Journal Logo


Effects of a 4-Month Recruit Training Program on Markers of Bone Metabolism


Author Information
Medicine & Science in Sports & Exercise: November 2008 - Volume 40 - Issue 11 - p S660-S670
doi: 10.1249/MSS.0b013e318189422b
  • Free


Beginning novel, high-volume exercise regimens without a progressive train-up period can lead to bone overuse injuries. Stress fracture, in particular, is a common and potentially debilitating bone overuse injury occurring frequently in both military recruits and athletes (34). Susceptibility to stress fracture during high-intensity, repetitive impact loading is hypothesized to result from accelerated bone remodeling (16), which may compromise bone strength at fracture prone sites due to the time delay in achieving full mineralization of newly formed bone matrices (39). This injury requires extensive rehabilitation time and can proceed to full fracture if physical activity is not severely limited (24). Thus, there is a need to develop methods to screen for changes in bone metabolism that lead to susceptibility for stress fracture during training.

The effect of mechanical loading on bone differs with the type and volume of exercise being performed (25,26) and may have differing effects on the remodeling process. Although resistance training interventions appear to favor bone formation without increased resorption (13,30,36), an anaerobic sprint training intervention resulted in increased concentrations of both bone formation and resorption markers over an 8-wk training period (42). Conversely, an aerobic running intervention was observed to decrease bone formation and resorption markers after 4 wk (42). Although the bone formation markers returned to baseline at 8 wk, resorption markers exhibited further decline, indicating that the early response to run training may favor a period of decreased bone formation during high-impact exercise.

Bone overuse injuries after sudden onset of unaccustomed, repetitive, high-impact training programs such as those undertaken during military training are hypothesized to result in changes in bone metabolism favoring bone resorption (32). In male military recruits, 10 wk of strenuous training combining high-impact aerobic, anaerobic, and resistance exercise resulted in a decrease in bone formation markers, although bone resorption was unchanged (11). The same trends toward decreased bone formation with repetitive high-impact exercise can be observed in long-distance runners (42) and are especially evident in women with amenorrhea (14). It is unclear whether women, who sustain stress fracture at much higher rates than men during strenuous recruit training programs (27), differ from men in their bone turnover response to similar exercise regimens. Although a consistent rise in a bone resorption marker was greater in women than men during an 11-wk gender-integrated recruit training program (32), the net effect on bone turnover could not be determined as markers of bone formation were not assessed.

Endocrine regulators of bone include parathyroid hormone (PTH), vitamin D, and calcium, all which may be affected during periods of strenuous exercise and may offer insight into gender differences in bone metabolism. In a healthy individual, serum calcium homeostasis is maintained by the action of PTH. An increase in PTH stimulates osteoclasts to reabsorb bone mineral, liberating calcium into the blood, and increases calcium absorption from the intestine by stimulating production of the active form of vitamin D. PTH increases after exercise (2,37) and may reflect a response to exercise that is accentuated under conditions of marginal calcium and vitamin D status, affecting bone turnover. A marker of vitamin D status, 25(OH)D, has been shown to increase during exercise (3), and vitamin D insufficiency has been observed to result in changes in bone turnover markers in girls but not in boys (12). Low calcium intake is associated with high levels of PTH in the blood, and higher levels of PTH have been associated with stress fracture (40). A recent publication reported that vitamin D and calcium supplementation decreased the occurrence of stress fracture in female recruits by 20% (23). Much remains to be learned about the contribution of nutrition to endocrine regulators of bone metabolism that may relate to stress fracture susceptibility during strenuous training programs.

The increased inflammatory response during overtraining (1) may contribute to gender differences in bone metabolism that favor resorption in susceptible individuals. The cytokine response to exercise stress, particularly with reference to interleukin 6 (IL-6), has been related to intensity and duration of physical activity (33,35) and may play a fundamental role in the regulation of bone remodeling during exercise (9,28). Cytokine levels were prognostic for fracture in elderly men and women, where the relative risk for fracture was greater in subjects with three or more (out of 7) high inflammatory markers that included IL-6 and tumor necrosis factor α (TNF-α) (7). Cortical bone resorption, thought to be the first stage of stress fracture development, has been related to the IL-6 genotype in men (9). Interleukin 1B (IL-1B) stimulates resorptive activity in osteoclasts (38), which may influence the bone adaptation response. The cytokine response to military training and the relationship between status of inflammatory markers and bone turnover status in men and women are greatly understudied.

The primary goal of this study was to evaluate gender disparity in the response of markers of bone turnover and other serum markers associated with bone metabolism in a group of healthy, age-matched men and women undergoing a 4-month period of strenuous, gender-integrated combat training. Additionally, we sought to determine the relationship between bone turnover status and anthropometric and fitness measures, endocrine regulators, and inflammatory markers that might relate to risk for bone overuse injuries.



A total of 257 healthy men (n = 58) and women (n = 199) entering a gender-integrated basic recruit training program in the Israeli Defense Forces volunteered to participate in this study. Data were collected at three times points: before training (baseline), at the midpoint of training (∼2 months), and the day before graduation from training (∼4 months).

