Fall Risk In Individuals Research Articles

The Effects of Body Awareness on Fall-Related Behaviors and Fall Risk in Geriatric Individuals

Aims Aging is an inevitable stage in which in addition to physiological and mental changes, perception and awareness decline, and memory functions gradually deteriorate. The aim of this study was to examine the effects of body awareness on fall-related behaviors and fall risk in geriatric individuals. Methods This cross-sectional study was conducted with 176 individuals over 65 years of age who presented to family health centers. Body awareness (BAQ), fall-related behaviors (FaB) and fall risk (Morse) were examined. Statistical significance was accepted as p < 0.05 in the analyzes. Results There was a moderate, negative, and statistically significant relationship between the Morse and BAQ scores of the participants (r=-0.576) (p < 0.05). There was a moderate, positive, and statistically significant relationship between the BAQ and FaB scores of the participants (r = 0.235) (p < 0.05). Conclusions The results showed a significant relationship between body awareness levels and fall-related behaviors and fall risk in geriatric individuals.

Peripheral neuropathy, an independent risk factor for falls in the elderly, impairs stepping as a postural control mechanism: A case-cohort study.

Peripheral neuropathies perturbate the sensorimotor system, causing difficulties in walking-related motor tasks and, eventually, falls. Falls result in functional dependency and reliance on healthcare, especially in older persons. We investigated if peripheral neuropathy is a genuine risk factor for falls in the elderly and if quantification of postural control via posturography is helpful in identifying subjects at risk of falls. Seventeen older persons with a clinical polyneuropathic syndrome of the lower limbs and converging electrophysiology were compared with 14 older persons without polyneuropathy. All participants were characterized via quantitative motor and sensory testing, neuropsychological assessment, and self-questionnaires. Video-nystagmography and caloric test excluded vestibulocochlear dysfunction. For further analysis, all subjects were stratified into fallers and non-fallers. Overall, 28 patients underwent computerized dynamic posturography for individual fall risk assessment. Regression analyses were performed to identify risk factors and predictive posturography parameters. Neuropathy is an independent risk factor for falls in the elderly, while no differences were observed for age, gender, weight, frailty, DemTect test, timed "Up & Go" test, and dizziness-related handicap score. In computerized dynamic posturography, fallers stepped more often to regain postural control in challenging conditions, while the Rhythmic Weight Shift test showed a lack of anterior-posterior bidirectional voluntary control. Our study confirms peripheral neuropathy as a risk factor for older persons' falls. Fallers frequently used stepping to regain postural control. The voluntary control of this coping movement was impaired. Further investigations into these parameters' value in predicting the risk of falls in the elderly are warranted.

Prognosis of fall risk in home care clients: A noninvasive approach using survival analysis

Abstract Aim The present study has designed, implemented, and evaluated a machine learning model that can predict fall risk and fall occurrence in community-dwelling elderly based on their home care usage. Subjects and methods A dataset consisting of 2542 weekly home care records for 1499 citizens (59% female, 41% male) with a mean age of 77 years (SD 10 years) was collected from a large municipality in Denmark. The data were recorded between January 1, 2021, and December 31, 2021. The dataset was divided into two cohorts. Subsequently, five machine learning-based survival analysis models were trained and evaluated using cross-validation. Results The CoxBoost model showed the best discriminative performance with a mean 0.64 (95% CI 0.57–0.72) Harrell’s concordance index, indicating better ranking than chance-level by 14% on average. However, the model could not accurately predict when the next fall would take place. Conclusions The proposed method enables professionals to assess individual fall risk by using home care records from an Electronic Health Record (EHR) system. This facilitates the initiation of targeted fall-prevention programs for those at highest risk. Additionally, it is expected that a risk-based approach can lead to a lower number needed to treat (NNT), indicating greater effectiveness of health interventions.

