Neighborhood Disadvantage Research Articles

Individual socioeconomic status, neighborhood disadvantage, and cognitive aging: A longitudinal analysis of the CLSA.

There are likely many contributors to variation in the rate of cognitive decline in middle and late adulthood, including individual and neighborhood socio-economic factors. This study examines whether individual socio-economic factors, namely income and wealth, correlate with cognitive decline, in part, through neighborhood-level social and material disadvantage. Using the three waves of data collection from the Canadian Longitudinal Study on Aging (CLSA), this study included 51,338 participants between the age of 45 and 85 years at baseline (51% female). Individual socio-economic status (SES) was assessed by annual household income and by the current value of savings and investments. Neighborhood disadvantage was measured by area-based material and social deprivation indices. Cognition was measured at each wave using verbal fluency, mental alternations, and delayed word recall. Latent change score models, incorporating direct and indirect pathways, were constructed to estimate the indirect effect of individual SES on cognitive change through area-level disadvantage. Multi-group models were constructed on the basis of age-group (45-64 years; 65-74 years; or 75+ years) to allow for varying estimates across age. Among 45-64-year-olds, income and wealth had indirect effects on initial cognitive level and on rate of cognitive decline through material disadvantage (standardized indirect effects = 0.01, p < 0.001), but only wealth had an indirect effect through social disadvantage (p = 0.019). Among 65-74-year-olds, income and wealth had indirect effects on initial cognitive level (p < 0.01) but not on rate of cognitive decline (p > 0.05), and among 75+ year-olds, no indirect effects were observed (p > 0.05). Wealth and income had direct effects, independent of neighborhood disadvantage, on cognition in all age groups (p < 0.05). Among middle-aged adults, greater individual SES may mitigate cognitive decline, in part, by allowing individuals to live in more materially and socially advantaged neighborhoods.

Benchmarking commercial healthcare claims data.

Commercial healthcare claims datasets represent a sample of the US population that is biased along socioeconomic/demographic lines; depending on the target population of interest, results derived from these datasets may not generalize. Rigorous comparisons of claims-derived results to ground-truth data that quantify this bias are lacking. (1) To quantify the extent and variation of the bias associated with commercial healthcare claims data with respect to different target populations; (2) To evaluate how socioeconomic/demographic factors may explain the magnitude of the bias. This is a retrospective observational study. Healthcare claims data come from the Merative™ MarketScan® Commercial Database; reference data for comparison come from the State Inpatient Databases (SID) and the US Census. We considered three target populations, aged 18-64 years: (1) all Americans; (2) Americans with health insurance; (3) Americans with commercial health insurance. We analyzed inpatient discharge records of patients aged 18-64 years, occurring between 01/01/2019 to 12/31/2019 in five states: California, Iowa, Maryland, Massachusetts, and New Jersey. We estimated rates of the 250 most common inpatient procedures, using claims data and using reference data for each target population, and we compared the two estimates. The average rate of inpatient discharges per 100 person-years was 5.39 in the claims data (95% CI: [5.37, 5.40]) and 7.003 (95% CI: [7.002, 7.004]) in the reference data for all Americans, corresponding to a 23.1% underestimate from claims. We found large variation in the extent of relative bias across inpatient procedures, including 22.8% of procedures that were underestimated by more than a factor of 2. There was a significant relationship between socioeconomic/demographic factors and the magnitude of bias: procedures that disproportionately occur in disadvantaged neighborhoods were more underestimated in claims data (R 2 51.6%, p < 0.001). When the target population was restricted to commercially insured Americans, the bias decreased substantially (3.2% of procedures were biased by more than factor of 2), but some variation across procedures remained. Naïve use of healthcare claims data to derive estimates for the underlying US population can be severely biased. The extent of bias is at least partially explained by neighborhood-level socioeconomic factors.

Association between Heat Vulnerability Index and Stroke Severity.

