Geographic Density Research Articles

Geographic Dialysis Facility Density and Early Dialysis Initiation.

The decision of when to start maintenance hemodialysis may be affected by health system-level support for high-intensity care as manifested by area dialysis facility density. Yet an association between early hemodialysis initiation and higher area density of dialysis facilities has not been shown. To examine whether there is an association between area dialysis facility density and earlier dialysis initiation. Cross-sectional analysis was conducted of publicly reported claims and geographic-based population data collected in the Medical Evidence files of the US Renal Data System (USRDS), a comprehensive registry of all patients initiating hemodialysis in the US, from calendar years 2011 through 2019. Data were linked to the American Community Survey, using residential zip codes, and then to health service area (HSA) primary care and hospitalization benchmarks, using the Dartmouth Atlas crosswalk. Data were analyzed from November 1, 2021, to August 31, 2023. Dialysis facility density at the level of HSA (number of dialysis facilities per 100 000 HSA residents) split into 5 categories. The odds of hemodialysis initiation at an estimated glomerular filtration rate (eGFR) greater than 10 mL/min/1.73 m2 vs less than or equal to 10 mL/min/1.73 m2. Hemodialysis was initiated in a total of 844 466 individuals at 3397 HSAs at a mean (SD) eGFR of 8.9 (3.8) mL/min/1.73 m2. Their mean (SD) age was 63.5 (14.7) years, and 484 346 participants (57.4%) were men. In the HSA category with the highest facility density, individuals were younger (63.3 vs 65.2 years in least-dense HSAs), poorer (mean percent of households living in poverty, 10.4% vs 8.4%), and more commonly had a higher percentage of Black individuals (40.6% vs 11.3%). More individuals in the dialysis-dense HSAs than least-dense HSAs had diabetes (60.1% vs 58.5%) and fewer had access to predialysis nephrology care (60.8% vs 64.1%); the rates of heart failure and immobility varied, but not in a consistent pattern, by HSA dialysis density. The mean (SD) facility density was 4.1 (1.89) centers per 100 000 population in the most dialysis-dense HSAs. Compared with patients in HSAs with a mean of 1.0 per 100 000 population, the odds of hemodialysis initiation at eGFR greater than 10 mL/min/1.73 m2 were 1.07 (95% CI, 1.03-1.11) for patients in the densest HSAs, and compared with HSAs with 0 facilities, the odds of early hemodialysis initiation were 1.06 (95% CI, 1.02-1.10) for patients in the densest HSAs. In this cross-sectional study of USRDS- and HSA-level data, HSA dialysis density was associated with early hemodialysis initiation.

The positive effects of the higher education expansion policy on urban innovation in China

<abstract> <p>Higher education not only enhances people's well-being, but also plays an important role in the in-depth implementation of the innovation-driven development strategy. In this paper, we use Chinese urban data for 1995–2020, utilizing the higher education expansion policy implemented in China in 1999 as an external shock. Using Double/Debiased Machine Learning (DML), we examine the impact of the aforementioned policy on urban innovation and its mechanisms. The results show that: (1) The higher education expansion policy significantly promotes urban innovation; (2) the policy promotes human capital expansion and strengthens government financial support, thereby significantly fostering urban innovation; (3) the impact of the policy varies across cities with different geographic locations, population densities and levels of marketization. Therefore, the findings of this paper provide empirical evidence that higher education expansion policy stimulates urban innovation. It also offers useful insights for China's transition from "Made in China" to "Created in China" during its high-quality development phase.</p> </abstract>

Sociodemographic predictors of successful screening and subsequent randomization in a digital health hypertension intervention.

