- Email: [email protected]
Physical Activity, Fitness, Weight Status, and Cognitive Performance in Adolescents
Physical Activity, Fitness, Weight Status, and Cognitive Performance in Adolescents Jonatan R. Ruiz, PhD, Francisco B. Ortega, PhD, Ruth Castillo, BSc, Miguel Martı´n-Matillas, PhD, Lydia Kwak, PhD, German Vicente-Rodrı´guez, PhD, Jose Noriega, PhD, Pablo Tercedor, PhD, Michael Sjo¨stro¨m, MD, PhD, and Luis A. Moreno, MD, PhD , on behalf of the AVENA Study Group* Objective To examine the association of participation in physical sports activity during leisure time, sedentary behaviors, cardiorespiratory and muscular fitness, and weight status with cognitive performance in Spanish adolescents. Study design This cross-sectional study comprised a total of 1820 adolescents (958 female) aged 13.0 to 18.5 years. Cognitive performance (verbal, numeric and reasoning abilities, and an overall score) was measured with the ‘‘SRA-Test of Educational Ability.’’ Participation in physical sports activity during leisure time (yes/no) and time devoted to study, television viewing, and playing video games were self-reported and categorized as #3 hours/day and >3 hours/day. We assessed cardiorespiratory and muscular fitness with field-based tests. Adolescents were classified as underweight, normal weight, overweight, and obese. Results Participation in physical sports activities during leisure time was associated with better cognitive performance study variables (all P < .001), independent of potential confounders including cardiorespiratory fitness and body mass index. We did not observe an association of time devoted to study, television viewing, or playing videogames with cognitive performance. Likewise, cognitive performance was similar across cardiorespiratory and muscular fitness levels and body weight categories. Conclusion Participation in physical sports activity during leisure time may positively influence cognitive performance in adolescents. (J Pediatr 2010;157:917-22).
T
here is increasing evidence that regular physical activity has positive effects on brain health and that it delays cognitive decline in adults.1 Whether this effect also apply to young people is not clear. Results from cross-sectional studies indicate a positive association between physical activity and academic performance in children.2,3 Findings from interventional studies also show that children in the physical activity intervention group have at least similar academic performance compared with children in the control group, despite a substantial reduction in time devoted to academics.2,3 Less is known, however, about the association between physical activity and specific cognitive abilities during adolescence, a period of life when the brain has profound plasticity.4 The effect that sedentary behaviors have on cognitive performance is of concern. Increased television viewing time is associated with worse academic performance in children5-7 and adolescents,8 yet playing action video games seems to improve cognitive performance in adults.9-11 Both cardiorespiratory fitness and fatness are considered important health From the Department of Medical Physiology, School of markers already in both children and adolescents.12,13 The association between Medicine, University of Granada, Granada, Spain (J.R., 3 F.O.); Unit for Preventive Nutrition, Department of physical fitness and cognitive performance in adolescents is contradictory. EtBiosciences and Nutrition at NOVUM, Karolinska Institutet, Huddinge, Sweden (J.R., F.O, L.K., M.S.); nier et al 14 concluded from a meta-analysis that there is no evidence for an asDepartment of Basic Psychology, School of Psychology, sociation between cardiorespiratory fitness and cognitive performance in adults, University of Malaga, Malaga, Spain (R.C.); Department 2 of Physical Education and Sport, School of Sport whereas Hillman et al provided evidence that cardiorespiratory fitness can have Sciences, University of Granada, Granada, Spain (M.M-M., P.T.); Department of Physiotherapy and a positive effect on cognitive performance, at least in pre-pubertal children. The Nursing, School of Health and Sport Sciences, University of Zaragoza, Huesca, Spain (G.V-R.); Department of association between overweight or obesity and cognitive performance in youth is Pediatrics, University of Cantabria, Santander, Spain 15-19 also inconclusive. (J.N.); and Department of Physiotherapy and Nursing, School of Health Sciences, University of Zaragoza, Zaragoza, Spain (L.M.)
ANCOVA AVENA BMI CI OR SD TEA VO2max
One-way analysis of covariance [Alimentacio´n y Valoracio´n del Estado Nutricional de los Adolescentes Espan˜oles] Food and Assessment of the Nutritional Status of Spanish Adolescents study Body mass index Confidence interval Odds ratio Standard deviation Test of Educational Ability Maximum oxygen consumption
*List of members of the AVENA Study Group available at www.jpeds.com (Appendix). Supported by the Spanish Ministry of Health (FIS no 00/ 0015), the Spanish Ministry of Education (grants EX2007-1124 and EX-2008-0641), Panrico S.A., Madaus S.A., Procter and Gamble S.A, the Swedish Council for Working Life and Social Research (F.S.), the Swedish Heart-Lung Foundation (20090635), and the Spanish Ministry of Health: Maternal, Child Health and Development Network (RD08/0072). The authors declare no conflicts of interest. 0022-3476/$ - see front matter. Copyright Ó 2010 Mosby Inc. All rights reserved. 10.1016/j.jpeds.2010.06.026
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Most of the aforementioned studies rely on self-reported data of academic performance, and did not control for potential confounders such as socioeconomic status and family structure.20,21 In this study, we examined the association of participation in physical sports activity during leisure time, sedentary behaviors (time devoted to study, television viewing, and playing videogames), cardiorespiratory and muscular fitness, and weight status with cognitive performance (including verbal, numeric and reasoning abilities, and an overall score) in Spanish adolescents. We also examined the relationships in the studied lifestyle-related factors and how these contribute to better understand the lifestyle-cognitive performance associations in adolescents.
Methods Participants were recruited from the AVENA (Alimentacio´n y Valoracio´n del Estado Nutricional de los Adolescentes Espan˜oles [Food and Assessment of the Nutritional Status of Spanish Adolescents]) study. The AVENA study is a crosssectional study that was primarily designed to assess the nutritional status of a representative sample of Spanish adolescents aged 13.0 to 18.5 years. Data collection took place from 2000 to 2002 in 5 Spanish cities (Madrid, Murcia, Granada, Santander, and Zaragoza). The complete methodology of the AVENA study has been detailed.22,23 This study included adolescents with complete data on cognitive performance (n = 1820; 958 female). The study sample did not differ from the complete AVENA sample (n = 2894) in any of the demographic variables (all P > .1). A comprehensive verbal description of the nature and purpose of the study was given to the parents, school supervisors, and adolescents. Written consent to participate was requested from both parents and adolescents. Adolescents with a personal history of cardiovascular disease or cognitive dysfunction, who were taking medication at the time of the study, or who were pregnant, were excluded. The study protocol was performed in accordance with the ethical standards laid down in the 1961 Declaration of Helsinki (as revised in 2000), and approved by the Review Committee for Research Involving Human Subjects of the Hospital Universitario Marque´s de Valdecilla (Santander, Spain). We used the Spanish version of the ‘‘SRA Test of Educational Ability’’ (TEA) to assess cognitive performance.24 This questionaire assesses intelligence with 3 basics school skills: verbal, numeric, and reasoning. The TEA test battery provides 3 complexity levels: level 1 for children aged 8 to 12 years, level 2 for children aged 11 to 14 years, and level 3 for adolescents aged 14 to 18 years. On the basis of the age range of our sample, we used levels 2 and 3. The psychometric properties of level 2 TEA test battery showed an internal consistency reliability of a = 0.78 for the verbal component, a = 0.83 for the numeric component, a = 0.88 for the reasoning component, and a = 0.92 for overall cognitive performance. For level 3, internal consistency reliability was a = 0.74 for the verbal component, a = 0.87 for the nu918
