea
White sugar
Peanut butter cup
Sirloin steak (lean, broiled)
Boiled potatoes
Sour cream
Tomato soup, canned
Soda, lemon and lime
Graham crackers
Peanut butter
Milk (2% fat)
Honey nut cheerios’
Whole milk
Half and half cream
White sugar
Brewed coffee
Apple juice
Plain bagel
Steak round (lean, broiled)
Hamburger roll
American cheese (jrocessed)
Pineapple juice
Cream of mushroom soup (canned)
Soda, lemon and lime
Jelly beans
Grape juice
Roast pork tenderloin, lean
French green beans
Boiled potatoes
White bread
Pears, canned in juice
Soda, ginger ale
Milk chocolate, plain
Pound cake
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Food item Weight
Fat overfeeding: diet example
Breakfast Cream of wheat, dry weight 35
Whipping cream 202
White sugar 11
Butter 9
Banana, peeled 70
Orange juice 120
Lunch Plain bagel 80
Roast turkey breast, no skin 50
Cheddar cheese 21
Lettuce 25
Mayonnaise 17
Chocolate milk (1% fat) 200
Whipping cream 120
Vanilla ice cream (16% fat) 140
Chocolate syrup 34
Snack Peanut butter cup 51
Dinner Round steak (lean, broiled) 81
Boiled potatoes 130
Whipping cream 30
White bread 25
Broccoli, boiled 90
Butter 30
Snack Saltine crackers 11
Cheddar cheese 20
Example of food module (only offered during baseline diet)2
Banana, peeled 65
Peanut butter 13
Milk (2% fat) 120
General Mills, Minneapolis.
2This food module was offered as milk shakes.
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... In normal circumstances overfeeding leads to weight gain and fat accumulation (Horton et al., 1995). Underfeeding, in contrast, produces weight reduction and fat loss (Hall et al., 2015). ...
... In nutrition science literature is not difficult to find studies that appear to verify the validity of the EBT (Hall et al., 2015;Horton et al., 1995;Leibel et al., 1992). History has shown, however, that it is possible to collect empirical data that seems to be in perfect agreement with an erroneous paradigm (Seeliger, 1895;Lakatos, 1975;Galilei and Hawking, 2002;Frisch, 2005). ...
Metabolic physiology asserts that body weight stability is achieved when over time the average absorbed energy intake equals the average expended energy. This principle, known as energy balance, justifies the design of numerous investigations that aim to elucidate the biology of obesity. The present work provides a mathematical analysis that demonstrates, nonetheless, that weight stability must coexist with a constant energy imbalance, i.e., the average absorbed energy intake and the average expended energy are significantly different during steady weight periods. This analytical finding is not in contradiction with the First Law of Thermodynamics since open systems can manifest a stable mass in the absence of energy equilibrium. The effect of caloric imbalance on weight fluctuations is thus the result of its underlying net mass flux. The energy balance theory is, consequently, an inconsistent paradigm; and as such, the data analysis and interpretation that follows from its postulates is expected to be erroneous.
... Such studies have also been performed in normal weight humans, with similar outcomes [73][74][75][76], although such responses are not always observed. Compared with underfeeding studies, manipulating normal weight individuals in the opposite way by overfeeding them to generate elevated fat stores has been performed much more frequently [76][77][78][79][80][81]. The main focus of such studies, however, has been the reaction to the overfeeding rather than following individuals after overfeeding stopped to evaluate hypophagic responses [82]. ...
Full-text available
Body weight and fatness appear to be regulated phenomena. Several different theoretical models are available to capture the essence of this idea. These include the set-point, dynamic equilibrium, adiposity force, control theory-settling point, Hall–Guo, operation point and dual intervention point (DIP) models. The set-point model posits a single reference point around which levels of fat are regulated. The dynamic equilibrium model suggests that the apparent regulation of body fat around a reference point is an illusion owing to the necessary impacts of weight change on energy expenditure. Control theory focuses on the importance of feedback gain and suggests set-point and dynamic equilibrium are ends of a continuum of feedback gain. Control theory models have also been called ‘settling point’ models. The Hall–Guo, operation point and DIP models also bring together the set-point and dynamic equilibrium ideas into a single framework. The DIP proposes a zone of indifference where dynamic equilibrium ‘regulation’ predominates, bounded by upper and lower intervention points beyond which physiological mechanisms are activated. The drifty gene hypothesis is an idea explaining where this individual variation in the upper intervention point might come from. We conclude that further experiments to test between the models are sorely required. This article is part of a discussion meeting issue ‘Causes of obesity: theories, conjectures and evidence (Part II)’.
