• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.66-71
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• 2003

This study investigates the spatial patterns of distributed population in terms of population density, age structure, sex structure and family structure in Chou (smallest political city boundaries) of seven cities of Kitakawachi region. This displays the population dynamics of those cities from 1955 to 1995. It demonstrates how the populations of the cities are distributed with topography and with respect to the train stations. The demographic characteristics of the cities are visualized utilizing Arc View GIS capabilities with new visualizing technique in 3D environment based on data from Pasco Digital Map 2000.

• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.919-924
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• 2009

Geographical location carries information such as demography, local economy, environment, and life styles, which could be the sources of cancer occurrence. Analyzing geographical location associated with cancer occurrence can be instructive to physicians, patients, and health administrators regarding resource allocation, expenditures, prophylaxis and treatments. In this paper, we explored the correspondence relationship between geographical locations and mortality rates of the cancers using correspondence analysis and illustrated the approach with the mortality rates of the top 10 cancers in the 75 counties in Arkansas from 2001 to 2005. Geographical variations with respect to the mortality rates of cancers are evaluated across Arkansas counties. Based on the contingency table, correspondence analysis model is developed and the simple indices which indicate the degree to which the regions and the cancers affect each other are calculated. Quantitative results are visualized and mapped in two-dimensional graphs.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.2
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• pp.719-722
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• 2016

Background: Cholangiocarcinoma (CCA) is a serious health problem in Thailand, particularly in northeastern and northern regions, but epidemiological studies are scarce and the spatial distribution of CCA remains to be determined. A database for the population at risk is required for monitoring, surveillance and organization of home health care. This study aim was to geo-visually display the distribution of CCA in northeast Thailand, using a geographic information system and Google Earth. Materials and Methods: A cross-sectional survey was carried out in 9 sub-districts and 133 villages in Chum Phuang district, Nakhon Ratchasima province during June and October 2015. Data on demography, and the population at risk for CCA were combined with the points of villages, sub-district boundaries, district boundaries, and points of hospitals in districts, then fed into a geographical information system. After the conversion, all of the data were imported into Google Earth for geo-visualization. Results: A total of 11,960 from 83,096 population were included in this study. Females and male were 52.5%, and 47.8%, the age group 41-50 years old 33.3%. Individual risk for CCA was identifed and classified by using the Korat CCA verbal screening test as low (92.8%), followed by high risk (6.74%), and no (0.49%), respectively. Gender ($X^2$-test=1143.63, p-value= 0.001), age group ($X^2$-test==211.36, p-value=0.0001), and sub-district ($X^2$-test=1471.858, p-value=0.0001) were significantly associated with CCA risk. Spatial distribution of the population at risk for CCA in Chum Phuang district was viewed with Google Earth. Geo-visual display followed Layer 1: District, Layer 2: Sub-district, Layer 3: Number of low risk in village, Layer 4: Number of high risk in village, and Layer 5: Hospital in Chum Phuang District and their related catchment areas. Conclusions: We present the first risk geo-visual display of CCA in this rural community, which is important for spatial targeting of control efforts. Risk appears to be strongly associated with gender, age group, and sub-district. Therefor, spatial distribution is suitable for the use in the further monitoring, surveillance, and home health care for CCA.

• Health Policy and Management
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• v.30 no.1
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• pp.50-61
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• 2020

Background: This study aims to analyze the effects of air pollutants, such as particular matter, to the number of outpatient visits for allergic rhinitis in eup, myeon, and dong administrative boundaries. Methods: Dependent variable was the number of outpatient visits for allergic rhinitis per 10,000 people by region. Independent variables were air pollutants such as PM₁₀, PM_2.5, SO₂, O₃, CO₂, NO₂, and temperature that estimated by using Kriging analysis in all eup, myeon, and dong boundaries. Panel analysis was applied for the analysis to prove the relation between outpatient visits and the concentration of air pollutants. Results: Analysis results showed that particular matter concentration varied by regions and season. Panel analysis showed that outpatient visits for allergic rhinitis had positive relationships with PM₁₀, PM_2.5, SO₂, O₃, and CO₂ in all panel models. Conclusion: Regional variation of particular matter concentration should be considered in establishing regional policies for allergic rhinitis.

• Journal of the Korean Geographical Society
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• v.47 no.1
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• pp.98-120
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• 2012

The main objective of this study is to conduct subnational population projections of Korea based on a multiregional cohort-component method. This objective is accomplished by: (i) establishing a viable framework to implement the multiregional cohort-component method with reference to the Markov chain model and Rogers' multiregional population projection model; (ii) applying the established framework to subnational population projections of Korea, 2005~2030. The main results are twofold. First, the proposed method turns out to be highly valid in a methodological sense, which is seen from a high level of coincidence between the estimated and the observed. Second, the projection results turn out to be highly useful in the sense that interregional migration flow matrices are resulted for projection periods. The projected migration flows are expected to provide invaluable information for an understanding of future population change and for a formulation of policy alternatives. This study is strongly inspired by the multiregional perspective emphasizing the evolution of multiple regional populations interconnected by interregional migration flows rather than the overall national change.