International Journal ofEnvironmental Researchand Public Health

ArticleAssociation between Proximity of the Elementary School andDepression in Japanese Older Adults: A Cross-Sectional Study
from the JAGES 2016 Survey
Megumi Nishida 1,2, * , Masamichi Hanazato 3 , Chie Koga 3
1

2
3

4

*

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Citation: Nishida, M.; Hanazato, M.;
Koga, C.; Kondo, K. Association
between Proximity of the Elementary
School and Depression in JapaneseOlder Adults: A Cross-Sectional

and Katsunori Kondo 3,4Advanced Preventive Medical Sciences, Graduate School of Medical and Pharmaceutical Sciences,
Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba-shi, Chiba 260-8672, Japan
Takenaka Corporation, 1-13, 4-chome, Hommachi, Chuo-ku, Osaka 541-0053, Japan
Center for Preventive Medical Sciences, Chiba University, 1-33 Yayoi-cyo, Inage-ku, Chiba-shi,
Chiba 263-8522, Japan; hanazato@chiba-u.jp (M.H.); chiekoga@chiba-u.jp (C.K.); kkondo@chiba-u.jp (K.K.)
Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology,
7-430 Morikoka-cho, Obu-shi, Aichi 474-8511, Japan
Correspondence: nishida.megumi@chiba-u.jp; Tel.: +81-80-2454-9101

Abstract: Depression among older adults is one of the most critical public health issues. The proximity of elementary schools has been positively associated with neighborhood social cohesion andquality of life. However, no studies have identified an association between the proximity of elementary school and older adults’ mental health. Therefore, this study aimed to examine the association
between the proximity of elementary schools, one of the core facilities of neighborhood communities
in Japan, and depression in older adults. A total of 131,871 participants (63,430 men 73.7 ± 6.1 years,
68,441 women 73.8 ± 6.2 years) were analyzed from the Japan Gerontological Evaluation Study(JAGES) 2016 survey. Logistic regression analysis showed that there was no association between distance to elementary school and depression among males. However, among females, compared withthe participants living within 400 m from the nearest elementary school, the odds ratio of depression
for those living between 400 and 799 m and more than 800 m away were 1.06 (95% confidence
interval (CI) 1.00–1.12) and 1.07 (95% CI 1.00–1.15), respectively. The findings may be useful when
considering the design of communities around elementary schools and the planning of facilities as apopulation-based approach to promote mental health of older women.

Study from the JAGES 2016 Survey.
Int. J. Environ. Res. Public Health 2021,
18, 500. https://doi.org/10.3390/
ijerph18020500

Keywords: older adults; depression; neighborhood environment; elementary school proximity;
intergenerational exchange; age-friendly cities; Japan

Received: 20 November 2020
Accepted: 6 January 2021
Published: 9 January 2021
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distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

1. Introduction
The incidence of depression is increasing worldwide, and a World Health Organization(WHO) report estimated that more than 300 million people, equivalent to 4.4% of theworld’s population, had depression in 2017. The total population with depression increased
by 18.4% between 2005 and 2015 [1], and its prevalence is exceptionally high among older
adults [1]. The age-standardized incidence of depression worldwide is also increasing inregions with higher sociodemographic indicators [2]. Depression significantly reduces thequality of life and increases the risk of suicide, dementia, functional decline, elder abuse,and disability in older adults [3–7], and constitutes a significant public health issue.
In 2006, the WHO advocated for primordial prevention by recommending a changeof attitudes, behaviors, and social values, which can be achieved by encouraging positive
health behaviors, preventing the adoption of risk behaviors, eliminating established risk
behaviors, and promoting the concept of health as a social good [8]. Primordial prevention
requires a population-based approach, which targets the whole population irrespective of
the risk level, and this is different from the high-risk approach, which focuses only on individuals or population groups with the highest risk of disease. In addition, it must confront

Int. J. Environ. Res. Public Health 2021, 18, 500. https://doi.org/10.3390/ijerph18020500

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Int. J. Environ. Res. Public Health 2021, 18, 500

