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Ann Geriatr Med Res > Volume 29(1); 2025 > Article
Shimokihara, Yokoyama, Ihira, Matsuzaki-Kihara, Mizumoto, Tashiro, Saito, Makino, Shimada, Yama, Miyajima, Sasaki, and Ikeda: Linear Association between Frailty as Assessed by the Kihon Checklist and Quality of Life in Community-Dwelling Older Adults: A Cross-Sectional Population-Based Study

Abstract

Background

The need for support focused on frailty and quality of life (QoL) in older adults is increasing. The Kihon Checklist (KCL) is a comprehensive and easy-to-use tool to assess frailty in older adults. Previous studies have shown associations between frailty and QoL; however, few studies have investigated the association between frailty using the KCL and QoL. In this study, the quantitative relationship between the KCL and QoL in community-dwelling older adults was investigated.

Methods

This cross-sectional study included from participants in the 2017–2019 baseline survey of a cohort study of community-dwelling older adults in Sapporo, Japan. The World Health Organization Five Well-Being Index (WHO-5) was used to assess QoL. The KCL was used to assess frailty, and the relationship between frailty and QoL was examined using binomial logistic regression analysis and restricted cubic spline models.

Results

Four-hundred participants were included in the analysis. Of the participants, 22.5% had a lower QoL and they were more likely to have frailty than healthy participants (p<0.001). The KCL scores were significantly associated with a lower QoL (p<0.001). Furthermore, the association between the KCL score and QoL was linear, and subscales of activities of daily living, and depressive mood were significantly associated with a lower QoL.

Conclusion

The KCL, a comprehensive frailty questionnaire, was associated with a lower QoL in older adults. To maintain QoL in community-dwelling older adults, it is necessary to provide them with appropriate support from the stage before they are identified as frail by the KCL.

INTRODUCTION

The number of adults aged 60 years and older is predicted to reach 2.1 billion by 2050.1) Accordingly, addressing health issues associated with population aging has become a major challenge for modern society. Japan is aging rapidly, and communities need to maintain the health and improve the quality of life (QoL) of older adults to prolong healthy life.
Frailty is a geriatric syndrome that is common among older adults. It is a state of increased vulnerability associated with aging that is known to result in an increased risk of adverse health outcomes, such as disability, hospitalization, and death.2) It is typically assessed using criteria related to physical function, mobility, and muscle strength.3) The prevalence of frailty in older adults varies, but it is estimated that 25%–50% of people aged 85 years and older are at risk for frailty and significantly increased risk of adverse outcomes.4,5) Another study reported that approximately one in six older adults living in the community may be frail.6) Among the several frailty criteria presented, the Kihon Checklist (KCL) has been widely used as a frailty assessment tool.7-9) The KCL consists of simple yes/no 25-item questionnaires that cover in depth several domains that are important geriatric syndromes. This indices, initially developed in Japan, have now been translated into English and other languages and used in non-Japanese populations.10-14) A prior research sought to validate the KCL as a frailty assessment tool and shown a strong correlation between the KCL and frailty state as defined by the Fried phenotype,8) which is now the most frequently used frailty criterion.15) The Fried phenotype defines frailty as a biological condition, identified by five specific physical symptoms: weight loss, fatigue, muscular weakness, lower gait speed, and low levels of physical activity.15) The KCL assessment of frailty has the advantage that it can be used in a wider range of settings as it does not require a direct assessment of the individual’s physical function. The Frailty Index (FI) is an additional widely utilized operationalization of frailty.16) This method allows the assessment of frailty status from more than 30 items specific to older adults and considers symptoms, signs, diseases, disabilities, or laboratory, radiographic, or electrocardiographic abnormalities and signs as health deficits.16) The KCL indices may be more similar to the conceptualization of the FI because they cover a wide range of instrumental and social activities of daily living (ADL), physical function, nutritional status, oral function, cognitive function, and depressive mood that can be used as a deficit to construct the FI. Previous research has shown that although the KCL has fewer items than the standard FI, the KCL is highly correlated with the FI and is compatible with the FI in predicting the risk of disability onset and death.17) Given the reversible nature of frailty,18) the need for detection of frailty in the older population, and the development of more effective prevention strategies to extend the healthy life expectancy of older adults, there are high expectations for the use of KCL.
According to the World Health Organization (WHO), QoL includes a sense of life in terms of values, culture, norms, interests, and goals.19) Thus, QoL is subjectively expressed in terms of an individual’s enjoyment of and satisfaction with life. In recent years, many tools have become available to easily assess QoL in older adults and can be used for community health checks.20-22) Previous studies have demonstrated a clear association between frailty and QoL. Frailty has been shown to affect multiple aspects of QoL in older adults, including physical and psychological health and social relationships.23,24) In addition, frailty status has been shown to be strongly associated with a lower QoL.25) In other words, frailty is significantly associated with a lower QoL in community-dwelling older adults. Early assessment, management, and intervention for frailty can help preserve QoL in older adults. However, many aspects of the specific relationship between frailty and QoL, as assessed using the KCL, remain to be fully elucidated. Investigating the relationship between comprehensive frailty assessments, such as the KCL and the WHO Five Well-Being Index (WHO-5), a brief assessment of QoL, is expected to be an important resource for understanding the status of frailty and QoL among older adults in a large region. Therefore, this study aimed to quantitatively evaluate the relationship between frailty and QoL using the KCL. Considering the risk of adverse outcomes of frailty in older adults, particularly in relation to QoL, we hypothesized that comprehensive frailty assessed using the KCL would be negatively associated with QoL in older adults. We expect that this study will provide the KCL to facilitate implementation of positive actions to improve frailty and QoL in community-dwelling older adults.

