Specific types of sports and exercise group participation and socio-psychological health in older people

ABSTRACT

Older people who engage in sports and exercise in a group render greater benefits for socio-psychological aspects compared to exercising alone. The aim of this study was to identify the prevalence of specific types of sports and exercise groups and the association with self-rated health, depressive symptoms, and frequency of laughter among community-dwelling older people. We used cross-sectional data from the 2016 Japan Gerontological Evaluation Study and analysed 63,465 males and 68,497 females aged ≥65 years. The top three most popular types among males were golf (11.3%), walking (8.4%), and ground golf (6.3%). Among females, the top three were fitness exercises (13.8%), walking (8.3%), and weight exercises (6.2%). After adjusting for potential confounders, engaging in golf with a group was significantly related with excellent self-rated health (prevalence ratio, PR, 1.31 in male and 1.78 in female), low depressive symptoms (PR, 0.70 and 0.71), and a high frequency of laughter (PR, 1.12 and 1.13). Among females, walking displayed a significant relationship with all three characteristics (PR, 1.23, 0.79, and 1.06, respectively). Golf in older males and walking in older females might be the first choice for an effective programme to spread sports and exercise groups within the older Japanese community.

KEYWORDS:

• Epidemiology
• subjective health
• depression
• laughing
• population density

1. Introduction

Engaging in group sports and exercise has been reported to reduce the risk of functional disability, (Kanamori et al., 2012) depressive symptoms, (Kanamori et al., 2018) and falls (Hayashi et al., 2018) among older people, compared to engaging in sports and exercise alone. The suspected mechanisms between sports and exercise group participation and health outcomes generally involve the benefits of physical activity (e.g., inducing good adherence and long duration), psychological factors (e.g., leading to enjoyment, enhanced self-esteem, and decreased stress), and social factors (e.g., receiving social support, social capital, and social influence) (Kanamori, Takamiya, & Inoue, 2015). Previous studies among middle-aged and older people revealed that exercising with others is significantly more effective for enjoyment, satisfaction, self-recognition, (Yokoyama et al., 2003) and mental well-being (Harada, Masumoto, & Kondo, 2019) compared with exercising alone. Participation in a sports and exercise group may also lower the risk of functional disability compared to other kinds of social activities (e.g., volunteer, local community, industry, or politics) (Kanamori et al., 2014). Growing evidence suggests that participation in group sports and exercise may have positive impacts on healthy ageing. However, the question of what specific types of sports and exercises are most common in older people participating in a group is unclear, and thus far, we have not found evidence examining health outcomes depending on specific activities. Several studies examined the health benefit of specific types of sports and exercise, regardless of individual or group participation (Koolhaas et al., 2018; Oja et al., 2017, 2015; Osuka et al., 2019, 2018). Those studies reported that cycling demonstrated the largest beneficial impact on health-related quality of life among middle-aged and older people, (Koolhaas et al., 2018) callisthenics was only significantly associated with preventing a decline in instrumental activities of daily living (IADL) among older people, (Osuka et al., 2018) and cycling, swimming, racquet sports, and aerobics significantly contributed to a lower risk of all-cause mortality among individuals aged 30–98 years (Oja et al., 2017).

In this cross-sectional study, we evaluated self-rated health, depressive symptoms, and frequency of laughter as socio-psychological health indicators based on specific group sports and exercise. Self-rated health and depressive symptoms are valid predictors of mortality regardless of other medical, behavioural, or psychosocial factors (Idler & Benyamini, 1997; Royall, Schillerstrom, Piper, & Chiodo, 2007). The potential benefit of laughter is increasingly recognised in relation to improved biomarkers and vascular function by moderating stress, improving mood, and enhancing immune system function (Gonot-Schoupinsky & Garip, 2018; Hirosaki et al., 2013). Frequency of laughter might be increased if one participates in a group rather than exercising individually due to the positive social interaction and enhanced enjoyment (Kanamori et al., 2015); however, these effects might differ with different sports and exercises.

The aim of this study was to identify: (1) the prevalence of specific sports and exercises engaged by older people in a group and (2) the association between the type of group sports and exercises and self-rated health, depressive symptoms, and frequency of laughter among community-dwelling Japanese older people. If we can identify specific types of group sports and exercises that are beneficial to socio-psychological health status, this evidence might encourage older people to participate in these activities, and stakeholders in the public health can focus on identifying the optimal intensity and amount of physical activity based on these specific activities.

