International Journal ofEnvironmental Researchand Public Health
ArticleSocial Participation and Functional Decline:
A Comparative Study of Rural and Urban Older
People, Using Japan Gerontological Evaluation
Study Longitudinal Data
Kazushige Ide 1,2, *, Taishi Tsuji 3 , Satoru Kanamori 4,5 , Seungwon Jeong 6 ,Yuiko Nagamine 3,7 and Katsunori Kondo 2,3,8
1
2
3
4
5
6
7
8

*

Department of Community General Support, Hasegawa Hospital, Yachimata, Chiba 289-1113, Japan
Department of Public Health, Graduate School of Medicine, Chiba University, Chuo-ku, Chiba 260-8670,
Japan; kkondo@chiba-u.jp
Department of Social Preventive Medical Sciences, Center for Preventive Medical Sciences, Chiba University,
Chuo-ku, Chiba 260-8670, Japan; tsuji.t@chiba-u.jp (T.T.); yuiko.mail@gmail.com (Y.N.)
School of Nursing, Tokyo Women’s Medical University, Shinjuku-ku, Tokyo 162-8666, Japan;
kanamori.satoru@twmu.ac.jp
Department of Preventive Medicine and Public Health, Tokyo Medical University, Shinjuku-ku,
Tokyo 160-8402, Japan
Department of Community Welfare, Faculty of Health Sciences, Niimi University, Nishigata Niimi,
Okayama 718-8585, Japan; k-jeong@niimi-u.ac.jp
Department of Family Medicine, Graduate School of Medical and Dental Sciences, Tokyo Medical and
Dental University, Bunkyo-ku, Tokyo 113-8510, Japan
Department of Geriatric Evaluation, Center for Gerontology and Social Science, National Center for
Geriatrics and Gerontology, Obu, Aichi 474-8511, Japan
Correspondence: idex_waka@yahoo.co.jp; Tel.: +81-43-444-0137

Received: 14 December 2019; Accepted: 15 January 2020; Published: 18 January 2020


Abstract: This study compared the relationship between social participation, including work, andincidence of functional decline in rural and urban older people in Japan, by focusing on the number andtypes of organizations older people participated in. The longitudinal data of the Japan Gerontological
Evaluation Study (JAGES) that followed 55,243 individuals aged 65 years or older for six years wereused. The Cox proportional hazards model was employed to calculate the hazard ratio (HR) of theincidence of functional decline over six years and the stratification of rural and urban settings. In thismodel, we adjusted 13 variables as behavioral, psychosocial, and functional confounders. The morerural and urban older people participated in various organizations, the more they were protected fromfunctional decline. Participation in sports (HR: rural = 0.79; urban = 0.83), hobby groups (HR: rural= 0.76; urban = 0.90), and work (HR: rural = 0.83; urban = 0.80) significantly protected against theincidence of decline in both rural and urban areas. For both rural and urban older people, promotingsocial participation, such as sports and hobby groups and employment support, seemed to be an
important aspect of public health policies that would prevent functional decline.
Keywords: social participation; work; functional decline; rural; urban

