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The U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA 02111.
4To whom correspondence should be addressed. E-mail: sroberts{at}hnrc.tufts.edu.
 |
ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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KEY WORDS: • aging • energy metabolism • humans • respiratory quotient • body composition
|
INTRODUCTION |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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,
Roberts et al. 1994
). After 65 y, body weight and
fat mass typically decrease (Shimokata et al. 1989
,
Steen, 1988
). Both of these shifts in body weight and
composition are thought to be undesirable. In particular, fat gain
through middle age is associated with increased risks for premature
death and disability (U.S. Department of Health and Human Services 1990), and weight and fat loss in late life predict
early death even in individuals without any detectable preexisting
disease (Pamuk et al. 1992
, Tayback et al. 1990
).
We previously speculated that a decrease in the body’s usual ability
to detect and appropriately compensate for normal fluctuations in
energy balance may be an important factor contributing to changes in
body composition with age (Roberts et al. 1994, 1996a and 1996b
). Concerning the energy expenditure component of this
compensation, we investigated the effects of age on energy metabolism
during 3 wk of overfeeding or underfeeding in men (Roberts et al. 1996a and 1996b
), but the results were inconclusive in some
respects. In particular, we found no significant difference in the
decrease in resting energy expenditure
(REE)5
with underfeeding between the young and older subjects and, in
addition, no significant difference was observed between the young and
older subjects in changes in the thermic effect of feeding (TEF) or
maintenance energy expenditure (averaged values for REE and TEF)
(Roberts et al. 1996b
). However, in a combined analysis
of the underfeeding data with similar data from an overfeeding study
(Saltzman and Roberts 1996
), a consistent attenuation of
energy expenditure responsiveness to both underfeeding and overfeeding
in the elderly was suggested. In other words, in the combined data set,
the elderly had attenuated energy expenditure responses to both
overfeeding and underfeeding.
The purpose of this investigation was to further examine changes in
energy regulation with age. Specifically, we tested the hypothesis
that, compared with young individuals, older men and women have an
impaired ability to reduce energy expenditure during negative energy
balance independent of differences in body fat content. In addition, we
tested the hypothesis that older men and women have a reduced ability
to oxidize fat during underfeeding because the extent to which basal
fat oxidation is impaired in elderly individuals remains unclear
(Arciero et al. 1995
, Bonadonna et al. 1994
, Calles-Escandon et al. 1995
,
Klausen et al. 1997
, Melanson et al. 1997
, Rising et al. 1996
, Weyer et al. 2000
).
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SUBJECTS AND METHODS |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Young men and women (n = 30) aged 19–30 y and
older men and women (n = 22) aged 64–78 y, all
Caucasian, non-Hispanic, were recruited for this study from the
Greater Boston Area. Half of the young group was of normal weight [YNW
group, body mass index (BMI) 18–24 kg/m2], and the other
half was overweight or obese (YOW group, BMI 25–39 kg/m2).
Because BMI in the older group spanned the range seen in the young
overweight subjects (OLD group, BMI 21–34 kg/m2),
it was expected that this would result in levels of body fat similar to
those of the YOW group. Forty of the recruited subjects successfully
completed the protocol, including passing dietary compliance tests as
described elsewhere (Moriguti et al. 2000
,
Saltzman et al. 2001
), and their characteristics are
given in Table 1
. Before the study, all subjects were free of disease, weight stable,
not taking any medications or drugs known to influence energy
regulation, and healthy as judged by normal results on physical
examination, routine screening laboratory tests (complete blood count,
urinalysis and serum sodium, potassium, bicarbonate, blood urea
nitrogen and creatinine) and electrocardiogram. Particular exclusions
for the study included engaging in >1 h/d of strenuous physical
activity, BMI outside the range 18–39 kg/m2,
dietary restraint score >9 (Stunkard and Messick 1985
)
and self-reported consumption of >2 alcoholic drinks/d. The
measurements were conducted in the Metabolic Research Unit at the Jean
Mayer USDA Human Nutrition Research Center at Tufts University. The
protocol was approved by the Human Investigations Review Committee of
the Tufts University New England Medical Center, and all subjects gave
written informed consent before participating.
