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자료유형
학술저널
저자정보
Kaewpitoon, Soraya J (Parasitic Disease Research Unit, Suranaree University of Technology) Rujirakul, Ratana (Parasitic Disease Research Unit, Suranaree University of Technology) Loyd, Ryan A (School of Family Medicine and Community Medicine, Suranaree University of Technology) Matrakool, Likit (Suranaree University of Technology Hospital, Suranaree University of Technology) Sangkudloa, Amnat (Geographic Information Technology Program, Faculty of Information Technology, Rajabhat Maha Sarakham University) Kaewthani, Sarochinee (Social Development Program, Faculty of Humanities and Social Science, Nakhon Ratchasima Rajabhat University) Khemplila, Kritsakorn (Environmental Technology Program, Nakhon Ratchasima Rajabhat University) Eaksanti, Thawatchai (Faculty of Public Health, Nakhon Ratchasima Rajabhat University) Phatisena, Tanida (Faculty of Public Health, Nakhon Ratchasima Rajabhat University) Kujapun, Jirawoot (Faculty of Public Health, Vongchavalitkul University) Norkaew, Jun (Faculty of Public Health, Vongchavalitkul University) Joosiri, Apinya (Parasitic Disease Research Unit, Suranaree University of Technology) Kaewpitoon, Natthawut (Parasitic Disease Research Unit, Suranaree University of Technology)
저널정보
아시아태평양암예방학회 Asian Pacific journal of cancer prevention : APJCP Asian Pacific journal of cancer prevention : APJCP 제17권 제2호
발행연도
2016.1
수록면
719 - 722 (4page)

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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.

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