CSP2023: 142 - Cost and effectiveness of Dual-task training on balance and fall risk in individuals with cerebellar ataxia: A randomized controlled trial

CSP2023: 142 - Cost and effectiveness of Dual-task training on balance and fall risk in individuals with cerebellar ataxia: A randomized controlled trial

Fall-risk assessment of aged workers using wearable inertial measurement units based on machine learning

Falls are the major cause of fatal and nonfatal incidents among aged workers. Estimating individual fall risk is crucial for occupational protection and public health. This study aimed to develop a fall-risk assessment method based on Machine Learning (ML) and Inertial Measurement Units (IMUs). A total of 28 aged workers (60 to 80 years old) participated in this study, recruited from community sanitation workers and janitors. They were categorized into high and low fall-risk groups based on functional gait assessment. Each participant performed 5 sets of motion experiments in the lab, covering 6 daily motions. We gathered their kinematic data with IMUs for training ML-based fall-risk assessment models. Five classic ML classifiers were optimized using grid search, and a Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM) hybrid deep neural network was built to recognize walking motion from kinematic data for input into the fall-risk assessment model. The results demonstrated that ML classifiers trained with walking motion data exhibited superior performance. Cross-validation revealed that the optimized Random Forest classifier, with IMU on the right upper leg, reached 91.3 % accuracy. Additionally, the CNN-LSTM models were evaluated using F1-score, which can balance accuracy and coverage of model performance evaluation. The CNN-LSTM achieved a maximum F1-score of 95.18 %, proving their effectiveness in extracting walking motion data. These findings indicate that the developed IMU-based ML method exhibits excellent performance in assessing fall risk, potentially allowing aged workers to assess their fall risk before clinical diagnosis by embedding it in wearable IMUs.

Associations between monitor-independent movement summary (MIMS) and fall risk appraisal combining fear of falling and physiological fall risk in community-dwelling older adults.

Introduction: Fall Risk Appraisal (FRA), a process that integrates perceived and objective fall risk measures, serves as a crucial component for understanding the incongruence between fear of falling (FOF) and physiological fall risk in older adults. Despite its importance, scant research has been undertaken to investigate how habitual physical activity (PA) levels, quantified in Monitor-Independent Movement Summary (MIMS), vary across FRA categories. MIMS is a device-independent acceleration summary metric that helps standardize data analysis across studies by accounting for discrepancies in raw data among research-grade and consumer devices. Objective: This cross-sectional study explores the associations between MIMS (volume and intensity) and FRA in a sample of older adults in the United States. Methods: We assessed FOF (Short Falls Efficacy Scale-International), physiological fall risk (balance: BTrackS Balance, leg strength: 30-s sit-to-stand test) and 7-day free-living PA (ActiGraph GT9X) in 178 community-dwelling older adults. PA volume was summarized as average daily MIMS (MIMS/day). PA intensity was calculated as peak 30-min MIMS (average of highest 30 non-consecutive MIMS minutes/day), representing a PA index of higher-intensity epochs. FRA categorized participants into following four groups: Rational (low FOF-low physiological fall risk), Irrational (high FOF-low physiological fall risk), Incongruent (low FOF-high physiological fall risk) and Congruent (high FOF-high physiological fall risk). Results: Compared to rational group, average MIMS/day and peak 30-min MIMS were, respectively, 15.8% (p = .025) and 14.0% (p = .004) lower in irrational group, and 16.6% (p = .013) and 17.5% (p < .001) lower in congruent group. No significant differences were detected between incongruent and rational groups. Multiple regression analyses showed that, after adjusting for age, gender, and BMI (reference: rational), only irrational FRA was significantly associated with lower PA volume (β = -1,452.8 MIMS/day, p = .034); whereas irrational and congruent FRAs were significantly associated with lower "peak PA intensity" (irrational: β = -5.40 MIMS/day, p = .007; congruent: β = -5.43 MIMS/day, p = .004). Conclusion: These findings highlight that FOF is a significant barrier for older adults to participate in high-intensity PA, regardless of their balance and strength. Therefore, PA programs for older adults should develop tailored intervention strategies (cognitive reframing, balance and strength exercises, or both) based on an individual's FOF and physiological fall risk.

