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Body mass index at different ages and its association with height at age 14 and with the whole growing process
APPLIED
NUTRITIONAL
INVESTIGATION
Nutrition Vol. 12, No. 6, 1996
Body Mass Index at Different Ages and Its Association With Height at Age 14 and With the Whole Growing Process MANUEL AMADOR, MD, PHD, JORGE BACALLAO, MSC, AND MIRTA HERMELO, MD, PHD From the Institute of Nutrition and Food Hygiene and the Higher Institute of Medical Sciences, Havana, Cuba Date accepted: 15 September 1995 ABSTRACT The relevance of the association of the body mass index (BMI) at 1, 4, 6, and 12 years of age with the growing process and its capacity for predicting height at age 14 was investigated in a sample of 354 adolescents (182 boys and 172 girls). Regression analysis showed that body bulk at various ages, as expressed by the BMI is closely related with the height attained at age 14, and longitudinal principal components analysis suggested that it is also associated with the whole growing process. The way in which BMI affects height could be related with the stage of sexual development, which seems to play an intermediate role in the pathway linking body bulk and height. Nutrition 1996; 12:416-422 Key words: body mass index, childhood, adolescence, body bulk and growth, longitudinal principal components analysis, stage of sexual development, adiposity
INTRODUCTION In children and adolescents, the association between height and weight is well known. Not quite as obvious is the association between height and relative weight. It is, however, a wellestablished fact that overfat children are usually taller than their lean peers of the same age and sex. A generally accepted explanation is that this is due to the increase of lean tissues that usually follows a positive balance between energy intake and expenditure. ~-3 The sequence "energy excess ~ energy storage --, increased lean body mass --, increased linear growth" is commonly observed among overfat growing subjects 4 and could be the expression of an underlying causal path that links several biological events with a common nutritional background. Johnston and Mack, 5 in a study of youths aged 9 - 1 5 y, found that those who had a relative weight above 1 SD at 1 y were on average 2 cm taller than those who had a relative weight below - 1 SD. Rona and Chinn 6 reported a positive correlation between birthweight and height of school ages in a study of 13,107 boys and girls, carried out among different ethnic groups in England. The present study intends to assess th'~ extent to which body bulk at different ages is associated with height at age 14 and with the growing process as a whole and to investigate the role
played by sexual development in the association between body bulk and height. SUBJECTS AND METHODS In 1972, a longitudinal study on weight and height in children aged 12 mo (___2wk) was initiated in one municipality in Havana. Those children have been followed up and remeasured three times during their lives: at preschool age (3.8-4.2 y), upon enrollment at the elementary school (5.8-6.2 y), and upon enrollment at high school ( 11.8-12.2 y). From the obstetric card of their mothers (a document kept for all pregnant women in Cuba for prenatal controls and other effects, which they are requested to conserve), birthweight was retrieved in all cases. In 1986, all students from two high schools at the municipality of Boyeros in Havana (who made up a subsample of the original sample for the follow-up study) with ages ranging from 13.6 to 14.5 y were selected for the present study if their birthweight was 2500 g or more. They made up a nonprobabilistic sample of 354 healthy adolescents ( 182 boys and 172 girls). Schools in Cuba provide a very useful and convenient sampling frame. Within a given municipality, at the very least, the socioeconomic differences that could have some impact on income, access to food sources, and, subsequently, on the nutritional condition are negligible if they exist at all. Both high schools
Correspondence to: Manuel Amador, MD, PhD, Institute of Nutrition and Food Hygiene, Calzada de Infanta 1158, La Habana 10300, Cuba.
Nutrition 12:416-422, 1996 ©Elsevier Science Inc. 1996 Printed in the USA. All rights reserved.
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BODY MASS INDEX AND GROWTH
417
might claim to be representative of the population of high schools in Havana. In addition, education is compulsory up to the third year of high school, or equivalent level in Cuba. Records on body weight and height at 1, 4, 6, and 12 y of age were kept for all the subjects in the sample. Body weight and height at age 14 were also measured. The measurements on body weight were made in kilograms to the nearest 100 g with Detecto scales. Supine length and stature were measured in centimeters to the nearest millimeter with Holtain infantometers and stadiometers, respectively. The methodology used for the measurements was that recommended by the International Biologic Programme 7 and the Cuban National Child Growth Study. 8 At 12 and 14 y of age, the stage of sexual development (SSD) was determined according to Tanner 9 and the decimal age 7 was recorded. The body mass index (BMI; kg/m 2) was calculated at 1, 4, 6, 12, and 14 y of age. The supine length was missing from most obstetric cards, and for that reason, the BMI at birth was not included in the study. All measurements were taken by the same well-trained anthropometrist with vast experience in both Cuban National Growth Studies of 1972 and 1982. The measurements at age 14 were performed twice and averaged and were all checked by one of the authors and found to fulfill the required standards of precision.
Data Analysis All analyses were carried out separately in boys and girls. Pearson partial correlation coefficients were computed and tested for significance between height at 14 and BMI at 1, 4, 6, 12, and 14 y of age. The control variable in the partial correlations was decimal age because around 14 y of age, height changes very quickly. A multiple linear regression was fitted for height at 14 on the BMI at 1, 4, 6, and 12 y of age. BMI at age 14 was purposefully omitted from the set of regressors. A matrix of autocorrelations among heights at different ages was calculated and factor analyzed by means of longitudinal principal components analysis (LPCA). ~°'H Factor scores on the unrotated components were correlated with the BMI at different ages. On the sample classified according to the stage of sexual development, descriptive statistics were obtained for the BMI at the ages already mentioned. Finally, a path analysis model j2 relating height at age 14
with the different measurements of the BMI and with SSD was fitted, and the corresponding path diagram was built. The expected correlations emerging from the model were compared with the actual correlations among the variables in order to verify the adequacy of the model. All calculations were performed with SYSTAT, release 3.0. RESULTS Table I contains descriptive statistics for body weight, height, and BMI at different ages for both sexes. Means and SDs of the BMI at 1, 4, 6, 12, and 14 y of age were computed for all subjects classified according to their SSD at 14. For every age considered, there was a significant difference between the subjects classified according to their SSD at 14. With the only exception of age 4 in boys, significant differences are found in the BMI of subjects classified according to their SSD at age 14. The highest values of the BMI are found among subjects in stage 5 at 14 y and the lowest among those in stage 3 at that age. This holds for both sexes and means that bulkier boys or girls at age 1, 4, or 6 tend to mature earlier. These descriptive results are shown in Tables II and III for boys and girls, respectively. Table IV contains the partial correlations, controlled for decimal age between height at 14 and the BMI at various ages for both sexes. The lowest correlation is the one that involves the BMI at age 14. All correlations except this one are highly significant. The pattern of associations is very similar for both sexes. Table V is the matrix of autocorrelations between repeated measurements of the BMI. The correlations are considerably higher for girls and are also higher between contiguous measurements of the BMI for both sexes. Tables VI and VII contain the results of the multiple linear regression equations for boys and girls, respectively. Both regressions show a very good fit, with significant F values and a very high percentage of variance explained. The relative pattern of the parameters is also very similar in both sexes: the parameters affecting BMI4 and BMI6 are not significant and those affecting BMI1 and BMI12 are significant. This is due not only to the predictive capacity of the latter variables but also to the fact that each of them is less colinear with the rest of the predictors than BMI4 or BMI6. This is clearly shown by the tolerances.
