E-Poster Presentation 30th Australian and New Zealand Bone and Mineral Society Annual Scientific Meeting 2020

How well do low population-specific values for poor muscle strength and lean mass associate with indices of poor health? (#118)

Sophia X. Sui 1 , Kara L. Holloway-Kew 1 , Natalie K. Hyde 1 , Lana J. Williams 1 , Monica C. Tembo 1 , Sarah Leach 2 , Julie A. Pasco 1 3 4 5
  1. Deakin University, Geelong, VIC, Australia
  2. GMHBA, 2Geelong Medical and Hospital Benefits Association (GMHBA), Geelong, Vic, Australia
  3. St Albans, The university of Melbourne, Melbourne, Vic, Australia
  4. Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia
  5. University Hospital Geelong, Barwon Health, Geelong, VIC, Australia

Background: We aimed to examine associations between measures of skeletal muscle deficits and indices of poor health, using cut-points that identify low values in the distribution of the same population in comparison with cut-points from EWGSOP2 and FNIH.

Methods: Participants (n=665; 323 women) aged 60-96yr were from the Geelong Osteoporosis Study. Handgrip strength (HGS) was measured by dynamometers and appendicular lean mass (ALM) by DXA. Cut-points equivalent to 2SDs below the mean young reference range from the same population were (for men and women): low ALM/height2 <5.30kg/m2, <6.94kg/m2; low ALM/BMI <0.512m2, <0.827m2; low HGS <16kg, <31kg. Cut-points for EWGSOP2 were ALM/height2 <5.50kg, <7.0kg/m2; HGS <16kg, <27kg. For FNIH, ALM/BMI <0.512m2, <0.789m2; HGS <16kg, <26kg. Indices of poor health included poor physical performance, fractures, falls and hospitalisations. Poor physical performance was identified as timed-up-and-go (TUG, 3m) >10s. Falls (at least one) in the past 12 months, fractures (at least one since age≥20yr, all sites and causes) and hospitalisations in the past month were self-reported. Logistic regression models (age and sex-adjusted) were used to identify to examine associations.

Results: There were 177 (25.3%) participants with falls, 189 (28.1%) with fractures including 20 rib 17 humerus, 15 tibia, 28 forearm/wrist, 14 ankle, 14 toe, and 34 others, 48 (6.9%) with hospitalisations and 233 (34.9%) with slow TUG. For all cut-points, low HGS was consistently associated with falls and slow TUG (Figure). Low ALM/BMI, using both population-specific and FNIH criteria, was associated with slow TUG. There was little evidence to support an association between ALM/height2, using any cut-point, and indices of poor health.

Conclusions: Overall, muscle strength performed better than lean mass measures for indicating poor indices of health. These findings add to the growing evidence base to inform decisions regarding the selection of skeletal muscle parameters and their optimal cut-points for identifying sarcopenia.

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