Geographic Disparities Research Articles

Online Learning Challenges Encountered by University Students Amidst the COVID-19 Pandemic: A Systematic Review of Digital Divide Perspective

The COVID-19 has required a rapid conversion from the conventional learning to online learning, revealing and intensifying the digital inequality amongst university pupils. The primary objectives of this systematic review study are to identify the digital divide challenges encountered by university students in online learning amidst the COVID-19 pandemic and to understand the underlying reasons contributing to these challenges. This study focuses on empirical research published between 2020 and 2023. The review utilized the seven phases of systematic review recommended by the Evidence for Policy and Practice Information and Co-ordinating Centre. A comprehensive Scopus and Web of Science search was undertaken using word string "higher education/university education/university students", "online learning/distance learning," "COVID-19/pandemic,” “digital divide/digital inequality/digital exclusion," and, and the initially 190 articles were extracted.The criteria for inclusion restricted the number of publications that were examined to a total of 11. The analysis reveals two primary categories of digital divide challenges: the first-level digital divide, characterized by limited access to essential digital devices and internet connectivity, and the second-level digital divide, which relates to varying levels of digital competency among students.Key factors contributing to these challenges include financial constraints, geographical disparities, and inadequate technological infrastructure. Students from economically disadvantaged backgrounds and rural areas faced significant obstacles in engaging with online learning platforms, leading to adverse academic outcomes. Strategies for bridging the digital divide should be implemented in collaboration with educational institutions, government agencies, and private sector stakeholders. These strategies should focus on the enhancement of technological infrastructure, the provision of financial support, and the provision of digital literacy training programs. The review highlights the importance of understanding the digital divide in shaping future educational practices and policies, aiming to create a more inclusive and resilient higher education system in the post-pandemic era. By addressing the identified challenges, institutions can empower all students to succeed in an increasingly digital learning environment.

Distribution and determinants of early marriage and motherhood: a multilevel and geospatial analysis of 707 districts in India

BackgroundEarly marriage and motherhood have long been prevalent in India, with 44.5% of women aged 20–24 reporting marriage before 18 in NFHS 3 (2005–2006), dropping to 26.8% in NFHS 4 (2015–2016). Early motherhood has also seen a significant decline, with first births by age 18 decreasing from 34.3% in NFHS I to 8.2% in NFHS V. Despite these improvements, significant regional disparities persist due to social, normative, and legal factors. This study investigates the spatial heterogeneity of early marriage and motherhood across Indian districts, offering a multilevel analysis that reveals critical local variations often obscured at broader levels. Understanding these patterns is crucial for targeted policy interventions and addressing the root causes of early marriage and motherhood.MethodsUtilizing data from the fifth round of National Family Health Survey, this study employs multilevel logistic regression and geospatial analysis to assess the determinants and spatial distribution of early marriage and early motherhood among ever-married women in India. The analysis incorporates individual, household, and community-level variables, complemented by spatial analysis techniques, including Empirical Bayes Bivariate Moran’s I values and LISA cluster maps, to identify regional patterns and hotspots.ResultsThis study revealed that educational attainment emerged as a critical determinant, with uneducated women significantly more likely to marry early. Socioeconomic factors, such as poverty and limited mass media exposure, also heightened the risk of early marriage and motherhood. Caste and religion were significantly associated with these events, with marginalized groups facing higher prevalence. Spatial analysis revealed significant geographic disparities, with central and eastern regions showing higher concentrations of early marriage and motherhood. District-level characteristics and the influence of neighboring districts were also significant, highlighting the importance of localized interventions.ConclusionsThe findings underscore the critical role of education, economic empowerment, and media literacy in mitigating early marriage and motherhood risks. The study calls for multi-sectoral interventions in geographical hotspots to break the cycle of early family formation and promote reproductive health. Policies enhancing educational opportunities, addressing economic disadvantages, and considering district-specific factors are essential. Comprehensive strategies are necessary to empower women, foster reproductive health, and address the multifaceted nature of early marriage and motherhood in India.

