Association between Physical Activity, Sedentary Time, and Healthy Fitness in Youth ADILSON MARQUES1, RUTE SANTOS2,3, ULF EKELUND4,5, and LUI´S B. SARDINHA6 1 Centro de Estudos de Educaça˜o e Promoça˜o da Sau´de, CIPER, Fac Motricidade Humana, Univ Lisboa, Cruz-Quebrada, PORTUGAL; 2Maia Institute of Higher Education (CIDAF), Maia, PORTUGAL; 3Research Centre in Physical Activity, Health and Leisure, Faculty of Sport, University of Porto, Porto, PORTUGAL; 4Department of Sport Medicine, Norwegian School of Sport Sciences, NORWAY; 5MRC Epidemiology Unit, University of Cambridge, Cambridge, UNITED KINGDOM; and 6Exercise and Health Laboratory, CIPER, Fac Motricidade Humana, Univ Lisboa, Cruz-Quebrada, PORTUGAL
ABSTRACT
P
(CRF)) is determined by nonmodifiable factors such as growth, sexual maturation, sex, age, and heredity; however, it is also influenced by moderate-to-vigorous physical activity (MVPA) and sedentary time (3). High levels of physical activity (PA) are related to better aerobic fitness and lower body mass index (BMI) (23). Sedentary time is related to lower CRF (17,24) and increase in childhood BMI (16). The FITNESSGRAM test battery was developed to assess physical fitness among young people with a health-related approach, and it is widely used in some states and school districts in the United States of America (14) and in other countries (15,18,23). On the basis of these measures, students are stratified as being above or below a predetermined threshold for the healthy fitness zone (HFZ), indicating whether their level of fitness is sufficient to reduce their risk for hypokinetic diseases. One of the most important contributions of the FITNESSGRAM is that the assessments are based on health standards for CRF (33), body composition (12), and musculoskeletal function (21). Two studies have recently examined the relation between self-reported PA and sedentary behaviors and several components of health-related fitness in young people using the
hysical fitness is associated with a variety of health benefits in young people (11), and it is considered one of the most important health status markers that predict cardiovascular disease and mortality (20). In children and adolescents, cross-sectional (18,26) and prospective studies (6,25) show that high levels of physical fitness are associated with improved health-related biomarkers that may further influence health in young adulthood. Physical fitness (e.g., body composition, upper body strength and endurance, abdominal strength and endurance, flexibility of the hamstrings and the lower back, cardiorespiratory fitness
Address for correspondence: Luı´s B. Sardinha, Ph.D., Interdisciplinary Center for the Study of Human Performance, Faculty of Human Kinetics, University of Lisbon, Estrada da Costa, 1499-002 Cruz-Quebrada, Portugal; E-mail: [email protected]. Submitted for publication February 2014. Accepted for publication June 2014. 0195-9131/15/4703-0575/0 MEDICINE & SCIENCE IN SPORTS & EXERCISEÒ Copyright Ó 2014 by the American College of Sports Medicine DOI: 10.1249/MSS.0000000000000426
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MARQUES, A., R. SANTOS, U. EKELUND, and L. B. SARDINHA. Association between Physical Activity, Sedentary Time, and Healthy Fitness in Youth. Med. Sci. Sports Exerc., Vol. 47, No. 3, pp. 575–580, 2015. Purpose: This study aimed to examine the associations between objectively measured physical activity (PA), sedentary time, and health-related fitness and to investigate the combined association of PA and sedentary time on health-related fitness in youths. Methods: PA and sedentary time were assessed with accelerometers in 2506 youths age 10–18 yr (Mage = 13.2 T 2.3). Participants were classified as active (Q60 minIdj1 of moderate-to-vigorous physical activity (MVPA)) versus inactive (G60 minIdj1 of MVPA) and as ‘‘low sedentary’’ versus ‘‘high sedentary’’ (according to the median value of sedentary time per day) and thereafter grouped as active/low sedentary, active/high sedentary, inactive/low sedentary, and inactive/high sedentary. Five physical fitness tests (body mass index, push-ups, curl-ups, sit and reach, and the Progressive Aerobic Cardiovascular Endurance Run test) were assessed with FITNESSGRAM, and participants were categorized as being in the healthy fitness zone (HFZ) versus the unhealthy fitness zone. A fitness composite score was calculated using the individual fitness test z-score. Regression models were used to examine the relation between PA, sedentary time, and physical fitness. Results: Time spent in MVPA (minIdj1) (A = 0.002, P G 0.001) was significantly associated with fitness score independent of sedentary time. Sedentary time was not associated with physical fitness independent of MVPA. Compared with the inactive/high sedentary group (referent), being categorized as active/low sedentary was associated with increased likelihood of being in the HFZ for sit and reach (odds ratio, 2.55; 95% confidence interval, 1.96–3.32) and having a higher fitness composite score (odds ratio, 1.38; 95% confidence interval, 1.13–1.69). Conclusions: Time in MVPA was associated with better physical fitness independent of sedentary time. Participants classified as active/low sedentary had higher odds of being in the HFZ, for flexibility, and to have a better fitness composite score. These findings suggest that time in MVPA contributes to better physical fitness in youths. Key Words: PHYSICAL FITNESS, FITNESSGRAM, HEALTH, COMBINED EFFECT
FITNESSGRAM test battery (19,31). Results from these studies indicated that attaining the recommended levels of PA and spending less time in sedentary behaviors lead to increase of the odds of achieving the FITNESSGRAM healthy zones. As recognized by the authors of these studies, self-report PA and sedentary time could be subjected to recall and social desirability bias (19,31). Objective assessments of PA and sedentary time are less prone to bias and may therefore provide more precise estimates of the associations between PA, sedentary time, and health-related fitness. Furthermore, none of these two studies analyzed the independent and combined associations between PA and sedentary time with individual fitness variables and with an overall fitness score. We have recently suggested that PA and sedentary time are independently and interdependently associated with CRF (24). However, few studies have examined the detailed associations between objectively measured MVPA, sedentary time, and several components of physical fitness in youth. Understanding the independent and combined association of PA and sedentary time on physical fitness is important from a public health perspective. Therefore, the aims of this study were to examine the associations between objectively measured PA, sedentary time, and health-related fitness and to investigate the combined association of PA and sedentary time on health-related fitness in children and adolescents age 10–18 yr.
