Longitudinal transitions in frailty and their impact on quality of life investigated by a 5-year community study

Longitudinal transitions in frailty and their impact on quality of life investigated by a 5-year community 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 Longitudinal transitions in frailty and their impact on quality of life investigated by a 5-year community study Ryotaro Oishi, Naoki Segi, Masaki Okazaki, Sadayuki Ito, Jun Ouchida, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5729095/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Apr, 2025 Read the published version in Scientific Reports → Version 1 posted 8 You are reading this latest preprint version Abstract The purpose of this study was to determine the association between frailty and quality of life (QOL) in a five-year longitudinal cohort of community-dwelling middle-aged and older adults and determine how to identify health-related QOL changes. This study included 124 volunteers (67 women; mean 65 years at baseline) who underwent health checkups in 2014 and 2019. The association between frailty status (robust, prefrail, frail), according to the Japanese Cardiovascular Health Study criteria, and health-related QOL, measured with the SF-36 questionnaire, were investigated. Five-year changes in frailty status were categorized into improved, maintained, and worsened groups. The baseline prevalence of prefrailty and frailty were 44.4% and 7.2%, respectively. Five years later, the frailty of 20 participants improved, 66 maintained frailty status, and frailty worsened in 38 participants. Significant trends toward higher scores on the physical component summary (PCS), role/social component summary (RCS), and subscales of physical functioning, role-physical, vitality, social functioning, and role-emotional were detected across groups with improvements in their frailty status from 2014 to 2019. The fully adjusted multivariable regression model revealed significantly higher PCS scores (β, 12.9; 95% confidence interval (CI), 6.0 to 19.9) and RCS scores (β, 13.6; 95% CI, 6.6 to 20.6) compared with the worsened group. In conclusion, this longitudinal cohort study demonstrates that frailty status is not static and improvements or maintenance of frailty are associated with better physical and social QOL outcomes. Addressing frailty early may reverse or mitigate its impact and improve the overall well-being of older adults. Biological sciences/Developmental biology/Ageing Health sciences/Health care/Geriatrics Health sciences/Medical research/Epidemiology frail prefrail quality of life (QOL) community-dwelling population longitudinal study Yakumo study Figures Figure 1 Figure 2 Figure 3 Introduction Frailty is a clinical syndrome marked by a decline in an individual’s quality of life due to age-related reductions in physiological reserve 1 . This syndrome represents an intermediate state between robust health and overt disability, increasing vulnerability to adverse health outcomes, including falls, disability, and mortality 2 . Attention has recently shifted toward a condition termed “prefrailty,” which precedes frailty and represents a stage where individuals are at a heightened risk of transitioning into a frail state 3 . Prefrail individuals, although not yet frail, often experience prolonged hospital stays and are at a higher risk of postoperative complications 4 , 5 . The prevalence of prefrailty exceeds the prevalence of frailty in the general population, including individuals living independently within the community 1 , 6 , 7 . Despite the significant implications, prefrailty frequently lacks symptoms, making early detection and intervention difficult 2 . The trajectory between different frailty states, including robust, prefrail, frail, and disabled, is recognized as a dynamic continuum of transitions over time 8 – 10 . However, comprehensive studies detailing these transitions are limited, with significant gaps in understanding the mechanisms and risk factors that drive changes between frailty states 3 . Prefrailty negatively influences the quality of life (QOL) across physical, mental, and social domains 11 – 13 , but the extent and nature of this impact are not well-understood 14 . Similarly, the interactions between frailty status and health-related QOL, especially over time, are not yet fully understood. A significant proportion of individuals at the prefrail stage are middle-aged and older adults living independently in communities 15 . Understanding how shifts in frailty status affect QOL is critical. For example, determining if frail or prefrail individuals can transition back to robust individuals with improved QOL is clinically relevant. The ability to transition back to the robust state broadens the implications of community-based health interventions, as appropriate interventions such as targeted exercise can ameliorate frailty 8 , 16 . Thus, understanding longitudinal changes in frailty status in community-dwelling individuals and determining the impact of frailty changes on health-related QOL and modifiable factors for improvement are essential. The present study aimed to fill these knowledge gaps by conducting a longitudinal analysis of frailty status among middle-aged and older adults in a community setting. The objective of this study was to determine the effects of transitions between frailty states over five years on health-related QOL, measured with the SF-36 survey. This analysis will provide insights into the reversibility of frailty and identify potential intervention points to enhance the well-being of community-dwelling adults. Methods Study population The study included middle-aged and older volunteers who participated in the Yakumo study 15,17,18 of community health checkups conducted annually since 1982. The Yakumo study included internal medicine, orthopedic, and psychiatric evaluations of the participants. The population of Yakumo is approximately 15,000 and ≥65 years are 35% 19 . Japan population ≥65 years was 28.4% in 2019 20 . Thus, the aging rate in Yakumo town was approximately 7% higher than that of Japan as a whole. An announcement outlining the aims of the health screening program was mailed annually to residents aged ≥ 40 years. The annual response rate of Yakumo town residents was approximately 12%. The inclusion criteria for the study were that participants had given written consent to participate in the study and underwent orthopedic and physical function examinations at the 2014 health checkup. The exclusion criteria were not participating in the 2019 health checkup and missing data on frailty status. All participants who had the data on change in frailty status completed the SF-36 questionnaire (Figure 1). Our institute’s ethics committee for human research and institutional review board approved the study protocol. Written informed consent was obtained from all participants. The study was conducted in accordance with the principles of the Declaration of Helsinki. Longitudinal study design and grouping Of the 583 participants enrolled in the Yakumo study in 2014, 231 participants attended the 2019 health checkup, and 124 of those participants completed the frailty status and health-related QOL assessments and were included in this study (Figure 1, Supplementary Table 1). Participants were categorized into three subgroups based on their frailty status (robust, prefrail, and frail), which was assessed using J-CHS criteria. Individuals were then categorized into three groups according to changes in frailty status from 2014 to 2019, as follows: improved group, participants who changed from prefrail to robust or from frail to prefrail or robust; maintained group, participants who maintained their frailty status; worsened group, participants who changed from robust to prefrail or frail or changed from prefrail to frail. Variables Parameters were collected from the checkups in 2014 and 2019, including age, sex, comorbidities (hypertension, diabetes mellitus, and chronic kidney disease), body mass index (BMI), fat mass index, fat-free mass index, waist circumference, body fat percentage, grip strength, and 10-meter walking time. Grip strength was assessed once per hand in a standing position, and the mean value was used for the analysis. The 10-meter walking time was measured once at the end point; participants walked 10 meters with a 3-meter buffer at their fastest pace. Data on personal weight loss (2 kg or more within 6 months), fatigue (within the past 2 weeks), regular physical activity habits, and QOL were collected using a questionnaire. The frailty status was diagnosed based on the Japanese Cardiovascular Health Study (J-CHS) criteria 21 . The J-CHS criteria included the following: 1) weight loss, unintentional loss of 2–3 kg or more within the previous 6 months; 2) walking speed, < 1.0 m/s; 3) muscle weakness, grip strength < 26.0 kg for men and < 18.0 kg for women, based on the 2014 Asian Working Group for Sarcopenia criteria; 4) fatigue, self-reported exhaustion assessed by asking the following question: “In the past 2 weeks, have you felt tired without a reason?”; 5) diminished physical activity, physical inactivity was defined as those who answered “no” to both of the following questions: “Do you engage in moderate levels of physical exercise or sports aimed at health? Do you engage in low levels of physical exercise aimed at health?”. According to the J-CHS criteria, participants were stratified into three groups, as follows: robust: no applicable components; prefrail: 1–2 components applied; frail: ≥ 3 components applied. The health-related QOL was assessed using the Medical Outcome Study Short-Form 36-Item Health Survey (SF-36, Japanese version 2.0), encompassing three component summary scores tailored to Japanese values and including a physical component summary (PCS), a mental component summary (MCS), a role/social component summary (RCS), and eight subscales (physical functioning, role-physical, bodily pain, general health perception, vitality, social functioning, role-emotional, and mental health). Statistical analyses All statistical analyses were conducted utilizing Stata MP 18.0 (StataCorp., TX, USA) and R 4.4.0 (http://www.R-project.org). Continuous variables are presented as means ± standard deviations for normally distributed data or medians with interquartile ranges (IQRs) for non-normally distributed data. Categorical variables are presented as numbers (%). Subgroup differences across baseline frailty status in 2014 were assessed using trend tests, including the Cochran–Armitage trend test and the Cuzick test, as appropriate. Paired t-tests or Wilcoxon signed-rank tests were used to test within-individual differences in the QOL scores for the three component summaries and the eight subscales between 2014 and 2019. A two-tailed P-value <0.05 was considered statistically significant, except for the eight subscales measured by the SF-36, for which the Bonferroni adjustment for multiple comparisons was applied with an adjusted significance threshold of P < 0.0063 (0.05/8). Participants were categorized into three groups according to their 5-year change in frailty status from 2014 to 2019. Within-individual differences across the three groups in the SF-36-derived QOL component summary scores (PCS, MCS, and RCS) and eight subscales were assessed using Cuzick’s test for trends, with exact p-values calculated using Monte Carlo permutations. The association between within-individual differences in the SF-36-derived QOL component summary scores and the three groups stratified by the changes in their frailty status from 2014 to 2019 was evaluated using multivariable linear regression analysis. Coefficients with 95% confidence intervals (CIs) were estimated for each of the improved and maintained groups as categorical variables using the worsened group as the reference. Cardiovascular disease was defined as an adjustment variable with either cerebrovascular disease or ischemic heart disease. Using three levels of sequential adjustments, the following models were developed: (i) unadjusted model, (ii) age- and sex-adjusted model (including age as a continuous variable and sex), and (iii) fully adjusted model (including age, sex, BMI, and baseline comorbidities such as hypertension, diabetes mellitus, chronic kidney disease, cardiovascular disease, and cancer). The residuals were checked for normal distribution using a histogram and a normal P-P plot. The Variance Inflation Factor (VIF) metric showed that all adjustment covariates had VIF values below 2.0, indicating only moderate multicollinearity. Results The baseline demographic and clinical characteristics of the three subgroups according to frailty status in 2014 are shown in Table 1 . The mean baseline age of the 124 participants was 65.0 ± 7.3 years, and 64 (52%) participants were women. Statistically significant trends toward lower grip strength and a higher percentage of women were found across the worse baseline frailty status. After 5 years, 66 participants maintained their frailty status, 38 participants worsened (26 from robust to prefrail, 7 from robust to frail, and 5 from prefrail to frail), and 20 participants improved (14 from prefrail to robust, 4 from frail to prefrail, and 2 from frail to robust). The number of participants who met the J-CHS criteria for prefrailty and frailty increased with aging. At baseline, 55 (44.4%) participants were prefrail and 9 (7.2%) were frail; in 2019, 66 (53.2%) participants were prefrail and 15 (12.1%) were frail (Fig. 2 ). Table 1 Baseline characteristics of the analytic cohort of the 124 participants in 2014. Subgroup of the baseline frailty status Total (n = 124) Robust (n = 60) Prefrail (n = 55) Frail (n = 9) P-trend Age, years 65.0 ± 7.3 64.2 ± 7.7 65.9 ± 7.2 65.3 ± 5.1 0.21 Age categories 0.24 40 to < 50 years 2% 2% 2% 0% 50 to < 60 years 21% 28% 15% 11% 60 to < 70 years 56% 50% 58% 78% 70 to < 80 years 18% 17% 22% 11% 80 to < 90 years 3% 3% 3% 0% Women 52% 38% 60% 89% 0.001 Comorbidities Hypertension 39% 45% 33% 33% 0.21 Diabetes mellitus 15% 12% 20% 11% 0.47 Chronic kidney disease 13% 15% 13% 0% 0.30 Cerebrovascular disease 2% 3% 2% 0% 0.47 Ischemic heart disease 4% 3% 5% 0% 0.97 Cancer 3% 3% 4% 0% 0.77 Body mass index, kg/m 2 23.8 ± 2.9 24.0 ± 2.8 23.4 ± 2.7 25.5 ± 4.5 0.71 Fat mass index, kg/m 2 7.0 ± 2.4 6.6 ± 2.2 7.1 ± 2.3 9.2 ± 3.3 0.016 Fat-free mass index, kg/m 2 16.8 ± 1.9 17.4 ± 1.9 16.3 ± 1.9 16.2 ± 1.5 0.008 Body fat percentage, % 28.9 ± 7.5 27.2 ± 7.1 29.8 ± 7.7 35.3 ± 6.8 0.002 Grip strength, kg 29.0 ± 8.5 31.8 ± 7.7 26.8 ± 8.3 22.9 ± 7.1 < 0.001 10-m walking time, s 5.5 ± 0.7 5.4 ± 0.6 5.5 ± 0.6 6.5 ± 2.1 0.17 Participants who met the J-CHS criteria Weight loss 11% 0% 20% 22% < 0.001 Weakness 26% 0% 47% 67% < 0.001 Exhaustion 19% 0% 27% 100% < 0.001 Slowness 6% 0% 4% 67% < 0.001 Low physical activity 20% 0% 29% 100% < 0.001 Laboratory measurements Hemoglobin, g/dL 13.7 ± 1.3 13.9 ± 1.2 13.7 ± 1.5 12.9 ± 1.2 0.015 Albumin, g/dL 4.4 ± 0.3 4.5 ± 0.3 4.4 ± 0.3 4.4 ± 0.3 0.23 Creatinine, mg/dL 0.74 ± 0.2 0.78 ± 0.2 0.73 ± 0.2 0.59 ± 0.1 < 0.001 Potassium, mEq/L 4.2 ± 0.3 4.2 ± 0.3 4.3 ± 0.4 4.2 ± 0.2 0.89 Total cholesterol, mg/dL 209 ± 28 212 ± 26 206 ± 31 207 ± 13 0.29 J-CHS, Japanese Cardiovascular Health Study. The baseline QOL scores representing physical, mental, and social QOL were 49.3 ± 10.1, 53.3 ± 8.9, and 52.2 ± 8.3, respectively, in 2014. In 2019, the differences in PCS within the QOL PCS score was − 1.4 (95% CI, − 1.4 to 0.8; p = 0.21), the difference in MCS was − 1.4 (95% CI, − 3.2 to 0.4; P = 0.11), and the difference in the RCS was − 2.8 (95% CI, − 5.0 to − 0.6; p = 0.014). In the post hoc analysis of the eight subscales of the SF-36, significant reductions were noted from 2014 to 2019 in bodily pain (75.2 ± 22.7 vs. 66.6 ± 21.6, p < 0.001), vitality (70.5 ± 17.3 vs. 62.0 ± 15.7, p < 0.001), and role-emotional (93.1 ± 13.6 vs. 86.8 ± 19.1, p < 0.001) using the adjusted significance levels for multiple comparisons (Table 2 ). Table 2 Comparison of health-related quality of life measured by SF-36 ( Japanese version 2.0) between 2014 and 2019 36-item Short-Form Survey Baseline (n = 124) After 5 yeas (n = 124) Difference within individuals a [95% CI] P-value Summary score 49.3 ± 10.1 47.9 ± 9.9 −1.4 [− 1.4 to 0.8] 0.21 Physical component summary 49.3 ± 10.1 47.9 ± 9.9 −1.4 [− 1.4 to 0.8] 0.21 Mental component summary 53.3 ± 8.9 51.9 ± 7.6 −1.4 [− 3.2 to 0.4] 0.11 Role/social component summary 52.2 ± 8.3 49.4 ± 10.4 −2.8 [− 5.0 to − 0.6] 0.014 Physical component subscale Physical functioning 90.7 ± 12.4 87.8 ± 14.7 −2.9 [− 5.7 to − 0.02] 0.047 Role-physical 91.1 ± 16.4 85.8 ± 19.3 −5.3 [− 9.5 to − 0.12] 0.011 Bodily pain 75.2 ± 22.7 66.6 ± 21.6 −8.6 [− 13.4 to − 3.9] < 0.001 General health perception 66.7 ± 17.1 67.6 ± 17.7 0.8 [− 3.0 to 5.0] 0.63 Mental component subscale Vitality 70.5 ± 17.3 62.0 ± 15.7 −8.5 [− 11.9 to − 5.0] < 0.001 Social functioning 92.1 ± 15.5 88.0 ± 18.1 −4.1 [− 8.2 to − 0.1] 0.044 Role-emotional 93.1 ± 13.6 86.8 ± 19.1 −6.3 [− 10.0 to − 2.6] < 0.001 Mental health 77.6 ± 18.5 75.3 ± 17.1 −2.3 [− 5.9 to 1.4] 0.22 a The difference was calculated for each individual by subtracting the 2014 health-related quality of life scores from the 2019 scores. SF-36, 36-Item Short-Form Health Survey; CI, confidence interval. Statistically significant trends toward higher scores on the PCS, RCS, and subscales of physical functioning, role-physical, vitality, social functioning, and role-emotional were detected across groups with improvements in frailty status from 2014 to 2019 (Fig. 3 , Table 3 ). In the multivariable linear regression analysis, the fully adjusted model indicated that the improved group was significantly associated with higher PCS (β, 12.9; 95% CI, 6.0 to 19.9) and RCS (β, 13.6; 95% CI, 6.6 to 20.6) than the worsened group (Table 4 ). Moreover, RCS was significantly higher in the maintained group compared with RCS in the worsened group in the fully adjusted model (β, 8.1; 95% CI, 3.2 to 13.0). In the subgroup analysis of the 55 participants who were prefrail at baseline, the fully adjusted model showed that the improved group was significantly associated with higher PCS (β, 20.2; 95% CI, 4.2 to 36.2) and RCS (β, 20.8; 95% CI, 5.5 to 36.2) than the worsened group, and the maintained group had significantly higher RCS (β, 16.7; 95% CI, 3.6 to 29.9) than the worsened group (Table 5 ). Table 3 Differences within individuals in SF-36 derived health-related quality of life between 2014 and 2019 across groups categorized by the 5-year change in frailty status. Change in frailty status between 2014 and 2019 in overall participants Improved (n = 20) Maintained (n = 66) Worsened (n = 38) SF-36-derived health-related QOL Difference within Individuals a [95% CI] Difference within individuals a [95% CI] Difference within individuals a [95% CI] P-trend b Summary score Physical component summary 7.6 [0.6 to 14.5] −1.8 [− 4.5 to 0.9] −5.4 [− 9.4 to − 1.4] 0.002 Mental component summary 1.8 [− 2.7 to 6.4] −1.9 [− 4.4 to 0.5] −2.2 [− 5.5 to 1.0] 0.17 Role/social component summary 3.9 [− 1.8 to 9.7] −1.4 [− 3.8 to 1.1] −8.8 [− 13.4 to − 4.1] 0.001 Physical component subscale Physical functioning 11.3 [1.9 to 20.6] −3.0 [− 5.7 to − 0.3] −10.1 [− 15.5 to − 4.7] < 0.001 Role-physical 15.0 [1.6 to 28.4] −2.7 [− 6.6 to 1.1] −20.6 [− 27.8 to − 13.3] < 0.001 Bodily pain 5.6 [− 7.9 to 19.1] −8.7 [− 15.7 to − 1.7] −16.0 [− 22.4 to − 9.7] 0.015 General health perception 15.5 [5.7 to 25.3] −1.2 [− 6.9 to 4.4] −2.8 [− 9.3 to 3.7] 0.009 Mental component subscale Vitality 6.3 [− 1.0 to 13.5] −6.9 [− 11.5 to − 2.3] −18.9 [− 24.4 to − 13.5] < 0.001 Social functioning 9.4 [− 1.7 to 20.4] −3.0 [− 8.0 to 2.0] −13.2 [− 20.6 to − 5.8] < 0.001 Role-emotional 11.3 [1.5 to 21.0] −5.7 [− 9.7 to − 1.7] −16.7 [− 23.7 to − 9.6] < 0.001 Mental health 6.5 [− 4.7 to 17.7] −2.8 [− 7.4 to 1.8] −6.1 [− 13.0 to 0.9] 0.04 a The difference was calculated for each individual by subtracting the 2014 health-related quality of life scores from the 2019 scores. b Group differences were evaluated using Cuzick’s test for trend with exact p-values by Monte Carlo permutations. CI, confidence interval. Table 4 Multivariable linear regression analysis of the difference between 2014 and 2019 on the three component summary scores of the health-related quality of life for each group categorized by each individual’s 5-year change in frailty status. Change in frailty status between 2014 and 2019 in overall participants Improved (n = 20) Maintained (n = 66) Worsened (n = 38) Multivariable regression models β 95% CI P-value β 95% CI P-value β 95% CI P-value Physical component summary score Model 1: Unadjusted 13.0 6.5 to 19.5 < 0.001 3.6 −1.2 to 8.4 0.14 Reference Reference n/a Model 2: Age- and sex-adjusted 12.5 5.7 to 19.3 < 0.001 3.5 −1.3 to 8.3 0.15 Reference Reference n/a Model 3: Fully adjusted a 12.9 6.0 to 19.9 < 0.001 3.5 −1.4 to 8.4 0.16 Reference Reference n/a Mental component summary score Model 1: Unadjusted 4.0 −1.4 to 9.4 0.14 0.3 −3.7 to 4.3 0.89 Reference Reference n/a Model 2: Age and sex adjusted 4.0 −1.7 to 9.6 0.17 0.3 −3.8 to 4.3 0.89 Reference Reference n/a Model 3: Fully adjusted a 3.7 −2.1 to 9.6 0.21 0.7 −3.4 to 4.8 0.73 Reference Reference n/a Role/social component summary score Model 1: Unadjusted 12.7 6.3 to 19.1 < 0.001 7.4 2.7 to 12.1 < 0.001 Reference Reference n/a Model 2: Age and sex adjusted 13.0 6.3 to 19.7 < 0.001 7.5 2.7 to 12.3 0.002 Reference Reference n/a Model 3: Fully-adjusted a 13.6 6.6 to 20.6 < 0.001 8.1 3.2 to 13.0 0.002 Reference Reference n/a a The fully adjusted model for multivariable regression analysis includes age, sex, body mass index, diabetes mellitus, chronic kidney disease, cardiovascular disease, and cancer as covariates. CI, confidence interval; n/a, not applicable. Table 5 A subgroup analysis of 55 participants with prefrailty at baseline using a multivariable linear regression model to estimate the difference between 2014 and 2019 in three component summary scores for each group stratified by the 5-year change in frailty status. Trends in frailty scores from 2014 to 2019 among participants with prefrailty Improved (n = 14) Maintained (n = 36) Worsened (n = 5) Multivariable regression models β 95% CI P-value β 95% CI P-value β 95% CI P-value Physical Component Summary score Model 1: Unadjusted 17.3 3.9 to 30.6 0.012 10.7 −1.4 to 22.9 0.084 reference reference n/a Model 2: Age- and sex-adjusted 17.4 4.0 to 31.0 0.012 11.1 −1.2 to 23.4 0.076 reference reference n/a Model 3: Fully-adjusted a 20.2 4.2 to 36.2 0.015 11.8 −1.9 to 25.5 0.090 reference reference n/a Mental Component Summary score Model 1: Unadjusted −0.1 −11.8 to 11.6 0.98 −3.8 −14.5 to 6.9 0.48 reference reference n/a Model 2: Age- and sex-adjusted 0.3 −11.5 to 12.1 0.96 −3.5 −14.3 to 7.3 0.52 reference reference n/a Model 3: Fully-adjusted a 0.6 −12.7 to 13.8 0.93 −4.4 −15.7 to 6.9 0.44 reference reference n/a Role/Social Component Summary score Model 1: Unadjusted 22.0 9.3 to 34.6 0.001 17.0 5.4 to 28.5 0.005 reference reference n/a Model 2: Age- and sex-adjusted 22.2 9.2 to 35.1 0.001 17.1 5.3 to 28.9 0.005 reference reference n/a Model 3: Fully-adjusted a 20.8 5.5 to 36.2 0.009 16.7 3.6 to 29.9 0.009 reference reference n/a a The fully adjusted model for multivariable regression analysis includes age, sex, body mass index, hypertension, diabetes mellitus, chronic kidney disease, cardiovascular disease, and cancer as covariates. CI, confidence interval; n/a, not applicable. Discussion This study provides valuable insights into the longitudinal changes and reversibility of frailty status, impacting health-related QOL in middle-aged and older adults living independently in the community. The results demonstrate that frailty, often considered a progressive and inevitable consequence of aging, can be reversed. Over five years, participants with improved or maintained frailty status exhibited significantly better physical and social QOL outcomes compared to participants with worsened frailty status. These findings emphasize the importance of early intervention and monitoring frailty in community-dwelling populations to enhance QOL and mitigate age-related decline. The prevalence and progression of frailty over time are noteworthy. Although various studies showed that frailty associated with illness is reversible 3 , 22 , 23 , longitudinal assessments of frailty in “healthy” community-dwelling individuals is limited. In agreement with previous studies, our results demonstrated a significant increase in frailty with age. Frailty status worsened in approximately 30% of participants in our study, including transitions from prefrail to frail. Previous longitudinal studies reported similar transition rates from robust to prefrail or frail of 28.0–33.9% 13,24,25 . Geographic and racial disparities, differences in age groups, differences in observation periods, and differences in assessment methods may have contributed to differences in frailty status changes 2 , 26 . Of note, many of the populations in previous reports were heterogeneous; the number of robust participants at baseline ranged from 32.0–56.0% in previous reports. Thus, our results may be generalizable to longitudinal changes in frailty status among community-dwelling middle-aged and older adults. Our results align with prior research showing that QOL tends to decrease with age, particularly after the age of 70 27–29 . Participants in the current study had a mean age of 65 in 2014, and the overall QOL declined over the five years of the study. However, individuals who improved or maintained their frailty status exhibited better physical and social QOL scores, suggesting that targeted interventions such as exercise and social engagement may prevent or reverse QOL decreases, even in an aging population. The multifaceted impact of frailty on QOL, particularly the negative correlations between frailty status and various aspects of QOL 12 , 30 , is evident in our findings. Previous studies primarily focused on the physical aspects of frailty. However, our study highlights the significance of social well-being. Participants who maintained or improved their frailty status experienced better physical functioning and improved social functioning, underscoring the importance of social participation in mitigating frailty. In contrast, mental QOL did not exhibit significant differences across frailty groups. This finding suggests that physical and social domains are closely linked to frailty status, but mental health is influenced by a broader range of factors, including depression, anxiety, and vitality 13 , 31 , 32 , which were not fully captured in our study. Importantly, our research demonstrates that QOL improvements are not limited to individuals who entirely recover from frailty. Even participants who maintained their frailty status showed better social QOL 33 compared with participants with worsened frailty. Communication and social participation with neighbors may be important for recovery from frailty or prevention of worsening frailty 22 , 34 , 35 . Our results demonstrate an association between changes in frailty status and social involvement, which is particularly relevant for public health strategies aimed at improving the well-being of older adults. Interventions that help maintain frailty status may improve recovery and