Area-level Socioeconomic Status Research Articles

The association between diabetes mellitus of different durations and risk of pancreatic cancer: an Australian national data-linkage study in women

AimsThe bidirectional association between diabetes mellitus (DM) and pancreatic cancer (PC) is established; however, the strength of association between duration of DM and risk of PC needs further investigation. MethodsWe conducted a case-control study nested within a population-based cohort of Australian women established using record linkage. Women diagnosed with PC from July 2007 to December 2013, were matched to five controls based on age and state of residence. DM was defined according to prescription of anti-diabetic medication from administrative prescription data. We used conditional logistic regression to calculate odds ratios (OR) and 95% confidence intervals (CI), adjusted for area-level socioeconomic status, rurality of residence, weighted comorbidity score, and predicted probability of obesity. ResultsThe analyses included 7,267 cases and 35,978 controls. The mean age at the time of DM diagnosis was 71 years whereas the mean age at the time of diagnosis of PC was 76 years. A history of DM of any duration was associated with a 2-fold increase in risk of PC (OR=2.12; 95%CI:1.96–2.29) compared to having no history of DM. The risk decreased with increasing duration of DM. The highest risk was in those who had recent-onset DM (OR=8.08; 95%CI:6.88–9.50 for <12 months of DM), but the risk remained elevated with ≥5 years of DM (OR=1.40; 95%CI:1.27–1.55). ConclusionThe markedly increased risk of PC in those with recent-onset DM emphasises the need for further research to distinguish patients for whom new-onset DM is a manifestation of PC from those with type-2 DM. The elevated risk associated with long-standing DM suggests that preventing DM may contribute to a reduction in the incidence of PC.

Persistent racial and ethnic inequities in cancer-specific mortality of head and neck cancers by human papillomavirus infection.

148 Background: Overlapping racial and ethnic disparities exist in the prevalence of risk factors that drive the prognosis of head and neck cancers in the US, including the use of tobacco products, socioeconomic status and human papillomavirus (HPV) infection. Our objective was to describe inequities in cancer-specific survival among patients diagnosed with head and neck cancers by HPV status and racial/ethnic group. Methods: We conducted a retrospective cohort study using the Surveillance, Epidemiology and End Results Head and Neck with HPV Status Database. Patients diagnosed with first primary cancers of the hypopharynx, nasopharynx, oropharynx, pharyngeal tonsil, other pharyngeal, soft palate and tongue base between 2010 and 2016 were included, and information on clinical and demographic characteristics including tumor information, cancer-directed treatment, area-level socioeconomic status and HPV status were collected from population-based cancer registry data. Estimates of 5-year cancer-specific survival were calculated using the Kaplan-Meier method, and multivariable Cox proportional hazards models were used to estimate adjusted hazard ratios (HR) and 95% confidence intervals (CI) for racial/ethnic inequities in survival stratified by HPV status. Results: Among 15,393 patients diagnosed with head and neck cancer with documented HPV status, the median age was 59 years (interquartile range 53-66) and 10,457 (68%) were HPV+. Compared to patients diagnosed with HPV- head and neck cancers, a higher proportion of patients with HPV+ head and neck cancers were male (87% vs. 77%), diagnosed at stage IV (75% vs. 66%) and non-Hispanic White (84% vs. 68%%); and a lower proportion of HPV+ patients were non-Hispanic Black (6% vs. 13%) and uninsured or had Medicaid coverage (13% vs. 25%). Overall, 5-year cancer-specific survival was higher among HPV+ patients (82%) than among HPV- patients (62%), with a wider disparity observed among Black head and neck cancer patients (HPV+ 74%, HPV- 44%). In multivariable models, significant differences in cancer-specific survival were found across racial/ethnic groups and HPV status (P-interaction: 0.045). Compared to White patients, persistent inequities in cancer-specific survival were observed among Black HPV+ (HR 1.49, 95% CI 1.19-1.87) and HPV- (HR 1.42, 95% CI 1.21-1.66); and among Latinx HPV+ patients (HR 1.32, 95% CI 1.03-1.69). Conclusions: In this population-based study of patients with head and neck cancers, significant disparities in cancer-specific survival were observed that differed by both race/ethnicity and HPV status. The complex inequities in outcomes of head and cancers likely reflect the clinical impacts of socioeconomic and demographic risk factors in addition to HPV-related dysregulation of tumor metabolism and the immune microenvironment.

