Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Physical Frailty and Fall Risk in Community-Dwelling Older Adults: A Cross-Sectional Study

Physical Frailty and Fall Risk in Community-Dwelling Older Adults: A Cross-Sectional Study Hindawi Journal of Aging Research Volume 2020, Article ID 3964973, 8 pages https://doi.org/10.1155/2020/3964973 ResearchArticle Physical Frailty and Fall Risk in Community-Dwelling Older Adults: A Cross-Sectional Study 1 1 2 1 Jiraporn Chittrakul, Penprapa Siviroj , Somporn Sungkarat, and Ratana Sapbamrer Department of Community Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, ailand DepartmentofPhysical erapy,FacultyofAssociatedMedicalSciences,ChiangMaiUniversity,ChiangMai 50200, ailand Correspondence should be addressed to Penprapa Siviroj; psiviroj@gmail.com Received 29 October 2019; Revised 25 March 2020; Accepted 13 April 2020; Published 4 July 2020 Academic Editor: Jean-Francois Grosset Copyright © 2020 Jiraporn Chittrakul et al. -is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Introduction. Frailty is a condition in older adults with decreased physical and cognitive performance that can affect health outcomes associated with fracture, disability, and falls. -e aim of this study was to compare fall risk with different physical frailty statuses and investigate factors associated with fall risk in community-dwelling older adults. Methods. -e population studied included 367 older adults (mean age � 73.2 years± 7.0; 237 females (64.6%) and 130 males (35.4%)) who live in Chiang Mai, -ailand. -is study was of cross-sectional design. Fried’s phenotype was used to screen the physical frailty status. -e physiological profile assessment (PPA) was used to screen for fall risk. One-way ANOVA analysis was used to compare the fall risk between the different levels of frailty status. Linear regression analysis was used to assess the association between frailty status and fall risk.Results. -e prevalence of the frailty group was 8.7% and that of the prefrailty group was 76.8%. -e three statuses of frailty identified were found to have different levels of risk of falling. -e frailty group had a higher fall risk than the nonfrailty group and the prefrailty group. In addition, the nonfrailty group had a lower fall risk than the prefrailty group.Conclusion. -e frailty group had the highest fall risk in this cohort of older adults living in a community-dwelling facility. -erefore, it is important to assess the frailty status among older adults as it can be a predictor for fall risk. -is assessment will therefore lead to a reduction in the rate of disability and death in the community. and 55.2% in the prefrailty group [5]. Meanwhile, in -ailand, 1. Introduction the frailty prevalence in the community-dwelling older adults Frailty involves the concepts associated with the deterio- was found to range from 15.0% to 17.2% [6, 7]. Currently, ration of the body related to the aging process. It encom- there are many methods used to assess frailty, of which Fried’s passes the decline in physiology and biological syndromes of frailty phenotype index is the most commonly used and decreased reserve and resistance to stressors that lead to currently has the highest levels of validity and reliability. It is poor health outcomes such as loss of physical and mental mainly used as a unidimensional frailty index and can be used for both clinical and community assessment [8–10]. -is performance [1–3]. -ree clinical conditions are commonly used in the identification and classification of vulnerable index has five components consisting of unintentional weight older adults, specifically, comorbidity, frailty, and disability, loss, self-reported exhaustion, weakness (grip strength), slow which can lead to multiple adverse outcomes such as hos- walking speed, and low physical activity. Scores in three or pitalization and premature mortality in an aging population more areas indicate the frailty group and in one to two areas [4]. Nonetheless, there is no consensus regarding the indicate the prefrailty group, and if there are no scores, the prevalence rate of frailty across countries. In low-income classification is the nonfrailty group [8, 9]. and middle-income countries, there are indicators that the In literature, a systematic review and meta-analysis frailty prevalence in older adults is 12.7% in the frailty group showed frailty can predict future falls in community- 2 Journal of Aging Research treatment of fall prevention in older adults should include an dwelling older adults [11]. Previous studies indicated that a major outcome of frailty is falling [12–15]. Frailty and exercise program, home-safe interventions, vitamin D supplements, and multifactorial intervention [41]. Physio- prefrailty are significant predictors of falls in older adults, and prefrail individuals have 1.36 higher odds of falling [16]. logical profile assessment is a multifactorial assessment of In addition, frailty causes decreased balance and mobility in fall risk which is used to evaluate a complete physiological older adults predicting falls within 12 months [17, 18]. assessment of fall risks in the older adults [39]. However, According to the current knowledge (2016), frailty was there is currently no study assessing fall risk among older associated with motor performance and the risk of falls in adults with frailty using PPA. older adults [19]. Other previous studies reported that the -erefore, this study was designed to investigate any association between all physiological aspects and falls in frail older adults who had low muscle strength, weight loss, decreased gait speed, and high-level fear of falling were older adults. -e objective was to increase the level of in- formation regarding the association between physical frailty associated with frailty and falls [20, 21]. Meanwhile, fear of falling in older adults was related with low dual-task per- status and difference in fall risk. Initial screening or as- sessment of fall risk in the older adults has been shown to formance and reduced activity of daily living function [22]. In addition, there are differences in cognitive frailty between prevent and reduce the risk of falling in a short space of time nonfrailty and prefrailty groups [23]. A prospective pop- [42]. -e aim of this study was to compare fall risk with ulation-based study found that frailty and psychological and different physical frailty statuses to understand more fully cognitive markers were associated with fall and fracture, the different risk of falling in relation to each aspect of increased recurrent falls and fractures, and decreased mo- physiology at each level of frailty in older adults. -is study bility [24, 25]. Likewise, frailty was associated with an in- also investigated factors associated with fall risk in com- munity-dwelling older adults. creasing health perception level, a decline in the ability to adjust to serious incidents and respond to life events, a decrease in quality of life, and a decreased survival rate in 2. Materials and Methods older adults [26–28]. In older adults, falls are the second highest cause of -is study was cross-sectional in design. Community-based injury-related deaths worldwide [29] and a significant factor participants were recruited from the Saraphi District of which can lead to fracture, disability, and mortality [30]. Chiang Mai Province, -ailand. All participants gave written People aged 65 and over comprise 28–35% of falls each year, informed consent prior to inclusion. Ethical approval was a figure increasing to 32–42% in those over 70 years of age given by the Human Research Ethics Committee of Medi- [29]. Falls are often associated with increase in age and frailty cine Faculty of Chiang Mai University (187/2018). level [29]. -e annual fall rate in older adults in Southeast Asia was found to be 6–31% in China and 20% in Japan [29] while in -ailand, in over-60-year population, it was 26.1%. 2.1. Participants. A power of population analysis was cal- Also, fall-related health problems accounted for 97.2% in the culated from the total population of older adults in the community [31]. Saraphi District using an alpha level of 0.05, the power was Risk factors for falling are both intrinsic and extrinsic 95%, and the effect size was 0.5. -e total population in- [32]. Intrinsic factors were gender, age, muscle weakness, cluded 367 participants, 237 females (64.6%) and 130 males gait and balance impairment, vision impairment, foot or (35.4%), whose average age was 73.22 years±7.00. -e ankle disorders, history of falling, fear of falling, poly- sample group selection was done by stratified random pharmacy, and medical conditions [33–35]. Extrinsic factors sampling from each group according to the population were home hazards, environmental hazards, inappropriate proportion of ten villages in the Khua Mung Subdistrict walking aids or assistive devices, footwear, and clothing which meant a list of all older adults was sifted from a [33, 35]. Intrinsic factors caused a higher frequency of falls database made available by the community health center. than extrinsic factors, which led to greater levels of disability -e randomly selected population was chosen from a and mortality [36]. A previous study found that the fall rate population of 804 people, aged 65 years or older, according associated with medical factors varied from 33.3% in cases of to the following inclusion criteria: permanently residing in diabetes mellitus to 71.4% foot problems. Behavioural fac- these villages and willing to participant in this study. Ex- tors associated with a higher fall rate were underweight, clusion criteria were employed, following those advised in abnormal balance, and gait [37]. Fried’s frailty phenotype [9] of disability and the physio- Almost all studies assessed fall risk by mobility and logical profile assessment [39]. -ese included severe audio physical performance tests to assess function and balance and visual impairment or noncorrected audio and visual and timed up and go tests. Currently, the most frequently impairment, neurological disease (stroke and Parkinson’s used tools of physical physiological fall assessment are the disease), and cognitive impairment using the -ai Mental Balance Evaluation System Test (BESTest) [38] and the State Examination (TMSE) enacted [43] by community physiological profile assessment (PPA) [39] which indicate medicine staff. -e cut-point established for the TMSE risk factors associated with falling. A systematic review defines cognitive impairment is≤ 23 scores [43]. -e indi- reported that a multifactorial assessment of fall risk led to viduals excluded from the sample were a single older adult targeted intervention with efficient and effective strategies with a current psychiatric diagnosis, sixty-eight older adults for preventing falls [40]. A previous study indicated that with disabilities, and one older adult with a current stroke Journal of Aging Research 3 medial-lateral value, and records the value [39].Z-score was diagnosis. -ree eligible and randomized seniors refused to participate in the study. After exclusions, random sampling, the standard of PPA fall risk score [39]. and obtaining consent to the study, 367 older adults were recruited. 