Discovering dominant tumor immune archetypes in a pan-cancer census.

Cancers display significant heterogeneity with respect to tissue of origin, driver mutations, and other features of the surrounding tissue. It is likely that individual tumors engage common patterns of the immune system-here "archetypes"-creating prototypical non-destructive tumor immune microenvironments (TMEs) and modulating tumor-targeting. To discover the dominant immune system archetypes, the University of California, San Francisco (UCSF) Immunoprofiler Initiative (IPI) processed 364 individual tumors across 12 cancer types using standardized protocols. Computational clustering of flow cytometry and transcriptomic data obtained from cell sub-compartments uncovered dominant patterns of immune composition across cancers. These archetypes were profound insofar as they also differentiated tumors based upon unique immune and tumor gene-expression patterns. They also partitioned well-established classifications of tumor biology. The IPI resource provides a template for understanding cancer immunity as a collection of dominant patterns of immune organization and provides a rational path forward to learn how to modulate these to improve therapy.

A multifaceted poverty reduction program has economic and behavioral consequences.

This paper examines the causal impact of poverty reduction interventions on the social preferences of the poor. A multifaceted poverty reduction program in China provides a setting for the use of a fuzzy regression discontinuity design. The design compares households with base-year income just below a preset criterion, who were more likely to receive the program treatment, with households just above the criterion. Five years after the program's launch, we conducted a lab-in-the-field experiment to measure the distributional preferences of household heads. Combining quasi-random variation from program rules with administrative census and experimental data, we find both economic and behavioral consequences of the program: It increased household income by 50% 5 y later, increased consistency with utility maximization by household heads, and increased their efficiency preference while reducing selfishness and leaving equality preference unchanged. Our findings advance scientific understanding of social preferences formation and highlight a broad perspective in evaluating poverty reduction interventions.

Genome-wide census of ATF4 binding sites and functional profiling of trait-associated genetic variants overlapping ATF4 binding motifs.

Activating Transcription Factor 4 (ATF4) is an important regulator of gene expression in stress responses and developmental processes in many cell types. Here, we catalogued ATF4 binding sites in the human genome and identified overlaps with trait-associated genetic variants. We probed these genetic variants for allelic regulatory activity using a massively parallel reporter assay (MPRA) in HepG2 hepatoma cells exposed to tunicamycin to induce endoplasmic reticulum stress and ATF4 upregulation. The results revealed that in the majority of cases, the MPRA allelic activity of these SNPs was in agreement with the nucleotide preference seen in the ATF4 binding motif from ChIP-Seq. Luciferase and electrophoretic mobility shift assays in additional cellular models further confirmed ATF4-dependent regulatory effects for the SNPs rs532446 (GADD45A intronic; linked to hematological parameters), rs7011846 (LPL upstream; myocardial infarction), rs2718215 (diastolic blood pressure), rs281758 (psychiatric disorders) and rs6491544 (educational attainment). CRISPR-Cas9 disruption and/or deletion of the regulatory elements harboring rs532446 and rs7011846 led to the downregulation of GADD45A and LPL, respectively. Thus, these SNPs could represent examples of GWAS genetic variants that affect gene expression by altering ATF4-mediated transcriptional activation.

An in-depth examination of requirements for disclosure risk assessment.

The use of formal privacy to protect the confidentiality of responses in the 2020 Decennial Census of Population and Housing has triggered renewed interest and debate over how to measure the disclosure risks and societal benefits of the published data products. We argue that any proposal for quantifying disclosure risk should be based on prespecified, objective criteria. We illustrate this approach to evaluate the absolute disclosure risk framework, the counterfactual framework underlying differential privacy, and prior-to-posterior comparisons. We conclude that satisfying all the desiderata is impossible, but counterfactual comparisons satisfy the most while absolute disclosure risk satisfies the fewest. Furthermore, we explain that many of the criticisms levied against differential privacy would be levied against any technology that is not equivalent to direct, unrestricted access to confidential data. More research is needed, but in the near term, the counterfactual approach appears best-suited for privacy versus utility analysis.

Census of exposed aggregation-prone regions in proteomes.

