Association between prolactin and history of stress fracture in elite sprinters and jumpers

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However, since there is not enough evidence to support the risk factors for stress fractures is not sufficient. The aim of this study is to investigate the risk factor for stress fractures and the characteristics of the laboratory data of them in eumenorrheic female track and field athletes competing at an elite level Methods Eumenorrheic sprinters and jumpers competing at a national level were recruited. Bone mineral density, bone metabolism markers, 25-OH Vitamin D, and hormones including prolactin and free testosterone were measured. Results A total of 84 high school and collegiate athletes were enrolled in the study, and among them, 33 athletes had a history of stress fracture after high school. Their personal background, bone mineral density, bone metabolism markers, 25-OH Vitamin D, and free testosterone were not different between the group with a history of stress fracture and without a history of stress fracture. Prolactin was higher in those with stress fractures compared to those without stress fractures, and it was statistically different between the two groups (15.70 ± 10.59 ng/mL and 11.59 ± 5.06 ng/mL, respectively, p = 0.019). Logistic regression analysis revealed that it was also a significant predictive factor for stress fractures (odds ratio: 1.10; 95% CI: 1.01–1.20; P = 0.023). Conclusion Prolactin may be linked to stress fractures in eumenorrheic sprinters and jumpers. prolactin stress fracture vitamin D track and field Introduction Stress fractures, which occur due to repetitive micro damage is devastating for athletes especially competing at a high level because although it differs by the severity, it generally requires a few months for return to play (Jamieson et al., 2017 ; Miller et al., 2018 ). Since the female athlete triad (the triad) was first described by the American College of Sports Medicine, many studies have focused on the epidemiology and treatment of stress fractures in athletes (Lodge et al., 2021 ; Skorseth et al., 2020 ). The triad, consisted by relative energy deficiency, osteoporosis, and amenorrhea has brought a lot of attention to athletes and coaches and more people are starting to understand the relationship between energy deficiency leading to amenorrhea which could cause low bone density and consequently causing stress fractures (M. J. De Souza et al., 2014 ; Thein-Nissenbaum & Carr, 2011 ) (Carter, 2018 ; Høeg et al., 2022 ; Skorseth et al., 2020 ). For example, as of track and field, there are many studies on the low BMD in long distance runners, and the link between with other symptoms related to the triad and relative energy deficiency in sport (RED-S) athletes since long distance runners are prone to the triad compared to other track and field events such as sprinting and jumping which are less prone to have those symptoms (Michelle T. Barrack et al., 2014 ; Edouard & Alonso, 2013 ; Høeg et al., 2022 ; J. Iwamoto et al., 2011 ; Kelsey et al., 2007 ; Okamoto et al., 2010 ; Pierpoint et al., 2016 ). However, although many studies have focused on predicting low energy availability and amenorrhea by medical history and laboratory data, studies focusing on just sprinters and jumpers with a history of stress fractures without amenorrhea does not exist to the best of our knowledge in Japan. However, according to the Medical Committee of the Japan Association of Athletics Federation, prevalence of stress fractures in female national level high school and collegiate sprinters were 17.6% and 15.9% respectively. These were not that different from middle and long distance runners which were 17.7% in high school athletes and 19.0% in collegiate athletes (Federations, 2018 ; 2020 ). Although the relationship between stress fractures and bone metabolism markers are still controversial (K. Bennell et al., 1998 ; Yanovich et al., 2013 ), bone turnover markers have been reported to have a relationship between stress fractures (Fujita et al., 2017 ; Nose-Ogura et al., 2020 ; Wakamatsu et al., 2012 ). Furthermore, hormones such as lutenizing hormone and estradiol has been reported to have a link between the symptoms related to the triad and RED-S (M. T. Barrack et al., 2010 ; Feingold & Hame, 2006 ; Loucks & Thuma, 2003 ). However, it fluctuates during the menstrual cycle and may not be considered as a predictor for consequences from the triad and reds including stress fractures for eumenorrheic athletes. Prolactin is a polypeptide hormone that increases during pregnancy and postpartum and has been reported to contribute to osteopenia by affecting bone turnover with increased bone resorption and suppressed bone formation (di Filippo et al., 2020 ; Wu et al., 2021 ). In fact, several case reports regarding stress fractures occurred during postpartum does exist and it has been reported that prolactin enhances bone turnover by enhancing osteoblast (Lin & Lane, 2003 ; Seriwatanachai et al., 2008 ; Thienpont et al., 1999 ). There have been studies investigating the relationship between prolactin and exercise (MARY JANE De Souza et al., 1991 ; Kochańska-Dziurowicz et al., 2001 ; Mougin et al., 1988 ; Schulte et al., 2013 ). It also increases with stress and Lennartsson et al. has reported the increase of prolactin by psychosocial stress (Lennartsson & Jonsdottir, 2011 ). However, relationship between stress fractures and prolactin has not been fully understood especially on athletes that are not prone to have the triad and RED-S such as sprinters. Since if there is a way to predict the occurrence of stress fractures, that would help many athletes. Thus, the purpose of this study is to investigate the risk factor for stress fractures and the characteristics of the laboratory data of them in eumenorrheic female track and field athletes competing at an elite level. Materials and Methods Subjects Collegiate and high school track and field athletes competing at a national level were recruited. The athletes were mostly recruited from the Kanto, Kansai, and Tokai regions of Japan and were examined at a designated hospital and universities. Since the body composition and the prevalence of amenorrhea is different per discipline, we recruited athletes specializing in the following events; 100meters (m), 200m, 400m, 100mH (meter hurdles), 400mH, long jump, triple jump, heptathlon, 4x100mR (meter relay) and 4X400mR. Since hormones could get affected by some medications including oral contraceptive pills, for those taking medications that could affect the hormonal levels were excluded (Garnero et al., 1995 ; Trémollieres, 2013 ). Also, for those who are experiencing amenorrhea and oligomenorrhea were also excluded since they have different bone metabolism and low bone mineral density compared to eumenorrheic athletes (Yuka Tsukahara et al., 2021 ). The measurement was performed during off-season and the recruitment took place between April 2021 to February 2022. Written informed consent was obtained from both the subjects and their legal guardians after being informed of the benefits and risks of the investigation. The study protocol was approved by the Ethics Review Procedures Concerning Research with Human Subjects Group of the authors’ affiliated institutions (approval number 2020 − 416). Laboratory data Participants were instructed to refrain from training and consume no food for at least 2 hours prior to blood collection which was performed between the timeframe of 11AM to 2PM. In order to assess bone metabolism, the following bone turnover markers were measured. 