Authors: Alysia Cohen, Heidi Wegis, Darren Dutto, Viktor Bovbjerg

Corresponding Author:
Alysia Cohen, PhD, ATC, CSCS
1435 Village Drive
Ogden, UT 84408
[email protected]
801-626-7115

Alysia Cohen is an Assistant Professor in the Department of Athletic Training at Weber State University.

The Role of Organized Youth Sports in Reducing Trends in Childhood Obesity

Abstract

Purpose: To examine physical activity (PA) levels of children playing youth sports and the relationship of recommended levels of PA to contextual factors of the organized youth sports environment that may boost fitness and health during childhood and adolescence.  Methods: Accelerometer-measured PA was obtained from 167 children (85 male, 82 female) aged 7-13 years. Sport contextual factors were recorded via direct observation of 29 coaches. PA levels were examined by age, gender, and between group variability. Direct observation intervals were analyzed by category using the Chi-square statistic for degree of association to moderate-to vigorous-intensity physical activity (MVPA).  Results: On average children spent 21.9 ±7.9 minutes in MVPA during sport practices (< 50% of practice time).  Proportion of practice time MVPA was lower among females (28.7 ± 7.2%) than males (35.0 ± 9.1%). Proportion of practice time MVPA was higher among children (male and female) aged 7-9 years (32.6 ± 1.4%) compared to children aged 10-13 years (30.66 ±1.25%). Longer practice times were not shown to increase the proportion of time spent in MVPA. The most frequently observed sport activities were sports drills (51.6%), activities involving all players (37.8%), management/general instruction (52.3%), and proximal positioning of the coach (99.5%). Management and general instruction coaching behavior was not significantly associated with MVPA but did consume a prominent proportion of practice time. Health-related fitness activities made up 1.7% of practice time.  Conclusions: In comparison with recommendations, youth sports appear active, however, a large portion of practice time is sedentary suggesting room for improvement.  Including fun non-specific or specific sport activities that promote participation from all players and increase heart rate. Fun play experiences during sport practices may encourage greater in active play within and outside of sport with behaviors persisting into adolescence and adulthood.  Applications in Sport: Training coaches to teach fun sport activities that engage all players would improve within practice active time and enjoyable experiences that may promote future participation in sport or activity outside of sport.

Key words: youth sport, obesity, physical activity, children

INTRODUCTION

Organized youth sports programs, including soccer, basketball, and football, are popular non-scholastic activities among youth. Sport participation during childhood and adolescence is associated with positive outcomes in physical fitness, body weight, mental health, academic performance, and social development (1,4,17,25,27-29). In particular, youth sport participation trends in the U.S. increased dramatically during the early 21st century (22), however, over the last 10 years nearly all sports experienced declines (26). Unfortunately, the downshift in sport participation occurred simultaneously with increased physical inactivity and prevalence of obesity among children and adolescents. Among youth aged 6 to 19 years, obesity prevalence increased from 16.8% (2007-2008) to 18.5% (2015-2016) (13). Physical inactivity is well known to be associated with being overweight or obese and with related noncommunicable diseases such as heart disease, type 2 diabetes, high blood pressure, and certain forms of cancer (15,21,27). Although many chronic diseases associated with physical inactivity do not present until adulthood, the precursors can begin to manifest as early as childhood (7,9). Recent health projections presented by the Global Obesity Prevention Center at John Hopkins University suggest an increase of 50% of youth that get and stay active until 18 years of age would live an average of 20.5 years longer and reduce their risk of becoming overweight or obese by 15.5 times compared to a child that does not maintain their activity level (3). In the moment, coaching physical activity behavior may seem like an inherent part of sport participation, but statistically, we see otherwise.  

In the last decade a few studies have provided an overview of physical activity (PA) behavior within and outside of sport participation. In general, Troiano et al. (30) reported youth aged 6 to 19 years participate in less than 50% of the daily recommendation of 60 minutes of moderate-to vigorous-intensity physical activity (MVPA) (33). Among youth participating in sports, daily MVPA is higher with one-third to three-quarters occurring during sport practices.  For instance, Leek et al. (18) and Cohen et al. (5) reported two very different perspectives with 46.1% and 36.8%, respectively, of practice time spent in MVPA. Translated to minutes of MVPA, 20 to 45 minutes of practices was spent in MVPA. Although significant, many youth programs practice one to two days a week resulting in activity levels well below the recommendations on non-sport days (35). When combined with other MVPA opportunities, such as physical education or free play, sport practices serve as a primary source of MVPA. Addressing the more than 50% of time spent in sedentary physical activity during sport practices is reasonable to increasing children’s daily MVPA and improving short-term and long-term health benefits.

