Orthopaedics 244
Bone Mineral Content of Junior Competitive Weightlifters K. Virvidakist, E. Georgiou2, A. Korkotsidis3 , K. Ntalles2, C. Pro uka kis2 'Medical Committee of the Hellenic Weightlifting Federation Dept. of Med. Physics, Athens University Medical School, Athens, Greece 3Dept of Economic Sciences, Athens University, Athens, Greece
has been described (6, 8), we thought that it would be of interK. Virvidakis, E. Georgiou, A. Korkotsidis, K. Ntalles and C. Proukakis, Bone Mineral Content of Junior Competitive Weightlifters. mi Sports Med, Vol 11, No 3, pp 244-246, 1990.
Accepted after revision: September 19, 1989
It is suggested that practicing various sports can increase the bone mineral content (BMC). However, we were unable to find any reports indicating BMC changes in weightlifting, a sport which involves both extremities and spine and increases muscle mass as well. Therefore, we thought that it might be of interest to measure BMC in junior competitive weightlifters. On the occasion of a recent Junior World Championship we measured, by single photon absorptiometry, BMC in 59 young competitive male athletes (aged 15 to 20 years) from 14 countries. Several variables were taken into account for each subject, including race, record, age, height and weight. Multiple regression analysis was performed in order to assess the contribution of the above mentioned variables to the variablility of both distal and proximal BMC. Finally, athletes' BMCs were compared to matched sex and age normals. Our results suggest that junior competitive weightlifters have an
increased BMC, well above the age-matched controls' mean. It seems that the vigorous exercise of weightlifters tends to fade out any race or age-related BMC differences. Finally, weightlifters' BMC seems to be highly correlated with body weight and record.
tntroduction
A number of studies suggest that increased physical activity can prevent or even reverse the loss of bone mineral content (1, 12, 16, 19). Studies comparing athletes with non-athletes have shown that different types of exercise can result in an increase in the bone mineral content (2, 4, 21). Bone mineral content (BMC) measurements have previously been published for athletes practicing different sports including running, dancing, cycling and swimming. Since a clear an-
atomical relationship between body muscle and bone mass mt. J. Sports Med. 11(1990)244—246
GeorgThieme Verlag StuttgartNew York
est to measure BMC of competitive weightlifters, a sport which increases body muscle and, therefore, bone mass as well.
Subjects and Methods
On the occasion of the 14th Junior World Championship held in Athens, Greece, in May 1988, we measured BMC of participating young competitive male athletes from different parts of the world. A total of 59 male junior athletes (aged 15—20 years) from 14 countries gave informed consent and participated in the study. All athletes were members of the respective national teams. Bone mineral content, expressed in gr/cm3, of the non-dominant forearm was measured by single photon absorptiometry (Nuclear Data, model I 100a) by means of a 125j
source (100 mCi) with photopeak at 27 KeY. With this method, BMC is measured in the proximal and distal part of the forearm, containing trabecular bone in the order of 10% and 45% and with a precision of 1% and 1.5%, respectively (14). The BMCs of the athletes were compared with those of 91 young healthy male controls of matched age, with normal physical activity, from our own database of Greek citizens.
For each subject, the following variables were also measured: (1) Race (C), (2) the official record of each ath-
lete's total during 1988 (R), (3) age (A), (4) height (H), (5) weight (W) and, finally, training hours per week (TI), weeks (T2) and years of training (T3). From the above mentioned, two more variables were derived: (6) Training index (T) derived as the product ofTi *T2*T3 and (7) the Sinclair equivalent of each
athlete's record (20). Multiple regression analysis was performed including detailed analysis of residuals in order to assess the contribution of the above mentioned variables to the variability of both distal and proximal BMC. Scatter plots of BMC versus each of the explanatory variables revealed the existence of, more or less, linear relations. Nevertheless, and in
spite of the fact that residual plots did not suggest the use of transformations, quite a few were attempted, none of which offered a significant improvement over the models with untransformed variables. Also, some non-linear models (nonlinear in the parameters) were investigated with no success. Thus, given also the fact that the residuals did not indicate gross violations of assumptions of the method (ordinary least
Downloaded by: NYU. Copyrighted material.
