The Impact of Socioeconomic Factors, Coverage and Access to Health on Heart Ischemic Disease Mortality in a Brazilian Southern State: A Geospatial Analysis

Untangling the Complex Multidimensionality of the Social Determinants of Cardiovascular Health: A Systematic Review

BACKGROUND

The cardiovascular literature is limited by the lack of consensus on what are the best metrics for reporting social determinants of health (SDH) or social deprivation, and if they should be reported as a single metric or separately by their domains.

METHODS

A systematic review of the literature on cardiovascular surgeries and procedures was conducted, identifying articles from January 1, 2010, to December 31, 2023, that studied the relationship between health outcomes after cardiovascular procedures or surgeries and SDH/social deprivation. The cardiovascular procedures/surgeries of interest were coronary and valve surgeries and procedures including coronary artery bypass grafting (CABG), percutaneous coronary intervention (PCI), valve replacement or repair, and transcatheter aortic valve intervention.

RESULTS

After screening 638 articles, we identified 47 papers that met our inclusion and exclusion criteria. The most common procedure evaluated was CABG and PCI; 46 of the studies focused on these 2 procedures. Almost all of the articles reported a different metric for SDH/social deprivation (41 different metrics); despite this, all of the metrics showed a consistent relationship with worse outcomes associated with greater degrees of SDH/deprivation. Only 9 reported on the individual domains of SDH/social deprivation; 3 studies showed a discordant relationship.

CONCLUSIONS

Although our systematic review identified numerous articles evaluating the relationship between SDH/social deprivation in cardiovascular disease, there was substantial heterogeneity in which metric was used and how it was reported. This reinforces the need for standards as to the best metrics for SDH/social deprivation as well as best practices for reporting.

Mortality in Women with Coronary Artery Disease in Paraná State, Brazil: A Bayesian Spatiotemporal Analysis

Background

Mortality resulting from coronary artery disease (CAD) among women is a complex issue influenced by many factors that encompass not only biological distinctions but also sociocultural, economic, and healthcare-related components. Understanding these factors is crucial to enhance healthcare provisions. Therefore, this study seeks to identify the social and clinical variables related to the risk of mortality caused by CAD in women aged 50 to 79 years old in Paraná state, Brazil, between 2010 and 2019.

Methods

This is an ecological study based on secondary data sourced from E-Gestor, IPARDES, and DATASUS. We developed a model that integrates both raw and standardized coronary artery disease (CAD) mortality rates, along with sociodemographic and healthcare service variables. We employed Bayesian spatiotemporal analysis with Markov Chain Monte Carlo simulations to assess the relative risk of CAD mortality, focusing specifically on women across the state of Paraná.

Results

A total of 14,603 deaths from CAD occurred between 2010 and 2019. Overall, temporal analysis indicates that the risk of CAD mortality decreased by around 22.6% between 2010 (RR of 1.06) and 2019 (RR of 0.82). This decline was most prominent after 2014. The exercise stress testing rate, accessibility of cardiology centers, and IPARDES municipal performance index contributed to the reduction of CAD mortality by approximately 4%, 8%, and 34%, respectively. However, locally, regions in the Central-West, Central-South, Central-East, and Southern regions of the Central-North parts of the state exhibited risks higher-than-expected.

Conclusion

In the last decade, CAD-related deaths among women in Paraná state decreased. This was influenced by more exercise stress testing, better access to cardiology centers, improved municipal performance index. Yet, elevated risks of deaths persist in certain regions due to medical disparities and varying municipal development. Therefore, prioritizing strategies to enhance women's access to cardiovascular healthcare in less developed regions is crucial.

Geospatial analysis of the hospitalisation rate of patients with rheumatoid arthritis in Hunan: a cross-sectional Chinese study

OBJECTIVE

Little is known about spatial variability of hospitalisation rate (HR) of patients with rheumatoid arthritis (RA) worldwide, especially in China.