2.5.StatisticalAnalyses. -e Shapiro–Wilk test was used to check normal distribution. Demographic data are presented as descriptive statistics. -ese included percentiles for ages, 2.2.DataCollection. Questionnaire interviews were used to gender, number of comorbidities, polypharmacy, and frailty obtain demographic characteristics (age, sex, weight, height, score. One-way ANOVA analysis was used to compare fall and body mass index [44]), health history, medication, risk components with different frailty statuses. Multiple weight loss, and exhaustion questions. Weight and height linear regression analysis was also used to investigate the were measured on the assessment day. We also collected factors associated with fall risk. physical frailty phenotype, and physiological profile as- sessment (PPA) estimated 40 min per participant. 3. Results -e cohort included 367 community-dwelling older adults. 2.3.FrailtyPhenotypeAssessment. -is research used the five -e frailty group was 32 (8.7%), the prefrailty group was 282 frailty phenotype criteria listed by Fried et al. [9] to assess (76.8%), and the nonfrailty group was 53 (14.4%). -is study frailty. -e cut-off was 0 items (nonfrailty group), 1-2 scores found the average of number of comorbidities was (prefrailty group), and 3–5 scores (frailty group). -ese 0.83± 0.80 with a polypharmacy of 0.78± 0.81 and PPA fall criteria included five components: (1) unintentional weight 2 risk (Z-score) of 2.80± 1.47. Body mass index (kg/m ) was loss of >10 lb or ≥4.5 kg in the past year; (2) exhaustion 14.4% underweight, 39.0% normal weight, 36.5% over- evaluation using a two-question questionnaire which is weight, and 10.1% obese (Table 1). derived from the Center for Epidemiological Studies De- -is study found differences in correlation between PPA pression (CES-D) scale; interpretation was carried out using fall risk and frailty status in all components. -e visual a total score equal to or greater than two points [45]; (3) low contrast sensitivity components in the nonfrailty and the physical activity assessed by a modified international prefrailty groups were significantly higher than those in the physical activity questionnaire which calculates kilocalories frailty group. Proprioception components in the nonfrailty for one week (man> 383 and woman>270 kilocalories) [46]; and the prefrailty groups were significantly lower than those (4) slow gait assessed by the overall walking time of the in the frailty group. -e knee extension strength compo- distance of 4.5 m; the interpretation was based on sex and nents in the nonfrailty and the prefrailty groups were sig- height; (5) weakness measurement assessed with a grip nificantly higher than those in the frailty group. Hand strength dynamometer (Takei T. K. K. 5401 grip-D). Par- reaction time components in the nonfrailty and the pre- ticipants were measured in a standing position. Participants frailty groups were significantly lower than those in the were asked to use their dominant hand and exert the greatest frailty group. Posture sway components in the nonfrailty and effort, performing the test three times. -e highest possible the prefrailty groups were significantly lower than those in value was elected and recorded in the results. Interpretation the frailty group. -e PPA fall risks score (z-score) in the of the results utilized sex and body mass index. frailty group was significantly higher than those in the nonfrailty and the prefrailty groups (Table 2). Multiple linear regression analysis found that frailty 2.4. Physiological Profile Assessment. -e physiological status (B � 0.71,95% CI � 0.42, 1.01), age (B � 0.07, 95% profile assessment (PPA) has five component measures: CI � 0.04, 0.09), and polypharmacy (B � 0.36, 95% CI � 0.00, visual contrast sensitivity, proprioception, quadriceps 0.72) were associated with fall risk when adjusted by con- muscle strength, hand reaction time, and postural sway [39]. founding factors such as age, sex, number of comorbidities, Visual contrast sensitivity was used to assess vision using the polypharmacy, and body mass index (Table 3). Melbourne Edge Test. -e visual assessment is a test of the Figure 1 shows an average of overall fall risk score by visibility of the intensity of a circular dividing line. -e frailty status and age. -e nonfrailty group has an age av- resulting score is the value of the last image seen [39]. -e erage of 70.60 years and an average overall score fall risk of proprioception test was used to assess sensations using a 2.15. -e prefrailty group has an average age of 73.20 years lower limb matching test. -e interpretation of the evalu- and an average overall score for risk of falls of 2.70. -e ation uses the difference in the degree of sensation in the big frailty group has an age average of 79.31 years and an average toes [39]. Quadriceps muscle strength was assessed using a overall score for fall risk of 4.47. -e nonfrailty and prefrailty spring gauge (kilograms) [39]. Hand reaction time was groups were at a marked level of fall risk, but the frailty assessed using light as a stimulus and a finger depression of a group was at a highly marked level of fall risk. switch as the response (milliseconds) [39]. Postural sway was assessed using the mass aggregation swing. -e tested person 4. Discussion stands on a foam sheet for 30 seconds, with a belt with a perpendicular nib, which draws a graph on the graph paper -is study will add to the available evidence associated with on the table while balancing. It takes the calculated graph the relationship between frailty in older adults and fall risk. from the anterior–posterior value, multiplies it by the -e results of this study confirm our hypothesis that fall risk 4 Journal of Aging Research Table 1: Characteristics of study participants. Frailty status (N � 367) Characteristics Total p value Nonfrail (n � 53, 14.4%) Prefrail (n � 282, 76.8%) Frail (n � 32, 8.7%) Sex, n (%) 0.641 Male 130 (35.4) 20 (15.4) 101 (77.7) 9 (6.9) Female 237 (64.6) 33 (13.9) 181 (76.4) 23 (9.7) Age (years), mean± SD 73.22± 7.00 70.60± 4.52 73.02± 6.95 79.31± 7.46 <0.001 Number of comorbidities, mean± SD 0.83± 0.80 0.75± 0.89 0.82± 0.79 0.97± 0.74 0.494 Polypharmacy, mean± SD 0.78± 0.81 0.64± 0.78 0.78± 0 .82 0.97± 0.74 <0.001 2 b Body mass index (kg/m ), mean± SD 22.63± 3.86 22.50± 2.91 22.81± 3.90 21.24± 4.59 <0.001 Underweight (<18.5), n (%) 53 (14.4) 4 (7.5) 38 (71.7) 11 (20.8) Normal weight (18.5–22.9), n (%) 143 (39.0) 25 (17.5) 109 (76.2) 9 (6.3) Overweight (23.0–27.5), n (%) 134 (36.5) 21 (15.7) 103 (76.9) 10 (7.4) Obese (˃27.5), n (%) 37 (10.1) 3 (8.1) 32 (86.5) 2 (5.4) PPA fall risk (Z-score) (mean± SD) 2.80± 1.47 2.15± 1.02 2.70± 1.38 4.47± 1.65 <0.001 a b Chi-square test. One-way ANOVA test analysis. PPA � physiological profile assessment. Table 2: Fall risk score using the physiological profile assessment compared with frailty status in older adults. Component Frailty status Mean± SD 95% confidence interval p value Nonfrailty 17± 4.29 15.82, 18.18 b acbc Visual contrast sensitivity (dB) Prefrailty 16.10± 5.00 15.50, 16.68 <0.001 Frailty 8.44± 6.34 6.15, 10.72 Nonfrailty 2.29± 0.95 2.02, 2.55 b ac ab Proprioception (degree) Prefrailty 2.72± 1.49 2.54, 2.89 0.001 Frailty 3.53± 1.99 2.81, 4.25 Nonfrailty 19.07± 8.07 16.84, 21.29 b ac ab bc Knee extension strength (kg) Prefrailty 14.13± 6.32 13.39, 14.87 <0.001 Frailty 7.57± 4.40 5.98, 9.16 Nonfrailty 345.17± 94.99 318.99, 371.35 b ac ab Hand reaction time (ms) Prefrailty 395.51± 136.49 379.51, 411.51 <0.001 Frailty 472.69± 228.53 390.29, 555.08 Nonfrailty 1216.24± 840.43 984.59, 1447.89 2 b ac bc Sway path (mm ) Prefrailty 1367.63± 1258.65 1220.10, 1515.17 <0.001 Frailty 2435.25± 1951.94 1731.50, 3139.00 Nonfrailty 2.15± 1.02 1.87, 2.42) b ac ab bc PPA fall risk (Z-score) Prefrailty 2.70± 1.38 2.54, 2.86) <0.001 Frailty 4.47± 1.65 3.87, 5.06) ac: nonfrailty group compared with the frailty group; ab: nonfrailty group compared with the prefrailty group; bc: prefrailty group compared with the frailty group; PPA � physiological profile assessment. -e first set of results found that the frailty group had a Table 3: Factors associated with fall risk. significantly higher overall fall risk score when compared to Linear regression analysis both the nonfrailty and prefrailty groups. -is is related to Independent variable p value B (SE) 95% CI the level of frailty being related to the degeneration of ∗∗ physical and cognitive factors, conferring both physical Frailty status 0.71 (0.14) (0.42, 1.01) <0.001 ∗∗ Age 0.07 (0.01) (0.04, 0.09) <0.001 frailty and cognitive frailty [23, 27]. Sex 0.26 (0.14) (−0.01, 0.54) 0.06 Our study about fall risk had five components. First, Number of comorbidities −0.28 (0.18) (−0.65, 0.07) 0.12 these study results found the frail group had poorer vision Polypharmacy 0.36 (0.18) (0.00, 0.72) 0.04 than the nonfrailty group which was consistent with pre- Body mass index −0.01 (0.01) (−0.05, 0.02) 0.42 vious studies that found poor vision function in the frailty ∗∗ ∗ Significance at p-value< 0.001. Significance at p value � 0.05. group caused falls in older adults [47–49]. -is may be explained by the aging process leading to a change in fo- differs between each frailty status. Individuals classified as cusing in the eyes leading to difficulty in focusing on distance or objects because of low contrast sensitivity [49, 50]. Frailty frail are at a greater risk of falling and then comes the prefrail and nonfrail groups. -e study found that individuals is also related to the concept of geriatric syndrome and age- classified as prefrail differ from those classified as nonfrail in associated reduction of physiological reserves [1–3, 51]. three aspects of physiology, which is interesting new Second, the frailty group had impaired proprioception when evidence. compared with the nonfrail group. Likewise, a previous Journal of Aging Research 5 study are based on new knowledge, reflecting that the sig- (F) Very marked naling changes in the brain were the first changes to occur 3 before the frail condition became identifiable [53]. Likewise, (P) Marked the prefrail group had slower reaction times in comparison (N) to the nonfrail group. -is reaction time indicates a decline Moderate in cognitive function in the prefrail group showing a decline in brain function, again before entering the status of frailty. Mild -e members of the prefrail group also had lower muscle strength in comparison to the nonfrail group [59]. A pre- Low vious study adds weight to this finding as it also found poor –1 muscle strength and physical