Effects of a Multimodal Exercise Program on Functional Outcomes and Fall Risk in Physically Active Older Adults: A Longitudinal Study

Effects of a Multimodal Exercise Program on Functional Outcomes and Fall Risk in Physically Active Older Adults: A Longitudinal Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Effects of a Multimodal Exercise Program on Functional Outcomes and Fall Risk in Physically Active Older Adults: A Longitudinal Study Vanessa Santos, Joana Serpa, José Mira, Estela São Martinho, Henrique Seita, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8262744/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Falls remain a public health concern among physically active older adults. This study examined the long-term effects of a three-year supervised multimodal exercise program on functional, psychological, and fall-related outcomes in active community-dwelling older adults. Methods: Twenty-nine participants (mean age 72.0 ± 4.9 years) were assessed annually for three years. Functional measures included gait speed/cadence, TUG, 5xSTS, handgrip strength, and balance (SF-FAB). Psychological parameters (FES-I, ABC) and fall-related variables were also evaluated. Results: Significant improvements were observed in gait speed, cadence, TUG, handgrip strength, and balance. Lower-limb strength remained stable. Psychological scores did not change significantly but remained high. Falls and balance complaints decreased over the first two years. Conclusions: Long-term participation in supervised multimodal exercise promotes meaningful functional improvements and may prevent falls, even in active older adults. These findings support its integration into community-based aging and fall prevention strategies. Health sciences/Health care Health sciences/Risk factors older adults multimodal exercise fall prevention functional fitness balance confidence Introduction The demographic shift toward an aging population is one of the most pressing global public health challenges of the 21st century. According to recent projections, individuals aged 65 years and older will comprise over 30% of the Portuguese population by 2050 [ 1 ], a trend echoed globally. This demographic transformation is associated with a rise in chronic conditions, functional decline, and, notably, an increased risk of falls, recognized as one of the leading causes of injury, disability, and mortality in older adults [ 2 , 3 ]. Falls are defined as “an event which results in a person coming to rest inadvertently on the ground or floor or other lower level” [ 4 ]. Falls among older adults represent one of the most complex and pervasive syndromes in geriatric health, emerging from an intricate interplay of physiological, psychological, behavioral, and environmental determinants. Intrinsic factors such as sarcopenia, impaired postural reflexes, neuromuscular degeneration, vestibular and visual deterioration, and delayed reaction times collectively diminish the body’s capacity to maintain balance and recover from perturbations [ 5 , 6 ]. Simultaneously, extrinsic contributors, ranging from poorly adapted home environments and uneven surfaces to inadequate lighting and the cumulative effects of polypharmacy, further amplify vulnerability [ 4 , 7 ]. Even seemingly minor obstacles can become critical threats when combined with age-related decline. Epidemiological data consistently show that nearly one in three community-dwelling individuals aged 65 and older will experience at least one fall each year, and alarmingly, up to half of these individuals become recurrent fallers [ 4 , 7 ]. These are not isolated events: each fall often initiates a downward spiral of fear, reduced activity, functional decline, and increased dependence. The personal consequences extend far beyond physical injury, as they include psychological distress, social withdrawal, and a loss of confidence in one’s own body. Moreover, the societal burden is immense: falls account for a substantial proportion of hospital admissions among older adults, place intense pressure on rehabilitation services, and contribute significantly to long-term care institutionalization [ 8 ]. From an economic perspective, falls represent a costly challenge to healthcare systems worldwide. The cumulative costs associated with emergency care, surgical interventions, post-acute rehabilitation, and ongoing assistance can be staggering, particularly in aging societies. More importantly, these incidents often mark the transition from independent living to chronic disability and institutional care, dramatically altering the trajectory of aging. As such, falls are not merely a clinical issue, they are a sentinel event signaling frailty, functional loss, and systemic gaps in prevention. Understanding and addressing falls through this broader lens is essential. It requires integrated strategies that go beyond symptom management, tackling the root causes across biological systems and daily environments. In this context, exercise emerges as one of the most powerful, cost-effective, and accessible interventions available to break this cycle. An expanding body of evidence underscores the critical role of both physical fitness and psychological resilience in modulating fall risk among older adults. While falls are often perceived as random and unpredictable, research consistently reveals that they are, in fact, strongly associated with measurable declines in functional capacity, particularly lower-limb strength, postural control, gait speed, and dynamic balance [ 9 , 10 ]. These physical parameters are fundamental to performing everyday tasks safely and efficiently. However, the narrative regarding fall risk is incomplete without addressing the psychological dimension. Constructs such as fall efficacy (the perceived ability to avoid falls) and balance confidence have emerged not as secondary factors but as central predictors of fall occurrence, especially in community-dwelling and even physically active populations [ 11 , 12 ]. Indeed, recent research has revealed that in some cohorts, psychological variables may surpass physical markers in their predictive power. Fall efficacy and balance confidence exhibited a stronger association with fall risk than objective measures like handgrip strength [ 11 ]. This finding aligns with broader gerontological models that highlight the interconnectedness of physical and psychological systems in aging, suggesting that fear of falling and lack of confidence can directly influence gait patterns, limit physical activity, and initiate a cycle of deconditioning and functional decline. In this context, fall prevention must go beyond mere objective measurements; it must address the mindset and emotional state of the individual. In response to this multifactorial understanding of falls, interventions that simultaneously address multiple physical domains, such as strength, endurance, agility, and balance, have gained prominence. These multicomponent or multimodal exercise programs are not merely additive in nature; they are synergistic. By targeting the diverse systems involved in fall prevention, they foster neuromuscular coordination, improve proprioception, and enhance the adaptability of motor responses to unexpected challenges. Both the World Health Organization [ 13 ] and the American College of Sports Medicine [ 14 ] strongly advocate for the inclusion of such comprehensive programs in public health strategies for older adults. Systematic reviews and large-scale meta-analyses support their effectiveness, showing reductions in fall incidence of up to 40% in older adults living in the community [ 15 , 16 , 17 ]. Despite these advances, most of the existing evidence comes from studies with short intervention durations or cross-sectional snapshots. These designs, while valuable, fall short of capturing the long-term sustainability and cumulative impact of exercise interventions, particularly in those who are already physically active. Older adults who engage in regular physical activity may present higher functional baselines, but they are not immune to the physiological effects of aging. In fact, this population may often be overlooked in fall prevention initiatives under the assumption that their risk is lower, when their needs may differ in nature but not in emergency [ 18 ]. There remains a critical gap in the literature concerning the longitudinal effects of structured, supervised multimodal exercise programs in maintaining or enhancing function and reducing fall risk in this subgroup. Understanding how this active population responds over time to targeted interventions may be the key to designing tailored strategies that are both preventive and performance-preserving. The present study aims to address this gap by investigating the longitudinal impact of a supervised multimodal exercise program on fall-related outcomes in community-dwelling older adults over a three-year period, with particular attention to the role of psychological engagement and consistent exposure in sustaining its benefits. Methods 2.1 Participants Twenty-nine participants were recruited from a community-based exercise program and were required to meet the following inclusion criteria: aged 55 years or older, maintaining a physically active lifestyle within the community, attending the structured group exercise sessions at least twice per week, and have the functional autonomy to move independently without external assistance. Exclusion criteria included any medical contraindications to engaging in physical activity or conditions that could interfere with the safe execution of functional fitness assessments on the day of evaluation. 2.2 Exercise Program Protocol Although the exercise intervention was not directly controlled by the research team, participants were enrolled in a structured, municipality-run community-based program. The program consisted of multimodal training sessions held twice per week, each lasting approximately 60 minutes. The sessions targeted various physical domains, including strength, balance, mobility, coordination, and endurance, and were conducted in group format under the supervision of trained exercise professionals. The general structure and regularity of the sessions were monitored by local authorities, but individual attendance and exercise intensity were not recorded. 2.3 Instruments and Variables This study employed a multidimensional evaluation protocol, incorporating anthropometric, physical, and psychological variables known to be associated with fall risk in older adults. Assessments were conducted under standardized conditions by trained professionals to ensure consistency and reliability of the data across timepoints. Data were collected at three timepoints: December 2022 (baseline), December 2023 (2nd evaluation), and December 2024 (3rd evaluation). 2.3.1 Anthropometric and Demographic Variables Sociodemographic data were collected through structured interviews and included age (in years), sex (male/female), number of self-reported comorbidities (e.g., hypertension, diabetes, osteoarthritis), and total number of medications taken daily, as polypharmacy is a recognized contributor to fall risk. Body weight was measured using a SECA 761 mechanical scale (Bacelar & Irmão Lda, Portugal), with participants wearing light clothing and no shoes. Height was self-reported. Both measures were recorded to the nearest 0.1 kg and 0.1 cm, respectively. Body Mass Index (BMI) was subsequently calculated using the standard equation: BMI= body weight(kg)/ height (m)2. 2.3.2 Fall History and Risk Classification To assess prior fall events, participants were interviewed using a standardized questionnaire adapted from the American Geriatrics Society & British Geriatrics Society Clinical Practice Guidelines [19]. They were asked the following questions: 1. “In the past 12 months, how many times have you fallen?” 2. “If you have fallen, did you require any medical attention?” 3. “Did the fall result in any difficulty with walking or maintaining balance?” Participants were classified based on their responses as non-fallers, single fallers, or recurrent fallers (≥2 falls in the past year). These distinctions were used to stratify fall risk in subsequent analyses. 