The association between neighborhood socioeconomic status and clinical outcomes among patients 1 year after hospitalization for cardiovascular disease

Latino Enclaves and Healthcare Accessibility: An Ecologic Study Across Five States

BACKGROUND

Hispanic or Latino populations (hereafter, "Latinos") are a rapidly expanding U.S. demographic and have documented inequities in preventable diseases and conditions. Many Latinos reside in ethnic enclaves, and understanding the context and healthcare accessibility within these places is critical.

OBJECTIVE

This study described the neighborhood social and built environment attributes of Latino enclaves and evaluated associations between enclaves and geographic healthcare accessibility.

DESIGN

Cross-sectional ecologic analysis.

SUBJECTS

Our unit of analysis was all neighborhoods (n ~ 20,000 census tracts) in California, Florida, New Jersey, New York, and Texas in years 2000 and 2010.

MAIN MEASURES

The primary exposure of interest, "Latino enclaves," was defined using neighborhood-level data on the percentage of Latino residents, foreign-born Latinos, Spanish speakers with limited English proficiency, and linguistically isolated Spanish-speaking households. The primary outcome was a neighborhood-level measure of geographic healthcare accessibility of primary care physicians, which accounted for both the supply of physicians and population demand for healthcare (i.e., population size within driving distance).

RESULTS

Approximately 30% of neighborhoods were classified as Latino enclaves, 87% of which were enclaves in both 2000 and 2010. Compared with non-enclaves, Latino enclaves had more markers of structural disadvantage including having higher proportions of poverty, uninsured individuals, crowded housing, and higher crime scores. Results from multivariable models suggest that more culturally distinct neighborhoods (i.e., higher enclave score) had lower healthcare accessibility, though when stratified, this association persisted only in high (≥ 20%) poverty neighborhoods.

CONCLUSION

This study highlights several neighborhood structural disadvantages within Latino enclaves, including higher poverty, uninsured individuals, and crime compared to non-enclave neighborhoods. Moreover, our findings point to the need for interventions aimed at improving healthcare accessibility particularly within socioeconomically disadvantaged Latino enclaves. Addressing these inequities demands multifaceted approaches that consider both social and structural factors to ensure equitable healthcare access for Latino populations.

Cardio and cerebrovascular diseases risk among Alzheimer's disease patients and racial/ethnic disparities, based on Hawaii Medicare data

Background

Alzheimer's disease (AD) and cardiovascular and cerebrovascular diseases (CVD) are significant concerns among the elderly, sharing overlapping risk factors. Hawaii's unique demographic profile, characterized by its strong ethnic diversity, shows marked racial health disparities. For instance, the Native Hawaiian/Pacific Islander (NHPI) population is identified as a high-risk group for multiple health conditions, including CVD.

Objective

This study investigates the impact of AD on the risk of developing CVD, with a focus on racial influences, utilizing Hawaii Medicare data.

Methods

Employing nine years of longitudinal Hawaii Medicare data, this study identified elderly patients diagnosed with AD who subsequently developed heart failure (HF), ischemic heart disease (IHD), atrial fibrillation (AF), acute myocardial infarction (AMI), or stroke. To assess the risk of CVD, we utilized multistate models and employed propensity score-matched controls. Additionally, we evaluated racial and ethnic differences in the risk of these diseases, while accounting for other relevant risk factors.

Results

Our findings revealed an elevated risk of AMI, HF, and IHD among individuals diagnosed with AD. Additionally, socioeconomic status (SE) was identified as a crucial factor in the risk of cardio and cerebrovascular diseases. Within the low SE group, NHPIs exhibited increased risks of HF and IHD compared to their white counterparts. Interestingly, NHPIs demonstrated reduced risks of HF in the higher SE group.

Conclusions

The presence of AD increases the likelihood of developing AMI, HF, and IHD. Moreover, the risk of CVD appears to be influenced by race/ethnicity in Hawaii, as well as socioeconomic status.

Race-ethnicity and sex differences in 1-year survival following percutaneous coronary intervention among Medicare fee-for-service beneficiaries

RATIONALE

Existing literature describing differences in survival following percutaneous coronary intervention (PCI) by patient sex, race-ethnicity and the role of socioeconomic characteristics (SEC) is limited.

AIMS AND OBJECTIVES

Evaluate differences in 1-year survival after PCI by sex and race-ethnicity, and explore the contribution of SEC to observed differences.

METHODS

Using a 20% sample of Medicare claims data for beneficiaries aged 65+, we identified fee-for-service patients who received PCI from 2007 to 2015. We performed logistic regression to assess how sex and race-ethnicity relate to procedural indication, inpatient versus outpatient setting, and 1-year mortality. We evaluated whether these relationships are moderated by sequentially controlling for factors including age, comorbidities, presence of acute myocardial infarction (AMI), county SEC, medical resource availability and inpatient versus outpatient procedural status.