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METHODS Study design and participants. The present study used data from a nationwide cross-sectional study aimed to examine students’ PA, physical fitness, overweight/obesity prevalence, and related factors in Portuguese school-age children and adolescents age 10–18 yr. Data from a proportionate stratified random sample of students were collected, taking into account the location and number of students by age and gender in each school in the Portuguese administrative regions (Alentejo, Algarve, Centro, Lisboa, and Norte). All students age between 10 and 18 yr with a health status that allowed participation in physical education classes were eligible. Data from 22,179 children and adolescents were collected (89% response rate). PA and sedentary time were objectively measured in a randomly selected subsample of 3165 youths. Participants that did not comply with accelerometer data collection criteria and missed data on any of the physical fitness components were excluded from the analysis. The final sample consisted of 2506 (79%) youths (1180 boys) age 10–18 yr (Mage = 13.2 T 2.3). Data collection was conducted during 2008–2009. Participants were examined during physical education classes by specifically trained physical education teachers. Participants were informed about the objectives of the study, and a written informed consent was obtained from the legal guardians. The study was approved by the institutional review board of the Faculty of Human Kinetics, University of Lisbon.
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Measures. Free living PA and sedentary time were measured with the accelerometer GT1M ActiGraph. Participants were instructed to wear the accelerometer, attached tightly on the hip by an elastic belt on the right side, during all waking hours except while bathing or doing other waterbased activities. The length of the sampling interval was set at 15 s to allow a more refined estimate of PA intensity (32). Data were downloaded to a computer, and an automated data reduction program (MAHUffe, http://www.mrc-epid.cam.ac.uk) was used to analyze the raw outcome data. Sequences of consecutive zeros for periods with 60 min were identified and were defined as missing data. At least 3 d of recording (two weekdays and one weekend day) with a minimum of 600-min wear time was required for inclusion of a day in analysis. Overall activity levels were expressed in terms of counts per minute, and intensity thresholds were established according to a previous study (30). Sedentary time was set at a range of 0–100 counts/min. MVPA was defined as Q4 METs and age-specific intensity thresholds according to those proposed by Freedson et al. (7). Participants were classified as meeting PA guidelines (Q60 minIdj1 in MVPA) or not meeting the guidelines (G60 minIdj1 in MVPA) (34). On the basis of sedentary time, participants were also classified as ‘‘low sedentary’’ and ‘‘high sedentary’’ according to the median value by age and sex. Using these classifications, participants were grouped in PA/sedentary time as active/ low sedentary, active/high sedentary, inactive/low sedentary, and inactive/high sedentary. To assess health-related fitness, the FITNESSGRAM test battery was used. The specific measures of the FITNESSGRAM are BMI, calculated from measured weight and height (kgImj2), push-ups (upper body strength and endurance), curl-ups (abdominal strength and endurance), sit and reach (flexibility of the hamstrings and the lower back), and the Progressive Aerobic Cardiovascular Endurance Run (PACER) test (CRF). In each test, participants were classified into two zones, HFZ and risk zone (unhealthy zone), according to the FITNESSGRAM cut points based on sex- and age-related criterion-referenced standards (4). A standardized fitness composite score (z-score) was calculated by summing the individual z-scores (individual value minus mean/SD) of the five fitness tests and thereafter dividing by five. All physical fitness test z-scores were calculated, specific for age and sex group. Data analysis. Descriptive statistics are presented as means and SD or percentages. t-Tests and chi-square tests were performed to assess sex differences for PA, sedentary time, physical fitness components (BMI, push-ups, curl-ups, and sit and reach), and the overall physical fitness score. The PACER test was not included in the analyses as an individual fitness test because we recently published a study (24) that analyzed the association of MVPA, sedentary time, and CRF. Binary logistic regressions were used first to estimate the independent relation between PA or sedentary time and physical fitness components. Then, we mutually adjusted PA and sedentary time for each other and examined the independent associations between PA and sedentary time
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on the physical fitness components. Linear regression analysis was performed to examine the independent associations between time spent in MVPA and sedentary time with the fitness composite score. The relation between physical fitness components, fitness composite score, and the combined association of PA and sedentary time was analyzed using multinomial logistic regression. The group of inactive/high sedentary was used as the reference group. All regressions models were performed with boys and girls combined, and the models were adjusted for sex because no significant interaction effect (sex–PA/sedentary time) was observed. Furthermore, we tested whether age modified the associations between PA/sedentary time and fitness components by including interaction terms (e.g., MVPA–age) in our models. No significant interactions were observed, and the entire sample was analyzed, adjusted for age. All analyses were further adjusted for accelerometer wear time. Data analysis was performed using SPSS version 20. The level of significance was set at 0.05.
RESULTS Descriptive statistics are presented in Table 1. On average, participants spent 41.5 T 24.7 minIdj1 in MVPA and 534.7 T 103.1 minIdj1 in sedentary behaviors. Boys were significantly more active (P G 0.001) and less sedentary (P G 0.001) than girls. Only 20.9% of the sample achieved the recommended levels of PA (e60 minIdj1 of MVPA), and the difference was significant between boys and girls (P G 0.001).
Of the participants, 43.7% was categorized as inactive/ high sedentary, 35.4% was categorized as inactive/low sedentary, 6.7% was categorized as active/high sedentary, and 14.3% was active/low sedentary. Most participants were in the HFZ of BMI (76.9%), upper body strength (69.1%), abdominal strength (91.0%), flexibility of the hamstrings and the lower back (58.1%), and CRF (77.6%) according to the FITNESSGRAM criteria. The associations and mutually adjusted associations between MVPA, sedentary time, and physical fitness are presented in Table 2. Time spent in MVPA (minIdj1) was positively associated with achieving the healthy zones for flexibility (odds ratio (OR), 1.020; 95% confidence interval (CI), 1.016–1.023; P G 0.001), BMI (OR, 1.004; 95% CI, 1.000–1.008; P G 0.01), and upper body strength (OR, 1.005; 95% CI, 1.002–1.009; P G 0.05). Sedentary time was associated with lower odds for flexibility (OR, 0.998; 95% CI, 0.997–0.998; P G 0.001) and abdominal strength (OR, 0.998; 95% CI, 0.997–1.000; P G 0.05). Time spent in MVPA (minIdj1) (A = 0.011; 95% CI, 0.007–0.016; P G 0.001) was significantly associated with the physical fitness composite score, and this association was somewhat attenuated but statistically significant after further adjustment for time spent sedentary (A = 0.002; 95% CI, 0.001–0.003). In contrast, timespent sedentary was not associated with the fitness composite score. Results of the multinomial logistic regression analysis for the combined associations between MVPA and sedentary time with physical fitness adjusted for age and sex and for
TABLE 1. Descriptive characteristics of the participants.
