Exercise during childhood and adolescence can improve bone mineral content (BMC) and areal bone mineral density (aBMD) with benefits maintained into adulthood (1). Low bone mass during adolescence is associated with increased fracture risk and osteoporosis later in life (2,3). The adolescent years are critical for bone development with up to 43% of peak bone mass acquired during the 5-yr period surrounding peak height velocity (PHV) (4). Bone acquisition depends on the ground reaction forces applied to the skeleton and the muscular contractions produced during exercise (5); therefore, not all the types of sport can improve bone geometry and structure (6,7).
Previous evidence indicates that weight-bearing sports, such us football, have higher aBMD and BMC at the loaded sites of the skeleton compared with non–weight-bearing sports, such as cycling and swimming (8–10). Prolonged participation in non–weight-bearing sports, such as swimming and cycling, may have a negative or no effect on bone status compared with controls (11,12), which may compromise the achievement of a higher peak bone mass (13). As part of the PRO-BONE study, we recently showed that footballers had significantly higher bone mineralization and geometrical outcomes compared with swimmers and cyclists in adolescent males at baseline and after a follow-up of 12 months (10,14,15). Collectively, these studies highlight the need to improve bone development of athletes involved in non–weight-bearing sports, such as swimming and cycling.
Football, cycling, and swimming are among the most popular sports worldwide for adolescents; however, there is currently no evidence on the effectiveness of interventions to improve bone mineralization in athletes during this period of life. Previous intervention studies were conducted in the school environment (16,17) and have shown that jumping can improve bone outcomes in nonathletic prepubertal and pubertal children (17,18). Adolescent footballers have been found to obtain the weight-bearing stimulus needed to optimize their bone health through the sport-specific weight-bearing training (10), but there is no evidence whether a jumping intervention can improve further their bone health. By contrast, adolescent swimmers and cyclists, despite improvements in lean mass, may not obtain the optimal bone mineralization during this critical period because of the lack of weight-bearing stimulus in the unloaded sites of the skeleton, such as lower limbs for swimmers (11,12). However, it is not known whether a jumping intervention can counteract the lack of weight-bearing stimulus in non–weight-bearing adolescent athletes, such as swimmers and cyclists.
Acquisition in BMC and aBMD and bone area (19) due to external mechanical loading can be measured by dual-energy x-ray absorptiometry (DXA), but adaptations in strength, structure, and geometry during growth or after an intervention such as jumping may not be detected because of the two-dimensional nature of DXA (20). However, there are studies using techniques such as hip structural analysis (HSA) to assess bone geometry estimates, such as cross-sectional area (CSA), cross-sectional moment of inertia (CSMI), and section modulus at the femoral neck in adolescents (8). In addition, the recently developed trabecular bone score (TBS), which can predict fracture risk and fragility of the lumbar spine, can provide an indirect textural index of trabecular microarchitecture in the lumbar spine (21). Moreover, the assessment of bone turnover and nutrition markers, such as N-terminal propeptide of procollagen type I (PINP), isomer of the carboxy-terminal telopeptide of type 1 collagen (CTX-I), total serum calcium, and 25-hydroxyvitamin D [25(OH)D], can provide important information about bone formation and resorption in relation to the sports practiced during adolescence (22). We recently found that footballers acquired significantly higher HSA and TBS outcomes compared with swimmers and cyclists after 1 yr of sport-specific training, and footballers had significantly higher bone formation compared with both non–weight-bearing sports (15).
The scope of the study was to examine the effects of a 9-month progressive jumping intervention program on BMC, hip geometry estimates at femoral neck, TBS at lumbar spine, and bone turnover markers in adolescent male swimmers (SWI), footballers (FOO), and cyclists (CYC). It was hypothesized that the intervention will induce significantly positive acquisition on bone outcomes in swimmers and cyclists but not in footballers.
