body composition, resting metabolic rate, and energy ... · increase in fat-free mass (ffm). values...
TRANSCRIPT
406 A�ii J (‘Ii,, Niar 1997:66:406-12. Printed in USA. U 1997 American Society f�r Clinical Nutrition
Body composition, resting metabolic rate, and energyrequirements of short- and normal-stature, low-incomeGuatemalan children13
Renee E Wren, Heidi B/nine. A’fanolo fts’fazariegos. Noel So/onions, Jose 0 Alvarez. (111(1 ?vfi(’hael I Goran
ABSTRACT We examined body composition using bioelec-
tnical impedance analysis and isotope dilution ( 80 and 2H). rest-
ing metabolic rate (RMR) by indirect calorimetry. and total energy
expenditure (TEE) by doubly labeled water in 15 short-stature
(height-for-age � - I .5 SD) and I 5 normal-stature (height-for-
age > - I .5 SD) Guatemalan children aged 4-6 y. Although. in
absolute tennis significant group differences were found in fat-free
mass (FFM). fat mass, and total body water (TBW). there were no
significant differences in fat mass and TBW after adjustment for
FFM. RMR of the short-stature children (3791 ± 376 kJ/d) was
not significantly different from that of normal-stature children
(4038 ± 53 1 kJ/d), and the regression between RMR and FFM was
also not significantly different between groups. TEE was not
significantly ditTerent in short-stature (4753 ± 761 kJ/d) compared
with normal-stature children (53()4 ± 1020 kJ/d): the regression
between TEE and FFM was not significantly different between the
two groups. There were no significant group differences in RMR
and TEE after adjustment for FFM. FFM was the strongest pre-
dictor of TEE, but could only explain 29% of the variance. We
conclude that 1) the lower TBW and fat mass in the short-stature
group is proportional to their lower FFM, 2) there is no significant
difference in either RMR or TEE between short- and normal-
stature children. and 3) TEE is highly variable among these chil-
dren and cannot be explained by differences in body size alone.
Am J Cliii Nuir 1997:66:406-I 2.
KEY WORDS Resting metabolic rate, energy expenditure.
body composition. total body water, stunting. Guatemala, chil-
dren, bioelectrical impedance analysis. indirect calorimetry.
doubly labeled water
INTRODUCTION
Linear growth retardation, or stunting. refers to a deficit in
attained length or height compared with maximal genetic
growth potential as reflected by international standards: it is
widely regarded as an index of poverty and malnutrition ( I . 2).
In many developing countries. � 30% of children < S y of age
may be stunted (3). In the Americas, Guatemala consistently
has one of the highest prevalences of stunting. reaching as high
as 70% (4). It is often assumed that stunted children have
adapted to lower food availability and increased episodes of
infection by changes in their body composition and a reduction
(if energy expenditure (2. 5). Despite this general perception.
only limited data on body composition amid energy expenditure
of children of short stature are available.
Evidence for a potentially adaptive change in body compo-
sition with reduced linear growth comes from a study of
Peruvian children. Boutton et al (6) found that low-income
children of the peniurban settlements of Lima had short stature
in association with high weight-for-height. This additional
weight was not due to increased adiposity. hut rather to an
increase in fat-free mass (FFM). Values for total body water
(TBW) as a percentage of body weight were relatively high in
comparison with normal children, averaging 67.4 ± 6.4%. The
hydration of the fat-free component of these children appeared
to be 82.7% on average.
Insights into energy metabolism and short stature come from
a recent study in Jamaica by Soares-Wynter and Walker (7).
Resting metabolic rate (RMR) in 34 stunted children aged 7-8
y [I 125 ± 136 kcal/d (4702 ± 570 kJ/d)J was significantly
lower than RMR for age-matched control children [I 388 ± 147
kcal/d (5802 ± 616 kJ/d)] and height-matched control children
I I 26 1 ± I 59 kcal/d (5269 ± 663 kJ/d)l of a younger age.
However. after group differences in FFM were adjusted for,
there were no differences in RMR between the stunted and
age-matched control subjects, suggesting that the difference in
RMR could be explained by the difference in FFM.