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Subjects were able and encouraged to follow a normal lifestyle during the study and all continued their usual occupations. The protocol was an 8-wk study divided into two phases. During the study, all food and energy-containing beverages were provided by the research center. Subjects were required to sleep at the research center on the night before the start of the study and on nights before metabolic testing, but otherwise could reside at home or the center as they preferred. If they chose to live at home, they came to the research center at least 5 times per week during wk 1 of the study and 3–4 times per week during the next 7 wk to collect their food for the following day and return leftovers and containers. Physical activity was not restricted, and subjects were requested to maintain their usual level and types of strenuous activities, which were monitored by using Caltrac activity monitors (Caltrac Muscle Dynamics Fitness Network, Torrance, CA 90502) (data not shown).
During the first 2 wk of the study, designated Phase 1, all subjects consumed the control diet provided. Weight-maintenance energy requirements were established for each subject during wk 1 of the phase and were generally maintained at that fixed level during wk 2. The amount of dietary energy provided to subjects on study d 1 was based on a dietitian’s estimate of energy requirements (using Nutrition Data System version 2.4/6A/21, Nutrition Coordinating Center, University of Minnesota School of Public Health), taking into account age, gender, fasting body weight on d 1 and the self-reported level of physical activity. Body weight was determined to ± 100 g at least five times during wk 1 (Toledo weight plate electronic balance, Model I5S, Ohaus Corporation, Florham Park, NJ), and energy intake was adjusted as necessary to maintain weight within 500 g of the value on d 1. Subjects were allowed to leave partial portions of food uneaten; these were reweighed to estimate their energy content. During wk 2 of Phase 1, subjects were given the calculated average of energy consumed during wk 1, and were required to completely consume all portions of food and rinse and scrape food containers unless a noticeable trend in body weight occurred (in which case a second adjustment to intake was made).
The following 6 wk of the study were designated Phase 2, and during this time energy intake was decreased by an average of 3.75 MJ/d relative to Phase 1 (see below). At the end of Phase 2, fasting body weight and body composition were again determined. It should be noted that we recognize that different results may be obtained in underfeeding studies depending on whether the chosen energy deficit is a fixed value for all subjects or proportional to initial energy requirements. Ultimately, studies with both fixed energy reductions and proportional energy reductions are required for evaluation of biological effects of underfeeding, but a fixed energy deficit was chosen for the initial study because some energy expenditure components (for example postprandial thermogenesis) are proportional to absolute energy intake. Interpretation of the results from a fixed energy deficit study requires fewer assumptions than interpretation of results from a study in which the energy deficit varies in magnitude among subjects.
Diets.
Meals consisted of normal food and beverage items divided between 3
meals plus a snack each day. Three menus were provided on a 3-d
rotating basis. Coffee and tea were available in fixed daily amounts if
they formed part of the subject’s normal diet. Sodium intake of foods
offered was fixed in Phase 1, remained constant throughout Phases 1 and
2, and subjects were advised to add no additional salt. In addition, a
standard multivitamin/mineral supplement was given throughout Phase 2
to ensure no deficiency in any essential nutrient when energy intake
was decreased. At least one meal per day was consumed in the research
center 5 d/wk during wk 1, and at least 3 d/wk subsequently. Others
meals were consumed either at the research center or at the subject’s
residence according to individual preference. As described elsewhere
(Moriguti et al. 2000
), compliance with the food
requirement component of the study was assessed by the urinary
osmolality procedure (Roberts et al. 1991
), and data
from three individuals with osmolar excretion rates >130% expected
were excluded from the data analysis because this indicated
noncompliance.
