# Associations of Visceral Adiposity Index and Body Roundness Index with chronic kidney disease in a Hakka population: mediating effect of blood pressure

**Authors:** Jinxia Su, Shengzhu Huang, Binran Zhao, Qiuyan Tan, Shanshan Li, Jing Huang, Boning Hu, Xiaolai Li, Bijun Li, Chen Li, Zengnan Mo, Ling Pan, Wei Li

PMC · DOI: 10.3389/fnut.2026.1732017 · Frontiers in Nutrition · 2026-02-05

## TL;DR

This study finds that higher Visceral Adiposity Index and Body Roundness Index are linked to increased chronic kidney disease risk in the Hakka population, with blood pressure playing a key mediating role.

## Contribution

The study introduces the mediating effects of blood pressure in the relationship between adiposity indices and CKD in the Hakka population.

## Key findings

- The highest quartiles of VAI and BRI were associated with 1.61 and 1.26 times higher CKD risk, respectively.
- Blood pressure indicators mediated the relationship between VAI/BRI and CKD, with stronger effects for BRI.
- Pulse pressure only mediated the BRI-CKD relationship.

## Abstract

This study aims to investigate the prevalence of chronic kidney disease (CKD) and explore the associations of the Visceral Adiposity Index (VAI) and Body Roundness Index (BRI) with CKD risk in the Hakka population, while quantitatively assessing the mediating effects of blood pressure indicators.

Data for this study were obtained from a cross-sectional survey conducted in Bobai County, Guangxi, which included 8971 adult participants. Log-binomial regression, robust Poisson regression, and restricted cubic spline regression were used to evaluate the associations between the VAI/BRI and CKD risk. Mediation analysis was further conducted to assess the role of blood pressure parameters in these associations.

The overall prevalence of CKD was 12.62% in the study population. In the fully adjusted multivariable model (Model 3), compared with the lowest quartiles (Q1, reference), the highest quartiles (Q4) of both VAI and BRI were significantly associated with increased risks of CKD, with prevalence ratios of 1.61 (95% CI: 1.32–1.98) and 1.26 (95% CI: 1.05–1.52), respectively. Restricted cubic spline analysis revealed nonlinear associations between VAI/BRI and CKD risk, with accelerated risk increments at higher levels of both indices. Mediation analysis revealed that blood pressure indicators significantly mediated the VAI/BRI-CKD relationships, with notably stronger effects observed for BRI (SBP: 42.69%; DBP: 51.16%; MAP: 53.38%) compared to VAI (SBP: 21.4%; DBP: 28.15%; MAP: 28.41%). Additionally, PP exhibited a significant mediating effect only in the BRI-CKD pathway (12.21, 95% CI: 7.28–20.70).

The VAI and BRI were independent risk factors for CKD in Hakka Biobank (HKB), with their associations with CKD are partially mediated by blood pressure. Given their ease of measurement and cost-effectiveness, VAI and BRI may serve as practical screening tools for identifying CKD high-risk individuals in community populations, thereby enabling early intervention and targeted prevention strategies of CKD.

## Linked entities

- **Diseases:** chronic kidney disease (MONDO:0005300)
- **Species:** Hakka (taxon 1112519)

## Full-text entities

- **Genes:** REN (renin) [NCBI Gene 5972] {aka ADTKD4, HNFJ2, RTD}, Agt (angiotensinogen) [NCBI Gene 11606] {aka AngI, AngII, Aogen, Serpina8}, Lepr (leptin receptor) [NCBI Gene 16847] {aka B219, LEP-R, LEPROT, Leprb, Modb1, OB-RGRP}, Lep (leptin) [NCBI Gene 16846] {aka ob, obese}, ALB (albumin) [NCBI Gene 213] {aka FDAHT, HSA, PRO0883, PRO0903, PRO1341}, INS (insulin) [NCBI Gene 3630] {aka IDDM, IDDM1, IDDM2, ILPR, IRDN, MODY10}, PGR (progesterone receptor) [NCBI Gene 5241] {aka NR3C3, PR}
- **Diseases:** RCS (MESH:D002313), kidney function (MESH:D007680), visceral obesity (MESH:D056128), Hyperuricemia (MESH:D033461), chronic (MESH:D002908), METS-VF (MESH:D007418), hypoxia (MESH:D000860), fatty kidney (MESH:D007674), obese (MESH:D009765), Adiposity (MESH:D018205), type 2 diabetes (MESH:D003924), ESRD (MESH:D007676), Diabetes mellitus (MESH:D003920), hypertrophy (MESH:D006984), renal function decline (MESH:D060825), arteriosclerosis (MESH:D001161), CVD (MESH:D002318), CKD (MESH:D051436), insulin resistance (MESH:D007333), intra (MESH:D057072), interstitial fibrosis (MESH:D005355), albuminuria (MESH:D000419), metabolic syndrome (MESH:D024821), inflammation (MESH:D007249), glomerulosclerosis (MESH:D005921), Hypertension (MESH:D006973), Dyslipidemia (MESH:D050171)
- **Chemicals:** Alcohol (MESH:D000438), Creatinine (MESH:D003404), Glucose (MESH:D005947), Cholesterol (MESH:D002784), nitric oxide (MESH:D009569), urea nitrogen (MESH:C530477), lipid (MESH:D008055), Uric Acid (MESH:D014527), TG (MESH:D014280), aldosterone (MESH:D000450), BRI (-), sodium (MESH:D012964), Diastolic Blood Pressure (MESH:D004145)
- **Species:** Mus musculus (house mouse, species) [taxon 10090], Rattus norvegicus (brown rat, species) [taxon 10116], Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12916385/full.md

## References

47 references — full list in the complete paper: https://tomesphere.com/paper/PMC12916385/full.md

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Source: https://tomesphere.com/paper/PMC12916385