TABLE I. BODY WEIGHT (BW), HEIGHT (HT), AND BODY MASS INDEX (BMI) AT DIFFERENT AGES FOR BOTH SEXES Boys (n = 182)
Girls (n = 172)
Ages (y)
BW
HT
BMI
BW
HT
BMI
1
10.33 (1.25) 16.19 (1.42) 20.51 (2.53) 43.94 (8.60) 56.70 (11.89)
74.8 (2.1) 101.7 (3.0) 114.8 (3.6) 147.6 (5.8) 164.2 (8.9)
18.4 (1.7) 15.8 (0.9) 15.8 (1.3) 18.7 (2.6) 21.2 (3.7)
10.24 (1.50) 16.79 (2.36) 20.29 (3.22) 45.11 (11.00) 53.45 (12.34)
73.5 (2.2) 101.6 (2.9) 114.5 (4.1) 148.9 (6.2) 157.5 (5.8)
18.8 (2.6) 16.9 (1.8) 15.5 (1.8) 20.4 (3.5) 21.4 (4.2)
4 6 12 14
Means and (standard deviations).
418
BODY MASS INDEX AND GROWTH TABLE II.
TABLE IV.
MEANS ± STANDARD DEVIATIONS OF BODY MASS INDEX (BMI) AT DIFFERENT AGES FOR BOYS CLASSIFIED ACCORDING TO THEIR STAGE OF SEXUAL DEVELOPMENT (SSD) AT 14 YEARS OF AGE
PARTIAL CORRELATIONS (CONTROLLED FOR DECIMAL AGE) BETWEEN HEIGHT AT 14 AND BODY MASS INDEX (BMI) AT 1, 4, 6, 12, AND 14 YEARS OF AGE FOR BOTH SEXES
BMI 1y 4y 6y 12 y 14 y
SSD= 3 (n = 45) 17.94 15.59 14.86 16.81 18.09
± 1.38 ± 0.71 ___0.39 ± 1.55 ± 1.83
SSD=4 (n = 107) 18.43 15.69 15.66 19.12 20.90
± 1.78 ± 1.00 ___ 1.38 ± 2.73 ± 3.73
SSD= 5 (n = 30) 19.09 15.88 16.17 20.58 25.05
F
± 1.43 3.19 ___0.76 0.66 ___ 1.01 10.09 ___2.02 17.52 __+ 1.24 32.39
Sex
BMI1
BMI4
BMI6
BMI12
BMI14
Boys Girls
0.45 0.55
0.36 0.59
0.46 0.58
0.59 0.61
0.03* 0.35
p 0.045 0.518" 0.000 0.000 0.000
* Not significant; the remaining correlations are significant for p -~ 0.001.
* Not significant. B M I 6 = p31BMI4 + e3 The matrix of autocorrelations a m o n g heights at different ages is represented in Table VIII for the two sexes, and the factor loadings matrices for each sex separately are s h o w n in Tables IX and X. In both sexes, the percentage of total variance explained b y the first two components is close to 90%. The first c o m p o n e n t describes a uniform pattern of growth with similar c o m p o n e n t loadings on height at 1, 4, 6, 12, and 14 y of age. Boys and girls with heights above average for their age are high scorers on this component. The second component, on the other hand, characterizes a nonuniform pattern of growth. Adolescents with the highest scores on this c o m p o n e n t were short until age 4 and experienced a rapid growth from then on. This second component, however, is a very marginal one for both sexes. Its associated Eigen value is considerably lower than 1. Figure 1 shows the correlations of the first c o m p o n e n t with the B M I at different ages for both sexes. All correlations are significant with the exception of those involving B M I at 14 y of age. There is a smooth but monotonous increase in the correlations from age 4 to 12 and a sharp decrease from age 12 to 14 where the association of the B M I with the growing process has no statistical significance. The scores on the second c o m p o n e n t are of marginal importance and therefore have not b e e n correlated with serial measurements of BMI. Figures 2 and 3 represent the path diagrams for boys and girls, respectively. Those diagrams with their path coefficients are the pictorial representation of the following path model:
B M I 1 2 = p41BMI6 + e4 B M I 1 4 = p s i B M I 1 2 + e5 SSD = p61BMI1 + p62BMI4 + p63BMI6 + P64BMI12 + p65BMI14 + e6 HT14 = pT~BMII + PTaBMI12 + P76SSD + e7
(1)
where the ei stand for error terms and the Pu are the path coefficients. The assumptions implicit in this model are as follows: 1) el denote error terms that condense the influence of m a n y exogenous variables and are mutually uncorrelated and independent of all the endogenous variables in the model, 2 ) the B M I at any age depends directly only on the value of the same variable at the previous age recorded, 3 ) HT14 depends directly only on B M I I and B M I 1 2 and on SSD, and 4 ) SSD at age 14 is influenced by the body bulk expressed by the BMI. Tables XI and XII show the actual and the estimated correlation coefficients a m o n g values of the BMI, the SSD, and height at 14 y of age for boys and girls, respectively. The estimated correlations are those generated by the assumptions underlying the path analysis models. There is a fairly good aproximation between actual and predicted correlations.
TABLE V.
BMI1 = e~ MATRIX OF AUTOCORRELATIONS AMONG REPEATED MEASUREMENTS OF BODY MASS INDEX (BMI) FOR BOTH SEXES
B M I 4 = p2~BMI1 + e2 TABLE III. MEANS ± STANDARD DEVIATIONS OF BODY MASS INDEX (BMI) AT DIFFERENT AGES FOR GIRLS. CLASSIFIED ACCORDING TO THEIR STAGE OF SEXUAL DEVELOPMENT (SSD) AT 14 YEARS OF AGE
BMI1
BMI4
BMI6
BMI12
BMI14 0.10
BMI1
BMI4 BMI 1y 4y 6y 12 y 14 y
SSD= 3 (n = 9) 17.18 15.23 14.96 16.15 18.22
± ± ± ± ±
1.72 0.65 0.63 1.48 2.23
SSD = 4 (n = 85) 17.85 15.73 14.90 18.41 19.24
___2.13 ___ 1.45 ± 1.22 ± 2.35 ± 2.59
SSD = 5 (n = 79) 20.18 17.36 16.41 23.07 24.17
± ± _ ± ±
2.62 1.84 2.00 3.15 3.99
F 15.89 17.63 15.46 41.18 38.51
p 0.000 0.000 0.000 0.000 0.000
BMI6 BMI12
1.00
0.51
0.28
0.11
1.00
0.74
0.54
0.50
0.28
--
1.00
0.50
0.13
0.09
--
1.00
0.74
0.58
0.35
--
--
1.00
0.52
0.14
--
--
1.00
0.65
0.49
--
--
--
1.00
0.32
--
1.00
0.75
--
BMI14 Girls in italic.
--
.
.
.
.
1.00
.
.
.
.
1.00
BODY MASS INDEX AND GROWTH
419
TABLE VI.
TABLE VIII.
RESULTS OF THE MULTIPLE REGRESSION MODEL OF HEIGHT AT AGE 14 ON BODY MASS INDEX (BMI) AT DIFFERENT AGES FOR BOYS
MATRIX OF AUTOCORRELATIONS AMONG REPEATED MEASUREMENTS OF HEIGHT (HT) FOR BOTH SEXES
Variable
Coeff.
SE
Tolerance
t
p
Constant BMI1 BMI4 BMI6 BMI12
77.26 1.71 1.27 0.12 1.80
9.61 0.37 0.76 0.57 0.23
-0.73 0.58 0.55 0.72
8.04 4.60 1.66 0.21 7.72
0.00" 0.00" 0.10 0.83 0.00"
HT 1
HT4
1.00
0.79
1.00
0.71
1.00 1.00
HT1 HT4 HT6 HT12
* Significant predictors, R2 = 0.55, F = 38.48, p --< 0.001.