METHODS

A cross-sectional study was conducted among patients with RA admitted to hospitals in Hunan Province. Global Moran's I and local indicators of spatial association were used to explore the geospatial pattern of the HR of patients with RA. Generalised estimating equation analysis and geographically weighted regression were used to identify the potential influencing factors of the HR of patients with RA.

RESULTS

There were a total of 11 599 admissions, and the average HR was 1.57 per 10 000 population in Hunan. We detected different cluster patterns of the HR among patients with RA by local indicators of spatial association. Age, ethnicity, average temperature, average temperature range, average rainfall, regions, gross domestic product per capita, and doctors and hospitals per 10 000 people were risk factors for the HR. However, only average temperature, gross domestic product per capita and hospitals per 10 000 people showed different regression coefficients on the HR in different counties. The increase in hospitals increased the probability of HR from east to west in Hunan with a positive coefficient, while temperature decreases increased the risk of HR from south to north negatively. Similarly, the growth of gross domestic product per capita decreased the probability of HR from southwest to northeast.

CONCLUSION

A non-random spatial distribution of the HR of patients with RA was demonstrated in Hunan, and average temperature, gross domestic product per capita and hospitals per 10 000 people showed different regression coefficients on the HR in different counties. Our study indicated that spatial and geostatistics may be useful approaches for further study among patients with RA.

Impact of invasive fungal infections in men from a state in southern Brazil: A geospatial analysis

OBJECTIVE

To analyse the records of male hospitalisation for fungal infections, including their spatial distribution and the main invasive epidemiological and sociodemographic characteristics in the State of Paraná, Brazil.

METHODS

Spatial analysis based on data from male admission records for invasive fungal infections (IFIs) in the State of Paraná, from 2015 to 2019. Data were taken from the hospital records obtained in the Hospital Information System of the Unified Health System, being collected, georeferenced and analysed to infer the existence of autocorrelation with the hospitalisation rates in the state.

RESULTS

From 2015 to 2019, there were 385 cases of IFIs in men, being more prevalent in white individuals aged 61-70 years. We observed that the metropolitan, southeast, central-eastern, north-central, northwestern and western regions formed high-high clusters, with regions with a high number of registered cases. In the regression, there was an association with socioeconomic and demographic factors that showed a correlation with the rates of hospitalisation for IFIs.

CONCLUSION

The study draws attention to Paraná as an endemic region for paracoccidioidomycosis, in addition to presenting high rates of nosocomial fungal infections. We also emphasise the importance of compulsory notification in the state and in the country to gain greater control over the incidence and prevalence of cases and to incentivise the creation of public policies for the prevention of IFIs.

Modelling geographical heterogeneity of diabetes prevalence and socio-economic and built environment determinants in Saudi City - Jeddah

Type-2 diabetes is a growing lifestyle disease mainly due to increasing physical inactivity but also associated with various other variables. In Saudi Arabia, around 58.5% of the population is deemed to be physically inactive. Against this background, this study attempts explore the spatial heterogeneity of Type-2 diabetes prevalence in Jeddah and to estimate various socio-economic and built environment variables contributing to the prevalence of this disease based on modelling by ordinary least squares (OLS), weighted regression (GWR) and multi-scale geographically weighted (MGWR). Our OLS results suggest that income, population density, commercial land use and Saudi population characteristics are statistically significant for Type-2 diabetes prevalence. However, by the GWR model, income, commercial land use and Saudi population characteristics were significantly positive while population density was significantly negative in this model for 70.6%, 9.1%, 26.6% and 58.7%, respectively, out of 109 districts investigated; by the MGWR model, the corresponding results were 100%, 22%, 100% and 100% of the districts. With the given data, the corrected Akaike information criterion (AICc), the adjusted R2, the log-likelihood and the residual sum of squares (RSS) indices demonstrated that the MGWR model outperformed the GWR and OLS models explaining 29% more variance than the OLS model, and 10.2% more than the GWR model. These results support the development of evidence-based policies for the spatial allocation of health associated resources for the control of Type-2 diabetes in Jeddah and other cities in the Arabian Gulf.

