participants selected for the present study were enrolled in the 1993 pelotas ( brazil ) birth cohort . detailed descriptions about the cohort methods are available elsewhere ( 12,32,33 ) . in brief , this birth cohort included 5249 of the 5265 newborn children ( 99.7% ) in the calendar year of 1993 in pelotas , a city in southern brazil . this study used data from the follow - ups that were carried out when participants were age 11 , 15 , and 18 yr . of the 5249 participants of the cohort , we were able to include data on 3235 ( 61.6% ) for this study . of the 2014 nonparticipants , 164 ( 3.1% ) were known to have died between birth and 18 yr of age , 974 ( 18.6% ) were not located , and 876 ( 16.7% ) did not provide valid physical activity data in at least one of the three follow up visits . before participating in the study , the study protocols were approved by the ethics committee of the medicine school from the federal university of pelotas . self - reported physical activity during leisure time ( minwk ) was assessed using two validated questionnaires . both questionnaires have shown a good reliability and adequate validity to assess physical activity in youth and adults from brazil when compared with pedometer measurements ( 1,6 ) . the questionnaire used at 11 and 15 yr included a list of physical activities typically practiced by youth in the region with the possibility to include other activities not listed previously . participants reported the frequency ( dwk ) and the mean duration ( h and/or mind ) that they engaged in each activity over the last 7 d ( 1 ) . for calculating the time spent in leisure time physical activity , we first multiplied the number of days by the average daily duration of each activity and we then summed the values across different activities . the questionnaire used at 18 yr was the leisure time section of the long version of the international physical activity questionnaire ( 6 ) . participants were asked about the frequency and duration that they spent in walking and in moderate - intensity and vigorous - intensity physical activity over the past week . time spent in leisure time physical activity at 18 yr was derived by summing the minutes engaged per week in each category . objectively measured physical activity was obtained by the geneactive accelerometer ( activinsights , kimbolton , united kingdom ) at 18 yr of age . the geneactive is a waterproof and triaxial accelerometer capable of measuring accelerations from 8 g to 8 g ( g = 9.81 ms ) with a sampling frequency set at 85.7 hz . data are stored directly as sampled from the microelectromechanical systems chip ( unfiltered data ) ( 7 ) . each participant wore the accelerometer on their nondominant wrist for four to seven free - living days including at least one weekend day . a recent validation study confirmed that there is a strong agreement for the vector magnitude of wrist acceleration ( mg ) between geneactiv and actigraph accelerometers ( 16 ) . the inclusion criterion was an activity monitor recording of at least 2 d. accelerometers were set up and downloaded using the geneactiv software . the data were analyzed in binary format with r - package ggir ( http://www.cran.r-project.org ) ( 31 ) . moderate - to - vigorous physical activity ( mvpa ) was estimated using an intensity threshold of 100 mg based on 5-s epoch data with minimum bout duration of 10 min , where > 80% of the data points are equal to or above the threshold . the intensity threshold was based on a recent methodological study in children and adults wearing a geneactiv accelerometer on their wrist while performing standardized activity types ( 16 ) . the physical activity variable used for this analysis was based on minutes per week at mvpa . the main confounding variables included were sex , body mass index ( bmi ) , birth weight , and two indicators of socioeconomic status : maternal schooling at birth and family income at birth . cognitive performance was assessed at 18 yr of age using an adapted brazilian version of the short form of the wechsler adult intelligence scale ( wais - iii ) . the wais - iii is a subsequent revision of the wais and the wais - r . the wais - iii short form included four selected wais - iii subtests ( the arithmetic , digit symbol , similarities , and picture completion subtests ) ( 19 ) . the main adaptations for the brazilian version were regarding to the content of some items of the verbal scale , the order of item presentation , the time limit and bonus concession , the criteria to start and discontinue the application , and the establishment of norms for age . an overall cognitive performance score was calculated by summing the score for each subtest and then applying a specific brazilian weighting ( 25 ) . descriptive characteristics are presented as means  sd , and differences between sexes were assessed by t - test . preliminary analyses showed no significant interactions among sex and physical activity variables ( all p > 0.10 ) ; thus , all analyses were performed sex combined . participants were classified according to their time