In the present study. we combined bioelectrical impedance
analysis and isotope dilution (t80 and 2H) techniques to exam-
me differences in body composition. In addition, we assessed
RMR by indirect calorimetry and total energy expenditure
(TEE) under free-living conditions using the doubly labeled
water technique. On the basis of the concept that daily energy
intake should be equivalent to total daily energy expenditure to
I From the Division of Physiology and Metabolism, Department of
Nutrition Sciences and the Department of International Health, School of
Public Health, University of Alabama at Birmingham, and the Center for
Studies of Sensory Impairment. Aging and Metabolism (CeSSIAM). Hos-
pital de Ojos y Oldos, Dr Rodolfo Robles V. Guatemala City. Guatemala.
2 Supported by the tiniversity of Alabama at Birmingham iohn J Spark-
man Center f�r International Public Health Education. MIG is supported by
the National Institute of Child Health and Human Development (R29
HD-32668.
C Address reprint requests to MI Goran. Division of Physiology and
Metabolism. Departmemit of Nutrition Sciences. University of Alabama atBirniinghani. Bimiiiigham. AL 35294-336(). E-mail: [email protected].
Received October 2. 1996.
Accepted for publication March 18. 1997.
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ENERGY METABOLISM IN GUATEMALAN CHILDREN 407
maintain energy balance. measurement of TEE by doubly la-
beled water provides a proxy indicator for the energy intake
required to maintain body energy stores. ie. energy require-
ments. Our objectives were to compare body composition. with
particular emphasis on TBW, and energy expenditure compo-
nents. namely. RMR and TEE of the shorter and taller children
from an underprivileged population of 4-6-y olds living in the
same poor. marginal urban community.
SUBJECTS AND METHODS
Study population
The study was conducted at a daycare center/school in a poor
community of Guatemala. Thirty children ( I 5 of short stature.
1 5 of normal stature) were selected from the population of
4-6-y olds enrolled at the facility. They were chosen as the
polar extremes of height from the base population. A short-
stature child was defined as having a height-for-age Z
score < - I .50 relative to National Center for Health Statistics
(NCHS) standards derived in US children (8). There was a
roughly equal number of girls and boys in the groups. The
children were not underweight as defined by weight-for-height
z scores.
The experimental protocol was approved by the Institutional
Review Board for Human Use of the University of Alabama at
Birmingham and by the Committee on Human Subjects of the
Center for Studies of Sensory Impairment. Aging and Metab-
olism in Guatemala City. Parents provided informed consent
after the nature and purpose of the study had been explained.
The doubly labeled water method
TEE was measured for 7 d under free-living conditions by
using the doubly labeled water technique. A sample of urine
was collected from each subject before isotope administration
to determine baseline concentrations of iS0 and 2H. Each
subject was given an oral dose of a mixture containing �0. 15
g �O and 0. 1 2 g 2H20/kg body wt. The container was then
rinsed with 2()-3() mL tap water that was also consumed. Two
timed urine samples were collected the day after dosing and an
additional two timed samples were collected �7 d after dosing.
Ten-milliliter aliquots of each urine sample were stored frozen
until isotopic analysis. Urine samples were analyzed in tnipli-
cate by isotope ratio-mass spectrometry (Fisons-VG Optima:
Energy Metabolism Research Unit, University of Alabama at
Birmingham) as described previously (9). Equation R2 of
Speakman et al ( 10) was used to derive carbon dioxide pro-
duction rate with use of the group mean ratio of 2H to SO
dilution space. which was I .045 ± 0.()4 in these 30 children
(there was no significant difference between short- and normal-
stature groups). Carbon dioxide production rate was converted
to energy expenditure with use of equation I 2 of de Weir ( 1 1)
and the mean value for the food quotient of the children’s diet
(0.93 ± 0.01. range: 0.92-0.95).
