Neighborhood Socioeconomic Factors Research Articles

Risk prediction of advanced colorectal neoplasia varies by race and neighbourhood socioeconomic status

ObjectiveNeighbourhood deprivation increases the risk of colorectal neoplasia and contributes to racial disparities observed in this disease. Developing race-specific advanced colorectal neoplasia (ACN) prediction models that include neighbourhood socioeconomic status...

Individual and Neighborhood Level Predictors of Children’s Exposure to Residential Greenspace

Inequities in urban greenspace have been identified, though patterns by race and socioeconomic status vary across US settings. We estimated the magnitude of the relationship between a broad mixture of neighborhood-level factors and residential greenspace using weighted quantile sum (WQS) regression, and compared predictive models of greenspace using only neighborhood-level, only individual-level, or multi-level predictors. Greenspace measures included the Normalized Difference Vegetation Index (NDVI), tree canopy, and proximity of the nearest park, for residential locations in Shelby County, Tennessee of children in the CANDLE cohort. Neighborhood measures include socioeconomic and education resources, as well as racial composition and racial residential segregation. In this sample of 1012 mother–child dyads, neighborhood factors were associated with higher NDVI and tree canopy (0.021 unit higher NDVI [95% CI: 0.014, 0.028] per quintile increase in WQS index); homeownership rate, proximity of and enrollment at early childhood education centers, and racial composition, were highly weighted in the WQS index. In models constrained in the opposite direction (0.028 unit lower NDVI [95% CI: − 0.036, − 0.020]), high school graduation rate and teacher experience were highly weighted. In prediction models, adding individual-level predictors to the suite of neighborhood characteristics did not meaningfully improve prediction accuracy for greenspace measures. Our findings highlight disparities in greenspace for families by neighborhood socioeconomic and early education factors, and by race, suggesting several neighborhood indicators for consideration both as potential confounders in studies of greenspace and pediatric health as well as in the development of policies and programs to improve equity in greenspace access.

A cohort study of patients hospitalised with SARS-CoV-2 infection in Ontario: patient characteristics and outcomes by wave.

Each wave of the COVID-19 pandemic exhibited a unique combination of epidemiological, social and structural characteristics. We explore similarities and differences in wave-over-wave characteristics of patients hospitalised with COVID-19. This was a population-based study in Ontario province, Canada. Patients hospitalised with SARS-CoV-2 between 26 February 2020 and 31 March 2022 were included. An admission was considered related to SARS-CoV-2 infection if the provincial inpatient or outpatient hospital databases contained the ICD-10 diagnostic codes U071/U072 or the Ontario Laboratories Information System indicated a positive SARS-CoV-2 test result (PCR or rapid antigen testing) during the admission or up to two weeks prior. The primary outcome was 90-day mortality (modified Poisson regression). Secondary outcomes were use of critical care during the admission (logistic regression) and total length-of-stay (linear regression with heteroskedastic-consistent standard-error estimators). All models were adjusted for demographic characteristics, neighbourhood socioeconomic factors and indicators of illness severity. There were 73,201 SARS-CoV-2-related admissions: 6127 (8%) during wave 1 (wild-type), 14,371 (20%) during wave 2 (wild-type), 16,653 (23%) during wave 3 (Alpha), 5678 (8%) during wave 4 (Delta) and 30,372 (42%) during wave 5 (Omicron). SARS-CoV-2 was the most responsible diagnosis for 70% of admissions during waves 1-2 and 42% in wave 5. The proportion of admitted patients who were long-term care residents was 18% (n = 1111) during wave 1, decreasing to 10% (n = 1468) in wave 2 and <5% in subsequent waves. During waves 1-3, 46% of all admitted patients resided in a neighbourhood assigned to the highest ethnic diversity quintile, which declined to 27% during waves 4-5. Compared to wave 1, 90-day mortality was similar during wave 2 (adjusted risk ratio [aRR]: 1.00 [95% CI: 0.95-1.04]), but lower during wave 3 (aRR: 0.89 [0.85-0.94]), wave 4 (aRR: 0.85 [0.79-0.91]) and wave 5 (aRR: 0.83 [0.80-0.88]). Improvements in survival over waves were observed among elderly patients (p-interaction <0.0001). Critical care admission was significantly less likely during wave 5 than previous waves (adjusted odds ratio: 0.50 [0.47-0.54]). The length of stay was a median of 8.5 (3.6-23.8) days during wave 1 and 5.3 (2.2-12.6) during wave 5. After adjustment, the mean length of stay was on average -10.4 (-11.1 to -9.8) days, i.e. shorter, in wave 5 vs wave 1. Throughout the pandemic, sociodemographic characteristics of patients hospitalised with SARS-CoV-2 changed over time, particularly in terms of ethnic diversity, but still disproportionately affected patients from more marginalised regions. Improved survival and reduced use of critical care during the Omicron wave are reassuring.