Vol. 157, No. 6 meric component, a = 0.77 for the reasoning component, and a = 0.89 for overall cognitive performance. The TEA battery administration is collective and requires 42 and 27 minutes for level 2 and 3, respectively. Verbal ability assesses command of language, verbal identification, and vocabulary; numeric ability assesses speed and precision in performing operations with numbers and quantitative concepts; and reasoning ability assesses logical ordination criteria in sets of figures, numbers, or letters. Direct scores (range, 0-33) were obtained for each of these variables, and we also computed an overall cognitive performance variable by summing the individual scores of the 3 items (range, 0-99). The adolescents answered the following question: ‘‘Do you practice any type of physical sports activity outside the school time?’’ The possible answers were yes (coded as 1) or no (coded as 0). We obtained the information about time devoted to study and time spent in television viewing and playing video games from the following questions: ‘‘How many hours a day do you do homework or study?’’ ‘‘How many hours a day do you watch television?’’ and ‘‘How many hours a day do you play videogames?’’ Possible answers were 0 = none, 1 = <30 minutes, 2 = <1 hour, 3 = 1 to 3 hours, 4 = >3 to 4 hours, 5 = >4 hours. Because of the relatively small sample size in each single category, we re-coded the variables in two categories: 0 when #3 hours/day and 1 when >3 hours/day.25 We assessed cardiorespiratory fitness with the 20-minute shuttle run test. The score was considered as the number of stages completed (precision of 0.5 stage). We estimated maximal oxygen consumption (VO2max) (mLO2/kg/min) with the equation reported by Le`ger.26 Adolescents were classified in two levels (ie, meeting/not meeting the cardiorespiratory fitness standards) on the basis of the FITNESSGRAM standards for Healthy Fitness Zone.27 The FITNESSGRAM standards are associated with cardiovascular disease risk factors in children and adolescents,28,29 and it would be of clinical and public health importance to understand whether they are also associated with cognitive performance. This test is valid and reliable in young people.30,31 Upper body muscular strength was assessed by means of the handgrip strength test. The test was performed on both hands with a hand dynamometer (Takei TKK 5101 Grip-D; Takey, Tokyo, Japan), standing and with the arm completely extended. The test was performed twice, and the best score was retained (in kg). The sum of the right and left hand was used in the analysis. Lower body muscular strength was assessed by means of the standing long jump test. The participants were instructed to push off vigorously and jump as far forward as possible, trying to land on both feet. The distance from the takeoff line to the point where the back of the heel closest to the take-off line landed on the floor was scored. The result was recorded in centimeters. The test was performed twice, and the best score was retained. Adolescents were classified in two levels according to their upper and lower body muscular strength levels as below (low) and above (high) the median. The handgrip Ruiz et al
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December 2010 strength and stranding long jump tests are valid and reliable field-based tests in children and adolescents.30-32 Weight and height were measured following standardized procedures, and body mass index (BMI) was calculated as weight in kilograms divided by square of height in meters (kg/m2). BMI was used as a surrogate marker of total body fat. Adolescents were classified according to the BMI international cutoff values as underweight, normal weight, overweight, and obese.33,34 Parents completed a questionnaire that addressed the adolescents’ earlier and current health status and socioeconomic status defined as the educational level and occupation of the father. According to this information, and following the recommendation of the Spanish Society for Epidemiology, the adolescents were classified in 5 categories of socioeconomic status: low (I), medium-low (II), medium (III), medium-high (IV), and high (V). We also obtained information on maternal education level (primary, secondary, or university). There is evidence indicating that socioeconomic status is one of the most important determinants of childhood cognitive performance.20 We obtained information about family structure through the aforementioned questionnaire. Family structure was defined as living with parents or any other arrangement (only mother, only father, grandparents, others). Family structure may positively influence adolescents’ cognitive performance.21 We assessed pubertal development according to Tanner and Whitehouse.35 Self-reported breast development in girls and genital development in boys was used for pubertal stage classification. Statistical Analysis Data are presented as means and SDs, unless otherwise indicated. Analyses were performed with the Statistical Package for Social Sciences software version 16.0 for Windows (SPSS, Chicago, Illinois) and the level of significance was set to 0.05. We analyzed the differences in cognitive performance (including verbal, numeric, and reasoning abilities and an overall score) between adolescents who participated in physical sports activity and adolescents who did not with one-way analysis of covariance (ANCOVA) after adjusting for age and pubertal status (model 1). We performed a second model
further including socioeconomic status and family structure as co-variates (model 2). We repeated the same model for the other exposures (ie, watching television, playing videogames, and time devoted to study #3 hours/day versus >3 hours/ day), cardiorespiratory and muscular fitness (low versus high), and weigh status (underweight, normal weight, overweight, and obese). Because we did not observe an interaction effect between sex * exposure variables and cognitive performance (all P > .2), all the analyses were performed with boys and girls together and sex was included in the analyses as a co-variate. We performed separate models for each main exposure, and sex, age and pubertal status were always retained as co-variates (in model 1), whereas socioeconomic status and family structure were additionally included as covariates in model 2. We also analyzed the associations in exposures with binary logistic regression analysis. Further, we determined the differences in cardiorespiratory fitness, muscular strength, and BMI among adolescents who participated in physical sports activity, those who did not, and those spending >3 hours/ day watching television or playing videogames with ANCOVA. All the models included sex, age, and pubertal status as co-variates. We calculated the effect size statistics as Cohen d (standardized mean differences) and 95% CI.36 Values of d equal to 0.2, 0.5, and 0.8 are considered small, medium, and large effects, respectively.
Results Adolescents engaged in physical sports activities during leisure time had significantly better cognitive performance that those who were not (Table I, model 1). The effect size, as determined with Cohen d, ranged from 0.25 (verbal ability) to 0.32 (overall cognitive performance). The results did not change when socioeconomic status and family structure were entered in the model (Table I, model 2). Further adjustments for cardiorespiratory fitness, BMI, and television viewing (or video games or time devoted to study) did not materially modify the results (data not shown). Similarly, when maternal educational status was used instead of socioeconomic status, the findings remained unaltered. We did not observe an association of time devoted to study, television viewing, or playing videogames with cognitive
Table I. Cognitive performance by participation in physical sports activity during leisure time in adolescents Model 1
Overall cognitive performance (0-99) Verbal ability (0-33) Numeric ability (0-33) Reasoning ability (0-33)
Model 2
Yes (n = 1053)
No (n = 506)
P
Cohen’s d (95% CI)
Yes (n = 817)
No (n = 393)
P
Cohen’s d (95% CI)
54.7 (13.0)
50.1 (13.5)
<.001
0.32 (0.221-0.421)
55.0 (14.3)
51.4 (13.9)
<.001
0.25 (0.139-0.365)
21.4 (6.5) 14.6 (3.2) 18.6 (6.5)
19.8 (6.7) 13.1 (4.5) 17.2 (6.7)
<.001 <.001 <.001
0.25 (0.153-0.353) 0.29 (0.191-0.391) 0.26 (0.160-0.360)
21.5 (5.7) 14.8 (5.7) 18.8 (5.6)
20.4 (5.9) 13.3 (5.8) 17.7 (5.7)
.006 <.001 .003
0.18 (0.063-0.289) 0.27 (0.153-0.380) 0.19 (0.076-0.303)
Values are means (SD). Covariates model 1: sex, age, and pubertal status. Covariates model 2: model 1 plus socioeconomic status and family structure.
