Hispanic County Research Articles

Unveiling Spatial Associations between COVID-19 Severe Health Index, Racial/Ethnic Composition, and Community Factors in the United States.

There are limited efforts to incorporate different predisposing factors into prediction models that account for population racial/ethnic composition in exploring the burden of high COVID-19 Severe Health Risk Index (COVID-19 SHRI) scores. This index quantifies the risk of severe COVID-19 symptoms among a county's population depending on the presence of some chronic conditions. These conditions, as identified by the Centers for Disease Control and Prevention (CDC), include Chronic Obstructive Pulmonary Disease (COPD), heart disease, high blood pressure, diabetes, and obesity. Therefore, the objectives of this study were (1) to investigate potential population risk factors preceding the COVID-19 pandemic that are associated with the COVID-19 SHRI utilizing non-spatial regression models and (2) to evaluate the performance of spatial regression models in comparison to non-spatial regression models. The study used county-level data for 3107 United States counties, utilizing publicly available datasets. Analyses were carried out by constructing spatial and non-spatial regression models. Majority White and majority Hispanic counties showed lower COVID-19 SHRI scores when compared to majority Black counties. Counties with an older population, low income, high smoking, high reported insufficient sleep, and a high percentage of preventable hospitalizations had higher COVID-19 SHRI scores. Counties with better health access and internet coverage had lower COVID-19 SHRI scores. This study helped to identify the county-level characteristics of risk populations to help guide resource allocation efforts. Also, the study showed that the spatial regression models outperformed the non-spatial regression models. Racial/ethnic inequalities were associated with disparities in the burden of high COVID-19 SHRI scores. Therefore, addressing these factors is essential to decrease inequalities in health outcomes. This work provides the baseline typology to further explore many social, health, economic, and political factors that contribute to different health outcomes.

The Association of Per- and Polyfluoroalkyl Substances Serum Levels and Allostatic Load by Country of Birth and the Length of Time in the United States.

Objectives: The aim of this study was to examine the association of per- and polyfluoroalkyl (PFAS) concentrations and allostatic load (AL) by the county of birth and the length of time in the United States of America (U.S.), in a representative sample of U.S. adults. Methods: Data from the 2007–2014 National Health and Nutrition Examination Survey (NHANES) were used in this cross-sectional study on the U.S. adults aged 20 and older. The analysis was stratified by the length of time in the U.S. and by the county of birth. In all, the sample contained those who were US-born (n = 10,264), Mexico-born (n = 4018), other Spanish speaking country-born (n = 2989), and other not–Hispanic speaking country-born (n = 3911). Poisson models were used to assess the differences in AL and PFAS levels depending on country of birth and length of time in the U.S. Results: Estimates indicated that those born in Other non–Spanish speaking counties had the highest PFAS levels among the country of birth category in the database. Regarding length of time in the U.S., those born in Mexico had low PFAS levels when their length of time in the U.S. was short. The Mexico-born category presented the most at-risk high serum PFAS levels, with AL levels increasing by length of time in the U.S. (p-value < 0.001). Conclusion: This study found that PFAS concentrations increased by the length of time residing in the U.S. Those born in other non–Hispanic counties had the highest PFAS levels among all the categories. In general, AL and PFAS levels are mostly associated with the length of time in the U.S., with foreign-born individuals having increased levels of both the longer they stay.

Associations between private well water and community water supply arsenic concentrations in the conterminous United States

Geogenic arsenic contamination typically occurs in groundwater as opposed to surface water supplies. Groundwater is a major source for many community water systems (CWSs) in the United States (US). Although the US Environmental Protection Agency sets the maximum contaminant level (MCL enforceable since 2006: 10 μg/L) for arsenic in CWSs, private wells are not federally regulated. We evaluated county-level associations between modeled values of the probability of private well arsenic exceeding 10 μg/L and CWS arsenic concentrations for 2231 counties in the conterminous US, using time invariant private well arsenic estimates and CWS arsenic estimates for two time periods. Nationwide, county-level CWS arsenic concentrations increased by 8.4 μg/L per 100% increase in the probability of private well arsenic exceeding 10 μg/L for 2006–2008 (the initial compliance monitoring period after MCL implementation), and by 7.3 μg/L for 2009–2011 (the second monitoring period following MCL implementation) (1.1 μg/L mean decline over time). Regional differences in this temporal decline suggest that interventions to implement the MCL were more pronounced in regions served primarily by groundwater. The strong association between private well and CWS arsenic in Rural, American Indian, and Semi Urban, Hispanic counties suggests that future research and regulatory support are needed to reduce water arsenic exposures in these vulnerable subpopulations. This comparison of arsenic exposure values from major private and public drinking water sources nationwide is critical to future assessments of drinking water arsenic exposure and health outcomes.

Race, explicit racial attitudes, implicit racial attitudes, and COVID-19 cases and deaths: An analysis of counties in the United States.

ObjectivesTo examine the potential moderating effects of explicit racial attitudes and implicit racial attitudes on the relationship between percent of Black county residents and COVID-19 cases and deaths.MethodsWe collected data from a variety of publicly available sources for 817 counties in the US. (26% of all counties). Cumulative COVID-19 deaths and cases from January 22 to August 31, 2020 were the dependent variables; explicit racial attitudes and implicit racial attitudes served as the moderators; subjective poor or fair health, food insecurity, percent uninsured, percent unemployed, median family income, percent women, percent of Asian county resident, percent of Hispanic county residents, and percent of people 65 or older were controls.ResultsThe percent of Black county residents was positively associated with COVID-19 cases and deaths at the county level. The relationship between percent of Black residents and COVID-19 cases was moderated by explicit racial attitudes and implicit racial attitudes.ConclusionsImplicit racial attitudes can take on a shared property at the community level and effectively explain racial disparities. COVID-19 cases are highest when both the percent of Black county residents and implicit racial attitudes are high.

