am j clin nutr 1996 reed 164 9
TRANSCRIPT
164 Am J Clin Nutr 1996;63:l64-9. Printed in USA. © l996American Society for Clinical Nutrition
Measuring the thermic effect of food�3
George W Reed and James 0 Hill
ABSTRACT The thermic effect of food (TEF), defined as the
increase in metabolic rate after ingestion of a meal, has been
studied extensively, but its role in body weight regulation is
controversial. We analyzed 13 1 TEF tests from a wide range of
subjects ingesting meals of varying sizes and compositions. Each
test lasted 6 h. Of the total 6-h TEF, 60% of the total had been
measured after 3 h, 78% after 4 h, and 91% after 5 h. We
developed a three-parameter curve to fit the data, which reduced
noise and gave additional information about the TEF. The area
under this parametric curve was positively correlated with fat-free
mass (FFM) and meal size (MS) and negatively correlated with
meal size squared (MS2) with an R2 of 0.35. The usual area under
a curve created by connecting the data points of a line was
correlated with the same factors but with an R2 of 0.28. The peak
of the parametric curve was positively correlated with FFM and
MS and negatively correlated with MS2. percent body fat, and
meal composition. The time at which the peak occurred correlated
positively with MS and percent fat in the meal. Our analysis
suggests that an inadequate measurement duration of the TEF
could lead to errors. In general, we recommend that the TEF be
measured for � 5 h. Am J Clin Nutr 1996;63: 164-9.
KEY WORDS Thermic effect of food, metabolic rate, en-
ergy expenditure, obesity
INTRODUCTION
In attempts to understand the regulation of energy balance,
investigators have studied all of the components of energy
expenditure (EE). EE can be divided into sleeping metabolic
rate (SMR), resting metabolic rate (RMR = SMR + arousal),
the thermic effect of exercise (TEE), and the thermic effect of
food (TEF) (1). The TEF, sometimes also called diet-induced
thermogenesis (DIT), is defined as the increase in RMR after
ingestion of a meal. Although this component of TEE may
account for a relatively small proportion of total EE (3-10%),
it could play a role in the development and/or maintenance of
obesity (2) because small differences in the TEF over long
periods of time could account for large differences among
individuals.
Although the TEF has been investigated quite extensively,
its role in energy balance in man is still controversial. For
example, D’Alessio et al (3) cite 15 papers reporting a reduced
TEF in obese subjects as compared with lean subjects and 12
papers reporting no difference in the TEF between the two
groups. Such discrepant results suggest that methodologic dif-
ferences between studies may be important. Except in the three
studies with 24-h measurements, the TEF was measured for
from 60 to 360 mm after the meal. Similarly, Kinabo and
Durnin (4) and Weststrate (5) point out numerous studies
showing discrepancies concerning the influence of various
factors (age, exercise, nutritional status, energy content of a
meal, and meal composition) on the TEF.
Many of these discrepancies may be the result of method-
ologic differences, particularly differences in the time taken to
measure TEF. Weststrate (5) suggests that the TEF can be
accurately assessed within 3 h for meals providing = 2508 kJ.
Kinabo and Durnin (4) showed that the TEF did not return to
baseline after 5 h for a 5016-Id meal and their data indicate that
the TEF did not return to baseline after 3 h for a 2508-lU meal.
Belko et al (6) showed that the TEF returned to baseline after
3 h for meals containing 15% of energy requirements but not
for meals containing 30% and 45% of energy requirements.
D’Alessio et al (3) indicated that the TEF could last as long as
8 h after meals providing � 6688 kJ and that the TEF did not
return to baseline after 4 h for meals providing 2090 kJ. Welle
et al (7) showed that the TEF did not return to baseline after
4 h for a 1672-id meal. Hill et al (8) showed that the TEF did
not return to baseline after 3 h for meals providing 2090, 4180,
and 6270 Id. Segal et al (9) showed that 70% of a 6-h TEF is
measured by 3 h for a 3010-id liquid meal and state, “. . .even
a 6-hour period may not be sufficient to quantify the total
thermic response to a meal in all individuals. .
