DOI: 10.1111/ggi.14439

ORIGINAL ARTICLE
EPIDEMIOLOGY, CLINICAL PRACTICE AND HEALTH

Predictive validity of the modiﬁed Kihon Checklist for theincidence of functional disability among older people: A
3-year cohort study from the JAGES
Ryota Watanabe,1,2 Taishi Tsuji,2,3 Kazushige Ide,2 Taiji Noguchi,4 Mikako Yasuoka,1Koto Kamiji,1,5 Shosuke Satake,1,6 Katsunori Kondo2,7 and Masayo Kojima1
1

Department of Frailty Research, Research Institute, National Center for Geriatrics and Gerontology, Obu City,
Aichi, Japan2
Department of Social Preventive Medical Sciences, Center for Preventive Medical Sciences, Chiba University, Chiba city, Chiba, Japan
3
Faculty of Health and Sport Sciences, University of Tsukuba, Bunkyo city, Tokyo, Japan
4
Department of Social Science, Research Institute, National Center for Geriatrics and Gerontology, Obu City, Aichi, Japan
5
Center for Professional Development of Teachers, Shizuoka University, Shizuoka City, Shizuoka, Japan
6
Department of Geriatric Medicine, Hospital, National Center for Geriatrics and Gerontology, Obu city, Aichi, Japan
7
Department of Gerontological Evaluation, Research Institute, National Center for Geriatrics and Gerontology, Obu City,
Aichi, Japan
Correspondence
Ryota Watanabe PhD, Department
of Frailty Research, ResearchInstitute, National Center for
Geriatrics and Gerontology, 7-430
Morioka, Obu City, Aichi
474-8511 Japan.
Email: ryota.
watanabe.1222@gmail.com
Received: 6 January 2022
Revised: 3 June 2022
Accepted: 18 June 2022

Aim: The original Kihon Checklist, validated to predict the incidence of functional disability, hasbeen modiﬁed to capture both functional ability (can/cannot) and performing state (do/do not). However, the predictive validity of the modiﬁed Kihon Checklist remains unveriﬁed. Therefore, this study
intends to verify the predictive validity of the modiﬁed Kihon Checklist and to clarify whether predictive discrimination differs between the classiﬁcation method of functional ability and performing state.
Methods: The participants comprised 67 398 older people who responded to the Japan
Gerontological Evaluation Study (2016). They were followed for 3.1 years on average. Cox’s
proportional hazards model with incidence of functional disability as the endpoint was used
to calculate the hazard ratio, adjusted for sex and age. The independent variables were judged
by two classiﬁcation methods, functional ability and performing state, using nine indicators
based on the modiﬁed Kihon Checklist. Additionally, we examined whether the two classiﬁcation methods produced different C-index estimates.
Results: Incidence of functional disability occurred in 6232 participants (9.2%). The
adjusted hazard ratio of those to whom the nine indicators applied was signiﬁcantly higher
than that of those to whom they did not. The range of the hazard ratio was 1.50–3.82 for bothclassiﬁcation methods. The C-index was slightly higher when the classiﬁcation was based on
performing state than when it was based on on functional ability.
Conclusions: Although predictive discrimination was slightly higher for the performing
state than for functional ability, the predictive validity of the modiﬁed Kihon Checklist was
conﬁrmed for both. Geriatr Gerontol Int 2022; ••: ••–••.
Keywords: functional ability, geriatric assessment, long-term care insurance, performing
state, predictive discrimination.

Introduction
The world’s population of older people is expected to increase byapproximately 34%, from 1 billion in 2019 to 1.4 billion in 2030.1
Consequently, it is necessary to effectively maintain and improve
the health of older people.
The World Health Organization has indicated that healthy
ageing should include functional ability as a health-related characteristic that enables a person to do something valuable and remain

in a desirable state, and it aims to maximize older people’s functional ability.2 One of the four priority areas for achieving this aim
is to “improve measurement, monitoring, and understanding.”2
Japan has the world’s oldest population,3 and its governmenthas been using the Kihon Checklist (KCL) as a tool for the early
detection of older people who are at risk for functional disability.4
The KCL is a 25-item self-administered questionnaire with two
Yes/No options and is a comprehensive geriatric assessment that
evaluates the functions of older people.5 In this evaluation,© 2022 The Authors. Geriatrics & Gerontology International
published by John Wiley & Sons Australia, Ltd on behalf of Japan Geriatrics Society.

|1This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution
in any medium, provided the original work is properly cited, the use is non-commercial and no modiﬁcations or adaptations are made.

