Accessibility to ERCP-performing hospitals among patients with pancreatic cancer living in SEER regions.

BACKGROUND AND AIMS: The two most common interventions used to treat painless jaundice from pancreatic cancer are endoscopic retrograde cholangiopancreatography (ERCP) and percutaneous transhepatic biliary drainage (PTBD). Our study aimed to characterize the geographic distribution of ERCP-performing hospitals among patients with pancreatic cancer in the United States and the association between geographic accessibility to ERCP-performing hospitals and biliary interventions patients receive. METHODS: This is a retrospective cohort study using the Surveillance, Epidemiology, and End Results (SEER)-Medicare database for pancreatic cancer from 2005 to 2013. Multilevel models were used to examine the association between accessibility to ERCP hospitals within a 30- and 45-min drive from the patient's residential ZIP Code and the receipt of ERCP treatment. A two-step floating catchment area model was used to calculate the measure of accessibility based on the distribution across SEER regions. RESULTS: 7464 and 782 patients underwent ERCP and PTBD, respectively, over the study period. There were 808 hospitals in which 8246 patients diagnosed with pancreatic cancer in SEER regions from 2005 to 2013 received a procedure. Patients with high accessibility within both 30- and 45-min drive to an ERCP-performing hospital were more likely to receive an ERCP (30-min adjusted odds ratio [aOR]: 1.53, 95% confidence interval [CI]: 1.17-2.01; 45-min aOR: 1.31, 95% CI: 1.01-1.70). Furthermore, in the adjusted model, Black patients (vs. White) and patients with stage IV disease were less likely to receive ERCP than PTBD. CONCLUSIONS: Patients with pancreatic cancer and high accessibility to an ERCP-performing hospital were more likely to receive ERCP. Disparities in the receipt of ERCP persisted for Black patients regardless of their access to ERCP-performing hospitals.

Data gaps and opportunities for modeling cancer health equity.

Population models of cancer reflect the overall US population by drawing on numerous existing data resources for parameter inputs and calibration targets. Models require data inputs that are appropriately representative, collected in a harmonized manner, have minimal missing or inaccurate values, and reflect adequate sample sizes. Data resource priorities for population modeling to support cancer health equity include increasing the availability of data that 1) arise from uninsured and underinsured individuals and those traditionally not included in health-care delivery studies, 2) reflect relevant exposures for groups historically and intentionally excluded across the full cancer control continuum, 3) disaggregate categories (race, ethnicity, socioeconomic status, gender, sexual orientation, etc.) and their intersections that conceal important variation in health outcomes, 4) identify specific populations of interest in clinical databases whose health outcomes have been understudied, 5) enhance health records through expanded data elements and linkage with other data types (eg, patient surveys, provider and/or facility level information, neighborhood data), 6) decrease missing and misclassified data from historically underrecognized populations, and 7) capture potential measures or effects of systemic racism and corresponding intervenable targets for change.

Effective inclusion practices for neurodiverse children and adolescents in informal STEM learning: a systematic review protocol.

BACKGROUND: Informal learning experiences in science, technology, engineering, and math (STEM) can enhance STEM learning that occurs in formal educational settings and curricula as well as generate enthusiasm for considering STEM careers. The aim of this systematic review is to focus on the experiences of neurodiverse students in informal STEM learning. Neurodiversity is a subgroup of neurodevelopmental conditions, such as autism, attention deficit disorder, dyslexia, dyspraxia, and other neurological conditions. The neurodiversity movement regards these conditions as natural forms of human variation, as opposed to dysfunction, and recognizes that neurodiverse individuals possess many strengths relevant to STEM fields. METHODS: The authors will systematically search electronic databases for relevant research and evaluation articles addressing informal STEM learning for K-12 children and youth with neurodiverse conditions. Seven databases and content-relevant websites (e.g., informalscience.org) will be searched using a predetermined search strategy and retrieved articles will be screened by two members of the research team. Data synthesis will include meta-synthesis techniques, depending on the designs of the studies. DISCUSSION: The synthesis of the findings resulting from various research and evaluation designs, across the K-12 age span, and across various informal STEM learning contexts, will lead to depth and breadth of understanding of ways to improve informal STEM learning programs for neurodiverse children and youth. The identification of informal STEM learning program components and contexts shown to yield positive results will provide specific recommendations for improving inclusiveness, accessibility, and STEM learning for neurodiverse children and youth. TRIAL REGISTRATION: The current study has been registered in PROSPERO. REGISTRATION NUMBER: CRD42021278618.

