Browse > Article
http://dx.doi.org/10.7314/APJCP.2014.15.1.455

Breast Cancer Clustering in Kanagawa, Japan: A Geographic Analysis  

Katayama, Kayoko (Cancer Prevention and Cancer Control Division, Kanagawa Cancer Center Research Institute)
Yokoyama, Kazuhito (Department of Epidemiology and Environmental Health, Juntendo University Faculty of Medicine)
Yako-Suketomo, Hiroko (Japan Women's College of Physical Education, Faculty of Sports and Health Sciences)
Okamoto, Naoyuki (Cancer Prevention and Cancer Control Division, Kanagawa Cancer Center Research Institute)
Tango, Toshiro (Center for Medical Statistics)
Inaba, Yutaka (Department of Epidemiology and Environmental Health, Juntendo University Faculty of Medicine)
Publication Information
Asian Pacific Journal of Cancer Prevention / v.15, no.1, 2014 , pp. 455-460 More about this Journal
Abstract
Background: The purpose of the present study was to determine geographic clustering of breast cancer incidence in Kanagawa Prefecture, using cancer registry data. The study also aimed at examining the association between socio-economic factors and any identified cluster. Materials and Methods: Incidence data were collected for women who were first diagnosed with breast cancer during the period from January to December 2006 in Kanagawa. The data consisted of 2,326 incidence cases extracted from the total of 34,323 Kanagawa Cancer Registration data issued in 2011. To adjust for differences in age distribution, the standardized mortality ratio (SMR) and the standardized incidence ratio (SIR) of breast cancer were calculated for each of 56 municipalities (e.g., city, special ward, town, and village) in Kanagawa by an indirect method using Kanagawa female population data. Spatial scan statistics were used to detect any area of elevated risk as a cluster for breast cancer deaths and/or incidences. The Student t-test was performed to examine differences in socio-economic variables, viz, persons per household, total fertility rate, age at first marriage for women, and marriage rate, between cluster and other regions. Results: There was a statistically significant cluster of breast cancer incidence (p=0.001) composed of 11 municipalities in southeastern area of Kanagawa Prefecture, whose SIR was 35 percent higher than that of the remainder of Kanagawa Prefecture. In this cluster, average value of age at first-marriage for women was significantly higher than in the rest of Kanagawa (p=0.017). No statistically significant clusters of breast cancer deaths were detected (p=0.53). Conclusions: There was a statistically significant cluster of high breast cancer incidence in southeastern area of Kanagawa Prefecture. It was suggested that the cluster region was related to the tendency to marry later. This study methodology will be helpful in the analysis of geographical disparities in cancer deaths and incidence.
Keywords
Breast cancer; cancer registry data; regional clustering; spatial epidemiology;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Fukuda Y, Nakamura K, Takano T (2005). Accumulation of health risk behaviors is associated with lower socioeconomic status and women's urban residence: a multilevel analysis in Japan. BMC Public Health, 5, 53.   DOI   ScienceOn
2 Health, Labour and Welfare Ministry (2005). Population Survey Report of Japan.
3 Hoover R, Mason TJ, McKay FW et al (1975). Cancer by county: new resource for etiologic clues. Science, 189, 1005-7.   DOI
4 Kanagawa Prefecture, Bureau of Health Welfare (2006). statistical yearbook of Kanagawa prefectural public health.
5 Kulldorff M (1997). A spatial scan statistic. Communication in Statistics. Theory and Methods, 26, 1481-96.   DOI   ScienceOn
6 Kulldorff M, Feuer EJ, MillerBA, et al (1997). Breast cancer clusters in the northeast United States: A geographical analysis. Am J Epidemiol, 146, 161-70.   DOI   ScienceOn
7 Kuroiwa T, Hirose K, Takezaki T, et al (2004). The cancer statistics white paper.-incidence/mortality/prognosis, cancer mortality in Japan (1950-2000). (in Japanese). Shinohara publishing company, Tokyo, pp 1-95.
8 Matsuda T, Marugame T, Kamo KI, et al (2011). The Japan Cancer surveillance research group: cancer incidence rates in Japan in 2005: based on data from 12 population-based cancer registries in the Monitoring of Cancer Incidence in Japan (MCIJ) Project. Jpn J Clin Oncol, 41, 139-47.   DOI   ScienceOn
9 Meng B, Wang JF, Zhang WZ, et al (2005). evaluation of regional disparity in china based on spatial Analysis. Scientia Geographica Sinica, 4, 393-400.
10 Takahashi K, YokoyamaT, TangoT (2010). FlexScan v3.1:Software for the Flexible Scan Statistic. Nath Inst Public Health. FlexScan User Guide, 1-15.
11 Ookubo T, Adachi S, Toyama T (1977). an application of the grid square method to the geographical distribution of mortality statistics i. geographical distribution of cancer mortality in Tokyo. Nihon Eiseigaku Zasshi, 32, 534-42 (in Japanese).   DOI
12 Alexander FE, McKinney PA, Moncrieff KC et al (1992). Residential proximity of children with leukaemia and non-Hodgkin's lymphoma in three areas of northern England. Br J Cancer, 65, 583-8.   DOI   ScienceOn
13 Openshaw S, Craft AW, Charlton M, et al (1988). Investigation of leukemia clusters by use of a geographical analysis machine. Lancet, 1, 272-3.
14 Sobue T, Katanoda K, Ajiki W, et al (2012).The Cancer Statistics white paper. (in Japanese). Shinohara Publishing Company, Tokyo, 1-273.
15 Kanagawa Prefecture, Bureau of Health Welfare (2011). Annual report of Kanagawa cancer registry, paragraph (34).Cancer Incidence in Kanagawa. rengousha-press, Kanagawa, 1-114.0
16 Tango T, Takahashi K (2012). A flexible spatial scan statistic with a restricted likelihood ratio for detecting disease clusters. Stat Med, 31, 4207-18.   DOI   ScienceOn
17 Tango T (2000). An introduction to Statistical Models. (in Japanese). Asakura Shoten, Tokyo. pp 1-256.
18 Tango T (2008). A spatial scan statistic with a restricted likelihood ratio. Japanese J Biometrics, 29, 75-95.   DOI
19 Tango T, Takahashi K (2005). A flexible shaped spatial scan statistic for detecting clusters. Int J Health Geographics, 4, 11.   DOI   ScienceOn
20 Tango T, Yokoyama T, Takahashi K (2007). An invitation to spatial epidemiology, medical statistics series No. 7. Asakura Shoten, Tokyo. pp 1-240.
21 Waller LA, Turnbull BW, Clark LC, et al (1992). Chronic disease surveillance and testing of clustering of disease and exposure: application to leukemia incidence and TCE-contaminated dumpsites in upstate New York. Environmentrics, 3, 281-300.   DOI
22 Cancer Statistics Editorial Committee Compilation (2010). Statistics for Cancer. Foundation for Cancer Research Promotion, Tokyo, 40-5.
23 Doi Y, Yokoyama T, Tango T et al (2010). Temporal trends and geographic clusters of mortality from amyotrophic lateral sclerosis in Japan, 1995-2004. J Neurol Sci, 298, 78-84.   DOI   ScienceOn
24 Ewertz M, Duffy S.W (1988). Risk of breast cancer in relation to reproductive factors in Denmark. Br J Cancer, 58, 99-104.   DOI
25 Nakaya T (2011). Evaluating Socio-economic inequalities in cancer mortality by using areal statistics in Japan: a note on the relation between municipal cancer mortality and areal deprivation index. Proceedings of the Institute of Statistical Mathematics, 59, 239-65.