spent in physical activity at 11 , 15 , and 18 yr on the basis of sex - specific tertiles ( low , middle , and high ) . we evaluated the prospective association between physical activity at 11 and 15 yr and cognitive performance at 18 yr using linear regression adjusting for sex , bmi at baseline , bmi at 18 yr , birth weight , family income at birth , and maternal schooling at birth . we also examined the cross - sectional association of objectively and self - reported physical activity with cognitive performance at 18 yr , including the same confounding variables . the differences in cognitive performance by changes in tertiles of physical activity ( consistently low , decreasing , consistently middle , increasing , consistently high ) from 11 to 18 and 15 to 18 yr were examined by multiple linear regression adjusted for sex , change in bmi from baseline ( 11 or 15 yr ) to 18 yr , birth weight , family income at birth , and maternal schooling at birth . all analyses were conducted using spss version 18.0 for windows ( ibm , armonk , ny ) , with significance set at p < 0.05 . participants selected for the present study were enrolled in the 1993 pelotas ( brazil ) birth cohort . detailed descriptions about the cohort methods are available elsewhere ( 12,32,33 ) . in brief , this birth cohort included 5249 of the 5265 newborn children ( 99.7% ) in the calendar year of 1993 in pelotas , a city in southern brazil . this study used data from the follow - ups that were carried out when participants were age 11 , 15 , and 18 yr . of the 5249 participants of the cohort , we were able to include data on 3235 ( 61.6% ) for this study . of the 2014 nonparticipants , 164 ( 3.1% ) were known to have died between birth and 18 yr of age , 974 ( 18.6% ) were not located , and 876 ( 16.7% ) did not provide valid physical activity data in at least one of the three follow up visits . before participating in the study , the study protocols were approved by the ethics committee of the medicine school from the federal university of pelotas . self - reported physical activity during leisure time ( minwk ) was assessed using two validated questionnaires . both questionnaires have shown a good reliability and adequate validity to assess physical activity in youth and adults from brazil when compared with pedometer measurements ( 1,6 ) . the questionnaire used at 11 and 15 yr included a list of physical activities typically practiced by youth in the region with the possibility to include other activities not listed previously . participants reported the frequency ( dwk ) and the mean duration ( h and/or mind ) that they engaged in each activity over the last 7 d ( 1 ) . for calculating the time spent in leisure time physical activity , we first multiplied the number of days by the average daily duration of each activity and we then summed the values across different activities . the questionnaire used at 18 yr was the leisure time section of the long version of the international physical activity questionnaire ( 6 ) . participants were asked about the frequency and duration that they spent in walking and in moderate - intensity and vigorous - intensity physical activity over the past week . time spent in leisure time physical activity at 18 yr was derived by summing the minutes engaged per week in each category . objectively measured physical activity was obtained by the geneactive accelerometer ( activinsights , kimbolton , united kingdom ) at 18 yr of age . the geneactive is a waterproof and triaxial accelerometer capable of measuring accelerations from 8 g to 8 g ( g = 9.81 ms ) with a sampling frequency set at 85.7 hz . data are stored directly as sampled from the microelectromechanical systems chip ( unfiltered data ) ( 7 ) . each participant wore the accelerometer on their nondominant wrist for four to seven free - living days including at least one weekend day . a recent validation study confirmed that there is a strong agreement for the vector magnitude of wrist acceleration ( mg ) between geneactiv and actigraph accelerometers ( 16 ) . the inclusion criterion was an activity monitor recording of at least 2 d. accelerometers were set up and downloaded using the geneactiv software . the data were analyzed in binary format with r - package ggir ( http://www.cran.r-project.org ) ( 31 ) . moderate - to - vigorous physical activity ( mvpa ) was estimated using an intensity threshold of 100 mg based on 5-s epoch data with minimum bout duration of 10 min , where > 80% of the data points are equal to or above the threshold . the intensity threshold was based on a recent methodological study in children and adults wearing a geneactiv accelerometer on their wrist while performing standardized activity types ( 16 ) . the physical activity variable used for this analysis was based on minutes per week at mvpa . the main confounding variables included were sex , body mass index ( bmi ) , birth weight , and two indicators of socioeconomic status : maternal schooling at birth and family income at birth . cognitive performance was assessed at 18 yr of age using an adapted