1) bone resorption markers tartrate-resistant acid phosphatase type 5b (TRACP-5b) and N-terminal telopeptide total (NTx) 2) bone formation markers pro-collagen type 1 amino-terminal propeptide (T-P1NP), bone-specific alkaline phosphatase (BAP), undercarboxylated osteocalcin (OC), and intact parathyroid hormone (iPTH) 3) bone matrix related markers osteocalcin undercarboxylated osteocalcin (ucOC), intact parathyroid hormone (iPTH) In addition to the above, 25-OH vitamin D (25OHVD) were also measured since although the relationship between vitamin D and stress fractures in athletes are scarce (Myburgh et al., 1990 ), some studies have reported the link between vitamin D and BMD in non-athletes (Dawson-Hughes et al., 1997 ; Mezquita-Raya et al., 2001 ; Palacios, 2006 ; Tenforde et al., 2010 ). In addition, although it was a study on male athletes, free testosterone was also reported to be low in male endurance athletes and thus we also decided to measure free testosterone to seek the relationship between stress fractures along with prolactin (Boden et al., 2001 ). Height weight and Bone mineral density Height was measured with the athlete standing erect without shoes to the nearest 0.1 cm using a stadiometer. Bone mineral density was assessed by whole body modedual-energy X-ray absorptiometry using a Delphi Bone Densitometer (Hologic, Inc., Bedford, MA, USA). After calibration, as for the whole body mode, the subjects, wearing a t-shirt without objects that could interfere with the test, were instructed to lay on a table with the shoulders slightly abducted and elbows slightly flexed, so that the forearms were parallel to the body axis, while extending, but not spreading, the fingers with the palms facing downward. The feet were bound to a polystyrene block in the shape of an isosceles triangle with the vertex angle of 30º, so that the fibulae were not hidden by the tibiae. The same technician performed all scans at each site. Training schedules and injuries A questionnaire was distributed to the athletes via online inquiring about the amount of training hours per day on both weekdays and weekends, resting days per week, weight training days per week, any past medical history of bone injuries. We also interviewed all athletes regarding their injuries and those who answered that they had been diagnosed to have stress fracture after high school and included those who were properly diagnosed by a physician following an imaging study were marked as stress fracture (+) and those without a history of stress fracture were marked as stress fracture (-). Statistical Analysis All data were analyzed using the Stata 16.1 (Stata Corporation, TX, USA). The results are presented as the mean ± standard deviation. The Shapiro–Wilk test was applied to assess the distribution of the data. Continuous data were compared using the independent t-test. A probability (p) value of < 0.05 was considered statistically significant. Logistic regression analysis was performed to identify independent variables and having a stress fracture after high school was used as a dependent variable. Results Characteristics of the subjects Total of 84 female track and field athletes were enrolled. Among them one was not able to obtain all bone metabolism markers since it was hard to draw the blood needed for analysis and ucOC and TRACP were not measured. Total of 33 athletes (39.3%) had a history of stress fractures in their lower extremity after high school. Both stress fracture (+) and stress fracture (-) groups had a similar height and body weight and they were not statistically significantly different between the two groups Age at menarche and the age they started track and field were also similar, and they both were around the age of late elementary school to junior high school. Training schedules of the athletes including training hours per day and rest days per week and scores of the IAAF scoring table was not different between the two meaning that they were competing at the same level. Characteristics of the subjects are listed in Table 1 . Table 1 Characteristics of athletes with and without a history of stress fractures Stress fracture (+) (N = 33) Stress fracture (-) (N = 51) p value Age (years) 20.9 ± 2.3 20.4 ± 1.8 0.260 Height (cm) 161.9 ± 4.9 161.7 ± 4.7 0.846 Body weight (kg) 55.3 ± 5.0 53.9 ± 4.2 0.210 Age at menarche (years) 12.2 ± 2.6 12.4 ± 2.3 0.738 Age they started track and field (years) 11.2 ± 2.4 11.2 ± 2.0 0.991 Training hours per day (hours/day) 2.8 ± 0.6 2.7 ± 0.6 0.459 Rest days per week (days/week) 1.6 ± 0.6 1.6 ± 0.6 0.759 IAAF Scoring Table (points) 993.6 ± 65.8 980.5 ± 82.4 0.445 IAAF; International Association of Athletics Federations Bone mineral density There was no statistically significant difference between the two groups. Both their Z and T score were above average meaning that they were higher than zero in both groups. Laboratory data Mean values were mostly in the reference range except for ucOC and T-P1NP in both groups. Among those without a history of stress fractures, one participant was not able to measure TARCP and ucOC because of the lack of sample. Bone resorption markers TRACP and BAP were not statistically significantly different between the two groups. All bone formation markers T-P1NP, BAP, and OC were also not statistically significantly different between the two groups. Furthermore, iPTH and ucOC were not statistically significantly different between the two groups. Reference range of the bone metabolism markers are also listed in Table 2 and they are according to the “Guidelines for the Use of Biochemical Markers of Bone Turnover in Osteoporosis of the Japan Osteoporosis Society” and the reference value suggested by the laboratory company (Nishizawa et al., 2019 ). Prolactin was higher in stress fracture (+) compared to stress fracture (-) (p = 0.019). Table 2 Results of BMD and laboratory data Stress fracture (+) (N = 33) Stress fracture (-) (N = 51) p-value Reference Value W- BMD (g/cm 2 ) 1.192 ± 0.093 1.190 ± 0.073 0.916 Z score 111.70 ± 8.71 111.59 ± 6.82 0.949 T score 108.39 ± 8.40 108.25 ± 6.58 0.933 TRACP (mU/dL)* 292.39 ± 120.25 278.72 ± 91.44 0.559 120–420 NTx (nmolBCE/L) 20.25 ± 10.09 18.85 ± 6.99 0.454 7.5–16.5 T-P1NP (ng/mL) 81.84 ± 28.95 77.15 ± 26.26 0.445 16.8–70.1 BAP (µg/L) 15.80 ± 6.66 14.07 ± 3.73 0.132 2.9–14.5 OC (mIU/mL) 19.81 ± 7.59 17.53 ± 4.91 0.097 7.8–30.8 iPTH (pg/mL) 35.70 ± 12.98 36.55 ± 13.48 0.775 10–65 ucOC (ng/mL)* 5.36 ± 3.20 4.68 ± 2.32 0.269 30 Prolactin (ng/mL) 15.70 ± 10.59 11.59 ± 5.06 0.019 4.91–29.32 Free testosterone(pg/mL) 1.152 ± 0.986 0.841 ± 0.517 0.063 0.4–2.3 W-BMD; bone mineral density of the whole body, T-P1NP; total pro-collagen type 1 amino-terminal propeptide, ucOC; undercarboxylated osteocalcin, OC; osteocalcin, TRACP; tartrate-resistant acid phosphatase-5b, BAP; bone-specific alkaline phosphatase, iPTH; intact parathyroid hormone, NTx; N-terminal telopeptide, 25OHVD; 25-OH Vitamin D. Logistic regression analysis None of the personal background of the athlete were related to have a stress fracture and neither were the training schedules. IAAF scoring table points, Z-score of their BMD, bone metabolism markers and 25OHVD were not related factors to have stress fractures. Prolactin had positive relationship to have stress fractures (OR 1.104, p = 0.023). Results of the logistic regression analysis are listed in Table 3 . Table 3 Results of logistic regression analysis to investigate the factors related to have stress fractures Odds Ratio 95% CI p value Age (years) 0.774 [0.561, 1.068] 0.119 BMI (kg/m 2 ) 0.755 [0.508, 1.122] 0.164 Age at menarche (years) 0.956 [0.755, 1.210] 0.708 Age they started track and field (years) 1.033 [0.780, 1.368] 0.819 Training hours per day (hours/day) 1.113 [0.421, 2.940] 0.830 Rest days per week (days/week) 0.566 [0.182, 1.755] 0.324 IAAF Scoring Table (points) 1.002 [0.994, 1.010] 0.645 Z-score 1.048 [0.963, 1.140] 0.276 TRACP (mU/dL) 0.996 [0.988, 1.004] 0.320 NTx (nmolBCE/L) 0.989 [0.923, 1.059] 0.750 T-P1NP (ng/mL) 0.968 [0.931, 1.006] 0.093 BAP (µg/L) 1.084 [0.899, 1.306] 0.399 OC (mIU/mL) 1.228 [0.978, 1.543] 0.077 iPTH (pg/mL) 0.983 [0.936, 1.033] 0.506 ucOC (ng/mL) 1.001 [0.649, 1.542] 0.998 25OHVD (ng/mL) 1.067 [0.975, 1.168] 0.156 Prolactin (ng/mL) 1.104 [1.014, 1.203] 0.023 Free testosterone (pg/mL) 1.621 [0.647, 4.060] 0.303 BMI; body mass index, IAAF; International Association of Athletics Federations, TRACP; tartrate-resistant acid phosphatase-5b, NTx; N-terminal telopeptide, T-P1NP; total pro-collagen type 1 amino-terminal propeptide, BAP; bone-specific alkaline phosphatase, OC; osteocalcin, iPTH; intact parathyroid hormone, ucOC; undercarboxylated osteocalcin, 25OHVD; 25-OH Vitamin D. Discussion Research on stress fractures have been performed numerously especially on female athletes after the female athlete triad had been announced by the American College of Sports Medicine and previous researches were mainly on athletes that are prone to have relative energy deficiency for example, long distance running because relative energy deficiency is one of the component of the triad (K. L. Bennell et al., 1995 ; Feingold & Hame, 2006 ; Jun Iwamoto & Takeda, 2003 ; Thein-Nissenbaum & Carr, 2011 ). However, stress fractures also do exist in power sports including jumping and sprinting events. In fact, 39.3% of the athletes in this study had a history of stress fracture after high school. Although