MATERIALS AND METHODS

Research Design

This study used a cross-sectional design. The survey was conducted using a self-administered questionnaire distributed by mail.

Participants

Data were obtained from the Widely Hokkaido Individual Training for Elderly (WHITE) study, a cohort study of older adults living in this region since 2017. The WHITE study was a health study of older adults living in Sapporo, Hokkaido, Northern Japan. Questionnaires were mailed in March 2021 to older adults who participated in a baseline survey between 2017 and 2019. Of the 460 individuals who returned questionnaires, we excluded (1) those certified as requiring assistance or care by the Japanese public long-term care insurance (LTCI) system (n=58) and (2) those with missing data (n=2). Ultimately, 400 participants were included in the analysis. A flowchart of the study is shown in Fig. 1. The LTCI certification system divides individuals into seven levels over two stages: support levels 1 and 2, and care needs levels 1 to 5.26) In Japan, LTCI users are considered to have higher levels of frailty and disability.27) They were excluded from the main analysis because their inclusion could have introduced bias as they are a different population from the community-dwelling older adults who are generally independent. The study was approved by the Sapporo Medical University Ethical Review Board (Approval No. 28-2-7). Written informed consent was obtained from each participant after explaining the procedure.

Operational Definition of Frailty

The KCL has previously been used to measure frailty.8,28,29) The KCL is a comprehensive 25-item self-administered questionnaire developed by the Japanese Ministry of Health, Labor, and Welfare to identify frail older adults who are at future risk of requiring support. It has been translated into many other languages, making it suitable for use in cross-cultural studies. The 25 items covered the following six domains: instrumental and social ADLs (seven items), physical function (five items), nutritional status (two items), oral function (three items), cognitive function (three items), and depressive mood (five items). The worse the state of each frailty-related domain, the higher the KCL score. Frailty was defined as a total KCL score ≥8 points, in accordance with a previous study.8)

Assessment of QoL

The Japanese version of the WHO-5 was used to assess QoL. The WHO-5 can easily and quantitatively assess QoL.30) The WHO-5 is a brief, self-administered measure of well-being over the previous 2 weeks.30) The WHO-5 consists of six items expressed in positive terms and rated on a six-point Likert scale ranging from 0 (at no time) to 5 (all times) (Supplementary Table S1). Raw scores range from 0 to 25, with lower scores indicating a lower QoL; scores of <13 are often used as a cutoff for poor health condition.31) In this study, as in previous reports,31) participants with a WHO-5 score of <13 were assigned to the lower QoL group, and other participants were assigned the normal QoL group. The Japanese version of the WHO-5 was validated and standardized in previous studies.31,32)

Covariates

Demographic information, such as age, sex, and living situation (living alone or with someone), was collected. The participants were also asked about their medical history, including the conditions for which they were currently being treated. In addition, the number of medications the participants were currently taking was recorded.

