Association of Shorter Secondary One-Leg Standing Time with Loss of Independence or Death in Community-Dwelling Older Adults in the Aizu Cohort Study (LOHAS)

Objectives

Although a previous report indicated that the primary one-leg standing time (OLST), defined as the longer OLST of both legs, is associated with death, the association between secondary OLSTs (the shorter OLSTs) and death remains unclear. This study investigated the association between secondary OLSTs and the loss of independence (LOI) or death.

Design

Population-based cohort study.

Setting and Participants

This study was conducted in 2 Japanese municipalities. Between 2008 and 2010, bilateral OLSTs were measured in independent adults aged ≥65 years. In total, 3278 participants were included in the primary analysis.

Methods

The outcome was a composite of LOI and death. LOI was defined as the need for complete support in basic activities of daily living, corresponding to care levels 3 to 5 of the Japanese long-term care insurance certification. A Cox proportional hazards model was used to estimate the adjusted hazard ratios (HRs) and 95% CIs for the association between secondary OLSTs and LOI or death. We also conducted additional analyses limited to those with normal primary OLSTs (≥30 seconds) and evaluated the independent role of secondary OLST.

Results

During follow-up (median: 7.22 years), LOI or death occurred in 452 (13.7%) participants. Shorter secondary OLSTs were associated with LOI or death; the multivariable HR (95% CI) was 2.17 (1.67-2.84) in those with secondary OLSTs of <10 seconds, 1.54 (1.13-2.10) for OLSTs of 10-20 seconds, and 0.88 (0.56-1.37) for OLSTs of 20-30 seconds, compared to those with normal secondary OLSTs (≥30 seconds). These associations remained consistent in additional analyses limited to those with normal primary OLSTs.

Conclusions and Implications

Shorter secondary OLSTs are risk factors for LOI or death in older adults, even when the primary OLSTs are within the normal range. Assessing OLSTs on both sides is important for predicting prognostic outcomes.