Original research

Taiji Noguchi ‍ ‍,1,2 Chiyoe Murata,1,3 Takahiro Hayashi,4 Ryota Watanabe,5,6Masashige Saito,7 Masayo Kojima,5 Katsunori Kondo,6,8 Tami Saito1►► Additional online
supplemental material ispublished online only. To view,please visit the journal online(http://d​ x.​doi.o​ rg/​10.​1136/​
jech-​2021-​217211).

For numbered affiliations see
end of article.
Correspondence to
Dr Taiji Noguchi, Department
of Social Science, ResearchInstitute, National Center for
Geriatrics and Gerontology,
Obu, Aichi, Japan;n​ oguchi.​taiji0415@​gmail.​com
Received 7 May 2021
Accepted 10 July 2021

© Author(s) (or theiremployer(s)) 2021. Re-­use
permitted under CC BY-­NC. No
commercial re-­use. See rights
and permissions. Publishedby BMJ.
To cite: Noguchi T, Murata C,
Hayashi T, et al. J Epidemiol
Community Health Epubahead of print: [please
include Day Month Year].
doi:10.1136/jech-2021217211

ABSTRACT
Background Little is known about the prospective
association between community-­level social capitaland individual-­level frailty onset. Therefore, this study
aimed to examine the impact of community-­level social
capital on frailty onset among older adults using 3-­year
longitudinal data.
Methods This prospective cohort study recruited non-­institutionalised older adults from the Japan Gerontological
Evaluation Study, established in 2013 and robust older
adults were followed up for 3 years. We assessed three
aspects of community-­level social capital (civic participation,social cohesion and reciprocity), and employed a multilevel
logistic regression analysis; frailty was evaluated using the
Kihon Checklist questionnaire, which has been widely used
as a screening tool for frailty in Japan.
Results In total, 21 940 older adults (from 384
communities) who were robust at baseline (2013)
completed the follow-­up survey (2016). Participants’mean age (SD) was 71.8 (4.9) years, and 51.2% werefemale. In the follow-­up period, frailty onset occurredin 622 participants (2.8%). Regarding community-­levelsocial capital variables, civic participation was inversely
associated with frailty onset (OR=0.94, 95% CI 0.90
to 0.97, p=0.001), after adjusting for individual-­level and community-­level covariates. The potential
intermediate factors of individual social relationships
and health behaviours did not largely change the results.
This association was found regardless of individual
socioeconomic status.
Conclusions Living in a community with rich civic
participation, such as engagement in social activities,
was associated with lower frailty onset among older
adults. Community development that fosters social
participation is essential for frailty prevention.

INTRODUCTION

The proportion of older adults is increasing worldwide.1 Japan has the highest life expectancy and themost rapidly ageing society.2 Such a populational
increase denotes higher healthcare, social security
costs and societal challenges. Thus, facilitating healthy
ageing (eg, by maintaining functional capacity) is
crucial.3 One measure in this regard is the preventive
aspect of dealing with frailty.
Frailty is a state of increased vulnerability to poor
resolution of homeostasis following stress, regarded

as an age-­related physiological syndrome,4 5 whichevokes greater risks for older adults regarding
adverse health outcomes, such as institutionalisation, hospitalisation, functional disability andmortality.6–9 While the definition is insufficiently
conclusive, frailty is also characterised as an
unstable state in which even very small stressors
could lead to major deterioration and functional
dependence, and is therefore regarded as an intermediate condition between being healthy and ill/
disabled.4 5 Therefore, frailty prevention is key for
older adults to achieve healthy ageing.10
According to the conceptual model, frailty is determined by multidimensional aspects, comprising physical, psychological, social and even environmental
domains.11–13 Focusing only on older adults’ physical problems when dealing with frailty may evoke
fragmented care.14 However, little is known about
the effects of environmental factors, such as poor-­
quality housing, community environments and social
network changes, on frailty. The environment thatolder adults inhabit can compensate for their intrinsic
capacity decline and help maintain their functional
abilities, which is essential for healthy ageing.15
Hence, examining the social-­environmental factors
of frailty seems important for its prevention.
One factor is social capital, which has been extensively examined, including its relation to health.16
There are several concepts of social capital. For
instance, Putnam et al define social capital as‘features of social organisation, such as trust, norms
and networks that can improve the efficiency
of society by facilitating coordinated actions’.17
Saito et al18 developed a community-­level social
capital scale based on the definitions of Putnam
et al,17 Coleman19 and Kawachi et al.20 This scale
was developed for community assessment, and its
concurrent validity with health indicators has been
confirmed.18 This scale also consists of ‘structural’(eg, social network density or civic engagement
patterns) and ‘cognitive’ (eg, level of trust perception and norms of reciprocity between individuals)
aspects of social capital.16 21 The present study
level social capital fromfocused on community-­
these two aspects using this scale.
Community social capital was shown to exert
a contextual effect on individual health throughthe diffusion of knowledge on health promotion;
maintenance of healthy behavioural norms throughNoguchi T, et al. J Epidemiol Community Health 2021;0:1–8. doi:10.1136/jech-2021-217211

