Preventive Medicine Reports 18 (2020) 101065

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Preventive Medicine Reports
journal homepage: www.elsevier.com/locate/pmedr

Association between childhood socioeconomic position and sports group
participation among Japanese older adults: A cross-sectional study from the
JAGES 2010 survey
Mitsuya Yamakitaa,⁎, Satoru Kanamorib,c, Naoki Kondod, Toyo Ashidae, Takeo Fujiwaraf,
Taishi Tsujig, Katsunori Kondog,haCollege of Liberal Arts and Sciences, Kitasato University, Japan
Department of Preventive Medicine and Public Health, Tokyo Medical University, Japan
Human Resource Management Department, ITOCHU Techno-Solutions Corporation, Japand
Departments of Health and Social Behavior/Health Education and Health Sociology, School of Public Health, University of Tokyo, Japane
Institute of Social Science, University of Tokyo, Japanf
Department of Global Health Promotion, Tokyo Medical and Dental University, Japang
Center for Preventive Medical Sciences, Chiba University, JapanhCenter for Gerontology and Social Science, National Center for Geriatrics and Gerontology, Japanbc

ARTICLE INFOABSTRACT

Keywords:
Childhood disadvantage
Sports participation
EducationOlder people
Life course

Sports group participation may have greater effects on health outcomes than exercising alone. Unhealthy lifestyles were reported to be specifically associated with lower socioeconomic positions (SEPs), and child poverty
and the bipolarization of sports participation are currently major policy concerns in children. However, it remains unclear whether childhood SEP has any long-latency effect on sports group participation among older
Japanese. Data were obtained from the Japan Gerontological Evaluation Study 2010 project, which used selfreport questionnaires to survey individuals aged ≥65 years without disability from 27 municipalities(n = 23,320). According to their answers, respondents were assigned to one of three SEP groups: high, middle,
or low. Poisson regression with robust variance and multiple imputations was used to examine the association
between childhood SEP and sports group participation. After adjusting for health-related factors, low childhood
SEP was negatively associated with sports group participation in men (prevalence ratio [PR] = 0.82, 95%
confidence interval [CI] = 0.74–0.91) and women (PR = 0.88, 95% CI = 0.80–0.97). The PR was greatly
attenuated after adjusting for educational attainment in both men (PR = 0.92, 95% CI = 0.83–1.02) and women(PR = 0.98, 95% CI = 0.89–1.08), and the significant association disappeared. Low childhood SEP is thus
associated with lower sports group participation among older Japanese, though this may be attenuated byeducation. These findings suggest that it may be necessary to consider childhood SEP and the importance of
education to increase sports group participation at an older age.

1. Introduction
Childhood socioeconomic position (SEP) are powerful predictors ofhealth outcomes such as cardiovascular mortality, all-cause mortality(Cohen et al., 2010), and others (Galobardes et al., 2008; Rocha et al.,2019; Tamayo et al., 2010). Thus, since socioeconomic inequalities inchildhood health have multiple adverse health consequences in later
life, tackling these inequalities is an important public policy goal. Unhealthy lifestyles are reported to be correlated to a lower SEP (Foster
et al., 2018). Several systematic reviews suggest that childhood SEP is⁎

an important determinant of later physical activity (PA) in adulthood(Elhakeem et al., 2015; Juneau et al., 2015). However, as there arefewer studies on older adults, it is not still completely understoodwhether childhood SEP contributes to later PA in old age.
The health benefits of PA for people of all ages are widely established (Lee et al., 2012; World Health Organization, 2018). In particular, sports group participation includes not only physiological benefits through increased PA but also psychological and social benefits
through social participation beyond improvements attributed to individual types of PA (Eime et al., 2013; Farrance et al., 2016). A large

Corresponding author at: College of Liberal Arts and Sciences, Kitasato University, Sagamihara, Kanagawa 252-0373, Japan.
E-mail address: yamakita@kitasato-u.ac.jp (M. Yamakita).

https://doi.org/10.1016/j.pmedr.2020.101065
Received 15 April 2019; Received in revised form 28 January 2020; Accepted 8 February 2020
Available online 17 February 2020
2211-3355/ © 2020 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license(http://creativecommons.org/licenses/BY/4.0/).

