Disparities in colorectal cancer time-to-treatment and survival time associated with racial and economic residential segregation surrounding the diagnostic hospital, Georgia 2010-2015.

PURPOSE: To evaluate patient-level colorectal cancer outcomes in relation to residential income and racial segregation and composition of the neighborhood surrounding the diagnosing hospitals, and characterize presence of cancer-relevant diagnosis and treatment modalities that might contribute to these associations. METHODS: We utilized Georgia state cancer registry data (2010-2015), matching diagnosis information to hospital technology provided by the American Hospital Association and spatial information to the US Census. We modeled time-to-treatment and survival time, using Cox proportional hazards models, stratified by segregation. Segregation was examined as residential economic and racial evenness (Atkinson index) and isolation (isolation index) and mean income at the Census tract level. To assess possible contributing factors, analysis of hospital diagnosis and treatment technologies in relation to segregation was conducted. RESULTS: Average income of the Census tract and racial residential segregation of the diagnosing hospital's neighborhood was generally unassociated with time-to-treatment or survival time. Higher income evenness around the diagnosing hospital was associated with shorter time-to-treatment, with no association with time-to-death. Higher income isolation for the diagnosing hospital, conversely, was associated with longer times to treatment, but also longer survival times. Hospitals in regions with higher level of residential income segregation were less likely to have a particular diagnosing or treatment technologies, such as virtual colonoscopy and chemotherapy. CONCLUSION: Hospital resources may be a function of their immediate economic environment, and this may have influence on cancer outcomes. Future work should evaluate patient outcomes in light of technologies or therapies utilized within particular economic environments.

Differentiating Black and Hispanic: outcome differences of segregated communities and police shootings in the USA, 2015-2020.

BACKGROUND: Police shootings are unevenly spatially distributed, with substantive spikes throughout the USA. While minorities are disproportionately the victims of police force, social or structural factors associated with this distribution are not well understood. The objective of this work was to evaluate police shootings in relation to victim race or ethnicity and residential segregation and racial diversity. METHODS: Validated crowdsourced data from the Washington Post's Fatal Force (2015-2020) were linked with census tract-level data from the American Community Survey. Residential minority dissimilarity, interaction, and a racial and ethnic diversity metric were calculated in order to assess the potentially variant importance of evenness in distribution, exposure likelihood, and general representation. Logistic and multinomial regression was used to model associations between segregation and diversity, adjusted for other ecological characteristics. Analyses were stratified by victim race or ethnicity (Black, Asian, or Hispanic). RESULTS: Across all races combined, the odds of a police shooting in a particular census tract were associated with non-Hispanic Black dissimilarity (OR = 0.98, 95% CI 0.97, 0.99) and racial and ethnic diversity (1.046, 95% CI 1.044, 1.060). Areas with higher racial diversity had a higher likelihood of having a police shooting event with Black victims (OR = 1.092, 95% CI 1.064, 1.120) or Asian victims (OR = 1.188, 1.051, 1.343) than less diverse areas. Higher non-Hispanic Black interaction was associated with a lower likelihood of having a police shooting event with Black victims (OR = 0.914, 95% CI 0.833, 0.946) than lower interaction areas. Higher Hispanic dissimilarity was associated with a lower likelihood of having a police shooting event with a Hispanic victim (OR = 0.398, 95% CI 0.324, 0.489) than lower dissimilarity areas. CONCLUSIONS: The variant effects of residential segregation are only seen when victims are analyzed separately by race. There appears to be a protective effect for Hispanic populations in Hispanic communities, while the reverse is true of Black individuals. We urge law enforcement responsible for locations with segregated communities to monitor individual interactions that police have with residents as well as the patterns of frequency and context of those interactions.

All-cause mortality and residential racial and ethnic segregation and composition as experienced differently by individual-level race, ethnicity, and gender: Mortality disparities in american communities data.

PURPOSE: Use a large nationally representative population to evaluate whether differences in mortality in relation to residential racial and ethnic segregation and diversity varied by gender, and race or Hispanic ethnicity in the United States. METHODS: The Mortality Disparities in American Communities (MDAC) was used to evaluate mortality risk in relation to segregation. MDAC is a nationally representative record linkage of the 2008 American Community Survey data with mortality outcomes derived from the National Death Index through 2015. Gender-stratified mortality risk for White, Black, and Hispanic groups in relation to quartiles of residential segregation, composition, and diversity were modeled using parametric survival regression with an exponential distribution, adjusted for individual-level socioeconomic characteristics. RESULTS: The study population included >3,950,000 individuals and >273,000 all-cause mortality outcomes. Statistically significant differences in associations were observed with Black segregation vs. Hispanic segregation across Black or Hispanic groups; some differences in stratification by gender for Hispanic and Non-Hispanic Black groups, but gender-stratified associations were more similar in non-Hispanic Whites. CONCLUSIONS: Future multidisciplinary and ethnographic research is needed to identify the specific structural mechanisms by which these associations differ to support means by which to more effectively target public health interventions.

