UNASSIGNED: This study examines the factors affecting unmet healthcare experiences by integrating individual-and community-level extinction indices.
UNASSIGNED: Using spatial autocorrelation and multilevel modeling, the study utilizes data from the Community Health Survey and Statistics Korea for 218 local government regions from 2018 to 2019.
UNASSIGNED: The analysis identifies significant clustering, particularly in non-metropolitan regions with a higher local extinction index. At the individual level, some factors affect unmet medical needs, and unmet healthcare needs increase as the local extinction index at the community level increases.
UNASSIGNED: The findings underscore the need for strategic efforts to enhance regional healthcare accessibility, particularly for vulnerable populations and local infrastructure development.

UNASSIGNED: In sub-Saharan Africa, achieving universal health coverage (UHC) and protecting populations from health-related financial hardship remain challenging goals. Subsequently, community-based health insurance (CBHI) has gained interest in low and middle-income countries, such as Ethiopia. However, the rural-urban disparity in CBHI enrollment has not been properly investigated using multivariate decomposition analysis. Therefore, this study aimed to assess the rural-urban disparity of CBHI enrollment in Ethiopia using the Ethiopian Mini Demographic Health Survey 2019 (EMDHS 2019).
UNASSIGNED: This study used the latest EMDHS 2019 dataset. STATA version 17.0 software was used for analyses. The chi-square test was used to assess the association between CBHI enrollment and the explanatory variables. The rural-urban disparity of CBHI enrollment was assessed using the logit-based multivariate decomposition analysis. A p-value of <0.05 with a 95% confidence interval was used to determine the statistical significance.
UNASSIGNED: The study found that there was a significant disparity in CBHI enrollment between urban and rural households (p < 0.001). Approximately 36.98% of CBHI enrollment disparities were attributed to the compositional (endowment) differences of household characteristics between urban and rural households, and 63.02% of the disparities were due to the effect of these characteristics (coefficients). The study identified that the age and education of the household head, family size, number of under-five children, administrative regions, and wealth status were significant contributing factors for the disparities due to compositional differences between urban and rural households. The region was the significant factor that contributed to the rural-urban disparity of CBHI enrollment due to the effect of household characteristics.
UNASSIGNED: There were significant urban-rural disparities in CBHI enrollment in Ethiopia. Factors such as age and education of the household head, family size, number of under-five children, region of the household, and wealth status of the household contributed to the disparities attributed to the endowment, and region of the household was the contributing factor for the disparities due to the effect of household characteristics. Therefore, the concerned body should design strategies to enhance equitable CBHI enrollment in urban and rural households.

BACKGROUND: Organized breast cancer screening (BCS) programs are effective measures among women aged 50-69 for preventing the sixth cause of death in Germany. Although the implementation of the national screening program started in 2005, participation rates have not yet reached EU standards. It is unclear which and how sociodemographic factors are related to BCS attendance. This scoping review aims to identify sociodemographic inequalities in BCS attendance among 50-69-year-old women following the implementation of the Organized Screening Program in Germany.
METHODS: Following PRISMA guidelines, we searched the Web of Science, Scopus, MEDLINE, PsycINFO, and CINAHL following the PCC (Population, Concept and Context) criteria. We included primary studies with a quantitative study design and reviews examining BCS attendance among women aged 50-69 with data from 2005 onwards in Germany. Harvest plots depicting effect size direction for the different identified sociodemographic inequalities and last two years or less BCS attendance and lifetime BCS attendance were developed.
RESULTS: We screened 476 titles and abstracts and 33 full texts. In total, 27 records were analysed, 14 were national reports, and 13 peer-reviewed articles. Eight sociodemographic variables were identified and summarised in harvest plots: age, education, income, migration status, type of district, employment status, partnership cohabitation and health insurance. Older women with lower incomes and migration backgrounds who live in rural areas and lack private insurance respond more favourably to BCS invitations. However, from a lifetime perspective, these associations only hold for migration background, are reversed for income and urban residency, and are complemented by partner cohabitation. Finally, women living in the former East German states of Saxony, Mecklenburg-Western Pomerania, Saxony-Anhalt, and Thuringia, as well as in the former West German state of Lower Saxony, showed higher BCS attendance rates in the last two years.
CONCLUSIONS: High-quality research is needed to identify women at higher risk of not attending BCS in Germany to address the existing research\'s high heterogeneity, particularly since the overall attendance rate still falls below European standards.
BACKGROUND: https://osf.io/x79tq/ .