play a vital role in enhancing the social and physical aspects of QOL. Our study is unique in its longitudinal approach, assessing frailty and QOL changes over five years. Previous studies examined the cross-sectional relationship between frailty and QOL, but few studies have explored the dynamic nature of frailty and its impact on QOL over time. Our findings suggest that frailty is reversible and improvements in frailty status are strongly associated with better QOL outcomes. This highlights the need for continued research into the factors that contribute to frailty improvement and the development of interventions aimed at the recovery and stabilization of frailty in aging populations. One limitation of this study is the potential generalization limitation due to the J-CHS criteria employed to discriminate frailty. The complexity and diversity of physiological dysregulation resulting from frailty has led to the development of many assessment tools 36 ; two major types of assessment methods have been proposed. The deficit accumulation model 37 , represented by the Frailty Index, estimates frailty status by cumulatively assessing a patient’s comorbidities. On the other hand, phenotype models, such as the one by Fried et al. 38 , are suitable for assessing the preliminary stages of the need for nursing care and can select older people for intervention at an early stage 39 . Additionally, the CHS criteria include a wide range of elements, including physical, social, and psychological domains, which are essential for a comprehensive assessment of frailty. Thus, the multidimensional approach of the J-CHS criteria may allow for more accurate identification of frailty compared to methods that focus solely on physical capacity or subjective questionnaires 21 , 40 . Other several limitations to this study should be acknowledged. First, selection bias introduced by the inclusion of relatively healthy volunteers who participated in two health checkups may have affected the generalizability of our findings. Second, the five-year follow-up period and the use of only two assessment time points may have limited our ability to capture the full trajectory of frailty and QOL changes. Third, the Yakumo study mainly focused on health status of the organ and musculoskeletal systems and QOL, socioeconomic factors such as the educational status of the participants were not available. Forth, gait status was assessed at 10-m walking test due to time constraints of the health checkup so that may not be as generalizable as the more common 6-minute walk test. However, we believe that this limitation is small because the correlation between these two tests has been demonstrated in recent years 41 , 42 . Finally, single assessment tools, such as the J-CHS criteria for frailty and the SF-36 for QOL, may not fully encompass the complexity of these conditions. Conclusions This longitudinal cohort study demonstrates that frailty is not static and improvements or maintenance of frailty are associated with better physical and social QOL outcomes. These findings highlight the importance of proactive monitoring and intervention in community-dwelling middle-aged and older adults to enhance QOL and promote healthy aging. Addressing frailty early may help reverse or mitigate the impact of frailty and improve the overall well-being of older adults. Declarations Acknowledgements The authors are grateful to the staff of the Comprehensive Health Care Program in Yakumo, Hokkaido, and to Ms. Hiromi Mio and Ms. Marie Inagaki at Nagoya University for their assistance throughout this study. We would also like to thank Enago (https://www.enago.jp) for the English review. Author contributions R. Oishi and N. Segi: Conceptualization, Methodology, Investigation, Formal analysis, Data curation, Writing–original draft preparation, Visualization. M. Okazaki: Methodology, Formal analysis, Writing–original draft preparation. S. Ito, J. Ouchida, I. Yamauchi, T. Seki, Y. Takegami, and S. Ishizuka: Investigation. A. Hashizume: Formal analysis. Y. Hasegawa and S. Imagama: Supervision, Funding acquisition. H. Nakashima: Methodology, Writing–review and editing. Data availability statement The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Declaration of conflicting interests The authors declare no competing interests. Funding This work was supported by the JSPS Grants-in-Aid for Scientific Research [grant number: 18K09102]. Ethical approval The study protocol was approved by the Human Research Ethics Committee and Institutional Review Board of Nagoya University (No.2014-0207). The study procedures were performed according to the principles of the Declaration of Helsinki. Informed consent was obtained from all participants included in the study. References Clegg, A., Young, J., Iliffe, S., Rikkert, M. O. & Rockwood, K. Frailty in elderly people. The Lancet 381 , 752–762 (2013). Fried, L. P. et al. Frailty in Older Adults: Evidence for a Phenotype. J. Gerontol. Ser. A 56 , M146–M157 (2001). Kutner, N. G. & Zhang, R. Frailty as a dynamic process in a diverse cohort of older persons with dialysis-dependent CKD. Front. Nephrol. 3 , (2023). Ornaghi, P. I. et al. Frailty impact on postoperative complications and early mortality rates in patients undergoing radical cystectomy for bladder cancer: a systematic review. Arab J. Urol. 19 , 9–23 (2020). Medina-Mirapeix, F. et al. The prognosis of pre-frail chronic obstructive pulmonary disease patients for hospitalizations and mortality depends on their level of functional physical performance. Chron. Respir. Dis. 19 , 14799731221119810 (2022). Rohrmann, S. Epidemiology of Frailty in Older People. in Frailty and Cardiovascular Diseases : Research into an Elderly Population (ed. Veronese, N.) 21–27 (Springer International Publishing, Cham, 2020). doi:10.1007/978-3-030-33330-0_3. Rasiah, J. et al. Prefrailty in older adults: A concept analysis. Int. J. Nurs. Stud. 108 , 103618 (2020). Liao, Y.-Y., Chen, I.-H. & Wang, R.-Y. Effects of Kinect-based exergaming on frailty status and physical performance in prefrail and frail elderly: A randomized controlled trial. Sci. Rep. 9 , 9353 (2019). Sugie, M. et al. Effectiveness of a far-infrared low-temperature sauna program on geriatric syndrome and frailty in community-dwelling older people. Geriatr. Gerontol. Int. 20 , 892–898 (2020). Apóstolo, J. et al. Effectiveness of interventions to prevent pre-frailty and frailty progression in older adults: a systematic review. JBI Evid. Synth. 16 , 140 (2018). Haider, S. et al. Associations between daily physical activity, handgrip strength, muscle mass, physical performance and quality of life in prefrail and frail community-dwelling older adults. Qual. Life Res. 25 , 3129–3138 (2016). Papathanasiou, I. V. et al. Frailty and Quality of Life Among Community-Dwelling Older Adults. Cureus 13 , e13049 (2021). De Rui, M. et al. Changes in Frailty Status and Risk of Depression: Results From the Progetto Veneto Anziani Longitudinal Study. Am. J. Geriatr. Psychiatry 25 , 190–197 (2017). Sánchez-García, S. et al. Comparison of quality of life among community-dwelling older adults with the frailty phenotype. Qual. Life Res. 26 , 2693–2703 (2017). Imagama, S. et al. Differences of locomotive syndrome and frailty in community-dwelling middle-aged and elderly people: Pain, osteoarthritis, spinal alignment, body balance, and quality of life. Mod. Rheumatol. 30 , 921–929 (2020). Sugie, M. et al. Effectiveness of Exercise-Training on Frailty and the Specificity of Exercise Effectiveness on Frailty-Related Indices among Community Dwelling Robust, Pre-Frailty and Frailty Older Peoples. Gerontol. Geriatr. Res. 7 , 1–7 (2018). Imagama, S. et al. Influence of spinal sagittal alignment, body balance, muscle strength, and physical ability on falling of middle-aged and elderly males. Eur. Spine J. 22 , 1346–1353 (2013). Imagama, S. et al. Multivariate analysis of factors related to the absence of musculoskeletal degenerative disease in middle-aged and older people. Geriatr. Gerontol. Int. 19 , 1141–1146 (2019). Yakumo Town. https://www.town.yakumo.lg.jp/. Statistics Bureau of the Ministry of Internal Affairs and Communications Website. https://www.stat.go.jp/data/jinsui/. Satake, S. & Arai, H. The revised Japanese version of the Cardiovascular Health Study criteria (revised J-CHS criteria). Geriatr. Gerontol. Int. 20 , 992–993 (2020). Cai, Z. et al. Associations of social engagement, and loneliness with the progression and reversal of frailty: longitudinal investigations of two prospective cohorts from the UK and the USA. Am. J. Epidemiol. kwae221 (2024) doi:10.1093/aje/kwae221. Salvatori, S. et al. Reversibility of Frail Phenotype in Patients with Inflammatory Bowel Diseases. J. Clin. Med. 12 , 2658 (2023). Trevisan, C. et al. Factors Influencing Transitions Between Frailty States in Elderly Adults: The Progetto Veneto Anziani Longitudinal Study. J. Am. Geriatr. Soc. 65 , 179–184 (2017). Thompson, M. Q., Theou, O., Adams, R. J., Tucker, G. R. & Visvanathan, R. Frailty state transitions and associated factors in South Australian older adults. Geriatr. Gerontol. Int. 18 , 1549–1555 (2018). Mitnitski, A. B., Mogilner, A. J. & Rockwood, K. Accumulation of Deficits as a Proxy Measure of Aging. Sci. World J. 1 , 323–336 (2001). Corbi, G. et al. Inter-relationships between Gender, Frailty and 10-Year Survival in Older Italian Adults: an observational longitudinal study. Sci. Rep. 9 , 18416 (2019). Grden, C. R. B. et al. Associations between frailty syndrome and sociodemographic characteristics in long-lived individuals of a community. Rev. Lat. Am. Enfermagem 25 , e2886 (2017). Lee, D. R. et al. Understanding functional and social risk characteristics of frail older adults: a cross-sectional survey study. BMC Fam. Pract. 19 , 170 (2018). Kojima, G. et al. Frailty predicts trajectories of quality of life over time among British community-dwelling older people. Qual. Life Res. 25 , 1743–1750 (2016). Feng, L., Nyunt, M. S. Z., Feng, L., Yap, K. B. & Ng, T. P. Frailty Predicts New and Persistent Depressive Symptoms Among Community-Dwelling Older Adults: Findings From Singapore Longitudinal Aging Study. J. Am. Med. Dir. Assoc. 15 , 76.e7-76.e12 (2014). Makizako, H. et al. Physical Frailty Predicts Incident Depressive Symptoms in Elderly People: Prospective Findings From the Obu Study of Health Promotion for the Elderly. J. Am. Med. Dir. Assoc. 16 , 194–199 (2015). Suzukamo, Y. et al. Validation testing of a three-component model of Short Form-36 scores. J. Clin. Epidemiol. 64 , 301–308 (2011). Chu, B.-L. & Zhang, W. Impact of transient and chronic loneliness on progression and reversion of frailty in community-dwelling older adults: four-year follow-up. BMC Geriatr. 22 , 642 (2022). Takatori, K. & Matsumoto, D. Social factors associated with reversing frailty progression in community-dwelling late-stage elderly people: An observational study. PLOS ONE 16 , e0247296 (2021). Perazza L. R., Avers D. & Thompson L. V. Measurement of Frailty: Tools and Interpretation. Top. Geriatr. Rehabil. 39 , 88 (2023). Mitnitski, A. B., Mogilner, A. J. & Rockwood, K. Accumulation of Deficits as a Proxy Measure of Aging. Sci. World J. 1 , 323–336 (2001). Fried, L. P. et al. Frailty in Older Adults: Evidence for a Phenotype. J. Gerontol. Ser. A 56 , M146–M157 (2001). Kuzuya, M. [Terminology: Frailty]. J. JSPEN 3 , 114–120 (2021). Bandeen-Roche, K. et al. Phenotype of Frailty: Characterization in the Women’s Health and Aging Studies. J. Gerontol. Ser. A 61 , 262–266 (2006). Lozano-Meca, J., Montilla-Herrador, J. & Gacto-Sánchez, M. Gait speed in knee osteoarthritis: A simple 10-meter walk test predicts the distance covered in the 6-minute walk test. Musculoskelet. Sci. Pract. 72 , 102983 (2024). Chan, W. L. S. & Pin, T. W. Reliability, validity and minimal detectable change of 2-minute walk test, 6-minute walk test and 10-meter walk test in frail older adults with dementia. Exp. Gerontol. 