ABSTRACT:

Introduction:

Active commuting to school could help increasing physical activity levels among adolescents. However, there is limited understanding on how the relationship between the environment in school surroundings, as well the distance to school, could affect this behavior.

Aim:

To analyze the characteristics of the environment and distance between house and school with objective measures and their association with active commuting between adolescents of Curitiba, Brazil.

Methods:

493 adolescents were interviewed and 124 schools evaluated. The study variables included the schools’ surroundings accessibility characteristics obtained through systematic observation, and the distance between home to school was determined through Geographic Information Systems (GIS) data.

Results:

The presence of “safety signs” was inversely associated with active commuting (PR = 0.78; 95%CI 0.67-0.91; p = 0.003), as well distance 1,501-3,000 m (PR = 0.53; 95%CI 0.40 - 0.71; p < 0.001) and ≥ 3,501 m (PR 0.29; 95%CI 0.18 - 0.45; p < 0.001). Overall, schools’ surroundings showed walking friendly characteristics.

Conclusion:

Traffic safety and distance to school were associated with active commuting to school among the study participants. Policies aiming at integrating access to school and traffic safety could help to promoting active commuting among adolescents.

Keywords:
Exercise; Transportation; Geographic information systems; Schools; Adolescent

INTRODUCTION

Active commuting to school is an important means of promoting physical activity for adolescents¹1. Panter JR, Jones AP, van Sluijs EM. Environmental determinants of active travel in youth: a review and framework for future research. Int J Behav Nutr Phys Act 2008; 5: 34. https://doi.org/10.1186/1479-5868-5-34
https://doi.org/https://doi.org/10.1186/... and health promotion²2. Janssen I, Leblanc AG. Systematic review of the health benefits of physical activity and fitness in school-aged children and youth. Int J Behav Nutr Phys Act 2010; 7: 40. https://doi.org/10.1186/1479-5868-7-40
https://doi.org/https://doi.org/10.1186/... . This behavior is extremely relevant, since eight out of ten adolescents do not meet the recommended levels of physical activity³3. Sallis JF, Bull F, Guthold R, Heath GW, Inoue S, Kelly P, et al. Progress in physical activity over the Olympic quadrennium. Lancet 2016; 388(10051): 1325-36. https://doi.org/10.1016/S0140-6736(16)30581-5
https://doi.org/https://doi.org/10.1016/... ^,44. World Health Organization. Global recommendations on physical activity for health [Internet]. World Health Organization; 2010 [acessado em 16 abr. 2014]. Disponível em: Disponível em: http://whqlibdoc.who.int/publications/2010/9789241599979_eng.pdf
http://whqlibdoc.who.int/publications/20... . Thus, actions such as walking and/or cycling to school can contribute to increasing the time spent in active behaviors⁵5. Yang X, Telama R, Hirvensalo M, Tammelin T, Viikari JS, Raitakari OT. Active commuting from youth to adulthood and as a predictor of physical activity in early midlife: the young Finns study. Prev Med 2014; 59: 5-11. https://doi.org/10.1016/j.ypmed.2013.10.019
https://doi.org/https://doi.org/10.1016/... .

In some Brazilian cities, active commuting is carried out by less than half of adolescents. In Florianópolis, for example, only 41% actively commute to school⁶6. Costa FF, Silva KS, Schmoelz CP, Campos VC, de Assis MA. Longitudinal and cross-sectional changes in active commuting to school among Brazilian schoolchildren. Prev Med 2012; 55(3): 212-14. https://doi.org/10.1016/j.ypmed.2012.06.023
https://doi.org/https://doi.org/10.1016/... . On the other hand, in Pernambuco, 43% of adolescents were considered physically inactive when commuting to school⁷7. Santos CM, Wanderley Júnior RS, Barros SSH, Farias Júnior JC, Barros MVG. Prevalência e fatores associados à inatividade física nos deslocamentos para escola em adolescentes. Cad Saúde Pública 2010; 26(7): 1419-30. https://doi.org/10.1590/S0102-311X2010000700021
https://doi.org/https://doi.org/10.1590/... , which exposes a variation in this prevalence between the regions of Brazil⁶6. Costa FF, Silva KS, Schmoelz CP, Campos VC, de Assis MA. Longitudinal and cross-sectional changes in active commuting to school among Brazilian schoolchildren. Prev Med 2012; 55(3): 212-14. https://doi.org/10.1016/j.ypmed.2012.06.023
https://doi.org/https://doi.org/10.1016/... ^,77. Santos CM, Wanderley Júnior RS, Barros SSH, Farias Júnior JC, Barros MVG. Prevalência e fatores associados à inatividade física nos deslocamentos para escola em adolescentes. Cad Saúde Pública 2010; 26(7): 1419-30. https://doi.org/10.1590/S0102-311X2010000700021
https://doi.org/https://doi.org/10.1590/... ^,88. Silva KS, Vasques DG, Martins C de O, Williams LA, Lopes AS. Active commuting: prevalence, barriers, and associated variables. J Phys Act Health 2011; 8(6): 750-7. https://doi.org/10.1123/jpah.8.6.750
https://doi.org/https://doi.org/10.1123/... ^,99. Silva KS, Lopes AS, Silva FM. Walking to school and leisure time among children and adolescents from João Pessoa, PB. Rev Bras Ciênc Mov 2007; 15(3): 61-70..

