Advertisement

Longitudinal Associations of Healthy Behaviors on Fitness in Adolescents: DADOS Study

Open AccessPublished:June 29, 2021DOI:https://doi.org/10.1016/j.amepre.2021.04.009

      Introduction

      This study aims to investigate the individual and combined associations of physical activity, sedentary time, diet, and sleep at baseline on cardiorespiratory fitness at 24-month follow-up in adolescents.

      Methods

      The DADOS (Deporte, ADOlescencia y Salud) prospective cohort study was performed between 2015 and 2017. Analyses were conducted in 2020 and included 189 adolescents aged 13.9 (SD=0.3) years at baseline. Vigorous physical activity, total sedentary time, and sleep duration were evaluated by GENEActiv accelerometer. Sleep quality and adherence to a Mediterranean diet were evaluated by questionnaires. Cardiorespiratory fitness was assessed by the 20-meter shuttle run test. A healthy lifestyle index was created by including positive scores for each individual behavior, and 3 categories of achievement (≤1, 2, ≥3) were established.

      Results

      Performing high vigorous physical activity and low screen time at baseline were individually associated with the likelihood of achieving high cardiorespiratory fitness at follow-up (OR=3.33 and 3.09, respectively). ANCOVA indicated that adolescents with a healthy lifestyle index ≥3 at baseline showed higher cardiorespiratory fitness at follow-up than those with a healthy lifestyle index of 2 and ≤1 (74.4 [SE=1.5] vs 68.9 [SE=1.4] and 67.8 [SE=1.5] laps, respectively; p<0.01). Adolescents with a healthy lifestyle index ≥3 at baseline were more likely to have high cardiorespiratory fitness at follow-up (OR=3.10) than their peers with ≤1.

      Conclusions

      The results showed a cumulative impact of baseline health-related behaviors on cardiorespiratory fitness at 24-month follow-up in adolescents. These findings underline the key role of promoting a healthy lifestyle to improve adolescents’ health.

      INTRODUCTION

      Cardiorespiratory fitness (CRF) during youth is considered an important indicator of current and future health.
      • Ortega FB
      • Ruiz JR
      • Castillo MJ
      • Sjöström M.
      Physical fitness in childhood and adolescence: a powerful marker of health.
      ,
      • Mintjens S
      • Menting MD
      • Daams JG
      • van Poppel MNM
      • Roseboom TJ
      • Gemke RJBJ.
      Cardiorespiratory fitness in childhood and adolescence affects future cardiovascular risk factors: a systematic review of longitudinal studies.
      High levels of CRF are favorably associated with healthy cardiovascular and metabolic profiles
      • Castro-Piñero J
      • Perez-Bey A
      • Segura-Jiménez V
      • et al.
      Cardiorespiratory fitness cutoff points for early detection of present and future cardiovascular risk in children: a 2-year follow-up study.
      as well as with mental health
      • Janssen A
      • Leahy AA
      • Diallo TMO
      • et al.
      Cardiorespiratory fitness, muscular fitness and mental health in older adolescents: a multi-level cross-sectional analysis.
      and cognition.
      • Donnelly JE
      • Hillman CH
      • Castelli D
      • et al.
      Physical activity, fitness, cognitive function, and academic achievement in children: a systematic review.
      Despite these data, the percentage of youth meeting the standards for healthy CRF appears to decrease with age.
      • Tomkinson GR
      • Carver KD
      • Atkinson F
      • et al.
      European normative values for physical fitness in children and adolescents aged 9-17 years: results from 2 779 165 Eurofit performances representing 30 countries.
      Thus, identification of factors contributing to CRF improvement later in life should be a health priority.
      An individual's CRF is highly determined by unmodifiable factors such as genetic heritability, sex, age, and pubertal status.
      • Zaqout M
      • Vyncke K
      • Moreno LA
      • et al.
      Determinant factors of physical fitness in European children.
      ,
      • Schutte NM
      • Nederend I
      • Hudziak JJ
      • Bartels M
      • de Geus EJC.
      Twin–sibling study and meta-analysis on the heritability of maximal oxygen consumption.
      Yet, current research suggests that modifiable lifestyle behaviors may also impact CRF in adolescents.
      • Beltran-Valls MR
      • Adelantado-Renau M
      • Moliner-Urdiales D.
      Reallocating time spent in physical activity intensities: longitudinal associations with physical fitness (DADOS study).
      • Carson V
      • Hunter S
      • Kuzik N
      • et al.
      Systematic review of sedentary behaviour and health indicators in school-aged children and youth: an update.
      • Galan-Lopez P
      • Sánchez-Oliver AJ
      • Ries F
      • González-Jurado JA.
      Mediterranean diet, physical fitness and body composition in Sevillian adolescents: a healthy lifestyle.
      • Tambalis KD
      • Panagiotakos DB
      • Psarra G
      • Sidossis LS.
      Association of cardiorespiratory fitness levels with dietary habits and lifestyle factors in schoolchildren.
      • Mota J
      • Vale S.
      Associations between sleep quality with cardiorespiratory fitness and BMI among adolescent girls.
      • Rey-López JP
      • de Carvalho HB
      • de Moraes ACF
      • et al.
      Sleep time and cardiovascular risk factors in adolescents: the HELENA (Healthy Lifestyle in Europe by Nutrition in Adolescence) study.
      • Kristensen PL
      • Moeller NC
      • Korsholm L
      • et al.
      The association between aerobic fitness and physical activity in children and adolescents: the European youth heart study.
      • Santos R
      • Mota J
      • Okely AD
      • et al.
      The independent associations of sedentary behaviour and physical activity on cardiorespiratory fitness.
      For instance, physical activity, particularly vigorous-intensity physical activity (accelerometer derived), has been positively associated with CRF in longitudinal studies.
      • Beltran-Valls MR
      • Adelantado-Renau M
      • Moliner-Urdiales D.
      Reallocating time spent in physical activity intensities: longitudinal associations with physical fitness (DADOS study).
      ,
      • Kristensen PL
      • Moeller NC
      • Korsholm L
      • et al.
      The association between aerobic fitness and physical activity in children and adolescents: the European youth heart study.
      Regarding the impact of total sedentary time, higher durations of accelerometer-derived sedentary time were significantly associated with lower CRF in children and adolescents,
      • Santos R
      • Mota J
      • Okely AD
      • et al.
      The independent associations of sedentary behaviour and physical activity on cardiorespiratory fitness.
      but longitudinal data in these age groups are scarce.
      • Carson V
      • Hunter S
      • Kuzik N
      • et al.
      Systematic review of sedentary behaviour and health indicators in school-aged children and youth: an update.
      Results about healthy dietary patterns are derived from cross-sectional studies, which showed that adolescents adhering to a Mediterranean diet presented higher CRF than their nonadhering peers.
      • Galan-Lopez P
      • Sánchez-Oliver AJ
      • Ries F
      • González-Jurado JA.
      Mediterranean diet, physical fitness and body composition in Sevillian adolescents: a healthy lifestyle.
      ,
      • Tambalis KD
      • Panagiotakos DB
      • Psarra G
      • Sidossis LS.
      Association of cardiorespiratory fitness levels with dietary habits and lifestyle factors in schoolchildren.
      With respect to sleep, limited data exist in adolescents; yet, cross-sectional research reported a positive association between CRF and sleep quality in adolescent girls.
      • Mota J
      • Vale S.
      Associations between sleep quality with cardiorespiratory fitness and BMI among adolescent girls.
      However, data regarding sleep duration showed conflicting results because both positive
      • Tambalis KD
      • Panagiotakos DB
      • Psarra G
      • Sidossis LS.
      Association of cardiorespiratory fitness levels with dietary habits and lifestyle factors in schoolchildren.
      and null
      • Rey-López JP
      • de Carvalho HB
      • de Moraes ACF
      • et al.
      Sleep time and cardiovascular risk factors in adolescents: the HELENA (Healthy Lifestyle in Europe by Nutrition in Adolescence) study.
      associations between sleep duration and CRF have been reported.
      In addition to the studies mentioned earlier that have explored the individual association between health-related lifestyle behaviors and CRF among adolescents, previous research has suggested that people do not adopt single lifestyle behaviors in isolation but a series of them, which may inter-relate with each other.
      • Spring B
      • Moller AC
      • Coons MJ.
      Multiple health behaviours: overview and implications.
      Indeed, several studies performed on different age populations have reported associations between the number of healthy lifestyle factors achieved and indicators such as academic achievement, weight status, physical functioning, or mortality.
      • Adelantado-Renau M
      • Jiménez-Pavón D
      • Beltran-Valls MR
      • Moliner-Urdiales D.
      Independent and combined influence of healthy lifestyle factors on academic performance in adolescents: DADOS study.
      • Atallah N
      • Adjibade M
      • Lelong H
      • et al.
      How healthy lifestyle factors at midlife relate to healthy aging.
      • May AM
      • Romaguera D
      • Travier N
      • et al.
      Combined impact of lifestyle factors on prospective change in body weight and waist circumference in participants of the EPIC-PANACEA study.
      • Veronese N
      • Li Y
      • Manson JE
      • Willett WC
      • Fontana L
      • Hu FB.
      Combined associations of body weight and lifestyle factors with all cause and cause specific mortality in men and women: prospective cohort study.
      Previous research in adolescents has also identified different patterns of lifestyle behaviors related to high CRF.
      • Cabanas-Sánchez V
      • Martínez-Gómez D
      • Izquierdo-Gómez R
      • Segura-Jiménez V
      • Castro-Piñero J
      • Veiga OL.
      Association between clustering of lifestyle behaviors and health-related physical fitness in youth: the UP&DOWN study.
      • Pérez-Rodrigo C
      • Gil Á
      • González-Gross M
      • et al.
      Clustering of dietary patterns, lifestyles, and overweight among Spanish children and adolescents in the ANIBES study.
      • Cuenca-García M
      • Huybrechts I
      • Ruiz JR
      • et al.
      Clustering of multiple lifestyle behaviors and health-related fitness in European adolescents.
      • Hartz J
      • Yingling L
      • Ayers C
      • et al.
      Clustering of health behaviors and cardiorespiratory fitness among U.S. adolescents.
      However, to the authors’ knowledge, no study has examined the longitudinal impact of all of these lifestyle behaviors on CRF in adolescents, leaving unknown the magnitude of association of these behaviors, both individually and in combination.
      Therefore, because lifestyle factors could synergistically interact with each other to impact health status, it is relevant to investigate the influence of concurrently adhering to several modifiable lifestyle factors on CRF during adolescence. Hence, the aim of this study is to investigate the individual and combined associations of physical activity, sedentary time, sleep, and diet at baseline on CRF at 24-month follow-up in adolescents.