R Watanabe et al.
performing state (do/do not) is used as a criterion, and one point
is added to the score if the content of each question is considered
to limit daily function. A systematic KCL review has shown that ahigher number of items predicts problematic health indicators,
including the incidence of functional disability.6 Furthermore,
longitudinal studies have indicated that the KCL can predict theincidence of functional disability among older people.7–9
However, the Ministry of Health, Labour and Welfare(MHLW) has also developed a modiﬁed version of the KCL for
the Public Survey of Long-Term Care Prevention and Needs in
Spheres of Daily Life, which introduced three options for severalof the responses in order to grasp both functional ability (can/cannot) and performing state.10 The option “I can, but don’t doit” was added. This change was made to reﬂect the opinion of themunicipal staff working on the prevention of functional decline
during the development of the survey questionnaire. Municipalities use this modiﬁed KCL in the Public Survey of Long-TermCare Prevention and Needs in Spheres of Daily Life to identify
issues and assess the risk of individuals developing long-term careneeds in each community.11 However, it is unclear whether themodiﬁed KCL can predict the incidence of functional disability
among older people. Additionally, it is unclear whether predictive
validity differs depending on whether the three-option response
items are classiﬁed as focusing on functional ability or performing
state.
This study aims to determine whether the modiﬁed KCL has
predictive validity for the incidence of functional disability. In
addition, it aims to examine the extent to which predictive validity
differs depending on whether the three options are classiﬁed asfunctional ability or performing state.

Methods
This study utilized the longitudinal cohort data from the Japan
Gerontological Evaluation Study (JAGES). The JAGES is an
ongoing cohort study investigating social and behavioral factors related to health decline, including the incidence of functional decline or cognitive impairment among individuals aged
≥65 years.12,13 The baseline survey that was undertaken was
self-reported and distributed by mail to 129 311 people aged
≥65 years between October and November 2016. The participants were older people who did not receive public long-termcare insurance (LTCI) certiﬁcation and were selected from18 municipalities in 10 prefectures of Japan. Furthermore, random sampling methods were used in 10 large municipalities,
and complete enumeration survey methods were used in eightsmaller municipalities. Among 92 234 respondents (response
rate 71.3%), sex, age, and area of residence were validly collected from 84 376 respondents. Out of the valid respondents,
83 079 (98.5%) participants were successfully linked to theincident records of LTCI certiﬁcation. Those participants who
answered the 25 questions of the KCL completely were
included in the study, and 15 681 participants who did notcomplete the questionnaire were excluded.
The analytical sample for this study comprised 67 398 participants (32 314 men and 35 084 women).
Ethical approval for the study was obtained from the National
Center for Geriatrics and Gerontology (application number: 1274–
2, approval date: December 18, 2020), Chiba University (application number: 3442, approval date: December 22, 2020), and theJapan Agency for Gerontological Evaluation Study (application
number: 2019–01, approval date: November 26, 2020).

2|

Dependent variable
The dependent variable was the incidence of functional
disability.7–9,14–16 and information was collected from those eligible for LTCI beneﬁts who were identiﬁed as having functional disability. Eligibility determination for LTCI was basedon nationally standardized procedures, including physician
evaluation of physical and cognitive functions.17 In addition,
veriﬁcation of certiﬁcation status during an average of 3.1 years
of follow-up (from 2016 to 2019) was performed by linking
cohort participants to records in the national LTCI database.

Independent variables
Table 2 lists the nine independent variables used in the study.
The KCL comprises 25 questions in seven domains, namely theInstrumental Activities of Daily Living (IADL) domain, physicaldomain, nutrition domain, eating domain, houseboundness
domain, memory domain, and mood domain. Each question
statement is listed in Table 1. Based on the scores of the original
KCL,5 a total of nine indicators, which have been validated to predict the incidence of functional disability,7,9,14–16 were evaluatedusing the modiﬁed KCL in accordance with the frailty,9,18 risk
assessment scale,7 and seven domains from the MHLW.4,5,15
Frailty, as assessed by the KCL, was related to the Cardiovascular Health Study criteria of Fried et al. (2001), a common measure of frailty.19 From a total KCL score of 25 points, 0–3 points
was deﬁned as robust; 4–7 points as pre-frail; and 8 points ormore as frailty.9,18 The sensitivity and speciﬁcity for frailty wasreported to be 89.5% and 80.7%, respectively and for pre-frailty
to be 70.3% and 78.3%.18
A risk assessment scale was calculated by extracting 10 important items from the KCL according to the criteria of Tsuji et al.
and adding points for each question, sex, and age (range: 0–48
points). Additionally, a cutoff of 16/17 points was used.7
The seven domains, based on the original KCL presented by
the MHLW consist of the following questions: (i) multi-domain
were nos. 1–20, (ii) physical domain were nos. 6–10, (iii) nutrition
domain were nos. 11 and 12, (iv) eating domain were nos. 13–15,(v) houseboundness domain were nos. 16–17, (vi) memory
domain were nos. 18–20, and (vii) mood domain were nos. 21–25.
The at-risk categories are scored based on number of difﬁculties
in each domain as follows: (i) ≥10 (multi-domain), (ii) ≥3 (physicaldomain), (iii) both of two (nutrition domain), (iv) ≥2 (eating
domain), (v) if no. 16 applies (houseboundness domain), (vi) ≥1(memory domain), and (vii) ≥2 (mood domain).
The modiﬁed KCL included three options within questions 1–
3 and 6–8. The three answer options were as follows: (i) I can anddo it, (ii) I can, but don’t do it, and (iii) I cannot do it.11 The “I
can, but don’t do it” item were conducted both when classiﬁed as
applicable and non-applicable to functional decline. When “I can,but don’t do it” is classiﬁed as non-applicable, the focus is on
functional ability (can/cannot), and when it is classiﬁed as applicable, the focus is on performing state (do/do not).