2 of 13the social, cultural, and community aspects of increased risk. Moreover, population-based
approaches achieve considerably greater health gains than high-risk approaches due to thelarger number of people involved [9].
These trends have intensified research on neighborhood environments that improvehealth [9,10]. There are many reports on the relationship between neighborhood environment
and physical health, such as the impact of parks, sidewalks, or other built environments on
physical activity and obesity rates [11,12]. There have also been studies on how the neighborhood environment affects mental health in older adults [13]. For example, the neighborhood
built environment comprising high walkability, better access to transportation and destinations, better street connectivity, traffic safety, large amount of greenspace, and the social
environment, such as high local social capital, is possibly related to improved mental healthin older adults [14–19].
To develop a healthy neighborhood environment, the WHO has published the agefriendly cities guide that promotes active aging of older adults [20]. This guideline has
indicators such as the accessibility of destinations, traffic safety, and social inclusion,and recommends the use of community facilities such as schools and recreation centers by
all community members, including older adults, to help them participate in community
activities and intergenerational exchange [21]. This implies that elementary schools can beconsidered components of age-friendly cities.
However, the relationship between elementary schools and the health of older adults
has not been sufficiently studied. For example, the proximity to an elementary school,
which represents the distance between the elementary school and the place of residence,has been shown to enhance neighborhood social cohesion as a place for increased interaction and group activities, improved quality of life, and increased children’s physicalactivity [22–26]. These participants may encompass the entire population of residents,
including older adults and children. Furthermore, none of the previous studies examined the relationship between proximity to an elementary school and older adults’ health,particularly depression.
Therefore, we hypothesized that proximity to an elementary school might be associated with improved mental health of older adults. In Japan, elementary schools are oneof the core facilities of a neighborhood community and are often used for local events,
such as elections and athletic events, which may enhance social capital that is said to be
associated with the health of individual or community health. In addition, the vicinity ofthe elementary schools may influence the safety of elementary school children on their
way to and from school. Furthermore, people residing near elementary schools have manypotential opportunities for daily contact with children, such as seeing, hearing, and talking
to elementary school students on their way to and from school, which may promote intergenerational exchange. The purpose of this study was to examine the relationship between
proximity to elementary schools and depression among Japanese older adults.
2. Methods
2.1. Population and Settings
This study used cross-sectional data from the Japanese Gerontological Evaluation
Study (JAGES) conducted in 2016 [27]. JAGES is an epidemiological research-based project
conducted every 3 years from 2010 and focuses on older adults from different regions
across Japan. It aims to build scientific evidence on the role of preventive medicine ina healthy aging society. Participants were older adults in a community (age ≥65 years)
who did not have physical or cognitive disabilities and had not received a certificationof long-term care [27,28]. Thirty-nine municipalities in 19 prefectures across Japan participated in this research project. The survey was a self-administered questionnaire thatwas returned by postal mail from October 3 to December 5, 2016. The questionnaire
forms were distributed to participants via the local government. Although the local governments were not randomly selected, they covered a wide range of characteristics interms of region and population size in Japan. The questionnaire examined health status,

