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BMJ (Clinical Research Ed.) Aug 2019To examine the dose-response associations between accelerometer assessed total physical activity, different intensities of physical activity, and sedentary time and all... (Meta-Analysis)
Meta-Analysis
OBJECTIVE
To examine the dose-response associations between accelerometer assessed total physical activity, different intensities of physical activity, and sedentary time and all cause mortality.
DESIGN
Systematic review and harmonised meta-analysis.
DATA SOURCES
PubMed, PsycINFO, Embase, Web of Science, Sport Discus from inception to 31 July 2018.
ELIGIBILITY CRITERIA
Prospective cohort studies assessing physical activity and sedentary time by accelerometry and associations with all cause mortality and reported effect estimates as hazard ratios, odds ratios, or relative risks with 95% confidence intervals.
DATA EXTRACTION AND ANALYSIS
Guidelines for meta-analyses and systematic reviews for observational studies and PRISMA guidelines were followed. Two authors independently screened the titles and abstracts. One author performed a full text review and another extracted the data. Two authors independently assessed the risk of bias. Individual level participant data were harmonised and analysed at study level. Data on physical activity were categorised by quarters at study level, and study specific associations with all cause mortality were analysed using Cox proportional hazards regression analyses. Study specific results were summarised using random effects meta-analysis.
MAIN OUTCOME MEASURE
All cause mortality.
RESULTS
39 studies were retrieved for full text review; 10 were eligible for inclusion, three were excluded owing to harmonisation challenges (eg, wrist placement of the accelerometer), and one study did not participate. Two additional studies with unpublished mortality data were also included. Thus, individual level data from eight studies (n=36 383; mean age 62.6 years; 72.8% women), with median follow-up of 5.8 years (range 3.0-14.5 years) and 2149 (5.9%) deaths were analysed. Any physical activity, regardless of intensity, was associated with lower risk of mortality, with a non-linear dose-response. Hazards ratios for mortality were 1.00 (referent) in the first quarter (least active), 0.48 (95% confidence interval 0.43 to 0.54) in the second quarter, 0.34 (0.26 to 0.45) in the third quarter, and 0.27 (0.23 to 0.32) in the fourth quarter (most active). Corresponding hazards ratios for light physical activity were 1.00, 0.60 (0.54 to 0.68), 0.44 (0.38 to 0.51), and 0.38 (0.28 to 0.51), and for moderate-to-vigorous physical activity were 1.00, 0.64 (0.55 to 0.74), 0.55 (0.40 to 0.74), and 0.52 (0.43 to 0.61). For sedentary time, hazards ratios were 1.00 (referent; least sedentary), 1.28 (1.09 to 1.51), 1.71 (1.36 to 2.15), and 2.63 (1.94 to 3.56).
CONCLUSION
Higher levels of total physical activity, at any intensity, and less time spent sedentary, are associated with substantially reduced risk for premature mortality, with evidence of a non-linear dose-response pattern in middle aged and older adults.
SYSTEMATIC REVIEW REGISTRATION
PROSPERO CRD42018091808.
Topics: Accelerometry; Aged; Exercise; Female; Humans; Male; Middle Aged; Mortality; Proportional Hazards Models; Prospective Studies; Risk Factors; Sedentary Behavior
PubMed: 31434697
DOI: 10.1136/bmj.l4570 -
Ageing Research Reviews May 2021Engaging in physical activity (PA) and avoiding sedentary behavior (SB) are important for healthy ageing with benefits including the mitigation of disability and... (Meta-Analysis)
Meta-Analysis Review
The association of objectively measured physical activity and sedentary behavior with skeletal muscle strength and muscle power in older adults: A systematic review and meta-analysis.
BACKGROUND
Engaging in physical activity (PA) and avoiding sedentary behavior (SB) are important for healthy ageing with benefits including the mitigation of disability and mortality. Whether benefits extend to key determinants of disability and mortality, namely muscle strength and muscle power, is unclear.
