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Humans show considerable interindividual variation in susceptibility to weight gain in response to overeating. The physiological basis of this variation was investigated by measuring changes in energy storage and expenditure in 16 nonobese volunteers who were fed 1000 kilocalories per day in excess of weight-maintenance requirements for 8 weeks. Two-thirds of the increases in total daily energy expenditure was due to increased nonexercise activity thermogenesis (NEAT), which is associated with fidgeting, maintenance of posture, and other physical activities of daily life. Changes in NEAT accounted for the 10-fold differences in fat storage that occurred and directly predicted resistance to fat gain with overfeeding (correlation coefficient = 0.77, probability < 0.001). These results suggest that as humans overeat, activation of NEAT dissipates excess energy to preserve leanness and that failure to activate NEAT may result in ready fat gain.
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used a double-wall Couette apparatus with gap of 1
mm and measured the frequency dependence of the
storage modulus G9(v) and loss modulus G0(v)ina
small-amplitude oscillatory shear experiment.
22. Without preshearing, G9(v) and G0(v) indicated sol-
id-like behavior similar to that reported for pure
smectics (7, 8) but with magnitudes of the moduli
three to four orders of magnitude smaller. This result
is consistent with the presence of a persistent mac-
roscopically disordered texture of cholesteric layers.
23. Recall that a solid is characterized by G9(v) 3
const Þ 0 and G0(v) 3 0asv 3 0; this implies G9(v)
. G0(v) at sufficiently low frequencies. In a liquid, in
contrast, G9(v)/G0(v) 3 0asv 3 0.
24. In addition to the measurements in the linear vis-
coelastic regime (u # 0.05) described above, we
measured G9(v,u) and G0(v,u) at strain amplitudes u
up to 0.4 and found uG9(v,u) to be practically u-
independent for 0.2 # u # 0.4 and v # 5 rad/s. The
low-frequency limit of uG9(v,u) in this range of u is
the yield stress s
, which we measured to be 0.04
dyne. The strain value u
. 0.15 at which uG9(v,u)
begins to saturate agrees well with s
9 . 0.2,
where G
950.2 dyne/cm
is the elastic shear mod-
ulus in the linear regime, thus providing an internal
consistency check of our data.
25. We thank T. Martin for participation in the early
stages of this project, V. Trappe for help with rhe-
ometry, and O. Lavrentovich for useful discussions.
This work was supported primarily through NSF grant
DMR95-07366, as well as the bourse Lavoisier du
Ministe`re Franc¸ais des Affaires Etrange`res.
11 September 1998; accepted 8 December 1998
Role of Nonexercise Activity
Thermogenesis in Resistance to
Fat Gain in Humans
James A. Levine, Norman L. Eberhardt, Michael D. Jensen*
Humans show considerable interindividual variation in susceptibility to weight
gain in response to overeating. The physiological basis of this variation was
investigated by measuring changes in energy storage and expenditure in 16
nonobese volunteers who were fed 1000 kilocalories per day in excess of
weight-maintenance requirements for 8 weeks. Two-thirds of the increases in
total daily energy expenditure was due to increased nonexercise activity ther-
mogenesis (NEAT), which is associated with fidgeting, maintenance of posture,
and other physical activities of daily life. Changes in NEAT accounted for the
10-fold differences in fat storage that occurred and directly predicted resistance
to fat gain with overfeeding (correlation coefficient 5 0.77, probability , 0.001).
These results suggest that as humans overeat, activation of NEAT dissipates
excess energy to preserve leanness and that failure to activate NEAT may result
in ready fat gain.
Weight gain occurs in healthy adults when
energy intake persistently exceeds energy ex-
penditure. Some individuals appear to in-
crease energy expenditure in response to
overeating without increasing volitional exer-
cise and thus maintain a stable body weight.
This interindividual variation in weight gain
with overfeeding (1, 2) suggests that a ther-
mogenic mechanism or mechanisms may be
activated to prevent weight gain or obesity.
When humans are overfed, more than 85%
of the stored excess energy is deposited as lipid
(3), primarily triglycerides. Lipid is ideally suit-
ed for long-term energy storage in mammals; it
is calorie-dense and hydrophobic, so that stor-
age occurs without water accumulation. In the
presence of persistent, positive energy balance,
enormous quantities of triglyceride can be
stored through increases in adipocyte size and
number (4, 5). Even lean individuals store
enough fat to meet energy requirements for
more than 1 month, whereas some obese indi-
viduals have fat stores that would exceed ener-
gy requirements for a year (6, 7). However,
why some people appear to accumulate adipose
tissue more efficiently than others is unclear
The efficiency of energy storage is calculat-
ed by dividing the excess calories stored by the
excess calories consumed. Energy storage effi-
ciency can never equal unity because heat trans-
fer is not perfect. An energy efficiency of zero
would indicate that all excess energy consumed
is dissipated through increased energy expendi-
ture. It has been argued that efficient energy
storage is beneficial because it allows longer
survival during famine. However, for many
Western populations, where food supply is
abundant and readily available, efficient energy
storage predisposes to obesity, the accumula-
tion of excess body fat. Obesity affects more
than one-third of the U.S. population and is a
major public health concern because it is asso-
ciated with diabetes, hypertension, hyperlipid-
emia, and cardiovascular disease (9).
Some humans appear to resist fat gain
with overeating, whereas others readily store
excess fat. These subjective observations
have been confirmed by a small number of
clinical studies that document a severalfold
interindividual variation in fat accumulation
with overfeeding (1, 2, 10). However, the
thermogenic adaptation that allows some in-
dividuals to resist weight gain despite over-
eating has not been identified.
To address this question, we designed a
study that allowed us to identify which compo-
nent or components of energy expenditure
showed enough variability to account for the
variability in resistance to fat gain during over-
feeding. Sixteen nonobese adults (12 males and
4 females, ranging in age from 25 to 36 years)
underwent measures of body composition and
energy expenditure before and after 8 weeks of
supervised overfeeding by 1000 kcal/day. Body
composition was measured with dual energy
x-ray absorptiometry (DXA) (11), and total dai-
ly energy expenditure was measured with dou-
bly labeled water (10, 12). The latter procedure
required the administration of water containing
J. A. Levine and M. D. Jensen, Department of Medicine,
Endocrine Research Unit, Mayo Clinic and Mayo Foun-
dation, 200 First Street Southwest, Rochester, MN
55905, USA. N. L. Eberhardt, Departments of Medi-
cine and of Biochemistry and Molecular Biology, En-
docrine Research Unit, Mayo Clinic and Mayo Foun-
dation, 200 First Street Southwest, Rochester, MN
55905, USA.