Int. J. Environ. Res. Public Health 2021, 18, 500

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psychological status, social support, social participation, hobbies, frequency of outings,
life habitats, and demographic information, including sex, age, education level,
equivalent income (annual household income), marital status, living arrangement,
self-reported socioeconomic status, etc. A total of 180,021 data points (response rate:
70.2%) were identified in 2016. We excluded older adults who did not live independently
with regards to their daily living based on their response to the following questions evaluating independence of activities of daily living (ADLs): “Do you regularly receive care
and assistance for walking, bathing, toileting, etc.?”; the responses included (1) does notneed care or assistance, (2) needs care or assistance but does not receive it, and (3) needs
care or assistance but does receive it. We defined (3) as being dependent for activities
of daily living [29]. A total of 131,871 individuals without missing data for the outcome(i.e., depression) and residential information for the explanatory variables were includedin the analysis.
2.2. Outcome Variable
The outcome variable was depression. A short version of the Geriatric Depression
Scale (GDS-15) was used to identify depression, which was indicated by a GDS-15 score of
5 or more in this study [30,31].
2.3. Explanatory Variable
The explanatory variable was the distance from the respondents’ place of residence
to the nearest elementary school. For accuracy, we used the latitude and longitude ofa representative point in the city-level location reference information provided by the
Ministry of Land, Infrastructure, Transport and Tourism, rather than the respondent’s
residence address. The network distance from the representative point of the respondent’s residence to the nearest elementary school was calculated using ArcGIS ver. 10.3.1(Esri, Redlands, CA, USA) [32]. The network distances were categorized into four groups forevery 400 m (<400, 400–799, 800–1199, and ≥1200 m). The 400-m category was determinedon the basis of prior literature and guidelines on the proximity to the destinations [33–35].
Walking distance within five minutes of walking time was often represented by a radius
measuring 400 m among urban planners [36]. The neighborhood concept proposed byClarence Stein also suggests that elementary schools should be located at the center ofneighborhood units within a 400-m walking distance of all residents [37].
2.4. Covariates
According to the covariates that were evaluated in previous studies, we used basic demographic information, including sex (male/female), age (65–69, 70–74, 75–79,
80–84, or ≥85 years), education level (≤9, ≥10 years, or missing), equivalent income(low: ≤1.9; middle: 2.0–3.9; high: ≥4 million yen/year; and missing), marital status(married, unmarried, others, missing), employment status (employed, unemployed, or missing), and family structure (living alone, living with a family member, others (e.g., living ininstitutional care or missing)) as covariates [38–40]. Furthermore, we added the frequencyof outings (>4 times a week, 1–3 times a week, 1–3 times a month, less than a few times a
year, or missing), driving habits (no driving or driving), and frequency of meeting friends(>4 times a week, 1–3 times a week, 1–3 times a month, less than a few times a year, or missing) as covariates as these were previously reported to be associated with depression [41,42].
House-owned status (owned, rented or otherwise, or missing) and duration of residence(<20, 20, 20–39, 40–59, 60–79, ≥80 years, and missing) were added as variables that could
be assumed as confounders of residence and depression [43,44]. To adjust for urbanity,
the township population density was added to the covariate as quintiles [45,46].
2.5. Statistical Analysis
Descriptive statistics were used to summarize the participants’ characteristics, their number, and the sex-stratified percentage of subjects for each variable. Chi-square tests wereInt. J. Environ. Res. Public Health 2021, 18, 500

4 of 13

used to report sex-related differences for each variable. Logistic regression analysis was
performed to investigate the association between depression and accessibility to the elementary school. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated by sex
because of the possibility of sex-related differences in descriptive statistics. Stata 16.1/IC(StataCorp, College Station, TX, USA) was used for all statistical analyses.
3. Results
Table 1 shows the sex-stratified results of the descriptive statistics of the 131,871
individuals. The incidence of depression was higher in males than in females (22.9% and22.3%, respectively, p < 0.001). Among the older adults, 15.2% lived near an elementary
school (<400 m), and there were no sex-related differences in the proximity to an elementary
school. The percentage of the target population of females (51.9%) was higher than thatof males (48.1%). The results of the chi-square test showed that a higher proportion ofmales had more than 10 years of education (70.5% of male participants and 64.4% offemale participants, p < 0.001) and employment (31.4% male participants and 20.1% female
participants, p < 0.001). Moreover, men were more likely to be married (84.8% of males
and 61.6% of females, p < 0.001) and less likely to live alone (37.9% of males and 48.9%of females, p < 0.001). A higher percentage of male participants drove cars than female
participants (76.1% and 40.1%, respectively, p < 0.001). Regarding psychosocial factors,
female participants tended to meet with friends more frequently than the male participants(more than once a week: 48.9% and 37.9%, respectively, p < 0.001).
Table 1. Sex-stratified descriptive statistics for the total study population.
CharacteristicsMalen = 63,430

Depression, n (%)
Normal
48,896 (77.1%)
Depression
14,534 (22.9%)
Distance to elementary school, m, n (%)<4009533 (15.0%)
400–799
21,491 (33.9%)
800–1199
17,727 (27.9%)≥1200
14,679 (23.1%)
Population density, person/km2 , n (%)<1119
15,325 (24.2%)
1119–4985
15,842 (25.0%)
4986–9377
16,332 (25.7%)≥9378
15,931 (25.1%)
Age group, years, n (%)
65–69
20,322 (32.0%)
70–74
17,206 (27.1%)
75–79
13,869 (21.9%)
80–848214 (12.9%)≥853819 (6.0%)
Education level, years, n (%)≤918,142 (28.6%)≥1044,718 (70.5%)
Missing
570 (0.9%)
Equivalent income, million yen/year, n (%)
Low (≤1.9)
24,660 (38.9%)
Mid (2–3.9)
22,086 (34.8%)
High (≥4)
6495 (10.2%)
Missing
10,189 (16.1%)

