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.
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The consequences of cardiovascular diseases are substantial and include increasing numbers of morbidity and mortality. With a population getting more and more inactive and having a sedentary lifestyle, the risk for cardiovascular disease and type 2 diabetes rises. This dissertation reports on people with one or more cardiovascular risk factor(s) and who are having an inactive lifestyle, and how healthcare professionals can encourage these people at risk to become and stay physically active in a way that cardiovascular fitness is improved. The assumption is that if an intervention can reduce the prevalence of risk factors, it can also reduce the prevalence of disease. When cardiovascular fitness improves and a person is capable of keeping a physically active lifestyle, levels and number of cardiovascular risk factors can decrease in a population.
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Children with Marfan (MFS) and Loeys-Dietz syndrome (LDS) report limitations in physical activities, sports, school, leisure, and work participation in daily life. This observational, cross-sectional, multicenter study explores associations between physical fitness and cardiovascular parameters, systemic manifestations, fatigue, and pain in children with MFS and LDS. Forty-two participants, aged 6–18 years (mean (SD) 11.5(3.7)), diagnosed with MFS (n = 36) or LDS (n = 6), were enrolled. Physical fitness was evaluated using the Fitkids Treadmill Test’s time to exhaustion (TTE) outcome measure. Cardiovascular parameters (e.g., echocardiographic parameters, aortic surgery, cardiovascular medication) and systemic manifestations (systemic score of the revised Ghent criteria) were collected. Pain was obtained by visual analog scale. Fatigue was evaluated by PROMIS® Fatigue-10a-Pediatric-v2.0-short-form and PROMIS® Fatigue-10a-Parent-Proxy-v2.0-short-form. Multivariate linear regression analyses explored associations between physical fitness (dependent variable) and independent variables that emerged from the univariate linear regression analyses (criterion p <.05). The total group (MFS and LDS) and the MFS subgroup scored below norms on physical fitness TTE Z-score (mean (SD) −3.1 (2.9); −3.0 (3.0), respectively). Univariate analyses showed associations between TTE Z-score aortic surgery, fatigue, and pain (criterion p <.05). Multivariate analyses showed an association between physical fitness and pediatric self-reported fatigue that explained 48%; 49%, respectively, of TTE Z-score variance (F (1,18) = 18.6, p ≤.001, r2 =.48; F (1,15) = 16,3, p =.01, r2 =.49, respectively). Conclusions: Physical fitness is low in children with MFS or LDS and associated with self-reported fatigue. Our findings emphasize the potential of standardized and tailored exercise programs to improve physical fitness and reduce fatigue, ultimately enhancing the physical activity and sports, school, leisure, and work participation of children with MFS and LDS. (Table presented.)
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Introduction: The optimal pre-participation screening strategy to identify athletes at risk for exercise-induced cardiovascular events is unknown. We therefore aimed to compare the American College of Sports Medicine (ACSM) and European Society of Cardiology (ESC) pre-participation screening strategies against extensive cardiovascular evaluations in identifying high-risk individuals among 35.50- year-old apparently healthy men. Methods: We applied ACSM and ESC pre-participation screenings to 25 men participating in a study on first-time marathon running. We compared screening outcomes against medical history, physical examination, electrocardiography, blood tests, echocardiography, cardiopulmonary exercise testing, and magnetic resonance imaging. Results: ACSM screening classified all participants as "medical clearance not necessary."ESC screening classified two participants as "high-risk."Extensive cardiovascular evaluations revealed ≥1 minor abnormality and/or cardiovascular condition in 17 participants, including three subjects with mitral regurgitation and one with a small atrial septal defect. Eleven participants had dyslipidaemia, six had hypertension, and two had premature atherosclerosis. Ultimately, three (12%) subjects had a serious cardiovascular condition warranting sports restrictions: aortic aneurysm, hypertrophic cardiomyopathy (HCM), and myocardial fibrosis post-myocarditis. Of these three participants, only one had been identified as "high-risk"by the ESC screening (for dyslipidaemia, not HCM) and none by the ACSM screening. Conclusion: Numerous occult cardiovascular conditions are missed when applying current ACSM/ ESC screening strategies to apparently healthy middle-aged men engaging in their first high-intensity endurance sports event.
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Living independently is an important component of quality of life. Cardiovascular diseases are prominent among the chronic conditions that predispose elderly people to functional limitations and disability, which impair quality of life. Insight into factors that play a role in the development process of limitations and disability of patients with subclinical cardiovascular diseases will aid in the development of preventive interventions. The aim of this study was to investigate the association of vascular status with muscle strength and physical functioning in middle aged and elderly men.
