The Burden of Travel-Time and Distance Traveled for Hemodialysis Patients in Australian Major City Areas.
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ABSTRACT:
SUBMITTER: McDonald SP
PROVIDER: S-EPMC10166733 | biostudies-literature | 2023 May
REPOSITORIES: biostudies-literature
Publications
The Burden of Travel-Time and Distance Traveled for Hemodialysis Patients in Australian Major City Areas.
McDonald Stephen P SP Ullah Shahid S Dansie Kathryn K Duncanson Emily E Gulyani Aarti A Davies Christopher E CE Jesudason Shilpanjali S
Kidney international reports 20230221 5
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Project description:IntroductionAn alarmingly high proportion of the Australian adult population does not meet national physical activity guidelines (57%). This is concerning because physical inactivity is a risk factor for several chronic diseases. In recent years, an increasing emphasis has been placed on the potential for transport and urban planning to contribute to increased physical activity via greater uptake of active transport (walking, cycling and public transport). In this study, we aimed to estimate the potential health gains and savings in health care costs of an Australian city achieving its stated travel targets for the use of active transport.MethodsAdditional active transport time was estimated for the hypothetical scenario of Brisbane (1.1 million population 2013) in Australia achieving specified travel targets. A multi-state life table model was used to estimate the number of health-adjusted life years, life-years, changes in the burden of diseases and injuries, and the health care costs associated with changes in physical activity, fine particle (<2.5 μm; PM2.5) exposure, and road trauma attributable to a shift from motorised travel to active transport. Sensitivity analyses were conducted to test alternative modelling assumptions.ResultsOver the life course of the Brisbane adult population in 2013 (860,000 persons), 33,000 health-adjusted life years could be gained if the travel targets were achieved by 2026. This was mainly due to lower risks of physical inactivity-related diseases, with life course reductions in prevalence and mortality risk in the range of 1.5%-6.0%. Prevalence and mortality of respiratory diseases increased slightly (≥0.27%) due to increased exposure of larger numbers of cyclists and pedestrians to fine particles. The burden of road trauma increased by 30% for mortality and 7% for years lived with disability. We calculated substantial net savings ($AU183 million, 2013 values) in health care costs.ConclusionIn cities, such as Brisbane, where over 80% of trips are made by private cars, shifts towards walking, cycling and public transport would cause substantial net health benefits and savings in health care costs. However, for such shifts to occur, investments are needed to ensure safe and convenient travel.
| S-EPMC5636090 | biostudies-literature
Project description:Car parking is of central importance to congestion on roads and the urban planning process of optimizing road networks, pricing parking lots and planning land use. The efficient placement, sizing and grid connection of charging stations for electric cars makes it even more important to know the spatio-temporal distribution of car parking densities on the scale of entire cities. Here, we generate car parking density maps using travel time measurements only. We formulate a Hidden Markov Model that contains non-linear functional relationships between the changing average travel times among the zones of a city and both the traffic activity and flow direction probabilities of cars. We then sample the traffic flow for 1,000 cars per city zone for each city from these probability distributions and normalize the resulting spatial parking distribution of cars in each time step. Our results cover the years 2015-2018 for 34 cities worldwide. We validate the model for Melbourne and reach about 90% accuracy for parking densities and over 93% for circadian rhythms of traffic activity.
| S-EPMC6704179 | biostudies-literature
Project description: Not available
| S-EPMC10660245 | biostudies-literature
Project description:The visual responses of neurons in the primary visual cortex (V1) are influenced by the animal's position in the environment [1-5]. V1 responses encode positions that co-fluctuate with those encoded by place cells in hippocampal area CA1 [2, 5]. This correlation might reflect a common influence of non-visual spatial signals on both areas. Place cells in CA1, indeed, do not rely only on vision; their place preference depends on the physical distance traveled [6-11] and on the phase of the 6-9 Hz theta oscillation [12, 13]. Are V1 responses similarly influenced by these non-visual factors? We recorded V1 and CA1 neurons simultaneously while mice performed a spatial task in a virtual corridor by running on a wheel and licking at a reward location. By changing the gain that couples the wheel movement to the virtual environment, we found that ∼20% of V1 neurons were influenced by the physical distance traveled, as were ∼40% of CA1 place cells. Moreover, the firing rate of ∼24% of V1 neurons was modulated by the phase of theta oscillations recorded in CA1 and the response profiles of ∼7% of V1 neurons shifted spatially across the theta cycle, analogous to the phase precession observed in ∼37% of CA1 place cells. The influence of theta oscillations on V1 responses was more prominent in putative layer 6. These results reveal that, in a familiar environment, sensory processing in V1 is modulated by the key non-visual signals that influence spatial coding in the hippocampus.