Most studies of the TEF have used small numbers of sub-
jects, which likely contributes to the controversy because
Weststrate (5) noted that the high intraindividual variation in
the measurement of TEF allows for small power in studies with
sample sizes of < 10 subjects.
It appears that differences in the duration of the TEF mea-
surement and the amount of variation in measurements are
contributing factors to the controversy regarding the impor-
tanceof differences in the TEF to body weight regulation. In
the present study we used an extensive database of TEF tests to
evaluate the effect of the duration of measurement on the TEF.
A second goal was to develop a model of the TEF to reduce
I From the Clinical Nutrition Research Unit, Vanderbilt University,
Nashville, TN, and the Center for Human Nutrition, University of Cob-
rado. Denver, CO 80262.
2 Supported by NIH grants DK42549 and DK26615.
3 Address reprint requests to GW Reed, Department of Preventive Mcd-
icine, Vanderbilt University School of Medicine, A- 1 124 Medical Center
North, Nashville, TN 37232-2637.
Received February 6, 1995.
Accepted for publication September 21, 1995.
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MEA�URINOTH� TK�MIC � O� P0011 1�some of the measurement variation and thus improve our
understanding of the factors that influence TEF.
SUBJECTS AND METHODS
The data consist of 131 independent baseline meal tests
conducted in the energy metabolism laboratory at Vanderbilt
University over 5 y (1988-1992). The TEF was measured
during several series of studies (10-17), although the TEF was
only reported in two studies (10, 14). Subjects participated invarious studies, with various interventions, but all tests used in
these analyses were baseline tests, before any intervention. If a
subject was in two separate studies, only the first baseline mealtest was used so that the 131 tests represent 131 separate
individuals.All subjects came to the laboratory early in the morning
between 0700 and 0800 after an overnight fast. Subjects layquietly for 45 mm, after which their RMR was determined for
30 mm with a ventilated-hood indirect calorimetry system(SensorMedics 2900; SensorMedics Corp. Anaheim, CA).Subjects then consumed the test meal within 15 mm. The testmeal size and composition varied for different studies. In some
studies, a fixed meal size and composition were given [eg,
4180 Id and 40% of energy as fat (10)] and in others the size
of the meal was related to the subject’s usual intake based ondiet records [25% of usual intake (14)]. All meals contained15% of energy as protein. RMR was then measured for 10 mm
every 30 mm for the subsequent 6 h, during which time thesubject remained lying down but awake. Energy expenditure
was calculated from the amount of oxygen consumed and
carbon dioxide produced (18). The TEF was calculated as thearea under the response curve minus the 6-h RMR (extrapo-
lated from the baseline measurement). Figure 1 illustrates asample TEF curve that was adjusted for RMR by subtractingthe RMR from the energy expenditure measured. The TEF isthe area under this curve, calculated by summing each trape-zoidal region formed with a base at zero.
There were 77 females (59%) and 54 males (41 %). Table 1
I 1 1 1 I J I
0 1 2 3 4 5 6
Time in hours
FIGURE 1. A sample of a TEF (thermic effect of food) curve that was
adjusted for resting metabolic rate (RMR) by subtracting the RMR from
the energy expenditure measured at each 30-ruin time point. The trapezoid
area of the TEF was measured as the area under this curve.
TABLE 1Subject and meal characteristics’
Value
Weight (kg) 88.6 (49.8-130.2)
Fat-free mass (kg) 56.5 (37.6-82.8)
Percent body fat (%) 35.4 (8.7-5 1.3)
Age (y) 38.1 (18-65)
Meal size (U) 3953 (2721-5831)
Meal composition(% of energy as fat) 36.6 (24-65)
(% of energy as carbohydrate) 48.4 (20-69)
(% of energy as protein)2 15
, j; range in parentheses. n = 54 males and 77 females.2 Fixed amount for all studies.
lists the subject and meal characteristics and the range ofvalues. Body composition was estimated from body density by
using underwater weighing to determine body volume (19).Residual lung volume was determined simultaneously with the
underwater weight by using the closed-circuit nitrogen-dilution
technique (19). Percent body fat was estimated from bodydensity by using the revised equation of Brozek Ct al (20).
