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Center for Geriatrics and Gerontology, Taipei Veterans General Hospital, Taipei, TaiwanDepartment of Geriatric Medicine, National Yang Ming Chiao Tung University, School of Medicine, Taipei, TaiwanInstitute of Public Health, National Yang Ming Chiao Tung University, Taipei, TaiwanCenter for Healthy Longevity and Aging Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
Center for Geriatrics and Gerontology, Taipei Veterans General Hospital, Taipei, TaiwanDepartment of Geriatric Medicine, National Yang Ming Chiao Tung University, School of Medicine, Taipei, TaiwanCenter for Healthy Longevity and Aging Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
Center for Geriatrics and Gerontology, Taipei Veterans General Hospital, Taipei, TaiwanDepartment of Geriatric Medicine, National Yang Ming Chiao Tung University, School of Medicine, Taipei, Taiwan
Center for Geriatrics and Gerontology, Taipei Veterans General Hospital, Taipei, TaiwanDepartment of Geriatric Medicine, National Yang Ming Chiao Tung University, School of Medicine, Taipei, TaiwanCenter for Healthy Longevity and Aging Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
Center for Geriatrics and Gerontology, Taipei Veterans General Hospital, Taipei, TaiwanDepartment of Geriatric Medicine, National Yang Ming Chiao Tung University, School of Medicine, Taipei, TaiwanCenter for Healthy Longevity and Aging Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
Institute of Public Health, National Yang Ming Chiao Tung University, Taipei, TaiwanOffice of the Deputy Superintendent, National Yang Ming Chiao Tung University Hospital, Yilan County, Taiwan
Graduate Institute of Clinical Pharmacy, College of Medicine, National Taiwan University, Taipei, TaiwanSchool of Pharmacy, College of Medicine, National Taiwan University, Taipei, TaiwanDepartment of Pharmacy, National Taiwan University Hospital, Taipei, Taiwan
Address correspondence to Liang-Kung Chen, MD, PhD, Center for Geriatrics and Gerontology, Taipei Veterans General Hospital, No. 201, Sec. 2, Shih-Pai Road, Taipei, Taiwan.
Center for Geriatrics and Gerontology, Taipei Veterans General Hospital, Taipei, TaiwanDepartment of Geriatric Medicine, National Yang Ming Chiao Tung University, School of Medicine, Taipei, TaiwanCenter for Healthy Longevity and Aging Sciences, National Yang Ming Chiao Tung University, Taipei, TaiwanTaipei Municipal Gan-Dau Hospital (Managed by Taipei Veterans General Hospital), Taipei, Taiwan
To explore the associations of (1) the frailty phenotype or frailty index transition with cause-specific mortality, and (2) different combinations of transition in frailty phenotype and frailty index with all-cause mortality.
Design
Retrospective cohort study.
Setting and Participants
Data from 3529 respondents aged >50 years who completed the 1999 and 2003 surveys of the Taiwan Longitudinal Study on Aging were analyzed.
Methods
Cox regression and subdistribution hazard models were constructed to investigate frailty phenotype or frailty index transitions (by categories of frailty phenotype, absolute and percentage changes in frailty index, and combined categories of the 2 measurements) and subsequent 4-year all-cause and cause-specific mortality, respectively.
Results
Among the frailty phenotype transition groups, the improved frailty group had overall mortality risk comparable to that of the maintained robustness/prefrailty group [hazard ratio (HR): 0.9; 95% CI: 0.7–1.2] and lower risk of mortality due to organ failure (HR: 0.4; 95% CI: 0.2–0.8; P = .015), whereas the worsened frailty group had the highest risk of all-cause mortality and death from infection, malignancy, cardiometabolic/cerebrovascular diseases, and other causes (HR: 1.8–3.7; all P < .03). The rapidly increased frailty index group had significantly higher all-cause and every cause-specific mortality than the decreased frailty index group (HR: 1.8–7.7; all P < .05). When frailty phenotype and frailty index transition groups were combined, participants with worsened frailty/rapidly increased frailty index had increased risk under the same frailty index/frailty phenotype transition condition, particularly for large changes in each factor (HR: 1.5–2.2; P < .01 for worsened frailty; 1.7–4.5, P < .03 for rapidly increased frailty index).
Conclusions and Implications
We found that considering both frailty phenotype and frailty index provided best mortality prediction. These associations were independent of baseline frailty status and comorbidities. Nevertheless, even capturing transitions in frailty phenotype or frailty index only can provide good mortality prediction, which supported adopting these approaches in different clinical settings.
Frailty is characterized by declines in physiological reserves across different systems and increased vulnerability to stressors during the process of aging.
the 2 most commonly adopted frailty assessment models, are predictive of long-term mortality despite baseline frailty status. Although comparisons between the 2 measurements at baseline and subsequent mortality have been investigated,
longitudinal comparisons remain to be explored. It is particularly of interest for the group with a discrepant transition between the 2 measurements (eg, a favorable frailty index transition + an unfavorable frailty phenotype transition).
