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Association of muscle mass measured by D3-Creatine (D3Cr), sarcopenic obesity, and insulin-glucose homeostasis in postmenopausal women

  • Harvard University
  • SUNY Buffalo
  • Duke University
  • University of California at Berkeley

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

The D3-Creatine (D3Cr) dilution method is a direct and accurate measure of skeletal muscle mass. In this study, we examined the association of D3Cr muscle mass with measures of insulin-glucose homeostasis in community dwelling postmenopausal women. Additionally, we examined association of sarcopenic obesity, defined as low D3Cr muscle mass and high percent body fat, with fasting plasma glucose, insulin, hemoglobin A1c and insulin resistance. Insulin resistance was measured by the homeostatic measure of insulin resistance (HOMA-IR). This pilot study included 74 participants (mean age = 82.3 years) from the Women’s Health Initiative-Buffalo site. The D3Cr method was initiated at a clinic visit and used to measure muscle mass via remote urine sample collection. Descriptive and graphical approaches and age-adjusted linear regression models were used to analyze study data. We examined muscle mass as an absolute value (kg) and scaled to body weight (D3Cr muscle mass/kg). There was an inverse relationship between skeletal muscle mass, and impaired insulin-glucose homeostasis. Women with low muscle mass had higher levels of insulin (uIU/mL; β = -0.40; 95% CI: -0.79, -0.01), fasting plasma glucose (mg/dL; β = -0.1; 95% CI: -0.2, 0.03), HbA1c (%; β = -2.30; 95% CI: -5.7, 1.1), and calculated homeostatic model of insulin resistance, HOMA-IR, (β = -1.49; 95% CI: -2.9, -0.1). Sarcopenic obesity was common in this population of women; 41% of participants were categorized as having low muscle mass and high percent body fat. Results demonstrate that D3Cr muscle mass is independently associated with measures of insulin-glucose homeostasis, but obesity is a stronger predictor of insulin resistance than muscle mass.

Original languageEnglish
Article numbere0278723
JournalPLOS ONE
Volume17
Issue number12 December
DOIs
StatePublished - Dec 2022

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