Some programs to encourage active commuting, such as Caminho da Escola¹⁰10. Brasil. Programa Caminho da Escola. Fundo Nacional de Desenvolvimento da Educação [Internet]. [acessado em 31 ago. 2015]. Disponível em: Disponível em: http://www.fnde.gov.br/programas/caminho-da-escola/caminho-da-escola-apresentacao/caminho-da-escola-historico
http://www.fnde.gov.br/programas/caminho... , Bicicleta na Escola¹¹11. Prefeitura de Florianópolis. Projeto Bicicleta na Escola [Internet]. Prefeitura de Florianópolis [acessado em 31 ago. 2015]. Disponível em: Disponível em: http://www.pmf.sc.gov.br/entidades/educa/index.php?cms=projetos+da+secretaria+municipal+de+educacao
http://www.pmf.sc.gov.br/entidades/educa... and the Bicicleta no seu Bairro¹²12. Prefeitura de Curitiba. Projeto Bicicleta no Seu Bairro [Internet]. Prefeitura de Curitiba; 2015 [acessado em 29 jul. 2015]. Disponível em: http://www.curitiba.pr.gov.br/noticias/projeto-bicicleta-no-seu-bairro-promove-atividades-na-fazendinha/36737
http://www.curitiba.pr.gov.br/noticias/p... projects have been implemented to encourage walking and/or cycling among children and adolescents. However, the success of these programs still depends on the presence of attributes of the built environment, such as bike paths and bike lanes, sidewalks in good condition, and road signs, especially in the streets surrounding schools¹³13. D’Haese S, De Meester F, De Bourdeaudhuij I, Deforche B, Cardon G. Criterion distances and environmental correlates of active commuting to school in children. Int J Behav Nutr Phys Act 2011; 8: 88. https://doi.org/10.1186/1479-5868-8-88
https://doi.org/https://doi.org/10.1186/... ^,1414. Nelson NM, Foley E, O’Gorman DJ, Moyna NM, Woods CB. Active commuting to school: how far is too far? Int J Behav Nutr Phys Act 2008; 5: 1. https://doi.org/10.1186/1479-5868-5-1
https://doi.org/https://doi.org/10.1186/... ^,1515. Chillón P, Panter J, Corder K, Jones AP, Van Sluijs EM. A longitudinal study of the distance that young people walk to school. Health Place 2015; 31: 133-7. https://dx.doi.org/10.1016%2Fj.healthplace.2014.10.013
https://doi.org/https://dx.doi.org/10.10... . Furthermore, the distance to services and leisure spaces in the community, in addition to the distance traveled by teenagers to school¹³13. D’Haese S, De Meester F, De Bourdeaudhuij I, Deforche B, Cardon G. Criterion distances and environmental correlates of active commuting to school in children. Int J Behav Nutr Phys Act 2011; 8: 88. https://doi.org/10.1186/1479-5868-8-88
https://doi.org/https://doi.org/10.1186/... ^,1414. Nelson NM, Foley E, O’Gorman DJ, Moyna NM, Woods CB. Active commuting to school: how far is too far? Int J Behav Nutr Phys Act 2008; 5: 1. https://doi.org/10.1186/1479-5868-5-1
https://doi.org/https://doi.org/10.1186/... ^,1515. Chillón P, Panter J, Corder K, Jones AP, Van Sluijs EM. A longitudinal study of the distance that young people walk to school. Health Place 2015; 31: 133-7. https://dx.doi.org/10.1016%2Fj.healthplace.2014.10.013
https://doi.org/https://dx.doi.org/10.10... , are factors related to the chosen mode of commuting.

Most studies that have sought to understand the relationship between these factors of the neighborhood’s built environment and active commuting were conducted in high-income countries with environmental and social characteristics that are different from Brazil¹⁶16. D’Haese S, Vanwolleghem G, Hinckson E, De Bourdeaudhuij I, Deforche B, Van Dyck D, et al. Cross-continental comparison of the association between the physical environment and active transportation in children: a systematic review. Int J Behav Nutr Phys Act 2015; 12: 145. https://doi.org/10.1186/s12966-015-0308-z
https://doi.org/https://doi.org/10.1186/... . For example, Brazilian cities have been affected by the sharp increase in private motorized transport, by the increase in public transport fares¹⁷17. Carvalho CHR, Pereira RHM. Efeitos da variação da tarifa e da renda da população sobre a demanda de transporte público coletivo urbano no Brasil. Transportes 2012; 20(1): 31-40. https://doi.org/10.4237/transportes.v20i1.464
https://doi.org/https://doi.org/10.4237/... , and by the precarious or lack of bicycling infrastructure¹⁸18. Debatin Neto MBA, Olkeszechen N. Barreiras e facilitadores no uso da bicicleta em deslocamentos diários: alternativas para a mobilidade urbana. Rev Ciên Humanas 2017; 51(1): 269-86. https://doi.org/10.5007/2178-4582.2017v51n1p269
https://doi.org/https://doi.org/10.5007/... . In addition, the majority of available studies use only the perceptions of environmental attributes and distance to school, which do not permit the verification of factors of the built environment that can contribute positively or negatively with the outcome, making the findings inconsistent. Thus, the objective of this study was to analyze the association between characteristics of the environment around the school, distance from the residence, and the active commuting of adolescents from Curitiba, Brazil.

