County Level Research Articles

Roles of Hospital Type and Community Setting in Rate of Screening for Metabolic Disorders Among Psychiatric Patients.

Globally, rates of metabolic disorders continue to climb, leading to significant disease morbidity and mortality. Individuals with mental illness are particularly prone to obesity, and some medications, such as antipsychotics, may increase the risk for metabolic disorders. The American Psychiatric Association and the American Diabetes Association recommend that patients taking antipsychotic medications receive regular screening for metabolic disorders. This study examined hospital and community factors associated with screening these patients for such disorders. The authors combined Centers for Medicare and Medicaid Services (CMS) hospital-level data on screening for metabolic disorders among patients with an antipsychotic prescription with community data, including urbanization classification, social vulnerability, and metabolic disease presence and risk factors. Data were merged at the county level and evaluated with a nonparametric multivariate regression model. The CMS data set included 1,497 U.S. hospitals with data on screening for metabolic disorders among patients with an antipsychotic prescription. Screening rates varied by type of facility; acute care and critical access hospitals outperformed freestanding psychiatric facilities (p<0.001). No other variables examined in the multivariate model were associated with screening for metabolic disorders. Despite common resource limitations, screening for metabolic disorders may be driven more by logistics and less by time, finances, or a community's primary care network. Identifying the specific logistical challenges of freestanding psychiatric facilities could aid in the development of targeted interventions to improve the rates of screening for and treatment of not only metabolic disorders but also other common comorbid conditions.

Inequality characteristics and influencing factors of CO2 emissions per capita in Jiangsu Province, China.

Analyzing the inequality characteristics and influencing factors of CO2 emissions per capita (CEPC) is conducive to balancing regional development and CO2 emissions reduction. This study applied the Gini coefficient and Theil index to investigate the CEPC inequalities during 2005-2017 at the county level in Jiangsu Province, China. Considering the spatial spillover and interaction effects, the factors influencing CEPC were analyzed by a hierarchical spatial autoregressive model. The results showed that the inequalities in CEPC first increased and then decreased at the inter-regional, and inter-county levels. The spatial pattern of CEPC was stable, and there was a significantly positive spatial autocorrelation of CEPC at the county level. The High-High type counties were mainly located in Sunan (southern Jiangsu). The spatial interaction effects of the CEPC between the prefecture and county levels indicated that governments at the prefecture level should integrate their county governments to reduce the CEPC. Moreover, carbon intensity, GDP per capita, land urbanization, and industrial structure play an important role in reducing CEPC. Our findings provide a scientific basis for formulating reasonable and effective carbon emission reduction policies.

The Social Determinants of Health and Athletic Trainer Availability in Indiana Secondary Schools.

The social determinants of health (SDOH) are circumstances under which individuals are born, work, and live that influence health outcomes. Previous researchers have examined 1 determinant of economic stability and found disparities in socioeconomic status and athletic trainer (AT) availability. To examine the SDOH characteristics of Indiana secondary schools and AT availability. Cross-sectional study. Database secondary analysis. A total of 426 secondary schools. All data were collected from publicly available databases. The independent variable was AT availability, and schools were classified as having a full-time AT, a part-time AT only, or no AT. The SDOH variables were gathered for each school (at the school and county levels). Data were summarized using measures of central tendencies, 1-way analysis of variance, and Kruskal-Wallis tests. School enrollment was larger in schools with greater AT availability (P< .001). The proportion of non-White students was greater in schools with more AT availability (P= .002). Greater AT availability was present in counties with higher graduation rates (P= .03). Post hoc comparisons revealed differences in graduation rates between schools with a part-time AT and those with no AT (P= .04). Schools with less AT availability were located in counties with a slightly higher percentage of the population uninsured (P= .02). Schools with greater AT availability were located in counties with a higher ratio of population to primary care physicians (P= .03). Schools with less AT availability were located in counties with a higher population experiencing severe housing problems (P= .02). No differences were found in AT availability based on the 3 social and community context variables (P> .05). Differences were noted in AT availability and SDOH characteristics at the secondary school level. We observed less AT availability where high school graduation rates and the population of primary care providers were lower. Strategies should be implemented to improve access to athletic health care in underresourced communities.

Geographic disparity in the distribution of cancer clinical trials in the United States and the associated factors.

