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Article Abstract

Background: Sarcopenia, defined by the gradual decline in skeletal muscle mass and functionality, is a common disorder in the aging population and is linked to an elevated risk of falls and osteoporotic fractures. The contemporary diagnosis of sarcopenia depends on intricate and expensive techniques, such as computed tomography (CT) scans or dual-energy X-ray absorptiometry (DXA), which hinder the timely prevention of sarcopenia.

Objective: This study seeks to explore the association between the Body Roundness Index (BRI) and sarcopenia in the older adult cohort, utilizing data from the National Health and Nutrition Examination Survey (NHANES) in the United States.

Methods: Our study adopted a cross-sectional design, encompassing 9,411 older individuals, of which 1,147 were diagnosed with sarcopenia. After weighting, the number of individuals with sarcopenia was 23,985,011. The study employed multivariate logistic regression analysis to evaluate the association between BRI and sarcopenia, incorporating stepwise adjustments for potential confounders.

Results: The outcomes of the multivariate logistic regression analysis revealed that, in contrast to individuals without sarcopenia, those with sarcopenia exhibited significantly higher mean BRI values and a greater prevalence of comorbid conditions, including hypertension and diabetes. A significant positive correlation was observed between BRI and the likelihood of developing sarcopenia. Specifically, after controlling for all covariates, each one-unit increase in BRI was linked to a 64% elevation in the risk of sarcopenia (OR = 1.64, 95% CI = 1.58-1.71). Furthermore, the receiver operating characteristic (ROC) curve analysis indicated that BRI is a robust predictor for diagnosing sarcopenia, with an AUC of 0.744.

Conclusion: These findings suggest that, within the U.S. older adult population, an elevated BRI is associated with a heightened risk of sarcopenia. BRI can function as a practical and cost-effective anthropometric index for more precise prediction of sarcopenia risk in older adults.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12006143PMC
http://dx.doi.org/10.3389/fpubh.2025.1554491DOI Listing

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