2.3.3 Physical Performance Measures All physical fitness tests were administered in accordance with published protocols and were selected based on their clinical validity, reproducibility, and feasibility in community settings. Gait speed and cadence were assessed using a 15-meter walk test following the protocol by Rikli and Jones [20]. Participants were instructed to walk at their usual pace along a flat 15-meter corridor. To exclude the influence of acceleration and deceleration, only the central 9 meters were timed. Speed was expressed in meters per second (m/s), while cadence was expressed in steps per second (steps/s). A gait speed < 0.8 m/s was used as a cutoff for elevated fall risk, based on normative data for older adults [21]. Agility and Mobility were assessed using the 8-Foot Up-and-Go test. Participants began seated in a chair placed near a wall, with a marker positioned 2.44 meters in front. At a verbal cue, they were instructed to rise from the chair, walk to the marker, circle it, return to the chair, and sit down as quickly as possible. Timing started with the cue and stopped once the participant was fully reseated [20]. Completion time (s) was recorded; higher times indicate poorer functional mobility. The measure was treated as a continuous variable; no fall-risk cut-offs were applied to 8UG. Lower-Limb Strength was assessed by Five Times Sit-to-Stand (5xSTS), a component of the Short Physical Performance Battery (SPPB) [22]. Participants were instructed to rise from a chair and sit back down five times as quickly as possible with arms folded across the chest. A digital stopwatch was used for timing. Risk thresholds were: ≤13 seconds: low risk; 14–17 seconds: moderate risk; ≥18 seconds: high risk [23]. Handgrip Strength (HGS) was assessed using a Jamar hydraulic dynamometer (Lafayette Instrument Company, USA), following the standardized protocol recommended by the American Society of Hand Therapists (ASHT). Participants were seated on a chair without armrests, with their shoulders adducted and neutrally rotated, elbow flexed at 90°, forearm in a neutral position, and wrist slightly extended (0–30°). They were instructed to squeeze the dynamometer as hard as possible for 3 to 5 seconds. Three trials were performed for each hand, alternating sides, with a rest interval of 30 seconds between attempts to minimize fatigue. The maximum value obtained from the dominant hand was recorded for analysis, as it has been shown to be the most reliable indicator of general upper-limb strength and overall functional capacity in older adults. Cut-off points suggesting reduced strength and potential functional impairment were considered according to normative data proposed by Cruz-Jentoft (2019), with values <27 kg for men and <16 kg for women associated with increased risk of disability and frailty [24]. Static and dynamic balance was assessed using the short version of the Fullerton Advanced Balance Scale (SF-FAB) [25], which includes four tasks, each scored from 0 to 4 points, for a maximum total of 16 points. The tasks were: (1) Transpose a 15 cm bench - the participant must place their dominant foot on the top of the bench and pass the opposite leg directly over it, resting the contralateral limb on the floor on the opposite side, repeating the movement with the opposite leg. (2) Walking in a straight line - this test assumes that the participant walks in a straight line on the floor, placing their heel on the tip of the opposite foot until they have completed a total of 10 steps. (3) Single-leg balance - the participant must stand, cross their arms over their chest and lift their preferred leg off the ground, without touching the other leg, holding this position with their eyes open for as long as possible. (4) Standing on foam with eyes closed - assumes that the participant can stand with arms crossed over chest and eyes closed in bipodal balance on foam for 20 seconds, or until loss of balance. A total score ≤ 9 points out of 16 is classified as a high risk of falling [25]. 2.3.4 Psychological Measures To evaluate psychological constructs associated with fall risk, two validated self-report questionnaires were employed: the Falls Efficacy Scale – International (FES-I) and the Activity-Specific Balance Confidence (ABC) Scale. Both tools have demonstrated predictive value for falls in older adults and are considered essential components in multidimensional fall risk assessment models. Fear of falling was measured using the Portuguese version of the Falls Efficacy Scale – International (FES-I), a widely used instrument developed to assess concern about falling across a variety of daily life situations. The scale comprises 16 items, each reflecting a common activity, such as walking around the house, using public transport, or going up or down stairs [26]. Participants were instructed to indicate their level of concern about the possibility of falling while performing each activity, using a 4-point Likert-type scale: 1 = Not at all concerned; 2 = Somewhat concerned; 3 = Fairly concerned; 4 = Very concerned. The total FES-I score is obtained by summing the responses, with higher total scores indicating greater fear of falling and reduced self-efficacy in managing daily physical tasks without experiencing a fall. This measure has been validated in the Portuguese population of older adults, showing strong internal consistency and construct validity. Elevated FES-I scores have been linked to activity restriction, deconditioning, and higher incidence of falls in prospective studies. The Activity-Specific Balance Confidence (ABC) Scale was used to assess participants’ self-perceived confidence in maintaining balance during functional tasks of varying complexity and environmental demands. The ABC comprises 16 activity-based items, including reaching overhead, walking on uneven surfaces, or stepping onto an escalator. Participants rated their confidence in completing each activity without losing balance or becoming unsteady, using a visual analogue scale from 0% to 100%, where: 0% = No confidence at all; 100% = Completely confident. The final ABC score is calculated by averaging 16 responses, yielding a mean percentage score that reflects the individual’s overall balance confidence. Lower ABC scores are indicative of greater balance anxiety and have been consistently associated with increased fall risk, functional limitations, and avoidance behaviors. This scale has been validated in Portuguese older adults [27], and its integration into fall risk assessment is supported by the literature due to its sensitivity in detecting subtle changes in psychological readiness for mobility. Combined, these two instruments, the Falls Efficacy Scale – International (FES-I) and the Activity-Specific Balance Confidence (ABC) Scale, offer a thorough assessment of psychological factors associated with fall risk. They complement objective physical evaluations, contributing to a more comprehensive and holistic understanding of fall risk among older adults living in the community. 2.4 Statistical Analysis All statistical analyses were conducted using IBM SPSS Statistics version 28.0 (IBM Corp., Armonk, NY, USA). Descriptive statistics were used to characterize the sample at baseline, presenting means, standard deviations, and percentages for sociodemographic and clinical variables such as age, sex, height, body weight, BMI, number of comorbidities, and medication use. Normality was evaluated using the Shapiro–Wilk test. Since most variables did not satisfy the normality assumptions, non-parametric statistical methods were employed. To examine changes over time across the three evaluation moments (baseline, 1-year, and 2-year follow-up), the Friedman test was used for repeated measures. This analysis included the Timed Up and Go (TUG) test, Gait Speed (GS), Five Times Sit-to-Stand Test (5xSTS), handgrip strength, the Short Fullerton Advanced Balance (SF-FAB) scale, and two psychological outcomes—the Falls Efficacy Scale – International (FES-I) and the Activity-Specific Balance Confidence (ABC) scale. Post hoc comparisons were conducted using the Wilcoxon signed-rank test, with Bonferroni correction for multiple comparisons. A significance level of p < 0.05 was adopted for all tests, and Kendall’s W was calculated as an effect size measure. The global risk classification (low vs high) was compared between the three evaluation moments using the McNemar test, to determine changes in risk category distribution over time. To assess the clinical significance of physical performance changes, the proportion of participants achieving the Minimal Clinically Important Difference (MCID) in gait speed (Δ ≥ 0.1 m/s), SF-FAB (Δ ≥ 1 point), and TUG (Δ ≤ −0.8 s) was calculated. Additionally, associations between achieving MCID and fall risk classification at the third year were analyzed using Fisher’s exact test. Differences in physical performance changes (ΔGS, ΔTUG, ΔSF-FAB) between fall risk categories (baseline, 1-year, and 2-year follow-up) were assessed using the Mann–Whitney U test. Finally, to explore the relationship between physical and psychological changes, Spearman’s rank correlation coefficient (rs) was calculated between changes in physical performance (ΔGS, ΔTUG, ΔSF-FAB) and psychological outcomes (ΔFES-I and ΔABC). In cases of missing data, pairwise deletion was applied to maximize the number of valid cases without introducing systematic bias. Results A total of 29 active older adults participated in the study. The majority were female (59%), with a mean age of 71.7 ± 5.7 years old. Participants presented with an average height of 1.57 ± 8.4 m and body weight of 68.7 ± 11.3 kg, resulting in a mean BMI of 27.6 ± 3.9 kg/m², which corresponds to the lower range of the overweight classification. Regarding health-related variables, participants reported an average of 1.3 ± 1.3 comorbidities and were taking an average of 2.4 ± 1.8 medications. These baseline data reflect a heterogeneous but functionally independent older adult population actively engaged in community-based exercise programs (Table 1 ). Table 1 Sociodemographic and clinical characteristics of the sample by sex at baseline Variables Total (n = 29) Male (n = 9) Female (n = 20) Age (years) 71.72 ± 5.68 72.00 ± 5.65 71.60 ± 5.82 Body Weight (kg) 68.72 ± 11.25 77.00 ± 10.44 65.00 ± 9.67 Height (m) 1.57 ± 8.36 1.66 ± 5.20 1.54 ± 6.62 BMI (kg/m 2 ) 27.59 ± 3.87 28.04 ± 4.65 27.39 ± 358 No. of medications 2.62 ± 2.07 3.56 ± 2.45 2.20 ± 1.80 No. of comorbidities 2.10 ± 1.26 3.56 ± 2.45 2.20 ± 1.80 Table 2 presents the descriptive data related to fall occurrences and associated clinical implications over the three-year follow-up period. At baseline (2022), 86.2% of participants reported not having experienced any falls in the previous 12 months. A small proportion reported one fall (6.9%), two falls (3.4%), or three or more falls (3.4%). By 2023, 79.3% of the sample remained fall-free, while 13.8% experienced one fall, and 6.9% reported two falls. In 2024, the proportion of participants with zero falls remained high (72.4%), with a modest increase in those reporting one (17.2%) or two falls (10.3%). Importantly, no participants reported three or more falls in the final year. When stratified by sex, all male participants reported no falls at baseline. However, by 2023, 22.2% of men reported one fall, and 11.1% did so again in 2024. Among females, the proportion of fallers was consistently higher: 20% reported one or more falls at baseline, 20% in 2023, and 35% in 2024. Regarding the need for medical intervention following a fall, only one participant in each follow-up year (3.5% in 2023 and 2024) required medical assistance, indicating low severity of fall-related injuries in this cohort. As for self-reported problems with balance or gait, 48.3% of participants indicated such issues at baseline. However, this proportion decreased notably to 27.6% in 2023 and remained relatively low in 2024 (37.9%), suggesting an improvement in perceived functional capacity. Among males, the prevalence of balance/mobility issues dropped from 33.3% in 2022 to just 11.1% in subsequent years. Among females, although 55% reported issues in 2022, the prevalence decreased to 35% in 2023 and stabilized at 50% in 2024. Table 2 Descriptive and inferential data on Fall History, Medical Intervention, and Self-Reported Balance/Gait Problems Across the Three-Year Follow-Up (2022–2024) Total (n = 29) Male (n = 9) Female (n = 20) Year 2022 Year 2023 Year 2024 p-value Year 2022 Year 2023 Year 2024 Year 2022 Year 2023 Year 2024 How many times have you fallen in the past 12 months? 