Little is known regarding the geographic disparity in the distribution of phase 1-3 clinical trials of new cancer treatments in the US and the associated factors. To examine county-level variation in the number of phase 1-3 cancer clinical trials and the associations between county characteristics and having phase 1-3 cancer clinical trials. We identified phase 1-3 cancer clinical trials started in the US between January 2008 and December 2022 from the Aggregate Analysis of ClinicalTrials.gov database. We analyzed the distribution of phase 1-3 cancer clinical trials at the county level. Using a mixed-effects regression with states as random intercepts, we estimated the associations between a county's median age, median household income, percentage of population from racial and ethnic minority groups, proportion of population aged 25 years or older with an educational attainment of bachelor's degree or higher, rurality, cancer incidence rate, and number of medical oncologists per population with having any phase 1-3 cancer clinical trial in a county. After excluding trials that were suspended, terminated, and withdrawn, a total of 14,977 phase 1-3 cancer clinical trials started in the United States between January 2008 and December 2022 were included in the primary analysis. Only 1,333 out of 3,143 counties (42.4%) had 1 or more trial during this period. Counties that were rural, with lower median household income, a less educated population, fewer medical oncologists per population, and lower cancer incidence rates demonstrated a significantly lower likelihood of having phase 1-3 cancer clinical trials. Our study revealed substantial geographic disparities in the distribution of phase 1-3 cancer clinical trials. Limited trial availability in low-income, low-education, low-oncologist, and rural areas can be a significant barrier to patient participation, potentially hindering adoption and worsening outcomes in disadvantaged populations.

253 What is still needed?: Community conversations about health research

OBJECTIVES/GOALS: While strategies for community engagement in health research and clinical trials are well documented, participation from underserved populations remains low. Our research team conducted a series of Community Engagement Studios for community members to discuss what is still needed for them to engage in health research. METHODS/STUDY POPULATION: In the spring of 2023, our research team conducted four community engagement studios using the Vanderbilt Community Engagement (CE) Studio model. Community members were recruited through health councils- which are a community-led collaborative, focused on health at the county level throughout the state. In the CE Studio model community members or stakeholders are referred to as experts. In total, 31 experts from 12 different health councils from around the state participated in the CE Studios via Zoom. The CE Studios centered around two main questions 1.) What do communities want to know before agreeing to participate in research? And 2.) When a study is presented as an opportunity for your community, what things need to be addressed to see if it is a good fit? RESULTS/ANTICIPATED RESULTS: Themed summaries for each CE Studio and one overall themed summary were developed by a designated notetaker on the research team. Of novelty were cultural considerations for each region that included recommendations such as “Foster kinship between those doing the research and the community” speaking to the shared community bond that unites people and the need for researchers to also spend time creating meaningful community bonds throughout the research process. The CE Studio overall summary revealed two main themes for researchers: 1.) Things that help with research participation, and 2.) Things that get in the way of research participation. Overall themes echoed documented best practices for community engagement efforts. DISCUSSION/SIGNIFICANCE: Each CE studio revealed cultural considerations that included recommendations to researchers. Overall themes echoed documented best practices for community engagement efforts implying that while strategies for researchers to engage with communities are well known, more needs to be done to continue to implement these practices.

Dynamics of urban expansion and form changes impacting carbon emissions in the Guangdong-Hong Kong-Macao Greater Bay Area counties

Cities are the main carriers of social and economic development, and they are also important sources of carbon emissions. Therefore, it is essential to explore the impact of urban expansion and form changes on carbon emissions. Here, we attempted to analyzes the relationship between urban expansion and carbon emissions at the county level in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 1997 to 2017. It further decomposes the driving effects of carbon emissions from multiple factors, and considers the spatial heterogeneity between different urban form changes and driving effects. The results show that: The relationship between urban expansion and carbon emissions in the GBA has gone through three stages from 1997 to 2017, with 2012 as a turning point. Optimization of economic development models and strict protection of the ecological environment can effectively control carbon emissions. After 2012, the economic development effect (GE) and population scale effect (PE) are the driving factors of carbon emissions, while the carbon emission intensity effect (CE) and urban land intensity effect (UE) are the inhibitory factors of carbon emissions. The contribution rate of UE to carbon emission reduction can reach 86 %. The impact of urban form changes on carbon emissions has spatial heterogeneity. The changes in urban form have a significant impact on the carbon emissions of counties in Dongguan and Shenzhen. The increase in fragmentation indirectly promotes carbon emissions. In 2007–2012, the increase in centrality significantly weakened the economic development effect, which is conducive to emission reduction. After 2007, the increase in compactness in counties in the eastern part of the GBA, including Zhongshan and Zhuhai, is not conducive to emission reduction.