2. Methods

2.1. Study design

We used cross-sectional data from the Japan Gerontological Evaluation Study (JAGES), which is an ongoing cohort study exploring social, environmental, and behavioural factors related to the loss of health concerning functional decline or cognitive impairment among individuals aged ≥65 years (Kondo, 2016). Between October 2016 and January 2017, we mailed a set of questionnaires to a total of 279,661 community-dwelling people aged ≥65 years, and these participants were selected from 39 municipalities including metropolitan, urban and semi urban, and rural communities in 18 prefectures from as far north as Hokkaido (i.e., the northernmost prefecture) and as far south as Kyushu (i.e., the southernmost region) in Japan. This was not a nationally representative sample because the participation of the municipal governments in the survey was voluntary. A random sample from the official residence registers in 22 large municipalities and a complete census of the older residents of the remaining 17 smaller municipalities were obtained. We received responses from 196,438 people, with a response rate of 70.2% (the range was 55.7%–80.5% in the 39 municipalities). We excluded: (i) 16,417 respondents who received a needed support and needed long-term care certification under the Japanese long-term care insurance system (i.e., loss of independence in IADL), (Tsutsui & Muramatsu, 2005) (ii) 22,290 respondents who reported limitations in IADL, defined as unable to walk, bathe, or use the toilet without assistance, to ensure that the sample was physically and cognitively independent, and (iii) 25,769 respondents whose status of sex, age, or extent of sports and exercise group participation was unknown. In total, we used data from 131,962 eligible respondents (63,465 males and 68,497 females). The JAGES participants were informed that participation in the study was voluntary and that completing and returning the questionnaire via mail indicated their informed consent to participate in the study. Ethical approval for the study was obtained from the Ethics Committee at Chiba University, Japan (Approval number: 2493) and the National Center for Geriatrics and Gerontology, Japan (Approval number: 992).

2.2. Types of sports and exercise group participation

Participants were queried on their frequency of sports clubs or group participation. The six possible responses were the following: ≥4 days/week, 2–3 days/week, 1 day/week, 1–3 days/month, a few times/year, or zero. For those who participated in a few times per year or often, they were asked “what type of sports do you currently do in those clubs or groups (multiple answers possible)?” Possible answers were (1) walking, (2) running and jogging, (3) fitness exercises, (4) weight exercises, (5) hiking, (6) golf, (7) ground golf, (8) gateball, (9) dance, (10) yoga, (11) aerobics, (12) petanque, (13) Tai Chi, (14) swimming, (15) aquatic exercises, (16) table tennis, (17) bowling, (18) bicycling, (19) tennis, and (20) other. Fitness exercises refer to low-to-moderate intensity exercises, such as callisthenics and seated exercises which mainly focus on health promotion and social interaction purposes. Ground golf is a new kind of golf game which simplifies the golf game, developed in Tottori, Japan by the Board of Education for the purpose of promoting lifelong sports, and this sport is widely popular among Japanese older people (Tottori Prefectural Government, 2017). Gateball is also a sport that originated in Japan, and this sport is familiar to older Japanese people; (Traphagan, 1998) Gateball is a team sport which competes for points by hitting a ball against a target using a stick. Detailed rules of these sports and how to play are shown in each reference.

2.3. Self-rated health, depressive symptoms, and frequency of laughter

We measured self-rated health using the question “how do you feel about your current health status: very good, good, somewhat poor, or poor?” “Very good” was categorised as excellent self-rated health. We assessed depressive symptoms using the 15-item Geriatric Depression Scale (GDS), (Burke, Roccaforte, & Wengel, 1991; Wada, Ishine, Kita, Fujisawa, & Matsubayashi, 2003) with a GDS score ≥5 defined as having depressive symptoms, in accordance with previous studies (Nyunt, Fones, Niti, & Ng, 2009; Schreiner, Hayakawa, Morimoto, & Kakuma, 2003). Internal consistency of the scale was good (Cronbach’s α = 0.80), (Nyunt et al., 2009) and the cut-off point was previously validated as a screening instrument for a major depressive disorder with 96% sensitivity and 95% specificity (Nyunt et al., 2009). We measured the frequency of laughter by the single-item question “how often do you laugh aloud in your daily life: almost every day, one to five times a week, one to three times a month, or almost none?” (Hayashi et al., 2016). “Almost every day” was categorised as high frequency of laughter.