... However, this diet effect had already diminished markedly during the second week, by about 300 kcal d −1 , suggesting it could extinguish after another week or two. Indeed, physiological studies dating back decades show that adaptation to a major change in macronutrients requires at least two to three weeks [40,[48][49][50][51]. This transient adaptive process explains findings of a new meta-analysis [40]: comparing low-carbohydrate to low-fat diets, energy expenditure was slightly reduced in trials of less than two weeks but more substantially increased in longer trials. ...
Full-text available
Conventional obesity treatment, based on the First Law of Thermodynamics, assumes that excess body fat gain is driven by overeating, and that all calories are metabolically alike in this regard. Hence, to lose weight one must ultimately eat less and move more. However, this prescription rarely succeeds over the long term, in part because calorie restriction elicits predictable biological responses that oppose ongoing weight loss. The carbohydrate-insulin model posits the opposite causal direction: overeating doesn't drive body fat increase; instead, the process of storing excess fat drives overeating. A diet high in rapidly digestible carbohydrates raises the insulin-to-glucagon ratio, shifting energy partitioning towards storage in adipose, leaving fewer calories for metabolically active and fuel sensing tissues. Consequently, hunger increases, and metabolic rate slows in the body's attempt to conserve energy. A small shift in substrate partitioning though this mechanism could account for the slow but progressive weight gain characteristic of common forms of obesity. From this perspective, the conventional calorie-restricted, low-fat diet amounts to symptomatic treatment, failing to target the underlying predisposition towards excess fat deposition. A dietary strategy to lower insulin secretion may increase the effectiveness of long-term weight management and chronic disease prevention. This article is part of a discussion meeting issue ‘Causes of obesity: theories, conjectures and evidence (Part II)’.
... To reduce the risk of overestimation, specifically with the Harris-Benedict equation, it has been recommended not to use the real weight of individuals with obesity, but rather the adjusted weight [28] at 25% or 50% [29,30]. This is because the increase in body weight not only increases body fat mass but also fat-free mass, which is metabolically more active and accounts for approximately 25% of the increase in total body weight [47]. The estimation of RMR by the Harris-Benedict equation using adjusted weight at 25% overestimated RMR IC by 176.6 calories on average, as opposed to the underestimation reported in another study [29]. ...
Full-text available
Underestimating/overestimating resting metabolic rate (RMR) affects energy prescription. The objective was to compare RMR by indirect calorimetry (RMR IC) and RMR estimated by predictive equations in women with excess body fat. This was an analytical cross-sectional study with 41 women aged 18–28 with overnutrition according to body composition. The RMR IC was measured and RMR estimated using the FAO/WHO/UNU (1985), FAO/WHO/UNU (2004), Harris–Benedict, and Mifflin–St Jeor equations. The percentage of adequacy (90–110%), overestimation (>110%), and underestimation (<90%) were evaluated for RMR IC. Data were described by percentiles because of non-normal distribution according to the Shapiro–Wilk test. The Kruskal–Wallis test and Bland–Altman analysis were applied at a significance level of α < 0.05. The RMR IC was 1192 and 1183 calories/day (p = 0.429) in women with obesity and overweight, respectively. The FAO/WHO/UNU (1985), FAO/WHO/UNU (2004), Harris–Benedict, and Mifflin–St Jeor equations overestimated the RMR IC by 283.2, 311.2, 292.7, and 203.0 calories/day and by 296.7, 413.8, 280.0, and 176.6 calories/day for women with overweight and obesity (p < 0.001), respectively. The Harris–Benedict adjusted weight (0.5) equation underestimated RMR IC by 254.7 calories/day. The predictive equations overestimated RMR IC in women with excess body fat. The Mifflin–St Jeor equation showed less overestimation and better adequacy, but was not exempt from inaccuracy.
... It has also been shown that if the diet composition is isoenergetically switched from low to high fat, then the body fat mass will increase. Therefore, a high-potency obesogenic effect of dietary fats is presumed to be one of the key contributing factors of the obesity epidemic observed in industrial societies (Flatt 1987;Horton et al. 1995;Schrauwen and Westerterp 2000;Astrup 2005). ...