Femalen = 68,441

χ2 Value(df)
7.3 (1) **53,184 (77.7%)
15,247 (22.3%)
1.4 (3)
10,402 (15.2%)
23,239 (34.0%)
18,955 (27.7%)
15,845 (23.2%)
16.0 (3) **16,934 (24.7%)
17,200 (25.1%)
17,000 (24.8%)
17,307 (25.3%)
11.9 (4) *21,471 (31.4%)
18,611 (27.2%)
15,358 (22.4%)
8757 (12.8%)4244 (6.2%)
584.7 (2) ***23,378 (34.2%)
44,081 (64.4%)
982 (1.4%)
1188.9 (3) ***26,325 (38.5%)
20,242 (29.6%)6036 (8.8%)
15,838 (23.1%)

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Table 1. Cont.
CharacteristicsMalen = 63,430

Marital status, n (%)
Married53,790 (84.8%)
Unmarried
8617 (13.6%)
Others457 (0.7%)
Missing
566 (0.9%)
Work status, n (%)
Employed
19,901 (31.4%)
Unemployed
37,341 (58.9%)
Missing6188 (9.8%)
Living arrangement, n (%)
Living alone
6247 (9.8%)
With family
48,700 (76.8%)
members
Other facilities
5820 (9.2%)
Missing2663 (4.2%)
Household status, n (%)
Owned
55,534 (87.6%)
Rental/others
7464 (11.8%)
Missing
432 (0.7%)
Duration of residence, years, n (%)<20
12,314 (19.4%)
20–39
19,323 (30.5%)
40–59
17,857 (28.2%)
60–79
10,840 (17.1%)≥802332 (3.7%)
Missing
764 (1.2%)
Outgoing frequency, n (%)≥4 times/week
42,713 (67.3%)
1–3 times/week
11,718 (18.5%)
1–3
1529 (2.4%)
times/month
A few
320 (0.5%)
times/year
Missing
537 (0.8%)
Driving habit, n (%)
No
15,170 (23.9%)
Yes
48,260 (76.1%)
Frequency of meeting friends, n (%)≥4 times/week
8474 (13.4%)
1–3 times/week
15,554 (24.5%)
1–3
12,727 (20.1%)
times/monthA few
19,227 (30.3%)
times/year
Missing
835 (1.3%)

Femalen = 68,441

χ2 Value(df)9297.9 (3) ***42,190 (61.6%)
25,086 (36.7%)
422 (0.6%)743 (1.1%)
3559.3 (2) ***13,740 (20.1%)
41,791 (61.1%)
12,910 (18.9%)2735.6 (3) ***12,564 (18.4%)
44,021 (64.3%)
7952 (11.6%)
3904 (5.7%)
91.1 (2) ***58,987 (86.2%)
8715 (12.7%)
739 (1.1%)
4403.8 (5) ***13,174 (19.2%)
19,698 (28.8%)
28,011 (40.9%)5900 (8.6%)
733 (1.1%)
925 (1.4%)
70.0 (4) ***44,935 (65.7%)
13,249 (19.4%)
1352 (2.0%)
250 (0.4%)481 (0.7%)
17,478.5 (1) ***41,030 (59.9%)27,411 (40.1%)
3544.5 (4) ***11,149 (16.3%)
22,331 (32.6%)
13,713 (20.0%)
11,898 (17.4%)
1176 (1.7%)*** p < 0.001, ** p < 0.01, * p < 0.05.

The OR and 95% CI for the association between living near an elementary school
and depression are shown in Table 2. Among male participants, there was no significant
association between distance to the elementary school and the incidence of depression.
However, among female participants, compared with the participants who lived lessthan 400 m away from the nearest elementary school, those who lived 400–799, 800–1199,
and >1200 m away were 1.06 (95% CI 1.00–1.12), 1.07 (95% CI 1.00–1.14), and 1.07 (95% CI
1.00–1.15) times, respectively, more likely to have depression. In terms of the association
between covariates and depression, the risk of depression was higher for both men andwomen with lower education and income, no job, unmarried, living alone, not living