AIMS
This systematic review aimed to describe the association of objective measures of PA and SB with measures of skeletal muscle strength and muscle power in community-dwelling older adults.
METHODS
Six databases were searched from their inception to June 21, 2020 for articles reporting associations between objectively measured PA and SB and upper body or lower body muscle strength or muscle power in community dwelling adults aged 60 years and older. An overview of associations was visualized by effect direction heat maps, standardized effect sizes were estimated with albatross plots and summarized in box plots. Articles reporting adjusted standardized regression coefficients (β) were included in meta-analyses.
RESULTS
A total of 112 articles were included representing 43,796 individuals (range: 21 to 3726 per article) with a mean or median age from 61.0 to 88.0 years (mean 56.4 % female). Higher PA measures and lower SB were associated with better upper body muscle strength (hand grip strength), upper body muscle power (arm curl), lower body muscle strength, and lower body muscle power (chair stand test). Median standardized effect sizes were consistently larger for measures of PA and SB with lower compared to upper body muscle strength and muscle power. The meta-analyses of adjusted β coefficients confirmed the associations between total PA (TPA), moderate-to-vigorous PA (MVPA) and light PA (LPA) with hand grip strength (β = 0.041, β = 0.057, and β = 0.070, respectively, all p ≤ 0.001), and TPA and MVPA with chair stand test (β = 0.199 and β = 0.211, respectively, all p ≤ 0.001).
CONCLUSIONS
Higher PA and lower SB are associated with greater skeletal muscle strength and muscle power, particularly with the chair stand test.
Topics: Aged; Aged, 80 and over; Exercise; Female; Hand Strength; Humans; Male; Middle Aged; Muscle Strength; Muscle, Skeletal; Sedentary Behavior
PubMed: 33607291
DOI: 10.1016/j.arr.2021.101266 -
Sports Medicine (Auckland, N.Z.) Sep 2017Accelerometers are widely used to measure sedentary time, physical activity, physical activity energy expenditure (PAEE), and sleep-related behaviors, with the ActiGraph... (Review)
Review
BACKGROUND
Accelerometers are widely used to measure sedentary time, physical activity, physical activity energy expenditure (PAEE), and sleep-related behaviors, with the ActiGraph being the most frequently used brand by researchers. However, data collection and processing criteria have evolved in a myriad of ways out of the need to answer unique research questions; as a result there is no consensus.
OBJECTIVES
The purpose of this review was to: (1) compile and classify existing studies assessing sedentary time, physical activity, energy expenditure, or sleep using the ActiGraph GT3X/+ through data collection and processing criteria to improve data comparability and (2) review data collection and processing criteria when using GT3X/+ and provide age-specific practical considerations based on the validation/calibration studies identified.
METHODS
Two independent researchers conducted the search in PubMed and Web of Science. We included all original studies in which the GT3X/+ was used in laboratory, controlled, or free-living conditions published from 1 January 2010 to the 31 December 2015.
RESULTS
The present systematic review provides key information about the following data collection and processing criteria: placement, sampling frequency, filter, epoch length, non-wear-time, what constitutes a valid day and a valid week, cut-points for sedentary time and physical activity intensity classification, and algorithms to estimate PAEE and sleep-related behaviors. The information is organized by age group, since criteria are usually age-specific.
CONCLUSION
This review will help researchers and practitioners to make better decisions before (i.e., device placement and sampling frequency) and after (i.e., data processing criteria) data collection using the GT3X/+ accelerometer, in order to obtain more valid and comparable data.
PROSPERO REGISTRATION NUMBER
CRD42016039991.