The nutrient content of the diets provided during Phase 1 was designed
to mimic a typical American diet, providing 35% of energy from fat,
13% of energy from protein and 52% from carbohydrate. During Phase 2,
protein intake (g) was maintained at the Phase 1 level and energy
intake was decreased by 
4.2 MJ/d relative to Phase 1 in all but
seven subjects (who had initial energy intakes that were low and for
whom a 4.2 MJ reduction was considered too severe; in these cases, a
3.3–3.8 MJ/d deficit was employed). The energy reduction was achieved
by a proportional reduction in carbohydrate and fat. In addition, all
subjects were randomly assigned within gender and age-group
categories to receive either a diet containing rolled oats (45 g/4.2
MJ) or a diet that had the same percentage of energy from fat, protein,
carbohydrate and the same insoluble fiber concentration per 4.2 MJ, but
with an equivalent amount of wheat products substituted for oats. There
was no effect of the oats vs. non-oats diet on body composition or
changes in body weight or composition as described elsewhere
(Saltzman et al. 2001
).
Anthropometry and body composition.
Body weight and height were measured to ± 100 g and 0.1 cm,
respectively, and body density was measured by hydrostatic weighing
after a 12-h overnight fast (Moriguti et al. 2000
). Body
density was calculated with the residual lung volume predicted by
Quanjer’s equation (Quanjer et al. 1993
). Hydrostatic
measurements were repeated until at least three were within 1% body
fat of each other, and the average of these three tests was used for
analysis. Fat mass and fat-free mass were calculated using the
equation of Siri (Siri 1961
). For subjects in whom body
composition was not measured on the very last day of a Phase, end of
phase values were calculated assuming proportional changes in body
weight and composition.
Calorimetric measurements of energy expenditure.
Resting VO2 and VCO2 were measured under thermoneutral temperature conditions in the fasting state on four occasions during the study (2 measurements in the last week of Phase 1, and 2 measurements in the last week of Phase 2) and in the fed state on one occasion. The measurements during the fasted state (for REE) were made for 30 min before breakfast, (12–13 h after the last meal) after the subjects had slept overnight at the research center. Subjects were instructed to relax and avoid hyperventilation, fidgeting and sleeping during measurements, which were made with the subjects in a supine position using an open-circuit indirect calorimeter (Deltatrac, SensorMedics, Yorba Linda, CA) calibrated using mixed reference gases of known concentration. For the postprandial measurement, which was performed immediately after one of the fasting measurements in Phase 1, subjects consumed a test meal containing energy equal to 80% of the measured REE and consisting of usual food items (cookies and milk) with the same proportions of macronutrients as the main diet. Postprandial measurements were made for 20 min out of each 30 until 6 h after the breakfast, and subjects remained resting or used the bathroom during the 10-min breaks. The CV for repeated measurements of REE was 5.7 ± 3.5% (r for measurement 1 vs. measurement 2 = 0.95, P < 0.001) and the CV for repeated measurements of the respiratory quotient (RQ) was 4.0 ± 2.5% (r for measurement 1 vs. measurement 2 = 0.50, P < 0.001)
Values for REE were calculated from each fasting determination of
VO2 and VCO2 using
Weir’s equation (Weir 1949
). The mean postprandial
increase in energy expenditure, or TEF, was calculated as the average
increment in metabolic rate above the fasting level for each
measurement in each subject, expressed as a percentage of energy intake
from the test meal. The means of duplicate measurements of REE and
fasting RQ within phases were used in the data analysis.
Statistical analyses.
Data were analyzed using SPSS version 10.0 and Systat Version 9.0 (SPSS, Chicago, IL) and are expressed as means ± SEM unless otherwise specified. Group means in Phases 1 and 2 were compared using ANOVA. Analysis of covariance (ANCOVA) was also used to compare group means for REE while adjusting for body weight or body composition. To compare differences among groups in changes over time, change variables between phases were calculated as Phase 2 - Phase 1, and ANOVA was performed. Post-hoc multiple comparisons were performed using a Bonferroni correction. Significant determinants of the change in REE were assessed by using stepwise, backwards ANCOVA procedures. This involved including group and other variables and their interaction in the first step. Subsequently, if the interaction was not significant, it was removed and the analysis was repeated. For all tests, statistical significance was accepted at the 0.05 level.
