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Nutrient balance and energy expenditure during ad libitum feeding of high- fat and high-carbohydrate diets in humans

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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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934 Am JC/in Nuir l992;55:934-42. Printed in USA. © 1992 American Society for Clinical Nutrition
Nutrient balance and energy expenditure during ad libitum
feeding of high-fat and high-carbohydrate diets in humans13
Cecilia D Thomas, John C Peters, George W Reed, Naji N Abumrad, Ming Sun, and James 0 Hill
ABSTRACT To study the influence ofdiet composition on
regulation of body weight, we fed 21 weight-stable subjects (1 1
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 (1 1 039 ± 2700 kJ/d) than on the HC (10 672 ± 2617
kJ/d) diet (P <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
ofthe 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 ofthe HF diet,
fat oxidation was significantly related to fat intake but the slope
ofthe line was 0.50, suggesting that overall fat balance was pos-
itive. However, this relationship was due entirely to lean subjects,
with obese subjects showing no relationship between fat intake
and oxidation. Am J Clin Nuir 1992;55:934-42.
KEY WORDS Obesity, thermogenesis, diet composition
Introduction
Stability of body weight and body composition requires that
over time, energy intake equals energy expenditure and also that
intakes of protein, carbohydrate, and fat equal the oxidation of
each (1, 2). Another way of stating this is that the respiratory
quotient (RQ), which is the carbon dioxide produced divided
by the oxygen consumed, must equal the food quotient (FQ),
which is the carbon dioxide produced divided by the oxygen
consumed if the diet were oxidized. If these conditions are not
met, changes will occur in the body stores of protein, carbohy-
drate, and fat, which affect overall body weight and composition.
Many studies have examined the regulation of energy intake
and/or energy expenditure to understand how the two are bal-
anced or, in the case ofdeveloping obesity, unbalanced (3). Few
studies have examined the regulation of substrate oxidation to
understand the extent to which the composition offuel oxidized
is adjusted to the composition of energy ingested. If such ad-
justments do not occur, imbalances in one or more nutrients
may lead to accumulation or depletion of stored energy and
thus changes in body weight.
Flatt (1, 2), has been a pioneer in this area and has proposed
that difficulty in achieving fat balance on typical mixed diets
may play a key role in the development of obesity. According
to Flatt, this is because fluctuations in dietary protein and car-
bohydrate are compensated for by immediate changes in protein
and carbohydrate oxidation, whereas changes in fat intake are
not balanced by rapid responses in fat oxidation. The result is
that excess dietary fat is almost entirely stored in the body
whereas excess protein and carbohydrate are not. In addition,
Flatt proposes that food intake is influenced by events related
to carbohydrate utilization so that a high-fat (HF) diet (low in
carbohydrate) promotes increased total food intake.
In support ofFlatt’s model is the finding that HF diets promote
obesity in rodents (4, 5). In studies ofrats given ad libitum access
to HF diets, we (6) and others (5) found that although most rats
readily become obese, some avoid obesity. We further found
that rats that avoided obesity on an HF diet had a lower daily
RQ than did those that did become obese (6), suggesting that
obesity-resistant rats increased fat oxidation in response to in-
creased fat intake more than did the latter group. Thus in rats,
differences in the ability to increase fat oxidation in response to
high dietary fat intake may determine susceptibility to fat gain
on an HF diet. We proposed that there are individual differences
in the extent to which a high intake of dietary fat results in
increased fat oxidation and body-fat gain, and thus there are
differences in the susceptibility of individuals to the effects of
diet composition in the development of obesity.
The purpose of the present study was to determine whether
alterations in the fat-carbohydrate ratio ofthe diet produce mea-
surable changes in total energy expenditure, the composition of
fuel oxidized by the body, and the total amount of energy con-
sumed. Flatt’s model (1,2) would predict an increase in car-
bohydrate oxidation when subjects are given a high-carbohydrate,
low-fat diet, but little or no increase in fat oxidation when subjects
are given a high-fat, low-carbohydrate diet. This model would
also predict a higher total food intake on an HF diet than on a
high-carbohydrate (HC) diet. Additionally, our intent was to
determine whether lean subjects differ from obese subjects either
in their ability to increase fat oxidation when eating the high-
fat, low-carbohydrate diet or in the effect of diet composition
on energy intake. To accomplish these aims, we fixed diet com-
1From the Clinical Nutrition Research Center ofthe Departments of
Pediatrics, Preventive Medicine, and Surgery, Vanderbilt University,
Nashville, TN; and The Procter and Gamble Co, Cincinnati.
2Supported by NIH grants DK42549, DK26657, and RR00095.
3Address reprint requests to JO Hill, Clinical Nutrition Research
Center, D-413O MCN, Department ofPediatrics, Vanderbilt University,
Nashville, TN 37232.
Received August 5, 1991.
Accepted for publication December 12, 1991.
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NUTRIENT BALANCE IN HUMANS 935
position (yielding a constant FQ) and allowed subjects to eat as
much or as little of the diet as they wanted. Total energy cx-
penditure and substrate oxidation were determined from data
obtained with a whole-room respiration chamber.
