National Dataset Research Articles

Conflict or Coordination? A Coupling Study of China’s Population–Urbanization–Ecological Environment

Whether the new type of urbanization implemented in China in the past decade has been effective in regulating urbanization and balancing human development and environmental protection remains to be verified. Therefore, this study develops a framework for assessing population-urbanization–ecological environment interactions by combining the coupling coordination degree model and the decoupling index. Firstly, the proposed framework establishes an indicator system of population, economy, society, space, environmental pressure, ecological governance, ecological status, and ecological services based on two sets of national census data; secondly, this study combines the coupling coordination degree model and decoupling index to comprehensively understand the coupling coordination relationship and the decoupling relationship of the population–urbanization–ecological environment across time and space. Overall, this study contributes to a deepened understanding of coupled population–urbanization–ecological environment interactions and provides a scientific basis for effective guidance on urban–rural management and the balance between human development and environmental protection.

Placental abruption and the risk of necrotizing enterocolitis in neonates with birth weight ≥1500 grams; US national database study.

The pathogenesis of necrotizing enterocolitis (NEC) is multifactorial, placental abruption is associated with serious neonatal complications attributed to disruption of the maternal-fetal vascular interface. This study aimed to investigate the association between placental abruption and NEC. We analyzed the United States (US) National Inpatient Sample (NIS) dataset for the years 2016-2018. Using the logistic regression model, the adjusted odds ratios (aOR) were calculated to assess the risk of NEC in infants born to mothers with placental abruption after controlling for significant confounders. Analyses were repeated after stratifying the population into two birth weight (BW) categories: <1500 g and ≥1500 g. The study included 11,597,756 newborns. Placental abruption occurred in 0.16% of the population. NEC was diagnosed in 0.18% of infants, with a higher incidence (2.5%) in those born to mothers with placental abruption (aOR = 1.2, 95% CI: 1.1-1.3, p < 0.001). Placental abruption was associated with NEC only in infants with BW ≥ 1500 g (aOR = 1.34, 95% CI: 1.11-1.62, p 0.003). Placental abruption is associated with an increased risk of NEC in neonates with BW ≥ 1500 g. Research is needed to explore the mechanisms behind this association and to develop targeted interventions to mitigate NEC risks in this population. Placental abruption is associated with an increased risk of developing necrotizing enterocolitis (NEC) in neonates with a birth weight ≥1500 grams. This effect could be via direct in utero bowel injury or due to indirect postnatal compromise that occurs in these infants. This is the first study to specifically address the association between placental abruption and NEC in neonates ≥1500 g. The study used a national dataset that included all neonates delivered in the US, thereby allowing for the generalization of the findings after adjustment for multiple confounding factors. This study lays the groundwork for subsequent studies aimed at modifying feeding strategies and other neonatal management for the prevention of NEC in infants delivered after placental abruption.

A Conterminous United States–Wide Validation of Relative Tidal Elevation Products

Recent large-scale spatial products have been developed to assess wetland position in the tidal frame, but nationwide comparisons and validations are missing for these products. Wetland position within the tidal frame is a commonly used characteristic to compare wetlands across biogeomorphic gradients and factors heavily into wetland vulnerability models. We utilize a dataset of 365 surface elevation table stations across the conterminous USA containing ground-surveyed tidal datum and elevation data to validate two gridded, conterminous USA–wide relative tidal elevation products. We identified substantial differences between our ground-surveyed dataset and the gridded products, with the Gulf coast exhibiting the greatest error (p < 0.0001, n = 140). Error in relative tidal elevation products varied by coast, tidal range, and latitude. These differences in errors indicate that gridded relative tidal elevation products may be more accurate in coastal wetlands with larger tidal ranges (> 30 cm) and are less accurate in freshwater wetlands near the coast. This paper makes advances in understanding why relative tidal elevation differences occur among national datasets and identifies areas of future work that could support more robust vulnerability models.

The incidence of lung cancer amongst primary care chest radiograph referrals-an evaluation of national and local datasets within the United Kingdom.