brazilian version of the short form of the wechsler adult intelligence scale ( wais - iii ) . the wais - iii is a subsequent revision of the wais and the wais - r . the wais - iii short form included four selected wais - iii subtests ( the arithmetic , digit symbol , similarities , and picture completion subtests ) ( 19 ) . the main adaptations for the brazilian version were regarding to the content of some items of the verbal scale , the order of item presentation , the time limit and bonus concession , the criteria to start and discontinue the application , and the establishment of norms for age . an overall cognitive performance score was calculated by summing the score for each subtest and then applying a specific brazilian weighting ( 25 ) . descriptive characteristics are presented as means  sd , and differences between sexes were assessed by t - test . preliminary analyses showed no significant interactions among sex and physical activity variables ( all p > 0.10 ) ; thus , all analyses were performed sex combined . participants were classified according to their time spent in physical activity at 11 , 15 , and 18 yr on the basis of sex - specific tertiles ( low , middle , and high ) . we evaluated the prospective association between physical activity at 11 and 15 yr and cognitive performance at 18 yr using linear regression adjusting for sex , bmi at baseline , bmi at 18 yr , birth weight , family income at birth , and maternal schooling at birth . we also examined the cross - sectional association of objectively and self - reported physical activity with cognitive performance at 18 yr , including the same confounding variables . the differences in cognitive performance by changes in tertiles of physical activity ( consistently low , decreasing , consistently middle , increasing , consistently high ) from 11 to 18 and 15 to 18 yr were examined by multiple linear regression adjusted for sex , change in bmi from baseline ( 11 or 15 yr ) to 18 yr , birth weight , family income at birth , and maternal schooling at birth . all analyses were conducted using spss version 18.0 for windows ( ibm , armonk , ny ) , with significance set at p < 0.05 . participants selected for the present study were enrolled in the 1993 pelotas ( brazil ) birth cohort . detailed descriptions about the cohort methods are available elsewhere ( 12,32,33 ) . in brief , this birth cohort included 5249 of the 5265 newborn children ( 99.7% ) in the calendar year of 1993 in pelotas , a city in southern brazil . this study used data from the follow - ups that were carried out when participants were age 11 , 15 , and 18 yr . of the 5249 participants of the cohort , we were able to include data on 3235 ( 61.6% ) for this study . of the 2014 nonparticipants , 164 ( 3.1% ) were known to have died between birth and 18 yr of age , 974 ( 18.6% ) were not located , and 876 ( 16.7% ) did not provide valid physical activity data in at least one of the three follow up visits . before participating in the study , the study protocols were approved by the ethics committee of the medicine school from the federal university of pelotas . self - reported physical activity during leisure time ( minwk ) was assessed using two validated questionnaires . both questionnaires have shown a good reliability and adequate validity to assess physical activity in youth and adults from brazil when compared with pedometer measurements ( 1,6 ) . the questionnaire used at 11 and 15 yr included a list of physical activities typically practiced by youth in the region with the possibility to include other activities not listed previously . participants reported the frequency ( dwk ) and the mean duration ( h and/or mind ) that they engaged in each activity over the last 7 d ( 1 ) . for calculating the time spent in leisure time physical activity , we first multiplied the number of days by the average daily duration of each activity and we then summed the values across different activities . the questionnaire used at 18 yr was the leisure time section of the long version of the international physical activity questionnaire ( 6 ) . participants were asked about the frequency and duration that they spent in walking and in moderate - intensity and vigorous - intensity physical activity over the past week . time spent in leisure time physical activity at 18 yr was derived by summing the minutes engaged per week in each category . objectively measured physical activity was obtained by the geneactive accelerometer ( activinsights , kimbolton , united kingdom ) at 18 yr of age . the geneactive is a waterproof and triaxial accelerometer capable of measuring accelerations from 8 g to 8 g ( g = 9.81 ms ) with a sampling frequency set at 85.7 hz . data are stored directly as sampled from the microelectromechanical systems chip ( unfiltered data ) ( 7 ) . each participant wore the accelerometer on their nondominant wrist for four to seven free - living days including at least one weekend day . a recent validation study confirmed that there is a strong agreement for the vector magnitude of wrist acceleration ( mg ) between geneactiv and actigraph accelerometers ( 16 ) . the inclusion criterion was an activity monitor recording of at least 2 d. accelerometers were set up and downloaded using the geneactiv software . the data were analyzed in binary format with r - package ggir ( http://www.cran.r-project.org ) ( 31 ) . moderate - to - vigorous physical activity ( mvpa ) was estimated using an intensity threshold of 100 mg based on 5-s epoch data with minimum bout duration of 10 min , where > 80% of the data points are equal to or above the threshold . the intensity threshold was based on a recent methodological study in children and adults wearing a geneactiv accelerometer on their wrist while performing standardized activity types ( 16 ) . the physical activity variable used for this analysis was based on minutes per week at mvpa . the main confounding variables included were sex , body mass index ( bmi ) , birth weight , and two indicators of socioeconomic status : maternal schooling at birth and family income at birth . cognitive performance was assessed at 18 yr of age using an adapted brazilian version of the short form of the wechsler adult intelligence scale ( wais - iii ) . the wais - iii is a subsequent revision of the wais and the wais - r . the wais - iii short form included four selected wais - iii subtests ( the arithmetic , digit symbol , similarities , and picture completion subtests ) ( 19 ) . the main adaptations for the brazilian version were regarding to the content of some items of the verbal scale , the order of item presentation , the time limit and bonus concession , the criteria to start and discontinue the application , and the establishment of norms for age . an overall cognitive performance score was calculated by summing the score for each subtest and then applying a specific brazilian weighting ( 25 ) . descriptive characteristics are presented as means  sd , and differences between sexes were assessed by t - test . preliminary analyses showed no significant interactions among sex and physical activity variables ( all p > 0.10 ) ; thus , all analyses were performed sex combined . participants were classified according to their time spent in physical activity at 11 , 15 , and 18 yr on the basis of sex - specific tertiles ( low , middle , and high ) . we evaluated the prospective association between physical activity at 11 and 15 yr and cognitive performance at 18 yr using linear regression adjusting for sex , bmi at baseline , bmi at 18 yr , birth weight , family income at birth , and maternal schooling at birth . we also examined the cross - sectional association of objectively and self - reported physical activity with cognitive performance at 18 yr , including the same confounding variables . the differences in cognitive performance by changes in tertiles of physical activity ( consistently low , decreasing , consistently middle , increasing , consistently high ) from 11 to 18 and 15 to 18 yr were examined by multiple linear regression adjusted for sex , change in bmi from baseline ( 11 or 15 yr ) to 18 yr , birth weight , family income at birth , and maternal schooling at birth . all analyses were conducted using spss version 18.0 for windows ( ibm , armonk , ny ) , with significance set at p < 0.05 . table 2 describes the tertiles of self - reported and objectively measured physical activity used in the analyses . at 11 , 15 , and 18 yr , , boys in the lowest tertile increased their physical activity whereas boys in the highest tertile decreased their physical activity . among girls , there was a decline of the mean self - reported physical activity for all three tertiles . at 18 yr of age , boys were more active than girls , both in terms of self - reported and objectively measured physical activity . on the basis of accelerometry , the lowest tertile accumulated on average 109 minwk and 36 minwk of mvpa in boys and girls , respectively . descriptive of physical activity by sex - specific tertiles at 11 , 15 , and 18 yr . in table 3 , we display the associations between physical activity at 11 , 15 , and 18 yr of age and cognitive performance at 18 yr . at 11 yr , participants in the middle tertile of physical activity had a 1.03 score ( 95% confidence interval ( ci ) ci for the difference , 0.081.98 ) higher than those in the lowest tertile . physical activity at 15 yr of age was unrelated to cognitive performance at 18 yr . self - reported physical activity at 18 yr of age was cross - sectionally positively associated with cognitive performance at 18 yr , but only the intermediate tertile continued to present higher cognitive performance scores in the adjusted analyses ( + 1.30 ; 95% ci for the difference , 0.332.27 ) . however , data from objectively measured pa suggested that higher amounts of mvpa were associated with lower cognitive performance . both in the crude and in the adjusted analysis , those in the upper mvpa tertile presented lower cognitive performance scores as compared with those in the bottom tertile ( 2.59 ; 95% ci for the difference , 3.41 ; 1.48 ) . analyses were also performed including total