Neighborhood socioeconomic index and stroke incidence in a national cohort of blacks and whites.
ABSTRACT: To assess the relationship between neighborhood socioeconomic characteristics and incident stroke in a national cohort of black and white participants.The study comprised black (n = 10,274, 41%) and white (n = 14,601) stroke-free participants, aged 45 and older, enrolled in 2003-2007 in Reasons for Geographic and Racial Differences in Stroke (REGARDS), a national population-based cohort. A neighborhood socioeconomic score (nSES) was constructed using 6 neighborhood variables. Incident stroke was defined as first occurrence of stroke over an average 7.5 (SD 3.0) years of follow-up. Proportional hazards models were used to estimate associations between nSES score and incident stroke, adjusted for demographics (age, race, sex, region), individual socioeconomic status (SES) (education, household income), and other risk factors for stroke.After adjustment for demographics, compared to the highest nSES quartile, stroke incidence increased with each decreasing nSES quartile. The hazard ratio (95% confidence interval) ranged from 1.28 (1.05-1.56) in quartile 3 to 1.38 (1.13-1.68) in quartile 2 to 1.56 (1.26-1.92) in quartile 1 (p < 0.0001 for linear trend). After adjustment for individual SES, the trend remained marginally significant (p = 0.085). Although there was no evidence of a differential effect by race or sex, adjustment for stroke risk factors attenuated the association between nSES and stroke in both black and white participants, with greater attenuation in black participants.Risk of incident stroke increased with decreasing nSES but the effect of nSES is attenuated through individual SES and stroke risk factors. The effect of neighborhood socioeconomic characteristics that contribute to increased stroke risk is similar in black and white participants.
Project description:<h4>Objectives</h4>to investigate whether psychosocial pathways mediate the association between neighbourhood socioeconomic disadvantage and stroke.<h4>Methods</h4>prospective cohort study with a follow-up of 11.5 years.<h4>Setting</h4>the Cardiovascular Health Study, a longitudinal population-based cohort study of older adults ?65 years.<h4>Measurements</h4>the primary outcome was adjudicated incident ischaemic stroke. Neighbourhood socioeconomic status (NSES) was measured using a composite of six census-tract variables. Psychosocial factors were assessed with standard measures for depression, social support and social networks.<h4>Results</h4>of the 3,834 white participants with no prior stroke, 548 had an incident ischaemic stroke over the 11.5-year follow-up. Among whites, the incident stroke hazard ratio (HR) associated with living in the lowest relative to highest NSES quartile was 1.32 (95% CI = 1.01-1.73), in models adjusted for individual SES. Additional adjustment for psychosocial factors had a minimal effect on hazard of incident stroke (HR = 1.31, CI = 1.00-1.71). Associations between NSES and stroke incidence were not found among African-Americans (n = 785) in either partially or fully adjusted models.<h4>Conclusions</h4>psychosocial factors played a minimal role in mediating the effect of NSES on stroke incidence among white older adults.
Project description:BACKGROUND:We addressed the hypothesis that individual-level factors act jointly with social and built environment factors to influence overall survival for men with prostate cancer and contribute to racial/ethnic and socioeconomic (SES) survival disparities. METHODS:We analyzed multi-level data, combining (1) individual-level data from the California Collaborative Prostate Cancer Study, a population-based study of non-Hispanic White (NHW), Hispanic, and African American prostate cancer cases (N?=?1800) diagnosed from 1997 to 2003, with (2) data on neighborhood SES (nSES) and social and built environment factors from the California Neighborhoods Data System, and (3) data on tumor characteristics, treatment and follow-up through 2009 from the California Cancer Registry. Multivariable, stage-stratified Cox proportional hazards regression models with cluster adjustments were used to assess education and nSES main and joint effects on overall survival, before and after adjustment for social and built environment factors. RESULTS:African American men had worse survival than NHW men, which was attenuated by nSES. Increased risk of death was associated with residence in lower SES neighborhoods (quintile 1 (lowest nSES) vs. 5: HR?=?1.56, 95% CI: 1.11-2.19) and lower education (<high school vs. college: HR?=?1.32, 95% CI: 1.05-1.67), and a joint association of low education and low nSES was observed. Adjustment for behavioral, hospital, and restaurant and food environment characteristics only slightly attenuated these associations between SES and survival. CONCLUSION:Both individual- and contextual-level SES influence overall survival of men with prostate cancer. Additional research is needed to identify the mechanisms underlying these robust associations.
