Evaluating the Connection Between Rural Travel Time and Health: A Cross-Sectional Analysis of Older Adults Living in the Northeast United States.

INTRODUCTION: To characterize the impact of rural patients' travel time to obtain healthcare on their reported utilization of preventive healthcare services and personal health outcomes. METHODS: Online survey data from rural adults ages 50+ years living in the Northeastern United States were collected from February to August 2021. Study measures included self-reported travel time to obtain healthcare, use of preventive healthcare, and health outcomes. The associations between travel time with use of preventive care and health outcomes were assessed using linear, Poisson, and logistic regression analyses controlling for demographic variables. RESULTS: Our study population included 1052 rural adults, with a mean travel time of 18.5 min (range: 0-60). Travel time was greater for racial/ethnic minority participants and for higher-income participants (both P < .05), but it was not associated with use of preventive healthcare. Greater travel time was associated with poorer mental health and more comorbidities, including cancer and diabetes (all P < .05). CONCLUSIONS: Travel time varied by patient demographic factors, and it was associated with mental health and comorbidities. There was no association between travel time and preventive care use, suggesting that other barriers likely contribute to suboptimal use of these services within rural communities. Further research is needed to elucidate the causal pathways linking travel time to mental health and comorbidities within rural communities, as increased travel may exacerbate intrarural health disparities.

Enhancing hydrological insight: isotopic methods revealing groundwater-surface water interactions in the Lower Quang Tri River Group, Vietnam.

The Lower Quang Tri River Group, situated in central Vietnam, faces a myriad of challenges, notably the decline in groundwater levels and the salinisation of both groundwater and surface water, significantly impacting water availability for domestic, agricultural, and industrial purposes. To address these pressing concerns, this study adopts a comprehensive methodology integrating hydrogeological measurements, isotopic techniques, and chemical analyses of various water sources, including local precipitation, surface water bodies, reservoirs, and groundwater samples. Utilising the deuterium and oxygen-18 signatures (δ2H and δ18O) in water molecules as environmental tracers for the assessment of base flow and water sources enables a nuanced understanding of the intricate interaction between surface water and groundwater. Research findings elucidate that during the dry season, groundwater recharge primarily stems from water in the reservoirs over approximately seven months. Base flow contributes between 80 and 85 % of streamflow during the rainy season, escalating to 100 % during the dry season. The mean travelling time of the base flow is estimated at 120 ± 10 days using the sine curve model developed by Rodgers et al. The insights gleaned from this study are poised to play a pivotal role in guiding the local water resources managers in licensing for the exploitation of a right quantities of groundwater as sustainable management strategies in the region.

Geographic Disparities in Access to Assisted Reproductive Technology Centers in China: Spatial-Statistical Study.

A study on infertility in China found that while 543 health care institutions are approved for assisted reproductive technology (ART), only 10.1% offer all ART services, with a significant skew toward the eastern regions, highlighting the accessibility challenges faced by rural and remote populations; this study recommends government measures including travel subsidies and education initiatives to improve ART access for economically disadvantaged individuals.

Chimeric Antigen Receptor T-Cell Access in Patients with Relapsed/Refractory Large B-Cell Lymphoma: Association of Access with Social Determinants of Health and Travel Time to Treatment Centers.

