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. 2006 May;61(3):366-74.
doi: 10.1265/jjh.61.366.

[Descriptive epidemiologic studies on geographical clusterings of pancreatic cancer mortality and incidence--an analysis in Niigata, Japan]

[Article in Japanese]
Affiliations

[Descriptive epidemiologic studies on geographical clusterings of pancreatic cancer mortality and incidence--an analysis in Niigata, Japan]

[Article in Japanese]
Takayuki Seino et al. Nihon Eiseigaku Zasshi. 2006 May.

Abstract

Objectives: The objectives of this study were to determine the mortality for pancreatic cancer in the 47 prefectures of Japan and to reveal the geographical distribution of the mortality and incidence for pancreatic cancer in Niigata.

Methods: Standardized mortality ratio (SMR) for pancreatic cancer in the 47 prefectures from 1998 to 2002 was calculated on the basis of the census and vital statistics of Japan. The same SMR in the 36 cities and counties in Niigata from 1995 to 2002 was calculated. These SMRs were compared with that of the national population. Then, standardized incidence ratio (SIR) for pancreatic cancer in the 36 cities and counties in Niigata from 1995 to 2002 was calculated on the basis of the Niigata Cancer Registry, compared with that of the general population of Niigata.

Results: The SMRs for pancreatic cancer for both sexes in Hokkaido, Aomori, Akita, Miyagi and Shimane were significantly higher than that of the national population (p<0.05). The SMR for males in Niigata was significantly high, whereas that for females was near the SMR of the national population. Among the 36 cities and counties in Niigata, significantly high SMRs for both sexes were observed only in Higashikanbara county; the SMRs [95% confidence interval (CI)] were 158.4 (104.4-230.5) and 172.2 (114.4-248.9) for males and females, respectively.

Conclusions: Significantly high SMRs for pancreatic cancer were observed in Hokkaido and most of the Tohoku region. A geographical clustering of pancreatic cancer in Higashikanbara county was found. Further studies are needed to clarify the determinants of the clustering.

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