previous research has demonstrated that those with lower BMI are prone to have stress fractures, it is speculated that this applies more to long-distance runners and not so much to sprinters since their physiques are different and sprinters and jumpers have higher BMI than the long-distance runners in general. In addition, according to many previous studies, the older the age of menarche, the risk to have stress fractures increased but it was not a related factor to have stress fractures in this study (K. L. Bennell et al., 1995 ; K. L. Bennell et al., 1996 ; Warren et al., 2002 ; Warren et al., 1991 ). Previous articles have reported that the more you train and the higher level the athlete compete in, the risk increases (Jun Iwamoto & Takeda, 2003 ). However, in this study, there were not any differences between the stress fracture (+) and stress fracture (-) groups and none of the factors that reflect the training schedules and levels of the athlete were an associated factor to have stress fractures. Bennell et al. has reported that in their study on track and field athletes, female athletes with low BMD developed stress fractures although the event of the athletes were not specified. However, surprisingly, neither BMD, Z-score, and T-score were not significantly different between stress fracture (+) and stress fracture (-) groups but since all athletes in this study are eumenorrhea, it is speculated that their BMD were within normal limits. 25OHVD which helps to boost up BMD were low in both groups. Although the BMD were higher than the average population possibly due to their training workouts strengthening their bone density (Benedetti et al., 2018 ; Chilibeck et al., 1995 ), they are not getting the recommended amount of vitamin D. Since track and field is an outdoor sport and most athletes train outdoors, it is speculated that they are getting enough sunlight. Thus, it is conjectured that they are not getting enough vitamin D from their food intake. In fact, Japanese food is not so high in vitamin D (Nakamura, 2006 ). Some of the mean value of bone metabolism markers were higher than the reference range. This could possibly from the fact that most references are based on premenopausal women typically between the age of 30–44 years old (Nishizawa et al., 2019 ). However, bone metabolism markers decrease in teen athletes as they get older, thus, it is hard conclude that it is out of the reference range or not (Y. Tsukahara et al., 2021 ). Although previous studies had reported that bone metabolism markers may have a link to stress fractures in female athletes, it was not the case in our athletes and future studies are required (Fujita et al., 2017 ; Nose-Ogura et al., 2020 ; Wakamatsu et al., 2012 ). Prolactin was the only thing that were different between the two groups and was a related factor in the logistic regression analysis and it was higher in stress fracture (+) compared to stress fracture (-). Prolactin is a hormone that increases during pregnancy and postpartum. It is also known to have osteopenia and there are case reports of stress fracture during postpartum (Lin & Lane, 2003 ; Thienpont et al., 1999 ). Thus, although it was in the reference range, it is speculated that those with stress fracture (+) were prone to have osteopenia. Prolactin has been reported to increase when there are psychological stress (Lennartsson & Jonsdottir, 2011 ). In our study, although we did not assess the psychological stress throughout their careers, they may have had extra stress which caused them to have an increased level of prolactin and thus leading them to have osteopenia which increases the risk of stress fractures. This study has several limitations. First of all, although we asked the athletes not to take any food and train for at least two hours prior, it was not possible to do the measurement at the same time due to scheduling difficulties. Second of all, although prolactin does not fluctuate by menstrual cycles, it would have been more accurate to measure other hormones as well at the same phase of their menstrual cycles but again was different to do so due to scheduling difficulties. In addition, although it is possible that some people have fasted much more than two hours since athletes came from different places which could have affected the bone turn over markers. Third, also equipment including their type of shoe and surface has been reported to have a link to stress fractures, those were not asked and future studies should ask about them and assess the risk to have stress fractures (Warden et al., 2006 ). Last, we have asked the history of having a stress fracture and not if they are currently suffering from stress fractures. Thus, we cannot determine if the prolactin was elevated solely secondary to fracture through the healing process and further investigation assessing the time relationship with between the stress fracture and prolactin is required. Stress fractures occur from multiple reasons and even though it is known to occur by over training, it still is question what this “over” is. Thus, we conjecture that it occurs from multiple factors but results of our study indicated that measuring prolactin could be the key to assess the stress of the athlete that could potentially lead to stress fractures. Stress fractures are commonly seen in track and field athletes specializing in sprinting and jumping that are eumenorrheic. None of the personal backgrounds including training schedules and level as an athlete were statistically significant difference between stress fracture (+) and stress fracture (-). Bone metabolism markers were also not different between the two groups but 25OHVD were below the normal value in both groups. Prolactin was higher in between stress fracture (+) compared to between stress fracture (-) and was also a related factor for having a history of stress fractures in logistic regression analysis. Declarations Conflict of interest The authors declare that they have no conflict of interest. Funding This study was financially supported by Japan Sports Agency, Support for Female Athletes. Author Contribution YTs, ST, FY, and TA conceived and designed research. YTs, YTa, ST, TK and HM conducted experiments. YTs, FY and TA analyzed data. YTs drafted the manuscript. 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Clin Chim Acta 498:101–107. https://doi.org/10.1016/j.cca.2019.08.012 Nose-Ogura S, Yoshino O, Dohi M, Torii S, Kigawa M, Harada M, Hiraike O, Kawahara T, Osuga Y, Fujii T (2020) Relationship between tartrate‐resistant acid phosphatase 5b and stress fractures in female athletes. J Obstet Gynecol Res 46(8):1436–1442 Okamoto S, Arai Y, Hara K, Tsuzihara T, Kubo T (2010) A displaced stress fracture of the femoral neck in an adolescent female distance runner with female athlete triad: A case report. BMC Sports Sci Med Rehabilitation 2(1):6. https://doi.org/10.1186/1758-2555-2-6 Palacios C (2006) The role of nutrients in bone health, from A to Z. Crit Rev Food Sci Nutr 46(8):621–628. https://doi.org/10.1080/10408390500466174 Pierpoint LA, Williams CM, Fields SK, Comstock RD (2016) Epidemiology of injuries in United States high school track and field: 2008–2009 through 2013–2014. Am J Sports Med 44(6):1463–1468 Schulte S, Schiffer T, Sperlich B, Knicker A, Podlog LW, Strüder HK (2013) The impact of increased blood lactate on serum S100B and prolactin concentrations in male adult athletes. Eur J Appl Physiol 113:811–817 Seriwatanachai D, Thongchote K, Charoenphandhu N, Pandaranandaka J, Tudpor K, Teerapornpuntakit J, Suthiphongchai T, Krishnamra N (2008) Prolactin directly enhances bone turnover by raising osteoblast-expressed receptor activator of nuclear factor κB ligand/osteoprotegerin ratio. Bone 42(3):535–546 Skorseth P, Segovia N, Hastings K, Kraus E (2020) Prevalence of Female Athlete Triad Risk Factors and Iron Supplementation Among High School Distance Runners: Results From a Triad Risk Screening Tool. Orthop J Sports Med 8(10):1–7. https://doi.org/10.1177/2325967120959725 Tenforde AS, Sayres LC, Sainani KL, Fredericson M (2010) Evaluating the relationship of calcium and vitamin D in the prevention of stress fracture injuries in the young athlete: a review of the literature. Pm&r 2(10):945–949 Thein-Nissenbaum JM, Carr KE (2011) Female athlete triad syndrome in the high school athlete. Phys Ther Sport 12(3):108–116. https://doi.org/10.1016/j.ptsp.2011.04.002 Thienpont E, Simon J-P, Fabry G (1999) Sacral stress fracture during pregnancy-a case report. Acta