Large B-cell lymphoma (LBCL) is the most common type of non-Hodgkin lymphoma. Chimeric antigen receptor T-cell (CAR T) therapy represents a novel treatment with curative potential for relapsed or refractory (R/R) LBCL, but there are access barriers to this innovative therapy that are not well-studied. Study objectives were: (1) Assess the impact of geographic factors and social determinants of health (SDOH) on access to treatment with CAR T in a sample of patients with R/R LBCL and ≥2 prior lines of therapy (LOT). (2) Compare and contrast patient characteristics, SDOH, and travel time between patients with R/R LBCL who received CAR T and those who did not. An observational, nested case-control study of patients with R/R LBCL, ≥2 prior LOT, not in a clinical trial, identified using 100% Medicare Fee-For-Service and national multi-payer claims databases. Patients were linked to near-neighborhood SDOH using 9-digit ZIP-code address. Driving distance and time between residence and nearest CAR T treatment center (TC) was calculated. Patients were stratified based on treatments received upon third LOT initiation (Index Date) or later: (1) received CAR T and (2) did not receive CAR T. Multivariable logistic regression was used to evaluate factors associated with CAR T. 5011 patients met inclusion criteria, with 628 (12.5%) in the CAR T group. Regression models found the likelihood of receiving CAR T decreased with patient age (odds ratio [OR] = .96, P < .001), and males were 29% more likely to receive CAR T (OR = 1.29, P = .02). Likelihood of CAR T increased with Charlson Comorbidity Index (CCI; OR = 1.07, P < .001) indicating patients with more comorbidities were more likely to receive CAR T. Black patients were less than half as likely to receive CAR T than White patients (OR = .44, P = .01). Asian patients did not significantly differ from White patients (OR = 1.43, P = .24), and there was a trend for Hispanic patients to have a slightly lower likelihood of CAR T (OR = .50, P = .07). Higher household income was associated with receipt of CAR T, with the lowest income group more than 50% less likely to receive CAR T than the highest (OR = .44, P = .002), and the second lowest income group more than 30% less likely (OR = .68, P = .02). Finally, likelihood of CAR T therapy was reduced when the driving time to the nearest TC was 121 to 240 minutes (reference group: ≤30 minutes; OR = .64, P = .04). Travel times between 31 and 121 or greater than 240 minutes were not significantly different from ≤30 minutes. Payer type was collinear with age and could not be included in the regression analysis, but patients with commercial insurance were 1.5 to 3 times more likely to receive CAR T than other payers on an unadjusted basis. We identified significant disparities in access to CAR T related to demographics and SDOH. Patients who were older, female, low income, or Black were less likely to receive CAR T. The positive association of CCI with CAR T requires further research. Given the promising outcomes of CAR T, there is urgent need to address identified disparities and increase efforts to overcome access barriers.

Early thrombus detection in the extracorporeal membrane oxygenation circuit by noninvasive real-time ultrasonic sensors.

Thrombus formation in extracorporeal membrane oxygenation (ECMO) remains a major concern as it can lead to fatal outcomes. To the best of our knowledge, there is no standard non-invasive method for quantitatively measuring thrombi. This study's purpose was to verify thrombus detection in an ECMO circuit using novel, non-invasive ultrasonic sensors in real-time, utilizing the fact that the ultrasonic velocity in a thrombus is known to be higher than that in the blood. Ultrasonic sensors with a customized chamber, an ultrasonic pulse-receiver, and a digital storage oscilloscope (DSO) were used to set up the measuring unit. The customized chamber was connected to an ECMO circuit primed with porcine blood. Thrombi formed from static porcine blood were placed in the circuit and ultrasonic signals were extracted from the oscilloscope at various ECMO flow rates of 1-4 L/min. The ultrasonic signal changes were successfully detected at each flow rate on the DSO. The ultrasonic pulse signal shifted leftward when a thrombus passed between the two ultrasonic sensors and was easily detected on the DSO screen. This novel real-time non-invasive thrombus detection method may enable the early detection of floating thrombi in the ECMO system and early management of ECMO thrombi.

Examining inequalities in spatial access to national health insurance fund contracted facilities in Kenya.

BACKGROUND: Kenya aims to achieve universal health coverage (UHC) by 2030 and has selected the National Health Insurance Fund (NHIF) as the 'vehicle' to drive the UHC agenda. While there is some progress in moving the country towards UHC, the availability and accessibility to NHIF-contracted facilities may be a barrier to equitable access to care. We estimated the spatial access to NHIF-contracted facilities in Kenya to provide information to advance the UHC agenda in Kenya. METHODS: We merged NHIF-contracted facility data to the geocoded inventory of health facilities in Kenya to assign facility geospatial locations. We combined this database with covariates data including road network, elevation, land use, and travel barriers. We estimated the proportion of the population living within 60- and 120-minute travel time to an NHIF-contracted facility at a 1-x1-kilometer spatial resolution nationally and at county levels using the WHO AccessMod tool. RESULTS: We included a total of 3,858 NHIF-contracted facilities. Nationally, 81.4% and 89.6% of the population lived within 60- and 120-minute travel time to an NHIF-contracted facility respectively. At the county level, the proportion of the population living within 1-hour of travel time to an NHIF-contracted facility ranged from as low as 28.1% in Wajir county to 100% in Nyamira and Kisii counties. Overall, only four counties (Kiambu, Kisii, Nairobi and Nyamira) had met the target of having 100% of their population living within 1-hour (60 min) travel time to an NHIF-contracted facility. On average, it takes 209, 210 and 216 min to travel to an NHIF-contracted facility, outpatient and inpatient facilities respectively. At the county level, travel time to an NHIF-contracted facility ranged from 10 min in Vihiga County to 333 min in Garissa. CONCLUSION: Our study offers evidence of the spatial access estimates to NHIF-contracted facilities in Kenya that can inform contracting decisions by the social health insurer, especially focussing on marginalised counties where more facilities need to be contracted. Besides, this evidence will be crucial as the country gears towards accelerating progress towards achieving UHC using social health insurance as the strategy to drive the UHC agenda in Kenya.

