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Correlation of Hemoglobin, Uric Acid, and Anthropometric as Predictor Parameters in Subcutaneous Fat Deposition Sari, Triyana; Sidharta, Erik; Santoso, Alexander Halim; Teguh, Stanislas Kotska Marvel Mayello; Gaofman, Brian Albert; Edbert, Bruce
JURNAL RISET RUMPUN ILMU KEDOKTERAN Vol. 4 No. 1 (2025): April : Jurnal Riset Rumpun Ilmu Kedokteran
Publisher : Pusat riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurrike.v4i1.4890

Abstract

Subcutaneous fat deposition is a key factor influencing overall health, playing a significant role in metabolic regulation, energy balance, and the risk of chronic diseases such as obesity and cardiovascular conditions. Understanding and accurately predicting subcutaneous fat accumulation is critical for early intervention and effective management of these health risks. This study aims to analyze the correlation between hemoglobin levels, uric acid, and anthropometric parameters as predictors of subcutaneous fat deposition in elderly individuals. A cross-sectional study was conducted on 32 elderly participants at St. Asisi Church. Anthropometric measurements, including body weight, height, muscle composition, and circumferences, were assessed using OMRON Body Composition Monitor HBF-375, elastic tape and GEA Medical HT721. Biochemical tests for hemoglobin and uric acid levels were performed using Fora 6 Plus. Spearman correlation analysis was used to evaluate the relationship between these variables and subcutaneous fat deposition. Body weight, upper arm circumference, abdominal circumference, and calf circumference showed strong positive correlations with subcutaneous fat (r>0.9, p<0.001). Skeletal muscle percentage exhibited a negative correlation with fat accumulation. Hemoglobin and uric acid levels had weaker correlations, suggesting more complex metabolic interactions. Anthropometric parameters serve as strong predictors of subcutaneous fat deposition in elderly individuals, while hemoglobin and uric acid levels show limited predictive capability.