METHODS

DESIGN, CHARACTERISTICS OF THE STUDY AND ETHICAL ASPECTS

The study had a cross-sectional design through a household survey¹⁸18. Debatin Neto MBA, Olkeszechen N. Barreiras e facilitadores no uso da bicicleta em deslocamentos diários: alternativas para a mobilidade urbana. Rev Ciên Humanas 2017; 51(1): 269-86. https://doi.org/10.5007/2178-4582.2017v51n1p269
https://doi.org/https://doi.org/10.5007/... and an observational study conducted in the city of Curitiba, Paraná. The city has 1,851,215 inhabitants²⁰20. Prefeitura Municipal de Curitiba. Perfil da cidade de Curitiba [Internet]. Prefeitura Municipal de Curitiba [acessado em 3 out. 2017]. Disponível em: Disponível em: https://www.curitiba.pr.gov.br/conteudo/perfil-da-cidade-de-curitiba/174
https://www.curitiba.pr.gov.br/conteudo/... and is mainly recognized for its urban planning and green areas²¹21. Moysés SJ, Moysés ST, Krempel MC. Avaliando o processo de construção de políticas públicas de promoção de saúde: a experiência de Curitiba. Ciênc Saúde Coletiva 2004; 9(3): 627-41. https://doi.org/10.1590/S1413-81232004000300015
https://doi.org/https://doi.org/10.1590/... . The data of the present study are part of an international multicentric project called International Physical Activity and the Environment Network (IPEN), which is carried out in 19 countries, with similar data collection protocol and measures²²22. International Physical Activity and The Environment Network. IPEN Project [Internet]. [acessado em 20 maio 2013]. Disponível em: Disponível em: http://www.ipenproject.org
http://www.ipenproject.org... . In Brazil, data collection was performed in the city of Curitiba, Paraná, between the months of August 2013 and May 2014. The project was approved by the Research Ethics Committee (CEP) of the Pontifícia Universidade Católica do Paraná (PUC-PR).

SELECTION OF LOCATIONS

Altogether, there were 2,395 census sectors in Curitiba²³23. Instituto Brasileiro de Geografia e Estatística. Censo 2010 [Internet]. [acessado em 15 jun. 2013]. Disponível em: Disponível em: https://censo2010.ibge.gov.br/
https://censo2010.ibge.gov.br/... , and it was considered the primary sampling unit. To maximize the variability of the data, the extremes of walkability and neighborhood income²⁴24. Hino AAF, Rech CR, Gonçalves PB, Hallal PC, Reis RS. Projeto ESPAÇOS de Curitiba, Brazil: applicability of mixed research methods and geo-referenced information in studies about physical activity and built environments. Rev Panam Salud Pública 2012; 32(3): 226-33. https://doi.org/10.1590/s1020-49892012000900008
https://doi.org/https://doi.org/10.1590/... were selected according to data from the Brazilian Institute of Geography and Statistics (Instituto Brasileiro de Geografia e Estatística - IBGE)²³23. Instituto Brasileiro de Geografia e Estatística. Censo 2010 [Internet]. [acessado em 15 jun. 2013]. Disponível em: Disponível em: https://censo2010.ibge.gov.br/
https://censo2010.ibge.gov.br/... . Walkability represents characteristics of the environment that can favor the practice of physical activity, defined by the sum of at least three attributes: residential density, street connectivity and mixed land use²⁵25. Reis RS, Hino AAF, Rech CR, Kerr J, Hallal PC. Walkability and Physical Activity: Findings from Curitiba, Brazil. Am J Prev Med 2013; 45(3): 269-75. https://doi.org/10.1016/j.amepre.2013.04.020
https://doi.org/https://doi.org/10.1016/... . The variables were ordered in deciles and the combinations of the extremes called quadrants were defined: low income and low walkability; low income and high walkability; high income and low walkability; and high income and high walkability. In order to obtain a spatially representative sample, eight census sectors in each quadrant were intentionally selected, totaling the 32 necessary for the study.

SELECTION OF RESIDENCES AND PARTICIPANTS

To select the residences, blocks were considered secondary sampling units. The enrollment process was carried out on all of the blocks, and the first was located at the southwest end of the sector. The residences were approached from the upper left side of the block (all houses present, one by one in a clockwise direction). In case of refusal or if a teenager did not reside there, the next house on the left was visited. In each household, an adolescent and a guardian were selected. The criteria for the selection of adolescents were: female - the youngest and male - the oldest, thus allowing for equal selection between the sexes. If the adolescent refused, another member of the same residence could be invited to the study voluntarily. The minimum sample for the project was 300 adolescents²²22. International Physical Activity and The Environment Network. IPEN Project [Internet]. [acessado em 20 maio 2013]. Disponível em: Disponível em: http://www.ipenproject.org
http://www.ipenproject.org... .

Adolescents aged between 12 and 17 years old, living in the city of Curitiba, Paraná, were considered eligible, specifically in the selected census sectors, for at least one year. Furthermore, the teenager had tto study at a school located in the city of Curitiba and not have any physical and/or cognitive limitations that would make physical activity impossible.

HOUSEHOLD SURVEY

The household survey was conducted in two stages. First, an invitation was made for the adolescent and their guardian to participate, and the interview was scheduled. Second, the interviews (guardians and adolescents) were carried out on the days and times previously scheduled. For the guardians, a questionnaire was applied with 215 questions involving environmental characteristics, physical activity and demographic information. For the adolescents, the questionnaire had 285 questions about environment, physical activity, psychosocial aspects, sedentary behavior, occupation, school and sociodemographic information. All interviews were conducted by members of the Research Group on Physical Activity and Quality of Life (Grupo de Pesquisa em Atividade Física e Qualidade de Vida - GPAQ), who received 12-hour theoretical and practical training on the selection criteria, how to approach to residences, how to fill out the forms, how to apply the questionnaire, how to ask the questions, and the appropriate answers. A trial was carried out to simulate the data collection process and to solidify the procedures.

