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This study examines the association of incarceration history and health insurance coverage and coverage changes in the U.S.Individuals with and without incarceration history were identified from the National Longitudinal Survey of Youth 1997 with follow-up through 2017-2018 (n=7,417). Generalized estimating equations were used to examine the associations between incarceration history and health insurance and coverage changes in the past 12 months. This study also assessed variation in associations by incarceration duration, frequency, and recency and reoffence history. Analysis was conducted in 2022.Individuals with incarceration history were more likely to be uninsured (AOR=1.69; 95% CI=1.55, 1.85) and to experience year-long uninsurance (AOR=1.34; 95% CI=1.12, 1.59) and were less likely to have stable health insurance coverage (AOR=1.30; 95% CI=1.08, 1.56) than individuals without incarceration history. Longer duration and more frequent incarcerations were associated with a higher likelihood of lack of and unstable insurance coverage and year-long uninsurance.People with an incarceration history had worse access to health insurance coverage. Targeted programs to improve health insurance coverage may reduce disparities associated with incarceration.

A cancer diagnosis can adversely affect other members of the family, including children. However, little is known about the extent to which history of parental cancer affects children's health.To examine associations of parental cancer with children's school absenteeism, medical care unaffordability, health care use, and mental health.This cross-sectional, nationally representative study used data from the 2010-2018 National Health Interview Survey. Statistical analyses were conducted from January to September 2021. Children aged 5 to 17 years living in families with and without a history of parental cancer were identified. Characteristics were grouped into child, parent, and family variables. Sequential multivariable regressions were conducted for unadjusted analyses and with the adjustment of child, parent, and family characteristics to assess associations between parental cancer and child outcomes.History of parental cancer.School absenteeism, medical care unaffordability, health care use, and mental health.A total of 1232 children (mean [SD] age, 11.7 [0.13] years; 579 [48.6%] female; weighted N = 846 730; 3.4% of total sample) were living in families with a history of parental cancer. Compared with 33 870 children without a history of parental cancer (mean [SD] age, 10.8 [0.03]; 16 287 [48.8%] female; weighted N = 24 315 452; 96.6% of total sample), children of cancer survivors were more likely to be older, non-Hispanic White, and living in single parent families. Parents with a history of cancer were more likely to be older, to be female, to have more comorbid conditions, and to have public health insurance compared with parents without a history of cancer. History of parental cancer was adversely associated with school absenteeism, medical care unaffordability, health care use, and mental health among children. Sequential adjustment with child, parent, and family characteristics reduced the magnitude of the associations. For example, the odds ratios for school absenteeism of 1 day or more changed from 1.33 (95% CI, 1.11-1.59; P = .002) to 1.12 (95% CI, 0.93-1.34; P = .23) and for any child hospital emergency department visit from 1.56 (95% CI, 1.31-1.86; P .001) to 1.36 (95 % CI, 1.13-1.64; P .001). Similar results were found for medical care unaffordability, prescription medication use, and mental health.In this study, parental cancer was associated with school absenteeism, medical care unaffordability, increased health care use, and poor mental health among children. Health care professionals and policies should consider the unique needs of affected children and develop school-, parent-, and family-directed strategies to ameliorate the negative associations between parental cancer and children's health.

Social determinants of health are the economic and environmental conditions under which people are born, live, work, and age that affect health. These structural factors underlie many of the long-standing inequities in cancer care and outcomes that vary by geography, socioeconomic status, and race and ethnicity in the United States. Housing insecurity, including lack of safe, affordable, and stable housing, is a key social determinant of health that can influence—and be influenced by—cancer care across the continuum, from prevention to screening, diagnosis, treatment, and survivorship. During 2021, the National Cancer Policy Forum of the National Academies of Science, Engineering, and Medicine sponsored a series of webinars addressing social determinants of health, including food, housing, and transportation insecurity, and their associations with cancer care and patient outcomes. This dissemination commentary summarizes the formal presentations and panel discussions from the webinar devoted to housing insecurity. It provides an overview of housing insecurity and health care across the cancer control continuum, describes health system interventions to minimize the impact of housing insecurity on patients with cancer, and identifies challenges and opportunities for addressing housing insecurity and improving health equity. Systematically identifying and addressing housing insecurity to ensure equitable access to cancer care and reduce health disparities will require ongoing investment at the practice, systems, and broader policy levels.