*To whom correspondence should be addressed. E-
Table 1. Energy partitioning in 16 healthy human volunteers who were fed 1000 kcal/day (4.2 MJ) in
excess of weight maintenance requirements for 8 weeks. Additional data are available at www.
Variable (unit) Mean Range
Baseline weight (kg) 65.8 53.3–91.7
Overfed weight (kg) 70.5 58.8–93.1
Weight gain (kg) 4.7 1.4–7.2
Fat gain (kcal/day)* 389 58687
Fat-free mass gain (kcal/day)* 43 15–78
Baseline dietary intake (kcal/day) 2824 2265–3785
Baseline resting energy expenditure (kcal/day) 1693 1470–1990
Overfed resting energy expenditure (kcal/day) 1772 1460 –2040
Baseline thermic effect of food (kcal/day) 218 89414
Overfed thermic effect of food (kcal/day) 354 133–483
Baseline total energy expenditure (kcal/day) 2807 2216–3818
Overfed total energy expenditure (kcal/day) 3361 25084601
*Energy contents of tissues were calculated with published constants (3).
8 JANUARY 1999 VOL 283 SCIENCE www.sciencemag.org212
isotopes of oxygen and hydrogen to the volun-
teers and measurement of the clearance of the
two isotopes from the body. The difference in
clearance of the two isotopes represents carbon
dioxide production (10, 12), which in turn re-
flects energy expenditure. These measurements
allowed us to observe how overeating affects
energy partitioning (Table 1). On average, 432
kcal/day of the excess energy ingested was
stored and 531 kcal/day was dissipated through
increased energy expenditure, thereby account-
ing for 97% of the additional 1000 kcal/day
(implying optimal compliance). Fat gain varied
10-fold among our volunteers, ranging from a
gain of only 0.36 kg to a gain of 4.23 kg, and
was inversely related to the increase in total
daily energy expenditure (r 520.86, P ,
Total daily energy expenditure is com-
posed of basal metabolic rate (BMR), post-
prandial thermogenesis, and physical activity
thermogenesis. BMR is the rate at which
energy is expended when an individual is
laying down at rest in the postabsorptive
state. We assessed BMR by using indirect
calorimetry to measure oxygen consumption
and carbon dioxide production (13). Changes
in BMR would be unlikely to account for the
10-fold variance in fat gain among our vol-
unteers because previous investigators have
found only modest increases (;10%) with
overfeeding (10, 14). In our study, BMR
increased by an average of 5% in response to
overfeeding (Table 2), accounting for 8% of
the excess ingested energy. Thus, the interin-
dividual changes in BMR did not account for
the variability in fat gain (Fig. 1A).
Postprandial thermogenesis is the increase
in energy expenditure associated with the
digestion, absorption, and storage of food. It
may be the invariant energy cost of convert-
ing food to metabolic fuels (15, 16 ), or it may
be actively regulated in response to changing
food intake (17, 18). We measured postpran-
dial thermogenesis using indirect calorimetry
and found that it increased by 14% with
overfeeding (Table 2). This increase was
more likely due to greater dietary intake (16 )
than to an adaptive response because the
thermic response to a meal of fixed energy
content (200 kcal, 0.8 MJ) was the same
before and after overfeeding (11 6 5 com-
pared with 12 6 7 kcal per meal), consistent
with observations of other investigators (14).
Furthermore, interindividual differences in
postprandial thermogenesis did not correlate
with fat gain (Fig. 1B), suggesting that this
was not a significant factor in fat gain.
Physical activity thermogenesis can be sub-
divided into volitional exercise (sports and fit-
ness-related activities) thermogenesis and what
we characterize as nonexercise activity thermo-
genesis (NEAT). NEAT is the thermogenesis
that accompanies physical activities other than
volitional exercise, such as the activities of
daily living, fidgeting, spontaneous muscle con-
traction, and maintaining posture when not re-
cumbent. The possibility that NEAT might me-
diate resistance to fat gain intrigued us because
spontaneous physical activity (a component of
NEAT) is a familial trait (19) that shows
marked interindividual differences in its contri-
bution to daily energy expenditure (19, 20) and
is somewhat predictive of future weight gain
(21). Also, nonresting energy expenditure
(which includes NEAT) increases in adults sub-
jected to a controlled 10% weight gain (22).
Finally, in previous overfeeding studies (3), it
has been possible to account for only ;30% of
the calories that are “wasted” through increased
energy expenditure. If NEAT accounts for the
remaining 70%, then variable activation of
NEAT in response to overeating could explain
the wide variations in weight gain.
Measurement of overfeeding-induced chang-
es in NEAT is formidable because of the
complexity of differentiating NEAT from vo-
litional exercise thermogenesis in free-living
humans. We accomplished this differentia-
tion by stringently maintaining volitional ex-
ercise at constant, low levels, and we con-
firmed compliance through questionnaires
and direct measures of physical activity. Al-
though we appreciated that volitional exer-
cise might change in response to overeating,
we viewed this as a behavioral rather than a
physiological adaptation and so elected to
eliminate it as a confounding variable. Be-
cause changes in exercise efficiency would
affect physical activity thermogenesis (23),
this variable was also measured. If the level
and efficiency of volitional exercise remained
constant over time, then changes in physical
activity thermogenesis (NEAT plus volitional
exercise) would represent changes in NEAT.
Hence, we assessed physical activity thermo-
genesis before and after overfeeding by mea-
suring total daily energy expenditure using
doubly labeled water and subtracting from it
the sum of basal and postprandial energy
expenditure. These steps allowed us to assess
whether changes in NEAT mediate resistance
to fat gain with overfeeding.
NEAT proved to be the principal mediator
of resistance to fat gain with overfeeding. The
average increase in NEAT (336 kcal/day)
accounted for two-thirds of the increase in
daily energy expenditure (Table 2), and the
range of change in NEAT in our volunteers
was large (298 to 1692 kcal/day). However,
most importantly, changes in NEAT directly
predicted resistance to fat gain with overfeed-
ing (Fig. 1C), and this predictive value was
not influenced by starting weight (24).