Statistical analysis
The Cox proportional hazards model was used to estimate hazard
ratios (HRs) and construct 95% conﬁdence intervals (CIs) whennine indicators were applicable, in comparison with those thatwere not applicable. In addition to the crude model, the analysis
further adjusted for age and sex.
We calculated Harrell’s C statistics (C-index) to clarify whether
predictive discrimination differs by using two different© 2022 The Authors. Geriatrics & Gerontology International
published by John Wiley & Sons Australia, Ltd on behalf of Japan Geriatrics Society.

Predictive validity of a modiﬁed KCL
Table 1 Distribution of participants’ responses at baseline and the cumulative incidence of functional disability during the follow-up
periodNo.

n = 67 398

Proportion (%)

Cumulative incidenceHR†

95% CI

P-valueSex
Male
32 314
47.9
9.0
1.00
Female35 084
52.1
9.5
1.08
1.02–1.13
Age (years)
65–69
21 519
31.9
1.7
1.00
70–74
18 976
28.2
5.0
3.02
2.68–3.41
75–79
15 170
22.5
10.8
6.83
6.09–7.65
80–84
8083
12.0
22.7
15.65
13.98–17.52
85+
3650
5.4
39.9
32.48
28.94–36.46
1 Do you go out by bus or train by yourself?‡
I cannot
1832
2.7
43.5
2.94
2.71–3.19
I do not
7643
11.3
23.2
2.14
2.02–2.27
2 Do you go shopping to buy daily necessities by yourself?
I cannot
1069
1.6
45.7
3.36
3.06–3.70
I do not
9717
14.4
16.8
1.76
1.66–1.86
3 Do you manage your own deposits and savings at the bank?‡
I cannot
1694
2.5
27.4
2.31
2.10–2.55
I do not
10 653
15.8
14.6
1.61
1.52–1.71
4 Do you sometimes visit your friends?
No
25 094
37.2
12.1
1.59
1.51–1.68
5 Do your family or friends turn to you for advice?
No
12 793
19.0
14.8
1.72
1.62–1.81
6 Do you normally climb stairs without using a handrail or wall for support?‡
I cannot
6660
9.9
29.1
2.64
2.49–2.80
I do not24 968
37.0
15.5
1.95
1.85–2.05
7 Do you normally stand up from a chair without any aids?‡TF1
I cannot
3711
5.5
31.9
2.63
2.46–2.81
I do not13 005
19.3
18.4
1.91
1.81–2.01
8 Do you normally walk continuously for 15 min?‡I cannot
1812
2.7
35.5
2.72
2.51–2.96
I do not
12 282
18.2
15.8
1.88
1.78–1.99
9 Have you experienced a fall in the past year?
Yes
15 314
22.7
14.5
1.54
1.46–1.62
10 Do you have a fear of falling while walking?
Yes
25 756
38.2
14.9
1.89
1.79–1.99
11 Have you lost 2 kg or more in the past 6 months?
Yes
8463
12.6
14.7
1.67
1.57–1.78
12 Height: cm, Weight: kg, BMI: kg/m2 If BMI is less than 18.5, this item is scored<18.5 kg/m2
4654
6.9
15.9
1.59
1.47–1.71
13 Do you have any difﬁculties eating tough foods compared to 6 months ago?
Yes
18 000
26.7
13.1
1.34
1.27–1.41
14 Have you choked on your tea or soup recently?
Yes
11 796
17.5
12.8
1.28
1.21–1.36
15 Do you often experience having a dry mouth?
Yes
13 433
19.9
13.9
1.47
1.39–1.55
16 Do you go out at least once a week?
<1 day/week
2157
3.2
27.8
2.26
2.08–2.47
17 Do you go out less frequently compared to last year?
Yes
9664
14.3
20.0
2.07
1.96–2.19
18 Do your family or your friends point out your memory loss? e.g., “You ask the same question over and over again.”
Yes
8753
13.0
15.5
1.63
1.53–1.73
19 Do you make a call by looking up phone numbers?
No
3394
5.0
20.6
2.15
1.99–2.33
20 Do you ﬁnd yourself not knowing today’s date?
Yes
15 402
22.9
13.6
1.47
1.40–1.55
21 In the last 2 weeks have you felt a lack of fulﬁllment in your daily life?
Yes
8112
12.0
16.3
1.82
1.71–1.93

0.003<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001(Continues)© 2022 The Authors. Geriatrics & Gerontology International
published by John Wiley & Sons Australia, Ltd on behalf of Japan Geriatrics Society.

|3

R Watanabe et al.
Table 1 Continued
n = 67 398

No.

