Revista Adolescência e Saúde

Revista Oficial do Núcleo de Estudos da Saúde do Adolescente / UERJ

NESA Publicação oficial
ISSN: 2177-5281 (Online)

Vol. 16 nº 1 - Jan/Mar - 2019

Original Article Imprimir 

Páginas 77 a 87


Sedentary behavior and associated factors in school adolescents in the municipality of Sombrio - SC

Comportamiento sedentario y factores asociados en adolescentes escolares del municipio de Sombrio - SC

Comportamento sedentário e fatores associados em adolescentes escolares do município de Sombrio - SC

Autores: Vanessa de Souza Vieira1; Susana da Costa Aguiar2; Maria Cristine Campos3; Ione Jayce Ceola Scheider4; Viviane de Menezes Caceres5; Danielle Soares Rocha Vieira6

1. Graduation in Physiotherapy by the Federal University of Santa Catarina (UFSC). Araranguá, SC, Brazil
2. Physiotherapist. Master in Rehabilitation Sciences by the Graduate Program in Rehabilitation Sciences of the Federal University of Santa Catarina (UFSC). Araranguá, SC, Brazil
3. Physiotherapist. Master in Rehabilitation Sciences by the Graduate Program in Rehabilitation Sciences of the Federal University of Santa Catarina (UFSC). Araranguá, SC, Brazil
4. Doctor in Public Health. Profa. Dra. Of the Department of Health Sciences Federal University of Santa Catarina (UFSC). Araranguá, SC, Brazil
5. Postdoctoral. Professor Dr. Department of Health Sciences, Federal University of Santa Catarina (UFSC). Araranguá, SC, Brazil
6. Dotorate in Rehabilitation Sciences. Profa. Ph.D., Department of Health Sciences, Federal University of Santa Catarina (UFSC). Araranguá, SC, Brazil

Danielle Soares Rocha Vieira
Rodovia Governador Jorge Lacerda, nº 3201 - Km 35,4 - Bairro: Jardim das Avenidas
Araranguá, SC, Brasil. CEP: 88906-072
danielle.vieira@usfc.br

PDF Portuguese      


Scielo

Medline


How to cite this article

Keywords: Adolescent; Sedentary Lifestyle; Adolescent Behavior.
Palabra Clave: Adolescente; Estilo de Vida Sedentario; Comportamiento del Adolescente.
Descritores: Adolescente; Estilo de Vida Sedentário; Comportamento do Adolescente.

Abstract:
OBJECTIVE: Characterize indicators of sedentary behavior (SB) in school adolescents and verify their associations with sociodemographic, anthropometric and physical activity (PA) factors.
METHODS: A total of 104 adolescents (63.3% female, 16.43 ± 0.98 years) from the city of Sombrio (SC) participated in the study. SB indicators (TV time, games, computer and mobile phone use on weekdays and weekends) were categorized as ≤ 2 and > 2 hours/day. The following variables were considered as independent variables: gender, parents' levels of education, type of school, socioeconomic index, body mass index and level of PA. A multivariate logistic regression was used to determine associations (p < 0.05).
RESULTS: SB related to cell phone use was the most prevalent, and present insufficient PA level increased the chances for this behavior (OR: 3.42; 95% CI: 1.15 - 10.16). Being female increased the chance for the use of the TV (OR: 4.54; 95% CI: 1.12 - 18.24). Not being overweight reduced the chance for SB related to cell phone use (OR: 0.19; 95% CI: 0.03 - 0.95) and TV time (OR: 0.08; 95% CI: 0.01 - 0.45).
CONCLUSION: SB related to cell phone use was high among adolescents and associations with BMI and level of PA need to be considered for the development of interventions for SB prevention in adolescence.

