Fat-free mass and glucose homeostasis: is greater fat-free mass an independent predictor of insulin resistance?
A greater fat-free mass (FFM) is purported to be associated with protective effects on insulin resistance (IR). However, recent studies suggested negative associations between FFM and IR.
(1) To explore the direction of the association between FFM and IR in a large heterogeneous sample after controlling for confounding factors. (2) To determine cut off values of FFM associated with an increased risk of IR.
Outcome variables were measured in 7044 individuals (48.6% women, 20–79 years; NHANES, 1999–2006): body composition [fat mass (FM), FFM and appendicular FFM (aFFM); DXA], FFM index [FFMI: FFM/height (kg/m2)], appendicular FFMI [aFFM/height (kg/m2)] and insulin resistance (HOMA-IR). Multivariate regression analyses were performed to determine the independent predictors of HOMA-IR in younger (20–49 years) and older (50–79 years) men and women. ROC analyses were used to determine FFM cut-offs to identify a higher risk of insulin resistance (HOMA-IR > 75th percentile).
aFFMI was an independent predictor of IR in younger (men: β = 0.21; women: β = 0.31; all p ≤ 0.001) and older (men: β = 0.11; women: β = 0.37; all p ≤ 0.001) individuals. Thresholds for aFFMI at which the risk of IR was significantly increased were 8.96 and 8.39 kg/m2 in younger and older men, and 7.22 and 6.64 kg/m2 in younger and older women, respectively.
Independently of age, a greater aFFMI was an independent predictor of IR. These results suggest revisiting how we envision the link between FFM and IR and explore potential mechanisms.
KeywordsFat-free mass Fat-free mass thresholds Insulin resistance HOMA-IR
A.G and J-C.L, both contributed to the review of literature, database design, statistical analysis, interpretation of the data and drafting of the manuscript. M.B and I.D contributed to the drafting and revision of the manuscript. All of the authors approved the final manuscript prior to submission and they are guarantors of this work and take responsibility for the integrity of the data and the accuracy of the data analysis.
Compliance with ethical standards
Conflict of interest
All authors declare no conflict of interest.
The protocol was approved by the National Center for Health Statistics.
All participants provided written and informed consent.
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