To determine the incidence of lung cancer amongst primary care referrals for investigation with a chest radiograph (CXR). Retrospective evaluation of datasets from the national Clinical Practice Research Datalink (CPRD) and from a single large regional centre. Data were extracted for cohorts of consecutive adults aged over 40 years for whom a CXR had been performed between 2016 and 2018. Using cancer registry data, the incidence of lung cancer within a 2 years of the CXR referral and the variations with age, gender, and smoking status were evaluated. A total of 291294 CXR events were evaluated from the combined datasets. The incidence of lung cancer amongst primary care CXR referrals was 1.4% in CPRD with a consistent correlation with increasing age and smoking status. The incidence of lung cancer within two-years of the CXR varied between 0.03% (95%CI, 0.0-0.1) amongst never smokers aged 40-45 years to 4.8% (95%CI, 4.2-5.5) amongst current-smokers aged 70-75 years. The findings were similar for the single large centre data, although cancer incidence was higher. A simple estimation and stratification of the risk of lung cancer amongst primary care referrals for investigation with a CXR is possible using age and smoking status. This is the first estimate of the incidence of lung cancer amongst primary care CXR referrals and a demonstration of how the demographic information contained within a request could be used to optimize investigations and interpret test results.

Factors associated with transfer from assisted living facilities to a nursing home: National Health Aging Trends Study 2011-2019.

Residents of assisted living facilities (ALF) transfer to a nursing home when they require a higher level of care, but limited research has examined risk factors for transfer to a nursing home. The aims of this study were to identify (1) baseline factors associated with transfer to a nursing home and (2) time-varying factors associated with transfer to a nursing home over 8 years, using a national dataset from the National Health Aging Trends Study (NHATS). NHATS participants were included in this study if they: (1) resided in ALF from Round 1 (2011) through Round 8 (2018); (2) completed the sample person (SP) interview at baseline; (3) were admitted to ALF at age 65 years or older. We conducted Cox proportional hazards regression to examine candidate predictors (difficulty with basic activities of daily living (ADL), chronic conditions, hospitalization, sleep disturbances, mental health, physical performance, self-reported health, participation in social and physical activity, and sociodemographic) associated with transfer to a nursing home. Employing backward elimination, we built parsimonious final models for analysis. The analytic sample included 970 participants of whom 143 transferred to nursing homes over 8 years. Those who had a better physical performance at baseline (HR = 0.83, 95% CI = 0.79-0.88) and were college educated (HR = 0.58, 95% CI = 0.36-0.92) demonstrated a significantly lower risk for transfer to a nursing home over 8 years. Residents who maintained physical activity (HR = 0.56, 95% CI = 0.37-0.86), better physical performance (HR = 0.87, 95% CI = 0.80-0.94), and difficulty with fewer basic ADLs (HR = 1.13, 95% CI = 1.02-1.26) were at lower risk for transfer to a nursing home over 8 years. Our findings can be used to identify older adults in ALFs at risk of transfer to a nursing home. Strategies to promote physical function and physical activity could avoid/delay the need to transfer. Helping older residents to age in place will have important health and economic benefits.

A guide to large data sets for population-based cancer research: Strengths, limitations, and pitfalls.

With the proliferation of cancer research based on large databases, misalignment of research questions and data set capabilities is inevitable. Nationally maintained databases are appealing to cancer researchers because of the ease of access to large amounts of patient data available for analysis and risk estimation. Data sets that are commonly used in cancer research include the National Cancer Database, the SEER (Surveillance, Epidemiology, and End Results) program of the National Cancer Institute, the SEER-Medicare database, the American College of Surgeons National Surgical Quality Improvement Program, and the Healthcare Cost and Utilization Project databases, among others. Each data set has pros and cons with respect to variable availability and the ability to analyze cancer-specific outcomes. It is critical for researchers to understand the strengths and limitations of each database. Changing variable definitions, the length of postoperative data collection, and the availability of patient-reported outcomes or social determinants of health data are examples of factors that researchers must consider when selecting a data set for research purposes. For the current review, the authors summarized the advantages and disadvantages of various national data sets for cohort studies in cancer populations.