Topics: Accelerometry; Adolescent; Aged; Child; Energy Metabolism; Exercise; Female; Humans; Infant, Newborn; Male; Reproducibility of Results; Sedentary Behavior; Sleep
PubMed: 28303543
DOI: 10.1007/s40279-017-0716-0 -
The European Respiratory Journal Dec 2022Physical inactivity is common in asthma and is recognised as an important modifiable risk for poor clinical outcomes such as impaired asthma control and health-related... (Meta-Analysis)
Meta-Analysis Review
INTRODUCTION
Physical inactivity is common in asthma and is recognised as an important modifiable risk for poor clinical outcomes such as impaired asthma control and health-related quality of life (HRQoL). Despite evidence supporting the role of physical activity in reducing the risk of these outcomes, little is known about optimal interventions for increasing physical activity in those with severe disease. This systematic review and meta-analysis evaluates the effectiveness of interventions in increasing physical activity in severe asthma.
METHODS
MEDLINE, the Cumulative Index to Nursing and Allied Health Literature, Embase, PubMed, Informit, SPORTDiscus and Cochrane databases were searched up to September 2021 for physical activity-based intervention studies that assessed physical activity outcomes ( steps per day, time spent undertaking physical activity) in adults with severe asthma. Data on asthma-related ( asthma control) and health-related outcomes ( HRQoL) were assessed as secondary outcomes. The revised Cochrane Risk of Bias tool was used to assess risk of bias. Random-effects meta-analyses synthesised data where possible.
RESULTS
Four randomised controlled trials (all 12 weeks in duration) including 176 adults with moderate-to-severe asthma were included. An increase in physical activity was reported with a moderate-vigorous intensity aerobic and resistance training intervention (steps per day and time spent undertaking physical activity), and an unsupervised pedometer-based intervention (steps per day). Meta-analyses showed that physical activity interventions had an overall positive effect on steps per day (mean difference (MD) 1588, 95% CI 399-2778; p0.009, I=23), asthma control (MD -0.65, 95% CI -0.95--0.35; p<0.0001, I=0%) and HRQoL (MD 0.56, 95% CI 0.10-1.01; p0.02, I=16%) compared to control.
CONCLUSION
While there is some evidence supporting the effectiveness of interventions in improving physical activity in adults with severe asthma, higher-quality, large-scale studies of longer duration are needed to determine the optimal intervention.
Topics: Adult; Humans; Quality of Life; Exercise; Sedentary Behavior; Asthma; Actigraphy
PubMed: 35896208
DOI: 10.1183/13993003.00546-2022 -
The Cochrane Database of Systematic... Jun 2018A large number of people are employed in sedentary occupations. Physical inactivity and excessive sitting at workplaces have been linked to increased risk of... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
A large number of people are employed in sedentary occupations. Physical inactivity and excessive sitting at workplaces have been linked to increased risk of cardiovascular disease, obesity, and all-cause mortality.
OBJECTIVES
To evaluate the effectiveness of workplace interventions to reduce sitting at work compared to no intervention or alternative interventions.
SEARCH METHODS
We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, CINAHL, OSH UPDATE, PsycINFO, ClinicalTrials.gov, and the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) search portal up to 9 August 2017. We also screened reference lists of articles and contacted authors to find more studies.
SELECTION CRITERIA
We included randomised controlled trials (RCTs), cross-over RCTs, cluster-randomised controlled trials (cluster-RCTs), and quasi-RCTs of interventions to reduce sitting at work. For changes of workplace arrangements, we also included controlled before-and-after studies. The primary outcome was time spent sitting at work per day, either self-reported or measured using devices such as an accelerometer-inclinometer and duration and number of sitting bouts lasting 30 minutes or more. We considered energy expenditure, total time spent sitting (including sitting at and outside work), time spent standing at work, work productivity and adverse events as secondary outcomes.
DATA COLLECTION AND ANALYSIS
Two review authors independently screened titles, abstracts and full-text articles for study eligibility. Two review authors independently extracted data and assessed risk of bias. We contacted authors for additional data where required.