Geospatial Social Determinants of Health Correlate with Disparities in Syphilis and Congenital Syphilis Cases in California

Syphilis and congenital syphilis (CS) are increasing in California (CA). From 2015 through 2019, for example, CA cases of early syphilis among reproductive-age females (15−44) and CS each increased by >200%. Certain populations—including people experiencing homelessness, using drugs, and/or belonging to certain racial/ethnic groups—have been disproportionately impacted. We hypothesized that geospatial social determinants of health (SDH) contribute to such health inequities. To demonstrate this, we geospatially described syphilis in CA using the Healthy Places Index (HPI). The HPI is a composite index that assigns a score to each CA census tract based on eight socioeconomic characteristics associated with health (education, housing, transportation, neighborhood conditions, clean environment, and healthcare access as well as economic and social resources). We divided CA census tracts into four quartiles based on HPI scores (with the lowest quartile having the least healthy socioeconomic and environmental conditions), then used 2013−2020 CA sexually transmitted diseases surveillance data to compare overall syphilis (among adults and adolescents) and CS case counts, incidence rates (per 100,000 population or live births), and incidence rate ratios (IRRs) among these quartiles. From 2013 to 2020, across all stages of syphilis and CS, disease burden was greatest in the lowest HPI quartile and smallest in the highest quartile (8308 cases (representing 33.2% of all incidents) versus 3768 (15.1%) for primary and secondary (P&S) syphilis; 5724 (31.6%) versus 2936 (16.2%) for early non-primary non-secondary (NPNS) syphilis; 11,736 (41.9%) versus 3026 (10.8%) for late/unknown duration syphilis; and 849 (61.9%) versus 57 (4.2%) for CS; all with p < 0.001). Using the highest HPI quartile as a reference, the IRRs in the lowest quartile were 17 for CS, 4.5 for late/unknown duration syphilis, 2.6 for P&S syphilis, and 2.3 for early NPNS syphilis. We thus observed a direct relationship between less healthy conditions (per HPI) and syphilis/CS in California, supporting our hypothesis that SDH correlate with disparities in syphilis, especially CS. HPI could inform allocation of resources to: (1) support communities most in need of assistance in preventing syphilis/CS cases and (2) reduce health disparities.

Emergency Care Gap in Brazil: Geographical Accessibility as a Proxy of Response Capacity to Tackle COVID-19

Background: The new coronavirus disease (COVID-19) has claimed thousands of lives worldwide and disrupted the health system in many countries. As the national emergency care capacity is a crucial part of the COVID-19 response, we evaluated the Brazilian Health Care System response preparedness against the COVID-19 pandemic.

Methods: A retrospective and ecological study was performed with data retrieved from the Brazilian Information Technology Department of the Public Health Care System. The numbers of intensive care (ICU) and hospital beds, general or intensivist physicians, nurses, nursing technicians, physiotherapists, and ventilators from each health region were extracted. Beds per health professionals and ventilators per population rates were assessed. A health service accessibility index was created using a two-step floating catchment area (2SFCA). A spatial analysis using Getis-Ord Gi^* was performed to identify areas lacking access to high-complexity centers (HCC).

Results: As of February 2020, Brazil had 35,682 ICU beds, 426,388 hospital beds, and 65,411 ventilators. In addition, 17,240 new ICU beds were created in June 2020. The South and Southeast regions have the highest rates of professionals and infrastructure to attend patients with COVID-19 compared with the northern region. The north region has the lowest accessibility to ICUs.

Conclusions: The Brazilian Health Care System is unevenly distributed across the country. The inequitable distribution of health facilities, equipment, and human resources led to inadequate preparedness to manage the COVID-19 pandemic. In addition, the ineffectiveness of public measures of the municipal and federal administrations aggravated the pandemic in Brazil.