In addition to the association with all-cause mortality, the association between frailty status and cause-specific mortality has attracted increasing research interest. Recent studies have suggested that the risk of cause-specific mortality due to cardiometabolic diseases, cancer, and infection may increase with increasing severity of the baseline frailty phenotype or frailty index.
The association between longitudinal frailty transition and cause-specific mortality has been rarely investigated and may provide more information for long-term risk prediction.
In this context, we analyzed data from a nationally representative cohort in Taiwan, with the specific aims of exploring the association between (1) frailty phenotype and frailty index transitions and subsequent 4-year all-cause and cause-specific mortality, and (2) different combinations of frailty phenotype/frailty index transitions and all-cause mortality.
Methods
The Taiwan Longitudinal Study on Aging (TLSA) is a nationally representative cohort study that includes community-dwelling residents older than 50 years and has been conducted by the Taiwan Health Promotion Administration since 1989; the respondents are followed every 3 to 4 years.
The study aims to address potential impacts on the economic, social, and medical aspects of population aging. We extracted data from participants of the 1999 TLSA survey (n = 4440) and excluded those who had died or were lost to follow-up before the 2003 TLSA survey (n = 911). Those who participated in both waves were recruited for final analysis to describe frailty phenotype and frailty index transitions (n = 3529).
The study was conducted in accordance with the principles of the Declaration of Helsinki and was approved by the Institutional Review Board (No. 2021-05-023CC).
Construction of Frailty Phenotype and Frailty Index
The definitions of frailty phenotype and frailty index have been previously described in detail,
which were mostly based on self-reported questionnaire items. In brief, the 5 components of frailty phenotype were modified according to the original Fried criteria
: (1) Weakness was defined as difficulty in picking up or twisting objects using the fingers. (2) Slowness was defined as difficulty walking 200 to 300 m. (3) Weight loss was defined as a body mass index ≤18.5. (4) Exhaustion was defined as self-reported answers of “I felt everything I did was an effort” or “I could not get going” >2 days/week for either answer on the Center for Epidemiological Studies-Depression Scale (CES-D) questionnaire. (5) Inactivity was defined as a sum of the weighted score ≤3 for men or ≤2 for women calculated from the frequency and intensity of leisure time activities.
Seventy-two variables were selected, including the following: (1) activities of daily living (ADLs), instrumental ADLs (IADLs), and mobility (22 variables); (2) comorbidities and health status (17 variables), and 13 comorbidities were ascertained by asking “have you ever been diagnosed with the following diseases by a physician?”; (3) psychological status (10 variables); (4) cognitive function (10 variables); (5) life satisfaction (6 variables); (6) stress (4 variables) and sensory domain (3 variables) (Supplementary Table 1).
For each individual, the frailty index was calculated as the sum of deficits divided by the maximum possible score.
Definitions of Frailty Phenotype and Frailty Index Transitions
Four approaches in capturing transitions in frailty [by categories of phenotype, categories (absolute changes) of frailty index, percentage changes in frailty index, and combined categories of frailty phenotype and frailty index]. The rationale we adopt these approaches is to test the feasibility of these measures in capturing transitions in frailty and their associations with risk of mortality.
Transitions in frailty phenotype and frailty index were calculated as the differences between values measured in 1999 and 2003. A positive value suggested worsening of frailty status. We categorized transition in frailty phenotype into 4 groups: (1) worsened frailty (frailty phenotype2003–1999 >0), (2) improved frailty (frailty phenotype2003–1999 <0), (3) maintained robustness/prefrailty (frailty phenotype2003–1999 = 0 and frailty phenotype1999 = 0–2), and (4) maintained frailty (frailty phenotype2003–1999 = 0 and frailty phenotype1999 = 3–5).
Because of the lack of consensus regarding the definition of frailty index transition, we adopted the minimally clinically significant change of 0.03/year proposed by Jang et al.
Thus, a frailty index increase of more than 0.12 in 4 years was considered a rapid increase, and frailty index transition was classified as the following categories: (1) decreased frailty index (frailty index2003–1999 < 0); (2) moderately increased frailty index (0 ≤ frailty index2003–1999 <0.12); and (3) rapidly increased frailty index (frailty index2003–1999 ≥0.12). In addition, we categorized the frailty index by percentage change: (1) decrease in the frailty index percentage: <0％; (2) moderate increase in the frailty index percentage: increase <50%; and (3) rapid increase in the frailty index percentage: increase ≥50% to check the robustness of the association between frailty index transition and mortality.
We further combined transitions in frailty phenotype (worsened frailty, improved frailty, maintained robustness/prefrailty, and maintained frailty) and transition in frailty index (decreased, moderately increased, and rapidly increased frailty index) to create 12 subcategories of transitions in both frailty phenotype and frailty index.