SAS software, version 6.03 (21), on a digital vaxstation 3100
with a VMS (a standard operating system) operating systemwas used for all statistical analyses and nonlinear curve fittingdescribed in the results. A nonparametric sign test was used to
test whether medians were different from zero; t tests were
used to test whether means were different from zero. Multiple-
regression analysis was used to compare the TEF area and
model parameters with subject and meal characteristics.
RESULTS
How long should the TEF be measured?
To determine the optimum time that it takes to measure the
TEF it was necessary to ask two questions. First, was there apositive component to TEF between N hours and 6 h, where
N = 3, 4, and 5? And second, what was the correlation betweentheTEFat6handtheTEFat3,4,and5h?
EE at the end of the TEF test (ie, at 6 h) was compared with
RMR (measured before the test meal). The mean differencewas 15.9 kJ/h and the median difference was 12.5 U/h; both
differences were significantly different from zero, P < 0.0001.Seventy percent of the subjects had positive differences at 6 h.
Next, the TEF was computed at 3, 4, 5, and 6 h andexpressed as a percentage of the meal size. The distributions ofthe difference between the TEF over 6 h and the TEF over 3,
4, and 5 h are illustrated in Figure 2. The distribution meansare all significantly different from zero (P < 0.0001) and thevariation becomes smaller as the time approaches 6 h. Aone-sample sign test in each case indicates that the mediandifference is significantly different from zero (P < 0.0001).Table 2 lists the median differences and the 25th percentiles of
the difference distributions to indicate that even between 5 and
6 h > 75% of the subjects had a positive component of theTEF. Assuming that the TEF at 6 h indicates the total TEF, we
computed the percentage of the total TEF that had not beenmeasured if the measurement were stopped at 3, 4, or 5 h. Themedian percentage of TEF “missed” at each stopping point is
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REED AND HILL
TEF Difference: 6 hrs - 3 hrs
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-0.02 0.0 0.02 0.04 0.06
Difference
TEF Difference: 6 hrs - 4 hrs
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-0.02 0.0 0.02 0.04 0.06
Difference
TEF Difference: 6 hrs - 5 hrs
1
0.0 0.02 0.04 0.06
TEF over 3 hours
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0.0 0.02 0.04 0.06 0.08 0.10
TEF over 4 hours
I-0.02 0.0 0.02 0.04 0.06 0.08 0.10 0.12
TEF over 5 hours
FIGURE 3. Regression line for TEF6 (thermic effect of food measured
for 6 h) compared with TEF3, TEF4, and TEF5 with the surrounding lines
showing the 95% CIs for individual measures. The variance explained (R2
value) is noted in the corner of each graph.
-I-0.02 0.0 0.02 0.04 0.06
Difference
FIGURE 2. Histograms of the difference in the TEF (thermic effect of
food) measured for 6 h and measured at 3, 4, and 5 h. The variation
decreases but the mean and median are significantly greater than zero even
at 5 h.
A measure of the TEF
listed in Table 2. At 4 h, > 20% of the TEF is not measured for
one-half of the subjects.
The TEF is related to meal size, but even for meals providing� 3344 Id (n = 39) the mean and median differences in theTEF at 6 and 5 h are significantly positive and the 25th
percentile is positive. For these smaller meals � 10% of the
total TEF was not measured at 4 h.
Figure 3 illustrates the correlation between the TEF at 6 hand the TEF at 3, 4, and 5 h. The variance explained is noted
on each graph. At 4 h 90% of the variance of TEF6 is ex-plained. There is still variation and hence information about
differences among individuals in the TEF from 4 to 6 h.
TABLE 2Thermic effect of food (TEF) missed by short-term measurements’
Median 25th Percentile Median percent of TEF6
TEF63 0.0252 0.0125 40.0
TEF64 0.0128 0.0057 22.5
TEF65 0.0054 0.0021 9.1
‘ The median and 25th percentile of the difference between TEF mea-
sured at 6 h and that at 3 (TEF63), 4 (TEF64), and 5 (TEF65) h. Thedifference is also expressed as a percent of TEF at 6 h. TEF is measured
as a proportion of meal size.
