Does handgrip strength improve cardiometabolic risk stratification beyond detailed body composition? NHANES 2011-2014 with temporal validation
- 1Monash University
Abstract
BackgroundHandgrip strength is associated with cardiometabolic abnormalities, but whether it adds information once detailed adiposity and muscle mass are known is unclear.
MethodsWe studied adults aged 40-59 years from NHANES 2011-2012 (development, n=508) and 2013-2014 (temporal validation, n=616). The outcome was at least two of four non-adiposity abnormalities (elevated blood pressure, fasting glucose or triglycerides, or low HDL cholesterol); waist circumference was not part of the outcome. A prespecified feature ladder added DXA body fat percentage and visceral adipose tissue to age, sex, BMI and waist circumference (M1), then appendicular skeletal muscle index (M2), then absolute (M3A, primary) or weight-normalised (M3B) grip strength. Logistic regression was primary; elastic-net and XGBoost were supportive. Development performance used nested cross-validation; frozen models were scored once in the validation cohort. Paired increments used 2000 stratified bootstrap resamples.
ResultsThe outcome occurred in 249 (49.0%) and 277 (45.0%) participants. Adding adiposity increased the logistic regression AUC by 0.0209 (95% CI 0.0024-0.0402) in development and 0.0209 (0.0032-0.0375) in temporal validation. Adding absolute grip strength to M2 changed the AUC by -0.0046 (-0.0107 to 0.0013) and 0.0045 (-0.0009 to 0.0098), respectively. All 12 grip-strength AUC increments across algorithms, definitions and cohorts had intervals that included zero. Calibration was unchanged and the incremental net benefit was not consistently positive. Model attributions to grip strength varied by algorithm.
ConclusionsIn middle-aged adults, detailed adiposity, but not grip strength, added reproducible information for concurrent cardiometabolic risk stratification beyond conventional anthropometry and muscle mass.
HighlightsO_LIDXA adiposity added about 0.02 AUC in both development and temporal validation C_LIO_LIGrip strength added no stable increment beyond adiposity and muscle mass C_LIO_LIAll 12 grip-strength AUC increments had 95% CIs that included zero C_LIO_LIGrip strength received model attributions that did not improve performance C_LIO_LIFrozen models were scored once in a later, temporally separated NHANES cycle C_LI
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BibTeX
@misc{zhan2026does,
title = {{Does handgrip strength improve cardiometabolic risk stratification beyond detailed body composition? NHANES 2011-2014 with temporal validation}},
author = {X. Zhan and M. Shen and Y. Zhang and X. Mao},
howpublished = {medRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.09.26365176},
url = {https://www.medrxiv.org/content/10.64898/2026.10.09.26365176v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Does handgrip strength improve cardiometabolic risk stratification beyond detailed body composition? NHANES 2011-2014 with temporal validation
AU - X. Zhan
AU - M. Shen
AU - Y. Zhang
AU - X. Mao
PY - 2026
DA - 2026/10/09
PB - medRxiv
DO - 10.64898/2026.10.09.26365176
UR - https://www.medrxiv.org/content/10.64898/2026.10.09.26365176v1
AB - BackgroundHandgrip strength is associated with cardiometabolic abnormalities, but whether it adds information once detailed adiposity and muscle mass are known is unclear. MethodsWe studied adults aged 40-59 years from NHANES 2011-2012 (development, n=508) and 2013-2014 (temporal validation, n=616). The outcome was at least two of four non-adiposity abnormalities (elevated blood pressure, fasting glucose or triglycerides, or low HDL cholesterol); waist circumference was not part of the outcome. A prespecified feature ladder added DXA body fat percentage and visceral adipose tissue to age, sex, BMI and waist circumference (M1), then appendicular skeletal muscle index (M2), then absolute (M3A, primary) or weight-normalised (M3B) grip strength. Logistic regression was primary; elastic-net and XGBoost were supportive. Development performance used nested cross-validation; frozen models were scored once in the validation cohort. Paired increments used 2000 stratified bootstrap resamples. ResultsThe outcome occurred in 249 (49.0%) and 277 (45.0%) participants. Adding adiposity increased the logistic regression AUC by 0.0209 (95% CI 0.0024-0.0402) in development and 0.0209 (0.0032-0.0375) in temporal validation. Adding absolute grip strength to M2 changed the AUC by -0.0046 (-0.0107 to 0.0013) and 0.0045 (-0.0009 to 0.0098), respectively. All 12 grip-strength AUC increments across algorithms, definitions and cohorts had intervals that included zero. Calibration was unchanged and the incremental net benefit was not consistently positive. Model attributions to grip strength varied by algorithm. ConclusionsIn middle-aged adults, detailed adiposity, but not grip strength, added reproducible information for concurrent cardiometabolic risk stratification beyond conventional anthropometry and muscle mass. HighlightsO_LIDXA adiposity added about 0.02 AUC in both development and temporal validation C_LIO_LIGrip strength added no stable increment beyond adiposity and muscle mass C_LIO_LIAll 12 grip-strength AUC increments had 95% CIs that included zero C_LIO_LIGrip strength received model attributions that did not improve performance C_LIO_LIFrozen models were scored once in a later, temporally separated NHANES cycle C_LI
ER -