1. Introduction
A strategy of active ageing [1], by linking the key policy domains of employment, pension,
retirement, health, and citizenship, provides a sound basis to respond to the challenges presented bypopulation ageing [2]. In recent times, the practical challenge has been to open up the innovative policy
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spaces that might make active ageing not only thinkable but also achievable [3]. In European countries,
the Active Aging Index (AAI) tool measures the untapped potential of older people for active andhealthy aging across countries [4]. The AAI consists of four domains: employment, participation insociety; independent, healthy, and secure living; and capacity and enabling environment for active
ageing [4,5].
The social participation of older people, one of the domains of AAI [4,5], is a key factor of“successful aging” [6] and an important element of “active aging” [7]. Social participation is one of thecore indicators of “age-friendly cities” proposed by the World Health Organization in recent years [8].
When considering public health services in a rapidly aging society, social participation is highlighted
as a modifiable target of health interventions.
In many longitudinal studies, social participation has been reported as effective for health outcomessuch as functional disability [9–13], cognitive disability [14–16], instrumental activities of daily living
decline [17–19], and basic activities of daily living decline [20]. Among them, some studies focused on
the number and types of organizations in which older people participated [10,13,16–18]. These studies
suggested that older people who participate in more organizations are healthier than those who do notparticipate, and that the relationships between social participation and health varied according to thetypes of organization they participate in.
However, these studies [10,13,16–18] do not consider two issues. First, these studies do notconsider “work” as a kind of social participation. According to the Organization for Economic
Co-Operation and Development (OECD) scoreboard for older workers, older workers aged 65–69
years increased from 20.3% to 25.5% between 2006 and 2016 and from 12.0% to 14.6% at age 70–74
years during the same period, in OECD member countries [21]. However, recommendations made by
the Council on Aging and Employment Policies [22] encourage supporting the employment of older
people. In AAI, work and social participation are separate domains, but these are also defined as theactual experience of active aging [4,5]. Considering these circumstances, it is necessary to include
work in social participation in the analysis of the number and types of organizations in which older
people participated. Second, these studies do not consider residential environments, such as ruraland urban areas. Generally, older people living in rural areas suffer with more depression [23], lower
levels of basic activities of daily living [20], and a higher risk of developing disability [24] compared tothose living in urban areas. In addition, the life expectancy is shorter in rural areas, and the difference
between urban and rural areas is widening [25]. Previous studies [13,26] showed that rural older
people were less socially active than urban older people. However, previous studies state that bondingsocial capital comprising a connection between community members is often stronger among rural
older adults, resulting in community strength [27,28]. In addition, environmental factors such asneighborhood socioeconomic status and access to services and transportation differ in rural and urban
areas [29]. Furthermore, the relationship between social participation and health outcomes, such as
depression [23] and self-rated health [26,30], also differs. These may be the reasons why rural older
people are unhealthier than urban older people. The relationship between social participation andfunctional decline may differ between rural and urban areas; however, such a relationship has notbeen clarified.
Thus, we aimed at clarifying whether there were differences between rural and urban areas in therelationship between social participation, including work, and incidence of functional decline. This
study was conducted to inform public health policies that could prevent the need for long-term care ofolder individuals residing in rural and urban areas, which have different environmental factors.
2. Materials and Methods
2.1. Data
We used longitudinal data from the Japan Gerontological Evaluation Study (JAGES). JAGES
is one of the few population-based gerontological repeated surveys in Japan focused on the social

Int. J. Environ. Res. Public Health 2020, 17, 617

3 of 13determinants of health and the social environment [31,32]. From August 2010 to January 2012,self-reported questionnaires were mailed to 95,827 community-dwelling independent individuals aged
65 years and older who were not eligible to receive benefits from public long-term care insurance
services. They were randomly selected from 13 municipalities, including rural and urban areas. Overall,
62,418 people participated (response rate, 65.1%) in the survey called JAGES2010. They were followed
up for about six years (minimum 5.2 years; maximum 6.4 years). Of the total respondents (response
rate 65.1%), 54,539 (87.4%) were successfully linked to the incident records of long-term care insurance
certification. We excluded 7223 responses for the following reasons: (i) missing information on address(n = 101) and activities of daily living (ADL) (n = 1482); and (ii) having physical or cognitive disabilities
reported in their questionnaires (n = 988). Moreover, 4662 respondents in long-term care within two
years were removed to avoid the possibility of reverse causality (i.e., the possibility that people who
were at high risk of functional decline did not participate socially). The final number of participants inthis analysis was 47,306.
Ethical approval for the study was obtained from the Nihon Fukushi University Ethics Committee(application number: 10–05), the National Center for Geriatrics and Gerontology (application number:
No. 992-2), and Chiba University Ethics Committee (application number: No. 2493).
2.2. Dependent Variable
The dependent variable was the incidence of functional decline during the follow-up period.
The incidence of functional decline was defined by medical certification for Long-Term Care Insurance.
Certification of decline is based on the formal evaluation of the need for Long-Term Care according
to uniform criteria applied throughout Japan, and comprises both a home-visit interview, as well as
the written opinion of a primary physician [33]. This formal evaluation is based on a standardized
multistep assessment of functional and cognitive impairments [33]. We obtained information on thecertification of long-term needs, death, and moving out of the study area, from the long-term careinsurance database maintained by the municipalities. These criteria for determining the onset offunctional decline have been used in previous epidemiological studies [4–6].
2.3. Independent Variable
The independent variable was social participation. With reference to previous research [5], social
participation was classified into the following six types: neighborhood groups (local community),
hobby groups (hobby), sports groups or clubs (sports), industrial groups (industry), volunteer groups(volunteer), and senior citizen clubs (citizen). Furthermore, we considered work (work) as a form ofsocial participation and therefore analyzed seven types of organizations in this study.
Participation in organizations other than work was assessed by using the following question:“How often do you participate in the following clubs or groups?”. Participants were given the following
choices: “almost every day”, “twice or thrice a week”, “once a week”, “once or twice a month”, “afew times a year” and “never”. The response was categorized as “yes” if individuals selected any of
the five options from “a few times a year” to “almost every day”, and “no” if they selected “never”.
Participation in work was assessed by using the following question: “What is your current working
status?”. Participants were given the following choices: “working”, “retired and not working now”
and “never had a job”. The response was categorized as “yes” if the participants answered “working”,
and “no” if they answered “retired and not working now” or “never got a job”.
The total number of types of organizations each participant participated in was tallied, andparticipation was categorized as 0 (no participation), 1, 2, or ≥3 organizations, or “missing”. If the
response to participation in all organizations was missing, we deemed it as “missing” category in thisanalysis. The organizations particularly unique to Japan among the types named above are seniorcitizen clubs. Japan’s senior citizens clubs conduct a wide range of activities, including group activities
such as sports, hobbies, cultural activities, and performing arts.