HT14 DISCUSSION A m o n g environmental factors, the balance of energy and nutrients play a crucial role in the growing process: intake above expenditure leads to an excessive storage of energy in the form of fat and to an increase of lean tissues. W h e n this happens during a period of faster growth, the effects on linear dimensions are more relevant and the growth rate is even more increased as a result of the adaptive process to energy unbalance. In a previous paper, we showed that relative body weight at different ages ( 1, 4, 6, and 12 y) might be useful to predict height at 14.13 Highly significant differences were found for height at 14 w h e n children were grouped according to their percentile distribution of weight for height. In addition, height was proven to be more strongly related with indicators of lean body mass than with indicators of adiposity, especially in boys, and SSD was also found to be closely associated with height at fourteen. Although relative weight and B M I are both measures of body bulk (because they express the amount of adiposity and of lean tissues), the latter is generally accepted as a suitable measure of adiposity in children, ~4-17 which, in addition, is independent of height. 18 In the present study, the correlations of the B M I at different ages with height at age 14 are highly significant, with the only exception of B M I at age 14 in boys. The correlations are higher in girls for all ages. A l t h o u g h there is m u c h controversy as to the selection and use of an indicator of body mass, the Quetelet index ( w e i g h t / height z) is by far the most frequently used for the assessment of the nutritional condition in growing subjects 14-18 despite its limitations for distinguishing between lean and fat body mass and the recent evidence that it has an age-dependent association
TABLE VII. RESULTS OF THE MULTIPLE REGRESSION MODEL OF HEIGHT AT AGE 14 ON BODY MASS INDEX (BMI) AT DIFFERENT AGES FOR GIRLS Variable
Coeff.
SE
Tolerance
t
p
Constant BMI1 BMI4 BMI6 BMI12
123.17 0.45 0.34 0.54 0.58
3.64 0.22 0.39 0.35 0.15
-0.44 0.29 0.38 0.55
33.81 2.04 0.88 1.54 3.96
0.00" 0.04* 0.38 0.13 0.00"
* Significant predictors, R2 = 0.48, F = 28.01, p --< 0.001.
HT6
HT 12
HT 14
0.76
0.73
0.72
0.57
0.56
0.58
0.77
0.72
0.68
0.82
0.84
0.79
--
--
1.00
0.82
0.79
--
--
1.00
0.89
0.81
--
--
--
1.00
0.85
--
--
--
1.00
0.92
.
.
.
.
1.00
.
.
.
.
1.00
Girls in italic.
with height and increasing variance with age, even after being log-transformed. 19 At most pediatric ages w e i g h t / h e i g h t squared has been shown to be more independent of height than other BMIs. t8 G r o w t h in height is influenced by genetic and environmental factors and by the interaction of both. During childhood, especially in males, it is most susceptible to the environmental influence represented by factors associated with diet and health. 2° There is no general agreement, however, as to the relative influence of genetics and e n v i r o n m e n t on the BMI. Stunkard et al. z~ considered that environmental factors have little or no influence at all, whereas Kramer et a l Y believed that adiposity and therefore body bulk and B M I are modified by environmental effects. In the present study, the maturation rate before 12 y of age was not available, hence the genetic background and the relative effects of genetics and e n v i r o n m e n t on body bulk could not be established. Nevertheless, the data available at ages 12 and 14 suggest that body bulk, as given by the BMI, is related with height through a chain of associations only partly mediated by maturation and sexual development. Johnston and M a c k 5 found no association between skeletal TABLE IX. FACTOR LOADINGS FOR THE FIRST TWO COMPONENTS YIELDED BY THE PRINCIPAL COMPONENTS ANALYSIS ON THE AUTOCORRELATION MATRIX FOR REPEATED MEASUREMENTS OF HEIGHT (HT) IN BOYS Components Variables
I
II
HT1 HT4 HT6 HT12 HT14
0.89 0.88 0.93 0.93 0.91
-0.28 -0.38 0.07 0.25 0.32
Percentage of total variance explained Eigenvalue
82.1 4. I 1
7.8 0.39
420
BODY MASS INDEX AND G R O W T H TABLE X.
FACTOR LOADINGS FOR THE FIRST TWO COMPONENTS YIELDED BY THE PRINCIPAL COMPONENTS ANALYSIS ON THE AUTOCORRELATION MATRIX FOR REPEATED MEASUREMENTS OF HEIGHT (HT) IN GIRLS Components Variables
I
II
HT1 HT4 HT6 HT12 HT14
0.75 0.93 0.92 0.95 0.93
-0.65 -0.09 0.18 0.24 0.19
Percentage of total variance explained Eigenvalue
80.8 4.04
11.1 0.55
maturation, height, and obesity in 15-y-old youths whose 1-y relative weights were known. Their findings suggest that the influence of relative weights during adolescence on height at 15 is independent of the rate of skeletal maturation. Although BMI is not a measure of fat body mass alone, its changes across ages resembles very much that of skinfolds and fat width measurements. 2~ Because no data on bone age, body composition, or other indicators of maturation were available, our study is based on the generally accepted assumption that BMI is a good proxy for adiposity. '4-17 Clear nutritional implications emerge from the conclusion that weight/height 2 at different ages is associated with height at age 14 and with growth in height viewed as a process. The highest correlations with height at age 14 for both sexes were found with the BMI at age 12. This is a critical period of growth that is related with the onset of pubertal changes and with the acceleration of lean tissue accretion. ~8'24Children approaching puberty get relatively heavy and relatively tall. BMI at age 12 is a proxy for early puberty, and therefore it is a good predictor of taller children. It is also the only period during childhood where body weight/height 2 and height have been found to be significantly correlated. ~4The correlation of height at age 14 is lower with BMI at that same age than with the
1
~
~
f 0.09
FIG. 2. Path diagram and coefficients for boys. BMI at 1 y = BMI1, 4 y = BMI4, 6 y = BMI6, 12y = BMI12, 14 y = BMI14. Stature at 14 r = HT14. previous measurements of BMI at 1, 4, 6, and 12 y. BMI at age 14 might reflect current but recent adiposity with no real bearing on the growth attained at that age. The BMI at 1 y of age is mainly the expression of the fast increase of adiposity that takes place during the first year of life and is a good predictor of height at age 14. The correlations of height at age 14 with the BMI at 4 y of age are much higher in girls than in boys. Girls experience an earlier adiposity rebound (from 3.0 to 5.5 y); in addition, they are expected to mature earlier and to be taller at 14 y.25 The so-called early adiposity rebound occurs in boys with a lag of almost 2 y with respect to girls and is independent of the degree of adiposity at 1 y.26 A very interesting fact is that although the BMI at all ages considered in this study is more strongly correlated with height at age 14 in girls than in boys, the regression equation based on all the measurements of the BMI taken jointly explains a higher percentage of variance in boys than in girls. The explanation to this can be found in the structure of the autocorrelation matrices among the BMIs for both sexes. The autocorrelations are much lower for boys, so that when all the variables are taken together, there is less multicollinearity and therefore less redundancy in the predictors. The shortcomings of linear models for explicative purposes have been very well documented. 12~7'28 It is not surprising that BMI at 4 and 6 y of age do not appear to be significant in the regression equations despite the fact that they are significantly correlated with height at age 14. A look at the tolerances and at the autocorrelation matrices shows very clearly that the BMI at 4 and 6 are more affected by collinearity than the BMI at ages 1 and 12, which are highly correlated only with BMI at ages 4 and 6, respectively. The comparative analysis of the BMI at different ages be-
0.8
0.6
0.4
0.2
0
J 1
i
I 4
12
14
A G E (Years)
BOyS
0.19
"4-" Gids
FIG. 1. Association of the factor scores on the first longitudinal component with BMI at different ages.