THE ADMINISTRATIVE-LEGAL POSITION OF THE COMMISSION FOR SECURITY AND ORDER

Public safety and order are special goods, being of interest to both national and local government administrations. In local government, a special role is played by the intermediate level of public affairs management; that is, the county (poviat). Tasks in the field of security and order at the county level are carried out mainly by the commission for security and order, which, under current legislation, appears as a multi-member specialized auxiliary body of the head of the county. The purpose of this article is to present the administrative-legal position of the commission for security and order, and to explore its competencies and tasks, as defined in both constitutional law and substantive laws. It also discusses the personnel structure of the commission, the procedure and rules for appointing its members, and the principles of financing its work.

Large-scale modeling of hurricane flooding and disrupted infrastructure impacts on accessibility to critical facilities

Post-hurricane accessibility to critical facilities is crucial for accelerating the recovery process, which can often be disrupted by hurricane-induced flooding. The State of Florida is especially vulnerable to flooding accompanied by hurricanes, which leads to significant roadway closures and accessibility challenges that require special attention. As such, this research aims to analyze changes in accessibility to critical facilities due to Hurricane Irma-induced flooding. Accordingly, this research aims to compare the average accessibility changes to critical facilities for vulnerable populations, including older people, disabled people, and older people with a disability with the general population. To accomplish these goals, flood mapping was done by analyzing Sentinel-1 images before and after Hurricane Irma (2017) using Google Earth Engine. The accessibility change from block groups to critical facilities was analyzed using a cumulative opportunities approach in GIS, considering flooded areas as the barriers, which were later aggregated to the county level. Finally, employing the population-weighted average accessibility method, a comparison of accessibility change of vulnerable and general populations was conducted. The result shows that 1193.80 square km of areas in 43 counties of Florida, mostly in the southern portions, were affected by flooding after Hurricane Irma. Later, the accessibility changes to critical facilities considering 15-min and 30-min travel time thresholds are presented and visualized. The county-wise change in accessibility of vulnerable and general populations was also computed. The knowledge acquired from this research can improve the development of efficient and equitable post-disaster recovery plans.

County-Level Cardiac Rehabilitation and Broadband Availability: Opportunities for Hybrid Care in the United States.

Cardiac rehabilitation (CR) improves patient outcomes and quality of life and can be provided virtually through hybrid CR. However, little is known about CR availability in conjunction with broadband access, a requirement for hybrid CR. This study examined the intersection of CR and broadband availability at the county level, nationwide. Data were gathered and analyzed in 2022 from the 2019 American Community Survey, the Centers for Medicare & Medicaid Services, and the Federal Communications Commission. Spatially adaptive floating catchments were used to calculate county-level percent CR availability among Medicare fee-for-service beneficiaries. Counties were categorized: by CR availability, whether lowest (ie, CR deserts), medium, or highest; and by broadband availability, whether CR deserts with majority-available broadband, or dual deserts. Results were stratified by state. County-level characteristics were examined for statistical significance by CR availability category. Almost half of US adults (n = 116 325 976, 47.2%) lived in CR desert counties (1691 counties). Among adults in CR desert counties, 96.8% were in CR deserts with majority-available broadband (112 626 906). By state, the percentage of the adult population living in CR desert counties ranged from 3.2% (New Hampshire) to 100% (Hawaii and Washington, DC). Statistically significant differences in county CR availability existed by race/ethnicity, education, and income. Almost half of US adults live in CR deserts. Given that up to 97% of adults living in CR deserts may have broadband access, implementation of hybrid CR programs that include a telehealth component could expand CR availability to as many as 113 million US adults.

Evaluating the representativeness of mobile big data: A comparative analysis between China's mobile big data and census data at the county level

Mobile big data has emerged as an essential tool for various scientific research fields. However, the credibility of mobile big data and the extent to which it can represent the real-world population remain unclear. This study evaluated the representativeness of mobile big data by comparing it to the most recent census data at the county level in China. Using power-law and multiple linear regression models, we aim to determine the accuracy and reliability of mobile big data in reflecting the population dynamics and characteristics of different geographical areas. Our results indicate that disparities among individuals with different socioeconomic statuses, demographic characteristics, or geographic locations may contribute to biased estimations of the actual population density. Higher illiteracy rates and median ages may be associated with underestimating population density. In contrast, higher GDP per capita, elevated urbanization levels, and larger percentages of the 15–64 year age group may be associated with overestimating population density. Our research highlights the importance of cross-validating population estimates and offering practical statistical methods for addressing potential biases and estimating population dynamics in future applications of mobile big data.

