Is socioeconomic segregation of the poor associated with higher premature mortality under the age of 60? A cross-sectional analysis of survey data in major Indian cities

COVID-19's effect on healthcare disparities: delivery, reimbursement, and premature mortality in residentially segregated populations

Introduction

Spatially segregated, socio-economically deprived communities often face significant health disparities. This paper evaluates the impact of COVID-19 on healthcare delivery and reimbursement disparities in Hungary, particularly focusing on segregated populations.

Aims

To examine healthcare utilization and reimbursement patterns among patients in segregated areas (SA) and non-segregated or complementary areas (CA) during the first year of the COVID-19 pandemic, compared to pre-pandemic levels, and to understand how these patterns influenced overall health outcomes.

Methods

A cross-sectional study using 2019 and 2020 healthcare data from all Hungarian general medical practices (GMPs) was conducted. Segregated areas were identified based on governmental criteria, and healthcare indicators were standardized by age, sex, and socioeconomic status. Key indicators included General Practitioner (GP) visits, outpatient services, Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) usage, hospitalizations, healthcare reimbursement, and premature mortality.

Results

In 2020, there was a notable reduction in healthcare services utilization due to COVID-19 restrictions, with GP visits declining by 10.43% in SAs and 4.13% in CAs. Outpatient services decreased by 19.16% in SAs and 12.45% in CAs, while hospitalizations dropped by over 23.52%. Despite these reductions, the relative risk (RR) of healthcare service use remained higher in SAs compared to CAs (RR = 1.22, 95% CI: 1.219;1.223). Healthcare reimbursement was significantly lower in SAs (RR = 0.940, 95% CI: 0.929;0.951), and premature mortality was higher (RR = 1.184, 95% CI: 1.087;1.289).

Conclusion

The COVID-19 pandemic led to a significant reduction in healthcare utilization across Hungary. However, segregated populations in 2020 continued to have higher healthcare service use but received lower reimbursement, indicating persistent healthcare disparities. The consistently higher premature mortality rate in SAs underscores the need for targeted interventions and improved healthcare access and quality for vulnerable communities. Future policies should be built on data from comprehensive monitoring systems to address and mitigate these disparities, ensuring equitable healthcare access in and out of health crises.

Measuring Spatial Social Polarization in Public Health Research: A Scoping Review of Methods and Applications

Spatial social polarization (SSP) refers to the uneven spatial distribution and subsequent concentration of polarized social and/or economic groups in a specified geographic area. However, there is heterogeneity in how SSP is measured and operationalized in research. To this end, we conducted a scoping review to characterize the use of SSP measures in public health research, providing a foundation for those seeking to navigate this complex literature, select measurement options, and identify opportunities for methodological development. Using a structured search strategy, we searched PubMed for any primary research, published since 2007, that examined the relationship between SSP and health outcomes. Across 117 included studies, we found a body of evidence that was primarily set in the United States (n = 104), published between 2020 and 2022 (n = 52), and focused on non-communicable diseases (n = 40). We found that defining SSP in the context of privilege, deprivation, and segregation returns a variety of measures. Among measures, we categorized 18 of them as SSP measures, with the Index of Concentration at the Extremes (n = 43) being the most common, and 5 of them as composite indices based on numerous underlying variables spanning several domains like education and race/ethnicity. While most employed a single SSP measure (n = 64), some included up to 5 measures to examine the robustness of findings or to identify how a multidimensional approach to SSP affected associations. Our findings fill a critical literature gap by summarizing options for operationalizing SSP measures and documenting their respective methodologies. Future research should consider using multiple SSP measures to capture the multidimensionality of SSP, widen the scope of health outcomes, and clearly explain the choice of measure(s) and methods used to derive them. Our findings can inform future research questions and help guide researchers in the selection and utilization of the various SSP measures.

Relationship between body mass index and residential segregation in large cities of Latin America

BACKGROUND

Obesity is a global health problem, and its connection with social and environmental factors is well-established. Social factors, such as urban segregation, may impact obesity through various mechanisms, including food and physical activity environments, as well as social norms and networks. This multilevel study aims to examine the effect of socio-economic residential segregation of Latin American cities on the obesity of individuals within those cities.

METHODS

We analyzed data from national surveys for a total of 59,340 individuals of 18-70 years of age, conducted in 156 cities across Brazil, Chile, Colombia, and Mexico between 2007 and 2013. We adjusted two-level linear mixed models for body mass index (BMI) stratified by sex and country, controlling for age, educational level and poverty. Separate models were built for dissimilarity and isolation segregation indices.

RESULTS

The relationships between segregation indices and BMI were mostly not statistically significant, and in some cases, they were opposite to what was expected. The only significant relationships were observed in Colombian men, using the dissimilarity index (-7.5 [95% CI: -14.4, -0.5]) and in Colombian women, using the isolation index (-7.9 [95% CI: -14.1, -1.7]).

CONCLUSIONS

While individual-level factors cannot fully explain differences among people in the same city, segregation indices may help. However, we found that in some cases, the relationship between BMI and segregation indices is opposite to what is expected based on prior literature. This should be considered in examining the phenomenon. Further research on obesogenic environments in segregated neighborhoods could provide valuable evidence.