115 , 9–18 (2019). Additional Declarations No competing interests reported. Supplementary Files YkmFrailQOLSupplTable20250320.pdf Cite Share Download PDF Status: Published Journal Publication published 30 Apr, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 02 Apr, 2025 Reviews received at journal 02 Apr, 2025 Reviews received at journal 30 Mar, 2025 Reviewers agreed at journal 28 Mar, 2025 Reviewers agreed at journal 28 Mar, 2025 Reviewers invited by journal 27 Mar, 2025 Submission checks completed at journal 27 Mar, 2025 First submitted to journal 21 Mar, 2025 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5729095","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":434723429,"identity":"d5b6e042-710d-45bb-b6bc-6a2fa500a56d","order_by":0,"name":"Ryotaro Oishi","email":"","orcid":"","institution":"Nagoya University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Ryotaro","middleName":"","lastName":"Oishi","suffix":""},{"id":434723430,"identity":"069def1b-ff40-4eec-8a59-0520e672e82c","order_by":1,"name":"Naoki Segi","email":"","orcid":"","institution":"Nagoya University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Naoki","middleName":"","lastName":"Segi","suffix":""},{"id":434723431,"identity":"d2b876d1-a3dc-4628-8848-0e919d4f1b98","order_by":2,"name":"Masaki Okazaki","email":"","orcid":"","institution":"Nagoya University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Masaki","middleName":"","lastName":"Okazaki","suffix":""},{"id":434723432,"identity":"7f4286b6-6fa4-4187-ba61-a70058ddab79","order_by":3,"name":"Sadayuki Ito","email":"","orcid":"","institution":"Nagoya University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Sadayuki","middleName":"","lastName":"Ito","suffix":""},{"id":434723433,"identity":"7078519e-9b5e-4318-b5bd-9ea718cfe3da","order_by":4,"name":"Jun Ouchida","email":"","orcid":"","institution":"Nagoya University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Ouchida","suffix":""},{"id":434723434,"identity":"e037e101-1cab-4f19-ba79-54b7efe3335c","order_by":5,"name":"Ippei Yamauchi","email":"","orcid":"","institution":"Nagoya University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Ippei","middleName":"","lastName":"Yamauchi","suffix":""},{"id":434723435,"identity":"bc7385c9-94dc-4a49-b291-c42813752d36","order_by":6,"name":"Taisuke Seki","email":"","orcid":"","institution":"Aichi Medical University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Taisuke","middleName":"","lastName":"Seki","suffix":""},{"id":434723436,"identity":"b66887e0-14e7-42d8-8488-dc28b732ebbb","order_by":7,"name":"Yasuhiko Takegami","email":"","orcid":"","institution":"Nagoya University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yasuhiko","middleName":"","lastName":"Takegami","suffix":""},{"id":434723437,"identity":"94417b61-3dc0-4da1-90b0-a848482e44b1","order_by":8,"name":"Shinya Ishizuka","email":"","orcid":"","institution":"Nagoya University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Shinya","middleName":"","lastName":"Ishizuka","suffix":""},{"id":434723438,"identity":"3c8b23e6-e2e5-45d5-977f-d3f6bda379a8","order_by":9,"name":"Atsushi Hashizume","email":"","orcid":"","institution":"Nagoya University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Atsushi","middleName":"","lastName":"Hashizume","suffix":""},{"id":434723439,"identity":"ac09dada-0651-47d4-882f-254a9fb7d08e","order_by":10,"name":"Yukiharu Hasegawa","email":"","orcid":"","institution":"Kansai University of Welfare Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yukiharu","middleName":"","lastName":"Hasegawa","suffix":""},{"id":434723440,"identity":"f09f2150-ecc6-4ee3-bfc9-50ea2c4f310c","order_by":11,"name":"Shiro Imagama","email":"","orcid":"","institution":"Nagoya University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Shiro","middleName":"","lastName":"Imagama","suffix":""},{"id":434723441,"identity":"3f3edb56-d47c-4042-88a3-1917e64b4982","order_by":12,"name":"Hiroaki Nakashima","email":"data:image/png;base64,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","orcid":"","institution":"Nagoya University Graduate School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Hiroaki","middleName":"","lastName":"Nakashima","suffix":""}],"badges":[],"createdAt":"2024-12-29 08:38:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5729095/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5729095/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-99843-7","type":"published","date":"2025-04-30T15:57:26+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79550189,"identity":"4a2b97b3-cd97-493d-972e-9cff52b5c694","added_by":"auto","created_at":"2025-03-31 06:30:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":86898,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStudy enrollment flowchart.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ-CHS, Japanese Cardiovascular Health Study.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5729095/v1/701b428634e9e9f419f4778e.png"},{"id":79550192,"identity":"780c88fe-c3f0-40ef-8985-89f3f81f3d83","added_by":"auto","created_at":"2025-03-31 06:30:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":204788,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChanges in the frailty states of the participants over 5 years.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-5729095/v1/80353d77af74d3caef9335cb.png"},{"id":79551288,"identity":"cf41135f-c485-4217-b7aa-c4431695f4e0","added_by":"auto","created_at":"2025-03-31 06:38:53","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":774599,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChanges in the SF-36 summary scores and subscales over 5 years.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-5729095/v1/99ca4d98cf7dea5d378d3ad1.png"},{"id":81987833,"identity":"9b1c5df7-0c98-4d3d-9caa-7d5802f7d40a","added_by":"auto","created_at":"2025-05-05 16:06:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2611807,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5729095/v1/72add963-3636-45b0-969c-3f6f86a31587.pdf"},{"id":79551289,"identity":"7d41dd76-1e68-418a-81d0-052b22abad28","added_by":"auto","created_at":"2025-03-31 06:38:53","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":142057,"visible":true,"origin":"","legend":"","description":"","filename":"YkmFrailQOLSupplTable20250320.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5729095/v1/812be22026e600d62ed15b8d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Longitudinal transitions in frailty and their impact on quality of life investigated by a 5-year community study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFrailty is a clinical syndrome marked by a decline in an individual\u0026rsquo;s quality of life due to age-related reductions in physiological reserve \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. This syndrome represents an intermediate state between robust health and overt disability, increasing vulnerability to adverse health outcomes, including falls, disability, and mortality \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Attention has recently shifted toward a condition termed \u0026ldquo;prefrailty,\u0026rdquo; which precedes frailty and represents a stage where individuals are at a heightened risk of transitioning into a frail state \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Prefrail individuals, although not yet frail, often experience prolonged hospital stays and are at a higher risk of postoperative complications \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. The prevalence of prefrailty exceeds the prevalence of frailty in the general population, including individuals living independently within the community \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Despite the significant implications, prefrailty frequently lacks symptoms, making early detection and intervention difficult \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe trajectory between different frailty states, including robust, prefrail, frail, and disabled, is recognized as a dynamic continuum of transitions over time \u003csup\u003e\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. However, comprehensive studies detailing these transitions are limited, with significant gaps in understanding the mechanisms and risk factors that drive changes between frailty states \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Prefrailty negatively influences the quality of life (QOL) across physical, mental, and social domains \u003csup\u003e\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, but the extent and nature of this impact are not well-understood \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Similarly, the interactions between frailty status and health-related QOL, especially over time, are not yet fully understood.\u003c/p\u003e \u003cp\u003eA significant proportion of individuals at the prefrail stage are middle-aged and older adults living independently in communities \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Understanding how shifts in frailty status affect QOL is critical. For example, determining if frail or prefrail individuals can transition back to robust individuals with improved QOL is clinically relevant. The ability to transition back to the robust state broadens the implications of community-based health interventions, as appropriate interventions such as targeted exercise can ameliorate frailty \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Thus, understanding longitudinal changes in frailty status in community-dwelling individuals and determining the impact of frailty changes on health-related QOL and modifiable factors for improvement are essential.\u003c/p\u003e \u003cp\u003eThe present study aimed to fill these knowledge gaps by conducting a longitudinal analysis of frailty status among middle-aged and older adults in a community setting. The objective of this study was to determine the effects of transitions between frailty states over five years on health-related QOL, measured with the SF-36 survey. This analysis will provide insights into the reversibility of frailty and identify potential intervention points to enhance the well-being of community-dwelling adults.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eStudy population\u003c/h2\u003e\n\u003cp\u003eThe\u0026nbsp;study included middle-aged and older volunteers who participated in the Yakumo study \u003csup\u003e15,17,18\u003c/sup\u003e of community health checkups conducted annually since 1982. The Yakumo study included internal medicine, orthopedic, and psychiatric evaluations of the participants. The population of Yakumo is approximately 15,000 and \u0026ge;65 years are 35%\u0026nbsp;\u003csup\u003e19\u003c/sup\u003e. Japan population \u0026ge;65 years was 28.4% in 2019\u0026nbsp;\u003csup\u003e20\u003c/sup\u003e. Thus, the aging rate in Yakumo town was approximately 7% higher than that of Japan as a whole.\u003c/p\u003e\n\u003cp\u003eAn announcement outlining the aims of the health screening program was mailed annually to residents aged \u0026ge; 40 years. The annual response rate of Yakumo town residents was approximately 12%. The inclusion criteria for the study were that participants had given written consent to participate in the study and underwent orthopedic and physical function examinations at the 2014 health checkup. The exclusion criteria were not participating in the 2019 health checkup and missing data on frailty status. All participants who had the data on change in frailty status completed the SF-36 questionnaire (Figure 1).\u003c/p\u003e\n\u003cp\u003eOur institute\u0026rsquo;s ethics committee for human research and institutional review board approved the study protocol. Written informed consent was obtained from all participants. The study was conducted in accordance with the principles of the Declaration of Helsinki.\u003c/p\u003e\n\u003ch2\u003eLongitudinal study design and grouping\u003c/h2\u003e\n\u003cp\u003eOf the 583 participants enrolled in the Yakumo study in 2014, 231 participants attended the 2019 health checkup, and 124 of those participants completed the frailty status and health-related QOL assessments and were included in this study\u0026nbsp;(Figure 1, Supplementary Table 1). Participants were categorized into three subgroups based on their frailty status (robust, prefrail, and frail), which was assessed using J-CHS criteria. Individuals were then categorized into three groups according to changes in frailty status from 2014 to 2019, as follows: improved group, participants who changed from prefrail to robust or from frail to prefrail or robust; maintained group, participants who maintained their frailty status; worsened group, participants who changed from robust to prefrail or frail or changed from prefrail to frail.\u003c/p\u003e\n\u003ch2\u003eVariables\u003c/h2\u003e\n\u003cp\u003eParameters were collected from the checkups in 2014 and 2019, including age, sex, comorbidities (hypertension, diabetes mellitus, and chronic kidney disease), body mass index (BMI), fat mass index, fat-free mass index, waist circumference, body fat percentage, grip strength, and 10-meter walking time. Grip strength was assessed once per hand in a standing position, and the mean value was used for the analysis. The 10-meter walking time was measured once at the end point; participants walked 10 meters with a 3-meter buffer at their fastest pace. Data on personal weight loss (2 kg or more within 6 months), fatigue (within the past 2 weeks), regular physical activity habits, and QOL were collected using a questionnaire.\u003c/p\u003e\n\u003cp\u003eThe frailty status was diagnosed based on the Japanese Cardiovascular Health Study (J-CHS) criteria \u003csup\u003e21\u003c/sup\u003e. The J-CHS criteria included the following: 1) weight loss, unintentional loss of 2\u0026ndash;3 kg or more within the previous 6 months; 2) walking speed, \u0026lt; 1.0 m/s; 3) muscle weakness, grip strength \u0026lt; 26.0 kg for men and \u0026lt; 18.0 kg for women, based on the 2014 Asian Working Group for Sarcopenia criteria; 4) fatigue, self-reported exhaustion assessed by asking the following question: \u0026ldquo;In the past 2 weeks, have you felt tired without a reason?\u0026rdquo;; 5) diminished physical activity, physical inactivity was defined as those who answered \u0026ldquo;no\u0026rdquo; to both of the following questions: \u0026ldquo;Do you engage in moderate levels of physical exercise or sports aimed at health? Do you engage in low levels of physical exercise aimed at health?\u0026rdquo;.\u0026nbsp;According to the J-CHS criteria, participants were stratified into three groups, as follows: robust: no applicable components; prefrail: 1\u0026ndash;2 components applied; frail:\u0026nbsp;\u0026ge; 3 components applied.\u003c/p\u003e\n\u003cp\u003eThe health-related QOL was assessed using the Medical Outcome Study Short-Form 36-Item Health Survey (SF-36, Japanese version 2.0), encompassing three component summary scores tailored to Japanese values and including a physical component summary (PCS), a mental component summary (MCS), a role/social component summary (RCS), and eight subscales (physical functioning, role-physical, bodily pain, general health perception, vitality, social functioning, role-emotional, and mental health).