Literature DB >> 20159128

Predictive validity of the classification schema for functional mobility tests in instrumental activities of daily living decline among older adults.

Hiroyuki Shimada1, Patricia Sawyer, Kazuhiro Harada, Satomi Kaneya, Kenji Nihei, Yasuyoshi Asakawa, Chiharu Yoshii, Akiyoshi Hagiwara, Taketo Furuna, Tatsuro Ishizaki.   

Abstract

OBJECTIVE: To determine predictive validity for cut points of the Timed Up & Go (TUG) test and life-space assessment (LSA) on decline in instrumental activities of daily living (IADLs) among older adults.
DESIGN: Cross-sectional and 1-year follow-up study.
SETTING: Preventive health care services. PARTICIPANTS: In a cross-sectional study, 2404 older adults (65-100 y) were recruited to determine cut points for the TUG and LSA for IADLs limitation. For longitudinal analysis, 436 older adults (65-100 y) were followed over 1 year to explore the validity of a classification model using the cut points to predict incident IADLs decline.
INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: The TUG, LSA, and Tokyo Metropolitan Institute of Gerontology index of IADLs measurement.
RESULTS: The cut points associated with IADLs limitations for the TUG and LSA were 12 seconds and 56 points, respectively. Participants were classified into fast/high (most able; TUG <12 and LSA >56), fast/low, slow/high, and slow/low (vulnerable; TUG > or =12 and LSA < or =56) groups; there were 813 (34%), 385 (16%), 246 (10%), and 960 (40%) participants in each group, respectively. The proportions of participants with IADLs limitation in the most able, fast/low, slow/high, and vulnerable groups were 19%, 64%, 61%, and 89%, respectively. The vulnerable group included significantly more participants with IADLs limitation than any other group (P<.001). Compared with a most able group, the odds ratios of IADLs decline for the fast/low and vulnerable groups were 2.52 (95% confidence interval 1.15-5.53, P<.05) and 2.87 (95% confidence interval 1.38-5.96, P<.01), respectively.
CONCLUSIONS: The combination of TUG and LSA identifies persons with future IADLs decline and has the potential to be used by community health care services to target individualized interventions. Copyright 2010 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2010        PMID: 20159128     DOI: 10.1016/j.apmr.2009.10.027

Source DB:  PubMed          Journal:  Arch Phys Med Rehabil        ISSN: 0003-9993            Impact factor:   3.966


  19 in total

1.  Mobility, disability, and social engagement in older adults.

Authors:  Andrea L Rosso; Jennifer A Taylor; Loni Philip Tabb; Yvonne L Michael
Journal:  J Aging Health       Date:  2013-04-02

2.  Life-Space Mobility and Relevant Factors in Community-dwelling Individuals with Stroke in Japan: A Cross-sectional Study.

Authors:  Hideyuki Tashiro; Takuya Isho; Takanori Takeda; Takahito Nakamura; Naoki Kozuka; Fumihiko Hoshi
Journal:  Prog Rehabil Med       Date:  2019-09-03

3.  Mobility as a predictor of all-cause mortality in older men and women: 11.8 year follow-up in the Tromsø study.

Authors:  Astrid Bergland; Lone Jørgensen; Nina Emaus; Bjørn Heine Strand
Journal:  BMC Health Serv Res       Date:  2017-01-10       Impact factor: 2.655

4.  Factors influencing life-space mobility change after total knee arthroplasty in patients with severe knee osteoarthritis.

Authors:  Takashi Tobinaga; Shigeru Obayashi; Ryuhei Miyamoto; Kodai Oba; Namiko Abe; Shiori Tsukamoto; Masato Ogawa; Yuki Tochigi; Koichiro Oka; Satoru Ozeki
Journal:  J Phys Ther Sci       Date:  2019-11-26

5.  Effects of exercise and horticultural intervention on the brain and mental health in older adults with depressive symptoms and memory problems: study protocol for a randomized controlled trial [UMIN000018547].

Authors:  Hyuma Makizako; Kota Tsutsumimoto; Takehiko Doi; Ryo Hotta; Sho Nakakubo; Teresa Liu-Ambrose; Hiroyuki Shimada
Journal:  Trials       Date:  2015-11-04       Impact factor: 2.279

6.  Concurrent validity of the Swedish version of the life-space assessment questionnaire.

Authors:  Sofi Fristedt; Ann-Sofi Kammerlind; Marie Ernsth Bravell; Eleonor I Fransson
Journal:  BMC Geriatr       Date:  2016-11-08       Impact factor: 3.921

7.  Life Space Assessment in Stroke Patients.

Authors:  You-Na Yang; Bo-Ram Kim; Kyeong Eun Uhm; Soo Jin Kim; Seunghwan Lee; Mooyeon Oh-Park; Jongmin Lee
Journal:  Ann Rehabil Med       Date:  2017-10-31

Review 8.  Assessing life-space mobility for a more holistic view on wellbeing in geriatric research and clinical practice.

Authors:  Joanne K Taylor; Iain E Buchan; Sabine N van der Veer
Journal:  Aging Clin Exp Res       Date:  2018-08-04       Impact factor: 3.636

Review 9.  Muscle mass, strength, and physical performance predicting activities of daily living: a meta-analysis.

Authors:  Daniel X M Wang; Jessica Yao; Yasar Zirek; Esmee M Reijnierse; Andrea B Maier
Journal:  J Cachexia Sarcopenia Muscle       Date:  2019-12-01       Impact factor: 12.910

10.  Exercise and Horticultural Programs for Older Adults with Depressive Symptoms and Memory Problems: A Randomized Controlled Trial.

Authors:  Hyuma Makizako; Kota Tsutsumimoto; Takehiko Doi; Keitaro Makino; Sho Nakakubo; Teresa Liu-Ambrose; Hiroyuki Shimada
Journal:  J Clin Med       Date:  2019-12-30       Impact factor: 4.241

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.