Socioeconomically disadvantaged neighborhoods are particularly vulnerable to heat-related illnesses. We aim to investigate the association between the heat vulnerability index (HVI), an established neighborhood-level metric of heat-related mortality risk, and acute ischemic stroke (AIS) severity. We conducted a retrospective analysis of consecutive AIS admissions to a comprehensive stroke center between 2012 and 2021. Stroke severity was defined upon admission based on the National Institutes of Health Stroke Scale (NIHSS). Demographic, socioeconomic, and clinical characteristics were extracted from electronic health records. HVI status was assigned using residential ZIP codes. Multivariable logistic regression analyses were performed. Of 3429 AIS admissions, 1123 (32.8%) were from high-HVI (scores 4-5) neighborhoods and 868 (25.3%) had severe stroke (NIHSS score ≥ 10). In the multivariable regression model with stepwise selection, a high HVI was independently associated with severe stroke (adjusted odds ratio: 1.40 [95% confidence interval 1.16-1.69]). The association between a high HVI and severe stroke underscores the importance of targeting policy interventions to mitigate heat-related illness in socioeconomically disadvantaged neighborhoods.

Neighborhood Socioeconomic Disadvantage and 30-Day Outcomes for Common Cardiovascular Conditions.

Understanding the relationship between neighborhood environment and cardiovascular outcomes is important to achieve health equity and implement effective quality strategies. We conducted a population-based cohort study to determine the association of neighborhood socioeconomic deprivation and 30-day mortality and readmission rate for patients admitted with common cardiovascular conditions. We examined claims data from fee-for-service Medicare beneficiaries aged ≥65 years between 2017 and 2019 admitted for heart failure, valvular heart disease, ischemic heart disease, or cardiac arrhythmias. The primary exposure was the Area Deprivation Index; outcomes were 30-day all-cause death and unplanned readmission. More than 2 million admissions were included. After sequential adjustment for patient characteristics (demographics, dual eligibility, comorbidities), area health care resources (primary care clinicians, specialists, and hospital beds per capita), and admitting hospital characteristics (ownership, size, teaching status), there was a dose-dependent association between neighborhood socioeconomic deprivation and 30-day mortality rate for all conditions. In the fully adjusted model for death, estimated effect sizes of residence in the most disadvantaged versus least disadvantaged neighborhoods ranged from adjusted odds ratio 1.29 (95% CI, 1.22-1.36) for the heart failure group to adjusted odds ratio 1.63 (95% CI, 1.36-1.95) for the valvular heart disease group. Neighborhood deprivation was associated with increased adjusted 30-day readmission rates, with estimated effect sizes from adjusted odds ratio 1.09 (95% CI, 1.05-1.14) for heart failure to adjusted odds ratio 1.19 (95% CI, 1.13-1.26) for arrhythmia. Neighborhood socioeconomic disadvantage was associated with 30-day mortality rate and readmission for patients admitted with common cardiovascular conditions independent of individual demographics, socioeconomic status, medical risk, care access, or admitting hospital characteristics.

Higher neighborhood disadvantage is associated with weaker interactions among cardiometabolic drivers

