Robbie Radjagobalou

Jean-François Blanco

Victoria Dias

Silva Freitas

Caroline Supplis

Fabrice Gros

Odile Dechy-Cabaret

Karine Loubière

A revised experimental protocol for implementing the actinometry method with the Reinecke's salt

Keywords:

The present short note aims at proposing a revised experimental protocol to implement the actinometry method with Reinecke's salt. It consists in substituting, for the dosing of the thiocyanate anions produced, perchloric acid (HClO 4 ) by nitric acid (HNO 3 ), the latter being carefully chosen regarding the chemical equilibria occurring in the aqueous medium and the moderate risks of HNO 3 . This substitution has been rigorously validated by carrying out the experiments in a dedicated torus batch photoreactor enabling simple treatment of experimental results from a one-dimensional model.

Introduction

Chemical actinometers are widely used in different application fields to determine the photon flux entering a reactive medium; the knowledge of this latter being of prime importance to study any photochemical reactors [START_REF] Braun | Technologie photochimique. Presses polytechniques romandes[END_REF][START_REF] Kuhn | Chemical actinometry[END_REF]. They involve a wavelength-dependent photoreaction characterized by a known quantum yield in a given spectral range [START_REF] Kuhn | Chemical actinometry[END_REF]. For the visible domain, the Reinecke's salt is the popular actinometer, involving the following chemical equation:

+ → + - - [Cr(NH ) (NCS) ] H O [Cr(NH ) (NCS) H O] NCS 3 2 4 2 hν 3 2 3 2 (1)
The use of the Reinecke's salt presents however some drawbacks: (i) the experiments should be performed in a dark room, (ii) the reaction medium is sensitive to the temperature and (iii) toxic reactant is used (perchloric acid). Consequently, alternative actinometers for the visible light have been proposed to determine the incident photon flux in the visible spectrum, mostly with irradiated volumes in the range of milliliter [START_REF] Heller | Photochromic heterocyclic fulgides. Part 3. The use of (E)a-(2.5-dimethyl-3-furylethylidene)(isopropylidene)succinic anhydride as a simple convenient chemical actinometer[END_REF][START_REF] Brauer | Chemical actinometry in the visible (475-610 nm) by meso-diphenylhelianthrene[END_REF][START_REF] Santos | Photochemical investigation of a photochromic diarylethene compound that can be used as a wide range actinometer[END_REF][START_REF] Pitre | Visiblelight actinometry and intermittent illumination as convenient tools to study Ru (bpy) 3 Cl 2 mediated photoredox transformations[END_REF][START_REF] Roibu | An accessible visible-light actinometer for the determination of photon flux and optical pathlength in flow photo microreactors[END_REF]. Unfortunately, these latter actinometers are either not commercially available (i. e. synthetically obtained), or expensive. Therefore, the Reinecke's salt remains an affordable actinometer, in particular for an implementation at pilot-or industrial -scale photoreactors.

The associated quantum yield is relatively stable (ϕ = 0.29 ± 0.02) in the range of 400-700 nm when the pH of the solution is between 3 and 5 [START_REF] Kuhn | Chemical actinometry[END_REF]. Wegner and Adamson pioneered the experimental protocol of the Reinecke's salt as an actinometer [START_REF] Wegner | Photochemistry of complex ions. III. Absolute quantum yields for the photolysis of some aqueous chromium(III) complexes. Chemical actinometry in the long wavelength visible region[END_REF], which was later revised by Cornet et al. [START_REF] Cornet | Revised technique for the determination of mean incident light fluxes on photobioreactors[END_REF]. This lab protocol is based on the use of the perchloric acid at a concentration moderately high (0.5 mol.L -1 ). Nevertheless, this acid is nowadays classified as a highly toxic chemical product [START_REF] Sigma-Aldrich | Safety Data Sheet of Perchloric Acid[END_REF] as various studies have pointed out the impact of perchlorate ions -ClO 4 on animal and human metabolisms and on the environment [START_REF] Motzer | Perchlorate: problems, detection, and solutions[END_REF][START_REF] Blount | Urinary perchlorate and thyroid hormone levels in adolescent and adult men and women living in the United States[END_REF]. Moreover, during the aging of the perchloric acid, -ClO 4 decomposes into Cl O 2 7 (dichlorine heptoxide) which is a precursor of an explosive mixture (ClO 2 (chlorine dioxide) and O 2 (dioxygen)) [START_REF] Smith | Further Applications in the Use of Perchloric Acid[END_REF][START_REF] Leuleu | ème éditi[END_REF].

The present research note aims at proposing a revised experimental protocol to implement the actinometry method with the Reinecke's salt. For that, perchloric acid will be substituted by nitric acid, the latter being carefully chosen according to a study of chemical equilibria occurring in the aqueous medium. This substitution will be rigorously validated by carrying out experiments in a dedicated torus batch photoreactor enabling simple treatment of experimental results from onedimensional models [START_REF] Dahi | A novel experimental bench dedicated to the accurate radiative analysis of photoreactors: the case study of CdS catalyzed hydrogen production from sacrificial donors[END_REF] 2. Description of the revised protocol

Photodissociation of the Reinecke's salt

According to Eq. ( 1), the rate of this photodissociation is equal to the rate of the production of the thiocyanate anion, -NCS . Therefore, the dosing of the -NCS ions, which are produced during a given ⁎ Corresponding author at: Laboratoire de Génie Chimique (CNRS UMR 5503), 4 allée Emile Monso, BP 84234, 31432 Toulouse cedex 4, France.

E-mail address: karine.loubiere@ensiacet.fr (K. Loubière). https://doi.org/10.1016/j.jphotochem.2019.111934

T (2)
Therefore, in some conditions more than one -NCS ion ligand could be substituted by molecules of water, and thus inducing a bias in the determination of the consumed molar quantity of the Reinecke's salt during a given irradiation time and an overestimation of the amount of -NCS produced. To limit this second reaction, Rochatte et al. [START_REF] Rochatte | Radiative transfer approach using Monte Carlo Method for actinometry in complex geometry and its application to Reinecke salt photodissociation within innovative pilot-scale photo(bio)reactors[END_REF] re- commended to work at low conversions χ, namely below a maximal value, noted χ max , equal to 30%.

The molar quantity of thiocyanate ions produced during the photoreaction (Eq. ( 1)) is classically evaluated by spectrophotometry. Iron (III) thiocyanate complexes can be formed when the -NCS ions are in the presence of Fe 3+ ions [START_REF] Lewin | The nature of iron (III) thiocyanate in solution[END_REF]. These complexes are known to absorb intensively in the visible spectral domain of light [START_REF] Lister | Some measurements on the iron(III) -Thiocyanate system in aqueous solution[END_REF].

Monitoring of the absorbance of the iron (III) thiocyanate complexes

All the values of formation constants for the iron complexes for the jth equilibrium are given at 25 °C and noted K f,j i , where i refers to the ligand.

In the aqueous medium for the spectrophotometric analysis, Fe 3+ ions should be in excess against -NCS ions [START_REF] Charlot | L'analyse qualitative et les réactions en solution[END_REF]:

+ ⇄ = - + + NCS Fe [Fe(NCS)] K 10 3 2 f,1 NCS 2.1 (3)
+ ⇄ = - + + NCS [Fe(NCS)] [Fe(NCS) ] K 10 2 2 f,2 NCS 1.3 (4)
When + C Fe 3 ≥ 10 × -C NCS , the equilibrium exposed in Eq. ( 3) is pre- ponderant when compared to the one in Eq. (4). In this case, the reaction of interest during the spectrophotometric analysis is the one described by Eq. (3). The maximum of absorbance of the solution is observed at 450 nm when + C Fe 3 ≥ 10 × -C NCS (the sample for the re- ference solution being always a non-irradiated Reinecke's salt solution). The concentration of the thiocyanate ions is determined according to

= - C θ.A l.ε NCS 450 C (5)
Where, l (m) is the width of the glass cell for the spectrophotometry, A 450 (-) is the absorbance of the solution measured at 450 nm, θ (-) the dilution factor applied for the sample and ε C (L. mol -1 . cm -1 ) the decadic molar absorption coefficient of + [Fe(NCS)] 2 measured at 450 nm, 25 °C and at the dilution rate θ.

Various iron (III) hydroxide complexes (Eqs. ( 6)-( 8)) could be formed depending on the value of the pH [START_REF] Monier | Elements de Chimie analytique, analyse qualitative minérale (Eléments de radiochimie)[END_REF]:

+ ⇄ = - + + OH Fe [Fe(OH)] K OH f,1 10
3 2 11 (6)
+ ⇄ = - + + OH [Fe(OH)] [Fe(OH) ] K 10 2 2 f,2 OH 10.7 (7)
+ ⇄ = - + OH [Fe(OH) ] [Fe(OH) ] K 10 2 3 f,3 OH 9.5 (8)
Furthermore, in an acidic medium, the most likely iron (III) hydroxide complex to be formed is the concentrations of Fe 3+ and of + [Fe(OH)] 2 in the medium at the equilibrium. As a consequence, the monitoring of the acidity becomes essential in order to correctly drive the selectivity of formation of hydroxide complexes [START_REF] Zall | Photometric determination of chlorides in water[END_REF]. In order to limit the formation of + [Fe(OH)] 2 , a mineral acid must be added to the ferric solution, which consists in dissolving the iron (III) nitrate nonahydrate Fe(NO 3 ) 3 .9H 2 O in water.