Mortality
Mortality was assessed from the 2003 TLSA survey until Dec 2007. The main International Classification of Diseases, ninth revision (ICD-9), codes for death as well as year and month of death were collected from the death certificate reporting system of the Ministry of Health and Welfare, Taiwan. We considered 5 causes of death in our analysis: infectious diseases, malignancy, cardiometabolic and cerebrovascular diseases, organ failure (including heart, lung, kidney, and liver), and others. The corresponding ICD-9 codes for each cause of death are presented in Supplementary Table 2.
Statistical Analysis
Descriptive statistics are presented as mean ± SDs for continuous variables or numbers (percentages) for categorical variables. Cox proportional hazard regression models were used to evaluate the relationship between frailty transition and subsequent 4-year all-cause mortality. Model 1 was adjusted for age and sex; model 2 was adjusted for age, sex, education years, marital status, alcohol consumption, smoking, and total number of comorbidities; and model 3 was further adjusted for baseline frailty phenotype or frailty index in addition to the variables in model 2 (Table 1). The transition groups of frailty phenotype and frailty index were combined in a fully adjusted Cox regression model to predict the mortality risk.
Table 1Frailty Phenotype and Frailty Index Transitions and 4-Year All-Cause Mortality
Model 3: adjusted for age, sex, education years, marital status, alcohol, smoke, number of comorbidities, baseline frailty phenotype or frailty index.
HR (95% CI)
P value
HR (95% CI)
P value
HR (95% CI)
P value
Total
655/3529 (18.6)
Frailty phenotype transition
Maintained robustness/prefrailty
197/1729 (11.4)
Ref
Ref
Ref
Worsened frailty
296/1065 (27.8)
2.3 (1.9, 2.8)
<.001
2.1 (1.7, 2.5)
<.001
2.0 (1.7, 2.5)
<.001
Improved frailty
124/667 (18.6)
1.6 (1.3, 2.0)
.001
1.5 (1.2, 1.9)
.001
0.9 (0.7, 1.2)
.472
Maintained frailty
38/68 (55.9)
4.2 (3.0, 6.0)
<.001
3.4 (2.4, 5.0)
<.001
1.5 (1.0, 2.3)
.074
Frailty index transition defined by absolute change
Decreased frailty index
168/1304 (12.9)
Ref
Ref
Ref
Moderately increased frailty index (increase <0.12)
248/1664 (14.9)
1.1 (0.9–1.3)
.537
1.0 (0.8–1.2)
.837
1.3 (1.0–1.6)
.020
Rapidly increased frailty index (increase ≥0.12)
239/561 (42.6)
2.8 (2.3–3.5)
<.001
2.6 (2.1–3.2)
<.001
3.3 (2.7–4.2)
<.001
Frailty index transition defined by percentage change
Decreased frailty index
168/1304 (12.9)
Ref
Ref
Ref
Moderately increased frailty index (increase <50%)
175/997 (17.6)
1.2 (1.0–1.5)
.046
1.1 (0.9–1.3)
.515
1.3 (1.0–1.6)
.020
Rapidly increased frailty index (increase ≥50%)
312/1228 (25.4)
1.7 (1.4–2.1)
<.001
1.6 (1.3–1.9)
<.001
2.6 (2.1–3.3)
<.001
∗ Model 1: adjusted for age, sex.
† Model 2: adjusted for age, sex, education years, marital status, alcohol, smoke, number of comorbidities.
‡ Model 3: adjusted for age, sex, education years, marital status, alcohol, smoke, number of comorbidities, baseline frailty phenotype or frailty index.
We used Fine and Gray subdistribution hazard (SDH) models to calculate cause-specific mortality in the different frailty transition groups. Death by any cause other than the cause of interest was defined as a competing event, and separate models were fit for each of the 5 causes of death. SDH models for death from infection and other causes included the same variables as the fully adjusted Cox proportional hazard model, and we performed further adjustment for related baseline comorbidities of malignancy, cardiometabolic, and organ failure. All statistical analyses were performed using SAS software 9.4 (SAS Institute Inc) and SPSS, version 24.0 (IBM Corp), and a P value (2-tailed) of less than 0.05 was considered statistically significant.
Results
In total, 3529 participants who completed the 1999 and 2003 waves were enrolled in the final analysis (mean age 67.6 ± 8.6 years in 1999, 51.5% male). Totals of 2041 (57.8%), 1263 (35.8%), and 225 (6.4%) participants were considered robust, prefrail, and frail, respectively, as defined by the frailty phenotype in 1999; the mean frailty index was 0.15 (SD 0.11). After 4 years, the prevalence rates of all comorbidities and the degree of frailty, either defined by frailty phenotype or frailty index, increased (Supplementary Table 3).