Project description:<h4>Objective</h4>Residence in a socioeconomically disadvantaged community is associated with mortality, but the mechanisms are not well understood. We examined whether socioeconomic features of the residential neighborhood contribute to poststroke mortality and whether neighborhood influences are mediated by traditional behavioral and biologic risk factors.<h4>Methods</h4>We used data from the Cardiovascular Health Study, a multicenter, population-based, longitudinal study of adults ?65 years. Residential neighborhood disadvantage was measured using neighborhood socioeconomic status (NSES), a composite of 6 census tract variables representing income, education, employment, and wealth. Multilevel Cox proportional hazard models were constructed to determine the association of NSES to mortality after an incident stroke, adjusted for sociodemographic characteristics, stroke type, and behavioral and biologic risk factors.<h4>Results</h4>Among the 3,834 participants with no prior stroke at baseline, 806 had a stroke over a mean 11.5 years of follow-up, with 168 (20%) deaths 30 days after stroke and 276 (34%) deaths at 1 year. In models adjusted for demographic characteristics, stroke type, and behavioral and biologic risk factors, mortality hazard 1 year after stroke was significantly higher among residents of neighborhoods with the lowest NSES than those in the highest NSES neighborhoods (hazard ratio 1.77, 95% confidence interval 1.17-2.68).<h4>Conclusion</h4>Living in a socioeconomically disadvantaged neighborhood is associated with higher mortality hazard at 1 year following an incident stroke. Further work is needed to understand the structural and social characteristics of neighborhoods that may contribute to mortality in the year after a stroke and the pathways through which these characteristics operate.
Project description:Long-term fine particulate matter (PM2.5) exposure is linked with cardiovascular disease, and disadvantaged status may increase susceptibility to air pollution-related health effects. In addition, there are concerns that this association may be partially explained by confounding by socioeconomic status (SES).We examined the roles that individual- and neighborhood-level SES (NSES) play in the association between PM2.5 exposure and cardiovascular disease.The study population comprised 51,754 postmenopausal women from the Women's Health Initiative Observational Study. PM2.5 concentrations were predicted at participant residences using fine-scale regionalized universal kriging models. We assessed individual-level SES and NSES (Census-tract level) across several SES domains including education, occupation, and income/wealth, as well as through an NSES score, which captures several important dimensions of SES. Cox proportional-hazards regression adjusted for SES factors and other covariates to determine the risk of a first cardiovascular event.A 5 ?g/m3 higher exposure to PM2.5 was associated with a 13% increased risk of cardiovascular event [hazard ratio (HR) 1.13; 95% confidence interval (CI): 1.02, 1.26]. Adjustment for SES factors did not meaningfully affect the risk estimate. Higher risk estimates were observed among participants living in low-SES neighborhoods. The most and least disadvantaged quartiles of the NSES score had HRs of 1.39 (95% CI: 1.21, 1.61) and 0.90 (95% CI: 0.72, 1.07), respectively.Women with lower NSES may be more susceptible to air pollution-related health effects. The association between air pollution and cardiovascular disease was not explained by confounding from individual-level SES or NSES. Citation: Chi GC, Hajat A, Bird CE, Cullen MR, Griffin BA, Miller KA, Shih RA, Stefanick ML, Vedal S, Whitsel EA, Kaufman JD. 2016. Individual and neighborhood socioeconomic status and the association between air pollution and cardiovascular disease. Environ Health Perspect 124:1840-1847;?http://dx.doi.org/10.1289/EHP199.
