Equal Potential Research Articles

Ambient air pollution and Alzheimer’s disease and other dementias: a global study between 1990 and 2019

BackgroundEmerging research found air pollution may be associated with incident Alzheimer’s disease (AD) and other dementias. However, few studies have examined these associations at the global scale. This study aimed to assess the dynamic associations between ambient air pollution and the burden of AD and other dementias worldwide.MethodsThis study synthesised 149 countries/territories between 1990 and 2019. These data include age-standardised mortality rate (ASMR) and disability-adjusted life-years (DALYs) of AD and other dementias, ambient air pollution (fine particulate matter [PM2.5], NO2 and O3 concentration) and a series of covariates were from various source. Average annual percentage changes (AAPCs) were calculated to investigate the temporal variations. Linear mixed models were adopted to assess the associations with single- and multi-pollutant separately. The associations between air pollution changes and the AD and other dementias were also examined using linear regression models. Stratified analyses by Global North–South divide and human development index were performed to explore the potential inequity in air pollution impacts.ResultsDuring 1990–2019, the global ASMR, DALYs and O3 increased by 0.11%, 0.09%, and 0.17% per year, respectively. In contrast, PM2.5 and NO2 decreased by 0.33% and 0.14% per year, respectively. Each 10 µg/m3 increase in PM2.5 was associated with a 0.118 (95% confidence interval [CI]: 0.060 − 0.175) higher ASMR and 0.966 (95%CI: 0.321 − 1.611) higher DALYs after adjusting for all the covariates. The ASMR increased by 0.112 and the DALYs increased by 1.068 for each 10 µg/m3 increase in O3. The NO2–dementia associations were relatively weak. Stronger O3–dementia associations were found in the Global South than those in the Global North.ConclusionsThe burden of dementia is expected to increase globally, given the continuously expansion of the ageing population. Air pollution was found to be significantly associated with a higher burden of AD and dementia. As a persistent challenge in urban cities, air pollution demands strict regulatory control.

Theory-informed refinement and tailored implementation of a quality improvement program in maternity care to reduce unwarranted clinical variation across a health service network

BackgroundUnwarranted clinical variation presents a major challenge in contemporary healthcare, indicating potential inequalities and inefficiencies, and unrealised potential for better outcomes. Despite an increasing focus on unwarranted clinical variation, and consideration of efforts to address this challenge, evidence-based strategies which achieve this are limited. Audit and feedback of healthcare processes (process auditing) and clinician engagement are important tools which may help to reduce unwarranted clinical variation, however their application in maternity care is yet to be thoroughly explored. We describe the development and implementation of a program to address unwarranted clinical variation across a multi-site maternity network termed Practice Improvement with Clinicians eNgaged in Improving Care (PICNIC). The goals of the program were to engage clinicians to identify and reduce unwarranted clinical variation and enhance the delivery of evidence-based care, with the intention of improving care quality, clinical outcomes, and efficiency of the health service.MethodsA theory-informed approach was used to design and implement the four-phase program, underpinned by implementation science and quality improvement methodologies. It utilised clinician-performed process auditing, built upon existing evidence for audit and feedback, and employed evidence-based implementation strategies to promote clinician behaviour change.ResultsThe intervention was implemented across the five maternity network sites in 2020 with around 300 clinicians participating in 18 audit topics over four years (2020–2023). A diverse array of evidence-based strategies were utilised to support implementation over this period and are mapped to the Behaviour Change Taxonomy and Expert Recommendation for Implementing Change (ERIC) compilation. Observed benefits of the program include the development and implementation of clinician co-designed system-level improvements that are tailored to context, to improve the delivery of best-practice healthcare and improve outcomes.ConclusionsImplementation science theory and quality improvement processes can be integrated pragmatically to engage clinicians to address unwarranted clinical variation, with the objective of creating meaningful behaviour change, and system-level improvements for better healthcare outcomes. The replicability of this approach in other disciplines and hospital networks should be explored.Trial registrationNot applicable to this report.

Association between socioeconomic status and patient-reported outcome at 1 year after shoulder arthroplasty for osteoarthritis or cuff-tear arthropathy: a nationwide cohort study of 2,292 arthroplasties.

