1. Necessity and Purpose of Research
The main problem facing the Korean healthcare sector is the increasing number of chronic diseases due to the aging of the population and the deterioration of health behavior. As of 2019, Korea is an aging society with 14.8% of the population aged 65 and over. The aging trend is rapidly progressing, and proportion of those aged 65 and over is expected to reach 24.3% by 2030. The life expectancy is also expected to increase from 83.0 years in 2019 to 85.2 years by 2030. Due to increases in the elderly population and changing health behavior, chronic diseases are increasing in general. The prevalence of chronic diseases, such as obesity, hypertension, and hypercholesterolemia, increased overall in male adults. Changes in the health care environment, such as an increase in elderly population, an increase in chronic illnesses, and deterioration of health behavior, usually result in an increase in health expenditures. The reason for increases in health expenditure on the elderly population is that the number of chronic degenerative diseases is increasing due to aging. In 2014, health expenditure for major chronic diseases such as hypertension, diabetes, cerebrovascular disease, heart disease and thyroid disorders accounted for 35% of the total health expenditures. Overall, health care use and health expenditures in accordance with the supply side, such as lack of demand and medical delivery system, oversupply of beds and equipment, such as population growth and aging society, improvement of income level, various needs for medical needs, and increase of chronic diseases. Expenditures are rising rapidly, and research shows that in 2050, national health care costs will reach 15-20% of GDP. As the rapid increase in medical consumption and medical expenses threatens the sustainability of not only the health insurance system but also the national health system, the policies of government departments that focused on the treatment of diseases have emerged as national issues. It is changing to preventive health care policies, including changes in health behavior. As the social atmosphere is being created for preventing health problems and reducing health expenditures through health behaviors such as sports, the necessity of related research and policy efforts is also increasing. But the effect of the practice of healthy living on health of the people has not been sufficiently examined in research. Under these circumstances, it is necessary to study how healthy living practices affect health expenditures. Therefore, the purpose of this study is to investigate the effects of physical exercise on health, health care use and work. In particular, this paper attempts to empirically estimate whether there is a difference in health, health care use and work between exercisers and non-exercisers. In addition, this study suggests the policy implications for establishing preventive health care policies by identifying the factors influencing these exercise behaviors.
2. Research method
This study used data from the Korea Medical Panel Survey in 2016. The subjects were 18 years of age or older who surveyed additional items (health hazards, etc.) related to the practice of healthy living such as exercise. A model for analyzing the effects of exercise on health and health care use was approached in terms of medical care needs rather than in terms of medical care demand. Because there are various factors affecting health and health care use, this study estimates the health and health care use required from the perspective of individual's basic health care needs, and does not compare the estimated health level and health care use with those who exercise. This is because we wanted to see the difference in health and health care use between people. The model for estimating the effect on exercise health consists of four models: sickness status, sick days, chronic disease status index, and subjective health status index. In addition, the model for estimating the effect of exercise on health care use is divided into medical type, outpatient medical care, inpatient medical care and emergency medical care. The model is divided into health care use, hospital stays, and medical expenses. In the health model, the independent variables consist of confounding variables such as sex, age, smoking status, drinking status, and hospitalization. In the health care use model, confusion variables include sex, age, health status, smoking status, and drinking status. Treatment independent variables are divided into exercise types. Lastly, the exercise model consists of exercise, vigorous exercise, moderate exercise, and walking activity. The exercise model consists of total exercise volume, intense exercise amount, moderate exercise amount, and walking exercise amount. The exercise model was constructed with all the factors related to exercise in order to find out the factors that influence exercise, not the viewpoint of medical needs. Therefore, the independent variables of the exercise model included gender, age, marital status, number of household members, health status, education level, household income, medical security, smoking status, drinking status, obesity index, region, and outpatient health care use.