Geographical disparities in temporal trends of low birth weight in Saskatchewan from 2002/2003 to 2021/2022: insights from a joinpoint regression analysis.

Low birth weight (LBW) is an important public health indicator that is associated with various negative health outcomes in infants. To effectively implement interventions that would improve health outcomes in children, it is important to understand both the historical trends and current levels of LBW rates. In this study, trends and regional differences in LBW rates in Saskatchewan from 2002/2003 to 2021/2022 were assessed. A joinpoint regression analysis was conducted using historical LBW rates, obtained from the Canadian Institute for Health Information database. Data were analysed using average percent change and average annual percent change. Spatial patterns and trends were identified using a choropleth map. From a provincial and national rate of 5.2% in 2002/2003, the LBW rate in Saskatchewan increased to 6.5% in 2021/2022, approaching the national rate of 6.8%. Over the 20-year period, average annual changes for Canada were 1.4% and 1.0% for Saskatchewan. There was a turning point in the study: 2004/2005 for Canada and 2011/2012 for Saskatchewan. Initially, Saskatchewan had stable LBW rates, increasing yearly by 0.1%, while the national rate was 5.7%. However, in recent years, Saskatchewan's rate increased to 1.8% annually, surpassing the national rate of 0.9%. Geographical differences were also observed within Saskatchewan, with the Far North region having the highest LBW rate (9.2%), and the Central West region having the lowest rate (4.3%) in 2021/2022. The Central East, Regina Qu'Appelle, and southern Saskatchewan saw significant upwards trends in LBW rates between 2015/2016 and 2021/2022. There is an increasing trend in LBW rates in Canada and Saskatchewan, as well as geographical disparities within the province. The geographical disparities in LBW rates underscore the need for tailored interventions in high-risk regions in the province.

Guidelines in Neurosurgery: a critical appraisal.

The process of grading and stratifying evidence in the extensive literature on neurosurgical guidelines has evolved significantly, ranging from high-quality standards to suggested options. However, the methodology for guideline development has become increasingly complex, leading to challenges in their application across various neurosurgical specialties and settings. This mini review aims to explore the practical implications of published suggestions for managing neurosurgical patients. A critical and focused collection of published literature concerning guidelines in different neurosurgical topics, from Pubmed and other sources formed the basis of this non-systematic narrative review. Only guidelines produced by neurosurgeons in the era of evidence based medicine (after 1996) were included. Neurosurgical guidelines often rely on a limited number of Randomized Controlled Trials (RCTs) and Class I evidence, particularly in surgical and emergency contexts where randomization of patient treatments may conflict with established clinical practices. Challenges also include the timely update of guidelines, which sometimes lags behind rapid shifts in evidence, and varying methodologies in guideline production that can result in divergent recommendations. Geographical disparities in disease burden and literature production further influence guideline applicability, suggesting a need for greater inclusion of authors from Low- and Middle-Income Countries (LMICs) to enhance realism and global relevance. Consensus conferences and expert reviews may serve as viable alternatives to address these challenges. While Evidence-Based Medicine remains pivotal, critical appraisal and practical application of guidelines must consider these complexities to optimize patient care and outcomes.