The food quotient was calculated from the relative macro-
nutrient composition of the children’s diet by using the equa-
tions of Black et al ( 12). Because the majority of the children’s
dietary intake was consumed while in school. five children
were observed while they ate and the weights of the meals
served and the leftovers were measured. Data on breakfast at
home (if consumed at all) was obtained from interviewing the
children. parents. and in several cases by observing what was
brought to school. The dietary intake of carbohydrate. protein.
and fat was obtained from the Central American food-compo-
sition tables (13). Dietary intake at dinner was not included
because dinner at home is very light (mostly carbohydrate) and
is similar to breakfast. Therefore, for the purpose of estimating
the food quotient. dietary intake at dinner was excluded. The
macronutrient composition of the children’s diet was 70.5%
carbohydrate. I 3.4% protein. and I 6.2% fat.
Indirect calorimetry
RMR was measured by using a portable Deltatrac II Meta-
bolic Monitor (SensorMedics, Yorba Linda. CA) that was
calibrated before each test against standard reference gases.
Subjects were acclimated to the monitor and the procedure was
explained the day before their first scheduled test: a notice was
sent home with each subject that instructed parents to bring
their children to school in the fasted condition the following
morning. An adult-size, transparent, plastic hood was used to
collect the expired air for 15 mm after a 5-mm equilibration
period. During the testing. subjects were instructed to lie still
and were allowed to watch carto�ins on a local television
station.In 26 of 30 children. the RMR was repeated on two separate
occasions within a 4-wk period. There was a highly significant
correlation between the RMR of the first and second tests (r =
0.87. P < 0.0()l ), showing excellent testing reliability. An
individual’s RMR value was expressed as the average of two
measurements when duplicate tests were available.
Physical activity energy expenditure
Activity energy expenditure was estimated from the differ-
ence between TEE and RMR. Because RMR was measured
under fasting conditions. the thermic effect of food as well as
energy from physical exertion were included in the activity
energy expenditure term.
Body composition
Anthropometnic and bioelectrical impedance measurements
were performed at the school and all measurements were made
by the same investigator (HB). The children were weighed on
a model 8435 digital, platform balance (Cardinal Detecto.
Webb City. MO) while barefoot and wearing light clothing.
Skinfold thicknesses for the triceps, biceps. subscapular. and
suprailiac sites were measured in duplicate to the nearest I mm
with a Lange (Lange. Cambridge. MD) skinfold caliper for the
calculation of the sum of four skinfolds. Midupper arm cm-
cumference (MUAC) was measured with a metallic tape mea-
sure to the nearest I mm on the right arm. Whole-body resis-
tance at 50 kHz was measured by using a Xitron 4(XX)B
multifrequency analyzer (Xitron Technologies. Inc. San Diego)
with the tetrapolar electrode placement.
TBW was calculated from the average of the SO and 2H
isotope dilution spaces as described previously (14. 15). Zero-
time enrichments of H2150 and 2H20 were calculated by back
extrapolation of the semiloganithmic plot of isotope enrichment
in urine versus time after dosing to time 0. and the dilution
spaces of SO and 2H were calculated according to the equa-
tions of Coward (16). To correct for isotope exchange into
nonaqueous compounds. the SO dilution space was divided by
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408 WREN ET AL
TABLE I
General characteristics of short- and miormal-stature Guatemalan
children’
All children Short stature Normal stature(nl5M,15F)(,:7M.8F)(n8M,7F)
Age (y) 5.4 ± 0.8 5.5 ± 0.9 5.3 ± 0.7
Height (cni) 106 ± 6.4 103 ± 4.6 1 10 ± 6.12
Sitting height (cmii) 59.9 ± 3.1 58.1 ± 2.0 61.7 ± 3.0’
Weight (kg) 17.8 ± 2.3 16.7 ± 1.5 19.0 ± 2.6�
Height-for-age
z score - I .29 ± I . I I - 2.22 � I .48 -0.36 ± 0.67�
Weight-for-height
z score 0.21 ± 0.64 0.21 ± 0.52 0.21 ± 0.76
‘ .t ± SD.2 4 Significantly different from short-stature group (ANOVA):
2 p 0.002. � P < 0(8)5, � P = 0(8)6.