Asian American Enclaves and Healthcare Accessibility: An Ecologic Study Across Five States.

INTRODUCTION: Access to primary care has been a long-standing priority for improving population health. Asian Americans, who often settle in ethnic enclaves, have been found to underutilize health care. Understanding geographic primary care accessibility within Asian American enclaves can help to ensure the long-term health of this fast-growing population. METHODS: U.S. Census data from five states (California, Florida, New Jersey, New York, and Texas) were used to develop and describe census-tract level measures of Asian American enclaves and social and built environment characteristics for years 2000 and 2010. The 2-step floating catchment area method was applied to National Provider Identifier data to develop a tract-level measure of geographic primary care accessibility. Analyses were conducted in 2022-2023, and associations between enclaves (versus nonenclaves) and geographic primary care accessibility were evaluated using multivariable Poisson regression with robust variance estimation, adjusting for potential area-level confounders. RESULTS: Of 24,482 census tracts, 26.1% were classified as Asian American enclaves. Asian American enclaves were more likely to be metropolitan and have less poverty, lower crime, and lower proportions of uninsured individuals than nonenclaves. Asian American enclaves had higher primary care accessibility than nonenclaves (adjusted prevalence ratio=1.23, 95% CI=1.17, 1.29). CONCLUSIONS: Asian American enclaves in five of the most diverse and populous states in the U.S. had fewer markers of disadvantage and greater geographic primary care accessibility. This study contributes to the growing body of research elucidating the constellation of social and built environment features within Asian American enclaves and provides evidence of health-promoting characteristics of these neighborhoods.

Correction: The Association of a Geographically Wide Social Media Network on Depression: County-Level Ecological Analysis.

[This corrects the article DOI: 10.2196/43623.].

The Association of a Geographically Wide Social Media Network on Depression: County-Level Ecological Analysis.

BACKGROUND: Social connectedness decreases human mortality, improves cancer survival, cardiovascular health, and body mass, results in better-controlled glucose levels, and strengthens mental health. However, few public health studies have leveraged large social media data sets to classify user network structure and geographic reach rather than the sole use of social media platforms. OBJECTIVE: The objective of this study was to determine the association between population-level digital social connectedness and reach and depression in the population across geographies of the United States. METHODS: Our study used an ecological assessment of aggregated, cross-sectional population measures of social connectedness, and self-reported depression across all counties in the United States. This study included all 3142 counties in the contiguous United States. We used measures obtained between 2018 and 2020 for adult residents in the study area. The study's main exposure of interest is the Social Connectedness Index (SCI), a pair-wise composite index describing the "strength of connectedness between 2 geographic areas as represented by Facebook friendship ties." This measure describes the density and geographical reach of average county residents' social network using Facebook friendships and can differentiate between local and long-distance Facebook connections. The study's outcome of interest is self-reported depressive disorder as published by the Centers for Disease Control and Prevention. RESULTS: On average, 21% (21/100) of all adult residents in the United States reported a depressive disorder. Depression frequency was the lowest for counties in the Northeast (18.6%) and was highest for southern counties (22.4%). Social networks in northeastern counties involved moderately local connections (SCI 5-10 the 20th percentile for n=70, 36% of counties), whereas social networks in Midwest, southern, and western counties contained mostly local connections (SCI 1-2 the 20th percentile for n=598, 56.7%, n=401, 28.2%, and n=159, 38.4%, respectively). As the quantity and distance that social connections span (ie, SCI) increased, the prevalence of depressive disorders decreased by 0.3% (SE 0.1%) per rank. CONCLUSIONS: Social connectedness and depression showed, after adjusting for confounding factors such as income, education, cohabitation, natural resources, employment categories, accessibility, and urbanicity, that a greater social connectedness score is associated with a decreased prevalence of depression.

The Texas Health Resources Clinical Scholars Program: Learning healthcare system workforce development through embedded translational research.

