International Journal of Obesity (1998) 22, 236±242
ß 1998 Stockton Press All rights reserved 0307±0565/98 $12.00
Differences in resting energy expenditure in
African-American vs Caucasian overweight
females
JM Jakicic and RR Wing
University of Pittsburgh School of Medicine, Pittsburgh, USA
OBJECTIVE: The purpose of this study was to examine differences in both resting energy expenditure (REE) and
respiratory quotient (RQ) between overweight African-American and Caucasian women of comparable age and body
mass index (BMI).
DESIGN: Cross-sectional.
SUBJECTS: REE was assessed in 41 women (22 African-American and 19 Caucasian) who were recruited to participate
in this study. The African-American women were aged 36.4 5.7 y with a BMI of 32.6 5.4 kg/m2, and the Caucasian
women were aged 35.4 5.7 y with a BMI of 31.3 3.4 kg/m2.
MEASUREMENTS: Body composition was assessed using dual energy x-ray absorptiometry (DEXA). REE was
assessed via the dilution technique following an overnight fast.
RESULTS: REE was lower in African-Americans (7279 825 kJ/d) compared to Caucasians (7807 854 kJ/d)
(P ˆ 0.051). Analysis of covariance showed that REE remained signi®cantly lower in African-American women after
correcting for body weight and lean body mass. There was no effect of ethnicity on RQ.
CONCLUSION: These results indicate that there is a signi®cant difference in REE between Caucasian and AfricanAmerican overweight women. This difference in REE may contribute to the higher rates of obesity found in the
African-American population. This difference may also partially explain the smaller weight losses typically seen in
African-American women when compared to Caucasian women enrolled in a weight loss program.
Keywords: metabolic rate; body composition; obesity; African-American
Introduction
It is estimated that approximately one in three adults
in the United States over the age of 20 y is at least
20% over their ideal body weight. However, the
number of overweight African-American women is
especially high, with approximately 48% of AfricanAmerican women classi®ed as overweight.1 It has
been hypothesized that this may be due in part to
cultural and socioeconomic differences,2±4 and to
behavioral factors such as lower levels of physical
activity compared to Caucasians.5±7 However, there is
evidence which indicates that differences in metabolic
factors may contribute to the higher rates of obesity in
African-American women.
Several recent studies have suggested that the rate
of resting energy expenditure (REE), which accounts
for approximately 65% of total energy expenditure,
may be lower in African-American women compared
to Caucasian women. The study by Foster et al8
reported a signi®cantly lower REE in obese AfricanAmerican women compared to obese Caucasian
Correspondence: John M Jakicic, PhD, University of Pittsburgh
School of Medicine, Western Psychiatric Institute and Clinic,
3811 O'Hara Street, Pittsburgh, PA 15213, USA.
Received 21 May 1997; revised 15 OCtober 1997; accepted
3 November 1997
women, and similar results were shown in lean
women.9 However, Nicklas et al10 showed no effect
of ethnicity on REE in older adults. In these studies,
the results remained unchanged after correcting for
fat-free mass (FFM).
It has been shown that bone density is higher in
African-Americans when compared to Caucasians,11,12 and this may contribute to a greater
amount of FFM in this population. However, studies
examining differences in REE between AfricanAmericans and Caucasians that have adjusted for
FFM have not considered the in¯uence of bone
density on these results. Therefore, it may be advantageous to include a measurement of bone density in
these studies.
Another physiological factor that may contribute to
the development of obesity is substrate oxidation
rates. Zurlo et al13 showed a signi®cant relationship
between 24 h respiratory quotient (RQ) measured in a
respiratory chamber and weight gain in Pima Indians.
In addition, data from the Baltimore Longitudinal
Study indicate that non-obese men with a higher
fasting RQ are at increased risk for weight gain
when compared to individuals with a lower RQ.14
These results suggest that individuals with a low rate
of fat oxidation (a high RQ) are more likely to gain
weight than individuals with a higher rate of fat
oxidation (a low RQ). However, the limited number
Ethnicity and resting energy expenditure
JM Jakicic and RR Wing
of studies that have compared African-American and
Caucasian women have had mixed results. Chitwood
et al9 showed a signi®cantly higher RQ in lean
African-American women compared to lean white
women. In contrast, both Nicklas et al10 and Foster
et al8 found no difference in resting RQ between
obese African-American and Caucasian women.