Preventive Medicine Reports 18 (2020) 101065

M. Yamakita, et al.

cohort study of Japanese older adults showed that people who participated in sports groups showed a greater likelihood of avoiding functional disability than those who exercised alone (Kanamori et al.,2012), and that increasing the frequency of sports group participation
alleviates worsening depressive symptoms compared with increasing
daily walking time (Tsuji et al., 2017). In addition, another longitudinal
study revealed that exercising with others has a more positive impact
on mental well-being than exercising alone (Harada et al., 2019).
Moreover, randomized controlled trials showed that social relations in
exercise programs improved loneliness in older adults (Ehlers et al.,2017). This growing evidence suggests the possibility that sports group
participation has a greater effect on health than PA alone, such as
walking.
Understanding the association of childhood SEP with sports group
participation among older adults may provide important insights into
the pathways through which socioeconomic inequalities lead to lifelong adverse health consequences. It is particularly meaningful to examine this association among the Japanese people with a high relative
child poverty rate (one in seven) (Ministry of Health, Labour andWelfare, 2018; OECD, 2019), along with the ongoing bipolarization ofsports participation (Sasakawa Sports Foundation, 2015). However,most previous studies were based on American or European populations
and have shown the association with PA, and no studies have examined
whether childhood SEP later contributes to sports group participation
among older Japanese adults. Therefore, this study aimed to examine
the association between childhood SEP and sports group participation
among Japanese older adults.
2. Methods
2.1. Study participantsThis study utilized data from the Japan Gerontological Evaluation
Study (JAGES) (Kondo and Rosenberg, 2018). The JAGES was established in 2010 to evaluate the social determinants of healthy aging
among non-disabled people aged 65 or above, sampled from 31 municipalities in 12 of the 47 prefectures throughout Japan. From August2010 to January 2012, a self-administered questionnaire was mailed to169,215 community-dwelling individuals aged 65 or above who were
physically and cognitively independent and living independently.
Random sampling was used in the 16 large municipalities, while thequestionnaire was sent to all eligible residents in the 15 small municipalities. Of the eligible participants, 112,123 returned the questionnaire(66.3% response rate) (Fig. 1). The JAGES questionnaire consisted ofbasic questions to be answered by all respondents, as well as five separate modules that were randomly allocated to participants (20%probability for each module). Of these, one data module, which included items related to childhood SEP (23,320 respondents; 10,657
men and 12,663 women), was used in this study. In this cross-sectional
study, the analysis included 22,311 participants (10,276 men and
12,035 women) after excluding participants who reported limitations in
activities of daily living (n = 1,009), defined as being unable to walk,take a bath, or use the toilet without assistance, and who were mistakenly included in the study (Fig. 1). The JAGES protocol was reviewed and approved by the Ethics Committee on Research of Human
Subjects at Nihon Fukushi University (Approval No. 10–05). Written
informed consent was assumed from the voluntary return of the questionnaire.

Fig. 1. Flow chart of participant selection in the Japan Gerontological
Evaluation Study (JAGES) 2010 survey. *1 SEP: socioeconomic position. *2
ADL: activities of daily living.

participation and those who have participated in sports groups, theparticipants were classified into two groups: “Non-participants (never)”and “Participants (other than never),” in accordance with a previous
study (Ashida et al., 2016). Sports group participation included participation in not only team sports, but also sports organizations.
2.3. Childhood SEP
This was retrospectively assessed by recalled subjective SEP using
the following question: “How would you rate your socioeconomic status
at the age of 15 years according to standards at that time?” Responses
were arranged on a five-point Likert scale: “high,” “middle-high,”“middle,” “middle-low,” and “low.” These responses were allocated tothree categories: high (including “high” and “middle-high”), middle,
and low (including “middle-low” and “low”) to maximize the sample
size for each category. This method has previously been validated using
siblings’ data (Ward, 2011). Moreover, recalled subjective SEP inchildhood has shown a good correlation with adult height (as a proxyfor childhood nutrition) and/or homeownership (Fujiwara et al., 2014;
Tani et al., 2016; Yanagi et al., 2017).

