County-Level Disparities in Heat-Related Emergencies.
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ABSTRACT:
SUBMITTER: Ramesh T
PROVIDER: S-EPMC10951733 | biostudies-literature | 2024 Mar
REPOSITORIES: biostudies-literature
Publications
County-Level Disparities in Heat-Related Emergencies.
Ramesh Tarun T Wozniak Gregory D GD Yu Hao H
JAMA network open 20240304 3
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Project description:ObjectiveTo determine which county-level social, economic, demographic, epidemiologic and access to care factors are associated with Latino/non-Latino White disparities in prevalence of diagnosed HIV infection.Methods and findingsWe used 2016 county-level prevalence rates of diagnosed HIV infection rates for Latinos and non-Latino Whites obtained from the National HIV Surveillance System and factors obtained from multiple publicly available datasets. We used mixed effects Poisson modeling of observed HIV prevalence at the county-level to identify county-level factors that explained homogeneous effects across race/ethnicity and differential effects for Latinos and NL-Whites. Overall, the median Latinos disparity in HIV prevalence is 2.4; 94% of the counties have higher rates for Latinos than non-Latinos, and one-quarter of the counties' disparities exceeded 10. Of the 41 county-level factors examined, 24 showed significant effect modification when examined individually. In multi-variable modeling, 11 county-level factors were found that significantly affected disparities. Factors that increased disparity with higher, compared to lower values included proportion of HIV diagnoses due to injection drug use, percent Latino living in poverty, percent not English proficient, and percent Puerto Rican. Latino disparities increased with decreasing percent severe housing, drug overdose mortality rate, percent rural, female prevalence rate, social association rate, percent change in Latino population, and Latino to NL-White proportion of the population. These factors while significant had minimal effects on diminishing disparity, but did substantially reduce the variance in disparity rates.ConclusionsLarge differences in HIV prevalence rates persist across almost all counties even after controlling for county-level factors. Counties that are more rural, have fewer Latinos, or have lower NL-White prevalence rates tend to have higher disparities. There is also higher disparity when community risk is low.
| S-EPMC7423131 | biostudies-literature
Project description:BackgroundPreliminary studies have suggested a link between socio-economic characteristics and COVID-19 mortality. Such studies have been carried out on particular geographies within the USA or selective data that do not represent the complete experience for 2020.MethodsWe estimated COVID-19 mortality rates, number of years of life lost to SARS-CoV-2 and reduction in life expectancy during each of the three pandemic waves in 2020 for 3144 US counties grouped into five socio-economic status categories, using daily death data from the Johns Hopkins University of Medicine and weekly mortality age structure from the Centers for Disease Control.ResultsDuring March-May 2020, COVID-19 mortality was highest in the most socio-economically advantaged quintile of counties and lowest in the two most-disadvantaged quintiles. The pattern reversed during June-August and widened by September-December, such that COVID-19 mortality rates were 2.58 times higher in the bottom than in the top quintile of counties. Differences in the number of years of life lost followed a similar pattern, ultimately resulting in 1.002 (1.000, 1.004) million years in the middle quintile to 1.381 (1.378, 1.384) million years of life lost in the first (most-disadvantaged) quintile during the whole year.ConclusionsDiverging trajectories of COVID-19 mortality among the poor and affluent counties indicated a progressively higher rate of loss of life among socio-economically disadvantaged communities. Accounting for socio-economic disparities when allocating resources to control the spread of the infection and to reinforce local public health infrastructure would reduce inequities in the mortality burden of the disease.
| S-EPMC8755340 | biostudies-literature
Project description:BackgroundLocal conditions where people live continue to influence prostate cancer outcomes. By examining local characteristics associated with trends in Black-White differences in prostate cancer-specific mortality over time, we aim to identify factors driving county-level prostate cancer-specific mortality disparities over a 15-year period.MethodsWe linked county-level data (Area Health Resource File) with clinicodemographic data of men with prostate cancer (Surveillance, Epidemiology, and End Results registry) from 2005 to 2020. Generalized linear mixed models evaluated associations between race and county-level age-standardized prostate cancer-specific mortality, adjusting for age; year of death; rurality; county-level education; income; uninsured rates; and densities of urologists, radiologists, primary care practitioners, and hospital beds.ResultsIn 1085 counties, 185 390 patients were identified of which 15.8% were non-Hispanic Black. Racial disparities in prostate cancer-specific mortality narrowed from 2005 to 2020 (25.4 per 100 000 to 19.2 per 100 000 overall, 57.9 per 100 000 to 38 per 100 000 for non-Hispanic Black patients, and 23.4 per 100 000 to 18.3 per 100 000 for non-Hispanic White patients). For non-Hispanic Black and non-Hispanic White patients, county prostate cancer-specific mortality changes varied greatly (-65% to +77% and -61% to +112%, respectively). From 2016 to 2020, non-Hispanic Black patients harbored greater prostate cancer-specific mortality risk (relative risk = 2.09, 95% confidence interval [CI] = 2.01 to 2.18); higher radiation oncologist density was associated with lower mortality risk (relative risk = 0.93, 95% CI = 0.89 to 0.98), while other practitioner densities were not.ConclusionAlthough overall rates improved, specific counties experienced worsening race-based disparities over time. Identifying locations of highest (and lowest) mortality disparities remains critical to development of location-specific solutions to racial disparities in prostate cancer outcomes.
