Living Environment and Mobility of Older Adults

被引:26
作者
Cress, M. Elaine [1 ]
Orini, Stefania [2 ]
Kinsler, Laura [1 ]
机构
[1] Univ Georgia, Dept Kinesiol, Athens, GA 30677 USA
[2] Univ Brescia, Fdn Richiedei, Gussago, Italy
关键词
Physical functioning; Physical activity; Pedometer; Housing; Independence; PHYSICAL FUNCTIONAL PERFORMANCE; HEALTH; OUTCOMES;
D O I
10.1159/000322195
中图分类号
R592 [老年病学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 100203 ;
摘要
Background: Older adults often elect to move into smaller living environments. Smaller living space and the addition of services provided by a retirement community (RC) may make living easier for the individual, but it may also reduce the amount of daily physical activity and ultimately reduce functional ability. Objective: With home size as an independent variable, the primary purpose of this study was to evaluate daily physical activity and physical function of community dwellers (CD; n = 31) as compared to residents of an RC (n = 30). Methods: In this cross-sectional study design, assessments included: the Continuous Scale Physical Functional Performance - 10 test, with a possible range of 0-100, higher scores reflecting better function; Step Activity Monitor (StepWatch 3.1); a physical activity questionnaire, the area of the home (in square meters). Groups were compared by one-way ANOVA. A general linear regression model was used to predict the number of steps per day at home. The level of significance was p < 0.05. Results: Of the 61 volunteers (mean age: 79 +/- 6.3 years; range: 65-94 years), the RC living space (68 +/- 37.7 m(2)) was 62% smaller than the CD living space (182.8 +/- 77.9 m(2); p = 0.001). After correcting for age, the RC took fewer total steps per day excluding exercise (p = 0.03) and had lower function (p = 0.005) than the CD. Conclusion: On average, RC residents take 3,000 steps less per day and have approximately 60% of the living space of a CD. Home size and physical function were primary predictors of the number of steps taken at home, as found using a general linear regression analysis. Copyright (C) 2010 S. Karger AG, Basel
引用
收藏
页码:287 / 294
页数:8
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