MAIN RESULTS
We found 34 studies - including two cross-over RCTs, 17 RCTs, seven cluster-RCTs, and eight controlled before-and-after studies - with a total of 3,397 participants, all from high-income countries. The studies evaluated physical workplace changes (16 studies), workplace policy changes (four studies), information and counselling (11 studies), and multi-component interventions (four studies). One study included both physical workplace changes and information and counselling components. We did not find any studies that specifically investigated the effects of standing meetings or walking meetings on sitting time.Physical workplace changesInterventions using sit-stand desks, either alone or in combination with information and counselling, reduced sitting time at work on average by 100 minutes per workday at short-term follow-up (up to three months) compared to sit-desks (95% confidence interval (CI) -116 to -84, 10 studies, low-quality evidence). The pooled effect of two studies showed sit-stand desks reduced sitting time at medium-term follow-up (3 to 12 months) by an average of 57 minutes per day (95% CI -99 to -15) compared to sit-desks. Total sitting time (including sitting at and outside work) also decreased with sit-stand desks compared to sit-desks (mean difference (MD) -82 minutes/day, 95% CI -124 to -39, two studies) as did the duration of sitting bouts lasting 30 minutes or more (MD -53 minutes/day, 95% CI -79 to -26, two studies, very low-quality evidence).We found no significant difference between the effects of standing desks and sit-stand desks on reducing sitting at work. Active workstations, such as treadmill desks or cycling desks, had unclear or inconsistent effects on sitting time.Workplace policy changesWe found no significant effects for implementing walking strategies on workplace sitting time at short-term (MD -15 minutes per day, 95% CI -50 to 19, low-quality evidence, one study) and medium-term (MD -17 minutes/day, 95% CI -61 to 28, one study) follow-up. Short breaks (one to two minutes every half hour) reduced time spent sitting at work on average by 40 minutes per day (95% CI -66 to -15, one study, low-quality evidence) compared to long breaks (two 15-minute breaks per workday) at short-term follow-up.Information and counsellingProviding information, feedback, counselling, or all of these resulted in no significant change in time spent sitting at work at short-term follow-up (MD -19 minutes per day, 95% CI -57 to 19, two studies, low-quality evidence). However, the reduction was significant at medium-term follow-up (MD -28 minutes per day, 95% CI -51 to -5, two studies, low-quality evidence).Computer prompts combined with information resulted in no significant change in sitting time at work at short-term follow-up (MD -10 minutes per day, 95% CI -45 to 24, two studies, low-quality evidence), but at medium-term follow-up they produced a significant reduction (MD -55 minutes per day, 95% CI -96 to -14, one study). Furthermore, computer prompting resulted in a significant decrease in the average number (MD -1.1, 95% CI -1.9 to -0.3, one study) and duration (MD -74 minutes per day, 95% CI -124 to -24, one study) of sitting bouts lasting 30 minutes or more.Computer prompts with instruction to stand reduced sitting at work on average by 14 minutes per day (95% CI 10 to 19, one study) more than computer prompts with instruction to walk at least 100 steps at short-term follow-up.We found no significant reduction in workplace sitting time at medium-term follow-up following mindfulness training (MD -23 minutes per day, 95% CI -63 to 17, one study, low-quality evidence). Similarly a single study reported no change in sitting time at work following provision of highly personalised or contextualised information and less personalised or contextualised information. One study found no significant effects of activity trackers on sitting time at work.Multi-component interventions Combining multiple interventions had significant but heterogeneous effects on sitting time at work (573 participants, three studies, very low-quality evidence) and on time spent in prolonged sitting bouts (two studies, very low-quality evidence) at short-term follow-up.
AUTHORS' CONCLUSIONS
At present there is low-quality evidence that the use of sit-stand desks reduce workplace sitting at short-term and medium-term follow-ups. However, there is no evidence on their effects on sitting over longer follow-up periods. Effects of other types of interventions, including workplace policy changes, provision of information and counselling, and multi-component interventions, are mostly inconsistent. The quality of evidence is low to very low for most interventions, mainly because of limitations in study protocols and small sample sizes. There is a need for larger cluster-RCTs with longer-term follow-ups to determine the effectiveness of different types of interventions to reduce sitting time at work.