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4 of 132.4. Covariates
Based on a previous study [10], sex, age, annual equivalized income, educational attainment,
marital status, and self-reported medical conditions were considered potential confounding factors that
may correlate with social participation and incidence of functional disability. In addition, behavioral,
psychosocial, and physiological factors were also used as covariates and potential mechanisms
influencing health and social participation. Smoking, alcohol consumption, daily walking time, andfrequency of going outdoors were assessed as behavioral factors. Depression (Geriatric Depression
Scale), emotional support, instrumental support, and frequency of meeting friends were assessed as
psychosocial factors. Instrumental activity of daily living (IADL) was assessed as a functional factor.
All variables were categorized as shown in Table 1 and set as dummy variables. A “missing” category
was used in the analysis to account for missing responses to questions.
2.5. Classification of Rural and Urban Settings
The definition of functional urban areas from the OECD metropolitan database [34] was used toclassify rural and urban settings. The definition of urban areas in OECD countries uses population
density to identify urban cores, and travel-to-work flows to identify the hinterlands whose labor market
is highly integrated with the cores. The methodology consisted of the three following main steps:(1) identification of core municipalities through gridded population data; (2) connecting noncontiguous
cores belonging to the same functional urban area; and (3) identification of urban hinterlands. Thismethodology makes it possible to compare functional urban areas of similar size across different
countries and classifies functional urban areas according to population size into the following fourtypes: (1) small urban areas (with a population below 200,000 people); (2) medium-sized urban areas(with a population between 200,000 and 500,000); (3) metropolitan areas (with a population between
500,000 and 1.5 million); and (4) large metropolitan areas (with a population of 1.5 million or more).
From the OECD’s four functional urban areas, all cities, including metropolitan and large metropolitan
areas, were designated urban areas in this study, and all others were designated rural areas. In thisstudy, eight municipalities were designated as rural, and five municipalities were designated as cities.
2.6. Statistical Analysis
First, we conducted a chi-square test to compare variables between rural and urban males andfemales. As the sample size in this study is very large, we calculated Cramer’s V as the effect size inaddition to the p-value. The criteria for Cramer’s V are 0.1 for small, 0.3 for medium, and 0.5 for large.
Second, the Cox proportional hazards model was employed to calculate the hazard ratios (HRs) and
95% confidence intervals (CI) of the incidence of functional decline over six years, stratified by rural,and urban settings. In each model, nonparticipation in an organization was set as the referent category.
In the analysis of the number or types of organization older people participate in, we conducted a trend
test. Further, six types of social participation were introduced in each model separately. The following
two models of analysis were used: a regression analysis was performed with simultaneous forced
entry of sex, age, equivalent income, educational attainment, marital status, and self-reported medical
conditions as covariates (Model 1). Model 2 added the following confounding factors to Model 1:
smoking, alcohol consumption, walking time, frequency of going outdoors, Geriatric Depression Scale,emotional support, instrumental support, frequency of meeting friends, and IADL. Finally, to confirm
the robustness of our finding, we performed a complete case analysis, excluding patients missing anyof the variables used in the analysis. STATA V.15 (Stata Corp, College Station, TX, USA) was used to
conduct a statistical analysis, with a significance level of 5%.

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Table 1. Baseline characteristics of respondents (2010–2012).

VariablesRural(n = 15,083)

Urban(n = 32,223)

n

%

n

%

p-Value(Cramer’s V)

Sex

Male
Female

6758
8325

44.8
55.2

15,163
17,06347.0
53.0<0.001(0.02)

Age(years)

65–69
70–74
75–79
80–84
85+

4287
4536
3470
1973
817

28.4
30.1
23.0
13.1
5.4

9676
10,343
7257
3611
1336

30.0
32.1
22.5
11.2
4.2

<0.001(0.04)

Equivalent income(million yen)

Low (<2.0)
Middle (2.0–3.9)
High (≥4.0)
Missing

7127
3988
939
3029

47.3
26.4
6.2
20.1

11,815
11,321
3616
5471

36.7
35.1
11.2
17.0

<0.001(0.13)

Educational
attainment(years)

<10
10–12
≥13
Missing

8404
4432
1853
394

55.7
29.4
12.3
2.6

14,103
11,182
6255
683

43.8
34.7
19.4
2.1

<0.001(0.12)

