Association between oral, social, and physical frailty in community-dwelling older adults

Sanae Hironakaa,b, Yoshihiro Kugimiyac, Yutaka Watanabeb,d, Keiko Motokawab, Hirohiko
Hiranob,e, Hisashi Kawaif, Takeshi Keraf,g, Motonaga Kojimah, Yoshinori Fujiwarai, Kazushige
Iharaj, Hunkyung Kimb, Shuichi Obuchif, Yasuaki KakinokiaaDepartment of Special Needs and Geriatric Dentistry, Kyushu Dental University, Kitakyushu,

Japan.
b

Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute ofGerontology, Tokyo, Japan.
c

Department of Removable Prosthodontics and Gerodontology, Tokyo Dental College, Tokyo, Japand

Gerodontology, Department of Oral Health Science, Faculty of Dental Medicine, Hokkaido

University, Sapporo, Japan.
efDepartment of Oral Surgery and Dentistry, Tokyo Metropolitan Geriatric Hospital, Tokyo, Japan.

Research Team for Human Care, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan.

g

Department of Physical Therapy, Takasaki University of Health and Welfare, Takasaki, Japan.

hDepartment of Physical Therapy, University of Tokyo Health Sciences, Tokyo, Japan.

i

Research Team for Social Participation and Community Health, Tokyo Metropolitan Institute ofGerontology, Tokyo, Japan.
jDepartment of Social Medicine, Hirosaki University Graduate School of Medicine, Hirosaki City,

Aomori, Japan.

Corresponding author:
Yutaka Watanabe DDS, PhD
Associate Professor
Gerodontology, Department of Oral Health Science, Faculty of Dental Medicine,
Hokkaido University
Nishi-7, Kita-13, Kita-ku, Sapporo, Hokkaido 060-8586, Japan.
Phone & Fax: 81-11-706-4582
Email: ywata■den.hokudai.ac.jp
Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute ofGerontology
35-2 Sakae-cho, Itabashi-ku, Tokyo 173-0015, Japan.

1

Abstract

2

Objectives Oral frailty (OF) has been shown to be a predictor of disability. Therefore, it is important to be3

able to identify factors associated with OF in order to prevent long-term dependence. The purpose of this4

study was to clarify the relationships between OF, social frailty (SF), and physical frailty (PF) in

5community-dwelling older adults, with the overarching aim of informing the future development of

6

effective measures to prevent frailty.

7

Methods Oral, physical, and social function, nutritional and psychological status, and medical history were8

examined in 682 community-dwelling individuals (267 men, 415 women) aged ≥ 65 years. Ordinal logistic

9

regression analysis with SF and PF as independent variables was performed with pass analysis to10

determine the relationship between the different types of frailty.

11

Results Logistic regression analysis revealed significant associations between OF and decline in social

12function, physical function, and nutritional status, and an increase in the number of medications used. Path13

analysis showed that SF was directly related to OF and that OF and SF were directly related to PF.

14

Conclusions These findings suggest that a decline in social function may directly influence a decline in

15

oral and physical function. The results of this study provide initial evidence, that may guide the future

16

development of measures that aim to prevent and manage OF.

17

Key words: oral frailty, social frailty, physical frailty, path analysis, oral function, polypharmacy

18

Abbreviations list

19

GFI, goodness of fit index

20

IADL, instrumental activities of daily living

21

JST-IC, Japan Science and Technology Agency Index of Competence

22

LTCI, Japanese public long-term care insurance system

23

MMSE, Mini-Mental State Examination

24

MNA-SF, Mini Nutritional Assessment-Short Form

25

NFI, normed fit index
11

ODK, oral diadochokinesis

2OF, oral frailty

3PF, physical frailty

4

RMSEA, root mean square error of approximation

5SF, social frailty

6

2

1
2

1. Introduction

3
4

expectancy in the super-aged population of Japan. Frailty is defined as “a clinical state in which there is an

5

by taking appropriate measures” (Morley et al., 2013). Risk factors for frailty include chronic disease6(Danon-Hersch, Rodondi, Spagnoli, & Santos-Eggimann, 2012; Denfeld et al., 2017), poor nutritional status

7
8(Soysal et al., 2019), and polypharmacy (Saum et al., 2017). There is also evidence suggesting a relationship910al., 2018).

11(Nakagawa et al., 2017; Tsuga, Maruyama, Yoshikawa, Yoshida, & Akagawa, 2011). Minakuchi et al.

12(2018) suggested that a multidimensional approach is necessary to evaluate oral function, which includes

13
14
15

mastication, swallowing, and phonation. No recent studies have demonstrated that a combination of oral

16
17

oral health status. In their longitudinal study on community-dwelling older adults, they found that OF was a

18
19

Establishing management for OF appears to be important for the prevention of dependency. The relation

Frailty is an important consideration in the development of strategies that aim to optimize a healthy life
increase in an individual's risk of dependence and/or mortality when exposed to a stressor that can be reduced

between frailty, number of teeth present, and oral function (Hakeem, Bernabé, & Sabbah, 2019; Tanaka etPrevious studies assessed oral function with only a single measure (e.g., tongue pressure or occlusal force)

functional impairments can predict a decline in general function and disability.
Tanaka et al. (2018) coined the term “oral frailty” (OF) to recognize the multidimensional nature of poor
predictor of physical frailty (PF), dependency, and mortality.
factor of OF requires clarification before obtaining the basic information needed to establish appropriate

20
21

management for OF. Moreover, there is an association between a decline in social function and decreases in22
23

Nagayoshi et al., 2017; Takeuchi, Aida, Kondo, & Osaka, 2013). Disability in social role functioning and24
25

living (IADL) (Fujiwara et al., 2003). This is of concern given that poor social relationships are recognized

26
27
28

term “social frailty” (SF) in a longitudinal study, that found a higher risk of disability in individuals with

29
30

(Tanaka et al., 2018) and SF (Makizako et al., 2015b) negatively impact health status, the relationship31
32

for frailty, which is a multifaceted concept. If the relationship between OF, SF, and PF, which is a predictor

33
34

We hypothesized that there would be associations between OF, SF, and PF. Therefore, in this study, we

35
36
37
38

subjective masticatory performance, number of teeth present, and tongue pressure (Mikami et al., 2019;intellectual activity were also identified as predictors of low performance in instrumental activities of daily
as a risk factor for mortality (Holt-Lunstad, Smith, & Layton, 2010). Makizako et al. (2015b) devised themultiple indicators of social decline (e.g., living alone and decreased frequency of going out).
Although two longitudinal studies in community-dwelling older adults have confirmed that both, OF
between OF and SF remains unclear. In the meantime, the effect seems to be limited in the alone measureof dependency, is clarified, more multifaceted and effective correspondence may be possible.
investigated the relationships between OF, SF, and PF in community-dwelling older adults using thedefinitions established for each type of frailty and a comprehensive range of variables, including nutritional
status, sex, and medical history.
2. Materials and Methods
3