Proportion (%)

Cumulative incidence

22 In the last 2 weeks have you felt a lack of joy when doing the things you used to enjoy?
Yes
6010
8.9
18.7
23 In the last 2 weeks have you felt difﬁculty in doing what you could do easily before?
Yes
13 12719.5
17.9
24 In the last 2 weeks have you felt helpless?
Yes
11 40516.9
16.9
25 In the last 2 weeks have you felt tired without a reason?
Yes
13 801
20.5
15.9

HR†

95% CI

P-value

1.94

1.82–2.07<0.001

1.91

1.82–2.02<0.001

1.71

1.62–1.81<0.001

1.75

1.66–1.84<0.001

Frailty: of the total score of nos. 1–25: 0–3, robust; 4–7, pre-frailty; 8 or more, frailty. Risk assessment scale: risk applicable for 17 points or more of
the 12 items for sex, age, nos. 1–3, nos. 6–10, no. 12, and no. 17. Multi-domain: risk applicable for 10 or more of the 20 items from no. 1 to no. 20.
Physical domain: risk applicable for 3 or more of the 5 items from no. 6 to no. 10. Nutrition domain: risk applicable for the 2 items from no. 11
and no. 12. Eating domain: risk applicable for 2 or more of the 3 items from no. 13 to no. 15. Houseboundness domain: risk applicable for no. 16of the 2 items from no. 16 and no. 17. Memory domain: risk applicable for 1 or more of the 3 items from no. 18 to no. 20. Mood domain: risk
applicable for 2 or more of the 5 items from no. 21 to no. 25.
†

Adjusted sex and age.

‡

Because there are three options, two methods (can/cannot, do/do not) are shown.

95% CI, 95% conﬁdence interval; BMI, body mass index; HR, hazard ratio.

classiﬁcation methods: functional ability and performing state.
The C-index estimates the probability of agreement between
predicted and observed responses. A value of 0.5 indicates thatpredictive discrimination is not possible, while a value of 1.0 indicates that participants with different outcomes are completely separated.20 The C-index is similar to the area under the curve(AUC), but it is a measure of discriminability that considers the
censoring nature of the data.20 In addition, statistical tests21 wereused to determine if the estimates of the C-index are different
when the three options are classiﬁed as functional ability or performing state.
Although all participants were ineligible for LTCI certiﬁcation
at baseline, some of those who responded to the self-administeredquestionnaire who needed assistance with daily living and those
who did not respond. To conﬁrm the robustness of the results,
we performed a sensitivity analysis excluding those who reported
needing daily living assistance or those who did not respond. In
addition, we conducted follow-up after periods of up to 1 and2 years to compare with previous studies. Furthermore, local governments often judge unanswered questions as applicable.22
Therefore, as a sensitivity analysis, the participants who did not
answer the KCL completely were included in the analysis, and theunanswered questions were considered as applicable.
All statistical analyses were conducted using Stata/MP 17.0
(Stata Corp, College Station, TX, USA), with P < 0.05 indicating
statistical signiﬁcance.

Results
The mean age (standard deviation: SD) was 73.6 (6.0) years. During a mean follow-up period of 3.1 years, the incidence of functional disability in 6232 participants was 9.2%. Table 1 lists theprevalence of each applicable question, the impairment rate, andthe incidence of functional disability for the 25 modiﬁed KCL
items. The incidence of functional disability was signiﬁcantly
higher for all questions.
Table 2 shows the results of examining the applicability andincidence of functional disability for each of the nine indicators.
The adjusted HRs for sex and age were calculated for each of thenine indicators, and the HR ranged from 1.50 to 3.82, indicating

4|

that all indicators were signiﬁcantly associated with the incidenceof functional disability.
Table 3 shows the C-index of the relationship between theincidence of functional disability and the total score of the nine
indicators. The C-index was 0.54–0.81. Consequently, the Cindex was signiﬁcantly higher in three out of four indicatiors,
except for the risk assessment scale indicators, when classiﬁed by
performing state compared with when classiﬁed by functional
ability.
Table 4 shows the sensitivity, speciﬁcity, and positive predictive
values of each indicator for the incidence of functional ability.
Sensitivity ranged from 3.9% in the nutritional domain to 79.7%
in the risk assessment scale. Speciﬁcity ranged from 69.0% in thememory domain to 98.8% in the nutrition domain. Positive predictive values ranged from 13.1% in the memory domain to
47.4% in the multi-domain.
The sensitivity analysis excludes those who responded thatthey required assistance at baseline and those who did not
respond. Compared with the main results, the C-index tended todecrease, but the trend of the results remained the same (Table
S1). The results of the C-index with a maximum follow-up periodof 1 and 2 years were also given (the larger the C-index, the shorterthe follow-up period; Table S2). Furthermore, a sensitivity analysis
was performed, which included non-respondents, on the items of
the KCL, and non-respondents’ items were treated as applicable.
The results show that the C-index improved for all indicators
except the risk assessment scale and the nutrition domain; sensitivity improved for all indicators; and speciﬁcity worsened for all indicators; however, the overall trend was the same.

Discussion
We examined the predictive validity of the original KCL’s criteria
for the incidence of functional disability by dividing it into functional ability and performing state in the modiﬁed KCL. The
results suggested that the two classiﬁcations using the modiﬁed
KCL had the predictive validity of incidence of functional disability. Regarding the handling of the three options, the predictive discrimination was higher when the evaluation was focused on
performing state rather than on functional ability.

© 2022 The Authors. Geriatrics & Gerontology International
published by John Wiley & Sons Australia, Ltd on behalf of Japan Geriatrics Society.

