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Adolescent’s physical activity levels and relatives’ physical activity engagement and encouragement: the HELENA study

Miguel Martín-Matillas, Francisco B. Ortega, Jonatan R. Ruiz, David Martínez-Gómez, Ascensión Marcos, Diego Moliner-Urdiales, Angela Polito, Raquel Pedrero-Chamizo, Laurent Béghin, Dénes Molnár, Anthony Kafatos, Luis A. Moreno, Ilse De Bourdeaudhuij, Michael Sjöström
DOI: http://dx.doi.org/10.1093/eurpub/ckq143 705-712 First published online: 8 October 2010

Abstract

Background: The aim of this article is to examine the association between adolescents’ physical activity (PA) levels and their relatives’ (father, mother, brothers, sisters and best friend) PA engagement and encouragement. Methods: Adolescents (52.3% girls) aged 12.5–17.5 years were gathered from the HELENA study. Adolescents’ PA levels were assessed by the International Physical Activity Questionnaire for Adolescents (valid data on 3007 participants) and accelerometry (valid data on 2200 participants). Relatives’ engagement and encouragement were reported by the adolescents and encoded into three categories (low, middle and high). Results: Analysis of covariance showed that relatives’ PA encouragement was more strongly associated with adolescents’ PA levels than relatives’ PA engagement. Pairwise comparisons indicated that the higher the encouragement level (from most relatives) the higher the adolescent’s PA levels. This finding was overall consistent when using self-report or objective methods for assessing adolescents’ PA levels, yet the associations were stronger when using self-report methods. Conclusions: These findings highlight the important role of social encouragement on adolescents’ PA levels. Community interventions aiming to enhance PA levels in the adolescent population might be more successful when family and peers are also targeted.

  • physical activity
  • adolescence
  • social support
  • lifestyle

Introduction

A physically active lifestyle during adolescence contributes to a healthier status and better physical and psychological well-being during these years and also later in life.1-3 A recent systematic review on trends in physical activity (PA) reported a decline in PA levels in young people over time.4 In order to attenuate, stop or invert this decline in PA it is important to identify those factors that determine PA levels in young people and take them into account in future interventions and health promotion strategies.1,5

Recent findings about psychological, physical and lifestyle factors, e.g. happiness, obesity and smoking, suggest that what surrounding people feel or do may largely influence an individual’s status.6-8 For instance, people who are surrounded by a happy social network are more likely to be happy.8 Therefore, it is reasonable to think that a physically active social environment can positively influence adolescents’ PA levels.9

Several studies examined the association of parents’ PA,10 peers’ PA5 or both11,12 with adolescents’ PA. Little is known, however, about how brothers’ and sisters’ PA influence adolescents’ PA levels. Few studies have examined the effect of all the relatives in a single study. Such study would allow determining which relative is more influential.

Not only what relatives do (engagement) but also the level of relatives’ PA encouragement might influence adolescents’ PA levels.13-17 Overall, these studies showed a positive association of both relatives’ PA engagement and encouragement with adolescents’ PA. However, the available literature is mainly based on data from North America and Australia, with limited information on this topic in European adolescents.

The aim of this study was to examine the influence of the relatives’ (father, mother, brother, sister and best friend) PA engagement and encouragement on European adolescents’ PA levels, assessed by subjective (questionnaire) and objective (accelerometry) methods.

Methods

Design and participants

Adolescents were part of the Healthy Lifestyle in Europe by Nutrition in Adolescence Cross Sectional Study (HELENA-CSS), which is a multicenter study conducted between 2006 and 2007, in 10 cities from 9 European countries: Athens (Greece), Dortmund (Germany), Ghent (Belgium), Heraklion (Greece), Lille (France), Pécs (Hungary), Rome (Italy), Stockholm (Sweden), Vienna (Austria) and Zaragoza (Spain). The main aim of the HELENA study was to obtain reliable and comparable data on nutrition and health-related parameters such as PA, fitness, body composition, food choices and preferences, cardiovascular risk factors, vitamins and mineral status, immunological biomarkers and genetic markers.18

This study included a total of 3528 adolescents (52.3% girls) aged 12.5–17.5 years, recruited at high schools and who met the inclusion criteria established in the HELENA study.18 From these, 3007 (52.6% girls) had complete and valid data on self-reported PA assessed by IPAQ, and 2200 adolescents (53.8% girls) had complete and valid data on objectively assessed PA by accelerometry. The number of valid data for relative’s PA engagement and encouragement differs by the relative studied (some adolescents do not have a brother, father, etc.) (see the Supplementary material figure S1).