Clinical trials often enroll nonrepresentative participant samples, limiting generalizability of trial findings. The current analysis explores the influences of remote recruitment and screening protocols on participation in a digital health intervention (DHI) to promote the evidence-based Dietary Approaches to Stop Hypertension (DASH) eating pattern. Nourish was a 12-month randomized controlled trial comparing the effectiveness of a DHI to an attention control arm among US adults with hypertension. Participants were recruited using digital approaches; eligible individuals completed several screening steps. We examined associations between sociodemographics and mobile technology use and completion of each screening step and compared those characteristics between randomized and nonrandomized participants (those consented but were screened out before randomization). A total of 678 adults consented to participate in Nourish; 44% of those consented were randomized (n = 301). Those randomized possessed a higher education level (p < 0.0001); were more likely to use health-related apps (p < 0.0001) and wearables (p < 0.0001); and were older (p = 0.01) than nonrandomized individuals. Randomized adults were more likely to use a desktop/laptop/tablet for Internet access (vs mobile phones) (p = 0.01). No significant association was observed existed between sex, race, ethnicity, income, or geographic density of residence and subsequent randomization. Participants with lower education levels or limited experience in using mobile technologies may require additional support to participate in DHIs. Future research is needed to evaluate remote clinical trial procedures and impacts on generalizability to achieve equitable clinical trial participation.

Geographical Spatial Distribution and Population Density of Wheat Stem Sawfly, Cephus pygmeus, in Wheat Fields in Southeastern, Eastern, and Northeastern Regions of Türkiye

The wheat stem sawfly (Cephus pygmeus) is a major pest of wheat crops in many regions of the world, including Eastern Türkiye. This study aimed to investigate the spatial distribution and population density of wheat stem sawfly in Eastern Türkiye and to evaluate the damage caused by this pest on wheat yield and quality. A total of 120 wheat fields were surveyed in six provinces of Eastern Türkiye during the 2018 growing season. The results showed that the population density of wheat stem sawflies varied significantly among the surveyed fields, with an average infestation rate of 37.4%. The highest infestation rate was recorded in the province of Kilis (62.5%) and Diyarbakır (61.9%), while the lowest was in the province of Ağrı (8.3%). The study also identified some factors that affect the population density of wheat stem sawflies, including host plants (mainly wheat, barley, and rye), altitude, temperature, and geographical structure such as mountains and forests. These findings provide valuable information for developing effective management strategies to control wheat stem sawfly populations and minimize the damage caused by this pest in Eastern Türkiye, especially Southeastern Anatolia Region.

Socioeconomic, Health Services, and Multimorbidity Disparities in Chinese Older Adults

IntroductionAs one of the world's most populous countries, China persistently confronts a significant multimorbidity burden. This study aimed to elucidate the multimorbidity burden experienced by Chinese older adults, explore its interplay with socioeconomic disparity, and investigate potential correlations between these provincial disparities and health services availability. MethodsThe fourth wave of China's national Urban and Rural Elderly Population study, conducted in 2015, was used to construct a multimorbidity index (MHI) and elucidate the geographical differences in the multimorbidity burden. Incorporating macro-level indicators about socioeconomic and health services availability, quantile regression and spearman correlation analyses were employed to investigate the relationship between multimorbidity and socioeconomic disparities, and examine the potential linkages between these provincial disparities and health services availability. Analyses were performed in 2023. ResultsFinal analysis included a total of 213,857 older adults. At the provincial level, significant geographic disparities in multimorbidity burden were identified. After adjusting for individual social determinants of health, an independent association was found between the human development index (HDI) and a higher MHI [coefficient = -0.22; 95% CI: (-0.24, -0.19)]. Furthermore, a significant positive correlation emerged between HDI and both population and geographic densities of health services availability. Notably, geographic density displayed greater inequality (Gini coefficients of 0.45 to 0.48) compared to population density (Gini coefficients of 0.03 to 0.10). ConclusionsThis study demonstrates that multimorbidity burden in China is linked to provincial socioeconomic disparities, and inequality in health services availability may account for this, which would advocate for a need to reduce disparities in health services availability.

Designing electricity distribution networks: The impact of demand coincidence

With the global effort to reduce carbon emissions, clean technologies such as electric vehicles and heat pumps are increasingly introduced into electricity distribution networks. These technologies considerably increase electricity flows and can lead to more coincident electricity demand. In this paper, we analyze how such increases in demand coincidence impact future distribution network investments. For this purpose, we develop a novel model for designing electricity distribution networks, called the distribution network reconfiguration problem with line-specific demand coincidence (DNRP-LSDC). Our analysis is two-fold: (1) We apply our model to a large sample of real-world networks from a Swiss distribution network operator. We find that a high demand coincidence due to, for example, a large-scale uptake of electric vehicles, requires a substantial amount of new network line construction and increases average network cost by 84% in comparison to the status quo. (2) We use a set of synthetic networks to isolate the effect of specific network characteristics. Here, we show that high coincidence has a more detrimental effect on large networks and on networks with low geographic consumer densities, as present in, e.g., rural areas. We also show that expansion measures are robust to variations in the cost parameters. Our results demonstrate the necessity of designing policies and operational protocols that reduce demand coincidence. Moreover, our findings show that operators of distribution networks must consider the demand coincidence of new electricity uses and adapt investment budgets accordingly. Here, our solution algorithms for the DNRP-LSDC problem can support operators of distribution networks in strategic and operational network design tasks.