2.2. Participation in sports groups

2.4. Covariates

This was assessed using the following question: “How often do you
participate in a sports group or club?” Those who answered, “almost
every day,” “2 or 3 times a week,” “once a week,” “once or twice amonth,” “a few times a year,” and “never.” To examine the differences
between people who have never been interested in sports group

Based on previous studies (Kanamori et al., 2012; Tani et al., 2016;
Yamakita et al., 2015; Yanagi et al., 2017), the following variables wereused as covariates. As health-related factors, age (continuous variables),current medical treatment (yes/no), instrumental activities of daily
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M. Yamakita, et al.

living (IADL), self-rated health, depression, body mass index (BMI),
smoking status (non-smoker, ex-smoker, current smoker), alcohol intake (non-drinker, ex-drinker, or current drinker), marital status(married, widowed, divorced, single), providing emotional social support (yes/no), and receiving emotional social support (yes/no) were
included. IADL was assessed using the Tokyo Metropolitan Institute ofGerontology Index of Competence (“good” [5 points] or “poor” [0–4
points]) (Koyano et al., 1991). Self-rated health is a subjective indicatorthat reflects the overall health status. In this study, we evaluated thisindicator by asking the following question: “How is your current healthstatus?” The possible responses were “excellent,” “good,” “fair,” and“poor.” Depression was measured using the short version of the Geriatric Depression Scale–15 (Japanese version) and was categorized into
three groups (“no” [0–4 points], “mild” [5–9 points], “moderate tosevere” [10–15 points]) (Nyunt et al., 2009; Schreiner et al., 2003).
Body mass index (BMI) was calculated from self-reported height andweight (kg/m2).

Table 1
Characteristics of participants of the Japan Gerontological Evaluation Study(JAGES) 2010 survey (n = 22,311).

Participation in sport group
Participants
Almost every day
2 or 3 times a week
Once a week
Once or twice a month
A few times a year
Non-participants (Never)MissingChildhood SEPHigh (high or middle-high)MiddleLow (middle-low or low)
Missing
Height*Tall
Middle-tallMiddleMiddle-short
Short
Missing
Educational level (years)
≥13
10–12
<10
MissingAnnual equivalized income(yen)≥4.00 million
2.00–3.99 million<2.00 million
Missing
Longest-held occupation
Non-manual
ManualNone
Missing

2.5. Mediators
According to a previous study, height (Fujiwara et al., 2014), educational attainment (Frenz et al., 2017; Galobardes et al., 2008; Lawlor
et al., 2006), and adulthood SEP (Cheval et al., 2018; Umeda et al.,2015) were used as potential mediators. These variables were assessedfrom the self-reported questionnaire. Height was used as a proxy for thechildhood nutritional environment and disease history (Silventoinen,2003), and was categorized into five groups at 5 cm intervals for eachsex, as shown in Tables 1-3. Previous studies confirmed a high correlation between self-reported and measured height among older peoplein Australia (Ng et al., 2011). Educational attainment was assessedcategorized into three groups by years of schooling (<10, 10–12,≥13 years). As indicators of adulthood SEP, current annual householdincome, which reflects SEP in old-age, and longest-held occupation,
which reflects SEP in middle-age, were included. Annual householdincome was calculated by dividing household income by the square rootof the number of household members and categorized into three groups(<2.00, 2.00–3.99, ≥4.00 million yen). Since previous studies haveconfirmed that the Japanese managerial/professional class appears topotentially experience a higher CHD risk compared to other occupations (Zaitsu et al., 2019), longest-held occupations were categorized
into three groups: non-manual occupations (professional, technical,
managerial work), manual occupations (clerical, sales/service, skilled/labor or agriculture/forestry/fishery worker, other), and no occupation(Tani et al., 2016).