Adolescents and their parents/guardians were informed of the characteristics of the HELENA study and all provided a written informed consent. Ethics committees from each country approved the HELENA study protocol19 and regulatory aspects relating to good clinical practices were conducted in concordance with the ethical guidelines of the Declaration of Helsinki 1961, as revised in Edinburgh 2000.

Measurements

Assessment of physical activity by the International Physical Activity Questionnaire for Adolescents (IPAQ-A)

The IPAQ-A (International Physical Activity Questionnaire for Adolescents), an adapted version of the original IPAQ, was used to assess adolescent’s PA of the last 7 days.20 Questions about PA at work were replaced by questions about PA at school (e.g. physical education, walking, moderate and vigorous PA at school). Furthermore, the module about activities in the household domain was shortened. Only one question (versus three in the original IPAQ) about PA in the garden or at home remained. Also the order of PA intensities was changed, to avoid over–reporting.21 The questionnaire was translated into French, Dutch, German, Greek, Hungarian, Italian, Spanish and Swedish and back-translated into English following the instructions given in the IPAQ manual (http://www.ipaq.ki.se/ipaq.htm).22

For each of the four domains (school, transport, housework and leisure time), total PA, moderate, vigorous and moderate to vigorous physical activity (MVPA) (expressed as minutes per week) were computed and summed to be used in the analyses, based on the guidelines for data processing and analyses of the IPAQ. The data were cleaned and truncated based on previous research.20

Assessment of physical activity by accelerometry

The Actigraph accelerometer model GT1M (Actigraph MTI, Manufacturing Technology Inc., Pensacola, FL, USA) was used to assess PA. This small uniaxial accelerometer measures accelerations (G) from 0.05 to 2.1 G in the vertical axis. Its acceleration is filtered, which discriminates human movements from vibrations. The accelerometers were initialized as described by the manufacturer. The data are stored at a sampling rate of 10 samples per second and summed over a selected time interval or epoch. For the present study, data was saved in 15 s intervals (epochs). Each adolescent was monitored for seven consecutive days. The adolescents wore the accelerometers on the lower back, secured with an elastic belt, underneath clothing and only during the waking hours.

After the testing period, the accelerometers were collected by the researcher and data were uploaded onto a computer. The rough data of all participants were analyzed centrally to ensure standardization. Data with periods of zero values during more than 20 min were excluded from the analysis. A recording of more than 20 000 counts per minute was seen as a potential malfunction of the accelerometer and was also excluded from the analyses. Data were considered as valid if the adolescents had accelerometer counts for at least 3 days with at least 8 h of recording time per day. Data were analyzed for minutes per day spent in moderate and vigorous intensity. The time engaged at moderate PA (3–6 metabolic equivalents) was calculated based on cutoff points of 2000–3999 counts min−1. The time spent in vigorous PA (>6 metabolic equivalents) was calculated based on a cut off of ≥4000 counts min−1. Those cutoff points are similar to those used in previous studies.23,24 The time engaged in at least moderate PA (MVPA, ≥2000 counts min−1) was also calculated. Moderate, vigorous and MVPA were expressed in minutes per day. Total PA was computed as the total sum of counts per day divided by the total time registered and is expressed as counts min−1.

Assessment of relatives’ PA engagement and encouragement

The adolescents were asked about the PA levels undertaken by their relatives (father, mother, brothers, sisters and best friend) using the following question: ‘How regularly does your father engage in physical activity?’.25 The corresponding question was used for each of the studied relatives. The PA engagement of the relatives was classified as Low if the answer to the question was ‘never’ or ‘few times per month/year’, Middle if ‘once a week’ or ‘few times per week’ and High if ‘almost daily’. Likewise, adolescents were asked about the PA encouragement provided by their relatives, using the following question: How often does your father encourage you to be physically active? The corresponding question was used for each relative studied. Answers were classified into Low if the answer to the question was ‘Not at all’ or ‘not much’, Middle if ‘Sometimes’ or ‘Often’ and High if ‘Very often’.

Statistical analysis

All statistical analyses were performed using PASW (Predictive Analytics SoftWare, formerly SPSS), version 18.0, SPSS Inc., Chicago, IL, USA. The level of significance was set at P < 0.05 for all the analyses. Descriptive data on the study sample are presented as means and standard errors, unless otherwise indicated. After square root transformation of vigorous PA (accelerometry), vigorous PA and MVPA (both from IPAQ-A) and logarithmic transformation for total PA (accelerometry), all the residuals showed a satisfactory pattern. Differences between adolescent’s PA level according to relatives’ PA engagement and encouragement were analyzed by one-way analysis of covariance (ANCOVA), with adolescents’ PA variables (each in a separate model) as dependent variables, relatives’ PA engagement or encouragement as fixed factor, sex and age as covariates and center as a random factor. Pairwise comparisons were performed using Bonferroni’s adjustment. Prior to the analysis, possible sex and age interactions were tested with the study associations and found no clear evidence of interaction. In addition, the analyses were run separately for boys and girls, and no substantial differences were observed. Consequently, all results were presented for boys and girls together and the models were adjusted for sex and age.