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Table II. Cognitive performance and sedentary behaviors in adolescents Model 1
Study Overall cognitive performance (0-99) Verbal ability (0-33) Numeric ability (0-33) Reasoning ability (0-33) Television viewing Overall cognitive performance Verbal ability Numeric ability Reasoning ability Playing videogames Overall cognitive performance Verbal ability Numeric ability Reasoning ability
Model 2
£3 hours/day
>3 hours/day
(n = 1207) 53.3 (13.9) 20.8 (6.3) 14.1 (4.9) 18.3 (5.6) (n = 1392) 53.3 (13.8) 20.9 (6.0) 14.1 (4.9) 18.3 (5.6) (n = 1483) 53.4 (13.9) 20.9 (6.2) 14.1 (5.0) 18.3 (5.4)
(n = 353) 53.3 (14.3) 21.2 (6.2) 14.0 (5.1) 18.1 (5.6) (n = 177) 52.1 (13.3) 20.5 (6.3) 13.8 (4.9) 17.8 (5.7) (n = 85) 51.3 (14.2) 20.1 (6.3) 13.4 (5.0) 17.8 (5.7)
P .969 .325 .568 .632 .255 .341 .484 .244 .194 .218 .208 .447
£ 3 hours/day
<3 hours/day
(n = 928) 54.1 (13.7) 21.1 (6.1) 14.3 (4.9) 18.6 (5.5) (n = 1096) 53.8 (13.6) 21.1 (6.0) 14.2 (4.6) 18.5 (5.6) (n = 1161) 53.9 (13.6) 21.1 (6.1) 14.3 (4.8) 18.5 (5.5)
(n = 290) 53.6 (13.8) 21.2 (6.1) 14.1 (4.9) 18.2 (5.6) (n = 125) 54.7 (13.8) 21.4 (6.1) 14.6 (4.9) 18.7 (5.6) (n = 61) 54.7 (13.9) 21.0 (6.2) 14.7 (4.9) 19.1 (5.6)
P .599 .711 .441 .307 .510 .643 .457 .651 .648 .856 .534 .439
Covariates model 1: sex, age and pubertal status. Covariates model 2: model 1 plus socioeconomic status and family structure.
performance (Table II). Likewise, cardiorespiratory fitness was not associated with cognitive performance (Figure 1; available at www.jpeds.com). The results did not materially change when we used a different equation to estimate cardiorespiratory fitness (VO2max).37 Neither upper body nor lower body muscular strength were associated with cognitive performance (Figures 2 and 3; available at www. jpeds.com), and the results persisted after we repeated the analysis comparing the upper and lower sex- and agespecific quintiles (data not shown). Cognitive performance was similar across weight status categories (Figure 4; available at www.jpeds.com). We did not observe an association between physical sports activity and time devoted to study (odds ratio [OR], 0.818; 95% CI, 0.630-1.064). Participation in physical sports activity during leisure time was associated with a lower OR of watching television for >3 hours/day (0.631; 95% CI, 0.445-0.894) and playing videogames for >3 hours/day (0.533; 95% CI, 0.320-0.887). Adolescents participating in physical sports activity had better cardiorespiratory and muscular fitness levels compared with those who did not for cardiorespiratory fitness (5.9 2.0 versus 4.9 1.9 stages, respectively; P < .001), standing long jump (177 31 versus 154 28 cm, respectively; P < .001), and handgrip strength (61.1 0.4 versus 59.6 0.5 cm, respectively; P = .023). BMI did not differ in physical sports activity categories (P = .606). Adolescents who spent >3 hours/day watching television tended to have a lower OR of spending >3 hours/day studying (0.629; 95% CI, 0.384-1.029). Adolescents who spent <3 hours/day playing video games had a significantly lower OR of spending >3 hours/day studying (0.375; 95% CI, 0.1470.959). Levels of cardiorespiratory fitness were lower in adolescents who spent >3 hours/day watching television compared with adolescents who spent #3 hours/day watching television (4.9 1.3 versus 5.6 2.1 stages, respectively; P < .001) and so were standing long jump levels (162 31 versus 169 32 cm, respectively; P = .019). BMI was higher in ad920
olescents who spent >3 hours/day watching television compared with those who spent #3 hours/day (22.4 3.4 versus 21.5 3.2 kg/m2, respectively; P = .002), regardless of sex, age, and puberty stage. Adolescents who played videogames for >3 hours/day had lower cardiorespiratory fitness compared with their peers who spent #3 hours/day (4.5 1.0 versus 5.6 2.2 stages, respectively; P < .001). The results were similar when we repeated all the analyses in boys and girls separately.
Discussion Although no conclusion can be drawn from this cross-sectional study about whether participation in physical sports activity during leisure time leads to improvements in cognitive performance in adolescents, these findings are of public health and clinical interest and extend earlier results that suggested the potential benefit of physical activity on cognitive performance already in youth.2,3 Adolescence is a period of life when the brain has profound plasticity because of changes in both structure and function.4 Therefore, the pubertal period offers high possibilities of stimulating cognitive function.4 The relationship between participation in physical sports activity and cognitive performance has been a subject of discussion between advocates and skeptics of physical sports activity, and especially in parents concerned about decreases in study and homework time. The assumption is based on the participation in physical sports activity may ‘‘displace’’ time that would normally be spent doing schoolwork, reading for pleasure, or engaging in other educational activities. In this study, we observed that participation in physical sports activity is not associated with lower time devoted to study. This concurs with intervention studies that indicated that children enrolled in more physical sports activity do not have poorer academic performance, despite a reduction in time in the so-called ‘‘academic subjects.’’3 Furthermore, we also observed that participation in physical sports activity was associated with lower television viewing and time Ruiz et al
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December 2010 devoted to play video games and with higher levels of cardiorespiratory and muscular fitness. This suggest that physical sports activity may indirectly prevent the deleterious effects ascribed to sedentary behaviors39, 40 and may have an indirect positive effect on health through its effect on fitness. Findings from intervention studies also reported a positive effect on fitness besides the aforementioned effects on academic performance.3 Even single bouts of physical activity (20 minutes of aerobic exercise at 60% of estimated maximum heart rate) may improve cognitive control and attention in children.41 Collectively, these findings are particularly important because of the existing pressure on children and adolescents, parents, and schools to maximize academic performance. We do not know whether sports participation is a marker of adolescents who are high achievers and who do better in this type of cognitive tests. Moreover, whether adolescents who persist in sports activity have other characteristics that allow them to perform well on cognitive tests remains to be elucidated. There is increasing concern about the amount of time that youth spend watching television or playing video games because of the potential effect they may have on health. Indeed, we observed that both television viewing and playing video games had a negative effect on cardiorespiratory fitness, lower body muscular strength, and BMI. Several studies reported an association between increased television viewing and decreased time spent reading and doing homework,42,43 which in turn may affect academic performance. Results from crosssectional and longitudinal studies reported that increased television time had a detrimental impact on academic performance in children5-7 and self-reported academic performance in adolescents.8 We observed that adolescents who spent more time watching television or playing video games devoted less time to study, which concurs with the so called ‘‘displacement hypothesis.’’44 However, despite this observation, we did not observe an association between television time and cognitive performance. Our data do not concur with experimental studies showing that playing action video games improve cognitive performance in young adults.9,10 Differences in the outcome variable, the participants’ age, and the study design make comparisons between studies difficult. Cardiorespiratory fitness is strongly linked to cardiovascular disease risk factors in youth.12,13 Whether it is also associated with cognitive performance is, however, debated. The conclusion from a meta-regression analysis was that cardiorespiratory fitness was not associated with cognitive performance in adults,14 which concur with our results, whereas other studies suggested the opposite in children.2 Hillman and co-workers showed in a series of studies that high cardiorespiratory fitness was associated with better cognition in pre-adolescent children.19,45,46 Several studies hypothesized that aerobic fitness may mediate the relationship between physical activity and cognitive performance,47 whereas other studies argued that cardiorespiratory fitness is a ‘‘‘gross’’ measure of the physiological status and therefore might not be sensitive enough for one to see any association with cognitive performance.14 The association between physical
sports activity and cognitive performance observed in this study persisted after further adjusting for either cardiorespiratory or muscular fitness. Whether more precise measurements of both cardiorespiratory fitness (ie, directly measured maximum oxygen consumption) and cognitive function (eg, electroencephalogram, neuroelectric activity) would yield to a different results in adolescents remains to be investigated.45 We did not observe an association between muscular fitness and cognitive performance, which concur with the results observed by other authors.19 A limited number of studies have examined whether increased body weight per se is associated with poorer cognitive performance.15-19 We did not observe an association between weight status and cognitive performance, which concurs with other studies.17,18 Overweight children and adolescents have lower cognitive performance than normal-weight ones after adjusting for a number of potential confounders.16 Mosuwan et al17 observed an association between overweight status and poor academic performance in children, but not in adolescents. Severely obese Chinese children had significantly lower intelligence quotient than the control subjects.15 Children with higher cognitive function in early life can be at decreased risk of overweight years later.48 Limitations of this study include its cross-sectional design, which precludes drawing conclusions on the direction of the associations. A second limitation relies on the use of a selfreported measure of physical sports activity. Moreover, this study focused only on sports-related activity, and therefore, the duration of the participation and other leisure time physical activity was not recorded. Further research should use physical activity assessed with objective measures such as accelerometry. We did not have data on watching television during weekends, which limited the analysis. We also did not ask what kinds of video games adolescents play. Strengths of this study include the use of a relatively large national sample, the inclusion of several potential confounders, and the use of an objective and standardized measure of cognitive performance. Because cognitive performance is potentially modifiable during the pubertal phase,4 it would be of interest to investigate whether targeted physical activity interventions especially on individuals with cognitive impairment might influence cognitive performance during adolescence and later in life. n Submitted for publication Feb 16, 2010; last revision received Apr 30, 2010; accepted Jun 16, 2010. Reprint requests: Jonatan R. Ruiz, PhD. Department of Biosciences and Nutrition, Unit for Preventive Nutrition, Karolinska Institutet, Stockholm, Sweden, Ha¨lsova¨gen 7-9, SE-141 57 Huddinge, Sweden. E-mail: [email protected].