Resumen:
OBJETIVO: Caracterizar indicadores de comportamiento sedentario (CS) en adolescentes escolares y verificar sus asociaciones con factores sociodemográficos, antropométrico y nivel de actividad física (AF).
MÉTODOS: Participaron del estudio 104 adolescentes (63.3% sexo femenino, 16.43 ± 0.98 años) del municipio de Sombrio - SC. Los indicadores de CS (uso d TV, juegos, usar computador y celular en los días de semana y fines de semana) fueron categorizados como ≤ 2 y > 2 horas/día. Se consideró como variables independientes: sexo, escolaridad de los padres, tipo de escuela, índice socioeconómico, índice de masa corporal y nivel de AF. Una regresión logística multivariada fue utilizada para determinar las asociaciones (p<0.05).
RESULTADOS: El CS relacionado al uso del celular fue el más prevalente y presentar nivel de AF insuficiente aumentó las posibilidades para este comportamiento (OR: 3.42; IC95%: 1.15 - 10.16). Ser del sexo femenino aumentó la posibilidad para el uso de TV (OR: 4.54; IC95%: 1.12 - 18.24). No presentar exceso de peso redujo la posibilidad para el CS relacionado al uso del celular (OR: 0.19; IC95%: 0.03 - 0.95) y el tiempo de TV (OR: 0.08; IC95%: 0.01 - 0.45).
CONCLUSIÓN: El CS relacionado al celular fue alto entre los adolescentes y las asociaciones con el IMC y con el nivel de AF necesitan ser consideradas para la elaboración de intervenciones para prevención de CS en la adolescencia.

Resumo:
OBJETIVO: Caracterizar indicadores de comportamento sedentário (CS) em adolescentes escolares e verificar suas associações com fatores sociodemográficos, antropométrico e nível de atividade física (AF).
MÉTODOS: Participaram do estudo 104 adolescentes (63.3% sexo feminino, 16.43 ± 0.98 anos) do município de Sombrio - SC. Os indicadores de CS (uso da TV, jogos, usar computador e celular nos dias de semana e finais de semana) foram categorizados como ≤ 2 e > 2 horas/dia. Considerou-se como variáveis independentes: sexo, escolaridade dos pais, tipo de escola, índice socioeconômicos, índice de massa corporal e nível de AF. Uma regressão logística multivariada foi utilizada para determinar as associações (p< 0.05).
RESULTADOS: O CS relacionado ao uso do celular foi o mais prevalente, e apresentar nível de AF insuficiente aumentou as chances para este comportamento (OR: 3.42; IC95%: 1.15 - 10.16). Ser do sexo feminino aumentou a chance para o uso da TV (OR: 4.54; IC95%: 1.12 - 18.24). Não apresentar excesso de peso reduziu a chance para o CS relacionado ao uso do celular (OR: 0.19; IC95%: 0.03 - 0.95) e o tempo de TV (OR: 0.08; IC95%: 0.01 - 0.45).
CONCLUSÃO: O CS relacionado ao celular foi elevado entre os adolescentes e as associações com o IMC e com o nível de AF precisam ser consideradas para a elaboração de intervenções para prevenção do CS na adolescência.

INTRODUCTION

Sedentary behavior (CS) is characterized by activities performed in the sitting, reclining or lying position and with energy expenditure of 1.5 MET1 or less (metabolic equivalent). Each MET is equivalent to a baseline O2 consumption of 3.5 ml/Kg.min.

Different types of CS include moving in transport, working in the sitting position and a set of behaviors usually characterized as "screen time," such as using a telephone and computer, watching television (TV) and playing video games2.

In adolescence, there are intense physical and psychological changes, characterizing a relevant time for the study of CS3. In addition, it has been demonstrated that several markers of CS have an impact on health outcomes such as obesity, hypertension, and hypercholesterolemia, low levels of self-esteem, social behavior problems, physical fitness and academic performance4.

There are no national recommendations on the minimum time to spend on CS5. However, Brazilian studies6-7 often follows international recommendations, which suggest that adolescents limit this time to less than two hours per day. This cut-off point is well established for the behaviors of watching TV, playing video games and using the computer. However, such devices do not fully represent the sedentary opportunities available to young people, since the use of mobile media, such as smartphones and tablets, is currently increasing among this population8.

The Health Behavior in School-Age Children (HBSC) report found that 56% to 65% of youths spent two hours or more a day watching TV. In turn, the National School Health Survey (PeNSE) estimated prevalence of 78% for this behavior. According to Barbosa et al.9, in 60% of the studies analyzed in their systematic review, the prevalence of excessive TV time was greater than 50% in Brazilian adolescents.

According to Guerra et al.2, studies have shown a positive association between longer screen time and low level of physical activity (AF) and higher intake of caloric foods. However, there are uncertain relationships with socioeconomic status and demographic factors, such as age and sex. These conflicting results can be justified by the heterogeneity of the cutoff points used to define the excessive screen time, as well as by the evaluation tools used, and the study drawings. In addition, there is a shortage of studies that evaluate the CS exploring other indicators such as the time of use of cell phones and tablets.