Age MVPA (minIdj1)a Inactive (minIdj1) Active (minIdj1) Sedentary time (minIdj1)a High sedentary (minIdj1) Low sedentary (minIdj1) Physical activityb Inactive Active Physical activity/sedentary timeb Inactive/high sedentary Inactive/less sedentary Active/high sedentary Active/less sedentary BMIb Unhealthy zone Healthy zone Push-upsb Unhealthy zone Healthy zone Curl-upsb Unhealthy zone Healthy zone Sit and reachb Unhealthy zone Healthy zone Fitness composite scorea
13.2 41.5 31.7 78.4 534.0 616.4 460.5
T T T T T T T
2.3 24.7 14.6 19.7 103.1 73.1 62.1
Boys (n = 1180) Mean T SD or % (n) 13.1 50.5 35.7 81.5 521.8 620.4 452.8
T T T T T T T
2.3 26.8 14.2 19.6 109.2 79.9 65.1
Girls (n = 1326) Mean T SD or % (n) 13.3 33.5 29.0 70.4 544.8 613.6 468.9
T T T T T T T
2.3 96.1 14.2 17.7 96.1 68.1 57.6
79.1 (1982) 20.9 (524)
67.7 (799) 32.3 (381)
89.1 (1181) 10.9 (145)
43.7 35.4 6.7 14.3
39.3 28.4 11.1 21.1
47.5 41.6 2.7 8.1
P 0.019 G0.001 G0.001 G0.001 G0.001 0.116 G0.001 G0.001
G0.001 (1095) (887) (168) (358)
(464) (335) (131) (249)
(630) (552) (36) (107) 0.058
23.1 (579) 76.9 (1927)
21.3 (251) 78.6 (927)
24.6 (326) 75.4 (1000)
30.9 (774) 69.1 (1732)
30.9 (365) 69.1 (815)
30.9 (410) 69.1 (916)
9.0 (226) 91.0 (2280)
6.9 (81) 93.1 (1099)
10.9 (145) 91.1 (1208
41.9 (1050) 58.1 (1456) 0.0 T 0.6
22.2 (262) 77.8 (918) 0.0 T 0.6
59.4 (788) 40.6 (538) 0.0 T 0.6
0.995
G0.001
G0.001
0.998
Participants were classified as low sedentary and high sedentary according to the median split by age and sex. Fitness composite score is a composite variable calculated by summing up the five fitness test z-scores and dividing by five. a Tested with t-test. b Tested with chi-square test.
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All (n = 2506) Mean T SD or % (n)
TABLE 2. Associations between MVPA and sedentary time with being categorized as being in the HFZ. Achieve HFZ
MVPAa
MVPA
Sedentary Time
Sedentary Timea
b
BMI Unhealthy zone Healthy zone Push-upsb Unhealthy zone Healthy zone Curl-upsb Unhealthy zone Healthy zone Sit and reachb Unhealthy zone Healthy zone Fitness composite scorec
1.000 (reference) 1.004 (1.000–1.008)*
1.000 (reference) 1.004 (1.000–1.008)*
1.000 (reference) 1.000 (0.999–1.001)
1.000 (reference) 1.000 (0.999–1.001)
1.000 (reference) 1.005 (1.002–1.009)**
1.000 (reference) 1.006 (1.003–1.010)**
1.000 (reference) 1.000 (0.999–1.001)
1.000 (reference) 1.000 (1.000–1.002)
1.000 (reference) 0.997 (0.992–1.003)
1.000 (reference) 0.995 (0.989–1.001)
1.000 (reference) 0.998 (0.997–1.000)*
1.000 (reference) 0.998 (0.997–0.999)**
1.000 (reference) 1.020 (1.016–1.023)*** 0.002 (0.001–0.003)***
1.000 (reference) 1.018 (1.014–1.022)*** 0.003 (0.002–0.004)***
1.000 (reference) 0.998 (0.997–0.998)*** 0.000 (0.000–0.000)
1.000 (reference) 0.999 (0.998–1.000)** 0.000 (0.000–0.000)
MVPA and sedentary time were modeled as continuous variables. The models were adjusted for age and sex. Composite fitness score is a composite variable calculated by summing up the five fitness test z-scores and dividing by five. The relation between MVPA, sedentary time (independent and mutually adjusted), and the composite fitness score were tested by linear regression analysis. Data were analyzed using binary logistic and linear regression analyses (n = 2506). a MVPA is additionally adjusted for sedentary time, and sedentary time is mutually adjusted for PA. b Data are OR and 95% CI. c Data are beta coefficients and 95% CI. *P G 0.05. **P G 0.01. ***P G 0.001.
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accelerometer wear time are shown in Table 3. Participants classified as active/low sedentary were more likely to be categorized in the healthy zone for flexibility (OR, 2.55; 95% CI, 1.96–3.32; P G 0.001) than participants from the inactive/high sedentary group. Participants classified as active/ low sedentary (OR, 1.38; 95% CI, 1.13–1.69; P G 0.01) and those classified as active/high sedentary (OR, 1.36; 95% CI, 1.04–1.79; P G 0.05) were more likely to have a higher fitness composite score compared with those from the inactive/ high sedentary group.
DISCUSSION The results from present study suggest that time spent in MVPA is associated with higher physical fitness composite score independent of time spent sedentary. In combined
analyses, higher odds of being categorized in the healthy zone for flexibility of the hamstrings and the lower back was observed with increasing activity levels. The composite score of physical fitness reflects the general physical fitness level of each participant. Higher scores may indicate the achievement of the healthy zone in more of the FITNESSGRAM physical fitness components. This is an important indication because there is evidence that a combined and accumulative effect of some physical fitness components have a positive outcome on young people’s health (2,18). Higher levels of time spent in MVPA were associated with increased odds of being categorized in the HFZ for body composition, upper body strength, and flexibility independent of sedentary time. Although some participants were categorized as healthy without achieving the recommended level for PA, these results emphasize the importance of attaining the recommended levels of PA.
TABLE 3. Multinomial regression examining the likelihood of being categorized in the healthy zone of physical fitness components by combined activity and sedentary groups (n = 2506). PA/Sedentary Time Group (Inactive/High Sedentary: Referent) Inactive/Low Sedentary, OR 95% CI BMI Unhealthy zone Healthy zone Push-ups Unhealthy zone Healthy zone Curl-ups Unhealthy zone Healthy zone Sit and reach Unhealthy zone Healthy zone Fitness composite score
Active/High Sedentary, OR 95% CI
Active/Low Sedentary, OR 95% CI
1.00 (reference) 0.97 (0.79–1.19)
1.00 (reference) 1.44 (0.95–2.19)
1.00 (reference) 1.35 (1.00–1.81)
1.00 (reference) 0.76 (0.63–0.92)*
1.00 (reference) 0.97 (0.68–1.38)
1.00 (reference) 1.18 (0.90–1.54)
1.00 (reference) 1.46 (1.06–2.00)**
1.00 (reference) 1.02 (0.59–1.74)
1.00 (reference) 1.26 (0.83–1.92)
1.00 (reference) 1.21 (1.02–1.45)** 0.99 (0.85–1.16)
1.00 (reference) 1.85 (1.31–2.61)*** 1.36 (1.04–1.79)**
1.00 (reference) 2.55 (1.96–3.32)*** 1.38 (1.13–1.69)*
Multinomial regressions were tested for selected variables. The models were adjusted for age and sex and for accelerometer wear time. Participants were classified as active (Q60 minIdj1 in MVPA) or inactive (G60 minIdj1 in MVPA). Participants were also classified as low sedentary and high sedentary according to the median split by age and sex. Fitness composite score is a composite variable calculated by summing up the five fitness test z-scores and dividing by five. *P G 0.01. **P G 0.05. ***P G 0.001.
