American Journal of Epidemiology
Copyright © 2003 by the Johns Hopkins Bloomberg School of Public Health
All rights reserved
Vol. 158, No. 6
Printed in U.S.A.
DOI: 10.1093/aje/kwg170
Influence of Participation in High-Impact Sports during Adolescence and Adulthood
on Bone Mineral Density in Middle-aged Men: A 27-Year Follow-up Study
Leen Van Langendonck1, Johan Lefevre1, Albrecht L. Claessens1, Martine Thomis1, Renaat
Philippaerts2, Katrien Delvaux3, Roeland Lysens4, Roland Renson1, Bart Vanreusel1, Bavo
Vanden Eynde5, Jan Dequeker6, and Gaston Beunen1
1 Department of Sport and Movement Sciences, Faculty of Physical Education and Physiotherapy, Catholic University Leuven,
Leuven, Belgium.
2 Department of Movement and Sports Sciences, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium.
3 Department of Physical Medicine–Rehabilitation, University Hospital Pellenberg, Pellenberg, Belgium.
4 Department of Rehabilitation Sciences, Faculty of Physical Education and Physiotherapy, Catholic University Leuven, Leuven,
Belgium.
5 Department of Kinesiology, Faculty of Physical Education and Physiotherapy, Catholic University Leuven, Leuven, Belgium.
6 Department of Rheumatology, University Hospital Gasthuisberg, Leuven, Belgium.
Received for publication March 20, 2002; accepted for publication February 25, 2003.
This study examined whether participation in high-impact sports during adolescence and adulthood contributes
to bone health in males aged 40 years. Data were analyzed on 154 Belgian men aged 13 years at study onset in
1969 and aged 40 years at the end of the 27-year follow-up. In a second analysis, subjects were divided into three
groups according to their sports participation history: participation during adolescence and adulthood in highimpact sports (HH; n = 18), participation during adolescence in high-impact sports and during adulthood in
nonimpact sports or no sports (HN; n = 15), and participation during adolescence and adulthood in nonimpact
sports or no sports (NN; n = 14). Body mass and impact loading during adulthood were significant predictors of
total body bone mineral density (BMD) and lumbar spine BMD. Analysis of variance revealed significant
differences for lumbar spine BMD between the HH (1.12 g/cm2) group and the HN (1.01 g/cm2) and NN (0.99 g/
cm2) groups (F = 5.07, p = 0.01). Total body BMD was also higher in the HH group at age 40 years, but not
significantly (F = 3.17, p = 0.0515). Covariance analyses for total body BMD and lumbar spine BMD, with body
mass and time spent participating in sports as covariates, confirmed these results. Continued participation in
impact sports is beneficial for the skeletal health of males aged 40 years.
adolescence; bone density; densitometry, x-ray; exercise; follow-up studies; men; sports
Abbreviations: BMD, bone mineral density; DXA, dual-energy x-ray absorptiometry; HH, subjects participating during
adolescence and adulthood in high-impact sports; HN, subjects participating during adolescence in high-impact sports and
during adulthood in nonimpact sports or no sports; NN, subjects participating during adolescence and adulthood in nonimpact
sports or no sports.
Osteoporosis is an increasing health care concern,
especially in industrialized countries, as populations age.
Although osteoporosis has traditionally been considered a
disease of the elderly, prevention is based on 1) maximizing peak bone mass during the growing years, 2) maintaining peak bone mass during adulthood, and 3) slowing
down accelerated bone loss in later years (1). Bone mass is
mostly genetically determined (2–4), but it can also be
influenced by environmental factors such as nutrition and
physical activity (1, 5, 6). Cross-sectional and longitudinal
studies of athletes have shown the beneficial influence of
physical activity on bone acquisition. These studies
provide evidence that especially high-impact sports have
an osteogenic effect (7–15).
Correspondence to Dr. Leen Van Langendonck, Faculty of Physical Education and Physiotherapy, Catholic University Leuven, Tervuursevest
101, B-3001 Leuven, Belgium (e-mail: [email protected]).
525
Am J Epidemiol 2003;158:525–533
526 Van Langendonck et al.
Although comparison of athletes participating in different
sports can give valuable information, the results must be
interpreted carefully because of the cross-sectional design
and the selectivity of the samples under study. However,
experimental studies examining the effect of physical
activity during childhood and adolescence support the
hypothesis that physical activity has a beneficial influence
on the skeleton during growth (16–23). Furthermore, most
experimental studies of adults have concluded that physical
activity is beneficial for bone health (24–34). Most of these
experimental studies focused on women, because
osteoporosis was considered primarily a woman’s disease.
Recently, the problem was also acknowledged in men (35).
Little is known about the influence of physical activity
during childhood and adolescence on adult bone mass. In
some retrospective studies, a positive association of former
physical activity with adult bone mass was reported (16, 36–
43), whereas other authors found no association (44). Only a
few longitudinal prospective studies have addressed the
issue of the contribution of physical activity during the
growing years to adult bone mass (45–48). These studies
concluded that physical activity during childhood or adolescence is a determinant of peak bone mass. Whether residual
benefits are maintained in later adulthood and older age still
needs to be demonstrated. Because the subjects of the few
longitudinal studies were rather young (aged 18–29 years),
this question could not be addressed.
In a previous study of the same group of men, we examined the extent to which lifetime physical activity and lifestyle parameters contribute to bone mass (49). However, that
study made no distinction between weight-bearing activities
and non-weight-bearing activities. Therefore, we conducted
the present 27-year follow-up study to examine whether
physical activity during adolescence and adulthood, with
special focus on the type of physical activity (high impact vs.
nonimpact), contributes to bone health in males aged 40
years. In the first part, we studied the relation between bone
mineral density (BMD) and impact loading due to sports
participation. It was hypothesized that impact loading is
positively associated with BMD. In the second part, we
addressed this question by analyzing contrasting groups with
different histories of sports participation. It was hypothesized that 1) the bone status of subjects involved in highimpact sports during adolescence and adulthood is better
than that of subjects involved in high-impact sports during
adolescence and in nonimpact sports during adulthood, and
2) the bone status of both of these groups is better than that
of subjects involved in nonimpact sports during adolescence
and adulthood.