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eStatistical analyses\u003c/h2\u003e\n\u003cp\u003eAll statistical analyses were conducted utilizing Stata MP 18.0 (StataCorp., TX, USA) and R 4.4.0 (http://www.R-project.org). Continuous variables are presented as means \u0026plusmn; standard deviations for normally distributed data or medians with interquartile ranges (IQRs) for non-normally distributed data. Categorical variables are presented as numbers (%). Subgroup differences across baseline frailty status in 2014 were assessed using trend tests, including the Cochran\u0026ndash;Armitage trend test and the Cuzick test, as appropriate. Paired t-tests or Wilcoxon signed-rank tests were used to test within-individual differences in the QOL scores for the three component summaries and the eight subscales between 2014 and 2019. A two-tailed P-value \u0026lt;0.05 was considered statistically significant, except for the eight subscales measured by the SF-36, for which the Bonferroni adjustment for multiple comparisons was applied with an adjusted significance threshold of P \u0026lt; 0.0063 (0.05/8).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eParticipants were categorized into three groups according to their 5-year change in frailty status from 2014 to 2019. Within-individual differences across the three groups in the SF-36-derived QOL component summary scores (PCS, MCS, and RCS) and eight subscales were assessed using Cuzick\u0026rsquo;s test for trends, with exact p-values calculated using Monte Carlo permutations. The association between within-individual differences in the SF-36-derived QOL component summary scores and the three groups stratified by the changes in their frailty status from 2014 to 2019 was evaluated using multivariable linear regression analysis. Coefficients with 95% confidence intervals (CIs) were estimated for each of the improved and maintained groups as categorical variables using the worsened group as the reference. Cardiovascular disease was defined as an adjustment variable with either cerebrovascular disease or ischemic heart disease. Using three levels of sequential adjustments, the following models were developed: (i) unadjusted model, (ii) age- and sex-adjusted model (including age as a continuous variable and sex), and (iii) fully adjusted model (including age, sex, BMI, and baseline comorbidities such as hypertension, diabetes mellitus, chronic kidney disease, cardiovascular disease, and cancer). The residuals were checked for normal distribution using a histogram and a normal P-P plot. The Variance Inflation Factor (VIF) metric showed that all adjustment covariates had VIF values below 2.0, indicating only moderate multicollinearity.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe baseline demographic and clinical characteristics of the three subgroups according to frailty status in 2014 are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The mean baseline age of the 124 participants was 65.0\u0026thinsp;\u0026plusmn;\u0026thinsp;7.3 years, and 64 (52%) participants were women. Statistically significant trends toward lower grip strength and a higher percentage of women were found across the worse baseline frailty status. After 5 years, 66 participants maintained their frailty status, 38 participants worsened (26 from robust to prefrail, 7 from robust to frail, and 5 from prefrail to frail), and 20 participants improved (14 from prefrail to robust, 4 from frail to prefrail, and 2 from frail to robust). The number of participants who met the J-CHS criteria for prefrailty and frailty increased with aging. At baseline, 55 (44.4%) participants were prefrail and 9 (7.2%) were frail; in 2019, 66 (53.2%) participants were prefrail and 15 (12.1%) were frail (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\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\u003eBaseline characteristics of the analytic cohort of the 124 participants in 2014.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\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\u003eSubgroup of the baseline frailty status\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;124)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRobust\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;60)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePrefrail\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;55)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFrail\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP-trend\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e65.0\u0026thinsp;\u0026plusmn;\u0026thinsp;7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.2\u0026thinsp;\u0026plusmn;\u0026thinsp;7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.9\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge categories\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40 to \u0026lt;\u0026thinsp;50 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50 to \u0026lt;\u0026thinsp;60 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60 to \u0026lt;\u0026thinsp;70 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70 to \u0026lt;\u0026thinsp;80 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e80 to \u0026lt;\u0026thinsp;90 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e89%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic kidney disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCerebrovascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIschemic heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat mass index, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat-free mass index, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody fat percentage, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.9\u0026thinsp;\u0026plusmn;\u0026thinsp;7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.2\u0026thinsp;\u0026plusmn;\u0026thinsp;7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.3\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrip strength, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.0\u0026thinsp;\u0026plusmn;\u0026thinsp;8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.9\u0026thinsp;\u0026plusmn;\u0026thinsp;7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10-m walking time, s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eParticipants who met the J-CHS criteria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight loss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeakness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExhaustion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSlowness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow physical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaboratory measurements\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin, g/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlbumin, g/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine, mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotassium, mEq/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal cholesterol, mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e209\u0026thinsp;\u0026plusmn;\u0026thinsp;28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e212\u0026thinsp;\u0026plusmn;\u0026thinsp;26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e206\u0026thinsp;\u0026plusmn;\u0026thinsp;31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e207\u0026thinsp;\u0026plusmn;\u0026thinsp;13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eJ-CHS, Japanese Cardiovascular Health Study.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe baseline QOL scores representing physical, mental, and social QOL were 49.3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.1, 53.3\u0026thinsp;\u0026plusmn;\u0026thinsp;8.9, and 52.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.3, respectively, in 2014. In 2019, the differences in PCS within the QOL PCS score was \u0026minus;\u0026thinsp;1.4 (95% CI, \u0026minus;\u0026thinsp;1.4 to 0.8; p\u0026thinsp;=\u0026thinsp;0.21), the difference in MCS was \u0026minus;\u0026thinsp;1.4 (95% CI, \u0026minus;\u0026thinsp;3.2 to 0.4; P\u0026thinsp;=\u0026thinsp;0.11), and the difference in the RCS was \u0026minus;\u0026thinsp;2.8 (95% CI, \u0026minus;\u0026thinsp;5.0 to \u0026minus;\u0026thinsp;0.6; p\u0026thinsp;=\u0026thinsp;0.014). In the post hoc analysis of the eight subscales of the SF-36, significant reductions were noted from 2014 to 2019 in bodily pain (75.2\u0026thinsp;\u0026plusmn;\u0026thinsp;22.7 vs. 66.6\u0026thinsp;\u0026plusmn;\u0026thinsp;21.6, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), vitality (70.5\u0026thinsp;\u0026plusmn;\u0026thinsp;17.3 vs. 62.0\u0026thinsp;\u0026plusmn;\u0026thinsp;15.7, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and role-emotional (93.1\u0026thinsp;\u0026plusmn;\u0026thinsp;13.6 vs. 86.8\u0026thinsp;\u0026plusmn;\u0026thinsp;19.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) using the adjusted significance levels for multiple comparisons (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\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\u003e\u003cb\u003eComparison of health-related quality of life measured by SF-36\u003c/b\u003e (\u003cb\u003eJapanese version 2.0) between 2014 and 2019\u003c/b\u003e\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=\"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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36-item Short-Form Survey\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;124)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAfter 5 yeas\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;124)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDifference within individuals\u003csup\u003ea\u003c/sup\u003e [95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\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\u003eSummary score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e49.3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e47.9\u0026thinsp;\u0026plusmn;\u0026thinsp;9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;1.4 [\u0026minus;\u0026thinsp;1.4 to 0.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical component summary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e49.3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e47.9\u0026thinsp;\u0026plusmn;\u0026thinsp;9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;1.4 [\u0026minus;\u0026thinsp;1.4 to 0.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMental component summary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e53.3\u0026thinsp;\u0026plusmn;\u0026thinsp;8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e51.9\u0026thinsp;\u0026plusmn;\u0026thinsp;7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;1.4 [\u0026minus;\u0026thinsp;3.2 to 0.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRole/social component summary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e52.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e49.4\u0026thinsp;\u0026plusmn;\u0026thinsp;10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;2.8 [\u0026minus;\u0026thinsp;5.0 to \u0026minus;\u0026thinsp;0.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical component subscale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical functioning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e90.7\u0026thinsp;\u0026plusmn;\u0026thinsp;12.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e87.8\u0026thinsp;\u0026plusmn;\u0026thinsp;14.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;2.9 [\u0026minus;\u0026thinsp;5.7 to \u0026minus;\u0026thinsp;0.02]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRole-physical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e91.1\u0026thinsp;\u0026plusmn;\u0026thinsp;16.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e85.8\u0026thinsp;\u0026plusmn;\u0026thinsp;19.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;5.3 [\u0026minus;\u0026thinsp;9.5 to \u0026minus;\u0026thinsp;0.12]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBodily pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e75.2\u0026thinsp;\u0026plusmn;\u0026thinsp;22.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e66.6\u0026thinsp;\u0026plusmn;\u0026thinsp;21.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;8.6 [\u0026minus;\u0026thinsp;13.4 to \u0026minus;\u0026thinsp;3.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneral health perception\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e66.7\u0026thinsp;\u0026plusmn;\u0026thinsp;17.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e67.6\u0026thinsp;\u0026plusmn;\u0026thinsp;17.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8 [\u0026minus;\u0026thinsp;3.0 to 5.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMental component subscale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e70.5\u0026thinsp;\u0026plusmn;\u0026thinsp;17.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e62.0\u0026thinsp;\u0026plusmn;\u0026thinsp;15.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;8.5 [\u0026minus;\u0026thinsp;11.9 to \u0026minus;\u0026thinsp;5.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial functioning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e92.1\u0026thinsp;\u0026plusmn;\u0026thinsp;15.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e88.0\u0026thinsp;\u0026plusmn;\u0026thinsp;18.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;4.1 [\u0026minus;\u0026thinsp;8.2 to \u0026minus;\u0026thinsp;0.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRole-emotional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e93.1\u0026thinsp;\u0026plusmn;\u0026thinsp;13.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e86.8\u0026thinsp;\u0026plusmn;\u0026thinsp;19.