Exploring the Impact of Multimodal Access on Property and Land Economies in Shanghai’s Inner Ring Districts: Leveraging Advanced Spatial Analysis Techniques

This study explores the impact of accessibility on property pricing and land economies by advanced spatial analysis techniques, focusing on Shanghai as a representative metropolis. Despite the impact of metro systems on residential property values, which has been frequently assessed, a research gap exists in understanding this phenomenon in Asian, particularly Chinese, urban contexts. Addressing this gap is crucial for shaping effective urban land use policy and improving the land economy rationally in China and similar settings facing urban challenges. To assess the impact of metro station accessibility on property prices in Shanghai, with extensive rail transit, and to deeply explore the overall impact of land value varieties driven by metro on urban development, we conducted a comprehensive analysis, with discussion about future aspirations for land planning and management along with landscape and facility design, and measures to improve land economy. The procedures involved creating neighborhood centroids to represent accessibility and using the Euclidean distance analysis to determine the shortest paths to metro stations. Our evaluation incorporated a hedonic pricing model, considering variables like neighborhood characteristics, housing attributes, and socio-economic factors. Advanced spatial analysis encompassing Ordinary Least Squares (OLS) regression and XGBoost analysis were employed to explore spatial effects, and Geographically Weighted Regression (GWR) helped examine spatial patterns and address autocorrelation challenges. Results revealed a negative association between distance to metro station and property prices, indicating a non-linear and spatially clustered relationship and heterogeneous spatial pattern. We dissected the non-linear results in detail, which complemented the conclusion in existing research. This study provides valuable insights into the dynamic interplay between metro accessibility and housing market behaviors in a significant Asian urban context, offering targeted suggestions for urban planners and governors to decide on more reasonable land use planning and management strategies, along with landscape and infrastructure design, to promote not only the healthy growth of the real estate market but also the sustainable urban development in China and similar regions.

Association Between Neighborhood Socioeconomic Factors and Length of Stay After Surgery for Congenital Heart Disease.

Neighborhood socioeconomic status, as measured by area deprivation index (ADI) is associated with longer length of stay (LOS) after surgery for hypoplastic left heart syndrome. We tested the hypothesis that LOS is associated with ADI in a large cohort of congenital heart disease (CHD) surgical cases of varying severity and sought to determine which other components of the ADI accounted for any associations. Retrospective analysis of a curated dataset. The Brokamp ADI was determined using residential addresses. Overall, ADI and each of its six individual components were dichotomized, and LOS compared between groups above versus below the median for the entire cohort and after stratifying by surgical The Society of Thoracic Surgeons-European Association for Cardio-Thoracic Surgery (STAT) severity category. Single-center academic pediatric teaching hospital. CHD patients who underwent surgical repair/palliation between September 2007 and August 2022. None. A total of 2462 patients (52.7% male) were included. Median age was 254 (interquartile range [IQR] 95-1628) days and median LOS in the hospital was 8 (IQR 5-18) days. We failed to identify an association between Brokamp ADI, above versus below the median for the entire cohort, and LOS; nor in STAT categories 1-4. However, in STAT category 5 ( n = 129) those with ADI above the median (more deprived) had a significantly longer LOS (48 [20-88] vs. 36 [18-49] d, p = 0.034). Of the individual components of the ADI, only percent below poverty level and percent vacant houses were associated with LOS in STAT category 5. LOS after CHD surgery is associated with Brokamp ADI in STAT category 5 cases, we failed to identify an association in lower-risk cardiac operations.

Effect of neighborhood and individual-level socioeconomic factors on breast cancer screening adherence in a multi-ethnic study

BackgroundAlthough mammography can significantly reduce breast cancer mortality, many women do not receive their annual breast cancer screening. Differences in screening adherence exist by race/ethnicity, socioeconomic status (SES), and insurance status. However, more detailed investigations into the impact of neighborhood disadvantage and access to resources on screening adherence are lacking.MethodsWe comprehensively examined the effect of individual social, economic, and demographic factors (n = 34 variables), as well as neighborhood level SES (nSES) indicators (n = 10 variables) on breast cancer screening adherence across a multi-ethnic population (n = 472). In this cross-sectional study, participants were surveyed from 2017 to 2018. The data was analyzed using univariate regression and LASSO for variable reduction. Significant predictors were carried forward into final multivariable mixed-effect logistic regression models where odds ratios (OR), 95% confidence intervals and p-values were reported.ResultsNineteen percent of participants were non-adherent to breast screening guidelines. Race/ethnicity was not associated with adherence; however, increasing age (OR = 0.97, 95%CI = 0.95–0.99, p = 0.01), renting a home (OR = 0.53, 95%CI = 0.30–0.94, p = 0.04), food insecurity (OR 0.46, 95%CI = 0.22–0.94, p = 0.01), and overcrowding (OR = 0.58, 95% CI = 0.32–0.94, p = 0.01) were significantly associated with lower breast cancer screening adherence.ConclusionSocioeconomic indicators at the individual and neighborhood levels impact low breast cancer screening adherence and may help to inform future screening interventions.