| S-EPMC11631307 | biostudies-literature
Project description:BackgroundAdapting to extreme heat is becoming more critical as our climate changes. Previous research reveals that very few communities in the United States have programs to sufficiently prevent health problems during hot weather.ObjectiveOur goal was to examine county-level local heat preparedness and response in 30 U.S. states following the unusually hot summer of 2011.MethodsUsing a multimodal survey approach, we invited local health and emergency response departments from 586 counties to participate in the largest survey to date of heat preparedness and response in the United States. County-level responses were pooled into national and regional-level summaries. Logistic regressions modeled associations between heat planning/response and county characteristics, including population, poverty rates, typical summer weather, and 2011 summer weather.ResultsOf 586 counties, 190 (32%) responded to the survey. Only 40% of these counties had existing heat plans. The most common heat responses were communication about heat, outreach, and collaborations with other organizations. Both heat preparedness and heat response were, on average, more extensive in counties with higher populations, lower poverty rates, and lower percentages of older people. Heat response was generally more extensive in counties with heat plans.ConclusionsMost responding counties were underprepared for extreme heat in 2011 and lacked a formal response plan. Because counties with heat plans were more likely to act to prevent adverse heat impacts to residents, local health departments should consider adopting such plans, especially because increased extreme heat is anticipated with further climate change.
| S-EPMC4048256 | biostudies-literature
Project description:As a southwestern province of China, Sichuan is confronted with geographical disparities in access to healthcare professionals because of its complex terrain, uneven population distribution and huge economic gaps between regions. With 10-year data, this study aims to explore the county-level spatial disparities in access to different types of healthcare professionals (licensed doctors, registered nurses, pharmacists, technologists and interns) in Sichuan using temporal and spatial analysis methods. The time-series results showed that the quantity of all types of healthcare professionals increased, especially the registered nurses, while huge spatial disparities exist in the distribution of healthcare professionals in Sichuan. The local Moran's I calculations showed that high-high clusters (significantly high healthcare professional quantity in a group of counties) were detected in Chengdu (capital of Sichuan) and relatively rich areas, while low-low clusters (significantly low healthcare professional quantity in a group of counties) were usually found near the mountain areas, namely, Tsinling Mountains and Hengduan Mountains. The findings may deserve considerations in making region-oriented policies in educating and attracting more healthcare professionals to the disadvantaged areas.
| S-EPMC8394835 | biostudies-literature
Project description:Educational disparities in health are well documented, yet the education-health relationship is inconsistent across racial/ethnic and nativity groups. These inconsistencies may arise from characteristics of the early life environments in which individuals attain their education. We evaluate this possibility by investigating (1) whether educational disparities in cardiometabolic risk vary by race/ethnicity and nativity among Black, Hispanic, and White young adults; (2) the extent to which racial/ethnic-nativity differences in the education-health relationship are contingent on economic, policy, and social characteristics of counties of early life residence; and (3) the county characteristics associated with the best health at higher levels of education for each racial/ethnic-nativity group. Using data from the National Longitudinal Study of Adolescent to Adult Health, we find that Black young adults who achieve high levels of education exhibit worse health across a majority of contexts relative to their White and Hispanic counterparts. Additionally, we observe more favorable health at higher levels of education across almost all contexts for White individuals. For all other racial/ethnic-nativity groups, the relationship between education and health depends on the characteristics of the early life counties of residence. Findings highlight place-based factors that may contribute to the development of racial/ethnic and nativity differences in the education-health relationship among U.S. young adults.
