The Neighborhood Where You Live Is a Risk Factor for Stroke

Geospatial Modeling Methods in Epidemiological Kidney Research: An Overview and Practical Example

Geospatial modeling methods in population-level kidney research have not been used to full potential because few studies have completed associative spatial analyses between risk factors and exposures and kidney conditions and outcomes. Spatial modeling has several advantages over traditional modeling, including improved estimation of statistical variation and more accurate and unbiased estimation of coefficient effect direction or magnitudes by accounting for spatial data structure. Because most population-level kidney research data are geographically referenced, there is a need for better understanding of geospatial modeling for evaluating associations of individual geolocation with processes of care and clinical outcomes. In this review, we describe common spatial models, provide details to execute these analyses, and perform a case-study to display how results differ when integrating geographic structure. In our case-study, we used U.S. nationwide 2019 chronic kidney disease (CKD) data from Centers for Disease Control and Prevention's Kidney Disease Surveillance System and 2006 to 2010 U.S. Environmental Protection Agency environmental quality index (EQI) data and fit a nonspatial count model along with global spatial models (spatially lagged model [SLM]/pseudo-spatial error model [PSEM]) and a local spatial model (geographically weighted quasi-Poisson regression [GWQPR]). We found the SLM, PSEM, and GWQPR improved model fit in comparison to the nonspatial regression, and the PSEM model decreased the positive relationship between EQI and CKD prevalence. The GWQPR also revealed spatial heterogeneity in the EQI-CKD relationship. To summarize, spatial modeling has promise as a clinical and public health translational tool, and our case-study example is an exhibition of how these analyses may be performed to improve the accuracy and utility of findings.

Fishing for health: Neighborhood variation in fish intake, fish quality and association with stroke risk among older adults in the Cardiovascular Health Study

BACKGROUND AND AIMS

Fish consumption has been associated with better health outcomes. Dietary patterns may vary substantially by neighborhood of residence. However, it is unclear if the benefits of a healthy diet are equivalent in different communities. This study examines associations of fish consumption with stroke incidence and stroke risk factors, and whether these differ by neighborhood socioeconomic status (NSES).

METHODS AND RESULTS

We studied 4007 participants in the Cardiovascular Health Study who were 65 years or older and recruited between 1989 and 1990 from 4 US communities. Outcomes included fish consumption type (bakes/broiled vs. fried) and frequency, stroke incidence, and stroke risk factors. Multilevel regressions models were used to estimate fish consumption associations with clinical outcomes. Lower NSES was associated with higher consumption of fried fish (aOR = 1.47, 95% CI: 1.10-1.98) and lower consumption of non-fried fish (0.64, 0.47-0.86). Frequent fried fish (11.9 vs. 9.2 person-years for at least once weekly vs. less than once a month, respectively) and less frequent non-fried fish (17.7 vs. 9.6 person-years for less than once a month vs. at least once weekly, respectively) were independently associated with an increased risk of stroke (p-values < 0.05). However, among those with similar levels of healthy fish consumption, residents with low NSES had less benefit on stroke risk reduction, compared with high NSES.

CONCLUSION

Fish consumption type and frequency both impact stroke risk. Benefits of healthy fish consumption differ by neighborhood socioeconomic status.

Neighbourhood Socioeconomic Processes and Dynamics and Healthy Ageing: A Scoping Review

Elderly citizens are concentrated in urban areas and are particularly affected by the immediate residential environment. Cities are unequal and segregated places, where there is an intensification of urban change processes such as gentrification and displacement. We aimed to understand how neighbourhood socioeconomic processes and dynamics influence older people’s health. Three bibliographic databases—PubMed, Web of Science, and Scopus—were used to identify evidence of the influence of neighbourhood socioeconomic deprivation, socio-spatial segregation, urban renewal, and gentrification on healthy ageing. We followed the method of Arksey and O’Malley, Levac and colleagues, the Joanna Briggs Institute, and the PRISMA-ScR. The included studies (n = 122) were published between 2001 and 2021. Most evaluated neighbourhood deprivation (n = 114), followed by gentrification (n = 5), segregation (n = 2), and urban renewal (n = 1). Overall, older people living in deprived neighbourhoods had worse healthy ageing outcomes than their counterparts living in more advantaged neighbourhoods. Older adults pointed out more negative comments than positive ones for gentrification and urban renewal. As to segregation, the direction of the association was not entirely clear. In conclusion, the literature has not extensively analysed the effects of segregation, gentrification, and urban renewal on healthy ageing, and more quantitative and longitudinal studies should be conducted to draw better inferences.