MATERIALS AND METHODS
Subjects
The subjects of this study were Belgian men aged 40 years
from the Leuven Longitudinal Study of Lifestyle, Fitness
and Health (50), originally the Leuven Growth Study of
Belgian Boys (51). These men were measured yearly from
1969 until 1974 and again in 1986, 1991, and 1996. In the
Leuven Growth Study of Belgian Boys, 588 subjects (aged
13–18 years) were followed longitudinally to study the
development of somatic, motor, and fitness characteristics.
Of these subjects, the Flemish-speaking males (n = 441)
were contacted again in 1986 for further follow-up in the
Leuven Longitudinal Study of Lifestyle, Fitness and Health.
In the first phase of this follow-up, 278 subjects agreed to
participate and were reevaluated at ages 30, 35, and 40 years.
Bone mineral measurements were taken from 154 men at the
last test session (1996).
In the first part of this study, the data on these 154 men
were used to study the relation between impact loading due
to sports participation and BMD. In the second part, the
following three groups based on sports participation during
adolescence and adulthood were formed to investigate this
question further: group 1—participation during adolescence
and adulthood in high-impact sports (HH; n = 18), group 2—
participation during adolescence in high-impact sports and
during adulthood in nonimpact sports or no sports (HN; n =
15), and group 3—participation during adolescence and
adulthood in nonimpact sports or no sports (NN; n = 14)
(refer to the section entitled “Sports participation (high
impact vs. nonimpact)”). Subjects whose sports participation
did not meet these criteria (n = 107) were not included in the
second part of this study.
Informed consent was obtained from all subjects. The
study was approved by the local medical committee.
Anthropometry
For all subjects, body mass was measured with a balance
scale accurate to 0.1 kg. Standing height was measured with
a Holtain stadiometer (Holtain Ltd., Crymych, United
Kingdom) with subjects barefooted. On each occasion, one
experienced anthropometrist took the anthropometric
measurements. On the basis of these measurements, a mean
score for body mass during adolescence (mean for ages 13–
18 years) and during adulthood (mean for ages 30, 35, and 40
years) was calculated. In addition, body mass index (weight
(kg)/height (m)2) was determined.
Bone measurements
Dual-energy x-ray absorptiometry. When subjects were
40 years of age, BMD (g/cm2) of the lumbar spine and total
body was determined by dual-energy x-ray absorptiometry
(DXA) (Hologic QDR-4500A; Hologic, Inc., Bedford,
Massachusetts). The in vivo precision of DXA at the University Hospital (Leuven) is approximately 1 percent for lumbar
spine BMD and less than 1 percent for total body BMD.
Radiogrammetry. In 1969, when subjects were 13 years
of age, DXA was not yet available. Therefore, bone was
measured by radiogrammetry. With a subject’s left hand in a
standardized position, radiographs were taken at an exposure
of 1.0 second at 30 mA and 70 kV to determine several
metacarpal II bone dimensions. The radiographs were
scanned and analyzed digitally. Length (L), periosteal width
(D), and medullary width (d) of the metacarpal II bone were
measured according to the guidelines of Dequeker (52).
Several derived measurements were calculated from these
basic measurements based on the formulas described by
Am J Epidemiol 2003;158:525–533
Influence of Long-term Impact Sports on BMD 527
Kimura (53) and Roy et al. (54), as follows: combined
cortical thickness = D – d (mm), cross-sectional cortical
area = π (D/2)2 – π (d/2)2 (mm2), and metacarpal cortical
index = (D – d)/D.
Intraobserver reliability coefficients of 0.99, 0.98, and
0.92 were obtained for L, D, and d, respectively. A paired t
test revealed a significant difference only between the two
measurements of periosteal width (∆ p = 0.002).
cence and participated in high-impact sports during adulthood should have formed a fourth group. Unfortunately,
subjects who met these criteria were not included in our
sample. This finding was not surprising, since previous
studies have demonstrated that subjects not involved in
sports activities during adolescence hardly participate in
sports during adulthood (56).
Dietary behavior and smoking habits
Sports participation (high impact vs. nonimpact)
Sports participation was investigated by using a sports
participation inventory (55). For each observation, information about the types of sports and the time spent per week
(Minutes Sport Participation per week) engaged in the
different sports activities was obtained for the period of the
year preceding each test session.
Numbers of minutes spent participating in sports activities
were calculated for adolescence and adulthood. The mean
score for 6 years (ages 13–18 years) was calculated to obtain
time spent in sports activities during adolescence, and the
mean score for the results at ages 30, 35, and 40 years was
calculated to obtain time spent in sports activities during
adulthood.
In addition, impact scores were calculated. As previously
described by Groothausen et al. (45), activities that involve
jumping actions were given a peak strain score of 3, those
involving explosive actions such as turning and sprinting
received a peak strain score of 2, weight-bearing activities
were assigned a peak strain score of 1, and all other activities
received a peak strain score of 0. First, all peak strain scores
for all activities registered in 1 year were summed to obtain
an impact score for that year. Furthermore, an impact score
for adolescence and an impact score for adulthood were
calculated by respectively summing the impact scores
obtained for subjects from age 13 years to age 18 years and
the impact scores obtained at ages 30, 35, and 40 years.
For the second part of the analysis, three groups were
formed based on subjects’ sports participation during adolescence and adulthood. First, the different sports were divided
according to the ground reaction forces involved. Sports
whose ground reaction forces were higher than four times
body weight were considered high-impact sports (e.g.,
basketball, volleyball, gymnastics). Sports whose ground
reaction forces were between two and four times, between
one and two times, and less than one time body weight were
respectively considered moderate-impact sports (e.g., tennis,
soccer), low-impact sports (e.g., jogging, ballroom dancing),
and nonimpact sports (e.g., bicycling, swimming) (23, 45).