RESULTS

We identified 300,491 PCI procedures, of which 94,863 (31.6%) were outpatient. There was a significant transition to outpatient PCI during the study period, especially for men compared with women and White patients compared with Black patients. Black patients were 3.50 percentage points (p < 0.001) and women were 3.41 percentage points (p < 0.001) more likely than White and male patients to undergo PCI at the time of AMI, which typically occurs in the inpatient setting. Controlling for age and calendar year, Black patients were 2.87 percentage points more likely than non-Hispanic White patients to die within 1 year after PCI. After controlling for Black-White differences in comorbidities, the differences in 1-year mortality decreased to 0.95 percentage points, which then became nonsignificant when further controlling for county resources and state of residence.

CONCLUSION

Women were more likely to experience PCI in the setting of AMI and had less transition to outpatient care during the period. Black patients experienced higher 1-year mortality following PCI, which is explained by differences in baseline comorbidities, county medical resources, and state of residence.

Area Deprivation Index Predicts Mortality for Critically Ill Surgical Patients With Sepsis

Background: The impact of socioeconomic status on outcomes after sepsis has been challenging to define, and no polysocial metric has been shown to predict mortality in sepsis. The primary objective of this study was to evaluate the association between the Area Deprivation Index (ADI) and mortality in patients admitted to the surgical intensive care unit (SICU) with sepsis. Patients and Methods: All patients admitted to the SICU with sepsis (Sequential Organ Failure Assessment [SOFA] score ≥2) were retrospectively reviewed. The ADI scores were obtained and classified as "high ADI" (≥85th percentile, n = 400, representative of high socioeconomic deprivation) and "control ADI" (ADI <85th percentile, n = 976). Baseline demographic and clinical characteristics were compared between groups. The primary outcome was 90-day mortality. Results: High ADI patients were younger (mean age 58.5 vs. 60.8; p = 0.01) and more likely to be non-white (23.7% vs. 10.0%; p < 0.0005) and to present with chronic obstructive pulmonary disease (26.5% vs. 19.0%; p = 0.002). High ADI patients had increased in-hospital (27.3% vs. 21.6%; p = 0.025) and 90-day mortality (35.0% vs. 28.9%; p = 0.03). High ADI patients also had increased rates of renal failure (20.3% vs. 15.3%; p = 0.02). Both cohorts had similar intensive care unit (ICU) lengths of stay and median hospital stay, Charlson comorbidity index, and rate of discharge to home. High ADI is an independent risk factor for 90-day mortality after admission for surgical sepsis (odds ratio [OR], 1.39 ± 0.24; p = 0.014). Conclusions: High ADI is an independent predictor of 90-day mortality in patients with surgical sepsis. Targeted community interventions are needed to reduce sepsis mortality for these at-risk patients.

Improving Genetic Association Studies with a Novel Methodology that Unveils the Hidden Complexity of All-Cause Heart Failure

Motivation

Genome-Wide Association Studies (GWAS) commonly assume phenotypic and genetic homogeneity that is not present in complex conditions. We designed Transformative Regression Analysis of Combined Effects (TRACE), a GWAS methodology that better accounts for clinical phenotype heterogeneity and identifies gene-by-environment (GxE) interactions. We demonstrated with UK Biobank (UKB) data that TRACE increased the variance explained in All-Cause Heart Failure (AHF) via the discovery of novel single nucleotide polymorphism (SNP) and SNP-by-environment (i.e. GxE) interaction associations. First, we transformed 312 AHF-related ICD10 codes (including AHF) into continuous low-dimensional features (i.e., latent phenotypes) for a more nuanced disease representation. Then, we ran a standard GWAS on our latent phenotypes to discover main effects and identified GxE interactions with target encoding. Genes near associated SNPs subsequently underwent enrichment analysis to explore potential functional mechanisms underlying associations. Latent phenotypes were regressed against their SNP hits and the estimated latent phenotype values were used to measure the amount of AHF variance explained.

Results

Our method identified over 100 main GWAS effects that were consistent with prior studies and hundreds of novel gene-by-smoking interactions, which collectively accounted for approximately 10% of AHF variance. This represents an improvement over traditional GWAS whose results account for a negligible proportion of AHF variance. Enrichment analyses suggested that hundreds of miRNAs mediated the SNP effect on various AHF-related biological pathways. The TRACE framework can be applied to decode the genetics of other complex diseases.

Availability

All code is available at https://github.com/EpistasisLab/latent_phenotype_project.