Is Population Density Associated with Non-Communicable Disease in Western Developed Countries? A Systematic Review

Over the last three decades, researchers have investigated population density and health outcomes at differing scale. There has not been a systematic review conducted in order to synthesise this evidence. Following the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines, we systematically reviewed quantitative evidence published since 1990 on population density and non-communicable disease (NCD) within Westernised countries. Fifty-four studies met the inclusion criteria and were evaluated utilising a quality assessment tool for ecological studies. High population density appears to be associated with higher mortality rates of a range of cancers, cardiovascular disease and COPD, and a higher incidence of a range of cancers, asthma and club foot. In contrast, diabetes incidence was found to be associated with low population density. High and low population density are therefore risk markers for a range of NCDs, indicating that there are unidentified factors and mechanisms underlying aetiology. On closer examination, our synthesis revealed important and complex relationships between population density, the built environment, the nature of greenspace and man-made exposures. In light of increasing rates of morbidity and mortality, future research is required to investigate these associations in order to establish causative agents for each NCD.

Association of Socioeconomic Status With Ischemic Stroke Survival

Background and Purpose- The aim of the study was to determine the impact of individuals' socioeconomic status and their Primary Care Service Area Socioeconomic Index on survival after ischemic stroke. Methods- We conducted a nationwide population-based cohort study in Catalonia, Spain. We included all patients with first ischemic stroke admitted to a public hospital between January 1, 2015, and December 31, 2016. We measured both individual socioeconomic status (categorized as exempts, <€18 000 [$US 20 468] income per year, and >€18 000 income per year) and Primary Care Service Area Socioeconomic Index (from 0 to 100 categorized in quartiles). We used mixed-effects logistic and survival models to estimate odds ratios and hazard ratios for the short- (30 days) and the long-term (3 years) all-cause case fatality rates by individuals' socioeconomic status groups. Results- The cohort consisted of 16 344 ischemic stroke patients with 24 638 person-years of follow-up. We did not find an association between the lowest socioeconomic individual status and short-term survival (odds ratio, 1.03; 95% CI, 0.76-1.40), although we found it in patients with <€18 000 income/year (odds ratio, 1.26; 95% CI, 1.10-1.45). At long-term, after adjustment, we observed a gradient in mortality risk with decreasing individual socioeconomic status (hazard ratio, 1.52; 95% CI, 1.30-1.77). The Primary Care Service Area Socioeconomic Index had only an influence on short-term survival (odds ratio, 1.19; 95% CI, 1.03-1.37). Conclusions- Individuals' socioeconomic status was associated with short- and long-term survival in patients with ischemic stroke. Conversely, Primary Care Service Area Socioeconomic Index measures had an influence only in short-term survival. A small fraction of this association is due to differences in comorbidity and cardiovascular risk factors. Interventions addressing both individuals' and primary care service socioeconomic aspects might eventually affect differently short- and long-term survival.

Neighborhood socioeconomic index and stroke incidence in a national cohort of blacks and whites

OBJECTIVE

To assess the relationship between neighborhood socioeconomic characteristics and incident stroke in a national cohort of black and white participants.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Emergency transport of stroke suspects in a rural state: opportunities for improvement

INTRODUCTION

Time delay is the key obstacle for receiving successful stroke treatment. Alteplase therapy must start within 4.5 hours from stroke occurrence. Rapid transport to a primary stroke center (PSC) or acute stroke-ready hospital (ASRH) by the emergency medical system (EMS) paramedics is vital. We determined transport time and destination data for EMS-identified and -delivered stroke suspects in Arkansas during 2013. Our objective was to analyze transport time and the hospital qualification for stroke care across the state.