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3. Trudeau F, Shephard RJ. Physical education, school physical activity, school sports and academic performance. Int J Behav Nutr Phys Act 2008;5:10. 4. Romeo RD, McEwen BS. Stress and the adolescent brain. Ann N Y Acad Sci 2006;1094:202-14. 5. Borzekowski DL, Robinson TN. The remote, the mouse, and the no 2 pencil: the household media environment and academic achievement among third grade students. Arch Pediatr Adolesc Med 2005;159:607-13. 6. Zimmerman FJ, Christakis DA. Children’s television viewing and cognitive outcomes: a longitudinal analysis of national data. Arch Pediatr Adolesc Med 2005;159:619-25. 7. Hancox RJ, Milne BJ, Poulton R. Association of television viewing during childhood with poor educational achievement. Arch Pediatr Adolesc Med 2005;159:614-8. 8. Sharif I, Sargent JD. Association between television, movie, and video game exposure and school performance. Pediatrics 2006;118:e1061-70. 9. Green CS, Bavelier D. Action video game modifies visual selective attention. Nature 2003;423:534-7. 10. Boot WR, Kramer AF, Simons DJ, Fabiani M, Gratton G. The effects of video game playing on attention, memory, and executive control. Acta Psychol (Amst) 2008;129:387-98. 11. Owen AM, Hampshire A, Grahn JA, Stenton R, Dajani S, Burns AS, et al. Putting brain training to the test. Nature 2010;465:775-8. 12. Ortega FB, Ruiz JR, Castillo MJ, Sjostrom M. Physical fitness in childhood and adolescence: a powerful marker of health. Int J Obes (Lond) 2008;32:1-11. 13. Ruiz JR, Castro-Pinero J, Artero EG, Ortega FB, Sjostrom M, Suni J, et al. Predictive validity of health-related fitness in youth: a systematic review. Br J Sports Med 2009;43:909-23. 14. Etnier JL, Nowell PM, Landers DM, Sibley BA. A meta-regression to examine the relationship between aerobic fitness and cognitive performance. Brain Res Rev 2006;52:119-30. 15. Li X. A study of intelligence and personality in children with simple obesity. Int J Obes Relat Metab Disord 1995;19:355-7. 16. Li Y, Dai Q, Jackson JC, Zhang J. Overweight is associated with decreased cognitive functioning among school-age children and adolescents. Obesity (Silver Spring) 2008;16:1809-15. 17. Mo-suwan L, Lebel L, Puetpaiboon A, Junjana C. School performance and weight status of children and young adolescents in a transitional society in Thailand. Int J Obes Relat Metab Disord 1999;23:272-7. 18. Datar A, Sturm R, Magnabosco JL. Childhood overweight and academic performance: national study of kindergartners and first-graders. Obes Res 2004;12:58-68. 19. Castelli DM, Hillman CH, Buck SM, Erwin HE. Physical fitness and academic achievement in third- and fifth-grade students. J Sport Exerc Psychol 2007;29:239-52. 20. Lawlor DA, Najman JM, Batty GD, O’Callaghan MJ, Williams GM, Bor W. Early life predictors of childhood intelligence: findings from the Mater-University study of pregnancy and its outcomes. Paediatr Perinat Epidemiol 2006;20:148-62. 21. Riesch SK, Anderson LS, Krueger HA. Parent-child communication processes: preventing children’s health-risk behavior. J Spec Pediatr Nurs 2006;11:41-56. 22. Gonzalez-Gross M, Castillo MJ, Moreno L, Nova E, GonzalezLamuno D, Perez-Llamas F, et al. Alimentacion y valoracion del estado nutricional de los adolescentes espanoles (estudio AVENA). Evaluacion de riesgos y propuesta de intervencion. I. descripcion metodologica del proyecto. Nutricion Hospitalaria 2003;18:15-28. 23. Ortega FB, Ruiz JR, Castillo MJ, Moreno LA, Gonzalez-Gross M, Warnberg J, et al. [Low level of physical fitness in Spanish adolescents. Relevance for future cardiovascular health (AVENA study)]. Rev Esp Cardiol 2005;58:898-909. 24. Thurstone L, Thurtone T. SRA Test of Educational Ability. Chicago: Science Research Associates; 1958. 25. Pate RR, Wang CY, Dowda M, Farrell SW, O’Neill JR. Cardiorespiratory fitness levels among US youth 12 to 19 years of age: findings from the 1999-2002 National Health and Nutrition Examination Survey. Arch Pediatr Adolesc Med 2006;160:1005-12. 922
Vol. 157, No. 6 26. Leger LA, Mercier D, Gadoury C, Lambert J. The multistage 20 metre shuttle run test for aerobic fitness. J Sports Sci 1988;6:93-101. 27. Cureton KJ, Warren GL. Criterion-referenced standards for youth health-related fitness tests: a tutorial. Res Q Exerc Sport 1990;61:7-19. 28. Ruiz JR, Ortega FB, Rizzo NS, Villa I, Hurtig-Wennlo¨f A, Oja L, et al. High cardiovascular fitness is associated with low metabolic risk score in children: the European Youth Heart Study. Pediatr Res 2007;61:350-5. 29. Lobelo F, Pate RR, Dowda M, Liese AD, Ruiz JR. Validity of cardiorespiratory fitness criterion-referenced standards for adolescents. Med Sci Sports Exerc 2009;41:1222-9. 30. Ortega FB, Artero EG, Ruiz JR, Vicente-Rodriguez G, Bergman P, Hagstromer M, et al. Reliability of health-related physical fitness tests in European adolescents. The HELENA Study. Int J Obes (Lond) 2008;32 Suppl. 5:S49–S57. 31. Castro-Pinero J, Artero EG, Espana-Romero V, Ortega FB, Sjostrom M, Suni J, et al. Criterion-related validity of field-based fitness tests in youth: a systematic review. Br J Sports Med 2009 [Epub ahead of print]. 32. Espana-Romero V, Ortega FB, Vicente-Rodriguez G, Artero EG, Rey JP, Ruiz JR. Elbow position affects handgrip strength in adolescents: validity and reliability of Jamar, DynEx, and TKK dynamometers. J Strength Cond Res 2010;24:272-7. 33. Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ 2000;320:1240-3. 34. Cole TJ, Flegal KM, Nicholls D, Jackson AA. Body mass index cut offs to define thinness in children and adolescents: international survey. BMJ 2007;335:194. 35. Tanner JM, Whitehouse RH. Clinical longitudinal standards for height, weight, height velocity, weight velocity, and stages of puberty. Arch Dis Child 1976;51:170-9. 36. Nakagawa S, Cuthill IC. Effect size, confidence interval and statistical significance: a practical guide for biologists. Biol Rev Camb Philos Soc 2007; 82:591-605. 37. Ruiz JR, Ramirez-Lechuga J, Ortega FB, Castro-Pinero J, Benitez JM, Arauzo-Azofra A, et al. Artificial neural network-based equation for estimating VO(2max) from the 20m shuttle run test in adolescents. Artif Intell Med 2008;44:233-45. 38. Cotman CW, Berchtold NC. Exercise: a behavioral intervention to enhance brain health and plasticity. Trends Neurosci 2002;25:295-301. 39. Ekelund U, Brage S, Froberg K, Harro M, Anderssen SA, Sardinha LB, et al. TV viewing and physical activity are independently associated with metabolic risk in children: the European Youth Heart Study. PLoS Med 2006;3:e488. 40. Rey-Lopez JP, Vicente-Rodriguez G, Biosca M, Moreno LA. Sedentary behaviour and obesity development in children and adolescents. Nutr Metab Cardiovasc Dis 2008;18:242-51. 41. Hillman CH, Pontifex MB, Raine LB, Castelli DM, Hall EE, Kramer AF. The effect of acute treadmill walking on cognitive control and academic achievement in preadolescent children. Neuroscience 2009;159:1044-54. 42. Wiecha JL, Sobol AM, Peterson KE, Gortmaker SL. Household television access: associations with screen time, reading, and homework among youth. Ambul Pediatr 2001;1:244-51. 43. Wolfe DA, Mendes MG, Factor D. A parent-administered program to reduce children’s television viewing. J Appl Behav Anal 1984;17:267-72. 44. Anderson DR, Huston AC, Schmitt KL, Linebarger DL, Wright JC. Early childhood television viewing and adolescent behavior: the recontact study. Monogr Soc Res Child Dev 2001;66. I-VIII, 1–147. 45. Hillman CH, Castelli DM, Buck SM. Aerobic fitness and neurocognitive function in healthy preadolescent children. Med Sci Sports Exerc 2005; 37:1967-74. 46. Buck SM, Hillman CH, Castelli DM. The relation of aerobic fitness to stroop task performance in preadolescent children. Med Sci Sports Exerc 2008;40:166-72. 47. North TC, McCullagh P, Tran ZV. Effect of exercise on depression. Exerc Sport Sci Rev 1990;18:379-415. 48. Guxens M, Mendez MA, Julvez J, Plana E, Forns J, Basagana X, et al. Cognitive function and overweight in preschool children. Am J Epidemiol 2009;170:438-46.
