Individual variation in body temperature and energy
expenditure in response to mild cold
Wouter D.
van Marken
Lichtenbelt,
Patrick
Schrauwen,
Stephanie
van de
Kerckhove, and
Margriet S.
Westerterp-Plantenga
Department of Human Biology, Maastricht University, 6200 MD
Maastricht, The Netherlands
 |
ABSTRACT |
We studied interindividual variation in
body temperature and energy expenditure, the relation between these
two, and the effect of mild decrease in environmental temperature (16 vs. 22°C) on both body temperature and energy expenditure. Nine males
stayed three times for 60 h (2000-0800) in a respiration
chamber, once at 22°C and twice at 16°C, in random order.
Twenty-four-hour energy expenditure, thermic effect of food, sleeping
metabolic rate, activity-induced energy expenditure, and rectal and
skin temperatures were measured. A rank correlation test with data of 6 test days showed significant interindividual variation in both rectal
and skin temperatures and energy expenditures adjusted for body
composition. Short-term exposure of the subjects to 16°C caused a
significant decrease in body temperature (both skin and core), an
increase in temperature gradients, and an increase in energy
expenditure. The change in body temperature gradients was negatively
related to changes in energy expenditure. This shows that
interindividual differences exist with respect to the relative
contribution of metabolic and insulative adaptations to cold.
temperature gradient; thermoregulation; respiration chamber; metabolic adaptation; insulative adaptation
 |
INTRODUCTION |
STUDIES ON THE EFFECT
OF AMBIENT TEMPERATURE on metabolism in humans often concentrate
on either energy expenditure (7) or body temperature
(14). Although there are many studies that examine cold
exposure in rodents and humans, relatively few studies have looked at
the interaction of energy metabolism and body temperature under more
moderate conditions, such as met in daily life (13, 17,
18). It is generally acknowledged that a low resting metabolic rate is a risk factor for weight gain (16). In this
respect, much less attention is given to relatively low body
temperatures, although animal studies indicate that low body
temperature may be a risk factor for obesity (5), and,
second, there are indications for associations between body temperature
and metabolic rate in humans (13, 18).
When we study body temperature, it is important to recognize that
different sites of the body have different temperatures and that their
responses to a variation in environmental temperature are site
specific. The body can be divided roughly into two compartments: the
thermal core and the thermal shell (2). Most of the energy produced within the core is dissipated into the environment via the
body surface. It follows that, under thermoneutral conditions (16 to
28°C, with the human body dressed), the skin temperature is lower
than the core temperature and the skin temperature varies more with the
ambient temperature.
Theoretically, three types of thermoregulatory adjustments have been
described during long-term adaptation to a colder environment (11): hypothermic adaptation (lowered thermoregulatory set
point), insulative adaptation (subcutaneous fat and/or more efficient vasoconstriction), and metabolic adaptation (or nonshivering thermogenesis).
Individuals may differ in their physiological adaptations to
environmental changes. For instance, during short-term exposure to mild
cold, people may differ in their response to the relative contribution
of these adaptations, especially the insulative and metabolic ones.
Indeed, exposure to mild cold has been shown to increase the
temperature gradient, i.e., a reduction of peripheral temperature at
relatively constant core temperature (8), whereas other studies showed that energy metabolism increased (3, 7). However, the combination, i.e., measuring the components of energy expenditure together with body temperature distribution in response to
mild cold, has not before been studied in detail.
In the present study, we aim to examine the interindividual set points
in body temperature and energy expenditure to determine whether
individual variation in energy expenditure is related to body
temperature and to investigate the effect of a mild decrease in
environmental temperature (16 vs. 22°C) on both body temperature and
energy expenditure.
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MATERIALS AND METHODS |
Nine healthy male Caucasian volunteers participated in the
study. They had grown up and were now living in the Netherlands. Body
mass was 76.2 ± 9.4 kg, body mass index amounted to 22.7 ± 2.1 kg/m2, percent body fat was 17.9 ± 5.4%, and age
was 23.8 ± 5.1 yr. The Medical Ethics Committee of Maastricht
University approved the study.
Body composition.