Absfract
mt. J. Sports Med. 11(1990) 245
Bone Mineral Content of Junior Competitive Weightl(flers
DISTAL PROXIMAL
Table 1 Mean Bone Mineral Content in weightlifters and agematched controls
300-i 2.
No.
Distal±1 S. D. Proximal±1 S.D.
2. 2O
Athletes 59
Controls
1.74±0.20 1.95±0.24
1.15±0.13 1.38±0.13
91
I
E 1.
C)
1. 1.
•
Table 2 Coefficients of multiple determination (A2) of regressions of BMC on the variables under study in competitive junior weightlifters
us •.fl •II
Distal
Proximal
R2
R2
0.5
0.3 32.7
Variables# 1.0
0.80Fig. 1 Individual BMC values as compared to the mean age-matched controls.
S. D. of
1. 2. 3. 4. 5. 6. 7.
37.2 14.0 16.6
12.1
13.2 31.4 8.9 7.5
41.9 6.5 4.3
6 =Training Index, 7= Sinclair corrected record
we based our analysis on linear models on the untransformed variables. squares),
Table 3 Coefficients of multiple determination (R2), adjusted-fl2
Results
(adj-R 2) and t-ratios of best regressions of BMC on the variables under study in competitive junior weightlifters
The individual BMC values of the athletes in the study are presented in Fig. 1. Average BMC of athletes and sex-and-age-matched controls is shown in Table 1. It can easily be seen that the mean of athletes' BMC is more than two standard deviations above the age-matched controls' mean.
The contribution of each of the variables under study in explaining distal and proximal BMC changes is pre-
Distal Model
Variables
R2
adj-R2
2+3+4+7 2 3 4 7
52.5
49.1
2+3+4+5 2 3 4 5
52.6
t —5.6 —1.8 —3.0 —3.7
Proximal Model Variables*
A2
3+4+5+7
41.7 37.4
3 4 5 7
sented in Table 2. As can be seen from this table, single variable
models were unsuccessful in explaining a significant proportion of the variability in BMC. However, the best single predictors for both distal and proximal BMC were the record and the weight of the athlete. Sinclair corrected record and race did not exhibit strong linear relationships with athletes' BMC.
2+3+4+5
49.1 —1.5 —1.5 —2.9 —3.7
adj-R t
2 3 4 5
—1.3 —1.9 —4.0 —1.9
41.7 37.4 —1.9 —1.4 —2.1
—2.3
*: 2=Record, 3=Age, 4=Height, 5=Weight, 7=Sinclair corr.
We found the best models arising from all possible combinations among the seven variables under study. The four best models which exhibited the strongest linear relation with BMC (two for distal and two for proximal) are presented in Table 3. As can be seen, these models involve four variables, while the addition of more parameters worsened the quality of the regression in terms of adjusted R2. In all these models, five parameters were persistently involved, i. e. record, age, height, weight and Sinclair corrected record. Discussion
The role of exercise in bone dynamics is not yet
fully understood. A direct neural or mechanical stress or osseous blood flow changes are possible mechanisms for the ef-
record.
duction of bone (17). In humans, studies comparing athletes with non-athletes have shown that different types of exercise (i. e. running) can result in an increase of the bone mineral content (2, 4, 21). It is also reported that people engaged in different sports and occupations revealed hypertrophy of the dominant extremity, where a higher bone mass has been noted (10, Ii, 15). However, there are conflincting reports on whether by practicing different sports, the radius, which is predominantly
cortical bone, is affected, whereas the mineral content of the vertebrae, which have more trabecular bone, might be more sensitive. This, however, is not the case with weightlifting, where both the hands and the spine are involved.
fect of muscle activity on bone. Bone tissue adapts to functional forces acting upon it. Osteoblastic bone forming activity is stimulated by weight bearing or muscle tension stress through a still unkonwn mechanism (18). Studies on animals suggest that vigorous exercise may possibly increase the pro-
It has been reported that black individuals, as compared to caucasian ones, have increased total body calcium, bone density and larger muscle mass (3, 7, 9). The fact that, in our sample of athletes, race did not show to affect
Downloaded by: NYU. Copyrighted material.