The effect of dyskinesia on postural control, balance, gait, and fall risk in people with Parkinson’s disease: a systematic review protocol

Dyskinesia affects the limbs, trunk, and head and is more prevalent in people with Parkinson’s disease (PD) and a history of falls. More evidence about the effects of dyskinesia on postural control, balance, gait, and fall risk could help improve the quality of life of individuals with PD. This review aims to examine associations between dyskinesia and postural control, balance, gait, and fall risk in individuals with PD. Such information could lead to new approaches to quality of life improvement among individuals with PD. PubMed, CINAHL, PsycInfo, Scopus, and SciELO will be searched for longitudinal, cohort, and case-control studies published in English or Portuguese in any year that investigated the association between dyskinesia and postural control, balance, gait, and fall risk in individuals with PD. Two reviewers will independently evaluate the titles, abstracts, and full texts according to PRISMA guidelines to select eligible studies for the review. Data on participants, dyskinesia, postural control, balance, gait, and fall risk will be extracted and summarized in tables. Two reviewers will independently assess the methodological quality of each study using the Newcastle Ottawa quality assessment scale. Meta-analysis will not be performed. The results of this systematic review will offer insight into the effects of dyskinesia on postural control, balance, gait, and fall risk. Such information could significantly contribute to informed decisions about early motor intervention in individuals with PD.

"Fall Risk Scoring" in Outpatient Gait Analysis: Validation of a New Fall Risk Assessment for Nursing Home Residents.

Falls in senior home residents are common. Individual preventive training can lower the fall risk. To detect the need for training, a systematic assessment of the individual fall risk is needed. The aim of this study was thus to assess whether a fall risk score based on free field insole measurements can distinguish between an at-risk group of senior home residents and a healthy young control group. A published fall risk score was used in senior home residents over the age of 75 and a young (<40 years) control group to determine the individual fall risk. In addition, the fall events over 12 months were assessed. Statistical analysis including ROC analysis was performed to determine the ability of the score to detect participants at heightened fall risk. In total, 18 nursing home residents and 9 young control participants were included. Of the nursing home residents, 15 had at least one fall, with a total of 37 falls recorded over 12 months. In the control group, no falls were recorded. The fall risk score was significantly different between nursing home residents and the control group (9.2+3.2 vs. 5.7±2.2). Furthermore, the score significantly differentiated fallers from non-fallers (10.3±1.8 vs. 5.2±2.5), with a cut-off >7.5 (AUC: 0.95) and a sensitivity of 86.7% (specificity 83.3%). The fall risk score is able to detect the difference between senior nursing home residents and young, healthy controls, as well as between fallers and non-fallers. Its main proof of concept is demonstrated, as based on movement data outside special gait labs, and it can simplify the risk of fall determination in geriatric nursing home residents and can now be used in further, prospective studies.

A prospective cohort study of the impact of chronic disease on fall injuries in middle-aged and older adults.

This cohort study investigated the impact of chronic diseases on fall risk in middle-aged and older individuals, offering insights for fall prevention strategies. Analysing data from 4,670 participants aged 40+ years, we used a Cox proportional risk model to assess chronic disease types, numbers, and interactions with other factors on fall injury risk across age groups. Results showed that middle-aged adults with respiratory diseases had a 26% increased fall risk (hazard ratio [HR] = 1.26, 95% confidence interval [CI]: 1.05-1.48), and a linear dose-response relationship was observed between chronic disease number and fall risk (p < 0.001). The study also examined interaction effects of chronic diseases with gender, disability, and fall injury history. Female middle-aged and older adults with chronic diseases had a 67% higher fall risk than their male counterparts without chronic diseases (HR = 1.67, 95% CI: 1.36-1.88). In conclusion, chronically ill middle-aged and older adults have a higher fall risk, with high-risk groups including women, those with chronic diseases, and individuals with fall injury history. Fall prevention efforts should target middle-aged adults as well.

Functional and structural lesion network mapping in neurological and psychiatric disorders: a systematic review.