The HH group (n = 18) comprised subjects who participated
for 6 years during adolescence in high-impact sports and in
medium- or high-impact sports in adulthood. Subjects who
participated for 6 years during adolescence in high-impact
sports but during adulthood in low- or nonimpact sports or
did not participate in any sports formed the HN group (n =
15). Subjects who participated during adolescence and adulthood in only nonimpact sports or who did not participate in
any sports were considered the NN group (n = 14).
Ideally, subjects who participated in only nonimpact
sports or who did not participate in any sports during adolesAm J Epidemiol 2003;158:525–533
Dietary information was derived from a 3-day (2 weekdays and 1 weekend day) food record at age 40 years. These
dietary records were reviewed by one research dietitian. In
this paper, information about only calcium and alcohol
consumption is given.
Information about smoking habits was obtained by questionnaire. Those who smoked daily and subjects who had
recently quit (less than 1 year ago) were considered smokers.
Subjects who had never smoked and quitters (more than 1
year ago) were considered nonsmokers.
Statistical analysis
For the first part of this study, descriptive statistics for the
anthropometric characteristics, impact scores, time spent
participating in sports, and BMD were calculated for the 154
subjects. Pearson and Spearman correlation coefficients
were calculated between BMD on the one hand and the
anthropometric and sports variables on the other. Full-model
regression analyses were performed with BMD as the dependent variable and body mass, impact scores during adolescence and during adulthood, and time spent participating in
sports during adolescence and during adulthood as independent variables. We decided to use body mass and not body
mass index as an independent variable because 1) higher
correlation coefficients were found between BMD and body
mass than between BMD and body mass index, and 2) impact
experienced by the bones during sports activities is related to
body mass.
In the second part of this study, the three groups with
different impact loading histories (HH, HN, and NN) were
contrasted. Descriptive statistics for the anthropometric
characteristics, time spent participating in sports, nutrition,
metacarpal II bone variables, and BMD were calculated for
the three groups.
Analyses of variance were executed to detect differences
between the three groups for the bone dimensions. Because
body mass is an important determinant of BMD and because
the amount of time that the subjects spent participating in
sports differed between the groups, analyses of covariance
were conducted by using body mass, Minutes Sport Participation per week during adolescence, and Minutes Sport
Participation per week during adulthood as covariates.
Doing so enabled us to detect the influence of high-impact
sports on BMD by taking into account the influence of body
mass and of time spent participating in sports activities.
For all statistical analyses, the SAS software package was
used (version 6.12; SAS Institute, Inc., Cary, North Carolina).
528 Van Langendonck et al.
TABLE 1. Descriptive statistics for 154 Belgian men studied to assess the influence of participation in
high-impact sports during adolescence and adulthood on bone mineral density
Mean (standard deviation)
Body mass (kg) at age 13 years (1969)
41.8 (7.7)
Body mass index (kg/m2) at age 13 years
18.0 (2.2)
Body mass (kg) at age 18 years (1974)
65.8 (7.0)
Body mass index
(kg/m2)
at age 18 years
21.2 (2.0)
Body mass (kg) at age 40 years (1996)
78.9 (10.2)
Body mass index (kg/m2) at age 40 years
25.0 (2.9)
Impact score during adolescence
36.0 (20.6)
Impact score during adulthood
6.2 (5.0)
Minutes Sport Participation per week (minutes) during adolescence
290 (190)
Minutes Sport Participation per week (minutes) during adulthood
170 (140)
Total body bone mineral density (g/cm2)
1.20 (0.10)
Lumbar spine bone mineral density
(g/cm2)
RESULTS
The descriptive statistics for the anthropometric dimensions, the sports participation indices (impact scores and
time spent participating in sports), and lumbar spine BMD
and total body BMD are presented for the total group (N =
154) in table 1. At baseline, subjects weighed 41.8 (standard
deviation, 7.7) kg. Mean time spent participating in sports
was almost 5 hours (290 (standard deviation, 190) minutes)
per week during adolescence and almost 3 hours (170
(standard deviation, 140) minutes) per week during adulthood. The impact score during adolescence was 36.0 (standard deviation, 20.6), but it decreased considerably during
adulthood.
1.07 (0.14)
The regression analysis that included body mass, impact
scores during adolescence and during adulthood, and time
spent participating in sports during adolescence and during
adulthood as independent variables revealed an explained
variance of 24.5 percent for total body BMD and of 24.2
percent for lumbar spine BMD. The regression analysis indicated that body mass during adulthood and impact score
during adulthood were predictors of total body BMD and
lumbar spine BMD (table 2).
In the second part of this study, we compared groups of
subjects with contrasting impact loading histories. The
descriptive statistics and the results of the analyses of variance for the anthropometric dimensions, time spent participating in sports, calcium and alcohol consumption, and
TABLE 2. Full-model regression analysis for bone mineral density parameters of Belgian men at age 40 years (1996) and body mass
and physical activity characteristics during adolescence (1969–1974) and adulthood
Standardized parameter
estimate (standard error)
t value for H0:
parameter = 0
95% confidence
interval
Intercept
–1.2805 exponent-15 (0.0714)
–0.00
–0.1400, 0.1400
Body mass during adolescence
0.0762 (0.0891)
0.86
–0.0984, 0.2508
Impact score during adolescence
–0.0810 (0.0999)
–0.81
–0.2769, 0.1149
Time spent participating in sports during
adolescence
0.1592 (0.1039)
1.53
–0.0444, 0.3628
Body mass during adulthood
0.3657 (0.0883)
4.14*
0.1927, 0.5388
Impact score during adulthood
0.2931 (0.0846)
3.46*
0.1272, 0.4589
Time spent participating in sports during
adulthood
–0.1705 (0.0889)
–1.92
–0.3448, 0.0039
Intercept
0.0010 (0.0718)
0.01
–0.1397, 0.1418
Body mass during adolescence
0.1530 (0.0894)
1.71
–0.0222, 0.3283
Impact score during adolescence
0.0445 (0.1003)
0.44
–0.1520, 0.2411
Time spent participating in sports during
adolescence
0.1291 (0.1041)
1.24
–0.0749, 0.3332
Body mass during adulthood
0.2941 (0.0892)
3.30*
0.1193, 0.4689
Impact score during adulthood
0.2633 (0.0848)
3.11*
0.0971, 0.4295
Time spent participating in sports during
adulthood
–0.1354 0.0892)
–1.52
–0.3102, 0.0394
Dependent variable
Total body bone mineral density
Lumbar spine bone mineral density
Predictors
* p < 0.01.