Frailty Phenotype or Frailty Index Transition and Subsequent 4-Year All-Cause Mortality
As of December 31, 2007, 2871 (81.4%) participants were alive, 3 (0.1%) had moved to other countries, and 655 (18.6%) had died. Regarding frailty phenotype transition and all-cause mortality, in comparison with the maintained robustness/prefrailty group, the maintained frailty group had the highest overall mortality, followed by the worsened frailty group, after adjustment for baseline characteristics (model 2) (all P ≤ .001). In the fully adjusted model, which took the baseline frailty phenotype score into consideration, the improved frailty group had a risk similar to the maintained robustness/prefrailty group (HR: 0.9; 95% CI: 0.7–1.2), and the worsened frailty group had the highest risk (HR: 2.0; 95% CI: 1.7–2.5; P < .001).
Regarding frailty index transition (defined by absolute change) and all-cause mortality, the dose–response relationship became significant after adjustment for baseline frailty index. The HR of the moderately increased and rapidly increased frailty index groups were 1.3 (95% CI: 1.0–1.6; P = .02) and 3.3 (95% CI: 2.7–4.2; P < .001), respectively. The results were similar when frailty index transition was defined as the percentage change (Table 1, Figure 1, A and B ).
Fig. 1(A) Frailty phenotype transition and all-cause mortality. (B) Frailty index transition and all-cause mortality.
Frailty Phenotype or Frailty Index Transition and Subsequent 4-Year Cause-specific Mortality
Among 655 deaths, 72 (11.0%) were due to infectious diseases, 168 (25.6%) were due to malignancy, 189 (28.9%) were due to cardiometabolic/cerebrovascular diseases, 130 (19.8%) were due to organ failure, and 96 (14.7%) were due to other causes.
Regarding frailty phenotype transition and cause-specific mortality, in comparison with the maintained robustness/prefrailty group, the worsened frailty group had significantly higher risks of death from infection (HR: 3.7; 95% CI: 1.9–7.4; P < .001), malignancy (HR: 2.0; 95% CI: 1.4–3.0; P < .001), cardiometabolic/cerebrovascular diseases (HR: 1.8; 95% CI 1.2–2.7; P = .003), and other causes (HR: 1.8; 95% CI 1.1–3.1; P = .027), whereas the improved frailty group had risks comparable risks to the maintained robustness/prefrailty group (HR ranged from 1.1–1.4; P > .2) for these 4 causes of death and a lower risk of death from organ failure (HR: 0.4; 95% CI 0.2–0.9; P = .017). The maintained frailty group had borderline increased mortality risks from infection (HR: 2.9; 95% CI 0.9–9.8; P = .084) and malignancy (HR: 2.8; 95 CI 0.9–8.9, P = .086) (Figure 2).
Fig. 2Frailty phenotype transition and cause-specific mortality.
Similarly, the rapidly increased frailty index group had remarkably higher risks of each cause of death than the decreased frailty index group (HR: 7.7; 95% CI 3.4–14.6 for infection; P < .001; HR: 1.8–2.5, CI ranged from 1.1 to 4.3, P < .03 for other 4 causes of death). In contrast, a moderate increase in the frailty index was predictive of a higher risk of infection-related mortality (HR: 3.3; 95% CI 1.5–7.4; P = .004) than mortality due to other causes of death in our analysis (Figure 3). The results were generally consistent when frailty index transition was defined as percentage change (Supplementary Table 4). These associations were independent of baseline comorbidities and frailty phenotype/frailty index.
Fig. 3Frailty index transition and cause-specific mortality.
Combined Frailty Index/Frailty Phenotype Transitions and All-Cause Mortality
Participants with decreased frailty index had a statistically similar mortality risk despite frailty phenotype transition, and the worsened frailty group had higher risk than the maintained robustness/prefrailty group when the frailty index increased moderately or rapidly (HR: 1.5; 95% CI 1.1–2.1; P = .006; HR: 2.2; 95% CI 1.4–3.3, P < .001 for moderately/rapidly increased frailty index respectively) (Figure 4A).
Fig. 4(A) Frailty phenotype transition and all-cause mortality by frailty index. (B) Frailty index transition and all-cause mortality by frailty phenotype.
On the other hand, compared with the decreased frailty index group, the rapidly increased frailty index group had significantly higher risk among the different frailty phenotype transitions (HR: 1.7; 95% CI: 1.1–2.8; P = .027 for the maintained robustness/prefrailty group; HR: 4.5; 95% CI: 2.9–7.0; P < .001 for the worsened frailty group; HR: 3.0; 95% CI: 1.6–5.7; P < .001 for the improved frailty group; HR: 2.4; 95% CI: 0.9–6.6; P = .089 for the maintained frailty group). The dose–response relationship between frailty index transition and mortality was more significant in the worsened and improved frailty groups (Figure 4B).