| S-EPMC7544510 | biostudies-literature
Project description:BackgroundSpeed and distance traveled provide quantifiable links between behavior and energetics, and are among the metrics most routinely estimated from animal tracking data. Researchers typically sum over the straight-line displacements (SLDs) between sampled locations to quantify distance traveled, while speed is estimated by dividing these displacements by time. Problematically, this approach is highly sensitive to the measurement scale, with biases subject to the sampling frequency, the tortuosity of the animal's movement, and the amount of measurement error. Compounding the issue of scale-sensitivity, SLD estimates do not come equipped with confidence intervals to quantify their uncertainty.MethodsTo overcome the limitations of SLD estimation, we outline a continuous-time speed and distance (CTSD) estimation method. An inherent property of working in continuous-time is the ability to separate the underlying continuous-time movement process from the discrete-time sampling process, making these models less sensitive to the sampling schedule when estimating parameters. The first step of CTSD is to estimate the device's error parameters to calibrate the measurement error. Once the errors have been calibrated, model selection techniques are employed to identify the best fit continuous-time movement model for the data. A simulation-based approach is then employed to sample from the distribution of trajectories conditional on the data, from which the mean speed estimate and its confidence intervals can be extracted.ResultsUsing simulated data, we demonstrate how CTSD provides accurate, scale-insensitive estimates with reliable confidence intervals. When applied to empirical GPS data, we found that SLD estimates varied substantially with sampling frequency, whereas CTSD provided relatively consistent estimates, with often dramatic improvements over SLD.ConclusionsThe methods described in this study allow for the computationally efficient, scale-insensitive estimation of speed and distance traveled, without biases due to the sampling frequency, the tortuosity of the animal's movement, or the amount of measurement error. In addition to being robust to the sampling schedule, the point estimates come equipped with confidence intervals, permitting formal statistical inference. All the methods developed in this study are now freely available in the ctmmR package or the ctmmweb point-and-click web based graphical user interface.
| S-EPMC6858693 | biostudies-literature
Project description:Distance traveled and home range size describe how animals move in space. The seasonal variations of these parameters are important to comprehensively understand animal ecology and its connection with reproductive behavior and energy costs. Researchers usually estimate the distance traveled as the sum of the straight-line displacements between sampled positions, but this approach is sensitive to the sampling frequency and does not account for the tortuosity of the animal's movements. By means of the continuous-time movement modeling which takes into account autocorrelation and tortuosity of movement data, we estimated the distance traveled and monthly home range size of 28 wild boar Sus scrofa and modeled their inter-sexual seasonal variability. Males traveled longer distances and used larger home ranges than females, particularly during the rut in autumn-winter, consistently with the different biological cycles of males and females. Males enlarged their home ranges during the rut but traveled constant average distances along the year, whereas females traveled shorter distances in correspondence with the peak of food resources and birth periods but exhibited constant home range size across seasons. The differences between the seasonal variation patterns of distance traveled and home range size, observed in both sexes, revealed the complex relationship between these two aspects of spatial behavior and the great opportunity of including both distance traveled and home range size in behavioral ecology investigations. We provided a detailed analysis of wild boar spatial behavior and its relationships with the reproductive cycles of males and females, promoting a deeper comprehension of their behavioral ecology.
| S-EPMC11255988 | biostudies-literature
Project description:Background The physical job demands of hospital nurses are known to be very high. Although many studies have measured the physical activities of nurses subjectively using questionnaires, it remains necessary to quantify and measure nurses’ physical activity at work using objective indicators. This study was conducted to address this gap in the literature by analyzing nurses’ physical activity using both objective measurements and subjective perceptions. The number of steps, distance traveled, and actual work hours were measured during work, and the influence of related factors was analyzed. Methods Using a cross-sectional design, survey and activity tracking data were collected from nurses who worked in three shifts in two tertiary hospitals located in the capital region of South Korea. The participants comprised 117 nurses working in four different units (medical ward, surgical ward, intensive care unit, emergency room), and data from 351 shifts were used in the final analysis. Between-group differences in the main variables were analyzed using the t-test, the Mann–Whitney test, analysis of variance, or the Kruskal–Wallis test, as appropriate. The relationships were examined through multiple linear regression analysis. Results The average number of steps and distance traveled were greatest for nurses working in the emergency room, followed by the intensive care unit, surgical ward, and medical ward (in descending order). Younger nurses and those with shorter unit experience tended to have the greatest number of steps and distance traveled. Conclusion Using activity trackers, this study derived physical activity measures such as number of steps and distance traveled, enabling an objective examination of physical activity during shifts. Nurses’ level of physical activity differed depending on the type of nursing unit, nurses’ age, and unit experience. These results suggest the need for support programs that are specific to the job demands of specific nursing units. Supplementary Information The online version contains supplementary material available at 10.1186/s12960-022-00768-3.
