An International Study on the Determinants of Poor Sleep Amongst 15,000 Users of Connected Devices.

BACKGROUND: Sleep is a modifiable lifestyle factor that can be a target for efficient intervention studies to improve the quality of life and decrease the risk or burden of some chronic conditions. Knowing the profiles of individuals with poor sleep patterns is therefore a prerequisite. Wearable devices have recently opened new areas in medical research as potential efficient tools to measure lifestyle factors such as sleep quantity and quality. OBJECTIVES: The goal of our research is to identify the determinants of poor sleep based on data from a large population of users of connected devices. METHODS: We analyzed data from 15,839 individuals (13,658 males and 2181 females) considered highly connected customers having purchased and used at least 3 connected devices from the consumer electronics company Withings (now Nokia). Total and deep sleep durations as well as the ratio of deep/total sleep as a proxy of sleep quality were analyzed in association with available data on age, sex, weight, heart rate, steps, and diastolic and systolic blood pressures. RESULTS: With respect to the deep/total sleep duration ratio used as a proxy of sleep quality, we have observed that those at risk of having a poor ratio (≤0.40) were more frequently males (odds ratio [OR]female vs male=0.45, 95% CI 0.38-0.54), younger individuals (OR>60 years vs 18-30 years=0.47, 95% CI 0.35-0.63), and those with elevated heart rate (OR>78 bpm vs ≤61 bpm=1.18, 95% CI 1.04-1.34) and high systolic blood pressure (OR>133 mm Hg vs ≤116 mm Hg=1.22, 95% CI 1.04-1.43). A direct association with weight was observed for total sleep duration exclusively. CONCLUSIONS: Wearables can provide useful information to target individuals at risk of poor sleep. Future alert or mobile phone notification systems based on poor sleep determinants measured with wearables could be tested in intervention studies to evaluate the benefits.

Middle-Aged Men With HIV Have Diminished Accelerometry-Based Activity Profiles Despite Similar Lab-Measured Gait Speed: Pilot Study.

BACKGROUND: People aging with HIV are living with increased risk for functional decline compared with uninfected adults of the same age. Early preclinical changes in biomarkers in middle-aged individuals at risk for mobility and functional decline are needed. OBJECTIVE: This pilot study aims to compare measures of free-living activity with lab-based measures. In addition, we aim to examine differences in the activity level and patterns by HIV status. METHODS: Forty-six men (23 HIV+, 23 HIV-) currently in the MATCH (Muscle and Aging Treated Chronic HIV) cohort study wore a consumer-grade wristband accelerometer continuously for 3 weeks. We used free-living activity to calculate the gait speed and time spent at different activity intensities. Accelerometer data were compared with lab-based gait speed using the 6-minute walk test (6-MWT). Plasma biomarkers were measured and biobehavioral questionnaires were administered. RESULTS: HIV+ men more often lived alone (P=.02), reported more pain (P=.02), and fatigue (P=.048). In addition, HIV+ men had lower blood CD4/CD8 ratios (P<.001) and higher Veterans Aging Cohort Study Index scores (P=.04) and T-cell activation (P<.001) but did not differ in levels of inflammation (P=.30) or testosterone (P=.83). For all participants, accelerometer-based gait speed was significantly lower than the lab-based 6-MWT gait speed (P<.001). Moreover, accelerometer-based gait speed was significantly lower in HIV+ participants (P=.04) despite the absence of differences in the lab-based 6-MWT (P=.39). HIV+ participants spent more time in the lowest quartile of activity compared with uninfected (P=.01), who spent more time in the middle quartiles of activity (P=.02). CONCLUSIONS: Accelerometer-based assessment of gait speed and activity patterns are lower for asymptomatic men living with HIV compared with uninfected controls and may be useful as preclinical digital biomarkers that precede differences captured in lab-based measures.

Home Monitoring of Blood Pressure: Short-Term Changes During Serial Measurements for 56398 Subjects.