Childhood Asthma Incidence, Early and Persistent Wheeze, and Neighborhood Socioeconomic Factors in the ECHO/CREW Consortium.

Childhood Asthma Incidence, Early and Persistent Wheeze, and Neighborhood Socioeconomic Factors in the ECHO/CREW Consortium.

Socioeconomic and Inflammatory Correlates of Plasma Cortisol Among Individuals with Sickle Cell Disease

Introduction: Cortisol plays a critical role in the biological link between stress and health outcomes. It is frequently investigated in the association between socioeconomic stress and morbidity, and the hypothesized biological mechanism by which socioeconomic stress and cortisol impact health is through chronically elevated systemic inflammation. This research is relevant to individuals with sickle cell disease (SCD) for several reasons. First, up to 40% of children and adolescents with SCD are impacted by neighborhood poverty. Furthermore, individuals with SCD are faced with significant disease-related morbidities, such as chronic and acute pain, renal injury, and cerebrovascular disease that are further complicated by elevated inflammatory markers. Finally, cortisol is heavily understudied in this population, with no research investigating socioeconomic or inflammatory correlates. The purpose of this study was to investigate plasma cortisol and its association with neighborhood-level socioeconomic factors (income and poverty) and immunomodulatory cytokines (IL-6, IL-10), among individuals with SCD. Method: Plasma from individuals with SCD within Children's Hospital of Philadelphia (CHOP) and University of Pennsylvania School of Medicine (Penn Medicine) BioBanks were identified. A cortisol radioimmunoassay was used to determine plasma cortisol levels. The Olink immune response panel was used to measure plasma levels of 92 proteins involved in inflammatory pathways. Home address collected from electronic health records was used to determine neighborhood census tract geoid, which was then used to collect data on median neighborhood income and percentage of families living in poverty from the 2020 American Census Survey. Bivariate and multivariate analyses were conducted across 4 subgroups in the total sample: pediatric patients, adult patients, SCA (HbSS/HbSß 0), and other SCD genotypes (HbSC/HbSß +). Control samples (healthy and sickle cell trait; n = 22) without neighborhood information were also available for comparison. Results: Fifty-four independent outpatient samples were identified after excluding duplicates and siblings. Twenty-seven samples were from children and adolescents receiving pediatric care at CHOP (Range age = .8 to 21; Mage= 13.6, SD = 5.3; 51.9% female, 74.1% SCA) and 27 samples were from adults receiving care at Penn Medicine (Range age = 19 to 56; Mage= 35.8, SD = 10.1; 51.9% female, 51.9% SCA). There were no significant differences in cortisol levels across each subgroup ( Mpeds= 16.6, SDpeds = 6.2; Madult= 13.4, SDadult = 6.9; MSCA= 15.1, SDSCA = 7.1; MSCD= 14.9, SDSCD = 6.3). Neighborhood income and poverty did not differ across pediatric and adult patients, and income did not differ across SCD types. However, neighborhood poverty was lower among patients with SCA ( M = 13.9; SD = 11.9) relative to other SCD genotypes ( M = 21.7; SD = 13.5; p = .041). Bivariate Spearman analyses found that neighborhood variables were not correlated with cortisol or cytokines in the total sample or subgroups. Yet, multivariate analyses controlling for sex and time of blood draw showed a positive main effect for patient age ( p = .019) and a significant age by poverty interaction ( p = .041) predicting cortisol among pediatric patients. Cortisol levels were higher with age, yet the association among poverty and cortisol was strongest in younger patients. Analyses also showed a sex*poverty interaction among pediatric patients that approached significance ( p = .081), such that poverty only predicted cortisol in male patients. There were no significant differences for immunomodulatory cytokines across each SCD subgroups; however, IL-6 and IL-10 were elevated in patients with SCA relative to healthy controls ( p IL6 = .021; p IL10 = .003). Bivariate Spearman correlations showed that cortisol was positively related to IL-6 (rho [ρ]= .38, p = .027) and IL-10 (ρ= .34, p = .048) among patients with SCA. There were no additional significant bivariate or multivariate effects. Conclusion: Neighborhood factors likely have downstream effects on the biological stress response and inflammation in SCD. Further research must be conducted to elucidate concurrent and prospective associations among neighborhood socioeconomic factors, stress-related cortisol response, and inflammatory outcomes when extending this work to investigate the impact of stress on SCD morbidity and mortality.

