Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=rjsp20 Journal of Sports Sciences ISSN: (Print) (Online) Journal homepage: www.tandfonline.com/journals/rjsp20 Skeletal site-specific effects of jump training on bone mineral density in adults: a systematic review and meta-analysis Gabriella E Florence, Tanja Oosthuyse & Andrew N Bosch To cite this article: Gabriella E Florence, Tanja Oosthuyse & Andrew N Bosch (2023) Skeletal site-specific effects of jump training on bone mineral density in adults: a systematic review and meta-analysis, Journal of Sports Sciences, 41:23, 2063-2076, DOI: 10.1080/02640414.2024.2312052 To link to this article: https://doi.org/10.1080/02640414.2024.2312052 View supplementary material Published online: 02 Feb 2024. Submit your article to this journal Article views: 177 View related articles View Crossmark data https://www.tandfonline.com/action/journalInformation?journalCode=rjsp20 https://www.tandfonline.com/journals/rjsp20?src=pdf https://www.tandfonline.com/action/showCitFormats?doi=10.1080/02640414.2024.2312052 https://doi.org/10.1080/02640414.2024.2312052 https://www.tandfonline.com/doi/suppl/10.1080/02640414.2024.2312052 https://www.tandfonline.com/doi/suppl/10.1080/02640414.2024.2312052 https://www.tandfonline.com/action/authorSubmission?journalCode=rjsp20&show=instructions&src=pdf https://www.tandfonline.com/action/authorSubmission?journalCode=rjsp20&show=instructions&src=pdf https://www.tandfonline.com/doi/mlt/10.1080/02640414.2024.2312052?src=pdf https://www.tandfonline.com/doi/mlt/10.1080/02640414.2024.2312052?src=pdf http://crossmark.crossref.org/dialog/?doi=10.1080/02640414.2024.2312052&domain=pdf&date_stamp=02 Feb 2024 http://crossmark.crossref.org/dialog/?doi=10.1080/02640414.2024.2312052&domain=pdf&date_stamp=02 Feb 2024 PHYSICAL ACTIVITY, HEALTH AND EXERCISE Skeletal site-specific effects of jump training on bone mineral density in adults: a systematic review and meta-analysis Gabriella E Florence a, Tanja Oosthuyse b,c and Andrew N Bosch c aInstitute of Sport and Exercise Medicine, Division of Orthopaedic Surgery, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa; bSchool of Physiology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; cHealth through Physical Activity, Lifestyle and Sport Research Centre, Division of Physiological Sciences, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa ABSTRACT Preserving or preventing declines in bone mineral density (BMD) is imperative. As jumping is a high- impact bone-loading action, this meta-analysis evaluated the efficacy of jump training to improve BMD and bone turnover relative to non-jumping controls in men and women > 18 years, following Preferred Reported Items for Systematic Reviews and Meta-Analysis guidelines. PubMed and COCHRANE Library databases were searched until February 2022. Fifteen articles (19 jumping-trials) met the predetermined search criteria. Eighteen trials were included for BMD data (n = 666 participants). There was a significant small-moderate effect of jumping on femoral neck BMD (%mean difference: 95%CI, +1.50%: 0.83%; 2.17%, p < 0.0001), that remained significant after sub-analysis by age for both younger (+1.81%: 0.98%; 2.65%) and older adults (+1.03%: 0.02%; 2.03%). BMD of total hip (+1.26%: 0.56%; 1.96% vs + 0.06%: −0.96%; 1.08%), and trochanter (+0.84%: 0.20%; 1.48% vs −0.16%: −1.08%; 0.76%) increased significantly with jump training only in younger adults and non-significantly at the lumbar spine (+0.84%: −0.02%; 1.7% vs −0.09%: −0.96%; 0.77%) only in younger but not older adults, respectively. The BMD response to jump training appears to be site-specific, with the highest sensitivity at the femoral neck. No dose-response effect suggests moderate certainty of a gain in femoral neck BMD when performing the median jump-load of 50 jumps four times weekly. ARTICLE HISTORY Received 21 June 2022 Accepted 19 January 2024 KEYWORDS Adults; bone mineral density; bone turnover; jumping; osteoporosis Introduction Peak bone mass is attained by 30 years. Inevitably, bone loss will begin to occur thereafter, with the greatest decline in bone mass occurring after 50 years (Dasarathy & Labrador, 2018). In fact, bone mass losses of 0.3%-1.1% per year at the hips and lumbar spine have been reported in men up to 50 years and premenopausal women (Vondracek et al., 2009; Warming et al., 2002). Notably, in men older than 50 years (Kanis, 2002) and postmenopausal women (Khosla & Riggs, 2005; Marcus, 2002), the rates of bone mass loss at these axial skeletal sites can increase to 0.7%–2% per year and up to 15% over 5 years during the menopausal period (Finkelstein et al., 2008). In time, this may lead to osteoporosis, a skeletal disorder charac- terised by low bone mass and increased bone fragility and susceptibility to fractures (Dasarathy & Labrador, 2018). Indeed, fractures occurring due to osteoporosis are often more serious than many realise, with reports of an 8%–36% mortality rate within 1 year for osteoporotic hip fractures (Abrahamsen et al., 2009). In addition, related medical expenses may present heavy socio-economic burdens on individuals and their families (Compston, 2010). Evidence suggests that performing sufficient weight- bearing or impact exercise can minimise a loss in bone mineral density (BMD) (Barry & Kohrt, 2008; Dasarathy & Labrador, 2018; Kohrt et al., 2004; Wolff et al., 1999), and to some extent, reverse age-related bone loss (Bolam et al., 2013; Mathis & Caputo, 2018; Wolff et al., 1999). In contrast, many endurance sports, such as cycling and swimming, are non-weight bearing and non-impact and consequently provide a poor bone loading stimulus at axial skeletal sites that are not directly stimulated by muscle contractions during the sports-specific exercise action (Dolan et al., 2006). Recently, the alert has been raised for the need to evaluate the efficacy of preventive interventions to curb or correct age-related declines in BMD (Hilkens et al., 2021; Jonvik et al., 2022; Karsenty & Khosla, 2022). Jumping is one such example of high impact, weight- bearing exercise that is expected to produce bone strains sufficient in size to promote and maintain bone mineralisation (Al Nazer et al., 2012; Dolan et al., 2006). Most studies imple- menting jumping interventions designed to improve bone health have planned each session to last less than 20 min, incorporating either simple one- or two-legged jumps or a variety of jumping styles (Table 1). Importantly, jumping interventions do