Racial/ethnic disparities in women's sleep duration, continuity, and quality, and their statistical mediators: Study of Women's Health Across the Nation.

STUDY OBJECTIVES: To describe racial/ethnic differences in sleep duration, continuity, and perceived sleep quality in postmenopausal women and to identify statistical mediators of differences in sleep characteristics. METHODS: Recruited from the observational Study of Women's Health Across the Nation (SWAN), 1,203 (548 white, 303 black, 147 Chinese, 132 Japanese, and 73 Hispanic; mean age 65 years, 97% postmenopausal) women participated in a week-long actigraphy and daily diary study in 2013-2015. Actigraphic measures of sleep duration and wake after sleep onset (WASO), and diary-rated sleep quality were averaged across the week. Candidate mediators included health-related variables; stress; and emotional well-being assessed up to 13 times across 18 years from baseline to sleep study. RESULTS: Whites slept longer than other groups; the significant mediators were concurrent financial hardship and increasing number of stressors for Hispanics or Japanese versus whites. Whites had less WASO than blacks and Hispanics; significant mediators were concurrent number of health problems, physical inactivity, waist circumference, vasomotor symptoms, number of life stressors, and financial hardship, and increasing number of health problems from baseline to sleep study. Whites reported better sleep quality than blacks, Chinese, and Japanese; significant mediators were concurrent physical inactivity, vasomotor symptoms, positive affect, and depressive symptoms. CONCLUSIONS: Sleep differences between blacks or Hispanics versus whites were mediated by health problems, number of stressors, and financial hardship, whereas sleep differences between Chinese or Japanese versus whites were mediated by emotional well-being. This is the first study using formal mediational approaches.

How consumer physical activity monitors could transform human physiology research.

A sedentary lifestyle and lack of physical activity are well-established risk factors for chronic disease and adverse health outcomes. Thus, there is enormous interest in measuring physical activity in biomedical research. Many consumer physical activity monitors, including Basis Health Tracker, BodyMedia Fit, DirectLife, Fitbit Flex, Fitbit One, Fitbit Zip, Garmin Vivofit, Jawbone UP, MisFit Shine, Nike FuelBand, Polar Loop, Withings Pulse O2, and others have accuracies similar to that of research-grade physical activity monitors for measuring steps. This review focuses on the unprecedented opportunities that consumer physical activity monitors offer for human physiology and pathophysiology research because of their ability to measure activity continuously under real-life conditions and because they are already widely used by consumers. We examine current and potential uses of consumer physical activity monitors as a measuring or monitoring device, or as an intervention in strategies to change behavior and predict health outcomes. The accuracy, reliability, reproducibility, and validity of consumer physical activity monitors are reviewed, as are limitations and challenges associated with using these devices in research. Other topics covered include how smartphone apps and platforms, such as the Apple ResearchKit, can be used in conjunction with consumer physical activity monitors for research. Lastly, the future of consumer physical activity monitors and related technology is considered: pattern recognition, integration of sleep monitors, and other biosensors in combination with new forms of information processing.

[Quantified self movement--the new mantra of life insurance companies]. / Quantified Self Movement--das neue Mantra der Lebensversicherer.

Wearables are small personal minicomputers that register biometric data. In such a way, the insurance industry hopes to create new sales opportunities and products, and simplify underwriting. Lower premiums will promote the use of wearables. The related possibilities and unanswered questions are discussed in this article. Utilisation of big data offers the insurance industry a range of new opportunities. The benefit must be proven in the future, however.