2.4. Covariates

We evaluated variables previously reported to be correlated to sports group participation in older people as potential confounders (Yamakita, Kanamori, Kondo, & Kondo, 2015). Sex was controlled by conducting a stratified analysis. Age groups were categorised as 65–69, 70–74, 75–79, 80–84, and ≥85 years. Drinking status (none, past, or current), smoking status (none, past, or current), marital status (married or unmarried), and years of education (≥13, 10–12, 6–9 or <6 years) were categorised by each answer choice. Annual equivalent income was calculated by dividing household income by the square root of the number of household members and categorised into three groups: ≥$40,000; $20,000–$39,999; or <$20,000 per year (1 dollar ~ 100 yen). Disease status included the following: hypertension, stroke, cardiovascular disease, diabetes mellitus, hyperlipidaemia, musculoskeletal disorders, and cancer assessed with yes or no answer choices. Frailty status was assessed using The Kihon Checklist which consists of 25 items (yes or no) is divided into the following seven categories: physical strength, nutrition, eating, socialisation, memory, mood, and lifestyle (Satake et al., 2016). The score ranges from 0 (no frailty) to 25 (severe frailty), and status was categorised into the following three groups: robust (0–3), prefrailty (4–7), or frailty (8–25) (Satake et al., 2016). Covariates for which data was not collected due to lack of participant response were assigned to a “missing” category for that particular question because this avoids premature exclusion of a participant for failing to answer one or more questions corresponding to covariates. We obtained population density per km² of the inhabitable area for each municipality and categorised the density into three levels of urbanness: ≥4,000 persons per km² for metropolitan, 1,000–3,999 persons per km² for urban and semi urban, and <1,000 persons per km² for rural areas (Tsuji, Kondo, Kondo, Aida, & Takagi, 2018).

2.5. Statistical analysis

We calculated the proportion of participants for each type of sport and exercise stratified by sex, age group (65–74 and ≥75 years), annual equivalent income (≥$40,000; $20,000–$39,999; and <$20,000 per year), and level of urbanness (metropolitan, urban and semiurban, and rural area) to investigate the popular types of sports and exercises preferred by each population category.

A Poisson regression analysis was performed to examine the association of the types of sports and exercise groups with self-rated health, depressive symptoms, and frequency of laughter. Because the percentages of individuals with excellent self-rated health (14.8%), depressive symptoms (23.3%), and high frequency of laughter (41.2%) were ≥ 10%, adjusted odds ratio derived from logistic regression are no longer appropriate to approximate the PR (Zhang & Yu, 1998). We introduced each type of sports and exercise group participation separately (reference category: non-participation in each type of group) and the total frequency of sports and exercise group participation. We conducted a multivariate adjustment using an inverse probability weighting (IPW) method based as the primary tool to adjust for differences between the two groups (i.e., participation or non-participation in each type of sport and exercise group) (Curtis et al., 2007). The propensity scores to estimate the probability that older people would participate in each type of sport and exercise group were developed with logistic regression to adjust for between-group differences in characteristics of the participants (provided in the covariates section). This approach was implemented to create balance and involved weighting each participant in each type of group by the inverse of the probability that they would participate in the group and weighting each participant who did not participate in the group by the inverse of the probability that they would not participate in the group. The PRs and their 95% confidence intervals (95% CIs) were calculated. We also conducted Poisson regression analyses with traditional regression modelling without propensity scores as sensitivity analyses. We used STATA 14/MP (StataCorp, College Station, TX, USA) for all statistical analyses with the statistical significance set at P < .05.

3. Results

Table 1 shows the descriptive statistics of participants by sex. Table 2 and Appendix Table 1, 2, and 3 show the proportions of older participants for each type of sports and exercises. Of 63,465 male and 68,497 female respondents, 21,346 (33.6%) and 25,592 (37.4%) participated in a sports and exercise group a few times per year or more. Golf was the most popular activity in males, except for those 75 years or older and in low-income categories, in which the highest frequency of the type of activity was walking. Except for those two categories and male participants living in a rural area, walking was the second most popular activity. Ground golf and weight exercises were also generally popular types in each category among male participants. Among females, fitness exercises were the most frequent in all categories and walking was the second most frequent type in all categories, except for the high-income category. Weight exercises, ground golf, dance, and yoga were also generally popular types in each category among female participants.