Whole body density was determined by underwater weighing in the morning
of subjects in fasted state. Body weight was measured with a digital
balance with an accuracy of ±0.01 kg (Sauter, type E1200). Lung volume
was measured simultaneously with the helium dilution technique by use
of a spirometer (Volugraph 2000, Mijnhardt). Percent body fat was
calculated using the equation of Siri (23). Fat-free mass
in kilograms was calculated by subtracting fat mass from body mass.
Energy expenditure.
Each of three tests lasted for 60 h. The test took place in a
14-m3 respiration chamber, as described in detail by
Schoffelen et al. (19). The room was ventilated with fresh
air. The ventilation rate was measured with a dry gas meter (G4
Schlumberger, The Netherlands) and amounted to 70-80 l/min. The
relative humidity was set at 55% at both 22 and 16°C. Physical
activity was monitored by means of a radar system based on the Doppler
principle; the sensitivity of this radar system is described by
Schoffelen et al. (19). Twenty-four-hour energy
expenditure (24-h EE) was determined from the subject's O2
consumption and CO2 production, according to the formula by
Weir (25). Five-minute measurements were used to calculate
mean 30-min values (4, 19). Sleeping metabolic rate (SMR)
was calculated as the lowest mean energy expenditure over three
consecutive hours between 2400 and 0700. Twenty-four-hour thermic
effect of food (TEF) was determined as the increase in EE above SMR,
corrected for activity-induced EE (AEE). This was achieved by plotting
EE against radar output. The intercept of the regression line at the
offset of the radar, thus at zero physical activity, represents the EE
in the inactive state: resting energy expenditure (RMR), which is equal
to SMR plus TEF. TEF was calculated by subtracting SMR from RMR
(26). AEE was obtained by subtracting TEF and SMR from
24-h EE. The physical activity index (PAI) was calculated as 24-h
EE/SMR.
Body temperature.
Subjects' skin temperatures were measured continuously from 0800 until
2400 by means of thermistor surface contact probes [series 400, type
409B, Yellow Springs Instrument (YSI); accuracy ±0.1°C] fixed on
the skin with thin, air-permeable, adhesive surgical tape. The probes
were applied to the following standardized regions: forehead, ventral
side of the liver, and nondominant sides of thigh, hand, and foot.
Distal skin temperatures were calculated from means of temperatures of
hand and foot, and proximal skin temperatures were derived by averaging
temperatures of forehead, liver, and thigh. The thermometric probes
were calibrated to within 0.05°C in a water bath against a reference
mercury thermometer (accuracy: ±0.02°C).
For the core temperature, the subjects measured their rectal
temperature each 30 min by means of a conventional digital thermometer (Philips HP 5315, accuracy ±0.1°C) that was inserted 3.5-4 cm from the anal sphincter. From 2400 until 0800, rectal temperature was
measured using thermistor probes (YSI series 400; accuracy ±0.1°C).
(At 22°C, the night rectal temperature measurement of one subject is
missing.) Measurements were done every 4 min, and from these, 30-min
values were calculated. Temperature measurements were thoroughly
explained to the subjects before they entered the respiration chambers.
Simultaneous measurements (i.e., within 5 min) with both thermometers
were carried out in the mornings and evenings. These measurements
revealed good agreement (r = 0.86, P < 0.0001) under the experimental conditions of this study, with a mean
difference (bias) of 0.09°C (Phillips minus YSI) and a standard
deviation (or error) of 0.2°C (n = 39).
Temperature gradients were calculated as the differences between core
temperature and proximal skin temperature, core temperature and distal
skin temperature, and proximal and distal skin temperatures.
Protocol.
The study took place at the Department of Human Biology, Maastricht
University, during the winter season from November 1998 to March 1999. Subjects stayed three times for 60 h each (2200-0800) in the
respiration chamber, once at 22°C and twice at 16°C, in random
order (Fig. 1). The first night was for
accustomation, and the data analyses were carried out twice for 24 h from 0800 to 0800. Body weight was determined before and after each
stay in the chamber, and the subjects weighed themselves each morning in fasted state after voiding. The interval between each stay in the
chamber was from 1 to 4 wk.

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Fig. 1.
The study design. Subjects stayed 3 times for 60 h
each time in the respiration chamber. Twenty-four-hour data were
analyzed from 0800 to 0800.
