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3D Ultrasound Imaging: Fast and Cost-effective Morphometry of Musculoskeletal Tissue
Published on: November 27, 2017
Skeletal muscle mass and risk of death in an elderly population
S-Y Chuang1, H-Y Chang1, M-S Lee2
1Institute of Population Health Sciences, National Health Research Institutes, Miaoli, Taiwan, ROC.
Background And Aim:
Body mass index (BMI) has a U-shaped relationship with mortality among the elderly, in contrast to the general adult population. Skeletal muscle mass may be more appropriate than BMI for classifying mortality risk among the elderly. We investigated the relationship between skeletal muscle mass and mortality among elderly Chinese persons.
Method And Results:
A total of 1512 elderly from the Nutrition and Health Survey in Taiwanese Elderly (1999-2000) was enrolled, and the survival status was followed using data from the National Death Registry. The skeletal muscle mass index (SMMI) was calculated by dividing skeletal muscle mass by height in meters squared. The Cox proportional hazard model was used to estimate the association between SMMI and mortality. During the follow-up (average time: 7.9 years), one-third elderly died (n = 506) by any cause and 25% of them was cardiovascular mortality (ICD-9-CM: between 390 and 459). The total mortality and cardiovascular mortality were 4.23 and 1.07 per 100 person-years. Elderly participants with the lowest SMMI had the highest total mortality and cardiovascular mortality among the four quartiles (6.72, 3.76, 3.25 and 3.50 per 100 PY for total mortality; 1.81, 0.76, 0.87, 0.93 for cardiovascular mortality). Those with a low (1st quartile) SMMI had a 2-fold increase in total mortality (1.96; 1.63-2.35) and cardiovascular mortality (2.16; 1.51-3.08) risk compared to those with a normal [2nd, 3rd, or 4th quartile] SMMI.
Conclusions:
The threshold relationship between SMMI and mortality is contrast to the reverse J-shaped relationship between BMI and total mortality. Therefore, skeletal muscle mass measurement may be considered with a high priority to identify elderly individuals with a high mortality risk.
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