Thus, activation of NEAT can explain the
variability in fat gain with overeating. As hu-
mans overeat, those with effective activation of
NEAT can dissipate the excess energy so that it
is not available for storage as fat, whereas those
with lesser degrees of NEAT activation will
likely have greater fat gain and be predisposed
to develop obesity. The maximum increase in
NEAT that we detected (692 kcal/day, volun-
teer 5) could be accounted for by an increase in
strolling-equivalent activity (25) by about 15
Fig. 1. The relation of the change in (A) basal metabolic rate, (B) postprandial thermogenesis, and
(C) activity thermogenesis with fat gain after overfeeding (2733). Exercise levels and the thermic
efficiency of exercise were unchanged with overfeeding, so that changes in activity thermogenesis
represent changes in NEAT.
Table 2. The fate of the excess 1000 kcal/day consumed by 16 volunteers during 8 weeks of overfeeding.
Data are expressed as kilocalories per day.
Variable Mean Standard deviation Range
Fat mass gain* 389 188 58687
Fat-free mass gain* 43 22 15–78
Change in resting energy expenditure 79 126 2100–360
Change in thermic effect of food 137 83 28.2–256
Change in NEAT 328 256 298.3–692
*Energy contents of tissues were calculated with published constants (3).
min/hour during waking hours. Of interest, the
four lowest values for change in NEAT corre-
sponded to the four female volunteers, although
the relation between change in NEAT and fat
gain was the same in males and females. A
larger study will be needed to determine the
significance of the preliminary gender differ-
ences noted here. Another limitation of our
study is the small errors inherent in measuring
energy expenditure and body composition in
physiological studies. Because these errors are
cumulative, they would be expected to weaken
the association between the change in NEAT
and the change in body fat. Thus, it is possible
that we have underestimated the contribution of
NEAT activation to the resistance to fat gain
with overfeeding.
Finally, our results suggest that efforts to
enhance NEAT activation, perhaps through
behavioral cues, may be a fruitful approach to
the prevention of obesity.
References and Notes
1. E. A. Sims et al., Recent. Prog. Horm. Res. 29, 457
2. C. Bouchard et al., N. Engl. J. Med. 322, 1477 (1990).
3. O. Deriaz, A. Tremblay, C. Bouchard, Obes. Res. 1, 179
4. J. B. Prins and S. O’Rahilly, Clin. Sci. 92, 3 (1997).
5. J. A. Levine, M. D. Jensen, N. L. Eberhardt, T. O’Brien,
J. Clin. Invest. 101, 1557 (1998).
6. A. E. Black, W. A. Coward, T. J. Cole, A. M. Prentice,
Eur. J. Clin. Nutr. 50, 72 (1996).
7. G. F. Cahill, N. Engl. J. Med. 282, 668 (1970).
8. E. A. Sims and E. Danforth, J. Clin. Invest. 79, 1019
9. W. P. James, Int. J. Obes. Relat. Metab. Disord. 16,
S23 (1992).
10. E. O. Diaz, A. M. Prentice, G. R. Goldberg, P. R.
Murgatroyd, W. A. Coward, Am. J. Clin. Nutr. 56, 641
11. B. M. Prior et al., J. Appl. Physiol. 83, 623 (1997).
12. W. A. Coward, S. B. Roberts, T. J. Cole, Eur. J. Clin.
Nutr. 42, 207 (1988).
13. E. Jequier and J. P. Felber, Bailliere’s Clin. Endocrinol.
Metab. 1, 911 (1987).
14. A. Tremblay, J. P. Despres, G. Theriault, G. Fournier, C.
Bouchard, Am. J. Clin. Nutr. 56, 857 (1992).
15. J. O. Hill, S. B. Heymsfield, C. D. McMannus, M.
DiGirolamo, Metabolism 33, 743 (1984).
16. D. A. Alessio et al., J. Clin. Invest. 81, 1781 (1988).
17. K. R. Segal et al., ibid. 89, 824 (1992).
18. E. Ravussin, B. Burnand, Y. Schutz, E. Jequier, Am. J.
Clin. Nutr. 41, 753 (1985).
19. E. Ravussin, S. Lillioja, T. E. Anderson, L. Christin, C.
Bogardus, J. Clin. Invest. 78, 1568 (1986).
20. S. Toubro, N. J. Christensen, A. Astrup, Int. J. Obes.
Relat. Metab. Disord. 19, 544 (1995).
21. F. Zurlo et al., Am. J. Physiol. 263, E296 (1992).
22. R. L. Leibel, M. Rosenbaum, J. Hirsch, N. Engl. J. Med.
332, 621 (1995).
23. J. Kang et al., Med. Sci. Sports Exercise 29, 377
24. If total daily energy expenditure measured with dou-
bly labeled water is assumed to equal weight main-
tenance requirements (rather than the measures of
weight maintenance dietary intake), the relation be-
tween the increase in NEAT and the efficiency of
energy storage (excess kilocalories stored/number of
excess kilocalories provided) is almost identical to the
relation we report in Fig. 1C (r 520.80, P , 0.001,
compared with r 520.77, P , 0.001).
25. N. G. Norgan and J. V. Durnin, Am. J. Clin. Nutr. 33,
978 (1980).
26. W. A. Coward, Proc. Nutr. Soc. 47, 209 (1988).
27. The 16 (12 males and 4 females) healthy volunteers
were 25 to 36 years old. Volunteers were excluded if
they used any medication at the time of the study or
within 6 months of the study, exercised more than
twice each week, smoked, used alcohol, were preg-
nant, had any acute or chronic illness, or reported
unstable body weight.
28. Volunteers were studied as outpatients for 10 weeks.
Meals were prepared in the metabolic kitchen at the
Mayo Clinic General Clinical Research Center (GCRC).
All foods were weighed to within 1 g. For the first 2
weeks, volunteers were fed so as to establish the dietary
intake necessary to maintain steady-state body weight.