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At 22°C and once at 16°C, subjects were fed in energy balance (EB)
on the 1st day and ad libitum (AL) on the 2nd day (22EB, 22AL;
16EB3, 16AL; Fig. 1). The other time at 16°C, subjects were fed in EB during both days (16EB1, 16EB2). This experimental setup allowed us to correct for the possible acclimation effects of a lowered
ambient temperature on EE. For pairwise comparison of 22 and 16°C,
16EB2 (day 2) was compared with 22EB, and 16AL with 22AL.
Feeding in energy balance was based on individually calculated energy
requirements: after measurement of SMR during the first night in the
respiration chamber, an estimated 24-h energy requirement was
calculated by multiplying SMR with a PAI of 1.65 (21).
Twenty-four-hour energy intake was 12.7 ± 2.0 MJ at 16°C and
11.9 ± 2.2 MJ at 22°C. Food composition and regimens at 22 and
16°C were identical. Macronutrient composition, by percent energy for
carbohydrate, protein, and fat, was 49:15:36.
The clothing was identical during all experiments and was tested before
each protocol began to assure comfort at 16°C as well as at 22°C.
During the day (0800-2400), the outfit consisted of 1 T-shirt, 1 cotton shirt, 1 jogging shirt (70% cotton, 30% polyester), 1 pair of
jogging trousers (50% cotton, 50% polyester), and a pair of sport
shoes. Subjects did not wear socks. The total insulative capacity of
the clothing amounted to 0.71 Clo. At night (2400-0800), subjects were asked to wear a T-shirt and boxer shorts and to lie under
a cotton sheet and duvet (375 g/m2). Daily activities were
standardized by describing every hour, and sometimes every 15 min, what
the subjects were supposed to do. These activities included household
activities, extensive standardized aerobic exercise, and sedentary
activities, such as reading and watching television. Also, meal and
snack times were standardized.
Statistics.
Body temperatures, temperature gradients, and EE components of the six
test days (16EB1, 16EB2, 16EB3, 16AL, 22EB, 22AL) were compared using
subjects, environmental temperature, and feeding regimen as independent
variables with factorial analyses of variance (ANOVA). For post hoc
pairwise comparisons, Student's t-test was used.
To assess the relationship between body temperature and energy
metabolism, EE parameters were adjusted for body composition by
performing multiple regression of energy expenditure (in MJ/day) against fat mass and fat-free mass (in kg) (15). For each
subject, the adjusted metabolic rate (i.e., the residual) was
calculated by subtracting the predicted value, by use of the regression
equation, from the actually measured metabolic rate.
For tracking of the body temperatures or EE throughout the different
experiments, individuals were ranked per test day. By ANOVA, it was
investigated whether the ranking was consistent throughout the
different days.
Statistical analyses were performed using STATVIEW SE+Graphics, ABACUS
concepts (Berkeley, CA). Outcomes were regarded as statistically
significantly different if P < 0.05.
 |
RESULTS |
Body temperature: individual differences.
Variations in body temperature (rectal, proximal skin, and distal skin)
were explained by individual differences and by environmental temperature (factorial ANOVA, Table 1).
There was no significant effect of the feeding regimen on body
temperatures. The site-specific skin temperature measurements revealed
comparable results (data not shown).
Rectal temperatures on day 1 and day 2 during all
experiments were significantly correlated, emphasizing
individual specific body temperatures. This holds for 24-h rectal
temperature (e.g., 16°C EB, day 1 and day 2:
R2 = 0.98, P < 0.0001), as
well as daytime rectal temperature (e.g., 16°C EB, day 1 and day 2: R2 = 0.95, P < 0.0001; see Fig. 2).
For tracking the body temperatures throughout the different
experiments, each individual was ranked according to body temperature.
By ANOVA, this ranking was consistent throughout the different
environmental temperatures or feeding regimens [24-h T rectal
(Trec): F = 37.6, df = 8, P < 0.0001].

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Fig. 2.
Relationship between day-time rectal temperatures
(Trectal) on the two consecutive days at 22°C
(R2 = 0.90, P < 0.0001).
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Ranking according to distal and proximal skin temperatures were also
significantly consistent throughout the experiments [distal (Tdis): F = 5.7, df = 8, P < 0.0001; proximal (Tprox): F = 8.9, df = 8, P < 0.0001].