Orthop Scand 70(5):525–526 Trémollieres F (2013) Impact of oral contraceptive on bone metabolism. Best Pract Res Clin Endocrinol Metab 27(1):47–53 Tsukahara Y, Torii S, Yamasawa F, Iwamoto J, Otsuka T, Goto H, Kusakabe T, Matsumoto H, Akama T (2021) Bone Metabolism, Bone Mineral Content, and Density in Elite Late Teen Female Sprinters. Int J Sports Med 42(13):1228–1233. https://doi.org/10.1055/a-1432-2587 Tsukahara Y, Torii S, Yamasawa F, Iwamoto J, Otsuka T, Goto H, Kusakabe T, Matsumoto H, Akama T (2021) Bone parameters of elite athletes with oligomenorrhea and prevalence seeking medical attention: a cross-sectional study. J Bone Miner Metab 39(6):1009–1018 Wakamatsu K, Sakuraba K, Suzuki Y, Maruyama A, Tsuchiya Y, Shikakura J, Ochi E (2012) Association between the stress fracture and bone metabolism/quality markers in lacrosse players. Open Access J Sports Med 3:67 Warden SJ, Burr DB, Brukner PD (2006) Stress fractures: pathophysiology, epidemiology, and risk factors. Curr Osteoporos Rep 4(3):103–109 Warren MP, Brooks-Gunn J, Fox RP, Holderness CC, Hyle EP, Hamilton WG (2002) Osteopenia in exercise-associated amenorrhea using ballet dancers as a model: a longitudinal study. J Clin Endocrinol Metab 87(7):3162–3168. https://doi.org/10.1210/jcem.87.7.8637 Warren MP, Brooks-Gunn J, Fox RP, Lancelot C, Newman D, Hamilton WG (1991) Lack of bone accretion and amenorrhea: evidence for a relative osteopenia in weight-bearing bones. J Clin Endocrinol Metab 72(4):847–853. https://doi.org/10.1210/jcem-72-4-847 Wu Y, Lu K, Girgis C, Preda M, Preda V (2021) Postpartum bilateral sacral stress fracture without osteoporosis—a case report and literature review. Osteoporos Int 32(4):623–631 Yanovich R, Evans RK, Friedman E, Moran DS (2013) Bone turnover markers do not predict stress fracture in elite combat recruits. Clin Orthop Relat Research® 471(4):1365–1372 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4179484","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":286311562,"identity":"5a6d46eb-bc8f-4ae5-90e6-fb5036d26042","order_by":0,"name":"Yuka Tsukahara","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYFACNjDJw8fAfABIS8gQr4WNgS0BpIWHaC1AiscArJegBoMbaYkfGNtsZNjYz3x+daPGgoeB/fDRDQS0HJZgbEvjYePJ3WadcwzoMJ60tBv4taQ3SDCcOQz0S+424xw2oBYJHjNCWpp/gLXwv3lmnPOPKC1pxyQYKoBaJHKYH+e2EaFF8syzNIuECqBfJJ6ZMef2SQA9RcAvfMfTjG98MLCx5+dPfvw551udHD/74WN4tSgcABIJEDabBJjEpxwE5BsQbOYPhFSPglEwCkbByAQAMUlAyqdwEscAAAAASUVORK5CYII=","orcid":"","institution":"Tokyo Women's College of Physical Education","correspondingAuthor":true,"prefix":"","firstName":"Yuka","middleName":"","lastName":"Tsukahara","suffix":""},{"id":286311563,"identity":"8a2b0e0d-fbf3-4411-87b5-66ef90b0ec63","order_by":1,"name":"Suguru Torii","email":"","orcid":"","institution":"Waseda University","correspondingAuthor":false,"prefix":"","firstName":"Suguru","middleName":"","lastName":"Torii","suffix":""},{"id":286311564,"identity":"233f40e9-4191-493c-8362-aa7ca6c3a5d2","order_by":2,"name":"Yukiko Taniguchi","email":"","orcid":"","institution":"Japanese Red-Cross Kyoto Daini Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yukiko","middleName":"","lastName":"Taniguchi","suffix":""},{"id":286311565,"identity":"721c1894-5170-48e8-a354-7f79c1559e96","order_by":3,"name":"Torao Kusakabe","email":"","orcid":"","institution":"Japanese Red-Cross Kyoto Daini Hospital","correspondingAuthor":false,"prefix":"","firstName":"Torao","middleName":"","lastName":"Kusakabe","suffix":""},{"id":286311566,"identity":"af6cd8e7-493f-4e27-833d-06c1d010f8bf","order_by":4,"name":"Hideki Murakami","email":"","orcid":"","institution":"Nagoya City University Graduate School of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Hideki","middleName":"","lastName":"Murakami","suffix":""},{"id":286311567,"identity":"e39ae8c4-c16f-403d-8692-17dbc21ecc46","order_by":5,"name":"Fumihiro Yamasawa","email":"","orcid":"","institution":"Japan Association of Athletics Federations (JAAF)","correspondingAuthor":false,"prefix":"","firstName":"Fumihiro","middleName":"","lastName":"Yamasawa","suffix":""},{"id":286311568,"identity":"cb27a3e5-f825-4e45-8423-dc2e72bcb76b","order_by":6,"name":"Takao Akama","email":"","orcid":"","institution":"Waseda University","correspondingAuthor":false,"prefix":"","firstName":"Takao","middleName":"","lastName":"Akama","suffix":""}],"badges":[],"createdAt":"2024-03-28 04:29:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4179484/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4179484/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54459686,"identity":"1d723ac8-ea40-4119-8a21-0a9731c67b05","added_by":"auto","created_at":"2024-04-10 22:07:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":258711,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4179484/v1/09627761-7309-4d2f-8e9a-33ad05d39686.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association between prolactin and history of stress fracture in elite sprinters and jumpers","fulltext":[{"header":"Introduction","content":"\u003cp\u003eStress fractures, which occur due to repetitive micro damage is devastating for athletes especially competing at a high level because although it differs by the severity, it generally requires a few months for return to play (Jamieson et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Miller et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Since the female athlete triad (the triad) was first described by the American College of Sports Medicine, many studies have focused on the epidemiology and treatment of stress fractures in athletes (Lodge et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Skorseth et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The triad, consisted by relative energy deficiency, osteoporosis, and amenorrhea has brought a lot of attention to athletes and coaches and more people are starting to understand the relationship between energy deficiency leading to amenorrhea which could cause low bone density and consequently causing stress fractures (M. J. De Souza et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Thein-Nissenbaum \u0026amp; Carr, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) (Carter, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; H\u0026oslash;eg et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Skorseth et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). For example, as of track and field, there are many studies on the low BMD in long distance runners, and the link between with other symptoms related to the triad and relative energy deficiency in sport (RED-S) athletes since long distance runners are prone to the triad compared to other track and field events such as sprinting and jumping which are less prone to have those symptoms (Michelle T. Barrack et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Edouard \u0026amp; Alonso, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; H\u0026oslash;eg et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; J. Iwamoto et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Kelsey et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Okamoto et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Pierpoint et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, although many studies have focused on predicting low energy availability and amenorrhea by medical history and laboratory data, studies focusing on just sprinters and jumpers with a history of stress fractures without amenorrhea does not exist to the best of our knowledge in Japan. However, according to the Medical Committee of the Japan Association of Athletics Federation, prevalence of stress fractures in female national level high school and collegiate sprinters were 17.6% and 15.9% respectively. These were not that different from middle and long distance runners which were 17.7% in high school athletes and 19.0% in collegiate athletes (Federations, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e ).