Comparison of field- and laboratory-based estimates of muscle quality index between octogenarians and young older adults: an observational study.
Dahan da Cunha NascimentoJonato PrestesJoyce de Sousa DinizPedro Rodrigues BealVicente Paulo AlvesWhitley StoneFabiani Lage Rodrigues BealPublished in: Journal of exercise rehabilitation (2020)
Muscle quality (the ratio of strength to lean muscle mass) might be a better indicator of muscle function than strength alone. Differences in muscle quality index (MQI) between octogenarians and young older adults remain unclear. The aims of the present cross-sectional study were to compare (1) MQI between octogenarians and young older adults, (2) lab versus field-based MQI tools, and (3) determine possible confounding factors affecting MQI in older adults. Compiled data from two cross-sectional studies included 175 younger and older adults (31 men and 144 women) with a mean age of 75.93±9.49 years. Participants with age ≥80 years old were defined as octogenarians (n=79) and <80 years was defined as young older adults (n=96). Laboratory MQI was derived from the ratio of grip strength to arm muscle mass (in kg) measured by dual-energy x-ray absorptiometry. Field-based MQI was quantified from the ratio of grip strength to body mass index (BMI). Octogenarians displayed lower field (P=0.003) and laboratory MQI (P<0.001) as compared with young older adults. There was a strong correlation effect between field MQI and laboratory MQI (P=0.001, R=0.85). BMI (P=0.001), and diabetes mellitus (P=0.001) negatively affected MQI. Women presented lower MQI (P=0.001) values than men. In light of this information, rehabilitation specialists should consider the use of field-based MQI as a tool for evaluation and follow-up of older population.
Keyphrases
- physical activity
- middle aged
- body mass index
- dual energy
- skeletal muscle
- cross sectional
- computed tomography
- type diabetes
- bone mineral density
- metabolic syndrome
- weight gain
- high resolution
- quality improvement
- electronic health record
- insulin resistance
- polycystic ovary syndrome
- artificial intelligence
- data analysis
- pregnancy outcomes