OBJECTIVE: To examine how a healthy lifestyle is related to life expectancy that is free from major chronic diseases.DESIGN: Prospective cohort study.SETTING AND PARTICIPANTS: The Nurses' Health Study (1980-2014; n=73 196) and the Health Professionals Follow-Up Study (1986-2014; n=38 366).MAIN EXPOSURES: Five low risk lifestyle factors: never smoking, body mass index 18.5-24.9, moderate to vigorous physical activity (≥30 minutes/day), moderate alcohol intake (women: 5-15 g/day; men 5-30 g/day), and a higher diet quality score (upper 40%).MAIN OUTCOME: Life expectancy free of diabetes, cardiovascular diseases, and cancer.RESULTS: The life expectancy free of diabetes, cardiovascular diseases, and cancer at age 50 was 23.7 years (95% confidence interval 22.6 to 24.7) for women who adopted no low risk lifestyle factors, in contrast to 34.4 years (33.1 to 35.5) for women who adopted four or five low risk factors. At age 50, the life expectancy free of any of these chronic diseases was 23.5 (22.3 to 24.7) years among men who adopted no low risk lifestyle factors and 31.1 (29.5 to 32.5) years in men who adopted four or five low risk lifestyle factors. For current male smokers who smoked heavily (≥15 cigarettes/day) or obese men and women (body mass index ≥30), their disease-free life expectancies accounted for the lowest proportion (≤75%) of total life expectancy at age 50.CONCLUSION: Adherence to a healthy lifestyle at mid-life is associated with a longer life expectancy free of major chronic diseases.
Background: For patients with coronary artery disease (CAD), smoking is an important risk factor for the recurrence of a cardiovascular event. Motivational interviewing (MI) may increase the motivation of the smokers to stop smoking. Data on MI for smoking cessation in patients with CAD are limited, and the active ingredients and working mechanisms of MI in smoking cessation are largely unknown. Therefore, this study was designed to explore active ingredients and working mechanisms of MI for smoking cessation in smokers with CAD, shortly after a cardiovascular event.Methods: We conducted a qualitative multiple case study of 24 patients with CAD who participated in a randomized trial on lifestyle change. One hundred and nine audio-recorded MI sessions were coded with a combination of the sequential code for observing process exchanges (SCOPE) and the motivational interviewing skill code (MISC). The analysis of the cases consisted of three phases: single case analysis, cross-case analysis, and cross-case synthesis. In a quantitative sequential analysis, we calculated the transition probabilities between the use of MI techniques by the coaches and the subsequent patient statements concerning smoking cessation.Results: In 12 cases, we observed ingredients that appeared to activate the mechanisms of change. Active ingredients were compositions of behaviors of the coaches (e.g., supporting self-efficacy and supporting autonomy) and patient reactions (e.g., in-depth self-exploration and change talk), interacting over large parts of an MI session. The composition of active ingredients differed among cases, as the patient process and the MI-coaching strategy differed. Particularly, change talk and self-efficacy appeared to stimulate the mechanisms of change “arguing oneself into change” and “increasing self-efficacy/confidence.”Conclusion: Harnessing active ingredients that target the mechanisms of change “increasing self-efficacy” and “arguing oneself into change” is a good MI strategy for smoking cessation, because it addresses the ambivalence of a patient toward his/her ability to quit, while, after the actual cessation, maintaining the feeling of urgency to persist in not smoking in the patient.
MULTIFILE
Background Having a partner is associated with better prognosis in patients with cardiovascular disease. However, the influence of partners on modification of patients’ lifestyle-related risk factors (LRFs) is unclear. Therefore, we studied the influence of partners and the level of partner participation on LRF modification in patients after an acute coronary syndrome (ACS) or revascularization. Methods The RESPONSE-2 trial was a community-based lifestyle intervention trial comparing nurse-coordinated referral to a comprehensive set of lifestyle interventions (physical activity, weight reduction and/or smoking cessation) to usual care. In the current analysis, we investigated the association of having a partner on the improvement in >1 LRF without deterioration in other LRFs at 12 months follow-up. Secondary, the influence of the level of partner participation (participating partner, non-participating partner and no partner) in the intervention group was studied. Results In total 824 individuals (411 intervention, 413 control) were included in the analysis. The presence of a partner was comparable in both groups (intervention 74%, control 69%). In the intervention group, 48% of partners participated in the lifestyle interventions. Overall, having a partner was positively associated with improvement in LRFs (odds ratio (OR) 2.57 (95% confidence interval (CI) 1.57 – 4.21), p<0.001). In the intervention group, having a participating partner was also positively associated with improvement in LRFs compared to patients without a partner (OR 2.45 95% CI 1.25 – 4.79, p=0.009). When analysed the influence of partners on LRFs separately, patients with a participating partner were most successful in reducing weight compared to patients without a partner (OR 2.71 95% CI 1.16 – 6.36, p=0.02). Conclusion Having a partner is associated with improvement on LRFs in patients after ACS or revascularization. Moreover, patients with participating partners in the lifestyle programs were most successful in LRF modification. Involvement of partners in lifestyle interventions should be considered in routine practice.
