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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Int J Public Health. Author manuscript; available in PMC 2010 September 1.
Published in final edited form as:
PMCID: PMC2732761

Interrelationships of adolescent physical activity, screen-based sedentary behaviour, and social and psychological health

Ronald J. Iannotti,1 Ian Janssen,2 Ellen Haug,3 Hanna Kololo,4 Beatrice Annaheim,5 and Alberto Borraccino6, the HBSC Physical Activity Focus Group



To examine how adolescent physical activity (PA) and screen-based media sedentary behaviours (SBM) relate to psychological and social health and identify cross-national differences in these relationships.


Associations were examined in five regions using two Health Behaviour in School-Aged Children (HBSC) countries from each.


Self-reported psychological and social health indices such as self-image, perceived health status, and quality of life were positively related to PA in all five regions but, with a few exceptions, negatively related to SBM. Negative health indices such as health complaints and tobacco use were negatively related to PA but, with exceptions, positively related to SBM. Significant regional differences were present.


Regional differences in correlates of PA and SBM suggest cultural differences in potential effects of PA and SBM and the need to tailor school and public health efforts to the different meanings of PA and SBM for positive and negative health consequences.

Keywords: Physical Activity, Sedentary Behaviour, Quality of life, Social relationships, Health complaints, Substance use

Physical activity (PA) is any physical movement or muscular exertion which increases energy expenditure; moderate to vigorous physical activity (MVPA) raises energy expenditure to at least three times one’s basal metabolic rate. The increase in energy expenditure and resulting challenge to pulmonary-cardiovascular systems has a number of beneficial effects on physical health, particularly improved cardiovascular functioning1. Sedentary behaviour on the other hand is any behaviour which maintains a level of energy expenditure close to that when one is resting; sedentary behaviours that involve screen-based media use (SBM) usually refer to leisure-time activities such as watching television, playing video or computer games, or using a computer. The reduced energy expenditure during periods of SBM may contribute a positive energy balance (i.e., less energy expenditure relative to energy intake) and has been associated with obesity and obesity-related health problems2.

Although there has been extensive research linking MVPA to markers of physical health such as decreased adiposity, improvement in Metabolic Syndrome (abdominal obesity, elevated blood pressure, elevated fasting glucose, and reduced HDL), decreased triglyceride level, increased HDL, bone density, muscular strength and endurance, and aerobic fitness, and improved mental health, studies relating PA to social and psychological health indicators have been less prevalent1,3.

Two potential mechanisms have been suggested for positive relationships between PA and psychological and social health. One set of hypothesis credits the physiological effect of PA on monoamines in the brain affecting neurotransmission or on the production of endorphins and their pain reduction and euphoric effects4. Alternatively, PA has been associated with positive self-concept and the reduction of anxiety and depression in adolescents; these positive psychological effects could generalize to improved management of stress and impact social interactions as well1, 48. However, the relationship of PA with social relationships (quality of family and peer relationships), health complaints, and negative health behaviours (aggression, tobacco use, and alcohol use and abuse) have either received little attention or focused on particular populations (athletes, local samples)7,914.

In addition to the potential effect of SBM on adiposity2, SBM has been associated with muscular-skeletal pain and behavioural problems such as aggression and substance use15,16. Because SBM is an indicator of inactivity, it might be assumed that SBM would have the opposite effects on psychological and social health as PA; however, research on the relationship between SBM and social and behavioural health indicators is characterized by noticeable gaps or inconsistent findings1719. Differences in findings may represent cultural differences in the samples studied. In order to strengthen the evidence base in this area, additional research identifying cross-cultural similarities and differences in potential influences of PA and SBM on various indicators of health is warranted. The current paper examines independent associations of PA and SBM with positive and negative health indicators in large nationally-representative samples from North America and Europe. It was predicted that PA would have positive associations with positive health indicators and negative relations with negative health indicators. The opposite pattern was predicted for SBM.


