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: mig@uah.edu.

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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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

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7

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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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10 12 14 16 18 20 22 3000 3500 4000 4500 5000 5500 6000

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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