Evidence map›Paper›PMID 41214331›Full record

ArticleHypertension research : official journal of the Japanese Society of Hypertension2026

Lean body mass index and hypertension risk in men: a nationwide epidemiological cohort study.

Tatsuhiko Azegami, Hidehiro Kaneko, Akira Okada, Yuta Suzuki, Kazuki Aoyama, Katsuhito Fujiu, Norifumi Takeda, Hiroyuki Morita, Takashi Yokoo, Masaomi Nangaku and 4 more

Abstract read
In one paragraph

Article in Hypertension research : official journal of the Japanese Society of Hypertension, 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. In Response to "Is low lean body mass a risk factor for hypertension?"Hypertension research : official journal of the Japanese Society of Hypertension · 2026
    Article
  2. Is low lean body mass a risk factor for hypertension?Hypertension research : official journal of the Japanese Society of Hypertension · 2026
    Article
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

14 authors.

Tatsuhiko AzegamiDivision of Nephrology, Endocrinology, and Metabolism, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan.
Hidehiro KanekoDepartment of Cardiovascular Medicine, The University of Tokyo, Tokyo, Japan. kanekohidehiro@gmail.com.
Akira OkadaDepartment of Prevention of Diabetes and Lifestyle-Related Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Yuta SuzukiDepartment of Cardiovascular Medicine, The University of Tokyo, Tokyo, Japan.
Kazuki AoyamaDivision of Nephrology, Endocrinology, and Metabolism, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan.
Katsuhito FujiuDepartment of Cardiovascular Medicine, The University of Tokyo, Tokyo, Japan.
Norifumi TakedaDepartment of Cardiovascular Medicine, The University of Tokyo, Tokyo, Japan.
Hiroyuki MoritaDepartment of Cardiovascular Medicine, The University of Tokyo, Tokyo, Japan.
Takashi YokooDivision of Nephrology and Hypertension, Department of Internal Medicine, Jikei University School of Medicine, Tokyo, Japan.
Masaomi NangakuDivision of Nephrology and Endocrinology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan.
Koichi NodeDepartment of Cardiovascular Medicine, Saga University, Saga, Japan.
Norihiko TakedaDepartment of Cardiovascular Medicine, The University of Tokyo, Tokyo, Japan.
Hideo YasunagaDepartment of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, Tokyo, Japan.
Kaori HayashiDivision of Nephrology, Endocrinology, and Metabolism, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hypertension, a leading global health challenge, is intricately linked to obesity in its pathogenesis. Body mass index, a common indicator of obesity, cannot distinguish between fat mass and lean body mass, which exert contrasting cardiovascular effects. This study aimed to evaluate the lean body mass index (LBMI), derived from height, weight, and waist circumference, as a predictor of hypertension risk in men. This retrospective study utilized a large-scale real-world database to evaluate the association between LBMI and hypertension risk in men. Hypertension incidence was identified via ICD-10 codes (I10-I15) utilizing an administrative claims database. Cox regression and spline models assessed risk, adjusting for confounders. To confirm the robustness of findings, stratified and sensitivity analyses were also conducted. Among 384,551 men (median age 51 years), lower quartile in LBMI was associated with a higher risk of hypertension onset in multivariable Cox regression (hazard ratio [95% confidence interval]: Q1, 1.20 [1.15-1.26]; Q2, 1.06 [1.02-1.10]; Q3, 1.03 [0.99-1.06]; Q4, 1 [reference value]). In the restricted cubic spline regression model, the risk of hypertension increased as LBMI decreased. Consistent results were observed across stratified analyses, including older adults and non-obese individuals, and the reliability of the findings was confirmed through sensitivity analyses such as multiple imputation and competing risks analysis. In conclusion, lower LBMI was associated with a higher risk of hypertension in men, underscoring the importance of promoting lean body mass. Future research should explore whether increasing lean body mass could reduce hypertension incidence and its complications.

Indexed as

Body Mass IndexHypertensionAdultAgedCohort StudiesHumansIncidenceMaleMiddle AgedRetrospective StudiesRisk FactorsDatabaseHypertensionLean mass

Identifiers

PMID41214331
PMCPMC12960225

What OpenQuestion holds

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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.