Identical self-report questions were used to survey students ages 11, 13 and 15 from countries participating in the Health Behaviour in School-Aged Children (HBSC) study during the 2005–2006 school year20. Self-completion questionnaires were administered in school classroom in each participating country and region, with requirements in terms of sampling, questionnaire items and survey administration being set out in a standardised research protocol. All of the questions used in the HBSC survey must have evidence of reliability and validity when used with children in multiple countries before they are considered for inclusion20. In the majority of countries, national representative samples were drawn and samples were stratified to ensure representation of relevant subgroups. Cluster sampling was used, the primary sampling unit being school class (or school where a sampling frame of classes was not available). Ten HBSC countries, two from each region, were randomly selected to represent North America (NA; U.S., Canada), Western Europe (WE; Switzerland, Netherlands), Eastern Europe (EE; Czech Republic, Poland), Northern Europe (NE; Finland, Norway), and Southern Europe (SE: Italy, Spain).

Participation in the survey was voluntary and each country conformed to the ethical and legal requirements of their country. Full details of the study’s development and methods employed can be found in this supplement and elsewhere20,21.

Physical Activity

After reading a definition of moderate-to-vigorous PA and examples, students indicated the number of days (from zero to 7) they engaged in at least 60 minutes of PA over the past seven days. This measure has been shown to have good reliability and validity22 and HBSC national averages are consistent with studies using other measures of PA2326.

Screen-based Media Use

SBM was estimated using 2 two-part questions asking how many hours (none, ½ 1 to 7 or more) per weekday and weekend day was spent: 1) using a computer during free time (excluding time spent doing homework), and 2) watching television (including videos). Using the values indicated, mean hours per day of both screen-based activities were calculated and summed to create a SBM score27.

Physical Self-Image

Perception of one’s body size indicated satisfaction with self-image (‘just right’ scored as 3) versus dissatisfaction (‘a bit too thin’ or ‘a bit too fat’ scored as 2, and ‘much too thin’ or ‘much too fat’ scored as 1) 28.

Perceived Health Status

Perceived health status was self-rated (4-point scale: fair, poor, good, and excellent) 29.

Quality of Life

Participants indicated where they stood on a 10-point ladder with zero being the ‘worst possible life’ and 10 being the ‘best possible life’30.

Quality of Family Relationships

Participants indicated how easy (4-point scale: very difficult, difficult, easy, and very easy) it was to talk to specific others about things that were bothering them. A mean score was derived from responses about six family members (excluding family members they don’t see or have): father, step-father, mother, step-mother, older brother and older sister (Cronbach’s alpha = .81) 31.

Quality of Peer Relationships

Three items asked whether it was easy to talk with a best friend, friends of the same sex, and friends of the opposite sex (4-point scale: very difficult, difficult, easy, and very easy). Two items asked the number of close male and female friends: none, one, two, or three or more. Two items asked how many days/week they usually spent time with friends immediately after school (zero to five+) and how many evenings/week they usually spent time with friends (zero to seven) 31. A weighted mean (each response divided by the maximum possible score for that item) of the seven items was the index for quality of peer relationships (Cronbach’s alpha = .66).

Health Complaints

Participants indicated how frequently (5-point scale: rarely or never, about every month, about every week, more than once a week, and about every day) they had each of eight symptoms (headache, stomach-ache, backache, feeling low, irritability or bad temper, feeling nervous, difficulties getting to sleep, feeling dizzy) 32. A mean of the responses represented subjective health complaints (Cronbach’s alpha = .80).

Physical Aggression

A mean of two items contributed to an index of physically aggressive behaviour: frequency of bullying other students in the past two months (5-point scale: I haven’t bullied another student(s) at school in the past couple of months, it has only happened once or twice, 2 or 3 times a month, about once a week, and several times a week); and number of times in a physical fight in the past 12 months (5-point scale: I have not been in a physical fight, 1 time, 2 times, 3 times, and 4 times or more) 33,34. A weighted mean of the two items was used for the index of aggression.