1
2

2.1 Study Design34health checkups conducted annually by the Tokyo Metropolitan Institute of Gerontology (Tokyo, Japan) as

5from a total of 7,162 older adults (aged 65–84 years) residing in nine towns in the Itabashi ward of Tokyo6
7

in 2011. Invitations for health checkups were sent to 6,699 older people, excluding those who were residing

8
9

for health checkups were sent to 7,015 older adults, excluding those who had reached 65 years of age or did

10
11

invitations for health checkups were sent in 2013–2018 to new study participants, who had reached 65 years

12
13
14

to a total of 2,440 older adults, including 1,463 who had participated in previous health checkups (in 2011–15
16

system and those with cognitive impairment (as indicated by a Mini-Mental State Examination [MMSE]

17
18

questionnaire (Tanaka et al., 2018). We also excluded individuals with missing cognitive or oral function

19
20

standardized evaluation criteria) and the use of evaluation instruments. The study protocol was approved by

21
22

Approval No. 16 in 2018) and conducted in accordance with the Strengthening the Reporting of

23
24

This study had a cross-sectional design, and included participants’ data collected from comprehensive
a part of the Otasha Kenshin study initiated in 2011. The participants in these health checkups were selected

in long-term care institutions and those who had been participant in previous research. In 2012, invitations
not reside at the same address (according to the inhabitant registry) in the preceding fiscal year. Subsequentof age and to older adults who had participated in previous health checkups. In 2018, invitations were mailed2017) and 977 new study participants, who had reached 65 years of age.
We excluded individuals receiving long-term care via the Japanese public long-term care insurance (LTCI)
score ≤ 18) to ensure the reliability of the subjective assessments, which included a self-administeredassessment data. All study investigators received training, that included measurement methods (using
the Ethics Committee of the Tokyo Metropolitan Institute of Gerontology (Approval No. 48 in 2011;
Observational Studies in Epidemiology statement.
2.2 Measurements

25
26
27

2.2.1 Basic characteristics

28
29(JST-IC) score to assess the ability to perform IADL (Iwasa et al., 2018).

30
312.2.2 Nutritional status32
33

was calculated from height and weight using the standard formula. Limb muscle mass was measured by the34
35

index was calculated by dividing the sum of limb muscle mass by the square of height in meters (Murakami

36
37

on which a score of ≤ 11 is considered to indicate a risk of malnutrition (Soysal et al., 2019).

38

2.2.3 Physical function

Information on sex, age, years of education, smoking status, and alcohol consumption was collected using
a self-administered questionnaire. We used the Japan Science and Technology Agency Index of Competence

Any one of three registered dietitians evaluated the nutritional status of each participant. Body mass index
bioelectrical impedance method using an InBody 770 system (Biospace, Seoul, Korea). Skeletal muscle mass
et al., 2015). Nutritional status was assessed using the Mini Nutritional Assessment-Short Form (MNA-SF),4

1

Any one of four specialist researchers assessed physical function. Grip strength was measured using a2

Smedley-type hand dynamometer (Yagami, Nagoya, Japan) and gait speed by the 5-m walk test (Kera et3al., 2018). Researchers asked participants to stand and grip the hand dynamometer as tightly as possible4

using their preferred hand. Tests were carried out twice, and the higher value was selected. To evaluate5

participants’ gait, their usual walking speed was measured on a 5-m course, with 3-m acceleration and6

deceleration courses placed at each end of the courses. Researchers asked participants to walk at their usual

7

speed.

89
10
11

2.2.4 Cognitive psychological function

12
13

MMSE (Folstein, Folstein, & McHugh, 1975; Sakuma et al., 2017). MMSE scores ≥ 19 were classified into

14
15
16

cognitive function) (Kaufer et al., 2008; Sakuma et al., 2017). Following the method devised by Fujisawa et

17
18

you used to do? (last 2 weeks)" (yes); "Do you think it is too much trouble to do the things you used to do?

19
20

you feel tired without any specific reason? (last 2 weeks)" (yes). Participants who met two or more criteria

21
22
23
24

Any one of three nurses or two psychologists assessed cognitive function using the Japanese version of thethree groups (≤ 24, moderate cognitive impairment; ≤ 27, mild cognitive impairment; and ≥ 28, preservedal. (2005), the tendency for depression was investigated using a self-administered questionnaire containing
the following five items: "Is your life pretty full? (last 2 weeks)" (yes); "Do you still enjoy doing the things(last 2 weeks)" (yes); "Do you feel that you are a useful person who is needed by others?" (yes); and "Do
were considered to be depressed (Ihara et al., 2016).
2.2.5 Medical history and number of medications
Either of two nurses recorded the medical history and number of medications taken. Information was sought
about the following diseases, each of which has been associated with PF: hypertension (Danon-Hersch et al.,25262012), heart disease (Denfeld et al., 2017), diabetes mellitus (Danon-Hersch et al., 2012), hyperlipidemia

27
28
29

Leung, Kwok, & Woo, 2014), osteoarthritis (Castell et al., 2015), spinal stenosis (Yagi et al., 2018),30312013), and fracture after 60 years of age (Kojima, 2016). Participants were asked how many medications

32
33

polypharmacy (Saum et al., 2017).

34
35

2.2.6 Oral function

36

the number of teeth present, masticatory performance, tongue pressure, and oral diadochokinesis (ODK),(Ramsay et al., 2015), osteoporosis (Li et al., 2017), chronic obstructive pulmonary disease (Lee, Auyeung,malignant neoplasm (Calado et al., 2016), anemia (Danon-Hersch, Rodondi, Spagnoli, & Santos-Eggimann,2016), stroke (Calado, Ferriolli, Moriguti, Martinez, & Lima, 2016), chronic kidney disease (Walker et al.,they were taking (0, 1, 2, 3, 4, or ≥ 5). The use of five or more medications related to PF was defined as

Any one of four dentists or four dental hygienists assessed oral function. The parameters measured were5

12

which represents the dexterity of the tongue. The number of teeth present was defined as the number of

3
4

performance was assessed using color-changeable chewing gum (Masticatory Performance Evaluating Gum

5measured in three places using a color-difference meter (CR-20 Color Reader; Konica Minolta, Tokyo,

6

Japan), with the mean value defined as the masticatory performance (Kugimiya et al., 2020). Tongue

7
8

pressure was assessed using a JMS tongue pressure device (JMS Co., Ltd., Hiroshima, Japan). The tongue

9
10

voluntary muscular effort for approximately 7 seconds. Three measurements were recorded, and the mean

11

measurement device (Kenkokun Handy; Takei Scientific Instruments Co., Ltd., Niigata, Japan). The study

12

participants were asked to repeat each given syllable /ta/ sequentially as fast as possible for 5 seconds. The

13
14
15

number of pronunciations per second was recorded (Watanabe et al., 2017).