Effects of Artificial Light at Night on Body Mass Index and Islet Autoimmunity Development in Children in Bavaria, Germany

Background and Aim: Worldwide, incidence of childhood obesity and early-onset type 1 diabetes (T1D) has risen over the past decades. Epidemiological studies have shown that in addition to genetic predisposition, environmental factors such as air pollution and temperature are associated with body mass index (BMI), T1D and its presymptomatic stage of autoimmunity to pancreatic islet cells. This study aimed to investigate the effect of exposure to light at night (LAN) on standardized BMI and islet autoimmunity (having 2 or more islet autoantibodies) in children in Bavaria, Germany. Methods: Exposure to LAN at baseline was assigned to the residential addresses of 52,636 children (&amp;#x3c;6 years of age) participating in the Fr1da study from 2015 to 2019. Information on demographic characteristics was extracted from self-administered questionnaires. We investigated the association of LAN with standardized BMI using linear regression and with islet autoimmunity using generalized additive models, segmented regression and quartile analysis. All models were adjusted for sex, age, family history of diabetes and area-level socioeconomic status (SES). Results: The mean standardized BMI was 0.12 &amp;#xb1; 1.04 and 225 children showed islet autoimmunity. A 10 nW/cm2/sr increase in LAN was significantly associated with a 2.14% increase in standardized BMI (95% confidence interval (CI): 0.86-3.45). Also, LAN exposure was linearly associated with a significantly higher odds of islet autoimmunity in children with exposure levels up to 11 nW/cm2/sr (Odds ratio (OR): 1.98; 95% CI: 1.14-3.45). Similar, quartile analyses showed a greater risk of islet autoimmunity especially for the third quartile (Q3: 5.2-11.6 nW/cm2/sr) of LAN compared to the lowest quartile (Q1: 0.0-2.0 nW/cm2/sr; OR: 1.71; 95% CI: 1.19-2.47). Conclusion: Exposure to LAN might be a further environmental risk factor contributing to higher BMI and islet autoimmunity in children. Keywords: Light at night, light pollution, body mass index, islet autoimmunity

Effects of greenness, public parks, and blue space on neurodegenerative disease hospitalizations in the US Medicare cohort

Background and Aim: Exposure to natural environments has been associated with health outcomes that are related to neurological disorders. However, the few studies that examined associations of natural environments with neurological disorders reported mixed findings. Our goal was to evaluate associations of multiple features of natural environments with Alzheimer’s disease and related dementia’s (ADRD) and Parkinson’s disease (PD) hospital admissions. Methods: We created an open cohort including all fee-for-service Medicare beneficiaries aged 65+, who lived in the contiguous US January 1, 2000 through December 31, 2016 (~63 million individuals). Zip code level greenness (Normalized Difference Vegetation Index, NDVI), percent public park cover, and percent blue space cover (&amp;#x2265;1 % cover vs. &amp;#x3c;1% cover) were assessed. We examined associations of these exposures with first ADRD or PD hospitalizations based on primary or secondary discharge diagnosis, using a novel Cox-equivalent Poisson model. We also assessed if associations varied by demographics and area-level socioeconomic status. Results: We observed 7,910,111 and 1,196,981 first ADRD and PD hospitalizations, respectively. After adjustment for potential individual- and area-level confounders, NDVI was negatively associated with ADRD hospitalization (HR=0.95, 95%CI: 0.94-0.96, per IQR increase). Percent public park cover and blue space cover were not associated with ADRD hospitalization. For PD hospitalization, we observed negative associations of NDVI (HR=0.94, 95%CI: 0.93-0.95, per IQR), percent public park cover (HR=0.97, 95%CI: 0.97-0.98, per IQR), and blue space cover (HR=0.97, 95%CI: 0.96-0.98, &amp;#x2265;1% v. &amp;#x3c;1%). Patterns of effect modification by demographics differed between the exposures. For example, for PD hospitalization, negative associations of NDVI were strongest in the mid and high SES neighbourhoods, while negative associations of percent public park cover were strongest in the low SES neighbourhoods. Conclusions: Features of natural environments are associated with a decreased risk of ADRD and PD hospitalization in this cohort of US-based older adults.