Tobacco Use

A single item asking “How often do you smoke tobacco at present?” (4-point scale: I do not smoke, less than once a week, at least once a week but not every day, and every day) indicated cigarette smoking35.

Alcohol Use and Getting Drunk

Alcohol use indicated the highest frequency of use (converted to days/week: never (0), rarely (.1), every month (.25), every week (1), and every day (7)) of beer, wine, or liquor/spirits. Students also indicated if they had ever had so much alcohol that they were really drunk (5-point scale: never, once, 2–3 times, 4–10 times, and more than 10 times) 36.

Analysis plan

Item distributions were evaluated. Skewed distributions for tobacco use and the two alcohol questions were adjusted using log transformations; however, to simplify the interpretation, the means shown in Table 1 are prior to transformation.

Table 1
Regional Means (Standard Deviations) of Physical Activity, Screen-based Media Use, and Positive and Negative Health Indicators

PA and SBM were initially regressed on age, gender, and the other activity variable (PA or SBM) to determine the relation of each of the activity variables to age and gender. Regression models including age, gender, PA and SBM indicated how PA and SBM independently related to each of the positive and negative health indices within each region. Because a disproportionate number of existing studies have been conducted with samples from North America and previous work examined these relationships in larger national samples from the U.S. and Canada37, North America was used as the reference region to determine if cultural differences might account for differences in findings across study samples. To examine potential regional effects, regression models paired North America with each European region; region by predictor variable interaction terms indicated whether associations were significantly different across regions. To control for cluster effects of the sampling design, SAS Version 9.1 Survey procedures were used for all analyses. Measures were standardized, pooling data from all countries, prior to regression analyses. Missing items within a multi-item scale were addressed by using a weighted mean of all remaining items. Listwise deletion was used when an element of the regression model was missing. Missing responses were distributed equally across age groups and averaged less than 3% with the exception of alcohol questions in Southern Europe (29%). Because analyses were repeated in five regions, the significance level was set at p < .01.


Self-reported physical activity (PA) varied across regions; adolescents in North America (NA) reported the highest rate and in Southern Europe (SE) reported the lowest. Screen-based sedentary behaviour (SBM) was highest in Eastern Europe (EE) and lowest in SE (Table 1). In all regions, PA decreased significantly with age and boys reported significantly more PA than girls (Table 2); similar to PA, SBM was higher in boys than girls (Table 3). However, SBM increased with age in Western Europe (WE), Northern Europe (NE), and SE, decreased with age in NA, and was unrelated to age in EE (Table 3). PA and SBM were unrelated in three regions but were negatively related in NA and NE (Table 2). [Tables 1, ,22 and and33 here]

Table 2
Regional Regression Coefficients for Demographics and Positive and Negative Health Indicators with Physical Activity
Table 3
Regional Regression Coefficients for Positive and Negative Health Indicators with Screen-Based Media Use

Across all regions, PA was positively related to all five indices of positive psychological and social health (Table 2). The associations of PA with perceived health status and peer relationships were the strongest across regions with average standardized regression coefficients of .18.

In all five regions, PA was negatively related to health complaints and in four of the five regions negatively related to tobacco use (Table 2). However, PA was positively related to alcohol use in three regions, positively related to aggression in two regions, and related to getting drunk in one region. The one region with a consistent pattern of positive relations between PA and aggression, alcohol use, and getting drunk was NA. However, for all regions the coefficients for physical aggression, tobacco use, alcohol use and getting drunk were quite small.

To evaluate regional differences, each of the four European regions was compared to NA. There were no significant regional differences in the associations of PA with self-image, quality of life, or alcohol, where the associations were either positive or non-significant. (Table 2). For the remaining positive and negative health indices, regions primarily differed in the strength of the relationships but not in direction. Where significant differences with NA existed, the strength of associations with PA was significantly weaker in EE but the direction of effects was mixed in the other three regions.

