ArticlePDF Available

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



Both the amount and composition of food eaten influence body-weight regulation. The purpose of this study was to determine whether and by what mechanism excess dietary fat leads to greater fat accumulation than does excess dietary carbohydrate. We overfed isoenergetic amounts (50% above energy requirements) of fat and carbohydrate (for 14 d each) to nine lean and seven obese men. A whole-room calorimeter was used to measure energy expenditure and nutrient oxidation on days 0, 1, 7, and 14 of each overfeeding period. From energy and nutrient balances (intake-expenditure) we estimated the amount and composition of energy stored. Carbohydrate overfeeding produced progressive increases in carbohydrate oxidation and total energy expenditure resulting in 75-85% of excess energy being stored. Alternatively, fat overfeeding had minimal effects on fat oxidation and total energy expenditure, leading to storage of 90-95% of excess energy. Excess dietary fat leads to greater fat accumulation than does excess dietary carbohydrate, and the difference was greatest early in the overfeeding period.
Am J Clin Nutr 1995;62:19-29. Printed in USA. © 1995 American Society for Clinical Nutrition 19
Fat and carbohydrate overfeeding in humans: different
effects on energy storage3
Tracy J Horton, Holly Drougas, Amy Brachey, George W Reed, John C Peters, and James 0 Hill
ABSTRACT Both the amount and composition of food eaten
influence body-weight regulation. The purpose of this study was to
determine whether and by what mechanism excess dietary fat leads
to greater fat accumulation than does excess dietary carbohydrate.
We overfed isoenergetic amounts (50% above energy require-
ments) of fat and carbohydrate (for 14 d each) to nine lean and
seven obese men. A whole-room calorimeter was used to measure
energy expenditure and nutrient oxidation on days 0, 1, 7, and 14
of each overfeeding period. From energy and nutrient balances
(intake-expenditure) we estimated the amount and composition of
energy stored. Carbohydrate overfeeding produced progressive
increases in carbohydrate oxidation and total energy expenditure
resulting in 75-85% of excess energy being stored. Alternatively,
fat overfeeding had minimal effects on fat oxidation and total
energy expenditure, leading to storage of 90-95% of excess en-
ergy. Excess dietary fat leads to greater fat accumulation than does
excess dietary carbohydrate, and the difference was greatest early
in the overfeeding period. Am J Clin Nutr 1995;62:19-29.
KEY WORDS Obesity, nutrient partitioning, nutrient bal-
ance, energy balance, diet composition
Obesity is a major health problem affecting more than 34
million Americans (1). An understanding of how obesity de-
velops is necessary to develop strategies for its prevention and
treatment. This could be facilitated by a better ability to iden-
tify individuals who are at risk of developing obesity. Such
individuals may be characterized by a metabolic and/or a
behavioral susceptibility to weight gain (2). Hill et al (2)
proposed that behavioral susceptibility to obesity creates the
opportunity for positive energy balance to occur (eg, overeat-
ing and underexercising), whereas metabolic susceptibility to
obesity determines the metabolic fate of the excess energy
when positive energy balance occurs. For example, an individ-
ual with a high metabolic susceptibility to obesity would be
inclined to accumulate more body fat but less glycogen during
periods of positive energy balance than would an individual
with a lesser metabolic susceptibility to obesity.
There are substantial data to suggest that individuals differ in
their behavioral response to different environmental condi-
tions. For example, many human subjects consume more total
energy on a high- than on a low-fat diet (3-6). Similarly, it is
unlikely that all subjects will show the same gain in body
weight and body fat when subjected to positive energy balance.
This was demonstrated in the overfeeding studies of Sims et al
(7) and Bouchard et al (8). Contrary to the concept of “luxu-
skonsumption”, many recent studies have demonstrated that
the majority of excess energy is stored and not expended as
heat during overfeeding (9-1 1). However, differences between
energy stored and energy expended and differences in the
composition of the fuel mixture oxidized may lead to important
individual differences in the metabolic fate of excess energy
under conditions of positive energy balance. These differences
could stem from differences in partitioning of excess energy
into 1) storage compared with expenditure, 2) storage in adi-
pose tissue compared with storage in lean body mass, and 3)
storage in visceral compared with peripheral adipose tissue.
Diet composition clearly has an important influence on
body-weight regulation. The strongest evidence for this comes
from rodent studies in which high-fat diets have been shown to
produce obesity independently of total energy intake (12, 13).
In human subjects, diet composition can influence total energy
intake (3-6) and can alter nutrient balance without changing
total energy expenditure (14, 15). In response to acute changes
in diet composition, it has been shown that human subjects
increase carbohydrate oxidation and total energy expenditure in
response to excess carbohydrate (16), but fail to increase fat
oxidation or energy expenditure in response to excess fat
(17-19). This suggests that under conditions of excess, dietary
fat leads to greater fat accumulation than does dietary carbo-
Energy and nutrient balances can be assessed during dietary
challenges by combining indirect calorimetry with dietary con-
trol. A major advantage of this technique is that changes in
body nutrient stores can be detected well before they could be
measured with available techniques for assessing body com-
position. In this study we used this approach to determine how
lean and obese men partitioned excess energy provided as
carbohydrate or fat.
IFrom the Center for Human Nutrition, University of Colorado Health
Sciences Center, Denver; the Department of Pediatrics and Preventive
Medicine, Vanderbilt University, Nashville, TN; and the Procter & Gamble
Co, Cincinnati.
2Supported by NIH grants DK42549 and RR00095.
3Address reprint requests to TJ Horton, Center for Human Nutrition,
Box C225, University of Colorado Health Sciences Center, Denver, CO
Received June 15, 1994.
Accepted for publication February 16, 1995.
by guest on July 13, 2011www.ajcn.orgDownloaded from
Male subjects aged 18-46 y were recruited for the study.
Subjects were excluded if they smoked or if they had a history
of diabetes, cardiovascular disease, or major health problems
other than obesity. Highly trained individuals and subjects
habitually consuming a very-low- or very-high-fat diet were
excluded. Nine lean (90-1 10% of ideal body weight as deter-
mined by the 1983 Metropolitan Life Insurance Tables; 20) and
seven obese (130-180% of ideal body weight) subjects com-
pleted the study. The protocol was approved by the Committee
for the Protection of Human Subjects of Vanderbilt University.
Table 1 shows the descriptive characteristics of study par-
ticipants and their estimated baseline energy requirements.
Lean subjects had a significantly greater maximum oxygen
consumption (VO2max) than obese subjects. Initial body
weight, percent body fat, fat-free mass (FFM), fat mass (FM),
and age were all significantly greater in the obese group than in
the lean group. Similarly, obese subjects had higher baseline
energy requirements and lower levels of physical activity. The
percent fat in the baseline diet did not differ between lean and
obese subjects.