Spatial–Temporal Evolution, Impact Mechanisms, and Reclamation Potential of Rural Human Settlements in China

In China’s pursuit of modernization, the government has introduced the rural revitalization strategy to combat rural decline, foster balanced urban–rural development, and reduce the urban–rural gap. Rural human settlements, as key components of this strategy, play a vital role. This paper examines the types and characteristics of human–earth relationships within rural settlements, emphasizing their significance. Using national land use and population census data, we analyze the spatiotemporal evolution of rural settlements at the county level, investigating landscape pattern changes, assessing the degree of coupling coordination between rural population and settlements, categorizing relationship types and features, and estimating the potential for remediation. Our findings reveal a growing trend in the scale of rural human settlements, particularly sourced from arable land, with significant expansions observed in the North China Plain and Northeast Plain, indicating potential for farmland reclamation and village consolidation. Landscape patterns of rural human settlements exhibit increased fragmentation, complex shapes, and aggregation. We categorize the utilization of rural human settlements into two types, each with four distinct features: human–land coordination is observed in regions characterized by either a higher rural population and larger rural settlement areas, or lower rural population and smaller rural settlement areas. Human–land trade-offs are evident in areas where there is either a higher rural population and smaller rural settlement areas, or lower rural population and larger rural settlement areas. This provides valuable insights for the Chinese government’s context-specific implementation of the rural revitalization strategy. It also serves as an experiential reference for the governance of rural human settlements in other developing countries.

Monitoring and influencing factors of grassland livestock overload in Xinjiang from 1982 to 2020.

It is crucial to estimate the theoretical carrying capacity of grasslands in Xinjiang to attain a harmonious balance between grassland and livestock, thereby fostering sustainable development in the livestock industry. However, there has been a lack of quantitative assessments that consider long-term, multi-scale grass-livestock balance and its impacts in the region. This study utilized remote sensing and empirical models to assess the theoretical livestock carrying capacity of grasslands. The multi-scale spatiotemporal variations of the theoretical carrying capacity in Xinjiang from 1982 to 2020 were analyzed using the Sen and Mann-Kendall tests, as well as the Hurst index. The study also examined the county-level grass-livestock balance and inter-annual trends. Additionally, the study employed the geographic detector method to explore the influencing factors. The results showed that: (1) The overall theoretical livestock carrying capacity showed an upward trend from 1982 to 2020; The spatial distribution gradually decreased from north to south and from east to west. In seasonal scale from large to small is: growing season > summer > spring > autumn > winter; at the monthly scale, the strongest livestock carrying capacity is in July. The different grassland types from largest to smallest are: meadow > alpine subalpine meadow > plain steppe > desert steppe > alpine subalpine steppe. In the future, the theoretical livestock carrying capacity of grassland will decrease. (2) From 1988 to 2020, the average grass-livestock balance index in Xinjiang was 2.61%, showing an overall increase. At the county level, the number of overloaded counties showed an overall increasing trend, rising from 46 in 1988 to 58 in 2020. (3) Both single and interaction factors of geographic detectors showed that annual precipitation, altitude and soil organic matter were the main drivers of spatiotemporal dynamics of grassland load in Xinjiang. The results of this study can provide scientific guidance and decision-making basis for achieving coordinated and sustainable development of grassland resources and animal husbandry in the region.

Analysis of Evolving Carbon Stock Trends and Influencing Factors in Chongqing under Future Scenarios