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;6.3 [\u0026minus;\u0026thinsp;10.0 to \u0026minus;\u0026thinsp;2.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMental health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e77.6\u0026thinsp;\u0026plusmn;\u0026thinsp;18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e75.3\u0026thinsp;\u0026plusmn;\u0026thinsp;17.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;2.3 [\u0026minus;\u0026thinsp;5.9 to 1.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ea\u003c/sup\u003e The difference was calculated for each individual by subtracting the 2014 health-related quality of life scores from the 2019 scores.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eSF-36, 36-Item Short-Form Health Survey; CI, confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eStatistically significant trends toward higher scores on the PCS, RCS, and subscales of physical functioning, role-physical, vitality, social functioning, and role-emotional were detected across groups with improvements in frailty status from 2014 to 2019 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In the multivariable linear regression analysis, the fully adjusted model indicated that the improved group was significantly associated with higher PCS (β, 12.9; 95% CI, 6.0 to 19.9) and RCS (β, 13.6; 95% CI, 6.6 to 20.6) than the worsened group (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Moreover, RCS was significantly higher in the maintained group compared with RCS in the worsened group in the fully adjusted model (β, 8.1; 95% CI, 3.2 to 13.0). In the subgroup analysis of the 55 participants who were prefrail at baseline, the fully adjusted model showed that the improved group was significantly associated with higher PCS (β, 20.2; 95% CI, 4.2 to 36.2) and RCS (β, 20.8; 95% CI, 5.5 to 36.2) than the worsened group, and the maintained group had significantly higher RCS (β, 16.7; 95% CI, 3.6 to 29.9) than the worsened group (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\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\u003eDifferences within individuals in SF-36 derived health-related quality of life between 2014 and 2019 across groups categorized by the 5-year change in frailty status.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e \u003cp\u003eChange in frailty status between 2014 and 2019 in overall participants\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eImproved (n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMaintained (n\u0026thinsp;=\u0026thinsp;66)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWorsened (n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSF-36-derived health-related QOL\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDifference within Individuals\u003csup\u003ea\u003c/sup\u003e [95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDifference within individuals\u003csup\u003ea\u003c/sup\u003e [95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDifference within individuals\u003csup\u003ea\u003c/sup\u003e [95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP-trend\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSummary score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical component summary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.6 [0.6 to 14.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;1.8 [\u0026minus;\u0026thinsp;4.5 to 0.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;5.4 [\u0026minus;\u0026thinsp;9.4 to \u0026minus;\u0026thinsp;1.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMental component summary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.8 [\u0026minus;\u0026thinsp;2.7 to 6.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;1.9 [\u0026minus;\u0026thinsp;4.4 to 0.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;2.2 [\u0026minus;\u0026thinsp;5.5 to 1.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRole/social component summary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.9 [\u0026minus;\u0026thinsp;1.8 to 9.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;1.4 [\u0026minus;\u0026thinsp;3.8 to 1.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;8.8 [\u0026minus;\u0026thinsp;13.4 to \u0026minus;\u0026thinsp;4.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical component subscale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical functioning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.3 [1.9 to 20.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;3.0 [\u0026minus;\u0026thinsp;5.7 to \u0026minus;\u0026thinsp;0.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;10.1 [\u0026minus;\u0026thinsp;15.5 to \u0026minus;\u0026thinsp;4.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRole-physical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.0 [1.6 to 28.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;2.7 [\u0026minus;\u0026thinsp;6.6 to 1.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;20.6 [\u0026minus;\u0026thinsp;27.8 to \u0026minus;\u0026thinsp;13.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBodily pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.6 [\u0026minus;\u0026thinsp;7.9 to 19.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;8.7 [\u0026minus;\u0026thinsp;15.7 to \u0026minus;\u0026thinsp;1.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;16.0 [\u0026minus;\u0026thinsp;22.4 to \u0026minus;\u0026thinsp;9.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneral health perception\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.5 [5.7 to 25.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;1.2 [\u0026minus;\u0026thinsp;6.9 to 4.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;2.8 [\u0026minus;\u0026thinsp;9.3 to 3.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMental component subscale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.3 [\u0026minus;\u0026thinsp;1.0 to 13.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;6.9 [\u0026minus;\u0026thinsp;11.5 to \u0026minus;\u0026thinsp;2.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;18.9 [\u0026minus;\u0026thinsp;24.4 to \u0026minus;\u0026thinsp;13.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial functioning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.4 [\u0026minus;\u0026thinsp;1.7 to 20.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;3.0 [\u0026minus;\u0026thinsp;8.0 to 2.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;13.2 [\u0026minus;\u0026thinsp;20.6 to \u0026minus;\u0026thinsp;5.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRole-emotional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.3 [1.5 to 21.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;5.7 [\u0026minus;\u0026thinsp;9.7 to \u0026minus;\u0026thinsp;1.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;16.7 [\u0026minus;\u0026thinsp;23.7 to \u0026minus;\u0026thinsp;9.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMental health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.5 [\u0026minus;\u0026thinsp;4.7 to 17.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;2.8 [\u0026minus;\u0026thinsp;7.4 to 1.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;6.1 [\u0026minus;\u0026thinsp;13.0 to 0.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003ea\u003c/sup\u003e The difference was calculated for each individual by subtracting the 2014 health-related quality of life scores from the 2019 scores.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003eb\u003c/sup\u003e Group differences were evaluated using Cuzick\u0026rsquo;s test for trend with exact p-values by Monte Carlo permutations.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eCI, confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\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\u003eMultivariable linear regression analysis of the difference between 2014 and 2019 on the three component summary scores of the health-related quality of life for each group categorized by each individual\u0026rsquo;s 5-year change in frailty status.\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=\"char\" char=\".\" 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=\"char\" char=\".\" 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=\"char\" char=\".\" 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=\"char\" char=\".\" 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\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"11\" nameend=\"c12\" namest=\"c2\"\u003e \u003cp\u003eChange in frailty status between 2014 and 2019 in overall participants\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eImproved (n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eMaintained (n\u0026thinsp;=\u0026thinsp;66)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003eWorsened (n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultivariable regression models\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\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\u003ePhysical component summary score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1: Unadjusted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.5 to 19.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026minus;1.2 to 8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2: Age- and sex-adjusted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.7 to 19.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026minus;1.3 to 8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 3: Fully adjusted\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.0 to 19.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026minus;1.4 to 8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMental component summary score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1: Unadjusted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;1.4 to 9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026minus;3.7 to 4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2: Age and sex adjusted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;1.7 to 9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026minus;3.8 to 4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 3: Fully adjusted\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;2.1 to 9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026minus;3.4 to 4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRole/social component summary score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1: Unadjusted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.3 to 19.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.7 to 12.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2: Age and sex adjusted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.3 to 19.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.7 to 12.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 3: Fully-adjusted\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.6 to 20.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.2 to 13.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003e\u003csup\u003ea\u003c/sup\u003e The fully adjusted model for multivariable regression analysis includes age, sex, body mass index, diabetes mellitus, chronic kidney disease, cardiovascular disease, and cancer as covariates.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003eCI, confidence interval; n/a, not applicable.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\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\u003eA subgroup analysis of 55 participants with prefrailty at baseline using a multivariable linear regression model to estimate the difference between 2014 and 2019 in three component summary scores for each group stratified by the 5-year change in frailty status.\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=\"char\" char=\".\" 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=\"char\" char=\".\" 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=\"char\" char=\".\" 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=\"char\" char=\".\" 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\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"11\" nameend=\"c12\" namest=\"c2\"\u003e \u003cp\u003eTrends in frailty scores from 2014 to 2019 among participants with prefrailty\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eImproved (n\u0026thinsp;=\u0026thinsp;14)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eMaintained (n\u0026thinsp;=\u0026thinsp;36)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003eWorsened (n\u0026thinsp;=\u0026thinsp;5)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultivariable regression models\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\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\u003ePhysical Component Summary score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1: Unadjusted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.9 to 30.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026minus;1.4 to 22.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2: Age- and sex-adjusted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.0 to 31.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026minus;1.2 to 23.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 3: Fully-adjusted\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.2 to 36.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026minus;1.9 to 25.