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Association between community-­level social capitaland frailty onset among older adults: a multilevellongitudinal study from the Japan Gerontological
Evaluation Study (JAGES)Original research

METHODS
Participants

In this prospective longitudinal study, we obtained panel datafrom the Japan Gerontological Evaluation Study (JAGES), an

Baseline survey, 2013

ongoing cohort study among non-­institutionalised and functionally independent older adults aged 65 years and above inJapan.29 The JAGES includes only older adults who are ineligible
for public long-­term care insurance benefits.
Figure 1 shows the sample selection flow chart. A baseline
survey was conducted between October and December 2013;
self-­reported questionnaires were mailed to eligible residents in
30 municipalities. Random sampling methods were used in 17
large municipalities; in the other 13, all eligible residents could
participate. Of the 193 694 people invited, 137 736 returned
the questionnaires (response rate: 71.1%). We excluded 7996
individuals whose age and gender could not be confirmed (valid
response rate: 67.0%). We also excluded 3066 individuals in 86
community areas with <50 respondents to avoid non-­precise
values from the sample size and 28 786 respondents withunknown area of residence; thus, 97 888 respondents from 478
communities were aggregated by school districts to evaluate
community-­level social capital.18 We selected school districts
as a community unit because, in Japan, school districts are thegeographical unit that older adults can easily travel by foot orbicycle within and are a valuable unit for considering local publichealth activities.
We excluded 3222 respondents with limitations in performing
basic activities of daily living (BADL), 4228 respondents withmissing responses on BADL items, 638 respondents with self-­reported dementia or Parkinson’s disease, 5099 respondents
with missing information about their present illness, 31 789
respondents with prefrailty or frailty assessed using the Kihon
Checklist (KCL),30–32 and 17 560 respondents with incomplete
responses to the KCL items.

Enrolment for the baseline survey(n = 193,694)
Non-response (n = 55,958)
Participants who responded(n = 137,736; response rate = 71.1%)
Invalid responses owing to a lack of age and sex data (n = 7,996)

Valid participants(n = 129,740; valid response rate = 67.0%)
Participants who had their communitylevel social capital analysed(n = 97,888; n = 478 community areas)

Calculating community-level social capital scores
Having difficulties performing basic activities of daily living (n = 3,222)
Lack of information regarding basic activities of daily living (n = 4,228)
Self-reported dementia or Parkinson’s disease (n = 638)
Lack of information regarding present illness (n = 5,099)
Pre-frailty or frailty (n = 31,789)
Incomplete response to items of the Kihon Checklist (n = 17,560)

Robust participants(n = 35,352)

Follow-up survey, 2016

Communities containing < 50 respondents (n = 3,066)
Lack of information regarding community areas (n = 28,786)

Robust participants eligible for the followup survey (n = 32,250)

Residents of municipalities not targeted in the follow-up
survey (n = 3,102)

Non-response (n = 10,310)
Final sample(n = 21,940; n = 384 community areas;
follow-up rate = 68.0%)

Figure 1 Sample selection flow chart.
2

Noguchi T, et al. J Epidemiol Community Health 2021;0:1–8. doi:10.1136/jech-2021-217211

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informal social control; promotion of access to local services andamenities; and psychological processes that provide emotional
support and mutual respect.22 Compared with conventional
studies using ecological-­level or individual-­level approaches, amultilevel analytical approach that can statistically differentiate
between group-­level and individual-­level associations can help
in better understanding the collective/contextual influences ofsocial capital.16
Although studies using multilevel analyses have revealed
the positive association of community-­level social capital withvarious health outcomes, including mortality and disability,23–26
only two studies have reported the effects of social capital on
frailty. In China, a cross-­sectional study found no significant association between community-­level social capital and individual
frailty.27 Meanwhile, in Japan, a cross-­sectional study examining
the effect of three forms of social capital (civic participation,social cohesion and reciprocity) reported an inverse association
between higher community-­level civic participation and the likelihood of individual frailty.28 However, there is lack of evidence
in longitudinal studies, and thus temporal relationships between
the two variables need to be clarified.
We examined the association between community-­level social
capital and frailty onset among older adults in Japan, using
multilevel analytical modelling and a 3-­year longitudinal study
design.

Original research

Frailty
Frailty was defined using the KCL developed by the Japanese
Ministry of Health, Labour and Welfare, which is widely used
for frailty screening in Japan.30 The KCL is a simple yes/noquestionnaire that assesses multiple aspects of daily living
functions, such as instrumental ADL, social living, motor, oral
and cognitive function, nutrition state, homebound status andmood.30 Responding ‘yes’ to any item counts as a point (score
range: 0–25), with higher scores indicating frailty tendency.
Based on previous studies,28 29 we classified participants into
three groups: robust (0–3 points), prefrailty (4–7) and frailty(≥8).
The JAGES uses a slightly modified version of this tool (online
supplemental table 1 and text 1). We used the scoring systemestablished in a prior study that used the same modified version
as the JAGES.28 We followed up participants who were robust atbaseline for 3 years.