IDENTIFICATION OF SCHOOLS AND THE ASSESSMENT TOOL

The evaluation of the school environment occurred simultaneously with the household survey. The collection took place between the months of August 2013 and May 2014 in public and private schools in the city of Curitiba, Paraná. From the information obtained in the questionnaires in the household survey, the schools in which the adolescents studied were identified, namely: the name of the school, the managing body, address and telephone number. At the time, the city had 1,034 schools (212 municipal, 167 state and 655 private)²⁶26. Paraná. Secretaria Estadual de Educação. SEED em números [Internet]. Curitiba: Secretaria Estadual de Educação; 2013 [acessado em 03 set. 2017]. Disponível em: Disponível em: http://www4.pr.gov.br/escolas/numeros/index.jsp
http://www4.pr.gov.br/escolas/numeros/in... . For access to the institutions, the Municipal Education Secretariat (Secretaria Municipal de Educação - SME) and the Paraná State Education Secretariat (Secretaria Estadual de Educação do Paraná - SEED) were contacted, requesting permission for the research. In addition to the authorization of the secretariats, the school principals had to sign the Informed Consent Form (ICF). All schools selected in the study were located in the city of Curitiba, and offered elementary and/or high school education and included Physical Education in the curriculum. Schools that did not complete all stages of the assessment were excluded.

The school environment and its surroundings were assessed through systematic observation with the School Audit Tool instrument, developed by Jones et al.²⁷27. Jones NR, Jones A, van Sluijs EM, Panter J, Harrison F, Griffin SJ. School environments and physical activity: The development and testing of an audit tool. Health Place 2010; 16(5): 776-83. https://doi.org/10.1016/j.healthplace.2010.04.002
https://doi.org/https://doi.org/10.1016/... in the United Kingdom and adapted to the Brazilian context. Characteristics related to the practice of physical activity were observed and divided into four sections:

The variables of this study are contained in section B of this instrument, and were composed of 14 items. The evaluations were carried out by four independent researchers, who underwent an eight-hour theoretical-practical training.

INDEPENDENT VARIABLES

Characteristics of the environment around the school

The environment around the school was characterized by the structures present in the streets around the space where the school is physically located²⁷27. Jones NR, Jones A, van Sluijs EM, Panter J, Harrison F, Griffin SJ. School environments and physical activity: The development and testing of an audit tool. Health Place 2010; 16(5): 776-83. https://doi.org/10.1016/j.healthplace.2010.04.002
https://doi.org/https://doi.org/10.1016/... . These structures were independently assessed in the section “area around the school” (bike paths, bike lanes, sidewalk on both sides, sidewalk on one side, crosswalk, traffic lights or speed reducers, school signs, traffic signs and route signs for cyclists): “no” for not present and “yes” for present. For analysis purposes, the sidewalk variable was added and categorized as “no” for not present and “yes” for present. Thus, it is possible to understand how each variable is related to the outcome. Also, based on the sum of the individual items around the school, a general score was computed, divided into tertiles, and later classified as “low”, “medium” and “high”.

DISTANCE FROM HOME

The geocoding of the participants occurred based on the self-reported information of the street, such as street name, house number and postal code (CEP). To compose the distance variable, the geographic locations of the residence and the school were considered. Thus, calculating the shortest distance between them through the network of city streets was performed using the command “Network analyst> Route” in ArcGIS 10.0. ESRI^® software²⁸28. D’Sousa E, Forsyth A, Koepp J. Twin Cities Walking Study - Environment and Physical Activity: GIS Protocols. University of Minnesota and Cornell; 2007.. As there is no pre-established cutoff point to quantify the distances, the categorization of the variable was performed based on the findings in the literature. As such, three categories were assigned in this study: ≤ 1,500 m; 1,501- 3,500 m; and ≥ 3,501 m¹⁵15. Chillón P, Panter J, Corder K, Jones AP, Van Sluijs EM. A longitudinal study of the distance that young people walk to school. Health Place 2015; 31: 133-7. https://dx.doi.org/10.1016%2Fj.healthplace.2014.10.013
https://doi.org/https://dx.doi.org/10.10... .

DEPENDENT VARIABLE

The practice of active commuting to school was assessed by the question “In a normal school week, how many days and how much time during the day do you use the following means of commuting (to and from school)?”, considering active commuting: walking, riding a bicycle or using skates to go to and/or from school. For analysis purposes, this variable was dichotomized into: “Do not”, for those who did not actively commuting during the week, and “Do”, for those who did it ≥ 1 time per week. This classification is commonly used in the literature¹³13. D’Haese S, De Meester F, De Bourdeaudhuij I, Deforche B, Cardon G. Criterion distances and environmental correlates of active commuting to school in children. Int J Behav Nutr Phys Act 2011; 8: 88. https://doi.org/10.1186/1479-5868-8-88
https://doi.org/https://doi.org/10.1186/... ^,2929. Silva KS, Pizarro AN, Garcia LM, Mota J, Santos MP. Which social support and psychological factors are associated to active commuting to school? Prev Med 2014; 63: 20-3. https://doi.org/10.1016/j.ypmed.2014.02.019
https://doi.org/https://doi.org/10.1016/... .