+ [Fe(OH)] 2 .
Several options of mineral acids can be proposed in analytical chemistry such as hydrochloric acid, sulfuric acid or nitric acid, knowing that the original protocol of Wegner and Adamson used perchloric acid [START_REF] Heller | Photochromic heterocyclic fulgides. Part 3. The use of (E)a-(2.5-dimethyl-3-furylethylidene)(isopropylidene)succinic anhydride as a simple convenient chemical actinometer[END_REF].

Using independently the four acids previously mentioned involves the complexation reactions described below [START_REF] Charlot | L'analyse qualitative et les réactions en solution[END_REF].

+ ⇄ = - + + Cl Fe [Fe(Cl)] K 10 3 2 f,1 Cl 1.5 (10)
+ ⇄ = - + + SO Fe [Fe(SO )] K 10 4 2 3 4 f,1 SO 3.85 4 (11)
+ ⇄ = - + + NO Fe [FeNO ] K 10 3 3 3 2 f,1 NO 1.0 3 (12)
+ ⇄ = - + + ClO Fe [FeClO ] K 10 4 3 4 2 f,1 ClO 1.2 4 ( 13
)
From Eq. ( 3) and Eq. ( 11), the -SO 4 2 ions form a complex with Fe 3+ more stable than

+ [Fe(NCS)] 2 since K f,1 SO4 > K f,1
NCS . Thus, the sulfuric acid should be excluded.

The occurrence of + [Fe(NCS)] 2 is predominant when using the perchloric (HClO 4 ), the nitric (HNO 3 ) and the hydrochloric (HCl) acids as K f,1 NO 3 , K f,1 ClO4 and K f,1 Cl are inferior to K f,1 NCS . Consequently, HClO 4 , HNO 3

and HCl favor the formation of + [Fe(NCS)] 2 complex. Note that the assay of -NCS by Fe 3+ is not affected by redox reac- tions when comparing the redox potentials of the present ionic species.

In addition, when the condition of a large excess of Fe 3+ is not fulfilled, the use of HCl should be avoided since K f,1

Cl > K f,2 NCS . And taking into account the toxicity of perchloric acid and perchlorate ion, the nitric acid is therefore the most suitable acid that can be selected to prepare the ferric solution.

Experimental protocol

In the following experiments, the Reinecke's salt was purchased from Sigma Aldrich (CAS: 13573-17-6; lot: MKB54395 V (100 g); purity: ≥ 93.0%; 336.43 g.mol -1 ). The procedure proposed by Cornet et al. [START_REF] Cornet | Revised technique for the determination of mean incident light fluxes on photobioreactors[END_REF] was carried out in this study. The first step consisted in permuting NH 4

+ by K + ions. Hence, the Reinecke's salt was solubilized at 20 °C in a solution of potassium hydroxide such as the initial concentration of the potassium hydroxide and of the Reinecke's salt were fixed respectively at 0.1 mol.L -1 and at 0.015 mol.L -1 for all the experiments. The obtained pH after mixing was approximately equal to 13 which made possible the ammoniac stripping by mechanical agitation (pKa[NH 3 /NH 4 + ] = 9.2). Then, a solution of concentrated sulfuric acid (98%) was added gently in order to reduce the pH between 4 and 5. Note that the whole procedure was carried out in a dark room.

The spectrophotometric measurements were also inspired from Cornet et al. [START_REF] Cornet | Revised technique for the determination of mean incident light fluxes on photobioreactors[END_REF]. Absorption spectra were measured by a Shimadzu UV-160A and the samples were analyzed in plastic cells of 10 mm at room temperature of 25 °C in the dark. By means of the revised procedure, the ferric solution was composed of 0.1 mol.L -1 of iron (III) nitrate nonahydrate Fe(NO 3 ) 3 .9H 2 O and 0.5 mol.L -1 of nitric acid HNO 3 (63% weight fraction). At last, the solution from the reaction medium (or the reference solution) for the spectrometric analysis was prepared as following: to 0.5 mL of an irradiated solution (or 0.5 mL of a non-irradiated solution), was added successively, in this order, 1.5 mL of the ferric solution and 10 mL of deionized water.

Note that the reference solution should be kept during all the experiment time in the dark so as to prepare the blank at each measurement, as the Reinecke's salt could react slowly with water according to irradiation time τ, enables to monitor the kinetic of the photoreaction. The absorption of the actinometer covers a wide range in the visible spectrum of light, with a maximum at 525 nm. It is important to note that the absorption of the by-product, [Cr(NH 3 ) 2 (NCS) 3 (H 2 O)], is of the same order of magnitude than the one of the actinometer, thus implying that its absorption should be taken account in the modelling [START_REF] Rochatte | Radiative transfer approach using Monte Carlo Method for actinometry in complex geometry and its application to Reinecke salt photodissociation within innovative pilot-scale photo(bio)reactors[END_REF]. Furthermore, as described by Szychlinski et al. [START_REF] Szychlinski | Complementary study on the use of the potassium Reinecke's salt as a chemical actinometer[END_REF], under acidic condition, the by-product could react with water according to Eq. ( 2 =0.0125 mol.L -1 , the maximal concentration of -NCS to be analyzed was equal to 1.88 × 10 -4 mol.L -1 (for χ max = 30%) in the solution.

Two precautions were taken:

(i) It was verified that the absorbance of the Reinecke's salt and the byproduct

+ [Cr(NH ) (NCS) (H O) ] 3 2 2 2 2
were negligible at 450 nm. According to [START_REF] Rochatte | Radiative transfer approach using Monte Carlo Method for actinometry in complex geometry and its application to Reinecke salt photodissociation within innovative pilot-scale photo(bio)reactors[END_REF], the molar absorption coefficient at 450 nm of the Reinecke's salt and of the by-product were equal to 30.4 L.mol -1 . cm -1 and to 29.5 L.mol -1 . cm -1 , respectively. Then, considering (a) the maximal conversion (χ = χ max = 30%), (b) an initial concentration of the Reinecke's salt equal to 0.015 mol.L -1 and (c) a dilution factor θ of 24, the absorbance of iron (III) complexes, of the Reinecke's salt and of the by-product were respectively equal to 0.638, 0.013 and 0.006 at 450 nm (for an optical length of 10 mm). , the conditions to form predominantly the iron (III) thiocyanate complex were fulfilled.

Validation of the revised experimental protocol

To validate this revised protocol, specific experiments were carried out in a benchmark batch flat torus photoreactor which offered the advantage to be perfectly characterized [START_REF] Dahi | A novel experimental bench dedicated to the accurate radiative analysis of photoreactors: the case study of CdS catalyzed hydrogen production from sacrificial donors[END_REF][START_REF] Rochatte | Radiative transfer approach using Monte Carlo Method for actinometry in complex geometry and its application to Reinecke salt photodissociation within innovative pilot-scale photo(bio)reactors[END_REF]. This photoreactor was irradiated by a quasi-collimated blue light LED panel (λ =457 nm) of a 12.5 × 12.5 cm 2 surface (the emission spectrum of this LED panel is reported in Rochatte et al. [START_REF] Rochatte | Radiative transfer approach using Monte Carlo Method for actinometry in complex geometry and its application to Reinecke salt photodissociation within innovative pilot-scale photo(bio)reactors[END_REF]). Furthermore, due to its specific design, the photoreactor could be described according to a one-dimensional Cartesian geometry enabling thus to define rigorously the specific surface of illumination as the inverse of the optical path δ (a light =40 m -1 with δ =0.025 m). The dark volume fraction was also determined and equal to 0.103 (which corresponds to the part of the volume not directly irradiated at the boundary, enabling then to easily correct the actual specific illuminated surface in case of conserved geometry). In addition, the reactor could be assumed as perfectly stirred [START_REF] Sigma-Aldrich | Safety Data Sheet of Perchloric Acid[END_REF].

The experimental concentration of -NCS obtained using perchloric acid for the preparation of the ferric solution was compared with those where nitric acid was replaced by perchloric acid. The spectrophotometric analysis was conducted by regularly taking samples (at every 180 s for low photon flux density, 120 or 90 s for higher densities).

Fig. 1 illustrates this comparison for different conditions of emitted photon fluxes. A good agreement was obtained whatever the acid used for each emission light. It showed that the use of the nitric acid permitted to calculate similar conversions in -NCS when the perchloric acid was used and for all the light emission modes.

To validate completely the new experimental protocol, the next step consisted in determining the received photon flux densities q 0 from the experimental results (Fig. 1), whatever the acid used. For that, a simple mathematical model was elaborated based on the coupling of the mass balance with the photon transport equation (Eq. ( 14)).

