Diabetes research and clinical practice · 2025
Imaging-based lean mass distribution and diabetic nephropathy in the US population.
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Zhang Xiaoqian, Han Bin, Yuan Weijie, Li Chenxin
Аннотация
AIMS: The present study aims to investigate the association between lean body mass (LBM) distribution and diabetic nephropathy (DN) in the US population with diabetes.
METHODS: This cross-sectional study utilized the 2011 to 2018 data from the NHANES. Body composition was assessed using DXA. Multivariable logistic regression analysis was conducted to evaluate the association between regional LBM distribution and the risk of DN. Linear regression analyses were also performed to examine the correlation between android-gynoid lean mass ratio (AGLR) and ACR.
RESULTS: After adjusting for sex, age, race, diabetes duration, and the levels of blood pressure, hemoglobin A1c (HbA1c), and non-high-density lipoprotein cholesterol (non-HDL-C), increases in both android lean mass index (LMI) and AGLR were significantly associated with the higher prevalence of DN. These associations remained statistically significant in males. Both univariable and multivariable linear regression analyses demonstrated a positive linear correlation between AGLR and ACR (p < 0.05).
CONCLUSIONS: The present study suggests that elevated android LMI and AGLR are associated with the prevalence of DN in individuals with diabetes. Moreover, AGLR also shows a statistically significant association with ACR. These findings highlight the importance of considering lean mass distribution when assessing the risk of DN.
METHODS: This cross-sectional study utilized the 2011 to 2018 data from the NHANES. Body composition was assessed using DXA. Multivariable logistic regression analysis was conducted to evaluate the association between regional LBM distribution and the risk of DN. Linear regression analyses were also performed to examine the correlation between android-gynoid lean mass ratio (AGLR) and ACR.
RESULTS: After adjusting for sex, age, race, diabetes duration, and the levels of blood pressure, hemoglobin A1c (HbA1c), and non-high-density lipoprotein cholesterol (non-HDL-C), increases in both android lean mass index (LMI) and AGLR were significantly associated with the higher prevalence of DN. These associations remained statistically significant in males. Both univariable and multivariable linear regression analyses demonstrated a positive linear correlation between AGLR and ACR (p < 0.05).
CONCLUSIONS: The present study suggests that elevated android LMI and AGLR are associated with the prevalence of DN in individuals with diabetes. Moreover, AGLR also shows a statistically significant association with ACR. These findings highlight the importance of considering lean mass distribution when assessing the risk of DN.