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Departments of Pediatrics, Obstetrics and Gynecology, University of Tennessee, Memphis, TN and * Computing and Information Technology, Wayne State University, Detroit, MI
2To whom correspondence should be addressed.
 |
ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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KEY WORDS: • race • gender • bone • fat • lean tissue • humans
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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). We reported previously that body mass is the dominant
predictor of bone mineral status in newborns (Koo et al. 1996
) and older infants (Koo et al. 1998
). This
is supported by other recent reports of bone mass measurements in
infants (Lapillonne et al. 1997
, Rigo et al. 1998
). Our finding is also consistent with the finding in
adults of a positive relation of body habitus (Aloia et al. 1999
, Chumlea and Guo 1999
, Ravn et al. 1999
) with bone mineral status, although lean body mass
(Courteix et al. 1999
, Ferretti et al. 1998
, Valdimarsson et al. 1999
) and fat mass
(Courteix et al. 1999
, Ferretti et al. 1998
) are thought to be stronger determinants of bone mass. In
contrast, little is known about the physiologic predictor of soft
tissue composition during infancy, and there are no data to determine
the predictive ability of soft tissue composition on bone mineral
status in infants. The aim of this study was to extend our previous
observation on bone mineral status (Koo et al. 1996
and 1998
) in newborn infants and throughout infancy to document the
differences in soft tissue composition during this period. We aimed to
determine the predictive value of anthropometric measurements and other
physiologic variables on soft tissue body composition measurements. In
addition, the predictive value of soft tissue composition on bone
mineral status also was assessed. |
SUBJECTS AND METHODS |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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The total study population included 214 singleton infants with birth
weights from 1002 to 3990 g. The subjects’ birth weights were
appropriate for gestational age (Brenner et al. 1976
).
Gestational ages of the subjects as determined by maternal menstrual
dating and/or ultrasound were from 27 to 42 wk and within 2 wk of
gestational age assessment by standard examination (Ballard et al. 1991
). Eighty-five subjects were preterm with
gestational age < 38 wk; of these, 53 subjects had low birth
weight (
2500 g). There were 101 Caucasian (60 boys, 41 girls) and 113
African American infants (55 boys, 58 girls). For infants beyond the
immediate newborn period, the type of milk and whether the infant was
receiving solids were recorded. This study was approved by the
Institutional Review Board for human subjects at the University of
Tennessee-Memphis, and written informed consent was obtained from
each subject’s parent.
Anthropometric measurements.
The nude weight and length of the infant were measured at each study. The weights of the cotton blanket that swaddled the infant and the diaper, if used, were also determined. An additional blanket or a large cotton sheet was used in 22 infants to better swaddle the larger infant. A diaper was used in all infants beyond the newborn period. The study weight is the total weight including the nude weight and the weight of blanket/s and diaper. The weight in grams was determined with a digital electronic scale (Air Shields, Vickers, OH). The scales were regularly maintained by the hospital Biomedical Instrumentation personnel and calibrated with known standard weights. Recumbent length was the average of two consecutive measurements within 0.4 cm and was determined using a standard length board (Ellard Instrumentation, Seattle, WA).
DXA measurements.
All infants were clinically well at the time of study, and each infant
was studied on one occasion. Scan acquisition of total body (TB) was
performed with a single beam whole-body scanner (Hologic QDR 1000/W
densitometer, Hologic, Waltham, MA), with the use of an infant
platform. With our densitometer, the typical maximum entry radiation
exposure during an infant whole body scan was 3 µSv (1
µSv = 0.1 mrem). The radiation scatter at 90 cm
from the scanner was <0.3 µSv from 10 min of
measurement (Koo et al. 1995a
).
All scans for this study were performed with the swaddled subject
placed on top of the infant platform with a cotton blanket interposed
between the subject and the platform (Koo et al. 1996
and 1998
). A heat lamp was used as needed to maintain a
satisfactory environmental temperature. All scans were performed
without sedation or additional restraint but a pacifier with
nonmetallic parts was used as needed. Occasionally, the scanning
procedure was interrupted if movement artifact was noted, and a repeat
scan was performed when the infant had been pacified.
Scans were analyzed using the software (Version 5.64p) developed in
conjunction with the manufacturer. In addition to the analysis of the
total body, analyses of different regions were also performed using the
same software if the position of the infant allowed adequate
delineation of separate regions. Regional analyses typically involved
the head and each of the four extremities. The residual region was
regarded as the trunk for a total of six regions. Each scan was
reviewed by one of two investigators (JW or WK) and was judged
technically satisfactory if the external calibration step phantom and
the skeletal outline of the subject lay within the scan region and
without significant movement artifact (Koo et al. 1995b
).
