Association between socio-ecological factors and leisure time physical activity (LTPA) among older adults in Sichuan, China: a structural equation modeling analysis

Abstract

Background Few studies examined socio-ecological factors and leisure time physical activities (LTPA) and rarely focused on self-regulation and social capital, which might play a significant role in impacting people’s physical activity behavior. This study aimed to examine the direct and indirect effects of individual level (perceived benefits, perceived barriers, and self-efficacy), interpersonal level (self-regulation), social level (social capital), and environmental level factors (perceived physical environment) on LTPA among older adults. Methods A cross-sectional study was conducted in 737 older adults from Sichuan, China. Structural equation modeling (SEM) analysis was used to examine the associations of individual, interpersonal, social, and environmental level factors with LTPA. Results The mean age of all participants was 71.22 (range, 60–97), and 56.1% of them were women. The SEM results showed that individual level variables (β = 0.32, ρ < 0.001), self-regulation (β = 0.18, ρ < 0.001) and social capital (β = 0.14, ρ < 0.001) could all directly affect LTPA while there was no significant association of perceived physical environment with LTPA. Self-regulation served as a bridge linking social capital and LTPA. Individual level variables contributed the largest total effect (0.32) on LTPA. Self-regulation and social capital had the same total effect (0.18) on LTPA. Conclusions Factors on three levels were all significantly associated with LTPA. Interventions that incorporate individual, interpersonal, social factors may be considered to promote LTPA in older adults. Self-regulation should receive more attention in future interventions.

Individual and environmental variables related to outdoor walking among older adults: Verifying a model to guide the design of interventions targeting outdoor walking

“…Among them, walking speed is also often used as an overall measure of preparedness for safe community mobility [ 83 , 84 ], further supporting the positive relationships between the individual variables related to walking capacity and OW. Walking self-efficacy, which refers to older adults’ confidence in walking outdoors, should predict OW behaviour based on self-efficacy theory [ 85 ] and has been shown to be significantly related to physical activity in several studies [ 22 , 86 , 87 ]. Individuals with higher income have been shown to have higher levels of mobility [ 88 ].…”

“…Using SEM, the correlation among observed variables can be accounted for by assuming a latent construct to be an underlying factor [ 21 ]. One study in this area applied an SEM approach and found that leisure time physical activities were significantly associated with individual level variables (i.e., perceived exercise benefits and barriers, and exercise self-efficacy) while not significantly associated with environmental level variables [ 22 ]. Another study applied SEM and found that individual factors (i.e., self-efficacy, perceived pros and cons of physical activity, and social support) had direct influences on physical activity, while the environmental factors affected physical activity indirectly through individual and social factors [ 23 ].…”

The geriatric nutrition risk index is longitudinally associated with incident Sarcopenia: evidence from a 5-year prospective cohort

“…ADL or IADL each represents daily self-care activities to support fundamental functioning or independent living [ 24 ], with ADL or IADL impairment identified by a total Barthel Index score below 100 or Lawton IADL Scale score below 14, respectively [ 25 , 26 ]. Physical activity level was determined by the validated China Leisure Time Physical Activity Questionnaire (CLTPAQ) [ 27 ], which was a modified version of the Minnesota Leisure Time Physical Activity Questionnaire (MLTPAQ) [ 28 ] adapted to Chinese lifestyle and cultural background. As previously detailed, CLTPAQ measured the total amount of energy (kcal) per week spent on a series of commonly performed physical activities, and the sex-specific threshold for low physical activity was the lowest 20th sex-specific percentile value of total energy consumption [ 29 ].…”

Association between residential environment and emotional wellbeing among older adults in China: the mediating effect of health lifestyle

“…McLeroy et al ( 50 ) introduced the social-ecological model into health research, noting that behavior is determined by intrapersonal factors, interpersonal processes, primary groups, institutional factors, community factors, and public policies. The socio-ecological model is often used to analyze the influencing factors of health-related factors, such as eating behaviors ( 51 ), physical activity ( 52 ), and mental wellbeing ( 53 ). The socio-ecological model differs from traditional psychological models in that it explicitly combines direct external influences with peripheral factors, making the socio-ecological model popular in the public health realm ( 54 ).…”