To reduce the noise and further describe the TEF, a three-parameter curve was used to describe each TEF curve over the
6-h period. Figure 4 illustrates the parametrized TEF model
curve. Each TEF curve was assumed to be of this form, the
equation for the curve being
A + Bte � t/C (1)
where t is the time in hours. The three parameters have the
following interpretation: A is the intercept, a term used for
adjustment for error in the measurement of RMR; BCe � is the
maximum value or peak value on the curve; and C is themaximum time or the time at which the peak value occurs.
For a given subject’ s TEF values, the parametric curve was
fit as illustrated in Figure 5. SAS proc NLIN was used to fiteach curve. Because the fit of the curve in some cases could be
sensitive to the initial values, a matrix of initial values was
considered, and the set that minimized the mean squared error
was used. (A was set at 0, B went from 0 to 40 in steps of 5,and C went from 0.5 to 4.5 in steps of 1.) This automated
curve-fitting method was used on all TEF curves. Of the 131
subject curves, 128 were fit by the automated program. The
three curves that did not converge or converged to a degenerate
curve were essentially flat curves. When the initial values were
adjusted and the program was rerun these curves could be fit
but this was felt to bias the fitting process. The analysis was
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MEASURING THE THERMIC EFFECT OF FOOD
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illustrates whether the relation was positive or negative. The
rc�u1t�forbothtlictrapezoidarcaan� the�niooth�dareaw�r�similar. The TEF was related to meal size in a quadratic fashionand was related to the subject’s FFM; however, the R2 value
was � 25% higher for the model area. This indicates a reduc-
tion in noise when the TEF model is used.
Table 4 shows the characteristics that were significantlyrelated to the parameters of the smooth curve that describes
TEF. The intercept was not correlated with any of the factors.
This was expected because the intercept represents an adjust-
ment for error in the initial RMR measurement. The peak EE
was related to meal size and FFM just as the smoothed area was
related to these factors; however, EE also correlated negatively
with the subject’s percentage body fat. There was a trend
(P = 0.06) for the peak to decrease with increases in therelative fat content of meals. The time of the peak was related
to meal size in a positive linear fashion and to amount of body
- I I I I I I I fat (kg) of the subject in a positive fashion. Figure 6 illustrates0 1 2 3 4 5 6 how the TEF curve shifts depending on the meal and subject
characteristics.Time in hours
00
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Time in hours
FIGURE 5. An example of one subject’s actual TEF (thermic effect of
food) data and the corresponding TEF curve that was fit to the data.
Equation of the TEF curve: - 10.28 + 175.9 X T X e T/I.3, where T
is time and e is the base of the natural logarithm. RMR, resting metabolic
rate.
0 1 2 3 4 5 6
FIGURE 4. An example of the form of the parametrized curve used to fit
the TEF(thermic effect offood)data. Equation: 175.9 X T X e TII 3 where
T is time and e is the base of the natural logarithm. RMR, resting metabolic
rate.
done using the 128 fitted curves. The average mean squared
error of the fitted curves was 336. The curve depicted in Figure
S has a mean squared error of 546.
Using the fitted curves, TEF could be computed by finding
the area under the smooth curve (smoothed area). The
smoothed area, the trapezoid area (original TEF), and the
smooth-curve parameters were compared with subject (FFM,
fat mass, percentage fat, age, and sex) and meal characteristics
(size and content) by using multiple-regression analysis.
Table 3 shows the characteristics that were significantlyrelated to the trapezoid area and the smoothed area. It also
DISCUSSION
Analysis of this database of meal tests strongly indicates that
the TEF lasts beyond 6 h for the majority of subjects. The TEF
is commonly measured for periods as short as 3 h. A 3-h
TEF measurement can miss > 40% of the total TEF, and a
4-h TEF measurement can miss 22.5% of the total TEF. Even
for meals providing 3344 kJ, 10% of the 6-h TEF is left
between 4 and 6 h. Most studies indicate that a positive
component exists beyond 3 h. Segal et al (9) indicate that
60-70% of the measured TEF is sufficient for comparison of
the TEF across subjects. We feel that there is important infor-
mation contained in the remaining unmeasured TEF. Although
the 3-h and 4-h TEFs are significantly correlated with the total
6-h TEF, our curve fitting indicates that many factors can
produce differences in the shape of the TEF curve. Thus, by not
measuring to � 5 h it is possible that important effects could
either be masked or misinterpreted. For example, our new
summarization of the TEF indicates that nonobese subjects
show an earlier and higher peak TEF than do obese subjects.