pa instead of mvpa , and results were virtually similar ( data not shown ) . association of physical activity at 11 , 15 , and 18 yr with cognitive performance at 18 yr . table 4 shows the effects of trajectories of self - reported physical activity throughout adolescence on cognitive performance at 18 yr of age . findings for the periods 1118 and 1518 yr were notably consistent . those who were consistently active at moderate levels  i.e . , categorized in the intermediate tertile presented significantly higher cognitive performance scores than those who were consistently inactive . maintaining an intermediate physical activity level from 11 to 18 yr and from 15 to 18 yr was associated with a higher cognitive performance score of 2.31 ( 95% ci , 0.713.91 ) and 1.84 score ( 95% ci , 0.253.42 ) , respectively . changes in physical activity from 11 and 1518 yr and cognitive performance at 18 yr . the main finding from this study was that being consistently moderately physically active throughout adolescence was significantly associated with cognitive performance at age 18 yr . this observation was similar in both prospective and cross - sectional analyses using self - reported physical activity . however , data from our cross - sectional analysis using objectively measured physical activity by accelerometry suggested that high physical activity levels might impair cognitive performance . our results contribute to the current knowledge by suggesting that intermediate levels of physical activity may have the greatest benefit on cognitive performance . several mechanisms may yield the effect of physical activity on brain function from early ages to even adulthood ( 4,14 ) . exercise increases the formation of new neurons and concentrations of brain - derived neurotrophic factor , improves cerebral blood flow and oxygen availability in the brain , as well as enhances activity - dependent synaptic plasticity . this set of physiological changes is related to 1 ) attention , 2 ) information processing , storage , and retrieval , as well as 3 ) concentration . importantly , adolescence is the period of life when the brain has profound plasticity , which offers high possibilities to stimulate cognitive function ( 27 ) . contradictorily , this period also experiences the greatest decreases in physical activity levels ( 8) . hence , adolescents who are physically inactive might be losing an important stimulus to improve learning and cognitive performance . our results in a large birth cohort showed that adolescents who were in the middle tertile of self - reported physical activity at 11 and 18 yr had higher cognitive performance at 18 yr compared with those in the lowest tertile . in addition , continued moderate levels of self - reported physical activity throughout adolescence were associated with higher cognitive performance before adulthood . for example , maintaining in the intermediate tertile from 11 and 1518 yr was associated with a + 2.33 score and a 1.96 score in cognitive performance compared with those who maintained in the lowest tertile , respectively . taken together , our results suggest that maintaining a regular active lifestyle might seem more strongly associated with cognitive performance compared with changing levels of physical activity during adolescence ( e.g. , being too inactive at a given age and too active at other ages ) . hence , the earlier to start to engage in moderate levels of physical activity , the higher improvement on cognitive performance before adulthood . to date , a limited number of prospective and interventional studies have examined whether increases in physical activity are associated with better cognitive performance ( 3,5,22,29 ) . two fairly small interventional studies including 48 and 232 adolescents , respectively from greece and the united states , found that being active at vigorous intensity during physical education classes was associated with increases in cognitive performance ( 5,29 ) . whereas these studies suggest that a  threshold intensity ,  specifically vigorous intensity , may be necessary to produce beneficial cognitive effects , our results support the hypothesis that a  threshold amount  of physical activity ( i.e. , moderate levels ) may be enough to enhance cognitive performance . however , it is important to take into account that these intervention studies were focused on physical education classes , but our prospective results were based on leisure time physical activity . further prospective and experimental studies in adolescents are necessary to examine the threshold hypothesis within different settings . another finding from the present study regarding to cross - sectional analysis with accelerometry was that adolescents at 18 yr who engaged in high levels of physical activity ( approximately 600 minwk ) had lower cognitive performance compared with the least active group . marsh and kleitman ( 22 ) also showed that sport participation at early adolescence was negatively associated with cognitive performance at grade 12 . indeed , similar results to ours and those from marsh