Table 1. Characteristics of participants.

	Male (n = 63,465)		Female (n = 68,497)
	n	%	n	%
Participating in a sports and exercise group
Zero	42,119	66.4%	42,905	62.6%
A few times/year	4,354	6.9%	1,590	2.3%
1–3 days/month	5,031	7.9%	4,179	6.1%
1 day/week	3,442	5.4%	6,492	9.5%
2–3 days/week	5,162	8.1%	8,728	12.7%
≥4 days/week	3,357	5.3%	4,603	6.7%
Age (years)
65–69	21,064	33.2%	22,923	33.5%
70–74	17,554	27.7%	19,247	28.1%
75–79	13,858	21.8%	15,129	22.1%
80–84	7,674	12.1%	7,875	11.5%
≥85	3,315	5.2%	3,323	4.9%
Self-rated health
Non-excellent	53,745	84.7%	57,805	84.4%
Excellent	9,399	14.8%	10,088	14.7%
Missing	321	0.5%	604	0.9%
Depressive symptoms
No (GDS < 5)	49,271	77.6%	53,858	78.6%
Yes (GDS ≥ 5)	13,269	20.9%	13,728	20.0%
Missing	925	1.5%	911	1.3%
Frequency of laughter
5 days/week or less	39,393	62.1%	35,367	51.6%
Almost every day	22,831	36.0%	31,504	46.0%
Missing	1,241	2.0%	1,626	2.4%
Drinking status
None	15,250	24.0%	48,558	70.9%
Past	9,130	14.4%	4,203	6.1%
Current	38,177	60.2%	13,868	20.3%
Missing	908	1.4%	1,868	2.7%
Smoking status
None	16,261	25.6%	60,627	88.5%
Past	34,917	55.0%	4,180	6.1%
Current	11,612	18.3%	2,767	4.0%
Missing	675	1.1%	923	1.4%
Marital status
Married	54,184	85.4%	42,794	62.5%
Unmarried	8,827	13.9%	25,079	36.6%
Missing	454	0.7%	624	0.9%
Education (years)
≥13	21,666	34.1%	15,006	21.9%
10–12	24,366	38.4%	31,127	45.4%
6–9	16,589	26.1%	20,962	30.6%
<6	325	0.5%	509	0.7%
Missing	519	0.8%	893	1.3%
Annual equivalent income
≥$40,000	6,656	10.5%	6,085	8.9%
$20,000–$39,999	22,839	36.0%	21,212	31.0%
<$20,000	24,274	38.3%	25,910	37.8%
Missing	9,696	15.3%	15,290	22.3%
Disease status in treatment
Hypertension (no)	34,536	54.4%	37,981	55.5%
Hypertension (yes)	27,523	43.4%	27,982	40.9%
Stroke (no)	59,740	94.1%	65,004	94.9%
Stroke (yes)	2,319	3.7%	959	1.4%
Cardiovascular disease (no)	54,246	85.5%	61,738	90.1%
Cardiovascular disease (yes)	7,813	12.3%	4,225	6.2%
Diabetes mellitus (no)	51,802	81.6%	59,667	87.1%
Diabetes mellitus (yes)	10,257	16.2%	6,296	9.2%
Hyperlipidaemia (no)	55,388	87.3%	54,711	79.9%
Hyperlipidaemia (yes)	6,671	10.5%	11,252	16.4%
Musculoskeletal disorders (no)	59,519	93.8%	55,713	81.3%
Musculoskeletal disorders (yes)	2,540	4.0%	10,250	15.0%
Cancer (no)	58,983	92.9%	63,817	93.2%
Cancer (yes)	3,076	4.9%	2,146	3.1%
Missing	1,406	2.2%	2,534	3.7%
Population density per inhabitable area (inhabitants per square kilometre)
≥4,000	27,758	43.7%	29,990	43.8%
1,000–3,999	20,688	32.6%	21,913	32.0%
<1,000	15,019	23.7%	16,594	24.2%
GDS: Geriatric Depression Scale.

Table 2. The top five most popular types of sports and exercise groups in each population category.