16
17

2.3.1 Oral frailty

18
19

defined as follows: number of teeth present (< 20); masticatory performance (men, < 14.2; women, < 10.8);

20
21

times/second). As a subjective evaluation, participants who responded “yes” to "Do you have any difficulties

22
23

and those who responded “yes” to "Have you choked on your tea or soup recently?" were considered to have

24
25

items, as previously described (Tanaka et al., 2018). Individuals who did not respond positively to any

26
27
28

categorized as having as oral prefrailty (preOF) and OF, respectively.

29
30

SF was evaluated as in the report by Makizako et al. (2015b). Cut-offs were set for each of the five items

erupted teeth in the oral cavity, excluding retained roots and teeth with severe periodontitis. Masticatory
Xylitol; Lotte Co., Ltd., Tokyo, Japan). The a* value for the gums after 1 minute of mastication waspressure probe was pinched between the tongue and palate, and tongue pressure was applied with maximal
value was defined as the tongue pressure (Tsuga et al., 2011). ODK was assessed using an oral functions

2.3 Definitions of frailty
Referencing the report by Tanaka et al. (2018), the cut-off values for the individual components were
tongue pressure (men, < 27.4 kPa; women, < 26.5 kPa); and ODK (men, < 5.2 times/second; women, < 5.4
eating tough foods compared to 6 months ago?" were considered to have decreased masticatory performance,
decreased swallowing function. OF was evaluated according to the responses to six objective and subjective
relevant items were regarded as robust. Those who responded positively to 1–2 items and ≥ 3 items were

2.3.2 Social frailty
as follows: “Do you go out less frequently compared with last year?” (yes), “Do you sometimes visit your31
32

friends?” (no), “Do you feel you are helpful to friends or family?” (no), “Do you live alone?” (yes), and “Do

33
34

robust. Those who had 1 item and ≥ 2 items were categorized as having social prefrailty (preSF) and SF,

35
36
37
38

you talk with someone every day?” (no). Individuals who did not have any relevant items were regarded as
respectively.
2.3.3 Physical frailty
As in the report by Makizako, Shimada, Doi, Tsutsumimoto, and Suzuki (2015a), PF was assessed for eachof the five categories with the following cut-off values: (1) unintentional weight loss, “Have you lost 2 kg
6

1
2

or more in the past 6 months?” (yes); (2) exhaustion, “In the last 2 weeks, have you felt tired for no reason?”3
4and “Do you engage in low levels of physical exercise aimed at health?” (participants who answered “no”

5

< 26.0 kg, women, < 18.0 kg), and (5) slowness, decreased gait (< 1.0 m/s). Individuals who did not have6

any relevant items were regarded as robust. Those who had 1–2 items and ≥ 3 items were categorized as

78having physical prefrailty (prePF) and PF, respectively.

910

2.4 Statistical analysis

11

square test for categorical variables. Continuous variables were Bonferroni-corrected after the Jonckheere-

12

Terpstra trend test to examine trends in the robust OF, preOF, and OF groups. Categorical variables were

13
14
15

analyzed using the chi-square test. Ordinal logistic regression analyses were then performed, treating the16172018). Therefore, the factors related to PF were treated as independent variables. The number of medications

18
19

ordinal logistic regression analysis was performed in order to examine the relationship between OF, SF, and20
21

fit index (NFI), and root mean square error of approximation (RMSEA). All statistical analyses were

22
23

with a significance level of less than 5%.

2425

3. Results

26
27
28

Figure 1 shows a flow chart outlining the process used to select participants for this study. Invitations for(yes); (3) low activity, “Do you engage in moderate levels of physical exercise or sports aimed at health?”
to both of these questions were classified as having low activity); (4) weakness, decreased grip strength (men,Sex-related differences were analyzed using the Mann-Whitney U test for continuous variables and the chi-three OF groups as objective variables to identify factors associated with OF. Currently, there are few reports
on factors associated with OF, but there is a report on the association between OF and PF (Tanaka et al.,was analyzed as a continuous variable with a cut-off value of five. Next, path analysis of the results of the
PF. The fit of the models in the path analysis was evaluated using the goodness of fit index (GFI), normed
performed using SPSS Statistics version 23 and SPSS Amos version 23 (IBM Corp., Armonk, NY, USA)

3.1 Participant characteristics
health checks were mailed to a total of 2,440 older adults, of whom 769 (31.5%) eventually participated.
Individuals with an MMSE score ≤ 18 (n=6, 0.2%), those receiving LTCI support (n=16, 0.7%), and those29
30

with missing cognitive or oral function data (n=65, 2.7%) were excluded, leaving 682 (27.9%) participants

31
32

are compared according to sex in Table 1. There was no significant sex-related difference in the OF or PF

33
34

according to OF status. Three hundred and eighty (55.7%) of the 682 participants had preOF and 65 (9.5%)3536function, and tended to be depressed. Appendices A1-A3 show the respective correspondence rate for each(267 men, 415 women; mean age 73.3 ± 6.6 years) for inclusion in the analyses. The OF, PF, and SF rates
rate; however, SF was found to be more common in men. Table 2 shows the results for the study endpoints
had OF. Participants with OF were older, were less independent in IADL, had lower physical and cognitive
item potentially associated with OF, SF, and PF.

37
7

1
2
3

Figure 1. Flow chart demonstrating the process used to select the study participants.