Marital status

MarriedSingleMissing

10,611
4111
361

70.3
27.3
2.4

23,315
8480
428

72.4
26.3
1.3

<0.001
0.04

Self-reported
medicalconditions

Illness
No illness
Missing

10,267
3508
1308

68.1
23.2
8.7

21,859
7677
2687

67.8
23.8
8.4

0.243
(0.01)

Smoking

Never smoked
Past smoker
Current smoker
Missing

8440
3566
1437
1640

56.0
23.6
9.5
10.9

17,174
8649
3330
3070

53.3
26.9
10.3
9.5

<0.001(0.04)

Alcoholconsumption

Never drank
Past drinker
Current drinker
Missing

9122
440
4684
837

60.5
2.9
31.1
5.5

18,4201021
10,836
1946

57.2
3.2
33.6
6.0

<0.001(0.03)Walking time(per day)>90 min
60–90 min
30–60 min
<30 min
Missing

2515
2130
4558
4905
975

16.7
14.1
30.2
32.5
6.5

5004
5029
10,960
9341
1889

15.5
15.6
34.0
29.0
5.9

<0.001(0.05)

Frequency ofgoing outdoors

Almost everyday
2–3 times/week
About once/week
RarelyMissing

6607
4601
1755
1351
769

43.8
30.5
11.6
9.0
5.1

18,496
8288
2253
1384
1802

57.4
25.7
7.0
4.3
5.6

<0.001(0.15)

Depression

No depression
Depressive tendency
Depression
Missing

9313
2613
822
2335

61.8
17.3
5.4
15.5

19,977
5343
1595
5308

62.0
16.6
4.9
16.5

0.002
(0.02)

Emotional
supportAvailable
Not available
Missing

13,052
1209
822

86.5
8.0
5.5

28,584
2310
1329

88.7
7.2
4.1

<0.001(0.03)

Instrumental
supportAvailable
Not available
Missing

12,369
1906
808

82.0
12.6
5.4

26,971
3906
1346

83.7
12.1
4.2

<0.001(0.03)

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Table 1. Cont.
Rural(n = 15,083)

Urban(n = 32,223)

n

%

n

%

Frequency of
meeting friends

Almost everyday
2–3 times/week
About once/week
1–2 times/month
A few times a year or lessMissing

2247
3513
2461
2914
2841
1107

14.90
23.30
16.30
19.30
18.80
7.40

4347
7206
5293
6049
7251
2077

13.5
22.4
16.4
18.8
22.5
6.4

<0.001(0.04)

Instrumental
activity of dailyliving (IADL)

Not decline
DeclineMissing

6073
7230
1780

40.3
47.9
11.8

12,57815,856
3789

39.0
49.2
11.8

0.025
(0.01)

Number of typesof organizations

0
1
2
≥3
Missing

3187
3420
2691
5227
558

21.1
22.7
17.8
34.7
3.7

7700
7964
6173
9588
798

23.9
24.7
19.1
29.8
2.5

<0.001(0.06)

Local community

Nonparticipation
Participation
Missing

5909
5886
3288

39.2
39.0
21.8

14,781
10,802
6640

45.9
33.5
20.6

<0.001(0.07)

Hobby

Nonparticipation
Participation
Missing

6656
5430
2997

44.1
36.0
19.9

13,411
13,212
5600

41.6
41.0
17.4

<0.001(0.05)

SportsNonparticipation
Participation
Missing

8540
3272
3271

56.6
21.7
21.7

18,242
7375
6606

56.6
22.9
20.5

0.001
(0.02)

Industry

Nonparticipation
Participation
Missing

8791
2020
4272

58.3
13.4
28.3

19,293
4829
8101

59.9
15.0
25.1

<0.001(0.04)

VolunteerNonparticipation
Participation
Missing

8787
2292
4004

58.3
15.2
26.5

19,803
4526
7894

61.5
14.0
24.5

<0.001(0.03)

CitizenNonparticipation
Participation
Missing

7842
4247
2994

52.0
28.2
19.8

19,244
6165
6814

59.7
19.1
21.2

<0.001(0.10)

Work

Nonparticipation
Participation
Missing

9002
3397
2684

59.7
22.5
17.8

21,572
7166
3485

67.0
22.2
10.8

<0.001(0.10)

Variables

p-Value(Cramer’s V)