BackgroundAdiposity, dysglycemia, and hypertension are metabolic drivers that have causal interactions with each other. However, the effect of neighborhood-level disadvantage on the intensity of interactions among these metabolic drivers has not been studied. The objective of this study is to determine whether the strength of the interplay between these drivers is affected by neighborhood-level disadvantage. MethodsThis cross-sectional study analyzed patients presenting to a multidisciplinary preventive cardiology center in New York City, from March 2017 to February 2021. Patients’ home addresses were mapped to the Area Deprivation Index to determine neighborhood disadvantage. The outcomes of interest were correlation coefficients (range from −1 to +1) among the various stages (0 - normal, 1 - risk, 2 - predisease, 3 - disease, and 4 - complications) of abnormal adiposity, dysglycemia, and hypertension at presentation, stratified by neighborhood disadvantage. ResultsThe cohort consisted of 963 patients (age, median [IQR] 63.8 [49.7–72.5] years; 624 [65.1 %] female). The correlation among the various stages of adiposity, dysglycemia, and hypertension was weaker with increasing neighborhood disadvantage (P for trend <0.001). Specifically, the correlation describing adiposity, dysglycemia, and hypertension interaction was weaker in the high neighborhood disadvantage group compared to the intermediate neighborhood disadvantage group (median [IQR]: 0.34 [0.27, 0.44] vs. median [IQR]: 0.39 [0.34, 0.45]; P < 0.001) and compared to the low neighborhood disadvantage group (median [IQR]: 0.34 [0.27, 0.44] vs. median [IQR]: 0.54 [0.52, 0.57]; P < 0.001), as well as weaker in the intermediate neighborhood disadvantage group compared to the low neighborhood disadvantage group (median [IQR]: 0.39 [0.34, 0.45] vs. 0.54 median [IQR]: 0.54 [0.52, 0.57]; P < 0.001). ConclusionsInteractions among the various stages of abnormal adiposity, dysglycemia, and hypertension with each other are weaker with increasing neighborhood disadvantage. Factors related to neighborhood-level disadvantage, other than abnormal adiposity, might play a crucial role in the development of dysglycemia and hypertension.

Carjacking and homicide in Minneapolis after the police killing of George Floyd: Evidence from an interrupted time series analysis

There is abundant research showing the disproportionate impacts of violence on health in disadvantaged neighborhoods, making an understanding of recent violent crime trends essential for promoting health equity. Carjackings have been of particular interest in the media, although little research has been undertaken on this violent crime. We use interrupted time series models to examine the impact of the police killing of George Floyd on the spatiotemporal patterns of carjacking in Minneapolis in relation to neighborhood disadvantage. To provide grounding, we compare our results to the well-studied patterns of homicides. Results indicate that carjackings both increased and dispersed spatially after the murder of George Floyd and subsequent social unrest, more so than homicides. Socially disadvantaged neighborhoods experienced the greatest absolute increase while more advantaged neighborhoods saw a greater relative increase. The challenge ahead is to identify policy responses that will effectively curb such violence without resorting to harsh and inequitable policing and sentencing practices.

Neighborhood disadvantage and breast cancer incidence among women living in the United States

Neighborhood disadvantage and breast cancer incidence among women living in the United States

Preoperative Exposure to Fine Particulate Matter and Risk of Postoperative Complications: A Single Center Observational Cohort Bayesian Analysis.

While exposure to fine particulate matter air pollution (PM 2.5 ) is known to cause adverse health effects, its impact on postoperative outcomes in US adults remains understudied. Perioperative exposure to PM 2.5 may induce inflammation that insidiously interacts with the systemic inflammatory response after surgery, leading to higher postoperative complications. We conducted a single center, retrospective cohort study using data from 64,313 surgical patients living along Utah's Wasatch Front and undergoing elective surgical procedures at a single academic medical center from 2016-2018. Patients' addresses were geocoded and linked to daily Census-tract level PM 2.5 estimates preoperatively. We hypothesized that elevated PM 2.5 concentrations in the seven days prior to surgery would be associated with an increase in a bundle of major postoperative complications. A hierarchical Bayesians regression model was fit adjusting for age, sex, season, neighborhood disadvantage, and the Elixhauser index of comorbidities. Postoperative complications increased in a dose-dependent manner with higher concentrations of PM 2.5 exposure, with a relative increase of 7% in the odds of complications for every 10ug/m3 increase in the highest single-day 24-hr PM 2.5 exposure during the 7 days prior to surgery. The association persisted after controlling for comorbidities and potential confounders; our inferences were robust to modeling choices and sensitivity analysis. In this large Utah cohort, exposure to elevated PM 2.5 concentrations in the week before surgery was associated with increased postoperative complications in a dose-dependent manner, suggesting a potential impact of air pollution on surgical outcomes. These findings merit replication in larger datasets to identify populations at risk and to define the interaction and impact of different pollutants. PM 2.5 exposure is a potential perioperative risk factor and, given the unmitigated air pollution in urban areas, a global health concern.

