Osteoporosis is an increasingly important health care concern; thus, information regarding bone status among young athletes is crucial to develop optimal exercise programs that focus not only on physical performance and muscle strength, but also on the biological and mechanical processes that facilitate the enhancement of bone acquisition during growth.
Research studies indicate that resistance training, including weight-bearing exercise, has been considered a key lifestyle factor for an optimum peak bone mass level (10,12,29,34,40). Most of the previous cross-sectional studies investigating the relationship between bone mineral status and practice of different sports were conducted in female athletes and have shown that high-impact activities were associated with a greater bone mineral content (BMC) or bone mineral density (BMD) when compared to other types of exercise which do not evoke high-impact stimulus (6,7,9,11,14,19-21,30,33,38). The few studies that included competitive swimmers demonstrated a negative association between participation in this nonimpact sport and bone mass (6,7,11,19-21,33,38).
Using the hip structure analysis to estimate the strength of the proximal femur in female adult athletes, Nikander et al. (22) have shown that high- and odd-impact sports were associated with a higher bone strength than the nonimpact sports, suggesting that the high strain rate that arises from dynamic and unusual movement directions enhances the osteogenic effect of loading in both bone mass and its distribution (22).
The relationship between bone mineral status and participation in physical activities with different mechanical loads applied to the skeleton in adolescent boys has been little explored. Ginty et al. (12) demonstrated that among adolescent boys (16–18 years of age), the daily participation in high-impact activities was associated with higher bone mass, especially at the hip. Nordstrom et al. (24-29) have thoroughly investigated bone mass status, muscle strength, and exercise participation in boys. They suggested the presence of a general osteogenic effect upon the practice of regular weight-bearing activities and also demonstrated site-specific increments in regional bone mass among those who were athletes. Additionally, a weak relationship was identified between BMD and muscle strength in adolescents engaged in sports training, whereas in nonathletes, muscle strength was found to significantly predict BMD (24-29,30). Alternatively, when Taaffe and Marcus (37) examined the role of long-term swimming on regional and total BMD in men, no osteogenic effect was identified.
The aim of this study was to compare total and regional dual-energy x-ray absorptiometry (DXA)-measured bone mineral parameters and fat-free body mass between 2 different categories of impact-loading sports in adolescent male athletes, having as reference an age-matched nonathletic control group. It was hypothesized that adolescent boys engaged in high-impact sports would have higher bone mineral and size at the whole-body and regional sites than both swimmers (nonimpact sport) and nonathlete boys do.
Experimental Approach to the Problem
The current investigation was a cross-sectional study that included adolescent male athletes and an age-matched nonathletic control group. The athletes were divided into 2 groups—a high-impact group which included athletes engaged in 1 of the 3 high-impact sports (gymnastic, basketball, and handball) and a nonimpact group, which included swimmers. A third group of boys served as control.
All athletes competed at regional, national, and international levels, whereas the control group included adolescent boys who did not practice any sport outside the school. For the athletes, the selection was made in local sports clubs, and for the sedentary controls, the selection was made in local secondary schools.
Measurements were performed by the same technician between February and April, during the morning and in standard conditions. Premeasurement conditions were standardized to maximize the validity of body composition measurements. To explore the association between bone variables and sports training, BMD, BMC, and bone area (BA) of the whole-body and selected anatomic sites were evaluated using whole-body and segmental DXA measurements. Segmental DXA measurements included the upper limbs (the average of the right and the left arms), the lumbar spine, and the lower limbs (the average of the right and the left arms). The results obtained for all the 3 groups were then analyzed. Some additional variables were also examined and used to control for growth and maturity. These included adjustments, first for the maturation level, body height, and body weight, and second for maturation, body height, and fat-free mass.
Eighty young male athletes, 9–18 years of age, were enrolled for the study. The athletes were classified into 2 groups according to the level of impact of their sport: The high-impact group (n = 34) included 9 gymnasts, 18 basketball and 7 handball players; the nonimpact group enrolled 20 swimmers. The control group included 26 age-matched nonathletic male adolescents.
All the athletes and nonathletes were recruited from local sport clubs or schools, respectively, through written and/or oral advertisements. Inclusion criteria for the athletes were the current participation in competitive sports at regional, national, or international levels for at least 2 h wk−1 in the previous 3 years. For the control group, subjects should not have participated regularly in sports training in the last 2 years. Exclusion criteria for all subjects consisted of medical history known to affect body composition, in particular bone metabolism. Subjects who were taking medication for illness or injuries along with those who were attempting to gain or lose weight were also prevented from taking part in the study.
Information about each subject's sport participation, medical history, and medication was obtained by a questionnaire.
