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Cardiovascular risk profile: Cross-sectional analysis of motivational determinants, physical fitness and physical activity

BACKGROUND: Cardiovascular risk factors are associated with physical fitness and, to a lesser extent, physical activity. Lifestyle interventions directed at enhancing physical fitness in order to decrease the risk of cardiovascular diseases should be extended. To enable the development of effective...

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Autores principales: Sassen, Barbara, Kok, Gerjo, Schaalma, Herman, Kiers, Henri, Vanhees, Luc
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3091554/
https://www.ncbi.nlm.nih.gov/pubmed/20929529
http://dx.doi.org/10.1186/1471-2458-10-592
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author Sassen, Barbara
Kok, Gerjo
Schaalma, Herman
Kiers, Henri
Vanhees, Luc
author_facet Sassen, Barbara
Kok, Gerjo
Schaalma, Herman
Kiers, Henri
Vanhees, Luc
author_sort Sassen, Barbara
collection PubMed
description BACKGROUND: Cardiovascular risk factors are associated with physical fitness and, to a lesser extent, physical activity. Lifestyle interventions directed at enhancing physical fitness in order to decrease the risk of cardiovascular diseases should be extended. To enable the development of effective lifestyle interventions for people with cardiovascular risk factors, we investigated motivational, social-cognitive determinants derived from the Theory of Planned Behavior (TPB) and other relevant social psychological theories, next to physical activity and physical fitness. METHODS: In the cross-sectional Utrecht Police Lifestyle Intervention Fitness and Training (UP-LIFT) study, 1298 employees (aged 18 to 62) were asked to complete online questionnaires regarding social-cognitive variables and physical activity. Cardiovascular risk factors and physical fitness (peak VO(2)) were measured. RESULTS: For people with one or more cardiovascular risk factors (78.7% of the total population), social-cognitive variables accounted for 39% (p < .001) of the variance in the intention to engage in physical activity for 60 minutes every day. Important correlates of intention to engage in physical activity were attitude (beta = .225, p < .001), self-efficacy (beta = .271, p < .001), descriptive norm (beta = .172, p < .001) and barriers (beta = -.169, p < .01). Social-cognitive variables accounted for 52% (p < .001) of the variance in physical active behaviour (being physical active for 60 minutes every day). The intention to engage in physical activity (beta = .469, p < .001) and self-efficacy (beta = .243, p < .001) were, in turn, important correlates of physical active behavior. In addition to the prediction of intention to engage in physical activity and physical active behavior, we explored the impact of the intensity of physical activity. The intentsity of physical activity was only significantly related to physical active behavior (beta = .253, p < .01, R(2 )= .06, p < .001). An important goal of our study was to investigate the relationship between physical fitness, the intensity of physical activity and social-cognitive variables. Physical fitness (R(2 )= .23, p < .001) was positively associated with physical active behavior (beta = .180, p < .01), self-efficacy (beta = .180, p < .01) and the intensity of physical activity (beta = .238, p < .01). For people with one or more cardiovascular risk factors, 39.9% had positive intentions to engage in physical activity and were also physically active, and 10.5% had a low intentions but were physically active. 37.7% had low intentions and were physically inactive, and about 11.9% had high intentions but were physically inactive. CONCLUSIONS: This study contributes to our ability to optimize cardiovascular risk profiles by demonstrating an important association between physical fitness and social-cognitive variables. Physical fitness can be predicted by physical active behavior as well as by self-efficacy and the intensity of physical activity, and the latter by physical active behavior. Physical active behavior can be predicted by intention, self-efficacy, descriptive norms and barriers. Intention to engage in physical activity by attitude, self-efficacy, descriptive norms and barriers. An important input for lifestyle changes for people with one or more cardiovascular risk factors was that for ca. 40% of the population the intention to engage in physical activity was in line with their actual physical active behavior.