FIG. 3. Path diagram and coefficients for girls. Abbreviations as in Figure 2.
B O D Y M A S S INDEX A N D G R O W T H
421 TABLE XI.
MATRIX OF ACTUAL AND ESTIMATED CORRELATIONS BETWEEN CHOSEN PREDICTORS FOR HEIGHT (HT) AT AGE 14 IN BOYS
BMI1 BMI4 BMI6 BMI12 BMI14 SSD HT14
BMI1
BMI4
BMI6
1.00 0.51 (0.51) 0.28 (0.29) 0.11 (0.14) 0.10 (0.11 ) 0.17 (0.21) 0.45 (0.47)
-1.00
---
0.50 (0.50) 0.13 (0.17) 0.09 (0.09) 0.16 (0.07) 0.36 (0.40)
1.00
BMI12
BMI14
SSD
HT14
m
m
m
0.52 (0.52) 0.14 (0.14) 0.40 (0.34) 0.46 (0.46)
1.00
0.32 (0.31) 0.41 (0.42) 0.59 (0.62)
1.00 0.55 (0.57) 0.03 (0.03)
1.00
0.43 (0.40)
1.00
Estimated correlations in parentheses.
tween boys and girls shows very similar mean values at 1, 6, and 14 y of age. Slight differences are found at 4 and 12 y of age when the first and second adiposity rebounds take place in girls. At those ages, the mean BMI is slightly higher in girls. At 4 y of age, girls catch up with boys in height and are about the same weight; at age 12 girls are taller and heavier than boys, a fact that corroborates the findings of Garn and LaVelle 29 and Himes and Roche 3° in the sense that stature is not independent of total body fat. The first component yielded by the L P C A in both sexes is useful to describe the whole growing process. It has similar correlations with measurements of height at all ages, although a little lower with height at age 1 in girls. The B M I at 4, 6, and 12 y of age in girls and at age 12 in boys is a very good proxy for growth and not only for the height attained at a given age. This difference between sexes con-
cerning the association of body bulk with height is consistent with the pattern of correlations among serial measurements of the BMI shown in Table V. The descriptive results of Tables II and III show that bulkier boys and girls will tend to have a faster or earlier sexual development than their lighter peers. This result suggests that sexual development and maturation are, to some extent, playing an intermediate role in the influence of infant fatness on height at age 14. The relation could be stated in the following terms: heavier or bulkier boys and girls tend to have a faster sexual development and therefore a faster growth. The previous considerations materialize in the theoretical model set forth in the set ( 1 ) of path equations depicted in the path diagrams of Figures 2 and 3 for boys and girls, respectively. The path coefficients show the consistent influence of the BMI at different ages on height at age 14, both directly
TABLE XII. MATRIX OF ACTUAL AND ESTIMATED CORRELATIONS BETWEEN CHOSEN PREDICTORS FOR HEIGHT (HT) AT AGE 14 IN GIRLS
BMI1 BMI4 BMI6 BMII 2 BMI14 SSD HT14
BMI1
BMI4
BMI6
1.00 0.74 (0.74) 0.54 (0.54) 0.50 (0.49) 0.28 (0.28) 0.39 (0.43) 0.55 (0.54)
-1.00
---
0.74 (0.74) 0.58 (0.57) 0.35 (0.34) 0.43 (0.45) 0.59 (0.57)
1.00 0.65 (0.65) 0.49 (0.49) 0.28 (0.40) 0.58 (0.58)
BMI12
BMI14
SSD
m
HT14 m
m
1.00
0.75 (0.75) 0.58 (0.62) 0.61 (0.61)
1.00 0.59 (0.59) 0.35 (0.36)
Estimated correlations in parentheses. BMI = body mass index, SSD = stage of sexual development.
1.00
0.49 (0.53)
1.00
422
BODY MASS INDEX AND GROWTH
and indirectly through the process of sexual development. The correlations among serial measurements of BMI are much lower in boys than in girls, a fact that confirms that body bulk in boys is much more influenced by environmental factors. Infant fatness can influence height at age 14 independently of childhood fatness. Figures 2 and 3 show that the body bulk at age 1 has a non-negligible direct effect on height at age 14, which is higher in boys (path coefficient = 0.38) than in girls (path coefficient = 0.28). The path connecting BMI at 1 and 12 y of age directly with height at age 14 shows higher path coefficients in boys, whereas the indirect path mediated by sexual development is much more important in girls. This may be due to the fact that a larger proportion of girls have completed their growing process at age 14. If postpubertal height data were available, say at 16 or 18 y of age, the direct and indirect effects in boys would probably be more balanced and would resemble that of girls at 14 y of age.
Although the path models are based on several restrictive assumptions, namely, the Markovian nature of the BMI, the absence of direct influence of the BMI at age 14 on height at that same age. Although it neglects the direct effect on height at age 14 of BMI at 4 and 6 y of age, it is coherent and tenable as shown by the good approximation to actual correlations through the correlations generated by the path coefficients yielded by the model. The path diagrams together with Tables II and III show that early fatness increases height at age 14 by two different mechanisms whose relative importance is different in boys and girls, namely, a direct one that leads from energy excess to energy storage to increased lean body mass and finally to increased linear growth, and an indirect one that makes bulkier boys and girls have a faster sexual development and therefore a faster growth.
REFERENCES 1. Cheek DB, Schultz RB, Parra A. Overgrowth of lean and adipose tissues in adolescent obesity. Pediatr Res 1970;4:268 2. Forbes GB. Body composition in adolescence. In: Falkner F, Tanner JM, eds. Human growth. New York: Plenum, 1978 3. Forbes GB. Body composition in adolescence. In: Nutrition and child health. Perspectives for the 1980"s. New York: Alan R. Liss, 1981:55 4. Vignolo M, Naselli A, DiBattista E, et al. Growth and development in simple obesity. Eur J Pediatr 1980; 147:242 5. Johnston FE, Mack RW. Obesity, stature and one year relative weight of 15-year-old youths. Human Biol 1980;52:35 6. Rona RJ, Chinn S. National study on health and growth: social and biological factors associated with height of children from ethnic groups living in England. Ann Human Biol 1986; 13:453 7. Weiner JS, Lourie JA. Human biology: a guide to field methods. International Biologic Programme, Handbook No. 9. Oxford: Blackwell, 1969 8. Jord~inJR. Desarrollo humano en Cuba. La Habana: Editorial Cientifico-Ttcnica, 1979:35 9. Tanner JM. Growth at adolescence. 2nd ed. Oxford: Blackwell Scientific Publications, 1962 10. Mueller WH. The use of multivariate biometric methods for the analysis of human growth data. In: Borms J, Hanspie R, Sand A, Susanne C, Hebbelinck M, eds. Human growth and development. New York: Plenum Press, 1984:775 11. Bacallao J. M~todos estad(sticos en los estudios de crecimiento y desarrollo. Serie Ciencia y Tecnolog[a en Salud (No. 6). La Habana: Instituto Superior de Ciencias Mtdicas, 1987 12. Kerlinger FN, Pedhazur EJ. Multiple regression in behavioral research. New York: Holt, Rinehart and Winston, 1973 13. Amador M, Bacallao J, Hermelo M. Adiposity and growth: relationship of stature at fourteen years with relative body weight at different ages and several measures of adiposity and body bulk~ Eur J Clin Nutr 1992;46:213 14. Rolland-Cachera MF, Semp6 M, Guilloud-Bataille M, et al. Adiposity indices in children. Am J Clin Nutr 1982;36:178 15. Rolland-Cachera MF, Bellisle F. No correlation between adiposity
16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
