Built environment and physical activity of adolescents: an approach with artificial neural networks

Authors

  • Murilo Gominho Antunes Correia Júnior Universidade de Pernambuco, Programa de Pós-Graduação em Hebiatria, Recife, Pernambuco, Brasil. Universidade de Pernambuco, Escola Superior de Educação Física, Programa Associado de Pós-Graduação em Educação Física Universidade de Pernambuco/Universidade Federal da Paraíba, Recife, Pernambuco, Brasil. https://orcid.org/0000-0002-2395-2210
  • Thaliane Mayara Pessôa dos Prazeres Universidade de Pernambuco, Escola Superior de Educação Física, Programa Associado de Pós-Graduação em Educação Física Universidade de Pernambuco/Universidade Federal da Paraíba, Recife, Pernambuco, Brasil. https://orcid.org/0000-0003-0640-2353
  • Rafael dos Santos Henrique Universidade Federal de Pernambuco, Departamento de Educação Física, Recife, Pernambuco, Brasil. https://orcid.org/0000-0003-3912-5559
  • Javiera Alarcon Universidade de Pernambuco, Escola Superior de Educação Física, Programa Associado de Pós-Graduação em Educação Física Universidade de Pernambuco/Universidade Federal da Paraíba, Recife, Pernambuco, Brasil. https://orcid.org/0000-0003-4267-046X
  • Isabele Goes Nobre Universidade Federal de Pernambuco, Departamento de Educação Física, Recife, Pernambuco, Brasil. https://orcid.org/0000-0003-4598-1060
  • Bruno Cesar Pereira Pinto Universidade Federal de Pernambuco, Departamento de Engenharia Cartográfica, Recife, Pernambuco, Brasil. https://orcid.org/0009-0000-1042-6249
  • Gustavo Aires de Arruda Universidade de Pernambuco, Escola Superior de Educação Física, Programa Associado de Pós-Graduação em Educação Física Universidade de Pernambuco/Universidade Federal da Paraíba, Recife, Pernambuco, Brasil https://orcid.org/0000-0002-9157-6114
  • Douglas Eduardo Ferreira Maia Universidade Federal de Pernambuco, Departamento de Educação Física, Recife, Pernambuco, Brasil. https://orcid.org/0000-0003-1257-846X
  • Lucilene Antunes Correia Marques de Sá Universidade Federal de Pernambuco, Departamento de Engenharia Cartográfica, Recife, Pernambuco, Brasil. https://orcid.org/0000-0003-4497-6243
  • Marcos André Moura dos Santos Universidade de Pernambuco, Programa de Pós-Graduação em Hebiatria, Recife, Pernambuco, Brasil. Universidade de Pernambuco, Escola Superior de Educação Física, Programa Associado de Pós-Graduação em Educação Física Universidade de Pernambuco/Universidade Federal da Paraíba, Recife, Pernambuco, Brasil. https://orcid.org/0000-0002-2734-8416

DOI:

https://doi.org/10.12820/rbafs.29e0346

Keywords:

Artificial neural network, Adolescents, Georeferencing

Abstract

The objective of this study was to analyze the association of the level of physical activity (PA) and body composition in relation to the amount and distance of built environments favorable to the practice of PA in relation to the homes of adolescents in the city of Lagoa do Carro/Pernambuco, Brazil. A total of 289 adolescents (153 boys; 10 to 18 years) participated in the study, duly enrolled in schools municipality. The self-administered Physical Activity Questionnaire for Children (PAQ-C) and Physical Activity Questionnaire for Adolescent (PAQ-A) was used to assess the PA level. The Geographic Information System was used to assess the built environments. Buffers of 100 to 500 meters were created from the center of the built environment. The Artificial Neural Network in the Feedforward method was used to assess the association and importance of built environment and body composition variables with PA level. The different distances from the built environment to the place of residence do not present statistical differences. It is noteworthy that the number of buffers up to 500 meters away was the variable that showed the greatest importance for the PA level, along with adolescents who live in places with greater exposure in terms of built environments, being considered more active. It was possible to conclude that the main determinants of the PA level of adolescents were the amount of buffers at 500 meters, sex and the distance to the built environment. However, the variables, housing area, body mass and amounts of buffers at 100 meters were the ones with the lowest power of influence.