Statistical Analysis

Participant characteristics were grouped according to the presence or absence of a lower QoL and tabulated using descriptive statistics. Continuous variables were tabulated as mean (standard deviation) and categorical variables as the number of observations (%). Statistical tests according to the distribution of variables were used as inferential statistics. Welch t-test or Mann-Whitney U test was used for continuous variables and the chi-square test for categorical variables. A binomial logistic regression model was used to determine the association between frailty and QoL, as assessed using the KCL. The dependent variable was QoL (1=a lower QoL), the independent variable was the total KCL score, and the covariates were age, sex, disease history, medications, and living situation. To examine whether this association varied by age and sex, we also performed analyses stratified by age (65–74 years, >75 years) and sex. Additionally, restricted cubic spline (RCS) models were developed to quantitatively examine the relationship between the KCL scores and a lower QoL. By comparing the spline and linear models using a likelihood ratio test, the statistical significance of the nonlinearity was determined. A statistically significant nonlinear link between the KCL score and QoL was shown by a p-value <0.05 for the nonlinearity test, leading to the adoption of the spline model. In contrast, when the test of nonlinearity yields a p-value ≥0.05, the linear model is accepted. As an additional analysis to explore the relationship between frailty and QoL, binomial logistic regression models were created, similar to the method presented above, for the association between the six subscales of the KCL and QoL. As the purpose of this study was to identify relevant subscales, the p-values were not adjusted.33) As a sensitivity analysis, we included 58 older adults certified as LTCI who were excluded from the main analysis of the current study. In a first step, those requiring the support level (n=47) were included in the analysis, and in a second step, those requiring the care level (n=11) were included. For all analyses, the statistical significance level was set at p<0.05. R ver. 4.4.0 (https://www.r-project.org/) was used for all analyses and plotting, and the "ggrcs" package was used to generate the RCS models.

RESULTS

Characteristics of Study Participants

The participant characteristics are shown in Table 1. The mean WHO-5 total score for all participants was 15.21±5.01. Ninety participants (22.5%) had a lower QoL, with a mean WHO-5 score of 7.98±3.55. The mean WHO-5 score for participants with normal QoL was 17.32±3.02. The participants with a lower QoL used significantly more medications than participants with normal QoL (U=11,648, p=0.04). The rate of frailty was significantly greater in the lower QoL group (χ2=8.40, p<0.001). There were no significant differences between the two groups in terms of age, sex, disease history, or living situation. Supplementary Table S2 shows data on the characteristics of the participants’ medical history. No differences in medical history were observed between the two groups, except for hyperlipidemia.

Association between the KCL and QoL

Table 2 provides a summary of the binomial logistic regression model, showing that the KCL score was significantly associated with the presence of a lower QoL and a positive association between the KCL score and a lower QoL (odds ratio [OR]=1.22, 95% confidence interval [CI] 1.12–1.32, p<0.001). Fig. 2 shows a linear relationship between the KCL score and a lower QoL; the nonlinear association between the KCL score and a lower QoL was not significant (p=0.13). The x-axis shows the KCL score and the histogram and the y-axis shows the OR for a lower QoL. The results confirmed a positive association between an increasing KCL score and higher odds of a lower QoL. The direction of this association was also shown to reverse around a KCL score of 4; as the KCL score decreased to less than 4, the OR of a decline in QoL also decreased to less than 1. Fig. 3 shows the results of the stratified analysis performed to examine the effects of sex and age. The results show that the overall association between KCL and QoL is consistent. The association was particularly high among male participants (OR=1.38, 95% CI 1.14–1.67, p<0.001).