4

LTCI, Japanese Public Long-Term Care Insurance System; MMSE, Mini-Mental State Examination.
8

Table 1. Characteristics of the study population

Overall (n = 682)

Men (n = 267)

Women (n = 415)
P-

Variable

Mean ± SD

Mean ± SD
Median, [Q1, Q3]

Mean ± SD
Median, [Q1, Q3]

n (%)

n (%)

Median [Q1, Q3]

value

n (%)

Age, years

73.3 ± 6.6

72.0 [68.0, 78.0]

72.8 ± 6.6

71.0 [67.0, 78.0]

73.6 ± 6.5

73.0 [68.0, 79.0]

0.101

Education, years

13.4 ± 2.8

12.0 [12.0, 16.0]

14.2 ± 2.8

16.0 [12.0, 16.0]

12.9 ± 2.7

12.0 [12.0, 14.0]<0.001

Current or past248

(36.4)

183(68.5)

65(15.7)<0.001

Drinks alcohol, n (%)

321(47.1)

182(68.2)

139(33.5)<0.001

JST-IC score12.1 ± 2.8

12.0 [11.0, 14.0]

12.0 ± 2.9

12.0 [10.0, 14.0]

12.2 ± 2.7

13.0 [11.0, 14.0]

0.222

BMI

22.8 ± 3.3

22.7 [20.6, 24.7]

23.6 ± 3.2

23.3 [21.7, 25.4]

22.3 ± 3.4

22.1 [20.1, 24.2]<0.001SMI

6.5 ± 1.0

6.3 [5.7, 7.3]

7.5 ± 0.7

7.5 [7.0, 7.9]

5.9 ± 0.7

5.8 [5.4, 6.3]

<0.001

MNA-SF score12.8 ± 1.3

13.0 [12.0, 14.0]

13.0 ± 1.3

13.0 [12.0, 14.0]

12.6 ± 1.3

13.0 [12.0, 14.0]<0.001smoker, n (%)≤ 11, n (%)
Handgrip strength, kg

126(18.5)

27.9 ± 8.5

3926.0 [22.0, 34.0]
9(14.6)

35.5 ± 6.9

8736.0 [31.0, 40.0](21.0)

22.9 ± 5.1

0.037
23.0 [19.0, 26.0]<0.001

Gait speed, m/s

1.4 ± 0.3

1.4 [1.2, 1.6]

1.4 ± 0.3

1.4 [1.2, 1.6]

1.4 ± 0.3

1.4 [1.2, 1.6]

0.643

MMSE score28.6 ± 1.6

29.0 [28.0, 30.0]

28.4 ± 1.7

29.0 [28.0, 30.0]

28.7 ± 1.5

29.0 [28.0, 30.0]

0.028≤ 23, n (%)

10

(1.5)

5

(1.9)

5

(1.2)

24−27, n (%)

126(18.5)

57(21.3)

69(16.6)≥ 28, n (%)

546(80.1)

205(76.8)

341(82.2)

Depression, n (%)

153(22.4)

51(19.1)

102(24.6)

0.218

0.094

Oral function
Present teeth, n21.6 ± 7.9

24.0 [18.0, 27.0]

22.5 ± 7.3

25.0 [20.0, 27.0]

21.1 ± 8.2

24.0 [18.0, 27.0]

0.046

22.0 ± 4.9

22.8 [19.6, 25.4]

23.3 ± 4.2

23.9 [21.1, 26.3]

21.1 ± 5.1

22.16 [18.8, 24.8] <0.001

33.0 ± 7.5

32.9 [28.1, 37.8]

33.7 ± 8.4

33.3 [27.8, 38.9]

32.6 ± 6.9

32.6 [28.3, 36.9]

0.109

6.4 ± 0.7

6.4 [6.0, 6.8]

6.4 ± 0.7

6.4 [6.0, 6.8]

6.4 ± 0.7

6.4 [6.0, 6.8]

0.853

Masticatory
performance
Tongue pressure,kPa
ODK, times/s
jeive difficulty in
147(21.6)

42

eating10(15.7)

105(25.3)

0.003

Subjective difficulty
182(26.7)

67(25.1)

115(25.7)

0.451

Hypertension, n (%)

282(41.3)

129(48.3)

153(36.9)

0.003

Heart disease, n (%)

109[16.0)

51(19.1)

58(14.0)

0.075

74(10.9)

38(14.2)

36

(8.7)

0.023

256

(37.5)

90(33.7)

166(40.0)

0.098

113(16.6)

11

(4.1)

102

(24.6)<0.001

3

(0.4)

3

(1.1)

0

(0.0)

0.030

98

(14.4)

19

(7.1)

79

(19.0)<0.00168(10.0)

25

(9.4)

43

(10.4)

0.671

in swallowing
Medical history

Diabetes mellitus, n(%)
Hyperlipidemia, n(%)
Osteoporosis, n (%)
Chronic obstructive
pulmonary disease, n(%)
Osteoarthritis, n (%)
Spinal stenosis, n(%)
11Malignant
98(14.4)

35(13.1)

63(15.2)

0.451

Anemia, n (%)

20

(2.9)

8

(3.0)

12

(2.9)

0.937

Stroke, n (%)

40

(5.9)

25

(9.4)

15

(3.6)

0.002

3

(0.4)

1

(0.4)

2

(0.5)

0.836

122

(17.9)

31(11.6)

91(21.9)

0.001

174(25.5)

81(30.3)

93(22.4)

0.020

Robust, n (%)

237(34.8)

100(37.5)

137(33.0)

Prefrailty, n (%)

380(55.7)

147(55.1)

233(56.1)

Frailty, n (%)

65

(9.5)

20

(7.5)

45

(10.8)

Robust, n (%)

287(42.1)

123(46.1)

164(39.5)

Prefrailty, n (%)

237(34.8)

71(26.6)

166(40.0)

neoplasm, n (%)

Chronic kidneydisease, n (%)
Fracture, n (%)
Medications ≥ 5, n(%)
Oral frailty

0.238

Social frailty

0.001

12

Frailty, n (%)

158(23.2)

73(27.3)

85(20.5)

Robust, n (%)

346(50.7)

136(50.9)

210(50.6)

Prefrailty, n (%)

312(45.7)

122(45.7)

190(45.8)

Frailty, n (%)

24

(3.5)

9

(3.4)

15

(3.6)

Physical frailty

0.984

Categorical variables are shown as the number (percentage) and were analyzed using the chi-square test. Continuous variables are expressed as the mean and standard
deviation and were analyzed using the Mann-Whitney U test. A P-value of < 0.05 was considered statistically significant. The number of participants taking more than
five medications was not documented; therefore, the number of participants on polypharmacy are shown as a proportion. BMI, body mass index; JST-IC, Japan Scienceand Technology Agency Index of Competence; MMSE, Mini-Mental State Examination; MNA-SF, Mini Nutritional Assessment-Short Form; ODK, oraldiadochokinesis; Q1, first quartile; Q3, third quartile; SD, standard deviation; SMI, skeletal muscle mass index.

