This randomized clinical trial examines the energy intake, energy expenditure, and body weight in adults who slept less than 6.5 hours per night.

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Effect of Sleep Extension on Objectively Assessed Energy Intake Among Adults With Overweight in Real-life Settings

PURPOSE This study aimed to present age- and sex-specific percentiles for daily wrist-worn movement metrics in US youth and adults. This metric represents a summary of all recorded movement, regardless of the purpose, context, or intensity. METHODS Wrist-worn accelerometer data from the combined 2011-2014 National Health and Nutrition Examination Survey cycles and the 2012 National Health and Nutrition Examination Survey National Youth Fitness Survey were used for this analysis. Monitor-Independent Movement Summary units (MIMS-units) from raw triaxial accelerometer data were used. We removed the partial first and last assessment days and days with ≥5% nonwear time. Participants with ≥1 valid day were included. Mean MIMS-units were calculated across all valid days. Percentile tables and smoothed curves of daily MIMS-units were calculated for each age and sex using the Generalized Additive Models for Location Shape and Scale. RESULTS The analytical sample included 14,705 participants age ≥3 yr. The MIMS-unit activity among youth was similar for both sexes, whereas adult females generally had higher MIMS-unit activity than did males. Median daily MIMS-units peaked at age 6 yr for both sexes (males, 20,613; females, 20,706). Lowest activity was observed for males and females 80+ yr of age: 8799 and 9503, respectively. CONCLUSIONS Population referenced MIMS-unit percentiles for US youth and adults are a novel means of characterizing total activity volume. By using MIMS-units, we provide a standardized reference that can be applied across various wrist-worn accelerometer devices. Further work is needed to link these metrics to activity intensity categories and health outcomes.

US Population-referenced Percentiles for Wrist-Worn Accelerometer-derived Activity.

Movement-based sleep-wake detection devices (i.e., actigraphy devices) were first developed in the early 1970s and have repeatedly been validated against polysomnography, which is considered the "gold-standard" of sleep measurement. Indeed, they have become important tools for objectively inferring sleep in free-living conditions. Standard actigraphy devices are rooted in accelerometry to measure movement and make predictions, via scoring algorithms, as to whether the wearer is in a state of wakefulness or sleep. Two important developments have become incorporated in newer devices. First, additional sensors, including measures of heart rate and heart rate variability and higher resolution movement sensing through triaxial accelerometers, have been introduced to improve upon traditional, movement-based scoring algorithms. Second, these devices have transcended scientific utility and are now being manufactured and distributed to the general public. This review will provide an overview of: (1) the history of actigraphic sleep measurement, (2) the physiological underpinnings of heart rate and heart rate variability measurement in wearables, (3) the refinement and validation of both standard actigraphy and newer, multisensory devices for real-world sleep-wake detection, (4) the practical applications of actigraphy, (5) important limitations of actigraphic measurement, and lastly (6) future directions within the field.

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Past, Present, and Future of Multisensory Wearable Technology to Monitor Sleep and Circadian Rhythms.

In Parkinson's disease (PD), abnormal movements consisting of hypokinetic and hyperkinetic manifestations commonly lead to nocturnal distress and sleep impairment, which significantly impact quality of life. In PD patients, these nocturnal disturbances can reflect disease-related complications (e.g., nocturnal akinesia), primary sleep disorders (e.g., rapid eye movement behaviour disorder), or both, thus requiring different therapeutic approaches. Wearable technologies based on actigraphy and innovative sensors have been proposed as feasible solutions to identify and monitor the various types of abnormal nocturnal movements in PD. This narrative review addresses the topic of abnormal nocturnal movements in PD and discusses how wearable technologies could help identify and assess these disturbances. We first examine the pathophysiology of abnormal nocturnal movements and the main clinical and instrumental tools for the evaluation of these disturbances in PD. We then report and discuss findings from previous studies assessing nocturnal movements in PD using actigraphy and innovative wearable sensors. Finally, we discuss clinical and technical prospects supporting the use of wearable technologies for the evaluation of nocturnal movements.

Shedding Light on Nocturnal Movements in Parkinson’s Disease: Evidence from Wearable Technologies

Despite prolific demands and sales, commercial sleep assessment is primarily limited by the inability to "measure" sleep itself; rather, secondary physiological signals are captured, combined, and subsequently classified as sleep or a specific sleep state. Using markedly different approaches compared with gold-standard polysomnography, wearable companies purporting to measure sleep have rapidly developed during recent decades. These devices are advertised to monitor sleep via sensors such as accelerometers, electrocardiography, photoplethysmography, and temperature, alone or in combination, to estimate sleep stage based upon physiological patterns. However, without regulatory oversight, this market has historically manufactured products of poor accuracy, and rarely with third-party validation. Specifically, these devices vary in their capacities to capture a signal of interest, process the signal, perform physiological calculations, and ultimately classify a state (sleep vs. wake) or sleep stage during a given time domain. Device performance depends largely on success in all the aforementioned requirements. Thus, this review provides context surrounding the complex hardware and software developed by wearable device companies in their attempts to estimate sleep-related phenomena, and outlines considerations and contributing factors for overall device success.

