BACKGROUND: Little is known about geographic variations in liver cancer at high incident regions. We aimed to identify spatial variation of hepatocellular carcinoma (HCC) at a high-risk area in China and determine its association with socioeconomic status (SES). METHODS: Based on 2299 liver cancer cases diagnosed in Haimen from 2003 to 2006, we calculated age-sex standardized incidence ratios (SIRs) and used two spatial scan statistics to determine the geographic variations in HCC. Bayesian hierarchical model was used to explore the association between HCC incidence and SES. RESULTS: Age and sex SIRs for HCC varied from 0.54 to 1.97 for 24 townships. The eastern region of Haimen was identified to have a significantly increased risk of HCC. Fitting of a Bayesian hierarchical model linking per-capita fiscal revenue with SIRs of HCC indicated that the area with a lower revenue had a significantly higher incidence of HCC [beta(log(revenue))=-0.179, posterior 95% Bayesian credible interval (CI)=(-0.326, -0.04)]. CONCLUSIONS: This study demonstrated substantial geographic variation in the incidence of HCC within a high-risk region, which was associated with SES. HCC control and intervention should focus on disadvantaged areas to reduce the HCC disparities.
BACKGROUND: Little is known about geographic variations in liver cancer at high incident regions. We aimed to identify spatial variation of hepatocellular carcinoma (HCC) at a high-risk area in China and determine its association with socioeconomic status (SES). METHODS: Based on 2299 liver cancer cases diagnosed in Haimen from 2003 to 2006, we calculated age-sex standardized incidence ratios (SIRs) and used two spatial scan statistics to determine the geographic variations in HCC. Bayesian hierarchical model was used to explore the association between HCC incidence and SES. RESULTS: Age and sex SIRs for HCC varied from 0.54 to 1.97 for 24 townships. The eastern region of Haimen was identified to have a significantly increased risk of HCC. Fitting of a Bayesian hierarchical model linking per-capita fiscal revenue with SIRs of HCC indicated that the area with a lower revenue had a significantly higher incidence of HCC [beta(log(revenue))=-0.179, posterior 95% Bayesian credible interval (CI)=(-0.326, -0.04)]. CONCLUSIONS: This study demonstrated substantial geographic variation in the incidence of HCC within a high-risk region, which was associated with SES. HCC control and intervention should focus on disadvantaged areas to reduce the HCC disparities.
Authors: Fatma M Shebl; David E Capo-Ramos; Barry I Graubard; Katherine A McGlynn; Sean F Altekruse Journal: Cancer Epidemiol Biomarkers Prev Date: 2012-06-05 Impact factor: 4.254
Authors: E Christina Persson; Barry I Graubard; Alison A Evans; W Thomas London; Jean-Philippe Weber; Alain LeBlanc; Gang Chen; Wenyao Lin; Katherine A McGlynn Journal: Int J Cancer Date: 2012-03-15 Impact factor: 7.396
Authors: Tao Hu; Qingyun Du; Fu Ren; Shi Liang; Denan Lin; Jiajia Li; Yan Chen Journal: Int J Environ Res Public Health Date: 2014-03-14 Impact factor: 3.390