Gentrification, neighborhood socioeconomic factors and urban vegetation inequities: A study of greenspace and tree canopy increases in Montreal, Canada

This study investigates the relationship between increasing urban vegetation and census tract-level green inequities, as well as the role of social indicators in this relationship. We analyzed the augmentation of greenspace and tree canopy in Montreal, Canada, between 2011 and 2017, and its effect on green inequities based on material deprivation, the percentage of visible minorities, and gentrification status using Poisson spatial random effect models. Our analyses showed an increase in greenspace from 57.4% to 65.8% and tree canopy from 21.1% to 22.3% between 2011 and 2017. Census tracts (CTs) with higher levels of material deprivation or a higher percentage of visible minority population had less greenspace and tree canopy at baseline in 2011. Additionally, CTs that were not gentrified had less greenspace and tree canopy than ineligible for gentrification CTs. Furthermore, CTs with more visible minorities, higher levels of material deprivation, or those that did not gentrify had smaller increases in greenspace and tree canopy between 2011 and 2017. Among CTs with more visible minorities or higher levels of material deprivation, those with greater greenspace and tree canopy at baseline also experienced greater increases during the study time period. Conversely, among ineligible for gentrification CTs, those with less greenspace/tree canopy at baseline experienced greater increase in greenspace/tree canopy. Our analysis revealed that despite an increase in urban vegetation, inequities in urban vegetation persists. To reduce green inequities and promote social equity in this particular study area, urban planning policies should prioritize CTs with higher levels of material deprivation, more visible minorities, or those that did not gentrify, and focus on increasing urban vegetation.

The implications of socioeconomic factors on salivary bioscience methodological variables in a large pediatric multi-site study.

Salivary bioscience has found increased utilization within pediatric research, given the non-invasive nature of self-collecting saliva for measuring biological markers. With this growth in pediatric utility, more understanding is needed of how social-contextual factors, such as socioeconomic factors or status (SES), influence salivary bioscience in large multi-site studies. Socioeconomic factors have been shown to influence non-salivary analyte levels across childhood and adolescent development. However, less is understood about relationships between these socioeconomic factors and salivary collection methodological variables (e.g., time of saliva collection from waking, time of day of saliva collection, physical activity prior to saliva collection, and caffeine intake prior to saliva collection). Variability in salivary methodological variables between participants may impact the levels of analytes measured in a salivary sample, thus serving as a potential mechanism for non-random systematic biases in analytes. Our objective is to examine relationships between socioeconomic factors and salivary bioscience methodological variables within the Adolescent Brain Cognitive Development Study© cohort of children aged 9-10 years old (n = 10,567 participants with saliva samples). We observed significant associations between household socioeconomic factors (poverty status, education) and salivary collection methodological variables (time since waking, time of day of sampling, physical activity, and caffeine intake). Moreover, lower levels of household poverty and education were significantly associated with more sources of potential bias in salivary collection methodological variables (e.g., longer times since waking, collections later in the day, higher odds of caffeine consumption, and lower odds of physical activity). Consistent associations were not observed with neighborhood socioeconomic factors and salivary methodological variables. Previous literature demonstrates associations between collection methodological variables and measurements of salivary analyte levels, particularly with analytes that are more sensitive to circadian rhythms, pH levels, or rigorous physical activity. Our novel findings suggest that unintended distortions in measured salivary analyte values, potentially resulting from the non-random systematic biases in salivary methodology, need to be intentionally incorporated into analyses and interpretation of results. This is particularly salient for future studies interested in examining underlying mechanisms of childhood socioeconomic health inequities in future analyses.

Characteristics of Multiple Sclerosis and Demyelinating Disease in an Asian American Population (P9-3.009)