and food intake: why are working class children fatter? Am J Clin Nutr 1986;44:779 Cole TJ. A critique of the NCHS weight for height standard. Human Biol 1985;57:183 Cole TJ. Weight/height p compared to weight/height 2 for assessing adiposity in childhood: influence of age and bone age on p during puberty. Ann Hum Biol 1986; 13:433 RoUand-Cachera MF, Deheeger M, Guilloud-Bataille M, et al. Tracking the development of adiposity from one month of age to adulthood. Ann Human Biol 1986; 14:219 Chinn S, Rona RJ, Gulliford MC, et al. Weight for height in children aged 4 to 12 years: a new index compared with the normalized body mass index. Eur J Clin Nutr 1992;46:489 Byard PJ, Siervogel RM, Roche AF. Age trends in transmissible and non-transmissible components of family resemblance for stature. Ann Human Biol 1988; 15:111 Stunkard AJ, Harris JR, Pedersen NL, et al. The body mass index of twins who had been reared apart. N Engl J Med 1990;322:1483 Kramer MS, Barr RG, Leduc DG, et al. Determinants of weight and adiposity in the first year of life. J Pediatr 1985; 106:10 Rolland-Cachera MF, Cole TJ, Semp6 M, et al. Body mass index variations: centiles from birth to 87 years. Eur J Clin Nutr 1991;45:13 Paffzkov~i J. Growth and growth velocity of lean body mass and fat in adolescent boys. Pediatr Res 1976; 10:647 Garn SM, LaVelle M, Rosenberg KR, et al. Maturational timing as a factor in female fatness and obesity. Am J Clin Nutr 1986;43:879 Rolland-Cachera MF, Deheeger M, Bellisle F, et al. Adiposity rebound in children: a simple indicator for predicting obesity. Am J Clin Nutr 1984;39:129 Bibby J. The general linear model--a cautionary tale. In: O'Muircheartaigh CA, Payne C, eds. The analysis of survey data. Vol. 2. Modelfitting. New York: Wiley & Sons, 1977:35 Achen C. Interpreting and using regression. Beverly Hills: Sage Publications, Sage University Press, 1983 Garn SM, LaVelle M. Two-decade follow-up of fatness in early childhood. Am J Dis Child 1985; 139:181 Himes JH, Roche AF. Subcutaneous fat and stature: relationship from infancy to adulthood. Ann Human B iol 1985; 12 (Suppl. 1 ):55
NUTRITIONAL
INVESTIGATION
Nutrition Vol. 12, No. 6, 1996
Body Mass Index at Different Ages and Its Association With Height at Age 14 and With the Whole Growing Process MANUEL AMADOR, MD, PHD, JORGE BACALLAO, MSC, AND MIRTA HERMELO, MD, PHD From the Institute of Nutrition and Food Hygiene and the Higher Institute of Medical Sciences, Havana, Cuba Date accepted: 15 September 1995 ABSTRACT The relevance of the association of the body mass index (BMI) at 1, 4, 6, and 12 years of age with the growing process and its capacity for predicting height at age 14 was investigated in a sample of 354 adolescents (182 boys and 172 girls). Regression analysis showed that body bulk at various ages, as expressed by the BMI is closely related with the height attained at age 14, and longitudinal principal components analysis suggested that it is also associated with the whole growing process. The way in which BMI affects height could be related with the stage of sexual development, which seems to play an intermediate role in the pathway linking body bulk and height. Nutrition 1996; 12:416-422 Key words: body mass index, childhood, adolescence, body bulk and growth, longitudinal principal components analysis, stage of sexual development, adiposity
INTRODUCTION In children and adolescents, the association between height and weight is well known. Not quite as obvious is the association between height and relative weight. It is, however, a wellestablished fact that overfat children are usually taller than their lean peers of the same age and sex. A generally accepted explanation is that this is due to the increase of lean tissues that usually follows a positive balance between energy intake and expenditure. ~-3 The sequence "energy excess ~ energy storage --, increased lean body mass --, increased linear growth" is commonly observed among overfat growing subjects 4 and could be the expression of an underlying causal path that links several biological events with a common nutritional background. Johnston and Mack, 5 in a study of youths aged 9 - 1 5 y, found that those who had a relative weight above 1 SD at 1 y were on average 2 cm taller than those who had a relative weight below - 1 SD. Rona and Chinn 6 reported a positive correlation between birthweight and height of school ages in a study of 13,107 boys and girls, carried out among different ethnic groups in England. The present study intends to assess th'~ extent to which body bulk at different ages is associated with height at age 14 and with the growing process as a whole and to investigate the role
played by sexual development in the association between body bulk and height. SUBJECTS AND METHODS In 1972, a longitudinal study on weight and height in children aged 12 mo (___2wk) was initiated in one municipality in Havana. Those children have been followed up and remeasured three times during their lives: at preschool age (3.8-4.2 y), upon enrollment at the elementary school (5.8-6.2 y), and upon enrollment at high school ( 11.8-12.2 y). From the obstetric card of their mothers (a document kept for all pregnant women in Cuba for prenatal controls and other effects, which they are requested to conserve), birthweight was retrieved in all cases. In 1986, all students from two high schools at the municipality of Boyeros in Havana (who made up a subsample of the original sample for the follow-up study) with ages ranging from 13.6 to 14.5 y were selected for the present study if their birthweight was 2500 g or more. They made up a nonprobabilistic sample of 354 healthy adolescents ( 182 boys and 172 girls). Schools in Cuba provide a very useful and convenient sampling frame. Within a given municipality, at the very least, the socioeconomic differences that could have some impact on income, access to food sources, and, subsequently, on the nutritional condition are negligible if they exist at all. Both high schools
Correspondence to: Manuel Amador, MD, PhD, Institute of Nutrition and Food Hygiene, Calzada de Infanta 1158, La Habana 10300, Cuba.
Nutrition 12:416-422, 1996 ©Elsevier Science Inc. 1996 Printed in the USA. All rights reserved.
ELSEVIER
0899-9007/96/$15.00 PII: S0899-9007(96)00097-4
BODY MASS INDEX AND GROWTH
417
might claim to be representative of the population of high schools in Havana. In addition, education is compulsory up to the third year of high school, or equivalent level in Cuba. Records on body weight and height at 1, 4, 6, and 12 y of age were kept for all the subjects in the sample. Body weight and height at age 14 were also measured. The measurements on body weight were made in kilograms to the nearest 100 g with Detecto scales. Supine length and stature were measured in centimeters to the nearest millimeter with Holtain infantometers and stadiometers, respectively. The methodology used for the measurements was that recommended by the International Biologic Programme 7 and the Cuban National Child Growth Study. 8 At 12 and 14 y of age, the stage of sexual development (SSD) was determined according to Tanner 9 and the decimal age 7 was recorded. The body mass index (BMI; kg/m 2) was calculated at 1, 4, 6, 12, and 14 y of age. The supine length was missing from most obstetric cards, and for that reason, the BMI at birth was not included in the study. All measurements were taken by the same well-trained anthropometrist with vast experience in both Cuban National Growth Studies of 1972 and 1982. The measurements at age 14 were performed twice and averaged and were all checked by one of the authors and found to fulfill the required standards of precision.