\u003c/p\u003e \u003cp\u003eAlthough the relationship between stress fractures and bone metabolism markers are still controversial (K. Bennell et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Yanovich et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), bone turnover markers have been reported to have a relationship between stress fractures (Fujita et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Nose-Ogura et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Wakamatsu et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Furthermore, hormones such as lutenizing hormone and estradiol has been reported to have a link between the symptoms related to the triad and RED-S (M. T. Barrack et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Feingold \u0026amp; Hame, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Loucks \u0026amp; Thuma, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). However, it fluctuates during the menstrual cycle and may not be considered as a predictor for consequences from the triad and reds including stress fractures for eumenorrheic athletes. Prolactin is a polypeptide hormone that increases during pregnancy and postpartum and has been reported to contribute to osteopenia by affecting bone turnover with increased bone resorption and suppressed bone formation (di Filippo et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Wu et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In fact, several case reports regarding stress fractures occurred during postpartum does exist and it has been reported that prolactin enhances bone turnover by enhancing osteoblast (Lin \u0026amp; Lane, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Seriwatanachai et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Thienpont et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). There have been studies investigating the relationship between prolactin and exercise (MARY JANE De Souza et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Kochańska-Dziurowicz et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Mougin et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Schulte et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). It also increases with stress and Lennartsson et al. has reported the increase of prolactin by psychosocial stress (Lennartsson \u0026amp; Jonsdottir, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). However, relationship between stress fractures and prolactin has not been fully understood especially on athletes that are not prone to have the triad and RED-S such as sprinters.\u003c/p\u003e \u003cp\u003eSince if there is a way to predict the occurrence of stress fractures, that would help many athletes. Thus, the purpose of this study is to investigate the risk factor for stress fractures and the characteristics of the laboratory data of them in eumenorrheic female track and field athletes competing at an elite level.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eSubjects\u003c/p\u003e\n\u003cp\u003eCollegiate and high school track and field athletes competing at a national level were recruited. The athletes were mostly recruited from the Kanto, Kansai, and Tokai regions of Japan and were examined at a designated hospital and universities. Since the body composition and the prevalence of amenorrhea is different per discipline, we recruited athletes specializing in the following events; 100meters (m), 200m, 400m, 100mH (meter hurdles), 400mH, long jump, triple jump, heptathlon, 4x100mR (meter relay) and 4X400mR. Since hormones could get affected by some medications including oral contraceptive pills, for those taking medications that could affect the hormonal levels were excluded (Garnero et al., \u003cspan class=\"CitationRef\"\u003e1995\u003c/span\u003e; Tr\u0026eacute;mollieres, \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). Also, for those who are experiencing amenorrhea and oligomenorrhea were also excluded since they have different bone metabolism and low bone mineral density compared to eumenorrheic athletes (Yuka Tsukahara et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). The measurement was performed during off-season and the recruitment took place between April 2021 to February 2022. Written informed consent was obtained from both the subjects and their legal guardians after being informed of the benefits and risks of the investigation. The study protocol was approved by the Ethics Review Procedures Concerning Research with Human Subjects Group of the authors\u0026rsquo; affiliated institutions (approval number 2020\u0026thinsp;\u0026minus;\u0026thinsp;416).\u003c/p\u003e\n\u003cp\u003eLaboratory data\u003c/p\u003e\n\u003cp\u003eParticipants were instructed to refrain from training and consume no food for at least 2 hours prior to blood collection which was performed between the timeframe of 11AM to 2PM. In order to assess bone metabolism, the following bone turnover markers were measured.\u003c/p\u003e\n\u003cp\u003e1) bone resorption markers\u003c/p\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n\u003cp\u003etartrate-resistant acid phosphatase type 5b (TRACP-5b) and N-terminal telopeptide total (NTx)\u003c/p\u003e\n\u003cp\u003e2) bone formation markers\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n\u003cp\u003epro-collagen type 1 amino-terminal propeptide (T-P1NP), bone-specific alkaline phosphatase (BAP), undercarboxylated osteocalcin (OC), and intact parathyroid hormone (iPTH)\u003c/p\u003e\n\u003cp\u003e3) bone matrix related markers\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n\u003cp\u003eosteocalcin undercarboxylated osteocalcin (ucOC), intact parathyroid hormone (iPTH)\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003eIn addition to the above, 25-OH vitamin D (25OHVD) were also measured since although the relationship between vitamin D and stress fractures in athletes are scarce (Myburgh et al., \u003cspan class=\"CitationRef\"\u003e1990\u003c/span\u003e), some studies have reported the link between vitamin D and BMD in non-athletes (Dawson-Hughes et al., \u003cspan class=\"CitationRef\"\u003e1997\u003c/span\u003e; Mezquita-Raya et al., \u003cspan class=\"CitationRef\"\u003e2001\u003c/span\u003e; Palacios, \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e; Tenforde et al., \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e). In addition, although it was a study on male athletes, free testosterone was also reported to be low in male endurance athletes and thus we also decided to measure free testosterone to seek the relationship between stress fractures along with prolactin (Boden et al., \u003cspan class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eHeight weight and Bone mineral density\u003c/p\u003e\n\u003cp\u003eHeight was measured with the athlete standing erect without shoes to the nearest 0.1 cm using a stadiometer. Bone mineral density was assessed by whole body modedual-energy X-ray absorptiometry using a Delphi Bone Densitometer (Hologic, Inc., Bedford, MA, USA). After calibration, as for the whole body mode, the subjects, wearing a t-shirt without objects that could interfere with the test, were instructed to lay on a table with the shoulders slightly abducted and elbows slightly flexed, so that the forearms were parallel to the body axis, while extending, but not spreading, the fingers with the palms facing downward. The feet were bound to a polystyrene block in the shape of an isosceles triangle with the vertex angle of 30\u0026ordm;, so that the fibulae were not hidden by the tibiae. The same technician performed all scans at each site.\u003c/p\u003e\n\u003cp\u003eTraining schedules and injuries\u003c/p\u003e\n\u003cp\u003eA questionnaire was distributed to the athletes via online inquiring about the amount of training hours per day on both weekdays and weekends, resting days per week, weight training days per week, any past medical history of bone injuries. We also interviewed all athletes regarding their injuries and those who answered that they had been diagnosed to have stress fracture after high school and included those who were properly diagnosed by a physician following an imaging study were marked as stress fracture (+) and those without a history of stress fracture were marked as stress fracture (-).\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\n\u003cp\u003eAll data were analyzed using the Stata 16.1 (Stata Corporation, TX, USA). The results are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. The Shapiro\u0026ndash;Wilk test was applied to assess the distribution of the data. Continuous data were compared using the independent t-test. A probability (p) value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant. Logistic regression analysis was performed to identify independent variables and having a stress fracture after high school was used as a dependent variable.