This article was downloaded by: [Umeå University Library]On: 22 September 2013, At: 06:52Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,37-41 Mortimer Street, London W1T 3JH, UK

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Seasonal variation in physical activity and sedentarytime in different European regions. The HELENA studyLuis Gracia-Marco a b , Francisco B. Ortega c d e , Jonatan R. Ruiz d e , Craig A. Williams a ,Maria HagstrÖmer e f , Yannis Manios g , Anthony Kafatos h , Laurent Béghin i , Angela Politoj , Stefaan De Henauw k , Jara Valtueña l , Kurt Widhalm m , Denes Molnar n , Ute Alexy o ,Luis A. Moreno b p , Michael Sjöström e & Helena Study Group* qa University of Exeter , UKb University of Zaragoza , Spainc University of Granada , Spaind PROFITH ‘PROmoting FITness and Health through physical activity’ research group ,University of Granada , Spaine Department of Bioscience and Nutrition , Karolinska Institutet , Swedenf Department of Neurobiology , Karolinska Institutet , Swedeng Harokopio University , Greeceh University of Crete , Crete , Greecei Université Lille Nord de France and CIC-9301-Inserm CHU , Francej National Research Institute for Food and Nutrition , Italyk Ghent University , Belgiuml Technical University of Madrid , Spainm Private Medical University , Austrian University of Pécs , Hungaryo Rheinische Friedrich-Wilhelms-Universität , Germanyp Universidad de Zaragoza , Spainq HELENA Study Group – Please see AppendixPublished online: 20 Sep 2013.

To cite this article: Luis Gracia-Marco , Francisco B. Ortega , Jonatan R. Ruiz , Craig A. Williams , Maria HagstrÖmer , YannisManios , Anthony Kafatos , Laurent Béghin , Angela Polito , Stefaan De Henauw , Jara Valtueña , Kurt Widhalm , DenesMolnar , Ute Alexy , Luis A. Moreno , Michael Sjöström & Helena Study Group* , Journal of Sports Sciences (2013): Seasonalvariation in physical activity and sedentary time in different European regions. The HELENA study, Journal of Sports Sciences,DOI: 10.1080/02640414.2013.803595

To link to this article: http://dx.doi.org/10.1080/02640414.2013.803595

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Seasonal variation in physical activity and sedentary time in differentEuropean regions. The HELENA study

LUIS GRACIA-MARCO1,2, FRANCISCO B. ORTEGA3,4,5, JONATAN R. RUIZ4,5,CRAIG A. WILLIAMS1, MARIA HAGSTRÖMER5,6, YANNIS MANIOS7, ANTHONYKAFATOS8, LAURENT BÉGHIN9, ANGELA POLITO10, STEFAAN DE HENAUW11, JARAVALTUEÑA12, KURT WIDHALM13, DENES MOLNAR14, UTE ALEXY15, LUIS A.MORENO2,16, MICHAEL SJÖSTRÖM5, & HELENA STUDY GROUP*

1University of Exeter, UK, 2University of Zaragoza, Spain, 3University of Granada, Spain, 4PROFITH ‘PROmotingFITness and Health through physical activity’ research group, University of Granada, Spain, 5Department of Bioscience andNutrition, Karolinska Institutet, Sweden, 6Department of Neurobiology, Karolinska Institutet, Sweden, 7HarokopioUniversity, Greece, 8University of Crete, Crete, Greece, 9Université Lille Nord de France and CIC-9301-Inserm CHU,France, 10National Research Institute for Food and Nutrition, Italy, 11Ghent University, Belgium, 12Technical University ofMadrid, Spain, 13Private Medical University, Austria, 14University of Pécs, Hungary, 15Rheinische Friedrich-Wilhelms-Universität, Germany, and 16Universidad de Zaragoza, Spain, and *HELENA Study Group – Please see Appendix

(Accepted 26 April 2013)

AbstractThis report aims (1) to examine the association between seasonality and physical activity (PA) and sedentary time inEuropean adolescents and (2) to investigate whether this association was influenced by geographical location (Central-Northversus South of Europe), which implies more or less extreme weather and daylight hours. Valid data on PA, sedentary timeand seasonality were obtained in 2173 adolescents (1175 females; 12.5–17.5 years) included in this study. Physical activityand sedentary time were measured by accelerometers. ANCOVA was conducted to analyse the differences in PA andsedentary time across seasons. Results showed that girls had lower levels of moderate to vigorous PA (MVPA) and averagePA, and spent more time in sedentary activities in winter compared with spring (all P < 0.05). Stratified analyses showeddifferences in PA and sedentary time between winter and spring in European girls from Central-North of Europe (P < 0.05for sedentary time). There were no differences between PA and sedentary time across seasonality in boys. In conclusion,winter is related with less time spent in MVPA, lower average PA and higher time spent in sedentary activities in Europeanadolescent girls, compared with spring. These differences seem to mainly occur in Central-North Europe.