The results were generally similar when frailty index transition was defined as percentage change, whereas the predictive ability of frailty index transition was less significant in the maintained robustness/prefrailty and maintained frailty groups (Supplementary Tables 5 and 6).
Discussion
In our study, we calculated and evaluated 4 approaches in capturing transitions in frailty [by categories of phenotype, categories (absolute changes) of frailty index, percentage changes in frailty index, and combined categories of phenotype and frailty index (12 subcategories)] on risk of mortality. We found that considering both frailty phenotype and frailty index provided the best predictability of mortality risk. Nevertheless, even capturing transitions in frailty phenotype or frailty index only can provide good predictability of mortality risk, which provided feasibility in adopting the approaches in different clinical settings.
Published studies have shown that an increased mortality risk is associated with increasing frailty phenotype levels (eg, robust to prefrail or frail, or prefrail to frail), whereas the impact of frailty phenotype improvement is controversial.
We defined frailty phenotype change with continuous instead of categorical variables, and the effect of frailty phenotype change on mortality risk was confounded but not modified by baseline measurement. The interaction term baseline frailty phenotype (robust, prefrail, frail)∗ frailty phenotype change was not statistically significant in the fully adjusted model (Supplementary Table 7). The results were in accordance with those by Xue et al.
; among frail participants, those fulfilling 5 frailty phenotype criteria had a significantly higher 1-year mortality risk than those fulfilling 3 or 4 criteria. A meta-analysis demonstrated that each 0.01 increase in the baseline frailty index was associated with a 4% increase in mortality risk,
and our study extends the findings longitudinally: the adjusted mortality risk increased by 1.04 (95% CI: 1.04–1.05; P < .001) for each 0.01 increase in the frailty index over 4 years.
Previous studies have demonstrated that the mortality risk from cancer, cardiovascular diseases, and respiratory disease increased linearly with severity of frailty phenotype at baseline.
In contrast, an incremental increase in the baseline frailty index, defined by either absolute or percentage change, was associated with excessive risks of cardiovascular- and respiratory-related mortality, whereas the association with cancer-related mortality was less conclusive.
To the best of our knowledge, very few studies have investigated the association between frailty transition and cause-specific mortality. In our analysis, among the 4 frailty phenotype transition groups, the worsened frailty group had the highest mortality risk from most causes except organ failure. In comparison with other causes of death, participants with major organ failure may have earlier and gradual function decline and higher risk of drop-out from the survey, which may lead to underestimation of the impact of worsened frailty. The maintained frailty group had a borderline increased risk of death from infectious diseases and malignancy, which was congruent with a recent study reporting an increased risk of cancer-related mortality in women with sustained or worsened frailty.
The risks in the improved frailty group were comparable to those in the maintained robustness/prefrailty group in most causes of death. The lower risk of organ failure–related death, should be interpreted with caution, which may be influenced by the fluctuation of function before death,
and there may be unmeasured confounders. Nevertheless, the results highlight the potential importance of frailty and physical performance in mortality prediction in these patients,
although further longitudinal or interventional studies of individual disease are warranted.
The rapidly increased frailty index group had consistently higher death risk from different causes in our analysis. Nevertheless, the dose–response relationship between frailty index transition and mortality was not evident in death other than infectious diseases. This result implies heterogeneity in the moderately increased frailty index group, whether defined by absolute or percentage change. Shi et al.
did not observe an impact of a large frailty index increase on mortality in those with a low baseline frailty index, possibly because of adequate reserve in this group. In our analysis, the moderately increased frailty index group had the lowest baseline frailty index compared with the other 2 groups, which may partially explain the results (baseline frailty index: 0.17 ± 0.12 in the improved frailty index group, 0.12 ± 0.10 in the moderately increased frailty index group, and 0.17 ± 0.11 in the rapidly increased frailty index group).
The frailty phenotype was defined by 5 fixed components and focused on physical frailty.
Frailty defined by phenotype was considered a pre-disability syndrome and predictive value of adverse outcomes may be restricted to nondisabled population and the categorical nature may facilitate clinical interpretation.
On the other hand, the main concept of frailty index was deficit accumulation, which encompasses symptoms and signs, diseases, and physical, psychosocial function parameters, and so forth.
Users can construct their own frailty index by standard procedure with similar prediction power, and the results were applicable independent of function status.
Difference among frailty phenotype and frailty index assessment tools by 1-time measurement have been compared: the population selected was related but distinct, and the superiority of mortality prediction was heterogeneous.
In our analysis, when transition groups by the 2 measurements were combined, the mortality risk increased with the degree of change in the frailty index among the different frailty phenotype transition groups. The dose–response relationships were more significant in the worsened and improved frailty groups. These results are generally consistent with those from our work investigating the relationship between frailty phenotype/frailty index transition and disability.