Project description:OBJECTIVE:To explore the influence of contextual factors on health-related quality of life (HRQoL), which is sometimes used as an indicator of quality of care, we examined the association of neighborhood socioeconomic status (NSES) and trajectories of HRQoL after hospitalization for acute coronary syndromes (ACS). METHODS:We studied 1481 patients hospitalized with acute coronary syndromes in Massachusetts and Georgia querying HRQoL via the mental and physical components of the 36-item short-form health survey (SF-36) (MCS and PCS) and the physical limitations and angina-related HRQoL subscales of the Seattle Angina Questionnaire (SAQ) during hospitalization and at 1-, 3-, and 6-month postdischarge. We categorized participants by tertiles of the neighborhood deprivation index (a residence-census tract-based measure) to examine the association of NSES with trajectories of HRQoL after adjusting for individual socioeconomic status (SES) and clinical characteristics. RESULTS:Participants had mean age 61.3 (SD, 11.4) years; 33% were female; 76%, non-Hispanic white; 11.2% had household income below the federal poverty level. During 6 months postdischarge, living in lower NSES neighborhoods was associated with lower mean PCS scores (1.5 points for intermediate NSES; 1.8 for low) and SAQ scores (2.4 and 4.2 points) versus living in high NSES neighborhoods. NSES was more consequential for patients with lower individual SES. Individuals living below the federal poverty level had lower average MCS and SAQ physical scores (3.7 and 7.7 points, respectively) than those above. CONCLUSIONS:Neighborhood deprivation was associated with worse health status. Using HRQoL to assess quality of care without accounting for individual SES and NSES may unfairly penalize safety-net hospitals.
Project description:Background:Prior studies suggest disparities in sepsis risk and outcomes based on place of residence. We sought to examine the association between neighborhood socioeconomic status (nSES) and hospitalization for infection and sepsis. Methods:We conducted a prospective cohort study using data from 30239 participants in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study. nSES was defined using a score derived from census data and classified into quartiles. Infection and sepsis hospitalizations were identified over the period 2003-2012. We fit Cox proportional hazards models, reporting hazard ratios (HRs) with 95% confidence intervals (CIs) and examining mediation by participant characteristics. Results:Over a median follow-up of 6.5 years, there were 3054 hospitalizations for serious infection. Infection incidence was lower for participants in the highest nSES quartile compared with the lowest quartile (11.7 vs 15.6 per 1000 person-years). After adjustment for demographics, comorbidities, and functional status, infection hazards were also lower for the highest quartile (HR, 0.84 [95% CI, .73-.97]), with a linear trend (P = .011). However, there was no association between nSES and sepsis at presentation among those hospitalized with infection. Physical weakness, income, and diabetes had modest mediating effects on the association of nSES with infection. Conclusions:Our study shows that differential infection risk may explain nSES disparities in sepsis incidence, as higher nSES is associated with lower infection hospitalization rates, but there is no association with sepsis among those hospitalized. Mediation analysis showed that nSES may influence infection hospitalization risk at least partially through physical weakness, individual income, and comorbid diabetes.
Project description:Neighborhood characteristics may influence the risk of stroke and contribute to socioeconomic disparities in stroke incidence. The objectives of this study were to examine the relationship between neighborhood socioeconomic status and incident ischemic stroke and examine potential mediators of these associations.We analyzed data from 3834 whites and 785 blacks enrolled in the Cardiovascular Health Study, a multicenter, population-based, longitudinal study of adults ages?65 years from 4 US counties. The primary outcome was adjudicated incident ischemic stroke. Neighborhood socioeconomic status was measured using a composite of 6 census tract variables. Race-stratified multilevel Cox proportional hazard models were constructed adjusted for sociodemographic, behavioral, and biological risk factors.Among whites, in models adjusted for sociodemographic characteristics, stroke hazard was significantly higher among residents of neighborhoods in the lowest compared with the highest neighborhood socioeconomic status quartile (hazard ratio, 1.32; 95% CI, 1.01-1.72) with greater attenuation of the hazard ratio after adjustment for biological risk factors (hazard ratio, 1.16; 0.88-1.52) than for behavioral risk factors (hazard ratio, 1.30; 0.99-1.70). Among blacks, we found no significant associations between neighborhood socioeconomic status and ischemic stroke.Higher risk of incident ischemic stroke was observed in the most disadvantaged neighborhoods among whites, but not among blacks. The relationship between neighborhood socioeconomic status and stroke among whites appears to be mediated more strongly by biological than behavioral risk factors.