Keywords: accelerometer, active, inactive, moderate-to-vigorous physical activity, paediatric population, season

Introduction

Physical activity (PA) is associated with short andlong-term health benefits in paediatric populations,including more favourable body composition(Gracia-Marco et al., 2011), mental and socialhealth (Biddle & Asare, 2011) and prevention ofcardiovascular diseases (Ekelund et al., 2012).However, a relatively low percentage of children(Troiano et al., 2008) and fewer adolescents (Ruizet al., 2011) meet the recommended 60 minutes ofmoderate to vigorous intensity PA (MVPA) per day(US Department of Health and Human Services,2008).

The engagement in PA is associated with manyindividual, social and environmental factors (Salliset al., 2006; Van Acker et al., 2012), and the identi-fication of these factors is of great importance fordesigning effective intervention programs. Some ofthese factors have been widely studied, such asaccess to facilities, parks and lack of leisure time(Dowda, Pfeiffer, Lobelo, Porter, & Pate, 2012;Fox, Mann, Ramos, Kleinman, & Horowitz, 2012).However, natural and environmental aspects, suchas the influence of seasonality among adolescents,are less understood. Seasonal variation of PA isdefined as ‘a fluctuation in PA levels that is asso-ciated with changes in the weather and daylight

*Correspondence: Luis Gracia-Marco, University of Exeter, Sport and Health Sciences, Heavitree Road, Exeter EX1 2LU, UK. Email: L.A.Gracia-Marco@exeter.ac.uk

Journal of Sports Sciences, 2013http://dx.doi.org/10.1080/02640414.2013.803595

© 2013 Taylor & Francis

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hours that accompany different seasons’ (Carson &Spence, 2010).

Previous research in European adolescents showedthat PA levels were lower and sedentary time higherin adolescents from the South of Europe comparedwith those from Central-North of Europe (Ruiz et al.,2011). However, the association between seasonalityand PA and sedentary time in these adolescents hasnot been studied yet. To date, most of studies exam-ining the influence of seasonality on PA and timespent sedentary (both self-reported and objectivelymeasured) have mainly been conducted in singlecountries (Beighle, Alderman, Morgan, & LeMasurier, 2008; Burdette, Whitaker, & Daniels,2004; Carson, Spence, Cutumisu, Boule, &Edwards, 2010; Kristensen et al., 2008; Mattockset al., 2007; Owen et al., 2009; Riddoch et al.,2007; Rifas-Shiman et al., 2001; Rowlands, Pilgrim,& Eston, 2009; Vermorel, Vernet, Bitar, Fellmann, &Coudert, 2002; Wennlof, Yngve, Nilsson, &Sjostrom, 2005). The association of season with PAand sedentary time is likely to be country-specific,since weather differs greatly between countries, i.e.mean low temperatures in Stockholm (Sweden) inJanuary range from –6 to –7°C against +7 to +10°Cin Zaragoza (Spain). Therefore, there is a need forresearch to better understand seasonal variation inadolescents’ PA. It can contribute to public healthinterventions aimed at reducing sedentary time andincreasing PA levels, which can be targeted at specifictimes of the year, as appropriate to the geographicallocation.

In this context, the Healthy Lifestyle in Europeby Nutrition in Adolescence Cross-Sectional Study(HELENA-CSS), assessed PA and sedentary timeusing accelerometers in a large sample of Europeanadolescents from ten different European cities(nine countries), and provides an ideal opportunityto explore from an European perspective the asso-ciation of seasonality with objectively measured PAand sedentary time in adolescence. In addition, itmight be that seasonality could have a strongerrelationship with PA and sedentary time in coun-tries from Central-North of Europe compared withthose from the South of Europe, since winter con-ditions are much more extreme in the North ofEurope (e.g. Sweden, Belgium) than in the Southof Europe (e.g. Spain, Greece), and that couldpotentially result in a lower level of PA and a highertime spent sedentary.

The present study aims to test the followinghypotheses in European adolescents: (1) levels ofPA are lower and sedentary time is higher in wintercompared to spring; (2) the association between PAand sedentary time and seasonality is stronger inadolescents from Central-North of Europe than inadolescents from South of Europe.