Racial and Ethnic Disparities in Stroke Reperfusion Therapy in the USA

Racial and ethnic inequities in stroke care are ubiquitous. Acute reperfusion therapies, i.e., IV thrombolysis (IVT) and mechanical thrombectomy (MT), are central to acute stroke care and are highly efficacious at preventing death and disability after stroke. Disparities in the use of IVT and MT in the USA are pervasive and contribute to worse outcomes among racial and ethnic minority individuals with ischemic stroke. A meticulous understanding of disparities and underlying root causes is necessary in order to develop targeted mitigation strategies with lasting effects. This review details racial and ethnic disparities in the use of IVT and MT after stroke and highlights inequities in the underlying process measures as well as the contributing root causes. Furthermore, this review spotlights the systemic and structural inequities that contribute to race-based differences in the use of IVT and MT, including geographic and regional differences and differences based on neighborhood, zip code, and hospital type. In addition, recent promising trends suggesting improvements in racial and ethnic IVT and MT disparities and potential approaches for future solutions to achieve equity in stroke care are briefly discussed.

Lost in Follow-Up: Predictors of Patient No-Shows to Clinic Follow-Up After Abdominal Injury

BACKGROUND

The aim of this study is to evaluate risk factors for non-attendance to post-discharge, hospital follow-up appointments for traumatically injured patients who underwent exploratory laparotomy.

METHODS

This is a retrospective chart review of patients who underwent exploratory laparotomy for traumatic abdominal injury at an urban, Midwestern, level I trauma center with clinic follow-up scheduled after discharge. Clinically, relevant demographic characteristics, patients' distance from hospital, and the presence of staples, sutures, and drains requiring removal were collected. Descriptive statistics of categorical variables were calculated as totals and percentages and compared with a chi-squared test or Fisher's exact when appropriate.

RESULTS

The sample included 183 patients who were largely assaultive trauma survivors (68%), male (80%), and black (53%) with a mean age of 35.4 ± 14.9 years. Overall, 18.5% no-showed for their follow-up appointment. On multivariate analysis for clinic no-show; length of stay (odds ratio = 0.92 [0.84-0.99], P = 0.04) and the need for suture, staple, or drain removal were protective for clinic attendance (odds ratio = 5.59 [1.07-7.01], P = 0.04). Overall, 12 patients (6.4%) were readmitted. Forty patients (18.3%) had their follow-up in the emergency department (ED). On multivariate regression of risk factors for ED visits, the only statistically significant factors (P < 0.05) were clinic appointment no-show (OR = 2.81) and self-pay insurance (OR = 4.78).

CONCLUSIONS

Abdominal trauma patients are at high risk of no-show for follow-up appointments and no-show visits are associated with ED visits. Future work is needed evaluating interventions to improve follow-up.

Your neighborhood matters: A machine-learning approach to the geospatial and social determinants of health in 9-1-1 activated chest pain

Healthcare disparities in the initial management of patients with acute coronary syndrome (ACS) exist. Yet, the complexity of interactions between demographic, social, economic, and geospatial determinants of health hinders incorporating such predictors in existing risk stratification models. We sought to explore a machine-learning-based approach to study the complex interactions between the geospatial and social determinants of health to explain disparities in ACS likelihood in an urban community. This study identified consecutive patients transported by Pittsburgh emergency medical service for a chief complaint of chest pain or ACS-equivalent symptoms. We extracted demographics, clinical data, and location coordinates from electronic health records. Median income was based on US census data by zip code. A random forest (RF) classifier and a regularized logistic regression model were used to identify the most important predictors of ACS likelihood. Our final sample included 2400 patients (age 59 ± 17 years, 47% Females, 41% Blacks, 15.8% adjudicated ACS). In our RF model (area under the receiver operating characteristic curve of 0.71 ± 0.03) age, prior revascularization, income, distance from hospital, and residential neighborhood were the most important predictors of ACS likelihood. In regularized regression (akaike information criterion = 1843, bayesian information criterion = 1912, χ²  = 193, df = 10, p < 0.001), residential neighborhood remained a significant and independent predictor of ACS likelihood. Findings from our study suggest that residential neighborhood constitutes an upstream factor to explain the observed healthcare disparity in ACS risk prediction, independent from known demographic, social, and economic determinants of health, which can inform future work on ACS prevention, in-hospital care, and patient discharge.

Community factors and hospital wide readmission rates: Does context matter?

Background

The environment in which a patient lives influences their health outcomes. However, the degree to which community factors are associated with readmissions is uncertain.

Objective

To estimate the influence of community factors on the Centers for Medicare & Medicaid Services risk-standardized hospital-wide readmission measure (HWR)–a quality performance measure in the U.S.

Research design

We assessed 71 community variables in 6 domains related to health outcomes: clinical care; health behaviors; social and economic factors; the physical environment; demographics; and social capital.

Subjects

Medicare fee-for-service patients eligible for the HWR measure between July 2014-June 2015 (n = 6,790,723). Patients were linked to community variables using their 5-digit zip code of residence.