ImportanceThe association between cancer mortality and risk factors may vary by geography. However, conventional methodological approaches rarely account for this variation.ObjectiveTo identify geographic variations in the association between risk factors and cancer mortality.Design, Setting, and ParticipantsThis geospatial cross-sectional study used county-level data from the National Center for Health Statistics for individuals who died of cancer from 2008 to 2019. Risk factor data were obtained from County Health Rankings & Roadmaps, Health Resources and Services Administration, and Centers for Disease Control and Prevention. Analyses were conducted from October 2021 to July 2022.Main Outcomes and MeasuresConventional random forest models were applied nationwide and by US region, and the geographical random forest model (accounting for local variation of association) was applied to assess associations between a wide range of risk factors and cancer mortality.ResultsThe study included 7 179 201 individuals (median age, 70-74 years; 3 409 508 women [47.5%]) who died from cancer in 3108 contiguous US counties during 2008 to 2019. The mean (SD) county-level cancer mortality rate was 177.0 (26.4) deaths per 100 000 people. On the basis of the variable importance measure, the random forest models identified multiple risk factors associated with cancer mortality, including smoking, receipt of Supplemental Nutrition Assistance Program (SNAP) benefits, and obesity. The geographical random forest model further identified risk factors that varied at the county level. For example, receipt of SNAP benefits was a high-importance factor in the Appalachian region, North and South Dakota, and Northern California; smoking was of high importance in Kentucky and Tennessee; and female-headed households were high-importance factors in North and South Dakota. Geographic areas with certain high-importance risk factors did not consistently have a corresponding high prevalence of the same risk factors.Conclusions and RelevanceIn this cross-sectional study, the associations between cancer mortality and risk factors varied by geography in a way that did not correspond strictly to risk factor prevalence. The degree to which other place-specific characteristics, observed and unobserved, modify risk factor effects should be further explored, and this work suggests that risk factor importance may be a preferable paradigm for selecting cancer control interventions compared with risk factor prevalence.

Background Access to stable and affordable housing is an important social determinant of health in the United States. However, research addressing housing and cancer care, diagnosis, and outcomes has not been synthesized. Methods We conducted a systematic review of studies examining associations of housing and cancer care and outcomes using PubMed, Embase, Scopus, and CINAHL. Included studies were conducted in the United States and published in English between 1980 and 2021. Study characteristics and key findings were abstracted and qualitatively synthesized. Results A total of 31 studies were identified. Housing-related measures were reported at the individual level in 20 studies (65%) and area level in 11 studies (35%). Study populations and housing measures were heterogeneous. The most common housing measures were area-level housing discrimination (8 studies, 26%), individual-level housing status (8 studies, 26%), and individual-level housing concerns (7 studies, 23%). The most common cancer outcomes were screening (12 studies, 39%) and mortality (9 studies, 29%). Few studies assessed multiple dimensions of housing. Most studies found that exposure to housing insecurity was statistically significantly associated with worse cancer care (11 studies) or outcomes (10 studies). Conclusions Housing insecurity is adversely associated with cancer care and outcomes, underscoring the importance of screening for housing needs and supporting systemic changes to advance equitable access to care. Additional research is needed to develop and test provider- and policy-level housing interventions that can effectively address the needs of individuals throughout the cancer care continuum.

Understanding the urban form-air quality relationship is essential to mitigate intra-urban air pollution and to improve urban ecology. However, few studies considered urban form and meteorological factors integratively and analyzed their synthetic effects on air pollution. We investigate how to model the integrated effects on the spatiotemporal distribution of PM2.5 in the Atlanta metropolitan area to improve the understanding of the urban form-air quality relationship. Two groups of models are developed: one uses urban form only and the other uses wind-direct urban form. Relative humidity, wind speed, and temperature are included as control variables. Both linear (Multiple Linear Regression) and nonlinear models (Random Forest and Artificial Neural Network) are constructed and tested with both tenfold cross-validation and field PM2.5 data obtained from a portable device, AirBeam2. Random Forest overall outperforms other models suggesting that the urban form-air quality relationship is most likely to be nonlinear. Additionally, the group using wind-direct urban form outperforms the other group and the contribution of the same urban form metrics differs in different wind sections proving that meteorological factors and urban form have synthetic effects on PM2.5. Finally, the patch density, dominance, and aggregation of roads and vegetation, demonstrate higher attribute significance than other urban form metrics. Urban planners, practitioners, and policymakers need to carefully consider not only the spatial configuration of roads and vegetation but also the local climate patterns to minimize intra-urban air pollution effectively.