Disparities in Access to Spasticity Chemodenervation Specialists in the United States: A Retrospective Cross-Sectional Study.

The aim of the study is to explore variations in access to spasticity chemodenervation specialists across several geographical, ethnic, racial, and population density factors. This is a retrospective cross-sectional study on Medicare Provider Utilization and Payment Data. Providers with substantial adult spasticity chemodenervation practices were included. Ratios were assessed across geographical regions as well as hospital referral regions. A multivariate linear regression model for the top 100 hospital referral regions by beneficiary population was created, using backward stepwise selection to eliminate variables with P values > 0.10 from final model. A total of 566 providers with spasticity chemodenervation practices were included. Unadjusted results showed lower access in nonurban versus urban areas in the form of higher patient:provider ratios (83,106 vs. 51,897). Access was also lower in areas with ≥25% Hispanic populations (141,800 vs. 58,600). Multivariate linear regression results showed similar findings with urban hospital referral regions having significantly lower ratios (-45,764 [ P = 0.004] vs. nonurban) and areas with ≥25% Hispanic populations having significantly higher ratios (+96,249 [ P = 0.003] vs. <25% Hispanic areas). Patients in nonurban and highly Hispanic communities face inequities in access to chemodenervation specialists. The Medicare data set analyzed only includes 12% of the US patient population; however, this elderly national cross-sectional cohort represents a saturated share of patients needing access to spasticity chemodenervation therapy. Future studies should venture to confirm whether findings are limited to this specialization, and strategies to improve access for these underserved communities should be explored.

Geographic Distribution of Social Service Resources for Stroke Survivors in Ohio Varies by Rurality.

Both social service resources and stroke prevalence vary by geography, and health care resources are scarcer in rural areas. We assessed whether distributions of resources relevant to stroke survivors were clustered around areas of the highest stroke prevalence in Ohio and whether this is varied by rurality using an ecological study design. Census tract (CT)-level self-reported stroke prevalence estimates (Centers for Disease Control and Prevention PLACES-2019 Behavioral Risk Factor Surveillance System) were linked with sociodemographic and rurality data (2019 American Community Survey) and geographic density of resources in Ohio (2020 findhelp data). Resources were grouped into categories: housing, in-home, financial, transportation, education, and therapy. Negative binomial regression models estimated the mean number of resources within 25 miles and 30 minutes of a CT centroid and quartiles of stroke prevalence for each resource group by rurality status (rural, urban, and suburban). Models were sequentially adjusted for total population and CT demographics. In Ohio, stroke prevalence was 3.9% (0.4%-14.2%). The highest stroke prevalence quartile (versus lowest) was associated with fewer resources within 25 miles overall (resource ratio [RR], 0.57-0.98). The most pronounced disparities were in rural CT; rural CTs with the highest quartile stroke prevalence had fewer housing (RR, 0.49 [95% CI, 0.32-0.75]), in-home (RR, 0.31 [95% CI, 0.20-0.49]), and therapy (RR, 0.23 [95% CI, 0.13-0.43]) resources compared with those with the lowest quartile stroke prevalence (reference: mean, 1.2 housing, 5.1 in-home, and 4.9 therapy resources, respectively). Rural disparities no longer persisted after adjustment for federal poverty limit (rural: housing [RR, 0.69 (95% CI, 0.40-1.20)], in-home [RR, 0.65 (95% CI, 0.34-1.23)], and therapy [RR, 0.66 (95% CI, 0.33-1.32)]). Stroke social service resources are inversely distributed relative to stroke prevalence in Ohio, particularly in rural areas. This inverse link in rural Ohio is likely explained by geographic differences in poverty. Stroke-specific resource-related interventions may be needed and should consider the roles of rurality and poverty.