Methods

Study design

The HELENA-CSS is a European Union-fundedproject conducted on adolescents from tenEuropean cities: Stockholm (Sweden), Athens andHeraklion (Greece), Rome (Italy), Zaragoza (Spain),Pecs (Hungary), Ghent (Belgium), Lille (France),Dortmund (Germany) and Vienna (Austria)(Moreno, Gonzalez-Gross, et al., 2008). Detaileddescriptions of the HELENA sampling and recruit-ment approaches, standardisation and harmonisationprocesses, data collection, analysis strategies, qualitycontrol activities and inclusion criteria have beendescribed in detail elsewhere (Moreno, De Henauw,et al., 2008). An extended and detailed manual ofoperations was designed for and thoroughly read byevery researcher involved in the fieldwork before thedata collection started. Parents and adolescentssigned an informed consent, the protocol wasapproved by Research Ethics Committees of eachcity involved and the study was performed followingthe ethical guidelines of the Declaration of Helsinki1964 (revision of Edinburgh 2000), Convention ofOviedo (1997), the Good Clinical Practice, and thelegislation about clinical research in humans in eachof the participating countries (Beghin et al., 2008).

Study sample

The geographical distribution of the 10 cities(>100,000 inhabitants) was not random and notrepresented by the strata, but it was decided accord-ing to the following criteria: representation of terri-torial units (countries) of Europe according togeographical location (North/South/East/West), cul-tural reference and socioeconomic situation; andselection of a territorial unit (city) in the country,which had an experienced research group to performthe study. The age range considered valid for theHELENA study was 12.5–17.5 years. All the ana-lyses conducted on the HELENA data were adjustedby a weighting factor to balance the sample accord-ing to the theoretical age distribution foreseen. Froma total sample of 3528 adolescents participating inthe HELENA study, 2914 wore the accelerometer.However, only 2173 (74.6%; 989 boys and 1175girls) met the inclusion criteria of at least 3 dayswith at least 8 h of recording time per day (afterexcluding periods of 20 min of consecutive zeros),and were therefore, included in this report.

Physical activity assessment

A uni-axial accelerometer (Actigraph GT1M,Manufacturing Technology Inc. Pensacola, FL,USA) was used to assess PA as described previously.

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Adolescents were instructed to place the monitorunderneath the clothing, at the lower back, using anelastic waistband and to wear it for seven consecutivedays. They were also instructed to wear the acceler-ometer during all times awake and only to remove itduring water-based activities, such as bathing orswimming. In this study, the time sampling interval(epoch) was set at 15 seconds (Ward, Evenson,Vaughn, Rodgers, & Troiano, 2005). The data werecollected all throughout the academic year.

The data were downloaded into a computer usingthe manufacturer’s software and were later analysedwith an ad hoc Visual Basic data reduction program.The rough data on all participants were analysedcentrally to ensure standardisation. Data with peri-ods of continuous zero values for more than 20 minwere considered ‘accelerometer non-wear’ periods(Martinez-Gomez et al., 2010) and were thereforeexcluded from the analyses. Monitor wearing timewas calculated by subtracting non-wear time fromthe total registered time for the day. Likewise, arecording of more than 20,000 counts per minutewas interpreted as a potential malfunction of theaccelerometer, and the value was excluded from theanalyses. At least 3 days of recording with a mini-mum of 8 or more hours of registration per day werenecessary for the adolescent to be included in thestudy (Ruiz et al., 2011).

Physical activity levels are shown in two ways:

1. Amount of time engaged in MVPA, based onthe standardised cut-off point of ≥2000 countsper minute (Andersen et al., 2006).

2. Average PA, expressed as mean counts perminute. Average PA is a measure of overallPA. We calculated mean counts per minuteby dividing the sum of total counts per epoch(15 seconds) for a valid day by the number ofminutes of wear time in that day across all validdays.

Sedentary time (minutes · day−1) was estimated as theamount of time accumulated below 100 counts perminute during periods of wear time (Ruiz et al., 2011).

Seasonality

A variable was computed by re-coding the originalvariable ‘date of visit’, which corresponds to the datein which accelerometers were programmed to startcounting, into ‘Seasonality’, as follows: winter (from21 December to 20 March, coded as 1), autumn(from 21 September to 20 December, coded as 2),spring (from 21 March to 20 June, coded as 3) andsummer (from 21 June to 20 September, coded as4), as was performed in previous studies (Gracia-Marco, Valtuena, et al., 2012). As the HELENA

study was performed during the academic year, fewadolescents (n = 25) were assessed in the first days ofsummer, and they were included along with thoseassessed during spring. Therefore, the final variablewas composed by three groups: winter (coded as 1),autumn (coded as 2) and spring (coded as 3)(Gracia-Marco, Valtuena, et al., 2012).

Geographical location

A variable was computed by re-coding the originalvariable ‘centre/country’ into ‘geographical location’,as follows: South of Europe (Athens and Heraklion(Greece), Rome (Italy) and Zaragoza (Spain)) andCentral-North of Europe (Stockholm (Sweden),Pecs (Hungary), Ghent (Belgium), Lille (France),Dortmund (Germany) and Vienna (Austria)).