      METHODS

      Study Sample

      This study is part of the DADOS (Deporte, ADOlescencia y Salud) prospective cohort study, which aimed to investigate the impact of lifestyle behaviors on health and academic achievement in adolescents. A convenience sampling technique was used to recruit participants. For that purpose, advertising leaflets about the research project were sent to secondary schools and sports clubs located in the province of Castellón (Spain), which included basic information and the general inclusion criteria of the DADOS study (i.e., to be enrolled in the second grade of secondary school and without any diagnosis of physical or mental disease). Volunteers who met the inclusion criteria contacted the research group and were included in the study. Baseline data were collected between February 2015 and May 2015 for 274 participants, and 205 were re-evaluated at follow-up in the same period of 2017 (2-year follow-up). A total of 189 adolescents (91 girls) aged 13.9 (SD=0.3) years at baseline with valid data on the variables of interest at baseline (2015) and at follow-up (2017) were included in the analyses. Adolescents and their parents were informed of the nature and characteristics of the study, and they all provided written informed consent. The study was performed following the ethical guidelines of the Declaration of Helsinki 1961 (revision of Fortaleza 2013), and the study protocol was approved by the Research Ethics Committee of the University Jaume I (UJI-28-07-2014).

      Measures

      Physical activity and sedentary time were measured using the GENEActiv accelerometer (Activinsights Ltd, Kimbolton, UK), a waterproof device that contains a triaxial microelectromechanical accelerometer that records both motion-related and gravitational acceleration and has a linear and equal sensitivity along the 3 axes. Although the GENEActiv accelerometer offers a body temperature sensor to detect wear and nonwear time, participants kept a daily physical activity and sedentary time log in which they registered wear and nonwear time to check possible inconsistencies. Accelerometer-derived data from all the participants comprised ≥4 days, including weekends and weekdays, with 24-hour valid data. The GENEActiv accelerometer has been found to be a reliable
      • Esliger DW
      • Rowlands AV
      • Hurst TL
      • Catt M
      • Murray P
      • Eston RG.
      Validation of the GENEA accelerometer.
      and valid measure of physical activity and sedentary time in young people.
      • Phillips LR
      • Parfitt G
      • Rowlands AV.
      Calibration of the GENEA accelerometer for assessment of physical activity intensity in children.
      Devices were programmed with a sampling frequency of 100 Hz, and data were stored in gravity (g) units (1 g=9.81 m/s²). The raw acceleration output was converted to 1-second epochs using the GENEActiv Post-Processing PC Software, version 2.2. According to Phillips et al.,
      • Phillips LR
      • Parfitt G
      • Rowlands AV.
      Calibration of the GENEA accelerometer for assessment of physical activity intensity in children.
      a GENEActiv cut off point for vigorous-intensity physical activity in adolescents was established for values >60 g, and sedentarism was established for values <7 g. Vigorous physical activity and sedentary time were expressed as the average (minutes/day) by combining all the registered days for each participant. Vigorous physical activity was chosen to be included in the analyses owing to its stronger relationship with CRF than moderate and low physical activity intensities.
      • Beltran-Valls MR
      • Adelantado-Renau M
      • Moliner-Urdiales D.
      Reallocating time spent in physical activity intensities: longitudinal associations with physical fitness (DADOS study).
      ,
      • Kristensen PL
      • Moeller NC
      • Korsholm L
      • et al.
      The association between aerobic fitness and physical activity in children and adolescents: the European youth heart study.
      Regarding physical activity, participants above the sex-specific 75th percentile were categorized as having high levels of physical activity, which corresponded to ≥17 minutes of vigorous physical activity. With regard to sedentary time, participants under the sex-specific 25th percentile were categorized as having low sedentary time, which corresponded to ≤660 minutes of sedentary time.
      The Spanish version of the Pittsburgh Sleep Quality Index (PSQI) questionnaire was used to assess sleep quality over the last month.
      • Royuela Rico A
      • Macías Fernández JA
      Propiedades clinimétricas de la versión castellana del cuestionario de Pittsburg.
      Lower scores in overall PSQI represent better sleep quality. The PSQI provides a sensitive measure to identify poor sleep quality if the total PSQI score is >5 and good sleep quality if the total PSQI score is ≤5.
      • Buysse DJ
      • Reynolds III CF
      • Monk TH
      • Berman SR
      • Kupfer DJ
      The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research.
      Daily sleep duration was objectively measured by the GENEActiv accelerometer, a reliable device to examine sleep (κ=0.85 [SD=0.06]).
      • te Lindert BH
      • Van Someren EJ.
      Sleep estimates using microelectromechanical systems (MEMS).
      Sleep duration was calculated by the algorithm included in GENEActiv Post-Processing PC Software, version 2.2. Although the GENEActiv accelerometer offers body temperature and luminosity sensors to establish sleep duration, participants kept a daily sleep time log in which they registered their sleep/wake schedule. All participants included data of ≥4 complete days, including weekends and weekdays, with 24-hour valid data. According to National Sleep Foundation, good sleep duration was defined as ≥8 hours of sleep per day.
      • Hirshkowitz M
      • Whiton K
      • Albert SM
      • et al.
      National Sleep Foundation's sleep time duration recommendations: methodology and results summary.
      Adherence to the Mediterranean diet was assessed using KIDMED, a questionnaire based on the Mediterranean dietary guidelines for children and adolescents that provides an overall indication of their dietary patterns. The score for the subjects’ adherence to the Mediterranean diet ranges from 0 to 12. Levels of adherence were classified into 2 groups: poor (0–7) and optimal. (8–12).
      • Serra-Majem L
      • Ribas L
      • Ngo J
      • et al.
      Food, youth and the Mediterranean diet in Spain. Development of KIDMED, Mediterranean Diet Quality Index in children and adolescents.
      A healthy lifestyle index ranging from 0 to 5 was defined specifically for the sample of this study according to the number of modifiable healthy lifestyle behaviors fulfilled by each adolescent. For each healthy behaviour achieved (high levels of vigorous physical activity, low sedentary time, good sleep quality, good sleep duration, or optimal adherence to the Mediterranean diet) participants scored 1; hence, a higher index indicated healthier lifestyle.
      Participant's CRF was assessed by research staff using the 20-meter shuttle run test as described by Léger and colleagues.
      • Léger LA
      • Mercier D
      • Gadoury C
      • Lambert J.
      The multistage 20 metre shuttle run test for aerobic fitness.
      Each participant ran straight between 2 lines 20 meters apart at a pace established by recorded audio signals. The test was completed when participants could not reach the end lines at the pace of the audio signals for 2 consecutive times or when they stopped because of fatigue. The number of laps completed (20 m) was used in the analyses. As indicated in the study by Tomkinson et al.,
      • Tomkinson GR
      • Carver KD
      • Atkinson F
      • et al.
      European normative values for physical fitness in children and adolescents aged 9-17 years: results from 2 779 165 Eurofit performances representing 30 countries.
      participants above the sex-specific 80th percentile according to European normative values were categorized as having high CRF.
      Owing to the impact of sex, pubertal stage, body fat percentage, and parents’ educational level on CRF levels, all models controlled for the baseline scores of these variables.
      • Zaqout M
      • Vyncke K
      • Moreno LA
      • et al.
      Determinant factors of physical fitness in European children.
      Pubertal status was self-reported according to the 5 stages described by Tanner and Whitehouse.
      • Tanner JM
      • Whitehouse RH.
      Clinical longitudinal standards for height, weight, height velocity, weight velocity, and stages of puberty.
      Skinfold thicknesses were measured at the left side of the body at the triceps and subscapular areas to the nearest 0.2 mm using a Holtain skinfold caliper following standardized procedures.
      • Nagy E
      • Vicente-Rodriguez G
      • Manios Y
      • et al.
      Harmonization process and reliability assessment of anthropometric measurements in a multicenter study in adolescents.
      Total body fat percentage was calculated by the equation described by Slaughter and colleagues.
      • Slaughter MH
      • Lohman TG
      • Boileau RA
      • et al.
      Skinfold equations for estimation of body fatness in children and youth.
      Parents or legal guardians reported their educational level, which was categorized into 2 groups using the highest educational level obtained by the mother or the father: (1) below university education and (2) university education.

      Statistical Analysis

      Study sample characteristics are presented as mean (SD) for continuous variables and as frequencies and percentages for categorical variables. Because preliminary analyses did not show a significant interaction of sex with the study variables in relation to CRF (all p>0.10), all analyses were performed with the total sample. Differences between the baseline and follow-up time points were assessed using t-tests for continuous variables and chi-square tests for nominal variables. Binary logistic regression was used to assess the association between baseline health-related behaviors and CRF at follow-up. CRF at follow-up was entered as the dependent variable, and each health-related behavior was entered as an independent variable in separate models.
      One-way ANCOVA with a Bonferroni posthoc test was performed to investigate whether CRF at follow-up differed depending on the number of healthy lifestyle behaviors achieved at baseline. In addition, logistic regression was conducted to examine the likelihood of achieving high CRF at follow-up depending on the number of healthy lifestyle behaviors attained at baseline (i.e., ≤1, 2, and ≥3). All analyses were adjusted for sex, pubertal stage, body fat percentage, parents’ educational level, and CRF at baseline. No multicollinearity was identified in the model (variance inflation factors <3). The analyses were performed using SPSS, version 22.0. The level of significance was set to p<0.05.