Longer time-to-treatment but better survival for colorectal cancer patients presumptively not diagnosed in a hospital.

PURPOSE: To evaluate time-to-treatment and survival time in colorectal cancer (CRC) patients who presumptively were not diagnosed in a hospital. METHODS: Colorectal tumor-level data from Georgia Cancer Registry (GCR) was merged with American Hospital Association data for 2010-2015 using hospital identification number. Patients with tumors lacking a diagnosis hospital in the GCR were classified as presumptive non-hospital diagnosis (PNHD). Cox proportional hazard models were used to model PNHD and time-to-treatment and time-to-death following cancer diagnosis, stratified by race and controlling for personal and tumor characteristics. RESULTS: PNHD (n = 6,885, 29.6%) was associated with a lower likelihood of treatment at a given point in time (i.e., longer time-to-treatment), but did not differ for Black (HR = 0.77, 95% CI: 0.73, 0.82) and White (HR = 0.73, 95% CI: 0.71, 0.76) patients. Time-to-death was longer (i.e., better survival) with PNHD, which also did not differ for Black (HR = 0.70, 95% CI: 0.64, 0.76) and White (HR = 0.71, 95% CI: 0.67, 0.75) patients. These results were not explained by confounding factors or differences in tumor stage at diagnosis. CONCLUSIONS: These observations warrant further research to understand whether there are potentially modifiable factors associated with the diagnosing location that can be used to benefit patient treatment trajectory and survival.

Descriptive Epidemiology of Homicides With Victim and Suspect Race or Hispanic Ethnicity Discordance in the United States: Analysis of National Violent Death Reporting System (NVDRS) 2005-2015.

Cross-racial violence is a high-profile issue in the United States; however, there is little empirical research on the epidemiology of cross-racial homicides. The objective of this work was to use national-level data to evaluate the characteristics of homicides in which the victim and suspect are of the same or different race or Hispanic ethnicity. Victims and suspects from National Violent Death Reporting System data (2005-2015) were classified into seven-categories on the basis of race/ethnicity (six non-Hispanic races or Hispanic ethnicity), and 51,454 homicide events were classified as concordant (same race or ethnicity), discordant (different race or ethnicity), or unknown (missing race or ethnicity or no suspect information). While discordancy was observed to be similar across all race and ethnicity groups, it was less likely with relatives, romantic partners, and relatives of romantic partners; less likely to occur at home; less likely to occur in intimate partner violence-related homicides; less likely when the homicide was preceded by an argument over money or property; less likely when the homicide was associated with a family problem; more likely among rival gangs and strangers than other known person relationships; and more likely with drug-involved homicides. There were differences for victims of non-Hispanic Black race. Notably, discordance was more likely for justifiable self-defense and more likely with victim having used a weapon. These results suggest that discordant homicides may follow patterns of peer groups and close relationships in society regardless of victim race/ethnicity, that is, individuals may form closer relationships with individuals of the same race/ethnicity.

Racial disparities in colorectal cancer time-to-treatment and survival time in relation to diagnosing hospital cancer-related diagnostic and treatment capabilities.

BACKGROUND: There is a need to understand structural issues, such as differential access to or utilization of technologies or capabilities, to better understand racial disparities in cancer outcomes. The objective of this work was to evaluate time-to-treatment and survival in relation to cancer-related diagnostic and treatment technologies of the diagnosing hospital. METHODS: Colorectal tumor-level data from George Cancer Registry was merged with hospital-level cancer technology data from the American Hospital Association (2010-2015). Cox proportional hazard models were used to model time-to-treatment and time-to-death following cancer diagnosis with cancer-related technologies for colon and rectosigmoid/rectal tumors, stratified by race and controlling for personal and tumor characteristics. RESULTS: Black individuals experienced lower likelihood of treatment (HR: 0.92, 95 % CI: 0.89, 0.96) for colon tumors, but not significantly different survival (HR: 1.03, 95 % CI: 0.98, 1.09). Larger capacity or size indicators (total surgical operations, emergency room visits, and licensed beds) were associated with higher likelihood of treatment in whites, but not blacks. Higher counts of treatment related technologies were associated with better survival in whites (HR = 0.92, 95 % CI: 0.85, 0.99), but not blacks (HR: 1.07, 95 % CI: 0.95, 1.19). Virtual colonoscopy emerged as a technology related to survival favorably in whites (HR: 0.84, 95 % CI: 0.77, 0.92) and blacks (HR: 0.89, 95 % CI: 0.79, 1.00). Overall results were similar for rectosigmoid/rectal tumors as observed for colon tumors. CONCLUSION: The role of cancer-related technologies presence or utilization for colorectal cancer outcomes and potential racial disparities warrants further research.