Anthropometric measurements

Anthropometric data in the HELENA-CSS wereobtained following International guidelines (Nagyet al., 2008). Body mass (kg) and height (cm) weremeasured with an electronic scale (Type SECA 861)and a stadiometer (Type Seca 225), respectively.

Socioeconomic status

The Family Affluence Scale is based on the conceptof material conditions in the family. Currie, Elton,Todd, & Platt (1997) chose a set of items that referto family expenditure and consumption (affluence).The Family Affluence Scale is a valid socio-economicstatus index in young people and has previously beenused in large epidemiological studies (Currie et al.,2008; Gracia-Marco, Ortega, et al., 2012). The scaleis composed of four questions: Do you have your ownbedroom? (No = 0, Yes = 1); How many cars arethere in your family? (None = 0, 1 = 1,2 = 2, >2 = 3); How many computers are there inyour home? (None = 0, 1 = 1, 2 = 2, ≥3 = 3); Do youhave internet access at home? (No = 0, Yes = 1). Wecomputed a final score by summing the answers fromall the questions (ranging from 0 to 8). Finally, wegrouped these scores into three levels: low (from 0 to2), medium (from 3 to 5) and high (from 6 to 8)(Gracia-Marco, Ortega, et al., 2012).

Statistical methods

After the natural logarithm transformation ofsedentary time, time spent at MVPA and averagePA, all variables showed distributions that moreclosely approximated normal (established usingKolmogorov–Smirnov tests).

One-way analysis of variance (ANOVA) and UMann-Whitney were used to calculate the descrip-tive data shown in Table I.

The HELENA study 3

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Tab

leI.Descriptive

characteristicsof

thepa

rticipan

tsby

geog

raph

ical

location

.

Total

sample

(n=21

73)

Cen

tral-N

orth

ofEurop

e‡

(n=13

62)

Sou

thof

Europ

e‡

(n=81

1)

Boy

s(n

=99

8)Girls

(n=11

75)

Boy

s(n

=62

8)Girls

(n=73

4)Boy

s(n

=37

0)Girls

(n=44

1)

Age

(year)

15.03(1.2)

15.03(1.2)

15.1

(1.2)

15.1

(1.2)

14.8

(1.2)*

14.9

(1.2)*

Bod

ymass(kg)

61.0

(52.7–

70.0)

55.0

(49.0–

61.4)

61.0

(52.7–

70.0)

54.8

(48.9–

61.2)

60.9

(52.8–

70.2)

55.2

(49.3–

61.8)

Heigh

t(cm)

170.6(163

.8–17

7.0)

162.0(157

.5–16

6.6)

172.0(164

.8–17

7.9)

163.3(158

.7–16

7.6)

168.9(161

.5–17

4.5)*

160.0(156

.0–16

4.3)*

Fam

ilyAfflue

nceScale

(low

/med

ium/high)

(%)

(11.3/57

.7/31.7)

(14.7/55

.9/29.4)

(9.3/51.8/38

.9)

(10.4/51

.3/38.2)

(14.9/67

.4/17.7)*

(22.2/64

.0/13.2)*

Seasona

lity(w

inter/au

tumn/spring

)(%

)(41.4/29

.6/29.0)

(40.8/30

.8/28.4)

(39.2/30

.7/30.1)

(34.8/32

.0/33.2)

(45.5/27

.5/27.0)*

(51.1/28

.7/20.2)*

Phy

sicalactivity

Sed

entary

(min

·da

y−1)

537.1(480

.0–58

7.6)

548.5(502

.6–58

9.7)

528.2(472

.0–58

2.5)

539.0(489

.6–58

3.9)

547.2(497

.6–59

7.3)*

559.1(520

.6–60

0.6)*

MVPA

(min

·da

y−1)

64.3

(48.2–

81.3)

48.7

(37.0–

61.8)

64.8

(49.9–

82.4)

52.1

(41.1–

65.2)

62.0

(45.7–

79.6)*

42.2

(31.6–

55.2)*

Average

PA

(cou

ntspe

rminute)

463.9(368

.0–58

2.6)

367.5(300

.3–44

9.2)

473.2(379

.4–59

7.0)

392.6(321

.6–47

9.9)

446.0(350

.5–55

6.3)*

328.1(267

.2–40

3.2)*

Registeredtimeusingaccelerometers(m

in·day

−1)

777.9(716

.5–82

4.5)

763.4(709

.0–81

6.6)

769.6(708

.3–82

6.6)

758.9(705

.2–81

4.4)

788.9(731

.6–82

9.1)*

770.1(714

.0–82

2.4)

ANOVA

was

performed

forno

rmally

distribu

tedvariab

les(m

ean(SD))

andU

Man

nW

hitney

forno

n-no

rmally

distribu

tedvariab

les(m

edian(interqu

artile

intervals)).

Percentages

werecalculated

forcatego

ricalvariab

les.