Loss of solubility usually leads to the detrimental elimination of protein function. In some cases, the protein aggregation is also required for beneficial functions. Given the duality of this phenomenon, it remains a fundamental question how natural selection controls the aggregation. The exponential growth of genomic sequence data and recent progress with in silico predictors of the aggregation allows approaching this problem by a large-scale bioinformatics analysis. Most of the aggregation-prone regions are hidden within the 3D structure, rendering them inaccessible for the intermolecular interactions responsible for aggregation. Thus, the most realistic census of the aggregation-prone regions requires crossing aggregation prediction with information about the location of the natively unfolded regions. This allows us to detect so-called 'exposed aggregation-prone regions' (EARs). Here, we analyzed the occurrence and distribution of the EARs in 76 reference proteomes from the three kingdoms of life. For this purpose, we used a bioinformatics pipeline, which provides a consensual result based on several predictors of aggregation. Our analysis revealed a number of new statistically significant correlations about the presence of EARs in different organisms, their dependence on protein length, cellular localizations, co-occurrence with short linear motifs and the level of protein expression. We also obtained a list of proteins with the conserved aggregation-prone sequences for further experimental tests. Insights gained from this work led to a deeper understanding of the relationship between protein evolution and aggregation.

Burnout in Urological Education: An In-Depth Study of Residents and Fellows in the 2021 AUA Census.

PURPOSE: Our goal was to explore the current trends in burnout, career choice regret, and well-being needs among urology residents and fellows, with specific emphasis on identifying key factors associated with burnout. MATERIALS AND METHODS: The AUA Workforce Workgroup collaborated with the AUA Data Team to analyze data from the 2021 AUA Census, comprising a total of 243 residents and fellows. Key demographics, benefits and resources, career choice and debt, and burnout levels were analyzed, focusing on variables like gender, PGY (postgraduate year) level, debt burden, and personal health appointments. RESULTS: Overall, 48% of residents and 33% of fellows met criteria for professional burnout, with a higher incidence among PGY-2 residents (70%). Depersonalization was particularly notable, with 74% of residents reporting medium to high levels. Burnout was significantly associated with difficulty attending personal health appointments (52% vs 34%) and lack of access to on-call rooms (54% vs 36%). In contrast, having children during residency was associated with lower burnout levels (30.8% vs 49.1%). Meal plans were ranked as the most desired benefit (32%), followed by ability to attend health appointments during work hours (17%) and paid family leave (16%). Educational debt over $150,000 was carried by 53% of residents and 48% of fellows. Interestingly, burnout rates showed no statistically significant difference in response rates across genders, relationship status, amount of educational debt, presence of paid maternity or paternity leave, and type of childcare arrangements. CONCLUSIONS: Burnout remains a significant issue among urology trainees, with a complex interplay of factors like lack of personal time and provision of call rooms. The alarming rates of depersonalization and exhaustion highlight the urgency of implementing targeted interventions. Enhanced support systems, improved access to health care appointments, provision of call rooms, and debt management programs are recommended to alleviate the growing problem of professional burnout in the field of urology.

Risk Factors and Inequities in Transportation Injury and Mortality in the Canadian Census Health and Environment Cohorts (CanCHECs).

BACKGROUND: Road traffic injury contributes substantially to morbidity and mortality. Canada stands out among developed countries in not conducting a national household travel survey, leading to a dearth of national transportation mode data and risk calculations that have appropriate denominators. Since traffic injuries are specific to the mode of travel used, these risk calculations should consider travel mode. METHODS: Census data on mode of commute is one of the few sources of these data for persons aged 15 and over. This study leveraged a national data linkage cohort, the Canadian Census Health and Environment Cohorts, that connects census sociodemographic and commute mode data with records of deaths and hospitalizations, enabling assessment of road traffic injury associations by indicators of mode of travel (commuter mode). We examined longitudinal (1996-2019) bicyclist, pedestrian, and motor vehicle occupant injury and fatality risk in the Canadian Census Health and Environment Cohorts by commuter mode and sociodemographic characteristics using Cox proportional hazards models within the working adult population. RESULTS: We estimated positive associations between commute mode and same mode injury and fatality, particularly for bicycle commuters (hazard ratios for bicycling injury was 9.1 and for bicycling fatality was 11). Low-income populations and Indigenous people had increased injury risk across all modes. CONCLUSIONS: This study shows inequities in transportation injury risk in Canada and underscores the importance of adjusting for mode of travel when examining differences between population groups.