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eCharacteristics of the subjects\u003c/p\u003e \u003cp\u003eTotal of 84 female track and field athletes were enrolled. Among them one was not able to obtain all bone metabolism markers since it was hard to draw the blood needed for analysis and ucOC and TRACP were not measured. Total of 33 athletes (39.3%) had a history of stress fractures in their lower extremity after high school.\u003c/p\u003e \u003cp\u003eBoth stress fracture (+) and stress fracture (-) groups had a similar height and body weight and they were not statistically significantly different between the two groups Age at menarche and the age they started track and field were also similar, and they both were around the age of late elementary school to junior high school. Training schedules of the athletes including training hours per day and rest days per week and scores of the IAAF scoring table was not different between the two meaning that they were competing at the same level. Characteristics of the subjects are listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of athletes with and without a history of stress fractures\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStress fracture (+)\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;33)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStress fracture (-)\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;51)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e20.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e20.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.260\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e161.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e161.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.846\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody weight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e55.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e53.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.210\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at menarche (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e12.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e12.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.738\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge they started track and field (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e11.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e11.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.991\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTraining hours per day (hours/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.459\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRest days per week (days/week)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.759\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIAAF Scoring Table (points)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e993.6\u0026thinsp;\u0026plusmn;\u0026thinsp;65.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e980.5\u0026thinsp;\u0026plusmn;\u0026thinsp;82.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.445\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eIAAF; International Association of Athletics Federations\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBone mineral density\u003c/p\u003e \u003cp\u003eThere was no statistically significant difference between the two groups. Both their Z and T score were above average meaning that they were higher than zero in both groups.\u003c/p\u003e \u003cp\u003eLaboratory data\u003c/p\u003e \u003cp\u003eMean values were mostly in the reference range except for ucOC and T-P1NP in both groups. Among those without a history of stress fractures, one participant was not able to measure TARCP and ucOC because of the lack of sample. Bone resorption markers TRACP and BAP were not statistically significantly different between the two groups. All bone formation markers T-P1NP, BAP, and OC were also not statistically significantly different between the two groups. Furthermore, iPTH and ucOC were not statistically significantly different between the two groups. Reference range of the bone metabolism markers are also listed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and they are according to the \u0026ldquo;Guidelines for the Use of Biochemical Markers of Bone Turnover in Osteoporosis of the Japan Osteoporosis Society\u0026rdquo; and the reference value suggested by the laboratory company (Nishizawa et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Prolactin was higher in stress fracture (+) compared to stress fracture (-) (p\u0026thinsp;=\u0026thinsp;0.019).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of BMD and laboratory data\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStress fracture (+)\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;33)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStress fracture (-)\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;51)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eW- BMD (g/cm\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.192\u0026thinsp;\u0026plusmn;\u0026thinsp;0.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.190\u0026thinsp;\u0026plusmn;\u0026thinsp;0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.916\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZ score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e111.70\u0026thinsp;\u0026plusmn;\u0026thinsp;8.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e111.59\u0026thinsp;\u0026plusmn;\u0026thinsp;6.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.949\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e108.39\u0026thinsp;\u0026plusmn;\u0026thinsp;8.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e108.25\u0026thinsp;\u0026plusmn;\u0026thinsp;6.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTRACP (mU/dL)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e292.39\u0026thinsp;\u0026plusmn;\u0026thinsp;120.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e278.72\u0026thinsp;\u0026plusmn;\u0026thinsp;91.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.559\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e120\u0026ndash;420\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNTx (nmolBCE/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e20.25\u0026thinsp;\u0026plusmn;\u0026thinsp;10.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e18.85\u0026thinsp;\u0026plusmn;\u0026thinsp;6.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.5\u0026ndash;16.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT-P1NP (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e81.84\u0026thinsp;\u0026plusmn;\u0026thinsp;28.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e77.15\u0026thinsp;\u0026plusmn;\u0026thinsp;26.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.8\u0026ndash;70.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBAP (\u0026micro;g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e15.80\u0026thinsp;\u0026plusmn;\u0026thinsp;6.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e14.07\u0026thinsp;\u0026plusmn;\u0026thinsp;3.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.9\u0026ndash;14.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOC (mIU/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e19.81\u0026thinsp;\u0026plusmn;\u0026thinsp;7.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e17.53\u0026thinsp;\u0026plusmn;\u0026thinsp;4.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.8\u0026ndash;30.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eiPTH (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e35.70\u0026thinsp;\u0026plusmn;\u0026thinsp;12.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e36.55\u0026thinsp;\u0026plusmn;\u0026thinsp;13.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.775\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u0026ndash;65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eucOC (ng/mL)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e5.36\u0026thinsp;\u0026plusmn;\u0026thinsp;3.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e4.68\u0026thinsp;\u0026plusmn;\u0026thinsp;2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;4.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25OHVD (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e26.71\u0026thinsp;\u0026plusmn;\u0026thinsp;6.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e24.44\u0026thinsp;\u0026plusmn;\u0026thinsp;5.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProlactin (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e15.70\u0026thinsp;\u0026plusmn;\u0026thinsp;10.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e11.59\u0026thinsp;\u0026plusmn;\u0026thinsp;5.