Spatial heterogeneity in unintended pregnancy and its determinants in India

BackgroundUnderstanding the geographic variation of unintended pregnancy is crucial for informing tailored policies and programs to improve maternal and child health outcomes. Although spatial analyses of unintended pregnancy have been conducted in several developing countries, such research is lacking in India. This study addresses this gap by investigating the geographic distribution and determinants of unintended pregnancy in India.MethodsWe analysed data from the National Family Health Survey-5 encompassing 232,920 pregnancies occurring between 2014 and 2021 in India. We conducted a spatial analysis to investigate the distribution of unintended pregnancies at both state and district levels using choropleth maps. To assess spatial autocorrelation, Global Moran’s I statistic was employed. Cluster and outlier analysis techniques were then utilized to identify significant clusters of unintended pregnancies across India. Furthermore, we employed Spatial Lag Model (SLM) and Spatial Error Model (SEM) to investigate the factors influencing the occurrence of unintended pregnancies within districts.ResultsThe national rate of unintended pregnancy in India is approximately 9.1%, but this rate varies significantly between different states and districts of India. The rate exceeded 10% in the states situated in the northern plain such as Haryana, Delhi, Uttar Pradesh, Bihar, and West Bengal, as well as in the Himalayan states of Himachal Pradesh, Uttarakhand, Sikkim, and Arunachal Pradesh. Moreover, within these states, numerous districts reported rates exceeding 15%. The results of Global Moran’s I indicated a statistically significant geographical clustering of unintended pregnancy rates at the district level, with a coefficient of 0.47 (p < 0.01). Cluster and outlier analysis further identified three major high-high clusters, predominantly located in the districts of Arunachal Pradesh, northern West Bengal, Bihar, western Uttar Pradesh, Haryana, Delhi, alongside a few smaller clusters in Odisha, Madhya Pradesh, Uttarakhand, and Himachal Pradesh. This geographic clustering of unintended pregnancy may be attributed to factors such as unmet needs for family planning, preferences for smaller family sizes, or the desire for male children. Results from the SEM underscored that parity and use of modern contraceptive were statistically significant predictors of unintended pregnancy at the district level.ConclusionOur analysis of comprehensive, nationally representative data from NFHS-5 in India reveals significant geographical disparities in unintended pregnancies, evident at both state and district levels. These findings underscore the critical importance of targeted policy interventions, particularly in geographical hotspots, to effectively reduce unintended pregnancy rates and can contribute significantly to improving reproductive health outcomes across the country.

Health benefits of US light-duty vehicle electrification: Roles of fleet dynamics, clean electricity, and policy timing

We present a dynamic perspective to quantify the air quality-related health impacts of the electrification of light-duty vehicles in the United States between 2022 and 2050. Using a fleet turnover model and future electricity generation mix scenarios, we compare ambitious vehicle electrification to fleet renewal relying on newer internal combustion engine vehicles, without electric vehicles. The model includes vehicle-level pollutant emission factors and a reduced complexity air quality and valuation model and covers direct (tailpipe, brake wear, and tire wear) and indirect (production of electricity and liquid fuels) emissions of NOx, SO2, PM2.5, NH3, and VOCs, with a breakdown at the county level to identify geographical disparities in the distribution of health impacts. Short-term health benefits are mostly generated by reductions in NOx emissions from newer gasoline vehicles, while fleet electrification generates further benefits in the long term. The electricity mix plays a crucial role in the success of electrification policies. With continued grid decarbonization, electrification would reduce harmful air quality-related health impacts cumulatively by 84 to 188 billion USD over the study period, compared with fleet renewal without electric vehicles. In contrast, artificially freezing the 2022 grid would make electrification responsible for 32 to 71 billion USD additional health disbenefits compared with fleet renewal. Finally, we show that while fleet electrification achieves most of its benefits over fleet renewal in the long term, delaying the implementation of such policies would sacrifice meaningful cumulative benefits.