Data Analysis All analyses were carried out separately in boys and girls. Pearson partial correlation coefficients were computed and tested for significance between height at 14 and BMI at 1, 4, 6, 12, and 14 y of age. The control variable in the partial correlations was decimal age because around 14 y of age, height changes very quickly. A multiple linear regression was fitted for height at 14 on the BMI at 1, 4, 6, and 12 y of age. BMI at age 14 was purposefully omitted from the set of regressors. A matrix of autocorrelations among heights at different ages was calculated and factor analyzed by means of longitudinal principal components analysis (LPCA). ~°'H Factor scores on the unrotated components were correlated with the BMI at different ages. On the sample classified according to the stage of sexual development, descriptive statistics were obtained for the BMI at the ages already mentioned. Finally, a path analysis model j2 relating height at age 14
with the different measurements of the BMI and with SSD was fitted, and the corresponding path diagram was built. The expected correlations emerging from the model were compared with the actual correlations among the variables in order to verify the adequacy of the model. All calculations were performed with SYSTAT, release 3.0. RESULTS Table I contains descriptive statistics for body weight, height, and BMI at different ages for both sexes. Means and SDs of the BMI at 1, 4, 6, 12, and 14 y of age were computed for all subjects classified according to their SSD at 14. For every age considered, there was a significant difference between the subjects classified according to their SSD at 14. With the only exception of age 4 in boys, significant differences are found in the BMI of subjects classified according to their SSD at age 14. The highest values of the BMI are found among subjects in stage 5 at 14 y and the lowest among those in stage 3 at that age. This holds for both sexes and means that bulkier boys or girls at age 1, 4, or 6 tend to mature earlier. These descriptive results are shown in Tables II and III for boys and girls, respectively. Table IV contains the partial correlations, controlled for decimal age between height at 14 and the BMI at various ages for both sexes. The lowest correlation is the one that involves the BMI at age 14. All correlations except this one are highly significant. The pattern of associations is very similar for both sexes. Table V is the matrix of autocorrelations between repeated measurements of the BMI. The correlations are considerably higher for girls and are also higher between contiguous measurements of the BMI for both sexes. Tables VI and VII contain the results of the multiple linear regression equations for boys and girls, respectively. Both regressions show a very good fit, with significant F values and a very high percentage of variance explained. The relative pattern of the parameters is also very similar in both sexes: the parameters affecting BMI4 and BMI6 are not significant and those affecting BMI1 and BMI12 are significant. This is due not only to the predictive capacity of the latter variables but also to the fact that each of them is less colinear with the rest of the predictors than BMI4 or BMI6. This is clearly shown by the tolerances.
TABLE I. BODY WEIGHT (BW), HEIGHT (HT), AND BODY MASS INDEX (BMI) AT DIFFERENT AGES FOR BOTH SEXES Boys (n = 182)
Girls (n = 172)
Ages (y)
BW
HT
BMI
BW
HT
BMI
1
10.33 (1.25) 16.19 (1.42) 20.51 (2.53) 43.94 (8.60) 56.70 (11.89)
74.8 (2.1) 101.7 (3.0) 114.8 (3.6) 147.6 (5.8) 164.2 (8.9)
18.4 (1.7) 15.8 (0.9) 15.8 (1.3) 18.7 (2.6) 21.2 (3.7)
10.24 (1.50) 16.79 (2.36) 20.29 (3.22) 45.11 (11.00) 53.45 (12.34)
73.5 (2.2) 101.6 (2.9) 114.5 (4.1) 148.9 (6.2) 157.5 (5.8)
18.8 (2.6) 16.9 (1.8) 15.5 (1.8) 20.4 (3.5) 21.4 (4.2)
4 6 12 14
Means and (standard deviations).
418
BODY MASS INDEX AND GROWTH TABLE II.
TABLE IV.
MEANS ± STANDARD DEVIATIONS OF BODY MASS INDEX (BMI) AT DIFFERENT AGES FOR BOYS CLASSIFIED ACCORDING TO THEIR STAGE OF SEXUAL DEVELOPMENT (SSD) AT 14 YEARS OF AGE
PARTIAL CORRELATIONS (CONTROLLED FOR DECIMAL AGE) BETWEEN HEIGHT AT 14 AND BODY MASS INDEX (BMI) AT 1, 4, 6, 12, AND 14 YEARS OF AGE FOR BOTH SEXES
BMI 1y 4y 6y 12 y 14 y
SSD= 3 (n = 45) 17.94 15.59 14.86 16.81 18.09
± 1.38 ± 0.71 ___0.39 ± 1.55 ± 1.83
SSD=4 (n = 107) 18.43 15.69 15.66 19.12 20.90
± 1.78 ± 1.00 ___ 1.38 ± 2.73 ± 3.73
SSD= 5 (n = 30) 19.09 15.88 16.17 20.58 25.05
F
± 1.43 3.19 ___0.76 0.66 ___ 1.01 10.09 ___2.02 17.52 __+ 1.24 32.39
Sex
BMI1
BMI4
BMI6
BMI12
BMI14
Boys Girls
0.45 0.55
0.36 0.59
0.46 0.58
0.59 0.61
0.03* 0.35
p 0.045 0.518" 0.000 0.000 0.000
* Not significant; the remaining correlations are significant for p -~ 0.001.
* Not significant. B M I 6 = p31BMI4 + e3 The matrix of autocorrelations a m o n g heights at different ages is represented in Table VIII for the two sexes, and the factor loadings matrices for each sex separately are s h o w n in Tables IX and X. In both sexes, the percentage of total variance explained b y the first two components is close to 90%. The first c o m p o n e n t describes a uniform pattern of growth with similar c o m p o n e n t loadings on height at 1, 4, 6, 12, and 14 y of age. Boys and girls with heights above average for their age are high scorers on this component. The second component, on the other hand, characterizes a nonuniform pattern of growth. Adolescents with the highest scores on this c o m p o n e n t were short until age 4 and experienced a rapid growth from then on. This second component, however, is a very marginal one for both sexes. Its associated Eigen value is considerably lower than 1. Figure 1 shows the correlations of the first c o m p o n e n t with the B M I at different ages for both sexes. All correlations are significant with the exception of those involving B M I at 14 y of age. There is a smooth but monotonous increase in the correlations from age 4 to 12 and a sharp decrease from age 12 to 14 where the association of the B M I with the growing process has no statistical significance. The scores on the second c o m p o n e n t are of marginal importance and therefore have not b e e n correlated with serial measurements of BMI. Figures 2 and 3 represent the path diagrams for boys and girls, respectively. Those diagrams with their path coefficients are the pictorial representation of the following path model:
B M I 1 2 = p41BMI6 + e4 B M I 1 4 = p s i B M I 1 2 + e5 SSD = p61BMI1 + p62BMI4 + p63BMI6 + P64BMI12 + p65BMI14 + e6 HT14 = pT~BMII + PTaBMI12 + P76SSD + e7
(1)
where the ei stand for error terms and the Pu are the path coefficients. The assumptions implicit in this model are as follows: 1) el denote error terms that condense the influence of m a n y exogenous variables and are mutually uncorrelated and independent of all the endogenous variables in the model, 2 ) the B M I at any age depends directly only on the value of the same variable at the previous age recorded, 3 ) HT14 depends directly only on B M I I and B M I 1 2 and on SSD, and 4 ) SSD at age 14 is influenced by the body bulk expressed by the BMI. Tables XI and XII show the actual and the estimated correlation coefficients a m o n g values of the BMI, the SSD, and height at 14 y of age for boys and girls, respectively. The estimated correlations are those generated by the assumptions underlying the path analysis models. There is a fairly good aproximation between actual and predicted correlations.
TABLE V.