The regression-based approach is used to analyze the difference between health level and health care use according to exercise, and then controls the sex, age and health status, and health risk factors. We assessed whether there was a difference between health and health care use, and quantified the difference between what is considered a health care use given basic medical needs. In the case of the model where the dependent variable is binary, the error term is normally distributed among the nonlinear models. In this study, the probit model is applied. Were simultaneously estimated. That is, a selection equation that estimates the probability of using each medical type to solve a selection problem, and an outcome equation that estimates health care use such as hospital stays or copayment costs for each medical type. Were estimated simultaneously using MLE. Also, in the exercise model, the selection equation for estimating exercise selection probability for each exercise type and the result equation for estimating exercise amount for each exercise type were simultaneously estimated using MLE as in the health care use model.
The first study quantitatively estimated how exercise affects health levels and, if so, how much. For this purpose, the health level was estimated quantitatively with the likelihood ratio test by setting four models of the disease experience rate, the number of disease days, the chronic disease status index, and the subjective health index perceived by me. Likelihood ratio test for all health level models showed that exercise had a significant effect on health level. In particular, it was estimated that those who exercise any exercise had better health than those who did not exercise at all in terms of the experience of sickness, days of illness, chronic disease status index, and subjective health index. Compared to those who do not exercise, 3.12% p of exercisers, 2.62% p of intense athletes, 3.05% p of moderate athletes, and 3.5% p of walking athletes have more sickness experience. It was estimated to be low. The number of sick days was 1.36 days for those who exercised, 1.17 days for intensive exercise, 1.26 days for moderate exercise and 1.31 days for walking exercise. The chronic disease index was 0.27 lower for exercisers, 0.28 for strenuous exercise, 0.32 for moderate exercise, and 0.36 for walking exercise, compared to those who did not exercise. The subjective health index that I perceived was healthier than those who did not exercise, 0.66 for those who exercise, 0.66 for those who exercise vigorously, 0.77 for those who do moderate exercise, and 0.85 for those who walk. Low. These results generally support the general hypothesis that exercise increases health levels, and quantitatively demonstrates how much better people exercise than those who do not exercise.
The second quantitatively estimated how exercise affects health care use and if so, to what extent. For this purpose, health care use was estimated quantitatively with the likelihood ratio test by setting outpatient, hospitalization and emergency medical models in terms of health care use experience, days of hospitalization and out-of-pocket medical expenses. The health care use effect of exercise was estimated to affect outpatient and hospitalization expenses except emergency medical treatment. Basically, the outpatient utilization rate, inpatient experience rate, and emergency health care use estimated after controlling factors such as gender, age, and health level that caused the difference in medical needs and the degree of practice of health behavior such as smoking and drinking Experience rates, outpatient visits, hospital stays, and emergency days were all lower than non-exercisers. However, in the case of medical expenses, outpatient medical expenses were lower in exercisers than non-exercisers, while in-patient and emergency medical expenses were lower in exercisers than non-exercisers. After controlling for the factors, the estimated patient burden medical expenses were higher for exercisers than for non-exercisers. This can be caused by various kinds of medical institutions or disease severity between exercisers and non-exercisers.
Third, we estimated an exercise model to find out what factors influence exercise. The exercise model was constructed and estimated by dividing four types of intensive exercise, moderate exercise, walking exercise, and three types of total exercise into exercise experience rate and exercise amount. In general, one of the most influential variables in athletic practice was gender. In other words, females are more experienced than males in terms of sex, females in their 30s and 44s and more than 75s in terms of age, and are single, single, separated, separated or separated from spouses in terms of marital status Significantly lower. In addition, the exercise experience rate of those with poor health was low, and the education experience rate increased with higher education and household income. In terms of health life practice, current smokers had low exercise experience rate, but non-smoking smokers had high exercise experience rate. This suggests that current smokers may not realize the need for exercise because they have not had any major health problems. On the other hand, it is estimated that the non-smoking person may have experienced exercise to promote health because of poor health or interest in health. The relationship between drinking and exercise was not statistically significant. As the obesity index is higher, the exercise experience rate tends to decrease, which is also considered to have caused obesity problems.
