Jethro Raphael Manio Suarez

Purpose: In the rapidly growing older adult demographic, falls are a critical issue as the leading cause of injury. Multifactorial interventions have been shown to improve fall risk, including physical function and fear of falling. This study evaluates the effect of the Physio-fEedback and Exercise pRogram (PEER), an 8-week multifactorial technology-based fall risk intervention. Methods : The longitudinal study included 387 community-dwelling, low-income older adults and was conducted at 4 timepoints at T1 (baseline), T2 (2 months), T3 (4 months), and T4 (6 months). The Timed Up and Go Test, 30-second chair stand test, and BTrackS Score were used as measures of physical function (dynamic balance, lower limb endurance, and static balance, respectively). The PEER intervention consisted of an 8-week technology-based physio-feedback, cognitive reframing, and group-based and at-home exercises (NCT05778604). Results: The PEER intervention mitigated time-related declines in dynamic balance post-intervention ( p <0.001) and subsequent follow-up ( p =0.005). Lower limb endurance and static balance did not show significant improvements. Conclusion: The intervention group showed sustained improvement of dynamic balance, indicating effectiveness of PEER after conclusion of the intervention. However, the lack of significant differences in the other fall risk metrics may be indicative of insufficient duration and/or intensity of the intervention. This study demonstrates both potential for the PEER technology-based mind-body fall prevention for improving dynamic balance and gaps in targeting measures of fall risk. Trial Registration: The trial was registered at ClinicalTrials.gov on March 21, 2023 (NCT05778604).

Frailty is a highly prevalent and adverse syndrome among older adults, and there are many different assessments for screening both frailty (robust + pre-frail vs. frail) and frailty process (robust vs. pre-frail + frail). Previous studies have suggested that the Short Physical Performance Battery (SPPB) can be used as a quick screening tool for frailty, demonstrating excellent agreement when compared to Fried’s phenotype as a criterion. However, to the best of our knowledge, no study has assessed the SPPB’s diagnostic accuracy using the FRAIL questionnaire as the criterion. In this cross-sectional study, we compared frailty (SPPB ≤ 8) and frailty process (SPPB ≤ 10) classifications for 371 community-dwelling older adults (≥60 yrs) by the SPPB to the FRAIL questionnaire using McNemar tables and a receiver operator characteristic analysis. The SPPB and the FRAIL questionnaire significantly differed in their appraisal of both frailty and frailty process (p < 0.001). For frailty, the SPPB scored a sensitivity of 62.9%, a specificity of 78.6%, and an area under the curve of 0.78. In addition, for the frailty process, the SPPB scored a sensitivity of 77.6%, a specificity of 55.3%, and an area under the curve of 0.70. The SPPB demonstrated limited diagnostic accuracy compared to the criterion FRAIL questionnaire. Our findings indicate that the SPPB should not be the sole method of assessing frailty among older adults. To address the complexity of frailty, clinicians should attempt to implement multiple assessments that combine biological, social, and functional aspects of frailty. Pre-registered on ClinicalTrials.gov (NCT05778604).

Background/Objectives: This study aimed to assess the impact of a physio-feedback exercise program (PEER) on the static balance of community-dwelling older adults. Methods: A clustered randomized controlled trial involving community-dwelling older adults (≥60 years of age) in the Central Florida area was conducted. Participants were randomized by research site into either (1) an 8-week exercise intervention program consisting of group-based and at-home exercises, along with a discussion with a researcher regarding their physiological health before and after the intervention period, or (2) a control group. Static balance outcomes included anterior–posterior root mean square (AP RMS), medial-lateral RMS (ML RMS), sway speed variability, and sway area measured using the Balance Tracking System (BTrackS) at baseline (T1), post-intervention (T2), one-month post-intervention (T3), and three months post-intervention (T4). Results: Among 373 community-dwelling older adults (mean age = 74.3 ± 7.1 years), a trend towards short-term improvement of sway area was observed for the intervention group, as seen through a small, marginally significant reduction in sway area at T2 (standardized β = −0.07; p = 0.050). However, the trend dissipated during post-intervention follow-up periods (T3 and T4). Sway speed variability significantly increased for the intervention group at T4 (standardized β = 0.10; p = 0.014). Conclusions: The PEER intervention may need to increase the total duration of the intervention, the frequency of the weekly exercise sessions, and the amount of standing stance exercises during the group-based and at-home exercise sessions to elicit improvements in static balance among older community-dwelling adults.