Am J Epidemiol 2003;158:525–533
Influence of Long-term Impact Sports on BMD 529
TABLE 3. Descriptive statistics and analysis of variance of three groups of Belgian men at age 40 years (1996) based on their sports
participation history
Mean (standard deviation)
HH* (n = 18)
HN* (n = 15)
NN* (n = 14)
F-test
value
p value
Body mass (kg) at age 13 years
39.2 (7.7)
43.5 (6.7)
43.8 (7.5)
2.09
0.1363
Body mass index (kg/m2) at age 13 years
17.4 (2.2)
17.9 (2.2)
18.1 (1.5)
0.40
0.6742
Body mass (kg) at age 18 years
66.5 (6.7)
66.0 (7.2)
66.6(6.0)
0.03
0.9718
Body mass index (kg/m2) at age 18 years
21.4 (1.8)
21.2 (2.5)
21.0 (1.0)
0.13
0.8814
Body mass (kg) at age 40 years
81.4 (12.1)
77.1 (6.8)
76.6 (11.0)
1.11
0.3389
Height (cm) at age 40 years
178.3 (5.6)
177.0 (6.2)
179.0 (7.3)
0.41
0.6675
Body mass index (kg/m2) at age 40 years
25.6 (3.0)
24.7 (2.5)
23.8 (2.4)
1.67
0.2004
Minutes Sport Participation per week (minutes) during adolescence
460 (300)
350 (260)
120 (110)
7.82†,‡
0.0012
Minutes Sport Participation per week (minutes) during adulthood
240 (210)
100 (80)
130 (120)
3.53§
0.0378
Calcium consumption (mg) at age 40 years
707.4 (276.9)
790.5 (282.4)
1012.8 (411.6)
3.03
0.0603
Alcohol consumption (g) at age 40 years
33.8 (28.3)
15.4 (14.3)
17.8 (22.8)
2.75
0.0771
Length of the metacarpal II bone (mm) at age 13 years
57.8 (4.6)
61.0 (3.2)
61.3 (4.8)
3.16
0.0532
D* (mm) at age 13 years
7.3 (0.8)
7.8 (0.8)
7.6 (0.7)
1.68
0.1992
d* (mm) at age 13 years
3.8 (0.8)
4.0 (0.9)
3.8 (0.6)
0.27
0.7678
CCT* (mm) at age 13 years
3.5 (0.5)
3.8 (0.4)
3.7 (0.4)
2.05
0.1423
CA* ((mm)2) at age 13 years
30.3 (7.1)
35.0 (4.9)
33.4 (6.0)
2.35
0.1080
MCI* at age 13 years
0.48 (0.07)
0.49 (0.08)
0.49 (0.05)
0.25
0.7820
Total body bone mineral density (g/cm2) at age 40 years
1.23 (0.10)
1.15 (0.07)
1.17 (0.08)
3.17
0.0515
Lumbar spine bone mineral density (g/cm2) at age 40 years
1.12 (0.15)
1.01 (0.11)
0.99 (0.11)
5.07†,§
0.0104
* HH, subjects participating during adolescence and adulthood in high-impact sports; HN, subjects participating during adolescence in high-impact sports and
during adulthood in nonimpact sports or no sports; NN, subjects participating during adolescence and adulthood in nonimpact sports or no sports; D, periosteal
width; d, medullary width; CCT, combined cortical thickness; CA, cortical area; MCI, metacarpal cortical index.
† Analysis of variance: HH group significantly different from the NN group.
‡ Analysis of variance: HN group significantly different from the NN group.
§ Analysis of variance: HH group significantly different from the HN group.
lumbar spine BMD and total body BMD are presented in
table 3. At 40 years of age, subjects’ mean weight and height
varied between 76.6 kg and 81.4 kg and between 177 cm and
179 cm, respectively. Mean time spent participating in sports
activities during adolescence was only 120 minutes (2 hours)
per week for the NN group, whereas the HN and HH groups
were involved for 350 minutes (almost 6 hours) and 460
minutes (almost 8 hours), respectively. During adulthood,
weekly time spent engaging in sports activities was 130
minutes and 100 minutes (±2 hours) for the NN and HN
groups, respectively, and 240 minutes (4 hours) for the HH
group. In the HH group and the NN group, three subjects
smoked or had quit less than 1 year before the last test
session. In the HN group, eight subjects were smokers or had
recently quit. However, a t test for independent samples indicated that total body BMD and lumbar spine BMD did not
differ between the smokers and nonsmokers in this group.
The analyses of variance revealed that the three sports
participation groups did not differ significantly regarding
weight, height, and body mass index during adolescence or
adulthood. During adolescence, the three groups differed
significantly in time spent participating in sports (Minutes
Sport Participation per week scores), with higher scores for
the HH and HN groups in comparison with the NN group. In
adulthood, the HH group had significantly higher Minutes
Sport Participation per week scores than the HN group. No
significant differences were found between the three groups
Am J Epidemiol 2003;158:525–533
concerning calcium and alcohol consumption. However, the
HH group tended to drink more alcohol, and the NN group
tended to consume more calcium. No significant differences
were found regarding the bone dimensions based on metacarpal II bone measurements, which indicates that the three
impact groups did not differ at baseline. Significant differences were found for lumbar spine BMD between the HH
(1.12 g/cm2) group and the HN (1.01 g/cm2) and NN (0.99 g/
cm2) groups (F = 5.07, p = 0.01). The results for total body
BMD just failed to reach significance (F = 3.17, p = 0.0515).
