Is there any relationship between physical activity level and patterns, and physical performance in children?

<p>Abstract</p> <p>Background</p> <p>It is often assumed that physical activity (PA) and physical performance during childhood and adolescence are beneficial for health during adulthood, but a positive relationship between PA and physical performance has not been precisely clarified in children. The lack or the weakness of the relationships between PA and physical performance could be due to the measure of PA. If the use of accelerometry is considered as an objective and common measure of PA, the real patterns of children's habitual PA must be reflected. The aim of this study was to investigate the relationship between the levels and patterns of PA assessed with high frequency accelerometry and physical performance in young children.</p> <p>Methods</p> <p>Eighty-six boys and 101 girls aged 6-12 years participated in this study. Physical activity was measured over a 7-day period, using a 5-s epoch. Physical performance was assessed by means of EUROFIT tests (anthropometrics, standing broad jump, the 10 × 5 meter shuttle run, the sit-and-reach, the handgrip, the number of sit-ups in 30 seconds, the 20-meter shuttle run).</p> <p>Results</p> <p>No relationship was found between PA and physical performance. In boys only, body fatness was negatively associated with vigorous PA (r = -0.38, p < 0.001) and very high PA (r = -0.35, p < 0.01), in contrast to light PA (r = 0.28, p < 0.01), which was positively related to body fatness.</p> <p>Conclusion</p> <p>In 6- to- 12 year- old children, the more active children were not the fittest. Our results also underline the need for uniformity in approach to measurement of PA, body composition and health-related fitness between studies.</p

The Relationships Between Skeletal Muscle Index and Bone Variables in a Group of Young Adults

International audienceThe purpose of this study was to investigate the relationships between skeletal muscle index (SMI) and bone variables in a group of young adults. Three hundred and thirty-five young adults (129 men and 206 women) whose ages ranged from 18 to 35 yr voluntarily participated in this study. Weight and height were measured, and body mass index (BMI) was calculated. Body composition, bone mineral content (BMC), bone mineral density (BMD), geometric indices of hip bone strength and trabecular bone score (TBS) were determined for each individual by Dual-energy X-ray absorptiometry (DXA). Appendicular skeletal mass (ASM, in kg) was calculated by summing the muscle masses of the 4 limbs, assuming that all nonfat and nonebone mass is skeletal muscle. Skeletal muscle index (SMI) was defined as ASM/height². In young men, SMI was positively correlated to WB BMC (r = 0.63; p < 0.001), WB BMD (r = 0.53; p < 0.001), L1-L4 BMC (r = 0.33; p < 0.001), L1-L4 BMD (r = 0.30; p < 0.001), L1-L4 TBS (r = 0.26; p < 0.01), TH BMC (r = 0.61; p < 0.001), TH BMD (r = 0.46; p < 0.001), FN BMC (r = 0.51; p < 0.001), FN BMD (r = 0.46; p < 0.001), FN cross-sectional area (CSA) (r = 0.56; p < 0.001), FN cross-sectional moment of inertia (CSMI) (r = 0.52; p < 0.001) and FN section modulus (Z) (r = 0.54; p < 0.001) but negatively correlated to FN strength index (SI) (r = -0.24; p < 0.01). In young women, SMI was positively correlated to WB BMC (r = 0.61; p < 0.001), WB BMD (r = 0.60; p < 0.001), L1-L4 BMC (r = 0.35; p < 0.001), L1-L4 BMD (r = 0.33; p < 0.001), L1-L4 TBS (r = 0.29; p < 0.001), TH BMC (r = 0.61; p < 0.001), TH BMD (r = 0.53; p < 0.001), FN BMC (r = 0.45; p < 0.001), FN BMD (r = 0.49; p < 0.001), FN CSA (r = 0.60; p < 0.001), FN CSMI (r = 0.52; p < 0.001), and FN Z (r = 0.40; p < 0.001) but negatively correlated to FN SI (r = -0.20; p < 0.01). The current study suggests that SMI is a positive determinant of bone mineral density and geometric indices of hip bone strength in young adults

Objectively assessed recess physical activity in girls and boys from high and low socioeconomic backgrounds