The relationship between land use changes and regional carbon storage is closely linked. Identifying evolving trends concerning and influencing factors on carbon storage under future scenarios is key in order to achieve the “dual carbon” goals. Using Chongqing as a case study, this study integrated the advantages of the PLUS model, InVEST model, and a geographic detector model. It conducted simulations of land use type data under scenarios of natural development (ND) and ecological protection (EP), and identified evolving trends and influencing factors regarding carbon storage. The results were as follows: (1) the PLUS model demonstrated excellent simulation performance, with a Kappa coefficient above 0.85 and an overall accuracy above 0.90. During the study period, significant changes occurred for cultivated land, forested land, water bodies, and construction, which were closely related to carbon storage; (2) carbon storage in Chongqing showed a decreasing trend, with a decrease of 10.07 × 106 t C from 2000 to 2020. Under the ND scenario, carbon storage was projected to decrease by 10.54 × 106 t C in 2030 compared to 2020, and it was expected to stabilize from 2030 to 2050. At the county level, Youyang, Fengjie, and Wuxi had the highest carbon storage, while Nanchuan, Jiangbei, and Dadukou had the lowest; (3) the spatial distribution of carbon storage presented an “eastern hotspot western cold spot aggregation” pattern. The proportions of regions with a decreased, unchanged, and increased aggregation of carbon storage in Chongqing during 2000–2010 and 2010–2020 were 2.99%, 95.95%, 1.06%; and 4.39%, 92.40%, 3.21%, respectively. The trend indicated a decrease in the aggregation of carbon storage, and future carbon storage was expected to stabilize; (4) elevation, terrain fluctuation, NDVI, annual average temperature, annual average precipitation, and nighttime light index had influence values of 0.88, 0.81, 0.61, 0.86, 0.77, and 0.81 on carbon storage, respectively, with different combinations of influencing factors having a greater impact. In the future, ecological priority and green development concepts should be followed, and comprehensive improvement of regional development conditions should be pursued to enhance carbon storage, thereby promoting the achievement of the “dual carbon” goals. This study provided an analytical path and data support for formulating optimized carbon storage policies at the regional level.

Cancer incidence trends in New York State and associations with common population-level exposures 2010–2018: an ecological study

The impact of common environmental exposures in combinations with socioeconomic and lifestyle factors on cancer development, particularly for young adults, remains understudied. Here, we leveraged environmental and cancer incidence data collected in New York State at the county level to examine the association between 31 exposures and 10 common cancers (i.e., lung and bronchus, thyroid, colorectal, kidney and renal pelvis, melanoma, non-Hodgkin lymphoma, and leukemia for both sexes; corpus uteri and female breast cancer; prostate cancer), for three age groups (25–49, 50–69, and 70–84 year-olds). For each cancer, we stratified by age group and sex, and applied regression models to examine the associations with multiple exposures simultaneously. The models included 642,013 incident cancer cases during 2010–2018 and found risk factors consistent with previous reports (e.g., smoking and physical inactivity). Models also found positive associations between ambient air pollutants (ozone and PM2.5) and prostate cancer, female breast cancer, and melanoma of the skin across multiple population strata. Additionally, the models were able to better explain the variation in cancer incidence data among 25–49 year-olds than the two older age groups. These findings support the impact of common environmental exposures on cancer development, particularly for younger age groups.

Analysis on the Cooperation Mechanism between CDC and Medical Community at County Level in China: From the Perspective of Evolutionary Game Theory

Objective: Using evolutionary game theory to explore the conditions for in-depth cooperation between county-level Center for Disease Control and Prevention (CDC) and Medical Community, and to raise policy recommendations. Methods: The basic assumptions of the evolutionary game model were set through the information collected from focus group interview and individual interview, then the basic model was established by constructing the payment matrix and the replicator dynamic equation. The condition of in-depth cooperation was deduced by stable equilibrium analysis. Results: To improve cooperation effectiveness, the following conditions should be met: total income of CDC and Medical Community after the cooperation increased, additional benefit to CDC from the cooperation increased, effort level of the cooperation increased, psychological cost of CDC and Medical Community from the cooperation decreased. Thus the Medical Community and CDC were more inclined to cooperate and setup cooperation network. Conclusion: To setup in-depth cooperation, it is suggested: 1) government administrative intervention to push forward the cooperation as the initial and external impetus; 2) unified or dual leadership to drive the prevention-and-treatment network as internal support; 3) in-depth resources sharing to foster organizational and structural interdependence as the basis of cooperation; 4) objective interdependence to push self-improvement of cooperation as continuous self-driven force.