We employ a spatio-temporal network modelling approach to identify possible relations between strong earthquakes and spatial regions worldwide. A global strong earthquake dataset containing 7736 events (Mw ≥ 6.0) from 1964 to 2018 is used. Statistical results identify power-law relationships and heavy tail phenomena in the spatial patterns of strong earthquakes. The interactions between regions follow the same law, with a few regions that may be hit by successive strong earthquakes with high probability. Also, we find that the interconnections between regions are mainly related to the succession of events in time, whereas the distribution of events is extremely inhomogeneous in space. This study provides a research prototype for the spatio-temporal analysis of global strong earthquakes, laying a foundation for obtaining insights into the network modelling approach for global strong earthquakes.

69 Background: In the 1930s, the federally-sponsored Home Owners’ Loan Corporation (HOLC) created maps that directed mortgage financing based largely on a neighborhood’s racial composition. American neighborhoods were subdivided into four risk-based rankings (A – best neighborhood, B – still desirable, C – in decline, and D – hazardous and mapped in red) for mortgage approvals and denials. “Redlining” resulted in racial segregation and systemic disinvestment in communities targeted for marginalization. We investigated the association between historical housing discrimination and contemporary diagnosis, treatment, and survival outcomes in colon cancer – a leading cause of cancer deaths amenable to early detection and treatment. Methods: Individuals diagnosed with colon cancer from 2007-2017 were identified from the National Cancer Database. Individuals residing within known zip code tabulation areas (ZCTA) in 196 cities with ≥10% HOLC coverage were included. Residences were assigned a HOLC grade (A, B, C, or D) based on the majority HOLC area represented. Multivariable logistic regression models (adjusted for age and sex) were used to investigate the association of housing discrimination and late stage (stages III/IV) diagnosis, time to chemotherapy initiation, and non-guideline-concordant care (no chemotherapy, surgery, or < 12 lymph node dissection). Multivariable Cox proportional hazard models with age as time scale were used to investigate the association of housing discrimination and overall survival. Results: There were 98,335 patients with new diagnoses of colon cancer with median age 68 years. Individuals residing in HOLC D were more likely to be non-Hispanic White (59%), have public insurance (46%), and income < $40,000/year. Compared to people living in majority HOLC A ZCTAs, living in majority HOLC D had higher odds of a late-stage diagnosis, and living in majority HOLC B, C, or D had higher odds of non-guideline concordant colon cancer care with longer time to chemotherapy initiation. For people living in majority HOLC C and D, overall survival for all stages and late stage was worse when compared to HOLC A ZCTAs. Findings were consistent in sensitivity analysis. Conclusions: Historical housing discrimination is adversely associated with contemporary colon cancer care and outcomes. Findings underscore the importance of state-and federal-level practices on mortgage lending regulation and fair housing practices in determining equitable cancer risk, access to care, and outcomes.[Table: see text]

3 Background: Disparities in receipt of care for non-small cell lung cancer (NSCLC) are well described. Discriminatory mortgage lending, which limits access to home ownership in specific neighborhoods overall and disproportionately for racialized groups, is a marker of systemic racism and lower levels of neighborhood investment. This may, in turn, decrease access to high quality care. We used the mortgage denial rate as a measure of housing discrimination and investigated its association with guideline-concordant NSCLC care. Methods: Mortgage denial rates were estimated at the zip code tabulation areas (ZCTAs) level using the Home Mortgage Disclosure Act (HMDA) database (2014-2019). Mortgage denial rates represent the proportion of denied home loans to total loans and were categorized into quartiles. Individuals ≥ 18 years diagnosed with NSCLC 2014-2019 were identified from the National Cancer Database and combined with HMDA. Multivariable logistic regression models examined associations between mortgage discrimination and receipt of guideline-concordant care, including surgery, chemotherapy, and chemoradiation. A multivariable Cox proportional hazard model examined the association between mortgage discrimination and time to chemotherapy initiation. Results: Cohort included 450,614 patients newly diagnosed with NSCLC resided in 33,120 ZCTAs. Individuals residing in ZCTAs with higher mortgage denial rates were more likely to be aged 45-64 years, male, non-Hispanic White, with private health insurance coverage and income < $40,000/year. 69% of all patients received guideline-concordant care. Likelihood of guideline-concordant care was lower in neighborhoods with higher mortgage denial rates, adjusting for age and sex (Table). This disparity was present in all care subgroups. Time to chemotherapy initiation was longer for patients in neighborhoods with higher mortgage denial rates. Conclusions: Mortgage discrimination is adversely associated with receipt of guideline-concordant NSCLC care. Our examination of institutional practices leading to barriers in access to resources highlights the critical need to understand the pathways through which area-level mortgage denials impact receipt of equitable cancer care.[Table: see text]