and kleitman ( 22 ) have been previously shown when examining the association of physical activity with regard to academic performance ( 2,9,26 ) . those with lower cognitive score might be those who start working earlier , who in turn , are more physically active at their working place . to test this hypothesis when including working status as a covariate , the results were virtually the same and there was no evidence of a modifying effect of working status ( i.e. , p for mvpa  working status interaction , > 0.1 ) on the association between mvpa and cognitive performance . another explanation could be that , although adolescents who are highly active have the biologically benefit of physical activity , they also may displace time that would usually be spent doing schoolwork , reading for pleasure , or engaging in other educational activities , which in turn may detract cognitive performance . surprisingly , we found discrepancies in cross - sectional findings when using self - reported and objective measures of physical activity in relation to cognitive performance . a possible explanation is that self - reported physical activity assesses specific domains of physical activity , such us extracurricular physical activity , physical education , or leisure time , whereas accelerometry covers almost the complete range of physical activity in which adolescents are involved ( i.e. , except cycling or swimming activities ) . thus , the association between physical activity and cognitive performance might depend on which specific component of total physical activity is measured . this reason could partially explain why our findings using self - reported physical activity showed positive associations with cognitive performance , whereas findings with objective measures of physical activity showed negative associations . the strengths of this study include the relative large sample size from a birth cohort , its prospective design , the use of accelerometers to assess physical activity , and the substantial time interval between measurements . however , the study also has limitations . changes in the main outcome were not available because cognitive performance data were not collected in previous waves , which preclude drawing conclusions with regard to causality . likewise , other confounding factors ( i.e. , pubertal status , physical fitness , parental cognitive status , or ethnicity ) were not available , so results should be interpreted with caution . in addition , prospective analyses were based on self - reported physical activity . future research using repeated measures of both objectively measured physical activity and different types of physical activity ( active commuting , physical education , recess physical activity ) and cognitive performance may provide further insights on this association . in conclusion , our results suggest that physical activity throughout adolescence is associated with cognitive performance ( referring to measures of intellectual quotient ) before adulthood . adolescents who are active at moderate levels , specifically those who maintain these levels of physical activity , tend to show higher cognitive performance
abstractpurposethis study aimed to examine the prospective associations of physical activity at 11 , 15 , and 18 yr of age with cognitive performance in young adulthood in a large birth cohort study from brazil.methodsparticipants were part of a large birth cohort study in pelotas , brazil ( n = 3235 participants ) . 
 physical activity was self - reported at 11 , 15 , and 18 yr and was also objectively measured at 18 yr . 
 cognitive performance was assessed using an adapted brazilian version of the short form of the wechsler adult intelligence scale at 18 yr.resultsat 11 yr , participants in the middle tertile of self - reported physical activity presented a significantly higher cognitive performance score as compared with the lowest tertile . 
 physical activity at 15 yr of age was unrelated to cognitive performance at 18 yr . 
 self - reported physical activity was cross - sectionally positively associated with cognitive performance at 18 yr ( p < 0.001 ) . 
 data from objectively measured physical activity at 18 yr showed that those in the highest moderate - to - vigorous physical activity tertile presented lower cognitive performance scores at 18 yr as compared with those in the lowest tertile ( 2.59 ; 95% confidence interval ( ci ) , 3.41 to 1.48 ) . 
 analyses on changes in tertiles of physical activity showed that maintaining an intermediate physical activity level from 11 to 18 yr and from 15 to 18 yr was associated with a higher cognitive performance score of 2.31 ( 95% ci , 0.713.91 ) and 1.84 score ( 95% ci , 0.253.42 ) , respectively.conclusionsphysical activity throughout adolescence is associated with cognitive performance before adulthood . 
 adolescents who are active at moderate levels , specifically those who maintain these levels of physical activity , tend to show higher cognitive performance . 
 however , high levels of physical activity might impair cognitive performance .