METHODS

The state's 75 counties were placed into 8 geographical regions (R1-R8). Transport time and hospital qualification were determined for all EMS-identified strokes. Each hospital's stroke care status was categorized as PSC, ASRH, a nonspecialty or unknown care facility (NSCF), out-of-state, or nonapplicable designation facilities.

RESULTS

There were 9588 EMS stroke ground transports with median within-region transport times of 29-40 minutes. Statewide, only 65% of EMS-transported stroke patients were transported to either PSC (12%) or ASRH (53%) facilities. One-third of the patients (30.6%) were delivered to NSCFs, where acute stroke therapy may rarely be performed. Regions with the highest suspected-stroke cases per capita also had the highest percentage of transports to NSCFs.

CONCLUSION

With only a few PSCs in Arkansas, EMS agencies should prioritize transporting stroke patients to ASRHs when PSCs are not regionally located.

Comparison of small-area deprivation measures as predictors of chronic disease burden in a low-income population

Background

Measures of small-area deprivation may be valuable in geographically targeting limited resources to prevent, diagnose, and effectively manage chronic conditions in vulnerable populations. We developed a census-based small-area socioeconomic deprivation index specifically to predict chronic disease burden among publically insured Medicaid recipients in South Carolina, a relatively poor state in the southern United States. We compared the predictive ability of the new index with that of four other small-area deprivation indicators.

Methods

To derive the ZIP Code Tabulation Area-Level Palmetto Small-Area Deprivation Index (Palmetto SADI), we evaluated ten census variables across five socioeconomic deprivation domains, identifying the combination of census indicators most highly correlated with a set of five chronic disease conditions among South Carolina Medicaid enrollees. In separate validation studies, we used both logistic and spatial regression methods to assess the ability of Palmetto SADI to predict chronic disease burden among state Medicaid recipients relative to four alternative small-area socioeconomic deprivation measures: the Townsend index of material deprivation; a single-variable poverty indicator; and two small-area designations of health care resource deprivation, Primary Care Health Professional Shortage Area and Medically Underserved Area/Medically Underserved Population.

Results

Palmetto SADI was the best predictor of chronic disease burden (presence of at least one condition and presence of two or more conditions) among state Medicaid recipients compared to all alternative deprivation measures tested.

Conclusions

A low-cost, regionally optimized socioeconomic deprivation index, Palmetto SADI can be used to identify areas in South Carolina at high risk for chronic disease burden among Medicaid recipients and other low-income Medicaid-eligible populations for targeted prevention, screening, diagnosis, disease self-management, and care coordination activities.

Historical Differences in School Term Length and Measured Blood Pressure: Contributions to Persistent Racial Disparities among US-Born Adults

INTRODUCTION

Legally mandated segregation policies dictated significant differences in the educational experiences of black and white Americans through the first half of the 20th century, with markedly lower quality in schools attended by black children. We determined whether school term length, a common marker of school quality, was associated with blood pressure and hypertension among a cohort of older Americans who attended school during the de jure segregation era.

METHODS

National Health and Nutrition Examination Survey I and II data were linked to state level historical information on school term length. We used race and gender-stratified linear regression models adjusted for age, state and year of birth to estimate effects of term length on systolic and diastolic blood pressure (SBP and DBP) and hypertension for US-born adults. We also tested whether correcting years of schooling for term length differences attenuated estimated racial disparities.

RESULTS

Among black women, 10% longer school term was associated with lower SBP, DBP and hypertension prevalence (2.1 mmHg, 1.0 mmHg, and 5.0 percentage points respectively). Associations for whites and for black men were not statistically significant. Adjustment for education incorporating corrections for differences in school term length slightly attenuated estimated racial disparities.

CONCLUSIONS

Longer school term length predicted better BP outcomes among black women, but not black men or whites.