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Appendix Members of the AVENA Study Group: Coordinator: A. Marcos, Madrid; principal researchers: M.J. Castillo, Granada; A. Marcos, Madrid; S. Zamora, Murcia; M. Garcı´a Fuentes, Santander; M Bueno, Zaragoza. Granada: M.J. Castillo, M.D. Cano, R. Sola (biochemistry), A. Gutie´rrez, J.L. Mesa, J. Ruiz (physical fitness), M. Delgado, P. Tercedor, P. Chillo´n (physical activity), F.B. Ortega, M. Martı´n, F. Carren˜o, G.V. Rodrı´guez, R. Castillo and F. Arellano (collaborators), Dpto Fisiologı´a, Universidad de Granada, E-18071 Granada; Madrid: A. Marcos, M. Gonza´lez-Gross, J. Wa¨rnberg, S. Medina, F. Sa´nchez Muniz, E. Nova, A. Montero, B. de la Rosa, S. Go´mez, S. Samartı´n, J. Romeo, R. A´lvarez (coordination, immunology), A. A´lvarez (cytometric analysis), L. Barrios (statistical analysis), A. Leyva, B. Paya´ (psychological assessment), L. Martı´nez, E. Ramos, R. Ortiz and A. Urzanqui (collaborators), Instituto de Nutricio´n y Bromatologı´a, Consejo Superior de Investigaciones Cientı´ficas (CSIC), E-28040 Madrid; Murcia: S. Zamora, M. Garaulet, F. Pe´rez-Llamas, J.C. Baraza, J.F. Marı´n, F. Pe´rez de Heredia, M.A. Ferna´ndez, C. Gonza´lez, R. Garcı´a, C. Torralba, E. Donat, E. Morales, M.D. Garcı´a, J.A. Martı´nez, J.J. Herna´ndez, A. Asensio, F.J. Plaza and M.J. Lo´pez (diet analysis), Dpto Fisiologı´a, Universidad de Murcia, E-30100 Murcia; Santander: M. Garcı´a Fuentes, D. Gonza´lez-Lamun˜o, P. de Rufino, R. Pe´rez-Prieto, D. Ferna´ndez and T. Amigo (genetic study), Dpto Pediatrı´a, Universidad de Cantabria, E- 19003 Santander; Zaragoza: M. Bueno, L.A. Moreno, A .Sarria´, J. Fleta, G. Rodrı´guez, C.M. Gil, M.I. Mesana, J.A. Casaju´s, V. Blay and M.G. Blay (anthropometric assessment), Escuela Universitaria de Ciencias de la Salud, Universidad de Zaragoza, E-50009 Zaragoza.
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Figure 1. Cognitive performance by cardiorespiratory fitness categories in adolescents. Values are means and SDs. Cut-off points are based on the FITNESSGRAM standards for Healthy Fitness Zone.
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Figure 2. Cognitive performance by upper body muscular strength (handgrip strength) categories in adolescents. Values are means and SDs. Low and high levels correspond to below and above the median, respectively.
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Figure 3. Cognitive performance by lower body muscular strength (standing broad jump) categories in adolescents. Values are means and SDs. Low and high levels correspond to below and above the median, respectively. Cohen’s d = 0.19 (95% CI, 0.0800.296) for numeric ability.
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Figure 4. Cognitive performance by BMI categories in adolescents. Analyses are adjusted for sex, age, pubertal status, socioeconomic status, and family structure. Values are means and SDs.
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T
here is increasing evidence that regular physical activity has positive effects on brain health and that it delays cognitive decline in adults.1 Whether this effect also apply to young people is not clear. Results from cross-sectional studies indicate a positive association between physical activity and academic performance in children.2,3 Findings from interventional studies also show that children in the physical activity intervention group have at least similar academic performance compared with children in the control group, despite a substantial reduction in time devoted to academics.2,3 Less is known, however, about the association between physical activity and specific cognitive abilities during adolescence, a period of life when the brain has profound plasticity.4 The effect that sedentary behaviors have on cognitive performance is of concern. Increased television viewing time is associated with worse academic performance in children5-7 and adolescents,8 yet playing action video games seems to improve cognitive performance in adults.9-11 Both cardiorespiratory fitness and fatness are considered important health From the Department of Medical Physiology, School of markers already in both children and adolescents.12,13 The association between Medicine, University of Granada, Granada, Spain (J.R., 3 F.O.); Unit for Preventive Nutrition, Department of physical fitness and cognitive performance in adolescents is contradictory. EtBiosciences and Nutrition at NOVUM, Karolinska Institutet, Huddinge, Sweden (J.R., F.O, L.K., M.S.); nier et al 14 concluded from a meta-analysis that there is no evidence for an asDepartment of Basic Psychology, School of Psychology, sociation between cardiorespiratory fitness and cognitive performance in adults, University of Malaga, Malaga, Spain (R.C.); Department 2 of Physical Education and Sport, School of Sport whereas Hillman et al provided evidence that cardiorespiratory fitness can have Sciences, University of Granada, Granada, Spain (M.M-M., P.T.); Department of Physiotherapy and a positive effect on cognitive performance, at least in pre-pubertal children. The Nursing, School of Health and Sport Sciences, University of Zaragoza, Huesca, Spain (G.V-R.); Department of association between overweight or obesity and cognitive performance in youth is Pediatrics, University of Cantabria, Santander, Spain 15-19 also inconclusive. (J.N.); and Department of Physiotherapy and Nursing, School of Health Sciences, University of Zaragoza, Zaragoza, Spain (L.M.)