Modeling county level COVID-19 transmission in the greater St. Louis area: Challenges of uncertainty and identifiability when fitting mechanistic models to time-varying processes

We use a compartmental model with a time-varying transmission parameter to describe county level COVID-19 transmission in the greater St. Louis area of Missouri and investigate the challenges in fitting such a model to time-varying processes. We fit this model to synthetic and real confirmed case and hospital discharge data from May to December 2020 and calculate uncertainties in the resulting parameter estimates. We also explore non-identifiability within the estimated parameter set. We find that the death rate of infectious non-hospitalized individuals, the testing parameter and the initial number of exposed individuals are not identifiable based on an investigation of correlation coefficients between pairs of parameter estimates. We also explore how this non-identifiability ties back into uncertainties in the estimated parameters and find that it inflates uncertainty in the estimates of our time-varying transmission parameter. However, we do find that R0 is not highly affected by non-identifiability of its constituent components and the uncertainties associated with the quantity are smaller than those of the estimated parameters. Parameter values estimated from data will always be associated with some uncertainty and our work highlights the importance of conducting these analyses when fitting such models to real data. Exploring identifiability and uncertainty is crucial in revealing how much we can trust the parameter estimates.

The Role of County-Level Persistent Poverty in Stroke Mortality in the USA.

Stroke is a major health concern in the USA, disproportionately affecting socioeconomically disadvantaged groups. This study investigates the link between persistent poverty and stroke mortality rates in residents aged 65 and above, positing that sustained economic challenges at the county level correlate with an increase in stroke-related deaths. Persistent poverty refers to a long-term state where a significant portion of a population lives below the poverty threshold for an extended period, typically measured over several decades. It captures the chronic nature of economic hardship faced by a community across multiple generations. Utilizing data from the CDC Wonder database and the American Community Survey, we conducted a comprehensive analysis across US counties, differentiating them by persistent poverty status. Our results indicate a statistically significant link between persistent poverty and increased mortality from ischemic and hemorrhagic strokes; counties afflicted by long-standing poverty were associated with an additional 33.49 ischemic and 8.16 hemorrhagic stroke deaths per 100,000 residents annually compared to their wealthier counterparts. These disparities persisted when controlling for known stroke risk factors and other socioeconomic variables. These results highlight the need for targeted public health strategies and interventions to address the disparities in stroke mortality rates and the broader implications for healthcare equity. The study underscores the vital role of socioeconomic context in health outcomes and the urgency of addressing long-term poverty as a key determinant of public health.

Abstract 4812: Evaluating racial and ethnic differences in advanced-stage laryngeal cancer treatment and outcomes in Florida: Unmasking the inequities

Abstract Purpose: To evaluate the association between race/ethnicity, treatment, and mortality among individuals with advanced-stage laryngeal cancer in Florida. Methods: We obtained data from the Florida Cancer Data System (FCDS) on non-Hispanic (NH)-White (the reference group), Hispanic, and NH-Black patients with advanced-stage (regional and distant) laryngeal cancer from 2009 to 2020. Sociodemographic factors were obtained from FCDS (age, marital status, and insurance) and the United States Census at the county level (education, household income, and rurality). Treatment strategies included chemoradiation, surgery followed by chemoradiation, chemotherapy, radiation, surgery, and surgery followed by chemotherapy. The primary outcome was overall mortality. Multivariable Cox proportional hazard models were used to calculate hazard ratios (HR) and 95% confidence intervals (95% CI) and to examine the association of race/ethnicity with treatment and survival, while adjusting for sociodemographic factors. Results: There were 4,522 participants with advanced-stage laryngeal cancer (57.9% &amp;lt;65 years, 79.5% male, 75.4% NH-White, 13.1% Hispanic, and 11.5% NH-Black) included in the analysis. Compared to NH-White patients, NH-Black patients were less likely to be married, have private insurance, and live in an urban county. Moreover, NH-Black individuals were less likely to receive chemoradiation alone and were more likely to receive surgery followed by chemoradiation. Government insurance was highly associated with chemoradiation receipt. In age-adjusted models, NH-Black patients with advanced-stage laryngeal cancer had a higher risk of death compared to NH-White patients (HR: 1.19; 95% CI: 1.06, 1.32), while Hispanic patients had a lower risk of death compared to NH-White patients (HR: 0.80; 95% CI: 0.71, 0.89). After adjusting for sociodemographic factors, there was no statistically significant difference in overall mortality in NH-Black patients compared to NH-White patients (HR: 1.07; 95% CI: 0.96, 1.20). However, among individuals who received chemoradiation, NH-Black patients had a higher risk of mortality, even after adjusting for sociodemographic factors, compared to NH-White patients (HR: 1.27; 95% CI: 1.04, 1.55). Conclusions: Among patients with advanced-stage laryngeal cancer in Florida, NH-Black patients experienced a higher risk of overall mortality compared to other racial and ethnic groups, but this discrepancy was primarily among those who received chemoradiation, even after accounting for sociodemographic factors. This study emphasizes the urgency of expanding laryngeal cancer care access for NH-Black individuals and investigating possible biological variations in their response to chemoradiation and subsequent survival outcomes. Citation Format: Caretia J. Washington, Chayil Lattimore, Dejana Braithwaite, Kristianna Fredenburg, Shama Karanth. Evaluating racial and ethnic differences in advanced-stage laryngeal cancer treatment and outcomes in Florida: Unmasking the inequities [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4812.