not appear to cause any adverse effects in premenopausal women (Bassey & Ramsdale, 1994), postmeno- pausal women (Hartley et al., 2020), older men (Bolam et al., 2013), osteopenic men (Hinton et al., 2015) or children (Heinonen et al., 2000; Vlachopoulos et al., 2018). As such, jumping exercise can be commended as a low cost, safe, and CONTACT Tanja Oosthuyse oosthuyse@polka.co.za HPALS Research Centre Division of Physiological Sciences, Department of Human Biology, University of Cape Town, Sports Science Institute of South Africa, Boundary Road, Cape Town 7700, South Africa Supplemental data for this article can be accessed online https://doi.org/10.1080/02640414.2024.2312052. JOURNAL OF SPORTS SCIENCES 2023, VOL. 41, NO. 23, 2063–2076 https://doi.org/10.1080/02640414.2024.2312052 © 2024 Informa UK Limited, trading as Taylor & Francis Group http://orcid.org/0000-0002-6203-405X http://orcid.org/0000-0002-4065-4506 http://orcid.org/0000-0002-9543-9408 https://doi.org/10.1080/02640414.2024.2312052 http://www.tandfonline.com https://crossmark.crossref.org/dialog/?doi=10.1080/02640414.2024.2312052&domain=pdf&date_stamp=2024-02-29 time-efficient non-pharmacological strategy that may be effec- tive at improving bone health. Additionally, the little space and equipment required make jumping an accessible form of exercise. According to the mechanostat theory for bone modelling, a certain minimum threshold of bone strain is required for bone maintenance (~200–1500 microstrain units), and healthy bone modelling (bone gain) occurs between ~ 1000 and 3000 micro- strain units (Frost, 2003; Hughes et al., 2020). Notably, the effects of exercise on bone are specific to the area on which mechanical loading is applied, with the biggest response occur- ring at sites where the mechanical load is the greatest (Oosthuyse et al., 2017). Jumping has been reported to gener- ate sufficient strain magnitudes to support bone maintenance and even bone accretion (Al Nazer et al., 2012). For example, a 2-legged vertical jump to a height of 5 cm above the ground imposes 600 microstrain units on the tibia, and the same jump to 10 cm imposes 1848 microstrain units on the tibia (Al Nazer et al., 2012). By comparison, level walking and running typically imposes 237 microstrain units and 847 microstrain units, while uphill/downhill walking and running imposes 381/414 micro- strain units and 743/1226 microstrain units on the tibia, respec- tively (Al Nazer et al., 2012). Both impact and non-impact exercise stimulate muscle con- tractions that produce strains on associated bones. However, ground reaction forces (GRFs) are only generated during impact exercise, which takes advantage of body weight to mechanically load the associated bones (Dolan et al., 2006; Groothausen et al., 1997). Typically, magnitudes of high and low bone-loading strains are defined as GRF values greater than 4 times body weight and less than 2 times body weight, respectively, with higher GRFs usually producing more favour- able effects on bone accretion (Groothausen et al., 1997). Previous research using two-legged jumping has reported var- ious landing GRF values of 2 times body weight (Bassey & Ramsdale, 1994; Heinonen et al., 1996), 3 times body weight (Arnett & Lutz, 2002; Bassey et al., 1998; McKay et al., 2005), and more than 5 times body weight (Bolam et al., 2015; Cheng et al., 2002; Fuchs et al., 2001; Heinonen et al., 1996; Kato et al., 2006; McKay et al., 2005; Vlachopoulos et al., 2015) during different jumping exercises. Each of these respective studies reported an increase in BMD or bone mineral content in at least one bone region attributed to the study’s jumping intervention. These findings add support for a GRF of larger than 2 times body weight being required to support bone accretion. Unilateral jumping, or hopping, has also been utilised in bone health interventions, generating GRFs between 2- and 3-times body weight (Allison et al., 2013, 2015; Bailey & Brooke-Wavell, 2010; Hartley et al., 2020), only this time, the GRF is applied to a single leg. Although the GRF produced during a unilateral hop and bilateral jump appear to be similar, bilateral jumps may be preferential from a time and effort perspective. A previous meta-analysis evaluated the effect of jump train- ing on BMD in premenopausal women but was limited to 7 jump-intervention groups from 6 studies of which 2 jump- intervention groups implemented combined jump and lower- body resistance training (Zhao et al., 2014). As a result, the low certainty of effect for the improvement in BMD at the femoral neck and trochanter in that prior population-restricted meta- analysis (Zhao et al., 2014) might not be exclusively attributed to jump training alone. Therefore, a more extensive review is necessary, that is inclusive of both sexes and all adult ages and excludes for concurrent lower-body resistance training. Given the above, we aimed to establish the mean expected percentage gain in BMD and the standardised effect size response to jump training, measured at axial skeletal sites (namely, the femoral neck, trochanter, total hip, and lumbar spine), to quantify efficacy. For this purpose, we conducted a systematic review and meta-analysis of prospective rando- mised controlled and non-randomised controlled intervention studies that assessed the effects of jump training on BMD and circulating bone turnover marker concentrations in adult men and women. In addition, sub-analyses for BMD were performed to investigate for differences between younger (<50 years) and older (>50 years) adults. Materials and methods This systematic review and meta-analysis was conducted according to the Cochrane Handbook for Systematic Reviews and Interventions (Higgins et al., 2011). All results are reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (Moher et al., 2009). Literature search We searched PubMed and COCHRANE Library databases up until 28-February 2022 for the effects of jump training on measurements of bone health (see Supplementary Material S1 for the list of search terms). Electronic searches were supple- mented with manual searches of references from review articles. Selection criteria Controlled intervention studies with pre- and post-intervention measurements comparing the effect of jump training with non- jumping groups on BMD or bone turnover markers were included. Only full-text, peer-reviewed journal articles written in English were included. We included all relevant human studies with healthy men and women older than 18 years and with no underlying illnesses or use of medication or hormone replacement therapy that may influence bone metabolism. Studies were excluded if the participants completed lower- body resistance training or high impact exercise in the six months preceding the jump intervention. Studies were included if only jumping exercises were performed for the jumping intervention group and compared with results from non-jumping controls. Outcomes The outcome measures were (a) mean percentage changes and its percentage standard deviation (SD) in BMD of the femoral neck, total hip, femoral trochanter and lumbar spine (L2-L4), as assessed by dual-energy x-ray absorptiometry (DXA) scans, and (b) absolute mean and SD of pre- and post-intervention circu- lating concentrations of bone turnover markers. 