The covariance analyses for total body BMD and lumbar
spine BMD with weight, Minutes Sport Participation per
week during adolescence, or Minutes Sport Participation per
week during adulthood as covariates confirmed the results
found in the analyses of variance. After adjustment for the
three covariates, results just failed to reach significance;
however, when each covariate was included separately, the
groups differed significantly. Thus, even after we accounted
for the covariates, impact during sports participation was a
significant factor and resulted in significant differences
between the HH group and the HN and NN groups for
lumbar spine BMD (table 4).
DISCUSSION
Osteoporosis is increasingly being recognized in men and
will become a worldwide public health problem, since more
530 Van Langendonck et al.
TABLE 4. Analysis of covariance for Belgian men at age 40 years, with body mass and with Minutes Sport Participation during
adolescence (1969–1974) and during adulthood as covariates
Lumbar spine mean (standard deviation)
HH* (n = 18)
HN* (n = 15)
NN* (n = 14)
1.22 (0.08)
1.16 (0.08)
1.18 (0.07)
F covariate
independent
variable
p value
Body mass
Total body bone mineral density (g/cm2)
Lumbar spine bone mineral density (g/cm2)
1.11 (0.13)
1.02 (0.12)
1.00 (0.11)
1.86
0.1792
2.44
0.0989
10.06
0.0028
3.69†,‡
0.0332
0.04
0.8383
2.70
0.0787
0.13
0.7218
3.67†,‡
0.0336
0.05
0.8249
2.87
0.0674
Minutes Sport Participation per week during adolescence
Total body bone mineral density (g/cm2)
Lumbar spine bone mineral density (g/cm2)
1.22 (0.08)
1.12 (0.13)
1.15 (0.08)
1.01 (0.12)
1.18 (0.11)
1.00 (0.15)
Minutes Sport Participation per week during adulthood
Total body bone mineral density (g/cm2)
Lumbar spine bone mineral density (g/cm2)
1.23 (0.08)
1.12 (0.13)
1.15 (0.08)
1.01 (0.12)
1.17 (0.07)
0.99 (0.11)
0.01
0.9423
4.25†,‡
0.0207
* HH, subjects participating during adolescence and adulthood in high-impact sports; HN, subjects participating during adolescence in high-impact sports and
during adulthood in nonimpact sports or no sports; NN, subjects participating during adolescence and adulthood in nonimpact sports or no sports.
† Analysis of covariance: HH group significantly different from the HN group.
‡ Analysis of covariance: HH group significantly different from the NN group.
than half of all women and about one third of all men will
develop fractures related to osteoporosis (57). Insight into
the determinants of bone mass is necessary to develop
preventive strategies. In a previous study by our group, we
investigated the extent to which bone mass is associated with
lifestyle, anthropometry, motor fitness, and lifetime physical
activity in middle-aged men (49). Results from correlation
and regression analyses showed that body mass index was
the most important determinant of total body BMD and
lumbar spine BMD. In addition, it was shown that sports
participation was related to bone mass. However, in that
study, no distinction was made between weight-bearing
activities and other types. Consequently, the purpose of the
present study was to examine whether participation in highimpact sports during adolescence and adulthood contributes
to bone health in males aged 40 years.
The regression analysis (N = 154) revealed that body mass
during adulthood and impact score during adulthood were
significant predictors of total body BMD and of lumbar
spine BMD (table 2). No other variables were significant
predictors. These results indicate that type of sports participation is more important than time spent participating in
sports. Body mass and impact during adulthood and not
during adolescence were significant predictors of bone mass.
However, since these parameters are significantly related,
the results do not indicate that body mass and impact during
adolescence would not influence bone mass at age 40 years
(lumbar spine BMD – body mass during adolescence: r =
0.30, p = 0.0002; lumbar spine BMD – impact during adolescence: r = 0.15, p = 0.06).
Analysis of variance (n = 47) revealed significant differences for lumbar spine BMD between the HH (1.12 g/cm2)
group and the HN (1.01 g/cm2) and NN (0.99 g/cm2) groups
(F = 5.07, p = 0.01). The differences for lumbar spine BMD
between the groups were of the magnitude of one standard
deviation, that is, an effect size of 1, which is of biologic
importance. In addition, it has previously been shown that
above a spinal BMD of about 1 g/cm2 (measured by dual
photon absorptiometry), vertebral fractures are rare. These
fractures become increasingly common as vertebral bone
mass declines below this density (58). The observed differences remained significant even after controlling for weight
or time spent participating in sports activities during adolescence or during adulthood. Comparison with a fourth group
comprising subjects who were not involved in sports or were
involved only in nonimpact sports during adolescence and
who participated in high-impact sports during adulthood
would have been very interesting. However, since it has been
shown that very few people exhibit this pattern of sports
participation (56), an experimental study should be
conducted to examine the effect of high-impact sports during
adulthood. Nonetheless, conclusions would have only theoretical value because, in general, very few people demonstrate this pattern of sports participation in normal life.
The results of this study can be explained in two ways.