For the remaining 8 weeks, each volunteer received
1000 kcal in addition to weight maintenance require-
ments. The diet composition remained constant
throughout the study at 40% carbohydrate, 40% fat,
and 20% protein. The volunteer’s body weight was
measured each morning under standardized conditions
(with an empty bladder, without shoes, and wearing
consistent, light clothing); these measures were made
by GCRC personnel. Volunteers were instructed not to
adopt new exercise practices and were questioned daily
regarding activities. In addition, volunteers’ family and
friends underwent structured interviews before and af-
ter feeding to determine compliance with exercise re-
strictions. During weeks 2 and 10, volunteers wore
accelerometers (with disabled liquid crystal displays)
(Caltrac; Muscle Dynamics, Torrance, CA) to measure
the extent of free-living exercise-related activity. To
ensure compliance with the feeding regimen, volunteers
were instructed to eat all foods provided, and almost all
meals were consumed under supervision at the GCRC.
Plates were inspected for solid or liquid remainders.
When food items were eaten outside of the GCRC,
preweighed food items were provided by the investiga-
tors, and empty food containers were inspected. On
occasion, volunteers’ home garbage was checked. Fam-
ily members, friends, and work colleagues of the volun-
teers were identified and contacted on several occa-
sions throughout the study to ensure that all food was
consumed and that exercise was not initiated. Informed
consent was obtained after the nature and possible
consequences of the study were explained.
29. Each volunteer was weighed daily with the same cali-
brated scale. Body fat and mineral mass were measured
in duplicate with DXA after baseline feeding (end of
week 2) and after completion of overfeeding (end of
week 10). To ensure that our measures of body com-
position were reproducible and precise, (i) we used the
same DXA scanner throughout the study, (ii) we cali-
brated the DXA scanner before each measurement with
tissue phantoms, and (iii) we calibrated the DXA scan-
ner against tissue blocks of known composition weekly.
A human adipose tissue block with a lipid content of
2891 g by chemical analysis was found to be 2949 g by
DXA scans. Comparison of fat-free mass obtained with
the DXA and isotope dilution revealed a strong corre-
lation (r 5 0.97, P , 0.0001). Finally, when a 600-g
block of adipose tissue was placed on a volunteer with
22.8 kg of body fat as assessed by DXA, 577 g of this
block was detected. Fat-free mass was calculated from
the difference between body weight and fat mass. The
test-retest difference for duplicate measurements was
30. BMR was measured on two consecutive mornings at
0630 in volunteers who had slept uninterrupted the
previous nights in the GCRC. Volunteers were not
moved before measurements and had not eaten since
2100 the night before. For each measurement, the
calorimeter (Deltatrac; SensorMedics, Yorba Linda, CA)
was calibrated with gases of known composition. Vol-
unteers were awake, semirecumbent (10° head bed tilt),
lightly clothed, and in thermal comfort (68° to 74°F) in
a dimly lit, quiet room. Measurements were performed
for 30 min during which time volunteers were not
allowed to talk or move. The test-retest difference for
duplicate measurements was ,3%.
31. Postprandial thermogenesis was measured on two
consecutive days at the end of weeks 2 and 10. On
the first study day, volunteers were given a meal that
provided one-third of their daily intake (40% carbo-
hydrate, 40% fat, and 20% protein). Energy expen-
diture was measured with the indirect calorimeter for
15 of every 30 min (to prevent agitation) until values
within 4 kcal/hour of resting energy expenditure
were recorded for two consecutive measurements.
On the second day, volunteers were provided with a
200-kcal meal (40% carbohydrate, 40% fat, and 20%
protein), and the same procedures were followed.
Areas under the curves for time (x axis) and energy
expenditure ( y axis) were used to determine post-
prandial thermogenesis. The mean duration of mea-
surement was 414 6 (SD) 39 min. Daily postprandial
thermogenesis was calculated by tripling the post-
prandial thermogenesis obtained after the meal pro-
viding one-third of daily intake.
32. Total energy expenditure was measured in weeks 2 and
10 with doubly labeled water (12, 26). Baseline urine
samples were collected, and after timed administration
of the isotopes, urine samples were collected at 0700,
1200, and 1800 each day for 7 days. The slope-intercept
equations described by Coward et al. (12) were used to
derive values for total energy expenditure. Propagation
or error analysis was performed (10) on each measure-
ment, and the calculated compounded errors (measure-
ment plus biological noise) were 3 6 1% for baseline
and 4 6 3% after overfeeding. Measures of baseline
total energy expenditure derived with doubly labeled
water were in excellent agreement with the measures
of baseline weight-maintenance dietary intake (r 5
0.89, P , 0.001, with an intercept not different from 0
and a slope not different than 1).
33. Changes in NEAT were measured by calculating activi-
ty-related thermogenesis before and after overfeeding.
Activity-related thermogenesis was determined by
measuring total energy expenditure, with doubly la-
beled water, and subtracting from it the sum of basal
energy expenditure and postprandial energy expendi-
ture. Subtraction of the value for activity-related ther-
mogenesis before overfeeding from the value obtained
after overfeeding represented the change in NEAT if
two conditions were met: (i) the total amount of voli-
tional exercise was unchanged and (ii) the thermic
efficiency of exercise was unchanged. We determined
that the amount of exercise did not change with over-
feeding on the basis of accelerometer readings [2905 6
(SD) 514 accelerometer units (AU)/day before over-
feeding compared with 2963 6 540 AU/day after over-
feeding], daily interviews with the volunteers regarding
their exercise level, and structured interviews with vol-
unteers and their relatives and friends before and after
overfeeding. The thermic efficiency of exercise was
assessed with two different measures of exercise-relat-
ed energy expenditure at the end of weeks 2 and 10.
The first measure was during treadmill walking at 3
mph (4.8 km/hour) for 10 min. Throughout this period,
inspired and expired gases were sampled for volume O
and CO
content with an integrated treadmill and gas
sampling mass spectrometer system. Mean VO
minutes 3 to 9 was calculated. The volunteers also
bicycled on a stationary bicycle at 100 W for 20 min.