Associations between green space, air pollution and birthweight in Sydney Metropolitan Area, Australia

Growing number of evidence have reported that exposure to air pollution was associated with unfavourable birth outcomes while increased exposure to green spaces was associated with better birth outcomes. However, the effect of interactions between air pollution and green spaces on pregnancy outcomes remain unclear. Using the data on all the live births recorded in Sydney between 2016 January and 2017 December, we built up multilevel linear and logistic regression models with random intercepts for statistical area level 2 (SA2) to examine the association between residential levels of air pollution (NO2, PM2.5, SO2 and O3) and pregnancy outcomes including birthweight, low birthweight, and preterm birth. This was followed by assessment of potential effect modification by green space quantity by fitting 2-way interaction term between each air pollutants and green space quantity separately. Furthermore, building on the 2-way interaction term, we explored 3-way interactions by adding area level socio-economic status and population density. Higher levels of PM2.5, NO2 and SO2 were statistically significantly associated with decrease in birthweights (p < 0.05) in the adjusted models. We observed statistically significantly association between the lower risks of preterm birth and higher levels of NO2 in the adjusted models (p < 0.05). However, none of the other air pollutants were statistically significantly associated with the odds of low birthweight and preterm birth. In the adjusted models, green space quantity was statistically significantly associated with reduced odds of preterm birth (p < 0.05). The results for birthweights were in the same direction (p < 0.05) however, some of these associations did not remain statistically significant after adjusting the models for air pollution. In general, no associations were found for low birthweight. Statistically significant 2-way interactions between green space quantity and NO2, PM2.5 and SO2 levels indicated that association between moderate levels of NO2, PM2.5 and birthweight weakened in the greener areas (>20 %) especially in the affluent and densely populated areas while the effect of SO2 did not differ consistently across green space levels with benefit of exposure to the greenest areas (>40 %) was evident, yet not statistically significant. Our findings suggest that increasing green spaces in cities may help supporting a healthy start in life by decreasing harms of moderate levels of air pollution. Replication in different contexts and consideration of potentially contrasting results with different types of green space is warranted.

Lifestyle factors as mediators of area-level socio-economic differentials in cardiovascular disease risk factors. The Tromsø Study

IntroductionCardiovascular disease (CVD) is a leading cause of death and disability and living in areas with low socio-economic status (SES) is associated with increased risk of CVD. Lifestyle factors such as smoking, physical inactivity, an unhealthy diet and harmful alcohol use are main risk factors that contribute to other modifiable risk factors, such as hypertension, raised blood cholesterol, obesity, and diabetes. The potential impact of area-level socio-economic status (ASES) on metabolic CVD risk factors via lifestyle behaviors independent of individual SES has not been investigated previously. AimsTo estimate associations of ASES with CVD risk factors and the mediating role of lifestyle behaviors independent of individual-level SES. MethodsIn this cross-sectional study, we included 19,415 participants (52% women) from the seventh survey of the Tromsø Study (2015–2016) (Tromsø7). The exposure variable ASES was created by aggregating individual-level SES variables (education, income, housing ownership) at the geographical subdivision level. Individual-level SES data and geographical subdivision of Tromsø municipality (36 areas) were obtained from Statistics Norway. Variables from questionnaires and clinical examinations obtained from Tromsø7 were used as mediators (smoking, snuff, alcohol, and physical activity), while the outcome variables were body mass index (BMI), total/high-density lipoprotein (HDL) cholesterol ratio, waist circumference, hypertension, diabetes. Mediation and mediated moderation analysis were performed with age as a moderator, stratified by sex. ResultsASES was significantly associated with all outcome variables. CVD risk factor level declined with an increase in ASES. These associations were mediated by differences in smoking habits, alcohol use and physical activity. The associations of ASES with total/HDL cholesterol ratio and waist circumference (women) were moderated by age, and the moderating effects were mediated by smoking and physical activity in both sexes. The largest mediated effects were seen in the associations of ASES with total/HDL cholesterol ratio, with the mediators accounting for 43% of the observed effects. ConclusionsLiving in lower SES areas is associated with increased CVD risk due to unhealthy lifestyle behaviors, such as smoking, alcohol use and physical inactivity. These associations were stronger in women and among older participants.