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.019\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.91\u0026ndash;29.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFree testosterone(pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.152\u0026thinsp;\u0026plusmn;\u0026thinsp;0.986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.841\u0026thinsp;\u0026plusmn;\u0026thinsp;0.517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4\u0026ndash;2.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eW-BMD; bone mineral density of the whole body, T-P1NP; total pro-collagen type 1 amino-terminal propeptide, ucOC; undercarboxylated osteocalcin, OC; osteocalcin, TRACP; tartrate-resistant acid phosphatase-5b, BAP; bone-specific alkaline phosphatase, iPTH; intact parathyroid hormone, NTx; N-terminal telopeptide, 25OHVD; 25-OH Vitamin D.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eLogistic regression analysis\u003c/p\u003e \u003cp\u003eNone of the personal background of the athlete were related to have a stress fracture and neither were the training schedules. IAAF scoring table points, Z-score of their BMD, bone metabolism markers and 25OHVD were not related factors to have stress fractures. Prolactin had positive relationship to have stress fractures (OR 1.104, p\u0026thinsp;=\u0026thinsp;0.023). Results of the logistic regression analysis are listed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of logistic regression analysis to investigate the factors related to have stress fractures\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds Ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.774\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e[0.561, 1.068]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.755\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e[0.508, 1.122]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at menarche (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e[0.755, 1.210]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.708\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge they started track and field (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e[0.780, 1.368]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.819\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTraining hours per day (hours/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e[0.421, 2.940]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.830\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRest days per week (days/week)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e[0.182, 1.755]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.324\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIAAF Scoring Table (points)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e[0.994, 1.010]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.645\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZ-score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e[0.963, 1.140]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.276\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTRACP (mU/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e[0.988, 1.004]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.320\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNTx (nmolBCE/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e[0.923, 1.059]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.750\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT-P1NP (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.968\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e[0.931, 1.006]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBAP (\u0026micro;g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e[0.899, 1.306]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.399\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOC (mIU/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e[0.978, 1.543]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eiPTH (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.983\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e[0.936, 1.033]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.506\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eucOC (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e[0.649, 1.542]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.998\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25OHVD (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e[0.975, 1.168]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProlactin (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e[1.014, 1.203]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFree testosterone (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.621\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e[0.647, 4.060]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.303\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eBMI; body mass index, IAAF; International Association of Athletics Federations, TRACP; tartrate-resistant acid phosphatase-5b, NTx; N-terminal telopeptide, T-P1NP; total pro-collagen type 1 amino-terminal propeptide, BAP; bone-specific alkaline phosphatase, OC; osteocalcin, iPTH; intact parathyroid hormone, ucOC; undercarboxylated osteocalcin, 25OHVD; 25-OH Vitamin D.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eResearch on stress fractures have been performed numerously especially on female athletes after the female athlete triad had been announced by the American College of Sports Medicine and previous researches were mainly on athletes that are prone to have relative energy deficiency for example, long distance running because relative energy deficiency is one of the component of the triad (K. L. Bennell et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Feingold \u0026amp; Hame, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Jun Iwamoto \u0026amp; Takeda, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Thein-Nissenbaum \u0026amp; Carr, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). However, stress fractures also do exist in power sports including jumping and sprinting events. In fact, 39.3% of the athletes in this study had a history of stress fracture after high school. Although previous research has demonstrated that those with lower BMI are prone to have stress fractures, it is speculated that this applies more to long-distance runners and not so much to sprinters since their physiques are different and sprinters and jumpers have higher BMI than the long-distance runners in general. In addition, according to many previous studies, the older the age of menarche, the risk to have stress fractures increased but it was not a related factor to have stress fractures in this study (K. L. Bennell et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; K. L. Bennell et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Warren et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Warren et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). Previous articles have reported that the more you train and the higher level the athlete compete in, the risk increases (Jun Iwamoto \u0026amp; Takeda, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). However, in this study, there were not any differences between the stress fracture (+) and stress fracture (-) groups and none of the factors that reflect the training schedules and levels of the athlete were an associated factor to have stress fractures. Bennell et al. has reported that in their study on track and field athletes, female athletes with low BMD developed stress fractures although the event of the athletes were not specified. However, surprisingly, neither BMD, Z-score, and T-score were not significantly different between stress fracture (+) and stress fracture (-) groups but since all athletes in this study are eumenorrhea, it is speculated that their BMD were within normal limits. 