Neighborhood Disadvantage and Prostate Tumor Aggressiveness among African American and European American Men.

Studies have identified associations between neighborhood disadvantage (ND), which is more likely to affect African American (AA) individuals, and aggressive prostate cancer. Thus, ND may contribute to prostate cancer disparities. However, it is unknown what ND components drive aggressive disease and whether associations vary by race. We evaluated associations between aggressive prostate cancer and four ND metrics-Area Deprivation Index (ADI), validated Bayesian Neighborhood Deprivation Index (NDI), racial isolation (RI) index, and historical redlining, and whether these factors interacted with race, among men with prostate cancer treated at the University of Maryland Greenebaum Comprehensive Cancer Center (2004-2021). We included 1,458 men (698 European American and 760 AA). AA men were more likely to experience ND. In adjusted models, the ADI, RI, and redlining were significantly associated with aggressive versus nonaggressive prostate cancer overall [ADI, OR for one SD increase = 1.14, 95% confidence interval (CI), 1.00-1.30; RI, OR = 1.27, CI, 1.07-1.51; redlining, OR = 1.77; CI, 1.23-2.56] and among AA men. The NDI was associated with aggressive prostate cancer among AA men (OR = 1.32, 95% credible interval: 1.13-1.57); percent in poverty received the largest importance weight. The ADI (P heterogeneity = 0.002) and NDI (exceedance probability heterogeneity = 98.1%) significantly interacted with race, such that associations were significantly stronger for AA men. We identified novel significant positive associations for racial segregation and historical redlining with aggressive prostate cancer and significant interactions between ND indices and race. Findings inform specific ND components that are associated with aggressive prostate cancer and suggest the ND effect is stronger for AA men, which has implications for interventions to reduce disparities.

The TBI Model Systems Neighborhood Socioeconomic Disadvantage Index (TBIMS-NSDI): Development and Comparison to Individual Socioeconomic Characteristics.

To create a census-based composite neighborhood socioeconomic deprivation index (NSDI) from geocoded residential addresses and to quantify how NSDI aligns with individual-level socioeconomic factors among people with traumatic brain injury (TBI). Community. People enrolled in the TBI Model Systems National Database (TBIMS NDB). Secondary analysis of a longitudinal cohort study. The TBIMS-NSDI was calculated at the census tract level for the United States population based on a principal components analysis of eight census tract-level variables from the American Community Survey. Individual socioeconomic characteristics from the TBIMS NDB were personal household income, education (years), and unemployment status. Neighborhood:Individual NSDI residuals represent the difference between predicted neighborhood disadvantage based on individual socioeconomic characteristics versus observed neighborhood disadvantage based on the TBIMS-NSDI. A single principal component was found to encompass the eight socioeconomic neighborhood-level variables. It was normally distributed across follow-up years 2, 5, and 10 post-injury in the TBIMS NDB. In all years, the TBIMS-NDSI was significantly associated with individual-level measures of household income and education but not unemployment status. Males, persons of Black and Hispanic background, Medicaid recipients, persons with TBI caused by violence, and those living in urban areas, as well as in the Northeast or Southern regions of the United States, were more likely to have greater neighborhood disadvantage than predicted based on their individual socioeconomic characteristics. The TBIMS-NSDI provides a neighborhood-level indicator of socioeconomic disadvantage, an important social determinant of outcomes from TBI. The Neighborhood:Individual NSDI residual adds another dimension to the TBIMS-NSDI by summarizing how a person's socioeconomic status aligns with their neighborhood socioeconomics. Future studies should evaluate how both measures affect TBI recovery and life quality. Research studying neighborhood socioeconomic disadvantage may improve our understanding of how systemic adversity influences outcomes after TBI.

