Neighborhood geographic disparities in heart attack and stroke mortality: comparison of global and local modeling approaches

Spatial Distribution of COVID-19 Hospitalizations and Associated Risk Factors in Health Insurance Data Using Bayesian Spatial Modelling

The onset of COVID-19 across the world has elevated interest in geographic information systems (GIS) for pandemic management. In Germany, however, most spatial analyses remain at the relatively coarse level of counties. In this study, we explored the spatial distribution of COVID-19 hospitalizations in health insurance data of the AOK Nordost health insurance. Additionally, we explored sociodemographic and pre-existing medical conditions associated with hospitalizations for COVID-19. Our results clearly show strong spatial dynamics of COVID-19 hospitalizations. The main risk factors for hospitalization were male sex, being unemployed, foreign citizenship, and living in a nursing home. The main pre-existing diseases associated with hospitalization were certain infectious and parasitic diseases, diseases of the blood and blood-forming organs, endocrine, nutritional and metabolic diseases, diseases of the nervous system, diseases of the circulatory system, diseases of the respiratory system, diseases of the genitourinary and symptoms, and signs and findings not classified elsewhere.

Proximity to coal-fired power plants and neurobehavioral symptoms in children

BACKGROUND

Coal-fired power plants are a major source of air pollution that can impact children's health. Limited research has explored if proximity to coal-fired power plants contributes to children's neurobehavioral disorders.

OBJECTIVE

This community-based study collected primary data to investigate the relationships of residential proximity to power plants and neurobehavioral problems in children.

METHODS

235 participants aged 6-14 years who lived within 10 miles of two power plants were recruited. Exposure to particulate matter ≤10 μm (PM10) was measured in children's homes using personal modular impactors. Neurobehavioral symptoms were assessed using the Child Behavior Checklist (CBCL). Multiple regression models were performed to test the hypothesized associations between proximity/exposure and neurobehavioral symptoms. Geospatial statistical methods were used to map the spatial patterns of exposure and neurobehavioral symptoms.

RESULTS

A small proportion of the variations of neurobehavioral problems (social problems, affective problems, and anxiety problems) were explained by the regression models in which distance to power plants, traffic proximity, and neighborhood poverty was statistically associated with the neurobehavioral health outcomes. Statistically significant hot spots of participants who had elevated levels of attention deficit hyperactivity disorder, anxiety, and social problems were observed in the vicinity of the two power plants.

SIGNIFICANCE

Results of this study suggest an adverse impact of proximity to power plants on children's neurobehavioral health. Although coal-fired power plants are being phased out in the US, health concern about exposure from coal ash storage facilities remains. Furthermore, other countries in the world are increasing coal use and generating millions of tons of pollutants and coal ash. Findings from this study can inform public health policies to reduce children's risk of neurobehavioral symptoms in relation to proximity to power plants.

Trends and Inequalities in the Incidence of Acute Myocardial Infarction among Beijing Townships, 2007-2018

Acute myocardial infarction (AMI) poses a serious disease burden in China, but studies on small-area characteristics of AMI incidence are lacking. We therefore examined temporal trends and geographic variations in AMI incidence at the township level in Beijing. In this cross-sectional analysis, 259,830 AMI events during 2007–2018 from the Beijing Cardiovascular Disease Surveillance System were included. We estimated AMI incidence for 307 consistent townships during consecutive 3-year periods with a Bayesian spatial model. From 2007 to 2018, the median AMI incidence in townships increased from 216.3 to 231.6 per 100,000, with a greater relative increase in young and middle-aged males (35–49 years: 54.2%; 50–64 years: 33.2%). The most pronounced increases in the relative inequalities was observed among young residents (2.1 to 2.8 for males and 2.8 to 3.4 for females). Townships with high rates and larger relative increases were primarily located in Beijing’s northeastern and southwestern peri-urban areas. However, large increases among young and middle-aged males were observed throughout peri-urban areas. AMI incidence and their changes over time varied substantially at the township level in Beijing, especially among young adults. Targeted mitigation strategies are required for high-risk populations and areas to reduce health disparities across Beijing.