Community-level social capital

Based on prior research,18 at baseline, we assessed the threecomponents of community-­level social capital: civic participation, social cohesion and reciprocity; civic participation isregarded as reflecting the structural aspects of social capital,and social cohesion and reciprocity as reflecting the cognitive
aspects.33 34 Individual-­level data were aggregated by school
districts.
Civic participation was assessed by the percentage of individual participation in a volunteer group, sports group, hobby
activity, study or culture group, and skill teaching in each
community. Each of the five items were assigned between 0 and
100 points.
Social cohesion was assessed by the percentage of ‘very’ or‘moderately’ answers (response scale: ‘very’, ‘moderately’,‘neutral’, ‘slightly’ or ‘not at all’) to three items: general trust(‘In general, do you think that people living in your area can betrusted?’), perception of others’ intention to help (‘Do you thinkpeople living in your area try to help others in most situations?’)
and attachment to the residential area (‘How attached are you tothe area where you live?’). Each of the three items was assigned
between 0 and 100 points.
Reciprocity was assessed by the percentage of ‘yes’ answers to
three items: emotional support receival (‘Do you have someone
who listens to your concerns and complaints?’), emotional
support provision (‘Do you listen to the concerns and complaintsof other(s)?’), and instrumental support receival (‘Do you havesomeone who looks after you when you are sick and confined
to bed?’). Each of the three items were assigned between 0 and
100 points.
We conducted a factor analysis using a total of 11 items withaggregated individual-­level data and used factor scores calculated as community-­level social capital scores in each school
district (online supplemental table 2).

Other variables

We used individual sociodemographic characteristics and healthstatus, and community-­level characteristics as covariates.
Individual-­level factors included age (65–69, 70–74, 75–79,
80–84 or ≥85 years), gender, living arrangement (living withothers or living alone), marital status (unmarried or married),education (<10, 10–12 or ≥13 years), equivalent income (bytertiles, calculated by dividing the income of each household by
the square root of the number of family members), self-­rated
health (good or poor), present illnesses (none, one, or two or
more of cancer, heart disease, stroke, respiratory disease, musculoskeletal disease, hypertension, dyslipidaemia and diabetes),
alcohol consumption (never/past or currently), smoking history(never/past or currently) and walking time (<60 or ≥60 min/day).
Individual social relationships were assessed using four variables: the frequency of contact with friends (more than or lessthan once a week), participation in community groups (no (0)or yes (≥1 point); this was measured using responses to theaforementioned five groups for community-­level civic participation, with a score range of 0–5), perception of community social
cohesion (no (0) or yes (≥1 point); measured using responses
to the aforementioned three items for community-­level social
cohesion, with a score range of 0–3), and social support (low(0–2) or high (3 points)); measured using responses to the aforementioned three items for community-­level reciprocity, with ascore range of 0–3).
Community-­level variables included urbanisation (defined,
based on population density, as follows: rural, <1000 people/
km2; suburban, 1000–1500 and urban, ≥1500), ageing rate (theproportion of people aged ≥65 years; divided into tertiles) andrate of low-­level education (the proportion of people in each
district who had graduated only from junior high school; divided
into tertiles). Information on these variables was obtained fromthe 2013 Japanese Census.

Statistical analysis

The data included individuals (first level) nested in community districts (second level). The multilevel analysis framework
assumes that individual outcomes are partly dependent on the
districts where individuals live; the variation in outcomes acrossdistricts (random effects); and the effects of community-­levelvariables on the outcomes, adjusting for individual characteristics (fixed effects).
Accordingly, we performed a multilevel logistic regression
analysis to calculate ORs and 95% CIs for frailty onset. ORs
were estimated based on a change of 10 percentage points incommunity-­level social capital scores. First, we used the nullmodel to assess whether frailty onset varied across districts.
In model 1, we examined the association between community-­level social capital and frailty onset, without adjusting forcovariates. In model 2, we included age, gender, living arrangement, marital status, education, equivalent income, self-­rated
health, present illness and community-­level variables. In model
3, we added the variables of individual social relationships andin model 4, we included additional health behaviours (alcohol
consumption, smoking history and walking time) to examine
if these factors attenuate the association between community-­level social capital and frailty onset. Based on the random-­
effects variance, we calculated the median OR to examine theunexplained heterogeneity between communities (a median
OR further away from 1 indicates a strong difference between
communities).35

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Then, 32 250 robust older adults were followed up to
check for new occurrences of frailty, excluding 3102 individuals whose municipalities were not targeted by the follow-­up
survey owing to the local governments’ refusal to cooperate.
up was conducted during October–November
The follow-­
2016. Finally, 21 940 participants (from 384 districts) who
completed the survey were included in the analysis (follow-­up
rate: 68.0%).