Topics: Accelerometry; Controlled Before-After Studies; Energy Metabolism; Ergonomics; Humans; Posture; Randomized Controlled Trials as Topic; Time Factors; Workplace
PubMed: 29926475
DOI: 10.1002/14651858.CD010912.pub4 -
Journal of Medical Internet Research Nov 2019Wearable sleep monitors are of high interest to consumers and researchers because of their ability to provide estimation of sleep patterns in free-living conditions in a... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Wearable sleep monitors are of high interest to consumers and researchers because of their ability to provide estimation of sleep patterns in free-living conditions in a cost-efficient way.
OBJECTIVE
We conducted a systematic review of publications reporting on the performance of wristband Fitbit models in assessing sleep parameters and stages.
METHODS
In adherence with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, we comprehensively searched the Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane, Embase, MEDLINE, PubMed, PsycINFO, and Web of Science databases using the keyword Fitbit to identify relevant publications meeting predefined inclusion and exclusion criteria.
RESULTS
The search yielded 3085 candidate articles. After eliminating duplicates and in compliance with inclusion and exclusion criteria, 22 articles qualified for systematic review, with 8 providing quantitative data for meta-analysis. In reference to polysomnography (PSG), nonsleep-staging Fitbit models tended to overestimate total sleep time (TST; range from approximately 7 to 67 mins; effect size=-0.51, P<.001; heterogenicity: I=8.8%, P=.36) and sleep efficiency (SE; range from approximately 2% to 15%; effect size=-0.74, P<.001; heterogenicity: I=24.0%, P=.25), and underestimate wake after sleep onset (WASO; range from approximately 6 to 44 mins; effect size=0.60, P<.001; heterogenicity: I=0%, P=.92) and there was no significant difference in sleep onset latency (SOL; P=.37; heterogenicity: I=0%, P=.92). In reference to PSG, nonsleep-staging Fitbit models correctly identified sleep epochs with accuracy values between 0.81 and 0.91, sensitivity values between 0.87 and 0.99, and specificity values between 0.10 and 0.52. Recent-generation Fitbit models that collectively utilize heart rate variability and body movement to assess sleep stages performed better than early-generation nonsleep-staging ones that utilize only body movement. Sleep-staging Fitbit models, in comparison to PSG, showed no significant difference in measured values of WASO (P=.25; heterogenicity: I=0%, P=.92), TST (P=.29; heterogenicity: I=0%, P=.98), and SE (P=.19) but they underestimated SOL (P=.03; heterogenicity: I=0%, P=.66). Sleep-staging Fitbit models showed higher sensitivity (0.95-0.96) and specificity (0.58-0.69) values in detecting sleep epochs than nonsleep-staging models and those reported in the literature for regular wrist actigraphy.
CONCLUSIONS
Sleep-staging Fitbit models showed promising performance, especially in differentiating wake from sleep. However, although these models are a convenient and economical means for consumers to obtain gross estimates of sleep parameters and time spent in sleep stages, they are of limited specificity and are not a substitute for PSG.
Topics: Actigraphy; Female; Humans; Male; Sleep; Wrist
PubMed: 31778122
DOI: 10.2196/16273 -
Behavioural Brain Research Mar 2021Despite increasing evidence that physical activity (PA) contributes to brain health in older individuals, both at the level of brain structure and function, this...
Despite increasing evidence that physical activity (PA) contributes to brain health in older individuals, both at the level of brain structure and function, this relationship is not yet well established. To explore this potential association, a systematic literature search was performed using PubMed, Scopus, and Web of Science, adhering to PRISMA guidelines. A total of 32 studies met the eligibility criteria: 24 cross-sectional and 8 longitudinal. Results from structural Magnetic Resonance Imaging (MRI) showed that PA associated with larger brain volumes (less brain atrophy) specifically in brain regions vulnerable to dementia, comprising the hippocampus, temporal, and frontal regions. Furthermore, functional MRI (fMRI) showed greater task-relevant activity in brain areas recruited in executive function and memory tasks. However, the dose-response relationship is unclear due to the high variability in PA measures. Further research using objective measures is needed to better understand which PA type, intensity, frequency, and duration, has the greatest protective effect on brain health. Findings highlight the importance of PA in both cognitive decline and dementia prevention.
