TY - JOUR
T1 - Sedentary time, physical activity, fitness, and physical function in older adults
T2 - What best predicts sleep quality?
AU - Ramos, Vera
AU - Carraça, Eliana V.
AU - Paiva, Teresa
AU - Baptista, Fátima
N1 - Publisher Copyright:
© 2019 Human Kinetics, Inc.
PY - 2019
Y1 - 2019
N2 - The aim of this study was to identify the best predictor of sleep quality (SQ) among physical behavior or capacity-related variables, namely physical activity, sedentary time, fitness, and physical function (activities of daily living) of independent elders using a representative sample of Portuguese aged 65 years and older (N = 437). SQ and activities of daily living were evaluated by a questionnaire, sedentary time, and physical activity through accelerometry, and physical fitness by means of the Senior Fitness Test. The logistic regression analysis revealed that activities of daily living measured by the Composite Physical Function was the only explanatory variable discriminating between poor SQ and good SQ. Receiver operating characteristic analysis showed that the best trade-off between sensitivity and specificity to discriminate older adults with poor SQ and good SQ was 20 points in the Composite Physical Function (sensitivity = 57.9%; specificity = 60.9%; area under the curve = 0.600, 95% confidence interval [0.536, 0.665], p = .003). Better physical function seems to be associated with better SQ in independent elders.
AB - The aim of this study was to identify the best predictor of sleep quality (SQ) among physical behavior or capacity-related variables, namely physical activity, sedentary time, fitness, and physical function (activities of daily living) of independent elders using a representative sample of Portuguese aged 65 years and older (N = 437). SQ and activities of daily living were evaluated by a questionnaire, sedentary time, and physical activity through accelerometry, and physical fitness by means of the Senior Fitness Test. The logistic regression analysis revealed that activities of daily living measured by the Composite Physical Function was the only explanatory variable discriminating between poor SQ and good SQ. Receiver operating characteristic analysis showed that the best trade-off between sensitivity and specificity to discriminate older adults with poor SQ and good SQ was 20 points in the Composite Physical Function (sensitivity = 57.9%; specificity = 60.9%; area under the curve = 0.600, 95% confidence interval [0.536, 0.665], p = .003). Better physical function seems to be associated with better SQ in independent elders.
KW - Accelerometry
KW - Composite Physical Function
KW - Senior Fitness Test
UR - http://www.scopus.com/inward/record.url?scp=85071713177&partnerID=8YFLogxK
U2 - 10.1123/japa.2018-0035
DO - 10.1123/japa.2018-0035
M3 - Article
C2 - 30676203
AN - SCOPUS:85071713177
SN - 1063-8652
VL - 27
SP - 538
EP - 544
JO - Journal of Aging and Physical Activity
JF - Journal of Aging and Physical Activity
IS - 4
ER -