Original researchParticipants’ characteristics
Overall 

Frailty onset
Non-­frailty 

n=21 940

n=18 712

Frailty

Missing

n=622

n=2606Age (years), n (%)

65–698244 (37.6)

7266 (38.8)

169 (27.2)

809 (31.0)

 

70–74

7943 (36.2)

6852 (36.6)

184 (29.6)

907 (34.8)

 

75–79

3989 (18.2)

3289 (17.6)

141 (22.7)

559 (21.5)

 

80–84

1406 (6.4)

1066 (5.7)

91 (14.6)

249 (9.6) 

85 or older

358 (1.6)

239 (1.3)

37 (5.9)

82 (3.1)

Gender, n (%)

Male

10 697 (48.8)9316 (49.8)

313 (50.3)

1068 (41.0) 

Female11 243 (51.2)

9396 (50.2)

309 (49.7)

1538 (59.0)

Living arrangement, n (%)

Living with others

19 145 (87.3)

16 435 (87.8)

534 (85.9)2176 (83.5) 

Living alone

2141 (9.8)

1783 (9.5)

58 (9.3)

300 (11.5) Missing

654 (3.0)494 (2.6)

30 (4.8)130 (5.0)

Marital status, n (%)

Unmarried

4164 (19.0)3456 (18.5)

129 (20.7)

579 (22.2)
1989 (76.3) 

Married17 649 (80.4)

15 172 (81.1)

488 (78.5) Missing

127 (0.6)

84 (0.4)

5 (0.8)38 (1.5)

Education (years), n (%)<107210 (32.9)

5769 (30.8)

264 (42.4)

1177 (45.2)

 

10–12

9341 (42.6)

8149 (43.5)

235 (37.8)

957 (36.7)

 

≥13

5290 (24.1)

4719 (25.2)

119 (19.1)

452 (17.3) Missing

99 (0.5)75 (0.4)

4 (0.6)20 (0.8)1025 (39.3)

Equivalent income, n (%)

Low7937 (36.2)

6659 (35.6)

253 (40.7) 

Middle5110 (23.3)

4487 (24.0)

135 (21.7)

488 (18.7)

 

High

6272 (28.6)

5542 (29.6)

141 (22.7)

589 (22.6) Missing

2621 (11.9)2024 (10.8)

93 (15.0)504 (19.3)

Self-­rated health, n (%)

Good

20 780 (94.7)

17 789 (95.1)

560 (90.0)2431 (93.3)

 

Poor

974 (4.4)793 (4.2)

54 (8.7)

127 (4.9) 

Missing

186 (0.8)130 (0.7)

8 (1.3)48 (1.8)

Present illness, n (%)

None7430 (33.9)6408 (34.2)

187 (30.1)

835 (32.0)
1149 (44.1)

 

One

9538 (43.5)8115 (43.4)

274 (44.1) 

Two or more

4972 (22.7)

4189 (22.4)

161 (25.9)

622 (23.9)

Frequency of contact with friends,n (%)

More than once a week

17 538 (79.9)

15 032 (80.3)

455 (73.2)

2051 (78.7) 

Less than once a week

3883 (17.7)

3289 (17.6)

141 (22.7)

453 (17.4) Missing

Participation in community groups, Non (%)

519 (2.4)

391 (2.1)

26 (4.2)

102 (3.9)8206 (37.4)

6890 (36.8)

281 (45.2)

1035 (39.7)

 

Yes

10 260 (46.8)

9041 (48.3)

227 (36.5)

992 (38.1) 

Missing3474 (15.8)

2781 (14.9)

114 (18.3)

579 (22.2)

Perception of community social
cohesion, n (%)

No1821 (8.3)

1482 (7.9)

91 (14.6)

248 (9.5) Yes

19 744 (90.0)

16 946 (90.6)

518 (83.3)

2280 (87.5) Missing

375 (1.7)

284 (1.5)

13 (2.1)

78 (3.0)

Social support, n (%)

Low1149 (5.2)

939 (5.0)

55 (8.8)

155 (5.9)2342 (89.9)

 

High

20 287 (92.5)

17 400 (93.0)545 (87.6) Missing

504 (2.3)

373 (2.0)

22 (3.5)

109 (4.2)

Alcohol consumption, n (%)

Never/past

13 236 (60.3)

11 112 (59.4)

411 (66.1)

1713 (65.7)
877 (33.7) 

Currently

8649 (39.4)

7561 (40.4)

211 (33.9) Missing

55 (0.3)

39 (0.2)

0 (0.0)16 (0.6)

Smoking history, n (%)

Never/past

19 936 (90.9)

17 000 (90.9)

550 (88.4)

2386 (91.6) 