The aims and procedures of the study were fully explained to all subjects and their parents or legal guardians, and a written informed consent was obtained. The research protocol was in accordance with the Helsinki Declaration and was approved by the Ethic Committee of the Faculty of Human Movement, Technical University of Lisbon.
Body Weight, Stature, and Pubertal Maturation
Body weight was measured using a scale (SECA model 770, Hamburg, Germany) to the nearest 0.1 kg. Stature was measured to the nearest 0.1 cm. Body mass index was calculated as body mass divided by body height (kg m−2). Pubertal maturation was determined by self-assessment of secondary sexual characteristics according to the criteria devised by Tanner (39). This method has been reported to be both valid and reliable in assessing sexual maturity among adolescent athletes (16).
Dietary Intake, Physical Activity, and Sport Participation
A semiquantitative Food Frequency Questionnaire, representing typical Portuguese foods, was administered during the laboratory visit to assess dietary intake. The questionnaire included 86 food items for which subjects indicate their habitual intake (from never or fewer than once per month to 6 or more times per day).
Habitual physical activity (PA) was assessed by a questionnaire previously validated (18,32). Each subject completed the questionnaire, and a PA index was determined. Each coach also reported the number of training sessions per week and the duration of each session. Training participation was also assessed using standard club assiduity reports completed by the respective coaches during the previous 12 months of the training season.
Bone Mass and Body Composition
A whole-body scan by DXA (QDR-4500; Hologic, Waltham, MA, USA; fan-beam mode) was used to obtain total and regional (upper and lower limbs, pelvis, and lumbar spine) measures of BMD, BMC, BA, fat-free body mass, and body fat (BF). Upper and lower limb BMD, BMC, and BA were calculated as the average of the right and left body sides. The arm region included the hand, forearm, and upper arm. This region was separated from the trunk by an inclined line crossing the scapulohumeral joint such that the humeral head was located in the arm region. The leg region included the foot and lower and upper leg and was defined by an inclined line passing just below the pelvis, crossing the neck of the femur. Bone mass in the lumbar spine was also obtained through the whole-body scan subregions.
The same laboratory technician positioned the subjects, performed the scans, and executed the analyses using the standard protocol. All subjects were asked to fast since the previous evening and to athletes to avoid sport training in the previous 24 hours. Quality assurance tests were performed each morning. On the basis of test–retest using 18 subjects, the technical error of measurement and the coefficient of variation were 0.02 kg and 1.6%, respectively.
The results are presented as mean ± SD. For regional body composition data analysis (arms and legs), we used the average of the arms and the average of the legs of the respective parameters ([right arm + left arm]/2) and [right leg + left leg/2]). We have also calculated the ratio of total BMD, total BMC, and total BA to fat-free mass.
Comparisons between the 2 groups of athletes, regarding week training hours and starting age of sport participation were made by independent t tests. Comparisons between the 3 groups regarding body composition and bone parameters were evaluated by analysis of variance with Bonferroni post hoc test when significant differences between groups occur. An analysis of covariance (ANCOVA) was further used to compare bone variables between groups, using maturation, body weight, and height as covariates. Further adjustments for maturation, stature and fat-free body mass were also performed. All statistical analyses were carried out with PASW Statistics package (SPSS Inc., Chicago, IL, USA), version 18.0.
Age, maturation level, body composition, PA, and calcium intake data are summarized in Table 1. The high-impact athletes were less mature than the other 2 groups (p < 0.05). The high-impact group presented significantly more stature and fat-free mass for the whole-body and upper and lower limbs than for the control group. Boys included in the control group had a greater percentage of BF and a lower PA index than did the other 2 groups. The nonimpact athletes trained for more hours than the high-impact athletes did (p < 0.05).
Values of the total and regional bone parameters of the participants are depicted in Table 2. The high-impact group presented greater BMD, BMC, and BA for the total body, lumbar spine, and upper and lower limbs when compared to the control group. Furthermore, this group also displayed greater BMD, BMC, and BA for the lower limbs in comparison to the nonimpact group (p < 0.05). The amount of BMC per kilogram of fat-free mass was higher in the high-impact group than in the other groups. No significant differences were observed between the nonimpact and the control group in all bone variables (p > 0.05).
The ANCOVA was performed to compare the 3 groups controlling for differences in the level of maturation, body weight, and height (Table 3). With the exception of BA variables and BMD for the upper limbs, all the differences between the high-impact and the control groups were also present between the 2 athletic groups, with the high-impact group displaying greater adjusted bone parameters (p < 0.05). No differences were observed between groups in lumbar spine and lower limbs BA (p > 0.05). Regarding fat-free mass, the high-impact athletes had higher values for total body and upper and lower limbs when compared to the control group and higher values for lower limbs when compared to the nonimpact athletes (p < 0.05). The ratio of total BA to fat-free mass remained similar for all 3 groups, whereas the amount of BMC per kilogram of fat-free mass remained higher in the high-impact athletes than in the other 2 groups (p < 0.05).