Quality control scans were performed daily on a
manufacturer-supplied anthropomorphic spine phantom, and the
long-term (>3 y) CV for the determination of bone mineral content
(BMC), bone area (Area) and bone mineral density (BMD) using an
anthropometric spine phantom are <0.31% for all parameters. The
average annual rate of change for each of these measurements was not
significantly different from zero. The in vivo replication of TB DXA
measurements in 50 infants was significantly correlated
[r = 0.99 and P < 0.001 for
all parameters, i.e., BMC, Area, BMD, lean mass (LM) and fat mass (FM),
respectively]. In our laboratory, the standard deviation
(SD) of difference (Bland and Altman 1986
)
between paired DXA measurements for TB BMC was 3.8% at a mean of
93 g; TB Area was 2.5% at a mean of 371 cm2; TB BMD
was 2.6% at a mean of 0.228 g/cm2; TB LM was 2.3% at a
mean of 3184 g; and TB FM was 7% at a mean of 995 g,
respectively.
Statistical analyses.
The data were treated as from two separate cohorts to determine the physiologic predictors of BC measurements at birth and postnatally. The "at birth" data consisted of DXA measurements of infants of all gestational ages studied during the first 8 d after birth, and the "postnatal" cohort consisted only of infants born at term and studied between birth and throughout infancy.
For the at birth cohort, a principal component factor analysis showed
that the three measures of weight (birth weight, study weight, nude
weight) were highly interrelated with loadings of 0.994 to 0.998. Thus,
any of the weight variables can be used in the regression analysis with
equal validity. Nude weight was used in all analyses to minimize the
entry of multiple colinear independent weight variables in the
analyses. Its use has other advantages because it is the most
consistent weight measurement without concern for the varying amounts
of clothing and covering; it also provides consistency with our
previous publications (Koo et al. 1996
and 1998
).
Stepwise multiple linear regression analyses were performed to determine the explanatory ability of each of seven independent variables on each of the six dependent variables [LM, FM, fat mass as a percentage of body weight (%FM), BMC, Area and BMD] separately. The independent variables are known to have the potential to affect growth and body composition; these included race, gender, gestational age, postnatal age at study, nude weight, length and season of birth. The season variable was determined by coding the month of birth at three monthly intervals beginning at March as spring, and was transformed into dummy variables using spring as the reference season. In addition, each of the three variables, LM, FM and nude weight, was entered alone as an independent variable to determine the value of each of these three independent variables in the prediction of BMC, Area and BMD.
For each of the dependent variables, a final model predictive equation
was generated, containing only significant independent variables. This
represents a hierarchical modeling process that first determines the
most powerful individual predictor of DXA measurements and then
determines whether any other set(s) of independent variable(s) either
augmented or diminished the model’s explanatory capability of the
single best predictor. Percentiles were also calculated for LM, FM and
%FM using Altman’s method (Altman 1993
) and the
best-fit curves were plotted on the basis of the actual data.
For the postnatal cohort, study weight and nude weight were significantly correlated (r2 = 0.99) and only nude weight was entered as an independent weight variable. Data analysis used the same procedures as described above. However, three additional variables were entered as independent variables. These included birth weight, the season at the time of study (derived from the study month and entered into regression model using the same technique described above) and, for infants beyond the immediate newborn period, the type of milk intake and use of solid food on the day of study. Milk intake was transformed into dummy variables before analyses using human milk as the reference milk.
All statistical tests were performed with SPSS 9.0 (SPSS, Chicago, IL) for Windows at an adopted significance level of 0.05. Values are means ± SD.
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RESULTS |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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At birth cohort.
Nude weight consistently proved to be the single best predictor of LM, FM and %FM with an adjusted R2 of 0.978, 0.837 and 0.632, respectively. Gender and length were the only additional predictors that could be forced into a predictive equation for these dependent variables on the basis of statistical significance, although the additional contributions to the prediction of LM, FM and %FM were 0.5, 3.2 and 6.2%, respectively. Female infants had significantly lower LM but higher FM and %FM (P < 0.01). The final regression equations (P < 0.001 for all models) for the prediction of TB LM, FM and %FM including all significant predictors are as follows:
DXA LM (g) = -714 + 0.626 nude weight (g) + 29.94 length (cm) - 39.7 gender
Adjusted R2 = 0.983, SEE 76 g
DXA FM (g) = 644 + 0.347 nude weight (g) - 25.9 length (cm) + 33.3 gender
Adjusted R2 = 0.869, SEE 70 g
DXA FM (%) = 22.0 + 6.525E-03 nude weight (g) - 0.581 length (cm) + 1.3 gender
Adjusted R2 = 0.694, SEE 2.1%
where gender = 0 for male infants and 1 for female infants and SEE is the standard error of estimate.
