Liver Cancer Disparities in New York City: A Neighborhood View of Risk and Harm Reduction Factors

Liver cancer is highly fatal, and death rates in the United States are increasing faster than for any other cancer, having doubled since the mid-1980s. In 2017, it is estimated that the disease will account for about 41,000 new cancer cases and 29,000 cancer deaths in the United States. In this article, data from the Surveillance, Epidemiology, and End Results (SEER) Program and the National Center for Health Statistics are used to provide an overview of liver cancer incidence, mortality, and survival rates and trends, including data by race/ethnicity and state. The prevalence of major risk factors for liver cancer is also reported based on national survey data from the Centers for Disease Control and Prevention. Despite the improvement in liver cancer survival in recent decades, only 1 in 5 patients survives 5 years after diagnosis. There is substantial disparity in liver cancer death rates by race/ethnicity (from 5.5 per 100,000 in non-Hispanic whites to 11.9 per 100,000 in American Indians/Alaska Natives) and state (from 3.8 per 100,000 in North Dakota to 9.6 per 100,000 in the District of Columbia) and by race/ethnicity within states. Differences in risk factor prevalence account for much of the observed variation in liver cancer rates. Thus, in contrast to the growing burden, a substantial proportion of liver cancer deaths could be averted, and existing disparities could be dramatically reduced, through the targeted application of existing knowledge in prevention, early detection, and treatment, including improvements in vaccination against hepatitis B virus, screening and treatment for chronic hepatitis C virus infections, maintaining a healthy body weight, access to high-quality diabetes care, preventing excessive alcohol drinking, and tobacco control, at both the state and national levels. CA Cancer J Clin 2017;67:273-289. © 2017 American Cancer Society.

Background Pandemic A (H1N1) 2009 mortality rates varied widely from one country to another. Our aim was to identify potential socioeconomic determinants of pandemic mortality and explain between-country variation. Methodology Based on data from a total of 30 European countries, we applied random-effects Poisson regression models to study the relationship between pandemic mortality rates (May 2009 to May 2010) and a set of representative environmental, health care-associated, economic and demographic country-level parameters. The study was completed by June 2010. Principal Findings Most regression approaches indicated a consistent, statistically significant inverse association between pandemic influenza-related mortality and per capita government expenditure on health. The findings were similar in univariable [coefficient: –0.00028, 95% Confidence Interval (CI): –0.00046, –0.00010, p = 0.002] and multivariable analyses (including all covariates, coefficient: –0.00107, 95% CI: –0.00196, –0.00018, p = 0.018). The estimate was barely insignificant when the multivariable model included only significant covariates from the univariate step (coefficient: –0.00046, 95% CI: –0.00095, 0.00003, p = 0.063). Conclusions Our findings imply a significant inverse association between public spending on health and pandemic influenza mortality. In an attempt to interpret the estimated coefficient (–0.00028) for the per capita government expenditure on health, we observed that a rise of 100 international dollars was associated with a reduction in the pandemic influenza mortality rate by approximately 2.8%. However, further work needs to be done to unravel the mechanisms by which reduced government spending on health may have affected the 2009 pandemic influenza mortality.

Individuals who use sexually transmitted disease (STD) clinics are at high risk for hepatitis B virus (HBV). While HBV vaccine is frequently offered to clients in this setting, reported vaccination rates are low. More information is needed about HBV vaccine knowledge, attitudes, beliefs, and behavior among high risk populations. The current study assesses these issues at an urban STD clinic. A survey assessing knowledge, attitudes, and beliefs concerning HBV vaccine was administered to individuals seeking services at an STD clinic before seeing the physician. Immediately after the clinical visit these individuals were interviewed and asked whether they had accepted vaccination and their reasons for acceptance or rejection. Fifty percent of unvaccinated study subjects elected to receive an HBV vaccine dose at the current visit. Significant predictors in a multiple logistic regression model for choosing to be vaccinated were: having a vaccinated acquaintance, perceived risk of disease, perceived healthfulness of vaccine, and clinician's recommendation. Knowledge regarding hepatitis B risks and outcomes was not related to vaccine choices. Patients expressed concern about vaccine safety and provider motivation. The role of acquaintances and the physician are central to the decision to be vaccinated, as are risk perception and familiarity with the vaccine. Mistrust of the medical establishment and of vaccines is a barrier to acceptance of HBV vaccine.