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Methods: Ten male participants performed RT tasks at rest, during and after cycling with three different workloads [40 %, 60 %, and 80 % peak oxygen uptake (VO2)] under either blinded normoxic [inspired fraction of oxygen (FIO2) = 0.21)] or hypoxic (FIO2 = 0.16) conditions.
Visual stimuli were randomly presented at 10° to either the right or left of the midpoint of the participant’s eyes. Cerebral oxygenation was continuously monitored over the right frontal cortex using near-infrared spectroscopy. In this study, RT was fractionated into premotor and motor components (Premotor time and Motor time) base on the onset of electromyogram recorded over the right forearm. We used Premotor time to assess the efficiency of central information processing.
Results: Under normoxia, Premotor time was significantly longer during exercise at 80% peak VO2 (mean ± SE; 214.2 ± 10.4 ms) relative
to that at rest (201.0 ± 8.6 ms) (p 0.05). Under hypoxia, Premotor time was significantly longer during exercise at all workloads (40%:
216.3 ± 8.8 ms, p 0.05; 60%: 216.1 ± 9.1 ms, p 0.05; 80%: 221.5 ± 9.5 ms, p 0.01) relative to that at rest (202.9 ± 9.4 ms). Increase in Premotor time during exercise was negatively correlated with corresponding cerebral oxygenation (r2 = 0.85, p 0.01) when data from normoxia and hypoxia were combined together.
Discussion: The results of the present study indicate that the increase in Premotor time to peripheral visual stimuli during exercise is closely associated with decrease in cerebral oxygenation. It is possible that decrease in oxygen availability and/or alteration of neurotransmitters turnover contributed to the detrimental effects of exercise under hypoxia. We conclude that cerebral oxygenation influences visual perceptual performance during exercise.
Reference Ando S, Kokubu M, Kimura T, Moritani T, Araki M (2008). Int J Sport Med, 29, 994-998.
14:00 - 15:30 Oral presentations OP-HF03 Health and Fitness 3
‘YOU NEED TO GET OUT MORE!’: SOCIAL AND PHYSICAL ENVIRONMENTS OF SEDENTARY AND ACTIVE BEHAVIOURS
OF YOUTH IN TWO CENTRAL-EASTERN EUROPEAN COUNTRIESSOOS, I., BIDDLE, S., HAMAR, P., SANDOR, I., SIMONEK, J.
1. UNIVERSITY OF SUNDERLAND, 2. LOUGHBOROUGH UNIVERSITY, 3, SEMMELWEIS UNIVERSITY, BUDAPEST, 4. BABES-BOLYAI UNIVERSITY,
CLUJ-NAPOCA, 5. CONSTANTINE THE PHILOSOPHER UNIVERSITY, NITRAIntroduction: There has been an increase in the study of sedentary behaviours in young people. Evidence shows that time spent in some sedentary behaviours may be associated with negative markers of health. However, in addition to studying the prevalence of sedentary behaviours, it is important to ascertain where such behaviours are taking place and whether different sedentary behaviours are intercorrelated. The main aim of this study, therefore, was to investigate the social and physical context of sedentary behaviours, as well as the interrelationships between behaviours.
Methods: Secondary school students (n=440), aged 13-18 years, from two countries (Romania n=313 and Slovakia n=127) were assessed.
Ecological momentary assessment was used in the form of a free-time diary and was administered across three weekdays in 2006The temporal factors and correlates of the key sedentary behaviours, the locations and the social context were analysed using SPSS
15.0 software package.
Results and Discussion: Temporal and location Results: TV viewing (97.45 min, s=65.14) occupied the most time of any single behaviour, followed by doing homework (91.51 min, s=60.91), active transport (40.68 min, s= 29.14), and sitting and taking (27.61 min, s=32.59).
Playing computer/ video games had a low mean score (15.0 min, s=34.84). Students spent most of their time in the bedroom (309.70 min, s=109.49) and living room (75.15 min, s=84.69), and much of their time alone (322.89 min, s=124.76), but also with friends (140.41 min, s=100.02), or with family (140.0 min, s=101.75).
Correlates of behaviours TV viewing negatively correlated with reading (r=-0.29*), active transport (r=-0.28*) and doing homework (r=-0.23*). Active transport also negatively correlated with using a computer (r=-0.22*). Playing computer/ video games positively correlated with cognitive hobbies (e.g.,
doing puzzles, playing cards) (r=0.20*) (* p0.001). Being outside was associated with more active behaviours (rs=0.21-0.44*) while being inside was associated with more sedentary behaviours.
Conclusion. Young people need to be encouraged to spend more time outside to reduce sedentary behaviours and increase physical activity.
THE EFFECTS OF A 2 YEAR SCHOOL-BASED PHYSICAL ACTIVITY AND DIETARY INTERVENTION PROGRAM ON PHYSICAL FITNESS AND BODY COMPOSITIONJOHANNSSON, E., HRAFNKELSSON, H., MAGNUSSON, K.
CENTER FOR RESEARCH IN SPORT AND HEALTH SCIENCES, UNIVERSITY OF ICELAND, REYKJAVÍK, ICELAND. SELTJARNARNES HEALTH CENTER,REYKJAVÍK, ICELAND.
INTRODUCTION: Overweight and obesity due to physical inactivity and unhealthy diet has become a widespread problem among children worldwide. The school setting has been suggested as an ideal platform to implement interventions that may tackle this problem.