Hypertension is one of the greatest contributors to premature morbidity and mortality worldwide. It has been demonstrated that lowering blood pressure (BP) by just a few mmHg can bring substantial clinical benefits, reducing the risk of stroke and ischemic heart disease. Properly managing high BP is one of the most pressing global health issues, but accurate methods to continuously monitoring BP at home are still under discussion. Indeed, the BP for any given individual can fluctuate significantly during intervals as short as a few minutes. In clinical settings, the guidelines suggest to wait for 5 or 10 minutes in seated rest before taking the measure, in order to alleviate the effect of the stress induced by the clinical environment. Alternatively, BP measured in the home environment is thought to provide a more accurate measure free of the stress of a clinical environment, but there is currently a lack of extensive studies on the trajectory of serial BP measurements over minutes in the home setting. In this paper, we aim at filling this gap by analyzing a large dataset of more than 16 million BP measurements taken at home with commercial BP monitoring devices. In particular, we propose new techniques to analyze this dataset, taking into account the limitations due to the uncontrolled data collection, and we study the characteristics of the BP trajectory for consecutive measures over several minutes. We show that the BP values significantly decrease after 10 minutes minutes from the initial measurement (4.1 and 6.6 mmHg for the diastolic and systolic BP, respectively), and continue to decrease for about 25 minutes. We also describe statistically the clinical relevance of this change, observing more than 50% misclassifications for measurements in the hypertension region. We then propose a model to study the inter-subject variability, showing significant variations in the expected decrease in systolic BP. These results may provide the initial evidence for future large clinical studies using participant-monitored BP.

Real World Home Blood Pressure Variability in Over 56,000 Individuals With Nearly 17 Million Measurements.

BACKGROUND: Using the data from 56,365 individuals, from 185 countries, and a Nokia Health Wireless blood pressure (BP) monitor, we investigated real-world characteristics of BP variability (BPV). METHODS: All included individuals self-measured and uploaded their BP using Bluetooth at least 20 times over a period of ≥1 month at a frequency and duration of their choosing. In total, 16,904,844 BP measurements were analyzed, with a median of 146 measurements per person (interquartile range [IQR] 73-321) over a median of 14 months (IQR 7-31). SD, coefficient of variation, maximum BP, and maximum minus minimum BP difference were all calculated as measures of BPV. RESULTS: BPV showed a distinct pattern, influenced by season of year, day of week, and time of day. BPV index was higher in females compared with males (P < 0.001) and increased with age (P < 0.001). Compared to the weekend, the weekday BPV index was significantly higher, and this finding was more prominent in females (P = 0.001). In multivariate analysis, BPV index were significantly associated with age, gender, geographic location, and mean BP values. CONCLUSION: Using the largest BP data set we are aware of, with the benefits and limitations of real-world measurement, we could show the pattern of BPV and provide reference values that may be helpful in understanding the nature of BPV as self-measurement at home becomes more common, and help guide individualized management.

Cross-Sectional and longitudinal associations of objectively-measured physical activity on blood pressure: evaluation in 37 countries.

Background: We examined the cross-sectional and longitudinal associations of objectively-measured physical activity (step counts) and blood pressure (BP) among adults spanning 37 countries. Methods: Across 37 countries, we used data from a pool of 9238 adult owners of Withings' Pulse activity trackers, which measures steps taken each day, and Wireless Blood Pressure Monitor, which measures BP. Analyses were adjusted on age, sex, number of days where the tracker was worn, and number of BP measurements. Data was collected from 2009 to 2013. Results: Subjects had a mean ± standard deviation (SD) age of 51.6 ± 11.3 years and a body mass index (BMI) of 28.7±5.5 kg/m2. A 1-month increase of more than 3000 steps per day was associated with a decrease of systolic BP (SBP) and diastolic BP (DBP) among the obese (1.57mm Hg and 1.29 mm Hg respectively, both P<0.001) and the overweight population (0.79 mm Hg and 0.84 mm Hg respectively, both P≤0.001), but not in the normal weight population (P=0.60 and P=0.36 respectively). Conclusion: One-month increases in daily step counts was associated with a decrease of SBP and DBP in a large obese and overweight free living population.