Evidence map›Paper›PMID 41547818›Full record

ArticleBMC public health2026

Health and social inequities among cisgender gay and bisexual men in Japan: a nationwide cross-sectional study using a large-scale web-based survey.

Kazuhiko Ikeuchi, Takahiro Tabuchi, Yuki Arisato, Shinya Matsumoto, Toshiyuki Kishida, Akira Kado, Kazuya Okushin, Hiroshi Yotsuyanagi, Takeya Tsutsumi

Abstract read
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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

9 authors.

Kazuhiko IkeuchiDepartment of Infectious Diseases, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan. kikeuchi@g.ecc.u-tokyo.ac.jp.
Takahiro TabuchiDivision of Epidemiology, School of Public Health, Tohoku University Graduate School of Medicine, Sendai, 980-8575, Japan.
Yuki ArisatoDepartment of Infectious Diseases, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
Shinya MatsumotoDepartment of Infectious Diseases, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
Toshiyuki KishidaDepartment of Infectious Diseases, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
Akira KadoDivision for Health Service Promotion, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
Kazuya OkushinDepartment of Gastroenterology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
Hiroshi YotsuyanagiDepartment of Infectious Diseases and Applied Immunology, IMSUT Hospital of the Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639, Japan.
Takeya TsutsumiDepartment of Infectious Diseases, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.

Funding

Japan Science and Technology Agency (JST), PRESTO JPMJPR23R1JSPS KAKENHI 21H04856
6 · The paper itself

Abstract

backgroundGay and bisexual men (GBM) face elevated risks of hypertension, diabetes, and depression, but these conditions are strongly influenced by social discrimination, economic disadvantage, and recreational substance use, complicating their interpretation. This study aimed to compare the social, lifestyle, and health characteristics of GBM with those of heterosexual men in Japan, where epidemiological data remain limited.

methodsWe analyzed data from the 2022 wave of the Japan COVID-19 and Society Internet Survey (JACSIS), a large-scale, web-based nationwide survey. Participants were classified as heterosexual, gay, or bisexual according to reported sexual attraction. Inverse probability weighting was applied to estimate population-level prevalence. Multivariable logistic regression was performed to examine associations between sexual orientation and lifestyle-related diseases, recreational substance use, and depression.

resultsAmong 13,271 eligible men, 830 (6.3%) identified as GBM (721 gay, 109 bisexual); the weighted prevalence was 6.6% (95% CI: 5.9–7.4%). GBM were more likely to report burden from night shift work (27.5% [228/830] vs. 15.9% [1,979/12,441], p < 0.001), workplace harassment (27.7% [185/667] vs. 12.2% [1,185/9,676], p < 0.001), fear of job loss (31.8% [212/667] vs. 22.1% [2,142/9,676], p < 0.001), receipt of public assistance (1.2% [10/830] vs. 0.3% [43/12,441], p < 0.001), and experience of recreational substance use (12.9% [107/830] vs. 4.1% [505/12,441], p < 0.001). Among participants under 50 years, GBM tended to have higher prevalence of hypertension (9.6% [49/508] vs. 5.2% [346/6,626]) and diabetes (6.7% [34/508] vs. 2.5% [168/6,626]), but these associations were not significant after adjustment (hypertension: gay aOR 1.20, 95% CI: 0.91–1.59; bisexual aOR 1.70, 95% CI: 0.89–3.25; diabetes: gay aOR 0.95, 95% CI: 0.65–1.39; bisexual aOR 1.46, 95% CI: 0.60–3.53). Depression was more common among GBM (7.2% [60/830] vs. 3.4% [417/12,441], p < 0.001), but not statistically significant among gay men (gay aOR 1.15 [0.76–1.75], bisexual aOR 2.34 [1.08–5.09]).

conclusionsGBM in Japan showed higher self-reported prevalence of depression, hypertension, and diabetes, particularly among men aged under 50, although these differences were attenuated in multivariable analysis. These findings highlight the importance of social and occupational contexts and recreational substance use when considering health disparities among GBM.

Indexed as

BisexualityHealth Status DisparitiesHomosexuality, MaleSexual and Gender MinoritiesAdultCross-Sectional StudiesDepressionHumansInternetJapanMaleMiddle AgedPrevalenceSocioeconomic Disparities in HealthSurveys and QuestionnairesYoung Adult

Identifiers

PMID41547818
PMCPMC12895739

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LicenceCC BY-NC-ND
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Registered trials

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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.