Int. J. Environ. Res. Public Health 2021, 18, 500

6 of 13in an owned house, and no driving habits. Less frequent going out and seeing friends
was associated with a higher risk of depression for both men and women, but this trend
was more pronounced in women than in men. Considering age group as a covariate,
older age was associated with a lower risk of depression for both men and women aged
70 years and older compared to those aged 65–69 years. The risk of depression has beenreported to increase with age, although this trend was reversed when educational history,
income, employment, and marital status were included as covariates in this analysis [42,47].
Among the associations between covariates and depression, the trend for men and women
differed in duration of residence. Men aged 60 years and older were at a higher riskof depression than those who lived for less than 20 years, but there was no association
between duration of residence and depression in women.
Table 2. The sex-stratified association between depression and the explanatory variables.
Male

Characteristics
Distance to elementary school, m<400
400–799
800–1199≥1200
Population density, person/km2<1119
1119–4985
4986–9377≥9378
Age group, years
65–69
70–74
75–79
80–84
≥85
Education level, years≤9≥10
Missing
Equivalent income
Low (≤1.9 million yen/year)
Mid (2–3.9 million yen/year)
High (≥4 million yen/year)
Missing
Marital status
Married
Unmarried
OthersMissingWork status
Employed
Unemployed
Missing
Living arrangement
Living alone
With family members
OthersMissing
Household status
Owned
Rental/others
Missing

Femalen

OR

95% CI

p-ValuenOR

95% CI

p-Value

9533
21,491
17,727
14,679

1.00
1.01
1.02
1.00

0.95–1.07
0.96–1.09
0.93–1.07

0.773
0.568
0.923

10,402
23,23918,955
15,845

1.00
1.06
1.07
1.07

1–1.12
1–1.14
1–1.15

0.059
0.035
0.051

15,325
15,842
16,332
15,931

1.00
0.92
0.91
0.84

0.87–0.98
0.85–0.97
0.78–0.90

0.006
0.003
<0.001

16,934
17,20017,00017,307

1.00
0.93
0.88
0.87

0.87–0.98
0.83–0.94
0.81–0.93

0.008<0.001<0.001

20,322
17,206
13,869
8214
3819

1.00
0.93
0.91
0.95
0.87

0.88–0.98
0.86–0.96
0.88–1.01
0.79–0.95

0.007
0.001
0.117
0.003

21,471
18,611
15,358
8757
4244

1.00
0.94
0.91
0.96
0.98

0.89–0.99
0.86–0.96
0.90–1.03
0.90–1.07

0.024
0.001
0.243
0.675

18,142
44,718
570

1.00
0.75
0.95

0.72–0.79
0.78–1.16<0.001
0.626

23,37844,081
982

1.00
0.80
0.92

0.77–0.83
0.79–1.07<0.001
0.276

24,66022,0866495
10,189

1.00
0.61
0.44
0.87

0.59–0.64
0.40–0.48
0.82–0.92<0.001<0.001<0.001

26,325
20,2426036
15,838

1.00
0.65
0.45
0.86

0.62–0.68
0.42–0.50
0.82–0.90<0.001<0.001<0.00153,790
8617
457
566

1.00
1.50
1.50
1.44

1.39–1.62
1.22–1.84
1.20–1.74<0.001<0.001<0.001

42,19025,086
422
743

1.00
1.18
1.49
1.27

1.12–1.24
1.20–1.85
1.07–1.50<0.001<0.001
0.005

19,901
37,341
6188

1.00
1.29
1.36

1.23–1.35
1.26–1.46<0.001<0.001

13,74041,791
12,910

1.00
1.21
1.24

1.15–1.28
1.16–1.32<0.001<0.0016247
48,700
5820
2663

1.00
0.63
0.66
0.70

0.58–0.69
0.59–0.73
0.62–0.79<0.001<0.001<0.001

12,56444,021
7952
3904

1.00
0.82
0.88
0.88

0.77–0.87
0.81–0.94
0.80–0.96<0.0010.001
0.006

55,534
7464
432

1.00
1.62
1.27

1.52–1.73
1.02–1.58<0.001
0.032

58,987
8715
739

1.00
1.53
1.33

1.44–1.62
1.12–1.56<0.0010.001

Int. J. Environ. Res. Public Health 2021, 18, 500

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Table 2. Cont.
Male

Characteristics
Duration of residence, years
≤19
20–39
40–59
60–70
≥80
Missing
Outgoing frequency≥4 times/week
1–3 times/week
1–3 times/month
A few times/year
Missing
Driving habit
No
Yes
Frequency of meeting friends≥4 times/week
1–3 times/week
1–3 times/month
A few times/year
Missing