ANCOVA AVENA BMI CI OR SD TEA VO2max
One-way analysis of covariance [Alimentacio´n y Valoracio´n del Estado Nutricional de los Adolescentes Espan˜oles] Food and Assessment of the Nutritional Status of Spanish Adolescents study Body mass index Confidence interval Odds ratio Standard deviation Test of Educational Ability Maximum oxygen consumption
*List of members of the AVENA Study Group available at www.jpeds.com (Appendix). Supported by the Spanish Ministry of Health (FIS no 00/ 0015), the Spanish Ministry of Education (grants EX2007-1124 and EX-2008-0641), Panrico S.A., Madaus S.A., Procter and Gamble S.A, the Swedish Council for Working Life and Social Research (F.S.), the Swedish Heart-Lung Foundation (20090635), and the Spanish Ministry of Health: Maternal, Child Health and Development Network (RD08/0072). The authors declare no conflicts of interest. 0022-3476/$ - see front matter. Copyright Ó 2010 Mosby Inc. All rights reserved. 10.1016/j.jpeds.2010.06.026
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Most of the aforementioned studies rely on self-reported data of academic performance, and did not control for potential confounders such as socioeconomic status and family structure.20,21 In this study, we examined the association of participation in physical sports activity during leisure time, sedentary behaviors (time devoted to study, television viewing, and playing videogames), cardiorespiratory and muscular fitness, and weight status with cognitive performance (including verbal, numeric and reasoning abilities, and an overall score) in Spanish adolescents. We also examined the relationships in the studied lifestyle-related factors and how these contribute to better understand the lifestyle-cognitive performance associations in adolescents.
Methods Participants were recruited from the AVENA (Alimentacio´n y Valoracio´n del Estado Nutricional de los Adolescentes Espan˜oles [Food and Assessment of the Nutritional Status of Spanish Adolescents]) study. The AVENA study is a crosssectional study that was primarily designed to assess the nutritional status of a representative sample of Spanish adolescents aged 13.0 to 18.5 years. Data collection took place from 2000 to 2002 in 5 Spanish cities (Madrid, Murcia, Granada, Santander, and Zaragoza). The complete methodology of the AVENA study has been detailed.22,23 This study included adolescents with complete data on cognitive performance (n = 1820; 958 female). The study sample did not differ from the complete AVENA sample (n = 2894) in any of the demographic variables (all P > .1). A comprehensive verbal description of the nature and purpose of the study was given to the parents, school supervisors, and adolescents. Written consent to participate was requested from both parents and adolescents. Adolescents with a personal history of cardiovascular disease or cognitive dysfunction, who were taking medication at the time of the study, or who were pregnant, were excluded. The study protocol was performed in accordance with the ethical standards laid down in the 1961 Declaration of Helsinki (as revised in 2000), and approved by the Review Committee for Research Involving Human Subjects of the Hospital Universitario Marque´s de Valdecilla (Santander, Spain). We used the Spanish version of the ‘‘SRA Test of Educational Ability’’ (TEA) to assess cognitive performance.24 This questionaire assesses intelligence with 3 basics school skills: verbal, numeric, and reasoning. The TEA test battery provides 3 complexity levels: level 1 for children aged 8 to 12 years, level 2 for children aged 11 to 14 years, and level 3 for adolescents aged 14 to 18 years. On the basis of the age range of our sample, we used levels 2 and 3. The psychometric properties of level 2 TEA test battery showed an internal consistency reliability of a = 0.78 for the verbal component, a = 0.83 for the numeric component, a = 0.88 for the reasoning component, and a = 0.92 for overall cognitive performance. For level 3, internal consistency reliability was a = 0.74 for the verbal component, a = 0.87 for the nu918
Vol. 157, No. 6 meric component, a = 0.77 for the reasoning component, and a = 0.89 for overall cognitive performance. The TEA battery administration is collective and requires 42 and 27 minutes for level 2 and 3, respectively. Verbal ability assesses command of language, verbal identification, and vocabulary; numeric ability assesses speed and precision in performing operations with numbers and quantitative concepts; and reasoning ability assesses logical ordination criteria in sets of figures, numbers, or letters. Direct scores (range, 0-33) were obtained for each of these variables, and we also computed an overall cognitive performance variable by summing the individual scores of the 3 items (range, 0-99). The adolescents answered the following question: ‘‘Do you practice any type of physical sports activity outside the school time?’’ The possible answers were yes (coded as 1) or no (coded as 0). We obtained the information about time devoted to study and time spent in television viewing and playing video games from the following questions: ‘‘How many hours a day do you do homework or study?’’ ‘‘How many hours a day do you watch television?’’ and ‘‘How many hours a day do you play videogames?’’ Possible answers were 0 = none, 1 = <30 minutes, 2 = <1 hour, 3 = 1 to 3 hours, 4 = >3 to 4 hours, 5 = >4 hours. Because of the relatively small sample size in each single category, we re-coded the variables in two categories: 0 when #3 hours/day and 1 when >3 hours/day.25 We assessed cardiorespiratory fitness with the 20-minute shuttle run test. The score was considered as the number of stages completed (precision of 0.5 stage). We estimated maximal oxygen consumption (VO2max) (mLO2/kg/min) with the equation reported by Le`ger.26 Adolescents were classified in two levels (ie, meeting/not meeting the cardiorespiratory fitness standards) on the basis of the FITNESSGRAM standards for Healthy Fitness Zone.27 The FITNESSGRAM standards are associated with cardiovascular disease risk factors in children and adolescents,28,29 and it would be of clinical and public health importance to understand whether they are also associated with cognitive performance. This test is valid and reliable in young people.30,31 Upper body muscular strength was assessed by means of the handgrip strength test. The test was performed on both hands with a hand dynamometer (Takei TKK 5101 Grip-D; Takey, Tokyo, Japan), standing and with the arm completely extended. The test was performed twice, and the best score was retained (in kg). The sum of the right and left hand was used in the analysis. Lower body muscular strength was assessed by means of the standing long jump test. The participants were instructed to push off vigorously and jump as far forward as possible, trying to land on both feet. The distance from the takeoff line to the point where the back of the heel closest to the take-off line landed on the floor was scored. The result was recorded in centimeters. The test was performed twice, and the best score was retained. Adolescents were classified in two levels according to their upper and lower body muscular strength levels as below (low) and above (high) the median. The handgrip Ruiz et al
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December 2010 strength and stranding long jump tests are valid and reliable field-based tests in children and adolescents.30-32 Weight and height were measured following standardized procedures, and body mass index (BMI) was calculated as weight in kilograms divided by square of height in meters (kg/m2). BMI was used as a surrogate marker of total body fat. Adolescents were classified according to the BMI international cutoff values as underweight, normal weight, overweight, and obese.33,34 Parents completed a questionnaire that addressed the adolescents’ earlier and current health status and socioeconomic status defined as the educational level and occupation of the father. According to this information, and following the recommendation of the Spanish Society for Epidemiology, the adolescents were classified in 5 categories of socioeconomic status: low (I), medium-low (II), medium (III), medium-high (IV), and high (V). We also obtained information on maternal education level (primary, secondary, or university). There is evidence indicating that socioeconomic status is one of the most important determinants of childhood cognitive performance.20 We obtained information about family structure through the aforementioned questionnaire. Family structure was defined as living with parents or any other arrangement (only mother, only father, grandparents, others). Family structure may positively influence adolescents’ cognitive performance.21 We assessed pubertal development according to Tanner and Whitehouse.35 Self-reported breast development in girls and genital development in boys was used for pubertal stage classification. Statistical Analysis Data are presented as means and SDs, unless otherwise indicated. Analyses were performed with the Statistical Package for Social Sciences software version 16.0 for Windows (SPSS, Chicago, Illinois) and the level of significance was set to 0.05. We analyzed the differences in cognitive performance (including verbal, numeric, and reasoning abilities and an overall score) between adolescents who participated in physical sports activity and adolescents who did not with one-way analysis of covariance (ANCOVA) after adjusting for age and pubertal status (model 1). We performed a second model
further including socioeconomic status and family structure as co-variates (model 2). We repeated the same model for the other exposures (ie, watching television, playing videogames, and time devoted to study #3 hours/day versus >3 hours/ day), cardiorespiratory and muscular fitness (low versus high), and weigh status (underweight, normal weight, overweight, and obese). Because we did not observe an interaction effect between sex * exposure variables and cognitive performance (all P > .2), all the analyses were performed with boys and girls together and sex was included in the analyses as a co-variate. We performed separate models for each main exposure, and sex, age and pubertal status were always retained as co-variates (in model 1), whereas socioeconomic status and family structure were additionally included as covariates in model 2. We also analyzed the associations in exposures with binary logistic regression analysis. Further, we determined the differences in cardiorespiratory fitness, muscular strength, and BMI among adolescents who participated in physical sports activity, those who did not, and those spending >3 hours/ day watching television or playing videogames with ANCOVA. All the models included sex, age, and pubertal status as co-variates. We calculated the effect size statistics as Cohen d (standardized mean differences) and 95% CI.36 Values of d equal to 0.2, 0.5, and 0.8 are considered small, medium, and large effects, respectively.