First, it is possible that the two groups involved in impact
sports during adolescence gained BMD at the lumbar spine
because of this sports participation. Sustained participation
by the HH group could have maintained this gain or decelerated bone loss, whereas discontinuation of activity by the
HN group could have resulted in bone loss. Because peak
bone mass is achieved at approximately age 25–30 years (5)
and thereafter bone is lost at a rate of about 0.5–1 percent per
year at most bony sites (59), it is possible that this loss was
Am J Epidemiol 2003;158:525–533
Influence of Long-term Impact Sports on BMD 531
responsible for the differences observed between the HH
group and the HN and NN groups. No significant differences
were found between the HN group and the NN group. It is
clear that impact only during adolescence did not result in a
better bone status at age 40 years. Second, another explanation could be that participating in high-impact sports during
adolescence did not result in bone gain but continued participation in impact sports during adulthood resulted in maintaining BMD or decelerating bone loss at the lumbar spine.
Because the spines of the subjects in the HN group and the
NN group were not subjected to high strain during adulthood, bone mineral could have been lost.
Regarding the results from former studies of athletes, it is
not very plausible that participation in high-impact sports for
6 years did not result in bone gain. Therefore, the first explanation is most likely more correct. Nordstrom et al. (14)
found, in a study of adolescent boys, that being involved in
badminton and ice hockey resulted in higher bone mass at
the weight-bearing sites. McCulloch et al. (12) found comparable results for adolescent soccer athletes. Pettersson et al.
(60) concluded that high-impact activity in adolescent
females resulted in higher BMD values at the loaded sites.
Population-based retrospective studies and longitudinal
studies have shown the importance of physical activity
during growth to maximize peak bone mass at the lumbar
spine (37, 46, 47). Retrospective studies of athletes resulted
in contrasting findings. Khan et al. (36) and Duppe et al. (38)
found, for retired ballet dancers and former football players,
respectively, a relation between sports participation during
childhood or adolescence and bone mass at the femur but not
at the lumbar spine at older ages. On the contrary, Kirchner
et al. (40) and Bass et al. (16) concluded that past participation in gymnastics may have a residual effect on adult BMD.
It is important to note that these studies differed in several
respects. Not only were the subjects involved in different
sports, but they also differed a great deal in age (Khan et al.,
mean age, 51 years; Duppe et al., ages 34–85 years; Kirchner
et al., ages 29–45 years; Bass et al., ages 18–35 years). As in
the study by Karlsson et al. (39) in which differences in bone
mass were found only between former weight lifters younger
than age 65 years and controls, it is possible that after quitting sports participation for a long period of time, the bone
mass gained because of the physical activity is no longer
maintained. These authors concluded that a high level of
physical activity has to be continued throughout life to maintain bone mass.
In the study by Hara et al. (42), the importance of physical
activity during different age periods (at ages 13–15 years, at
ages 16–18 years, and during adulthood) was investigated.
These authors concluded that subjects who participated in
high-impact sports during each period had significantly
higher current total body BMD and lumbar spine BMD even
after the authors controlled for hours per week and types of
exercise during other periods. Groothausen et al. (45), on the
contrary, concluded that if strain due to physical activity
occurred only during the teenage period, the influence of
peak strain on lumbar spine BMD at age 27 years was not of
great importance.
The present study had some limitations. Mainly, the BMD
measurements were not longitudinal. No such measurements
Am J Epidemiol 2003;158:525–533
were made at the start of the study. It is possible that there
was a natural selection when the study began. The boys in the
high-impact group were perhaps more strongly built and
therefore had a higher BMD at the beginning, which still
could have been evident at age 40 years. However, the fact
that the metacarpal II bone variables at age 13 years did not
differ between the three groups provides some indication that
no baseline differences existed. Another concern is the generalizability of the results. As mentioned in a former study (61),
the subjects in this study were a subsample of the 588 boys
followed longitudinally over 6 years (51). The somatic,
motor, and sociocultural characteristics of this subsample did
not differ significantly from the total Flemish sample at 18
years of age. Thus, it is assumed that they were representative
of the sample of boys followed longitudinally through adolescence (62). Moreover, the BMD of the subjects in the present
study was comparable with BMD values for men of the same
age reported by other studies (63–65). Since the femoral neck
is also an important fracture site, this measure should be
incorporated in future studies.
Based on the regression analysis and the differences found
between the HH group on the one hand and the HN and NN
groups on the other, it can be concluded that continued
participation in high-impact sports during adulthood is
necessary to maintain BMD or at least slow down the loss.
The influence of participation in high-impact sports during
the growing years on skeletal health—as measured by DXA
and expressed as BMD—in adulthood is still a matter of
discussion. To resolve this question, longitudinal BMD data
are required.
ACKNOWLEDGMENTS
Contract grant sponsors for the Leuven Growth Study of
Belgian Boys: The Administration of Sport, Physical Education, and Open Air Activities of the Ministry of Nederlandse
Kultuur and the Ministry of Culture Française; the Administration of Social Medicine of the Ministry of Public Health;
and the Foundation for Medical Scientific Research.
Contract grant sponsors for the Leuven Longitudinal Study
on Lifestyle, Fitness and Health: National Scientific Fund
(NFWO 3.0188.96), Ministry of Public Health, and ABB
Insurance Company.
The authors thank the staff of the University Hospital
Department of Rheumatology (Leuven) for the DXA
measurements.
REFERENCES
1. Bailey DA, Martin AD. Physical activity and skeletal health in
adolescents. Pediatr Exerc Sci 1994;6:330–47.
2. Krall EA, Dawson-Hughes B. Heritable and life-style determinants of bone mineral density. J Bone Miner Res 1993;8:1–9.
3. Nguyen TV, Howard GM, Kelly PJ, et al. Bone mass, lean
mass, and fat mass: same genes or same environments? Am J
Epidemiol 1998;147:3–16.
4. Slemenda CW, Turner CH, Peacock M, et al. The genetics of
proximal femur geometry, distribution of bone mass and bone
532 Van Langendonck et al.
mineral density. Osteoporos Int 1996;6:178–82.
5. Heaney RP, Abrams S, Dawson-Hughes B, et al. Peak bone
mass. Osteoporos Int 2000;11:985–1009.