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RESULTS |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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shows the characteristics and weight change of the
subjects. Weight and BMI during Phase 1 were significantly higher in
the YOW and OLD groups than in the YNW subjects. In addition, relative
body fat (fat mass expressed as % body weight) was significantly
higher in the OLD subjects than the YNW and YOW subjects, but the
relative body fat of YOW subjects was not significantly different from
YNW subjects.
Table 2
shows values for the energy expenditure parameters and weight change in
both study phases. Weight change during Phase 1 (approximate weight
maintenance) was not significantly different among the groups, but
weight change in Phase 2 (intentional weight loss phase) was
significantly greater in OLD subjects than YNW subjects. As described
elsewhere, there was no significant difference among groups in the
composition of weight loss in Phase 2 (Moriguti et al. 2000
). REE did not differ significantly among the three groups
in either Phase 1 or Phase 2. However, in Phase 1, both REE adjusted
for body weight and REE adjusted for fat-free mass and fat mass
were significantly lower in OLD subjects compared with the YNW and YOW
groups. Thus, REE was lower in OLD subjects compared with young
subjects after taking into account differences in weight or body
composition among groups. In Phase 2, REE adjusted for weight was again
significantly lower in OLD than in YNW and YOW subjects, whereas REE
adjusted for fat-free mass and fat mass was significantly lower in
OLD than in YNW subjects, but was not significantly lower in OLD than
YOW subjects (P = 0.183). Fasting RQ did not differ
significantly among the groups in either phase. REE and fasting RQ were
significantly lower in Phase 2 compared with Phase 1, but there were no
significant differences in the changes among groups. There was also no
significant different in postprandial RQ among groups (data not shown).
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REE between phases as shown in
Table 3
. The best fitting model included group, weight change in Phase 1 and a
significant interaction between group and change in weight (adjusted
R2 = 0.17). The equations show that
the decrease in REE between the end of Phase 1 and the end of Phase 2
was smaller in the OLD than the young subjects in relation to the
change in body weight, and this is also illustrated in Figure 1
. There were no significant models that predicted RQ in Phase 2 (data
not shown).
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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) with the result that the absolute decrease in REE was
reduced in OLD subjects relative to body weight loss. As shown in
Figure 1
, REE was suppressed at all rates of weight loss in young
subjects, but was not measurably depressed in OLD subjects unless
weight loss was very rapid. Weight loss is a well-known correlate
of reduced REE during underfeeding (Saltzman and Roberts 1995
) and thus was an expected predictor of the change in REE
with underfeeding in this study. However, the question of whether aging
is associated with abnormalities in the change in REE with energy
balance had not been resolved (Roberts et al. 1996b
, Saltzman and Roberts 1996
). The
results are consistent with our previous suggestion that the reduction
in REE during dieting is attenuated in the elderly compared with young
subjects (Saltzman and Roberts 1996
), and suggest an
age-related impairment in the normal mechanisms that serve to
conserve energy during periods of reduced food intake. Further studies
in this area are warranted to investigate such factors as sympathetic
nervous system activity, thyroid hormone status and uncoupling
activity, that may mediate the observed age-related change in REE
responsiveness.
There was no significant difference in unadjusted REE or TEF among the
groups either at baseline in Phase 1 or after weight loss in Phase 2.