In all five regions, higher levels of SBM were associated with poorer self-image (Table 3). More frequent SBM was associated with poorer quality of life in four regions and poorer perceived health status and family relationships in three regions. However, SBM was positively related to family relationships in WE and positively related to quality of peer relationships in all regions.

The pattern for associations between SBM and negative health indices was very different (Table 3). Where significant relationships were found, they were uniformly in a positive direction. In all five regions, SBM was positively related to aggression, alcohol use, and getting drunk. The strongest association was with physical aggression where the average coefficient across regions was .14.

There were more regional differences for associations with SBM than there were for PA (Table 3). EE differed from NA in seven of ten health index comparisons. NE and NA were comparable in the magnitude and direction of coefficients for all health indices.


In addition to known physical benefits, the present study demonstrates that PA appears to be positively related to psychosocial health and other health behaviours for school-aged children. The only exceptions appear to be an association with aggression and alcohol use. In contrast, it appears that across regions SBM is associated with a range of health risks and lower quality of life beyond those previously studied. These findings are troublesome because children in none of the regions studied averaged sufficient PA to meet the minimum guidelines of at least 60 min of PA five days a week1 and in all regions the average child spent significantly more time per day engaged in SBM than the recommendations for no more than two hours per day of SBM17 (see Table 1).

One theory for potential negative health effects of SBM is that time spent in sedentary activities displaces time available for PA38. However, SBM was not significantly related to PA in three regions. Furthermore, in all regions studied, boys were higher in both PA and SBM than girls. And while PA consistently decreased across age in all five regions, SBM increased across age in only three of the five regions. These results suggest that adolescents are not replacing PA with SBM. Finally, even with PA in the equation SBM had significant negative associations with health indices. Although PA generally had a positive association with positive health indices and negative associations with negative health indices, the pattern of associations for SBM was not a mirror image and regression coefficients were still significant when both PA and SBM were in the models. Overall, a strong argument can be made that PA and SBM are independent behaviours, each with significant health correlates.

PA may have broad positive relationships to mental as well as physical health as evident in the positive associations with positive health indices. The positive effects of PA on psychological and social health may be due to physiological effects of PA or to the positive effects of PA on mental health indicators such as self-esteem and self-concept4. The uniformly positive relations between PA and self-image would support these hypotheses; however, PA appears to have even stronger relations with perceived quality of life and quality of peer interactions.

Although the size of many of these associations was modest, the consistent pattern across regions and the fact that PA levels were below recommended guidelines while SBM levels were substantially above recommended guidelines suggest that these behaviours could have significant public health implications. In addition to better physical health and fewer health complaints, PA was associated with better mental and social health (self-image, quality of life, family, and peer relationships) and lower prevalence of a major health risk behaviour (cigarette use). So far, physical activity interventions for children and adolescents have to a large extent focused on the public health effect of reducing the emerging paediatric overweight epidemic and maximizing physical health. The present findings provide additional justification for public health strategies to increase physical activity for the general population and for more structured intervention efforts focusing on children at risk for developing mental health problems and risky behaviours.

Although there were regional differences in these associations, in most cases they were differences in the magnitude of the associations rather than the direction. In contrast, SBM had a pattern of negative relationships with self-image and quality of life and positive associations with physical aggression, getting drunk, and quality of peer relationships. In most regions, SBM was negatively related to perceived health status and quality of family relationships and positively related to health complaints, smoking and alcohol use. Thus, with the exception of quality of peer relationships, SBM would appear to be associated with poorer psychological and social health.