<h3>Objective:</h3> To explore the clinical presentation of MS and neuromyelitis optica spectrum disorder (NMOSD) in patients of Asian ancestry in the United States. <h3>Background:</h3> Race and ancestry influence the course of demyelinating conditions like Multiple Sclerosis (MS). Asian patients are underrepresented in clinical research in the United States. <h3>Design/Methods:</h3> Demographic, clinical and radiologic data were extracted from the medical record for adults with Asian self-identified race and diagnosis of demyelinating disease cared for at a single North American MS center between 2006/02/06 and 2022/06/09. Descriptive statistics were used to describe the cohort, then demographic and clinical factors were compared according to region of ancestry. <h3>Results:</h3> The cohort included 282 patients from 11 different countries; 73.1% were born in Asia. Most patients (94.7%) preferred English for medical communication, but fewer of East Asian ancestry did (p=0.0001). South Asian ancestry was associated with higher neighborhood household income (p=0.002) and Southeast Asian ancestry with smoking (p=0.08). Diagnoses included MS (76.2%) and NMOSD (13.8%). More patients with NMOSD than MS were of East Asian and Southeast Asian ancestry (p=0.004). For MS patients, levels of optic nerve and spinal cord involvement were similar across regions of ancestry. Most (83.7%) patients were currently on MS treatment (42.3% on antiCD20 therapies). MS Severity Scale (MSSS), while similar to the clinic average. was worse with Southeast Asian ancestry (p=0.006) and also worse with smoking, and lower neighborhood median household income or educational attainment. <h3>Conclusions:</h3> Patients of Asian ancestry are underrepresented in research in the United States. In this cohort, Asian patients with MS were actively treated and disease severity reflected the overall clinic. Both region of origin and neighborhood socioeconomic factors were associated with disease characteristics. Further research is needed to uncover genetic, socioeconomic, or environmental factors accounting for worse MSSS in Southeast Asian patients. <b>Disclosure:</b> Dr. Fan has nothing to disclose. Ms. Alexander has nothing to disclose. Mr. Poole has nothing to disclose. Ms. Wijangco has received research support from National Institutes of Health. Dr. Henson has received personal compensation for serving as an employee of Piedmont Healthcare. An immediate family member of Dr. Henson has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Tempus. Dr. Henson has received personal compensation in the range of $10,000-$49,999 for serving as an Expert Witness for various law firms. Ruth Dobson has nothing to disclose. Dr. Guo has received personal compensation in the range of $5,000-$9,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Genentech. Dr. Bove has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for Biogen. Dr. Bove has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Horizon. Dr. Bove has received personal compensation in the range of $5,000-$9,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Biogen. Dr. Bove has received personal compensation in the range of $5,000-$9,999 for serving on a Scientific Advisory or Data Safety Monitoring board for EMD Serono. Dr. Bove has received personal compensation in the range of $10,000-$49,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Genzyme Sanofi. Dr. Bove has received personal compensation in the range of $10,000-$49,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Novartis. Dr. Bove has received personal compensation in the range of $10,000-$49,999 for serving on a Scientific Advisory or Data Safety Monitoring board for TG Therapeutics. Dr. Bove has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Jansen. Dr. Bove has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Alexion. The institution of Dr. Bove has received research support from Biogen. The institution of Dr. Bove has received research support from Roche Genentech. The institution of Dr. Bove has received research support from Novartis.

Neighborhood Social Determinants of Health in Patients Seen in Neurology Movement Disorders Clinics.

Chronic health conditions are influenced by social determinants of health (SDH) including neighborhood-linked markers of affluence. We explored whether neighborhood socioeconomic factors differ in people with different types of clinical movement disorders (MDs). We conducted a retrospective study of patients seen in MD clinics at our center in 2021. Patient data were linked to the US National Neighborhood Data Archive linked to US census tract data. We evaluated variations in neighborhood socioeconomic factors across 8 different categories of MDs. Compared with the neighborhoods of patients with Parkinson disease, neighborhoods of patients with cerebellar ataxias, functional movement disorders, and Huntington disease were characterized by higher proportions of people earning less than 15,000 US dollars/year, people receiving public assistance, and people with less than a high school diploma. Neighborhood-linked SDH vary among different MDs. These findings have implications for public health interventions aimed at improving the care of people affected by MDs.

Neighborhood deprivation and childhood opportunity indices are associated with violent injury among children in Los Angeles County.

Previous research has demonstrated mixed relationships between individual neighborhood socioeconomic factors and incidences of violence, such as poverty level, population density, and income inequality. We used the Childhood Opportunity Index and Area Disadvantage Index to evaluate the relationship between neighborhood characteristics and the number of incidents of violence among children across the zip codes of Los Angeles (LA) County. We performed a retrospective cross-sectional study of children younger than 18 years from 2017 to 2019 who were entered in the LA County Trauma and Emergency Medicine Information System registry with violent mechanisms of injury, including gunshot, stabbing, or assault. Mechanisms classified as self-inflicted injuries were excluded from the study. The number of incidences of violent mechanism per 100,000 persons younger than 18 years for each zip code was calculated using population data from the US Census American Community Survey 5-Year estimates from 2019. The incidences of violence per capita younger than 18 years for each zip code was compared with the zip code Area Deprivation Index and Childhood Opportunity Index using logistic regression models. There were 6,791 trauma activations in LA County over the study period, 12.8% (n = 866) of which were due to violence. The mean prevalence of pediatric violent mechanism of injury per zip code was 4 cases per 100,000 persons younger than 18 years. Most injuries were the result of firearms (n = 345 [60.4%]) and occurred among Hispanic/Latino children (n = 362 [57.1%]). There were significantly greater rates of violent injury among children from highest disadvantage (odds ratio, 8.84) and lowest opportunity (odds ratio, 42.48) zip codes. Children living in high disadvantage or low opportunity zip codes had greater rates of violent injury. Further study of neighborhood factors is needed to develop targeted effective interventions to reduce violent injuries among children living in low opportunity areas. Prognostic and Epidemiological; Level IV.