We aimed to evaluate the association between socioeconomic factors and patient-reported Western Ontario Osteoarthritis of the Shoulder (WOOS) index at 1 year after hemiarthroplasty, reverse, or anatomical total shoulder arthroplasty for osteoarthritis or cuff-tear arthropathy. Eligible patients were identified using linked national data from the Danish Shoulder Arthroplasty Registry and Statistics Denmark between April 2012 and April 2019. Univariable and multivariable linear regression was used to identify the association between socioeconomic factors and the WOOS index at 1 year following primary shoulder arthroplasty adjusted for age, sex, underlying diagnosis, implant design, and comorbidities. We examined socioeconomic factors including employment status, marital status, education, and income. Estimates were provided with 95% confidence intervals (CI). 2,292 patients were identified with a mean WOOS index of 76 (standard deviation 24). In the adjusted analysis, unemployed patients had a significantly lower WOOS index compared with patients with low-level jobs (14, CI 7.0-21), patients with high-level jobs (19, CI 12-25), and retired patients (14, CI 8.3-21). Low education level was associated with a lower WOOS index compared with medium education (4.8, CI 2.6-7.0) and high education level (7.7, CI 5.0-10). There was no association between WOOS index and income or marital status. Unemployment and low education level were associated with worse WOOS index 1 year after shoulder arthroplasty for osteoarthritis or cuff-tear arthropathy. This highlights a potential inequity in patient-reported outcomes after shoulder arthroplasty.

Inequalities in cancer two-week-wait referrals: a cross-sectional study in English general practice.

Practices with higher two-week-wait (2WW) referral-rates demonstrate higher survival for several cancers. Yet, there is little up-to-date evidence exploring factors influencing 2WW-referral-rates and whether health inequalities exist, particularly after COVID-19. To establish which patient-factors (eg, age, sex, ethnicity, deprivation) and practice-factors (eg, remote consultations, frequency of seeing a preferred-GP) independently predict 2WW-referral-rates. A cross-sectional, observational study was performed using data from English general practices for 2021-2022. Multivariable linear regression was used to identify the strongest, independent predictors of 2WW-referral-rates for all-cancers (primary outcome) and for breast, lower-gastrointestinal, lung and skin cancers separately (secondary outcome). The analysis included 6307 practices. Practices with more females, patients aged 75+and with a greater burden of long-term conditions were associated with higher 2WW-referrals for all-cancers, as were practices in Northwest England and those with higher scores for patients feeling involved in care decisions. Conversely, practices with a higher frequency of seeing a preferred-GP were predictive of fewer all-cancer 2WW-referrals. Whilst practices with a higher proportion of current smokers and Asian and Black ethnicity patients predicted fewer all-cancer 2WW-referrals, these associations were strongest for skin cancer, and for breast cancer (except for Black ethnicity). Higher socioeconomic deprivation predicted lower 2WW-referrals for lung cancer only. This study analyses factors influencing 2WW-referral-rates and highlights potential inequalities. This work identifies priority populations, including smokers and Asian and Black ethnicity patients, who may benefit from interventions to increase primary care access. Shared-decision-making may be an underexplored resource for increasing all-cancer 2WW-referral-rates.

“No data, no problem”? Potential inequities in psychosis among immigrants in the United States

“No data, no problem”? Potential inequities in psychosis among immigrants in the United States

Schizophrenia more employable than depression? Language-based artificial intelligence model ratings for employability of psychiatric diagnoses and somatic and healthy controls.

Artificial Intelligence (AI) assists recruiting and job searching. Such systems can be biased against certain characteristics. This results in potential misrepresentations and consequent inequalities related to people with mental health disorders. Hence occupational and mental health bias in existing Natural Language Processing (NLP) models used in recruiting and job hunting must be assessed. We examined occupational bias against mental health disorders in NLP models through relationships between occupations, employability, and psychiatric diagnoses. We investigated Word2Vec and GloVe embedding algorithms through analogy questions and graphical representation of cosine similarities. Word2Vec embeddings exhibit minor bias against mental health disorders when asked analogies regarding employability attributes and no evidence of bias when asked analogies regarding high earning jobs. GloVe embeddings view common mental health disorders such as depression less healthy and less employable than severe mental health disorders and most physical health conditions. Overall, physical, and psychiatric disorders are seen as similarly healthy and employable. Both algorithms appear to be safe for use in downstream task without major repercussions. Further research is needed to confirm this. This project was funded by the London Interdisciplinary Social Science Doctoral Training Programme (LISS-DTP). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