The potential effect of missing values was tested on the current analyses. Adolescents with valid data on IPAQ-A were 0.29 years older, 1.48 kg lighter and had 1.04 kg m−2 lower BMI than adolescents without valid data on IPAQ-A. No differences were observed by the sex or sexual maturation group. Likewise, adolescents with valid data on accelerometry were 0.17 years younger, 2.64 kg lighter and had 0.76 kg m−2 lower BMI than adolescents without valid data on accelerometry (P < 0.05). The percentage of valid data on accelerometry was slightly higher in girls than in boys (64 vs. 60%, respectively).

Results

Characteristics of the study sample are shown in table S1 (see the Supplementary material). Descriptive data (percentages) on relatives’ PA engagement and encouragement as reported by the adolescents are shown in Supplementary material figure S1. The lowest relatives’ PA engagements were observed in father, mother and sisters, and the highest in brothers and the best friend. Father and mother provided the highest relatives’ PA encouragement, while brothers, sisters and the best friend showed the lowest scores.

Associations between relatives’ PA engagement and adolescents’ PA

Adolescents’ PA levels, measured by IPAQ-A (subjective method), according to relatives’ PA engagement, after controlling for sex, age and center, are shown in table 1. Overall, we observed a dose–response association for all the relatives. Pairwise comparisons mostly showed significant differences among groups, adolescents’ PA level being higher as the relatives’ PA engagement increased. Stronger associations were observed in brothers, sisters and the best friend, compared to parents. The same analyses but using accelerometry (objective method) are shown in table 2. Few significant differences and inconsistent patterns were observed.

View this table:
Table 1

Adolescents’ PA levels, measured by the IPAQ-A, according to relatives’ PA levels, controlled by sex, age and centre

LowMiddleHighOverall P
Fathern = 889n = 1182n = 499
    Moderate465.8(14.6)a477.6(18.1)542.6(21.5)a0.014
    Vigorousd219.7(11.0)232.2(13.7)252.8(16.2)0.146
    MVPAd685.6(21.5)a709.6(26.8)795.0(31.7)a0.037
    Total PA1115.2(28.9)a1120.2(36.0)1251.5(42.6)a0.031
Mothern = 957n = 1283n = 464
    Moderate471.9(14.5)481.3(16.0)523.0(21.8)0.093
    Vigorousd211.6(10.8)a248.2(11.9)a246.1(16.1)0.021
    MVPAd683.1(21.2)729.2(23.5)769.1(31.9)0.050
    Total PA1120.8(28.6)1138.3(31.6)1236.5(43.0)0.131
Brothersn = 235n = 864n = 489
    Moderate429.4(30.8)a489.1(16.4)b574.6(21.9)a,b0.001
    Vigorousd194.7(23.3)a224.2(12.4)b305.3(16.5)a,b<0.001
    MVPAd624.1(45.2)a713.3(24.1)b879.5(32.1)a,b<0.001
    Total PA1046.4(60.5)a1161.0(32.2)b1374.3(43.0)a,b<0.001
Sistersn = 317n = 891n = 281
    Moderate419.3(24.9)a,b493.4(17.6)a,c596.1(31.3)b,c0.002
    Vigorousd192.4(18.5)a221.6(13.1)b298.8(23.2)a,b0.003
    MVPAd611.7(37.1)a,b715.0(26.2)a,c894.9(46.6)b,c0.001
    Total PA986.7(49.6)a,b1157.1(35.1)a1313.0(62.3)b0.001
Best friendn = 321n = 1626n = 663
    Moderate428.4(25.3)a477.0(13.9)b576.9(20.3)a,b<0.001
    Vigorousd181.7(18.7)a,b213.0(10.3)a,c307.6(15.0)b,c<0.001
    MVPAd610.0(37.0)a,b690.0(20.4)a,c883.6(29.7)b,c<0.001
    Total PA1066.0(50.1)a1117.2(27.6)b1322.0(40.2)a,b<0.001
  • Data are means (standard errors). MVPA, moderate to vigorous physical activity. All PA variables are expressed as minutes per week. Low was considered when the answer to the question was ‘never’ or ‘few times per month/year’, Middle if ‘once a week’ or ‘few times per week’, and High if ‘(almost) daily’