Methods
Subjects
Twenty-one adult subjects were recruited for this study, which
was approved by the Vanderbilt University Committee for the
Protection of Human Subjects. Subjects were recruited to fit
into one of the following classifications: 1) nonobese (body fat
<25% for men; <30% for women) with no obese first-degree
relatives (determined from the subject’s recall); or 2) obese (body
fat >25% for men; >30% for women) with at least two obese
first-degree relatives (determined by the subject’s recall). Subjects
were eliminated if they reported a personal or family history of
diabetes or other endocrine disease. An attempt was made to
recruit an equal number ofmen and women in each group. The
characteristics ofthe 21 volunteers (10 obese, 1 1 nonobese) that
met these criteria are shown in Table I.
Procedures
All subjects were studied during a 2-wk prestudy period, during
a l-wk baseline period, and during 2 experimental wks of diet
manipulations. Subjects were inpatients during their stays in the
whole-room calorimeter and on all other days they received all
oftheir food from the Clinical Research Center (CRC). The two
experimental weeks were separated by a 1-mo washout period.
During the prestudy period subjects recorded all food eaten,
using diet diaries, which were analyzed to determine the amount
and composition ofenergy ingested. During the baseline period
subjects were fed the amount and composition offood that they
reported eating during the prestudy period. During the baseline
week, subjects received all oftheir food from the CRC. However,
adjustments in total food provided were made for some subjects
who lost weight during the first few days of the baseline period.
All subjects were studied in our whole-room calorimeter during
days I and 7 of the baseline period.
After the baseline period subjects were randomly assigned to
receive either the HC or HF diet for 1 wk. This was followed by
a 1-mo washout period during which the subject ate ad libitum
at home, and then subjects were fed the remaining experimental
diet for 1 wk. During both experimental weeks, subjects received
all of their food from the Vanderbilt CRC. All subjects were
studied in our whole-room calorimeter on day 7 of each of the
two experimental weeks.
Diets
Diets were individualized for each subject to allow us to assess
energy expenditure and nutrient balance at their usual diet com-
position (ie, during baseline) and with a relatively similar increase
or decrease in the carbohydrate-fat ratio of the diet. This was
accomplished as follows. Because we could not ensure that the
usual diets ofall subjects were ofthe same composition, we tried
to change diet composition by a similar magnitude for all subjects
during the experimental weeks. We estimated the average RQ
ofthe habitual diet on the basis offood-intake records, assuming
that subjects were maintaining near-zero energy balance. To
formulate the HF diet, we subtracted 0.04 from the measured
baseline RQ and provided a diet with an FQ (RQ of the diet)
equal to this value. For the HC diet we added 0.04 to the baseline
RQ and provided a diet with an FQ equal to this value. Thus
we produced a change in diet composition that was relatively
uniform for each subject.
Because altering voluntary food intake represents one way by
which subjects could adjust to changes in diet composition, the
goal of this study was to fix diet composition (ie, FQ), but not
to restrict the amount of food eaten by the subjects. This was
accomplished as follows. Each subject’s maintenance energy re-
quirement was assumed to be 1.4 X measured resting metabolic
(RMR) rate. An equivalent amount of energy was provided to
the subject each day in the form of a diet with a fixed FQ. Ad-
ditionally, subjects could request an unlimited number of food
modules, all of 836 Id and all having the target FQ at any time
ofthe day. The FQ ofthe food modules was also individualized
for each subject. This protocol was in effect during the time
spent in the calorimeter as well as during the outpatient portion
of the study. Thus, within the limits of this procedure subjects
were allowed to eat ad libitum a diet with a constant FQ.
Subjects received all of their food from the Vanderbilt CRC
dietitians during the baseline week and the two experimental
weeks. CRC dietitians weighed all food provided and all food
not eaten. The composition of foods used to prepare diets was
determined from food tables (7). The digestible energy contents
of protein, carbohydrate, and fat were also estimated from the
food tables. The average digestible energy ofthe protein used in
this study was estimated to be 85% of gross protein energy. Di-
gestible intakes of carbohydrate and fat were estimated to be
95% of the gross energy of these food components. This value
TABLE 1
Characteristics of subjects
Age Height Weight BMI t Percent fat Insulin sensitivity
ycm kg %X104
Lean men (n =6) 24 ±2181.8 ± 3.2 83.2 ±4.4 24 ±1 21 ±21.78 ± 0.53
Lean women (n =5) 27 ±2 169.6 ±3.6 59.0 ±3.1 21 ±I26 ±1 3.45 ±0.68
Obesemen(n=5) 27±2 185.2±2.1 107.7±4.4 31 ±135± 1 1.56±0.44
Obesewomen(n=5) 28± 1 161.4±2.7 85.1 ±2.7 31 ±2 43±3 1.56±0.69
*I ± SE.
tBody mass index [in kg (wt)/m2 (ht)].
tSI value from Bergman’s minimal model.
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936 THOMAS ET AL
periods when the subject reported having slept and when sleep
was obtained by averaging the digestible energy of representative
carbohydrate and fat sources used in the present study.
