• The Korean Journal of Rehabilitation Nursing
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• v.9 no.2
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• pp.134-144
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• 2006

Purpose: This study was done to investigate correlations among Health Promoting Lifestyles, Health Risk Indicators, Activities of Daily Living, and Depression of the in-house stroke patients. Method: The subjects were 58 in-house stroke patients in a health center and two welfare centers. Data was collected using questionnaires and measuring health risk indicators such as blood pressure, total cholesterol, triglyceride, blood sugar, body fat rate. Data was analyzed using descriptive statistics, t-test, ANOVA, and Pearson correlation coefficients. Result: The health promoting lifestyle performance showed a significant negative correlation with health risk indicators and depression. There was a significant negative correlation between activities of daily living and depression. Conclusion: Health promoting lifestyle which focus on regular physical check-up, medication, diet management, exercise, smoking cessation, drinking abstinence, and stress management should be developed to improve health risk indicator and depression of the in-house stroke patients.

• Journal of the Korean Society of School Health
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• v.18 no.2
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• pp.85-92
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• 2005

Purpose： This study reviews the Youth Risk Behavior Surveillance System (YRBSS) in the United States. This review focuses on the purposes, questionnaires, survey methods, and use of survey results. The author also discussesthe establishment and use of Korean Youth Risk Behavior Surveillance System. Results：The YRBSS was developed in 1990 to monitor priority health risk behaviors that contribute to the leading causes of death, disability, and social problems among youth and adults in the United States. The purpose of YRBSS is to determine the prevalence of health risk behaviors, to assess the trend of health risk behavior prevalence, provide comparable data, monitor progress toward achieving the Healthy People 2010. The questionnaires inquire about health-related behaviors, including tobacco use, unhealthydietary behaviors, inadequate physical activity, alcohol and drug use, sexual activity, behaviors that contribute to unintentional injuries and violence. The results of YRBS have been used to estimate the prevalence of risk behaviors among youth, to set goals for school health programs, for training and development of health program personnel, for the development of health education curriculum, to support enactment of health-related regulations, and to support funding for futher research. Conclusions： The YRBSS represents a potentially valuable program that can be applied in Korea. Assessment of risk behaviors among Korean youths will provide invaluable insight for many potential purposes.

• Annals of Occupational and Environmental Medicine
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• v.35
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• pp.35.1-35.11
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• 2023

Background: Cardio-cerebrovascular diseases (CVDs) are the most common cause of death worldwide. Various CVD risk assessment tools have been developed. In South Korea, the Korea Occupational Safety & Health Agency (KOSHA) and the National Health Insurance Service (NHIS) have provided CVD risk assessments with health checkups. Since 2018, the KOSHA guide has stated that NHIS CVD risk assessment tool could be used as an alternative of KOSHA assessment tool for evaluating CVD risk of workers. The objective of this study was to determine the correlation and agreement between the KOSHA and the NHIS CVD risk assessment tools. Methods: Subjects of this study were 17,485 examinees aged 20 to 64 years who had undergone medical examinations from January 2021 to December 2021 at a general hospital. We classified subjects into low-risk, moderate-risk, high-risk, and highest-risk groups according to KOSHA and NHIS's CVD risk assessment tools. We then compared them with cross-analysis, Spearman correlation analysis, and linearly weighted kappa coefficient. Results: The correlation between KOSHA and NHIS tools was statistically significant (p-value < 0.001), with a correlation coefficient of 0.403 and a kappa coefficient of 0.203. When we compared risk group distribution using KOSHA and NHIS tools, CVD risk of 6,498 (37.1%) participants showed a concordance. Compared to the NHIS tool, the KOSHA tool classified 9,908 (56.7%) participants into a lower risk category and 1,079 (6.2%) participants into a higher risk category. Conclusions: In this study, KOSHA and NHIS tools showed a moderate correlation with a fair agreement. The NHIS tool showed a tendency to classify participants to higher CVD risk group than the KOSHA tool. To prevent CVD more effectively, a higher estimation tool among verified CVD risk assessment methods should be selected and managements such as early intervention and treatment of risk factors should be performed targeting the high-risk group.