The traditional approach to studying the neurobiological mechanisms of brain disorders and localizing brain function involves identifying brain abnormalities and comparing them to matched controls. This method has been instrumental in clinical neurology, providing insight into the functional roles of different brain regions. However, it becomes challenging when lesions in diverse regions produce similar symptoms. To address this, researchers have begun mapping brain lesions to functional or structural networks, a process known as lesion network mapping (LNM). This approach seeks to identify common brain circuits associated with lesions in various areas. In this review, we focus on recent studies that have utilized LNM to map neurological and psychiatric symptoms, shedding light on how this method enhances our understanding of brain network functions. We conducted a systematic search of four databases: PubMed, Scopus, and Web of Science, using the term "Lesion network mapping." Our focus was on observational studies that applied lesion network mapping in the context of neurological and psychiatric disorders. Following our screening process, we included 52 studies, comprising a total of 6,814 subjects, in our systematic review. These studies, which utilized functional connectivity, revealed several regions and network overlaps across various movement and psychiatric disorders. For instance, the cerebellum was found to be part of a common network for conditions such as essential tremor relief, parkinsonism, Holmes tremor, freezing of gait, cervical dystonia, infantile spasms, and tics. Additionally, the thalamus was identified as part of a common network for essential tremor relief, Holmes tremor, and executive function deficits. The dorsal attention network was significantly associated with fall risk in elderly individuals and parkinsonism. LNM has proven to be a powerful tool in localizing a broad range of neuropsychiatric, behavioral, and movement disorders. It holds promise in identifying new treatment targets through symptom mapping. Nonetheless, the validity of these approaches should be confirmed by more comprehensive prospective studies.

Cardiac rehabilitation participation and risk of falls in older individuals with cardiovascular disease

Abstract Funding Acknowledgements Type of funding sources: None. Background Falls are the leading cause of injury-related morbidity and mortality among older adults in the United States, including those with cardiovascular disease. Cardiac rehabilitation (CR) helps to optimize functional capacity, strength, and balance in patients with cardiovascular disease and, in theory, may reduce the risk of falls. However, little evidence has been published in this regard. Purpose The purpose of this study was to assess the association between CR participation and risk of falls in a community-based sample of individuals 65 years of age and older with cardiovascular disease who were eligible for CR participation. Methods Individuals from Southeastern MN and Western WI, USA, 65 years of age and older who had experienced a cardiovascular event that qualified them for CR (MI, PCI, CABG, Valve Surgery, Transplant) between January 1, 2000, and December 31, 2018, were included in this study. Participation in CR (≥1 sessions, CR-group) and subsequent falls (moderate or severe, using the Campbell classification system) were ascertained using the Rochester Epidemiology Project records-linkage system. Logistic model to create propensity weighting were used to test the association between CR participation and falls after adjustment for potentially confounding factors. Results A total of 5004 individuals met inclusion criteria for the study, with 2183 (44%) included in the CR group and 2821 (56%) in the non-CR group (CR was indicated, but the individual did not participate). Overall, 1122 patients experienced a fall within the first 5 years (16% of those in the CR-group, 23% of those in the non-CR group). After adjustment, CR participation was not associated with falls, but older individuals, females, and those with a history of falls were more likely to have had a fall, compared to young individuals, males, and those without a history of a fall. Conclusions While CR is beneficial for patients with cardiovascular disease, our study did not find evidence of an association between CR participation and fall risk in individuals 65 years of age and older who have cardiovascular disease. Additional research is needed to evaluate the role of CR components that may potentially reduce modifiable risk factors for falls and thereby reduce the risk of falls.

Evaluating the Effect of Activity and Environment on Fall Risk in a Paradigm-Depending Laboratory Setting: Protocol for an Experimental Pilot Study