Improving the quality of service indices of task allocation in mobile crowd sensing with fuzzy-based inverse stackelberg game theory

This paper introduces a comprehensive strategy for heterogeneously allocating tasks, aiming to optimize mobile crowd sensing through the use of fuzzy logic and thus achieving superior coverage quality. We employed a deep learning method to address the diverse range of requests. Recognizing the instability during the learning process, we utilized an approximation function for the Q-values, thereby preventing divergence during the training phase of the model. A prominent challenge is ensuring robust user participation in mobile crowd sensing initiatives. Essentially, a higher number of monitoring nodes within an area correlates with improved coverage quality. We employed fuzzy logic to estimate participation density, taking into account both the duration of users' presence in the study region and the geographical density. Our results are compelling: the proposed method boosts coverage levels by over 17% compared to standard techniques. Additionally, with an accuracy spanning 91.5% to 95.3% for the correct allocation of resources using a dataset from Google, the efficacy of our approach is further underscored.

Spatiotemporal Differentiation and Influencing Factors of Frost Key Date in Harbin Municipality from 1961 to 2022

This study analyzed frost formation data provided by the Harbin Meteorological Bureau and considered geographic factors, temperature, and population density. Various analytical methods, including linear fitting, the Mann–Kendall mutation test, the Pettitt method, and the sliding t-test, were employed to identify the temporal and spatial changes as well as the effects of these factors on frost dates in Harbin. The study shows that the first FSD occurred on 18 August, in both 1966 and 1967, which was the 255th day. The latest FSD was observed on 10 October 2006, which was the 283rd day. The earliest occurrence of an FED was on 24 April 2015, which was the 114th day, and the latest was on 21 April 1974, which was the 141st day. The highest number of frost days occurred in 2012, with 161 days, whereas the shortest year was 1966, with only 123 frost days. Throughout the study period, the FSD increased by 7.8 days at a rate of −1.27d/10a, the FED increased by 10.9 days at a rate of 1.77d/10a, and the FFS increased by 18.9 days at a rate of 3.05d/10a. The propensity rates of the FSD and FFS at each location in Harbin indicate an upward trend, while for the FED, certain locations display an upward trend. In general, the FSD has exhibited a delayed trend, the FED has shown an earlier trend, and the FFS has experienced an extended trend. With one-way linear regression, the FSD exhibited an increasing trend at each site, while the FFS also indicated a similar trend, and the FED showed an overall decreasing trend. Throughout the study period, a change was observed in the FSD in 2000, resulting in an average arrival time of the 265th day, or 22 September, of that year. Subsequently, post mutation, the average arrival time of the FSD in the study area was the 272nd day, or 29 September, of that year. In 2006, the FED also underwent a change, with the average arrival time in the study area being the 128th day, or 4 April, of that year. After the change, the average arrival time of the FED in the study area was the 121st day, i.e., 8 April. In 1 April 2004 of that year saw a change in the FFS. Prior to the change, the FFS in the study area averaged the 137th day, whilst following the change, the FFS in the study area averaged the 150th day. The FSD and FFS within Harbin exhibit a negative correlation with latitude and a positive correlation with temperature. Additionally, the FED displays a positive correlation with latitude and a negative correlation with temperature. As the FSD, FED, and FFS in central Harbin are the earliest, latest, and longest, the Pearson correlation coefficient method and multiple regression cannot adequately reflect the effect of longitude.