Results Adolescents engaged in physical sports activities during leisure time had significantly better cognitive performance that those who were not (Table I, model 1). The effect size, as determined with Cohen d, ranged from 0.25 (verbal ability) to 0.32 (overall cognitive performance). The results did not change when socioeconomic status and family structure were entered in the model (Table I, model 2). Further adjustments for cardiorespiratory fitness, BMI, and television viewing (or video games or time devoted to study) did not materially modify the results (data not shown). Similarly, when maternal educational status was used instead of socioeconomic status, the findings remained unaltered. We did not observe an association of time devoted to study, television viewing, or playing videogames with cognitive
Table I. Cognitive performance by participation in physical sports activity during leisure time in adolescents Model 1
Overall cognitive performance (0-99) Verbal ability (0-33) Numeric ability (0-33) Reasoning ability (0-33)
Model 2
Yes (n = 1053)
No (n = 506)
P
Cohen’s d (95% CI)
Yes (n = 817)
No (n = 393)
P
Cohen’s d (95% CI)
54.7 (13.0)
50.1 (13.5)
<.001
0.32 (0.221-0.421)
55.0 (14.3)
51.4 (13.9)
<.001
0.25 (0.139-0.365)
21.4 (6.5) 14.6 (3.2) 18.6 (6.5)
19.8 (6.7) 13.1 (4.5) 17.2 (6.7)
<.001 <.001 <.001
0.25 (0.153-0.353) 0.29 (0.191-0.391) 0.26 (0.160-0.360)
21.5 (5.7) 14.8 (5.7) 18.8 (5.6)
20.4 (5.9) 13.3 (5.8) 17.7 (5.7)
.006 <.001 .003
0.18 (0.063-0.289) 0.27 (0.153-0.380) 0.19 (0.076-0.303)
Values are means (SD). Covariates model 1: sex, age, and pubertal status. Covariates model 2: model 1 plus socioeconomic status and family structure.
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Table II. Cognitive performance and sedentary behaviors in adolescents Model 1
Study Overall cognitive performance (0-99) Verbal ability (0-33) Numeric ability (0-33) Reasoning ability (0-33) Television viewing Overall cognitive performance Verbal ability Numeric ability Reasoning ability Playing videogames Overall cognitive performance Verbal ability Numeric ability Reasoning ability
Model 2
£3 hours/day
>3 hours/day
(n = 1207) 53.3 (13.9) 20.8 (6.3) 14.1 (4.9) 18.3 (5.6) (n = 1392) 53.3 (13.8) 20.9 (6.0) 14.1 (4.9) 18.3 (5.6) (n = 1483) 53.4 (13.9) 20.9 (6.2) 14.1 (5.0) 18.3 (5.4)
(n = 353) 53.3 (14.3) 21.2 (6.2) 14.0 (5.1) 18.1 (5.6) (n = 177) 52.1 (13.3) 20.5 (6.3) 13.8 (4.9) 17.8 (5.7) (n = 85) 51.3 (14.2) 20.1 (6.3) 13.4 (5.0) 17.8 (5.7)
P .969 .325 .568 .632 .255 .341 .484 .244 .194 .218 .208 .447
£ 3 hours/day
<3 hours/day
(n = 928) 54.1 (13.7) 21.1 (6.1) 14.3 (4.9) 18.6 (5.5) (n = 1096) 53.8 (13.6) 21.1 (6.0) 14.2 (4.6) 18.5 (5.6) (n = 1161) 53.9 (13.6) 21.1 (6.1) 14.3 (4.8) 18.5 (5.5)
(n = 290) 53.6 (13.8) 21.2 (6.1) 14.1 (4.9) 18.2 (5.6) (n = 125) 54.7 (13.8) 21.4 (6.1) 14.6 (4.9) 18.7 (5.6) (n = 61) 54.7 (13.9) 21.0 (6.2) 14.7 (4.9) 19.1 (5.6)
P .599 .711 .441 .307 .510 .643 .457 .651 .648 .856 .534 .439
Covariates model 1: sex, age and pubertal status. Covariates model 2: model 1 plus socioeconomic status and family structure.
performance (Table II). Likewise, cardiorespiratory fitness was not associated with cognitive performance (Figure 1; available at www.jpeds.com). The results did not materially change when we used a different equation to estimate cardiorespiratory fitness (VO2max).37 Neither upper body nor lower body muscular strength were associated with cognitive performance (Figures 2 and 3; available at www. jpeds.com), and the results persisted after we repeated the analysis comparing the upper and lower sex- and agespecific quintiles (data not shown). Cognitive performance was similar across weight status categories (Figure 4; available at www.jpeds.com). We did not observe an association between physical sports activity and time devoted to study (odds ratio [OR], 0.818; 95% CI, 0.630-1.064). Participation in physical sports activity during leisure time was associated with a lower OR of watching television for >3 hours/day (0.631; 95% CI, 0.445-0.894) and playing videogames for >3 hours/day (0.533; 95% CI, 0.320-0.887). Adolescents participating in physical sports activity had better cardiorespiratory and muscular fitness levels compared with those who did not for cardiorespiratory fitness (5.9 2.0 versus 4.9 1.9 stages, respectively; P < .001), standing long jump (177 31 versus 154 28 cm, respectively; P < .001), and handgrip strength (61.1 0.4 versus 59.6 0.5 cm, respectively; P = .023). BMI did not differ in physical sports activity categories (P = .606). Adolescents who spent >3 hours/day watching television tended to have a lower OR of spending >3 hours/day studying (0.629; 95% CI, 0.384-1.029). Adolescents who spent <3 hours/day playing video games had a significantly lower OR of spending >3 hours/day studying (0.375; 95% CI, 0.1470.959). Levels of cardiorespiratory fitness were lower in adolescents who spent >3 hours/day watching television compared with adolescents who spent #3 hours/day watching television (4.9 1.3 versus 5.6 2.1 stages, respectively; P < .001) and so were standing long jump levels (162 31 versus 169 32 cm, respectively; P = .019). BMI was higher in ad920
olescents who spent >3 hours/day watching television compared with those who spent #3 hours/day (22.4 3.4 versus 21.5 3.2 kg/m2, respectively; P = .002), regardless of sex, age, and puberty stage. Adolescents who played videogames for >3 hours/day had lower cardiorespiratory fitness compared with their peers who spent #3 hours/day (4.5 1.0 versus 5.6 2.2 stages, respectively; P < .001). The results were similar when we repeated all the analyses in boys and girls separately.
