Normative Data for Lean Mass Using FNIH Criteria in an Australian Setting

Abstract The new ICD‐10‐CM (M62.84) code for sarcopenia represents a major step forward in recognizing sarcopenia as a disease. This should lead to an increase in availability of diagnostic tools and the enthusiasm for pharmacological companies to develop drugs for sarcopenia.

The aim of this study was to develop reference ranges for total and appendicular lean mass measured using dual-energy X-ray absorptiometry (DXA) from a randomly selected population-based sample of men and women residing in southeastern Australia. Men (n = 1,411) and women (n = 960) aged 20-93 years, enrolled in the Geelong Osteoporosis Study, were randomly selected from the Barwon Statistical Division using the electoral roll as a sampling frame in 2001-2006 (67 % participation) and 1993-1997 (77 % participation), respectively. Using DXA (Lunar DPX-L or Prodigy Pro) at baseline for men and at the 10-year follow-up for women (2004-2008), total and appendicular lean mass were measured. Means and standard deviations for each lean mass measure (absolute and relative to height squared) were generated for each age decade, and cutpoints equivalent to T scores of -2.0 and -1.0 were calculated using data from young adult men and women aged 20-39 years. Young adult reference data were derived from 374 men and 308 women. Cutpoints for relative appendicular lean mass equal to T scores of -2.0 and -1.0 were 6.94 and 7.87 kg/m(2) for men and 5.30 and 6.07 kg/m(2) for women. The proportions of men and women aged ≥80 years with a T score less than -2.0 were 16.0 and 6.2 %, respectively. These reference ranges may be useful for identifying lean mass deficits in the assessment of muscle wasting and sarcopenia.

Background The body mass index (BMI) is commonly used as a surrogate marker for adiposity. However, the BMI indicates weight-for-height without considering differences in body composition and the contribution of body fat to overall body weight. The aim of this cross-sectional study was to identify sex-and-age-specific values for percentage body fat (%BF), measured using whole body dual energy x-ray absorptiometry (DXA), that correspond to BMI 18.5 kg/m2 (threshold for underweight), 25.0 kg/m2 (overweight) and 30.0 kg/m2 (obesity) and compare the prevalence of underweight, overweight and obesity in the adult white Australian population using these BMI thresholds and equivalent values for %BF. These analyses utilise data from randomly-selected men (n = 1446) and women (n = 1045), age 20–96 years, who had concurrent anthropometry and DXA assessments as part of the Geelong Osteoporosis Study, 2001–2008. Results Values for %BF cut-points for underweight, overweight and obesity were predicted from sex, age and BMI. Using these cut-points, the age-standardised prevalence among men for underweight was 3.1% (95% CI 2.1, 4.1), overweight 40.4% (95% CI 37.7, 43.1) and obesity 24.7% (95% CI 22.2, 27.1); among women, prevalence for underweight was 3.8% (95% CI 2.6, 5.0), overweight 32.3% (95% CI 29.5, 35.2) and obesity 29.5% (95% CI 26.7, 32.3). Prevalence estimates using BMI criteria for men were: underweight 0.6% (95% CI 0.2, 1.1), overweight 45.5% (95% CI 42.7, 48.2) and obesity 19.7% (95% CI 17.5, 21.9); and for women, underweight 1.4% (95% CI 0.7, 2.0), overweight 30.3% (95% CI 27.5, 33.1) and obesity 28.2% (95% CI 25.4, 31.0). Conclusions Utilising a single BMI threshold may underestimate the true extent of obesity in the white population, particularly among men. Similarly, the BMI underestimates the prevalence of underweight, suggesting that this body build is apparent in the population, albeit at a low prevalence. Optimal thresholds for defining underweight and obesity will ultimately depend on risk assessment for impaired health and early mortality.