Methods

We used a random forest algorithm to rank variables for their importance in predicting HWR scores. Variables were entered into 6 domain-specific multivariable regression models in order of decreasing importance. Variables with P-values <0.10 were retained for a final model, after eliminating any that were collinear.

Results

Among 71 community variables, 19 were retained in the 6 domain models and in the final model. Domains which explained the most to least variance in HWR were: physical environment (R² = 15%); clinical care (R² = 12%); demographics (R² = 11%); social and economic environment (R² = 7%); health behaviors (R² = 9%); and social capital (R² = 8%). In the final model, the 19 variables explained more than a quarter of the variance in readmission rates (R² = 27%).

Conclusions

Readmissions for a wide range of clinical conditions are influenced by factors relating to the communities in which patients reside. These findings can be used to target efforts to keep patients out of the hospital.

Maternal cytomegalovirus immune status and hearing loss outcomes in congenital cytomegalovirus-infected offspring

Objectives

The purpose of this study is to determine the relationship between maternal primary and recurrent CMV infection during pregnancy, symptoms at birth in the newborn, and long term hearing loss through18 years of age.

Patients and methods

237 mother-infant pairs in the Houston, Texas area identified through maternal CMV IgG and IgM antibody serologic screening and newborn screening using urine CMV culture to identify congenital CMV infection were enrolled in the Houston Congenital CMV Longitudinal Study. Mothers were categorized as having primary or recurrent or unknown maternal CMV infections, and newborns were categorized at birth as having symptomatic or asymptomatic congenital CMV infection, or as uninfected controls. All three newborn groups were followed longitudinally with serial hearing evaluations up to 18 years of age. The relationship between type of maternal CMV infection, newborn classification, and the occurrence of hearing loss over time was determined through Kaplan-Meier survival analysis, life table analysis, and a simulated ascertainment of maternal infection type for the unknown categories.

Results

Of 77 newborns with symptomatic congenital CMV infection, 12 (16%) of mothers had a primary CMV infection during pregnancy; 4 (5%) had a non-primary infection, and the type of infection in 48 (79%) could not be determined and were classified as unknown type of maternal infection. Fifty Seven (74%) of the 77 symptomatic children had hearing loss by 18 years of age, including 9 of the 12 (75%) who were born to mothers with primary infection and 48 (79%) of the 61 with unknown type of maternal infection. Of the 109 newborns with asymptomatic congenital CMV infection, 51 (47%) were born to mothers with a primary CMV infection during pregnancy, 18 (17%) to mothers with a recurrent infection; and 40 (37%) had unknown type of infection. Of these 109 asymptomatic cases, 22 (20%) developed hearing loss, including 14 out of 51 (28%) of those born to mothers with primary infection, two out of the 18 (11%) born to mothers with recurrent infection, and 6 out of the 40 (15%) to mothers of unknown infection type. Of the 51 uninfected newborn controls, 10 (20%) of mothers had a primary CMV infection during pregnancy, 5 (10%) had a non-primary infection, 10 (20%) were never infected, and 26 (51%) were assigned unknown type of infection. Three controls (6%) developed hearing loss, with 1 being born to a mother with primary infection and 1 to a mother never infected with CMV.

Conclusions

Both primary and non-primary maternal CMV infections during pregnancy resulted in symptomatic and asymptomatic congenital CMV infection. Symptomatic congenital CMV infection was more likely to occur after primary maternal CMV infection. Sensorineural hearing loss occurred in children born to mothers with both primary and non-primary CMV infections, and in both asymptomatic and symptomatic congenital CMV infection, but was more common after maternal primary infection. Most, but not all, hearing loss in children with cCMV associated hearing loss was first detected within the first year of life.

Impact of Geographic Socioeconomic Disadvantage on Minor Amputation Outcomes in Patients With Diabetes

BACKGROUND

Socioeconomic disadvantage is a known contributor to adverse events and higher admission rates in the diabetic population. However, its impact on outcomes after lower extremity amputation is unclear. We aimed to assess the association of geographic socioeconomic disadvantage with short- and long-term outcomes after minor amputation in patients with diabetes.

MATERIALS AND METHODS

Geographic socioeconomic disadvantage was determined using the area deprivation index (ADI). All patients from the Maryland Health Services Cost Review Commission database (2012-2019) who underwent minor amputation with a concurrent diagnosis of diabetes were included and stratified by the ADI quartile. Associations of the ADI quartile with 30-day readmission and 1-year reamputation were evaluated using Kaplan-Meier survival analyses and multivariable logistic regression models adjusting for baseline differences.

