Evidence map›Paper›PMID 30281638›Full record

ArticlePloS one2018

Prevalence of childhood obstructive sleep apnea syndrome and its role in daytime sleepiness.

Eriko Tsukada, Shingo Kitamura, Minori Enomoto, Aiko Moriwaki, Yoko Kamio, Takashi Asada, Tetsuaki Arai, Kazuo Mishima

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 4 pooled it
2.3field-weighted citation impact, top 11% 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

30 citing papers in PubMed, 4 syntheses or guidelines pooled it, 60 citations in OpenAlex.

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  10. An Explainable Deep-Learning Approach to Detect Pediatric Sleep Apnea From Single-Channel Airflow.IEEE journal of translational engineering in health and medicine · 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

8 authors at 5 institutions in 1 country.

Eriko TsukadaDepartment of Psychophysiology, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira-city, Tokyo, Japan.
Shingo KitamuraDepartment of Psychophysiology, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira-city, Tokyo, Japan.
Minori EnomotoDepartment of Psychophysiology, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira-city, Tokyo, Japan.
Aiko MoriwakiSupport Room for Students with Disabilities, Tokyo Gakugei University, Koganei-city, Tokyo, Japan.
Yoko KamioDepartment of Child and Adolescent Mental Health, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira-city, Tokyo, Japan.
Takashi AsadaDepartment of Neuropsychiatry, University of Tokyo Medical and Dental University, Bunkyo-ku, Tokyo, Japan.
Tetsuaki AraiDepartment of Psychiatry, Graduate School of Comprehensive Human Sciences, University of Tsukuba, Tsukuba-city, Ibaraki, Japan.
Kazuo MishimaDepartment of Psychophysiology, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira-city, Tokyo, Japan.ORCID 0000-0003-1182-1181
National Center of Neurology and Psychiatry · JPUniversity of Tsukuba · JPAkita University · JPTokyo Gakugei University · JPTokyo Medical and Dental University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo investigate childhood obstructive sleep apnea syndrome (OSAS) and its role in daytime sleepiness among school-age children.

methodsA questionnaire survey was conducted with 25,211 children aged 6-15 (mean, 10.39) years attending 148 elementary and 71 middle schools in 10 prefectures across Japan and their parents. Questions concerned 4 sleep habit items (bedtime, sleep onset latency, wake time after sleep onset, wake-up time) and 4 sleep disorder items (loud snoring, snorts/gasps, breathing pauses, seems very sleepy in the daytime). Total sleep time (TST) was calculated with sleep habits. Severe possible OSAS (p-OSAS) was defined as having loud snoring, snorts and gasps, or breathing pauses "frequently" (≥ 5 times per week), and mild p-OSAS was rated as having any of these "sometimes" (2-4 times per week). Severe daytime sleepiness was defined as seeming very sleepy "frequently" and mild daytime sleepiness as seeming very sleepy "sometimes".

resultsMean prevalence of mild to severe p-OSAS and severe p-OSAS in children across all grade levels was 9.5% and 1.6%, respectively. p-OSAS was particularly prevalent in children at lower elementary levels, decreasing with advancing grade levels. Prevalence of mild and severe daytime sleepiness was 6.1% and 0.9%, respectively, among all children (7.0%). Prevalence of daytime sleepiness increased with advancing grade levels, particularly in middle-school level. Average TST was 8.4 ± 2.2 h in both elementary and middle-school levels, and decreased as grades advanced, particularly in middle-school levels. Multivariate logistic regression analysis showed that middle-school level, TST < 8 h, and p-OSAS were independent factors for daytime sleepiness. Strong correlations were found between severe daytime sleepiness and severe p-OSAS or TST < 6 h, and between daytime sleepiness and loud snoring or breathing pauses.

conclusionp-OSAS may be an independent factor influencing daytime sleepiness in school-age children. Loud snoring and breathing pauses could be clinical markers for children with severe daytime sleepiness.

Indexed as

SleepinessAdolescentAge FactorsChildFemaleHumansMalePrevalenceRisk FactorsSeverity of Illness IndexSleepSleep Apnea, ObstructiveSnoringStudents

Identifiers

PMID30281638
PMCPMC6169921
OpenAlexW2894746672

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.