Knowledge about the causal factors leading to falls is still limited, and fall prevention interventions urgently need to be more effective to limit the otherwise increasing burden caused by falls in older people. To identify individual fall risk, it is important to understand the complex interplay of fall-related factors. Although fall events are common, they are seldom observed, and fall reports are often biased. Due to the rapid development of wearable inertial sensors, an objective approach to capture fall events and the corresponding circumstances is provided. The aim of this work is to operationalize a prototypical dynamic fall risk model regarding 4 ecologically valid real-world scenarios (opening a door, slipping, tripping, and usage of public transportation). We hypothesize that individual fall risk is associated with an interplay of intrinsic risk factors, activity, and environmental factors that can be estimated by using data measured within a laboratory simulation setting. We will recruit 30 community-dwelling people aged 60 years or older. To identify several fall-related intrinsic fall risk factors, appropriate clinical assessments will be selected. The experimental setup is adaptable so that the level of fall risk for each activity and each environmental factor is adjustable. By different levels of difficulty, the effect on the risk of falling will be investigated. An 8-camera motion tracking system will be used to record absolute body motions and limits of stability. All laboratory experiments will also be recorded by inertial sensors (L5, dominant leg) and video camera. Logistic regression analyses will be used to model the association between risk factors and falls. Continuous fall risk will be modeled by generalized linear regression models using margin of stability as outcome parameter. The results of this project will prove the concept and establish methods to further use the dynamic fall risk model. Recruitment and measurement initially began in October 2020 but were halted because of the COVID-19 pandemic. Recruitment and measurements recommenced in October 2022, and by February 2023, a total of 25 of the planned 30 subjects have been measured. In the field of fall prevention, a more precise fall risk model will have a significant impact on research leading to more effective prevention approaches. Given the described burden related to falls and the high prevalence, considerable improvements in fall prevention will have a significant impact on individual quality of life and also on society in general by reducing institutionalization and health care costs. The setup will enable the analysis of fall events and their circumstances ecologically valid in a laboratory setting and thereby will provide important information to estimate the individual instantaneous fall risk. DERR1-10.2196/46930.

Predictive ability of a self-rated fall risk assessment tool in community-dwelling older women

BackgroundFalls are a substantial health problem among older adults. An accessible and reliable tool for assessing individual fall risk is needed.AimsThe predictive ability of a one-page self-rated fall risk assessment form (KaatumisSeula® [KS]) was evaluated among older women in its current form.MethodsA subsample (n = 384) of community-living older women (aged 72–84 years) participating in the Kuopio Fall Prevention Study (KFPS) completed the KS form. Participants’ falls were prospectively registered for 12 months with SMS messages. Their group status and form-based fall risk category were compared to the verified fall events during the KFPS intervention. Negative binomial regression and multinomial regression analyses were used. Physical performance measurements (single leg stance, leg extension strength and grip strength) were used as covariates.ResultsDuring the follow-up, 43.8% of women fell at least once. Among the fallers, 76.8% had at least one self-determined injurious fall, and 26.2% had falls requiring medical attention. According to KS, 7.6% of the women had low fall risk, 75.0% moderate, 15.4% substantial, and only 2.1% high fall risk. Women in the “moderate fall risk” group had 1.47-fold (95% CI 0.74–2.91; nonsignificant), in “substantial fall risk” 4.00-fold (1.93–8.3; p < 0.001) and in “high fall risk” 3.00-fold (0.97–9.22; nonsignificant) higher risk of falls compared to the “low fall risk” group. Performance in physical tests did not account for future falls.ConclusionsThe KS form proved to be a feasible tool for self-administered fall risk assessment with moderate predictive ability.Trial registrationClinicalTrials.gov identifier: NCT02665169, date of first registration 27/01/2016.

Validation of the Self-Assessed Dynamic Gait Index in People with Multiple Sclerosis

