International Journal ofEnvironmental Researchand Public Health

ArticleCommunity-Level Participation in Volunteer Groups andIndividual Depressive Symptoms in Japanese Older
People: A Three-Year Longitudinal Multilevel
Analysis Using JAGES Data
Motoki Tamura 1,2, * , Shinji Hattori 2,3 , Taishi Tsuji 3,4 , Katsunori Kondo 3,5 , Masamichi Hanazato 3 ,Kanami Tsuno 1 and Hiroyuki Sakamaki 1
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Citation: Tamura, M.; Hattori, S.;
Tsuji, T.; Kondo, K.; Hanazato, M.;
Tsuno, K.; Sakamaki, H.
Community-Level Participation in
Volunteer Groups and Individual
Depressive Symptoms in JapaneseOlder People: A Three-Year
Longitudinal Multilevel Analysis
Using JAGES Data. Int. J. Environ.
Res. Public Health 2021, 18, 7502.
https://doi.org/10.3390/
ijerph18147502
Academic Editors: Sara Rubinelli,Nicola Diviani and Claudia Zanini
Received: 25 May 2021
Accepted: 10 July 2021

5*

School of Health Innovation, Kanagawa University of Human Services, Kawasaki 210-0821, Japan;
ktsuno-tky@umin.ac.jp (K.T.); hiroyuki.sakamaki@nifty.com (H.S.)
Research Department, Institute for Health Economics and Policy, Tokyo 105-0003, Japan;
shin-ji.hattori@ihep.jp
Center for Preventive Medical Sciences, Chiba University, Chiba 263-8522, Japan;
tsu-ji.taishi.gn@u.tsukuba.ac.jp (T.T.); kkondo@kkondo.net (K.K.); hanazato@chiba-u.jp (M.H.)
Faculty of Health and Sport Sciences, University of Tsukuba, Tokyo 112-0012, Japan
Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology,
Obu 474-8511, Japan
Correspondence: d21020@hama-med.ac.jp; Tel.: +81-44-589-8100

Abstract: Background: The current study aimed to investigate the contextual effect of volunteer
group participation on subsequent depressive symptoms in older people. Methods: We analyzed thelongitudinal data of 37,552 people aged 65 years and older in 24 municipalities surveyed in the Japan
Gerontological Evaluation Study. Volunteer group participation of older people was assessed in 2013
by one question and depressive symptoms were assessed by the Geriatric Depression Scale 15 in 2016.
To investigate a contextual effect, we aggregated individual-level volunteer group participation byeach residence area as a community-level independent variable. We conducted a two-level multilevel
Poisson regression analysis using the Random Intercepts and Fixed Slopes Model. Results: Theaverage proportion of community-level volunteer group participation was 10.6%. The results of the
Poisson regression analysis showed that community-level volunteer group participation reduced therisk for the onset of depressive symptoms by 13% with a 10 percentage point increase in participation,
after adjusting for sex, age, population density, total annual sunshine hours and annual rainfall(incident rate ratio, 0.87; 95% confidence interval, 0.78–0.98). Conclusions: Older people living inareas with higher volunteer group participation had a lower risk of developing depressive symptoms
regardless of whether or not they participated in a volunteer group.

Published: 14 July 2021

Keywords: social capital; contextual effects; depression risk; social contagion
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1. Introduction
Depression is an important issue of public health in the world [1]. In particular, theprevalence of depression among aged 65 and older people is estimated to be between 5 and
10% and is projected to be the second leading cause of disease burden in this population by
the year 2020 [2,3]. Additionally, a few studies have suggested that depressive symptoms
in older people are strongly associated with being housebound and isolated, which maylead to a decline in physical and cognitive functions and eventually to premature death [4].
Depression in older people is one of the risk factors for ameliorable dementia and persistentdepression may lead to the development of dementia [5]. The proportion of people over
65 years of age in the total population, i.e., the aging rate, continues to increase, especiallyin developed countries. In Japan, the proportion of older people in the total population

Int. J. Environ. Res. Public Health 2021, 18, 7502. https://doi.org/10.3390/ijerph18147502

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Int. J. Environ. Res. Public Health 2021, 18, 7502