KCL Subscales Associated with QoL

Fig. 4 shows the associations between the six KCL subscales and QoL. A significant association was found between higher instrumental and social ADLs (OR=1.60, 95% CI 1.18–2.17, p=0.002) and depressive mood (OR=1.70, 95% CI 1.41–2.04, p<0.001) subscale scores and a lower QoL. The details of all the regression models are provided in Supplementary Table S3.

Sensitivity Analysis

In a sensitivity analysis including 58 older adults with LTCI who were excluded from the main analysis, a significant association between KCL and QoL was found in both a regression model with support needs (n=547; OR=1.60, 95% CI 1.18–2.17, p=0.01) and a model with care needs (n=558; OR=1.16, 95% CI 1.04–1.31, p=0.01). This is a similar trend to our main results, but the magnitude of the association was slightly smaller.

DISCUSSION

This study investigated the quantitative relationship between the KCL, a comprehensive frailty assessment scale used in many locations, and QoL in community-dwelling older adults. The results showed that 22.5% of participants experienced a decline in QoL. Of the participants with a lower QoL, 23.3% were classified as frail according to the KCL. Furthermore, a positive linear relationship between a lower QoL and the KCL scores was confirmed, with particularly significant associations between ADLs and depressive mood subscale scores on the KCL and QoL. The KCL can be used to assess not only the frailty status of older adults but also their relationship with QoL and may provide more useful information to support older adults living in the community.
A lower QoL is more likely to be observed in older adults with impaired physical health.34) In the participants of this study, there was no association between a history of disease and a lower QoL, but the higher the number of medications taken, the lower the QoL. Furthermore, a detailed examination of the participants’ medical history revealed the only association between lower QoL and a history of hyperlipidemia, but this result may not be as important given the multiplicity of statistical tests. Many previous studies have reported reduced QoL in older adults with certain medical conditions.35-37) It is possible that the participants in this study were a relatively healthy sample and the association between specific diseases and QoL may have been underestimated. Future studies should focus on community-dwelling older adults with specific diseases and conduct more detailed analyses. In contrast, some studies reported that the association between polypharmacy and a lower QoL was negative38); however, the QoL assessment was based on the reports of others and was unlikely to reflect the opinions of the subjects themselves. Similar to the present study, a positive association between ability to perform ADLs and QoL has been shown,39) and it is possible that ADLs support for older adults in the community may be important. ADLs assessed in the KCL include higher-level ADLs, such as using public transportation, outdoor shopping, and managing property. Community-dwelling older adults with a lower QoL may feel inconvenienced by these higher-level ADLs and require advanced support using social resources, and information and communication technology.
Many studies have reported a very strong relationship between depressive symptoms and QoL among older adults.40,41) The results of the present study support these findings, as the OR for the depressive mood subcategory was the highest of the six subscales, suggesting that assessing depressive symptoms is essential for assessing QoL in older adults. In particular, among community-dwelling older adults, having depressive symptoms assessed by the KCL had a hazard ratio (HR) of 1.81 for the occurrence of long-term care at 2 years, compared with those who did not have depressive symptoms.42) Therefore, it is important to evaluate the depressive items of the KCL in community-dwelling older adults and provide appropriate interventions to prevent, not only a decline in QoL, but also the subsequent requirement for long-term care. Whereas the association between the KCL subscales of cognitive function, oral function, nutritional status, and physical function and QoL was not significant. This may be related to the relatively good health status of the study participants. It should be noted that in a larger study assessing frailty in community-dwelling older adults using the KCL, the proportion of older adults with frailty was 30.8% for men and 33.3% for women,43) a slightly higher proportion than in the present study population.
Interestingly, the results of this study showed a linear relationship, in which the OR of QoL decline was greater than 1 when the KCL score was greater than 4. Previous reports have recommended a KCL cutoff score of 7 or 8 to identify older adults with frailty,8) but this cutoff may not be sufficient to assess a decline in QoL in older adults. In fact, in a previous large-scale study that used the KCL to investigate the incidence of new cases of long-term care, scores of 4 or more points were a significant predictor of the incidence of long-term care; the group with a total KCL score of 4–7 points had an HR of 2.03, whereas the group with a total KCL score of 8 or more points had an HR of 4.77, when the group with a KCL score of 0–3 points was the reference.9) Consistent with these reports, the present study showed that as KCL scores worsen (i.e., as frailty-related domains worsen), the association with a lower QoL in older adults increases. This suggests that preventive measures for long-term care are important even before the patient is classified as frail by the KCL, which may also be important for maintaining and improving QoL. In addition, the results of the stratified analysis of this study showed that although the proportion of persons with lower QoL was higher in females (females 25.3%; males 16.3%), the association between KCL and QoL was highest in males. Previous studies have shown that older men are more likely to have lower QoL than older women.44,45) Older men experience lower testosterone levels and changes in thyroid hormones,46) and the involvement of cultural norms and gender role factors also contributes to poor health.47) These factors may emphasize the association between lower function in multiple domains assessed by the KCL and reduced QoL. However, older women who are childless and have experienced psychosocial losses have been shown to have lower subjective well-being compared to men.44,48) Therefore, when considering the impact of gender on QoL in future studies, it is important to assess multiple perspectives, including physical, cognitive, and psychosocial aspects.
This study has several limitations that must be considered when interpreting the results. First, the participants were able to proactively participate in the university health check-up program, which may have included many physically and mentally healthy participants. Therefore, when generalizing the results of this study, one should be aware of the possibility of underestimating the percentage QoL decline among the participants. Additionally, the assessments included self-reported measures. It should be noted that these measures may be subject to biases that could influence the results, such as recall and social desirability biases. Next, there is a lack of data on socioeconomic status (SES), one of the determinants of QoL among the older adults. Factors such as income, education, and occupation have been shown to influence QoL.49,50) The lack of SES data may have led to an incomplete understanding of the relationship between KCL and QoL, as variations in SES could contribute to disparities in QoL that were not captured in this study. Future research should aim to include SES-related variables to better account for their potential confounding effects and provide a more comprehensive understanding of the factors affecting QoL in community-dwelling older adults. Finally, the cross-sectional design of this study made it difficult to address the causal relationship between a lower QoL and the KCL score. Despite these limitations, this study, which examined the relationship between KCL and QoL, in detail, will contribute to maintaining the well-being of older adults.