Gender difference of geographic distribution of the stroke incidence affected by socioeconomic, clinical and urban-rural factors: an ecological study based on data from the Brest stroke registry in France

Background

Mapping the spatial distribution of disease occurrence is a strategy to identify contextual factors that could be useful for public health policies. The purpose of this ecological study was to examine to which extent the socioeconomic deprivation and the urbanization level can explain gender difference of geographic distribution in stroke incidence in Pays de Brest, France between 2008 and 2013.

Methods

Stroke cases aged 60 years or more were extracted from the Brest stroke registry and combined at the census block level. Contextual socioeconomic, demographic, and geographic variables at the census block level come from the 2013 national census. We used spatial and non-spatial regression models to study the geographic correlation between socioeconomic deprivation, degree or urbanization and stroke incidence. We generated maps using spatial geographically weighted models, after longitude and latitude smoothing and adjustment for covariates.

Results

Stroke incidence was comparable in women and men (6.26 ± 3.5 vs 6.91 ± 3.3 per 1000 inhabitants-year, respectively). Results showed different patterns of the distribution of stroke risk and its association with deprivation or urbanisation across gender. For women, stroke incidence was spatially homogeneous over the entire study area, but was associated with deprivation level in urban census blocks: age adjusted risk ratio of high versus low deprivation = 1.24, [95%CI 1.04–1.46]. For men, three geographic clusters were identified. One located in the northern rural and deprived census blocks with a 9–14% increase in the risk of stroke. Two others clusters located in the south-eastern (mostly urban part) and south-western (suburban and rural part) with low deprivation level and associated with higher risk of stroke incidence between (3 and 8%) and (8.5 and 19%) respectively. There were no differences in profile of cardiovascular risk factors, stroke type and stroke severity between clusters, or when comparing clusters cases to the rest of the study population.

Conclusions

Understanding whether and how neighborhood and patient’s characteristics influence stroke risk may be useful for both epidemiological research and healthcare service planning.

Sociodemographic Determinants of Acute Myocardial Infarction Hospitalization Risks in Florida

Background Identifying social determinants of myocardial infarction (MI) hospitalizations is crucial for reducing/eliminating health disparities. Therefore, our objectives were to identify sociodemographic determinants of MI hospitalization risks and to assess if the impacts of these determinants vary by geographic location in Florida. Methods and Results This is a retrospective ecologic study at the county level. We obtained data for principal and secondary MI hospitalizations for Florida residents for the 2005-2014 period and calculated age- and sex-adjusted MI hospitalization risks. We used a multivariable negative binomial model to identify sociodemographic determinants of MI hospitalization risks and a geographically weighted negative binomial model to assess if the strength of associations vary by location. There were 645 935 MI hospitalizations (median age, 72 years; 58.1%, men; 73.9%, white). Age- and sex-adjusted risks ranged from 18.49 to 69.48 cases/10 000 persons, and they were significantly higher in counties with low education levels (risk ratio [RR]=1.033, P<0.0001) and high divorce rate (RR, 0.995; P=0.018). However, they were significantly lower in counties with high proportions of rural (RR, 0.996; P<0.0001), black (RR, 1.026; P=0.032), and uninsured populations (RR, 0.983; P=0.040). Associations of MI hospitalization risks with education level and uninsured rate varied geographically (P for non-stationarity test=0.001 and 0.043, respectively), with strongest associations in southern Florida (RR for <high school education, 1.036-1.041; RR for uninsured rate, 0.971-0.976). Conclusions Black race, divorce, rural residence, low education level, and lack of health insurance were significant determinants of MI hospitalization risks, but associations with the latter 2 were stronger in southern Florida. Thus, interventions for addressing MI hospitalization risks need to prioritize these populations and allocate resources based on empirical evidence from global and local models for maximum efficiency and effectiveness.

Geographic disparities and temporal changes in risk of death from myocardial infarction in Florida, 2000-2014

Background

Identifying disparities in myocardial infarction (MI) burden and assessing its temporal changes are critical for guiding resource allocation and policies geared towards reducing/eliminating health disparities. Our objectives were to: (a) investigate the spatial distribution and clusters of MI mortality risk in Florida; and (b) assess temporal changes in geographic disparities in MI mortality risks in Florida from 2000 to 2014.