Body temperature: response to mild cold.
At 16°C, mean proximal skin temperatures were 1.2-1.5°C lower
than those at 22°C (Table 1). Body core temperature at 16°C was
significantly 0.2 ± 0.15°C lower than at 22°C during EB only (P < 0.02).
Temperature gradients increased significantly at 16°C compared
with 22°C (all P values <0.005, Table 1).
Temperature gradients between days were also significantly related at
16°C (16EB1 and 16EB2, Trec-Tdis:
R2 = 0.80 P < 0.001;
Trec-Tprox: R2 = 0.94, P < 0.0001; for example, see Fig.
3). At 22°C only,
Trec-Tprox was related between day 1 and day 2 (R2 = 0.73, P < 0.01).

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Fig. 3.
Relationship between the gradients
(Trectal-Tproximal) on 2 consecutive days at
16°C during energy balance (EB, R2 = 0.94, P < 0.0001).
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The 22 to 16°C changes in body temperatures during EB were
significantly related to those from AL experiments for daytime Trec (R2 = 0.83, P < .001). This indicates that not only body
temperatures and body temperature gradients, but also the response to
the changes in environmental temperature, showed interindividual differences.
EE.
EB (24-h energy intake minus EE) was not significantly different from
zero during the EB test days but was significantly increased during AL
feeding at both 16°C (4.54 ± 2.23 MJ/day, P < 0.001) and 22°C (4.07 ± 1.97 MJ/day, P < 0.001, Table 2).
Apart from individual differences in 24-h EE, there was a significant
effect of environmental temperature and also an effect of the feeding
regimen (factorial ANOVA P < 0.05, Table 2). The same
accounts for the TEF and AEE. There were no significant effects of the
environmental temperature and feeding regimens on SMR and the PAI. At
16°C, 24-h EE is increased compared with that at 22°C. This holds
for the EB situation (16EB2 vs. 22EB) as for the AL (16AL vs. 22AL)
situation. The increased TEF at 16°C compared with 22°C is
significant only in the EB situation.
Twenty-four-hour EE and TEF were elevated during AL feeding compared
with EB at both environmental temperatures (Table 2, compare 16EB3 and
16AL, and 22EB and 22AL).
Adjusted values of 24-h EE and SMR were significantly related between
day 1 and day 2 within each test (Fig.
4, A and B). Comparing the results of the six test days also revealed that the
adjusted 24-h EE and SMR values were significantly related (rank test
24-h EE: F = 35.70 , df = 8, P < 0.0001; SMR: F = 41.11, df = 8, P < 0.0001), which emphasized that EE is an individual trait, even after
adjustment for fat-free mass and fat mass.

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Fig. 4.
A: relationships between sleeping metabolic
rates (SMR), adjusted for fat mass (FM) and fat-free mass (FFM), on 2 consecutive days. Adjusted SMR is depicted as the residual from the
relationship of SMR against FM and FFM. Data from all experiments:
, 16°C, EB, R2 = 0.97, P < 0.0001; , 16°C, EB-AL,
R2 = 0.85, P < 0.0005;
, 22°C, R2 = 0.98, P < 0.0001. B: relationships between 24-h
EE, adjusted for FM and FFM, on 2 consecutive days. Adjusted 24-h EE is
depicted as the residual from the relationship of SMR against FM and
FFM. Data from all experiments: , 16°C, EB,
R2 = 0.99, P < 0.0001;
, 16°C, EB-AL, R2 = 0.82, P < 0.005; , 22°C,
R2 = 0.86, P < 0.0005.
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The 16-22°C changes in 24-h EE and SMR, adjusted for body
composition from EB, were significantly related to those from AL experiments (P < 0.01 and P < 0.05, respectively).
Relations between body temperature and EE.
At 22°C, 24-h EE and SMR, adjusted for body composition, were related
to rectal temperature at day 1 (24-h EE:
R2: 0.46, P = 0.06; SMR:
R2: 0.54, P < 0.05) and
day 2 (24-h EE: R2: 0.83, P < 0.005, Fig. 5; SMR:
R2: 0.64, P < 0.02). AEE was
related to rectal temperature on day 2 only [AEE day
1: not significant (NS), AEE day 2:
R2: 0.82, P < 0.005]. SMR was
related to rectal temperature at night on day 1 only
(R2: 0.62, P < 0.02).