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMental Component Summary score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1: Unadjusted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;11.8 to 11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026minus;14.5 to 6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2: Age- and sex-adjusted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;11.5 to 12.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026minus;14.3 to 7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 3: Fully-adjusted\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;12.7 to 13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026minus;15.7 to 6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRole/Social Component Summary score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1: Unadjusted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.3 to 34.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.4 to 28.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2: Age- and sex-adjusted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.2 to 35.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.3 to 28.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 3: Fully-adjusted\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.5 to 36.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.6 to 29.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003e\u003csup\u003ea\u003c/sup\u003e The fully adjusted model for multivariable regression analysis includes age, sex, body mass index, hypertension, diabetes mellitus, chronic kidney disease, cardiovascular disease, and cancer as covariates.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003eCI, confidence interval; n/a, not applicable.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study provides valuable insights into the longitudinal changes and reversibility of frailty status, impacting health-related QOL in middle-aged and older adults living independently in the community. The results demonstrate that frailty, often considered a progressive and inevitable consequence of aging, can be reversed. Over five years, participants with improved or maintained frailty status exhibited significantly better physical and social QOL outcomes compared to participants with worsened frailty status. These findings emphasize the importance of early intervention and monitoring frailty in community-dwelling populations to enhance QOL and mitigate age-related decline.\u003c/p\u003e \u003cp\u003eThe prevalence and progression of frailty over time are noteworthy. Although various studies showed that frailty associated with illness is reversible \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, longitudinal assessments of frailty in \u0026ldquo;healthy\u0026rdquo; community-dwelling individuals is limited. In agreement with previous studies, our results demonstrated a significant increase in frailty with age. Frailty status worsened in approximately 30% of participants in our study, including transitions from prefrail to frail. Previous longitudinal studies reported similar transition rates from robust to prefrail or frail of 28.0\u0026ndash;33.9% \u003csup\u003e13,24,25\u003c/sup\u003e. Geographic and racial disparities, differences in age groups, differences in observation periods, and differences in assessment methods may have contributed to differences in frailty status changes \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Of note, many of the populations in previous reports were heterogeneous; the number of robust participants at baseline ranged from 32.0\u0026ndash;56.0% in previous reports. Thus, our results may be generalizable to longitudinal changes in frailty status among community-dwelling middle-aged and older adults.\u003c/p\u003e \u003cp\u003eOur results align with prior research showing that QOL tends to decrease with age, particularly after the age of 70 \u003csup\u003e27\u0026ndash;29\u003c/sup\u003e. Participants in the current study had a mean age of 65 in 2014, and the overall QOL declined over the five years of the study. However, individuals who improved or maintained their frailty status exhibited better physical and social QOL scores, suggesting that targeted interventions such as exercise and social engagement may prevent or reverse QOL decreases, even in an aging population. The multifaceted impact of frailty on QOL, particularly the negative correlations between frailty status and various aspects of QOL \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e, is evident in our findings. Previous studies primarily focused on the physical aspects of frailty. However, our study highlights the significance of social well-being. Participants who maintained or improved their frailty status experienced better physical functioning and improved social functioning, underscoring the importance of social participation in mitigating frailty. In contrast, mental QOL did not exhibit significant differences across frailty groups. This finding suggests that physical and social domains are closely linked to frailty status, but mental health is influenced by a broader range of factors, including depression, anxiety, and vitality \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, which were not fully captured in our study.\u003c/p\u003e \u003cp\u003eImportantly, our research demonstrates that QOL improvements are not limited to individuals who entirely recover from frailty. Even participants who maintained their frailty status showed better social QOL \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e compared with participants with worsened frailty. Communication and social participation with neighbors may be important for recovery from frailty or prevention of worsening frailty \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Our results demonstrate an association between changes in frailty status and social involvement, which is particularly relevant for public health strategies aimed at improving the well-being of older adults. Interventions that help maintain frailty status may improve recovery and play a vital role in enhancing the social and physical aspects of QOL. Our study is unique in its longitudinal approach, assessing frailty and QOL changes over five years. Previous studies examined the cross-sectional relationship between frailty and QOL, but few studies have explored the dynamic nature of frailty and its impact on QOL over time. Our findings suggest that frailty is reversible and improvements in frailty status are strongly associated with better QOL outcomes. This highlights the need for continued research into the factors that contribute to frailty improvement and the development of interventions aimed at the recovery and stabilization of frailty in aging populations.\u003c/p\u003e \u003cp\u003eOne limitation of this study is the potential generalization limitation due to the J-CHS criteria employed to discriminate frailty. The complexity and diversity of physiological dysregulation resulting from frailty has led to the development of many assessment tools \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e; two major types of assessment methods have been proposed. The deficit accumulation model \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e, represented by the Frailty Index, estimates frailty status by cumulatively assessing a patient\u0026rsquo;s comorbidities. On the other hand, phenotype models, such as the one by Fried et al. \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, are suitable for assessing the preliminary stages of the need for nursing care and can select older people for intervention at an early stage \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Additionally, the CHS criteria include a wide range of elements, including physical, social, and psychological domains, which are essential for a comprehensive assessment of frailty. Thus, the multidimensional approach of the J-CHS criteria may allow for more accurate identification of frailty compared to methods that focus solely on physical capacity or subjective questionnaires \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOther several limitations to this study should be acknowledged. First, selection bias introduced by the inclusion of relatively healthy volunteers who participated in two health checkups may have affected the generalizability of our findings. Second, the five-year follow-up period and the use of only two assessment time points may have limited our ability to capture the full trajectory of frailty and QOL changes. Third, the Yakumo study mainly focused on health status of the organ and musculoskeletal systems and QOL, socioeconomic factors such as the educational status of the participants were not available. Forth, gait status was assessed at 10-m walking test due to time constraints of the health checkup so that may not be as generalizable as the more common 6-minute walk test. However, we believe that this limitation is small because the correlation between these two tests has been demonstrated in recent years \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e,\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Finally, single assessment tools, such as the J-CHS criteria for frailty and the SF-36 for QOL, may not fully encompass the complexity of these conditions.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis longitudinal cohort study demonstrates that frailty is not static and improvements or maintenance of frailty are associated with better physical and social QOL outcomes. These findings highlight the importance of proactive monitoring and intervention in community-dwelling middle-aged and older adults to enhance QOL and promote healthy aging. Addressing frailty early may help reverse or mitigate the impact of frailty and improve the overall well-being of older adults.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eThe authors are grateful to the staff of the Comprehensive Health Care Program in Yakumo, Hokkaido, and to Ms. Hiromi Mio and Ms. Marie Inagaki at Nagoya University for their assistance throughout this study. We would also like to thank Enago (https://www.enago.jp) for the English review.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eAuthor contributions\u003c/h2\u003e\n\u003cp\u003eR. Oishi and N. Segi: Conceptualization, Methodology, Investigation, Formal analysis, Data curation, Writing\u0026ndash;original draft preparation, Visualization. M. Okazaki: Methodology, Formal analysis, Writing\u0026ndash;original draft preparation. S. Ito, J. Ouchida, I. Yamauchi, T. Seki, Y. Takegami, and S. Ishizuka: Investigation. A. Hashizume: Formal analysis. Y. Hasegawa and S. Imagama: Supervision, Funding acquisition. H. Nakashima: Methodology, Writing\u0026ndash;review and editing.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eData availability statement\u003c/h2\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eDeclaration of conflicting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis work was supported by the JSPS Grants-in-Aid for Scientific Research [grant number: 18K09102].\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eEthical approval\u003c/h2\u003e\n\u003cp\u003eThe study protocol was approved by the Human Research Ethics Committee and Institutional Review Board of Nagoya University (No.2014-0207). The study procedures were performed according to the principles of the Declaration of Helsinki. Informed consent was obtained from all participants included in the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eClegg, A., Young, J., Iliffe, S., Rikkert, M. O. \u0026amp; Rockwood, K. Frailty in elderly people. \u003cem\u003eThe Lancet\u003c/em\u003e \u003cstrong\u003e381\u003c/strong\u003e, 752\u0026ndash;762 (2013).\u003c/li\u003e\n\u003cli\u003eFried, L. P. \u003cem\u003eet al.\u003c/em\u003e Frailty in Older Adults: Evidence for a Phenotype. \u003cem\u003eJ. Gerontol. Ser. A\u003c/em\u003e \u003cstrong\u003e56\u003c/strong\u003e, M146\u0026ndash;M157 (2001).\u003c/li\u003e\n\u003cli\u003eKutner, N. G. \u0026amp; Zhang, R. Frailty as a dynamic process in a diverse cohort of older persons with dialysis-dependent CKD. \u003cem\u003eFront. Nephrol.\u003c/em\u003e \u003cstrong\u003e3\u003c/strong\u003e, (2023).\u003c/li\u003e\n\u003cli\u003eOrnaghi, P. I. \u003cem\u003eet al.\u003c/em\u003e Frailty impact on postoperative complications and early mortality rates in patients undergoing radical cystectomy for bladder cancer: a systematic review. \u003cem\u003eArab J. Urol.\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, 9\u0026ndash;23 (2020).\u003c/li\u003e\n\u003cli\u003eMedina-Mirapeix, F. \u003cem\u003eet al.\u003c/em\u003e The prognosis of pre-frail chronic obstructive pulmonary disease patients for hospitalizations and mortality depends on their level of functional physical performance. \u003cem\u003eChron. Respir. Dis.\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, 14799731221119810 (2022).\u003c/li\u003e\n\u003cli\u003eRohrmann, S. Epidemiology of Frailty in Older People. in \u003cem\u003eFrailty and Cardiovascular Diseases : Research into an Elderly Population\u003c/em\u003e (ed. Veronese, N.) 21\u0026ndash;27 (Springer International Publishing, Cham, 2020). doi:10.1007/978-3-030-33330-0_3.\u003c/li\u003e\n\u003cli\u003eRasiah, J. \u003cem\u003eet al.\u003c/em\u003e Prefrailty in older adults: A concept analysis. \u003cem\u003eInt. J. Nurs. Stud.\u003c/em\u003e \u003cstrong\u003e108\u003c/strong\u003e, 103618 (2020).\u003c/li\u003e\n\u003cli\u003eLiao, Y.-Y., Chen, I.-H. \u0026amp; Wang, R.-Y. Effects of Kinect-based exergaming on frailty status and physical performance in prefrail and frail elderly: A randomized controlled trial. \u003cem\u003eSci. Rep.\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 9353 (2019).\u003c/li\u003e\n\u003cli\u003eSugie, M. \u003cem\u003eet al.