Socioeconomic deprivation and survival outcomes in primary central nervous system lymphomas

ObjectiveTo our knowledge, the impact of area-level socioeconomic status (SES) has not yet been described in primary central nervous system lymphomas (PCNSLs). Current study sought to explore the association of socioeconomic deprivation, measured using the Area Deprivation Index (ADI), with PCNSL outcomes.MethodsThe Surveillance, Epidemiology, and End Results (SEER) database was used to identify PCNSL patients diagnosed between 2006 and 2015 for our analyses. The impact of ADI on overall survival (OS) and cancer-specific survival (CSS) were investigated. Survival analyses were conducted using Kaplan-Meier method with log-rank tests. The Inverse Probability Weighting (IPW) analysis and multivariate cox proportional hazards regression analysis were employed to make covariate adjustments. Multiple mediation analysis (MMA) was performed to estimate the mediating effects.ResultsA total of 3159 PCNSL patients classified into low and high ADI subgroups according to the median ADI score were studied. The Kaplan-Meier analyses showed that low ADI was significantly associated with higher OS rates (HR 1.15, 95%CI 1.06-1.26, P<0.01) and CSS rates (HR 1.15, 95%CI 1.05-1.27, P<0.01). Similar results were observed in analyses adjusted via IPW and multivariate cox methods. Subgroup analyses revealed that ADI could remain a prognostic indictor among different subsets. MMA revealed that several factors including chemotherapy and HIV status making up about 40% of the overall effect, mediated PCNSL survival disparities related to the ADI. Finally, multivariable logistic regression analysis showed that ADI as well as several other factors were independently related to receipt of chemotherapy.ConclusionsOur study highlights the role of area-level SES in prognosis of PCNSLs. And several factors including chemotherapy and HIV status of PCNSL patents contributed to the CSS disparities between ADI subgroups were uncovered by MMA. Such relationships would highlight the importance of policies development to enhance healthcare delivery and promote awareness of HIV prevention and treatment in low-resource neighborhoods.

A Comparison of Area-Level Socioeconomic Status Indices in Colorectal Cancer Care

IntroductionThere are multiple measures of area socioeconomic status (SES) and there is little evidence on the comparative performance of these measures. We hypothesized adding area SES measures improves model ability to predict guideline concordant care and overall survival compared to models with standard clinical and demographic data alone. Materials and methodsWe included patients with colorectal cancer from 2006 to 2015 from the North Carolina Cancer Registry merged with insurance claims data. The primary area SES study variables were the Social Deprivation Index, Distressed Communities Index, Area Deprivation Index, and Social Vulnerability Index. We used multivariable logistic modeling and Cox proportional hazards modeling to assess the adjusted association of each indicator, with guideline concordant care and overall survival, respectively. Model performance of the SES measures was compared to a base model using likelihood ratio testing and area under the curve (AUC) assessments to compare SES indicator models with each other. ResultsWe found that the Area Deprivation Index, Social Vulnerability Index and Social Deprivation Index, but not Distressed Communities Index, were significantly associated with receiving guideline concordant care and significantly improved model fit over the base model on likelihood ratio testing. All models had similar AUCs. With respect to overall survival, we found that all indices were independently and significantly associated with survival and had significantly improved model fit over the base model on likelihood ratio testing. AUC analysis again showed all area SES measures had comparable performance for overall survival at 5 y. ConclusionsThis analysis demonstrates the importance of including these measures in risk adjustment models. However, of the commonly available measures, no one measure stood out as superior to others.

Completeness and representativeness of small area socioeconomic data linked with the UK Clinical Practice Research Datalink (CPRD)

BackgroundThe Clinical Practice Research Datalink (CPRD) holds primary care electronic healthcare records for 25% of the UK population. CPRD data can be linked via practice postcode in the UK, and...

Potential Determinants of Cardio-Metabolic Risk among Aboriginal and Torres Strait Islander Children and Adolescents: A Systematic Review.