6. Snow-Harter C, Marcus R. Exercise, bone mineral density, and
osteoporosis. Exerc Sport Sci Rev 1991;19:351–88.
7. Bennell KL, Malcolm SA, Khan KM, et al. Bone mass and
bone turnover in power athletes, endurance athletes, and controls: a 12-month longitudinal study. Bone 1997;20:477–84.
8. Cassell C, Benedict M, Specker B. Bone mineral density in elite
7- to 9-yr-old female gymnasts and swimmers. Med Sci Sports
Exerc 1996;28:1243–6.
9. Courteix D, Lespessailles E, Peres SL, et al. Effect of physical
training on bone mineral density in prepubertal girls: a comparative study between impact-loading and non-impact-loading
sports. Osteoporos Int 1998;8:152–8.
10. Dook JE, James C, Henderson NK, et al. Exercise and bone
mineral density in mature female athletes. Med Sci Sports
Exerc 1997;29:291–6.
11. Dyson K, Blimkie CJ, Davison KS, et al. Gymnastic training
and bone density in pre-adolescent females. Med Sci Sports
Exerc 1997;29:443–50.
12. McCulloch RG, Bailey DA, Whalen RL, et al. Bone density and
bone mineral content of adolescent soccer athletes and competitive swimmers. Pediatr Exerc Sci 1992;4:319–30.
13. Nichols DL, Sanborn CF, Bonnick SL, et al. The effects of
gymnastics training on bone mineral density. Med Sci Sports
Exerc 1994;26:1220–5.
14. Nordstrom P, Pettersson U, Lorentzon R. Type of physical
activity, muscle strength, and pubertal stage as determinants of
bone mineral density and bone area in adolescent boys. J Bone
Miner Res 1998;13:1141–8.
15. Rourke KM, Bowering J, Turkki P, et al. Bone mineral density
in weight-bearing and nonweight-bearing female athletes.
Pediatr Exerc Sci 1998;10:28–37.
16. Bass S, Pearce G, Bradney M, et al. Exercise before puberty
may confer residual benefits in bone density in adulthood: studies in active prepubertal and retired female gymnasts. J Bone
Miner Res 1998;13:500–7.
17. McKay HA, Petit MA, Schutz RW, et al. Augmented trochanteric bone mineral density after modified physical education
classes: a randomized school-based exercise intervention study
in prepubescent and early pubescent children. J Pediatr 2000;
136:156–62.
18. MacKelvie KJ, McKay HA, Khan KM, et al. A school-based
exercise intervention augments bone mineral accrual in early
pubertal girls. J Pediatr 2001;139:501–8.
19. Fuchs RK, Bauer JJ, Snow CM. Jumping improves hip and
lumbar spine bone mass in prepubescent children: a randomized controlled trial. J Bone Miner Res 2001;16:148–56.
20. Morris FL, Naughton GA, Gibbs JL, et al. Prospective tenmonth exercise intervention in premenarcheal girls: positive
effects on bone and lean mass. J Bone Miner Res 1997;12:
1453–62.
21. Bradney M, Pearce G, Naughton G, et al. Moderate exercise
during growth in prepubertal boys: changes in bone mass, size,
volumetric density, and bone strength: a controlled prospective
study. J Bone Miner Res 1998;13:1814–21.
22. Heinonen A, Sievänen H, Kannus P, et al. High-impact exercise
and bones of growing girls: a 9-month controlled trial.
Osteoporos Int 2000;11:1010–17.
23. Witzke KA, Snow CM. Effects of plyometric jump training on
bone mass in adolescent girls. Med Sci Sports Exerc 2000;32:
1051–7.
24. Bassey EJ, Rothwell MC, Littlewood JJ, et al. Pre- and postmenopausal women have different bone mineral density
responses to the same high-impact exercise. J Bone Miner Res
1998;13:1805–13.
25. Berard A, Bravo G, Gauthier P. Meta-analysis of the effectiveness of physical activity for the prevention of bone loss in postmenopausal women. Osteoporos Int 1997;7:331–7.
26. Friedlander AL, Genant HK, Sadowsky S, et al. A two-year
program of aerobics and weight training enhances bone mineral
density of young women. J Bone Miner Res 1995;10:574–85.
27. Grove KA, Londeree BR. Bone density in postmenopausal
women: high impact vs low impact exercise. Med Sci Sports
Exerc 1992;24:1190–4.
28. Heinonen A, Oja P, Sievanen H, et al. Effect of two training
regimens on bone mineral density in healthy perimenopausal
women: a randomized controlled trial. J Bone Miner Res 1998;
13:483–90.
29. Kelly GA. Exercise and regional bone mineral density in postmenopausal women: a meta-analytic review of randomized trials. Am J Phys Med Rehabil 1998;77:76–87.
30. Layne JE, Nelson ME. The effects of progressive resistance
training on bone density: a review. Med Sci Sports Exerc 1999;
31:25–30.
31. Lohman T, Going S, Pamenter R, et al. Effects of resistance
training on regional and total bone mineral density in premenopausal women: a randomized prospective study. J Bone Miner
Res 1995;10:1015–24.
32. Peterson SE, Peterson MD, Raymond G, et al. Muscle strength
and bone density with weight training in middle-aged women.
Med Sci Sports Exerc 1991;23:499–504.
33. Sinaki M, Wahner HW, Bergstralh AJ, et al. Three-year controlled, randomized trial of the effect of dose-specified loading
and strengthening exercises on bone mineral density of spine
and femur in nonathletic, physically active women. Bone 1996;
19:233–44.
34. Wolff I, van Croonenborg JJ, Kemper HC, et al. The effect of
exercise training programs on bone mass: a meta-analysis of
published controlled trials in pre- and postmenopausal women.
Osteoporos Int 1999;9:1–12.
35. Bilezikian JP. Osteoporosis in men. J Clin Endocrinol Metab
1999;84:3431–4.