activity in a prefrail group Very low when compared with nonfrail individuals [56]. In addition, a previous study found a reduction in mitochondrial genes in 30 40 50 60 70 80 90 100 muscles which led to a reduction in muscle function [61]. Age (years) -e results of this study show that physiological changes before entering the frailty phase are a decrease in brain Fall risk score function and decrease in muscle strength which is inter- Normal population esting knowledge because it can be used as a way to prevent frailty in the future. Figure 1: Overall fall risk score by frailty status and age using the fall risk calculator by NeuRA FallScreen . N � nonfrail group On the other hand, we found no differences in fall risk for (Z-score � 2.15); P � prefrail group (Z-score � 2.70); F � frail group two components between the nonfrailty and the prefrailty (Z-score � 4.47). groups. -ese were vision and sway which may have occurred because the prefrailty group was nearly the same age as the study found the frailty group had greater impaired propri- nonfrailty group, and vision may be more closely related to oception than older adults not classified as frail [52]. Frailty is age than frailty. Vision is the main component of postural associated with a decline and change in physiology including control that affects postural sway [62, 63]. -us, no difference the central nervous system (CNS) that serves to send sen- in vision results in no postural sway differences for both sations to the joints. -is may explain this result as propri- statuses. In addition, we found the fall risk components oception has cumulative neural input from mechanoreceptors proprioception and reaction time were no different between such as muscular, articular, and cutaneous receptors [53]. the frailty group and the prefrailty group. -ose in the -ird, the frailty group had a more decreased muscle strength prefrailty group are likely to develop changes in physiological than the nonfrailty group which could be due to decreased functions and progress to the frailty status. Sarcopenia is muscle size and muscle mass from muscle fiber changes (IIA prevalent in the frailty group affecting neuromuscular and IIB) producing lower strength in the frailty group [54]. changes that, together with those of greater age in the pre- Another study found a weakness of lower limbs was asso- frailty group, will be related to loss of muscle mass and size ciated with the frailty group [55]. In addition, muscle which affect proprioception and reaction time [64]. weakness was found to be associated with the frailty group of In addition, we found frailty status, age, and poly- older adults in community [56]. Fourth, this study found that pharmacy were factors associated with fall risk. -e meta- the frailty group had a longer reaction time than the nonfrailty analysis found frailty was a risk factor for falling in com- group which had not been reported in other studies. -e munity-dwelling older adults [15]. A prospective cohort explanation for this may be due to the reaction time being study found a correlation between age and fall rate [32, 65]. sensory in nature, responding to stimuli which reflected the A review of relevant literature showed polypharmacy to have speed impulses are passed to the central nervous system [57]. a variable link to falling in older adults [66]. However an- Reaction time in this study was assessed by hand reaction time other, nationwide nested case-control study found a direct that represents cognitive processes of the brain [58]. Similarly, relationship between polypharmacy and injurious falls [67]. frailty is associated with cognitive impairment which could -is is probably the first study to separate the physiology also go some way to explaining the increase in the length of of each aspect in assessing falls. However, our research the reaction time [59]. Finally, this study found the frailty showed some limitations that may have impact on the re- group has a greater postural sway than the nonfrailty group. sults. -e first limitation of this study is that it was cross- Frailty is associated with reduced musculoskeletal and brain sectional in nature. Second, the subgroup of frail individuals activity and both systems work together in coordinating was too small. Finally, this study measured only the fall risk posture stability. -is study found the frailty group had a using physical performance assessment and there are many greater impairment of balance and gait [60] -is therefore led others factors associated with fall risk; therefore, in a future to a high fall risk score (PPA Z-score) in the frailty group study, we would consider a prospective cohort design study. which was significantly different from the nonfrailty group. In the second part of the study, we found the prefrail 5. Conclusions group to have proprioception differences compared with the nonfrail group. Basically, the prefrail group had a poorer -is study found five different fall risk components asso- proprioception than the nonfrail group. -e results of this ciated with the frailty status. -e frailty group had the better Fall risk score (SD) worse 6 Journal of Aging Research in early-old community dwellers of -ailand,” International highest fall risk score. In addition, the prefrail group was JournalofEnvironmentalResearchandPublicHealth, vol. 16, susceptible to changes related to physiology as regards no. 18, 2019. proprioception, reaction time, and change in muscle [8] E. Dent, P. Kowal, and E. O. Hoogendijk, “Frailty measure- strength, all of which were poorer than those in individuals ment in research and clinical practice: a review,” European in the nonfrail group. In addition, the frailty status, age, and Journal of Internal Medicine, vol. 31, pp. 3–10, 2016. polypharmacy were factors associated with fall risk which [9] L. P. Fried, C. M. Tangen, J. Walston et al., “Frailty in older can be used to predict the risk of falling among older adults adults: evidence for a phenotype,” eJournalsofGerontology in the community. -us, the older adults in the community Series A: Biological Sciences and Medical Sciences, vol. 56, should be screened for level of frailty and fall risk to reduce no. 3, pp. M146–M157, 2001. and prevent impact on disability and mortality. -e results [10] M. Roppplo, A. Mulasso, R. J. Gobbens, C. O. Mosso, and of our study can serve as a reference for specific intervention E. Rabaglietti, “A comparison between uni-and multidi- in the prevention of fall risk in community-dwelling older mensional frailty measures: prevalence, functional status, and relationships with disability,” Clinical Interventions in Aging, adults and also inform the assessment of other factors vol. 10, p. 1669, 2015. among community-dwelling older adults. [11] G. Kojima, “Frailty as a predictor of future falls among community-dwelling older people: a systematic review and Data Availability meta-analysis,” Journal of the American Medical Directors Association, vol. 16, no. 12, pp. 1027–1033, 2015. -e data that support the findings of this study are available [12] C. Curcio, G. Henao, and F. Gomez, “Frailty among rural from the corresponding author upon reasonable request. elderly adults,” BMC Geriatrics, vol. 14, no. 2, 2014. [13] J. R. Fhon, R. A. Rodrigues, W. F. Neira, V. M. Huayta, and Conflicts of Interest M. L. Robazzi, “Fall and its association with the frailty syn- drome in the elderly: systematic review with meta-analysis,” -e authors declared no conflicts of interest with respect to Revista da Escola de Enfermagem da USP, vol. 50, no. 6, this research, authorship, and/or publication of this article. pp. 1003–1010, 2016. [14] E. Y. Shim, S. H. Ma, S. H. Hong et al., “Correlation between Acknowledgments frailty level and adverse health-related outcomes of commu- nity-dwelling elderly, one year retrospective study,” Korean -e authors thank the Faculty of Medicine and Faculty of Journal of Family Medicine, vol. 32, no. 4, pp. 249–256, 2011. Associated Medical Sciences, Chiang Mai University, [15] M.-H. Cheng and S.-F. Chang, “Frailty as a risk factor for falls -ailand, for providing support. -e authors also thank the among community dwelling people: evidence from a meta- cohort of older adults who participated in this study. -e analysis,” Journal of Nursing Scholarship, vol. 49, no. 5, pp. 529–536, 2017. authors wish to acknowledge the funding from the Faculty of [16] R. Samper-Ternent, A. Karmarkar, J. Graham, T. Reistetter, Medicine, Chiang Mai University, under Grant no. 124/ and K. Ottenbacher, “Frailty as a predictor of falls in older Mexican Americans,” Journal of Aging and Health, vol. 24, no. 4, pp. 641–653, 2012. References [17] A. Mulasso, M. Roppolo, R. J. Gobbens, and E. Rabaglietti, “Mobility, balance and frailty in community-dwelling older [1] Q.-L. Xue, “-e frailty syndrome: definition and natural adults: what is the best 1-year predictor of falls?”Geriatrics& history,”ClinicsinGeriatricMedicine, vol. 27, no. 1, pp. 1–15, GerontologyInternational, vol. 17, no. 10, pp. 1463–1469, 2017. [18] J. M. VanSwearingen, K. A. Paschal, P. Bonino, and [2] A. Clegg, J. Young, S. Iliffe, M. O. Rikkert, and K. Rockwood, T.-W. Chen, “Assessing recurrent fall risk of community- “Frailty in elderly people,” e Lancet, vol. 381, no. 9868, dwelling, frail older veterans using specific tests of mobility pp. 752–762, 2013. and the physical performance test of function,” eJournalsof [3] X. Chen, G. Mao, and S. X. Leng, “Frailty syndrome: an GerontologySeriesA:BiologicalSciencesandMedicalSciences, overview,” Clinical Interventions in Aging, vol. 19, no. 9, vol. 53A, no. 6, pp. M457–M464, 1998. pp. 433–441, 2014. [19] M. J Ohler, C. S Wendel, R. Taylor-Piliae, N. Toosizadeh, and [4] L. P. Fried, L. Ferrucci, J. Darer, J. D. Williamson, and B. Najafi, “Motor performance and physical activity as pre- G. Anderson, “Untangling the concepts of disability, frailty, dictors of prospective falls in community-dwelling older and comorbidity: implications for improved targeting and adults by frailty level: application of wearable technology,” care,” Journal of Gerontology Series A, Biological Sciences and Gerontology, vol. 62, pp. 654–664, 2016. Medical Sciences, vol. 59, no. 3, 2004. [20] T. Silveira, M. S. Pegorari, S. S. D. Castro, G. Ruas, [5] D. D. Siriwardhana, S. Hardoon, G. Rait, M. C. Weerasinghe, S. G. Novais-Shimano, and L. J. Patrizzi, “Association of falls, and K. R. Walters, “Prevalence of frailty and pre-frailty among community-dwelling older adults in low-income and middle- fear of falling, handgrip strength and gait speed with frailty levels in the community elderly,” Medicina (Ribeirao Preto. income countries: a systematic review and meta-analysis,” BMJ Open, vol. 8, Article ID e018195, 2018. Online), vol. 48, no. 6, pp. 549–556, 2015. [21] C. Cardon, M. Verbecqa, M. Loustaub et al., “Predicting falls [6] S. Morarit, K. Taypa, W. Boonyod, and P. Siviroj, “Frailty