Introduction: Texas Health Resources (THR), a large, nonprofit health care system based in the Dallas-Fort Worth area, has collaborated with the University of Texas Southwestern Medical Center (UTSW) to develop and operate a unique, integrated approach for Learning Health System (LHS) workforce development. This training model centers on academic health system faculty members conducting later-stage translational research within a partnering regional care delivery organization. Methods: The THR Clinical Scholars Program engages early career UTSW faculty members to conduct studies that are likely to have an impact on care delivery at the health system level. Interested candidates submit formal applications to the program. A joint committee comprised of senior research faculty from UTSW and THR clinical leadership reviews proposals with a focus on the shared LHS needs of both institutions-developing high quality research output that can be applied to enhance care delivery. A key prioritization criterion for funding is the degree to which the research addresses a question relevant to THR as a high-volume network with multiple channels for consumers to access care. The program emphasis is on supporting embedded research initiatives using health system data to generate knowledge that will improve the quality and efficiency of care for the patient populations served by the participant organizations. Results: We discuss specific strategic and tactical components of the THR Clinical Scholars Program including an overview of the academic affiliation agreement between the collaborating organizations, criteria for successful program applications, data sharing, and funding. We also share project summaries from selected clinical scholars as examples of the LHS research done in the program to date. Conclusion: This experience report provides an implementation framework for other academic health systems interested in adopting similar LHS workforce training models with community partners.

Colorectal Cancer Incidence, Inequalities, and Prevention Priorities in Urban Texas: Surveillance Study With the "surveil" Software Package.

BACKGROUND: Monitoring disease incidence rates over time with population surveillance data is fundamental to public health research and practice. Bayesian disease monitoring methods provide advantages over conventional methods including greater flexibility in model specification and the ability to conduct formal inference on model-derived quantities of interest. However, software platforms for Bayesian inference are often inaccessible to nonspecialists. OBJECTIVE: To increase the accessibility of Bayesian methods among health surveillance researchers, we introduce a Bayesian methodology and open source software package, surveil, for time-series modeling of disease incidence and mortality. Given case count and population-at-risk data, the software enables health researchers to draw inferences about underlying risk and derivative quantities including age-standardized rates, annual and cumulative percent change, and measures of inequality. METHODS: We specify a Poisson likelihood for case counts and model trends in log-risk using the first-difference (random-walk) prior. Models in the surveil R package were built using the Stan modeling language. We demonstrate the methodology and software by analyzing age-standardized colorectal cancer (CRC) incidence rates by race and ethnicity for non-Latino Black (Black), non-Latino White (White), and Hispanic/Latino (of any race) adults aged 50-79 years in Texas's 4 largest metropolitan statistical areas between 1999 and 2018. RESULTS: Our analysis revealed a cumulative decline of 31% (95% CI -37% to -25%) in CRC risk among Black adults, 17% (95% CI -23% to -11%) for Latino adults, and 35% (95% CI -38% to -31%) for White adults from 1999 to 2018. None of the 3 observed groups experienced significant incidence reduction in the final 4 years of the study (2015-2018). The Black-White rate difference (per 100,000) was 44 (95% CI 30-57) in 1999 and 35 (95% CI 28-43) in 2018. Cumulatively, the Black-White gap accounts for 3983 CRC cases (95% CI 3746-4219) or 31% (95% CI 29%-32%) of total CRC incidence among Black adults in this period. CONCLUSIONS: Stalled progress on CRC prevention and excess CRC risk among Black residents warrant special attention as cancer prevention and control priorities in urban Texas. Our methodology and software can help the public and health agencies monitor health inequalities and evaluate progress toward disease prevention goals. Advantages of the methodology over current common practice include the following: (1) the absence of piecewise linearity constraints on the model space, and (2) formal inference can be undertaken on any model-derived quantities of interest using Bayesian methods.

The Politicization of Ivermectin Tweets During the COVID-19 Pandemic.

Background: We explore the ivermectin discourse and sentiment in the United States with a special focus on political leaning through the social media blogging site Twitter. Methods: We used sentiment analysis and topic modeling to geospatially explore ivermectin Twitter discourse in the United States and compared it to the political leaning of a state based on the 2020 presidential election. Results: All modeled topics were associated with a negative sentiment. Tweets originating from democratic leaning states were more likely to be negative. Conclusions: Real-time analysis of social media content can identify public health concerns and guide timely public health interventions tackling disinformation.

Ethnic Disparities in Early-Onset Gastric Cancer: A Population-Based Study in Texas and California.