Percentiles for DXA measurements of TB LM, FM and %FM in newborn
infants based on nude weights are shown in Figure 1A–C
. It should be noted that percentiles are descriptive, not predictive,
and draw attention to the increasing variability of the dependent
variables as nude weights increased. The standard error of estimate for
a predictive equation is a function of the dependent variable and
represents the strength of the correlation between independent and
dependent variables. The adequacy of the predictive equation across the
body weight range of our newborn cohort was determined by computing
predictive equations based on two nude weight ranges divided
approximately at the midpoint of the total weight range. The resultant
r and SEE values of the prediction equations generated from
the total cohort and from the two subpopulations are shown in
Table 1
. With increasing body weight from 1.5 to 3.5 kg, the average proportion
of TB LM decreased from 90.8 to 81.8% and the average proportion of TB
FM increased from 7.5 to 16.2%.
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1.85. The average increase in FM at these regions was 540,
528 and 345%, respectively, whereas the trunk:extremities ratio for FM
decreased from 1.03 to 0.79. Postnatal cohort.
For term infants during infancy, length was the most dominant predictor of LM, with an adjusted R2 of 0.915. However, nude weight became the dominant predictor for LM with an adjusted R2 of 0.958 if length was excluded from the regression. Nude weight was the dominant predictor of FM with an adjusted R2 of 0.738. There was no single predictor of %FM that resulted in an adjusted R2 of >0.20. Gender and postnatal (study) age were the additional predictors that could be forced into a predictive equation for these dependent variables on the basis of statistical significance, although the additional contribution to the prediction of LM, FM and %FM was <3, <12 and 6.2%, respectively. Female infants had significantly lower LM but higher FM and %FM (P < 0.001). Incorporating any other independent variable including type of milk intake (10 infants were fed human milk, 9 infants were fed homogenized whole cow’s milk and the others were fed infant formulas) and the use of solids in the diet concurrent with DXA assessment failed to improve prediction. The final regression equations (P < 0.001 for all models) for the prediction of TB LM, FM and %FM including all significant predictors are as follows:
DXA LM (g) = -1319 + 0.278 nude weight (g) + 64.59 length (cm) - 307 gender + 2.473 age (d)
Adjusted R2 = 0.944, SEE 338 g
DXA FM (g) = 908.4 + 0.706 nude weight (g) - 53.0 length (cm) + 358.5 gender - 3.057 age (d)
Adjusted R2 = 0.856, SEE 345 g
DXA FM (%) = 9.57 + 0.0037 nude weight (g) + 4.56 gender - 0.0538 age (d)
Adjusted R2 = 0.403, SEE 4.7%
where gender = 0 for male infants and 1 for female infants.
Percentiles for DXA measurements of LM, FM and %FM in term infants
during infancy based on nude weights are shown in Figure 2A–C
. Adequacy of the predictive equation across the body weight range of
our postnatal cohort was determined as for the newborn cohort (Table 1)
. After birth, the proportion of TB LM continued to decrease, whereas
the TB FM increased. The TB LM and TB FM averaged 66.3 and 31.4%,
respectively, at the body weight of 10.5 kg.
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1.90. The average increase in FM at these regions was 485,
573 and 365%, respectively, whereas the trunk:extremities ratio for FM
decreased from 0.82 to 0.57. Body weight vs. soft tissue mass prediction of DXA bone measurements.
When each of the variables (nude weight, LM and FM) was entered
independently into the regression model, nude weight consistently
provided the best predictive value at birth and throughout infancy for
DXA bone measurements compared with LM and FM (Table 2
). Details of the DXA bone measurements are reported elsewhere
(Koo et al. 1996
and 1998
).
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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);
low bone mass increases the fracture risk independently of age
(Kanis et al. 1994
, Koo and Steichen 1998
); low body mass index associated with low body fat
increases the risk for bone loss (Ravn et al. 1999
) and
possibly the development of osteoporosis and its complications. In
contrast, the very high body mass index associated with high body fat
predisposes the individual to the numerous complications of obesity
(Dietz 1998
). Thus, an increased understanding of the
relation between physiologic determinants of BC in infants may lead to
a greater understanding of the role of genetic and environmental
influence on changes in BC and may be critical to the management of
healthy and sick infants, particularly in the design and assessment of
the role of nutritional intervention (Shetty 1999
).