Men (n = 10,276)

Women (n = 12,035)

n

(%)

n

(%)

2,450
228
647
497
474
604
6,084
1,742

(23.8)
(2.2)
(6.3)
(4.8)
(4.6)
(5.9)
(59.2)(17.0)

2,513
182
923
811
347
250
6,762
2,760

(20.9)
(1.5)
(7.7)
(6.7)
(2.9)
(2.1)
(56.2)(22.9)

937
3,740
5,057
542

(9.1)
(36.4)(49.2)
(5.3)

1,942
5,155
4,173
765

(16.1)(42.8)(34.7)
(6.4)

1,460
2,687
3,292
1,745
846
246

(14.2)(26.2)(32.0)(17.0)
(8.2)
(2.4)

553
2,051
3,986
3,394
1,517
534

(4.6)
(17.0)(33.1)(28.2)(12.6)
(4.4)

2,250
3,365
4,481
180

(21.9)(32.8)(43.6)
(1.8)

1,472
4,324
5,883
356

(12.2)(35.9)(48.9)
(3.0)

1,064
3,630
4,272
1,310

(10.4)(35.3)(41.6)(12.8)

1,005
3,401
4,820
2,809

(8.4)
(28.3)(40.0)(23.3)

3,367
5,905
54
950

(32.8)(57.5)
(0.5)
(9.2)

1,099
7,473
1,061
2,402

(9.1)
(62.1)(8.8)(20.0)

SEP: socioeconomic position.
*Height in cm (men, women): tall (≥170, ≥160), middle-tall (165–169.9,
155–159.9), middle (160–164.9, 150–154.9), middle-short (155–159.9,
145–149.9), short (<155, <145).

overestimate prevalence ratios (Barros and Hirakata, 2003; McNutt
et al., 2003).
Model 1 was first adjusted for health-related factors (age, current
medical treatment, IADL, self-rated health, depression, BMI, smoking
status, alcohol intake, marital status, providing or receiving emotionalsocial support). Next, Model 2 added height as a childhood circumstance to investigate how much it changes the association. In addition,
since several studies indicated that educational attainment resulted inattenuation of the associations between low childhood SEP and adverse
health outcomes later in life (Frenz et al., 2017; Galobardes et al., 2008;
Lawlor et al., 2006), educational attainment was further adjusted inModel 3 to examine whether it influences these associations. Additionally, adulthood SEP (annual equivalized income and longest-held
occupations) was added to Model 3 to investigate the effect on participants of all SEP (Model 4).
For sensitivity analyses (as a complete case analysis), different
multiple imputation analyses were performed for participants, which
excluded the missing values for sports group participation (outcome)and childhood SEP (explanatory) variables (Supplementary Tables 2
and 3). In addition, sensitivity analyses with the cut-off setting of “onceor twice a month” for sports group participation were performed(Supplementary Tables 4 and 5). All statistical analyses and multiple
imputations were performed using Stata/SE version 15.1 (StataCorp

2.6. Statistical analysis
Because sex has been shown to influence the relationship between
childhood SEP and physical inactivity (Cheval et al., 2018)—and because, as noted by Hawkes et al. (2013), disaggregation by sex is essential in health research—sex was controlled by conducting stratified
analysis.
To account for potential biases due to missing values, we conducted
multiple imputation analyses with 22,311 study participants, who experienced no limitations in activities of daily living. Following Sterne
et al. (2009), all variables included in the analysis, such as the outcome
variables, explanatory variables, and covariates, were imputed. Table 1
and Supplementary Table 1 presents the number of participants forwhom data was imputed (because of missing values). Under a missingat-random assumption, we created 20 imputed data using a chained
equation procedure (White et al., 2011). The estimated parameters
were combined using Rubin’s combination method (Rubin, 1987).
Poisson regression with robust variance was used to examine the association between childhood SEP and sports group participation due tothe relatively high prevalence of the latter (>10%): in such cases, odds
ratios obtained from logistic regression models can significantly3

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M. Yamakita, et al.