‡Cen

tral-N

orth

ofEurop

e:Stockho

lm(Swed

en),Pecs(H

ungary),Ghe

nt(B

elgium

),Lille(F

ranc

e),Dortm

und(G

erman

y)an

dVienn

a(A

ustria);Sou

thof

Europ

e:Athen

san

dHeraklio

n(G

reece),

Rom

e(Italy)an

dZaragoza(Spa

in).

*P<0.05

betw

eenbo

ys(C

entral-N

orth

vs.Sou

thof

Europ

e)or

girls(C

entral-N

orth

vs.Sou

thof

Europ

e).

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In order to analyse the differences in PA andsedentary time across seasonality, one-way analysisof covariance (ANCOVA) was conducted, whereseasonality was entered as the fixed factor and PAand sedentary time were entered as dependent vari-ables, respectively. Age, Family Affluence Scale andregistered time of PA (except for the average PA, asthis variable was calculated using the time of regis-tration) were included as covariates. In addition, thecategorical variable ‘centre’ was entered in the modelas a random factor in the analyses for the wholesample, not when stratifying by centre (i.e. Southversus Central-North of Europe).

All the analyses were performed using theStatistical Package for Social Sciences software(SPSS, v. 19.0 for WINDOWS; SPSS Inc.,Chicago, IL, USA), and values of P < 0.05 wereconsidered statistically significant.

Results

Table I shows descriptive characteristics of the sam-ple by gender and geographical location. Boys andgirls from Central-North of Europe were older andtaller; they also had higher levels of MVPA andaverage PA, and lower sedentary time than theircounterparts from South of Europe, as previouslyreported (Ruiz et al., 2011). In addition, boys andgirls from Central-North of Europe had a higher

Family Affluence Scale and most of them were mea-sured during autumn or spring.

Table II shows estimated means of MVPA, aver-age PA and sedentary time across seasonality bygender and geographical location in European ado-lescents. Girls showed lower levels of MVPA(P = 0.014) and average PA (P = 0.007) and higherlevels in sedentary activities in winter compared withspring (P = 0.005). When the analyses were stratifiedby geographical location, the same differences (i.e.less MVPA, less average PA and more sedentarytime in winter) were observed in girls from Central-North of Europe, but not in their peers from Southof Europe, yet these differences were significant(P = 0.032) only for sedentary time. There were nodifferences on PA and sedentary time across season-ality in boys.

Discussion

The main findings of this study indicated that (1)European adolescent girls had lower levels of MVPAand average PA, and were more sedentary duringwinter compared with spring; and (2) girls fromCentral-North of Europe were more sedentaryduring winter compared with spring; while no asso-ciation between season and PA and sedentary timewas observed in boys and girls from the South ofEurope.

Table II. Physical activity and sedentary time estimated means across seasonality by gender and geographical location in Europeanadolescents.

Total sample** (n = 2173)Central-North of Europe‡

(n = 1362) South of Europe‡ (n = 811)

Dependent variable

Boys(n = 998)

Girls(n = 1175)

Boys(n = 628)

Girls(n = 734)

Boys(n = 370)

Girls(n = 441)

Mean SE Mean SE Mean SE Mean SE Mean SE Mean SE

Sedentary (min · day−1)*Winter 537.2 2.8 552.4 a 1.9 533.3 3.6 547.7 a 2.4 542.9 4.1 558.4 2.8Autumn 537.1 2.8 546.6 2.1 529.5 3.5 539.7 2.7 552.6 4.5 557.3 3.2Spring 533.7 3.1 543.4 2.2 531.1 3.9 537.8 2.6 537.1 5.3 558 4.1

MVPA (min · day−1)*Winter 65.4 1.3 49.4 a 0.9 67.0 1.7 53.1 1.2 63 2 44.8 1.3Autumn 66.5 1.3 51.8 1 68.2 1.6 56.6 1.3 62.9 2.2 44.3 1.5Spring 68.8 1.5 53.3 1.1 69.0 1.8 55.4 1.2 69 2.5 47.5 1.9

Average PA (counts per min)†

Winter 483.4 8.7 375.5 a 5.8 500.2 11.4 399.1 7.8 458.7 13.2 344.4 8Autumn 484.9 8.8 392.2 6.6 501.1 11.1 423.9 8.6 452.7 14.5 342.4 9.3Spring 504.7 9.7 413 6.9 508.0 12.1 419.9 8.2 503.3 16.2 360.9 11.8

Results are showed as mean ± standard error (SE).*Results are adjusted for age, Family Affluence Scale and the time registered by accelerometers (minutes).†Results are adjusted for age and Family Affluence Scale.**Results for the whole study sample were additionally adjusted for centre.‡Central-North of Europe: Stockholm (Sweden), Pecs (Hungary), Ghent (Belgium), Lille (France), Dortmund (Germany) and Vienna(Austria); South of Europe: Athens and Heraklion (Greece), Rome (Italy) and Zaragoza (Spain).a; P < 0.05 between winter-spring.P values were obtained using log-transformed data, yet raw means are presented to be more meaningful.

