Longitudinal transitions in frailty and health-related quality of life investigated by a 5-year community study

Frailty is a clinical syndrome marked by a decline in an individual’s quality of life due to age-related reductions in physiological reserve¹. This syndrome represents an intermediate state between robust health and overt disability, increasing vulnerability to adverse health outcomes, including falls, disability, and mortality². 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 state³. 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 difficult².

The trajectory between different frailty states, including robust, prefrail, frail, and disabled, is recognized as a dynamic continuum of transitions over time^8,9,10. However, comprehensive studies detailing these transitions are limited, with significant gaps in understanding the mechanisms and risk factors that drive changes between frailty states³. Prefrailty negatively influences the quality of life (QOL) across physical, mental, and social domains^11,12,13, but the extent and nature of this impact are not well-understood¹⁴. 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 communities¹⁵. 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.

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 2019²⁰. 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 (Fig. 1).

Study enrollment flowchart. J-CHS, Japanese Cardiovascular Health Study.

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The study protocol was approved by the Human Research Ethics Committee and Institutional Review Board of Nagoya University. Written informed consent was obtained from all participants. The study was conducted in accordance with the principles of the Declaration of Helsinki.

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 m 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) criteria²¹. 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).

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.

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).

Changes in the frailty states of the participants over 5 years.

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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).

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).

Changes in the SF-36 summary scores and subscales over 5 years.

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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 to 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 70^27,28,29. 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 QOL³³ 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 tools³⁶; two major types of assessment methods have been proposed. The deficit accumulation model²⁶, 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.², are suitable for assessing the preliminary stages of the need for nursing care and can select older people for intervention at an early stage³⁷. 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^21,38.

Several other 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. As shown in Fig. 1, a significant proportion of participants with missing data on the frailty or the health-related QOL in 2019 health checkups were excluded. Although those excluded were not significantly different from those included in baseline comorbidities, missingness due to missing at random or missing not at random mechanisms (missingness that depends on the unmeasured frailty or the health-related QOL statuses in 2019 health checkup) is likely. Therefore, the complete case analysis conducted in this study could yield biased results. 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. Fourth, 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^39,40. 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.

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Author notes

1. Ryotaro Oishi and Naoki Segi contributed equally.

Authors and Affiliations

1. Department of Orthopaedic Surgery, Nagoya University Graduate School of Medicine, 65 Tsurumai, Showa Ward, Nagoya, 466-8560, Aichi, Japan

   Ryotaro Oishi, Naoki Segi, Sadayuki Ito, Jun Ouchida, Ippei Yamauchi, Yasuhiko Takegami, Shinya Ishizuka, Shiro Imagama & Hiroaki Nakashima

2. Department of Clinical Research Education, Nagoya University Graduate School of Medicine, Nagoya, 466-8560, Aichi, Japan

   Masaki Okazaki & Atsushi Hashizume

3. Department of Orthopedic Surgery, Aichi Medical University Medical Center, Okazaki, 444- 2148, Aichi, Japan

   Taisuke Seki

4. Department of Rehabilitation, Kansai University of Welfare Sciences, Kashiwara, 582-0026, Osaka, Japan

   Yukiharu Hasegawa

5. Department of Orthopedic Surgery, Japanese Red Cross Aichi Medical Center Nagoya Daiichi Hospital, Nagoya, 453-8511, Aichi, Japan

   Ryotaro Oishi

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.

Corresponding author

Correspondence to Hiroaki Nakashima.

Competing interests

The authors declare no competing interests.

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.

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