Considering that (a) the reactor behaved as a perfectly mixed reactor (i. e. the concentration is uniform in the entire volume), (b) the light was monochromatic, emitted perpendicularly to the flow direction as a mono-directional and collimated light source, uniformly distributed along the reactor walls, and (c) the optical surface of the reactor was flat and non-reflective, Rochatte et al. [START_REF] Rochatte | Radiative transfer approach using Monte Carlo Method for actinometry in complex geometry and its application to Reinecke salt photodissociation within innovative pilot-scale photo(bio)reactors[END_REF] demonstrated that the analytical expression of the production of -NCS during the irra- diation time, noted τ (s), was given by

= - + -- + - dC dτ (1 f ). φ. a . q . κ ¯. C κ ¯. C κ ¯. C . (1 e ) NCS d l i g h t 0 R R R R P P (κ ¯.C κ ¯.C ).δ R R P P (14)
Where q 0 (mol. m -2 .s -1 ) was the incident photon flux density, C R (mol. m -3 ) the concentration of the Reinecke's salt, C P (mol. m -3 ) the concentration of the by-product, δ (m) the optical path, a light (m -1 ) the irradiated specific surface, ϕ (-) the quantum yield, and f d (-) the dark volume fraction. The mean molar naperian absorption coefficient of the Reinecke's salt, κ ¯R (m 2 . mol -1 ), and the mean molar naperian absorption coefficient of the by-product, κ ¯P (m 2 . mol -1 ) were calculated according to

∫ ∫ = κ ¯κ . f .dλ .f .dλ λ λ λ λ LED λ λ λ LED min max min max (15)
Where f λ LED (-) is the density function of the blue light LED panel and κ λ (m 2 . mol -1 ) is the naperian absorption coefficient at each wavelength λ (m). The values of f λ LED , and of κ λ of Reinecke's salt and of the by- product are reported in [START_REF] Sigma-Aldrich | Safety Data Sheet of Perchloric Acid[END_REF]. Eq. ( 15) allowed to calculate a mean value of the absorption coefficient by taking into account the emission spectrum of the light source. This method of calculation was verified to be well adapted for the batch flat torus photoreactor irradiated by the blue light LED panel [START_REF] Rochatte | Radiative transfer approach using Monte Carlo Method for actinometry in complex geometry and its application to Reinecke salt photodissociation within innovative pilot-scale photo(bio)reactors[END_REF]. Note that the flat torus photoreactor was built in such manner that the assumptions underlying the establishment of Eq. ( 14) were fulfilled.

The resolution of the latter equations was done using the software Matlab®. The identification of q 0 in Eq. ( 14) was made by minimizing the difference between the variations of the thiocyanate ion concentrations with the irradiation time predicted by Eq. ( 14) and the experimental ones.

From the modelling (Eq. ( 14)), the incident photon flux density q 0 related to each experimental protocol could be calculated (see Table 1). Both experimental protocols then led to almost similar incident photon flux densities where the maximal relative standard deviation was equal to 5%.

At last, the incident photon flux density was also determined via a physical method using a LI-COR® quantum sensor (LI-190Sa) connected to a LI-189 display (see Table 1). The latter measured the flux densities in the Photosynthetically Active Radiation domain ([400 nm; 700 nm]) directly in μmol.m -2 .s -1 and was calibrated at the factory with an uncertainty of 5%. The region of interest (i.e. the area where the liquid circulated into the reactor) was fractioned into 16 surfaces of measurement (which represented 15% of the total illuminated surface). Taking into account the deviation between these measurement points, and the latter uncertainty, the relative standard deviation on the values of q 0 from LI-COR® was estimated to 15%. Table 1 shows that these values were consistent with those obtained with the actinometry methods.

Conclusion

In this short note, the classical experimental protocol to determine the incident photon flux density by actinometry with the Reinecke'salt was revised. As the use of the acid perchloric could cause serious damages to the environment and injuries to experimenters, the proposed method consisted in substituting the perchloric acid by a less hazardous a thermal pathway [START_REF] Szychlinski | Complementary study on the use of the potassium Reinecke's salt as a chemical actinometer[END_REF]. The applied dilution factor θ and the final pH were then equal to 24 and 1.2 for all the samples, respectively. Under this dilution, at 450 nm, ε C was determined and found equal to 3400 ( ± 100) L. mol -1 .cm -1 , which is the same value as already reported in [START_REF] Brauer | Chemical actinometry in the visible (475-610 nm) by meso-diphenylhelianthrene[END_REF]. Finally, the concentration of NCS -was determined by using Eq. ( 5).

The dilution factor fixed at 24 was chosen so as to allow measuring absorbances with cells having an optical path of 10 mm in the detection acid. The choice of the acid resulted from a study of the chemical equilibria and at last, the acid nitric was selected. Finally, the new protocol was rigorously validated in a benchmark batch photoreactor.

In the future, a way to improve the proposed protocol would be to use cells with 1 mm of optical pathlength for the measurement of absorbance making possible the decrease of the dilution factor and, consequently, the increase of the occurrence of the formation of iron (III) thiocyanate complexes. Fig. 1. Photography of the flat torus photoreactor and variation of the concentration in NCS -as a function of the irradiation time, depending whether perchloric acid or nitric acid was used (see [START_REF] Rochatte | Radiative transfer approach using Monte Carlo Method for actinometry in complex geometry and its application to Reinecke salt photodissociation within innovative pilot-scale photo(bio)reactors[END_REF] for more details about the design of the flat torus reactor with the blue LED).

Table 1

Incident photon flux densities q 0 related each experimental protocol resulting from the modelling (Eq. ( 14), with a relative standard deviation estimated to 5%) and measured by a LI-COR® quantum sensor (a relative standard deviation estimated to 15%).

  Therefore, from the ex- pression of the constant of formation of + [Fe(OH)] 2 ; e (-) is the equilibrium constant of the autoprotolysis of water and equal to 10 -14 and

-C

  (ii) The determination of -NCS via the protocol was feasible only if + [Fe(NCS)] 2 was predominant. Let's assume χ = χ max , i. e. a maximal conversion in -NCS , the final concentrations of + [Fe(NCS)] 2 and of + [Fe(OH)] 2 were equal to the initial concentration of -NCS ( = 1.88 × 10 -4 mol.L -1 ) and of -OH ( = 1.58 × 10 -13 mol.L -1

Acknowledgements

This work has been sponsored by the French Research Agency under its Collaborative Research Project program PICPOSS (ANR-15-CE07-0008-01), the French government research program "Investissements d'Avenir" through the IDEX-ISITE initiative 16-IDEX-0001 (CAP 20-25) and the IMobS 3 Laboratory of Excellence (ANR-10-LABX-16-01). The authors thank also the CAPES program BRAFITEC (with the process 88881.142573/2017-01).


Jeremy Vanhelst

Laurent Beghin

Alain Duhamel

Stefaan De Henauw

Jonatan R Ruiz

Anthony Kafatos

Yannis Manios

Kurt Widhalm

Béatrice Mauro

Michael Sjöström

Jérémy Vanhelst

Laurent Béghin

Frédéric Gottrand

Physical activity awareness of European adolescents: The HELENA study

Keywords: Youth, Health, Assessment

niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers,

Introduction

Physical activity (PA) is recognized as an important determinant of health in children and adolescents. Increasing participation in moderate-to-vigorous PA (MVPA) has important health benefits, such as decreasing risk factors for obesity, cardiovascular and pulmonary diseases, cancer, and depression, and improving bone health (Halla, Victora, Azevedo, & Wells, 2006). Physical inactivity in children and adolescents is associated with low physical abilities and increase morbidity and mortality in adulthood (Garcia Cruz et al., 2014).

Adolescence is a crucial period for the development of healthy lifestyle habits.

However, this period is marked by a decline in PA mainly by reducing the time spent in MVPA [START_REF] Zook | Physical activity trajectories and multilevel factors among adolescent girls[END_REF][START_REF] Olds | How do school-day activity patterns differ with age and gender across adolescence[END_REF][START_REF] Bélanger | When adolescents drop the ball: sustainability of physical activity in youth[END_REF][START_REF] Van Mechelen | Physical activity of young people: the Amsterdam Longitudinal Growth and Health Study[END_REF][START_REF] Telama | Decline of physical activity from youth to young adulthood in Finland[END_REF]. Moreover, interventions to promote PA in children and adolescents have had limited success [START_REF] Dobbins | School-based physical activity programs for promoting physical activity and fitness in children and adolescents aged 6 to 18[END_REF][START_REF] Van Sluijs | Effectiveness of interventions to promote physical activity in children and adolescents: systematic review of controlled trials[END_REF]. The hypothesis most often used to explain the limited effectiveness of interventions or promotion programs is the lack of awareness of adolescents about their health status [START_REF] Hebert | Gender differences in social desirability and social approval bias in dietary self-report[END_REF][START_REF] Oenema | Feedback strategies to raise awareness of personal dietary intake: results of a randomized controlled trial[END_REF]. The perception of being physically active or inactive is difficult for children and adolescents to appreciate. Therefore, adolescents may think they are achieving healthy lifestyle habits, but overestimate their PA levels. Only two studies on PA awareness have been performed in children and adolescents, and these have shown that a substantial number of adolescents and children believe themselves to be more physically active than they really are [START_REF] Corder | Physical Activity Awareness of British Adolescents[END_REF][START_REF] Corder | Perception versus reality awareness of physical activity levels of British children[END_REF]. Data from adolescents are scarce and are limited to British adolescents.