Brexit and the London housing market: An empirical contribution

This study aims to analyse the impact of Brexit on London’s housing market, exploring socio-economic and regional disparities. By examining property transaction data from 2012 to 2022, the research seeks to understand how Brexit has influenced real housing prices across different boroughs of London. The methodology involves aggregating transaction data from the Her Majesty (HM) Price Paid database and normalizing prices using the Consumer Price Index (CPI) to obtain real price variations. These data were segmented into three distinct periods: pre-Brexit (2012–2016), post-plebiscite Brexit (2016–2019), and post-implementation Brexit (2020–2022). Spatial analysis was conducted using the software Quantum Geographic Information System (QGIS), transforming point data (postcodes) into polygonal data (wards) for better visualization and comparison. The findings reveal significant socio-economic impacts, with traditionally affluent areas such as Westminster, Kensington, and Chelsea experiencing notable declines in real housing prices. Conversely, certain outer boroughs like Newham and Barnet showed resilience, with positive real price variations despite decreased sales. This geographical disparity underscores the uneven distribution of Brexit’s economic consequences, highlighting the critical role of localized economic policies and development projects in mitigating adverse effects. The results confirm existing literature on the polarization and regional inequalities exacerbated by Brexit while providing new insights into the complex interplay of local and global factors affecting housing markets. The findings emphasize the need for targeted policy interventions to address the diverse challenges posed by Brexit, ensuring both affluent and disadvantaged areas receive adequate support. This research is crucial for informing public policy, urban planning, and housing market strategies in a post-Brexit context, promoting equitable and sustainable development across London.

Geographical variation, socioeconomic inequalities of low birth weight, and its relationship with maternal dietary diversity: Insights from the maternal infant and young child nutrition programme in Bangladesh.

Globally, every year, 20 million neonates are born with weights below 2500 g and are considered low birth weight (LBW). About 90% of these births occur in low- and middle-income countries. Information regarding the geographical variation, socioeconomic inequalities of LBW neonates, and the relationship between maternal inadequate dietary diversity and LBW is limited in rural areas of Bangladesh. We aimed to explore the geographical disparities and socioeconomic inequalities in the prevalence of LBW and its association with inadequate maternal dietary diversity. We extracted data from a large-scale evaluation programme conducted as a part of the maternal infant and young child nutrition phase two in Bangladesh, implemented by BRAC. We used the concentration index (CIX) to measure the socioeconomic inequalities of LBW. We performed a cluster-adjusted multiple logistic regression analysis to determine the association between LBW and maternal dietary diversity. A total of 4651 children aged <5 years with their mother's information were included. The overall prevalence of LBW was 13.5%. About 16% of mothers living in the poorest wealth quintile gave birth to LBW babies, whereas 10% of mothers living in the richest households gave birth to LBW babies. The CIX exhibited LBW babies were more prevalent among the socioeconomically worst-off (poorest) group (CIX = -0.08), indicating mothers of the poorest households are vulnerable to giving birth to normal-weight babies. An adjusted multiple logistic regression model indicated that mothers with inadequate dietary diversity had higher odds (adjusted odds ratio (AOR) = 1.27; 95% confidence interval (CI) = 1.04, 1.54) of giving birth to LBW babies. Notably, in the interaction of mothers' age and dietary diversity, we found that adolescent mothers (aged ≤ 19 years) with inadequate dietary diversity had 2.56 times (AOR = 2.56; 95% CI = 1.14, 5.76) higher odds of giving birth to LBW babies compared to adult mothers (aged >19 years) who consumed diversified foods. Intervention strategies for reducing LBW prevalence should target the poorest households. Also, interventions for improving the dietary diversity of adolescent pregnant mothers are expected to reduce the number of LBW babies from the rural areas of Bangladesh.

Liver Cancer Etiology: Old Issues and New Perspectives.