BackgroundThe school environment influences children&rsquo;s opportunities for physical activity participation. The aim of the present study was to assess objectively measured school recess physical activity in children from high and low socioeconomic backgrounds.MethodsFour hundred and seven children (6&ndash;11 years old) from 4 primary schools located in high socioeconomic status (high-SES) and low socioeconomic status (low-SES) areas participated in the study. Children&rsquo;s physical activity was measured using accelerometry during morning and afternoon recess during a 4-day school week. The percentage of time spent in light, moderate, vigorous, very high and in moderate- to very high-intensity physical activity were calculated using age-dependent cut-points. Sedentary time was defined as 100 counts per minute.ResultsBoys were significantly (p&thinsp;&lt;&thinsp;0.001) more active than girls. No difference in sedentary time between socioeconomic backgrounds was observed. The low-SES group spent significantly more time in light (p&thinsp;&lt;&thinsp;0.001) and very high (p&thinsp;&lt;&thinsp;0.05) intensity physical activity compared to the high-SES group. High-SES boys and girls spent significantly more time in moderate (p&thinsp;&lt;&thinsp;0.001 and p&thinsp;&lt;&thinsp;0.05, respectively) and vigorous (p&thinsp;&lt;&thinsp;0.001) physical activity than low-SES boys.ConclusionsDifferences were observed in recess physical activity levels according to socioeconomic background and sex. These results indicate that recess interventions should target children in low-SES schools.<br /

Commentaries on Viewpoint: Do oxidative and anaerobic energy production in exercising muscle change throughout growth and maturation?

International audienceTo examine cardiorespiratory fitness, resting cardiac parameters, and muscle oxygenation changes in soccer players having undergone anterior cruciate ligament reconstruction and to assess the benefits of a one-leg cycling (OLC) aerobic training program performed during the rehabilitation period

Are Intensified Physical Education Sessions Able to Elicit Heart Rate at a Sufficient Level to Promote Aerobic Fitness in Adolescents?

International audienceThepurpose of this study was to determine theeffects of intensifiedphysicaleducationsessions on adolescents ages 11-16years. Theyweredividedintotwoexperimentalgroups-high-intensity runninggroup(HIRG) and high-intensityjumpinggroup (HIJG)-and a controlgroup(C).During thesessions, heartrate(HR) wasmonitored. There wasnosignificantdifference between meanHRfor HIRG and HIJG, whilethemeanHR wassignificantlylowerfor C(p < .001). ForbothHIRG and HIJG, the mean H R was significantly higherfor girls than for bays (p < .001). Our results suggested that these intensified physical educationlessons require a highpercentage ofmaximal HR in adolescents and can beusedtoimproveaerobicfitnes

Defining Velocity and Acceleration Ranges for Time-Motion Analysis from a 7-Sided Game in U11 Soccer Players Using Global Positioning System Devices: A Case Study

International audienceThe aims of this study were (1) to define speed and acceleration thresholds from youth match activity of soccer players and (2) to analyze the activity performed by young soccer players during a match using GPS devices and according to these thresholds. Ten U11 soccer players from a professional club participated in a 7-sided match being equipped with global positioning system (GPS) devices (sampling frequency 5 Hz) to measure the speed of each player. The Kernel Density Estimate (KDE) was used to observe the occurrences of velocities. The range of velocities was described by a distribution curve, from which the speed and acceleration thresholds for each category of movement were defined and time–motion analysis of the match was made. The model with 4 Gaussian laws was the best when using the Akaike Information Criterion (AIC). In this study, the thresholds defined for each category of movement were: standing (< 0.1 km/h), walking (0.1–5.6 km/h), slow running (5.7–7.7 km/h), fast running (7.8–12.7 km/h) and sprint (≥ 12.8 km/h). Acceleration thresholds were calculated to define movement considered as a sprint for each category of movement: standing (0.3 m/s2), walking (0.66 m/s2), slow running (1.01 m/s2) or fast running (0.97 m/s2). All the acceleration thresholds were significantly different from each other (P < 0.001) with large effect sizes, excepting the comparison between slow and fast running (P = 0.41) with a small effect size. In U-11 soccer players, time–motion analysis may be performed according to five categories of movement. This study has also defined sprint and acceleration thresholds for this category of age

Suivi longitudinal de la condition physique de garçons et de filles entre 11 et 16 ans : relations avec le niveau d’activité physique