Second to school settings, youth sports engage with a high volume of children. Similar to education teachers, sport coaches serve as teachers and role models in their field. However, a difference between teachers and many sport coaches is the presence of training in their respective field. According to recent survey data of youth coaches, 4 in 10 coaches lack adequate and routine training in areas of basic life support, concussion management, general safety and injury prevention, physical conditioning, sport skills and tactics, and effective motivational techniques (26). When considering the emphasis given to youth sports in addressing a national health crisis involving physical inactivity and obesity among youth and adults, a lack of training may explain the more than 50% of sedentary PA during sport practices.   

Guagliano et al. (12) examined the effect of single 2-hour coach education training session on mediating factors of player MVPA (eg, coach MVPA, management, knowledge delivery, promoting PA, and demonstrating PA).  Coaches received training on 4 topics: 1) strategies to increase MVPA and decrease inactivity during practice, 2) self-monitoring, 3) goal-setting, and 4) recommended target step counts per minute. Although the training was shown to be effective at improving player MVPA, the effect was isolated to changes in the coaches’ physical activity behavior during practice. For instance, following the intervention, coaches that were more physically active during practice also observed more active players (compared to pre-test measurements). Unfortunately, training on more effective management strategies, delivery of knowledge to players, promoting PA, and use of PA demonstration in coaching pedagogical strategies did not improve player MVPA, which contradicts results from Dudley et al. (6) that suggest training of physical educators reduced time spent in management and knowledge delivery alongside increases in MVPA during physical education classes. While both studies aimed to address factors of MVPA, the setting (school, youth sports) and source of instruction (teacher, coach) are quite different and are not always reflective of each other. The purpose of this study was to provide a greater understanding of the physical activity strengths and weaknesses of sport practices to better address coaching competencies and organizational strategies to enhance physical behavior within sport and known directly related health benefits.

METHODS

Study Participants and Setting

The current study design was nonexperimental. Two organized youth soccer programs (American Youth Soccer Organization and a Parks and Recreation Department) from two small Pacific Northwest cities were recruited for participation in the study. A total of 30 youth soccer teams (15 male and 15 female) and 29 volunteer (unpaid) coaches (23 male, 6 female), aged 35 years and older, consented to participate. Consent was obtained from parents/guardians of 167 children (85 male, 82 female) aged 7-13 years (mean age 8.97 years) that provided written and verbal assent to participate in the study. Participant characteristics are provided in Table 1. This study was approved by the Oregon State University Institutional Review Board (IRB) and both participating youth sports organizations.

Table 1: Participant Characteristics
Teams (n=30) Male Female Coaches (n=29) Male Female
  15 15   23 6
Children
 85 82      
(n=167)     35-39 years 11
 2
7 years old 23 24 40-44 years 7
 2
8 years old 11
 19
 45-49 years 2
 1
9 years old 16
 11
 > 50 years   3 1
10 years old 16
 12
      
11 years old 8
 10
      
12 years old 8 5
      
13 years old 3 1      

Measurement Procedures

Accelerometry

Physical activity levels of children participating in the study were obtained using Actigraph (Actigraph Corporation, Pensacola, FL) GT1M and GT3X accelerometer-based motion sensors. The GT1M and GT3X have been shown to be valid and reliable instruments for measuring children’s physical activity levels (31-32) with no observed differences in physical activity measurement outcomes between the two models (24). Prior to each practice, the accelerometers were synchronized to a universal time clock within the propriety computer software then each unit was initialized to record counts via a 15-second epoch setting. A 15-second epoch setting was selected based on protocol established by Evenson et al. (8) for measuring physical activity levels in children (19). A universal stopwatch was also synched to the computer software time clock and used to report start and stop wear-time, practice time, and direct observation interval time.  Accelerometers positioned around the waist of each child on the right hip and held in place by an elastic waist belt. Data from each accelerometer was later downloaded to the Actigraph proprietary software. Physical activity levels were interpreted as total counts using the intensity-based cut-points developed by Evenson et al. (8).

Direct Observation

Children’s physical activity and contextual factors of the practice environment were gathered via momentary-time sampling procedures of the Observation System for Recording Activity in Children, Youth Sports version (OSRAC:YS). The OSRAC:YS was selected based on its validity (r = 0.73, P < .001) and reliability (Kappa coefficients of 0.67 to 0.93) among youth soccer players for measuring PA levels and contextual factors of PA during soccer practices (5).