COVARIABLES

The adolescent’s sex (“male”; “female”) was observed, and the age was classified into three age groups (“12-13 years”, “14-15 years” and “16-17 years”). Socioeconomic status was assessed with the questionnaire from the Brazilian Association of Research Companies (Associação Brasileira de Empresas de Pesquisa - ABEP)³⁰30. Associação Brasileira de Empresas de Pesquisa. Critério de classificação econômica Brasil [Internet]. Associação Brasileira de Empresas de Pesquisa [acessado em 18 out. 2017]. Disponível em: Disponível em: http://www.abep.org/
http://www.abep.org/... , which was later classified into seven levels. For the analysis, the participants were classified into three categories: “high” (class A), “medium” (class B) and “low” (class C + D + E). Vehicle ownership was assessed according to the number of vehicles present in the residence: “no”, when there were no vehicles, and “yes”, for ≥ 1 vehicle. The type of school administration was classified as “public” or “private”.

DATA ANALYSIS

The frequency distribution and χ² test for heterogeneity, linear trend and Fisher’s exact test were used to describe the characteristics of the sample. Poisson regression was used to test the crude association between the characteristics of the environment around the school, the distance from the residence and active commuting. In the adjusted analysis, the potential covariates identified in the crude analysis, with p <0.05, were inserted in the final model. The analyzes were performed using Statistical Package for the Social Science (SPSS) 20.0 and STATA 12.0 statistical software, with the significance level maintained at 5%.

RESULTS

Of the 930 adolescents eligible to participate in the project, 493 actually made up the final sample, with a refusal rate of 53.0%, distributed similarly between sex and neighborhood income. One hundred and sixty-three schools were identified, of which ten (6.1%) were ineligible and 29 (17.8%) refused to participate in the study. There was less refusal among public schools than among private schools (public 5.5% versus private 12.9%). The distribution of participants was balanced in terms of sex (girls = 51.2%), but the sample was predominantly composed of adolescents aged 12-13 years (43.1%), of the average socioeconomic level (65.2% ), from public schools (70.6%) and who owned at least one car at home (81.0%). At least three in four schools had at least one bus stop (84.8%), sidewalks (99.0%), pedestrian crossings (75.2%), speed reducers (80.4%), road signs (90.4%) and safety signs (96.3%). Approximately one in ten schools had bicycle paths (12.0%), bicycle lanes (1.5%) and signposting routes for cyclists (11.3%). Most participants lived less than 1,500 m from the school (55.9%) (Table 1).

Among adolescents who live up to 1,500m from school, the proportion of those who actively commute to school is higher among those enrolled in a public school (public 59.7% versus private 13.6%). Walking is more common among adolescents from public and private schools at distances <1,500 m (59.1 and 13.6%, respectively). In relation to the use of bicycles, for trips to public schools, they were more used in distances <1,500 m (1.5%), while for trips to private schools, the distances they were used was > 3,501 m (2.5%) (Figure 1).

The unadjusted analyzes indicated that the female sex (PR = 0.84; 95%CI 0.73 - 0.97; p = 0.024) and car ownership (PR = 0.70; 95%CI 0.60 - 0, 81; p <0.001) were inversely associated with active commuting, while the 14-15 age group (PR = 1.19; 95%CI 1.00 - 1.41; p = 0.044), the average socioeconomic levels (PR = 1.98; 95%CI 1.42 - 2.76; p <0.001) and low (PR = 2.78; 95%CI 2.00 - 3.86; p <0.001) and enrollment in a public school (PR = 2.40; 95%CI 1.79 - 3.23; p <0.001) were positively associated with the outcome (Table 2). Furthermore, the presence of bus stops (PR = 0.80; 95%CI 0.65 - 0.98; p = 0.039) and the distances between home and school of 1,500- 3,500 m (PR = 0.48; 95%CI 0.35 - 0.64; p <0.001) and ≥ 3,501 m (PR = 0.24; 95%CI 0.15 - 0.39; p <0.001) showed an inverse association with active displacement. In the adjusted analyzes, the presence of safety signs (RP = 0.78; 95%CI 0.66 - 0.91; p = 0.003) and the distances of 1500-3,500 m (RP = 0.53; 95%CI 0.40 - 0.71; p <0.001) and ≥ 3,501m (PR= 0.29; 95%CI 0.18 - 0.45; p <0.001) remained associated with the outcome (Table 3).

DISCUSSION

This is the first study conducted in Brazil that explored the association between the characteristics of the environment around the school, assessed through systematic observation²⁷27. Jones NR, Jones A, van Sluijs EM, Panter J, Harrison F, Griffin SJ. School environments and physical activity: The development and testing of an audit tool. Health Place 2010; 16(5): 776-83. https://doi.org/10.1016/j.healthplace.2010.04.002
https://doi.org/https://doi.org/10.1016/... , and the distance from home, assessed by Geographic Information System (GIS)³¹31. Silva AT, Fermino RC, Lopes AAS, Alberico CO, Reis RS. Distance to fitness zone, use of facilities and physical activity in adults. Rev Bras Med Esporte 2018; 24(2). https://doi.org/10.1590/1517-869220182402180439
https://doi.org/https://doi.org/10.1590/... , with the active commuting of adolescents. The combination of methods made it possible to identify quantitative and qualitative attributes of the environment built around schools and the possible routes between homes and schools, which contributes to the understanding of how people choose their mode of transport, and are relevant and innovative factors of the study.