Volunteers were recruited from three separate gender-integrated recruit training programs over a 2-yr period (Table 1). All volunteers were medically cleared by a physician before entering the training program and were eligible to participate in the study only upon providing written informed consent. This investigation was reviewed and approved by the institutional review boards of the Committee for Research on Human Subjects, Israeli Defense Forces Medical Corps, Israel, and the Human Use Review Committee, US Army Research Institute of Environmental Medicine, Natick, MA.

Study recruitment summary from three training regimens.


Volunteers traveled to the Heller Institute for baseline data collection on the first or second day after reporting to their unit for mandatory service. Approximately halfway into the training period (approximately 2 months after baseline), the study team traveled to the basic training site for the midpoint data collection. The day before graduation (approximately 4 months after baseline), volunteers again reported for 1 day to the Heller Institute for final data collection. Blood and anthropometric measures were collected at pre-, mid-, and posttime points, whereas all other measures were taken at the pre- and posttime points.

Training Program

The training regimen was nearly identical for men and women and was scheduled to take place over a 4-month period. The recruits were housed for the entire period at a remote training site, were offered identical daily food choices in a communal dining facility, and had limited access to food supplements. Physical training was standardized for both men and women and included strenuous physical activities such as marching under load, running and jumping, battle drills, and walking and standing for prolonged periods of time.

Anthropometric Variables

Height (cm) was measured using a stadiometer, and weight (kg) was determined with a metric scale. Skinfold thickness was measured at four sites (biceps, triceps, suprailiac, and subscapular) with Lange skinfold calipers (Beta Technology, Santa Cruz, CA). The same investigator performed all skinfold measurements at all periods. Percent body fat was estimated from the skinfold measurements using previously established methods in a young adult population (10). Fat mass was determined by taking the subject's weight in kilograms and multiplying this by percent body fat determined by skinfold measurements. Lean mass was then determined by subtracting the volunteer's fat mass from their total body weight.

Blood Draw

A fasting blood sample was collected from all volunteers between 0700 and 0800 h using the following procedure: approximately 30 mL of blood were drawn from an antecubital vein using sterile venipuncture techniques. Blood was collected in 5-mL silicone-coated tubes (BD Vacutainer SST II Advance; Becton, Dickinson & Company, Franklin Lakes, NJ), allowed to sit for 30 min at room temperature, and immediately centrifuged at 4°C at 2000g for 15 min. Serum samples were then separated and stored at −70°C immediately after collection and remained frozen until analysis.

Fitness Assessments

Maximum volume of oxygen consumption (V˙O2max) was measured using a continuous, uphill, stepwise, treadmill protocol. The volunteer warmed-up by walking for 3 min at 3.1 mph (5 km·h−1) on a level grade. The volunteer then began running on the treadmill at a 2% grade and a speed determined to be easy to moderate based on the volunteer's heart rate during the warm-up run. The volunteer wore a face mask connected by a flexible hose to a metabolic measurement system (SensorMedics Corp., Yorba Linda, CA), which monitored oxygen uptake and displayed and printed oxygen uptake every 10 s. Every 2 min, the treadmill grade was increased by 2% without changing the treadmill speed. The volunteer was considered to have reached maximal oxygen uptake if, 1 min after a speed increase, oxygen uptake had not increased by at least 2 mL·kg−1·min−1. The volunteers reached maximum oxygen uptake within 10-15 min after starting the test.

The 2-km run time was measured as part of a maximal effort run during a three-event (push-up, sit-up, and 2-km run) physical fitness test. This test was administered by the volunteers' military unit as part of a military testing requirement, and results were provided to the research team.

Serum Analysis

Assays were performed in duplicate with an average of both assays used as the final measure. Samples from each subject were analyzed in the same assay to minimize the effects of assay variability. To accurately assess changes in production, we used assay results for albumin to adjust bone turnover markers for potential plasma volume shifts (8).

Bone turnover markers

Bone alkaline phosphatase (BAP), a measure of bone formation, was assayed by enzyme-linked immunosorbent assay (ELISA; Octeia™ Octase® BAP Immunoenzymetric assay; IDS Ltd., England, UK), which is specific to the bone isoform. Interassay coefficient of variation (CV) was 6%. Reference values (mean ± SD) for healthy men and premenopausal women are 12.3 ± 4.3 and 8.7 ± 2.9 μg·L−1, respectively, with a reference range of 3.7-20.9 μg·L−1. Procollagen I N-terminal peptide (PINP) was measured by the UNiQ radioimmunoassay (RIA) from Orion Diagnostica (Espoo, Finland). Interassay CV was 9.5%. The reference range of values for healthy men and premenopausal women is 22.0-87.0 μg·L−1. Tartrate-resistant acid phosphatase (TRAP5b) was measured using way of ELISA using the BoneTRAP® assay (IDS Ltd.). The interassay variation was 8%. Reference values (mean ± SD) for young men and premenopausal women are 3.06 ± 0.88 and 2.59 ± 0.78 U·L−1, respectively. The upper limit for normal men and women is 4.82 and 4.15 U·L−1, respectively, with a reference range of 1.3-4.8 U·L−1. C-telopeptide cross-links of type I collagen (CTx; Serum Crosslaps) were measured using ELISA kits from Nordic Bioscience Diagnostics (Herlev, Denmark). Interassay CV was 5%. Reference values for healthy mean and healthy premenopausal women are 0.115 ± 0.748 and 0.112 ± 0.738 ng·mL−1, respectively, with a reference range of 0.010-0.712 ng·mL−1.