After adjusting for maturation level, fat-free mass, and body height (Table 4), most of the differences between the high-impact and control groups disappeared (p > 0.05) with the exception of the lumbar spine BMC that stayed greater in the high-impact than in the control group (p < 0.05). The high-impact group was found to have higher total body and lower limb BMD and BMC and higher lumbar spine BMC than the nonimpact group (p < 0.05). Concurrently, the control group had higher total body BMD and BMC and greater limb BMC than the nonimpact group (p < 0.05).
Figure 1 summarizes BMD, BMC, and BA comparisons between high-impact and nonimpact groups of athletes having the control group as reference. Significant differences are shown between high-impact athletes and controls after adjustments for maturation, body height, and body weight (Figures 1A–C) and between both athletic groups and controls after adjustments for maturation, body height, and fat-free mass (Figures 1D–F).
This study revealed that, after correction for maturation, body height, and weight, adolescent boys engaged in high-impact sports presented greater levels of BMC and BMD at the whole body, lumbar spine, and appendicular skeleton and greater bone size at the total body and upper limbs than nonathlete boys did. With the exception of the lumbar spine BMC, these differences were explained by the greater amount of fat-free mass in high-impact athletes, because most of the differences disappeared when adjustments for this variable were made. However, fat-free mass was not responsible for BMD or BMC differences in the total body, and especially in the axial skeleton (lumbar spine and lower limbs) between the 2 groups of athletes, in that higher values of these bone parameters were observed in high-impact athletes. When maturation, body height and fat-free mass were used to adjust values, athletes engaged in the nonimpact sport had 5–7% less total body BMD and BMC and 13% less lower limb BMC than the high-impact group of athletes did, and 3–8% less BMD and BMC than the control group in the same skeletal regions.
As previously stated, the high-impact group of this study included young male basketball players, gymnasts, and handball players. Playing basketball produces a variable pattern of high-intensity mechanical loading with peak ground-reaction forces 3.9–6.0 times the body weight, as those produced in netball (6,9,36). The basketball training of athletes participating in this study involved mainly several cycles of repetitive loads through plyometric training, running, turning with torsional and compressive forces upon the limbs, jump-shots, lay-ups, vertical jump-landing exercises, rebounding, and shooting. Additionally, these athletes performed 4–6 hours of weightlifting exercises per week.
Handball players are known to be exposed to similar impact-loading strains to those generated during basketball training. Considering bone loading forces, the current handball athletes performed maximal efforts, namely, short sprints, repeated jumps, and landings from small heights often involving the hands, and leaping and turning exercises, which are expected to produce large compressive forces on both the upper and lower limbs.
Early studies have argued that running and jumping forces, generated during gymnastic exercises, produce ground-reaction forces that may go up to 10 times body weight (4,13). During training and competitions, male gymnasts performed several sprint-running exercises with weight-bearing and jumping-landing activities, at an extreme of high-impact forces, along with exercises on the beam and trampoline, tumbling and acrobatic sequences. As opposed to basketball and handball, the mechanical loads performed by the arms during gymnastic events are symmetric because both arms are required to sustain repeated impact bursts during tumbling and vaulting and also to support the body on the bars and beam.
The nonimpact group of this study consisted of swimmers, who train in a nonweight-bearing environment where the muscle forces generated on the arms, and to a lesser degree on the legs, allow them to propel through and against the water.
Regarding bone variables, studies comparing athletes involved in high-impact sports (most included volleyball, basketball, gymnastics, netball, and softball athletes) with swimmers and nonathletic controls, have been widely developed among women (6,7,11,19,20,21,33,38). Overall, our results demonstrate that those male athletes engaged in swimming and sedentary individuals display significantly lower bone mass than those athletes involved in sports producing the greatest weight-bearing forces. In addition, it appears that the absence of impact, associated with swimming, is negatively related to bone formation and thus bone density. Taaffe and Marcus (37) examined the role of long-term swimming on regional and total BMD in adult men and confirmed the large body of results indicating no osteogenic effects of nonimpact exercises, found among women, which agrees with our findings.