Currently

1934 (8.8)

1661 (8.9)

69 (11.1)

204 (7.8) Missing

70 (0.3)

51 (0.3)

3 (0.5)16 (0.6)

Walking time (min/day), n (%)<60

11 260 (51.3)

9575 (51.2)

358 (57.6)

1327 (50.9)

 

≥60

10 595 (48.3)9080 (48.5)

261 (42.0)

1254 (48.1) Missing

85 (0.4)

57 (0.3)

3 (0.5)25 (1.0)

4

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Table 1

Original research
Characteristics of the communities (n=384)nMean (SD)Minimum,
maximum

Community-­level social capital*  Civic participation

384

0.15 (0.90)−2.57, 3.51

 Social cohesion384−0.09 (0.95)−3.11, 2.88

 Reciprocity

384−0.02 (0.87)−3.74, 2.11

Urbanisation†  Rural58―― Suburban

40

―

―

 Urban

286――

Ageing rate‡

 

 Low

134

―

―

 Middle

129

―

―

 High121――

Rate of low-­level education§

 

 Low

142

―

―

 Middle

117

―

―

 High125――*Factor score.
†Defined by population density (persons/km2 in an inhabitable area): rural, <1000;
suburban, 1000–1500 and urban, ≥1500 persons/km2.
‡Defined by the percentage of people aged 65 years or older: low, 17.3%–19.8%; middle,
19.9%–21.8%; high, 22.0%–47.6%.
§Defined by the percentage of people who had graduated only from junior high school:
low, 5.2%–10.1%; middle, 11.0%–16.4%; high, 16.4%–38.0%.

To confirm the results’ robustness against potential misclassification of frailty onset, we performed a sensitivity analysis
using modified frailty diagnostic criteria (online supplemental
table 1 and text 1). We also analysed the data using prefrailty
and frailty onset as the combined outcome. Additionally, we
conducted stratified analyses for the following variables: age(65–74 or ≥75 years), gender, education (low: <10 or high:≥10 years) and equivalent income (divided into two by median(low or high) value).
To mitigate potential biases caused by missing information,
we used the multiple imputation approach, under the missing
at random assumption. We generated 20 imputed datasets using
the multiple imputation by chained equations procedure andpooled the results using the standard Rubin’s rule.36
Significance was set at p<0.05. Statistical analyses wereconducted using R software (V.3.6.3 for Windows).

RESULTSWe analysed data from 21 940 robust participants. Table 1
shows the participants’ characteristics at baseline. Participants’mean age was 71.8 years (SD=4.9), and 51.2% were female.
In the follow-­up period, 622 (2.8%) had experienced frailty
onset. Participants with frailty onset were more likely to: beolder, have low education, have low equivalent income, have
low social support, have poorer self-­rated health, have shorter
daily walking time, less frequently contact their friends, notparticipate in community groups, not perceive community social
cohesion and not consume alcohol.
Table 2 shows the characteristics of the 384 communities analysed. The average frailty onset was 2.6% (minimum:
0.0%; maximum: 33.3%). The mean (SD) of community-­levelsocial capital scores were 0.15 (0.90), –0.09 (0.95) and −0.02(0.87) for civic participation, social cohesion and reciprocity,respectively.

Table 3 shows the association between community-­levelsocial capital and frailty onset (all information about the results
is provided in online supplemental table 3). Higher community
civic participation demonstrated a significant association witha lower risk for frailty onset, after adjusting for individual-­level
and community-­level covariates (model 2: OR (95% CI) 0.94
(0.90 to 0.97), p=0.001). This association remained largely
unchanged after incorporating the variables of individual social
relationships (model 3: OR=0.94 (95% CI 0.91 to 0.98),
p=0.003) and health behaviours (model 4: OR=0.94 (95% CI
0.91 to 0.98), p=0.003) into the analytical model. The sensitivity analysis using the modified frailty criteria (online supplemental table 4) and prefrailty and frailty onset as the combined
outcome (online supplemental table 5) showed similar trends tothe main results. We also found similar results in the complete-­case analysis (online supplemental table 6).
Table 4 shows the results of the stratified analyses. Community-­level civic participation and frailty onset showed an inverse
association at all strata; that is, there were no interactions (age,p=0.344; gender, p=0.399; education, p=0.740; equivalent
income, p=0.614).