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References

Malina RM, Bouchard C, Bar-Or O. Growth, maturation, and physical activity: Human kinetics; 2004. DOI: https://doi.org/10.5040/9781492596837

Collishaw S, Maughan B, Goodman R, Pickles A. Time trends in adolescent mental health. J Child Psychol Psychiatry. 2004;45(8):1350-62. doi: https://doi.org/10.1111/j.1469-7610.2004.00842.x. DOI: https://doi.org/10.1111/j.1469-7610.2004.00842.x

Aneshensel CS, Sucoff CA. The neighborhood context of adolescent mental health. J Health Soc Behav. 1996;37(4):293-310. DOI: https://doi.org/10.2307/2137258

Gustafsson PE, Bozorgmehr K, Hammarström A, San Sebastian M. What role does adolescent neighborhood play for adult health? A cross-classified multilevel analysis of life course models in Northern Sweden. Health Place. 2017;46:137-44. doi: https://doi.org/10.1016/j.healthplace.2017.04.013. DOI: https://doi.org/10.1016/j.healthplace.2017.04.013

Sallis JF, Cervero RB, Ascher W, Henderson KA, Kraft MK, Kerr J. An ecological approach to creating active living communities. Annu Rev Public Health. 2006;27:297-322. doi: https://doi.org/10.1146/annurev.publhealth.27.021405.102100. DOI: https://doi.org/10.1146/annurev.publhealth.27.021405.102100

Carlson JA, Saelens BE, Kerr J, Schipperijn J, Conway TL, Frank LD, et al. Association between neighborhood walkability and GPS-measured walking, bicycling and vehicle time in adolescents. Health Place. 2015;32:1-7. doi: https://doi.org/10.1016/j.healthplace.2014.12.008. DOI: https://doi.org/10.1016/j.healthplace.2014.12.008

Hallal PC, Reis RS, Parra DC, Hoehner C, Brownson RC, Simões EJ. Association between perceived environmental attributes and physical activity among adults in Recife, Brazil. J Phys Act Health. 2010;7(Suppl 2):S213-S22. doi: https://doi.org/10.1123/jpah.7.s2.s213. DOI: https://doi.org/10.1123/jpah.7.s2.s213

Audrey S, Batista-Ferrer H. Healthy urban environments for children and young people: a systematic review of intervention studies. Health Place. 2015;36:97-117. doi: https://doi.org/10.1016/j.healthplace.2015.09.004. DOI: https://doi.org/10.1016/j.healthplace.2015.09.004

Knuth AG, Hallal P. School environment and physical activity in children and adolescents: systematic review. Rev Bras Ativ Fis Saúde. 2012;17(6):463-73. DOI: https://doi.org/10.12820/2317-1634.2012v17n6p463

Sallis JF, Conway TL, Cain KL, Carlson JA, Frank LD, Kerr J, et al. Neighborhood built environment and socioeconomic status in relation to physical activity, sedentary behavior, and weight status of adolescents. Prev Med. 2018;110:47-54. doi: https://doi.org/10.1016/j.ypmed.2018.02.009. DOI: https://doi.org/10.1016/j.ypmed.2018.02.009

Oreskovic NM, Perrin JM, Robinson AI, Locascio JJ, Blossom J, Chen ML, et al. Adolescents’ use of the built environment for physical activity. BMC Public Health. 2015;15:1-9. doi: https://doi.org/10.1186/s12889-015-1596-6. DOI: https://doi.org/10.1186/s12889-015-1596-6

Duncan MJ, Badland HM, Mummery WK. Applying GPS to enhance understanding of transport-related physical activity. J Sci Med Sport. 2009;12(5):549-56. doi: https://doi.org/10.1016/j.jsams.2008.10.010. DOI: https://doi.org/10.1016/j.jsams.2008.10.010

Beheshti R, Jalalpour M, Glass TA. Comparing methods of targeting obesity interventions in populations: an agent-based simulation. SSM Popul Health. 2017;3:211-8. doi: https://doi.org/10.1016/j.ssmph.2017.01.006. DOI: https://doi.org/10.1016/j.ssmph.2017.01.006

DeGregory K, Kuiper P, DeSilvio T, Pleuss J, Miller R, Roginski J, et al. A review of machine learning in obesity. Obes Rev. 2018;19(5):668-85. doi: https://doi.org/10.1111/obr.12667. DOI: https://doi.org/10.1111/obr.12667

IBGE. Coordenação de População e Indicadores Sociais, Estimativas da população residente com data de referência 1 de julho de 2017. 2018. Disponível em: https://www.ibge.gov.br/estatisticas/sociais/populacao/9103-estimativas-de-populacao.html. [2018 Agosto].

Rao DC. Genetic dissection of complex traits: An overview. Adv Genet. 2001;42:13-34. doi: https://doi.org/10.1016/s0065-2660(01)42012-8. DOI: https://doi.org/10.1016/S0065-2660(01)42012-8

Lohman TG, Going SB. Body composition assessment for development of an international growth standard for preadolescent and adolescent children. Food Nutr Bull. 2006;27(4 Suppl Growth Standard):S314-S25. doi: https://doi.org/10.1177/15648265060274S512. DOI: https://doi.org/10.1177/15648265060274S512

World Health Organization (WHO). WHO AnthroPlus for personal computers Manual: Software for assessing growth of the world’s children and adolescents. Geneva: WHO, 2009.

