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Sport Specificity And Training Influence Bone And Body Composition In Women Collegiate Athletes: 2264
Abstract
Sport Specificity and Training Influence Bone and Body Composition In Women Collegiate Athletes Jennifer M. Markos†, Aaron F. Carbuhn†, Tara E. Fernandez‡, Amy F. Bragg‡, John S. Green‡, FACSM, and Stephen F. Crouse‡, FACSM. Department of Health and Kinesiology and Department of Athletics, Texas A&M University, College Station, TX 77843, (Sponsor: S.F. Crouse)This is a novel descriptive study to characterize off-season, pre-season, and post-season bone and body composition measures in women collegiate athletes.PURPOSE: To quantify changes in women collegiate athletes’ bone mineral content, bone mineral density (BMD), arm BMD, leg BMD, pelvis BMD, spine BMD, and body composition (i.e., total body mass, lean mass, fat mass, and percent body fat) within each sport through the seasonal periods, and among the sports at each seasonal period. METHODS: 67 women collegiate athletes from softball (n = 17), basketball (n = 10), volleyball (n = 7), swimming (n = 16), and track jumpers and sprinters (n = 17) were scanned using duel energy x-ray absorptiometry (DXA) at three seasonal periods: 1) before pre-season training defined as off-season (OFF), 2) at end of preseason training (PRE), and 3) after the competitive season (POST). Summary of RESULTS: Repeated measures ANOVA within-sport seasonal changes in table; PRE/POST = highest value measured at PRE or POST. α < 0.05 for all tests of significance. Seasonal Period %Body fat BMD (g/cm2) Pelvis BMD (g/cm2) Spine BMD (g/cm2) Softball OFF 27.1±5.0* 1.254±0.081* 1.385±0.127 1.216±0.149 PRE/POST 25.7±5.0 1.261±0.082 1.405±0.141 1.268±0.154 Basketball OFF 25.5±5.5* 1.333±0.064* 1.469±0.123* 1.356±0.178 PRE/POST 22.7±5.6 1.349±0.055 1.494±0.119 1.391±0.146 Volleyball OFF 27.7±4.1 1.284±0.065* 1.366±0.139 1.254±0.102* PRE/POST 27.1±5.1 1.310±0.071 1.371±0.149 1.360±0.121 Swimming OFF 22.0±4.3 1.112±0.067 1.110±0.104* 1.063±0.127* PRE/POST 21.9±4.1 1.121±0.067 1.124±0.105 1.105±0.126 Track Jumpers and Sprinters OFF 15.4±4.6* 1.292±0.075* 1.432±0.124* 1.280±0.135* PRE/POST 14.3±3.9 1.307±0.080 1.470±0.128 1.337±0.140 Values are means ± standard deviations. *Significant difference between off-season and pre or post-season ANOVA for differences by sports at the PRE/POST period showed results for both pelvis BMD and spine BMD as follows: softball = basketball = volleyball = track > swimmers.CONCLUSION: These data serve as sport-specific benchmarks for comparisons at in-season and off-season training periods among women collegiate athletes in various sports. They also serve to document changes in body composition and bone density with training, and may serve to guide coaches in the development of sport specific nutritional and strength and conditioning programs to optimize athletic performance.Research supported in part by the Sydney & J.L. Huffines Institute for Sports Medicine and Human Performance
... With the rigorous strength and conditioning programs that most female collegiate athletes engage in, what body composition changes can they expect throughout their collegiate career? Numerous investigators have reported the body composition of intercollegiate female athletes within various sports (1,4,6,7,9,10,121314151617182021222326,27,29,31,33,35,37,38). Several have examined off/preseason to peak season changes in female collegiate basketball (BB) (6,14,33,35), soccer (SOC) (7,23), swimming (SW) (6,14,15,18,22,27,29,31,38), track and field (TR) (6,14,21), and volleyball (VB) (6,14) athletes. ...
... Numerous investigators have reported the body composition of intercollegiate female athletes within various sports (1,4,6,7,9,10,121314151617182021222326,27,29,31,33,35,37,38). Several have examined off/preseason to peak season changes in female collegiate basketball (BB) (6,14,33,35), soccer (SOC) (7,23), swimming (SW) (6,14,15,18,22,27,29,31,38), track and field (TR) (6,14,21), and volleyball (VB) (6,14) athletes. However, multiyear body composition data on female collegiate athletes are sparse (30). ...
