Simple-measured leg muscle strength and the prevalence of diabetes among Japanese males: a cross-sectional analysis of data from the Kameda health study.
Rumi Miyamoto, Susumu S Sawada, Yuko Gando and 6 others
PMID 32082019WHAT IT FOUND
Japanese men who could not stand up on one leg from a 40 cm chair with either leg were more likely to have diabetes.
The main result used one chair height and one attempt, so it may be a simple marker of leg strength.
Key findings
01Men who could not stand up on one leg from a 40 cm chair with either leg had higher adjusted odds of diabetes than men who could stand up on one leg with both legs (adjusted OR 1.52, 95% CI 1.16 to 2.00).
02After further adjustment for body mass index, the higher odds remained significant (adjusted OR 1.37, 95% CI 1.04 to 1.81).
03The diabetes prevalence was 27.2% overall and 39.5% among men who failed to stand up on both right and left legs.
STILL TO COME
How it was doneWhat they foundWhat it means for PTs
Read the rest of this summary
You get three full summaries a month, free, and we do not ask for a card. Search, the TL;DRs and your library stay unlimited either way.
What it does not show
This was a cross-sectional analysis, so it cannot show that weak leg strength caused diabetes or that diabetes caused weak leg strength. Only Japanese men were included, so it is unclear whether the same finding applies to women. The median age was 61 years, with an interquartile range of 56 to 67 years, so it is unclear whether the same finding applies to younger men. Men chose the Locomo-test as an option within a comprehensive health examination, so the sample may not represent all men. Some men were classified as having diabetes based on a questionnaire answer about diagnosis or treatment.
Declared interests
The authors declared that they have no conflict of interest.
The easy way to misread this
Do not conclude that the one-leg stand-up test diagnoses diabetes or that improving leg strength will reduce diabetes. The study was cross-sectional and measured diabetes prevalence at the same time as the test, so it shows an association, not cause or effect.