In infants, body weight can predict various aspects of BC during the
newborn period (Koo et al. 1996
and 1998
,
Lapillonne et al. 1997
, Rigo et al. 1998
), but no data exist concerning the predictive effect of
various physiologic parameters on BC beyond this period. This study
demonstrated that body weight contributed heavily to the model’s
explanatory power for soft tissue (LM and FM) composition during
infancy. Length becomes the dominant predictor of LM with increasing
postnatal age, although the predictive value of body weight on soft
tissue composition remains significant throughout infancy because
length and weight are colinear.
It is well documented that in children (Taylor et al. 1997
) and adults (Frisancho 1993
), females have
more FM and less LM than males. Females are shorter and weigh less than
males at birth and throughout infancy (Brenner et al. 1976
, Hamill et al. 1979
), but little is known
about the earliest onset of gender-related difference in FM and LM.
Only one report in newborn infants specifically showed greater FM in
females compared with males (Rigo et al. 1998
). Our data
demonstrated that gender has an independent predictive effect on the
amount of LM and FM at birth. In addition, the gender difference in FM
and LM increased throughout infancy. The increase in FM in females was
accompanied by a similar decrease in LM. In contrast, there is no
gender-related difference in bone mass measurements throughout
infancy (Koo et al. 1996
and 1998
). The consistency and
persistence of the gender-related difference in soft tissue
composition is also reflective of the standardized technique in scan
acquisition, including the consistency in the type and amount of
covering used for each infant, thus minimizing any interference with
DXA soft tissue measurements from variable types and amounts of
clothing and covering.
On the basis of differences in adjusted
R2 values in the statistical models,
our study demonstrated that the independent physiologic variables,
i.e., weight, length and gender, appear to be stronger predictors for
the amount of LM than for FM. The ability of physiologic variables to
predict FM and in particular %FM decreases with increasing postnatal
age. This is presumably related to the increased role of environmental
influences such as dietary intake (and physical activity in older
children) on fat mass accumulation compared with lean mass
(Barlow and Dietz 1998
, Grandjean 1999
,
Shetty 1999
). In this study, the type of milk intake and
the use of solids on the day of DXA assessment did not contribute to
the determination of body composition in infants. However, this study
was not designed to determine the influence of dietary intake because
no details on the duration or quantity of specific intake were
available.
It is important to note that the large range of LM, FM and %FM at any given body weight shown in the figures represents biologic variability expressed as percentile channels rather than predictive value of body weight on these DXA measurements. However, stability of the correlations (r-values) for the prediction of LM whether from body weights of total or subpopulations supports the adequacy of our model based on the total population of subjects in each cohort. Lack of significant differences in the residuals derived from the prediction equations based on subpopulations also supports the contention that the predictive value of nude weight on LM is independent of the range of body weights within each cohort. We presented SEE in standard Z-score form to reflect the role of correlation in determining the SEE because the standard deviation of the dependent variable is unity in the Z-score measure. The observed stability of correlation across body weight ranges means that a difference in SEE between two ranges of body weights was due to the increased variability in dependent measure, not to a change in correlation. Our data support a similar conclusion for FM prediction, although the predictive ability of body weight for FM decreased somewhat in heavier postnatal infants. FM%, a calculated value, is poorly predicted by body weight especially in the postnatal cohort whether the prediction equation was based on the total or subpopulations.
In contrast to the well-defined racial differences in BC of
children (Aloia et al. 1999
, Chumlea and Guo 1999
, Gilsanz et al. 1991
) and adults
(Aloia et al. 1999
, Chumlea and Guo 1999
,
Ortiz et al. 1992
), our study showed that there is no
racial effect on soft tissue composition in this age group once body
weight and length are taken into account. This is consistent with our
previous reports on TB DXA bone measurements (Koo et al. 1996
and 1998
), and other reports on skeletal weight, density and
percentage of ash (Trotter and Hixon 1974
), and distal
radial BMC (Namgung et al. 1994
) during infancy. Racial
difference in BC found in older ages presumably is also related to the
increasing importance of environmental influence and possibly the
genetic and environmental interaction. Similarly, season did not affect
soft tissue composition during infancy.
In the range of body weights studied, changes in TB LM can be represented by linear modeling but the changes in FM were represented by both linear and nonlinear models depending on the body weight range. The pattern of accumulation of TB LM and FM in our birth and postnatal cohorts reflects the rapid growth during the last trimester and after birth, particularly the accumulation of TB FM during the late in utero and postnatal periods. With increasing body weight, there was a greater range of LM and FM, especially of FM, supporting the greater biologic variability and increasingly important role of environmental influences such as differences in dietary intake in larger and older infants.