#: 1=Race, 2=Record, 3=Age, 4Height, 5=Weight,
246 mt. J. Sports Med. 11(1990)
K. Virvidakis, E. Georgiou, A. Korkotsidis, K. Nta/les, C. Proukakis
References
BMC, could be explained by the assumption that the vigorous exercise these individuals performed by far outweighted any race differences.
The fact that the most important single variables in explaining BMC variations were body weight and record, two obviously inter-related variables, both strongly re-
Aloia J. F., Cohn S. H., Ostuni J. A., Cane R., Ellis K.: Prevention of involutional bone loss by exercise. Ann Intern Med 89: 356—358, 2
1978a.
Aloia J. F., Cohn S. H., Babu T., Abesamis C., Kalici N., Ellis K.: Skeletal mass and body composition in marathon runners. Metabolism, 27: 1793—1796, 1978b.
lated to muscle mass, clearly suggests that the latter increases BMC.
Cohn S., Abesamis C., Yasumura S., Aloia J., Zanzi J., Ellis K.: Comparative skeletal mass and radial bone mineral content in black and white women. Metabolism 26: 171—178, 1977.
Dalen N., Olsson K. C.: Bone mineral content and physical activity.Acta OrthopScand45: 170—174, 1974. Drinkwater B. L.: Maximizing bone mass in the premenopausal years: Positive and negative factors. In: Osteoporosis 1987. Christiansen C., Johansen J. S., Riis B. J., Eds, Osteopress, Copenhagen, Vol. l,p484—488, 1987. Doyle F., Brown J., LaChance C.: Relation between bone mass
Given the known relevance of age on bone mass, the fact that age contribution was not statistically significant in our sample of weightlifters could be explained by the combination of the small variability in age values (between 15
and 20 years) which our sample covered and the possibility that strenuous exercise increases BMC far more than age in the short age span we studied.
and muscle weight. Lancet 1: 391—393, 1970.
Dubovsky J., Dubovski E., Balcarek K., Yester M.: Differences between young black and white women in bone mineral and size by
Some observations could be made about the
Another possible explanation for the increased BMC in our sample could be the contribution of the possible use of anabolic steroids, which can cause a long-term increase
photon absorptiometry. In: Osteoporosis 1987. Christiansen C., Johansen J. S., Riis B. J., Eds, Osteopress, Copenhagen, Vol. 1 p 60—61, 1987.
Ellis K., Cohn S.: Correlation between skeletal calcium mass and muscle mass in men. JApplPhysiol 38: 455—460, 1975.
Heaney R.: Natural history of osteoporosis. In: Osteoporosis. Social and clinical aspects. Gennari C., Segre G., Eds, Excerpta Medica, Amsterdam, p87—93, 1983.
o Jones H., Priest J., Hayes W.: Humeral hypertrophy in response to exercise.JBoneJoiniSurg59: 204—208, 1977. 2 13
Christiansen C., Johansen J. S., Riis B. J., Eds, Osteopress, Copenhagen, Vol. 2,p 1226—1229,1987. 14 Nilas L., Borg J., Cotfredsen A., Christiansen C.: Comparison of
single- and dual- photon absorptiometry in postmenopausal bone 15 16
doping control during the championship, only one case (marked with an asterisk in Fig. 1) was proven positive. As can be seen, his BMC was not different from the group's mean.
It can be concluded that junior competitive weightlifters have a substantially increased BMC well above the age-matched controls' mean. It is evident that, due to their vigorous training, their increased BMC covers up any race or age-related difference. Finally, their BMC is highly correlated with body weight and record.
Need A., Horovitz M., Chatterton B., Robertson A., Nordin B.:
Effects of nadrolone decanoate and antiresorptive therapy on bone density of osteoporotic women. In: Osteoporosis 1987.
in BMC (13). This possibility is very difficult to exclude. How-
ever, among the 13 athletes of our sample who underwent a
King J., Breisford H., Tullos H.: Analysis of the pitching arm of the professional baseball pitcher. Clin Orthop 67: 116—123, 1969. Krolner B., Toft B.: Vertebral bone loss: an unheeded side effect of theurapeutic bed rest. Clin Sci 64: 537—540, 1983.