Background and Purpose The Dynamic Gait Index (DGI) is a validated clinical measure of walking ability in people with multiple sclerosis (MS). There is need for a self-assessed version of the DGI that can be conducted remotely and that demonstrates concurrent validity with the original DGI in people with MS. We therefore developed a self-assessed Dynamic Gait Index (sDGI). The purpose of this study is to evaluate the relationship between the sDGI, clinically-assessed DGI, and falls in people with MS with gait impairment. Methods We will enroll 50 ambulatory people with MS with gait impairment. Participants will complete the sDGI (online questionnaire) and then, within 4-weeks, the DGI (in-person evaluation by a physical therapist). Other outcome measures include: modified Telephone Interview for Cognitive Status (TICS-M) and self-reported fall history in the past 3 months. We will calculate concordance between the sDGI and DGI, and use linear regression to determine if concordance is impacted by cognition. The ability of the sDGI to identify fallers will be evaluated using the receiver operating characteristic curve. Results At time of submission, 41 participants are enrolled, 31 have completed the study. Anticipated date of study completion is March 2023. Full study results will be presented at the meeting. Discussion The sDGI has potential to be used by physicians, physical therapists, and others to remotely assess walking ability and identify fallers in people with MS. Information from this study will determine how self-assessment of walking ability compares with clinically-assessed walking ability in people with MS. Our study will also determine if cognition impacts the validity of the sDGI. If concordance between sDGI and DGI is lower in those with worse cognitive performance, users of the sDGI might exercise greater caution using this measure to approximate DGI and predict fall risk in individuals with cognitive impairment. The Dynamic Gait Index (DGI) is a validated clinical measure of walking ability in people with multiple sclerosis (MS). There is need for a self-assessed version of the DGI that can be conducted remotely and that demonstrates concurrent validity with the original DGI in people with MS. We therefore developed a self-assessed Dynamic Gait Index (sDGI). The purpose of this study is to evaluate the relationship between the sDGI, clinically-assessed DGI, and falls in people with MS with gait impairment. We will enroll 50 ambulatory people with MS with gait impairment. Participants will complete the sDGI (online questionnaire) and then, within 4-weeks, the DGI (in-person evaluation by a physical therapist). Other outcome measures include: modified Telephone Interview for Cognitive Status (TICS-M) and self-reported fall history in the past 3 months. We will calculate concordance between the sDGI and DGI, and use linear regression to determine if concordance is impacted by cognition. The ability of the sDGI to identify fallers will be evaluated using the receiver operating characteristic curve. At time of submission, 41 participants are enrolled, 31 have completed the study. Anticipated date of study completion is March 2023. Full study results will be presented at the meeting. The sDGI has potential to be used by physicians, physical therapists, and others to remotely assess walking ability and identify fallers in people with MS. Information from this study will determine how self-assessment of walking ability compares with clinically-assessed walking ability in people with MS. Our study will also determine if cognition impacts the validity of the sDGI. If concordance between sDGI and DGI is lower in those with worse cognitive performance, users of the sDGI might exercise greater caution using this measure to approximate DGI and predict fall risk in individuals with cognitive impairment.

Association of motor index scores with fall incidence among community-dwelling older people

BackgroundSeveral kinds of motor dysfunction have been studied for predicting future fall risk in community-dwelling older individuals. However, no study has tested the ability of the fine motor index (FINEA) and gross motor index (GROSSA) to predict the risk of falling, as well as the specific fall type.ObjectiveWe investigated the associations of FINEA/GROSSA scores with fall risk, explained falls, and unexplained falls.MethodsA total of 6267 community-dwelling adults aged ≥ 50 years from the Irish Longitudinal Study on Aging (TILDA) cohort were included. First, the associations of FINEA and GROSSA scores with the history of total falls, explained falls and unexplained falls were assessed in a cross-sectional study and further verified in a prospective cohort after 2 years of follow-up by Poisson regression analysis.ResultsWe found that high FINEA and GROSSA scores were positively associated with almost all fall histories (FINEA scores: total falls: adjusted prevalence ratio [aPR] = 1.28, P = 0.009; explained falls: aPR = 1.15, P = 0.231; unexplained falls: aPR = 1.88, P < 0.001; GROSSA scores: total falls: aPR = 1.39, P < 0.001; explained falls: aPR = 1.28, P = 0.012; unexplained falls: aPR = 2.18, P < 0.001) in a cross-sectional study. After 2 years of follow-up, high FINEA scores were associated with an increased incidence of total falls (adjusted rate ratio [aRR] = 1.42, P = 0.016) and explained falls (aRR = 1.51, P = 0.020) but not with unexplained falls (aRR = 1.41, P = 0.209). High GROSSA scores were associated with an increased incidence of unexplained falls (aRR = 1.57, P = 0.041) and were not associated with either total falls (aRR = 1.21, P = 0.129) or explained falls (aRR = 1.07, P = 0.656). Compared with individuals without limitations in either the FINEA or GROSSA, individuals with limitations in both indices had a higher risk of falls, including total falls (aRR = 1.35, P = 0.002), explained falls (aRR = 1.31, P = 0.033) and unexplained falls (aRR = 1.62, P = 0.004).ConclusionFINEA scores were positively associated with accidental falls, while GROSSA scores were positively associated with unexplained falls. The group for whom both measures were impaired showed a significantly higher risk of both explained and unexplained falls. FINEA or GROSSA scores should be investigated further as possible tools to screen for and identify community-dwelling adults at high risk of falling.