phenotype characteristics of Community-dwelling frail el- with the cognitive timed up-and-go dual task in frail older patients,” Annals of Physical and Rehabilitation Medicine, derly people in a sub-district,” Naresuan Phayao Journal, vol. 11, no. 2, pp. 56–60, 2018. vol. 60, pp. 83–86, 2017. [22] P. R. Brustio, D. Magistro, M. Zecca, M. E. Liubicich, and [7] W. Semmarath, M. Seesen, S. Yodkeeree et al., “-e associ- ation between frailty indicators and blood-based biomarkers E. Rabaglietti, “Fear of falling and activities of daily living Journal of Aging Research 7 function: mediation effect of dual-task ability,” Aging & [39] S. R. Lord, H. B. Menz, and A. Tiedemann, “A physiological Mental Health, vol. 22, no. 6, pp. 856–861, 2018. profile approach to falls risk assessment and prevention,” [23] M. Roppplo, A. Mulasso, and E. Rabaglietti, “Cognitive frailty Physical erapy, vol. 83, no. 3, pp. 237–252, 2003. in Italian community-dwelling older adults: prevalence rate [40] S. Gates, J. D. Fisher, M. W. Cooke, Y. H. Carter, and and its association with disability,” e Journal of Nutrition, S. E. Lamb, “Multifactorial assessment and targeted inter- Health and Aging, vol. 21, no. 6, pp. 631–636, 2017. vention for preventing falls and injuries among older people [24] O. J. de Vries, G. M. E. E. Peeters, P. Lips, and D. J. H. Deeg, in community and emergency care settings: systematic review “Does frailty predict increased risk of falls and fractures? A and meta-analysis,” BMJ, vol. 336, no. 7636, pp. 130–133, prospective population-based study,” Osteoporosis Interna- 2008. tional, vol. 24, no. 9, pp. 2397–2403, 2013. [41] M. C. Robertson and L. D. Gillespie, “Fall prevention in [25] K. E. Ensrud, S. K. Ewing, B. C. Taylor et al., “Frailty and risk community-dwelling older adults,” JAMA, vol. 309, no. 13, of falls, fracture, and mortality in older women: the study of pp. 1406-1407, 2013. osteoporotic fractures,” e Journals of Gerontology Series A: [42] E. A. Phelan and K. Ritchey, “Fall prevention in community- Biological Sciences and Medical Sciences, vol. 62, no. 7, dwelling older adults. Annals of internal medicine,”Annalsof pp. 744–751, 2007. Internal Medicine, vol. 169, no. 11, 2018. [26] C. de Labra, A. Maseda, L. Lorenzo-Lopez et al., “Social factors [43] S. Kanjananopinit, S. Charoensak, and T. Keawpornsawan, and quality of life aspects on frailty syndrome in community- “-e study of psychometric properties of cognistat -ai version,” Journal of the Psychiatrist Association of ailand, dwelling older adults: the verisaude study,” BMC Geriatrics, vol. 18, no. 1, p. 66, 2018. vol. 59, no. 4, pp. 409–418, 2014. [44] T. Liabsuetrakul, “Southern soil-transmitted helminths [27] A. Mulasso, M. Roppolo, and E. Rabaglietti, “Physical frailty, disability, and dynamics in health perceptions: a preliminary and maternal health working group, “is international or mediation model,” Clinical Interventions in Aging, vol. 11, Asian criteria-based body mass index associated with pp. 275–8, 2016. maternal anaemia, low birthweight, and preterm births [28] S.-F. Chang and P.-L. Lin, “Frail phenotype and mortality among -ai population? An observational study,” Journal prediction: a systematic review and meta-analysis of pro- Health Population Nutrition, vol. 29, no. 3, pp. 218–228, spective cohort studies,” International Journal of Nursing 2011. [45] J. G. Orme, J. Reis, and E. J. Herz, “Factorial and discriminant Studies, vol. 52, no. 8, pp. 1362–1374, 2015. [29] World Health Organization, Epidemiology of Falls, “WHO validity of the center for epidemiological studies depression (CES-D) scale,” Journal of Clinical Psychology, vol. 42, no. 1, GlobalReportonFallsPreventioninOlderAge, World Health Organization Press, Geneva, Switzerland, 2008. pp. 28–33, 1986. [30] F. Bloch, M. -ibaud, B. Dugu e, ´ C. Breque, ` A. Rigaud, and [46] P. Rattanawiwatpong, A. Khunphasee, C. Pongurgsorn, and G. Kemoun, “Episodes of falling among elderly people: a P. Intarakamhang, “Validity and reliability of the -ai version systematic review and meta-analysis of social and demo- of short format international physical activity questionnaire graphic pre-disposing characteristics,” Clinics, vol. 65, no. 9, (IPAQ),” Journal of ai Rehabilitation Medicine, vol. 16, pp. 895–903, 2010. pp. 147–160, 2006. [31] P. Kuhirunyaratn, P. Prasomrak, and B. Jindawong, “Factors [47] B. E. Klein, R. Klein, M. D. Knudtson, and K. E. Lee, “Re- related to falls among community dwelling elderly,” e lationship of measures of frailty to visual function: the beaver dam eye study,” Transactions of the American Ophthalmo- Southeast Asian Journal of Tropical Medicine and Public Health, vol. 44, no. 5, pp. 906–915, 2013. logical Society, vol. 101, pp. 191–199, 2003. [32] S. I. Sharif, A. B. Al-Harbi, A. M. Al-Shihabi, D. S. Al-Daour, [48] A. E. M. Liljas, L. A. Carvalho, E. Papachristou et al., “Self- and R. S. Sharif, “Falls in the elderly: assessment of prevalence reported vision impairment and incident prefrailty and frailty and risk factors,”PharmacyPractice, vol. 16, no. 3, p. 1206, 2018. in English community-dwelling older adults: findings from a [33] E. Kwan, S. Straus, and J. Holroyd-Leduc, Risk factors for falls 4-year follow-up study,” Journal of Epidemiology and Com- in the elderly, in Medication-elated Falls in Older People, A. munity Health, vol. 71, no. 11, pp. 1053–1058, 2017. [49] D. K. Y. Miu, “Visual impairment contributes to frailty among Huang, and L. Mallet, et al., Adis, Cham, Switzerland, 2016. [34] Y. Amatullah, S. B. Sastradimaja, and L. Dwipa, “Intrinsic risk a group of healthy community dwelling older population,” Journal of Geriatric Medicine and Gerontology, vol. 4, no. 2, factors of falls in elderly,”AltheaMedicalJournal, vol. 3, no. 3, 2016. 2018. [50] J. M. Wood, P. Lacherez, A. A. Black, M. H. Cole, [35] World Health Organization, What Are the Main Risk Factors for Falls Amongst Older People and What Are the Most Ef- M. Y. Boon, and G. K. Kerr, “Risk of falls, injurious falls, and fective Interventions to Prevent ese Falls?”, World Health other injuries resulting from visual impairment among older Organization, Geneva, Switzerland, 2004. adults with age-related macular degeneration,” Investigative [36] A. Bueno-Cavanillas, F. Padilla-Ruiz, J. J. Jimenez-Mole ´ on, ´ Opthalmology&VisualScience, vol. 52, no. 8, pp. 5088–5092, C. A. Peinado-Alonso, and R. Galvez-Vargas, ´ “Risk factors in 2011. falls among the elderly according to extrinsic and intrinsic [51] K. Miyamura, J. R. S. Fhon, de A. B. Alexandre, W. F. N Luis, C. P. S. Cristina, and R. A. P. Rodrigues, “Frailty syndrome precipitating causes,” European Journal Of Epidemiology, vol. 16, no. 9, pp. 849–859, 2000. and cognitive impairment in older adults: systematic review of [37] S. Patil, S. Suryanarayana, N. Shivraj, N. Murthy, and the literature,” Revista Latino-Americana de Enfermagem, R. Dinesh, “Risk factors for falls among elderly: a community- vol. 27, pp. 1–12, 2019. based study,” International Journal of Health & Allied Sci- [52] M. L. Fritz, “Neuromuscular aging and frailty,” Dissertation, ences, vol. 4, no. 3, p. 135, 2015. Colorado State University, Department of Health and Exercise [38] F. B. Horak, D. M. Wrisley, and J. Frank, “-e balance Science, Fort Collins, Colorado, 2016, https://mountainscholar. evaluation systems test (BESTest) to differentiate balance org/bitstream/handle/10217/176604/Fritz_colostate_0053A_ deficits,”Physical erapy, vol. 89, no. 5, pp. 484–498, 2009. 13632.pdf?sequence=1&isAllowed=y. 8 Journal of Aging Research [53] A. S. Buchman, L. Yu, R. S. Wilson et al., “Brain pathology contributes to simultaneous change in physical frailty and cognition in old age,” e Journals of Gerontology: Series A, vol. 69, no. 12, pp. 1536–1544, 2014. [54] D. Wilson, T. Jackson, E. Sapey, and M. L Janet, “Frailty and sarcopenia: the potential role of an aged immune system,” Ageing Research Reviews, vol. 36, pp. 1–10, 2017. [55] E. Gielen, S. Verschueren, T. W. O’Neill et al., “Musculo- skeletal frailty: a geriatric syndrome at the core of fracture occurrence in older age,” Calcified Tissue International, vol. 91, no. 3, pp. 161–177, 2012. [56] F. S. Batista, G. A. D. O. Gomes, A. L. Neri et al., “Relationship between lower-limb muscle strength and frailty among elderly people,” Sao Paulo Medical Journal, vol. 130, no. 2, pp. 102– 108, 2012. [57] R. D. Seidler, J. A. Bernard, T. B. Burutolu et al., “Motor control and aging: links to age-related brain structural, functional, and biochemical effects,” Neuroscience & Bio- behavioral Reviews, vol. 34, no. 5, pp. 721–733, 2010. [58] Y. Shub, I. E. Ashkenazi, and A. Reinberg, “Differences be- tween left- and right-hand reaction time rhythms: indications of shifts in strategies of human brain activity,”CognitiveBrain Research, vol. 6, no. 2, pp. 141–146, 1997. [59] L. Sargent, M. Nalls, A. Starkweather et al., “Shared biological pathways for frailty and cognitive impairment: a systematic review,” Ageing Research Reviews, vol. 47, pp. 149–158, 2018. [60] H. Makizako, T. Kubozono, R. Kiyama et al., “Associations of social frailty with loss of muscle mass and muscle weakness among community-dwelling older adults,” Geriatrics & Gerontology International, vol. 19, no. 1, pp. 76–80, 2019. [61] P. A. Andreux, M. P. J. van Diemen, M. R. Heezen et al., “Mitochondrial function is impaired in the skeletal muscle of pre-frail elderly,” Scientific Reports, vol. 8, no. 8548, pp. 1–12, [62] E. E. Hansson, A. Beckman, and A. Hakansson, ˚ “Effect of vision, proprioception, and the position of the vestibular organ on postural sway,” Acta Oto-Laryngologica, vol. 130, no. 12, pp. 1358–1363, 2010. [63] M. Tomomitsu, A. Alonso, E. Morimoto, T. Bobbio, and J. Greve, “Static and dynamic postural control in low-vision and normal-vision adults,”Clinics, vol. 68, no. 4, pp. 517–521, [64] B. C. Clark, “Neuromuscular changes with aging and sar- copenia,” eJournalofFrailty&Aging, vol. 8, pp. 7–9, 2019. [65] A. F. Ambrose, G. Paul, and J. M. Hausdorff, “Risk factors for falls among older adults: a review of the literature,”Maturitas, vol. 75, no. 1, pp. 51–61, 2013. [66] T. Hammond and A. Wilson, “Polypharmacy and falls in the elderly: a literature review,” Nursing and Midwifery Studies, vol. 2, no. 2, pp. 171–175, 2013. [67] L. Morin, A. Calderon Larrañaga, A.-K. Welmer, D. Rizzuto, J. Wastesson, and K. Johnell, “Polypharmacy and injurious falls in older adults: a nationwide nested case-control study,” Clinical Epidemiology, vol. 11, pp. 483–493, 2019. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Aging Research Hindawi Publishing Corporation

Physical Frailty and Fall Risk in Community-Dwelling Older Adults: A Cross-Sectional Study

Loading next page...
 
/lp/hindawi-publishing-corporation/physical-frailty-and-fall-risk-in-community-dwelling-older-adults-a-BX9ekgxx9J

References

References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.