| S-EPMC9548108 | biostudies-literature
Project description:Rapid urbanization and increasing demand for transportation burdens urban road infrastructures. The interplay of number of vehicles and available road capacity on their routes determines the level of congestion. Although approaches to modify demand and capacity exist, the possible limits of congestion alleviation by only modifying route choices have not been systematically studied. Here we couple the road networks of five diverse cities with the travel demand profiles in the morning peak hour obtained from billions of mobile phone traces to comprehensively analyse urban traffic. We present that a dimensionless ratio of the road supply to the travel demand explains the percentage of time lost in congestion. Finally, we examine congestion relief under a centralized routing scheme with varying levels of awareness of social good and quantify the benefits to show that moderate levels are enough to achieve significant collective travel time savings.
| S-EPMC4796288 | biostudies-literature
Project description:Infectious diseases attack humans from time to time and threaten the lives and survival of people all around the world. An important strategy to prevent the spatial spread of infectious diseases is to restrict population travel. With the reduction of the epidemic situation, when and where travel restrictions can be lifted, and how to organize orderly movement patterns become critical and fall within the scope of this study. We define a novel diffusion distance derived from the estimated mobility network, based on which we provide a general model to describe the spatiotemporal spread of infectious diseases with a random diffusion process and a deterministic drift process of the population. We consequently develop a multi-source data fusion method to determine the population flow in epidemic areas. In this method, we first select available subregions in epidemic areas, and then provide solutions to initiate new travel flux among these subregions. To verify our model and method, we analyze the multi-source data from mainland China and obtain a new travel flux triggering scheme in the selected 29 cities with the most active population movements in mainland China. The testable predictions in these selected cities show that reopening the borders in accordance with our proposed travel flux will not cause a second outbreak of COVID-19 in these cities. The finding provides a methodology of re-triggering travel flux during the weakening spread stage of the epidemic.
| S-EPMC8550429 | biostudies-literature
Project description:ImportanceGenotype-matched trials, which are becoming increasingly important in the precision oncology era, require referrals from institutions providing comprehensive genomic profiling (CGP) testing to those conducting these trials, and the travel burden for trial participation is significant. However, it remains unknown whether travel time or distance are associated with genotype-matched trial participation.ObjectiveTo assess whether travel time or distance are associated with disparities in genotype-matched trial participation following CGP testing.Design, setting, and participantsThis retrospective cohort study from June 2020 to June 2022 included patients with advanced or metastatic solid tumors referred to the National Cancer Center Hospital for participation in genotype-matched trials following CGP testing and discussion by molecular tumor boards. Data were analyzed from June to October 2022.ExposuresTravel time and distance.Main outcomes and measuresThe primary and secondary outcomes were enrollment in genotype-matched trials and all-cancer clinical trials, respectively.ResultsOf 1127 patients (mean [range] age, 62 [16-85] years; 584 women [52%]; all residents of Japan), 127 (11%) and 241 (21%) were enrolled in genotype-matched trials and all-cancer clinical trials, respectively. The overall median (IQR) travel distance and time were 38 (21-107) km and 55 (35-110) minutes, respectively. On multivariable regression with 23 covariates, travel distance (≥100 km vs <100 km) was not associated with the likelihood of genotype-matched trial participation (26 of 310 patients [8%] vs 101 of 807 patients [12%]; odds ratio [OR], 0.64; 95% CI, 0.40-1.02), whereas in patients with travel time of 120 minutes or more, the likelihood of genotype-matched trial participation was significantly lower than those with travel time less than 120 minutes (19 of 276 patients [7%] vs 108 of 851 patients [13%]; OR, 0.51; 95% CI, 0.29-0.84). The likelihood of genotype-matched trial participation decreased as travel time increased from less than 40 (38 of 283 patients [13%]) to 40 to 120 (70 of 568 patients [12%]) and 120 or more (19 of 276 patients [7%]) minutes (OR, 0.74; 95% CI, 0.48-1.17; OR, 0.41; 95% CI, 0.22-0.74, respectively). Neither travel time nor distance were associated with the likelihood of all-cancer clinical trial participation.Conclusions and relevanceIn this cohort study of patients undergoing CGP testing, an increased travel time was associated with a decreased likelihood of genotype-matched trial participation. This warrants further research on interventions, such as decentralization of clinical trials to mitigate travel burden.
| S-EPMC10504617 | biostudies-literature