Neighborhood disadvantage, race, and clinical outcomes in neuromyelitis optica spectrum disorder

Background: Little is known about the relationship between neighborhood disadvantage and neuromyelitis optica spectrum disorder (NMOSD) outcomes. Objective: The objective is to determine the impact of neighborhood disadvantage on time from symptom onset to diagnosis and annualized relapse rate (ARR). Methods: Neighborhood disadvantage were captured with the Area Deprivation Index (ADI), a validated measure of neighborhood-level disadvantage. Negative binomial regression models assessed the impact of ADI on diagnostic delay (⩾3 months between symptom onset and diagnosis) and ARR. Results: A total of 158 NMOSD patients were identified, a majority of whom were White (56.3%) and female (89.9%) with a mean age of 46 years at diagnosis. The ADI did not significantly affect odds of diagnostic delay (odds ratio (OR) = 0.99, p = 0.26). In univariable models, the ADI was not significantly associated with ARR (OR = 1.004, p = 0.29), but non-White race (OR = 1.541, p = 0.02) and time on immunosuppressive therapies (ISTs; OR = 0.994, p = 0.03) were. White patients used IST for an average of 81% of the follow-up period, compared to an average of 65% for non-White patients (p < 0.01). Conclusion: No significant relationship between neighborhood-level disadvantage and diagnostic delay or ARR in NMOSD patients was observed. Non-White patients had a higher ARR, which may be related to less IST use.

Anxiety disorders in the elderly: the effect of child maltreatment

Introduction: Anxiety disorders in the elderly, when analyzed in light of the effects of childhood maltreatment, are notable not only for the high prevalence of these disorders in this age group, but also for the growing evidence that traumatic childhood experiences may play a significant role in its late development. Objective: To evaluate the influence of the occurrence and characteristics of child abuse and the clinical manifestation of anxiety disorders in the elderly. Methodology: This is a cross-sectional study, carried out with elderly people from socioeconomically disadvantaged neighborhoods in Porto Alegre, Brazil (n = 274), who responded to the Childhood Trauma Questionnaire (CTQ) and the Mini International Neuropsychiatric Interview 5.0 (MINI). more. Results: The development of anxiety disorder in the elderly was associated with several factors, reflecting a complex interaction between past experiences and present conditions. Among these factors, it was possible to deduce that the presence of child abuse, psychiatric comorbidities, disadvantaged financial conditions and low levels of education stood out. Conclusion: It is concluded that these findings support the hypothesis that child maltreatment is associated with anxiety disorders in the elderly and with specific levels of financial and educational conditions. Although they suggest that improving maladaptive social conditions in childhood could prevent anxiety disorders in the elderly.

Influence of Neighborhood Disadvantage and Individual Sociodemographic Conditions on Heart Failure Self-care.

Residence in socioeconomically disadvantaged neighborhoods and individual sociodemographic conditions contribute to worse heart failure (HF) outcomes and may influence HF self-care. However, associations between neighborhood disadvantage, socioeconomic conditions, and HF self-care are unclear. The purpose of this secondary analysis was to investigate whether neighborhood disadvantage and individual socioeconomic conditions predicted worse HF self-care. This study was a secondary analysis of baseline data from a mixed-method study of 82 adults with HF. Participant zip codes were assigned a degree of neighborhood disadvantage using the Area Deprivation Index. Those in the top 20% most disadvantaged neighborhoods (Area Deprivation Index ≥ 80) were compared with those in the least disadvantaged neighborhoods. The Self-Care of Heart Failure Index was used to measure self-care maintenance and monitoring. Multiple linear regression was conducted. Of all participants, 59.8% were male, 59.8% were persons of color, and the mean age was 64.87 years. Residing in a disadvantaged neighborhood and living alone predicted worse HF self-care maintenance and monitoring. Having no college education was also a predictor of worse HF self-care maintenance. Although persons of color were more likely to reside in disadvantaged neighborhoods, race was not associated with HF self-care. Residing in a disadvantaged neighborhood and living alone may be important risk factors for worse HF self-care. Differences in self-care cannot be attributed solely to the individual sociodemographic determinants of race, gender, age, annual household income, or marital status. More research is needed to understand the connection between neighborhood disadvantage and HF self-care.

