The purpose of this research was to investigate the relationships between the socioeconomic condition, health attitude and the eye health of the elderly. Thereupon, this study is attributed to promote the eye health of the elderly. Data were collected through questionnaire by one-to-one interview in a community. The content of original questionnaires were revised by literature review and the pilot study. The sample was consisted of 285 elderly with a mean age of 71.8 years. In the study group, female was 52.3% and male was 47.7%, respectively. In age group, over 80 years was 16.5%, 75-79 was 21.0%, 70-74 was 29.5%, 65-69 was 26.0% and 60-64 was 7.0%. In maritai status, married and living with spouse was 54.4%, widowed was 45.6%. The elderly were suffering with diseases of arthritis(33.3%), hypertension(20.1%), cataract(14.2%) and diabetes(9.7%), respectively. Socioeconomics conditions were measured with monthly allowance money : The upper group those who can spend over 310,000 won was 13.6%, 110,000-300,000 won was 34.0%, less than 100,000 won was 52.5%, respectively. Therefore, the person who were very active health practice group were correlated positively with the wealthier group. Of the total, 33.2% of the elderly answered, they are suffering from two kinds of diseases combined at the same time. For the elderly who have the more concem on eye health were positively correlated with the higher educational level, live with spouse, and the ones who can spend the more monthly allowances. Eye health concem is positively correlated to health attitude.

This study tried to construct a direction in regional planning concerning the structural relationship between the ratio of aged population and the industrial characteristics. We investigated this structural relationship incorporating the aged population index and the number of classified companies. We applied diverse statistical analyses to understand the relationship. We classified the number of companies to reflect regional industrial characteristics using the principal component analysis. We applied a multiple regression model to understand the relationship between these two indices. The aged population index represents the degree of being old divided by the ratio of juvenile population and aged population. We found that such industries as manufacturing, service, and conveyance increase the ratio of juvenile population. However, industries such as tourism, waterworks, forestry, agriculture and etc. have a positive effect on the aged population index. In addition to these findings, we believe that the efficacy of this study is the possibility that can be used as the basic data when central or local autonomous entities need to adopt rural development planning.