A Concrete Core Void Imaging Approach and Parameter Analysis of Concrete-Filled Steel Tube Members Using Travel Time Tomography: Multi-Physics Simulations and Experimental Studies.

Concrete-filled steel tube (CFST) members have been widely used in civil engineering due to their advanced mechanical properties. However, internal defects such as the concrete core voids and interface debonding in CFST structures are likely to weaken their load-carrying capacity and stiffness, which affects the safety and serviceability. Visualizing the inner defects of the concrete cores in CFST members is a critical requirement and a challenging task due to the obvious difference in the material mechanical parameters of the concrete core and steel tube in CFST members. In this study, a curved ray theory-based travel time tomography (TTT) with a least square iterative linear inversion algorithm is first introduced to quantitatively identify and visualize the sizes and positions of the concrete core voids in CFST members. Secondly, a numerical investigation of the influence of different parameters on the inversion algorithm for the defect imaging of CFST members, including the effects of the model weighting matrix, weighting factor and grid size on the void's imaging quality and accuracy, is carried out. Finally, an experimental study on six CFST specimens with mimicked concrete core void defects is performed in a laboratory and the mimicked defects are visualized. The results demonstrate that TTT can identify the sizes and positions of the concrete core void defects in CFST members efficiently with the use of optimal parameters.

Factors intrinsic to handling and transport in pre-slaughter behavioural changes in beef cattle.

The aim of this study was to evaluate handling and transport variables as potential causes of disturbed behaviour in response to seeing a person on an overhead observation platform during pre-slaughter in batches of females and castrated males composed of pure or crossed Bos Taurus animals (Aberdeen Angus, Red Angus, Hereford and Charolais) with a maximum of 37.5% Bos indicus, and maturity at slaughter varying from zero to eight teeth, coming from pasture and confined systems. For the batches of castrated males, the independent variables included the distance covered on the trip, and the handling and facilities on the farms. For the female batches, the variables were travel time and waiting time prior to unloading. For both sexes, the presence of horns in the batches and the load density were included in the regression equations. Disturbed behaviour, the result of factors related to animal handling and transportation, is detrimental to satisfactory results in production systems. It is up to the managers in the production chain to seek alternatives in order to minimise inappropriate behaviour, which is one determinant of loss. Handling and transport are determining factors in the behaviour of beef cattle during the pre-slaughter period.

Mapping roadless areas in regions with contrasting human footprint.

In an increasingly human- and road-dominated world, the preservation of functional ecosystems has become highly relevant. While the negative ecological impacts of roads on ecosystems are numerous and well documented, roadless areas have been proposed as proxy for functional ecosystems. However, their potential remains underexplored, partly due to the incomplete mapping of roads. We assessed the accuracy of roadless areas identification using freely available road-data in two regions with contrasting levels of anthropogenic influence: boreal Canada and temperate Central Europe (Poland, Slovakia, Czechia, and Hungary). Within randomly selected circular plots (per region and country), we visually examined the completeness of road mapping using OpenStreetMap 2020 and assessed whether human influences affect mapping quality using four variables. In boreal Canada, roads were completely mapped in 3% of the plots, compared to 40% in Central Europe. Lower Human Footprint Index and road density values were related to greater incompleteness in road mapping. Roadless areas, defined as areas at least 1 km away from any road, covered 85% of the surface in boreal Canada (mean size ± s.d. = 272 ± 12,197 km2), compared to only 0.4% in temperate Central Europe (mean size ± s.d. = 0.6 ± 3.1 km2). By visually interpreting and manually adding unmapped roads in 30 randomly selected roadless areas from each study country, we observed a similar reduction in roadless surface in both Canada and Central Europe (27% vs 28%) when all roads were included. This study highlights the urgent need for improved road mapping techniques to support research on roadless areas as conservation targets and surrogates of functional ecosystems.