Endocrine regulators

Albumin and calcium were both measured spectrophotometrically using a DXC600 Pro (Bechman Coulter, Fullerton, CA). Interassay CVs were 1.4% and 1.7%, respectively. Reference values for healthy men and premenopausal women are 3.1 to 5.4 g·dL−1 for albumin and 8.9-10.4 mg·dL−1 for calcium. Radioimmunoassay (RIA) was used to measure 25(OH)D levels (DiaSorin, Stillwater, MN). Interassay CV was 9.86%. Reference values for healthy men and premenopausal women are from 8.9 to 46.7 ng·mL−1. Parathyroid hormone (PTH) was measured by immunoassay with chemiluminescent detection on the Immulite 2000 (Diagnostics Products Corporation, Los Angeles, CA). Interassay CV was 4.7%. Reference values for healthy men and premenopausal women range from 12.0 to 72.0 pg·mL−1.

Inflammatory markers

TNF-α, IL-1b, and IL-6 were measured by ELISA from Linco (Linco Research Inc., St. Charles, MO) on the Luminex Labmap 100 (Luminex Corp., Austin, TX). Interassay CV were 10.9%, 13.3%, and 12.7%, respectively. The reference ranges for IL-1B, IL-6, and TNF-α are < 3.2-52, < 3.2-263, and < 3.2-36.4 pg·mL−1, respectively (sensitivity of these assays is 3.2 pg·mL−1).

Statistical Analysis

To assess gender differences in the response to training, we analyzed data using a repeated-measures ANOVA with time and gender as factors. Significant interactions were further analyzed using Fisher's Least Significant Difference (LSD). The mean change from baseline was analyzed for bone turnover and endocrine markers. For inflammatory markers, an additional analysis was made to determine whether individuals with high baseline levels responded differently than those with low levels at baseline. Further, if a significant training response in endocrine or inflammatory markers was observed, Pearson product moment correlation analyses were used to determine the relationship between the change in the marker and the change in markers of bone turnover. Correlation analyses were also used to assess the relationship between markers of bone turnover at baseline and anthropometric, fitness, endocrine, and inflammatory measures that might relate to bone adaptation status on entry to service. To determine the future utility of using bone turnover markers as an index of bone adaptation, we conducted stepwise regression analyses to predict the contribution of anthropometric and fitness measures possibly related to gender and stress fracture risk to each bone turnover marker. Significance was accepted at a level of P < 0.05.


Subject characteristics

Of the 257 total volunteers who were present for baseline data collection, 92% of the volunteers (90% men and 93% women) were present for data collection at 2 months and 83% were present for the final data collection (81% men and 84% women). A complete data set (data collected at all three time points) was obtained from 194 volunteers (75%) who graduated after completion of the 4-month training program (41 men and 153 women). Subject characteristics for volunteers at baseline and at 4 months are presented in Table 2. Forty-six women and 17 men did not participate in one or more follow-up measures for one of the following reasons: withdrawal from study, unavailable at time of data collection, transferred to another unit, or left military service. None of the volunteers left military service for reasons related to bone overuse injuries.

Subject characteristics at baseline (mean ± SD).

Training program

Although unforeseen circumstances resulted in a 3-wk break midtraining for group 2, this group's training period was extended so that all groups completed an identical 4-month training protocol. Midpoint data collection for this group was conducted at a point best coinciding with the completion of training that would normally occur at the 2-month midpoint. To assure that the 3-wk break did not result in differences in the bone turnover response for group 2, we conducted a repeated-measures ANOVA and revealed no significant group differences in the bone turnover response.

Anthropometric and fitness measurements

Gender differences were evident in lean mass, fat mass, percent body fat, V˙O2max, and 2-km run times; however, changes over time were similar in men and women (Table 3).

Changes in lean mass (LM), fat mass (FM), % body fat (%BF), aerobic fitness (V˙O2max), and run time in men and women over a 4-month training period (mean ± SD).

Markers of bone turnover

All markers of bone formation and resorption were significantly higher in men than women at baseline and remained higher at all time points (P < 0.001; Fig. 1). The bone formation markers BAP and PINP increased significantly over time (main effect, P < 0.001), although this change did not differ between genders. For BAP, the increase was evident from 0 to 2 months (P < 0.001), with no changes observed from 2 to 4 months (Fig. 1A). Women exhibited a greater percent increase in PINP than men from 0 to 2 months (20.6% vs 5.2%, respectively), although this difference was not statistically significant and dropped significantly from 2 to 4 months in both genders (P < 0.01; Fig. 1B). Bone resorption markers changed similarly for both genders (main time effect, P < 0.001 and P = 0.03 for CTx and TRAP5b, respectively). CTx increased in both men and women between 0 and 2 months (P < 0.001) and returned to baseline at 4 months (P = 0.003; Fig. 1C), whereas a change in TRAP5b was evident as an increase from 0 to 2 months only (P < 0.001; Fig. 1D).

Change in markers of bone formation (panel A: BAP, μg·L−1; panel B: PINP, μg·L−1) and resorption (panel C: CTx, ng·mL−1; panel D: TRAP5b, U·L−1) in men and women over a 4-month training period (mean ± SE). Post hoc analysis of a main time effect (P < 0.001) denotes * significant change from baseline and # significant change from 2 to 4 months (men and women combined) (P < 0.01).