Experimental design
Each subject completed two separate 14-d periods of over-
feeding. Each overfeeding period was preceded by 1 wk of
consuming a baseline (maintenance) diet. Excess energy was
set at 50% above baseline energy intake and was provided
entirely as fat during one period and as carbohydrate during the
other. Subjects spent 24-h in a whole-room indirect calorimeter
to determine energy and nutrient balances on day 7 of baseline
(which corresponds to day 0 of the protocol) and on days 1, 7,
and 14 of each overfeeding period. This allowed us to estimate
how much excess energy was expended compared with stored,
as well as the form of stored energy in the body. Physical
Subject characteristics’
Lean subjects
Obese subjects
Age (y) 28.6 ±5.4 37.6 ±532
Height (m) 1.79 ±0.07 1.79 ±0.03
Weight (kg) 68.4 ±9.9 103.9 ±10.92
VO2 max
(mL kg’ .mm’) 41.7 ±4.7 31.5 ±3.8
Percent body fat (%) 21.4 ±3.2 35.4 ±5.22
Fat mass (kg) 14.7 ± 3.2 37.0 ± 8.22
Fat-free mass (kg) 53.8 ± 7.8 66.9 ± 6.22
Body mass index (kg/m2) 21.3 ±1.5 32.3 ±2.72
Baseline energy
requirements (kJ/d) 11 123 ±961 13 965 ± 8362
Percent fat in baseline
diet (%) 36 ±3 33 ±2.5
Baseline activity (Caltrac
units)3 345 ±33 237 ±102
‘1 ± SEM.
2Significantly different from lean, P<0.01.
3One caltrac unit =0.5 METS (one MET is equal to the oxygen
consumption of a seated individual at rest, =3.5 mL .kg1 .mint).
activity was held constant throughout the study as described
below. Sample diets are shown in Appendix A.
Determination of baseline energy requirements
We took great care to accurately assess usual energy intake
during baseline to ensure that the degree of overfeeding was
similar for each subject. After recruitment, each subject com-
pleted a 14-d weighed diet diary to estimate their usual food
intake. Subjects met with a dietitian and were provided with a
set of weighing scales and given detailed instructions of how to
accurately complete the diet record by describing types of food
consumed and to record appropriate weights. Periodic checks
were made to ensure that subjects were completing the record
in the required manner.
One week after completing the diet records, subjects began
the first dietary control phase. For 1 wk, subjects were fed a
baseline diet reflecting their self-reported habitual intake of
energy, fat, carbohydrate, and protein, as assessed from their
diet records. The diets consisted, as much as possible, of the
foods usually consumed by the subjects and were delivered in
a pattern approximating the subject’s usual pattern. Additional
food modules (838 kJ), of the same nutrient composition as the
diet, were available on request. Use of these modules was
previously described (3). This approximated ad libitum feed-
ing. All food was provided and prepared by the Clinical Re-
search Center (CRC) metabolic kitchen, and subjects were
required to consume at least one meal at the CRC each day. All
other food was packaged to be taken away and eaten in the
subject’s home or workplace. Body weight was measured daily
during the baseline diet to confirm weight stability. In response
to trends to decrease body weight (there were no trends to
increase body weight), the dietitian met with the subject to alter
the diet plan as needed to reachieve weight stability.
Each subject’s usual level of physical activity was estimated
by using Caltrac accelerometers (Hemokinetics Inc, Madison,
WI). Each subject wore an accelerometer for 7 d before begin-
fling the overfeeding period. The accelerometer clips to the
waistband or pocket at the front of the body and measures
whole-body acceleration. It can be programmed to measure
movement in units, where 1 unit =2.0 METS. One MET is
equal to the oxygen consumption of a seated individual at rest,
which is “‘3.5 mL kg1 .min (21). Other activities that the
accelerometer cannot monitor (swimming, cycling, calisthen-
ics, weight training, etc) were recorded separately in terms of
type of activity, intensity, and duration. The Caltrac values
were averaged over the initial 7-d period, including estimates
of the unit equivalent of other activity [(METS/mm activity X
duration) X 0.5]. This value was used to design an appropriate
activity routine while the subject stayed in the whole-room
calorimeter and to check for possible changes in activity during
the overfeeding periods. Each subject spent the last baseline
day in the whole-room calorimeter eating at his usual energy
intake and undergoing a usual physical activity routine. It is
obviously not possible to exactly reproduce usual physical
activity in a room calorimeter, but for each subject, activity in
the calorimeter was constant during each stay and in the range
of usual activity.
Oveifeeding: phase 1
Immediately after the baseline week, subjects began the first
overfeeding period, which lasted for 14 d. Subjects were fed a
by guest on July 13, 2011www.ajcn.orgDownloaded from
0CHO Overfeeding
.Fat Overfeeding
00 7 14
Time (days)
FIGURE 1. Changes in body weight during and for 21 d after fat and
carbohydrate (CHO) overfeeding in 16 male subjects.
diet providing 150% of their energy intake during the baseline
week. The additional 50% of energy was given as either all fat
or all carbohydrate. All food was provided by the CRC. Daily
energy expenditure and nutrient oxidation were measured in
the whole-room calorimeter on days 1, 7, and 14 of overfeed-
ing. Subjects did not have access to food modules during the
overfeeding periods. Activity was monitored (with Caltrac
accelerometers) during the last 7 d of overfeeding.
Overfeeding: phase 2
A 4-wk washout period separated the first and second phases
of the experimental period. During the first 3 wk subjects were
free to consume whatever food they chose. In the fourth week
subjects were fed the diet reflecting their habitual intake. The
second overfeeding phase mirrored the first exactly except that
the form of the excess energy (fat or carbohydrate) was
switched. The diets were administered in a randomized cross-
over design.
Dependent measures
A treadmill test to exhaustion, using the protocol of Bruce et
al (21), was used to estimate maximal oxygen uptake of sub-
jects. Body weight and height were measured on a Platform
Detecto scale (Webb City, MO) and graduated wall meter,
respectively. Body composition was estimated from body den-
sity by using underwater weighing to determine body volume,
with simultaneous measurement of residual lung volume with
the closed-circuit, nitrogen-dilution technique (22). Percent
body fat was estimated from body density by using the revised
equation of Brozek et al (23). Body weight was measured on
each morning before entering the metabolic chamber and body
composition was determined immediately before and after each
overfeeding period.
Blood was taken from each subject to determine circulating
concentrations of free fatty acids, insulin, and glucose. Samples
were taken after an overnight fast during the week before
beginning each overfeeding period and at the end of each
overfeeding period.
Total daily energy expenditure and substrate oxidation were
measured in a whole-room indirect calorimeter, located in the
CRC, as described previously (3, 14, 24). Subjects entered the
chamber at 0800 and left the following day at 0700. Results
were extrapolated to 24 h. Oxygen consumption and carbon
dioxide production were determined from the flow rate and
differences in gas concentrations between entering and exiting
air. Values were corrected for temperature, barometric pres-
sure, and humidity. Energy expenditure was calculated from
oxygen consumption and respiratory quotient (RQ). The oper-
ation of the chamber was controlled by a personal computer by
using a software program written in TURBO C. The program
was based on calculations described by Jequier et al (25).
Values for all indexes were averaged over 2-mm intervals and
recorded in a data file. An activity button system was linked to
the computer. This was used to mark events (eg, sleep, meals,
exercise) and the appropriate button was pressed before com-
mending and on completion of an event.