Survival analysis under imperfect record linkage using historic census data.

BACKGROUND: Advancements in linking publicly available census records with vital and administrative records have enabled novel investigations in epidemiology and social history. However, in the absence of unique identifiers, the linkage of the records may be uncertain or only be successful for a subset of the census cohort, resulting in missing data. For survival analysis, differential ascertainment of event times can impact inference on risk associations and median survival. METHODS: We modify some existing approaches that are commonly used to handle missing survival times to accommodate this imperfect linkage situation including complete case analysis, censoring, weighting, and several multiple imputation methods. We then conduct simulation studies to compare the performance of the proposed approaches in estimating the associations of a risk factor or exposure in terms of hazard ratio (HR) and median survival times in the presence of missing survival times. The effects of different missing data mechanisms and exposure-survival associations on their performance are also explored. The approaches are applied to a historic cohort of residents in Ambler, PA, established using the 1930 US census, from which only 2,440 out of 4,514 individuals (54%) had death records retrievable from publicly available data sources and death certificates. Using this cohort, we examine the effects of occupational and paraoccupational asbestos exposure on survival and disparities in mortality by race and gender. RESULTS: We show that imputation based on conditional survival results in less bias and greater efficiency relative to a complete case analysis when estimating log-hazard ratios and median survival times. When the approaches are applied to the Ambler cohort, we find a significant association between occupational exposure and mortality, particularly among black individuals and males, but not between paraoccupational exposure and mortality. DISCUSSION: This investigation illustrates the strengths and weaknesses of different imputation methods for missing survival times due to imperfect linkage of the administrative or registry data. The performance of the methods may depend on the missingness process as well as the parameter being estimated and models of interest, and such factors should be considered when choosing the methods to address the missing event times.

Prevalence of menthol cigarette use among adults who smoke from the United States by census division and demographic subgroup, 2002-2020: findings from the International Tobacco Control (ITC) project.

BACKGROUND: Targeted marketing of menthol cigarettes in the US influences disparities in the prevalence of menthol smoking. There has been no analysis of sub-national data documenting differences in use across demographic subgroups. This study estimated trends in the prevalence of menthol use among adults who smoke in the nine US census divisions by sex, age, and race/ethnicity from 2002 to 2020. METHODS: Data from 12 waves of the US ITC Survey were used to estimate the prevalence of menthol cigarette use across census divisions and demographic subgroups using multilevel regression and post-stratification (n = 12,020). Multilevel logistic regression was used to predict the prevalence of menthol cigarette use in 72 cross-classified groups of adults who smoke defined by sex, age, race/ethnicity, and socioeconomic status; division-level effects were fit with a random intercept. Predicted prevalence was weighted by the total number of adults who smoke in each cross-classified group and aggregated to divisions within demographic subgroup. Estimates were validated against the Tobacco Use Supplement to the Current Population Survey (TUS-CPS). RESULTS: Overall modeled prevalence of menthol cigarette use was similar to TUS-CPS estimates. Prevalence among adults who smoke increased in each division from 2002 to 2020. By 2020, prevalence was highest in the Middle (46.3%) and South Atlantic (42.7%) and lowest in the Pacific (25.9%) and Mountain (24.2%) divisions. Prevalence was higher among adults aged 18-29 (vs. 50+) and females (vs. males). Prevalence among non-Hispanic Black people exceeded 80% in the Middle Atlantic, East North Central, West North Central, and South Atlantic in all years and varied most among Hispanic people in 2020 (Pacific: 26.5%, New England: 55.1%). CONCLUSIONS: Significant geographic variation in the prevalence of menthol cigarette use among adults who smoke suggests the proposed US Food and Drug Administration (FDA) menthol cigarette ban will exert differential public health benefits and challenges across geographic and demographic subgroups.

