본 연구에서는 질병관리본부에서 수집한 2009년 심정지 조사 자료 및 지역사회건강 조사 자료에 생태학적 방법론 및 지리적 가중회귀모형(GWR)을 적용하여 지역단위의 심정지 발생 위험요인을 규명함은 물론, 지역별 심정지 예방관리 사업에 GWR 모형 적용의 유용성도 함께 검토하고자 하였다. 그 결과, 지역별 심정지 발생의 주요 요인으로 중등도 신체활동 실천율, 비만율, 고혈압 평생 의사 진단 경험률 및 당뇨병 평생의사 진단 경험률이 도출되었고, 지역별로 일부 차이가 존재하나 대체로 이들이 높을수록 심정지 발생률이 높게 나타났다. 모형개발에 사용된 자료의 한계로 인해 본 연구에서 도출된 GWR 모형의 설명력은 낮으나, 모형 부합도를 비교한 결과 전통적인 OLS 모형보다는 우수한 모형인 것으로 나타났다. 개인별 자료 확보 대비 지역사회 단위 자료확보의 용이성 및 GWR 모형이 가지는 특성 등을 고려해볼 때, 향후 이와 관련된 후속연구가 지속적으로 진행된다면 각 지역별 심정지 발생 예방관리를 위한 우선 사업 순위선정에 본 연구에서 접근한 방법이 매우 유용할 것으로 판단된다.;This study sought to use the ecological study design and geographically weighted regression(GWR) to identify regional factors regarding the occurrence of cardiac arrest and to investigate the utility of GWR. Our data came from two main sources: 2009 Out-of-Hospital Cardiac Arrest Surveillance and Community Health Survey. As the result, risk factors on cardiac arrest are moderate-intensity physical activity, obesity rate, diagnosis rates of hypertension and diabetes mellitus which generally increase incidences of cardiac arrest. Our finding showed that GWR increased goodness-of-fit of model in comparison with traditional OLS regression. Considering the usefulness of ecological studies and GWR, methods of this study will help policymakers in terms of planning health programs and identifying priority regions for prevention of cardiac arrest.
1988년 국민연금제도의 도입 이후 기금적립금 규모는 지속적으로 막대한 규모로 증가하고 있어 국민연금기금이 금융부문은 물론 경제전반에 미치는 파급효과가 매우 클 것으로 예상된다. 따라서 본 고에서는 국민연금부문을 포함한 거시계량모형을 구축하여 GDP, 임금수준, GDP환가지수, 고용수준 및 회사채유통수익률 등의 주요 거시경제변수들의 국민연금기금에 대한 민감도 분석을 통하여 국민연금기금이 이들 거시경제변수에 미치는 파급효과를 분석하였다. 또한 국민연금기금은 현재의 빠른 기금증가에도 불구하고 저부담-고급여 구조와 인구구조의 고령화 등으로 장기적 관점에서는 재정 건전성이 문제로 지적되고 있는 바, 분석은 국민연금 기금규모의 변화가 거시경제변수에 미치는 파급효과를 장기적인 문제점중의 하나인 재정건전성 문제에 대한 근본적인 해결방안인 ‘보험료의 증가’와 ‘급여의 감소’ 두 가지 시나리오 하에 분석하였다. 분석결과, 주요 거시경제변수의 적립기금 단위변화에 대한 민감도의 크기는 보험급여의 감소에 의한 경우가 보험료증가에 의한 경우보다 크게 나타났으며, 주요 거시경제변수별 민감도의 크기는 두 시나리오 모두 회사채유통수익률, 임금수준, GDP, GDP환가지수, 고용수준의 순으로 나타났다.;Since the introduction of the National Pension Scheme (NSP) in 1988, the balance of the National Pension Fund (NPF) has been rising continuously, reaching 61 trillion won in 2000. The Fund is expected to reach 517 trillion won, taking up 43.4% of GDP, by the year 2020. The huge volume of the NPF is likely to affect profoundly not only the banking sector and stock market of Korea, but also Korea's economy as a whole. Despite this, however, the problem of financing has long been at the center of heated debate among pension specialists and scholars because, under the current low-contributionhigh- benefit structure and the increasing pace of population aging, the depletion of the fund is likely in a long-term perspective. In this regard, this paper aims to analyze, based on the national pension macroeconometric (NPM) model, the impact the NPF has on such major macroeconomic fundamentals as GDP, GDP deflator, national employment level, wage and interest rate. The sensitivity analysis of major economic variables is carried out in the context of two scenarios that often use such pensionrelated exogenous variables as contribution and benefit. In the first scenario, the contribution is increased by 10%, while in the second, the benefit is reduced by 10%. In both scenarios, the problem of financing is alleviated. The NPM model, a modified version of Keynesian macroecomomic model, reflects restraint on supply side by GDP gap. The GDP gap affects the price level, and the goods sector, in turn, is influenced by the change in the real money supply that is associated with a change in the price level. The analysis of these scenarios is conducted based on Gauss-Seidel Method (historical simulation analysis). The NPM model is composed of 12 behavioral equations that are estimated by Ordinary Least Square (OLS) method, 4 equations of definition and 1 identity. NPM model used time series data of National Income Account from 1970 to 2000. In estimating behavioral equations, the problem of sample size arises due to the short history of the NPS. If the estimating equation contains a national pension-related variable as an independent variable, the availability of annual data is confined to 13 data points. So, to avoid the problem of insufficient data, national pension-related variables are included in the other explanatory variables of the behavioral equations. For example, disposable income, one of the explanatory variables in private consumption function, is drawn by subtracting total contribution from, and adding total payment to, the disposable income amount of national income account. For the criterion of the NPM model, arithmetic mean of root mean squared error (RSME) of endogenous variable (0.089) is used. The simulation results are as follows. In the scenario of increased contribution rate, a 1% increase in NPF leads to increases in GDP (1.26%), employment level (0.35%), wage (1.66%) and GDP deflator (0.75%), while bringing out a 19.00% decrease in the interest rate. In the second scenario of decreased benefit level, a 1% increase in NPF brought increases in GDP (1.83%), employment level (0.54%), wage (2.04%) and GDP deflator (0.81%), but the interest rate falls by 33.26%. In terms of the degree of sensitivity of the macroeconomic variables, interest rate came first, followed in order by rate, wage, GDP, GDP deflator, and employment level in both scenarios. The degree of impact is found to have been greater in the second scenario than in the first. The immediate implication for policymakers is that they should take benefit reduction approach to alleviate the problem of financing NPS.