Deconstructing Commercial Wearable Technology: Contributions toward Accurate and Free-Living Monitoring of Sleep

Actigraphy, a method for inferring sleep/wake patterns based on movement data gathered using actigraphs, is increasingly used in population-based epidemiologic studies because of its ability to monitor activity in natural settings. Using special software, actigraphic data are analyzed to estimate a range of sleep parameters. To date, despite extensive application of actigraphs in sleep research, published literature specifically detailing the methodology for derivation of sleep parameters is lacking; such information is critical for the appropriate analysis and interpretation of actigraphy data. Reporting of sleep parameters has also been inconsistent across studies, likely reflecting the lack of consensus regarding the definition of sleep onset and offset. In addition, actigraphy data are generally underutilized, with only a fraction of the sleep parameters generated through actigraphy routinely used in current sleep research. The objectives of this paper are to review existing algorithms used to estimate sleep/wake cycles from movement data, demonstrate the rules/methods used for estimating sleep parameters, provide clear technical definitions of the parameters, and suggest potential new measures that reflect intraindividual variability. Utilizing original data collected using Motionlogger Sleep Watch (Ambulatory Monitoring Inc., Ardsley, NY), we detail the methodology and derivation of 29 nocturnal sleep parameters, including those both widely and rarely utilized in research. By improving understanding of the actigraphy process, the information provided in this paper may help: ensure appropriate use and interpretation of sleep parameters in future studies; enable the recalibration of sleep parameters to address specific goals; inform the development of new measures; and increase the breadth of sleep parameters used.

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Actigraphy-Based Assessment of Sleep Parameters.

Law enforcement is a dangerous profession not only due to assaults, accidents and homicides but also due to health risks. This study examined trends in the national frequency and rate of law enforcement job-related illness deaths in the United States over a 22-year period (1997–2018).,Data were obtained from the National Law Enforcement Officers Memorial Fund (NLEOMF) on death frequencies related to health issues at work. Death rates were based on the total number of police officers in the United States [rate = (frequency/population at risk) × 100,000]. Trends were examined using standardized regression.,A total of 646 deaths were attributed to job-related illness. There was a significant upward trend in overall job-related illness deaths (frequency analyses: β = 0.88, p < 0.0001; rate analyses: β = 0.82, p ≤ 0.0001) mainly driven by a significant increase in 911 cancer deaths (frequency analyses: β = 0.88, p < 0.0001; rate analyses: β = 0.88, p ≤ 0.0001). Nearly 82 percent of circulatory deaths were from a heart attack, with an average death age of 46.5 years.,Deaths were not included if they failed to meet medical requirements of the NLEOMF. The data are descriptive, do not estimate risk and should be interpreted cautiously.,Police wellness programs may help to reduce the danger of deaths associated with job-related illness.,This is among the first studies to examine frequency and rate of police health–related deaths due to job exposures.

Hidden danger : A 22-years analysis of law enforcement deaths associated with duty-related illnesses (1997–2018)

Objective Little information is available on the prevalence and associated risk factors of diabetes and prediabetes in the community located in Hangzhou city, Zhejiang Province, southeast China. This study aims to investigate the prevalence of adult diabetes and prediabetes and their associated risk factors among a community population in Hangzhou. Methods A multistage sampling method was used in this study. Ten communities located in Shangcheng district of Hangzhou city were selected, and 3096 permanent residents (resident for ≥6 months) aged 18 years and above were enrolled into this study. Finally, a total of 2986 participants were included. A questionnaire interview and physical examination were conducted for all participants by trained investigators in a local medical center. Anthropometric measurements covered height, weight, waist circumference (WC) and blood pressure, while the blood tests included fasting blood glucose, an oral glucose tolerance test and fasting lipid profiles. The American Diabetes Association diabetes diagnosis criteria were used to discriminate among normal blood glucose, diabetes and prediabetes. The Rao–Scott adjusted χ2 test and complex sampling design-based unconditional multivariate logistic regression analysis were used to evaluate factors associated with diabetes and prediabetes. Descriptive and inferential statistics were calculated in Stata version 15. P-values <0.05 indicate statistical significance. Results The overall prevalence of diabetes was 13.97%, of which 81.54% had prediagnosed diabetes and 18.46% were newly diagnosed with diabetes in the present study. The prevalence of prediabetes was 18.89%. Multivariable logistic regression analysis showed that age, education, once smoking, family history of diabetes, obesity, central obesity and hypertension were factors associated with diabetes, while age, smoking, drinking, central obesity and hypertension were significant factors related to prediabetes. Conclusion The prevalence of diabetes and prediabetes in adults in Hangzhou city remains high. Interventions aiming to modify risk factors such as drinking, obesity, central obesity and hypertension are urgently required.

https://www.dovepress.com/getfile.php?fileID=78760

Mingming Shi

Papers

Actigraphy-Based Assessment of Sleep Parameters.

Hidden danger : A 22-years analysis of law enforcement deaths associated with duty-related illnesses (1997–2018)

The Prevalence of Diabetes, Prediabetes and Associated Risk Factors in Hangzhou, Zhejiang Province: A Community-Based Cross-Sectional Study