Cohort and study design
The present 9-month randomized controlled trial intervention is the last part of the 21-month longitudinal PRO-BONE study that consisted of three measurement points (baseline, 12 months, and 21 months), and the methodology has been described previously (23). We have published the findings from (i) the cross-sectional differences in bone outcomes between the studies groups at baseline (10) and (ii) the longitudinally after 12 months of sport-specific practice in bone mass (14) and geometry and metabolism (15). The present novel 9-month randomized controlled trial jumping intervention includes bone mass and geometry outcomes at the lumbar spine and femoral neck and metabolism markers of the athletic groups.
The initial inclusion criteria of the study were adolescent males 12–14 yr old, engaged (≥3 h·wk−1) in weight-bearing (football) and/or non–weight-bearing (swimming and cycling) sports in the last 3 yr or more. The exclusion criteria were participation in another clinical trial, any acute infection lasting until <1 wk before inclusion, medical history of diseases or medications affecting bone metabolism or the presence of an injury (before inclusion) that may affect participation in their respective sports, and non-Caucasian participants. Informed consent and assent were obtained from all parents and participants included in the study. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Ethics approval was received from the following committees: 1) the Ethics Review Sector of Directorate-General of Research (European Commission, ref. number 618496), 2) the Sport and Health Sciences Ethics Committee (University of Exeter, ref. number 2014/766), and 3) the National Research Ethics Service Committee (NRES Committee South West–Cornwall & Plymouth, ref. number 14/SW/0060). For the present study, data obtained before (autumn/winter 2015/2016) and after (summer/autumn 2016) the intervention program (mean difference of visits = 289 d) are used. The Consolidated Standards of Reporting Trials (CONSORT) flow diagram is presented in Figure 1. A total of 93 adolescent males (14.1 ± 1.0 yr at preintervention) completed all pre- and postmeasurements. The sports groups were simply randomized by an independent researcher into two different groups: INT and sport (INT-SWI = 19, INT-FOO = 15, and INT-CYC = 14) and sport only (without any additional intervention) (CON-SWI = 18, CON-FOO = 15, and CON-CYC = 12).
PRO-BONE study jumping intervention program
The 9-month progressive jump intervention program (~10 min·d−1) consisted of countermovement jumps (CMJ) and was performed by participants in the INT groups. The intervention consisted of three levels (12 wk each) using adjustable weight vests (The Sports HQ, UK) and was performed on a hard surface. The intensity and the volume increased progressively by modifying the weight in the vests and the number of sets performed at each level (level 1 = 20 jumps, 0 kg, 3 sets per day, 3 times per week; level 2 = 20 jumps, 2 kg, 4 sets per day, 3 times per week; level 3 = 20 jumps, 5 kg, 4 sets per day, 4 times per week). A jump diary was used to record the number of jumps performed at each level and was returned to the research group every 3 months. Before the intervention, trained research assistants explained and demonstrated the CMJ only to INT groups, and participants executed the CMJ to ensure proper technique. The CMJ was chosen for the intervention as it has a high rate of change in force (493 times body weight per second) and ground reaction forces (5 times body weight) in 8.3- to 11.7-yr-old boys and girls (24). The reliability and validity of the CMJ has been previously reported (25).
Bone outcomes: DXA, HSA, TBS, and biochemical markers
A Lunar Prodigy DXA scanner (GE Healthcare Inc., Wisconsin) was used to measure BMC (g), fat mass (g), and lean mass (g). The lumbar spine (LS, L1–L4) and bilateral proximal femora scans were used to assess BMC. All DXA scans and subsequent in-software analyses were completed by the same researcher using the same Lunar Prodigy DXA scanner and the enCORE software version 14.10.022 (GE Healthcare Inc.) and following the International Society of Clinical Densitometry guidelines (26). The coefficient of variation (CV) was not determined in the present study, but previous pediatric studies have shown that the DXA percentage CV was between 0.6% and 1.2% at femoral neck and lumbar spine regions (27).
The HSA software analyzed the hip scans at the narrow neck region across the narrowest point of the femoral neck. The HSA software uses the distribution of bone mineral mass in line of pixels across the bone axis to measure the structural dimensions of bone cross sections (28). The hip geometry estimates of the femoral neck were obtained, and the following variables used: 1) the CSA (mm2), which is the total bone surface area of the hip excluding the soft tissue area and the trabecular bone; 2) the CSMI (mm4), which is an index of structural rigidity and reflects the distribution of mass in the center of a structural element; and 3) the section modulus (Z, mm3), which is an indicator of maximum bending strength in a cross section. The CV of these variables has been reported to be between 7.9% and 11.7% (29).