Childhood Asthma Incidence, Early and Persistent Wheeze, and Neighborhood Socioeconomic Factors in the ECHO/CREW Consortium

Childhood Asthma Incidence, Early and Persistent Wheeze, and Neighborhood Socioeconomic Factors in the ECHO/CREW Consortium

Impact of Patient Demographics and Neighborhood Socioeconomic Variables on Clinical Trial Participation Patterns for Non-Hodgkin Lymphoma at a Major Academic Institution

Background: There have been tremendous advancements in Non-Hodgkin Lymphoma (NHL) therapies and outcomes in large part due to clinical trials. Prior studies have demonstrated that certain populations including the elderly, certain racial and/or ethnic minority groups, and women are underrepresented in cancer clinical trials. Better understanding of how social context impacts clinical trial enrollment will allow us to better design tailored interventions to address barriers to clinical trial participation. We performed a retrospective analysis of patients with NHL seen at MD Anderson Cancer Center (MDACC) to systematically investigate the association between clinical trial participation patterns and sociodemographic context measured by neighborhood socioeconomic factors based on place of residence. Examining our practice patterns may then inform strategies to enhance trial recruitment of underrepresented groups. Methods: We examined 3448 patients, age ≥18 years with a diagnosis of NHL seen at MDACC between January 2017 and December 2020. Using patient address, geolocation software and American Community Survey (2015 - 2020) and 2020 census data available through data.Census.gov we ascertained 35 neighborhood level socioeconomic status (nSES) variables corresponding to each census tract including the domains of educational attainment, neighborhood median income, poverty, crowding, race composition and home values. We performed descriptive analysis to understand the demographics of the total populations and those enrolled in clinical trials. We performed univariate analysis of clinical trial enrollment patterns by sex, race, age, histology type, insurance type and nSES variables using 2-sample t-test and Mann-Whitney tests (MHT). Using exhaustive variable selection based upon minimizing the Akaike Information Criteria, including 2-way interactions, we found the set of variables that generated an optimal generalized additive logistic regression model for incidence of participation in clinical trials. We repeated this procedure for the diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL) subgroups. We adjusted alpha 0.05/3=0.017 as the criteria for significance in these models to address multiple testing. Results: We excluded 130 patients with international patient addresses and 427 patients without complete address information. and found no significant difference in baseline characteristic or clinical trial enrollment between the 572 excluded patients and the study cohort of 2943 patients. The study population was 59% male, 74.6% Non-Hispanic white (NHW), 13.2% Hispanic, 6.1% black, 3.7% Asian; 29.5% had DLBCL, 22% FL, 13.2% mantle cell, 9% marginal zone, 8.3% T-cell, and 6.5% high grade B cell lymphoma. The most common insurance was managed care 47% and Medicare 45.7%; 2.5% of patients were self-pay, 1.2% had Medicaid, and 2.1% had other government insurance. There was a high overall clinical trial participation rate of 30.5% with 20.9% enrolled in therapeutic trials and participation differed by diagnosis (Table). In univariate analyses, lower participation rates were associated with lower nSES including: increasing % of populations living below poverty level, increasing % living in crowded households, increasing % above age 25 years with less than high school diploma, and decreasing median household income. Racial composition of census tract was not associated with differences in clinical trial participation. Participation did not differ by insurance type. In multivariable analysis, incidence of participation declined nonlinearly with age in the overall, FL, and DLBCL models. In the DLBCL subset Hispanic patients had lower odds of participation than Whites (odds ratio 0.34, p=0.0003). No nSES variable predicted clinical trial participation in these models. Conclusion: In a large academic cohort, age and diagnosis not race, gender, insurance type, or nSES were independent predictors of trial participation. One major limitation to the generalizability of these results is the select patient population seen at our institution are relatively well insured. Examination of multi-center datasets including community practices when underinsured patients received care and evaluation of interventions to influence access to clinical trials are needed. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Associations between the urban exposome and type 2 diabetes: Results from penalised regression by least absolute shrinkage and selection operator and random forest models