Geographical access to hemodialysis: an analysis of patient choices / Accès géographique à l'hémodialyse : une analyse sur les choix des patients

Introduction: Patients do not always go to the facility closest to their home. Description: A study was carried out in Provence-Alpes Côtes d'Azur (PACA) on patients' preferences to mobilize the hemodialysis offer. Methods: The data were extracted from the REIN Registry. Potential access was compared with actual access. A survey was carried out among a sample of patients travelling an additional distance of more than 25 km. Results: About a quarter of the patients did not travel to the nearest facility. Of these, 16.3% travelled an additional distance of over 25 km. Patients' choices were determined by the relationship of trust with the team that first set up dialysis, followed by their desire to be followed in a multi-purpose facility. Discussion: While distance remained the decisive factor, human factors were cited in the majority of cases to explain the bypass. Conclusion: The links between the first team and the next one should be strengthened.

Introduction: Les patients ne se rendent pas toujours dans l'établissement le plus proche de leur domicile. Description: Une étude a été réalisée en Provence-Alpes Côtes d'Azur (PACA) sur les préférences des patients à mobiliser l'offre d'hémodialyse. Méthodes: Les données ont été extraites du Registre REIN. L'accès potentiel a été comparé à l'accès réalisé. Une enquête a été effectuée auprès d'un échantillon de patients parcourant une distance supplémentaire supérieure à 25 km. Résultats: Environ un quart des patients ne se rendait pas dans la structure la plus proche. Parmi eux, 16,3 % parcouraient un trajet supplémentaire supérieur à 25 km. Les choix des patients étaient déterminés par la relation de confiance avec l'équipe de la première mise en place de dialyse, puis par le souhait d'être suivis dans une structure polyvalente. Discussion: Si la distance restait le facteur décisif, les facteurs humains étaient majoritairement cités. Conclusion: Il faudrait renforcer les liens entre la première équipe et celle qui prend la suite.

Analysis of railway accessibility in Fujian Province and the influence of economic development on its spatial differentiation.

Understanding railway accessibility supports railway regulation and development, but few studies consider different perspectives. We study the spatial distribution of accessibility indicators at the county (city) scale in Fujian Province by spatiotemporal syntax and weighted average travel time using railway timetable data. Export trade, rich commercial activities, and high-speed rail had a significant positive effect on objective accessibility. Fuzhou, Sanming, and Longyan were main transfer centers. The most accessible nodes based on weighted average travel time formed a "U"-shaped corridor along the coast. The county-wide average accessibility was 1.72 h. According to spatiotemporal syntax, local general public budget expenditure (0.758993) and export volume of goods-total retail sales of consumer goods (0.956257) had the most interactive impact, while according to weighted average accessibility, import volume of goods (0.618447) and per capita gross regional product-import volume of goods (0.878573) did. These results provide reference for transportation planning and regional development in Fujian Province.

Enhancing Path Planning Capabilities of Automated Guided Vehicles in Dynamic Environments: Multi-Objective PSO and Dynamic-Window Approach.

Automated guided vehicles (AGVs) are vital for optimizing the transport of material in modern industry. AGVs have been widely used in production, logistics, transportation, and commerce, enhancing productivity, lowering labor costs, improving energy efficiency, and ensuring safety. However, path planning for AGVs in complex and dynamic environments remains challenging due to the computation of obstacle avoidance and efficient transport. This study proposes a novel approach that combines multi-objective particle swarm optimization (MOPSO) and the dynamic-window approach (DWA) to enhance AGV path planning. Optimal AGV trajectories considering energy consumption, travel time, and collision avoidance were used to model the multi-objective functions for dealing with the outcome-feasible optimal solution. Empirical findings and results demonstrate the approach's effectiveness and efficiency, highlighting its potential for improving AGV navigation in real-world scenarios.

Prolonged travel time to transplantation center is associated with poor outcomes following heart transplantation.

BACKGROUND: This study aims to examine the impact of home-to-transplantation center travel time as a potential barrier to healthcare accessibility. METHODS: Observational study examined adult heart transplant recipients who received a graft between 2012 and 2022 in the United States. Travel time was calculated using the Google Distance Matrix API between the recipient's residence and transplantation center. A multivariable parametric survival model was fitted to minimize confounding bias. RESULTS: Among the 25,923 recipients that met the selection criteria, the median travel time was 51 â€‹min and 95 â€‹% of recipients lived within a 5-h radius of their center. White recipients experienced longer median travel times (62 â€‹min, p â€‹< â€‹0.001) compared to Black (36 â€‹min) or Hispanic (40 â€‹min) recipients. A travel time of 1-2 â€‹h (survival time ratio [STR] 0.867, p â€‹= â€‹0.035) or >2 â€‹h (STR 0.873, p â€‹= â€‹0.026) away from the transplantation center was independently associated with lower long-term survival rates. CONCLUSION: Extended travel times to transplantation centers may negatively impact long-term survival outcomes for heart transplant recipients, suggesting the need to address this potential barrier to healthcare accessibility.