1.01 and the 2H dilution space by 1.04 (17). TBW was esti-
mated from the mean of the 2H + SO derived estimates for
TBW.
Weight-for-height and height-for-age Z scores were calcu-
lated in relation to the median of the reference population of the
NCHS. Fat mass was calculated from skinfold thicknesses and
height2/resistance by using the equation of Goran et al ( 18)
derived from data on white children using dual-energy X-ray
absorptiometry as a standard. FFM was calculated from the
difference between body weight and fat mass.
Statistical analysis
The data are expressed as means ± SDs unless stated oth-
erwise. Pearson correlation coefficients were used to derive the
level of association between pairs of variables. One-way anal-
ysis of variance was used to examine the differences between
group means. The difference between slopes and intercepts of
separate regression equations within each subgroup were ex-
amined by use of t tests and analysis of covaniance to test for
homogeneity of regression slopes. The level of statistical sig-
nificance was set at P � 0.05 for all tests. All statistical and
data manipulations were performed on a personal computer by
using either QUATTRO PRO 6.02 (Corel Corporation. Farm-
ingdale, NY), the Statistical Analysis System 6.10 (SAS: SAS
Institute, Cary. NC) for Microsoft Windows (Microsoft, Inc.
Redmond, WA), or SIGMAPLOT 2.01 (Jandel Corporation,
San Rafael, CA) software packages.
RESULTS
General characteristics
The general characteristics of the children. including height.
weight. sitting height, and Z scores are given in Table 1. The
children were not underweight as a group. with a mean weight-
for-height Z score of 0.2 1 ± 0.64. The average height-for-age
z score for the short-stature group was -2.22 ± 1.48 (range:
- 3.66 to - I .66). The average height-for-age Z score for the
normal-stature group was -0.36 ± 0.67 (range: - I .33 to
1 .05). As expected, the differences in height, sitting height. and
height-for-age Z score were significant as was weight. which is
closely associated with height. There was no significant differ-
TABLE 2
Body-composition variables and indexes of short- and normal-stature
Guatemalan children determined by anthropometric measurements.
bioelectrical impedance analysis. and isotope dilution’
All children Short stature Normal stature
(,1 = IS M. 15 F)(n 7 M. 8 F)(n - 8 M, 7 F)
MUAC (mm) 17.7 ± 1.0 17.3 ± 0.6 18.0 ± 1.2
Skinfold thicknesses
(mm) 26.8 ± 6.4 26.0 ± 5.7 27.5 ± 7.2
Fat-free miiass(kg) 15.3 ± 1.9 14.5 ± 1.5 16.1 ± 1.92
Fat mass(kg) 2.6 ± 0.85 2.3 � 0.5 2.9 ± l.0�(C/i ofbody wt) 14.3 ± 3.7 13.6 � 3.2 14.9 ± 4.1
Total body water
(kg) 9.7 ± 1.4 9.1 ± 1.1 10.3 ± l.4�
(%) 54.3 ± 2.7 54.1 ± 2.6 54.6 ± 2.9
TBW:FFM 0.63 ± 0.03 0.63 ± 0.02 0.64 ± 0.03
‘ S � SD. MUAC. midupper arm circumference.24 Significantly different from short-stature group (ANOVA):
2 p 0.01. ‘ P = 0.()4, ‘ P = 0.008.
ence in age or weight-for-height (P = 0.60 and 0.98,
respectively).
Body composition
The means and SD for the various body-composition van-
ables and indexes are shown in Table 2 for the whole sample
and the two subgroups. In absolute terms, there was a signifi-
cant difference in FFM, fat mass, and TBW between the
groups. When TBW was expressed as a percentage of body
weight, there was no significant difference between the two
groups (P = 0.62). In addition, there was no significant dif-
fenence between the groups when fat mass was expressed as a
percentage of body weight (P = 0.34).
The linear-regression relation between TBW and body
weight is shown in Figure 1. The slopes and intercepts of the
separate regression equations, when compared by t test, were
not significantly different (Table 3). For both groups. 86% of
the variance in TBW was explained by weight. The association
of TBW and FFM is shown in Figure 1, with a highly signif-
icant correlation (r = 0.95, P < 0.005); similarly, the slopes
and intercepts of the regression equations were not signifi-
cantly different between groups (Table 3).