BMI1 = e~ MATRIX OF AUTOCORRELATIONS AMONG REPEATED MEASUREMENTS OF BODY MASS INDEX (BMI) FOR BOTH SEXES
B M I 4 = p2~BMI1 + e2 TABLE III. MEANS ± STANDARD DEVIATIONS OF BODY MASS INDEX (BMI) AT DIFFERENT AGES FOR GIRLS. CLASSIFIED ACCORDING TO THEIR STAGE OF SEXUAL DEVELOPMENT (SSD) AT 14 YEARS OF AGE
BMI1
BMI4
BMI6
BMI12
BMI14 0.10
BMI1
BMI4 BMI 1y 4y 6y 12 y 14 y
SSD= 3 (n = 9) 17.18 15.23 14.96 16.15 18.22
± ± ± ± ±
1.72 0.65 0.63 1.48 2.23
SSD = 4 (n = 85) 17.85 15.73 14.90 18.41 19.24
___2.13 ___ 1.45 ± 1.22 ± 2.35 ± 2.59
SSD = 5 (n = 79) 20.18 17.36 16.41 23.07 24.17
± ± _ ± ±
2.62 1.84 2.00 3.15 3.99
F 15.89 17.63 15.46 41.18 38.51
p 0.000 0.000 0.000 0.000 0.000
BMI6 BMI12
1.00
0.51
0.28
0.11
1.00
0.74
0.54
0.50
0.28
--
1.00
0.50
0.13
0.09
--
1.00
0.74
0.58
0.35
--
--
1.00
0.52
0.14
--
--
1.00
0.65
0.49
--
--
--
1.00
0.32
--
1.00
0.75
--
BMI14 Girls in italic.
--
.
.
.
.
1.00
.
.
.
.
1.00
BODY MASS INDEX AND GROWTH
419
TABLE VI.
TABLE VIII.
RESULTS OF THE MULTIPLE REGRESSION MODEL OF HEIGHT AT AGE 14 ON BODY MASS INDEX (BMI) AT DIFFERENT AGES FOR BOYS
MATRIX OF AUTOCORRELATIONS AMONG REPEATED MEASUREMENTS OF HEIGHT (HT) FOR BOTH SEXES
Variable
Coeff.
SE
Tolerance
t
p
Constant BMI1 BMI4 BMI6 BMI12
77.26 1.71 1.27 0.12 1.80
9.61 0.37 0.76 0.57 0.23
-0.73 0.58 0.55 0.72
8.04 4.60 1.66 0.21 7.72
0.00" 0.00" 0.10 0.83 0.00"
HT 1
HT4
1.00
0.79
1.00
0.71
1.00 1.00
HT1 HT4 HT6 HT12
* Significant predictors, R2 = 0.55, F = 38.48, p --< 0.001.
HT14 DISCUSSION A m o n g environmental factors, the balance of energy and nutrients play a crucial role in the growing process: intake above expenditure leads to an excessive storage of energy in the form of fat and to an increase of lean tissues. W h e n this happens during a period of faster growth, the effects on linear dimensions are more relevant and the growth rate is even more increased as a result of the adaptive process to energy unbalance. In a previous paper, we showed that relative body weight at different ages ( 1, 4, 6, and 12 y) might be useful to predict height at 14.13 Highly significant differences were found for height at 14 w h e n children were grouped according to their percentile distribution of weight for height. In addition, height was proven to be more strongly related with indicators of lean body mass than with indicators of adiposity, especially in boys, and SSD was also found to be closely associated with height at fourteen. Although relative weight and B M I are both measures of body bulk (because they express the amount of adiposity and of lean tissues), the latter is generally accepted as a suitable measure of adiposity in children, ~4-17 which, in addition, is independent of height. 18 In the present study, the correlations of the B M I at different ages with height at age 14 are highly significant, with the only exception of B M I at age 14 in boys. The correlations are higher in girls for all ages. A l t h o u g h there is m u c h controversy as to the selection and use of an indicator of body mass, the Quetelet index ( w e i g h t / height z) is by far the most frequently used for the assessment of the nutritional condition in growing subjects 14-18 despite its limitations for distinguishing between lean and fat body mass and the recent evidence that it has an age-dependent association
TABLE VII. RESULTS OF THE MULTIPLE REGRESSION MODEL OF HEIGHT AT AGE 14 ON BODY MASS INDEX (BMI) AT DIFFERENT AGES FOR GIRLS Variable
Coeff.
SE
Tolerance
t
p
Constant BMI1 BMI4 BMI6 BMI12
123.17 0.45 0.34 0.54 0.58
3.64 0.22 0.39 0.35 0.15
-0.44 0.29 0.38 0.55
33.81 2.04 0.88 1.54 3.96
0.00" 0.04* 0.38 0.13 0.00"
* Significant predictors, R2 = 0.48, F = 28.01, p --< 0.001.
HT6
HT 12
HT 14
0.76
0.73
0.72
0.57
0.56
0.58
0.77
0.72
0.68
0.82
0.84
0.79
--
--
1.00
0.82
0.79
--
--
1.00
0.89
0.81
--
--
--
1.00
0.85
--
--
--
1.00
0.92
.
.
.
.
1.00
.
.
.
.
1.00
Girls in italic.
with height and increasing variance with age, even after being log-transformed. 19 At most pediatric ages w e i g h t / h e i g h t squared has been shown to be more independent of height than other BMIs. t8 G r o w t h in height is influenced by genetic and environmental factors and by the interaction of both. During childhood, especially in males, it is most susceptible to the environmental influence represented by factors associated with diet and health. 2° There is no general agreement, however, as to the relative influence of genetics and e n v i r o n m e n t on the BMI. Stunkard et al. z~ considered that environmental factors have little or no influence at all, whereas Kramer et a l Y believed that adiposity and therefore body bulk and B M I are modified by environmental effects. In the present study, the maturation rate before 12 y of age was not available, hence the genetic background and the relative effects of genetics and e n v i r o n m e n t on body bulk could not be established. Nevertheless, the data available at ages 12 and 14 suggest that body bulk, as given by the BMI, is related with height through a chain of associations only partly mediated by maturation and sexual development. Johnston and M a c k 5 found no association between skeletal TABLE IX. FACTOR LOADINGS FOR THE FIRST TWO COMPONENTS YIELDED BY THE PRINCIPAL COMPONENTS ANALYSIS ON THE AUTOCORRELATION MATRIX FOR REPEATED MEASUREMENTS OF HEIGHT (HT) IN BOYS Components Variables
I
II
HT1 HT4 HT6 HT12 HT14
0.89 0.88 0.93 0.93 0.91
-0.28 -0.38 0.07 0.25 0.32
Percentage of total variance explained Eigenvalue
82.1 4. I 1
7.8 0.39
420
BODY MASS INDEX AND G R O W T H TABLE X.