Diet-induced obesity is known to develop whether exposed to a high-energy diet (HED) or a high-fat diet (HFD). However, it is still not clear whether the elevated energy content or the macronutrient imbalance is the key factor in early disease progression. Therefore, this study compared the short-term effects of 2 widely used rodent obesogenic diets, an HFD with 60 kcal% fat content and a carbohydrate-based HED, on the body weight, body fat content, glucose tolerance, and neuronal taste responses in rats. We found that only HFD induced an early significant body weight increase compared with the control normal diet (ND) group, starting on week 4, and resulting in a significantly elevated body adiposity compared with both the ND and HED groups. Oral glucose tolerance test revealed no difference across groups. Subsequently, we also found that HFD resulted in a significant body weight gain even under energy-restricted (isocaloric to ND) conditions. In vivo electrophysiological recordings revealed that only the ad libitum HFD and not the isocaloric-HFD altered the brain stem gustatory neural responses to oral taste stimulation. In conclusion, this study showed that increased fat intake might result in significant body weight gain even under isocaloric and metabolically healthy conditions and demonstrated changes in central taste processing in an early stage of dietary obesity. A better understanding of these initial physiological changes may offer new drug targets for preventing obesity.
... Nevertheless, this possibility requires further investigation." Furthermore, metabolic adaptations to macronutrient changes may require several weeks to months [135][136][137][138][139][140][141]. A recent metaanalysis reported higher total energy expenditure, with low heterogeneity, among studies ≥2.5 weeks duration comparing low-vs. ...
Full-text available
The obesity pandemic continues unabated despite a persistent public health campaign to decrease energy intake (“eat less”) and increase energy expenditure (“move more”). One explanation for this failure is that the current approach, based on the notion of energy balance, has not been adequately embraced by the public. Another possibility is that this approach rests on an erroneous paradigm. A new formulation of the energy balance model (EBM), like prior versions, considers overeating (energy intake > expenditure) the primary cause of obesity, incorporating an emphasis on “complex endocrine, metabolic, and nervous system signals” that control food intake below conscious level. This model attributes rising obesity prevalence to inexpensive, convenient, energy-dense, “ultra-processed” foods high in fat and sugar. An alternative view, the carbohydrate-insulin model (CIM), proposes that hormonal responses to highly processed carbohydrates shift energy partitioning toward deposition in adipose tissue, leaving fewer calories available for the body’s metabolic needs. Thus, increasing adiposity causes overeating to compensate for the sequestered calories. Here, we highlight robust contrasts in how the EBM and CIM view obesity pathophysiology and consider deficiencies in the EBM that impede paradigm testing and refinement. Rectifying these deficiencies should assume priority, as a constructive paradigm clash is needed to resolve long-standing scientific controversies and inform the design of new models to guide prevention and treatment. Nevertheless, public health action need not await resolution of this debate, as both models target processed carbohydrates as major drivers of obesity.
Obesity is a chronic disease that increases morbidity and mortality and adversely affects quality of life. The rapid rise of obesity has outpaced the development and deployment of effective therapeutic interventions, thereby creating a global health crisis. The presentation, complications, and response to obesity treatments vary, yet lifestyle modification, which is the foundational therapeutic intervention for obesity, is often "one size fits all." The concept of personalized medicine uses genetic and phenotypic information as a guide for disease prevention, diagnosis, and treatment and has been successfully applied in diseases such as cancer, but not in obesity. As we gain insight into the pathophysiologic mechanisms of obesity and its phenotypic expression, specific pathways can be targeted to yield a greater, more sustained therapeutic impact in an individual patient with obesity. A phenotype-based pharmacologic treatment approach utilizing objective measures to classify patients into predominant obesity mechanism groups resulted in greater weight loss (compared with a non-phenotype-based approach) in a recent study by Acosta and colleagues. In this review, we discuss the application of lifestyle modifications, behavior therapy and pharmacotherapy using the obesity phenotype-based approach as a framework.