2064 G. E. FLORENCE ET AL. Procedures Selection of studies Two reviewers (GEF and TO) independently reviewed the inclu- sion and exclusion of articles and disagreements were dis- cussed and resolved. Data extraction and management Data from included reports were independently extracted and analysed twice by the two reviewers (GEF and TO). In the absence of numerical values for outcome measurements, values were extracted from published figures. Most studies presented BMD percentage changes in bar graphs either as mean percen- tage change and standard error (SE) or 95% confidence interval (95%CI), which were converted to standard deviation (SD) using standard statistical equations (see Supplementary Material S2 for the data extraction method and equations). Bone turnover markers were reported according to units specific to each marker. Risk of bias assessment Included studies were assessed for risk of bias by the two reviewers (GEF and TO) using the Cochrane Collaboration risk of bias tool (Higgins et al., 2011). The included studies were evalu- ated for low risk, high risk, or an unclear risk of selection bias, performance bias, detection bias, attrition bias and reporting bias. Any additional sources of bias were identified. The two reviewers provided justifications for the risk of bias selection. Consensus between the two reviewers was obtained for all risk of bias assessments. Funnel plots were applied for the assessment of publication bias for BMD data. In the absence of publication bias, the funnel plot should create a symmetrical inverted funnel shape. Conversely, an asymmetrical funnel shape may indicate that some level of publication bias is present (Sterne et al., 2011). Review Manager (RevMan 5.4.1) was used to perform the risk of bias assessments and generate funnel plots. Statistical analyses Measures of treatment effect Review Manager was used for primary data analyses and forest plots. The random effects model was applied to per- form the meta-analysis at each BMD site and obtain the mean difference (MD) and standardised mean differences (SMD) with 95% confidence intervals for the jump- intervention relative to the control-intervention. The ran- dom effects model allows for possible variability in popula- tion effect sizes (Borenstein et al., 2010) that could occur owing to the inclusion of studies with various sample popu- lations differing in adult ages or sex. The MD and SMD estimated the mean percentage change and effect size (ES) at each BMD site, respectively. Bone turnover marker concentrations were reported only as absolute pre- and post-intervention concentrations and for this reason were analysed separately for the jump-intervention and control- intervention to obtain SMD with 95%CI to estimate effect sizes for jump and control conditions separately. The SMD effect size scores were interpreted as: 0.0–0.2, trivial; 0.2–0.6, small; 0.6–1.2, moderate; or 1.2-2.0, large effects, respectively (Hopkins et al., 2009). A p-value <0.05 was regarded as significant. Assessment of heterogeneity Heterogeneity between the included studies was quantified with I-squared (I2). I2 values between 0% and < 50% were considered low heterogeneity; 50% to < 75% were considered moderate heterogeneity; and ≥ 75% were considered high heterogeneity. In the case of significant heterogeneity (I2 >50% or p > 0.10), firstly subgroup analysis and finally sensitivity tests were applied to determine if a select study was responsible for the heterogeneity. Sub-group analyses Sub-analyses for age grouped as younger adults (<50 years) and older adults (>50 years) were conducted for BMD outcome variables, which concurrently stratified the studies in premeno- pausal women with younger adults and postmenopausal women with older adults. Differences in the mean effects between sub-groups were tested, where p < 0.1 was regarded as significant (Richardson et al., 2019). Sub-group study char- acteristics (Table 1) were compared using an unpaired t-test with significance accepted as p < 0.05. Osteogenic index We calculated the osteogenic index (OI) per week for each jump-intervention group (Table 1) using the method described by Turner and Robling (2003). The OI integrates the jumps per session and weekly jump frequency to generate a composite bone stimulus index (see Supplementary Material S3 for a description of OI and the equations applied). Grading of the evidence The GRADE approach (grading of recommendations, assess- ment, development, and evaluation) was used to assess the certainty of the effect estimate outcomes (see Supplementary Material S4 for the list of standard grading criteria). Results Search results Figure 1 shows the systematic search and selection of included articles. Of the 1092 articles identified from searches, 1035 were excluded based on their titles and abstracts. Thirty articles were reviewed in full, and an additional 15 articles were excluded based on eligibility criteria. One study included upper body resistance training with the jumping exercise intervention and the results pertaining to changes in bone turnover markers were excluded from this meta-analysis (Bolam et al., 2015). The meta-analysis was conducted on 14 randomised controlled trials (where participants were randomly assigned to the inter- vention or control group) and 1 non-randomised controlled trial (where participants self-selected to participate in either the intervention or control group), including a total of 760 participants. Fifteen articles that included a total of 19 inter- vention groups met the predetermined search criteria. JOURNAL OF SPORTS SCIENCES 2065 Ta bl e 1. G en er al c ha ra ct er is tic s of in cl ud ed s tu di es . Au th or