Dataset Information

Daily Patterns of Accelerometer Activity Predict Changes in Sleep, Cognition, and Mortality in Older Men.

ABSTRACT:

Background

There is growing interest in the area of "wearable tech" and its relationship to health. A common element of many of these devices is a triaxial accelerometer that can yield continuous information on gross motor activity levels; how such data might predict changes in health is less clear.

Methods

We examined accelerometry data from 2,976 older men who were part of the Osteoporotic Fractures in Men (MrOS) study. Using a shape-naive technique, functional principal component analysis, we examined the patterns of motor activity over the course of 4-7 days and determined whether these patterns were associated with changes in polysomnographic-determined sleep and cognitive function (Trail Making Test-Part B [Trails B], Modified Mini-Mental State Examination [3MS]), as well as mortality over 6.5-8 years of follow-up.

Results

In comparing baseline to 6.5 years later, multivariate modeling indicated that low daytime activity at baseline was associated with worsening of sleep efficiency (p < .05), more wake after sleep onset (p < .05), and a decrease in cognition (Trails B; p < .001), as well as a 1.6-fold higher rate of all-cause mortality (hazard ratio = 1.64 [1.34-2.00]). Earlier wake and bed times were associated with a decrease in cognition (3MS; p < .05). Having a late afternoon peak in activity was associated with a 1.4-fold higher rate of all-cause mortality (hazard ratio = 1.46 [1.21-1.77]). Those having a longer duration of their daytime activity with a bimodal activity pattern also had over a 1.4-fold higher rate of cardiovascular-related mortality (hazard ratio = 1.42 [1.02-1.98]).

Conclusions

Patterns of daily activity may be useful as predictive biomarkers for changes in clinically relevant outcomes, including mortality and changes in sleep and cognition in older men.

SUBMITTER: Zeitzer JM

PROVIDER: S-EPMC5905637 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Publications

Daily Patterns of Accelerometer Activity Predict Changes in Sleep, Cognition, and Mortality in Older Men.

Zeitzer Jamie M JM Blackwell Terri T Hoffman Andrew R AR Cummings Steve S Ancoli-Israel Sonia S Stone Katie K

The journals of gerontology. Series A, Biological sciences and medical sciences 20180401 5

<h4>Background</h4>There is growing interest in the area of "wearable tech" and its relationship to health. A common element of many of these devices is a triaxial accelerometer that can yield continuous information on gross motor activity levels; how such data might predict changes in health is less clear.<h4>Methods</h4>We examined accelerometry data from 2,976 older men who were part of the Osteoporotic Fractures in Men (MrOS) study. Using a shape-naive technique, functional principal compone ...[more]

PMID: 28158467

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Project description:BackgroundSleep efficiency is often used as a measure of sleep quality. Getting sufficiently high-quality sleep has been associated with better cognitive function among older adults; however, the relationship between day-to-day sleep quality variability and cognition has not been well-established.ObjectiveWe aimed to determine the relationship between day-to-day sleep efficiency variability and cognitive function among older adults, using accelerometer data and 3 cognitive tests.MethodsWe included older adults aged >65 years with at least 5 days of accelerometer wear time from the National Health and Nutrition Examination Survey (NHANES) who completed the Digit Symbol Substitution Test (DSST), the Consortium to Establish a Registry for Alzheimer's Disease Word-Learning subtest (CERAD-WL), and the Animal Fluency Test (AFT). Sleep efficiency was derived using a data-driven machine learning algorithm. We examined associations between sleep efficiency variability and scores on each cognitive test adjusted for age, sex, education, household income, marital status, depressive symptoms, diabetes, smoking habits, alcohol consumption, arthritis, heart disease, prior heart attack, prior stroke, activities of daily living, and instrumental activities of daily living. Associations between average sleep efficiency and each cognitive test score were further examined for comparison purposes.ResultsA total of 1074 older adults from the NHANES were included in this study. Older adults with low average sleep efficiency exhibited higher levels of sleep efficiency variability (Pearson r=-0.63). After adjusting for confounding factors, greater average sleep efficiency was associated with higher scores on the DSST (per 10% increase, β=2.25, 95% CI 0.61 to 3.90) and AFT (per 10% increase, β=.91, 95% CI 0.27 to 1.56). Greater sleep efficiency variability was univariably associated with worse cognitive function based on the DSST (per 10% increase, β=-3.34, 95% CI -5.33 to -1.34), CERAD-WL (per 10% increase, β=-1.00, 95% CI -1.79 to -0.21), and AFT (per 10% increase, β=-1.02, 95% CI -1.68 to -0.36). In fully adjusted models, greater sleep efficiency variability remained associated with lower DSST (per 10% increase, β=-2.01, 95% CI -3.62 to -0.40) and AFT (per 10% increase, β=-.84, 95% CI -1.47 to -0.21) scores but not CERAD-WL (per 10% increase, β=-.65, 95% CI -1.39 to 0.08) scores.ConclusionsTargeting consistency in sleep quality may be useful for interventions seeking to preserve cognitive function among older adults.