The aim of the present study was to examine awareness of PA in a large sample of European adolescents and to identify anthropometric and psychosocial factors that can lead to a misreporting of PA.

Materials and Methods

Study Design

The current report is based on data from the Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) study. The aim of the HELENA study was to obtain a broad range of standardized, reliable, and comparable nutrition-and health-related data from a random sample of European adolescents aged 12.5-17.5 years. Data were collected in 2006 and 2007 in 10 European cities: Vienna (Austria), Ghent (Belgium), Lille (France), Athens (Greece), Heraklion (Greece), Pecs (Hungary), Rome (Italy), Dortmund (Germany), Zaragoza (Spain), and Stockholm (Sweden). In total, 3528 adolescents (1844 girls and 1684 boys) meeting the inclusion criteria completed all examinations. A detailed description of the HELENA study methodology and sampling has been published elsewhere [START_REF] Béghin | Main characteristics and participation rate of European adolescents included in the HELENA study[END_REF]Moreno et al., 2008a;Moreno et al., 2008b).

The aims and objectives were explained carefully to each adolescent and their parents. Written, informed consent was obtained from the adolescent and their parents. The HELENA study was approved by the local ethics committee for each country, and all procedures were performed in accordance with the ethical standards of the Helsinki Declaration of 1975 as revised in 2008 and with the European Good Clinical Practices [START_REF] Béghin | Quality assurance of ethical issues and regulatory aspects relating to good clinical practices in the HELENA Cross-Sectional Study[END_REF].

From the total population of 3528 adolescents, 2044 with complete data for selfrated PA and objectively assessed PA were included in the present study.

Measurements

Anthropometric Characteristics. Body weight was measured with the subjects wearing light clothes and without shoes to the nearest 0.1 kg using an electronic scale (SECA 871; SECA, Hamburg, Germany). Height was measured without shoes to the nearest 0.1 cm using a telescopic height-measuring instrument (SECA 225; SECA).

Body mass index (BMI) was calculated as weight (kg)/height 2 (m 2 ). The nutritional status was assessed using the International Obesity Task Force scale [START_REF] Cole | Establishing a standard definition for child overweight and obesity worldwide: international survey[END_REF]. Body composition (fat mass) was assessed using the bioelectrical impedance method (BodyGram V. 1.31; Akern Bioresearch, Florence, Italy) as described previously (Vicente-Rodriguez et al., 2012).

Self-perception PA. Self-perception PA was assessed before the objective PA assessment. The adolescents answered a single question: "Do you think you are physically active?" The possible answers were "very inactive," "fairly inactive," "moderately active," "fairly active," and "very active." The adolescents were classified into two categories: inactive when the answer was "very inactive", "fairly inactive" or "moderately active" and active when the answer was "fairly active" or "very active" [START_REF] Corder | Physical Activity Awareness of British Adolescents[END_REF].

Objective PA Assessment. The ActiGraph GT1M ® monitor (ActiGraph, Pensacola, FL, USA) was used to assess the participants' PA in free-living conditions. The device is a uniaxial accelerometer that measures 51 × 41 × 15 mm and weighs 43 g.

Accelerometry assesses PA by measuring mechanical movement. This device has been validated against oxygen consumption and heart rate for the assessment of PA levels [START_REF] Treuth | Defining accelerometer thresholds for activity intensities in adolescent girls[END_REF]. The interinstrument reliability of this device is high for both sedentary activities than for vigorous activities [START_REF] Vanhelst | Comparative interinstrument reliability of uniaxial and triaxial accelerometers in free-living conditions[END_REF][START_REF] Mcclain | Actigraph accelerometer interinstrument reliability during free-living in adults[END_REF]. The epoch interval for the ActiGraph GT1M ® monitor was set at 15 s. The adolescents wore the accelerometer on the lower back with an elastic belt and adjustable buckle. The adolescents were then asked to follow their normal daily routine. They were instructed to remove the accelerometer during swimming, showering, and bathing. The accelerometer recorded activity for 7 consecutive days and was taken off at night. Data were uploaded from the monitor to a computer after the completed 7-day registration period. Participants who did not record at least 3 days of recording with a minimum of 8 h of activity per day were excluded from the analyses. Zero activity periods of 20 min or longer were interpreted as "not worn time," and these periods were removed from the summation of activity. The assessment of time spent in sedentary, light, moderate, and vigorous PA was based on cutoff points of 0-500, 501-1999501- , 2000501- -2999501- , and >2999 counts/min, respectively (Riddoch et al., 2004;;[START_REF] Ekelund | Independent associations of physical activity and cardiorespiratory fitness with metabolic risk factors in children: the European youth heart study[END_REF]. Adolescents were classified as active or inactive using the thresholds of 60 minutes per day of MVPA, according to the world health public recommendations on PA [START_REF] Cale | Exercise recommendations for young people: An update[END_REF].

Psychosocial Factors. Parental educational level (PEL) was classified into one of four categories using a specific questionnaire adapted from the International Standard Classification of Education (ISCED) (http://www.uis.unesco.org/ Library/Documents/isced97-en.pdf). PEL was scored as 1, primary and lower education (levels 0, 1, and 2 in the ISCED classification); 2, higher secondary (levels 3 and 4 in the ISCED classification); and 3, tertiary (levels 5 and 6 in the ISCED classification).

Socioeconomic status was assessed according to the International Standard

Classification

of Occupations (ISCO: http://unstats.un.org/unsd/class/family/family2.asp?Cl=224). The ISCO categories of 1 (highest level) to 9 (lowest level) were scored as high (ISCO categories 1 and 2), medium (ISCO categories 3-5), and low (ISCO categories 6-9).

Encouragement by relatives and friends to be physically active was assessed in the questionnaire. The adolescents were asked the following question about the encouragement about PA they received from family members (father, mother, brothers, and sisters) and best friend: "How often does your relative encourage you to be physically active?" There were separate questions for father, mother, brothers, sisters, and best friend. Answers were also classified into two levels (categories) of encouragement: no, if the answer was "not at all." "not much," or "sometimes," and yes if the answer was "often" or "very often."

Cardiorespiratory fitness. 20m shuttle run test assesses the cardiorespiratory fitness. The adolescents performed the test as described earlier [START_REF] Léger | The multistage 20 metre shuttle run test for aerobic fitness[END_REF]. Participants are required to run between two lines 20 m apart, while keeping pace with audio signals emitted from a pre-recorded CD. The initial speed is 8.

5 km•h -1 , which is increased by 0.5 km•h -1 •min -1 (

Statistical Analysis

The qualitative variables are expressed as frequency and percentage. The continuous variables are reported as mean ± standard deviation (SD).

To access the selection bias related to missing data on self-rated PA or objective PA assessment, the main patients' characteristics were compared using Student's t test for quantitative variables, Chi-Square test for qualitative nominal variables and Mantel-Haenszel trend test for qualitative ordinal variables between included and excluded adolescents. To evaluate the magnitude of differences between included and excluded adolescents, we calculated the absolute standardized differences; a standardized difference higher than 20% denotes meaningful imbalance.

Adolescents were classified into four PA awareness subgroups (realistically active, over-estimators, under-estimators, and realistically inactive) according to the comparison between their perception of PA and objectively assessed PA. We compared the characteristics and psychosocial factors of adolescents firstly between over-estimators and realistically inactive adolescents (active adolescent analysis), and secondly between under-estimators and realistically active adolescents (inactive adolescent analysis). Between-group comparisons were performed using mixed logistic regression models including center as a random effect. For both active and inactive adolescents analyses, variables associated with misreporting of PA with a P < .10 were considered as candidates predictors into multivariable logistic regression analysis, except brother and sister support PA since some adolescents were single children. Moreover, since fat mass, BMI and nutritional status were highly correlated, only nutritional status were considered as candidate. The full models were simplified with a backward selection procedure with a value of P < .05 used as the cutoff for retention in the model. To avoid case deletion in multivariable analyses due to missing data on candidate predictors, missing data were treated by multiple imputation using regression switching imputation (chained equations approach, with m = 10 imputations using all adolescent's and psychosocial characteristics except brother and sister support) with predictive mean matching method for continuous variables, logistic regression model for binary variables, and ordinal logistic regression for ordered categorical variables [START_REF] Van Buuren | MICE: Multivariate Imputation by Chained Equations in R[END_REF]. Odds ratios (ORs) with their 95% confidence intervals (95% CIs) were calculated using realistically active as the reference in the active adolescents analysis and realistically inactive as reference in the inactive adolescents analysis. We further evaluated the impact of brother and sister support PA on misreporting of PA in separate multivariable analyses including the independent predictors identified in backward stepwise regressions analyses.