17 18
mineral loss. JNucl Med 26: 1257—1262, 1985. Nilsson B., Westlin M: Bone density in athletes. Clin Orthop 77: 179—182, 1971.
Orwoll E. S., Ferar J., Oviat S. K., Huntington K., McGlung M. R.: Swimming exercise and bone mass. In: Osteoporosis 1987. Christiansen C., Johansen J. S., Riis B. J., Eds, Osteopress, Copenhagen, Vol.2, p 494—498, 1987. Saville
P., Whyte M.: Muscle and bone hypertrophy. Positive ef-
fect of running exercise in the rat. Clin Orthop 77: 81—88, 1969. Schapira D.: Physical exercise in the prevention and treatment of osteoporosis: A review. JSocMed8l: 46 1—463, 1988. Smith E. L., Reddan W., Smith P. E.: Physical activity and calcium
modalities for bone mineral increase in aged women. Med. Sci 20
Sports Exerc 13: 60—64, 1981. Sinclair R.: Normalising the performances of athletes in Olympic
21
Weightlifting, Can JAppI Sport Sci 10:94—98,1985. Williams J. A., Wagner J., Wasnich R., Heilburn L.: The effect of
long distance running upon appendicular bone mineral content. Med Sci Sports Exerc 16: 223—227, 1984.
E. Georgiou M. D. 66—70, Imitou str.
Athens 11634
Greece
Downloaded by: NYU. Copyrighted material.
signs of the various coefficients, as they are exhibited in Table 3, always taking into account the fact that these are multivariable models in which the explanatory variables' intercorrelations may affect the sign and the magnitude of coefficients in intractable ways. Therefore, the direction of the effect of each variable on the response (BMC) may be obscured by the presence (or absence) of other variables in (from) the model. This observation may explain the opposite signs of Sinclair's record in models 1 and 2, as well as the consistently negative sign of height. With regard to the other variables, we point out the consistently positive signs of age, record and weight, a fact which seems to conform with previous statements about their direct relation with BMC (2, 5). Finally, the absolute t-ratio values are individually significant at the 5% or lower levels for most variables, with 1.3 being the smallest value encountered.
Bone Mineral Content of Junior Competitive Weightlifters K. Virvidakist, E. Georgiou2, A. Korkotsidis3 , K. Ntalles2, C. Pro uka kis2 'Medical Committee of the Hellenic Weightlifting Federation Dept. of Med. Physics, Athens University Medical School, Athens, Greece 3Dept of Economic Sciences, Athens University, Athens, Greece
has been described (6, 8), we thought that it would be of interK. Virvidakis, E. Georgiou, A. Korkotsidis, K. Ntalles and C. Proukakis, Bone Mineral Content of Junior Competitive Weightlifters. mi Sports Med, Vol 11, No 3, pp 244-246, 1990.
Accepted after revision: September 19, 1989
It is suggested that practicing various sports can increase the bone mineral content (BMC). However, we were unable to find any reports indicating BMC changes in weightlifting, a sport which involves both extremities and spine and increases muscle mass as well. Therefore, we thought that it might be of interest to measure BMC in junior competitive weightlifters. On the occasion of a recent Junior World Championship we measured, by single photon absorptiometry, BMC in 59 young competitive male athletes (aged 15 to 20 years) from 14 countries. Several variables were taken into account for each subject, including race, record, age, height and weight. Multiple regression analysis was performed in order to assess the contribution of the above mentioned variables to the variablility of both distal and proximal BMC. Finally, athletes' BMCs were compared to matched sex and age normals. Our results suggest that junior competitive weightlifters have an
increased BMC, well above the age-matched controls' mean. It seems that the vigorous exercise of weightlifters tends to fade out any race or age-related BMC differences. Finally, weightlifters' BMC seems to be highly correlated with body weight and record.
tntroduction
A number of studies suggest that increased physical activity can prevent or even reverse the loss of bone mineral content (1, 12, 16, 19). Studies comparing athletes with non-athletes have shown that different types of exercise can result in an increase in the bone mineral content (2, 4, 21). Bone mineral content (BMC) measurements have previously been published for athletes practicing different sports including running, dancing, cycling and swimming. Since a clear an-
atomical relationship between body muscle and bone mass mt. J. Sports Med. 11(1990)244—246
GeorgThieme Verlag StuttgartNew York
est to measure BMC of competitive weightlifters, a sport which increases body muscle and, therefore, bone mass as well.
