Comparison of Wearable Trackers’ Ability to Estimate Sleep

Tracking physical activity and sleep patterns using wearable trackers has become a current trend. However, little information exists about the comparability of wearable trackers measuring sleep. This study examined the comparability of wearable trackers for estimating sleep measurement with a sleep diary (SD) for three full nights. A convenience sample of 78 adults were recruited in this research with a mean age of 27.6... 11.0 years. Comparisons between wearable trackers and sleep outcomes were analyzed using the mean absolute percentage errors, Pearson correlations, Bland–Altman Plots, and equivalent testing. Trackers that showed the greatest equivalence with the SD for total sleep time were the Jawbone UP3 and Fitbit Charge Heart Rate (effect size = 0.09 and 0.23, respectively). The greatest equivalence with the SD for time in bed was seen with the SenseWear Armband, Garmin Vivosmart, and Jawbone UP3 (effect size = 0.09, 0.16, and 0.07, respectively). Some of the wearable trackers resulted in closer approximations to self-reported sleep outcomes than a previously sleep research-grade device, these trackers offer a lower-cost alternative to tracking sleep in healthy populations

Systematic review of symptom clusters in cardiovascular disease

Background: Although individual symptoms and symptom trajectories for various cardiovascular conditions have been reported, there is limited research identifying the symptom clusters that may provide a better understanding of patients’ experiences with heart disease. Aims: To summarize the state of the science in symptom cluster research for patients with acute coronary syndrome, myocardial infarction, coronary artery bypass surgery, and heart failure through systematic review and to provide direction for the translation of symptom cluster research into the clinical setting. Methods: Databases were searched for articles from January 2000 through to May 2015 using MESH terms “symptoms, symptom clusters, acute coronary syndrome (ACS), myocardial infarction (MI), coronary heart disease (CHD), ischemic heart disease (IHD), heart failure (HF), coronary artery bypass surgery (CABS), cluster analyses, and latent classes.” The search was limited to human studies, English language articles, and original articles investigating symptom clusters in individuals with heart disease. Fifteen studies meeting the criteria were included. Results: For patients with ACS and MI, younger persons were more likely to experience clusters with the most symptoms. Older adults were more likely to experience clusters with the lowest number of symptoms and more diffuse and milder symptom clusters that are less reflective of classic ACS presentations. For HF patients, symptom clusters frequently included physical and emotional/cognitive components; edema clustered in only three studies. Symptom expression was congruent across geographical regions and cultures. Conclusions: The findings demonstrated similarities in symptom clusters during ACS, MI, and HF, despite multiple methods and analyses. These results may help clinicians to prepare at-risk patients for proper treatment-seeking and symptom self-management behaviors

Comparison of Wearable Trackers’ Ability to Estimate Sleep

Tracking physical activity and sleep patterns using wearable trackers has become a current trend. However, little information exists about the comparability of wearable trackers measuring sleep. This study examined the comparability of wearable trackers for estimating sleep measurement with a sleep diary (SD) for three full nights. A convenience sample of 78 adults were recruited in this research with a mean age of 27.6 ± 11.0 years. Comparisons between wearable trackers and sleep outcomes were analyzed using the mean absolute percentage errors, Pearson correlations, Bland–Altman Plots, and equivalent testing. Trackers that showed the greatest equivalence with the SD for total sleep time were the Jawbone UP3 and Fitbit Charge Heart Rate (effect size = 0.09 and 0.23, respectively). The greatest equivalence with the SD for time in bed was seen with the SenseWear Armband, Garmin Vivosmart, and Jawbone UP3 (effect size = 0.09, 0.16, and 0.07, respectively). Some of the wearable trackers resulted in closer approximations to self-reported sleep outcomes than a previously sleep research-grade device, these trackers offer a lower-cost alternative to tracking sleep in healthy populations

Association between Caffeine Intake and All-Cause and Cause-Specific Mortality: An Analysis of the National Health and Nutrition Examination Survey (NHANES) 1999–2014 Database

Sixty-four percent of adults in America drink coffee daily, and caffeine is the main reason people tend to drink coffee habitually. Few studies have examined the association between caffeine and all-cause and cause-specific mortality. The objective of this study was to examine the association between caffeine and all-cause and cause-specific mortality using the National Health and Nutrition Examination Survey (NHANES) 1999–2014 database. The multivariate Cox proportional hazards regression model was used to examine 23,878 individuals 20 years and older. Daily caffeine intake was measured once at baseline. A total of 2206 deaths occurred, including 394 cardiovascular (CVD) deaths and 525 cancer deaths. Compared to those with a caffeine intake of <100 mg/day, the hazard ratios (HRs) for CVD mortality were significantly lower in the participants with a caffeine intake of 100–200 mg/day (HR, 0.63; 95% confidence interval [CI], 0.45–0.88), and those with a caffeine intake of >200 mg/day (HR, 0.67; 95% CI, 0.50–0.88) after adjusting for potential confounders. The HRs for all-cause mortality were significantly lower in the participants with a caffeine intake of 100–200 mg/day (HR, 0.78; 95% CI, 0.67–0.91), and those with a caffeine intake of >200 mg/day (HR, 0.68; 95% CI, 0.60–0.78). Subgroup analyses showed that caffeine may have different effects on all-cause mortality among different age and body mass index (BMI) groups. In conclusion, higher caffeine intake was associated with lower all-cause and CVD mortality

Spirituality and well being among elders: differences between elders with heart failure and those without heart failure

Mary T Quinn Griffin1, Yi-Hui Lee2, Ali Salman1, Yaewon Seo1, Patricia A Marin3, Randall C Starling3, Joyce J Fitzpatrick11Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, OH; 2College of Nursing and Health Wright State University Dayton, OH; 3Cleveland Clinic, Cleveland, OhioAbstract: Heart failure is a chronic debilitating disease that affects all aspects of a person’s life, including physical, mental and spiritual dimensions. The associations among these dimensions, and the relationship to overall health status, have not been clearly identified. The purpose of this quantitative, descriptive study was to explore differences between spirituality, depressive symptoms, and quality of life among elders with and without heart failure. A total of 44 elders with heart failure and 40 non-heart failure elders completed several questionnaires including: The Daily Spiritual Experiences Scale (DSES), Spirituality Index of Well-Being (SIWB), Center for Epidemiologic Studies Depression Scale (CES-D), and SF-12™ Health Survey. There were significant differences in the groups on gender and ethnicity; thus these variables were controlled in the analyses related to the dependent variables. After controlling for gender and ethnicity, there were significant differences in the physical component of quality of life and spiritual well-being. The heart failure patients had significantly lower physical quality of life but more spiritual well-being than the non-heart failure patients. There were no significant differences in daily spiritual experiences, mental component of quality of life, and depressive symptoms between the two groups.Keywords: spiritual experience, spiritual well-being, heart failure, depressive symptoms, quality of life, elder