David van Bodegom
Please Note
3 records found
1
Setting your clock
Associations between timing of objective physical activity and cardiovascular disease risk in the general population
Aims Little is known about the impact of daily physical activity timing (here referred to as 'chronoactivity') on cardiovascular disease (CVD) risk. We aimed to examined the associations between chronoactivity and multiple CVD outcomes in the UK Biobank. Methods and results physical activity data were collected in the UK-Biobank through triaxial accelerometer over a 7-day measurement period. We used K-means clustering to create clusters of participants with similar chronoactivity irrespective of the mean daily intensity of the physical activity. Multivariable-adjusted Cox-proportional hazard models were used to estimate hazard ratios (HRs) comparing the different clusters adjusted for age and sex (model 1), and baseline cardiovascular risk factors (model 2). Additional stratified analyses were done by sex, mean activity level, and self-reported sleep chronotype. We included 86 657 individuals (58% female, mean age: 61.6 [SD: 7.8] years, mean BMI: 26.6 [4.5] kg/m2). Over a follow-up period of 6 years, 3707 incident CVD events were reported. Overall, participants with a tendency of late morning physical activity had a lower risk of incident coronary artery disease (HR: 0.84, 95%CI: 0.77, 0.92) and stroke (HR: 0.83, 95%CI: 0.70, 0.98) compared to participants with a midday pattern of physical activity. These effects were more pronounced in women (P-value for interaction=0.001). We did not find evidence favouring effect modification by total activity level and sleep chronotype. Conclusion Irrespective of total physical activity, morning physical activity was associated with lower risks of incident cardiovascular diseases, highlighting the potential importance of chronoactivity in CVD prevention.
Improving Employee Health
Lessons from an RCT
employability. As part of a larger employer vitality program and a work site RCT
(Randomized Controlled Trial, n=59 intervention arm) to assess cardiac risk impacts, we conducted a design analysis on a hybrid eHealth solution. The control condition was a six weeks waiting list and then start of the hybrid eHealth support (n=57).
Based on preliminary 6 week- and 3 month-results, the hybrid eHealth support
generated statistically significant risk factors improvement (like LDL cholesterol). The waiting list condition yielded no significant improvements. The late start after the waiting list did yield significant improvements, but not as large as a direct start. The direct start also appears to yield higher satisfaction and intention to recommend.
Our analysis supports three types of conclusions. First, the hybrid eHealth intervention did significantly improve physical risk factor variables after 6 weeks. Motivation and measurement alone (waiting list) did not. Second, theory on timing of health support for patient appeared generalizable to employees: it did help to offer support at a moment of high motivation, instead of later. Third, a design analysis was conducted regarding service mix efficacy in relation to key requirements for designing ICT-enabled lifestyle interventions. This resulted in several recommendations and improved service adoption. ...
employability. As part of a larger employer vitality program and a work site RCT
(Randomized Controlled Trial, n=59 intervention arm) to assess cardiac risk impacts, we conducted a design analysis on a hybrid eHealth solution. The control condition was a six weeks waiting list and then start of the hybrid eHealth support (n=57).
Based on preliminary 6 week- and 3 month-results, the hybrid eHealth support
generated statistically significant risk factors improvement (like LDL cholesterol). The waiting list condition yielded no significant improvements. The late start after the waiting list did yield significant improvements, but not as large as a direct start. The direct start also appears to yield higher satisfaction and intention to recommend.
Our analysis supports three types of conclusions. First, the hybrid eHealth intervention did significantly improve physical risk factor variables after 6 weeks. Motivation and measurement alone (waiting list) did not. Second, theory on timing of health support for patient appeared generalizable to employees: it did help to offer support at a moment of high motivation, instead of later. Third, a design analysis was conducted regarding service mix efficacy in relation to key requirements for designing ICT-enabled lifestyle interventions. This resulted in several recommendations and improved service adoption.