Femalen

OR

95% CI

p-ValuenOR

95% CI

p-Value

12,314
19,323
17,857
10,840
2332
764

1.00
0.98
0.95
1.09
1.18
1.26

0.93–1.04
0.90–1.01
1.02–1.17
1.05–1.33
1.06–1.49

0.572
0.127
0.015
0.007
0.009

13,174
19,69828,011
5900
733
925

1.00
0.98
0.97
0.97
1.08
1.16

0.93–1.04
0.92–1.03
0.89–1.05
0.90–1.29
0.99–1.35

0.515
0.335
0.483
0.413
0.068

46,463
13,684
2103
555
625

1.00
1.53
2.05
3.10
1.26

1.46–1.60
1.86–2.26
2.59–3.70
1.04–1.51<0.001<0.001<0.0010.017

49,337
15,933
2047
503
621

1.00
1.64
2.50
3.52
1.29

1.57–1.71
2.27–2.75
2.92–4.24
1.07–1.56<0.001<0.001<0.001
0.008

15,17048,2601.00
0.77

0.73–0.81<0.001

41,03027,4111.00
0.91

0.87–0.95<0.0019197
17,061
14,10022,005
1067

1.00
1.26
1.61
2.53
1.84

1.17–1.36
1.49–1.74
2.35–2.71
1.58–2.15<0.001<0.001<0.001<0.001

12,261
24,962
15,42814,247
1543

1.00
1.43
1.88
2.91
1.93

1.34–1.52
1.75–2.01
2.72–3.11
1.70–2.20<0.001<0.001<0.001<0.001

OR: Odds ratios; CI: Confidence interval.

4. Discussion
The present study confirmed the association between depression and basic demographic information as reported in previous studies: Frequency of going out and visiting
friends, home ownership, length of residence in a community, and population density.
For example, a significant association was found between higher education and higher
income and lower risk of depression. Being married, having a family, and having a job
were also associated with a lower risk of depression. Further, those who went out more
frequently and had frequent interactions with friends had a lower risk of depression.
Regarding the residential environment, the results suggest that owning a house and having
a longer residence duration may be protective factors for the risk of depression in men.
Although the association between population density and risk of depression was been
consistent, the present study showed an association between higher population density
and lower risk of depression [14,48].
The present analysis also suggests that older women who live near an elementary
school may have a lower risk of depression than those who do not, even after controllingfor basic demographic information such as frequency of going out, frequency of meeting
friends, household status, duration of residence, and population density, which are reported
to be associated with depression [31–39]. The ORs for the association between elementary
school proximity and depression were smaller than those of basic demographic informationand other data; however, the large number of participants analyzed in this study allowed
us to detect the effect. We discuss several mechanisms by which the environment near anelementary school may reduce the risk of depression among older women.
4.1. High Social Capital as the Center of the Community in the Elementary School Neighborhood Environment
Social capital may be related to the association between high proximity to an elementary school and low depression. Putnam defined social capital as “features of socialorganization, such as networks, norms, and social trust that facilitate coordination andcooperation for mutual benefit” [49]. In addition, evidence suggests that areas with higher
social capital, that is, more connected people and more cooperative behavior, have lower