This review aims to synthesize the old issues and current understandings of the etiology of liver cancer, focusing on the diverse causative factors influenced by geographical, socioeconomic, and lifestyle variations across different regions. We highlight significant geographic disparities in liver cancer risk factors. While hepatitis B and C viruses, aflatoxin exposure, and alcohol consumption remain globally established contributors; metabolic dysfunction-associated steatotic liver disease and metabolic syndromes are increasingly prominent in the West. Chronic HBV and aflatoxin continue to dominate as risk factors in Asia and Africa. Dietary factors, metabolic diseases like diabetes and obesity, genetic predispositions, environmental risk factors and lifestyle choices such as smoking and alcohol use play substantial roles in specific populations. Protective factors like coffee and tea consumption, along with aspirin use, vegetables and fruits have shown potential in reducing HCC risk, although findings vary by population and dietary habits. Liver cancer etiology is influenced by various factors that differ by region. Established risk factors include hepatitis B and C, aflatoxin, and alcohol. Emerging risks, such as metabolic dysfunction-associated steatotic liver disease, are more prevalent in Western countries, while aflatoxin and HBV remains significant in Asia and Africa. Diet, metabolic conditions like diabetes and obesity, genetic predispositions, and lifestyle choices also play crucial roles. Coffee, tea, aspirin, vegetables, and fruits may reduce HCC risk, but effectiveness varies. Future research should integrate epidemiology, genetics, and nutrition, with global cooperation and data sharing essential for effective cancer control strategies.

Modeling cigarette smoking exposure in subsets of the population

Modeling cigarette smoking exposure in subsets of the population Understanding and acknowledging various factors that impact cigarette smoking and exposure is critical when creating public health interventions to curb tobacco use. Here, Theodore R. Holford from Yale University discusses the impact of different approaches to tobacco control. The harmful effects of cigarette smoking have been widely recognized for more than 50 years (1), and the huge toll that it has taken in shortening lives has led to the recognition of an urgent need to reduce associated exposure. Because cigarette smoking is an addictive behavior, it has been a public health challenge to reduce the level of exposure in the population, even though alternative approaches have been used. These approaches include the introduction of taxes that increase cost to users, changing the legal age at which cigarettes can be purchased, introducing clean air laws that limit locations where individuals are allowed to smoke, and establishing resources that will assist those who wish to quit smoking. These efforts can be undertaken on a national level, but more often, such efforts are implemented at different times and in different ways in different regions. In the US, these laws are more commonly introduced by a state, county, or city. (2) This introduces geographic disparities in cigarette smoking exposure, and it is important to understand these differences when planning approaches to protect public health.

Trends in racial/ethnic and geographic disparities in substance use disorders mortality in the United States, 2000-2019.

Substance use disorders (SUD) are a major public health concern in the United States. This study examined racial/ethnic and state-level disparities in SUD mortality in the United States from 2000 to 2019. Age-standardized mortality rates for SUD were obtained for 5 racial/ethnic groups (White respondents, Black respondents, Latino, Asian-Pacific Islander [API], American Indian/Alaska Native [AIAN]) by state and sex from 2000 to 2019. Joinpoint regression analysis was used to model temporal trends overall and by demographic factors. From 2000 to 2019, the overall mortality rate increased from 8.0 to 28.8 deaths per 100,000 population across all groups. AIANs had the highest mortality in 2019 (57.8 per 100,000), followed by Black respondents, White respondents, Latinos, and APIs. Significant increases occurred across all racial/ethnic groups, with the greatest average annual percentage change (AAPC2000-2019) among White respondents (6.7%; 95% confidence interval [CI]: 6.2%-7.3%), APIs (6.0%, 95% CI: 5.6%-6.2%), and AIANs (5.9%, 95% CI: 5.6%-6.2%). Mortality rates increased more rapidly for females than males among White respondents, AIANs, Black respondents, and Latinos. Substantial state-level variation emerged, with the highest mortality rates in 2019 seen in West Virginia, the District of Columbia, Delaware, Ohio, and Pennsylvania. Racial/ethnic and geographic disparities in SUD mortality have widened significantly from 2000 to 2019, highlighting priority areas for prevention efforts. This study provides detailed insights into long-term trends in racial, ethnic, and geographic disparities in SUD mortality across the United States, informing targeted prevention and intervention strategies.