Energy expenditure
The means and SDs for the various energy expenditure
variables and indexes are shown in Table 4. Mean RMR in our
subjects was 3917 ± 468 kJ/d (937 ± 1 12 kcal/d), ranging
from 3323 to 5350 kJ/d (795 to 1280 kcal/d). Absolute RMR
was numerically higher in the normal-stature children at
4038 ± 53 1 kJ/d (966 ± I 27 kcal/d) than in the short-stature
children 13791 ± 376 kJ/d (907 ± 90 kcal/d)1, but this was not
significant (P = 0. 14). RMR was most strongly correlated with
FFM. weight, TBW, and height, in descending order (Table 5).
After separating the children into their respective subgroups.
the correlations remained significant in the normal-stature
group whereas only the associations of RMR with weight and
FFM were significant in the short-stature group. The scatter
plot of RMR versus FFM is presented individually for the two
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ci)cci
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F-
12 14 16 18 20 22 24 26
Weight (kg)
10 12 14 16 18 20 22
Fat-free mass (kg)
FIGURE 1. Regressiomi of total body water (TBW) on weight and on fat-free mass of short- and normal-stature children. Short-stature (solid hue. closed
circles): TBW = - 1.9 + 0.66 weight. r = 0.93, P < 0.005: TBW = -0.46 + 0.66 FFM, r = 0.95. P < 0.005. Normal-stature (dotted line, open circles:
TBW = 0.73 + 0.51 weight. r = 0.93. P < 0.005: B: TBW = - 1.1 1 + 0.71 FFM, r = 0.95. P < 0.005.
ENERGY METABOLISM IN GUATEMALAN CHILDREN 409
‘.i ± SEE.
15
14
13
12
11
10
9
8
7
6
groups in Figure 2. The slopes and intercepts of the regression
equations were not significantly different (Table 6).
Mean TEE for the entire sample was 5029 ± 928 kJ/d
(1203 ± 222 kcal/d), ranging from 3553 to 6145 kJ/d (850 to
1470 kcal/d) (Table 4). Although mean TEE was slightly
higher among the normal-stature children at 5304 ± 1020 kJ/d
(1269 ± 244kcal/d)comparedwith4753 ± 761 kJ/d(l137 ±
I 82 kcal/d) in the short-stature children, this difference was not
significant (P 0.10). As with RMR, TEE was significantly
correlated with the variables listed in Table 5, but with a lesser
strength of association than for RMR given the identical sam-
ple size.
The linear regression between TEE and FFM is shown in
Figure 3. The slopes and intercepts of the regression equations
were not significantly different (Table 6). When data from the
two groups were combined, the correlation became significant
(r 0.50, P 0.002), but only 25% of the variance in TEE
could be explained by FFM. The relation between TEE and
RMR was also not significantly different between groups, as
shown in Figure 3; although the regression lines for TEE versus
RMR for the respective groups provide the visual impression of
difference, comparison of the slopes and intercepts of the
respective regression equations showed no significant differ-
ences (Table 6).
DISCUSSION
In the present study, we examined both body composition
and energy expenditure in short- and normal-stature children
TABLE 3
15
14
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I- 8
7
6
from a poor community of a developing country. We fcund that
the smaller size of the short-stature group accounted for their
lower TBW and lower fat mass. RMR and TEE were not
significantly different between groups, especially after adjust-
ment for the difference in FFM. In addition, TEE was highly
variable and could not be explained by differences in body size
alone.
The first objective of this study was to examine the body
composition of short- and normal-stature Guatemalan children,
with particular emphasis on TBW. We also wanted to compare
our measurements of short-stature Guatemalan children with
others, including the short-stature Peruvian children studied by
Boutton et al (6). As a percentage of body weight. the average
TBW measurement of the Guatemalan children was 54.3 ±
2.7% with no significant difference between the short-stature
and normal-stature groups. This value is slightly lower than the
value of 58% that we measured previously in 4-6-y-old chil-
dren from Vermont and Arizona in the United States (19).