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Fig. 5.
Twenty-four-hour (24-h) EE, adjusted for FM and FFM,
plotted against rectal temperature (R2 = 0.83, P < 0.002). Adjusted 24-h EE is depicted as the
residual from the relationship of SMR against FM and FFM.
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In search for acclimation effects, 16°C EB values on day 1 and day 2 were compared. Twenty-four-hour EE, TEF, and AEE
were elevated on day 2. No apparent significant differences
in body temperatures were found. However, clearly individual
differences were evident: some individuals increased their gradient
(Trec-Tprox), whereas others decreased that
gradient. Twenty-four-hour EE increased on average, but with large
individual differences (mean change in 24-h EE: 0.8 ± 0.7 MJ/day). The relation between the change in temperature gradients was
significantly negatively related to the change in 24-h EE (Fig.
6). This means that those subjects without or with little increase in 24-h EE showed no change or an
increase in their body temperature gradient, whereas those that
increased their 24-h EE showed a decrease in their body temperature gradient.

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Fig. 6.
Changes from day 1 to day 2 in body
temperature gradient (Trectal-Tproximal)
plotted against changes in 24-h EE (R2 = 0.82, P < 0.002). Data from EE experiment at 16°C
(16EB1 and 16EB2).
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 |
DISCUSSION |
Short-term exposure of normal-weight men who were used to an
ambient temperature of 22°C (normal temperature in the building and
in most rooms in the Netherlands) to 16°C caused a significant decrease in body temperature (both skin and core), an increase in
temperature gradients, and an increase in EE. It was demonstrated that
both body temperatures and EEs adjusted for body composition were
subject specific. This was shown by significant correlations between
these measurements on the different test days and by a rank correlation
test comparing the results from six different test days. EEs (24-h EE
and SMR adjusted for body composition) were significantly related to
body core temperature (Trec 24-h and Trec
night, respectively). In response to mild cold, the change in body
temperature gradients was negatively related to changes in EE. This
shows that interindividual differences exist with respect to the
relative contribution of metabolic and insulative adaptations to cold.
Individual differences in body temperature.
Studies on interindividual variation in body set point temperature in
humans are very scarce. One of the oldest studies on a large group is
from Wunderlich (27). Although this study noted individual
differences in axillary body temperature, it was not until 1992, when
Rising et al. (18) in their reexamination of the Minnesota
semi-starvation study showed that (oral) body temperatures varied more
between individuals than can be attributed to intraindividual variance.
Recently we showed interindividual variation in tympanic temperature in
a study in women in which the environmental temperatures of 27 and
22°C were compared (13). Oral and tympanic (by infrared sensor) temperatures may not be representative measures of core temperature. In situations in which body temperatures do not fluctuate very fast, core temperature can be measured rectally (24).
Our data on significant interindividual variance in rectal temperature thus provide the strongest evidence so far that, indeed, different individuals regulate body temperature to different set points.
Individual differences in EE and relation to body temperature.
The largest ranges in adjusted 24-h EE and SMR were
1.73 to 1.42 MJ/day (during 16°C AL) and
1.34 to 1.21 MJ/day (during 16°C EB),
respectively. The range of SMR (2.6 MJ/day), which might be diminished
because of cover use during the night, approaches the range reported
for Pima Indians of 3 MJ/day (18). Regression analyses and
rank correlation both showed significant interindividual variance in
adjusted 24-h EE, SMR, and AEE. Thus, as with body temperature, the
relative level of EE is individually specific, possibly genetically
determined. We have shown previously that uncoupling proteins might be
one of the determinants underlying the variation in SMR adjusted for
fat-free mass (22). The magnitude of the range in EE just
mentioned has large physiological and clinical consequences, as shown
by Rising et al. (18) and Ravussin et al.
(16).
In search for relations between body temperature and EE, we used the
data of the 22°C test, which could be considered to be the subjects'
habitual environmental temperature. Indeed, 24-h EE and SMR, adjusted
for body composition, were related to 24-h rectal temperatures.