Full-text available
High-fat diet (HFD) is associated with gut microbiome dysfunction and mental disorders. However, the time-dependence as to when this occurs is unclear. We hypothesized that a short-term HFD causes colonic tissue integrity changes resulting in behavioral changes. Rats were fed HFD or low-fat diet (LFD) for a month and gut microbiome, colon, and behavior were evaluated. Behavioral despair was found in the HFD group. Although obesity was absent, the HFD group showed increased percent weight gain, epididymal fat tissue, and leptin expression. Moreover, the HFD group had increased colonic damage, decreased expression of the tight junction proteins, and higher lipopolysaccharides (LPS) in serum. Metagenomic analysis revealed that the HFD group had more Bacteroides and less S24-7 which correlated with the decreased claudin-5. Finally, HFD group showed an increase of microglia percent area, increased astrocytic projections, and decreased phospho-mTOR. In conclusion, HFD consumption in a short period is still sufficient to disrupt gut integrity resulting in LPS infiltration, alterations in the brain, and behavioral despair even in the absence of obesity.
Full-text available
This report deals with the association between the constituents of lean body mass (LBM) and resting metabolic rate (RMR) before and after a 100-d overfeeding period. Computed-tomography (CT) scan of 22 young adult males at nine different body levels were used to estimate adipose tissue mass (ATMCT), LBMCT, skeletal-muscle mass (SMMCT), and non-muscular LBMCT (NM-LBMCT). Before overfeeding, all body constituents, except ATMCT, were significantly correlated with RMR. Only body mass changes were significantly correlated with RMR changes. Comparison of these results with those of several studies in the literature reveals that the relationship between RMR and fat-free mass is highly influenced by the size of the SD for the latter variable. In stepwise-multiple-regression analysis, only SMMCT could be used to predict RMR. It was concluded that SMMCT and ATMCT, but not NM-LBMCT, increased during overfeeding and that the best correlates of RMR remain LBMCT, SMMCT, and body massType: JOURNAL ARTICLELanguage: Eng
Full-text available
Possible adaptive mechanisms that may defend against weight gain during periods of excessive energy intake were investigated by overfeeding six lean and three overweight young men by 50% above baseline requirements with a mixed diet for 42 d [6.2 +/- 1.9 MJ/d (mean +/- SD), or a total of 265 +/- 45 MJ]. Mean weight gain was 7.6 +/- 1.6 kg (58 +/- 18% fat). The energy cost of tissue deposition (28.7 +/- 4.4 MJ/kg) matched the theoretical cost (26.0 MJ/kg). Basal metabolic rate (BMR) increased by 0.9 +/- 0.4 MJ/d and daily energy expenditure assessed by whole-body calorimetry (CAL EE) increased by 1.8 +/- 0.5 MJ/d. Total free-living energy expenditure (TEE) measured by doubly labeled water increased by 1.4 +/- 2.0 MJ/d. Activity and thermogenesis (computed as CAL EE--BMR and TEE--BMR) increased by only 0.9 +/- 0.4 and 0.9 +/- 2.1 MJ/d, respectively. All outcomes were consistent with theoretical changes due to the increased fat-free mass, body weight, and energy intake. There was no evidence of any active energy-dissipating mechanisms.
Full-text available
Two studies were performed to investigate the association between body fat mass and fat oxidation. The first, a cross-sectional study of 106 obese women maintaining stable body weight, showed that these two variables were significantly correlated (r = 0.56, P less than 0.001) and the regression coefficient indicated that a 10-kg change in fat mass corresponded to a change in fat oxidation of approximately 20 g/d. The second, a prospective study, validated this estimate and quantifies the long-term adaptations in fat oxidation resulting from body fat loss. Twenty-four moderately obese women were studied under controlled dietary conditions at stable weight before and after mean weight and fat losses of 12.7 and 9.8 kg, respectively. The reduction in fat oxidation was identical to that predicted by the above regression. We conclude that changes in fat mass significantly affect fat oxidation and that this process may contribute to the long-term regulation of fat and energy balance in obese individuals.
Full-text available
To study the influence of diet composition on regulation of body weight, we fed 21 weight-stable subjects (11 lean, 10 obese) high-carbohydrate (HC) and high-fat (HF) diets for 1 wk each. Although diet composition was fixed, total energy intake was unrestricted. Subjects had a higher energy intake on the HF (11,039 +/- 2700 kJ/d) than on the HC (10,672 +/- 2617 kJ/d) diet (P less than 0.05), but energy expenditure was not different between diets. On day 7 of the HC diet, carbohydrate (CHO) oxidation was significantly related to CHO intake with the slope of the regression line 0.99, suggesting that overall CHO balance was near zero. However, the slope of the regression line was greater for obese than for lean subjects. On day 7 of the HF diet, fat oxidation was significantly related to fat intake but the slope of the line was 0.50, suggesting that overall fat balance was positive. However, this relationship was due entirely to lean subjects, with obese subjects showing no relationship between fat intake and oxidation.
