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J Exerc Rehabil > Volume 21(2);2025 > Article
Kang, Choi, Kim, and Shin: A cross-sectional study on exercise participation and barriers among older adults

Abstract

This study examined the weekly frequency of exercise participation among older adults in South Korea and identified the factors influence this frequency. A frequency analysis compared sociodemographic characteristics based on weekly frequency of exercise participation. A linear regression analysis identified factors influencing participation in exercise less than 3 times a week and participation in no exercise. A total of 312 participants (mean age, 80.47±6.80 years), women exercised less frequently than men. Increased age correlated with lower exercise participation, with the lowest rates among individuals aged 86 or older. Higher education levels were associated with more frequent exercise, as individuals with 16 or more years of education exhibiting the highest participation rates. Compared to individuals aged 65–75, individuals aged 81–85 and those 86 or older showed significantly higher odds ratios for insufficient exercise. Conversely individuals with 16 or more years of education had significantly lower odds ratios. Economic, psychological, emotional, environmental, and physical factors, as well as information-seeking ability, were key barriers to exercise participation. These findings suggest that women and individuals aged 81 or older need more encouragement to engage in frequent exercise. Furthermore, information-seeking ability and economic, psychological, environmental, and exercise-related/personal factors significantly impact exercise participation among older adults.

INTRODUCTION

A super-aged society is one in which over 20% of the population is aged 65 years or older. The proportion of individuals aged 65 or older in South Korea was 19.2% in 2024. This proportion was expected to exceed 20% in 2025 (Statistics Korea, 2024), and the country has now transitioned into a super-aged society. According to the United Nations, South Korea has had the fastest transition into a super-aged society (United Nations, 2019).
The aging process is accompanied by a decline in physical function and an increased risk of disability, which can cause various age-related health problems. Regular exercise and physical activity are strongly recommended to prevent or delay the onset of these health issues. Regular exercise helps in not only reducing all-cause mortality (Mora and Valencia, 2018) but also preventing or managing chronic diseases (Jones et al., 2024) and frailty (Vazquez-Guajardo et al., 2024). In addition, it enhances cognitive function (Gómez-Soria et al., 2023), reduces the risk of dementia (De Santis et al., 2023), and improves mental health (Cunha et al., 2024).
Despite the well-documented benefits of exercise and physical activity, participation rates tend to decline with advancing age. In Korea, reports have shown that exercise participation increases from age 30 to 50 but declines among individuals aged 60 or older (Ministry of Culture, Sports and Tourism, 2024). Specifically, 68% of individuals in their 60s exercise at least once a week, but this percentage drops to 28.1% among those in their 70s and 15.1% among those in their 80s. This decreasing trend is concerning, particularly given the importance of regular exercise in advanced age. Furthermore, the proportion of individuals aged 75 or older has steadily increased since 2000, with those aged 85 or older particularly vulnerable to age-related health problems (Park and Yu, 2016).
These statistics make it vital to promote exercise among middle-old (individuals aged 75–84 years) and oldest-old (those aged 85 or older) individuals. To effectively promote exercise participation among older adults, it is essential to identify the factors that influence older adults’ exercise participation across different old age groups. Previous research has identified several age-specific barriers to exercise participation. Among the individuals aged 65–74 years, social factors (Meredith et al., 2023) and the lack of self-management skills (Hwang et al., 2011) have been found to be key barriers. Among those aged 75 or older, barriers such as chronic diseases and fear of falls (Hwang et al., 2011) become more prominent. Among those aged 85 or older, additional challenges propagate, such as a rapid decline in physical function (Merchant et al., 2021), cognitive impairment (Xu et al., 2023), dependency on caregivers (Breitholtz et al., 2013), and social isolation (Meredith et al., 2023). These findings suggest that barriers to exercise participation are age-specific among older adults and tend to evolve with increasing age.
Some older adults lead sedentary lives even in the absence of physical or mental disabilities. This may be due to the lack of awareness of the benefits of frequent exercise and the recommended frequency of exercise. Previous studies have shown that older adults who engage in regular exercise experience greater health benefits than those who do not (Cunningham et al., 2020; Sun et al., 2013). Moreover, exercise frequency is associated with higher quality of life for seniors (Kell and Rula, 2019). Given these findings, it is essential to increase awareness of not only the benefits of participating in exercise but also the recommended frequency of exercise. Notably, one must exercise at least 3 times a week for optimal health. However, few studies have identified the factors associated with the weekly frequency of exercise participation among older adults in South Korea. Considering the country’s rapidly aging population, this study examined the weekly frequency of exercise participation among older adults in South Korea and identified the factors that influence this frequency.