Emulation of seismic-phase traveltimes with machine learning

SUMMARY We present a machine learning (ML) method for emulating seismic-phase traveltimes that are computed using a global-scale 3-D earth model and physics-based ray tracing. Accurate traveltime predictions based on 3-D earth models are known to reduce the bias of event location estimates, increase our ability to assign phase labels to seismic detections and associate detections to events. However, practical use of 3-D models is challenged by slow computational speed and the unwieldiness of pre-computed lookup tables that are often large and have prescribed computational grids. In this work, we train a ML emulator using pre-computed traveltimes, resulting in a compact and computationally fast way to approximate traveltimes that are based on a 3-D earth model. Our model is trained using approximately 850 million P-wave traveltimes that are based on the global LLNL-G3D-JPS model, which was developed for more accurate event location. The training-set consists of traveltimes between 10 393 global seismic stations and randomly sampled event locations that provide a prescribed, distance-dependent geographic sample density for each station. Prediction accuracy is dependent on event-station distance and whether the station was included in the training set. For stations included in the training set the mean absolute deviation (MAD) of the difference between traveltimes computed using ray tracing through the 3-D model and the ML emulator for local, regional, and teleseismic distances are 0.090, 0.125 and 0.121 s, respectively. For tested station locations not included in the training set, MAD values for the three distance ranges increase to 0.173, 0.219 and 0.210 s, respectively. Empirical traveltime residuals for a global reference data are indistinguishable when ML emulation or the 3-D model is used to compute traveltimes. This result holds regardless of whether the recording station is used in ML training or not.

Watershed-scale provenance heterogeneity within Eocene nonmarine basin fill: Southern Greater Green River Basin, western USA

Weathering, erosion, and sediment transport in modern landscapes may be investigated via direct observation of attributes such as elevation, relief, bedrock lithology, climate, drainage organization, watershed extent, and others. Studies of ancient landscape evolution lack this synoptic perspective, however, and instead must rely more heavily on downstream records of fluvial deposits. Provenance analysis based on detrital grain ages has greatly enhanced the utility of such records but has often focused broadly on regional to continental scales. This approach may overlook important details of localized watersheds, which could lead to significant misinterpretation of past sediment dispersal patterns. The present study, therefore, explores the impact of geographic and stratigraphic sampling density on detrital zircon provenance, based on a high-density investigation of U-Pb ages (N = 23, n = 4905) obtained from a narrow chronostratigraphic range (∼2 m.y.) within a relatively small (∼25,000 km2) area of an Eocene nonmarine sedimentary basin. Based on multi-dimensional scaling and DZmix modeling, these strata comprise seven distinct, approximately isochronous detrital zircon (DZ) chronofacies, defined as “. . . a group of sedimentary rocks that contains a specified suite of detrital zircon age populations” (Lawton et al., 2010). Four of these DZ chronofacies reflect long-distance transport from extrabasinal source areas. DZ chronofacies CO-1 and CO-2 are interpreted to derive from a primary sediment source in central Colorado (USA), corroborating previously proposed long-distance sediment transport via the Aspen paleoriver. DZ chronofacies ID-1 and ID-2 are interpreted to have been delivered to the basin from central Idaho by the Idaho paleoriver. In contrast, DZ chronofacies UT-1 and UT-2 are interpreted to reflect local drainage from the Uinta Uplift south of the basin, and DZ chronofacies WY-1 is interpreted to have been sourced from the Rawlins, Granite, and Sierra Madre uplifts to the north and east via the Toya Puki paleoriver. Lateral transitions between different DZ chronofacies in some cases occur over distances as little as 5 km, implying that depositional systems carrying sand from disparate watersheds directly competed to fill available basin accommodation. The results of this study reveal a high degree of complexity of Eocene rivers that converged on the Greater Green River Basin, indicating that their deposits contain a rich record of fine-scale landscape evolution across much of the Laramide foreland and Cordilleran orogen. These results illustrate the need for adequate sample density when assessing basin-scale provenance and offer a cautionary consideration for researchers using sandstone (and incorporated authigenic cement) in other nonmarine basins as the basis for paleoaltimetry or detrital thermochronology studies.

Study on geographical distribution and population density of Stenopelmus rufinasus Gyllenhal, in paddy fields and aquatic ecosystems in northern Iran

Study on geographical distribution and population density of Stenopelmus rufinasus Gyllenhal, in paddy fields and aquatic ecosystems in northern Iran

CORR Insights®: What Is the Geographic Distribution and Density of Orthopaedic Advanced Practice Professionals in Rural Counties? A Large-database Study.

CORR Insights®: What Is the Geographic Distribution and Density of Orthopaedic Advanced Practice Professionals in Rural Counties? A Large-database Study.