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Joule for joule, dietary fat may promote obesity more than protein or carbohydrate. In this study we determined whether the addition of 50 g dietary fat to a standard breakfast would increase energy expenditure or fat oxidation during the immediate 6-h postprandial period or over the ensuing 18 h. We also determined whether subjects with a high level of aerobic physical fitness would show a greater increase in fat oxidation after the ingestion of the extra fat than would less fit subjects. Adding fat did not increase fat oxidation or energy expenditure either during the immediate 6-h postprandial period or over the following 18 h. This was true regardless of the subject's fitness level. Acutely, dietary fat ingested in excess of its usual rate of oxidation appears to be stored in the body. Being physically fit does not appear to provide an advantage in avoiding short-term storage of excess dietary fat.
Diet composition can play a role in obesity treatment because it can influence energy intake and nutrient balance. The greatest potential effect of diet composition occurs not during weight reduction but during maintenance of a reduced body weight. During weight reduction, the extent of negative energy balance is the greatest determinant of the amount and rate of weight loss, and any effects of diet composition are likely to be very small. Conversely, during the maintenance period after weight reduction, maintenance energy requirements are reduced and the rate of fat oxidation may be low. Prevention of fat storage and regain of body weight can be achieved either by increasing fat oxidation (for example, by increasing exercise) or by reducing the fat content of the habitual diet
This study was conducted to examine long-term effects of amount and type of dietary fat on body weight and body composition. Adult male Wistar rats were fed high fat (HF; 60% of calories) or low fat (LF; 20% of calories) diets for 28 weeks. Half of the rats in each condition received diets with saturated fat (lard) (S) and the remainder received diets with polyunsaturated fat (corn oil) (U). From 28-39 weeks, HF rats were switched to LF diets (fat type remained constant). From 40-50 weeks, previously HF fed rats were weight-matched to rats in the LF fed groups. HF rats became fatter than LF rats during weeks 1-28 and remained heavier and fatter from weeks 28-39. During weeks 1-28, type of dietary fat had no effect on total body fat in either HF or LF rats, but during period 2 (weeks 28-39), U rats were heavier and fatter than S rats. There was some indication that U diets were associated with greater accumulation of fat in subcutaneous adipose tissue depots than S diets. From 40-50 weeks, rats previously fed the HF diet required less food to maintain their body weight than did LF diet rats. In summary, these results suggest that although both amount and type of dietary fat can affect body weight and body composition, the effects of the type of fat are less than those of amount of dietary fat.
The intent of this study was to determine whether a relationship exists between susceptibility to high-fat diet (HFD)-induced obesity and skeletal muscle fiber type. Forty-four adult male Wistar rats were given ad libitum access to a HFD (60% of calories from fat) for 4 wk. Rats were then grouped into quartiles for total weight gain, and the top-quartile [obesity prone (OP)] rats were compared with the bottom-quartile [obesity resistant (OR)] rats. OP rats gained 1.5 times as much weight as OR rats. OR rats had a significantly higher proportion of type I muscle fibers in the medial head of the gastrocnemius muscle than OP rats both before (determined from a muscle biopsy) and after the HFD feeding period. A greater proportion of type I fibers may be associated with a greater capacity for fat oxidation, which would favor resistance to body fat accumulation. Preexisting differences in muscle fiber composition may play a role in determining susceptibility to dietary obesity.
Data from the Second National Health and Nutrition Examination Survey (NHANES II) indicated that in the period 1976-1980 approximately 34 million US adults (25.7%) were overweight, with more women (19 million) than men (15 million) affected. Selected demographic factors, eg, low educational attainment and low family income were associated with the prevalence of overweight and with the incidence of weight gain. Analyses of the NHANES I Epidemiologic Follow-up Survey indicated that in a 10-y period, women had a greater mean weight gain. The overall incidence of a major weight gain (ie, an increase of five or more body mass index units) was twice as great among females (5.3%) than males (2.3%). Data on overweight and weight gain in the United States by selected demographic characteristics are summarized.