Type of social participation

3. Results
Table 1 presents the descriptive statistics of rural and urban variables. Of the 47,306 respondents
included in the analyses, 21,921 were male and 25,385 were female. Of the 21,921 males, 6758 lived
in rural and 15,163 lived in urban settings. Of the 25,385 females, 8375 lived in rural and 17,060
lived in urban settings. The average age of the rural and urban older people was 73.8 (standard
deviation (SD), 5.9) and 73.3 (SD, 5.6) years, respectively. Of the respondents in rural and urban areas,
2399 (15.9%) and 4018 (15.3%) reported functional decline, respectively. The average tracking period
was 2028.1 days (SD = 364.1) for rural and 1951.8 days (SD = 361.7) for urban older peoples. The
comparison of variables across rural and urban areas revealed that there were many urban–ruraldifferences. However, the sample size for this study was so large that even minor differences could
result in statistical differences. In fact, Cramer’s V in the chi-square test between almost all variables
was judged to be very small, and the realistic effect size was small. However, describing the differenceInt. J. Environ. Res. Public Health 2020, 17, 617

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between rural areas and cities when the effect size is 0.1 or more indicated that older people in rural
areas had a lower equivalent income (p < 0.001), lower educational attainment (p < 0.001), and went
outdoors less frequently (p < 0.001) than those in urban areas. Although the effect size was small, thedistribution of the number of organizations in which older people participated differed between ruraland urban areas (p < 0.001). When types of social participation were analyzed, rural older people
participated a lot more in senior citizen clubs (p < 0.001) than urban older people. The distributionof participation in work differed between rural and urban areas (p < 0.001; Cramer’s V = 0.1); it wasthought to be due to the missing category.
Table 2 presents the results of a Cox proportional hazards model analysis of the different types oforganizations and incidence of functional decline. In the crude model and Model 1, a “dose–response”
relationship was seen both among rural and urban areas, with progressively lower HRs as the numberof different types of organizations increased. In Model 2 for rural older people, the HRs were 0.94
(95% CI: 0.84–1.05) for participation in one, 0.85 (0.75–0.97) for participation in two, and 0.76 (0.67–0.86)
for participation in three or more different types of organizations, with the significant difference
disappearing only for participation in one type of organization. For urban older people, the HRs
were 0.92 (95% CI: 0.85–0.99) for participation in one, 0.87 (0.80–0.96) for participation in two, and0.82 (0.75–0.89) for participation in three or more different types of organizations, with the statisticalsignificance for one or more different types of organizations. In other words, older people in urban
areas were protected from functional decline through one type of participation. On the other hand,older people in rural areas required more than one type of participation, but older people in rural
areas had lower HRs when participating in more than two types of organizations than older people inurban areas.
Table 2. HRs for participation in one, two, and three or more different types of organizations.
Rural
0
1
2
≥3
Trend p
Urban
0
1
2
≥3
Trend pCrude Model

Model 1Model 2

HR (95% CI)

HR (95% CI)

HR (95% CI)

1.00 Ref
0.71 * (0.64–0.79)
0.57 * (0.50–0.64)
0.43 * (0.39–0.49)
p < 0.05

1.00 Ref
0.87 * (0.78–0.97)
0.75 * (0.66–0.85)
0.62 * (0.56–0.70)
p < 0.05

1.00 Ref
0.94 (0.84–1.05)
0.85 * (0.75–0.97)
0.76 * (0.67–0.86)
p < 0.05

Crude model

Model 1Model 2

HR (95% CI)

HR (95% CI)

HR (95% CI)

1.00 Ref
0.69 * (0.64–0.75)
0.59 * (0.55–0.65)
0.48 * (0.44–0.52)
p < 0.05

1.00 Ref
0.85 * (0.79–0.91)
0.77 * (0.71–0.84)
0.67 * (0.62–0.72)
p < 0.05

1.00 Ref
0.92 * (0.85–0.99)
0.87 * (0.80–0.96)
0.82 * (0.75–0.89)
p < 0.05

HR: Hazard ratio; CI: confidence interval; Ref: reference. * p < 0.05. Model 1: Crude model + sex, age, equivalent
income, educational attainment, marital status, and self-reported medical conditions. Model 2: Model 1 + smoking,alcohol consumption, walking time (per day), frequency of going outdoors, depression, emotional support,
instrumental support, frequency of meeting friends, and IADL.

The results of the complete case analysis are shown in Table S1. The results of the complete caseanalysis, excluding patients missing any of the variables used in the analysis were similar to thosewhen the “missing” category was used in the analysis to account for missing responses to questions.
The full modeling results in Model 2 were presented in Table S2. In this study, Model 2 added social
networks such as emotional support, instrumental support, and frequency of meeting friends. Ruraland urban older people who could not avail emotional support were not protective against functional
decline compared with those who could avail it. Furthermore, urban older people who could not avail
instrumental support were not protective against functional decline compared with those who couldInt. J. Environ. Res. Public Health 2020, 17, 617

