Morphology and Hydrodynamic Resistance in Young Swimmers

Pediatric Exercise Science, 2001, 13, 246-255 O 2001 Human Kinetics Publishers. Inc. Morphology and Hydrodynamic Resistance in Young Swimmers Nataphoom Benjanuvatra, Brian A. Blanksby, and Bruce C. Elliott Six 9-, 11-, and 13-year-old, anthropometrically matched males and females were towed on the water surface via a mechanical winch at 1.3 to 2.5 ms-i in increments of 0.3 ms-i during a prone streamlined glide. Passive drag force of the 13-year age group was significantly larger than that of the 9-year age group at 1.9,2.2, and 2.5 ms-i, but not at 1.3-1.6 ms-i. While anthropometry did not feature in any regression equation at any age for passive drag at velocities of 1.3 and 1.6 ms-i, body mass was the best predictor of drag at 1.9 and 2.5 ms-i. Optimization of swimming speed involves the interaction of propulsive and resistive forces. Understanding the relationship between human morphology and hydrodynamic resistances enables coaches to modify swimming stroke mechanics to improve performance. Total hydrodynamic resistance consists of frictional, form, and wave-making drag. Frictional drag results from skin friction and has been shown to have little influence on human hydrodynamics (7, 20). Form drag is created by a swimmer's dimensions, whereas wave-making drag occurs primarily at the water surface (11) and is the most deleterious form of resistance (24). Total drag can be quantified with the body in a fixed position (passive drag) or while in motion (active drag) such as during front crawl swimming (24). Passive drag tests have produced reliable results by towing a swimmer in a prone streamline position (3, 4, 7, 10, 13, 15, 16, 17). Active drag tests have yielded inconsistent results. Indirect methods of estimating active drag by calculating changes in oxygen consumption at various drag loads while swimming indicated that active drag was larger than passive drag (5, 6,7, 9). The Measure of Active Drag (MAD) system was the first to directly measure active drag. This method showed that active drag during front crawl swimming was significantly lower, and closer to previously reported passive drag values (12, 13). Kolmogorov and Duplishcheva (16) calculated active drag as a function of power output and found active drag values for freestyle, backstroke, and butterfly were significantly lower than for passive drag. They attributed this to the out-of-the-water recovery in all strokes other than breaststroke. Studies of passive and active drag and body anthropometry have produced varying results (5,6,7,14,29). General body form, but not body surface area, has been shown to influence passive drag (3,4,5,6,7,20,29). Others have found the link between morphology and active drag to yield contrasting results (7, 14, 16, The authors are with the Department of Human Movement & Exercise Science at The University of Western Australia, Nedlands WA 6907, Australia. 246

Morphology and Hydrodynamic Resistance - 247 17), and Huijing et al. (14) found significant correlations between anthropometry and active drag, particularly maximal body cross-sectional area. More recent studies have found that swimming mechanics have a greater influence on active drag than body morphology (16,17). As children become adolescents, they experience physiological, morphological, and body composition changes. Toussaint et al. (27) examined the effects of growth on active drag in swimmers via the MAD system while swimming at 1.25 ms-' over a 2.5-year period. Despite an 11% increase in height, 37% increase in mass, and 16% increase in the body cross-sectional area, no differences were found in active drag at the above velocity. They suggested that the lack of change in active drag was due to increased height reducing the wave drag component in accordance with Froude number theory (18). That is, reduced wave-making resistance offset any increased form and frictional drag (27). However, swimming technique also can affect active drag (8, 16, 17), and changes in stroke mechanics, skill, and streamlining ability could have contributed to the lack of change in total drag after 2.5 years of training and growth (27). Kolmogorov et al. (17) found no difference in the active drag profile for all strokes between male and female swimmers at the same velocity. However, while pre-adolescent male and female athletes have similar anthropometry, post-adolescent males and females differ in height, mass, skinfold sum, waist, and chest girths (1). As body configuration can affect active and passive drag (3,4,7, 14, 15), the relationship between drag and size differences for young males and females requires further investigation. Passive drag has contributed significantly in predicting swimming performance (3,4), as the gliding phase of the start and turns approximate 10-25% of the total event depending on the stroke and race distance (3). While the relationship between active and passive drag is equivocal, passive drag is evidently more closely related to human morphology. This study examined differences in the anthropometric variables and passive drag of 9-, 11-, and 13-year-old children to ascertain whether any changes occurred as a result of growth. Subjects Methods Six male and six female swimmers from each of the 9-, 1 I-, and 13-year age groups participated in the study. Height and mass measures were within f 1.0 standard deviation of the anthropometric means of Western Australian children (1). All participants were from the Uniswim program in the Department of Human Movement & Exercise Science at The University of Western Australia. Following Human Rights clearance, the test protocol was explained, and parentlswirnmer con- - - s e n t & n n w e r e c o r n p l e t e d ~ e n 3 h e t e s ~ - pometric measures were taken with participants wearing bathers. The passive drag forces at velocities of 1.3 to 2.5 m-' were measured in random order. Anthropometry Anthropometry measures followed established procedures (2), and maximum body cross-sectional area and body surface area were calculated via the mathematical formulae (7):