Disparities by Social Determinants of Health: Links Between Long COVID and Cardiovascular Disease

Long COVID has been defined by the World Health Organisation as "continuation or development of new symptoms 3 months after the initial SARS-CoV-2 infection, with these symptoms lasting for at least 2 months with no other explanation." Cardiovascular disease is implicated as a risk factor, concomitant condition, and consequence of long COVID. As well as heterogeneity in definition, presentation, and likely underlying pathophysiology of long COVID, disparities by social determinants of health, extensively studied and described in cardiovascular disease, have been observed in 3 ways. First, underlying long-term conditions, such as cardiovascular disease and its risk factors, are associated with incidence and severity of long COVID, and previously described socioeconomic disparities in these factors are important in exacerbating disparities in long COVID. Second, socioeconomic disparities in management of COVID-19 may themselves lead to distal disparities in long COVID. Third, there are socioeconomic disparities in the way that long COVID is diagnosed, managed, and prevented. Together, factors such as age, sex, deprivation, and ethnicity have far-reaching implications in this new postviral syndrome across its management spectrum. There are similarities and differences compared with disparities for cardiovascular disease. Some of these disparities are in fact, inequalities, that is, rather than simply observed variations, they represent injustices with costs to individuals, communities, and economies. This review of current literature considers opportunities to prevent or at least attenuate these socioeconomic disparities in long COVID and cardiovascular disease, with special challenges for research, clinical practice, public health, and policy in a new disease which is evolving.

Urban income segregation and homicides: An analysis using Brazilian cities selected by the Salurbal project

This paper investigates the associations of income segregation with homicide mortality across 152 cities in Brazil. Despite GDP increases, an important proportion of the Brazilian population experiences poverty and extreme poverty. Segregation refers to the way that different groups are located in space based on their socioeconomic status, with groups defined based on education, unemployment, race, age, or income levels. As a measure of segregation, the dissimilarity index showed that overall, it would be necessary to relocate 29.7% of urban low-income families to make the spatial distribution of income homogeneous. For the ten most segregated cities, relocation of more than 37% of families would be necessary. Using negative binomial models, we found a positive association between segregation and homicides for Brazilian cities: one standard deviation higher segregation index was associated with a 50% higher homicide rate when we analyze all the socioeconomic context. Income segregation is potentially an important determinant of homicides, and should be considered in setting public policies.

Socioeconomic and Clinical Predictors of Mortality in Patients with Acute Dyspnea

Background

Factors predicting long-term prognosis in patients with acute dyspnea may guide both acute management and follow-up. The aim of this study was to identify socioeconomic and clinical risk factors for all-cause mortality among acute dyspnea patients admitted to an Emergency Department.

Methods

We included 798 patients with acute dyspnea admitted to the ED of Skåne University Hospital, Malmö, Sweden from 2013 to 2016. Exposures were living in the immigrant-dense urban part of Malmö (IDUD), country of birth, annual income, comorbidities, smoking habits, medical triage priority and severity of dyspnea. Mean follow-up time was 2.2 years. Exposures were related to risk of all-cause mortality using Cox proportional hazard model.

Results

During follow-up 40% died. In models adjusted for age and gender, low annual income, previous or ongoing smoking, certain comorbidities, high medical triage priority and severe dyspnea were all significantly associated with increased mortality. After adjusting for age, gender and all significant exposures, the lowest quintile of income, ongoing or previous smoking, history of serious infection, anemia, hip fracture, high medical triage priority and severe dyspnea significantly and independently predicted mortality. In contrast, neither country of birth nor living in IDUD predicted a mortality risk.

Conclusion

Apart from several clinical risk factors, low annual income predicts two-year mortality risk in patients with acute dyspnea. This is not the case for country of birth and living in IDUD. Our results underline the wide range of mortality risk factors in acute dyspnea patients. Knowledge of patients' annual income as well as certain clinical features may aid risk stratification and determining the need of follow-up both in hospital and after discharge from an ED.

Risk of late cervical cancer screening in the Paris region according to social deprivation and medical densities in daily visited neighborhoods

Background

Social and physical characteristics of the daily visited neighborhoods have gained an extensive interest in analyzing socio-territorial inequalities in health and healthcare. The objective of the present paper is to estimate and discuss the role of individual and contextual factors on participation in preventive health-care activities (smear screening) in the Greater Paris area focusing on the characteristics of daily visited neighborhoods in terms of medical densities and social deprivation.

Methods

The study included 1817 women involved in the SIRS survey carried out in 2010. Participants could report three neighborhoods they regularly visit (residence, work/study, and the next most regularly visited). Two “cumulative exposure scores” have been computed from household income and medical densities (general practitioners and gynecologists) in these neighborhoods. Multilevel logistic regression models were used to measure association between late cervical screening (> 3 years) and characteristics of daily visited neighborhoods (residential, work or study, visit).

Results

One-quarter of the women reported that they had not had a smear test in the previous 3 years. Late smear test was found to be more frequent among younger and older women, among women being single, foreigners and among women having a low-level of education and a limited activity space. After adjustment on individual characteristics, a significant association between the cumulative exposure scores and the risk of a delayed smear test was found: women who were exposed to low social deprivation and to low medical densities in the neighborhoods they daily visit had a significantly higher risk of late cervical cancer screening than their counterparts.

Conclusions

For a better understanding of social and territorial inequalities in healthcare, there is a need for considering multiple daily visited neighborhoods. Cumulative exposure scores may be an innovative approach for analyzing contextual effects of daily visited neighborhoods rather than focusing on the sole residential neighborhood.