  • a, b, c Common superscripts in a same row indicate a pairwise significant difference (P < 0.05). Pairwise comparisons were performed by using Bonferroni’s adjustment

  • d Row data are shown, yet square root transformed data were used in the analyses

View this table:
Table 2

Adolescents’ PA levels, measured by accelerometry, according to relatives’ PA levels, controlled by sex, age and centre

LowMiddleHighOverall P
Fathern = 673n =849n =341
    Moderate40.0(0.6)38.5(0.6)39.6(0.9)0.224
    Vigorousa18.6(0.5)18.1(0.5)19.3(0.8)0.645
    MVPA58.7(0.9)56.7(0.9)58.9(1.4)0.294
    Total PAa436.2(6.0)428.9(6.1)446.2(9.3)0.385
Mothern =718n =901n =329
    Moderate38.4(0.6)40.1(0.6)38.4(0.9)0.116
    Vigorousa17.9(0.5)b19.4(0.5)b17.1(0.8)0.021
    MVPA56.3(0.9)b59.5(0.9)b55.5(1.4)0.023
    Total PAa424.9(5.9)b444.5(5.7)b427.1(9.3)0.015
Brothersn =153n =615n =366
    Moderate39.3(1.2)39.5(0.6)40.6(0.9)0.619
    Vigorousa19.1(1.1)18.9(0.6)19.3(0.9)0.793
    MVPA58.4(1.8)58.4(1.0)59.9(1.5)0.732
    Total PAa436.6(11.7)433.9(6.2)454.1(9.5)0.187
Sistersn =225n =666n =231
    Moderate39.6(1.0)39.2(0.6)38.3(1.2)0.644
    Vigorousa17.4(0.9)18.5(0.5)18.3(1.1)0.238
    MVPA57.0(1.6)57.7(0.9)56.6(1.8)0.818
    Total PAa431.0(10.4)433.0(5.9)439.0(11.9)0.725
Best friendn =218n =1214n =473
    Moderate38.6(1.1)39.0(0.5)40.1(1.0)0.585
    Vigorousa16.7(1.0)18.2(0.4)19.9(0.9)0.080
    MVPA55.3(1.8)57.2(0.7)60.0(1.6)0.240
    Total PAa419.2(11.8)429.2(4.6)456.7(10.1)0.073
  • Data are means (standard errors). MVPA, moderate to vigorous physical activity. All PA variables are expressed as minutes per day, except for total PA that is counts per minute. Low was considered when the answer to the question was ‘never’ or ‘few times per month/year’, Middle if ‘once a week’ or ‘few times per week’, and High if ‘(almost) daily’

  • a Row data are shown, yet square root (Vigorous) and logarithmic (Total PA) transformed data were used in the analyses

  • b Common superscripts in a same row indicate a pairwise significant difference (P < 0.05). Pairwise comparisons were performed by using Bonferroni’s adjustment

Associations between relatives’ PA encouragement and adolescents’ PA

Adolescents’ PA levels, measured by IPAQ-A, according to relatives’ PA encouragement, after controlling for sex, age and centre, are shown in table 3. Dose–response associations were observed between relatives’ PA encouragement (all the variables) and adolescent’s PA. Pairwise comparisons mostly showed significant differences among groups, adolescent’s PA level being higher as the relative’s PA encouragement increase. Overall, the use of accelerometry instead of IPAQ-A (table 4) provided consistent results, showing significant association of fathers’, sisters’ and the best friends’ PA encouragement with adolescents’ PA, yet no associations or not consistent associations were found for brothers’ and mothers’ PA encouragement. In general, the level of significance in the associations when using accelerometry was smaller than when using IPAQ-A. Overall, stronger and more consistent (between methods) associations were observed for encouragement than for engagement.

View this table:
Table 3

Adolescents’ PA levels, measured by the IPAQ-A, according to relatives’ encouragement levels, controlled by sex, age and centre

