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INTRODUCTION Osteopenia and osteoporosis are common diseases in the world. It is well known, that bone degeneration can be prevented or decreased by regular physical activity. High-impact exercise, like football has been shown to be associated with higher bone mass. Football involves running, kicking, jumping, tackling, turning, sprinting. During these movements the lower extremities are loaded with high-impact forces (Tarakçi and Oral 2009). A quantitative ultrasound measurements is relatively inexpensive, portable, non-invasive and radiation-free method of evaluating bone status. The main aim of this pilot study was to analyze the relationships between different physical activity levels, anthropometric and bone parameters in prepubertal boys. Table 1: Basic statistics of the anthropometric variables MATERIAL AND METHODS The subjects were non-athletic (n=34) and soccer player prepubertal boys (n=76), grouped also as younger (9-10yrs, n=64) and older (11-12yrs, n=46) ones. They had a 1.5 to 4 years sport related experience. Anthropometric measurements were taken by the suggestion of the IBP (Weiner and Lourie 1969), including estimated body fat percentage (Pařižková 1961) and physique was characterised by Conrad's growth type (1963). Biological age was assessed by anthropometric measurements using the method of Mészáros and Mohácsi (1983). Calcaneal quantitative ultrasound parameters were registered by a Sonost 3000 bone densitometer. The analysis included speed of sound (SOS, m/s), broadband ultrasound attenuation (BUA, dB/MHz) and the calculated bone quantity index (BQI=αSOS+βBUA, αβ: temperature corrections). Correlation patterns of anthropometric variables and bone characteristics for total sample and for subgroups were analyzed. Differences between athletic and non-athletic boys were tested by Student t-test; and if the F-test of ANOVA was significant for the respective means (age and physical activity), Tukey's post-hoc test was used at the 5% level of effective random error. Morph.Age (yrs) Mean SD Mean 1.32 140.66 8.17 33.20 6.39 13.92 5.49 64.90 3.86 -1.53 0.24 Nonathletes 11.17 1.51 148.52 9.62 43.93 11.91 20.47 7.73 69.96 4.84 -1.55 0.37 Younger 9.19 1.26 7.56 32.90 8.30 14.82 6.49 64.65 4.50 -1.48 0.28 Older 11.18 1.20 149.33 7.61 41.35 9.78 17.53 7.33 68.89 Table 1. summarizes the basic stats of the anthropometric variables. There were moderate significant relationships between age, stature, plastic index and SOS, BUA, BQI for the total sample. In non-athletes every bone parameter correlated with age significantly and no significant correlation was found in athletes but for SOS (Table 2, Figure 1). Mean SD Mean SD MIX Athletes 9.55 138.3 SD PLX (cm) SD 4.11 Mean SD -1.62 0.29 Table 2: Correlation pattern of anthropometric and bone parameters (in blue italics: significant correlation coefficient) Total Sample Athletes Non-athletes Age (yrs) Height (cm) BUA 0.26 0.19 0.19 0.20 SOS 0.35 0.29 0.16 0.20 BQI 0.37 0.26 0.18 0.22 BUA 0.06 0.02 0.06 0.07 SOS 0.24 0.18 0.16 0.16 BQI 0.20 0.16 0.17 0.19 BUA 0.75 0.60 0.30 0.37 SOS 0.50 0.72 0.30 0.01 0.08 0.51 0.13 0.20 BQI dB/MHz Weight PLX (cm) (kg) dB/MHz 90 85 80 75 70 65 60 55 50 90 85 80 75 70 65 60 55 50 A r = 0.29 Weight (kg) Mean RESULTS AND DISCUSSION r = 0.37 Height (cm) Fat % * Y NA O r = 0.22 Figure 2: Broadband ultrasound attenuation (BUA, dB/MHz), means and SD Age (yrs) Stature (cm) Plastic index (cm) Figure 1: Significant correlations between age, stature, plastic index and BQI in total sample In comparison of the activity-related subgroups the bone parameters i.e. BUA in dB/MHz (71.92±11.29 vs. 74.38±11.12), SOS in m/s (1493.4 ±10.78 vs. 1497.6±9.57) and BQI (60.16±11.17 vs. 63.00±10.87) did not differ. Bone variables differed significantly by age: SOS (1491.59±9.69 vs. 1499.09±10.24), BUA (70.11±10.69 vs. 76.26±11.13) and BQI (57.27±10.05 vs.66.27±10.45) (Figures 2-4). A REFERENCES NA * Y O Figure 3: Speed of sound (SOS, m/s), means and SD SUMMARY The bone variables did not significantly differ in athletes and in non-athletic prepubertal boys, similar to Cvijetić et al. (2003), in contrast to Falk et al. (2003) and Mentzel et al. (2005). It seems that quantity bone parameters depend on the chronological as well as biological age. Although the bone parameters were related with antropometric variables no difference was found at the same age even with various body size. That means that age had the strongest effect on bone parameters in prepubertal boys. The older boys had larger values, so that favourable characteristics of bone in this sample, irrespective to body size. m/s 1514 1510 1506 1502 1498 1494 1490 1486 1482 m/s 1514 1510 1506 1502 1498 1494 1490 1486 1482 80 80 75 75 70 70 65 65 60 60 55 55 50 50 A NA * Y O Figure 4: The calculated bone quantity index, means and SD Conrad, K. (1963) Der Konstitutionstypus (2. Aufl.) Springer, Berlin. Cvijetić, S., Barić, I.C., Bolanca, S., Juresa, V., Ozegović, D.D. (2003) Ultrasound bone measurement in children and adolescents. Correlation with nutrition, puberty, anthropometry, and physical activity. Journal of Clinical Epidemiology, 56(6):591-7. Falk, B., Bronsthein, Z., Constantini, N.W., Eliakim, A. (2003) Quantitative Ultrasound of the Tibia and Radius in Prepubertal and Early-Pubertal Female Athletes. Arch Pediatr Adolesc Med. 157:139-143. Mentzel, H.-J., Wünsche, K., Malich, A., Böttcher, J., Vogt, S., Kaiser, W. A., 2005, Einfluss sportlicher Aktivität von Kindern und Jugendlichen auf den Kalkaneus – Eine Untersuchung mit quantitativem Ultraschall, Pädiatrische Radiologie, 177(4): 524-52. Mészáros, J., Mohácsi, J. (1983) A biológiai fejlettség meghatározása és a felnőtt termet elõrejelzése a városi fiatalok fejlődésmenete alapján. Kandidátusi értekezés, Budapest. Pařižková, J. (1961) Total body fat and skinfold thickness in children. Metabolism; 10. pp. 794-807. Tarakçi, D. and Oral, A. (2009) How do contralateral calcaneal quantitative ultrasound measurements in male professional football (soccer) players reflect the effects of high-impact physical activity on bone? J. of Sports Medicine and Physical Fitness, 49 (1):78-84. Weiner J. E. S., Lourie. J. A. (1969) (Eds.) Human Biology. A Guide to Fields Methods. IBP Handbook, No. 9. Blackwell, Oxford.