Active commuting to school was reported by 62% of adolescents in the sample, with a higher proportion among those enrolled in public schools (public 59.7% versus private 13.6%), especially when homes are located at a distance up to 1,500 m from the institution. This data can be justified by the enrollment procedure adopted by the State Department of Education (Secretaria Estadual de Educação - SEED), which prioritizes the enrollment of students in public institutions close to their homes, while private institutions do not follow this criterion³²32. Paraná. Secretaria de Estado de Educação do Paraná (SEED). Matrícula por Georreferenciamento [Internet]. Secretaria de Estado de Educação do Paraná [acessado em 03 set. 2017]. Disponível em: Disponível em: http://www.gestaoescolar.diaadia.pr.gov.br/modules/conteudo/conteudo.php?conteudo=2http://www.celepar.pr.gov.br/modules/conteudo/conteudo.php?conteudo=541
http://www.gestaoescolar.diaadia.pr.gov.... . However, the farthest distance observed in this study was 22,400 m, suggesting that enrollment in the education system does not necessarily follow the distance to the school as suggested by SEED. As for the type of active commuting, while walking is a popular way to get to school, the use of bicycles in Brazil is less common among teenagers, mainly because there is no culture linked to the use, little or no infrastructure in the neighborhood and around schools, in addition to topographic variations³³33. Mandic S, Hopkins D, Bengoechea EG, Flaherty CJW, Williams J, Sloane L, et al. Adolescents’ perceptions of cycling versus walking to school: Understanding the New Zealand context. J Transp Health 2017; 4: 294-304. https://doi.org/10.1016/j.jth.2016.10.007
https://doi.org/https://doi.org/10.1016/... .

Individual characteristics may be one of the factors that justify the choice of active commuting, since the outcome, in the present study, is less frequent among girls and those whose family owns at least one car. In the study by Rech et al.³⁴34. Rech CR, Rosa CO, Avrela PR, Halpern R, Costanzi CB, Bergmann MLA, et al. Fatores associados ao deslocamento ativo em escolares. Rev Bras Ativ Fis Saúde 2013; 18(3): 332-8. https://doi.org/10.12820/rbafs.v.18n3p332
https://doi.org/https://doi.org/10.12820... , 56.8% of girls were active commuters to school. The same pattern was observed in the study by Silva et al.²⁹29. Silva KS, Pizarro AN, Garcia LM, Mota J, Santos MP. Which social support and psychological factors are associated to active commuting to school? Prev Med 2014; 63: 20-3. https://doi.org/10.1016/j.ypmed.2014.02.019
https://doi.org/https://doi.org/10.1016/... , in which 48.6% of the adolescents actively commuted to school in some way. This relationship could be explained by psychological and socio-cultural factors of greater overprotection by parents or guardians in relation to girls, especially when the educational level of parents or guardians is medium-low³⁴34. Rech CR, Rosa CO, Avrela PR, Halpern R, Costanzi CB, Bergmann MLA, et al. Fatores associados ao deslocamento ativo em escolares. Rev Bras Ativ Fis Saúde 2013; 18(3): 332-8. https://doi.org/10.12820/rbafs.v.18n3p332
https://doi.org/https://doi.org/10.12820... ^,3535. Wong BY, Faulkner G, Buliung R, Irving H. Mode shifting in school travel mode: examining the prevalence and correlates of active school transport in Ontario, Canada. BMC Public Health 2011; 11: 618. https://doi.org/10.1186/1471-2458-11-618
https://doi.org/https://doi.org/10.1186/... . Furthermore, a family’s purchasing power can interfere in the mode of transport due to the convenience and the perception of safety. Ownership of cars can influence this transport choice, giving preference to car commuting instead of traveling on foot³⁵35. Wong BY, Faulkner G, Buliung R, Irving H. Mode shifting in school travel mode: examining the prevalence and correlates of active school transport in Ontario, Canada. BMC Public Health 2011; 11: 618. https://doi.org/10.1186/1471-2458-11-618
https://doi.org/https://doi.org/10.1186/... ^,3636. Hallal PC, Bertoldi AD, Gonçalves H, Victora CG. Prevalência de sedentarismo e fatores associados em adolescentes de 10-12 anos de idade. Cad Saúde Pública 2006; 22(6): 1277-87. https://doi.org/10.1590/S0102-311X2006000600017
https://doi.org/https://doi.org/10.1590/... ^,3737. Molina-Garcia J, Queralt A. Neighborhood Built Environment and Socioeconomic Status in Relation to Active Commuting to School in Children. J Phys Act Health 2017; 14(10): 761-5. https://doi.org/10.1123/jpah.2017-0033
https://doi.org/https://doi.org/10.1123/... .