Predictive validity of a modiﬁed KCL
Table 2 Incidence of functional disability in nine indicators (Cox proportional hazard ratio)
Total numberof peoplen = 67 398

Proportion(%)

Cumulative
incidence

Crude
HR

95% CI

Model 1
P-value

Evaluating “functional ability” (including indicators that do not have a three-option question)
Frailty
Robust40 171
59.6
4.7
1.00
Pre-frailty
19 10828.4
11.2
2.49 2.34–2.65<0.001
Frailty
8119
12.0
26.9
6.83 6.42–7.27<0.001
Risk assessment scale≤16
49 424
73.3
3.6
1.00
≥17
17 97426.7
24.9
8.15 7.71–8.61<0.001
Multi-domainNot
65 930
97.8
8.4
1.00
applicable
Applicable
1468
2.2
47.4
8.32 7.68–9.00<0.001
Physical domainNot
62 948
93.4
7.6
1.00
applicable
Applicable
4450
6.6
32.9
5.34 5.03–5.66<0.001
Nutrition domain
Not
66 401
98.5
9.0
1.00
applicable
Applicable
997
1.5
24.7
3.20 2.81–3.63<0.001
Eating domainNot
56 836
84.3
8.1
1.00
applicable
Applicable
10 56215.7
15.5
2.04 1.93–2.16<0.001
Houseboundness domain
Not
65 241
96.8
8.6
1.00
applicable
Applicable
2157
3.2
27.8
3.85 3.54–4.19<0.001
Memory domainNot
45 605
67.7
7.4
1.00
applicable
Applicable
21 79332.3
13.1
1.85 1.76–1.94<0.001
Mood domain
Not
53 666
79.6
7.1
1.00
applicable
Applicable
13 73220.4
17.6
2.69 2.55–2.83<0.001
Evaluating “performing state”
Frailty
Robust32 147
47.7
4.1
1.00
Pre-frailty
22 94634.0
9.0
2.29 2.14–2.45<0.001
Frailty
12 305
18.3
23.2
6.62 6.20–7.06<0.001
Risk assessment scale≤16
43 586
64.7
2.9
1.00
≥17
23 81235.3
20.9
8.16 7.67–8.68<0.001
Multi-domain
Not
64 347
95.5
7.9
1.00
applicable
Applicable
3051
4.5
37.9
6.34 5.94–6.75<0.001
Physical domain
Not
53 962
80.1
6.3
1.00
applicable
Applicable
13 43619.9
20.9
3.65 3.47–3.84<0.001

HR

95% CI

P-value

1.00
1.89
3.82

1.77–2.01
3.58–4.08<0.001<0.001

1.00
3.65

3.33–4.00<0.001

3.35–3.96<0.001

2.65–3.00<0.001

2.01–2.60<0.001

1.42–1.59<0.001

2.08–2.47<0.001

1.48–1.64<0.001

1.97

1.87–2.07<0.001

1.00
1.79
3.77

1.67–1.92
3.53–4.04<0.001<0.001

1.00
3.27

2.98–3.59<0.001

2.97–3.40<0.001

2.21–2.46<0.001

1.00
3.64
1.00
2.82
1.00
2.29
1.00
1.50
1.00
2.26
1.00
1.56
1.00

1.00
3.18
1.00
2.33

Model 1, adjusted for sex and age.
95% CI, 95% conﬁdence interval; HR, hazard ratio.

© 2022 The Authors. Geriatrics & Gerontology International
published by John Wiley & Sons Australia, Ltd on behalf of Japan Geriatrics Society.

|5

R Watanabe et al.
Table 3 Comparison between functional ability and performing state of the C-index for each indicator (n = 67 398)
Evaluating “functional ability” (including indicators that do nothave three-option questions)Frailty
Risk assessment scaleMulti-domain
Physical domain
Nutrition domain
Eating domain
Houseboundness domain
Memory domain
Mood domain

Evaluating “performing
state”

C-index

95% CI

C-index

95% CI

0.717
0.813
0.712
0.686
0.557
0.586
0.535
0.586
0.633

0.710–0.724
0.808–0.819
0.706–0.719
0.679–0.692
0.551–0.563
0.579–0.593
0.532–0.539
0.579–0.593
0.627–0.640

0.722
0.813
0.718
0.694

0.715–0.728
0.808–0.818
0.711–0.724
0.688–0.701

P-value*<0.0010.590<0.001<0.001*Statistical analysis was performed to compare the C-index of functional ability and performing state.
95% CI, 95% conﬁdence interval; C-index, Harrell’s C statistics.