\u003c/em\u003e Effectiveness of a far-infrared low-temperature sauna program on geriatric syndrome and frailty in community-dwelling older people. \u003cem\u003eGeriatr. Gerontol. Int.\u003c/em\u003e \u003cstrong\u003e20\u003c/strong\u003e, 892\u0026ndash;898 (2020).\u003c/li\u003e\n\u003cli\u003eAp\u0026oacute;stolo, J. \u003cem\u003eet al.\u003c/em\u003e Effectiveness of interventions to prevent pre-frailty and frailty progression in older adults: a systematic review. \u003cem\u003eJBI Evid. Synth.\u003c/em\u003e \u003cstrong\u003e16\u003c/strong\u003e, 140 (2018).\u003c/li\u003e\n\u003cli\u003eHaider, S. \u003cem\u003eet al.\u003c/em\u003e Associations between daily physical activity, handgrip strength, muscle mass, physical performance and quality of life in prefrail and frail community-dwelling older adults. \u003cem\u003eQual. Life Res.\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 3129\u0026ndash;3138 (2016).\u003c/li\u003e\n\u003cli\u003ePapathanasiou, I. V. \u003cem\u003eet al.\u003c/em\u003e Frailty and Quality of Life Among Community-Dwelling Older Adults. \u003cem\u003eCureus\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, e13049 (2021).\u003c/li\u003e\n\u003cli\u003eDe Rui, M. \u003cem\u003eet al.\u003c/em\u003e Changes in Frailty Status and Risk of Depression: Results From the Progetto Veneto Anziani Longitudinal Study. \u003cem\u003eAm. J. Geriatr. Psychiatry\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 190\u0026ndash;197 (2017).\u003c/li\u003e\n\u003cli\u003eS\u0026aacute;nchez-Garc\u0026iacute;a, S. \u003cem\u003eet al.\u003c/em\u003e Comparison of quality of life among community-dwelling older adults with the frailty phenotype. \u003cem\u003eQual. Life Res.\u003c/em\u003e \u003cstrong\u003e26\u003c/strong\u003e, 2693\u0026ndash;2703 (2017).\u003c/li\u003e\n\u003cli\u003eImagama, S. \u003cem\u003eet al.\u003c/em\u003e Differences of locomotive syndrome and frailty in community-dwelling middle-aged and elderly people: Pain, osteoarthritis, spinal alignment, body balance, and quality of life. \u003cem\u003eMod. Rheumatol.\u003c/em\u003e \u003cstrong\u003e30\u003c/strong\u003e, 921\u0026ndash;929 (2020).\u003c/li\u003e\n\u003cli\u003eSugie, M. \u003cem\u003eet al.\u003c/em\u003e Effectiveness of Exercise-Training on Frailty and the Specificity of Exercise Effectiveness on Frailty-Related Indices among Community Dwelling Robust, Pre-Frailty and Frailty Older Peoples. \u003cem\u003eGerontol. Geriatr. Res.\u003c/em\u003e \u003cstrong\u003e7\u003c/strong\u003e, 1\u0026ndash;7 (2018).\u003c/li\u003e\n\u003cli\u003eImagama, S. \u003cem\u003eet al.\u003c/em\u003e Influence of spinal sagittal alignment, body balance, muscle strength, and physical ability on falling of middle-aged and elderly males. \u003cem\u003eEur. Spine J.\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e, 1346\u0026ndash;1353 (2013).\u003c/li\u003e\n\u003cli\u003eImagama, S. \u003cem\u003eet al.\u003c/em\u003e Multivariate analysis of factors related to the absence of musculoskeletal degenerative disease in middle-aged and older people. \u003cem\u003eGeriatr. Gerontol. Int.\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, 1141\u0026ndash;1146 (2019).\u003c/li\u003e\n\u003cli\u003eYakumo Town. https://www.town.yakumo.lg.jp/.\u003c/li\u003e\n\u003cli\u003eStatistics Bureau of the Ministry of Internal Affairs and Communications Website. https://www.stat.go.jp/data/jinsui/.\u003c/li\u003e\n\u003cli\u003eSatake, S. \u0026amp; Arai, H. The revised Japanese version of the Cardiovascular Health Study criteria (revised J-CHS criteria). \u003cem\u003eGeriatr. Gerontol. Int.\u003c/em\u003e \u003cstrong\u003e20\u003c/strong\u003e, 992\u0026ndash;993 (2020).\u003c/li\u003e\n\u003cli\u003eCai, Z. \u003cem\u003eet al.\u003c/em\u003e Associations of social engagement, and loneliness with the progression and reversal of frailty: longitudinal investigations of two prospective cohorts from the UK and the USA. \u003cem\u003eAm. J. Epidemiol.\u003c/em\u003e kwae221 (2024) doi:10.1093/aje/kwae221.\u003c/li\u003e\n\u003cli\u003eSalvatori, S. \u003cem\u003eet al.\u003c/em\u003e Reversibility of Frail Phenotype in Patients with Inflammatory Bowel Diseases. \u003cem\u003eJ. Clin. Med.\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 2658 (2023).\u003c/li\u003e\n\u003cli\u003eTrevisan, C. \u003cem\u003eet al.\u003c/em\u003e Factors Influencing Transitions Between Frailty States in Elderly Adults: The Progetto Veneto Anziani Longitudinal Study. \u003cem\u003eJ. Am. Geriatr. Soc.\u003c/em\u003e \u003cstrong\u003e65\u003c/strong\u003e, 179\u0026ndash;184 (2017).\u003c/li\u003e\n\u003cli\u003eThompson, M. Q., Theou, O., Adams, R. J., Tucker, G. R. \u0026amp; Visvanathan, R. Frailty state transitions and associated factors in South Australian older adults. \u003cem\u003eGeriatr. Gerontol. Int.\u003c/em\u003e \u003cstrong\u003e18\u003c/strong\u003e, 1549\u0026ndash;1555 (2018).\u003c/li\u003e\n\u003cli\u003eMitnitski, A. B., Mogilner, A. J. \u0026amp; Rockwood, K. Accumulation of Deficits as a Proxy Measure of Aging. \u003cem\u003eSci. World J.\u003c/em\u003e \u003cstrong\u003e1\u003c/strong\u003e, 323\u0026ndash;336 (2001).\u003c/li\u003e\n\u003cli\u003eCorbi, G. \u003cem\u003eet al.\u003c/em\u003e Inter-relationships between Gender, Frailty and 10-Year Survival in Older Italian Adults: an observational longitudinal study. \u003cem\u003eSci. Rep.\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 18416 (2019).\u003c/li\u003e\n\u003cli\u003eGrden, C. R. B. \u003cem\u003eet al.\u003c/em\u003e Associations between frailty syndrome and sociodemographic characteristics in long-lived individuals of a community. \u003cem\u003eRev. Lat. Am. Enfermagem\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, e2886 (2017).\u003c/li\u003e\n\u003cli\u003eLee, D. R. \u003cem\u003eet al.\u003c/em\u003e Understanding functional and social risk characteristics of frail older adults: a cross-sectional survey study. \u003cem\u003eBMC Fam. Pract.\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, 170 (2018).\u003c/li\u003e\n\u003cli\u003eKojima, G. \u003cem\u003eet al.\u003c/em\u003e Frailty predicts trajectories of quality of life over time among British community-dwelling older people. \u003cem\u003eQual. Life Res.\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 1743\u0026ndash;1750 (2016).\u003c/li\u003e\n\u003cli\u003eFeng, L., Nyunt, M. S. Z., Feng, L., Yap, K. B. \u0026amp; Ng, T. P. Frailty Predicts New and Persistent Depressive Symptoms Among Community-Dwelling Older Adults: Findings From Singapore Longitudinal Aging Study. \u003cem\u003eJ. Am. Med. Dir. Assoc.\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, 76.e7-76.e12 (2014).\u003c/li\u003e\n\u003cli\u003eMakizako, H. \u003cem\u003eet al.\u003c/em\u003e Physical Frailty Predicts Incident Depressive Symptoms in Elderly People: Prospective Findings From the Obu Study of Health Promotion for the Elderly. \u003cem\u003eJ. Am. Med. Dir. Assoc.\u003c/em\u003e \u003cstrong\u003e16\u003c/strong\u003e, 194\u0026ndash;199 (2015).\u003c/li\u003e\n\u003cli\u003eSuzukamo, Y. \u003cem\u003eet al.\u003c/em\u003e Validation testing of a three-component model of Short Form-36 scores. \u003cem\u003eJ. Clin. Epidemiol.\u003c/em\u003e \u003cstrong\u003e64\u003c/strong\u003e, 301\u0026ndash;308 (2011).\u003c/li\u003e\n\u003cli\u003eChu, B.-L. \u0026amp; Zhang, W. Impact of transient and chronic loneliness on progression and reversion of frailty in community-dwelling older adults: four-year follow-up. \u003cem\u003eBMC Geriatr.\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e, 642 (2022).\u003c/li\u003e\n\u003cli\u003eTakatori, K. \u0026amp; Matsumoto, D. Social factors associated with reversing frailty progression in community-dwelling late-stage elderly people: An observational study. \u003cem\u003ePLOS ONE\u003c/em\u003e \u003cstrong\u003e16\u003c/strong\u003e, e0247296 (2021).\u003c/li\u003e\n\u003cli\u003ePerazza L. R., Avers D. \u0026amp; Thompson L. V. Measurement of Frailty: Tools and Interpretation. \u003cem\u003eTop. Geriatr. Rehabil.\u003c/em\u003e \u003cstrong\u003e39\u003c/strong\u003e, 88 (2023).\u003c/li\u003e\n\u003cli\u003eMitnitski, A. B., Mogilner, A. J. \u0026amp; Rockwood, K. Accumulation of Deficits as a Proxy Measure of Aging. \u003cem\u003eSci. World J.\u003c/em\u003e \u003cstrong\u003e1\u003c/strong\u003e, 323\u0026ndash;336 (2001).\u003c/li\u003e\n\u003cli\u003eFried, L. P. \u003cem\u003eet al.\u003c/em\u003e Frailty in Older Adults: Evidence for a Phenotype. \u003cem\u003eJ. Gerontol. Ser. A\u003c/em\u003e \u003cstrong\u003e56\u003c/strong\u003e, M146\u0026ndash;M157 (2001).\u003c/li\u003e\n\u003cli\u003eKuzuya, M. [Terminology: Frailty]. \u003cem\u003eJ. JSPEN\u003c/em\u003e \u003cstrong\u003e3\u003c/strong\u003e, 114\u0026ndash;120 (2021).\u003c/li\u003e\n\u003cli\u003eBandeen-Roche, K. \u003cem\u003eet al.\u003c/em\u003e Phenotype of Frailty: Characterization in the Women\u0026rsquo;s Health and Aging Studies. \u003cem\u003eJ. Gerontol. Ser. A\u003c/em\u003e \u003cstrong\u003e61\u003c/strong\u003e, 262\u0026ndash;266 (2006).\u003c/li\u003e\n\u003cli\u003eLozano-Meca, J., Montilla-Herrador, J. \u0026amp; Gacto-S\u0026aacute;nchez, M. Gait speed in knee osteoarthritis: A simple 10-meter walk test predicts the distance covered in the 6-minute walk test. \u003cem\u003eMusculoskelet. Sci. Pract.\u003c/em\u003e \u003cstrong\u003e72\u003c/strong\u003e, 102983 (2024).\u003c/li\u003e\n\u003cli\u003eChan, W. L. S. \u0026amp; Pin, T. W. Reliability, validity and minimal detectable change of 2-minute walk test, 6-minute walk test and 10-meter walk test in frail older adults with dementia. \u003cem\u003eExp. Gerontol.\u003c/em\u003e \u003cstrong\u003e115\u003c/strong\u003e, 9\u0026ndash;18 (2019).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"frail, prefrail, quality of life (QOL), community-dwelling population, longitudinal study, Yakumo study","lastPublishedDoi":"10.21203/rs.3.rs-5729095/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5729095/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe purpose of this study was to determine the association between frailty and quality of life (QOL) in a five-year longitudinal cohort of community-dwelling middle-aged and older adults and determine how to identify health-related QOL changes. This study included 124 volunteers (67 women; mean 65 years at baseline) who underwent health checkups in 2014 and 2019. The association between frailty status (robust, prefrail, frail), according to the Japanese Cardiovascular Health Study criteria, and health-related QOL, measured with the SF-36 questionnaire, were investigated. Five-year changes in frailty status were categorized into improved, maintained, and worsened groups. The baseline prevalence of prefrailty and frailty were 44.4% and 7.2%, respectively. Five years later, the frailty of 20 participants improved, 66 maintained frailty status, and frailty worsened in 38 participants. Significant trends toward higher scores on the physical component summary (PCS), role/social component summary (RCS), and subscales of physical functioning, role-physical, vitality, social functioning, and role-emotional were detected across groups with improvements in their frailty status from 2014 to 2019. The fully adjusted multivariable regression model revealed significantly higher PCS scores (β, 12.9; 95% confidence interval (CI), 6.0 to 19.9) and RCS scores (β, 13.6; 95% CI, 6.6 to 20.6) compared with the worsened group. In conclusion, this longitudinal cohort study demonstrates that frailty status is not static and improvements or maintenance of frailty are associated with better physical and social QOL outcomes. Addressing frailty early may reverse or mitigate its impact and improve the overall well-being of older adults.\u003c/p\u003e","manuscriptTitle":"Longitudinal transitions in frailty and their impact on quality of life investigated by a 5-year community study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-31 06:30:48","doi":"10.21203/rs.3.rs-5729095/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-02T10:58:38+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-02T05:45:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-30T12:17:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"16031315456231437588831481463480032379","date":"2025-03-29T01:11:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"179812759661531856639301574080507485569","date":"2025-03-28T04:53:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-27T09:06:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-27T06:15:55+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-03-21T06:56:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2dd0d569-4276-484f-a7ab-9f0a350e9d15","owner":[],"postedDate":"March 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":46287980,"name":"Biological sciences/Developmental biology/Ageing"},{"id":46287981,"name":"Health sciences/Health care/Geriatrics"},{"id":46287982,"name":"Health sciences/Medical research/Epidemiology"}],"tags":[],"updatedAt":"2025-05-05T16:02:57+00:00","versionOfRecord":{"articleIdentity":"rs-5729095","link":"https://doi.org/10.1038/s41598-025-99843-7","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-04-30 15:57:26","publishedOnDateReadable":"April 30th, 2025"},"versionCreatedAt":"2025-03-31 06:30:48","video":"","vorDoi":"10.1038/s41598-025-99843-7","vorDoiUrl":"https://doi.org/10.1038/s41598-025-99843-7","workflowStages":[]},"version":"v1","identity":"rs-5729095","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5729095","identity":"rs-5729095","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}