Evidence map›Paper›PMID 41639643›Full record

ArticleBMC public health2026

Prevalence, subtypes, and comorbidity of DSM-5 insomnia disorder among adults in Beijing, China: a large-scale cross-sectional study.

Lili Shang, Yanjie Zhao, Anan Cong, Ping Lv, Hua Ding, Xuequan Zhu, Ling Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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.

Lili ShangBeijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Yanjie ZhaoBeijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Anan CongBeijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Ping LvInstitute of Social Science Survey, Peking University, Beijing, China.
Hua DingInstitute of Social Science Survey, Peking University, Beijing, China.
Xuequan ZhuBeijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China. xuequanzhu@ccmu.edu.cn.
Ling ZhangBeijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China. zhangling@ccmu.edu.cn.

Funding

Beijing Key Diseases Flow Control and Prevention grant ZX035High-level Public Health Technical Talent Development Project Subject Backbone-03-27Prevention and Control of Major Infectious Diseases grant XM202111
6 · The paper itself

Abstract

backgroundDespite the crucial distinction between insomnia symptoms and a diagnosed disorder, population-level studies based on contemporary criteria and clinical interviews are scarce. This study therefore examined the insomnia spectrum by assessing the prevalence, identifying subtypes, and exploring associations with sociodemographic factors and comorbid mental disorders for both conditions.

methodsThis large-scale, community-based cross-sectional study was conducted in Beijing from October to December 2021. A sample of 10,778 adults was recruited via multistage stratified random sampling. Trained psychiatrists conducted standardized diagnostic interviews based on the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) to collect data on insomnia disorder and mental disorders. Descriptive analysis and weighted Rao-Scott chi-square tests, were performed using the Statistical Analysis System (SAS, version 9.4).

resultsThe weighted prevalence rates were 17.7% for subjective sleep problems, 10.7% for clinically assessed insomnia symptoms, and 3.0% for DSM-5-diagnosed insomnia disorder. Among insomnia subtypes, initial insomnia was most prevalent, both as a symptom (8.1%) and a disorder (2.6%). Furthermore, insomnia disorder prevalence varied by sociodemographics, being higher in females, older adults (≥ 60 years), and those with lower education. Among individuals with insomnia disorder, 31.3% had comorbid other mental disorders, particularly alcohol-related disorders (13.4%). Conversely, insomnia disorder was observed in 14.4% of individuals with other mental disorders, with the highest prevalence in depressive (21.4%) and anxiety disorders (19.2%).

conclusionsThe marked disparity between prevalent insomnia symptoms and formal diagnoses, compounded by significant psychiatric comorbidity, mandates a public health shift toward population-level screening and early intervention. This imperative includes adopting standardized diagnostics and implementing integrated, transdiagnostic treatment models as a pivotal preventive strategy.

Indexed as

Mental DisordersSleep Initiation and Maintenance DisordersAdolescentAdultAgedBeijingComorbidityCross-Sectional StudiesDiagnostic and Statistical Manual of Mental DisordersFemaleHumansMaleMiddle AgedPrevalenceYoung AdultComorbidityDSM-5Insomnia disorderInsomnia subtypeInsomnia symptoms

Identifiers

PMID41639643
PMCPMC12973733

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.