Table 4 Sensitivity, speciﬁcity, and positive predictive value for the incidence of functional disability in each indicator (n = 67 398)
Evaluating “functional ability” (including indicatorsthat do not have three-option questions)Frailty
Risk assessment scaleMulti-domain
Physical domain
Nutrition domain
Eating domain
Houseboundness
domainMemory domain
Mood domain

Sensitivity(%)

Speciﬁcity(%)

Positive predictive
value (%)

Sensitivity(%)

Speciﬁcity(%)

Positive predictive
value (%)

35.1
71.8
11.2
23.5
3.9
26.3
9.6

90.3
77.9
98.7
95.1
98.8
85.4
97.5

26.9
24.9
47.4
32.9
24.7
15.5
27.8

45.8
79.7
18.6
45.0

84.6
69.2
96.9
82.6

23.2
20.9
37.9
20.9

45.9
38.7

69.0
81.5

13.1
17.6

The results of this study support those of previous studies thatpredicted incidence of functional disability based on the original
KCL.7,9,14–16 The sensitivity analysis results, which excluded those
who required care or who did not respond at baseline for robustness, also indicated the same trend. Therefore, we concluded thatthe predictive validity of incidence of functional disability was conﬁrmed in the modiﬁed KCL.
The AUC, which indicates the predictive discrimination ofincidence of functional disability assessed by the indicator
for frailty, was 0.76 (95% CI: 0.74–0.79)9 in a previous study. The
C-index of 0.72 (0.71–0.72), which indicates predictive discrimination, was lower in the present study compared with a previous
study. Similarly, the AUC was reported for seven domains of the
MHLW ranged from 0.62 (95% CI: 0.59–0.65) to 0.83 (0.81–0.85)
and sensitivity from 13.5% to 71.4%.15 While the present study
indicated the C-index ranged from 0.54 (0.53–0.54) to 0.71 (0.71–0.72) and sensitivity from 3.9% to 45.9%, all values are lower inthe present study. However, speciﬁcity and positive predictive
value were higher in this study than in previous studies. Therefore, false negatives are more likely to appear and false positives
are less likely in the current study than in previous studies. There
are two reasons for this difference in predictive discrimination,
sensitivity, speciﬁcity, and positive predictive value. First, thefollow-up period of this study was longer, averaging 3.1 years,
compared with 1 year in previous studies.15 Tables S2 and S3

6|

Evaluating “performing state”

show that values of the C-index and sensitivity increased when thefollow-up period was shortened. In contrast, speciﬁcity and positive predictive value decreased when the follow-up period was
shortened, approaching the values of a previous study.15 Second,the difference in the target population of the analysis inﬂuences
the level of predictive discrimination. In the current study, only
those who responded to all 25 questions of the modiﬁed KCL
were included in the analysis; however, previous studies included
those who did not respond to all questions in the analysis andtreated the unanswered questions as corresponding to functional
decline.15 Other studies have included all respondents to the original KCL but used telephone or face-to-face contact to obtain
answers for previously unanswered questions.9 Furthermore, previous studies have indicated that the risk of death is higher for
those who do not answer the questions.23 In sensitivity analyses inwhich unanswered questions were considered applicable, the Cindex and sensitivity scores improved and the speciﬁcity scores
decreased, approaching those of previous studies.
In this study, we conducted two forms of assessments, one forfunctional ability and one for performing state. The C-index was
higher when the focus was on performing state than when it wason functional ability, except for the risk assessment scale. Functional ability (can/cannot) may differ from performance status(do/do not) of activities of daily living, while performing state asks
about actual performance status, which may be directly reﬂected in© 2022 The Authors. Geriatrics & Gerontology International
published by John Wiley & Sons Australia, Ltd on behalf of Japan Geriatrics Society.

Predictive validity of a modiﬁed KCL
physical activity. Speciﬁcally, no. 8, “Do you normally walk continuously for 15 min?” asks for physical activity. Furthermore, nos. 1–3
are IADL items, and IADL-independent persons are known to havehigh levels of physical activity.24 Studies examining the relationshipbetween physical activity and disability25 and all-cause mortality26
have reported a dose–response relationship, with higher levels ofphysical activity associated with lower levels of disability and allcause mortality. One study compared functional ability and performing state in some of the questions of the KCL amongcommunity-dwelling older adults.27 It was reported that performing
state scores were lower than scores for functional ability; the resultsof this study support those of previous studies. The International
Classiﬁcation of Functioning, Disability, and Health proposed by
the WHO28 explains that functional ability is evaluated under astandardized evaluation setting, while performing state is evaluatedin various different environments, including with respect to theindividual’s socioeconomic status. Predictive discrimination may
have been higher in the performing state, reﬂecting differences inindividual environment and physical activity.
The fact that only the risk assessment scale failed to present a
difference in the C-index by the classiﬁcation method is partly
explained by its inclusion of sex and age. Actually, when the Cindex of the risk assessment scale excluding sex and age was calculated, it was also higher in the performing state; that is, 0.72 forperforming state and 0.71 for functional ability (P = 0.016).
However, the predictive validity of all nine indicators for incidence of functional disability was conﬁrmed for the functional
ability and performing state classiﬁcation methods. Therefore, it isrecommended that the classiﬁcation method should be based on
purpose, such as classiﬁcation by functional ability when identifying high-risk older people, or classiﬁcation by performing state
when extracting a wide range of high-risk older people.
The strength of this study derives from its conﬁrmation of thepredictive validity of incidence of functional disability using the modiﬁed KCL used in epidemiological investigation among 67 398 older
people living in 18 municipalities. This indicator is used by municipalities to assess the risk of developing LTCI and to identify local
issues.11 It enables municipalities to understand the risk of LTCI withexisting data. However, the current study also includes the following
limitations. First, it is limited to participants who answered all 25 questions of the KCL, and thus there is a selection bias towards a relatively
healthy population. However, a similar trend was conﬁrmed in thesensitivity analysis of the questions in the KCL left unanswered in theanalysis. Second, the incidence of functional disability in this study
was deﬁned by LTCI, which is a voluntary reporting system, and not
all people with reduced ADL apply for LTCI.
In conclusion, the predictive validity of the modiﬁed KCL for
the incidence of functional disability was conﬁrmed. However,some indicators might show false negatives with high speciﬁcity
and low sensitivity. Although predictive discrimination was slightly
higher for the performing state than for functional ability, the predictive validity of the modiﬁed KCL was conﬁrmed for both.
Therefore, it is essential to choose the classiﬁcation appropriately
based on the purpose for which the modiﬁed KCL is being used.