0 falls 25 persons (86.2%) 23 persons (79.3%) 21 persons (72.4%) p = 0.651 9 (100%) 7 (77,8%) 8 (88,9%) 16 (80%) 16 (80%) 13 (65%) 1 fall 2 persons (6.9%) 4 persons (13.8%) 5 persons (17.2%) 0 (0%) 2 (22,2%) 0(0%) 2 (10%) 2 (10%) 5 (25%) 2 falls 1 person (3.4%) 2 persons (6.9%) 3 persons (10.3%) 0 (0%) 0 (0%) 1 (11,1%) 1 (5%) 2 (10%) 2 (10%) 3 falls 1 person (3.4%) 0 persons (0%) 3 persons (10.3%) 0 (0%) 0 (0%) 0 (0%) 1 (5%) 0 (0%) 0 (0%) If yes, did you require medical attention? Yes 0 persons (0%) 1 person (3.45%) 1 person (3.4%) NA 0 (0%) 0 (0%) 0 (0%) 0 (0%) 1 (5%) 1 (5%) No 29 persons (100%) 28 persons (96.55%) 28 persons (82.8%) 9 (100%) 9 (100%) 9 (100%) 9 (100%) 19 (95%) 19 (95%) Do you have balance or gait problems? Yes 14 persons (48.3%) 8 persons (27.6%9 11 persons (37.93%) NA 3 (33,3%) 1 (11,1%) 1 (11,1%) 11 (55%) 7 (35%) 10 (50%) No 15 persons (51.75%) 21 persons (72.4%) 18 persons (62.07%) 6 (66,7%) 8 (88,9%) 8 (88,9%) 9 (45%) 13 (65%) 10 (50%) Legend: NA- not applicable; * p < 0.05 significant to assess changes in fall frequency distribution across the three years. The analysis of the global fall risk across the three-year follow-up showed no statistically significant differences between time points. From baseline to the first year, 25% of participants initially classified as high risk transitioned to low risk, whereas 15.6% of those initially at low risk worsened to high risk (McNemar, p = 0.727). From the first to the second year, all participants initially at high risk migrated to low risk, while 17.2% of those at low risk worsened (McNemar, p = 1.000). Similarly, when comparing baseline to the third year, 71.4% of participants initially at high risk transitioned to low risk, and 13.5% of those at low risk progressed to high risk (McNemar, p = 1.000). These observations indicate a potential trend towards risk reduction, although no statistically significant changes were observed (Table 3 ). Table 3 Change in global fall risk from baseline to the third year of follow-up. 2022–2024 year Low Risk 3rd Year (n, %) High Risk 3rd Year (n, %) Total Low Risk Baseline 32 (86.5%) 5 (13.5%) 37 High Risk Baseline 5 (71.4%) 2 (28.6%) 7 Total 37 (84.1%) 7 (15.9%) 44 McNemar p-value 1.000 A clinically meaningful improvement was observed in a substantial proportion of participants. Specifically, 69% improved gait speed by at least 0.1 m/s, 55.2% increased SF-FAB scores by ≥ 1 point, while only 3.4% reduced TUG time by ≥ 0.8 s from baseline to the third year (Table 4 ). Table 4 Proportion of participants achieving minimal clinically important difference (MCID) from baseline to the third year Variable MCID Criterion Achieved MCID n (%) Gait Speed Δ ≥ 0.1 m/s 20 (69.0%) SF-FAB Δ ≥ 1 point 16 (55.2%) TUG Δ ≤ -0.8 s 1 (3.4%) Legend: MCID – Minimal Clinically Important Difference; Δ – change from baseline to third year. No significant differences in delta changes (Δ) were observed when comparing participants classified as high or low fall risk at baseline, first year, or third year. Median improvements in gait speed, TUG, and SF-FAB were similar across risk categories (all p > 0.05), suggesting that the intervention benefited participants regardless of their initial or final fall risk classification. The relationship between achieving MCID and fall risk classification at the third year was not statistically significant. A higher proportion of participants who achieved MCID in gait speed were classified as low risk (83.3% vs 75.0%), although this trend did not reach significance (Fisher, p = 0.628). Similarly, no significant associations were observed for SF-FAB (p = 0.356) or TUG (p = 0.808) (Table 5 ). Table 5 Association between achieving minimal clinically important difference (MCID) and fall risk classification at the third year Variable Low Risk n (%) High Risk n (%) p-value (Fisher) MCID Gait Speed 15 (83.3%) 3 (16.7%) 0.628 MCID SF-FAB 11 (73.3%) 4 (26.7%) 0.356 MCID TUG 1 (100.0%) 0 (0%) 0.808 Legend: MCID – Minimal Clinically Important Difference; Δ – change from baseline to third year. A significant moderate negative correlation was observed between changes in gait speed and fear of falling (ΔGS vs ΔFES-I: rs = -0.55, p = 0.002), indicating that participants who improved their gait speed reported lower concern about falling. No significant correlations were found between changes in functional performance (SF-FAB) and psychological outcomes (all p > 0.05), although a positive trend was noted between gait speed and balance confidence (ΔGS vs ΔABC: rs = 0.33, p = 0.077). Table 6 will show all correlations. Table 6 Spearman correlations between changes in physical and psychological outcomes Correlation r s p-value ΔGS vs ΔFES-I -0.55 0.002* ΔGS vs ΔABC 0.33 0.077 ΔSF-FAB vs ΔFES-I -0.14 0.458 ΔSF-FAB vs ΔABC -0.10 0.593 ΔTUG vs ΔFES-I 0.20 0.302 ΔTUG vs ΔABC -0.04 0.842 Legend: GS – Gait Speed; SF-FAB – Short Form Fullerton Advanced Balance; TUG – Timed Up and Go; FES-I – Falls Efficacy Scale International; ABC – Activities-specific Balance Confidence Specifically, three core variables were analyzed: the Short Fullerton Advanced Balance Scale (FAB), used to assess dynamic balance through functional tasks; the Falls Efficacy Scale – International (FES-I), which quantifies the individual’s concern or fear of falling during daily activities; and the Activity-Specific Balance Confidence Scale (ABC), which measures confidence in maintaining balance across common tasks. These instruments have been validated for use in older Portuguese adults and provide complementary insight into both physical competence and psychological readiness to cope with daily movement challenges. The statistical approach employed for this analysis was the Friedman test, a non-parametric alternative to repeated measures ANOVA, suitable for small samples and ordinal or non-normally distributed data. Pairwise comparisons between timepoints were performed to determine where statistically significant differences occurred. Table 7 presents the results of this longitudinal comparison. Notably, a statistically significant improvement was observed in FAB scores between year one and year three (p = 0.02), indicating enhanced functional balance over time. Although the increase from year one to year two approached significance (p = 0.08), no further significant change was detected between year two and three, suggesting a plateau effect after initial gains. In contrast, the FES-I and ABC scores did not exhibit statistically significant changes across the three timepoints, although descriptive trends suggested slight improvements in fear of falling and balance confidence. These results underscore the potential for balance-focused physical training to yield measurable improvements over time, particularly in objective balance performance, while psychological adaptations may require more individualized or targeted interventions to reach statistical relevance. Table 7 Analysis of differences in physical and psychological variables related to fall risk across the three evaluation timepoints (2022, 2023, and 2024) Variables Baseline (year 2022) 2th time point (year 2023) 3th time point (year 2024) p-values Gait Speed (m/s) 1.92 ± 0.29 2.05 ± 0.29 2.11 ± 0.37 M1- M2 0.02* M1- M3 0.001* M2 - M3 0.28 Gait Cadence (steps/s) 2.35 ± 0.26 2.76 ± 0.31 4.63 ± 0.59 M1- M2 < 0.01* M1- M3 < 0.01* M2 - M3 < 0.01* TUG (s) 6.00 ± 1.03 5.29 ± 1.02 5.76 ± 1.33 M1- M2 < 0.01* M1- M3 0.057 M2 - M3 0.007* 5xSTS (s) - 8.59 ± 1.73 8.23 ± 2.12 M2 - M3 0.163 Handgrip Strength (kg) 25.10 ± 7.20 26.24 ± 7.73 26.98 ± 7.18 M1- M2 0.316 M1- M3 0.016* M2- M3 0.161 SF-FAB (points) 13.86 ± 2.11 14.52 ± 1.47 14.66 ± 1.44 M1-M2 0.08 M1- M3 0.02* M2 - M3 0.59 FES-I (points) 1.34 ± 0.28 1.38 ± 0.40 1.35 ± 0.34 M1-M2 0.572 M1- M3 0.566 M2- M3 0.258 ABC Scale (%) 91.27 ± 7.46 88.72 ± 11.82 91.56 ± 15.01 M1-M2 0.39 M1- M3 0.59 M2 - M3 0.74 Legend: TUG- timed up and go; 5xSTS – five times sit-to-stand; SF-FAB – Short Form of Fullerton Advanced Balance; FES-I – Falls efficacy scale; ABC Scale - Activity-Specific Balance Confidence Scale; NA- not applicable; M – evaluation moment p < 0.05 statistically significant differences between timepoints Discussion The present longitudinal study investigated the effects of a three-year multimodal exercise intervention on functional, psychological, and fall-related outcomes in physically active community-dwelling older adults. Overall, the results demonstrated significant improvements in functional balance, gait performance, and lower-limb strength, while psychological outcomes showed maintenance of high baseline confidence levels. However, the analysis of global fall risk and fall episodes revealed no statistically significant changes over time, although clinically relevant trends were observed. These findings provide valuable insights into the long-term effects of multimodal exercise in a population that already exhibited high functional capacity at baseline. A key finding was the significant improvement in GS and cadence across the three timepoints, particularly between baseline and follow-up assessments. Gait speed is widely recognized as a biomarker of healthy aging and survival [ 28 ], reflecting integrated neuromuscular, cardiovascular, and cognitive functions. The observed improvements are likely explained by enhanced neuromuscular coordination and central nervous system efficiency, as balance and functional mobility training stimulate cortical plasticity and optimize agonist–antagonist muscle activation patterns [ 5 ]. Moreover, the inclusion of dual-task and cognitively demanding balance exercises may have promoted cognitive-motor integration, improving attentional control and reactive postural adjustments during walking [ 29 ]. The analysis of clinical relevance, based on minimal clinically important difference (MCID), further strengthened these findings. A substantial proportion of participants achieved meaningful functional gains, with 69% improving gait speed by at least 0.1 m/s and 55.2% increasing SF-FAB scores by ≥ 1 point, whereas only 3.4% achieved a clinically significant reduction in TUG time (≥ 0.8 s). These results are clinically relevant because gait speed improvements of this magnitude have been associated with reduced disability risk and mortality in older adults [ 30 ], while SF-FAB improvements are linked to enhanced dynamic balance and fall prevention [ 25 ]. The low proportion achieving MCID for TUG likely reflects a ceiling effect, as participants had high functional mobility at baseline, limiting the potential for large detectable changes. Importantly, the correlation analysis provided evidence of a link between physical and psychological adaptations. A moderate negative correlation between ΔGS and ΔFES-I (rs = − 0.55, p = 0.002) indicated that participants who improved their gait speed reported reduced fear of falling. Although causality cannot be inferred due to the absence of a control group, the observed decrease in self-reported balance and mobility issues over the three years may suggest potential benefits of sustained participation in a structured multimodal exercise program. These findings support the hypothesis that functional improvements can indirectly influence psychological outcomes, even when no significant group-level differences are detected in psychological measures. Maintaining high confidence levels throughout the program, despite non-significant group-level changes in FES-I and ABC, remain clinically relevant, as fear of falling is a major predictor of activity restriction and functional decline [ 12 ]. The analysis of global fall risk classification revealed no statistically significant changes across the three moments (Cochran’s Q = 0.857, p = 0.651), although a gradual increase in the proportion of participants classified as high risk was observed (9.1% at baseline, 13.6% at 1-year, and 18.2% at 3-year follow-up). While these results contrast with previous evidence reporting significant fall risk reduction after multimodal interventions [ 11 ], the lack of significance in the present study is likely explained by the high functional baseline of participants, small sample size, and the natural progression of aging-related impairments over a three-year period. Notably, most participants maintained a low-risk classification throughout the follow-up (≥ 80%), which itself may be considered a positive outcome in aging, where a natural trajectory of functional decline is expected. The exploratory analysis of the relationship between achieving MCID and fall risk at the third year revealed no significant associations, although clinically meaningful trends were observed. Participants who achieved MCID in gait speed were more frequently classified as low risk at the final assessment (83.3% vs 75.0%, p = 0.628), suggesting that even small but clinically meaningful mobility gains may contribute to maintaining low fall risk over time. Conversely, no clear trends were observed for SF-FAB or TUG. These findings highlight the importance of interpreting both statistical and clinical significance, as functional improvements may have protective effects not fully captured by categorical risk classification. TUG should ideally be used in combination with other physical or cognitive assessments [ 31 ]. While some researchers continue to support the TUG as a practical and accessible tool for fall risk screening [ 32 ], others caution that its sensitivity and specificity may not be sufficient for comprehensive risk profiling [ 33 ]. Functional mobility, assessed by TUG, improved significantly during the first two years, with a plateau between the second and third years, suggesting early neuromuscular and sensorimotor adaptations followed by capacity stabilization. This pattern aligns with the expected trajectory in older adults, where initial neuromuscular gains plateau as training adaptations consolidate [ 15 ]. Maintaining TUG performance over three years is clinically meaningful, as it is strongly associated with independence in activities of daily living and reduced institutionalization risk. Similarly, lower-limb strength (5xSTS) showed modest but clinically relevant improvements, consistent with the prevention of the typical 1–3% annual decline in muscle mass and power reported in older adults [ 9 ]. Upper-limb strength (HGS) increased significantly, reflecting systemic benefits of multimodal training. Although not directly linked to fall risk, greater upper-body strength may indirectly reduce fall severity by improving protective arm reactions during perturbations [ 34 ]. Balance performance, as measured by SF-FAB, improved significantly, likely due to enhanced proprioceptive acuity, vestibular sensitivity, and optimized anticipatory and reactive postural adjustments, as previously described [ 25 ]. From a clinical and public health perspective, these findings reinforce the importance of long-term, structured multimodal exercise programs even for physically active older adults. Maintaining functional performance and low fall risk over three years in this high-functioning cohort is clinically significant, as it suggests that continuous training may prevent early transitions to