Getting out and giving back: repertoires of destigmatization in the private social safety net

Abstract Receiving assistance can be stigmatizing. As the cash welfare rolls have fallen to near-historic lows, the privatization of the social safety net in many states has brought up new questions about how recipients of assistance meet their material needs without sacrificing their sense of dignity. I draw on 15 months of ethnographic observation and 44 interviews with social service recipients in two majority Black neighborhoods in Houston, Texas to explore how they destigmatize their encounters with social service providers. I find that service recipients primarily seek out organizations that will treat them with respect due to the stigma attached to receiving assistance. This stigma is both racialized and gendered, such that groups with identities congruent with negative stereotypes about welfare recipients—like Black women—see themselves at higher risk of stigmatization and therefore practice destigmatization strategies with greater frequency. I build on these findings by highlighting two repertoires of destigmatization that service recipients draw upon to access both material and symbolic resources simultaneously: getting out of their neighborhoods to receive services anonymously and giving back by volunteering at local organizations. In doing so, I highlight multiple pathways through which residents of disadvantaged neighborhoods move from stigmatization to destigmatization in the welfare system.

Shared challenges, divergent practices. The impact of institutional frameworks on area-based initiatives in Barcelona and Paris

ABSTRACT In recent decades, the persisting inequalities in European cities have spurred the implementation of area-based initiatives (ABI) in the most disadvantaged neighbourhoods. This paper investigates how the interplay between diverse institutional frameworks and housing ownership regimes influences the design and execution of ABI policies in France and Spain. Focusing on the specific cases of Pla de Barris in Barcelona and Contrat de Ville in Paris, the study elucidates the strengths and limitations of different urban renewal strategies, emphasizing the imperative of a multi-level governance approach for effective ABIs.

Social determinants of health and outcome disparities in spine tumor surgery. Part 2: Neighborhood disadvantage and long-term outcomes.

Neighborhood-level resource disadvantage has been previously shown to predict extent of resection, oncological follow-up, adjuvant treatment, and clinical trial participation for malignancies, including glioblastoma. The authors aimed to characterize the association between neighborhood disadvantage and long-term outcomes after spine tumor surgery. The authors analyzed all patients who underwent surgery for primary or secondary (all metastatic pathologies) spine tumors at a single spinal oncology specialty center in the United States from 2015 to 2022. The Area Deprivation Index (ADI), a validated metric compositing 17 social determinants of health variables that ranges continuously from 0% (higher advantage) to 100% (higher disadvantage), was used to quantify neighborhood disadvantage. Patient addresses were matched to ADI on the basis of the census block of residence. Subsequently, the study population was dichotomized into advantaged (ADI 0%-33%) and disadvantaged (ADI 34%-100%) cohorts. The primary endpoint was functional status, as defined by Eastern Cooperative Oncology Group (ECOG) Performance Status Scale grade, with secondary endpoints including inpatient outcomes, mortality, readmissions, reoperations, and clinical research participation. Multivariable logistic, gamma log-link, and Cox regression adjusted for 14 confounders, including patient and oncological characteristics, general and tumor-related presenting severity, and treatment. In total, 237 patients underwent spine tumor surgery from 2015 to 2022, with an average age of 53.9 years, and 57.0% had primary tumors whereas 43.0% had secondary tumors; 55.3% (n = 131) were classified by ADI into the disadvantaged cohort. This cohort had higher rates of ambulation deficits on presentation (39.1% vs 23.5%, p = 0.015) and nonelective surgery (35.1% vs 23.6%, p = 0.030). Postoperatively, disadvantaged patients exhibited higher odds of residual tumor (OR 2.55, p = 0.026), especially for secondary tumors (OR 4.92, p = 0.045). Patients from disadvantaged neighborhoods additionally exhibited significantly higher odds of poor functional status at follow-up (OR 3.94, p = 0.002). Postoperative survival was 74.7% (mean follow-up 17.6 months), with the disadvantaged cohort experiencing significantly shorter survival (HR 1.92, p = 0.049). Moreover, this population had higher odds of readmission (OR 1.92, p = 0.046) and, for primary tumors, reoperation (OR 9.26, p = 0.005). Elective participation in prospective clinical research was lower among the disadvantaged cohort (OR 0.45, p = 0.016). Neighborhood disadvantage predicts higher rates of residual tumor, readmission, and reoperation, as well as poorer functional status, shorter postoperative survival, and decreased elective research participation. The ADI may be used to risk stratify spine oncology patients and guide targeted interventions to ameliorate neurosurgical disparities and to reduce barriers to research participation.