However, REE adjusted for either weight or fat-free mass plus fat
mass was significantly lower in the OLD subjects compared with YNW and
YOW subjects. Several previous studies have investigated whether REE is
lower in the elderly after adjusting for fat-free mass and results
have been conflicting, with some studies reporting lower adjusted REE
in the elderly (Fukagawa et al. 1990
, Poehlman et al. 1993a
, Roberts, 1995
, Vaughan et al. 1991
) and others finding no difference between young and
elderly groups (Cunningham 1980
, Poehlman et al. 1993b
, Roubenoff et al. 2000
). However,
only one of the previous studies took into account the energy
expenditure resulting from both fat-free mass and fat mass
(Vaughan et al. 1991
), and in that case REE was lower in
the older subjects. In this study, we also accounted for fat mass by
adjusting REE simultaneously for both fat-free mass and fat mass,
and values were significantly lower than both YNW and YOW subjects in
Phase 1 and lower than YNW subjects in Phase 2. These findings strongly
suggest that REE is indeed lower in the elderly compared with young
adults after taking body composition changes with age into account. The
primary causes of this decline in adjusted REE with age are not certain
and require further study.
Also relevant to REE, it is noteworthy that mean absolute values for
REE in the elderly subjects in this study were only slightly lower than
values for YNW subjects, in apparent contrast to the widely quoted
1–2% decline per decade (Keys et al. 1973
). This is
because the 1–2% decline assumes that constant body weight and the
substantial weight gain now typically experienced during early adult
and middle age (Flegal et al. 1998
) can compensate for
the potential loss of REE due to changes in body composition. The net
effect is that absolute values for REE may now be similar to, or even
higher (Klausen et al. 1997
) in older subjects compared
with young ones.
We also found no significant difference in fasting or postprandial RQ
among the groups, and no differences in changes in RQ with weight loss.
Some previous studies, including one from our laboratory
(Calles-Escandon et al. 1995
, Melanson et al. 1997
), have previously reported lower fat oxidation in older
individuals, whereas other work has suggested higher fat oxidation in
elderly individuals (Bonadonna et al. 1994
). The present
results suggest no effect of age on fat oxidation in either the fasting
or postprandial state. It is possible that defects in fat oxidation
associated with old age occur under specific circumstances, perhaps
dependent on metabolic conditions such as postprandial state, overall
level of energy intake, and possibly factors such as gender and test
meal type. In relation to the last-mentioned suggestion, this study
used the same relative meal size for all subjects (80% of REE,
compared with the fixed 4.2 MJ meal size in our previous study) and
also a more palatable test meal (cookies and milk, compared with
sandwiches and milk previously). Palatability has recently been shown
to have independent effects on digestion rate (Sawaya et al. 2000), which may have affected the results obtained. Further
studies in this area are clearly warranted.
In conclusion, data from this 6-wk underfeeding study in young and
older men and women are consistent with our previous suggestion, based
on 3-wk underfeeding in men (Saltzman and Roberts, 1996
), that older individuals experience an overall decrease in
the ability to conserve energy during undereating. The combination of
this finding with our previous observation that the regulation of
energy intake is impaired in older men (Roberts et al. 1994
) may help to explain the increased susceptibility of the
elderly to weight loss.
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ACKNOWLEDGMENTS |
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|
FOOTNOTES |
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2 The first two authors made similar
contributions.
3 J.C.M. was funded in part by
Fundação de Amparo à Pesquisa do Estado de São
Paulo, Brazil and the Medical School of Ribeirão Preto of
São Paulo University, Brazil.
5 Abbreviations used: ANCOVA, analysis of
covariance; BMI, body mass index; OLD, old; REE, resting energy
expenditure; RQ, respiratory quotient; TEF, thermic effect of feeding;
YNW, young normal weight; YOW, young overweight.
Manuscript received August 23, 2000. Initial review completed October 4, 2000. Revision accepted March 22, 2001.
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Weyer C., Pratley R., Salbe A., Bogardus C., Ravussin E., Tataranni P. Energy expenditure, fat oxidation, and body weight regulation: a study of metabolic adaptation to long-term weight change. J. Clin. Endocrinol. Metab. 2000;85:1087-1094
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