A Systematic Review on the Socioeconomic Impacts of Industrial Innovation Parks in Developing Countries

This research investigates the socioeconomic impact of Industrial Innovation Parks (IIPs) in developing countries. IIPs, encompassing science parks, technology parks, and innovation districts, aim to foster innovation, attract investment, and drive economic growth. This study systematically reviews existing literature, analyzing research on the impact of IIPs on key socioeconomic indicators, including job creation, economic growth, and regional development. The review examines the role of various factors influencing IIP success, such as government policies, infrastructure development, access to finance, and the availability of skilled labor. Findings indicate that IIPs have the potential to stimulate economic growth, create high-value jobs, and promote technological advancement in developing countries. However, challenges such as potential social inequities, the need for strong public-private partnerships, and the importance of context-specific approaches are also highlighted. Furthermore, this research develops a conceptual model of the socioeconomic impact of IIPs, highlighting key inputs, processing activities, and key socioeconomic indicators as outputs. This review contributes to a better understanding of the multifaceted nature of IIPs and provides valuable insights for policymakers and practitioners seeking to maximize the socioeconomic impact of these initiatives in developing economies.

Macro-level socioeconomic factors and mental health in midlife and older adults in China: a multilevel analysis

ObjectiveThis study explores the associations between four macro-level factors—Economic Development (ED), Economic Inequality (EI), Governmental Willingness and capacities to invest in Public Health (GWPH) and Public Health-Related Infrastructures (PHRI)—and three mental health indicators: depressive symptoms, cognitive function and life satisfaction, among middle-aged and older adults in China.Materials and methodsWe obtained individual-level data from the Harmonised China Health and Retirement Longitudinal Survey (H-CHARLS) 2018 and acquired our provincial-level data from the Chinese Statistical Yearbook. Two-level linear mixed models are used to examine the associations. Supplementary analyses are carried out to test the robustness of the study.ResultsThere are provincial variations in macro-level factors. Depressive symptoms and cognitive functions also vary across provinces, whereas life satisfaction does not. We find that ED contributes to better depressive status. EI contributes to worse cognitive functions and life dissatisfaction. GWPH and PHRI are not associated with mental health.ConclusionThe study suggests that macro-level ED contributes to better depressive status. EI and potential systematic inequality lead to worsened cognitive functions and life dissatisfaction. It is too soon to generalise whether institutional factors like GWPH and PHRI are good or bad for mental health, but the current public health system in China does not adequately support mental and cognitive health.

Social and Economic Impact of Measurable Fishing Policies on Fishermen in North Aceh Regency

The measured fishing policy, or catch share, aims to manage marine resources sustainably by providing special quotas to fishermen, but its implementation in North Aceh Regency shows complex social and economic impacts. While these policies can reduce overfishing and improve planning for fishers' activities, potential inequalities in quota distribution can exacerbate economic inequality, with large fishers better able to control quotas than small or traditional fishers. This can affect the social structure within the fishing community and create tension. While there is potential to strengthen cooperation between fishers and increase incomes, the success of these policies relies heavily on fair and inclusive planning to ensure optimal economic and social benefits and sustainability of marine resources. Theoretical perspective on the impact of socio-economic change. Data collection was carried out through Live in, observation, in-depth interviews and the use of documents. The data analysis process is carried out interactively through stages; Data collection, data verification, data patterns, data coding, data thematic networks, meaning and conclusion drawn. The results of this study show that the measured fishing policy in North Aceh aims to preserve marine resources through the regulation of catch quotas. Despite the impact on fishermen's income and society, this policy has the potential to provide long-term benefits if managed properly, through increased fish stocks, stable incomes, and fisher participation.

Working to Work: Gaining Employment After Inclusive Postsecondary Education

ABSTRACTBackgroundIndividuals with intellectual disability in the United States have historically been underemployed due to societally constructed barriers. Recently, more individuals with intellectual disability have been attending Inclusive Postsecondary Education (IPSE) programmes, which have contributed to improving their employment outcomes.MethodsThis qualitative study analyzed the experiences of five graduates from one IPSE programme who completed an internship during their programme. Semistructured interviews were used to discuss their IPSE internship experiences, current employment and future goals. Transcripts were coded and analyzed inductively.FindingsAt the time of the interviews, each participant had competitive employment. The findings illustrated two significant categories of resources used to gain employment postgraduation: internal university resources such as university staff, course content, work sites and networking groups; and external university resources, including parents, community service agencies and the Internet.ConclusionsAlthough external university resources were important to the participants in this study, they may be an area of inequity when considering the intersectionality of disability and other marginalized identities such as race and socioeconomic status. To combat any lack of external resources a student may have, IPSE programmes should plan to address potential inequities programmatically.