Regarding the studies that have shown the osteogenic effect of high-impact activities/exercises (2,3,5-9,11,12,14,19-24,26-31,33,37,38,41), only 4 of them were conducted in adolescent boys (12,24,27,28), and no more than 1 was developed in prepubescent boys (41). One of the studies (27) included an athletic group of badminton players, besides the hockey and control groups (27). It was shown that the badminton players had a significantly higher BMD at the proximal and distal femur, compared to the ice hockey group, and this difference may have been a result of the short high-impact bursts when jumping (not present in ice hockey) and high strains in unusual directions present in badminton exercises.
A typical explanation for differential skeletal adaptations to PA/exercise is based on the overload and specificity principles: bones directly loaded by PA will increase their material properties appreciably if imposed mechanical loads exceed the normal loading patterns (1). It has been also theorized that muscle forces produced during nongravitational sports such as swimming and cycling may not exceed the minimum effective strain stimulus threshold to induce an osteogenic effect (11,15). Other studies observed that muscular contractions may have an osteogenic effect on adjacent bones (12,17,29,31,35). However, Pettersson et al (30) showed that female athletes practicing a high-impact sport (rope skipping) displayed a significantly greater BMD at several sites compared with controls, whereas no significant differences in muscle strength or lean body mass were observed. The authors suggested that the forces generated during weight-bearing activities seem to be of a greater importance than strains induced during muscular contractions. Fehling et al. (11) observed 18.5% more lean body mass in their female swimmers (9–20 years of age) than in nonathletic controls, although BMD was similar for the 2 groups (11). Among junior hockey players (24,28), a nonsignificant relationship between muscle strength of the thigh and BMD of the adjacent femur, proximal femur, and distant head was found, whereas in the control group, there was a general association between muscle strength of the thigh and the different BMD sites measures. It was suggested that the correlations between thigh muscle strength and measured BMD sites were attenuated in the athletes as compared to the reference group because normal pubertal changes in both muscle strength and the BMD of adjacent bones predominate at that time.
The variable more correlated with most of the bone parameters in this study was fat-free body mass (data not shown), commonly used as a surrogate measure of muscle mass (3). It is noteworthy that despite our nonimpact group's 9.5% greater maturation, body weight, and height adjusted fat-free mass than the controls, primarily from the upper-torso, no differences in BMD, BA, or BMC were found for the whole-body and selected sites for both swimmers and control group. Additionally, the significantly greater amounts of BMC per kilogram of fat-free mass in our boy athletes engaged in high-impact sports compared with the other 2 groups reinforces the association between regular participation in high-impact sports and bone content acquisition, independently of fat-free mass development.
Strengths of this study include the sample of adolescent male athletes, which are a relatively understudied group. Limitations of our study included the small number of athletes in each sport group and in the control group and the fact that all the bone measurements were derived from a whole-body scan.
The current cross-sectional study suggests that participation in high-impact sports such as basketball, handball, or gymnastic during adolescence is associated with greater bone benefits, particularly on bone mass in the axial skeleton (lumbar spine and lower limbs), compared to youth not involved in this type of PA. It is however possible that bone differences between groups existed before their participation in sports.
It is important to promote regular sports participation among adolescents because of the greatest fat-free mass displayed by the athletes in relation to nonathletes. Fat-free mass is composed primarily of skeletal muscle, which is an important health feature, and larger muscles develop greater forces in the bones to which they are attached.
Additionally, our results point toward a greater osteogenic effect in adolescent boys participating in high-impact sports when compared to both nonimpact athletes and controls. Thus, we suggest that the practice of sports that do not evoke ground-reaction forces must be offset with high-impact weight-bearing PA to stimulate bone mass accretion, besides fat-free mass.
These observations are supported by the National Strength and Conditioning Association (10) which states that teachers, coaches, parents, and health care providers should recognize the potential health- and performance-related benefits of incorporating resistance training among youth (10). Resistance training includes plyometric training, different strength- and weight-training such as body-weight exercises, isometric contractions, weight-machines, and other strength-building instruments such as medicine balls, elastic bands, free-weights. This is particularly important during childhood and adolescence because of the bone modeling and remodeling process (10).
Considering the interest in osteoporosis and efforts to optimize bone status and overall health features such as fat-free body mass among adolescents, it is important to include specific training programs properly designed, age-appropriated, and supervised to avoid risk of injury. Compressive and tensile forces associated with high-impact weight-bearing, and strength-building exercises should be included into the training routines of nonimpact athletes, such as swimmers and cyclists. On the other hand, nonathletic youth must be encouraged to practice weight-bearing PA and sports that incorporate strength-building and high-impact exercises. Nonetheless, additional clinical and scientific trials are needed to more adequately define exercise prescription to optimize long-term training-induced improvements in bone health and exercise adherence among youth.
The authors gratefully acknowledge the effort of the participants and their parents. This research was supported by the Portuguese Science and Technology Foundation.
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