Subjects and Methods
On the occasion of the 14th Junior World Championship held in Athens, Greece, in May 1988, we measured BMC of participating young competitive male athletes from different parts of the world. A total of 59 male junior athletes (aged 15—20 years) from 14 countries gave informed consent and participated in the study. All athletes were members of the respective national teams. Bone mineral content, expressed in gr/cm3, of the non-dominant forearm was measured by single photon absorptiometry (Nuclear Data, model I 100a) by means of a 125j
source (100 mCi) with photopeak at 27 KeY. With this method, BMC is measured in the proximal and distal part of the forearm, containing trabecular bone in the order of 10% and 45% and with a precision of 1% and 1.5%, respectively (14). The BMCs of the athletes were compared with those of 91 young healthy male controls of matched age, with normal physical activity, from our own database of Greek citizens.
For each subject, the following variables were also measured: (1) Race (C), (2) the official record of each ath-
lete's total during 1988 (R), (3) age (A), (4) height (H), (5) weight (W) and, finally, training hours per week (TI), weeks (T2) and years of training (T3). From the above mentioned, two more variables were derived: (6) Training index (T) derived as the product ofTi *T2*T3 and (7) the Sinclair equivalent of each
athlete's record (20). Multiple regression analysis was performed including detailed analysis of residuals in order to assess the contribution of the above mentioned variables to the variability of both distal and proximal BMC. Scatter plots of BMC versus each of the explanatory variables revealed the existence of, more or less, linear relations. Nevertheless, and in
spite of the fact that residual plots did not suggest the use of transformations, quite a few were attempted, none of which offered a significant improvement over the models with untransformed variables. Also, some non-linear models (nonlinear in the parameters) were investigated with no success. Thus, given also the fact that the residuals did not indicate gross violations of assumptions of the method (ordinary least
Downloaded by: NYU. Copyrighted material.
Absfract
mt. J. Sports Med. 11(1990) 245
Bone Mineral Content of Junior Competitive Weightl(flers
DISTAL PROXIMAL
Table 1 Mean Bone Mineral Content in weightlifters and agematched controls
300-i 2.
No.
Distal±1 S. D. Proximal±1 S.D.
2. 2O
Athletes 59
Controls
1.74±0.20 1.95±0.24
1.15±0.13 1.38±0.13
91
I
E 1.
C)
1. 1.
•
Table 2 Coefficients of multiple determination (A2) of regressions of BMC on the variables under study in competitive junior weightlifters
us •.fl •II
Distal
Proximal
R2
R2
0.5
0.3 32.7
Variables# 1.0
0.80Fig. 1 Individual BMC values as compared to the mean age-matched controls.
S. D. of
1. 2. 3. 4. 5. 6. 7.
37.2 14.0 16.6
12.1
13.2 31.4 8.9 7.5
41.9 6.5 4.3
6 =Training Index, 7= Sinclair corrected record
we based our analysis on linear models on the untransformed variables. squares),
Table 3 Coefficients of multiple determination (R2), adjusted-fl2
Results
(adj-R 2) and t-ratios of best regressions of BMC on the variables under study in competitive junior weightlifters
The individual BMC values of the athletes in the study are presented in Fig. 1. Average BMC of athletes and sex-and-age-matched controls is shown in Table 1. It can easily be seen that the mean of athletes' BMC is more than two standard deviations above the age-matched controls' mean.
The contribution of each of the variables under study in explaining distal and proximal BMC changes is pre-
Distal Model
Variables
R2
adj-R2
2+3+4+7 2 3 4 7
52.5
49.1
2+3+4+5 2 3 4 5
52.6
t —5.6 —1.8 —3.0 —3.7
Proximal Model Variables*
A2
3+4+5+7
41.7 37.4
3 4 5 7
sented in Table 2. As can be seen from this table, single variable
models were unsuccessful in explaining a significant proportion of the variability in BMC. However, the best single predictors for both distal and proximal BMC were the record and the weight of the athlete. Sinclair corrected record and race did not exhibit strong linear relationships with athletes' BMC.