Our analysis suggests that the shorter the duration of measure-ment, the more likely it is that the total TEF will differ between
TABLE 3Regression analysis of trapezoid area and smoothed area TEF’
Variable P Relation
Trapezoid area (R2 = 0.28)
Meal size 0.02 +
Meal size squared 0.03 -
FFM 0.0001 +
Smoothed area (R2 = 0.35)
Meal size 0.0001 +
Meal size squared 0.0002 -
FFM 0.0001 +
‘ Results of multiple-regression analysis using the usual trapezoid area
measure of the TEF (thermic effect of food) and the area under the
smoothed curve. The R2 values indicate that the relation of the smoothed-
area TEF is stronger with increased meal size and fat-free mass (FFM) than
the usual trapezoid area TEF measure.
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‘ Meal and subject characteristics were significantly related to the pa-
rameters of the TEF (thermic effect of food) curve, by multiple-regression
analysis.
FFM
Meal Size
‘1’Meal Size
Fat
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168 REED AND HILL
TABLE 4Characteristics related to peak energy expenditure and time of peak’
Variable P Relation
Peak energy expenditure (maximum; R2 = 0.39)
Meal size 0.0001 +
Meal size squared 0.0001 -
FFM 0.001 +
Percentage body fat 0.004 -
Meal composition 0.06 -
Time of peak (maximum time; R2 = 0.09)
Meal size 0.003 +
Fat 0.004 +
obese and nonobese subjects. A measurement lasting an addi-
tional 2 h may wipe out that difference. It is of interest to note
that if the smooth curve for the TEF is projected to 8 h, the totalTEF would increase an average of 7% and that the increase is
correlated with meal size (r = 0.28, P < 0.002).We used our database to show how a three-parameter
curve fit to TEF data will give a more detailed summary of
these data points. The curve is not intended to predict the
individual TEF based on subject and meal characteristics
anymore so than subject and meal characteristics can predict
TEF measured by the trapezoid area under the curve. Eachindividual with different meal tests would have different
parameters in the same way that they would have different
areas. The purpose of the curve fitting is to give a more
detailed description of the measure of the TEF. The usual
area under the curve can be thought of as a single-parameter
description of the TEF. The new curve can be thought of as
I I I I I I I
FIGURE 6. An illustration of how the TEF (thermic effect of food)
curve shifts depending on subject and meal characteristics. Meal size and
fat-free mass (FFM) tend to increase the peak; subject’s body fat and meal
size squared (MS2) tend to lower the peak; meal size and subject’s body fat
tend to move the time of the peak further out. There is some evidence that
increased fat in the meal may decrease the peak. Illustrated curve equation:
175.9 x T X e T/I.3 where T is time and e is the base of the natural
logarithm. RMR, resting metabolic rate.
distilling the curve to two parameters (plus one parameter
for noise reduction). We believe two individuals can havethe same area under the curve, but drastically different TEF
curves. The usual trapezoid area method of measuring the
TEF would not pick this up. The new method can pick thisup. The data illustrate that the shape of the TEF curve may
differ between lean and obese individuals. Ifthe shape of the curvediffers, but the total TEF does not, this might explain why some
studies find differences in the total TEF between lean and obese
individuals and others do not. When the TEF is measured to 3 h,
there may be differences in the TEF curve between lean and obese
subjects; however, when the TEF is measured to 6 h, these
differences may disappear.
Our parametric curve fitting reduces some of the variationin TEF measurements and opens a new avenue of investi-
gation of the TEF. Our method demonstrates the same
relation between factors such as FFM and meal size and TEF
as the conventional measurement, but the R2 value increases.