RESULTS

A total of 7415 patients with diabetes underwent minor amputation (70.1% male, 38.7% black race), including 28.1% ADI1 (least deprived), 42.8% ADI2, 22.9% ADI3, and 6.2% ADI4 (most deprived). After adjusting for demographic and clinical factors, the odds of 30-day readmission were greater in the intermediate ADI groups than those in the ADI1 group, but not among the most deprived. Adjusted odds of 1-year reamputation were greater among ADI4 than those among ADI1. Kaplan-Meier analysis confirmed a greater likelihood of reamputation with an increasing ADI quartile over a 1-year period (P < 0.001).

CONCLUSIONS

Geographic socioeconomic disadvantage is independently associated with both short- and long-term outcomes after minor diabetic amputations in Maryland. A targeted approach addressing the health care needs of deprived regions may be beneficial in optimizing postoperative care in this vulnerable population.

Geocoding Error, Spatial Uncertainty, and Implications for Exposure Assessment and Environmental Epidemiology

Although environmental epidemiology studies often rely on geocoding procedures in the process of assigning spatial exposure estimates, geocoding methods are not commonly reported, nor are consequent errors in exposure assignment explored. Geocoding methods differ in accuracy, however, and, given the increasing refinement of available exposure models for air pollution and other exposures, geocoding error may account for an increasingly larger proportion of exposure misclassification. We used residential addresses from a reasonably large, dense dataset of asthma emergency department visits from all New York City hospitals (n = 21,183; 26.9 addresses/km²), and geocoded each using three methods (Address Point, Street Segment, Parcel Centroid). We compared missingness and spatial patterning therein, quantified distance and directional errors, and quantified impacts on pollution exposure estimates and assignment to Census areas for sociodemographic characterization. Parcel Centroids had the highest overall missingness rate (38.1%, Address Point = 9.6%, Street Segment = 6.1%), and spatial clustering in missingness was significant for all methods, though its spatial patterns differed. Street Segment geocodes had the largest mean distance error (µ = 29.2 (SD = 26.2) m; vs. µ = 15.9 (SD = 17.7) m for Parcel Centroids), and the strongest spatial patterns therein. We found substantial over- and under-estimation of pollution exposures, with greater error for higher pollutant concentrations, but minimal impact on Census area assignment. Finally, we developed surfaces of spatial patterns in errors in order to identify locations in the study area where exposures may be over-/under-estimated. Our observations provide insights towards refining geocoding methods for epidemiology, and suggest methods for quantifying and interpreting geocoding error with respect to exposure misclassification, towards understanding potential impacts on health effect estimates.

Community economic factors influence outcomes for patients with primary malignant glioma

Background

Community economics and other social health determinants influence outcomes in oncologic patient populations. We sought to explore their impact on presentation, treatment, and survival in glioma patients.

Methods

A retrospective cohort of patients with glioma (World Health Organization grades III-IV) diagnosed between 1999 and 2017 was assembled with data abstracted from medical record review. Patient factors included race, primary care provider (PCP) identified, marital status, insurance status, and employment status. Median household income based on zip code was used to classify patients as residing in high-income communities (HICs; ie, above the median state income) or low-income communities (LICs; ie, below the median state income). The Kaplan-Meier method was used to assess overall survival (OS); Cox proportional hazards regression was used to explore associations with OS.

Results

Included were 312 patients, 73% from LICs. Survivors residing in LICs and HICs did not differ by age, sex, race, tumor grade, having a PCP, employment status, insurance, time to presentation, or baseline performance status. Median OS was 4.1 months shorter for LIC patients (19.7 vs 15.6 mo; hazard ratio [HR], 0.75; 95% CI: 0.56-0.98, P = 0.04); this difference persisted with 1-year survival of 66% for HICs versus 61% for LICs at 1 year, 34% versus 24% at 3 years, and 29% versus 17% at 5 years. Multivariable analysis controlling for age, grade, and chemotherapy treatment showed a 25% lower risk of death for HIC patients (HR, 0.75; 95% CI: 0.57-0.99, P < 0.05).

Conclusions

The economic status of a glioma patient's community may influence survival. Future efforts should investigate potential mechanisms such as health care access, stress, treatment adherence, and social support.

Outcomes in Bilateral Vocal Fold Immobility: A Retrospective Cohort Analysis

OBJECTIVE

To test the hypothesis that the etiologies of bilateral vocal fold mobility impairment (BLVFI), bilateral vocal fold paralysis (BVFP), and posterior glottis stenosis (PGS) have distinct clinical outcomes. To identify patient-specific and procedural factors that influence tracheostomy-free survival.

STUDY DESIGN

Retrospective cohort study.

SETTING

Johns Hopkins Medical Center from 2004 to 2015.

SUBJECTS AND METHODS

Case series with chart review of 68 patients with PGS and 17 patients with BVFP. Multiple logistic regression analysis determined factors associated with airway prosthesis dependence at last follow-up and the procedural burden (defined as number of operative procedures per year).