Prevention initiatives during childhood and adolescence have great potential to address the health inequities experienced by Aboriginal and Torres Strait Islander (Indigenous) populations in Australia by targeting modifiable risk factors for cardio-metabolic diseases. We aimed to synthesize existing evidence about potential determinants of cardio-metabolic risk markers—obesity, elevated blood pressure, elevated blood glucose, abnormal lipids, or a clustering of these factors known as the metabolic syndrome (MetS)—for Indigenous children and adolescents. We systematically searched six databases for journal articles and three websites for relevant grey literature. Included articles (n = 47) reported associations between exposures (or interventions) and one or more of the risk markers among Indigenous participants aged 0–24 years. Data from 18 distinct studies about 41 exposure–outcome associations were synthesized (by outcome: obesity [n = 18]; blood pressure [n = 9]; glucose, insulin or diabetes [n = 4]; lipids [n = 5]; and MetS [n = 5]). Obesity was associated with each of the other cardio-metabolic risk markers. Larger birth size and higher area-level socioeconomic status were associated with obesity; the latter is opposite to what is observed in the non-Indigenous population. There were major gaps in the evidence for other risk markers, as well as by age group, geography, and exposure type. Screening for risk markers among those with obesity and culturally appropriate obesity prevention initiatives could reduce the burden of cardio-metabolic disease.

Drivers of racial, regional, and socioeconomic disparities in late-stage breast cancer mortality.

The authors identified tumor, treatment, and patient characteristics that may contribute to differences in breast cancer (BC) mortality by race, rurality, and area-level socioeconomic status (SES) among women diagnosed with stage IIIB-IV BC in Georgia. Using the Georgia Cancer Registry, 3084 patients with stage IIIB-IV primary BC (2013-2017) were identified. Cox proportional hazards regression was used to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs) comparing mortality among non-Hispanic Black (NHB) versus non-Hispanic White (NHW), residents of rural versus urban neighborhoods, and residents of low- versus high-SES neighborhoods by tumor, treatment, and patient characteristics. The mediating effects of specific characteristics on the association between race and BC mortality were estimated. Among the study population, 41% were NHB, 21% resided in rural counties, and 72% resided in low SES neighborhoods. The authors observed mortality disparities by race (HR, 1.27; 95% CI, 1.13, 1.41) and rurality (HR, 1.14; 95% CI, 1.00, 1.30), but not by SES (HR, 1.04; 95% CI, 0.91, 1.19). In the stratified analyses, racial disparities were the most pronounced among women with HER2 overexpressing tumors (HR, 2.30; 95% CI, 1.53, 3.45). Residing in a rural county was associated with increased mortality among uninsured women (HR, 2.25; 95% CI, 1.31, 3.86), and the most pronounced SES disparities were among younger women (<40 years: HR, 1.46; 95% CI, 0.88, 2.42). There is considerable variation in racial, regional, and socioeconomic disparities in late-stage BC mortality by tumor, treatment, and patient characteristics.

Supportive care needs and psychosocial outcomes of rural versus urban women with breast cancer.

To identify whether supportive care needs vary according to remoteness and area-level socio-economic status and to identify the combinations of socio-demographic, area-level and health factors that are associated with poorer quality of life, psychological distress and severity of unmet supportive care needs. Cross sectional data was collected from women with a breast cancer diagnosis (n=2635) in Queensland, Australia, through a telephone survey including socio-demographic, health, psychosocial and supportive care needs measures. Hierarchical regression and cluster analyses were applied to assess the predictors of unmet need and psychosocial outcomes and to identify socio-demographic and health status profiles of women, comparing their level of unmet needs and psychosocial outcomes. Women living in outer regional areas reported the highest severity of unmet need in the patient care domain. Greater unmet need for health systems and information and patient care was also evident for those in moderately and most disadvantaged areas. Three clusters were identified reflecting (1) older women with poorer health and lower education (19%); (2) younger educated women with better health and private insurance (61%); and (3) physically active women with localised cancer who had completed treatment (20%). Poorer outcomes were evident in the first two of these clusters. This better understanding of the combinations of characteristics associated with poorer psychosocial outcomes and higher unmet need can be used to identify women with higher supportive care needs early and to target interventions.

Health Disparity Resulting from the Effect of Built Environment on Temperature-Related Mortality in a Subtropical Urban Setting.

Whereas previous studies have assessed the overall health impact of temperature in Hong Kong, the aim of this study was to investigate whether the health impact is modified by local temperature of small geographic units, which may be related to the diverse socioeconomic characteristics of these units. The effects of local temperature on non-accidental and cause-specific mortality were analyzed using Bayesian spatial models at a small-area level, adjusting for potential confounders, i.e., area-level air pollutants, socioeconomic status, and green space, as well as spatial dependency. We found that a 10% increase in green space density was associated with an estimated 4.80% decrease in non-accidental mortality risk and a 5.75% decrease in cardiovascular disease mortality risk in Hong Kong, whereas variation in local annual temperature did not significantly contribute to mortality. We also found that the spatial variation of mortality within this city could be explained by the geographic distribution of green space and socioeconomic factors rather than local temperature or air pollution. The findings and methodology of this study may help to further understanding and investigation of social and structural determinants of health disparities, particularly place-based built environment across class-based small geographic units in a city, taking into account the intersection of multiple factors from individual to population levels.