13

Table 2. Evaluation of items potentially affecting oral frailty status

Robust (n = 237)

preOF (n = 380)

OF (n = 65)

Mean ± SD

Mean ± SD

Mean ± SD

PVariable

Median [Q1, Q3]

Median [Q1, Q3]n (%)
Age, years

71.1 ± 5.7

Men, n (%)

100

Education, years

13.9 ± 2.9

n (%)
69.0 [67.0, 75.0](42.2)

74.0 ± 6.6
147

14.0 [12.0, 16.0]

74.0 [68.0, 79.0](38.7)

13.2 ± 2.7

Median [Q1, Q3]

value

78.0 [73.0, 81.0]<0.001n (%)
77.1 ± 6.5
2012.0 [12.0, 16.0](30.8)

12.5 ± 2.8

0.238
12.0 [10.5, 14.0]<0.001

Current or past72

(30.4)

150(39.5)

26(40.0)

0.060

Drinks alcohol, n (%)

123(51.9)

182(47.9)

16(24.6)<0.001

JST-IC score12.8 ± 2.3

13.0 [11.0, 15.0]

12.0 ± 2.8

12.0 [10.0, 14.0]

10.6 ± 3.4

11.0 [7.5, 13.0]<0.001

BMI

23.1 ± 3.4

23.0 [21.0, 24.9]

22.7 ± 3.3

22.6 [20.5, 24.5]

22.4 ± 3.4

22.3 [20.0, 24.7]

0.049

SMI

6.7 ± 1.1

6.6 [5.8, 7.5]

6.5 ± 1.0

6.3 [5.7, 7.3]

6.1 ± 0.9

5.9 [5.4, 6.6]

<0.001

MNA-SF score13.0 ± 1.2

13.0 [12.0, 14.0]

12.7 ± 1.3

13.0 [12.0, 14.0]

12.4 ± 1.5

13.0 [11.0, 14.0]

0.002

smoker, n (%)≤ 11, n (%)

32(13.5)

75
14(19.7)

19(29.2)

0.010

Handgrip strength, kg

29.7 ± 8.6

28.0 [24.0, 37.0]

27.5 ± 8.3

26.0 [22.0, 33.0]

23.5 ± 7.4

24.0 [17.0, 27.0]<0.001

Gait speed, m/s

1.4 ± 0.2

1.5 [1.3, 1.6]

1.4 ± 0.3

1.4 [1.2, 1.5]

1.2 ± 0.3

1.3 [1.1, 1.4]

<0.001

MMSE score28.9 ± 1.4

29.0 [28.0, 30.0]

28.5 ± 1.7

29.0 [28.0, 30.0]

28.0 ± 1.9

29.0 [27.0, 29.0]<0.001≤23, n (%)

1

(0.4)

6

(1.6)

3

(4.6)

24−27, n (%)

33(13.9)

76(20.0)

17(26.2)≥ 28, n (%)

203(85.7)

298(78.4)

45(69.2)

Depression, n (%)

30(12.7)

95)[25.0)(28)[43.1)

0.009<0.001

Oral functions
Present teeth, n26.1 ± 2.6

26.0 [24.0, 28.0]

20.5 ± 8.1

23.0 [16.0, 27.0]

11.4 ± 8.2

13.0 [4.0, 18.0]―

23.8 ± 3.0

24.2 [21.9, 26.0]

21.9 ± 4.3

22.6 [19.2, 25.1]

15.4 ± 7.4

16.8 [10.2, 21.6]―

35.3 ± 5.8

34.1 [31.1, 38.3]

32.3 ± 7.7

32.1 [26.6, 37.6)

28.5 ± 9.1

26.2 [21.4, 36.1]―

6.6 ± 0.6

6.6 [6.2, 7.0]

6.4 ± 0.7

6.4 [6.0, 6.8]

5.9 ± 1.0

6.2 [5.2, 6.6]―

Masticatory
performance
Tongue pressure,kPa
ODK, times/s
Subjective difficulty
0

(0.0)

92

in eating15(24.2)

55(84.6)―

Subjective difficulty
0

(0.0)

144

(37.9)

38(58.5)―

Hypertension, n (%)

92(38.8)

160(42.1)

30(46.2)

0.513

Heart disease, n (%)

31(13.1)

63(16.6)

15(23.1)

0.134

21

(8.9)

43

(11.3)

10(15.4)

0.296

87(36.7)

145(38.2)

24(36.9)

0.931

26(11.0)

74(19.5)

13(20.0)

0.016

0

(0.0)

2

(0.5)

1

(1.5)

0.234

30

(12.7)

61(16.1)

7(10.8)

0.346

22

(9.3)

41

(10.8)

5

(7.7)

0.675

in swallowing
Medical history

Diabetes mellitus, n(%)
Hyperlipidemia, n(%)
Osteoporosis, n (%)
Chronic obstructive
pulmonary disease, n(%)
Osteoarthritis, n (%)
Spinal stenosis, n(%)
16

Malignant
22

(9.3)

70

(18.4)

6

(9.2)

0.003

Anemia, n (%)

5

(2.1)

10

(2.6)

5

(7.7)

0.053

Stroke, n (%)

8

(3.4)

21

(5.5)

11

(16.9)<0.001

1

(0.4)

1

(0.3)

1

(1.5)

0.356

35

(14.8)

71(18.7)

16(24.6)

0.154

36(15.2)

111(29.2)

27(41.5)<0.001

Robust, n (%)

118(49.8)

155(40.8)

14(21.5)

Prefrailty, n (%)

84(35.4)

131(34.5)

22(33.8)

Frailty, n (%)

35(14.8)

94(24.7)

29(44.6)

Robust, n (%)

151(63.7)

178(46.8)

17(26.2)

Prefrailty, n (%)

82(34.6)

188(49.5)

42(64.6)

neoplasm, n (%)

Chronic kidneydiseases, n (%)
Fracture, n (%)
Medications ≥ 5, n(%)
Social frailty<0.001

Physical frailty<0.00117

Frailty, n (%)

4

(1.7)

14

(3.7)

6

(9.2)

Categorical variables are shown as the number (percentage) and were analyzed using the chi-square test. A P-value < 0.05 was considered statistically significant.
Continuous variables were analyzed with the Bonferroni-corrected Jonckheere-Terpstra test. A P-value < 0.006 was considered statistically significant. The JonckheereTerpstra test was not used because it was clear that oral functions decreased with OF. The number of participants taking more than five medications was not documented;
Therefore, the number of participants on polypharmacy are shown as a proportion. BMI, body mass index; JST-IC, Japan Science and Technology Agency Index ofCompetence; MMSE, Mini-Mental State Examination; MNA-SF, Mini Nutritional Assessment-Short Form; ODK, oral diadochokinesis; Q1, first quartile; Q3, third
quartile; SD, standard deviation; SMI, skeletal muscle mass index.