Body composition
Body composition was determined once during baseline for
each subject from measurements of body density estimated by
underwater weighing. Body weights in air and underwater were
measured to the nearest 25 g by using Detecto platform (Webb
City, MO) and Chatillon spring (Kew Gardens, NY) scales, re-
spectively. Residual lung volume was determined (simulta-
neously with underwater weighing) with a closed-circuit, nitro-
gen-dilution method (8). Nitrogen concentration during re-
breathing was measured with a Med-Science 505-D Nitralizer
(St Louis). Percent body fat was estimated from body density
by using the revised equation ofLohman et al (9). We performed
many studies in which body composition, determined by using
this technique, is determined in the same subjects on many dif-
ferent occasions. From these studies we estimated our absolute
error as 2-5%.
Energy expenditure
Total 24-h energy expenditure was measured with a whole-
room indirect calorimeter, which was described previously (10).
While in the calorimeter, the subjects were free to move around
but were not provided with exercise equipment or given specific
instructions to exercise. The calorimeter is located within the
CRC and is connected via an intercom to the nursing station.
Oxygen consumption and carbon dioxide production are deter-
mined from the flow rate and the differences in gas concentra-
tions between entering and exiting air. Values are corrected for
temperature, barometric pressure, and humidity. Energy expen-
diture is calculated from the oxygen consumption and RQ. The
operation of the chamber is 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 (1 1). Values
for all indices were averaged over 30-mm intervals and recorded
in a data file.
In addition to total 24-h energy expenditure, the individual
components of energy expenditure were estimated during each
24-h stay in the whole-room calorimeter. Energy expenditure
due to activity or movement (EEAcr) was estimated with the
assistance ofa Doppler radar system (12), installed in the whole-
room calorimeter. The instrument records relative activity, which
is significantly correlated with metabolic rate. It is possible to
calculate the caloric cost of activity (the slope of the regression
line describing the relationship between activity and metabolic
rate) and total EEA4,. (cost of activity times amount of activity
by using linear regression. The metabolic rate at zero activity
would represent RMR and the thermic effect of food (TEF).
After leaving the calorimeter at 0700 after a 23-h stay, subjects
were moved to an adjacent room and allowed to rest for 45 mm,
and RMR was measured for 30 mm with a ventilated-hood sys-
tern (Sensormedics 2900 Oxygen Uptake System, Anaheim, CA).
In addition to RMR, we measured sleeping metabolic rate
(SMR), which we defined as the average metabolic rate measured
during sleep. Periods of sleep were determined from an activity
diary maintained by the subject while in the whole-room calo-
rimeter as well as from measures of activity obtained from the
radar detector. SMR was taken to be the average of all 30-mm
could be inferred from the subject’s diary and when activity by
radar was <1%.
Substrate-oxidation rates and daily nutrient balance
Daily rates ofoxidation ofprotein, carbohydrate, and fat were
determined for each 24-h stay in the whole-room calorimeter.
Protein oxidation was determined from 24-h urinary nitrogen
excretion (measured with the Kjeldahl technique), with correc-
tion for any change in the blood-urea-nitrogen pool (13); car-
bohydrate and fat oxidation were determined from total energy
expenditure and the nonprotein RQ (14). Nutrient balance was
calculated as the difference between intake and oxidation of each
nutrient over 24 h.
Insulin sensitivity
We obtained a measure of each subject’s insulin sensitivity,
using Bergman’s minimal model program with a modified fre-
quent sampling intravenous glucose tolerance test (I 5). This
procedure was performed on all subjects during the baseline
period. Three baseline blood samples were drawn and then 0.3
g50% dextrose/kg body wt was infused over 2 mm. Additional
blood samples were taken at 3, 6, 10, 14, 19, 23, 25, 26, 29, 30,
32, 35, 50, 70, 100, 140, and 180 mm. Tolbutamide (5 mg/kg)
was given to subjects 20 mm after glucose infusion. Blood sam-
ples were analyzed for glucose (autoanalyzer) and insulin (16).
SI (equivalent to insulin sensitivity) was calculated by using a
minimal model software program obtained from Bergman (15).
Statistical methods
All dependent variables were analyzed by using repeated-
measures analysis of variance with subject phenotype (lean vs
obese) and gender (male vs female) as the between-groups factors
and responses to the three experimental diet conditions as the
within-subjects factor. Post hoc tests were performed when ap-
propriate by using the Newman-Keuls method (17). Linear-
regression analysis was used to describe the relationship between
selected variables. The 95% confidence limits were calculated
for the slopes of each regression line to determine if they were
different from 0 and from each other.
Results
Body weight
Individual body weights fluctuated (by <0.25 kg) throughout
the study, but we did not observe any systematic increase or
decrease in the body weight of any subject. Additionally, there
was not a significant change in the average body weight of the
group as a whole over the course of the study.
Average dailyfood intake
Table 2 shows the average daily intake for each group
throughout the study. The first column in this table shows the
average intake during a 14.4 period preceding the study and
was based on self reports of food intake by the subjects. The
remaining columns reflect average food intake as determined
by the CRC dietitians. During the baseline period, the average
diet composition was 13.8% protein, 48.3% carbohydrate, and
37.9% fat. Obese subjects tended to have a slightly higher fat
intake as percent of calories than did lean subjects. During the
HC diet the average diet composition was 12.7% protein, 6 1.6%
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NUTRIENT BALANCE IN HUMANS 937
*I ± SE. HC, high carbohydrate; HF, high fat.