If the new model was not a closer approximation to TEF, it
is possible that the variation could increase. Thus, our
smooth curve increases the power to identify factors that
influence the TEF. Both the trapezoid area and smoothed
area are positively related to a subject’s FFM and to meal
size. However, the smoothed area identifies a negative qua-
dratic relation between TEF and meal size. This positive
linear and negative quadratic effect was reported previously
(6, 8, 22) and could be an indication of a meal-size thresholdeffect. Once the meal reaches a certain size, no increase in
meal size will increase the TEF. It is also possible that this
resulted because the TEF was only measured for 6 h and that
the total TEF was underestimated for large meals as
suggested by D’Alessio et al (3). However, the small posi-
tive difference between the TEF at 6 h and RMR was not
correlated with meal size (P - 0.43, r = 0.07) whereas the
positive difference between the TEF at 5 h and the RMR
was significantly correlated with meal size (P = 0.002,
r 0.26).
We present an alternative to the standard way of assessing
the area under the TEF curve. Our three-parameter curve
summarizes other information in addition to total TEF and
thus provides a means of better assessing the ways in which
characteristics of the subject and of the diet effect the TEF.
For example, we found that whereas total TEF may not beinfluenced by the subject’s body fat content, the shape of the
TEF curve may differ by the subject’s body fat content. Asseen in Figure 6, the peak of the TEF curve moves up as
meal size and the subject’s FFM increase. The peak is
related positively to meal size and negatively to meal size
squared in the same way as for the total TEF. This nonlinear
relation to meal size indicates that the peak increases with
meal size, then reaches a saturation level. The new factor
here is that peak TEF is inversely related to percent body fat
of the subject.
Using this three-parameter curve, we can begin to under-
stand how characteristics of the meal and of the subject influ-
ence the TEF. As meal size increases, the peak TEF increases
and occurs at a later time after meal ingestion, and total TEF
increases. The peak (and possibly the total TEF) appears to
reach a threshold once the meal reaches a certain size. There is
a direct positive relation between the amount of FFM of the
subject and both the peak and total TEF. The body fat content
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I Lean
L- Obese
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MEASURING THE THERMIC EFFECT OF FOOD 169
0 1 2 3 4 5 6
Time in hours
FIGURE 7. Predicted TEF (thermic effect of food) curves for a lean
individual with a higher peak and a shorter time of occurrence of peak
(dotted line) and for an obese individual (solid line). Equation for lean
subjects: 175.9 X T X e 771.3; Equation for obese subjects: 113.6x T X e_T/I85 where T is time and e is the base of the natural logarithm.
RMR, resting metabolic rate.
of the subjects (either amount or percent) appears to effect the
shape of the TEF response but not the total amount of the TEF.
As the subject’s body fat content increases, the peak TEF is
lowered and occurs at a later time after the meal. Figure 7
illustrates the possible difference in the TEF due to differences
in body fat content. The dotted line shows the response of the
theoretical lean individual, who will have a high early peak that
then drops off. Conversely, the theoretical obese individual
(solid line) will have a lower flat curve. The total area under
both curves would be the same.Measuring the TEF for 6 h and using the parametric curve
will not resolve all differences. For example, Segal et al (9)measured the TEF for 6 h and found differences in the TEF
between lean and obese subjects. In general, we did not find
such a difference across a variety of conditions. However, com-
pared with our study, Segal et al used meals that were lower in fat,
meals that had a lower energy content, and a liquid diet.
It is likely that the pattern of the TEF is more complicated
than is the three-parameter curve presented here; however, ahigher-order model is more difficult to fit given 12 data points.
Our studies show that a three-parameter curve reduces noisebetter than does a two-parameter curve (excluding the interceptterm) and that a four-parameter curve fits fewer TEF curves
(101 of 131).In summary, our results indicate that the TEF is a response
lasting � 6 h in most people and we recommend that measure-
ments last � 5 h. Additionally, we demonstrated that variation in
the TEF can be reduced by fining the data to a three-parameter
curve. This alternative summary ofTEF data provides information
not only about total TEF but also about the time course of the TEF
and will be useful in understanding how characteristics of the diet
and of the subject influence the TEF. U
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