Endocrine regulators

Serum calcium was higher in men than women at baseline and remained higher at all time points (P < 0.001). Gender differences in the response to training were not evident; however, a post hoc analysis of a significant time effect revealed that serum calcium decreased from 0 to 2 months (P < 0.001) and returned to baseline during the 2- to 4-month period (P < 0.001; Fig. 2A). The change in serum calcium was negatively associated with changes in all markers of bone turnover from 0 to 2 months and with PINP and CTx from 2 to 4 months (Table 5).

Change in markers of serum calcium (A) (mg·dL−1), PTH (B) (pg·mL−1), and 25(OH)D (C) (ng·mL−1) in men and women over a 4-month training period (mean ± SE). Post hoc analysis of a main time effect (P < 0.001) denotes * significant change from baseline and # significant change from 2 to 4 months (men and women combined) (P < 0.05). ** Significant change in men only from baseline (P < 0.05).

PTH values did not differ between genders. There was a main effect of time (P < 0.001); PTH decreased in both men and women from 0 to 2 months (P < 0.001) and returned to baseline from 2 to 4 months (P = 0.05; Fig. 2B). PTH values were within the normal range of 12.0-72.0 pg·mL−1 at all time points. The change in PTH was positively related to the change in BAP and CTx from 0 to 2 months and with BAP only from 2 to 4 months (Table 5).

Vitamin D status, as determined by serum 25(OH)D, was not significantly different between men and women. Analysis of a significant interaction (P = 0.001) between genders revealed a decrease in 25(OH)D from 0 to 4 months in men (P = 0.007), whereas values remained at baseline levels in women (Fig. 2C). The change in 25(OH)D was negatively associated with the change in PINP from 0 to 2 months and in BAP, PINP, and TRAP5b from 2 to 4 months (Table 5).

Given the potential for seasonal variations in recruitment to affect vitamin D status, a separate combined gender analysis was run to compare the three training groups (training groups 1 and 3 trained from winter to spring, and training group 2 trained from spring to winter; see Table 1). A significant interaction between training groups (P < 0.001) revealed that group 3 exhibited persistently lower values during training than groups 1 and 2 (P < 0.001). A decrease in training group 1 was noted over time, whereas training groups 2 and 3 increased over time (Table 4). These differences were not attributable to the time of year training took place, as groups 1 and 3 trained from winter to spring, but had different characteristics both at baseline and over time.

Changes in 25(OH)D over time for the three recruitment groups (mean ± SD).

Inflammatory response

Mean IL-1B values did not change significantly over time and did not differ significantly between genders. Men and women with low normal (3.2-10.0 pg·mL−1, n = 189) and high normal (>10.0 pg·mL−1, n = 5; normal range = 3.2-52 pg·mL−1) values at baseline responded differently over time (significant interaction, P < 0.001). The high normal group experienced a decrease of 29.6% from 0 to 2 months and of 37.7% from 2 to 4 months, whereas the low normal group did not change (Fig. 3A). Further correlation analysis in the high normal group revealed a strong positive correlation between the change in IL-1B and the change in TRAP5b from 0 to 4 months (0.922, P = 0.009).

Change in IL-1B (A) (pg·mL−1), IL-6 (B) (pg·mL−1), and TNF-α (C) (pg·mL−1) (men and women combined) in individuals presenting with low, medium (IL-6), or high values at baseline (mean ± SD). * Significant change from baseline (P < 0.05).

Similar to IL-1B, mean IL-6 values exhibited no differences over time or between genders, although the mean values were slightly higher in men (P = 0.07). Individuals were grouped into low normal (3.2-10.0 pg·mL−1, n = 106), midnormal (>10-200 pg·mL−1, n = 80), and high (>200 pg·mL−1, n = 8; normal range = 3.2 to 263 pg·mL−1) values at baseline. As revealed by analysis of a significant interaction between groups (P = 0.02), individuals with low and midnormal values at baseline did not change significantly over time, whereas the high group decreased by 6% over the first 2 months of the study (P = 0.03) and remained at this level (Fig. 3B). The change in the high group was not significantly correlated with a change in any of the bone turnover markers.

TNF-α values did not differ between men and women nor did the time course differ between genders. Analysis of a main time effect (P = 0.001) revealed an increase in the mean from 6.45 to 6.92 pg·mL−1 (P = 0.14) over the first 2 months, which decreased to 5.86 pg·mL−1 at the 4-month point (P < 0.001). Further breakdown placed 88% in the low normal range (3.2-10 pg·mL−1, n = 171) and the remainder in the high normal range (>10.0 pg·mL−1, n = 23; normal range = 3.2 to 36 pg·mL−1). Similar to IL-1B and IL-6, individuals who were in the low normal range at baseline did not change significantly over time, whereas individuals in the high normal range decreased by 29.9% from 0 to 4 months (Fig. 3C). This change was not significantly correlated with a change in any of the bone turnover markers.

