Running towards health: the association of running volume with running-related injuries

Bibliographic Details
Main Author: Nakaoka, Gustavo Bezerra
Publication Date: 2020
Format: Master thesis
Language: eng
Source: Repositório do Centro Universitário Braz Cubas
Download full: https://repositorio.cruzeirodosul.edu.br/handle/123456789/881
Summary: Background: Running-related injuries (RRI) may lead to drop out from running practice and reduce the likelihood of keeping up a physically active lifestyle. Training workload could be either a risk or a protective factor for sports-related injuries. The acute:chronic workload ratio (ACWR) is a method that considers the current (i.e., acute workload) sport workload performed by an individual in relation to the workload this individual is prepared for (i.e., chronic workload). Purpose: To investigate the longitudinal association between the ACWR and RRIs. Methods: This is a secondary analysis using a database composed of data from three studies conducted with the same surveillance system in the Netherlands. Longitudinal data were collected biweekly. Bayesian logistic mixed models were used to analyse the data. A time-lag technique was applied to the RRI incidence data to ensure that the running workload was collected before the reporting of the RRIs. The uncoupled ACWR was calculated as the most recent workload divided by the average of the previous three biweekly periods. The model was adjusted for age, sex, body mass index, running experience and previous RRIs. Repeated measurements and cohort samples based on the studies included in this analysis were included as random effects. Results were presented as odds ratio (OR) and the 95% credible interval (95% CrI). Results: The sample was composed of 435 Dutch runners (276 males). Although significant, the relation between RRIs and the ACWR was found to vary from small to moderate (1% to 10%) with a tendency pointing out higher ACWR related to lower RRIs risk. For external workloads calculated using exposition in hours, runners whose ACWR were under 0.65 had a 9% probability of sustaining an RRI (i.e., 0.09 [95% CrI 0.07 to 0.12]). Conclusions: In runners, the ACWR showed an association with RRIs approximately linear and inversely proportional. Being a useful tool indicating injured runners reducing their training workload.
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spelling Running towards health: the association of running volume with running-related injuriesRunningSports injuriesDecision support techniquesArtificial intelligenceNeural networks (Computer)Machine learningAthletic injuriesSportsRisk managementEndurance trainingCNPQ::CIENCIAS DA SAUDE::FISIOTERAPIA E TERAPIA OCUPACIONALBackground: Running-related injuries (RRI) may lead to drop out from running practice and reduce the likelihood of keeping up a physically active lifestyle. Training workload could be either a risk or a protective factor for sports-related injuries. The acute:chronic workload ratio (ACWR) is a method that considers the current (i.e., acute workload) sport workload performed by an individual in relation to the workload this individual is prepared for (i.e., chronic workload). Purpose: To investigate the longitudinal association between the ACWR and RRIs. Methods: This is a secondary analysis using a database composed of data from three studies conducted with the same surveillance system in the Netherlands. Longitudinal data were collected biweekly. Bayesian logistic mixed models were used to analyse the data. A time-lag technique was applied to the RRI incidence data to ensure that the running workload was collected before the reporting of the RRIs. The uncoupled ACWR was calculated as the most recent workload divided by the average of the previous three biweekly periods. The model was adjusted for age, sex, body mass index, running experience and previous RRIs. Repeated measurements and cohort samples based on the studies included in this analysis were included as random effects. Results were presented as odds ratio (OR) and the 95% credible interval (95% CrI). Results: The sample was composed of 435 Dutch runners (276 males). Although significant, the relation between RRIs and the ACWR was found to vary from small to moderate (1% to 10%) with a tendency pointing