frailty and mitigate age-related functional decline [ 13 , 14 ]. However, the study presents some limitations, including the small sample size, high baseline functional level, and the absence of a control group. These factors limit the generalizability of the findings and hinder the ability to determine whether the observed changes resulted from the intervention itself or from other factors, such as natural aging. Future research should include control groups and stratify participants by baseline fall risk and psychological profiles to better understand differential responses. Additionally, integrating dual-task or cognitive-behavioral components may improve psychological outcomes, particularly fear of falling, which appears partially independent of physical improvements. Conclusions This three-year longitudinal study provides robust evidence supporting the effectiveness of sustained participation in multimodal exercise programs for promoting functional health and reducing fall risk in physically active community-dwelling older adults. Meaningful improvements were observed in gait performance, postural balance, and upper-limb strength, accompanied by a consistent trend toward fewer fall episodes and reduced balance-related complaints over time. Although psychological outcomes did not reach statistical significance, the maintenance of high confidence levels alongside functional gains reinforces the preventive value of continued engagement in structured and supervised exercise. Additionally, the incorporation of educational strategies specifically focused on fall prevention within exercise programs may further enhance psychological outcomes, such as reducing fear of falling and improving balance confidence. These findings highlight that even older adults already engaged in regular physical activity benefit significantly from targeted multimodal training, which appears to counteract age-related neuromuscular decline and support the preservation of functional independence. From a public health perspective, long-term supervised exercise programs should be considered a key strategy to promote healthy aging, delay the onset of frailty, and lessen the healthcare burden associated with falls. Future studies with larger samples and neurophysiological assessments are recommended to confirm these findings and further elucidate the mechanisms underlying the observed functional adaptations. Statements and Declarations Ethical approval and informed consent The study was approved by the Ethics Committee of Instituto Piaget (Ref: CE-Piaget-2022-03). All participants provided written informed consent prior to participation. Consent to participate Written informed consent was obtained from all participants. Consent for publication Not applicable – the manuscript does not contain any identifiable personal data, images, or videos. Declaration of conflicting interest The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding statement This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Data availability statement The data that support the findings of this study are available from the corresponding author upon reasonable request. References Instituto Nacional de Estatística. Projeções da população residente 2018–2080. INE. (2021). World Health Organization & Falls (2020). https://www.who.int/news-room/fact-sheets/detail/fallsWorld Bourke, R. et al. Cardiovascular disorders and falls among older adults: A systematic review and meta-analysis. 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The Global Status Report on Physical Activity. (2022). https://www.who.int/teams/health-promotion/physical-activity/global-status-report-on-physical-activity-2022 ACSM. ACSM’s Guidelines for Exercise Testing and Prescription (11th ed.) Wolters Kluwer. (2021). Dautzenberg, L. et al. Interventions for preventing falls and fall-related fractures in community-dwelling older adults: A systematic review and network meta-analysis. J. Am. Geriatr. Soc. 69 (10), 2973–2984. https://doi.org/10.1111/jgs.17375 (2021). Zhu, X., Yin, S., Lang, M., He, R. & Li, J. The more the better? A meta-analysis on effects of combined cognitive and physical intervention on cognition in healthy older adults. Ageing Res. Rev. 31 , 67–79. https://doi.org/10.1016/j.arr.2022.101674 (2023). Sadaqa, M. et al. Multicomponent Exercise Intervention for Preventing Falls and Improving Physical Functioning in Older Nursing Home Residents: A Single-Blinded Pilot Randomised Controlled Trial. 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Prescripción de ejercicio físico. El programa Vivifrail como modelo Multicomponent physical exercise program: Vivifrail. Nutr Hosp. 36 (Spec No2):50–56. Spanish. http://doi : (2019). 10.20960/nh.02680 . PMID: 31189323. Guralnik, J. M., Simonsick, E. M., Ferrucci, L. & Glynn, R. JA short physical performance battery assessing lower extremity function: Association with self-reported disability and prediction of mortality and nursing home admission. J. Gerontol. 49 (2), M85–M94. https://doi.org/10.1093/geronj/49.2.M85 (1994). Reider, N. & Gaul, C. Fall risk screening in the elderly: A comparison of the minimal chair height standing ability test and 5-repetition sit-to-stand test. Arch. Gerontol. Geriatr. 65 , 133–139. https://doi.org/10.1016/j.archger.2016.03.004 (2016). Cruz-Jentoft, A. J., Bahat, G., Bauer, J., Boirie, Y., Bruyère, O., Cederholm, T.,… Schols, J. Sarcopenia: Revised European consensus on definition and diagnosis (EWGSOP2).Age and Ageing, 48(1), 16–31. (2019) https://doi.org/10.1093/ageing/afy169. Rose, D. J., Lucchese, N. & Wiersma, L. D. Development of a multidimensional balance scale for use with functionally independent older adults. Arch. Phys. Med. Rehabil. 87 (11), 1478–1485. https://doi.org/10.1016/j.apmr.2006.07.263 (2006). Marques-Vieira, C. M., Sousa, L. M., Sousa, L. M. & Berenguer, S. M. Validation of the Falls Efficacy Scale–International in a sample of Portuguese elderly. Revista brasileira de enfermagem . 71 , 747–754. https://doi.org/10.1590/0034-7167-2017-0497 (2018). Branco, P. S. Validação da versão portuguesa da activities-specific balance confidence scale validation of the portuguese version of the activities-specific balance confidence scale. Rev. Soc. Port Med. Física Reabil . 19 , 20–25. https://doi.org/10.25759/spmfr.40 (2010). Studenski, S., Perera, S., Patel, K., Rosano, C., Faulkner, K., Inzitari, M., … Guralnik,J. Gait speed and survival in older adults. JAMA, 305(1), 50–58, (2011) https://doi.org/10.1001/jama.2010.1923. Voelcker-Rehage, C., Godde, B. & Staudinger, U. M. Physical and cognitive activity and brain plasticity in later life: A review. Eur. Rev. Aging Phys. Activity . 8 (2), 95–106. https://doi.org/10.1007/s11556-011-0073-0 (2011). Perera, S., Mody, S. H., Woodman, R. C. & Studenski, S. A. Meaningful change and responsiveness in common physical performance measures in older adults. J. Am. Geriatr. Soc. May . 54 (5), 743–749. https://doi.org/10.1111/j.1532-5415.2006.00701.x (2006). Park, S. H. Tools for assessing fall risk in the elderly: A review of the literature. Annals Rehabilitation Med. 42 (3), 369–378. https://doi.org/10.5535/arm.2018.42.3.369 (2018). Pooranawatthanakul, S. & Siriphorn, A. Accuracy of the Timed Up and Go test for predicting falls in older adults: A systematic review and meta-analysis. BMC Geriatr. 23 , 410. https://doi.org/10.1186/s12877-023-04154-9 (2023). Schlenstedt, C. et al. Comparing the timed up and go test with the dynamic gait index in Parkinson’s disease: Reliability, validity, and responsiveness. Mov. Disord. 31 (4), 560–569. https://doi.org/10.1002/mds.26572 (2016). Bohannon, R. W. Grip strength: An indispensable biomarker for older adults. Clin. Interv. Aging . 14 , 1681–1691. https://doi.org/10.2147/CIA.S194543 (2019). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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According to recent projections, individuals aged 65 years and older will comprise over 30% of the Portuguese population by 2050 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], a trend echoed globally. This demographic transformation is associated with a rise in chronic conditions, functional decline, and, notably, an increased risk of falls, recognized as one of the leading causes of injury, disability, and mortality in older adults [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFalls are defined as \u0026ldquo;an event which results in a person coming to rest inadvertently on the ground or floor or other lower level\u0026rdquo; [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Falls among older adults represent one of the most complex and pervasive syndromes in geriatric health, emerging from an intricate interplay of physiological, psychological, behavioral, and environmental determinants. Intrinsic factors such as sarcopenia, impaired postural reflexes, neuromuscular degeneration, vestibular and visual deterioration, and delayed reaction times collectively diminish the body\u0026rsquo;s capacity to maintain balance and recover from perturbations [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Simultaneously, extrinsic contributors, ranging from poorly adapted home environments and uneven surfaces to inadequate lighting and the cumulative effects of polypharmacy, further amplify vulnerability [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Even seemingly minor obstacles can become critical threats when combined with age-related decline.\u003c/p\u003e \u003cp\u003eEpidemiological data consistently show that nearly one in three community-dwelling individuals aged 65 and older will experience at least one fall each year, and alarmingly, up to half of these individuals become recurrent fallers [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These are not isolated events: each fall often initiates a downward spiral of fear, reduced activity, functional decline, and increased dependence. The personal consequences extend far beyond physical injury, as they include psychological distress, social withdrawal, and a loss of confidence in one\u0026rsquo;s own body. Moreover, the societal burden is immense: falls account for a substantial proportion of hospital admissions among older adults, place intense pressure on rehabilitation services, and contribute significantly to long-term care institutionalization [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFrom an economic perspective, falls represent a costly challenge to healthcare systems worldwide. The cumulative costs associated with emergency care, surgical interventions, post-acute rehabilitation, and ongoing assistance can be staggering, particularly in aging societies. More importantly, these incidents often mark the transition from independent living to chronic disability and institutional care, dramatically altering the trajectory of aging. As such, falls are not merely a clinical issue, they are a sentinel event signaling frailty, functional loss, and systemic gaps in prevention. Understanding and addressing falls through this broader lens is essential. It requires integrated strategies that go beyond symptom management, tackling the root causes across biological systems and daily environments. In this context, exercise emerges as one of the most powerful, cost-effective, and accessible interventions available to break this cycle.\u003c/p\u003e \u003cp\u003eAn expanding body of evidence underscores the critical role of both physical fitness and psychological resilience in modulating fall risk among older adults. While falls are often perceived as random and unpredictable, research consistently reveals that they are, in fact, strongly associated with measurable declines in functional capacity, particularly lower-limb strength, postural control, gait speed, and dynamic balance [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. These physical parameters are fundamental to performing everyday tasks safely and efficiently. However, the narrative regarding fall risk is incomplete without addressing the psychological dimension. Constructs such as fall efficacy (the perceived ability to avoid falls) and balance confidence have emerged not as secondary factors but as central predictors of fall occurrence, especially in community-dwelling and even physically active populations [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIndeed, recent research has revealed that in some cohorts, psychological variables may surpass physical markers in their predictive power. Fall efficacy and balance confidence exhibited a stronger association with fall risk than objective measures like handgrip strength [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. This finding aligns with broader gerontological models that highlight the interconnectedness of physical and psychological systems in aging, suggesting that fear of falling and lack of confidence can directly influence gait patterns, limit physical activity, and initiate a cycle of deconditioning and functional decline. In this context, fall prevention must go beyond mere objective measurements; it must address the mindset and emotional state of the individual.