Other published values include those of Friis-Hansen et al (20).
who showed that, beyond 6 mo of age. TBW varied between
53% and 63% of body weight, and Cheek et al (21 ) found an
average TBW of 61 .8% of body weight in 40 normal children
aged 4-17 y. Similar results were obtained by Flynn et al (22)
and Fomon et al (23). These values for Guatemalan and North
American children are considerably lower than those found
previously in short-stature Peruvian children in whom TBW
represents 67.4 ± 6.4% of body weight (6). In summary, a
comparative analysis of reported data suggest that there is
variation in the level of hydration of body mass with apparently
Comparison of slopes and intercepts from regression equations that predict total body water of short- and normal-stature Guatemalan children’
Slope Intercept
Short Normal P Short Normal P
kg/kg kg
Total body water (kg) versusWeight (kg) 0.66 ± 0.1 0.51 ± 0.1 0.15 -1.90 ± 1.2 0.73 ± 1.1 0.14Fat-free mass (kg) 0.66 ± 0.1 0.71 ± 0.1 0.56 -0.46 ± 0.9 - 1.1 1 � 1.0 0.64
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‘ .f :t SD. RMR. resting metabolic rate: TEE. total energy expenditure:
AEE. activity emiergy expenditure. There were no significant differences
between groups.
10 12 14 16 18 20 22
Fat-free mass (kg)
TABLE 5
410 WREN ET AL
TABLE 4Energy expenditure variables and indexes of short- and normal-stature
Guatemalami children by indirect calorimetry and doubly labeled water’
All children Short stature Normal stature
(‘S 15 M. 15 F) (a = 7 M. 8 F) (a 8 M. 7 F)
Respiratory quotient 0.97 ± 0.05 0.99 ± 0.()4 0.96 ± 0.05
RMR (kJ/d) 3917 ± 468 3791 ± 376 4038 ± 531
TEE (kJId) 5029 ± 928 4753 ± 761 53()4 ± 1020
AEE (kJ/d) I l()4 ± 803 957 ± 769 1250 ± 832
TEE:RMR 1.28 ± 0.21 1.26 � 0.22 1.31 ± 0.20
less hydration in Guatemalan children (�54%), and greater
hydration in Peruvian children (�67%), compared with North
American children (�58%). Further studies are warranted to
examine the sources and explanation of these differences.
We also examined the hydration of the fat-free component in
the Guatenialan children by regressing TBW on FFM for both
the short- and normal-stature groups. These regressions pro-
duced equations with slopes of 0.66 and 0.7 1 . respectively.
Because the intercepts from these regressions were not signif-
icantly different from zero. the observed slopes are equivalent
to the proportion of water in FFM. ie. 66% and 71%. These
values are much lower than the estimated 82.7% obtained in
Peru and are also lower than 75. 1 % for white male and 76.0%
for white female prepubescent children of normal stature stud-
ied by Boileau et al (24). Therefore. the phenomenon of in-
creased weight-for-height due to increased hydration of FFM in
association with short stature that was observed previously in
Peruvian children was not found in our population of Guate-
malan children.
Other body-composition variables in our study. when exam-
med as a percentage of body weight. did not show a significant
difference between the short- and normal-stature children. Per-
centage body fat in the short-stature Guatemalan children
(13.6 ± 3.2%) was higher than the 9.4 ± 3.0% obtained in Peru
(6). but lower than the 17.7 ± 3.0% obtained in stunted
Jamaican children (7). Well-nourished children 6-6() mo of age
generally have 15-30% fat (23). Therefore, the short-stature
FIGURE 2. Regression of resting metabolic rate (RMR) on fat-free
mass (FFM) of short- and normal-stature children. Short-stature (solid line.
closed circles): RMR = 391.2 + 35.68 FFM, r = 0.62. P = 0.02:
n(innal-stature (dotted line, open circles): RMR = -21.8 + 61.42 FFM.
r 0.89. P < 0(8)5: combined (ii 30): RMR 201.7 + 48.13 FFM.
r 0.80, P < 0.18)5.