Medical school origins of award-winning anaesthetists; analysis of a complete national dataset

BackgroundThe ultimate aim of medical education is to produce successful practitioners, which is a goal that educators, students and stakeholders support. These groups consider success to comprise optimum patient care with consequently positive career progression. Accordingly, identification of the common educational features of such high-achieving doctors will facilitate the generation of clinical excellence amongst future medical trainees. In our study we source data from British clinical merit award schemes and subsequently identify the medical school origins of anaesthetists who have achieved at least national distinction.MethodsBritain operates Distinction Award/Clinical Excellence Award schemes which honour National Health Service doctors in Scotland, Wales and England who are identified as high achievers. This quantitative observational study used these awards as an outcome measure in an analysis of the 2019–20 dataset of all 901 national award-winning doctors. Where appropriate, Pearson's Chi-Square test was applied.ResultsThe top five medical schools (London university medical schools, Edinburgh, Dundee, Aberdeen and Glasgow) were responsible for 56.4% of the anaesthetist award-winners, despite the dataset representing 85 medical schools. 93.6% of the anaesthetist merit award-winners were from European medical schools. 8.06% of the anaesthetist award-winners were international medical graduates compared with 11.5% non-anaesthetist award-winners being international medical graduates.ConclusionsThe majority of anaesthetists who were national merit award-winners originated from only five, apparently overrepresented, UK university medical schools. In contrast, there was a greater diversity of medical school origins among the lower grade national award-winners; tier 3 award-winners represented 20 different medical schools from three continents. As well as ranking educationally successful university medical schools, this study assists UK and international students, by providing a roadmap for rational decision making when selecting anaesthetist and non-anaesthetist medical education pathways that are more likely to fulfil their career ambitions.

Treatment drop-in in a contemporary cohort used to derive cardiovascular risk prediction equations

BackgroundNo routinely recommended cardiovascular disease (CVD) risk prediction equations have adjusted for CVD preventive medications initiated during follow-up (treatment drop-in) in their derivation cohorts. This will lead to underestimation of...

Mineral Reconnaissance Through Scientific Consensus: First National Prospectivity Maps for PGE–Ni–Cu–Cr and Witwatersrand-type Au Deposits in South Africa

AbstractWe present here the first experimental science (consensus)-based mineral prospectivity mapping (MPM) method and its validation results in the form of national prospectivity maps and datasets for PGE–Ni–Cu–Cr and Witwatersrand-type Au deposits in South Africa. The research objectives were: (1) to develop the method toward applicative uses; (2) to the extent possible, validate the effectiveness of the method; and (3) to provide national MPM products. The MPM method was validated by targeting mega-deposits within the world’s largest and best exploited geological systems and mining districts—the Bushveld Complex and the Witwatersrand Basin. Their incomparable knowledge and mega-deposit status make them the most useful for validating MPM methods, serving as “certified reference targets”. Our MPM method is built using scientific consensus via deep ensemble construction, using workflow experimentation that propagates uncertainty of subjective workflow choices by mimicking the outcome of an ensemble of data scientists. The consensus models are a data-driven equivalent to expert aggregation, increasing confidence in our MPM products. By capturing workflow-induced uncertainty, the study produced MPM products that not only highlight potential exploration targets but also offer a spatial consensus level for each, de-risking downstream exploration. Our MPM results agree qualitatively with exploration and geological knowledge. In particular, our method identified areas of high prospectivity in known exploration regions and geologically and geospatially corresponding to the known extents of both mineral systems. The convergence rate of the ensemble demonstrated a high level of statistical durability of our MPM products, suggesting that they can guide exploration at a national scale until significant new data emerge. Potential new exploration targets for PGE–Ni–Cu–Cr are located northwest of the Bushveld Complex; for Au, promising areas are west of the Witwatersrand Basin. The broader implications of this work for the mineral industry are profound. As exploration becomes more data-driven, the question of trust in MPM products must be addressed; it can be done using the proposed scientific method. Graphical Abstract

Predicting avian diversity based on land use and cover on a national scale

This study explores the relationship between landscape features and avian diversity in South Korea, examining both taxonomic and functional diversity. The Korean Peninsula serves as a pivotal habitat for resident bird species and a migratory pathway in the East Asia-Pacific flyway. Using a national dataset with block sizes ranging from 3.5 to 4.5 kilometers per side, we found that less urbanized open plains exhibit higher taxonomic diversity, while coastal regions with diverse water bird populations show higher functional diversity. These findings underscore the significance of conserving the existing land types and qualities in specific regions to substantially impact bird distribution and regional biodiversity. Remarkably, closed forests display diversity patterns akin to urban/built-up areas, despite their disparate land use characteristics. The stability of bird diversity indices across different land use types enables us to predict bird diversity indices based on the particular land use and land cover configurations. This study emphasizes the complementary nature of functional biodiversity indices in comprehending bird distribution patterns alongside taxonomic diversity indices.