\u003c/p\u003e \u003cp\u003eIn response to this multifactorial understanding of falls, interventions that simultaneously address multiple physical domains, such as strength, endurance, agility, and balance, have gained prominence. These multicomponent or multimodal exercise programs are not merely additive in nature; they are synergistic. By targeting the diverse systems involved in fall prevention, they foster neuromuscular coordination, improve proprioception, and enhance the adaptability of motor responses to unexpected challenges. Both the World Health Organization [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and the American College of Sports Medicine [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] strongly advocate for the inclusion of such comprehensive programs in public health strategies for older adults. Systematic reviews and large-scale meta-analyses support their effectiveness, showing reductions in fall incidence of up to 40% in older adults living in the community [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite these advances, most of the existing evidence comes from studies with short intervention durations or cross-sectional snapshots. These designs, while valuable, fall short of capturing the long-term sustainability and cumulative impact of exercise interventions, particularly in those who are already physically active. Older adults who engage in regular physical activity may present higher functional baselines, but they are not immune to the physiological effects of aging. In fact, this population may often be overlooked in fall prevention initiatives under the assumption that their risk is lower, when their needs may differ in nature but not in emergency [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere remains a critical gap in the literature concerning the longitudinal effects of structured, supervised multimodal exercise programs in maintaining or enhancing function and reducing fall risk in this subgroup. Understanding how this active population responds over time to targeted interventions may be the key to designing tailored strategies that are both preventive and performance-preserving.\u003c/p\u003e \u003cp\u003eThe present study aims to address this gap by investigating the longitudinal impact of a supervised multimodal exercise program on fall-related outcomes in community-dwelling older adults over a three-year period, with particular attention to the role of psychological engagement and consistent exposure in sustaining its benefits.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Participants\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwenty-nine participants were recruited from a community-based exercise program and were required to meet the following inclusion criteria: aged 55 years or older, maintaining a physically active lifestyle within the community, attending the structured group exercise sessions at least twice per week, and have the functional autonomy to move independently without external assistance. Exclusion criteria included any medical contraindications to engaging in physical activity or conditions that could interfere with the safe execution of functional fitness assessments on the day of evaluation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Exercise Program Protocol\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAlthough the exercise intervention was not directly controlled by the research team, participants were enrolled in a structured, municipality-run community-based program. The program consisted of multimodal training sessions held twice per week, each lasting approximately 60 minutes. The sessions targeted various physical domains, including strength, balance, mobility, coordination, and endurance, and were conducted in group format under the supervision of trained exercise professionals. The general structure and regularity of the sessions were monitored by local authorities, but individual attendance and exercise intensity were not recorded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Instruments and Variables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study employed a multidimensional evaluation protocol, incorporating anthropometric, physical, and psychological variables known to be associated with fall risk in older adults. Assessments were conducted under standardized conditions by trained professionals to ensure consistency and reliability of the data across timepoints. Data were collected at three timepoints: December 2022 (baseline), December 2023 (2nd evaluation), and December 2024 (3rd evaluation).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3.1 Anthropometric and Demographic Variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSociodemographic data were collected through structured interviews and included age (in years), sex (male/female), number of self-reported comorbidities (e.g., hypertension, diabetes, osteoarthritis), and total number of medications taken daily, as polypharmacy is a recognized contributor to fall risk.\u003c/p\u003e\n\u003cp\u003eBody weight was measured using a SECA 761 mechanical scale (Bacelar \u0026amp; Irmão Lda, Portugal), with participants wearing light clothing and no shoes. Height was self-reported. Both measures were recorded to the nearest 0.1 kg and 0.1 cm, respectively. Body Mass Index (BMI) was subsequently calculated using the standard equation: BMI= body weight(kg)/ height (m)2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3.2 Fall History and Risk Classification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess prior fall events, participants were interviewed using a standardized questionnaire adapted from the American Geriatrics Society \u0026amp; British Geriatrics Society Clinical Practice Guidelines\u0026nbsp;[19]. They were asked the following questions:\u003c/p\u003e\n\u003cp\u003e1.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;“In the past 12 months, how many times have you fallen?”\u003c/p\u003e\n\u003cp\u003e2.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;“If you have fallen, did you require any medical attention?”\u003c/p\u003e\n\u003cp\u003e3.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;“Did the fall result in any difficulty with walking or maintaining balance?”\u003c/p\u003e\n\u003cp\u003eParticipants were classified based on their responses as non-fallers, single fallers, or recurrent fallers (≥2 falls in the past year). These distinctions were used to stratify fall risk in subsequent analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3.3 Physical Performance Measures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll physical fitness tests were administered in accordance with published protocols and were selected based on their clinical validity, reproducibility, and feasibility in community settings.\u003c/p\u003e\n\u003cp\u003eGait speed and cadence were assessed using a 15-meter walk test following the protocol by Rikli and Jones\u0026nbsp;[20]. Participants were instructed to walk at their usual pace along a flat 15-meter corridor. To exclude the influence of acceleration and deceleration, only the central 9 meters were timed. Speed was expressed in meters per second (m/s), while cadence was expressed in steps per second (steps/s). A gait speed \u0026lt; 0.8 m/s was used as a cutoff for elevated fall risk, based on normative data for older adults\u0026nbsp;[21].\u003c/p\u003e\n\u003cp\u003eAgility and Mobility were assessed using the 8-Foot Up-and-Go test. Participants began seated in a chair placed near a wall, with a marker positioned 2.44 meters in front. At a verbal cue, they were instructed to rise from the chair, walk to the marker, circle it, return to the chair, and sit down as quickly as possible. Timing started with the cue and stopped once the participant was fully reseated\u0026nbsp;[20]. Completion time (s) was recorded; higher times indicate poorer functional mobility. The measure was treated as a continuous variable; no fall-risk cut-offs were applied to 8UG.\u003c/p\u003e\n\u003cp\u003eLower-Limb Strength was assessed by Five Times Sit-to-Stand (5xSTS), a component of the Short Physical Performance Battery (SPPB)\u0026nbsp;[22]. Participants were instructed to rise from a chair and sit back down five times as quickly as possible with arms folded across the chest. A digital stopwatch was used for timing. Risk thresholds were: ≤13 seconds: low risk; 14–17 seconds: moderate risk; ≥18 seconds: high risk\u0026nbsp;[23].\u003c/p\u003e\n\u003cp\u003eHandgrip Strength (HGS) was assessed using a Jamar hydraulic dynamometer (Lafayette Instrument Company, USA), following the standardized protocol recommended by the American Society of Hand Therapists (ASHT). Participants were seated on a chair without armrests, with their shoulders adducted and neutrally rotated, elbow flexed at 90°, forearm in a neutral position, and wrist slightly extended (0–30°). They were instructed to squeeze the dynamometer as hard as possible for 3 to 5 seconds. Three trials were performed for each hand, alternating sides, with a rest interval of 30 seconds between attempts to minimize fatigue. The maximum value obtained from the dominant hand was recorded for analysis, as it has been shown to be the most reliable indicator of general upper-limb strength and overall functional capacity in older adults. Cut-off points suggesting reduced strength and potential functional impairment were considered according to normative data proposed by Cruz-Jentoft (2019), with values \u0026lt;27 kg for men and \u0026lt;16 kg for women associated with increased risk of disability and frailty\u0026nbsp;[24].\u003c/p\u003e\n\u003cp\u003eStatic and dynamic balance was assessed using the short version of the Fullerton Advanced Balance Scale (SF-FAB)\u0026nbsp;[25], which includes four tasks, each scored from 0 to 4 points, for a maximum total of 16 points. The tasks were: (1) Transpose a 15 cm bench - the participant must place their dominant foot on the top of the bench and pass the opposite leg directly over it, resting the contralateral limb on the floor on the opposite side, repeating the movement with the opposite leg. (2) Walking in a straight line - this test assumes that the participant walks in a straight line on the floor, placing their heel on the tip of the opposite foot until they have completed a total of 10 steps. (3) Single-leg balance - the participant must stand, cross their arms over their chest and lift their preferred leg off the ground, without touching the other leg, holding this position with their eyes open for as long as possible. (4) Standing on foam with eyes closed - assumes that the participant can stand with arms crossed over chest and eyes closed in bipodal balance on foam for 20 seconds, or until loss of balance. A total score ≤ 9 points out of 16 is classified as a high risk of falling\u0026nbsp;[25].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3.4 Psychological Measures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo evaluate psychological constructs associated with fall risk, two validated self-report questionnaires were employed: the Falls Efficacy Scale – International (FES-I) and the Activity-Specific Balance Confidence (ABC) Scale. Both tools have demonstrated predictive value for falls in older adults and are considered essential components in multidimensional fall risk assessment models.\u003c/p\u003e\n\u003cp\u003eFear of falling was measured using the Portuguese version of the Falls Efficacy Scale – International (FES-I), a widely used instrument developed to assess concern about falling across a variety of daily life situations. The scale comprises 16 items, each reflecting a common activity, such as walking around the house, using public transport, or going up or down stairs\u0026nbsp;[26]. Participants were instructed to indicate their level of concern about the possibility of falling while performing each activity, using a 4-point Likert-type scale: 1 = Not at all concerned; 2 = Somewhat concerned; 3 = Fairly concerned; 4 = Very concerned. The total FES-I score is obtained by summing the responses, with higher total scores indicating greater fear of falling and reduced self-efficacy in managing daily physical tasks without experiencing a fall. This measure has been validated in the Portuguese population of older adults, showing strong internal consistency and construct validity. Elevated FES-I scores have been linked to activity restriction, deconditioning, and higher incidence of falls in prospective studies.\u003c/p\u003e\n\u003cp\u003eThe Activity-Specific Balance Confidence (ABC) Scale was used to assess participants’ self-perceived confidence in maintaining balance during functional tasks of varying complexity and environmental demands. The ABC comprises 16 activity-based items, including reaching overhead, walking on uneven surfaces, or stepping onto an escalator. Participants rated their confidence in completing each activity without losing balance or becoming unsteady, using a visual analogue scale from 0% to 100%, where: 0% = No confidence at all; 100% = Completely confident. The final ABC score is calculated by averaging 16 responses, yielding a mean percentage score that reflects the individual’s overall balance confidence. Lower ABC scores are indicative of greater balance anxiety and have been consistently associated with increased fall risk, functional limitations, and avoidance behaviors. This scale has been validated in Portuguese older adults\u0026nbsp;[27], and its integration into fall risk assessment is supported by the literature due to its sensitivity in detecting subtle changes in psychological readiness for mobility.