All statistical tests were performed at the two-tailed α level of .05. Data were analyzed using SAS software (version 9.4; SAS Institute Inc., Cary, NC, USA).

Results

Of 3528 adolescents meeting the inclusion criteria, 2044 (57.9%) were finally included in the statistical analysis after excluding those with missing data on selfrated PA or objective PA assessment. Characteristics of the population studied are presented in Table 1. We found differences between included and excluded adolescents on characteristics but with no meaningful differences regarding the absolute standardized differences.

Forty-five percent of the adolescents estimated their PA correctly: 34.8%

realistically active and 10.1% realistically inactive (Table 2). By contrast, 55% of the adolescents perceived their PA levels incorrectly, mostly by overestimating their PA.

Of the 59.4% of adolescents who were inactive, 82.9% overestimated their PA levels (49.3% of all participants). Very few of the adolescents who were active underestimated their PA levels (5.8% of all participants).

Among the active adolescents, compared with those classified as realistically active, those who underestimated their PA level were older, had a greater nutritional status, fat mass and BMI, had lower ISCO mother status, received less encouragement about PA from their father, mother, brother, sister and best friend and had lower cardiorespiratory fitness (Table 3). In multivariable analysis, having a greater nutritional status, a lower ISCO mother status and not receiving encouragement about PA from their mother and best friend were independently associated with PA underestimation (Table 4). For adolescents who have a brother, not receiving encouragement about PA from them was associated with underestimation (OR= 0.39; 95%CI = 0.16 -0.96; p = 0.040). For adolescents who have a sister, not receiving encouragement about PA from them was not associated with underestimation (OR = 0.48; 95%CI = 0.20 -1.16; p = 0.10).

Among the inactive adolescents, compared with those classified as realistically inactive, those who overestimated their PA level were, received more encouragement about PA from their father, mother, sister and best friend and had higher cardiorespiratory fitness (Table 5). In multivariable analysis, having a higher cardiorespiratory fitness, being older and receiving more encouragement about PA from their mother and best friend were independently associated with PA overestimation (Table 6). For adolescents who have a brother, receiving encouragement about PA from them was not associated with overestimation (OR = 0.98; 95%CI = 0.56 -1.72; p = 0.95). For adolescents who have a sister, receiving encouragement about PA from them was not associated with overestimation (OR = 1.22; 95%CI = 0.63 -2.37; p = 0.55).

Discussion

To our knowledge, only one study has addressed PA awareness in adolescents [START_REF] Corder | Physical Activity Awareness of British Adolescents[END_REF]. Our study is the first to investigate this topic in a large sample of European adolescents and to try to identify the anthropometric and psychosocial factors that may lead to their misreporting PA. The results of the present study show that >50% of adolescents have an overestimation of their PA habits.

The high rate of misperception about their PA levels may be explained by social desirability (the tendency to respond in such a way as to avoid criticism) and social approval (the tendency to seek praise), which can bias answers in structured questionnaires [START_REF] Hebert | Gender differences in social desirability and social approval bias in dietary self-report[END_REF]. Our findings support the previous observations in the literature, which suggest that adolescents have a worst perception of their PA than are children [START_REF] Corder | Perception versus reality awareness of physical activity levels of British children[END_REF]. The European adolescents included in our study appeared to overestimate their PA levels compared with the British adolescents included in an earlier study [START_REF] Corder | Physical Activity Awareness of British Adolescents[END_REF]. In our study, 50% of inactive European adolescents believed themselves to be physically active compared with 60.3% and 64.8% in the British adolescents girls and boys, respectively [START_REF] Corder | Physical Activity Awareness of British Adolescents[END_REF]. These differences might be actual or explained by differences in sample size (larger in our study) and/or methodology to assess PA (cutoffs for PA intensity).

Indeed, methodological issues relating to calibration of the accelerometer might explain the discrepancies we found in the present study. Several studies showed clearly that the differences in accelerometer cut-points in the published references can lead to a large discrepancy in the assessment of PA patterns [START_REF] Vanhelst | Impact of the choice of threshold on physical activity patterns in free living conditions among adolescents measured using a uniaxial accelerometer: The HELENA study[END_REF][START_REF] Trost | Comparison of accelerometer cut points for predicting activity intensity in youth[END_REF][START_REF] Guinhouya | Moderate-to-vigorous physical activity among children: Discrepancies in accelerometry-based cut-off points[END_REF]. The percentages of adolescents relative to the total population studies fulfilling the recommendation of 60 min of MVPA per day can to vary between 5.9% to 37%

according to the method used [START_REF] Vanhelst | Impact of the choice of threshold on physical activity patterns in free living conditions among adolescents measured using a uniaxial accelerometer: The HELENA study[END_REF].

We identified some characteristics and psychosocial factors as associated with the overestimation of PA. First, we found that age influences the overestimation of PA. Adolescents who overestimated their PA level were older than those realistic about their inactivity. This finding is in agreement with previous studies performed in British children and adolescents separately [START_REF] Corder | Physical Activity Awareness of British Adolescents[END_REF][START_REF] Corder | Perception versus reality awareness of physical activity levels of British children[END_REF]. Authors found in children aged 9 to 10 years that 40% of inactive children perceived themselves as actives while in adolescents aged 14 to 15 years, 60% of inactive adolescents perceived themselves as actives [START_REF] Corder | Physical Activity Awareness of British Adolescents[END_REF][START_REF] Corder | Perception versus reality awareness of physical activity levels of British children[END_REF]. Therefore, the adolescents appear to be less aware than children about their PA levels. Our results with previous studies show the age might have an impact on the PA awareness. The first possible explanation could be due to social desirability bias, more important in adolescent compared to the children who can be unaware of PA benefits on health. Another explanation could be the fact that the PA declines with age [START_REF] Ortega | Objectively measured physical activity and sedentary time during childhood, adolescence and young adulthood: a cohort study[END_REF][START_REF] Corder | Change in objectively measured physical activity during the transition to adolescence[END_REF].

Adolescents were more likely to overestimate their PA levels when they had more support from their best friend and their mother. Our results are in agreement with the previous study performed in British adolescents [START_REF] Corder | Physical Activity Awareness of British Adolescents[END_REF].

Although several studies highlighted the positive role of social encouragement on adolescents' PA levels (Martin-Matillas et al., 2011;[START_REF] Sallis | A review of correlates of physical activity of children and adolescents[END_REF], our data unexpectidely show that peer and parent support are negatively associated with PA awareness. We have no clear explanation for these findings but on a practical point of view, this should be taken into account when designing interventions involving family and friends where the positive influence on PA levels could be counterbalance by a negative PA awareness.

Adolescents who overestimated their PA levels reported higher cardiorespiratory fitness than those realistic about their inactivity. Like peer support, although a higher cardiorespiratory fitness appears to be associated with a lack of PA awareness, the aerobic fitness has other health benefits, such as reduced risk factors for cardiovascular disease, to have fewer mental, nutritional, gastroenterological, cardiac, and respiratory diseases [START_REF] Ortega | Physical fitness in childhood and adolescence: A powerful marker of health[END_REF]. Our data show that cardiorespiratory fitness was positively associated with overestimation of PA while a good agreement between cardiorespiratory fitness measured objectively and self-reported physical fitness has been previously reported in adolescents [START_REF] Ortega | The International Fitness Scale (IFIS): usefulness of self-reported fitness in youth[END_REF][START_REF] Marsh | Physical fitness self-concept: relations of physical fitness to field and technical indicators in boys and girls aged 9-15[END_REF]. This finding suggest that overestimators might assume that they are enough active due to their favorable physical fitness.

Our finding that 50% of the adolescents misreported their PA level emphasizes the importance of improving awareness of PA as the first step in interventions to improve PA and the need to focus on the risk factors identified. If adolescents feel they are physically active when in fact they are not, they may be less sensitive to interventions aiming to increase PA. In this respect, the use of new technology (e.g., smartphone applications) may help [START_REF] Nolan | Validity of the Apple iPhone/iPod Touch® as an Accelerometer-Based Physical Activity Monitor: A Proof-of-Concept Study[END_REF][START_REF] Wu | Classification accuracies of physical activities using smartphone motion sensors[END_REF].

The current study has strengths and limitations. The strengths of the study are the large sample size of adolescents with gender-specific information in 10 European cities, the use of standardized procedures, the strong methodology to assess PA objectively (accelerometry), and the assessment of cardiorespiraory fitness which was not included in previous studies. The limitations of the study include the crosssectional design and that the observed associations cannot be interpreted to reflect causal relationships. Missing data on self-rated PA or objective PA assessment led to exclusion of 42% of adolescent enrolled in HELENA study. Although there was no meaningful differences between included and not included adolescents, we could not exclude that missing data could introduce a selection bias. In addition, the thresholds used for the PA assessment might have affected the results, as previously described [START_REF] Vanhelst | Impact of the choice of threshold on physical activity patterns in free living conditions among adolescents measured using a uniaxial accelerometer: The HELENA study[END_REF]. Variations in weather (wind, rain and sunshine) during the PA assessment were not recorded in our study and might also have affected our results. Moreover, the PA was assessed during one week while the questionnaire provided no time interval. We did not inform the adolescents about PA recommendations before the questionnaire was applied. This can lead to a misunderstanding on the assessment of the awareness. Then, as this study was performed ten years ago (2006)(2007), we can not be sure our results represent the present situation.