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spelling pubmed-30915542011-05-11 Cardiovascular risk profile: Cross-sectional analysis of motivational determinants, physical fitness and physical activity Sassen, Barbara Kok, Gerjo Schaalma, Herman Kiers, Henri Vanhees, Luc BMC Public Health Research Article BACKGROUND: Cardiovascular risk factors are associated with physical fitness and, to a lesser extent, physical activity. Lifestyle interventions directed at enhancing physical fitness in order to decrease the risk of cardiovascular diseases should be extended. To enable the development of effective lifestyle interventions for people with cardiovascular risk factors, we investigated motivational, social-cognitive determinants derived from the Theory of Planned Behavior (TPB) and other relevant social psychological theories, next to physical activity and physical fitness. METHODS: In the cross-sectional Utrecht Police Lifestyle Intervention Fitness and Training (UP-LIFT) study, 1298 employees (aged 18 to 62) were asked to complete online questionnaires regarding social-cognitive variables and physical activity. Cardiovascular risk factors and physical fitness (peak VO(2)) were measured. RESULTS: For people with one or more cardiovascular risk factors (78.7% of the total population), social-cognitive variables accounted for 39% (p < .001) of the variance in the intention to engage in physical activity for 60 minutes every day. Important correlates of intention to engage in physical activity were attitude (beta = .225, p < .001), self-efficacy (beta = .271, p < .001), descriptive norm (beta = .172, p < .001) and barriers (beta = -.169, p < .01). Social-cognitive variables accounted for 52% (p < .001) of the variance in physical active behaviour (being physical active for 60 minutes every day). The intention to engage in physical activity (beta = .469, p < .001) and self-efficacy (beta = .243, p < .001) were, in turn, important correlates of physical active behavior. In addition to the prediction of intention to engage in physical activity and physical active behavior, we explored the impact of the intensity of physical activity. The intentsity of physical activity was only significantly related to physical active behavior (beta = .253, p < .01, R(2 )= .06, p < .001). An important goal of our study was to investigate the relationship between physical fitness, the intensity of physical activity and social-cognitive variables. Physical fitness (R(2 )= .23, p < .001) was positively associated with physical active behavior (beta = .180, p < .01), self-efficacy (beta = .180, p < .01) and the intensity of physical activity (beta = .238, p < .01). For people with one or more cardiovascular risk factors, 39.9% had positive intentions to engage in physical activity and were also physically active, and 10.5% had a low intentions but were physically active. 37.7% had low intentions and were physically inactive, and about 11.9% had high intentions but were physically inactive. CONCLUSIONS: This study contributes to our ability to optimize cardiovascular risk profiles by demonstrating an important association between physical fitness and social-cognitive variables. Physical fitness can be predicted by physical active behavior as well as by self-efficacy and the intensity of physical activity, and the latter by physical active behavior. Physical active behavior can be predicted by intention, self-efficacy, descriptive norms and barriers. Intention to engage in physical activity by attitude, self-efficacy, descriptive norms and barriers. An important input for lifestyle changes for people with one or more cardiovascular risk factors was that for ca. 40% of the population the intention to engage in physical activity was in line with their actual physical active behavior. BioMed Central 2010-10-07 /pmc/articles/PMC3091554/ /pubmed/20929529 http://dx.doi.org/10.1186/1471-2458-10-592 Text en Copyright ©2010 Sassen et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Sassen, Barbara
Kok, Gerjo
Schaalma, Herman
Kiers, Henri
Vanhees, Luc
Cardiovascular risk profile: Cross-sectional analysis of motivational determinants, physical fitness and physical activity
title Cardiovascular risk profile: Cross-sectional analysis of motivational determinants, physical fitness and physical activity
title_full Cardiovascular risk profile: Cross-sectional analysis of motivational determinants, physical fitness and physical activity
title_fullStr Cardiovascular risk profile: Cross-sectional analysis of motivational determinants, physical fitness and physical activity
title_full_unstemmed Cardiovascular risk profile: Cross-sectional analysis of motivational determinants, physical fitness and physical activity
title_short Cardiovascular risk profile: Cross-sectional analysis of motivational determinants, physical fitness and physical activity
title_sort cardiovascular risk profile: cross-sectional analysis of motivational determinants, physical fitness and physical activity
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3091554/
https://www.ncbi.nlm.nih.gov/pubmed/20929529
http://dx.doi.org/10.1186/1471-2458-10-592
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