\u003c/p\u003e\n\u003cp\u003eCombined, these two instruments, the Falls Efficacy Scale – International (FES-I) and the Activity-Specific Balance Confidence (ABC) Scale, offer a thorough assessment of psychological factors associated with fall risk. They complement objective physical evaluations, contributing to a more comprehensive and holistic understanding of fall risk among older adults living in the community.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Statistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were conducted using IBM SPSS Statistics version 28.0 (IBM Corp., Armonk, NY, USA). Descriptive statistics were used to characterize the sample at baseline, presenting means, standard deviations, and percentages for sociodemographic and clinical variables such as age, sex, height, body weight, BMI, number of comorbidities, and medication use. Normality was evaluated using the Shapiro–Wilk test. Since most variables did not satisfy the normality assumptions, non-parametric statistical methods were employed.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo examine changes over time across the three evaluation moments (baseline, 1-year, and 2-year follow-up), the Friedman test was used for repeated measures. This analysis included the Timed Up and Go (TUG) test, Gait Speed (GS), Five Times Sit-to-Stand Test (5xSTS), handgrip strength, the Short Fullerton Advanced Balance (SF-FAB) scale, and two psychological outcomes—the Falls Efficacy Scale – International (FES-I) and the Activity-Specific Balance Confidence (ABC) scale. Post hoc comparisons were conducted using the Wilcoxon signed-rank test, with Bonferroni correction for multiple comparisons. A significance level of p \u0026lt; 0.05 was adopted for all tests, and Kendall’s W was calculated as an effect size measure.\u003c/p\u003e\n\u003cp\u003eThe global risk classification (low vs high) was compared between the three evaluation moments using the McNemar test, to determine changes in risk category distribution over time. To assess the clinical significance of physical performance changes, the proportion of participants achieving the Minimal Clinically Important Difference (MCID) in gait speed (Δ ≥ 0.1 m/s), SF-FAB (Δ ≥ 1 point), and TUG (Δ ≤ −0.8 s) was calculated. Additionally, associations between achieving MCID and fall risk classification at the third year were analyzed using Fisher’s exact test. Differences in physical performance changes (ΔGS, ΔTUG, ΔSF-FAB) between fall risk categories (baseline, 1-year, and 2-year follow-up) were assessed using the Mann–Whitney U test. Finally, to explore the relationship between physical and psychological changes, Spearman’s rank correlation coefficient (rs) was calculated between changes in physical performance (ΔGS, ΔTUG, ΔSF-FAB) and psychological outcomes (ΔFES-I and ΔABC). In cases of missing data, pairwise deletion was applied to maximize the number of valid cases without introducing systematic bias.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 29 active older adults participated in the study. The majority were female (59%), with a mean age of 71.7\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7 years old. Participants presented with an average height of 1.57\u0026thinsp;\u0026plusmn;\u0026thinsp;8.4 m and body weight of 68.7\u0026thinsp;\u0026plusmn;\u0026thinsp;11.3 kg, resulting in a mean BMI of 27.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9 kg/m\u0026sup2;, which corresponds to the lower range of the overweight classification. Regarding health-related variables, participants reported an average of 1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3 comorbidities and were taking an average of 2.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8 medications. These baseline data reflect a heterogeneous but functionally independent older adult population actively engaged in community-based exercise programs (Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSociodemographic and clinical characteristics of the sample by sex at baseline\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;29)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale (n\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFemale (n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e71.72\u0026thinsp;\u0026plusmn;\u0026thinsp;5.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e72.00\u0026thinsp;\u0026plusmn;\u0026thinsp;5.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e71.60\u0026thinsp;\u0026plusmn;\u0026thinsp;5.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody Weight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e68.72\u0026thinsp;\u0026plusmn;\u0026thinsp;11.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e77.00\u0026thinsp;\u0026plusmn;\u0026thinsp;10.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e65.00\u0026thinsp;\u0026plusmn;\u0026thinsp;9.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight (m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.57\u0026thinsp;\u0026plusmn;\u0026thinsp;8.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.66\u0026thinsp;\u0026plusmn;\u0026thinsp;5.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.54\u0026thinsp;\u0026plusmn;\u0026thinsp;6.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e27.59\u0026thinsp;\u0026plusmn;\u0026thinsp;3.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e28.04\u0026thinsp;\u0026plusmn;\u0026thinsp;4.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e27.39\u0026thinsp;\u0026plusmn;\u0026thinsp;358\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of medications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.62\u0026thinsp;\u0026plusmn;\u0026thinsp;2.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.56\u0026thinsp;\u0026plusmn;\u0026thinsp;2.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of comorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.10\u0026thinsp;\u0026plusmn;\u0026thinsp;1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.56\u0026thinsp;\u0026plusmn;\u0026thinsp;2.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the descriptive data related to fall occurrences and associated clinical implications over the three-year follow-up period. At baseline (2022), 86.2% of participants reported not having experienced any falls in the previous 12 months. A small proportion reported one fall (6.9%), two falls (3.4%), or three or more falls (3.4%). By 2023, 79.3% of the sample remained fall-free, while 13.8% experienced one fall, and 6.9% reported two falls. In 2024, the proportion of participants with zero falls remained high (72.4%), with a modest increase in those reporting one (17.2%) or two falls (10.3%). Importantly, no participants reported three or more falls in the final year.\u003c/p\u003e \u003cp\u003eWhen stratified by sex, all male participants reported no falls at baseline. However, by 2023, 22.2% of men reported one fall, and 11.1% did so again in 2024. Among females, the proportion of fallers was consistently higher: 20% reported one or more falls at baseline, 20% in 2023, and 35% in 2024.\u003c/p\u003e \u003cp\u003eRegarding the need for medical intervention following a fall, only one participant in each follow-up year (3.5% in 2023 and 2024) required medical assistance, indicating low severity of fall-related injuries in this cohort.\u003c/p\u003e \u003cp\u003eAs for self-reported problems with balance or gait, 48.3% of participants indicated such issues at baseline. However, this proportion decreased notably to 27.6% in 2023 and remained relatively low in 2024 (37.9%), suggesting an improvement in perceived functional capacity. Among males, the prevalence of balance/mobility issues dropped from 33.3% in 2022 to just 11.1% in subsequent years. Among females, although 55% reported issues in 2022, the prevalence decreased to 35% in 2023 and stabilized at 50% in 2024.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive and inferential data on Fall History, Medical Intervention, and Self-Reported Balance/Gait Problems Across the Three-Year Follow-Up (2022\u0026ndash;2024)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;29)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003eMale (n\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003eFemale (n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eYear 2022\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eYear 2023\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eYear 2024\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eYear 2022\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eYear 2023\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eYear 2024\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eYear 2022\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003eYear 2023\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003eYear 2024\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eHow many times have you fallen in the past 12 months?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0 falls\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 persons (86.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23 persons (79.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21 persons (72.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.651\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7 (77,8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8 (88,9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e16 (80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e16 (80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e13 (65%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1 fall\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 persons (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 persons (13.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 persons (17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2 (22,2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0(0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e5 (25%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2 falls\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 person (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 persons (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 persons (10.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (11,1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1 (5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2 (10%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e3 falls\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 person (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 persons (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 persons (10.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1 (5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIf yes, did you require medical attention?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 persons (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 person (3.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 person (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1 (5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1 (5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 persons (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 persons (96.55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28 persons (82.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e19 (95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e19 (95%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDo you have balance or gait problems?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 persons (48.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 persons (27.6%9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11 persons (37.93%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3 (33,3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (11,1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (11,1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e11 (55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e7 (35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e10 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 persons (51.75%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 persons (72.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18 persons (62.07%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6 (66,7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8 (88,9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8 (88,9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9 (45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e13 (65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e10 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003eLegend: NA- not applicable; * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 significant to assess changes in fall frequency distribution across the three years.