MATERIALS AND METHODS

Participants and data collection

This study targeted individuals aged 65 or older who had sufficient cognitive ability to complete the survey and did not have orthopedic conditions or other health issues that could restrict exercise or physical activity. The participants were recruited primarily from community welfare and senior centers in Seoul and Chungnam, South Korea. Before data collection, the researchers visited the institutions where the study was conducted to explain the study’s purpose and procedures.
Data were collected using a survey conducted from November 2024 to January 2025. A total of 312 older adults (mean age, 80.47±6.80 years) voluntarily participated in the study. Informed consent was obtained from all participants before they participated in the survey. The researchers visited the study institutions to distribute the questionnaires, and the questionnaires were administered in person. Participants completed the questionnaires by themselves, and researchers were available to provide clarification if needed. Upon completion, the questionnaires were immediately collected by the researchers. This study was approved by the Institutional Review Board of Sangmyung University, Seoul, Korea (ex-2024-039) and conducted in compliance with the relevant ethical guidelines.

Study instrument and variables

Data were collected using a structured questionnaire. The participants were asked how frequently they exercised for at least 30 min in a week. The weekly frequency of exercise participation was categorized as never, 1–2 days, or ≥3 days. The questionnaire also comprised 26 items: five items on sociodemographic factors and 12 items on barriers to exercise participation. The sociodemographic factors were selected based on previous studies and included sex, education level, age, perceived economic status, and area of residence (Murata et al., 2010; Södergren et al., 2014; Wang et al., 2022). In accordance with the objectives of this study, the items on potential barriers to exercise participation were categorized into five domains: economic barriers, psychological and emotional barriers, information-seeking ability, environmental and physical constraints, and exercise-related and personal constraints (Spiteri et al., 2019; U.S. Centers for Disease Control and Prevention, 2024; Waterworth and Honey, 2018). These items were rated on a 5-point Likert scale. The reliability of the questionnaire was assessed using Cronbach α, and it yielded a Cronbach α value of 0.837.

Data analysis

A frequency analysis was performed to compare participants’ sociodemographic characteristics based on the weekly frequency of their exercise participation. Then, a linear regression analysis was performed to determine the factors influencing the weekly frequency of exercise participation. Model 1 compared individuals who exercised ≥3 days a week (the reference group) with those who exercised less than 3 days a week or did not exercise at all. Model 2 compared individuals who exercised at least once a week (the reference group) with those who did not exercise at all. All statistical analyses were performed using IBM SPSS Statistics ver. 29.0 (IBM Co., Armonk, NY, USA), and statistical significance was set at α=0.05.