      RESULTS

      Descriptive characteristics of the population at baseline and at 24-month follow-up are shown in Table 1. Overall, participants showed higher levels of vigorous physical activity and spent less time in sedentary activities, reported better sleep quality and duration, and reported lower levels of CRF at baseline than at 24-month follow-up (all p<0.01).
      Table 1Characteristics of Participants at Baseline and at 24-Month Follow-Up (N=189)
      VariablesBaselineFollow-up
      Age, years13.9 (0.3)15.8 (0.3)
      Tanner stage (I‒V), %0/8/33/49/100/0/10/54/36
      Total body fat mass, %21.4 (7.5)24.4 (9.1)
      Parents with university educational level, %91 (48)
      Healthy lifestyle behaviors
       Vigorous physical activity (minutes/day)12.4 (8.3)7.0 (7.6)
       Sedentary time (minutes/day)699.1 (78.8)741.2 (64.3)
       Sleep quality score (0‒21)4.6 (2.5)5.2 (2.8)
       Good sleep quality, %127 (67)119 (63)
       Sleep duration, hours8.0 (0.9)7.8 (1.0)
       Good sleep duration, %96 (51)70 (37)
       Adherence to the Mediterranean diet score (0‒12)7.1 (2.2)7.2 (2.2)
       Optimal adherence to Mediterranean diet, %89 (47)83 (44)
      Cardiorespiratory fitness, laps66.3 (24.5)70.4 (26.9)
      High cardiorespiratory fitness, %106 (56)110 (58)
      Note: Boldface indicates statistical significance (p<0.01). Statistical significance differences between baseline and follow-up were tested by paired t-test.
      Data are shown as mean (SD) or frequency (percentage). Good sleep quality was measured by the Pittsburg sleep quality index of ≤5. Good sleep duration indicates ≥8 hours of sleep per day. Optimal adherence to the Mediterranean diet indicates a score ≥8. High cardiorespiratory fitness indicates performing ≥80th sex-specific percentile according to European normative values.
      The individual associations of healthy lifestyle behaviors at baseline with CRF at follow-up are shown in Table 2. Performing high vigorous physical activity (≥75th sex-specific percentile) and low sedentary time (≤25th percentile) at baseline were positively associated with the likelihood of achieving high CRF (≥80th percentile of normative values) at 24-month follow-up.
      Table 2Logistic Regression Analyses Examining the Individual Influence of Healthy Lifestyle Behaviors at Baseline on High Cardiorespiratory Fitness at 24-Month Follow-Up in Adolescents (N=189)
      Healthy lifestyle behaviorHigh cardiorespiratory fitness
      Vigorous physical activity
       Low1 (ref)
       High3.33 (1.18, 9.41)
      Sedentary time
       High1 (ref)
       Low3.09 (1.13, 8.48)
      Sleep quality
       Poor1 (ref)
       Good1.58 (0.68, 3.69)
      Sleep duration
       <8 hours1 (ref)
       ≥8 hours1.27 (0.57, 2.81)
      Adherence to the Mediterranean diet
       Poor1 (ref)
       Optimal1.89 (0.86, 4.12)
      Note: Boldface indicates statistical significance (p<0.05).
      OR (95% CI) represent increased odds of achieving high cardiorespiratory fitness. Analyses were adjusted for sex, pubertal stage, body fat percentage, parents’ educational level, and cardiorespiratory fitness at baseline.
      Figure 1 shows the differences in CRF at follow-up according to the healthy lifestyle index at baseline. Overall, adolescents with a healthy lifestyle index of ≥3 at baseline showed higher CRF at follow-up than those with a healthy lifestyle index of 2 and ≤1 (mean=74.42 [SE=1.5] laps vs 68.9 [SE=1.4] and 67.8 [SE=1.5] laps, respectively; p<0.01).
      Figure 1
      Figure 1Differences in CRF at 24-month follow-up according to the healthy lifestyle index at baseline, after adjustment for sex, pubertal stage, body fat percentage, parents’ educational level, and cardiorespiratory fitness at baseline.
      Note: Estimated marginal means and SEs are presented. The single asterisk (*) indicates significant differences, p<0.05; double asterisks (**) indicate significant differences, p<0.01. For healthy lifestyle index ≤1, n=56; for healthy lifestyle index=2, n=69; and for healthy lifestyle index ≥3, n=64.
      CRF, cardiorespiratory fitness.
      The healthy lifestyle index at baseline predicting high CRF at follow-up is shown in Figure 2. Logistic regression analysis showed that adolescents with a healthy lifestyle index ≥3 at baseline were more likely to have high CRF at 24-month follow-up than their peers with a healthy lifestyle index ≤1. In terms of ORs, adolescents with a healthy lifestyle index ≥3 at baseline were 3.1 times more likely of having high CRF 24 months later (OR=3.10, 95% CI=1.10, 8.73).
      Figure 2
      Figure 2Logistic regression model predicting high CRF at 24-month follow-up according to the healthy lifestyle index at baseline.
      Note: Analysis adjusted for sex, pubertal stage, body fat percentage, parents’ educational level, and cardiorespiratory at baseline. Reference (OR=1.00): adolescents with a healthy lifestyle index ≤1. For healthy lifestyle index ≤1, n=56; for healthy lifestyle index=2, n=69; and for healthy lifestyle index ≥3, n=64.
      CRF, cardiorespiratory fitness.