2 of 13is estimated to increase from 26.6% in 2015 to 38.1% in 2060 [6]. Thus, the prevention ofdepressive symptoms in the increasing number of older people is becoming an important
public health issue to reduce the risk of developing dementia or premature death.
Volunteer activities may have a potential protective factor for depression amongolder people. For instance, a four-year follow-up study of 6000 Japanese individuals aged
55 to 64 years reported that individual volunteer activities were significantly associatedwith a reduced risk of developing depression [7]. Volunteer activities are defined as“spontaneous activities that voluntarily contribute to others and society” [8] and previous
studies have reported that volunteer activities among older people are associated withpsychological health such as life satisfaction, depression, a sense of self-control and ahealthy self-esteem [9,10]. As a social mechanism, it is also hypothesized that volunteer
activities can expand human relationships and provide new social support and social
networks [11,12].
Recent studies have shown that people in areas with a greater social participation
have higher levels of health even if they are not in social participation because of the richsocial capital [13–15]. This characteristic of the community’s influence on an individual’s
health is called the contextual effect [16]. In other words, the higher the social capital at
the community level, the better the health of the individual possible. Community-levelsocial participation has been strongly or moderately associated with the subjective healthperceptions and health indicators of older people, such as depressive symptoms, even after
adjusting for individual-level social participation [17]. Another previous study suggested
that individual participation mediated the association between community-level social
capital and the onset of depressive symptoms [18]. Previous studies have reported thedifferences in the effects of the types of social participation [19] and individual volunteer
activities did not reduce depressive symptoms in individuals [19]. However, it is not clear
whether the areas with a high proportion of volunteer group participation have higher
levels of individual health or not, regardless of their individual participation in volunteer
groups.
The present study aimed to investigate whether older residents living in community
areas with higher volunteer group participation of older people are less likely to havesubsequent depressive symptoms compared with those living in community areas with alower prevalence of such participation after adjusting for individual-level volunteer group
participation. It was hypothesized that the proportion of community-level volunteer group
participation was negatively associated with the onset of depressive symptoms.
2. Materials and Methods
2.1. Study Design and Subjects
We used panel data from the Japan Gerontological Evaluation Study (JAGES) [20]. The
JAGES is an ongoing cohort study investigating social and behavioral factors related to theloss of health concerning a functional decline or cognitive impairment among individuals
65 years old or older. This cohort consists of physically and cognitively independent
individuals who have not received any required support and have not needed long-termcare certification under the Japanese long-term care insurance system.
The baseline survey was conducted in December 2013 via self-reported questionnaires
distributed by mail to 154,496 people 65 years or older selected from 24 municipalities inJapan. Among those who answered the baseline questionnaire (N = 103,664, response rate,
67.1%), 1192 were excluded because their residential area was unknown. In order to obtaina stable count for calculating community-level volunteer group participation proportions,
we then excluded 647 people living in the community areas with fewer than 30 respondents
per area [21]. Thus, 101,825 people were invited to answer the follow-up survey in 2016. In
the present study, one community area is equivalent to an elementary school district or ajunior high school district, which is a range of the community area that the older people inJapan can access on foot or by bicycle [22].

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Participation in the JAGES project was voluntary and those who agreed to participate
in the survey returned the survey questionnaire. The research plan was approved by
the Research Ethics Committee of the Graduate School of Health Innovation, Kanagawa
University of Human Services (approval number: SHI-19–006).
2.2. Measurements
2.2.1. Individual-Level Depressive Symptoms
Depression symptoms were measured by the 15-item Geriatric Depression Scale (GDS15) [23,24] both at the baseline and follow-up. GDS-15 assesses whether respondents haveexperienced depressive symptoms in their daily lives and a higher score equates to having
greater depressive symptoms. Response options were “yes” and “no” and those who had≥ 8 responses to GDS items both in the baseline and follow-up survey were included in theanalyses. Depressive symptoms are defined as having 5 points or higher of GDS-15 [25,26].
GDS-15 has been used in previous studies [23–25,27] to evaluate the risk of developing
mild or severe depression and good levels of validity and reliability have been reported.
For instance, Cronbach’s α coefficient for the internal consistency of the scale was 0.80 [23]and the overall sensitivity and specificity were found to be 0.97 and 0.95, respectively [23].
2.2.2. Individual- and Community-Level Participation in Volunteer Groups
Participants were queried on their frequency of volunteer group participation with
one question at the baseline survey in 2013. Response options were ≥ 4 days/week,
2–3 days/week, 1 day/week, 1–3day(s)/month, a few days/year or zero. In the present
study, participating in volunteer group activities was defined as participating in more than
1 day/month [28]. In previous studies, volunteer activity of more than 1 day/month was
found to be effective in maintaining daily functioning [28] but there is no consensus on the
optimal cutoff point.
At the individual level, individual participation in volunteer groups was used as anindependent variable. Community-level participation in volunteer groups was calculated
by averaging individual volunteer group participation in each community area and the
proportion was tabulated as an independent variable for the community areas. The proportion of community volunteer group participation was centralized and then multipliedby 10% so that an estimate per 10 percentage points for participation was calculated byfeeding the value into the model. Additionally, cross-level interaction terms were createdby multiplying the value centering on individual volunteer group participation by the
proportion of community volunteer group participation. As a result, three independent
variables were created: (1) the individual volunteer group participation, (2) the proportion of community volunteer group participation that was estimated at 10% and (3) thecross-level interaction terms.
2.2.3. Individual-Level Covariates
Individual-level covariates were sex (men and women), age (65–69, 70–74, 75–79,
80–84 and ≥ 85 years old), education (less than 6 years, more than 7 years and missing),
equivalent income (JPY < 2,000,000, JPY 2,000,000–3,999,999, JPY ≥ 4,000,000 and missing),
living alone (living with others, living alone and missing), drinking alcohol (never, past,current and missing), smoking (never, past, current and missing), chronic disease (yes andno) and body mass index (BMI (kg/m2 ) < 18.5, ≥ 18.5 and missing).
Having chronic disease was measured by asking participants if they were currently
receiving any medical treatment related to strokes, hypertension, diabetes or ear disease;response options were “yes” and “no”. These four diseases of missing values were set as
MNAR (Missing Not At Random) and were included in the “no” category. BMI (kg/m2 )was calculated using the height and weight that the participants answered in the questionnaire. Regarding BMI (kg/m2 ), previous studies suggest that there is no consensus
on the association between weight and depressive symptoms [29,30]. Based on this, three
categories of BMI (kg/m2 ) were used in the current study: thin(< 18.5), others (≥ 18.5) andInt. J. Environ. Res. Public Health 2021, 18, 7502