Table 2Adjusted prevalence ratio with 95% CI for association of childhood SEP with participation in sports groups in older Japanese men in the Japan Gerontological
Evaluation Study (JAGES) 2010 survey with all variable multiple imputations (n = 10,276).
Model 1PR (95% CI)

pModel 2PR (95% CI)

pModel 3
PR (95% CI)

pModel 4
PR (95% CI)

pReference
0.93 (0.84–1.02)
0.82 (0.74–0.91)

0.136<0.001

Reference
0.93 (0.84–1.03)
0.83 (0.75–0.92)

0.175<0.001

Reference
0.98 (0.89–1.09)
0.92 (0.83–1.02)

0.714
0.120

Reference
0.99 (0.89–1.09)
0.93 (0.84–1.04)

0.826
0.191

Reference
1.00 (0.92–1.11)
0.93 (0.84–1.02)
0.90 (0.80–1.01)
0.81 (0.69–0.95)

0.849
0.127
0.076
0.010

Reference
1.03 (0.93–1.13)
0.96 (0.87–1.06)
0.95 (0.85–1.07)
0.87 (0.75–1.02)

0.596
0.390
0.428
0.094

Reference
1.04 (0.94–1.14)
0.98 (0.89–1.07)
0.98 (0.87–1.10)
0.91 (0.77–1.06)

0.469
0.620
0.689
0.223

Reference
0.90 (0.83–0.97)
0.70 (0.64–0.76)

0.005<0.001

Reference
0.93 (0.86–1.01)
0.75 (0.69–0.82)

0.083<0.001

Annual equivalized income≥4.00 million yen
2.00–3.99 million yen<2.00 million yen

Reference
0.94 (0.86–1.04)
0.86 (0.78–0.95)

0.225
0.003

Longest-held occupation
Non-manual
ManualNone

Reference
0.86 (0.80–0.92)
0.69 (0.36–1.33)<0.001
0.267

Childhood SEP
High
MiddleLow
HeightTall
Middle-tallMiddleMiddle-short
Short
Education (years)
≥13
10–12
<10

SEP: socioeconomic position; PR: prevalence ratio; CI: confidence interval.
Model 1: Adjusted for health-related factors (age, medication, instrumental activities of daily living, self-rated health, depression, body mass index, smoking status,
alcohol intake, marital status, and social support).
Model 2: Model 1 + height.
Model 3: Model 2 + education.
Model 4: Model 3 + adulthood SEP (annual equivalized income, longest-held occupation).

Table 3Adjusted prevalence ratio with 95% CI for association of childhood SEP with participation in sports groups in older Japanese women in the Japan Gerontological
Evaluation Study (JAGES) 2010 survey with all variable multiple imputations (n = 12,035).
Model 1PR (95% CI)

pModel 2PR (95% CI)

pModel 3
PR (95% CI)

pModel 4
PR (95% CI)

pReference
0.98 (0.90–1.07)
0.88 (0.80–0.97)

0.668
0.011

Reference
0.99 (0.91–1.08)
0.90 (0.82–0.99)

0.785
0.025

Reference
1.04 (0.95–1.13)
0.98 (0.89–1.08)

0.433
0.724

Reference
1.03 (0.95–1.12)
0.98 (0.89–1.08)

0.485
0.674

Reference
1.11 (0.95–1.29)
1.01 (0.87–1.18)
0.99 (0.85–1.16)
0.85 (0.71–1.03)

0.205
0.837
0.906
0.091

Reference
1.12 (0.96–1.31)
1.04 (0.89–1.21)
1.03 (0.88–1.20)
0.90 (0.75–1.08)

0.150
0.608
0.717
0.242

Reference
1.12 (0.96–1.31)
1.04 (0.89–1.21)
1.03 (0.88–1.21)
0.90 (0.75–1.09)

0.154
0.624
0.693
0.280

Reference
0.91 (0.84–0.99)
0.74 (0.68–0.82)

0.032<0.001

Reference
0.92 (0.84–1.00)
0.77 (0.69–0.85)

0.057<0.001

Annual equivalized income≥4.00 million yen
2.00–3.99 million yen<2.00 million yen

