[논문]연령에 따른 교육수준과 만성질환의 관계

이민아

연령에 따른 교육수준과 만성질환의 관계
Differential Effects of Educational Attainment on Chronic Diseases with Age 원문보기

한국인구학 = Korea journal of population studies, v.34 no.1, 2011년, pp.179 - 198

이민아 (Department of Sociology, Chung-Ang University)

초록
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본 논문의 목적은 연령과 교육수준이 한국인의 만성질환에 미치는 영향을 분석하는 데 있다. 이를 위해 한국노동연구원이 2006년에 수집한 '고령화연구패널조사(KLoSA: Korean Longitudinal Study of Ageing)'에 참여한 45세 이상의 한국인을 분석하였다. 분석결과는 먼저 연령과 만성질환이 비선형 관계를 갖고 있음을 보여준다. 연령이 증가함에 따라 응답자가 만성질환을 앓고 있을 확률도 증가하나 약 74세를 기준으로 다시 감소한다. 또한 이러한 연령과 만성질환의 관계는 교육수준에 따라 다르게 나타났다. 교육수준이 낮을수록 상대적으로 이른 나이에 만성질환이 발현하여 70대 초까지 상대적으로 만성질환에 노출될 확률이 높게 나타난다. 그러나 이러한 교육수준에 따른 건강격차는 수렴현상(convergence)을 보이다가 70대 초반 이후부터 역전되어 다시 분기(divergence)한다. 즉, 고령층에서는 오히려 교육수준이 높을수록 만성질환을 가질 확률이 높게 나타나는 것이다. 이러한 결과는 교육수준이 낮은 사람들이 만성질환에 상대적으로 더 젊은 나이에 노출되고 결국에는 이른 사망으로 이어질 수 있다는 점을 함의한다.

Abstract ▼ AI-Helper

The purpose of this study was to examine relationships between chronic diseases, age, and education in Korea. Logistic regression techniques were used to analyze data from the Korean Longitudinal Study of Ageing (KLoSA), which is a nationally representative sample of Koreans aged 45 years and older. The findings show that probability of having chronic diseases increased with age up to about 74; however, it was reduced for respondents aged 74 years or older. Associations between age and chronic diseases were also differential by education. Less educated Koreans tended to have chronic diseases earlier in their lifetime; however, they were likely to have chronic diseases later in life less than more educated counterparts. The findings suggest that individuals with fewer years of education are at an increased risk of developing chronic diseases earlier in their lifetimes, thereby, leading to a higher rate of mortality at younger ages.

주제어

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문제 정의

In addition, according to cumulative inequality theory, given that advantages such as higher education accumulate over the life course, cumulative inequality leads to premature morality, which results in observation of reduced health inequality in later life(Ferraro and Shippee, 2009). This study supports that population truncation due to nonrandom mortality selection in old age can give the appearance of the converging and re-diverging inequality in chronic diseases. Lower educated people in the oldest group might be healthier than higher educated counterparts in that they are successful survivors.

제안 방법

Logistic regression was used to estimate the parameters of covariates in a sample of Koreans aged 45 and older.

대상 데이터

The data used in this study were drawn from the Korean Longitudinal Study of Ageing(KLoSA), collected by the Korean Labor Institute in 2006. The KLoSA is based on a nationally representative sample of Koreans aged 45 and older.

성능/효과

The relationships between education and chronic diseases are still significant after controlling for age and its quadratic term in model 2. Only middle school graduates became not significant after controlling for other covariates in model 3. Odds ratios of the significant education variables show that the likelihood of having chronic diseases reduces as educational level increases.
The findings of the present study show that the likelihood of having chronic diseases experienced by Koreans differs according to age and educational attainment. First, higher educated people were less likely to have chronic disease than lower educated counterparts even after controlling for all covariates in general. The findings support previous studies showing the beneficial effects of educational attainment on the health of Koreans(Son, 2002; Kim, 2007).
The second logistic regression model tests interactions between education and age in order to assess whether and how relationships between age and chronic diseases are affected by differential levels of education in the study sample. Using the results of logistic regression models, predicted probabilities of having chronic diseases classified by education and age would be calculated.

후속연구

This study has several limitations. First, although it is not a critical problem, in terms of causality between education and chronic diseases, that the data are cross-sectional, further studies need to analyze longitudinal data for examining relationships between onset of chronic diseases between survey waves and education. Another issue is that age and cohort effects are not distinguishable in the cross-sectional data analysis(Kim, 2007; Park, 2005).

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