36. Khan KM, Bennell KL, Hopper JL, et al. Self-reported ballet
classes undertaken at age 10–12 years and hip bone mineral
density in later life. Osteoporos Int 1998;8:165–73.
37. Puntila E, Lakka T, Honkanen R, et al. Physical activity in adolescence and bone density in peri- and postmenopausal women:
a population-based study. Bone 1997;21:363–7.
38. Duppe H, Gardsell P, Johnell O, et al. Bone mineral density in
female junior, senior and former football players. Osteoporos
Int 1996;6:437–41.
39. Karlsson MK, Johnell O, Obrant KJ. Is bone mineral density
advantage maintained long-term in previous weight lifters?
Calcif Tissue Int 1995;57:325–8.
40. Kirchner EM, Lewis RD, O’Connor PJ. Effect of past gymnastics participation on adult bone mass. J Appl Physiol 1996;80:
226–32.
41. Kriska AM, Black Sandler R, Cauley JA, et al. The assessment
of historical physical activity and its relation to adult bone
parameters. Am J Epidemiol 1988;127:1053–63.
42. Hara S, Yanagi H, Amagai H, et al. Effect of physical activity
during teenage years, based on type of sport and duration of
exercise, on bone mineral density of young, premenopausal
Japanese women. Calcif Tissue Int 2001;68:23–30.
43. Ward JA, Lord SR, Williams P, et al. Physiologic, health and
lifestyle factors associated with femoral neck bone density in
older women. Bone 1995;16:373S–378S.
44. Lindholm C, Hagenfeldt K, Ringertz H. Bone mineral content
of young female former gymnasts. Acta Paediatr 1995;84:
1109–12.
Am J Epidemiol 2003;158:525–533
Influence of Long-term Impact Sports on BMD 533
45. Groothausen J, Siemer H, Kemper HC, et al. Influence of peak
strain on lumbar bone mineral density: an analysis of 15-year
physical activity in young males and females. Pediatr Exerc Sci
1997;9:159–73.
46. Cooper C, Cawley M, Bhalla A, et al. Childhood growth, physical activity, and peak bone mass in women. J Bone Miner Res
1995;10:940–7.
47. Välimäki MJ, Kärkkäinen M, Lamberg-Allardt C, et al. Exercise, smoking, and calcium intake during adolescence and early
adulthood as determinants of peak bone mass. Cardiovascular
Risk in Young Finns Study Group. BMJ 1994;309:230–5.
48. Lloyd T, Chinchilli VM, Johnson-Rollings N, et al. Adult
female bone density reflects teenage sports-exercise patterns
but not teenage calcium intake. Pediatrics 2000;106:40–4.
49. Delvaux K, Lefevre J, Philippaerts RM, et al. Bone mass and
lifetime physical activity in Flemish males: a 27-year follow-up
study. Med Sci Sports Exerc 2001;33:1868–75.
50. Beunen G, Ostyn M, Simons J, et al. Development and tracking
in fitness components: Leuven Longitudinal Study on Lifestyle,
Fitness and Health. Int J Sports Med 1997;18(suppl 3):S171–8.
51. Beunen GP, Malina RM, Van ‘t Hof MA, et al. Adolescent
growth and motor performance: a longitudinal study of Belgian
boys. Champaign, IL: Human Kinetics, 1988.
52. Dequeker J. Quantitative radiology: radiogrammetry of cortical
bone. Br J Radiol 1976;49:912–20.
53. Kimura K. Age and sex differences in bone density of the second metacarpal in its midshaft cross-section. Ann Hum Biol
1990;17:399–406.
54. Roy TA, Ruff CB, Plato CC. Hand dominance and bilateral
asymmetry in the structure of the second metacarpal. Am J
Phys Anthropol 1994;94:203–11.
55. Simons J, Beunen G, Renson R, et al. The mixed-longitudinal
growth study. In: Ostyn M, Simons J, Beunen G, et al, eds.
Somatic and motor development of Belgian secondary schoolboys: norms and standards. Leuven, Belgium: Leuven Univer-
Am J Epidemiol 2003;158:525–533
sity Press, 1980:11–23.
56. Vanreusel B, Renson R, Beunen G, et al. A longitudinal study
of youth sport participation and adherence to sport in adulthood. Int Rev Sociol Sport 1997;32:373–87.
57. Ross PD. Osteoporosis: epidemiology and risk assessment. J
Nutr Health Aging 1998;2:178–83.
58. Cummings SR, Kelsey JL, Nevitt MC, et al. Epidemiology of
osteoporosis and osteoporotic fractures. Epidemiol Rev 1985;7:
178–208.
59. Wark JD. Osteoporotic fractures: background and prevention
strategies. Maturitas 1996;23:193–207.
60. Pettersson U, Nordstrom P, Alfredson H, et al. Effect of high
impact activity on bone mass and size in adolescent females: a
comparative study between two different types of sports. Calcif
Tissue Int 2000;67:207–14.
61. Van Langendonck L, Claessens AL, Lefevre J, et al. Association between bone mineral density (DXA), body structure, and
body composition in middle-aged men. Am J Hum Biol 2002;
14:735–42.
62. Beunen G, Malina RM, Lefevre J, et al. Size, fatness and relative fat distribution of males of contrasting maturity status during adolescence and as adults. Int J Obes Relat Metab Disord
1994;18:670–8.
63. Hadjidakis D, Kokkinakis E, Giannopoulos G, et al. Bone mineral density of vertebrae, proximal femur and os calcis in normal Greek subjects as assessed by dual-energy X-ray
absorptiometry: comparison with other populations. Eur J Clin
Invest 1997;27:219–27.
64. Karlsson MK, Gärdsell P, Johnell O, et al. Bone mineral normative data in Malmö, Sweden. Acta Orthop Scand 1993;64:168–
72.
65. Nuti R, Martine G, Gennari C. Age-related changes of whole
skeleton and body composition in healthy men. Calcif Tissue
Int 1995;57:336–9.