Methods

This is a retrospective ecologic study with county as the spatial unit of analysis. We obtained data for MI deaths occurring among Florida residents between 2000 and 2014 from the Florida Department of Health, and calculated county-level age-adjusted MI mortality risks and Spatial Empirical Bayesian smoothed MI mortality risks. We used Kulldorff’s circular spatial scan statistics and Tango’s flexible spatial scan statistics to identify spatial clusters.

Results

There was an overall decline of 48% in MI mortality risks between 2000 and 2014. However, we found substantial, persistent disparities in MI mortality risks, with high-risk clusters occurring primarily in rural northern counties and low-risk clusters occurring exclusively in urban southern counties. MI mortality risks declined in both low- and high-risk clusters, but the latter showed more dramatic decreases during the first nine years of the study period. Consequently, the risk difference between the high- and low-risk clusters was smaller at the end than at the beginning of the study period. However, the rates of decline levelled off during the last six years of the study, and there are signs that the risks may be on an upward trend in parts of North Florida. Moreover, MI mortality risks for high-risk clusters at the end of the study period were on par with or above those for low-risk clusters at the beginning of the study period. Thus, high-risk clusters lagged behind low-risk clusters by at least 1.5 decades.

Conclusion

Myocardial infarction mortality risks have decreased substantially during the last 15 years, but persistent disparities in MI mortality burden still exist across Florida. Efforts to reduce these disparities will need to target prevention programs to counties in the high-risk clusters.

Geographical inequalities in acute myocardial infarction beyond neighbourhood-level and individual-level sociodemographic characteristics: a Danish 10-year nationwide population-based cohort study

OBJECTIVE

This study examined whether geographical patterns in incident acute myocardial infarction (AMI) were explained by neighbourhood-level and individual-level sociodemographic characteristics.

DESIGN

An open cohort study design of AMI-free adults (age ≥30 years) with a residential location in Denmark in 2005-2014 was used based on nationwide administrative population and health register data linked by the unique personal identification number. Poisson regression of AMI incidence rates (IRs) with a geographical random effect component was performed using a Bayesian approach. The analysis included neighbourhood-level variables on income, ethnic composition, population density and population turnover and accounted for individual-level age, sex, calendar year, cohabitation status, income and education.

SETTING

Residents in Denmark (2005-2014).

PARTICIPANTS

The study population included 4 128 079 persons (33 907 796 person-years at risk) out of whom 98 265 experienced an incident AMI.

OUTCOME MEASURE

Incident AMI registered in the National Patient Register or the Register of Causes of Death.

RESULTS

Including individual and neighbourhood sociodemographic characteristics in the model decreased the variation in IRs of AMI. However, living in certain areas was associated with up to 40% increased IRs of AMI in the adjusted model and accounting for sociodemographic characteristics only moderately changed the geographical disease patterns.

CONCLUSIONS

Differences in sociodemographic characteristics of the neighbourhood and individuals explained part, but not all of the geographical inequalities in incident AMI. Prevention strategies should address the confirmed social inequalities in incident AMI, but also target the areas with a heavy disease burden to enable efficient allocation of prevention resources.

Association between local-level resources for home care and home deaths: A nationwide spatial analysis in Japan

Aim

Little is known about whether and how local-level resources regarding home care are associated with the prevalence of home deaths. We aimed to investigate whether geographic patterns of the resources for home care were associated with the prevalence of home deaths, taking spatial variation into consideration.

Methods

We conducted an ecological cross-sectional study in Japan using nationwide data in 2014. The areal unit was the municipality, the smallest administrative unit in Japan. We investigated the association between the percentage of home deaths and the resources of home care support clinics with available 24-hour-a-day functions, considering the geographic effect of neighboring municipalities by applying a geographically weighted regression model.