248 - Benjanuvatra, Blanksby, and Elliott Body surface area = 0.0112 mass + 0.0051 height - 0.0718 (1) Body cross-sectional area = 6.9256 mass + 3.5043 height - 377.156 (2) In addition, the ponderal index (height/3dfige), length-thickness ratio (height2/ body cross-sectional area m2/x]), and length surface ratio (height2/body surface area m2/bsa]) were calculated to represent the wave making, form, and frictional drag, respectively (7,20). Force Measurement A towing system described by Lyttle et al. (22) was used to determine the drag force (Figure 1). The subjects were towed on the water surface at five velocities between 1.3 and 2.5 ms-l, in 0.3 ms-i increments, in a prone streamlined position with both arms extended over the head, feet together, and plantar flexed. For each participant, only one successful trial was recorded from each towing condition and velocity in the desired body position. The participants wore a pair of standard racing bathers, rubber cap, and goggles during the testing sessions. Velocities were randomized to prevent an order effect. To prevent variation in the coefficient of drag, conditions were maintained at a constant water temperature (7). The AP30 computer program (23) was used to collect and analyze the force data. Inter-day and intra-day reliability tests indicated that the towing and force measurement system consistently calculated the drag force experienced by swimmers (22). A Panasonic SVSH video camera in an underwater housing was positioned perpendicular to the swimmer's line of motion. The video camera was attached to a Panasonic VCR player to relay the images to a television set for observation. Thus, each subject's body position was monitored throughout each trial, and feedback ensured that the desired body position was achieved and maintained. FM Transminer VDO recmder and monitor / \ Swimmer Load Cell & Pool Amplifiers Figure 1 - Schema of the experimental set up.

Morphology and Hydrodynamic Resistance - 249 Analysis To counteract low subject numbers, a significance level of 0.01 was established for all analyses. The Multivariate analysis of variance (MANOVA) was used to ascertain any interaction between gender and age group effects in the anthropometric measures. The two-way repeated measure analysis of variance (ANOVA) was used to find any interactions between velocity and age group. Pearson product moment correlation and stepwise multiple regression statistical procedures were used to examine any relationships between passive drag and anthropometric variables. Anthropometry Results The MANOVA with all the anthropometric variables and indices as dependent variables revealed no significant interaction between age group and gender, but the age group effect was significant (F = 11 377, p <.0 1). Pooled summaries of the selected anthropometric variables for each age group and gender, together with Scheffe post-hoc comparisons, are listed in Table 1. Force Analysis A two-way repeated measures ANOVA was conducted to examine the differences and interactions in the passive drag between the towing velocities and age groups. Significan' interactions were recorded between age groups and velocity (F = 3.115, p <.01: The means and standard deviations of the passive drag at each velocity, along with the post hoc analysis, are in Table 2. Passive Drag and Anthropometric Variables A bivariate Pearson product moment correlation table was constructed to display any shared variance between passive drag force at each velocity and anthropometry (Table 3) and between passive drag and anthropometric indices (Table 4). No significant correlations were recorded between the anthropometric variables and the passive drag at 1.3 and 1.6 ms-l. However, as velocity increased to 1.9, 2.2, and 2.5 ms-i, all variables other than skinfolds were significantly and positively correlated to passive drag. Only the H2/X variable of the anthropometric indices correlated significantly with the passive drag at 1.9,2.2 and 2.5 ms-i (Table 4). Stepwise multiple regression equations with all of the anthropometric measures and indices included were developed to determine which variables best predicted passive drag at each velocity (Table 5). Because there were no significant -- -amelations between-theansanthropometricc_v_ariables and passive drag-at 1.3 and 1.6 ms-i, no regression equations could be computed. However, body mass was the only predictor of passive drag at 1.9,2.2 and 2.5 ms-l. A post hoc power analysis of the passive drag data indicated that sample size of 12 subjects per group was enough to ensure confidence in the interpretation of statistics (power = 0.8392).

