@article{SaalChaabeneHelmetal.2022,
  author    = {Saal, Christian and Chaabene, Helmi and Helm, Norman and Warnke, Torsten and Prieske, Olaf},
  title     = {Network analysis of associations between anthropometry, physical fitness, and sport-specific performance in young canoe sprint athletes},
  series = {Frontiers in sports and active living},
  volume    = {4},
  journal   = {Frontiers in sports and active living},
  publisher = {Frontiers Media},
  address   = {Lausanne},
  issn      = {2624-9367},
  doi       = {10.3389/fspor.2022.1038350},
  pages     = {13},
  year      = {2022},
  abstract  = {Introduction Anthropometric and physical fitness data can predict sport-specific performance (e.g., canoe sprint race time) in young athletes. Of note, inter-item correlations (i.e., multicollinearity) may exist between tests assessing similar physical qualities. However, multicollinearity among tests may change across age and/or sex due to age-/sex-specific non-linear development of test performances. Therefore, the present study aimed at analyzing inter-item correlations between anthropometric, physical fitness, and sport-specific performance data as a function of age and sex in young canoe sprint athletes. Methods Anthropometric, physical fitness, and sport-specific performance data of 618 male and 297 female young canoe sprint athletes (discipline: male/female kayak, male canoe) were recorded during a national talent identification program between 1992 and 2019. For each discipline, a correlation matrix (i.e., network analysis) was calculated for age category (U13, U14, U15, U16) and sex including anthropometrics (e.g., standing body height, body mass), physical fitness (e.g., cardiorespiratory endurance, muscle power), and sport-specific performance (i.e., 250 and 2,000-m on-water canoe sprint time). Network plots were used to explore the correlation patterns by visual inspection. Further, trimmed means (mu(trimmed)) of inter-item Pearson's correlations coefficients were calculated for each discipline, age category, and sex. Effects of age and sex were analyzed using one-way ANOVAs. Results Visual inspection revealed consistent associations among anthropometric measures across age categories, irrespective of sex. Further, associations between physical fitness and sport-specific performance were lower with increasing age, particularly in males. In this sense, statistically significant differences for mu(trimmed) were observed in male canoeists (p < 0.01, xi = 0.36) and male kayakers (p < 0.01, xi = 0.38) with lower mu(trimmed) in older compared with younger athletes (i.e., >= U15). For female kayakers, no statistically significant effect of age on mu(trimmed) was observed (p = 0.34, xi = 0.14). Discussion Our study revealed that inter-item correlation patterns (i.e., multicollinearity) of anthropometric, physical fitness, and sport-specific performance measures were lower in older (U15, U16) versus younger (U13, U14) male canoe sprint athletes but not in females. Thus, age and sex should be considered to identify predictors for sport-specific performance and design effective testing batteries for talent identification programs in canoe sprint athletes.},
  language  = {en}
}
@article{NevillNegraMyersetal.2020,
  author    = {Nevill, Alan M. and Negra, Yassine and Myers, Tony D. and Sammoud, Senda and Chaabene, Helmi},
  title     = {Key somatic variables associated with, and differences between the 4 swimming strokes},
  series = {Journal of sports sciences},
  volume    = {38},
  journal   = {Journal of sports sciences},
  number    = {7},
  publisher = {Routledge, Taylor \& Francis Group},
  address   = {London},
  issn      = {0264-0414},
  doi       = {10.1080/02640414.2020.1734311},
  pages     = {787 -- 794},
  year      = {2020},
  abstract  = {This 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).},
  language  = {en}
}
@article{SammoudNevillNegraetal.2018,
  author    = {Sammoud, Senda and Nevill, Alan Michael and Negra, Yassine and Bouguezzi, Raja and Chaabene, Helmi and Hachana, Youn{\´e}s},
  title     = {Key somatic variables in young backstroke swimmers},
  series = {Journal of sports sciences},
  volume    = {37},
  journal   = {Journal of sports sciences},
  number    = {10},
  publisher = {Routledge, Taylor \& Francis Group},
  address   = {Abingdon},
  issn      = {0264-0414},
  doi       = {10.1080/02640414.2018.1546547},
  pages     = {1162 -- 1167},
  year      = {2018},
  abstract  = {The purpose of this study was to estimate the optimal body size, limb-segment length, girth or breadth ratios for 100-m backstroke mean speed performance in young swimmers. Sixty-three young swimmers (boys [n = 30; age: 13.98 ± 0.58 years]; girls [n = 33; age: 13.02 ± 1.20 years]) participated in this study. To identify the optimal body size and body composition components associated with 100-m backstroke speed performance, we adopted a multiplicative allometric log-linear regression model, which was refined using backward elimination. The multiplicative allometric model exploring the association between 100-m backstroke mean speed performance and the different somatic measurements estimated that biological age, sitting height, leg length for the lower-limbs, and two girths (forearm and arm relaxed girth) are the key predictors. Stature and body mass did not contribute to the model, suggesting that the advantage of longer levers was limb-specific rather than a general whole-body advantage. In fact, it is only by adopting multiplicative allometric models that the abovementioned ratios could have been derived. These findings highlighted the importance of considering somatic characteristics of young backstroke swimmers and can help swimming coaches to classify their swimmers and enable them to suggest what might be the swimmers' most appropriate stroke (talent identification).},
  language  = {en}
}