TABLE 2
Daily energy intake
Diet diariest Baseline HC wk HF wk
kJ/d
Leanmen(n=6) 11718±1382 11267±1382 11939±1026 12417±1216
Lean women (n =5) 8 5 11 ±534 8 446 ±561 7 934 ±598 9 609 ±1 324
Obesemen(n=5) 11873±1110 11328±760 12832±894 12756±891
Obese women (n =5) 8 713 ± 1 007 9 338 ±752 9 653 ±866 10 376 ±976
*I ± SE. HC, high carbohydrate; HF, high fat.
tMeasured over 14 d.
carbohydrate, and 25.7% fat. During the HF diet the average
diet composition was 12.6% protein, 35.4% carbohydrate, and
52.0% fat.
Total energy intake was higher on the HF diet (by 690 kJ/d)
than on the HC diet (P <0.05). Total energy ingested during
the three measured periods was higher for men than for women
(P <0.01) and was higher for obese subjects than forlean subjects
(P <0.01).
Energy expenditure
Table 3 shows the average daily rates of energy expenditure
measured at baseline and on day 7 of each feeding period.
Changes in diet composition did not produce measurable changes
in energy expenditure. Energy expenditure was higher in males
than in females (P <0.01) and higher in obese subjects than in
lean subjects (P <0.01). Both differences would be expected
based on differences in fat-free mass between subject groups.
In addition, neither SMR nor RMR was influenced by the
composition ofthe diet eaten (data not shown). Similarly, there
were no significant differences due to diet composition in the
estimated energy expended in physical activity while in the cal-
orimeter (Table 4).
Table 5 shows the difference between average energy con-
sumed during each period during the study and measured energy
expenditure in the room calorimeter. If the energy expenditure
measured in the room calorimeter reflects sedentary energy ex-
penditure, the difference between these values might reflect 1)
the difference in the energy expended in spontaneous activity
between a sedentary day and a “usual” day; and 2) the degree
of positive energy balance created by the change in diet corn-
position. We will refer to the value as positive energy balance
(PEB). Without independent measures ofspontaneous physical
activity, it is impossible to determine whether changes in PEB
simply reflect changes in spontaneous physical activity. However,
if the assumptions above are reasonable, this allows for some
interesting speculation. First, during the 2-wk period of keeping
diet diaries, subjects should be near energy balance and, if so,
PEB would most likely reflect energy expended in spontaneous
physical activity. Ifthis assumption is correct and ifdiet diaries
accurately reflect food intake during this period, lean males and
females expended significantly (P <0.01) more energy during
a usual day than during a sedentary day in the room calorimeter.
However, the value for PEB in obese subjects was not different
from zero, which suggests either that activity during a usual day
was not different than activity seen in the room calorimeter, an
unlikely event, or that diet diaries underestimated actual food
intake in these subjects. For the first day of the baseline period
there was a negative correlation between PEB and percent body
fat that was nearly statistically significant(r =-0.42, P=0.0575).
We found that PEB was greater on the HF diet than on the
HC diet, and this difference (673 kJ/d) also approached statistical
significance (P <0.06).
Nutrient oxidation in relation to nutrient intake
Table 6 shows values for the 24-h RQ during each stay in the
whole-room calorimeter. The RQ was significantly higher on
day 7 of the HC week than it was on day 7 of the HF week (P
<0.01) for all subjects. The RQ measured during sleep is shown
in Table 7 for the various groups during baseline and diet treat-
ments. Obese subjects had a lower sleeping RQ on the HF than
on the HC diet (P <0.003) but there was no difference for lean
subjects.
Figures 1-3 show intakes ofprotein, carbohydrate, and fat in
relation to oxidation of each on the first day of the baseline
TABLE 3
Twenty-four-hour energy expenditure in the calorimeter*
Baseline
(day 1) Baseline
(day 7) HC wk
(day 7) HF wk
(day 7)
kJ/d
Lean men (n =6) 9 762 ±480 9 699 ±372 9 730 ±441 9 7 16 ±352
Lean women (n =5) 7 450 ±214 7 077 ±341 7 113 ±351 6 928 ±447
Obesemen(n=5) 11678±573 11280±483 11266±435 11280±304
Obesewomen(n=5) 8807±610 8327±518 8 194±526 841±S24
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938 THOMAS ET AL
*Determined as average daily intake during each specified diet; i ±SE. HC, high carbohydrate; HF, high fat.
TABLE 4
Energy expended in physical activity in room calorimeter
Baseline
(day 1)Baseline
(day 7) HC wk
(day 7) HF wk
(day 7)
kJ/d
Leanmen(n=6) 1316±246 1176± 197 1053±286 1185 ±229
Lean women (n =5) 896 ±109 850 ±219 829 ±303 829 ±218
Obese men (n =5) 1580 ±171 1747 ±264 1597 ± 341 1435 ± 163
Obese women (n =5) 1521 ±203 1465 ±436 1 1 10 ±262 1316 ±330
* : SE. HC, high carbohydrate; HF, high fat.
period and on day 7 of the HC and HF treatment periods. For
each plot we show the regression line for all 2 1 subjects (solid
line) as well as the regression lines for lean and obese subjects
separately. On day I of baseline (Fig 1), protein intake and ox-
idation were correlated (r =0.54, P<0.025) when all subjects
were considered. This relationship did not differ between lean
and obese subjects and the slopes of the regression lines were
similar and significantly different from 0. Carbohydrate intake
and oxidation were also positively correlated when all subjects
were considered (r =0.60, P<0.0 1). The correlations for lean
and obese subjects were also high, although statistically significant
only with lean subjects. There was not a significant relationship
between fat intake and fat oxidation in all subjects (r =0.09,
NS) or in either lean or obese subjects when considered sepa-
rately. The slopes ofthe regression lines describing fat oxidation
in relation to fat intake were not different from 0.