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missing [29]. If participants did not respond to the individual-level covariates, corresponding observations were assigned to “missing” categories.
2.2.4. Community-Level Covariates
Population density, sunshine hours and rainfall were used as covariates at the community level because these variables are associated with volunteer activities or depressive
symptoms [31–33]. For example, the volunteer participation rate rapidly declines when the
population density of residential areas exceeds 4000 people per square kilometer [31]. In
other words, the lower the population density of inhabitable areas is, the more active volunteer participation the residents engage in is. The population density per square kilometer(persons/km2 ) of the 522 community areas were in quartiles calculated and classified into
four category variables (< 5066, 5092–8929, 8968–11,282 and ≥ 11,300 persons/km2 ).
Previous research has suggested that weather changes such as sunshine and rainfall
are associated with mood disorders [32]. In the same manner, annual total hours ofsunshine for the 522 community areas were in quartiles calculated and classified into four
category variables (< 1912, 1912–2047, 2047–2075 and ≥ 2076 mean hours). The Japan
Meteorological Agency (JMA) has a definition for the sunshine duration. According to
the JMA’s website, the duration of sunshine is defined as the time when direct sunlightirradiates the ground surface and “direct irradiance is 0.12 kW/m2 or more” [34]. Annual
rainfall (mm) for the 522 community areas were in quartiles calculated and categorized
into four category variables (< 1483, 1483–1520, 1521–1621 and ≥ 1622 mm). Rainfall isdefined by the Ministry of Land, Infrastructure, Transport, and Tourism (MLIT). According
to the website of the MLIT, “(t)he amount of rainfall is the depth of water if the rainfall
does not run off anywhere and accumulates as it is,” and “(t)he amount of rainfall is therisk of rainwater not running off anywhere else, not evaporating, and not seeping into theground and so on, and how deep it goes” [35].
2.3. Statistical Analysis
To examine the contextual effects of volunteer group participation on the risk of individual subsequent depressive symptoms, we conducted a two-level multilevel Poisson
regression analysis (level 1 for individuals and level 2 for communities) using the Random
Intercepts and Fixed Slopes Model. The incidence rate ratio (IRR) and 95% confidence
interval (CI) were calculated. The reason for using the Poisson regression analysis was because the prevalence of depressive symptoms (10.4%) in the current study was greater than
10% [36]. Three models were created for the analysis. In Model 1, depressive symptoms as
the dependent variable, individual-level volunteer group participation, the proportion ofcommunity-level volunteer group participation and cross-level interaction terms as independent variables were entered, adjusted for age and sex. In Model 2, all community-levelcovariates were additionally added. In Model 3, other individual-level covariates wereadditionally added. IRRs and 95% CIs had calculated estimates per 10 percentage points ofcommunity volunteer group participation. All statistical analyses were performed using
STATA 16/SE (Stata Corp LLC, College Station, TX, USA).
3. Results
Figure 1 shows a flowchart of the participant inclusion and exclusion criteria. Amongthe 101,825 baseline eligible respondents, 61,267 answered the follow-up questionnaire in
December 2016 (follow-up rate: 59.8%). The number of residential areas was 792. Those
who had not died, not moved or not received any required long-term care certification
and were available for 3 years of follow-up were eligible for our study. Among them,
9231 people with a missing response for participation in volunteer activities in 2013,
3138 people with GDS-15 answers of ≤ 8 items (i.e., ≥ half of the items were missing) and
255 people who had depression, dementia and Parkinson’s disease in 2013 were excluded.
As our dependent variable was the onset of depressive symptoms, we also excluded people
who had depressive symptoms at the baseline (n = 9070). The final analytic participants

Int. J. Environ. Res. Public Health 2021, 18, 7502

5 of 13were 37,522 people (17,575 males and 19,977 females, mean age 72.6, mean (SD) 5.4 years
old) nested in 522 community areas.

Figure 1. Flow of participants in the cohort study.

Table 1 shows the descriptive statistics for each variable at the individual level. In 2013,
5830 (7.5%) participated in a volunteer group 1 day/month or more often. In 2016, 3908
(10.4%) newly-developed depressive symptoms. At the community level, participationin volunteer groups ranged from 1.1%–27.4%. For individual-level covariates, a higher
prevalence of depressive symptoms (≥ 10.4%) was observed in people who did not participate in the volunteer group, women, ≥ 75 years old, < 9 years of education, people withan equivalent income of < JPY 2 million, those currently receiving any medical treatment,
those living alone, past drinkers, non-drinkers, current smokers and BMI (kg/m2 ) < 18.5
or ≥ 25.

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Table 2 shows the IRRs and 95% CIs calculated by the multilevel Poisson regression
analysis. In Model 1, individual volunteer participation (IRR, 0.70; 95% CI, 0.63–0.78)
as well as the proportion of community volunteer group participation (IRR, 0.86; 95%
CI, 0.77–0.97) was statistically significant in lowering the risk of developing depressive
symptoms. In Model 2, after additionally adjusting for population density, annual sunshine
hours and annual rainfall, this association remained significant. In Model 3, after additionally adjusting for individual covariates, individual volunteer participation (IRR, 0.72; 95%
CI, 0.65–0.80) was statistically significant in lowering the risk of developing depressive
symptoms whereas the proportion of community volunteer group participation (IRR, 0.90;
95% CI, 0.80–1.01) was not statistically significant in lowering the risk of developing depressive symptoms. A greater age was statistically significant with the risk of developing
depressive symptoms in either model. The cross-level interaction term was not statisticallysignificant with a lower risk of developing depressive symptoms in either model.
Table 1. Descriptive statistics of individual-level covariates and incidence rates of depressive symptoms.