Relations between psychological and social health for SBM were not a mirror image of those for PA. This suggests that the mechanism for the effects of SBM on these health indices is not simply due to inactivity. In all regions, SBM was positively related to quality of peer interactions but generally had negative effects on health. One explanation for the negative effects of SBM on these health indicators is the content of television programming and computer games. Further exploration of regional differences in television programming and the correlates of SBM may shed light on this explanation. Alternatively, it may be that children with poor physical and mental health choose to spend more time on SBM. Still, efforts to replace some screen-based activity with participation in PA are likely to have a positive effect for children reporting poor physical and mental health. Substantial regional differences suggest that engaging in SBM may have different meaning in different cultures, and be influenced by behavioural traditions. Therefore, efforts to modify SBM need to take these cultural differences into account. Physical aggression is one exception to the contrasting relationships of PA and SBM with health indices. PA was not significantly related to physical aggression in two regions and was weakly but positively associated in the other three. It may be that cultural differences with regard to organized PA (e.g., youth sport teams) establish different expectations regarding personal behaviour39. Cross-country differences in the prevalence of contact sports may also influence this relationship40. As in previous research15,16, SBM was consistently related to aggression across regions. Violent content of television, videos, and computer games as well as aggressive conflicts displayed during televised sports needs to be considered if the association of PA and SBM with youth aggression is to be addressed.

The other exception to the pattern is in quality of peer relationships; both PA and SBM were positively associated with peer relationships. The positive association between SBM and quality of social relationships is particularly interesting. TV viewing and computer use are an active part of the peer culture and may reflect overall peer socialization41. Interestingly, in some cultures these SBM activities were associated with a poorer quality of family communication.

A limitation of this study is that the data are cross-sectional and do not permit inferences about causality. Still, these associations are a first step in generating hypothesis for further research. In addition, all of the indices are based on self-report. Finally, the sample does not include countries outside of Europe and North America.

These limitations need to be balanced against the considerable assets of this study. The dataset includes large, nationally-representative samples representing different countries and cultures. The consistent patterns of results across countries and regions are compelling.

PA and SBM do not appear to be opposite ends of a single dimension. The study adds to previous research by demonstrating consistent cross-regional positive associations between PA and psychological and social health, as well as negative associations between SBM and these health indicators. This provides additional justification for intervention efforts. It is likely that psychological and social health effects could serve as effective motivators because they provide immediate benefits compared to the long-term risk of cardiovascular disease. However, regional differences in the correlates of PA and SBM suggest cultural differences in effects and the need to tailor school and public health efforts to the different meanings of PA and SBM for positive and negative health consequences. More research is needed, particularly for SBM which has received less attention than PA and for which only a limited number of countries have developed official health recommendations.


Work on this manuscript was supported by the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development. The WHO-HBSC is a WHO/Euro collaborative study. International Coordinator of the 2005/06 study: Candace Currie, University of Edinburgh, Scotland; Data Bank Manager: Oddrun Samdal, University of Bergen, Norway.