Discussion

To the best of our knowledge, this was the first study to examine
the prospective association between community-­level social
capital and frailty onset in older adults. Specifically, living incommunities with higher civic participation was associated witha lower frailty onset within 3 years. Our findings suggest that
community development with rich social participation can help
prevent frailty among older adults.
In a previous study in China, neighbourhood-­level social
cohesion and social participation were both not found to be
associated with frailty.27 However, in that study, the sample
sizes of individuals and communities investigated were somewhat smaller, thereby leading to potential non-­detection of its
effects. Meanwhile, in Japan, a nationwide study suggested aninverse association between high community-­level civic particlevel frailty28; ouripation and the likelihood of individual-­
results supported this finding and revealed the longitudinalassociation between community-­level civic participation andfrailty.
Several longitudinal studies have suggested the protective effects of community-­level civic participation on healthoutcomes related to frailty (eg, oral health and depression).37 38
Thus, living in a community with rich civic participation could
prevent multiple aspects of frailty. Since social-­environmental
factors that promote social activities are key to healthy ageing,15
fostering community-­level social capital may be essential for
frailty prevention.
Our results show that each 10% points increase in community-­level civic participation reduces frailty onset by approximately
6%. The effect size is not large, but it may be appropriate as anindividual health effect caused by social-­environmental factors.
Rather, because social-­
environmental factors can cause widespread exposure to the residents in the area, social capital might
be an important intervention target in public health to prevent
frailty among older adults.
The association between community-­level civic participationand frailty onset remained largely unchanged after including
individual social relationships and health behaviours into analytical models. Although we hypothesised that the contextual
effects of community-­level social capital on frailty prevention
are mediated by the promotion of individual social relationships

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Table 2

Original research

Null model Model 1 

Model 2OR (95% CI)

P value

Model 3Model 4

OR (95% CI)

P value

OR (95% CI)

P value

OR (95% CI)

P value

0.94 (0.90 to 0.97)

0.001

0.94 (0.91 to 0.98)

0.003

0.94 (0.91 to 0.98)

0.003

Fixed effects
Community-­level variables
Social capital* Civic participation

0.91 (0.88 to 0.94) <0.001 Social cohesion

1.01 (0.98 to 1.05)

0.462

0.98 (0.94 to 1.02)

0.295

0.99 (0.95 to 1.03)

0.483

0.99 (0.95 to 1.03)

0.498 Reciprocity

1.02 (0.98 to 1.06)

0.277

1.03 (0.99 to 1.07)

0.093

1.04 (1.00 to 1.08)

0.075

1.04 (1.00 to 1.08)

0.073

Individual-­level variables
Frequency of contact withfriends (ref: more than oncea week)Less thanonce a week

1.19 (1.00 to 1.41)

0.051

1.18 (0.99 to 1.41)

0.060

Participation in community
groups (ref: no)Yes

0.74 (0.64 to 0.86) <0.001

0.75 (0.65 to 0.88)<0.001

Perception of community
social cohesion (ref: no)Yes

0.59 (0.47 to 0.73) <0.001

0.59 (0.48 to 0.74)<0.001Social support (ref: low)High0.59 (0.46 to 0.75) <0.001

0.59 (0.46 to 0.76)<0.001

Alcohol consumption (ref:never/past)

Currently

0.88 (0.75 to 1.04)

0.136

Smoking history (ref: never/past)

Currently

1.35 (1.06 to 1.70)

0.013

Walking time (ref: <60 min/
day)

≥60

0.85 (0.75 to 0.98)

0.020

Random effects
Community-­level variance

0.194

0.147

0.063

0.066

0.064

 Median OR

1.52

1.44

1.27

1.28

1.27

Model 1 was a crude model; model 2 was adjusted for age, gender, living arrangement, marital status, education, equivalent income, self-­rated health, present illness and community-­level
characteristics (urbanisation, ageing rate and rate of low-­level education); model 3 was adjusted for frequency of contact with friends, participation in community groups, perception of community
social cohesion and social support in addition to model 2 covariates; model 4 was adjusted for alcohol consumption, smoking history and walking time in addition to model 3 covariates.
All information about the results is provided in online supplemental table 3.
*Estimation per 10 percentage points.

or health behaviours, these mediations were hardly observed.
The contextual effects of group-­level social capital on healthare considered to involve mechanisms such as social contagion(dissemination of health information and behaviour), informalsocial control (loose management of unhealthy behaviour) or
collective efficacy (mobilisation of groups for the developmentof health-­related facilities or systems).22 Alternatively, in termsof network nature, rich civic participation in the communities
could loosely connect diverse people (bridging) or promote thelinks between people from different social classes (linking).16 21
Meanwhile, because several clinical and lifestyle factors, suchas nutritional status, sedentary behaviour and polypharmacy,39
are considered risk factors for frailty, these pathways might also
be involved. Therefore, further investigations on the mechanisms and nature of the links between community-­level social
capital and frailty are needed.
The stratified analyses of age, gender, education, andequivalent income showed that the association between

Table 4 Stratified analyses for the association between community-­level social capital and frailty onset by individual demographic factors basedon a multilevel logistic regression analysis with multiple imputation approach
Community-­level social capital* 

Civic participation 

OR (95% CI)†P value

Social cohesion
OR (95% CI)†

Reciprocity
P value

OR (95% CI)†P value

Age

65–74 years

0.92 (0.87 to 0.96)<0.0010.96 (0.91 to 1.01)

0.095

1.05 (1.00 to 1.10)