out higher ACWR related to lower RRIs risk. For external workloads calculated using exposition in hours, runners whose ACWR were under 0.65 had a 9% probability of sustaining an RRI (i.e., 0.09 [95% CrI 0.07 to 0.12]). Conclusions: In runners, the ACWR showed an association with RRIs approximately linear and inversely proportional. Being a useful tool indicating injured runners reducing their training workload.Objectives: To develop an artificial intelligence (AI) algorithm in order to identify running-related injury (RRI) risk profiles in recreational runners, and to investigate the internal validity of such algorithm. Methods: This was a 3-step AI study using data from a prospective cohort study. In step 1, variable selection and exploratory analyses were conducted in the original (n=191) and simulated data (n=5000). In step 2, the AI algorithm was developed using machine learning techniques (selforganising maps, k-means and probabilistic neural network). The algorithm was trained in 80% (n=4000) of the simulated data, and the internal validity was investigated applying the algorithm in the remaining 20% (n=1000). The characterisation of RRI risk profiles was performed in step 3. Results: Four out of eight variables included in the algorithm were considered the main classification features: sex; running intensity; history of RRIs; and current musculoskeletal complaints or discomfort related to running Five groups were suggested by the AI algorithm. Male runners reporting previous RRIs and running in low-to-moderate intensities (>6 min/km) were at the highest risk of RRIs. Male runners reporting previous RRIs and running in high intensities (3 to 5 min/km) in about 32.1% of the time were at the lowest risk of RRIs. The accuracy of the RRI risk algorithm presented a median of 99.6% (25% to 75% interquartile range 99.5% to 99.8%). Conclusions: An AI algorithm was successfully developed and was able to correctly classify more than 99% of the runners in five RRI risk profiles.Universidade Cidade de São PauloBrasilPós-GraduaçãoPrograma de Pós-Graduação de Mestrado em FisioterapiaUNICIDHespanhol Junior, Luiz Carloshttps://orcid.org/0000-0003-1774-4746http://lattes.cnpq.br/5224710039315770Nakaoka, Gustavo Bezerra2020-08-04T14:41:17Z2020-08-04T14:41:17Z2020-05-06info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfNAKAOKA, Gustavo Bezerra. Running towards health: the association of running volume with running-related injuries. Orientador: Luiz Carlos Hespanhol Junior. 2020. 80f. Dissertação (Mestrado em Fisioterapia) - Universidade Cidade de São Paulo. 2020.https://repositorio.cruzeirodosul.edu.br/handle/123456789/881enginfo:eu-repo/semantics/openAccessreponame:Repositório do Centro Universitário Braz Cubasinstname:Centro Universitário Braz Cubas (CUB)instacron:CUB2020-08-04T14:46:19Zoai:repositorio.cruzeirodosul.edu.br:123456789/881Repositório InstitucionalPUBhttps://repositorio.brazcubas.edu.br/oai/requestbibli@brazcubas.edu.bropendoar:2020-08-04T14:46:19Repositório do Centro Universitário Braz Cubas - Centro Universitário Braz Cubas (CUB)false
dc.title.none.fl_str_mv Running towards health: the association of running volume with running-related injuries
title Running towards health: the association of running volume with running-related injuries
spellingShingle Running towards health: the association of running volume with running-related injuries
Nakaoka, Gustavo Bezerra
Running
Sports injuries
Decision support techniques
Artificial intelligence
Neural networks (Computer)
Machine learning
Athletic injuries
Sports
Risk management
Endurance training
CNPQ::CIENCIAS DA SAUDE::FISIOTERAPIA E TERAPIA OCUPACIONAL
title_short Running towards health: the association of running volume with running-related injuries
title_full Running towards health: the association of running volume with running-related injuries
title_fullStr Running towards health: the association of running volume with running-related injuries
title_full_unstemmed Running towards health: the association of running volume with running-related injuries
title_sort Running towards health: the association of running volume with running-related injuries
author Nakaoka, Gustavo Bezerra
author_facet Nakaoka, Gustavo Bezerra
author_role author
dc.contributor.none.fl_str_mv Hespanhol Junior, Luiz Carlos