Neighborhood racial income inequality and cognitive health.

Neighborhood socioeconomic status (SES) has been linked to dementia, but the distribution of SES within a neighborhood may also matter. Data from 460 (47% Black, 46% White) older adults from the Michigan Cognitive Aging Project were linked to census tract-level data from the National Neighborhood Data Archive (NaNDA). Neighborhood SES included two composites reflecting disadvantage and affluence. Neighborhood racial income inequality was the ratio of median incomes for White versus Black residents. Generalized estimating equations examined associations between neighborhood factors and cognitive domains. Neighborhood racial income inequality was uniquely associated with worse cognitive health, and these associations did not differ by participant race. Neighborhood disadvantage was only associated with worse cognitive health among Black participants. Both the level and racial distribution of SES within a neighborhood may be relevant for dementia risk. Racial differences in the level and impact of neighborhood SES contribute to dementia inequalities. Black participants lived in neighborhoods with lower socioeconomic status (SES) than White participants, on average. Neighborhood SES and racial income inequality were associated with worse cognition. Effects of neighborhood racial income inequality did not differ across racial groups. Effects of neighborhood SES were only evident among Black participants.

Development of Composite Measures of Neighborhood Economic Factors for Use in Spinal Cord Injury Outcomes Studies: A Spinal Cord Injury Model Systems Database Study

ObjectiveTo develop composite measures of neighborhood economic factors for use with the national Spinal Cord Injury Model Systems (SCIMSs) database in cross-sectional and longitudinal investigations of the social determinants of health. DesignSecondary data analysis of administrative data from the 2009, 2014, and 2019 American Community Survey (ACS) 5-year estimates and survey data collected for the SCIMS database. SettingCommunity. ParticipantsThe validity of the neighborhood economic measures developed from the ACS data was tested with a sample of SCIMS participants who completed a follow-up interview between 2017 and 2021 (N=8,130). The predictive validity of the neighborhood measures was assessed with a subsample of cases with complete data on the outcome and covariate measures (N=6,457). InterventionsNot applicable. Main Outcome MeasuresA binary measure of self-rated health status (1=poor/fair health; 0=good/very good/excellent). ResultsA combination of panel review and data reduction techniques yielded 2 distinct measuring neighborhood socioeconomic status (SES) and neighborhood socioeconomic disadvantage that were validated using 3 waves of ACS data and the SCIMS data. The odds of reporting poor health were lower among people living in moderate- and high-SES neighborhoods and highest among people living in moderately and highly disadvantaged neighborhoods. The negative association between neighborhood SES and poor health was fully attenuated by differences in participants’ individual demographic and economic characteristics whereas the positive association between neighborhood disadvantage and poor health persisted after adjusting for individual differences. ConclusionsThe two composite measures of neighborhood economic factors developed by this study are robust in samples from different periods of time and valid for use with the SCIMS database. Future investigations conducting surveillance of the needs of the SCI population using this resource may consider using these measures to assess the effect of the social determinants of health in outcomes after SCI.