Conclusions

A high proportion of adolescents believe that they are physically active when they are not really. The adolescents with a higher cardiorespiratory fitness, receiving more support by their peers and being older more frequently inaccurately estimate they are active. The results from our study suggest the health promotion programs

  1 min equals one stage). Participants are instructed to run in a straight line, to pivot on completing a shuttle, and to pace themselves in accordance with the audio signals. The test is finished when the participant fails to reach the end lines concurrent with the audio signals on two consecutive occasions. Otherwise, the test ends when the participant stops because of fatigue. All measurements were carried out under standardized conditions on an indoor rubber-floored gymnasium. The participants were encouraged to keep running as long as possible throughout the course of the test. The last completed stage or half-stage at which the participant drops out was scored.

Table 1 .

 1 Comparison of main characteristics between the included and non-included adolescents Pubertal status staging according to Tanner c Education level: lower education (I); higher secondary education (II); higher education or university degree (III).

				Absolute
	Included	Not included	P-value	standardized
				difference (%)

b

Table 2 .

 2 Classification of 2044 adolescents into 4 physical activity awareness groups according to adolescent perception and the objective assessment

	Objectively assessed physical activity
	830 Active (40.6%)	1214 Inactive (59.4%)

Table 3 .

 3 Comparison of adolescent's characteristics and psychosocial factors between adolescent classified as realistically active and under-estimators

	Under-estimator	Realistically active	P

Table 4 .

 4 Multivariate analysis of independent factors associated with underestimation of physical activity among the active adolescents Calculated from backward-stepwise mixed logistic regression after handle missing data on adolescent's characteristics. Candidate variables included in the model were age, nutritional status, ISCO mother, father, mother and best friend support PA and cardiorespiratory fitness.

		Odds-ratio	95% CI	P
	Nutritional Status	1.61	1.16 -2.22	0.004
	Mother Support PA	0.60	0.39 -0.92	0.021
	ISCO mother	0.72	0.54 -0.97	0.028
	Best friend Support PA	0.58	0.34 -0.98	0.041

Table 6 .

 6 Multivariate analysis of independent factors associated with overestimation of physical activity among the inactive adolescents Calculated from backward-stepwise mixed logistic regression after handle missing data on adolescent's characteristics. Candidate variables included in the model were age, father, mother and best friend support PA and cardiorespiratory fitness. * Odds ratio calculated per one standard deviation increase (SD=7.5).

		Odds-ratio	95% CI	P
	Cardiorespiratory fitness*	1.43	1.15 -1.77	0.001
	Mother Support PA	1.67	1.20 -2.32	0.002
	Age	1.23	1.06 -1.42	0.006
	Best friend Support PA	1.81	1.14 -2.88	0.012

Funding

The HELENA study is made possible by the financial support of the European Community Sixth RTD Framework Programme (Contract FOOD- CT-20056007034) and the Spanish Ministry of Science and Innovation (RYC-2010-05957 and RYC-2011-09011). The content of this paper reflects only the authors' views, and the European Community is not liable for any use that may be made of the information contained therein.

should consider adolescents' awareness of their PA level and that this may not necessarily be accurate. Increasing their awareness of PA might help to bring about behavioral changes and might have positive effects on their health status. Our results support the idea that the first step of any intervention program on PA should focused on awareness, especially in the at risk groups we defined. Any intervention without first being aware of actual PA levels should fail.

Conflict of interest

The authors do not have any competing interests.


Jeremy Vanhelst
email: jeremy.vanhelst@chru-lille.fr

Laurent Beghin

Alain Duhamel

PhD Yannis Manios

PhD Denes Molnar

Stefaan De Henauw

MD Luis A Moreno

Ortega Francisco

Michael Sjostrom

MD Kurt Widhalm

Vanhelst Jérémy

PhD Béghin Laurent

MD Sefaan De Henauw

MD Francisco B Ortega

PhD Michael Sjöström

MD Gottrand Frédéric

Physical Activity Is Associated with Attention Capacity in Adolescents

Keywords: Youth, Lifestyle habits, Health, Cognitive function

ou non, émanant des établissements d'enseignement et de recherche

Introduction

Physical activity (PA) is an important determinant of health throughout the whole lifespan. Engaging in regular moderate-to-vigorous PA (MVPA) has important health benefits, especially in the treatment of metabolic syndrome-related disorders such as obesity, heart and pulmonary diseases, bone and joint diseases, cancer, depression, asthma and in cognitive function. [START_REF] Pedersen | Evidence for prescribing exercise as therapy in chronic disease[END_REF][START_REF] Sibley | The relationship between physical activity and cognition in children: A meta-analysis[END_REF][START_REF] Kashihara | Positive effects of acute and moderate physical exercise on cognitive function[END_REF] The two important parameters of cognition in children and adolescents are attention and concentration because they are indispensable elements in comprehension and learning processes. [START_REF] Pesce | Physical activity and mental performance in preadolescents: effects of acute exercise on free-recall memory[END_REF][START_REF] Diamond | The early development of executive functions[END_REF][START_REF] Zervas | Physical activity and cognitive functioning[END_REF] Attention is the behavioral and cognitive process of selectively concentrating on one aspect of the environment while ignoring other things. [START_REF] Diamond | The early development of executive functions[END_REF][START_REF] Zervas | Physical activity and cognitive functioning[END_REF] Sibley and Etnier performed a meta-analysis on PA and cognition in children. [START_REF] Sibley | The relationship between physical activity and cognition in children: A meta-analysis[END_REF] They concluded that there is a significant positive relationship between PA and cognitive function in children. [START_REF] Sibley | The relationship between physical activity and cognition in children: A meta-analysis[END_REF] However, this only included studies conducted to investigate the effects of exercise type on cognitive functions. Moreover, in this meta-analysis eight categories of cognitive assessment tools were used: perceptual skills, intelligent quotient, achievement, verbal tests, math tests, memory, developmental level and academic readiness. Although there could be overlap between IQ testing and some aspect of attention, no specific study assessing attention capacity has been included in the metaanalysis. Some interventional studies showed that the type [START_REF] Pesce | Physical activity and mental performance in preadolescents: effects of acute exercise on free-recall memory[END_REF][START_REF] Brisswalter | Effects of acute physical exercise characteristics on cognitive performance[END_REF] , the duration [START_REF] Budde | Acute coordinative exercise improves attentional performance in adolescents[END_REF][START_REF] Budde | Steroid hormones in the saliva of adolescents after different exercise intensities and their influence on working memory in a school setting[END_REF] or the intensity of PA positively influenced cognitive functions. [START_REF] Hillman | The effect of acute treadmill walking on cognitive control and academic achievement in preadolescent children[END_REF] Indeed, studies have suggested that short bouts of exercise on coordinative skills or a single and acute bouts of MVPA might have an impact on attention capacity in adolescents. [START_REF] Brisswalter | Effects of acute physical exercise characteristics on cognitive performance[END_REF][START_REF] Budde | Acute coordinative exercise improves attentional performance in adolescents[END_REF][START_REF] Budde | Steroid hormones in the saliva of adolescents after different exercise intensities and their influence on working memory in a school setting[END_REF][START_REF] Gallotta | Effects of varying type of exertion on children's attention capacity[END_REF][START_REF] Gallotta | Acute physical activity and delayed attention in primary school students[END_REF][START_REF]The association between school based physical activity, including physical education, and academic performance[END_REF] All these studies examined the improvement of the attention ability after an acute challenge intervention. [START_REF] Brisswalter | Effects of acute physical exercise characteristics on cognitive performance[END_REF][START_REF] Budde | Acute coordinative exercise improves attentional performance in adolescents[END_REF][START_REF] Budde | Steroid hormones in the saliva of adolescents after different exercise intensities and their influence on working memory in a school setting[END_REF][START_REF] Gallotta | Effects of varying type of exertion on children's attention capacity[END_REF][START_REF] Gallotta | Acute physical activity and delayed attention in primary school students[END_REF][START_REF]The association between school based physical activity, including physical education, and academic performance[END_REF] However, to our knowledge, there is no study examining the baseline attention capacity with respect to adolescent PA patterns.

Therefore, the primary aim of this study was to investigate the relationship of PA, measured objectively, with the attention capacity of European adolescents. The secondary aim was to establish the optimal PA intensity cut-off that best discriminated between low and good attention capacities.