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rates of anxiety, depression, and other psychiatric disorders. A study examining the relationship between public space and sense of community in Australian neighborhoods
reported a significant association between distance to the nearest school and sense ofcommunity, with greater distance to the nearest school being linked with a lower senseof community [50]. The authors considered that participation in more neighborhood andschool activities may contribute to expanding social networks, developing friendships,
and a greater sense of community. In contrast, an American study reported no linear association between the distance to a school and social cohesion, which is one index of social
capital [51]. The lack of association was assumed to be related to the means of transportation for getting to school. If a school has many students who commute to school by bus or
private transportation, there may be fewer opportunities to increase the school’s collective
effects. In other words, students are more likely to walk to school in their neighborhood
up to a certain threshold distance, and there is a positive relationship between social
cohesion and school proximity up to that threshold. However, the relationship betweensocial cohesion and school proximity may disappear farther away from that threshold [51].
Thus, we can speculate that the association between elementary school proximity andsocial capital is related to whether the school is within walking distance. More than 90% ofJapanese elementary school students walk to school [52]. This study found a higher odds
ratio for depression among female older adults living at a distance of more than 400 m
from an elementary school, which roughly supports the findings of previous studies.
Moreover, the Ministry of Health, Labour and Welfare suggests that elementary
schools can be a base for social capital because they are a venue for student activities and aplace for interaction between parents and community members. Moreover, it cites the factthat the activities of community organizations are often organized within the elementary
school district as a possible reason for the above factors [53]. A questionnaire surveyof Japanese adults older than 65 years reported that women were less likely to go out,
work, and engage in hobby activities than men. However, in contrast, women were more
likely to participate in neighborhood and community association activities [54]. Given thatparticipation in elementary school-based activities of community organizations is relevantin the mechanism by which high elementary school proximity contributes to improvedsocial capital, sex-related differences in community activity participation may explain theassociation, especially for women.
4.2. The Safety of the Elementary School Neighborhood Environment
The second factor regarding high proximity to elementary schools that was associatedwith lower depression among older adults can be assumed to be the high safety level inthe environment near elementary schools. The Cabinet Office in Japan promotes traffic
safety on school routes through the cooperation of residents, schools, boards of education,municipalities, and the police, which includes community-based supervision, police patrols, and traffic restrictions [55]. In Japan, school zones are designated as critical areas
for traffic safety policies to protect children from traffic accidents and are located within a
500-m radius of an elementary school on the school route. The school zone imposes various
traffic restrictions, such as installing new crosswalks and curb mirrors, sidewalk widening, one-way traffic and speed restrictions, and a ban on traffic during school hours [56].
These strategies have contributed to traffic-related safety in the elementary school neighborhood environment.
Perceived neighborhood traffic-related safety was negatively related to possible depression in older adults [57,58]. Furthermore, neighborhood risk perceptions are reported
to be higher in women than in men [59]. Thus, women may be more sensitive and stressed
about low traffic safety in their neighborhoods. The results of this study match those ofearlier studies about the high incidence of depression in women living at a greater distancefrom elementary schools.

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9 of 134.3. Potential for Contact and Intergenerational Interaction with Children in an Elementary School
Neighborhood Environment
A third factor that may contribute to less depression as elementary school proximity
increases is that more frequent contact with children in the elementary school neighborhood
environment may foster generativity. Erikson defined the concept of generativity as an interestin contributing to the well-being of others, especially the younger generation, and as a developmental challenge in middle age and later years [60,61]. Childbearing, parenting, and social
interactions possibly foster generativity by increasing interest in the younger generation’s
development and well-being [60,62,63]. Furthermore, higher levels of generational interest
and more frequent generational interactions, that is, greater generativity are associatedwith better mental health in old age [62–65]. According to the findings of a US study,
intergenerational exchange was associated with improved subjective health status andpsychological well-being [66]. In another study of older Japanese adults, positive intergenerational interaction was suggested to foster generativity and improve well-being inolder age [61]. Previous research reported that generativity tends to be higher in womenthan in men [67]. Another study has shown that generativity impacts subjective well-being,with the trend being more robust in women than in men [62]. The results of this study are
consistent with previous research findings, which showed that women tend to have greater
generativity and better well-being.
4.4. Strengths and Limitations
The strength of this study is that it is one of the few studies that investigated the relationship between elementary school proximity and depression among older adults in a large
epidemiological dataset covering both urban and rural areas. Understanding the relationshipbetween depression in older adults and their neighborhood environment is essential for
supporting community-dwelling older adults. Clarifying the health risk-preventing effects
of elementary school neighborhoods, which exist in tens of thousands of locations nationwide, may have implications for city design, such as developing senior living centers nearelementary schools.
Another strength of this analysis is that it uses objective data as an explanatory variable.
Subjective indicators using questionnaires have often been used to analyze environmental
factors; however, it has been noted that there are individual differences in the perceptionof subjectively measured environmental factors. The use of objective data as an indicatorfacilitates objective assessment and comparison of regional differences.
Nonetheless, this study has the following limitations. First, the cross-sectional designprecludes the identification of a causal relationship. The second limitation is that respondents
who needed long-term care and were not independent in their activities of daily living (ADLs)
were excluded from this analysis. The results are only for community-dwelling older adults
who can live independently before being certified for long-term care. The third limitationis that some of the residential data used in the analysis may differ from the actual address.
For privacy reasons, the participant’s residence point data were substituted with the latitude
and longitude of the representative points of the block-level location reference information
provided by the Ministry of Land, Infrastructure, and Transport. Therefore, the network
distance to the nearest elementary school, which is the explanatory variable in this study,
differs from the actual distance from the point of residence. However, since the averageradius at the block was 258.7 m, few respondents were expected to move across this
explanatory variable’s 400-m category. Finally, we cannot precisely discern how elementary
school proximity affects depression among older female respondents because our results
did not specifically identify the factors in the elementary school neighborhood environmentthat prevent depression among older women. It is unknown whether it is the elementary
school environment’s safety and walkability or influence by direct or indirect contact withchildren that contributes to the abovementioned effect. A more detailed analysis is neededin the future, as clarification of the mechanisms will allow more effective and specificinterventions to be implemented.