Adjusted SMR values were related to night rectal temperatures on
day 1. It follows that the relation between 24-h EE and
rectal temperature can partly be explained by the relation between SMR
and night temperatures. Apart from SMR, the relation between 24-h EE
and body temperature can be explained by activity. Indeed, adjusted AEE
was significantly related to 24-h Trec on day 1.
As indicated previously (13), because the daily activities
protocol was standardized, the differences in AEE can be explained by
the so-called nonexercise activity thermogenesis, or NEAT
(12). The relative contribution of AEE and RMR to the relation between 24-h EE and body temperature is difficult to unravel.
Stepwise regression indicates a significant contribution of SMR to 24-h
Trec, without inclusion of AEE. Of course, body temperature
is an effect not only of EE, but also of (individual differences in)
heat dissipation, which is subject to further investigation.
Response to mild cold.
The slight but significant decrease in core body temperature at 16°C
relative to 22°C, combined with much larger decreases in skin
temperatures, conforms to earlier studies: mild cold was shown to
increase the temperature gradient, i.e., a reduction of peripheral
temperature at relatively constant core temperature (8).
Our results indicate that the increase in 24-h EE can be attributed to
the increases of TEF, AEE, and possibly nonshivering thermogenesis.
Adjacent to our finding that different individuals regulate body
temperature to different set points, our data indicate that changes in
body temperature in different situations are individual specific. This
is shown by the significant relation between changes in skin
temperature from 22 to 16°C in the comparison of days 1 and 2. Although differences in response to (mild or more
severe) cold between groups have been reported before (1, 9, 10, 20), to our knowledge this relation has not been shown before on
an individual level within a population.
In response to the mild cold, 24-h EE increased slightly (EB:
EE = 0.74 MJ/day; AL:
EE = 0.48 MJ/day) but
significantly, comprising an increase of 6 and 4%, respectively. This
approaches the values reported by Dauncey (7), who found
an increase in 24-h EE of 7% over a comparable change in environmental
temperature (6°C).
Combining the results of EE and body temperatures, we found a
significant relation between the changes from day 1 to
day 2 during the 16°C test in body temperature gradient
(rectal to proximal) and the change in 24-h EE
(R2 = 0.82). This means that those subjects
with hardly any increase in 24-h EE showed an increase or no change in
the temperature gradient, whereas those with a clear increase in 24-h
EE showed a decrease in the temperature gradient. In other words, there is a continuum between those subjects showing a metabolic adaptation during the two test days with a decrease of their insulative component and those showing hardly any or no metabolic adaptation, with no change
or even an increase in their insulative component. The magnitude of
changes within individuals (max change in EE: 1.5 MJ/day; body
temperature gradient: 0.5°C) approaches the interindividual differences that may have significant physiological and clinical metabolic consequences (13, 18).
The interindividual differences in response to a cold environment
implicate individual differences in energy-conserving mechanisms that may explain individual differences in predisposition to obesity. Whether these differences are of genetic origin cannot be deduced from
this study. It was shown several decades ago that adaptive changes to
cold exposure can be brought about experimentally in humans
(6). This means that the differences in response to the
mild cold can partly be explained by differences in daily living
circumstances. Nevertheless, a genetic component cannot be ruled out
and deserves further investigation.
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ACKNOWLEDGEMENTS |
We thank Paul Schoffelen for assistance with the respiration
chamber measurements and Loek Wouters for helping with the body temperature registrations. We also appreciate the enthusiastic support
of Heidi Strobbe and the constructive comments of an anonymous reviewer.
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FOOTNOTES |
Address for reprint requests and other correspondence:
W. D. van Marken Lichtenbelt, P. Schrauwen, and/or M. S. Westerterp-Plantenga, Dept. of Human Biology, Maastricht Univ., PO
Box 616, 6200 MD Maastricht, The Netherlands (E-mail:
MarkenLichtenbelt{at}HB.unimaas.NL; P.Schrauwen{at}HB.unimaas.NL;
M.Westerterp{at}HB.unimaas.NL).
The costs of publication of this
article were defrayed in part by the
payment of page charges. The article
must therefore be hereby marked
"advertisement"
in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
First published January 8, 2002;10.1152/ajpendo.00020.2001
Received 22 January 2001; accepted in final form 2 January 2002.
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