Team practices were observed once during the first half of the programs’ 8-week soccer season. For each practice, the researcher observed a single volunteer coach and player. For teams with more than one coach (n=2), only the head coach was observed. Prior to the start of practice this information was verbally confirmed with the coaches. Player observation order was determined randomly prior to a team’s scheduled practice.  Upon arriving at practice and identifying players present, any child not in attendance was passed over in the observation order. Identifying information (eg, color of socks, shorts) were recorded on the observation worksheet allowing the observer to quickly identify a focal child. A median of five children per practice were observed. A single observation time period of 10 minutes was completed for each player in attendance, which included a total of 20 observation cycles consisting of a 10-second observation followed by 20-second recording interval. Observation periods less than 10 minutes occurred when (1) the focal-child was removed from practice for a restroom break, behavioral issue (instructed by the parent, coach, or self-selected not to participate), or an injury, (2) practice ended prior to interval completion, or (3) the researcher was unable to complete the observation interval (environmental factors such as loss of daylight; equipment malfunction). Incomplete observation periods were included in the final data analysis. At the conclusion of each observation period, approximately 2 minutes was delegated to setting up for the next period, thus, a 60 minute practice included approximately five observation periods. In addition to use of the instrument for purposes of the study, specific psychometric tests (i.e., Kappa coefficients and percent agreement) were included to address accuracy in direct observation of defined contexts of the practice setting.

The OSRAC:YS consists of five observational categories: 1) physical activity level, 2) practice context, 3) social context, 4) coach behavior, and 5) coach proximity, each with defined observational codes (Table 2). When observing children’s physical activity level, codes were recorded based on the Children’s Activity Rating Scale (CARS). The CARS instrument (23) includes five levels of activity that are described in Table 2. The CARS instrument was found to be a valid and reliable (84.1% agreement) tool for measuring children’s physical activity levels. More recently, testing of the OSRAC:YS and CARS demonstrated reliability (Kappa coefficient 0.71) of the instrument to measure children’s physical activity levels during youth sport practices (5).

Table 2: Observational contexts with coding categories and descriptions of each code.
Context Code Description
Physical Activity Level (1) Stationary/Motionless Sedentary physical activity
(2) Stationary/movement of trunk or limbs
  (3) Slow/easy movement Low-intensity physical activity
  (4) Moderate movement Moderate-intensity physical activity
  (5) Fast movement Vigorous intensity physical activity
Practice Context (1) Warm-up any activity performed at the start of practice (e.g. low- to moderate-intensity aerobic activity and/or stretching)
  (2) Drills activity with a set purpose to focus on a specific component of the activity/sport
  (3) Tactic/instruction activity with a set purpose on learning the game rules or skill development
  (4) Fitness activity for improving player cardiovascular fitness or muscular strength
  (5) Game full team activity in which all players of the team are involved, either working together or opposing other players
  (6) Cooldown end of practice activities with focus on reducing the intensity
  (7) Transition change between two practice contexts that do not include activities associated with sport activity (e.g., water or restroom break, free time)
Social Context (1) Solitary action or physical activity behavior is independent of the action of another player (e.g., personal skill development, periods of transition)
  (2) 1v1 focal child is paired with another player to complete a desired task or activity
  (3) Greater than 2, < full team activity involving more than 2 players (the focal child and at least two other children/teammates) but less than all players on the team
  (4) Full team all players are involved in a single activity in which player participation and actions are dependent on each other
Coach Behavior (1) Watching with feedback watching a player then providing feedback for the skill or task performed
  (2) Watching without feedback watching the focal player or more than one player but not providing feedback
  (3) Demonstration any skill demonstrated by the coach or participation of the coach in the practice activity (e.g., playing with the team during a scrimmage)
  (4) Management/general instruction engaged in practice set-up activities (i.e., setting up a drill), provides activity instructions to the team or general team or sport discussions with the players
  (5) Disengaged/off-task coach appearing to be removed or uninvolved in any form to the practice activities
Coach Proximity (1) Proximal within the boundary of the activity
  (2) Distal coach outside of the playing boundary

During each 10-second observation interval, the observer followed along, identifying physical activity levels of the focal child and contextual factors from each category. Physical activity level is coded at the highest level observed for continuous 3 or more seconds of the 10-second observation interval. Practice context, social context, coach behavior, and coach proximity followed the same 3-second protocol but did not include a rank. For each category, a single code is recorded based on its occurrence with a standard of 3 seconds established as the baseline. For instance, if practice context was observed for 3 seconds as a drill followed by 7 seconds in a transition, the interval would be coded as “transition”. For each 10-second observation interval, the observer identified and recorded findings for all 5 OSRAC:YS categories.