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PA, SEDENTARY TIME, AND HEALTHY FITNESS
change in adiposity in youths. The disparity of the results could be due to different methodological approaches to assess PA and sedentary time. Specific sedentary behaviors assessed by self-report (e.g., sedentary screen time) seems to be associated with adiposity (13,28,31), whereas objectively measured total sedentary time seems unrelated to adiposity (5). Furthermore, sedentary time may lead to increases in adiposity whereas high adiposity may also increase time spent sedentary (a bidirectional association). Indeed, this has previously been suggested in observational (5) and prospective studies (9). The strengths of this study include the following: the objective assessment of PA and time spent sedentary in a large nationwide sample of children and adolescents representing various geographical locations of Portugal and the use of a cut point of G100 counts per minute to identify sedentary behaviors, as this cutoff has shown excellent accuracy (30). Nevertheless, this study has some limitations. These include the cross-sectional design, which means that causal inferences cannot be made, and the fact that the accelerometers do not capture water-based activities, cycling, and upper body activities. The HFZ cutoffs used in the study were developed in the United States and may not be applicable to Portuguese children. However, it should be recognized that the cutoffs developed for body composition and aerobic capacity standards included in the composite score are related to health and are independent of the sample distribution. Finally, all physical fitness tests were conducted in schools and it is likely that more accurate measurements would have been obtained if these tests were performed in a laboratory. However, any error in the fitness tests associated with field testing is likely to be random, therefore attenuating the observed associations.
CONCLUSIONS AND RECOMMENDATION Time spent in MVPA was independently associated with physical fitness components and fitness composite score. The combined effect of PA and time devoted to sedentary behaviors was also related to physical fitness components and fitness composite score. However, these associations were mainly driven by time spent in MVPA rather than sedentary time. These findings may suggest that PA contributes to physical fitness to a greater extent than sedentary behaviors do. From a public health perspective and physical education curricular policy, these results reinforce the importance of promoting PA and reducing time in sedentary behaviors in relation to physical fitness in youths. The authors gratefully acknowledge the participation of the adolescents in this study and the physical education teachers for their assistance in helping collect data. This research was supported by the Interdisciplinary Center for the Study of Human Performance— Portuguese Science and Technology Foundation. The authors declare that there are no conflicts of interest. The results of the present study do not constitute endorsement by the American College of Sports Medicine.
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Moreover, the results from linear regression analyses confirmed the observed results from the stratified analyses and higher amounts of time spent in time spent in MVPA was associated with a more favorable fitness composite score. Accumulating approximately 47 min of time spent in MVPA was associated with a positive fitness composite score (i.e., 90), suggesting that meeting PA guidelines (Q60 minIdj1 in MVPA) seems beneficial for overall physical fitness. Given the known associations between physical fitness and indicators of health in young people (11,18,26), we may speculate that physical fitness may partly mediate the associations between PA and health status. We further verified whether the combined association of PA and sedentary time was related to physical fitness. Although there was independent association between PA and sedentary time on physical fitness, combined association was also observed. Those classified as active/low sedentary had higher odds of being in the FITNESSGRAM healthy zone for flexibility of the hamstrings and the lower back than those classified as inactive/high sedentary. Moreover, those categorized as active/low sedentary were more likely to have a higher overall score of physical fitness than those categorized as inactive/high sedentary. This highlights the importance of increasing PA and decreasing time devoted to sedentary behaviors to improve young people’s health and possibly prevent diseases. However, these two behaviors may be seen as independent because they are two different constructs and may carry independent health risks (27). Therefore, efforts to increase PA might be independent of efforts to decrease sedentary behaviors. Among young Portuguese people, the promotion of higher levels of PA seems particularly important, given that previous data have shown that only 36% of those age 10–11 yr and 4% of those age 16–17 yr were considered sufficiently active according to the World Health Organization 2010 PA guidelines (1). However, although the prevalence of sufficiently active Portuguese children seems low, it is still higher than the prevalence estimates reported in youths in the United States (29). Despite differences in prevalence estimates between studies, it is likely that our results are applicable to other settings because differences in the prevalence of sufficiently active youths do not affect the statistical association analysis. Therefore, our results emphasize the importance of addressing PA promotion programs, particularly in countries where majority of youths do not attend PA recommendation. Thus, young people’s parents and educators should be challenged to develop strategies to make youths more active. Being physically active increases the odds of being categorized as attaining a high level of healthrelated fitness. We did not observe an association between BMI and sedentary time. However, time spent in MVPA was related to BMI also after adjusting for sedentary time. This observation is opposite to some (10,31) and consistent with other cross-sectional (19,22) and prospective studies (3,8), suggesting that sedentary time is unrelated to adiposity and
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18. Moreira C, Santos R, de Farias Junior JC, et al. Metabolic risk factors, physical activity and physical fitness in Azorean adolescents: a cross-sectional study. BMC Public Health. 2011;11:214. 19. Morrow JR Jr, Tucker JS, Jackson AW, Martin SB, Greenleaf CA, Petrie TA. Meeting physical activity guidelines and health-related fitness in youth. Am J Prev Med. 2013;44(5):439–44. 20. Ortega FB, Ruiz JR, Castillo MJ, Sjo¨stro¨m M. Physical fitness in childhood and adolescence: a powerful marker of health. Int J Obes (Lond). 2008;32(1):1–11. 21. Plowman SA. Muscular strength, endurance and flexibility assessments. In: Welk GJ, Meredith MD, editors. FITNESSGRAM/ ACTIVITYGRAM Reference Guide. Dallas (TX): The Cooper Institute; 2008. pp. 8–8-1–55. 22. 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(3):242–51. 23. Ruiz JR, Ortega FB, Martı´nez-Go´mez D, et al. Objectively measured physical activity and sedentary time in European adolescents: the HELENA study. Am J Epidemiol. 2011;174(2):173–84. 24. Santos R, Mota J, Okely AD, et al. The independent associations of sedentary behaviour and physical activity on cardiorespiratory fitness. Br J Sports Med. 2014;48(20):1508–12. 25. Simmons RK, Griffin SJ, Steele R, Wareham NJ, Ekelund U; ProActive Research Team. Increasing overall physical activity and aerobic fitness is associated with improvements in metabolic risk: cohort analysis of the ProActive trial. Diabetologia. 2008;51(5): 787–94. 