Fair and Transparent Student Admission Prediction Using Machine Learning Models

Student admission prediction is a crucial aspect of academic planning, offering insights into enrollment trends, resource allocation, and institutional growth. However, traditional methods often lack the ability to address fairness and transparency, leading to potential biases and inequities in the decision-making process. This paper explores the development and evaluation of machine learning models designed to predict student admissions while prioritizing fairness and interpretability. We employ a diverse set of algorithms, including Logistic Regression, Decision Trees, and ensemble methods, to forecast admission outcomes based on academic, demographic, and extracurricular features. Experimental results on real-world datasets highlight the effectiveness of the proposed models in achieving competitive predictive performance while adhering to fairness metrics such as demographic parity and equalized odds. Our findings demonstrate that machine learning can not only enhance the accuracy of admission predictions but also support equitable access to education by promoting transparency and accountability in automated systems.

Direct and indirect effects of the COVID-19 pandemic on mortality: an individual-level population-scale analysis using linked electronic health records, Wales, United Kingdom, 2016 to 2022.

BackgroundThe COVID-19 pandemic resulted in increased mortality directly and indirectly associated with COVID-19.AimTo assess the impact of the COVID-19 pandemic on all-cause and disease-specific mortality and explore potential health inequalities associated with area-level deprivation in Wales.MethodsTwo population-based cohort studies were derived from multi-sourced, linked demographic, administrative and electronic health record data from 2016 to 2019 (n=3,113,319) and 2020 to 2022 (n=3,571,471). Data were analysed using generalised linear models adjusting for age, sex, area-level deprivation and time at risk.ResultsCOVID-19 deaths peaked in January 2021 (54.9/100,000 person-months, 95% confidence interval (CI): 52.4-57.5). The pandemic indirectly affected deaths, with higher than expected maximum relative mortality rates (RR) related to cancer (RR: 1.24, 95% CI: 1.13-1.36), infectious diseases (excluding respiratory infections) (RR: 2.09, 95% CI: 1.27- 3.43), circulatory system (RR: 1.41, 95% CI: 1.28-1.56), trauma (RR: 2.04, 95% CI: 1.57- 2.65), digestive system (RR: 1.54, 95% CI: 1.25-1.91), nervous system (RR: 1.63; 95% CI: 1.34-2.00) and mental and behavioural disorders (RR: 1.85, 95% CI: 1.58-2.16). Mortality associated with respiratory diseases (unrelated to COVID-19) were lower than expected (minimum RR: 0.52, 95% CI: 0.45-0.60). All-cause mortality was lower in least deprived communities compared with most deprived (RR: 0.61, 95% CI: 0.60-0.62), and the magnitude of this effect increased during the pandemic.ConclusionsAll-cause and disease-specific mortality directly and indirectly associated with COVID-19 increased during the COVID-19 pandemic. Socioeconomic disparities were exacerbated during this time.

Coping Strategies and Inequalities during the COVID-19 Pandemic Period: Evidence from Kenya

Abstract Governments worldwide have implemented stringent lockdown measures in response to the COVID-19 pandemic outbreak, which had an adverse impact on employment, affecting people's public life, health and well-being. People have witnessed job losses, cuts in wages and a decline in their living standards. This study aims to estimate the inequalities and well-being costs, demonstrating the living standards necessary to make up for people's wage reduction or job losses. In particular, we aim to explore the coping strategies used to enhance their well-being compared to those of households without a coping strategy. We use food insecurity as a measure of well-being outcome. The empirical analysis relies on detailed household surveys from the World Bank Microdata Library. We use seven waves of the Panel COVID-19 Rapid Response Phone Survey with Households in 2020–2022 in Kenya. Also, the results highlight the potential inequalities of the COVID-19 pandemic across gender and types of workers, such as those employed in the informal sector and on temporary contracts. The findings show that specific coping strategies, such as delayed payment obligations, credit purchases and reduced non-food consumption, are associated with larger inequalities. Regarding the gender of the head of the household, the results suggest that the disparities between female-headed households that had to cope with income and employment loss and female-headed households that did not require to follow any strategy are significantly higher compared to their male counterparts. We derive similar concluding remarks when we consider households with social security coverage and the type of employment contract.