0.055

 

≥75 years

0.97 (0.92 to 1.02)

0.250

1.02 (0.96 to 1.08)

0.598

1.01 (0.95 to 1.06)

0.793

GenderMale

0.95 (0.91 to 1.01)

0.085

0.99 (0.94 to 1.05)

0.726

1.03 (0.98 to 1.08)

0.279

 

Female0.92 (0.87 to 0.97)

0.004

0.97 (0.92 to 1.03)

0.321

1.03 (0.98 to 1.09)

0.254

Education<10 years

0.94 (0.89 to 0.99)

0.022

0.98 (0.92 to 1.04)

0.462

1.02 (0.96 to 1.08)

0.499

 

≥10 years

0.93 (0.89 to 0.98)

0.007

0.97 (0.93 to 1.02)

0.289

1.04 (1.00 to 1.10)

0.070

Equivalent income

Low

0.94 (0.89 to 0.98)

0.003

0.99 (0.95 to 1.04)

0.647

1.03 (0.99 to 1.08)

0.157

High

0.94 (0.88 to 1.00)

0.063

0.95 (0.89 to 1.02)

0.172

1.04 (0.97 to 1.11)

0.267*Estimation per 10 percentage points.
†Adjusted for age, gender, living arrangement, marital status, education, equivalent income, self-­rated health, present illness and community-­level covariates (urbanisation, ageing rate, andrate of low-­level education).

6

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Table 3 Association between community-­level social capital and frailty onset, based on a multilevel logistic regression analysis with multiple
imputation approachOriginal research

CONCLUSIONSThis multilevel longitudinal study found that higher community
civic participation was associated with lower frailty onset amongolder adults. Fostering social capital through promoting civic
participation such as social activities in the community could
help prevent frailty among older adults.

What is already known on this subject►► Communities rich in social capital may have protective

effects on various health outcomes for older adults.

►► However, evidence on the effects of community-­level social

capital on frailty remains unclear. Moreover, no prior researchon the topic has conducted a longitudinal analysis.

What this study adds►► This longitudinal study revealed that communities with richsocial capital, particularly high civic participation, could
prevent frailty onset among older adults, regardless of
individual socioeconomic status.
►► Fostering civic participation in communities, including
social activities, is of great importance when considering
population-­based approaches to frailty prevention in older
adults.

Author affiliations
1
Department of Social Science, Research Institute, National Center for Geriatrics andGerontology, Obu, Aichi, Japan2
Department of Public Health, Nagoya City University Graduate School of Medical
Sciences and Medical School, Nagoya, Aichi, Japan3
Department of Health and Nutrition, Tokai Gakuen University, Nagoya, Aichi, Japan
4
Department of Rehabilitation and Care, Seijoh University, Tokai, Aichi, Japan
5
Department of Frailty Research, Research Institute, National Center for Geriatrics
and Gerontology, Obu, Aichi, Japan
6
Department of Social Preventive Medical Sciences, Center for Preventive Medical
Sciences, Chiba University, Chiba, Japan
7
Faculty of Social Welfare, Nihon Fukushi University, Chita-­gun, Aichi, Japan
8
Department of Gerontological Evaluation, Research Institute, National Center for
Geriatrics and Gerontology, Obu, Aichi, Japan
Acknowledgements We wish to express our sincere thanks to the staff in thesurveyed municipalities for their contributions. We also thank the members of theJapan Gerontological Evaluation Study.
Contributors TN conceptualised and designed the study, analysed the data anddrafted and revised the manuscript. CM, TH, RW, MS and MK helped to develop
the study concept, interpret the results and reviewed and critically revised themanuscript. KK, the principal investigator of the JAGES project, helped to develop thestudy concept, participated in data collection and study design, and reviewed andcritically revised the manuscript. TS helped to develop the study concept, interpretthe results and reviewed and critically revised the manuscript. All authors approved
submission of the final manuscript.
Funding This work was supported by Japan Society for the Promotion of Science(JSPS), KAKENHI Grant Numbers (17K04306, 19K24277, 21K17322). The JAGES is
supported by MEXT (Ministry of Education, Culture, Sports, Science and Technologyof Japan)-­Supported Program for the Strategic Research Foundation at Private
Universities (2009-2013), JSPS (Japan Society for the Promotion of Science)
KAKENHI Grant Numbers (JP18390200, JP22330172, JP22390400, JP23243070,
JP23590786, JP23790710, JP24390469, JP24530698, JP24683018, JP25253052,
JP25870573, JP25870881, JP26285138, JP26882010, JP15H01972), Health
Labour Sciences Research Grants (H22-­Choju-­Shitei-008, H24-­Junkanki-­Ippan-007,
H24-­Chikyukibo-­Ippan-009, H24-­Choju-­Wakate-009, H25-­Kenki-­Wakate-015,
H25-­Choju-­Ippan-003, H26-­Irryo-­Shitei-003 [Fukkou], H26-­Choju-­Ippan-006,
H27-­Ninchisyou-­Ippan-001, H28-­Choju-­Ippan-002, H28-­Ninchisho-­Ippan-002, H30-­
Kenki-­Ippan-006, H30-­Junkankitou-­Ippan-004), Japan Agency for Medical Researchand Development (AMED) (JP17dk0110017, JP18dk0110027, JP18ls0110002,
JP18le0110009, JP19dk0110034), the Research Funding for Longevity Sciences fromthe National Centre for Geriatrics and Gerontology (24-17, 24-23, 29-42, 30-22,
20-40, 21-17, 21-20), and the Open Innovation Platform with Enterprises, andResearch Institute and Academia (OPEEA, JPMJOP1831) from the Japan Science andTechnology Agency.
Disclaimer The funding sources had no role in the study design, data collection
and analysis, decision to publish, or preparation of the manuscript.
Competing interests None declared.
Patient consent for publication Not required.
Ethics approval This study was reviewed and approved by the ethics committees
at the University of Tokyo (No. 10555), Nihon Fukushi University (No. 13–14),
National Centre for Geriatrics and Gerontology (No. 992), and Chiba University (No.
1777 and 2493). The mailed questionnaire was accompanied by a study explanation;
participants who returned the completed questionnaire were considered to haveprovided informed consent. All our procedures conformed to the Declaration of
Helsinki.
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement Data may be obtained from a third party and are
not publicly available. For the JAGES, all inquiries are to be addressed to the data