Table 1 Combined Means, SD, and Range of the Anthropometry Variables of the Swimmers in the 9-, 11-, and W-year Age m 2. Groups Along With the Scheff6 Post Hoe Analysis 2 c Age groups E 9 years (n = 12 11 years (n = 12 13 years (n = 12) 2 X 0) r Mean f SD Range Mean f SD Range Mean f SD Range A 5 Anthropometric measures Height (cm) Mass (kg) Chest girth (cm) Cross sectional area (cm2) Body surface area (m2) Skinfold (mm) Anthropometric indices The ponderal index H2/BSA H2/X #Significant difference between 9- and 1 1-year age groups at.o1 level. * Significant difference between 9- and 13-year age groups at.o1 level. + Significant difference between 11- and 13-year age groups at.o1 level.

Morphology and Hydrodynamic Resistance - 251 Table 2 Means, Standard Deviations, and Ranges of Passive Drag Measured During Towing in the Streamlined Glide for the 9-, 11-, and 13-year Age Groups Age group results (N) 9 years 11 years 13 years n= 12 n= 12 n=12 Passive drag force at (ms-i) Mean f SD Range Mean f SD Range Mean f SD Range A Note: Scheff6 post hoc comparisons are reported in the right column. #Significant difference between 9- and 11-yr age groups at 0.01 level. * Significant difference between 9- and 13-yr age groups at 0.01 level. + Sigmficant difference between 11- and 13-yr age groups at 0.01 level. Table 3 Pearson Product Moment Coefficient Correlations Between the Net Forces at Different Velocities and the Anthropometric Variables (N = 36) Passive drag force at (N) 1.3 ms-i 1.6 ms-i 1.9 ms-' 2.2 ms-i 2.5 ms-i Height.207.246.549*.620*.568* Mass.210.304.615*.701*.653* Chest girth.213.215.535*.613*.575* Cross-sectional area.216.289.608*.690*.639* Body surface area.216.290.609*.692*.640* Skinfold -.I91 -.240.025.I10.I48 *Correlation is significant at the.o1 level. Table 4 Pearson Product Moment Coefficient Correlations Between Passive Drag at Different Velocities and the Anthropometric Indices (N = 36) Passive drag force at (N) 1.3 ms-i 1.6 ms-i 1.9 ms-i 2.2 ms-i 2.5 ms-i - - Ponderal index -.016 -.084 -.068 -.086 -.lo0 H2/B S A.049 -.012.081.081.057 HZ/X -.248 -.308 -.593* -.674* -.637* *Correlation is significant at the.o1 level