RESULTS

Table 1 presents the results of comparing participants’ sociodemographic characteristics based on the weekly frequency of exercise participation. A comparison based on sex revealed that the proportion of individuals who did not exercise at all was higher among women (38.9%) than among men (32.9%). Furthermore, the proportion of individuals who exercised at least 3 times a week was lower among women (23.4%) than among men (26.0%). A comparison based on education level revealed that higher education levels are associated with more frequent exercise participation. Specifically, among those with no formal education, only 14.2% exercised at least 3 times a week, whereas among those with 16 or more years of education, 62.5% exercised at least 3 times a week. A comparison based on age revealed that the proportion of individuals who did not exercise at all was the lowest among those aged 65–75 years (28.2%). This percentage increased with age and was the highest among those aged 86 years or older (48.0%). Additionally, the proportion of individuals who exercised at least 3 times a week was the highest in the 65–75 age group (35.2%) and the lowest among those aged 86 or older (18.2%). Regarding perceived economic status, the proportion of individuals who did not exercise at all was the highest among individuals who believed they had a high economic status (48.5%). Additionally, the proportion of individuals who exercised at least 3 times a week was the lowest in this group (12.1%). Regarding area of residence, urban dwellers had a higher proportion of individuals exercising at least 3 times a week (25.4%) than rural residents (15.5%). Additionally, the proportion of individuals who did not exercise at all was significantly higher among rural residents (49.0%) than among urban dwellers (35.6%).
Table 2 presents the descriptive statistics of barriers to exercise participation based on the weekly frequency of exercise participation.
Table 3 presents the results of identifying the factors affecting the weekly frequency of exercise participation. Compared to individuals aged 65–75, the odds ratio (OR) for exercising less than 3 times a week was 2.20 among individuals aged 81–85 (Model 1; 95% confidence interval [CI], 1.11–4.35; P=0.023). Among individuals aged 86 or older, the OR for exercising less than 3 times a week was 2.45 (Model 1: 95% CI, 1.15–5.21; P=0.020), and the OR for not exercising at all was 2.36 (Model 2: 95% CI, 1.19–4.67; P=0.014). These findings suggested that from the age of 81, aging becomes a significant barrier to exercise participation, with a particularly greater hindrance observed from the age of 86.
Compared to individuals with no formal education, individuals with 16 or more years of education showed an OR of 0.10 for exercising less than 3 times a week (Model 1: 95% CI, 0.03–0.032; P<0.001) and an OR of 0.19 for not exercising at all (Model 2: 95% CI, 0.05–0.72; P=0.015). These findings indicated that individuals with more years of education are less likely to experience barriers to exercise participation.
Compared to individuals who believed they had an average or low economic status, individuals who believed they had a high economic status exhibited an OR of 2.62 for exercising less than 3 times a week (Model 1: 95% CI, 1.18–5.81; P=0.018) and an OR of 1.76 for not exercising at all (Model 2: 95% CI, 1.01–3.07; P=0.048). This finding indicated that higher levels of perceived economic status do not necessarily facilitate exercise participation and may, in fact, act as a barrier to exercise participation. However, membership and lesson fees (i.e., economic factors that may hinder exercise participation) showed an OR of 2.26 for exercising less than 3 times a week (Model 1: 95% CI, 1.22–4.16; P=0.009).
All six psychological and emotional barriers exhibited statistically significant ORs for exercising less than 3 times a week (Model 1) and not exercising at all (Model 2). These results suggested that psychological and emotional factors hinder exercise participation. The three items concerning information-seeking ability also showed statistically significant ORs in both models, confirming that poor information-seeking ability impedes exercise participation.
Regarding environmental and physical constraints, a few of the seven items showed statistically significant ORs. Poor facilities, lack of time, and a large class size combined with an uncomfortable environment were not identified as significant barriers to exercise participation.
Among exercise-related and personal constraints, the lack of knowledge about exercise methods exhibited statistically significant ORs for exercising less than 3 times a week (Model 1: OR, 23.62; 95% CI, 12.13–46.00; P<0.001) as well as not exercising at all (Model 2: OR, 4.8; 95% CI, 2.56–8.99; P<0.001). Similarly, the other two factors showed significantly high ORs in both models, indicating that exercise-related and personal constraints hinder exercise participation.