Reference
1.09 (0.97–1.22)
0.96 (0.86–1.07)

0.144
0.495

Longest-held occupation
Non-manual
ManualNone

Reference
0.95 (0.86–1.05)
0.91 (0.79–1.04)

0.307
0.169

Childhood SEP
High
MiddleLow
HeightTall
Middle-tallMiddleMiddle-short
Short
Education (years)
≥13
10–12
<10

SEP: socioeconomic position; PR: prevalence ratio; CI: confidence interval.
Model 1: Adjusted for health-related factors (age, medication, instrumental activities of daily living, self-rated health, depression, body mass index, smoking status,
alcohol intake, marital status, and social support).
Model 2: Model 1 + height.
Model 3: Model 2 + education.
Model 4: Model 3 + adulthood SEP (annual equivalized income, longest-held occupation).
4

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M. Yamakita, et al.

LLC, College Station, TX, USA) with statistical significance inferred at a
two-tailed p-value of <0.05.

study of older adults found that lower childhood SEP groups were lesslikely to participate in sports groups. While both men and women
showed similar results, PR was consistently lower for men than women.
One possible explanation is a sex difference in the tracking of PA fromchildhood to adulthood. Several previous studies have reported thatmen show greater stability in tracking PA compared to women in allphases of the life course (Telama et al., 2014). This difference is supported by findings that many life events, such as pregnancy, getting
married, or having small children, have a greater influence on the PA ofwomen than on that of men (Allender et al., 2008; Engberg et al., 2012;
Telama et al., 2014). In addition, it has been suggested that men are
more likely to participate in PA than women in childhood (World
Health Organization, 2018), and also that men from lower SEP groups
are more likely than women to engage in risky health behaviors, such as
smoking, an unhealthy diet, and physical inactivity (Lawlor et al.,2006), which may be further explanations for the sex difference.
Our findings demonstrate that educational attainment has astronger effect than other factors in attenuating the association of low
childhood SEP with lower sports group participation in older adults.
Our findings showed that the PR for participation in sports groups remained almost unchanged after adjusting for height, a variable often
utilized as a proxy for childhood nutrition. In contrast, after adjustingfor educational attainment, the PR in the low childhood SEP group was
greatly attenuated. This is consistent with many previous studies(Elhakeem et al., 2015; Gidlow et al., 2006). Education is completed
early in the life course and associated with subsequent income, employment, social networks, and behaviors (Byhoff et al., 2017). Moreover, educational attainment is associated with numerous mental andphysical health outcomes (Byhoff et al., 2017; Kubota et al., 2017;
Ladin, 2008; Xu et al., 2016). Furthermore, those who achieve higher
educational attainment might have pursued a healthy lifestyle regardless of their personal income changes (Montez and Friedman, 2015).
Our findings support the importance of education in explaining the link
between childhood SEP and PA in adulthood (Elhakeem et al., 2015),
and show that education also explains the link between childhood SEP
and sports group participation in older adults. In the model, after adjusting for adulthood SEP, the PR remained almost unchanged. Thissuggest that education more strongly mediates the association between
childhood SEP and sports group participation in adulthood thanadulthood SEP. Thus, although education mediates the association between childhood SEP later-life sports participation, further study iscalled for to examine the indirect effects mediating educational attainment.
The mechanisms that explain the association between childhood
SEP and later-life sports participation are not fully understood.
However, given the similarity of the association between childhood SEP
and PA (Elhakeem et al., 2015), educational attainment that increases
health literacy may be one possible pathway (Montez and Friedman,2015). Lower childhood SEP tends to restrict future SEP (Byhoff et al.,2017), as mentioned above. Another pathway may be the tracking of
PA. Numerous studies consistently show that children from families
with low SEP participate less in sports groups compared to high- SEP
children (Stalsberg & Pedersen, 2010), and participation in PA andsports in childhood tends to be maintained throughout adulthood(Cleland et al., 2012; Telama et al., 2014) and thus old age. For thesereasons, intervention to enhance educational attainment and promote
sports in childhood may be an effective investment to increase sports
group participation in future older adults. These childhood investments
may lead to extending healthy life expectancy in the future. Additional
studies conducting a mediation analysis are needed in order to demonstrate these associations and clarify the mechanism driving childhood SEP and sports group participation later in life.