BACKGROUND: When medically indicated, caesarean section (CS) can be a life-saving intervention for mothers and their newborns. This study assesses the prevalence of CS and its associated factors, focussing on inequalities between rural and urban areas in Nigeria.
METHODS: We disaggregated the Nigeria Demographic and Health Survey 2018 and performed analyses separately for Nigeria\'s overall, rural, and urban residences. We summarised data using frequency tabulations and identified factors associated with CS through multivariable logistic regression analysis.
RESULTS: CS prevalence was 2.7% in Nigeria (overall), 5.2% in urban and 1.2% in rural areas. The North-West region had the lowest prevalence of 0.7%, 1.5% and 0.4% for the overall, urban and rural areas, respectively. Mothers with higher education demonstrated a greater CS prevalence of 14.0% overall, 15.3% in urban and 9.7% in rural residences. Frequent internet use increased CS prevalence nationally (14.3%) and in urban (15.1%) and rural (10.1%) residences. The southern regions showed higher CS prevalence, with the South-West leading overall (7.0%) and in rural areas (3.3%), and the South-South highest in urban areas (8.5%). Across all residences, rich wealth index, maternal age ≥ 35, lower birth order, and ≥ eight antenatal (ANC) contacts increased the odds of a CS. In rural Nigeria, husbands\' education, spouses\' joint healthcare decisions, birth size, and unplanned pregnancy increased CS odds. In urban Nigeria, multiple births, Christianity, frequent internet use, and ease of getting permission to visit healthcare facilities were associated with higher likelihood of CS.
CONCLUSIONS: CS utilisation remains low in Nigeria and varies across rural-urban, regional, and socioeconomic divides. Targeted interventions are imperative for uneducated and socioeconomically disadvantaged mothers across all regions, as well as for mothers in urban areas who adhere to Islam, traditional, or \'other\' religions. Comprehensive intervention measures should prioritise educational opportunities and resources, especially for rural areas, awareness campaigns on the benefits of medically indicated CS, and engagement with community and religious leaders to promote acceptance using culturally and religiously sensitive approaches. Other practical strategies include promoting optimal ANC contacts, expanding internet access and digital literacy, especially for rural women (e.g., through community Wi-Fi programs), improving healthcare infrastructure and accessibility in regions with low CS prevalence, particularly in the North-West, and implementing socioeconomic empowerment programs, especially for women in rural areas.

BACKGROUND: People with diabetes, vascular disease, and asthma often struggle to maintain stability in their chronic health conditions, particularly those in rural areas, living in poverty, or racially or ethnically minoritized populations. These groups can experience inequities in healthcare, where one group of people has fewer or lower-quality resources than others. Integrating behavioral healthcare services into primary care holds promise in helping the primary care team better manage patients\' conditions, but it involves changing the way care is delivered in a clinic in multiple ways. Some clinics are more successful than others in fully integrating behavioral health models as shown by previous research conducted by our team identifying four patterns of implementation: Low, Structural, Partial, and Strong. Little is known about how this variation in integration may be related to chronic disease management and if IBH could be a strategy to reduce healthcare inequities. This study explores potential relationships between IBH implementation variation and chronic disease management in the context of healthcare inequities.
METHODS: Building on a previously published latent class analysis of 102 primary care clinics in Minnesota, we used multiple regression to establish relationships between IBH latent class and healthcare inequities in chronic disease management, and then structural equation modeling to examine how IBH latent class may moderate those healthcare inequities.
RESULTS: Contrary to our hypotheses, and demonstrating the complexity of the research question, clinics with better chronic disease management were more likely to be Low IBH rather than any other level of integration. Strong and Structural IBH clinics demonstrated better chronic disease management as race in the clinic\'s location became more White.
CONCLUSIONS: IBH may result in improved care, though it may not be sufficient to resolve healthcare inequities; it appears that IBH may be more effective when fewer social determinants of health are present. Clinics with Low IBH may not be motivated to engage in this practice change for chronic disease management and may need to be provided other reasons to do so. Larger systemic and policy changes are likely required that specifically target the mechanisms of healthcare inequities.

BACKGROUND: Overall, research on social determinants of access and quality of outpatient care in Germany is scarce. Therefore, social disparities (according to sex, age, income, migration background, and health insurance) in perceived access and quality of consultation in outpatient care (primary care physicians and specialists) in Germany were explored in this study.
METHODS: Analyses made use of a cross-sectional online survey. An adult population sample was randomly drawn from a panel which was recruited offline (N = 2,201). Perceived access was assessed by waiting time for an appointment (in days) and travel time to the practice (in minutes), while quality of consultation was measured by consultation time (in minutes) and quality of communication (scale of four items, Cronbach\'s Alpha 0.89).
RESULTS: In terms of primary care, perceived access and quality of consultation was worse among women compared to men. Estimated consultation time was shorter among people with statutory health insurance compared to privately insured respondents. Regarding specialist care, people aged 60 years and older reported shorter waiting times and better quality of communication. Lower income groups reported lower quality of communication, while perceived access and quality of consultation was worse among respondents with a statutory health insurance. Variances explained by the social characteristics ranged between 1% and 4% for perceived access and between 3% and 7% for quality of consultation.
CONCLUSIONS: We found social disparities in perceived access and quality of consultation in outpatient care in Germany. Such disparities in access may indicate structural discrimination, while disparities in quality of consultation may point to interpersonal discrimination in health care.