Conflicts of Interest



1. Strong WB, Malina RM, Bumke CJ, et al. Evidence based physical activity for school-age children. Journal of Pediatrics. 2005;146:732–737. [PubMed]
2. DeMattia L, Lemont L, Meurer L. Do interventions to limit sedentary behaviours change behaviour and reduce childhood obesity? A critical review of the literature. Obesity Reviews. 2007;8:69–81. [PubMed]
3. Hallal PC, Victora CG, Azevedo RM, Wells JCK. Adolescent physical activity and health. A systematic review. Sports Medicine. 2006;36:1019–1030. [PubMed]
4. Paluska SA, Schwenk TL. Physical activity and mental health. Sports Medicine. 2000;29:167–180. [PubMed]
5. Aarnio M, Winter T, Kujala U, Kaprio J. Associations of health and related behavior, social relationships, and health status with persistent physical activity and inactivity: a study of Finnish adolescent twins. British Journal of Sports Medicine. 2002;36:360–364. [PMC free article] [PubMed]
6. Biddle SJH. Emotion, mood and physical activity. In: Biddle SJH, Fox KR, Boutcher SH, editors. Physical activity and psychological well-being. New York: Routledge; 2000. pp. 63–87.
7. Nelson MD, Gordon-Larsen P. Physical activity and sedentary behavior patterns are associated with selected adolescent health risk behaviors. Pediatrics. 2006;117:1281–1290. [PubMed]
8. Strauss RS, Rodzilsky D, Burack G, Colin M. Psychosocial correlates of physical activity in healthy children. Archives of Pediatric and Adolescent Medicine. 2001;155:897–902. [PubMed]
9. Archer J, Pearson NA, Westerman KE. Aggressive behaviour of children aged 6–11: gender differences and their magnitude. British Journal of Social Psychology. 1988;27:371–384. [PubMed]
10. McHale JP, Vinden PG, Bush L, Richter D, Shaw D, Smith B. Patterns of personal and social adjustment among sport-involved and noninvolved urban middle-school children. Sociology of Sport Journal. 2005;22:119–136.
11. Peretti-Watel P, Beck F, Legleye S. Beyond the U-curve: the relationship between sport and alcohol, cigarette and cannabis use in adolescents. Addiction. 2002;97:707–716. [PubMed]
12. Tercedor P, Martin-Matillas M, Chillón P, Pérez López IJ, Ortega FM, Warnberg J, Ruiz JR, Delgado M. Incremento del consumo de tabaco y disminución del nivel de práctica de actividad física en adolescentes españoles: Estudio AVENA. Nutrición Hospitalaria. 2007;22:89–94. [PubMed]
13. Thorlindsson T. Sport participation, smoking, and drug and alcohol use among Icelandic youth. Sociology of Sport Journal. 1989;6:136–143.
14. Vilhjalmsson R, Thorlindsson T. Factors related to physical activity: a study of adolescents. Social Science and Medicine. 1998;47:665–675. [PubMed]
15. Hakala PT, Rimpelä AH, Saarni LA, Salminen JJ. Frequent computer-related activities increase the risk of neck-shoulder and low back pain in adolescents. European Journal of Public Health. 2006;16:536–541. [PubMed]
16. American Academy of Pediatrics. Children, adolescents and television. Pediatrics. 2001;107:423–426. [PubMed]
17. Leatherdale ST, Wong SL. Modifiable characteristics associated with sedentary behaviours among youth. International Journal of Pediatric Obesity. 2008;3:93–101. [PubMed]
18. Pate RR, Heath GW, Dowda M, Trost SG. Associations between physical activity and other health behaviors in a representative sample of US adolescents. American Journal of Public Health. 1996;86:1577–1581. [PubMed]
19. Tur JA, Puig MS, Pons A, Benito E. Alcohol consumption among school adolescents in Palma de Mallorca. Alcohol and Alcoholism. 2003;38:243–248. [PubMed]
20. Roberts C, Freeman J, Samdal O, Schnohr C, Looze M, Nic Gabhainn S, Iannotti R, and the HBSC Methods Development Group The Health Behaviour in School-aged Children (HBSC) study: methodological developments and current tensions. International Journal of Public Health. 2009;xx(Suppl):xx–xx. [PMC free article] [PubMed]
21. Currie C, Nic Gabhainn S, Godeau E, Roberts C, Smith R, Currie D, Pickett W, Richter M, Morgan A, Barnekow V, editors. Health Policy for Children and Adolescents, No. 5. Copenhagen: WHO Regional Office for Europe; 2008. Inequalities in young people’s health: HBSC international report from the 2005/2006 Survey.