	Male						Female
	All (n = 63,465)		65–74 years (n = 38,618)		≥75 years (n = 24,847)		All (n = 68,497)		65–74 years (n = 42,170)		≥75 years (n = 26,327)
Rank	Type	%	Type	%	Type	%	Type	%	Type	%	Type	%
1	Golf	11.3%	Golf	12.7%	Walking	10.1%	Fitness exercises	13.8%	Fitness exercises	13.3%	Fitness exercises	14.7%
2	Walking	8.4%	Walking	7.3%	Ground golf	10.1%	Walking	8.3%	Walking	8.2%	Walking	8.4%
3	Ground golf	6.3%	Weight exercises	4.0%	Golf	9.2%	Weight exercises	6.2%	Weight exercises	7.2%	Ground golf	6.7%
4	Weight exercises	3.6%	Ground golf	3.8%	Fitness exercises	3.9%	Ground golf	4.5%	Yoga	4.6%	Weight exercises	4.6%
5	Fitness exercises	2.8%	Hiking	2.7%	Weight exercises	3.0%	Dance	4.0%	Dance	4.1%	Dance	3.7%
	Any of	33.6%	Any of	33.0%	Any of	34.6%	Any of	37.4%	Any of	38.5%	Any of	35.6%
Stratified by annual equivalent income
	≥$40,000 (n = 6,656)		$20,000–$39,999 (n = 22,839)		<$20,000 (n = 24,274)		≥$40,000 (n = 6,085)		$20,000–$39,999 (n = 21,212)		<$20,000 (n = 25,910)
Rank	Type	%	Type	%	Type	%	Type	%	Type	%	Type	%
1	Golf	21.3%	Golf	14.0%	Walking	7.6%	Fitness exercises	14.2%	Fitness exercises	15.9%	Fitness exercises	13.1%
2	Walking	9.0%	Walking	9.4%	Golf	7.5%	Weight exercises	8.9%	Walking	9.3%	Walking	7.9%
3	Weight exercises	5.3%	Ground golf	5.9%	Ground golf	6.9%	Walking	8.5%	Weight exercises	7.9%	Weight exercises	5.0%
4	Ground golf	3.9%	Weight exercises	4.5%	Weight exercises	2.8%	Yoga	5.5%	Yoga	4.7%	Ground golf	4.5%
5	Fitness exercises	2.9%	Hiking	3.3%	Fitness exercises	2.5%	Dance	4.6%	Dance	4.7%	Dance	3.6%
	Any of	42.1%	Any of	38.0%	Any of	29.2%	Any of	42.6%	Any of	42.6%	Any of	34.3%
Stratified by population density per inhabitable area (inhabitants per square kilometre)
	≥4,000 (n = 27,758)		1,000–3,999 (n = 20,688)		<1,000 (n = 15,019)		≥4,000 (n = 29,990)		1,000–3,999 (n = 21,913)		<1,000 (n = 16,594)
Rank	Type	%	Type	%	Type	%	Type	%	Type	%	Type	%
1	Golf	13.0%	Golf	10.8%	Golf	9.0%	Fitness exercises	14.4%	Fitness exercises	16.3%	Fitness exercises	9.6%
2	Walking	9.4%	Walking	8.3%	Ground golf	8.8%	Walking	9.2%	Walking	8.1%	Walking	7.0%
3	Weight exercises	5.0%	Ground golf	6.6%	Walking	6.7%	Weight exercises	7.3%	Weight exercises	6.1%	Ground golf	5.6%
4	Ground golf	4.6%	Weight exercises	2.9%	Fitness exercises	1.9%	Dance	5.1%	Ground golf	4.9%	Weight exercises	4.2%
5	Hiking	3.4%	Fitness exercises	2.6%	Hiking	1.9%	Yoga	5.1%	Yoga	3.3%	Dance	3.1%
	Any of	35.5%	Any of	32.3%	Any of	32.0%	Any of	39.6%	Any of	38.2%	Any of	32.2%