RESULTS

PGS comprised the majority of BLVFI (76%). PGS injury arose primarily after endotracheal intubation (91%), while BVFP most commonly was due to iatrogenic surgical injury to bilateral recurrent laryngeal nerves (88%, P < .001). Overall in BLVFI, 66% were tracheostomy free at last follow-up (62% in PGS, 82% in BVFP). Of those who underwent an operative intervention to be decannulated, 88% were decannulated (90% PGS, 80% BVFP). Patients with PGS required higher procedural burden to achieve decannulation compared with the BVFP cohort (3.1 ± 5.2 vs 0.71 ± 1.4, P = .002). In multivariate analysis of PGS, smoking was a risk factor for tracheostomy dependence (P = .026).

CONCLUSIONS

BLVFI is primarily an iatrogenic complication. There are high rates of tracheostomy dependence in BLVFI, with procedural intervention needed for decannulation. Compared with BVFP, patients with PGS had a higher procedural burden overall and to achieve decannulation. Patients with PGS should be counseled that smoking, a modifiable risk factor, may increase the risk of tracheostomy dependence.

Pain-related distress among patients referred to a community-based palliative care program

OBJECTIVE

Numerous studies have characterized the pain reported by patients with advanced illness in terms of descriptors such as severity, but few have measured pain-related distress. Distress may be important in the clinical approach to pain. To evaluate pain-related distress among adult patients with advanced illness and pain following enrollment in an urban, specialist-level, community-based palliative care program.

METHOD

In a retrospective cross-sectional analysis, data were extracted from the electronic health records of all patients who were able to complete the pain item from the Condensed Memorial Symptom Assessment Scale at the start of care. Bivariate and multivariate analyses evaluated the associations between distress and both sociodemographics and disease-related information.

RESULTS

The 506 patients completing the pain item had a mean (SD) age of 70.7 years (13.8); 64.2% were women, 32.1% were Hispanic, 32.6% were white, and 27.7% were black. Of the 503 patients who indicated some level of distress on a 0-4 scale, 221 (43.7%) had high distress, defined as a score ≥3 ("quite a bit" or "very much"). Cancer diagnosis and poor performance status (unable to care for self) were predictors of high pain-related distress (both p &lt; 0.05).Significance of resultsAmong patients with advanced illness who reported pain at the start of care by a specialist palliative care program, high pain-related distress was common, particularly among those with cancer or poor physical function. Further studies are needed to explore the extent to which pain-related distress should inform the assessment and management of pain.

Is a Patient's Current Address of Record a Reasonable Measure of Neighborhood Deprivation Exposure? A Case for the Use of Point in Time Measures of Residence in Clinical Care

Purpose: Interest is increasing in the use of geocoded patient address data to understand the effects that social determinants of health have on healthcare outcomes. Use of a patient's current address of record is often problematic given population mobility. Intragenerational economic mobility research suggests that patients will reside within neighborhoods with similar relative deprivation over time despite geographic mobility. The purpose of this study was to measure evidence of patient neighborhood deprivation persistence given a change in address of record.

Methods: A retrospective cohort study of patients receiving active care in an integrated delivery system in a high-mobility United States region. Neighborhood deprivation was measured using a block-group level area deprivation index. Neighborhood deprivation persistence was measured as the probability that an individual with an address of record change remained within a neighborhood with a similar deprivation score. Logistic regression was used to conduct multivariate analysis.

Results: Geographic mobility was highest among patients living in the most deprived neighborhoods versus least-deprived (odds ratio 1.75; 95% confidence interval: 1.71–1.79). Seventy-eight percent of all patients with a change of address did so to a neighborhood with a similar deprivation quintile. The probability that a random patient selected from the study had a change of address outside the same or neighboring quintile within a 1-year period ranged from 2% to 13%.

Conclusions: Neighborhood deprivation persistence was high among this population of patients from a high mobility region. A current address of record is a reasonable indicator of patient exposure to neighborhood deprivation within a 1–3-year timeframe that is useful in evaluating healthcare disparities.

A novel approach for measuring residential socioeconomic factors associated with cardiovascular and metabolic health

Individual-level characteristics, including socioeconomic status, have been associated with poor metabolic and cardiovascular health; however, residential area-level characteristics may also independently contribute to health status. In the current study, we used hierarchical clustering to aggregate 444 US Census block groups in Durham, Orange, and Wake Counties, NC, USA into six homogeneous clusters of similar characteristics based on 12 demographic factors. We assigned 2254 cardiac catheterization patients to these clusters based on residence at first catheterization. After controlling for individual age, sex, smoking status, and race, there were elevated odds of patients being obese (odds ratio (OR)=1.92, 95% confidence intervals (CI)=1.39, 2.67), and having diabetes (OR=2.19, 95% CI=1.57, 3.04), congestive heart failure (OR=1.99, 95% CI=1.39, 2.83), and hypertension (OR=2.05, 95% CI=1.38, 3.11) in a cluster that was urban, impoverished, and unemployed, compared with a cluster that was urban with a low percentage of people that were impoverished or unemployed. Our findings demonstrate the feasibility of applying hierarchical clustering to an assessment of area-level characteristics and that living in impoverished, urban residential clusters may have an adverse impact on health.