Guatemalan children were, at best, at the low end of the normal
range of fat mass.
Because of the small sample size and negative findings, we
also analyzed the data using a multiple-regression approach
using a dummy variable for the two groups, and examining the
influence of stature on body composition and energy expendi-
ture as a continuous variable. Our major findings were verified
with these approaches. In addition, the negative findings and
low sample size warrant a consideration of power issues. Thus,
for example. although absolute TBW was significantly lower in
short-stature children (Table 2). there was no significant dif-
ference after FFM was adjusted for (Table 3). The small,
nonsignificant difference in TBW after adjustment for FFM
(9.84 ± 0.40 kg compared with 10.17 ± 0.40 kg) is equivalent
to an effect size of �0.4; our power calculations estimate that
a total sample size of 50 children would be required to detect
this small 3% difference as significant with a power of 0.8.
The second objective of this study was to examine energyexpenditure components in short- and normal-stature children.
Pearson correlation coeflicients (r) between resting nietabolic rate (RMR). total energy expenditure (TEE). and selected variables’
Al(0=
I children15M.15F)
Short stature(n=7M.8F)
Normal stature(n=8M,7F)
RMR
Weight (kg) 0.78’ 0.57’ 0.86’
Height (ciii ) 0.59’ 0.4 1 0.63’
Fat-free mass (kg) 0.80’ 0.62’ 0.89’
Total body water (kg) 0.72’ 0.45 0.82’
TEEWeight (kg) 0.5 I ‘ 0.57’ 0.39
Height (ciii I 0.50’ 0.50 0.38
Fat-free mass (kg) 0.54’ 0.50 0.46
Total body water (kg) 0.54’ 0.57’ 0.42
Resting metabolic rate (ki/d) 0.50’ 0.23 0.58’
‘ P � 0.05.
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Resting metabolic rate (kJ/d)
FIGURE 3. Regression of total energy expenditure (TEE) on fat-free mass (FFM) and on resting metabolic rate (RMR) of short- and normal-stature
children. Short-stature (solid line, closed circles): TEE = 267.8 + 60.14 FFM. r = 0.50, P = 0.06: TEE = 746.7 + 0.43 RMR. r = 0.23. P = 0.45.
Noniial-stature (dotted line. open circles): TEE = 290.8 + 60.77 FFM. r = 0.46, P = 0.08: TEE = 169.5 + 1.14 RMR. r = 0.58. P = 0.02. Combined
(F? = 30): TEE 217 + 64.51 FFM. r 0.54. P 0.002: TEE 268.0 + 0.998 RMR. r 0.50. P 0(8)5.
Fat-free mass (kg)
ENERGY METABOLISM IN GUATEMALAN CHILDREN 411
TABLE 6
Comparison of slopes and intercepts from regression equations that predict resting metabolic rate (RMR) and total emiergy expenditure (TEE) of short-
and noriiial-staturc Guatcnialan children’
Slope Intercept
Short Normal P Short Normal P
ki ‘ �i ‘ . kg ‘ . kJ/dRMR (kJ/d) versus FFM (kg) 36 ± 13 61 ± 8 0.10 391 ± 190 -22 � 137 0.09
TEE (ki/d) versus
FFM (kg) 60 ± 29 61 ± 3 0.99 268 ± 419 291 ± 526 0.99
RMR (kJ/d) 0.43 ± 0.55 1.14 � 0.43 0.33 747 ± 502 170 ± 420 0.33
‘ I ± SEE. FFM. fat-free mass.
Stunting is assumed to result in smaller individuals with ne-
duced daily energy requirements. We showed that in this group
of short-stature Guatemalan children, RMR and TEE were not
significantly different from those observed in their normal-
stature counterparts. especially after the small differences in
body composition were adjusted for. The small difference in
absolute TEE (10%) and RMR (6%) between short- and nor-
mal-statune children (Table 4) is equivalent to an effect size of
“�0.3: our power calculations estimate that a total sample size
of 80 children would be required to detect these small differ-
ences in energy expenditure as significant with a power of 0.8.