The presence of safety signs was inversely associated with active commuting (PR = 0.78; 95%CI 0.66 - 0.91). This result is in contradiction with the literature, in which the presence of signing tends to provide a greater perception of safety and increase the chances of active commuting¹⁶16. D’Haese S, Vanwolleghem G, Hinckson E, De Bourdeaudhuij I, Deforche B, Van Dyck D, et al. Cross-continental comparison of the association between the physical environment and active transportation in children: a systematic review. Int J Behav Nutr Phys Act 2015; 12: 145. https://doi.org/10.1186/s12966-015-0308-z
https://doi.org/https://doi.org/10.1186/... . The findings can be explained, in part, by the fact that, in developing countries such as Brazil, in the busiest places - with regard to traffic or flow of motor vehicles -, there is a greater amount of signage, which aim at greater movement control and the reduction of possible accidents¹⁶16. D’Haese S, Vanwolleghem G, Hinckson E, De Bourdeaudhuij I, Deforche B, Van Dyck D, et al. Cross-continental comparison of the association between the physical environment and active transportation in children: a systematic review. Int J Behav Nutr Phys Act 2015; 12: 145. https://doi.org/10.1186/s12966-015-0308-z
https://doi.org/https://doi.org/10.1186/... ^,3838. Kerr J, Rosenberg D, Sallis JF, Saelens BE, Frank LD, Conway TL. Active commuting to school: Associations with environment and parental concerns. Med Sci Sports Exerc 2006; 38(4): 787-94. https://doi.org/10.1249/01.mss.0000210208.63565.73
https://doi.org/https://doi.org/10.1249/... . This can inhibit active commuting, considering the large flow of cars and the negative perception of safety, especially by parents or guardians³⁹39. Olvera N, Smith DW, Lee C, Liu J, Lee J, Kellam S, et al. Hispanic maternal and children’s perceptions of neighborhood safety related to walking and cycling. Health Place 2012; 18(1): 71-5. https://doi.org/10.1016/j.healthplace.2011.08.022
https://doi.org/https://doi.org/10.1016/... ^,4040. Oluyomi AO, Lee C, Nehme E, Dowdy D, Ory MG, Hoelscher DM. Parental safety concerns and active school commute: correlates across multiple domains in the home-to-school journey. Int J Behav Nutr Phys Act 2014; 11(1): 32. https://doi.org/10.1186/1479-5868-11-32
https://doi.org/https://doi.org/10.1186/... ^,4141. Becker LA, Fermino RC, Lima AV, Rech CR, Rodriguez-Añez CR, Reis RS. Perceived barriers for active commuting to school among adolescents from Curitiba, Brazil. Rev Bras Ativ Fis Saúde 2017; 22(1): 24-34. https://doi.org/10.12820/rbafs.v.22n1p24-34
https://doi.org/https://doi.org/10.12820... .

In fact, the findings of the present study demonstrated an inverse association between greater distances, such as 1,501-3,500 m (PR = 0.53; 95%CI 0.40 - 0.70) and ≥ 3,501 m (PR = 0.29; 95%CI 0.18 - 0.45), and active commuting to school. The results suggest a consistency with the literature that analyzed the distance traveled from the residence to the school, both for perceived measures⁴¹41. Becker LA, Fermino RC, Lima AV, Rech CR, Rodriguez-Añez CR, Reis RS. Perceived barriers for active commuting to school among adolescents from Curitiba, Brazil. Rev Bras Ativ Fis Saúde 2017; 22(1): 24-34. https://doi.org/10.12820/rbafs.v.22n1p24-34
https://doi.org/https://doi.org/10.12820... ^,4242. Beck LF, Nguyen DD. School transportation mode, by distance between home and school, United States, ConsumerStyles 2012. J Safety Res 2017; 62: 245-51. https://doi.org/10.1016/j.jsr.2017.04.001
https://doi.org/https://doi.org/10.1016/... and for objective measures⁸8. Silva KS, Vasques DG, Martins C de O, Williams LA, Lopes AS. Active commuting: prevalence, barriers, and associated variables. J Phys Act Health 2011; 8(6): 750-7. https://doi.org/10.1123/jpah.8.6.750
https://doi.org/https://doi.org/10.1123/... . A study carried out in Belgium by D’Haese et al.¹³13. D’Haese S, De Meester F, De Bourdeaudhuij I, Deforche B, Cardon G. Criterion distances and environmental correlates of active commuting to school in children. Int J Behav Nutr Phys Act 2011; 8: 88. https://doi.org/10.1186/1479-5868-8-88
https://doi.org/https://doi.org/10.1186/... pointed out that distances of up to 1,500 m between home and school are suitable for walking, and distances of up to 3,000 m are suitable for cycling. A study carried out in Ireland by Nelson et al.¹⁴14. Nelson NM, Foley E, O’Gorman DJ, Moyna NM, Woods CB. Active commuting to school: how far is too far? Int J Behav Nutr Phys Act 2008; 5: 1. https://doi.org/10.1186/1479-5868-5-1
https://doi.org/https://doi.org/10.1186/... demonstrated that distances above 4,000 m are characterized as a barrier to active commuting, reinforcing that the proximity of the home can stimulate this practice¹1. Panter JR, Jones AP, van Sluijs EM. Environmental determinants of active travel in youth: a review and framework for future research. Int J Behav Nutr Phys Act 2008; 5: 34. https://doi.org/10.1186/1479-5868-5-34
https://doi.org/https://doi.org/10.1186/... ^,1515. Chillón P, Panter J, Corder K, Jones AP, Van Sluijs EM. A longitudinal study of the distance that young people walk to school. Health Place 2015; 31: 133-7. https://dx.doi.org/10.1016%2Fj.healthplace.2014.10.013
https://doi.org/https://dx.doi.org/10.10... ^,4343. Davison KK, Werder JL, Lawson CT. Children’s active commuting to school: current knowledge and future directions. Prev Chronic Dis 2008; 5(3): A100.^,4444. Bringolf-Isler B, Grize L, Mader U, Ruch N, Sennhauser FH, Braun-Fahrlander C. Personal and environmental factors associated with active commuting to school in Switzerland. Prev Med 2008; 46(1): 67-73. https://doi.org/10.1016/j.ypmed.2007.06.015
https://doi.org/https://doi.org/10.1016/... , provided that factors such as perceived safety of adolescents and parents or guardians, in addition to the presence of attributes (walkability, density and accessibility), are linked¹⁶16. D’Haese S, Vanwolleghem G, Hinckson E, De Bourdeaudhuij I, Deforche B, Van Dyck D, et al. Cross-continental comparison of the association between the physical environment and active transportation in children: a systematic review. Int J Behav Nutr Phys Act 2015; 12: 145. https://doi.org/10.1186/s12966-015-0308-z
https://doi.org/https://doi.org/10.1186/... ^,3838. Kerr J, Rosenberg D, Sallis JF, Saelens BE, Frank LD, Conway TL. Active commuting to school: Associations with environment and parental concerns. Med Sci Sports Exerc 2006; 38(4): 787-94. https://doi.org/10.1249/01.mss.0000210208.63565.73
https://doi.org/https://doi.org/10.1249/... . In Brazil, Silva et al.⁸8. Silva KS, Vasques DG, Martins C de O, Williams LA, Lopes AS. Active commuting: prevalence, barriers, and associated variables. J Phys Act Health 2011; 8(6): 750-7. https://doi.org/10.1123/jpah.8.6.750
https://doi.org/https://doi.org/10.1123/... identified that the main barrier to active commuting was the distance to school. Thus, the results seem to strengthen the importance of policies that integrate access to school and traffic safety. It is also important to highlight that these commuting alternatives have direct implications for the education and health of the population, as well as for the economy and sustainability of cities⁴⁵45. Voorhees CC, Ashwood S, Evenson KR, Sirard JR, Rung AL, Dowda M, et al. Neighborhood design and perceptions: relationship with active commuting. Med Sci Sports Exerc 2010; 42(7): 1253-60. https://doi.org/10.1249/MSS.0b013e3181cd5dfd
https://doi.org/https://doi.org/10.1249/... ^,4646. Mandic S, Sandretto S, Bengoechea EG, Hopkins D, Moore A, Rodda J, et al. Enrolling in the Closest School or Not? Implications of school choice decisions for active transport to school. J Transp Health 2017; 6: 347-57..