LowMiddleHighOverall P
Fathern = 669n = 1340n = 581
    Moderate481.8(19.7)a474.5(12.1)b561.6(22.6)a,b0.004
    Vigorousd217.4(14.8)a224.9(9.1)b285.3(17.0)a,b0.001
    MVPAd699.1(29.0)a699.0(17.9)b846.9(33.4)a,b<0.001
    Total PA1127.3(39.1)a1128.7(24.1)b1302.0(44.9)a,b0.002
Mothern = 586n = 1557n = 594
    Moderate464.6(20.4)a481.3(11.7)b541.1(20.2)a,b0.053
    Vigorousd220.0(15.3)a219.7(8.8)b285.7(15.2)a,b0.001
    MVPAd684.6(30.0)a700.8(17.2)b826.0(29.7)a,b<0.001
    Total PA1107.5(40.5)a1126.7(23.2)b1293.0(40.1)a,b0.001
Brothersn = 834n = 516n = 190
    Moderate460.4(16.9)a521.2(20.6)600.2(33.0)a<0.001
    Vigorousd205.9(12.5)a,b279.2(15.3)a281.1(24.5)b0.002
    MVPAd666.1(24.5)a,b800.4(30.0)a881.3(48.1)b<0.001
    Total PA1108.3(33.1)a,b1281.9(40.5)a1349.5(65.0)b0.001
Sistersn = 835n = 474n = 154
    Moderate453.9(15.9)a,b554.5(31.1)a602.4(34.8)b0.001
    Vigorousd208.2(11.9)a274.0(23.1)305.7(25.9)a<0.001
    MVPAd662.1(23.6)a,b828.4(46.0)a908.1(51.5)b<0.001
    Total PA1084.7(31.5)a1231.1(61.4)1391.3(68.9)a<0.001
Best friendn = 1227n = 1062n = 303
    Moderate469.0(15.1)a504.8(14.0)b577.7(27.0)a,b0.009
    Vigorousd205.5(11.2)a,b255.4(10.4)a312.1(20.1)b<0.001
    MVPAd674.6(22.9)a,b760.1(20.5)a,c887.2(39.7)b,c<0.001
    Total PA1096.8(29.9)a,b1197.1(27.6)a,c1421.9(53.5)b,c<0.001
  • Data are means (standard errors). MVPA, moderate to vigorous physical activity. All PA variables are expressed as minutes per week. Low was considered when the answer to the question was ‘not at all’ or ‘not much’, Middle if ‘sometimes’ or ‘often’ and High if ‘very often’

  • a, b, c Common superscripts in a same row indicate a pairwise significant difference (P < 0.05). Pairwise comparisons were performed by using Bonferroni’s adjustment

  • d Row data are shown, yet square root transformed data were used in the analyses

View this table:
Table 4

Adolescents’ PA levels, measured by accelerometry, according to relatives’ encouragement levels, controlled by sex, age and centre

LowMiddleHighOverall P
Fathern = 456n = 998n = 428
    Moderate37.7(0.8)a39.4(0.5)40.6(0.8)a0.038
    Vigorousc17.4(0.7)a17.9(0.4)b20.4(0.7)a,b0.007
    MVPA55.0(1.3)a57.3(0.7)b61.0(1.3)a,b0.005
    Total PAc418.1(8.3)a429.5(4.8)b461.7(8.2)a,b<0.001
Mothern = 399n = 1142n = 442
    Moderate39.8(0.8)39.1(0.4)38.6(0.7)0.242
    Vigorousc20.1(0.7)17.9(0.4)18.7(0.7)0.033
    MVPA59.9(1.3)57.0(0.7)57.3(1.2)0.030
    Total PAc444.7(8.4)427.8(4.6)440.3(7.6)0.016
Brothersn = 581n = 374n = 131
    Moderate39.1(0.6)40.1(0.8)39.6(1.5)0.492
    Vigorousc19.1(0.6)19.1(0.7)17.8(1.4)0.545
    MVPA58.3(1.0)59.2(1.3)57.4(2.4)0.563
    Total PAc433.4(6.7)444.8(8.0)440.3(15.3)0.233
Sistersn = 628n = 352n = 118
    Moderate37.9(0.6)a40.7(0.8)a41.0(1.4)0.002
    Vigorousc17.9(0.5)18.5(0.7)19.9(1.3)0.132
    MVPA55.8(1.0)59.3(1.3)60.8(2.3)0.009
    Total PAc421.1(6.1)a440.8(8.1)468.0(14.5)a0.003
Best friendn = 895n = 777n = 217
    Moderate38.1(0.5)a,b40.0(0.5) a42.2(1.2)b0.004
    Vigorousc18.1(0.5)a18.4(0.5)21.0(1.1)a0.015
    MVPA56.1(0.9)a58.5(0.9)63.2(1.9)a0.001
    Total PAc425.6(5.6)a435.7(5.6)b474.9(12.1)a,b0.001
  • Data are means (standard errors). MVPA, moderate to vigorous physical activity. All PA variables are expressed as minutes per day, except for total PA that is counts per minute. Low was considered when the answer to the question was ‘not at all’ or ‘not much’, Middle if ‘sometimes’ or ‘often’, and High if ‘very often’

  • a, b Common superscripts in a same row indicate a pairwise significant difference (P < 0.05). Pairwise comparisons were performed by using Bonferroni’s adjustment

  • c Row data are shown, yet square root (Vigorous) and logarithmic (Total PA) transformed data were used in the analyses

Additional analyses

There were more missing data on accelerometry than on IPAQ-A, so for exploratory purposes, we repeated all the analyses selecting those adolescents having valid data on both accelerometry and IPAQ-A, and overall, the results persisted. We also repeated all the analyses using sexual maturation instead of age as covariates to examine if this decision could affect the results, but no substantial differences were found. (data not shown).