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe analysis of the global fall risk across the three-year follow-up showed no statistically significant differences between time points. From baseline to the first year, 25% of participants initially classified as high risk transitioned to low risk, whereas 15.6% of those initially at low risk worsened to high risk (McNemar, p\u0026thinsp;=\u0026thinsp;0.727). From the first to the second year, all participants initially at high risk migrated to low risk, while 17.2% of those at low risk worsened (McNemar, p\u0026thinsp;=\u0026thinsp;1.000). Similarly, when comparing baseline to the third year, 71.4% of participants initially at high risk transitioned to low risk, and 13.5% of those at low risk progressed to high risk (McNemar, p\u0026thinsp;=\u0026thinsp;1.000). These observations indicate a potential trend towards risk reduction, although no statistically significant changes were observed (Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChange in global fall risk from baseline to the third year of follow-up.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2022\u0026ndash;2024 year\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow Risk 3rd Year (n, %)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh Risk 3rd Year (n, %)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow Risk Baseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (86.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (13.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh Risk Baseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (71.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (84.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (15.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMcNemar p-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eA clinically meaningful improvement was observed in a substantial proportion of participants. Specifically, 69% improved gait speed by at least 0.1 m/s, 55.2% increased SF-FAB scores by \u0026ge;\u0026thinsp;1 point, while only 3.4% reduced TUG time by \u0026ge;\u0026thinsp;0.8 s from baseline to the third year (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eProportion of participants achieving minimal clinically important difference (MCID) from baseline to the third year\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMCID Criterion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAchieved MCID n (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGait Speed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eΔ\u0026thinsp;\u0026ge;\u0026thinsp;0.1 m/s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (69.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSF-FAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eΔ\u0026thinsp;\u0026ge;\u0026thinsp;1 point\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (55.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eΔ \u0026le; -0.8 s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eLegend: MCID \u0026ndash; Minimal Clinically Important Difference; Δ \u0026ndash; change from baseline to third year.\u003c/p\u003e \u003cp\u003eNo significant differences in delta changes (Δ) were observed when comparing participants classified as high or low fall risk at baseline, first year, or third year. Median improvements in gait speed, TUG, and SF-FAB were similar across risk categories (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), suggesting that the intervention benefited participants regardless of their initial or final fall risk classification.\u003c/p\u003e \u003cp\u003eThe relationship between achieving MCID and fall risk classification at the third year was not statistically significant. A higher proportion of participants who achieved MCID in gait speed were classified as low risk (83.3% vs 75.0%), although this trend did not reach significance (Fisher, p\u0026thinsp;=\u0026thinsp;0.628). Similarly, no significant associations were observed for SF-FAB (p\u0026thinsp;=\u0026thinsp;0.356) or TUG (p\u0026thinsp;=\u0026thinsp;0.808) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between achieving minimal clinically important difference (MCID) and fall risk classification at the third year\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow Risk n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh Risk n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value (Fisher)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCID Gait Speed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (83.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.628\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCID SF-FAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (73.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (26.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.356\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCID TUG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.808\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"1\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLegend: MCID \u0026ndash; Minimal Clinically Important Difference; Δ \u0026ndash; change from baseline to third year.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eA significant moderate negative correlation was observed between changes in gait speed and fear of falling (ΔGS vs ΔFES-I: rs = -0.55, p\u0026thinsp;=\u0026thinsp;0.002), indicating that participants who improved their gait speed reported lower concern about falling. No significant correlations were found between changes in functional performance (SF-FAB) and psychological outcomes (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), although a positive trend was noted between gait speed and balance confidence (ΔGS vs ΔABC: rs\u0026thinsp;=\u0026thinsp;0.33, p\u0026thinsp;=\u0026thinsp;0.077). Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e will show all correlations.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSpearman correlations between changes in physical and psychological outcomes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCorrelation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003csub\u003es\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔGS vs ΔFES-I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔGS vs ΔABC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔSF-FAB vs ΔFES-I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.458\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔSF-FAB vs ΔABC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.593\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔTUG vs ΔFES-I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔTUG vs ΔABC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.842\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eLegend: GS \u0026ndash; Gait Speed; SF-FAB \u0026ndash; Short Form Fullerton Advanced Balance; TUG \u0026ndash; Timed Up and Go; FES-I \u0026ndash; Falls Efficacy Scale International; ABC \u0026ndash; Activities-specific Balance Confidence\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSpecifically, three core variables were analyzed: the Short Fullerton Advanced Balance Scale (FAB), used to assess dynamic balance through functional tasks; the Falls Efficacy Scale \u0026ndash; International (FES-I), which quantifies the individual\u0026rsquo;s concern or fear of falling during daily activities; and the Activity-Specific Balance Confidence Scale (ABC), which measures confidence in maintaining balance across common tasks. These instruments have been validated for use in older Portuguese adults and provide complementary insight into both physical competence and psychological readiness to cope with daily movement challenges.\u003c/p\u003e \u003cp\u003eThe statistical approach employed for this analysis was the Friedman test, a non-parametric alternative to repeated measures ANOVA, suitable for small samples and ordinal or non-normally distributed data. Pairwise comparisons between timepoints were performed to determine where statistically significant differences occurred.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e presents the results of this longitudinal comparison. Notably, a statistically significant improvement was observed in FAB scores between year one and year three (p\u0026thinsp;=\u0026thinsp;0.02), indicating enhanced functional balance over time. Although the increase from year one to year two approached significance (p\u0026thinsp;=\u0026thinsp;0.08), no further significant change was detected between year two and three, suggesting a plateau effect after initial gains.\u003c/p\u003e \u003cp\u003eIn contrast, the FES-I and ABC scores did not exhibit statistically significant changes across the three timepoints, although descriptive trends suggested slight improvements in fear of falling and balance confidence. These results underscore the potential for balance-focused physical training to yield measurable improvements over time, particularly in objective balance performance, while psychological adaptations may require more individualized or targeted interventions to reach statistical relevance.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnalysis of differences in physical and psychological variables related to fall risk across the three evaluation timepoints (2022, 2023, and 2024)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003cp\u003e(year 2022)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2th time point (year 2023)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3th time point (year 2024)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-values\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGait Speed (m/s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eM1- M2 0.02*\u003c/p\u003e \u003cp\u003eM1- M3 0.001*\u003c/p\u003e \u003cp\u003eM2 - M3 0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGait Cadence (steps/s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eM1- M2\u0026thinsp;\u0026lt;\u0026thinsp;0.01*\u003c/p\u003e \u003cp\u003eM1- M3\u0026thinsp;\u0026lt;\u0026thinsp;0.01*\u003c/p\u003e \u003cp\u003eM2 - M3\u0026thinsp;\u0026lt;\u0026thinsp;0.01*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.00\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.29\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eM1- M2\u0026thinsp;\u0026lt;\u0026thinsp;0.01*\u003c/p\u003e \u003cp\u003eM1- M3 0.057\u003c/p\u003e \u003cp\u003eM2 - M3 0.007*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5xSTS (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.59\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.23\u0026thinsp;\u0026plusmn;\u0026thinsp;2.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eM2 - M3 0.163\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHandgrip Strength (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.10\u0026thinsp;\u0026plusmn;\u0026thinsp;7.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.24\u0026thinsp;\u0026plusmn;\u0026thinsp;7.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.98\u0026thinsp;\u0026plusmn;\u0026thinsp;7.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eM1- M2 0.316\u003c/p\u003e \u003cp\u003eM1- M3 0.016*\u003c/p\u003e \u003cp\u003eM2- M3 0.161\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSF-FAB (points)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.86\u0026thinsp;\u0026plusmn;\u0026thinsp;2.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.66\u0026thinsp;\u0026plusmn;\u0026thinsp;1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eM1-M2 0.08\u003c/p\u003e \u003cp\u003eM1- M3 0.02*\u003c/p\u003e \u003cp\u003eM2 - M3 0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFES-I (points)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eM1-M2 0.572\u003c/p\u003e \u003cp\u003eM1- M3 0.566\u003c/p\u003e \u003cp\u003eM2- M3 0.258\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABC Scale (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91.27\u0026thinsp;\u0026plusmn;\u0026thinsp;7.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88.72\u0026thinsp;\u0026plusmn;\u0026thinsp;11.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e91.56\u0026thinsp;\u0026plusmn;\u0026thinsp;15.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eM1-M2 0.39\u003c/p\u003e \u003cp\u003eM1- M3 0.59\u003c/p\u003e \u003cp\u003eM2 - M3 0.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eLegend: TUG- timed up and go; 5xSTS \u0026ndash; five times sit-to-stand; SF-FAB \u0026ndash; Short Form of Fullerton Advanced Balance; FES-I \u0026ndash; Falls efficacy scale; ABC Scale - Activity-Specific Balance Confidence Scale; NA- not applicable; M \u0026ndash; evaluation moment\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05 statistically significant differences between timepoints\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present longitudinal study investigated the effects of a three-year multimodal exercise intervention on functional, psychological, and fall-related outcomes in physically active community-dwelling older adults. Overall, the results demonstrated significant improvements in functional balance, gait performance, and lower-limb strength, while psychological outcomes showed maintenance of high baseline confidence levels. However, the analysis of global fall risk and fall episodes revealed no statistically significant changes over time, although clinically relevant trends were observed. These findings provide valuable insights into the long-term effects of multimodal exercise in a population that already exhibited high functional capacity at baseline.