This is the first generation of teenagers created entirely in the digital age, which has repercussions on a lifestyle centered on technological devices. Although increasing access to such devices is evident, there is no consensus in the literature about which variables are associated with this type of CS. Therefore, it is necessary to contribute to the understanding of these associations and, from this, to increase the evidence on the implications of exposure to these behaviors and to encourage the development of preventive health interventions.

Thus, the objective of this study was to characterize four CS indicators in school adolescents and to verify their associations with sociodemographic, anthropometric and physical activity (FA) factors.


METHOD

An observational, cross-sectional, observational study was performed. The sample consisted of adolescents of both sexes, aged 14 to 19 years, regularly enrolled in high school (1st, 2nd and 3rd years) of two state public schools and one private school in the municipality of Sombrio (Santa Catarina State ). According to the Brazilian Institute of Geography and Statistics (IBGE), the municipality has three public schools and one private school, and in 2015 it had 1,197 students enrolled in high school.

For the study, it was chosen to include in the sample 10% of the enrolled students. The selection of public schools included in the study was performed by means of a random lottery. Eligible students were those present in the classroom on the day of data collection. The exclusion criteria adopted were: age less than 14 years and over 19 years and present mental and / or audiovisual limitations. Referees were considered as students who didn´t sign the agreement or didn´t deliver the free and informed consent form signed by the parents. Those who didn´t attend the classroom on the day of collection were considered as losses.

Instruments

Information on sociodemographic aspects, CS and AF practice were extracted from a questionnaire elaborated in partnership with the Research and Physical Activity and Health Center of the Federal University of Santa Catarina, based on the questionnaire Behaviors of Adolescents Catarinenses (COMPAC)10. SPHYNXR software (Sphynx Software Solutions Incorporation, Washington, USA) was used for the optical reading of the questionnaires.

To measure the body mass of participants, a digital scale (Glass 200 G-Tech, Zhongshan, China) was used, and the stature was determined by a portable stadiometer (Sanny, São Paulo, Brazil).

Procedures

Data collection took place from September to November 2016 with the participation of a team previously trained to apply the collection instruments. For the anthropometric evaluation, the technical error of measurement (ETM) was used and a standard deviation of ± 2 was considered acceptable. To do this, researchers involved in data collection evaluated 10 adolescents at two different times, with a minimum interval of seven days and a maximum of 15 days. The measures of the most experienced evaluator were considered as gold standard.

Prior to the application of the questionnaire, the students were instructed to complete each section of the questionnaire. The application time was 40 to 50 minutes on average.

The socio-demographic variables analyzed in this study were: gender, age in complete years, schooling of the father and mother, index of goods and type of school (public or private). The index of goods was determined based on the methodology of the Brazilian Association of Research Companies (ABEP), which considers the presence of material goods and monthly employees in the residence. It was calculated taking into account the different weights of the assets proposed by ABEP, with 0 being the minimum score and 87 being the maximum possible score. The schooling of the father and the mother was determined by the question "Mark the alternative that best represents the level of study of his father and his mother", with the following categories of answers: never studied, didn´t finish elementary school, finished elementary school , didn´t complete high school, completed high school, didn´t complete college, the college concluded.

The CS was operated from four indicators (average daily time spent watching TV, playing video games and/or using the computer to play, using the computer without being to play and using cell phones), evaluated separately for weekdays and weekend . CS was defined as spending more than two hours doing each of these activities2.

To measure the level of PA, the adolescents reported how often (times/week) and duration per day (hours/minutes) they practiced different activities of moderate to vigorous intensity. In order to characterize adolescents as active and insufficiently active, World Health Organization (WHO) criteria were used11.

After completing the questionnaire, body mass and height were measured. From the measurements obtained, the body mass index (BMI) was calculated, which was categorized according to gender and age and expressed as a z score on the WHO reference curve12. The BMI was later classified as "non-overweight" (normal weight, lean and lean) and "overweight" (overweight and obese).

The research was approved by the Committee of Ethics in Research with Human Beings of the institution under the number CAAE 66721517.2.0000.0121.