26. Stabelini Neto A, Sasaki JE, Mascarenhas LP, et al. Physical activity, cardiorespiratory fitness, and metabolic syndrome in adolescents: a cross-sectional study. BMC Public Health. 2011;11:674. 27. Tremblay MS, Colley RC, Saunders TJ, Healy GN, Owen N. Physiological and health implications of a sedentary lifestyle. Appl Physiol Nutr Metab. 2010;35(6):725–40. 28. Tremblay MS, Willms JD. Is the Canadian childhood obesity epidemic related to physical inactivity? Int J Obes Relat Metab Disord. 2003;27(9):1100–5. 29. Troiano RP, Berrigan D, Dodd KW, Maˆsse LC, Tilert T, McDowell M. Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc. 2008;40(1):181–8. 30. Trost SG, Loprinzi PD, Moore R, Pfeiffer KA. Comparison of accelerometer cut points for predicting activity intensity in youth. Med Sci Sports Exerc. 2011;43(7):1360–8. 31. Tucker JS, Martin S, Jackson AW, Morrow JR Jr, Greenleaf CA, Petrie TA. Relations between sedentary behavior and FITNESSGRAMÒ healthy fitness zone achievement and physical activity. J Phys Act Health. 2014;11(5):1006–11. 32. Ward DS, Evenson KR, Vaughn A, Rodgers AB, Troiano RP. Accelerometer use in physical activity: best practices and research recommendations. Med Sci Sports Exerc. 2005;37(11 Suppl):S582–8. 33. Welk GJ, Laurson KR, Eisenmann JC, Cureton KJ. Development of youth aerobic-capacity standards using receiver operating characteristic curves. Am J Prev Med. 2011;41(4 Suppl 2):S111–6. 34. World Health Organization. Global Recommendations on Physical Activity for Health. Geneva (Switzerland): World Health Organization; 2010.
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ABSTRACT
P
(CRF)) is determined by nonmodifiable factors such as growth, sexual maturation, sex, age, and heredity; however, it is also influenced by moderate-to-vigorous physical activity (MVPA) and sedentary time (3). High levels of physical activity (PA) are related to better aerobic fitness and lower body mass index (BMI) (23). Sedentary time is related to lower CRF (17,24) and increase in childhood BMI (16). The FITNESSGRAM test battery was developed to assess physical fitness among young people with a health-related approach, and it is widely used in some states and school districts in the United States of America (14) and in other countries (15,18,23). On the basis of these measures, students are stratified as being above or below a predetermined threshold for the healthy fitness zone (HFZ), indicating whether their level of fitness is sufficient to reduce their risk for hypokinetic diseases. One of the most important contributions of the FITNESSGRAM is that the assessments are based on health standards for CRF (33), body composition (12), and musculoskeletal function (21). Two studies have recently examined the relation between self-reported PA and sedentary behaviors and several components of health-related fitness in young people using the
hysical fitness is associated with a variety of health benefits in young people (11), and it is considered one of the most important health status markers that predict cardiovascular disease and mortality (20). In children and adolescents, cross-sectional (18,26) and prospective studies (6,25) show that high levels of physical fitness are associated with improved health-related biomarkers that may further influence health in young adulthood. Physical fitness (e.g., body composition, upper body strength and endurance, abdominal strength and endurance, flexibility of the hamstrings and the lower back, cardiorespiratory fitness
Address for correspondence: Luı´s B. Sardinha, Ph.D., Interdisciplinary Center for the Study of Human Performance, Faculty of Human Kinetics, University of Lisbon, Estrada da Costa, 1499-002 Cruz-Quebrada, Portugal; E-mail: [email protected]. Submitted for publication February 2014. Accepted for publication June 2014. 0195-9131/15/4703-0575/0 MEDICINE & SCIENCE IN SPORTS & EXERCISEÒ Copyright Ó 2014 by the American College of Sports Medicine DOI: 10.1249/MSS.0000000000000426
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MARQUES, A., R. SANTOS, U. EKELUND, and L. B. SARDINHA. Association between Physical Activity, Sedentary Time, and Healthy Fitness in Youth. Med. Sci. Sports Exerc., Vol. 47, No. 3, pp. 575–580, 2015. Purpose: This study aimed to examine the associations between objectively measured physical activity (PA), sedentary time, and health-related fitness and to investigate the combined association of PA and sedentary time on health-related fitness in youths. Methods: PA and sedentary time were assessed with accelerometers in 2506 youths age 10–18 yr (Mage = 13.2 T 2.3). Participants were classified as active (Q60 minIdj1 of moderate-to-vigorous physical activity (MVPA)) versus inactive (G60 minIdj1 of MVPA) and as ‘‘low sedentary’’ versus ‘‘high sedentary’’ (according to the median value of sedentary time per day) and thereafter grouped as active/low sedentary, active/high sedentary, inactive/low sedentary, and inactive/high sedentary. Five physical fitness tests (body mass index, push-ups, curl-ups, sit and reach, and the Progressive Aerobic Cardiovascular Endurance Run test) were assessed with FITNESSGRAM, and participants were categorized as being in the healthy fitness zone (HFZ) versus the unhealthy fitness zone. A fitness composite score was calculated using the individual fitness test z-score. Regression models were used to examine the relation between PA, sedentary time, and physical fitness. Results: Time spent in MVPA (minIdj1) (A = 0.002, P G 0.001) was significantly associated with fitness score independent of sedentary time. Sedentary time was not associated with physical fitness independent of MVPA. Compared with the inactive/high sedentary group (referent), being categorized as active/low sedentary was associated with increased likelihood of being in the HFZ for sit and reach (odds ratio, 2.55; 95% confidence interval, 1.96–3.32) and having a higher fitness composite score (odds ratio, 1.38; 95% confidence interval, 1.13–1.69). Conclusions: Time in MVPA was associated with better physical fitness independent of sedentary time. Participants classified as active/low sedentary had higher odds of being in the HFZ, for flexibility, and to have a better fitness composite score. These findings suggest that time in MVPA contributes to better physical fitness in youths. Key Words: PHYSICAL FITNESS, FITNESSGRAM, HEALTH, COMBINED EFFECT
FITNESSGRAM test battery (19,31). Results from these studies indicated that attaining the recommended levels of PA and spending less time in sedentary behaviors lead to increase of the odds of achieving the FITNESSGRAM healthy zones. As recognized by the authors of these studies, self-report PA and sedentary time could be subjected to recall and social desirability bias (19,31). Objective assessments of PA and sedentary time are less prone to bias and may therefore provide more precise estimates of the associations between PA, sedentary time, and health-related fitness. Furthermore, none of these two studies analyzed the independent and combined associations between PA and sedentary time with individual fitness variables and with an overall fitness score. We have recently suggested that PA and sedentary time are independently and interdependently associated with CRF (24). However, few studies have examined the detailed associations between objectively measured MVPA, sedentary time, and several components of physical fitness in youth. Understanding the independent and combined association of PA and sedentary time on physical fitness is important from a public health perspective. Therefore, the aims of this study were to examine the associations between objectively measured PA, sedentary time, and health-related fitness and to investigate the combined association of PA and sedentary time on health-related fitness in children and adolescents age 10–18 yr.