2+3+4+5
49.1 —1.5 —1.5 —2.9 —3.7
adj-R t
2 3 4 5
—1.3 —1.9 —4.0 —1.9
41.7 37.4 —1.9 —1.4 —2.1
—2.3
*: 2=Record, 3=Age, 4=Height, 5=Weight, 7=Sinclair corr.
We found the best models arising from all possible combinations among the seven variables under study. The four best models which exhibited the strongest linear relation with BMC (two for distal and two for proximal) are presented in Table 3. As can be seen, these models involve four variables, while the addition of more parameters worsened the quality of the regression in terms of adjusted R2. In all these models, five parameters were persistently involved, i. e. record, age, height, weight and Sinclair corrected record. Discussion
The role of exercise in bone dynamics is not yet
fully understood. A direct neural or mechanical stress or osseous blood flow changes are possible mechanisms for the ef-
record.
duction of bone (17). In humans, studies comparing athletes with non-athletes have shown that different types of exercise (i. e. running) can result in an increase of the bone mineral content (2, 4, 21). It is also reported that people engaged in different sports and occupations revealed hypertrophy of the dominant extremity, where a higher bone mass has been noted (10, Ii, 15). However, there are conflincting reports on whether by practicing different sports, the radius, which is predominantly
cortical bone, is affected, whereas the mineral content of the vertebrae, which have more trabecular bone, might be more sensitive. This, however, is not the case with weightlifting, where both the hands and the spine are involved.
fect of muscle activity on bone. Bone tissue adapts to functional forces acting upon it. Osteoblastic bone forming activity is stimulated by weight bearing or muscle tension stress through a still unkonwn mechanism (18). Studies on animals suggest that vigorous exercise may possibly increase the pro-
It has been reported that black individuals, as compared to caucasian ones, have increased total body calcium, bone density and larger muscle mass (3, 7, 9). The fact that, in our sample of athletes, race did not show to affect
Downloaded by: NYU. Copyrighted material.
#: 1=Race, 2=Record, 3=Age, 4Height, 5=Weight,
246 mt. J. Sports Med. 11(1990)
K. Virvidakis, E. Georgiou, A. Korkotsidis, K. Nta/les, C. Proukakis
References
BMC, could be explained by the assumption that the vigorous exercise these individuals performed by far outweighted any race differences.
The fact that the most important single variables in explaining BMC variations were body weight and record, two obviously inter-related variables, both strongly re-
Aloia J. F., Cohn S. H., Ostuni J. A., Cane R., Ellis K.: Prevention of involutional bone loss by exercise. Ann Intern Med 89: 356—358, 2
1978a.
Aloia J. F., Cohn S. H., Babu T., Abesamis C., Kalici N., Ellis K.: Skeletal mass and body composition in marathon runners. Metabolism, 27: 1793—1796, 1978b.
lated to muscle mass, clearly suggests that the latter increases BMC.
Cohn S., Abesamis C., Yasumura S., Aloia J., Zanzi J., Ellis K.: Comparative skeletal mass and radial bone mineral content in black and white women. Metabolism 26: 171—178, 1977.
Dalen N., Olsson K. C.: Bone mineral content and physical activity.Acta OrthopScand45: 170—174, 1974. Drinkwater B. L.: Maximizing bone mass in the premenopausal years: Positive and negative factors. In: Osteoporosis 1987. Christiansen C., Johansen J. S., Riis B. J., Eds, Osteopress, Copenhagen, Vol. l,p484—488, 1987. Doyle F., Brown J., LaChance C.: Relation between bone mass
Given the known relevance of age on bone mass, the fact that age contribution was not statistically significant in our sample of weightlifters could be explained by the combination of the small variability in age values (between 15
and 20 years) which our sample covered and the possibility that strenuous exercise increases BMC far more than age in the short age span we studied.
and muscle weight. Lancet 1: 391—393, 1970.