| S-EPMC9190239 | biostudies-literature
Project description:BackgroundDisparities in cardiovascular disease mortality among breast cancer survivors are documented, but geographic factors by county-level socioeconomic status (SES) and rurality are not well described.MethodsWe analyzed 724 518 women diagnosed with localized or regional stage breast cancer between 2000 and 2017 within Surveillance, Epidemiology, and End Results Program-18 with follow-up until 2018. We calculated relative risks (RRs) of cardiovascular disease mortality using Poisson regression, accounting for age- and race-specific rates in the general population, according to county-level quintiles of SES (measured by Yost index), median income, and rurality at breast cancer diagnosis. We also calculated 10-year cumulative mortality risk of cardiovascular disease accounting for competing risks.ResultsCardiovascular disease mortality was 41% higher among breast cancer survivors living in the lowest SES (RR = 1.41, 95% confidence interval [CI] = 1.36 to 1.46, Ptrend < .001) and poorest (RR = 1.41, 95% CI = 1.36 to 1.47, Ptrend < .001) counties compared with the highest SES and wealthiest counties, and 24% higher for most rural relative to most urban counties (RR = 1.24, 95% CI = 1.17 to 1.30, Ptrend < .001). Disparities for the lowest SES relative to highest SES counties were greatest among younger women aged 18-49 years (RR = 2.32, 95% CI = 1.90 to 2.83) and aged 50-59 years (RR = 2.01, 95% CI = 1.77 to 2.28) and within the first 5 years of breast cancer diagnosis (RR = 1.53, 95% CI = 1.44 to 1.64). In absolute terms, however, disparities were widest for women aged 60+ years, with approximately 2% higher 10-year cumulative cardiovascular disease mortality risk in the poorest compared with wealthiest counties.ConclusionsGeographic factors at breast cancer diagnosis were associated with increased cardiovascular disease mortality risk. Studies with individual- and county-level information are needed to inform public health interventions and reduce disparities among breast cancer survivors.
| S-EPMC9901273 | biostudies-literature
Project description:There are substantial gaps in educational outcomes between black and white students in the United States. Recently, increased attention has focused on differences in the rates at which black and white students are disciplined, finding that black students are more likely to be seen as problematic and more likely to be punished than white students are for the same offense. Although these disparities suggest that racial biases are a contributor, no previous research has shown associations with psychological measurements of bias and disciplinary outcomes. We show that county-level estimates of racial bias, as measured using data from approximately 1.6 million visitors to the Project Implicit website, are associated with racial disciplinary disparities across approximately 96,000 schools in the United States, covering around 32 million white and black students. These associations do not extend to sexuality biases, showing the specificity of the effect. These findings suggest that acknowledging that racial biases and racial disparities in education go hand-in-hand may be an important step in resolving both of these social ills.
| S-EPMC6486724 | biostudies-literature
Project description:Background: The objectives of the present study are to understand the longitudinal variability in COVID-19 reported cases at the county level and to associate the observed rates of infection with the adoption and lifting of stay-home orders.Materials and Methods: The study uses the trajectory of the pandemic in a county and controls for social and economic risk factors, physical environment, and health behaviors to elucidate the social determinants contributing to the observed rates of infection.Results and conclusion: Results indicated that counties with higher percentages of young individuals, racial and ethnic minorities and, higher population densities experienced greater difficulty suppressing transmission.Except for Education and the Gini Index, all factors were influential on the rate of COVID-19 spread before and after stay-home orders. However, after lifting the orders, six of the factors were not influential on the rate of spread; these included: African-Americans, Population Density, Single Parent Households, Average Daily PM2.5, HIV Prevalence Rate, and Home Ownership. It was concluded that different factors from the ones controlling the initial spread of COVID-19 are at play after stay-home orders are lifted.KEY MESSAGESObserved rates of COVID-19 infection at the County level in the U.S. are not directly associated with adoption and lifting of stay-home orders.Disadvantages in sociodemographic determinants negatively influence the rate of COVID-19 spread.Counties with more young individuals, racial and ethnic minorities, and higher population densities have greater difficulty suppressing transmission.
| S-EPMC9090380 | biostudies-literature
Project description:IntroductionThe purpose of this study is to examine nationwide disparities in drug, alcohol, and suicide mortality; evaluate the association between county-level characteristics and these mortality rates; and illustrate spatial patterns of mortality risk to identify areas with elevated risk.MethodsThe authors applied a Bayesian spatial regression technique to investigate the association between U.S. county-level characteristics and drug, alcohol, and suicide mortality rates for 2004-2016, accounting for spatial correlation that occurs among counties.ResultsMortality risks from drug, alcohol, and suicide were positively associated with the degree of rurality, the proportion of vacant housing units, the population with a disability, the unemployed population, the population with low access to grocery stores, and the population with no health insurance. Conversely, risks were negatively associated with Hispanic population, non-Hispanic Black population, and population with a bachelor's degree or higher.ConclusionsSpatial disparities in drug, alcohol, and suicide mortality exist at the county level across the U.S. social determinants of health; educational attainment, degree of rurality, ethnicity, disability, unemployment, and health insurance status are important factors associated with these mortality rates. A comprehensive strategy that includes downstream interventions providing equitable access to healthcare services and upstream efforts in addressing socioeconomic conditions is warranted to effectively reduce these mortality burdens.
| S-EPMC10997338 | biostudies-literature