Figures 1–3 show the PRs and 95% CIs calculated by the IPW method for having excellent self-rated health, depressive symptoms, and a high frequency of laughter for participation in each type of sports and exercise group compared to non-participation. Male participants playing golf in a group were more likely to demonstrate excellent self-rated health (PR, 1.31; 95% CI, 1.20–1.43), less likely to experience depressive symptoms (PR, 0.70; 95% CI, 0.63–0.79), and laugh more (PR, 1.12; 95% CI, 1.06–1.19) than those who did not play golf in a group. Males who hike in groups also have higher self-rated health (PR, 1.95; 95% CI, 1.67–2.27) and lower depressive symptoms (PR, 0.62; 95% CI, 0.50–0.78) compared to those who did not hike in a group. Males who walk in a group have lower depressive symptoms (PR, 0.82; 95% CI, 0.74–0.91) and laugh more (PR, 1.06; 95% CI, 1.01–1.11) compared to those who did not participate in a walking group. Older females participating in a walking and golf group were more likely to demonstrate excellent self-rated health (PR, 1.23; 95% CI, 1.15–1.31 and PR, 1.78; 95% CI, 1.51–2.08, respectively), were less likely to experience depressive symptoms (PR, 0.79; 95% CI, 0.73–0.87 and PR, 0.72; 95% CI, 0.55–0.93, respectively), and laugh more (PR, 1.06; 95% CI, 1.02–1.10 and PR, 1.13; 95% CI, 1.02–1.25, respectively) than those who did not participate in a walking and golf group. Participating in a group of running and jogging, hiking, dancing, bowling, and weight exercises were significantly associated with excellent self-rated health and low depressive symptoms among female participants. Appendix Figures 1, 2, and 3 show the results of Poisson regression analyses without the IPW method. Although sports and exercise types with significant associations slightly decreased, golf was still significantly associated with all outcomes among male participants. Likewise, golf, hiking, and dance showed significant associations with excellent self-rated health and low depressive symptoms among female participants.

Figure 1. Prevalence ratios (PRs) of excellent self-rated health according to each type of sport and exercise group participation adjusted for frequency of participation, age, drinking status, smoking status, marital status, education, equivalent income, disease status, frailty status, and levels of urbanness using an inverse probability weighting method.

Figure 2. Prevalence ratios (PRs) of depressive symptoms according to each type of sport and exercise group participation adjusted for frequency of participation, age, drinking status, smoking status, marital status, education, equivalent income, disease status, frailty status, and levels of urbanness using an inverse probability weighting method.

Figure 3. Prevalence ratios (PRs) of high frequency of laughter according to each type of sport and exercise group participation adjusted for frequency of participation, age, drinking status, smoking status, marital status, education, equivalent income, disease status, frailty status, and levels of urbanness using an inverse probability weighting method.

4. Discussion

To the best of our knowledge, this is the first study to describe the prevalence of specific types of sports and exercises engaged by older people in a group. Golf was the most popular activity for older males regardless of age, economic status, and urbanness of residence. After golf, there were a number of older males who walked, lifted weights, and played ground golf in groups. Among older females, fitness exercises were most popular regardless of age, economic status, and urbanness. After fitness exercises, the next most popular activities were walking, weight exercises, ground golf, dance, and yoga. Launching and increasing the number of available clubs or groups which incorporate those sports and exercise types in the community might attract greater interest from older people and encourage participation. According to a survey performed by the Japanese government (Japan Sports Agency), (Japan Sports Agency, 2018) the top five sports and exercise types males in their 70s participated in (regardless of their participation in a group or individual participation) were walking (73.0%), fitness exercises (18.1%), golf (16.0%), bicycling (13.6%), and weight exercises (10.9%). The top five types females in their 70s participated in were walking (68.6%), fitness exercises (25.9%), weight exercises (12.9%), bicycling (10.3%), and aerobics, yoga, ballet, and Pilates (9.7%). The latent population of group participation is considered large for sports and exercise types, with a divergence between the proportion of players as a whole and that of players participating in a group (e.g., walking and bicycling).

In this cross-sectional study, we assumed that self-rated health, depressive symptoms, and frequency of laughter were proxies leading to subsequent serious health problems. Therefore, we investigated the relationship of these factors with the participation in each type of sport and exercise group. We found that golf had a significant relationship with all three characteristics in both sexes and walking among the female participants.

According to a scoping review, playing golf could provide a moderate-intensity physical activity and was associated with physical health benefits (e.g., improving cardiovascular, respiratory, and metabolic profiles) (Murray et al., 2017). Although several qualitative and quantitative studies with small sample sizes described benefits related to self and group identity and social connections, the evidence related to golf and mental health and wellness is still limited. Our findings of excellent self-rated health, low depressive symptoms, and a high frequency of laughter in many older individuals who golf in a group suggest that this is a group activity which has a positive effect on mental health and wellness among the older people. Golf is thought to be a sport with many intergenerational interactions, (Murray et al., 2017) which may explain why it is preferable to these participants. However, further study is required to investigate the detailed mechanism behind these benefits.