Statistical Analysis

Descriptive statistics (means and standard deviations) were determined for physical activity levels obtained by accelerometry. Physical activity intensity levels were examined across all participants, by team, age, and gender. Total time (minutes) and percent practice time spent in sedentary, MVPA, and vigorous-intensity levels were assessed. Independent samples t-tests examined differences between groups (gender and age category). Coding frequencies were calculated for each observation category via the OSRAC:YS as well as observations associated with MVPA from direct observation (code of 4 or 5). Chi-square tests of independence were performed for intervals coded as MVPA and corresponding codes from the OSRAC:YS contextual categories. Corresponding p-values were calculated as well as a Pearson product-moment correlation for significant chi-square values. Psychometric properties of the OSRAC:YS were characterized via Kappa coefficients and percent agreement of each contextual category. Kappa coefficients were interpreted using the rating scale developed by Landis and Koch (16): 0 to 0.2 poor, 0.2 to 0.4 fair, 0.4 to 0.6 moderate, 0.6 to 0.8 substantial, and 0.8 to 1.0 almost perfect agreement. An interrater correlation coefficient (ICC) was obtained to estimate the agreement between observers to rate MVPA. All statistical analysis procedures were performed in SPSS version 25 (SPSS Inc., Chicago, IL) with statistical significance established at P < .05.

RESULTS

Reliability of the OSRAC:YS

Inter-observer percent agreement and Kappa coefficients for each of the five OSRAC:YS observational categories are reported in Table 3. Two observers completed 170 observations on two non-consecutive days during the 8-week season and for two different teams. Kappa coefficients ranged from 0.74 to 0.98 (Table 3). Inter-observer percent agreement of 80% and higher was determined for all five categories. An ICC of 0.85 suggests significant agreement between observers in classifying physical activity levels via direct observation and percent agreement of coding MVPA.

Table 3: OSRAC:YS Reliability Coefficients
Contextual Category % Agreement Kappa Statistic 95% CI
Physical Activity Level 87.7% 0.83 0.76 to 0.89
Practice Context 98.2% 0.98 0.94 to 1.00
Social Context 94.7% 0.89   0.83 to 0.96
Coach Behavior 85.3% 0.74 0.64 to 0.83
Coach Proximity 100.0% N/A N/A

Physical Activity Levels

Across teams, practice ranged from 60 to 90 minutes (mean 68.8, SD±12. 8). On average, children aged 7-13 years spent the greatest proportion of practice in sedentary activity, followed by MVPA and then light intensity PA (Table 4). No significant differences were found between age groups for time spent in MVPA as a percent of practice time (df=28, P=0.54) or in minutes (df=28, P=0.47) or percent time in sedentary physical activity (df=28, P=0.31). Significant differences were observed for percent MVPA by gender with boys more active than girls (35.0% ± 9.1 vs 28.7% ± 7.2, respectively, P=0.006). Although the researchers did not observe a significant decline in PA from age 7 to 13 for all participants, increases in practice time across both genders and ages resulted in a percent decrease in overall practice time MVPA and increase in time spent in sedentary activity.

Table 4:  Physical Activity Levels by Age Group
Mean Activity
Level (SD)		 All Subjects
(n=167)		 95% CI Age 7-9 years
(n=104)		 95% CI Age 10-13 years
(n=63)		 95% CI
Sedentary            
Minutes 27.25 (±9.13) (25.86 to 28.63) 25.51 (±2.57) (22.61 to 28.41) 33.84 (±5.50) (28.45 to 39.23)
Percentage 39.93 (±10.63) (38.32 to 41.54) 38.83 (±1.89) (36.72 to 40.93) 41.89 (±1.65) (40.28 to 43.50)
Vigorous            
Minutes 13.97 (±5.77) (13.09 to 14.84) 13.76 (±2.09) (11.40 to 16.12) 16.34 (±2.99) (13.41 to 19.27)
Percentage 20.45 (±7.15) (19.37 to 21.53) 20.64 (±1.01) (19.50 to 21.78) 20.19 (±1.01) (19.08 to 21.30)
MVPA            
Minutes 21.88 (±7.93) (20.67 to 23.08) 21.76 (±3.12) (18.23 to 25.29) 24.89 (±4.10) (20.87 to 28.91)
Percentage 31.97 (±8.79) (30.63 to 33.30) 32.59 (±1.44) (30.96 to 34.22) 30.66 (±1.25) (29.44 to 31.88)

