Evidence map›Paper›PMID 37246064›Full record

ArticleSleep health2023

Six multidimensional sleep health facets in older adults identified with factor analysis of actigraphy: Results from the Einstein Aging Study.

Linying Ji, Meredith L Wallace, Lindsay Master, Margeaux M Schade, Yuqi Shen, Carol A Derby, Orfeu M Buxton

Abstract read
In one paragraph

Article in Sleep health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

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  10. Associations between AHA's Life's Essential 8 and cognition in midlife and older adults.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024
    Article
  11. Multidimensional Sleep Health Problems Across Middle and Older Adulthood Predict Early Mortality.The journals of gerontology. Series A, Biological sciences and medical sciences · 2024
    Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Linying JiDepartment of Biobehavioral Health, The Pennsylvania State University, University Park, Pennsylvania, USA.
Meredith L WallaceDepartment of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Lindsay MasterDepartment of Biobehavioral Health, The Pennsylvania State University, University Park, Pennsylvania, USA.
Margeaux M SchadeDepartment of Biobehavioral Health, The Pennsylvania State University, University Park, Pennsylvania, USA.
Yuqi ShenDepartment of Biobehavioral Health, The Pennsylvania State University, University Park, Pennsylvania, USA.
Carol A DerbySaul R. Korey Department of Neurology, and Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, New York, USA.
Orfeu M BuxtonDepartment of Biobehavioral Health, The Pennsylvania State University, University Park, Pennsylvania, USA. Electronic address: orfeu@psu.edu.

Funding

Vascular Structure and Function in Cognitive AgingP01AG003949 · NIA · YESHIVA UNIVERSITY · PI Richard B. LIPTON · 1985 to 2026
$73.9M
Application of ambulatory methods for assessing short- and long-term associations of sleep health with cognitive decline in older adultsR01AG062622 · NIA · ALBERT EINSTEIN COLLEGE OF MEDICINE · PI BUXTON, ORFEU M, DERBY, CAROL A. · 2019 to 2022
$3.1M
Business and regulatory development for Integrating sleep enhancement technology into clinical practiceR44AG056250 · NIA · PROACTIVE LIFE, INC. · PI GARTENBERG, DANIEL · 2020 to 2022
$2.5M
Sleep Health Profiles Predicting Impaired Cognition and Depressive Symptoms in Older Adults: Extending Novel Statistical Methods in Multi-Cohort ApplicationsRF1AG056331 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI WALLACE, MEREDITH JOANNE LOTZ · 2021 to 2021
$2.0M
Non-pharmacological improvement of sleep structure in older peopleR43AG056250 · NIA · MOBILE SLEEP TECHNOLOGIES, LLC · PI GARTENBERG, DANIEL, GERASHCHENKO, DMITRY · 2017 to 2018
$696k
NIA NIH HHS P01 AG003949NIA NIH HHS R01 AG062622NIA NIH HHS R43 AG056250NIA NIH HHS R44 AG056250NIA NIH HHS RF1 AG056331
6 · The paper itself

Abstract

objectivesThe concept of multi-dimensional sleep health, originally based on self-report, was recently extended to actigraphy in older adults, yielding five components, but without a hypothesized rhythmicity factor. The current study extends prior work using a sample of older adults with a longer period of actigraphy follow-up, which may facilitate observation of the rhythmicity factor.

methodsWrist actigraphy measures of participants (N = 289, M

resultsExploratory factor analysis identified six factors: Regularity: standard deviations of four sleep measures: midpoint, sleep onset time, night total sleep time (TST), and 24-hour TST; Alertness/Sleepiness (daytime): amplitude, napping (mins and #/day); Timing: sleep onset, midpoint, wake-time (of nighttime sleep); up-mesor, acrophase, down-mesor; Efficiency: sleep maintenance efficiency, wake after sleep onset; Duration: night rest interval(s), night TST, 24-hour rest interval(s), 24-hour TST; Rhythmicity (pattern across days): mesor, alpha, and minimum. Greater sleep efficiency was associated with better Montreal Cognitive Assessment performance (β [95% confidence interval] = 0.63 [0.19, 1.08]).

conclusionsActigraphic records over 2 weeks revealed that Rhythmicity may be an independent factor in sleep health. Facets of sleep health can facilitate dimension reduction, be considered predictors of health outcomes, and be potential targets for sleep interventions.

Indexed as

ActigraphySleepAgedAgingFemaleHumansMalePolysomnographyRestActigraphyCosinor analysisFactor analysisMultidimensional sleep healthRest-activity rhythmRU-SATED

Identifiers

PMID37246064
PMCPMC10593097

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.