TBS is a DXA-based technological tool that provides an indirect textural index of trabecular microarchitecture in the lumbar spine and has been shown to significantly predict fracture risk independent of BMC (21). TBS assesses DXA images of the lumbar spine scans using a gray-level analysis as the slope at the origin of the log–log representation of the experimental variogram (30). All TBS analyses were performed by the same trained researcher using the TBS iNsight Software (research version 3.0, Medimaps, Pessac, France). The calculation was performed at the lumbar spine region of interest as in the BMC measurement. The CV of TBS in relation to BMC has been reported to be 1.1% to 1.9% (31).
Capillary blood samples were collected in the morning of nontraining weekends using heparin fluoride coated microvettes (CB 300 tubes; Sarstedt Ltd., Leicester, UK) and centrifuged at 3000 rpm for 15 min at 4°C. Serum samples were stored at −80°C until later analysis. Total serum levels of PINP, CTX-I, 25(OH)D, and total calcium were analyzed. ELISA kits (Abbexa Ltd., Cambridge, UK) for PINP (test range, 6–400 pg·mL−1; sensitivity, 1.2 pg·mL−1; inter- and intra-assay CV, 8.6% and 9.1%, respectively), CTX-I (test range, 0.1–7.0 ng·mL−1; sensitivity, 0.03 ng·mL−1; inter- and intra-assay CV, 8.3% and 9.2%, respectively), and 25(OH)D (test range, 3–80 ng·mL−1; sensitivity: 1.2 ng·mL−1; inter- and intra-assay CV, 6.4% and 8.0%, respectively) were used. Total calcium serum was measured using direct colorimetric assay (Cayman Chemical Company, Ann Arbor, MI) and had a sensitivity of 0.25 mg·dL−1, and the absorbance was read at 570–590 nm (inter- and intra-assay CV: 7.9% and 9.0%, respectively).
Anthropometry and maturity status
Stature (cm) and body mass (kg) were measured by using a stadiometer (Harpenden, Holtain Ltd., Crymych, UK) and an electronic scale (Seca 877, Seca Ltd., Birmingham, UK), respectively. Somatic maturity status was assessed using predicted age at PHV, which is a somatic biological maturity indicator and reflects the maximum growth velocity during adolescence. The age at PHV was predicted using age and height in validated algorithm showing how far an individual is from this maturity milestone (years from age at PHV). The coefficient of determination has been reported (R2 = 0.90, SE = 0.5) (32).
Physical activity and training characteristics
Physical activity was measured for seven consecutive days at pre- and postintervention using wrist accelerometers (GENEA, Cambridgeshire, UK). The validity and reliability of the accelerometer has been established previously in children and adolescents (33). Data were collected at 100 Hz and analyzed at 1-s epoch intervals to establish time spent in MVPA using a validated cut point (33). Weekly training hours were obtained by face to face interviews at pre- and postintervention.
Statistical analyses were performed using the SPSS version 21.0 for Windows (IBM Corp., Armonk, NY). The sample size was calculated to achieve at least 90% of statistical power as previously described (23). Data were checked for normality and presented as mean and SD. Data were analyzed for each sport group separately using 1) paired t-tests to detect mean differences in descriptive characteristics and blood marker outcomes between pre- and postintervention visits, 2) one-way ANOVA with Bonferroni post hoc to detect differences in the bone outcomes and blood markers between the intervention and the nonintervention groups of each specific sport at pre- and postintervention, and 3) one-way ANCOVA with Bonferroni post hoc was used after controlling for PRE bone status, change in lean mass, and postintervention maturity status (years from PHV) to detect differences between the intervention and the nonintervention groups in 9-month adjusted acquisition (Δ BMC, Δ HSA, and Δ TBS). The selection of the covariates was based on relevant predictors of bone outcomes in adolescents (34–36). Percentages of difference between the intervention and the nonintervention groups were used to quantify the magnitude of the differences in adjusted bone acquisition. Significance was set at P < 0.05.