Some limitations must be considered for the proper interpretation of the results of this study. Active commuting was self-reported, which prevents a more accurate estimation of the behavior⁴⁷47. Pizarro AN, Schipperijn J, Andersen HB, Ribeiro JC, Mota J, Santos MP. Active commuting to school in Portuguese adolescents: Using PALMS to detect trips. J Transp Health 2016; 3(3): 297-304. https://doi.org/10.1016/j.jth.2016.02.004
https://doi.org/https://doi.org/10.1016/... . The evaluation of the schools’ surroundings was restricted to the streets around the block where the institution was located, which does not allow to extrapolate the characteristics to other streets in the community environment. The sample of schools is not representative of the city, and their selection was associated with the institutions in which the adolescents were enrolled. Although the shortest distance through the network of streets, between the residence and the school of the adolescents was measured using GIS, this does not reflect the real route taken by them, like, for example, data provided by Global Positioning System (GPS)⁴⁸48. Alberico CO, Schipperijn J, Reis RS. Use of global positioning system for physical activity research in youth: ESPACOS Adolescentes, Brazil. Prev Med 2017; 103S: S59-S65. https://doi.org/10.1016/j.ypmed.2016.12.026
https://doi.org/https://doi.org/10.1016/... . Therefore, in the present study, it was not possible to assess the “quality” of the total area that covers the path that the teenager frequently used or was exposed to, for example, areas of sausage buffer of 25 or 75 m of street segments or sidewalk⁴⁹49. Frank LD, Fox EH, Ulmer JM, Chapman JE, Kershaw SE, Sallis JF, et al. International comparison of observation-specific spatial buffers: maximizing the ability to estimate physical activity. Int J Health Geogr 2017; 16.https://doi.org/10.1186/s12942-017-0077-9
https://doi.org/https://doi.org/10.1186/... . Finally, the cross-sectional design limits the causal interpretation between the variables.

CONCLUSION

The presence of safety signs and the distance between home and school showed an inverse association with active commuting among adolescents from public and private schools in Curitiba, Paraná. The findings indicate that traffic safety and proximity to home can contribute to active commuting to school. Policies that integrate access to schools close to home and traffic safety can contribute to encouraging active commuting to school among teenagers, and also involve the perceptions of teenagers and their parents or guardians. It is necessary, then, to provide improvements in the conditions of the neighborhood and surrounding schools for the development of effective interventions⁵⁰50. Mandic S, Leon de la Barra S, Garcia Bengoechea E, Stevens E, Flaherty C, Moore A, et al. Personal, social and environmental correlates of active transport to school among adolescents in Otago, New Zealand. J Sci Med Sport 2015; 18(4): 432-7. https://doi.org/10.1016/j.jsams.2014.06.012
https://doi.org/https://doi.org/10.1016/... .

ACKNOWLEDGMENTS

The Coordination for the Improvement of Higher Education Personnel (CAPES), the National Institutes of Health (NIH) and the members of the Research Group on Physical Activity and Quality of Life (Grupo de Pesquisa em Atividade Física e Qualidade de Vida - GPAQ).

References

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