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Our hypotheses were partially confirmed. Wefound a stronger relationship between seasonalityand PA and sedentary time in Central-North ofEurope, which could be explained by their moreextreme winter conditions (i.e. colder and darker)that might have a higher impact on activity/sedentarybehaviours; but this was only significant for seden-tary time in girls. Adolescence is a period charac-terised by a decrease in PA and sport participation(Gracia-Marco et al., 2010; Troiano, et al., 2008),and it is clear that boys are more active than girls(Ruiz et al., 2011). The effect that seasonality mayhave on PA can be mainly related to exercise out-doors. Recent literature has shown that boys (15 to18 years) are more likely to exercise outdoors thangirls (Dunton et al., 2010). In this regard, boys mayengage in more PA outdoors because they perceivemore opportunities for activity when they are out-doors, they have more access to outdoor exerciseenvironments (because of parental safety concernsfor girls) and/or prefer to exercise outdoors (whereasgirls could prefer home-based exercise) (Dunton,et al., 2010). Therefore, our significant associationbetween seasonality and PA in girls from theCentral-North of Europe might be related to thisfactor, which is a key point in Central-NorthEuropean countries due to the wider contrast oftemperature and the climatological conditions ofthese countries in the winter compared with spring,in comparison with the differences in these para-meters in countries from the South of Europe. Inspite of this, adolescents from Central-North Europeare even more active and less sedentary than theirpeers from the South of Europe, as previously shownin the HELENA-CSS (Ruiz et al., 2011).

To our knowledge, there is a lack of studies thathave considered the influence of gender on seasonalvariation of PA (Owen et al., 2009; Rowlands et al.,2009). Rowlands et al. (2009) in their study with 64UK children (9–11 years) found higher levels of PA(total, moderate and vigorous) during the summerthan winter in both genders. Owen et al. (2009)showed in 144 children (11 years) that the averagePA (counts per minute) was higher in the summerthan winter (adjusting per month) but did not varyby gender. Our results are difficult to compare withthese for many reasons: these studies were per-formed only in the UK, sample sizes were smalland some covariates were not used (i.e. age).

Several studies conducted in European countriesfound seasonal variation in children and adolescents’PA with higher levels during spring/summer com-pared with autumn/winter (Kristensen et al., 2008;Mattocks et al., 2007; Riddoch et al., 2007;Rowlands et al., 2009; Vermorel et al., 2002;Wennlof et al., 2005). For example, Riddoch et al.(2007) in their study with 5595 children (11 years)

showed that the average PA (counts per minute) andMVPA was higher in summer than in winter. Inaddition, Wennlof et al. (2005) showed thatSwedish children (9 and 15 years) measured onceonly in spring, autumn and winter, were most activeduring spring compared with autumn and/or winter.Similarly, PA was highest in the spring/summer andlowest in the autumn/winter in North America(Beighle, et al., 2008; Burdette, et al., 2004;Carson, et al., 2010; Rifas-Shiman, et al., 2001). Incontrast, some studies did not report significant sea-sonal differences in PA levels (Bringolf-Isler et al.,2009; Burdette, et al., 2004; Finn, Johannsen, &Specker, 2002; Nilsson et al., 2009; Ridgers,Stratton, Clark, Fairclough, & Richardson, 2006;Smith, Rhodes, Naylor, & McKay, 2008). To thebest of our knowledge, no studies have been con-ducted in more than one country that analyse theassociation between PA-related variables and season-ality, and therefore, our results are not comparable atthis scale.

Two recent reviews have been published in rela-tion to the effect of seasonal variation in PA inchildren and adolescents (Carson & Spence, 2010;Rich, Griffiths, & Dezateux, 2012). Carson andSpence (2010) highlighted some key factors to con-sider in this topic, such as the region where theparticipants reside, their age, the method of mea-surement of PA and the design of the study, showingthat the latter factor did not seem to impact theresults of seasonal variation. In addition, Rich et al.(2012) highlighted that future studies need to uselarge samples, present count data, minutes of MVPAand also to consider the gender as a potential deter-minant of seasonal patterns in PA. All previous fac-tors, together with a valid index of socioeconomicstatus (such as the Family Affluence Scale), whichhas been shown to be associated with the engage-ment in extracurricular sports in adolescents(Gracia-Marco et al., 2010), have been consideredin the present study.