Figure 2 shows the results for day 7 ofthe HC feeding. Protein
intake and oxidation were positively correlated for all subjects
(r =0.68, P<0.001) and also for lean and obese subjects when
considered separately. Slopes ofall ofthese regression lines were
significantly different from 0. Carbohydrate intake and oxidation
were also significantly correlated for all subjects (r 0.7 1, P
<0.01). The equation for the regression line was y(CHO oxi-
dation) =0.99x + 20. Carbohydrate intake and oxidation were
also significantly correlated for lean and obese subjects when
considered separately. Slopes ofall regression lines were different
from 0. The slope of the regression line for obese subjects (y
=l.2lx -12) was significantly (P <0.05) higher than that for
lean subjects (y =0.94x -6). There was no significant rela-
tionship between fat intake and oxidation for all subjects (r
=-0.03) or for either lean or obese subjects. The slopes of these
regression lines were not different from 0. On day 7 of the HC
TABLE 5
diet, note that obese subjects tended to oxidize proportionally
more carbohydrate and less fat than did lean subjects over the
range of intakes presented in Figure 2.
Figure 3 shows the results for day 7 ofthe HF feeding. Protein
intake and oxidation were significantly related for all subjects (r
=0.72, P<0.01) and for lean and obese subjects separately.
There was not a significant relationship between carbohydrate
intake and oxidation either for all subjects together (r =0.22)
or for lean or obese subjects considered separately. There was a
significant relationship between fat intake and fat oxidation (r
=0.57, P<0.01) for all subjects. The regression line was y(fat
oxidation) =0.50x + 46). However the relationship between
intake and oxidation of fat was entirely explained by lean sub-
jects, with obese subjects not demonstrating a significant cor-
relation between fat intake and oxidation. The slope of the
regression line for lean subjects (y =0.65x + 17) was significantly
different from 0 but the slope of the regression line for obese
subjects (y =0.02x +124) was not.
Insulin sensitivity
Insulin sensitivity (estimated from S) was slightly but non-
significantly (P <0.08) higher in lean than in obese subjects
(Table 1). We were unable to show any significant relationship
between S and any measure of substrate balance on either the
HC or HF diets.
Discussion
The results of this study provide support for the basic tenet
of Flatt’s model (1, 2), that the ability ofan individual to match
fat intake and oxidation plays a key role in body-weight regu-
lation. We extended this model to suggest that there are mdi-
Difference between average energy in take and energy expended in the room calorimete r (E1 -
Baseline
(day 1)Baseline
(day 7) HC wk
(day 7) HF wk
(day 7)
kJ/d
Lean men (n =6)
Leanwomen(n =5)
Obese men (n =5)
Obese women (n =5)
1956 ±1062
1061 ±439
196 ±902
-94 ±744
1568 ±933
1369± 365
48 ±606
101 1 ±660
2208 ±1104
821 ±363
1566 ±475
1460 ±754
2701 ±1101
2681 ±1125
1476 ± 842
1925 ±656
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NUTRIENT BALANCE IN HUMANS 939
*I ± SE. HC, high carbohydrate; HF, high fat.
TABLE 6
Average 24-h respiratory quotient in the calorimeter*
Baseline Baseline HC wk HF wk
(day 1) (day 7) (day 7) (day 7)
Lean men (n =6) 0.855 ±0.016 0.839 ±0.010 0.907 ±0.007 0.824 ±0.0 15
Lean women (n =5) 0.869 ±0.022 0.882 ±0.014 0.910 ±0.022 0.870 ±0.013
Obese men (n =5) 0.875 ± 0.004 0.853 ±0.023 0.943 ± 0.022 0.828 ±0.009
Obese women (n =5) 0.866 ±0.029 0.858 ±0.016 0.919 ±0.040 0.830 ±0.013
*I ± SE. HC, high carbohydrate; HF, high fat.
vidual differences in the ability to achieve fat balance when hu-
mans consume an HF diet and that lean subjects may have a
better ability to achieve fat balance under these conditions than
obese subjects. Additionally, on day 7 of the HC diet, obese
subjects showed a proportionally higher oxidation of carbohy-
drate and lower oxidation of fat than did lean subjects. We hy-
pothesize that differences in the proportion of carbohydrate vs
fat oxidized under some dietary conditions may be important
in determining who is susceptible to dietary-induced obesity.
We further speculate that a poor ability to match fat oxidation
to fat intake may play a role in the development of obesity in
obese subjects and a good ability to match fat oxidation to fat
intake may play a role in the avoidance ofobesity in lean subjects.