Correlation and regression analyses of baseline data

Baseline values of each bone turnover marker, all of which were greater for men than women (Fig. 1), were significantly and positively correlated with height, lean mass, and V˙O2max and negatively correlated with fat mass and percent body fat (Table 6). As well, an association was observed between serum calcium and bone turnover markers and 25(OH)D and bone resorption, although these results were inconsistent. With the exception of a small but significant negative correlation between IL-6 and CTx (−0.140, P = 0.025), inflammatory markers were not correlated with markers of bone turnover at baseline.

Results from a regression analysis, after adjusting for gender in the model, revealed that V˙O2max (P = 0.008) and serum calcium (P = 0.03) were positive predictors of baseline BAP level (R2 = 0.317). Lean mass positively (P < 0.001) predicted CTx levels, whereas fat mass (P < 0.001) and 25(OH)D (P = 0.004) were inversely predictive (R2 = 0.368). V˙O2max (P = 0.04) was a positive predictor, and lean mass was a negative predictor (P = 0.03) of TRAP5b level (R2 = 0.194). When conducting regression models for each gender independently, fat mass (P < 0.001), V˙O2max (P = 0.005), and height (P = 0.05) positively predicted the bone formation marker BAP in women, whereas lean mass was a negative predictor (P = 0.001; R2 = 0.133). Fat mass (P < 0.001) and 25(OH)D (P = 0.04) inversely predicted CTx, whereas lean mass (P < 0.001) was a positive predictor (R2 = 0.173). Conversely, lean mass inversely predicted TRAP5b (P = 0.04; R2 = 0.020). In men, the only significant predictor of any bone turnover marker was fat mass, which was inversely predictive of TRAP5b (R2 = 0.181, P = 0.001).


The primary goal of this study was to investigate gender disparities in markers of bone metabolism in response to a 4-month gender-integrated military training regimen. We observed that markers of bone turnover were significantly greater in men than women throughout the study, although the response to training was similar between genders. This was reflected by an increase in markers of bone formation and resorption during the first 2 months, suggesting that bone turnover was accelerated in the initial phase of training in both men and women. There were no gender differences in the training response for markers of serum calcium or PTH, although a decrease in 25(OH)D was observed over the training period in men. The cytokine response did not differ between genders.

Bone turnover response

Although few studies have compared the bone turnover response with identical training regimens in men and women, gender differences in bone cell activity may influence the adaptive response of bone to training and risk for injury (18). We hypothesized that a high-volume repetitive load training program typically resulting in a high number of stress fracture injuries in women may result in changes in bone turnover favoring bone resorption and that the response would be greater in women than men. Contrary to our hypothesis, we observed a similar increase in markers of both formation and resorption in men and women undergoing an identical exercise regimen incorporating a high volume of strengthening and endurance activities.

The mechanical load placed on bone during resistance-type exercise places a high-tension load on the bone at the muscle-bone interface, which may stimulate the bone formation through periosteal apposition and the modeling process. This concept is supported by resistance training studies, which have been found to increase serum markers of bone formation in young men and women (13,30,36) similar to those observed in our study. In contrast, however, these resistance training studies observed a concomitant suppression of markers of bone resorption (13,30,36), whereas we observed a significant rise in markers of bone resorption. Resistance-type training combined with high impact loading may additionally stimulate bone resorption through accelerated remodeling. Similar to our study, anaerobic sprint training, which trains muscles using both resistance and impact loading, increased markers of both bone formation and resorption over a 2-month period (42).

Our results are also supported in part by a gender-integrated recruit training study conducted by Sheehan et al. (32), where DPD, an index of bone resorption, increased in both men and women and corresponded to an increase in miles of weight bearing exercise performed during training. Bone formation markers were not assessed, however, which does not allow us to draw conclusions as to whether this response favored bone resorption. In contrast to our findings, bone formation and resorption markers were observed to decrease over a 10-wk period in British recruits (11), implying a fall in bone turnover. Similar results occurred after a high-endurance run training program in young men, which evidenced a significant decline in markers of bone formation and resorption at 4 and 8 wk (42). Further, single bouts of exhaustive running exercise have been observed to induce a temporary inhibition of bone formation and a stimulation of bone resorption in both men and women (4). The equivocal findings between our study results and others may be related to differences in training type, volume, and length of training regimens. The gender-integrated training program in our study was 16 wk and incorporated a large volume of prolonged standing activities and marching under load rather, whereas other studies of 8-10 wk focused additionally on run training. Our study suggests that a longer training program incorporating a gradual ramp-up to a variety of resistance, anaerobic loading and aerobic endurance activities may prevent conditions favoring bone resorption during military training regimens.

Significant gender disparities were observed in baseline bone turnover values in our study. Bone formation markers were 80-85% greater in men than women whereas bone resorption markers were 36% to 47% higher. Higher values of bone markers in males have been hypothesized to occur due to larger bone mass (15), greater body size, and more muscle mass, although there are more studies speculating rather than providing evidence for these differences. We observed significant correlations between bone turnover markers and height, lean mass, fat mass, and percent body fat, which inherently vary between genders (Table 5). When including both men and women in our regression analysis model and after adjusting for anthropometric factors that differ between the sexes by including them in the model, our analyses revealed that V˙O2max, a measure of aerobic fitness, was a positive and an independent predictor of bone formation (BAP) and resorption (TRAP5b) activity in men and women (Table 6).