Energy expenditure due to activity was estimated by using a
mechanical-force platform serving as the chamber floor. The
platform detects vertical and horizontal displacement of the
center of gravity and is capable of detecting displacements as
small as 50 g. This system was described in detail elsewhere
and has been shown to be accurate to within 1% (26). The
accelerometer was worn during each chamber stay and subjects
performed a prescribed amount of walking and stepping exer-
cises, aimed at mimicking the total amount of activity usually
performed outside the chamber. Walking was performed at a
rate of 8 m/10 s and stepping at 4 steps/lO s. The number and
duration of exercise bouts was individually adjusted to achieve
a value similar to the average accelerometer reading. Activity
was scheduled at 1030, 0130, 1600, and 1900 when necessary.
Subjects collected all of their urine while in the calorimeter.
Aliquots were analyzed for total nitrogen content (27).
Data analysis
Results were analyzed by using repeated-measures analysis
of variance (ANOVA) with obesity status as a grouping factor
(lean compared with obese). Diet (overfeeding fat compared
with overfeeding carbohydrate) and time (measures at baseline
and days 1, 7, and 14 for each diet) were repeated-measures
factors. A nonparametric Mann-Whitney Utest was used to
establish any differences in initial subject characteristics. SAS
statistical software (SAS Institute, Cary, NC) was used for the
Body weight and body composition
Body weight increased significantly after both fat and car-
bohydrate overfeeding (P <0.001), with the greatest increase
occurring between days 1 and 7 (Figure 1). Baseline body
weight was significantly positively correlated with weight gain
during the carbohydrate (r =0.55, P <0.05) but not the
high-fat (r =0.34, NS) overfeeding. At the end of the washout
period, body weight had declined to near prestudy values. The
body weights for lean subjects before the first and second
21 28 35
by guest on July 13, 2011www.ajcn.orgDownloaded from
Day 1 Day 7 Day 14
Changes in body composition’
 1.0
Cl) 0.9#{149}
Ot 0.8
 0.6
C 0.3
E 0.2
0. 0.0
FIGURE 3. The proportion of excess energy stored in the body is
shown for fat and carbohydrate (CHO) overfeeding in 16 male subjects.
The proportion of excess stored is calculated as (total excess minus the
measured increase in daily energy expenditure)/total excess.
overfeeding periods were 68.1 ± 3.3 and 68.8 ± 7.3 kg,
respectively. For obese subjects the weights before the first and
second overfeeding periods were 103.7 ± 9.1 and 105.1 ± 9.1
kg, respectively.
Body-composition changes, as determined by underwater
weighing, are shown in Table 2. FM and FFM increased
significantly with carbohydrate overfeeding (P <0.02) and fat
overfeeding (P <0.001). There were no significant differences
between diets and/or groups in body weight or body-composi-
tion changes. The percentage of weight gained as FM (54-
56%) or FFM (44-46%) was similar between diets and groups.
Note, however, that the changes in body composition were very
small and near the detection limits of our technique. The study
was not designed to produce significant alterations in body
composition, but rather to predict changes in body stores of
protein, carbohydrate, and fat from measures of intake and
oxidation of each.
Energy balance
The increase in energy expenditure caused by fat overfeed-
ing was not statistically significant. With carbohydrate over-
feeding there was a significant increase in energy expenditure
on days 7 and 14 (Figure 2). We assumed that excess energy
not expended was stored in the body. Figure 3 shows the
estimated energy stored as a proportion of excess ingested
 energy. This allows for differences between groups and mdi-
viduals in the absolute excess energy consumed. Overall, a
greater proportion of the excess energy was stored when the
excess was given as fat compared with carbohydrate (P <
0.002). However, there was a significant day Xdiet interaction
(P <0.05) so that energy storage remained constant over time
with fat but not carbohydrate overfeeding. With fat overfeeding
91-95% of the excess energy was stored throughout the study.
Although =90% of the excess energy was stored on the first
day of carbohydrate overfeeding, it declined significantly on
days 7 and 14, with 77% and 83% of the excess being stored,
respectively (P <0.04).
Nutrient balance
Nutrient oxidation
The observed changes in nutrient oxidation were very dif-
ferent between carbohydrate and fat overfeeding. Figures 4
and 5show changes in daily oxidation rates of protein, carbo-
All subjects
Carbohydrate overfeeding
Body fat (%) 0.69 ±0.62 0.77 ±0.31 0.72 ±0.37
Fat mass (kg) 1.09 ±0.49 2.06 ± 0.232 1.48 ±0.322
Fat-free mass (kg) 1.38 ±0.52 1.41 ±56 1.40 ±0.372
Fat overfeeding
zBody fat (%) 0.93 ±0.28 0.80 ±0.22 0.88 ±0.182
zFat mass (kg) 1.21 ± 0.29 1.90 ± 0.392 1.51 ± 0.242
Fat-free mass (kg) 1.10 ±0.25 1.08 ±0.192 1.09 ± 0.162
‘5 ± SEM.
2Significantly different from zero.
CHO overfeeding
Fat overfeeding
FIGURE 2. The increase in total daily energy expenditure above
baseline (day 0) is shown for each overfeeding period in 16 male subjects.
hydrate, and fat during each overfeeding period. Protein oxi-
dation decreased over time during both overfeeding periods
(P <0.05), with a trend for this to be greater with carbohydrate
than fat overfeeding (P <0.08). Fat overfeeding produced only
minimal changes in fat and carbohydrate oxidation whereas
carbohydrate overfeeding produced significant changes in both
(P <0.001). During carbohydrate overfeeding there was a
rapid increase in carbohydrate oxidation and a significant de-
dine in fat oxidation.
Nutrient storage
The accumulation of energy, protein, fat, and carbohydrate
was estimated from the balance of each (Figure 6). Energy
balance was near zero at baseline and became positive during
both overfeeding periods. Carbohydrate balance was positive
and fat balance was negative at baseline. This was likely due to
the inability to exactly reproduce amount and type of usual
0CHO Overfeeding
.Fat Overfeeding
by guest on July 13, 2011www.ajcn.orgDownloaded from
Protein Oxidation
Protein Oxidation
ID 8
-) 6
 6
Carbohydrate Oxidation
12 -
> 10-
 8-
14 -
12 -
10 -
 6-
Fat Oxidation
>, 10
t5 8
Fat Oxidation
0 1 7 14
0 1 7
FIGURE 4. Total daily oxidation rates of protein, carbohydrate, and fat
at baseline and during the carbohydrate overfeeding period for 16 male
physical activity in the calorimeter. Protein balance increased
over time with both overfeeding diets (day effect, P<0.03).
Because fat overfeeding had minimal effects on fat and carbo-
hydrate oxidation, the majority of the excess dietary fat was
stored as body fat. This remained constant throughout the
overfeeding period. Fat accumulation was initially lower and
carbohydrate accumulation higher with carbohydrate than with
fat overfeeding (P <0.001). However, with the progressive
decline in fat oxidation, fat storage increased so that on day 14
there was no difference between diets in fat or carbohydrate
>1 10.
. 8
 6
Carbohydrate Oxidation
FIGURE 5. Total daily oxidation rates of protein, carbohydrate, and fat
at baseline and during the fat overfeeding period for 16 male subjects.
Figure 7 shows nutrient storage expressed relative to the
total excess energy. This takes into account the different abso-
lute amounts of excess energy fed to subjects and groups.