18

1
2

3.2 Ordinal logistic regression analysis

34

associated with OF, are shown in Table 3. There were significant associations with age (odds ratio [OR]5

stroke (OR 2.423, 95% CI 1.197 – 4.899), number of medications used (OR 1.127, 95% CI 1.010 – 1.259),

6

SF (OR 1.680, 95% CI 1.080 – 2.612), and prePF (OR 1.726, 95% CI 0.202 – 2.479).

The results of the ordinal logistic regression analysis, which was performed to investigate the factors
1.075, 95% confidence interval [CI] 1.045 – 1.104), MNA-SF score (OR 0.837, 95% CI 0.735 – 0.953),

7
8

Table 3. Ordinal logistic regression analyses

VariableOR

95% CI

P-value

Age

1.075

1.045 – 1.104< 0.001

Sex (0: men, 1: women)

0.797

0.555 – 1.145

0.219

Education

0.948

0.892 – 1.007

0.082

MNA-SF scores

0.837

0.735 – 0.953

0.007

MMSE scores

0.987

0.888 – 1.097

0.810

Depression (0: no, 1: yes)

1.508

0.970 – 2.347

0.068

Hypertension (0: no, 1: yes)

0.780

0.539 – 1.129

0.188

Heart disease (0: no, 1: yes)

1.021

0.653 – 1.597

0.927

1.213

0.716 – 2.054

0.474

Hyperlipidemia (0: no, 1: yes)

0.868

0.614 – 1.228

0.425

Osteoporosis (0: no, 1: yes)

0.929

0.581 – 1.486

0.758

Osteoarthritis (0: no, 1: yes)

0.976

0.617 – 1.543

0.918

Spinal stenosis (0: no, 1: yes)

0.929

0.542 – 1.590

0.788

1.408

0.899 – 2.208

0.136

1.451

0.572 – 3.680

0.433

Diabetes mellitus (0: no, 1:
yes)Malignant neoplasm (0: no, 1:
yes)Anemia (0: no, 1: yes)

19

Stroke (0: no, 1: yes)

2.423

1.197 – 4.899

0.014

Fracture (0: no, 1: yes)

1.010

0.662 – 1.540

0.963

Number of medications

1.127

1.010 – 1.259

0.033

SF

PF

1
2

Robust1.000 （Reference）

preSF

1.138

0.790 – 1.639

0.488

SF

1.680

1.080 – 2.612

0.021

Robust1.000 （Reference）

prePF

1.726

1.202 – 2.479

0.003

PF

1.347

0.546 – 3.327

0.519

MNA-SF and MMSE were analyzed as continuous variables. Age, MNA-SF, stroke, number of medications,3
4SF, and prePF were significantly associated with OF. CI, confidence interval; MMSE, Mini-Mental State5

physical frailty; SF, social frailty

Examination; MNA-SF, Mini Nutritional Assessment-Short Form; OF, oral frailty; OR, odds ratio; PF,

67
8

3.3 Path analysis

910

the path diagram derived by path analysis in this study. The best fit was selected among the path diagrams

11

starting factor affected the stabbing factor. The diagram also shows that SF was directly related to OF and

12

that the path coefficient from SF to OF was 0.141. Furthermore, both OF and SF were directly related to PF.

13
14

The path coefficient from OF to PF was 0.155 and that from SF to PF was 0.206. All pathways werePath analysis is a statistical method used to analyze relationships between multiple factors. Figure 2 shows
created by referring to the results of the ordinal logistic regression analysis. The pathway shows that thestatistically significant. The GFI was 0.982, the NFI was 0.961, and the RMSEA was 0.026.

15
16
17
18
20

1
2

Figure 2. A pathway diagram demonstrating the relationship between OF and SF. MNA-SF (Mini3
4

Nutritional Assessment-Short Form), MMSE (Mini-Mental State Examination), OF (oral frailty), SF (social

56
7(0, male; 1, female), medications (0, ≤ 4; 1, ≥ 5), OF, SF, PF (0, robust; 1, prefrailty; 2, frailty), MNA-SF

frailty), PF (physical frailty), and number of medications used were analyzed as categorical variables. Sex(0, ≥ 12; 1, ≤ 11), MMSE (0, ≥ 28; 1, 24 – 27; 2, ≤ 23). OF was directly related to PF, and SF was in the
background of OF. SF was directly associated with PF, and SF was associated with PF via OF.

8910

4. Discussion

11
12

decline in social function, are both predictors of dependency (Makizako et al., 2015b; Tanaka et al., 2018).

13
14

status. However, previous studies have not clearly defined the relationships between OF, SF, and PF. If a

15
16
17

preventing dependency could be established. The results of the present study suggest that SF directly relates

18
19

The rate of PF in this study was 3.5%, which was lower than the prevalence of 7.4% reported by a meta-

Longitudinal studies have shown that OF, an indicator of decline in oral function, and SF, an indicator of
A decline in oral and social function appears connected to the deterioration of an individual’s general healthrelationship between the three frailties could be clarified, a more multifaceted and effective method forto OF and that both, OF and SF are directly related to PF.

analysis of Japanese community-dwelling older adults aged 65 years or older (Kojima et al., 2017). In the20
21

present study, the mean JST-IC score for IADL was 12.1 ± 2.8, which is higher than the mean value of 9.5

22
23(Iwasa et al., 2018). This study found that the ability to perform IADL was maintained; therefore, it ispreviously reported for individuals aged 65 years or older (mean, 74.0 ± 2.8 years) in other regions of Japanreasonable to assume that the participants in this study maintained good physical function and that the rate
21

1
2

of PF was low. Furthermore, this study found that deterioration from robust oral function to OF tended to be34

and cognitive function, tended to be depressed, and were on polypharmacy. These findings are similar tomore common in participants who were older, less educated, had poor nutritional status, had poorer physicalthose reported by Tanaka et al. (2018).

5
6

In accordance with previous studies, this investigation defined three stages of OF, SF, and PF, comprising

7
8

robust (no functional decline), prefrailty (mild functional decline), and frailty (accumulation of several types

910

reflect the association of a more severe stage with a greater risk of dependency.

11

the factors associated with OF. Using path analysis, we examined how the factors associated with OF in the

12

ordinal logistic regression analysis were associated with OF, SF, PF, and cognitive decline (Feng et al., 2017),

13
14
15

which is an indicator of the psychological aspects of frailty. This study included a path analysis that could

16
17

The logistic regression analysis showed significant associations of OF with age, MNA-SF scores, history

18
19

of functional decline) (Makizako et al., 2015a; Makizako et al., 2015b; Tanaka et al., 2018). These definitions
Ordinal logistic regression analysis using the factors associated with PF as independent variables identified

infer relationships between different types of frailty and clarify the factors associated with OF.

of stroke, number of medications used, SF, and prePF.
The findings of the present study regarding the association between multidimensional aspects of oral andsocial function are consistent with those in several previous reports (Mikami et al., 2019; Nagayoshi et al.,20
21

2017; Nakanishi et al., 1999; Takeuchi et al., 2013).

