Life-space mobility trajectory patterns and associated characteristics in older cancer survivors: a secondary data analysis - Richard A. Taylor; Marie Bakitas; Rachel Wells; J. Nicholas Odom; Richard. Kennedy; Grant R. Williams; Jennifer Frank; Peng Li (BMC Geriatrics)
Abstract Background Life-space mobility (LSM) measures the size of the real-world geographic area an individual purposely transverses in their daily life. While older cancer survivors often have declines in LSM that negatively affects their quality of life, independence, and social engagement the factors that predispose to adverse outcomes are unknown. Understanding different patterns of LSM and its decline can help identify those needing support. The purpose of this study was to identify: (1) LSM trajectory patterns and (2) factors associated with those patterns in older cancer survivors. Methods This paper reports a secondary data analysis of 153 participants with cancer ≥ 65 years from the University of Alabama Study of Aging. LSM was assessed using the UAB Life-Space Assessment-Composite score (LSA-C) at study entry and every 6 months for 96 months (LSA-C < 60 = restricted LSM). LSM trajectory patterns based on the LSA-C were determined using group-based trajectory analysis. A classification tree analysis revealed factors that predicted the trajectory patterns. Results Participants (n = 153) were a mean age of 76.1 (SD 6.33), mostly male (58%), White (58%), married (55%) or widowed (37%), and had a diagnosis of prostate (37.3%), breast (20.3%), or colon (11.8%) cancer. Three LSM trajectory patterns were identified: (1) high start and stable (37.3%) with unrestricted LSM (LSA-C = 81.2) at study entry, which remained stable over time, (2) high start progressive decline (27.5%) with unrestricted LSM (LSA-C = 78.0) at study entry that progressively declined, and (3) low start progressive decline (35.3%) with restricted LSM level (LSA-C = 42.0) at study entry, which progressively declined. Each pattern was associated with a unique set of demographic and clinical characteristics. Baseline physical performance score was the most important predictor of the LSM trajectory patterns. Conclusions Three distinct LSM trajectory patterns, each with unique demographic and clinical characteristics, were identified. Because older cancer survivors have distinct LSM patterns, interventions should be tailored to address specific characteristics and clinical needs. LSM measurement can contribute to assessment of older adults generally and should become part of standard assessment in older cancer survivors.