Breast Cancer Clustering in Kanagawa, Japan: A Geographic Analysis

Katayama, Kazuhisa; Yokoyama, Kazuhito; Yako-Suketomo, Hiroko; Okamoto, Naoyuki; Tango, Toshiro; Inaba, Yutaka

doi:10.7314/apjcp.2014.15.1.455

Cited by 10 publications

(5 citation statements)

References 14 publications

(7 reference statements)

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“…It is worth pointing out that other studies have used FSSS to identify spatial clusters of other health outcomes such as measles (Tang et al, 2017), cancer (Katayama et al, 2014;Amin, Nelson & McDougall, 2018), suicide mortality (Yamaoka et al, 2020), and cardiovascular diseases (Roberson et al, 2019;Odoi et al, 2019). Recent research in Florida has demonstrated that FSSS is a useful technique for the identification of geographic disparities in stroke prevalence (Roberson et al, 2019) and hospitalizations due to myocardial infarction (Odoi et al, 2019).…”

Section: Spatial Patterns and Clusters Of Pre-diabetes Prevalencementioning

confidence: 99%

Geographic disparities, determinants, and temporal changes in the prevalence of pre-diabetes in Florida

Lord

Roberson

Odoi

2021

PeerJ

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Background Left unchecked, pre-diabetes progresses to diabetes and its complications that are important health burdens in the United States. There is evidence of geographic disparities in the condition with some areas having a significantly high risks of the condition and its risk factors. Identifying these disparities, their determinants, and changes in burden are useful for guiding control programs and stopping the progression of pre-diabetes to diabetes. Therefore, the objectives of this study were to investigate geographic disparities of pre-diabetes prevalence in Florida, identify predictors of the observed spatial patterns, as well as changes in disease burden between 2013 and 2016. Methods The 2013 and 2016 Behavioral Risk Factor Surveillance System data were obtained from the Florida Department of Health. Counties with significant changes in the prevalence of the condition between 2013 and 2016 were identified using tests for equality of proportions adjusted for multiple comparisons using the Simes method. Flexible scan statistics were used to identify significant high prevalence geographic clusters. Multivariable regression models were used to identify determinants of county-level pre-diabetes prevalence. Results The state-wide age-adjusted prevalence of pre-diabetes increased significantly (p ≤ 0.05) from 8.0% in 2013 to 10.5% in 2016 with 72% (48/67) of the counties reporting statistically significant increases. Significant local geographic hotspots were identified. High prevalence of pre-diabetes tended to occur in counties with high proportions of non-Hispanic black population, low median household income, and low proportion of the population without health insurance coverage. Conclusions Geographic disparities of pre-diabetes continues to exist in Florida with most counties reporting significant increases in prevalence between 2013 and 2016. These findings are critical for guiding health planning, resource allocation and intervention programs.

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Section: Spatial Patterns and Clusters Of Pre-diabetes Prevalencementioning

confidence: 99%

Geographic disparities, determinants, and temporal changes in the prevalence of pre-diabetes in Florida

Lord

Roberson

Odoi

2021

PeerJ

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“…Other relatively new developments regarding cancer registries include focusing on clustering, for example of breast cancer in Japan[42] and colorectal cancer in Malaysia[43]. Demonstration of quality of care measurement using the Japanese liver cancer registry has been reported[44] and improving trends in ‘cure’ fraction from colorectal cancer by age and tumour stage between 1975 and 2000 was established using population-based data for Osaka[45].…”

Section: Cancer Burden and Cancer Registriesmentioning

confidence: 99%

Cancer Control Programs in East Asia: Evidence From the International Literature

Moore¹

2014

J Prev Med Public Health

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Cancer is a major cause of mortality and morbidity throughout the world, including the countries of North-East and South-East Asia. Assessment of burden through cancer registration, determination of risk and protective factors, early detection and screening, clinical practice, interventions for example in vaccination, tobacco cessation efforts and palliative care all should be included in comprehensive cancer control programs. The degree to which this is possible naturally depends on the resources available at local, national and international levels. The present review concerns elements of cancer control programs established in China, Taiwan, Korea, and Japan in North-East Asia, Viet Nam, Thailand, Malaysia, and Indonesia as representative larger countries of South-East Asia for comparison, using the published literature as a guide. While major advances have been made, there are still areas which need more attention, especially in South-East Asia, and international cooperation is essential if standard guidelines are to be generated to allow effective cancer control efforts throughout the Far East.

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“…Thus, some studies have already attempted to monitor cancer‐related data on the basis of smaller units, such as cities, counties, towns, and even villages . Monitoring cancer‐related data on the basis of smaller units might not only obtain detailed information about the cancer incidences or mortalities, but also identify the potential clusters more accurately . The spatial statistical analysis developed by Kulldorff and Nagarwalla has been proved to be an effective method for discerning geographical patterns and detecting spatial clusters based on smaller units …”

Section: Introductionmentioning

confidence: 99%

Lung cancer mortality clusters in urban and rural areas of Shandong Province, China: A spatial scan statistical analysis

Chu

et al. 2019

Precision Radiation Oncology

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Objective: To detect the spatial distribution and high-risk clusters of lung cancer mortality for the years 2011-2013 in Shandong Province, China. The urban-rural differences in the spatial distribution and clusters of disease mortality were also examined.Methods: Lung cancer mortality data were obtained from Shandong Death Registration System during 2011-2013, and were adjusted with the underreporting rate. The purely spatial scan statistics method was carried out using a discrete Poisson model. Results: Seven significant spatial clusters of high mortality of lung cancer were detected in Shandong Province at the county level, mainly in the eastern, northern, central, and southwestern regions. The spatial distributions were different between urban and rural populations. Population aging influenced the distribution of lung cancer clusters for the urban and rural eastern region residents. Conclusions:This study provided evidence for the presence of clusters of lung cancer mortality in Shandong, China, and found urban-rural differences in the clusters, which might be helpful in developing effective strategies to control lung cancer in different areas. K E Y W O R D Slung cancer, mortality, Shandong, spatial scan statistics

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Breast Cancer Clustering in Kanagawa, Japan: A Geographic Analysis

Cited by 10 publications

References 14 publications

Geographic disparities, determinants, and temporal changes in the prevalence of pre-diabetes in Florida

Geographic disparities, determinants, and temporal changes in the prevalence of pre-diabetes in Florida

Cancer Control Programs in East Asia: Evidence From the International Literature

Lung cancer mortality clusters in urban and rural areas of Shandong Province, China: A spatial scan statistical analysis

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