Project description:STUDY OBJECTIVES:The goal of this study was to examine daily associations between sleep and cognition in older adults suffering from insomnia, with or without a history of chronic pain. METHODS:Sixty older adults with insomnia and a history of chronic pain (HxCP; n = 33, mean age = 69.5 years, standard deviation = 7.8) or no history of chronic pain (NCP; n = 27, mean age = 69.7 years, standard deviation = 7.9) completed 14 days of diaries and actigraphy, measuring sleep onset latency (SOL), wake after sleep onset (WASO), sleep efficiency (SE), and sleep quality. Participants completed daily cognitive measures of processing speed (ie, symbol digit modalities test, SDMT), reasoning (ie, letter series), and verbal memory (ie, word list delayed recall). For HxCP and NCP, associations between sleep parameters, daily pain, depressive symptoms (ie, Beck Depression Inventory, Second Edition scores), and daily cognition, controlling for age, and global cognition were examined through multilevel modeling. RESULTS:For HxCP, greater self-reported WASO was associated with worse next-day SDMT performance, whereas greater actigraphic WASO was associated with better next-day SDMT performance. Greater depression was associated with worse daily letter series performance. Greater self-reported WASO and SE were associated with better next-day delayed recall. For NCP, greater self-reported WASO and depression were associated with better daily SDMT performance, whereas worse daily pain was associated with worse SDMT and delayed recall performance. CONCLUSIONS:In older adults with HxCP, improving sleep may benefit lower level cognition, whereas reducing depression may affect higher level cognition. Discrepancies in sleep parameters promote assessment of objective and subjective sleep outcomes when investigating effects of insomnia on cognition. CLINICAL TRIAL REGISTRATION:Title: Intraindividual Variability in Sleep and Cognitive Performance in Older Adults (REST), Registry: ClinicalTrials.gov, Identifier: NCT02967185, URL: https://clinicaltrials.gov/ct2/show/NCT02967185.

Project description:ObjectiveTo test the hypothesis that non-frail older men with poorer sleep at baseline are at increased risk of frailty and death at follow-up.MethodsIn this prospective cohort study, subjective (questionnaires) and objective sleep parameters (actigraphy, in-home overnight polysomnography) were measured at baseline in 2505 non-frail men aged ≥67years. Repeat frailty status assessment performed an average of 3.4 years later; vital status assessed every four months. Sleep parameters expressed as dichotomized predictors using clinical cut-points. Status at follow-up exam classified as robust, intermediate (pre-frail) stage, frail, or died in interim.ResultsNone of the sleep disturbances were associated with the odds of being intermediate/frail/dead (vs. robust) at follow-up. Poor subjective sleep quality (multivariable odds ratio [MOR] 1.26, 95% CI 1.01-1.58), greater nighttime wakefulness (MOR 1.31, 95% CI 1.04-1.66), and greater nocturnal hypoxemia (MOR 1.47, 95% CI 1.02-2.10) were associated with a higher odds of frailty/death at follow-up (vs. robust/intermediate). Excessive daytime sleepiness (MOR 1.60, 95% CI 1.03-2.47), greater nighttime wakefulness (MOR 1.57, 95% CI 1.12-2.20), severe sleep apnea (MOR 1.74, 95% CI 1.04-2.89), and nocturnal hypoxemia (MOR 2.28, 95% CI 1.45-3.58) were associated with higher odds of death (vs. robust/intermediate/frail at follow-up). The association between poor sleep efficiency and mortality nearly reached significance (MOR 1.48, 95% CI 0.99-2.22). Short sleep duration and prolonged sleep latency were not associated with frailty/death or death at follow-up.ConclusionsAmong non-frail older men, poor subjective sleep quality, greater nighttime wakefulness, and greater nocturnal hypoxemia were independently associated with higher odds of frailty or death at follow-up, while excessive daytime sleepiness, greater nighttime wakefulness, severe sleep apnea and greater nocturnal hypoxemia were independently associated with an increased risk of mortality.

