Opportunity zones: Do tax benefits go to the most distressed communities?

Purpose The exact criteria used by state governors for choosing opportunity zones (OZs) are not publicly available. This paper aims to examine whether state governors selected the most distressed communities, or those with the highest proportions of minorities, as OZs. Design/methodology/approach This paper compares the distressed communities chosen as OZs in states throughout the country to an equal number of those eligible distressed communities but not selected. Moreover, this paper uses regression analysis to determine whether the poverty rate, median family income, population, percentage of population that is minority and the percentage of population that is African American are significant explanatory factors in the choice of OZs. Findings After describing the tax incentives for investing in OZs, this paper documents that governors did not select many of the most distressed communities, or those with high proportions of minorities, in their individual states. Originality/value This paper describes in some detail the way in which investors may generate tax benefits by investing in eligible property or businesses in OZs. It also examines the extent to which the degree of poverty and the percentage of the population that is minority (and African American) were key factors in the selection of OZs. It arises an issue that the chosen communities are not necessarily those most in need of more investment or those heavily populated by minorities, particularly African Americans.

Hispanic and Black Patients with Adult B-Cell Acute Lymphoblastic Leukemia Have a Significantly Worse Survival in the Modern Era - a SEER 2010-2016 Analysis

Prior studies have evaluated incidence and survival trends for B-Acute Lymphoblastic Leukemia (B-ALL) in children and adults. However, there have been no recent studies evaluating the difference in survival between different race and ethnicities in the era of tyrosine kinase inhibitors and novel combination therapy. We wanted to determine 5-year observed survival for adult patients with B-ALL diagnosed in recent years and assess for any difference in survival by race-ethnicity. Methods: We used Surveillance Epidemiology End Results (SEER) 18 registry to identify B-ALL patients using ICD-O-3 codes 9811-9818 and 9836. SEER 18 covers ~28% of US population. The year of diagnosis was limited to 2010-2016 in order to capture a patient population most likely treated with modern therapies. We limited our study to adults aged 20 years (yrs) or more, which were then divided into the following age groups: 20-29, 30-39, 40-49, 50-59, 60-69,70-79,80+ yrs of age. Gender, race-ethnicity, median family income and observed overall survival (OS) were obtained from SEER. For multivariate survival analysis, Cox proportional hazard model was used to adjust for clinically important and other relevant variables (age, gender, race-ethnicity, median income). We included median family income, a county level characteristic in our analysis as a surrogate for access to care. We divided these counties into quintiles based on median family income and included that variable in the multivariate model. We did not adjust for genetic risk or patient insurance status, as the information provided in SEER was inadequate and would likely lead to misclassification bias. SEER Stat 8.3.5 and SAS student edition were used for analysis. Results: 4244 cases of B-ALL were identified with an age adjusted incidence rate of 0.92 per 100,000. B-ALL occurred at all ages, but incidence was higher in young adults (<30 yrs) and adults older than 50 yrs of age, with peak incidence noted in the oldest age group (80+yrs). Of note, our cohort included adults older than or equal to 20 yrs of age, hence did not capture the early peak of childhood B-ALL. Females had a statistically significant lower incidence of B-ALL as compared to males (Incidence rate ratio (IRR) 0.77, p-value<0.05). Table 1 lists counts and IRR by different patient characteristics. Age adjusted incidence was the highest among Hispanics (1.61{1.53-1.71}), followed by Non-Hispanic Whites (NHW)(0.77{0.73-0.8}, Non-Hispanic Asian Pacific Islander (NHAPI)(0.7{0.63-0.78}) and Non-Hispanic Blacks (NHB)(0.54{0.47-0.61}); this difference was statistically significant (p-value <0.05). When we evaluated the age adjusted incidence rate in each age group by different race-ethnicities, Hispanics had a statistically significant higher incidence in each age group except in 80+ yrs age group. About 52% of population died during the study period from any cause. We limited our survival analysis to patients without second malignancy to avoid the confounding effect of another cancer associated mortality. We evaluated OS differences between race-ethnicity in a multivariate model that adjusted for age, sex and income. We found that when compared to NHW, Hispanics (Hazard Ratio (HR) 1.3{1.16-1.46}; p<0.01) and NHB (HR 1.24{1.03-1.5};p 0.02) had worse overall survival. We also showed increased mortality in older than younger adults with B-ALL (Table 2), in line with prior knowledge. There was slightly decreased OS seen in males compared to females, and the difference barely reached statistical significance (HR 0.91{0.83-1.0}; p 0.05). Patients from the poorest counties had worse survival than those in counties with higher median income (Table 2). Conclusion: Our study showed a significant survival disparity in adult B-ALL by race and ethnicity in the modern era. This can partly be attributed to differences in access to care as shown in our study. Interestingly, Hispanic and NHB have a significantly worse overall survival compared to NHW and NHAPI even after accounting for income differences, as a surrogate for access to care. This could be due to other unaccounted measure of health disparity, availability of allogeneic transplantation and/or difference in disease biology. Further studies are needed to evaluate such differences, identify barriers to care in minority populations and characterize potential differences in the genetic make-up of B-ALL in the various ethnic/racial groups. Disclosures Sica: Physician's Education Resources (PER): Honoraria. Verma:Stelexis: Equity Ownership, Honoraria; Acceleron: Honoraria; Celgene: Honoraria; BMS: Research Funding; Janssen: Research Funding.