s Pa rt ic ip an ts Sa m pl e si ze (n ) Ag e (m ea n± SD ) Ju m p in te rv en tio n du ra tio n (m on th s) Ju m p in te rv en tio n de ta ils v s. Co nt ro l Ju m p fr eq ue nc y (d ay s/ w ee k) To ta l ju m ps p er w ee k Ju m p O st eo ge ni c In de x pe r w ee k (O I/ w k) M ea su re d BM D s ite s; B on e tu rn ov er m ar ke rs YO U N G ER A D U LT S (< 50 y ea rs ) Ba ile y an d Br oo ke -W av el l (2 01 0) Pr em en op au sa l w om en J2 : 1 6 J4 : 1 3 J7 : 1 6 C: 2 0 34 ± 1 1 6 50 1 -le g ho ps vs . c on le g 2 4 7 10 0 20 0 35 0 24 47 83 Fe m or al n ec k, t ot al h ip , tr oc ha nt er Ba ss ey e t al . (1 99 8) Pr em en op au sa l w om en J: 30 C: 2 5 37 ± 8 5 50 2 -le g ju m ps vs . c on 6 30 0 70 Fe m or al ne ck , l um ba r sp in e, tr oc ha nt er ; O C, N Tx H ei no ne n et a l. (1 99 6) Pr em en op au sa l w om en J: 39 C: 4 5 39 ± 3 18 10 0– 20 0 2- le g ju m ps v s. c on 3 45 0 48 Fe m or al n ec k, t ro ch an te r Ka to e t al . ( 20 06 ) Pr em en op au sa l w om en J: 18 C: 1 8 20 ± 1 6 10 2 -le g ju m ps vs . c on 3 30 22 Fe m or al n ec k, lu m ba r sp in e, t ro ch an te r; D PD Sh ib at a et a l. (2 00 3) Pr em en op au sa l w om en J: 11 C: 1 7 37 ± 6 12 10 2 -le g ju m ps & 1 0 00 0 st ep s vs . 1 0 00 0 st ep s co n 7 70 50 Fe m or al n ec k Su gi ya m a et a l. (2 00 2) Pr em en op au sa l w om en J: 14 C: 1 6 48 ± 4 6 10 0 2- le g ju m ps vs . c on 2 20 0 32 Fe m or al n ec k, lu m ba r sp in e, t ot al h ip Tu ck er e t al . (2 01 5) Pr em en op au sa l w om en J1 0: 2 3 J2 0: 1 4 C: 2 3 40 ± 5 4 J1 0: 1 0 2- le g ju m p 2× /d ay J 20 : 20 2 -le g ju m p 2× /d ay v s. c on 6 6 12 0 24 0 75 95 To ta l h ip Va in io np ää e t al . (2 00 5) Pr em en op au sa l w om en J: 39 C: 4 1 38 ± 2 12 †4 0 m in h ig h- im pa ct ju m p vs . c on 3 80 0 66 Fe m or al n ec k, t ro ch an te r YO U N G ER A D U LT S (< 50 y ea rs ) M ed ia n 37 6 50 4 20 0 50 M ea n (R an ge ) 36 (2 0– 48 )* 8 (4 –1 8) 69 (1 0– 16 7) 4 (2 –7 ) 26 0 (3 0– 80 0) 56 (2 2– 95 ) O LD ER A D U LT S (> 50 y ea rs ) Al lis on e t al . (2 01 3) O ld er m en J: 35 C: 3 5 70 ± 4 12 50 1 -le g ho ps vs . c on le g 7 35 0 83 Fe m or al n ec k, t ro ch an te r Ba ss ey e t al . (1 99 8) Po st m en op au sa l w om en J: 45 C: 3 2 55 ± 4 12 50 2 -le g ju m ps v s. c on 6 30 0 70 70 Fe m or al n ec k, lu m ba r sp in e, t ro ch an te r; O C, N Tx Bo la m e t a l. (2 01 5) O ld er m en J4 0: 1 5 J8 0: 1 3 C: 1 3 60 ± 7 9 J4 0: 4 0 2- le g ju m ps J8 0: 8 0 2- le g ju m ps vs . c on 4 4 16 0 32 0 45 53 Fe m or al n ec k, lu m ba r sp in e, t ot al h ip , tr oc ha nt er H ar tle y et a l. (2 02 0) Po st m en op au sa l w om en J: 35 C: 3 5 62 ± 4 6 50 1 -le g ho ps vs . c on le g 7 35 0 83 Fe m or al n ec k Se n et a l. (2 02 0) Po st m en op au sa l w om en J: 16 C: 1 8 54 ± 5 6 60 2 -le g ju m ps vs . c on 3 18 0 37 Fe m or al n ec k, lu m ba r sp in e, t ot al h ip ; O C, C Tx Su gi ya m a et a l. (2 00 2) Po st m en op au sa l w om en J: 13 C: 1 3 53 ± 4 6 10 0 2- le g ju m ps vs . c on 2 20 0 32 Fe m or al n ec k, lu m ba r sp in e, t ot al h ip O LD ER A D U LT S (> 50 y ea rs ) M ed ia n 59 9 50 4 30 0 53 M ea n (R an ge ) 59 (5 3– 70 )* 9 (6 –1 2) 60 (4 0– 87 ) 5 (2 –7 ) 26 6 (1 60 –3 50 ) 58 (3 2– 83 ) (C on tin ue d) 2066 G. E. FLORENCE ET AL. Ta bl e 1. (C on tin ue d) . Au th or s Pa rt ic ip an ts Sa m pl e si ze (n ) Ag e (m ea n± SD ) Ju m p in te rv en tio n du ra tio n (m on th s) Ju m p in te rv en tio n de ta ils v s. Co nt ro l Ju m p fr eq ue nc y (d ay s/ w ee k) To ta l ju m ps p er w ee k Ju m p O st eo ge ni c In de x pe r w ee k (O I/ w k) M ea su re d BM D s ite s; B on e tu rn ov er m ar ke rs A LL B M D S TU D IE S M ed ia n 41 6 50 4 20 0 52 M ea n (R an ge ) 45 (2 0– 70 ) 8 (4 –1 8) 65 (1 0– 26 7) 5 (2 –7 ) 25 2 (3 0– 80 0) 56 (2 2– 95 ) A D D IT IO N A L BO N E TU RN O V ER M A RK ER S TU D IE S H in to n et a l. (2 01 5) O st eo pe ni c m en J: 19 RT : 1 9 44 ± 2 12 12 0 2- le g ju m ps vs . R T co n 3 36 0 48 O C, C Tx Ra nt al ai ne n et a l. (2 01 1) O ld er m en J: 9 C: 9 72 ± 4 3 7× 10 s 2 -le g ju m ps vs . c on 3 21 0 28 PI CP , C Tx Va in io np ää e t al . (2 00 9) Pr em en op au sa l w om en J: 37 C: 3 9 38 ± 2 12 50 2 -le g ju m ps vs . c on 6 30 0 71 P1 N P, T RA P5 b A LL B O N E TU RN O V ER M A RK ER S TU D IE S M ed ia n 44 6 50 3 30 0 48 M ea n (R an ge ) 46 (2 0– 72 ) 8 (3 –1 2) 59 (1 0– 12 0) 4 (3 –6 ) 24 0 (3 0– 36 0) 49 (2 2– 71 ) BM D : b on e m in er al d en si ty ; C : n on -e xe rc is in g co nt ro l g ro up ; P IC P: C -t er m in al c ol la ge n pr op ep tid e; c on : n on -e xe rc is in g co nt ro l; CT x: C -t er m in al te lo pe pt id e of ty pe I co lla ge n; D PD : d eo xy py rid in ol in e; J: ju m p in te rv en tio n gr ou p; J2 : ju m p 2 da ys /w ee k; J 4: ju m p 4 da ys /w ee k; J 7: ju m p 7 da ys /w ee k; J 10 : 1 0 ju m ps 2 × /d ay ; J 20 : 2 0 ju m ps 2 × /d ay ; J 40 : 4 0 ju m ps /s es si on ; J 80 : 8 0 ju m ps /s es si on ; N Tx : N -t er m in al te lo pe pt id es o f t yp e I c ol la ge n; O C: o st eo ca lc in ; P 1N P: N -t er m in al p ro pe pt id e of ty pe I pr oc ol la ge n; R T: re si st an ce tr ai ni ng ; T RA P5 b: ta rt ra te re si st an t a ci d ph os ph at as e; † de no te s th at th e ex ac t n um be r o f j um ps /s es si on is u nk no w n fo r t hi s st ud y an d an e st im at e is a pp lie d ba se d on tim e; * de no te s a si gn ifi ca nt d iff er en ce in t he a ge o f t he p ar tic ip an ts in t he y ou ng er (< 50 y ea rs ) a nd o ld er (> 50 y ea rs ) s tu di es , p < 0 .0 00 1. JOURNAL OF SPORTS SCIENCES 2067 Description of studies The general descriptions of the included studies are presented in Table 1. Studies were conducted in premenopausal women, postmenopausal women or older men, in addition to one single study in young osteopenic men that was included only for the change in bone turnover markers. Five studies included more than one jump exercise group. Studies incorporating more than one jump intervention group differed in the weekly frequency (Bailey & Brooke-Wavell, 2010) or intensity of the jump training (Bolam et al., 2015; Tucker et al., 2015) or age of participant groups, and in this latter case included separate age-matched control groups (Bassey et al., 1998; Sugiyama et al., 2002). Each jump group was analysed separately and compared with the non-jumping control group. Four studies were conducted in the United Kingdom (Allison et al., 2013; Bailey & Brooke-Wavell, 2010; Bassey et al., 1998; Hartley et al., 2020), one in Australia (Bolam et al., 2015), four in Finland (Heinonen et al., 1996; Rantalainen et al., 2011; Vainionpää et al., 2005, 2009), three in Japan (Kato et al., 2006; Shibata et al., 2003; Sugiyama et al., 2002), two in the United States of America (Hinton et al., 2015; Tucker et al., 2015), and one in Istanbul (Sen et al., 2020). Types of jumping interventions All the studies compared the effectiveness of a jump training intervention with a non-jumping control group. Three studies designed a unilateral jump intervention and their non-jumping control group corresponds to the non-jumping contralateral leg (Allison et al., 2013; Bailey & Brooke-Wavell, 2010; Hartley et al., 2020). Most of the included studies’ durations ranged from 6 to 12 months (Table 1). There was no significant difference in study duration between sub-groups stratified by age (p = 0.6554). The weekly frequency of jump training varied from twice per week to daily, with a median frequency of 4 jump training sessions per week and a median of 50 jumps per training session (Table 1). The median total number of jumps completed per week for studies reporting BMD was 200 jumps/week where nine intervention groups performed ≤ 200 jumps per week and nine intervention groups performed > 200 jumps per week. There was no significant difference between the studies strati- fied by age as younger (<50 years) and older (>50 years) adults for the number of jumps per session (p = 0.7702), total number of jumps per week (p = 0.9486), the jump frequency per week (p = 0.7887) or the osteogenic index per week (p = 0.8647) (Table 1). In addition, there was no significant difference in Figure 1. Flow diagram for the selection of studies. 2068 G. E. FLORENCE ET AL. the vertical ground reaction force (GRF) relative to body weight of the jump routines in the studies in younger (mean ± SD: 3.7 ± 0.6, measured in 7 of the 11 intervention groups) and older adults (4.0 ± 1.3, measured in 5 of the 7 intervention groups) (p = 0.5865). However, as expected the age of participants differed significantly between the younger (<50 years) and older (>50 years) adult studies (p < 0.0001) (Table 1). Risk of bias assessment Most studies were marked as having either low or unclear risk of bias for all categories (see Supplementary Material S5 for the risk of bias figure summary and justification for each study’s characterisation per category). Funnel plots Symmetrical funnel plots were obtained for femoral neck, tro- chanter and lumbar spine BMD. A small degree of asymmetry was observed for total hip BMD, likely owing to the few studies available for this BMD site (see Supplementary Material S6 to view the funnel plots). Meta-analysis of the effect of jumping on bone mineral density Twelve included studies presented BMD data from a total of 418 premenopausal women, 172 postmenopausal women, and 76 older men across 18 jump training groups. Femoral neck Changes in femoral neck BMD were reported in 11 studies and included 16 jumping intervention groups from a total of 601 participants. There was a significant overall percentage gain in BMD at the femoral neck from pre- to post-jump training relative to non-jumping controls of moderate effect size (Figure 2), however, with significant heterogeneity (I2 = 70%, p < 0.0001). Sub-analysis by age revealed a gain in femoral neck BMD relative to non-jumping controls of moderate effect size in younger premenopausal women (<50 years) and small effect size in older adults (>50 years), where significance was retained for both sub-groups, and with no significant difference between sub-groups (Figure 2). Total hip Changes in total hip BMD were reported in 4 studies and included a total of 7 jumping intervention groups from 209 participants. Overall jump training resulted in a small effect improvement in total hip BMD from pre- to post-intervention relative to non-jumping controls that was not significant (Figure 3), with low heterogeneity. However, sub-analysis by age revealed a significant moderate gain in total hip BMD relative to non-jumping controls only in younger adults and no significant effect in older adults (Figure 3). This difference between sub-groups was significant (Figure 3). Trochanter Seven studies reported changes in trochanter BMD and included a total of 11 jumping intervention groups from 441 participants. Overall, there was a trivial effect of the jumping interventions on Figure 2. Forest plots presented as percentage mean difference (%) for changes in bone mineral density at the femoral neck with jump training for younger (<50 years) and older (>50 years) adults, relative to non-jumping controls. The diamond denotes the sub-group and overall treatment outcomes with 95% confidence intervals (95%CI) and ES denotes effect size. JOURNAL OF SPORTS SCIENCES 2069 the trochanter BMD from pre- to post-intervention relative to non-jumping controls (Figure 4), with low heterogeneity. However, sub-analysis by age revealed a significant small gain in trochanter BMD relative to non-jumping controls only in younger, but not in older adults (Figure 4). The difference between sub-groups was significant (Figure 4). Lumbar spine Seven studies that included a total of 10 jumping intervention groups reported change in the L2-L4 lumbar spine from a total of 406 participants. Overall jump training had a trivial, non-significant effect on lumbar spine BMD from pre to post intervention relative to non-jumping controls, (Figure 5), with low heterogeneity. Sub- analysis by age revealed a small effect on L2-L4 lumbar spine BMD relative to non-jumping controls in younger adults that was not significant, and no effect in older adults, with no significant differ- ence between sub-groups (Figure 5). Sensitivity analysis at the femoral neck The significant heterogeneity in the effect outcome at the femoral neck could not be explained by sub-analyses for age, and therefore sensitivity testing was performed to identify Figure 3. Forest plots presented as percentage mean difference (%) for changes in bone mineral density at the total hip with jump training for younger (<50 years) and older (>50 years) adults, relative to non-jumping controls. The diamond denotes the sub-group and overall treatment outcomes with 95% confidence intervals (95%CI) and ES denotes effect size. Figure 4. Forest plots presented as percentage mean difference (%) for changes in bone mineral density at the trochanter with jump training for younger (<50 years) and older (>50 years) adults, relative to non-jumping