Individual-Level Variables
Total≥4 day/week
2–3 day/week
1 day/week
1–3 day/month
A few times a day/year
Zero
Man
Woman
65–69
70–74
75–79
80–84
≥85
<6
6–9
10–12
≥13
Other and missing<2,000,000
2,000,000–3,999,999≥4,000,000
Missing
Stroke no
Stroke yes
Stroke missing
Hypertension noHypertension yes
Hypertension missing
Diabetes no
Diabetes yes
Diabetes missing
Ear disease no
Ear disease yes
Ear disease missing

Total N

Developing Depressive Symptoms (GDS-15 ≥ 5) a
Number of Cases
Cumulative Incidence

37,552
3908
Frequency of participation in a volunteer group
509
36
977
74
1144
81
3200
248
3598
345
28,1243124
Sex
17,575
1788
19,9772120
Age, year
12,3461063
12,879
1241
7683
881
3489
511
1155
212
Education, year263
51
13,1651673
14,849
1454
8801
668
474
62
Annual equivalent income, JPY
13,905
1750
13,925
1214
4284
272
5438
672
Disease status in treatment
34,413
3624
868
112
2271
172
19,3542005
15,927
1731
2271
172
30,916
3225
4365
511
2271
172
33,451
3470
1830
266
2271
172

10.40%
7.10%
7.60%
7.10%
7.80%
9.60%
11.10%
10.20%
10.60%
8.60%
9.60%
11.50%
14.60%
18.40%
19.40%
12.70%
9.80%
7.60%
13.10%
12.60%
8.70%
6.30%
12.40%
10.50%
12.90%
7.60%
10.40%
10.90%
7.60%
10.40%
11.70%
7.60%
10.40%
14.50%
7.60%

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Table 1. Cont.

Individual-Level Variables

Total NNo
Yes
Missing

32,829
3383
1340

None
Past
Current
Missing

21,6901442
14,029
391

None
Past
Current
Missing

27,987
5909
3246
410

Developing Depressive Symptoms (GDS-15 ≥ 5) a
Number of Cases
Cumulative Incidence
Living alone
3327
405
176

10.10%
12.00%
13.10%

2397
207
1261
43

11.10%
14.40%
9.00%
11.00%

2863
611
382
52

10.20%
10.30%
11.80%
12.70%

279
2593
784
73
179

13.10%
9.90%
10.50%
10.80%
14.90%

Drinking status

Smoking status

BMI b (kg/m2 )<18.5≥18.5 and <25≥25 and <30≥30 and <50
Missing

2127
26,106
7441
679
1199

a GDS-15: Geriatric Depression Scale 15. b BMI: body mass index.

Table 2. Association of depressive symptoms with community-level and individual-level volunteer participation by amultilevel Poisson regression.
Model 1: Adjusted for Outcome, Individual-Level, Community-Level, Cross-Level, Age and Sex
Total, N = 37,552

IRR b

95% CI c

0.70(0.63–0.78)

0.86(0.77–0.97)

1.06(0.79–1.42)

1.00
1.13
1.35
1.71
2.12

(1.04–1.22)(1.23–1.47)(1.54–1.90)(1.83–2.46)

1.00
1.04
0.08

(0.98–1.11)
1.807

0.005

0.022

Fixed effects
Volunteer participation at the individual level
Proportion of volunteer participation at the community
level 10% estimation a
Cross-level interaction
Age, y
65–69
70–74
75–79
80–84
=85
Sex
Man
Woman
Intercept (SE) d
Random effectΩµ (SE) d

a . Cross-level interaction: community-level exposure 10% estimation × individual-level exposure.
b . IRR: incidence rate ratio.
c . CI: confidence interval.
d . SE: standard error.

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Table 2. Cont.
Model 2: Model 1 Adjusted for Community-Level Covariates
IRR b

Total, N = 37,552

Fixed effects
Volunteer participation at the individual level
0.70
Proportion of volunteer participation at the community
0.87
level 10% estimation a
Cross-level interaction
1.06
Population density, persons per kilometer squared of inhabitable area
Highest quartile (≥11,385)
1.00
Second quartile (9028–11,378)
1.00
Third quartile (5194–8977)
1.06
Lowest quartile (<5158)
1.21
Total annual sunshine hours
Highest quartile (≥ 2076)
Second quartile (2047–2075)
0.92
Third quartile (1911–2047)
0.97
Lowest quartile (<1911)
0.98
Annual Rainfall (mm)Highest quartile (≥1622)
1.00
Second quartile (1521–1621)
0.90
Third quartile (1483–1520)
0.98
Lowest quartile (<1483)
0.82
Age, y
65–69
1.00
70–74
1.13
75–79
1.34
80–84
1.70
=85
2.09
Sex
Man
1.00
Woman
1.04
0.08
Intercept (SE) d
Random effectCommunity-level variance0.036Ωµ (SE) d

95% CI c(0.63–0.77)(0.78–0.98)(0.79–1.43)(0.86–1.16)(0.91–1.22)(1.06–1.38)(0.81–1.03)(0.83–1.13)(0.87–1.11)(0.76–1.06)(0.84–1.14)(0.72–0.95)(1.04–1.22)(1.22–1.47)(1.53–1.89)(1.80–2.43)(0.98–1.11)
0.008

0.008

a . Cross-level interaction: community-level exposure 10% estimation × individual-level exposure.
b . IRR: incidence rate ratio.
c . CI: confidence interval.
d . SE: standard error.