Publisher
Hindawi Publishing Corporation
Copyright
Copyright © 2020 Jiraporn Chittrakul et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
ISSN
2090-2204
eISSN
2090-2212
DOI
10.1155/2020/3964973
Publisher site
See Article on Publisher Site

Abstract

Hindawi Journal of Aging Research Volume 2020, Article ID 3964973, 8 pages https://doi.org/10.1155/2020/3964973 ResearchArticle Physical Frailty and Fall Risk in Community-Dwelling Older Adults: A Cross-Sectional Study 1 1 2 1 Jiraporn Chittrakul, Penprapa Siviroj , Somporn Sungkarat, and Ratana Sapbamrer Department of Community Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, ailand DepartmentofPhysical erapy,FacultyofAssociatedMedicalSciences,ChiangMaiUniversity,ChiangMai 50200, ailand Correspondence should be addressed to Penprapa Siviroj; psiviroj@gmail.com Received 29 October 2019; Revised 25 March 2020; Accepted 13 April 2020; Published 4 July 2020 Academic Editor: Jean-Francois Grosset Copyright © 2020 Jiraporn Chittrakul et al. -is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Introduction. Frailty is a condition in older adults with decreased physical and cognitive performance that can affect health outcomes associated with fracture, disability, and falls. -e aim of this study was to compare fall risk with different physical frailty statuses and investigate factors associated with fall risk in community-dwelling older adults. Methods. -e population studied included 367 older adults (mean age � 73.2 years± 7.0; 237 females (64.6%) and 130 males (35.4%)) who live in Chiang Mai, -ailand. -is study was of cross-sectional design. Fried’s phenotype was used to screen the physical frailty status. -e physiological profile assessment (PPA) was used to screen for fall risk. One-way ANOVA analysis was used to compare the fall risk between the different levels of frailty status. Linear regression analysis was used to assess the association between frailty status and fall risk.Results. -e prevalence of the frailty group was 8.7% and that of the prefrailty group was 76.8%. -e three statuses of frailty identified were found to have different levels of risk of falling. -e frailty group had a higher fall risk than the nonfrailty group and the prefrailty group. In addition, the nonfrailty group had a lower fall risk than the prefrailty group.Conclusion. -e frailty group had the highest fall risk in this cohort of older adults living in a community-dwelling facility. -erefore, it is important to assess the frailty status among older adults as it can be a predictor for fall risk. -is assessment will therefore lead to a reduction in the rate of disability and death in the community. and 55.2% in the prefrailty group [5]. Meanwhile, in -ailand, 1. Introduction the frailty prevalence in the community-dwelling older adults Frailty involves the concepts associated with the deterio- was found to range from 15.0% to 17.2% [6, 7]. Currently, ration of the body related to the aging process. It encom- there are many methods used to assess frailty, of which Fried’s passes the decline in physiology and biological syndromes of frailty phenotype index is the most commonly used and decreased reserve and resistance to stressors that lead to currently has the highest levels of validity and reliability. It is poor health outcomes such as loss of physical and mental mainly used as a unidimensional frailty index and can be used for both clinical and community assessment [8–10]. -is performance [1–3]. -ree clinical conditions are commonly used in the identification and classification of vulnerable index has five components consisting of unintentional weight older adults, specifically, comorbidity, frailty, and disability, loss, self-reported exhaustion, weakness (grip strength), slow which can lead to multiple adverse outcomes such as hos- walking speed, and low physical activity. Scores in three or pitalization and premature mortality in an aging population more areas indicate the frailty group and in one to two areas [4]. Nonetheless, there is no consensus regarding the indicate the prefrailty group, and if there are no scores, the prevalence rate of frailty across countries. In low-income classification is the nonfrailty group [8, 9]. and middle-income countries, there are indicators that the In literature, a systematic review and meta-analysis frailty prevalence in older adults is 12.7% in the frailty group showed frailty can predict future falls in community- 2 Journal of Aging Research treatment of fall prevention in older adults should include an dwelling older adults [11]. Previous studies indicated that a major outcome of frailty is falling [12–15]. Frailty and exercise program, home-safe interventions, vitamin D supplements, and multifactorial intervention [41]. Physio- prefrailty are significant predictors of falls in older adults, and prefrail individuals have 1.36 higher odds of falling [16]. logical profile assessment is a multifactorial assessment of In addition, frailty causes decreased balance and mobility in fall risk which is used to evaluate a complete physiological older adults predicting falls within 12 months [17, 18]. assessment of fall risks in the older adults [39]. However, According to the current knowledge (2016), frailty was there is currently no study assessing fall risk among older associated with motor performance and the risk of falls in adults with frailty using PPA. older adults [19]. Other previous studies reported that the -erefore, this study was designed to investigate any association between all physiological aspects and falls in frail older adults who had low muscle strength, weight loss, decreased gait speed, and high-level fear of falling were older adults. -e objective was to increase the level of in- formation regarding the association between physical frailty associated with frailty and falls [20, 21]. Meanwhile, fear of falling in older adults was related with low dual-task per- status and difference in fall risk. Initial screening or as- sessment of fall risk in the older adults has been shown to formance and reduced activity of daily living function [22]. In addition, there are differences in cognitive frailty between prevent and reduce the risk of falling in a short space of time nonfrailty and prefrailty groups [23]. A prospective pop- [42]. -e aim of this study was to compare fall risk with ulation-based study found that frailty and psychological and different physical frailty statuses to understand more fully cognitive markers were associated with fall and fracture, the different risk of falling in relation to each aspect of increased recurrent falls and fractures, and decreased mo- physiology at each level of frailty in older adults. -is study bility [24, 25]. Likewise, frailty was associated with an in- also investigated factors associated with fall risk in com- munity-dwelling older adults. creasing health perception level, a decline in the ability to adjust to serious incidents and respond to life events, a decrease in quality of life, and a decreased survival rate in 2. Materials and Methods older adults [26–28]. In older adults, falls are the second highest cause of -is study was cross-sectional in design. Community-based injury-related deaths worldwide [29] and a significant factor participants were recruited from the Saraphi District of which can lead to fracture, disability, and mortality [30]. Chiang Mai Province, -ailand. All participants gave written People aged 65 and over comprise 28–35% of falls each year, informed consent prior to inclusion. Ethical approval was a figure increasing to 32–42% in those over 70 years of age given by the Human Research Ethics Committee of Medi- [29]. Falls are often associated with increase in age and frailty cine Faculty of Chiang Mai University (187/2018). level [29]. -e annual fall rate in older adults in Southeast Asia was found to be 6–31% in China and 20% in Japan [29] while in -ailand, in over-60-year population, it was 26.1%. 2.1. Participants. A power of population analysis was cal- Also, fall-related health problems accounted for 97.2% in the culated from the total population of older adults in the community [31]. Saraphi District using an alpha level of 0.05, the power was Risk factors for falling are both intrinsic and extrinsic 95%, and the effect size was 0.5. -e total population in- [32]. Intrinsic factors were gender, age, muscle weakness, cluded 367 participants, 237 females (64.6%) and 130 males gait and balance impairment, vision impairment, foot or (35.4%), whose average age was 73.22 years±7.00. -e ankle disorders, history of falling, fear of falling, poly- sample group selection was done by stratified random pharmacy, and medical conditions [33–35]. Extrinsic factors sampling from each group according to the population were home hazards, environmental hazards, inappropriate proportion of ten villages in the Khua Mung Subdistrict walking aids or assistive devices, footwear, and clothing which meant a list of all older adults was sifted from a [33, 35]. Intrinsic factors caused a higher frequency of falls database made available by the community health center. than extrinsic factors, which led to greater levels of disability -e randomly selected population was chosen from a and mortality [36]. A previous study found that the fall rate population of 804 people, aged 65 years or older, according associated with medical factors varied from 33.3% in cases of to the following inclusion criteria: permanently residing in diabetes mellitus to 71.4% foot problems. Behavioural fac- these villages and willing to participant in this study. Ex- tors associated with a higher fall rate were underweight, clusion criteria were employed, following those advised in abnormal balance, and gait [37]. Fried’s frailty phenotype [9] of disability and the physio- Almost all studies assessed fall risk by mobility and logical profile assessment [39]. -ese included severe audio physical performance tests to assess function and balance and visual impairment or noncorrected audio and visual and timed up and go tests. Currently, the most frequently impairment, neurological disease (stroke and Parkinson’s used tools of physical physiological fall assessment are the disease), and cognitive impairment using the -ai Mental Balance Evaluation System Test (BESTest) [38] and the State Examination (TMSE) enacted [43] by community physiological profile assessment (PPA) [39] which indicate medicine staff. -e cut-point established for the TMSE risk factors associated with falling. A systematic review defines cognitive impairment is≤ 23 scores [43]. -e indi- reported that a multifactorial assessment of fall risk led to viduals excluded from the sample were a single older adult targeted intervention with efficient and effective strategies with a current psychiatric diagnosis, sixty-eight older adults for preventing falls [40]. A previous study indicated that with disabilities, and one older adult with a current stroke Journal of Aging Research 3 medial-lateral value, and records the value [39].Z-score was diagnosis. -ree eligible and randomized seniors refused to participate in the study. After exclusions, random sampling, the standard of PPA fall risk score [39]. and obtaining consent to the study, 367 older adults were recruited. 