FACTOR LOADINGS FOR THE FIRST TWO COMPONENTS YIELDED BY THE PRINCIPAL COMPONENTS ANALYSIS ON THE AUTOCORRELATION MATRIX FOR REPEATED MEASUREMENTS OF HEIGHT (HT) IN GIRLS Components Variables
I
II
HT1 HT4 HT6 HT12 HT14
0.75 0.93 0.92 0.95 0.93
-0.65 -0.09 0.18 0.24 0.19
Percentage of total variance explained Eigenvalue
80.8 4.04
11.1 0.55
maturation, height, and obesity in 15-y-old youths whose 1-y relative weights were known. Their findings suggest that the influence of relative weights during adolescence on height at 15 is independent of the rate of skeletal maturation. Although BMI is not a measure of fat body mass alone, its changes across ages resembles very much that of skinfolds and fat width measurements. 2~ Because no data on bone age, body composition, or other indicators of maturation were available, our study is based on the generally accepted assumption that BMI is a good proxy for adiposity. '4-17 Clear nutritional implications emerge from the conclusion that weight/height 2 at different ages is associated with height at age 14 and with growth in height viewed as a process. The highest correlations with height at age 14 for both sexes were found with the BMI at age 12. This is a critical period of growth that is related with the onset of pubertal changes and with the acceleration of lean tissue accretion. ~8'24Children approaching puberty get relatively heavy and relatively tall. BMI at age 12 is a proxy for early puberty, and therefore it is a good predictor of taller children. It is also the only period during childhood where body weight/height 2 and height have been found to be significantly correlated. ~4The correlation of height at age 14 is lower with BMI at that same age than with the
1
~
~
f 0.09
FIG. 2. Path diagram and coefficients for boys. BMI at 1 y = BMI1, 4 y = BMI4, 6 y = BMI6, 12y = BMI12, 14 y = BMI14. Stature at 14 r = HT14. previous measurements of BMI at 1, 4, 6, and 12 y. BMI at age 14 might reflect current but recent adiposity with no real bearing on the growth attained at that age. The BMI at 1 y of age is mainly the expression of the fast increase of adiposity that takes place during the first year of life and is a good predictor of height at age 14. The correlations of height at age 14 with the BMI at 4 y of age are much higher in girls than in boys. Girls experience an earlier adiposity rebound (from 3.0 to 5.5 y); in addition, they are expected to mature earlier and to be taller at 14 y.25 The so-called early adiposity rebound occurs in boys with a lag of almost 2 y with respect to girls and is independent of the degree of adiposity at 1 y.26 A very interesting fact is that although the BMI at all ages considered in this study is more strongly correlated with height at age 14 in girls than in boys, the regression equation based on all the measurements of the BMI taken jointly explains a higher percentage of variance in boys than in girls. The explanation to this can be found in the structure of the autocorrelation matrices among the BMIs for both sexes. The autocorrelations are much lower for boys, so that when all the variables are taken together, there is less multicollinearity and therefore less redundancy in the predictors. The shortcomings of linear models for explicative purposes have been very well documented. 12~7'28 It is not surprising that BMI at 4 and 6 y of age do not appear to be significant in the regression equations despite the fact that they are significantly correlated with height at age 14. A look at the tolerances and at the autocorrelation matrices shows very clearly that the BMI at 4 and 6 are more affected by collinearity than the BMI at ages 1 and 12, which are highly correlated only with BMI at ages 4 and 6, respectively. The comparative analysis of the BMI at different ages be-
0.8
0.6
0.4
0.2
0
J 1
i
I 4
12
14
A G E (Years)
BOyS
0.19
"4-" Gids
FIG. 1. Association of the factor scores on the first longitudinal component with BMI at different ages.
FIG. 3. Path diagram and coefficients for girls. Abbreviations as in Figure 2.
B O D Y M A S S INDEX A N D G R O W T H
421 TABLE XI.
MATRIX OF ACTUAL AND ESTIMATED CORRELATIONS BETWEEN CHOSEN PREDICTORS FOR HEIGHT (HT) AT AGE 14 IN BOYS
BMI1 BMI4 BMI6 BMI12 BMI14 SSD HT14
BMI1
BMI4
BMI6
1.00 0.51 (0.51) 0.28 (0.29) 0.11 (0.14) 0.10 (0.11 ) 0.17 (0.21) 0.45 (0.47)
-1.00
---
0.50 (0.50) 0.13 (0.17) 0.09 (0.09) 0.16 (0.07) 0.36 (0.40)
1.00
BMI12
BMI14
SSD
HT14
m
m
m
0.52 (0.52) 0.14 (0.14) 0.40 (0.34) 0.46 (0.46)
1.00
0.32 (0.31) 0.41 (0.42) 0.59 (0.62)
1.00 0.55 (0.57) 0.03 (0.03)
1.00
0.43 (0.40)
1.00
Estimated correlations in parentheses.
tween boys and girls shows very similar mean values at 1, 6, and 14 y of age. Slight differences are found at 4 and 12 y of age when the first and second adiposity rebounds take place in girls. At those ages, the mean BMI is slightly higher in girls. At 4 y of age, girls catch up with boys in height and are about the same weight; at age 12 girls are taller and heavier than boys, a fact that corroborates the findings of Garn and LaVelle 29 and Himes and Roche 3° in the sense that stature is not independent of total body fat. The first component yielded by the L P C A in both sexes is useful to describe the whole growing process. It has similar correlations with measurements of height at all ages, although a little lower with height at age 1 in girls. The B M I at 4, 6, and 12 y of age in girls and at age 12 in boys is a very good proxy for growth and not only for the height attained at a given age. This difference between sexes con-
cerning the association of body bulk with height is consistent with the pattern of correlations among serial measurements of the BMI shown in Table V. The descriptive results of Tables II and III show that bulkier boys and girls will tend to have a faster or earlier sexual development than their lighter peers. This result suggests that sexual development and maturation are, to some extent, playing an intermediate role in the influence of infant fatness on height at age 14. The relation could be stated in the following terms: heavier or bulkier boys and girls tend to have a faster sexual development and therefore a faster growth. The previous considerations materialize in the theoretical model set forth in the set ( 1 ) of path equations depicted in the path diagrams of Figures 2 and 3 for boys and girls, respectively. The path coefficients show the consistent influence of the BMI at different ages on height at age 14, both directly
TABLE XII. MATRIX OF ACTUAL AND ESTIMATED CORRELATIONS BETWEEN CHOSEN PREDICTORS FOR HEIGHT (HT) AT AGE 14 IN GIRLS
BMI1 BMI4 BMI6 BMII 2 BMI14 SSD HT14
BMI1
BMI4
BMI6
1.00 0.74 (0.74) 0.54 (0.54) 0.50 (0.49) 0.28 (0.28) 0.39 (0.43) 0.55 (0.54)
-1.00
---
0.74 (0.74) 0.58 (0.57) 0.35 (0.34) 0.43 (0.45) 0.59 (0.57)
1.00 0.65 (0.65) 0.49 (0.49) 0.28 (0.40) 0.58 (0.58)
BMI12
BMI14
SSD
m
HT14 m
m
1.00
0.75 (0.75) 0.58 (0.62) 0.61 (0.61)
1.00 0.59 (0.59) 0.35 (0.36)
Estimated correlations in parentheses. BMI = body mass index, SSD = stage of sexual development.
1.00
0.49 (0.53)
1.00
422
BODY MASS INDEX AND GROWTH
and indirectly through the process of sexual development. The correlations among serial measurements of BMI are much lower in boys than in girls, a fact that confirms that body bulk in boys is much more influenced by environmental factors. Infant fatness can influence height at age 14 independently of childhood fatness. Figures 2 and 3 show that the body bulk at age 1 has a non-negligible direct effect on height at age 14, which is higher in boys (path coefficient = 0.38) than in girls (path coefficient = 0.28). The path connecting BMI at 1 and 12 y of age directly with height at age 14 shows higher path coefficients in boys, whereas the indirect path mediated by sexual development is much more important in girls. This may be due to the fact that a larger proportion of girls have completed their growing process at age 14. If postpubertal height data were available, say at 16 or 18 y of age, the direct and indirect effects in boys would probably be more balanced and would resemble that of girls at 14 y of age.
Although the path models are based on several restrictive assumptions, namely, the Markovian nature of the BMI, the absence of direct influence of the BMI at age 14 on height at that same age. Although it neglects the direct effect on height at age 14 of BMI at 4 and 6 y of age, it is coherent and tenable as shown by the good approximation to actual correlations through the correlations generated by the path coefficients yielded by the model. The path diagrams together with Tables II and III show that early fatness increases height at age 14 by two different mechanisms whose relative importance is different in boys and girls, namely, a direct one that leads from energy excess to energy storage to increased lean body mass and finally to increased linear growth, and an indirect one that makes bulkier boys and girls have a faster sexual development and therefore a faster growth.
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