Evidence map›Paper›PMID 34642124›Full record

ArticleSleep health2021

Multidimensional sleep health in a diverse, aging adult cohort: Concepts, advances, and implications for research and intervention.

Joon Chung, Matthew Goodman, Tianyi Huang, Suzanne Bertisch, Susan Redline

Abstract read
In one paragraph

Article in Sleep health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed, 3 pooled it
–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

46 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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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

5 authors.

Joon ChungBrigham and Women's Hospital, Boston, Massachusetts, USA; Harvard Medical School, Boston, Massachusetts, USA. Electronic address: jchung26@bwh.harvard.edu.
Matthew GoodmanBrigham and Women's Hospital, Boston, Massachusetts, USA; Harvard Medical School, Boston, Massachusetts, USA.
Tianyi HuangBrigham and Women's Hospital, Boston, Massachusetts, USA; Harvard Medical School, Boston, Massachusetts, USA.
Suzanne BertischBrigham and Women's Hospital, Boston, Massachusetts, USA; Harvard Medical School, Boston, Massachusetts, USA.
Susan RedlineBrigham and Women's Hospital, Boston, Massachusetts, USA; Harvard Medical School, Boston, Massachusetts, USA.

Funding

TRAINING IN SLEEP, CIRCADIAN &RESPIRATORY NEUROBIOLOGYT32HL007901 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI Charles A Czeisler · 1998 to 2026
$18.5M
ASSOCIATION OF SLEEP DISORDERS WITH CARDIOVASCULAR HEALTH ACROSS ETHNIC GROUPSR01HL098433 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI REDLINE, SUSAN S. · 2010 to 2015
$8.2M
National Sleep Research Resource (NSRR)R24HL114473 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI REDLINE, SUSAN S., ZHANG, GUO-QIANG · 2013 to 2017
$7.5M
Phenotypic and Molecular Signatures for Sleep Apnea and Related MorbiditiesR35HL135818 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI REDLINE, SUSAN S. · 2017 to 2023
$7.2M
NTP INFORMATION SYSTEMS SUPPORT27305C0011 · NIEHS · Z-TECH CORPORATION · 2007 to 2009
$4.3M
Cigarette Smoke and Susceptibility to Influenza InfectionR01HL095163 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI JASPERS, ILONA, NOAH, TERRY L · 2009 to 2013
$2.0M
Adjunctive Use of Apyrase to Fibrinolytic TherapyR44HL095169 · NHLBI · APT THERAPEUTICS, INC. · PI CHEN, RIDONG · 2012 to 2013
$1.3M
SUBCLINICAL CARDIOVASCULAR DISEASE STUDYN01HC095166 · HC · UNIVERSITY OF VERMONT &ST AGRIC COLLEGE · PI TRACY, RUSSELL P · 1999 to 2001
$758k
SUBCLINICAL CARDIOVASCULAR DISEASE STUDY-FIELD CENTERN01HC095162 · HC · JOHNS HOPKINS UNIVERSITY · PI SZKLO, MOYSES A · 1999 to 2000
$694k
SUBCLINICAL CARDIOVASCULAR DISEASE STUDY--FIELD CENTERN01HC095161 · HC · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SHEA, STEVEN · 1999 to 2001
$642k
SUBCLINICAL CARDIOVASCULAR DISEASE STUDY--FIELD CENTERN01HC095165 · HC · WAKE FOREST UNIVERSITY · PI BURKE, GREGORY L · 1999 to 2001
$616k
SUBCLINICAL CARDIOVASCULAR DISEASE STUDY--FIELD CENTERN01HC095160 · HC · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SAAD, MOHAMMED F · 1999 to 2001
$592k
NHLBI NIH HHS HHSN268201500003CNHLBI NIH HHS HHSN268201500003INHLBI NIH HHS N01 HC095159NHLBI NIH HHS N01 HC095160NHLBI NIH HHS N01 HC095161NHLBI NIH HHS N01 HC095162NHLBI NIH HHS N01 HC095163NHLBI NIH HHS N01 HC095164NHLBI NIH HHS N01 HC095165NHLBI NIH HHS N01 HC095166NHLBI NIH HHS N01 HC095167NHLBI NIH HHS N01 HC095168NHLBI NIH HHS N01 HC095169NHLBI NIH HHS R01 HL098433NHLBI NIH HHS R24 HL114473NHLBI NIH HHS R35 HL135818NHLBI NIH HHS T32 HL007901NIEHS NIH HHS 27305C0011NIEHS NIH HHS 27307C0011NIEHS NIH HHS 27398C0011
6 · The paper itself

Abstract

purposeTo illustrate 2 frameshifts of multidimensional sleep health: i) use of composite sleep metrics; and ii) the correlations among sleep dimensions.

participants735 adults of diverse backgrounds aged <65 years who participated in the Multi-Ethnic Study of Atherosclerosis. MEASURES: In-home polysomnography, 7-day wrist actigraphy, and validated questionnaires.

methodsThe Buysse Ru SATED model-sleep regularity, satisfaction, alertness, timing, efficiency, duration-was operationalized, then extended by including additional measures of sleep architecture and sleep apnea from polysomnography and difficulties initiating sleep from questionnaire and sleep onset latency and duration [ir]regularity from actigraphy. We dichotomized sleep variables, operationalizing optimal and nonoptimal ranges as 1 and 0, respectively, summed into a sleep health score, and computed global sleep health scores via principal components analysis.

findingsParticipants showed low prevalence of sleep regularity in timing (<30 minutes standard deviation [SD]; 21.4% favorable) and duration (<60 minutes SD; 36.9%). Although 62.7% of participants demonstrated favorable sleep duration by actigraphy, few met criteria for favorable levels of % N3 (11.4%) or %R (34.1%). The average Sleep Health Score was 5.6 of 13 (higher is better). Sleep variables were variably intercorrelated (r = 0 to r = -0.72). The first principal component for each operationalization of sleep health was interpretable as a "health" score; all summary scores captured variable but systematic shifts towards more favorable sleep in each sleep variable.

conclusionsMultidimensional sleep health can be measured by complementary composite scores as well as consideration of multiple individual dimensions.

Indexed as

SleepSleep Initiation and Maintenance DisordersActigraphyAdultAgingHumansPolysomnographyactigraphymultidimensionalpolysomnographySleepsleep health

Identifiers

PMID34642124
PMCPMC8665047

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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.