Model 3: Model 2 Adjusted for Individual-Level Covariates
Total, N = 37,552

IRR b

Fixed effects
Volunteer participation at the individual level
0.72
Proportion of volunteer participation at the community
0.90
level 10% estimation a
Cross-level interaction
1.06
Population density, persons per kilometer squared of inhabitable area
Highest quartile (≥11,385)
1.00
Second quartile (9028–11,378)
0.99
Third quartile (5194–8977)
1.02
Lowest quartile (<5158)
1.12
Total annual sunshine hours
Highest quartile (≥2076)
1.00
Second quartile (2047–2075)
0.91
Third quartile (1911–2047)
0.96
Lowest quartile (<1911)
0.96

95% CI c(0.65–0.80)(0.80–1.01)(0.79–1.42)(0.85–1.15)(0.88–1.19)(0.99–1.28)(0.81–1.02)(0.83–1.12)(0.84–1.08)

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Table 2. Cont.
Model 3: Model 2 Adjusted for Individual-Level Covariates
IRR b

Total, N = 37,552

95% CI c

Annual Rainfall (mm)Highest quartile (≥1622)
Second quartile (1521–1621)
Third quartile (1483–1520)
Lowest quartile (<1483)

1.00
0.88
0.98
0.83

(0.75–1.04)(0.84–1.14)(0.73–0.96)

1.00
1.08
1.25
1.55
1.88

(1.00–1.18)(1.14–1.37)(1.39–1.73)(1.62–2.20)

1.00
1.02

(0.94–1.10)

Age, y
65–69
70–74
75–79
80–84
= 85
Sex
Man
Woman
Education, y=6<6
Other and missing=4,000,000<2,000,000
2,000,000-3,999,999
Missing
Stroke no
Stroke yes
Hypertension noHypertension yes
Diabetes no
Diabetes yes
Ear disease no
Ear disease yesNo
Yes (living alone)
Missing
None
Past
Current
Missing
None
Past
Current
Missing

=18.5
<18.5
Missing
Intercept (SE) eΩµ (SE) e

1.00
1.24
1.16
Annual equivalent income, JPY
1.00
1.83
1.35
1.72
Disease status in treatment
1.00
1.13
1.00
1.04
1.00
1.14
1.00
1.32
Family structure
1.00
1.07
1.13
Drinking status
1.00
1.21
0.86
0.78
Smoking status
1.00
1.10
1.29
1.30
BMI e (kg/m2 )
1.00
1.24
1.24
0.06
Random effectCommunity-level variance0.035(0.94–1.64)(0.85–1.58)(1.61–2.09)(1.19–1.54)(1.50–1.99)(0.93–1.36)(0.98–1.11)(1.04–1.30)(1.16–1.50)(0.97–1.20)(0.97–1.32)(1.04–1.41)(0.79–0.93)(0.51–1.18)(0.99–1.22)(1.15–1.44)(0.89–1.90)(1.10–1.41)(1.06–1.44)
0.007

0.008

a . Cross-level interaction: community-level exposure 10% estimation × individual-level exposure. b . IRR: incidence rate ratio. c . CI:

confidence interval. e . BMI: body mass index. SE: standard error.

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4. Discussion
In the present study, we investigated the association between the proportion ofcommunity-level volunteer group participation and an individual’s risk of developing
depressive symptoms. In the results, a higher proportion of community-level volunteer
group participation was found to lower the risk of developing depressive symptoms
among all older people, regardless of whether or not he/she participated in a volunteer
group. To the best of our knowledge, this is the first study that has shown the contextual
effect of volunteer group participation of older people on lowering the risk of developing depressive symptoms. Our findings, which showed that community-level volunteer
group participation reduces the risk of developing depressive symptoms, support previous
studies reporting that community-level social participation reduces the risk of developing
depressive symptoms [17].
Social contagion, one of the components of social capital, is a potential pathway that
explains the contextual effects of community-level volunteer participation on individuallevel health [37]. Social contagion refers to the notion that behaviors spread more quickly
through a tightly-knit social network [38]. Social contagion may prevent depressive symptoms in community areas where community-level volunteer group participation is moreprevalent by increasing the frequency of outings through volunteer activities of older people and increasing human contact opportunities. In addition, being proactive in volunteer
activities in the community areas may increase the chances of receiving social support fromothers. Increased opportunities to receive social support from others may be associatedwith a lower risk of developing depressive symptoms even if he/she does not participate
in volunteer activities. This is also in line with the studies reporting that social support isassociated with a lower risk of developing depressive symptoms [39–41].
The results of the present study also revealed that individuals who participated ina volunteer activity at least once a month had a 28% lower risk of developing depressive symptoms. The possible reasons why individual participation in volunteer activity
prevents the onset of depressive symptoms are because of the increase in physical activity due to volunteer group participation [42], the increase in social networks and social
support [39–41] and the acquisition of a sense of fulfillment and purpose in life throughobtaining a role [43].
In the present study, cross-level interactions were not statistically significant in any
model. In other words, the expected lower risk of developing depressive symptoms
associated with a higher proportion of community-level volunteer group participation was
not different between individual-level volunteer group participation and non-participation,suggesting the effect was homogeneous.
The results of the study also suggest the risk of developing depressive symptoms increases with aging. The risk of developing depressive symptoms in older people is known
to be influenced by chronic diseases such as hypertension and diabetes. This result is
indicative of previous studies supporting a higher risk of developing depressive symptoms
in older people [4]. As the results in this study showed that the risk of developing depressive symptoms was 8% higher in the age group 70–74 years compared with 65–69 years, if
volunteer group participation increased by 10% points in the community areas, the riskof developing depressive symptoms in the community’s older people as a whole would
decrease by 10% and the risk of developing depressive symptoms in the 70–74 year age
group could be almost the same or greater than that in the 65–69 year age group, which
could be equivalent to more than five years of mental health rejuvenation.
The strength of the present study is that it analyzed a large cohort sample of older
people aged 65 years and older from 24 municipalities across Japan. In addition, we
conducted a multilevel analysis of participation in volunteer groups and revealed theassociation with individual health; that is, the contextual effects considering the community
characteristics. It is also important to note that the contextual effect was confirmed by the
proportion of volunteer activities more than 1 day/month in the current study. This result
supports previous studies reporting that volunteer participation at least 1 day/month isInt. J. Environ. Res. Public Health 2021, 18, 7502