Flatt’s model (1, 2), if applied to humans, would suggest that
alterations in carbohydrate intake are quickly adjusted for by
changes in carbohydrate oxidation but that changes in fat intake
are poorly compensated for by appropriate alterations in fat ox-
idation. Overall, our results provide four lines of support for
this notion. First, when subjects were studied in the room cal-
orimeter after 2 wk ofeating their usual diets, both protein and
carbohydrate oxidation were correlated with intake ofeach; the
slope ofthe line describing this relationship was near unity. The
slope of the line plotting fat intake and oxidation did not ap-
proach unity, even in lean individuals. It is important to point
out that all subjects were in slight positive energy balance in the
room calorimeter because of low physical activity. Second, all
subjects in this study increased carbohydrate oxidation when
given the HC diet, the increase in oxidation being roughly
equivalent to the increase in carbohydrate intake. The slope of
the regression line was significantly greater for obese than for
lean subjects (P <0.05), but the yintercepts did not differ be-
tween groups. Third, although there was an increase in fat oxi-
dation in lean subjects after 7 d of feeding the HF diet, this
increase in oxidation was much less than the increase in fat
intake, resulting in a state of positive fat balance. Finally, the
difference between energy ingested and energy expended in the
whole-room calorimeter was greater during HF feeding than
during HC feeding. Unless voluntary physical activity increased
during HF as compared with HC feeding, this is further mdi-
cation that there was greater positive energy balance on the HF
diet, suggesting that the HF diet was more obesity producing
than was the HC diet.
These results provide additional evidence that HF diets pro-
mote obesity in humans. Both lean and obese subjects were in
positive fat balance during feeding ofthe HF diet. Additionally,
HF diets also appeared to disrupt the usual relationship between
carbohydrate oxidation and carbohydrate intake in both lean
and obese subjects. This leaves obese individuals particularly
prone to body-weight (and fat) gain because rates of intake of
both carbohydrate and fat may exceed rates ofoxidation of each.
Lean subjects may have a better (or quicker) ability than obese
subjects to increase total fat oxidation in response to the increased
fat intake. The greater insulin sensitivity of lean subjects may
be a key to the ability to adjust nutrient oxidation to nutrient
intake. For example, at least under some conditions studied in
this study, obese subjects differed from lean subjects in that they
tended to oxidize proportionally more carbohydrate and less fat
than did the latter group. Reduced insulin sensitivity in obese
subjects would require increased insulin concentrations in order
to sustain a high degree ofcarbohydrate oxidation (18). Because
insulin has antilipolytic effects (19), increased circulating insulin
concentrations may limit lipolysis, an effect that may also limit
total fat oxidation (20).
If one projects these short-term results over a longer time
period, both lean and obese subjects should gain body fat when
eating an HF diet, but this should be greater for obese subjects.
It is not possible to provide any reasonable estimate of how
much difference in fat storage would occur over time between
lean and obese subjects because it could be that the difference
in response to the HF diet between lean and obese subjects only
TABLE 7
Respiratory quotient during sleep
Baseline
(day 1) Baseline
(day 7) HC wk
(day 7) HF wk
(day 7)
Lean men (n =6) 0.827 ±0.013 0.812 ±0.009 0.866 ±0.010 0.827 ±0.036
Lean women (n =5) 0.826 ±0.018 0.855 ±0.013 0.846 ±0.022 0.840 ±0.022
Obese men (n =5) 0.816 ±0.003 0.827 ±0.033 0.898 ±0.016 0.781 ±0.0 12
Obese women (n =5) 0.794 ±0.032 0.828 ±0.019 0.903 ±0.052 0.802 ±0.009
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200
150
z
0
4
0
x
0
0
100
50
00
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BASELINE DA Y 1 This is a lesser difference than that reported by others, who re-
  ported average differences between intake on HF and HC diets
0Lean, r =0.48. n.s. of4799 (25), 27 1 7 (26), and 2 1 32 (27) kJ/d. This lesser difference
.Obese; r=0.62. p<0.05 #{149}. . . . . . . . may be due to the design of the present study where the com-
However, these results do provide further evidence for a greater . . . . . . . . . #{149}L#{149}-- - -  position of additional food available was fixed. For example, a
. . . .  #{149}L#{149}.:#{149}-- - - subject on the HF diet who desired a pure fat snack could not. . . . . . - - eat a snack containing more fat than was in the diet as a whole.total energy intake on an HF than on an HC diet.
.....0 We did not find any differences in total daily energy expen-
diture due to diet condition. This finding agrees with previous
50 100 150 200 work in humans (10, 28). However, this does not necessarily
PROTEIN INTAKE (g/day) mean that diet composition does not affect energy expenditure,
it may be that the difference in energy expenditure between diet
conditions would be less than can be reliably measured with
HIGH CHO DA Y 7
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0 100 200 300 400 500
CHO INTAKE (g/day)
Lean; r= -0.14, n.s.
.Obese; r= -0.09, n.s.
.
o #{176} -- -
.2OO
. 0Lean;r=0.79,p<0.01
0 50 100 150
PROTEIN INTAKE (g/day)
0 50 100 150
200
0 200
...
400 600 800
FAT INTAKE (g/day)
FIG I .Relationship between intake (x axis) and oxidation (y axis) of
protein, carbohydrate (CHO), and fat for all subjects on the first day of
the baseline period. (-), regression line for all 21 subjects; (---),
regression line for lean subjects; and ( . . . . ), regression line for obese
subjects.
reflects a temporal difference in the rate at which the body adjusts
fat oxidation to match fat intake. Although it will be important
to determine whether this is the case, this situation would still
tend to promote obesity more in obese than in lean subjects.