252 - Benjanuvatra, Blanksby, and Elliott Table 5 Results of the Stepwise Multiple Regression for Prediction of the Passive Drag of the Various Velocities (N = 36) Velocity Predicting Coefficient Adjusted (ms-') variables (PI t F R2 R2 1.3-1.6-1.9 Constant Mass 2.2 Constant Mass 2.5 Constant Mass Note: At 1.3 and 1.6 ms-', the regression equation cannot be computed as no significant correlation between the anthropometric variables were found. *F ratio and t value are significant at p <.O1 level. Discussion Age Differences in Net Forces for the Streamlined Glide Condition This cross-sectional study examined whether passive drag force was associated with anthropometric differences, with respect to age. The net force recorded during towing at various velocities comprised solely of a passive resistive force that varied across the age groups. Drag values were similar at the lower velocities of 1.3 and 1.6 ms-i for all three groups. At 1.3 and 1.6 ms-', this study agreed with Toussaint et al. (27) that increased growth did not influence drag. However, at velocities of 1.9, 2.2 and 2.5 ms-i, the 9-year-olds recorded significantly lower drag than the 13-year age group. The mean for the 11-year age group fell between the 9- and 13-year age groups, but the differences in means were not statistically significant. This disagreed with Toussaint et al. (27) who reported no change in active drag of children swimming front crawl at 1.25 ms-i over a 2.5-year growth period. They considered that the increased height decreased the Froude number, reduced wave-making drag, and compensated for any increased frictional and form drag created by larger body surface and cross-sectional areas (27). If this was consistent across the three age groups, similar levels of passive drag also could have been expected. This was so at the lower velocities of 1.3 and 1.6 ms-i, despite large increases in mean height and mass measures (Table 1). However, the older swimmers recorded larger passive drag at higher velocities (1.9,2.2, and 2.5 ms-') than their younger counterparts. At velocities of 1.9,2.2, and 2.5 ms-' this study agreed with hydrodynamic studies showing that passive drag was influenced by body morphology (3,4,5,6, 15). Height, mass, chest girth, cross-sectional area, and body surface area were progressively larger as age increased, but skinfolds were similar across all age oups

Morphology and Hydrodynamic Resistance - 253 The differences in the passive drag between the 9- and 13-year groups at the higher velocities can be explained by increases in body dimensions. However, it is unclear as to why there were no significant differences at the lower velocities of 1.3 and 1.6 ms-'. Perhaps drag components are also a function of velocity (15,25, 26). Frictional drag increases linearly with velocity, form drag increases with the square of the velocity, and wave drag varies with the cube of velocity (24). Hence, 1.3 and 1.6 ms-' might be too slow for body morphology to influence passive drag and could explain the low correlations between anthropometric variables and indices and drag forces at these velocities (Tables 3 and 4). Also, this prevented the calculation of a regression equation to predict the drag force (Table 5). Relationship Between Anthropometry and Passive Drag Despite the Froude number theory implying that height is inversely related to the wave making resistance (18, 27), height was significantly and positively correlated with passive drag at the three higher velocities (Table 3). Previous studies have shown that passive drag of young male and female swimmers correlated positively with height, body mass, and body surface area, and height with mass and body surface area (4, 29). However, older swimmers who recorded greater drag forces were also larger in height and mass. Thus, the role of height could not be assessed independently. The anthropometric indices could provide a better indication of how body morphology interacts with passive drag (5). The ponderal index has been associated with the wave-making component of drag (20), and the H2/BSA and the H2/X indices are related to frictional and form drag, respectively (5). Only the H2/X index correlated significantly, but negatively, with passive drag at 1.9,2.2, and 2.5 ms-i (Table 4). Here, the influence of height becomes more apparent. Greater height per unit of body cross-sectional area corresponded to lower passive drag. This finding supports data from Clarys (5,7) and Lyttle et al. (20), in that frictional drag has little effect on the total passive drag. The irregularity in the body curvature created a turbulent flow and increased form drag but reduced frictional drag. However, in contrast to Lyttle et al. (20), this study did not find any significant correlation between the ponderal index and passive drag. The significant correlation between H2/X and passive drag at higher velocities indicates an inverse relationship between height and passive drag. However, the stepwise multiple regression revealed body mass to be the only factor included in the final models to predict passive drag at the velocities of 1.9,2.2, and 2.5 ms- ' (Table 5). Hence, increased body mass was the main factor contributing to increased passive drag at higher velocities for 9-, 11-, and 13-year-olds. This differed from Toussaint et al. (27) in that, at velocities above 1.9 ms-', body size and passive drag both increased from 9 to 13 years of age. Greater height of the older swimmers could not compensate for other anthropometric changes as Toussaint et -- al.-(27) h-a-dsugg-5st-ea;-- - - - -- -- - At velocities of 1.3 and 1.6 ms-l, there was no significant difference in the passive drag force with respect to age and body size. These lower velocities also equate with swimming performance times expected from children of these ages. That is, 1.3 ms-'equals 38.50 s for 50 m, and 1.6 ms-' represents 31.25 s for 50 m.