BACKGROUND: Incidence rates of gastric cancer are increasing in young adults (age <50 years), particularly among Hispanic persons. We estimated incidence rates of early-onset gastric cancer (EOGC) among Hispanic and non-Hispanic White persons by census tract poverty level and county-level metro/nonmetro residence. METHODS: We used population-based data from the California and Texas Cancer Registries from 1995 to 2016 to estimate age-adjusted incidence rates of EOGC among Hispanic and non-Hispanic White persons by year, sex, tumor stage, census tract poverty level, metro versus nonmetro county, and state. We used logistic regression models to identify factors associated with distant stage diagnosis. RESULTS: Of 3,047 persons diagnosed with EOGC, 73.2% were Hispanic White. Incidence rates were 1.29 [95% confidence interval (CI), 1.24-1.35] and 0.31 (95% CI, 0.29-0.33) per 100,000 Hispanic White and non-Hispanic White persons, respectively, with consistently higher incidence rates among Hispanic persons at all levels of poverty. There were no statistically significant associations between ethnicity and distant stage diagnosis in adjusted analysis. CONCLUSIONS: There are ethnic disparities in EOGC incidence rates that persist across poverty levels. IMPACT: EOGC incidence rates vary by ethnicity and poverty; these factors should be considered when assessing disease risk and targeting prevention efforts.

Associations of Obesity and Neighborhood Factors With Urinary Stone Parameters.

INTRODUCTION: Obesity is associated with kidney stone disease, but it is unknown whether this association differs by SES. This study assessed the extent to which obesity and neighborhood characteristics jointly contribute to urinary risk factors for kidney stone disease. METHODS: This was a retrospective analysis of adult patients with kidney stone disease evaluated with 24-hour urine collection (2001-2020). Neighborhood-level socioeconomic data were obtained for a principal component analysis, which identified 3 linearly independent factors. Associations between these factors and 24-hour urine measurements were assessed using linear regression as well as groupings of 24-hour urine results using multivariable logistic regression. Finally, multiplicative interactions were assessed testing effect modification by obesity, and analyses stratified by obesity were performed. Analyses were performed in 2021. RESULTS: In total, 1,264 patients met the study criteria. Factors retained on principal component analysis represented SES, family structure, and housing characteristics. On linear regression, there was a significant inverse correlation between SES and 24-hour urine sodium (p=0.0002). On multivariable logistic regression, obesity was associated with increased odds of multiple stone risk factors (OR=1.61; 95% CI=1.15, 2.26) and multiple dietary factors (OR=1.33; 95% CI=1.06, 1.67). No significant and consistent multiplicative interactions were observed between obesity and quartiles of neighborhood SES, family structure, or housing characteristics. CONCLUSIONS: Obesity was associated with the presence of multiple stone risk factors and multiple dietary factors; however, the strength and magnitude of these associations did not vary significantly by neighborhood SES, family structure, and housing characteristics.

District-Level Universal Masking Policies and COVID-19 Incidence During the First 8 Weeks of School in Texas.

Texas discontinued state-sponsored business restrictions and mask mandates on March 10, 2021, and mandated that no government officials, including public school officials, may implement mask requirements even in areas where COVID-19 hospitalizations comprised more than 15% of hospitalizations. Nonetheless, some public school districts began the 2021-2022 school year with mask mandates in place. We used quasi-experimental methods to analyze the impact of school mask mandates, which appear to have resulted in approximately 40 fewer student cases per week in the first eight weeks of school. (Am J Public Health. 2022;112(6):871-875. https://doi.org/10.2105/AJPH.2022.306769).

Residence in a Latinx enclave and end-induction minimal residual disease positivity among children with acute lymphoblastic leukemia.

Racial and ethnic inequities in survival persist for children with acute lymphoblastic leukemia (ALL). In the US, there are strong associations between SES, race/ethnicity, and place of residence. This is evidenced by ethnic enclaves: neighborhoods with high concentrations of ethnic residents, immigrants, and language isolation. The Latinx enclave index (LEI) can be used to investigate how residence in a Latinx enclave is associated with health outcomes. We studied the association between LEI score and minimal residual disease (MRD) in 142 pediatric ALL patients treated at Texas Children's Hospital. LEI score was associated with end-induction MRD positivity (OR per unit increase 1.63, CI 1.12-2.46). There was also a significant trend toward increased odds of MRD positivity among children living in areas with the highest enclave index scores. MRD positivity at end of induction is associated with higher incidence of relapse and lower overall survival among children with ALL; future studies are needed to elucidate the exact causes of these findings and to improve ALL outcomes among children residing within Latinx enclaves.Supplemental data for this article is available online at https://doi.org/10.1080/08880018.2022.2047850.

Residence in a Hispanic Enclave Is Associated with Inferior Overall Survival among Children with Acute Lymphoblastic Leukemia.