Overall lifestyles and socioeconomic inequity in mortality and life expectancy in China: the China health and nutrition survey

socioeconomic inequity in mortality and life expectancy remains inconclusive in low- and middle-income countries, and to what extent the associations are mediated or modified by lifestyles remains debatable. we included 21,133 adults from China Health and Nutrition Survey (1991-2011) and constructed three parameters to reflect participants' overall individual- (synthesising income, education and occupation) and area-level (urbanisation index) socioeconomic status (SES) and lifestyles (counting the number of smoking, physical inactivity and unhealthy diet and bodyweight). HRs for mortality and life expectancy were estimated by time-dependent Cox model and life table method, respectively. during a median follow-up of 15.2years, 1,352 deaths were recorded. HRs (95% CIs) for mortality comparing low versus high individual- and area-level SES were 2.38 (1.75-3.24) and 1.84 (1.51-2.24), respectively, corresponding to 5.7 (2.7-8.6) and 5.0 (3.6-6.3) life-year lost at age 50. Lifestyles explained ≤11.5% of socioeconomic disparity in mortality. Higher lifestyle risk scores were associated with higher mortality across all socioeconomic groups. HR (95% CI) for mortality comparing adults with low individual-level SES and 3-4 lifestyle risk factors versus those with high SES and 0-1 lifestyle risk factors was 7.06 (3.47-14.36), corresponding to 19.1 (2.6-35.7) life-year lost at age 50. this is the first nationwide cohort study reporting that disadvantaged SES was associated with higher mortality and shorter life expectancy in China, which was slightly mediated by lifestyles. Risk lifestyles were related to higher mortality across all socioeconomic groups, and those with risk lifestyles and disadvantaged SES had much higher mortality risks.

Investigating service delivery and perinatal outcomes during the low prevalence first year of COVID-19 in a multiethnic Australian population: a cohort study

ObjectiveInvestigate the impact of the COVID-19 pandemic on perinatal outcomes in an Australian high migrant and low COVID-19 prevalent population to identify if COVID-19 driven health service changes and societal...

Association of area-level socioeconomic status and non-small cell lung cancer stage by race/ethnicity and health care-level factors: Analysis of the National Cancer Database.

This study examined whether the association of socioeconomic status (SES) and non-small cell lung cancer (NSCLC) stage varied by race/ethnicity and health care access measures. This study used data from the 2004-2016 National Cancer Database for patients aged 18-89 years who had been diagnosed with Stage 0-IV NSCLC. Adjusted odds ratios (aORs) with 95% confidence intervals (CIs) were calculated for the associations of area-level SES with an advanced stage at diagnosis via multilevel, multivariable logistic regression. The stage at diagnosis was dichotomized into early (0-II) and advanced (III-IV) stages, and area-level SES was categorized on the basis of the patient's zip code level: (1) the proportion of adults aged ≥25 years without a high school degree and (2) the median household income. The models were stratified by race/ethnicity (non-Hispanic [NH] White, NH Black, Hispanic, Asian, American Indian/Alaskan Native, and Native Hawaiian/Pacific Islander), insurance status (none, government, and private), and health care facility type (community, comprehensive community, academic/research, and integrated network). The study population included 1,329,972 patients. Although only 17% of the NH White patients were in the lowest income quartile, 50% of the NH Black patients were in this group. Lower area-level education and income were associated with higher odds of an advanced-stage diagnosis (aOR for education, 1.12; 95% CI, 1.10-1.13; aOR for income, 1.13; 95% CI, 1.11-1.14). These associations persisted among NH White, NH Black, Hispanic, and Asian patients; among those with government and private insurance (but not the uninsured); and among those treated at each facility type. Area-level income and education are strongly associated with an advanced NSCLC diagnosis regardless of the facility type and among those with government and private insurance.