National audienceLes études épidémiologiques sur l'évolution du niveau d'activité physique des enfants et les interrelations entre condition physique, activité physique et santé ont surtout été conduites aux Etats-Unis1, mais il existe peu d'études longitudinales associant, les effets de la croissance, aux changements de la condition physique des enfants et des adolescents, et ceci tout particulièrement chez les jeunes Français. Les objectifs de cette étude étaient par conséquent d’analyser les évolutions et les relations entre ces paramètres lors d'un suivi longitudinal de 4 ans en milieu scolaire.Mille six cent et un enfants et adolescents, âgés de 11 à 16 ans ont participé à cette étude. Parmi cette population, un échantillon de 193 enfants (95 garçons et 98 filles) a été suivi pendant quatre ans de la classe de sixième (11,5 ± 0,6 ans, septembre 1997) à celle de troisième (15,4 ± 0,6 ans, juin 2001). Au début et en fin de chaque année scolaire, des mesures anthropométriques et 6 tests de terrain appartenant à la batterie Européenne de tests moteurs (EUROFIT)2 ont été réalisés. Les tests choisis étaient le saut en longueur sans élan (SLO), la course navette 10*5m (CNA), la flexion longitudinale du tronc (FLT), la dynamométrie manuelle (DYM), le nombre maximal de redressements en station assise effectués en 30 secondes (RSA) et le test de course en navette de 20m (NAV). Un formulaire de 50 à 80 questions3, selon l’âge des sujets, a été également présenté aux enfants, au début et à la fin de l’expérimentation, afin d’étudier les relations entre la condition physique, la santé et les modes de vie. À partir des questionnaires, les enfants ont été répartis, de façon rétrospective, en différents groupes suivant leur niveau d’activité physique.L'analyse de variance a indiqué que les performances aux tests de terrain sont significativement plus élevées (p < 0,001) chez les garçons, hormis la souplesse (FLT). Les gains de performances sont significativement plus importants chez les garçons que chez les filles, hormis FLT. Pour l’endurance abdominale (RSA), aucune différence significative entre les sexes n’a été trouvée. Les garçons sont davantage régulièrement actifs que les filles et il existe plus de filles que de garçons peu actifs. Toutefois, à la fin du suivi, la proportion d’inactifs avait augmenté de 9,5 à 15,8% et celle des régulièrement actifs de 31,6 à 39,2%. Chez les garçons, il n’existait aucune influence du niveau d'activité physique sur le niveau de condition physique, avant et après l’expérimentation. Par contre, chez les filles, l’analyse de variance (activité physique*condition physique) a montré une influence significative du niveau d’activité physique pour RSA (p < 0,05) et à la fin du suivi, pour SLO, FLT, RSA (p < 0,05) et CNA (p < 0,001).Si l’accroissement des performances est significativement inférieur chez les filles, leur niveau d’activité physique influence, de façon significative, certaines dimensions de la condition physique à l’adolescence

Energy Expenditure During School and Free Days in Children: A Focus on Recess

International audienceBackground: School recess time offers an opportunity for children to be physically active. This study objectively investigated the contribution of recess and break times to daily physical activity energy expenditure (PAEE). Methods: Participants included 18 children from an elementary school (11 girls, 7 boys). They wore an Actiheart (CamNtech, Cambridge, UK) for 3 days (2 week-days and one weekend day). This device recorded accel- erometry (ACC) and heart rate (HR) data using an epoch setting of 15 s. PAEE was estimated using the branched model equations (activity counts + HR). Physical activity level (PAL) was calculated following the ratio Total Energy Expenditure (TEE)/Resting Energy Expenditure (REE). During the school time, children’s PAEE during the two recess periods (RP PAEE) lasting about 15 min (morning and afternoon) and during the break time’s midday (11.30 am - 1.30 pm, BT PAEE) were also assessed. Results: Recess and break time’s midday represented 8.7% and 16.7% of the PAEE during school days in boys and 6.8% and 14% in girls, respectively. A relationship between BT PAEE and PAEE was found both in boys and in girls (r2 = 0.92, p<0.001 and r2 = 0.50, p<0.05, respectively) and between RP PAEE and PAEE in boys (r2=0.62, p<0.05). No relationship was found between school and free days for PAEE children. Discussion: Ridgers et al. (2011) have reported that recess contributed 17.9% and 15.6% toward boys’ and girls’ school day physical activity levels. In the present study, recess less contribute toward boys’ and girls’ school day PAEE. MVPA should not be the only outcome to be considered to show the impact of recess or recess interventions on physical activity. Reference: Ridgers ND, Saint-Maurice PF, Welk GJ, Siahpush M, Huberty J. Differences in physical activity during school recess

Fréquence cardiaque lors de séances d’éducation Physique intensifiées chez les adolescents

International audienc