22
23(Tanaka et al., 2018; Watanabe et al., 2017). Although the present study found no association between OF

24
25

OF and PF in this study was due to the low PF rate of 3.5% (n = 24). A relationship between OF and the

26
27
28

between a decline in oral function and decreased nutritional status (Kwon et al., 2017; Kwon, Suzuki,

29
30

Xerostomia is one of the adverse effects of several medications commonly used in older adults and is31
32

hazardous events caused by an increase in the number of medications may be associated with a decline in

33
34

medications was collected in this study. The mechanism of declining oral function and number of35
36

Stroke has a variety of sequelae, including both, motor and sensory impairments (Winstein et al., 2016),

37
38

There were reports of an association between decline in oral function and decline in physical function
and PF, there was an association between prePF and OF. It was inferred that the lack of association between
MNA-SF score was identified; this is consistent with the findings of previous studies on the association
Kumagai, Shinkai, & Yukawa, 2006; Sura, Madhavan, Carnaby, & Crary, 2017).
Older adults often have multiple comorbidities and are likely to be on polypharmacy (Sirois et al., 2019).
associated with caries, deterioration of masticatory performance, and dysphagia (Barbe, 2018). The risk oforal function; however, this relationship is unclear, because no information regarding the adverse effects ofmedications used or medication-related adverse events warrants further investigation in future studies.
and is responsible for considerable disability (Naruse, Sakai, Matsumoto, & Nagata, 2015). Patientsrequiring nursing care were excluded from this study, suggesting that the functional impairment attributable
to stroke was mild. However, we demonstrated an association between stroke and OF; therefore, it may be
22

1
2

that various symptoms resulting from a history of stroke were related to a decline in oral function, even if
they were mild.

3
4

The results of path analysis showed that SF was directly related to OF. Kobayashi, Wardle, & von Wagner

5(2015) reported an association between decline in social function and decreased health literacy. Preservation

6of health literacy is useful for health maintenance in daily life; however, a decline in health literacy leads to7
8worsening health care and ability to self-manage disease (Sørensen et al., 2012). Oral diseases, such as caries

910

Therefore, a lowering of general health literacy, which stems from a decline in social function, seems to be11

tooth loss, and even a decline in oral function. Furthermore, the opportunities for conversation are likely to12decrease alongside a decline in social function. Decreased speaking may lead to reduced tongue pressure as

13
14
15

a result of a decrease in the tongue movements involved in speech intelligibility. Furthermore, tongue

16
17

tongue pressure, decreased masticatory performance, and slowing of tongue movement. Therefore, the1819

appropriate. This study found that SF was directly associated with PF, which is in line with previous research

20
21

to environmental changes reduces the frequency of activity by narrowing the range of behaviors in older

22
23

is linked to PF. This study found that SF was not only directly related to PF, but also indirectly via OF.

2425function was connected to a decline in physical function. The process by which this occurs may involve not

26
27
28

interaction with others and decreased opportunities for conversation. The decline in social function may lead

29
30

maintaining and improving social function. This will involve securing opportunities to engage with others,

31
32

Tanaka et al. (2018) reported that age and polypharmacy were directly related to OF. Barbe (2018) also

and periodontal disease, are associated with lifestyle habits, including diet and hygiene (Petersen, 2008).
connected with a lowering of oral health literacy. Decreased oral health literacy can lead to poor oral hygiene,pressure is associated with masticatory performance and speed of tongue movement (Kugimiya et al., 2019;
Sagawa et al., 2019). These reports suggest that decreased opportunities for conversation lead to decreased
results of this path analysis, which demonstrate the possibility of SF in the background of OF, seem to be(Makizako et al., 2019). Shimada et al. (2010) reported that loss of social roles and difficulty in responding
adults. Narrowing of the range and frequency of activity decreases the amount of physical activity, and thisMoreover, a decline in oral function was identified to be one of the factors through which a decline in social
only a decrease in physical activity, but also a decline in oral function due to a reduction in the amount of
to a lowering of oral health literacy via a weakening of relationships with others, and in turn, cause a decline
in oral function. Therefore, strategies to prevent or manage a decline in oral function should also focus onwith the aim of maintaining oral health literacy.
reported an association of medication-induced xerostomia with caries, deterioration of masticatory

33
34

performance, and dysphagia. Comorbidity and the long-term morbidity associated with several chronic

35
36

An accumulation of adverse events associated with chronic disease and polypharmacy and may be related3738This study also found a direct association between the MNA-SF score and OF. There are reports of an

diseases are also associated with frailty (Castrejón-Pérez, Gutiérrez-Robledo, Cesari, & Pérez-Zepeda, 2017).
to not only deterioration of general health status but also a decline in oral function.
association between masticatory performance and vitamin and mineral deficiency (Kwon et al., 2017),
23

1
2

deterioration in subjective masticatory performance with a decline in diversity in the diet (Kwon et al., 2006),

3
4

performance and swallowing, may negatively impact the intake of nutrients. The results of this study are5robust oral function to OF. Therefore, management of OF may prevent undernutrition.

6

The factors found to be directly related to OF in this study support the findings of previous reports.

78Furthermore, MNA-SF was directly associated with SF, suggesting that OF may lead to SF via malnutrition.

9
10

be investigated in future longitudinal and interventional studies.

11

an association between age and SF and Tani et al. (2015) identified an association between unhealthy dietary

12

behaviors and eating or living alone. Furthermore, given that use of five or more medications was identified

13
14
15

as a risk factor for falls (Kojima et al., 2012) and that falls are associated with social isolation (Pohl, Cochrane,

16
17

regard also support the validity of this study.

18
19

previous investigations that identified associations between polypharmacy and PF (Saum et al., 2017) and20
21

background of PF in this study are consistent with previous reports. Age, the MNA-SF score, and22
23

association between cognitive decline and aging (Sakuma et al., 2017), malnutrition (Ozawa et al., 2013),

24
25

polypharmacy, an association that has also been reported before (Saum et al., 2017).