Evaluating Methods for Mapping Historical Redlining to Census Tracts for Health Equity Research.

Neighborhood characteristics including housing status can profoundly influence health. Recently, increasing attention has been paid to present-day impacts of "redlining," or historic area classifications that indicated less desirable (redlined) areas subject to decreased investment. Scholarship of redlining and health is emerging; limited guidance exists regarding optimal approaches to measuring historic redlining in studies of present-day health outcomes. We evaluated how different redlining approaches (map alignment methods) influence associations between redlining and health outcomes. We first identified 11 existing redlining map alignment methods and their 37 logical extensions, then merged these 48 map alignment methods with census tract life expectancy data to construct 9696 linear models of each method and life expectancy for all 202 redlined cities. We evaluated each model's statistical significance and R2 values and compared changes between historical and contemporary geographies and populations using Root Mean Squared Error (RMSE). RMSE peaked with a normal distribution at 0.175, indicating persistent difference between historical and contemporary geographies and populations. Continuous methods with low thresholds provided higher neighborhood coverage. Weighting methods had more significant associations, while high threshold methods had higher R2 values. In light of these findings, we recommend continuous methods that consider contemporary population distributions and mapping overlap for studies of redlining and health. We developed an R application {holcmapr} to enable map alignment method comparison and easier method selection.

The effect of educational attainment on birthrate in Japan: an analysis using the census and the vital statistics from 2000 to 2020.

BACKGROUND: In Japan, difference in birth rates depending on educational attainment has not been investigated. This study aimed to reveal birth rates in Japan depending on the highest level of educational attainment and their trends over the years using nationwide government statistics data. METHODS: Individual-level data from Vital Statistics and the Census from 2000, 2010, and 2020 were used for birth and population data, respectively. Data linkage was conducted for males and females in the Census and fathers and mothers in the Vital Statistics using information about gender, household, nationality, marital status, birth year, birth month, prefecture, and municipality for individuals. The birth rate was calculated by gender, a five-year age group, the highest level of educational attainment achieved, and year. In addition, the slope index of inequality (SII) and relative index of inequality (RII) were calculated to evaluate the degree of inequality in birth rates, depending on the educational attainment. RESULTS: Birth rates were higher in persons with lower educational attainment compared to those with a higher educational attainment among males and females in their twenties, while they tended to be higher in persons with higher educational attainment among those in their thirties and forties. Additionally, an increase in the birth rate from 2000 to 2020 was the largest in university graduates among males aged 25-49 years and women aged 30-49 years, and a decrease in the birth rate was the smallest in university graduates among males and females aged 20-24 years. As a result, SII and RII increased from 2000 to 2020 among males and females in their thirties and forties. CONCLUSIONS: In conclusion, persons with higher educational attainment tended to have a relatively favorable trend in the birth rate compared with persons with lower educational attainment in recent decades. It suggested that enhanced administrative support for individuals with lower educational attainment or lower socioeconomic status may be required to ameliorate the declining birth rate in Japan.

U.S. Fertility in Life Course Context: A Research Note on Using Census-Held Linked Administrative Records for Geographic and Sociodemographic Subgroup Estimation.

Fertility is a life course process that is strongly shaped by geographic and sociodemographic subgroup contexts. In the United States, scholars face a choice: they can situate fertility in a life course perspective using panel data, which is typically representative only at the national level; or they can attend to subnational contexts using rate schedules, which do not include information on life course statuses. The method and data source we introduce here, Census-Held Linked Administrative Records for Fertility Estimation (CLAR-FE), permits both. It derives fertility histories and rate schedules from U.S. Census Bureau-held data for the nation and by state, racial and ethnic subgroups, and the important life course status of parity. We generate three types of rates for 2000-2020 at the national and state levels by race and ethnicity: age-specific rates and both unconditional and conditional parity- and age-specific rates. Where possible, we compare these rates with those produced by the National Center for Health Statistics. Our new rate schedules illuminate state and racial and ethnic differences in transitions to parenthood, providing evidence of the important subgroup heterogeneity that characterizes the United States. CLAR-FE covers nearly the entire U.S. population and is available to researchers on approved projects through the Census Bureau's Federal Statistical Research Data Centers.