8 of 13avail it, but this was not the case in rural areas. The frequency of meeting friends was not statisticallysignificant in rural and urban areas.
Table 3 presents the results of the Cox proportional hazards model analysis of the type of social
participation and incidence of functional decline. Almost all types of organizational participation werestrongly protective against functional decline, but senior citizen clubs had the opposite relationshipin the crude model. Similarly, many types of organizational participation were protective against
functional decline in Model 1. In Model 2 for rural older people, participation in hobbies (HR = 0.76;
95% CI: 0.68–0.85), sports (HR = 0.79; 95% CI: 0.69–0.89), work (HR = 0.83; 95% CI: 0.76–0.91), andlocal community (HR = 0.86; 95% CI: 0.77–0.95) was found to be protective against the incidence of
decline. For urban older people, participation in work (HR = 0.80; 95% CI: 0.70–0.91), sports (HR =0.83; 95% CI: 0.77–0.91), and hobbies (HR = 0.90; 95% CI: 0.84–0.97) was found to be protective against
the incidence of decline.
Table 3. HRs for type of social participation (reference: nonparticipation in each organization).
Rural
Local Community
Hobby
SportsIndustry
Volunteer
CitizenWork
Urban
Local Community
Hobby
SportsIndustry
Volunteer
CitizenWork

Crude Model

Model 1Model 2

HR (95% CI)

HR (95% CI)

HR (95% CI)

0.59 * (0.54–0.65)
0.57 * (0.52–0.64)
0.62 * (0.55–0.70)
0.67 * (0.58–0.78)
0.62 * (0.54–0.72)
1.40 * (1.27–1.54)
0.48 * (0.42–0.54)

0.77 * (0.70–0.86)
0.61 * (0.60–0.75)
0.70 * (0.62–0.78)
0.92 (0.84–1.01)
0.77 * (0.67–0.89)
0.94 (0.85–1.03)
0.74 * (0.65–0.84)

0.86 * (0.77–0.95)
0.76 * (0.68–0.85)
0.79 * (0.69–0.89)
1.01 (0.87–1.18)
0.89 (0.77–1.03)
1.02 (0.93–1.13)
0.83 * (0.76–0.91)

Crude Model

Model 1Model 2

HR (95% CI)

HR (95% CI)

HR (95% CI)

0.70 * (0.65–0.75)
0.70 * (0.66–0.75)
0.60 * (0.55–0.65)
0.81 * (0.74–0.89)
0.66 * (0.60–0.73)
1.37 * (1.28–1.47)
0.50 * (0.46–0.55)

0.84 * (0.79–0.90)
0.78 * (0.73–0.84)
0.73 * (0.67–0.79)
0.90 (0.78–1.05)
0.80 * (0.73–0.89)
0.89 * (0.83–0.96)
0.80 *(0.73–0.87)

0.95 (0.88–1.01)
0.90 * (0.84–0.97)
0.83 *(0.77–0.91)
1.04 (0.95–1.15)
0.94 (0.85–1.04)
0.99 (0.92–1.07)
0.80 * (0.70–0.91)

HR: Hazard ratio; CI: confidence interval; Ref: reference. * p < 0.05. Model 1: Crude model + sex, age, equivalent
income, educational attainment, marital status, and self-reported medical conditions. Model 2: Model 1 + smoking,alcohol consumption, walking time (per day), frequency of going outdoors, depression, emotional support,
instrumental support, frequency of meeting friends, and IADL.

The results of the complete case analysis are shown in Table S3. In the complete case analysis
for rural older people, the HR for participation in work and local community was below 1.00, but thestatistical significance disappeared. Further, the results of the complete case analysis for urban older
people, excluding patients missing any of the variables used in the analysis, were similar to thosewhen the “missing” category was used in the analysis, to account for missing responses to questions.
The full modeling results in Model 2 were presented in Table S4. The result of the social networks,
such as emotional support, instrumental support, and frequency of meeting friends, added in Model 2,
was similar to the analysis of the number of organizations.
4. Discussion
To the best of our knowledge, this is the first longitudinal study to compare the relationshipbetween the number and type of organizations, including work, and incidence of functional decline inrural and urban areas separately.
In all, two findings were obtained from this study: (1) a “dose–response” relationship was seen
both among rural and urban areas, with progressively lower HRs as the number of different types of