The livability of the cities and attractiveness of our environment can be improved by smarter choices for mobility products and travel modes. A change from current car-dependent lifestyles towards the use of healthier and less polluted transport modes, such as cycling, is needed. With awareness campaigns, cycling facilities and cycle infrastructure, the use of the bicycle will be stimulated. But which campaigns are effective? Can we stimulate cycling by adding cycling facilities along the cycle path? How can we design the best cycle infrastructure for a region? And what impact does good cycle infrastructure have on the increase of cycling?To find answers for these questions and come up with a future approach to stimulate bicycle use, BUas is participating in the InterReg V NWE-project CHIPS; Cycle Highways Innovation for smarter People transport and Spatial planning. Together with the city of Tilburg and other partners from The Netherlands, Belgium, Germany and United Kingdom we explore and demonstrate infrastructural improvements and tackle crucial elements related to engaging users and successful promotion of cycle highways. BUas is responsible for the monitoring and evaluation of the project. To measure the impact and effectiveness of cycle highway innovations we use Cyclespex and Cycleprint.With Cyclespex a virtual living lab is created which we will use to test several readability and wayfinding measures for cycle infrastructure. Cyclespex gives us the opportunity to test different scenario’s in virtual reality that will help us to make decisions about the final solution that will be realized on the cycle highway. Cycleprint will be used to develop a monitoring dashboard where municipalities of cities can easily monitor and evaluate the local bicycle use.
Wheelchair users with a spinal cord injury (SCI) or amputation generally lead an inactive lifestyle, associated with reduced fitness and health. Digital interventions and sport and lifestyle applications (E-platforms) may be helpful in achieving a healthy lifestyle. Despite the potential positive effects of E-platforms in the general population, no studies are known investigating the effects for wheelchair users and existing E-platforms can not be used to the same extent and in the same manner by this population due to differences in physiology, body composition, exercise forms and responses, and risk injury. It is, therefore, our aim to adapt an existing E-platform (Virtuagym) within this project by using existing data collections and new data to be collected within the project. To reach this aim we intend to make several relevant databases from our network available for analysis, combine and reanalyze these existing databases to adapt the existing E-platform enabling wheelchair users to use it, evaluate and improve the use of the adapted E-platform, evaluate changes in healthy active lifestyle parameters, fitness, health and quality of life in users of the E-platform (both wheelchair users and general population) and identify determinants of these changes, identify factors affecting transitions from an inactive lifestyle, through an intermediate level, to an athlete level, comparing wheelchair users with the general population, and comparing Dutch with Brazilian individuals. The analysis of large datasets of exercise and fitness data from various types of individuals with and without disabilities, collected over the last years both in the Netherlands and Brazil, is an innovative and potentially fruitful approach. It is expected that the comparison of e.g. wheelchair users in Amsterdam vs. Sao Paulo or recreative athletes vs. elite athletes provides new insight in the factors determining a healthy and active lifestyle.
Wheelchair users with a spinal cord injury (SCI) or amputation generally lead an inactive lifestyle, associated with reduced fitness and health. Digital interventions and sport and lifestyle applications (E-platforms) may be helpful in achieving a healthy lifestyle. Despite the potential positive effects of E-platforms in the general population, no studies are known investigating the effects for wheelchair users and existing E-platforms can not be used to the same extent and in the same manner by this population due to differences in physiology, body composition, exercise forms and responses, and risk injury. It is, therefore, our aim to adapt an existing E-platform (Virtuagym) within this project by using existing data collections and new data to be collected within the project. To reach this aim we intend to make several relevant databases from our network available for analysis, combine and reanalyze these existing databases to adapt the existing E-platform enabling wheelchair users to use it, evaluate and improve the use of the adapted E-platform, evaluate changes in healthy active lifestyle parameters, fitness, health and quality of life in users of the E-platform (both wheelchair users and general population) and identify determinants of these changes, identify factors affecting transitions from an inactive lifestyle, through an intermediate level, to an athlete level, comparing wheelchair users with the general population, and comparing Dutch with Brazilian individuals. The analysis of large datasets of exercise and fitness data from various types of individuals with and without disabilities, collected over the last years both in the Netherlands and Brazil, is an innovative and potentially fruitful approach. It is expected that the comparison of e.g. wheelchair users in Amsterdam vs. Sao Paulo or recreative athletes vs. elite athletes provides new insight in the factors determining a healthy and active lifestyle.