Acknowledgements
This study used data from JAGES (the Japan Gerontological Evaluation Study). This study was supported by grants from the JSPS
(Japan Society for the Promotion of Science; KAKENHI grant
JP15H01972, JP20H03954), Health Labour Sciences (research
grant H28-Choju-Ippan-002), the Japan Agency for Medical
ResearchandDevelopment(AMED)(JP18dk0110027,

JP18ls0110002, JP18le0110009, JP20dk0110034, JP21lk0310073,
JP21dk0110037), and the Open Innovation Platform with Enterprises, Research Institute and Academia (OPERA, JPMJOP1831)
from the Japan Science and Technology (JST). It also received
grants from the Innovative Research Program on Suicide Countermeasures (1–4), the Sasakawa Sports Foundation, the Japan
Health Promotion & Fitness Foundation, the Chiba Foundationfor Health Promotion & Disease Prevention, the 8020 Research
Grant for ﬁscal 2019 from the 8020 Promotion Foundation(adopted number: 19-2-06), and grants from the Meiji Yasuda
Life Foundation of Health and Welfare and the Research Fundingfor Longevity Sciences from National Center for Geriatrics andGerontology (29-42, 30-22, 20-19, 21-20, 21-19).

Disclosure statement
The authors declare no conﬂict of interest.

Data availability statement
Data are from the JAGES study. All enquiries are to be addressedat the data management committee via e-mail: dataadmin.
ml@jages.net. All JAGES datasets have ethical or legal restrictions
for public deposition due to inclusion of sensitive informationfrom the human participants.

References
1 World Health Organization. Decade of healthy ageing: Plan of Action
2020 [Cited 28 Dec 2021]. Available from URL: https://cdn.who.int/
media/docs/default-source/decade-of-healthy-ageing/ﬁnal-decadeproposal/decade-proposal-ﬁnal-apr2020-en.pdf?sfvrsn=b4b75ebc_25&
download=true
2 World Health Organization. World Report on Ageing and Health, 2015
[Cited 28 Dec 2021]. Available from URL: https://www.who.int/
publications/i/item/9789241565042
3 Arai H, Ouchi Y, Toba K et al. Japan as the front-runner of super-agedsocieties: perspectives from medicine and medical care in Japan. Geriatr
Gerontol Int 2015; 15: 673–687.
4 Ministry of Health, Labour and Welfare. Preventing Long-Term Care
Manual, Revised edition; 2012 (In Japanese). [Cited 28 Dec 2021].
Available from URL: https://www.mhlw.go.jp/topics/2009/05/dl/tp05011_1.pdf
5 Ministry of Health, Labour and Welfare. Utilize of the Kihon Checklist;
2005 (In Japanese). [Cited 28 Dec 2021]. Available from URL: https://www.wam.go.jp/wamappl/bb05Kaig.nsf/0/
842faf619ff7dbee492570dc0023a07f/$FILE/siryou2.pdf
6 Sewo Sampaio PY, Sampaio RA, Yamada M, Arai H. Systematic reviewof the Kihon checklist: is it a reliable assessment of frailty? Geriatr
Gerontol Int 2016; 16: 893–902.
7 Tsuji T, Kondo K, Kondo N, Aida J, Takagi D. Development of a risk
assessment scale predicting incident functional disability among older
people: Japan Gerontological evaluation study. Geriatr Gerontol Int 2018;
18: 1433–1438.
8 Tsuji T, Takagi D, Kondo N, Kondo K. Development of risk assessment scales for needed support/long-term care certiﬁcation: a longitudinal study using the Kihon checklist and medical assessment data. Nihon
Koshu Eisei Zasshi 2017; 64: 246–257 (In Japanese).
9 Satake S, Shimokata H, Senda K, Kondo I, Toba K. Validity of Total
Kihon checklist score for predicting the incidence of 3-year dependency
and mortality in a community-dwelling older population. J Am Med Dir
Assoc 2017; 18: e551–552.e556.
10 Ministry of Health, Labour and Welfare. Brieﬁng on Various Surveys,
for the Formulation of Long-Term Care Insurance Business Plans;
2016 (In Japanese). [Cited 28 Dec 2021]. Available from URL: https://www.mhlw.go.jp/ﬁle/05-Shingikai-12301000-Roukenkyoku-Soumuka/
0000142077.pdf
11 Ministry of Health, Labour and Welfare. Instructions of Conducting the
Public Survey of Long-Term Care Prevention and Needs in Spheres of Daily Life(the Version of 23 October, 2019); 2019 (In Japanese). [Cited 28 Dec 2021].