Topics: Aged; Aging; Brain; Cognitive Dysfunction; Dementia; Exercise; Humans
PubMed: 33359570
DOI: 10.1016/j.bbr.2020.113061 -
BMC Public Health Jun 2016The aim of this study is to review accelerometer wear methods and correlations between accelerometry and physical activity questionnaire data, depending on participant... (Review)
Review
BACKGROUND
The aim of this study is to review accelerometer wear methods and correlations between accelerometry and physical activity questionnaire data, depending on participant characteristics.
METHODS
We included 57 articles about physical activity measurement by accelerometry and questionnaires. Criteria were to have at least 100 participants of at least 18 years of age with manuscripts available in English. Accelerometer wear methods were compared. Spearman and Pearson correlation coefficients between questionnaires and accelerometers and differences between genders, age categories, and body mass index (BMI) categories were assessed.
RESULTS
In most investigations, requested wear time was seven days during waking hours and devices were mostly attached on hips with waist belts. A minimum of four valid days with wear time of at least ten hours per day was required in most studies. Correlations (r = Pearson, ρ = Spearman) of total questionnaire scores against accelerometer measures across individual studies ranged from r = 0.08 to ρ = 0.58 (P < 0.001) for men and from r = -0.02 to r = 0.49 (P < 0.01) for women. Correlations for total physical activity among participants with ages ≤65 ranged from r = 0.04 to ρ = 0.47 (P < 0.001) and from r = 0.16 (P = 0.02) to r = 0.53 (P < 0.01) among the elderly (≥65 years). Few studies investigated stratification by BMI, with varying cut points and inconsistent results.
CONCLUSION
Accelerometers appear to provide slightly more consistent results in relation to self-reported physical activity among men. Nevertheless, due to overall limited consistency, different aspects measured by each method, and differences in the dimensions studied, it is advised that studies use both questionnaires and accelerometers to gain the most complete physical activity information.
Topics: Accelerometry; Exercise; Humans; Reproducibility of Results; Self Report; Surveys and Questionnaires
PubMed: 27306667
DOI: 10.1186/s12889-016-3172-0 -
Journal of Medical Internet Research Aug 2019Among areas that have challenged the progress of dementia care has been the assessment of change in symptoms over time. Digital biomarkers are defined as objective,...
Current State of Digital Biomarker Technologies for Real-Life, Home-Based Monitoring of Cognitive Function for Mild Cognitive Impairment to Mild Alzheimer Disease and Implications for Clinical Care: Systematic Review.
BACKGROUND
Among areas that have challenged the progress of dementia care has been the assessment of change in symptoms over time. Digital biomarkers are defined as objective, quantifiable, physiological, and behavioral data that are collected and measured by means of digital devices, such as embedded environmental sensors or wearables. Digital biomarkers provide an alternative assessment approach, as they allow objective, ecologically valid, and long-term follow-up with continuous assessment. Despite the promise of a multitude of sensors and devices that can be applied, there are no agreed-upon standards for digital biomarkers, nor are there comprehensive evidence-based results for which digital biomarkers may be demonstrated to be most effective.
OBJECTIVE
In this review, we seek to answer the following questions: (1) What is the evidence for real-life, home-based use of technologies for early detection and follow-up of mild cognitive impairment (MCI) or dementia? And (2) What transformation might clinicians expect in their everyday practices?