• Child Health Nursing Research
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• v.15 no.2
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• pp.182-189
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• 2009

Purpose: The purpose of this study was to identify the factors influencing health risk behavior in high school students. Methods: The subjects were 512 students from 4 high schools in 3 cities. The questionnaire measured the level of self-esteem, self-efficacy, internal locus of control and health risk behaviors. The data were analyzed using descriptive statistics, t-test, ANOVA, Scheffe test, Pearson's correlation coefficient and stepwise multiple regression analysis. Results: There were significant differences in the health risk behaviors according to sex, a classification of the school, whether or not smoking of mother, whether or not live alone, level of harmonious family, level of satisfying school-life and three variables of them were significant differences by Scheffe test. There was a significant positive correlation between sub-dimension of health risk behaviors and the self-efficacy, self-esteem, internal locus of control were negative correlation with health risk behaviors. The most important influential factor of the health risk behaviors was the self-efficacy. Conclusion: From the studies reviewed, improving the self-efficacy, self-esteem, internal locus of control and the general social environment of students will probably be the most effective strategies for primary prevention of health risk behaviors.

• Child Health Nursing Research
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• v.8 no.3
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• pp.251-259
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• 2002

The purpose of the study was to investigate physical stress symptoms and health risk behaviors of adolescent athletes and high school students as a basis for providing a health promotion program of adolescent athletes. The subjects consisted of 160 male students of a physical education high school(athletes) in Kyonggi and 147 male high school students(non-athletes) in Seoul. Data was obtained from the physical stress symptoms and the health risk behaviors questionnaire. The result were as follows : 1. Physical stress symptoms didn't make significant difference between groups. GI symptom, as the subscale of physical stress symptoms of non-athletes were higher then those of athletes. The highest ranked physical stress symptoms in athletes was cardiopulmonary symptom Ⅱ(upper respiratory symptoms) and in non- athletes was central-neurological symptoms. 2. Health risk behaviors didn't make significant difference between groups. Weight control, as the subscale of health risk behaviors of athletes were higher then those of non-athletes. The highest ranked health risk behaviors in athletes was alcohol and in non-athletes was smoking. 3.There were the low positive correlation between physical stress symptoms and health risk behaviors.

• Journal of the Korea Safety Management & Science
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• v.26 no.3
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• pp.19-27
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• 2024

This study analyzes the impact of occupational health risk assessments on the safety and health levels and the safety behaviors of workers in manufacturing workplaces. An online survey was conducted among 3,172 companies, yielding 637 responses. The statistical analysis on the collected responses revealed three key findings. First, the safety and health levels (safety importance, safety comprehension, safety awareness) positively influence the outcomes of occupational health risk assessments(safety practice, safety management, safety improvement) and safety behaviors (activity change, safety check). Second, the effectiveness of occupational health risk assessments has a positive impact on safety behaviors. Lastly, the effectiveness of occupational health risk assessments partially mediate the relationship between safety and health levels and safety behaviors. These findings are expected to contribute to the promotion of risk assessments in the field of industrial health and to enhancing safety performance by improving workplace safety, health levels, and safety behavior.

• Journal of agricultural medicine and community health
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• v.49 no.2
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• pp.111-120
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• 2024

Objective: This study aimed to analyze the correlation between factors affecting health risk behaviors of rural residents according to regional scale. Methods: Restricted-access data from the 2016~2021 Korea National Health and Nutrition Examination Survey and the multivariate probit model were used. As for health risk behaviors, smoking, drinking, lack of aerobic exercise, low level of healthy eating index, unvaccination, and non-participation in health examination were considered. Results: Controlling for individuals' socio-demographic characteristics, in general, correlation coefficients between unobservable factors affecting health risk behaviors were significant. However, the magnitude and statistical significance of the correlation coefficients varied by regional scale (dong/eup/myeon). This suggests that rural residents engage in health risk behaviors due to their different characteristics compared with urban dwellers, which also varies by whether residents are located in eup or myeon area. Conclusion: It is necessary to differentiate health care services between urban and rural areas in terms of type of service and programs based on the relationship between unobservable factors affecting each type of health risk behaviors.