The predictive ability of the three times stand and walk test to determine frailty and its association with fear of falling, cognitive function in community-dwelling older adults.

The three-time stand and walk test (TTSW) is a complex functional task used to determine muscle strength, balance, and fall risk in older individuals. This study hypothesized that TTSW is an appropriate tool for detecting frailty related to falls and the cognition of community-dwelling older adults. The study objectives were to 1) assess the ability of the TTSW to determine frailty by exploring the optimal cut-off score and 2) investigate the correlations between TTSW outcomes with falls and cognitive function in 118 community-dwelling older adults. The demographic data of eligible participants were assessed, and the participants were diagnosed with frailty based on the frailty phenotype. The participants then completed the Frail Non-Disabled (FiND) Questionnaire, TTSW, Falls Efficacy Scale-International (FES-I), and Mini-Mental State Examination Thai version (MMSE-Thai 2002). The results demonstrated that the TTSW outcomes were significantly correlated with FiND, FES-I, and MMSE-Thai 2002 (rho = .705 and r = .482 and -.510, respectively, p < .001). Moreover, a TTSW time of 18 s or longer had a good ability to indicate frailty in older individuals (sensitivity = 88.41, specificity = 83.67, and area under the receiver operating characteristic curve = .926). Implementing this tool in a community setting may be useful for the initial screening, monitoring, and referral of data by healthcare professionals. A cut-off TTSW time of 18 s or longer was the optimal criterion to indicate frailty in community-dwelling older people.

Profiles of Motor-Cognitive Interference in Parkinson's Disease-The Trail-Walking-Test to Discriminate between Motor Phenotypes.

Background and Aims. Most research on Parkinson’s disease (PD) focuses on describing symptoms and movement characteristics. Studies rarely focus on the early detection of PD and the search for suitable markers of a prodromal stage. Early detection is important, so treatments that may potentially change the course of the disease can be attempted early on. While gait disturbances are less pronounced in the early stages of the disease, the prevalence, and severity increase with disease progression. Therefore, postural instability and gait difficulties could be identified as sensitive biomarkers. The aim was to evaluate the discriminatory power of the Trail-Walking Test (TWT; Schott, 2015) as a potential diagnostic instrument to improve the predictive power of the clinical evaluation concerning the severity of the disease and record the different aspects of walking. Methods. A total of 20 older healthy (M = 72.4 years, SD = 5.53) adults and 43 older adults with PD and the motor phenotypes postural instability/gait difficulty (PIGD; M = 69.7 years, SD = 8.68) and tremor dominant (TD; M = 68.2 years, SD = 8.94) participated in the study. The participants performed a motor-cognitive dual task (DT) of increasing cognitive difficulty in which they had to walk a given path (condition 1), walk to numbers in ascending order (condition 2), and walk to numbers and letters alternately and in ascending order (condition 3). Results. With an increase in the cognitive load, the time to complete the tasks (seconds) became longer in all groups, F(1.23, 73.5) = 121, p < 0.001, ɳ2p = 0.670. PIGD showed the longest times in all conditions of the TWT, F(2, 60) = 8.15, p < 0.001, ɳ2p = 0.214. Mutual interferences in the cognitive and motor domain can be observed. However, clear group-specific patterns cannot be identified. A differentiation between the motor phenotypes of PD is especially feasible with the purely motor condition (TWT-M; AUC = 0.685, p = 0.44). Conclusions. PD patients with PIGD must be identified by valid, well-evaluated clinical tests that allow for a precise assessment of the disease’s individual fall risk, the severity of the disease, and the prognosis of progression. The TWT covers various aspects of mobility, examines the relationship between cognitive functions and walking, and enables differentiation of the motor phenotypes of PD.