Exploration of the food environment in different socioeconomic areas in Hong Kong and Singapore: a cross-sectional case study

This study explored the local food environment of Hong Kong and Singapore using a qualitative case study approach to inform future upstream public health nutrition policies. Food outlets that provide food to be eaten in the home were mapped in selected areas of high and low socioeconomic status (SES) of Hong Kong and Singapore. Food outlet density relative to land area was determined. In both countries, lower SES areas surveyed were shown to have higher food outlet density while higher SES areas had fewer but larger food outlets. In Hong Kong, both SES areas reported similar proportions of healthy and unhealthy food outlets.This study highlights the accessibility of food outlet types through their geographical location and density. Future research assessing the differences in eating culture between these two countries should be considered alongside this study’s findings, to investigate strategies influencing the food environment in order to promote healthier eating habits.

Analysis on the equity of dentist resource allocation in China

Objective: To analyze the equity of national stomatologist resource allocation from 2016 to 2020, providing relevantly referenced basis for further stomatologist resource allocation. Methods: Collect data of domestic and international stomatologist resources in 2016, 2018 and 2020, and analyze the relevant data by using the health resources agglomeration degree and population agglomeration degree. Results: At present, at the international level, the number of dentists per 10 000 people ranks 46th in 2010-2019. The quantity of domestic dental resources is on the rise, with a balanced gender distribution and a concentrated age distribution mainly in 25-44 years old. At the specialized technical level, the proportion of junior titles can reach 79.5%-83.0%. The ratio of resource agglomeration of dental practitioners and assistants calculated based on geographical area and population density shows that the ratio of HRAD to PAD in the eastern provinces is greater than 1, while the ratios of most provinces in the central and western regions are less than 1. The eastern regions have excessive allocations, while ones in the central and western regions are insufficient. Conclusions: Unfairness still exists in the allocation of resources for dentists in China. At the national level, it is necessary to continue to cultivate high-quality stomatologists and intensify efforts to support the grass-roots and remote areas. The ability, quality and work competence of on-the-job personnel should be comprehensively improved. Multi-point practice of stomatologists should be standardized and popularized, promoting the rational flow of oral health personnel.

Demographic disparities in lung cancer mortality and trends in the United States between 1999 and 2020: A population-based CDC database analysis.

6603 Background: Lung cancer is the leading cause of cancer-related mortality in the US and is projected to account for 127,070 deaths in 2023. While the lung cancer mortality rate has been decreasing over the last decade, demographic disparities in mortality still exist. We sought to determine the impact of demographic factors on lung cancer mortality and trends in the US. Methods: We queried the Centers for Disease Control database for mortality statistics with an underlying cause of death of lung and bronchus cancer (ICD-10 code C34.0.x) between the years 1999 – 2020. Age-adjusted mortality rates (AAMR) were calculated per 100,000 deaths. We assessed the AAMR by demographic variables, including race (Hispanic, Non-Hispanic White, Non-Hispanic Black, Non-Hispanic Asian or Pacific Islander, Non-Hispanic American Indian/Native American), geographic density (Urban, Suburban, Rural), sex, age (25-44, 45-64, 65+ years), and US Census Region. Temporal trends were evaluated using Joinpoint regression software. Average annual percent change (AAPC) was considered statistically significant if p &lt; 0.05. Results: Between 1999 and 2020, lung cancer led to 3,380,830 deaths. The AAMR decreased by 42% from 55.1 to 31.8 with an associated AAPC of -2.6% (p &lt; 0.001). In 1999, men had an AAMR of 76.8, almost twice as high as women, who had an AAMR of 40.2. These differences became less pronounced over time, and in 2020 men had an AAMR of 38.1, while women had an AAMR of 26.9. Between 1999 and 2020, rural populations experienced the highest AAMR at 52.3, and the slowest rate of decrease at -1.7% annually (p &lt; 0.001), compared with urban populations who experienced the lowest AAMR of 40.6 and fastest AAPC decrease of -3.1% (p &lt; 0.001). Non-Hispanic Black individuals experienced the highest AAMR at 49.8, with an annual decrease of -3.0% (p &lt; 0.001), followed by Non-Hispanic White individuals who had an AAMR of 48.5 with an annual decrease of -2.5% (p &lt; 0.001). Subgroup analysis demonstrated that Non-Hispanic Black men who resided in rural counties experienced the highest mortality at 60.2, with an associated decrease of -2.9% annually (p &lt; 0.001). States in the 90th percentile of mortality included Arkansas and Kentucky; states in the 10th percentile of mortality included Hawaii and Utah. The West experienced the fastest decrease at -3.1% annually (p &lt; 0.001), while the Midwest experienced the slowest decrease at -2.0% annually (p &lt; 0.001). Conclusions: While lung cancer mortality has been decreasing since 1999, not all demographic groups have experienced the same rates of decline, and disparities in outcomes remain prevalent. Vulnerable subgroups may benefit from targeted interventions, such as tailored smoking cessation education and efforts to increase participation in clinical trials. Expansion of screening CT scans and telehealth platforms may also improve access to care for these populations.