Discussion

Our results suggest that relatives’ PA encouragement is more strongly and consistently associated with adolescents’ PA level than relatives’ PA engagement. Dose–response associations were observed indicating that the higher the level of encouragement the higher the level of adolescents’ PA. This finding was overall consistent when using self-report (IPAQ-A) or objective (accelerometry) methods for assessing adolescents’ PA level, yet the associations tended to be stronger when using self-report methods. Since there were more missing data on accelerometry than on IPAQ-A, we wondered whether this fact could explain the weaker associations observed when using accelerometry compared to IPAQ-A, but the exploratory analyses performed did not support this notion. An explanation for the stronger associations observed for self-reported PA could be that relatives’ PA variables were reported by the adolescents, so were adolescents’ PA levels when using IPAQ-A; these two measurements are therefore based on a common factor, the adolescent’s perception. This may partially explain why the associations were stronger when using IPAQ-A compared to accelerometry. One study simultaneously assessed PA both subjectively and objectively,13 but unfortunately the relatives were not separately analyzed, which make the comparison with our results difficult. The authors found that family support was positively related with adolescents’ PA as assessed by both subjective (Physical Activity Questionnaire—Adolescents) and objective (accelerometry) methods, without clear differences between subjective and objective methods.

Associations between relatives’ PA engagement and adolescents’ PA

Previous literature supports a positive association between relatives’ PA engagement and adolescents’ PA level. Eriksson et al.10 reported that having two active parents was related to four to eight times higher odds of being active. Similar associations were also observed between siblings’ and peers’ PA engagement and adolescents’ PA levels.5,26 These associations became stronger when the engagement was combined with the encouragement.11,17 In a longitudinal study, Davison and Jago27 found that parents’ PA engagement at the age of 9 and 11 years, and a stable logistic support (e.g. taking them to places where they can be active, enrolling them in sport activities) from 9 to 15 years old is associated with remaining active in girls during the study period.

In this study, when using subjective methods, the strongest associations were observed between brothers’, sisters’ and the best friend’s PA engagement and adolescents’ PA levels. These results concur with those from Seabra et al.26 that observed that siblings’ PA engagement was related to two to three times higher odds of being active, compared to parents’ PA engagement. Likewise, Keresztes et al.5 observed sisters and brothers being the most influential in boys and classmates in girls. Moreover, Vilhjalmsson and Kristjansdottir28 also studied several relatives separately and observed the strongest association between friends’ PA engagement and adolescents’ PA level. Our self-reported data, together with the studies mentioned above (all using self-reported data), support the idea that siblings’ and friends’ PA engagement is more strongly associated with adolescents’ PA level than mothers’ or fathers’ PA engagement. However, our accelerometry data do not support these results.

Associations between relatives’ PA encouragement and adolescents’ PA

A major finding of this study was the association between relatives’ PA encouragement and adolescents’ PA level, which was overall consistent when using subjective and objective methods. Our results are supported by previous studies relating adolescents’ PA with encouragement or support by family,29 family and friends,14,17 parents and peers,15,16 or friends and peers.30 These relationships also showed that low parent and low peer support were associated with reduced odds of being regularly active after school15. Family support emerged as the most significant and consistent factor associated with MVPA of both adolescent boys and girls. This relationship was noted even when different methods of measuring MVPA were used (PAQ-A and accelerometry).13

We observed positive encouragement association for most of the relatives studied, only brothers’ and mothers’ PA encouragement being not associated or not consistently associated with adolescents’ PA level when measured with accelerometry. Robbins et al.16 reported that father’s PA encouragement was more strongly associated to adolescents’ PA levels than other relatives. This finding is consistent with what was noted in other studies.31,32 These studies used self-reported methods to assess adolescent’s PA level. Information on accelerometry is scarce on this topic.

Limitations and strengths

A first limitation of this study was the lack of objective information of the relatives’ PA. Secondly, information about the brothers’ and sisters’ age was not collected, therefore not possible to determine whether the associations are stronger for younger or older siblings. Strengths of this study are the large sample size and the geographical spread of the study sample all over Europe, as well as the highly standardized procedures and the central handling and analysis of the accelerometer data used within the HELENA study. In addition, further strengths and contribution of this work to the previous literature are the independent and separate analysis of the adolescents’ surrounding people, the inclusion of both relatives’ engagement and encouragement, and the use of both subjective and objective methods for assessing PA levels in adolescents.