DISCUSSION

The findings of this study demonstrated that women, individuals aged 81 or older, those with less than 16 years of education level, and individuals residing in rural areas engage in less frequent exercise in a week. Furthermore, age, education level, perceived economic status, psychological and emotional factors, information-seeking ability, environmental and physical factors, and exercise-related and personal factors were identified as barriers to sufficient exercise participation in a week.
This study conducted comparative analyses based on the weekly frequency of older adults’ exercise participation, as limited research has explored the exercise participation of Korean older adults. Exercise frequency is a key factor in health benefits (Kell and Rula, 2019). According to the World Health Organization guidelines (World Health Organization, 2020), older adults should exercise at least 3 times a week. Meanwhile, Musich et al. (2017) have reported that older adults who engage in physical activity 5 or more times a week exhibit significantly better health outcomes than those who do not.
In this study, older women showed lower exercise participation rates than older men. This result can be attributed to several reasons. Household responsibilities may limit women’s available time for exercise. Concerns about neighborhood safety and access to appropriate exercise facilities may discourage exercise participation among women more than men (Lee, 2005). Additionally, physical limitations may play a vital role, as women tend to experience greater physical constraints in engaging in physical activity than men (Stalling et al., 2024). Further, sex-based differences in priorities, access to exercise-related resources, availability of leisure time, lifestyle patterns, and fundamental perceptions of exercise may have influenced the disparity in the exercise participation rate. Accordingly, the impact of sex-based differences on exercise participation should be carefully considered in devising public health measures aimed at promoting older adults’ exercise participation.
Age-based comparisons of the weekly frequency of exercise participation revealed that the proportion of individuals exercising at least 3 times a week is the lowest among individuals aged 86 or older (18.2%). Similarly, the regression analysis showed an association between older age and lower exercise participation. Specifically, the OR for exercising less than 3 times a week was higher among individuals aged 86 or older (OR, 2.45) than among individuals aged 81–85 (OR, 2.20). These findings suggest that advanced age, particularly beyond 80 years, impedes exercise participation, with a potentially greater impact among individuals aged 86 or older. After completing the survey, follow-up discussions regarding insufficient exercise indicated that some participants believed exercising once a week is adequate for maintaining health. Additionally, some individuals believed that rather than engaging in exercise throughout the week, engaging in prolonged exercise sessions on weekends is beneficial. These findings suggest that older adults lack information and understanding about the importance of engaging in regular exercise or maintaining an appropriate frequency for enhanced health benefits. They also highlight the need to increase awareness of not only the significance of exercise in old age but also the importance of frequent and consistent physical activity for overall health.
Regarding psychological and emotional barriers to exercise participation, feeling lazy and unmotivated was the most significant barrier to exercising less than 3 times a week, with an OR of 27.73. This factor was followed by the absence of someone to exercise with, which had an OR of 14.46. Follow-up discussion with the participants of this study revealed that the loss of exercise partners due to death, surgery, or nursing home admission reduced participants’ motivation to exercise, leading to decreased exercise participation. These findings suggest that psychological factors play a more significant role in restricting older adults’ physical activity than exercise facilities or the physical environment.
Concerning education level, only individuals with 16 or more years of education exhibited significantly lower ORs for exercising less than 3 times a week (OR, 0.10) and not exercising at all (OR, 0.19). This result may be attributed to the fact that individuals with higher levels of education tend to have more knowledge about the benefits of exercise and are more likely to understand and adopt health recommendations (Bauman et al., 2012; Carlson et al., 2010). Furthermore, higher education levels are often associated with better health literacy and awareness, which may facilitate proactive engagement in exercise.
An unanticipated finding in this study was that individuals who believed they had a high perceived economic status exhibited statistically higher ORs for exercising less than 3 times and not exercising at all. This contradictory result may stem from a discrepancy between one’s actual economic status and their own perceptions of their financial standing. Some individuals may exhibit optimism bias, whereby they may overestimate their financial status compared to their actual income or assets (Kraus and Keltner, 2009). Conversely, others may experience relative deprivation, perceiving themselves as economically disadvantaged regardless of their actual financial condition (Kuo et al., 2024). These psychological factors may contribute to the unexpected relationship observed between perceived economic status and exercise participation in this study.
Recent studies have highlighted the increasing importance of digital literacy in obtaining health information, even among older adults. In this study, all 3 items concerning information-seeking ability exhibited significant ORs in Models 1 and 2. Notably, a lack of information related to exercise events, places, etc. or not knowing how to search for this information showed a significant OR for exercising less than 3 times a week (OR, 12.52). This finding indicates that a lack of exercise-related information or the inability to search for it is a strong barrier to exercise participation. This finding aligns with that of previous studies reporting that poor information-seeking ability may limit access to exercise-related information, thereby restricting exercise participation (Harada et al., 2016). De Santis et al. (2023) reported that older individuals who effectively utilize digital technology tend to actively seek health-related information and are more likely to engage in preventive health behaviors. Similarly, Nutakor et al. (2024) and Sinha and Serin (2024) demonstrated that older adults who actively search for online health information tend to participate in physical activity more frequently and engage in preventive health behaviors, such as regular physical exercise. Considering these findings, digital literacy can be regarded as a crucial determinant of older adults’ health management behaviors. Furthermore, a notable finding of this study was that difficulty in reading small text impedes older adults from obtaining health-related information. This finding suggests that text readability plays a crucial role in facilitating or hindering older individuals’ exercise participation.
Among environmental and physical constraints, inconvenient transportation, lack of exercise facilities near the place of residence, and difficulty in registration were identified as key barriers to exercise participation. According to previous research, older adults tend to prefer nearby locations and facilities. Easily accessible places (Liu et al., 2020) and facilities within 500 meters walking distance (Portegijs et al., 2020) are associated with increased participation in physical activity. Additionally, older adults who reside farther from community centers tend to engage in lower levels of physical activity (Okuyama et al., 2021). These findings emphasize establishing exercise facilities near residential areas and building a safe and convenient environment to promote older adults’ exercise participation. Efforts should also be made to mitigate the challenges faced in the registration and application processes.
All 3 items concerning exercise-related and personal constraints (i.e., lack of knowledge about exercise methods, concern about pain or injury from exercising, and fatigue or exhaustion) showed very high ORs. These findings imply the necessity of educating older adults about simple exercises that are highly beneficial and can be performed independently. Additionally, it is crucial to emphasize that exercise enhances energy levels rather than inducing fatigue, thereby fostering more positive perceptions of exercise. As age increases, these exercise-related and personal factors may hinder older adults’ exercise participation. Therefore, tailored exercise programs and guidance for different age groups are necessary to address personal concerns and promote sustained participation in exercise.
This study has several limitations. First, the recruitment of older male participants was challenging, resulting in a sex-based imbalance in the sample. Future studies should increase the number of male participants to enhance the reliability of comparative analyses and provide more robust conclusions. Second, this study did not account for differences in exercise settings. Specifically, it did not distinguish between individual exercise routines, participation in exercise programs led by community-based instructors, or privately funded gym memberships. Third, there was a discrepancy in the proportion of urban and rural dwellers. Considering regional environmental conditions may yield insights into the specific barriers faced by older adults in different settings. Despite these limitations, this study’s strength lies in its examination of exercise participation rates across different age groups among older adults; older adults in this study ranged from those in their 60s to those aged 80 or older. Given that exercise frequency is a crucial determinant of health outcomes in older adults, this approach enhances the explanatory power of the findings and serves as a key strength of the study.
In conclusion, this study emphasizes the need for more frequent exercise among older adults, particularly women and those aged 81 or older. It also suggests that minimizing the barriers to exercise participation requires a multifaceted approach.