26
27
28

between OF, SF, and PF, as in previous research. The congruence between these results and those in previous

29
30

There are several limitations to this study. First, the associations between decline in oral function andand dysphagia with malnutrition (Sura et al., 2017). A decline in oral function, such as masticatory
consistent with these reports. It is clear that the risk of malnutrition was associated with a transition from

The interaction between decreased social function and oral function may indeed be bidirectional, and should
Age, the MNA-SF score, and polypharmacy were directly related to SF. Makizako et al. (2015b) reported

Schepp, & Woods, 2018), the relationship between polypharmacy and SF is likely to be consistent. The
relationship between SF and its background factors is in line with previous reports, and the results in thisPolypharmacy and the MMSE score were directly related to PF in this investigation; this is consistent with
between cognitive decline and PF (Feng et al., 2017). Furthermore, the factors identified to be in thepolypharmacy were directly related to the MMSE score, supporting previous reports, which identified an
and polypharmacy (Niikawa et al., 2017). This study also identified that aging was directly related to
The path model used in this investigation had a high level of fit, and all pathways showed a relationshipreports confirm the generalizability of these findings.

cognitive decline (Kugimiya et al., 2019; Watanabe et al., 2018), social relationships and risk of dementia

31
32(Kuiper et al., 2015), and dietary patterns and risk of dementia (Ozawa et al., 2013) have already been

33
34

was no significant pathway between OF or SF and the MMSE score. The path analysis also indicated a

35
36

status was involved in the process which decreased oral and social function lead to cognitive decline. OF,3738

et al., 2015b; Soysal et al., 2019; Tanaka et al., 2018). The fact that the relationships between these four

reported. Although the path analysis showed a relationship between the MNA-SF and MMSE scores, there
circular relationship between OF, SF, and the MNA-SF score, suggesting that a deterioration in nutritionalSF, malnutrition, and cognitive decline are associated with PF and dependency (Feng et al., 2017; Makizako
factors could be inferred in this study is one of the important grounds for investigating effective measures
24

1
2

for the multifaceted concept of frailty in the future. These relationships could not be determined in this study

3
4although Makizako et al. (2015a) have reported an association between age and PF, there was no significant

5

participated in previous health checkups and maintained their level of physical function over the course of6

the study. Third, although Soysal et al. (2019) reported an association between malnutrition and PF, we could

78

not identify a significant pathway between the MNA-SF score and PF in this study. The MNA-SF score was

910

there seemed to be a connection between malnutrition and a decline in physical function via declines in

11

cognition when the relationships between malnutrition and decline in physical function are examined in the

12

future. Fourth, this study only included older individuals who were able to independently attend for

13
14
15

assessment and excluded those with severe deterioration of physical and cognitive function; this could have

16
17

relationships could be identified; however, the path model used in the study had a high level of fit. All OF,

18
19adult populations. This study suggests that the relationship between OF, SF, and PF would lead to a general

20
21

because of its cross-sectional design; therefore, longitudinal and intervention studies are needed. Second,
pathway between these two variables in this study, possibly because the older participants had alreadyindirectly associated with PF via SF, and the MMSE score but was not directly associated with PF. However,social and cognitive function. Therefore, it will be necessary to consider decreased social function andintroduced a degree of selection bias. Therefore, the results of this study cannot be generalized to persons
with severe psychosomatic impairment. Finally, the cross-sectional nature of the study meant that no causal
SF, and PF pathways were significant, as in previous reports, and are generalizable to older independent
deterioration in health. This may provide an important perspective for future research on frailty.
The logistic regression analysis showed that the factors associated with OF were a decline in social function,

22
23

a decline in physical function, decreased nutritional status, and an increased number of medications used.

24
25

important to detect OF at an early stage and use a multifaceted approach to maintain general health. The

26

of comprehensive and effective methods to manage declines in oral function will also need to consider

27

evaluation of social function and its role in the maintenance of oral health literacy.

28
29

5. Conclusion

30
31

was directly related to OF, and OF in turn was directly related to PF. A decline in social function may

32
33

require evaluation and management of SF. These associations will be important considerations when

34
35
36
37

These are known frailty-related factors (Makizako et al., 2015b; Saum et al., 2017; Soysal et al., 2019). It is
results of the path analysis highlight the possibility that SF is connected to OF. Therefore, the development

In this study, OF, SF, and PF were found to be mutually related in community-dwelling older adults. SF
contribute to decreased oral and physical function. This implies that optimal management of OF will also
devising appropriate measures for management of OF.
Funding
This work was supported by JSPS KAKENHI (grant numbers: 16K01853 and 18K18462), 2018 Healthand Labor Sciences Research Grants (46–35), and 2018 Research Funding for Longevity Sciences (28–30
25

1
2

and 29–42) from the National Center for Geriatrics and Gerontology (NCGG), Japan.

34Declarations of interest
None.

5
6

Acknowledgments

7
8

We express our gratitude to the local authorities responsible for the Itabashi Ward for their support andthank everyone who participated in the study. We would also like to thank the members of the Otasha

9Kenshin study staff for their cooperation.

10
11

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Appendices2

Table A1. Correspondence rate for each item potentially associated with oral frailty

Overall

Men

Women

n (%)

n (%)

n (%)

Number of present teeth

190 (27.9)

64 (24.0)

126 (30.4)

Masticatory performance27 (4.0)

7 (2.6)20 (4.8)

Tongue pressure

141 (20.7)

62 (23.2)

79 (19.0)

ODK /ta/39 (5.7)

9 (3.4)30 (7.2)

Subjective difficulty in eating (yes)147 (21.6)

42 (15.7)

105 (25.3)

Subjective difficulty in swallowing (yes)182 (26.7)

67 (25.1)

115 (27.7)

Oral frailty

3

ODK, oral diadochokinesis

4
5
6
7
8
9
10
11
32

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Table A2. Correspondence rate for each item potentially associated with social frailty

Overall

Men

Women

n (%)

n (%)

n (%)

185 (27.1)

42 (15.7)

143 (34.5)

127 (18.6)

50 (18.7)

77 (18.6)

Visits friends sometimes (no)211 (30.9)

108 (40.4)

103 (24.8)

Feels helpful to friends or family (no)57 (8.4)

36 (13.5)

21 (5.1)

Talks with someone every day (no)65 (9.5)

27 (10.1)

38 (9.2)

Social frailty
Living alone (yes)Going out less frequently compared withlast year (yes)

2
3
4
5
6
7
8
9
10
11
33

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Table A3. Correspondence rate for each item potentially associated with physical frailty

Overall

Men

Women

n (%)

n (%)

n (%)

Unintentional weight loss

83 (12.2)

47 (17.6)

36 (8.7)

Exhaustion

171 (25.1)

59 (22.1)

112 (27.0)

Low activity

102 (15.0)

39 (14.6)

63 (15.2)

Weakness

85 (12.5)

25 (9.4)

60 (14.5)

Slowness

47 (6.9)

17 (6.4)

30 (7.2)

Physical frailty

234