Chemotherapy-induced peripheral neuropathy among breast cancer survivors

This review investigates that effective cancer treatment enhances the number of survivors in Denmark, but late complications like chemotherapy-induced peripheral neuropathy (CIPN) are a challenge. CIPN affects sensory nerves and can persist post-treatment. Diagnosis relies on symptoms and the medical history. Treatment options are limited and management faces geographic disparities and clinical capacity issues. Future research targets predictive markers and possible preventative interventions. CIPN, among other late complications, remains a significant concern in survivorship care.

MNGA-04 SOCIOECONOMIC DISPARITIES IN ACCESS TO SUBSPECIALTY CARE FOR MENINGIOMA PATIENTS: A LITERATURE REVIEW

Abstract Meningiomas, the most prevalent brain tumors, constitute nearly 40% of all head tumors, with the majority being benign. Presenting symptoms vary widely, including headaches, vision changes, seizures, and extremity weakness. Given the frequency of meningiomas and their diverse symptoms, access to subspecialty care is crucial for determining treatment necessity. However, existing global healthcare disparities often limit access to the necessary subspecialty care for addressing meningiomas. This literature review investigates the impact of socioeconomic disparities on neuro-oncologic care access, drawing from retrospective cohort studies and multi-cohort analyses. PubMed was utilized to search for articles published between 2000 and 2024, focusing on the relationship between socioeconomic status (SES) and care access, treatment, and outcomes among meningioma patients. Demographic analyses across studies revealed disparities in access to care across age groups, from young adults (20-39 years old) to the elderly (60 years and older). Additionally, disparities were noted among racial and ethnic groups, including African American, Hispanic, and Caucasian populations. Geographic disparities were also evident, with studies spanning regions within the United States and globally, underscoring variations in healthcare access and outcomes. Findings consistently emphasized the disproportionate burden borne by individuals from lower SES backgrounds, characterized by delayed diagnosis, limited treatment options, and poorer survival rates compared to their higher SES counterparts. Structural barriers, such as inadequate health literacy, limited insurance coverage, and geographical constraints, were significant contributors to these disparities, perpetuating health inequities among meningioma patients. Addressing disparities requires comprehensive interventions, including policy reforms to improve insurance coverage, enhance specialist access, and promote culturally sensitive care. Prioritizing initiatives targeting socioeconomic barriers ensures equitable care for all meningioma patients. In conclusion, concerted efforts at all levels are needed to dismantle structural barriers and foster equitable healthcare access and delivery.

Higher levels of neighborhood deprivation and risk for incident colorectal cancer and mortality outcomes: A systematic review and meta-analysis.

131 Background: Significant geographic and racial disparities exist for colorectal cancer (CRC) incidence and mortality in the United States (US), which may be caused by neighborhood-level deprivation and limited access to preventative cancer screening. We completed the first systematic review and meta-analysis of neighborhood-level deprivation in relation to CRC incidence, mortality, and screening among individuals from the US. Methods: A systematic literature review was completed to identify original research articles from PubMed, Scopus, and Web of Science. Eligible studies reported associations between deprivation at the census block or tract level using a validated deprivation index (e.g. the Area Deprivation Index or Yost Index) and CRC incidence, mortality, or screening outcomes in a US-based sample. A fixed-effects meta-analysis was completed using inverse-variance weighting to estimated hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (CIs) for CRC incidence, mortality, and screening outcomes, comparing the highest vs. lowest quantiles of neighborhood-level deprivation. All analyses were completed using the meta package in R. Results: In total, 19 studies were included in the meta-analysis. Living in a neighborhood in the highest quantile of deprivation was associated with significantly higher risk for incident CRC (HR 1.37, 95% CI 1.34-1.41, seven studies). In stratified analysis, positive associations with incident CRC were observed for White (HR 1.43, 95% CI 1.39-1.47, three studies), Black (HR 1.18, 95% CI 0.96-1.44, three studies), and Asian/Pacific Islander individuals (HR 1.18, 95% CI 1.08-1.28, two studies). For individuals diagnosed with CRC, higher deprivation was associated with elevated risk for overall mortality (HR 1.11, 95% CI 1.10-1.13, four studies) and CRC-specific mortality (HR 1.17, 95% CI 1.15-1.19, seven studies). Higher deprivation was associated with lower completion of recommended screening for CRC, including colonoscopy, sigmoidoscopy, or fecal occult blood testing (OR 0.76, 95% CI 0.74-0.79, four studies). Conclusions: Individuals who reside in neighborhoods with high levels of deprivation have significantly elevated risk for CRC incidence and mortality compared to individuals from low deprivation neighborhoods. Targeting healthcare resources to highly deprived neighborhoods to increase uptake of preventative screening may help to address racial and geographic disparities for CRC.