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Despite the limitations described above, this study presents findings that can help
create a community that prevents depression among older adults.
5. Conclusions
This study suggests that proximity to an elementary school may be a protective factor
for the mental health of community-dwelling older women living independently in the community, confirming part of our hypothesis. It may encourage participation in community
activities based on the elementary school and promotes interaction with children, as promotedby the age-friendly cities guide [20]. In the future, clarifying the mechanism of the protective
effect of elementary school proximity on depression among older women may help examine
specific interventions to prevent depression. Furthermore, examining the mechanisms underlying the gender differences in this study may help develop effective approaches for both
men and women. The above research to elucidate such mechanisms could contribute to a
design guide for age-friendly cities.
Author Contributions: Conceptualization, M.N.; methodology, M.N., C.K., M.H. and K.K.;
formal analysis, M.N.; investigation, K.K. (principal investigator for the JAGES project);writing—original draft preparation, M.N.; writing—review and editing, M.N., C.K. and M.H.;
visualization, M.N.; supervision, M.H.; project administration, K.K.; funding acquisition, M.H. andK.K. 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). This study
was supported by Grants-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, 19H03901, 19H03915, 19H03860, 19K04785, 19K10641, 19K11657, 19K19818,
19K19455, 19K24060, 19K20909, 20H00557, and 20K13721) from the 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-JyunkankinadoIppan-004, 18H04071, 19FA1012, and 19FA2001) from the Ministry of Health, Labour and Welfare,Japan; Research and Development Grants for Longevity Science from Japan Agency for Medical Research and Development (JP17dk0110027, JP18dk0110027, JP18ls0110002, JP18le0110009,
JP20dk0110034, and JP20dk0110037); Research Funding for Longevity Sciences from National Center for Geriatrics and Gerontology (24-17, 24-23, 29-42, 30-30, 30-22, and 20-19); Open Innovation
Platform with Enterprises, Research Institute and Academia (JPMJOP1831) from the Japan Scienceand Technology (JST) Center; 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 2019from the 8020 Promotion Foundation (adopted number: 19-2-06); a grant from Niimi University(1915010); and grants from Meiji Yasuda Life Foundation of Health and Welfare. The views andopinions expressed in this article are those of the authors and do not necessarily reflect the official
policy or position of the respective funding organizations.
Institutional Review Board Statement: This study was approved by the Ethics Committee on
Research of Human Subjects at Nihon Fukushi University (approval no. 10-05) and the Ethics
Committee at the Chiba University Faculty of Medicine (approval no. 2493).
Informed Consent Statement: Potential participants received written information on the purpose
and significance of the JAGES study; the burden, expected risks, and possible benefits of study
participation; voluntary consent and withdrawal of consent; and handling of personal informationand privacy protection, and that the submission of the completed survey form would be regarded as
their consent for study participation.
Data Availability Statement: Data is not suitable for public deposition due to ethical concerns.
Data are from the JAGES study. Requests for data may be sent to the data management committee:
dataadmin@jages.net.

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Acknowledgments: This study used data from the JAGES, conducted by the Nihon Fukushi University Center for Well-Being and Society for their research projects. We are extremely grateful to all
study participants for the use of their personal data. We would like to express our deepest gratitude
to everyone who participated and cooperated in the surveys.
Conflicts of Interest: Megumi Nishida is an employee of Takenaka Corporation.

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