Relative fat balance was significantly greater and carbohydrate
balance less during fat than during carbohydrate overfeeding
(P <0.001). However, relative fat balance during carbohydrate
overfeeding increased significantly over time (P <0.05),
by guest on July 13, 2011www.ajcn.orgDownloaded from
2000 Energy Balance
-) 500
0-500 0 2 4 6 8 10 12 14 16
Time (days)
Carbohydrate Balance
CHO overfeeding
Fat Overfeeding
0 2 4 6 8 10 12 14 16
Time (days)
Fat Balance
0 2 4 6 8 10121416 0 2 4 6 8 10121416
Time (days) Time (days)
FIGURE 6. Daily balances of energy, protein, carbohydrate (CHO), and fat are shown for fat and CHO overfeeding for 16 male subjects. Daily balances
were calculated as total intake minus total oxidation of each nutrient.
Protein Balance
achieving a similar amount of fat storage by day 14 as with fat
overfeeding day 14.
Lean-obese differences
We examined differences in the response to overfeeding
between lean and obese subjects. In general, both groups re-
sponded similarly to overfeeding, keeping in mind that over-
feeding was based on energy requirements, so that obese sub-
jects received more total energy during overfeeding than lean
subjects. There were no significant differences between groups
in energy or nutrient balance, although the individual differ-
ences in these measures were large. Obese subjects, however,
had a higher average RQ and oxidized proportionally more
carbohydrate than lean subjects during both overfeeding pen-
ods (P <0.007).
Fasting concentrations of insulin, glucose, and free
fatty acids
Table 3 shows the fasting concentrations of insulin, glucose,
and free fatty acids on day 0 and on the morning of day 15 of
each overfeeding period. Values are shown separately for lean
and obese subjects. In general, insulin concentrations were
higher and free fatty acid concentrations were lower on the
morning of day 15 after carbohydrate overfeeding than on day
15 after fat ovenfeeding. Glucose concentrations did not vary
significantly with either diet.
Results of this study demonstrate that diet composition can
have important effects on energy expenditure and body energy
storage when subjects are in positive energy balance. Greater
than 75% of the excess energy consumed by our subjects was
stored in the body, not expended, regardless of the composition
of the excess. Other recent overfeeding studies have reached
the same conclusion (9-11). However, our results demonstrate
that excess carbohydrate affects energy and nutrient balances
differently than does excess fat. We found that for equivalent
amounts of excess energy, fat leads to more body fat accumu-
lation than does carbohydrate.
by guest on July 13, 2011www.ajcn.orgDownloaded from
. a
LU -#{176}
 04
FIGURE 7. Storage of each nutrient during fat and carbohydrate (CHO)
overfeeding is expressed as a percent of total excess energy stored in each
of 16 male subjects. This accounts for differences in intake of each nutrient
between subjects.
2 4 6 8 10 12 14 16
Time (days)
oCHO overfeeding
#{149}Fat Overfeeding
Using our whole-room calorimeter, we were able to demon-
strate different effects of excess fat compared with excess
carbohydrate on energy expenditure, substrate oxidation, and
nutrient balance. It is generally accepted that dietary carbohy-
drate promotes its own oxidation, whereas dietary fat does not
(16-19). This was clearly the case in the present study. Four-
teen days of fat overfeeding produced no significant changes in
fat oxidation or total daily energy expenditure. The small
increase in energy expenditure with fat overfeeding can be
explained by an increased thermic effect of food (TEF) and a
slight increase in body mass. By comparing fat intake with fat
oxidation, we found that the degree of positive fat balance
during fat ovenfeeding was equal to 90-95% of the total excess
energy consumed. Moreover, because fat ovenfeeding hardly
increased substrate oxidation, this high storage efficiency con-
tinued throughout the study.
Carbohydrate overfeeding produced a very different picture.
Progressive increases in both carbohydrate oxidation and total
energy expenditure were seen with carbohydrate overfeeding.
Both were evident on the first day of overfeeding and reached
maximum by day 7. The increased energy expenditure seen
with carbohydrate overfeeding was approximately double that
which could be explained by the combination of increased TEF
and increased body mass. Thus with carbohydrate overfeeding,
more of the excess energy was oxidized and less stored in the
body than was seen during fat overfeeding.
We anticipated that sustained carbohydrate overfeeding
would lead to accumulation of body fat due to de novo lipo-
genesis. Although the issue of whether carbohydrate overfeed-
ing led to de novo lipogenesis in tissues such as the liver cannot
be definitively determined in this study, the calorimetry data
indicate that net lipogenesis from carbohydrate did not occur.
There were short periods during some carbohydrate overfeed-
ing days in which the nonprotein RQ was >1 .0, suggesting that
some de novo lipogenesis occurred. It is impossible under
conditions of this study to accurately quantify this de novo
lipogenesis. Other investigators using isotopic techniques have
reported that de novo lipogenesis in human subjects is not a
major way to accumulate body fat stores (28). It may, however,
be slightly higher in hypeninsulinemic obese subjects than in
lean subjects and may depend on the type of carbohydrate in
the diet (29). From these results, however, we conclude that
positive fat balance was due to a decrease in fat oxidation
accompanying the increase in carbohydrate oxidation. By day
14 of the overfeeding period, the proportion of total stored
energy that was stored as body fat did not differ between the
two diets.
When the total 14-d overfeeding period is considered (ie,
areas under the curve for total energy and fat), substantially
more total energy and more total fat is stored when the excess
is fat compared with carbohydrate. Even on day 14, when the
portion of the excess stored as fat was not significantly differ-
ent between the two diets, total energy expenditure was higher
with carbohydrate overfeeding so that the total stored energy
was less than with fat overfeeding.
Other investigators have demonstrated in a single meal (18,
19) and over an entire day (17) that excess fat does not increase
fat oxidation. These results extend that work to show that fat
has only a slight effect on fat oxidation over the course of a
2-wk ovenfeeding period. This is consistent with the notion that
increases in fat oxidation occur secondary to increases in the
body fat mass (30). The change in body fat mass in the present
study was small. The effects of excess carbohydrate on energy
and nutrient balance require further explanation. In particular,
the extent of fat storage during carbohydrate overfeeding de-
pended on the extent to which fat oxidation was inhibited.
As might be expected, carbohydrate overfeeding was asso-
ciated with a small increase in overnight fasting plasma insulin
and a decrease in nonestenified fatty acids, whereas fat over-
feeding did not affect these measures. These responses are
consistent with the observed pattern of changes in substrate
oxidation in which carbohydrate overfeeding stimulated carbo-
hydrate utilization while suppressing fat oxidation. Fat over-
feeding did not noticeably alter fuel metabolism. The lack of a
more substantial change in these measures, especially with
carbohydrate overfeeding, is not surprising.
by guest on July 13, 2011www.ajcn.orgDownloaded from
Fasting plasma insulin and free fatty acid (FFA) concentrations’
Lean subjects Obese subjects
CHO overfeeding Fat overfeeding CHO overfeeding Fat overfeeding
Day 0 Day 15 Day 0 Day 15 Day 0 Day 15 Day 0 Day 15
Insulin (pmolfL)
Glucose (mmol/L)
132 ± 50
4.9 ±0.2
207 ± 110
4.8 ±0.1
228 ±120
4.6 ± 0.2
108 ± 312
5.0 ±0.22
199 ±42
5.0 ±0.2
332 ±10923
4.9 ±0.3
172 ±77
4.9 ±O.i
278 ±7023
5.0 ± 0.1
FFA(mgfL) 90±13 43±72 88±15 58±112 86±15 54±7 80±20 74±16
Ii ±SEM.