Discussion Although no conclusion can be drawn from this cross-sectional study about whether participation in physical sports activity during leisure time leads to improvements in cognitive performance in adolescents, these findings are of public health and clinical interest and extend earlier results that suggested the potential benefit of physical activity on cognitive performance already in youth.2,3 Adolescence is a period of life when the brain has profound plasticity because of changes in both structure and function.4 Therefore, the pubertal period offers high possibilities of stimulating cognitive function.4 The relationship between participation in physical sports activity and cognitive performance has been a subject of discussion between advocates and skeptics of physical sports activity, and especially in parents concerned about decreases in study and homework time. The assumption is based on the participation in physical sports activity may ‘‘displace’’ time that would normally be spent doing schoolwork, reading for pleasure, or engaging in other educational activities. In this study, we observed that participation in physical sports activity is not associated with lower time devoted to study. This concurs with intervention studies that indicated that children enrolled in more physical sports activity do not have poorer academic performance, despite a reduction in time in the so-called ‘‘academic subjects.’’3 Furthermore, we also observed that participation in physical sports activity was associated with lower television viewing and time Ruiz et al
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December 2010 devoted to play video games and with higher levels of cardiorespiratory and muscular fitness. This suggest that physical sports activity may indirectly prevent the deleterious effects ascribed to sedentary behaviors39, 40 and may have an indirect positive effect on health through its effect on fitness. Findings from intervention studies also reported a positive effect on fitness besides the aforementioned effects on academic performance.3 Even single bouts of physical activity (20 minutes of aerobic exercise at 60% of estimated maximum heart rate) may improve cognitive control and attention in children.41 Collectively, these findings are particularly important because of the existing pressure on children and adolescents, parents, and schools to maximize academic performance. We do not know whether sports participation is a marker of adolescents who are high achievers and who do better in this type of cognitive tests. Moreover, whether adolescents who persist in sports activity have other characteristics that allow them to perform well on cognitive tests remains to be elucidated. There is increasing concern about the amount of time that youth spend watching television or playing video games because of the potential effect they may have on health. Indeed, we observed that both television viewing and playing video games had a negative effect on cardiorespiratory fitness, lower body muscular strength, and BMI. Several studies reported an association between increased television viewing and decreased time spent reading and doing homework,42,43 which in turn may affect academic performance. Results from crosssectional and longitudinal studies reported that increased television time had a detrimental impact on academic performance in children5-7 and self-reported academic performance in adolescents.8 We observed that adolescents who spent more time watching television or playing video games devoted less time to study, which concurs with the so called ‘‘displacement hypothesis.’’44 However, despite this observation, we did not observe an association between television time and cognitive performance. Our data do not concur with experimental studies showing that playing action video games improve cognitive performance in young adults.9,10 Differences in the outcome variable, the participants’ age, and the study design make comparisons between studies difficult. Cardiorespiratory fitness is strongly linked to cardiovascular disease risk factors in youth.12,13 Whether it is also associated with cognitive performance is, however, debated. The conclusion from a meta-regression analysis was that cardiorespiratory fitness was not associated with cognitive performance in adults,14 which concur with our results, whereas other studies suggested the opposite in children.2 Hillman and co-workers showed in a series of studies that high cardiorespiratory fitness was associated with better cognition in pre-adolescent children.19,45,46 Several studies hypothesized that aerobic fitness may mediate the relationship between physical activity and cognitive performance,47 whereas other studies argued that cardiorespiratory fitness is a ‘‘‘gross’’ measure of the physiological status and therefore might not be sensitive enough for one to see any association with cognitive performance.14 The association between physical
sports activity and cognitive performance observed in this study persisted after further adjusting for either cardiorespiratory or muscular fitness. Whether more precise measurements of both cardiorespiratory fitness (ie, directly measured maximum oxygen consumption) and cognitive function (eg, electroencephalogram, neuroelectric activity) would yield to a different results in adolescents remains to be investigated.45 We did not observe an association between muscular fitness and cognitive performance, which concur with the results observed by other authors.19 A limited number of studies have examined whether increased body weight per se is associated with poorer cognitive performance.15-19 We did not observe an association between weight status and cognitive performance, which concurs with other studies.17,18 Overweight children and adolescents have lower cognitive performance than normal-weight ones after adjusting for a number of potential confounders.16 Mosuwan et al17 observed an association between overweight status and poor academic performance in children, but not in adolescents. Severely obese Chinese children had significantly lower intelligence quotient than the control subjects.15 Children with higher cognitive function in early life can be at decreased risk of overweight years later.48 Limitations of this study include its cross-sectional design, which precludes drawing conclusions on the direction of the associations. A second limitation relies on the use of a selfreported measure of physical sports activity. Moreover, this study focused only on sports-related activity, and therefore, the duration of the participation and other leisure time physical activity was not recorded. Further research should use physical activity assessed with objective measures such as accelerometry. We did not have data on watching television during weekends, which limited the analysis. We also did not ask what kinds of video games adolescents play. Strengths of this study include the use of a relatively large national sample, the inclusion of several potential confounders, and the use of an objective and standardized measure of cognitive performance. Because cognitive performance is potentially modifiable during the pubertal phase,4 it would be of interest to investigate whether targeted physical activity interventions especially on individuals with cognitive impairment might influence cognitive performance during adolescence and later in life. n Submitted for publication Feb 16, 2010; last revision received Apr 30, 2010; accepted Jun 16, 2010. Reprint requests: Jonatan R. Ruiz, PhD. Department of Biosciences and Nutrition, Unit for Preventive Nutrition, Karolinska Institutet, Stockholm, Sweden, Ha¨lsova¨gen 7-9, SE-141 57 Huddinge, Sweden. E-mail: [email protected].
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Appendix Members of the AVENA Study Group: Coordinator: A. Marcos, Madrid; principal researchers: M.J. Castillo, Granada; A. Marcos, Madrid; S. Zamora, Murcia; M. Garcı´a Fuentes, Santander; M Bueno, Zaragoza. Granada: M.J. Castillo, M.D. Cano, R. Sola (biochemistry), A. Gutie´rrez, J.L. Mesa, J. Ruiz (physical fitness), M. Delgado, P. Tercedor, P. Chillo´n (physical activity), F.B. Ortega, M. Martı´n, F. Carren˜o, G.V. Rodrı´guez, R. Castillo and F. Arellano (collaborators), Dpto Fisiologı´a, Universidad de Granada, E-18071 Granada; Madrid: A. Marcos, M. Gonza´lez-Gross, J. Wa¨rnberg, S. Medina, F. Sa´nchez Muniz, E. Nova, A. Montero, B. de la Rosa, S. Go´mez, S. Samartı´n, J. Romeo, R. A´lvarez (coordination, immunology), A. A´lvarez (cytometric analysis), L. Barrios (statistical analysis), A. Leyva, B. Paya´ (psychological assessment), L. Martı´nez, E. Ramos, R. Ortiz and A. Urzanqui (collaborators), Instituto de Nutricio´n y Bromatologı´a, Consejo Superior de Investigaciones Cientı´ficas (CSIC), E-28040 Madrid; Murcia: S. Zamora, M. Garaulet, F. Pe´rez-Llamas, J.C. Baraza, J.F. Marı´n, F. Pe´rez de Heredia, M.A. Ferna´ndez, C. Gonza´lez, R. Garcı´a, C. Torralba, E. Donat, E. Morales, M.D. Garcı´a, J.A. Martı´nez, J.J. Herna´ndez, A. Asensio, F.J. Plaza and M.J. Lo´pez (diet analysis), Dpto Fisiologı´a, Universidad de Murcia, E-30100 Murcia; Santander: M. Garcı´a Fuentes, D. Gonza´lez-Lamun˜o, P. de Rufino, R. Pe´rez-Prieto, D. Ferna´ndez and T. Amigo (genetic study), Dpto Pediatrı´a, Universidad de Cantabria, E- 19003 Santander; Zaragoza: M. Bueno, L.A. Moreno, A .Sarria´, J. Fleta, G. Rodrı´guez, C.M. Gil, M.I. Mesana, J.A. Casaju´s, V. Blay and M.G. Blay (anthropometric assessment), Escuela Universitaria de Ciencias de la Salud, Universidad de Zaragoza, E-50009 Zaragoza.
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Figure 1. Cognitive performance by cardiorespiratory fitness categories in adolescents. Values are means and SDs. Cut-off points are based on the FITNESSGRAM standards for Healthy Fitness Zone.
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Figure 2. Cognitive performance by upper body muscular strength (handgrip strength) categories in adolescents. Values are means and SDs. Low and high levels correspond to below and above the median, respectively.
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Figure 3. Cognitive performance by lower body muscular strength (standing broad jump) categories in adolescents. Values are means and SDs. Low and high levels correspond to below and above the median, respectively. Cohen’s d = 0.19 (95% CI, 0.0800.296) for numeric ability.
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Figure 4. Cognitive performance by BMI categories in adolescents. Analyses are adjusted for sex, age, pubertal status, socioeconomic status, and family structure. Values are means and SDs.
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