Int. J. Environ. Res. Public Health 2020, 17, 617

9 of 13organizations increased; and (2) participation in sports, hobbies, and work were protective against
incidences of decline in both rural and urban areas. In this study the classification of rural andurban areas is as proposed by the OECD. Previous studies have used population density and nationalclassification; however this study adopted an international classification system. Even when classifying
areas by population density, the results of this study were almost the same.
The analysis of the number of organizations revealed the HRs of the number of types oforganizations progressively decreased as the number of participating organizations. This supports
previous studies, including those measuring other health outcomes [10,13,16–18]. In this study, HRs
were lower when participated in two or more types of organizations in rural areas than in urban areas.
The social relationships specific to rural areas may be the reason why older people living in these areas
need to join more than one organization. Previous studies have indicated that bonding social capitalcomprising a connection between community members is often stronger among rural older adults,
resulting in community strength [27,28]. In this study, participation in local community organizations
was higher in rural areas than in urban areas. However, excessive bonding social capital tends tohave negative effects [35]. According to the systematic review of the negative health effects of social
capital [35], there are downsides to social capital that emerge in the context of strong bonding social
capital, but not in weak bridging social capital. (1) Strong bonding ties impose heavy obligations
on community members by following a dominant social hierarchy and social norms, and it exclude
outsiders. (2) The lack of bridging SC is crucial in socioeconomically disadvantaged communities. (3)In such settings, the connection of members to outside sources of support is even more important. In
closed communities, such as those in rural areas, participation in more organizations may improve
bridging social capital. For the above reasons, older people in rural areas may benefit from participation
in a greater number of organizations.
Many types of organizational participation were protective against functional decline in Model 1,
which included factors such as age, equivalent income, educational attainment, marital status, andself-reported medical conditions. However, in Model 2, factors such as behavioral, psychosocial, andfunctional confounders, as well as participation in sports, hobbies, and work, were protective against
incidences of decline.
This is the first longitudinal study to compare work with other community organizations bydefining work as a type of social participation. Previous longitudinal studies focusing on the relationshipbetween work and health outcomes among older people have examined work alone [20,36,37], andcomparisons with other community organizations have been cross-sectional studies [38]. Given thecurrent challenges posed by a rapidly declining birthrate and aging population, it is necessary todevelop a social structure where many older people work [39]. Working support for older people
is expected to contribute not only to a substantial increase in the labor force but also to a decreasein the number of older people requiring care [39]. This study showed that working support andimprovement of working environment could be public health policies that would prevent the need forthe provision of long-term care in rural and urban areas. In longitudinal studies of work and healthoutcomes [20,36,37], work is generally considered good for health. However, poor-quality work [36] is
not good for health; therefore, additional analysis is necessary, since this research did not consider thetype of work.
The results indicating that participation in sports and hobby groups were protective against
disability were similar to previous studies [10]. According to this result, a good public health policy
would include local government provision of regular opportunities for social participation in sports
and hobbies in both rural and urban areas. Participation in sports and hobby groups has also beenreported to prevent other poor health outcomes [16,18,19]. Previous studies have shown that older
people in rural areas were unhealthier than older people in urban areas [20,24,29,30], but in this study,
there was no difference in the incidence of functional disability between older people in rural andurban areas. The reason may be that there was no difference in the urban–rural participation rates
in sports and hobby groups among the participants of this study. Even in rural areas, promoting

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participation in groups such as sports and hobbies groups could prevent the incidence of functional
decline. In Japan, the salon-type community intervention [40] has been implemented as one of theways to promote social participation. These salons, managed by local volunteers, are held once or
twice a month in communal spaces within walking distance of community members’ homes, and older
people can meet and interact with others through enjoyable, relaxing, and sometimes educational
programs [40]. Moreover, participation in local community organizations was only protective against
decline in rural older people in this study. In the scoping review by Carver et al. [41], older people
who lived in rural areas had many opportunities to engage in community-association activities, andthrough such social participation, a sense of belonging was created. They suggested that such social
participation is important for achieving successful aging in rural areas.
The preventive effects against functional decline of the number and types of social participation
were almost the same among both rural and urban areas in this study. Quite a few studies on
age-friendly cities showed that urban areas are suitable for active aging [42]. One of the reasons forthat may be a larger quantity of amenities and possibilities for social interactions/organizations andeasier access to those in urban areas compared to rural areas. It could be an effective intervention thatolder people move to urban areas when their health/physical ability starts to decline. Nowadays, thecompact city, i.e., located in the rural city center, but short-distance from urban functions, trials havebegun in Japan [43,44], and their effectiveness is expected to be verified.
This study has two strengths. First, this is the first study to target older people in manymunicipalities, including rural and urban areas, in contrast to previous studies that only focused on
the number and type of organization in which older people participated [10,13,16–18]. Second, thedata used in this study was collected over a long period (about six years) and excluded respondents
receiving long-term care within two years, thereby removing the possibility of reverse causality (i.e.,
the possibility that people who had a high risk of functional decline did not participate socially).
This study had three limitations. First, we did not consider the frequency of social participation.
It has been reported that the relationship between social participation and health outcomes differs
depending on the frequency of social participation [16,18,38]. However, this research emphasized acomparison between rural and urban areas in line with a previous study [10]. Second, we did notconsider the older people’s role of the organization they participated in, such as being a member or aleader. A leading role in an organization has an additional effect on social participation and healthoutcomes [15,45]. Finally, this study only focuses on the differences between rural and urban areas;
however, there may be other environmental characteristics to consider. The NuAge Study showedenvironmental factors associated with social participation of older people vary by living areas, such as
metropolitan, urban, and rural areas [29]. In Japan, it was reported that environmental factors such asaccess to facilities, shops, and parks and sidewalks were related to participation in sports groups [46].
Future longitudinal or interventional studies focusing on rural and urban environmental improvement
will be needed.
5. Conclusions
We compared the relationship between social participation, including work and incidence offunctional decline in rural and urban older people, to inform public health policies that would prevent
functional decline in older individuals residing in Japan. Participating in various organizations
protected older people from functional decline, and, thus, it might be essential to facilitate the benefitsof such participation to both rural and urban older people. Furthermore, participation in sports,
hobbies, and work was protective against incidences of decline in both rural and urban regions. For
both rural and urban older people, promoting social participation, such as sports and hobbies groups
and employment support, seems to be an important aspect of public health policies that would prevent
functional decline.