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community-­level civic participation and low frailty onset was
broadly similar and showed the same direction in all strata.
Previous studies have shown the association of low individual
education and income with frailty,40 41 suggesting a socioeconomic disparity of frailty. In our study, rich community-­level
civic participation had protective effects on frailty regardlessof individual socioeconomic status; thus, fostering community-­level civic participation could be key to addressing healthdisparities among older adults. Meanwhile, in the stratified
analysis by age, the associations were in the same direction
for both young-­old adults and old-­old adults, but the effectsize was somewhat smaller among individuals aged ≥75 years;
environmental factors might vary withthe effects of social-­increasing age. As the physical function decline tends to be
more accentuated in old-­old adults than in young-­old adults,42
for old-­old adults, community-­level civic participation might
not be sufficiently effective and may require individual interventions alongside the fostering of community social capital.
Although this study provided pertinent insights regarding
social-­environmental factors for frailty prevention, there wereseveral limitations. First, the social capital measurement was
based on a self-­administered questionnaire, denoting potential
response measurement biases; social desirability bias may artificially affect the assessment of social capital,43 causing the overestimation of social capital. Second, the JAGES used a slightly
modified version of the KCL, and slightly different versions
were used in the baseline and follow-­up surveys, which could
have caused errors in frailty measurements. However, because
only robust participants at baseline were followed, we were able
to examine their frailty onset. Besides, our sensitivity analysis
showed almost the same evidence to the main results. Thus,
the effects of measurement error could be small. Third, considering the reversible nature of frailty,5 we cannot account for thechanges in the frailty status during the follow-­up period. Further
examinations that consider recovery from frailty are necessary.
Fourth, although this was a prospective longitudinal study, thenature of the observational study was unable to clarify causality
due to unmeasured confounders. However, we have tried toadjust for major confounding variables on the individuals andcommunities. Finally, the geographical scale of our community
unit (school districts) may be somewhat large for the neighbourhood units. However, in Japan, school districts represent an area
where older adults can easily travel on foot/bicycle and community organisations conduct their activities; thus, we believethat using school districts is meaningful for understanding thecommunity characteristics.

Original research

Supplemental material This content has been supplied by the author(s).
It has not been vetted by BMJ Publishing Group Limited (BMJ) and may nothave been peer-­reviewed. Any opinions or recommendations discussed aresolely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all
liability and responsibility arising from any reliance placed on the content.
Where the content includes any translated material, BMJ does not warrant theaccuracy and reliability of the translations (including but not limited to local
regulations, clinical guidelines, terminology, drug names and drug dosages), andis not responsible for any error and/or omissions arising from translation andadaptation or otherwise.
Open access This is an open access article distributed in accordance with theCreative Commons Attribution Non Commercial (CC BY-­NC 4.0) license, which
permits others to distribute, remix, adapt, build upon this work non-­commercially,and license their derivative works on different terms, provided the original work is
properly cited, appropriate credit is given, any changes made indicated, and the use
is non-­commercial. See: http://​creativecommons.​org/​licenses/​by-​nc/​4.​0/.
ORCID iD
Taiji Noguchi http://​orcid.​org/​0000-​0001-9​ 165-​5501

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management committee via the following email: ​dataadmin.​ml@​jages.​net. All JAGES
datasets have ethical or legal restrictions for being placed in public repositories
owing to the existence of sensitive information about the human participants.