Thus, additional research in this area appears warranted.
Therefore, the purpose of this study was to examine
the following questions: 1) Are there signi®cant differences in REE between African-American women
and Caucasian women after correcting for body
weight, FFM and bone mineral content (BMC), and
2) are there signi®cant differences in resting RQ
between overweight African-American and Caucasian
women?
Methods
Subjects
Fifty-®ve overweight women (27 Caucasian and 28
African-American) were recruited to participate in
this study. Participants were recruited through local
newspaper and radio advertisements. Subjects were
asked to identify their ethnic/racial group and were to
select from the following choices: 1) White, 2) African-American or Black, 3) Asian American or Asian,
4) Native American Indian, 5) Hispanic, 6) other
ethnic/racial group. Only those individuals identifying
themselves as `White' or `African-American or
Black' were eligible to participate in this study.
Subjects were aged 25±45 y and had a body mass
index (BMI) of 25.0±40.0 kg/m2. In an attempt to
recruit participants of similar age and BMI from
each of the ethnic groups, eligible subjects were
divided into three BMI categories and two age cate-
gories according to the age and BMI reported during
an initial telephone interview. Age categories were
25±35 y and 36±45 y, with BMI categories set at
<30 kg/m2, 30±35 kg/m2 and >35 kg/m2. For younger
women, the BMI distribution was eight (three Caucasian, ®ve African-American), nine (®ve Caucasian,
four African-American), and three (one Caucasian,
two African-American) in each of the BMI categories.
For women aged 36±45 y the distribution in the BMI
categories was 16 (nine Caucasian, seven AfricanAmerican), 13 (seven Caucasian, six African-American), and six (two Caucasian, four African-American), respectively. Based on self-reported medical
history, subjects were not taking prescription medication, were free from metabolic disorders (for example
hypothyroidism, diabetes) and were non-smokers.
Seven Caucasians and eight African-Americans
reported never consuming alcoholic beverages, with
the remainder of the subjects reporting consuming
alcoholic beverages 2 d/week. Descriptive characteristics of these subjects are presented in Table 1.
Prior to participation in this study, all subjects
provided written informed consent and competed a
medical history questionnaire. All procedures were
approved by the Institutional Review Board at the
University of Pittsburgh.
Weight and height
Each subject wore a light-weight hospital gown and
was weighed on a calibrated balance-beam scale
(Detecto Inc, Webb City, MO). Height was measured
using a calibrated stature board (Perspective Enterprises Inc, Kalamazoo, MI).
Body composition and bone mineral content
Body composition and bone mineral content (BMC)
were measured using a Lunar (Madison, WI) DPXL
Dual-Energy X-ray Absorptiometer (DEXA). The
Table 1 Comparison of age, weight, and body composition between overweight African-American and Caucasian women (mean standard deviation)
African-American (n ˆ 28)a
Age (y)
Weight (kg)
BMI (kg/m2)
BMD (g/cm2)a
BMC (kg)a
FFM (kg) (tissue ‡ BMC)a
FFM (kg) (tissue only)a
Fat mass (kg)a
Percent body fat (FFM ˆ tissue ‡ BMC)a
Percent body fat (FFM ˆ tissue only)a
Dietary recallb
Total intake (kJ/d)
Carbohydrates (g/d)
Fat (g/d)
Protein (g/d)
Physical activity (kJ/week)
a
Caucasian (n ˆ 27)b
P-value
36.9 5.7
86.3 14.6
32.1 5.1
1.3 0.1
2.7 0.3
49.5 4.5
46.8 4.4
34.9 9.5
40.7 5.5
42.0 5.4
36.9 5.7
83.1 11.5
31.2 3.6
1.2 0.1
2.5 0.3
47.3 5.0
44.8 4.8
34.8 8.2
42.0 5.0
43.3 5.1
0.98
0.36
0.43
<0.001
0.01
0.09
0.12
0.98
0.39
0.40
8230 4826
250 161
75 56
74 39
970 944
6974 3056
202 106
68 35
61 19
1381 1238
0.26
0.20
0.61
0.13
0.27
Body composition values were not obtained on one African-American individual due to weight limitations of the dual energy x-ray
absorptiometry (DEXA), thus the n for those variables equals 27.