Background Breast cancer is the most common cancer among women in the United States. However, data on spatial disparities in survival for breast cancer are limited in the country. This study estimated 5-year relative survival (RS) of female breast cancer and examined the spatial variations across the contiguous United States. Methods Women newly diagnosed with breast cancer in 2003-2010 in the United States were identified from the National Cancer Database and followed up through 2016. The crude 5-year RS at the county level was estimated and adjusted for patients' key sociodemographic and clinical factors. To account for spatial effects, the RS estimates were smoothed using the Bayesian spatial survival model. A local spatial autocorrelation analysis with the Getis-Ord Gi* statistics was applied to identify geographic clusters of low or high RS. Results Clusters of low RS were identified in more than 15 states covering 671 counties, mostly in the southeast and southwest regions, including Georgia, Alabama, Mississippi, Louisiana, Arkansas, Oklahoma, and Texas. Approximately 30% of these clusters can be explained by patients' characteristics: Race, insurance, and stage at diagnosis appeared to be the major attributable factors. Conclusions Significant spatial disparity in female breast cancer survival was found, with low RS clusters identified in Georgia, Alabama, Mississippi, Louisiana, Arkansas, Oklahoma, and Texas. Policies and interventions that focus on serving Black women, improvements in insurance coverage, and early detection in these areas could potentially mitigate the spatial disparities.

12014 Background: A cancer diagnosis is associated with substantial economic burden among cancer survivors and their families. Some families make sacrifices that adversely affect food, housing, and transportation to offset high out-of-pocket medical expenses. Cancer survivors with minor children may be particularly vulnerable to financial hardship, even years after diagnosis. However, little is known about the extent to which parental cancer affects minor children’s food insecurity, unmet housing needs, and delayed medical care due to transportation barriers. Methods: The 2013 to 2018 National Health Interview Survey was used to identify minor children (ages 5-17 years) living in families with a parental cancer history (n = 812, representing 860,488 children) and children without a parental cancer history (n = 22,129, representing about 24.5 million children). Multivariable logistic regressions were used to compare family-level food insecurity, parent’s worry about ability to pay monthly bills and housing costs, and delayed medical care for the child because of no transportation between minor children with and without a parental cancer history. All analyses adjusted for child-, parent-, and family-related characteristics, including child’s age group, sex, and race/ethnicity; parent’s age group, sex, race/ethnicity, health insurance coverage, number of comorbid conditions, and obesity status; family’s structure (married/cohabiting parents versus single parent families), highest educational attainment in the family, and family income as a percentage of the federal poverty level. Results: About 3.4% of minor children were living in families with a parental cancer history. In adjusted analyses and compared to children whose parents did not report a history of cancer, children of cancer survivors were more likely to live in families that experience shortages in basic economic needs, such as food bought did not last 26.0% (95% confidence intervals[CI]: 22.3%-29.7%) vs 16.7% (95CI: 16.1%-17.3%), inability to afford balanced meals 16.9% (95CI: 13.8%-20.0%) vs 13.3% (95CI: 12.8%-13.8%), worry about paying monthly bills 44.8% (95CI: 40.6%-48.9%) vs 37.9% (95CI: 37.1%-38.7%), and worry about housing costs 35.7% (95CI: 31.9%-39.5%) vs 30.7% (95CI: 30.0%-31.5%). Moreover, children with a parental cancer history were more likely to experience delayed medical care due to lack of transportation than children without a parental cancer history 3.6% (95CI: 2.2%-4.9%) vs 1.6% (95CI: 1.4%-1.9%), all p

This study investigates the spatiotemporal pattern of the 2014 Ebola virus disease (EVD) epidemic in the most heavily affected countries in West Africa and also mines the spatial associations between such pattern and other geographically distributed factors. Utilizing the publicly available open-source data, this study demonstrates a research design that integrates various geospatial data processing, analysis, and data-mining techniques to achieve the research objectives. For the 2014 EVD epidemic, spatiotemporal patterns were analyzed and visualized. Fine-grained population data were obtained through a population interpolation method to conduct healthcare accessibility analysis. Finally, associations between the spatiotemporal patterns of the incidences and healthcare accessibility as well as other factors were examined. The results suggest that (1) poor accessibility to healthcare facilities and EVD clusters are identified in many urban areas as well as some remote areas; and (2) EVD cases were more likely to be found in border areas of these countries where accessibility to healthcare facilities is poorer.