In conclusion, high levels of relatives’ PA encouragement are associated with high levels of adolescents’ PA. This finding was mostly consistent when using self-report (IPAQ-A) or objective (accelerometry) methods for assessing adolescents’ PA level. Relatives’ PA engagement was also positively related with adolescent’ PA level, as assessed by self-report methods, but not as assessed by objective methods. Community interventions aiming to enhance PA levels in the adolescent population might be more successful if family and peers are also targeted. In this context, relatives’ encouragement could play an important role. Self-reported data in combination with objective data are needed to clarify the role of the relatives’ PA engagement and encouragement in adolescents.

Supplementary data

Supplementary data are available at EURPUB online.

Funding

The HELENA study takes place with the financial support of the European Community Sixth RTD Framework Programme (Contract FOOD-CT-2005-007034). This study is also being supported by grants from the Spanish Ministry of Education (EX-2007-1124, EX-2008-0641, AP2006-02464), the Swedish Heart-Lung Foundation (20090635), the Swedish Council for Working Life and Social Research and the ALPHA study, a European Union-funded study, in the framework of the Public Health Programme (Ref: 2006120), and the Spanish Ministry of Health: Maternal, Child Health and Development Network (number RD08/0072). The content of this article reflects only the authors’ views, and the European Community is not liable for any use that may be made of the information contained therein.

Conflicts of interest: None declared.

Key points

  • This study adds the separate analysis of the adolescents’ surrounding people, including both engagement and encouragement, and using different methods for assessing PA levels in adolescents.

  • High levels of relatives’ PA encouragement are associated with high levels of adolescents’ PA, overall regardless of the use of self-report (IPAQ-A) or objective (accelerometry) methods.

  • Relatives’ PA engagement was also positively related with adolescent’ PA level, as assessed by self-report methods, but not as assessed by objective methods.

  • Community interventions aiming to enhance PA levels in the adolescent population might be more successful if family and peers are also targeted, with special focus on relatives’ encouragement.

Acknowledgements

We acknowledge all participating children and adolescents, as well as their parents and teachers for their collaboration. We also acknowledge our staff members for their efforts and great enthusiasm during the fieldwork.

Appendix 1

HELENA Study Group

Co-ordinator: Luis A. Moreno.

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

Steering Committee: Anthony Kafatos (President), Luis A. Moreno, Christian Libersa, Stefaan De Henauw, Sara Castelló, Fréderic Gottrand, Mathilde Kersting, Michael Sjöstrom, Dénes Molnár, Marcela González-Gross, Jean Dallongeville, Chantal Gilbert, Gunnar Hall, Lea Maes, 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, Carmen Lachen, Juan Fernández Alvira, Gloria Bueno, Aurora Lázaro, Olga Bueno, Juan F. León, Jesús Ma Garagorri, Manuel Bueno, Juan Pablo Rey López, Iris Iglesia, Paula Velasco, Silvia Bel.

  2. Consejo Superior de Investigaciones Científicas (Spain)

    Ascensión Marcos, Julia Wärnberg, Esther Nova, Sonia Gómez, Ligia Esperanza Díaz, Javier Romeo, Ana Veses, Belén Zapatera, Tamara Pozo, David Martínez.

  3. Université de Lille 2 (France)

    Laurent Beghin, Christian Libersa, Frédéric Gottrand, Catalina Iliescu, Juliana Von Berlepsch.

  4. Research Institute of Child Nutrition Dortmund, Rheinische Friedrich-Wilhelms-Universität Bonn (Germany)

    Mathilde Kersting, Wolfgang Sichert-Hellert, Ellen Koeppen.

  5. Pécsi Tudományegyetem (University of Pécs) (Hungary)

    Dénes Molnar, Eva Erhardt, Katalin Csernus, Katalin Török, Szilvia Bokor, Mrs. Angster, Enikö Nagy, Orsolya Kovács, Judit Répasi.

  6. University of Crete School of Medicine (Greece)

    Anthony Kafatos, Caroline Codrington, María Plada, Angeliki Papadaki, Katerina Sarri, Anna Viskadourou, Christos Hatzis, Michael Kiriakakis, George Tsibinos, Constantine Vardavas, Manolis Sbokos, Eva Protoyeraki, Maria Fasoulaki.