Spatial Associations Between Land Use and Infectious Disease: Zika Virus in Colombia.

Land use boundaries represent human-physical interfaces where risk of vector-borne disease transmission is elevated. Land development practices, coupled with rural and urban land fragmentation, increases the likelihood that immunologically naïve humans will encounter infectious vectors at land use interfaces. This research consolidated land use classes from the GLC-SHARE dataset; calculated landscape metrics in linear (edge) density, proportion abundance, and patch density; and derived the incidence rate ratios of the Zika virus occurrence in Colombia, South America during 2016. Negative binomial regression was used to evaluate vector-borne disease occurrence counts in relation to Population Density, Average Elevation, Per Capita Gross Domestic Product, and each of three landscape metrics. Each kilometer of border length per square kilometer of area increase in the linear density of the Cropland and Grassland classes is associated with an increase in Zika virus risk. These spatial associations inform a risk reduction approach to rural and urban morphology and land development that emphasizes simple and compact land use geometry that decreases habitat availability for mosquito vectors of Zika virus.

County-level socioeconomic factors and residential racial, Hispanic, poverty, and unemployment segregation associated with drug overdose deaths in the United States, 2013-2017.

PURPOSE: The purpose of the study was to evaluate overdose death rates in relation to socioeconomic characteristics and measures of socioeconomic residential segregation at substate geography. METHODS: County overdose deaths were linked to socioeconomic characteristics that are related to social vulnerability. Dissimilarity and isolation segregation (comparing individual counties to the adjacent counties and state) and diversity were calculated for race, Hispanic ethnicity, poverty, and unemployment. Negative binomial regression was used to compare county characteristics to death rates. RESULTS: Percent civilian disabled was positively associated with mortality across race and Hispanic ethnicity groups. Some discordant associations included racial and unemployment diversity (null for White, inverse for Hispanic and Black), percent unemployment (positive for White, inverse for Hispanic), percent crowded housing (positive for Black), uninsured (null for White, inverse for Black and Hispanic), and per capita income (positive for Black, inverse for Hispanic). Several residential segregation measures were also significantly associated with overdose death rates, and different magnitudes and directions of associations were observed by race and Hispanic ethnicity. CONCLUSIONS: These results provide future directions, including roles of civilian disability, diversity, and evaluating differential impacts of segregation across racial and ethnic groups. Individual-level data, drug overdose incidence, or larger studies to evaluate interactions may help to elucidate mechanisms.

Complexity of the Basic Reproduction Number (R0).

The basic reproduction number (R0), also called the basic reproduction ratio or rate or the basic reproductive rate, is an epidemiologic metric used to describe the contagiousness or transmissibility of infectious agents. R0 is affected by numerous biological, sociobehavioral, and environmental factors that govern pathogen transmission and, therefore, is usually estimated with various types of complex mathematical models, which make R0 easily misrepresented, misinterpreted, and misapplied. R0 is not a biological constant for a pathogen, a rate over time, or a measure of disease severity, and R0 cannot be modified through vaccination campaigns. R0 is rarely measured directly, and modeled R0 values are dependent on model structures and assumptions. Some R0 values reported in the scientific literature are likely obsolete. R0 must be estimated, reported, and applied with great caution because this basic metric is far from simple.

Examining the spatiotemporal evolution of vaccine refusal: nonmedical exemptions from vaccination in California, 2000-2013.