Between minutes 3 to 5 and 13 to 15, exhaled air was
collected with a three-way mouth piece and leak-proof
bag. The volume of expired air for the 2-min period was
measured with a Tissot spirometer, and the O
and CO
concentrations were measured with a calibrated mass
spectrometer. Gas volumes were corrected for standard
temperature and pressure and humidity. Average oxy-
gen consumption (VO
) for the two bag collections was
calculated. The thermic responses to cycling and walk-
ing did not change with overfeeding; before overfeed-
ing, VO
during cycling at 100 W was 1693 6 39
ml/min, and after overfeeding it was 1772 6 43 ml/
min; before overfeeding, VO
during walking at 3 mph
was 1028 6 59 ml/min, and after overfeeding it was
1061 6 38 ml/min. Thus, because volitional exercise
and the thermic efficiency of exercise were unchanged
with overfeeding, any change in activity-related ther-
mogenesis after overfeeding represented the change in
NEAT. Finally, to ensure that energy wastage did not
occur through malabsorption, 3-day stool fat was mea-
sured before and after overfeeding. There was no sig-
nificant increase in stool fat after overfeeding (25 6 13
kcal/day compared with 38 6 15 kcal/day).
34. We thank the volunteers, dietitians, food technicians,
and nursing staff at the GCRC and A. Wright and
W. A. Coward for assistance with doubly labeled water
calculations. Supported by NIH grants DK45343,
DK50456, and M01 RR00585 and the Mayo Foundation.
21 May 1998; accepted 13 November 1998
8 JANUARY 1999 VOL 283 SCIENCE www.sciencemag.org214
... In response to overfeeding, the 10% from DIT will obviously give rise to a higher absolute DIT, but not in a compensatory fashion to oppose the overfeeding-induced weight gain [26]. Whereas DIT thermogenesis seems dispensable for the defence against weight gain, there is some data to support that NEAT is engaged to oppose weight gain in response to overfeeding [27]. Estimates of NEAT stem from subtracting basal metabolic rate (BMR) and DIT from total energy expenditure in response to overfeeding and the initial studies proposed that NEAT promotes resistance to weight gain [27]. ...
... Whereas DIT thermogenesis seems dispensable for the defence against weight gain, there is some data to support that NEAT is engaged to oppose weight gain in response to overfeeding [27]. Estimates of NEAT stem from subtracting basal metabolic rate (BMR) and DIT from total energy expenditure in response to overfeeding and the initial studies proposed that NEAT promotes resistance to weight gain [27]. Subsequent studies have challenged the role of NEAT and found less pronounced effects in response to overfeeding [2,28] (figure 2). ...
... In contrast with these observations, a sixweek overfeeding study from 1980 did not find remarkable inter-individual differences in faecal energy excretion [12]. Moreover, other studies in humans have not found differences in energy excretion between subjects with leanness and obesity [37], nor observed an increase in faecal energy and fat excretion in response to overfeeding [27,38,39]. Thus, it is currently unclear if increased energy excretion contributes to the defence against weight gain (figure 2). ...
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Body weight is under physiological regulation. When body fat mass decreases, a series of responses are triggered to promote weight regain by increasing food intake and decreasing energy expenditure. Analogous, in response to experimental overfeeding, excessive weight gain is counteracted by a reduction in food intake and possibly by an increase in energy expenditure. While low blood leptin and other hormones defend against weight loss, the signals that oppose overfeeding-induced fat mass expansion are still unknown. In this article, we discuss insights gained from overfeeding interventions in humans and intragastric overfeeding studies in rodents. We summarize the knowledge on the relative contributions of energy intake, energy expenditure and energy excretion to the physiological defence against overfeeding-induced weight gain. Furthermore, we explore literature supporting the existence of unidentified endocrine and non-endocrine pathways that defend against weight gain. Finally, we discuss the physiological drivers of constitutional thinness and suggest that overfeeding of individuals with constitutional thinness represents a gateway to understand the physiology of weight gain resistance in humans. Experimental overfeeding, combined with modern multi-omics techniques, has the potential to unveil the long-sought signalling pathways that protect against weight gain. Discovering these mechanisms could give rise to new treatments for obesity. This article is part of a discussion meeting issue ‘Causes of obesity: theories, conjectures and evidence (Part I)’.
... Evidence for the genetic predisposition of obesity has come from identical twin and adoption studies [3][4][5]. Differences among individuals have been shown in forced overfeeding studies where, despite a group of individuals being overfed by the same amount, a range of weight gain has been observed [11]. In those who did not gain weight, there was an increase in energy expenditure by around 2000 kJ [11]. ...
... Differences among individuals have been shown in forced overfeeding studies where, despite a group of individuals being overfed by the same amount, a range of weight gain has been observed [11]. In those who did not gain weight, there was an increase in energy expenditure by around 2000 kJ [11]. This increase in energy expenditure was caused by an increase in spontaneous movement, not as an increase in metabolic rate. ...
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Obesity is the major modifiable risk factor for osteoarthritis (OA). A major focus of management in OA is weight loss. Although we live in an obesogenic environment, obesity has a predominantly genetic and epigenetic basis. This explains a person's weight set point which is defended by biological mechanisms making weight loss difficult to achieve and maintain long term, regardless of the methods used. Significant weight regain occurs after weight loss, with weight tending to return to pre-treatment levels after cessation of interventions including the glucagon-like peptide-1 (GLP-1) agonists. An area that has received little attention is the slow, insidious weight creep of 0.5–1 kg/year over adulthood that sees individuals relentlessly increase weight. There is evidence that low intensity, personalised lifestyle interventions can prevent this weight creep, providing patients with achievable goals. In this narrative review, we examine the evidence for weight loss in OA, the biological mechanisms that make weight loss difficult to achieve and maintain and the potential negative impacts on patients. We review the evidence for preventing weight gain, the improvement in patient outcomes and the potential for significant healthcare savings through reduced knee replacements. We propose a combined approach of weight loss when indicated, together with targeting weight creep across adult years and the potential role of metformin. Implementing these combined approaches is likely to be more effective in improving patient related outcomes, reducing joint damage and healthcare costs, than our current focus on achieving weight loss in OA.
... We applied baseline data from 20 participants from a study conducted at the Mayo Clinic [18], evaluating the effects of non-exercise adaptive thermogenesis on overfeeding. The original study participants (N = 21) were approximately half-lean and half of them were individuals with obesity (BMI = 28.5 ± 6.2 kg/m 2 ). ...