      DISCUSSION

      The main finding of this longitudinal study revealed that a combination of modifiable health-related lifestyle behaviors (denoted by a healthy lifestyle index), including high vigorous physical activity, low sedentary time, good sleep quality, good sleep duration, and optimal adherence to the Mediterranean diet at baseline was associated with higher CRF at 24-month follow-up in adolescents. Indeed, adolescents adhering to a healthy lifestyle index ≥3 at baseline were more likely to have high CRF at 24-month follow-up than those adhering to ≤1, considering potential cofounders. These results complement the scarce current literature investigating the individual and combined longitudinal relationships between modifiable health-related behaviors and CRF in adolescents and contribute to a better understanding of the complexity of their interaction.
      The results about the individual associations of the studied healthy lifestyle behaviors with CRF in adolescents concur with the results of previous longitudinal research showing that CRF was associated positively with vigorous physical activity
      • Beltran-Valls MR
      • Adelantado-Renau M
      • Moliner-Urdiales D.
      Reallocating time spent in physical activity intensities: longitudinal associations with physical fitness (DADOS study).
      and negatively with sedentary time.
      • Carson V
      • Hunter S
      • Kuzik N
      • et al.
      Systematic review of sedentary behaviour and health indicators in school-aged children and youth: an update.
      Conversely to previous knowledge,
      • Galan-Lopez P
      • Sánchez-Oliver AJ
      • Ries F
      • González-Jurado JA.
      Mediterranean diet, physical fitness and body composition in Sevillian adolescents: a healthy lifestyle.
      • Tambalis KD
      • Panagiotakos DB
      • Psarra G
      • Sidossis LS.
      Association of cardiorespiratory fitness levels with dietary habits and lifestyle factors in schoolchildren.
      • Mota J
      • Vale S.
      Associations between sleep quality with cardiorespiratory fitness and BMI among adolescent girls.
      in this study, sleep patterns and adherence to the Mediterranean diet were not individually associated with CRF.
      The association between high levels of vigorous physical activity and CRF may be explained by the fact that intensity seems to be a key element in physical fitness enhancement in adolescents because previous research has observed that increased levels of vigorous physical activity rather than lower intensities are associated with higher CRF in children and adolescents.
      • Beltran-Valls MR
      • Adelantado-Renau M
      • Moliner-Urdiales D.
      Reallocating time spent in physical activity intensities: longitudinal associations with physical fitness (DADOS study).
      ,
      • Kristensen PL
      • Moeller NC
      • Korsholm L
      • et al.
      The association between aerobic fitness and physical activity in children and adolescents: the European youth heart study.
      These results could be explained by the physiologic and mechanical stress that vigorous physical activity exerts on the cardiorespiratory and the muscular systems leading to specific adaptations such as greater oxidative capacity.
      • MacInnis MJ
      • Gibala MJ.
      Physiological adaptations to interval training and the role of exercise intensity.
      Concerning total sedentary time, its association with CRF might be due to specific physiologic changes, such as reduced muscle blood flow or endothelial function, which may occur during prolonged common sedentary activities such as sitting or lying.
      • Raichlen DA
      • Pontzer H
      • Zderic TW
      • et al.
      Sitting, squatting, and the evolutionary biology of human inactivity.
      ,
      • Hamilton MT.
      The role of skeletal muscle contractile duration throughout the whole day: reducing sedentary time and promoting universal physical activity in all people.
      Although optimal adherence to the Mediterranean diet and good sleep patterns were not associated with CRF through adolescence on an individual level in this study, some previous cross-sectional studies reported positive associations of these variables with CRF in adolescents.
      • Galan-Lopez P
      • Sánchez-Oliver AJ
      • Ries F
      • González-Jurado JA.
      Mediterranean diet, physical fitness and body composition in Sevillian adolescents: a healthy lifestyle.
      • Tambalis KD
      • Panagiotakos DB
      • Psarra G
      • Sidossis LS.
      Association of cardiorespiratory fitness levels with dietary habits and lifestyle factors in schoolchildren.
      • Mota J
      • Vale S.
      Associations between sleep quality with cardiorespiratory fitness and BMI among adolescent girls.
      To the authors’ knowledge, no longitudinal study to date has investigated the impact of adherence to the Mediterranean diet and sleep patterns on CRF, which hinders the direct comparability with the findings of this study. Nevertheless, because health-related lifestyle behaviors seem to not act in isolation,
      • Spring B
      • Moller AC
      • Coons MJ.
      Multiple health behaviours: overview and implications.
      it is likely that on a combined level, diet and sleep patterns may also contribute to improved CRF. For instance, the inter-relationship of physical activity and sedentary behaviors with a Mediterranean diet
      • García-Hermoso A
      • Ezzatvar Y
      • López-Gil JF
      • Ramírez-Vélez R
      • Olloquequi J
      • Izquierdo M.
      Is adherence to the Mediterranean Diet associated with healthy habits and physical fitness? A systematic review and meta-analysis including 565 421 youths.
      and sleep
      • Saunders TJ
      • Gray CE
      • Poitras VJ
      • et al.
      Combinations of physical activity, sedentary behaviour and sleep: relationships with health indicators in school-aged children and youth.
      have been previously reported in the literature, which together may influence adolescents’ energy balance and nutrient supply
      • Arnaoutis G
      • Georgoulis M
      • Psarra G
      • et al.
      Association of anthropometric and lifestyle parameters with fitness levels in Greek schoolchildren: results from the EYZHN program.