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METHODS Study design and participants. The present study used data from a nationwide cross-sectional study aimed to examine students’ PA, physical fitness, overweight/obesity prevalence, and related factors in Portuguese school-age children and adolescents age 10–18 yr. Data from a proportionate stratified random sample of students were collected, taking into account the location and number of students by age and gender in each school in the Portuguese administrative regions (Alentejo, Algarve, Centro, Lisboa, and Norte). All students age between 10 and 18 yr with a health status that allowed participation in physical education classes were eligible. Data from 22,179 children and adolescents were collected (89% response rate). PA and sedentary time were objectively measured in a randomly selected subsample of 3165 youths. Participants that did not comply with accelerometer data collection criteria and missed data on any of the physical fitness components were excluded from the analysis. The final sample consisted of 2506 (79%) youths (1180 boys) age 10–18 yr (Mage = 13.2 T 2.3). Data collection was conducted during 2008–2009. Participants were examined during physical education classes by specifically trained physical education teachers. Participants were informed about the objectives of the study, and a written informed consent was obtained from the legal guardians. The study was approved by the institutional review board of the Faculty of Human Kinetics, University of Lisbon.
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Measures. Free living PA and sedentary time were measured with the accelerometer GT1M ActiGraph. Participants were instructed to wear the accelerometer, attached tightly on the hip by an elastic belt on the right side, during all waking hours except while bathing or doing other waterbased activities. The length of the sampling interval was set at 15 s to allow a more refined estimate of PA intensity (32). Data were downloaded to a computer, and an automated data reduction program (MAHUffe, http://www.mrc-epid.cam.ac.uk) was used to analyze the raw outcome data. Sequences of consecutive zeros for periods with 60 min were identified and were defined as missing data. At least 3 d of recording (two weekdays and one weekend day) with a minimum of 600-min wear time was required for inclusion of a day in analysis. Overall activity levels were expressed in terms of counts per minute, and intensity thresholds were established according to a previous study (30). Sedentary time was set at a range of 0–100 counts/min. MVPA was defined as Q4 METs and age-specific intensity thresholds according to those proposed by Freedson et al. (7). Participants were classified as meeting PA guidelines (Q60 minIdj1 in MVPA) or not meeting the guidelines (G60 minIdj1 in MVPA) (34). On the basis of sedentary time, participants were also classified as ‘‘low sedentary’’ and ‘‘high sedentary’’ according to the median value by age and sex. Using these classifications, participants were grouped in PA/sedentary time as active/ low sedentary, active/high sedentary, inactive/low sedentary, and inactive/high sedentary. To assess health-related fitness, the FITNESSGRAM test battery was used. The specific measures of the FITNESSGRAM are BMI, calculated from measured weight and height (kgImj2), push-ups (upper body strength and endurance), curl-ups (abdominal strength and endurance), sit and reach (flexibility of the hamstrings and the lower back), and the Progressive Aerobic Cardiovascular Endurance Run (PACER) test (CRF). In each test, participants were classified into two zones, HFZ and risk zone (unhealthy zone), according to the FITNESSGRAM cut points based on sex- and age-related criterion-referenced standards (4). A standardized fitness composite score (z-score) was calculated by summing the individual z-scores (individual value minus mean/SD) of the five fitness tests and thereafter dividing by five. All physical fitness test z-scores were calculated, specific for age and sex group. Data analysis. Descriptive statistics are presented as means and SD or percentages. t-Tests and chi-square tests were performed to assess sex differences for PA, sedentary time, physical fitness components (BMI, push-ups, curl-ups, and sit and reach), and the overall physical fitness score. The PACER test was not included in the analyses as an individual fitness test because we recently published a study (24) that analyzed the association of MVPA, sedentary time, and CRF. Binary logistic regressions were used first to estimate the independent relation between PA or sedentary time and physical fitness components. Then, we mutually adjusted PA and sedentary time for each other and examined the independent associations between PA and sedentary time
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on the physical fitness components. Linear regression analysis was performed to examine the independent associations between time spent in MVPA and sedentary time with the fitness composite score. The relation between physical fitness components, fitness composite score, and the combined association of PA and sedentary time was analyzed using multinomial logistic regression. The group of inactive/high sedentary was used as the reference group. All regressions models were performed with boys and girls combined, and the models were adjusted for sex because no significant interaction effect (sex–PA/sedentary time) was observed. Furthermore, we tested whether age modified the associations between PA/sedentary time and fitness components by including interaction terms (e.g., MVPA–age) in our models. No significant interactions were observed, and the entire sample was analyzed, adjusted for age. All analyses were further adjusted for accelerometer wear time. Data analysis was performed using SPSS version 20. The level of significance was set at 0.05.
RESULTS Descriptive statistics are presented in Table 1. On average, participants spent 41.5 T 24.7 minIdj1 in MVPA and 534.7 T 103.1 minIdj1 in sedentary behaviors. Boys were significantly more active (P G 0.001) and less sedentary (P G 0.001) than girls. Only 20.9% of the sample achieved the recommended levels of PA (e60 minIdj1 of MVPA), and the difference was significant between boys and girls (P G 0.001).