Abstract 3668: Socioeconomic disparities in healthcare utilization and overall survival among patients with cancer: Application of area-level socioeconomic status in a nationwide electronic health record-derived database

Abstract Introduction: While lower socioeconomic status (SES) is associated with worse cancer outcomes, most electronic health records (EHRs) lack documentation of SES. Here we apply an area-level SES measure to an EHR-derived database to evaluate representativeness according to SES. We then examine socioeconomic disparities in the timeliness of healthcare utilization (biomarker testing and systemic treatment) and overall survival (OS) in 3 common cancers. Methods: This retrospective study uses the nationwide Flatiron Health EHR-derived de-identified database of cancer patients who have clinical activity between January 2011-August 2021. Census block group data from the American Community Survey (2015-2019) was used to measure SES per the Yost Index (incorporating income, home values, rental costs, poverty, blue-collar employment, unemployment, and education information). SES quintiles were determined from the US population and then applied to patients based on their residential addresses. Our database included 2,067,644 cancer patients from community practices. Patients with advanced non-small-cell lung cancer (aNSCLC, n=51,596), metastatic breast cancer (mBC, n=18,268), and multiple myeloma (MM, n=8,246) were sampled and followed from advanced, metastatic, or initial diagnosis date, respectively. Differences were evaluated using Χ2 tests for categorical variables and log-rank tests for Kaplan-Meier survivor functions. Results: Compared to the US population, our database of cancer patients has a similar SES distribution (differences &amp;lt;3%), capturing cancer patients living in the most (Q1) and least affluent areas (Q5) of the country. Yet, among the 1.5% of cancer patients who participated in clinical trials, only 15.2% lived in the least affluent areas. aNSCLC and mBC patients living in the least affluent areas were less likely to receive biomarker testing within 30 days of index diagnosis than those in the most affluent areas (59.4% vs. 68.7%; 74.9% vs. 81.0%, both p&amp;lt;.01). Similar patterns were observed in receipt of systemic treatment within 60 days of index diagnosis (aNSCLC: 58.9% vs. 64.9%; mBC: 76.0% vs. 80.1%, both p&amp;lt;.01). No differences in healthcare utilization were observed among MM patients. Patients in the least affluent areas had lower median OS (months) than those in the most affluent areas (aNSCLC: 10.8 [95% CI: 10.4-11.3] vs. 12.2 [95% CI: 11.8-12.7]; mBC: 28.0 [95% CI: 26.6-29.5] vs. 34.5 [95% CI: 33.1-36.9], MM: 57.4 [95% CI: 53.5-61.5] vs. 67.5 [95% CI: 62.5-76.4]; all p&amp;lt;.01). Conclusion: Lower SES was associated with reduced clinical trial participation, less timely healthcare utilization, and worse OS. Making SES available in real-world data can support the development of inclusive clinical trials and inform interventions to reduce cancer care disparities. Citation Format: Jenny S. Guadamuz, Xiaoliang Wang, Jeremy Snider, James Walters, Rebecca A. Miksad, Gregory S. Calip. Socioeconomic disparities in healthcare utilization and overall survival among patients with cancer: Application of area-level socioeconomic status in a nationwide electronic health record-derived database [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3668.

PM2.5 air pollution exposure and nonalcoholic fatty liver disease in the Nationwide Inpatient Sample

BackgroundNonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease. Particulate matter air pollution <2.5 μm in diameter (PM2.5) is a ubiquitous exposure primarily produced from fossil fuel combustion. Previous epidemiologic studies have been mixed. The objective of this study was to examine the association between ambient PM2.5 exposure and NAFLD among hospitalized patients in the Nationwide Inpatient Sample (NIS). MethodsWe conducted a cross-sectional analysis of hospitalizations from 2001 to 2011 using the NIS, the largest nationally representative all-payer inpatient care administrative database in the United States. Average annual PM2.5 exposure was estimated by linking census tracts (based on NIS-provided hospital ZIP Codes) with a spatiotemporal exposure model. Clinical conditions were identified using hospital discharge diagnosis codes. Multivariable logistic regression incorporating discharge weights was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between PM2.5 exposure and odds of NAFLD among hospitalized patients adjusting for age, sex, race/ethnicity, year, individual- and area-level socioeconomic status, urbanicity, region, obesity, diabetes, metabolic syndrome, impaired fasting glucose, dyslipidemia, hypertension, obstructive sleep apnea, and smoking. ResultsThere were 269,705 hospitalized patients with NAFLD from 2001 to 2011 (total unweighted n = 45,433,392 hospitalizations). Higher ambient PM2.5 exposure was associated with increased odds of NAFLD among hospitalized patients (adjusted OR: 1.24 per 10 μg/m3 increase, 95% CI 1.15–1.33, p < 0.01). There were statistically significant interactions between PM2.5 exposure and age, race/ethnicity, diabetes, smoking, and region, with stronger positive associations among patients who were aged ≥45 years, non-Hispanic White or Asian/Pacific Islander, non-diabetics, non-smokers, or in the Midwest and West regions, respectively. ConclusionsIn this nationwide cross-sectional analysis of the NIS database, there was a positive association between ambient PM2.5 exposure and odds of NAFLD among hospitalized patients. Future research should examine the effects of long-term historical PM2.5 exposure and incident NAFLD cases.

