건강군과 미병군의 한열지표 차이에 관한 연구
A Study on the Difference of Cold-heat Patterns between Health and Mibyeong Group
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Objectives : In this study, we diagnosed Mibyeong group of adult by taking into Mibyeong Index consideration, and identified the correlation of a Mibyeong group with cold-heat pattern and life quality of them. Methods : The questionnaires were collected by Gallup Korea professional surveyor through face to face interviews. To analyze the differences between health and mibyeong group, we used the descriptive statistics, Pearson’s correlation, ANOVA. And multinomial logistic regression was used to generate the odds ratios (ORs) and 95 % confidence interval (CI) for the differences between health and mibyeong group. Results and Conclusions : The gender composition of respondents in this study that there 545 male (49.5%) and 555 female (50.5%). The score of both cold pattern(health: 21.33±4.25, MI 1: 22.43±4.29, MI 2: 24.09± 5.03; post hoc test, p <0.001) and heat pattern(health: 18.4±4.01, MI 1: 19.48±4.10 MI 2: 19.88±4.81; post hoc test, p <0.001) in mibyeong group is higher than the score health group. And, these result have no relevance to age. The score of both Physical component summary (PCS) and Mental component summary (MCS) in health group is higher than the score mibyeong group. Cold-heat pattern and quality of life vary significantly according to health status. This results suggest the analysis of cold-heat pattern and quality of life by health status could provide the setting of direction to promote public health depending on health status
Abstract
Objectives : In this study, we diagnosed Mibyeong group of adult by taking into Mibyeong Index consideration, and identified the correlation of a Mibyeong group with cold-heat pattern and life quality of them. Methods : The questionnaires were collected by Gallup Korea professional surveyor through face to face interviews. To analyze the differences between health and mibyeong group, we used the descriptive statistics, Pearson’s correlation, ANOVA. And multinomial logistic regression was used to generate the odds ratios (ORs) and 95 % confidence interval (CI) for the differences between health and mibyeong group. Results and Conclusions : The gender composition of respondents in this study that there 545 male (49.5%) and 555 female (50.5%). The score of both cold pattern(health: 21.33±4.25, MI 1: 22.43±4.29, MI 2: 24.09± 5.03; post hoc test, p <0.001) and heat pattern(health: 18.4±4.01, MI 1: 19.48±4.10 MI 2: 19.88±4.81; post hoc test, p <0.001) in mibyeong group is higher than the score health group. And, these result have no relevance to age. The score of both Physical component summary (PCS) and Mental component summary (MCS) in health group is higher than the score mibyeong group. Cold-heat pattern and quality of life vary significantly according to health status. This results suggest the analysis of cold-heat pattern and quality of life by health status could provide the setting of direction to promote public health depending on health status
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