Dietary recall data not obtained on one Caucasian individual, thus n for those variables equals 26.
BMI ˆ body mass index; BMD ˆ body mineral density; BMC ˆ body mineral content; FFM ˆ fat-free mass.
b
237
Ethnicity and resting energy expenditure
JM Jakicic and RR Wing
238
subject was placed in a supine position while their
body was scanned in the total body scanning mode
according to the scanning speeds recommended by the
manufacturer. Results of this assessment provide
estimates of fat mass, total FFM (FFMtotal ˆ
tissue ‡ BMC), tissue FFM (FFMtissue ˆ total FFM ÿ
BMC), BMC, and bone mineral density (BMD).
Resting energy expenditure (REE) and respiratory
quotient (RQ)
Subjects were instructed to fast and abstain from
vigorous activity for 12 h prior to the evaluation of
REE. During this time subjects were instructed not to
take any over-the-counter medications and were not to
consume any ¯uids which contained caffeine (for
example, coffee, tea, diet colas, etc.), however
normal water consumption was permitted. These procedures are identical to the procedures used by Foster
et al8 in their study of REE differences in Caucasian
and African-American women. All REE assessments
were completed between 07:00 and 09:00 h. REE was
measured via the dilution technique15 using a SensorMedics 2900 metabolic measuring cart (Yorba Linda,
CA) and a plastic canopy. The metabolic cart was
calibrated prior to each test using known gas concentrations and volumes according to the procedures
recommended by the manufacturer.
Upon entering the laboratory the morning of the
evaluation, subjects changed into a hospital gown and
were weighed. Following a 5 min rest period in a seated
position in an isolated room, resting blood pressure and
heart rate were assessed. Subjects were then placed in a
supine position for a rest period of 30 min prior to the
assessment of REE. Following this 30 min rest period,
subjects were placed under the canopy in a supine
position for a 5 min acclimation period, which was
followed by a 5 min steady state measurement period.
The coef®cient of variation in REE was less than 5% for
this minute-by-minute data. Similar methods were used
by Foster et al.8 Unpublished results from our laboratory
have shown no signi®cant difference in REE measured
in the initial 5 min steady state period and the REE
measured during a 20 min evaluation period with the
mean difference being 117 343 kJ/d (28 82 kcal/d)
and these values were signi®cantly correlated (r ˆ 0.92,
P < 0.001). The coef®cient of variation for test-retest in
our laboratory is 5.3%. The ratio of carbon dioxide
produced to the volume of oxygen consumed, was
used to compute the RQ that corresponded to each
minute. Takala et al16 reported that the accuracy of the
dilution method using a device similar to the SensorMedics 2900 Metabolic Cart is 4%. Therefore, because
of this possible error, RQ's 0.68 were acceptable in
this study.
Dietary recall
Intake of total calories and grams of carbohydrates,
fats and proteins were estimated using the Block Food
Frequency Questionnaire.17
Physical activity recall
The Paffenbarger Physical Activity Questionnaire18,19
was used to assess physical activity.
Statistical analysis
Statistical analyses were performed using Statistical
Packages for the Social Sciences (version 7.5 for
Windows). Statistical signi®cance was de®ned as
P < 0.05. Independent t-tests were used to assess
differences in age, body weight, body composition,
BMC, dietary intake, REE and RQ between Caucasian
and African-American women. Differences in physical activity were assessed using a Mann-Whitney test.
In addition, REE was analyzed using analysis of
covariance (ANCOVA) controlling for body weight
and FFM (FFMtotal and FFMtissue).