Conclusion

In the present study, we investigated the detailed association between QoL and the KCL, a comprehensive frailty assessment tool, in community-dwelling older adults. We found a significant linear association between KCL scores and QoL, with a significantly higher proportion of participants having a lower QoL and frailty as assessed using the KCL. These results also suggest that a lower QoL in older adults may be associated with the prodromal phase of frailty. In particular, among the KCL subcategories, the ADLs and depressive mood subscales were significantly associated with a lower QoL. This suggests the need to use a comprehensive frailty questionnaire, such as the KCL, to promote the well-being of community-dwelling older adults at an early stage.

ACKNOWLEDGMENTS

The authors would like to thank all participants in this study.

CONFLICT OF INTEREST

The researchers claim no conflicts of interest.

FUNDING

This research was funded by the Japan Agency for Medical Research and Development (Research Project No. 20dk0207027h0005), an academic grant from Sapporo Medical University (No. 2100201), and Grants-in-Aid for Scientific Research (KAKENHI; Grant No. 24KJ1846 and 24K05415).

AUTHOR CONTRIBUTIONS

Conceptualization, SS, KY; Data curation, SS, KY; Funding acquisition, SS; Investigation, KY, HI, YMK, AM, HT, HS, KS, KY, RM, TS; Methodology, SS; Project administration, KY, HI, NI; Supervision, HI, NI; Writing–original draft, SS, KY; Writing–review & editing, HI, YMK, AM, HT, HS, KS, KY, RM, TS, NI.