Callaway C. New weight guidelines for Americans. Am J Clin Nutr. 1991;54(1):171-4. doi: https://doi.org/10.1093/ajcn/54.1.171. DOI: https://doi.org/10.1093/ajcn/54.1.171a

Mirwald RL, Baxter-Jones AD, Bailey DA, Beunen GP. An assessment of maturity from anthropometric measurements. Med Sci Sports Exerc. 2002;34(4):689-94. doi: https://doi.org/10.1097/00005768-200204000-00020. DOI: https://doi.org/10.1249/00005768-200204000-00020

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(1):4. doi: https://doi.org/10.1186/s12942-017-0077-9. DOI: https://doi.org/10.1186/s12942-017-0077-9

Guedes DP, Guedes JERP. Measuring Physical Activity In Brazilian Youth: Reproducibility And Validity Of The Paq-C And Paq-A. Rev Bras Med Esporte. 2015;21(6):425-32. doi: https://doi.org/10.1590/1517-869220152106147594. DOI: https://doi.org/10.1590/1517-869220152106147594

Benítez-Porres J, Alvero-Cruz JR, Sardinha LB, López-Fernández I, Carnero EA. Cut-off values for classifying active children and adolescents using the Physical Activity Questionnaire: PAQ-C and PAQ-A. Nutr Hosp. 2016;33(5):564. doi: https://doi.org/10.20960/nh.564. DOI: https://doi.org/10.20960/nh.564

Brownson RC, Hoehner CM, Day K, Forsyth A, Sallis JF. Measuring the built environment for physical activity: state of the science. Am J Prev Med. 2009;36(4):S99-123. e12. doi: https://doi.org/10.1016/j.amepre.2009.01.005. DOI: https://doi.org/10.1016/j.amepre.2009.01.005

Grieco EP, Portugal LdS, Alves RM. Aplicação de um índice do ambiente construído para avaliação da mobilidade sustentável. Ambient Const. 2016;16(4):215-25. doi: https://doi.org/10.1590/s1678-86212016000400115. DOI: https://doi.org/10.1590/s1678-86212016000400115

Cohen DA, Han B, Kraus L, Young DR. The contribution of the built environment to physical activity among young women. Environ Behav 2019;51(7):811-27. doi: https://doi.org/10.1177/001391651775303. DOI: https://doi.org/10.1177/0013916517753036

Hinckson E, Cerin E, Mavoa S, Smith M, Badland H, Stewart T, et al. Associations of the perceived and objective neighborhood environment with physical activity and sedentary time in New Zealand adolescents. Int J Behav Nutr Phys Act. 2017;14(1):1-15. doi: https://doi.org/10.1186/s12966-017-0597-5. DOI: https://doi.org/10.1186/s12966-017-0597-5

Peters P, Gold A, Abbott A, Contreras D, Keim A, Oscarson R, et al. A quasi-experimental study to mobilize rural low-income communities to assess and improve the ecological environment to prevent childhood obesity. BMC Public Health. 2016;16(1):1-7. doi: https://doi.org/10.1186/s12889-016-3047-4. DOI: https://doi.org/10.1186/s12889-016-3047-4

Virginia-Añez E, Fornieles-Deu A, Sánchez-Carracedo D. Longitudinal study of physical activity in Spanish young adolescents: weight status and gender differences. Rev Psicol Deport. 2020;29(1):57-66.

Bird M, Datta GD, van Hulst A, Cloutier M-S, Henderson M, Barnett TA. A park typology in the QUALITY cohort: Implications for physical activity and truncal fat among youth at risk of obesity. Prev Med. 2016;90:133-8. doi: https://doi.org/10.1016/j.ypmed.2016.06.042. DOI: https://doi.org/10.1016/j.ypmed.2016.06.042

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Published

2024-09-18

How to Cite

1.
Correia Júnior MGA, Prazeres TMP dos, Henrique R dos S, Alarcon J, Nobre IG, Pinto BCP, et al. Built environment and physical activity of adolescents: an approach with artificial neural networks. Rev. Bras. Ativ. Fís. Saúde [Internet]. 2024 Sep. 18 [cited 2024 Nov. 21];29:1-12. Available from: https://rbafs.org.br/RBAFS/article/view/15217

Issue

Vol. 29 (2024)

Section

Original Articles

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Copyright (c) 2024 Murilo Gominho, Thaliane Mayara Pessôa dos Prazeres, Rafael dos Santos Henrique, Javiera Alarcon, Isabele Gois Nobre, Bruno Cesar Pereira Pinto, Gustavo Aires de Arruda, Douglas Eduardo Ferreira Maia, Lucilene Antunes Correia Marques de Sá, Marcos André Moura dos Santos

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