Results
Comparisons of the two ethnic groups showed no
signi®cant differences in age, weight, BMI, fat mass,
percent body fat, dietary intake or physical activity
(see Table 1). Body composition, BMC and BMD
data were available on 54 of the 55 subjects, with one
subject not tested because she exceeded the maximum
weight capacity of the DEXA (maximum weight
capacity ˆ 120 kg). FFMtotal and FFMtissue were
approximately 2 kg higher in the African-American
women compared to the white women, but this difference was not statistically signi®cant. BMC was
0.21 kg higher in African-Americans compared to
Caucasians (P < 0.01), and bone mineral density was
1.30 0.07 g/cm2 in the African-American women
and 1.23 0.08 g/cm2 in the Caucasian women
(P < 0.001).
The focus of this study was to examine differences
in both REE and RQ between African-American and
Caucasian overweight women. Close examination of
the REE and RQ data showed that 14 subjects did not
meet either the REE (coef®cient of variation <5%) or
RQ (0.68) criteria outlined earlier (see Methods).
Therefore, data from 41 subjects were analyzed and
characteristics of these subjects are presented in Table
2). Results showed that REE was 7489 825 kJ/d
(1739 197 kcal/d) in African-American women
compared to 7995 875 kJ/d (1865 204 kcal/d) in
Caucasian women (P ˆ 0.051).
REE remained signi®cantly lower in the AfricanAmerican women after correcting for body weight and
body composition (Table 3). Using ANCOVA and
including body weight as a covariate, results showed
that REE was 707 kJ/d (169 kcal/d) lower in AfricanAmerican women (P < 0.001). The same pattern of
results were shown when either FFMtotal or FFMtissue
(Figure 1), rather than body weight, were included as
covariates in the analysis (P < 0.001).
Five women in this study (four Caucasian, one
African-American) reported taking oral contracep-
Ethnicity and resting energy expenditure
JM Jakicic and RR Wing
Table 2 Comparison of age, weight, and body composition between overweight African-American and Caucasian women (mean
standard deviation) in 41 subjects achieving assessment criteria for REE and RQ
African-American (n ˆ 22)a
Age (y)
Weight (kg)
BMI (kg/m2)
BMD (g/cm2)a
BMC (kg)a
FFM (kg) (tissue ‡ BMC)a
FFM (kg) (tissue only)a
Fat mass (kg)a
Percent body fat (FFM ˆ tissue ‡ BMC)a
Percent body fat (FFM ˆ tissue only)a
Dietary recall
Total intake (kJ/d)
Carbohydrates (g/d)
Fat (g/d)
Protein (g/d)
Physical activity (kJ/week)
Caucasian (n ˆ19)
P-value
36.4 5.7
88.7 15.0
32.6 5.4
1.3 0.1
2.7 0.3
50.1 4.4
46.4 4.2
36.3 9.9
41.4 5.5
42.7 5.5
35.4 5.7
84.4 10.9
31.3 3.4
1.2 0.1
2.5 0.3
48.2 4.3
45.7 4.1
35.1 8.5
41.6 5.5
42.9 5.6
0.58
0.31
0.37
0.03
0.12
0.18
0.20
0.68
0.90
0.90
8669 4684
252 137
83 59
81 40
4412 4303
6852 2943
200 111
65 30
63 19
6672 5701
0.16
0.21
0.24
0.09
0.25
a
Body composition values were not obtained on one individual due to weight limitations of the dual energy x-ray absorptiometry
(DEXA), thus the n for those variables equals 21.
Table 3 Analysis of covariance assessing resting energy expenditure (REE) between overweight
African-American and Caucasian women controlling for weight and fat-free mass (FFM) (adjusted
means standard deviation)
Unadjusted REE kJ/d
(kcal/d)
REE adjusted for weight kJ/d
(kcal/d)
REE adjusted for FFMtotal kJ/d
(kcal/d)
REE adjusting for FFMtissue kJ/d
(kcal/d)
African-American (n ˆ 22)a
Caucasian (n ˆ19)
7279 825
(1739 197)
7192 825
(1718 197)
7133 825
(1704 197)
7346 825
(1705 197)
7807 854
(1865 204)
7903 854
(1888 204)
7912 854
(1890 204)
8108 854
(1889 204)
P-value
0.051
<0.001
<0.001
<0.001
FFMtotal ˆ tissue fat-free mass plus bone mineral content; FFMtissue ˆ total fat-free mass minus bone
mineral content.