Estimating the impact of vadose zone heterogeneity on agricultural managed aquifer recharge: A combined experimental and modeling study.

Agricultural managed aquifer recharge (Ag-MAR) is a promising approach to replenish groundwater resources using flood water and cropland as spreading grounds. However, site selection, particularly the layering of sediment deposits in the subsurface, can greatly influence Ag-MAR efficacy as it controls water flow and solute transport in the vadose zone. In this study, we use the HYDRUS-1D software to simulate water flow and solute transport from the land surface to the groundwater table in three vadose zone profiles (LS, MS, HS) characterized by differing fractions of sand (44 %, 47 %, and 64 %). For each profile, the single- and dual-porosity models (i.e., considering or not nonequilibrium water flow and solute transport) were calibrated using observed surface ponding, soil water content, and KBr breakthrough data. Water flow and bromide transport in the profile with the lowest sand fraction (LS) were best captured using the model that considered both preferential flow and nonequilibrium bromide transport. Water flow and bromide transport in the profile with the highest sand fraction (HS) was best simulated with the model that considered preferential flow and equilibrium bromide transport. Uniform water flow and nonequilibrium bromide transport provided the best fit for the third profile (MS). The degree of preferential flow was highest in the profile with the largest sand fraction (HS), which also showed the largest flow velocities compared to the profiles with lower sand amounts (LS and MS). Preferential flow did not significantly impact the overall water balance (within 3 %), but caused a significant decrease in vadose zone travel times (bromide) by up to 38 %, relative to a single-porosity model fit. Recharge efficiency varied between 88 % and 90 %, while the average travel times from the soil surface to groundwater varied up to 119 % (from 3.6 to 7.9 days) between the three sites. This study demonstrates that similar recharge efficiency can be achieved at sites with differing soil texture profiles, but subsurface heterogeneity can substantially affect contaminant transport processes and their travel times.

Location selection of field hospitals amid COVID-19 considering effectiveness and fairness: A case study of Florida.

The world has experienced an unprecedented global health crisis since 2020, the COVID-19 pandemic, which inflicted massive burdens on countries' healthcare systems. During the peaks of the pandemic, the shortages of intensive care unit (ICU) beds illustrated a critical vulnerability in the fight. Many individuals suffering the effects of COVID-19 had difficulty accessing ICU beds due to insufficient capacity. Unfortunately, it has been observed that many hospitals do not have enough ICU beds, and the ones with ICU capacity might not be accessible to all population strata. To remedy this going forward, field hospitals could be established to provide additional capacity in helping emergency health situations such as pandemics; however, location selection is a crucial decision ultimately for this purpose. As such, we consider finding new field hospital locations to serve the demand within certain travel-time thresholds, while accounting for the presence of vulnerable populations. A multi-objective mathematical model is proposed in this paper that maximizes the minimum accessibility and minimizes the travel time by integrating the Enhanced 2-Step Floating Catchment Area (E2SFCA) method and travel-time-constrained capacitated p-median model. This is performed to decide on the locations of field hospitals, while a sensitivity analysis addresses hospital capacity, demand level, and the number of field hospital locations. Four counties in Florida are selected to implement the proposed approach. Findings can be used to identify the ideal location(s) of capacity expansions concerning the fair distribution of field hospitals in terms of accessibility with a specific focus on vulnerable strata of the population.

The Role of Travel Time on Hospital Utilization in the Islands Area: A Cross-Sectional Study in the Maluku Region, Indonesia, in 2018.

Background: Maluku region is one of the vulnerable areas in Indonesia, and this region has extreme geographical conditions with thousands of islands. The study aims to analyze the role of travel time to a hospital in the Maluku region in Indonesia. Material and Methods: This cross-sectional study analyzed the 2018 Indonesian Basic Health Survey data. The research included 14,625 respondents by stratification and multistage random sampling. The study used hospital utilization as an outcome variable and the travel time to the hospital as an exposure variable. Moreover, the study employed nine control variables: province, residence, age, gender, marital status, education, employment, wealth, and health insurance. The study performed binary logistic regression to interpret the data in the final analysis. Results: The result shows a relationship between travel time and hospital utilization. Someone with a travel time of 30 min or less to the hospital has a 1.792 (95% CI 1.756-1.828) higher probability than those with a travel time of more than 30 min. The results of this analysis find that shorter travel time to the hospital has a better possibility of hospital utilization. In addition, the study also found eight control variables to have a significant relationship with hospital utilization. Conclusion: Shorter travel time to the hospital is more likely to be utilized in the Maluku region.