Notes

CONFLICT OF INTEREST

No potential conflict of interest relevant to this article was reported.

ACKNOWLEDGMENTS

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2024S1A5C3A02043877).

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Table 1
Descriptive statistics of sociodemographic characteristics based on the weekly frequency of exercise participation
Variable Weekly frequency of exercise participation

Never 1–2 Days ≥3 Days Total
Sex
 Female 93 (38.9) 90 (37.7) 56 (23.4) 239
 Male 24 (32.9) 30 (41.1) 19 (26.0) 73

Education level (yr)
 None 21 (42.9) 21 (42.9) 7 (14.2) 49
 6 61 (42.7) 57 (39.9) 25 (17.4) 143
 9 20 (41.6) 14 (29.2) 14 (29.2) 48
 12 12 (25.0) 22 (45.8) 14 (29.2) 48
 ≥16 3 (12.5) 6 (25.0) 15 (62.5) 24

Age (yr)
 65–75 20 (28.2) 26 (36.6) 25 (35.2) 71
 76–80 19 (32.8) 24 (41.4) 15 (25.8) 58
 81–85 41 (38.7) 44 (41.5) 21 (19.8) 106
 ≥86 37 (48.0) 26 (33.8) 14 (18.2) 77

Perceived economic status
 Average 75 (34.9) 83 (38.6) 57 (26.5) 215
 Low 10 (32.2) 11 (35.6) 10 (32.2) 31
 High 32 (48.5) 26 (39.4) 8 (12.1) 66

Area of residence
 Urban 95 (35.6) 104 (39.0) 68 (25.4) 267
 Rural 22 (49.0) 16 (35.5) 7 (15.5) 45

Values are presented as number (%).

