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Key somatic variables associated with, and differences between the 4 swimming strokesThis study identified key somatic and demographic characteristics that benefit all swimmers and, at the same time, identified further characteristics that benefit only specific swimming strokes. Three hundred sixty-three competitive-level swimmers (male [n = 202]; female [n = 161]) participated in the study. We adopted a multiplicative, allometric regression model to identify the key characteristics associated with 100 m swimming speeds (controlling for age). The model was refined using backward elimination. Characteristics that benefited some but not all strokes were identified by introducing stroke-by-predictor variable interactions. The regression analysis revealed 7 "common" characteristics that benefited all swimmers suggesting that all swimmers benefit from having less body fat, broad shoulders and hips, a greater arm span (but shorter lower arms) and greater forearm girths with smaller relaxed arm girths. The 4 stroke-specific characteristics reveal that backstroke swimmers benefit from longer backs, a finding that can be likened to boats with longer hulls also travel faster through the water. Other stroke-by-predictor variable interactions (taken together) identified that butterfly swimmers are characterized by greater muscularity in the lower legs. These results highlight the importance of considering somatic and demographic characteristics of young swimmers for talent identification purposes (i.e., to ensure that swimmers realize their most appropriate strokes).
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Resting metabolic rate in obese and nonobese Chinese Singaporean boys aged 13–15 yBackground: Previous studies investigating the hypothesis that a low resting metabolic rate (RMR) is a cause of obesity yielded discrepant findings. Two explanations for these findings are the use of imprecise methods to determine obesity and a failure to control for differences in fat mass (FM) and fat-free mass (FFM) when comparing RMR values. Objective: This study tested the hypothesis that RMR is lower in obese than in nonobese boys (with the use of precise methods to quantify body fatness and with adjustment for differences in both FM and FFM). Design: Forty Chinese Singaporean boys aged 12.8–15.1 y were recruited. Boys were classified as obese (n = 20) or nonobese (n = 20) on the basis of their adiposity index (ratio of FM to FFM: >0.60 = obese, <0.40 = nonobese) determined by dualenergy X-ray absorptiometry. RMR was determined by using indirect calorimetry. RMR values were compared by using both linear (analysis of covariance) and log-linear (analysis of covariance with log-transformed data) regression to control for differences in FM and FFM. Results: Age, height, and FFM did not differ significantly between groups. Body mass was 13 kg greater and FM was 16 kg greater in the obese boys than in the nonobese boys (P < 0.001). After control for FFM and FM, RMR did not differ significantly between the groups. Conclusion: When body composition is appropriately controlled for, RMR does not differ significantly between obese and nonobese boys.