BACKGROUND: Vaccine hesitancy continues to be an issue throughout the United States, as numerous vaccine hesitant parents are choosing to exempt their children from school-entry vaccination requirements for nonmedical reasons, despite the safety and effectiveness of vaccines. We conduct an analysis of how vaccine refusal, measured by the use of nonmedical exemptions (based on personal or religious beliefs) from vaccination (NMEs), evolved across space and over time in California. METHODS: Using school-entry data from the California Department of Public Health, we examined NMEs for students entering kindergarten in California from 2000 to 2013. We conduct global and local spatial autocorrelation analysis to determine whether NME use became more geographically clustered over the study period and whether the location of local clusters of high use were temporally stable. We conducted a grouping analysis that identified the general temporal trends in NME use over the time period. RESULTS: The use of NMEs increased from 0.73% of all kindergarteners in 2000 to 3.09% in 2013 and became more geographically clustered over the study period. Local geographic clusters of high use were relatively isolated early in the study period, but expanded in size over time. The grouping analysis showed that regions with high NME use early in the study period were generally few (15% of all US Census tracts) and relatively isolated. Regions that had low initial NME use and moderate to large increases over the study period were located in close proximity to the initial high use regions. The grouping analysis also showed that roughly half of all tracts had 0% or very low NME use throughout the study period. CONCLUSIONS: We found an observable spatial structure to vaccine refusal and NME use over time, which appeared to be a self-reinforcing process, as well as a spatially diffusive process. Importantly, we found evidence that use of NMEs in the initially isolated regions appeared to stimulate vaccine refusal in geographically proximal regions. Thus, our results suggest that efforts aimed at decreasing future NME use may be most effective if they target regions where NME use is already high, as well as the nearby regions.

It could have been much worse: The Minnesota measles outbreak of 2017.

In 2017, Minnesota battled its largest measles outbreak in nearly 30 years, with 79 cases, most of them Somali-American children. In this study, we gathered vaccination and enrollment data for incoming kindergarteners in Minnesota over fall 2012-2016 from the Minnesota Department of Health. We also gathered the number of measles cases by county in 2017. We found that MMR coverage has substantial variation across districts and district types. The minimum MMR coverage is 58.3% and the maximum is 100%. Private schools, which represent approximately six percent of Minnesota's kindergarten enrollment, have a substantially lower coverage rate, with an overall coverage of 83.00%. The 2017 outbreak was relatively isolated. However, the MMR coverage data suggests that other communities could have been at risk given their geographic proximity to the outbreak and modest coverage rates.

Variation in Vaccination Data Available at School Entry Across the United States.

OBJECTIVES: To compile substate-level data on US school-age children's vaccination rates. METHODS: For states that did not have suitable data online, in 2015 we submitted information requests to the state health department and followed up with the state's Freedom of Information Act when necessary. RESULTS: The accessibility, scale, and types of vaccination data varied considerably. Whereas 26 states provided data online, 14 released data only after a Freedom of Information Act request. School or school-district data were available for 24 states, 19 at the county level, 2 at the health department level, and 6 provided no substate-level data. CONCLUSIONS: Effective vaccination policy requires a robust understanding of vaccination behavior. Some states make it difficult to access data or provide low-resolution data of limited value for identifying vaccination behavior.

A spatiotemporal analysis of non-medical exemptions from vaccination: California schools before and after SB277.

Childhood vaccination programs are considered one of the most beneficial public health programs in modern history. In the United States, the increasing use of non-medical exemptions (NMEs) from school entry vaccination requirements has garnered attention and scrutiny in the popular press, academic literature, and policy forums. In 2016, California law SB277 goes into effect, eliminating the NME option for students attending the state's public and private schools. Whereas SB277 is a strong move to increase vaccination coverage within California's schools, the new law contains an important caveat - students already having a valid NME (obtained prior to the 2016 school year) are "grandfathered" in until their next grade checkpoint (seventh grade). Although no new students will enter the California school system with a NME after 2016, the law's grandfather clause will allow NMEs to persist within the state school system until 2022. This analysis demonstrates how the past "build up" of students with pre-SB277 NMEs and the law's grandfather clause will act in combination to affect NME rates across the state after the implementation of SB277. We construct spatially explicit, yearly models of all students (K-12) enrolled in the California school system from 2011 to 2022. Our analysis finds that, although all regions of the state will eventually reach an NME rate of 0% by 2022, SB277's effect will be highly spatially and temporally variable. Some school districts will continue to experience elevated NME rates and increased risk of disease outbreak for years after SB277 is implemented. Our analysis highlights the potential spatially variant consequences of SB277's grandfather clause, providing important information for other states considering similar policy initiatives.

Sociodemographic Predictors of Vaccination Exemptions on the Basis of Personal Belief in California.

OBJECTIVES: We examined the variability in the percentage of students with personal belief exemptions (PBEs) from mandatory vaccinations in California schools and communities according to income, education, race, and school characteristics. METHODS: We used spatial lag models to analyze 2007-2013 PBE data from the California Department of Public Health. The analyses included school- and regional-level models, and separately examined the percentage of students with exemptions in 2013 and the change in percentages over time. RESULTS: The percentage of students with PBEs doubled from 2007 to 2013, from 1.54% to 3.06%. Across all models, higher median household income and higher percentage of White race in the population, but not educational attainment, significantly predicted higher percentages of students with PBEs in 2013. Higher income, White population, and private school type significantly predicted greater increases in exemptions from 2007 to 2013, whereas higher educational attainment was associated with smaller increases. CONCLUSIONS: Personal belief exemptions are more common in areas with a higher percentage of White race and higher income.