\u003c/p\u003e \u003cp\u003eA key finding was the significant improvement in GS and cadence across the three timepoints, particularly between baseline and follow-up assessments. Gait speed is widely recognized as a biomarker of healthy aging and survival [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], reflecting integrated neuromuscular, cardiovascular, and cognitive functions. The observed improvements are likely explained by enhanced neuromuscular coordination and central nervous system efficiency, as balance and functional mobility training stimulate cortical plasticity and optimize agonist\u0026ndash;antagonist muscle activation patterns [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Moreover, the inclusion of dual-task and cognitively demanding balance exercises may have promoted cognitive-motor integration, improving attentional control and reactive postural adjustments during walking [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe analysis of clinical relevance, based on minimal clinically important difference (MCID), further strengthened these findings. A substantial proportion of participants achieved meaningful functional gains, with 69% improving gait speed by at least 0.1 m/s and 55.2% increasing SF-FAB scores by \u0026ge;\u0026thinsp;1 point, whereas only 3.4% achieved a clinically significant reduction in TUG time (\u0026ge;\u0026thinsp;0.8 s). These results are clinically relevant because gait speed improvements of this magnitude have been associated with reduced disability risk and mortality in older adults [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], while SF-FAB improvements are linked to enhanced dynamic balance and fall prevention [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The low proportion achieving MCID for TUG likely reflects a ceiling effect, as participants had high functional mobility at baseline, limiting the potential for large detectable changes.\u003c/p\u003e \u003cp\u003eImportantly, the correlation analysis provided evidence of a link between physical and psychological adaptations. A moderate negative correlation between ΔGS and ΔFES-I (rs\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.55, p\u0026thinsp;=\u0026thinsp;0.002) indicated that participants who improved their gait speed reported reduced fear of falling. Although causality cannot be inferred due to the absence of a control group, the observed decrease in self-reported balance and mobility issues over the three years may suggest potential benefits of sustained participation in a structured multimodal exercise program. These findings support the hypothesis that functional improvements can indirectly influence psychological outcomes, even when no significant group-level differences are detected in psychological measures. Maintaining high confidence levels throughout the program, despite non-significant group-level changes in FES-I and ABC, remain clinically relevant, as fear of falling is a major predictor of activity restriction and functional decline [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe analysis of global fall risk classification revealed no statistically significant changes across the three moments (Cochran\u0026rsquo;s Q\u0026thinsp;=\u0026thinsp;0.857, p\u0026thinsp;=\u0026thinsp;0.651), although a gradual increase in the proportion of participants classified as high risk was observed (9.1% at baseline, 13.6% at 1-year, and 18.2% at 3-year follow-up). While these results contrast with previous evidence reporting significant fall risk reduction after multimodal interventions [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], the lack of significance in the present study is likely explained by the high functional baseline of participants, small sample size, and the natural progression of aging-related impairments over a three-year period. Notably, most participants maintained a low-risk classification throughout the follow-up (\u0026ge;\u0026thinsp;80%), which itself may be considered a positive outcome in aging, where a natural trajectory of functional decline is expected.\u003c/p\u003e \u003cp\u003eThe exploratory analysis of the relationship between achieving MCID and fall risk at the third year revealed no significant associations, although clinically meaningful trends were observed. Participants who achieved MCID in gait speed were more frequently classified as low risk at the final assessment (83.3% vs 75.0%, p\u0026thinsp;=\u0026thinsp;0.628), suggesting that even small but clinically meaningful mobility gains may contribute to maintaining low fall risk over time. Conversely, no clear trends were observed for SF-FAB or TUG. These findings highlight the importance of interpreting both statistical and clinical significance, as functional improvements may have protective effects not fully captured by categorical risk classification. TUG should ideally be used in combination with other physical or cognitive assessments [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. While some researchers continue to support the TUG as a practical and accessible tool for fall risk screening [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], others caution that its sensitivity and specificity may not be sufficient for comprehensive risk profiling [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFunctional mobility, assessed by TUG, improved significantly during the first two years, with a plateau between the second and third years, suggesting early neuromuscular and sensorimotor adaptations followed by capacity stabilization. This pattern aligns with the expected trajectory in older adults, where initial neuromuscular gains plateau as training adaptations consolidate [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Maintaining TUG performance over three years is clinically meaningful, as it is strongly associated with independence in activities of daily living and reduced institutionalization risk. Similarly, lower-limb strength (5xSTS) showed modest but clinically relevant improvements, consistent with the prevention of the typical 1\u0026ndash;3% annual decline in muscle mass and power reported in older adults [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eUpper-limb strength (HGS) increased significantly, reflecting systemic benefits of multimodal training. Although not directly linked to fall risk, greater upper-body strength may indirectly reduce fall severity by improving protective arm reactions during perturbations [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Balance performance, as measured by SF-FAB, improved significantly, likely due to enhanced proprioceptive acuity, vestibular sensitivity, and optimized anticipatory and reactive postural adjustments, as previously described [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFrom a clinical and public health perspective, these findings reinforce the importance of long-term, structured multimodal exercise programs even for physically active older adults. Maintaining functional performance and low fall risk over three years in this high-functioning cohort is clinically significant, as it suggests that continuous training may prevent early transitions to frailty and mitigate age-related functional decline [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, the study presents some limitations, including the small sample size, high baseline functional level, and the absence of a control group. These factors limit the generalizability of the findings and hinder the ability to determine whether the observed changes resulted from the intervention itself or from other factors, such as natural aging. Future research should include control groups and stratify participants by baseline fall risk and psychological profiles to better understand differential responses. Additionally, integrating dual-task or cognitive-behavioral components may improve psychological outcomes, particularly fear of falling, which appears partially independent of physical improvements.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis three-year longitudinal study provides robust evidence supporting the effectiveness of sustained participation in multimodal exercise programs for promoting functional health and reducing fall risk in physically active community-dwelling older adults. Meaningful improvements were observed in gait performance, postural balance, and upper-limb strength, accompanied by a consistent trend toward fewer fall episodes and reduced balance-related complaints over time. Although psychological outcomes did not reach statistical significance, the maintenance of high confidence levels alongside functional gains reinforces the preventive value of continued engagement in structured and supervised exercise. Additionally, the incorporation of educational strategies specifically focused on fall prevention within exercise programs may further enhance psychological outcomes, such as reducing fear of falling and improving balance confidence.\u003c/p\u003e \u003cp\u003eThese findings highlight that even older adults already engaged in regular physical activity benefit significantly from targeted multimodal training, which appears to counteract age-related neuromuscular decline and support the preservation of functional independence. From a public health perspective, long-term supervised exercise programs should be considered a key strategy to promote healthy aging, delay the onset of frailty, and lessen the healthcare burden associated with falls. Future studies with larger samples and neurophysiological assessments are recommended to confirm these findings and further elucidate the mechanisms underlying the observed functional adaptations.\u003c/p\u003e"},{"header":"Statements and Declarations","content":"\u003cp\u003eEthical approval and informed consent\u003cbr\u003e\u0026nbsp;The study was approved by the Ethics Committee of Instituto Piaget (Ref: CE-Piaget-2022-03). All participants provided written informed consent prior to participation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003cbr\u003e\u003c/strong\u003eWritten informed consent was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003cbr\u003e\u003c/strong\u003eNot applicable – the manuscript does not contain any identifiable personal data, images, or videos.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of conflicting interest\u003cbr\u003e\u003c/strong\u003eThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding statement\u003cbr\u003e\u003c/strong\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003cbr\u003e\u003c/strong\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eInstituto Nacional de Estat\u0026iacute;stica. 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Aging\u003c/em\u003e. \u003cb\u003e14\u003c/b\u003e, 1681\u0026ndash;1691. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2147/CIA.S194543\u003c/span\u003e\u003cspan address=\"10.2147/CIA.S194543\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"older adults, multimodal exercise, fall prevention, functional fitness, balance confidence","lastPublishedDoi":"10.21203/rs.3.rs-8262744/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8262744/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: Falls remain a public health concern among physically active older adults. This study examined the long-term effects of a three-year supervised multimodal exercise program on functional, psychological, and fall-related outcomes in active community-dwelling older adults.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMethods: Twenty-nine participants (mean age 72.0 ± 4.9 years) were assessed annually for three years. Functional measures included gait speed/cadence, TUG, 5xSTS, handgrip strength, and balance (SF-FAB). Psychological parameters (FES-I, ABC) and fall-related variables were also evaluated.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResults: Significant improvements were observed in gait speed, cadence, TUG, handgrip strength, and balance. Lower-limb strength remained stable. Psychological scores did not change significantly but remained high. Falls and balance complaints decreased over the first two years.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConclusions: Long-term participation in supervised multimodal exercise promotes meaningful functional improvements and may prevent falls, even in active older adults. These findings support its integration into community-based aging and fall prevention strategies.\u003c/p\u003e","manuscriptTitle":"Effects of a Multimodal Exercise Program on Functional Outcomes and Fall Risk in Physically Active Older Adults: A Longitudinal Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-16 16:27:37","doi":"10.21203/rs.3.rs-8262744/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3ef7108a-a3e3-46da-913f-9719a42ac3b9","owner":[],"postedDate":"December 16th, 2025","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-05T09:37:49+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":59583707,"name":"Health sciences/Health care"},{"id":59583708,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-05-05T10:13:25+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-16 16:27:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8262744","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8262744","identity":"rs-8262744","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}