Table 1 shows the mean total compliance of the intervention. There were no differences between the groups on the number of jumps performed. Table 2 presents the descriptive characteristics of the participants pre- and postintervention. No differences were observed in the descriptive characteristics presented at Table 2 between INT and CON groups at pre- and postintervention for each specific sport, P > 0.05. Footballers reported significantly higher participation in plyometric exercises (INT-FOO = 57%, CON-FOO = 55%) compared with cyclists (INT-CYC = 29%, CON-CYC = 26%) and swimmers (INT-SWI = 43%, CON-SWI = 41%). In all INT groups, all variables significantly increased from pre- and postintervention, except fat mass in INT-CYC and MVPA in all groups. Similarly, all variables significantly increased before and after in CON-SWI, CON-FOO, and CON-CYC except MVPA and fat mass.
Bone quantity, geometry, and texture
Figure 2 shows the percentage of difference on 9-month adjusted bone acquisition in BMC between the sport-specific intervention and control groups. The INT-CYC group acquired significantly higher lumbar spine BMC (4.6%) and femoral neck BMC (9.8%) than CON-CYC. Figure 3 shows the percentage of difference on 9-month adjusted bone acquisition in HSA and TBS outcomes between the sport-specific intervention and control groups. INT-CYC acquired significantly higher CSA (11.0%), CSMI (10.1%), and TBS (4.4%) than CON-CYC. INT-SWI acquired significantly higher femoral neck BMC (6.0%) and CSMI (10.9%) than CON-SWI. There were no significant differences between INT-FOO and CON-FOO for any of the bone outcomes.
Bone turnover and nutrition markers
Table 3 shows the biochemical markers of the participants pre- and postintervention. Bone formation, as measured by PINP, was reduced in all CON sport groups (4.4% in SWI, 3.3% in FOO, and 4.2% in CYC). Interestingly, bone formation did not decline in INT-SWI and INT-CYC, but it slightly did in INT-FOO (1.8%). Bone resorption, as measured by CTX-I, was reduced by 3.8% in CON-SWI and CON-CYC. However, bone resorption did not vary in any of the INT groups or in CON-FOO. 25(OH)D significantly increased in INT-CYC (3.1%), CON-CYC (3.7%), INT-FOO (3.1%), and CON-FOO (3.5%), but not in INT-SWI and CON-SWI. In all groups, serum calcium significantly increased from pre- and postintervention.
This is the first study to examine the effect of jumping intervention on BMC at clinically relevant sites, hip geometry estimates, TBS, and bone turnover markers in adolescent male athletes involved in weight-bearing (football) and non–weight-bearing (swimming and cycling) sports. The findings demonstrate that a 9-month progressive jumping intervention program can significantly improve BMC, HSA, and TBS bone outcomes at the clinically relevant skeletal sites of lumbar spine and femoral neck in non–weight-bearing sport athletes, such as swimmers and cyclists, but not in the weight-bearing sport athletes, such as footballers [see Table, Supplemental Digital Content 1, PRE and 9-month adjusted acquisition in BMC (g) HSA parameters and TBS of the intervention and control groups, https://links.lww.com/MSS/B347]. In addition, bone formation (PINP) was maintained in the non–weight-bearing INT sport groups but decreased in the CON non–weight-bearing sport groups. Moreover, bone resorption (CTX-I) significantly decreased in the CON non–weight-bearing sport groups but did not vary in any of the INT groups, suggesting an increased bone turnover in these groups.