  7. Institut für ErInstitut für Ernährungs-und Lebensmittelwissenschaften—Ernährungphysiologie. Rheinische Friedrich Wilhelms Universität (Germany)

    Peter Stehle, Klaus Pietrzik, Marcela González-Gross, Christina Breidenassel, Andre Spinneker, Jasmin Al-Tahan, Miriam Segoviano, Anke Berchtold, Christine Bierschbach, Erika Blatzheim, 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, David Jiménez-Pavón, Palma Chillón, Cristóbal Sánchez-Muñoz, Magdalena Cuenca

  9. Istituto Nazionalen di Ricerca per gli Alimenti e la Nutrizione (Italy)

    Davide Arcella, Elena Azzini, Emma Barrison, Noemi Bevilacqua, Pasquale Buonocore, Giovina Catasta, Laura Censi, Donatella Ciarapica, Paola D'Acapito, Marika Ferrari, Myriam Galfo, Cinzia Le Donne, Catherine Leclercq, Giuseppe Maiani, Beatrice Mauro, Lorenza Mistura, Antonella Pasquali, Raffaela Piccinelli, Angela Polito, Raffaella Spada, Stefania Sette, Maria Zaccaria.

  10. University of Napoli ‘Federico II’ Dept of Food Science (Italy)

    Luca Scalfi, Paola Vitaglione, Concetta Montagnese.

  11. Ghent University (Belgium)

    Ilse De Bourdeaudhuij, Stefaan De Henauw, Tineke De Vriendt, Lea Maes, Christophe Matthys, Carine Vereecken, Mieke de Maeyer, Charlene Ottevaere, Inge Huybrechts.

  12. Medical University of Vienna (Austria)

    Kurt Widhalm, Katharina Phillipp, Sabine Dietrich, Birgit Kubelka Marion Boriss-Riedl.

  13. Harokopio University (Greece)

    Yannis Manios, Eva Grammatikaki, Zoi Bouloubasi, Tina Louisa Cook, Sofia Eleutheriou, Orsalia Consta, George Moschonis, Ioanna Katsaroli, George Kraniou, Stalo Papoutsou, Despoina Keke, Ioanna Petraki, Elena Bellou, Sofia Tanagra, Kostalenia Kallianoti, Dionysia Argyropoulou, Katerina Kondaki, Stamatoula Tsikrika, Christos Karaiskos.

  14. Institut Pasteur de Lille (France)

    Jean Dallongeville, Aline Meirhaeghe.

  15. Karolinska Institutet (Sweden)

    Michael Sjöstrom, Jonatan R Ruiz, Francisco B. Ortega, María Hagströmer, Anita Hurtig Wennlöf, Lena Hallström, Emma Patterson, Lydia Kwak, Julia Wärnberg, Nico Rizzo.

  16. Asociación de Investigación de la Industria Agroalimentaria (Spain)

    Jackie Sánchez-Molero, Sara Castelló, Elena Picó, Maite Navarro, Blanca Viadel, José Enrique Carreres, Gema Merino, Rosa Sanjuán, María Lorente, María José Sánchez.

  17. Campden BRI (United Kingdom)

    Chantal Gilbert, Sarah Thomas, Elaine Allchurch, Peter Burgess.

  18. SIK - Institutet foer Livsmedel och Bioteknik (Sweden)

    Gunnar Hall, Annika Astrom, Anna Sverkén, Agneta Broberg.

  19. Meurice Recherche & Development asbl (Belgium)

    Annick Masson, Claire Lehoux, Pascal Brabant, Philippe Pate, Laurence Fontaine.

  20. Campden & Chorleywood Food Development Institute (Hungary)

    Andras Sebok, Tunde Kuti, Adrienn Hegyi.

  21. Productos Aditivos SA (Spain)

    Cristina Maldonado, Ana Llorente.

  22. Cárnicas Serrano SL (Spain)

    Emilio García.

  23. Cederroth International AB (Sweden)

    Holger von Fircks, Marianne Lilja Hallberg, Maria Messerer

  24. Lantmännen Food R&D (Sweden)

    Mats Larsson, Helena Fredriksson, Viola Adamsson, Ingmar Börjesson.

  25. European Food Information Council (Belgium)

    Laura Fernández, Laura Smillie, Josephine Wills.

  26. Universidad Politécnica de Madrid (Spain)

    Marcela González-Gross, Agustín Meléndez, Pedro J. Benito, Javier Calderón, David Jiménez-Pavón, Jara Valtueña, Paloma Navarro, Alejandro Urzanqui, Ulrike Albers, Raquel Pedrero, Juan José Gómez Lorente.

Footnotes

  • *The members of the HELENA Study Group are listed in Appendix 1.

References

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