controls. The diamond denotes the sub-group and overall treatment outcomes with 95% confidence intervals (95%CI) and ES denotes effect size. 2070 G. E. FLORENCE ET AL. whether one or more study group was responsible for the notable heterogeneity. Markedly, two premenopausal study groups from two separate studies presenting large effect responses (Kato et al., 2006; Sugiyama et al., 2002) appeared to be mainly responsible for the significant heterogeneity at the femoral neck. When these two study groups were excluded, the level of heterogeneity was reduced and no longer significant (I2 = 39%, p = 0.07) with the outcome having a small significant effect (ES = 0.41 (95%CI: 0.21 to 0.62)); and %MD of 1.16% (95% CI: 0.65% to 1.67%) (p < 0.0001). When a third study with post- menopausal women presenting a negative trivial response was excluded (Bassey et al., 1998), the level of heterogeneity at the femoral neck was reduced further to zero (I2 = 0%, p = 0.60) and the outcome remains as a small effect (ES = 0.50 (95%CI: 0.34 to 0.67)) with %MD of 1.34% (95%CI: 0.92% to 1.76%) (p < 0.0001). Dose-response analysis Eleven studies with a total of 16 jumping intervention groups and 601 participants were included in a dose-response linear regression analysis for BMD changes relative to non-jumping controls at the femoral neck with the number of weekly jumps or weekly OI. The linear regression plots showed no significant correlation between the percentage mean difference (%MD) at the femoral neck and total number of jumps per week (r = −0.1741, p = 0.5349) (Figure 6(a)), or OI per week (r = −0.2822, p = 0.2895) (Figure 6(b)) for the jumping loads used in the included studies. Meta-analyses of the effect of jumping on bone turnover markers Changes in circulating bone formation marker concentrations from pre- to post-intervention were reported in 5 studies with a total of 126 jumpers and 98 non-jumping controls. Three studies measured changes in osteocalcin (OC) (ng/ml) (Bassey et al., 1998; Hinton et al., 2015; Sen et al., 2020), one study measured C-terminal propeptide of type I procollagen (PICP) (ng/ml) (Rantalainen et al., 2011), and one study measured N-terminal propeptide of type I procollagen (P1NP) (ng/ml) (Vainionpää et al., 2009). There was a trivial effect in both the jumpers (ES (95%CI): 0.12 (−0.13 to 0.37), Z = 0.93, p = 0.35) and non-jumping controls (ES (95%CI): 0.14 (−0.15 to 0.42), Z = 0.94, p = 0.35) for the change in bone formation marker concentra- tions, with low heterogeneity for the jumpers (I2 = 0%, p = 0.42) and non-jumping controls (I2 = 0%, p = 0.54). Six studies reported changes in circulating bone resorption marker concentrations from a total of 136 jumpers and 108 non-jumping controls. Measured bone resorption markers included C-terminal telopeptide of type I collagen (CTx) (ng/ml) in three studies (Hinton et al., 2015; Rantalainen et al., 2011; Sen et al., 2020), N-terminal telopeptides of type I collagen (NTx) in one study (nmol BCEs/mmol Cr) (Bassey et al., 1998), deoxypyridinoline (DPD) (nmol/mmol Cr) in one study (Kato et al., 2006), and tartrate resistant acid phosphatase (TRAP5b) (U/L) in one study (Vainionpää et al., 2009). There was a trivial effect in both the jumpers (ES (95%CI): 0.02 (−0.22 to 0.25), Z = 0.13, p = 0.90) and non-jumping controls (ES (95%CI): 0.06 (−0.21 to 0.33), Z = 0.44, p = 0.66) for the change in bone resorption marker concentrations, with low heterogeneity for the jumpers (I2 = 0%, p = 0.45) and non-jumping controls (I2 = 0%, p = 0.89) (see Supplementary Material S7 for bone turnover marker forest plots). GRADE assessment All outcomes were downgraded for possible publication bias because published studies only exist for premenopausal and Figure 5. Forest plots presented as percentage mean difference (%) for changes in bone mineral density at the L2-L4 lumbar spine with jump training for younger (<50 years) and older (>50 years) adults, relative to non-jumping controls. The diamond denotes the sub-group and overall treatment outcomes with 95% confidence intervals (95%CI) and ES denotes effect size. JOURNAL OF SPORTS SCIENCES 2071 postmenopausal women and older men, with only one study in younger men. Femoral neck BMD was initially downgraded for inconsistency according to notable heterogeneity but follow- ing sensitivity testing that identified the two outlier studies that caused majority of the heterogeneity, the inconsistency was removed. Total hip BMD and bone turnover marker outcomes were downgraded for imprecision due to the small sample size of studies and wide confidence intervals. No upgrades were warranted. As a result, the certainty in the evidence is moderate for femoral neck, trochanter and lumbar spine BMD and low for total hip BMD and bone turnover markers (see Supplementary Material S8 for a Table showing the detailed GRADE assessment results). Discussion The primary purpose of this systematic review and meta- analysis was to quantify the effect of jump training on changes in BMD relative to non-jumping controls at the femoral neck, total hip, femoral trochanter, and lumbar spine. Additionally, bone turnover markers, as a secondary bone health outcome, were measured to evaluate for changes in bone formation and bone resorption activity. Most notably, the current meta- analysis found that jump training induces a positive effect on BMD at the femoral neck, both in younger premenopausal women (<50 years) and in older men and postmenopausal women (>50 years). Jump training is also effective at increasing BMD at total hip and trochanter, only in younger premenopau- sal women (<50 years), but not older men and postmenopausal women (>50 years). No dose-response relation is evident in the number of weekly jumps or weekly OI and the percentage gain in BMD at the femoral neck. In addition, there were only trivial effects of jump training on markers of bone formation and bone resorption activity. Effect of jumping on BMD Despite the moderate and small effect size outcomes for femoral neck BMD relative to non-jumping controls in younger and older adults, respectively, the mean percentage gain in BMD at the femoral neck from pre- to post-intervention was not significantly different between sub-groups. However, sensitivity analysis was used to identify the source of hetero- geneity in the BMD outcome at the femoral neck and supports a disparate effect of age on BMD responsiveness to jumping exercises. The significant heterogeneity in the BMD outcome at the femoral