Background Accurately estimating energy requirements represents a standard activity for developing effective diet and exercise interventions. Mathematical models that predict energy requirements as a product of physical activity level (PAL) and a resting energy expenditure (REE) formula is a commonly applied method to provide a first pass estimate. These estimates require knowledge of an individual's PAL and an accurate prediction of REE. Access to different anthropometric data or body composition and even REE measurements can improve and personalize predictions without making assumptions involving PAL. Methods Total energy expenditure measured by DLW and metabolic chamber from 733 subjects obtained from compiled study database of baseline measurements measured at Pennington Biomedical Research Center was applied as two different output variables. The DLW measures were applied to develop free‐living energy requirement models and the chamber data was applied to develop in‐residence energy requirement models. Twenty‐eight different linear regression models were developed that included different combinations of input variables that may be accessible to investigators and clinicians. The input variables were age, height, gender, weight, waist circumference, fat mass, fat free mass, and REE. The simplest model predicting DLW measured energy expenditures was validated on the Institute of Medicine DLW database (N=473) and compared to the product of 1.6 and the Mifflin St. Jeor prediction of REE. Results The adjusted R ² values for the models predicting free‐living energy requirements in males ranged from 0.65 with minimal covariates of age, height, and weight to 0.73 in models that included body composition or REE. For females adjusted R ² ranged from 0.68 to 0.74. The adjusted R ² values for the models predicting in‐residence energy requirements were lower (males 0.43–0.45, females (0.32–0.33). The bias in the newly developed models was −95±461 kcal/d while the bias obtained from using 1.6 times REE predicted by Mifflin St. Jeor yielded a bias of −315±444 kcal/d. Conclusions The newly developed class of models offers an improved alternative to estimating a PAL value and energy requirements using REE formulas. Additionally, when available, the models include additional covariates that improve predictions even further.
... Etiology of the Obesity Epidemic Bray (1998) has succinctly summarized the etiology of obesity: "Genes load the gun, the environment pulls the trigger." Genes are currently thought to explain 25%-40% of the variance in BMI (Bouchard, 1994;Price, 2002) and contribute to differences among people in resting metabolic rate, in weight gain in response to overfeeding, and in where excess fat is stored (i.e., body fat distribution; Bouchard, 1994;Bouchard et al., 1989Bouchard et al., , 1990J. A. Levine, Eberhardt, & Jensen, 1999). Thus, some individuals appear to be born with a genetic predisposition to obesity that is readily nurtured by our nation's lifestyle, as discussed later. ...
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Obesity has reached epidemic proportions in the United States and other developed nations. In the United States, 27% of adults are obese and an additional 34% are overweight. Research in the past decade has shown that genetic influences clearly predispose some individuals to obesity. The marked increase in prevalence, however, appears to be attributable to a toxic environment that implicitly discourages physical activity while explicitly encouraging the consumption of supersized portions of high-fat, high-sugar foods. Management of the obesity epidemic will require a two-pronged approach. First, better treatments, including behavioral, pharmacologic, and surgical interventions, are needed for individuals who are already obese. The second and potentially more promising approach is to prevent the development of obesity by tackling the toxic environment. This will require bold public policy initiatives such as regulating food advertising directed at children. The authors call not for the adoption of a specific policy initiative, but instead propose that policy research, based on viewing obesity as a public health problem, become a central focus of research.
... Variations in energy efficiency are implied in several controlled human feeding studies. Individuals who have the greatest increase in energy expenditure during overfeeding are most resistant to weight gain [68] whereas those that decrease energy expenditure most during food deprivation are most likely to gain weight [69]. Such variations are most likely genetically determined. ...
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Changes correlating with increasing obesity include insulin resistance, hyperlipidaemia, hyperinsulinaemia, highly processed food and environmental toxins including plastics and air pollution. The relationship between the appearance of each of these potential causes and the onset of obesity is unknown. The cause(s) must precede obesity, the consequence, and temporally relate to its rising incidence. Macronutrients such as carbohydrates or fats are unlikely to cause obesity since these have long been constituents of human diets. Furthermore, food consumption and body weight have been well-regulated in most humans and other species until recent times. Thus, attention must focus on changes that have occurred in the last half-century and the relationship between such changes and specific populations that are impacted. The hypothesis presented here is that substances that have entered our bodies recently cause obesity by generating false and misleading information about energy status. We propose that this misinformation is caused by changes in the oxidation–reduction (redox) potential of metabolites that circulate and communicate to organs throughout the body. Examples are provided of food additives that generate reactive oxygen species and impact redox state, thereby, eliciting inappropriate tissue-specific functional changes, including insulin secretion. Reversal requires identification, neutralization, or removal of these compounds. This article is part of a discussion meeting issue ‘Causes of obesity: theories, conjectures and evidence (Part I)’.
A person's metabolic rate corresponds to the whole-body level sum of all oxidative reactions occurring on the cellular level. The energy expenditure (EE) can be categorized into various essential and facultative processes. In sedentary adults, basal metabolic rate is the largest contributor to total daily EE, and interindividual variability can be significant. Additional EE to support facultative processes corresponds to digesting and metabolizing food; thermoregulatory adaptation to cold; and to supporting exercise and non-exercise body movements. Interindividual variability also exists for facultative EE processes, even after controlling for known factors. The complex mechanisms of interindividual variability in EE can have genetic and environmental origins and require further investigation. Exploration of interindividual variability in EE and its underlying factors holds importance to metabolic health, as it may predict disease risk, and be useful in the personalisation of preventative and treatment strategies.