• Journal of the Korean Society of School Health
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• v.36 no.3
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• pp.113-125
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• 2023

Purpose: The purpose of this study is to develop a model for predicting mental health risk among adolescents based on health behavior information by employing a hybrid machine learning method. Methods: The study analyzed data of 51,850 domestic middle and high school students from 2022 Youth Health Behavior Survey conducted by the Korea Disease Control and Prevention Agency. Firstly, mental health risk levels (stress perception, suicidal thoughts, suicide attempts, suicide plans, experiences of sadness and despair, loneliness, and generalized anxiety disorder) were classified using the k-mean unsupervised learning technique. Secondly, demographic factors (family economic status, gender, age), academic performance, physical health (body mass index, moderate-intensity exercise, subjective health perception, oral health perception), daily life habits (sleep time, wake-up time, smartphone use time, difficulty recovering from fatigue), eating habits (consumption of high-caffeine drinks, sweet drinks, late-night snacks), violence victimization, and deviance (drinking, smoking experience) data were input to develop a random forest model predicting mental health risk, using logistic and XGBoosting. The model and its prediction performance were compared. Results: First, the subjects were classified into two mental health groups using k-mean unsupervised learning, with the high mental health risk group constituting 26.45% of the total sample (13,712 adolescents). This mental health risk group included most of the adolescents who had made suicide plans (95.1%) or attempted suicide (96.7%). Second, the predictive performance of the random forest model for classifying mental health risk groups significantly outperformed that of the reference model (AUC=.94). Predictors of high importance were 'difficulty recovering from daytime fatigue' and 'subjective health perception'. Conclusion: Based on an understanding of adolescent health behavior information, it is possible to predict the mental health risk levels of adolescents and make interventions in advance.

• Research in Community and Public Health Nursing
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• v.16 no.4
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• pp.392-403
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• 2005

Purpose: This study was to evaluate the nutritional status of low-income elders in urban areas and factors affecting their nutritional risk. Methods: A cross-sectional analysis was conducted. The subjects were 300 elders selected from home visiting clients of DongJack Public Health Center. Data were collected using a questionnaire containing questions on socio-demographic characteristics. health behavior and disease. dietary pattern. Nutritional Screening Initiative. Geriatric Depression Scale and Barthel Index for ADL. Collected data were analyzed through descriptive statistics. $X^2-test$ and multiple regression analysis using SPSS. Results: Of the subjects, 63% had high nutritional risk, 21.3% moderate nutritional risk, and 15.7% good nutritional risk. NSI score was significantly different according to economic status, subjective health condition, medication, dental health, depression. regularity of diet and meal with family. Multiple regression analysis revealed that depression, subjective health condition, dental health and regularity of diet and meal with family explain 38.1% of nutritional risk. Conclusion: It is necessary to evaluate nutrition status and to control nutritional risk factors such as depression, dental health, regularity of diet and meal with family for improving the health of the low-income elderly.

• Korean Journal of Health Education and Promotion
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• v.29 no.1
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• pp.13-25
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• 2012

Objectives: The aim of this study was to measure secular trends in health risk behaviors among middle and high school students in Korea between 2005 and 2009 by using data from the Korea Youth Risk Behavior Web-based Survey(KYRBS). Methods: The analyses were performed using data from the 2005, 2006, 2007, 2008, and 2009 KYRBS, which included a nationally representative sample of middle and high school students. A total of 34 health behavior indices were used for the assessment of secular trends in health risk behaviors. Logistic regression models were used to identify statistically significant secular trends in health risk behaviors, after adjusting for gender and grade. Linear and higher-order time variables were simultaneously entered into the statistical models. Results: There was evidence of small, but statistically significant increasing or decreasing trends in certain health risk behaviors. Secular trends in health risk behaviors varied by gender. Conclusions: This study indicates that between 2005 and 2009, changes in health risk behaviors among Korean adolescents were generally small, but represented statistically significant increases or decreases. Further research should explore why certain health risk behaviors are increasing or decreasing and what types of interventions are most effective.