254 - Benjanuvatra, Blanksby, and Elliott This suggests that differences in body morphology do not provide any significant hydrodynamic disadvantage. Velocities of 1.9, 2.2, and 2.5 ms-' are greater than free swimming velocity of children and are more closely related to the gliding phases found after a wall push-off or a dive. At these velocities, larger and heavier swimmers would experience greater passive drag and decelerate faster as they glide away from the wall. Therefore, they must begin stroking earlier. Hence, the streamline position adopted during this glide phase becomes increasingly important to maximize the gliding velocity and distance achieved. In conclusion, as age increased, so too did the anthropometric variables and passive drag at velocities exceeding 1.9ms-l. Body mass was found to be the only significant factor in determining the passive drag at these velocities. The effect of increased height on passive drag requires further empirical investigation. References 1. Blanksby, B.A., J. Bloomfield, T.R. Ackland, B.C. Elliott, anda.r. Morton. Athletics, Growth, and Development in Children. Chur, Switzerland: Harwood Academic, 1994. 2. Bloomfield, J., T.R. Ackland, and B.C. Elliott. Applied Anatomy and Biomechanics and Sport. Carlton, Victoria: Blackwell Scientific, 1994. 3. Chatard, J.C., B. Bourgoin, and J.R. Lacour. Passive drag is still a good evaluator of swimming aptitude. Europ. J. Appl. Physiol. 59:399-404, 1990. 4. Chatard, J.C., J.M. Lavoie, B. Bourgoin, and J.R. Lacour. The contribution of passive as a determinant of swimming performance. Int. J. Sports Med. 11:367-372, 1990. 5. Clarys, J.P. An experimental investigation of the application of fundamental hydrodynamics to the human body. In: Swimming Medicine N, B. Eriksson and B. Furberg (Eds.). Baltimore: University Park Press, 1978, pp. 386-394. 6. Clarys, J.P. Relationship of human body form to passive and active hydrodynamic drag. In: Biomechanics VI-B, E. Asmussen and K. JGrgensen (Eds.). Baltimore: University Park Press, 1978, pp. 120-125. 7. Clarys, J.P. Human morphology and hydrodynamics. In: Swimming 111, J.P. Clarys and L. Lewillie (Eds.). Baltimore: University Park Press, 1979, pp. 3-41. 8. Clarys, J.P. Human body dimensions and applied hydrodynamics: selection criteria for top swimmers. SNIPES J. 9:32-41, 1986. 9. di Prampero, P.E., D.R. Pendergast, D.W. Wilson, and D.W. Rennie. Energetics of swimming in man. J. Appl. Physiol. 37:l-5, 1974. 10. Hay, J.G. The status of research of biomechanics of swimming. In: Swimming Science V, B. Ungerechts, K. Wilke, and K. Reischle (Eds.). Champaign, IL: Human Kinetics, 1988, pp. 3-14. 11. Hertel, H. Structure-Fom-Movement. New York: Reinhold, 1966. 12. Hollander, A.P., G. de Groot, G.J. van Ingen Schenau, H.M. Toussaint, H. de Best, W. Peeters, A. Meulemans, and A.W. Schreurs. Measurement of active drag during crawl arm stroke swimming. J. Sports Sci. 421-30, 1986. 13. Hollander, A.P., G. de Groot, and G.J.van Ingen Schenau. Active drag in female swirnmers. In: BiomechanicsX-B, B. Jonsson (Ed.). Champaign, IL: Human Kinetics, 1987, pp. 712-720. 14. Huijing, P.A., H.M. Toussaint, R. Mackay, K. Vervoorn, J.P. Clarys, G. de Groot, and A.P. Hollander. Active drag related to the body dimensions. In. Swimming Science V, B.E. Ungerechts, K. Wilke, and K. Reischle (Eds.). Champaign, JL Human Kinetics, 1987, pp. 3

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