Results

The mean and standard deviation of the percentages of home deaths were 11.4% (5.0%), and those of the number of home care support clinics per 10,000 elderly population were 3.4 (3.7). The percentages of home deaths in neighboring municipalities tended to be significantly correlated (Moran’s I 0.34, p<0.001). Adjusting for the number of hospital beds, total population, and the socio-economic status of municipality, the results of an ordinary least squares regression model showed a positive correlation between the percentage of home deaths and the local resources for home care support clinics per 10,000 elderly population (regression coefficient 0.15, 95% confidence interval 0.07, 0.22), while the existence of spatial autocorrelation of the residual was suggested (Moran’s I of the residual 0.227, p<0.001). The geographically weighted regression model showed local regression coefficients varying across municipalities with a better model fit over the analogous ordinary least squares model (adjusted R² 0.414 vs. 0.131).

Conclusion

Home deaths were more prevalent in municipalities with greater home care resources. This association was geographically varied and further strengthened in some areas.

Congruence of Home, Social and Sex Neighborhoods among Men Who Have Sex with Men, NYCM2M Study

Substantial literature demonstrates the influence of the neighborhood environment on health behaviors and outcomes. But limited research examines on how gay and bisexual men experience and exist in various geographic and virtual spaces and how this relates to their sexual behavior. New York City Men 2 Men (NYCM2M) was a cross-sectional study designed to identify neighborhood-level characteristics within the urban environment that influence sexual risk behaviors, substance use, and depression among men who have sex with men (MSM) living in NYC. The sample was recruited using a modified venue-based time-space sampling methodology and through select websites and mobile applications. Whether key neighborhoods of human activity, where a participant resided (termed home), socialized (termed social), or had sex most often (termed sex), were the same or different was evaluated. "Congruence" (or the sameness) of home, social, and most often sex neighborhood was reported by 17 % of men, while 30 % reported that none of their neighborhoods were the same. The largest group of men (39 %) reported that their home and sex neighborhoods were the same but their social neighborhood was different while 10 % reported that their home neighborhood was different than their social and sex neighborhood; 5 % men reported same home and social neighborhoods with a different sex neighborhood. Complete neighborhood incongruence was highest among men who were Black and/or Latino, had lower education and personal income levels, and had greater financial insecurity. In adjusted analysis, serodiscordant condomless anal intercourse and condomless anal intercourse with partners from the Internet or mobile applications were significantly associated with having the same social and sex (but not home) neighborhoods. Understanding the complexity of how different spaces and places relate to the health and sexual behavior of MSM is essential for focusing interventions to best reach various populations of interest.

Regional differences of standardised mortality rates for ischemic heart diseases in the Slovak Republic for the period 1996-2013 in the context of income inequality

BACKGROUND

The aim of paper is to analyse the development of standardised mortality rates for ischemic heart diseases in relation to the income inequality in the regions of Slovakia. This paper assesses different types of income indicators, such as mean equivalised net income per household, Gini coefficient, unemployment rate, at risk of poverty threshold (60 % of national median), S80/S20 and their effect on mortality.

METHODS

Using data from the Slovak mortality database 1996-2013, the method of direct standardisation was applied to eliminate variances resulted from differences in age structures of the population across regions and over time. To examine the relationships between income indicators and standardised mortality rates, we used the tools of descriptive statistics and methods of correlation and regression analysis.

RESULTS

At first, we show that Slovakia has the worst values of standardised mortality rates for ischemic heart diseases in EU countries. Secondly, mortality rates are significantly higher for males compared with females. Thirdly, mortality rates are improving from Eastern Slovakia to Western Slovakia; additionally, high differences in the results of variability are seen among Slovak regions. Finally, the unemployment rate, the poverty rate and equivalent disposable income were statistically significant income indicators.

CONCLUSIONS

Main contribution of paper is to demonstrate regional differences between mortality and income inequality, and to point out the long-term unsatisfactory health outcomes.

Spatial variations in cervical cancer prevention in Colombia: Geographical differences and associated socio-demographic factors

We examined spatial variations in the frequencies of women who had not heard of human papillomavirus vaccination (NHrd-Vac) and who had not had Pap testing (NHd-Pap) among Colombian administrative divisions (departments), before and after considering differences in socio-demographic factors. Following global and local tests for clustering, Bayesian Poisson hierarchical models identified department factors associated with NHrd-Vac and NHd-Pap, as well as the extent of the spatially structured and unstructured heterogeneity. Models of spatial variations for both outcomes included the department percentage of women with subsidised health insurance. The relative risks of NHrd-Vac and NHd-Pap were highest in several departments adjacent to the Colombian border. Our finding that the risk of not having adequate access to cervical cancer (CC) prevention programmes in Colombia was location-dependent, could be used to focus resources for CC prevention programmes.