Currently, it seems there are equivocal results ofseasonal differences in PA levels, which are affectedby the region, the sample size, method for PA mea-surement (objective versus subjective), gender andthe use of confounders. Our study provides a morecomprehensive overview of the seasonal influence onPA levels (MVPA and average PA) and sedentarytime in European adolescent boys and girls fromnine different countries, considering two regions(Central-North and South of Europe). It is impor-tant to understand which factors affect PA participa-tion in children and adolescents as their levels havebeen associated with many health outcomes, e.g.cardiovascular effects (Andersen et al., 2006). Thefindings of the present study will help to betterdesign interventions for the promotion of PA in

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Europe based on seasonality and place of residence,in order to provide different opportunities and pro-grammes at different times of the year, whichaccording to data in the study is especially importantfor girls.

Limitations and strengths

The main limitation of this study is that PA was notmeasured in the same adolescents throughout thedifferent seasons, i.e. the present study is a cross-sectional study instead of longitudinal. In spite ofthis limitation, recent reviews have shown that bothcross-sectional and longitudinal studies have pro-vided consistent findings regarding seasonality andPA levels (Carson & Spence, 2010; Rich et al.,2012). In addition, we cannot know the extent towhich weather conditions such as rainfall influencePA participation during specific times of the year(Chan & Ryan, 2009). The large sample size, theobjective measurement of PA and sedentary timeand the European dimension of the HELENAstudy are further strengths of this study.

Conclusion

Our results suggest that winter, compared with spring,is related to less time being spent in MVPA, loweraverage PA and more time spent in sedentary activitiesfor European adolescent girls. These differences seemto mainly occur in Central-North Europe rather thanin the South of Europe. Our data however did notshow any association between seasonality and PA inadolescent boys. These findings should be consideredwhen designing interventions for the promotion of PAin Europe, especially for girls.

Conflict of interest

None declared.

Acknowledgements

The HELENA-CSS takes place with the financial sup-port of the European Community Sixth RTDFramework Program (Contract FOOD-CT-2005-007034). This study was also supported by grantsfrom the Spanish Ministry of Economy andCompetitiveness: RYC-2010-05957, RYC-2011-09011.We gratefully acknowledge all participating ado-lescents and their parents for their collaboration. All theauthors have substantially contributed to this work.

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Appendix

Helena Study Group

Co-ordinator: Luis A. Moreno

Core Group members: Luis A. Moreno, FrédericGottrand, Stefaan De Henauw, Marcela González-Gross, Chantal Gilbert.

Steering Committee: Anthony Kafatos(President), Luis A. Moreno, Christian Libersa,Stefaan De Henauw, Jackie Sáchez, FrédericGottrand, Mathilde Kesting, Michael Sjostrom,Dénes Molnár, Marcela González-Gross, JeanDallongeville, Chantal Gilbert, Gunnar Hall, LeaMaes, Luca Scalfi.

Project Manager: Pilar Meléndez

1. Universidad de Zaragoza (Spain): Luis A.Moreno, Jesús Fleta, José A. Casajús,Gerardo Rodríguez, Concepción Tomás,María I. Mesana, Germán Vicente-Rodríguez, Adoración Villarroya, Carlos M.Gil, Ignacio Ara, Juan Revenga, CarmenLachen, Juan Fernández Alvira, GloriaBueno, Aurora Lázaro, Olga Bueno, Juan F.León, Jesús Mª Garagorri, Manuel Bueno,Juan Pablo Rey López, Iris Iglesia, PaulaVelasco, Silvia Bel, Luis Gracia-Marco,Theodora Mouratidou.

2. Consejo Superior de InvestigacionesCientíficas (Spain): Ascensión Marcos,Julia Wärnberg, Esther Nova, Sonia Gómez,Esperanza Ligia Díaz, Javier Romeo, AnaVeses, Mari Angeles Puertollano, BelénZapatera, Tamara Pozo.

3. Université de Lille 2 (France): LaurentBeghin, Christian Libersa, Frédéric Gottrand,Catalina Iliescu, Juliana Von Berlepsch.

4. Research Institute of Child NutritionDortmund, Rheinische Friedrich-Wilhelms-Universität Bonn (Germany):Mathilde Kersting, Wolfgang Sichert-Hellert,Ellen Koeppen.

5. Pécsi Tudományegyetem (University ofPécs) (Hungary): Dénes Molnar, EvaErhardt, Katalin Csernus, Katalin Török,Szilvia Bokor, Mrs Angster, Enikö Nagy,Orsolya Kovács, Judit Repásy.

6. University of Crete School of Medicine(Greece): Anthony Kafatos, CarolineCodrington, María Plada, Angeliki Papadaki,Katerina Sarri, Anna Viskadourou, ChristosHatzis, Michael Kiriakakis, George Tsibinos,Constantine Vardavas Manolis Sbokos, EvaProtoyeraki, Maria Fasoulaki.