OSRAC:YS – Contextual Factors of Physical Activity

The primary researcher observed a total of 2939 intervals. Results of contextual factor frequency to MVPA are reported in Table 5. For the four contextual categories – practice context, social context, coach behavior, and coach proximity – the frequency of codes recorded as well as percent of which were recorded with a physical activity level code of 3 or 4 (moderate, fast), or MVPA, were determined. Within the practice context category, drill-like practice activities were observed most frequently (51.6%) followed by tactic/instruction (16.9%), transition (15.2%), game (10.3%), warm-up (4.1%), fitness (1.7%), and cool-down (0.3%). There was a significant association between the type of practice context and MVPA (X2=299, df=6, P < .001). The proportion of time spent in MVPA for each code varied with greatest proportion occurring during fitness-related activities (75.5%). Because the proportion of MVPA determined for each code is relative to the frequency of each code, the overall proportion of practice time spent in MVPA during fitness activities was relatively high despite low occurrence of fitness-related activities. Not surprisingly, MVPA was not observed during cool-down activities. The proportion of practice time spent in each social context code was greatest among full team activities (37.8%) followed by solitary (36.5%) , group (13.5%), and 1v1 activities (12.1%). No significant association was found between social context of practice activities and MVPA (X2=4.63, df=3, P=0.20). The proportion of each social context code spent in MVPA varied relatively little, ranging from 28.4% for group activities to 23.3% for solitary activities. Over half (52.3%) of all coach behavior codes observed were recorded as management/general instruction with a low portion of such codes resulting in MVPA during practice time (14.1%). There was a significant association between coaching behavior and MVPA (X2=212, df=4, P < .001). Watching without giving verbal feedback was recorded nearly one-third of all coach behavior observations and was more associated with MVPA than other codes of coaching behavior. Watching and providing verbal feedback was less frequent but displayed a higher proportion of time with MVPA (39.9%) compared to no feedback given (36.9%). The remaining coach behavior codes, demonstration and appearing disengaged, made up a small portion of the observations. Despite the low occurrence of demonstration (2.5% of practice time), almost half of all demonstration codes were found to be associated with MVPA. Finally, MVPA was associated more frequently with the disengaged/off-task code than management/general instruction suggesting children moved more when the coach appeared withdrawn from practice activities. For the remaining contextual factor, coach proximity, the vast majority of observations recorded were marked as proximal. There was no significant association between placement of the coach to players’ MVPA (X2=.55, df=1, P=0.46).

Table 5:  OSRAC:YS Categorical Code Frequencies
  Proportion of Intervals Proportion of Intervals in MVPA
Contextual Category All subjects
(2939
intervals)

7-9 y
 (2016
intervals)

 10-13 y
(923
intervals)		 All
subjects		 7-9 y 10-13 y
Physical Activity Level
Stationary/No Movement
Stationary Limb
Movement
Slow Easy
Moderate
Fast
30.5%
16.3%
28.2%
11.4%
13.6%
25.1%		  
29.6%
15.9%
28.7%
12.3%
13.5%
25.8%		  
32.4%
17.1%
27.0%
9.5%
13.9%
23.4%		      
Practice Context**
Warm-up
Drills
Tactic/Instruction
Fitness
Game
Cooldown
Transition		  
4.1%
51.6%
16.9%
1.7%
10.3%
0.3%
15.2%		  
2.8%
51.4%
14.0%
1.4%
13.3%
0.1%
17.0%		  
6.8%
52.0%
23.2%
2.3%
3.6%
0.8%
11.4%		  
30.8%
32.1%
2.6%
75.5%
35.4%
0.0%
12.5%		  
29.8%
31.9%
2.8%
89.3%
34.6%
0.0%
13.7%		  
31.7%
32.5%
2.3%
57.1%
42.4%
0.0%
8.6%
Social Context
Solitary
1 v 1
Group
Full Team		  
36.5%
12.1%
13.5%
37.8%		  
36.1%
12.0%
11.7%
40.1%		  
37.4%
12.4%
17.6%
32.7%		  
23.3%
26.6%
28.4%
25.1%		  
24.1%
25.9%
25.4%
27.5%		  
21.4%
28.1%
32.7%
18.9%
Coach Behavior**
Watching with Feedback
Watching w/o Feedback
Demonstration
Management / Instruction
Disengaged/Off-task		  
12.7%
31.7%
2.5%
52.3%
0.9%		  
14.5%
29.8%
2.5%
52.1%
1.0%		  
8.6%
35.6%
2.4%
52.9%
0.5%		  
39.5%
36.2%
41.1%
14.1%
24.0%		  
39.9%
36.6%
41.2%
15.2%
15.0%		  
38.0%
35.6%
40.9%
11.7%
60.0%
Coach Proximity
Proximal
Distal		  
99.5%
0.5%		  
99.4%
0.6%		  
99.7%
0.3%		  
25.0%
33.3%		  
25.8%
25.0%		  
23.3%
66.7%
** Significant at <.001