Statistical analysis

For data analysis, descriptive statistics were initially performed, followed by bivariate analysis. Multivariate logistic regression was used to identify the independent factors associated with CS. Regression models were constructed that had as dependent variable each of the four CS indicators during the week and at the end of the week (binary categorical outcome: no CS - > 2 hours / day and CS -> 2 hours / day), and as (female and male), schooling of the father and the mother (Incomplete Elementary School, Complete Elementary School or Incomplete High School, Complete Secondary or Complete or Incomplete Higher Education), type of school (Public or Private) ), index of assets (categorized in tertile), BMI (not overweight and overweight), and FA level (insufficiently active and active). The results were expressed in Odds ratio (OR). Statistical analysis was performed using the statistical package SPSS (Statistical Package for the Social Sciences) version 17.0.


RESULTS

Of the 175 potentially eligible adolescents, 104 participated in the study, whose mean age was 16.43 ± 0.98 years. As shown in Table 1, 63.5% were female, 82.7% were in a public school, 68.3% were insufficiently active, 17.2% were overweight or obese, and 26.4% were fathers, and 45.3% of mothers completed at least high school.




Figures 1 and 2 show the percentages of adolescents according to recommended screen time (≤2 hours/day) and not recommended (> 2 hours / day) for use of TV, games (on computer and video games), computer use without being to play and mobile during the week and at the end of the week. Higher percentages were observed related to the use of cell phones and TV during the week and at the end of the week. The time spent playing games on the computer or video game was the behavior with lower percentages for both weekdays and weekends.


Figure 1. Percentage of adolescents in sedentary behavior on weekdays according to time spent (≤ 2 hours and> 2 hours / day), Sombrio (SC), Brazil, 2016. N = 104



Figure 2. Percentage of adolescents according to time spent (≤ 2 hours and> 2 hours / day) in sedentary behavior at the weekend, Sombrio (SC), Brazil, 2016. N = 104



Tables 2 and 3 present the results of logistic regression for association between CS of watching TV and cell phone use on weekdays and weekend days, respectively, and sociodemographic, anthropometric and AF levels. In this regression, the information regarding 86 adolescents was used, due to the occurrence of missing data.






It was possible to observe a statistically significant association between sex and CS relative to TV time (p = 0.034). Being female increased the chance (OR = 4.52; 95% CI = 1.12 - 18.24) of spending time exceeding two hours watching TV on weekdays. In addition, an association was found between the BMI variable and the CS regarding cell phone use on weekdays. Individuals without excess weight had a reduced chance of spending more than two hours using cell phones during the days of the week (OR = 0.19; 95% CI = 0.03 - 0.95) (Table 2).

CS related to the habit of watching TV on weekends was associated with BMI. Individuals who were not overweight were less likely to spend more than two hours watching TV (OR = 0.08; 95% CI = 0.01 - 0.45). In addition, excessive time related to cell phone use at the weekend was significantly associated with the level of AF. Adolescents with insufficient AF level were more likely to spend more than two hours adopting such behavior (OR = 3.42, 95% CI = 1.15 - 10.16) (Table 3).

Statistically significant associations (p > 0.05) were not observed between the other CS types on weekdays and weekends and the independent variables investigated in the present study.


DISCUSSION

The main results of the present study were: 1) Among the four CS indicators related to screen time, higher percentages were observed for cell phone use during the week and at the weekend. 2) It was found that being female increased the chance of spending time above the recommended (> 2 hours/day) watching TV. 3) Not being overweight has reduced the chances of spending excessive time for cell phone use on weekdays. 4) For the weekends, it was observed that not being overweight reduced the chances of spending excessive time watching TV, while the level of insufficient AF increased the chances of adopting the CS relative to the use of the cell phone.

Regarding the CS indicators related to screen time analyzed, there was a highlight for "cell phone use" activity, which reached values of 63.4% on weekdays and 60.6% on weekends. Although high rates for this CS were observed, these results are lower than those reported in a previous study, which reported a rate of 88.2% of this behavior13. The high prevalence of CS among adolescents may be justified by the technological growth of Brazil. With the advent of the digital age, a new way of life has been configured and activities that were previously active were gradually replaced by the use of tablets and cell phones, especially in large urban centers9.

The use of mobile devices, including cell phones, contributes significantly to the reduction of energy expenditure among adolescents and is among the main environmental determinants of obesity and overweight in adolescents14. Thus, the data collected in this study indicated that adolescents with adequate BMI are less likely to spend more than two hours a week using the mobile phone. These findings reinforce those found by Kenney and Gortmaker, 15 who found that adolescents who spent more than five hours using screen devices (smarthphones, tablets, computers and/or video games), with the exception of TV, had a higher risk of developing obesity.