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Project description:INTRODUCTION:The way physical activity (PA) and sedentary behavior (SB) are accumulated throughout the day (i.e., patterns) may be important for health, but identifying measurable and meaningful metrics of behavioral patterns is challenging. This study evaluated accelerometer-derived metrics to determine whether they predicted PA and SB patterns and were reliably measured. METHODS:We defined and measured 55 metrics that describe daily PA and SB using data collected by using the activPAL monitor in four studies. The first two studies were randomized crossover designs that included recreationally active participants. Study 1 experimentally manipulated time spent in moderate-to-vigorous-intensity PA and sedentary time, and study 2 held time in exercise constant and manipulated SB. Study 3 included inactive participants who increased exercise, decreased sedentary time, or both. The study conditions induced distinct behavioral patterns; thus, we tested whether the new metrics could improve the prediction of an individual's study condition after adjusting for the overall volume of PA or SB using conditional logistic regression. In study 4, we measured the 3-month reliability for the pattern metrics by calculating intraclass correlation coefficients in a community-dwelling sample who wore the activPAL monitor twice for 7 d. RESULTS:In each of the experimental studies, we identified new metrics that could improve the accuracy for predicting condition beyond SB and moderate-to-vigorous-intensity PA volume. In study 1, 23 metrics were predictive of a highly active condition, and in study 2, 24 metrics were predictive of a highly sedentary condition. In study 4, the median intraclass correlation coefficients (25-75th percentiles) of the metrics were 0.59 (0.46-0.65). CONCLUSIONS:Several new metrics were predictive of patterns of SB, exercise, and nonexercise behavior and are moderately reliable for a 3-month period. Applying these metrics to determine whether daily behavioral patterns are associated with health-outcomes is an important area of future research.

Project description:BackgroundTime awake with advancing age is increasingly spent sedentary and has several negative health consequences. We examined associations between the frequency of daily sedentary and active bouts with all-cause mortality.MethodsData are from 2816 men in the Osteoporotic Fractures in Men (MrOS) Study (mean age ± SD: 79.1 ± 5.2 years) with free-living activity monitor (SenseWear® Pro3 Armband) data (5.1 ± 0.3 days worn >90%) at the Year 7 visit (2007-2009). Sedentary bout frequency was defined as the number of sedentary bouts per day lasting 5+ min to activity of any intensity. Active bout frequency was defined as the number of active bouts per day lasting 5+ min to sedentary behavior. Sleep time was excluded from the analysis. Deaths were centrally adjudicated using death certificates. Cox proportional hazard models were used to separately examine associations between quartiles of sedentary (Q1 referent, <13.6 bouts/day) or active (Q1 referent, <5 bouts/day) bout frequency with mortality.ResultsAfter 9.3 ± 3.8 years of follow-up, 1487 (52.8%) men died. Men averaged 16.8 ± 5.1 and 8.2 ± 4.2 sedentary and active bouts/day, respectively. After full covariate adjustment, each quartile reflecting more frequent sedentary bouts (Q4 vs. Q1 HR: 0.69, 95%CI: 0.58, 0.81, p-trend <0.001) was associated with lower mortality risk. Likewise, each quartile reflecting more frequent active bouts (Q4 vs. Q1 HR: 0.58, 95%CI: 0.49, 0.70, p-trend <0.001) was associated with lower mortality risk. Results for the sedentary bouts model remained significant after adjusting for total minutes per day in sedentary behavior (Q4 vs. Q1 HR: 0.63, 95%CI: 0.61, 0.86, p-trend = 0.001). The association between active bout frequency with mortality was attenuated after adjusting for total minutes per day active.ConclusionsRegardless of total time spent sedentary, reducing duration of sedentary bouts with more frequent and shorter bouts may be a simple and feasible method to delay mortality risk among community-dwelling older men.

Dataset Information

Daily Patterns of Accelerometer Activity Predict Changes in Sleep, Cognition, and Mortality in Older Men.

Background

Methods

Results

Conclusions

Publications

Daily Patterns of Accelerometer Activity Predict Changes in Sleep, Cognition, and Mortality in Older Men.

Similar Datasets

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