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good for health [28]. Volunteer group participation 1 day/month is feasible and could be agood implication for public health experts to prevent depression among older people.
However, several limitations of this study should be noted. First, the response andfollow-up rate were 67.1% and 59.8%, respectively. Therefore, there is a possibility of
selection bias because those dropouts during the follow-up were associated with required
long-term care certification or more serious conditions. Second, the questionnaire usedin the present study did not ask participants the type of volunteer activities undertaken.
Previous reports showed that Japanese older people tend to participate in volunteer activities such as academic, sports, culture and art promotion; community development;
disaster prevention and crime prevention; long-term care prevention; parenting and healthpromotion [44]. Future studies should ask the participants the type of volunteer activities
undertaken and investigate the community-level effect on individual health. Finally, depressive symptoms were not a clinical diagnosis but measured by a scale. However, a highsensitivity and specificity have been shown in previous studies [23] and are not likely tobias the results.
5. Conclusions
Older people living in community areas with a higher prevalence of volunteer group
participation of older people are less likely to have subsequent depressive symptoms by
10% compared with those living in a community area with a lower prevalence of volunteer
group participation. In other words, the study showed potential contextual effects in theprevention of developing depressive symptoms in older people. Promoting an increased
number of older people participating in volunteer groups may be effective as a population
approach to lower the risk of developing depressive symptoms among the older people
living in community areas.
Author Contributions: Conceptualization, M.T., S.H. and T.T.; data curation, T.T. and M.H.; formal
analysis, M.T.; methodology, M.T.; project administration, S.H.; supervision, T.T., K.K., K.T. and H.S.;
validation, M.T. and T.T.; writing—original draft, M.T.; writing—review and editing, T.T., K.K., M.H.,
K.T and H.S. All authors have read and agreed to the published version of the manuscript.
Funding: This study used data from the Japan Gerontological Evaluation Study (JAGES), whichwere supported by MEXT (Ministry of Education, Culture, Sports, Science and Technology, 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, 20H00557, 19K20909), Health Labour
Sciences Research Grants (H22-Choju-Shitei-008, H24-Junkanki (Seishu)-Ippan-007, H24-ChikyukiboIppan-009, H24-Choju-Wakate-009, H25-Kenki-Wakate-015, H25-Choju-Ippan-003, H26-Irryo-Shitei003 (Fukkou), H26-Choju-Ippan-006, H27-Ninchisyou-Ippan-001, H28-choju-Ippan-002,
H28-Ninchisyou-Ippan-002, H30-Kenki-Ippan-006, H30-Junkankitou-Ippan-004, 18H00953, 18H03047,
18H04071, 19FA2001, 19FA1012, 21GA0101, 21K11108, 21GA0101), Japan Agency for Medical Research and Development (AMED) (JP17dk0110017, JP18dk0110027, JP18ls0110002, JP18le0110009,
JP19dk0110034, JP20dk0110034, 20lk0310073h0001, 21lk0310073h00), the Research Funding forLongevity Sciences from the National Center for Geriatrics and Gerontology (24–17, 24–23, 29–
42, 30–22, 20–19, 21–20), the Research Institute and Academia (OPERA, JPMJOP1831) from the Japan
Science and Technology (JST). The views and opinions expressed in this article are those of the authorsand do not necessarily reflect the official policy or position of the respective funding organizations.
Institutional Review Board Statement: The study was conducted according to the Declarationof Helsinki and approved by The Research Ethics Committee of the Graduate School of HealthInnovation, Kanagawa University of Human Services (approval number: SHI-19–006 and 12 July2019).
Informed Consent Statement: Written informed consent has been obtained from the patient(s) topublish this paper.

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Data Availability Statement: Restrictions apply to the availability of these data. Data was obtained
from Japan Gerontological Evaluation Study.
Acknowledgments: The author would like to thank the study participants and the JAGES team forthe data collection. In addition, we would like to thank the JAGES team for covering the costs of thisresearch achievement.
Conflicts of Interest: The funders had no role in the design of the study; in the collection, analyses,
or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
The co-author, Masamichi Hanazato, has received grant support from the Takenaka Corporation,
AEON MALL, Inc. and AEON TOWN Co. In addition, the same author has received support fromthe Takenaka Corporation in the form of scholarship (incentive) donations and endowed courses
provided by the company. None of the authors have any other conflict of interest to disclose.

References
1.

2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.

14.
15.
16.
17.
18.
19.
20.

21.
22.