a
indicates that n ˆ 21 when REE adjusted for FFMtotal and FFMtissue.
tives. Therefore, the data were reanalyzed excluding
these ®ve subjects. Results showed that REE for
Caucasians was 7803 745 kJ/d (1864 178 kcal/d)
and 7317 825 kJ/d (1748 197 kcal/d) for AfricanAmericans (P < 0.08). After adjusting for body
weight, FFMtotal, or FFMtissue, REE was 674 kJ/d
(161 kcal/d), 737 kJ/d (176 kcal/d), and 720 kJ/d
(172 kcal/d) lower in African-American women,
respectively (P < 0.005).
Women were separated into three groups based on
the number of days which had elapsed since their last
menstrual cycle at the time that they were assessed.
This was based on self-report and these groups were
as follows: 1) no longer experiencing a normal menstrual cycle, 2) within 1±13 days of their last menstrual cycle, or 3) within 14±28 days of their last
menstrual cycle. A similar grouping was used by
Westrate.20 Results showed no difference in REE
between the three groups when analyzed separately
for Caucasians and African-Americans. REE for Caucasians in the three groups was 7912 578 kJ
(1890 138 kcal), 7962 1231 kJ (1902 294 kcal),
and 7531 578 kJ (1799 138 kcal), respectively
(P > 0.10). For African-Americans in the three
Figure 1 Relationship between resting energy expenditure
(REE) and fat-free mass (FFM) (tissue only) for Caucasian
(n ˆ 19) and African-American (n ˆ 21) women.
239
Ethnicity and resting energy expenditure
JM Jakicic and RR Wing
240
groups, REE was 7397 938 kJ (1767 224 kcal),
7480 1059 kJ (1787 253 kcal), and 7091 628 kJ
(1694 150 kcal), respectively (P > 0.10).
RQ was not signi®cantly lower in African-American
women (0.72 0.02) compared to Caucasian women
(0.73 0.03), indicating no difference in substrate
utilization rates under resting conditions. There were
no differences in RQ between the two groups after
reanalyzing the data using only those women not
taking oral contraceptives. Further, there was no effect
of menstrual cycle phase on resting RQ in either the
Caucasian or African-American women (data not
shown).
Discussion
Evidence suggests that metabolic differences may
exist between African-Americans and Caucasians
that may contribute to differences in the development
of obesity in African-American women. The results of
this study showed that there are differences in REE,
with REE being signi®cantly lower in African-American women compared to Caucasian women, and this
supports the ®ndings of other investigators.8,9 The
magnitude of this difference in REE for the current
study was approximately 506 kJ/d (120 kcal/d), which
appears to be similar to the results shown by others.
Chitwood et al 9 reported a difference in REE of
753 kJ/d (180 kcal/d) in lean women, whereas Foster
et al 8 reported a difference of 393 kJ/d (94 kcal/d) in
overweight adults.
The results of this study showed that this difference
in REE remained signi®cant even after correcting for
both body weight and lean body mass (Table 3 and
Figure 1). This further supports the ®ndings of both
Chitwood et al 9 and Foster et al.8 However, both
Chitwood et al 9 and Foster et al 8 estimated lean body
mass using hydrostatic weighing, which did not allow
them to correct for potential differences in BMC and
BMD that exist between the two ethnic groups. The
current study used DEXA and results showed that
BMC was 0.2 kg higher in African-American women
(P ˆ 0.12). Therefore, a strength of this study is the
ability to examine the relationship between REE and
FFMtissue after correcting for this potential difference
in BMC. A second advantage to using DEXA is the
ease of use compared to other methods such as
hydrostatic weighing, and this may contribute to a
reliable estimate of body composition. In fact, testretest using DEXA to assess body composition in our
laboratory has shown a mean difference of
0.23 0.26% for percent body fat, 0.26 0.18 kg for
fat mass, 0.12 0.10 kg for lean body mass, and
0.02 0.02 kg for BMC.
