Journal of pain and symptom management · 2014
A population-based cross-sectional study that defined normative population data for the Life-Space Mobility Assessment-composite score.
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Phillips Jane, Dal Grande Eleonora, Ritchie Christine, Abernethy Amy P, Currow David C
Аннотация
CONTEXT: Mobility is linked to health status and quality of life. Life-Space Mobility Assessment (LSMA; range 0-120) measures the spatial extent of people's excursion and physical support needs over the preceding month.
OBJECTIVES: The aim of this study was to generate normative population data for an LSMA-Composite (LSMA-C) score, irrespective of age or health service contact and explore the LSM of people with diabetes, current asthma, arthritis, and osteoporosis.
METHODS: LSMA questions were included in the 2011 South Australian Health Omnibus Survey, a multistage, systematic, and clustered sample of household face-to-face interviews. Sociodemographic and clinical variables were explored in relation to LSMA scores using descriptive, univariable, and multivariable analyses and receiver operator curves.
RESULTS: For the 3032 respondents, the mean LSMA score was 98.3 (SD 20.3; median 100; interquartile range 34 [86-120]; range 6-120). Five percent of respondents scored <60, 11% scored between ≥ 60 and 79, 27% scored between ≥ 80 and 99, and the remainder scored between 100 and 120. After 55 years of age, LSMA-C scores declined, more so in females. In multivariable analysis, declining scores were associated with being female, being older, living in rural areas, lower educational attainment, not working, lower household income, and higher numbers of chronic conditions (R(2) = 0.35, P < 0.001). The receiver operator curve demonstrated a highly specific but relatively insensitive measure.
CONCLUSION: Having controlled for known confounders, the male/female difference cannot be easily explained. These data will help to contextualize studies in the future that use the LSMA-C score.
OBJECTIVES: The aim of this study was to generate normative population data for an LSMA-Composite (LSMA-C) score, irrespective of age or health service contact and explore the LSM of people with diabetes, current asthma, arthritis, and osteoporosis.
METHODS: LSMA questions were included in the 2011 South Australian Health Omnibus Survey, a multistage, systematic, and clustered sample of household face-to-face interviews. Sociodemographic and clinical variables were explored in relation to LSMA scores using descriptive, univariable, and multivariable analyses and receiver operator curves.
RESULTS: For the 3032 respondents, the mean LSMA score was 98.3 (SD 20.3; median 100; interquartile range 34 [86-120]; range 6-120). Five percent of respondents scored <60, 11% scored between ≥ 60 and 79, 27% scored between ≥ 80 and 99, and the remainder scored between 100 and 120. After 55 years of age, LSMA-C scores declined, more so in females. In multivariable analysis, declining scores were associated with being female, being older, living in rural areas, lower educational attainment, not working, lower household income, and higher numbers of chronic conditions (R(2) = 0.35, P < 0.001). The receiver operator curve demonstrated a highly specific but relatively insensitive measure.
CONCLUSION: Having controlled for known confounders, the male/female difference cannot be easily explained. These data will help to contextualize studies in the future that use the LSMA-C score.