© 2022 The Authors. Geriatrics & Gerontology International
published by John Wiley & Sons Australia, Ltd on behalf of Japan Geriatrics Society.

|7

R Watanabe et al.
Availablefrom:https://www.mhlw.go.jp/content/12301000/
000560423.pdf
12 Kondo K. Progress in aging epidemiology in Japan: the JAGES project.
J Epidemiol 2016; 26: 331–336.
13 Kondo K, Rosenberg M. World Health Organization. Advancing universal
health coverage through knowledge translation for healthy ageing: lessons learnt
from the Japan gerontological evaluation study. Geneva: World Health Organization, 2018.
14 Kamegaya T, Yamaguchi H, Hayashi K. Evaluation by the basic checklist and the risk of 3 years incident long-term care insurance certiﬁcation. J Gen Fam Med 2017; 18: 230–236.
15 Tomata Y, Hozowa A, Ohomori-Matsuda K et al. Validation of the
Kihon checklist for predicting the risk of 1-year incident long-term careinsurance certiﬁcation: the Ohsaki cohort 2006 study. Nihon Koshu Eisei
Zasshi 2011; 58: 3–13 (In Japanese).
16 Hamazaki Y, Morikawa Y, Nakamura K, Morimoto S, Nakagawa H.
Relationship between participation in a secondary screening test for thefrail elderly and new onset of the need for long-term care among theelderly in a rural town. Nihon Koshu Eisei Zasshi 2012; 59: 801–809(In Japanese).
17 Tsutsui T, Muramatsu N. Japan’s universal long-term care system
reform of 2005: containing costs and realizing a vision. J Am Geriatr Soc
2007; 55: 1458–1463.
18 Satake S, Senda K, Hong YJ et al. Validity of the Kihon checklist forassessing frailty status. Geriatr Gerontol Int 2016; 16: 709–715.
19 Fried LP, Tangen CM, Walston J et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001; 56: M146–
M156.
20 Harrell FE Jr, Lee KL, Mark DB. Multivariable prognostic models:issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 1996; 15:
361–387.
21 Newson RB. Comparing the predictive powers of survival models
using Harrell’s C or Somers’ D. The Stata Journal 2010; 10:339–358.
22 Ministry of Health, Labour and Welfare. Instructions of Community General
Support Center; 2007 (In Japanese). [Cited 25 Mar 2021]. Available from:https://www.mhlw.go.jp/topics/2007/03/tp0313-1.html
23 Tolonen H, Laatikainen T, Helakorpi S, Talala K, Martelin T,
Prättälä R. Marital status, educational level and household income
explain part of the excess mortality of survey non-respondents. Eur J
Epidemiol 2010; 25: 69–76.
24 Crevenna R, Dorner TE. Association between fulﬁlling the recommendations for health-enhancing physical activity with (instrumental) activities of daily living in older Austrians. Wien Klin Wochenschr 2019; 131:
265–272.
25 Chen T, Honda T, Chen S, Narazaki K, Kumagai S. Dose-response
association between accelerometer-assessed physical activity and8|incidence of functional disability in older Japanese adults: a 6-year prospective study. J Gerontol A Biol Sci Med Sci 2020; 75: 1763–1770.
26 Ekelund U, Tarp J, Steene-Johannessen J et al. Dose-response associations between accelerometry measured physical activity and sedentary
time and all cause mortality: systematic review and harmonised metaanalysis. BMJ 2019; 366: l4570.
27 Suzuki N, Makigami K, Goto A, Yokokawa H, Yasumura S. Comparison of ability-based and performance-based IADL evaluation ofcommunity-dwelling elderly using the Kihon checklist and TMIG index
of competence. Nihon Ronen Igakkai Zasshi 2007; 44: 619–626.
28 World Health Organization. The International Classiﬁcation of Functioning,
Disability and Health (ICF). 2001 [Cited 25 Mar 2021]. Available from:https://www.who.int/classiﬁcations/international-classiﬁcation-of-functioningdisability-and-healthSupporting Information
Additional supporting information may be found in the online
version of this article at the publisher’s website:
Table S1. Comparison between functional ability and performing
state of the C-index for each indicator, and sensitivity analysis
excluding those with potential for care at baseline.
Table S2. Comparison between functional ability and performing
state of the C-index for each indicator and sensitivity analysis fordifferent follow-up periods.
Table S3. Sensitivity speciﬁcity, positive predictive value for theincidence of functional disability in each indicator and sensitivity
analysis for different follow-up periods.

How to cite this article: Watanabe R, Tsuji T, Ide K,
et al. Predictive validity of the modiﬁed Kihon Checklist for
the incidence of functional disability among older people:
A 3-year cohort study from the JAGES. Geriatr. Gerontol.
Int. 2022;1–8. https://doi.org/10.1111/ggi.14439© 2022 The Authors. Geriatrics & Gerontology International
published by John Wiley & Sons Australia, Ltd on behalf of Japan Geriatrics Society.