In the present study, female adolescents were more likely to spend time than recommended watching TV on weekdays. Similarly, a study conducted in 56 public schools in Pelotas (RS) with a sample of 8,661 students found positive associations between female sex and TV time16. On the other hand, Lucena et al.6, showed that male adolescents belonging to the higher economic classes presented higher chances of exposure to the time than recommended watching TV. One of the reasons for this disagreement may be the different cutoff points used to categorize CS related to the use of TV2.

In this study, subjects who were not overweight were less likely to spend more than two hours watching TV on weekends. Similar results were found in the study by Júnior et al.17, conducted with adolescents of similar age, in which the habit of watching TV for two hours or more was associated with the prevalence of overweight and obesity. In contrast to these findings, Biddle et al.18 concluded that the associations between CS and adiposity in adolescents are still weak and there is little or no evidence that this association is causal.

Silva et al.19 verified a prevalence of insufficient levels of AF above 50% in 8 of the 16 studies conducted with Brazilian adolescents, demonstrating the need to elaborate public policies focused on promoting healthy life habits in youth. At this stage of life, frequent CS adoption, such as cell phone use, increases the chances of having lower levels of AF. Data found in the present study reinforce these assertions, since schoolchildren with insufficient AF level presented increased chances of spending more than two hours using the cellphone at weekends. Similarly, study conducted with American college students found negative association between cell phone use and physical fitness. Individuals who used mobile phones more frequently were more likely to give up physical activity opportunities and preferred to adopt more sedentary activities such as accessing Facebook and Twitter, surfing the internet, playing games, and using apps13. Although there are still few studies that evaluate separately the behavior "cellular use" and its influence on the individual's level of AF, it is already described in the literature that the reduction of the time spent with the sedentary activities is a strategy to reduce the physical inactivity20.

Some limitations should be considered when interpreting the results of the present study. First, the exposures and data presented were based on self-report measures and the estimates may have been under or overestimated. Most of the sampled adolescents belong to the public school system. Data were collected in a specific region of Brazil, and the students included in the sample may not represent the adolescent population as a whole. In addition, the absence of other statistical significance may have occurred by the sample number evaluated.

Finally, this study presented as a strong point the measurement of CS related to screen time in addition to the commonly investigated electronic devices (TV, video games and computer). Mobile media has dominated different age groups and replaced old forms of entertainment and leisure in a growing way. Therefore, the inclusion of cell phone use in this and future studies is important for the research to fit the current technological scenario.


CONCLUSION

Among CS indicators, cell phone use was the most frequent among adolescents, both on weekdays and on weekends. In addition, the use of cell phones and TV was associated with modifiable aspects through health interventions such as the level of AF and BMI. Therefore, the results obtained can contribute to the elaboration of actions aimed at reducing this behavior among adolescents.

It is important to investigate the associations regarding the use of mobile media devices, such as mobile phones, as these have become an alternative platform for viewing content previously restricted to TV sets. Therefore, to amplify the evidences regarding the use of these devices is necessary in order to recognize the impacts that these provide to the health and the habits acquired in adolescence.


ACKNOWLEDGMENTS

We thank the team that participated in the data collection, the adolescents, parents, the schools of the municipality of Sombrio and the Research and Physical Activity and Health Center of UFSC.


FINANCIAL SUPPORT

National Council of Scientific and Technological Development (CNPq), Call MCTI / CNPQ / UNIVERSAL 14/2014 - Case 456567/2014-3. Student Vanessa de Souza Vieira received a scholarship from the Institutional Scholarship Program for Initiation in Scientific Research (PIBIC/CNPq). The student Susana da Costa Aguiar received a scholarship from the Coordination for the Improvement of Higher Education Personnel (CAPES) and the University Scholarship Program of Santa Catarina.


REFERENCES

1. Tremblay MS, Aubert S, Barnes JD, Saunders TJ, Carson V, Latimer-Cheung AE, et al. Sedentary Behavior Research Network (SBRN) - Terminology Consensus Project process and outcome. Int J Behav Nutr Phys Act. 2017;14(1):75.

2. Guerra PH, Júnior JCF, Florindo AA. Sedentary behavior in Brazilian children and adolescents: a systematic review. Rev Saúde Pub. 2016;50(9):1-15.

3. Qidwai W, Ishaque S, Shah S, Rahim M. Adolescent lifestyle and behaviour: a survey from a developing country. PLoS One. 2010;5(9): e12914.

