ArticleJournal of obesity2026
Body Roundness Index and Body Shape Index as Predictors for All-Cause Mortality Beyond Body Mass Index: Findings From a National Cohort Study.
Article in Journal of obesity, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Body composition changes in the postpartum: a systematic review on measurements and predictors.BMC pregnancy and childbirth · 2026Pooled it
- Associations of Physical Activity, Sedentary Behaviour, and Sleep with Somatotype Components and a Body Shape Index in Young Adults.Journal of functional morphology and kinesiology · 2026Article
- Obesity and reduced renal corticomedullary differentiation on T1 mapping: a population-based UK Biobank study.International urology and nephrology · 2026Article
- Six anthropometric indices and all-cause mortality in ageing populations: an observational cohort study in six longitudinal studies.BMC public health · 2026Observational
- Body Roundness Index and Body Shape Index as Predictors for All-Cause Mortality Beyond Body Mass Index: Findings From a National Cohort Study.Journal of obesity · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Body mass index (BMI) has been criticised for its inability to differentiate between fat and nonfat tissues and to reflect body fat distribution. Body Roundness Index (BRI) and A Body Shape Index (ABSI) are novel indices addressing these limitations, yet their mortality risk-stratification utility remains understudied in Asian populations. Methods: In this retrospective cohort study using a nationally representative Japanese claims database (2014-2022), we analysed 778,812 individuals who underwent healthcare checkups. Anthropometric indices were categorised into five groups based on restricted cubic spline curve-derived cutoffs. Multivariate Cox proportional hazards models, adjusted for demographic factors, lifestyle variables and comorbidities, assessed associations between these categorical variables and all-cause mortality. Results: Among participants (mean [standard deviation] age of 62.8 [9.6] years and 445,250 [57.2%] women), 14,690 deaths occurred during a median [interquartile range] follow-up of 4.53 [3.28-6.23] years. While BMI and BRI showed U-shaped relationships with all-cause mortality, ABSI demonstrated a J-shaped relationship. Significant differences in mortality risk compared with the reference category were observed in three categories for BMI, four categories for BRI and four categories for ABSI. Conclusions: BRI and ABSI identified mortality risk differences across more categories than BMI, indicating that these indices may provide additional insights beyond BMI for mortality risk assessment.
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Registered trials
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.