World Health Organization. Depression and Other Common Mental Disorders Global Health Estimates. 2017. Available online:
https://apps.who.int/iris/bitstream/handle/10665/254610/WHO-MSD-MER-2017.2-eng.pdf;#:~{}:text=
Commonmentaldisordersrefertoarangeofanxietyand,and3.6%25fromanxietydisorder (accessed on 20 May 2020).
Lopez, A.D.; Murray, C.C.J.L. The global burden of disease, 1990–2020. Nat. Med. 1998, 4, 1241–1243. [CrossRef]
Blazer, D.G. Depression in Late Life: Review and Commentary. J. Gerontol. Med. Sci. 2003, 58, M249–M265. Available online:
https://academic.oup.com/biomedgerontology/article/58/3/M249/684130 (accessed on 20 May 2020). [CrossRef] [PubMed]
Fiske, A.; Wetherell, J.L.; Gatz, M.; Fiske, A.; Wetherell, J.L.; Gatz, M. Depression in Older Adults. Annu. Rev. Clin. Psychol. 2009,
5, 363–389. [CrossRef] [PubMed]
Livingston, G.; Sommerlad, A.; Orgeta, V.; Costafreda, S.G.; Huntley, J.; Ames, D.; Ballard, C.; Banerjee, S.; Burns, A.; CohenMansfield, J.; et al. Dementia prevention, intervention, and care. Lancet 2017, 390, 2673–2734. [CrossRef]
White Paper on Aging Society. 2020. Available online: https://www8.cao.go.jp/kourei/whitepaper/w-2020/html/zenbun/
index.html (accessed on 9 December 2020).
Sugihara, Y.; Sugisawa, H.; Shibata, H.; Harada, K. Productive Roles, Gender, and Depressive Symptoms: Evidence From a
National Longitudinal Study of Late-Middle-Aged Japanese. J. Gerontol. Ser. B 2008, 63, P227–P234. [CrossRef] [PubMed]
Ministry of Health. Labour and Welfare. Volunteer Activities. Available online: https://www.mhlw.go.jp/stf/seisakunitsuite/bunya/hukushi_kaigo/seikatsuhogo/volunteer/index.html (accessed on 6 November 2020).
Fujiwara, Y.; Sugihara, Y.; Shinkai, S. Effects of volunteer activities on the mental and physical health of the elderly: Significanceof volunteer activities for the elderly in community health and welfare. Jpn. J. Public Health 2005, 52, 293–307. [CrossRef]
Thoits, P.A.; Hewitt, L.N. Volunteer Work and Well-Being. J. Health Soc. Behav. 2001, 42, 115–131. [CrossRef]
Musick, M.A.; Wilson, J. Volunteering and depression: The role of psychological and social resources in different age groups. Soc.
Sci. Med. 2003, 56, 259–269. [CrossRef]
Lin, N.; Ye, X.; Ensel, W.M. Social Support and Depressed Mood: A Structural Analysis. J. Health Soc. Behav. 2019, 40, 119–134.
[CrossRef]
Fujihara, S.; Tsuji, T.; Miyaguni, Y.; Aida, J.; Saito, M.; Koyama, S.; Kondo, K. Does Community-Level Social Capital Predict
Decline in Instrumental Activities of Daily Living? A JAGES Prospective Cohort Study. Int. J. Environ. Res. Public Health 2019, 16,828. [CrossRef]
Nakagomi, A.; Shiba, K.; Hanazato, M.; Kondo, K.; Kawachi, I. Does community-level social capital mitigate the impact ofwidowhood & living alone on depressive symptoms? A prospective, multi-level study. Soc. Sci. Med. 2020, 259, 113140. [CrossRef]
Tsuji, T.; Miyaguni, Y.; Kanamori, S.; Hanazato, M.; Kondo, K. Community-level Sports Group Participation and Older Individuals’
Depressive Symptoms. Med. Sci. Sports Exerc. 2018, 50, 1199–1205. [CrossRef]
Sauzet, O.; Leyland, A.H. Contextual effects on health inequalities: A research agenda. Eur. J. Public Health 2017, 27, 587–588.
[CrossRef]
Saito, M.; Kondo, N.; Aida, J.; Kawachi, I.; Koyama, S.; Ojima, T.; Kondo, K. Development of an instrument for community-level
health related social capital among Japanese older people: The JAGES Project. J. Epidemiol. 2017, 27, 221–227. [CrossRef]
Yamaguchi, M.; Inoue, Y.; Shinozaki, T.; Saito, M.; Takagi, D.; Kondo, K.; Kondo, N. Community Social Capital and Depressive
Symptoms Among Older People in Japan: A Multilevel Longitudinal Study. J. Epidemiol. 2019, 29, 363–369. [CrossRef]
Park, M.-J. Impact of social capital on depression trajectories of older women in Korea. Aging Ment. Health 2017, 21, 354–361.
[CrossRef]
Kondo, K.; Rosenberg, M. (Eds.) Advancing Universal Health Coverage through Knowledge Translation for Healthy Ageing Lessons
Learnt from the Japan Gerontological Evaluation Study: Lessons Learnt from the Japan Gerontological Evaluation Study; World HealthOrganization: Geneva, Switzerland, 2018. Available online: http://apps.who.int/bookorders (accessed on 20 May 2020).
Tsuji, T.; Kanamori, S.; Miyaguni, Y.; Hanazato, M.; Kondo, K. Community-Level Sports Group Participation and the Risk of
Cognitive Impairment. Med. Sci. Sports Exerc. 2019, 51, 2217–2223. [CrossRef] [PubMed]
Takagi, D.; Kondo, K.; Kawachi, I. Social participation and mental health: Moderating effects of gender, social role and rurality.
BMC Public Health 2013, 13, 701. [CrossRef] [PubMed]

Int. J. Environ. Res. Public Health 2021, 18, 7502

23.

24.

25.
26.
27.
28.

29.
30.
31.

32.
33.
34.
35.
36.
37.
38.
39.
40.
41.

42.

43.
44.

