Application of Bayesian model and Spatial-temporal scan statistic in mortality spatial distribution characteristics of gastric cancer

LIAO Wei-bin; SUN Jian-guo; YONG Wan-ling; YU Guo-wei; TIAN De-hong; WANG Xi-bei

doi:10.16462/j.cnki.zhjbkz.2016.08.023

Volume 20 Issue 8

Aug. 2016

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Article Navigation > CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION > 2016 > 20(8): 847-850

LIAO Wei-bin, SUN Jian-guo, YONG Wan-ling, YU Guo-wei, TIAN De-hong, WANG Xi-bei. Application of Bayesian model and Spatial-temporal scan statistic in mortality spatial distribution characteristics of gastric cancer[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2016, 20(8): 847-850. doi: 10.16462/j.cnki.zhjbkz.2016.08.023

Citation:

LIAO Wei-bin, SUN Jian-guo, YONG Wan-ling, YU Guo-wei, TIAN De-hong, WANG Xi-bei. Application of Bayesian model and Spatial-temporal scan statistic in mortality spatial distribution characteristics of gastric cancer[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2016, 20(8): 847-850. doi: 10.16462/j.cnki.zhjbkz.2016.08.023

Citation:

LIAO Wei-bin, SUN Jian-guo, YONG Wan-ling, YU Guo-wei, TIAN De-hong, WANG Xi-bei. Application of Bayesian model and Spatial-temporal scan statistic in mortality spatial distribution characteristics of gastric cancer[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2016, 20(8): 847-850. doi: 10.16462/j.cnki.zhjbkz.2016.08.023

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Application of Bayesian model and Spatial-temporal scan statistic in mortality spatial distribution characteristics of gastric cancer

doi: 10.16462/j.cnki.zhjbkz.2016.08.023

1. Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China;
2. Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou 730070, China;
3. Institute of West Environment and Health, Northwest University for Nationalities, Lanzhou 730124, China;
4. Institute of Nutrition and Food Hygiene, School of Public Health, Lanzhou University, Lanzhou 730000, China

Received Date: 2016-02-20
Rev Recd Date: 2016-05-28

Abstract

Abstract

Objective Based on the Bayesian model and the spatial-temporal scan statistic, to analysze the spatial distribution of gastric cancer from 2012-2013 in Liangzhou District of Wuwei, taking the percent of male mortality and the distribution of the river into consideration to estimate the relative risk of gastric cancer mortality, and provide the basis for gastric cancer risk factors and spatial aggregation analysis. Methods Based on the morality data of gastric cancer in Liangzhou district of Wuwei during 2012-2013, Bayesian model (BYM) and spatial-temporal scan statistics analysis were carried out. Results The result of Bayesian models showed there exist high relative risk areas in Liangzhou District of Wuwei from 2012 to 2013, which were distributed in the northern, central and southeast of Liangzhou district. The model with risk factors was performed better than BYM, and the result of spatial-temporal scan statistic indicated that there were two clusters of gastric cancer mortality in 2012, besides, the area with high RR value and spatial temporal clusters were similar. Conclusions The gastric cancer morality in Liangzhou District of Wuwei exist high risk and aggregation areas, and the distribution of these regions may related to the river pollution and other environmental risk factors, the correlation between these factors and high risk areas needs further study.
- Stomach neoplasms,
- Risk factors,
- Epidemiologic studies

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References(20)

References

Yang L. Incidence and mortality of gastric cancer in China [J]. World J Gastroenterol, 2006,12(1):17-20.

Rahman R, Asombang AW, Ibdah JA. Characteristics of gastric cancer in Asia [J]. World J Gastroenterol, 2014,20(16):4483-4490.

Gastric Cancer Diagnosis and Treatment Expert Panel of the Chinese Ministry of Health. Chinese guidelines for diagnosis and treatment of gastric cancer (2011 edition) [J]. Transl Gastrointest Cancer, 2012,1:103-14.

Kamangar F, Dores GM, Anderson WF. Patterns of cancer incidence, mortality, and prevalence across five continents: defining priorities to reduce cancer disparities in different geographic regions of the world [J]. J Clin Oncol, 2006,24(14):2137-2150.

Liu J, Sun LP, Gong YH, et al. Risk Factors of Precancerous Gastric Lesions in A Population at High Risk of Gastric Cancer. Chin J Cancer Res, 2010,22(4):267-273.

孔灵芝. 中国肿瘤死亡报告—全国第三次死因回顾抽样调查 [M]. 北京:人民卫生出版社, 2010.

罗好曾,付全德,冯春兰. 2001-2009年武威市凉州区胃癌发病和死亡状况分析 [J]. 中国初级卫生保健, 2011,25(11):80-82.

郑杨,李晓松. 贝叶斯时空模型在疾病时空数据分析中的应用 [J]. 中华预防医学杂志, 2010,44(12):1136-1139.

Bilancia M, Fedespina A. Geographical clustering of lung cancer in the province of Lecce, Italy: 1992–2001 [J]. Int J Health Geogr, 2009,8:40.

Cressie NAC. Statistics for spatial data (revised edition)[M]. New York, 1993,50(50).

Besag J, York J, Mollié A. Bayesian image restoration, with two applications in spatial statistics [J]. Annals of the Institute of Statistical Mathematics, 1991,43(1):1-20.

陈有明,张聘年,刘海峰,等. 2004-2005年甘肃省武威市凉州区癌症死因调查 [J]. 地方病通报, 2010,25(1):18-20.

罗好曾,米登海,景天忠,等. 胃癌高发区武威市胃癌发病因素探讨 [J]. 癌症, 2005,24(5):563-566.

Kulldorff M. A spatial scan statistic [J]. Communications in Statistics-Theory and Methods, 1997,26(6):1481-1496.

徐敏,曹春香,程锦泉,等. 甲流感疫情时空聚集性的GIS分析 [J]. 地球信息科学学报, 2010,12(5):707-712.

Spiegelhalter DJ, Best NG, Carlin BP, et al. Bayesian measures of model complexity and fit [J]. Journal of the Royal Statistical Society, 2002,64(4):583-639.

徐致祥,韩建英,谭家驹,等. 中国食管癌高发区形成的五大环境因素及预防策略 [K]. 2008.

韩建英,徐致祥,邢海平,等. 中国食管癌高发区与河流的相关研究 [J]. 河南预防医学杂志, 2008,19(1):1-3,封3,封4.

葛辉,周脉耕,王晓风,等. 多水平贝叶斯模型在灵璧县食道癌死亡率空间分布模式研究中应用 [J]. 中华疾病控制杂志,2013,17(6):534-537.

Best NG, Arnold RA, Thomas A, et al. Bayesian models for spatially correlated disease and exposure data [K]. 1999.

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