DISCUSSION

In this study, youth sports were found to provide less than half of the recommended daily levels of MVPA. Unfortunately, longer practices did not positively reflect an increase in MVPA. Rather, children were more sedentary. In general, practice context (eg, type of activity occurring) and coaches behavior (eg, demonstrating a skill) were more likely to be associated with MVPA among children participating in youth sports practices, while number of players involved in the practice activity (social context) and proximity of the coach to the players did not significantly influence player MVPA. Children were more likely to achieve health-related PA levels during fitness, sport-specific drills, game activities, receiving feedback from the coach, and during activities when the coach was active alongside players (demonstrating a skill or activity). Contextual factors of coach behavior that are not associated with MVPA but make up a significant proportion (>50%) of coaching behavior, such as management and general instruction, during practice time. These are important considerations in the development of coach education training programs that aim to improve children’s time spent in health-related levels of PA.

Despite substantial research on physical activity levels during youth sport practices, very little remains understood about components of sport practices could be improved to further increase time spent in recommended levels of PA, as well as enhance motivation among children to engage in such behaviors during practices and on their own time. This study aimed to address this gap by examining the relationship between contextual factors of the practice setting and levels of MVPA. By acknowledging the dynamics of the youth sport environment, including its strengths and weaknesses, we learn more about the role of volunteer youth sport coaches in teaching and delivering physically active sports programs.

In addition to this study, Guagliano et al. (10) identified a few emerging themes among coaches in their perceived responsibility toward PA outcomes of sport. According to interviews conducted with youth sport coaches, many did not define themselves as a role model for PA and that being physically active during practice was emphasized as a performance factor (eg, outperform an opponent during competition) over a whole body health benefit. In addition, fitness activities were considered a part of early season training but once sufficient, practice time emphasized teaching sport-related skills, which in the current study was found to be less likely to produce MVPA opportunities. These perceptions are important as they may impose a barrier to revising youth sport outcomes and programs to include PA behavior awareness and advocacy.

Since interventions to decrease instruction and practice management in youth sports are limited, claims of effectiveness of coach education training are derived from past research performed in the PE setting among trained PE teachers (McKenzie et al., 2010). Recent literature has suggested positive effects on MVPA during PE following educational teacher training (20,34). In 2015, Guagliano et al. (11) replicated similar methods from interventions in the PE setting and found a significant increase in MVPA among players of coaches that received the intervention compared to players of coaches that were not given the training, a change of 15.1% and 0.4% of practice time, respectively. The change in MVPA was reported in a separate study, which was defined as an action of the coach to increase their own activity level during practices that resulted in more active players (12). This result is consistent with our findings between player MVPA and a coach observed demonstrating a sport behavior (eg, being physically active with a child). An increase in coach PA behavior during practices may suggest coaches more skilled in movements of the sport and are physically capable of performing them would positively influence player participation and PA levels during sport. These findings reflect a content focus for coach education programs. However, compared to the 2-year intervention performed by McKenzie et al. (20), the coaching intervention was provided on 2 days over a 5 day period with measurement occurring on the first and fifth day. It is unclear whether or not observed increases in MVPA would fatigue over time. More research is needed to examine long-term effects of coach education training programs that emphasize outcomes associated with players’ physical activity behavior within and outside of sport participation and retention of youth in sport.

CONCLUSIONS

Physical inactivity is a growing concern among youth and associated health-related outcomes in adolescence and adulthood. Participation in organized youth sports are shown to be beneficial toward meeting recommended levels of MVPA during the day, however, more than half of practice time is spent in sedentary PA levels with no effect observed for longer practice time periods. Further, it appears that physical activity behavior within sport does not transfer to time outside of sport, suggesting a lack of coaching emphasis on lifestyle physical activity skills and motivation of youth to live an active lifestyle, which may be fostered through a fun and enjoyable sport experiences. Volunteer coaches play an important role in the development of the physical activity profile of youth sport experiences (14). Practice design and delivery, and coaching behaviors reflect the likelihood that children will engage in MVPA as well as continued participation in sport, all of which can be influenced through targeted coach education training on physical activity and health. A majority of youth sport organizations do not require volunteer coaches to have specific training or knowledge of any aspect of coaching. By highlighting youth sports as a viable source of daily MVPA and future health of those children participating in sport, we recommend coach education training in recommended areas of 1) philosophy and ethics, 2) safety and injury prevention, 3) physical conditioning, 4) growth and development, 5) teaching and communication, 6) sport skills and tactics, 7) organization and administration, and 8) evaluation, as presented by SHAPE America, formerly known as American Alliance for Health, Physical Education, Recreation and Dance (2). Promoting change from the administrative level of youth sport organizations can help drive positive change at the community level.