7. Institut für Ernährungs- und Lebens-mittelwissenschaften –Ernährungphy-siologie. Rheinische Friedrich WilhelmsUniversität (Germany): Peter Stehle,Klaus Pietrzik, Marcela González-Gross,Christina Breidenassel, Andre Spinneker,Jasmin Al-Tahan, Miriam Segoviano, AnkeBerchtold, Christine Bierschbach, ErikaBlatzheim, Adelheid Schuch, Petra Pickert.

8. University of Granada (Spain): Manuel J.Castillo, Ángel Gutiérrez, Francisco B.Ortega, Jonatan R Ruiz, Enrique G. Artero,Vanesa España-Romero, David Jiménez-Pavón, Palma Chillón.

9. Istituto Nazionale di Ricerca per gliAlimenti e la Nutrizione (Italy): DavideArcella, Elena Azzini, Emma Barrison,Noemi Bevilacqua, Pasquale Buonocore,Giovina Catasta, Laura Censi, DonatellaCiarapica, Paola D’Acapito, Marika Ferrari,Myriam Galfo, Cinzia Le Donne, CatherineLeclercq, Giuseppe Maiani, Beatrice Mauro,Lorenza Mistura, Antonella Pasquali, RaffaelaPiccinelli, Angela Polito, Raffaella Spada,Stefania Sette, Maria Zaccaria.

10. University of Napoli “Federico II” Deptof Food Science (Italy): Luca Scalfi, PaolaVitaglione, Concetta Montagnese.

11. Ghent University (Belgium): Ilse DeBourdeaudhuij, Stefaan De Henauw, TinekeDe Vriendt, Lea Maes, Christophe Matthys,Carine Vereecken, Mieke de Maeyer,Charlene Ottevaere, Inge Huybrechts.

12. Medical University of Vienna (Austria):Kurt Widhalm, Katharina Phillipp, SabineDietrich.

13. Harokopio University (Greece): YannisManios, Eva Grammatikaki, Zoi Bouloubasi,Tina Louisa Cook, Sofia Eleutheriou, OrsaliaConsta, George Moschonis, Ioanna Katsaroli,George Kraniou, Stalo Papoutsou, DespoinaKeke, Ioanna Petraki, Elena Bellou, SofiaTanagra, Kostalenia Kallianoti, DionysiaArgyropoulou, Katerina Kondaki,Stamatoula Tsikrika, Christos Karaiskos.

14. Institut Pasteur de Lille (France): JeanDallongeville, Aline Meirhaeghe.

15. Karolinska Institutet (Sweden): MichaelSjöstrom, Patrick Bergman, MaríaHagströmer, Lena Hallström, MårtenHallberg, Eric Poortvliet, Julia Wärnberg,Nico Rizzo, Linda Beckman, Anita HurtigWennlöf, Emma Patterson, Lydia Kwak,Lars Cernerud, Per Tillgren, StefaanSörensen.

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16. Asociación de Investigación de laIndustria Agroalimentaria (Spain): JackieSánchez-Molero, Elena Picó, Maite Navarro,Blanca Viadel, José Enrique Carreres, GemaMerino, Rosa Sanjuán, María Lorente, MaríaJosé Sánchez, Sara Castelló.

17. Campden & Chorleywood Food ResearchAssociation (United Kingdom): ChantalGilbert, Sarah Thomas, Elaine Allchurch,Peter Burguess.

18. SIK - Institutet foer Livsmedel ochBioteknik (Sweden): Gunnar Hall,Annika Astrom, Anna Sverkén, AgnetaBroberg.

19. Meurice Recherche & Development asbl(Belgium): Annick Masson, Claire Lehoux,Pascal Brabant, Philippe Pate, LaurenceFontaine.

20. Campden & Chorleywood FoodDevelopment Institute (Hungary):Andras Sebok, Tunde Kuti, Adrienn Hegyi.

21. Productos Aditivos SA (Spain): CristinaMaldonado, Ana Llorente.

22. Cárnicas Serrano SL (Spain): EmilioGarcía.

23. Cederroth International AB (Sweden):Holger von Fircks, Marianne Lilja Hallberg,Maria Messerer.

24. Lantmännen Food R&D (Sweden): MatsLarsson, Helena Fredriksson, ViolaAdamsson, Ingmar Börjesson.

25. European Food Information Council(Belgium): Laura Fernández, Laura Smillie,Josephine Wills.

26. Universidad Politécnica de Madrid(Spain): Marcela González-Gross, JaraValtueña, David Jiménez-Pavón, UlrikeAlbers, Raquel Pedrero, Agustín Meléndez,Pedro J. Benito, Juan José Gómez Lorente,David Cañada, Alejandro Urzanqui, JuanCarlos Ortiz, Francisco Fuentes, Rosa MaríaTorres, Paloma Navarro.

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