Neighborhood-Level Disparities in Hypertension Prevalence and Treatment Among Middle-Aged Adults

Hypertension in middle-aged adults (35-50 years) is associated with poorer health outcomes in late life. Understanding how hypertension varies by race and ethnicity across levels of neighborhood disadvantage may allow for better characterization of persistent disparities. To evaluate spatial patterns of hypertension diagnosis and treatment by neighborhood socioeconomic position and racial and ethnic composition. In this cross-sectional study of middle-aged adults in Cuyahoga County, Ohio, who encountered primary care in 2019, geocoded electronic health record data were linked to the area deprivation index (ADI), a neighborhood disadvantage measure, at the US Census Block Group level (ie, neighborhood). Neighborhoods were stratified by ADI quintiles, with the highest quintile indicating the most disadvantage. Data were analyzed between August 7, 2023, and June 1, 2024. Essential hypertension. The primary outcome was a clinician diagnosis of essential hypertension. Spatial analysis was used to characterize neighborhood-level patterns of hypertension prevalence and treatment. Interaction analysis was used to compare hypertension prevalence by racial and ethnic group within similar ADI quintiles. A total of 56 387 adults (median [IQR] age, 43.1 [39.1-46.9] years; 59.8% female) across 1157 neighborhoods, which comprised 3.4% Asian, 31.1% Black, 5.5% Hispanic, and 60.0% White patients, were analyzed. A gradient of hypertension prevalence across ADI quintiles was observed, with the highest vs lowest ADI quintile neighborhoods having a higher hypertension rate (50.7% vs 25.5%) and a lower treatment rate (61.3% vs 64.5%). Of the 315 neighborhoods with predominantly Black (>75%) patient populations, 200 (63%) had a hypertension rate greater than 35% combined with a treatment rate of less than 70%; only 31 of 263 neighborhoods (11.8%) comprising 5% or less Black patient populations met this same criterion. Compared with a spatial model without covariates, inclusion of ADI and percentage of Black patients accounted for 91% of variation in hypertension diagnosis prevalence among men and 98% among women. Men had a higher prevalence of hypertension than women across race and ADI quintiles, but the association of ADI and hypertension risk was stronger in women. Sex prevalence differences were smallest between Black men and women, particularly in the highest ADI quintile (1689 [60.0%] and 2592 [56.0%], respectively). These findings show an association between neighborhood deprivation and hypertension prevalence, with disparities observed particularly among Black patients, emphasizing a need for structural interventions to improve community health.

Territory and lack of water access: an educational experience in disadvantaged neighborhoods in Turbo, Antioquia (Colombia)

RESUMEN Esta reflexión emerge de un proyecto educativo orientado a mejorar algunos aspectos relacionados con el acceso y manejo del agua en tres barrios informales. El objetivo es reflexionar acerca de las nociones de territorio que se construyen en el contexto de proyectos educativos en comunidades que habitan barrios informales. El proyecto inició con la conformación de un grupo de participantes quienes realizaron la cartografía social de sus barrios para identificar aspectos críticos sobre agua y saneamiento. La validación de los mapas y los recorridos por cada sector aportaron elementos para los talleres relacionados con acceso, manejo, cuidado y derecho al agua, que posteriormente fueron multiplicados en cada comunidad. Este proceso permitió reconocer situaciones relacionadas con la negación del derecho al agua, el malestar, la tensión entre ilegalidad e informalidad, las maneras en que las comunidades resuelven sus necesidades y las relaciones que establecen con su territorio, en medio de grandes inequidades. En conclusión, existe una relación profunda entre salud y territorio, que se hace más evidente en comunidades en condiciones críticas. Los proyectos de educación para la salud requieren hacer un trabajo situado y establecer una mirada interdisciplinaria, que reconozca la complejidad e interdependencia de las dinámicas sociales y ambientales.