2Significantly different from day 0, P<0.05.
3Significantly different from lean subjects, P<0.05.
Whereas lean and obese subjects responded similarly, in
general, to the overfeeding periods, there was one important
difference. Regardless of the composition of the overfeeding
diet, obese subjects oxidized proportionally more carbohydrate
and less fat than did lean subjects. We have proposed that
subjects who show the greatest reliance on carbohydrate oxi-
dation during perturbations to energy balance may be most at
risk to develop obesity (2, 3). Others have also suggested that
a high RQ may be associated with susceptibility to obesity
(31). Because the obese subjects in this study were already
obese, it is impossible to determine whether a high reliance on
carbohydrate oxidation in response to overfeeding contributed
to obesity development. It could clearly contribute to mainte-
nance of the obese state. It may be hypothesized that individual
differences in RQ after overfeeding predict susceptibility to
obesity. This has been demonstrated in rats, in whom a high
RQ in response to a high-fat diet predicts subsequent weight
gain (32).
We believe it is important to consider individual differences
in the influence of diet composition on body-weight regulation.
Individual differences in fat compared with carbohydrate oxi-
dation may underlie differences in fat storage during overfeed-
ing. Much longer periods of overfeeding may be necessary to
see such individual differences during fat overfeeding, because
such differences may occur secondary to substantial changes in
body fat mass (30). However, a 14-d period appears to provide
a good opportunity to study individual differences in response
to carbohydrate overfeeding. For example, it would be inter-
esting in future studies to assess whether the lean subjects who
showed the greatest reduction in fat oxidation during carbohy-
drate overfeeding would be more metabolically susceptible to
develop obesity than those with a lesser decline. In support of
this speculation, Bouchard et al (8) reported large differences
in the amount and composition of weight gained during exper-
imental overfeeding of mixed diets. Those subjects with the
highest oxidative capacity of skeletal muscle (as assessed by
citrate synthase activity) had the lowest ratio of fat to lean mass
in weight gain (33). Similar, we (34) and others (35) have
demonstrated that the fiber composition of skeletal muscle may
predict development of obesity.
In evaluating the role of diet composition on body-weight
regulation, the plane of energy balance (ie, positive, negative,
or zero) must be considered. Whereas fat and carbohydrate
clearly differ in effects on energy expenditure and substrate
oxidation during overfeeding, such differences may not be as
apparent when overfeeding is not present. For example, when
fed high- compared with low-fat diets containing a fixed
amount of energy estimated to provide maintenance energy
requirements, human subjects rapidly adjust substrate oxida-
tion to substrate intake, with no significant differences in total
energy expenditure (14). Leibel et al (36) found no difference
in body weight when subjects were fed maintenance levels of
diets differing in fat content. Similarly, differences in diet
composition during energy restriction would be expected to
have only slight effects on energy and nutrient balance (37).
This illustrates that obesity cannot develop without an initial
period in which energy intake exceeds energy expenditure and
that overfeeding is an important tool for studying obesity
There are several reasons in general to be concerned about
high-fat diets. Such diets are much more likely to be associated
with overeating than are diets high in carbohydrate (3-6).
Second, excess energy as fat is stored more efficiently than is
excess energy as carbohydrate (12). Finally, diets high in fat
may have a negative impact on health independently of obesity
We found the greatest differences between fat and carbohy-
drate overfeeding early in the overfeeding period, before car-
bohydrate overeating produced substantial decreases in fat
oxidation. From these results we can speculate that if obesity
arises as a result of long periods of sustained overeating, the
composition of excess energy would have relatively small
effects on fat storage, with slightly more fat stored if the excess
is high in fat rather than in carbohydrate. However, if obesity
arises as a result of multiple periods of overeating over a single
day or over a few days, the difference in fat storage would be
greater with excess fat than with excess carbohydrate. Future
work will be necessary to determine whether the same pattern
of differences seen in this study would be seen during a second
or third bout of overfeeding.
It is important to note that in this study we required subjects
to eat all excess food during periods of overfeeding. There are
data suggesting that diets high in carbohydrate are more sati-
ating than are diets high in fat (3-5), and that voluntary intake
is likely to be lower with high-carbohydrate than with high-fat
diets. However, some people may be poor regulators of food
intake, and these individuals should be aware that intake of
low-fat foods also needs to be regulated because body fat
accumulation can result from overconsumption of these foods.
In summary, this study provides important information about
the potential impact of diet composition on body-weight reg-
ulation and obesity development. First, all overeating will
eventually lead to obesity. Regardless of diet composition,
most excess energy is stored in the body and not expended as
by guest on July 13, 2011www.ajcn.orgDownloaded from
heat. Although we demonstrated differences between carbohy-
drate and fat overfeeding, which we believe are important, the
fact remains that obesity can develop from overeating carbo-
hydrate. Advising people that they can eat an unlimited amount
of a high-carbohydrate diet is not appropriate. Second, excess
dietary fat is stored with a very high efficiency and the body
does not acutely adjust to increased fat intake. If overeating
occurs, more of the excess will end up as body fat if the excess
is fat compared with carbohydrate. This may be particularly
important if obesity develops in some people from cumulative
acute periods of overeating. Third, whereas fat overeating
would be predicted to lead to efficient storage of excess energy
in all subjects, some differences might be seen with carbohy-
drate overfeeding. In particular, those subjects who show the
greatest inhibition of fat oxidation during carbohydrate over-
feeding would be expected to show the greatest accumulation
of body fat. A major goal for weight maintenance should be
avoidance of a positive fat balance. This can be accomplished
by both reducing dietary intake of fat and increasing physical
activity. A
I.Kuczmarski Ri. Prevalence of overweight and weight gain in the
United States. Am J Clin Nutr 1992;55(suppl):4955-502S.
2. Hill JO, Pagliassotti MJ, Peters JC. Nongenetic determinants of obe-
sity and fat topography. In: Bouchard C, ed. Genetic determinants of
obesity. Boca Raton, FL: CRC Press, Inc 1994:35-48.
3. Thomas CD, Peters JC, Reed OW, Abumrad NN, Sun M, Hill JO.
Nutrient balance and energy expenditure during ad libitum feeding of
high-fat and high-carbohydrate diets in humans. Am J Clin Nutr
4. Lissner L, Levitsky DA, Strupp BJ, Kalkwarf Hi, Roe DA. Dietary fat
and the regulation of energy intake in human subjects. Am J Clin Nutr
5. Kendall A, Levitsky DA, Strupp BJ, Lissner L. Weight loss on a
low-fat diet: consequence of the imprecision of the control of food
intake in humans. Am J Clin Nutr 1991;53:1124-9.