Geographic Disparities In Physical Activity, Sedentary Behavior, Play Time, And BMI In Nigerian Preschoolers

Geographic Disparities In Physical Activity, Sedentary Behavior, Play Time, And BMI In Nigerian Preschoolers

Trends and Racial and Geographic Disparities in AKI-Related Mortality Rate in the United States, 1999-2019

Trends and Racial and Geographic Disparities in AKI-Related Mortality Rate in the United States, 1999-2019

Current Burden of and Geographic Disparities in Liver Mortality and Access to Liver Transplant

Liver disease is a leading cause of mortality in the US. Liver transplant can be a lifesaving procedure for patients with severe liver disease. To assess temporal trends and geographic variance in liver-related mortality (LRM) and liver transplant in the US. In this cohort study, the frequencies and geographic variance of LRM in 2018 and 2021 were obtained in a cross-sectional analysis of the Underlying Cause of Death data available on the Centers for Disease Control and Prevention's Epidemiologic Research database. The number of livers donated and transplanted according to the state of residence of each donor and recipient were obtained from the United Network for Organ Sharing. Liver-related mortality in 2018 and 2021, overall and by state, as well as the liver transplant rate according to state of residence of recipient and donor. Overall LRM in the US was 93 418 in 2021, with a crude rate of 28.1 per 100 000 individuals, an increase of 19.1% compared with rates seen immediately prior to the COVID-19 pandemic in 2018 (77 282 [23.6 per 100 000 individuals]). Liver-related mortality in 2021 varied several-fold between states, from 18.4 per 100 000 individuals per year in Utah to 65.9 per 100 000 individuals per year in New Mexico. The mean number of liver-related deaths per transplant from all donor sources (in state and out of state) was 7.2 in the lowest LRM quintile compared with 21.5 in the highest (95% CI, 12.1-16.6; SE, 1.1; P < .001). Ten states had no liver transplant center. Paradoxically, residents of states with the highest LRM had a much lower rate of liver transplant (at any location) from organs procured from in-state residents than states with the lowest LRM quintile (13.0% vs 35.2% in-state donors; 95% CI, 14.1%-30.3%; SE, 3.9%; P < .001). This study suggests that rates of LRM have increased dramatically since the COVID-19 pandemic and vary several-fold between states. Rates of liver transplant are paradoxically lowest among residents living in states with the highest LRM. These findings highlight apparent geographic disparities in access to liver transplant that allocation policy cannot address.

Community profiles in northeastern and central Pennsylvania characterized by distinct social, natural, food, and physical activity environments and their relation to type 2 diabetes.

