Lipids in health and disease · 2024
Associations of the fat-free mass index and the fat mass index with the risk of developing diabetes and prediabetes in US adults: a nationally representative cross-sectional study.
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Liu Da, Lei You-Lan, Zhang Li, Wang Wenyao, Shao Chunli, Zhou Qing, Liu Haiping, Wen Jun, Wang Jingjia, Li Chen, Luo Yiming, Rao Jingxin, Shi Yukun, Liu Gang, Yang Jie, Zheng Mingqi, Tang Yi-Da
Аннотация
BACKGROUND: Obesity and overweight, as determined by the body mass index (BMI), are harmful to metabolic health. However, the BMI can not reflect body composition or fat distribution. The fat-free mass index (FFMI) and the fat mass index (FMI) can provide more information on body composition. The aim of the observational research was to determine whether the FMI and the FFMI are significantly associated with the risk of developing diabetes and prediabetes.
METHODS: The investigators included data for 10,085 National Health and Nutrition Examination Survey (2011-2018) participants aged over 20 years who underwent dual-energy X-ray absorptiometry (DXA). The FFMI and the FMI were determined based on total fat mass and lean mass measured by DXA. Diabetes and prediabetes status were determined by medical history and laboratory examination. Logistic regression analyses were performed to explore the correlations between the FMI/FFMI and the risk of developing diabetes/prediabetes. Restricted cubic spline analysis was used to explore underlying nonlinear associations.
RESULTS: In the present study, 1,135 patients were diagnosed with diabetes, 3,258 had prediabetes, and 5,692 were classified as control participants. The FFMI (odds ratio (OR) = 1.10, 95% confidence interval (CI) = 1.04-1.16) and the FMI (OR = 1.08, 95% CI = 1.04-1.12) were independently related to an increased risk of developing diabetes. Moreover, the FFMI (OR 1.08, 95% CI 1.02-1.16) and the FMI (OR 1.07, 95% CI 1.02-1.13) also independently correlated with a rising risk of developing prediabetes. The restricted cubic spline (RCS) outcomes suggested that the associations are approximately linear.
CONCLUSIONS: Both the FMI and the FFMI significantly correlated with the danger of developing diabetes and prediabetes, and the correlations are approximately linear.
METHODS: The investigators included data for 10,085 National Health and Nutrition Examination Survey (2011-2018) participants aged over 20 years who underwent dual-energy X-ray absorptiometry (DXA). The FFMI and the FMI were determined based on total fat mass and lean mass measured by DXA. Diabetes and prediabetes status were determined by medical history and laboratory examination. Logistic regression analyses were performed to explore the correlations between the FMI/FFMI and the risk of developing diabetes/prediabetes. Restricted cubic spline analysis was used to explore underlying nonlinear associations.
RESULTS: In the present study, 1,135 patients were diagnosed with diabetes, 3,258 had prediabetes, and 5,692 were classified as control participants. The FFMI (odds ratio (OR) = 1.10, 95% confidence interval (CI) = 1.04-1.16) and the FMI (OR = 1.08, 95% CI = 1.04-1.12) were independently related to an increased risk of developing diabetes. Moreover, the FFMI (OR 1.08, 95% CI 1.02-1.16) and the FMI (OR 1.07, 95% CI 1.02-1.13) also independently correlated with a rising risk of developing prediabetes. The restricted cubic spline (RCS) outcomes suggested that the associations are approximately linear.
CONCLUSIONS: Both the FMI and the FFMI significantly correlated with the danger of developing diabetes and prediabetes, and the correlations are approximately linear.