      as well as endocrine system regulation.
      • Dolezal BA
      • Neufeld EV
      • Boland DM
      • Martin JL
      • Cooper CB.
      Interrelationship between sleep and exercise: a systematic review.
      The combination of these physiologic responses may impact cardiometabolic system functioning and ultimately CRF. Thus, these factors were included in the healthy lifestyle index to examine the combined associations with CRF at follow-up.
      The combined analyses revealed that adolescents with a healthy lifestyle index ≥3 at baseline showed higher CRF at 24-month follow-up than those with an index ≤2. Moreover, adolescents with a healthy lifestyle index ≥3 at baseline had an increased likelihood of achieving high CRF at follow-up compared with their peers with a healthy lifestyle index ≤1. Previous cross-sectional studies have analyzed the combined influence of some health-related behaviors on CRF in adolescents and preadolescents using cluster analyses.
      • Cabanas-Sánchez V
      • Martínez-Gómez D
      • Izquierdo-Gómez R
      • Segura-Jiménez V
      • Castro-Piñero J
      • Veiga OL.
      Association between clustering of lifestyle behaviors and health-related physical fitness in youth: the UP&DOWN study.
      • Pérez-Rodrigo C
      • Gil Á
      • González-Gross M
      • et al.
      Clustering of dietary patterns, lifestyles, and overweight among Spanish children and adolescents in the ANIBES study.
      • Cuenca-García M
      • Huybrechts I
      • Ruiz JR
      • et al.
      Clustering of multiple lifestyle behaviors and health-related fitness in European adolescents.
      • Hartz J
      • Yingling L
      • Ayers C
      • et al.
      Clustering of health behaviors and cardiorespiratory fitness among U.S. adolescents.
      Although cluster analysis results are not directly comparable with the findings of this study, these previous studies also showed that health-related behaviors manifest together with a specific impact on CRF in adolescents. For instance, in boys, the cluster with the highest amount of sedentary time had the lowest CRF, even though it had the highest diet scores and showed similar physical activity levels to other clusters.
      • Hartz J
      • Yingling L
      • Ayers C
      • et al.
      Clustering of health behaviors and cardiorespiratory fitness among U.S. adolescents.
      In another recent study, Cabanas-Sánchez et al.
      • Cabanas-Sánchez V
      • Martínez-Gómez D
      • Izquierdo-Gómez R
      • Segura-Jiménez V
      • Castro-Piñero J
      • Veiga OL.
      Association between clustering of lifestyle behaviors and health-related physical fitness in youth: the UP&DOWN study.
      found that youths in the most active cluster obtained the highest score on CRF than their peers in the rest of the clusters. Similarly, Pérez-Rodrigo and colleagues
      • Pérez-Rodrigo C
      • Gil Á
      • González-Gross M
      • et al.
      Clustering of dietary patterns, lifestyles, and overweight among Spanish children and adolescents in the ANIBES study.
      showed that adolescents in the most active cluster had the highest CRF scores than those in the other clusters. Alternatively, Cuenca-García et al.
      • Cuenca-García M
      • Huybrechts I
      • Ruiz JR
      • et al.
      Clustering of multiple lifestyle behaviors and health-related fitness in European adolescents.
      found that the most active adolescents with better dietary patterns showed better CRF. However, the studies from Cuenca-García and colleagues
      • Cuenca-García M
      • Huybrechts I
      • Ruiz JR
      • et al.
      Clustering of multiple lifestyle behaviors and health-related fitness in European adolescents.
      and Hartz et al.
      • Hartz J
      • Yingling L
      • Ayers C
      • et al.
      Clustering of health behaviors and cardiorespiratory fitness among U.S. adolescents.
      did not include sleep patterns, which hampers comparisons among studies.
      The results obtained in this study reinforce the idea that the combination of different healthy lifestyle behaviors may have a notable impact on youths’ health status. Indeed, no individual behavior has been proposed as being the unique predictor of poor health indicators.
      • Cabanas-Sánchez V
      • Martínez-Gómez D
      • Izquierdo-Gómez R
      • Segura-Jiménez V
      • Castro-Piñero J
      • Veiga OL.
      Association between clustering of lifestyle behaviors and health-related physical fitness in youth: the UP&DOWN study.
      Adolescence is a crucial period in life because health-related behaviors are usually adopted during this age span and appear to moderately track into adulthood.
      • Hayes G
      • Dowd KP
      • MacDonncha C
      • Donnelly AE.
      Tracking of physical activity and sedentary behavior from adolescence to young adulthood: a systematic literature review.
      • Movassagh EZ
      • Baxter-Jones ADG
      • Kontulainen S
      • Whiting SJ
      • Vatanparast H.
      Tracking dietary patterns over 20 years from childhood through adolescence into young adulthood: the Saskatchewan Pediatric Bone Mineral Accrual Study.
      • Viner RM
      • Ross D
      • Hardy R
      • et al.
      Life course epidemiology: recognising the importance of adolescence.
      Therefore, educational and public health programs promoting a healthy lifestyle should target these modifiable behaviors during adolescence given its potential influence on CRF, which is an important indicator of current and future health status.
      • Ortega FB
      • Ruiz JR
      • Castillo MJ
      • Sjöström M.
      Physical fitness in childhood and adolescence: a powerful marker of health.
      ,
      • Mintjens S
      • Menting MD
      • Daams JG
      • van Poppel MNM
      • Roseboom TJ
      • Gemke RJBJ.
      Cardiorespiratory fitness in childhood and adolescence affects future cardiovascular risk factors: a systematic review of longitudinal studies.
      The lifestyle index used in this study was based on scientific evidence, which helps to give a simple and useful message for intervention and counseling purposes as well as for encouraging adolescents to follow a healthier lifestyle.