Introduction: Accelerometers are a common method of direct activity measurement, but the continuous release of newly developed accelerometer device models warrant comparison with previously validated models. The performance of the ActiGraph LEAP, the successor to the widely used ActiGraph GT9X Link, has rarely been compared directly with other accelerometer models. Methods: Healthy young adults wore both the ActiGraph LEAP and GT9X Link on their non-dominant wrist for seven consecutive days in free-living conditions. An open-source R package (GGIR) was utilized to quantify activity from raw accelerometer data. Raw accelerometer data files were resampled to a common sample rate (30 Hz) and timestamp matched by minute. Aggregated activity metrics, specifically average daily acceleration and peak 30-minute acceleration, were compared through intraclass correlation coefficients (ICC2,1), mean absolute percent error (MAPE), and equivalence tests utilizing ±10% equivalence bounds. Bland-Altman plots visualized agreement. Results: A total of 25 young adults were included (21.2 ± 4.0 years) with an average of 4.1 days of valid wear (≥ 10 hours). Both activity metrics exhibited good to excellent agreement, low MAPE values (<10%), and passed equivalency tests. Additionally, significant proportional bias was not found when analyzing the Bland-Altman plots for each activity metric. Conclusions: The performance of the ActiGraph LEAP is comparable to that of the ActiGraph GT9X Link among healthy young adults, as seen through comparison of aggregated acceleration metrics quantified using the GGIR method.

Introduction: Despite the sit-to-stand transition being an acute period of increased fall risk among older adults, it is currently unclear how lower-limb joint range-of-motion (ROM) during this task relates to fall risk. Methods: We examined 45 community-dwelling older adults (female = 32 (71.1%), age = 76.5±6.1years, BMI = 26.4±4.0kg/m2) within this cross-sectional study, assessing lower-limb mobility during 10 seconds of sit-to-stand repetitions using a single camera marker-less system. Hip and knee flexion, hip adduction, and ankle dorsiflexion were assessed for the right and left limbs, as well as asymmetry indices between sides. Fall risk was assessed using the STEADI checklist, Short Physical Performance Battery (SPPB), lower-body muscular power, postural sway, the Short Fall Efficacy Scale-International (FES-I), and 4-meter walking gait speed. Spearman’s rho (ρ) and Kruskal Wallis H-test were used due to nonnormal data distributions. Results: High fall risk participants had significantly lower muscular power (2.8±0.6W/kg, p = 0.004, ε2 = 0.187) and higher knee flexion asymmetry (4.5±2.5°; p = 0.021, ε2 = 0.121) than low fall risk participants (3.6±1.0W/kg; 2.9±2.4°). All correlations between joint movements and fall risk assessments were relatively small/weak (ρ ≤ |0.38|). Hip flexion asymmetries were significantly correlated with SPPB performance (ρ = -0.33, p = 0.03) and Short FES-I scores (i.e., fear of falling; ρ = 0.35, p = 0.02). Conclusions: Lower-limb ROM during the sit-to-stand transition may not be a strong indicator of fall risk on its own but may provide clinically relevant insight when paired with a validated fall risk assessment.

Background/Objective : Group exercise is a common fall risk intervention among older adults. However, many older adults approach exercise adoption with knowledge of their current physiological health (i.e., physio-feedback), which may influence the expected changes in physical function and body composition. We compared changes in body composition, bioimpedance (phase angle, impedance ratio, etc.), and physical function (Short Physical Performance Battery; handgrip strength) between a physio-feedback-based intervention and a control group among community-dwelling older adults. Methods : We assessed 186 participants (female = 88%, age = 74.1 ± 6.8 years, body mass index = 30.5 ± 6.5 kg/m ² ) during an 8-week cluster-randomized controlled trial. The physio-feedback-based intervention included a one-on-one physio-feedback debrief session following baseline testing, once weekly 60-min group classes, and 60 min of at-home exercises per week. Data were analyzed using a linear mixed-effects model with clustered sites and individual participants as random coefficients. Intervention adherence was monitored via in-class attendance and at-home exercise logs. Results: We observed significant interaction effects with phase angle and impedance ratio ( p < .05) and significant time effects for Short Physical Performance Battery scores, handgrip strength, and bioelectrical resistance ( p < .05). Participants demonstrated good-to-excellent adherence to the in-person group class (80.9 ± 20.0%) and at-home exercises (71.8 ± 26.9%). Conclusion: The present form of this physio-feedback-based exercise intervention may not provide sufficient stimulus to improve body composition and physical function, but may mitigate decrements in phase angle and impedance ratio. Significance/Implications: The high adherence rate suggests that the intervention has potential for future applications in community settings. Clinicians and community partners aiming to implement physio-feedback-based exercise interventions may need to modify the protocol to elicit desired adaptations. ClinicalTrials.gov (NCT05778604).