Assessment of healthcare accessibility in Guangdong-Hong Kong-Macao Greater Bay Area

Hospitals play a crucial role in promoting public health and well-being, but their distribution and accessibility can significantly affect healthcare outcomes. The Guangdong-Hong Kong-Macau Greater Bay Area (GBA) boasts an abundance of healthcare resources; however, access to these facilities can be challenging due to population clustering and inadequate resource allocation. Unfortunately, quantifying residents' access to healthcare is complicated by the lack of a centralized database and complex transportation systems. To address these limitations, we developed a comprehensive healthcare facility dataset comprising 54,902 sites, utilizing internet maps' precise location services. Furthermore, we developed a novel framework for real-time driving-based path planning that integrates facility geographic coordinates and population density data. Our analysis revealed that 6.7% (4.8 million people) could not reach a healthcare facility within 30 min. Even after accounting for rural clinic facilities, 2.5% (1.8 million people) remained unable to access healthcare, mainly in peripheral cities. Finally, we simulated a scenario in which 12 new hospitals were added to demonstrate the effectiveness of reasonable hospital placement in improving healthcare accessibility. By investigating GBA's experience, we can derive best practices, pinpoint areas for improvement, and inform policy development aimed at enhancing healthcare accessibility for all residents. Our findings can serve as a blueprint for other provinces in China and provide insights into healthcare accessibility and resource allocation strategies for other nations with similar hierarchical healthcare systems.

Five Years Later: Continuing Disparity in the Geographic Density and Distribution of U.S. Dermatologists

Objectives: A discrepancy exists in the geographical distribution of dermatologists across the United States (US). The aim of this study was to reexamine the current geographical density of dermatologists to describe any changes compared to date from 5 and 12 years ago.&#x0D; Methods: Membership data from the 2021 American Academy of Dermatology (AAD) database were retrieved to characterize the distribution of dermatologists in 3-digit zip code areas.&#x0D; Results: Out of 712 populated zip codes with dermatologists, 510 (71.6%) had less than 4 dermatologists per 100,000, as compared to 515 (72.3%) in 2016 (– 0.19% CAGR). The dermatologist density of the 100 most populated areas (M = 4.5 dermatologists per 100,000, SD = 3.3) and 100 least populated areas (M = 1.6 dermatologists per 100,000, SD = 6.2) were significantly different (P &lt; 0.0001).&#x0D; Conclusion: This analysis provides continued trends to compare to previous studies performed in 2016 and 2009. The highest and lowest density areas were similar to results from previous studies. The results indicate an enduring and significant maldistribution of dermatologists in the US.

Understanding the Differences in Educational Resources between Rural and Urban Female in China

China has a long history of agriculture. After the economy developed, coastal cities gradually developed. However, in the vast territory, there still exist some rural areas that rely on mainly agricultural production. The development of each place is not balanced. In this context, the urban-rural gap was created. This was accompanied by disparities in geographic location, industrial patterns, and population density. Those differences bring many imbalances. Education and gender equality have been several issues that have received strong attention from society. The question of whether there is greater gender inequality in the context of unequal educational resources comes out. This essay attempts to comprehend the disparity in educational opportunities between Chinese women living in rural and urban areas. Researchers define the problem related to economic development, some related system and policies, social factors, and so on. They find out that gender inequality in rural is more obvious and serious. It is influenced by economic differences, government support, family, culture, and so on. Also, there is a cycle between the problems and impacts. These economic issues, among others, lead to unequal access to education for women, and as a result, the economic gap is exacerbated. Therefore, more help should be invested in rural education resources. Some corresponding laws also need to be enacted or improved to help.