Our data are comparable to other reports using the same DXA technique
for newborn (Lapillonne et al. 1997
, Rigo et al. 1998
) and older (Mehta et al. 1998
) infants.
However, strict comparison among studies is difficult because of the
different populations studied. Some reports included infants with birth
weights of >4 kg, thus raising the possibility of
large-for-gestational-age infants in the study cohort
(Lapillonne et al. 1997
, Rigo et al. 1998
); additional small differences may be related to the use
of different models of DXA densitometer (Abrahamsen et al. 1995
) and different versions of software (Picaud et al. 1999
), even those provided by the same manufacturer.
Nevertheless, despite the limitations associated with all in vivo
techniques of BC measurement (Koo 2000
), there appears
to be general agreement in the overall absolute and relative changes in
the soft tissue composition among the various reports of BC based on
the same DXA technique.
None of the in vivo DXA data are directly comparable with the chemical
analysis of cadavers (Widdowson 1975
, Ziegler 1976
) because the techniques used in deriving the LM and FM are
not comparable with the in vivo reports (Koo 2000
).
Furthermore, BC extrapolated from chemical analysis may not be truly
representative of normal infants because most of the subjects reported
were below the fiftieth percentile on the growth curve, the causes of
death, especially those that may have affected growth and BC, were not
available, and there is a lack of cadaver data beyond the newborn
period.
Our data show that body weight is also a major predictor of regional
DXA soft tissue composition, although its predictive ability is
somewhat weaker than that for TB soft tissue. Similar to our findings
for DXA bone measurements (Koo et al. 1996
and 1998
),
there was extensive variation in the amount of LM and FM among
different regions (upper and lower extremities, trunk); the changes in
these regions during in utero and postnatal growth as indicated by our
"at birth" and "postnatal" cohorts, were not directly
proportional to the changes in body weight or the soft tissue
composition of the whole body. The relative difference in regional BC
was also reflected in a proportionately greater increase in FM at the
extremities compared with the trunk as body weight increases, whereas
the proportion of LM between trunk and extremities remained steady
throughout infancy.
Caution is required in the interpretation of DXA BMD, an areal density
based on BMC divided by skeletal area (Nelson and Koo 1999
, Prentice et al. 1994
). The reasons for
this caution include the dissimilar rate of increase in BMC and
skeletal area during infancy and childhood, and the technical
difficulty in obtaining an accurate TB area in a swaddled infant/child.
To allow better interpretation of DXA bone mass measurements, attempts
have been made to normalize the DXA bone measurements on the basis of
the reports in adults that LM is a good predictor of bone mass as BMC
(Ferretti et al. 1998
, Valdimarsson et al. 1999
) or as BMD (Courteix et al. 1999
,
Valdimarsson et al. 1999
) and that FM is a good
predictor of BMC (Ferretti et al. 1998
) and BMD
(Courteix et al. 1999
). However, we showed that in
healthy infants, LM is an independent predictor of TB BMC throughout
infancy and TB Area in newborns, but is consistently weaker than the
use of body weight to predict these measurements. Furthermore, LM has
minimal predictive value on TB BMD, and FM has minimal predictive value
for any DXA bone measurement except BMC in the newborn period. These
findings suggest that weight-bearing and impact-loading
exercise critical to the increase of LM and bone mass in older subjects
(Courteix et al. 1999
, Pettersson et al. 1999
) are not well developed in younger subjects. Thus the use
of LM or FM provides no advantage over body weight in the prediction of
skeletal bone mineral status during infancy.
We conclude that in healthy infants, body weight is the dominant predictor of LM and FM, although length has the same or stronger predictive value for LM with increasing postnatal age. Physiologic variables have little predictive value for %FM beyond the newborn period. Gender difference in LM and FM can be demonstrated at birth and increases throughout infancy. The use of LM or FM offers no advantage over body weight in the prediction or normalization of bone mass measurements during infancy. Our data on the precision of DXA measurement and the physiologic factors that influence BC are important to the design and assessment of nutritional intervention studies in infants under various physiologic and pathologic situations.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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3 Abbreviations used: Area, bone area; BC, body composition; BMC, bone mineral content; BMD, bone mineral density; DXA, dual energy X-ray absorptiometry; FM, fat mass; %FM, fat mass as a percentage of body weight; LM, lean body mass; SEE, standard error of estimate; TB, total body.
Manuscript received January 12, 2000. Initial review completed February 2, 2000. Revision accepted April 7, 2000.
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