METHODS
A systematic search was conducted in PubMed, Cochrane, and Scopus databases for papers published from inception to July 2018. We searched for studies examining the implementation of digital biomarker technologies for mild cognitive impairment or mild Alzheimer disease follow-up and detection in nonclinic, home-based settings. All studies that included the following were examined: community-dwelling older adults (aged 65 years or older); cognitively healthy participants or those presenting with cognitive decline, from subjective cognitive complaints to early Alzheimer disease; a focus on home-based evaluation for noninterventional follow-up; and remote diagnosis of cognitive deterioration.
RESULTS
An initial sample of 4811 English-language papers were retrieved. After screening and review, 26 studies were eligible for inclusion in the review. These studies ranged from 12 to 279 participants and lasted between 3 days to 3.6 years. Most common reasons for exclusion were as follows: inappropriate setting (eg, hospital setting), intervention (eg, drugs and rehabilitation), or population (eg, psychiatry and Parkinson disease). We summarized these studies into four groups, accounting for overlap and based on the proposed technological solutions, to extract relevant data: (1) data from dedicated embedded or passive sensors, (2) data from dedicated wearable sensors, (3) data from dedicated or purposive technological solutions (eg, games or surveys), and (4) data derived from use of nondedicated technological solutions (eg, computer mouse movements).
CONCLUSIONS
Few publications dealt with home-based, real-life evaluations. Most technologies were far removed from everyday life experiences and were not mature enough for use under nonoptimal or uncontrolled conditions. Evidence available from embedded passive sensors represents the most relatively mature research area, suggesting that some of these solutions could be proposed to larger populations in the coming decade. The clinical and research communities would benefit from increasing attention to these technologies going forward.
Topics: Accelerometry; Aged; Alzheimer Disease; Automobile Driving; Biomarkers; Cognition; Cognitive Dysfunction; Disease Progression; Early Diagnosis; Geographic Information Systems; Humans; Independent Living; Surveys and Questionnaires; Technology; Telemedicine; Wearable Electronic Devices
PubMed: 31471958
DOI: 10.2196/12785 -
Sleep Medicine Reviews Oct 2021Epidemiological and interventional research has highlighted sleep as a potentially modifiable risk factor associated with poor physical and mental health. Emerging... (Meta-Analysis)
Meta-Analysis Review
Epidemiological and interventional research has highlighted sleep as a potentially modifiable risk factor associated with poor physical and mental health. Emerging evidence from (behavioral) genetic research also shows that sleep characteristics are under strong genetic control. With this study we aimed to meta-analyze the literature in this area to quantify the heritability of sleep duration and sleep quality in the general population. We conducted a systematic literature search in five online databases on January 24th 2020. Two authors independently screened 5644 abstracts, and 160 complete articles for the inclusion criteria of twin studies from the general population reporting heritability statistics on sleep duration and/or quality, and written in English. We ultimately included 23 papers (19 independent samples: 45,328 twins between 6 mo and 88 y) for sleep duration, and 13 papers (10 independent samples: 39,020 twins between 16 and 95 y) for sleep quality. Collectively, we showed that 46% of the variability in sleep duration and 44% of the variability in sleep quality is genetically determined. The remaining variation in the sleep characteristics can mostly be attributed to the unique environment the twins experience, although the shared environment seemed to play a role for the variability of childhood sleep duration. Meta-analyzed heritability estimates for sleep duration, however, varied substantially with age (17% infancy, 20-52% childhood, 69% adolescence and 42-45% adulthood) and reporter (8% parent-report, 38-52% self-report). Heritability estimates for actigraphic and Polysomnography (PSG)-estimated sleep were based on few small samples, warranting more research. Our findings highlight the importance of considering genetic influences when aiming to understand the underlying mechanisms contributing to the trajectories of sleep patterns across the lifespan.
Topics: Actigraphy; Adolescent; Adult; Humans; Polysomnography; Self Report; Sleep; Sleep Wake Disorders
PubMed: 33636423
DOI: 10.1016/j.smrv.2021.101448