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Impact of Long-Term Insulin Therapy on Body Composition and Metabolic Age in Type 2 Diabetes Mellitus Patients: A Cross-Sectional Study Using Bioelectrical Impedance Analysis
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Darmawati2
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Sarah Firdausa3
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Irfanita Nurhidayah4
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Ahyana1
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Authors Info & Affiliations
Abstract
Introduction
Patients with Type 2 Diabetes Mellitus (T2DM) are prone to changes in body composition, which are often characterized by excess visceral fat and metabolic aging. Long-term insulin use is known to influence weight and fat distribution, but its effect on metabolic age remains unclear.
Objective
To examine the relationship between Body Mass Index (BMI), visceral fat, metabolic age, and the duration of insulin therapy among patients with T2DM using Bioelectrical Impedance Analysis (BIA).
Methods
This cross-sectional study involved 199 adults with T2DM receiving insulin therapy at the Endocrine Outpatient Polyclinic. Anthropometric data and BIA-derived parameters were analyzed. Spearman’s correlation assessed relationships among BMI, visceral fat, and metabolic age, while the Mann–Whitney U test compared body composition between short-term (<5 years) and long-term (≥5 years) insulin users.
Results
The majority of T2DM patients were in the obese category (69.3%). BMI showed significant positive correlations with both visceral fat (ρ = 0.43, p < 0.001) and metabolic age (ρ = 0.41, p <0.001). Visceral fat was also weakly but significantly correlated with metabolic age (ρ = 0.21, p = 0.002). Patients on insulin for less than five years had slightly higher BMI than those on longer therapy (26.7 vs 25.6 kg/m2; p = 0.025), while visceral fat and metabolic age did not differ significantly.
Discussion
These findings emphasize that adiposity plays a more dominant role than insulin exposure duration in determining metabolic aging and changes in body composition.
Conclusion
Higher adiposity, especially visceral fat, is strongly linked with accelerated metabolic aging in insulin-treated T2DM, whereas insulin duration has minimal effect. Nurses should facilitate routine body-composition monitoring using BIA to detect early metabolic deterioration and support individualized interventions targeting weight control and metabolic health.