It also supports the findings that mortality risk increases with higher frailty index among participants with the same frailty phenotype level from a 1-time measurement.
On the other hand, worsened frailty contributed to the increased risk compared with the other frailty phenotype transition groups among participants with moderately or rapidly increased frailty index. The previously mentioned findings suggested that frailty phenotype and frailty index transitions may be complementary in mortality prediction, especially for those with a large change in either one of these measurements.
Despite the extensive effort that went into this research, there were several limitations. First, participants who were lost to follow-up before the 2003 survey were not included. The exclusion of these participants, with possibly higher frailty levels or disease severity, might result in low case number in some of the transition groups (especially the maintained frailty group), and underestimate the impact of unfavorable frailty change on mortality. Second, as this is a “survey-based” study in community-dwelling adults, the construction of frailty measurements was mostly defined by self-report items. However, their constructions were based on one of our previously published studies
to increase the validity of these measures. Nevertheless, our results could be more robust if some variables could be captured from objective measures such as those documented in the medical record. Third, the frailty status was measured twice, with a 4-year interval, which may be inadequate to capture the change in a timely manner, and whether mortality prediction improves with the frequency of measurement deserves further investigation. Fourth, the lack of consensus regarding the definition of a “moderate increase in the frailty index” may have contributed to the nonsignificant association with most cause-specific deaths. Studies investigating clinically meaningful cutoffs for different outcomes (eg, mortality, disability) may be warranted.
Conclusions and Implications
In this nationally representative cohort in Taiwan, middle-aged and older adults with worsened frailty had the highest 4-year overall mortality and mortality due to infection, malignancy, cardiometabolic/cerebrovascular diseases, and other causes among the 4 different frailty phenotype transition groups. The risk of the improved frailty group was generally comparable to that of the maintained robustness/prefrailty group, and the risk of death from organ failure was even lower. On the other hand, in comparison with the decreased frailty index group, the rapidly increased frailty index group had the highest all-cause and cause-specific mortality. These associations were independent of baseline frailty status and comorbidities. When considering both frailty phenotype and frailty index, it provided best predictability of mortality risk in comparison to either frailty phenotype or frailty index. Nevertheless, even capturing transitions in frailty phenotype or frailty index alone can provide good predictability of mortality risk, which provided good feasibility in adopting the approaches in different clinical settings.
Acknowledgments
Prof. Nicole Huang and Prof. Fei-Yuan Hsiao provided critical comments to the study.
American Journal Experts provided professional editorial services.
Supplementary Data
Supplementary Table 1Frailty Index Variables
Deficit Categories and Component Items
Answer (Corresponding Frailty Index Value)
I: Health status and comorbidities (17 items)
1. Multimorbidities (confirmed by physician diagnosis): hypertension, diabetes mellitus, heart disease, stroke, cancer, bronchitis or emphysema or asthma, arthritis or rheumatism, peptic ulcer or gastric diseases, hepatobiliary diseases, hip fracture, cataract, renal disease (including stones), gout.
’8’ denotes that a responder did not have the comorbidity (according to question in the original questionnaire), meaning that the question about daily life impact was not applicable.
: No (0), 0: Yes, no impact to daily life (0.33),
1: Yes, some impact on daily life (0.66),
2: Yes, much impact on daily life (1)
3. Diabetes mellitus
8: No (0), 0: Yes, no impact on daily life (0.33),
1: Yes, some impact on daily life (0.66),
2: Yes, much impact on daily life (1)
4. Heart disease
8: No (0), 0: Yes, no impact on daily life (0.33),
1: Yes, some impact on daily life (0.66),
