Longitudinal Age-Related Morphological and Physiological Changes in Adolescent Male Basketball Players.

Author:Sekine, Yuta
 
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Introduction

Basketball players must have particular physical characteristics and high physiological performance levels, because they perform short sprints comprising 10% of the movements during matches, and they jump 46-70 times and cover 4500-5000 m with approximately 1000 movement pattern changes during basketball games (Crisafulli et al., 2002; Drinkwater et al., 2008; van der Does et al., 2016). The physical and physiological attributes crucial for determining the success of basketball players around puberty relate to maturity and chronological age (CA) (Torres-Unda et al., 2013).

Numerous differences in morphological growth and physiological development are evident during maturation (Malina et al., 2004a; Philippaerts et al., 2006; Torres-Unda et al., 2013 ), but different age grou p s often play in the same category, which requires careful consideration when training youth athletes or selecting talent. Muscle growth occurs from 13 years to 17.5 years of age, and boys' relative muscle mass increases from 46% to 54% of their body mass during this growth period (Malina et al., 2004a). The mean peak growth of the quadriceps femoris (QF) muscle heads occurs at a mean age of 15.4 (1.7) years and from 2 to 2.8 years after the age at peak height velocity (APHV) in Japanese boys (Satake et al., 1993; Sekine and Hirose, 2017). However, only a few longitudinal studies analyzing age-related changes in adolescent muscle have been conducted (Mersmann et al., 2017), and research into muscle growth according to CA and biological maturation is required.

Sprinting and jumping reflect power generation, and they are used to indicate neuromuscular fitness and identify talent (Asadi et al., 2018). Maximal power production occurs 2 years after the APHV (Malina et al., 2004a). Conversely, several studies' findings indicate that spurts of anaerobic capacity occur at the time of the APHV (Philippaerts et al., 2006). In youth basketball, the years from the APHV was proposed as the best predictor of sprint or jump performances that could enable players who might mature earlier or were of advanced maturity to be targeted during talent identification and given opportunities to facilitate success (Torres-Unda et al., 2016). Previous studies' findings have shown that biological maturity level influences physiological capacity strongly (Malina et al., 2004b; Meyers et al., 2015). At present, several studies that indicate the relationships between maturational characteristics and anthropometric, physiological characteristics in Spanish (Torres-Unda et al., 2013; 2016) and Portuguese male youth basketball players (Ramos et al., 2018; 2019a; 2019b) have been reported. However, research into Japanese youth athletes is required because the times at which the APHV is reached may vary according to race or the birth environment (Beunen et al., 2006; Malina et al., 2015; Satake et al., 1993).

All parties involved in youth sports should understand how morphological growth and physiological development occur to ensure youth athletes are trained safely and effectively. Clarifying age-related morphological growth and physiological development will provide the knowledge required to create suitable conditioning programs for youth athletes. We hypothesized that morphological growth and physiological development depend on CA and biological age. This study examined longitudinal age-related changes in muscle morphology and jump and sprint performances in male basketball players.

Methods

Study design and participants

A longitudinal study design was adopted to examine age-related changes in the muscle morphology and anaerobic capacities of 41 adolescent male basketball players aged 12-14 years at baseline. Measurements were performed in June and December from 2015 until 2018, and this study analyzed each participant's consecutive 1-year data. All participants in this longitudinal study were expected to have lived roughly the same lifestyle throughout the study period, that is, to attend classes from 9:00 AM to 3:30 PM on weekdays and trained on average 12.5 to 14 h a week, including 4.5 to 5 h strength and conditioning program (body weight exercises, sprint training, resistance training, stability exercises) and 8 to 9 h of sport-specific practice. In the game season, 1 to 2 games are held on the weekend. All participants performed the same strength and conditioning program with supervision by the same qualified trainer.

The participants were assigned to three groups based on differences between their estimated APHVs and CAs at baseline, as follows: the late group, CA >6 months before APHV (n = 12); mid group, CA within 6 months of the APHV (n = 12); and early group, CA >6 months after APHV (n = 17). Upper arm muscle thickness (MT) and sprint were added during the study, and 17 participants were unable to measure continuous 1-year longitudinal data. Therefore, we examined these measurements in 24 participants, comprising eight in the late group, 10 in the mid group, and six in the early group. Participants who had undergone lower extremity surgery were excluded from this study. Mean and standard deviation values of each group's characteristics are provided in Table 1. Before the study was started, the briefing session was held to explain the study details and any safety concerns to the participants, their parents, and the team manager. Written consent was obtained from each participant and their parent prior to study participation. This study was performed according to the Declaration of Helsinki and was approved by the university's human ethics review committee (No. 29-034-1).

APHV estimation

The APHV was assessed using a triphasic generalized logistic model (BTT model) based on the participants' serial stature records that had been measured previously (AUXAL, version 3.0; Scientific Software International Inc., Skokie, IL, USA) (Ali et al., 2007).

Ultrasound measurements

The distance between the anterior superior iliac spine and the superior tip of the patella (APD) was measured using a steel gauge to determine the locations at which ultrasound images of the individual QF portions would be evaluated. Based on previous studies (Giles et al., 2015a; Sekine and Hirose, 2017), the circumference was measured at 20% of the APD for the vastus medialis (VM) and at 50% of the APD for the rectus femoris (RF), vastus intermedius (VI), and vastus lateralis (VL). To determine the location of the VM, measurements were acquired at 12.5% of the circumference in the medial direction at 20% of the APD. The location of the VL was marked at 10% of the circumference in the lateral direction at 50% of the APD. Ultrasound images of the RF and VI were captured at 50% of the APD. The biceps brachii (BB) and triceps brachii (TB) sites were determined 60% distally between the lateral epicondyle of the humerus and the acromial process of the scapula (Ogasawara et al., 2012), and images were captured at 25% and 75% of the circumference in the medial direction, respectively. These measurement points were marked with a pen to facilitate...

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