Abstract 17410: Geographic and Racial/ Ethnic Disparities in Heart Transplant Listing by County and Associated Risk Factors

Introduction: It is unknown if there are disparities in the transition from heart failure (HF) to listing for heart transplant (HT), although there are clear disparities in this transition in the transplant of other organs. Methods: We used CDC WONDER data and SRTR transplant data to identify county-level age-adjusted HF mortality and number of candidates listed for HT from 2006 to 2018 among racial/ ethnic subgroups. We determined rates of candidate listing and age-adjusted HF deaths (AAHFD) per 100,000 persons on aggregate and by racial/ ethnic subgroups. County-level demographic, socioeconomic, cardiovascular disease risk, and healthcare factors from public databases were used in multivariate models to determine factor groups explaining variation in candidates listed per AAHFD. Results: The median (IQR) candidates per AAHFD for the aggregated county cohort was 1.3 (0.75-2.0; 2558 counties reported data), the non-Hispanic white (NHW) county cohort was 1.5 (0.88-2.2; 2426 counties), the non-Hispanic black (NHB) county cohort was 1.1 (0.64-1.6; 860 counties), and the Hispanic county cohort was 1.1 (0.67-1.8; 254 counties) (p-value &lt;0.001). The lowest candidates per AAHFD were in the South for NHW (median 1.3) and NHB (0.97), but in the West for Hispanic (0.84). Multivariate models with all county-level variables, explained (R 2 ) 28.7%, 38.7%, and 57.3% of variation in candidates listed per AAHFD for NHW, NHB, and Hispanic cohorts, respectively. Socioeconomic factors (R 2 0.14), healthcare factors (R 2 0.21), and cardiovascular disease risk factors (R 2 0.18), respectively, explained the greatest variation in models using variable subgroups. Conclusions: When age-adjusted rates of HF mortality by race/ ethnicity group is considered, HT candidate listing for NHB and Hispanic candidates is 27% lower than for NHW. County-level factors that explain variation in HT listing vary by racial/ ethnicity group, and explain more variation in NHB and Hispanic cohorts.

Robert Adams and the ‘Persistent Beauty’ of Colorado Landscapes

Robert Adams established his reputation in the burgeoning Front Range suburbs of Colorado, yet, during that same period, 1965–1975, he was photographing traditional communities in the eastern Great Plains and the Hispanic counties in the southernmost part of the state. This less studied set of images complements the other, more familiar body of work. In the white churches and adobe structures he saw history, values and relationships that were being lost in suburban developments. In both settings he photographed life that persisted in ruin.

Types of rapidly growing counties of the U.S., 1970–1990

Recent economic growth and in-migration have led to an interesting patchwork of rapidly growing counties in the United States. This paper identifies 299 U.S. counties that were growing at least 70% from 1970 to 1990, a rate greater than one standard deviation above the mean of all counties. Using a k-means cluster algorithm, seven distinct types of rapidly growing counties, with meaningful spatial patterns, were found. Four of these clusters were primarily urban: smaller fast-growing cities in the south, large sunbelt cities, as well as both white and blue-collar suburban counties ringing many of the more dynamic metropolitan regional centers of the country. Also, there were two predominately rural clusters: retirement counties and several counties in the Intermontane West characterized by environmental amenities and isolated growth. Lastly, we observed a distinct cluster of several Hispanic counties in the southwest primarily along the U.S.–Mexico border. We believe these seven clusters present a remarkably clear portrait of the significant forces underlying the rapid growth of counties in the United States.

County characteristics and racial and ethnic disparities in the use of preventive services

Background. Studies examining predictors of preventive service utilization generally focus on individual characteristics and ignore the role of contextual variables. To help address this gap in the literature, the present study investigates whether county-level characteristics, such as racial and ethnic composition, are associated with the use of preventive services. Methods. Data from the Medical Expenditure Panel Survey and the Area Resource Files (1996–1998) are used to identify the individual- and county-level predictors of five types of preventive services ( n = 49,063). Results. County racial or ethnic composition is associated with the utilization of certain preventive services, net of individual-level characteristics. Specifically, individuals in high percent Hispanic counties are more likely to report cholesterol screenings, while those in counties with more blacks are more likely to have regular mammograms. Moreover, county racial or ethnic composition modifies the relationship between individual race or ethnicity and preventive use. In particular, Hispanic individuals who reside in high percent black counties report higher levels of utilization for most preventive services compared to Hispanics living in other counties. Conclusions. Physical and social environments are key determinants of health behaviors and outcomes. Future studies should take into account the racial or ethnic composition of an area and how this interacts with individual race or ethnicity when investigating predictors of preventive care use.

Race, Poverty, and American Tort Awards: Evidence from Three Data Sets

We investigate the impact of the race and income of the jury pool on trial awards. The average tort award increases as black and Hispanic county population rates increase and especially as black and Hispanic county poverty rates increase. An increase in the black county poverty rate of 1 percentage point tends to raise the average personal injury tort award by 3–10 percent. An increase in the Hispanic county poverty rate of 1 percentage point tends to raise awards by as much as 7 percent, although this effect is less well estimated. Forum shopping for high‐poverty minority counties could raise awards by hundreds of thousands of dollars. Average awards decrease with increases in white (nonblack, non‐Hispanic) poverty rates in two of our data sets, making these findings even more surprising. Awards increase with black and Hispanic county poverty rates even after controlling for a wide variety of other potential causes.