6. Tremblay A, Plourde 0, Despr#{233}sJP, Bouchard C. Impact of dietary fat
content and fat oxidation on energy intake in humans. Am I Clin Nutr
7. Sims EAH, Goldman RF, Gluck CM, Horton ES, Kelleher PC, Rowe
DW. Experimental obesity in man. Trans Assoc Am Phys l968;81:
8. Bouchard C, Tremblay A, Despr#{233}s JP, et al. The response to
long-term overfeeding in identical twins. N Engl J Med l990;322:
9. Klein 5, Goran M. Energy metabolism in response to overfeeding in
young adult men. Metabolism 1993;42:1201-5.
10. Diaz EO, Prentice AM, Goldberg OR, Murgatroyd PR, Coward WA.
Metabolic response to experimental overfeeding in lean and over-
weight healthy volunteers. Am i Clin Nutr 1992;56:641-55.
11. Roberts SB, Young yR. Fuss P. et al. Energy expenditure and subse-
quent nutrient intakes in overfed young men. Am J Physiol 1990;259:
12. Oscai LB, Brown MM, Miller WC. Effect ofdietary fat on food intake,
growth, and body composition in rats. Growth 1984;48:415-24.
13. Hill JO, Lin D, Yakubu F, Peters JC. Development of dietary obesity
in rats: influence of amount and composition of dietary fat. Int I Obes
1992; 16:321-33.
14. Hill JO, Peters JC, Reed OW, Schlundt DO, Sharp T, Greene HL.
Nutrient balance in humans: effects of diet composition. Am J Clin
Nutr 1991;54:lO-7.
15. Abbott WGH, Howard BV, Ruotolo 0, Ravussin E. Energy expendi-
ture in humans: effects of dietary fat and carbohydrate. Am J Physiol
16. Acheson KJ, Schutz Y, Bessard T, Anantharaman K, Flatt JP,
J#{233}quier E. Olycogen storage capacity and de novo lipogenesis
during massive carbohydrate overfeeding in man. Am J Clin Nutr
17. SchuLz Y, Flatt JP, J#{233}quierE. Failure of dietary fat intake to promote
fat oxidation: a factor favoring the development of obesity. Am J Clin
Nutr 1989;50:307-14.
18. Bennett C, Reed OW, Peters JC, Abumrad NN, Sun M, Hill JO.
Short-term effects of dietary-fat ingestion on energy expenditure and
nutrient balance. Am J Clin Nutr 1992;55:l071-7.
19. Flatt JP, Ravussin E, Acheson KJ, J#{233}quierE. Effects of dietary fat on
post-prandial substrate oxidation and on carbohydrate and fat balances.
J Clin Invest 1985;76:1019-24.
20. American College of Sports Medicine. Guidelines for exercise
testing and prescription. 3rd ed. Philadelphia: Lea & Febiger,
21. Bruce RA, Kusumi F, Hosmer D. Maximal oxygen intake and mono-
graphic assessment of functional aerobic impairment in cardiovascular
disease. Am Heart J 1973;85:545-62.
22. Goldman RF, Buskirk ER. Body volume measurement by underwater
weighing: description of a method. In: Brozek J, ed. Techniques for
measuring body composition. Washington, DC: National Academy of
Sciences, 1961:78-9.
23. Brozek J, Grande 0, Anderson I, Keys A. Densitometric analysis of
body composition: revision of some quantitative assumptions. Ann N
YAcad Sci 1963;1l0:113-40.
24. Sun M, Reed OW, Hill JO. Modification of a whole-room calorimeter
for measurement of rapid changes in energy expenditure. I Appl
Physiol 1994;76:1937-45.
25. J#{233}quierE, Acheson KJ, Schutz Y. Assessment of energy expenditure
and fuel utilization in man. Annu Rev Nutr 1987;7:187-208.
26. Sun M, Hill JO. A method for measuring mechanical work and work
efficiency during human activities. J Biomechan 1993;26:229-41.
27. Skogerboe KJ, Labb#{233}RF, Rettmer RL, Sundquist JP, Gargett AM.
Chemiluminescent measurement of total urinary nitrogen for accurate
calculation of nitrogen balance. Clin Chem 1990;36:752-5.
28. Hellerstein MK, Christiansen M, Kaempfer 5, et al. Measurement of
de novo lipogenesis in humans using stable isotopes. J Clin Invest
29. Schwartz JM, Neese RA, Basinger A, Hellerstein MK. Effect of oral
fructose on lipolysis, fat oxidation, fractional and absolute de novo
lipogenesis (DNL) using mass isotopomer distribution analysis
(MIDA). FASEB J 1993;7:A867(abstr).
30. Schutz Y, Tremblay A, Weinsier RL, Nelson KM. Role of fat oxida-
tion in the long-term stabilization of body weight in obese women. Am
J Clin Nutr 1992;55:670-4.
31. Zurlo F, Lillioja 5, Esposito-Del Puente A, et al. Low ratio of fat to
carbohydrate oxidation as predictor of weight gain: study of 24-h RQ.
Am i Physiol 1990;259:E650-7.
32. Chang 5, Graham B, Yakubu F, Lin D, Peters JC, Hill JO. Metabolic
differences between obesity prone and obesity resistant rats. Am I
Physiol 1990;259:R1096-102.
33. D#{233}riaz0, Fournier 0, Tremblay A, Despr#{233}sJP, Bouchard C. Lean-
body-mass composition and resting energy expenditure before and
after long-term overfeeding. Am I Clin Nutr 1992;56:840-7.
34. Abou Mrad J, Yakubu F, Lin D, Peters IC, Atkinson JB, Hill JO.
Skeletal muscle composition in dietary obesity-susceptible and dietary
obesity-resistant rats. Am J Physiol 1992;262:R684-8.
35. Wade AJ, Marbut MM, Round JM. Muscle fibre type and aetiology of
obesity. Lancet 1990;335:805-8.
36. Leibel RL, Hirsch J, Appel BE, Checani GC. Energy intake required
to maintain body weight is not affected by wide variation in diet
composition. Am IClin Nutr 1992;55:350-5.
37. Hill JO, Drougas H, Peters JC. Obesity treatment: can diet composition
play a role? Ann Intern Med 1993;1 19:694-7.
by guest on July 13, 2011www.ajcn.orgDownloaded from
Carbohydrate overfeeding: diet example
38. Hayek T, Ito Y, Azrolan N, et al. Dietary fat increases high density
lipoprotein (HDL) levels both by increasing the transport rates and
decreasing the fractional catabolic rates of HDL cholesterol ester and
apolipoprotein (Apo) A-I. Presentation of a new animal model and
mechanistic studies in human Apo A-I transgenic and control mice. I
Clin Invest 1993;91:1665-71.
39. Hegsted DM, Ausman LM, Johnson IA, Dallal GE. Dietary fat and
serum lipids: an evaluation of the experimental data. Am I Clin Nutr
40. Barrett-Connor E, Friedlander NJ. Dietary fat, calories, and the risk of
breast cancer in postmenopausal women: a prospective population-
based “study. J Am Coll Nutr 1993;12:390-9.