Correlations (r) between changes in markers of bone turnover and endocrine and inflammatory markers in men and women over a 4-month period of recruit training.
Correlations (r) between markers of bone turnover, anthropometric and fitness measures, and serum calcium and 25(OH)D in men and women at baseline.

Aerobic fitness is known to be protective for bone overuse injuries (31); thus, there exists the potential for bone turnover markers to reflect bone adaptation status resulting from higher activity levels that lead to improved aerobic fitness. Our results, which showed an increase in both V˙O2max and markers of bone turnover over a 4-month period of training, support this possibility. Previous research supports a relationship between aerobic fitness levels and bone turnover. Higher bone turnover values have been observed in athletes compared with controls (19). Further, these athletes' bone formation markers decreased after 2 wk of reduced physical activity and increased again after only 10 d with a return to activity (20), indicating a sensitivity of bone turnover markers to changes in activity levels within short periods, even in trained athletes. Thus, although baseline bone turnover values may be related to gender-inherent factors, changes related to fitness may be exclusive of gender and may be of value in predicting the state of bone adaptation to previous activity. Further study to determine the value of bone turnover markers in predicting bone adaptations that may protect against stress fracture is warranted.

Endocrine response

An interesting finding in our study was that women presented with significantly lower values of serum calcium, although serum PTH and 25(OH)D values between men and women were equivalent. A study conducted in southern Italy also found that men had significantly higher serum calcium levels than women throughout the year; however, in contrast to our results, the higher calcium levels in men were accompanied by higher levels of 25(OH)D and lower PTH (6). Marginal vitamin D deficiency prevalence in women participating in the previously referenced study may have contributed to their higher PTH values (5), whereas values for both men and women in our study were within the normal reference range (10-50 ng·mL−1). Interestingly, although 25(OH)D values did not differ between men and women at baseline in our study, there was a significant decline in 25(OH)D noted in men over the training period, which resulted in lower values at the 4-month point.

We observed that serum calcium was a positive predictor of baseline BAP level, independent of gender, and was lower in women, which may explain in part the lower bone formation markers in our female volunteers. In support of this relationship, we observed weak but significant correlations between changes in serum calcium (negative), PTH (positive), and 25(OH)D (negative) and changes in markers of bone turnover from 0 to 2 months and from 2 to 4 months. A decrease in 25(OH)D, which could represent a conversion of 25(OH)D to the more active 1,25(OH)D stimulated by PTH, was weakly associated with increased bone turnover in our study. Scharla et al. (29) hypothesized that moderately low serum levels of 25(OH)D can lead to osteopenia via increased bone resorption, and higher levels of PTH have been associated with stress fracture (40). Thus, although the mean levels of serum calcium, PTH, and 25(OH)D remained within normal ranges for both men and women during training, our results suggest that subtle changes within the normal range of values were related to changes in markers of bone turnover. In a recent study, vitamin D and calcium supplementation resulted in a 26% decrease in stress fracture incidence in women undergoing a 9-wk recruit training program (23). Although these results are promising, the effect of supplementation on bone metabolism in young men and women is still unclear and greatly understudied. Definitive data supporting or refuting the use of supplements to optimize bone metabolism in young men and women undergoing strenuous training are needed.

To address the fact that two thirds of our volunteers trained from winter to summer whereas one third trained from spring to summer, we conducted an independent analysis to determine whether groups training in the winter presented with different 25(OH)D levels and responses than those who entered in the spring. We found that the two recruitment groups entering in the winter presented with significantly different baseline values (34.3 ± 7.3 and 22.9 ± 7.7) and, interestingly, the group with the higher baseline experienced an increase in 25(OH)D levels whereas the group with the lower baseline experienced a decrease (Table 4). These findings suggest an influence on 25(OH)D other than seasonal variations. Although not analyzed in this article, the differences in our training groups might be explained by dietary vitamin D intake, supplement use, and sun exposure over the previous 6 months (5).

Cytokine response

The cytokine response has been related to intensity and duration of physical activity (33,35). The training regimen undertaken by our volunteers was quite moderate to rigorous, depending on individual fitness; however, we did not observe an increase in inflammatory cytokines IL-1B, IL-6, or TNF-α. In fact, in individuals who presented with high normal levels at baseline, we noted a significant decrease from 0 to 4 months, which was strongly correlated with a decrease in TRAP5b (r = 0.922). We are not aware of other studies that have observed this relationship, which warrants further study in a larger population.

Sleep loss, a frequent occurrence during military training, has been associated with elevations in inflammatory cytokines (41). Sustained suppression of IL-6 has also been noted after a brief 2-h nap (41). Our volunteers were required to rest and sleep a minimum of 7 h the night before testing, which may have contributed to our low IL-6 levels. Sleep habits were not monitored during this study, so it is not known whether sleep deprivation was a significant factor for our volunteers.

Study limitations

A major limitation to our study is the lack of hormonal data providing further insight into gender differences in bone metabolism. When adding explanatory factors, such as body size, that would adjust for inherent differences between men and women, gender still factored into the model, indicating that other factors related to gender, such as inherent differences in the hormonal milieu between men and women, may play a key role in bone metabolism. This supposition is supported in an animal model, where levels of PICP, a marker of bone formation, were observed to become higher in fillies than colts only during the springtime, possibly reflecting an influence of sex hormones on collagen turnover (18). Additionally, hormonal influences of growth at bone surfaces results are gender dependent. In rats, gonadectomy reduced sex differences in bone growth by halving periosteal bone formation in males and doubling it in females (22). In young men, IGF-I levels were associated with trabecular number and density (21). Thus, the potential role of sex and metabolic hormones influencing bone metabolism should not be ignored.