Table 2
Descriptive statistics of barriers to exercise participation based on the weekly frequency of exercise participation
Variable Weekly frequency of exercise participation


Barriers to exercise participation Never 1–2 Days ≥3 Days Total
Economic barriers
 Membership and lesson fees No 72 (34.9) 75 (36.4) 59 (28.7) 206
Yes 45 (42.5) 45 (42.5) 16 (15.0) 106

Psychological and emotional barriers
 No interest or dislike in exercising Yes 40 (51.9) 32 (41.6) 5 (6.5) 77
No 77 (32.7) 88 (37.5) 70 (29.8) 235
 Dislike interacting with people or moving my body in the same space as others No 77 (32.8) 88 (37.4) 70 (29.8) 235
Yes 40 (51.9) 32 (41.6) 5 (6.5) 77
 Absence of someone to provide emotional support and encouragement No 46 (27.0) 60 (35.3) 64 (37.7) 170
Yes 71 (50.0) 60 (42.3) 1 (7.7) 142
 Absence of someone to exercise with No 23 (17.4) 45 (34.1) 64 (48.5) 132
Yes 94 (52.2) 75 (41.7) 11 (6.1) 180
 Feeling lazy and unmotivated No 21 (19.1) 24 (21.8) 65 (59.1) 110
Yes 96 (47.5) 96 (47.5) 10 (5.0) 202
 Do not want others to see me in workout clothes or exercising No 98 (36.2) 102 (37.6) 71 (26.2) 271
Yes 19 (46.3) 18 (43.9) 4 (9.8) 41

Information-seeking ability
 Lack of information related to classes, sports, locations, events, etc., or do not know how to search for it No 29 (21.8) 41 (30.8) 63 (47.4) 133
Yes 88 (49.2) 79 (44.1) 12 (6.7) 179
 Not good at using a smartphone and miss calls or information No 31 (25.2) 39 (31.7) 53 (43.1) 123
Yes 86 (45.5) 81 (42.9) 22 (11.6) 189
 Difficulty finding information due to poor eyesight No 36 (27.7) 40 (30.8) 54 (41.5) 130
Yes 81 (44.5) 80 (44.0) 21 (11.5) 182

Environmental and physical constraints
 The place for exercising is far away or has inconvenient transportation No 66 (31.3) 77 (36.5) 68 (32.2) 211
Yes 51 (50.5) 43 (42.6) 7 (6.9) 101
 No facilities near my residence No 72 (33.8) 74 (34.7) 67 (31.5) 213
Yes 45 (45.5) 46 (46.5) 8 (8.0) 99
 Poor facilities No 79 (34.0) 92 (39.7) 61 (26.3) 232
Yes 38 (47.5) 28 (35.0) 14 (17.5) 80
 Lack of time No 86 (38.8) 80 (36.0) 56 (25.2) 222
Yes 31 (34.4) 40 (44.4) 19 (21.2) 90
 A large number of participants and an uncomfortable environment No 73 (39.7) 65 (35.3) 46 (25.0) 184
Yes 44 (34.3) 55 (43.0) 29 (22.7) 128
 Difficulty in registering or applying No 48 (33.1) 53 (36.6) 44 (30.3) 145
Yes 69 (41.3) 67 (40.1) 31 (18.6) 167
 A predominance of a specific sex or age group at the place No 55 (34.1) 59 (36.7) 47 (29.2) 161
Yes 62 (41.1) 61 (40.4) 28 (18.5) 151

Exercise-related and personal constraints
 Lack of knowledge about exercise methods No 14 (15.4) 18 (19.8) 59 (64.8) 91
Yes 103 (46.6) 102 (46.2) 16 (7.2) 221
 Concern about pain or injury caused by exercising No 14 (14.6) 25 (26.0) 57 (59.4) 96
Yes 103 (47.7) 95 (44.0) 18 (8.3) 216
 Fatigue or exhaustion No 13 (14.6) 25 (28.1) 51 (57.3) 89
Yes 104 (46.6) 95 (42.6) 24 (10.8) 223

Values are presented as number (%).