25OHVD which helps to boost up BMD were low in both groups. Although the BMD were higher than the average population possibly due to their training workouts strengthening their bone density (Benedetti et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Chilibeck et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1995\u003c/span\u003e), they are not getting the recommended amount of vitamin D. Since track and field is an outdoor sport and most athletes train outdoors, it is speculated that they are getting enough sunlight. Thus, it is conjectured that they are not getting enough vitamin D from their food intake. In fact, Japanese food is not so high in vitamin D (Nakamura, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Some of the mean value of bone metabolism markers were higher than the reference range. This could possibly from the fact that most references are based on premenopausal women typically between the age of 30\u0026ndash;44 years old (Nishizawa et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). However, bone metabolism markers decrease in teen athletes as they get older, thus, it is hard conclude that it is out of the reference range or not (Y. Tsukahara et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Although previous studies had reported that bone metabolism markers may have a link to stress fractures in female athletes, it was not the case in our athletes and future studies are required (Fujita et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Nose-Ogura et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Wakamatsu et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eProlactin was the only thing that were different between the two groups and was a related factor in the logistic regression analysis and it was higher in stress fracture (+) compared to stress fracture (-). Prolactin is a hormone that increases during pregnancy and postpartum. It is also known to have osteopenia and there are case reports of stress fracture during postpartum (Lin \u0026amp; Lane, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Thienpont et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Thus, although it was in the reference range, it is speculated that those with stress fracture (+) were prone to have osteopenia. Prolactin has been reported to increase when there are psychological stress (Lennartsson \u0026amp; Jonsdottir, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In our study, although we did not assess the psychological stress throughout their careers, they may have had extra stress which caused them to have an increased level of prolactin and thus leading them to have osteopenia which increases the risk of stress fractures.\u003c/p\u003e \u003cp\u003eThis study has several limitations. First of all, although we asked the athletes not to take any food and train for at least two hours prior, it was not possible to do the measurement at the same time due to scheduling difficulties. Second of all, although prolactin does not fluctuate by menstrual cycles, it would have been more accurate to measure other hormones as well at the same phase of their menstrual cycles but again was different to do so due to scheduling difficulties. In addition, although it is possible that some people have fasted much more than two hours since athletes came from different places which could have affected the bone turn over markers. Third, also equipment including their type of shoe and surface has been reported to have a link to stress fractures, those were not asked and future studies should ask about them and assess the risk to have stress fractures (Warden et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Last, we have asked the history of having a stress fracture and not if they are currently suffering from stress fractures. Thus, we cannot determine if the prolactin was elevated solely secondary to fracture through the healing process and further investigation assessing the time relationship with between the stress fracture and prolactin is required.\u003c/p\u003e \u003cp\u003eStress fractures occur from multiple reasons and even though it is known to occur by over training, it still is question what this \u0026ldquo;over\u0026rdquo; is. Thus, we conjecture that it occurs from multiple factors but results of our study indicated that measuring prolactin could be the key to assess the stress of the athlete that could potentially lead to stress fractures.\u003c/p\u003e \u003cp\u003eStress fractures are commonly seen in track and field athletes specializing in sprinting and jumping that are eumenorrheic. None of the personal backgrounds including training schedules and level as an athlete were statistically significant difference between stress fracture (+) and stress fracture (-). Bone metabolism markers were also not different between the two groups but 25OHVD were below the normal value in both groups. Prolactin was higher in between stress fracture (+) compared to between stress fracture (-) and was also a related factor for having a history of stress fractures in logistic regression analysis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of interest\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis study was financially supported by Japan Sports Agency, Support for Female Athletes.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eYTs, ST, FY, and TA conceived and designed research. YTs, YTa, ST, TK and HM conducted experiments. YTs, FY and TA analyzed data. YTs drafted the manuscript. All authors edited, read and approved the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe would like to thank the participants for their cooperation.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eRaw data for dataset are not publicly available to preserve individuals\u0026rsquo; privacy under the Data Protection Regulation of the IRB of the author's institution but is available upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBarrack MT, Gibbs JC, De Souza MJ, Williams NI, Nichols JF, Rauh MJ, Nattiv A (2014) Higher Incidence of Bone Stress Injuries With Increasing Female Athlete Triad\u0026ndash;Related Risk Factors: A Prospective Multisite Study of Exercising Girls and Women. 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Clin Orthop Relat Research\u0026reg; 471(4):1365\u0026ndash;1372\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"prolactin, stress fracture, vitamin D, track and field","lastPublishedDoi":"10.21203/rs.3.rs-4179484/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4179484/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003ePurpose\u003c/b\u003e\u003c/p\u003e \u003cp\u003eResearch related to stress fractures and the female athlete triad is abundant. However, since there is not enough evidence to support the risk factors for stress fractures is not sufficient. The aim of this study is to investigate the risk factor for stress fractures and the characteristics of the laboratory data of them in eumenorrheic female track and field athletes competing at an elite level\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eEumenorrheic sprinters and jumpers competing at a national level were recruited. Bone mineral density, bone metabolism markers, 25-OH Vitamin D, and hormones including prolactin and free testosterone were measured.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA total of 84 high school and collegiate athletes were enrolled in the study, and among them, 33 athletes had a history of stress fracture after high school. Their personal background, bone mineral density, bone metabolism markers, 25-OH Vitamin D, and free testosterone were not different between the group with a history of stress fracture and without a history of stress fracture. Prolactin was higher in those with stress fractures compared to those without stress fractures, and it was statistically different between the two groups (15.70\u0026thinsp;\u0026plusmn;\u0026thinsp;10.59 ng/mL and 11.59\u0026thinsp;\u0026plusmn;\u0026thinsp;5.06 ng/mL, respectively, p\u0026thinsp;=\u0026thinsp;0.019). Logistic regression analysis revealed that it was also a significant predictive factor for stress fractures (odds ratio: 1.10; 95% CI: 1.01\u0026ndash;1.20; P\u0026thinsp;=\u0026thinsp;0.023).\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eProlactin may be linked to stress fractures in eumenorrheic sprinters and jumpers.\u003c/p\u003e","manuscriptTitle":"Association between prolactin and history of stress fracture in elite sprinters and jumpers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-02 10:30:51","doi":"10.21203/rs.3.rs-4179484/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"afc48261-44f8-46c4-a6f4-30c87c793d96","owner":[],"postedDate":"April 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-10T21:59:22+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-02 10:30:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4179484","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4179484","identity":"rs-4179484","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}