This study compared BMI, body fat % and physical fitness (PF) level between two study groups of children born in 1999 (7 years old at baseline) before and after a two-year intervention period.
METHODS: Six elementary schools in Reykjavik Iceland were randomly assigned into either an intervention group or to serve as controls.
In 2006 children entering second grade at each participating school were invited to take part in the study. Participation of 268 children in some or all parts of the study produced 86% participation rate. At baseline and after a two-year intervention period the children‘s height and weight was measured. Whole body DEXA scans were run providing data on body composition, including body fat % and PF was assessed with a cycle ergometer, measured as watts/kg. Reliable data was observed from 170 children who participated in the three measurements at both time points. The main objective of the physical activity intervention was to better integrate physical activity and the schools’ curriculum. Further, to increase physical activity up to at least 1 hr/day each school day. Hence, between fall of 2006 and fall of 2008 the physical activity level at the intervention schools was progressively increased via teacher-led daily activities. A two-way repeated measure ANOVA was performed to assess a change in outcome measures with time in both groups. Data was analyzed using R version 2.6.2.
RESULTS: The mean BMI and body fat % were slightly, yet significantly lower among children in the intervention group at both time points, but there was no significant interaction between group and time for either variable. However, there was not a significant difference in PF between the groups at baseline. A group by time interaction was demonstrated when comparing pre and post intervention PF (p=0.048).
Children in the intervention group increased their PF capacity by 10% (2.49±0.58 watts/kg in 2006 to 2.74±0.53 watts/kg in 2008), while children in the control group increased their PF by 5% (2.36±.49 watts/kg in 2006 to 2.48±0.47 watts/kg in 2008). Similar yet not significant trends were observed when stratified by sex.
DISCUSSION: Our study suggests that the two-year school-based intervention program may have had positive effects on children‘s PF while no apparent effect was on children‘s BMI or body fat %. These results may add weight to the body of knowledge on how the school setting can effectively keep its children more active and healthier. Further analysis of the data may provide more specific reasons for this effect on children‘s fitness.
ASSOCIATION BETWEEN BODY FAT, SCREEN TIME AND PHYSICAL ACTIVITY IN 8-10 YEAR OLD CHILDREN EXCEEDING
ELECTRONIC MEDIA GUIDELINESGRAVES, L.E.F., RIDGERS, N.D., STRATTON, G.
LIVERPOOL JOHN MOORES UNIVERSITYOBJECTIVE: Previous associations between body fat, and, physical activity (PA) and screen time (ST), both predisposing factors for obesity (Myers, 2005), are limited by the use of body mass index as an indicator of adiposity, and pedometry or self-report as measures of PA (Kautiainen et al., 2005; Laurson et al., 2008). Using more sensitive methods this study examined associations of television viewing (TV), video gaming (VG), ST and PA on the percent total body fat (%BF) of children exceeding the daily recommended 2 hours of engagement with electronic media (American Academy of Pediatrics, 2001).
METHODS: A total of 47 primary school children (age mean 9.2, SD 0.6) provided at least 9 hours of accelerometry-derived habitual PA information on a minimum of 3 weekdays and 1 weekend day. Data were analysed using individually calibrated activity count thresholds for PA at 4km∙h-1 (PA4) and 8km∙h-1 (PA8), and a sedentary threshold of 100 counts per minute. Dual-energy x-ray absorptiometry (DEXA) was used to measure %BF. Weekday and weekend day TV and VG time were self-reported using a questionnaire, allowing calculation of a weekly estimate of each and ST (VG + TV). Correlations evaluated the strength of relationships between variables. Only significantly correlated variables were used in multiple linear regression and partial correlation analysis. This analysis helped explain the variance in %BF whilst controlling for age. Statistical significance was set at p0.05.
RESULTS: Based on body fat reference curves (McCarthy et al., 2006), 19.5% of the group were overfat (≥85th 95th centile) and 40.4% obese (≥95th centile). VG, TV and ST were not significantly correlated with %BF (r 0.2) or any PA variable (r -0.23), except TV (r = -0.41) and ST (r = -0.26) with PA8. %BF was significantly correlated with sedentary time (r = 0.264), PA4, PA8, PA4 and total PA (r
-0.3). Regression analysis showed only PA4 and total PA significantly predicted %BF. Subsequent partial correlations indicated PA4 and total PA explained 7.8% and 6.9% of the variance in %BF, respectively. A 1-minute increase in activity of intensity greater than 4km∙h-1, and total PA, is associated with a 0.062 (95% CI:
-0.118 to -0.005) and 0.044 (95% CI:
-0.087 to -0.001) decrease in %BF, respectively.
DISCUSSION: Stronger associations with %BF for PA variables compared to screen time variables suggest PA is a more important risk factor for overfat in children who exceed electronic media guidelines. Increasing total PA, and PA of intensity greater than 4km∙hwhich is equivalent to walking, should be targeted in interventions seeking to reduce %BF in children who report high media usage.
American Academy of Pediatrics (2001) Pediatrics 107 423-26 Kautiainen et al. (2005) Int J Obes 29(8) 925-33 Laurson et al. (2008) J Pediatr 153 209-14 McCarthy et al. (2006) Int J Obes 30 598-602 Myers (2005) J Am Diet Assoc 105 S79