Catalyst Awardee

Project Description

Technology-Based Fall Risk Assessments for Older Adults in Low-Income Settings

Ladda Thiamwong, Ph.D., RN | University of Central Florida; Jeffrey R. Stout, Ph.D.; Joon-Hyuk Park, Ph.D.; Xin Yan, Ph.D.
Competition Sponsor: National Institute on Aging, National Institutes of Health
Awardee Year: 2020

In the US, older adults (OAs) who live in low-income communities are less likely to engage in physical activity (PA). Lack of PA is related to chronic conditions and poor quality of life. Limited data suggest that OAs who report fear of falling (FOF) and overestimate their fall risk are less likely to participate in PA; and the association between FOF and PA intensity differs by fear severity. One-third of OAs have maladaptive fall risk appraisal (FRA), a condition in which there is a discrepancy between levels of FOF) and balance performance.  Maladaptive FRA may impede low-income OAs participation in PA and can result in social isolation. Measuring FRA in OAs can be challenging due to self-report bias and cognitive deficit. Thus, we developed a fall risk appraisal matrix, a graphical grid categorizing levels of FOF and balance performance into four groups (rational/ incongruent/ irrational/ congruent).  Additionally, body composition (e.g., obesity, low skeletal muscle mass) has been associated with FOF and functional impairment.  However, research has not examined the association among body composition, FRA, and PA using Assistive Health Technology (AHT), which is the application of organization knowledge, skills, procedures, and systems in order to improve functioning. We propose to explore the associations among body composition, FRA, and PA using AHT including bioelectric impedance analysis (BIA), BTracK Balance System (BBS), and accelerometer-based physical activity devices. These devices are portable, non-invasive, safe, valid, reliable and allow for home testing. We employ a cross-sectional study. Aim 1 is to examine the feasibility of recruitment (e.g., how many OAs need to be screened to recruit the sample?) and acceptability of technologies and procedures for use among OAs in low-income settings. Aim 2 is to examine the associations among fall risk appraisal, body composition, and physical activity.  Participants (N=120) will be enrolled if they are: 1) ≥ 60 years of age, 2) low-income (using poverty thresholds from the US Census Bureau), 3) no marked cognitive impairment, and 4) live in their own homes or apartments. Exclusion criteria: 1) a medical condition precluding balance test (e.g., unable to stand on the balance plate) and/or PA (e.g., shortness of breath when performing PA); or 2) currently receiving treatment from a rehabilitation facility, or 3) medical implants (e.g., pacemakers). Data will be collected at OAs’ place of residence.  OAs will be assessed FOF, balance performance, and body composition using a questionnaire, BBS, and BIA, respectively. OAs will wear an accelerometer-based physical activity device (ActiGraph GT9X Link) for 7 days.  Accurate FRA is essential in implementing physical activity programs. This study will provide data for the development of a technology-based intervention that facilitates a shift from maladaptive to adaptive FRA, and improving participation in PA, thus enhancing healthy longevity among OAs in low-income settings.

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