      Limitations

      Strengths of this study include the longitudinal design with a homogenous sample in terms of age and the consideration of several lifestyle behaviors for the analyses (physical activity, sedentary behavior, sleep, and diet). In addition, physical activity, sedentary time, and sleep duration were assessed by accelerometry, which has several advantages over questionnaires and self-report methods, although some controversies have also been reported.
      • Migueles JH
      • Cadenas-Sanchez C
      • Ekelund U
      • et al.
      Accelerometer data collection and processing criteria to assess physical activity and other outcomes: a systematic review and practical considerations.
      CRF was assessed by a valid and reliable test, which is feasible and time efficient in observational studies; however, it is acknowledged that more accurate data could be obtained in laboratory settings. The analyses were controlled for several potential cofounders, but other unmeasured confounders such as genetic, environmental, or social factors could have influenced the results of this study. Limitations of this study also include the fact that adherence to the Mediterranean diet and sleep quality results were derived from a questionnaire, which is considered a subjective method; however, both questionnaires were previously validated. Moreover, the healthy lifestyle index used in the analyses has not been validated previously. The convenience sampling technique may have biased the results because participants’ healthy behaviors accomplishment could not be representative of the general population. The inclusion of smoking or alcohol consumption in the healthy lifestyle index could have broadened the insight about health behaviors linked to CRF in adolescents.

      CONCLUSIONS

      The results of this study suggest that although some health-related behaviors at baseline may be individually and positively associated with CRF at follow-up in adolescents, the more health-related behaviors achieved at baseline, the higher the CRF at 24-month follow-up. These findings are of paramount importance because of the increasing evidence suggesting the impact of high CRF on adolescents’ overall health. Educational and public health intervention and prevention strategies addressed to improve adolescents’ health should take into account the promotion of multiple health-related lifestyle behaviors throughout this age span.

      ACKNOWLEDGMENTS

      The DADOS study is funded by the Spanish Ministry of Economy and Competitiveness (DEP2013–45515-R) and by the University Jaume I of Castellón (P1•1A2015-05 and UJI-A2019-12). MRBV is supported by a mobility grant from the Spanish Ministry of Science, Innovation and Universities (CAS19/00032).
      MRBV, DMU, and MAR contributed to the conception and design of the study, acquisition of data, and analysis and interpretation of data. MRBV prepared the first draft of the manuscript. DMU, JM, and MAR revised the manuscript critically for important intellectual content. All authors gave final approval and agreed to be accountable for all aspects of the work.
      No financial disclosures were reported by the authors of this paper.