Of the participants, 43.7% was categorized as inactive/ high sedentary, 35.4% was categorized as inactive/low sedentary, 6.7% was categorized as active/high sedentary, and 14.3% was active/low sedentary. Most participants were in the HFZ of BMI (76.9%), upper body strength (69.1%), abdominal strength (91.0%), flexibility of the hamstrings and the lower back (58.1%), and CRF (77.6%) according to the FITNESSGRAM criteria. The associations and mutually adjusted associations between MVPA, sedentary time, and physical fitness are presented in Table 2. Time spent in MVPA (minIdj1) was positively associated with achieving the healthy zones for flexibility (odds ratio (OR), 1.020; 95% confidence interval (CI), 1.016–1.023; P G 0.001), BMI (OR, 1.004; 95% CI, 1.000–1.008; P G 0.01), and upper body strength (OR, 1.005; 95% CI, 1.002–1.009; P G 0.05). Sedentary time was associated with lower odds for flexibility (OR, 0.998; 95% CI, 0.997–0.998; P G 0.001) and abdominal strength (OR, 0.998; 95% CI, 0.997–1.000; P G 0.05). Time spent in MVPA (minIdj1) (A = 0.011; 95% CI, 0.007–0.016; P G 0.001) was significantly associated with the physical fitness composite score, and this association was somewhat attenuated but statistically significant after further adjustment for time spent sedentary (A = 0.002; 95% CI, 0.001–0.003). In contrast, timespent sedentary was not associated with the fitness composite score. Results of the multinomial logistic regression analysis for the combined associations between MVPA and sedentary time with physical fitness adjusted for age and sex and for
TABLE 1. Descriptive characteristics of the participants.
Age MVPA (minIdj1)a Inactive (minIdj1) Active (minIdj1) Sedentary time (minIdj1)a High sedentary (minIdj1) Low sedentary (minIdj1) Physical activityb Inactive Active Physical activity/sedentary timeb Inactive/high sedentary Inactive/less sedentary Active/high sedentary Active/less sedentary BMIb Unhealthy zone Healthy zone Push-upsb Unhealthy zone Healthy zone Curl-upsb Unhealthy zone Healthy zone Sit and reachb Unhealthy zone Healthy zone Fitness composite scorea
13.2 41.5 31.7 78.4 534.0 616.4 460.5
T T T T T T T
2.3 24.7 14.6 19.7 103.1 73.1 62.1
Boys (n = 1180) Mean T SD or % (n) 13.1 50.5 35.7 81.5 521.8 620.4 452.8
T T T T T T T
2.3 26.8 14.2 19.6 109.2 79.9 65.1
Girls (n = 1326) Mean T SD or % (n) 13.3 33.5 29.0 70.4 544.8 613.6 468.9
T T T T T T T
2.3 96.1 14.2 17.7 96.1 68.1 57.6
79.1 (1982) 20.9 (524)
67.7 (799) 32.3 (381)
89.1 (1181) 10.9 (145)
43.7 35.4 6.7 14.3
39.3 28.4 11.1 21.1
47.5 41.6 2.7 8.1
P 0.019 G0.001 G0.001 G0.001 G0.001 0.116 G0.001 G0.001
G0.001 (1095) (887) (168) (358)
(464) (335) (131) (249)
(630) (552) (36) (107) 0.058
23.1 (579) 76.9 (1927)
21.3 (251) 78.6 (927)
24.6 (326) 75.4 (1000)
30.9 (774) 69.1 (1732)
30.9 (365) 69.1 (815)
30.9 (410) 69.1 (916)
9.0 (226) 91.0 (2280)
6.9 (81) 93.1 (1099)
10.9 (145) 91.1 (1208
41.9 (1050) 58.1 (1456) 0.0 T 0.6
22.2 (262) 77.8 (918) 0.0 T 0.6
59.4 (788) 40.6 (538) 0.0 T 0.6
0.995
G0.001
G0.001
0.998
Participants were classified as low sedentary and high sedentary according to the median split by age and sex. Fitness composite score is a composite variable calculated by summing up the five fitness test z-scores and dividing by five. a Tested with t-test. b Tested with chi-square test.
PA, SEDENTARY TIME, AND HEALTHY FITNESS
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All (n = 2506) Mean T SD or % (n)
TABLE 2. Associations between MVPA and sedentary time with being categorized as being in the HFZ. Achieve HFZ
MVPAa
MVPA
Sedentary Time
Sedentary Timea
b
BMI Unhealthy zone Healthy zone Push-upsb Unhealthy zone Healthy zone Curl-upsb Unhealthy zone Healthy zone Sit and reachb Unhealthy zone Healthy zone Fitness composite scorec
1.000 (reference) 1.004 (1.000–1.008)*
1.000 (reference) 1.004 (1.000–1.008)*
1.000 (reference) 1.000 (0.999–1.001)
1.000 (reference) 1.000 (0.999–1.001)
1.000 (reference) 1.005 (1.002–1.009)**
1.000 (reference) 1.006 (1.003–1.010)**
1.000 (reference) 1.000 (0.999–1.001)
1.000 (reference) 1.000 (1.000–1.002)
1.000 (reference) 0.997 (0.992–1.003)
1.000 (reference) 0.995 (0.989–1.001)
1.000 (reference) 0.998 (0.997–1.000)*
1.000 (reference) 0.998 (0.997–0.999)**
1.000 (reference) 1.020 (1.016–1.023)*** 0.002 (0.001–0.003)***
1.000 (reference) 1.018 (1.014–1.022)*** 0.003 (0.002–0.004)***
1.000 (reference) 0.998 (0.997–0.998)*** 0.000 (0.000–0.000)
1.000 (reference) 0.999 (0.998–1.000)** 0.000 (0.000–0.000)
MVPA and sedentary time were modeled as continuous variables. The models were adjusted for age and sex. Composite fitness score is a composite variable calculated by summing up the five fitness test z-scores and dividing by five. The relation between MVPA, sedentary time (independent and mutually adjusted), and the composite fitness score were tested by linear regression analysis. Data were analyzed using binary logistic and linear regression analyses (n = 2506). a MVPA is additionally adjusted for sedentary time, and sedentary time is mutually adjusted for PA. b Data are OR and 95% CI. c Data are beta coefficients and 95% CI. *P G 0.05. **P G 0.01. ***P G 0.001.
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accelerometer wear time are shown in Table 3. Participants classified as active/low sedentary were more likely to be categorized in the healthy zone for flexibility (OR, 2.55; 95% CI, 1.96–3.32; P G 0.001) than participants from the inactive/high sedentary group. Participants classified as active/ low sedentary (OR, 1.38; 95% CI, 1.13–1.69; P G 0.01) and those classified as active/high sedentary (OR, 1.36; 95% CI, 1.04–1.79; P G 0.05) were more likely to have a higher fitness composite score compared with those from the inactive/ high sedentary group.
DISCUSSION The results from present study suggest that time spent in MVPA is associated with higher physical fitness composite score independent of time spent sedentary. In combined
analyses, higher odds of being categorized in the healthy zone for flexibility of the hamstrings and the lower back was observed with increasing activity levels. The composite score of physical fitness reflects the general physical fitness level of each participant. Higher scores may indicate the achievement of the healthy zone in more of the FITNESSGRAM physical fitness components. This is an important indication because there is evidence that a combined and accumulative effect of some physical fitness components have a positive outcome on young people’s health (2,18). Higher levels of time spent in MVPA were associated with increased odds of being categorized in the HFZ for body composition, upper body strength, and flexibility independent of sedentary time. Although some participants were categorized as healthy without achieving the recommended level for PA, these results emphasize the importance of attaining the recommended levels of PA.