Income and Wealth Disparities, and the Demand Curve

The Federal Reserve Bank in May 2016, reported “median family income is in the range between $40,000 and $49,999.” The middle class is shrinking. Income and wealth inequalities are hitting the demand curve causing anemic growth and more frequent, severe economic downturns. In 2011–2012, corporate profits had risen to constitute their largest share of the economy since 1929. The campaign finance cases and the increase in income inequality also appear highly correlated with a steep increase in government deficits and national debt. The logical implication of this work is that democracy may be necessary to establish, or sustain, capitalism. If political power becomes concentrated in relatively few people, then economic power will likely become similarly concentrated: oligarchy will lead to oligopoly. If democracy is necessary to obtain sustained capitalism, and if distributive autonomy is necessary to sustain democracy, it would appear that distributive autonomy is necessary to sustain capitalism.

INCREASE INCOME AND MORTALITY OF COLORRECTAL CANCER IN BRAZIL, 2001-2009

ContextSeveral international studies have observed a correlation between the improvement of socio-demographic indicators and rates of incidence and mortality from cancer of the colon and rectum.ObjectiveThe objective of this study is to estimate the correlation between average per capita income and the rate of colorectal cancer mortality in Brazil between 2001 and 2009.MethodsWe obtained data on income inequality (Gini index), population with low incomes (½ infer the minimum wage/month), average family income, per capita ICP and mortality from colon cancer and straight between 2001-2009 by DATASUS. A trend analysis was performed using linear regression, and correlation between variables by Pearson's correlation coefficient.ResultsThere was a declining trend in poverty and income inequality, and growth in ICP per capita and median family income and standardized mortality rate for colorectal cancer in Brazil. There was also strong positive correlation between mortality from this site of cancer and inequality (men r = -0.30, P = 0.06, women r = -0.33, P = 0.05) income low income (men r = -0.80, P<0.001, women r = -0.76, P<0.001), median family income (men r = 0.79, P = 0.06, women r = 0.76, P<0.001) and ICP per capita (men r = 0.73, P<0.001, women r = 0.68, P<0.001) throughout the study period.ConclusionThe increase of income and reducing inequality may partially explain the increased occurrence of colorectal cancer and this is possibly due to differential access to food recognized as a risk factor, such as red meat and high in fat. It is important therefore to assess the priority of public health programs addressing nutrition in countries of intermediate economy, as is the case of Brazil.

Effect of Socioeconomic Status on Surgery for Pancreatic Adenocarcinoma

Survival for pancreatic cancer remains poor. Surgical resection remains the only chance for cure. The intent of this study was to investigate the role of socioeconomic status (SES) on resection rates for pancreatic adenocarcinoma. The National Cancer Institute's Surveillance, Epidemiology, and End results database was used to identify patients with pancreatic adenocarcinoma. Disease was deemed resectable or unresectable based on the extent of disease code. Median family income was used as a SES variable to compare patients who underwent resection with those who did not. Median family income was organized into three categories based on definitions from the national census: less than $34,680 (low income), $34,680 to $48,650 (middle), and greater than $48,650 (high income). A total of 5,908 patients with potentially resectable disease were included. A total of 3,331 patients did not have a surgical resection despite having resectable disease. Subgroup analysis of income status revealed that patients with a low or middle income were less likely to have a resection when compared with those with high income (33.0 vs 39.9 vs 45.8%, P = 0.0001). Multivariate analysis revealed that low and middle SES and race were significant predictors of resection. Ongoing study of access to health care may help define the means to eliminate the disparities in the care of patients with pancreatic adenocarcinoma.

Determinants of Returns in Rural Tourism

The goal of this study, based on data collected through community surveys and visitors' surveys, is to determine and analyze factors impacting returns from rural tourism. Our first model shows that age of event, median family income, and hired labor have a significant impact on the revenues collected from tourism events. Furthermore, it shows brochures and flyers to be the most effective form of advertisement. The second multivariate regression model proves that traveling greater distances, staying overnight at a hotel, and plans for visiting surrounding areas contribute positively and significantly to higher individual expenditures by tourists.

Socioeconomic Differentials and Neonatal Mortality: Racial Comparison of California Singletons

The median family income of the zip code of maternal residence was used to estimate the presence and determine the extent of socioeconomic differentials in the neonatal mortality rates of a cohort of 401,399 white and of 66,577 black Californian singletons born from 1982 to 1983. The neonatal mortality rate in the white infants increased from 3.99 in mothers residing in zip codes with a median family income &gt;$25,000 to 12.1 for mothers residing in zip codes with a median family income &lt;$11,000. With decreasing socioeconomic status there was also a significant increase in the percentage of white infants weighing less than 2,500 g (percentage of low birth weight increased from 3.75 to 8.33) and weighing less than 1,500 g (percentage of very low birth weight increased from 0.56 to 1.46). When the source of the socioeconomic difference in white neonatal mortality was partitioned, 77.4% was due to deterioration in the birth weight distribution and 22.6% to deterioration in birth weight-specific mortality rates. For the black cohort, the neonatal mortality rate increased from 5.9 in the most, to 9.0 in the least affluent strata. Although decreasing residential median family income was associated with an increase in the percent low birth weight (8.19 v 12.86), the percentage of very low birth weight was not significantly different (1.59 v 2.10). When the source of the differential in black neonatal mortality was partitioned, only 29% was due to deterioration of the birth weight distribution, whereas 71% was secondary to less favorable birth weight-specific mortality rates. These findings support the usefulness of zip code median family income to estimate socioeconomic differentials in neonatal mortality and justify the importance of California's statewide program to decrease low birth weight.