neck is mostly accounted for by 2 studies in pre- menopausal women that produced an exaggerated large effect (Kato et al., 2006; Sugiyama et al., 2002). Moreover, when accounting for a third study with postmenopausal women reporting a trivial negative effect at the femoral neck (Bassey et al., 1998), the heterogeneity was eliminated at the femoral neck. However, 8% of the postmenopausal women in the latter study were smokers (Bassey et al., 1998), and this may have further caused a notably smaller effect of jumping on femoral neck BMD in this study, contributing to heterogeneity in the overall effect. Interestingly, jump training was also effective in increasing BMD from pre- to post-intervention relative to non-jumping controls at all the other measured bone sites only in younger but not in older adults. These results suggest that jumping may have a larger effect in adults younger than 50 years and a lesser effect in individuals older than 50 years, despite a similar jump load, frequency and intensity (measured by vertical GRF). However, the rate of force produced was mostly not reported and whether jump rate differed between studies in younger and older adults cannot be known. Nevertheless, the apparent similar jump load and intensity between studies in younger and older adults suggests that the noted age-related differences in the BMD response to jump training is possibly due to age-related variations in mechanosensation. This may be owing to the age- associated decline in androgens (Chen et al., 2004; Žofková, 2008) and oestrogen (Geoghegan et al., 2019) that has been shown to reduce new bone formation (Demontiero et al., 2012; Ott, 2018), and the increase in sympathetic nervous system tone with ageing that promotes bone resorption dominance (Karsenty & Khosla, 2022). The high inflammatory status asso- ciated with ageing in both men and women and with oestrogen- deficiency in postmenopausal women negatively impact osteo- cyte mechanosensory perception and signalling in response to mechanical loading (Geoghegan et al., 2019; Metzger & Narayanan, 2019). Specifically, osteocyte integrin receptor integ- rity has been shown to be compromised in older individuals (Metzger & Narayanan, 2019) and in postmenopausal women Figure 6. Dose-response showing best-fit line and 95%CI for the correlation between percentage mean difference in bone mineral density at the femoral neck and total number of jumps completed per week (a) or osteogenic index per week (b), for the jumping loads applied. One study was excluded from the regression analysis for weekly jumps as an outlier with 800 jumps/week (Vainionpää et al., 2005). 2072 G. E. FLORENCE ET AL. (Geoghegan et al., 2019). These integrin receptors are essential in sensing fluid sheer stress in the lacuno-canalicular network that is induced by mechanical loading and that initiates osteocyte signalling in favour of bone formation (Galea et al., 2017); thus, further explaining why older adults may be less responsive to bone-loading exercise than younger adults. The bigger or more consistent significant effect of jump training on BMD at the femoral neck compared with a smaller significant effect in younger adults or lack of effect in older adults at the other bone sites, could possibly be explained by the loading of a jump action. Performing a normal jump sub- jects the femoral neck to both bending and compressive forces (Niu et al., 2010), of which both types of forces may attenuate by the time they have been transmitted to the hip and trochan- ter regions. Therefore, the jumping exercises may have gener- ated sufficient bone strains to be perceived by nearby osteocytes only at the femoral neck, particularly in older adults. Although the current meta-analysis shows a moderate sig- nificant effect only in younger and no significant change in older adults in BMD at the total hip, it has been speculated that changes in femoral neck may better predict hip fractures than total hip BMD alone. Specifically, a decrease in femoral neck BMD of 1 SD may increase the fracture risk at the hip by 2.6 times in postmenopausal women (Cummings et al., 1993). Therefore, the larger increase in femoral neck BMD compared with the small increases in total hip and trochanter BMD may still yield clinical importance in reducing the risk of hip frac- tures. Furthermore, during a normal jump, the bone strains generated at the hip and femoral neck are higher than that received at the lumbar spine and is likely owing to the attenua- tion of the mechanical stimuli by the time it is transmitted to the lumbar spine region (Coventry et al., 2006). Therefore, it is unsurprising that the lumbar spine BMD did not respond in the same manner as the BMD of the hip and femoral neck, produ- cing only a nonsignificant small effect in younger adults and no effect in older adults. These results suggest that the effect of jump training causes greater bone adaptations where the impact is highest and less noticeable effects at more distal bone regions (Vainionpää et al., 2005, 2007). In addition, the dose-response regression plots in the cur- rent meta-analysis revealed no significant correlations between BMD effect (relative to non-jumping controls) at the femoral neck and the number of weekly jumps applied in the included studies; with a median of 50 jumps per training session, per- formed with a median frequency of 4 times weekly. However, the effectiveness of jump training to improve bone health may depend on the provision of short breaks interspersed between jumping sets. Previous research has demonstrated that provid- ing rest periods between repeated sets of load-bearing exer- cises is vital for enhancing bone accretion (Robling et al., 2000; Rubin & Lanyon, 1984; Srinivasan et al., 2002) where such repeated on-off loading cycles maximise fluid flow near osteo- cytes (Donahue et al., 2001; Lanyon, 1987). Without rest peri- ods, the continued loading will cause osteocytes to habituate and stop responding to the mechanical stimuli (Robling et al., 2000; Turner, 1998). Accordingly, within a single jump session, 10–20 s of rest has been suggested between each set of 10 jumps to limit mechanosensory habituation (Boudenot et al., 2021; Srinivasan et al., 2002). Similarly, training frequency may be an important considera- tion for bone responsiveness, where splitting a fixed-weekly training volume over more days per week has been shown to be better than completing all in one or 2 days per week (Turner & Robling, 2003). Moreover, two