22. Prochaska JJ, Sallis JF, Long B. A physical activity screening measure for use with adolescents in primary care. Archives of Pediatrics & Adolescent Medicine [Arch Pediatr Adolesc Med] 2001;155:554–559. [PubMed]
23. Nader PR, Bradley RH, Houts RM, McRitchie LS, O’Brien M. Moderate-to-vigorous physical activity from ages 9 to 15 years. Journal of the American Medical Association. 2008;300:295–305. [PubMed]
24. Nelson MC, Neumark-Stzainer D, Hannan PJ, Sirard JR, Story M. Longitudinal and secular trends in physical activity and sedentary behavior during adolescence. Pediatrics. 2006;118:e1627–e1634. [PubMed]
25. Riddoch CJ, Andersen LB, Wedderkopp N, Harro M, Klasson-Heggeb□ L, Sardinha LB, Cooper AR, Ekelund U. Physical activity levels and patterns of 9- and 15-yr-ld European children. Medicine & Science in Sports & Exercise. 2004;36:86–92. [PubMed]
26. Tammelin T, Ekelund U, Remes J, Näyhä S. Physical activity and sedentary behaviors among Finnish youth. Medicine & Science in Sports & Exercise. 2007;39:1067–1074. [PubMed]
27. Schmitz KH, Harnack L, Fulton JE, et al. Reliability and validity of a brief questionnaire to assess television viewing and computer use by middle school children. Journal of School Health. 2004;74:370–377. [PubMed]
28. Välimaa R, Ojala K. Body weight status, self-perceived body weight, dieting and weight control behaviour among school-aged children in 1984–2002. (In Finnish) In: Kannas L, editor. School children’s health and health behaviour in change. Vol. 2. HBSC Study 20 yrs University of Jyväskylä, Research Center for Health Promotion; 2004. pp. 55–78.
29. Idler EL, Benyamini Y. Self-rated health and mortality: A review of twenty-seven community studies. Journal of Health and Social Behavior. 1997;38:21–37. [PubMed]
30. Cantril H. The pattern of human concerns. New Brunswick, NJ: Rutgers University Press; 1965.
31. Granado MC, Pedersen JM, Carrasco AM. Greenland family structure and communication with parents: influence on schoolchildren’s drinking behaviour. International Journal of Circumpolar Health. 2002;61:319–331. [PubMed]
32. Hagquist C, Andrich D. Measuring subjective health among adolescents in Sweden. Social Indicators Research. 2004;68:201–220.
33. Brener ND, Collins JL, Kann L, Warren CW, Williams BI. Reliability of the Youth Risk Behavior Survey questionnaire. American Journal of Epidemiology. 1995;141:575–580. [PubMed]
34. Olweus D. Bullying at school: long term outcomes for the victims and an effective school based intervention program. In: Huesmann LR, editor. Aggressive Behavior: Current Perspectives. New York: Plenum Press; 1994. pp. 97–130.
35. Post A, Gilljam H, Rosendahl I, Meurling L, Bremberg S, Galanti MR. Validity of self reports in a cohort of Swedish adolescent smokers and smokeless tobacco (snus) users. Tobacco Control. 2005;14:114–117. [PMC free article] [PubMed]
36. Schmid H, ter Bogt T, Godeau E, Hublet A, Dias SF, Fotiou A. Drunkenness among young people. A cross-national comparison Journal of Studies on Alcohol. 2003;64:650–661. [PubMed]
37. Iannotti RJ, Kogan MD, Janssen I, Boyce WF. Patterns of Adolescent Physical Activity, Screen-Based Media Use and Positive and Negative Health Indicators in the U.S. and Canada. Journal of Adolescent Health. in press. [PMC free article] [PubMed]
38. Rey-Lopez JP, Vicente-Rodriguez G, Biosca M, Moreno LA. Sedentary behaviour and obesity development in children and adolescents. Nutrition, Metabolism & Cardiovascular Diseases. 2008;18:242–251. [PubMed]
39. Moore MJ, Werch CDC. Sport and physical activity participation and substance use among adolescents. Journal of Adolescent Health. 2005;36:486–493. [PubMed]
40. Conroy DE, Silva JM, Newcomer RR, Walker BW, Johnson MS. Personal and participatory socializers of the perceived legitimacy of aggressive behavior in sport. Aggressive Behavior. 2001;27:405–418.
41. Lenhart A, Madden M, MacGill AR, Smith A. The use of social media gains a greater foothold in teen life as they embrace the conversational nature of interactive online media. Pew Internet & American Life Project. 2007 December 19;