      REFERENCES

        • Ortega FB
        • Ruiz JR
        • Castillo MJ
        • Sjöström M.
        Physical fitness in childhood and adolescence: a powerful marker of health.
        Int J Obes (Lond). 2008; 32: 1-11https://doi.org/10.1038/sj.ijo.0803774
        • Mintjens S
        • Menting MD
        • Daams JG
        • van Poppel MNM
        • Roseboom TJ
        • Gemke RJBJ.
        Cardiorespiratory fitness in childhood and adolescence affects future cardiovascular risk factors: a systematic review of longitudinal studies.
        Sports Med. 2018; 48: 2577-2605https://doi.org/10.1007/s40279-018-0974-5
        • Castro-Piñero J
        • Perez-Bey A
        • Segura-Jiménez V
        • et al.
        Cardiorespiratory fitness cutoff points for early detection of present and future cardiovascular risk in children: a 2-year follow-up study.
        Mayo Clin Proc. 2017; 92: 1753-1762https://doi.org/10.1016/j.mayocp.2017.09.003
        • Janssen A
        • Leahy AA
        • Diallo TMO
        • et al.
        Cardiorespiratory fitness, muscular fitness and mental health in older adolescents: a multi-level cross-sectional analysis.
        Prev Med. 2020; 132105985https://doi.org/10.1016/j.ypmed.2020.105985
        • Donnelly JE
        • Hillman CH
        • Castelli D
        • et al.
        Physical activity, fitness, cognitive function, and academic achievement in children: a systematic review.
        Med Sci Sports Exerc. 2016; 48: 1197-1222https://doi.org/10.1249/MSS.0000000000000901
        • Tomkinson GR
        • Carver KD
        • Atkinson F
        • et al.
        European normative values for physical fitness in children and adolescents aged 9-17 years: results from 2 779 165 Eurofit performances representing 30 countries.
        Br J Sports Med. 2018; 52: 1445-14563https://doi.org/10.1136/bjsports-2017-098253
        • Zaqout M
        • Vyncke K
        • Moreno LA
        • et al.
        Determinant factors of physical fitness in European children.
        Int J Public Health. 2016; 61: 573-582https://doi.org/10.1007/s00038-016-0811-2
        • Schutte NM
        • Nederend I
        • Hudziak JJ
        • Bartels M
        • de Geus EJC.
        Twin–sibling study and meta-analysis on the heritability of maximal oxygen consumption.
        Physiol Genomics. 2016; 48: 210-219https://doi.org/10.1152/physiolgenomics.00117.2015
        • Beltran-Valls MR
        • Adelantado-Renau M
        • Moliner-Urdiales D.
        Reallocating time spent in physical activity intensities: longitudinal associations with physical fitness (DADOS study).
        J Sci Med Sport. 2020; 23: 968-972https://doi.org/10.1016/j.jsams.2020.04.012
        • Carson V
        • Hunter S
        • Kuzik N
        • et al.
        Systematic review of sedentary behaviour and health indicators in school-aged children and youth: an update.
        Appl Physiol Nutr Metab. 2016; 41 (suppl 3): S240-S265https://doi.org/10.1139/apnm-2015-0630
        • Galan-Lopez P
        • Sánchez-Oliver AJ
        • Ries F
        • González-Jurado JA.
        Mediterranean diet, physical fitness and body composition in Sevillian adolescents: a healthy lifestyle.
        Nutrients. 2009; 11 (2019)https://doi.org/10.3390/nu11092009
        • Tambalis KD
        • Panagiotakos DB
        • Psarra G
        • Sidossis LS.
        Association of cardiorespiratory fitness levels with dietary habits and lifestyle factors in schoolchildren.
        Appl Physiol Nutr Metab. 2019; 44: 539-545https://doi.org/10.1139/apnm-2018-0407
        • Mota J
        • Vale S.
        Associations between sleep quality with cardiorespiratory fitness and BMI among adolescent girls.
        Am J Hum Biol. 2010; 22: 473-475https://doi.org/10.1002/ajhb.21019
        • Rey-López JP
        • de Carvalho HB
        • de Moraes ACF
        • et al.
        Sleep time and cardiovascular risk factors in adolescents: the HELENA (Healthy Lifestyle in Europe by Nutrition in Adolescence) study.
        Sleep Med. 2014; 15: 104-110https://doi.org/10.1016/j.sleep.2013.07.021
        • Kristensen PL
        • Moeller NC
        • Korsholm L
        • et al.
        The association between aerobic fitness and physical activity in children and adolescents: the European youth heart study.
        Eur J Appl Physiol. 2010; 110: 267-275https://doi.org/10.1007/s00421-010-1491-x
        • 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: 1508-1512https://doi.org/10.1136/bjsports-2012-091610
        • Spring B
        • Moller AC
        • Coons MJ.
        Multiple health behaviours: overview and implications.
        J Public Health (Oxf). 2012; 34: i3-i10https://doi.org/10.1093/pubmed/fdr111
        • Adelantado-Renau M
        • Jiménez-Pavón D
        • Beltran-Valls MR
        • Moliner-Urdiales D.
        Independent and combined influence of healthy lifestyle factors on academic performance in adolescents: DADOS study.
        Pediatr Res. 2019; 85: 456-462https://doi.org/10.1038/s41390-019-0285-z
        • Atallah N
        • Adjibade M
        • Lelong H
        • et al.
        How healthy lifestyle factors at midlife relate to healthy aging.
        Nutrients. 2018; 10: 854https://doi.org/10.3390/nu10070854
        • May AM
        • Romaguera D
        • Travier N
        • et al.
        Combined impact of lifestyle factors on prospective change in body weight and waist circumference in participants of the EPIC-PANACEA study.
        PLoS One. 2012; 7: e50712https://doi.org/10.1371/journal.pone.0050712
        • Veronese N
        • Li Y
        • Manson JE
        • Willett WC
        • Fontana L
        • Hu FB.
        Combined associations of body weight and lifestyle factors with all cause and cause specific mortality in men and women: prospective cohort study.
        BMJ. 2016; 355: i5855https://doi.org/10.1136/bmj.i5855
        • Cabanas-Sánchez V
        • Martínez-Gómez D
        • Izquierdo-Gómez R
        • Segura-Jiménez V
        • Castro-Piñero J
        • Veiga OL.
        Association between clustering of lifestyle behaviors and health-related physical fitness in youth: the UP&DOWN study.
        J Pediatr. 2018; 199 (e1): 41-48https://doi.org/10.1016/j.jpeds.2018.03.075
        • Pérez-Rodrigo C
        • Gil Á
        • González-Gross M
        • et al.
        Clustering of dietary patterns, lifestyles, and overweight among Spanish children and adolescents in the ANIBES study.
        Nutrients. 2015; 8: 11https://doi.org/10.3390/nu8010011