2.5.StatisticalAnalyses. -e Shapiro–Wilk test was used to check normal distribution. Demographic data are presented as descriptive statistics. -ese included percentiles for ages, 2.2.DataCollection. Questionnaire interviews were used to gender, number of comorbidities, polypharmacy, and frailty obtain demographic characteristics (age, sex, weight, height, score. One-way ANOVA analysis was used to compare fall and body mass index [44]), health history, medication, risk components with different frailty statuses. Multiple weight loss, and exhaustion questions. Weight and height linear regression analysis was also used to investigate the were measured on the assessment day. We also collected factors associated with fall risk. physical frailty phenotype, and physiological profile as- sessment (PPA) estimated 40 min per participant. 3. Results -e cohort included 367 community-dwelling older adults. 2.3.FrailtyPhenotypeAssessment. -is research used the five -e frailty group was 32 (8.7%), the prefrailty group was 282 frailty phenotype criteria listed by Fried et al. [9] to assess (76.8%), and the nonfrailty group was 53 (14.4%). -is study frailty. -e cut-off was 0 items (nonfrailty group), 1-2 scores found the average of number of comorbidities was (prefrailty group), and 3–5 scores (frailty group). -ese 0.83± 0.80 with a polypharmacy of 0.78± 0.81 and PPA fall criteria included five components: (1) unintentional weight 2 risk (Z-score) of 2.80± 1.47. Body mass index (kg/m ) was loss of >10 lb or ≥4.5 kg in the past year; (2) exhaustion 14.4% underweight, 39.0% normal weight, 36.5% over- evaluation using a two-question questionnaire which is weight, and 10.1% obese (Table 1). derived from the Center for Epidemiological Studies De- -is study found differences in correlation between PPA pression (CES-D) scale; interpretation was carried out using fall risk and frailty status in all components. -e visual a total score equal to or greater than two points [45]; (3) low contrast sensitivity components in the nonfrailty and the physical activity assessed by a modified international prefrailty groups were significantly higher than those in the physical activity questionnaire which calculates kilocalories frailty group. Proprioception components in the nonfrailty for one week (man> 383 and woman>270 kilocalories) [46]; and the prefrailty groups were significantly lower than those (4) slow gait assessed by the overall walking time of the in the frailty group. -e knee extension strength compo- distance of 4.5 m; the interpretation was based on sex and nents in the nonfrailty and the prefrailty groups were sig- height; (5) weakness measurement assessed with a grip nificantly higher than those in the frailty group. Hand strength dynamometer (Takei T. K. K. 5401 grip-D). Par- reaction time components in the nonfrailty and the pre- ticipants were measured in a standing position. Participants frailty groups were significantly lower than those in the were asked to use their dominant hand and exert the greatest frailty group. Posture sway components in the nonfrailty and effort, performing the test three times. -e highest possible the prefrailty groups were significantly lower than those in value was elected and recorded in the results. Interpretation the frailty group. -e PPA fall risks score (z-score) in the of the results utilized sex and body mass index. frailty group was significantly higher than those in the nonfrailty and the prefrailty groups (Table 2). Multiple linear regression analysis found that frailty 2.4. Physiological Profile Assessment. -e physiological status (B � 0.71,95% CI � 0.42, 1.01), age (B � 0.07, 95% profile assessment (PPA) has five component measures: CI � 0.04, 0.09), and polypharmacy (B � 0.36, 95% CI � 0.00, visual contrast sensitivity, proprioception, quadriceps 0.72) were associated with fall risk when adjusted by con- muscle strength, hand reaction time, and postural sway [39]. founding factors such as age, sex, number of comorbidities, Visual contrast sensitivity was used to assess vision using the polypharmacy, and body mass index (Table 3). Melbourne Edge Test. -e visual assessment is a test of the Figure 1 shows an average of overall fall risk score by visibility of the intensity of a circular dividing line. -e frailty status and age. -e nonfrailty group has an age av- resulting score is the value of the last image seen [39]. -e erage of 70.60 years and an average overall score fall risk of proprioception test was used to assess sensations using a 2.15. -e prefrailty group has an average age of 73.20 years lower limb matching test. -e interpretation of the evalu- and an average overall score for risk of falls of 2.70. -e ation uses the difference in the degree of sensation in the big frailty group has an age average of 79.31 years and an average toes [39]. Quadriceps muscle strength was assessed using a overall score for fall risk of 4.47. -e nonfrailty and prefrailty spring gauge (kilograms) [39]. Hand reaction time was groups were at a marked level of fall risk, but the frailty assessed using light as a stimulus and a finger depression of a group was at a highly marked level of fall risk. switch as the response (milliseconds) [39]. Postural sway was assessed using the mass aggregation swing. -e tested person 4. Discussion stands on a foam sheet for 30 seconds, with a belt with a perpendicular nib, which draws a graph on the graph paper -is study will add to the available evidence associated with on the table while balancing. It takes the calculated graph the relationship between frailty in older adults and fall risk. from the anterior–posterior value, multiplies it by the -e results of this study confirm our hypothesis that fall risk 4 Journal of Aging Research Table 1: Characteristics of study participants. Frailty status (N � 367) Characteristics Total p value Nonfrail (n � 53, 14.4%) Prefrail (n � 282, 76.8%) Frail (n � 32, 8.7%) Sex, n (%) 0.641 Male 130 (35.4) 20 (15.4) 101 (77.7) 9 (6.9) Female 237 (64.6) 33 (13.9) 181 (76.4) 23 (9.7) Age (years), mean± SD 73.22± 7.00 70.60± 4.52 73.02± 6.95 79.31± 7.46 <0.001 Number of comorbidities, mean± SD 0.83± 0.80 0.75± 0.89 0.82± 0.79 0.97± 0.74 0.494 Polypharmacy, mean± SD 0.78± 0.81 0.64± 0.78 0.78± 0 .82 0.97± 0.74 <0.001 2 b Body mass index (kg/m ), mean± SD 22.63± 3.86 22.50± 2.91 22.81± 3.90 21.24± 4.59 <0.001 Underweight (<18.5), n (%) 53 (14.4) 4 (7.5) 38 (71.7) 11 (20.8) Normal weight (18.5–22.9), n (%) 143 (39.0) 25 (17.5) 109 (76.2) 9 (6.3) Overweight (23.0–27.5), n (%) 134 (36.5) 21 (15.7) 103 (76.9) 10 (7.4) Obese (˃27.5), n (%) 37 (10.1) 3 (8.1) 32 (86.5) 2 (5.4) PPA fall risk (Z-score) (mean± SD) 2.80± 1.47 2.15± 1.02 2.70± 1.38 4.47± 1.65 <0.001 a b Chi-square test. One-way ANOVA test analysis. PPA � physiological profile assessment. Table 2: Fall risk score using the physiological profile assessment compared with frailty status in older adults. Component Frailty status Mean± SD 95% confidence interval p value Nonfrailty 17± 4.29 15.82, 18.18 b acbc Visual contrast sensitivity (dB) Prefrailty 16.10± 5.00 15.50, 16.68 <0.001 Frailty 8.44± 6.34 6.15, 10.72 Nonfrailty 2.29± 0.95 2.02, 2.55 b ac ab Proprioception (degree) Prefrailty 2.72± 1.49 2.54, 2.89 0.001 Frailty 3.53± 1.99 2.81, 4.25 Nonfrailty 19.07± 8.07 16.84, 21.29 b ac ab bc Knee extension strength (kg) Prefrailty 14.13± 6.32 13.39, 14.87 <0.001 Frailty 7.57± 4.40 5.98, 9.16 Nonfrailty 345.17± 94.99 318.99, 371.35 b ac ab Hand reaction time (ms) Prefrailty 395.51± 136.49 379.51, 411.51 <0.001 Frailty 472.69± 228.53 390.29, 555.08 Nonfrailty 1216.24± 840.43 984.59, 1447.89 2 b ac bc Sway path (mm ) Prefrailty 1367.63± 1258.65 1220.10, 1515.17 <0.001 Frailty 2435.25± 1951.94 1731.50, 3139.00 Nonfrailty 2.15± 1.02 1.87, 2.42) b ac ab bc PPA fall risk (Z-score) Prefrailty 2.70± 1.38 2.54, 2.86) <0.001 Frailty 4.47± 1.65 3.87, 5.06) ac: nonfrailty group compared with the frailty group; ab: nonfrailty group compared with the prefrailty group; bc: prefrailty group compared with the frailty group; PPA � physiological profile assessment. -e first set of results found that the frailty group had a Table 3: Factors associated with fall risk. significantly higher overall fall risk score when compared to Linear regression analysis both the nonfrailty and prefrailty groups. -is is related to Independent variable p value B (SE) 95% CI the level of frailty being related to the degeneration of ∗∗ physical and cognitive factors, conferring both physical Frailty status 0.71 (0.14) (0.42, 1.01) <0.001 ∗∗ Age 0.07 (0.01) (0.04, 0.09) <0.001 frailty and cognitive frailty [23, 27]. Sex 0.26 (0.14) (−0.01, 0.54) 0.06 Our study about fall risk had five components. First, Number of comorbidities −0.28 (0.18) (−0.65, 0.07) 0.12 these study results found the frail group had poorer vision Polypharmacy 0.36 (0.18) (0.00, 0.72) 0.04 than the nonfrailty group which was consistent with pre- Body mass index −0.01 (0.01) (−0.05, 0.02) 0.42 vious studies that found poor vision function in the frailty ∗∗ ∗ Significance at p-value< 0.001. Significance at p value � 0.05. group caused falls in older adults [47–49]. -is may be explained by the aging process leading to a change in fo- differs between each frailty status. Individuals classified as cusing in the eyes leading to difficulty in focusing on distance or objects because of low contrast sensitivity [49, 50]. Frailty frail are at a greater risk of falling and then comes the prefrail and nonfrail groups. -e study found that individuals is also related to the concept of geriatric syndrome and age- classified as prefrail differ from those classified as nonfrail in associated reduction of physiological reserves [1–3, 51]. three aspects of physiology, which is interesting new Second, the frailty group had impaired proprioception when evidence. compared with the nonfrail group. Likewise, a previous Journal of Aging Research 5 study are based on new knowledge, reflecting that the sig- (F) Very marked naling changes in the brain were the first changes to occur 3 before the frail condition became identifiable [53]. Likewise, (P) Marked the prefrail group had slower reaction times in comparison (N) to the nonfrail group. -is reaction time indicates a decline Moderate in cognitive function in the prefrail group showing a decline in brain function, again before entering the status of frailty. Mild -e members of the prefrail group also had lower muscle