BackgroundType 2 diabetes (T2D) is thought to be influenced by environmental stressors such as air pollution and noise. Although environmental factors are interrelated, studies considering the exposome are lacking. We simultaneously assessed a variety of exposures in their association with prevalent T2D by applying penalised regression Least Absolute Shrinkage and Selection Operator (LASSO), Random Forest (RF), and Artificial Neural Networks (ANN) approaches. We contrasted the findings with single-exposure models including consistently associated risk factors reported by previous studies. MethodsBaseline data (n = 14,829) of the Occupational and Environmental Health Cohort study (AMIGO) were enriched with 85 exposome factors (air pollution, noise, built environment, neighbourhood socio-economic factors etc.) using the home addresses of participants. Questionnaires were used to identify participants with T2D (n = 676(4.6 %)). Models in all applied statistical approaches were adjusted for individual-level socio-demographic variables. ResultsLower average home values, higher share of non-Western immigrants and higher surface temperatures were related to higher risk of T2D in the multivariable models (LASSO, RF). Selected variables differed between the two multi-variable approaches, especially for weaker predictors. Some established risk factors (air pollutants) appeared in univariate analysis but were not among the most important factors in multivariable analysis. Other established factors (green space) did not appear in univariate, but appeared in multivariable analysis (RF). Average estimates of the prediction error (logLoss) from nested cross-validation showed that the LASSO outperformed both RF and ANN approaches. ConclusionsNeighbourhood socio-economic and socio-demographic characteristics and surface temperature were consistently associated with the risk of T2D. For other physical-chemical factors associations differed per analytical approach.

Childhood Asthma Incidence, Early and Persistent Wheeze, and Neighborhood Socioeconomic Factors in the ECHO/CREW Consortium

In the United States, Black and Hispanic children have higher rates of asthma and asthma-related morbidity compared with White children and disproportionately reside in communities with economic deprivation. To determine the extent to which neighborhood-level socioeconomic indicators explain racial and ethnic disparities in childhood wheezing and asthma. The study population comprised children in birth cohorts located throughout the United States that are part of the Children's Respiratory and Environmental Workgroup consortium. Cox proportional hazard models were used to estimate hazard ratios (HRs) of asthma incidence, and logistic regression was used to estimate odds ratios of early and persistent wheeze prevalence accounting for mother's education, parental asthma, smoking during pregnancy, child's race and ethnicity, sex, and region and decade of birth. Neighborhood-level socioeconomic indicators defined by US census tracts calculated as z scores for multiple tract-level variables relative to the US average linked to participants' birth record address and decade of birth. The parent or caregiver reported the child's race and ethnicity. Prevalence of early and persistent childhood wheeze and asthma incidence. Of 5809 children, 46% reported wheezing before age 2 years, and 26% reported persistent wheeze through age 11 years. Asthma prevalence by age 11 years varied by cohort, with an overall median prevalence of 25%. Black children (HR, 1.47; 95% CI, 1.26-1.73) and Hispanic children (HR, 1.29; 95% CI, 1.09-1.53) were at significantly increased risk for asthma incidence compared with White children, with onset occurring earlier in childhood. Children born in tracts with a greater proportion of low-income households, population density, and poverty had increased asthma incidence. Results for early and persistent wheeze were similar. In effect modification analysis, census variables did not significantly modify the association between race and ethnicity and risk for asthma incidence; Black and Hispanic children remained at higher risk for asthma compared with White children across census tracts socioeconomic levels. Adjusting for individual-level characteristics, we observed neighborhood socioeconomic disparities in childhood wheeze and asthma. Black and Hispanic children had more asthma in neighborhoods of all income levels. Neighborhood- and individual-level characteristics and their root causes should be considered as sources of respiratory health inequities.

Impacts of Neighborhood Characteristics and Surgical Treatment Disparities on Overall Mortality in Stage I Renal Cell Carcinoma Patients.

Racial/ethnic minority groups in the United States have high renal cell carcinoma (RCC) mortality rates. This study assessed surgical treatment disparities across racial/ethnic groups and impacts of neighborhood socioeconomic characteristics on surgical treatments and overall mortality. Stage I RCC patients diagnosed between 2004 and 2016 from National Cancer Database were included (n = 238,141). We assessed differences in associations between race/ethnicity and treatment patterns using logistic regression and between race/ethnicity and overall mortality using Cox regression with and without neighborhood characteristics in the regression models. When compared to non-Hispanic Whites (NHWs), American Indians/Alaska Natives and non-Hispanic Blacks (NHBs) were more likely not to receive surgical care and all racial/ethnic minority groups had significantly increased odds of undergoing radical rather than partial nephrectomy, even after adjusting for neighborhood characteristics. Including surgical treatment and neighborhood factors in the models slightly attenuated the association, but NHBs had a significantly increased risk of overall mortality. NHBs who underwent radical nephrectomy had an increased risk of mortality (HR 1.15, 95% CI: 1.08–1.23), but not for NHBs who underwent partial nephrectomy (HR 0.92, 95% CI: 0.84–1.02). Neighborhood factors were associated with surgical treatment patterns and overall mortality in both NHBs and NHWs. Neighborhood socioeconomic factors may only partly explain RCC disparities.