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Purpose: The aim of this study was to investigate the occupational well-being among employees with chronic diseases, and the buffering effect of four job resources, possibly offering targets to enhance occupational well-being.Method: This cross-sectional study (N = 1951) was carried out among employees in educational and (semi-)governmental organizations in the Netherlands. The dimensions of the survey were chronic diseases (i.e., physical, mental, or both physical and mental), occupational well-being (i.e., work ability, burnout complaints, and work engagement), and job resources (i.e., autonomy, social support by colleagues, supportive leadership style, and open and communicative culture). First, it was analyzed if chronic diseases were associated with occupational well-being. Second, it was analyzed if each of the four job resources would predict better occupational well-being. Third, possible moderation effects between the chronic disease groups and each job resource on occupational well-being were examined. Regression analyses were used, controlling for age.Results: Each chronic disease group was associated with a lower work ability. However, higher burnout complaints and a lower work engagement were only predicted by the group with mental chronic diseases and by the group with both physical and mental chronic disease(s). Furthermore, all four job resources predicted lower burnout complaints and higher work engagement, while higher work ability was only predicted by autonomy and a supportive leadership style. Some moderation effects were observed. Autonomy buffered the negative relationship between the chronic disease groups with mental conditions (with or without physical conditions) and work ability, and the positive relationship between the group with both physical and mental chronic disease(s) and burnout complaints. Furthermore, a supportive leadership style is of less benefit for occupational well-being among the employees with mental chronic diseases (with or without physical chronic diseases) compared to the group employees without chronic diseases. No buffering was demonstrated for social support of colleagues and an open and communicative organizational culture.Conclusion: Autonomy offers opportunities to reinforce occupational well-being among employees with mental chronic diseases. A supportive leadership style needs more investigation to clarify why this job resource is less beneficial for employees with mental chronic diseases than for the employees without chronic diseases.
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The high prevalence and burden of cardiovascular diseases (CVD) is largely attributable to unhealthy lifestyle factors such as smoking, alcohol consumption, physical inactivity and unhealthy food habits. Prevention of CVD, through the promotion of healthy lifestyles, appears to be a Sisyphean task for healthcare professionals, as the root causes of an unhealthy lifestyle lie largely outside their scope. Since most lifestyle choices are habitual and a response to environmental cues, rather than rational and deliberate choices, nationwide policies targeting the context in which lifestyle behaviours occur may be highly effective in the prevention of CVD. In this point-of-view article, we emphasise the need for government policies beyond those mentioned in the National Prevention Agreement in the Netherlands to effectively reduce the CVD risk, and we address the commonly raised concerns regarding ‘paternalism’.
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Alongside the growing number of older persons, the prevalence of chronic diseases is increasing, leading to higher pressure on health care services. eHealth is considered a solution for better and more efficient health care. However, not every patient is able to use eHealth, for several reasons. This study aims to provide an overview of: (1) sociodemographic factors that influence the use of eHealth; and (2) suggest directions for interventions that will improve the use of eHealth in patients with chronic disease. A structured literature review of PubMed, ScienceDirect, Association for Computing Machinery Digital Library (ACMDL), and Cumulative Index to Nursing and Allied Health Literature (CINAHL) was conducted using four sets of keywords: “chronic disease”, “eHealth”, “factors”, and “suggested interventions”. Qualitative, quantitative, and mixed-method studies were included. Four researchers each assessed quality and extracted data. Twenty-two out of 1639 articles were included. Higher age and lower income, lower education, living alone, and living in rural areas were found to be associated with lower eHealth use. Ethnicity revealed mixed outcomes. Suggested solutions were personalized support, social support, use of different types of Internet devices to deliver eHealth, and involvement of patients in the development of eHealth interventions. It is concluded that eHealth is least used by persons who need it most. Tailored delivery of eHealth is recommended
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Stroke is the second most common cause of death and the third leading cause of disability worldwide,1,2 with the burden expected to increase during the next 20 years.1 Almost 40% of the people with stroke have a recurrent stroke within 10 years,3 making secondary prevention vital.3,4 High amounts of sedentary time have been found to increase the risk of cardiovascular disease,5–11 particularly when the sedentary time is accumulated in prolonged bouts.12–15 Sedentary behavior, is defined as “any waking behavior characterized by an energy expenditure ≤1.5 Metabolic Equivalent of Task (METs) while in a sitting, reclining or lying posture”.16,17 Studies in healthy people, as well as people with diabetes and obesity, have shown that reducing the total amount of sedentary time and/or breaking up long periods of uninterrupted sedentary time, reduces metabolic risk factors associated with cardiovascular disease.6,9,10,12–15 Recent studies have shown that people living in the community after stroke spend more time each day sedentary, and more time in uninterrupted bouts of sedentary time compared to age-matched healthy peers.18–20 Reducing sedentary time and breaking up long sedentary bouts with short bursts of activity may be a promising intervention to reduce the risk of recurrent stroke and other cardiovascular diseases in people with stroke. To develop effective interventions, it is important to understand the factors associated with sedentary time in people with stroke. Previous studies have found associations between self-reported physical function after stroke and total sedentary time, but inconsistent results with regards to the relationship of age, stroke severity, and walking speed with sedentary time.20,21 These results are from secondary analyses of single-site observational studies, not powered to address associations, and inconsistent in the methods used to determine waking hours; thus making direct comparisons between studies difficult.20,21 Individual participant data pooling, with consistent processing of wake time data, allows novel exploratory analyses of larger datasets with greater power. By pooling all available individual participant data internationally, this study aimed to comprehensively explore the factors associated with sedentary time in community-dwelling people with stroke. Specifically, our research questions were: (1) What factors are associated with total sedentary time during waking hours after stroke? (2) What factors are associated with time spent in prolonged sedentary bouts during waking hours?
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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 VO2) 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, R2 = .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 (R2 = .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
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