https://orcid.org/0000-0003-1774-4746
http://lattes.cnpq.br/5224710039315770
dc.contributor.author.fl_str_mv Nakaoka, Gustavo Bezerra
dc.subject.por.fl_str_mv Running
Sports injuries
Decision support techniques
Artificial intelligence
Neural networks (Computer)
Machine learning
Athletic injuries
Sports
Risk management
Endurance training
CNPQ::CIENCIAS DA SAUDE::FISIOTERAPIA E TERAPIA OCUPACIONAL
topic Running
Sports injuries
Decision support techniques
Artificial intelligence
Neural networks (Computer)
Machine learning
Athletic injuries
Sports
Risk management
Endurance training
CNPQ::CIENCIAS DA SAUDE::FISIOTERAPIA E TERAPIA OCUPACIONAL
description Background: Running-related injuries (RRI) may lead to drop out from running practice and reduce the likelihood of keeping up a physically active lifestyle. Training workload could be either a risk or a protective factor for sports-related injuries. The acute:chronic workload ratio (ACWR) is a method that considers the current (i.e., acute workload) sport workload performed by an individual in relation to the workload this individual is prepared for (i.e., chronic workload). Purpose: To investigate the longitudinal association between the ACWR and RRIs. Methods: This is a secondary analysis using a database composed of data from three studies conducted with the same surveillance system in the Netherlands. Longitudinal data were collected biweekly. Bayesian logistic mixed models were used to analyse the data. A time-lag technique was applied to the RRI incidence data to ensure that the running workload was collected before the reporting of the RRIs. The uncoupled ACWR was calculated as the most recent workload divided by the average of the previous three biweekly periods. The model was adjusted for age, sex, body mass index, running experience and previous RRIs. Repeated measurements and cohort samples based on the studies included in this analysis were included as random effects. Results were presented as odds ratio (OR) and the 95% credible interval (95% CrI). Results: The sample was composed of 435 Dutch runners (276 males). Although significant, the relation between RRIs and the ACWR was found to vary from small to moderate (1% to 10%) with a tendency pointing out higher ACWR related to lower RRIs risk. For external workloads calculated using exposition in hours, runners whose ACWR were under 0.65 had a 9% probability of sustaining an RRI (i.e., 0.09 [95% CrI 0.07 to 0.12]). Conclusions: In runners, the ACWR showed an association with RRIs approximately linear and inversely proportional. Being a useful tool indicating injured runners reducing their training workload.
publishDate 2020
dc.date.none.fl_str_mv 2020-08-04T14:41:17Z
2020-08-04T14:41:17Z
2020-05-06
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv NAKAOKA, Gustavo Bezerra. Running towards health: the association of running volume with running-related injuries. Orientador: Luiz Carlos Hespanhol Junior. 2020. 80f. Dissertação (Mestrado em Fisioterapia) - Universidade Cidade de São Paulo. 2020.
https://repositorio.cruzeirodosul.edu.br/handle/123456789/881
identifier_str_mv NAKAOKA, Gustavo Bezerra. Running towards health: the association of running volume with running-related injuries. Orientador: Luiz Carlos Hespanhol Junior. 2020. 80f. Dissertação (Mestrado em Fisioterapia) - Universidade Cidade de São Paulo. 2020.
url https://repositorio.cruzeirodosul.edu.br/handle/123456789/881
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Cidade de São Paulo
Brasil
Pós-Graduação
Programa de Pós-Graduação de Mestrado em Fisioterapia
UNICID
publisher.none.fl_str_mv Universidade Cidade de São Paulo
Brasil
Pós-Graduação
Programa de Pós-Graduação de Mestrado em Fisioterapia
UNICID
dc.source.none.fl_str_mv reponame:Repositório do Centro Universitário Braz Cubas
instname:Centro Universitário Braz Cubas (CUB)
instacron:CUB
instname_str Centro Universitário Braz Cubas (CUB)
instacron_str CUB
institution CUB
reponame_str Repositório do Centro Universitário Braz Cubas
collection Repositório do Centro Universitário Braz Cubas
repository.name.fl_str_mv Repositório do Centro Universitário Braz Cubas - Centro Universitário Braz Cubas (CUB)
repository.mail.fl_str_mv bibli@brazcubas.edu.br
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