Evidence map›Paper›PMID 40596327›Full record

ArticleScientific reports2025

Associations between anthropometric indices and biological age acceleration in American adults: insights from NHANES 2009-2018 data.

Xinyun Chen, Xia Chen, Fangyu Shi, Wenhui Yu, Chang Gao, Shenju Gou, Ping Fu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

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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. 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

7 authors.

Xinyun Chen *Department of Health Management, Health Management Center, General Practice Center, West China Hospital, Sichuan University, Chengdu, 610041, China.
Xia Chen *Department of Nephrology, Kidney Research Institute, Institute of Kidney Diseases, West China Hospital, Sichuan University, 37 Guoxue Alley, Chengdu, 610041, China.
Fangyu ShiDepartment of Health Management, Health Management Center, General Practice Center, West China Hospital, Sichuan University, Chengdu, 610041, China.
Wenhui YuDepartment of Nephrology, Kidney Research Institute, Institute of Kidney Diseases, West China Hospital, Sichuan University, 37 Guoxue Alley, Chengdu, 610041, China.
Chang GaoDepartment of Nephrology, Kidney Research Institute, Institute of Kidney Diseases, West China Hospital, Sichuan University, 37 Guoxue Alley, Chengdu, 610041, China.
Shenju GouDepartment of Nephrology, Kidney Research Institute, Institute of Kidney Diseases, West China Hospital, Sichuan University, 37 Guoxue Alley, Chengdu, 610041, China. goushenju@scu.edu.cn.
Ping FuDepartment of Nephrology, Kidney Research Institute, Institute of Kidney Diseases, West China Hospital, Sichuan University, 37 Guoxue Alley, Chengdu, 610041, China.

Funding

1.3.5 project for disciplines of excellence from West China Hospital of Sichuan University ZYGD23015Sichuan Medical Association Nephrology Special Project Grant No. 2024SY01Sichuan Science and Technology Program No.2020JDRC0022
6 · The paper itself

Abstract

Population aging has become a global phenomenon with significant implications for public health. Aging accelerates the development of age-related diseases, leading to increased social and economic burdens. Obesity further exacerbates these effects by increasing the risk of comorbidities and reducing life expectancy. This study examines the relationships between various anthropometric indices-A Body Shape Index (ABSI), Body Roundness Index (BRI), Body Mass Index (BMI), and Conicity Index (C-index)-and biological age acceleration, providing insights into the effectiveness of these indices in predicting biological aging. Data were sourced from the National Health and Nutrition Examination Survey (NHANES) 2009-2018, involving 22,921 participants after exclusions. Biological aging acceleration was assessed using Phenotypic Age Acceleration (PhenoAgeAccel) and Klemera-Doubal Method Age Acceleration (KDM-AA) algorithms. Associations between anthropometric indices and biological aging acceleration were evaluated using weighted multiple linear and logistic regression models, adjusted for potential confounders. Restricted Cubic Spline (RCS) regression explored non-linear associations. Receiver Operating Characteristic (ROC) curve analysis assessed the predictive capabilities of the anthropometric indices. Higher values of all four anthropometric indices (ABSI, BRI, BMI, and C-index) were significantly associated with increased biological aging acceleration (both PhenoAgeAccel and KDM-AA), even after adjusting for covariates. Significant non-linear relationships were observed in all four anthropometric indices. Subgroup analyses revealed robust associations across various demographics and health conditions. The area under the ROC curve (AUC) showed that the C-index exhibited the highest predictive capability for biological age acceleration. This study reveals significant associations between higher anthropometric indices and biological age acceleration in American adults, with the C-index being the most effective predictor.

Indexed as

AgingAnthropometryAdultAgedBody Mass IndexFemaleHumansMaleMiddle AgedNutrition SurveysROC CurveUnited StatesYoung AdultABSIBiological age accelerationBMIBRIC-index

Identifiers

PMID40596327
PMCPMC12217343

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