Food item Weight
Maintenance: diet example
Plain bagel
Cream cheese
Milk (2% fat)
White sugar
Brewed coffee
White bread
Round steak (lean, broiled)
Potato chips
Brewed tea
White sugar
Peanut butter cup
Sirloin steak (lean, broiled)
Boiled potatoes
Sour cream
Tomato soup, canned
Soda, lemon and lime
Graham crackers
Peanut butter
Milk (2% fat)
Honey nut cheerios’
Whole milk
Half and half cream
White sugar
Brewed coffee
Apple juice
Plain bagel
Steak round (lean, broiled)
Hamburger roll
American cheese (jrocessed)
Pineapple juice
Cream of mushroom soup (canned)
Soda, lemon and lime
Jelly beans
Grape juice
Roast pork tenderloin, lean
French green beans
Boiled potatoes
White bread
Pears, canned in juice
Soda, ginger ale
Milk chocolate, plain
Pound cake
by guest on July 13, 2011www.ajcn.orgDownloaded from
Food item Weight
Fat overfeeding: diet example
Breakfast Cream of wheat, dry weight 35
Whipping cream 202
White sugar 11
Butter 9
Banana, peeled 70
Orange juice 120
Lunch Plain bagel 80
Roast turkey breast, no skin 50
Cheddar cheese 21
Lettuce 25
Mayonnaise 17
Chocolate milk (1% fat) 200
Whipping cream 120
Vanilla ice cream (16% fat) 140
Chocolate syrup 34
Snack Peanut butter cup 51
Dinner Round steak (lean, broiled) 81
Boiled potatoes 130
Whipping cream 30
White bread 25
Broccoli, boiled 90
Butter 30
Snack Saltine crackers 11
Cheddar cheese 20
Example of food module (only offered during baseline diet)2
Banana, peeled 65
Peanut butter 13
Milk (2% fat) 120
General Mills, Minneapolis.
2This food module was offered as milk shakes.
by guest on July 13, 2011www.ajcn.orgDownloaded from
... However, even with fasting, ketones do not reach a steady state until 3 wk (148); on a ketogenic diet, nitrogen balance may remain negative (indicating lean mass breakdown) for 1 mo (149). An adaptive process of several weeks has also been observed with more moderate, nonketogenic macronutrient changes (150)(151)(152). In a recent meta-analysis, low-compared with high-carbohydrate diets slightly reduced energy expenditure in trials < 2.5 wk, but low-carbohydrate diets increased energy expenditure in longer trials (100). ...
Full-text available
According to a commonly held view, the obesity pandemic is caused by overconsumption of modern, highly palatable, energy-dense processed foods, exacerbated by a sedentary lifestyle. However, obesity rates remain at historic highs, despite a persistent focus on eating less and moving more, as guided by the energy balance model (EBM). This public health failure may arise from a fundamental limitation of the EBM itself. Conceptualizing obesity as a disorder of energy balance restates a principle of physics without considering the biological mechanisms that promote weight gain. An alternative paradigm, the carbohydrate-insulin model (CIM), proposes a reversal of causal direction. According to the CIM, increasing fat deposition in the body—resulting from the hormonal responses to a high-glycemic-load diet—drives positive energy balance. The CIM provides a conceptual framework with testable hypotheses for how various modifiable factors influence energy balance and fat storage. Rigorous research is needed to compare the validity of these 2 models, which have substantially different implications for obesity management, and to generate new models that best encompass the evidence.
... Despite the fact that TG levels increase in all pregnancies as a normal physiological function, increased mTG level in early pregnancy suggests an excess intake of fat, even if BMI is normal. While weight increases as the pregnancy progress, the speed of adipose tissue accumulation differs in women, depending on the amount of fat intake [33]. Moreover, weight gain is not linear during pregnancy. ...
Full-text available
A high maternal triglyceride (mTG) level during early pregnancy is linked to adverse pregnancy outcomes, but the use of specific interventions has been met with limited success. A retrospective cohort study was designed to investigate the impact of gestational weight gain (GWG) on the relationship between high levels of mTG and adverse pregnancy outcomes in normal early pregnancy body mass index (BMI) women. The patients included 39,665 women with normal BMI who had a singleton pregnancy and underwent serum lipids screening during early pregnancy. The main outcomes were adverse pregnancy outcomes, including gestational hypertension, preeclampsia, gestational diabetes, cesarean delivery, preterm birth, and large or small size for gestational age (LGA or SGA) at birth. As a result, the high mTG (≥2.05mM) group had increased risks for gestational hypertension ((Adjusted odds ratio (AOR), 1.80; 95% CI, 1.46 to 2.24)), preeclampsia (1.70; 1.38 to 2.11), gestational diabetes (2.50; 2.26 to 2.76), cesarean delivery (1.22; 1.13 to 1.32), preterm birth (1.42, 1.21 to 1.66), and LGA (1.49, 1.33 to 1.68) compared to the low mTG group, after adjustment for potential confounding factors. Additionally, the risks of any adverse outcome were higher in each GWG subgroup among women with high mTG than those in the low mTG group. High mTG augmented risks of gestational hypertension, preeclampsia, preterm birth, and LGA among women with 50th or greater percentile of GWG. Interestingly, among women who gained less than the 50th percentile of GWG subgroups, there was no relationship between high mTG level and risks for those pregnancy outcomes when compared to low mTG women. Therefore, weight control and staying below 50th centile of the suggested GWG according to gestational age can diminish the increased risks of adverse pregnancy outcomes caused by high mTG during early pregnancy.
... The connection between fatty liver and atherosclerosis is well-described (29). It is very possible that the transport of excess glucose to the adipose tissue via lipoproteins creates the particles that cause the atherosclerotic damage (small LDL) (Figure 1) (30)(31)(32). This entire process of dietary carbohydrate leading to fatty liver, leading to small LDL, is reversed by a diet without carbohydrate (26,33,34). ...
Full-text available
Type 2 Diabetes Mellitus (T2DM) is characterized by chronically elevated blood glucose (hyperglycemia) and elevated blood insulin (hyperinsulinemia). When the blood glucose concentration is 100 milligrams/deciliter the bloodstream of an average adult contains about 5–10 grams of glucose. Carbohydrate-restricted diets have been used effectively to treat obesity and T2DM for over 100 years, and their effectiveness may simply be due to lowering the dietary contribution to glucose and insulin levels, which then leads to improvements in hyperglycemia and hyperinsulinemia. Treatments for T2DM that lead to improvements in glycemic control and reductions in blood insulin levels are sensible based on this pathophysiologic perspective. In this article, a pathophysiological argument for using carbohydrate restriction to treat T2DM will be made.
Type 2 diabetes and obesity have reached pandemic proportions throughout the world, so much so that the World Health Organisation coined the term “Globesity” to help encapsulate the magnitude of the problem. G protein-coupled receptors (GPCRs) are highly tractable drug targets due to their wide involvement in all aspects of physiology and pathophysiology, indeed, GPCRs are the targets of approximately 30% of the currently approved drugs. GPCRs are also broadly involved in key physiologies that underlie type 2 diabetes and obesity including feeding reward, appetite and satiety, regulation of blood glucose levels, energy homeostasis and adipose function. Despite this, only two GPCRs are the target of approved pharmaceuticals for treatment of type 2 diabetes and obesity. In this review we discuss the role of these, and select other candidate GPCRs, involved in various facets of type 2 diabetic or obese pathophysiology, how they might be targeted and the potential reasons why pharmaceuticals against these targets have not progressed to clinical use. Finally, we provide a perspective on the current development pipeline of anti-obesity drugs that target GPCRs.
