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Health effects of active commuting: Design, rationale and baseline characteristics of a randomized-controlled trial. The GISMO Study

Session Poster Session 3

Speaker David Niederseer

Event : ESC Preventive Cardiology (Formerly EuroPrevent) 2018

  • Topic : e-cardiology / digital health, public health, health economics, research methodology
  • Sub-topic : Public Health and Health Economics - Other
  • Session type : Poster Session

Authors : D Niederseer (Zurich,CH), M Loidl (Salzburg,AT), MD Fernandez Lapuente De Battre (Salzburg,AT), B Reich (Salzburg,AT), B Zagel (Salzburg,AT), J Niebauer (Salzburg,AT), CM Schmied (Zurich,CH)

Authors:
D Niederseer1 , M Loidl2 , MD Fernandez Lapuente De Battre3 , B Reich3 , B Zagel2 , J Niebauer3 , CM Schmied1 , 1University Hospital Zurich, Department of Cardiology - Zurich - Switzerland , 2University of Salzburg, Z_GIS - Salzburg - Austria , 3Paracelsus Private Medical University - Salzburg - Austria ,

Citation:
European Journal of Preventive Cardiology ( May 2018 ) 25 ( Supplement 1 ), 148

Background Sedentary lifestyle is a major modifiable risk factor for cardiovascular diseases and triggers substantial costs due to early retirement and the inability to participate in the work force. Active commuting has been proposed to at least in part overcome these problems; however, convincing data to support this recommendation are sparse. Purpose To investigate the health effects of active commuting and herewith provide data to design a geographical information support tool to help promote active commuting especially in corporate health management. Methods We screened 300 subjects with regard to the following inclusion criteria: employment at the University Clinic Salzburg, Austria; age 18-70 years; volunteering to participate in the study; and willingness to change from passive to active commute. Exclusion criteria were physical and mental conditions that rendered a completion of the study unlikely. Thereafter, 76 subjects were randomized into an intervention group (IG) or control group (CG) in a 2:1 strata. Depending on the distance to the work place, IG participants either travel by a combination of public transportation and walking or cycling (IG-PT), or they commute by walking and/or cycling only (IG-CW). The CG was asked to commute as usual. Baseline assessment included anthropometrics, cardiovascular risk profile, electrocardiogram, cycle ergometry, detailed and structured questionnaires on physical activity, everyday mobility, general health and quality of life. Every subject is required to document his or her commuting mobility in an online mobility diary. In order to control for the validity of these data and to estimate the subjects’ energy turnover, subjects were additionally asked to wear a fitness watches with GPS and heart rate sensor for two consecutive weeks at the beginning and towards the end of the intervention phase. All measurements will be repeated after one year in IG and CG. Results Of 76 subjects, 53 were randomized into IG (IG-PT n=26; IG-CW n= 27) and 23 into CG. Participants in IG were significantly older (IG 47±9, CG 42±10 years, p=0.023), BMI (IG 26±4; CG 26±5kg/m2) was increased in all groups with no difference between groups (p=0.999). Heart SCORE (IG 0.4±0.4%; CG 0.3±0.6%; p=0.394), hypercholesteremia (51%; 39%, p=0.463), arterial hypertension (IG 8%; CG 0%; p=0.308) and smoking (IG 20%; 22%; p=0.999) was well comparable between groups and both ECGs and ergometries were inconspicuous. Conclusions This randomized controlled trial will provide data on the effects of an active commute to work on modifiable cardiovascular risk factors related to sedentary lifestyle. Furthermore, the integration of GPS-based data will enable the investigators to design a geographical information support tool to help promote active commuting.

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