A cost-benefit analysis of the life-prolonging effect of nonsteroidal anti-inflammatory drugs for persons with dementia and pain

ABSTRACT Persons with dementia are more susceptible to pain. If they take Nonsteroidal Anti-Inflammatory Drugs (NSAID) as pain relievers, the policy question is whether these medicines will be socially worthwhile. In this paper, a Cost-Benefit Analysis (CBA) was undertaken of the NSAID to see whether their benefits outweigh the costs for elderly persons with dementia. To construct the benefits, a Quality Adjusted Life Year was used as the intervention output, which was then converted into monetary terms using the Value of a Statistical Life Year. Using estimates based on a large, US national panel data set, the CBA found that the NSAID generated positive net-benefits. It was possible to re-evaluate all the prior dementia interventions that were based on the same data set, using the same methods as for the NSAID CBA. By comparing the NSAID results with those from the other alternative dementia interventions one can establish public funding priorities.

Specialist intellectual disability liaison nurses in general hospitals in England: cohort study using a large mortality dataset

ObjectiveIntellectual disability liaison nurses in general hospitals could enhance access to high-quality, adapted healthcare and improve outcomes. We aimed to explore associations between the input of intellectual disability liaison nurses...

"We Need a Seismic Shift": Disabled Student Perspectives on Disability Inclusion in U.S. Medical Education.

Students with disabilities have inequitable access to medical education, despite widespread attention to their inclusion. Although systemic barriers and their adverse effects on medical student performance are well documented, few studies include disabled students' first-person accounts. Existing first-person accounts are limited by their focus predominantly on students who used accommodations. This study bridged these gaps by analyzing a national dataset of medical students with disabilities to understand their perceptions of disability inclusion in U.S. medical education. The authors analyzed 674 open-text responses by students with disabilities from the 2019 and 2020 Association of American Medical Colleges Year Two Questionnaire responding to the prompt, "Use the space below if you would like to share anything about your experiences regarding disability and medical school." Following reflexive thematic analysis principles, the authors coded the data using an inductive semantic approach to develop and refine themes. The authors used the political-relational model of disability to interpret themes. Student responses were wide-ranging in experience. The authors identified key dimensions of the medical education system that influenced student experiences: program structure, processes, people, and culture. These dimensions informed the changes students perceived as possible to support their access to education and whether pursuing such change would be acceptable. In turn, students took action to navigate the system, using administrative, social, and internal mechanisms to manage disability. Key dimensions of medical school affect student experiences of and interactions with disability inclusion, demonstrating the political-relational production of disability. Findings confirm earlier studies on disability inclusion that suggest systemic change is necessary, while adding depth to understand how and why students do not pursue accommodations. On the basis of student accounts, the authors identify existing resources to help medical schools remedy deficits in their systems to improve their disability inclusion practice.

2234 Temporal trends in Parkinson’s disease-related mortality from 1999–2020: a Nationwide cohort study

Abstract Introduction Parkinson’s disease (PD) is the most common neurodegenerative movement disorder and is associated with significant disability. The prevalence of PD is increasing and the literature demonstrates potential sex and race disparities in patient outcomes. There is a paucity of data about the demographic trends in PD-related mortality in the United States (US). This descriptive study aimed to report the national demographic trends in PD-related mortality over a 20-year period. Methods From January 1999 to December 2020, the US Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiological Research (CDC-WONDER) Underlying Cause of Death database was queried. Data were extracted to determine the PD-related age adjusted mortality rate (AAMR) stratified by age, sex, ethnicity and geographic area, with the 1999 deaths as the reference group. Annual percentage change (APC) for AAMR was then calculated using Joinpoint regression. Results From 1999 to 2020, there were 515,884 PD-related deaths in the study period. AAMR increased from 5.3 per 100,000 population in 1999 to 9.8 per 100,000 in 2020. Males had consistently higher AAMR than females and white race had consistently higher overall AAMR (7.6 per 100,000), followed by American Indians/Alaska Natives (4.4 per 100,000), Asians/Pacific Islanders (4.1 per 100,000) and Black/African Americans (3.4 per 100,000). The Midwest had the highest AAMR followed by West, South and Northeast. Utah, Idaho and Minnesota had the highest state-level AAMR. Conclusion This study using a national dataset identified significant age, sex, race and geographic disparities in PD-related mortality in the US. Older age, male sex, white race and Midwest locality were associated with the highest AAMR.

