What question did this study set out to answer?

The study aims to evaluate the utility of two obesity indices, ABSI and TyG-ABSI, in predicting risk and mortality for chronic kidney disease (CKD).

March 28, 2026Open Access

Stage-specific utility of obesity indices across the chronic kidney disease continuum

Key Result

TyG-ABSI optimally identifies chronic kidney disease risk (OR 1.58), whereas ABSI is a superior predictor of cardiovascular (HR 2.40) and all-cause mortality (HR 1.50) in established CKD.

Key Points

The study aims to evaluate the utility of two obesity indices, ABSI and TyG-ABSI, in predicting risk and mortality for chronic kidney disease (CKD).
Analysis of data from the US NHANES survey (1999-2018; n=14,175)
Comparison of ABSI and TyG-ABSI for CKD risk identification
Use of logistic regression for prevalence and hazard ratio calculations
Application of restricted cubic splines for ABSI z-score thresholds
TyG-ABSI shows superior performance for identifying prevalent CKD (OR = 1.58)
ABSI predicts all-cause mortality risk above z = 0.624 (HR = 1.44) and CVD mortality above z = 0.416 (HR = 1.35)
ABSI maintains significant associations with mortality in CKD (HR = 1.50 for all-cause, HR = 2.40 for CVD)
ABSI demonstrates higher discriminative accuracy (AUC of 0.68 for all-cause mortality) compared to TyG-ABSI.

Structured PICO

Do novel obesity indices (ABSI and TyG-ABSI) predict CKD risk and mortality across the chronic kidney disease continuum?

Population

Participants from the US National Health and Nutrition Examination Survey (NHANES, 1999-2018)

Intervention

A Body Shape Index (ABSI) and Triglyceride Glucose-A Body Shape Index (TyG-ABSI)

Comparator

Lower quartiles/scores of ABSI and TyG-ABSI

Outcome

Prevalent CKD identification and all-cause/CVD mortality predictionhard clinical

TyG-ABSI is optimal for identifying CKD risk, whereas ABSI is superior for predicting mortality in established CKD, supporting stage-specific risk stratification.

Main Result

Absolute Event Rate: 0% vs 0%

Abstract

This large-scale study utilizing the US National Health and Nutrition Examination Survey (NHANES, 1999-2018; n = 14,175) compared the diagnostic and prognostic utility of two novel obesity indices-A Body Shape Index (ABSI), and Triglyceride Glucose-A Body Shape Index (TyG-ABSI), evaluating their stage-specific utility for CKD risk identification and mortality prediction within the same cohort. TyG-ABSI demonstrated superior performance for identifying prevalent CKD, with the highest quartile (Q4) showing a significantly increased risk after full adjustment (OR = 1.58, 95% CI:1.23-2.03). Conversely, ABSI emerged as a stronger, nonlinear predictor of mortality in established CKD patients. Restricted cubic splines identified significant ABSI z-score thresholds: all-cause mortality risk increased steeply above z = 0.624 (HR = 1.44, 95% CI:1.17-1.77), and cardiovascular disease (CVD) mortality above z = 0.416 (HR = 1.35, 95% CI:1.09-1.83). After full adjustment, ABSI Q4 remained significantly associated with both all-cause (HR = 1.50) and CVD mortality (HR = 2.40), while TyG-ABSI associations attenuated. ABSI demonstrated superior discriminative accuracy for both all-cause mortality (area under the curve AUC = 0.68 vs. TyG-ABSI AUC = 0.66) and CVD mortality (AUC = 0.64 vs. TyG-ABSI AUC = 0.59). Subgroup analyses confirmed the robustness of ABSI for mortality prediction. These findings suggest a shift in the primary driver of adverse outcomes as CKD progresses: TyG-ABSI, capturing metabolic dysregulation, is optimal for identifying CKD risk, whereas ABSI, reflecting anatomical fat distribution, becomes the superior predictor of mortality in established CKD. This differential utility supports stage-specific risk stratification strategies and highlights the broader clinical relevance of obesity phenotyping for cardiovascular risk assessment, metabolic disease screening, and geriatric prognosis.