3. Results
Among all participants including missing values, 22.2% were sports
group participants (Table 1), and 49.2% of men and 34.7% of womenreported low or middle-low SEP in childhood, while 9.1% of men and16.1% of women reported high or middle-high childhood SEP. Amongmen, the percentages for 13 or more years’ educational attainment andnon-manual occupation were higher than among women.
The sociodemographic and health characteristics of the participants
are shown in Supplemental Table 1. The mean age (standard deviation)
was 73.9 (6.1) years (ranging from 65 to 101 years); 46.1% were men.
Among men, being married was higher than among women. By contrast, compared to men, more women were non-smokers, non-drinkers,
and had good IADL.
Table 2 shows the association between childhood SEP and theprevalence ratio (PR) of sports group participation in older men.
Compared with the high childhood SEP group, the PR of sports group
participation was 7% lower in the middle childhood SEP group and
18% lower in the low childhood SEP group in the health-related factorsadjusted model (Model 1). When analyses were controlled for height,
the point estimates of PR for participation in sports groups were veryslightly attenuated (Model 2). However, when analyses were controlled
for educational attainment, the PR in the childhood SEP group was
greatly attenuated (PR = 0.92, Model 3), and statistical significancedisappeared. This association was very slightly attenuated in the low
childhood SEP group after adjusting for adulthood SEP (Model 4).
When analyses were controlled for height, the point estimates of PR
for participation in sports groups were slightly attenuated, althoughstatistical significance remained the same (Model 2).
Among women, compared with the high childhood SEP group, thePR of sports group participation was 12% lower in the low childhood
SEP group in the health-related factors-adjusted model (Model 1 inTable 3). When analyses were controlled for height, the point estimatesof PR for participation in sports groups were slightly attenuated, although statistical significance remained the same (Model 2). However,when analyses were controlled for educational attainment, this association was no longer statistically significant (PR = 0.98, Model 3 inTable 3). The association was almost unchanged after adjusting for
adulthood SEP (Model 4 in Table 3).
The sensitivity analysis that excluded the missing values for sports
group participation and childhood SEP variables exhibited similar results with slightly smaller PRs (Supplemental Tables 2 and 3). The
sensitivity analyses with the cut-off setting of “once or twice a month”
revealed that the point estimates of PR exhibited similar results with acut-off setting of “participants or non-participants” among men andwomen (Supplemental Tables 4 and 5).
4. Discussion
This study investigated the association between childhood SEP andsports group participation in older adults. Its results demonstrate that
low childhood SEP is associated with lower sports group participationin older men, even after adjusting for health-related factors. After adjustment for educational attainment, the PR in the low childhood SEP
group was both greatly attenuated and more attenuated than when
adjusted for any other health-related or social characteristic in adulthood. This suggests that education may possibly shrink differences in
the association between childhood SEP and sports group participation
among older adults.
Despite inconsistencies in the results, prior evidence suggests that
low childhood SEP groups participate less frequently in leisure-time PA
in adulthood and early old age compared with high childhood SEP
groups (Elhakeem et al., 2015, 2017). Consistent with these studies, our

4.1. Strengths and lsimitations
This study’s strengths include the large sample, comprising older
5Preventive Medicine Reports 18 (2020) 101065