Additionally, although our study presented identical food choices to both men and women and although both men and women exhibited increased lean mass and decreased fat mass over the study period, we did not analyze the relationship between differences in food intake that might have contributed to differences in energy deficit between genders. It is possible that energy deficit during strenuous training in women may contribute to changes in bone metabolism favoring resorption (17,43).


A strenuous 4-month period of military recruit training resulted in similar increases in serum markers of bone formation and resorption in both men and women. These changes were evident during the first 2 months of training, suggesting that the initial response to rapid onset of moderate to strenuous exercise is acceleration of bone turnover that does not differ between genders. Studies involving more frequent sampling methods may provide insight into the time course of changes in markers of bone metabolism in response to exercise in men and women are recommended. Further, bone formation markers at baseline were related to aerobic fitness (V˙O2max) and serum calcium independent of gender, suggesting additional studies to assess the possible benefits of exercise and dietary interventions to optimize bone health before recruit training.

We would like to acknowledge the expert laboratory assistance of Jeffrey Staab, USARIEM, and the staff at Pennington Research Laboratories, Baton Rouge, LA. We also thank the staff at the Heller Institute for their research support.

The opinions and assertions in this article are those of the authors and do not necessarily represent official interpretation, policy, or views of the US Department of Defense or the Israeli Defense Forces.