4. Conclusion and Implications
The results of this study support the general hypothesis that exercise will increase health levels in general, and quantitatively demonstrate how much better health levels are for exercisers than for non-exercisers. In terms of health care use, although it differs depending on the type of medical care, it supports the findings of reducing health care use. Therefore, in order to realize the life cycle movement program support project in the detailed project of the national health promotion comprehensive plan established by the government, cooperation between each sector should be strengthened and the infrastructure for the project should be supplemented. In particular, discussions over the existing practice such as health care service and chronic disease management system have been active in recent years, but the response from the medical field seems to be inadequate. The findings of this study are as follows. At the national level, there is a need to lead a comprehensive campaign of athletics, a social advocacy activity for strengthening
the school's sports environment and facilities that can promote sports, and provides consultations and data from doctors during primary care, as well as referrals between medical and sports professionals. You need to find a business plan. In addition, walking projects can be considered for groups who do not exercise. At the local level, it will be necessary to keep pace with national projects through social advocacy activities, such as the establishment of places to exercise and improvement of accessibility and staircase utilization projects, depending on the local government's circumstances. At the time of consultation, exercise counseling and data provision, patient referral to the medical and athletic field, and reorganization of the health insurance system should be initiated, and the focus should be on reducing the burden of chronic diseases.
As Korean society integrates more and more into the global village at large, the number of migrant children with Korean backgrounds and living outside Korea continues to grow. The double challenge of having to adapt to the new society and the new family environment complicates the prospects for these children growing into well-adapted and thriving citizens. This study sheds light on Korean migrant children who have returned, with their parents, to Yanbian in China and Vietnam - two major places of origin for many marriage immigrants.
Despite the government’s efforts to increase fertility rate, Korea’s period total fertility rate was tentatively counted at 0.92 in 2019, which is consistently below 1 in 2018. This study looked at the long-term trends in the cohort total fertility rates, and analyzed postponement and recuperation of child births in each group of birth cohort. Both period total fertility rates and cohort fertility rates fell significantly. This means that the number of children women give birth during her reproductive period has decreased. Period total fertility rate fell because the age of childbirth rose and the delayed childbirth was not realized. The recent drop in the cohort fertility rate was largely due to the increase in women who did not have children. It is unlikely that Korea will expect to see a rebound in the fertility rate in the near future because delayed childbirths were hardly realized. The instability of the labor market due to the economic recession is likely to lead to uncertainty toward the future, resulting in involuntary unmarried young people. Promoting social policy to help younger generation have a positive outlook and a sense of stability is essential to tackling the deepening low birth rate.
The 23rd Global Social Security Forum: The Challenges and Role of Poverty Policy: Brazil and the UK's Experience in Focus11 December 2019 - 1:00 p.m. to 5:30 p.m.Brahams Hall(19th Floor), Hotel President, SeoulHosted by Sejong Welfare Foundation and the Korea Institute for Health and Social Affairs Program 13:00-13:20 Registration 13:20-14:00 Presentation: Poverty and Anti-Poverty Policy in the UK, David Gordon, Professor, University of Bristol 14:00-14:30 Presentation: The Impact of Universal Credit on the Debts of the Poor in the UK, Rod Hick, Professor, Cardiff University 14:30-15:00 Discussion Moderator: Moon Jin-Young, Professor, Sogang University Discussants: Kim, Ki-tae, Associate Research Fellow, KIHASA; Jung Yun-Tae, Senior Research Fellow, Sejong Welfare Foundation; Choi Young Jun, Professor, Yonsei University 15:00-15:30 Coffee Break 15:30-16:00 Presentation: Brizilian Poverty Policy, Ana Paula Matias, Directory Technical Advisor, National Secretariat for the Promotion of Human Development 16:00-16:30 Presentation: Social Protection and Family Benefit in Brazil, Joana Mostafa, Research Specialist, Institute for Applied Economic Research of the Federal Government of Brazil 16:30-17:00 Presentation: History of Social Security in Brazil, Martene Santos, Professor, University of Brasilia 17:00-17:30 Discussion Moderator: Lee Chang Gon, President, Hankyoreh Economy & Society Research Institute Discussants: Kwak Yoonkyung, Associate Research Fellow, KIHASA; Won Il, Research Fellow, Sejong Weflare Foundation; Lee Jeong-Hee, Research Fellow, Korea Labor Institute