Hispanic children with acute lymphoblastic leukemia (ALL) experience poorer overall survival (OS) than non-Hispanic White children; however, few studies have investigated the social determinants of this disparity. In Texas, many Hispanic individuals reside in ethnic enclaves-areas with high concentrations of immigrants, ethnic-specific businesses, and language isolation, which are often socioeconomically deprived. We determined whether enclave residence was associated with ALL survival, overall and among Hispanic children. We computed Hispanic enclave index scores for Texas census tracts, and classified children (N = 4083) as residing in enclaves if their residential tracts scored in the highest statewide quintile. We used Cox regression to evaluate the association between enclave residence and OS. Five-year OS was 78.6% for children in enclaves, and 77.8% for Hispanic children in enclaves, both significantly lower (p < 0.05) than the 85.8% observed among children not in enclaves. Children in enclaves had increased risk of death (hazard ratio (HR) 1.20, 95% confidence interval (CI) 1.01-1.49) after adjustment for sex, age at diagnosis, year of diagnosis, metropolitan residence and neighborhood socioeconomic deprivation and after further adjustment for child race/ethnicity (HR 1.19, 95% CI 0.97-1.45). We observed increased risk of death when analyses were restricted to Hispanic children specifically (HR 1.30, 95% CI 1.03-1.65). Observations suggest that children with ALL residing in Hispanic enclaves experience inferior OS.

Disparities in Kidney Stone Disease: A Scoping Review.

PURPOSE: We reviewed the available evidence regarding health disparities in kidney stone disease to identify knowledge gaps in this area. MATERIALS AND METHODS: A literature search was conducted using PubMed®, Embase® and Scopus® limited to articles published in English from 1971 to 2020. Articles were selected based on their relevance to disparities in kidney stone disease among adults in the United States. RESULTS: Several large epidemiological studies suggest disproportionate increases in incidence and prevalence of kidney stone disease among women as well as Black and Hispanic individuals in the United States, whereas other studies of comparable size do not report racial and ethnic demographics. Numerous articles describe disparities in imaging utilization, metabolic workup completion, analgesia, surgical intervention, stone burden at presentation, surgical complications, followup, and quality of life based on race, ethnicity, socioeconomic status and place of residence. Differences in urinary parameters based on race, ethnicity and socioeconomic status may be explained by both dietary and physiological factors. All articles assessed had substantial risk of selection bias and confounding. CONCLUSIONS: Health disparities are present in many aspects of kidney stone disease. Further research should focus not only on characterization of these disparities but also on interventions to reduce or eliminate them.

Do mobile units contribute to spatial accessibility to mammography for uninsured women?

Limited spatial accessibility to mammography, and socioeconomic barriers (e.g., being uninsured), may contribute to rural disparities in breast cancer screening. Although mobile mammography may contribute to population-level access, few studies have investigated this relationship. We measured mammography access for uninsured women using the variable two-step floating catchment area (V2SFCA) method, which estimates access at the local level using estimated potential supply and demand. Specifically, we measured supply with mammography machine certifications in 2014 from FDA and brick-and-mortar and mobile facility data from the community-based Breast Screening and Patient Navigation (BSPAN) program. We measured potential demand using Census tract-level estimates of female residents aged 45-74 from 5-year 2012-2016 American Community Survey data. Using the sign test, we compared mammography access estimates based on 3 facility groupings: FDA-certified, program brick-and-mortar only, and brick-and-mortar plus mobile. Using all mammography facilities, accessibility was high in urban Dallas-Ft. Worth, low for the ring of adjacent counties, and high for rural counties outlying this ring. Brick-and-mortar-based estimates were lower for the outlying ring, and mobile-unit contribution to access was observed more in urban tracts. Weak mobile-unit contribution across the study area may indicate suboptimal dispatch of mobile units to locations. Geospatial methods could identify the optimal locations for mobile units, given existing brick-and-mortar facilities, to increase access for underserved areas.

Nativity, ethnic enclave residence, and breast cancer survival among Latinas: Variations between California and Texas.