Background : The ActiGraph GT9X Link wearable accelerometer has been widely utilized for physical activity (PA) measurement but is no longer in production. The performance of the ActiGraph LEAP, regarded as its successor and released in 2023, remains unevaluated in comparison to other accelerometers. This study aimed to establish concurrent validity of the ActiGraph LEAP device through PA measurements and comparison with the GT9X Link. Methods : A total of 26 young adults (mean age = 21 ± 4 years) wore the ActiGraph LEAP and GT9X Link simultaneously for 7 consecutive days on their nondominant wrist. Monitor Independent Movement Summary units were utilized for calculation of daily sedentary time, light PA, and moderate to vigorous PA across valid days of wear (≥10 hr). Nonwear time was determined using a preexisting algorithm. Intraclass correlation coefficient, mean absolute percent error, equivalence tests (with GT9X Link as reference), and Bland–Altman plots assessed agreement between daily values of sedentary time, light PA, and moderate to vigorous PA recorded by each device across all valid days recorded among participants. Results : A total of 149 days of data were compared between the two devices. Across all PA levels, acceptable-excellent agreement was found (mean absolute percent error = 3.86%–13.86% and intraclass correlation coefficient = .94–.99), and Bland–Altman plots showed that at least 90% of recorded data fell within the 95% limits of agreement. Conclusions : The findings suggest that sedentary time and PA measurements using Monitor Independent Movement Summary units from the ActiGraph LEAP compare well with the GT9X Link, indicating that the LEAP performs similarly to the GT9X Link.

The fall risk appraisal (FRA) matrix provides multidimensional approaches to detecting falls in late adulthood. This study investigated a modified FRA (mFRA) matrix based on self-assessed fall risk (SFR) and fear of falling (FOF). We also compared the mental health and characteristics of the four mFRA groups: Rational (low SFR and low FOF), Irrational (low SFR and high FOF), Incongruent (high SFR and low FOF), and Congruent (high SFR and high FOF). This study used data from 181 older adults (MeanAge = 74.58, SDAge = 7.13) in Central Florida. SFR was measured using the CDC Stopping Elderly Accidents, Deaths, and Injuries fall checklist. FOF was measured using the Short Fall Efficacy Scale-International. Descriptive and group comparison analyses were performed using SPSS. The participants were categorized: Rational (n = 80, 44.2%), Irrational (n = 12, 6.6%), Incongruent (n = 26, 14.4%), and Congruent (n = 63, 34.8%). Rational showed better mental health, fewer falls, and higher health literacy. In contrast, Congruent reported worse mental health, more falls, and lower health literacy. Findings provided empirical evidence to design fall prevention and interventions that consider older adults' experiential and psychological fall risks. Fall risks of older adults may be measured and comprehended as a multidimensional concept.

Background: Depression is prevalent among older adults and is known to negatively affect balance, ultimately leading to falls. However, few studies have investigated the effect of depression on static balance metrics beyond postural sway distance and area of older adults without mild cognitive impairment (MCI). Aims: To investigate if postural sway distance, sway area, medial-lateral (ML) sway range, anterior-posterior (AP) sway range, and center-of-pressure (COP) sway speed variability differed between non-cognitively impaired older adults with minimal-to-no depression (Minimally Depressive group) and mild-to-severe depression (Mildly-to-Severely Depressive group). Methods: A total of 204 community-dwelling older adults were included. Depression was measured using the Patient Health Questionnaire-9 (PHQ-9), MCI using the Rowland Universal Dementia Assessment Scale (RUDAS), and static balance metrics using the Balance Tracking System (BTrackS). Mann-Whitney U tests determined differences between groups. Results: Sway area, AP sway range, and ML sway range were significantly greater in the Mildly-to-Severely Depressive group than the Minimally Depressive group (p = 0.010, p = 0.016, and p = 0.031, respectively). Sway distance (p = 0.445) and COP sway speed variability (p = 0.193) were not significantly different between groups. Discussion: The findings revealed greater sway area, as well as greater ranges in the AP and ML directions, in the Mildly-to-Severely Depressive group when compared to the Minimally Depressive Group. Reduced concentration and affected postural stabilization mechanisms driven by depression may have attributed to these results. Conclusions: This study highlights the need for further understanding of how static balance metrics, such as directional sway, are affected by depression, thereby creating interventions tailored to individual’s postural sway characteristics to help reduce fall risk and improve balance. Trial registration: ClinicalTrials.gov (NCT05778604).

The Fall Risk Appraisal Matrix (FRAM) is a simple fall risk assessment tool that categorizes older adults into four separate groups based on their fear of falling (FOF) and static balance performance. Static balance for the FRAM is evaluated solely by postural sway distance, which does not account for other static balance parameters, such as sway area, anterior–posterior (AP) sway range, medial–lateral (ML) sway range, and sway velocity. The objective of this study was to compare these additional metrics across the FRAM groups to assess their relevance and validity for inclusion in static balance performance assessment. Hence, these measures were compared among the four different fall risk groups within the FRAM (203 participants; mean age = 75.0 ± 7.2 years) using Kruskal–Wallis test, followed by Dunn’s post hoc tests with Bonferroni correction. All balance metrics were significantly greater in the Incongruent (poor balance/low FOF) and Congruent (poor balance/high FOF) groups than the Rational (good balance/low FOF) group, as well as in the Congruent group than the Irrational (good balance/high FOF) group (p < 0.001). Additionally, AP sway range and sway velocity significantly differed between the Irrational and Incongruent groups (p < 0.001). The results suggest that the inclusion of these additional static balance measures, in addition to sway distance, reveals specific tendencies in static balance among different fall risk groups, which can serve as a reference for other researchers and future studies to develop more individually tailored intervention programs based on their static balance specificities.