Mary M Ford1, Elena Ivanina2, Payal Desai3, Linda Highfield4, Baozhen Qiao5, Maria J Schymura5, Fabienne Laraque3. 1. Division of Disease Control, Bureau of Communicable Disease, New York City Department of Health and Mental Hygiene, 42-09 28th St, Long Island City, NY, 11101, USA. mford@pcdc.org. 2. Division of Epidemiology, New York City Department of Health and Mental Hygiene, 42-09 28th St, Long Island City, NY, 11101, USA. 3. Division of Disease Control, Bureau of Communicable Disease, New York City Department of Health and Mental Hygiene, 42-09 28th St, Long Island City, NY, 11101, USA. 4. Department of Management, Policy and Community Health Practice, University of Texas School of Public Health, 1200 Pressler RAS Bldg., E913, Houston, TX, 77030, USA. 5. New York State Department of Health, Bureau of Cancer Epidemiology, 150 Broadway Suite 361, Albany, NY, 12204, USA.
Abstract
PURPOSE: Liver cancer (hepatocellular carcinoma (HCC)) incidence and mortality rates are increasing in the United States. New York City (NYC) has a high burden of liver cancer risk factors, including hepatitis C (HCV) and hepatitis B (HBV) infection, which disproportionately affect persons of low socioeconomic position. Identifying neighborhoods with HCC disparities is essential to effectively define targeted cancer control strategies. METHODS: New York State Cancer Registry data from 1 January 2001 through 31 December 2012 were matched with NYC HCV and HBV surveillance data. HCC data were aggregated to NYC Zip Code Tabulation Areas (ZCTAs). Moran's I cluster analysis, Poisson regression, and geographically weighted Poisson regression were used to identify hotspots in HCC incidence and to examine the spatial associations with viral hepatitis rates, poverty, and uninsured status. RESULTS: Among NYC residents, 8,827 HCC cases were diagnosed during 2001-2012. Significant clustering was detected in the HCC rates (Moran's I = 0.25) with the strongest clustering found in HCC patients with comorbid HCV infection (Moran's I = 0.47). Poverty and uninsured status were associated (p < 0.05) with increased rates of HCC patients with HBV or HCV infection. Neighborhoods with high rates of HCC without viral hepatitis infection had lower rates of poverty and uninsured status. CONCLUSIONS: The geographic variation in HCC highlights the need for neighborhood-targeted interventions to address risk factors and barriers to care. The clusters of HCC by viral hepatitis status may serve as a basis for healthcare policymakers and practitioners to prioritize neighborhoods for cancer screening and control efforts.
PURPOSE:Liver cancer (hepatocellular carcinoma (HCC)) incidence and mortality rates are increasing in the United States. New York City (NYC) has a high burden of liver cancer risk factors, including hepatitis C (HCV) and hepatitis B (HBV) infection, which disproportionately affect persons of low socioeconomic position. Identifying neighborhoods with HCC disparities is essential to effectively define targeted cancer control strategies. METHODS: New York State Cancer Registry data from 1 January 2001 through 31 December 2012 were matched with NYC HCV and HBV surveillance data. HCC data were aggregated to NYC Zip Code Tabulation Areas (ZCTAs). Moran's I cluster analysis, Poisson regression, and geographically weighted Poisson regression were used to identify hotspots in HCC incidence and to examine the spatial associations with viral hepatitis rates, poverty, and uninsured status. RESULTS: Among NYC residents, 8,827 HCC cases were diagnosed during 2001-2012. Significant clustering was detected in the HCC rates (Moran's I = 0.25) with the strongest clustering found in HCC patients with comorbid HCV infection (Moran's I = 0.47). Poverty and uninsured status were associated (p < 0.05) with increased rates of HCC patients with HBV or HCV infection. Neighborhoods with high rates of HCC without viral hepatitis infection had lower rates of poverty and uninsured status. CONCLUSIONS: The geographic variation in HCC highlights the need for neighborhood-targeted interventions to address risk factors and barriers to care. The clusters of HCC by viral hepatitis status may serve as a basis for healthcare policymakers and practitioners to prioritize neighborhoods for cancer screening and control efforts.
Authors: Amin Bemanian; Laura D Cassidy; Raphael Fraser; Purushottam W Laud; Kia Saeian; Kirsten M M Beyer Journal: Cancer Causes Control Date: 2019-09-17 Impact factor: 2.506
Authors: Meera Sangaramoorthy; Juan Yang; Alice Guan; Mindy C DeRouen; Michele M Tana; Ma Somsouk; Caroline A Thompson; Joseph Gibbons; Chanda Ho; Janet N Chu; Iona Cheng; Scarlett Lin Gomez; Salma Shariff-Marco Journal: Cancer Epidemiol Biomarkers Prev Date: 2021-11-30 Impact factor: 4.090
Authors: Amin Bemanian; Laura D Cassidy; Raphael Fraser; Purushottam W Laud; Kia Saeian; Kirsten M M Beyer Journal: Int J Environ Res Public Health Date: 2021-09-15 Impact factor: 4.614