Neighbourhood walkability and dietary attributes: effect modification by area-level socio-economic status.

Higher neighbourhood walkability would be expected to contribute to better health, but the relevant evidence is inconsistent. This may be because residents' dietary attributes, which vary with socio-economic status (SES) and influence their health, can be related to walkability. We examined associations of walkability with dietary attributes and potential effect modification by area-level SES. The exposure variable of this cross-sectional study was neighbourhood walkability, calculated using residential density, intersection density and destination density within 1-km street-network buffer around each participant's residence. The outcome variables were dietary patterns (Western, prudent and mixed) and total dietary energy intake, derived from a FFQ. Main and interaction effects with area-level SES were estimated using two-level linear regression models. Participants were from all states and territories in Australia. The analytical sample included 3590 participants (54 % women, age range 34 to 86). Walkability was not associated with dietary attributes in the whole sample. However, we found interaction effects of walkability and area-level SES on Western diet scores (P < 0·001) and total energy intake (P = 0·012). In low SES areas, higher walkability was associated with higher Western dietary patterns (P = 0·062) and higher total energy intake (P = 0·066). In high SES areas, higher walkability was associated with lower Western diet scores (P = 0·021) and lower total energy intake (P = 0·058). Higher walkability may not be necessarily conducive to better health in socio-economically disadvantaged areas. Public health initiatives to enhance neighbourhood walkability need to consider food environments and socio-economic contexts.

“Residential greenness and site-specific cancer: A registry based cohort of 144,427 participants with a 21-years of follow-up, Tel-Aviv district, Israel”

BackgroundFew longitudinal studies evaluated the beneficial associations between cumulative residential greenness and site-specific cancer. Our objective was to evaluate the associations between cumulative residential greenness exposure and site-specific cancer incidence (lung, bladder, breast, prostate, and skin cancer) within a registry-based cohort study. MethodsThis study was based on 144,427 participants who lived in the Tel Aviv district during 1995–2015. The residential greenness exposure was estimated for every participant, as the weighted mean residential greenness exposure, based on the mean Normalized Difference Vegetation Index (NDVI) in the residential area and the duration of the residence in this area. Cox regression models were used to evaluate the unadjusted and adjusted associations between exposure to greenness and cancer incidence during 1998–2015 (Hazard Ratios (HRs) and 95% Confidence Intervals (CIs)). Covariates included in adjusted models were selected based on prior knowledge and directed acyclic graphs. We imputed missing data and further sensitivity analyses were conducted. ResultsAfter adjustments, beneficial associations between exposure to greenness and cancer incidence were observed. An interquartile range (IQR) increase in NDVI was associated with a lower HRs for lung cancer (HRadj. = 0.75 95% CI: 0.66–0.85), bladder cancer (HRadj. = 0.71, 95% CI: 0.62–0.82), breast cancer (HRadj. = 0.81, 95% CI: 0.74–0.88), prostate cancer (HRadj. = 0.77, 95% CI: 0.70–0.86) and skin cancer (HRadj. = 0.78, 95% CI: 0.69–0.88). Generally, the patterns of associations were consistent between complete-case models and imputed models, when estimated for participants aged 16 years or 40 years and older at baseline, when stratified by area level socioeconomic status, when evaluated for non-movers participants and after further adjustment to social determinants of health. ConclusionResidential greenness may reduce the risk for lung, bladder, breast, prostate, and skin cancers. If our observations will be replicated, it may present a useful avenue for public-health intervention to reduce cancer burden.