Methods

Study design

This is an ancillary study of the HELENA project (Healthy Lifestyle in Europe by Nutrition in Adolescence; www.helenastudy.com) performed in European adolescents (2006-2007). The aim of the HELENA study was to obtain a broad range of standardized, reliable, and comparable nutrition-and health-related data from a random sample of European adolescents aged 12.5-17.5 years. The random selection of schools and classes was performed centrally (by the Ghent University) for almost all cities (except for Pecs and Athens, where schools were locally selected due to local administrative constraints). Details about the selection criteria for schools and classes were previously reported. [START_REF] Moreno | Design and implementation of the Healthy Lifestyle in Europe by Nutrition in Adolescence Cross-Sectional Study[END_REF] The inclusion criteria in the study were: (i) Male and female subjects aged [12.5-17.5] years old; (ii) Schooling in one of the participating classes; (iii) Informed consent form signed by the parents and/or the legal guardian; (iv) Subject was not participating simultaneously in another similar study. Each participating center was asked to include about 150 male and female adolescents per age stratum (12.5-14; 14-15; 15-16; 16-17.5

years).

In total, 3528 adolescents (1844 girls and 1684 boys) meeting the inclusion criteria completed all examinations. A detailed description of the HELENA study methodology and sampling has been published elsewhere. [START_REF] Moreno | Assessing, understanding and modifying nutritional status, eating habits and physical activity in European adolescents: the HELENA (Healthy Lifestyle in Europe by Nutrition in Adolescence) Study[END_REF][START_REF] Béghin | Quality assurance of ethical issues and regulatory aspects relating to good clinical practices in the HELENA Cross-Sectional Study[END_REF] For the purposes of the present study, all participants with valid data on PA, anthropometric characteristics, aerobic fitness and attention ability were included into the analysis (n= 273) (Figure 1). Data were obtained from six countries: France (Lille), Spain (Zaragoza), Austria (Vienna), Germany (Dortmund), Hungary (Pecs), and Greece (Athens).

The aims and objectives were carefully explained and written consents were obtained from the adolescents and their parents. The local ethics committee for each country approved the HELENA study, and all procedures were performed in accordance with the ethical standards of the Helsinki Declaration of 1975 (as revised in 2008) and the European Good Clinical Practice Guidelines. 17

Measurements

Participants' Characteristics

Weight was measured in light clothes, without shoes, to the nearest 0.1 kg using an electronic scale (SECA 871; SECA, Hamburg, Germany). Height was measured without shoes to the nearest 0.1 cm using a telescopic height-measuring instrument (SECA 225; SECA). Body mass index (BMI) was calculated as weight (kg)/height 2 (m 2 ). The nutritional status was assessed by the International Obesity Task Force scale. [START_REF] Cole | Establishing a standard definition for child overweight and obesity worldwide: international survey[END_REF] Total fat and fat free mass were assessed using bioelectrical impedance analysis (AKERN ® ; BIA101 AKERN, Pontassieve, Italy). Following a 5-min rest, subjects were placed in a supine position with arms and legs in abduction between 30 and 40° from the trunk. Electrode tape, conductivity gel, and current electrodes were placed on the dorsal surfaces of the right hand and foot at the distal metacarpals and metatarsals, respectively. [START_REF] Houtkooper | Bioelectrical impedance estimation of fat-free body mass in children and youth: a cross-validation study[END_REF] The parental educational level was classified into one of four categories using a specific questionnaire,

Attention capacity

Attention capacity was assessed by the d2 Test of Attention (d2T). [START_REF] Brickenkamp | The d2 Test of Attention[END_REF] The choice to use the d2T was made because it is low cost, easily and rapidly administered, and enables large numbers of people to be tested simultaneously. It was developed to measure sustained attention and concentration under stress induced by a completion time. The principle of this test is to assess performance in terms of visual perceptual speed and concentrative capacities by assessing an individual's ability to selectively focus on certain relevant aspects in a task while ignoring other irrelevant ones, as well as doing so quickly and accurately. This principle reflects three components of attentional/concentration behavior:

(i) speed/velocity by quantity of work in a period of time, (ii) concentration by quality of work (iii), and performance quality by assessing the relationship between speed/velocity and work quality.

The d2T is a paper-and-pencil letter-cancellation test comprising 14 different lines, each one containing 47 randomly-mixed letters ("p" and "d"), for a total of 658 letters. Letters "p" and "d" appear with one or two dashes above or below each letter. The test subject has to carefully check if each letter "d" has two dashes either above or below it, at a rate of 20 s per line. The complete duration of the test is 4 min and 30 seconds. Testing using d2T was carried out in a classroom under the supervision of an HELENA fieldworker during the morning. All d2T were performed before the PA assessment. A low error rate indicates high-quality performance. The reliability of the d2T has a range between 0.95 and 0.98, and the validity coefficient is 0.47. [START_REF] Brickenkamp | The d2 Test of Attention[END_REF] The attention capacity was calculated by the formula: number of correct guesses, this is, number of correct relevant elements -commissions, number of irrelevant elements marked. Percentiles (%ile) of attention capacity were determined by using the norms given in the test manual, according to sex and age through raw data. Percentiles of attention capacity could be divided into two categories: 1. Low attention capacity (%ile < 25), normal to high attention capacity (%ile ≥ 25 and 75).

Physical Activity

The ActiGraph ® Monitor (ActiGraph GT1M ® ; ActiGraph, Pensacola, FL, USA) was used to assess the physical activity in free-living conditions. [START_REF] Ruiz | Objectively measured physical activity and sedentary time in European adolescents: the HELENA study[END_REF] This is a uniaxial accelerometer that measures 51  41  15 mm and weighs 43 g. This device has been validated against oxygen consumption and heart rate to assess physical activity. [START_REF] Vanhelst | New validated thresholds for various intensities of physical activity in adolescents using the Actigraph accelerometer[END_REF] The inter-instrument reliability of this device is high for both sedentary and vigorous activities. The epoch interval for the ActiGraph ® monitor was set at 15 s. The adolescents wore the accelerometer on the lower back with an elastic belt and adjustable buckle. They were instructed to remove the accelerometer during swimming, showering, and bathing. The accelerometers recorded activity for 7 consecutive days and were taken off at night.

Data were uploaded from the monitor to a computer after the completed registration period (7 days).

Participants who did not record at least 3 days of recording with a minimum of 8 hours of activity per day were excluded from the analyses. Zero activity periods of 20 min or longer were interpreted as "not worn time," and these periods were removed from the summation of activity. Moderate-tovigorous physical activity levels of the adolescents were assessed using the thresholds reported in previous studies of adolescents. [START_REF] Ekelund | Independent associations of physical activity and cardiorespiratory fitness with metabolic risk factors in children: the European youth heart study[END_REF][START_REF] Riddoch | Physical activity levels and patterns of 9-and 15-yr-old European children[END_REF] The assessment of time spent in sedentary, light, moderate, and vigorous physical activity was based on cut-off ranges of 0-500, 501-1999, 2000-2999, and > 2999 counts•min -1 , respectively. fitness level and center). [START_REF] Khan | The relation of childhood physical activity and aerobic fitness to brain function and cognition: a review[END_REF][START_REF] Castillo | Associations between parental educational/occupational levels and cognitive performance in Spanish adolescents: the AVENA study[END_REF][START_REF] Davis | Fitness, fatness, cognition, behavior, and academic achievement among overweight children: do cross-sectional associations correspond to exercise trial outcomes?[END_REF] Since nutritional status was based on BMI, we included only BMI into regression models; similar results were found when multivariable regression models were refit replacing BMI with nutritional status (data not shown). We assessed the heterogeneity in association between PA parameters and attention capacity across sex by including the corresponding interaction term into multivariable regression models.

Statistical analysis

In order to assess the linearity of relationship between attention capacity and PA parameters, further analyses were done after categorization of PA according to quartiles using analysis of covariance; linear contrasts were used to perform trend tests.

Receiver operating-characteristic (ROC) curves were used to calculate the optimal physical activity cut-off points for moderate, vigorous, and moderate-to-vigorous PA that best discriminated between low and good attention capacity categories. The area under the curve (AUC) was determined by plotting sensitivity vs 1-specifıcity of a test as the threshold varies over its entire range. Taking into account the suggested cut-off points, the test can be: non informative/test equal to chance (AUC = 0.5); less accurate (0.5 < AUC  0.7); moderately accurate (0.7 < AUC  0.9); highly accurate (0.9 < AUC < 1.0), or a perfect discriminatory test (AUC = 1.0). [START_REF] Swets | Measuring the accuracy of diagnostic systems[END_REF] Cut-off points were selected for those scores optimizing the sensibility-specifıcity relationship.

Results

A descriptive analysis of the study population is reported in Table 1. One hundred thirty adolescents (47.6%) performed more 60 min.day -1 of moderate-to-vigorous PA.

Insert Table 1 In multivariate analyses, time spent in moderate or moderate-to-vigorous PA in free-living conditions were significantly associated with an increase adolescents' attention capacity after adjustment for the level of education of the father and mother, age, sex, BMI, center, fat mass and aerobic fitness level (P < 0.05) (Table 2). In addition to PA parameters, only mother's education level and center remained independently associated with attention capacity in any of multivariate analyses (data not shown). We found no significant heterogeneity in the association of each PA parameters and attention capacity across sex (P for all interaction>0.80).

