Older Adults' Choice of Patterns of Outdoor Physical Activity Duration: A Mixed Multinomial Logit Model

Predictors of the Level of Physical Activity in Physically Active Older People

There has not been much study of risk profiles in older people according to different levels of practice in physical activity. For this reason, the aim of this research was to evaluate whether the elements that influence the quality of life and factors such as gender and education can predict the level of physical activity in the physically active elderly population. The Fernández−Ballesteros quality of life questionnaire and the WHO International Physical Activity Questionnaire were applied to a sample of 397 people with a mean age of 69.65 years (SD = 4.71). The results revealed the following predictive factors of practicing a low level of physical activity (p < 0.05): being a woman; having a low educational level; and low scores in activity and leisure and in functional skills. In conclusion, gender, education, functional skills, activity and leisure, and health are elements of quality of life that predict the level of physical activity performed by the elderly, where it is necessary to use leisure activities (visiting friends, playing games, running errands) as an indirect way to increase participation in physical activity.

Role of Environmental Quality of Life in Physical Activity Status of Individuals with and without Physical Disabilities in Saudi Arabia

The promotion of physical activity (PA) in various subgroups of the population such as people with physical disabilities has been spotlighted in the revised guidelines of The World Health Organization (WHO), Geneva, Switzerland. In order to update public health interventions, there is a need to identify factors that may promote or prevent engagement in PA for special subgroups of the population. This study aims to calculate the PA levels of individuals with and without physical disabilities in Saudi Arabia, their assessment of the environmental (EQoL), and the predictive role of EQoL in PA. The International Physical Activity Questionnaire (IPAQ) and the EQoL domain in standardized WHOQoL Questionnaire were administered on both groups of the population. The study sample comprised 116 individuals with physical disabilities and 243 individuals without any form of disability as a control group. A regression analysis was performed to analyze the predictors of PA in both groups. Findings showed that among the individuals with disabilities, older people were more likely to engage in PA as compared to the younger age group (p < 0.05) and males were significantly less likely to meet the PA criteria. Some of the EQoL features such as safety increased the likelihood of PA up to 2.3 times (p < 0.05) in individuals with physical disabilities. In addition, opportunities for leisure activities were a significant predictor of PA among both groups of individuals with and without physical disabilities (p < 0.05). Our findings suggest that upcoming public health interventions should focus on improving various dimensions of EQoL for the promotion of physical activity among individuals with physical disabilities. Additional studies are needed to further explore various sociodemographic and environmental factors which can affect the PA status of disabled groups.

Differences in the Correlation between the Built Environment and Walking, Moderate, and Vigorous Physical Activity among the Elderly in Low- and High-Income Areas

Studies have proved that activity and fitness behaviors are closely related to the quality of life and health status of the elderly. However, different intensities of physical activity (PA)—walking, moderate PA, and vigorous PA—have different correlations with the built environment (BE). This study combines the high and low socioeconomic status (SES) of Guangzhou to establish two types of BE models. The physical activity time of 600 elderly people was collected from questionnaires. Through ArcGIS software, 300 m, 500 m, 800 m, and 1000 m buffer zones were identified, and the land use diversity, street design, population density, distance to destination, distance to public transportation—the five Ds of the BE—were measured. SPSS software was adopted to analyze the correlation between the BE and PA. Results: The PA of people living in low-SES areas was more dependent on the BE, whereas the correlation may be limited in high SES areas. Moreover, in low SES areas, walking was negatively correlated with street connectivity; moderate PA was positively correlated with street connectivity and the shortest distance to the subway station, but negatively correlated with the density of entertainment points of interest (POIs). Studying the relevant factors of the environment can propose better strategies to improve the initiative of the elderly to engage in PA.