Epidemiology of falls in St. Petersburg (based on research by the Department of Family Medicine)

Introduction: prevention of falls and fractures in older adults is a strategic task of the geriatric service.Aim: to estimate the prevalence of falls and its risk factors, as well as their association with geriatric syndromes in St. Petersburg.Materials and methods: analysis of the results of four studies conducted in St. Petersburg between 2009 and 2019. The total number of participants was 1398 persons aged 60 years and older. Main parameters: comprehensive geriatric assessment, measurement of cardio-ankle vascular index (CAVI) using Vasera VS-1500 volumetric sphygmography computer complex, detection of silent atrial fibrillation using «MyDiagnostick 1001R» device.Results: every third person falls at the age of 65 to 74 years old, and every second person falls at the age of 85 and older. In 50% of cases, falls are accompanied by injuries. The main factors associated with a higher risk of falls were arterial hypertension, atrial fibrillation, stroke/transient ischemic attack, cognitive impairment, sensory deficits, urinary incontinence, decreased physical functioning and CAVI above predicted value. Vision correction reduced the risk of falls by 46.7%, improved/good nutrition status according to self-assessment data by 55.3%, correction of urinary incontinence by 55.8%, improved cognitive functioning by 73.3%, and eating two or more fruits and vegetables a day by 66.0%. Individualized analysis of fall risk factors and development of fall prevention programs can reduce the risk of falls by a factor of nine within the first year.Conclusion: Screening to assess the risk of falls and compiling individual fall prevention programs can significantly reduce the risk of falls in older and senile age. The effectiveness of individual fall risk reduction programs decreases after the first year of implementation. Consequently, it is necessary to conduct annual screening of older patients to assess the risk of falls and subsequent adjustment of personalized fall prevention plan.

Wearable Sensor Systems for Fall Risk Assessment: A Review.

Fall risk assessment and fall detection are crucial for the prevention of adverse and long-term health outcomes. Wearable sensor systems have been used to assess fall risk and detect falls while providing additional meaningful information regarding gait characteristics. Commonly used wearable systems for this purpose are inertial measurement units (IMUs), which acquire data from accelerometers and gyroscopes. IMUs can be placed at various locations on the body to acquire motion data that can be further analyzed and interpreted. Insole-based devices are wearable systems that were also developed for fall risk assessment and fall detection. Insole-based systems are placed beneath the sole of the foot and typically obtain plantar pressure distribution data. Fall-related parameters have been investigated using inertial sensor-based and insole-based devices include, but are not limited to, center of pressure trajectory, postural stability, plantar pressure distribution and gait characteristics such as cadence, step length, single/double support ratio and stance/swing phase duration. The acquired data from inertial and insole-based systems can undergo various analysis techniques to provide meaningful information regarding an individual's fall risk or fall status. By assessing the merits and limitations of existing systems, future wearable sensors can be improved to allow for more accurate and convenient fall risk assessment. This article reviews inertial sensor-based and insole-based wearable devices that were developed for applications related to falls. This review identifies key points including spatiotemporal parameters, biomechanical gait parameters, physical activities and data analysis methods pertaining to recently developed systems, current challenges, and future perspectives.

Locomotor Adaptation Deficits in Older Individuals With Cognitive Impairments: A Pilot Study.

Gait dysfunction and fall risk have been well documented in people with Alzheimer's Disease (AD) and individuals with mild cognitive impairment (MCI). Normal locomotor adaptation may be an important prerequisite for normal and safe community walking function, especially in older adults with age-related neural, musculoskeletal, or cardiovascular changes and cognitive impairments. The split-belt walking task is a well-studied and robust method to evaluate locomotor adaptation (e.g., the ability to adjust stepping movements to changing environmental demands). Here, we capitalized on the split-belt adaptation task to test our hypothesis that a decreased capacity for locomotor adaptation may be an important contributing factor and indicator of increased fall risk and cognitive decline in older individuals with MCI and AD. The objectives of this study were to (1) compare locomotor adaptation capacity in MCI and AD compared to healthy older adults (HOA) during split-belt treadmill walking, and (2) evaluate associations between locomotor adaptation and cognitive impairments. Our results demonstrated a significant decrease in split-belt locomotor adaptation magnitude in older individuals with MCI and AD compared to HOA. In addition, we found significant correlations between the magnitude of early adaptation and de-adaptation vs. cognitive test scores, demonstrating that individuals with greater cognitive impairment also display a reduced capacity to adapt their walking in response to the split-belt perturbation. Our study takes an important step toward understanding mechanisms underlying locomotor dysfunction in older individuals with cognitive impairment.