A Research Note on Community Resilience Estimates: New U.S. Census Bureau Data With an Application to Excess Deaths From COVID-19.

In this research note, we describe the results of the first validation study of the U.S. Census Bureau's new Community Resilience Estimates (CRE), which uses Census microdata to develop a tract-level vulnerability index for the United States. By employing administrative microdata to link Social Security Administration mortality records to CRE, we show that CRE quartiles provide more stable predictions of COVID-19 excess deaths than single demographic categorizations such as race or age, as well as other vulnerability measures including the U.S. Centers for Disease Control and Prevention's Social Vulnerability Index (SVI) and the Federal Emergency Management Agency's National Risk Index (NRI). We also use machine learning techniques to show that CRE provides more predictive power of COVID-19 excess deaths than standard socioeconomic predictors of vulnerability such as poverty and unemployment, as well as SVI and NRI. We find that a 10-percentage-point increase in a key CRE risk measure is associated with one additional death per neighborhood during the initial outbreak of COVID-19 in the United States. We conclude that, compared with alternative measures, CRE provides a more accurate predictor of community vulnerability to a disaster such as a pandemic.

Prevalence and correlates of disability in older adults, Ghana: evidence from the Ghana 2021 Population and Housing Census.

BACKGROUND: Although there are studies on disabilities in older persons, most of these studies have been carried out in developed countries. Hence, there are limited studies on disability in older adults in sub-Saharan Africa, including Ghana. The few studies that have examined the prevalence and correlates of disability in older adults used survey data for their analyses. To contribute to addressing this knowledge gap that has arisen, this study used a national census, the 2021 Ghana Population and Housing Census, to examine the prevalence and correlates of disability in older adults in Ghana. METHODS: The 2021 Ghana Population and Housing Census data was used for this study. A sample size of 197,057 Ghanaians aged 60 years and above was used for this study. The Washington Group questions on disability were used to measure disability by asking older adults about their difficulties in performing the six domains of disability (physical, sight, intellectual, hearing, self-care, and speech). A multinomial logistic regression housed in STATA was used to analyse the correlates of disability in older adults in Ghana. A p-value less than 0.05 was used for statistical significance. RESULTS: The results show that slightly more than one-third (38.4%) of the older adults were disabled. In terms of the number of disabilities in older adults, 16.9% had one disability condition, while 2.4% had six disability conditions. Also, 9.4% had two disability conditions. Older adults who were females, aged 70-79 years and 80 years and above, resided in rural areas, with primary, JHS/Middle, SHS, unaffiliated with religion, ever married and never married, unemployed, and belonged to the middle and rich households were more likely to have a disability condition. Also, older adults residing in the Middle and Northern zones, having no health insurance, and using clean cooking fuel were less likely to have a disability condition. CONCLUSIONS: The results show that socio-demographic and household factors were associated with disability in older adults in Ghana. Hence, policymakers and researchers should target these factors when designing appropriate policies, programmes, and interventions to improve the wellbeing of older adults.

Precision mapping child undernutrition for nearly 600,000 inhabited census villages in India.

There are emerging opportunities to assess health indicators at truly small areas with increasing availability of data geocoded to micro geographic units and advanced modeling techniques. The utility of such fine-grained data can be fully leveraged if linked to local governance units that are accountable for implementation of programs and interventions. We used data from the 2011 Indian Census for village-level demographic and amenities features and the 2016 Indian Demographic and Health Survey in a bias-corrected semisupervised regression framework to predict child anthropometric failures for all villages in India. Of the total geographic variation in predicted child anthropometric failure estimates, 54.2 to 72.3% were attributed to the village level followed by 20.6 to 39.5% to the state level. The mean predicted stunting was 37.9% (SD: 10.1%; IQR: 31.2 to 44.7%), and substantial variation was found across villages ranging from less than 5% for 691 villages to over 70% in 453 villages. Estimates at the village level can potentially shift the paradigm of policy discussion in India by enabling more informed prioritization and precise targeting. The proposed methodology can be adapted and applied to diverse population health indicators, and in other contexts, to reveal spatial heterogeneity at a finer geographic scale and identify local areas with the greatest needs and with direct implications for actions to take place.