The causes of obesity are somewhat clearer today due to biochemical, genetic, and technological advances that have allowed a better understanding of the disease. The causes can be grouped into three well-defined blocks. The first one is framed by the positive energy balance in which overeating is analyzed in its quantitative aspects including its measurement and qualitative aspects together with their causal importance. Within this balance, the energy expenditure through physical activity is considered in relation to the peculiarities of the ages. The second block is made up of genetic predisposition and known causes: genetic variations and monogenic obesities, as well as the growing importance of epigenetics. Syndromic obesity is represented according to its clinical incidence. The third block is that of risk factors, where cohort studies and data analysis are clarifying their role and discovering new and important associations with environmental causes. This rejects different initial interpretations whose paradigm might be weight excess in the pre and periconceptional stages.KeywordsBreastfeedingPediatric obesityEtiologic factorsComplementary feedingRapid weight gainEnergy balancePregestational obesityGestational obesityProspective studiesRisk factors
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Self The use of artistic expression as a form of therapy has a long and storied history. The human experience has been represented, communicated and elevated through the use of the arts since the earliest signs on cave walls and healing ceremonies performed by artists. Recognizing the capacity of art to improve one's quality of life, the World Health Organization (WHO) conducted research on the evidence supporting the role of art in promoting one's health and well-being (Fancourt and Finn, 2019). In addition, the World Health Organization officially inaugurated its arts and health initiative, which will include organizing events, supporting research and raising awareness (Arts and Health). It is no accident, therefore, that this Research Topic, which requests additional data on the psychological and physiological advantages of art, includes a commentary by Christopher Bailey, leader of the arts and health at WHO. Differences in the duration, frequency and intensity of physical activities can create significant differences in total energy expenditure. It has been shown that increases in activity-induced energy expenditure result in increases in total energy expenditure that are generally greater than increases in activity-induced energy expenditure. No evidence of spontaneous increase in physical activity measured by diary, interview, or accelerometer was found. However, this does not exclude increased physical activity that cannot be measured by these methods. Part of the difference may also be explained by the increased metabolic rate after exercise. If changes in physical activity level affect energy balance, this should result in changes in body mass or body composition. It is found in body mass and fat mass in response to increases in physical activity induced by exercise training, which are usually smaller than predicted from the increase in energy expenditure. This indicates that the training-induced increase in total energy expenditure is at least partially compensated by an increase in energy
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Bugelski's (1973, 1982) stance on reduction to hypothetical physiology has a long and glorious history. For example, some French and German materialists of the 18th and 19th centuries saw consciousness and thinking as secretions of the brain and thus linked psychology to hypothetical (or fictitious) physiologies. This view was common in Europe at that time (Kantor, 1969, pp. 203-204, 258-259). More recent examples include Hull's (1943) use of terms that sound physiological but not, such as afferent neural interaction; Hebb's (1949) conceptual invention of the nervous system with no reference to the real nervous system; adaptive network models, which are CURRENT SCIENCE 3 THIS JOURNAL INCLUDED IN MANY INDEXES, INCLUDING ADVANCED SCIENCES INDEX. ADVANCED SCIENCES INDEX (ASI) EUROPEAN SCIENCE EVALUATION CENTER WHERE TOGETHER KIRCHSTRASSE 4.56761 | RHINELAND-PALATINATE, GERMANY PHONE: +49(177) 8684-353 PHONE : +49(177) 8684-353 EMAILS: ASI@EUROPE.DE simulations of physiological processes with "loosely resembling neurons" units (Palmer & Donahoe, 1992, p. 1355); and other non-existent versions of modem connectivity (Hilgard, 1987, p. 190). Another example is that one of the criteria proposed by cognitive theorists to assess the adequacy of any information processing model is the consistency of the model with what is known about neural physiology (Klahr and Wallace, 1976, p. 5; Palmer and Donahoe, 1992). ; Simon, 1972), but even with this consistency the model is not physiological. Another example is one of the criteria proposed by cognitive theorists to evaluate the adequacy of any knowledge process. However, these theories and models may be scientifically useful for other purposes that will not be covered in this article. Another method known as the "mind over the brain" approach is used by some connectionists ; however, this method does not seem to have much relevance in the scientific community. This shift was opposed by Skinner (1974) as an attempt to escape from the then prevalent mind-body dichotomy rather than as an attempt to offer a physiological explanation. Cognitivists seem to use it not to avoid mentalism, but to make mentalism more palatable, although Ryle (1949) argues that this statement is less misleading and therefore preferred "in the mind." Another metaphor used by some cognitivists is "in the head" as a vague euphemistic way of saying "in mind" (e.g., Brown, 1975; Jenkins, 1971). However, the term is sometimes used simply to supply stylistic diversity (e.g.
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Adipose tissue growth results from de novo adipocyte recruitment (hyperplasia) and increased size of preexisting adipocytes. Adipocyte hyperplasia accounts for the severalfold increase in adipose tissue mass that occurs throughout life, yet the mechanism of adipocyte hyperplasia is unknown. We studied the potential of macrophage colony-stimulating factor (MCSF) to mediate adipocyte hyperplasia because of the profound effects MCSF exerts on pluripotent cell recruitment and differentiation in other tissues. We found that MCSF mRNA and protein were expressed by human adipocytes and that adipocyte MCSF expression was upregulated in rapidly growing adipose tissue that encircled acutely inflamed bowel and in adipose tissue from humans gaining weight (4-7 kg) with overfeeding. Localized overexpression of adipocyte MCSF was then induced in rabbit subcutaneous adipose tissue in vivo using adenoviral-mediated gene transfer. Successful overexpression of MCSF was associated with 16-fold increases in adipose tissue growth compared with a control adenovirus expressing beta-galactosidase. This occurred in the absence of increased cell size and in the presence of increased nuclear staining for MIB-1, a marker of proliferation. We conclude that MCSF participates in adipocyte hyperplasia and the physiological regulation of adipose tissue growth.
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The effect of overfeeding on energy expenditure was investigated in 23 young men subjected to a 353-MJ energy intake surplus over 100 d. The major part of this excess (222 MJ) was stored as body energy. The increase in energy cost of weight maintenance amounted to 52 MJ and was proportional to body weight gain. When it was added to the obligatory cost of fat and fat-free mass gains, the overall increase in energy expenditure amounted to a mean of 100 MJ. Four months after overfeeding, subjects had lost 82%, 74%, and 100% of the overfeeding gain in body weight, fat mass, and fat-free mass, respectively. We conclude that 1) in response to overfeeding, two-thirds of the excess energy intake is stored as body energy; 2) overfeeding induces an increase in energy cost of weight maintenance proportional to body weight gain, and 3) preoverfeeding energy balance tends to be restored when nonobese individuals return to their normal daily-life habits.
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Possible adaptive mechanisms that may defend against weight gain during periods of excessive energy intake were investigated by overfeeding six lean and three overweight young men by 50% above baseline requirements with a mixed diet for 42 d [6.2 +/- 1.9 MJ/d (mean +/- SD), or a total of 265 +/- 45 MJ]. Mean weight gain was 7.6 +/- 1.6 kg (58 +/- 18% fat). The energy cost of tissue deposition (28.7 +/- 4.4 MJ/kg) matched the theoretical cost (26.0 MJ/kg). Basal metabolic rate (BMR) increased by 0.9 +/- 0.4 MJ/d and daily energy expenditure assessed by whole-body calorimetry (CAL EE) increased by 1.8 +/- 0.5 MJ/d. Total free-living energy expenditure (TEE) measured by doubly labeled water increased by 1.4 +/- 2.0 MJ/d. Activity and thermogenesis (computed as CAL EE--BMR and TEE--BMR) increased by only 0.9 +/- 0.4 and 0.9 +/- 2.1 MJ/d, respectively. All outcomes were consistent with theoretical changes due to the increased fat-free mass, body weight, and energy intake. There was no evidence of any active energy-dissipating mechanisms.