Small-area Variation in Hypertension Prevalence among Black and White Medicaid Enrollees

OBJECTIVES

To examine within-state geographic heterogeneity in hypertension prevalence and evaluate associations between hypertension prevalence and small-area contextual characteristics for Black and White South Carolina Medicaid enrollees in urban vs rural areas.

DESIGN

Ecological.

SETTING

South Carolina, United States.

MAIN OUTCOME MEASURES

Hypertension prevalence.

METHODS

Data representing adult South Carolina Medicaid recipients enrolled in fiscal year 2013 (N=409,907) and ZIP Code Tabulation Area (ZCTA)-level contextual measures (racial segregation, rurality, poverty, educational attainment, unemployment and primary care physician adequacy) were linked in a spatially referenced database. Optimized Getis-Ord hotspot mapping was used to visualize geographic clustering of hypertension prevalence. Spatial regression was performed to examine the association between hypertension prevalence and small-area contextual indicators.

RESULTS

Significant (alpha=.05) hotspot spatial clustering patterns were similar for Blacks and Whites. Black isolation was significantly associated with hypertension among Blacks and Whites in both urban (Black, b=1.34, P<.01; White, b=.66, P<.01) and rural settings (Black, b=.71, P=.02; White, b=.70, P<.01). Primary care physician adequacy was associated with hypertension among urban Blacks (b=-2.14, P<.01) and Whites (b=-1.74, P<.01).

CONCLUSIONS

The significant geographic overlap of hypertension prevalence hotspots for Black and White Medicaid enrollees provides an opportunity for targeted health intervention. Provider adequacy findings suggest the value of ACA network adequacy standards for Medicaid managed care plans in ensuring health care accessibility for persons with hypertension and related chronic conditions.

Spatial social polarisation: using the Index of Concentration at the Extremes jointly for income and race/ethnicity to analyse risk of hypertension

BACKGROUND

Growing spatial social and economic polarisation may be an important societal determinant of health, but only a few studies have used the recently developed Index of Concentration at the Extremes (ICE) to analyse the impact of joint concentrations of privilege and privation on health outcomes. We explore use of the ICE to investigate risk of hypertension in an urban, multiracial/ethnic, and predominantly working-class study population of US adults.

METHODS

We generated novel ICE measures at the census tract level that jointly assess extreme concentrations of both income and racial/ethnic composition. We then linked the ICE measures to data from two observational, cross-sectional studies conducted in the Boston metropolitan area (2003-2004; 2008-2010; N=2145).

RESULTS

The ICE measure for extreme concentrations of white compared with black residents was independently associated with lower odds of hypertension (OR=0.76; 95% CI 0.62 to 0.93), controlling for race/ethnicity, age, gender, smoking, body mass index, household income, education and self-reported exposure to racial discrimination. Even stronger associations were observed for the ICE measures that compared concentrations of high-income white residents versus low-income residents of colour (OR=0.61; 95% CI 0.40 to 0.96) and high-income white versus low-income black residents (OR=0.48; 95% CI 0.29 to 0.81).

CONCLUSIONS

Results suggest public health studies should explore the joint impact of racial/ethnic and economic spatial polarisation on population health.

Spatial social polarisation: using the Index of Concentration at the Extremes jointly for income and race/ethnicity to analyse risk of hypertension

BACKGROUND

Growing spatial social and economic polarisation may be an important societal determinant of health, but only a few studies have used the recently developed Index of Concentration at the Extremes (ICE) to analyse the impact of joint concentrations of privilege and privation on health outcomes. We explore use of the ICE to investigate risk of hypertension in an urban, multiracial/ethnic, and predominantly working-class study population of US adults.

METHODS

We generated novel ICE measures at the census tract level that jointly assess extreme concentrations of both income and racial/ethnic composition. We then linked the ICE measures to data from two observational, cross-sectional studies conducted in the Boston metropolitan area (2003-2004; 2008-2010; N=2145).

RESULTS

The ICE measure for extreme concentrations of white compared with black residents was independently associated with lower odds of hypertension (OR=0.76; 95% CI 0.62 to 0.93), controlling for race/ethnicity, age, gender, smoking, body mass index, household income, education and self-reported exposure to racial discrimination. Even stronger associations were observed for the ICE measures that compared concentrations of high-income white residents versus low-income residents of colour (OR=0.61; 95% CI 0.40 to 0.96) and high-income white versus low-income black residents (OR=0.48; 95% CI 0.29 to 0.81).