Social cartography and satellite-derived building coverage for post-census population estimates in difficult-to-access regions of Colombia.

Effective government services rely on accurate population numbers to allocate resources. In Colombia and globally, census enumeration is challenging in remote regions and where armed conflict is occurring. During census preparations, the Colombian National Administrative Department of Statistics conducted social cartography workshops, where community representatives estimated numbers of dwellings and people throughout their regions. We repurposed this information, combining it with remotely sensed buildings data and other geospatial data. To estimate building counts and population sizes, we developed hierarchical Bayesian models, trained using nearby full-coverage census enumerations and assessed using 10-fold cross-validation. We compared models to assess the relative contributions of community knowledge, remotely sensed buildings, and their combination to model fit. The Community model was unbiased but imprecise; the Satellite model was more precise but biased; and the Combination model was best for overall accuracy. Results reaffirmed the power of remotely sensed buildings data for population estimation and highlighted the value of incorporating local knowledge.

[Working Time of Physicians in Germany: Results of the Micro-Census with a Focus on Established Practitioners]. / Arbeitszeit von Ärztinnen und Ärzten in Deutschland: Ergebnisse des Mikrozensus mit Fokus auf Niedergelassene.

Medical practitioners are considered to be an occupational group with a high workload. However, findings on working hours are incomplete. Therefore, we investigated data on "normal" working hours and corresponding preferences in the course of an analysis of the Microcensus 2017. Established physicians reported an average working time of 48,8 h per week for full-time employment, 46,2 h as dependent employees. Dependent employees working part-time, reported about 4 h more than established doctors. Male doctors reported about 4 h more than female doctors when working full-time, and 5 h less when working part-time. The proportion of part-time work was significantly higher for female physicians than for male physicians (28% vs. 10%). The specific analysis for established doctors also showed an inverse discrepancy: if part-time, female physicians worked 4 h more than male physicians; if full-time, male physicians worked 4 h more than female physicians. Established doctors worked less than employees when working part-time. Here, too, the rate was higher for female physicians (19,5% vs. 10,6%). Overall, 14% worked part-time (just under 20 h per week), 86% full-time (just under 49 h). Dentists reported slightly lower working hours, while general practitioners and specialists were about the same at 45 hours. This difference was due to differences in full-time work, which is about 50 h for general practitioners and specialists and 46 h for dentists. In contrast, part-time dentists worked longer hours (24 vs. 18 h). Only a few physicians, especially those working part-time (6,5%), stated that they would like to work more. Most of them would like to work slightly more hours. The majority of women cited family obligations (68%) as the reason for part-time work, while men mostly cited "other" reasons (76%) and less often childcare or personal/family obligations (15%). A total of 13% of those working full-time would like to work fewer hours, women slightly more often. This analysis complements sources such as the Zi Practice Panel. At the overall level, the microcensus average was 5 h lower than the ZiPP (50 h/week). The limitations for survey data known from methodology are countered by the very high sample quality.

Assessing the impact of socio-demographics and farming activity on ward-level mortality patterns using farm and population decennial censuses.

INTRODUCTION AND OBJECTIVE: Farmers experience a specific set of unique dangers, which increases their risk of mortality compared with any other occupation. This study hypothesised that Northern Ireland's (NIs) agriculturally saturated Wards have a higher risk of mortality compared against non-agriculturally based Wards. DESIGN: The Population Census and Farm Census information were downloaded from the Northern Ireland Neighbourhood Service (NINIS) online depository to compile three mortality-based data sets (2001, 2011, pooled data sets). Assessing the impact of socio-demographics and farming activity on Ward-level mortality patterns using farm and population decennial censuses. This study analysed all 582 Ward areas of NI, which enclosed the entire populace of the country in 2001 and 2011. FINDINGS: Path analysis was utilised to examine direct and indirect paths linked with mortality within two census years (2001; 2011), alongside testing pathways for invariance between census years (pooled data set). Ward-level results provided evidence for exogenous variables to mortality operating through three/four endogenous variables via: (i) direct effects (age), (ii) summed indirect effects (age; males; living alone; farming profit; and deprivation) and (iii) total effects (age; males; living alone; and deprivation). Multi-group results cross-validated these cause-and-effect relationships relating to mortality. DISCUSSION AND CONCLUSION: This study demonstrated that farming intensity scores, farming profits and socio-demographics' influence on mortality risk in a Ward were dependent on the specific social-environmental characteristics within that area. In line with earlier area level research, results support the aggregated interpretation that higher levels of farming activity within a Ward increase the risk of mortality within those Wards of NI. This was an essential study to enable future tailoring of new strategies and upgrading of current policies to bring about significant mortality risk change at local level.