Other investigators showed that adding dietary fat to a mixed
diet does not produce an increase in fat oxidation over a 6-h
(2 1, 22) or 24-h (22, 23) period, whereas adding carbohydrate
does produce an increase in carbohydrate oxidation as early as
1 d later (24). Our results suggest that switching subjects to an
HF diet can produce changes in fat oxidation after 7 d but only
in lean subjects.
Flatt’s model also predicts that food intake is linked to a
mechanism related to carbohydrate utilization, so that total en-
ergy intake should be higher on HF diets than on HC diets (unless
the regulated amount ofglycogen or ofglucose utilization drops).
Subjects are 41 8-627 kJ/d more when given the HF vs HC diet.
CHO INTAKE (g/day)
2OO I
>.
. 150 0Lean; r=0.06, n.s.
#{149}Obese; r=-0.08, n.s.
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0#{149}
#{149}#{149}#{149}
a #{149} a
o.#{149}
I1_ I
0 50 100 150 200
FAT INTAKE (g/day)
FIG 2. Relationship between intake (x) and oxidation (y) of protein,
carbohydrate (CHO), and fat for all subjects on day 7 of the high-
carbohydrate feeding period. (-), regression line for all 21 subjects;
(-- -), regression line for lean subjects; and ( . . . . ), regression line for
obese subjects.
940 THOMAS ET AL
by guest on July 9, 2011www.ajcn.orgDownloaded from
High Fat Day 7
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? 400
 300 -
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 200
0 50 100 150
PROTEIN INTAKE (g/day)
-) Leanr-0
.Obese; r=0.14,n.s.
NUTRIENT BALANCE IN HUMANS 941
0 100 200 300 400 500
CHO INTAKE (g/day)
. .‘
Co u Lean;r=0.78,p<0.01
. #{149}Obese; r=O.02, n.s.
;0
0’
0 100 200 300
FAT INTAKE (g/day)
FIG 3. Relationship between intake (x axis) and oxidation (y) of pro-
tein, carbohydrate (CHO), and fat for all subjects on day 7 of the high-
fat feeding period. (-), regression line for all 2 1 subjects; (---), regres-
.sion line for lean subjects; and (. . . . ), regression line for obese subjects.
current techniques. Energy expenditure can be subdivided into
various components, such as SMR, RMR, EEACT, and TEF.
The component that would be expected to differ because of diet
condition would be TEF, because the energy costs of utilizing
fat and carbohydrate are different. However, the expected dif-
ference would be small and would not likely be reliably measured
with current methodologies. We found no significant differences
in SMR, RMR, EEAC-I., or TEF between diet conditions.
We believe that these results provide support for use of the
nutrient-balance technique over a relatively short period of time
to assess the role of the amount and composition of food intake
in affecting body weight. These results in combination with our
previous report (10) suggest that measurable changes in substrate
oxidation occur within 7 d of altering the composition of the
habitual diet. By measuring nutrient balance (intake -oxida-
tion), predictions can be made about longer-term changes in
body weight and body composition. Although, it will be necessary
to verify these with long-term studies, this technique can con-
tribute to the theoretical and practical basis for conducting such
studies. We were also encouraged with the use of food modules
that allowed total intake to vary while diet composition remained
fixed. Although this technique clearly does not provide true ad
libitum intake, the subjects did make use of the modules and
there were differences in food intake across the conditions of
the study.
One objective of the present study was to assess whether the
200 l-wk baseline period would allow us to demonstrate an equality
ofthe FQ and RQ. Flatt clearly pointed out that this is a necessary
condition of energy balance and stability of body composition.
-We did this by assessing usual food intake from diet diaries and
then feeding subjects what they reported eating. The hope was
that at the end of the week, we could demonstrate zero balance
for all nutrients. This was not the case and it may be useful to
consider why. First, the theoretical condition of FQ =RQ re-
quires not only that nutrient intake equal nutrient oxidation but
also that the amount of energy ingested be exactly enough to
meet energy requirements, because overfeeding increases RQ in
relation to FQ and underfeeding reduces RQ in relation to FQ.
Additionally, the amount of physical activity performed during
the RQ measurement must be exactly equal to usual physical
activity. This is obviously not the case inside the whole-room
calorimeter. Therefore, we conclude that the equality ofFQ and
RQ, although a necessary condition for energy and substrate
balance, is extremely difficult to demonstrate in human subjects
over the short term (24 h). Although equality of FQ and RQ
must occur over the long term, it is not clear that this would
always be apparent over 24-h periods. It is possible that mdi-
viduals differ in how quickly the equilibrium between the FQ
and RQ is achieved after disruption ofdiet and/or exercise, and
that such time-course differences may be important in deter-
mining susceptibility to dietary obesity.
Our results suggest that HF diets are more obesity producing
than are HC diets. This is because there was a greater total energy
intake on HF than on HC diets and because humans have a
lesser ability to increase fat oxidation in response to increased
fat intake than to increase carbohydrate oxidation in response
to increased carbohydrate intake. Additionally, we found some
evidence to suggest that obese humans may be more susceptible
to dietary obesity than are lean humans. When the diet contained
ahigh amount of carbohydrate, obese subjects oxidized pro-
portionally more carbohydrate and less fat than did lean subjects.