Table 3
Logistic regression analysis of the factors influencing the weekly frequency of exercise participation
Variable Model 1 Model 2


OR (95% CI) P-value OR (95% CI) P-value
Sex
 Female 1.00 (reference)
 Male 0.87 (0.48–1.59) 0.650 0.77 (0.44–1.34) 0.352

Age (yr)
 65–75 1.00 (reference)
 76–80 1.56 (0.73–3.34) 0.255 1.24 (0.58–2.64) 0.573
 81–85 2.20 (1.11–4.35) 0.023 1.61 (0.84–3.08) 0.151
 ≥86 2.45 (1.15–5.21) 0.021 2.36 (1.19–4.67) 0.014

Residence
 Urban 1.00 (reference)
 Rural 1.85 (0.79–4.35) 0.155 1.73 (0.92–3.27) 0.091

Education level (yr)
 None 1.00 (reference)
 6 0.79 (0.32–1.95) 0.605 0.99 (0.51–1.91) 0.981
 9 0.40 (0.15–1.12) 0.080 0.95 (0.43–2.13) 0.906
 12 0.40 (0.15–1.12) 0.080 0.44 (0.19–1.05) 0.066
 ≥16 0.10 (0.03–0.32) <0.001 0.19 (0.05–0.72) 0.015

Perceived economic status
 Average 1.00 (reference)
 Low 0.76 (0.34–1.71) 0.503 0.89 (0.40–1.99) 0.774
 High 2.62 (1.18–5.81) 0.018 1.76 (1.01–3.07) 0.048

Membership and lesson fees
 No 1.00 (reference)
 Yes 2.26 (1.22–4.16) 0.009 1.37 (0.85–2.22) 0.196

Psychological and emotional barriers
 No interest or dislike in exercising
  No 1.00 (Reference)
  Yes 6.11 (2.37–15.77) <0.001 2.22 (1.31–3.74) 0.003
 Dislike interacting with people or moving my body in the same space as others
  No 1.00 (Reference)
  Yes 6.11 (2.37–15.77) <0.001 2.22 (1.31–3.74) 0.003
 Absence of someone to provide emotional support and encouragement
  No 1.00 (Reference)
  Yes 7.19 (3.61–14.32) <0.001 2.70 (1.68–4.32) <0.001
 Absence of someone to exercise with
  No 1.00 (Reference)
  Yes 14.46 (7.19–29.09) <0.001 5.18 (3.03–8.86) <0.001
 Feeling lazy and unmotivated
  No 1.00 (Reference)
  Yes 27.73 (13.22–58.17) <0.001 3.84 (2.21–6.65) <0.001
 Do not want others to see me in workout clothes or exercising
  No 1.00 (Reference)
  Yes 3.28 (1.13–9.54) 0.029 1.52 (0.79–2.96) 0.212

Information-seeking ability
 Lack of information related to classes, sports, locations, events, etc., or do not know how to search for it No (reference)
12.52 (6.36–24.66)
<0.001 3.47 (2.09–5.75) <0.001
 Not good at using a smartphone and miss calls or information 5.75 (3.25–10.16) <0.001 2.48 (1.51–4.08) <0.001
 Difficulty finding information due to poor eyesight 5.45 (3.07–9.66) <0.001 2.09 (1.29–3.39) 0.003

Environmental and physical constraints
 The place for exercising is far away or has inconvenient transportation No (reference)
6.39 (2.81–14.5)
<0.001 2.24 (1.38–3.65) 0.001
 No facilities near my residence 5.22 (2.4–11.37) <0.001 1.63 (1.00–2.66) 0.049
 Poor facilities 1.68 (0.88–3.21) 0.115 1.75 (1.05–2.94) 0.033
 Lack of time 1.26 (0.70–2.27) 0.442 0.83 (0.50–1.39) 0.478
 A large number of participants and an uncomfortable environment 1.14 (0.67–1.94) 0.634 0.80 (0.50–1.27) 0.342
 Difficulty in registering or applying 1.91 (1.13–3.24) 0.016 1.42 (0.9–2.26) 0.136
 A predominance of a specific sex or age group at the place 1.81 (1.06–3.09) 0.029 1.34 (0.85–2.13) 0.209

Exercise-related and personal constraints
 Lack of knowledge about exercise methods No (reference)
23.62 (12.13–46.00)
<0.001 4.8 (2.56–8.99) <0.001
 Concern about pain or injury caused by exercising 16.08 (8.55–30.23) <0.001 5.34 (2.85–9.99) <0.001
 Fatigue or exhaustion 11.13 (6.13–20.21) <0.001 5.11 (2.68–9.73) <0.001

Model 1: OR for engaging in exercise <3 times per week with ≥3 times per week as the reference group. Model 2: OR for engaging in no exercise per week with participation in exercise more than 1 time per week as the reference group.

OR, odds ratio; CI, confidence interval.

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