APPLICATIONS IN SPORT

Youth sports are long existing community service programs. Continued access to youth sports programs remains a vital resource to communities, however, as most communities grow and their needs change, so too should programs to address gaps and unhealthy trends, such as that of physical inactivity, overweight and obesity. The pulse of a program is housed in its many adult parent volunteers. Children look up to coaches and benefit from coaches educated and trained in the importance and value of being physically active during and outside of sport participation. By incorporating physical activity-related concepts to coach education training programs, public health practitioners will be better able to measure immediate and long-term outcomes associated with children’s physical activity behavior and attrition or continued participation in sport.

ACKNOWLEDGMENTS

None

REFERENCES

  1. Agata, K. & Monyeki, M.A. (2018). Associations between sport participation, body composition, physical fitness, and social correlates among adolescents: The PAHL study. International Journal of Environmental Research and Public Health, 15, 2793-2808. doi:10.3390/ijerph15122793
  2. American Alliance for Health, Physical Education, Recreation and Dance. Maximizing the benefits of youth sports (2013). Journal of Physical Education, Recreation and Dance, 84, 8-13.
  3. Aspen Institute (2019). Benefits of progress. Retrieved from https://www.aspenprojectplay.org/benefits-of-progress
  4. Basterfield, L., Reilly, J.K., Pearce, M.S., Parkinson, K.N., Adamson, A.J., Reilly, J.J., & Vella, S.A. (2015). Longitudinal associations between sports participation, body composition and physical activity from childhood to adolescence. Journal of Science and Medicine in Sport, 18, 178-182.
  5. Cohen, A., McDonald, S., McIver, K., Pate, R., & Trost, S. (2014). Assessing physical activity during youth sport: The observational system for recording activity in children: youth sports (OSRAC:YS). Pediatric Exercise Science, 26, 203-209.
  6. Dudley, D.A., Okely, A.D., Cotton, W.G., Pearson, P., & Caputi, P. (2012). Physical activity levels and movement skill instruction in secondary school physical education. Journal of Science and Medicine in Sport, 15, 231-237.
  7. Elkiran, O., Yilmaz, E., Koc, M., Kamanli, A., Ustundag, B., & Ilhan, N. (2013). The association between intima media thickness, central obesity and diastolic blood pressure in obese and overweight children: A cross-sectional school-based study. International Journal of Cardiology, 165, 528-532.
  8. Evenson, K.R., Catelier, D.J., Gill, K., Ondrak, K.S., & McMurray, R.G. (2008). Calibration of two objective measures of physical activity for children. Journal Sports Science, 24, 1557-1565.
  9. Giannini, C., de Giorgis, T., Scarinci, A., Ciampani, M., Marcovecchio, M.L., Chiarelli, F., & Mohn, A. (2008). Obese related effects of inflammatory markers and insulin resistance on increased carotid intima media thickness in pre-pubertal children. Athereoschlerosis, 197, 448-456.
  10. Guagliano, J.M., Lonsdale, C., Rosenkranz, R.R., Kolt, G.S., & George, E.S. (2014).  Do coaches perceive themselves as influential on physical activity for girls in organized youth sport? PLoS ONE 9(9): e105960. https://doi:10.1371/journal.pone.0105960.
  11. Guagliano, J.M., Lonsdale, C., Kolt, G.S., Rosenkranz, R.R., & George, E.S. (2015). Increasing girls’ physical activity during a short-term organized youth sport basketball program: a randomized controlled trial. Journal of Science and Medicine in Sport, 18, 412-417.
  12. Guagliano, J.M., Lonsdale, C., Rosenkranz, R.R., Parker, P.D., Agho, K.E., & Kolt, G.S. (2015). Mediators effecting moderate-to-vigorous physical activity and inactivity for girls from an intervention program delivered in an organized youth sports setting. Journal of Science and Medicine in Sport, 18, 678-683.
  13. Hales, C.M., Fryer, C.D., Carroll, M.D., Freedman, D.S., & Ogden, C.L. (2018). Trends in obesity and severe obesity prevalence in US youth and adults by sex and age, 2007-2008 to 2015-2016. Journal of American Medical Association, 319, 1723-1725.
  14. Institute for Sport Coaching (2010). The value of quality trained sport coaches. Acton, MA. Retrieved from http://www.instituteforsportcoaching.org/advocacy/workshops/