1. Angeli A, Minetto M, Dovio A, Paccotti P. The overtraining syndrome in athletes: a stress-related disorder. J Endocrinol Invest. 2004;27:603-12.
2. Barry DW, Kohrt WM. Acute effects of 2 hours of moderate-intensity cycling on serum parathyroid hormone and calcium. Calcif Tissue Int. 2007;80:359-65.
3. Bell NH, Godsen RN, Henry DP, Shary J, Epstein S. The effects of muscle-building exercise on vitamin D and mineral metabolism. J Bone Miner Res. 1988;3:369-73.
4. Brahm H, Piehl-Aulin K, Ljunghall S. Biochemical markers of bone metabolism during distance running in healthy, regularly exercising men and women. Scand J Med Sci Sports. 1996;6:26-30.
5. Burgaz A, Akesson A, Oster A, Michaelsson K, Wolk A. Associations of diet, supplement use, and ultraviolet B radiation exposure with vitamin D status in Swedish women during winter. Am J Clin Nutr. 2007;86:1399-404.
6. Carnevale V, Modoni S, Pileri M, et al. Longitudinal evaluation of vitamin D status in healthy subjects from southern Italy: seasonal and gender differences. Osteoporos Int. 2001;12:1026-30.
7. Cauley JA, Danielson ME, Boudreau RM, et al. Inflammatory markers and incident fracture risk in older men and women: the Health Aging and Body Composition Study. J Bone Miner Res. 2007;22:1088-95.
8. Dall R, Lange KH, Kjaer M, et al. No evidence of insulin-like growth factor-binding protein 3 proteolysis during a maximal exercise test in elite athletes. J Clin Endocrinol Metab. 2001:86:669-74.
9. Dhamrait SS, James L, Brull DJ, et al. Cortical bone resorption during exercise is interleukin-6 genotype-dependent. Eur J Appl Physiol. 2003:89:21-5.
10. Durnin JV, Rahaman MM. The assessment of the amount of fat in the human body from measurements of skinfold thickness. Br J Nutr. 1967:21:681-9.
11. Etherington J, Keeling J, Bramley R, Swaminathan R, McCurdie I, Spector TD. The effects of 10 weeks military training on heel ultrasound and bone turnover. Calcif Tissue Int. 1999;64:389-93.
12. Fares JE, Choucair M, Nabulsi M, Salamoun M, Shahine CH, Fuleihan Gel H. Effect of gender, puberty, and vitamin D status on biochemical markers of bone remodeling. Bone. 2003;33:242-7.
13. Fujimura R, Ashizawa N, Watanabe M, et al. Effect of resistance exercise training on bone formation and resorption in young male subjects assessed by biomarkers of bone metabolism. J Bone Miner Res. 1997;12:656-62.
14. Gibson JH, Mitchell A, Harries MG, Reeve J. Nutritional and exercise-related determinants of bone density in elite female runners. Osteoporos Int. 2004;15:611-8.
15. Henry YM, Eastell R. Ethnic and gender differences in bone mineral density and bone turnover in young adults: effect of bone size. Osteoporos Int. 2000;11:512-7.
16. Hetland ML, Haarbo J, Christiansen C. Low bone mass and high bone turnover in male long distance runners. J Clin Endocrinol Metab. 1993;77:770-5.
17. Ihle R, Loucks AB. Dose-response relationships between energy availability and bone turnover in young exercising women. J Bone Miner Res. 2004;19:1231-40.
18. Jackson BF, Lonnell C, Verheyen K, Wood JL, Pfeiffert DU, Price JS. Gender differences in bone turnover in 2-year-old Thoroughbreds. Equine Vet J. 2003;35:702-6.
19. Karlsson KM, Karlsson C, Ahlborg HG, Valdimarsson O, Ljunghall S. The duration of exercise as a regulator of bone turnover. Calcif Tissue Int. 2003;73:350-5.
20. Karlsson KM, Karlsson C, Ahlborg HG, Valdimarsson O, Ljunghall S, Obrant KJ. Bone turnover responses to changed physical activity. Calcif Tissue Int. 2003;72:675-80.
21. Khosla S, Melton LJ 3rd, Achenbach SJ, Oberg AL, Riggs BL. Hormonal and biochemical determinants of trabecular microstructure at the ultradistal radius in women and men. J Clin Endocrinol Metab. 2006;91:885-91.
22. Kim BT, Mosekilde L, Duan Y, et al. The structural and hormonal basis of sex differences in peak appendicular bone strength in rats. J Bone Miner Res. 2003;18:150-5.
23. Lappe J, Cullen D, Thompson K, Ahlf R. Calcium and vitamin D supplementation decreases incidence of stress fractures in female Navy recruits. J Bone Miner Res. 2008;23:741-9.
24. Lee CH, Huang GS, Chao KH, Jean JL, Wu SS. Surgical treatment of displaced stress fractures of the femoral neck in military recruits: a report of 42 cases. Arch Orthop Trauma Surg. 2003;123:527-33.
25. Lorentzon M, Mellstrom D, Ohlsson C. Association of amount of physical activity with cortical bone size and trabecular volumetric BMD in young adult men: the GOOD study. J Bone Miner Res. 2005;20:1936-43.
26. Nikander R, Sievanen H, Heinonen A, Kannus P. Femoral neck structure in adult female athletes subjected to different loading modalities. J Bone Miner Res. 2005;20:520-8.
27. Pester S, Smith PC. Stress fractures in the lower extremities of soldiers in basic training. Orthop Rev. 1992;21:297-303.
28. Sahin G, Ozturk C, Bagis S, Cimen OB, Erdogan C. Correlation of serum cytokine levels with axial bone mineral density. Singapore Med J. 2002;43:576-8.
29. Scharla SH, Scheidt-Nave C, Leidig G, et al. Lower serum 25-hydroxyvitamin D is associated with increased bone resorption markers and lower bone density at the proximal femur in normal females: a population-based study. Exp Clin Endocrinol Diabetes. 1996;104:289-92.
30. Schroeder ET, Hawkins SA, Jaque SV. Musculoskeletal adaptations to 16 weeks of eccentric progressive resistance training in young women. J Strength Cond Res. 2004;18:227-35.
31. Shaffer RA, Rauh MJ, Brodine SK, Trone DW, Macera CA. Predictors of stress fracture susceptibility in young female recruits. Am J Sports Med. 2006;34:108-15.
32. Sheehan KM, Murphy MM, Reynolds K, Creedon JF, White J, Kazel M. The response of a bone resorption marker to marine recruit training. Mil Med. 2003;168:797-801.
33. Shephard RJ. Cytokine responses to physical activity, with particular reference to IL-6: sources, actions, and clinical implications. Crit Rev Immunol. 2002;22:165-82.
34. Snyder RA, Koester MC, Dunn WR. Epidemiology of stress fractures. Clin Sports Med. 2006;25:37-52, viii.
35. Suzuki K, Nakaji S, Yamada M, et al. Impact of a competitive marathon race on systemic cytokine and neutrophil responses. Med Sci Sports Exerc. 2003;35(2):348-55.
36. Tajima O, Ashizawa N, Ishii T, et al. Interaction of the effects between vitamin D receptor polymorphism and exercise training on bone metabolism. J Appl Physiol. 2000;88:1271-6.
37. Thorsen K, Kristoffersson A, Hultdin J, Lorentzon R. Effects of moderate endurance exercise on calcium, parathyroid hormone, and markers of bone metabolism in young women. Calcif Tissue Int. 1997;60:16-20.
38. Trebec DP, Chandra D, Gramoun A, Li K, Heersche JN, Manolson MF. Increased expression of activating factors in large osteoclasts could explain their excessive activity in osteolytic diseases. J Cell Biochem. 2007;101:205-20.
39. Uthgenannt BA, Kramer MH, Hwu JA, Wopenka B, Silva MJ. Skeletal self-repair: stress fracture healing by rapid formation and densification of woven bone. J Bone Miner Res. 2007;22:1548-56.
40. Valimaki VV, Alfthan H, Lehmuskallio E, et al. Risk factors for clinical stress fractures in male military recruits: a prospective cohort study. Bone. 2005;37:267-73.
41. Vgontzas AN, Pejovic S, Zoumakis E, et al. Daytime napping after a night of sleep loss decreases sleepiness, improves performance, and causes beneficial changes in cortisol and interleukin-6 secretion. Am J Physiol Endocrinol Metab. 2007;292:E253-61.
42. Woitge HW, Friedmann B, Suttner S, et al. Changes in bone turnover induced by aerobic and anaerobic exercise in young males. J Bone Miner Res. 1998;13:1797-804.
43. Zanker CL, Swaine IL. Responses of bone turnover markers to repeated endurance running in humans under conditions of energy balance or energy restriction. Eur J Appl Physiol. 2000;83:434-40.


©2008The American College of Sports Medicine