Understanding geographic disparities in type 2 diabetes (T2D) requires approaches that account for communities' multidimensional nature. In an electronic health record nested case-control study, we identified 15,884 cases of new-onset T2D from 2008 to 2016, defined using encounter diagnoses, medication orders, and laboratory test results, and frequency-matched controls without T2D (79,400; 65,069 unique persons). We used finite mixture models to construct community profiles from social, natural, physical activity, and food environment measures. We estimated T2D odds ratios (OR) with 95% confidence intervals (CI) using logistic generalized estimating equation models, adjusted for sociodemographic variables. We examined associations with the profiles alone and combined them with either community type based on administrative boundaries or Census-based urban/rural status. We identified four profiles in 1069 communities in central and northeastern Pennsylvania along a rural-urban gradient: "sparse rural," "developed rural," "inner suburb," and "deprived urban core." Urban areas were densely populated with high physical activity resources and food outlets; however, they also had high socioeconomic deprivation and low greenness. Compared with "developed rural," T2D onset odds were higher in "deprived urban core" (1.24, CI = 1.16-1.33) and "inner suburb" (1.10, CI = 1.04-1.17). These associations with model-based community profiles were weaker than when combined with administrative boundaries or urban/rural status. Our findings suggest that in urban areas, diabetogenic features overwhelm T2D-protective features. The community profiles support the construct validity of administrative-community type and urban/rural status, previously reported, to evaluate geographic disparities in T2D onset in this geography.

Geographic disparities in primary care physicians: Local impact on long-term outcomes in adult liver transplant recipients

BackgroundGeographic inequities are known to affect access to liver transplant (LT); however, the impact of these disparities postoperatively remains unknown. We focus on primary care physicians (PCPs), as frequent managers of long-term LT recipient care. MethodsClinical data on adults undergoing liver-only transplant 2010–2021 were obtained from the Organ Procurement and Transplantation Network and linked to zip code-based PCP density and social vulnerability index (SVI) data to quantify the impact of PCP density on graft and overall survival. Results64,593 patients were divided into quintiles by PCP density. Compared to patients in the lowest PCP quintile, patients in the 3rd, 4th, and 5th quintiles had 6%–8% lower mortality risk (HR3rd ​= ​0.94, HR4th ​= ​0.92, HR5th ​= ​0.94, p for trend ​= ​0.002). PCP density remained significant after accounting for SVI and local surgeon and gastroenterologist availability (p ​= ​0.002). ConclusionsIncreased PCP availability is associated with improved survival, emphasizing the importance of establishing longitudinal care.

Associations Among Circle-Based Kidney Allocation, Center Waiting Time, and Likelihood of Deceased-Donor Kidney Transplantation

The kidney allocation system (KAS250), using circle-based distribution, attempts to address geographic disparities through broader sharing of deceased-donor kidney allografts. This study sought to evaluate the association between KAS250 and likelihood of deceased-donor kidney transplantation (DDKT) among waitlisted candidates, and whether the policy has differentially affected centers with shorter vs. longer waiting time. Retrospective cohort study. & Participants: 160,941 candidates waitlisted at 176 transplant centers between 3/2017-3/2024. KAS250 allocation policy. Rate of DDKT. Multivariable Cox regression, modeling KAS250 as a time-dependent variable. KAS250 was not independently associated with likelihood of DDKT overall (HR=1.01 vs. pre-KAS250, 95% C.I. 0.97-1.04). KAS250's association with likelihood of DDKT varied across centers from HR=0.18 (DDKT less likely after KAS250) to HR=17.12 (DDKT more likely) and varied even among neighboring centers. KAS250 was associated with decreased DDKT at 25.6% and increased DDKT at 18.2% of centers. Centers with previously long median waiting times (57+ months) experienced increased likelihood of DDKT after KAS250 (HR=1.20, 95% C.I. 1.15-1.26), whereas centers with previously short median waiting times (6-24mo.; HR=0.88, 0.84-0.92) experienced decreased likelihood of DDKT. Retrospective study of allocation policy changes, confounded by multiple changes over the study timeframe. Association between KAS250 and DDKT varied across centers. For one-in-four centers, DDKT was less likely after KAS250 relative to pre-KAS250 trends. Candidates at centers with previously long waiting times experienced increased likelihood of DDKT after KAS250. Thus, broader distribution of kidneys may be associated with improved equity in access to DDKT, but additional strategies may be needed to minimize disparities between centers.