• Journal of The Korean Society of Integrative Medicine
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• v.11 no.3
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• pp.99-114
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• 2023

Purpose : The purpose of this study was to determine factors that affect the quality of life (QoL) of people with diabetes. We hope to provide a basis for intervention strategies for health promotion and related research among patients with diabetes in the field of physical therapy. Methods : We selected individuals diagnosed with diabetes who were aged 19 years or higher by using data from the 2019 Korean Health Panel survey and analyzed the results of 1,527 people. The influencing factors were sex, age, household income, marital status, age, education level, subjective health status, body mass index (BMI), smoking, drinking, regular exercise, experience of depression and anxiety, suicidal thoughts, stress, and frequency of walking (days/week). Frequency analysis, descriptive statistics, independent sample t-test, one-way analysis of variance, and multiple regression analysis were performed. Results : The EQ-5D score for QoL was .87 ± .12, with pain and discomfort being the most detrimental to the QoL of people with diabetes. In terms of patients characteristics, the QoL was lower among participants who were female, older, and separated/widowed/divorced; had an education level below middle school; had a poor subjective health status; were non-smokers and drinkers; and did not walk and exercise regularly, experienced a lot of stress, and experienced depression and anxiety; and had suicidal thoughts (p<.001). Being separated/bereaved/divorced; experiencing a lot of stress, depression, and anxiety; and having suicidal thoughts were negatively associated with QoL in people with diabetes (p<.01). On the other hand, age of 65 years or younger; graduation from high school, fair or better subjective health, regular exercise and alcohol consumption, and walking (days/week) were positively associated with QoL (p<.05). Conclusion : Regarding the QoL of patients with diabetes, intervention strategies should be formulated by considering general characteristics and disease-related characteristics. Among the various factors affecting QoL, the number of walking and regular exercise were found to be the factors that improved the QoL of patients with diabetes. These results can be used as a basis for the education and management of patients with diabetes in the field of physical therapy.

• Physical Therapy Rehabilitation Science
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• v.12 no.2
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• pp.80-91
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• 2023

Objective: The purpose of this study is to identify factors that affect the incidence of hypertension using logistic regression and decision tree analysis, and to build and compare predictive models. Design: Secondary data analysis study Methods: We analyzed 9,859 subjects from the Korean health panel annual 2019 data provided by the Korea Institute for Health and Social Affairs and National Health Insurance Service. Frequency analysis, chi-square test, binary logistic regression, and decision tree analysis were performed on the data. Results: In logistic regression analysis, those who were 60 years of age or older (Odds ratio, OR=68.801, p<0.001), those who were divorced/widowhood/separated (OR=1.377, p<0.001), those who graduated from middle school or younger (OR=1, reference), those who did not walk at all (OR=1, reference), those who were obese (OR=5.109, p<0.001), and those who had poor subjective health status (OR=2.163, p<0.001) were more likely to develop hypertension. In the decision tree, those over 60 years of age, overweight or obese, and those who graduated from middle school or younger had the highest probability of developing hypertension at 83.3%. Logistic regression analysis showed a specificity of 85.3% and sensitivity of 47.9%; while decision tree analysis showed a specificity of 81.9% and sensitivity of 52.9%. In classification accuracy, logistic regression and decision tree analysis showed 73.6% and 72.6% prediction, respectively. Conclusions: Both logistic regression and decision tree analysis were adequate to explain the predictive model. It is thought that both analysis methods can be used as useful data for constructing a predictive model for hypertension.