... Numerous investigators have reported the body composition of intercollegiate female athletes within various sports (1,4,6,7,9,10,121314151617182021222326,27,29,31,33,35,37,38). Several have examined off/preseason to peak season changes in female collegiate basketball (BB) (6,14,33,35), soccer (SOC) (7,23), swimming (SW) (6,14,15,18,22,27,29,31,38), track and field (TR) (6,14,21), and volleyball (VB) (6,14) athletes. However, multiyear body composition data on female collegiate athletes are sparse (30). ...
Body composition can affect athletic performance. Numerous studies have documented changes in body composition in female collegiate athletes from pre- to post-season; however, longitudinal studies examining changes across years are scarce. Therefore, the primary purpose of this study was to assess longitudinal body composition changes among female collegiate athletes across three years. Two hundred and twelve female athletes from basketball (BB; n=38), soccer (SOC; n=47), swimming (SW; n=52), track (sprinters and jumpers; TR; n=49), and volleyball (VB; n=26) with an initial mean age of 19.2±1.2 yrs, height of 172.4±8.9 cm, and total mass of 66.9±9.0 kg had body composition assessments using DXA pre- and post-season over three years. A restricted maximum-likelihood linear mixed model regression analysis examined body composition differences by sport, and year. Changes (p <0.05) over three years included the following: Lean mass increased in VB from year 1 to 2 (0.7 kg), year 2 to 3 (1.1 kg) and year 1 to 3 (1.8 kg) and in SW from year 1 to 3 (0.6 kg); and %BF increased in BB from year 1 to 3 (1.7%). There were no changes in SOC or TR. These results indicate that during their college careers, female collegiate athletes can be expected to maintain their %BF and athletes in sports like SW and VB can anticipate an increase in lean mass, but the increases may be less than many athletes, coaches and trainers envision.
... We compared the expected difference due to growth in males and females with the observed change in LST over the season and the results pointed out that the observed increase was greater than the expected difference due to growth (males: 2.5 kg vs. 0.9 kg, p = 0.015; females: 1.5 kg vs. 0.07 kg, p = 0.009) which reinforces an effect of the training process in LST over the season. In addition to the findings previously mentioned in non-athletic pediatric subjects, it is important to address that our results extend the findings of other studies that followed young basketball players over a season, specifically the similar increases occurred in FFM (Siders et al. 1991) and LST (Carbuhn et al. 2010). In view of the aforementioned studies (Carbuhn et al. 2010; Kim et al. 2006; Molgaard and Michaelsen 1998; Siders et al. 1991) it is likely that the effect of the training process greatly contributed to the observed increases in LST even though a potential effect of growth may have occurred, specifically in our male players . ...
... In addition to the findings previously mentioned in non-athletic pediatric subjects, it is important to address that our results extend the findings of other studies that followed young basketball players over a season, specifically the similar increases occurred in FFM (Siders et al. 1991) and LST (Carbuhn et al. 2010). In view of the aforementioned studies (Carbuhn et al. 2010; Kim et al. 2006; Molgaard and Michaelsen 1998; Siders et al. 1991) it is likely that the effect of the training process greatly contributed to the observed increases in LST even though a potential effect of growth may have occurred, specifically in our male players . Nonetheless we address the absence of a control group as a limitation of this study. ...
We aimed to analyze the association between changes in total and regional fat (FM) and fat-free mass (FFM) over a season with resting (REE) and total energy expenditure (TEE) in elite basketball players. At the beginning of the pre-season and at the final of the competitive period, measures of total and regional FM, FFM, lean soft tissue (LST), and bone mineral estimated by DXA and REE by indirect calorimetry were obtained in eight males and nine females of the Portuguese basketball team (16-17 years). TEE was assessed by doubly labeled water. Handgrip and a vertical-jumping were used to assess strength and power. Changes were expressed as a percentage from the baseline values. Resting energy expenditure and TEE increased by 13.2 ± 12.6 and 13.3 ± 12.7% (p < 0.01), respectively. Increases in FFM (3.6 ± 2.2%) and reductions in relative FM (-4.0 ± 6.6%) were observed (p < 0.01). The strength and power increased by 14.4 ± 9.9 and 9.8 ± 10.6%, respectively (p < 0.001). Alone, FFM and arms LST differences explained 25 and 23% of the total variance in REE alteration. These variables remained associated after adjusting for gender and baseline values (β = 0.536, p = 0.042; and β = 2.023, p = 0.016, respectively). Over the season, the REE increase was explained by changes in FFM. The increase in REE along with the strength and power improvement may suggest that a qualitative change in the metabolic active tissues occurred. Furthermore, these findings highlight the regional LST contribution, specifically located at the upper limbs, as a key component for the higher REE occurred over the season in junior basketball players.