Full-text available
In Ancient days, the day break was started with worships but the trend has changed, now the day break starts with Social networking sites for the youth. Social networking sites like Myspace and Face book have seen tremendous growth over the past few years by attracting youngsters. In recent years social networking sites are playing vital role in youngster’s life. The main objective of this study is aimed to know the Impact of social Networking sites on Young Consumer Buying Behaviour. The present study is empirical in nature .A Stratified sample of 380 respondents was taken for data collection. For Data analysis, Correlation analysis, Mean, Chi-square test are constituted.
Accumulating evidence suggests that maternal overnutrition can result in a higher development risk of obesity and renal disease in the offspring’s adulthood. The present study tested different lipid levels in the maternal diet during pregnancy and lactation and its repercussions on the offspring of Wistar rats. Offspring of 1, 7, 30 and 90-d-old were divided into the following groups: Control (CNT) – offspring of dams that consumed a standard chow diet (3.5% of lipids); Experimental 1 (EXP1) – offspring of dams exposed to a high-fat diet (HFD) (28% of lipids); and Experimental 2 (EXP2) – offspring of dams exposed to a HFD (40% of lipids). Regarding maternal data, there was a decrease in the amount of diet ingested by EXP2. Daily caloric intake was higher in EXP1, while protein and carbohydrate intakes were lower in EXP2. While lipid intake was higher in the experimental groups, EXP1 consumed more lipids than EXP2, despite the body weight gain being higher in EXP2. Adult offspring from EXP1 presented higher blood glucose. Regarding morphometric analysis, in both experimental groups, there was an increase in the glomerular tuft and renal corpuscle areas, but an increase in the capsular space area only in EXP1. There was a decrease in the glomerular filtration rate (GFR) in EXP1, in contrast to an increase in GFR of EXP2, along with an increase in urinary protein excretion. In conclusion, the maternal HFDs caused significant kidney damage in offspring, but had different repercussions on the type and magnitude of recorded change.
Full-text available
The incidence of childhood obesity has been increased alarmingly for the past three decades. To know the influence of life style habits in school going children on obesity and to create awareness for practicing healthy lifestyle. A questionnaire was circulated among 200 students between 10-14 years of age in a private school after taking permission from the authorities.190 children participated in the study. 23 questions were asked which included the habits like eating chocolates, sleeping in the afternoon, playing outdoor or indoor, family history of obesity, mode of transport etc. Two image based questions were included to know their interests towards playing outdoor games or indoor videogames and liking towards junk food or fresh vegetables. The response was evaluated and represented graphically.
Full-text available
Parkinson’s disease (PD) is characterized by the degeneration of dopaminergic neurons in the substantia nigra and the formation of Lewy bodies. The mechanisms underlying these molecular and cellular effects are largely unknown. Previously, based on genetic and other data, we built a molecular landscape of PD that highlighted a central role for lipids. To explore which lipid species may be involved in PD pathology, we used published genome-wide association study (GWAS) data to conduct polygenic risk score-based analyses to examine putative genetic sharing between PD and blood levels of 370 lipid species and lipid-related molecules. We found a shared genetic etiology between PD and blood levels of 25 lipids. We then used data from a much-extended GWAS of PD to try and corroborate our findings. Across both analyses, we found genetic overlap between PD and blood levels of eight lipid species, namely two polyunsaturated fatty acids (PUFA 20:3n3-n6 and 20:4n6), four triacylglycerols (TAG 44:1, 46:1, 46:2, and 48:0), phosphatidylcholine aa 32:3 (PC aa 32:3) and sphingomyelin 26:0 (SM 26:0). Analysis of the concordance—the agreement in genetic variant effect directions across two traits—revealed a significant negative concordance between PD and blood levels of the four triacylglycerols and PC aa 32:3 and a positive concordance between PD and blood levels of both PUFA and SM 26:0. Taken together, our analyses imply that genetic variants associated with PD modulate blood levels of a specific set of lipid species supporting a key role of these lipids in PD etiology.
Full-text available
The aim of this study was to determine the relationships between maternal metabolic flexibility during pregnancy and neonatal health outcomes. Percent change in lipid oxidation (before and after a high-fat meal) was calculated as the measure of “metabolic flexibility”. Neonatal adiposity was assessed within 48 h of delivery by skinfold anthropometry. Metabolic flexibility (r = −0.271, p = 0.034), maternal HOMA-IR (r = 0.280, p = 0.030), and maternal body mass index (r = 0.299, p = 0.018) were correlated with neonatal subscapular skinfold (i.e., measure of neonatal adiposity). Clinical Trail Registration Number: NCT03504319. Novelty: This is the first study to link maternal metabolic flexibility, body mass index, and insulin resistance during pregnancy to neonatal adiposity at parturition.
We tested the hypothesis that a high-fat diet increases the risk of breast cancer in a population-based study of 590 women aged 40-79 years who were without known breast cancer when they provided a quantitative 24-hour diet recall. Fifteen postmenopausal women were diagnosed with incident breast cancer during the next 15 years (approximately 7600 person-years of follow-up). These women had significantly higher age-adjusted intake of all fats (monounsaturated, polyunsaturated, and saturated), and oleic, linoleic, and linolenic acids, with a stepwise increase in risk across tertiles of intake. Fat intake was associated with total calories, protein, and carbohydrates, and women with incident breast cancer consumed more calories, protein, and carbohydrates than did other subjects. When each nutrient variable (calories, fats, protein, and carbohydrates) was adjusted for age, body mass index, age at menopause, parity, and alcohol consumption, the strongest risks for incident breast cancer were associated with total calories (relative risk per standard deviation = 2.72, 95% confidence interval = 1.51-4.89, p = 0.002) and total fats (relative risk per standard deviation = 2.01, 95% confidence interval = 1.19-3.41, p = 0.01). Fat composition of the diet, expressed either as percent of energy or as fat intake adjusted for calories by regression analysis, was not significantly associated with risk of breast cancer. These results support the hypothesis that total calorie consumption, as well as dietary fat consumption, is a risk factor for breast cancer in postmenopausal women, and parallel observations in animal models.
Regression analysis of the combined published data on the effects of dietary fatty acids and cholesterol on serum cholesterol and lipoprotein cholesterol evaluated with groups of human subjects shows that 1) saturated fatty acids increase and are the primary determinants of serum cholesterol, 2) polyunsaturated fatty acids actively lower serum cholesterol, 3) monounsaturated fatty acids have no independent effect on serum cholesterol and, 4) dietary cholesterol increases serum cholesterol and must be considered when the effects of fatty acids are evaluated. More limited data on low-density-lipoprotein cholesterol (LDL-C) show that changes in LDL-C roughly parallel the changes in serum cholesterol but that changes in high-density-lipoprotein cholesterol cannot be satisfactorily predicted from available data.
Weight the losson food a diet:theimprecisionofcontrolof intakein humans
  • A Levitsky
  • Da
  • Bj Strupp
  • Lissnerl
A,Levitsky consequence DA,Strupp of BJ,LissnerL.Weight the losson food a diet:theimprecisionofcontrolof intakein humans.AmJ ClinNutr1991;53:1124-9