shorter training sessions per day (given a minimum recovery of 6–8 h) have been shown to be more effective than a single longer daily session (Turner & Robling, 2003). Accordingly, Turner and Robling (2003) developed a composite OI that takes into consideration the number of jumps per session, the weekly jump-session frequency, and the recovery time between jump sessions. Their model suggests that 24 h is needed for complete restora- tion of osteocyte mechanosensation and if repeated exercise sessions are performed within a single day, then the subse- quent sessions will not afford full osteogenic loading benefits (Turner & Robling, 2003). Notably, when the jump routines of the studies included in the current meta-analysis were ranked according to the calculated OI per week, no dose-response was noted for magnitude of change in BMD at the femoral neck and OI scores varying between 22 and 83 per week (with a median OI of 52 per week), implying an equal gain across that range. Effect of jumping on bone turnover markers The overall effect of jumping on bone turnover markers appeared to be trivial and non-significant in this meta- analysis in both the jumpers and non-jumping controls. Bone turnover markers obtained from serum or urine samples are not site-specific but rather reflect whole body bone metabolism (Banfi et al., 2010; Lanyon, 1987) and, therefore, may not be sufficiently sensitive to identify changes in bone turnover that may occur only at one or selected skeletal sites. Therefore, the trivial effect of jumping exercise on bone turnover obtained in this meta-analysis indicates no notable change in whole body bone metabolism, despite the meaningful BMD changes that occurred possibly only at a selected skeletal site, for example, in this case, only at the femoral neck in older adults. The lack of effect in bone turnover markers may also be a consequence of only comparing pre- to post-intervention values following a long intervention period. The findings by Sen et al. (2020) and Rantalainen et al. (2011) add support for smaller changes being detected over a longer duration (6 months) compared with shorter durations of approximately 3 months. It may be that once the initial bone modelling is accomplished, the bone turnover response reverts to normal bone maintenance at this new established gain in bone mass without any further accrual to the now accustomed bone- loading routine. As a result, serum bone marker concentrations measured at this later post-intervention period again reflect pre-intervention levels. In addition, certain bone markers depict bone enzyme activ- ities that may represent delayed responses or may represent increased metabolic demands, such as OC (Kanazawa, 2015; Wei & Karsenty, 2015). For that reason, OC may not be a suitable bone formation marker on its own when assessing the effects of an exercise intervention on bone turnover. Rather, changes in circulating concentrations of P1NP and CTx are indicative of current bone turnover status because they are peptide fragments cleaved from bone procollagen precursor JOURNAL OF SPORTS SCIENCES 2073 or matrix collagen during formation or resorption activity, respectively (Banfi et al., 2010) and are the current recom- mended markers in bone health research (Hu et al., 2013; Jenkins et al., 2013). However, only one study reported changes in P1NP (Vainionpää et al., 2009) and only three reported changes in CTx (Hinton et al., 2015; Rantalainen et al., 2011; Sen et al., 2020). Further investigation is warranted to deter- mine the effect of jumping on changes in P1NP and CTx con- centrations following the early weeks of the training program. Limitations It should be noted that BMD is only one representative measure of bone strength and does not identify microstructure, geo- metric factors, or torsional strength indices (Fonseca et al., 2014; Manske et al., 2010). The sparsity of jump training studies in male participants is noted and of these, most included elderly men (50–80 years) with only one study in younger men (Hinton et al., 2015). Future studies should investigate for a sex effect of jump training on BMD and bone turnover markers. Notably, three studies included some participants who were smokers (Bassey et al., 1998; Vainionpää et al., 2005, 2009), and it is well-accepted that smoking can negatively impact bone health (Al-Bashaireh et al., 2018). Future research should investigate for differences between smokers and non-smokers in bone indices’ responses to jump training. Conclusions Bone mineral density responses to jump training appear to be site- specific, with the highest sensitivity at the femoral neck. The overall finding of 1.50% improvement in femoral neck BMD after a median of 6 months of jump training relative to non-jumping controls in the current meta-analysis is graded as moderate certainty and may be clinically relevant in reducing the risk and severity of hip frac- tures. Notably, lack of a dose-response relation within the range of weekly jumps tested implies moderate certainty of achieving a small-moderate effect size gain in femoral neck BMD when performing the median jump-load of 50 jumps four times weekly. Furthermore, jump training has a small-moderate positive signifi- cant effect on BMD relative to non-jumping controls at total hip, trochanter and a small nonsignificant effect at the lumbar spine only in young premenopausal women but not in older men and postmenopausal women with these findings graded as low, mod- erate and moderate certainty, respectively. Thus, sedentary indivi- duals should begin jump training at an early age to avoid progressive bone loss at these axial skeletal sites. Disclosure statement No potential conflict of interest was reported by the author(s). Funding The author(s) reported there is no funding associated with the work featured in this article. ORCID Gabriella E Florence http://orcid.org/0000-0002-6203-405X Tanja Oosthuyse http://orcid.org/0000-0002-4065-4506 Andrew N Bosch http://orcid.org/0000-0002-9543-9408 References Abrahamsen, B., van Staa, T., Ariely, R., Olson, M., & Cooper, C. (2009). Excess mortality following hip fracture: A systematic epidemiological review. Osteoporosis International, 20(10), 1633–1650. https://doi.org/10.1007/ s00198-009-0920-3 Al-Bashaireh, A. M., Haddad, L. G., Weaver, M., Chengguo, X., Kelly, D. L., & Yoon, S. (2018). The effect of tobacco smoking on bone mass: An over- view of pathophysiologic mechanisms. 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