Renal Cell Carcinoma Surgical Treatment Disparities in American Indian/Alaska Natives and Hispanic Americans in Arizona.

American Indians/Alaska Natives (AI/AN) and Hispanic Americans (HA) have higher kidney cancer incidence and mortality rates compared to non-Hispanic Whites (NHW). Herein, we describe the disparity in renal cell carcinoma (RCC) surgical treatment for AI/AN and HA and the potential association with mortality in Arizona. A total of 5111 stage I RCC cases diagnosed between 2007 and 2016 from the Arizona Cancer Registry were included. Statistical analyses were performed to test the association of race/ethnicity with surgical treatment pattern and overall mortality, adjusting for patients’ demographic, healthcare access, and socioeconomic factors. AI/AN were diagnosed 6 years younger than NHW and were more likely to receive radical rather than partial nephrectomy (OR 1.49 95% CI: 1.07–2.07) compared to NHW. Mexican Americans had increased odds of not undergoing surgical treatment (OR 1.66, 95% CI: 1.08–2.53). Analysis showed that not undergoing surgical treatment and undergoing radical nephrectomy were statistically significantly associated with higher overall mortality (HR 1.82 95% CI: 1.21–2.76 and HR 1.59 95% CI: 1.30–1.95 respectively). Mexican Americans, particularly U.S.-born Mexican Americans, had an increased risk for overall mortality and RCC-specific mortality even after adjusting for neighborhood socioeconomic factors and surgical treatment patterns. Although statistically not significant after adjusting for neighborhood-level socioeconomic factors and surgical treatment patterns, AI/AN had an elevated risk of mortality.

Abstract PO-169: Impacts of neighborhood characteristics and surgical treatment disparities on overall mortality in stage I renal cell carcinoma patients

Abstract Background Racial/ethnic minority groups in the United States have high kidney cancer mortality rates. Disparities in treatments may contribute to higher mortality in racial/ethnic minority groups, but the relationship between treatment disparities and kidney cancer mortality is not well understood. In this study, we assessed if there are differences in surgical treatments across racial/ethnic groups and surgical treatments influence disparities in overall mortality. Methods Stage I renal cell carcinoma patients who were diagnosed between 2004 and 2016 from National Cancer Database were included. Logistic regression was performed to assess associations between race/ethnicity and treatment patterns adjusting for neighborhood socioeconomic (SES) and other factors. Cox regression analysis was performed to assess associations between race/ethnicity and overall mortality. Results A total of 238,141 patients were included in the analysis. Compared to non-Hispanic Whites, American Indians/Alaska Natives, and non-Hispanic Blacks (NHBs) were more likely not to receive surgical care even after adjusting for neighborhood SES (OR 1.85, 95% CI: 1.28-2.70 and OR 1.32 95% CI: 1.20-1.45 respectively). Although all racial/ethnic groups had significantly increased odds of undergoing radical nephrectomy rather than partial nephrectomy,. NHBs had the greatest odds of receiving radical rather than partial nephrectomy (OR 1.38, 95% CI: 1.33-1.44).. The associations were slightly attenuated after including healthcare access and neighborhood SESNHBs had an elevated risk of overall mortality, while Asian Americans and Hispanic Americans had reduced risk. Including surgical treatment, health access and neighborhood factors slightly attenuated the association for NHBs, but the associations between race/ethnicity and overall mortality remained significant. Analysis was performed stratifying samples based on surgical treatment to further assess effects of surgical treatment disparities on associations between race/ethnicity and overall mortality. NHBs who had surgical treatment had increased risk of mortality (HR 1.11, 95% CI:1.06-1.17).. Among patients who underwent nephrectomy, NHBs who underwent radical nephrectomy had increased risk of mortality (HR 1.15, 95% CI: 1.08-1.23), but not NHBs who underwent partial nephrectomy (HR 0.92, 95% CI:0.84-1.02). Conclusion Racial/ethnic minority patients were more likely not to receive surgical treatment. When they do, they are likely to have less optimal surgical treatment (radical rather than partial nephrectomy). Surgical treatment disparities account for high kidney cancer mortality in NHBs. Citation Format: Alejandro Cruz, Faith Dickerson, Kathryn R. Pulling, Kyle Garcia, Francine C. Gachupin, Chiu-Hsieh Hsu, Juan Chipollini, Benjamin R. Lee, Ken Batai. Impacts of neighborhood characteristics and surgical treatment disparities on overall mortality in stage I renal cell carcinoma patients [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-169.