The study develops a modeling framework to quantify the saliency of individual buildings and to visualize them accordingly in a virtual 3D urban environment for wayfinding. Based on the cognitive characteristics of wayfinding behaviors and considering the relationships among pathfinder, buildings, and local context of the urban environment, this study defines and distinguishes two types of variables related to the saliency of a building, the global salience variables and the local salience variables. Then an adaptive weight distribution method is developed to determine the weight for each variable. Global salience is estimated in the context of a broader urban space, while local salience is estimated in the local region. Finally, a synthesized salience model is constructed by integrating the global and local salience values with consideration of the visibility factor. The salience values are used to identify most salient landmarks in each scene on the path of wayfinding. In the implemented prototype, 3D visualization is made for each scene showing buildings with varying levels of details according to their salience values. This study contributes to the research on intelligent 3D navigation systems by providing effective visual guidance for wayfinding tasks in virtual urban environments.

This paper focuses on the relationships among global strong earthquakes, elevation and crustal thickness. The earthquake frequencies under different elevations and crustal thicknesses are counted. The results show that the elevation-based earthquake frequency has two maxima when the elevation e ∈ ( − 2000 , − 1600 ) and e ∈ ( − 400 , 0 ) , and the crustal thickness-based earthquake frequency reaches two maxima when the crustal thickness 7 km c 8 km and 10 km c 11 km . The combination analysis of elevation and crustal thickness indicates that the high earthquake frequency appears at c = 8 km and 11 km, and − 4000 m e − 1200 m . Besides, this study finds that the relationships between earthquake frequency and crustal thickness present different characteristics for undersea quakes and land quakes. Moreover, the frequency of strong earthquakes under the common constraint of both elevation and crustal thickness shows a heavy-tail distribution with the exponent less than 1, which indicates that there exists some regions with high earthquake frequencies, and these regions may have similar properties in elevation and crustal thickness.

Cities are complicated dynamic systems that result in the agglomerations of streets, population and socioeconomic activities. In this paper, we use the partition method of regular grid model to divide a city into small areas, and introduce the concept of agglomeration centrality for describing agglomeration characteristics of local areas in a city. A new measure of agglomeration centrality is defined considering the penetrability of roads within a local area from the 2-dimension plane perspective. Based on this, we introduce the concept of overall agglomeration intensity to illustrate the agglomeration pattern of the city from macro level. Experiments on a set of cities show that the agglomeration centrality distribution of local areas in a city present a power law phenomenon. Besides, the results reveal a crucial important phenomenon that the power law exponent is related to city area and partition scale. The exponent can be described using a power function with two terms and has an upper limit. Moreover, we find that the overall agglomeration intensity indicator is useful to reflect the spatial agglomeration pattern of street networks. In summary, this study develops a new centrality measure from 2-dimension perspective and demonstrates its effectiveness for understanding the spatial agglomeration pattern of cities.

Cities grow with processes resulting in the agglomeration of population and socioeconomic activities. At any stage of urban development, a city possesses a spatial structure of urban fabric to facilitate its functions. In this study, we find that the agglomeration characteristics of a city are significant for the identification and understanding of urban spatial structure. We propose a new centrality measure, termed agglomeration centrality, to examine the centrality of a node based on its relative level of clumpiness in an urban road network. We show a simple method to computationally define the agglomeration centrality based on Voronoi tessellations of all nodes in the network. On this basis, we investigate the spatial distribution of agglomeration centrality of urban road networks. Experiments on a set of randomly selected cities show that the agglomeration distributions of all these urban street networks present a remarkable double-power-law phenomenon. The distribution of the agglomeration centrality measures shows an invariant spatial scaling rule for cities. The regions with the highest centralities are always found to be urban centers. In comparison, this cannot be achieved by any current centrality measures. Finally, in an effort to explore the potential additional applicability of the new centrality measure to aid our understanding of spatial structures of other urban demographic or socioeconomic attributes, the agglomeration centrality was combined with the population data to create a population agglomeration index. The distribution of this index indicates a single-power-law property. In summary, this study develops a new centrality measure and demonstrates its effectiveness for understanding the spatial structures and spatial evolution of cities.