Factors Affecting the Physical Activity of Older Adults in the Community

Abstract

The aim of this paper was to determinate the factors that affect physical activity of community-dwelling elders. Methods: A cross-sectional approach was used to explore factors promoting physical activity. Participants were 203 individuals aged 65 years and over living in either the C or D cities. Each participant completed a questionnaire which included the Korean Version of Physical Activity Scale for the Elderly (K-PASE), geriatric depression, fear of falling and mini mental state examination Data were collected from July, 20 to August, 30, 2015 and statistical analysis was used to examine the participant characteristics, physical activity differences according to characteristics, correlation between physical activity and research variables, and factors affecting the physical activity. Results: The mean score for K-PASE was 106.00±67.49. K-PASE showed significantly negative correlations with depression (r=-.16, p=.026) and fear of falling (r=-.31, p<.001) and a positive correlation with cognitive function (r=.37, p<.001). In regression analysis, factors influencing the physical activity were age, educational level and cognitive function. Explanatory rate of these factors for K-PASE was 21.0%. Conclusion: Findings from the study indicate that the physical activity programs should include intervention strategies to enhance cognitive function while considering age and education level.

Factors Associated with Physical Activity in Older Adults by Region: Based on the 2017 Community Health Survey

“…Individual factors affecting the physical activity of older adults common to both urban and nonurban areas were found to be age, gender, economic activity, current smoking status, current drinking status, degree of obesity, sleep duration and subjective health status. In this study, it was found that current smokers, current drinkers, and those who rated their subjective health status as good were significantly more likely to be in the physical activity group than in the inactive group, which is inconsistent with the results of a previous study [14]. In addition, the current smoker group, the obese group, and the poor subjective health status group were significantly less likely to be in the physical activity group than in the inactive group.…”

“…Regarding the health-related characteristics of older adults in urban and non-urban areas, the prevalence of multimorbidity and the percentages of the drinking group and the obese group related to undesirable lifestyle habits were higher among urban older adults. These findings were consistent with those of prior studies in Korea [11,12], which reported that the prevalence of major chronic diseases was higher among urban or metropolitan older adults than rural older adults, but the results were inconsistent with the findings of a foreign study [14], which found that the prevalence of multimorbidity was higher among rural older adults. Considering the health care system of Korea, this disagreement in study results can be attributed to the fact that the use of medical services is not constrained by a high financial burden in Korea because of low medical costs due to the National Health Insurance system [20] and that since urban areas provide greater ease of use for medical institutions and higher accessibility to them than rural areas [11], the percentage of older adults who get an early diagnosis and management of diseases through regular health check-ups or visits to hospitals is higher in urban areas than rural areas.…”

“…Participants were divided into the inactive, minimally active, and health-enhancing physical activity groups according to the amount of physical activity, and the level of physical activity was set as the dependent variable. Based on the results of previous studies [3,[5][6][7][8][9]14,15], individual, social, and environmental factors which were expected to affect physical activity were entered into the logistic regression model to calculate the odds ratios and determine statistical significance with a 95% confidence interval. A value of p<.05 was considered statistically significant.…”

“…The research variables used in this study were individual, social, and environmental factors including sociodemographic and health-related characteristics which were selected among variables available in the Community Health Survey data by referring to the items reported as factors re-Lee, Hyun-Ju • Lee, Yeongsuk • Yun, Jungmi lated to physical activity in previous studies [3,[5][6][7][8][9]14,15].…”

“…Previous studies on the health of older adults according to the place of residence or residential area were mostly focused on individual factors such as demographic characteristics and health-related characteristics [11,12] and a study considered the impact of social support on health status together with other factors [13]. Most previous studies on physical activity in older adults limited research to one type of area, such as urban or rural areas, or investigated related factors without the division of residential areas [3,5,8,14]. Although a small number of studies compared predictive factors for physical activity among urban and rural older adults [15], few studies have sufficiently considered the social and environmental characteristics reflecting the physical and human health resources of residential areas.…”