Elevation-dependent biases of raw and bias-adjusted EURO-CORDEX regional climate models in the European Alps

Data from the EURO-CORDEX ensemble of regional climate model simulations and the CORDEX-Adjust dataset were evaluated over the European Alps using multiple gridded observational datasets. Biases, which are here defined as the difference between models and observations, were assessed as a function of the elevation for different climate indices that span average and extreme conditions. Moreover, we assessed the impact of different observational datasets on the evaluation, including E-OBS, APGD, and high-resolution national datasets. Furthermore, we assessed the bi-variate dependency of temperature and precipitation biases, their temporal evolution, and the impact of different bias adjustment methods and bias adjustment reference datasets. Biases in seasonal temperature, seasonal precipitation, and wet-day frequency were found to increase with elevation. Differences in temporal trends between RCMs and observations caused a temporal dependency of biases, which could be removed by detrending both observations and RCMs. The choice of the reference observation datasets used for bias adjustment turned out to be more relevant than the choice of the bias adjustment method itself. Consequently, climate change assessments in mountain regions need to pay particular attention to the choice of observational dataset and, furthermore, to the elevation dependence of biases and the increasing observational uncertainty with elevation in order to provide robust information on future climate.

Life Course Models of Child Maltreatment: Effects on General Psychopathology Outcomes in a Longitudinal Sample.

The study compared life course models (LCM; accumulation, recency, and sensitive period) of child maltreatment and general psychopathology in a large, national longitudinal data set of 1354 youth ages birth-16years (657 boys, 53.2% Black, 59.7% <$40K caregiver income). Previous research has supported the accumulation and recency models, albeit with shorter or fewer time periods of outcome measurement. We extend this work by modeling the impact of combined abuse and neglect allegations on a general psychopathology factor (dysregulation profile). Cross-sectional structural equation models were constructed using LCMs and tested across two-year periods from 4-16years old and compared using Akaike Information Criterion weights. The recency variable generally explained the greatest proportion of variance in psychopathology. Notably, maltreatment more proximal to the time of outcome measurement had the strongest effect, suggesting that more recent maltreatment may have stronger effects on general psychopathology. These results lend support to a recency effect of maltreatment on psychopathology outcomes, although substantive overlaps with the accumulation model are noted.

State inequities: Gaps in planned treatment for criminal legal referrals with opioid use disorder across two decades of US treatment admissions.

Criminal-legal (CL) referrals to addiction treatment have historically had low utilization of medications for opioid use disorder (MOUD). While state differences have been reported, an in-depth longitudinal analysis of state-by-state differences is lacking. The Substance Abuse and Mental Health Services Administration Treatment Episode Dataset-Admissions 2000-2020 provided data for individuals entering their initial treatment with an opioid as their primary substance. Outcome was planned use of MOUD, assessing odds ratio (OR) of CL referrals relative to non-CL referrals cumulatively over the 21-year period and as incremental change (change in relative disparity) using effect sizes, stratified by each state. 2,187,447 cases met the criteria. Planned MOUD occurred in 37.7% of non-CL clients versus 6.5% of CL clients (OR = 0.11, 95% confidence interval = 0.11-0.12). For all clients, planned MOUD increased from 2000 (33.9%) to 2020 (44.8%). This increase was blunted within CL clients, increasing from 2000 (6.4%) to 2020 (13.3%). Rhode Island saw the greatest improvements in equity. While rates of planned MOUD increased over the 21 years, a significant disparity persisted among CL clients in most states. As opioid use disorders and opioid-related overdoses are more prevalent among those involved with the CL system, improving this has high impact. Provides the most comprehensive analysis of state-by-state inequities in MOUD access for CL relative to non-CL referrals over a 21-year period through use of a national data set. Positive outliers are used as case examples for others to follow in pursuit of more equitable care.