Vulnerability to snakebite envenoming and access to healthcare in the Terai region of Nepal: a geospatial analysis.

Background: Snakebite envenoming is a neglected tropical disease that mainly affects poor populations in rural areas. In hyperendemic regions, prevention could partially reduce the constant risk, but the population still needs timely access to adequate treatment. In line with WHO's snakebite roadmap, we aim to understand snakebite vulnerability through modelling of risk and access to treatment, and propose plausible solutions to optimise resource allocation. Methods: We combined snakebite-risk distribution rasters with travel-time accessibility analyses for the Terai region of Nepal, considering three vehicle types, two seasons, two snakebite syndromes, and uncertainty intervals. We proposed localised and generalised optimisation scenarios to improve snakebite treatment coverage for the population, focusing on the neurotoxic syndrome. Findings: In the Terai, the neurotoxic syndrome is the main factor leading to high snakebite vulnerability. For the most common scenario of season, syndrome, and transport, an estimated 2.07 (15.3%) million rural people fall into the high vulnerability class. This ranges between 0.3 (2.29%) and 6.8 (50.43%) million people when considering the most optimistic and most pessimistic scenarios, respectively. If all health facilities treating snakebite envenoming could optimally treat both syndromes, treatment coverage of the rural population could increase from 65.93% to 93.74%, representing a difference of >3.8 million people. Interpretation: This study is the first high-resolution analysis of snakebite vulnerability, accounting for uncertainties in both risk and travel speed. The results can help identify populations highly vulnerable to snakebite envenoming, optimise resource allocation, and support WHO's snakebite roadmap efforts. Funding: Swiss National Science Foundation.

Enhancing travel time prediction with deep learning on chronological and retrospective time order information of big traffic data.

With growing environmental concerns and the exploitation of ubiquitous big data, smart transportation is transforming logistics business and operations into a more sustainable approach. To answer questions in intelligent transportation planning, such as which data are feasible, which methods are applicable for intelligent prediction of such data, and what are the available operations for prediction, this paper offers a new deep learning approach called bi-directional isometric-gated recurrent unit (BDIGRU). It is merged to the deep learning framework of neural networks for predictive analysis of travel time and business adoption for route planning. The proposed new method directly learns high-level features from big traffic data and reconstructs them by its own attention mechanism drawn by temporal orders to complete the learning process recursively in an end-to-end manner. After deriving the computational algorithm with stochastic gradient descent, we use the proposed method to perform predictive analysis of stochastic travel time under various traffic conditions (especially for congestions) and then determine the optimal vehicle route with the shortest travel time under future uncertainty. Based on empirical results with big traffic data, we show that the proposed BDIGRU method can (1) significantly improve the predictive accuracy of one-step 30 min ahead travel time compared to several conventional (data-driven, model-driven, hybrid, and heuristics) methods measured with several performance criteria, and (2) efficiently determine the optimal vehicle route in relation to the predictive variability under uncertainty.

The association of urbanicity and travel time with lung cancer screening utilization.

BACKGROUND: To examine 1) the rate of lung cancer screening (LCS) utilization in a large healthcare system in South Carolina; 2) associations of urbanicity and travel time with LCS utilization. METHODS: LCS-eligible patients from 2019 were identified. The outcome was LCS utilization. The exposures were zip-code level urbanicity and travel time from the centroid of zip-code area to the nearest screening site (<10,10-<20, ≥20 min). Covariates included age, sex, race, marital status, insurance, body mass index, chronic obstructive pulmonary disease, Charlson Comorbidity Index (0, 1, 2, ≥3), and zip-code level median income. Chi-square tests and logistic regressions were employed. RESULTS: The analysis included 6930 patients, among whom 1432 (20.66%) received LCS. After adjusting for covariates, living in a non-metropolitan area (adjusted odds ratio: 0.32; 95% confidence interval: 0.26-0.40) and having longer travel time (0.80 [0.65-0.98] and 0.68 [0.54-0.86] for 10-<20 and ≥20 min travel time, respectively, compared to <10 min travel time) were significantly associated with lower odds of LCS utilization. CONCLUSIONS: The LCS utilization rate of a healthcare system was about 20% in 2019. Living in non-metropolitan areas or having longer travel time to LCS site were associated with lower LCS utilization.