Insert Table 2

Quartile analysis of each PA parameters confirmed the linearity of association of attention capacity with the time spent in moderate or moderate-to-vigorous PA (Figure 2). Those adolescent with moderate-to-vigorous PA more 60 min.day -1 had a mean score of attention capacity test at 48.7 (± 30.0) while those are sedentary (<60 min.day -1 ) had a mean score of 40.9 (± 29.8) (P < 0.05). As shown in figure 2, any of the PA levels really influence attention capacity suggesting that duration of moderate to vigorous PA is the main contributor to increase attention capacity score.

Insert Figure 2 ROC analysis showed that PA levels discriminate good from low attention capacity in adolescents are presented in Table 3.

Insert Table 3

Discussion

This study is the first to investigate the potential impact of PA, measured objectively, on adolescents' attention capacity. Our findings revealed a significant positive correlation between moderate-to-vigorous PA and underlying attention capacity.

The association between PA levels and attention capacity, taking into account age, BMI, sex, educational level of parents, center, fat mass and aerobic fitness levels, supports the hypothesis that there is a positive effect of PA on attention capacity in adolescents. These associations were independent of sex, but we caution that we lacked of adequate statistical power to detect significant interaction. Due to the cross sectional design of our study we however cannot exclude that those adolescents who have a high underlying attention ability are those capable of the increased attention necessary to perform moderate-to-vigorous activity regularly, whereas the others are not. The effects of PA on cognitive functions could be due to physiological changes, such as increased levels of brainderived neurotrophic factor (BDNF). BDNF facilitates learning and maintains cognitive functions by improving synaptic plasticity, acting as a neuroprotective agent, increasing brain circulation and improving neuroelectric functionality. [START_REF] Hillman | The effect of acute treadmill walking on cognitive control and academic achievement in preadolescent children[END_REF] Previous studies on the attention capacity and PA were intervention studies using a pre and post test, with an intervening acute challenge. [START_REF] Pesce | Physical activity and mental performance in preadolescents: effects of acute exercise on free-recall memory[END_REF][START_REF] Budde | Acute coordinative exercise improves attentional performance in adolescents[END_REF][START_REF] Hillman | The effect of acute treadmill walking on cognitive control and academic achievement in preadolescent children[END_REF][START_REF] Gallotta | Effects of varying type of exertion on children's attention capacity[END_REF][START_REF] Gallotta | Acute physical activity and delayed attention in primary school students[END_REF][START_REF]The association between school based physical activity, including physical education, and academic performance[END_REF] Our study is the first to examine the baseline, general attention performance with respect to adolescent PA patterns levels. Our findings suggest that increasing PA in free living conditions might be a helpful method for adolescent to reach a higher performance level during teaching lessons or other cognitive tasks.

One interesting finding of our study is that moderate, but not vigorous, PA had a significant positive effect on the attention capacity test (Table 2). Shephard has suggested that involvement in the PA may have induced an immediate arousal and relief from boredom, with the result that the adolescents paid better attention capacity. [START_REF] Shephard | Habitual physical activity and academic performance[END_REF] As suggested Coe et al, it is possible that a threshold level of activity may be needed to produce these potentially desirable effects. [START_REF] Coe | Effect of physical education and activity levels on academic achievement in children[END_REF] This may explain why high attention capacity is associated with moderate activity and not with vigorous PA in our present study.

Indeed, vigorous PA might lead to an increase the fatigue compared to moderate PA, and therefore to a decline of the attention capacity. While teachers in Western countries have reported increasing difficulty in maintaining adequate attention and concentration levels in children and adolescents, our results suggest to reinforce the necessity to offer regular physical education lessons with exercise at a moderate intensity in order to improve these two components of cognitive function and help the learning process. However, future research is needed to investigate PA intensity effects on attention capacity using an intervention study with a control group.

A secondary outcome of our study was to establish the optimal physical activity time at moderate and high PA intensities to "obtain" good attention capacity in adolescents. The current physical activity recommendation of at least 60 min•day -1 of moderate-to-vigorous physical activity intensity has been based on obesity prevention or other health outcomes. [START_REF] Pedersen | Evidence for prescribing exercise as therapy in chronic disease[END_REF] We found similar results in our study;

i.e. spending more than 58 min•day -1 in moderate to vigorous physical activity intensity would be associated with better attention capacity. These findings support the use of the current physical activity recommendations for preventive purposes related to a good attention capacity in adolescents, but have to be taken with caution because of the low accuracy of PA cut-offs. Due to its cross-sectional design, the observed associations cannot be interpreted to reflect causal relationships. In addition, the lack of assessment of further neuropsychological functions beyond performance on the d2T may limit the interpretation of the results of our study. However, the use of standardized procedures that are strictly adhered to across different centers is a remarkable strength of the HELENA study. [START_REF] Moreno | Design and implementation of the Healthy Lifestyle in Europe by Nutrition in Adolescence Cross-Sectional Study[END_REF][START_REF] Moreno | Assessing, understanding and modifying nutritional status, eating habits and physical activity in European adolescents: the HELENA (Healthy Lifestyle in Europe by Nutrition in Adolescence) Study[END_REF] Harmonization and reliability of anthropometric and PA assessment techniques were carefully assessed throughout the study. [START_REF] Nagy | Harmonization process and reliability assessment of anthropometric measurements in a multicenter study in adolescents[END_REF] Another strength of this study is the inclusion of several confounding factors in the statistical analyses.

Conclusions

The results from this study show a positive association between physical activity and attention capacity in European adolescents. Moderate-to-vigorous PA might play a role in improving attention capacity in adolescents, which is an important component of cognitive function. The data obtained from this study contribute to develop a better understanding of the link between PA and attention capacity in youth. However, future research should be performed using an experimental design (i.e control and experimental groups with subjects randomization) in order to confirm the results of this present observational study. 466.4 ± 157.4 204.9-1047.4 a Nutritional status: underweight (UW), normal weight (NW), overweight (OW), obese (O). b Education level: lower education (I); lower secondary education (II); higher secondary education (III); higher education or university degree (IV). c Attention ability expressed in percentile. d Attention ability: low ability (I), normal to high ability (II). MVPA: moderate-to-vigorous physical activity.

Legends

  //www.uis.unesco.org/Library/Documents/isced97-en.pdf). Parental educational level was classified as [score = 1] primary education (level 0 and 1 from ISCED classification); [score = 2] lower secondary (level 2 from ISCED classification); [score = 3] higher secondary (level 3 and 4 from ISCED classification); [score = 4] tertiary (level 5 and 6 from ISCED classification).

Figure 1 .

 1 Figure 1. Final sample size flowchart (online only).

Figure 2 .

 2 Figure 2. Unadjusted and adjusted means of attention capacity according to the quartiles of

  Categorical data are expressed as percentages and continuous data are expressed as mean and standard deviations (SD). Normality of the distribution was tested by Shapiro-Wilk test. Statistical testing was conducted at the 2-tailed α level of 0.05. Data were analyzed with SAS software version 9.3 (SAS Institute Inc., Cary, NC, USA) (2013).

The association of each PA parameters with attention capacity were investigated in separate multivariate linear regression analysis including the potential confounding factors associated with attention capacity (age, sex, BMI, nutritional status, parental educational level, fat mass, aerobic

Table 1 .

 1 Standard errors of mean and adjusted p for trend are reported. Adjustments were done for age sex, mother's and father's educational level, BMI, center, fat mass and aerobic fitness level. Characteristics of the population studied (147 girls and 126 boys).

Table 2 .

 2 Association between each PA levels and attention capacity adjusted for potential confounding factors.

Table 3 .

 3 Physical activity cut-off points to predict good attention capacity in adolescents by ROC analysis.

Table 1 .

 1 Characteristics of the population studied (147 girls and 126 boys)

	Mean ± SD	Range
	(unless stated
	otherwise)

Table 2 .

 2 Association between each PA levels and attention capacity adjusted for potential confounding factors P-value adjusted for confounding factors : age, sex, BMI, educational level of parents, center, fat mass and aerobic fitness level

	PA levels	β ± SE	P*	Partial coefficient
				determination
	Sedentary PA	0.01 ± 0.02	0.4472	0.002
	Light PA	0.01 ± 0.04	0.8471	0.0001
	Moderate PA	0.30 ± 0.13	0.0195	0.016
	Vigorous PA	0.17 ± 0.15	0.2439	0.004
	Moderate to Vigorous PA	0.17 ± 0.08	0.0352	0.013
	β indicates regression coefficients; SE = Standard Error

*

The HELENA study is made possible by the financial support of the European Community Sixth RTD Framework Programme (Contract FOOD-CT-20056007034) and the Spanish Ministry of Science and Innovation (RYC-2010-05957 and RYC-2011-09011). The content of this paper reflects only the authors' views, and the European Community is not liable for any use that may be made of the information contained therein.

PA: physical activity, MVPA: moderate-to-vigorous physical activity; AUC: area under the curve.