BACKGROUND: Among Latinas with breast cancer, residence in an ethnic enclave may be associated with survival. However, findings from prior studies are inconsistent. METHODS: The authors conducted parallel analyses of California and Texas cancer registry data for adult (aged ≥18 years) Latinas who were diagnosed with invasive breast cancer from 1996 to 2005, with follow-up through 2014. Existing indices applied to tract-level 2000 US Census data were used to measure Latinx enclaves and neighborhood socioeconomic status (nSES). Multivariable Cox proportional hazard models were fit for all-cause and breast cancer-specific survival adjusted for year of diagnosis, patient age, nativity (with multiple imputation), tumor stage, histology, grade, size, and clustering by census tract. RESULTS: Among 38,858 Latinas, the majority (61.3% in California and 70.5% in Texas) lived in enclaves. In fully adjusted models for both states, foreign-born women were found to be more likely to die of breast cancer and all causes when compared with US-born women. Living in enclaves and in neighborhoods with higher SES were found to be independently associated with improved survival from both causes. When combined into a 4-level variable, those in low nSES nonenclaves had worse survival for both causes compared with those living in low nSES enclaves and, in the all-cause but not breast cancer-specific models, those in high nSES neighborhoods, regardless of enclave status, had improved survival from all causes. CONCLUSIONS: Applying the same methods across 2 states eliminated previously published inconsistent associations between enclave residence and breast cancer survival. Future studies should identify specific protective effects of enclave residence to inform interventions.

County-level phenomapping to identify disparities in cardiovascular outcomes: An unsupervised clustering analysis: Short title: Unsupervised clustering of counties and risk of cardiovascular mortality.

INTRODUCTION: Significant heterogeneity in cardiovascular disease (CVD) risk and healthcare resource allocation has been demonstrated in the United States, but optimal methods to capture heterogeneity in county-level characteristics that contribute to CVD mortality differences are unclear. We evaluated the feasibility of unsupervised machine learning (ML)-based phenomapping in identifying subgroups of county-level social and demographic risk factors with differential CVD outcomes. METHODS: We performed a cross-sectional study using county-level data from 2008 to 2018 from the Centers for Disease Control (CDC) WONDER platform and the 2020 Robert Wood Johnson County Health Rankings program. Unsupervised clustering was performed on 46 facets of population characteristics spanning the demographic, health behaviors, socioeconomic, and healthcare access domains. Spatial autocorrelation was assessed using the Moran's I test, and temporal trends in age-adjusted CVD outcomes were evaluated using linear mixed effect models and least square means. RESULTS: Among 2676 counties, 4 county-level phenogroups were identified (Moran's I p-value <0.001). Phenogroup 1 (N â€‹= â€‹924; 24.5%) counties were largely white, suburban households with high income and access to healthcare. Phenogroup 2 counties (N â€‹= â€‹451; 16.9%) included predominantly Hispanic residents and below-average prevalence of CVD risk factors. Phenogroup 3 (N â€‹= â€‹951; 35.5%) counties included rural, white residents with the lowest levels of access to healthcare. Phenogroup 4 (350; 13.1%) comprised counties with predominantly Black residents, substantial cardiovascular comorbidities, and physical and socioeconomic burdens. Least square means in age-adjusted cardiovascular mortality over time increased in a stepwise fashion from 223 in phenogroup 1 to 317 per 100,000 residents in phenogroup 4. CONCLUSIONS: Unsupervised ML-based clustering on county-level population characteristics can identify unique phenogroups with differential risk of CVD mortality. Phenogroup identification may aid in developing a uniform set of preventive initiatives for clustered counties to address regional differences in CVD mortality.

Exposures at day labor corners: using existing georeferenced data to describe features of urban environments.

PURPOSE: Latino day laborers are male immigrants from mainly Mexico and Central America who congregate at corners, that is, informal hiring sites, to solicit short-term employment. Studies describing the occupational environment of Latino day laborers traditionally measure jobsite exposures, not corner exposures. We sought to elucidate exposures at corners by describing their demographic, socioeconomic, occupational, business, built, and physical environmental characteristics and by comparing corner characteristics with other locations in a large urban county in Texas. METHODS: We used multiple publicly available data sets from the U.S. Census, local tax authority, Google's Nearby Places Application Programming Interface, and Environmental Protection Agency at fine spatial scale to measure 34 characteristics of corners with matched comparison locations. RESULTS: Corners were located close to highways, high-traffic intersections, hardware and moving stores, and gas stations. Corners were in neighborhoods with large foreign-born and Latino populations, high rates of limited English proficiency, and high construction-sector employment. CONCLUSIONS: Publicly available data sources describe demographic, socioeconomic, occupational, business, built, and physical environment characteristics of urban environments at fine spatial scale. Using these data, we identified unique corner-based exposures experienced by day laborers. Future research is needed to understand how corner environments may influence health for this uniquely vulnerable population.