Research
How well do cognitive and environmental variables predict active commuting?
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* Corresponding author: Gaston Godin Gaston.Godin@fsi.ulaval.ca
- † Equal contributors
1 Department of Social and Preventive Medicine, Division of Kinesiology, Laval University, Québec, Canada
2 Research Group on Behaviour in the Field of Health, Laval University, Québec, Canada
3 Canada Research Chair on Behaviour and Health, Faculty of Nursing, Pavillon Ferdinand-Vandry, 1050 rue De la Médecine, 3e étage, Laval University, Québec, G1V 0A6, Canada
International Journal of Behavioral Nutrition and Physical Activity 2009, 6:12 doi:10.1186/1479-5868-6-12
Published: 6 March 2009Abstract
Background
In recent years, there has been growing interest in theoretical studies integrating cognitions and environmental variables in the prediction of behaviour related to the obesity epidemic. This is the approach adopted in the present study in reference to the theory of planned behaviour. More precisely, the aim of this study was to determine the contribution of cognitive and environmental variables in the prediction of active commuting to get to and from work or school.
Methods
A prospective study was carried out with 130 undergraduate and graduate students (93 females; 37 males). Environmental, cognitive and socio-demographic variables were evaluated at baseline by questionnaire. Two weeks later, active commuting (walking/bicycling) to get to and from work or school was self-reported by questionnaire. Hierarchical multiple regression analyses were performed to predict intention and behaviour.
Results
The model predicting behaviour based on cognitive variables explained more variance than the model based on environmental variables (37.4% versus 26.8%; Z = 3.86, p < 0.001). Combining cognitive and environmental variables with socio-demographic variables to predict behaviour yielded a final model explaining 41.1% (p < 0.001) of the variance. The significant determinants were intention, habit and age. Concerning intention, the same procedure yielded a final model explaining 78.2% (p < 0.001) of the variance, with perceived behavioural control, attitude and habit being the significant determinants.
Conclusion
The results showed that cognitive variables play a more important role than environmental variables in predicting and explaining active commuting. When environmental variables were significant, they were mediated by cognitive variables. Therefore, individual cognitions should remain one of the main focuses of interventions promoting active commuting among undergraduate and graduate students.