CONCLUSIONS

Results suggest public health studies should explore the joint impact of racial/ethnic and economic spatial polarisation on population health.

Cross-sectional associations between residential environmental exposures and cardiovascular diseases

BACKGROUND

Prior research examining neighbourhood effects on cardiovascular diseases (CVDs) has focused on the impact of neighbourhood socio-economic status or a few selected environmental variables. No studies of cardiovascular disease outcomes have investigated a broad range of urban planning related environmental factors. This is the first study to combine multiple neighbourhood influences in an integrated approach to understanding the association between the built and social environment and CVDs. By modeling multiple neighbourhood level social and environmental variables simultaneously, the study improved the estimation of effects by accounting for potential contextual confounders.

METHODS

Data were collected using a cross-sectional survey (n = 2411) across 87 census tracts (CT) in Toronto, Canada, and commercial and census data were accessed to characterize the residential environment. Multilevel regressions were used to estimate the associations of neighbourhood factors on the risk of CVD.

RESULTS

Exposure to violent crimes, environmental noise, and proximity to a major road were independently associated with increased odds of CVDs (p < 0.05) in the fully adjusted model. While reduced access to food stores, parks/recreation, and increased access to fast food restaurants were associated with increased odds of CVDs in partially adjusted models (p < 0.05), these associations were fully attenuated after adjusting for BMI and physical activity. Housing disrepair was not associated with CVD risk.

CONCLUSIONS

These findings illustrate the importance of measuring and modeling a broad range of neighborhood factors--exposure to violent crimes, environmental noise, and traffic, and access to food stores, fast food, parks/recreation areas--to identify specific stressors in relation to adverse health outcomes. Further research to investigate the temporal order of events is needed to better understand the direction of causation for the observed associations.

Examination of spatial polygamy among young gay, bisexual, and other men who have sex with men in New York City: the P18 cohort study

The few previous studies examining the influence of the neighborhood context on health and health behavior among young gay, bisexual, and other men who have sex with men (YMSM) have predominantly focused on residential neighborhoods. No studies have examined multiple neighborhood contexts among YMSM or the relationships between sociodemographic characteristics, psychosocial factors, social support network characteristics, health behaviors, and neighborhood concordance. In this study, we assessed spatial polygamy by determining the amount of concordance between residential, social, and sex neighborhoods (defined as boroughs) in addition to examining individual-level characteristics that may be associated with neighborhood concordance. These data come from the baseline assessment of Project 18, a cohort of racially and ethnically diverse YMSM residing in the New York City metropolitan area. Participants (N = 598) provided information on their residential, social, and sex boroughs as well as information on their sociodemographic characteristics, psychosocial factors, social support network characteristics, and health behaviors (e.g., substance use and condomless sex). Descriptive analyses were conducted to examine the distribution of boroughs reported across all three contexts, i.e., residential, social, and sex boroughs. Next, concordance between: (1) residential and social boroughs; (2) residential and sex boroughs; (3) social and sex boroughs; and (4) residential, social, and sex boroughs was assessed. Finally, bivariable analyses were conducted to examine the relationships between sociodemographic characteristics, psychosocial factors, social support network characteristics, and health behaviors in relation to borough concordance. Approximately two-thirds of participants reported concordance between residential/socializing, residential/sex, and sex/socializing boroughs, whereas 25% reported concordance between all three residential/socializing/sex boroughs. Borough concordance varied by some individual-level characteristics. For example, White YMSM and YMSM reporting lower perceived socioeconomic status were significantly more likely to report residential/socializing/sex borough concordance (p < 0.001). With regard to psychosocial factors, YMSM who reported experiencing gay-related stigma in public forums were more likely to report discordant socializing/sex and residential/socializing/sex boroughs (p < 0.001). Greater frequency of communication with network members (≥weekly) was associated with less residential/social borough concordance (p < 0.05). YMSM who reported residential/socializing/sex borough concordance were more likely to report recent (last 30 days) alcohol use, recent marijuana use, and recently engaging in condomless oral sex (all p < 0.05). These findings suggest that spatial polygamy, or an individual moving across and experiencing multiple neighborhood contexts, is prevalent among urban YMSM and that spatial polygamy varies by multiple individual-level characteristics. Future research among YMSM populations should consider multiple neighborhood contexts in order to provide a more nuanced understanding of how and which neighborhood contexts influence the health and well-being of YMSM. This further examination of spatial polygamy (and individual-level characteristics associated with it) may increase understanding of the most appropriate locations for targeted disease prevention and health promotion interventions (e.g., HIV prevention interventions).