Additionally, on day 7 of the HF diets, lean subjects demon-
strated a significant positive relationship between fat intake and
oxidation whereas obese subjects did not. These differences are
interesting and could contribute to resistance to weight gain on
an HF diet in lean subjects.
We thank the staff of the Vanderbilt Clinical Research Center, par-
ticularly Patricia Heller, Donna Rice, for assistance in conducting this
study.
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... HFD administration caused a decrease in both VO 2 consumption and BEE sufficient to lower total metabolic rate at rest of about~25% compared to Ctrl mice ( Figure 2). This is consistent with data published in humans showing a decreased basal energy expenditure in individuals chronically fed a diet containing 40% more fats compared to a control diet [48,49], although some genetic individual variability was found [50]. In our mice, the metabolic changes caused by HFD were accompanied by oxidative stress and dysfunction of skeletal muscle, the organ responsible for the overgeneration of heat during heat stress. ...
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A high-dietary fat intake may be an important environmental factor leading to obesity in some people. The mechanism could be either a decrease in energy expenditure and/or an increase in caloric intake. To determine the relative importance of these mechanisms we measured 24-h energy expenditure in a whole body calorimeter in 14 nondiabetic subjects and in six subjects with non-insulin-dependent diabetes mellitus, eating isocaloric, weight-maintenance, high-fat, and high-carbohydrate diets. All subjects were Pima Indians. In nondiabetics, the mean total 24-h energy expenditure was similar (2,436 +/- 103 vs. 2,359 +/- 82 kcal/day) on high-fat and high-carbohydrate diets, respectively. The means for sleeping and resting metabolic rates, thermic effect of food, and spontaneous physical activity were unchanged. Similar results were obtained in the diabetic subjects. In summary, using a whole body calorimeter, we found no evidence of a decrease in 24-h energy expenditure on a high-fat diet compared with a high-carbohydrate diet.
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Recently, indirect calorimetry has frequently been used together with hyperinsulinemic clamps. With few exceptions, however, no attention was paid in these studies to the possible effects of hyperinsulinemia on urea nitrogen (N) pool size and the consequences of such changes on the calculated rates of protein, lipid, and carbohydrate (CHO) oxidation. We have determined the effects of euglycemic-hyperinsulinemic clamps on urea N pool size, urinary N excretion, and rates of protein, lipid, and CHO oxidation (measured by indirect calorimetry) in six normal men. Insulin infusion (1 mU.kg-1.min-1) increased peripheral venous insulin concentration from 7 +/- 1.2 (mean +/- SE) to 51 +/- 4 microU/ml. Glucose concentration was clamped at 84 +/- 1.1 mg/dl. Between 0 (preclamp) and 360 min (end of clamp), blood urea N concentration decreased from 17.2 +/- 1.1 to 11 +/- 0.8 mg/dl (P less than .001), and the urea N pool decreased from 604 +/- 41 to 388 +/- 30 mmol (P less than .001). The urea N production rate decreased from 461 +/- 91 (preclamp) to 91 +/- 63 mumol/min during the last 4 h of the clamp (P less than .05). Urinary N excretion remained unchanged (705 +/- 113 vs. 905 +/- 125 mumol/min, NS). Correction of urinary N excretion for insulin-induced reductions in the urea N pool resulted in the following changes in substrate oxidation rates (calculated for the last 4 h of the clamp).(ABSTRACT TRUNCATED AT 250 WORDS)
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The range within which glycogen levels are maintained and the size of the adipose tissue mass appear to play important roles in complementing the body's metabolic and endocrine regulatory responses. Together these lead to the oxidation of a fuel mix whose composition matches the nutrient distribution in the diet. The carbohydrate-to-fat ratio in the diet is thus a significant factor in determining for which body composition the steady state of weight maintenance will be maintained. Increases in the size of the adipose tissue mass should be expected when the fat content of the diet is raised. This is particularly the case when the constant availability of highly palatable foods makes a spontaneous reduction of the range within which glycogen levels are maintained less likely, and when sustained physical activity capable of enhancing fat oxidation is not part of the daily routine.
Article
After 15 wk on a moderately high-calorie high-fat (CM) diet, 43% of 40 3-mo-old male Sprague-Dawley rats developed diet-induced obesity (DIO) (29% more weight gain), whereas 57% of diet-resistant (DR) rats gained no more weight than 20 chow-fed controls. When switched to chow for another 7 wk, DR rats ate 13% less, gained 55% less weight, and had 49% lower food efficiency, whereas DIO rats ate 4% less but had comparable weight gain and efficiency to controls. DIO rats had 29% more carcass lipid (percent of carcass weight). DIO rat retroperitoneal white adipose pads had 65% more cells that were the same size as those in chow-fed pads; DR rat cells were similar to controls. Both DR and DIO rats increased norepinephrine turnover in their interscapular brown adipose pads by greater than 90%. DIO rats also had 40% lower pancreatic turnover; their plasma insulin levels were 327% of controls after 15 wk on the CM diet and 188% after 7 wk on chow. DR levels were the same as controls at both times. Therefore, regulation of caloric intake, pancreatic sympathetic tone, and plasma insulin levels were three important differences between rats that resisted and those that developed DIO on high-energy diets.