strength in comparison to the nonfrail group [59]. A pre- Low vious study adds weight to this finding as it also found poor –1 muscle strength and physical activity in a prefrail group Very low when compared with nonfrail individuals [56]. In addition, a previous study found a reduction in mitochondrial genes in 30 40 50 60 70 80 90 100 muscles which led to a reduction in muscle function [61]. Age (years) -e results of this study show that physiological changes before entering the frailty phase are a decrease in brain Fall risk score function and decrease in muscle strength which is inter- Normal population esting knowledge because it can be used as a way to prevent frailty in the future. Figure 1: Overall fall risk score by frailty status and age using the fall risk calculator by NeuRA FallScreen . N � nonfrail group On the other hand, we found no differences in fall risk for (Z-score � 2.15); P � prefrail group (Z-score � 2.70); F � frail group two components between the nonfrailty and the prefrailty (Z-score � 4.47). groups. -ese were vision and sway which may have occurred because the prefrailty group was nearly the same age as the study found the frailty group had greater impaired propri- nonfrailty group, and vision may be more closely related to oception than older adults not classified as frail [52]. Frailty is age than frailty. Vision is the main component of postural associated with a decline and change in physiology including control that affects postural sway [62, 63]. -us, no difference the central nervous system (CNS) that serves to send sen- in vision results in no postural sway differences for both sations to the joints. -is may explain this result as propri- statuses. In addition, we found the fall risk components oception has cumulative neural input from mechanoreceptors proprioception and reaction time were no different between such as muscular, articular, and cutaneous receptors [53]. the frailty group and the prefrailty group. -ose in the -ird, the frailty group had a more decreased muscle strength prefrailty group are likely to develop changes in physiological than the nonfrailty group which could be due to decreased functions and progress to the frailty status. Sarcopenia is muscle size and muscle mass from muscle fiber changes (IIA prevalent in the frailty group affecting neuromuscular and IIB) producing lower strength in the frailty group [54]. changes that, together with those of greater age in the pre- Another study found a weakness of lower limbs was asso- frailty group, will be related to loss of muscle mass and size ciated with the frailty group [55]. In addition, muscle which affect proprioception and reaction time [64]. weakness was found to be associated with the frailty group of In addition, we found frailty status, age, and poly- older adults in community [56]. Fourth, this study found that pharmacy were factors associated with fall risk. -e meta- the frailty group had a longer reaction time than the nonfrailty analysis found frailty was a risk factor for falling in com- group which had not been reported in other studies. -e munity-dwelling older adults [15]. A prospective cohort explanation for this may be due to the reaction time being study found a correlation between age and fall rate [32, 65]. sensory in nature, responding to stimuli which reflected the A review of relevant literature showed polypharmacy to have speed impulses are passed to the central nervous system [57]. a variable link to falling in older adults [66]. However an- Reaction time in this study was assessed by hand reaction time other, nationwide nested case-control study found a direct that represents cognitive processes of the brain [58]. Similarly, relationship between polypharmacy and injurious falls [67]. frailty is associated with cognitive impairment which could -is is probably the first study to separate the physiology also go some way to explaining the increase in the length of of each aspect in assessing falls. However, our research the reaction time [59]. Finally, this study found the frailty showed some limitations that may have impact on the re- group has a greater postural sway than the nonfrailty group. sults. -e first limitation of this study is that it was cross- Frailty is associated with reduced musculoskeletal and brain sectional in nature. Second, the subgroup of frail individuals activity and both systems work together in coordinating was too small. Finally, this study measured only the fall risk posture stability. -is study found the frailty group had a using physical performance assessment and there are many greater impairment of balance and gait [60] -is therefore led others factors associated with fall risk; therefore, in a future to a high fall risk score (PPA Z-score) in the frailty group study, we would consider a prospective cohort design study. which was significantly different from the nonfrailty group. In the second part of the study, we found the prefrail 5. Conclusions group to have proprioception differences compared with the nonfrail group. Basically, the prefrail group had a poorer -is study found five different fall risk components asso- proprioception than the nonfrail group. -e results of this ciated with the frailty status. -e frailty group had the better Fall risk score (SD) worse 6 Journal of Aging Research in early-old community dwellers of -ailand,” International highest fall risk score. In addition, the prefrail group was JournalofEnvironmentalResearchandPublicHealth, vol. 16, susceptible to changes related to physiology as regards no. 18, 2019. proprioception, reaction time, and change in muscle [8] E. Dent, P. Kowal, and E. O. Hoogendijk, “Frailty measure- strength, all of which were poorer than those in individuals ment in research and clinical practice: a review,” European in the nonfrail group. In addition, the frailty status, age, and Journal of Internal Medicine, vol. 31, pp. 3–10, 2016. polypharmacy were factors associated with fall risk which [9] L. P. Fried, C. M. Tangen, J. Walston et al., “Frailty in older can be used to predict the risk of falling among older adults adults: evidence for a phenotype,” eJournalsofGerontology in the community. -us, the older adults in the community Series A: Biological Sciences and Medical Sciences, vol. 56, should be screened for level of frailty and fall risk to reduce no. 3, pp. M146–M157, 2001. and prevent impact on disability and mortality. -e results [10] M. Roppplo, A. Mulasso, R. J. Gobbens, C. O. Mosso, and of our study can serve as a reference for specific intervention E. Rabaglietti, “A comparison between uni-and multidi- in the prevention of fall risk in community-dwelling older mensional frailty measures: prevalence, functional status, and relationships with disability,” Clinical Interventions in Aging, adults and also inform the assessment of other factors vol. 10, p. 1669, 2015. among community-dwelling older adults. [11] G. Kojima, “Frailty as a predictor of future falls among community-dwelling older people: a systematic review and Data Availability meta-analysis,” Journal of the American Medical Directors Association, vol. 16, no. 12, pp. 1027–1033, 2015. -e data that support the findings of this study are available [12] C. Curcio, G. Henao, and F. Gomez, “Frailty among rural from the corresponding author upon reasonable request. elderly adults,” BMC Geriatrics, vol. 14, no. 2, 2014. [13] J. R. Fhon, R. A. Rodrigues, W. F. Neira, V. M. Huayta, and Conflicts of Interest M. L. Robazzi, “Fall and its association with the frailty syn- drome in the elderly: systematic review with meta-analysis,” -e authors declared no conflicts of interest with respect to Revista da Escola de Enfermagem da USP, vol. 50, no. 6, this research, authorship, and/or publication of this article. pp. 1003–1010, 2016. [14] E. Y. Shim, S. H. Ma, S. H. Hong et al., “Correlation between Acknowledgments frailty level and adverse health-related outcomes of commu- nity-dwelling elderly, one year retrospective study,” Korean -e authors thank the Faculty of Medicine and Faculty of Journal of Family Medicine, vol. 32, no. 4, pp. 249–256, 2011. Associated Medical Sciences, Chiang Mai University, [15] M.-H. Cheng and S.-F. Chang, “Frailty as a risk factor for falls -ailand, for providing support. -e authors also thank the among community dwelling people: evidence from a meta- cohort of older adults who participated in this study. -e analysis,” Journal of Nursing Scholarship, vol. 49, no. 5, pp. 529–536, 2017. authors wish to acknowledge the funding from the Faculty of [16] R. Samper-Ternent, A. Karmarkar, J. Graham, T. Reistetter, Medicine, Chiang Mai University, under Grant no. 124/ and K. Ottenbacher, “Frailty as a predictor of falls in older Mexican Americans,” Journal of Aging and Health, vol. 24, no. 4, pp. 641–653, 2012. References [17] A. Mulasso, M. Roppolo, R. J. Gobbens, and E. Rabaglietti, “Mobility, balance and frailty in community-dwelling older [1] Q.-L. Xue, “-e frailty syndrome: definition and natural adults: what is the best 1-year predictor of falls?”Geriatrics& history,”ClinicsinGeriatricMedicine, vol. 27, no. 1, pp. 1–15, GerontologyInternational, vol. 17, no. 10, pp. 1463–1469, 2017. [18] J. M. VanSwearingen, K. A. Paschal, P. Bonino, and [2] A. Clegg, J. Young, S. Iliffe, M. O. Rikkert, and K. Rockwood, T.