This study was conducted to compare gross efficiency (GE), net efficiency(NE), work efficiency (WE), and delta efficiency (DE) between arm crank and cycle exercise at the same relative intensities. Eight college-aged males underwent two experimental trials presented in a randomized counterbalanced order. During each trial subjects performed three intermittent 7-min exercise bouts separated by 10-min rest intervals on an arm or semirecumbent leg ergometer. The power outputs for the three bouts of arm crank or cycle exercise corresponded to 50, 60, and 70% of the mode-specific˙VO2peak. GE, NE, and WE were determined as the ratio of Kcal·min-1 equivalent of power output to Kcal·min-1 of total energy expended, energy expended above rest and energy expended above unloaded exercise, respectively. DE was determined as the ratio of the increment of Kcal·min-1 of power output above the previous lower intensity to the increment of Kcal·min-1 of total energy expended above the previous lower intensity. GE and NE did not differ between arm crank and cycle exercises. However, WE was lower (P < 0.05) during arm crank than cycle exercise at 50, 60, and 70% ˙VO2peak. DE was also lower(P < 0.05) during arm crank than cycle exercise at Δ 50-60 and at Δ 60-70% ˙VO2peak. It is concluded metabolic efficiency as determined by work and delta efficiency indices was lower during arm crank compared with cycle exercise at the same relative intensities. These findings add to the understanding of the difference in metabolic efficiency between upper and lower body exercise.
The relationship between size of a mixed, liquid meal and the thermic effect of food (TEF) was studied in two groups of nonobese male subjects differing in maximum serobic capacity (VO2 max). A design using repeated measures was chosen in which each subject received each meal (water, 500 kcal, 1000 kcal, 1500 kcal) on a different morning. TEF was measured by indirect calorimetry for three hours following each meal and was found to increase systematically, in a nonlinear fashion, as meal size was increased. Subjects with a high VO2 max responded to the two higher calorie meals with a greater TEF than did subjects with a low VO2 max. They also showed a greater increase in TEF for any given increase in meal size. This study establishes a precise relationship between meal size and the thermic effect of food. It also identifies an important variable, VO2 max, in determination of the individual thermic response to food. These findings suggest that individuals with a high VO2 max (such as aerobically trained athletes) show a greater caloric expenditure after eating, particularly after a large meal, than do individuals with a low VO2 max. A high thermic response to food could be beneficial in body weight homeostasis.
We undertook this study to determine whether there are differences in the responses of different persons to long-term overfeeding and to assess the possibility that genotypes are involved in such differences. After a two-week base-line period, 12 pairs of young adult male monozygotic twins were overfed by 4.2 MJ (1000 kcal) per day, 6 days a week, for a total of 84 days during a 100-day period. The total excess amount each man consumed was 353 MJ (84,000 kcal). During overfeeding, individual changes in body composition and topography of fat deposition varied considerably. The mean weight gain was 8.1 kg, but the range was 4.3 to 13.3 kg. The similarity within each pair in the response to overfeeding was significant (P less than 0.05) with respect to body weight, percentage of fat, fat mass, and estimated subcutaneous fat, with about three times more variance among pairs than within pairs (r approximately 0.5). After adjustment for the gains in fat mass, the within-pair similarity was particularly evident with respect to the changes in regional fat distribution and amount of abdominal visceral fat (P less than 0.01), with about six times as much variance among pairs as within pairs (r approximately 0.7). We conclude that the most likely explanation for the intrapair similarity in the adaptation to long-term overfeeding and for the variations in weight gain and fat distribution among the pairs of twins is that genetic factors are involved. These may govern the tendency to store energy as either fat or lean tissue and the various determinants of the resting expenditure of energy.
In the doubly-labelled water (2H2(18)O) method for the measurement of carbon dioxide production rate in man, single exponential disappearance curves for 2H2O and H2(18)O in body water are used; the precision with which the slopes and intercepts of the curves are estimated determines the precision of the estimate of carbon dioxide production rate. In studies with infants, and in computer simulations, the effect of different experimental regimes on the overall precision of the carbon dioxide production estimate was investigated. When the number of data points used was progressively reduced by shortening the total observation period from 7 d (about 3 biological half-lives for the isotopes) to 1 d there was a deleterious effect on precision and in the infants there was an upward bias in the values for carbon dioxide production. When the number of data points was reduced by removing points from the middle of the exponential curves with the maintenance of the 7-d experimental period, precision was also reduced but by less than in the former procedure and there were no consistent trends in the average values for carbon dioxide production.
Indirect calorimetry is a method which allows the non-invasive measurement of energy expenditure and substrate utilization in humans. The procedure is described and the main equations to calculate energy expenditure and substrate utilization are presented. The limitations of the method include physiological effects, such as hyperventilation, and the influence of metabolic processes such as gluconeogenesis, ketogenesis and lipogenesis. The general principle is that intermediate processes do not influence overall conclusions, provided that the intermediate substrates which are formed do not accumulate within the body or are not excreted. Continuous measurements of metabolic rate and respiratory quotient using the ventilated hood system have been carried out during the last 5 years to study carbohydrate and lipid metabolism in lean subjects, in obese and diabetic patients. By using the euglycaemic insulin clamp technique or by giving oral glucose loads, it has been shown that the main effect of insulin on carbohydrate metabolism is to stimulate glucose storage. By raising plasma free fatty acid levels with a neutral fat infusion in lean subjects, both glucose oxidation and glucose storage were imparied during euglycaemic insulin clamps. Glucose storage was found to be markedly impaired in non-diabetic obese patients, during euglycaemic insulin clamps in the presence of elevated lipid oxidation. In obese diabetic patients, the impairment in glucose storage was more pronounced than in non-diabetic obese; this defect was particularly marked during euglycaemic insulin clamps, but it was also present after an oral glucose load. It is concluded that impairment of glucose storage is a major defect of glucose utilization in type II diabetes.