Geospatial analysis of sports tourism resources in China's urban clusters: a case study of the Sichuan-Chongqing region utilizing GIS and the geographic detector

IntroductionThis study aims to elucidate the temporal and spatial distribution patterns of sports tourism resources within the Sichuan-Chongqing Urban Agglomeration, examining how these distributions reflect the developmental pathways of urban regions. The theoretical framework posits that the availability and allocation of sports tourism resources are influenced by various geographical and socio-economic factors, with topography, economic conditions, and population density playing pivotal roles in determining their distribution and development.MethodsUtilizing GeoDetector technology alongside indices such as the Geographic Concentration Index and the Disparities Index, we conducted a comprehensive analysis of the spatiotemporal dynamics of sports tourism resources, revealing that the distribution of these resources serves as a key indicator of urban development speed.ResultsOur findings indicate that topographical features significantly influence sports tourism resource development differently in Chengdu compared to Chongqing. Furthermore, we identified a strong positive correlation between population density and the distribution of sports tourism resources, highlighting the motivational role of populated areas and emphasizing potential inequalities if attention is focused solely on densely populated regions.DiscussionThis research provides novel insights into the complex relationships governing sports tourism resource distribution by employing advanced geo-analytical tools. It offers a strategic roadmap for equitable and sustainable urban development by addressing disparities in resource allocation, ultimately contributing to informed policy-making and enhanced regional resilience. This research aids in the strategic planning and sustainable development of sports tourism, providing a blueprint for urban development in the region that balances the needs of diverse populations and landscapes.

Strategies for Sustainable Growth and Decent Work in the Platform Economy

Achieving Sustainable Development Goal 8 (SDG 8) is imperative for promoting global prosperity and social equity. This article explores the multifaceted challenges and opportunities associated with fostering sustainable, inclusive, and enduring economic growth, full and productive employment, and decent work for all—particularly in the context of platform economies and temporary employment. By synthesizing recent literature and integrating economic and labour market theories, we examine how technological advancements influence economic productivity and job creation. We also address ethical concerns and potential inequalities arising from these technologies if not managed responsibly. Strategies such as upskilling initiatives, portable benefits, worker cooperatives, and ethical AI development are discussed as means to mitigate these challenges. The article underscores the need for a comprehensive and collaborative approach involving policymakers, platform operators, and stakeholders to achieve the objectives of SDG 8.

Modeling the Potential Health, Health Economic, and Health Inequality Impact of a Large-Scale Rollout of the Drink Less App in England.

Alcohol places a significant burden on the National Health Service (NHS); yet, uptake of cost-effective approaches remains low. Digital interventions may overcome some barriers to delivery. The Drink Less app has evidence of being effective at supporting heavier drinkers to reduce their alcohol intake. In this study, we estimate the longer-term health impacts, cost-effectiveness, and health inequality impact of a large-scale rollout of the Drink Less app. We used the Sheffield Alcohol Policy Model to estimate changes in alcohol consumption, hospital admissions, mortality, and NHS costs of 2 rollout scenarios over a 20-year time horizon: (1) a mass media awareness campaign and (2) a targeted drive to embed referral to Drink Less within primary care. We modeled the cost-effectiveness and inequality impact of each approach in a distributional cost-effectiveness analysis. A mass media campaign is estimated to reduce per capita alcohol consumption by 0.07 units/week and avert 108 556 hospital admissions and 2606 deaths over 20 years, gaining 24 787 quality-adjusted life-years at a net saving to the NHS of £417 million. Embedding in primary care is estimated to reduce consumption by 0.13 units/week, saving 188 452 admissions and 4599 deaths and gaining 38 897 quality-adjusted life-years at a net saving of £590 million. Both scenarios are estimated to reduce health inequalities, with a larger reduction for the primary care approach. A large-scale rollout of the Drink Less app is estimated to be health improving, cost saving, and reducing health inequalities. Embedding the use of Drink Less within primary care is likely to be the more effective approach.