-W. Chen, “Assessing recurrent fall risk of community- “Frailty in elderly people,” e Lancet, vol. 381, no. 9868, dwelling, frail older veterans using specific tests of mobility pp. 752–762, 2013. and the physical performance test of function,” eJournalsof [3] X. Chen, G. Mao, and S. X. Leng, “Frailty syndrome: an GerontologySeriesA:BiologicalSciencesandMedicalSciences, overview,” Clinical Interventions in Aging, vol. 19, no. 9, vol. 53A, no. 6, pp. M457–M464, 1998. pp. 433–441, 2014. [19] M. J Ohler, C. S Wendel, R. Taylor-Piliae, N. Toosizadeh, and [4] L. P. Fried, L. Ferrucci, J. Darer, J. D. Williamson, and B. Najafi, “Motor performance and physical activity as pre- G. Anderson, “Untangling the concepts of disability, frailty, dictors of prospective falls in community-dwelling older and comorbidity: implications for improved targeting and adults by frailty level: application of wearable technology,” care,” Journal of Gerontology Series A, Biological Sciences and Gerontology, vol. 62, pp. 654–664, 2016. Medical Sciences, vol. 59, no. 3, 2004. [20] T. Silveira, M. S. Pegorari, S. S. D. Castro, G. Ruas, [5] D. D. Siriwardhana, S. Hardoon, G. Rait, M. C. Weerasinghe, S. G. Novais-Shimano, and L. J. Patrizzi, “Association of falls, and K. R. Walters, “Prevalence of frailty and pre-frailty among community-dwelling older adults in low-income and middle- fear of falling, handgrip strength and gait speed with frailty levels in the community elderly,” Medicina (Ribeirao Preto. income countries: a systematic review and meta-analysis,” BMJ Open, vol. 8, Article ID e018195, 2018. Online), vol. 48, no. 6, pp. 549–556, 2015. [21] C. Cardon, M. Verbecqa, M. Loustaub et al., “Predicting falls [6] S. Morarit, K. Taypa, W. Boonyod, and P. Siviroj, “Frailty phenotype characteristics of Community-dwelling frail el- with the cognitive timed up-and-go dual task in frail older patients,” Annals of Physical and Rehabilitation Medicine, derly people in a sub-district,” Naresuan Phayao Journal, vol. 11, no. 2, pp. 56–60, 2018. vol. 60, pp. 83–86, 2017. [22] P. R. Brustio, D. Magistro, M. Zecca, M. E. Liubicich, and [7] W. Semmarath, M. Seesen, S. Yodkeeree et al., “-e associ- ation between frailty indicators and blood-based biomarkers E. Rabaglietti, “Fear of falling and activities of daily living Journal of Aging Research 7 function: mediation effect of dual-task ability,” Aging & [39] S. R. Lord, H. B. Menz, and A. Tiedemann, “A physiological Mental Health, vol. 22, no. 6, pp. 856–861, 2018. profile approach to falls risk assessment and prevention,” [23] M. Roppplo, A. Mulasso, and E. Rabaglietti, “Cognitive frailty Physical erapy, vol. 83, no. 3, pp. 237–252, 2003. in Italian community-dwelling older adults: prevalence rate [40] S. Gates, J. D. Fisher, M. W. Cooke, Y. H. Carter, and and its association with disability,” e Journal of Nutrition, S. E. Lamb, “Multifactorial assessment and targeted inter- Health and Aging, vol. 21, no. 6, pp. 631–636, 2017. vention for preventing falls and injuries among older people [24] O. J. de Vries, G. M. E. E. Peeters, P. Lips, and D. J. H. Deeg, in community and emergency care settings: systematic review “Does frailty predict increased risk of falls and fractures? A and meta-analysis,” BMJ, vol. 336, no. 7636, pp. 130–133, prospective population-based study,” Osteoporosis Interna- 2008. tional, vol. 24, no. 9, pp. 2397–2403, 2013. [41] M. C. Robertson and L. D. Gillespie, “Fall prevention in [25] K. E. Ensrud, S. K. Ewing, B. C. Taylor et al., “Frailty and risk community-dwelling older adults,” JAMA, vol. 309, no. 13, of falls, fracture, and mortality in older women: the study of pp. 1406-1407, 2013. osteoporotic fractures,” e Journals of Gerontology Series A: [42] E. A. Phelan and K. Ritchey, “Fall prevention in community- Biological Sciences and Medical Sciences, vol. 62, no. 7, dwelling older adults. Annals of internal medicine,”Annalsof pp. 744–751, 2007. Internal Medicine, vol. 169, no. 11, 2018. [26] C. de Labra, A. Maseda, L. Lorenzo-Lopez et al., “Social factors [43] S. Kanjananopinit, S. Charoensak, and T. Keawpornsawan, and quality of life aspects on frailty syndrome in community- “-e study of psychometric properties of cognistat -ai version,” Journal of the Psychiatrist Association of ailand, dwelling older adults: the verisaude study,” BMC Geriatrics, vol. 18, no. 1, p. 66, 2018. vol. 59, no. 4, pp. 409–418, 2014. [44] T. Liabsuetrakul, “Southern soil-transmitted helminths [27] A. Mulasso, M. Roppolo, and E. Rabaglietti, “Physical frailty, disability, and dynamics in health perceptions: a preliminary and maternal health working group, “is international or mediation model,” Clinical Interventions in Aging, vol. 11, Asian criteria-based body mass index associated with pp. 275–8, 2016. maternal anaemia, low birthweight, and preterm births [28] S.-F. Chang and P.-L. Lin, “Frail phenotype and mortality among -ai population? An observational study,” Journal prediction: a systematic review and meta-analysis of pro- Health Population Nutrition, vol. 29, no. 3, pp. 218–228, spective cohort studies,” International Journal of Nursing 2011. [45] J. G. Orme, J. Reis, and E. J. Herz, “Factorial and discriminant Studies, vol. 52, no. 8, pp. 1362–1374, 2015. [29] World Health Organization, Epidemiology of Falls, “WHO validity of the center for epidemiological studies depression (CES-D) scale,” Journal of Clinical Psychology, vol. 42, no. 1, GlobalReportonFallsPreventioninOlderAge, World Health Organization Press, Geneva, Switzerland, 2008. pp. 28–33, 1986. [30] F. Bloch, M. -ibaud, B. Dugu e, ´ C. Breque, ` A. Rigaud, and [46] P. Rattanawiwatpong, A. Khunphasee, C. Pongurgsorn, and G. Kemoun, “Episodes of falling among elderly people: a P. Intarakamhang, “Validity and reliability of the -ai version systematic review and meta-analysis of social and demo- of short format international physical activity questionnaire graphic pre-disposing characteristics,” Clinics, vol. 65, no. 9, (IPAQ),” Journal of ai Rehabilitation Medicine, vol. 16, pp. 895–903, 2010. pp. 147–160, 2006. [31] P. Kuhirunyaratn, P. Prasomrak, and B. Jindawong, “Factors [47] B. E. Klein, R. Klein, M. D. Knudtson, and K. E. Lee, “Re- related to falls among community dwelling elderly,” e lationship of measures of frailty to visual function: the beaver dam eye study,” Transactions of the American Ophthalmo- Southeast Asian Journal of Tropical Medicine and Public Health, vol. 44, no. 5, pp. 906–915, 2013. logical Society, vol. 101, pp. 191–199, 2003. [32] S. I. Sharif, A. B. Al-Harbi, A. M. Al-Shihabi, D. S. Al-Daour, [48] A. E. M. Liljas, L. A. Carvalho, E. Papachristou et al., “Self- and R. S. Sharif, “Falls in the elderly: assessment of prevalence reported vision impairment and incident prefrailty and frailty and risk factors,”PharmacyPractice, vol. 16, no. 3, p. 1206, 2018. in English community-dwelling older adults: findings from a [33] E. Kwan, S. Straus, and J. Holroyd-Leduc, Risk factors for falls 4-year follow-up study,” Journal of Epidemiology and Com- in the elderly, in Medication-elated Falls in Older People, A. munity Health, vol. 71, no. 11, pp. 1053–1058, 2017. [49] D. K. Y. Miu, “Visual impairment contributes to frailty among Huang, and L. Mallet, et al., Adis, Cham, Switzerland, 2016. [34] Y. Amatullah, S. B. Sastradimaja, and L. Dwipa, “Intrinsic risk a group of healthy community dwelling older population,” Journal of Geriatric Medicine and Gerontology, vol. 4, no. 2, factors of falls in elderly,”AltheaMedicalJournal, vol. 3, no. 3, 2016. 2018. [50] J. M. Wood, P. Lacherez, A. A. Black, M. H. Cole, [35] World Health Organization, What Are the Main Risk Factors for Falls Amongst Older People and What Are the Most Ef- M. Y. Boon, and G. K. Kerr, “Risk of falls, injurious falls, and fective Interventions to Prevent ese Falls?”, World Health other injuries resulting from visual impairment among older Organization, Geneva, Switzerland, 2004. adults with age-related macular degeneration,” Investigative [36] A. Bueno-Cavanillas, F. Padilla-Ruiz, J. J. Jimenez-Mole ´ on, ´ Opthalmology&VisualScience, vol. 52, no. 8, pp. 5088–5092, C. A. Peinado-Alonso, and R. Galvez-Vargas, ´ “Risk factors in 2011. falls among the elderly according to extrinsic and intrinsic [51] K. Miyamura, J. R. S. Fhon, de A. B. Alexandre, W. F. N Luis, C. P. S. Cristina, and R. A. P. Rodrigues, “Frailty syndrome precipitating causes,” European Journal Of Epidemiology, vol. 16, no. 9, pp. 849–859, 2000. and cognitive impairment in older adults: systematic review of [37] S. Patil, S. Suryanarayana, N. Shivraj, N. Murthy, and the literature,” Revista Latino-Americana de Enfermagem, R. Dinesh, “Risk factors for falls among elderly: a community- vol. 27, pp. 1–12, 2019. based study,” International Journal of Health & Allied Sci- [52] M. L. Fritz, “Neuromuscular aging and frailty,” Dissertation, ences, vol. 4, no. 3, p. 135, 2015. Colorado State University, Department of Health and Exercise [38] F. B. Horak, D. M. Wrisley, and J. Frank, “-e balance Science, Fort Collins, Colorado, 2016, https://mountainscholar. evaluation systems test (BESTest) to differentiate balance org/bitstream/handle/10217/176604/Fritz_colostate_0053A_ deficits,”Physical erapy, vol. 89, no. 5, pp. 484–498, 2009. 13632.pdf?sequence=1&isAllowed=y. 8 Journal of Aging Research [53] A. S. Buchman, L. Yu, R. S. Wilson et al., “Brain pathology contributes to simultaneous change in physical frailty and cognition in old age,” e Journals of Gerontology: Series A, vol. 69, no. 12, pp. 1536–1544, 2014. [54] D. Wilson, T. Jackson, E. Sapey, and M. L Janet, “Frailty and sarcopenia: the potential role of an aged immune system,” Ageing Research Reviews, vol. 36, pp. 1–10, 2017. [55] E. Gielen, S. Verschueren, T. W. O’Neill et al., “Musculo- skeletal frailty: a geriatric syndrome at the core of fracture occurrence in older age,” Calcified Tissue International, vol. 91, no. 3, pp. 161–177, 2012. [56] F. S. Batista, G. A. D. O. Gomes, A. L. Neri et al., “Relationship between lower-limb muscle strength and frailty among elderly people,” Sao Paulo Medical Journal, vol. 130, no. 2, pp. 102– 108, 2012. [57] R. D. Seidler, J. A. Bernard, T. B. Burutolu et al., “Motor control and aging: links to age-related brain structural, functional, and biochemical effects,” Neuroscience & Bio- behavioral Reviews, vol. 34, no. 5, pp. 721–733, 2010. [58] Y. Shub, I. E. Ashkenazi, and A. Reinberg, “Differences be- tween left- and right-hand reaction time rhythms: indications of shifts in strategies of human brain activity,”CognitiveBrain Research, vol. 6, no. 2, pp. 141–146, 1997. [59] L. Sargent, M. Nalls, A. Starkweather et al., “Shared biological pathways for frailty and cognitive impairment: a systematic review,” Ageing Research Reviews, vol. 47, pp. 149–158, 2018. [60] H. Makizako, T. Kubozono, R. Kiyama et al., “Associations of social frailty with loss of muscle mass and muscle weakness among community-dwelling older adults,” Geriatrics & Gerontology International, vol. 19, no. 1, pp. 76–80, 2019. [61] P. A. Andreux, M. P. J. van Diemen, M. R. Heezen et al., “Mitochondrial function is impaired in the skeletal muscle of pre-frail elderly,” Scientific Reports, vol. 8, no. 8548, pp. 1–12, [62] E. E. Hansson, A. Beckman, and A. Hakansson, ˚ “Effect of vision, proprioception, and the position of the vestibular organ on postural sway,” Acta Oto-Laryngologica, vol. 130, no. 12, pp. 1358–1363, 2010. [63] M. Tomomitsu, A. Alonso, E. Morimoto, T. Bobbio, and J. Greve, “Static and dynamic postural control in low-vision and normal-vision adults,”Clinics, vol. 68, no. 4, pp. 517–521, [64] B. C. Clark, “Neuromuscular changes with aging and sar- copenia,” eJournalofFrailty&Aging, vol. 8, pp. 7–9, 2019. [65] A. F. Ambrose, G. Paul, and J. M. Hausdorff, “Risk factors for falls among older adults: a review of the literature,”Maturitas, vol. 75, no. 1, pp. 51–61, 2013. [66] T. Hammond and A. Wilson, “Polypharmacy and falls in the elderly: a literature review,” Nursing and Midwifery Studies, vol. 2, no. 2, pp. 171–175, 2013. [67] L. Morin, A. Calderon Larrañaga, A.-K. Welmer, D. Rizzuto, J. Wastesson, and K. Johnell, “Polypharmacy and injurious falls in older adults: a nationwide nested case-control study,” Clinical Epidemiology, vol. 11, pp. 483–493, 2019.

Journal

Journal of Aging ResearchHindawi Publishing Corporation

Published: Jul 4, 2020

References