Classification of Urban and Rural Populations of Korea by Time Activity Pattern

Abstract

Time activity pattern is critical to assess personal exposure. Demographic and lifestyle factors may affect time activity pattern. The purposes of this study were to classify the metropolitan population by their time activity patterns and to determine difference of the time activity patterns between urban and rural areas. The time location pattern data for the 31,634 subjects were collected by the Time Use Survey of the Statistics Korea. Seoul and Busan, the two largest metropolitan cities in Korea, were selected for classification of urban population in metropolitan cities. Daejeon and Chungcheongnam Province (Chungnam) were selected to compare the urban and rural areas, respectively. Multivariate linear regression was conducted to determine factors for residential indoor and transportation times in each region. Weekday time activity data of 1,000 subjects randomly selected from each region were used in cluster analysis. Ten groups were identified by the cluster analysis using K-mean method from each region. Characteristics of the groups were determined by analyzing personal characteristics including age, gender, education, marriage status, job, and monthly income. Nine groups with distinctive time activity patterns were identified each in Seoul and Busan. The population groups in the two cities had five comparable groups which had similar time activity patterns. Daejeon had nine distinctive time activity patterns and Chungnam had ten groups. The population groups in the two cities had five comparable groups. Compared to Daejeon, Chungnam population did not have groups of university students and non-working elderly. The rural area had three agricultural workers groups whose activity patterns were different: two groups stayed home at lunch time with different proportions of outdoor activity in daytime and the other went in and out of residence throughout the day without any specific patterns. High school students in Chungnam had similar patterns of elementary and junior high schools students, while they were different in Daejeon. Urban populations were classified by 9 activity patterns, although more characterization of the 9 groups is needed. While urban populations had similar activity patterns, activity patterns in rural population were different from urban population. Different activity patterns of urban and rural populations should be considered in exposure science study.