  15. Janssen, I. & LeBlanc, A.G. (2010). Systematic review of the health benefits of physical activity and fitness in school-aged children and youth. International Journal Behavior Nutrition Physical Activity, 7, 40-56.
  16. Landis, J.R. & Koch, G.G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33, 159-174.
  17. Landry, B.W. & Whateley Driscoll, S. (2012). Physical activity in children and adolescents. American Journal Physical Medicine Rehabilitation, 4, 826-832.
  18. Leek, D., Carlson, J.A., Cain, K.L., Henrichon, S., Rosenberg, D., Patrick, K., & Sallis, J.F. (2011). Physical activity during youth sport practices. Arch. Pediatr. Adolesc. Med., 165, 294-299.
  19. Loprinzi, P., Lee, H., Cardinal, B., Crespo, C., Anderson, R., & Smit, E. (2012). The relationship of Actigraph accelerometer cut-points for estimating physical activity with selected health outcomes. Research Quarterly for Exer. & Sport, 83, 422-430.
  20. McKenzie, T.L., Sallis, J.F., Prochaska, J.J., Conway, T.L., Marshall, S.J., & Rosengard, P. (2010). Evaluation of a two-year middle-school physical education intervention: M-SPAN. Med. Sci. Sports Exerc., 36, 1382-1388.
  21. Must, A. & Tybor, D.J. (2005). Physical activity and sedentary behavior: a review of longitudinal studies of weight and adiposity in youth. Int. J. Obes., 29, 584-596.
  22. National Council of Youth Sports (2008). Reports on trends and participation in organized youth sports. Retrieved from http://www.ncys.org/publications/2008-sports-participation-study.php
  23. Puhl, J., Greaves, K., Hoyt, M., & Baranowski, T. (1990). Children’s activity rating scale (CARS): Description and calibration. Res. Quart. Exerc. Sport, 61, 26-36.
  24. Robusto, K.M. & Trost, S.G. (2012). Comparison of three generations of Actigraph activity monitors in children and adolescents. J. Sports. Sci., 30, 1429-1435.
  25. Sacheck, J.M., Nelson, T., Ficker, L., Kafka, T., Kuder J., & Economos, C.D. (2011). Physical activity during soccer and its contribution to physical activity recommendations in normal weight and overweight children. Pediatric Exercise Science, 23, 281-292.
  26. Solomon, J. (2019, September 4). Staying in the game: Progress and challenges in youth sports. Retrieved from https://www.aspeninstitute.org/blog-posts/staying-in-the-game-progress-and-challenges-in-youth-sports/
  27. Strong, W.B., Malina, R.M., Blimkie, C.J.R., Daniels, S.R., Dishman, K., Gutin, B., & Trudeau, F. (2005). Evidence based physical activity for school-aged youth. J. Pediatr., 146, 732-737.
  28. Telford, R.M., Telford, R.D., Cochrane, T., Cunningham, R.B., Olive, L.S., & Davey, R. (2016). The influence of sport club participation on physical activity, fitness and body fat during childhood and adolescence: The LOOK longitudinal study. Journal of Science and Medicine in Sport, 19, 400-406.
  29. Theokas, C. (2009). Youth sport participation – A view of the issues: Introduction to the special section. Dev. Psychol., 45, 303-306.
  30. Troiano, R.P., Berrigan, D., Dodd, K.W., Masse, L.C., Tilbert, T., & McDowell, M. (2008). Physical activity in the United States measured by accelerometer. Med. Sci. Sports Exerc., 40, 181-188.
  31. Trost, S.G., Pate, R.R., Sallis, J.F., Freedson, P.S., Wendell, C.T., Dowda, M., & Sirard, J. (2002). Age and gender difference in objectively measured physical activity in youth. Med. Sci. Sports Exerc., 34, 350-355.
  32. Trost, S.G., McIver, K.L., & Pate, R.R. (2005). Conducting accelerometer-based activity assessments in field-based research. Med. Sci. Sports Exerc., 37, S531-S543.
  33. U.S. Department of Health and Human Services (2018). Physical Activity Guidelines for Americans, 2nd edition. Washington, D.C: U.S. Department of Health and Human Services.
  34. Verstraete, S.J.M., Cardon, G.M., De Clercq, D.L.R., De Bourdeaudhuij, I.M.M. (2007). Effectiveness of a two-year health-related physical education intervention in elementary schools. Journal of Teaching in Physical Education, 26, 20-34.
  35. Wickel, E.E. & Eisenmann, J.C. (2007). Contribution of youth sports to total daily physical activity among 6- to 12-yr-old boys. Med. Sci. Sports Exerc., 39, 1493-1500.
Print Friendly, PDF & Email