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Editorial
. 2021 Dec;16(4):609-614.
doi: 10.26574/maedica.2021.16.4.609.

Assessment of Fall Risk in Elderly Rural Population

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Editorial

Assessment of Fall Risk in Elderly Rural Population

Jeganathan Geetha et al. Maedica (Bucur). 2021 Dec.

Abstract

Background: Fall risk assessment is an essential component of a comprehensive fall reduction and prevention program. Fall risk assessment is done to identify patients' risk for falls and ultimately prevent falls from occurring. The aim of the study was to identify the risk factors for fall in the elderly population. Methods:This study included 250 elderly patients > 60 years (105 males, 145 females) attending Medicine OPD in a tertiary care hospital. Detailed history including the previous h/o falls, medication history elicited and divided study subjects into two groups: fallers and non-fallers. Cardiovascular, neurological, and musculoskeletal system examinations were done. Handgrip, 30 seconds chair standing test (CST), "timed up and go" test (TUG), and performance-oriented mobility assessment (POMA) were performed. Results:The prevalence of falls in our study was 27.6%. The mean age of fallers was 72.22±6.219 years (P 0.002). Females had significant falls compared to males (p < 0.001). In binary logistic regression, age >80 [OR-3.8, CI (1.8-8.1); p 0.016], female gender [OR-19.2, CI (3.03-122.2); p 0.002], visual impairment [OR-8.9, CI (1.4-55.4); p 0.019], postural hypotension [OR-59.8, CI (3.3-1.07); p 0.006] and presence of more than three risk factors [OR-9.6, CI (4.6-2.01); p 0.000] were significantly associated with fall in our study. Conclusion:Falls among older people were common, especially among individuals aged over 80. Females were more prone to fall. The number of risk factors, visual impairment, and postural hypotension increased the fall risk. Simple clinical assessment can identify high-risk patients.

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Figures

TABLE 1.
TABLE 1.
Characteristics of study population
TABLE 2.
TABLE 2.
TUG vs falls
TABLE 3.
TABLE 3.
POMA vs falls
TABLE 4.
TABLE 4.
Binary logistic regression of risk factors for fall

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