Despite the advantages of using DEXA to assess
body composition, this methodology is not without
limitations. For example, both Kohrt21 and Roubenoff
et al22 have suggested that there are factors which can
affect the accuracy of DEXA when assessing soft
tissue, one of which is hydration status. We did not
conduct a clinical examination of these subjects,
however none of the subjects in this study reported
taking medications that would affect hydration or ¯uid
balance (for example diuretics), nor did they indicate
the presence of edema. Additional limitations include
the cost and availability of this technology. A recent
study conducted in our laboratory suggested that bioelectrical impedance analysis (BIA) may provide
similar body composition data compared to DEXA
in an obese sample of Caucasian and African-American women when the appropriate population prediction equation is used to estimate FFM.23 Therefore, it
may be possible to use a lower cost, more readily
available technology such as BIA to estimate FFM,
and this can be used to provide an accurate adjustment
of REE.
The ®nding that REE remains signi®cantly lower in
African-America women after correcting for the
potential difference in BMC would suggest that the
FFM of African-Americans is less metabolically
active compared to Caucasians (Figure 1). The data
presented in Table 3 shows that the difference in REE
increased from approximately 500 kJ/d to 800 kJ/d
when adjusted for either body weight, FFMtotal, or
FFMtissue. This may provide a potential physiological
mechanism to explain the difference in REE shown in
this study, which could impact on weight regulation
and contribute to the obese state in these individuals.
However, because of the cross-sectional nature of
these studies, the contribution that this lower REE
has to the development of obesity in the AfricanAmerican women cannot be determined. To determine
the effect of a lower REE on the development of
obesity in African-American compared to Caucasian
women, one would need to assume that caloric intake
and physical activity were equal in these two ethnic
groups. However, survey data has shown that patterns
of energy intake24 and physical activity5±7 are different in African-American women compared to Caucasian women. Therefore, because energy expenditure
and energy intake affect energy balance, the magnitude that each of these factors has on weight regulation may vary between individuals as well as
population groups.
There has been some evidence to suggest that
African-American women are less successful than
Caucasian women in weight loss programs.25±27
Data from this study suggest that a lower REE may
contribute to the poorer weight loss in African-Americans which has been shown by other investigators.
However, despite being statistically signi®cant, the
magnitude of the difference in REE is rather small,
suggesting that other factors may also contribute to
poorer weight regulation in African-American
women. For example, Wing and Anglin28 showed
that African-Americans reported smaller decreases in
calorie intake during the initial six months of treatment and had poorer attendance during months 6±12
Ethnicity and resting energy expenditure
JM Jakicic and RR Wing
than Caucasians, and this could have contributed to
poorer weight loss and faster weight regain in this
ethnic group. In addition, there may be other behavioral (for example, physical activity) and cultural
factors (for example, social support) that could affect
weight regulation in minority populations. Future
studies should examine the interaction between physiological, behavioral and cultural factors that may
explain the differences in both weight loss and weight
gain in these two ethnic groups.
The results published by Zurlo et al13 and Seidell et
14
al suggest that a low rate of fat oxidation, re¯ected
by a high RQ, could contribute to weight gain. Thus,
because of the high prevalence of obesity in adult
African-American women compared to adult Caucasian women, it could be hypothesized that AfricanAmerican women would have a higher RQ than
Caucasian women under resting conditions. The
results published by Chitwood et al9 would support
this hypothesis. However, the results of other studies8,10 showed no difference in RQ between with the
two ethnic groups. The results of the current study
also showed no signi®cant difference in resting RQ
between the two groups. To explain these differences
in results, one possible explanation may be differences
in measurement procedures. However, a variety of
other factors may contribute to the difference in
®ndings regarding RQ. For example, studies showing
no difference in RQ between the ethnic groups examined subjects that were older (mean age > 35 y) and
heavier (mean BMI > 30 kg/m2) compared to those
subjects in the Chitwood et al9 study, and this may
have in¯uenced the results. Whether the difference in
RQ which exists in younger, normal weight women9
contributes to the development of obesity should be
examined further.