Among older females, walking is the most popular exercise type regardless of their participation in a group or as individuals, (Japan Sports Agency, 2018) and this exercise is associated with better mental health and health-related quality of life (Heesch, Burton, & Brown, 2011; Heesch, van Uffelen, van Gellecum, & Brown, 2012). Heesch and colleagues showed an inverse dose-response relationship of weekly walking minutes with concurrent and future depressive and anxiety symptoms (Heesch et al., 2011) among older females and a positive dose-response relationship with concurrent and future health-related quality life, particularly with regard to physical function and vitality (Heesch et al., 2012). The results of this study provide some insight to the work by Heesch and colleagues in that older females who participated in a walking group had a higher self-rated health, less depressive symptoms, and a higher frequency of laughter (Heesch et al., 2011, 2012). Evaluating walking time usually includes a semi-mandatory walking activity such as transport walking and dog-walking as an individual. Conversely, walking for the purpose of exercise, leisure, and enjoyment in a group may produce additional benefits to psychological and social factors in addition to the increased physical activity.

Fitness exercise was the most frequent type of exercise group participation among older females, but there was no significant correlation with self-rated health, depressive symptoms, or frequency of laughter. The results of this study contrast with findings from a 4-year prospective cohort study in Japan identifying the associations between 16 exercise types and the onset of IADL decline among older females, which reported that callisthenics (nearly synonymous with “fitness exercises” in this study) delayed IADL decline (Osuka et al., 2018). In that previous study, the authors suspected that higher feasibility of the fitness exercises which is easily incorporated into daily lifestyle might delay the decline in IADL. While fitness exercises may be effective for health outcomes which mostly rely on physical functions such as IADLs, the benefits may be less effective for socio-psychological aspects such as depressive symptoms and laughter, even if they engage in group fitness exercises.

Aside from golf and walking, several types of sports and exercise groups showed a significant relationship with one or two factors of self-rated health, depressive symptoms, and frequency of laughter. For example, hiking in a group was significantly related to excellent self-rated health and depressive symptoms in both males and females. However, discussing the relevance of each type of sports and exercise group to each health status separately in detail is difficult, as this was a cross-sectional study. A previous meta-analysis (Oja et al., 2015) determined that the relationship with a specific type of sport was different among health outcomes but provided no solid evidence as most studies were cross-sectional, even less so from prospective cohorts and intervention studies.

The strengths of this study are its large, nationwide, and population-based sample, enabling a sex-stratified analysis to clarify the prevalence and health benefits of 19 types of sports and exercise group participation among older people. However, this study has some limitations which warrant discussion. First, reverse causality could occur due to the nature of the cross-sectional design; thus, further longitudinal studies are required to address this limitation. Second, we could not consider frequency, duration, or intensity for each type of sport and exercise group participation because of space restrictions on questionnaire, although the total frequency of participation was adjusted. Future studies should collect information on frequency, duration, and intensity of each type of activity to determine an optimal dose for the greatest benefit. Third, despite examining the one-to-one relationship between each type of group sports and exercises, and each socio-psychological health outcome, we neither investigated the combined effect of participating in multiple types of group sports and exercises nor collected data on specific types of sports and exercising alone. Because older people engage in various types of sports and exercises, further studies that clarify their combined effects are required. One of the reasons why golf and walking group participation has been well associated with socio-psychological health status in this study may be due to the likelihood that these types of exercises would prompt older people to engage in other sports and exercising activities.

5. Conclusions

This study results indicate that golf and walking were popular activities among males and females, respectively, involved in such groups regardless of their age, income, and urbanness related to residence. Further, they had greater self-rated health, lower depressive symptoms, and greater daily laughter compared with those who did not participate in golf and walk groups. Therefore, golf and walking may be promoted as a first choice programme to improve participation in sport and exercise groups by the older Japanese people.

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplementary material

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Additional information

Funding

This work was supported by the Japan Gerontological Evaluation Study (JAGES) under JSPS (Japan Society for the Promotion of Science) KAKENHI [grant number JP15H01972], [grant number JP16K16595]; Health Labour Sciences Research Grants [grant number H28-Choju-Ippan-002]; Japan Agency for Medical Research and Development (AMED) [grant number 171s0110002], [grant number 18le0110009]; and the Research Funding for Longevity Sciences from National Center for Geriatrics and Gerontology [grant number 29-42].