Project description:INTRODUCTION:Neighborhood socioeconomic (nSES) factors have been implicated in prostate cancer (PCa) disparities. In line with the Precision Medicine Initiative that suggests clinical and socioenvironmental factors can impact PCa outcomes, we determined whether nSES variables are associated with time to PCa diagnosis and could inform PCa clinical risk assessment. MATERIALS AND METHODS:The study sample included 358 high risk men (PCa family history and/or Black race), aged 35-69 years, enrolled in an early detection program. Patient variables were linked to 78 nSES variables (employment, income, etc.) from previous literature via geocoding. Patient-level models, including baseline age, prostate specific antigen (PSA), digital rectal exam, as well as combined models (patient plus nSES variables) by race/PCa family history subgroups were built after variable reduction methods using Cox regression and LASSO machine-learning. Model fit of patient and combined models (AIC) were compared; p-values<0.05 were significant. Model-based high/low nSES exposure scores were calculated and the 5-year predicted probability of PCa was plotted against PSA by high/low neighborhood score to preliminarily assess clinical relevance. RESULTS:In combined models, nSES variables were significantly associated with time to PCa diagnosis. Workers mode of transportation and low income were significant in White men with a PCa family history. Homeownership (%owner-occupied houses with >3 bedrooms) and unemployment were significant in Black men with and without a PCa family history, respectively. The 5-year predicted probability of PCa was higher in men with a high neighborhood score (weighted combination of significant nSES variables) compared to a low score (e.g., Baseline PSA level of 4ng/mL for men with PCa family history: White-26.7% vs 7.7%; Black-56.2% vs 29.7%). DISCUSSION:Utilizing neighborhood data during patient risk assessment may be useful for high risk men affected by disparities. However, future studies with larger samples and validation/replication steps are needed.
Project description:This study examined the interrelationship of race and socioeconomic status (SES) upon infant birthweight at the individual and neighborhood levels within a Midwestern US county marked by high Black infant mortality. The study conducted a multi-level analysis utilizing individual birth records and census tract datasets from 2010, linked through a spatial join with ArcGIS 10.0. The maternal population of 2861 Black and White women delivering infants in 2010, residing in 57 census tracts within the county, constituted the study samples. The main outcome was infant birthweight. The predictors, race and SES were dichotomized into Black and White, low-SES and higher-SES, at both the individual and census tract levels. A two-part Bayesian model demonstrated that individual-level race and SES were more influential birthweight predictors than community-level factors. Specifically, Black women had 1.6 higher odds of delivering a low birthweight (LBW) infant than White women, and low-SES women had 1.7 higher odds of delivering a LBW infant than higher-SES women. Moderate support was found for a three-way interaction between individual-level race, SES and community-level race, such that Black women achieved equity with White women (4.0% Black LBW and 4.1% White LBW) when they each had higher-SES and lived in a racially congruous neighborhood (e.g., Black women lived in disproportionately Black neighborhood and White women lived in disproportionately White neighborhood). In sharp contrast, Black women with higher-SES who lived in a racially incongruous neighborhood (e.g., disproportionately White) had the worst outcomes (14.5% LBW). Demonstrating the layered influence of personal and community circumstances upon health, in a community with substantial racial disparities, personal race and SES independently contribute to birth outcomes, while environmental context, specifically neighborhood racial congruity, is associated with mitigated health risk.
Project description:Racial and gender disparities in out-of-hospital deaths from coronary heart disease (CHD) have been well-documented, yet disparities by neighborhood socioeconomic status (nSES) have been less systematically studied in US population-based surveillance efforts.We examined the association of nSES, classified into tertiles, with 3,743 out-of-hospital fatal CHD events, and a subset of 2,191 events classified as sudden, among persons aged 35 to 74 years in four US communities under surveillance by the Atherosclerosis Risk in Communities (ARIC). Poisson generalized linear mixed models generated age-, race- (white, black) and gender-specific standardized mortality rate ratios and 95% confidence intervals (RR, 95% CI).Regardless of nSES measure used, inverse associations of nSES with all out-of-hospital fatal CHD and sudden fatal CHD were seen in all race-gender groups. The magnitude of these associations was larger among women than men. Further, among blacks, associations of low nSES (vs. high nSES) were stronger for sudden cardiac deaths (SCD) than for all out-of-hospital fatal CHD.Low nSES was associated with an increased risk of out-of-hospital CHD death and SCD. Measures of the neighborhood context are useful tools in population-based surveillance efforts for documenting and monitoring socioeconomic disparities in mortality over time.