Despite the results of this study being similar to
result shown by others,8±10 the current study is not
without limitations. The subjects in this study reported
to the laboratory the morning of the assessment of
REE, and this did not allow for maximum control over
factors that could potentially affect REE such as food
intake, physical activity and sleep. Berke et al29
showed that the REE is affected by the pretest
environment and the REE is elevated when measured
under outpatient conditions compared to inpatient
conditions. A second limitation may be the lack of
control related to the phase of the menstrual cycle
during which REE was assessed. The results of this
study showed that REE did not differ between women
categorized according to self-reported days since the
®rst day of their current menstrual cycle, and
Westrate20 showed similar results. However, previous
studies have shown that REE may differ from 5±10%
between the luteal and follicular phases of the menstrual cycle.30,31 Therefore, future studies should consider factors related to pretest environment and
menstrual cycle when examining REE.
In summary, this study showed that REE is signi®cantly lower in overweight African-American
women compared to Caucasians, and this difference
remains signi®cant after correcting for both body
weight and lean body mass. These results suggest
that differences in REE may contribute to differences
in weight regulation and could potentially contribute
to an increase in the prevalence rates of obesity in
African-Americans. Furthermore, the results from this
study indicate that African-American and Caucasian
women had similar patterns of substrate oxidation
when expressed by the resting RQ. Future research
should focus on the interaction of REE and RQ with
other physiological, behavioral, and cultural factors to
assess their in¯uence on the development and treatment of obesity in minority populations.
Acknowledgments
This study was supported by the National Institutes of
Health with awards to Dr Wing (DK29757) and Dr
Jakicic (HL561227), and the Obesity/Nutrition
Research Center at the University of Pittsburgh
(DK46204). The authors would like to thank Carena
Winters, MS, Kim Petrovich, RN and Gwendolyn
Chancellor for assisting with the collection of data
for this project.
References
1 Kuczmarski RJ, Flegal KM, Campbell SM, Johnson CL.
Increasing prevalence of overweight among US adults: the
National Health and Nutrition Examination Surveys, 1960 to
1991. JAMA 1994; 272: 205±211.
2 Kumanyika SK. Obesity in minority populations: an epidemiological assessment. Obes Res 1994; 2: 166±182.
3 Kumanyika SK. Special issues regarding obesity in minority
populations. Ann Intern Med 1993; 119(7 : 2): 650±654.
4 Striegel-Moore RH, Wil¯ey DE, Caldwell MB, Needham ML,
Brownell KD. Weight-related attitudes and behaviors of
women who diet to lose weight: a comparison of black dieters
and white dieters. Obes Res 1996; 4: 109±116.
5 Kushner RF, Racette SB, Neil K, Schoeller DA. Measurement
of physical activity among black and white obese women.
Obes Res 1995; 3(Suppl 2): 261s±265s.
6 Myers HF, Kagawa-Singer M, Kumanyika SK, Lex BW,
Markides KS. Panel III: Behavioral risk factors related to
chronic diseases in ethnic minorities. Health Psychology 1995;
14: 613±621.
7 Bild DE, Jacobs DR, Sidneys S, Haskell WL, Anderssen N,
Oberman A. Physical activity in young black and white
women: the CARDIA study. Ann Epidemiol 1993; 3: 636±644.
8 Foster GD, Wadden TA, Vogt RA. Resting energy expenditure
in obese african-american and caucasian women. Obes Res
1997; 5: 1±8.
9 Chitwood LF, Brown SP, Lundy MJ, Dupper MA. Metabolic
propensity toward obesity in black vs white females: responses
during rest, exercise and recovery. Int J Obes 1996; 20: 455±462.
10 Nicklas BJ, Toth MJ, Goldberg AP, Poehlman ET. Racial
differences in plasma leptin concentrations in obese premenopausal women. J Clin Endocrinol Metab 1997; 82: 315±317.
11 Liel Y, Edwards J, Shary J, Spicer KM, Gordon L, Bell NH.
The effects of race and body habitus on bone mineral density
of the radius, hip, and spine in premenopausal women. J Clin
Endocrinol Metab 1988; 6: 1247±1250.