Powering prosperity: Unveiling the impacts of renewable energy policies on economy, employment, and income distribution in Indonesia

This study analyzes the economic and distributional impacts of a Production Tax Credit (PTC) on Indonesia's renewable electricity sector using a Computable General Equilibrium (CGE) model. The simulation spans 2018 to 2030, utilizing the 2018 Social Accounting Matrix (SAM). Results indicate significant reductions in electricity prices by 2025 under two scenarios of total factor productivity (TFP) growth (20 % and 30 %), with continued price decreases through 2030. The study reveals that while urban households and highly educated labour benefit from reduced energy costs and income gains, rural and lower-skilled workers experience fewer advantages, highlighting potential inequalities. The findings underscore the importance of inclusive renewable energy policies to ensure equitable economic outcomes during the energy transition. This research contributes to existing literature by offering new insights into the role of PTC in promoting sustainable energy development in emerging economies like Indonesia, with critical implications for policy design.

Exploring socio-economic inequalities in access to the 15-minute city across 200 Swedish built-up areas

In recent years, the 15-minute city has gained prominence as a vision for urban development, aiming to create attractive and vibrant neighborhoods where essential services are within a 15-minute walk. However, its implementation raises concerns about socio-spatial segregation, as the potential increase in desirability of these neighborhoods—combined with various underlying factors—can lead to increased housing prices, potentially excluding economically vulnerable groups. Despite its popularity, few studies have thoroughly explored how access to the 15-minute city varies among different socio-economic groups and across different cities and towns, highlighting a significant research gap. This study aims to explore potential socio-economic inequalities in 15-minute city access across the 200 largest built-up areas in Sweden. Specifically, our study compares average incomes among residents living in neighborhoods that either meet or do not meet various 15-minute city criteria within each built-up area. These criteria are designed to operationalize the proximity dimension of the 15-minute city by capturing which residents that have access to different sets of non-work urban social functions (e.g., healthcare, restaurants, retail) within 1 km from their homes. Two research questions guide the study: Are there differences in access to the 15-minute city, in terms of proximity to non-work urban social functions, across different income groups in Swedish built-up areas? How do variations in the types of functions included in the 15-minute city model, as well as differences in built-up areas characterized by population size, density, land use mix, and the proportion of older buildings, affect these outcomes? Findings reveal significant impact from both the definition of the 15-minute city and across different types of built-up areas. When the 15-minute city only encompasses basic functions such as a grocery store, school, restaurant, etc., average incomes are lower, irrespective of population size. However, mean incomes are notably higher for residents who can locally access many different urban social functions, indicative of larger cities with a higher population density and jobs-to-worker ratio. This highlights a cautionary aspect for cities and planners implementing the 15-minute city vision, as the city characteristics strongly correlated with effective adherence to the 15-minute city may also contribute to excluding lower-income groups.

Music teacher licensure in the United States: a policy analysis

The purpose of this study was to construct a comprehensive, national profile of music teacher licensure practices. Our objectives in this research were a) to construct a descriptive, national profile of legislative policy about music teacher licensure, b) to identify licensure parameters required of music teacher candidates, and c) to identify points of convergence or divergence across state-level written policies. Teacher licensure is one of many policy-related topics that necessitate consistently updated, descriptive research to establish an understanding of current practice. In addition, the current national teacher shortage calls for an in-depth exploration of potential pipeline barriers or inequities. We therefore conducted a retrospective, or ex post policy analysis, which involves the distillation and transmission of information and policies after they have been implemented. Within this retrospective policy analysis, we adopted a problem-finding perspective (Dunn, 2012). That is, we sought not only to describe music teacher licensure policy but to identify and explain elements that may contribute to problems with inconsistency or inequity. State-level music teacher licensure policy existed predominately in the form of statute or code, with most states offering a holistic, rather than leveled or tracked music teacher certification. Most states required two or more written examinations of content knowledge or pedagogy. Under one-half of states required a portfolio assessment of teacher performance. The notion of certification reciprocity presented multiple points of convergence and divergence in policy across states.

Surgical and transcatheter aortic valve interventions for aortic stenosis in England: sociodemographic variations in treatment trends and outcome over 20 years

BackgroundHealth inequalities in cardiovascular care have been identified in the UK. The sociodemographic characteristics of patients undergoing intervention for aortic stenosis (AS) in England, and the impact of COVID-19, is...