Swimming, a sport practiced in hypogravity, has sometimes been associated with decreased bone mass.
This systematic review aims to summarize and update present knowledge about the effects of swimming on bone mass, structure and metabolism in order to ascertain the effects of this sport on bone tissue.
A literature search was conducted up to April 2013. A total of 64 studies focusing on swimmers bone mass, structure and metabolism met the inclusion criteria and were included in the review.
It has been generally observed that swimmers present lower bone mineral density than athletes who practise high impact sports and similar values when compared to sedentary controls. However, swimmers have a higher bone turnover than controls resulting in a different structure which in turn results in higher resistance to fracture indexes. Nevertheless, swimming may become highly beneficial regarding bone mass in later stages of life.
Swimming does not seem to negatively affect bone mass, although it may not be one of the best sports to be practised in order to increase this parameter, due to the hypogravity and lack of impact characteristic of this sport. Most of the studies included in this review showed similar bone mineral density values in swimmers and sedentary controls. However, swimmers present a higher bone turnover than sedentary controls that may result in a stronger structure and consequently in a stronger bone.
Elite adolescent figure skaters must accommodate both the physical demands of competitive training and the accelerated rate of bone growth that is associated with adolescence, in this sport that emphasizes leanness. Although, these athletes apparently have sufficient osteogenic stimuli to mitigate the effects of possible low energy availability on bone health, the extent or magnitude of bone accrual also varies with training effects, which differ among skater disciplines.
We studied differences in total and regional bone mineral density in 36 nationally ranked skaters among 3 skater disciplines: single, pairs, and dancers.
Bone mineral density (BMD) of the total body and its regions was measured by dual energy x-ray absorptiometry (DXA). Values for total body, spine, pelvis and leg were entered into a statistical mixed regression model to identify the effect of skater discipline on bone mineralization while controlling for energy, vitamin D, and calcium intake.
The skaters had a mean body mass index of 19.8 ± 2.1 and % fat mass of 19.2 ± 5.8. After controlling for dietary intakes of energy, calcium, and vitamin D, there was a significant relationship between skater discipline and BMD (p = 0.002), with single skaters having greater BMD in the total body, legs, and pelvis than ice dancers (p < 0.001). Pair skaters had greater pelvic BMD than ice dancers (p = 0.001).
Single and pair skaters have greater BMD than ice dancers. The osteogenic effect of physical training is most apparent in single skaters, particularly in the bone loading sites of the leg and pelvis.
Body composition is well known to be associated with endurance performance among adult skiers; however, the association among adolescent crosscountry and alpine skiers is inadequately explored. The study sample comprised 145 male and female adolescent subjects (aged 15-17 years), including 48 crosscountry skiers, 33 alpine skiers, and 68 control subjects. Body composition (%body fat [BF], %lean mass [LM], bone mineral density [grams per centimeter squared]) was measured with a dual-emission x-ray absorptiometer, and pulse and oxygen uptake was measured at 3 break points during incremental performance tests to determine physical fitness levels. Female crosscountry and alpine skiers were found to have significantly higher %LM (mean difference = 7.7%, p < 0.001) and lower %BF (mean difference = 8.1%, p < 0.001) than did female control subjects. Male crosscountry skiers were found to have lower %BF (mean difference = 3.2%, p < 0.05) and higher %LM (mean difference = 3.3%, p < 0.01) than did male alpine skiers and higher %LM (mean difference = 3.7%, p < 0.05) and %BF (mean difference = 3.2%, p < 0.05) than did controls. This study found strong associations between %LM and the onset of blood lactate accumulation and VO2max weight adjusted thresholds among both genders of the crosscountry skiing cohort (r = 0.47-0.67, p < 0.05) and the female alpine-skiing cohort (r = 0.77-0.79, p < 0.001 for all). This study suggests that body composition is associated with physical performance amongst adolescents.
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