Variability in Kidney Cancer Treatment and Survival in England: Results of a National Cohort Study

AimsTo establish whether there are geographic differences in treatments and outcomes for patients with kidney cancer (KC) in England which could potentially be improved by the creation of national guidelines. Materials and methodsA multidisciplinary group convened by the charity Kidney Cancer UK developed Quality Performance Indicators (QPIs) for the treatment of KC. Adherence to these QPIs was reported for all patients with a histological diagnosis of KC diagnosed in England between 2017 and 2018. Utilising data extracted from national datasets, logistic and linear probability models were used to estimate geographic variation in the delivery of surgery and systemic anti-cancer therapy at Cancer Alliance and NHS trust levels. Results were adjusted for a priori confounders, including age at diagnosis, area deprivation of residence, and Charlson Comorbidity Index. Differences in overall survival are reported. ResultsThe cohort comprised 18,640 tumours in 18,421 patients. Of tumours diagnosed, median patient age was 68 (interquartile range 58–77) years and 63.4% were in males. When stratified by Cancer Alliance, the proportions of T1a/T1b/N0/M0 KC that had radical nephrectomy (RN), nephron sparing surgery or ablation ranged from 53.3% (95% CI [48.7, 57.8]) to 80.3% (95% CI [73.0, 86.0]). For stage T1b-3 cancers, the proportion that received RN ranged from 65.6% (95% CI [60.3, 70.5]) to 77.3% (95% CI [72.1, 81.7]). Patients with M0 (n = 12,365) and M1 KC (n = 3312) at diagnosis had 24-month survival of 87.5% and 25.1%, respectively. Of patients diagnosed with M1 KC, 50.3% received systemic anti-cancer therapy, ranging from 39.7% (95% CI [33.7, 46.1]) to 70.7% (95% CI [59.6, 79.8]) between Cancer Alliances. The six-month survival of these patients was 77.4% compared to 27.6% for those that did not receive SACT. ConclusionThese major geographical differences in surgical and systemic therapy practice have led to national guideline development.

CHILD MIGRATION TRENDS IN INDIA: INSIGHTS FROM NATIONAL DATASETS

The child migration in India is a complex socio-economic phenomenon profoundly impacting childrens well-being and development. This paper analyzes trends and vulnerabilities among child migrants using national datasets, focusing on education, health, and socio-economic disparities.The study identifies a significant increase in internal migration, predominantly rural, driven by familial and economic factors. Gender disparities show higher migration rates among boys, influenced by socio-cultural norms and economic incentives. The regional disparities highlight Goa, Kerala, and Maharashtra as key migration hubs, shaped by economic opportunities and cultural dynamics. Despite higher literacy rates, migrant children face challenges like early employment and educational disruptions. Health outcomes vary, with improved nutrition but lower immunization coverage compared to non-migrant peers.Child marriage rates among migrant girls underscore socio-economic inequities. Vulnerability analysis reveals risks among economically disadvantaged and rural migrants, necessitating targeted policy interventions. The policy recommendations stress legal enforcement against child marriage and robust implementation of education and child labor laws. Collaborative efforts involving government, NGOs, and communities are crucial to address the needs of child migrants, especially from marginalized groups.This research paper informs inclusive policies to protect child migrants rights and opportunities, aiming for a more equitable societal framework.

Medical school origins of award-winning pathologists; analysis of a complete national dataset

BackgroundThe ultimate aim of medical education is to produce successful practitioners, which is a goal that educators, students and stakeholders support. These groups consider success to comprise optimum patient care with consequently positive career progression. Accordingly, identification of the common educational features of such high-achieving doctors will facilitate the generation of clinical excellence amongst future medical trainees. In our study we source data from British clinical merit award schemes and subsequently identify the medical school origins of pathologists who have achieved at least national distinction.MethodsBritain operates Distinction Award/Clinical Excellence Award schemes which honour National Health Service doctors in Scotland, Wales and England who are identified as high achievers. This quantitative observational study used these awards as an outcome measure in an analysis of the 2019-20 dataset of all 901 national award-winning doctors. Where appropriate, Pearson’s Chi-Square test was applied.ResultsThe top five medical schools (London university medical schools, Aberdeen, Edinburgh, Oxford and Cambridge) were responsible for 60.4% of the pathologist award-winners, despite the dataset representing 85 medical schools. 96.4% of the pathologist merit award-winners were from European medical schools. 9.0% of the pathologist award-winners were international medical graduates in comparison with 11.4% of all 901 award-winners being international medical graduates.ConclusionsThe majority of pathologists who were national merit award-winners originated from only five, apparently overrepresented, UK university medical schools. In contrast, there was a greater diversity in medical school origin among the lower grade national award-winners; the largest number of international medical graduates were in these tier 3 awards (13.9%). As well as ranking educationally successful university medical schools, this study assists UK and international students, by providing a roadmap for rational decision making when selecting pathologist and non-pathologist medical education pathways that are more likely to fulfil their career ambitions.