13 of 13

Nyunt, M.S.Z.; Fones, C.; Niti, M.; Ng, T.-P. Criterion-Based Validity and Reliability of the Geriatric Depression Screening
Scale (GDS-15) in a Large Validation Sample of Community-Living Asian Older Adults. Aging Mental Health 2009, 13, 376–382.
[CrossRef] [PubMed]
Schreiner, A.S.; Hayakawa, H.; Morimoto, T.; Kakuma, T. Screening for late life depression: Cut-off scores for the GeriatricDepression Scale and the Cornell Scale for Depression in Dementia among Japanese subjects. Int. J. Geriatr. Psychiatry 2003, 18,
498–505. [CrossRef]
Yesavage, J.A.; Brink, T.L.; Rose, T.L.; Lum, O.; Huang, V.; Adey, M.; Leirer, O. Geriatric Depression Scale. Psychopharm. Bull 1988,
24, 709–710. [CrossRef]
The Japan Geriatrics Society. Geriatric Depression Scale 15 (GDS15): Useful Tools for Medical Care of the Older People. Available
online: https://www.jpn-geriat-soc.or.jp/tool/ (accessed on 15 February 2021).
Tani, Y.; Sasaki, Y.; Haseda, M.; Kondo, K.; Kondo, N. Eating alone and depression in older men and women by cohabitation
status: The JAGES longitudinal survey. Age Ageing 2015, 44, 1019–1026. [CrossRef]
Nonaka, K.; Suzuki, H.; Murayama, H.; Hasebe, M.; Koike, T.; Kobayashi, E.; Fujiwara, Y. For how many days and what types ofgroup activities should older Japanese adults be involved in to maintain health? A 4-year longitudinal study. PLoS ONE 2017, 12,e0183829. [CrossRef] [PubMed]
Jung, S.J.; Woo, H.-T.; Cho, S.; Park, K.; Jeong, S.; Lee, Y.J.; Kang, D.; Shin, A. Association between body size, weight change anddepression: Systematic review and meta-analysis. Br. J. Psychiatry 2017, 211, 14–21. [CrossRef]
Nozaki, T. Diabetes mellitus, obesity and depression. In Proceedings of the 51st Annual Meeting of the Japanese Society ofPsychosomatic Medicine, Sendai, Japan, 26–27 June 2010; Volume 51, pp. 886–895.
Kuniaki, S. Factor Promoting Volunteer Activity in the Middle-Aged and the Elderly and Community Life Satisfaction: An Analysis
Based on JGSS-2006; JGSS Research Series No.5: Japan edition General Social Surveys Research Papers; Faculty of Business
Administration, Osaka University of Commerce: Osaka, Japan, 2009; Volume 8, pp. 41–65.
Sato, J.; Mizoguchi, H.; Fukaya, K. Weather change and Mood Disorder. Weather change and Mood Disorder. J. Jpn. Soc.
Biometeorol. 2011, 48, 3–7.
O’Hare, C.; O Sullivan, V.; Flood, S.; Kenny, R.A. Seasonal and meteorological associations with depressive symptoms in older
adults: A geo-epidemiological study. J. Affect. Disord. 2016, 191, 172–179. [CrossRef]
Japan Meteorological Agency. What Is the Definition of Sunshine Duration? Available online: https://www.jma.go.jp/jma/kishou/know/faq/faq5.html (accessed on 20 May 2020).
Ministry of Land, Infrastructure, Transport and Tourism. Available online: https://www.river.go.jp/kawabou/reference/index0
8.html (accessed on 20 May 2020).
Zhang, J.; Yu, K.F. What’s the relative risk? A method of correcting the odds ratio in cohort studies of common outcomes. J. Am.
Med. Assoc. 1998, 280, 1690–1691. [CrossRef] [PubMed]
Kawachi, I.; Berkman, L.F. Social Capital, Social Cohesion, and Health. In Social Epidemiology Second Edition; Berkman, L.F.,
Kawachi, I., Glymour, M.M., Eds.; Oxford University Press: New York, NY, USA, 2014; pp. 290–319. [CrossRef]
Christakis, N.A.; Fowler, J.H. The collective dynamics of smoking in a large social network. N. Engl. J. Med. 2008, 358, 2249–2258.
[CrossRef]
Murata, C.; Saito, Y.; Kondo, K.; Hirai, H. Relationship between social support and depression in community-dwelling elderly:
AGES Project. Gerontol. Soc. Sci. 2011, 33, 15–22.
Zunzunegui, M.V.; Béland, A.O.F. Support from children, living arrangements, self-rated health and depressive symptoms ofolder people in Spain. Int. J. Epidemiol. 2001, 30, 1090–1099. [CrossRef]
Kameyama, A.; Sakamoto, M.; Tanaka, E.; Sato, K.; Neichi, E.; Ohno, H. Relationships between social support and depression
among community-dwelling middle-aged and elderly people: Investigation in town A in Aomori Prefecture. Jpn. J. Stress Sci.
2007, 22, 191–199.
Shimanuki, H.; Honda, H.; Ito, T.; Kasai, T.; Takato, J.; Sakamoto, Y.; Inuzuka, G.; Ito, Y.; Arayama, N.; Ueki, S.; et al. Relationshipbetween volunteer activities to promote long-term care prevention and social and physical health and QOL of communitydwelling elderly. Jpn. J. Public Health 2007, 54, 749–759.
Hattori, S.; Ichida, Y.; Wada, Y.; Kondo, K. Volunteer Activities of the Elderly: Life Satisfaction, Higher Life Functions, and Background
Factors; Japan Longevity and Social Development Center, Research on Life Satisfaction: Tokyo, Japan, 2017; Volume 23, pp. 28–47.
National Council of Social Welfare, National Center for the Advancement of Volunteerism and Citizenship. Annual Report on
Volunteer Activities 2011; Shin Kasumigaseki Building: Tokyo, Japan, 2012.