Jumping intervention effects on BMC at femoral neck and lumbar spine
Currently, there are no jumping intervention studies conducted in an athletic population to improve bone outcomes; therefore, the findings of the present study were compared with jumping interventions applied in nonathletic children and adolescents (16–18). The present jumping intervention significantly improved femoral neck BMC (6.0%–9.8%) in INT-SWI and INT-CYC compared with CON-SWI and CON-CYC, and lumbar spine BMC (4.6%) in INT-CYC compared with CON-CYC. Previously, an 8-month school-based jumping intervention reported that nonathletic adolescent males and females acquired 6.0% higher femoral neck BMC and 2.3% higher lumbar spine BMC compared with controls (17). Also, a 7-month school-based jumping intervention reported that nonathletic prepubescent children had 4.5% and 3.1% significantly higher acquisition at femoral neck and lumbar spine BMC, respectively, compared with age-matched controls (37). The greater magnitude of improvements observed in HSA at the femoral neck and TBS at lumbar spine of swimmers and cyclists in the current study may be explained by the ability of the unloaded skeletons of the non–weight-bearing groups to respond better to the external stimulus of the jumping intervention (8). Another explanation might be the longer duration of the present intervention (9 vs 7–8 months) and the greater number of jumps performed in the present study (160 vs 90 jumps per week) (18,20) by increasing the ground reaction forces applied to the skeleton progressively using the weight vests. These improvements may indicate a window of opportunity to counteract the lack of weight-bearing stimulus observed in adolescent swimmers and cyclists (10,12,38). By contrast, but consistent with our hypothesis, the stimulus provided by the jumping intervention was insufficient to induce significant bone acquisition in INT-FOO compared with CON-FOO. This finding may be explained by the mechanostat theory, indicating that bones adapt their strength and content in response to the strain caused by external physiological loads up to a certain point (39). We therefore propose that footballers may have reached a threshold for bone improvements through their sport-specific training as we have previously shown, in a 1-yr follow-up, this group to have greater bone outcomes compared with swimmers and cyclists (10). However, it cannot be discounted that a longer jumping intervention program may be needed to further improve bone outcomes in weight-bearing sports, such as football.
Jumping intervention effects on HSA and TBS outcomes
In addition to BMC adaptations, the present 9-month jumping intervention significantly improved HSA and TBS bone parameters. More specifically, INT-CYC acquired significantly higher CSA (11.0%), CSMI (10.1%), and TBS (4.4%) compared with CON-CYC, and INT-SWI acquired significantly higher CSMI (10.9%) compared with CON-SWI. Previously, only two studies previously used HSA to describe bone geometry and structural strength adaptations from a jumping intervention in nonathletic populations (18). Petit et al. (20) reported that a 7-month jumping intervention induced significantly greater increase in CSA (2.3%) and section modulus (4.0%) in the intervention group compared with an age-matched nonathletic control group. McKay et al. (18) did not find significant improvements in HSA parameters after an 8-month jumping intervention in nonathletic pubertal children, but section modulus (3.3%) and CSA (2.0%) had similar magnitude of increase with the study of Petit et al. In the present study, the greater improvements in bone outcomes of swimmers and cyclists compared with footballers may be explained by mechanoadaptation that converts the external stimulus of the jumping intervention to greater structural adaptations of previously unloaded bones (40). The present study is the first to present findings on TBS adaptations after a jumping intervention in adolescent athletes. Currently, there are no jumping intervention studies using TBS, and only a recent cross-sectional study in adults reported that moderate impact loading sports was associated with a lower TBS score and increased fracture risk compared with high impact loading sports (41). The present study indicates that trabecular structure at the lumbar spine may be adapted to the forces produced from the jumping intervention after controlling for potential confounders (42). The compliance in the present study was slightly lower compared with a different study (70% vs 80%) (16), and this might be due to the longer duration of the present intervention (9 vs 7 months) (16). However, the present jumping intervention had 1–2 months greater duration and progressive loading compared with previous studies, which might be responsible for the higher acquisition observed. The latter is similar with a 20-month exercise randomized control trial in prepubertal nonathletic males that found greater magnitude of improvements in CSMI (12.3%) and section modulus (7.4%) in the intervention group compared with age-matched controls (43).