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Supplementary Materials: The following are available online at http://www.mdpi.com/1660-4601/17/2/617/s1,
Table S1: Complete case analysis: HRs for participation in one, two, and three or more different types oforganizations, Table S2: The full modeling results for participation in one, two, and three or more different typesof organizations in Model 2, Table S3: Complete case analysis: HRs for type of social participation (reference:
nonparticipation in each organization), Table S4: The full modeling results for HRs for type of social participation(reference: nonparticipation in each organization).
Author Contributions: Conceptualization and methodology, K.I., T.T., and S.K.; validation, K.I. and T.T.; formal
analysis, K.I.; data curation, T.T.; writing—original draft preparation, K.I.; writing—review and editing, T.T.
and S.K.; supervision, S.J., Y.N., and K.K.; project administration, K.K. All authors have read and agreed to the
published version of the manuscript.
Funding: This study used data from JAGES (the Japan Gerontological Evaluation Study). This study was supported
by Grant-in-Aid for Scientific Research (15H01972, 15H04781, 15H05059, 15K03417, 15K03982, 15K16181, 15K17232,
15K18174, 15K19241, 15K21266, 15KT0007, 15KT0097, 16H05556, 16K09122, 16K00913, 16K02025, 16K12964,
16K13443, 16K16295, 16K16595, 16K16633, 16K17256, 16K17281, 16K19247, 16K19267, 16K21461, 16K21465,
16KT0014, 17K04305, 17K34567, 17K04306, 25253052, 25713027, 26285138, 26460828, 26780328, 18H03018, 18H04071,
18H03047, 18H00953, 18H00955, 18KK0057, 18074040, 19H03901, 19H03915, 19H03860, 19K04785, 19K10641,
19K11657, 19K19818, 19K19455, 19K24060, 19K20909) from JSPS (Japan Society for the Promotion of Science);
Health Labour Sciences Research Grants (H26-Choju-Ippan-006, H27-Ninchisyou-Ippan-001 H28-Choju-Ippan-002,
H28-Ninchisyou-Ippan-002, H29-Chikyukibo-Ippan-001, H30-Jyunkankinado-Ippan-004, 18H04071, 19FA1012,
19FA2001) from the Ministry of Health, Labour and Welfare, Japan; the Research and Development Grantsfor Longevity Science from Japan Agency for Medical Research and development (AMED) (JP17dk0110027,
JP18dk0110027, JP18ls0110002, JP18le0110009, JP19dk0110034, JP19dk0110037), the Research Funding for Longevity
Sciences from National Center for Geriatrics and Gerontology (24-17, 24-23, 29-42, 30-30, 30-22); Open Innovation
Platform with Enterprises, Research Institute and Academia (OPERA, JPMJOP1831) from the Japan Scienceand Technology (JST); a grant from the Japan Foundation For Aging And Health (J09KF00804), a grant from
Innovative Research Program on Suicide Countermeasures (1-4), a grant from Sasakawa Sports Foundation, a
grant from Japan Health Promotion & Fitness Foundation, a grant from Chiba Foundation for Health Promotion& Disease Prevention, the 8020 Research Grant for fiscal 2019 from the 8020 Promotion Foundation (adopted
number: 19-2-06), a grant from Niimi University (1915010), grants from Meiji Yasuda Life Foundation of Healthand Welfare. The views and opinions expressed in this article are those of the authors and do not necessarilyreflect the official policy or position of the respective funding organizations.
Acknowledgments: We would like to thank the study participants. We would also like to thank Hanazato (Chiba
University) for teaching us the classification of rural and urban settings.
Conflicts of Interest: The authors declare no conflicts of interest.

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