• A new waist-to-height ratio predicts abdominal adiposity in adults.

      Nevill, Alan M.; Stewart, Arthur D; Olds, Tim; Duncan, Michael J (Taylor & Francis, 2018-07-25)
      Our aim was to identify the best anthropometric index associated with waist adiposity. The six weight-status indices included body mass index (BMI), waist-to-hip ratio (WHR), waist-to-height ratio (WHTR), and a new waist-by-height
    • Allometric associations between body size, shape, and physical performance of Greek children.

      Nevill, Alan M.; Tsiotra, Georgia D.; Tsimeas, P. D.; Koutedakis, Yiannis; School of Sport, Performing Arts and Leisure, University of Wolverhampton, Walsall WS1 3BD, UK. (Human Kinetics, Inc., 2009)
      We adopted allometric models to identify the most appropriate body size/shape characteristics associated with physical performance activities of Greek school children. Children underwent assessments for aerobic and anaerobic fitness, flexibility and hand-grip strength. Results suggest that the inverse Ponderal index and not BMI is the most appropriate body-shape indicator associated with running and jumping activities. Height was negatively associated with flexibility, but both height and weight were positively associated with hand-grip strength. In conclusion, allometric models provide a valuable insight into the most appropriate body size and shape characteristics associated with children's physical performances and at the same time ensure valid inference when investigating group/population differences (e.g., between gender and maturation status).
    • Key somatic variables associated with, and differences between the 4 swimming strokes

      Nevill, Alan M; Negra, Yassine; Myers, Tony D; Sammoud, Senda; Chaabene, Helmi; Faculty of Education, Health and Wellbeing, University of Wolverhampton, Wolverhampton, UK. (Informa UK Limited, 2020-03-04)
      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).
    • Modelling handgrip strength in the presence of confounding variables: results from the Allied Dunbar National Fitness Survey.

      Nevill, Alan M.; Holder, R L (Taylor & Francis, 2000-10)
      Differences in handgrip strength, caused by risk factors such as physical inactivity, will be influenced by 'confounding' variables, e.g. age, body size. The aims of the study were to identify the confounding variables associated with handgrip strength and to assess the benefit that physical activity plays in maintaining grip strength within a population, having adjusted for differences in these confounding variables. The most appropriate linear body size dimension associated with grip strength was height rather than demispan. Non-linear associations with age and body mass were also identified. Handgrip strength peaked in the age group 25 - 34 years for male subjects and in the age group 35 - 44 years for female subjects. Similarly, handgrip strength increased with body mass until it peaked at a body mass of approximately 100 kg for male and 90 kg for female subjects; thereafter a rapid decline in grip strength was observed. Differences in handgrip strength were found to be significantly associated with levels of physical activity even having controlled for differences in age and body size (height, mass and percentage body fat), but the observed association was not linear. The level of physical activity necessary to maintain an optimal level of handgrip strength was found to be a balance of moderate or vigorous occasions of physical activity.
    • Modelling the determinants of 2000 m rowing ergometer performance: a proportional, curvilinear allometric approach

      Nevill, Alan M.; Allen, S. V.; Ingham, S. A. (Wiley-Blackwell, 2011)
      Previous studies have investigated the determinants of indoor rowing using correlations and linear regression. However, the power demands of ergometer rowing are proportional to the cube of the flywheel's (and boat's) speed. A rower's speed, therefore, should be proportional to the cube root (0.33) of power expended. Hence, the purpose of the present study was to explore the relationship between 2000 m indoor rowing speed and various measures of power of 76 elite rowers using proportional, curvilinear allometric models. The best single predictor of 2000 m rowing ergometer performance was power at V̇O2max ()0.28, that explained R2=95.3% in rowing speed. The model realistically describes the greater increment in power required to improve a rower's performance by the same amount at higher speeds compared with that at slower speeds. Furthermore, the fitted exponent, 0.28 (95% confidence interval 0.226–0.334) encompasses 0.33, supporting the assumption that rowing speed is proportional to the cube root of power expended. Despite an R2=95.3%, the initial model was unable to explain “sex” and “weight-class” differences in rowing performances. By incorporating anaerobic as well as aerobic determinants, the resulting curvilinear allometric model was common to all rowers, irrespective of sex and weight class.
    • Scaling concept II rowing ergometer performance for differences in body mass to better reflect rowing in water

      Nevill, Alan M.; Beech, C.; Holder, Roger L.; Wyon, Matthew A. (John Wiley & Sons, 2010)
      We investigated whether the concept II indoor rowing ergometer accurately reflects rowing on water. Forty-nine junior elite male rowers from a Great Britain training camp completed a 2000m concept II model C indoor rowing ergometer test and a water-based 2000msingle-scull rowing test. Rowing speed in water (3.66 m/s) was significantly slower than laboratory-based rowing performance (4.96m/s). The relationship between the two rowing performances was found to be R2528.9% (r50.538). We identified that body mass (m) made a positive contribution to concept II rowing ergometer performance (r50.68, Po0.001) but only a small, non-significant contribution to single-scull water rowing performance (r50.039, P50.79). The contribution that m made to single-scull rowing in addition to ergometer rowing speed (using allometric modeling) was found to be negative (Po0.001), confirming that m has a significant drag effect on water rowing speed. The optimal allometric model to predict single-scull rowing speed was the ratio (ergometer speed m 0.23)1.87 that increased R2 from 28.2% to 59.2%. Simply by dividing the concept II rowing ergometer speed by body mass (m0.23), the resulting ‘‘powerto- weight’’ ratio (ergometer speed m 0.23) improves the ability of the concept II rowing performance to reflect rowing on water.