2: Yes, much impact on daily life (1)
5. Stroke
8: No (0), 0: Yes, no impact on daily life (0.33),
1: Yes, some impact on daily life (0.66),
2: Yes, much impact on daily life (1)
6. Cancer
8: No (0), 0: Yes, no impact on daily life (0.33),
1: Yes, some impact on daily life (0.66),
2: Yes, much impact on daily life (1)
7. Bronchitis or emphysema or asthma
8: No (0), 0: Yes, no impact on daily life (0.33),
1: Yes, some impact on daily life (0.66),
2: Yes, much impact on daily life (1)
8. Arthritis or rheumatism
8: No (0), 0: Yes, no impact on daily life (0.33),
1: Yes, some impact on daily life (0.66),
2: Yes, much impact on daily life (1)
9. Peptic ulcer or gastric diseases
8: No (0), 0: Yes, no impact on daily life (0.33),
1: Yes, some impact on daily life (0.66),
2: Yes, much impact on daily life (1)
10. Hepatobiliary diseases
8: No (0), 0: Yes, no impact on daily life (0.33),
1: Yes, some impact on daily life (0.66),
2: Yes, much impact on daily life (1)
11. Hip fracture
8: No (0), 0: Yes, no impact on daily life (0.33),
1: Yes, some impact on daily life (0.66),
2: Yes, much impact on daily life (1)
12. Cataract
8: No (0), 0: Yes, no impact on daily life (0.33),
1: Yes, some impact on daily life (0.66),
2: Yes, much impact on daily life (1)
13. Renal disease (including stones)
8: No (0), 0: Yes, no impact on daily life (0.33),
1: Yes, some impact on daily life (0.66),
2: Yes, much impact on daily life (1)
14. Gout
8: No (0), 0: Yes, no impact on daily life (0.33),
1: Yes, some impact on daily life (0.66)
2: Yes, much impact on daily life (1)
15. Self-rated health
1: Very poor (1), 2: Poor (0.75), 3: Fair (0.5),
4: Good (0.25), 5: Very good (0)
16. Pain
0: None (0), 1: Mild (0.25), 2: Moderate (0.5),
3: Severe (tolerable) (0.75), 4: Very severe (intolerable) (1)
17. Health status evaluated by spouse
1: Very good (0), 2: Good (0.25), 3: Fair (0.5),
4: Poor (0.75), 5: Very poor (1)
II: Physical activity, ADL and IADL (22 items)
1. Fall or accidental injury in past year
0: No (0), 1: Yes (1)
2. Stand for 15 minutes
0: No difficulty (0), 1: Some difficulty (0.33),
2: Much difficulty (0.66), 3: Can’t do it at all (1)
3. Stand for 2 hours
0: No difficulty (0), 1: Some difficulty (0.33),
2: Much difficulty (0.66), 3: Can’t do it at all (1)
4. Squatting
0: No difficulty (0), 1: Some difficulty (0.33),
2: Much difficulty (0.66), 3: Can’t do it at all (1)
5. Raising both hands over head
0: No difficulty (0), 1: Some difficulty (0.33),
2: Much difficulty (0.66), 3: Can’t do it at all (1)
6. Grasping objects with fingers
0: No difficulty (0), 1: Some difficulty (0.33),
2: Much difficulty (0.66), 3: Can’t do it at all (1)
7. Lifting 11–12 kilograms
0: No difficulty (0), 1: Some difficulty (0.33),
2: Much difficulty (0.66), 3: Can’t do it at all (1)
8. Run for 20–30 minutes
0: No difficulty (0), 1: Some difficulty (0.33),
2: Much difficulty (0.66), 3: Can’t do it at all (1)
9. Walking 200–300 m
0: No difficulty (0), 1: Some difficulty (0.33),
2: Much difficulty (0.66), 3: Can’t do it at all (1)
10. Climb 2–3 flights of stairs
0: No difficulty (0), 1: Some difficulty (0.33),
2: Much difficulty (0.66), 3: Can’t do it at all (1)
11. Taking Bath
0: No difficulty (0), 1: Some difficulty (0.33),
2: Much difficulty (0.66), 3: Can’t do it at all (1)
12. Dressing
0: No difficulty (0), 1: Some difficulty (0.33),
2: Much difficulty (0.66), 3: Can’t do it at all (1)
13. Eating
0: No difficulty (0), 1: Some difficulty (0.33),
2: Much difficulty (0.66), 3: Can’t do it at all (1)
14. Get up from bed; stand; sit on the chair
0: No difficulty (0), 1: Some difficulty (0.33),
2: Much difficulty (0.66), 3: Can’t do it at all (1)
15. Moving around the house
0: No difficulty (0), 1: Some difficulty (0.33),
2: Much difficulty (0.66), 3: Can’t do it at all (1)
16. Toileting
0: No difficulty (0), 1: Some difficulty, (0.33),
2: Much difficulty (0.66), 3: Can’t do it at all (1)
17. Buying personal item
0: No difficulty (0), 1: Some difficulty (0.33),
2: Much difficulty (0.66), 3: Can’t do it at all (1)
18. Managing money
0: No difficulty (0), 1: Some difficulty (0.33),
2: Much difficulty (0.66), 3: Can’t do it at all (1)
19. Riding bus/train on one’s own
0: No difficulty (0), 1: Some difficulty (0.33),
2: Much difficulty (0.66), 3: Can’t do it at all (1)
20. Doing light tasks at home
0: No difficulty (0), 1: Some difficulty (0.33),