An approach for estimating vaccination coverage for communities using school-level data and population mobility information.

Childhood vaccination data are made available at a school level in some U.S. states. These data can be geocoded and may be considered as having a high spatial resolution. However, a school only represents the destination location for the set of students that actually reside and interact within some larger areal region, creating a spatial mismatch. Public school districts are often used to represent these regions, but fail to account for private schools and school of choice programs. We offer a new approach to estimate childhood vaccination coverage rates at a community level by integrating school level data with population commuting information. The resulting mobility-adjusted vaccine coverage estimates resolve the spatial mismatch problem and are more aligned with the geographic scale at which public health policies are implemented. We illustrate the utility of our approach using a case study on diphtheria, tetanus, and pertussis (DTP) vaccination coverage for kindergarten students in California. The modeled community-level DTP coverage estimates yield a statewide coverage of 92.37%, which is highly similar to the 92.44% coverage rate calculated from the original school-level data.

Diabetes, obesity, and recommended fruit and vegetable consumption in relation to food environment sub-types: a cross-sectional analysis of Behavioral Risk Factor Surveillance System, United States Census, and food establishment data.

BACKGROUND: Social and spatial factors are an important part of individual and community health. The objectives were to identify food establishment sub-types and evaluate prevalence of diabetes, obesity, and recommended fruit and vegetable consumption in relation to these sub-types in the Washington DC metropolitan area. METHODS: A cross-sectional study design was used. A measure of retail food environment was calculated as the ratio of number of sources of unhealthier food options (fast food, convenience stores, and pharmacies) to healthier food options (grocery stores and specialty food stores). Two categories were created: ≤ 1.0 (healthier options) and > 1.0 (unhealthier options). k-means clustering was used to identify clusters based on proportions of grocery stores, restaurants, specialty food, fast food, convenience stores, and pharmacies. Prevalence data for county-level diabetes, obesity, and consumption of five or more fruits or vegetables per day (FV5) was obtained from the Behavioral Risk Factor Surveillance System. Multiple imputation was used to predict block-group level health outcomes with US Census demographic and economic variables as the inputs. RESULTS: The healthier options category clustered into three sub-types: 1) specialty food, 2) grocery stores, and 3) restaurants. The unhealthier options category clustered into two sub-types: 1) convenience stores, and 2) restaurants and fast food. Within the healthier options category, diabetes prevalence in the sub-types with high restaurants (5.9 %, p = 0.002) and high specialty food (6.1 %, p = 0.002) was lower than the grocery stores sub-type (7.1 %). The high restaurants sub-type compared to the high grocery stores sub-type had significantly lower obesity prevalence (28.6 % vs. 31.2 %, p < 0.001) and higher FV5 prevalence (25.2 % vs. 23.1 %, p < 0.001). Within the larger unhealthier options category, there were no significant differences in diabetes, obesity, or higher FV5 prevalence across the two sub-types. However, restaurants (including fast food) sub-type was significantly associated with lower diabetes and obesity, and higher FV prevalence compared to grocery store sub-type. CONCLUSIONS: These results suggest that there are sub-types within larger categories of food environments that are differentially associated with adverse health outcomes. These observations support the specific food establishment composition of an area may be an important component of the food establishment-health relationship.

Distribution and determinants of young child feeding practices in the East African region: demographic health survey data analysis from 2008-2011.

We utilized the most recent Demographic Health Survey data to explore the distribution of feeding practices and examine relationships between complementary feeding and socio-demographic and health behaviour indicators in Kenya, Uganda and Tanzania. We based our analysis on complementary dietary diversity scores calculated for children 6-23 months old. Geographically, Kenya displayed clear division of children's diet diversity scores across its regions, unlike Uganda and Tanzania. Less than 40% of the children's meal frequencies in Uganda and Tanzania had met the minimum daily recommended levels. Only 30-40% of children in Kenya, Tanzania and Uganda had consumed diets with adequate diversity. Children's age, breastfeeding status, mother's education level and working status, household wealth index, prenatal care visits, receiving vitamin A supplements, using modern contraceptives and meal frequencies were significantly associated with adequate complementary food diversity in at least one of the three countries included in the current analyses. These analyses contribute to a better understanding and targeting of infant and young child feeding within the East African region.