Evidence map›Paper›PMID 34845630›Full record

ArticleSleep & breathing = Schlaf & Atmung2022

Validation of the National Health And Nutritional Survey (NHANES) single-item self-reported sleep duration against wrist-worn accelerometer.

Paul H Lee

Open access · hybridAbstract read
In one paragraph

Article in Sleep & breathing = Schlaf & Atmung, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
3.1field-weighted citation impact, top 8% of its field
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

17 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. The Role of Fatigue in the Relationship Between Sleep and Concentration Among Online College Students.International journal of environmental research and public health · 2025
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  5. Associations of a metal mixture and vitamin D with sleep duration among adolescents and young adults from the 2011-2018 NHANES cycles.Journal of trace elements in medicine and biology : organ of the Society for Minerals and Trace Elements (GMS) · 2025
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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

1 author at 1 institution in 1 country.

Paul H LeeDepartment of Health Sciences, George Davies Centre, University of Leicester, University Road, Leicester, LE1 7RH, UK. paul.h.lee@leicester.ac.uk.
University of Leicester · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PURPOSE AND

methodsThis study aimed to validate the single-item sleep duration question used in the National Health And Nutritional Survey (NHANES), "How much sleep do you usually get at night on weekdays or workdays (hours)?", against a wrist-worn accelerometer (ActiGraph GT3X +) in waves 2011-2012 and 2013-2014 among an adult population aged 20 or above (n = 8,438, mean age 49.7, 48% male).

resultsThe accelerometer-measured and self-reported sleep duration were 6.01 (SD 1.48) and 6.88 (SD 1.40) h/day, respectively, representing a 0.87 h/day of over-reporting (SD 1.90, p < 0.001). Such an over-reporting was observed in all subgroups, where the over-reporting ranged from 0.72 (those aged 41-50) to 1.13 h/day (those aged 71 or above). The correlation between accelerometer-measured and self-reported sleep duration was low (ρ = 0.14, p < 0.001).

conclusionsThe associations between sleep duration and other health outcomes identified using NHANES data should be further tested using more accurate and valid measures of sleep duration.

Indexed as

SleepWristAccelerometryActigraphyAdultFemaleHumansMaleMiddle AgedNutrition SurveysSelf ReportActigraphyMeasurementQuestionnaireSleep

Identifiers

PMID34845630
PMCPMC9663342
OpenAlexW3215465281

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.