4. Carson V, Hunter S, Kuzik N, Gray CE, Poitras VJ, Chaput JP, et al. Systematic review of sedentary behaviour and health indicators in school-aged children and youth: an update. Appl Physiol Nutr Metab. 2016;41(6 Suppl 3):S240-65.

5. Nardo N, J., Silva DA, Ferrari GLDM, Petroski EL, Pacheco RL, Martins PC, et al. Results From Brazil's 2016 Report Card on Physical Activity for Children and Youth. J Phys Act Health. 2016;13(11 Suppl 2): S104-9.

6. Lucena JMSD, Cheng LA, Cavalcante TLM, Silva VAD, Farias Júnior JCD. Prevalence of excessive screen time and associated factors in adolescents. Rev Paul Pediatr. 2015;33(4):407-14.

7. Sousa GRD, Silva DAS. Sedentary behavior based on screen time: prevalence and associated sociodemographic factors in adolescents. Ciên Saúde Colet. 2017;22(12):4061-72.

8. Odiaga JA, Doucette J. Technological Media and Sedentary Behavior in Pediatrics. J Nurse Pract. 2017;13(1):72-8.

9. Barbosa VCF, Campos WD, Lopes ADS. Epidemiology of physical inactivity, sedentary behaviors, and unhealthy eating habits among Brazilian adolescents. Ciên saúde colet. 2014;19(1):173-94.

10. Silva KSD, Lopes ADS, Hoefelmann LP, Cabral LGDA, De Bem MFL, Barros MVGD, et al. Projeto COMPAC (comportamentos dos adolescentes catarinenses): aspectos metodológicos, operacionais e éticos. Rev bras cineantropom desempenho hum. 2013;15(1):1 -15.

11. WHO. Global recommendations on physical activity for health: World Health Organization; 2015. Disponível em: http://www.who.int/dietphysicalactivity/factsheet_recommendations/en/.

12. WHO. Obesity and overweight: World Health Organization; 2017. Disponível em: http://www.who.int/mediacentre/factsheets/fs311/en/.

13. Lepp A, Barkley JE, Sanders GJ, Rebold M, Gates P. The relationship between cell phone use, physical and sedentary activity, and cardiorespiratory fitness in a sample of U.S. college students. Int J Behav Nutr Phys Act. 2013;10(79):2-9.

14. Camargo APPDMD, Barros Filho ADA, Antonio MÂRDGM, Giglio JS. The non-perception of obesity can be an obstacle to the role of mothers in taking care of their children. Ciên saúde colet. 2013;18(2):323-33.

15. Kenney EL, Gortmaker SL. United States Adolescents' Television, Computer, Videogame, Smartphone, and Tablet Use: Associations with Sugary Drinks, Sleep, Physical Activity, and Obesity. J Pediatr. 2017;182:144-9.

16. Ferreira RW, Rombaldi AJ, Ricardo LIC, Hallal PC, Azevedo MR. Prevalence of sedentary behavior and its correlates among primary and secondary school students. Rev Paul Pediatr. 2016;34(1):56-63.

17. Júnior LMS, Santos AP, Souza OF, Farias ES. Prevalence of excess weight and associated factors in adolescents of private schools of an Amazonic urban area, Brazil. Rev Paul Pediatr. 2012;30(2):217-22.

18. Biddle SJ, Garcia BE, Wiesner G. Sedentary behaviour and adiposity in youth: a systematic review of reviews and analysis of causality. Int J Behav Nutr Phys Act. 2017 Mar;14(1):43.

19. Silva KSD, Nahas MV, Hoefelmann LP, Lopes ADS, Oliveira ESD. Associações entre atividade física, índice de massa corporal e comportamentos sedentários em adolescentes. Rev Bras Epidemiol. 2008;11(1):159-68.

20. Koezuka N, Koo M, Allison KR, Adlaf EM, Dwyer JJ, Faulkner G, et al. The relationship between sedentary activities and physical inactivity among adolescents: results from the Canadian Community Health Survey. J Adolesc Health. 2006;39(4):515-522.
adolescencia adolescencia adolescencia
GN1 © 2004-2019 Revista Adolescência e Saúde. Fone: (21) 2868-8456 / 2868-8457
Núcleo de Estudos da Saúde do Adolescente - NESA - UERJ
Boulevard 28 de Setembro, 109 - Fundos - Pavilhão Floriano Stoffel - Vila Isabel, Rio de Janeiro, RJ. CEP: 20551-030.
E-mail: revista@adolescenciaesaude.com