Abstract 4833: Impact of poverty in surrounding neighborhoods in cancer mortality in the US: A nationwide study among US women

Abstract Background: Poverty at the individual and county levels is known to lead to worse cancer outcomes. We believe the relationship between poverty and cancer may involve individual-level factors including tumor biology, socioeconomic status, and community measures that alter cancer outcomes such as death. We aim to understand to what extent poverty in the surrounding neighborhood may identify counties at the highest risk of cancer mortality and whether it is modifiable. Methods: This study used data collected by SEER to examine the association between neighborhood effects of poverty on the top three sites of cancer mortality among women. We included women &amp;gt;= 20 years of age diagnosed with breast, lung, and colorectal cancer between 2005-2009 and 2010-2014 who survived more than one year after diagnosis. We determined county-level neighborhood poverty environments using local spatial autocorrelation (LISA) analysis with Local Moran’s I of five-year county-level poverty estimates from the American Community Survey. US counties with poverty estimates above or below the national median were defined as high (H)- or low (L)- poverty counties, respectively. We defined neighborhood poverty environments as H-counties among H-counties (HH), L-counties among L-counties (LL), H-counties among LL-counties (HL), and L-counties among HH-counties (LH). We used a Poisson regression model adjusting for age at diagnosis, race/ethnicity, cancer stage, year of diagnosis, treatment, and cancer type to assess county-level neighborhood poverty environment effects on cancer mortality. We also used stratified analyses to explore the effect of cancer type, stage, and race/ethnicity strata on the association between neighborhood poverty environments and cancer death. Results: Our analysis includes 36,481 women with 4,740 cancer deaths. In total 7,182 women were in HH counties; 21,112 women were in LL counties; 6,476 women were in HL counties; and 1,711 women were in LH counties. Women in HH, LH, and HL counties had a respective 1.23 [95%CI:1.14,1.32], 1.20 [95%CI:1.05,1.36], and 0.95 [95%CI: 0.88,1.03] relative risk (RR) of cancer death when compared to deaths in LL counties. In our stratified analyses, women with breast cancer in HH and HL counties had higher cancer deaths (RR = 1.21 [95%CI:1.03,1.42] and 1.37 [95%CI:1.13,1.65], respectively) when compared to women with lung cancer. We also observed higher cancer deaths from counties that were LL in 2005-2009 and changed to HH counties in 2010-2014 (RR = 1.60 [95%CI:0.85,2.68]) when compared to unchanged LL counties. Conclusion: We used LISA spatial clustering to demonstrate the effects HH and LH environments have on cancer mortality. We also demonstrate the impact that changes in neighborhood environments can have on cancer mortality. Our findings suggest that prioritization of resource allocations to HH neighborhoods could improve the burden of women with cancer. Citation Format: Ifeoma Nwigwe, Michael Desjardins, Kala Visvanathan. Impact of poverty in surrounding neighborhoods in cancer mortality in the US: A nationwide study among US women [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4833.

Unmasking outdoor preferences: an analysis of the effects of COVID-19 mandates on recreation behaviour in Idaho

ABSTRACT A number of studies have examined park visitation patterns and consumer preferences using available national and state park visitation data. However, municipal park visitation remains largely understudied due to the difficulty and costliness associated with data collection and analysis. This study utilizes high frequency mobile device location data to measure changes in visitation to municipal and state parks and other outdoor recreation points of interest (POIs) after COVID-19 mask mandates were instituted. We exploit spatial and temporal variation in COVID-19 mandates at the county level in the U.S. state of Idaho. We find an increase in POI visitation in areas without mask mandates. Visitation rates were approximately seven percent lower in areas with a mask mandate compared to non-mandate counties. Our research brings insight on the behavioural response to restrictions and on recreational choice behaviour.