Looking at the difference in TEE adjusted for RMR, the
difference is reduced to an 8% lower value in short-stature
children. and power calculations show that a total sample size
of I 30 children would be required to show this difference as
significant with a power of 0.8.
Absolute RMR of the short-stature children tended to be
lower, but was not significantly lower than that of normal-
stature children. However, after adjustment for differences in
FFM. generally considered one of the most accurate predictors
of RMR in children (25), the two groups were not significantly
different, indicating that the lower RMR in the short-stature
children was due to their smaller size. These results are similar
to those comparing stunted and nonstunted Jamaican children
(7), in whom the RMRs of stunted and age-matched (nons-
tunted) groups were not significantly different after adjustment
for FFM. Surprisingly. FFM was a better predictor of RMR in
our normal-stature children than in the short-stature children.
explaining 80% of its variance in contrast with only explaining
36% of the variance in the short-stature group. In comparison.
FFM explained 55% of the variance in RMR in stunted Jamai-
can children (7) and, in a study examining RMRs in 1 13
prepubertal children (white and Mohawk) 3.9-7.8 y of age
(25). FFM was one of the best predictors of RMR. explaining
59% of its variance.
Absolute TEE in the short-stature group also tended to be
lower than that in the normal-stature group, but these differ-
ences were not significant after differences in FFM were ad-
justed for. This again indicates that the lower TEE in the
short-stature group was due to their smaller size. The TEE
values obtained in the present study are similar to those ob-
tamed by Spurr and Reina (26) in children from the poor
barrios of Cali, Colombia. Spurr and Reina measured TEE
using the minute-by-minute heart-rate method in 132 normal
and undernourished boys and 1 10 girls aged 6-8, 10-12. and
14-16 y. They found that lower TEE values in undernourished
boys (5050 ± 1020 kJ/d) and girls (5120 ± 1020 kJ/d) than in
control boys (6590 ± 1590 kJ/d) and girls (564() ± 1080 kJ/d)
aged 6-8 y could be accounted for by differences in body size.
In addition, we compared our data with healthy children living
in the United States. TEE in our normal-stature children was
only slightly lower than TEE from normally nourished children
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412 WREN ET AL
in the United States (9. 27). Using the doubly labeled water
technique, Goran et al (9) measured TEE in 4-6-y-old children
and found a mean TEE of I 379 ± 290 kcal/d (5764 ± I 212
kJ/d) and Fontvieille et al (27) found a mean TEE of 1370 ±
222 kcal/d (5727 ± 928 kJ/d) in 5-y-old children. In both of
those studies. one of the major determinants of TEE was FFM,
which explained 74% of the variance of TEE in the Gonan et al
study and 54% in the study of Fontvieille et al. In the present
study, although FFM was the strongest predictor of TEE, it
only explained 29% of its variance. FFM for our normal-stature
subjects (16.1 ± 1.9 kg: range: 13.1-20.5 kg) was similar to
that of the healthy subjects of Gonan et al ( I 6.2 ± 2.7 kg;
range: 12.5-22.7 kg) and Fontvieille et al [range: � 1 1.5-22.5
kg (exact data not given)]. This indicates that energy expendi-
tune in our subjects was highly variable and could not be
predicted from body size alone. To better understand the daily
energy expenditure patterns in these children, one would have
to look more specifically at the variability in physical activity.
In summary, TBW, fat mass. and FFM were lower in short-
stature children than in normal-stature children from the same
community. However, these differences were not significant
after body size was controlled for. Short-stature children also
tended to have lower RMR and TEE than normal-stature chil-
dren, but no significant differences could be detected after
differences in FFM were controlled for. Thus, we find no
evidence to support the notion of altered energy metabolism or
body composition in short-stature Guatemalan children. A
We thank Harry Vaughn ftr his technical assistance with the isotope
ratio-mass spectrometer and Cheng Lung Li for his help with the statistical
analysis. Most of all. we thank the administration. teachers. parents. and
especially the children of Santa Clara who enthusiastically participated in
the study.
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