TABLE 3. Multinomial regression examining the likelihood of being categorized in the healthy zone of physical fitness components by combined activity and sedentary groups (n = 2506). PA/Sedentary Time Group (Inactive/High Sedentary: Referent) Inactive/Low Sedentary, OR 95% CI BMI Unhealthy zone Healthy zone Push-ups Unhealthy zone Healthy zone Curl-ups Unhealthy zone Healthy zone Sit and reach Unhealthy zone Healthy zone Fitness composite score
Active/High Sedentary, OR 95% CI
Active/Low Sedentary, OR 95% CI
1.00 (reference) 0.97 (0.79–1.19)
1.00 (reference) 1.44 (0.95–2.19)
1.00 (reference) 1.35 (1.00–1.81)
1.00 (reference) 0.76 (0.63–0.92)*
1.00 (reference) 0.97 (0.68–1.38)
1.00 (reference) 1.18 (0.90–1.54)
1.00 (reference) 1.46 (1.06–2.00)**
1.00 (reference) 1.02 (0.59–1.74)
1.00 (reference) 1.26 (0.83–1.92)
1.00 (reference) 1.21 (1.02–1.45)** 0.99 (0.85–1.16)
1.00 (reference) 1.85 (1.31–2.61)*** 1.36 (1.04–1.79)**
1.00 (reference) 2.55 (1.96–3.32)*** 1.38 (1.13–1.69)*
Multinomial regressions were tested for selected variables. The models were adjusted for age and sex and for accelerometer wear time. Participants were classified as active (Q60 minIdj1 in MVPA) or inactive (G60 minIdj1 in MVPA). Participants were also classified as low sedentary and high sedentary according to the median split by age and sex. Fitness composite score is a composite variable calculated by summing up the five fitness test z-scores and dividing by five. *P G 0.01. **P G 0.05. ***P G 0.001.
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PA, SEDENTARY TIME, AND HEALTHY FITNESS
change in adiposity in youths. The disparity of the results could be due to different methodological approaches to assess PA and sedentary time. Specific sedentary behaviors assessed by self-report (e.g., sedentary screen time) seems to be associated with adiposity (13,28,31), whereas objectively measured total sedentary time seems unrelated to adiposity (5). Furthermore, sedentary time may lead to increases in adiposity whereas high adiposity may also increase time spent sedentary (a bidirectional association). Indeed, this has previously been suggested in observational (5) and prospective studies (9). The strengths of this study include the following: the objective assessment of PA and time spent sedentary in a large nationwide sample of children and adolescents representing various geographical locations of Portugal and the use of a cut point of G100 counts per minute to identify sedentary behaviors, as this cutoff has shown excellent accuracy (30). Nevertheless, this study has some limitations. These include the cross-sectional design, which means that causal inferences cannot be made, and the fact that the accelerometers do not capture water-based activities, cycling, and upper body activities. The HFZ cutoffs used in the study were developed in the United States and may not be applicable to Portuguese children. However, it should be recognized that the cutoffs developed for body composition and aerobic capacity standards included in the composite score are related to health and are independent of the sample distribution. Finally, all physical fitness tests were conducted in schools and it is likely that more accurate measurements would have been obtained if these tests were performed in a laboratory. However, any error in the fitness tests associated with field testing is likely to be random, therefore attenuating the observed associations.
CONCLUSIONS AND RECOMMENDATION Time spent in MVPA was independently associated with physical fitness components and fitness composite score. The combined effect of PA and time devoted to sedentary behaviors was also related to physical fitness components and fitness composite score. However, these associations were mainly driven by time spent in MVPA rather than sedentary time. These findings may suggest that PA contributes to physical fitness to a greater extent than sedentary behaviors do. From a public health perspective and physical education curricular policy, these results reinforce the importance of promoting PA and reducing time in sedentary behaviors in relation to physical fitness in youths. The authors gratefully acknowledge the participation of the adolescents in this study and the physical education teachers for their assistance in helping collect data. This research was supported by the Interdisciplinary Center for the Study of Human Performance— Portuguese Science and Technology Foundation. The authors declare that there are no conflicts of interest. The results of the present study do not constitute endorsement by the American College of Sports Medicine.
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Moreover, the results from linear regression analyses confirmed the observed results from the stratified analyses and higher amounts of time spent in time spent in MVPA was associated with a more favorable fitness composite score. Accumulating approximately 47 min of time spent in MVPA was associated with a positive fitness composite score (i.e., 90), suggesting that meeting PA guidelines (Q60 minIdj1 in MVPA) seems beneficial for overall physical fitness. Given the known associations between physical fitness and indicators of health in young people (11,18,26), we may speculate that physical fitness may partly mediate the associations between PA and health status. We further verified whether the combined association of PA and sedentary time was related to physical fitness. Although there was independent association between PA and sedentary time on physical fitness, combined association was also observed. Those classified as active/low sedentary had higher odds of being in the FITNESSGRAM healthy zone for flexibility of the hamstrings and the lower back than those classified as inactive/high sedentary. Moreover, those categorized as active/low sedentary were more likely to have a higher overall score of physical fitness than those categorized as inactive/high sedentary. This highlights the importance of increasing PA and decreasing time devoted to sedentary behaviors to improve young people’s health and possibly prevent diseases. However, these two behaviors may be seen as independent because they are two different constructs and may carry independent health risks (27). Therefore, efforts to increase PA might be independent of efforts to decrease sedentary behaviors. Among young Portuguese people, the promotion of higher levels of PA seems particularly important, given that previous data have shown that only 36% of those age 10–11 yr and 4% of those age 16–17 yr were considered sufficiently active according to the World Health Organization 2010 PA guidelines (1). However, although the prevalence of sufficiently active Portuguese children seems low, it is still higher than the prevalence estimates reported in youths in the United States (29). Despite differences in prevalence estimates between studies, it is likely that our results are applicable to other settings because differences in the prevalence of sufficiently active youths do not affect the statistical association analysis. Therefore, our results emphasize the importance of addressing PA promotion programs, particularly in countries where majority of youths do not attend PA recommendation. Thus, young people’s parents and educators should be challenged to develop strategies to make youths more active. Being physically active increases the odds of being categorized as attaining a high level of healthrelated fitness. We did not observe an association between BMI and sedentary time. However, time spent in MVPA was related to BMI also after adjusting for sedentary time. This observation is opposite to some (10,31) and consistent with other cross-sectional (19,22) and prospective studies (3,8), suggesting that sedentary time is unrelated to adiposity and
EPIDEMIOLOGY
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