Dubovsky J., Dubovski E., Balcarek K., Yester M.: Differences between young black and white women in bone mineral and size by
Some observations could be made about the
Another possible explanation for the increased BMC in our sample could be the contribution of the possible use of anabolic steroids, which can cause a long-term increase
photon absorptiometry. In: Osteoporosis 1987. Christiansen C., Johansen J. S., Riis B. J., Eds, Osteopress, Copenhagen, Vol. 1 p 60—61, 1987.
Ellis K., Cohn S.: Correlation between skeletal calcium mass and muscle mass in men. JApplPhysiol 38: 455—460, 1975.
Heaney R.: Natural history of osteoporosis. In: Osteoporosis. Social and clinical aspects. Gennari C., Segre G., Eds, Excerpta Medica, Amsterdam, p87—93, 1983.
o Jones H., Priest J., Hayes W.: Humeral hypertrophy in response to exercise.JBoneJoiniSurg59: 204—208, 1977. 2 13
Christiansen C., Johansen J. S., Riis B. J., Eds, Osteopress, Copenhagen, Vol. 2,p 1226—1229,1987. 14 Nilas L., Borg J., Cotfredsen A., Christiansen C.: Comparison of
single- and dual- photon absorptiometry in postmenopausal bone 15 16
doping control during the championship, only one case (marked with an asterisk in Fig. 1) was proven positive. As can be seen, his BMC was not different from the group's mean.
It can be concluded that junior competitive weightlifters have a substantially increased BMC well above the age-matched controls' mean. It is evident that, due to their vigorous training, their increased BMC covers up any race or age-related difference. Finally, their BMC is highly correlated with body weight and record.
Need A., Horovitz M., Chatterton B., Robertson A., Nordin B.:
Effects of nadrolone decanoate and antiresorptive therapy on bone density of osteoporotic women. In: Osteoporosis 1987.
in BMC (13). This possibility is very difficult to exclude. How-
ever, among the 13 athletes of our sample who underwent a
King J., Breisford H., Tullos H.: Analysis of the pitching arm of the professional baseball pitcher. Clin Orthop 67: 116—123, 1969. Krolner B., Toft B.: Vertebral bone loss: an unheeded side effect of theurapeutic bed rest. Clin Sci 64: 537—540, 1983.
17 18
mineral loss. JNucl Med 26: 1257—1262, 1985. Nilsson B., Westlin M: Bone density in athletes. Clin Orthop 77: 179—182, 1971.
Orwoll E. S., Ferar J., Oviat S. K., Huntington K., McGlung M. R.: Swimming exercise and bone mass. In: Osteoporosis 1987. Christiansen C., Johansen J. S., Riis B. J., Eds, Osteopress, Copenhagen, Vol.2, p 494—498, 1987. Saville
P., Whyte M.: Muscle and bone hypertrophy. Positive ef-
fect of running exercise in the rat. Clin Orthop 77: 81—88, 1969. Schapira D.: Physical exercise in the prevention and treatment of osteoporosis: A review. JSocMed8l: 46 1—463, 1988. Smith E. L., Reddan W., Smith P. E.: Physical activity and calcium
modalities for bone mineral increase in aged women. Med. Sci 20
Sports Exerc 13: 60—64, 1981. Sinclair R.: Normalising the performances of athletes in Olympic
21
Weightlifting, Can JAppI Sport Sci 10:94—98,1985. Williams J. A., Wagner J., Wasnich R., Heilburn L.: The effect of
long distance running upon appendicular bone mineral content. Med Sci Sports Exerc 16: 223—227, 1984.
E. Georgiou M. D. 66—70, Imitou str.
Athens 11634
Greece
Downloaded by: NYU. Copyrighted material.
signs of the various coefficients, as they are exhibited in Table 3, always taking into account the fact that these are multivariable models in which the explanatory variables' intercorrelations may affect the sign and the magnitude of coefficients in intractable ways. Therefore, the direction of the effect of each variable on the response (BMC) may be obscured by the presence (or absence) of other variables in (from) the model. This observation may explain the opposite signs of Sinclair's record in models 1 and 2, as well as the consistently negative sign of height. With regard to the other variables, we point out the consistently positive signs of age, record and weight, a fact which seems to conform with previous statements about their direct relation with BMC (2, 5). Finally, the absolute t-ratio values are individually significant at the 5% or lower levels for most variables, with 1.3 being the smallest value encountered.