M. Yamakita, et al.

adults from across Japan, and the inclusion of a wide range of variables.
To our knowledge, no prior study has investigated the association between childhood SEP and sports group participation in older adults. Ourfindings establish childhood SEP as a new factor associated with sports
group participation among Japanese older adults.
However, several limitations of this study should be considered.
First, childhood SEP was evaluated retrospectively due to the crosssectional design and self-reported method and is therefore susceptible
to recall bias and could not establish causality. However, previous
studies have confirmed the validity of retrospectively evaluating subjective childhood SEP (Ward, 2011) and childhood neighborhood
context (Osypuk et al., 2015). In addition, the childhood subjective SEP
was found to correlate with other objective indicators, of deprivation,such as height and SEP achieved in adulthood (Sakurai et al., 2010).
Further studies are needed to examine whether there is a similar association between objective childhood SEP and participation in sports
groups in old age. Second, since all measures were self-reported and thehealth status of some items such as smoking status and alcohol intake
did not have detailed information, it is possible that measurement error
occurred. Third, for the sampling method, while randomization wasused in urban areas, the questionnaire was given to all eligible residents
in the rural areas due to the small number of residents. Fourth, thegeneralizability of the results requires attention since this study did notinclude older adults with long-term-care insurance. Finally, information
on participation in PA and in sports groups, including intensity, frequency, and types, was lacking. It would be useful to understand themechanisms whereby childhood SEP affects sports group participationin old age. Therefore, further robust studies, including participation in
PA and sports group participation at the early life stage, are needed toclarify this association.

Wakate-009, H25-Kenki-Wakate-015, H25-Choju-Ippan-003, H26Irryo-Shitei-003 [Fukkou], H26-Choju-Ippan-006, H27-NinchisyouIppan-001, H28-choju-Ippan-002, H28- Ninchisyou-Ippan-002, H29Chikyukibo-Ippan-001, H30- Kenki-Ippan-006, H30-JyunkankitouIppan-004, 19FA1012, 19FA2001) from the Ministry of Health, Labourand Welfare, Japan, the Research and Development Grants forLongevity Science from Japan Agency for Medical Research and development (AMED) (JP171s0110002, JP18le0110009,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), World Health Organization Centre for Health
Development (WHO Kobe Centre) (WHO APW 2017/713981), Open
Innovation Platform with Enterprises, Research Institute and Academia(OPERA, JPMJOP1831) from the Japan Science and Technology (JST),a grant from the Japan Foundation For Aging And Health(J09KF00804), and the Yamanashi Research Grant for Young Scholars.
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. The funding sources had no role instudy design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors declare that they have noconflicts of interest. The results of this study are presented clearly,
honestly, and without fabrication, falsification, or inappropriate data
manipulation.
Availability of data and materials
Data are from the JAGES project. All inquiries should be addressedto the data management committee via e-mail: dataadmin.ml@jages.net. All JAGES datasets have ethical or legal restrictions for publicdeposition due to the inclusion of sensitive information from humanparticipants.

5. Conclusion
This study demonstrated that low childhood SEP is associated withlower participation in sports groups among older adults, although thisassociation may be attenuated by education. Our study highlighted theimportance of education and implementing policies to tackle childpoverty in order to increase sports group participation across the life
course.

Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.org/10.1016/j.pmedr.2020.101065.
References

CRediT authorship contribution statement

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Mitsuya Yamakita: Conceptualization, Methodology, Formal analysis, Writing - original draft. Satoru Kanamori: Methodology,
Investigation, Writing - review & editing. Naoki Kondo: Data curation,
Formal analysis, Writing - review & editing, Supervision, Funding acquisition, Project administration. Toyo Ashida: Methodology, Writing review & editing. Takeo Fujiwara: Investigation, Methodology,
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Acknowledgments
This study used data from JAGES (the Japan Gerontological
Evaluation Study). This study was supported by MEXT (Ministry of
Education, Culture, Sports, Science and Technology-Japan)-Supported
Program for the Strategic Research Foundation at Private Universities(2009-2013), Grants-in-Aid for Scientific Research (18390200,
22330172, 22390400, 23243070, 23590786, 23790710, 24390469,
24530698, 24683018, 25253052, 25870573, 25870881, 26285138,
26882010, 15H01972, 15K03417, 17K01794, 17K19793, and
18H04071) from JSPS (Japan Society for the Promotion of Science),
Health Labour Sciences Research Grants (H22-Choju-Shitei-008, H24Junkanki [Seishu]- Ippan-007, H24-Chikyukibo-Ippan-009, H24-Choju6

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