Exploring spatial patterns in the associations between local AIDS incidence and socioeconomic and demographic variables in the state of Rio de Janeiro, Brazil

Access to antiretroviral therapy (ART), universally provided in Brazil since 1996, resulted in a reduction in overall morbidity and mortality due to AIDS or AIDS-related complications, but in some municipalities of Rio de Janeiro, AIDS incidence remains high. Public health surveillance remains an invaluable tool for understanding current AIDS epidemiologic patterns and local socioeconomic and demographic factors associated with increased incidence. Geographically Weighted Poisson Regression (GWPR) explores spatial varying impacts of these factors across the study area focusing attention on local variations in ecological associations. The set of sociodemographic variables under consideration revealed significant associations with local AIDS incidence and these associations varied geographically across the study area. We find the effects of predictors on AIDS incidence are not constant across the state, contrary to assumptions in the global models. We observe and quantify different local factors driving AIDS incidence in different parts of the state.

Does Place of Residence or Time of Year Affect the Risk of Stroke Hospitalization and Death? A Descriptive Spatial and Temporal Epidemiologic Study

Background

Identifying geographic areas with significantly high risks of stroke is important for informing public health prevention and control efforts. The objective of this study was to investigate geographic and temporal patterns of stroke hospitalization and mortality risks so as to identify areas and seasons with significantly high burden of the disease in Florida. The information obtained will be useful for resource allocation for disease prevention and control.

Methods

Stroke hospitalization and mortality data from 1992 to 2012 were obtained from the Florida Agency for Health Care Administration. Age-adjusted stroke hospitalization and mortality risks for time periods 1992–94, 1995–97, 1998–2000, 2001–03, 2004–06, 2007–09 and 2010–12 were computed at the county spatial scale. Global Moran’s I statistics were computed for each of the time periods to test for evidence of global spatial clustering. Local Moran indicators of spatial association (LISA) were also computed to identify local areas with significantly high risks.

Results

There were approximately 1.5 million stroke hospitalizations and over 196,000 stroke deaths during the study period. Based on global Moran’s I tests, there was evidence of significant (p<0.05) global spatial clustering of stroke mortality risks but no evidence (p>0.05) of significant global clustering of stroke hospitalization risks. However, LISA showed evidence of local spatial clusters of both hospitalization and mortality risks with significantly high risks being observed in the north while the south had significantly low risks of stroke deaths. There were decreasing temporal trends and seasonal patterns of both hospitalization and mortality risks with peaks in the winter.

Conclusions

Although stroke hospitalization and mortality risks have declined in the past two decades, disparities continue to exist across Florida and it is evident from the results of this study that north Florida may, in fact, be part of the stroke belt despite not being in any of the traditional stroke belt states. These findings are useful for guiding public health efforts to reduce/eliminate inequities in stroke outcomes and inform policy decisions. There is need to continually identify populations with significantly high risks of stroke to better guide the targeting of limited resources to the highest risk populations.

Exploring the Spatial Association between Social Deprivation and Cardiovascular Disease Mortality at the Neighborhood Level

Cardiovascular disease (CVD), the leading cause of death in the United States, is impacted by neighborhood-level factors including social deprivation. To measure the association between social deprivation and CVD mortality in Harris County, Texas, global (Ordinary Least Squares (OLS) and local (Geographically Weighted Regression (GWR)) models were built. The models explored the spatial variation in the relationship at a census-tract level while controlling for age, income by race, and education. A significant and spatially varying association (p < .01) was found between social deprivation and CVD mortality, when controlling for all other factors in the model. The GWR model provided a better model fit over the analogous OLS model (R² = .65 vs. .57), reinforcing the importance of geography and neighborhood of residence in the relationship between social deprivation and CVD mortality. Findings from the GWR model can be used to identify neighborhoods at greatest risk for poor health outcomes and to inform the placement of community-based interventions.