2: Much difficulty (0.66), 3: Can’t do it at all (1)
21. Doing physical work at home
0: No difficulty (0), 1: Some difficulty (0.33),
2: Much difficulty (0.66), 3: Can’t do it at all (1)
22. Making phone calls
0: No difficulty (0), 1: Some difficulty (0.33),
2: Much difficulty (0.66), 3: Can’t do it at all (1)
III: Cognitive domain (10 items)
1. Orientation to time (year)
0: Wrong (1), 1: Right (0)
2. Orientation to time (month)
0: Wrong (1), 1: Right (0)
3. Orientation to time (day)
0: Wrong (1), 1: Right (0)
4. Orientation to time (day of the week)
0: Wrong (1), 1: Right (0)
5. Recall home address
0: Wrong (1), 1: Right (0)
6. Recall mother’s family name
0: Wrong (1), 1: Right (0)
7. Recall current president’s name
0: Wrong (1), 1: Right (0)
8. Recall former president’s name
0: Wrong (1), 1: Right (0)
9. Know his/her own age
0: Wrong (1), 1: Right (0)
10. Immediate recall (10 items)
Participants answering X items, score = (1- (X/10))
IV: Psychological (10 items)
1. Poor appetite
0: No (0), 1: Seldom (1 day/week) (0.33),
2: Sometimes (2–3 days/week) (0.66),
3: Usually or often (more than 4 days/week) (1)
2. Everything was an effort
0: No (0), 1: Seldom (1 day/week) (0.33),
2: Sometimes (2–3 days/week) (0.66),
3: Usually or often (more than 4 days/week) (1)
3. Could not get going
0: No (0), 1: Seldom (1 day/week) (0.33),
2: Sometimes (2–3 days/week) (0.66),
3: Usually or often (more than 4 days/week) (1)
4. Insomnia
0: No (0), 1: Seldom (1 day/week) (0.33),
2: Sometimes (2–3 days/week) (0.66),
3: Usually or often (more than 4 days/week) (1)
5. Feels lonely
0: No (0), 1: Seldom (1 day/week) (0.33),
2: Sometimes (2–3 days/week) (0.66),
3: Usually or often (more than 4 days/week) (1)
6. Low mood
0: No (0), 1: Seldom (1 day/week) (0.33),
2: Sometimes (2–3 days/week) (0.66),
3: Usually or often (more than 4 days/week) (1)
7. Feel others are unfriendly
0: No (0), 1: Seldom (1 day/week) (0.33),
2: Sometimes (2–3 days/week) (0.66),
3: Usually or often (more than 4 days/week) (1)
8. Feels happy
0: Usually or often (more than 4 days/week) (0),
1: Sometimes (2–3 days/week) (0.33),
2: Seldom (1 day/week) (0.66), 3: Never (1)
9. Life goes well
0: Usually or often (more than 4 days/week) (0),
1: Sometimes (2–3 days/week) (0.33),
2: Seldom (1 day/week) (0.66), 3: Never (1)
10. Feels sad
0: No (0), 1: Seldom (1 day/week) (0.33),
2: Sometimes (2–3 days/week) (0.66),
3: Usually or often (more than 4 days/week) (1)
V: Life satisfaction, stress, and financial status (10 items)
1. Satisfaction with life
0: No (1), 1: Yes (0)
2. Satisfaction with what you’re doing
0: No (1), 1: Yes (0)
3. Living in a safe and secure environment
0: No (1), 1: Yes (0)
4. Satisfaction with current financial status
1: Very good (0), 2: Good (0.25), 3: Fair (0.5),
4: Poor (0.75), 5: Very poor (1)
5. Meeting living expenses
1: No difficulty (0), 2: Fair (0.33),
3: Some difficulty (0.66), 4: Much difficulty (1)
6. Stress on one’s own finances
0: None (0), 1: Sometimes (0.5), 2: Often (1)
7. Stress on one’s job
0: None (0), 1: Sometimes (0.5), 2: Often (1)
8. Stress on family member’s health, finances, or job
0: None (0), 1: Sometimes (0.5), 2: Often (1)
9. Stress on family’s relationship
0: None (0), 1: Sometimes (0.5), 2: Often (1)
10: Concerns from family and friends
1: Very good (0), 2: Good (0.25), 3: Fair (0.5),
4: Poor (0.75), 5: Very poor (1)
VI: Sensory (3 items)
1. Visual impairment
0: Can see without glasses (0),
1: Can see with glasses (0.5),
2: Visual impairment (1)
2. Hearing impairment
0: Can hear without hearing aids (0),
1: Can hear with hearing aids (0.5),
2: Hearing impairment (1)
3. Oral intake difficulty
0: Can eat without denture (0),
1: Can eat with denture (0.5),
2: Poor oral intake (1)
ADL. activities of daily living; IADL, instrumental activities of daily living.
∗ ’8’ denotes that a responder did not have the comorbidity (according to question in the original questionnaire), meaning that the question about daily life impact was not applicable.
Y.J.C. and L.K.C. contributed equally to the study.
This work was supported by the Ministry of Science and Technology, Taiwan (MOST 109–2314-B-010 -047 -MY2 and MOST 111-2314-B-A49-018-MY3), National Health Research Insitute, Taiwan (NHRI-11A1-CG-CO-01-2225-1) and Taipei Veterans General Hospital. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors declare no conflicts of interest.
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