        • Cuenca-García M
        • Huybrechts I
        • Ruiz JR
        • et al.
        Clustering of multiple lifestyle behaviors and health-related fitness in European adolescents.
        J Nutr Educ Behav. 2013; 45: 549-557https://doi.org/10.1016/j.jneb.2013.02.006
        • Hartz J
        • Yingling L
        • Ayers C
        • et al.
        Clustering of health behaviors and cardiorespiratory fitness among U.S. adolescents.
        J Adolesc Health. 2018; 62: 583-590https://doi.org/10.1016/j.jadohealth.2017.11.298
        • Esliger DW
        • Rowlands AV
        • Hurst TL
        • Catt M
        • Murray P
        • Eston RG.
        Validation of the GENEA accelerometer.
        Med Sci Sports Exerc. 2011; 43: 1085-1093https://doi.org/10.1249/MSS.0b013e31820513be
        • Phillips LR
        • Parfitt G
        • Rowlands AV.
        Calibration of the GENEA accelerometer for assessment of physical activity intensity in children.
        J Sci Med Sport. 2013; 16: 124-128https://doi.org/10.1016/j.jsams.2012.05.013
        • Royuela Rico A
        • Macías Fernández JA
        Propiedades clinimétricas de la versión castellana del cuestionario de Pittsburg.
        Vigilia-Sueño. 1997; 9: 81-94
        • Buysse DJ
        • Reynolds III CF
        • Monk TH
        • Berman SR
        • Kupfer DJ
        The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research.
        Psychiatry Res. 1989; 28: 193-213https://doi.org/10.1016/0165-1781(89)90047-4
        • te Lindert BH
        • Van Someren EJ.
        Sleep estimates using microelectromechanical systems (MEMS).
        Sleep. 2013; 36: 781-789https://doi.org/10.5665/sleep.2648
        • Hirshkowitz M
        • Whiton K
        • Albert SM
        • et al.
        National Sleep Foundation's sleep time duration recommendations: methodology and results summary.
        Sleep Health. 2015; 1: 40-43https://doi.org/10.1016/j.sleh.2014.12.010
        • Serra-Majem L
        • Ribas L
        • Ngo J
        • et al.
        Food, youth and the Mediterranean diet in Spain. Development of KIDMED, Mediterranean Diet Quality Index in children and adolescents.
        Public Health Nutr. 2004; 7: 931-935https://doi.org/10.1079/phn2004556
        • Léger LA
        • Mercier D
        • Gadoury C
        • Lambert J.
        The multistage 20 metre shuttle run test for aerobic fitness.
        J Sports Sci. 1988; 6: 93-101https://doi.org/10.1080/02640418808729800
        • Tanner JM
        • Whitehouse RH.
        Clinical longitudinal standards for height, weight, height velocity, weight velocity, and stages of puberty.
        Arch Dis Child. 1976; 51: 170-179https://doi.org/10.1136/adc.51.3.170
        • Nagy E
        • Vicente-Rodriguez G
        • Manios Y
        • et al.
        Harmonization process and reliability assessment of anthropometric measurements in a multicenter study in adolescents.
        Int J Obes (Lond). 2008; 32: S58-S65https://doi.org/10.1038/ijo.2008.184
        • Slaughter MH
        • Lohman TG
        • Boileau RA
        • et al.
        Skinfold equations for estimation of body fatness in children and youth.
        Hum Biol. 1988; 60: 709-723
        • MacInnis MJ
        • Gibala MJ.
        Physiological adaptations to interval training and the role of exercise intensity.
        J Physiol. 2017; 595: 2915-2930https://doi.org/10.1113/JP273196
        • Raichlen DA
        • Pontzer H
        • Zderic TW
        • et al.
        Sitting, squatting, and the evolutionary biology of human inactivity.
        Proc Natl Acad Sci U S A. 2020; 117: 7115-7121https://doi.org/10.1073/pnas.1911868117
        • Hamilton MT.
        The role of skeletal muscle contractile duration throughout the whole day: reducing sedentary time and promoting universal physical activity in all people.
        J Physiol. 2018; 596: 1331-1340https://doi.org/10.1113/JP273284
        • García-Hermoso A
        • Ezzatvar Y
        • López-Gil JF
        • Ramírez-Vélez R
        • Olloquequi J
        • Izquierdo M.
        Is adherence to the Mediterranean Diet associated with healthy habits and physical fitness? A systematic review and meta-analysis including 565 421 youths.
        Br J Nutr. 2020; (In pressOnline December 9)https://doi.org/10.1017/S0007114520004894
        • Saunders TJ
        • Gray CE
        • Poitras VJ
        • et al.
        Combinations of physical activity, sedentary behaviour and sleep: relationships with health indicators in school-aged children and youth.
        Appl Physiol Nutr Metab. 2016; 41 (suppl 3): S283-S293https://doi.org/10.1139/apnm-2015-0626
        • Arnaoutis G
        • Georgoulis M
        • Psarra G
        • et al.
        Association of anthropometric and lifestyle parameters with fitness levels in Greek schoolchildren: results from the EYZHN program.
        Front Nutr. 2018; 5: 10https://doi.org/10.3389/fnut.2018.00010
        • Dolezal BA
        • Neufeld EV
        • Boland DM
        • Martin JL
        • Cooper CB.
        Interrelationship between sleep and exercise: a systematic review.
        Adv Prev Med. 2017; 2017 ([published correction appears in Adv Prev Med. 2017;2017:5979510]) (1364387)https://doi.org/10.1155/2017/1364387
        • Hayes G
        • Dowd KP
        • MacDonncha C
        • Donnelly AE.
        Tracking of physical activity and sedentary behavior from adolescence to young adulthood: a systematic literature review.
        J Adolesc Health. 2019; 65: 446-454https://doi.org/10.1016/j.jadohealth.2019.03.013
        • Movassagh EZ
        • Baxter-Jones ADG
        • Kontulainen S
        • Whiting SJ
        • Vatanparast H.
        Tracking dietary patterns over 20 years from childhood through adolescence into young adulthood: the Saskatchewan Pediatric Bone Mineral Accrual Study.
        Nutrients. 2017; 9: 990https://doi.org/10.3390/nu9090990
        • Viner RM
        • Ross D
        • Hardy R
        • et al.
        Life course epidemiology: recognising the importance of adolescence.
        J Epidemiol Community Health. 2015; 69: 719-720https://doi.org/10.1136/jech-2014-205300
        • Migueles JH
        • Cadenas-Sanchez C
        • Ekelund U
        • et al.
        Accelerometer data collection and processing criteria to assess physical activity and other outcomes: a systematic review and practical considerations.
        Sports Med. 2017; 47: 1821-1845https://doi.org/10.1007/s40279-017-0716-0