Understanding Disparities in Receipt of Complex Gastrointestinal Cancer Surgery at a Small Geographic Scale.

OBJECTIVE: To define neighborhood-level disparities in the receipt of complex cancer surgery. BACKGROUND: Little is known about the geographic variation of receipt of surgery among patients with complex gastrointestinal (GI) cancers, especially at a small geographic scale. METHODS: This study included individuals diagnosed with 5 invasive, nonmetastatic, complex GI cancers (esophagus, stomach, pancreas, bile ducts, liver) from the Ohio Cancer Incidence Surveillance System during 2009 and 2018. To preserve patient privacy, we combined US census tracts into the smallest geographic areas that included a minimum number of surgery cases (n=11) using the Max-p-regions method and called these new areas "MaxTracts." Age-adjusted surgery rates were calculated for MaxTracts, and the Hot Spot analysis identified clusters of high and low surgery rates. US Census and CDC PLACES were used to compare neighborhood characteristics between the high- and low-surgery clusters. RESULTS: This study included 33,091 individuals with complex GI cancers located in 1006 MaxTracts throughout Ohio. The proportion in each MaxTract receiving surgery ranged from 20.7% to 92.3% with a median (interquartile range) of 48.9% (42.4-56.3). Low-surgery clusters were mostly in urban cores and the Appalachian region, whereas high-surgery clusters were mostly in suburbs. Low-surgery clusters differed from high-surgery clusters in several ways, including higher rates of poverty (23% vs. 12%), fewer married households (40% vs. 50%), and more tobacco use (25% vs. 19%; all P <0.01). CONCLUSIONS: This improved understanding of neighborhood-level variation in receipt of potentially curative surgery will guide future outreach and community-based interventions to reduce treatment disparities. Similar methods can be used to target other treatment phases and other cancers.

Census Tracts Are Not Neighborhoods: Addressing Spatial Misalignment in Studies Examining the Impact of Historical Redlining on Present-day Health Outcomes.

BACKGROUND: Research examining the effects of historical redlining on present-day health outcomes is often complicated by the misalignment of contemporary census boundaries with the neighborhood boundaries drawn by the US Home Owners' Loan Corporation (HOLC) in the 1930s. Previous studies have used different approaches to assign historical HOLC grades to contemporary geographies, but how well they capture redlining exposure is unknown. METHODS: Our analysis included 7711 residences identified in the Multiple Listing Service database in Atlanta, Georgia (2017-2022). We evaluated the classification of HOLC grade assignment (A, B, C, D, or ungraded) when assigning exposure under four area-level approaches (centroid, majority land area, weighted score, and highest HOLC) compared with using complete address data (gold standard). We additionally compared approaches across three 2020 census geographies (tract, block group, and block). RESULTS: When comparing the use of census tracts to complete address data, sensitivity was highest for the weighted score approach, which correctly identified 77% of residences in truly A-D graded neighborhoods as compared with the majority land area (44%), centroid (54%), and highest HOLC (59%) approaches. Regarding specificity, the majority land area approach best-classified residences in truly ungraded neighborhoods (93%) as compared with the weighted score (65%), centroid (81%), and highest HOLC (54%) approaches. Classification improved regardless of approach when using census block compared with the census tract. CONCLUSIONS: Misclassification of historical redlining exposure is inevitable when using contemporary census geographies rather than complete address data. This study provides a framework for assessing spatial misalignment and selecting an approach for classification.