Jumping intervention effects on biochemical markers
The analysis of biochemical markers in the present study showed that the jumping intervention prevented the significant decline of bone formation (PINP) and resorption (CTX-I) markers in INT-SWI and INT-CYC. By contrast, bone formation significantly decreased in INT-FOO and all CON-SPORT groups, and bone resorption significantly decreased in CON-SWI and CON-CYC. Previous studies have shown that bone turnover markers are associated with bone outcomes during growth and can provide additional information about bone remodeling (22). In addition, the intensity of physical activity and the type of sports practiced may be potent regulators of bone remodeling (15). Recently, a study has shown that one session of plyometric jumping exercises can stimulate bone formation in boys and young men, with boy’s response to be more pronounced (44). However, there are no studies investigating the response of bone turnover markers after a longer jumping intervention in combination with clinically relevant bone outcomes. The findings of the present study suggest that the cellular activity of bone turnover markers (both formation and resorption) in INT-SWI and INT-CYC was protected from declining due to the jumping intervention. In addition, serum calcium significantly increased from pre- and postintervention, and 25(OH)D significantly increased in INT-CYC, CON-CYC, INT-FOO, and CON-FOO, but not in INT-SWI and CON-SWI. There was an expected increase in serum calcium levels by age in adolescents, and the significant increase of 25(OH)D in cyclists and footballers might be explained by the higher exposure to sunlight during training in these sports, although other parameters such as dietary intake and the sampling period have been reported to affect 25(OH)D levels (45).
Strengths and limitations
The strengths of the present study include the evaluation for first time of a novel 9-month progressive jumping intervention program in adolescent athletes participating in weight-bearing and non–weight-bearing sports. In addition, the combination of DXA, HSA, TBS, and biochemical markers can provide novel and clinically relevant findings regarding the bone acquisition induced from a jumping intervention program in adolescent male athletes. The low cost and relative ease jumping program for young athletes represents an additional strength, and almost any sport club could implement the program with minimal training for the coach and the athlete. The limitations of this intervention include the lack of ground reaction forces assessment and the unavailability of three-dimensional imaging techniques to assess bone strength and structure, such as peripheral quantitative computed tomography. We studied only Caucasian athletes due to the evidence that bone accrual and the effectiveness of an intervention varies depending on the ethnicity (16,46). The latter would have required of a much larger sample size and resources, which was beyond the scope of this study. Future interventions could be conducted in more diverse populations including females, other ethnic and sports groups.
This is the first randomized control trial to investigate the effects of a 9-month progressive jumping intervention program on bone mass, geometry, texture, and biochemical markers in adolescent male athletes. The findings indicate that the jumping intervention program can significantly improve bone quantity, geometry, and TBS bone outcomes at the femoral neck and lumbar spine and maintain the bone turnover in adolescent male athletes involved in swimming and cycling, but not in football. The present jumping intervention program can be implemented by non–weight-bearing sports clubs and athletes to improve bone health.
The authors gratefully acknowledge the adolescents, parents, and sport coaches and schools who helped and participated in this study. The authors also gratefully acknowledge the researchers of Children’s Health and Exercise Research Centre for their continuous support and help with the study.
Dr. Gracia-Marco acknowledges “Programa de Captacion de Talento-UGR Fellows”; as part of “Plan Propio” of the University of Granada (Spain). The research leading to these results has received funding from the European Union Seventh Framework Programme ([FP7/2007–2013] under grant agreement no. PCIG13-GA-2013-618496.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.
Ethics approval was received from the following committees: 1) the Ethics Review Sector of Directorate-General of Research (European Commission, ref. no. 618496), 2) the Sport and Health Sciences Ethics Committee (University of Exeter, ref. no. 2014/766), and 3) the National Research Ethics Service Committee (NRES Committee South West–Cornwall & Plymouth, ref. no. 14/SW/0060).
The authors declare that they have no competing interests.
The results of the study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation, and the present study does not constitute endorsement by the American College of Sports Medicine.
D. V. collected the data and drafted the manuscript. L. G. M. designed the study and approved the final manuscript as submitted. A. R. B. and C. A. W. coordinated and supervised data collection, critically reviewed the manuscript, and approved the final manuscript as submitted. E. U. G. contributed to data collection and critically reviewed the manuscript and approved the final manuscript as submitted. All authors have read and approved this work.
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