OBJECTIVE: To estimate the prevalence of general and public access to prescription drugs in the Brazilian population aged 15 or older in 2019, and to identify inequities in access, according to intersections of gender, color/race, socioeconomic level, and territory.
METHODS: We analyzed data from the 2019 National Health Survey with respondents aged 15 years or older who had been prescribed a medication in a healthcare service in the two weeks prior to the interview (n = 19,819). The outcome variable was access to medicines, subdivided into general access (public, private and mixed), public access (via the Unified Health System - SUS) for those treated by the SUS, and public access (via the SUS) for those not treated by the SUS. The study\'s independent variables were used to represent axes of marginalization: gender, color/race, socioeconomic level, and territory. The prevalence of general and public access in the different groups analyzed was calculated and the association of the outcomes with the aforementioned axes was estimated with odds ratios (OR) using logistic regression models.
RESULTS: There was a high prevalence of general access (84.9%), when all sources of access were considered, favoring more privileged segments of the population, such as men, white, and those of high socioeconomic status. When only the medicines prescribed in the SUS were considered, there was a low prevalence (30.4% access) that otherwise benefited marginalized population segments, such as women, black, and people from low socioeconomic backgrounds.
CONCLUSIONS: Access to medicines through the SUS proves to be an instrument for combating intersectional inequities, lending credence to the idea that the SUS is an efficient public policy for promoting social justice.

Many people living with dementia and unpaid carers experience inequalities in care related to challenges in receiving a correct diagnosis, care and support. Whilst complexities of the evidence are well recognised including barriers in receiving a diagnosis or post-diagnostic care, no coherent model has captured the far-reaching types and levels of inequalities to date. Building on the established Dahlgren & Whitehead Rainbow model of health determinants, this paper introduces the new Dementia Inequalities model. The Dementia Inequalities model, similar to the original general rainbow model, categorises determinants of health and well-being in dementia into three layers: (1) Individual; (2) Social and community networks; and (3) Society and infrastructure. Each layer comprises of general determinants, which have been identified in the original model but also may be different in dementia, such as age (specifically referring to young- versus late-onset dementia) and ethnicity, as well as new dementia-specific determinants, such as rare dementia subtype, having an unpaid carer, and knowledge about dementia in the health and social care workforce. Each layer and its individual determinants are discussed referring to existing research and evidence syntheses in the field, arguing for the need of this new model. A total of 48 people with lived, caring, and professional experiences of dementia have been consulted in the process of the development of this model. The Dementia Inequalities model provides a coherent, evidence-based overview of inequalities in dementia diagnosis and care and can be used in health and social care, as well as in commissioning of care services, to support people living with dementia and their unpaid carers better and try and create more equity in diagnosis and care.

BACKGROUND: Most older adults wish to remain in their homes and communities as they age. Despite this widespread preference, disparities in health outcomes and access to healthcare and social support may create inequities in the ability to age in place. Our objectives were to synthesise evidence of social inequity in ageing in place among older adults using an intersectional lens and to evaluate the methods used to define and measure inequities.
METHODS: We conducted a mixed studies systematic review. We searched MEDLINE, EMBASE, PsycINFO, CINAHL and AgeLine for quantitative or qualitative literature that examined social inequities in ageing in place among adults aged 65 and older in Organisation for Economic Co-operation and Development (OECD) member countries. Results of included studies were synthesised using qualitative content analysis guided by the PROGRESS-Plus framework.
RESULTS: Of 4874 identified records, 55 studies were included. Rural residents, racial/ethnic minorities, immigrants and those with higher socioeconomic position and greater social resources are more likely to age in place. Women and those with higher educational attainment appear less likely to age in place. The influence of socioeconomic position, education and social resources differs by gender and race/ethnicity, indicating intersectional effects across social dimensions.
CONCLUSIONS: Social dimensions influence the ability to age in place in OECD settings, likely due to health inequalities across the lifespan, disparities in access to healthcare and support services, and different preferences regarding ageing in place. Our results can inform the development of policies and programmes to equitably support ageing in place in diverse populations.

Despite higher per-capita health care spending than any other country, the United States lags far behind in health outcomes. Additionally, there are significant health inequities by race, ethnicity, socioeconomic position, and rurality. One set of potential solutions to improve these outcomes and reduce inequities is through health policy. Policy focused on improving access to care through insurance coverage, such as the Affordable Care Act\'s Medicaid expansion, has led to better health and reduced mortality. Policy aimed at improving health care delivery, including value-based payment and alternative payment models, has improved quality of care but has had little impact on population health outcomes. Policies that influence broader issues of economic opportunity likely have a strong influence on health, but lack the evidence base of more targeted interventions. To advance health outcomes and equity, further policy change is crucial.