SUPPLEMENTARY MATERIALS

Supplementary materials can be found via https://doi.org/10.4235/agmr.24.0117.
Supplementary Table S1.
The 5-item World Health Organization Well-Being Index (WHO-5)
agmr-24-0117-Supplementary-Table-S1.pdf
Supplementary Table S2.
Medical history characteristics of participants
agmr-24-0117-Supplementary-Table-S2.pdf
Supplementary Table S3.
Details of all regression models used to examine the relationship between KCL subscales and QoL
agmr-24-0117-Supplementary-Table-S3.pdf

Fig. 1.
Flowchart of the study.
agmr-24-0117f1.jpg
Fig. 2.
Linear relationship between Kihon Checklist (KCL) scores and quality of life. The red dashed line indicates the OR of 1.0. The blue solid line and shaded areas show ORs and 95% CI for KCL scores. OR, odds ratio; CI, confidence interval.
agmr-24-0117f2.jpg
Fig. 3.
Stratified analysis of association between Kihon Checklist (KCL) scores and quality of life (QoL). In the four binomial logistic regression models, the dependent variable was QoL, the independent variables were KCL score. Covariates included age, sex, medical history, medications, and living situation, but sex was excluded from covariates in the model stratified by sex, and age was excluded from the covariates in the model stratified by age. A significant association between the KCL subscale scores and a lower QoL are indicated by adjusted odds ratios (aOR) and 95% confidence interval (CI) greater than 1.00.
agmr-24-0117f3.jpg
Fig. 4.
Relationship between six Kihon Checklist (KCL) subscales and quality of life (QoL).
In the six binomial logistic regression models, the dependent variable was QoL, the independent variables were the subscale scores of the KCL, and the covariates were age, sex, disease history, medications, and living situation. A significant association between the KCL subscale scores and a lower QoL are indicated by odds ratio (OR) and 95% confidence interval (CI) greater than 1.00.
agmr-24-0117f4.jpg
Table 1.
Characteristics of study participants
Characteristic Overall (n=400) Normal QoL (n=310) Lower QoL (n=90) p-valuea)
Age (y) 76.1±5.5 76.0±5.5 76.6±5.5 0.44
Sex 0.05
 Male 123 (30.8) 103 (33.2) 20 (22.5)
 Female 277 (69.3) 207 (66.8) 70 (77.8)
Disease historyb) 0.76
 None 71 (17.8) 56 (18.1) 15 (16.7)
 Yes 329 (82.3) 254 (81.9) 75 (83.3)
Medication 2.9±3.8 2.8±3.9 3.4±3.5 0.04
Living situation 0.73
 Living with someone 283 (70.8) 218 (70.3) 65 (72.2)
 Living alone 117 (29.3) 92 (29.7) 25 (27.8)
Frailty <0.001
 Robust 344 (86.0) 275 (88.7) 69 (76.7)
 Frailty 56 (14.0) 35 (11.3) 21 (23.3)

Values are presented as mean±standard deviation or number (%).

QoL, quality of life.

a)p-value calculated by Mann-Whitney U test or Pearson χ2 test.

b)If the participant has at least one medical condition, the option is yes.

Table 2.
Summary of the binominal logistic regression model used to investigate the association between KCL and QoL
Estimate SE OR 95% CI
p-value
Lower Upper
Age 0.02 0.02 1.02 0.97 1.06 0.51
Sex (ref. male) 0.55 0.32 1.73 0.92 3.23 0.09
Disease history (ref. none) -1.20 0.35 0.87 0.44 1.77 0.73
Medication 0.02 0.03 1.02 0.96 1.09 0.48
Living situation (ref. living with someone) -0.32 0.30 0.73 0.41 1.30 0.29
KCL 0.20 0.04 1.22 1.12 1.32 <0.001

KCL, Kihon Checklist; QoL, quality of life; SE, standardized error; OR, odds ratio; CI, confidence interval.

Overall model test: χ2=29.58, p<0.001, Akaike information criterion=402.9, Bayesian information criterion=430.8, all variance inflation factor <1.50.

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