12 Perry HM, Horowitx M, Morley JE, Fleming S, Jensen J,
Caccione P, Miller DK, Kaiser FE, Sundarum M. Aging and
bone metabolism in african-american and caucasian women. J
Clin Endocrinol Metab 1996; 1108±1117.
241
Ethnicity and resting energy expenditure
JM Jakicic and RR Wing
242
13 Zurlo F, Lilloija S, Puente A, Nyomba BL, Raz I, Saad MF,
Swinburn BA, Knowler WC, Bogardus C, Ravussin E.
Low ratio of fat to carbohydrate oxidation as predictor of
weight gain: study of 24-h RQ. Am J Physiol 1991; 259:
E650±E657.
14 Seidell JC, Muller DC, Sorkin JD, Andres R. Fasting respiratory exchange ratio and resting metabolic rate as predictors of
weight gain: the Baltimore longitudinal study on aging. Int J
Obes 1992; 16: 667±674.
15 Branson RD. The measurement of energy expenditure: instrumentation, practical considerations, and clinical application.
Respiratory Care 1990; 35: 640±656.
16 Takala J, Keinanen O, Vaisanen P, Kari A. Measurement
of gas exchange in intensive care: laboratory and clinical
evaluation of a new device. Crit Care Med 1989; 17: 1041±
1047.
17 Block G, Hartman AM, Dresser CM, Carroll MD. A databased approach to diet questionnaire design and testing. Am J
Epidemiol 1986; 124: 151±160.
18 Paffenbarger RS, Hyde RT, Wing AL, Chung-cheng H.
Physical activity, all-cause mortality, and longevity of college
alumni. N Engl J Med 1986; 314: 605±613.
19 Paffenbarger RS, Wing AL, Hyde RT. Physical activity as an
index of heart attack risk in college alumni. Am J Epidemiol
1978; 108: 161±175.
20 Westrate JA. Resting metabolic rate and diet-induced thermogenesis: a methodological reappraisal. Am J Clin Nutr 1993;
58: 592±601.
21 Kohrt WM. Body composition by DXA: tried and true? Med
Sci Sports Exerc 1995; 27: 1349±1353.
22 Roubenoff R, Kehayias JJ, Dawson-Hughes B, Heyms®eld S.
Use of dual-energy x-ray absorptiometry in body-composition
23
24
25
26
27
28
29
30
31
studies: not yet a `gold standard'. Am J Clin Nutr 1993; 58:
589±591.
Meier AD, Jakicic JM, Wing RR. Comparison of body
composition measured by dual energy x-ray absorptiometry
and bioelectrical impedance in obese females (abstract). Med
Sci Sports Exerc 1997; 29 (Suppl 5): S186.
Norris J, Harnack L, Pouane T, Wakimoto P, Block G.
US trends in nutrient intake: the 1987 and 1992 National
Health Interview Surveys. Am J Public Health 1997; 87: 740±
746.
Kumanyika SK, Obarzanek E, Stevens VJ, Herbert PR, Whelton PK. Weight-loss experience of black and white participants in NHLBI-sponsored clinical trials. Am J Clin Nutr
1991; 53: 1631±138.
Yanovski SZ, Gormally JF, Leser MS, Gwirtsman HE,
Yanovski JA. Binge eating disorder affects outcome of comprehensive very-low-calorie diet treatment. Obes Res 1994; 2:
205±212.
Darga LL, Holden JH, Olson SM, Lucas CP. Comparison of
cardiovascular risk factors in obese blacks and whites. Obes
Res 1994; 2: 239±245.
Wing RR, Anglin K. Effectiveness of a behavioral weight
control program for blacks and whites with NIDDM. Diabetes
Care 1996; 19: 409±413.
Berke EM, Gardner AW, Goran MI, Poehlman ET. Resting
metabolic rate and the in¯uence of the pretesting environment.
Am J Clin Nutr 1992; 55: 626±629.
Solomon SJ, Kurzer MS, Calloway DH. Menstrual cycle and
basal metabolic rate in women. Am J Clin Nutr 1982; 36: 611±
616.
Webb P. 24-hour energy expenditure and the menstrual cycle.
Am J Clin Nutr 1986; 44: 614±619.